A Critical Review for Developing Accurate and Dynamic Predictive Models Using Machine Learning Methods in Medicine and Health Care.

PubMed

Alanazi, Hamdan O; Abdullah, Abdul Hanan; Qureshi, Kashif Naseer

2017-04-01

Recently, Artificial Intelligence (AI) has been used widely in medicine and health care sector. In machine learning, the classification or prediction is a major field of AI. Today, the study of existing predictive models based on machine learning methods is extremely active. Doctors need accurate predictions for the outcomes of their patients' diseases. In addition, for accurate predictions, timing is another significant factor that influences treatment decisions. In this paper, existing predictive models in medicine and health care have critically reviewed. Furthermore, the most famous machine learning methods have explained, and the confusion between a statistical approach and machine learning has clarified. A review of related literature reveals that the predictions of existing predictive models differ even when the same dataset is used. Therefore, existing predictive models are essential, and current methods must be improved.

Kinetics, prognostic and predictive values of ESR1 circulating mutations in metastatic breast cancer patients progressing on aromatase inhibitor

PubMed Central

Clatot, Florian; Perdrix, Anne; Augusto, Laetitia; Beaussire, Ludivine; Delacour, Julien; Calbrix, Céline; Sefrioui, David; Viailly, Pierre-Julien; Bubenheim, Michael; Moldovan, Cristian; Alexandru, Cristina; Tennevet, Isabelle; Rigal, Olivier; Guillemet, Cécile; Leheurteur, Marianne; Gouérant, Sophie; Petrau, Camille; Théry, Jean-Christophe; Picquenot, Jean-Michel; Veyret, Corinne; Frébourg, Thierry; Jardin, Fabrice

2016-01-01

Purpose To assess the prognostic and predictive value of circulating ESR1 mutation and its kinetics before and after progression on aromatase inhibitor (AI) treatment. Patients and methods ESR1 circulating D538G and Y537S/N/C mutations were retrospectively analyzed by digital droplet PCR after first-line AI failure in patients treated consecutively from 2010 to 2012 for hormone receptor-positive metastatic breast cancer. Progression-free survival (PFS) and overall survival (OS) were analyzed according to circulating mutational status and subsequent lines of treatment. The kinetics of ESR1 mutation before (3 and 6 months) and after (3 months) AI progression were determined in the available archive plasmas. Results Circulating ESR1 mutations were found at AI progression in 44/144 patients included (30.6%). Median follow-up from AI initiation was 40 months (range 4-94). The median OS was decreased in patients with circulating ESR1 mutation than in patients without mutation (15.5 versus 23.8 months, P=0.0006). The median PFS was also significantly decreased in patients with ESR1 mutation than in patients without mutation (5.9 vs 7 months, P=0.002). After AI failure, there was no difference in outcome for patients receiving chemotherapy (n = 58) versus non-AI endocrine therapy (n=51) in patients with and without ESR1 mutation. ESR1 circulating mutations were detectable in 75% of all cases before AI progression, whereas the kinetics 3 months after progression did not correlate with outcome. Conclusion ESR1 circulating mutations are independent risk factors for poor outcome after AI failure, and are frequently detectable before clinical progression. Interventional studies based on ESR1 circulating status are warranted. PMID:27801670

Kinetics, prognostic and predictive values of ESR1 circulating mutations in metastatic breast cancer patients progressing on aromatase inhibitor.

PubMed

Clatot, Florian; Perdrix, Anne; Augusto, Laetitia; Beaussire, Ludivine; Delacour, Julien; Calbrix, Céline; Sefrioui, David; Viailly, Pierre-Julien; Bubenheim, Michael; Moldovan, Cristian; Alexandru, Cristina; Tennevet, Isabelle; Rigal, Olivier; Guillemet, Cécile; Leheurteur, Marianne; Gouérant, Sophie; Petrau, Camille; Théry, Jean-Christophe; Picquenot, Jean-Michel; Veyret, Corinne; Frébourg, Thierry; Jardin, Fabrice; Sarafan-Vasseur, Nasrin; Di Fiore, Frédéric

2016-11-15

To assess the prognostic and predictive value of circulating ESR1 mutation and its kinetics before and after progression on aromatase inhibitor (AI) treatment. ESR1 circulating D538G and Y537S/N/C mutations were retrospectively analyzed by digital droplet PCR after first-line AI failure in patients treated consecutively from 2010 to 2012 for hormone receptor-positive metastatic breast cancer. Progression-free survival (PFS) and overall survival (OS) were analyzed according to circulating mutational status and subsequent lines of treatment. The kinetics of ESR1 mutation before (3 and 6 months) and after (3 months) AI progression were determined in the available archive plasmas. Circulating ESR1 mutations were found at AI progression in 44/144 patients included (30.6%). Median follow-up from AI initiation was 40 months (range 4-94). The median OS was decreased in patients with circulating ESR1 mutation than in patients without mutation (15.5 versus 23.8 months, P=0.0006). The median PFS was also significantly decreased in patients with ESR1 mutation than in patients without mutation (5.9 vs 7 months, P=0.002). After AI failure, there was no difference in outcome for patients receiving chemotherapy (n = 58) versus non-AI endocrine therapy (n=51) in patients with and without ESR1 mutation. ESR1 circulating mutations were detectable in 75% of all cases before AI progression, whereas the kinetics 3 months after progression did not correlate with outcome. ESR1 circulating mutations are independent risk factors for poor outcome after AI failure, and are frequently detectable before clinical progression. Interventional studies based on ESR1 circulating status are warranted.

Cortisol evaluation during the acute phase of traumatic brain injury-A prospective study.

PubMed

Bensalah, Meriem; Donaldson, Malcolm; Aribi, Yamina; Iabassen, Malek; Cherfi, Lyes; Nebbal, Mustapha; Medjaher, Meriem; Haffaf, ElMehdi; Abdennebi, Benaissa; Guenane, Kamel; Djermane, Adel; Kemali, Zahra; OuldKablia, Samia

2018-05-01

Biochemical diagnosis of adrenal insufficiency (AI) is difficult in the context of traumatic brain injury (TBI). To assess the frequency and predictive factors of AI in victims of TBI from Algiers. Between November 2009 and December 2013, TBI victims had a single 8-9 am serum cortisol measurement during the acute postinjury period (0-7 days). AI was defined according to basal cortisol levels of 83, 276 and 414 nmol/L. Variables studied were TBI severity according to Glasgow coma scale, duration of intubation and coma, pupillary status, hypotension, anaemia, brain imaging findings, diabetes insipidus and medication. Insulin tolerance test was performed during the recovery phase, defining AI as peak cortisol <500 nmol/L. Cortisol samples were obtained at median 3 (1-7) days from 277 patients (257M: 20F) aged 32 (18-65) years. Acute AI frequency was 8 (2.8%), 20 (21%) and 35 (37%), respectively using the three cortisol cut-offs. Factors predicting AI were diastolic hypotension, sedative medication, diabetes insipidus, skull base fracture and intraparenchymal haematoma. Mortality was highest in patients with acute cortisol <276 nmol/L (44.6% with OR for death 1.64, 95% CI 0.92-3.0, P = .12). During the recovery phase, AI was present in 3 of 3, 12 of 24, 4 of 16 and 20 of 66 patients with week 1 cortisol <83, 83-276, 277-414 and >414 nmol/L. Hydrocortisone replacement is advised in TBI patients with morning cortisol <276 nmol/L or those <414 nmol/L with additional risk factors for AI. As acute and subsequent AI are poorly correlated, patients with moderate/severe TBI require adrenal re-evaluation during the recovery phase. © 2018 John Wiley & Sons Ltd.

Frequency dependent hub role of the dorsal and ventral right anterior insula.

PubMed

Wang, Yifeng; Zhu, Lixia; Zou, Qijun; Cui, Qian; Liao, Wei; Duan, Xujun; Biswal, Bharat; Chen, Huafu

2018-01-15

The right anterior insula (rAI) plays a crucial role in generating adaptive behavior by orchestrating multiple brain networks. Based on functional separation findings of the insula and spectral fingerprints theory of cognitive functions, we hypothesize that the hub role of the rAI is region and frequency dependent. Using the Human Connectome Project dataset and backtracking approach, we segregate the rAI into dorsal and ventral parts at frequency bands from slow 6 to slow 3, indicating the frequency dependent functional separation of the rAI. Functional connectivity analysis shows that, within lower than 0.198 Hz frequency range, the dorsal and ventral parts of rAI form a complementary system to synchronize with externally and internally-oriented networks. Moreover, the relationship between the dorsal and ventral rAIs predicts the relationship between anti-correlated networks associated with the dorsal rAI at slow 6 and slow 5, suggesting a frequency dependent regulation of the rAI to brain networks. These findings could improve our understanding of the rAI by supporting the region and frequency dependent function of rAI and its essential role in coordinating brain systems relevant to internal and external environments. Copyright © 2017 Elsevier Inc. All rights reserved.

Obesity, Diabetes, and Birth Outcomes Among American Indians and Alaska Natives.

PubMed

Anderson, Kermyt G; Spicer, Paul; Peercy, Michael T

2016-12-01

Objectives To examine the relationships between prepregnancy diabetes mellitus (DM), gestational diabetes mellitus (GDM), and prepregnancy body mass index, with several adverse birth outcomes: preterm delivery (PTB), low birthweight (LBW), and macrosomia, comparing American Indians and Alaska Natives (AI/AN) with other race/ethnic groups. Methods The sample includes 5,193,386 singleton US first births from 2009-2013. Logistic regression is used to calculate adjusted odds ratios controlling for calendar year, maternal age, education, marital status, Kotelchuck prenatal care index, and child's sex. Results AI/AN have higher rates of diabetes than all other groups, and higher rates of overweight and obesity than whites or Hispanics. Neither overweight nor obesity predict PTB for AI/AN, in contrast to other groups, while diabetes predicts increased odds of PTB for all groups. Being overweight predicts reduced odds of LBW for all groups, but obesity is not predictive of LBW for AI/AN. Diabetes status also does not predict LBW for AI/AN; for other groups, LBW is more likely for women with DM or GDM. Overweight, obesity, DM, and GDM all predict higher odds of macrosomia for all race/ethnic groups. Conclusions for Practice Controlling diabetes in pregnancy, as well as prepregnancy weight gain, may help decrease preterm birth and macrosomia among AI/AN.

Respiratory impedance is correlated with airway narrowing in asthma using three-dimensional computed tomography.

PubMed

Karayama, M; Inui, N; Mori, K; Kono, M; Hozumi, H; Suzuki, Y; Furuhashi, K; Hashimoto, D; Enomoto, N; Fujisawa, T; Nakamura, Y; Watanabe, H; Suda, T

2018-03-01

Respiratory impedance comprises the resistance and reactance of the respiratory system and can provide detailed information on respiratory function. However, details of the relationship between impedance and morphological airway changes in asthma are unknown. We aimed to evaluate the correlation between imaging-based airway changes and respiratory impedance in patients with asthma. Respiratory impedance and spirometric data were evaluated in 72 patients with asthma and 29 reference subjects. We measured the intraluminal area (Ai) and wall thickness (WT) of third- to sixth-generation bronchi using three-dimensional computed tomographic analyses, and values were adjusted by body surface area (BSA, Ai/BSA, and WT/the square root (√) of BSA). Asthma patients had significantly increased respiratory impedance, decreased Ai/BSA, and increased WT/√BSA, as was the case in those without airflow limitation as assessed by spirometry. Ai/BSA was inversely correlated with respiratory resistance at 5 Hz (R5) and 20 Hz (R20). R20 had a stronger correlation with Ai/BSA than did R5. Ai/BSA was positively correlated with forced expiratory volume in 1 second/forced vital capacity ratio, percentage predicted forced expiratory volume in 1 second, and percentage predicted mid-expiratory flow. WT/√BSA had no significant correlation with spirometry or respiratory impedance. Respiratory resistance is associated with airway narrowing. © 2018 John Wiley & Sons Ltd.

Genetic and Environmental Risk Factors for Alcohol Use Disorders in American Indians and Alaskan Natives

PubMed Central

Enoch, Mary-Anne; Albaugh, Bernard J.

2016-01-01

Background and Objectives Genetic and environmental predictors for alcohol use disorder (AUD) are both important in the general population. As a group, American Indian and Alaskan Native individuals (AI/AN) are at increased risk for alcohol-related morbidity /mortality, early onset problem drinking and AUD. Methods Alcohol consumption behaviors amongst AI/AN tribes, environmental stressors and genetic studies in AI/AN and European-ancestry individuals are reviewed followed by an analysis of unique difficulties for undertaking research with AI/AN. Results Some AI/AN tribes have high rates of childhood trauma that predict psychopathology including AUD. The deleterious effects of historical trauma and forced placement in boarding schools cross generations to the present day. There are scanty numbers of genetic studies of AUD in AI/AN and these derive from only a few tribes. However, it is important to note that the results are largely similar to findings in European-ancestry individuals indicating that AI/AN do not have increased genetic risk for AUD. Conducting AI/AN genetic studies has been challenging, in part because of tribe disillusionment and mistrust over past experiences and unique hurdles in getting consent from tribes, each a sovereign nation. However, it is encouraging that a new way forward has been established – community-based participatory research with tangible health benefits and a focus on strength-based approaches. Conclusions and Scientific Significance Given the high prevalence of AUD in many AI/AN tribes and limited knowledge about genetic risk-resilience factors, it is important for our understanding of prevention and treatment that AI/AN research progresses and that more tribes are represented. PMID:27599369

Model-based evaluation of highly and low pathogenic avian influenza dynamics in wild birds

USGS Publications Warehouse

Hénaux, Viviane; Samuel, Michael D.; Bunck, Christine M.

2010-01-01

There is growing interest in avian influenza (AI) epidemiology to predict disease risk in wild and domestic birds, and prevent transmission to humans. However, understanding the epidemic dynamics of highly pathogenic (HPAI) viruses remains challenging because they have rarely been detected in wild birds. We used modeling to integrate available scientific information from laboratory and field studies, evaluate AI dynamics in individual hosts and waterfowl populations, and identify key areas for future research. We developed a Susceptible-Exposed-Infectious-Recovered (SEIR) model and used published laboratory challenge studies to estimate epidemiological parameters (rate of infection, latency period, recovery and mortality rates), considering the importance of age classes, and virus pathogenicity. Infectious contact leads to infection and virus shedding within 1–2 days, followed by relatively slower period for recovery or mortality. We found a shorter infectious period for HPAI than low pathogenic (LP) AI, which may explain that HPAI has been much harder to detect than LPAI during surveillance programs. Our model predicted a rapid LPAI epidemic curve, with a median duration of infection of 50–60 days and no fatalities. In contrast, HPAI dynamics had lower prevalence and higher mortality, especially in young birds. Based on field data from LPAI studies, our model suggests to increase surveillance for HPAI in post-breeding areas, because the presence of immunologically naïve young birds is predicted to cause higher HPAI prevalence and bird losses during this season. Our results indicate a better understanding of the transmission, infection, and immunity-related processes is required to refine predictions of AI risk and spread, improve surveillance for HPAI in wild birds, and develop disease control strategies to reduce potential transmission to domestic birds and/or humans.

The JAGUAR Score Predicts 1-Month Disability/Death in Ischemic Stroke Patient Ineligible for Recanalization Therapy.

PubMed

Widhi Nugroho, Aryandhito; Arima, Hisatomi; Takashima, Naoyuki; Fujii, Takako; Shitara, Satoshi; Miyamatsu, Naomi; Sugimoto, Yoshihisa; Nagata, Satoru; Komori, Masaru; Kita, Yoshikuni; Miura, Katsuyuki; Nozaki, Kazuhiko

2018-06-22

Most available scoring system to predict outcome after acute ischemic stroke (AIS) were established in Western countries. We aimed to develop a simple prediction score of 1-month severe disability/death after onset in AIS patients ineligible for recanalization therapy based on readily and widely obtainable on-admission clinical, laboratory and radiological examinations in Asian developing countries. Using the Shiga Stroke Registry, a large population-based registry in Japan, multivariable logistic regression analysis was conducted in 1617 AIS patients ineligible for recanalization therapy to yield ß-coefficients of significant predictors of 1-month modified Rankin Scale score of 5-6, which were then multiplied by a specific constant and rounded to nearest integer to develop 0-10 points system. Model discrimination and calibration were evaluated in the original and bootstrapped population. Japan Coma Scale score (J), age (A), random glucose (G), untimely onset-to-arrival time (U), atrial fibrillation (A), and preadmission dependency status according to the modified Rankin Scale score (R), were recognized as independent predictors of outcome. Each of their β-coefficients was multiplied by 1.3 creating the JAGUAR score. Its area under the curve (95% confidence interval) was .901 (.880- .922) and .901 (.900- .901) in the original and bootstrapped population, respectively. It was found to have good calibration in both study population (P = .27). The JAGUAR score can be an important prediction tool of severe disability/death in AIS patients ineligible for recanalization therapy that can be applied on admission with no complicated calculation and multimodal neuroimaging necessary, thus suitable for Asian developing countries. Copyright © 2018 National Stroke Association. Published by Elsevier Inc. All rights reserved.

Review on applications of artificial intelligence methods for dam and reservoir-hydro-environment models.

PubMed

Allawi, Mohammed Falah; Jaafar, Othman; Mohamad Hamzah, Firdaus; Abdullah, Sharifah Mastura Syed; El-Shafie, Ahmed

2018-05-01

Efficacious operation for dam and reservoir system could guarantee not only a defenselessness policy against natural hazard but also identify rule to meet the water demand. Successful operation of dam and reservoir systems to ensure optimal use of water resources could be unattainable without accurate and reliable simulation models. According to the highly stochastic nature of hydrologic parameters, developing accurate predictive model that efficiently mimic such a complex pattern is an increasing domain of research. During the last two decades, artificial intelligence (AI) techniques have been significantly utilized for attaining a robust modeling to handle different stochastic hydrological parameters. AI techniques have also shown considerable progress in finding optimal rules for reservoir operation. This review research explores the history of developing AI in reservoir inflow forecasting and prediction of evaporation from a reservoir as the major components of the reservoir simulation. In addition, critical assessment of the advantages and disadvantages of integrated AI simulation methods with optimization methods has been reported. Future research on the potential of utilizing new innovative methods based AI techniques for reservoir simulation and optimization models have also been discussed. Finally, proposal for the new mathematical procedure to accomplish the realistic evaluation of the whole optimization model performance (reliability, resilience, and vulnerability indices) has been recommended.

Interpersonal suicide risk for American Indians: investigating thwarted belongingness and perceived burdensomeness.

PubMed

O'Keefe, Victoria M; Wingate, LaRicka R; Tucker, Raymond P; Rhoades-Kerswill, Sarah; Slish, Meredith L; Davidson, Collin L

2014-01-01

American Indians (AIs) experience increased suicide rates compared with other groups in the United States. However, no past studies have examined AI suicide by way of a recent empirically supported theoretical model of suicide. The current study investigated whether AI suicidal ideation can be predicted by two components: thwarted belongingness and perceived burdensomeness, from the Interpersonal-Psychological Theory of Suicide (T. E. Joiner, 2005, Why people die by suicide. Cambridge, MA: Harvard University Press). One hundred seventy-one AIs representing 27 different tribes participated in an online survey. Hierarchical regression analyses showed that perceived burdensomeness significantly predicted suicidal ideation above and beyond demographic variables and depressive symptoms; however, thwarted belongingness did not. Additionally, the two-way interaction between thwarted belongingness and perceived burdensomeness significantly predicted suicidal ideation. These results provide initial support for continued research on the components of the Interpersonal-Psychological Theory of Suicide, an empirically supported theoretical model of suicide, to predict suicidal ideation among AI populations.

Optimization of DRASTIC method by supervised committee machine artificial intelligence to assess groundwater vulnerability for Maragheh-Bonab plain aquifer, Iran

NASA Astrophysics Data System (ADS)

Fijani, Elham; Nadiri, Ata Allah; Asghari Moghaddam, Asghar; Tsai, Frank T.-C.; Dixon, Barnali

2013-10-01

Contamination of wells with nitrate-N (NO3-N) poses various threats to human health. Contamination of groundwater is a complex process and full of uncertainty in regional scale. Development of an integrative vulnerability assessment methodology can be useful to effectively manage (including prioritization of limited resource allocation to monitor high risk areas) and protect this valuable freshwater source. This study introduces a supervised committee machine with artificial intelligence (SCMAI) model to improve the DRASTIC method for groundwater vulnerability assessment for the Maragheh-Bonab plain aquifer in Iran. Four different AI models are considered in the SCMAI model, whose input is the DRASTIC parameters. The SCMAI model improves the committee machine artificial intelligence (CMAI) model by replacing the linear combination in the CMAI with a nonlinear supervised ANN framework. To calibrate the AI models, NO3-N concentration data are divided in two datasets for the training and validation purposes. The target value of the AI models in the training step is the corrected vulnerability indices that relate to the first NO3-N concentration dataset. After model training, the AI models are verified by the second NO3-N concentration dataset. The results show that the four AI models are able to improve the DRASTIC method. Since the best AI model performance is not dominant, the SCMAI model is considered to combine the advantages of individual AI models to achieve the optimal performance. The SCMAI method re-predicts the groundwater vulnerability based on the different AI model prediction values. The results show that the SCMAI outperforms individual AI models and committee machine with artificial intelligence (CMAI) model. The SCMAI model ensures that no water well with high NO3-N levels would be classified as low risk and vice versa. The study concludes that the SCMAI model is an effective model to improve the DRASTIC model and provides a confident estimate of the pollution risk.

Using activity-based monitoring systems to detect dairy cows in oestrus: a field evaluation.

PubMed

Dela Rue, B T; Kamphuis, C; Burke, C R; Jago, J G

2014-03-01

To assess the use and performance of activity-based oestrus detection systems (ODS) on two commercial dairy farms using a gold standard based on profiles of concentrations of progesterone in milk, artificial insemination (AI) records and pregnancy diagnosis results. Two activity-based ODS were evaluated in mature cows on two large pasture-grazed dairy farms (>500 cows) over the first 3 weeks of AI. Farm 1 (n=286 cows) used a leg-mounted device and cows were drafted automatically based on activity alerts. Decisions regarding AI were then made based on tail-paint and cow history for these cows. Farm 2 (n=345 cows) used a collar-mounted device and activity alerts were used in conjunction with other information, before the farmer manually selected cows for AI. The gold standard to define the timing of oestrus was based on profiles of concentrations of progesterone in milk measured twice-weekly, used in conjunction with AI records and pregnancy diagnosis results. Sensitivity and positive predictive value (PPV) were calculated for the activity-based ODS data only, and then for AI decisions, against the gold standard. Farm 1 had 195 confirmed oestrus events and 209 activity alerts were generated. The sensitivity of the activity-based ODS was 89.2% with a PPV of 83.3%. Using tail-paint and cow history to confirm activity-based alerts 175 cows were inseminated, resulting in a sensitivity of 89.2% and an improved PPV of 99.4%. Farm 2 had 343 confirmed oestrus events, and 726 alerts were generated by the activity-based ODS, giving a sensitivity of 69.7% with a PPV of 32.9%. A total of 386 cows had AI records, giving a sensitivity of 81.3% and PPV of 72.3%. The two activity-based ODS were used differently on-farm; one automatically selecting cows and the other supporting the manual selection of cows in oestrus. Only one achieved a performance level suggested to be acceptable as a stand-alone ODS. Use of additional tools, such as observation of tail paint to confirm activity-based oestrus alerts before AI, substantially improved the PPV. A well performing activity-based ODS can be a valuable tool in identifying cows in oestrus prior to visual confirmation of oestrus status. However the performance of these ODS technologies varies considerably.

Immunity-based detection, identification, and evaluation of aircraft sub-system failures

NASA Astrophysics Data System (ADS)

Moncayo, Hever Y.

This thesis describes the design, development, and flight-simulation testing of an integrated Artificial Immune System (AIS) for detection, identification, and evaluation of a wide variety of sensor, actuator, propulsion, and structural failures/damages including the prediction of the achievable states and other limitations on performance and handling qualities. The AIS scheme achieves high detection rate and low number of false alarms for all the failure categories considered. Data collected using a motion-based flight simulator are used to define the self for an extended sub-region of the flight envelope. The NASA IFCS F-15 research aircraft model is used and represents a supersonic fighter which include model following adaptive control laws based on non-linear dynamic inversion and artificial neural network augmentation. The flight simulation tests are designed to analyze and demonstrate the performance of the immunity-based aircraft failure detection, identification and evaluation (FDIE) scheme. A general robustness analysis is also presented by determining the achievable limits for a desired performance in the presence of atmospheric perturbations. For the purpose of this work, the integrated AIS scheme is implemented based on three main components. The first component performs the detection when one of the considered failures is present in the system. The second component consists in the identification of the failure category and the classification according to the failed element. During the third phase a general evaluation of the failure is performed with the estimation of the magnitude/severity of the failure and the prediction of its effect on reducing the flight envelope of the aircraft system. Solutions and alternatives to specific design issues of the AIS scheme, such as data clustering and empty space optimization, data fusion and duplication removal, definition of features, dimensionality reduction, and selection of cluster/detector shape are also analyzed in this thesis. They showed to have an important effect on detection performance and are a critical aspect when designing the configuration of the AIS. The results presented in this thesis show that the AIS paradigm addresses directly the complexity and multi-dimensionality associated with a damaged aircraft dynamic response and provides the tools necessary for a comprehensive/integrated solution to the FDIE problem. Excellent detection, identification, and evaluation performance has been recorded for all types of failures considered. The implementation of the proposed AIS-based scheme can potentially have a significant impact on the safety of aircraft operation. The output information obtained from the scheme will be useful to increase pilot situational awareness and determine automated compensation.

Toward detecting California shrubland canopy chemistry with AIS data

NASA Technical Reports Server (NTRS)

Price, Curtis V.; Westman, Walter E.

1987-01-01

Airborne Imaging Spectrometer (AIS)-2 data of coastal sage scrub vegetation were examined for fine spectral features that might be used to predict concentrations of certain canopy chemical constituents. A Fourier notch filter was applied to the AIS data and the TREE and ROCK mode spectra were ratioed to a flat field. Portions of the resulting spectra resemble spectra for plant cellulose and starch in that both show reduced reflectance at 2100 and 2270 nm. The latter are regions of absorption of energy by organic bonds found in starch and cellulose. Whether the relationship is sufficient to predict the concentration of these chemicals from AIS spectra will require testing of the predictive ability of these wavebands with large field sample sizes.

Characterization and Predictive Value of Segmental Curve Flexibility in Adolescent Idiopathic Scoliosis Patients.

PubMed

Yao, Guanfeng; Cheung, Jason P Y; Shigematsu, Hideki; Ohrt-Nissen, Søren; Cheung, Kenneth M C; Luk, Keith D K; Samartzis, Dino

2017-11-01

A prospective radiographic analysis of adolescent idiopathic scoliosis (AIS) patients managed with alternate-level pedicle screw fixation was performed. The objective of this study was to characterize segmental curve flexibility and to determine its predictive value in curve correction in AIS patients. Little is known regarding the distinct segmental curve characteristics and their ability to predict curve correction in patients with AIS. The segmental Cobb angle was measured on posteroanterior standing radiographs and on fulcrum bending radiographs. Radiographs were analyzed preoperatively and at 2 years postoperatively and the curve was divided into upper, mid, and lower segments based on predefined criteria. The segmental flexibility and the segmental fulcrum bending correction index (FBCI) were calculated. Eighty patients were included with mean age of 15 years. Preoperative mean segmental Cobb angles were 18, 31, and 17 degrees in the upper, mid, and lower segments, respectively. Segmental bending Cobb angles were 6, 13, and 4 degrees, respectively, corresponding to segmental flexibilities of 50%, 47%, and 83% in the upper, mid, and lower segments, respectively (P < 0.001). At 2-year follow up, the mean segmental FBCI were 155%, 131%, and 100% in the upper, mid, and lower segments, respectively (P < 0.001), which suggested that the lower segment of the curve was more flexible than the other segments and that higher correction was noted in the upper segments. A significant, positive correlation was noted between the segmental bending Cobb angle and the segmental FBCI (P < 0.05), whereby the strength of the correlation varied based on the curve segment. This is the first study to demonstrate the segmental variations in curve flexibility using the fulcrum bending radiograph in AIS patients. Curve flexibility is not uniform throughout the curve and different segments exhibit greater flexibility/correctibility than others. Segmental flexibility should be considered in assessing AIS patients and in the clinical decision-making strategy to optimize curve correction outcomes. 03.

Prediction of Mortality in Patients with Isolated Traumatic Subarachnoid Hemorrhage Using a Decision Tree Classifier: A Retrospective Analysis Based on a Trauma Registry System.

PubMed

Rau, Cheng-Shyuan; Wu, Shao-Chun; Chien, Peng-Chen; Kuo, Pao-Jen; Chen, Yi-Chun; Hsieh, Hsiao-Yun; Hsieh, Ching-Hua

2017-11-22

Background: In contrast to patients with traumatic subarachnoid hemorrhage (tSAH) in the presence of other types of intracranial hemorrhage, the prognosis of patients with isolated tSAH is good. The incidence of mortality in these patients ranges from 0-2.5%. However, few data or predictive models are available for the identification of patients with a high mortality risk. In this study, we aimed to construct a model for mortality prediction using a decision tree (DT) algorithm, along with data obtained from a population-based trauma registry, in a Level 1 trauma center. Methods: Five hundred and forty-five patients with isolated tSAH, including 533 patients who survived and 12 who died, between January 2009 and December 2016, were allocated to training ( n = 377) or test ( n = 168) sets. Using the data on demographics and injury characteristics, as well as laboratory data of the patients, classification and regression tree (CART) analysis was performed based on the Gini impurity index, using the rpart function in the rpart package in R. Results: In this established DT model, three nodes (head Abbreviated Injury Scale (AIS) score ≤4, creatinine (Cr) <1.4 mg/dL, and age <76 years) were identified as important determinative variables in the prediction of mortality. Of the patients with isolated tSAH, 60% of those with a head AIS >4 died, as did the 57% of those with an AIS score ≤4, but Cr ≥1.4 and age ≥76 years. All patients who did not meet the above-mentioned criteria survived. With all the variables in the model, the DT achieved an accuracy of 97.9% (sensitivity of 90.9% and specificity of 98.1%) and 97.7% (sensitivity of 100% and specificity of 97.7%), for the training set and test set, respectively. Conclusions: The study established a DT model with three nodes (head AIS score ≤4, Cr <1.4, and age <76 years) to predict fatal outcomes in patients with isolated tSAH. The proposed decision-making algorithm may help identify patients with a high risk of mortality.

Artificial intelligence in predicting bladder cancer outcome: a comparison of neuro-fuzzy modeling and artificial neural networks.

PubMed

Catto, James W F; Linkens, Derek A; Abbod, Maysam F; Chen, Minyou; Burton, Julian L; Feeley, Kenneth M; Hamdy, Freddie C

2003-09-15

New techniques for the prediction of tumor behavior are needed, because statistical analysis has a poor accuracy and is not applicable to the individual. Artificial intelligence (AI) may provide these suitable methods. Whereas artificial neural networks (ANN), the best-studied form of AI, have been used successfully, its hidden networks remain an obstacle to its acceptance. Neuro-fuzzy modeling (NFM), another AI method, has a transparent functional layer and is without many of the drawbacks of ANN. We have compared the predictive accuracies of NFM, ANN, and traditional statistical methods, for the behavior of bladder cancer. Experimental molecular biomarkers, including p53 and the mismatch repair proteins, and conventional clinicopathological data were studied in a cohort of 109 patients with bladder cancer. For all three of the methods, models were produced to predict the presence and timing of a tumor relapse. Both methods of AI predicted relapse with an accuracy ranging from 88% to 95%. This was superior to statistical methods (71-77%; P < 0.0006). NFM appeared better than ANN at predicting the timing of relapse (P = 0.073). The use of AI can accurately predict cancer behavior. NFM has a similar or superior predictive accuracy to ANN. However, unlike the impenetrable "black-box" of a neural network, the rules of NFM are transparent, enabling validation from clinical knowledge and the manipulation of input variables to allow exploratory predictions. This technique could be used widely in a variety of areas of medicine.

Three-Dimensional Spinal Morphology Can Differentiate Between Progressive and Nonprogressive Patients With Adolescent Idiopathic Scoliosis at the Initial Presentation

PubMed Central

Nault, Marie-Lyne; Mac-Thiong, Jean-Marc; Roy-Beaudry, Marjolaine; Turgeon, Isabelle; deGuise, Jacques; Labelle, Hubert

2014-01-01

Study Design. This is a prospective case-control study. Objective. The objective of this study was to compare 3-dimensional (3D) morphological parameters of the spine at the first visit between a nonprogressive (NP) and a progressive (P) group of immature adolescent idiopathic scoliosis (AIS). Summary of Background Data. Prediction of curve progression remains challenging in AIS at the first visit. Prediction of progression is based on curve type, curve magnitude, and skeletal or chronological age. Methods. A prospective cohort of 133 AIS was followed from skeletal immaturity to maturity (mean, 37 mo). The first group was made up of patients with AIS with a minimum 6-degree progression of the major curve between the first and last follow-up (P) (n = 53) and the second group was composed of patients with NP who reached maturity with less than 6-degree progression (n = 81). Computerized measurements were taken on reconstructed 3-dimensional (3D) spine radiographs of the first visit. There were 6 categories of measurements: angle of plane of maximum curvature, Cobb angles (kyphosis, lordosis), 3D wedging (apical vertebra, apical disks), rotation (upper and lower junctional vertebra, apical vertebra, and thoracolumbar junction), torsion, and slenderness (height/width ratio). t tests were also conducted. Results. There was no statistical difference between the 2 groups for age and initial Cobb angle. P presented significant hypokyphosis, and parameters related to rotation presented significant statistical differences between NP and P (plane of maximal curvature, torsion, and apical axial rotation). Depth slenderness also presented statistical differences. Conclusion. This study confirms that even at the initial visit, 3D morphological differences exist between P and NP AIS. It supports the use of 3D reconstructions of the spine in the initial evaluation of AIS to help predict outcome. Level of Evidence: 3 PMID:24776699

Forecasting Caspian Sea level changes using satellite altimetry data (June 1992-December 2013) based on evolutionary support vector regression algorithms and gene expression programming

NASA Astrophysics Data System (ADS)

Imani, Moslem; You, Rey-Jer; Kuo, Chung-Yen

2014-10-01

Sea level forecasting at various time intervals is of great importance in water supply management. Evolutionary artificial intelligence (AI) approaches have been accepted as an appropriate tool for modeling complex nonlinear phenomena in water bodies. In the study, we investigated the ability of two AI techniques: support vector machine (SVM), which is mathematically well-founded and provides new insights into function approximation, and gene expression programming (GEP), which is used to forecast Caspian Sea level anomalies using satellite altimetry observations from June 1992 to December 2013. SVM demonstrates the best performance in predicting Caspian Sea level anomalies, given the minimum root mean square error (RMSE = 0.035) and maximum coefficient of determination (R2 = 0.96) during the prediction periods. A comparison between the proposed AI approaches and the cascade correlation neural network (CCNN) model also shows the superiority of the GEP and SVM models over the CCNN.

A New Weighted Injury Severity Scoring System: Better Predictive Power for Pediatric Trauma Mortality.

PubMed

Shi, Junxin; Shen, Jiabin; Caupp, Sarah; Wang, Angela; Nuss, Kathryn E; Kenney, Brian; Wheeler, Krista K; Lu, Bo; Xiang, Henry

2018-05-02

An accurate injury severity measurement is essential for the evaluation of pediatric trauma care and outcome research. The traditional Injury Severity Score (ISS) does not consider the differential risks of the Abbreviated Injury Scale (AIS) from different body regions nor is it pediatric specific. The objective of this study was to develop a weighted injury severity scoring (wISS) system for pediatric blunt trauma patients with better predictive power than ISS. Based on the association between mortality and AIS from each of the six ISS body regions, we generated different weights for the component AIS scores used in the calculation of ISS. The weights and wISS were generated using the National Trauma Data Bank (NTDB). The Nationwide Emergency Department Sample (NEDS) was used to validate our main results. Pediatric blunt trauma patients less than 16 years were included, and mortality was the outcome. Discrimination (areas under the receiver operating characteristic curve, sensitivity, specificity, positive predictive value, negative predictive value, concordance) and calibration (Hosmer-Lemeshow statistic) were compared between the wISS and ISS. The areas under the receiver operating characteristic curves from the wISS and ISS are 0.88 vs. 0.86 in ISS=1-74 and 0.77 vs. 0.64 in ISS=25-74 (p<0.0001). The wISS showed higher specificity, positive predictive value, negative predictive value, and concordance when they were compared at similar levels of sensitivity. The wISS had better calibration (smaller Hosmer-Lemeshow statistic) than the ISS (11.6 versus 19.7 for ISS=1-74 and 10.9 versus 12.6 for ISS= 25-74). The wISS showed even better discrimination with the NEDS. By weighting the AIS from different body regions, the wISS had significantly better predictive power for mortality than the ISS, especially in critically injured children.Level of Evidence and study typeLevel IV Prognostic/Epidemiological.

Diagnostic accuracy of the Kampala Trauma Score using estimated Abbreviated Injury Scale scores and physician opinion.

PubMed

Gardner, Andrew; Forson, Paa Kobina; Oduro, George; Stewart, Barclay; Dike, Nkechi; Glover, Paul; Maio, Ronald F

2017-01-01

The Kampala Trauma Score (KTS) has been proposed as a triage tool for use in low- and middle-income countries (LMICs). This study aimed to examine the diagnostic accuracy of KTS in predicting emergency department outcomes using timely injury estimation with Abbreviated Injury Scale (AIS) score and physician opinion to calculate KTS scores. This was a diagnostic accuracy study of KTS among injured patients presenting to Komfo Anokye Teaching Hospital A&E, Ghana. South African Triage Scale (SATS); KTS component variables, including AIS scores and physician opinion for serious injury quantification; and ED disposition were collected. Agreement between estimated AIS score and physician opinion were analyzed with normal, linear weighted, and maximum kappa. Receiver operating characteristic (ROC) analysis of KTS-AIS and KTS-physician opinion was performed to evaluate each measure's ability to predict A&E mortality and need for hospital admission to the ward or theatre. A total of 1053 patients were sampled. There was moderate agreement between AIS criteria and physician opinion by normal (κ=0.41), weighted (κ lin =0.47), and maximum (κ max =0.53) kappa. A&E mortality ROC area for KTS-AIS was 0.93, KTS-physician opinion 0.89, and SATS 0.88 with overlapping 95% confidence intervals (95%CI). Hospital admission ROC area for KTS-AIS was 0.73, KTS-physician opinion 0.79, and SATS 0.71 with statistical similarity. When evaluating only patients with serious injuries, KTS-AIS (ROC 0.88) and KTS-physician opinion (ROC 0.88) performed similarly to SATS (ROC 0.78) in predicting A&E mortality. The ROC area for KTS-AIS (ROC 0.71; 95%CI 0.66-0.75) and KTS-physician opinion (ROC 0.74; 95%CI 0.69-0.79) was significantly greater than SATS (ROC 0.57; 0.53-0.60) with regard to need for admission. KTS predicted mortality and need for admission from the ED well when early estimation of the number of serious injuries was used, regardless of method (i.e. AIS criteria or physician opinion). This study provides evidence for KTS to be used as a practical and valid triage tool to predict patient prognosis, ED outcomes and inform referral decision-making from first- or second-level hospitals in LMICs. Copyright © 2016 Elsevier Ltd. All rights reserved.

Diagnostic accuracy of the Kampala Trauma Score using estimated Abbreviated Injury Scale scores and physician opinion

PubMed Central

Gardner, Andrew; Forson, Paa Kobina; Oduro, George; Stewart, Barclay; Dike, Nkechi; Glover, Paul; Maio, Ronald F.

2016-01-01

Background The Kampala Trauma Score (KTS) has been proposed as a triage tool for use in low- and middle-income countries (LMICs). This study aimed to examine the diagnostic accuracy of KTS in predicting emergency department outcomes using timely injury estimation with Abbreviated Injury Scale (AIS) score and physician opinion to calculate KTS scores. Methods This was a diagnostic accuracy study of KTS among injured patients presenting to Komfo Anokye Teaching Hospital A&E, Ghana. South African Triage Scale (SATS); KTS component variables, including AIS scores and physician opinion for serious injury quantification; and ED disposition were collected. Agreement between estimated AIS score and physician opinion were analyzed with normal, linear weighted, and maximum kappa. Receiver operating characteristic (ROC) analysis of KTS-AIS and KTS-physician opinion was performed to evaluate each measure’s ability to predict A&E mortality and need for hospital admission to the ward or theatre. Results A total of 1,053 patients were sampled. There was moderate agreement between AIS criteria and physician opinion by normal (κ=0.41), weighted (κlin=0.47), and maximum (κmax=0.53) kappa. A&E mortality ROC area for KTS-AIS was 0.93, KTS-physician opinion 0.89, and SATS 0.88 with overlapping 95% confidence intervals (95%CI). Hospital admission ROC area for KTS-AIS was 0.73, KTS-physician opinion 0.79, and SATS 0.71 with statistical similarity. When evaluating only patients with serious injuries, KTS-AIS (ROC 0.88) and KTS-physician opinion (ROC 0.88) performed similarly to SATS (ROC 0.78) in predicting A&E mortality. The ROC area for KTS-AIS (ROC 0.71; 95%CI 0.66–0.75) and KTS-physician opinion (ROC 0.74; 95%CI 0.69–0.79) was significantly greater than SATS (ROC 0.57; 0.53–0.60) with regard to need for admission. Conclusions KTS predicted mortality and need for admission from the ED well when early estimation of the number of serious injuries was used, regardless of method (i.e. AIS criteria or physician opinion). This study provides evidence for KTS to be used as a practical and valid triage tool to predict patient prognosis, ED outcomes and inform referral decision-making from first- or second-level hospitals in LMICs. PMID:27908493

Which AIS based scoring system is the best predictor of outcome in orthopaedic blunt trauma patients?

PubMed

Harwood, Paul J; Giannoudis, Peter V; Probst, Christian; Van Griensven, Martijn; Krettek, Christian; Pape, Hans-Christoph

2006-02-01

Abbreviated Injury Scale (AIS)-based systems-the Injury Severity Score (ISS), New Injury Severity Score (NISS), and AISmax-are used to assess trauma patients. The merits of each in predicting outcome are controversial. A large prospective database was used to assess their predictive capacity using receiver operator characteristic curves. In all, 10,062 adult, blunt-trauma patients met the inclusion criteria. All systems were significant outcome predictors for sepsis, multiple organ failure (MOF), length of hospital stay, length of intensive care unit (ICU) admission and mortality (p < 0.0001). NISS was a significantly better predictor than the ISS for mortality (p < 0.0001). NISS was equivalent to the AISmax for mortality prediction and superior in patients with orthopaedic injuries. NISS was significantly better for sepsis, MOF, ICU stay, and total hospital stay (p < 0.0001). NISS is superior or equivalent to the ISS and AISmax for prediction of all investigated outcomes in a population of blunt trauma patients. As NISS is easier to calculate, its use is recommended to stratify patients for clinical and research purposes.

AI AND SAR APPROACHES FOR PREDICTING CHEMICAL CARCINOGENICITY: SURVEY AND STATUS REPORT

EPA Science Inventory

A wide variety of artificial intelligence (AI) and structure-activity relationship (SAR approaches have been applied to tackling the general problem of predicting rodent chemical carcinogenicity. Given the diversity of chemical structures and mechanisms relative to this endpoin...

In Vitro Measures for Assessing Boar Semen Fertility.

PubMed

Jung, M; Rüdiger, K; Schulze, M

2015-07-01

Optimization of artificial insemination (AI) for pig production and evaluation of the fertilizing capacity of boar semen are highly related. Field studies have demonstrated significant variation in semen quality and fertility. The semen quality of boars is primarily affected by breed and season. AI centres routinely examine boar semen to predict male fertility. Overall, the evaluation of classical parameters, such as sperm morphology, sperm motility, sperm concentration and ejaculate volume, allows the identification of ejaculates corresponding to poor fertility but not high-efficiency prediction of field fertility. The development of new sperm tests for measuring certain sperm functions has attempted to solve this problem. Fluorescence staining can categorize live and dead spermatozoa in the ejaculate and identify spermatozoa with active mitochondria. Computer-assisted semen analysis (CASA) provides an objective assessment of multiple kinetic sperm parameters. However, sperm tests usually assess only single factors involved in the fertilization process. Thus, basing prediction of fertilizing capacity on a selective collection of sperm tests leads to greater accuracy than using single tests. In the present brief review, recent diagnostic laboratory methods that directly relate to AI performance as well as the development of a new boar fertility in vitro index are discussed. © 2015 Blackwell Verlag GmbH.

[Artificial intelligence in medicine: limits and obstacles.

PubMed

Santoro, Eugenio

2017-12-01

Data scientists and physicians are starting to use artificial intelligence (AI) even in the medical field in order to better understand the relationships among the huge amount of data coming from the great number of sources today available. Through the data interpretation methods made available by the recent AI tools, researchers and AI companies have focused on the development of models allowing to predict the risk of suffering from a specific disease, to make a diagnosis, and to recommend a treatment that is based on the best and most updated scientific evidence. Even if AI is used to perform unimaginable tasks until a few years ago, the awareness about the ongoing revolution has not yet spread through the medical community for several reasons including the lack of evidence about safety, reliability and effectiveness of these tools, the lack of regulation accompanying hospitals in the use of AI by health care providers, the difficult attribution of liability in case of errors and malfunctions of these systems, and the ethical and privacy questions that they raise and that, as of today, are still unanswered.

Risk score to predict gastrointestinal bleeding after acute ischemic stroke.

PubMed

Ji, Ruijun; Shen, Haipeng; Pan, Yuesong; Wang, Penglian; Liu, Gaifen; Wang, Yilong; Li, Hao; Singhal, Aneesh B; Wang, Yongjun

2014-07-25

Gastrointestinal bleeding (GIB) is a common and often serious complication after stroke. Although several risk factors for post-stroke GIB have been identified, no reliable or validated scoring system is currently available to predict GIB after acute stroke in routine clinical practice or clinical trials. In the present study, we aimed to develop and validate a risk model (acute ischemic stroke associated gastrointestinal bleeding score, the AIS-GIB score) to predict in-hospital GIB after acute ischemic stroke. The AIS-GIB score was developed from data in the China National Stroke Registry (CNSR). Eligible patients in the CNSR were randomly divided into derivation (60%) and internal validation (40%) cohorts. External validation was performed using data from the prospective Chinese Intracranial Atherosclerosis Study (CICAS). Independent predictors of in-hospital GIB were obtained using multivariable logistic regression in the derivation cohort, and β-coefficients were used to generate point scoring system for the AIS-GIB. The area under the receiver operating characteristic curve (AUROC) and the Hosmer-Lemeshow goodness-of-fit test were used to assess model discrimination and calibration, respectively. A total of 8,820, 5,882, and 2,938 patients were enrolled in the derivation, internal validation and external validation cohorts. The overall in-hospital GIB after AIS was 2.6%, 2.3%, and 1.5% in the derivation, internal, and external validation cohort, respectively. An 18-point AIS-GIB score was developed from the set of independent predictors of GIB including age, gender, history of hypertension, hepatic cirrhosis, peptic ulcer or previous GIB, pre-stroke dependence, admission National Institutes of Health stroke scale score, Glasgow Coma Scale score and stroke subtype (Oxfordshire). The AIS-GIB score showed good discrimination in the derivation (0.79; 95% CI, 0.764-0.825), internal (0.78; 95% CI, 0.74-0.82) and external (0.76; 95% CI, 0.71-0.82) validation cohorts. The AIS-GIB score was well calibrated in the derivation (P = 0.42), internal (P = 0.45) and external (P = 0.86) validation cohorts. The AIS-GIB score is a valid clinical grading scale to predict in-hospital GIB after AIS. Further studies on the effect of the AIS-GIB score on reducing GIB and improving outcome after AIS are warranted.

A Study of Impairing Injuries in Real World Crashes Using the Injury Impairment Scale (IIS) and the Predicted Functional Capacity Index (PFCI-AIS)

PubMed Central

Barnes, Jo; Morris, Andrew

2009-01-01

The ability to predict impairment outcomes in large databases using a simplified technique allows researchers to focus attention on preventing costly impairing injuries. The dilemma that exists for researchers is to determine which method is the most reliable and valid. This study examines available methods to predict impairment and explores the differences between the IIS and pFCI applied to real world crash injury data. Occupant injury data from the UK Co-operative Crash Injury Study (CCIS) database have been coded using AIS 1990 and AIS 2005. The data have subsequently been recoded using the associated impairment scales namely the Injury Impairment Scale (IIS) and the predicted Functional Capacity Index (pFCI) to determine the predicted impairment levels of injuries at one year post crash. Comparisons between the levels of impairment were made and any differences further explored. Injury data for the period February 2006 to September 2008 from the CCIS database were used in the analysis which involved a dataset of 2,437 occcupants who sustained over 8000 injuries. This study found some differences between the impairment scales for injuries coded to the AIS 1990 and AIS 2005 coding dictionaries. The pFCI predicts 31.5% of injuries to be impairing in AIS 2005, less than the IIS (38.5%) using AIS 1990. Using CCIS data the pFCI predicted that only 6% of the occupants with a coded injury would have an impairing injury compared to 24% of occupants using the IIS. The main body regions identified as having the major differences between the two impairment scales for car occupants were the head and spine. Follow up data were then used for a small number of cases (n=31, lower extremity and whiplash injuries) to examine any differences in predicted impairment versus perceived impairment. These data were selected from a previous study conducted between 2003 and 2006 and identified the discrepancy between predicted impairment and actual perceived impairment as defined by the participant. Overall the work highlights the variaton between the pFCI and IIS and emphasises the importance and need for a single validated impairment scale that can be universally applied. This would allow emphasis to be directed towards preventing injuries that are associated with the most significant impairment outcomes. PMID:20184844

A study of impairing injuries in real world crashes using the Injury Impairment Scale (IIS) and the predicted Functional Capacity Index (PFCI-AIS).

PubMed

Barnes, Jo; Morris, Andrew

2009-10-01

The ability to predict impairment outcomes in large databases using a simplified technique allows researchers to focus attention on preventing costly impairing injuries. The dilemma that exists for researchers is to determine which method is the most reliable and valid. This study examines available methods to predict impairment and explores the differences between the IIS and pFCI applied to real world crash injury data. Occupant injury data from the UK Co-operative Crash Injury Study (CCIS) database have been coded using AIS 1990 and AIS 2005. The data have subsequently been recoded using the associated impairment scales namely the Injury Impairment Scale (IIS) and the predicted Functional Capacity Index (pFCI) to determine the predicted impairment levels of injuries at one year post crash. Comparisons between the levels of impairment were made and any differences further explored. Injury data for the period February 2006 to September 2008 from the CCIS database were used in the analysis which involved a dataset of 2,437 occcupants who sustained over 8000 injuries. This study found some differences between the impairment scales for injuries coded to the AIS 1990 and AIS 2005 coding dictionaries. The pFCI predicts 31.5% of injuries to be impairing in AIS 2005, less than the IIS (38.5%) using AIS 1990. Using CCIS data the pFCI predicted that only 6% of the occupants with a coded injury would have an impairing injury compared to 24% of occupants using the IIS. The main body regions identified as having the major differences between the two impairment scales for car occupants were the head and spine. Follow up data were then used for a small number of cases (n=31, lower extremity and whiplash injuries) to examine any differences in predicted impairment versus perceived impairment. These data were selected from a previous study conducted between 2003 and 2006 and identified the discrepancy between predicted impairment and actual perceived impairment as defined by the participant. Overall the work highlights the variation between the pFCI and IIS and emphasises the importance and need for a single validated impairment scale that can be universally applied. This would allow emphasis to be directed towards preventing injuries that are associated with the most significant impairment outcomes.

Human Frontal Lobes and AI Planning Systems

NASA Technical Reports Server (NTRS)

Levinson, Richard; Lum, Henry Jr. (Technical Monitor)

1994-01-01

Human frontal lobes are essential for maintaining a self-regulating balance between predictive and reactive behavior. This paper describes a system that integrates prediction and reaction based on neuropsychological theories of frontal lobe function. In addition to enhancing our understanding of deliberate action in humans' the model is being used to develop and evaluate the same properties in machines. First, the paper presents some background neuropsychology in order to set a general context. The role of frontal lobes is then presented by summarizing three theories which formed the basis for this work. The components of an artificial frontal lobe are then discussed from both neuropsychological and AI perspectives. The paper concludes by discussing issues and methods for evaluating systems that integrate planning and reaction.

Prediction of shipboard electromagnetic interference (EMI) problems using artificial intelligence (AI) technology

NASA Technical Reports Server (NTRS)

Swanson, David J.

1990-01-01

The electromagnetic interference prediction problem is characteristically ill-defined and complicated. Severe EMI problems are prevalent throughout the U.S. Navy, causing both expected and unexpected impacts on the operational performance of electronic combat systems onboard ships. This paper focuses on applying artificial intelligence (AI) technology to the prediction of ship related electromagnetic interference (EMI) problems.

Using the abbreviated injury severity and Glasgow Coma Scale scores to predict 2-week mortality after traumatic brain injury.

PubMed

Timmons, Shelly D; Bee, Tiffany; Webb, Sharon; Diaz-Arrastia, Ramon R; Hesdorffer, Dale

2011-11-01

Prediction of outcome after traumatic brain injury (TBI) remains elusive. We tested the use of a single hospital Glasgow Coma Scale (GCS) Score, GCS Motor Score, and the Head component of the Abbreviated Injury Scale (AIS) Score to predict 2-week cumulative mortality in a large cohort of TBI patients admitted to the eight U.S. Level I trauma centers in the TBI Clinical Trials Network. Data on 2,808 TBI patients were entered into a centralized database. These TBI patients were categorized as severe (GCS score, 3-8), moderate (9-12), or complicated mild (13-15 with positive computed tomography findings). Intubation and chemical paralysis were recorded. The cumulative incidence of mortality in the first 2 weeks after head injury was calculated using Kaplan-Meier survival analysis. Cox proportional hazards regression was used to estimate the magnitude of the risk for 2-week mortality. Two-week cumulative mortality was independently predicted by GCS, GCS Motor Score, and Head AIS. GCS Severity Category and GCS Motor Score were stronger predictors of 2-week mortality than Head AIS. There was also an independent effect of age (<60 vs. ≥60) on mortality after controlling for both GCS and Head AIS Scores. Anatomic and physiologic scales are useful in the prediction of mortality after TBI. We did not demonstrate any added benefit to combining the total GCS or GCS Motor Scores with the Head AIS Score in the short-term prediction of death after TBI.

Comparison of clinician-predicted to measured low vision outcomes.

PubMed

Chan, Tiffany L; Goldstein, Judith E; Massof, Robert W

2013-08-01

To compare low-vision rehabilitation (LVR) clinicians' predictions of the probability of success of LVR with patients' self-reported outcomes after provision of usual outpatient LVR services and to determine if patients' traits influence clinician ratings. The Activity Inventory (AI), a self-report visual function questionnaire, was administered pre-and post-LVR to 316 low-vision patients served by 28 LVR centers that participated in a collaborative observational study. The physical component of the Short Form-36, Geriatric Depression Scale, and Telephone Interview for Cognitive Status were also administered pre-LVR to measure physical capability, depression, and cognitive status. After patient evaluation, 38 LVR clinicians estimated the probability of outcome success (POS) using their own criteria. The POS ratings and change in functional ability were used to assess the effects of patients' baseline traits on predicted outcomes. A regression analysis with a hierarchical random-effects model showed no relationship between LVR physician POS estimates and AI-based outcomes. In another analysis, kappa statistics were calculated to determine the probability of agreement between POS and AI-based outcomes for different outcome criteria. Across all comparisons, none of the kappa values were significantly different from 0, which indicates that the rate of agreement is equivalent to chance. In an exploratory analysis, hierarchical mixed-effects regression models show that POS ratings are associated with information about the patient's cognitive functioning and the combination of visual acuity and functional ability, as opposed to visual acuity or functional ability alone. Clinicians' predictions of LVR outcomes seem to be influenced by knowledge of patients' cognitive functioning and the combination of visual acuity and functional ability-information clinicians acquire from the patient's history and examination. However, clinicians' predictions do not agree with observed changes in functional ability from the patient's perspective; they are no better than chance.

Effect of education on ability of AI professionals and herd-owner inseminators to detect cows not in oestrus and its relation with progesterone concentration on day of re-insemination.

PubMed

Vartia, K; Taponen, J; Heikkinen, J; Lindeberg, H

2017-10-15

The effect of training background of persons performing artificial insemination (AI) (herd-owner inseminators (OWNER), AI technicians (AI-T), and fertility consultants (FC)) on pregnancy rate and their ability to detect cows not in oestrus were studied. A total of 1584 re-AI occasions on 754 dairy farms were included. Milk samples for progesterone (P4) analysis in all cases were collected, as were data on the herd, previous breeding attempts, oestrous signs, uterine tone, slipperiness of cervix, and co-operation of the cow. Further breeding attempts and next calving or culling date were sought from registers. The cases were distributed into three categories based on P4 concentrations; <6 nmol/l (no luteal activity, could be in oestrus), 6-10 nmol/l (some luteal activity), and >10 nmol/l (high luteal activity, not in oestrus). Of cows offered for re-AI 7.7% had P4 concentration >10 nmol/l, with no difference between OWNER farms and farms using AI service. OWNERs chose for AI more cows having intermediate P4 than farms using AI service (9.8% vs. 5.9%, p < 0.05). AI-Ts recommended no AI significantly less often than FCs (1.6% vs. 4.9%, p < 0.01). Both groups were equally right: 71% and 68% of cows that were recommended to have no AI had high P4 concentration. Due to courageous and correct rejection of cows with high P4, FCs inseminated proportionally more cows in low P4 and less cows in intermediate P4 than OWNERs (p < 0.05). Of cows finally inseminated, 36.7% became pregnant, with no difference between OWNER farms and farms using AI service. Fertility consultants had higher pregnancy rates than AI-Ts (39.6% vs. 32.6%, p < 0.05). Toneless uterus and sticky cervix at AI significantly correlated with AI occurring at the wrong time (p < 0.001). Behaviour of the cow at AI did not predict P4 concentration. In conclusion, 7.7% of cows offered for re-AI had high P4 concentration. Training of AI personnel increased their ability to detect and reject these cows. Copyright © 2017 Elsevier Inc. All rights reserved.

Civic engagement and political participation among American Indians and Alaska natives in the US†

PubMed Central

Huyser, Kimberly R.; Sanchez, Gabriel R.; Vargas, Edward D.

2016-01-01

Within the growing literature seeking to understand civic and political engagement among racial and ethnic minorities, our understanding of political behavior among American Indian and Alaska Native’s (AI/AN) remains limited. We use the Current Population Survey Civic Engagement and Voting and Registration supplements (2006-2012) to compare AI/AN voter registration, voting, and overall civic engagement to other racial and ethnic groups and to assess whether factors that predict higher levels of civic engagement vary across these populations. We find a few key socio-economic status indicators that predict civic and political engagement uniquely for AI/ANs, but they are not consistently significant across all years or all types of political participation. We find marital status, age, household size, education, and veteran status to be important in predicting civic engagement for AI/ANs. However, for voting and registration, we find that family income, age, marital status, household size, and residential stability to be important contributors. Although we find AI/ANs are less likely to register and vote compared to non-Hispanic whites, we find that the difference is not statistically significant in congressional years, which may suggest that AI/ANs are engaged in local politics and vote for representatives that will represent their tribal interests in national politics. PMID:29226016

Civic engagement and political participation among American Indians and Alaska natives in the US.

PubMed

Huyser, Kimberly R; Sanchez, Gabriel R; Vargas, Edward D

2017-01-01

Within the growing literature seeking to understand civic and political engagement among racial and ethnic minorities, our understanding of political behavior among American Indian and Alaska Native's (AI/AN) remains limited. We use the Current Population Survey Civic Engagement and Voting and Registration supplements (2006-2012) to compare AI/AN voter registration, voting, and overall civic engagement to other racial and ethnic groups and to assess whether factors that predict higher levels of civic engagement vary across these populations. We find a few key socio-economic status indicators that predict civic and political engagement uniquely for AI/ANs, but they are not consistently significant across all years or all types of political participation. We find marital status, age, household size, education, and veteran status to be important in predicting civic engagement for AI/ANs. However, for voting and registration, we find that family income, age, marital status, household size, and residential stability to be important contributors. Although we find AI/ANs are less likely to register and vote compared to non-Hispanic whites, we find that the difference is not statistically significant in congressional years, which may suggest that AI/ANs are engaged in local politics and vote for representatives that will represent their tribal interests in national politics.

The significance of eosinophils in predicting the severity of acute ischemic stroke

PubMed Central

Wang, Jun; Ma, Li; Lin, Tao; Li, Shi-Jing; Chen, Lei-Lei; Wang, De-Zhao

2017-01-01

Background Previous studies have shown that tumor-associated tissue eosinophilia have a role in various types of solid tumors. However, the relationship between eosinophil and acute ischemic stroke (AIS) is unclear. We aimed to investigate the diagnostic significance of eosinophil in AIS patients. Methods This study included 300 AIS patients without hypereosinophilic syndrome (HES). The hematologic indices were collected from each patient, including white blood count, eosinophil count, eosinophil percentage, neutrophil count, red blood count, and platelet. The severity of AIS was estimated by national institute of health stroke scale (NIHSS). Logistic regression analyses were performed to confirm the biomarkers for NIHSS and in-hospital non-death among the cases. Moreover, receiver-operating characteristics (ROC) analyses were used to investigate the clinical performances of eosinophils and NIHSS in prediction of non-death. Results The admission NIHSS (P<0.001) and BMI (P<0.001) were predictors to the non-death of the patients. There was a significant correlation between eosinophil counts or eosinophil percentage and NIHSS score (r= -0.451, P < 0.001; r= -0.617, P<0.001, Spearson Correlation). ROC analysis showed that eosinophil counts and eosinophil percentage could predict non-death of the patients in-hospital, with the areas under the curves (AUC) of 0.791 and 0.867, respectively. Conclusions Our study revealed a relationship between eosinophil and NIHSS score in the patients with AIS. Eosinophils might have certain value for predicting the severity of AIS. PMID:29262636

Heart rate turbulence predicts ICD-resistant mortality in ischaemic heart disease.

PubMed

Marynissen, Thomas; Floré, Vincent; Heidbuchel, Hein; Nuyens, Dieter; Ector, Joris; Willems, Rik

2014-07-01

In high-risk patients, implantable cardioverter-defibrillators (ICDs) can convert the mode of death from arrhythmic to pump failure death. Therefore, we introduced the concept of 'ICD-resistant mortality' (IRM), defined as death (a) without previous appropriate ICD intervention (AI), (b) within 1 month after the first AI, or (c) within 1 year after the initial ICD implantation. Implantable cardioverter-defibrillator implantation in patients with a high risk of IRM should be avoided. Implantable cardioverter-defibrillator patients with ischaemic heart disease were included if a digitized 24 h Holter was available pre-implantation. Demographic, electrocardiographic, echocardiographic, and 24 h Holter risk factors were collected at device implantation. The primary endpoint was IRM. Cox regression analyses were used to test the association between predictors and outcome. We included 130 patients, with a mean left ventricular ejection fraction (LVEF) of 33.6 ± 10.3%. During a follow-up of 52 ± 31 months, 33 patients died. There were 21 cases of IRM. Heart rate turbulence (HRT) was the only Holter parameter associated with IRM and total mortality. A higher New York Heart Association (NYHA) class and a lower body mass index were the strongest predictors of IRM. Left ventricular ejection fraction predicted IRM on univariate analysis, and was the strongest predictor of total mortality. The only parameter that predicted AI was non-sustained ventricular tachycardia. Implantable cardioverter-defibrillator implantation based on NYHA class and LVEF leads to selection of patients with a higher risk of IRM and death. Heart rate turbulence may have added value for the identification of poor candidates for ICD therapy. Available Holter parameters seem limited in their ability to predict AI. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2013. For permissions please email: journals.permissions@oup.com.

Development and Validation of the Alcohol Identity Implicit Associations Test (AI-IAT)

PubMed Central

Gray, Heather M.; LaPlante, Debi A.; Bannon, Brittany L.; Ambady, Nalini; Shaffer, Howard J.

2011-01-01

Alcohol identity is the extent to which an individual perceives drinking alcohol to be a defining characteristic of his or her self-identity. Although alcohol identity might play an important role in risky college drinking practices, there is currently no easily administered, implicit measure of this concept. Therefore we developed a computerized implicit measure of alcohol identity (the Alcohol Identity Implicit Associations Test; AI-IAT) and assessed its reliability and predictive validity in relation to risky college drinking practices. One hundred forty-one college students completed the AI-IAT. Again 3- and 6-months later, we administered the AI-IAT and indices of engagement in risky college drinking practices. A subset of participants also completed the previously-validated implicit measure of alcohol identity. Scores on the AI-IAT were stable over time, internally consistent, and positively correlated with the previously-validated measure of alcohol identity. Baseline AI-IAT scores predicted future engagement in risky college drinking practices, even after controlling for standard alcohol consumption measures. We conclude that the AI-IAT reliably measures alcohol identity, a concept that appears to play an important role in risky college drinking practices. PMID:21621924

Pharmaceutical management through environmental product labeling in Sweden.

PubMed

Wennmalm, Ake; Gunnarsson, Bo

2009-07-01

There is an increased awareness that medicinal products for human use may cause negative effects in the environment. In Sweden a voluntary environmental classification system for drugs has been established in collaboration between producers, authorities and the public health care, and used for five years. The idea is to enhance the market demand for medicines with less environmental impact, which in turn will stimulate the producers to design future medicines to be more environmentally friendly. The system is open to the public and based on assessment of the active ingredient in the medicinal product into several classes of risk and hazard, respectively. It is closely related to the EMEA guidelines. Risk is expressed as the ratio between the predicted environmental concentration (PEC) of the active ingredient (AI) and its predicted no effect concentration (PNEC). The hazard is expressed in terms of the AI's persistence, potential to bioaccumulation, and eco-toxicity. Drug data for the classification are delivered by the respective producers. Hitherto more than 300 AI, representing more than 50% of the Swedish volume of drug use, have been classified. Data for risk assessment were missing in 47% of AI. Among drugs with data 7% had a PEC/PNEC ratio >1, and another 7% had a ratio between 0.1 and 1. The AIs with highest ratio (>10) were two estrogens. Data for hazard assessment were lacking in 16% of the AI. Among drugs with environmental data 92% were not ready biodegradable, 23% had potential to bioaccumulation, and 61% were toxic to aquatic organisms at a concentration below 1 mg/l. These data are utilized by regional pharmaceutical expert groups when selecting substances to be recommended in public health care in Sweden. They may also be used by prescribing doctors who want to identify the environmentally most favourable substance among several with equivalent medical effect. We conclude that environmental data on human medicinal products are often missing, or reveal unfavourable environmental properties. A proper judgement of the environmental impact of an AI requires a joint evaluation of its risk and hazard. We suggest that the pharmaceutical producers should highlight environmental precaution when designing new AIs, and that the environmental data should be transparent to the general public.

[Predictive quality of the injury severity score in the systematic use of cranial MRI].

PubMed

Woischneck, D; Lerch, K; Kapapa, T; Skalej, M; Firsching, R

2010-09-01

The ABBREVIATED INJURY SCORE (AIS) for the head is mostly coded on the basis of cranial computed tomography (CT). It defines, to a large extent, the predictive potency of the INJURY SEVERITY SCORE (ISS). The present study investigates whether the predictive capacity of the ISS can be improved by the systematic use of data from cranial MRI. 167 patients, who had been in a coma for at least 24 hours following trauma, underwent an MRI examination within 8 days. All had been found to have an intracranial injury on initial CT. 49 % had also suffered extracranial injuries. The GLASGOW OUTCOME SCALE (GOS) was determined 6 months post trauma. AIS, ISS and GOS values were rated as ordinal measurements. A contingency table was used as the statistical method of analysis, with a significance assumed as p < 0.05 (Chi (2) test). The median ISS based on CT was 16 and did not correlate with the GOS. 63 % of the patients revealed brain stem lesions on MRI. If these were coded with an AIS of 5, the median ISS increased significantly to 29. Thus, the correlation to the GOS was now significant. At ISS scores of 5-9, 18 % of the patients died; at scores of 50-54 the rate of favourable treatment outcomes still amounted to 50 %. Since it is now known that brain stem lesions can also have a favourable prognosis, the AIS coding was modified and adapted to the mortality of the singular types of lesion. Hence the median ISS again decreased to 16. The correlation to the GOS was significant, and the predictive potency of the ISS further improved. The prognostic potency of the REVISED INJURY SEVERITY CLASSIFICATION (RISC) score was improved by use of adapted MRI data. If visible brain stem lesions on MRI were coded according to the AIS guidelines, there was a significant increase in the ISS which correlated significantly to the GOS. If the AIS coding was adjusted to the prognostic significance of individual brain stem lesions, there was a further improvement in the prognostic potency of the ISS. The study encourages the inclusion of data obtained from MRI diagnostics in the ISS calculation. There are alternative ways. © Georg Thieme Verlag KG Stuttgart · New York.

Diagnostic accuracy and reproducibility of pleural and lung ultrasound in discriminating cardiogenic causes of acute dyspnea in the emergency department.

PubMed

Cibinel, Gian Alfonso; Casoli, Giovanna; Elia, Fabrizio; Padoan, Monica; Pivetta, Emanuele; Lupia, Enrico; Goffi, Alberto

2012-02-01

Dyspnea is a common symptom in patients admitted to the Emergency Department (ED), and discriminating between cardiogenic and non-cardiogenic dyspnea is often a clinical dilemma. The initial diagnostic work-up may be inaccurate in defining the etiology and the underlying pathophysiology. The aim of this study was to evaluate the diagnostic accuracy and reproducibility of pleural and lung ultrasound (PLUS), performed by emergency physicians at the time of a patient's initial evaluation in the ED, in identifying cardiac causes of acute dyspnea. Between February and July 2007, 56 patients presenting to the ED with acute dyspnea were prospectively enrolled in this study. In all patients, PLUS was performed by emergency physicians with the purpose of identifying the presence of diffuse alveolar-interstitial syndrome (AIS) or pleural effusion. All scans were later reviewed by two other emergency physicians, expert in PLUS and blinded to clinical parameters, who were the ultimate judges of positivity for diffuse AIS and pleural effusion. A random set of 80 recorded scannings were also reviewed by two inexperienced observers to assess inter-observer variability. The entire medical record was independently reviewed by two expert physicians (an emergency medicine physician and a cardiologist) blinded to the ultrasound (US) results, in order to determine whether, for each patient, dyspnea was due to heart failure, or not. Sensitivity, specificity, and positive/negative predictive values were obtained; likelihood ratio (LR) test was used. Cohen's kappa was used to assess inter-observer agreement. The presence of diffuse AIS was highly predictive for cardiogenic dyspnea (sensitivity 93.6%, specificity 84%, positive predictive value 87.9%, negative predictive value 91.3%). On the contrary, US detection of pleural effusion was not helpful in the differential diagnosis (sensitivity 83.9%, specificity 52%, positive predictive value 68.4%, negative predictive value 72.2%). Finally, the coexistence of diffuse AIS and pleural effusion is less accurate than diffuse AIS alone for cardiogenic dyspnea (sensitivity 81.5%, specificity 82.8%, positive predictive value 81.5%, negative predictive value 82.8%). The positive LR was 5.8 for AIS [95% confidence interval (CI) 4.8-7.1] and 1.7 (95% CI 1.2-2.6) for pleural effusion, negative LR resulted 0.1 (95% CI 0.0-0.4) for AIS and 0.3 (95% CI 0.1-0.8) for pleural effusion. Agreement between experienced and inexperienced operators was 92.2% (p < 0.01) and 95% (p < 0.01) for diagnosis of AIS and pleural effusion, respectively. In early evaluation of patients presenting to the ED with dyspnea, PLUS, performed with the purpose of identifying diffuse AIS, may represent an accurate and reproducible bedside tool in discriminating between cardiogenic and non-cardiogenic dyspnea. On the contrary, US detection of pleural effusions does not allow reliable discrimination between different causes of acute dyspnea in unselected ED patients.

Mortality prediction of head Abbreviated Injury Score and Glasgow Coma Scale: analysis of 7,764 head injuries.

PubMed

Demetriades, Demetrios; Kuncir, Eric; Murray, James; Velmahos, George C; Rhee, Peter; Chan, Linda

2004-08-01

We assessed the prognostic value and limitations of Glasgow Coma Scale (GCS) and head Abbreviated Injury Score (AIS) and correlated head AIS with GCS. We studied 7,764 patients with head injuries. Bivariate analysis was performed to examine the relationship of GCS, head AIS, age, gender, and mechanism of injury with mortality. Stepwise logistic regression analysis was used to identify the independent risk factors associated with mortality. The overall mortality in the group of head injury patients with no other major extracranial injuries and no hypotension on admission was 9.3%. Logistic regression analysis identified head AIS, GCS, age, and mechanism of injury as significant independent risk factors of death. The prognostic value of GCS and head AIS was significantly affected by the mechanism of injury and the age of the patient. Patients with similar GCS or head AIS but different mechanisms of injury or ages had significantly different outcomes. The adjusted odds ratio of death in penetrating trauma was 5.2 (3.9, 7.0), p < 0.0001, and in the age group > or = 55 years the adjusted odds ratio was 3.4 (2.6, 4.6), p < 0.0001. There was no correlation between head AIS and GCS (correlation coefficient -0.31). Mechanism of injury and age have a major effect in the predictive value of GCS and head AIS. There is no good correlation between GCS and head AIS.

Accuracy and Calibration of High Explosive Thermodynamic Equations of State

DTIC Science & Technology

2010-08-01

physics descriptions, but can also mean increased calibration complexity. A generalized extent of aluminum reaction, the Jones-Wilkins-Lee ( JWL ) based...predictions compared to experiments 3 3 PAX-30 JWL and JWLB cylinder test predictions compared to experiments 4 4 PAX-29 JWL and JWLB cylinder test...predictions compared to experiments 5 5 Experiment and modeling comparisons for HMX/AI 85/15 7 TABLES 1 LX-14 JWL and JWLB cylinder test velocity

A modified artificial immune system based pattern recognition approach -- an application to clinic diagnostics

PubMed Central

Zhao, Weixiang; Davis, Cristina E.

2011-01-01

Objective This paper introduces a modified artificial immune system (AIS)-based pattern recognition method to enhance the recognition ability of the existing conventional AIS-based classification approach and demonstrates the superiority of the proposed new AIS-based method via two case studies of breast cancer diagnosis. Methods and materials Conventionally, the AIS approach is often coupled with the k nearest neighbor (k-NN) algorithm to form a classification method called AIS-kNN. In this paper we discuss the basic principle and possible problems of this conventional approach, and propose a new approach where AIS is integrated with the radial basis function – partial least square regression (AIS-RBFPLS). Additionally, both the two AIS-based approaches are compared with two classical and powerful machine learning methods, back-propagation neural network (BPNN) and orthogonal radial basis function network (Ortho-RBF network). Results The diagnosis results show that: (1) both the AIS-kNN and the AIS-RBFPLS proved to be a good machine leaning method for clinical diagnosis, but the proposed AIS-RBFPLS generated an even lower misclassification ratio, especially in the cases where the conventional AIS-kNN approach generated poor classification results because of possible improper AIS parameters. For example, based upon the AIS memory cells of “replacement threshold = 0.3”, the average misclassification ratios of two approaches for study 1 are 3.36% (AIS-RBFPLS) and 9.07% (AIS-kNN), and the misclassification ratios for study 2 are 19.18% (AIS-RBFPLS) and 28.36% (AIS-kNN); (2) the proposed AIS-RBFPLS presented its robustness in terms of the AIS-created memory cells, showing a smaller standard deviation of the results from the multiple trials than AIS-kNN. For example, using the result from the first set of AIS memory cells as an example, the standard deviations of the misclassification ratios for study 1 are 0.45% (AIS-RBFPLS) and 8.71% (AIS-kNN) and those for study 2 are 0.49% (AIS-RBFPLS) and 6.61% (AIS-kNN); and (3) the proposed AIS-RBFPLS classification approaches also yielded better diagnosis results than two classical neural network approaches of BPNN and Ortho-RBF network. Conclusion In summary, this paper proposed a new machine learning method for complex systems by integrating the AIS system with RBFPLS. This new method demonstrates its satisfactory effect on classification accuracy for clinical diagnosis, and also indicates its wide potential applications to other diagnosis and detection problems. PMID:21515033

Providing culturally competent services for American Indian and Alaska Native veterans to reduce health care disparities.

PubMed

Noe, Timothy D; Kaufman, Carol E; Kaufmann, L Jeanne; Brooks, Elizabeth; Shore, Jay H

2014-09-01

We conducted an exploratory study to determine what organizational characteristics predict the provision of culturally competent services for American Indian and Alaska Native (AI/AN) veterans in Department of Veterans Affairs (VA) health facilities. In 2011 to 2012, we adapted the Organizational Readiness to Change Assessment (ORCA) for a survey of 27 VA facilities in the Western Region to assess organizational readiness and capacity to adopt and implement native-specific services and to profile the availability of AI/AN veteran programs and interest in and resources for such programs. Several ORCA subscales (Program Needs, Leader's Practices, and Communication) statistically significantly predicted whether VA staff perceived that their facilities were meeting the needs of AI/AN veterans. However, none predicted greater implementation of native-specific services. Our findings may aid in developing strategies for adopting and implementing promising native-specific programs and services for AI/AN veterans, and may be generalizable for other veteran groups.

Providing Culturally Competent Services for American Indian and Alaska Native Veterans to Reduce Health Care Disparities

PubMed Central

Kaufman, Carol E.; Kaufmann, L. Jeanne; Brooks, Elizabeth; Shore, Jay H.

2014-01-01

Objectives. We conducted an exploratory study to determine what organizational characteristics predict the provision of culturally competent services for American Indian and Alaska Native (AI/AN) veterans in Department of Veterans Affairs (VA) health facilities. Methods. In 2011 to 2012, we adapted the Organizational Readiness to Change Assessment (ORCA) for a survey of 27 VA facilities in the Western Region to assess organizational readiness and capacity to adopt and implement native-specific services and to profile the availability of AI/AN veteran programs and interest in and resources for such programs. Results. Several ORCA subscales (Program Needs, Leader’s Practices, and Communication) statistically significantly predicted whether VA staff perceived that their facilities were meeting the needs of AI/AN veterans. However, none predicted greater implementation of native-specific services. Conclusions. Our findings may aid in developing strategies for adopting and implementing promising native-specific programs and services for AI/AN veterans, and may be generalizable for other veteran groups. PMID:25100420

Artificial intelligence in hematology.

PubMed

Zini, Gina

2005-10-01

Artificial intelligence (AI) is a computer based science which aims to simulate human brain faculties using a computational system. A brief history of this new science goes from the creation of the first artificial neuron in 1943 to the first artificial neural network application to genetic algorithms. The potential for a similar technology in medicine has immediately been identified by scientists and researchers. The possibility to store and process all medical knowledge has made this technology very attractive to assist or even surpass clinicians in reaching a diagnosis. Applications of AI in medicine include devices applied to clinical diagnosis in neurology and cardiopulmonary diseases, as well as the use of expert or knowledge-based systems in routine clinical use for diagnosis, therapeutic management and for prognostic evaluation. Biological applications include genome sequencing or DNA gene expression microarrays, modeling gene networks, analysis and clustering of gene expression data, pattern recognition in DNA and proteins, protein structure prediction. In the field of hematology the first devices based on AI have been applied to the routine laboratory data management. New tools concern the differential diagnosis in specific diseases such as anemias, thalassemias and leukemias, based on neural networks trained with data from peripheral blood analysis. A revolution in cancer diagnosis, including the diagnosis of hematological malignancies, has been the introduction of the first microarray based and bioinformatic approach for molecular diagnosis: a systematic approach based on the monitoring of simultaneous expression of thousands of genes using DNA microarray, independently of previous biological knowledge, analysed using AI devices. Using gene profiling, the traditional diagnostic pathways move from clinical to molecular based diagnostic systems.

Long-range AIS message analysis based on the TianTuo-3 micro satellite

NASA Astrophysics Data System (ADS)

Li, Shiyou; Chen, Lihu; Chen, Xiaoqian; Zhao, Yong; Bai, Yuzhu

2017-07-01

The "Type-27 AIS message" is the long-range AIS broadcast message, which is primarily intended for the long-range detection of AIS typically by satellite. The TT3-AIS uses a four-frequency receiver scheme which includes two frequency channels conventionally applied by the AIS system and two new frequency channels allocated to the long-range AIS broadcast message. To the end of April 2016, the TT3-AIS has already received more than 11,400 packets of Type-27 AIS messages. In this paper, a detailed analysis of the Type-27 AIS messages is performed. Firstly, an eavesdropper diagram of the space-borne AIS received from the worldwide vessels is obtained. Secondly, the analysis to the trend of the number and the ratio of the new-type vessels is performed based on the Type-27 AIS message. The detection probability of the new-type vessels is also discussed. The result would be helpful on the usage of the long-range AIS message both for data application and for the improvement in designing the next space-based AIS receiver.

Estimating the Accuracy of the Chedoke-McMaster Stroke Assessment Predictive Equations for Stroke Rehabilitation.

PubMed

Dang, Mia; Ramsaran, Kalinda D; Street, Melissa E; Syed, S Noreen; Barclay-Goddard, Ruth; Stratford, Paul W; Miller, Patricia A

2011-01-01

To estimate the predictive accuracy and clinical usefulness of the Chedoke-McMaster Stroke Assessment (CMSA) predictive equations. A longitudinal prognostic study using historical data obtained from 104 patients admitted post cerebrovascular accident was undertaken. Data were abstracted for all patients undergoing rehabilitation post stroke who also had documented admission and discharge CMSA scores. Published predictive equations were used to determine predicted outcomes. To determine the accuracy and clinical usefulness of the predictive model, shrinkage coefficients and predictions with 95% confidence bands were calculated. Complete data were available for 74 patients with a mean age of 65.3±12.4 years. The shrinkage values for the six Impairment Inventory (II) dimensions varied from -0.05 to 0.09; the shrinkage value for the Activity Inventory (AI) was 0.21. The error associated with predictive values was greater than ±1.5 stages for the II dimensions and greater than ±24 points for the AI. This study shows that the large error associated with the predictions (as defined by the confidence band) for the CMSA II and AI limits their clinical usefulness as a predictive measure. Further research to establish predictive models using alternative statistical procedures is warranted.

Mortality Risk in Pediatric Motor Vehicle Crash Occupants: Accounting for Developmental Stage and Challenging Abbreviated Injury Scale Metrics.

PubMed

Doud, Andrea N; Weaver, Ashley A; Talton, Jennifer W; Barnard, Ryan T; Schoell, Samantha L; Petty, John K; Stitzel, Joel D

2015-01-01

Survival risk ratios (SRRs) and their probabilistic counterpart, mortality risk ratios (MRRs), have been shown to be at odds with Abbreviated Injury Scale (AIS) severity scores for particular injuries in adults. SRRs have been validated for pediatrics but have not been studied within the context of pediatric age stratifications. We hypothesized that children with similar motor vehicle crash (MVC) injuries may have different mortality risks (MR) based upon developmental stage and that these MRs may not correlate with AIS severity. The NASS-CDS 2000-2011 was used to define the top 95% most common AIS 2+ injuries among MVC occupants in 4 age groups: 0-4, 5-9, 10-14, and 15-18 years. Next, the National Trauma Databank 2002-2011 was used to calculate the MR (proportion of those dying with an injury to those sustaining the injury) and the co-injury-adjusted MR (MRMAIS) for each injury within 6 age groups: 0-4, 5-9, 10-14, 15-18, 0-18, and 19+ years. MR differences were evaluated between age groups aggregately, between age groups based upon anatomic injury patterns and between age groups on an individual injury level using nonparametric Wilcoxon tests and chi-square or Fisher's exact tests as appropriate. Correlation between AIS and MR within each age group was also evaluated. MR and MRMAIS distributions of the most common AIS 2+ injuries were right skewed. Aggregate MR of these most common injuries varied between the age groups, with 5- to 9-year-old and 10- to 14-year-old children having the lowest MRs and 0- to 4-year-old and 15- to 18-year-old children and adults having the highest MRs (all P <.05). Head and thoracic injuries imparted the greatest mortality risk in all age groups with median MRMAIS ranging from 0 to 6% and 0 to 4.5%, respectively. Injuries to particular body regions also varied with respect to MR based upon age. For example, thoracic injuries in adults had significantly higher MRMAIS than such injuries among 5- to 9-year-olds and 10- to 14-year-olds (P =.04; P <.01). Furthermore, though AIS was positively correlated with MR within each age group, less correlation was seen for children than for adults. Large MR variations were seen within each AIS grade, with some lower AIS severity injuries demonstrating greater MRs than higher AIS severity injuries. As an example, MRMAIS in 0- to 18-year-olds was 0.4% for an AIS 3 radius fracture versus 1.4% for an AIS 2 vault fracture. Trauma severity metrics are important for outcome prediction models and can be used in pediatric triage algorithms and other injury research. Trauma severity may vary for similar injuries based upon developmental stage, and this difference should be reflected in severity metrics. The MR-based data-driven determination of injury severity in pediatric occupants of different age cohorts provides a supplement or an alternative to AIS severity classification for pediatric occupants in MVCs.

Artificial intelligence in healthcare: past, present and future.

PubMed

Jiang, Fei; Jiang, Yong; Zhi, Hui; Dong, Yi; Li, Hao; Ma, Sufeng; Wang, Yilong; Dong, Qiang; Shen, Haipeng; Wang, Yongjun

2017-12-01

Artificial intelligence (AI) aims to mimic human cognitive functions. It is bringing a paradigm shift to healthcare, powered by increasing availability of healthcare data and rapid progress of analytics techniques. We survey the current status of AI applications in healthcare and discuss its future. AI can be applied to various types of healthcare data (structured and unstructured). Popular AI techniques include machine learning methods for structured data, such as the classical support vector machine and neural network, and the modern deep learning, as well as natural language processing for unstructured data. Major disease areas that use AI tools include cancer, neurology and cardiology. We then review in more details the AI applications in stroke, in the three major areas of early detection and diagnosis, treatment, as well as outcome prediction and prognosis evaluation. We conclude with discussion about pioneer AI systems, such as IBM Watson, and hurdles for real-life deployment of AI.

Artificial intelligence in healthcare: past, present and future

PubMed Central

Jiang, Fei; Jiang, Yong; Zhi, Hui; Dong, Yi; Li, Hao; Ma, Sufeng; Wang, Yilong; Dong, Qiang; Shen, Haipeng; Wang, Yongjun

2017-01-01

Artificial intelligence (AI) aims to mimic human cognitive functions. It is bringing a paradigm shift to healthcare, powered by increasing availability of healthcare data and rapid progress of analytics techniques. We survey the current status of AI applications in healthcare and discuss its future. AI can be applied to various types of healthcare data (structured and unstructured). Popular AI techniques include machine learning methods for structured data, such as the classical support vector machine and neural network, and the modern deep learning, as well as natural language processing for unstructured data. Major disease areas that use AI tools include cancer, neurology and cardiology. We then review in more details the AI applications in stroke, in the three major areas of early detection and diagnosis, treatment, as well as outcome prediction and prognosis evaluation. We conclude with discussion about pioneer AI systems, such as IBM Watson, and hurdles for real-life deployment of AI. PMID:29507784

How Is Pulmonary Function and Exercise Tolerance Affected in Patients With AIS Who Have Undergone Spinal Fusion?

PubMed

Jeans, Kelly A; Lovejoy, John F; Karol, Lori A; McClung, Anna M

2017-11-01

Prospectively enrolled AIS patients who underwent spinal fusion, with 2 year follow-up. To evaluate the cardiovascular fitness and activity level in patients with AIS pre- and post-spinal fusion and to determine if initial curve magnitude or pulmonary function is predictive of exercise capacity. Researchers have tried to link pulmonary function testing (PFT) to exercise capacity; the results are mixed. Some report no improvement in PFTs or aerobic activity after surgical correction, and PFT measures were not predictive of exercise capacity. Conflicting results have shown Vo 2max results to fall within normal range in AIS patients while PFTs show minimal impairment. AIS patients underwent PFT and oxygen consumption (VO 2 ) testing during a submaximal graded exercise test (GXT) pre- and post-spinal fusion. Vo 2max was predicted in those patients who completed the test to 85% of maximal heart rate. Pre- to postoperative changes were assessed and then compared to age-matched control subjects. Correlations between Vo 2max and curve severity, pulmonary function, and activity level were assessed. Thirty-seven patients participated. Vo 2max was predicted in 23 patients pre- and postoperation. There was a significant reduction in Vo 2max postfusion (39.5 ± 6.5 mL/kg/min vs 42.1 ± 8.1 mL/kg/min, p = .033); however, compared with controls (40.5 ± 6.5 mL/kg/min), all data were within the normal range (p > .05). AIS patients reporting high activity had significantly greater Vo 2max than those reporting low activity both pre and postoperatively, but this difference only met statistical significance preop (p < .05). Curve magnitude and PFT measures were not found to correlate with Vo 2max (p > .05). Vo 2max in patients with AIS is within normal range both pre- and postfusion. Pulmonary limitations are accommodated for with a slightly increased breathing rate and a slightly reduced overall workload. Activity level rather than curve severity affects Vo 2max outcomes following fusion in AIS. Copyright © 2017 Scoliosis Research Society. Published by Elsevier Inc. All rights reserved.

Modeling river total bed material load discharge using artificial intelligence approaches (based on conceptual inputs)

NASA Astrophysics Data System (ADS)

Roushangar, Kiyoumars; Mehrabani, Fatemeh Vojoudi; Shiri, Jalal

2014-06-01

This study presents Artificial Intelligence (AI)-based modeling of total bed material load through developing the accuracy level of the predictions of traditional models. Gene expression programming (GEP) and adaptive neuro-fuzzy inference system (ANFIS)-based models were developed and validated for estimations. Sediment data from Qotur River (Northwestern Iran) were used for developing and validation of the applied techniques. In order to assess the applied techniques in relation to traditional models, stream power-based and shear stress-based physical models were also applied in the studied case. The obtained results reveal that developed AI-based models using minimum number of dominant factors, give more accurate results than the other applied models. Nonetheless, it was revealed that k-fold test is a practical but high-cost technique for complete scanning of applied data and avoiding the over-fitting.

Blunt Cardiac Injury in the Severely Injured – A Retrospective Multicentre Study

PubMed Central

Hanschen, Marc; Kanz, Karl-Georg; Kirchhoff, Chlodwig; Khalil, Philipe N.; Wierer, Matthias; van Griensven, Martijn; Laugwitz, Karl-Ludwig; Biberthaler, Peter; Lefering, Rolf; Huber-Wagner, Stefan

2015-01-01

Background Blunt cardiac injury is a rare trauma entity. Here, we sought to evaluate the relevance and prognostic significance of blunt cardiac injury in severely injured patients. Methods In a retrospective multicentre study, using data collected from 47,580 patients enrolled to TraumaRegister DGU (1993-2009), characteristics of trauma, prehospital / hospital trauma management, and outcome analysis were correlated to the severity of blunt cardiac injury. The severity of cardiac injury was assessed according to the abbreviated injury score (AIS score 1-6), the revised injury severity score (RISC) allowed comparison of expected outcome with injury severity-dependent outcome. N = 1.090 had blunt cardiac trauma (AIS 1-6) (2.3% of patients). Results Predictors of blunt cardiac injury could be identified. Sternal fractures indicate a high risk of the presence of blunt cardiac injury (AIS 0 [control]: 3.0%; AIS 1: 19.3%; AIS 2-6: 19.1%). The overall mortality rate was 13.9%, minor cardiac injury (AIS 1) and severe cardiac injury (AIS 2-6) are associated with higher rates. Severe blunt cardiac injury (AIS 4 and AIS 5-6) is associated with a higher mortality (OR 2.79 and 4.89, respectively) as compared to the predicted average mortality (OR 2.49) of the study collective. Conclusion Multiple injured patients with blunt cardiac trauma are at high risk to be underestimated. Careful evaluation of trauma patients is able to predict the presence of blunt cardiac injury. The severity of blunt cardiac injury needs to be stratified according to the AIS score, as the patients’ outcome is dependent on the severity of cardiac injury. PMID:26136126

Acute Ischemic Stroke After Moderate to Severe Traumatic Brain Injury: Incidence and Impact on Outcome.

PubMed

Kowalski, Robert G; Haarbauer-Krupa, Juliet K; Bell, Jeneita M; Corrigan, John D; Hammond, Flora M; Torbey, Michel T; Hofmann, Melissa C; Dams-O'Connor, Kristen; Miller, A Cate; Whiteneck, Gale G

2017-07-01

Traumatic brain injury (TBI) leads to nearly 300 000 annual US hospitalizations and increased lifetime risk of acute ischemic stroke (AIS). Occurrence of AIS immediately after TBI has not been well characterized. We evaluated AIS acutely after TBI and its impact on outcome. A prospective database of moderate to severe TBI survivors, admitted to inpatient rehabilitation at 22 Traumatic Brain Injury Model Systems centers and their referring acute-care hospitals, was analyzed. Outcome measures were AIS incidence, duration of posttraumatic amnesia, Functional Independence Measure, and Disability Rating Scale, at rehabilitation discharge. Between October 1, 2007, and March 31, 2015, 6488 patients with TBI were enrolled in the Traumatic Brain Injury Model Systems National Database. One hundred and fifty-nine (2.5%) patients had a concurrent AIS, and among these, median age was 40 years. AIS was associated with intracranial mass effect and carotid or vertebral artery dissection. High-velocity events more commonly caused TBI with dissection. AIS predicted poorer outcome by all measures, accounting for a 13.3-point reduction in Functional Independence Measure total score (95% confidence interval, -16.8 to -9.7; P <0.001), a 1.9-point increase in Disability Rating Scale (95% confidence interval, 1.3-2.5; P <0.001), and an 18.3-day increase in posttraumatic amnesia duration (95% confidence interval, 13.1-23.4; P <0.001). Ischemic stroke is observed acutely in 2.5% of moderate to severe TBI survivors and predicts worse functional and cognitive outcome. Half of TBI patients with AIS were aged ≤40 years, and AIS patients more often had cervical dissection. Vigilance for AIS is warranted acutely after TBI, particularly after high-velocity events. © 2017 American Heart Association, Inc.

A Novel Framework for Characterizing Exposure-Related ...

EPA Pesticide Factsheets

Descriptions of where and how individuals spend their time are important for characterizing exposures to chemicals in consumer products and in indoor environments. Herein we create an agent-based model (ABM) that is able to simulate longitudinal patterns in behaviors. By basing our ABM upon a needs-based artificial intelligence (AI) system, we create agents that mimic human decisions on these exposure-relevant behaviors. In a case study of adults, we use the AI to predict the inter-individual variation in the start time and duration of four behaviors: sleeping, eating, commuting, and working. The results demonstrate that the ABM can capture both inter-individual variation and how decisions on one behavior can affect subsequent behaviors. Preset NERL's research on the use of agent based modeling in exposure assessments. To obtain feed back on the approach from the leading experts in the field.

Decadal climate prediction with a refined anomaly initialisation approach

NASA Astrophysics Data System (ADS)

Volpi, Danila; Guemas, Virginie; Doblas-Reyes, Francisco J.; Hawkins, Ed; Nichols, Nancy K.

2017-03-01

In decadal prediction, the objective is to exploit both the sources of predictability from the external radiative forcings and from the internal variability to provide the best possible climate information for the next decade. Predicting the climate system internal variability relies on initialising the climate model from observational estimates. We present a refined method of anomaly initialisation (AI) applied to the ocean and sea ice components of the global climate forecast model EC-Earth, with the following key innovations: (1) the use of a weight applied to the observed anomalies, in order to avoid the risk of introducing anomalies recorded in the observed climate, whose amplitude does not fit in the range of the internal variability generated by the model; (2) the AI of the ocean density, instead of calculating it from the anomaly initialised state of temperature and salinity. An experiment initialised with this refined AI method has been compared with a full field and standard AI experiment. Results show that the use of such refinements enhances the surface temperature skill over part of the North and South Atlantic, part of the South Pacific and the Mediterranean Sea for the first forecast year. However, part of such improvement is lost in the following forecast years. For the tropical Pacific surface temperature, the full field initialised experiment performs the best. The prediction of the Arctic sea-ice volume is improved by the refined AI method for the first three forecast years and the skill of the Atlantic multidecadal oscillation is significantly increased compared to a non-initialised forecast, along the whole forecast time.

Seismic lateral prediction in chalky limestone reservoirs offshore Qatar

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rubbens, I.B.H.M.; Murat, R.C.; Vankeulen, J.

Following the discovery of non-structurally trapped oil accumulations in Cretaceous chalky reservoirs on the northern flank of the North Dome offshore QATAR, a seismic lateral prediction study was carried out for QATAR GENERAL PETROLEUM CORPORATION (Offshore Operations). The objectives of this study were to assist in the appraisal of these oil accumulations by predicting their possible lateral extent and to investigate if the technique applied could be used as a basis for further exploration of similar oil prospects in the area. Wireline logs of eight wells and some 1000 km of high quality seismic data were processed into acoustic impedancemore » (A.I.) logs and seismic A.I. sections. Having obtained a satisfactory match of the A.I. well logs and the A.I. of the seismic traces at the well locations, relationships were established by the use of well log data which allowed the interpretation of the seismic A.I. in terms of reservoir quality. Measurements of the relevant A.I. characteristics were then carried out by computer along all seismic lines and porosity distribution maps prepared for some of the reservoirs. These maps, combined with detailed seismic depth contour maps at reservoir tops, lead to definition of good reservoir development areas downdip from poor reservoir quality zones i.e. of the stratigraphic trap areas, and drilling locations could thus be proposed. The system remains to be adequately calibrated when core material becomes available in the area of study.« less

Changing to AIS 2005 and agreement of injury severity scores in a trauma registry with scores based on manual chart review.

PubMed

Stewart, Kenneth E; Cowan, Linda D; Thompson, David M

2011-09-01

The Abbreviated Injury Scale (AIS) recently underwent a major revision from AIS 98 to AIS 05. AIS injury codes form the basis of widely used injury severity scores such as the injury severity score (ISS). ISS thresholds are often used in trauma case definitions and ISS is widely used in injury research to adjust for injury severity. This study evaluated changes from AIS 98 to AIS 05, the changes' effect on ISS distributions, and presents an application of the results. Injury descriptions from medical records of 137 randomly selected patients in the Oklahoma Trauma Registry (OTR) were obtained. A single trained coder used AIS 98 and AIS 05 to code each injury. ISS values were calculated and grouped into 4 categories: 1-8, 9-14, 16-24, >24. Paired ISS was compared using Kappa statistics and tests of symmetry. We identified common injury diagnoses for which AIS severity changed between versions. Estimates of the proportion of patients changing ISS groups were applied to the entire OTR to assess the impact on reporting and on a model for reimbursement. OTR AIS 98 and manual AIS 98-based ISS values had a weighted Kappa of 0.71. OTR AIS 98 and manual AIS 05-based ISS values had a Kappa of 0.58. Manual AIS 98 and manual AIS 05 ISS had the highest Kappa of 0.81, however, though the scores differed by only 1 ISS category, there were 30 discordant pairs. The distribution of these discordant pairs was not symmetrical (Bowker's S=30; df=6; p<0.0001) with AIS 05-based ISS values consistently shifted to a lower ISS category. Reductions in AIS severity and ISS values using AIS 05 were common for extremity fractures and thorax injuries. The results suggest fewer patients would be reported to the OTR or be eligible for reimbursement. Changing from AIS 98 to AIS 05 injury coding resulted in systematic changes in AIS codes and ISS. Specific injuries and body regions were differentially affected. Trauma registries and injury researchers that use AIS based injury coding can use this information to evaluate the potential impact of changes in AIS 2005. Copyright © 2010 Elsevier Ltd. All rights reserved.

AiResearch QCGAT engine: Acoustic test results

NASA Technical Reports Server (NTRS)

Kisner, L. S.

1980-01-01

The noise levels of the quiet, general aviation turbofan (QCGAT) engine were measured in ground static noise tests. The static noise levels were found to be markedly lower than the demonstrably quiet AiResearch model TFE731 engine. The measured QCGAT noise levels were correlated with analytical noise source predictions to derive free-field component noise predictions. These component noise sources were used to predict the QCGAT flyover noise levels at FAR Part 36 conditions. The predicted flyover noise levels are about 10 decibels lower than the current quietest business jets.

How feasible is the rapid development of artificial superintelligence?

NASA Astrophysics Data System (ADS)

Sotala, Kaj

2017-11-01

What kinds of fundamental limits are there in how capable artificial intelligence (AI) systems might become? Two questions in particular are of interest: (1) How much more capable could AI become relative to humans, and (2) how easily could superhuman capability be acquired? To answer these questions, we will consider the literature on human expertise and intelligence, discuss its relevance for AI, and consider how AI could improve on humans in two major aspects of thought and expertise, namely simulation and pattern recognition. We find that although there are very real limits to prediction, it seems like AI could still substantially improve on human intelligence.

Analysis of ESR1 mutation in circulating tumor DNA demonstrates evolution during therapy for metastatic breast cancer

PubMed Central

Schiavon, Gaia; Hrebien, Sarah; Garcia-Murillas, Isaac; Cutts, Rosalind J; Pearson, Alex; Tarazona, Noelia; Fenwick, Kerry; Kozarewa, Iwanka; Lopez-Knowles, Elena; Ribas, Ricardo; Nerurkar, Ashutosh; Osin, Peter; Chandarlapaty, Sarat; Martin, Lesley-Ann; Dowsett, Mitch; Smith, Ian E; Turner, Nicholas C.

2016-01-01

Acquired ESR1 mutations are a major mechanism of resistance to aromatase inhibitors (AI). We developed ultra-high sensitivity multiplexed digital PCR assays for ESR1 mutations in circulating tumor DNA (ctDNA) and used these to investigate the clinical relevance and origin of ESR1 mutations in a cohort of 171 women with advanced breast cancer. ESR1 mutation status in ctDNA showed high concordance with contemporaneous tumor biopsies, and could be assessed in samples shipped at room temperature in preservative tubes without loss of accuracy. ESR1 mutations were found exclusively in patients with estrogen receptor positive breast cancer previously exposed to AI. Patients with ESR1 mutations had a substantially shorter progression-free survival on subsequent AI-based therapy (HR 3.1, 95%CI 1.9-23.1, log rank p=0.0041). ESR1 mutation prevalence differed markedly between patients that were first exposed to AI during the adjuvant and metastatic settings (5.8% (3/52) vs 36.4% (16/44) respectively, p=0.0002). In an independent cohort, ESR1 mutations were identified in 0% (0/32, 95%CI 0-10.9%) tumor biopsies taken after progression on adjuvant AI. In a patient with serial samples taken during metastatic treatment, ESR1 mutation was selected during metastatic AI therapy, to become the dominant clone in the cancer. ESR1 mutations can be robustly identified with ctDNA analysis and predict for resistance to subsequent AI therapy. ESR1 mutations are rarely acquired during adjuvant AI therapy, but are commonly selected by therapy for metastatic disease, providing evidence that the mechanisms of resistance to targeted therapy may be substantially different between the treatment of micro-metastatic and overt metastatic cancer. PMID:26560360

Analysis of ESR1 mutation in circulating tumor DNA demonstrates evolution during therapy for metastatic breast cancer.

PubMed

Schiavon, Gaia; Hrebien, Sarah; Garcia-Murillas, Isaac; Cutts, Rosalind J; Pearson, Alex; Tarazona, Noelia; Fenwick, Kerry; Kozarewa, Iwanka; Lopez-Knowles, Elena; Ribas, Ricardo; Nerurkar, Ashutosh; Osin, Peter; Chandarlapaty, Sarat; Martin, Lesley-Ann; Dowsett, Mitch; Smith, Ian E; Turner, Nicholas C

2015-11-11

Acquired ESR1 mutations are a major mechanism of resistance to aromatase inhibitors (AIs). We developed ultra high-sensitivity multiplex digital polymerase chain reaction assays for ESR1 mutations in circulating tumor DNA (ctDNA) and investigated the clinical relevance and origin of ESR1 mutations in 171 women with advanced breast cancer. ESR1 mutation status in ctDNA showed high concordance with contemporaneous tumor biopsies and was accurately assessed in samples shipped at room temperature in preservative tubes. ESR1 mutations were found exclusively in estrogen receptor-positive breast cancer patients previously exposed to AI. Patients with ESR1 mutations had a substantially shorter progression-free survival on subsequent AI-based therapy [hazard ratio, 3.1; 95% confidence interval (CI), 1.9 to 23.1; P = 0.0041]. ESR1 mutation prevalence differed markedly between patients who were first exposed to AI during the adjuvant and metastatic settings [5.8% (3 of 52) versus 36.4% (16 of 44), respectively; P = 0.0002]. In an independent cohort, ESR1 mutations were identified in 0% (0 of 32; 95% CI, 0 to 10.9) tumor biopsies taken after progression on adjuvant AI. In a patient with serial sampling, ESR1 mutation was selected during metastatic AI therapy to become the dominant clone in the cancer. ESR1 mutations can be robustly identified with ctDNA analysis and predict for resistance to subsequent AI therapy. ESR1 mutations are rarely acquired during adjuvant AI but are commonly selected by therapy for metastatic disease, providing evidence that mechanisms of resistance to targeted therapy may be substantially different between the treatment of micrometastatic and overt metastatic cancer. Copyright © 2015, American Association for the Advancement of Science.

An auto-inhibitory helix in CTP:phosphocholine cytidylyltransferase hijacks the catalytic residue and constrains a pliable, domain-bridging helix pair

PubMed Central

Ramezanpour, Mohsen; Lee, Jaeyong; Taneva, Svetla G.; Tieleman, D. Peter; Cornell, Rosemary B.

2018-01-01

The activity of CTP:phosphocholine cytidylyltransferase (CCT), a key enzyme in phosphatidylcholine synthesis, is regulated by reversible interactions of a lipid-inducible amphipathic helix (domain M) with membrane phospholipids. When dissociated from membranes, a portion of the M domain functions as an auto-inhibitory (AI) element to suppress catalysis. The AI helix from each subunit binds to a pair of α helices (αE) that extend from the base of the catalytic dimer to create a four-helix bundle. The bound AI helices make intimate contact with loop L2, housing a key catalytic residue, Lys122. The impacts of the AI helix on active-site dynamics and positioning of Lys122 are unknown. Extensive MD simulations with and without the AI helix revealed that backbone carbonyl oxygens at the point of contact between the AI helix and loop L2 can entrap the Lys122 side chain, effectively competing with the substrate, CTP. In silico, removal of the AI helices dramatically increased αE dynamics at a predicted break in the middle of these helices, enabling them to splay apart and forge new contacts with loop L2. In vitro cross-linking confirmed the reorganization of the αE element upon membrane binding of the AI helix. Moreover, when αE bending was prevented by disulfide engineering, CCT activation by membrane binding was thwarted. These findings suggest a novel two-part auto-inhibitory mechanism for CCT involving capture of Lys122 and restraint of the pliable αE helices. We propose that membrane binding enables bending of the αE helices, bringing the active site closer to the membrane surface. PMID:29519816

A vessel noise budget for Admiralty Inlet, Puget Sound, Washington (USA).

PubMed

Bassett, Christopher; Polagye, Brian; Holt, Marla; Thomson, Jim

2012-12-01

One calendar year of Automatic Identification System (AIS) ship-traffic data was paired with hydrophone recordings to assess ambient noise in northern Admiralty Inlet, Puget Sound, WA (USA) and to quantify the contribution of vessel traffic. The study region included inland waters of the Salish Sea within a 20 km radius of the hydrophone deployment site. Spectra and hourly, daily, and monthly ambient noise statistics for unweighted broadband (0.02-30 kHz) and marine mammal, or M-weighted, sound pressure levels showed variability driven largely by vessel traffic. Over the calendar year, 1363 unique AIS transmitting vessels were recorded, with at least one AIS transmitting vessel present in the study area 90% of the time. A vessel noise budget was calculated for all vessels equipped with AIS transponders. Cargo ships were the largest contributor to the vessel noise budget, followed by tugs and passenger vessels. A simple model to predict received levels at the site based on an incoherent summation of noise from different vessels resulted in a cumulative probability density function of broadband sound pressure levels that shows good agreement with 85% of the temporal data.

In Silico Testing of an Artificial-Intelligence-Based Artificial Pancreas Designed for Use in the Intensive Care Unit Setting

PubMed Central

DeJournett, Leon; DeJournett, Jeremy

2016-01-01

Background: Effective glucose control in the intensive care unit (ICU) setting has the potential to decrease morbidity and mortality rates which should in turn lead to decreased health care expenditures. Current ICU-based glucose controllers are mathematically derived, and tend to be based on proportional integral derivative (PID) or model predictive control (MPC). Artificial intelligence (AI)–based closed loop glucose controllers may have the ability to achieve control that improves on the results achieved by either PID or MPC controllers. Method: We conducted an in silico analysis of an AI-based glucose controller designed for use in the ICU setting. This controller was tested using a mathematical model of the ICU patient’s glucose-insulin system. A total of 126 000 unique 5-day simulations were carried out, resulting in 107 million glucose values for analysis. Results: For the 7 control ranges tested, with a sensor error of ±10%, the following average results were achieved: (1) time in control range, 94.2%, (2) time in range 70-140 mg/dl, 97.8%, (3) time in hyperglycemic range (>140 mg/dl), 2.1%, and (4) time in hypoglycemic range (<70 mg/dl), 0.09%. In addition, the average coefficient of variation (CV) was 11.1%. Conclusions: This in silico study of an AI-based closed loop glucose controller shows that it may be able to improve on the results achieved by currently existing ICU-based PID/MPC controllers. If these results are confirmed in clinical testing, this AI-based controller could be used to create an artificial pancreas system for use in the ICU setting. PMID:27301982

In Silico Testing of an Artificial-Intelligence-Based Artificial Pancreas Designed for Use in the Intensive Care Unit Setting.

PubMed

DeJournett, Leon; DeJournett, Jeremy

2016-11-01

Effective glucose control in the intensive care unit (ICU) setting has the potential to decrease morbidity and mortality rates which should in turn lead to decreased health care expenditures. Current ICU-based glucose controllers are mathematically derived, and tend to be based on proportional integral derivative (PID) or model predictive control (MPC). Artificial intelligence (AI)-based closed loop glucose controllers may have the ability to achieve control that improves on the results achieved by either PID or MPC controllers. We conducted an in silico analysis of an AI-based glucose controller designed for use in the ICU setting. This controller was tested using a mathematical model of the ICU patient's glucose-insulin system. A total of 126 000 unique 5-day simulations were carried out, resulting in 107 million glucose values for analysis. For the 7 control ranges tested, with a sensor error of ±10%, the following average results were achieved: (1) time in control range, 94.2%, (2) time in range 70-140 mg/dl, 97.8%, (3) time in hyperglycemic range (>140 mg/dl), 2.1%, and (4) time in hypoglycemic range (<70 mg/dl), 0.09%. In addition, the average coefficient of variation (CV) was 11.1%. This in silico study of an AI-based closed loop glucose controller shows that it may be able to improve on the results achieved by currently existing ICU-based PID/MPC controllers. If these results are confirmed in clinical testing, this AI-based controller could be used to create an artificial pancreas system for use in the ICU setting. © 2016 Diabetes Technology Society.

Streamflow prediction using multi-site rainfall obtained from hydroclimatic teleconnection

NASA Astrophysics Data System (ADS)

Kashid, S. S.; Ghosh, Subimal; Maity, Rajib

2010-12-01

SummarySimultaneous variations in weather and climate over widely separated regions are commonly known as "hydroclimatic teleconnections". Rainfall and runoff patterns, over continents, are found to be significantly teleconnected, with large-scale circulation patterns, through such hydroclimatic teleconnections. Though such teleconnections exist in nature, it is very difficult to model them, due to their inherent complexity. Statistical techniques and Artificial Intelligence (AI) tools gain popularity in modeling hydroclimatic teleconnection, based on their ability, in capturing the complicated relationship between the predictors (e.g. sea surface temperatures) and predictand (e.g., rainfall). Genetic Programming is such an AI tool, which is capable of capturing nonlinear relationship, between predictor and predictand, due to its flexible functional structure. In the present study, gridded multi-site weekly rainfall is predicted from El Niño Southern Oscillation (ENSO) indices, Equatorial Indian Ocean Oscillation (EQUINOO) indices, Outgoing Longwave Radiation (OLR) and lag rainfall at grid points, over the catchment, using Genetic Programming. The predicted rainfall is further used in a Genetic Programming model to predict streamflows. The model is applied for weekly forecasting of streamflow in Mahanadi River, India, and satisfactory performance is observed.

Predictors of spine deformity progression in adolescent idiopathic scoliosis: A systematic review with meta-analysis

PubMed Central

Noshchenko, Andriy; Hoffecker, Lilian; Lindley, Emily M; Burger, Evalina L; Cain, Christopher MJ; Patel, Vikas V; Bradford, Andrew P

2015-01-01

AIM: To evaluate published data on the predictors of progressive adolescent idiopathic scoliosis (AIS) in order to evaluate their efficacy and level of evidence. METHODS: Selection criteria: (1) study design: randomized controlled clinical trials, prospective cohort studies and case series, retrospective comparative and none comparative studies; (2) participants: adolescents with AIS aged from 10 to 20 years; and (3) treatment: observation, bracing, and other. Search method: Ovid MEDLINE, Embase, the Cochrane Library, PubMed and patent data bases. All years through August 2014 were included. Data were collected that showed an association between the studied characteristics and the progression of AIS or the severity of the spine deformity. Odds ratio (OR), sensitivity, specificity, positive and negative predictive values were also collected. A meta-analysis was performed to evaluate the pooled OR and predictive values, if more than 1 study presented a result. The GRADE approach was applied to evaluate the level of evidence. RESULTS: The review included 25 studies. All studies showed statistically significant or borderline association between severity or progression of AIS with the following characteristics: (1) An increase of the Cobb angle or axial rotation during brace treatment; (2) decrease of the rib-vertebral angle at the apical level of the convex side during brace treatment; (3) initial Cobb angle severity (> 25o); (4) osteopenia; (5) patient age < 13 years at diagnosis; (6) premenarche status; (7) skeletal immaturity; (8) thoracic deformity; (9) brain stem vestibular dysfunction; and (10) multiple indices combining radiographic, demographic, and physiologic characteristics. Single nucleotide polymorphisms of the following genes: (1) calmodulin 1; (2) estrogen receptor 1; (3) tryptophan hydroxylase 1; (3) insulin-like growth factor 1; (5) neurotrophin 3; (6) interleukin-17 receptor C; (7) melatonin receptor 1B, and (8) ScoliScore test. Other predictors included: (1) impairment of melatonin signaling in osteoblasts and peripheral blood mononuclear cells (PBMC); (2) G-protein signaling dysfunction in PBMC; and (3) the level of platelet calmodulin. However, predictive values of all these findings were limited, and the levels of evidence were low. The pooled result of brace treatment outcomes demonstrated that around 27% of patents with AIS experienced exacerbation of the spine deformity during or after brace treatment, and 15% required surgical correction. However, the level of evidence is also low due to the limitations of the included studies. CONCLUSION: This review did not reveal any methods for the prediction of progression in AIS that could be recommended for clinical use as diagnostic criteria. PMID:26301183

Predictors of spine deformity progression in adolescent idiopathic scoliosis: A systematic review with meta-analysis.

PubMed

Noshchenko, Andriy; Hoffecker, Lilian; Lindley, Emily M; Burger, Evalina L; Cain, Christopher Mj; Patel, Vikas V; Bradford, Andrew P

2015-08-18

To evaluate published data on the predictors of progressive adolescent idiopathic scoliosis (AIS) in order to evaluate their efficacy and level of evidence. (1) study design: randomized controlled clinical trials, prospective cohort studies and case series, retrospective comparative and none comparative studies; (2) participants: adolescents with AIS aged from 10 to 20 years; and (3) treatment: observation, bracing, and other. Ovid MEDLINE, Embase, the Cochrane Library, PubMed and patent data bases. All years through August 2014 were included. Data were collected that showed an association between the studied characteristics and the progression of AIS or the severity of the spine deformity. Odds ratio (OR), sensitivity, specificity, positive and negative predictive values were also collected. A meta-analysis was performed to evaluate the pooled OR and predictive values, if more than 1 study presented a result. The GRADE approach was applied to evaluate the level of evidence. The review included 25 studies. All studies showed statistically significant or borderline association between severity or progression of AIS with the following characteristics: (1) An increase of the Cobb angle or axial rotation during brace treatment; (2) decrease of the rib-vertebral angle at the apical level of the convex side during brace treatment; (3) initial Cobb angle severity (> 25(o)); (4) osteopenia; (5) patient age < 13 years at diagnosis; (6) premenarche status; (7) skeletal immaturity; (8) thoracic deformity; (9) brain stem vestibular dysfunction; and (10) multiple indices combining radiographic, demographic, and physiologic characteristics. Single nucleotide polymorphisms of the following genes: (1) calmodulin 1; (2) estrogen receptor 1; (3) tryptophan hydroxylase 1; (3) insulin-like growth factor 1; (5) neurotrophin 3; (6) interleukin-17 receptor C; (7) melatonin receptor 1B, and (8) ScoliScore test. Other predictors included: (1) impairment of melatonin signaling in osteoblasts and peripheral blood mononuclear cells (PBMC); (2) G-protein signaling dysfunction in PBMC; and (3) the level of platelet calmodulin. However, predictive values of all these findings were limited, and the levels of evidence were low. The pooled result of brace treatment outcomes demonstrated that around 27% of patents with AIS experienced exacerbation of the spine deformity during or after brace treatment, and 15% required surgical correction. However, the level of evidence is also low due to the limitations of the included studies. This review did not reveal any methods for the prediction of progression in AIS that could be recommended for clinical use as diagnostic criteria.

Comparison of Physician-Predicted to Measured Low Vision Outcomes

PubMed Central

Chan, Tiffany L.; Goldstein, Judith E.; Massof, Robert W.

2013-01-01

Purpose To compare low vision rehabilitation (LVR) physicians’ predictions of the probability of success of LVR to patients’ self-reported outcomes after provision of usual outpatient LVR services; and to determine if patients’ traits influence physician ratings. Methods The Activity Inventory (AI), a self-report visual function questionnaire, was administered pre and post-LVR to 316 low vision patients served by 28 LVR centers that participated in a collaborative observational study. The physical component of the Short Form-36, Geriatric Depression Scale, and Telephone Interview for Cognitive Status were also administered pre-LVR to measure physical capability, depression and cognitive status. Following patient evaluation, 38 LVR physicians estimated the probability of outcome success (POS), using their own criteria. The POS ratings and change in functional ability were used to assess the effects of patients’ baseline traits on predicted outcomes. Results A regression analysis with a hierarchical random effects model showed no relationship between LVR physician POS estimates and AI-based outcomes. In another analysis, Kappa statistics were calculated to determine the probability of agreement between POS and AI-based outcomes for different outcome criteria. Across all comparisons, none of the kappa values were significantly different from 0, which indicates the rate of agreement is equivalent to chance. In an exploratory analysis, hierarchical mixed effects regression models show that POS ratings are associated with information about the patient’s cognitive functioning and the combination of visual acuity and functional ability, as opposed to visual acuity or functional ability alone. Conclusions Physicians’ predictions of LVR outcomes appear to be influenced by knowledge of patients’ cognitive functioning and the combination of visual acuity and functional ability - information physicians acquire from the patient’s history and examination. However, physicians’ predictions do not agree with observed changes in functional ability from the patient’s perspective; they are no better than chance. PMID:23873036

The value of the injury severity score in pediatric trauma: Time for a new definition of severe injury?

PubMed

Brown, Joshua B; Gestring, Mark L; Leeper, Christine M; Sperry, Jason L; Peitzman, Andrew B; Billiar, Timothy R; Gaines, Barbara A

2017-06-01

The Injury Severity Score (ISS) is the most commonly used injury scoring system in trauma research and benchmarking. An ISS greater than 15 conventionally defines severe injury; however, no studies evaluate whether ISS performs similarly between adults and children. Our objective was to evaluate ISS and Abbreviated Injury Scale (AIS) to predict mortality and define optimal thresholds of severe injury in pediatric trauma. Patients from the Pennsylvania trauma registry 2000-2013 were included. Children were defined as younger than 16 years. Logistic regression predicted mortality from ISS for children and adults. The optimal ISS cutoff for mortality that maximized diagnostic characteristics was determined in children. Regression also evaluated the association between mortality and maximum AIS in each body region, controlling for age, mechanism, and nonaccidental trauma. Analysis was performed in single and multisystem injuries. Sensitivity analyses with alternative outcomes were performed. Included were 352,127 adults and 50,579 children. Children had similar predicted mortality at ISS of 25 as adults at ISS of 15 (5%). The optimal ISS cutoff in children was ISS greater than 25 and had a positive predictive value of 19% and negative predictive value of 99% compared to a positive predictive value of 7% and negative predictive value of 99% for ISS greater than 15 to predict mortality. In single-system-injured children, mortality was associated with head (odds ratio, 4.80; 95% confidence interval, 2.61-8.84; p < 0.01) and chest AIS (odds ratio, 3.55; 95% confidence interval, 1.81-6.97; p < 0.01), but not abdomen, face, neck, spine, or extremity AIS (p > 0.05). For multisystem injury, all body region AIS scores were associated with mortality except extremities. Sensitivity analysis demonstrated ISS greater than 23 to predict need for full trauma activation, and ISS greater than 26 to predict impaired functional independence were optimal thresholds. An ISS greater than 25 may be a more appropriate definition of severe injury in children. Pattern of injury is important, as only head and chest injury drive mortality in single-system-injured children. These findings should be considered in benchmarking and performance improvement efforts. Epidemiologic study, level III.

Absolute & Convective Instabilities in the Boundary Layer on a Rotating Sphere

NASA Astrophysics Data System (ADS)

Garrett, Stephen; Peake, Nigel

2001-11-01

We are concerned with absolute (AI) and convective instabilities (CI) in the boundary-layer on a sphere rotating in an otherwise still fluid. Both AI and CI are found at every latitude within specific parameter spaces. The local Reynolds number at the predicted onset of AI matches experimental data well for the onset of turbulence at ψ =30^o from the axis of rotation, beyond this latitude the discrepancy increases but remains relatively small below ψ =70^o. We suggest that this AI may cause the onset of transition. The results of the CI analysis show that a crossflow instability mode is the most dangerous below ψ =66^o. Above this latitude a streamline-curvature mode is found to be the most dangerous, which coincides with the appearance of reverse flow in the radial component of the mean flow. Our predictions of the Reynolds number and vortex angle at the onset of CI are consistent with existing experimental measurements. Close to the pole the predictions of each stability analysis are seen to approach those of existing rotating disk investigations.

Estimating the Accuracy of the Chedoke–McMaster Stroke Assessment Predictive Equations for Stroke Rehabilitation

PubMed Central

Dang, Mia; Ramsaran, Kalinda D.; Street, Melissa E.; Syed, S. Noreen; Barclay-Goddard, Ruth; Miller, Patricia A.

2011-01-01

ABSTRACT Purpose: To estimate the predictive accuracy and clinical usefulness of the Chedoke–McMaster Stroke Assessment (CMSA) predictive equations. Method: A longitudinal prognostic study using historical data obtained from 104 patients admitted post cerebrovascular accident was undertaken. Data were abstracted for all patients undergoing rehabilitation post stroke who also had documented admission and discharge CMSA scores. Published predictive equations were used to determine predicted outcomes. To determine the accuracy and clinical usefulness of the predictive model, shrinkage coefficients and predictions with 95% confidence bands were calculated. Results: Complete data were available for 74 patients with a mean age of 65.3±12.4 years. The shrinkage values for the six Impairment Inventory (II) dimensions varied from −0.05 to 0.09; the shrinkage value for the Activity Inventory (AI) was 0.21. The error associated with predictive values was greater than ±1.5 stages for the II dimensions and greater than ±24 points for the AI. Conclusions: This study shows that the large error associated with the predictions (as defined by the confidence band) for the CMSA II and AI limits their clinical usefulness as a predictive measure. Further research to establish predictive models using alternative statistical procedures is warranted. PMID:22654239

Correlations between social-emotional feelings and anterior insula activity are independent from visceral states but influenced by culture

PubMed Central

Immordino-Yang, Mary Helen; Yang, Xiao-Fei; Damasio, Hanna

2014-01-01

The anterior insula (AI) maps visceral states and is active during emotional experiences, a functional confluence that is central to neurobiological accounts of feelings. Yet, it is unclear how AI activity correlates with feelings during social emotions, and whether this correlation may be influenced by culture, as studies correlating real-time AI activity with visceral states and feelings have focused on Western subjects feeling physical pain or basic disgust. Given psychological evidence that social-emotional feelings are cognitively constructed within cultural frames, we asked Chinese and American participants to report their feeling strength to admiration and compassion-inducing narratives during fMRI with simultaneous electrocardiogram recording. Trial-by-trial, cardiac arousal and feeling strength correlated with ventral and dorsal AI activity bilaterally but predicted different variance, suggesting that interoception and social-emotional feeling construction are concurrent but dissociable AI functions. Further, although the variance that correlated with cardiac arousal did not show cultural effects, the variance that correlated with feelings did. Feeling strength was especially associated with ventral AI activity (the autonomic modulatory sector) in the Chinese group but with dorsal AI activity (the visceral-somatosensory/cognitive sector) in an American group not of Asian descent. This cultural group difference held after controlling for posterior insula (PI) activity and was replicated. A bi-cultural East-Asian American group showed intermediate results. The findings help elucidate how the AI supports feelings and suggest that previous reports that dorsal AI activation reflects feeling strength are culture related. More broadly, the results suggest that the brain's ability to construct conscious experiences of social emotion is less closely tied to visceral processes than neurobiological models predict and at least partly open to cultural influence and learning. PMID:25278862

Temporal prediction errors modulate task-switching performance

PubMed Central

Limongi, Roberto; Silva, Angélica M.; Góngora-Costa, Begoña

2015-01-01

We have previously shown that temporal prediction errors (PEs, the differences between the expected and the actual stimulus’ onset times) modulate the effective connectivity between the anterior cingulate cortex and the right anterior insular cortex (rAI), causing the activity of the rAI to decrease. The activity of the rAI is associated with efficient performance under uncertainty (e.g., changing a prepared behavior when a change demand is not expected), which leads to hypothesize that temporal PEs might disrupt behavior-change performance under uncertainty. This hypothesis has not been tested at a behavioral level. In this work, we evaluated this hypothesis within the context of task switching and concurrent temporal predictions. Our participants performed temporal predictions while observing one moving ball striking a stationary ball which bounced off with a variable temporal gap. Simultaneously, they performed a simple color comparison task. In some trials, a change signal made the participants change their behaviors. Performance accuracy decreased as a function of both the temporal PE and the delay. Explaining these results without appealing to ad hoc concepts such as “executive control” is a challenge for cognitive neuroscience. We provide a predictive coding explanation. We hypothesize that exteroceptive and proprioceptive minimization of PEs would converge in a fronto-basal ganglia network which would include the rAI. Both temporal gaps (or uncertainty) and temporal PEs would drive and modulate this network respectively. Whereas the temporal gaps would drive the activity of the rAI, the temporal PEs would modulate the endogenous excitatory connections of the fronto-striatal network. We conclude that in the context of perceptual uncertainty, the system is not able to minimize perceptual PE, causing the ongoing behavior to finalize and, in consequence, disrupting task switching. PMID:26379568

Temporal prediction errors modulate task-switching performance.

PubMed

Limongi, Roberto; Silva, Angélica M; Góngora-Costa, Begoña

2015-01-01

We have previously shown that temporal prediction errors (PEs, the differences between the expected and the actual stimulus' onset times) modulate the effective connectivity between the anterior cingulate cortex and the right anterior insular cortex (rAI), causing the activity of the rAI to decrease. The activity of the rAI is associated with efficient performance under uncertainty (e.g., changing a prepared behavior when a change demand is not expected), which leads to hypothesize that temporal PEs might disrupt behavior-change performance under uncertainty. This hypothesis has not been tested at a behavioral level. In this work, we evaluated this hypothesis within the context of task switching and concurrent temporal predictions. Our participants performed temporal predictions while observing one moving ball striking a stationary ball which bounced off with a variable temporal gap. Simultaneously, they performed a simple color comparison task. In some trials, a change signal made the participants change their behaviors. Performance accuracy decreased as a function of both the temporal PE and the delay. Explaining these results without appealing to ad hoc concepts such as "executive control" is a challenge for cognitive neuroscience. We provide a predictive coding explanation. We hypothesize that exteroceptive and proprioceptive minimization of PEs would converge in a fronto-basal ganglia network which would include the rAI. Both temporal gaps (or uncertainty) and temporal PEs would drive and modulate this network respectively. Whereas the temporal gaps would drive the activity of the rAI, the temporal PEs would modulate the endogenous excitatory connections of the fronto-striatal network. We conclude that in the context of perceptual uncertainty, the system is not able to minimize perceptual PE, causing the ongoing behavior to finalize and, in consequence, disrupting task switching.

Quantifying the tracking capability of space-based AIS systems

NASA Astrophysics Data System (ADS)

Skauen, Andreas Nordmo

2016-01-01

The Norwegian Defence Research Establishment (FFI) has operated three Automatic Identification System (AIS) receivers in space. Two are on dedicated nano-satellites, AISSat-1 and AISSat-2. The third, the NORAIS Receiver, was installed on the International Space Station. A general method for calculating the upper bound on the tracking capability of a space-based AIS system has been developed and the results from the algorithm applied to AISSat-1 and the NORAIS Receiver individually. In addition, a constellation of AISSat-1 and AISSat-2 is presented. The tracking capability is defined as the probability of re-detecting ships as they move around the globe and is explained to represent and upper bound on a space-based AIS system performance. AISSat-1 and AISSat-2 operates on the nominal AIS1 and AIS2 channels, while the NORAIS Receiver data used are from operations on the dedicated space AIS channels, AIS3 and AIS4. The improved tracking capability of operations on the space AIS channels is presented.

A New Method to Classify Injury Severity by Diagnosis: Validation using Workers' Compensation and Trauma Registry Data

PubMed Central

Sears, Jeanne M.; Bowman, Stephen M.; Rotert, Mary; Hogg-Johnson, Sheilah

2015-01-01

Purpose Acute work-related trauma is a leading cause of death and disability among U.S. workers. Existing methods to estimate injury severity have important limitations. This study assessed a severe injury indicator constructed from a list of severe traumatic injury diagnosis codes previously developed for surveillance purposes. Study objectives were to: (1) describe the degree to which the severe injury indicator predicts work disability and medical cost outcomes; (2) assess whether this indicator adequately substitutes for estimating Abbreviated Injury Scale (AIS)-based injury severity from workers' compensation (WC) billing data; and (3) assess concordance between indicators constructed from Washington State Trauma Registry (WTR) and WC data. Methods WC claims for workers injured in Washington State from 1998-2008 were linked to WTR records. Competing risks survival analysis was used to model work disability outcomes. Adjusted total medical costs were modeled using linear regression. Information content of the severe injury indicator and AIS-based injury severity measures were compared using Akaike Information Criterion and R2. Results Of 208,522 eligible WC claims, 5% were classified as severe. Among WC claims linked to the WTR, there was substantial agreement between WC-based and WTR-based indicators (kappa=0.75). Information content of the severe injury indicator was similar to some AIS-based measures. The severe injury indicator was a significant predictor of WTR inclusion, early hospitalization, compensated time loss, total permanent disability, and total medical costs. Conclusions Severe traumatic injuries can be directly identified when diagnosis codes are available. This method provides a simple and transparent alternative to AIS-based injury severity estimation. PMID:25900409

A complete backbone spectral assignment of human apolipoprotein AI on a 38 kDa preβHDL (Lp1-AI) particle

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ren, Xuefeng; Yang, Yunhuang; Neville, T.

2007-06-12

Apolipoprotein A-I (apoAI, 243-residues) is the major protein component of the high-density lipoprotein (HDL) that has been a hot subject of interests because of its anti-atherogenic properties. This important property of apoAI is related to its roles in reverse cholesterol transport pathway. Upon lipid-binding, apoAI undergoes conformational changes from lipid-free to several different HDL-associated states (1). These different conformational states regulate HDL formation, maturation and transportation. Two initial conformational states of apoAI are lipid-free apoAI and apoAI/preβHDL that recruit phospholipids and cholesterol to form HDL particles. In particular, lipid-free apoAI specifically binds to phospholipids to form lipid-poor apoAI, including apoAI/preβ-HDLmore » (~37 kDa). As a unique class of lipid poor HDL, both in vitro and in vivo evidence demonstrates that apoAI/preβ-HDLs are the most effective acceptors specifically for free cholesterol in human plasma and serves as the precursor of HDL particles (2). Here we report a complete backbone spectral assignment of human apoAI/preβHDL. Secondary structure prediction using backbone NMR parameters indicates that apoAI/preβHDL displays a two-domain structure: the N-terminal four helix-bundle domain (residues 1-186) and the C-terminal flexible domain (residues 187-243). A structure of apoAI/preβ-HDL is the first lipid-associated structure of apoAI and is critical for us to understand how apoAI recruits cholesterol to initialize HDL formation. BMRB deposit with accession number: 15093.« less

Synthesis, anti-inflammatory, bactericidal activities and docking studies of novel 1,2,3-triazoles derived from ibuprofen using click chemistry.

PubMed

Angajala, Kishore Kumar; Vianala, Sunitha; Macha, Ramesh; Raghavender, M; Thupurani, Murali Krishna; Pathi, P J

2016-01-01

Nonsteroidal anti-inflammatory drugs are of vast therapeutic benefit in the treatment of different types of inflammatory conditions. 1,2,3-Triazoles and their derivatives have a wide range of applications as anti-bacterial, anti-fungal, anti-tubercular, cytostatic, anti-HIV, anti-allergic, anti-neoplastic and anti-inflammatory (AI) agents. Considering the individual biological and medicinal importance of ibuprofen and 1,2,3-triazoles, we wanted to explore novel chemical entities based on ibuprofen and triazole moieties towards their biological significance. Click chemistry has utilized as an ideal strategy to prepare novel ibuprofen-based 1,4-disubstituted 1,2,3-triazole containing molecules. These compounds were screened for their in vivo AI activity, among all the synthesized analogues 13o was shown potent effect than the reference AI drug ibuprofen at the same concentration (10 mg/kg body weight). Compounds 13l, 13g, 13c, 13k, 13i, 13n, 13m and 13j were shown significant AI activity. These triazole analogues were also screened for their bactericidal profile. Compounds 13c, 13i, 13l and 13o exhibited considerable bactericidal activity against gram positive and gram negative strains. In addition to this, molecular docking studies were also carried out into cyclooxygenase-2 active site to predict the affinity and orientation of these novel compounds (13a-q). In summary, we have designed and synthesized 1,2,3-triazole analogues of ibuprofen in good yields using Click chemistry approach. AI and bactericidal activities of these compounds were evaluated and shown remarkable results.

Towards a Definition for Health Care–Associated Infection

PubMed Central

Friedman, N Deborah; Levit, Dana; Taleb, Eyal; Marcus, Gil; Michaeli, Leah; Broide, Mor; Mengesha, Bethlehem; Zaidenstein, Ronit; Lazarovitch, Tsilia; Dadon, Mor; Kaye, Keith S; Marchaim, Dror

2018-01-01

Abstract Background Health care–associated infection (HcAI) is a term frequently used to describe community-onset infections likely to be caused by multidrug-resistant organisms (MDROs). The most frequently used definition was developed at Duke University Medical Center in 2002 (Duke-2002). Although some professional societies have based management recommendations on Duke-2002 (or modifications thereof), neither Duke-2002 nor other variations have had their performance measured. Methods A case–control study was conducted at Assaf Harofeh Medical Center (AHMC) of consecutive adult bloodstream infections (BSIs). A multivariable model was used to develop a prediction score for HcAI, measured by the presence of MDRO infection on admission. The performances of this new score and previously developed definitions at predicting MDRO infection on admission were measured. Results Of the 504 BSI patients enrolled, 315 had a BSI on admission and 189 had a nosocomial BSI. Patients with MDRO-BSI on admission (n = 100) resembled patients with nosocomial infections (n = 189) in terms of epidemiological characteristics, illness acuity, and outcomes more than patients with non-MDRO-BSI on admission (n = 215). The performances of both the newly developed score and the Duke-2002 definition to predict MDRO infection on admission were suboptimal (area under the receiver operating characteric curve, 0.76 and 0.68, respectively). Conclusions Although the term HcAI is frequently used, its definition does not perform well at predicting MDRO infection present on admission to the hospital. A validated score that calculates the risk of MDRO infection on admission is still needed to guide daily practice and improve patient outcomes.

Space-based detection of spoofing AIS signals using Doppler frequency

NASA Astrophysics Data System (ADS)

Guo, Shanzeng

2014-05-01

The Automatic Identification System (AIS) is a self-reporting system based on VHF radio to transmit a vessel's identity, position, speed, heading and other parameters to improve maritime domain awareness. However, AIS information can be programmatically spoofed by terrorists or other criminals, who often choose to masquerade as innocent civilians and exploit the vulnerabilities of military and civilian infrastructures for their purposes. Therefore, detecting and localizing a spoofing AIS ship become a critical and challenging issue for maritime security. This paper presents an algorithm to detect and geolocalize a spoofing AIS emitter using space-based AIS signals with its Doppler frequency. With an AIS signal sensor on a fast orbiting satellite, the measured AIS Doppler frequency of an AIS emitter can be used to define a double-napped cone of which the satellite is at its vertex and satellite velocity coincides with its axis, such that the theoretical Doppler frequency derived from the radial velocity to the AIS emitter matches the measured Doppler frequency. All such matches can only lie on either cone extending out from the satellite, which cuts the Earth's surface in two curves, so we know that the AIS emitter must lie somewhere on these curves. Two such AIS Doppler frequency measurements for the same stationary AIS emitter produce two valid curves which intersect at the position of the AIS emitter. Multiple Doppler frequency measurements can be used to better estimate the position fix of an AIS emitter, hence determine the spoofing AIS ship if the estimated position fix unreasonably differs from the position carried in its AIS message. A set of formulas are derived which relate an AIS emitter position to its Doppler frequency measurements.

Quality Evaluation of Shelled and Unshelled Macadamia Nuts by Means of Near-Infrared Spectroscopy (NIR).

PubMed

Canneddu, Giovanna; Júnior, Luis Carlos Cunha; de Almeida Teixeira, Gustavo Henrique

2016-07-01

The quality of shelled and unshelled macadamia nuts was assessed by means of Fourier transformed near-infrared (FT-NIR) spectroscopy. Shelled macadamia nuts were sorted as sound nuts; nuts infected by Ecdytolopha aurantiana and Leucopteara coffeella; and cracked nuts caused by germination. Unshelled nuts were sorted as intact nuts (<10% half nuts, 2014); half nuts (March, 2013; November, 2013); and crushed nuts (2014). Peroxide value (PV) and acidity index (AI) were determined according to AOAC. PCA-LDA shelled macadamia nuts classification resulted in 93.2% accurate classification. PLS PV prediction model resulted in a square error of prediction (SEP) of 3.45 meq/kg, and a prediction coefficient determination value (Rp (2) ) of 0.72. The AI PLS prediction model was better (SEP = 0.14%, Rp (2) = 0.80). Although adequate classification was possible (93.2%), shelled nuts must not contain live insects, therefore the classification accuracy was not satisfactory. FT-NIR spectroscopy can be successfully used to predict PV and AI in unshelled macadamia nuts, though. © 2016 Institute of Food Technologists®

Fifteen-Minute Comprehensive Alcohol Risk Survey: Reliability and Validity Across American Indian and White Adolescents

PubMed Central

Komro, Kelli A; Livingston, Melvin D; Kominsky, Terrence K; Livingston, Bethany J; Garrett, Brady A; Molina, Mildred Maldonado; Boyd, Misty L

2015-01-01

Objective: American Indians (AIs) suffer from significant alcohol-related health disparities, and increased risk begins early. This study examined the reliability and validity of measures to be used in a preventive intervention trial. Reliability and validity across racial/ethnic subgroups are crucial to evaluate intervention effectiveness and promote culturally appropriate evidence-based practice. Method: To assess reliability and validity, we used three baseline surveys of high school students participating in a preventive intervention trial within the jurisdictional service area of the Cherokee Nation in northeastern Oklahoma. The 15-minute alcohol risk survey included 16 multi-item scales and one composite score measuring key proximal, primary, and moderating variables. Forty-four percent of the students indicated that they were AI (of whom 82% were Cherokee), including 23% who reported being AI only (n = 435) and 18% both AI and White (n = 352). Forty-seven percent reported being White only (n = 901). Results: Scales were adequately reliable for the full sample and across race/ethnicity defined by AI, AI/White, and White subgroups. Among the full sample, all scales had acceptable internal consistency, with minor variation across race/ethnicity. All scales had extensive to exemplary test–retest reliability and showed minimal variation across race/ethnicity. The eight proximal and two primary outcome scales were each significantly associated with the frequency of alcohol use during the past month in both the cross-sectional and the longitudinal models, providing support for both criterion validity and predictive validity. For most scales, interpretation of the strength of association and statistical significance did not differ between the racial/ethnic subgroups. Conclusions: The results support the reliability and validity of scales of a brief questionnaire measuring risk and protective factors for alcohol use among AI adolescents, primarily members of the Cherokee Nation. PMID:25486402

Arterial Wall Imaging in Pediatric Stroke.

PubMed

Dlamini, Nomazulu; Yau, Ivanna; Muthusami, Prakash; Mikulis, David J; Elbers, Jorina; Slim, Mahmoud; Askalan, Rand; MacGregor, Daune; deVeber, Gabrielle; Shroff, Manohar; Moharir, Mahendranath

2018-04-01

Arteriopathy is common in childhood arterial ischemic stroke (AIS) and predicts stroke recurrence. Currently available vascular imaging techniques mainly image the arterial lumen rather than the vessel wall and have a limited ability to differentiate among common arteriopathies. We aimed to investigate the value of a magnetic resonance imaging-based technique, namely noninvasive arterial wall imaging (AWI), for distinguishing among arteriopathy subtypes in a consecutive cohort of children presenting with AIS. Children with confirmed AIS and magnetic resonance angiography underwent 3-Tesla AWI including T1-weighted 2-dimensional fluid-attenuated inversion recovery fast spin echo sequences pre- and post-gadolinium contrast. AWI characteristics, including wall enhancement, wall thickening, and luminal stenosis, were documented for all. Twenty-six children with AIS had AWI. Of these, 9 (35%) had AWI enhancement. AWI enhancement was associated with anterior circulation magnetic resonance angiography abnormality and cortical infarction in 8 of 9 (89%) children and normal magnetic resonance angiography with posterior circulation subcortical infarction in 1 (1 of 9; 11%) child. AWI enhancement was not seen in 17 (65%), 10 (59%) of whom had an abnormal magnetic resonance angiography. Distinct patterns of pre- and postcontrast signal abnormality were demonstrated in the vessel wall in the region of interest in children with transient cerebral arteriopathy, arterial dissection, primary central nervous system angiitis, dissecting aneurysm, and cardioembolic stroke. AWI is a noninvasive, high-resolution magnetic resonance AWI technique, which can be successfully used in children presenting with AIS. Patterns of AWI enhancement are recognizable and associated with specific AIS pathogeneses. Further studies are required to assess the additional diagnostic utility of AWI over routine vascular imaging techniques, in childhood AIS. © 2018 American Heart Association, Inc.

The AI Interdisciplinary Context: Single or Multiple Research Bases?

ERIC Educational Resources Information Center

Khawam, Yves J.

1992-01-01

This study used citation analysis to determine whether the disciplines contributing to the journal literature of artificial intelligence (AI)--philosophy, psychology, linguistics, computer science, and engineering--share a common AI research base. The idea that AI consists of a completely interdisciplinary endeavor was refuted. (MES)

The effect of interface properties on nickel base alloy composites

NASA Technical Reports Server (NTRS)

Groves, M.; Grossman, T.; Senemeier, M.; Wright, K.

1995-01-01

This program was performed to assess the extent to which mechanical behavior models can predict the properties of sapphire fiber/nickel aluminide matrix composites and help guide their development by defining improved combinations of matrix and interface coating. The program consisted of four tasks: 1) selection of the matrices and interface coating constituents using a modeling-based approach; 2) fabrication of the selected materials; 3) testing and evaluation of the materials; and 4) evaluation of the behavior models to develop recommendations. Ni-50Al and Ni-20AI-30Fe (a/o) matrices were selected which gave brittle and ductile behavior, respectively, and an interface coating of PVD YSZ was selected which provided strong bonding to the sapphire fiber. Significant fiber damage and strength loss was observed in the composites which made straightforward comparison of properties with models difficult. Nevertheless, the models selected generally provided property predictions which agreed well with results when fiber degradation was incorporated. The presence of a strong interface bond was felt to be detrimental in the NiAI MMC system where low toughness and low strength were observed.

Anal sphincter trauma and anal incontinence in urogynecological patients.

PubMed

Guzmán Rojas, R A; Kamisan Atan, I; Shek, K L; Dietz, H P

2015-09-01

To determine the prevalence of evidence of residual obstetric anal sphincter injury, to evaluate its association with anal incontinence (AI) and to establish minimal diagnostic criteria for significant (residual) external anal sphincter (EAS) trauma. This was a retrospective analysis of ultrasound volume datasets of 501 patients attending a tertiary urogynecological unit. All patients underwent a standardized interview including determination of St Mark's score for those presenting with AI. Tomographic ultrasound imaging (TUI) was used to evaluate the EAS and the internal anal sphincter (IAS). Among a total of 501 women, significant EAS and IAS defects were found in 88 and 59, respectively, and AI was reported by 69 (14%). Optimal prediction of AI was achieved using a model that included four abnormal slices of the EAS on TUI. IAS defects were found to be less likely to be associated with AI. In a multivariable model controlling for age and IAS trauma, the presence of at least four abnormal slices gave an 18-fold (95% CI, 9-36; P < 0.0001) increase in the likelihood of AI, compared with those with fewer than four abnormal slices. Using receiver-operating characteristics curve statistics, this model yielded an area under the curve of 0.86 (95% CI, 0.80-0.92). Both AI and significant EAS trauma are common in patients attending urogynecological units, and are strongly associated with each other. Abnormalities of the IAS seem to be less important in predicting AI. Our data support the practice of using, as a minimal criterion, defects present in four of the six slices on TUI for the diagnosis of significant EAS trauma. Copyright © 2015 ISUOG. Published by John Wiley & Sons Ltd.

Injury versus non-injury factors as predictors of post-concussive symptoms following mild traumatic brain injury in children

PubMed Central

McNally, Kelly A.; Bangert, Barbara; Dietrich, Ann; Nuss, Kathy; Rusin, Jerome; Wright, Martha; Taylor, H. Gerry; Yeates, Keith Owen

2013-01-01

Objective To examine the relative contributions of injury characteristics and non-injury child and family factors as predictors of postconcussive symptoms (PCS) following mild traumatic brain injury (TBI) in children. Methods Participants were 8- to 15-year-old children, 186 with mild TBI and 99 with mild orthopedic injuries (OI). Parents and children rated PCS shortly after injury and at 1, 3, and 12 months post-injury. Hierarchical regression analyses were conducted to predict PCS from (1) demographic variables; (2) pre-morbid child factors (WASI IQ; WRAT-3 Reading; Child Behavior Checklist; ratings of pre-injury PCS); (3) family factors (Family Assessment Device General Functioning Scale; Brief Symptom Inventory; and Life Stressors and Social Resources Inventory); and (4) injury group (OI, mild TBI with loss of consciousness [LOC] and associated injuries [AI], mild TBI with LOC but without AI, mild TBI without LOC but with AI, and mild TBI without LOC or AI) Results Injury group predicted parent and child ratings of PCS but showed a decreasing contribution over time. Demographic variables consistently predicted symptom ratings across time. Premorbid child factors, especially retrospective ratings of premorbid symptoms, accounted for the most variance in symptom ratings. Family factors, particularly parent adjustment, consistently predicted parent, but not child, ratings of PCS. Conclusions Injury characteristics predict PCS in the first months following mild TBI but show a decreasing contribution over time. In contrast, non-injury factors are more consistently related to persistent PCS. PMID:23356592

Full Field and Anomaly Initialisation using a low order climate model: a comparison, and proposals for advanced formulations

NASA Astrophysics Data System (ADS)

Weber, Robin; Carrassi, Alberto; Guemas, Virginie; Doblas-Reyes, Francisco; Volpi, Danila

2014-05-01

Full Field (FFI) and Anomaly Initialisation (AI) are two schemes used to initialise seasonal-to-decadal (s2d) prediction. FFI initialises the model on the best estimate of the actual climate state and minimises the initial error. However, due to inevitable model deficiencies, the trajectories drift away from the observations towards the model's own attractor, inducing a bias in the forecast. AI has been devised to tackle the impact of drift through the addition of this bias onto the observations, in the hope of gaining an initial state closer to the model attractor. Its goal is to forecast climate anomalies. The large variety of experimental setups, global coupled models, and observational networks adopted world-wide have led to varying results with regards to the relative performance of AI and FFI. Our research is firstly motivated in a comparison of these two initialisation approaches under varying circumstances of observational errors, observational distributions, and model errors. We also propose and compare two advanced schemes for s2d prediction. Least Square Initialisation (LSI) intends to propagate observational information of partially initialized systems to the whole model domain, based on standard practices in data assimilation and using the covariance of the model anomalies. Exploring the Parameters Uncertainty (EPU) is an online drift correction technique applied during the forecast run after initialisation. It is designed to estimate, and subtract, the bias in the forecast related to parametric error. Experiments are carried out using an idealized coupled dynamics in order to facilitate better control and robust statistical inference. Results show that an improvement of FFI will necessitate refinements in the observations, whereas improvements in AI are subject to model advances. A successful approximation of the model attractor using AI is guaranteed only when the differences between model and nature probability distribution functions (PDFs) are limited to the first order. Significant higher order differences can lead to an initial conditions distribution for AI that is less representative of the model PDF and lead to a degradation of the initalisation skill. Finally, both ad- vanced schemes lead to significantly improved skill scores, encouraging their implementation for models of higher complexity.

Understanding the role of the immune system in adolescent idiopathic scoliosis: Immunometabolic CONnections to Scoliosis (ICONS) study protocol

PubMed Central

Samaan, M Constantine; Missiuna, Paul; Peterson, Devin; Thabane, Lehana

2016-01-01

Introduction Adolescent idiopathic scoliosis (AIS) affects up to 3% of children around the world. There is limited knowledge of AIS aetiopathogenesis, and this evidence is needed to develop new management strategies. Paraspinal muscle in AIS demonstrates evidence of differential fibrosis based on curve sidedness. Fibrosis is the hallmark of macrophage-driven inflammation and tissue remodelling, yet the mechanisms of fibrosis in paraspinal muscle in AIS are poorly understood. Objectives The primary objective of this study is to determine the influence of curve sidedness on paraspinal muscle inflammation. Secondary objectives include defining the mechanisms of macrophage homing to muscle, and determining muscle–macrophage crosstalk in muscle fibrosis in AIS. Methods and analysis This is a cross-sectional study conducted in a tertiary paediatric centre in Hamilton, Ontario, Canada. We will recruit boys and girls, 10–17 years of age, who are having surgery to correct AIS. We will exclude children who have an active infection or are on immunosuppressive therapies within 2 weeks of surgery, smokers and pregnant girls. Paraspinal muscle biopsies will be obtained at the start of surgery. Also, blood and urine samples will be collected from participants, who will fill questionnaires about their lifestyle. Anthropometric measures will also be collected including height, weight, waist and hip circumferences. Ethics and dissemination This study has received ethics authorisation by the institutional review board. This work will be published in peer-reviewed journals and will be presented in oral and poster formats at scientific meetings. Discussion This study will explore the mechanisms of paraspinal muscle inflammation, remodelling and fibrosis in AIS. This will help identify pathways and molecules as potential therapeutic targets to treat and prevent AIS. It may also yield markers that predict scoliosis progression and response to treatment in these children. PMID:27401365

Artificial Intelligence Support for Computational Chemistry

NASA Astrophysics Data System (ADS)

Duch, Wlodzislaw

Possible forms of artificial intelligence (AI) support for quantum chemistry are discussed. Questions addressed include: what kind of support is desirable, what kind of support is feasible, what can we expect in the coming years. Advantages and disadvantages of current AI techniques are presented and it is argued that at present the memory-based systems are the most effective for large scale applications. Such systems may be used to predict the accuracy of calculations and to select the least expensive methods and basis sets belonging to the same accuracy class. Advantages of the Feature Space Mapping as an improvement on the memory based systems are outlined and some results obtained in classification problems given. Relevance of such classification systems to computational chemistry is illustrated with two examples showing similarity of results obtained by different methods that take electron correlation into account.

Deep into the Brain: Artificial Intelligence in Stroke Imaging

PubMed Central

Lee, Eun-Jae; Kim, Yong-Hwan; Kim, Namkug; Kang, Dong-Wha

2017-01-01

Artificial intelligence (AI), a computer system aiming to mimic human intelligence, is gaining increasing interest and is being incorporated into many fields, including medicine. Stroke medicine is one such area of application of AI, for improving the accuracy of diagnosis and the quality of patient care. For stroke management, adequate analysis of stroke imaging is crucial. Recently, AI techniques have been applied to decipher the data from stroke imaging and have demonstrated some promising results. In the very near future, such AI techniques may play a pivotal role in determining the therapeutic methods and predicting the prognosis for stroke patients in an individualized manner. In this review, we offer a glimpse at the use of AI in stroke imaging, specifically focusing on its technical principles, clinical application, and future perspectives. PMID:29037014

Deep into the Brain: Artificial Intelligence in Stroke Imaging.

PubMed

Lee, Eun-Jae; Kim, Yong-Hwan; Kim, Namkug; Kang, Dong-Wha

2017-09-01

Artificial intelligence (AI), a computer system aiming to mimic human intelligence, is gaining increasing interest and is being incorporated into many fields, including medicine. Stroke medicine is one such area of application of AI, for improving the accuracy of diagnosis and the quality of patient care. For stroke management, adequate analysis of stroke imaging is crucial. Recently, AI techniques have been applied to decipher the data from stroke imaging and have demonstrated some promising results. In the very near future, such AI techniques may play a pivotal role in determining the therapeutic methods and predicting the prognosis for stroke patients in an individualized manner. In this review, we offer a glimpse at the use of AI in stroke imaging, specifically focusing on its technical principles, clinical application, and future perspectives.

Sensitivity and specificity of the 'knee-up test' for estimation of the American Spinal Injury Association Impairment Scale in patients with acute motor incomplete cervical spinal cord injury.

PubMed

Yugué, Itaru; Okada, Seiji; Maeda, Takeshi; Ueta, Takayoshi; Shiba, Keiichiro

2018-04-01

A retrospective study. Precise classification of the neurological state of patients with acute cervical spinal cord injury (CSCI) can be challenging. This study proposed a useful and simple clinical method to help classify patients with incomplete CSCI. Spinal Injuries Centre, Japan. The sensitivity and specificity of the 'knee-up test' were evaluated in patients with acute CSCI classified as American Spinal Injury Association Impairment Scale (AIS) C or D. The result is positive if the patient can lift the knee in one or both legs to an upright position, whereas the result is negative if the patient is unable to lift the knee in either leg to an upright position. The AIS of these patients was classified according to a strict computerised algorithm designed by Walden et al., and the knee-up test was tested by non-expert examiners. Among the 200 patients, 95 and 105 were classified as AIS C and AIS D, respectively. Overall, 126 and 74 patients demonstrated positive and negative results, respectively, when evaluated using the knee-up test. A total of 104 patients with positive results and 73 patients with negative results were classified as AIS D and AIS C, respectively. The sensitivity, specificity, positive predictive and negative predictive values of this test for all patients were 99.1, 76.8, 82.5 and 98.7, respectively. The knee-up test may allow easy and highly accurate estimation, without the need for special skills, of AIS classification for patients with incomplete CSCI.

Results from service tests on AI-91 gasoline

DOE Office of Scientific and Technical Information (OSTI.GOV)

Turovskii, F.V.; Bakaleinik, A.M.; Belyaev, A.A.

1988-01-01

Research was conducted to establish whether the operational reliability of engines will be affected by the use of a gasoline with an octane number two points lower than that of commercial AI-93 leaded gasoline with knock resistance in acceleration that is better than that of the AI-93 by approximately the same amount. Extended road tests were run in VAZ-2106 and Moskvich-2140 automobiles using gasoline with a research octane number of 91, containing an antiknock additive based on tetramethyl lead, and AI-93. The experimental AI-91 and the commercial AI-93 gasolines were prepared from the same base blend. Average specific fuel consumptionsmore » were identical for automobiles using AI-93 and AI-91 with the tetramethyl lead additive. For automobiles using AI-91 with the additive and with ethyl bromide as a lead scavenger the fuel consumption was 2% lower.« less

Protein subcellular localization prediction using artificial intelligence technology.

PubMed

Nair, Rajesh; Rost, Burkhard

2008-01-01

Proteins perform many important tasks in living organisms, such as catalysis of biochemical reactions, transport of nutrients, and recognition and transmission of signals. The plethora of aspects of the role of any particular protein is referred to as its "function." One aspect of protein function that has been the target of intensive research by computational biologists is its subcellular localization. Proteins must be localized in the same subcellular compartment to cooperate toward a common physiological function. Aberrant subcellular localization of proteins can result in several diseases, including kidney stones, cancer, and Alzheimer's disease. To date, sequence homology remains the most widely used method for inferring the function of a protein. However, the application of advanced artificial intelligence (AI)-based techniques in recent years has resulted in significant improvements in our ability to predict the subcellular localization of a protein. The prediction accuracy has risen steadily over the years, in large part due to the application of AI-based methods such as hidden Markov models (HMMs), neural networks (NNs), and support vector machines (SVMs), although the availability of larger experimental datasets has also played a role. Automatic methods that mine textual information from the biological literature and molecular biology databases have considerably sped up the process of annotation for proteins for which some information regarding function is available in the literature. State-of-the-art methods based on NNs and HMMs can predict the presence of N-terminal sorting signals extremely accurately. Ab initio methods that predict subcellular localization for any protein sequence using only the native amino acid sequence and features predicted from the native sequence have shown the most remarkable improvements. The prediction accuracy of these methods has increased by over 30% in the past decade. The accuracy of these methods is now on par with high-throughput methods for predicting localization, and they are beginning to play an important role in directing experimental research. In this chapter, we review some of the most important methods for the prediction of subcellular localization.

Use of airborne imaging spectrometer data to map minerals associated with hydrothermally altered rocks in the northern grapevine mountains, Nevada, and California

USGS Publications Warehouse

Kruse, F.A.

1988-01-01

Three flightlines of Airborne Imaging Spectrometer (AIS) data, acquired over the northern Grapevine Mountains, Nevada, and California, were used to map minerals associated with hydrothermally altered rocks. The data were processed to remove vertical striping, normalized using an equal area normalization, and reduced to reflectance relative to an average spectrum derived from the data. An algorithm was developed to automatically calculate the absorption band parameters band position, band depth, and band width for the strongest absorption feature in each pixel. These parameters were mapped into an intensity, hue, saturation (IHS) color system to produce a single color image that summarized the absorption band information, This image was used to map areas of potential alteration based upon the predicted relationships between the color image and mineral absorption band. Individual AIS spectra for these areas were then examined to identify specific minerals. Two types of alteration were mapped with the AIS data. Areas of quartz-sericite-pyrite alteration were identified based upon a strong absorption feature near 2.21 ??m, a weak shoulder near 2.25 ??m, and a weak absorption band near 2.35 ??m caused by sericite (fine-grained muscovite). Areas of argillic alteration were defined based on the presence of montmorillonite, identified by a weak to moderate absorption feature near 2.21 ??m and the absence of the 2.35 ??m band. Montmorillonite could not be identified in mineral mixtures. Calcite and dolomite were identified based on sharp absorption features near 2.34 and 2.32 ??m, respectively. Areas of alteration identified using the AIS data corresponded well with areas mapped using field mapping, field reflectance spectra, and laboratory spectral measurements. ?? 1988.

Measurement level AIS/radar fusion for maritime surveillance

NASA Astrophysics Data System (ADS)

Habtemariam, Biruk K.; Tharmarasa, R.; Meger, Eric; Kirubarajan, T.

2012-05-01

Using the Automatic Identification System (AIS) ships identify themselves intermittently by broadcasting their location information. However, traditionally radars are used as the primary source of surveillance and AIS is considered as a supplement with a little interaction between these data sets. The data from AIS is much more accurate than radar data with practically no false alarms. But unlike the radar data, the AIS measurements arrive unpredictably, depending on the type and behavior of a ship. The AIS data includes target IDs that can be associated to initialized tracks. In multitarget maritime surveillance environment, for some targets the revisit interval form the AIS could be very large. In addition, the revisit intervals for various targets can be different. In this paper, we proposed a joint probabilistic data association based tracking algorithm that addresses the aforementioned issues to fuse the radar measurements with AIS data. Multiple AIS IDs are assigned to a track, with probabilities updated by both AIS and radar measurements to resolve the ambiguity in the AIS ID source. Experimental results based on simulated data demonstrate the performance the proposed technique.

The Short-term Prognostic Value of the Triglyceride-to-high-density Lipoprotein Cholesterol Ratio in Acute Ischemic Stroke

PubMed Central

Wang, Huan; Lei, Leix; Zhang, Han-Qing; Gu, Zheng-Tian; Xing, Fang-Lan; Yan, Fu-Ling

2018-01-01

The triglyceride (TG)-to-high-density lipoprotein cholesterol (HDL-C) ratio (TG/HDL-C) is a simple approach to predicting unfavorable outcomes in cardiovascular disease. The influence of TG/HDL-C on acute ischemic stroke remains elusive. The purpose of this study was to investigate the precise effect of TG/HDL-C on 3-month mortality after acute ischemic stroke (AIS). Patients with AIS were enrolled in the present study from 2011 to 2017. A total of 1459 participants from a single city in China were divided into retrospective training and prospective test cohorts. Medical records were collected periodically to determine the incidence of fatal events. All participants were followed for 3 months. Optimal cutoff values were determined using X-tile software to separate the training cohort patients into higher and lower survival groups based on their lipid levels. A survival analysis was conducted using Kaplan-Meier curves and a Cox proportional hazards regression model. A total of 1459 patients with AIS (median age 68.5 years, 58.5% male) were analyzed. Univariate Cox regression analysis confirmed that TG/HDL-C was a significant prognostic factor for 3-month survival. X-tile identified 0.9 as an optimal cutoff for TG/HDL-C. In the univariate analysis, the prognosis of the TG/HDL-C >0.9 group was markedly superior to that of TG/HDL-C ≤0.9 group (P<0.001). A multivariate Cox regression analysis showed that TG/HDL-C was independently correlated with a reduced risk of mortality (hazard ratio [HR], 0.39; 95% confidence interval [CI], 0.24-0.62; P<0.001). These results were confirmed in the 453 patients in the test cohort. A nomogram was constructed to predict 3-month case-fatality, and the c-indexes of predictive accuracy were 0.684 and 0.670 in the training and test cohorts, respectively (P<0.01). The serum TG/HDL-C ratio may be useful for predicting short-term mortality after AIS. PMID:29896437

The Short-term Prognostic Value of the Triglyceride-to-high-density Lipoprotein Cholesterol Ratio in Acute Ischemic Stroke.

PubMed

Deng, Qi-Wen; Li, Shuo; Wang, Huan; Lei, Leix; Zhang, Han-Qing; Gu, Zheng-Tian; Xing, Fang-Lan; Yan, Fu-Ling

2018-06-01

The triglyceride (TG)-to-high-density lipoprotein cholesterol (HDL-C) ratio (TG/HDL-C) is a simple approach to predicting unfavorable outcomes in cardiovascular disease. The influence of TG/HDL-C on acute ischemic stroke remains elusive. The purpose of this study was to investigate the precise effect of TG/HDL-C on 3-month mortality after acute ischemic stroke (AIS). Patients with AIS were enrolled in the present study from 2011 to 2017. A total of 1459 participants from a single city in China were divided into retrospective training and prospective test cohorts. Medical records were collected periodically to determine the incidence of fatal events. All participants were followed for 3 months. Optimal cutoff values were determined using X-tile software to separate the training cohort patients into higher and lower survival groups based on their lipid levels. A survival analysis was conducted using Kaplan-Meier curves and a Cox proportional hazards regression model. A total of 1459 patients with AIS (median age 68.5 years, 58.5% male) were analyzed. Univariate Cox regression analysis confirmed that TG/HDL-C was a significant prognostic factor for 3-month survival. X-tile identified 0.9 as an optimal cutoff for TG/HDL-C. In the univariate analysis, the prognosis of the TG/HDL-C >0.9 group was markedly superior to that of TG/HDL-C ≤0.9 group (P<0.001). A multivariate Cox regression analysis showed that TG/HDL-C was independently correlated with a reduced risk of mortality (hazard ratio [HR], 0.39; 95% confidence interval [CI], 0.24-0.62; P<0.001). These results were confirmed in the 453 patients in the test cohort. A nomogram was constructed to predict 3-month case-fatality, and the c-indexes of predictive accuracy were 0.684 and 0.670 in the training and test cohorts, respectively (P<0.01). The serum TG/HDL-C ratio may be useful for predicting short-term mortality after AIS.

Implementing embedded artificial intelligence rules within algorithmic programming languages

NASA Technical Reports Server (NTRS)

Feyock, Stefan

1988-01-01

Most integrations of artificial intelligence (AI) capabilities with non-AI (usually FORTRAN-based) application programs require the latter to execute separately to run as a subprogram or, at best, as a coroutine, of the AI system. In many cases, this organization is unacceptable; instead, the requirement is for an AI facility that runs in embedded mode; i.e., is called as subprogram by the application program. The design and implementation of a Prolog-based AI capability that can be invoked in embedded mode are described. The significance of this system is twofold: Provision of Prolog-based symbol-manipulation and deduction facilities makes a powerful symbolic reasoning mechanism available to applications programs written in non-AI languages. The power of the deductive and non-procedural descriptive capabilities of Prolog, which allow the user to describe the problem to be solved, rather than the solution, is to a large extent vitiated by the absence of the standard control structures provided by other languages. Embedding invocations of Prolog rule bases in programs written in non-AI languages makes it possible to put Prolog calls inside DO loops and similar control constructs. The resulting merger of non-AI and AI languages thus results in a symbiotic system in which the advantages of both programming systems are retained, and their deficiencies largely remedied.

A Complete NMR Spectral Assignment of the Lipid-free Mouse Apolipoprotein A-I (ApoAI) C-terminal Truncation Mutant, ApoAI(1-216)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Yunhuang; Hoyt, David W.; Wang, Jianjun

2007-07-28

Apolipoprotein A-I (apoAI) is the major protein component of the high-density lipoprotein (HDL) that has been a hot subject of interests because of its anti-atherogenic properties. Upon lipid-binding, apoAI undergoes conformational changes from lipid-free to several different HDL-associated states (1). These different conformational states regulate HDL formation, maturation and transportation. Recent crystal structure of lipid-free human apoAI represents a major progress of structural study of lipid-free apoAI (2). However, no structural is available for lipid-free mouse apoAI (240-residues). Since mouse HDL is homogenous with only HDL2-like size, whereas human HDL is heterogeneous, containing HDL2/HDL3 as its main species, a structuralmore » comparison between human and mouse apoAI may allow us to identify structure basis of HDL size distribution difference between human and mouse. We carried out an NMR structure determination of lipid-free mouse apoAI (1-216) and completely assigned backbone atoms (except backbone amide proton and nitrogen atoms for residues D1, N48, W107, K108, K132, E135, F147, R148, M169 and K203). Secondary structure prediction using backbone NMR parameters indicates that lipid-free mouse apoAI consists of a four helical segments in the N-terminal domain, residues 1-180. In addition, two short helices are also observed between residues 190-195 and 210-215. The helix locations are significantly different from those in the crystal structure of human apoAI, suggesting that mouse apoAI may have a different conformational adaptation upon lipid-binding. BMRB deposit with accession number: 15091.« less

Diagnostic Accuracy of Perioperative Measurement of Basal Anterior Pituitary and Target Gland Hormones in Predicting Adrenal Insufficiency After Pituitary Surgery.

PubMed

Cerina, Vatroslav; Kruljac, Ivan; Radosevic, Jelena Marinkovic; Kirigin, Lora Stanka; Stipic, Darko; Pecina, Hrvoje Ivan; Vrkljan, Milan

2016-03-01

The insulin tolerance test (ITT) is the gold standard for diagnosing adrenal insufficiency (AI) after pituitary surgery. The ITT is unpleasant for patients, requires close medical supervision and is contraindicated in several comorbidities. The aim of this study was to analyze whether tumor size, remission rate, preoperative, and early postoperative baseline hormone concentrations could serve as predictors of AI in order to increase the diagnostic accuracy of morning serum cortisol. This prospective study enrolled 70 consecutive patients with newly diagnosed pituitary adenomas. Thirty-seven patients had nonfunctioning pituitary adenomas (NPA), 28 had prolactinomas and 5 had somatotropinomas. Thyroxin (T4), thyrotropin (TSH), prolactin, follicle-stimulating hormone (FSH), luteinizing hormone (LH), testosterone, and insulin-like growth factor 1 (IGF-I) were measured preoperatively and on the sixth postoperative day. Serum morning cortisol was measured on the third postoperative day (CORT3) as well as the sixth postoperative day (CORT6). Tumor mass was measured preoperatively and remission was assessed 3 months after surgery. An ITT was performed 3 to 6 months postoperatively. Remission was achieved in 48% of patients and AI occurred in 51%. Remission rates and tumor type were not associated with AI. CORT3 had the best predictive value for AI (area under the curve (AUC) 0.868, sensitivity 82.4%, specificity 83.3%). Tumor size, preoperative T4, postoperative T4, and TSH were also associated with AI in a multivariate regression model. A combination of all preoperative and postoperative variables (excluding serum cortisol) had a sensitivity of 75.0% and specificity of 77.8%. The predictive power of CORT3 substantially improved by adding those variables into the model (AUC 0.921, sensitivity 94.1%, specificity 78.3%, PPV 81.9%, NPV of 92.7%). In a subgroup analysis that included only female patients with NPA, LH had exactly the same predictive value as CORT3. The addition of baseline LH to CORT3, increased sensitivity to 100.0%, specificity to 88.9%, PPV to 90.4%, and NPV to 100.0%. Besides CORT3, tumor size, thyroid hormones, and gonadotropins can serve as predictors of AI. LH in postmenopausal female patients with NPA has similar diagnostic accuracy as CORT3. Further studies are needed in order to validate the scoring system proposed by this study.

Fertility prediction of frozen boar sperm using novel and conventional analyses

USDA-ARS?s Scientific Manuscript database

Frozen-thawed boar sperm is seldom used for artificial insemination (AI) because fertility is lower than fresh or cooled semen. Despite the many advantages of AI including reduced pathogen exposure and ease of semen transport, cryo-induced damage to sperm usually results in decreased litter sizes a...

Integrating Motivational Interviewing and Traditional Practices to Address Alcohol and Drug Use Among Urban American Indian/Alaska Native Youth.

PubMed

Dickerson, Daniel L; Brown, Ryan A; Johnson, Carrie L; Schweigman, Kurt; D'Amico, Elizabeth J

2016-06-01

American Indians/Alaska Natives (AI/AN) exhibit high levels of alcohol and drug (AOD) use and problems. Although approximately 70% of AI/ANs reside in urban areas, few culturally relevant AOD use programs targeting urban AI/AN youth exist. Furthermore, federally-funded studies focused on the integration of evidence-based treatments with AI/AN traditional practices are limited. The current study addresses a critical gap in the delivery of culturally appropriate AOD use programs for urban AI/AN youth, and outlines the development of a culturally tailored AOD program for urban AI/AN youth called Motivational Interviewing and Culture for Urban Native American Youth (MICUNAY). We conducted focus groups among urban AI/AN youth, providers, parents, and elders in two urban communities in northern and southern California aimed at 1) identifying challenges confronting urban AI/AN youth and 2) obtaining feedback on MICUNAY program content. Qualitative data were analyzed using Dedoose, a team-based qualitative and mixed methods analysis software platform. Findings highlight various challenges, including community stressors (e.g., gangs, violence), shortage of resources, cultural identity issues, and a high prevalence of AOD use within these urban communities. Regarding MICUNAY, urban AI/AN youth liked the collaborative nature of the motivational interviewing (MI) approach, especially with regard to eliciting their opinions and expressing their thoughts. Based on feedback from the youth, three AI/AN traditional practices (beading, AI/AN cooking, and prayer/sage ceremony) were chosen for the workshops. To our knowledge, MICUNAY is the first AOD use prevention intervention program for urban AI/AN youth that integrates evidence-based treatment with traditional practices. This program addresses an important gap in services for this underserved population. Copyright © 2015. Published by Elsevier Inc.

Integrating motivational interviewing and traditional practices to address alcohol and drug use among urban American Indian/Alaska Native youth

PubMed Central

Dickerson, Daniel L.; Brown, Ryan A.; Johnson, Carrie L.; Schweigman, Kurt; D’Amico, Elizabeth J.

2015-01-01

American Indians/Alaska Natives (AI/AN) exhibit high levels of alcohol and drug (AOD) use and problems. Although approximately 70% of AI/ANs reside in urban areas, few culturally relevant AOD use programs targeting urban AI/AN youth exist. Furthermore, federally-funded studies focused on the integration of evidence-based treatments with AI/AN traditional practices are limited. The current study addresses a critical gap in the delivery of culturally appropriate AOD use programs for urban AI/AN youth, and outlines the development of a culturally tailored AOD program for urban AI/AN youth called Motivational Interviewing and Culture for Urban Native American Youth (MICUNAY). We conducted focus groups among urban AI/AN youth, providers, parents, and elders in two urban communities in northern and southern California aimed at 1) identifying challenges confronting urban AI/AN youth and 2) obtaining feedback on MICUNAY program content. Qualitative data were analyzed using Dedoose, a team-based qualitative and mixed methods analysis software platform. Findings highlight various challenges, including community stressors (e.g., gangs, violence), shortage of resources, cultural identity issues, and a high prevalence of AOD use within these urban communities. Regarding MICUNAY, urban AI/AN youth liked the collaborative nature of the motivational interviewing (MI) approach, especially with regard to eliciting their opinions and expressing their thoughts. Based on feedback from the youth, three AI/AN traditional practices (beading, AI/AN cooking, and prayer/sage ceremony) were chosen for the workshops. MICUNAY is the first AOD use prevention intervention program for urban AI/AN youth that integrates evidence-based treatment with traditional practices. This program addresses an important gap in services for this underserved population. PMID:26306776

Impact of the version of the abbreviated injury scale on injury severity characterization and quality assessment of trauma care.

PubMed

Tohira, Hideo; Jacobs, Ian; Matsuoka, Tetsuya; Ishikawa, Kazuo

2011-07-01

The Abbreviated Injury Scale (AIS) was updated in 2008 (AIS 2008). We aimed to investigate the impact of AIS 2008 on the characterization of injury severity and quality assessment of trauma care. We identified all blunt trauma patients in the Japan Trauma Data Bank. First, we converted AIS 98 codes to AIS 2008 codes using a mapping table. Next, we compared Injury Severity Scores (ISSs) and New ISSs (NISSs) based on AIS 98 and AIS 2008. We compared the proportion of major trauma (ISS >15) between the two AISs. We derived risk-adjusted models using the two AISs and separately ranked hospitals according to the observed-to-expected death (OE) ratio. We counted the number of performance outliers for the two rankings. We analyzed the association between the percent change in OE ratios and the proportion of NISS outliers (change in NISS of <-12). There were 19,899 subjects. The ISSs and NISSs based on AIS 2008 were significantly less than those based on AIS 98. The proportion of major trauma was 46.3% and 38.9% for AIS 98 and AIS 2008, respectively (p < 0.001). The numbers of performance outliers were different between the two rankings. There was a significant positive linear relationship between the percent change in the OE ratio and the proportion of NISS outliers. The use of different AIS versions influenced the selection of major trauma patients and affected the quality assessment of the trauma care. Researchers should be aware of these findings when selecting the version of the AIS.

Acromion Index in Korean Population and Its Relationship with Rotator Cuff Tears.

PubMed

Kum, Dong Ho; Kim, Jun Ho; Park, Keun Min; Lee, Eun Su; Park, Yong Bok; Yoo, Jae Chul

2017-06-01

Among the many causes of rotator cuff tears, scapular morphology is associated with the accelerating degenerative process of the rotator cuff. Acromion index (AI) was previously introduced and compared in two populations. We enrolled 100 Korean patients diagnosed with full-thickness rotator cuff tears by magnetic resonance imaging and intraoperative arthroscopic findings between January and December 2013. Another 100 Korean patients with an intact rotator cuff tendon identified on magnetic resonance imaging and other shoulder diseases, such as frozen shoulder and instability, were enrolled as controls. We retrospectively compared these 100 rotator cuff tear patients (mean age, 63 years) and 100 controls (mean age, 51 years) in this study. Two independent orthopedic surgeons assessed the AI on radiographs. We performed an interobserver reliability test of the AI assessment, and then compared the AI between two groups. The measurement of the AI showed excellent reliability (intraclass correlation coefficient, 0.82). The mean AI in the rotator cuff tear group was 0.68 and it was significantly different between groups ( p <0.001, 95% confidence interval). The AI was not related to tear size. Our study showed that the AI was an effective predictive factor for rotator cuff tears in a Korean population.

Validation of the Avoidance and Inflexibility Scale (AIS) among treatment-seeking smokers.

PubMed

Farris, Samantha G; Zvolensky, Michael J; DiBello, Angelo M; Schmidt, Norman B

2015-06-01

The Avoidance and Inflexibility Scale (AIS; Gifford et al., 2004) was derived as a smoking-specific measure of experiential avoidance. However, there has been little investigation of the psychometric proprieties of the AIS and no published work on the topic. The current study aimed to test the reliability and validity of the AIS among a sample of adult treatment-seeking daily smokers (n = 465; 48.2% female, 17.8 [SD = 9.60] cigarettes per day). The AIS was administered at 3 time points (baseline, quit-day, and 1 month postquit) as part of a larger smoking cessation trial. An exploratory factor analysis indicated a 2-factor solution, described by inflexibility and avoidance because of smoking related "thoughts/feelings" (9 items) and "somatic sensations" (4 items). Results revealed that the AIS-total and factor scores demonstrated high internal consistency and test-retest reliability. The AIS total and factor scores also displayed high convergent, discriminant, and incremental predictive validity with theoretically relevant smoking and affective variables. The present data suggest that the AIS measure appears to be a valid and reliable smoking-specific index of experiential avoidance. (c) 2015 APA, all rights reserved).

Validation of the Avoidance and Inflexibility Scale (AIS) among Treatment-Seeking Smoker

PubMed Central

Farris, Samantha G.; Zvolensky, Michael J.; DiBello, Angelo M.; Schmidt, Norman B.

2015-01-01

The Avoidance and Inflexibility Scale (AIS; Gifford et al., 2004) was derived as smoking-specific measure of experiential avoidance. However, there has been little investigation of the psychometric proprieties of the AIS and no published work on the topic. The current study aimed to test the reliability and validity of the AIS among a sample of adult treatment-seeking daily smokers (n = 465; 48.1% female, 17.8 [SD = 9.60] cigarettes per day). The AIS was administered at three time points (Baseline, Quit day, 1 month post-quit) as part of a larger smoking cessation trial. An exploratory factor analysis indicated a two-factor solution, described by inflexibility and avoidance due to smoking related “thoughts/feelings” (9 items) and “somatic sensations” (4 items). Results revealed that the AIS-total and factor scores demonstrated high internal consistency and test-retest reliability. The AIS total and factor scores also displayed high convergent, discriminant, and incremental predictive validity with theoretically-relevant smoking and affective variables. The present data suggest that the AIS measure appears to be a valid and reliable smoking-specific index of experiential avoidance. PMID:25642937

Combat injury coding: a review and reconfiguration.

PubMed

Lawnick, Mary M; Champion, Howard R; Gennarelli, Thomas; Galarneau, Michael R; D'Souza, Edwin; Vickers, Ross R; Wing, Vern; Eastridge, Brian J; Young, Lee Ann; Dye, Judy; Spott, Mary Ann; Jenkins, Donald H; Holcomb, John; Blackbourne, Lorne H; Ficke, James R; Kalin, Ellen J; Flaherty, Stephen

2013-10-01

The current civilian Abbreviated Injury Scale (AIS), designed for automobile crash injuries, yields important information about civilian injuries. It has been recognized for some time, however, that both the AIS and AIS-based scores such as the Injury Severity Score (ISS) are inadequate for describing penetrating injuries, especially those sustained in combat. Existing injury coding systems do not adequately describe (they actually exclude) combat injuries such as the devastating multi-mechanistic injuries resulting from attacks with improvised explosive devices (IEDs). After quantifying the inapplicability of current coding systems, the Military Combat Injury Scale (MCIS), which includes injury descriptors that accurately characterize combat anatomic injury, and the Military Functional Incapacity Scale (MFIS), which indicates immediate tactical functional impairment, were developed by a large tri-service military and civilian group of combat trauma subject-matter experts. Assignment of MCIS severity levels was based on urgency, level of care needed, and risk of death from each individual injury. The MFIS was developed based on the casualty's ability to shoot, move, and communicate, and comprises four levels ranging from "Able to continue mission" to "Lost to military." Separate functional impairments were identified for injuries aboard ship. Preliminary evaluation of MCIS discrimination, calibration, and casualty disposition was performed on 992 combat-injured patients using two modeling processes. Based on combat casualty data, the MCIS is a new, simpler, comprehensive severity scale with 269 codes (vs. 1999 in AIS) that specifically characterize and distinguish the many unique injuries encountered in combat. The MCIS integrates with the MFIS, which associates immediate combat functional impairment with minor and moderate-severity injuries. Predictive validation on combat datasets shows improved performance over AIS-based tools in addition to improved face, construct, and content validity and coding inter-rater reliability. Thus, the MCIS has greater relevance, accuracy, and precision for many military-specific applications. Over a period of several years, the Military Combat Injury Scale and Military Functional Incapacity Scale were developed, tested and validated by teams of civilian and tri-service military expertise. MCIS shows significant promise in documenting the nature, severity and complexity of modern combat injury.

Iron metabolism in critically ill patients developing anemia of inflammation: a case control study.

PubMed

Boshuizen, Margit; Binnekade, Jan M; Nota, Benjamin; van de Groep, Kirsten; Cremer, Olaf L; Tuinman, Pieter R; Horn, Janneke; Schultz, Marcus J; van Bruggen, Robin; Juffermans, Nicole P

2018-05-02

Anemia occurring as a result of inflammatory processes (anemia of inflammation, AI) has a high prevalence in critically ill patients. Knowledge on changes in iron metabolism during the course of AI is limited, hampering the development of strategies to counteract AI. This case control study aimed to investigate iron metabolism during the development of AI in critically ill patients. Iron metabolism in 30 patients who developed AI during ICU stay was compared with 30 septic patients with a high Hb and 30 non-septic patients with a high Hb. Patients were matched on age and sex. Longitudinally collected plasma samples were analyzed for levels of parameters of iron metabolism. A linear mixed model was used to assess the predictive values of the parameters. In patients with AI, levels of iron, transferrin and transferrin saturation showed an early decrease compared to controls with a high Hb, already prior to the development of anemia. Ferritin, hepcidin and IL-6 levels were increased in AI compared to controls. During AI development, erythroferrone decreased. Differences in iron metabolism between groups were not influenced by APACHE IV score. The results show that in critically ill patients with AI, iron metabolism is already altered prior to the development of anemia. Levels of iron regulators in AI differ from septic controls with a high Hb, irrespective of disease severity. AI is characterized by high levels of hepcidin, ferritin and IL-6 and low levels of iron, transferrin and erythroferrone.

Effect of early or late resynchronization based on different methods of pregnancy diagnosis on reproductive performance of dairy cows.

PubMed

Sinedino, L D P; Lima, F S; Bisinotto, R S; Cerri, R L A; Santos, J E P

2014-01-01

The aim of this study was to compare the reproductive performance of dairy cows subjected to early (ER) or late (LR) resynchronization programs after nonpregnancy diagnoses based on either pregnancy-associated glycoproteins (PAG) ELISA or transrectal palpation, respectively. In addition, the accuracy of the PAG ELISA for early pregnancy diagnosis was assessed. Lactating Holstein cows were subjected to a Presynch-Ovsynch protocol with timed artificial insemination (AI) performed between 61 and 74 DIM. On the day of the first postpartum AI, 1,093 cows were blocked by parity and assigned randomly to treatments; however, because of attrition, 452 ER and 520 LR cows were considered for the statistical analyses. After the first postpartum AI, cows were observed daily for signs of estrus and inseminated on the same day of detected estrus. Cows from ER that were not reinseminated in estrus received the first GnRH injection of the Ovsynch protocol for resynchronization 2d before pregnancy diagnosis. On d 28 after the previous AI (d 27 to 34), pregnancy status was determined by PAG ELISA, and nonpregnant cows continued on the Ovsynch protocol for reinsemination. Pregnant cows had pregnancy status reconfirmed on d 46 after AI (d 35 to 52) by transrectal palpation, and those that lost the pregnancies were resynchronized. Cows assigned to LR had pregnancy diagnosed by transrectal palpation on d 46 after AI (d 35 to 52) and nonpregnant cows were resynchronized with the Ovsynch protocol. Blood was sampled on d 28 after AI (d 27 to 34) from cows in both treatments that had not been reinseminated on estrus and again on d 46 after AI (d 35 to 52) for assessment of PAG ELISA to determine the accuracy of the test. Cows were subjected to treatments for 72d after the first insemination. Pregnancy per AI (P/AI) at first postpartum timed AI did not differ between treatments and averaged 28.9%. The proportion of nonpregnant cows that were resynchronized and received timed AI was greater for ER than for LR (30.0 vs. 7.6%). Cows in ER had a shorter interval between inseminations when inseminated following spontaneous estrus (21.7±1.1 vs. 27.8±0.8d) or after timed AI (35.3±1.2 vs. 55.2±1.4d). Nevertheless, the ER did not affect the rate of pregnancy (adjusted hazard ratio=1.23; 95% confidence interval=0.94 to 1.61) or the median days postpartum to pregnancy (ER=132 vs. LR=140). A total of 2,129 PAG ELISA were evaluated. Overall, sensitivity, specificity, and positive and negative predictive values averaged 95.1, 89.0, 90.1, and 94.5%, respectively, and the accuracy was 92.1%. In conclusion, PAG ELISA for early diagnosis of pregnancy had acceptable accuracy, but early resynchronization after nonpregnancy diagnosis with PAG ELISA did not improve the rate of pregnancy or reduce days open in dairy cows continuously observed for estrus. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

AI techniques in geomagnetic storm forecasting

NASA Astrophysics Data System (ADS)

Lundstedt, Henrik

This review deals with how geomagnetic storms can be predicted with the use of Artificial Intelligence (AI) techniques. Today many different Al techniques have been developed, such as symbolic systems (expert and fuzzy systems) and connectionism systems (neural networks). Even integrations of AI techniques exist, so called Intelligent Hybrid Systems (IHS). These systems are capable of learning the mathematical functions underlying the operation of non-linear dynamic systems and also to explain the knowledge they have learned. Very few such powerful systems exist at present. Two such examples are the Magnetospheric Specification Forecast Model of Rice University and the Lund Space Weather Model of Lund University. Various attempts to predict geomagnetic storms on long to short-term are reviewed in this article. Predictions of a month to days ahead most often use solar data as input. The first SOHO data are now available. Due to the high temporal and spatial resolution new solar physics have been revealed. These SOHO data might lead to a breakthrough in these predictions. Predictions hours ahead and shorter rely on real-time solar wind data. WIND gives us real-time data for only part of the day. However, with the launch of the ACE spacecraft in 1997, real-time data during 24 hours will be available. That might lead to the second breakthrough for predictions of geomagnetic storms.

Diagnostic classification of cancer using DNA microarrays and artificial intelligence.

PubMed

Greer, Braden T; Khan, Javed

2004-05-01

The application of artificial intelligence (AI) to microarray data has been receiving much attention in recent years because of the possibility of automated diagnosis in the near future. Studies have been published predicting tumor type, estrogen receptor status, and prognosis using a variety of AI algorithms. The performance of intelligent computing decisions based on gene expression signatures is in some cases comparable to or better than the current clinical decision schemas. The goal of these tools is not to make clinicians obsolete, but rather to give clinicians one more tool in their armamentarium to accurately diagnose and hence better treat cancer patients. Several such applications are summarized in this chapter, and some of the common pitfalls are noted.

The exponential function transforms the Abbreviated Injury Scale, which both improves accuracy and simplifies scoring.

PubMed

Wang, M D; Fan, W H; Qiu, W S; Zhang, Z L; Mo, Y N; Qiu, F

2014-06-01

We present here the exponential function which transforms the Abbreviated Injury Scale (AIS). It is called the Exponential Injury Severity Score (EISS), and significantly outperforms the venerable but dated New Injury Severity Score (NISS) and Injury Severity Score (ISS) as a predictor of mortality. The EISS is defined as a change of AIS values by raising each AIS severity score (1-6) by 3 taking a power of AIS minus 2 and then summing the three most severe injuries (i.e., highest AIS), regardless of body regions. EISS values were calculated for every patient in two large independent data sets: 3,911 and 4,129 patients treated during a 6-year period at the Class A tertiary hospitals in China. The power of the EISS to predict mortality was then compared with previously calculated NISS values for the same patients in each of the two data sets. We found that the EISS is more predictive of survival [Zhejiang: area under the receiver operating characteristic curve (AUC): NISS = 0.932, EISS = 0.949, P = 0.0115; Liaoning: AUC: NISS = 0.924, EISS = 0.942, P = 0.0139]. Moreover, the EISS provides a better fit throughout its entire range of prediction (Hosmer-Lemeshow statistic for Zhejiang: NISS = 21.86, P = 0.0027, EISS = 13.52, P = 0.0604; Liaoning: NISS = 23.27, P = 0.0015, EISS = 15.55, P = 0.0164). The EISS may be used as the standard summary measure of human trauma.

Artificial intelligence: A joint narrative on potential use in pediatric stem and immune cell therapies and regenerative medicine.

PubMed

Sniecinski, Irena; Seghatchian, Jerard

2018-05-09

Artificial Intelligence (AI) reflects the intelligence exhibited by machines and software. It is a highly desirable academic field of many current fields of studies. Leading AI researchers describe the field as "the study and design of intelligent agents". McCarthy invented this term in 1955 and defined it as "the science and engineering of making intelligent machines". The central goals of AI research are reasoning, knowledge, planning, learning, natural language processing (communication), perception and the ability to move and manipulate objects. In fact the multidisplinary AI field is considered to be rather interdisciplinary covering numerous number of sciences and professions, including computer science, psychology, linguistics, philosophy and neurosciences. The field was founded on the claim that a central intellectual property of humans, intelligence-the sapience of Homo Sapiens "can be so precisely described that a machine can be made to simulate it". This raises philosophical issues about the nature of the mind and the ethics of creating artificial beings endowed with human-like intelligence. Artificial Intelligence has been the subject of tremendous optimism but has also suffered stunning setbacks. The goal of this narrative is to review the potential use of AI approaches and their integration into pediatric cellular therapies and regenerative medicine. Emphasis is placed on recognition and application of AI techniques in the development of predictive models for personalized treatments with engineered stem cells, immune cells and regenerated tissues in adults and children. These intelligent machines could dissect the whole genome and isolate the immune particularities of individual patient's disease in a matter of minutes and create the treatment that is customized to patient's genetic specificity and immune system capability. AI techniques could be used for optimization of clinical trials of innovative stem cell and gene therapies in pediatric patients by precise planning of treatments, predicting clinical outcomes, simplifying recruitment and retention of patients, learning from input data and applying to new data, thus lowering their complexity and costs. Complementing human intelligence with machine intelligence could have an exponentially high impact on continual progress in many fields of pediatrics. However how long before we could see the real impact still remains the big question. The most pertinent question that remains to be answered therefore, is can AI effectively and accurately predict properties of newer DDR strategies? The goal of this article is to review the use of AI method for cellular therapy and regenerative medicine and emphasize its potential to further the progress in these fields of medicine. Copyright © 2018. Published by Elsevier Ltd.

Proper coding of the Abbreviated Injury Scale: can clinical parameters help as surrogates in estimating blood loss?

PubMed

Burkhardt, M; Holstein, J H; Moersdorf, P; Kristen, A; Lefering, R; Pohlemann, T; Pizanis, A

2014-08-01

The Abbreviated Injury Scale (AIS) requires the estimation of the lost blood volume for some severity assignments. This study aimed to develop a rule of thumb for facilitating AIS coding by using objective clinical parameters as surrogate markers of blood loss. Using the example of pelvic ring fractures, a retrospective analysis of TraumaRegister DGU(®) data from 2002 to 2011 was performed. As potential surrogate markers of blood loss, we recorded the hemoglobin (Hb) level, systolic blood pressure (SBP), base excess (BE), Quick's value, units of packed red blood cells (PRBCs) transfused before intensive care unit (ICU) admission, and mortality within 24 h. We identified 11,574 patients with pelvic ring fractures (Tile/OTA classification: 39 % type A, 40 % type B, 21 % type C). Type C fractures were 73.1 % AISpelvis 4 and 26.9 % AISpelvis 5. Type B fractures were 47 % AISpelvis 3, 47 % AISpelvis 4, and 6 % AISpelvis 5. In type C fractures, cut-off values of <7 g/dL Hb, <90 mmHg SBP, <-9 mmol/L BE, <35 % Quick's value, >15 units PRBCs, and death within 24 h had a positive predictive value of 47 % and a sensitivity of 62 % for AISpelvis 5. In type B fractures, these cut-off values had poor sensitivity (48 %) and positive predictive value (11 %) for AISpelvis 5. We failed to develop a rule of thumb for facilitating a proper future AIS coding using the example of pelvic ring fractures. The estimation of blood loss for severity assignment still remains a noteworthy weakness in the AIS coding of traumatic injuries.

Literature and Product Review of Visual Analytics for Maritime Awareness

DTIC Science & Technology

2009-10-28

the user’s knowledge and experience. • Riveiro et al [107] provide a useful discussion of the cognitive process of anomaly detection based on...changes over time can be seen visually. • Wilkinson et al [140] suggests that we need visual analytics for three principal purposes: checking raw data...Predictions within the Current Plot • Yue et al [146] describe an AI blackboard-based agent that leverages interactive visualization and mixed

Extracurricular activity availability and participation and substance use among American Indian adolescents.

PubMed

Moilanen, Kristin L; Markstrom, Carol A; Jones, Elizabeth

2014-03-01

School-based extracurricular activity involvement has been associated with lower levels of substance use among adolescents from various populations; however, these associations have only been slightly examined among American Indian (AI) adolescents. Building from various theoretical perspectives, it was hypothesized that AI adolescents' perceived access to and the intensity (i.e., frequency) of participation in extracurricular activities would be associated with lower substance use and less engagement in risky substance use behaviors (i.e., being drunk or high at school, riding/driving with an intoxicated driver, and selling drugs). The moderating influences of sex, age, reservation residence, and metropolitan status also were examined. Data from the 2010 Arizona Youth Survey were analyzed for 5,701 8th, 10th, and 12th grade AI adolescents (49.1% female). The expected protective effects of extracurricular participation were demonstrated, such that high levels of perceived availability and intensity of participation consistently predicted low levels of all outcomes. Some of these associations were moderated by one or more demographic factors, with unique patterns emerging for each behavior. Ultimately, the findings suggest that AI adolescents benefit from the availability of extracurricular activities and intensity of participation in them, but the degree of the effect is contingent upon other individual and contextual characteristics.

Integration of SAR and AIS for ship detection and identification

NASA Astrophysics Data System (ADS)

Yang, Chan-Su; Kim, Tae-Ho

2012-06-01

This abstract describes the preliminary design concept for an integration system of SAR and AIS data. SAR sensors are used to acquire image data over large coverage area either through the space borne or airborne platforms in UTC. AIS reports should also obtained on the same date as of the SAR acquisition for the purpose to perform integration test. Once both data reports are obtained, one need to match the timings of AIS data acquisition over the SAR image acquisition time with consideration of local time & boundary to extract the closest time signal from AIS report in order to know the AIS based ship positions, but still one cannot be able to distinguish which ships have the AIS transponder after projection of AIS based position onto the SAR image acquisition boundary. As far as integration is concerned, the ship dead-reckoning concept is most important forecasted position which provides the AIS based ship position at the time of SAR image acquisition and also provides the hints for azimuth shift which occurred in SAR image for the case of moving ships which moves in the direction perpendicular to the direction of flight path. Unknown ship's DR estimation is to be carried out based on the initial positions, speed and course over ground, which has already been shorted out from AIS reports, during the step of time matching. This DR based ship's position will be the candidate element for searching the SAR based ship targets for the purpose of identification & matching within the certain boundary around DR. The searching method is performed by means of estimation of minimum distance from ship's DR to SAR based ship position, and once it determines, so the candidate element will look for matching like ship size match of DR based ship's dimension wrt SAR based ship's edge, there may be some error during the matching with SAR based ship edges with actual ship's hull design as per the longitudinal and transverse axis size information obtained from the AIS reports due to blurring effect in SAR based ship signatures, once the conditions are satisfied, candidate element will move & shift over the SAR based ship signature target with the minimum displacement and it is known to be the azimuth shift compensation and this overall methodology are known to be integration of AIS report data over the SAR image acquisition boundary with assessment of time matching. The expected result may provide the good accuracy of the SAR and AIS contact position along with dimension and classification of ships over SAR image. There may be possibilities of matching speed and course from candidate element with SAR based ship signature, but still the challenges are presents in front of us that to estimation of speed and course by means of SAR data, if it may be possible so the expected final result may be more accurate as due to extra matching effects and the results may be used for the near real time performance for ship identification with help of integrated system design based on SAR and AIS data reports.

Performance of the Hack's Impairment Index Score: A Novel Tool to Assess Impairment from Alcohol in Emergency Department Patients.

PubMed

Hack, Jason B; Goldlust, Eric J; Ferrante, Dennis; Zink, Brian J

2017-10-01

Over 35 million alcohol-impaired (AI) patients are cared for in emergency departments (EDs) annually. Emergency physicians are charged with ensuring AI patients' safety by identifying resolution of alcohol-induced impairment. The most common standard evaluation is an extemporized clinical examination, as ethanol levels are not reliable or predictive of clinical symptoms. There is no standard assessment of ED AI patients. The objective was to evaluate a novel standardized ED assessment of alcohol impairment, Hack's Impairment Index (HII score), in a busy urban ED. A retrospective chart review was performed for all AI patients seen in our busy urban ED over 24 months. Trained nurses evaluated AI patients with both "usual" and HII score every 2 hours. Patients were stratified by frequency of visits for AI during this time: high (≥ 6), medium (2-5), and low (1). Within each category, comparisons were made between HII scores, measured ethanol levels, and usual nursing assessment of AI. Changes in HII scores over time were also evaluated. A total of 8,074 visits from 3,219 unique patients were eligible for study, including 7,973 (98.7%) with ethanol levels, 5,061 (62.7%) with complete HII scores, and 3,646 (45.2%) with health care provider assessments. Correlations between HII scores and ethanol levels were poor (Pearson's R 2  = 0.09, 0.09, and 0.17 for high-, medium-, and low-frequency strata). HII scores were excellent at discriminating nursing assessment of AI, while ethanol levels were less effective. Omitting extrema, HII scores fell consistently an average 0.062 points per hour, throughout patients' visits. The HII score applied a quantitative, objective assessment of alcohol impairment. HII scores were superior to ethanol levels as an objective clinical measure of impairment. The HII declines in a reasonably predictable manner over time, with serial evaluations corresponding well with health care provider evaluations. © 2017 by the Society for Academic Emergency Medicine.

Whither the etiopathogenesis (and scoliogeny) of adolescent idiopathic scoliosis? Incorporating presentations on scoliogeny at the 2012 IRSSD and SRS meetings

PubMed Central

2013-01-01

This paper aims to integrate into current understanding of AIS causation, etiopathogenetic information presented at two Meetings during 2012 namely, the International Research Society of Spinal Deformities (IRSSD) and the Scoliosis Research Society (SRS). The ultimate hope is to prevent the occurrence or progression of the spinal deformity of AIS with non-invasive treatment, possibly medical. This might be attained by personalised polymechanistic preventive therapy targeting the appropriate etiology and/or etiopathogenetic pathways, to avoid fusion and maintain spinal mobility. Although considerable progress had been made in the past two decades in understanding the etiopathogenesis of adolescent idiopathic scoliosis (AIS), it still lacks an agreed theory of etiopathogenesis. One problem may be that AIS results not from one cause, but several that interact with various genetic predisposing factors. There is a view there are two other pathogenic processes for idiopathic scoliosis namely, initiating (or inducing), and those that cause curve progression. Twin studies and observations of family aggregation have revealed significant genetic contributions to idiopathic scoliosis, that place AIS among other common disease or complex traits with a high heritability interpreted by the genetic variant hypothesis of disease. We summarize etiopathogenetic knowledge of AIS as theories of pathogenesis including recent multiple concepts, and blood tests for AIS based on predictive biomarkers and genetic variants that signify disease risk. There is increasing evidence for the possibility of an underlying neurological disorder for AIS, research which holds promise. Like brain research, most AIS workers focus on their own corner and there is a need for greater integration of research effort. Epigenetics, a relatively recent field, evaluates factors concerned with gene expression in relation to environment, disease, normal development and aging, with a complex regulation across the genome during the first decade of life. Research on the role of environmental factors, epigenetics and chronic non-communicable diseases (NCDs) including adiposity, after a slow start, has exploded in the last decade. Not so for AIS research and the environment where, except for monozygotic twin studies, there are only sporadic reports to suggest that environmental factors are at work in etiology. Here, we examine epigenetic concepts as they may relate to human development, normal life history phases and AIS pathogenesis. Although AIS is not regarded as an NCD, like them, it is associated with whole organism metabolic phenomena, including lower body mass index, lower circulating leptin levels and other systemic disorders. Some epigenetic research applied to Silver-Russell syndrome and adiposity is examined, from which suggestions are made for consideration of AIS epigenetic research, cross-sectional and longitudinal. The word scoliogeny is suggested to include etiology, pathogenesis and pathomechanism. PMID:23448588

Groundhog Day for Medical Artificial Intelligence.

PubMed

London, Alex John

2018-05-01

Following a boom in investment and overinflated expectations in the 1980s, artificial intelligence entered a period of retrenchment known as the "AI winter." With advances in the field of machine learning and the availability of large datasets for training various types of artificial neural networks, AI is in another cycle of halcyon days. Although medicine is particularly recalcitrant to change, applications of AI in health care have professionals in fields like radiology worried about the future of their careers and have the public tittering about the prospect of soulless machines making life-and-death decisions. Medicine thus appears to be at an inflection point-a kind of Groundhog Day on which either AI will bring a springtime of improved diagnostic and predictive practices or the shadow of public and professional fear will lead to six more metaphorical weeks of winter in medical AI. © 2018 The Hastings Center.

Performance of International Classification of Diseases-based injury severity measures used to predict in-hospital mortality: A systematic review and meta-analysis.

PubMed

Gagné, Mathieu; Moore, Lynne; Beaudoin, Claudia; Batomen Kuimi, Brice Lionel; Sirois, Marie-Josée

2016-03-01

The International Classification of Diseases (ICD) is the main classification system used for population-based injury surveillance activities but does not contain information on injury severity. ICD-based injury severity measures can be empirically derived or mapped, but no single approach has been formally recommended. This study aimed to compare the performance of ICD-based injury severity measures to predict in-hospital mortality among injury-related admissions. A systematic review and a meta-analysis were conducted. MEDLINE, EMBASE, and Global Health databases were searched from their inception through September 2014. Observational studies that assessed the performance of ICD-based injury severity measures to predict in-hospital mortality and reported discriminative ability using the area under a receiver operating characteristic curve (AUC) were included. Metrics of model performance were extracted. Pooled AUC were estimated under random-effects models. Twenty-two eligible studies reported 72 assessments of discrimination on ICD-based injury severity measures. Reported AUC ranged from 0.681 to 0.958. Of the 72 assessments, 46 showed excellent (0.80 ≤ AUC < 0.90) and 6 outstanding (AUC ≥ 0.90) discriminative ability. Pooled AUC for ICD-based Injury Severity Score (ICISS) based on the product of traditional survival proportions was significantly higher than measures based on ICD mapped to Abbreviated Injury Scale (AIS) scores (0.863 vs. 0.825 for ICDMAP-ISS [p = 0.005] and ICDMAP-NISS [p = 0.016]). Similar results were observed when studies were stratified by the type of data used (trauma registry or hospital discharge) or the provenance of survival proportions (internally or externally derived). However, among studies published after 2003 the Trauma Mortality Prediction Model based on ICD-9 codes (TMPM-9) demonstrated superior discriminative ability than ICISS using the product of traditional survival proportions (0.850 vs. 0.802, p = 0.002). Models generally showed poor calibration. ICISS using the product of traditional survival proportions and TMPM-9 predict mortality more accurately than those mapped to AIS codes and should be preferred for describing injury severity when ICD is used to record injury diagnoses. Systematic review and meta-analysis, level III.

Traumatic brain injury: It is all about definition.

PubMed

Savitsky, B; Givon, A; Rozenfeld, M; Radomislensky, I; Peleg, K

2016-01-01

TBI may be defined by different methods. Some may be most useful for immediate clinical purposes, however less optimal for epidemiologic research. Other methods, such as the Abbreviated Injury Score (AIS), may prove more beneficial for this task, if the cut-off-points for their categories are defined correctly. To reveal the optimal cut-off-points for AIS in definition of severity of TBI in order to ensure uniformity between future studies of TBI. Mortality of patients with TBI AIS 3, 4 was 1.9% and 2.9% respectively, comparing with 31.1% among TBI AIS 5+. Predictive discrimination ability of the model with cut-off-points of 5+ for TBI AIS (in comparison with other cut-off-points) was better. Patients with missing Glasgow Coma Scale (GCS) in the ED had an in-hospital mortality rate of 11.5%. In this group, 25% had critical TBI according to AIS. Normal GCS didn't indicate an absence of head injury, as, among patients with GCS 15 in the ED, 26% had serious/critical TBI injury. Moreover, 7% of patients with multiple injury and GCS 3-8 had another reason than head injury for unconsciousness. This study recommends the adoption of an AIS cut-off ≥ 5 as a valid definition of severe TBI in epidemiological studies, while AIS 3-4 may be defined as 'moderate' TBI and AIS 1-2 as 'mild'.

A cognitive approach to game usability and design: mental model development in novice real-time strategy gamers.

PubMed

Graham, John; Zheng, Liya; Gonzalez, Cleotilde

2006-06-01

We developed a technique to observe and characterize a novice real-time-strategy (RTS) player's mental model as it shifts with experience. We then tested this technique using an off-the-shelf RTS game, EA Games Generals. Norman defined mental models as, "an internal representation of a target system that provides predictive and explanatory power to the operator." In the case of RTS games, the operator is the player and the target system is expressed by the relationships within the game. We studied five novice participants in laboratory-controlled conditions playing a RTS game. They played Command and Conquer Generals for 2 h per day over the course of 5 days. A mental model analysis was generated using player dissimilarity-ratings of the game's artificial intelligence (AI) agents analyzed using multidimensional scaling (MDS) statistical methods. We hypothesized that novices would begin with an impoverished model based on the visible physical characteristics of the game system. As they gained experience and insight, their mental models would shift and accommodate the functional characteristics of the AI agents. We found that all five of the novice participants began with the predicted physical-based mental model. However, while their models did qualitatively shift with experience, they did not necessarily change to the predicted functional-based model. This research presents an opportunity for the design of games that are guided by shifts in a player's mental model as opposed to the typical progression through successive performance levels.

Usefulness of Time-Point Serum Cortisol and ACTH Measurements for the Adjustment of Glucocorticoid Replacement in Adrenal Insufficiency.

PubMed

Rousseau, Elise; Joubert, Michael; Trzepla, Géraldine; Parienti, Jean Jacques; Freret, Thomas; Vanthygem, Marie Christine; Desailloud, Rachel; Lefebvre, Hervé; Coquerel, Antoine; Reznik, Yves

2015-01-01

Adjustment of daily hydrocortisone dose on clinical criteria lacks sensitivity for fine tuning. Long term hydrocortisone (HC) over-replacement may lead to increased morbidity and mortality in patients with adrenal insufficiency (AI). Biochemical criteria may help detecting over- or under-replacement but have been poorly evaluated. Multicenter, institutional, pharmacokinetic study on ACTH and cortisol plasma profiles during HC replacement in 27 AI patients compared to 29 matched controls. All AI patients were administered HC thrice daily at doses of 6, 10 and 14 mg/m2/d. Blood samples were drawn hourly from 0800h to 1900h. The main outcome measures were: i) plasma peak cortisol and cortisol area under the curve (AUC) in AI patients compared to controls, ii) correlations between cortisol AUC vs single-point cortisol or ACTH decrease from baseline (ΔACTH) and iii) the predictive value of the two latters for obtaining AI patients' cortisol AUC in the control range. Cortisol peaks were observed 1h after each HC intake and a dose response was demonstrated for cortisol peak and cortisol AUC. The comparison of AI patients' cortisol AUC to controls showed that 81.5% AI patients receiving 6mg/m2/d were adequately replaced, whereas most patients receiving higher doses were over-replaced. The correlation coefficient between 1000h/1400h cortisol concentrations and 0800-1900h cortisol AUC were 0.93/0.88 respectively, whereas the 0800-1200h ΔACTH fairly correlated with 0800-1900h cortisol AUC (R = 0.57). ROC curve analysis indicated that the 1000h and 1400h cortisol concentrations best predicted over-replacement. Patients receiving a 6mg/m2 hydrocortisone daily dose exhibited the most physiological daytime cortisol profile. Single point plasma cortisol correlated with daytime cortisol AUC in AI patients. Although hydrocortisone dose should be currently determined on clinical grounds, our data suggest that single point plasma cortisol may be an adjunct for further hydrocortisone dose adjustment in AI patients.

Usefulness of Time-Point Serum Cortisol and ACTH Measurements for the Adjustment of Glucocorticoid Replacement in Adrenal Insufficiency

PubMed Central

Trzepla, Géraldine; Parienti, Jean Jacques; Freret, Thomas; Vanthygem, Marie Christine; Desailloud, Rachel; Lefebvre, Hervé; Coquerel, Antoine; Reznik, Yves

2015-01-01

Background Adjustment of daily hydrocortisone dose on clinical criteria lacks sensitivity for fine tuning. Long term hydrocortisone (HC) over-replacement may lead to increased morbidity and mortality in patients with adrenal insufficiency (AI). Biochemical criteria may help detecting over- or under-replacement but have been poorly evaluated. Methods Multicenter, institutional, pharmacokinetic study on ACTH and cortisol plasma profiles during HC replacement in 27 AI patients compared to 29 matched controls. All AI patients were administered HC thrice daily at doses of 6, 10 and 14 mg/m2/d. Blood samples were drawn hourly from 0800h to 1900h. The main outcome measures were: i) plasma peak cortisol and cortisol area under the curve (AUC) in AI patients compared to controls, ii) correlations between cortisol AUC vs single-point cortisol or ACTH decrease from baseline (ΔACTH) and iii) the predictive value of the two latters for obtaining AI patients’ cortisol AUC in the control range. Results Cortisol peaks were observed 1h after each HC intake and a dose response was demonstrated for cortisol peak and cortisol AUC. The comparison of AI patients’ cortisol AUC to controls showed that 81.5% AI patients receiving 6mg/m2/d were adequately replaced, whereas most patients receiving higher doses were over-replaced. The correlation coefficient between 1000h/1400h cortisol concentrations and 0800-1900h cortisol AUC were 0.93/0.88 respectively, whereas the 0800-1200h ΔACTH fairly correlated with 0800-1900h cortisol AUC (R = 0.57). ROC curve analysis indicated that the 1000h and 1400h cortisol concentrations best predicted over-replacement. Conclusions Patients receiving a 6mg/m2 hydrocortisone daily dose exhibited the most physiological daytime cortisol profile. Single point plasma cortisol correlated with daytime cortisol AUC in AI patients. Although hydrocortisone dose should be currently determined on clinical grounds, our data suggest that single point plasma cortisol may be an adjunct for further hydrocortisone dose adjustment in AI patients. PMID:26317782

Assessment of the effects and limitations of the 1998 to 2008 Abbreviated Injury Scale map using a large population-based dataset.

PubMed

Palmer, Cameron S; Franklyn, Melanie

2011-01-07

Trauma systems should consistently monitor a given trauma population over a period of time. The Abbreviated Injury Scale (AIS) and derived scores such as the Injury Severity Score (ISS) are commonly used to quantify injury severities in trauma registries. To reflect contemporary trauma management and treatment, the most recent version of the AIS (AIS08) contains many codes which differ in severity from their equivalents in the earlier 1998 version (AIS98). Consequently, the adoption of AIS08 may impede comparisons between data coded using different AIS versions. It may also affect the number of patients classified as major trauma. The entire AIS98-coded injury dataset of a large population based trauma registry was retrieved and mapped to AIS08 using the currently available AIS98-AIS08 dictionary map. The percentage of codes which had increased or decreased in severity, or could not be mapped, was examined in conjunction with the effect of these changes to the calculated ISS. The potential for free text information accompanying AIS coding to improve the quality of AIS mapping was explored. A total of 128280 AIS98-coded injuries were evaluated in 32134 patients, 15471 patients of whom were classified as major trauma. Although only 4.5% of dictionary codes decreased in severity from AIS98 to AIS08, this represented almost 13% of injuries in the registry. In 4.9% of patients, no injuries could be mapped. ISS was potentially unreliable in one-third of patients, as they had at least one AIS98 code which could not be mapped. Using AIS08, the number of patients classified as major trauma decreased by between 17.3% and 30.3%. Evaluation of free text descriptions for some injuries demonstrated the potential to improve mapping between AIS versions. Converting AIS98-coded data to AIS08 results in a significant decrease in the number of patients classified as major trauma. Many AIS98 codes are missing from the existing AIS map, and across a trauma population the AIS08 dataset estimates which it produces are of insufficient quality to be used in practice. However, it may be possible to improve AIS98 to AIS08 mapping to the point where it is useful to established registries.

Assessment of the effects and limitations of the 1998 to 2008 Abbreviated Injury Scale map using a large population-based dataset

PubMed Central

2011-01-01

Background Trauma systems should consistently monitor a given trauma population over a period of time. The Abbreviated Injury Scale (AIS) and derived scores such as the Injury Severity Score (ISS) are commonly used to quantify injury severities in trauma registries. To reflect contemporary trauma management and treatment, the most recent version of the AIS (AIS08) contains many codes which differ in severity from their equivalents in the earlier 1998 version (AIS98). Consequently, the adoption of AIS08 may impede comparisons between data coded using different AIS versions. It may also affect the number of patients classified as major trauma. Methods The entire AIS98-coded injury dataset of a large population based trauma registry was retrieved and mapped to AIS08 using the currently available AIS98-AIS08 dictionary map. The percentage of codes which had increased or decreased in severity, or could not be mapped, was examined in conjunction with the effect of these changes to the calculated ISS. The potential for free text information accompanying AIS coding to improve the quality of AIS mapping was explored. Results A total of 128280 AIS98-coded injuries were evaluated in 32134 patients, 15471 patients of whom were classified as major trauma. Although only 4.5% of dictionary codes decreased in severity from AIS98 to AIS08, this represented almost 13% of injuries in the registry. In 4.9% of patients, no injuries could be mapped. ISS was potentially unreliable in one-third of patients, as they had at least one AIS98 code which could not be mapped. Using AIS08, the number of patients classified as major trauma decreased by between 17.3% and 30.3%. Evaluation of free text descriptions for some injuries demonstrated the potential to improve mapping between AIS versions. Conclusions Converting AIS98-coded data to AIS08 results in a significant decrease in the number of patients classified as major trauma. Many AIS98 codes are missing from the existing AIS map, and across a trauma population the AIS08 dataset estimates which it produces are of insufficient quality to be used in practice. However, it may be possible to improve AIS98 to AIS08 mapping to the point where it is useful to established registries. PMID:21214906

Teaching AI Search Algorithms in a Web-Based Educational System

ERIC Educational Resources Information Center

Grivokostopoulou, Foteini; Hatzilygeroudis, Ioannis

2013-01-01

In this paper, we present a way of teaching AI search algorithms in a web-based adaptive educational system. Teaching is based on interactive examples and exercises. Interactive examples, which use visualized animations to present AI search algorithms in a step-by-step way with explanations, are used to make learning more attractive. Practice…

An Immune Agent for Web-Based AI Course

ERIC Educational Resources Information Center

Gong, Tao; Cai, Zixing

2006-01-01

To overcome weakness and faults of a web-based e-learning course such as Artificial Intelligence (AI), an immune agent was proposed, simulating a natural immune mechanism against a virus. The immune agent was built on the multi-dimension education agent model and immune algorithm. The web-based AI course was comprised of many files, such as HTML…

Evaluation of the field relevance of several injury risk functions.

PubMed

Prasad, Priya; Mertz, Harold J; Dalmotas, Danius J; Augenstein, Jeffrey S; Diggs, Kennerly

2010-11-01

An evaluation of the four injury risk curves proposed in the NHTSA NCAP for estimating the risk of AIS>= 3 injuries to the head, neck, chest and AIS>=2 injury to the Knee-Thigh-Hip (KTH) complex has been conducted. The predicted injury risk to the four body regions based on driver dummy responses in over 300 frontal NCAP tests were compared against those to drivers involved in real-world crashes of similar severity as represented in the NASS. The results of the study show that the predicted injury risks to the head and chest were slightly below those in NASS, and the predicted risk for the knee-thigh-hip complex was substantially below that observed in the NASS. The predicted risk for the neck by the Nij curve was greater than the observed risk in NASS by an order of magnitude due to the Nij risk curve predicting a non-zero risk when Nij = 0. An alternative and published Nte risk curve produced a risk estimate consistent with the NASS estimate of neck injury. Similarly, an alternative and published chest injury risk curve produced a risk estimate that was within the bounds of the NASS estimates. No published risk curve for femur compressive load could be found that would give risk estimates consistent with the range of the NASS estimates. Additional work on developing a femur compressive load risk curve is recommended.

Short-Term fo F2 Forecast: Present Day State of Art

NASA Astrophysics Data System (ADS)

Mikhailov, A. V.; Depuev, V. H.; Depueva, A. H.

An analysis of the F2-layer short-term forecast problem has been done. Both objective and methodological problems prevent us from a deliberate F2-layer forecast issuing at present. An empirical approach based on statistical methods may be recommended for practical use. A forecast method based on a new aeronomic index (a proxy) AI has been proposed and tested over selected 64 severe storm events. The method provides an acceptable prediction accuracy both for strongly disturbed and quiet conditions. The problems with the prediction of the F2-layer quiet-time disturbances as well as some other unsolved problems are discussed

Evolutionary Analysis Predicts Sensitive Positions of MMP20 and Validates Newly- and Previously-Identified MMP20 Mutations Causing Amelogenesis Imperfecta

PubMed Central

Gasse, Barbara; Prasad, Megana; Delgado, Sidney; Huckert, Mathilde; Kawczynski, Marzena; Garret-Bernardin, Annelyse; Lopez-Cazaux, Serena; Bailleul-Forestier, Isabelle; Manière, Marie-Cécile; Stoetzel, Corinne; Bloch-Zupan, Agnès; Sire, Jean-Yves

2017-01-01

Amelogenesis imperfecta (AI) designates a group of genetic diseases characterized by a large range of enamel disorders causing important social and health problems. These defects can result from mutations in enamel matrix proteins or protease encoding genes. A range of mutations in the enamel cleavage enzyme matrix metalloproteinase-20 gene (MMP20) produce enamel defects of varying severity. To address how various alterations produce a range of AI phenotypes, we performed a targeted analysis to find MMP20 mutations in French patients diagnosed with non-syndromic AI. Genomic DNA was isolated from saliva and MMP20 exons and exon-intron boundaries sequenced. We identified several homozygous or heterozygous mutations, putatively involved in the AI phenotypes. To validate missense mutations and predict sensitive positions in the MMP20 sequence, we evolutionarily compared 75 sequences extracted from the public databases using the Datamonkey webserver. These sequences were representative of mammalian lineages, covering more than 150 million years of evolution. This analysis allowed us to find 324 sensitive positions (out of the 483 MMP20 residues), pinpoint functionally important domains, and build an evolutionary chart of important conserved MMP20 regions. This is an efficient tool to identify new- and previously-identified mutations. We thus identified six functional MMP20 mutations in unrelated families, finding two novel mutated sites. The genotypes and phenotypes of these six mutations are described and compared. To date, 13 MMP20 mutations causing AI have been reported, making these genotypes and associated hypomature enamel phenotypes the most frequent in AI. PMID:28659819

Evolutionary Analysis Predicts Sensitive Positions of MMP20 and Validates Newly- and Previously-Identified MMP20 Mutations Causing Amelogenesis Imperfecta.

PubMed

Gasse, Barbara; Prasad, Megana; Delgado, Sidney; Huckert, Mathilde; Kawczynski, Marzena; Garret-Bernardin, Annelyse; Lopez-Cazaux, Serena; Bailleul-Forestier, Isabelle; Manière, Marie-Cécile; Stoetzel, Corinne; Bloch-Zupan, Agnès; Sire, Jean-Yves

2017-01-01

Amelogenesis imperfecta (AI) designates a group of genetic diseases characterized by a large range of enamel disorders causing important social and health problems. These defects can result from mutations in enamel matrix proteins or protease encoding genes. A range of mutations in the enamel cleavage enzyme matrix metalloproteinase-20 gene ( MMP20 ) produce enamel defects of varying severity. To address how various alterations produce a range of AI phenotypes, we performed a targeted analysis to find MMP20 mutations in French patients diagnosed with non-syndromic AI. Genomic DNA was isolated from saliva and MMP20 exons and exon-intron boundaries sequenced. We identified several homozygous or heterozygous mutations, putatively involved in the AI phenotypes. To validate missense mutations and predict sensitive positions in the MMP20 sequence, we evolutionarily compared 75 sequences extracted from the public databases using the Datamonkey webserver. These sequences were representative of mammalian lineages, covering more than 150 million years of evolution. This analysis allowed us to find 324 sensitive positions (out of the 483 MMP20 residues), pinpoint functionally important domains, and build an evolutionary chart of important conserved MMP20 regions. This is an efficient tool to identify new- and previously-identified mutations. We thus identified six functional MMP20 mutations in unrelated families, finding two novel mutated sites. The genotypes and phenotypes of these six mutations are described and compared. To date, 13 MMP20 mutations causing AI have been reported, making these genotypes and associated hypomature enamel phenotypes the most frequent in AI.

Fuzzy Cognitive Maps for Glacier Hazards Assessment: Application to Predicting the Potential for Glacier Lake Outbursts

NASA Astrophysics Data System (ADS)

Furfaro, R.; Kargel, J. S.; Fink, W.; Bishop, M. P.

2010-12-01

Glaciers and ice sheets are among the largest unstable parts of the solid Earth. Generally, glaciers are devoid of resources (other than water), are dangerous, are unstable and no infrastructure is normally built directly on their surfaces. Areas down valley from large alpine glaciers are also commonly unstable due to landslide potential of moraines, debris flows, snow avalanches, outburst floods from glacier lakes, and other dynamical alpine processes; yet there exists much development and human occupation of some disaster-prone areas. Satellite remote sensing can be extremely effective in providing cost-effective and time- critical information. Space-based imagery can be used to monitor glacier outlines and their lakes, including processes such as iceberg calving and debris accumulation, as well as changing thicknesses and flow speeds. Such images can also be used to make preliminary identifications of specific hazardous spots and allows preliminary assessment of possible modes of future disaster occurrence. Autonomous assessment of glacier conditions and their potential for hazards would present a major advance and permit systematized analysis of more data than humans can assess. This technical leap will require the design and implementation of Artificial Intelligence (AI) algorithms specifically designed to mimic glacier experts’ reasoning. Here, we introduce the theory of Fuzzy Cognitive Maps (FCM) as an AI tool for predicting and assessing natural hazards in alpine glacier environments. FCM techniques are employed to represent expert knowledge of glaciers physical processes. A cognitive model embedded in a fuzzy logic framework is constructed via the synergistic interaction between glaciologists and AI experts. To verify the effectiveness of the proposed AI methodology as applied to predicting hazards in glacier environments, we designed and implemented a FCM that addresses the challenging problem of autonomously assessing the Glacier Lake Outburst Flow Potential and Impound Water Upstream Flow Potential. The FCM is constructed using what is currently our understanding of how glacier lake outbursts occur, whereas the causal connection between concepts is defined to capture the expertise of glacier scientists. The proposed graph contains 27 nodes and a network of connections that represent the causal link between concepts. To test the developed FCM, we defined three scenarios representing glacier lake environmental conditions that either occurred or that are likely to occur in such highly dynamic environments. For each case, the FCM has been initialized using observables extracted from hypothesized remote sensing imagery. The map, which converges to a fixed point for all of the test scenarios within 15 iterations, shows reasoning consistent with that of glacier experts. The FCM-based cognitive approach has the potential to be the AI core of real-time operational hazards assessment and detection systems.

An Interoperable, Agricultural Information System Based on Satellite Remote Sensing Data

NASA Technical Reports Server (NTRS)

Teng, William; Chiu, Long; Doraiswamy, Paul; Kempler, Steven; Liu, Zhong; Pham, Long; Rui, Hualan

2005-01-01

Monitoring global agricultural crop conditions during the growing season and estimating potential seasonal production are critically important for market development of US. agricultural products and for global food security. The Goddard Space Flight Center Earth Sciences Data and Information Services Center Distributed Active Archive Center (GES DISC DAAC) is developing an Agricultural Information System (AIS), evolved from an existing TRMM Online Visualization and Analysis System (TOVAS), which will operationally provide satellite remote sensing data products (e.g., rainfall) and services. The data products will include crop condition and yield prediction maps, generated from a crop growth model with satellite data inputs, in collaboration with the USDA Agricultural Research Service. The AIS will enable the remote, interoperable access to distributed data, by using the GrADS-DODS Server (GDS) and by being compliant with Open GIS Consortium standards. Users will be able to download individual files, perform interactive online analysis, as well as receive operational data flows. AIS outputs will be integrated into existing operational decision support systems for global crop monitoring, such as those of the USDA Foreign Agricultural Service and the U.N. World Food Program.

Cross-Sectional Comparison of Executive Attention Function in Normally Aging Long-Term T'ai Chi, Meditation, and Aerobic Fitness Practitioners Versus Sedentary Adults

PubMed Central

Manselle, Wayne; Woollacott, Marjorie H.

2014-01-01

Abstract This cross-sectional field study documented the effect of long-term t'ai chi, meditation, or aerobic exercise training versus a sedentary lifestyle on executive function. It was predicted that long-term training in t'ai chi and meditation plus exercise would produce greater benefits to executive function than aerobic exercise. T'ai chi and meditation plus exercise include mental and physical training. Fifty-four volunteers were tested: t'ai chi (n=10); meditation+exercise (n=16); aerobic exercisers (n=16); and sedentary controls (n=12). A one-factor (group), one-covariate (age) multivariate analysis of covariance was performed. Significant main effects of group and age were found (group, 67.9%, p<0.001; age, 76.3%, p=0.001). T'ai chi and meditation practitioners but not aerobic exercisers outperformed sedentary controls on percent switch costs (p=0.001 and p=0.006, respectively), suggesting that there may be differential effects of training type on executive function. PMID:24286339

A NEW LOG EVALUATION METHOD TO APPRAISE MESAVERDE RE-COMPLETION OPPORTUNITIES

DOE Office of Scientific and Technical Information (OSTI.GOV)

Albert Greer

2003-09-11

Artificial intelligence tools, fuzzy logic and neural networks were used to evaluate the potential of the behind pipe Mesaverde formation in BMG's Mancos formation wells. A fractal geostatistical mapping algorithm was also used to predict Mesaverde production. Additionally, a conventional geological study was conducted. To date one Mesaverde completion has been performed. The Janet No.3 Mesaverde completion was non-economic. Both the AI method and the geostatistical methods predicted the failure of the Janet No.3. The Gavilan No.1 in the Mesaverde was completed during the course of the study and was an extremely good well. This well was not included inmore » the statistical dataset. The AI method predicted very good production while the fractal map predicted a poor producer.« less

TU-G-BRA-05: Predicting Volume Change of the Tumor and Critical Structures Throughout Radiation Therapy by CT-CBCT Registration with Local Intensity Correction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Park, S; Robinson, A; Kiess, A

2015-06-15

Purpose: The purpose of this study is to develop an accurate and effective technique to predict and monitor volume changes of the tumor and organs at risk (OARs) from daily cone-beam CTs (CBCTs). Methods: While CBCT is typically used to minimize the patient setup error, its poor image quality impedes accurate monitoring of daily anatomical changes in radiotherapy. Reconstruction artifacts in CBCT often cause undesirable errors in registration-based contour propagation from the planning CT, a conventional way to estimate anatomical changes. To improve the registration and segmentation accuracy, we developed a new deformable image registration (DIR) that iteratively corrects CBCTmore » intensities using slice-based histogram matching during the registration process. Three popular DIR algorithms (hierarchical B-spline, demons, optical flow) augmented by the intensity correction were implemented on a graphics processing unit for efficient computation, and their performances were evaluated on six head and neck (HN) cancer cases. Four trained scientists manually contoured nodal gross tumor volume (GTV) on the planning CT and every other fraction CBCTs for each case, to which the propagated GTV contours by DIR were compared. The performance was also compared with commercial software, VelocityAI (Varian Medical Systems Inc.). Results: Manual contouring showed significant variations, [-76, +141]% from the mean of all four sets of contours. The volume differences (mean±std in cc) between the average manual segmentation and four automatic segmentations are 3.70±2.30(B-spline), 1.25±1.78(demons), 0.93±1.14(optical flow), and 4.39±3.86 (VelocityAI). In comparison to the average volume of the manual segmentations, the proposed approach significantly reduced the estimation error by 9%(B-spline), 38%(demons), and 51%(optical flow) over the conventional mutual information based method (VelocityAI). Conclusion: The proposed CT-CBCT registration with local CBCT intensity correction can accurately predict the tumor volume change with reduced errors. Although demonstrated only on HN nodal GTVs, the results imply improved accuracy for other critical structures. This work was supported by NIH/NCI under grant R42CA137886.« less

Artificial Intelligence and Machine Learning in Radiology: Opportunities, Challenges, Pitfalls, and Criteria for Success.

PubMed

Thrall, James H; Li, Xiang; Li, Quanzheng; Cruz, Cinthia; Do, Synho; Dreyer, Keith; Brink, James

2018-03-01

Worldwide interest in artificial intelligence (AI) applications, including imaging, is high and growing rapidly, fueled by availability of large datasets ("big data"), substantial advances in computing power, and new deep-learning algorithms. Apart from developing new AI methods per se, there are many opportunities and challenges for the imaging community, including the development of a common nomenclature, better ways to share image data, and standards for validating AI program use across different imaging platforms and patient populations. AI surveillance programs may help radiologists prioritize work lists by identifying suspicious or positive cases for early review. AI programs can be used to extract "radiomic" information from images not discernible by visual inspection, potentially increasing the diagnostic and prognostic value derived from image datasets. Predictions have been made that suggest AI will put radiologists out of business. This issue has been overstated, and it is much more likely that radiologists will beneficially incorporate AI methods into their practices. Current limitations in availability of technical expertise and even computing power will be resolved over time and can also be addressed by remote access solutions. Success for AI in imaging will be measured by value created: increased diagnostic certainty, faster turnaround, better outcomes for patients, and better quality of work life for radiologists. AI offers a new and promising set of methods for analyzing image data. Radiologists will explore these new pathways and are likely to play a leading role in medical applications of AI. Copyright © 2017 American College of Radiology. Published by Elsevier Inc. All rights reserved.

METEOR - an artificial intelligence system for convective storm forecasting

DOE Office of Scientific and Technical Information (OSTI.GOV)

Elio, R.; De haan, J.; Strong, G.S.

1987-03-01

An AI system called METEOR, which uses the meteorologist's heuristics, strategies, and statistical tools to forecast severe hailstorms in Alberta, is described, emphasizing the information and knowledge that METEOR uses to mimic the forecasting procedure of an expert meteorologist. METEOR is then discussed as an AI system, emphasizing the ways in which it is qualitatively different from algorithmic or statistical approaches to prediction. Some features of METEOR's design and the AI techniques for representing meteorological knowledge and for reasoning and inference are presented. Finally, some observations on designing and implementing intelligent consultants for meteorological applications are made. 7 references.

Mortality-based Quantification of Injury Severity for Frequently Occurring Motor Vehicle Crash Injuries

PubMed Central

Weaver, Ashley A.; Barnard, Ryan T.; Kilgo, Patrick D.; Martin, R. Shayn; Stitzel, Joel D.

2013-01-01

The study purpose was to develop mortality-based metrics of injury severity for frequent motor vehicle crash (MVC) injuries. Injury severity was quantified with mortality-based metrics for 240 injuries comprising the top 95% most frequently occurring AIS 2+ injuries in the National Automotive Sampling System – Crashworthiness Data System (NASS-CDS) 2000–2011. Mortality risk ratios (MRRs) were computed by dividing the number of deaths by occurrences for each of the 240 injuries using National Trauma Data Bank Research Data System (NTDB-RDS) MVC cases. MRRMAIS was computed using only patients with a maximum AIS (MAIS) equal to the AIS severity of a given injury. Each injury had an associated MRR and MRRMAIS which ranged from zero (0% mortality representing low severity) to one (100% or universal mortality representing high severity). Injuries with higher MRR and MRRMAIS values are considered more severe because they resulted in a greater proportion of deaths among injured patients. The results illustrated an overall positive trend between AIS severity and the MRR and MRRMAIS values as expected, but showed large variations in MRR and MRRMAIS for some injuries of the same AIS severity. Mortality differences up to 83% (MRR) and 54% (MRRMAIS) were observed for injuries of the same AIS severity. The MRR-based measures of injury severity indicate that some lower AIS severity injuries may result in as many deaths as higher AIS severity injuries. This data-driven determination of injury severity using MRR and MRRMAIS provides a supplement or an alternative to AIS severity classification. PMID:24406961

Mortality-based Quantification of Injury Severity for Frequently Occurring Motor Vehicle Crash Injuries.

PubMed

Weaver, Ashley A; Barnard, Ryan T; Kilgo, Patrick D; Martin, R Shayn; Stitzel, Joel D

The study purpose was to develop mortality-based metrics of injury severity for frequent motor vehicle crash (MVC) injuries. Injury severity was quantified with mortality-based metrics for 240 injuries comprising the top 95% most frequently occurring AIS 2+ injuries in the National Automotive Sampling System - Crashworthiness Data System (NASS-CDS) 2000-2011. Mortality risk ratios (MRRs) were computed by dividing the number of deaths by occurrences for each of the 240 injuries using National Trauma Data Bank Research Data System (NTDB-RDS) MVC cases. MRRMAIS was computed using only patients with a maximum AIS (MAIS) equal to the AIS severity of a given injury. Each injury had an associated MRR and MRRMAIS which ranged from zero (0% mortality representing low severity) to one (100% or universal mortality representing high severity). Injuries with higher MRR and MRRMAIS values are considered more severe because they resulted in a greater proportion of deaths among injured patients. The results illustrated an overall positive trend between AIS severity and the MRR and MRRMAIS values as expected, but showed large variations in MRR and MRRMAIS for some injuries of the same AIS severity. Mortality differences up to 83% (MRR) and 54% (MRRMAIS) were observed for injuries of the same AIS severity. The MRR-based measures of injury severity indicate that some lower AIS severity injuries may result in as many deaths as higher AIS severity injuries. This data-driven determination of injury severity using MRR and MRRMAIS provides a supplement or an alternative to AIS severity classification.

Test de Français Laval-Montreal: Does It Measure What It Should Measure?

ERIC Educational Resources Information Center

Schmit, Romain; Saif, Shahrzad

2015-01-01

This article reports on a study conducted as part of a larger investigation of the predictive validity of the Test de Français Laval-Montreal (TFLM), a high-stakes French language test used for admission and placement purposes for Teacher-Training Programs (TTPs) in major francophone universities in Canada (Schmitt, 2015). The objective of this…

Connecting Technological Innovation in Artificial Intelligence to Real-world Medical Practice through Rigorous Clinical Validation: What Peer-reviewed Medical Journals Could Do

PubMed Central

2018-01-01

Artificial intelligence (AI) is projected to substantially influence clinical practice in the foreseeable future. However, despite the excitement around the technologies, it is yet rare to see examples of robust clinical validation of the technologies and, as a result, very few are currently in clinical use. A thorough, systematic validation of AI technologies using adequately designed clinical research studies before their integration into clinical practice is critical to ensure patient benefit and safety while avoiding any inadvertent harms. We would like to suggest several specific points regarding the role that peer-reviewed medical journals can play, in terms of study design, registration, and reporting, to help achieve proper and meaningful clinical validation of AI technologies designed to make medical diagnosis and prediction, focusing on the evaluation of diagnostic accuracy efficacy. Peer-reviewed medical journals can encourage investigators who wish to validate the performance of AI systems for medical diagnosis and prediction to pay closer attention to the factors listed in this article by emphasizing their importance. Thereby, peer-reviewed medical journals can ultimately facilitate translating the technological innovations into real-world practice while securing patient safety and benefit. PMID:29805337

Connecting Technological Innovation in Artificial Intelligence to Real-world Medical Practice through Rigorous Clinical Validation: What Peer-reviewed Medical Journals Could Do.

PubMed

Park, Seong Ho; Kressel, Herbert Y

2018-05-28

Artificial intelligence (AI) is projected to substantially influence clinical practice in the foreseeable future. However, despite the excitement around the technologies, it is yet rare to see examples of robust clinical validation of the technologies and, as a result, very few are currently in clinical use. A thorough, systematic validation of AI technologies using adequately designed clinical research studies before their integration into clinical practice is critical to ensure patient benefit and safety while avoiding any inadvertent harms. We would like to suggest several specific points regarding the role that peer-reviewed medical journals can play, in terms of study design, registration, and reporting, to help achieve proper and meaningful clinical validation of AI technologies designed to make medical diagnosis and prediction, focusing on the evaluation of diagnostic accuracy efficacy. Peer-reviewed medical journals can encourage investigators who wish to validate the performance of AI systems for medical diagnosis and prediction to pay closer attention to the factors listed in this article by emphasizing their importance. Thereby, peer-reviewed medical journals can ultimately facilitate translating the technological innovations into real-world practice while securing patient safety and benefit.

Detection and genotyping of Trypanosoma cruzi from açai products commercialized in Rio de Janeiro and Pará, Brazil.

PubMed

Ferreira, Renata Trotta Barroso; Cabral, Maria Luiza; Martins, Ronald Sodré; Araujo, Paula Finamore; da Silva, Sérgio Alves; Britto, Constança; Branquinho, Maria Regina; Cardarelli-Leite, Paola; Moreira, Otacilio C

2018-04-10

Several cases of food-borne acute Chagas disease (ACD) have been reported in the Brazilian Amazon so far. Up to 2004, the occurrence of ACD by oral transmission, associated with food consumption, was rare. Recent cases of ACD in Brazil have been attributed to the consumption of juice from the açai palm containing reservoir animals or insect vectors waste, infected with Trypanosoma cruzi. This study aimed to determine the T. cruzi contamination rate and to genotype the parasite in food samples prepared from açai, which are commercialized in Rio de Janeiro and the Pará States in Brazil. The amplificability of DNA extracted from açai samples, and T. cruzi and Triatominae detection were performed by conventional PCR. Molecular characterization was done by multilocus PCR analysis, to determine the parasite discrete type units (DTUs) based on the size of PCR products in agarose gels, using the intergenic region of the spliced leader (SL), 24 Sα rDNA and nuclear fragment A10 as targets. From the 140 samples of açai-based products analyzed, T. cruzi DNA was detected in 14 samples (10%); triatomine DNA was detected in one of these 14 samples. The parasite genotyping demonstrated that food samples containing açai showed a mixture of T. cruzi DTUs with TcIII, TcV and TcI prevailing. In this study, the molecular detection and identification of T. cruzi from açai-based manufactured food samples, was performed for the first time. Although parasite DNA is a marker of possible contamination during food manufacturing, our findings do not indicate that açai is a source of Chagas disease via oral transmission per se, as live parasites were not investigated. Nevertheless, a molecular approach could be a powerful tool in the epidemiological investigation of outbreaks, supporting previous evidence that açai-based food can be contaminated with T. cruzi. Furthermore, both food quality control and assessment of good manufacturing practices involving açai-based products can be improved, assuring the safety of açai products.

Revisiting AI-2 quorum sensing inhibitors: direct comparison of alkyl-DPD analogues and a natural product fimbrolide.

PubMed

Lowery, Colin A; Abe, Takumi; Park, Junguk; Eubanks, Lisa M; Sawada, Daisuke; Kaufmann, Gunnar F; Janda, Kim D

2009-11-04

Quorum sensing (QS) systems have been discovered in a wide variety of bacteria, and mediate both intra- and interspecies communication. The AI-2-based QS system represents the most studied of these proposed interspecies systems and has been shown to regulate diverse functions such as bioluminescence, expression of virulence factors, and biofilm formation. As such, the development of modulatory compounds, both agonists and antagonists, is of great interest for the study of unknown AI-2-based QS systems and the potential treatment of bacterial infections. The fimbrolide class of natural products has exhibited excellent inhibitory activity against AI-2-based QS and as such may be considered the "gold standard" of AI-2 inhibitors. Thus, we sought to include a fimbrolide as a control compound for our recently developed alkyl-DPD panel of AI-2 modulators. Herein, we present a revised synthesis of a commonly studied fimbrolide as well as a direct comparison between the fimbrolide and alkyl-DPD analogues. We demonstrate that our alkyl-DPD analogues are more potent inhibitors of QS in both Vibrio harveyi and Salmonella typhimurium, the two organisms with defined AI-2 QS systems, and in doing so call into question the widely accepted use of fimbrolide-derived compounds as the "gold standard" of AI-2 inhibition.

Intelligent monitoring and control of semiconductor manufacturing equipment

NASA Technical Reports Server (NTRS)

Murdock, Janet L.; Hayes-Roth, Barbara

1991-01-01

The use of AI methods to monitor and control semiconductor fabrication in a state-of-the-art manufacturing environment called the Rapid Thermal Multiprocessor is described. Semiconductor fabrication involves many complex processing steps with limited opportunities to measure process and product properties. By applying additional process and product knowledge to that limited data, AI methods augment classical control methods by detecting abnormalities and trends, predicting failures, diagnosing, planning corrective action sequences, explaining diagnoses or predictions, and reacting to anomalous conditions that classical control systems typically would not correct. Research methodology and issues are discussed, and two diagnosis scenarios are examined.

Applying AI tools to operational space environmental analysis

NASA Technical Reports Server (NTRS)

Krajnak, Mike; Jesse, Lisa; Mucks, John

1995-01-01

The U.S. Air Force and National Oceanic Atmospheric Agency (NOAA) space environmental operations centers are facing increasingly complex challenges meeting the needs of their growing user community. These centers provide current space environmental information and short term forecasts of geomagnetic activity. Recent advances in modeling and data access have provided sophisticated tools for making accurate and timely forecasts, but have introduced new problems associated with handling and analyzing large quantities of complex data. AI (Artificial Intelligence) techniques have been considered as potential solutions to some of these problems. Fielding AI systems has proven more difficult than expected, in part because of operational constraints. Using systems which have been demonstrated successfully in the operational environment will provide a basis for a useful data fusion and analysis capability. Our approach uses a general purpose AI system already in operational use within the military intelligence community, called the Temporal Analysis System (TAS). TAS is an operational suite of tools supporting data processing, data visualization, historical analysis, situation assessment and predictive analysis. TAS includes expert system tools to analyze incoming events for indications of particular situations and predicts future activity. The expert system operates on a knowledge base of temporal patterns encoded using a knowledge representation called Temporal Transition Models (TTM's) and an event database maintained by the other TAS tools. The system also includes a robust knowledge acquisition and maintenance tool for creating TTM's using a graphical specification language. The ability to manipulate TTM's in a graphical format gives non-computer specialists an intuitive way of accessing and editing the knowledge base. To support space environmental analyses, we used TAS's ability to define domain specific event analysis abstractions. The prototype system defines events covering reports of natural phenomena such as solar flares, bursts, geomagnetic storms, and five others pertinent to space environmental analysis. With our preliminary event definitions we experimented with TAS's support for temporal pattern analysis using X-ray flare and geomagnetic storm forecasts as case studies. We are currently working on a framework for integrating advanced graphics and space environmental models into this analytical environment.

Discrimination of Avian Influenza Virus using Host-cell Infection Fingerprinting by Sulfinate-based Fluorescence Superoxide Probe.

PubMed

Hong, Seong Cheol; Murale, Dhiraj P; Jang, Se-Young; Haque, Md Mamunul; Seo, Minah; Lee, Seok; Woo, Deok Ha; Kwon, Junghoon; Song, Chang-Seon; Kim, Yun Kyung; Lee, Jun-Seok

2018-06-22

Avian Influenza (AI) caused an annual epidemic outbreak that led to destroying tens of millions of poultry worldwide. Current gold standard AI diagnosis method is an embryonic egg-based hemagglutination assay followed by immunoblotting or PCR sequencing to confirm subtypes. It requires, however, specialized facilities to handle egg inoculation and incubation, and the subtyping methods relied on costly reagents. Here, we demonstrated the first differential sensing approach to distinguish AI subtypes using series of cell lines and fluorescent sensor. Susceptibility of AI virus differs depending on genetic backgrounds of host cells. Thus, we examined cells from different organ origin, and the infection patterns against a panel of cells were utilized for AI virus subtyping. To quantify AI infection, we designed a highly cell-permeable fluorescent superoxide sensor to visualize infection. Though many AI monitoring strategies relied on sophisticated antibody have been extensively studied, our differential sensing strategy successfully proved discriminations of AI subtypes and demonstrated as a useful primary screening platform to monitor a large number of samples. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Predicting patients that require care at a trauma center: analysis of injuries and other factors.

PubMed

Schoell, Samantha L; Doud, Andrea N; Weaver, Ashley A; Barnard, Ryan T; Meredith, J Wayne; Stitzel, Joel D; Martin, R Shayn

2015-04-01

The detection of occult or unpredictable injuries in motor vehicle crashes (MVCs) is crucial in correctly triaging patients and thus reducing fatalities. The purpose of the study was to develop a metric that indicates the likelihood that an injury sustained in a MVC would require management at a Level I/II trauma centre (TC) versus a non-trauma centre (non-TC). Transfer Scores (TSs) were computed for 240 injuries that comprise the top 95% most frequently occurring injuries in the National Automotive Sampling System-Crashworthiness Data System (NASS-CDS) with an Abbreviated Injury Scale (AIS) severity of 2 or greater. A TS for each injury was computed using the proportions of patients involved in a MVC from the National Inpatient Sample (NIS) that were transferred to a TC or managed at a non-TC. Similarly, a TSMAIS that excludes patients with higher severity co-injuries was calculated using the proportion of patients with a maximum AIS (MAIS) equal to the AIS severity of a given injury. The results indicated for injuries of a given AIS severity, body region, and injury type, there were large variations in the TSMAIS. Overall results demonstrated higher TSMAIS values when injuries were internal, haemorrhagic, intracranial or of moderate severity (AIS 3-5). Specifically, injuries to the head possessed a TSMAIS that ranged from 0.000 to 0.889, with head injuries of AIS 3-5 severities being the most likely to be transferred. The analysis indicated that the TSMAIS is not solely correlated with AIS severity and therefore it captures other important aspects of injury such as predictability and trauma system capabilities. The TS and TSMAIS can be useful in advanced automatic crash notification (AACN) research for the detection of highly unpredictable injuries in MVCs that require direct transport to a TC. Copyright © 2014 Elsevier Ltd. All rights reserved.

Glasgow Coma Scale and Outcomes after Structural Traumatic Head Injury in Early Childhood

PubMed Central

Heather, Natasha L.; Derraik, José G. B.; Beca, John; Hofman, Paul L.; Dansey, Rangi; Hamill, James; Cutfield, Wayne S.

2013-01-01

Objective To assess the association of the Glasgow Coma Scale (GCS) with radiological evidence of head injury (the Abbreviated Injury Scale for the head region, AIS-HR) in young children hospitalized with traumatic head injury (THI), and the predictive value of GCS and AIS-HR scores for long-term impairment. Methods Our study involved a 10-year retrospective review of a database encompassing all patients admitted to Starship Children’s Hospital (Auckland, New Zealand, 2000–2010) with THI. Results We studied 619 children aged <5 years at the time of THI, with long-term outcome data available for 161 subjects. Both GCS and AIS-HR scores were predictive of length of intensive care unit and hospital stay (all p<0.001). GCS was correlated with AIS-HR (ρ=-0.46; p<0.001), although mild GCS scores (13–15) commonly under-estimated the severity of radiological injury: 42% of children with mild GCS scores had serious–critical THI (AIS-HR 3–5). Increasingly severe GCS or AIS-HR scores were both associated with a greater likelihood of long-term impairment (neurological disability, residual problems, and educational support). However, long-term impairment was also relatively common in children with mild GCS scores paired with structural THI more severe than a simple linear skull fracture. Conclusion Severe GCS scores will identify most cases of severe radiological injury in early childhood, and are good predictors of poor long-term outcome. However, young children admitted to hospital with structural THI and mild GCS scores have an appreciable risk of long-term disability, and also warrant long-term follow-up. PMID:24312648

The recomBead Borrelia antibody index, CXCL13 and total IgM index for laboratory diagnosis of Lyme neuroborreliosis in children.

PubMed

Skogman, B H; Lager, M; Henningsson, A J; Tjernberg, I

2017-11-01

For laboratory diagnostics of Lyme neuroborreliosis (LNB), the recomBead Borrelia antibody index (AI) assay has shown promising results in a mixed age population, but has not previously been evaluated with specific focus on paediatric patients. The aim of the study was to evaluate the recomBead Borrelia AI assay in cerebrospinal fluid (CSF) for the laboratory diagnosis of LNB in children. We also wanted to explore whether early markers, such as CXCL13 in CSF and/or total IgM index could be useful as complementary diagnostic tools. Children being evaluated for LNB in a Swedish Lyme endemic area were included in the study (n = 146). Serum and CSF were collected on admission. Patients with other specific diagnoses were controls (n = 15). The recomBead Borrelia AI assay and the recomBead CXCL13 assay (Mikrogen) were applied together with total IgM index. The overall sensitivity for recomBead Borrelia AI (IgM and IgG together) was 74% and the specificity was 97%. However, the highest sensitivity (91%) at an acceptable level of specificity (90%) was obtained by recomBead Borrelia AI together with CXCL13 and total IgM index, showing a positive predictive value of 84% and a negative predictive value of 95%. Thus, the recomBead Borrelia AI assay performs with moderate sensitivity and high specificity in paediatric LNB patients. The major advantage seems to be increased sensitivity in the possible LNB group compared to the IDEIA assay. The diagnostic sensitivity may be further increased by using a combination of early markers, such as CXCL13 in CSF and total IgM index.

Meeting calcium recommendations during middle childhood reflects mother-daughter beverage choices and predicts bone mineral status2

PubMed Central

Fisher, Jennifer O; Mitchell, Diane C; Smiciklas-Wright, Helen; Mannino, Michelle L; Birch, Leann L

2008-01-01

Background Longitudinal data regarding the influence of beverage intakes on calcium adequacy are lacking. Objective This study evaluated calcium intake from ages 5 to 9 y as a function of mother-daughter beverage choices and as a predictor of bone mineral status. Design Intakes of energy, calcium, milk, sweetened beverages, fruit juices, and non-energy-containing beverages were measured with the use of three 24-h dietary recalls in 192 non-Hispanic white girls aged 5, 7, and 9 y and their mothers. Calcium intakes from ages 5 to 9 y were categorized as either meeting or falling below recommended adequate intakes (AIs). The girls’ bone mineral status was assessed with dual-energy X-ray absorptiometry at age 9 y. Results The mean 5-y calcium intake was related to bone mineral density at age 9 y (β = 0.27, P < 0.001). The girls who met the AI for calcium were not heavier (P = 0.83) but had higher energy intakes (P < 0.0001) than did the girls who consumed less than the AI. Compared with the girls who consumed less than the AI, the girls who met the AI consumed, on average, almost twice as much milk (P < 0.0001), had smaller decreases in milk intake (P < 0.01), and consumed 18% less sweetened beverages (P < 0.01) from ages 5 to 9 y; the 2 groups did not differ significantly in juice and non-energy-containing beverage intakes. The girls who met the AI were also served milk more frequently than were the girls who consumed less than the AI (P < 0.0001) and had mothers who drank milk more frequently (P < 0.01) than did the mothers of the girls who consumed less than the AI. Conclusions These findings provide new longitudinal evidence that calcium intake predicts bone mineral status during middle childhood and reflects mother-daughter beverage choice patterns that are established well before the rapid growth and bone mineralization observed in adolescence. PMID:15051617

Artificial Intelligence in Precision Cardiovascular Medicine.

PubMed

Krittanawong, Chayakrit; Zhang, HongJu; Wang, Zhen; Aydar, Mehmet; Kitai, Takeshi

2017-05-30

Artificial intelligence (AI) is a field of computer science that aims to mimic human thought processes, learning capacity, and knowledge storage. AI techniques have been applied in cardiovascular medicine to explore novel genotypes and phenotypes in existing diseases, improve the quality of patient care, enable cost-effectiveness, and reduce readmission and mortality rates. Over the past decade, several machine-learning techniques have been used for cardiovascular disease diagnosis and prediction. Each problem requires some degree of understanding of the problem, in terms of cardiovascular medicine and statistics, to apply the optimal machine-learning algorithm. In the near future, AI will result in a paradigm shift toward precision cardiovascular medicine. The potential of AI in cardiovascular medicine is tremendous; however, ignorance of the challenges may overshadow its potential clinical impact. This paper gives a glimpse of AI's application in cardiovascular clinical care and discusses its potential role in facilitating precision cardiovascular medicine. Copyright © 2017 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Preliminary geological investigation of AIS data at Mary Kathleen, Queensland, Australia

NASA Technical Reports Server (NTRS)

Huntington, J. F.; Green, A. A.; Craig, M. D.; Cocks, T. D.

1986-01-01

The Airborne Imaging Spectrometer (AIS) was flown over granitic, volcanic, and calc-silicate terrain around the Mary Kathleen Uranium Mine in Queensland, in a test of its mineralocial mapping capabilities. An analysis strategy and restoration and enhancement techniques were developed to process the 128 band AIS data. A preliminary analysis of one of three AIS flight lines shows that the data contains considerable spectral variation but that it is also contaminated by second-order leakage of radiation from the near-infrared region. This makes the recognition of expected spectral absorption shapes very difficult. The effect appears worst in terrains containing considerable vegetation. Techniques that try to predict this supplementary radiation coupled with the log residual analytical technique show that expected mineral absorption spectra can be derived. The techniques suggest that with additional refinement correction procedures, the Australian AIS data may be revised. Application of the log residual analysis method has proved very successful on the cuprite, Nevada data set, and for highlighting the alunite, linite, and SiOH mineralogy.

Artificial Intelligence in Medical Practice: The Question to the Answer?

PubMed

Miller, D Douglas; Brown, Eric W

2018-02-01

Computer science advances and ultra-fast computing speeds find artificial intelligence (AI) broadly benefitting modern society-forecasting weather, recognizing faces, detecting fraud, and deciphering genomics. AI's future role in medical practice remains an unanswered question. Machines (computers) learn to detect patterns not decipherable using biostatistics by processing massive datasets (big data) through layered mathematical models (algorithms). Correcting algorithm mistakes (training) adds to AI predictive model confidence. AI is being successfully applied for image analysis in radiology, pathology, and dermatology, with diagnostic speed exceeding, and accuracy paralleling, medical experts. While diagnostic confidence never reaches 100%, combining machines plus physicians reliably enhances system performance. Cognitive programs are impacting medical practice by applying natural language processing to read the rapidly expanding scientific literature and collate years of diverse electronic medical records. In this and other ways, AI may optimize the care trajectory of chronic disease patients, suggest precision therapies for complex illnesses, reduce medical errors, and improve subject enrollment into clinical trials. Copyright © 2018 Elsevier Inc. All rights reserved.

Sensation-seeking predicts initiation of daily smoking behavior among American Indian high school students

PubMed Central

Spillane, Nichea S.; Muller, Clemma J.; Noonan, Carolyn; Goins, R. Turner; Mitchell, Christina M.; Manson, Spero

2013-01-01

Purpose American Indian (AI) youth have a high risk of smoking initiation. Sensation-seeking, defined as the tendency to seek novel and thrilling experiences, has been associated with smoking initiation in other groups but has never been examined in AI youth. Methods Data were from the Voices of Indian Teens Project (VOICES), a longitudinal study of AI youth from seven high schools in four AI communities in the western United States. Participants completed annual surveys in school over a three-year period. Our sample comprised 764 students who were non-smokers at baseline. Smoking initiation was defined as endorsement of daily smoking after baseline. We used binary logistic regression to evaluate the association of baseline sensation-seeking with odds of daily smoking initiation, stratified by gender Results Participants were 353 males and 411 females aged 13 to 21 years at baseline. After adjusting for covariates, baseline sensation-seeking correlated with smoking initiation differently in males and females. Sensation-seeking did not predict daily smoking in males. Among females, however, higher sensation-seeking scores at baseline predicted daily smoking in both the unadjusted (odds ratio = 1.4; 95% CI = 1.1 – 1.8; p = 0.005) and covariate-adjusted (odds ratio = 1.3; 95% CI = 1.0 – 1.6; p = 0.04) models Conclusion Gender-specific prevention programs may be warranted in addressing different risk-factor profiles in this high-risk population PMID:22958862

The natural logarithm transforms the abbreviated injury scale and improves accuracy scoring.

PubMed

Wang, Xu; Gu, Xiaoming; Zhang, Zhiliang; Qiu, Fang; Zhang, Keming

2012-11-01

The Injury Severity Score (ISS) and the New Injury Severity Score (NISS) are widely used for anatomic severity assessments, but they do not display a linear relation to mortality. The mortality rates are significantly different between pairs of the Abbreviated Injury Scale (AIS) triplets that generate the same ISS/NISS total. The Logarithm Injury Severity Score (LISS) is defined as a change in AIS values by raising each AIS severity score (1-6) by taking the natural logarithm to a power of 5.53 multiplied by 1.7987 and then adding the three most severe injuries (i.e. highest AIS), regardless of body region. LISS values were calculated for every patient in three large independent data sets: 3,784, 4,436, and 4,018 patients treated over a six-year period at Class A tertiary comprehensive hospitals in China. The power of LISS to predict morality was then compared with previously calculated NISS values for the same patients in each of the three data sets. We found that LISS is more predictive of survival as well (Hangzhou: receiver operating characteristic (ROC): NISS=0.931, LISS=0.949, p=0.006; Similarly, Zhejiang and Shenyang: ROC NISS vs. LISS, p<0.05). Moreover, LISS provides a better fit throughout its entire range of predicting (Hosmer-Lemeshow statistic for Hangzhou NISS=15.76, p=0.027; LISS=13.79, p=0.055; Similarly, for Zhejiang and Shenyang). LISS should be used as the standard summary measure of human trauma.

Dissociable Roles of Right Inferior Frontal Cortex and Anterior Insula in Inhibitory Control: Evidence from Intrinsic and Task-Related Functional Parcellation, Connectivity, and Response Profile Analyses across Multiple Datasets

PubMed Central

Ryali, Srikanth; Chen, Tianwen; Li, Chiang-Shan R.

2014-01-01

The right inferior frontal cortex (rIFC) and the right anterior insula (rAI) have been implicated consistently in inhibitory control, but their differential roles are poorly understood. Here we use multiple quantitative techniques to dissociate the functional organization and roles of the rAI and rIFC. We first conducted a meta-analysis of 70 published inhibitory control studies to generate a commonly activated right fronto-opercular cortex volume of interest (VOI). We then segmented this VOI using two types of features: (1) intrinsic brain activity; and (2) stop-signal task-evoked hemodynamic response profiles. In both cases, segmentation algorithms identified two stable and distinct clusters encompassing the rAI and rIFC. The rAI and rIFC clusters exhibited several distinct functional characteristics. First, the rAI showed stronger intrinsic and task-evoked functional connectivity with the anterior cingulate cortex, whereas the rIFC had stronger intrinsic and task-evoked functional connectivity with dorsomedial prefrontal and lateral fronto-parietal cortices. Second, the rAI showed greater activation than the rIFC during Unsuccessful, but not Successful, Stop trials, and multivoxel response profiles in the rAI, but not the rIFC, accurately differentiated between Successful and Unsuccessful Stop trials. Third, activation in the rIFC, but not rAI, predicted individual differences in inhibitory control abilities. Crucially, these findings were replicated in two independent cohorts of human participants. Together, our findings provide novel quantitative evidence for the dissociable roles of the rAI and rIFC in inhibitory control. We suggest that the rAI is particularly important for detecting behaviorally salient events, whereas the rIFC is more involved in implementing inhibitory control. PMID:25355218

The Potential Role of Artificial Intelligence Technology in Education.

ERIC Educational Resources Information Center

Salem, Abdel-Badeeh M.

The field of Artificial Intelligence (AI) and Education has traditionally a technology-based focus, looking at the ways in which AI can be used in building intelligent educational software. In addition AI can also provide an excellent methodology for learning and reasoning from the human experiences. This paper presents the potential role of AI in…

Why the United States Must Adopt Lethal Autonomous Weapon Systems

DTIC Science & Technology

2017-05-25

2017. http://www.designboom.com/ technology /designboom-tech-predictions-robotics-12-26- 2016/. Egan, Matt. "Robots Write Thousands Of News Stories A...views on the morality of artificial intelligence (AI) and robotics technology . Eastern culture sees artificial intelligence as an economic savior...Army, 37 pages. The East and West have differing views on the morality of artificial intelligence (AI) and robotics technology . Eastern culture

Abnormal skeletal growth patterns in adolescent idiopathic scoliosis--a longitudinal study until skeletal maturity.

PubMed

Yim, Annie P Y; Yeung, Hiu-Yan; Hung, Vivian W Y; Lee, Kwong-Man; Lam, Tsz-Ping; Ng, Bobby K W; Qiu, Yong; Cheng, Jack C Y

2012-08-15

A cross-sectional and prospective longitudinal study on the anthropometric parameters and growth pattern of girls with adolescent idiopathic scoliosis (AIS). To investigate the growth pattern of girls with AIS with different severities, using cross-sectional and prospective longitudinal data set in comparison with age-matched healthy controls. AIS occurs in children during their pubertal growth spurt. Although there is no clear consensus on the difference in body height between girls with AIS and healthy controls, it is generally thought that the development and curve progression in girls with AIS is closely associated with their growth rate. There is no concrete prospective longitudinal study to document clearly the growth pattern and growth rate of subjects with AIS . A total of 611 girls with AIS and 296 healthy age-matched controls were included in the study and among them, 194 girls with AIS and 116 healthy controls were followed up until skeletal maturity. The girls with AIS were grouped into moderate (AIS20) and severe curve (AIS40) groups on the basis of maximum curve magnitude at skeletal maturity. Clinical data and detailed anthropometric parameters were recorded. In the cross-sectional analysis, the groups of subjects were compared within different age groups (from the age of 12-16 yr). In the longitudinal study, linear mixed modeling with respect to age or years since menarche was employed to formulate the growth trajectory of different anthropometric parameters. In the cross-sectional analysis, the girls with AIS were generally taller, with longer arm span and lower body mass index than the healthy controls. The girls with AIS40 were found to be significantly shorter in height (P = 0.006) and arm span (P = 0.025) at the age of 12 years but caught up and overtook the control group at the age of 14 to 16 years. In the longitudinal study, the average growth rate of arm span in girls with AIS40 was significantly higher than that in girls with AIS20 (> 30%) (P = 0.004) and controls (> 70%) (P = 0.0004). The age of menarche of girls with AIS40 was significantly delayed by 5.9 months and 3.8 months when compared with the control group and girls with AIS20, respectively (P < 0.05). The growth patterns of girls with AIS with confirmed curve severities were significantly different from healthy age-matched controls. Girls with severe AIS had delayed menarche with faster skeletal growth rate during the age of 12 to 16 years. Monitoring the rate of change of arm span of girls with AIS could be an important additional clinical parameter in helping predict curve severity in girls with AIS.

Raman spectroscopy-based screening of IgM positive and negative sera for dengue virus infection

NASA Astrophysics Data System (ADS)

Bilal, M.; Saleem, M.; Bilal, Maria; Ijaz, T.; Khan, Saranjam; Ullah, Rahat; Raza, A.; Khurram, M.; Akram, W.; Ahmed, M.

2016-11-01

A statistical method based on Raman spectroscopy for the screening of immunoglobulin M (IgM) in dengue virus (DENV) infected human sera is presented. In total, 108 sera samples were collected and their antibody indexes (AI) for IgM were determined through enzyme-linked immunosorbent assay (ELISA). Raman spectra of these samples were acquired using a 785 nm wavelength excitation laser. Seventy-eight Raman spectra were selected randomly and unbiasedly for the development of a statistical model using partial least square (PLS) regression, while the remaining 30 were used for testing the developed model. An R-square (r 2) value of 0.929 was determined using the leave-one-sample-out (LOO) cross validation method, showing the validity of this model. It considers all molecular changes related to IgM concentration, and describes their role in infection. A graphical user interface (GUI) platform has been developed to run a developed multivariate model for the prediction of AI of IgM for blindly tested samples, and an excellent agreement has been found between model predicted and clinically determined values. Parameters like sensitivity, specificity, accuracy, and area under receiver operator characteristic (ROC) curve for these tested samples are also reported to visualize model performance.

Attitude Determination and Control System (ADCS) and Maintenance and Diagnostic System (MDS): A maintenance and diagnostic system for Space Station Freedom

NASA Technical Reports Server (NTRS)

Toms, David; Hadden, George D.; Harrington, Jim

1990-01-01

The Maintenance and Diagnostic System (MDS) that is being developed at Honeywell to enhance the Fault Detection Isolation and Recovery system (FDIR) for the Attitude Determination and Control System on Space Station Freedom is described. The MDS demonstrates ways that AI-based techniques can be used to improve the maintainability and safety of the Station by helping to resolve fault anomalies that cannot be fully determined by built-in-test, by providing predictive maintenance capabilities, and by providing expert maintenance assistance. The MDS will address the problems associated with reasoning about dynamic, continuous information versus only about static data, the concerns of porting software based on AI techniques to embedded targets, and the difficulties associated with real-time response. An initial prototype was built of the MDS. The prototype executes on Sun and IBM PS/2 hardware and is implemented in the Common Lisp; further work will evaluate its functionality and develop mechanisms to port the code to Ada.

GDNF-RET signaling in ER-positive breast cancers is a key determinant of response and resistance to aromatase inhibitors

PubMed Central

Morandi, Andrea; Martin, Lesley-Ann; Gao, Qiong; Pancholi, Sunil; Mackay, Alan; Robertson, David; Zvelebil, Marketa; Dowsett, Mitch; Plaza-Menacho, Ivan; Isacke, Clare M.

2013-01-01

Most breast cancers at diagnosis are estrogen receptor (ER)-positive and depend on estrogen for growth and survival. Blocking estrogen biosynthesis by aromatase inhibitors (AI) has therefore become a first-line endocrine therapy for post-menopausal women with ER-positive breast cancers. Despite providing substantial improvements in patient outcome, AI resistance remains a major clinical challenge. The receptor tyrosine kinase RET and its co-receptor GFRα1 are upregulated in a subset of ER-positive breast cancers, and the RET ligand, glial-derived neurotrophic factor (GDNF) is upregulated by inflammatory cytokines. Here we report the findings of a multidisciplinary strategy to address the impact of GDNF-RET signaling in the response to AI treatment. In breast cancer cells in 2D and 3D culture, GDNF-mediated RET signaling is enhanced in a model of AI resistance. Further, GDNF-RET signaling promoted the survival of AI-resistant cells and elicited resistance in AI-sensitive cells. Both these effects were selectively reverted by the RET kinase inhibitor NVP-BBT594. Gene expression profiling in ER-positive cancers defined a proliferation-independent GDNF-response signature that prognosed poor patient outcome and, more importantly, predicted poor response to AI treatment with the development of resistance. We validated these findings by demonstrating increased RET protein expression levels in an independent cohort of AI-resistant patient specimens. Together, our results establish GDNF-RET signaling as a rational therapeutic target to combat or delay the onset of AI resistance in breast cancer. PMID:23650283

A survey of artificial immune system based intrusion detection.

PubMed

Yang, Hua; Li, Tao; Hu, Xinlei; Wang, Feng; Zou, Yang

2014-01-01

In the area of computer security, Intrusion Detection (ID) is a mechanism that attempts to discover abnormal access to computers by analyzing various interactions. There is a lot of literature about ID, but this study only surveys the approaches based on Artificial Immune System (AIS). The use of AIS in ID is an appealing concept in current techniques. This paper summarizes AIS based ID methods from a new view point; moreover, a framework is proposed for the design of AIS based ID Systems (IDSs). This framework is analyzed and discussed based on three core aspects: antibody/antigen encoding, generation algorithm, and evolution mode. Then we collate the commonly used algorithms, their implementation characteristics, and the development of IDSs into this framework. Finally, some of the future challenges in this area are also highlighted.

Deriving urban dynamic evolution rules from self-adaptive cellular automata with multi-temporal remote sensing images

NASA Astrophysics Data System (ADS)

He, Yingqing; Ai, Bin; Yao, Yao; Zhong, Fajun

2015-06-01

Cellular automata (CA) have proven to be very effective for simulating and predicting the spatio-temporal evolution of complex geographical phenomena. Traditional methods generally pose problems in determining the structure and parameters of CA for a large, complex region or a long-term simulation. This study presents a self-adaptive CA model integrated with an artificial immune system to discover dynamic transition rules automatically. The model's parameters are allowed to be self-modified with the application of multi-temporal remote sensing images: that is, the CA can adapt itself to the changed and complex environment. Therefore, urban dynamic evolution rules over time can be efficiently retrieved by using this integrated model. The proposed AIS-based CA model was then used to simulate the rural-urban land conversion of Guangzhou city, located in the core of China's Pearl River Delta. The initial urban land was directly classified from TM satellite image in the year 1990. Urban land in the years 1995, 2000, 2005, 2009 and 2012 was correspondingly used as the observed data to calibrate the model's parameters. With the quantitative index figure of merit (FoM) and pattern similarity, the comparison was further performed between the AIS-based model and a Logistic CA model. The results indicate that the AIS-based CA model can perform better and with higher precision in simulating urban evolution, and the simulated spatial pattern is closer to the actual development situation.

Purification, developmental expression, and in silico characterization of α-amylase inhibitor from Echinochloa frumentacea.

PubMed

Panwar, Priyankar; Verma, A K; Dubey, Ashutosh

2018-05-01

Barnyard ( Echinochloa frumentacea ) and finger ( Eleusine coracana ) millet growing at northwestern Himalaya were explored for the α-amylase inhibitor (α-AI). The mature seeds of barnyard millet variety PRJ1 had maximum α-AI activity which increases in different developmental stage. α-AI was purified up to 22.25-fold from barnyard millet variety PRJ1. Semi-quantitative PCR of different developmental stages of barnyard millet seeds showed increased levels of the transcript from 7 to 28 days. Sequence analysis revealed that it contained 315 bp nucleotide which encodes 104 amino acid sequence with molecular weight 10.72 kDa. The predicted 3D structure of α-AI was 86.73% similar to a bifunctional inhibitor of ragi. In silico analysis of 71 α-AI protein sequences were carried out for biochemical features, homology search, multiple sequence alignment, phylogenetic tree construction, motif, and superfamily distribution of protein sequences. Analysis of multiple sequence alignment revealed the existence of conserved regions NPLP[S/G]CRWYVV[S/Q][Q/R]TCG[V/I] throughout sequences. Superfam analysis revealed that α-AI protein sequences were distributed among seven different superfamilies.

Thiophenone Attenuates Enteropathogenic Escherichia coli O103:H2 Virulence by Interfering with AI-2 Signaling.

PubMed

Witsø, Ingun Lund; Valen Rukke, Håkon; Benneche, Tore; Aamdal Scheie, Anne

2016-01-01

Interference with bacterial quorum sensing communication provides an anti-virulence strategy to control pathogenic bacteria. Here, using the Enteropathogenic E. coli (EPEC) O103:H2, we showed for the first time that thiophenone TF101 reduced expression of lsrB; the gene encoding the AI-2 receptor. Combined results of transcriptional and phenotypic analyses suggested that TF101 interfere with AI-2 signalling, possibly by competing with AI-2 for binding to LsrB. This is supported by in silico docking prediction of thiophenone TF101 in the LsrB pocket. Transcriptional analyses furthermore showed that thiophenone TF101 interfered with expression of the virulence genes eae and fimH. In addition, TF101 reduced AI-2 induced E. coli adhesion to colorectal adenocarcinoma cells. TF101, on the other hand, did not affect epinephrine or norepinephrine enhanced E. coli adhesion. Overall, our results showed that thiophenone TF101 interfered with virulence expression in E. coli O103:H2, suggestedly by interfering with AI-2 mediated quorum sensing. We thus conclude that thiophenone TF101 might represent a promising future anti-virulence agent in the fight against pathogenic E. coli.

Thiophenone Attenuates Enteropathogenic Escherichia coli O103:H2 Virulence by Interfering with AI-2 Signaling

PubMed Central

Valen Rukke, Håkon; Benneche, Tore; Aamdal Scheie, Anne

2016-01-01

Interference with bacterial quorum sensing communication provides an anti-virulence strategy to control pathogenic bacteria. Here, using the Enteropathogenic E. coli (EPEC) O103:H2, we showed for the first time that thiophenone TF101 reduced expression of lsrB; the gene encoding the AI-2 receptor. Combined results of transcriptional and phenotypic analyses suggested that TF101 interfere with AI-2 signalling, possibly by competing with AI-2 for binding to LsrB. This is supported by in silico docking prediction of thiophenone TF101 in the LsrB pocket. Transcriptional analyses furthermore showed that thiophenone TF101 interfered with expression of the virulence genes eae and fimH. In addition, TF101 reduced AI-2 induced E. coli adhesion to colorectal adenocarcinoma cells. TF101, on the other hand, did not affect epinephrine or norepinephrine enhanced E. coli adhesion. Overall, our results showed that thiophenone TF101 interfered with virulence expression in E. coli O103:H2, suggestedly by interfering with AI-2 mediated quorum sensing. We thus conclude that thiophenone TF101 might represent a promising future anti-virulence agent in the fight against pathogenic E. coli. PMID:27309855

A review on experimental design for pollutants removal in water treatment with the aid of artificial intelligence.

PubMed

Fan, Mingyi; Hu, Jiwei; Cao, Rensheng; Ruan, Wenqian; Wei, Xionghui

2018-06-01

Water pollution occurs mainly due to inorganic and organic pollutants, such as nutrients, heavy metals and persistent organic pollutants. For the modeling and optimization of pollutants removal, artificial intelligence (AI) has been used as a major tool in the experimental design that can generate the optimal operational variables, since AI has recently gained a tremendous advance. The present review describes the fundamentals, advantages and limitations of AI tools. Artificial neural networks (ANNs) are the AI tools frequently adopted to predict the pollutants removal processes because of their capabilities of self-learning and self-adapting, while genetic algorithm (GA) and particle swarm optimization (PSO) are also useful AI methodologies in efficient search for the global optima. This article summarizes the modeling and optimization of pollutants removal processes in water treatment by using multilayer perception, fuzzy neural, radial basis function and self-organizing map networks. Furthermore, the results conclude that the hybrid models of ANNs with GA and PSO can be successfully applied in water treatment with satisfactory accuracies. Finally, the limitations of current AI tools and their new developments are also highlighted for prospective applications in the environmental protection. Copyright © 2018 Elsevier Ltd. All rights reserved.

Abbreviated Injury Scale: not a reliable basis for summation of injury severity in trauma facilities?

PubMed

Ringdal, Kjetil G; Skaga, Nils Oddvar; Hestnes, Morten; Steen, Petter Andreas; Røislien, Jo; Rehn, Marius; Røise, Olav; Krüger, Andreas J; Lossius, Hans Morten

2013-05-01

Injury severity is most frequently classified using the Abbreviated Injury Scale (AIS) as a basis for the Injury Severity Score (ISS) and the New Injury Severity Score (NISS), which are used for assessment of overall injury severity in the multiply injured patient and in outcome prediction. European trauma registries recommended the AIS 2008 edition, but the levels of inter-rater agreement and reliability of ISS and NISS, associated with its use, have not been reported. Nineteen Norwegian AIS-certified trauma registry coders were invited to score 50 real, anonymised patient medical records using AIS 2008. Rater agreements for ISS and NISS were analysed using Bland-Altman plots with 95% limits of agreement (LoA). A clinically acceptable LoA range was set at ± 9 units. Reliability was analysed using a two-way mixed model intraclass correlation coefficient (ICC) statistics with corresponding 95% confidence intervals (CI) and hierarchical agglomerative clustering. Ten coders submitted their coding results. Of their AIS codes, 2189 (61.5%) agreed with a reference standard, 1187 (31.1%) real injuries were missed, and 392 non-existing injuries were recorded. All LoAs were wider than the predefined, clinically acceptable limit of ± 9, for both ISS and NISS. The joint ICC (range) between each rater and the reference standard was 0.51 (0.29,0.86) for ISS and 0.51 (0.27,0.78) for NISS. The joint ICC (range) for inter-rater reliability was 0.49 (0.19,0.85) for ISS and 0.49 (0.16,0.82) for NISS. Univariate linear regression analyses indicated a significant relationship between the number of correctly AIS-coded injuries and total number of cases coded during the rater's career, but no significant relationship between the rater-against-reference ISS and NISS ICC values and total number of cases coded during the rater's career. Based on AIS 2008, ISS and NISS were not reliable for summarising anatomic injury severity in this study. This result indicates a limitation in their use as benchmarking tools for trauma system performance. Copyright © 2012 Elsevier Ltd. All rights reserved.

Integration of artificial intelligence methods and life cycle assessment to predict energy output and environmental impacts of paddy production.

PubMed

Nabavi-Pelesaraei, Ashkan; Rafiee, Shahin; Mohtasebi, Seyed Saeid; Hosseinzadeh-Bandbafha, Homa; Chau, Kwok-Wing

2018-08-01

Prediction of agricultural energy output and environmental impacts play important role in energy management and conservation of environment as it can help us to evaluate agricultural energy efficiency, conduct crops production system commissioning, and detect and diagnose faults of crop production system. Agricultural energy output and environmental impacts can be readily predicted by artificial intelligence (AI), owing to the ease of use and adaptability to seek optimal solutions in a rapid manner as well as the use of historical data to predict future agricultural energy use pattern under constraints. This paper conducts energy output and environmental impact prediction of paddy production in Guilan province, Iran based on two AI methods, artificial neural networks (ANNs), and adaptive neuro fuzzy inference system (ANFIS). The amounts of energy input and output are 51,585.61MJkg -1 and 66,112.94MJkg -1 , respectively, in paddy production. Life Cycle Assessment (LCA) is used to evaluate environmental impacts of paddy production. Results show that, in paddy production, in-farm emission is a hotspot in global warming, acidification and eutrophication impact categories. ANN model with 12-6-8-1 structure is selected as the best one for predicting energy output. The correlation coefficient (R) varies from 0.524 to 0.999 in training for energy input and environmental impacts in ANN models. ANFIS model is developed based on a hybrid learning algorithm, with R for predicting output energy being 0.860 and, for environmental impacts, varying from 0.944 to 0.997. Results indicate that the multi-level ANFIS is a useful tool to managers for large-scale planning in forecasting energy output and environmental indices of agricultural production systems owing to its higher speed of computation processes compared to ANN model, despite ANN's higher accuracy. Copyright © 2018 Elsevier B.V. All rights reserved.

Advancing Community–Based Research with Urban American Indian Populations: Multidisciplinary Perspectives

PubMed Central

Hartmann, William E.; Wendt, Dennis C.; Saftner, Melissa A.; Marcus, John; Momper, Sandra L.

2014-01-01

The U.S. has witnessed significant growth among urban AI populations in recent decades, and concerns have been raised that these populations face equal or greater degrees of disadvantage than their reservation counterparts. Surprisingly little urban AI research or community work has been documented in the literature, and even less has been written about the influences of urban settings on community-based work with these populations. Given the deep commitments of community psychology to empowering disadvantaged groups and understanding the impact of contextual factors on the lives of individuals and groups, community psychologists are well suited to fill these gaps in the literature. Toward informing such efforts, this work offers multidisciplinary insights from distinct idiographic accounts of community-based behavioral health research with urban AI populations. Accounts are offered by three researchers and one urban AI community organization staff member, and particular attention is given to issues of community heterogeneity, geography, membership, and collaboration. Each first-person account provides “lessons learned” from the urban context in which the research occurred. Together, these accounts suggest several important areas of consideration in research with urban AIs, some of which also seem relevant to reservation-based work. Finally, the potential role of research as a tool of empowerment for urban AI populations is emphasized, suggesting future research attend to the intersections of identity, sense of community, and empowerment in urban AI populations. PMID:24659391

The blubber adipocyte index: A nondestructive biomarker of adiposity in humpback whales (Megaptera novaeangliae).

PubMed

Castrillon, Juliana; Huston, Wilhelmina; Bengtson Nash, Susan

2017-07-01

The ability to accurately evaluate the energetic health of wildlife is of critical importance, particularly under conditions of environmental change. Despite the relevance of this issue, currently there are no reliable, standardized, nonlethal measures to assess the energetic reserves of large, free-roaming marine mammals such as baleen whales. This study investigated the potential of adipocyte area analysis and further, a standardized adipocyte index (AI), to yield reliable information regarding humpback whale ( Megaptera novaeangliae ) adiposity. Adipocyte area and AI, as ascertained by image analysis, showed a direct correlation with each other but only a weak correlation with the commonly used, but error prone, blubber lipid-percent measure. The relative power of the three respective measures was further evaluated by comparing humpback whale cohorts at different stages of migration and fasting. Adipocyte area, AI, and blubber lipid-percent were assessed by binary logistic regression revealing that adipocyte area had the greatest probability to predict the migration cohort with a high level of redundancy attributed to the AI given their strong linear relationship (r = -.784). When only AI and lipid-percent were assessed, the performance of both predictor variables was significant but the power of AI far exceeded lipid-percent. The sensitivity of adipocyte metrics and the rapid, nonlethal, and inexpensive nature of the methodology and AI calculation validate the inclusion of the AI in long-term monitoring of humpback whale population health, and further raises its potential for broader wildlife applications.

The BSM-AI project: SUSY-AI-generalizing LHC limits on supersymmetry with machine learning

NASA Astrophysics Data System (ADS)

Caron, Sascha; Kim, Jong Soo; Rolbiecki, Krzysztof; de Austri, Roberto Ruiz; Stienen, Bob

2017-04-01

A key research question at the Large Hadron Collider is the test of models of new physics. Testing if a particular parameter set of such a model is excluded by LHC data is a challenge: it requires time consuming generation of scattering events, simulation of the detector response, event reconstruction, cross section calculations and analysis code to test against several hundred signal regions defined by the ATLAS and CMS experiments. In the BSM-AI project we approach this challenge with a new idea. A machine learning tool is devised to predict within a fraction of a millisecond if a model is excluded or not directly from the model parameters. A first example is SUSY-AI, trained on the phenomenological supersymmetric standard model (pMSSM). About 300, 000 pMSSM model sets - each tested against 200 signal regions by ATLAS - have been used to train and validate SUSY-AI. The code is currently able to reproduce the ATLAS exclusion regions in 19 dimensions with an accuracy of at least 93%. It has been validated further within the constrained MSSM and the minimal natural supersymmetric model, again showing high accuracy. SUSY-AI and its future BSM derivatives will help to solve the problem of recasting LHC results for any model of new physics. SUSY-AI can be downloaded from http://susyai.hepforge.org/. An on-line interface to the program for quick testing purposes can be found at http://www.susy-ai.org/.

A framework for qualitative reasoning about solid objects

NASA Technical Reports Server (NTRS)

Davis, E.

1987-01-01

Predicting the behavior of a qualitatively described system of solid objects requires a combination of geometrical, temporal, and physical reasoning. Methods based upon formulating and solving differential equations are not adequate for robust prediction, since the behavior of a system over extended time may be much simpler than its behavior over local time. A first-order logic, in which one can state simple physical problems and derive their solution deductively, without recourse to solving the differential equations, is discussed. This logic is substantially more expressive and powerful than any previous AI representational system in this domain.

Wall-modeled large eddy simulation of high-lift devices from low to post-stall angle of attacks

NASA Astrophysics Data System (ADS)

Bodart, Julien; Larsson, Johan; Moin, Parviz

2013-11-01

The flow around a McDonnell-Douglas 30P/30N multi-element airfoil at the flight Reynolds number of 9 million (based on chord) is computed using LES with an equilibrium wall-model with special treatment for transitional flows. Several different angles of attack are considered, up to and including stall, challenging the wall-model in several flow regimes. The maximum lift coefficient, which is generally difficult to predict with RANS approaches, is accurately predicted, as compared to experiments performed in the NASA LPT wind-tunnel. NASA grant: NNX11AI60A.

Bracing and exercise-based treatment for idiopathic scoliosis.

PubMed

Kalichman, Leonid; Kendelker, Liron; Bezalel, Tomer

2016-01-01

Various conservative therapies are available for treating adolescent idiopathic scoliosis (AIS), however, the disparities between them and the evidence of their efficacy and effectiveness is still unclear. To evaluate the effectiveness of different conservative treatments on AIS. A literature-based narrative review of the English language medical literature. The most appropriate treatment for each patient should be chosen individually and based on various parameters. Bracing has been found to be a most effective conservative treatment for AIS. There is limited evidence that specific physical exercises also an effective intervention for AIS. Exercise-based physical therapy, if correctly administered, can prevent a worsening of the curve and may decrease need for bracing. In addition, physical exercises were found to be the only treatment improving respiratory function. Combining bracing with exercise increases treatment efficacy compared with a single treatment. Additional, well-designed and good quality studies are required to assess the effectiveness of different conservative methods in treating AIS. Copyright © 2015 Elsevier Ltd. All rights reserved.

Effects of long-term, near-term, and real-time energy balance, and blood progesterone concentrations, on the pregnancy rate of contemporary dairy cows.

PubMed

Gomez, N A; Conley, A J; Robinson, P H

2018-02-01

This study aimed to contribute to understanding the interface between reproductive and nutritional energetic physiology in contemporary dairy cattle. Multiparous Holstein cows (n = 32) between 70 and 180 days in milk were used in a study starting 10 d prior to the artificial insemination (AI) date and were estrous synchronized using a hormonal regimen. Fourteen cows were determined pregnant on day 39 post-AI. Coccygeal blood samples of all cows were collected on d -10 and -3 prior to AI to determine estrous cyclicity, as well as at AI and at 6, 13 and 20 d post-AI. Milk progesterone was measured 20 d post-AI, and body condition was scored (BCS; 1-5 scale) on days -10, 0, 13 and 27 relative to AI. Blood non-esterified fatty acid concentrations, measured on the same days as BCS, and changes of BCS from d -10 to AI were not predictive of pregnancy outcome. The BCS of cows on the day of AI was greater (P = 0.02) for pregnant cows with an approximate minimum BCS for a high probability of conception being 2.50. Serum progesterone concentrations of pregnant cows were greater (P < 0.05) on days 6, 13 and 20 post-AI, as was milk progesterone at day 20 post-AI (P < 0.01). Pregnant cows had greater (P = 0.02) net energy output (NE L ), which is inconsistent with a common belief that low pregnancy rates in contemporary dairy cows are due to excessive milk production, but is consistent with published studies in this study area. The present research indicates that current low pregnancy rates in commercial high-producing multiparous dairy cattle may be partly due to breeding cows that have insufficient BCS to support pregnancy. Published by Elsevier B.V.

Artificial intelligence applications in space and SDI: A survey

NASA Technical Reports Server (NTRS)

Fiala, Harvey E.

1988-01-01

The purpose of this paper is to survey existing and planned Artificial Intelligence (AI) applications to show that they are sufficiently advanced for 32 percent of all space applications and SDI (Space Defense Initiative) software to be AI-based software. To best define the needs that AI can fill in space and SDI programs, this paper enumerates primary areas of research and lists generic application areas. Current and planned NASA and military space projects in AI will be reviewed. This review will be largely in the selected area of expert systems. Finally, direct applications of AI to SDI will be treated. The conclusion covers the importance of AI to space and SDI applications, and conversely, their importance to AI.

Feasibility of the Dutch ICF Activity Inventory: a pilot study

PubMed Central

2010-01-01

Background Demographic ageing will lead to increasing pressure on visual rehabilitation services, which need to be efficiently organised in the near future. The Dutch ICF Activity Inventory (D-AI) was developed to assess the rehabilitation needs of visually impaired persons. This pilot study tests the feasibility of the D-AI using a computer-assisted telephone interview. Methods In addition to the regular intake, the first version of the D-AI was assessed in 20 patients. Subsequently, patients and intake assessors were asked to fill in an evaluation form. Based on these evaluations, a new version of the D-AI was developed. Results Mean administration time of the D-AI was 88.8 (± 41.0) minutes. Overall, patients and assessors were positive about the D-AI assessment. However, professionals and 60% of the patients found the administration time to be too long. All included items were considered relevant and only minor adjustments were recommended. Conclusion The systematic character of the revised D-AI will prevent topics from being overlooked and indicate which needs have the highest priority from a patient-centred perspective. Moreover, ongoing assessment of the D-AI will enhance evaluation of the rehabilitation process. To decrease administration time, in the revised D-AI only the top priority goals will be fully assessed. Using the D-AI, a rehabilitation plan based on individual needs can be developed for each patient. Moreover, it enables better evaluation of the effects of rehabilitation. A larger validation study is planned. PMID:21110871

Refining Stimulus Parameters in Assessing Infant Speech Perception Using Visual Reinforcement Infant Speech Discrimination: Sensation Level.

PubMed

Uhler, Kristin M; Baca, Rosalinda; Dudas, Emily; Fredrickson, Tammy

2015-01-01

Speech perception measures have long been considered an integral piece of the audiological assessment battery. Currently, a prelinguistic, standardized measure of speech perception is missing in the clinical assessment battery for infants and young toddlers. Such a measure would allow systematic assessment of speech perception abilities of infants as well as the potential to investigate the impact early identification of hearing loss and early fitting of amplification have on the auditory pathways. To investigate the impact of sensation level (SL) on the ability of infants with normal hearing (NH) to discriminate /a-i/ and /ba-da/ and to determine if performance on the two contrasts are significantly different in predicting the discrimination criterion. The design was based on a survival analysis model for event occurrence and a repeated measures logistic model for binary outcomes. The outcome for survival analysis was the minimum SL for criterion and the outcome for the logistic regression model was the presence/absence of achieving the criterion. Criterion achievement was designated when an infant's proportion correct score was >0.75 on the discrimination performance task. Twenty-two infants with NH sensitivity participated in this study. There were 9 males and 13 females, aged 6-14 mo. Testing took place over two to three sessions. The first session consisted of a hearing test, threshold assessment of the two speech sounds (/a/ and /i/), and if time and attention allowed, visual reinforcement infant speech discrimination (VRISD). The second session consisted of VRISD assessment for the two test contrasts (/a-i/ and /ba-da/). The presentation level started at 50 dBA. If the infant was unable to successfully achieve criterion (>0.75) at 50 dBA, the presentation level was increased to 70 dBA followed by 60 dBA. Data examination included an event analysis, which provided the probability of criterion distribution across SL. The second stage of the analysis was a repeated measures logistic regression where SL and contrast were used to predict the likelihood of speech discrimination criterion. Infants were able to reach criterion for the /a-i/ contrast at statistically lower SLs when compared to /ba-da/. There were six infants who never reached criterion for /ba-da/ and one never reached criterion for /a-i/. The conditional probability of not reaching criterion by 70 dB SL was 0% for /a-i/ and 21% for /ba-da/. The predictive logistic regression model showed that children were more likely to discriminate the /a-i/ even when controlling for SL. Nearly all normal-hearing infants can demonstrate discrimination criterion of a vowel contrast at 60 dB SL, while a level of ≥70 dB SL may be needed to allow all infants to demonstrate discrimination criterion of a difficult consonant contrast. American Academy of Audiology.

A Survey of Artificial Immune System Based Intrusion Detection

PubMed Central

Li, Tao; Hu, Xinlei; Wang, Feng; Zou, Yang

2014-01-01

In the area of computer security, Intrusion Detection (ID) is a mechanism that attempts to discover abnormal access to computers by analyzing various interactions. There is a lot of literature about ID, but this study only surveys the approaches based on Artificial Immune System (AIS). The use of AIS in ID is an appealing concept in current techniques. This paper summarizes AIS based ID methods from a new view point; moreover, a framework is proposed for the design of AIS based ID Systems (IDSs). This framework is analyzed and discussed based on three core aspects: antibody/antigen encoding, generation algorithm, and evolution mode. Then we collate the commonly used algorithms, their implementation characteristics, and the development of IDSs into this framework. Finally, some of the future challenges in this area are also highlighted. PMID:24790549

GLADIS: GLobal AIS & Data-X International Satellite Constellation

DTIC Science & Technology

2008-01-01

1Approved for public release; distribution is unlimited GLADIS : GLobal AIS & Data-X International Satellite Constellation Space-Based System for...TYPE N/A 3. DATES COVERED - 4. TITLE AND SUBTITLE GLADIS : GLobal AIS & Data-X International Satellite Constellation 5a. CONTRACT NUMBER 5b...Maritime & Technology Challenges • GLADIS Mission Objective • AIS & Data-X capabilities • GLADIS Architecture • International Strategy – MSSIS as Model

Predictive capacity of sperm quality parameters and sperm subpopulations on field fertility after artificial insemination in sheep.

PubMed

Santolaria, P; Vicente-Fiel, S; Palacín, I; Fantova, E; Blasco, M E; Silvestre, M A; Yániz, J L

2015-12-01

This study was designed to evaluate the relevance of several sperm quality parameters and sperm population structure on the reproductive performance after cervical artificial insemination (AI) in sheep. One hundred and thirty-nine ejaculates from 56 adult rams were collected using an artificial vagina, processed for sperm quality assessment and used to perform 1319 AI. Analyses of sperm motility by computer-assisted sperm analysis (CASA), sperm nuclear morphometry by computer-assisted sperm morphometry analysis (CASMA), membrane integrity by acridine orange-propidium iodide combination and sperm DNA fragmentation using the sperm chromatin dispersion test (SCD) were performed. Clustering procedures using the sperm kinematic and morphometric data resulted in the classification of spermatozoa into three kinematic and three morphometric sperm subpopulations. Logistic regression procedures were used, including fertility at AI as the dependent variable (measured by lambing, 0 or 1) and farm, year, month of AI, female parity, female lambing-treatment interval, ram, AI technician and sperm quality parameters (including sperm subpopulations) as independent factors. Sperm quality variables remaining in the logistic regression model were viability and VCL. Fertility increased for each one-unit increase in viability (by a factor of 1.01) and in VCL (by a factor of 1.02). Multiple linear regression analyses were also performed to analyze the factors possibly influencing ejaculate fertility (N=139). The analysis yielded a significant (P<0.05) relationship between sperm viability and ejaculate fertility. The discriminant ability of the different semen variables to predict field fertility was analyzed using receiver operating characteristic (ROC) curve analysis. Sperm viability and VCL showed significant, albeit limited, predictive capacity on field fertility (0.57 and 0.54 Area Under Curve, respectively). The distribution of spermatozoa in the different subpopulations was not related to fertility. Copyright © 2015 Elsevier B.V. All rights reserved.

Reproductive performance of lactating dairy cows managed for first service using timed artificial insemination with or without detection of estrus using an activity-monitoring system.

PubMed

Fricke, P M; Giordano, J O; Valenza, A; Lopes, G; Amundson, M C; Carvalho, P D

2014-05-01

Lactating dairy cows (n=1,025) on a commercial dairy farm were randomly assigned at 10 ± 3 d in milk (DIM) to 1 of 3 treatments for submitting cows to first artificial insemination (AI) and were fitted with activity-monitoring tags (Heatime; SCR Engineers Ltd., Netanya, Israel) at 24 ± 3 DIM. Cows (n=339) in treatment 1 were inseminated based on increased activity from the end of the voluntary waiting period (50 DIM) until submission to an Ovsynch protocol; cows without increased activity from 21 to 65 DIM began an Ovsynch protocol at 65 ± 3 DIM, whereas cows without increased activity from 21 to 50 DIM but not from 51 to 79 DIM began an Ovsynch protocol at 79 ± 3 DIM. Cows (n=340) in treatment 2 were inseminated based on activity after the second PGF2α injection of a Presynch-Ovsynch protocol at 50 DIM, and cows without increased activity began an Ovsynch protocol at 65 ± 3 DIM. Cows (n=346) in treatment 3 were monitored for activity after the second PGF2α injection of a Presynch-Ovsynch protocol, but all cows received timed AI (TAI) at 75 ± 3 DIM after completing the Presynch-Ovsynch protocol. The activity-monitoring system detected increased activity in 56, 69, and 70% of cows in treatments 1, 2, and 3, respectively. Treatment-2 cows had the fewest average days to first AI (62.5), treatment-3 cows had the most average days to first AI (74.9), and treatment-1 cows had intermediate average days to first AI (67.4). Treatment-1 and -2 cows in which inseminations occurred as a combination between increased activity and TAI had fewer overall pregnancies per AI (P/AI) 35 d after AI (32% for both treatments) compared with treatment-3 cows, all of which received TAI after completing the Presynch-Ovsynch protocol (40%). Based on survival analysis, although the rate at which cows were inseminated differed among treatments, treatment did not affect the proportion of cows pregnant by 300 DIM. Thus, use of an activity-monitoring system to inseminate cows based on activity reduced days to first AI, whereas cows receiving 100% TAI after completing a Presynch-Ovsynch protocol had more P/AI. The trade-off between AI service rate and P/AI in the rate at which cows became pregnant was supported by an economic analysis in which the net present value ($/cow per year) differed by only $4 to $8 among treatments. We conclude that a variety of strategies using a combination of AI based on increased activity using an activity-monitoring system and synchronization of ovulation and TAI can be used to submit cows for first AI. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Predicting Help-Seeking Attitudes Toward Mental Health Services Among American Indian Older Adults: Is Andersen's Behavioral Model a Good Fit?

PubMed

Roh, Soonhee; Burnette, Catherine E; Lee, Kyoung Hag; Lee, Yeon-Shim; Martin, James I; Lawler, Michael J

2017-01-01

American Indian (AI) older adults are vulnerable to mental health disparities, yet very little is known about the factors associated with help-seeking for mental health services among them. The purpose of this study was to investigate the utility of Andersen's Behavioral Model in explaining AI older adults' help-seeking attitudes toward professional mental health services. Hierarchical regression analysis was used to examine predisposing, enabling, and need variables as predictors of help-seeking attitudes toward mental health services in a sample of 233 AI older adults from the Midwest. The model was found to have limited utility in the context of older AI help-seeking attitudes, as the proportion of explained variance was low. Gender, perceived stigma, social support, and physical health were significant predictors, whereas age, perceived mental health, and health insurance were not. © The Author(s) 2014.

Predictors of Wellness and American Indians

PubMed Central

Hodge, Felicia S.; Nandy, Karabi

2012-01-01

Wellness is an important American Indian (AI) concept, understood as being in balance with one’s body, mind, and environment. Wellness predictors are reported in this paper within the context of health. A cross-sectional randomized household survey of 457 AI adults at 13 rural health care sites in California was conducted. Measures included wellness perceptions, barriers, health status/health conditions, spirituality, cultural connectivity, high-risk behaviors and abuse history. Statistical analysis obtained the best predictive model for wellness. Predictors of wellness were general health status perception, participation in AI cultural practices and suicide ideation. Significant differences in wellness status were observed depending on experience of adverse events in childhood and adulthood (neglect, physical abuse, and sexual abuse). Cultural connectivity (speaking tribal language, participating in AI practices, and feeling connected to community) was also associated with perceptions of wellness. Recommendations are for culturally-appropriate education and interventions emphasizing community and cultural connectivity for improving wellness status. PMID:21841279

Spinoff 1999

NASA Technical Reports Server (NTRS)

1999-01-01

A survey is presented of NASA-developed technologies and systems that were reaching commercial application in the course of 1999. Attention is given to the contributions of each major NASA Research Center. Representative 'spinoff' technologies include the predictive AI engine monitoring system EMPAS, the GPS-based Wide Area Augmentation System for aircraft navigation, a CMOS-Active Pixel Sensor camera-on-a-chip, a marine spectroradiometer, portable fuel cells, hyperspectral camera technology, and a rapid-prototyping process for ceramic components.

American Indians, substance use, and sexual behavior: do predictors of sexually transmitted infections explain the race gap among young adults?

PubMed

Eitle, David; Greene, Kaylin; Eitle, Tamela McNulty

2015-02-01

In this study, we examined whether substance use and risky sexual behaviors predicted sexually transmitted infections (STIs) among American Indian (AI) and white young adults. Furthermore, we explored whether these factors explained the race disparity in STIs. We conducted a cross-sectional analysis of wave 3 of the National Longitudinal Study of Adolescent Health collected in 2001 to 2002. Young adult participants (aged 18-26 years) provided urine specimens that were tested for chlamydia, gonorrhea, and trichomoniasis infection. Estimates of the association between AI with any STI were adjusted for sexual and other risk behavior correlates using multivariate regression techniques. Nine percent of AIs (n = 367) and 3.6% of whites (n = 7813) tested positive for an STI. Race differences were found for substance use (injection drug use, 3.1% AI vs. 1.3% white; alcohol use frequency, 2.01% AI vs. 2.5% white; binge drinking frequency, 1.25% AI vs. 1.53% white). Among sexually active respondents, AIs were more likely to have paid for sex (9%) than whites (3%). After adjustment, early sexual initiation (adjusted odds ratio, 1.69; 95% confidence interval, 1.19-2.41), no condom use at last sex (adjusted odds ratio, 1.47; 95% confidence interval, 1.08-2.01), and AI race (adjusted odds ratio, 2.45; 95% confidence interval 1.46-4.11) were significantly associated with having an STI. Individual-level sexual and other risk behaviors do not fully explain disparities in STIs among AIs compared with white young adults. Further examination of network and community factors is needed to explain these disparities.

Further validation and definition of the psychometric properties of the Asthma Impact Survey.

PubMed

Schatz, Michael; Zeiger, Robert S; Yang, Su-Jau; Chen, Wansu; Kosinski, Mark

2011-07-01

The Asthma Impact Survey (AIS-6) is a brief disease-specific quality-of-life instrument with limited published validation data. To obtain additional validation data and psychometric properties of the AIS-6. In November, 2007, patients with persistent asthma were mailed a survey that included the AIS-6, the mini-Asthma Quality of Life Questionnaire (mAQLQ), and the Asthma Control Test (ACT). Follow-up surveys were sent in April, July, and October 2008. Year 2008 exacerbations and short-acting β-agonist (SABA) dispensings were captured from administrative data. A total of 2680 patients had complete baseline survey data. Criterion validity was demonstrated by the strong correlations of the AIS-6 with the mAQLQ (r = -0.84 to -0.86); construct validity by significant relationships (P < .0001) of the AIS-6 with mAQLQ domain scores, ACT score, and history of exacerbations; and predictive validity by significant relationships (P < .0001) between AIS-6 scores at the end of 2007 and year 2008 exacerbations and high SABA dispensings. Responsiveness was demonstrated by significant (P < .0001) correlations (r = -0.39 to -0.58) between changes in AIS-6 scores and changes in mAQLQ and ACT scores over time. A preliminary minimally important difference (MID) in AIS-6 was estimated to be 4 by using the mAQLQ MID as an anchor. Excellent internal consistency (α = 0.94) and test-retest reliability (intraclass correlation coefficient = 0.86-0.91) were also demonstrated. The AIS-6 demonstrated good psychometric properties in a large independent sample and could be used to assess asthma-specific quality of life in clinical practice and clinical research. Copyright © 2011 American Academy of Allergy, Asthma & Immunology. Published by Mosby, Inc. All rights reserved.

The aggregate complexity of decisions in the game of Go

NASA Astrophysics Data System (ADS)

Harré, M. S.; Bossomaier, T.; Gillett, A.; Snyder, A.

2011-04-01

Artificial intelligence (AI) research is fast approaching, or perhaps has already reached, a bottleneck whereby further advancement towards practical human-like reasoning in complex tasks needs further quantified input from large studies of human decision-making. Previous studies in psychology, for example, often rely on relatively small cohorts and very specific tasks. These studies have strongly influenced some of the core notions in AI research such as the reinforcement learning and the exploration versus exploitation paradigms. With the goal of contributing to this direction in AI developments we present our findings on the evolution towards world-class decision-making across large cohorts of subjects in the formidable game of Go. Some of these findings directly support previous work on how experts develop their skills but we also report on several previously unknown aspects of the development of expertise that suggests new avenues for AI research to explore. In particular, at the level of play that has so far eluded current AI systems for Go, we are able to quantify the lack of `predictability' of experts and how this changes with their level of skill.

Anisotropic pressure and hyperons in neutron stars

NASA Astrophysics Data System (ADS)

Sulaksono, A.

2015-01-01

We study the effects of anisotropic pressure (AI-P) on properties of the neutron stars (NSs) with hyperons inside its core within the framework of extended relativistic mean field. It is found that the main effects of AI-P on NS matter is to increase the stiffness of the equation of state EOS, which compensates for the softening of the EOS due to the hyperons. The maximum mass and redshift predictions of anisotropic neutron star with hyperonic core are quite compatible with the result of recent observational constraints if we use the parameter of AI-P model h ≤ 0.8 [L. Herrera and W. Barreto, Phys. Rev. D 88 (2013) 084022.] and Λ ≤ -1.15 [D. D. Doneva and S. S. Yazadjiev, Phys. Rev. D 85 (2012) 124023.]. The radius of the corresponding NS at M = 1.4 M⊙ is more than 13 km, while the effect of AI-P on the minimum mass of NS is insignificant. Furthermore, due to the AI-P in the NS, the maximum mass limit of higher than 2.1 M⊙ cannot rule out the presence of hyperons in the NS core.

An AIS-based approach to calculate atmospheric emissions from the UK fishing fleet

NASA Astrophysics Data System (ADS)

Coello, Jonathan; Williams, Ian; Hudson, Dominic A.; Kemp, Simon

2015-08-01

The fishing industry is heavily reliant on the use of fossil fuel and emits large quantities of greenhouse gases and other atmospheric pollutants. Methods used to calculate fishing vessel emissions inventories have traditionally utilised estimates of fuel efficiency per unit of catch. These methods have weaknesses because they do not easily allow temporal and geographical allocation of emissions. A large proportion of fishing and other small commercial vessels are also omitted from global shipping emissions inventories such as the International Maritime Organisation's Greenhouse Gas Studies. This paper demonstrates an activity-based methodology for the production of temporally- and spatially-resolved emissions inventories using data produced by Automatic Identification Systems (AIS). The methodology addresses the issue of how to use AIS data for fleets where not all vessels use AIS technology and how to assign engine load when vessels are towing trawling or dredging gear. The results of this are compared to a fuel-based methodology using publicly available European Commission fisheries data on fuel efficiency and annual catch. The results show relatively good agreement between the two methodologies, with an estimate of 295.7 kilotons of fuel used and 914.4 kilotons of carbon dioxide emitted between May 2012 and May 2013 using the activity-based methodology. Different methods of calculating speed using AIS data are also compared. The results indicate that using the speed data contained directly in the AIS data is preferable to calculating speed from the distance and time interval between consecutive AIS data points.

Improving adult immunization equity: Where do the published research literature and existing resources lead?

PubMed

Prins, Wendy; Butcher, Emily; Hall, Laura Lee; Puckrein, Gary; Rosof, Bernard

2017-05-25

Evidence suggests that disparities in adult immunization (AI) rates are growing. Providers need adequate patient resources and information about successful interventions to help them engage in effective practices to reduce AI disparities. The primary purposes of this paper were to review and summarize the evidence base regarding interventions to reduce AI disparities and to scan for relevant resources that could support providers in their AI efforts to specifically target disparities. First, building on a literature review conducted by the U.S. Centers for Disease Control and Prevention, we searched the peer-reviewed literature to identify articles that either discussed interventions to reduce AI disparities or provided reasons and associations for disparities. We scanned the articles and conducted an internet search to identify tools and resources to support efforts to improve AI rates. We limited both searches to resources that addressed influenza, pneumococcal, hepatitis B, Tdap, and/or herpes zoster vaccinations. We found that most articles characterized AI disparities, but several discussed strategies for reducing AI disparities, including practice-based changes, communication and health literacy approaches, and partnering with community-based organizations. The resources we identified were largely fact sheets and handouts for patients and journal articles for providers. Most resources pertain to influenza vaccination and Spanish was the most prevalent language after English. More evaluation is needed to assess the health literacy levels of the materials. We conclude that additional research is needed to identify effective ways to reduce AI disparities and more resources are needed to support providers in their efforts. We recommend identifying best practices of high performers, further reviewing the appropriateness and usefulness of available resources, and prioritizing which gaps should be addressed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Subtyping pathological gamblers based on impulsivity, depression and anxiety

PubMed Central

Ledgerwood, David M.; Petry, Nancy M.

2010-01-01

This study examined putative subtypes of pathological gamblers (PGs) based on the Pathways Model, and it also evaluated whether the subtypes would benefit differentially from treatment. Treatment-seeking PGs (N = 229) were categorized into Pathways subtypes based on scores from questionnaires assessing anxiety, depression and impulsivity. The Addiction Severity Index Gambling assessed severity of gambling problems at baseline, post-treatment and 12-month follow-up. Compared with Behaviorally Conditioned (BC) gamblers, Emotionally Vulnerable (EV) gamblers had higher psychiatric and gambling severity, and were more likely to have a parent with a psychiatric history. Antisocial Impulsive (AI) gamblers also had elevated gambling and psychiatric severity relative to BC gamblers. They were more likely to have antisocial personality disorder and had the highest legal and family/social severity scores. They were also most likely to have a history of substance abuse treatment, history of inpatient psychiatric treatment, and a parent with a substance use or gambling problem. AI and EV gamblers experienced greater gambling severity throughout treatment than BC gamblers, but all three subtypes demonstrated similar patterns of treatment response. Thus, the three Pathways subtypes differ based on some baseline characteristics, but subtyping did not predict treatment outcomes beyond a simple association with problem gambling severity. PMID:20822191

Waterway Performance Monitoring via Automatic Identification System (AIS) Data

DTIC Science & Technology

2013-08-01

Transceivers onboard the vessels broadcast the 4 AIS signal containing position, heading, speed, and other identifying information to shore- based 5 towers...Great Lakes system based 31 on the voyage histories reconstructed with the Destination field from the AIS static reports. In 32 spite of the much... Information Systems for Estimating Coastal Maritime Risk. 38 Transportation Research Record: Journal of the Transportation Research Board, No. 2222, 39 TRB

Application of the KeratinoSens™ assay for assessing the skin sensitization potential of agrochemical active ingredients and formulations.

PubMed

Settivari, Raja S; Gehen, Sean C; Amado, Ricardo Acosta; Visconti, Nicolo R; Boverhof, Darrell R; Carney, Edward W

2015-07-01

Assessment of skin sensitization potential is an important component of the safety evaluation process for agrochemical products. Recently, non-animal approaches including the KeratinoSens™ assay have been developed for predicting skin sensitization potential. Assessing the utility of the KeratinoSens™ assay for use with multi-component mixtures such as agrochemical formulations has not been previously evaluated and is a significant need. This study was undertaken to evaluate the KeratinoSens™ assay prediction potential for agrochemical formulations. The assay was conducted for 8 agrochemical active ingredients (AIs) including 3 sensitizers (acetochlor, meptyldinocap, triclopyr), 5 non-sensitizers (aminopyralid, clopyralid, florasulam, methoxyfenozide, oxyfluorfen) and 10 formulations for which in vivo sensitization data were available. The KeratinoSens™ correctly predicted the sensitization potential of all the AIs. For agrochemical formulations it was necessary to modify the standard assay procedure whereby the formulation was assumed to have a common molecular weight. The resultant approach correctly predicted the sensitization potential for 3 of 4 sensitizing formulations and all 6 non-sensitizing formulations when compared to in vivo data. Only the meptyldinocap-containing formulation was misclassified, as a result of high cytotoxicity. These results demonstrate the promising utility of the KeratinoSens™ assay for evaluating the skin sensitization potential of agrochemical AIs and formulations. Copyright © 2015 Elsevier Inc. All rights reserved.

Lipid-related markers and cardiovascular disease prediction.

PubMed

Di Angelantonio, Emanuele; Gao, Pei; Pennells, Lisa; Kaptoge, Stephen; Caslake, Muriel; Thompson, Alexander; Butterworth, Adam S; Sarwar, Nadeem; Wormser, David; Saleheen, Danish; Ballantyne, Christie M; Psaty, Bruce M; Sundström, Johan; Ridker, Paul M; Nagel, Dorothea; Gillum, Richard F; Ford, Ian; Ducimetiere, Pierre; Kiechl, Stefan; Koenig, Wolfgang; Dullaart, Robin P F; Assmann, Gerd; D'Agostino, Ralph B; Dagenais, Gilles R; Cooper, Jackie A; Kromhout, Daan; Onat, Altan; Tipping, Robert W; Gómez-de-la-Cámara, Agustín; Rosengren, Annika; Sutherland, Susan E; Gallacher, John; Fowkes, F Gerry R; Casiglia, Edoardo; Hofman, Albert; Salomaa, Veikko; Barrett-Connor, Elizabeth; Clarke, Robert; Brunner, Eric; Jukema, J Wouter; Simons, Leon A; Sandhu, Manjinder; Wareham, Nicholas J; Khaw, Kay-Tee; Kauhanen, Jussi; Salonen, Jukka T; Howard, William J; Nordestgaard, Børge G; Wood, Angela M; Thompson, Simon G; Boekholdt, S Matthijs; Sattar, Naveed; Packard, Chris; Gudnason, Vilmundur; Danesh, John

2012-06-20

The value of assessing various emerging lipid-related markers for prediction of first cardiovascular events is debated. To determine whether adding information on apolipoprotein B and apolipoprotein A-I, lipoprotein(a), or lipoprotein-associated phospholipase A2 to total cholesterol and high-density lipoprotein cholesterol (HDL-C) improves cardiovascular disease (CVD) risk prediction. Individual records were available for 165,544 participants without baseline CVD in 37 prospective cohorts (calendar years of recruitment: 1968-2007) with up to 15,126 incident fatal or nonfatal CVD outcomes (10,132 CHD and 4994 stroke outcomes) during a median follow-up of 10.4 years (interquartile range, 7.6-14 years). Discrimination of CVD outcomes and reclassification of participants across predicted 10-year risk categories of low (<10%), intermediate (10%-<20%), and high (≥20%) risk. The addition of information on various lipid-related markers to total cholesterol, HDL-C, and other conventional risk factors yielded improvement in the model's discrimination: C-index change, 0.0006 (95% CI, 0.0002-0.0009) for the combination of apolipoprotein B and A-I; 0.0016 (95% CI, 0.0009-0.0023) for lipoprotein(a); and 0.0018 (95% CI, 0.0010-0.0026) for lipoprotein-associated phospholipase A2 mass. Net reclassification improvements were less than 1% with the addition of each of these markers to risk scores containing conventional risk factors. We estimated that for 100,000 adults aged 40 years or older, 15,436 would be initially classified at intermediate risk using conventional risk factors alone. Additional testing with a combination of apolipoprotein B and A-I would reclassify 1.1%; lipoprotein(a), 4.1%; and lipoprotein-associated phospholipase A2 mass, 2.7% of people to a 20% or higher predicted CVD risk category and, therefore, in need of statin treatment under Adult Treatment Panel III guidelines. In a study of individuals without known CVD, the addition of information on the combination of apolipoprotein B and A-I, lipoprotein(a), or lipoprotein-associated phospholipase A2 mass to risk scores containing total cholesterol and HDL-C led to slight improvement in CVD prediction.

A virus spreading model for cognitive radio networks

NASA Astrophysics Data System (ADS)

Hou, L.; Yeung, K. H.; Wong, K. Y.

2012-12-01

Since cognitive radio (CR) networks could solve the spectrum scarcity problem, they have drawn much research in recent years. Artificial intelligence(AI) is introduced into CRs to learn from and adapt to their environment. Nonetheless, AI brings in a new kind of attacks specific to CR networks. The most powerful one is a self-propagating AI virus. And no spreading properties specific to this virus have been reported in the literature. To fill this research gap, we propose a virus spreading model of an AI virus by considering the characteristics of CR networks and the behavior of CR users. Several important observations are made from the simulation results based on the model. Firstly, the time taken to infect the whole network increases exponentially with the network size. Based on this result, CR network designers could calculate the optimal network size to slow down AI virus propagation rate. Secondly, the anti-virus performance of static networks to an AI virus is better than dynamic networks. Thirdly, if the CR devices with the highest degree are initially infected, the AI virus propagation rate will be increased substantially. Finally, it is also found that in the area with abundant spectrum resource, the AI virus propagation speed increases notably but the variability of the spectrum does not affect the propagation speed much.

L-Arabinose isomerase and its use for biotechnological production of rare sugars.

PubMed

Xu, Zheng; Li, Sha; Feng, Xiaohai; Liang, Jinfeng; Xu, Hong

2014-11-01

L-Arabinose isomerase (AI), a key enzyme in the microbial pentose phosphate pathway, has been regarded as an important biological catalyst in rare sugar production. This enzyme could isomerize L-arabinose into L-ribulose, as well as D-galactose into D-tagatose. Both the two monosaccharides show excellent commercial values in food and pharmaceutical industries. With the identification of novel AI family members, some of them have exhibited remarkable potential in industrial applications. The biological production processes for D-tagatose and L-ribose (or L-ribulose) using AI have been developed and improved in recent years. Meanwhile, protein engineering techniques involving rational design has effectively enhanced the catalytic properties of various AIs. Moreover, the crystal structure of AI has been disclosed, which sheds light on the understanding of AI structure and catalytic mechanism at molecular levels. This article reports recent developments in (i) novel AI screening, (ii) AI-mediated rare sugar production processes, (iii) molecular modification of AI, and (iv) structural biology study of AI. Based on previous reports, an analysis of the future development has also been initiated.

Artificial intelligence techniques used in respiratory sound analysis--a systematic review.

PubMed

Palaniappan, Rajkumar; Sundaraj, Kenneth; Sundaraj, Sebastian

2014-02-01

Artificial intelligence (AI) has recently been established as an alternative method to many conventional methods. The implementation of AI techniques for respiratory sound analysis can assist medical professionals in the diagnosis of lung pathologies. This article highlights the importance of AI techniques in the implementation of computer-based respiratory sound analysis. Articles on computer-based respiratory sound analysis using AI techniques were identified by searches conducted on various electronic resources, such as the IEEE, Springer, Elsevier, PubMed, and ACM digital library databases. Brief descriptions of the types of respiratory sounds and their respective characteristics are provided. We then analyzed each of the previous studies to determine the specific respiratory sounds/pathology analyzed, the number of subjects, the signal processing method used, the AI techniques used, and the performance of the AI technique used in the analysis of respiratory sounds. A detailed description of each of these studies is provided. In conclusion, this article provides recommendations for further advancements in respiratory sound analysis.

Mapping AIS coverage for trusted surveillance

NASA Astrophysics Data System (ADS)

Lapinski, Anna-Liesa S.; Isenor, Anthony W.

2010-10-01

Automatic Identification System (AIS) is an unattended vessel reporting system developed for collision avoidance. Shipboard AIS equipment automatically broadcasts vessel positional data at regular intervals. The real-time position and identity data from a vessel is received by other vessels in the area thereby assisting with local navigation. As well, AIS broadcasts are beneficial to those concerned with coastal and harbour security. Land-based AIS receiving stations can also collect the AIS broadcasts. However, reception at the land station is dependent upon the ship's position relative to the receiving station. For AIS to be used as a trusted surveillance system, the characteristics of the AIS coverage area in the vicinity of the station (or stations) should be understood. This paper presents some results of a method being investigated at DRDC Atlantic, Canada) to map the AIS coverage characteristics of a dynamic AIS reception network. The method is shown to clearly distinguish AIS reception edges from those edges caused by vessel traffic patterns. The method can also be used to identify temporal changes in the coverage area, an important characteristic for local maritime security surveillance activities. Future research using the coverage estimate technique is also proposed to support surveillance activities.

Predictive value of flat-panel CT for haemorrhagic transformations in patients with acute stroke treated with thrombectomy.

PubMed

Rouchaud, Aymeric; Pistocchi, Silvia; Blanc, Raphaël; Engrand, Nicolas; Bartolini, Bruno; Piotin, Michel

2014-03-01

Haemorrhagic transformations are pejorative for patients with acute ischaemic stroke (AIS). We estimated flat-panel CT performances to detect brain parenchymal hyperdense lesions immediately after mechanical thrombectomy directly on the angiography table in patients with AIS, and its ability to predict haemorrhagic transformation. We also evaluated an easy-reading protocol for post-procedure flat-panel CT evaluation by clinicians to enable them to determine the potential risk of haemorrhage. Two neuroradiologists retrospectively reviewed post-procedural flat-panel CT and 24 h follow-up imaging. We evaluated hyperdense lesions on flat-panel CT to predict the occurrence of haemorrhagic transformation within 24 h detected with conventional imaging. Of 63 patients, 60.3% presented post-procedural parenchymal hyperdensity and 54.0% had haemorrhagic transformation. Significantly more patients with hyperdense lesions on post-thrombectomy flat-panel CT presented haemorrhagic transformation (84.2% vs 8.0%; p<0.0001). No significant haemorrhagic transformations were detected for patients without parenchymal hyperdensity. Sensitivity and specificity of hyperdense lesions on flat-panel CT for the prediction of haemorrhagic transformation were 94.1% (80.3-99.3%) and 79.3% (60.3-92.0%), respectively. The positive and negative predictive values for the occurrence of haemorrhage were 84.2% (68.8-94.0%) and 92.0% (74.0-99.0%), respectively. For significant parenchymal haemorrhage type 2, sensitivity and negative predictive values were 100%. We observed good homogeneity between the different readers. Hyperdensity on post-procedural flat-panel CT was associated with a tendency for higher risk of death and lower risk of good clinical outcome. Flat-panel CT appears to be a good tool to detect brain parenchymal hyperdensities after mechanical thrombectomy in patients with AIS and to predict haemorrhagic transformation.

Early Detection of Progressive Adolescent Idiopathic Scoliosis: A Severity Index.

PubMed

Skalli, Wafa; Vergari, Claudio; Ebermeyer, Eric; Courtois, Isabelle; Drevelle, Xavier; Kohler, Remi; Abelin-Genevois, Kariman; Dubousset, Jean

2017-06-01

Early detection of progressive adolescent idiopathic scoliosis (AIS) was assessed based on 3D quantification of the deformity. Based on 3D quantitative description of scoliosis curves, the aim is to assess a specific phenotype that could be an early detectable severity index for progressive AIS. Early detection of progressive scoliosis is important for adapted treatment to limit progression. However, progression risk assessment is mainly based on the follow up, waiting for signs of rapid progression that generally occur during the growth peak. Sixty-five mild scoliosis (16 boys, 49 girls, Cobb Angle between 10 and 20°) with a Risser between 0 and 2 were followed from their first examination until a decision was made by the clinician, either considering the spine as stable at the end of growth (26 patients) or planning to brace because of progression (39 patients). Calibrated biplanar x-rays were performed and 3D reconstructions of the spine allowed calculating six local parameters related to main curve deformity. For progressive curve 3D phenotype assessment, data were compared with those previously assessed for 30 severe scoliosis (Cobb Angle > 35°), 17 scoliosis before brace (Cobb Angle > 29°) and 53 spines of nonscoliosis subjects. A predictive discriminant analysis was performed to assess similarity of mild scoliosis curves either to those of scoliosis or nonscoliosis spines, yielding a severity index (S-index). S-index value at first examination was compared with clinical outcome. At the first exam, 53 out of 65 predictions (82%) were in agreement with actual clinical outcome. Approximately, 89% of the curves that were predicted as progressive proved accurate. Although still requiring large scale validation, results are promising for early detection of progressive curves. 2.

Automated Cervical Screening and Triage, Based on HPV Testing and Computer-Interpreted Cytology.

PubMed

Yu, Kai; Hyun, Noorie; Fetterman, Barbara; Lorey, Thomas; Raine-Bennett, Tina R; Zhang, Han; Stamps, Robin E; Poitras, Nancy E; Wheeler, William; Befano, Brian; Gage, Julia C; Castle, Philip E; Wentzensen, Nicolas; Schiffman, Mark

2018-04-11

State-of-the-art cervical cancer prevention includes human papillomavirus (HPV) vaccination among adolescents and screening/treatment of cervical precancer (CIN3/AIS and, less strictly, CIN2) among adults. HPV testing provides sensitive detection of precancer but, to reduce overtreatment, secondary "triage" is needed to predict women at highest risk. Those with the highest-risk HPV types or abnormal cytology are commonly referred to colposcopy; however, expert cytology services are critically lacking in many regions. To permit completely automatable cervical screening/triage, we designed and validated a novel triage method, a cytologic risk score algorithm based on computer-scanned liquid-based slide features (FocalPoint, BD, Burlington, NC). We compared it with abnormal cytology in predicting precancer among 1839 women testing HPV positive (HC2, Qiagen, Germantown, MD) in 2010 at Kaiser Permanente Northern California (KPNC). Precancer outcomes were ascertained by record linkage. As additional validation, we compared the algorithm prospectively with cytology results among 243 807 women screened at KPNC (2016-2017). All statistical tests were two-sided. Among HPV-positive women, the algorithm matched the triage performance of abnormal cytology. Combined with HPV16/18/45 typing (Onclarity, BD, Sparks, MD), the automatable strategy referred 91.7% of HPV-positive CIN3/AIS cases to immediate colposcopy while deferring 38.4% of all HPV-positive women to one-year retesting (compared with 89.1% and 37.4%, respectively, for typing and cytology triage). In the 2016-2017 validation, the predicted risk scores strongly correlated with cytology (P < .001). High-quality cervical screening and triage performance is achievable using this completely automated approach. Automated technology could permit extension of high-quality cervical screening/triage coverage to currently underserved regions.

Axon Initial Segment Cytoskeleton: Architecture, Development, and Role in Neuron Polarity

PubMed Central

Svitkina, Tatyana M.

2016-01-01

The axon initial segment (AIS) is a specialized structure in neurons that resides in between axonal and somatodendritic domains. The localization of the AIS in neurons is ideal for its two major functions: it serves as the site of action potential firing and helps to maintain neuron polarity. It has become increasingly clear that the AIS cytoskeleton is fundamental to AIS functions. In this review, we discuss current understanding of the AIS cytoskeleton with particular interest in its unique architecture and role in maintenance of neuron polarity. The AIS cytoskeleton is divided into two parts, submembrane and cytoplasmic, based on localization, function, and molecular composition. Recent studies using electron and subdiffraction fluorescence microscopy indicate that submembrane cytoskeletal components (ankyrin G, βIV-spectrin, and actin filaments) form a sophisticated network in the AIS that is conceptually similar to the polygonal/triangular network of erythrocytes, with some important differences. Components of the AIS cytoplasmic cytoskeleton (microtubules, actin filaments, and neurofilaments) reside deeper within the AIS shaft and display structural features distinct from other neuronal domains. We discuss how the AIS submembrane and cytoplasmic cytoskeletons contribute to different aspects of AIS polarity function and highlight recent advances in understanding their AIS cytoskeletal assembly and stability. PMID:27493806

The Impact of Pre-Hospital Administration of Lactated Ringer's Solution versus Normal Saline in Patients with Traumatic Brain Injury

PubMed Central

Rowell, Susan E.; Barbosa, Ronald R.; Watters, Jennifer M.; Bulger, Eileen M.; Holcomb, John B.; Cohen, Mitchell J.; Rahbar, Mohammad H.; Fox, Erin E.; Schreiber, Martin A.

2016-01-01

Abstract Lactated Ringer's (LR) and normal saline (NS) are both used for resuscitation of injured patients. NS has been associated with increased resuscitation volume, blood loss, acidosis, and coagulopathy compared with LR. We sought to determine if pre-hospital LR is associated with improved outcome compared with NS in patients with and without traumatic brain injury (TBI). We included patients receiving pre-hospital LR or NS from the PRospective Observational Multicenter Major Trauma Transfusion (PROMMTT) study. Patients with TBI (Abbreviated Injury Scale [AIS] head ≥3) and without TBI (AIS head ≤2) were compared. Cox proportional hazards models including Injury Severity Score (ISS), AIS head, AIS extremity, age, fluids, intubation status, and hospital site were generated for prediction of mortality. Linear regression models were generated for prediction of red blood cell (RBC) and crystalloid requirement, and admission biochemical/physiological parameters. Seven hundred ninety-one patients received either LR (n = 117) or NS (n = 674). Median ISS, AIS head, AIS extremity, and pre-hospital fluid volume were higher in TBI and non-TBI patients receiving LR compared with NS (p < 0.01). In patients with TBI (n = 308), LR was associated with higher adjusted mortality compared with NS (hazard rate [HR] = 1.78, confidence interval [CI] 1.04–3.04, p = 0.035). In patients without TBI (n = 483), no difference in mortality was demonstrated (HR = 1.49, CI 0.757–2.95, p = 0.247). Fluid type had no effect on admission biochemical or physiological parameters, 6-hour RBC, or crystalloid requirement in either group. LR was associated with increased mortality compared with NS in patients with TBI. These results underscore the need for a prospective randomized trial comparing pre-hospital LR with NS in patients with TBI. PMID:26914721

Expert Perspectives on Time Sensitivity and a Related Metric for Children Involved in Motor Vehicle Crashes.

PubMed

Doud, Andrea N; Schoell, Samantha L; Weaver, Ashley A; Talton, Jennifer W; Barnard, Ryan T; Petty, John K; Meredith, J Wayne; Stitzel, Joel D

2017-04-01

Advanced Automatic Crash Notification (AACN) uses vehicle telemetry data to predict risk of serious injury among motor vehicle crash occupants and can thus improve the accuracy with which injured children are triaged by first responders. To better define serious injury for AACN systems (which typically use Abbreviated Injury Scale [AIS] metrics), an age-specific approach evaluating severity, time sensitivity (TS), and predictability of injury has been developed. This study outlines the development of the TS score. The 95% most frequent AIS 2+ injuries in a national motor vehicle crash data set spanning 2000 to 2011 were determined for the following age groups: 0 to 4, 5 to 9, 10 to 14, and 15 to 18 years. For each age-specific injury, clinicians with pediatric trauma expertise were asked if treatment at a trauma center was required and were asked about the urgency of treatment. A TS score (range 0-1) was calculated by combining the mean trauma center decision and urgency scores. A total of 30 to 32 responses were obtained for each age-specific injury. The most frequent motor vehicle crash-induced injuries in the younger groups received significantly higher scores than those in the older groups (median TS score 0 to 4 years: 0.89, 5-9 years: 0.87, 10-14 years: 0.82, 15-18 years: 0.72, P < .001). Large variations in TS existed within each AIS severity level; for example, scores among AIS 2 injuries in 0- to 4-year-olds ranged from 0.12 to 0.98. The TS of common pediatric injuries varies on the basis of age and may not be accurately reflected by AIS metrics. AIS may not capture all aspects of injury that should be considered by AACN systems. Copyright © 2016 Academic Pediatric Association. Published by Elsevier Inc. All rights reserved.

Process evaluation of appreciative inquiry to translate pain management evidence into pediatric nursing practice

PubMed Central

2010-01-01

Background Appreciative inquiry (AI) is an innovative knowledge translation (KT) intervention that is compatible with the Promoting Action on Research in Health Services (PARiHS) framework. This study explored the innovative use of AI as a theoretically based KT intervention applied to a clinical issue in an inpatient pediatric care setting. The implementation of AI was explored in terms of its acceptability, fidelity, and feasibility as a KT intervention in pain management. Methods A mixed-methods case study design was used. The case was a surgical unit in a pediatric academic-affiliated hospital. The sample consisted of nurses in leadership positions and staff nurses interested in the study. Data on the AI intervention implementation were collected by digitally recording the AI sessions, maintaining logs, and conducting individual semistructured interviews. Data were analysed using qualitative and quantitative content analyses and descriptive statistics. Findings were triangulated in the discussion. Results Three nurse leaders and nine staff members participated in the study. Participants were generally satisfied with the intervention, which consisted of four 3-hour, interactive AI sessions delivered over two weeks to promote change based on positive examples of pain management in the unit and staff implementation of an action plan. The AI sessions were delivered with high fidelity and 11 of 12 participants attended all four sessions, where they developed an action plan to enhance evidence-based pain assessment documentation. Participants labeled AI a 'refreshing approach to change' because it was positive, democratic, and built on existing practices. Several barriers affected their implementation of the action plan, including a context of change overload, logistics, busyness, and a lack of organised follow-up. Conclusions Results of this case study supported the acceptability, fidelity, and feasibility of AI as a KT intervention in pain management. The AI intervention requires minor refinements (e.g., incorporating continued follow-up meetings) to enhance its clinical utility and sustainability. The implementation process and effectiveness of the modified AI intervention require evaluation in a larger multisite study. PMID:21092118

AI-based (ANN and SVM) statistical downscaling methods for precipitation estimation under climate change scenarios

NASA Astrophysics Data System (ADS)

Mehrvand, Masoud; Baghanam, Aida Hosseini; Razzaghzadeh, Zahra; Nourani, Vahid

2017-04-01

Since statistical downscaling methods are the most largely used models to study hydrologic impact studies under climate change scenarios, nonlinear regression models known as Artificial Intelligence (AI)-based models such as Artificial Neural Network (ANN) and Support Vector Machine (SVM) have been used to spatially downscale the precipitation outputs of Global Climate Models (GCMs). The study has been carried out using GCM and station data over GCM grid points located around the Peace-Tampa Bay watershed weather stations. Before downscaling with AI-based model, correlation coefficient values have been computed between a few selected large-scale predictor variables and local scale predictands to select the most effective predictors. The selected predictors are then assessed considering grid location for the site in question. In order to increase AI-based downscaling model accuracy pre-processing has been developed on precipitation time series. In this way, the precipitation data derived from various GCM data analyzed thoroughly to find the highest value of correlation coefficient between GCM-based historical data and station precipitation data. Both GCM and station precipitation time series have been assessed by comparing mean and variances over specific intervals. Results indicated that there is similar trend between GCM and station precipitation data; however station data has non-stationary time series while GCM data does not. Finally AI-based downscaling model have been applied to several GCMs with selected predictors by targeting local precipitation time series as predictand. The consequences of recent step have been used to produce multiple ensembles of downscaled AI-based models.

Applications of Artificial Intelligence in Education--A Personal View.

ERIC Educational Resources Information Center

Richer, Mark H.

1985-01-01

Discusses: how artificial intelligence (AI) can advance education; if the future of software lies in AI; the roots of intelligent computer-assisted instruction; protocol analysis; reactive environments; LOGO programming language; student modeling and coaching; and knowledge-based instructional programs. Numerous examples of AI programs are cited.…

Health Data Entanglement and artificial intelligence-based analysis: a brand new methodology to improve the effectiveness of healthcare services.

PubMed

Capone, A; Cicchetti, A; Mennini, F S; Marcellusi, A; Baio, G; Favato, G

2016-01-01

Healthcare expenses will be the most relevant policy issue for most governments in the EU and in the USA. This expenditure can be associated with two major key categories: demographic and economic drivers. Factors driving healthcare expenditure were rarely recognised, measured and comprehended. An improvement of health data generation and analysis is mandatory, and in order to tackle healthcare spending growth, it may be useful to design and implement an effective, advanced system to generate and analyse these data. A methodological approach relied upon the Health Data Entanglement (HDE) can be a suitable option. By definition, in the HDE a large amount of data sets having several sources are functionally interconnected and computed through learning machines that generate patterns of highly probable future health conditions of a population. Entanglement concept is borrowed from quantum physics and means that multiple particles (information) are linked together in a way such that the measurement of one particle's quantum state (individual health conditions and related economic requirements) determines the possible quantum states of other particles (population health forecasts to predict their impact). The value created by the HDE is based on the combined evaluation of clinical, economic and social effects generated by health interventions. To predict the future health conditions of a population, analyses of data are performed using self-learning AI, in which sequential decisions are based on Bayesian algorithmic probabilities. HDE and AI-based analysis can be adopted to improve the effectiveness of the health governance system in ways that also lead to better quality of care.

Renal alpha-smooth muscle actin: a new prognostic factor for lupus nephritis.

PubMed

Makni, Kaouthar; Jarraya, Faïçal; Khabir, Abdelmajid; Hentati, Basma; Hmida, Mohamed Ben; Makni, Hafedh; Boudawara, Tahia; Jlidi, Rchid; Hachicha, Jamil; Ayadi, Hammadi

2009-08-01

Systemic lupus erythematosus (SLE) is the prototype of autoimmune disease where renal involvement is frequent and always severe. Histological prognostic factors proposed for lupus nephritis (LN) including the World Health Organization and International Society of Nephrology/Renal Pathology Society--Working Group on the Classification classifications, active (AI) and chronicity (CI) indices may not predict response to treatment. The aim of this study was to correlate alpha-smooth muscle actin (alpha-SMA) expression, an early marker of glomerular and interstitial response to injury, to AI and CI, renal scarring progression and response to treatment. Fifty-seven kidney biopsy specimens obtained from 32 patients suffering from LN were studied. Twenty patients with class IV LN at first biopsy were identified to study renal progression to chronic renal failure until the use of immunosuppressive treatment. Interstitial alpha-SMA (I-alpha-SMA) was correlated only with CI (P < 0.001) whereas mesangial alpha-SMA (M-alpha-SMA) was correlated with neither LN activity (P = 0.126) nor sclerosis (P = 0.297). Only I-alpha-SMA was correlated with renal failure (P = 0.01). We divided patients with class IV LN into progressors and non-progressors based on the slope of serum creatinine. At first biopsy, M-alpha-SMA and I-alpha-SMA, but not AI and CI, were correlated with renal failure progression (M-alpha-SMA, 9.7b1.1 vs 7.8b1.4, P = 0.004; and I-alpha-SMA, 9.3b1.1 vs 6.5b3.2, P = 0.011). The study data highlight that I-alpha-SMA immunostain in class IV LN patients was correlated with chronicity indices. Moreover, M-alpha-SMA and I-alpha-SMA expression in first biopsy predicted renal progression modality. alpha-SMA expression may therefore be a useful marker to predict renal prognosis in LN.

Multi-time-step ahead daily and hourly intermittent reservoir inflow prediction by artificial intelligent techniques using lumped and distributed data

NASA Astrophysics Data System (ADS)

Jothiprakash, V.; Magar, R. B.

2012-07-01

SummaryIn this study, artificial intelligent (AI) techniques such as artificial neural network (ANN), Adaptive neuro-fuzzy inference system (ANFIS) and Linear genetic programming (LGP) are used to predict daily and hourly multi-time-step ahead intermittent reservoir inflow. To illustrate the applicability of AI techniques, intermittent Koyna river watershed in Maharashtra, India is chosen as a case study. Based on the observed daily and hourly rainfall and reservoir inflow various types of time-series, cause-effect and combined models are developed with lumped and distributed input data. Further, the model performance was evaluated using various performance criteria. From the results, it is found that the performances of LGP models are found to be superior to ANN and ANFIS models especially in predicting the peak inflows for both daily and hourly time-step. A detailed comparison of the overall performance indicated that the combined input model (combination of rainfall and inflow) performed better in both lumped and distributed input data modelling. It was observed that the lumped input data models performed slightly better because; apart from reducing the noise in the data, the better techniques and their training approach, appropriate selection of network architecture, required inputs, and also training-testing ratios of the data set. The slight poor performance of distributed data is due to large variations and lesser number of observed values.

Coupling artificial intelligence and numerical computation for engineering design (Invited paper)

NASA Astrophysics Data System (ADS)

Tong, S. S.

1986-01-01

The possibility of combining artificial intelligence (AI) systems and numerical computation methods for engineering designs is considered. Attention is given to three possible areas of application involving fan design, controlled vortex design of turbine stage blade angles, and preliminary design of turbine cascade profiles. Among the AI techniques discussed are: knowledge-based systems; intelligent search; and pattern recognition systems. The potential cost and performance advantages of an AI-based design-generation system are discussed in detail.

Architecture studies and system demonstrations for optical parallel processor for AI and NI

NASA Astrophysics Data System (ADS)

Lee, Sing H.

1988-03-01

In solving deterministic AI problems the data search for matching the arguments of a PROLOG expression causes serious bottleneck when implemented sequentially by electronic systems. To overcome this bottleneck we have developed the concepts for an optical expert system based on matrix-algebraic formulation, which will be suitable for parallel optical implementation. The optical AI system based on matrix-algebraic formation will offer distinct advantages for parallel search, adult learning, etc.

Adventures in supercomputing: Scientific exploration in an era of change

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gentry, E.; Helland, B.; Summers, B.

1997-11-01

Students deserve the opportunity to explore the world of science surrounding them. Therefore it is important that scientific exploration and investigation be a part of each student`s educational career. The Department of Energy`s Adventures in Superconducting (AiS) takes students beyond mere scientific literacy to a rich embodiment of scientific exploration. AiS provides today`s science and math students with a greater opportunity to investigate science problems, propose solutions, explore different methods of solving the problem, organize their work into a technical paper, and present their results. Students learn at different rates in different ways. Science classes with students having varying learningmore » styles and levels of achievement have always been a challenge for teachers. The AiS {open_quotes}hands-on, minds-on{close_quotes} project-based method of teaching science meets the challenge of this diversity heads on! AiS uses the development of student chosen projects as the means of achieving a lifelong enthusiasm for scientific proficiency. One goal of AiS is to emulate the research that takes place in the everyday environment of scientists. Students work in teams and often collaborate with students nationwide. With the help of mentors from the academic and scientific community, students pose a problem in science, investigate possible solutions, design a mathematical and computational model for the problem, exercise the model to achieve results, and evaluate the implications of the results. The students then have the opportunity to present the project to their peers, teachers, and scientists. Using this inquiry-based technique, students learn more than science skills, they learn to reason and think -- going well beyond the National Science Education Standard. The teacher becomes a resource person actively working together with the students in their quest for scientific knowledge.« less

Community-Based Study Recruitment of American Indian Cigarette Smokers and Electronic Cigarette Users.

PubMed

Carroll, Dana Mowls; Brame, Lacy S; Stephens, Lancer D; Wagener, Theodore L; Campbell, Janis E; Beebe, Laura A

2018-02-01

Data on the effectiveness of strategies for the recruitment of American Indians (AIs) into research is needed. This study describes and compares methods for identifying and recruiting AI tobacco users into a pilot study. Community-based strategies were used to recruit smokers (n = 35), e-cigarette users (n = 28), and dual users (n = 32) of AI descent. Recruitment was considered proactive if study staff contacted the individual at a pow wow, health fair, or vape shop and participation on-site or reactive if the individual contacted the study staff and participation occurred later. Screened, eligible, participated and costs and time spent were compared with Chi square tests. To understand AI descent, the relationship between number of AI grandparents and AI blood quantum was examined. Number of participants screened via the proactive strategy was similar to the reactive strategy (n = 84 vs. n = 82; p-value = 0.8766). A significantly greater proportion of individuals screened via the proactive than the reactive strategy were eligible (77 vs. 50%; p-value = 0.0002) and participated (75 vs. 39%; p-value = < 0.0001). Per participant cost and time estimated for the proactive strategy was $89 and 87 min compared to $79 and 56 min for the reactive strategy. Proportion at least half AI blood quantum was 32, 33, and 70% among those with 2, 3, and 4 AI grandparents, respectively (p = 0.0017). Proactive strategies resulted in two-thirds of the sample, but required more resources than reactive strategies. Overall, we found both strategies were feasible and resulted in the ability to reach sample goals. Lastly, number of AI biological grandparents may be a good, non-invasive indicator of AI blood quantum.

Mating disruption of citrus leafminer mediated by a noncompetitive mechanism at a remarkably low pheromone release rate.

PubMed

Stelinski, L L; Miller, J R; Rogers, M E

2008-08-01

The citrus leafminer, Phyllocnistis citrella Stainton (Lepidoptera: Gracillariidae), is a worldwide pest of citrus. A season-long investigation was conducted that evaluated mating disruption for this pest. Effective disruption of the male P. citrella orientation to pheromone traps (98%) and reduced flush infestation by larvae was achieved for 221 d with two deployments of a 3:1 blend of (Z,Z,E)-7,11,13-hexadecatrienal/(Z,Z)-7,11-hexadecadienal at a remarkably low rate of 1.5 g active ingredient (AI)/ha per deployment. To gain insight into the mechanism that mediates the disruption of P. citrella, male moth catch was quantified in replicated plots of citrus treated with varying densities of pheromone dispensers. The densities of septum dispensers compared were: 0 (0/ha, 0.0 g AI/ha), 0.2 (one every fifth tree or 35/ha, 0.05 g AI/ha), 1 (215/ha, 0.29 g AI/ha), and 5 per tree (1,100/ha, 1.5 g AI/ha). Profile analysis by previously published mathematical methods matched predictions of noncompetitive mating disruption. Behavioral observations of male P. citrella in the field revealed that males did not approach mating disruption dispensers in any of the dispenser density treatments. The current report presents the first set of profile analyses combined with direct behavioral observations consistent with previously published theoretical predictions for a noncompetitive mechanism of mating disruption. The results suggest that disruption of P. citrella should be effective even at high population densities given the density-independent nature of disruption for this species and the remarkably low rate of pheromone per hectare required for efficacy.

Real-time differentiation of adenomatous and hyperplastic diminutive colorectal polyps during analysis of unaltered videos of standard colonoscopy using a deep learning model.

PubMed

Byrne, Michael F; Chapados, Nicolas; Soudan, Florian; Oertel, Clemens; Linares Pérez, Milagros; Kelly, Raymond; Iqbal, Nadeem; Chandelier, Florent; Rex, Douglas K

2017-10-24

In general, academic but not community endoscopists have demonstrated adequate endoscopic differentiation accuracy to make the 'resect and discard' paradigm for diminutive colorectal polyps workable. Computer analysis of video could potentially eliminate the obstacle of interobserver variability in endoscopic polyp interpretation and enable widespread acceptance of 'resect and discard'. We developed an artificial intelligence (AI) model for real-time assessment of endoscopic video images of colorectal polyps. A deep convolutional neural network model was used. Only narrow band imaging video frames were used, split equally between relevant multiclasses. Unaltered videos from routine exams not specifically designed or adapted for AI classification were used to train and validate the model. The model was tested on a separate series of 125 videos of consecutively encountered diminutive polyps that were proven to be adenomas or hyperplastic polyps. The AI model works with a confidence mechanism and did not generate sufficient confidence to predict the histology of 19 polyps in the test set, representing 15% of the polyps. For the remaining 106 diminutive polyps, the accuracy of the model was 94% (95% CI 86% to 97%), the sensitivity for identification of adenomas was 98% (95% CI 92% to 100%), specificity was 83% (95% CI 67% to 93%), negative predictive value 97% and positive predictive value 90%. An AI model trained on endoscopic video can differentiate diminutive adenomas from hyperplastic polyps with high accuracy. Additional study of this programme in a live patient clinical trial setting to address resect and discard is planned. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Do Postpartum Levels of Apolipoproteins Prospectively Predict the Development of Type 2 Diabetes in Women with Previous Gestational Diabetes Mellitus?

PubMed

Lappas, Martha; Georgiou, Harry M; Velagic, Anida; Willcox, Jane C; Permezel, Michael; Shub, Alexis

2018-03-12

The risk of developing type 2 diabetes is greater in women with previous gestational diabetes mellitus (GDM). Apolipoprotein (Apo) species have been associated with the development of type 2 diabetes in the general population. The aim of this study was to determine if circulating levels of Apo species can predict development of type 2 diabetes in women with previous GDM. Apo AI, Apo AII, Apo B, Apo CII, Apo CIII and Apo E levels were measured in 95 women with normal glucose tolerance, 12 weeks following an index GDM pregnancy. Women were assessed for up to 10 years for the development of type 2 diabetes. Postpartum Apo CIII levels, and Apo CIII/Apo AI, Apo CIII/Apo AII, Apo CIII/Apo CII, Apo CIII/Apo E and Apo E/Apo CIII ratios were significantly and positively associated with the development of type 2 diabetes. After controlling for age and BMI, these associations, except for the Apo E/Apo CIII ratio, remained significant. In a clinical model of prediction of type 2 diabetes that included age, BMI, and pregnancy and postnatal fasting glucose, the addition of Apo CIII levels, Apo CIII/Apo AI, Apo CIII/Apo AII, Apo CIII/Apo CII, and Apo CIII/Apo E resulted in a net reclassification improvement of 16.2%. High Apo CIII levels and the Apo CIII/Apo AI, Apo CIII/Apo AII, Apo CIII/Apo CII, and Apo CIII/Apo E ratios are all significant risk factors for the development of type 2 diabetes in women with a previous GDM pregnancy. © Georg Thieme Verlag KG Stuttgart · New York.

Predicting Adherence to Aromatase Inhibitor Therapy among Breast Cancer Survivors: An Application of the Protection Motivation Theory

PubMed Central

Karmakar, Monita; Pinto, Sharrel L; Jordan, Timothy R; Mohamed, Iman; Holiday-Goodman, Monica

2017-01-01

The purpose of this observational study was to determine if the Protection Motivation Theory could predict and explain adherence to aromatase inhibitor (AI) therapy among breast cancer survivors. Purposive sampling was used to identify 288 survivors who had been prescribed AI therapy. A valid and reliable survey was mailed to survivors. A total of 145 survivors completed the survey. The Morisky scale was used to measure adherence to AI. The survivors reported a mean score of 6.84 (±0.66) on the scale. Nearly 4 in 10 survivors (38%) were non-adherent. Adherence differed by age, marital status, insurance status, income, and presence of co-morbid conditions. Self-efficacy (r=0.485), protection motivation (r=0.310), and Response Efficacy (r=0.206) were positively and significantly correlated with adherence. Response Cost (r=-0.235) was negatively correlated with adherence. The coping appraisal constructs were statistically significant predictors medication adherence (β=0.437) with self-efficacy being the strongest significant predictor of adherence (β = 0.429). PMID:28469437

Predicting Adherence to Aromatase Inhibitor Therapy among Breast Cancer Survivors: An Application of the Protection Motivation Theory.

PubMed

Karmakar, Monita; Pinto, Sharrel L; Jordan, Timothy R; Mohamed, Iman; Holiday-Goodman, Monica

2017-01-01

The purpose of this observational study was to determine if the Protection Motivation Theory could predict and explain adherence to aromatase inhibitor (AI) therapy among breast cancer survivors. Purposive sampling was used to identify 288 survivors who had been prescribed AI therapy. A valid and reliable survey was mailed to survivors. A total of 145 survivors completed the survey. The Morisky scale was used to measure adherence to AI. The survivors reported a mean score of 6.84 (±0.66) on the scale. Nearly 4 in 10 survivors (38%) were non-adherent. Adherence differed by age, marital status, insurance status, income, and presence of co-morbid conditions. Self-efficacy (r=0.485), protection motivation (r=0.310), and Response Efficacy (r=0.206) were positively and significantly correlated with adherence. Response Cost (r=-0.235) was negatively correlated with adherence. The coping appraisal constructs were statistically significant predictors medication adherence (β=0.437) with self-efficacy being the strongest significant predictor of adherence (β = 0.429).

Validating the Hamilton Anatomy of Risk Management-Forensic Version and the Aggressive Incidents Scale.

PubMed

Cook, Alana N; Moulden, Heather M; Mamak, Mini; Lalani, Shams; Messina, Katrina; Chaimowitz, Gary

2018-06-01

The Hamilton Anatomy of Risk Management-Forensic Version (HARM-FV) is a structured professional judgement tool of violence risk developed for use in forensic inpatient psychiatric settings. The HARM-FV is used with the Aggressive Incidents Scale (AIS), which provides a standardized method of recording aggressive incidents. We report the findings of the concurrent validity of the HARM-FV and the AIS with widely used measures of violence risk and aggressive acts, the Historical, Clinical, Risk Management-20, Version 3 (HCR-20 V3 ) and a modified version of the Overt Aggression Scale. We also present findings on the predictive validity of the HARM-FV in the short term (1-month follow-up periods) for varying severities of aggressive acts. The results indicated strong support for the concurrent validity of the HARM-FV and AIS and promising support for the predictive accuracy of the tool for inpatient aggression. This article provides support for the continued clinical use of the HARM-FV within an inpatient forensic setting and highlights areas for further research.

Comparison of full field and anomaly initialisation for decadal climate prediction: towards an optimal consistency between the ocean and sea-ice anomaly initialisation state

NASA Astrophysics Data System (ADS)

Volpi, Danila; Guemas, Virginie; Doblas-Reyes, Francisco J.

2017-08-01

Decadal prediction exploits sources of predictability from both the internal variability through the initialisation of the climate model from observational estimates, and the external radiative forcings. When a model is initialised with the observed state at the initial time step (Full Field Initialisation—FFI), the forecast run drifts towards the biased model climate. Distinguishing between the climate signal to be predicted and the model drift is a challenging task, because the application of a-posteriori bias correction has the risk of removing part of the variability signal. The anomaly initialisation (AI) technique aims at addressing the drift issue by answering the following question: if the model is allowed to start close to its own attractor (i.e. its biased world), but the phase of the simulated variability is constrained toward the contemporaneous observed one at the initialisation time, does the prediction skill improve? The relative merits of the FFI and AI techniques applied respectively to the ocean component and the ocean and sea ice components simultaneously in the EC-Earth global coupled model are assessed. For both strategies the initialised hindcasts show better skill than historical simulations for the ocean heat content and AMOC along the first two forecast years, for sea ice and PDO along the first forecast year, while for AMO the improvements are statistically significant for the first two forecast years. The AI in the ocean and sea ice components significantly improves the skill of the Arctic sea surface temperature over the FFI.

Prediction of dissolved oxygen concentration in hypoxic river systems using support vector machine: a case study of Wen-Rui Tang River, China.

PubMed

Ji, Xiaoliang; Shang, Xu; Dahlgren, Randy A; Zhang, Minghua

2017-07-01

Accurate quantification of dissolved oxygen (DO) is critically important for managing water resources and controlling pollution. Artificial intelligence (AI) models have been successfully applied for modeling DO content in aquatic ecosystems with limited data. However, the efficacy of these AI models in predicting DO levels in the hypoxic river systems having multiple pollution sources and complicated pollutants behaviors is unclear. Given this dilemma, we developed a promising AI model, known as support vector machine (SVM), to predict the DO concentration in a hypoxic river in southeastern China. Four different calibration models, specifically, multiple linear regression, back propagation neural network, general regression neural network, and SVM, were established, and their prediction accuracy was systemically investigated and compared. A total of 11 hydro-chemical variables were used as model inputs. These variables were measured bimonthly at eight sampling sites along the rural-suburban-urban portion of Wen-Rui Tang River from 2004 to 2008. The performances of the established models were assessed through the mean square error (MSE), determination coefficient (R 2 ), and Nash-Sutcliffe (NS) model efficiency. The results indicated that the SVM model was superior to other models in predicting DO concentration in Wen-Rui Tang River. For SVM, the MSE, R 2 , and NS values for the testing subset were 0.9416 mg/L, 0.8646, and 0.8763, respectively. Sensitivity analysis showed that ammonium-nitrogen was the most significant input variable of the proposal SVM model. Overall, these results demonstrated that the proposed SVM model can efficiently predict water quality, especially for highly impaired and hypoxic river systems.

Cultural Identity Among Urban American Indian/Alaska Native Youth: Implications for Alcohol and Drug Use.

PubMed

Brown, Ryan A; Dickerson, Daniel L; D'Amico, Elizabeth J

2016-10-01

American Indian / Alaska Native (AI/AN) youth exhibit high rates of alcohol and other drug (AOD) use, which is often linked to the social and cultural upheaval experienced by AI/ANs during the colonization of North America. Urban AI/AN youth may face unique challenges, including increased acculturative stress due to lower concentrations of AI/AN populations in urban areas. Few existing studies have explored cultural identity among urban AI/AN youth and its association with AOD use. This study used systematic qualitative methods with AI/AN communities in two urban areas within California to shed light on how urban AI/AN youth construct cultural identity and how this relates to AOD use and risk behaviors. We conducted 10 focus groups with a total of 70 youth, parents, providers, and Community Advisory Board members and used team-based structured thematic analysis in the Dedoose software platform. We identified 12 themes: intergenerational stressors, cultural disconnection, AI/AN identity as protective, pan-tribal identity, mixed racial-ethnic identity, rural vs. urban environments, the importance of AI/AN institutions, stereotypes and harassment, cultural pride, developmental trajectories, risks of being AI/AN, and mainstream culture clash. Overall, youth voiced curiosity about their AI/AN roots and expressed interest in deepening their involvement in cultural activities. Adults described the myriad ways in which involvement in cultural activities provides therapeutic benefits for AI/AN youth. Interventions that provide urban AI/AN youth with an opportunity to engage in cultural activities and connect with positive and healthy constructs in AI/AN culture may provide added impact to existing interventions.

Predicting work-related disability and medical cost outcomes: a comparison of injury severity scoring methods.

PubMed

Sears, Jeanne M; Blanar, Laura; Bowman, Stephen M

2014-01-01

Acute work-related trauma is a leading cause of death and disability among U.S. workers. Occupational health services researchers have described the pressing need to identify valid injury severity measures for purposes such as case-mix adjustment and the construction of appropriate comparison groups in programme evaluation, intervention, quality improvement, and outcome studies. The objective of this study was to compare the performance of several injury severity scores and scoring methods in the context of predicting work-related disability and medical cost outcomes. Washington State Trauma Registry (WTR) records for injuries treated from 1998 to 2008 were linked with workers' compensation claims. Several Abbreviated Injury Scale (AIS)-based injury severity measures (ISS, New ISS, maximum AIS) were estimated directly from ICD-9-CM codes using two software packages: (1) ICDMAP-90, and (2) Stata's user-written ICDPIC programme (ICDPIC). ICDMAP-90 and ICDPIC scores were compared with existing WTR scores using the Akaike Information Criterion, amount of variance explained, and estimated effects on outcomes. Competing risks survival analysis was used to evaluate work disability outcomes. Adjusted total medical costs were modelled using linear regression. The linked sample contained 6052 work-related injury events. There was substantial agreement between WTR scores and those estimated by ICDMAP-90 (kappa=0.73), and between WTR scores and those estimated by ICDPIC (kappa=0.68). Work disability and medical costs increased monotonically with injury severity, and injury severity was a significant predictor of work disability and medical cost outcomes in all models. WTR and ICDMAP-90 scores performed better with regard to predicting outcomes than did ICDPIC scores, but effect estimates were similar. Of the three severity measures, maxAIS was usually weakest, except when predicting total permanent disability. Injury severity was significantly associated with work disability and medical cost outcomes for work-related injuries. Injury severity can be estimated using either ICDMAP-90 or ICDPIC when ICD-9-CM codes are available. We observed little practical difference between severity measures or scoring methods. This study demonstrated that using existing software to estimate injury severity may be useful to enhance occupational injury surveillance and research. Copyright © 2013 Elsevier Ltd. All rights reserved.

Full-field and anomaly initialization using a low-order climate model: a comparison and proposals for advanced formulations

NASA Astrophysics Data System (ADS)

Carrassi, A.; Weber, R. J. T.; Guemas, V.; Doblas-Reyes, F. J.; Asif, M.; Volpi, D.

2014-04-01

Initialization techniques for seasonal-to-decadal climate predictions fall into two main categories; namely full-field initialization (FFI) and anomaly initialization (AI). In the FFI case the initial model state is replaced by the best possible available estimate of the real state. By doing so the initial error is efficiently reduced but, due to the unavoidable presence of model deficiencies, once the model is let free to run a prediction, its trajectory drifts away from the observations no matter how small the initial error is. This problem is partly overcome with AI where the aim is to forecast future anomalies by assimilating observed anomalies on an estimate of the model climate. The large variety of experimental setups, models and observational networks adopted worldwide make it difficult to draw firm conclusions on the respective advantages and drawbacks of FFI and AI, or to identify distinctive lines for improvement. The lack of a unified mathematical framework adds an additional difficulty toward the design of adequate initialization strategies that fit the desired forecast horizon, observational network and model at hand. Here we compare FFI and AI using a low-order climate model of nine ordinary differential equations and use the notation and concepts of data assimilation theory to highlight their error scaling properties. This analysis suggests better performances using FFI when a good observational network is available and reveals the direct relation of its skill with the observational accuracy. The skill of AI appears, however, mostly related to the model quality and clear increases of skill can only be expected in coincidence with model upgrades. We have compared FFI and AI in experiments in which either the full system or the atmosphere and ocean were independently initialized. In the former case FFI shows better and longer-lasting improvements, with skillful predictions until month 30. In the initialization of single compartments, the best performance is obtained when the stabler component of the model (the ocean) is initialized, but with FFI it is possible to have some predictive skill even when the most unstable compartment (the extratropical atmosphere) is observed. Two advanced formulations, least-square initialization (LSI) and exploring parameter uncertainty (EPU), are introduced. Using LSI the initialization makes use of model statistics to propagate information from observation locations to the entire model domain. Numerical results show that LSI improves the performance of FFI in all the situations when only a portion of the system's state is observed. EPU is an online drift correction method in which the drift caused by the parametric error is estimated using a short-time evolution law and is then removed during the forecast run. Its implementation in conjunction with FFI allows us to improve the prediction skill within the first forecast year. Finally, the application of these results in the context of realistic climate models is discussed.

Effect of Alcoholic Intoxication on the Risk of Inflammatory Bowel Disease: A Nationwide Retrospective Cohort Study

PubMed Central

Hsu, Tai-Yi; Shih, Hong-Mo; Wang, Yu-Chiao; Lin, Leng-Chieh; He, Guan-Yi; Chen, Chih-Yu; Kao, Chia-Hung; Chen, Chao-Hsien

2016-01-01

Purpose This study investigated whether alcoholic intoxication (AI) increases the risk of inflammatory bowel disease (IBD) by using a population-based database in Taiwan. Methods This retrospective matched-cohort study included 57 611 inpatients with new-onset AI (AI cohort) and 230 444 randomly selected controls (non-AI cohort). Each patient was monitored for 10 years to individually identify those who were subsequently diagnosed with Crohn disease (CD) and ulcerative colitis (UC) during the follow-up period. Cox proportional hazard regression analysis was conducted to determine the risk of IBD in patients with AI compared with controls without AI. Results The incidence rate of IBD during the 10-year follow-up period was 2.69 per 1 000 person-years and 0.49 per 1 000 person-years in the AI and non-AI cohorts, respectively. After adjustment for age, sex, and comorbidity, the AI cohort exhibited a 3.17-fold increased risk of IBD compared with the non-AI cohort (hazard ratio [HR] = 3.17, 95% confidence interval [CI] = 2.19–4.58). Compared with the non-AI cohort, the HRs of CD and UC were 4.40 and 2.33 for the AI cohort, respectively. After stratification for the severity of AI according to the duration of hospital stay, the adjusted HRs exhibited a significant correlation with the severity; the HRs of IBD were 1.76, 6.83, and 19.9 for patients with mild, moderate, and severe AI, respectively (p for the trend < .0001). Conclusion The risk of IBD was higher in patients with AI and increased with the length of hospital stay. PMID:27802288

Operations mission planner

NASA Technical Reports Server (NTRS)

Biefeld, Eric; Cooper, Lynne

1990-01-01

The findings are documented of the OMP research task, which investigated the applicability of artificial intelligence (AI) technology in support of automated scheduling. The goals of the effort are summarized and the technical accomplishments are highlighted. The OMP task succeeded in identifying how AI technology could be applied and demonstrated an AI-based automated scheduling approach through the OMP prototypes.

Development of vaccines for poultry against H5 avian influenza based on turkey herpesvirus vector

USDA-ARS?s Scientific Manuscript database

Avian influenza (AI) remains a major threat to public health as well as to the poultry industry. AI vaccines are considered a suitable tool to support AI control programs in combination with other control measures such as good biosecurity and monitoring programs. We constructed recombinant turkey he...

Cross reactive cellular immune responses in chickens previously exposed to low pathogenic avian influenza

USDA-ARS?s Scientific Manuscript database

Avian influenza (AI) infection in poultry can result in high morbidity and mortality, and negatively affect international trade. Because most AI vaccines used for poultry are inactivated, our knowledge of immunity against AI is based largely on humoral immune responses. In fact, little is known abo...

Engaging Students and Staff with Educational Development through Appreciative Inquiry

ERIC Educational Resources Information Center

Kadi-Hanifi, Karima; Dagman, Ozlem; Peters, John; Snell, Ellen; Tutton, Caroline; Wright, Trevor

2014-01-01

Appreciative inquiry (AI) offers a constructive, strengths-based framework for engaging students and staff in the enhancement of academic programmes of study. This paper explores the basis of AI, its potential for educational development and the many agendas it might help address. Students and academic staff involved in an AI project, focused on…

The Air Force Advanced Instructional System (AIS): An Overview.

ERIC Educational Resources Information Center

Yasutake, Joseph Y.; Stobie, William H.

The Air Force Advanced Instructional System (AIS) is a prototype computer-based multimedia system for the administration and management of individualized technical training on a large scale. The paper provides an overview of the AIS: (1) its purposes and goals, (2) the background and rationale for the development approach, (3) a basic description…

AI Based Personal Learning Environments: Directions for Long Term Research. AI Memo 384.

ERIC Educational Resources Information Center

Goldstein, Ira P.; Miller, Mark L.

The application of artificial intelligence (AI) techniques to the design of personal learning environments is an enterprise of both theoretical and practical interest. In the short term, the process of developing and testing intelligent tutoring programs serves as a new experimental vehicle for exploring alternative cognitive and pedagogical…

Effects of the "Circle of Life" HIV-prevention program on marijuana use among American Indian middle school youths: a group randomized trial in a Northern Plains tribe.

PubMed

Asdigian, Nancy L; Whitesell, Nancy Rumbaugh; Keane, Ellen M; Mousseau, Alicia C; Kaufman, Carol E

2018-01-01

Early substance use threatens many American Indian/Alaska Native (AI/AN) communities, as it is a risk factor for maladaptive use and adverse health outcomes. Marijuana is among the first substances used by AI/AN youth, and its use becomes widespread during adolescence. Interventions that delay or reduce marijuana use hold the promise of curbing substance disorders and other health risk disparities in AI/AN populations. We evaluated the effectiveness of the Circle of Life (COL) program in reducing marijuana use among young AI adolescents. COL is a culturally tailored, theory-based human immunodeficiency virus (HIV) and sexually transmitted disease (STD) intervention shown to delay sexual initiation among AI youths. We conducted secondary analyses of data from a school-based group randomized trial conducted between 2006 and 2007 in all 13 middle schools on a rural, Northern Plains reservation (N = 635, 47% female). We used discrete-time survival analysis (DTSA) to assess COL effectiveness on risk of marijuana initiation among AI youths and latent growth curve modeling (LGCM) to evaluate effects on frequency of marijuana use over time. DTSA models showed that the overall risk of marijuana initiation was 17.3% lower in the COL group compared to the control group. No intervention effect on frequency of marijuana use emerged in LGCM analyses. COL is a multifaceted, culturally tailored, skills-based program effective in preventing marijuana uptake among AI youth.

Altering the time of the second gonadotropin-releasing hormone injection and artificial insemination (AI) during Ovsynch affects pregnancies per AI in lactating dairy cows.

PubMed

Brusveen, D J; Cunha, A P; Silva, C D; Cunha, P M; Sterry, R A; Silva, E P B; Guenther, J N; Wiltbank, M C

2008-03-01

Based on previous research, we hypothesized that Cosynch at 72 h [GnRH-7 d-PGF(2alpha)-72 h-GnRH + artificial insemination (AI)] would result in a greater number of pregnancies per AI (P/AI) than Cosynch at 48 h. Further, we hypothesized that P/AI would be improved to a greater extent when GnRH was administered at 56 h after PGF(2alpha) before AI at 72 h due to a more optimal interval between the LH surge and AI. Nine hundred twenty-seven lactating dairy cows (n = 1,507 AI) were blocked by pen, and pens rotated through treatments. All cows received GnRH followed 7 d later by PGF(2alpha) and then received one of the following: 1) GnRH + timed AI 48 h after PGF(2alpha) (Cosynch-48); 2) GnRH 56 h after PGF(2alpha) + timed AI 72 h after PGF(2alpha) (Ovsynch-56); or 3) GnRH + timed AI 72 h after PGF(2alpha) (Cosynch-72). Pregnancy diagnoses were performed by ultrasound at 31 to 33 d post-AI and again at 52 to 54 d post-AI. Overall P/AI were similar for the Cosynch-48 (29.2%) and Cosynch-72 (25.4%) groups. The Ovsynch-56 group had a greater P/AI (38.6%) than Cosynch-48 or Cosynch-72. Presynchronized first-service animals had greater P/AI than cows at later services in Cosynch-48 (36.2 vs. 23.0%) and Ovsynch-56 (44.8 vs. 32.7%) but not in Cosynch-72 (24.6 vs. 26.2%). Similarly, primiparous cows had greater P/AI than multiparous cows in Cosynch-48 (34.1 vs. 22.9%) and Ovsynch-56 (41.3 vs. 32.6%), but not Cosynch-72 (29.8 vs. 25.3%). In conclusion, we found no advantage to Cosynch at 72 h vs. 48 h. In contrast, we found a clear advantage to treating with GnRH at 56 h, 16 h before a 72-h AI, probably because of more-optimal timing of AI before ovulation.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Park, Ki Seok; Lee, Jiyeung; Ahn, So Shin

Development of effective vaccines against highly pathogenic avian influenza (HPAI) H5N1 viruses is a global public health priority. Considering the difficulty in predicting HPAI H5N1 pandemic strains, one strategy used in their design includes the development of formulations with the capacity of eliciting broad cross-protective immunity against multiple viral antigens. To this end we constructed a replication-defective recombinant adenovirus-based avian influenza virus vaccine (rAdv-AI) expressing the codon-optimized M2eX-HA-hCD40L and the M1-M2 fusion genes from HPAI H5N1 human isolate. Although there were no significant differences in the systemic immune responses observed between the intramuscular prime-intramuscular boost regimen (IM/IM) and the intranasalmore » prime-intramuscular boost regimen (IN/IM), IN/IM induced more potent CD8{sup +} T cell and antibody responses at mucosal sites than the IM/IM vaccination, resulting in more effective protection against lethal H5N2 avian influenza (AI) virus challenge. These findings suggest that the strategies used to induce multi-antigen-targeted mucosal immunity, such as IN/IM delivery of rAdv-AI, may be a promising approach for developing broad protective vaccines that may be more effective against the new HPAI pandemic strains.« less

The discovery and mechanism of action of letrozole

PubMed Central

2007-01-01

Because estrogen contributes to the promotion and progression of breast cancer, a greater understanding of the role of estrogen in breast cancer has led to therapeutic strategies targeting estrogen synthesis, the estrogen receptor, and intracellular signaling pathways. The enzyme aromatase catalyses the final step in estrogen biosynthesis and was identified as an attractive target for selective inhibition. Modern third-generation aromatase inhibitors (AIs) effectively block the production of estrogen without exerting effects on other steroidogenic pathways. The discovery of letrozole (Femara®) achieved the goal of discovering a highly potent and totally selective AI. Letrozole has greater potency than other AIs, including anastrozole, exemestane, formestane, and aminoglutethimide. Moreover, letrozole produces near complete inhibition of aromatase in peripheral tissues and is associated with greater suppression of estrogen than is achieved with other AIs. The potent anti-tumor effects of letrozole were demonstrated in several animal models. Studies with MCF-7Ca xenografts successfully predicted that letrozole would be clinically superior to the previous gold standard tamoxifen and also indicated that it may be more effective than other AIs. An extensive program of randomized clinical trials has demonstrated the clinical benefits of letrozole across the spectrum of hormone-responsive breast cancer in postmenopausal women. PMID:17912633

Effects of Ai Chi on balance, quality of life, functional mobility, and motor impairment in patients with Parkinson's disease^.

PubMed

Kurt, Emine Eda; Büyükturan, Buket; Büyükturan, Öznur; Erdem, Hatice Rana; Tuncay, Figen

2018-04-01

In this study, we aimed to investigate effects of Ai Chi on balance, functional mobility, health-related quality of life, and motor impairment in patients with Parkinson's disease. This study was conducted as an open-label randomized controlled trial (ISRCTN26292510) with repeated measures. Forty patients with Parkinson's disease stages 2 to 3 according to the Hoehn and Yahr Scale were randomly allocated to either an Ai Chi exercise group or a land-based exercise control group for 5 weeks. Balance was measured using the Biodex-3,1 and the Berg Balance Scale. Functional mobility was evaluated using the Timed Up and Go Test. Additionally, health-related quality of life and motor activity were assessed with the Parkinson's Disease Questionnaire-39 and the Unified Parkinson's Disease Rating Scale-III. Although patients in both groups showed significant improvement in all outcome variables, improvement of dynamic balance was significantly greater in the Ai Chi group (p < 0.001), Berg Balance Scale (p < 0.001), Timed Up and Go Test (p = 0.002), Parkinson's Disease Questionnaire-39 (p < 0.001), Unified Parkinson's Disease Rating Scale-III (p < 0.001). Our results suggest that an Ai Chi exercise program improves balance, mobility, motor ability, and quality of life. In addition, Ai Chi exercise was more effective as an intervention than land-based exercise in patients with mild to moderate Parkinson's disease. Implications for rehabilitation Ai Chi exercises (aquatic exercises) may help improve balance, functional mobility, health-related quality of life, and motor ability in patients with mild to moderate Parkinson's disease more efficiently than similar land-based exercises. Ai Chi exercises should be considered as a rehabilitation option for treatment of patients with mild or moderate Parkinson's disease.

Posttreatment Variables Improve Outcome Prediction after Intra-Arterial Therapy for Acute Ischemic Stroke

PubMed Central

Prabhakaran, Shyam; Jovin, Tudor G.; Tayal, Ashis H.; Hussain, Muhammad S.; Nguyen, Thanh N.; Sheth, Kevin N.; Terry, John B.; Nogueira, Raul G.; Horev, Anat; Gandhi, Dheeraj; Wisco, Dolora; Glenn, Brenda A.; Ludwig, Bryan; Clemmons, Paul F.; Cronin, Carolyn A.; Tian, Melissa; Liebeskind, David; Zaidat, Osama O.; Castonguay, Alicia C.; Martin, Coleman; Mueller-Kronast, Nils; English, Joey D.; Linfante, Italo; Malisch, Timothy W.; Gupta, Rishi

2014-01-01

Background There are multiple clinical and radiographic factors that influence outcomes after endovascular reperfusion therapy (ERT) in acute ischemic stroke (AIS). We sought to derive and validate an outcome prediction score for AIS patients undergoing ERT based on readily available pretreatment and posttreatment factors. Methods The derivation cohort included 511 patients with anterior circulation AIS treated with ERT at 10 centers between September 2009 and July 2011. The prospective validation cohort included 223 patients with anterior circulation AIS treated in the North American Solitaire Acute Stroke registry. Multivariable logistic regression identified predictors of good outcome (modified Rankin score ≤2 at 3 months) in the derivation cohort; model β coefficients were used to assign points and calculate a risk score. Discrimination was tested using C statistics with 95% confidence intervals (CIs) in the derivation and validation cohorts. Calibration was assessed using the Hosmer-Lemeshow test and plots of observed to expected outcomes. We assessed the net reclassification improvement for the derived score compared to the Totaled Health Risks in Vascular Events (THRIVE) score. Subgroup analysis in patients with pretreatment Alberta Stroke Program Early CT Score (ASPECTS) and posttreatment final infarct volume measurements was also performed to identify whether these radiographic predictors improved the model compared to simpler models. Results Good outcome was noted in 186 (36.4%) and 100 patients (44.8%) in the derivation and validation cohorts, respectively. Combining readily available pretreatment and posttreatment variables, we created a score (acronym: SNARL) based on the following parameters: symptomatic hemorrhage [2 points: none, hemorrhagic infarction (HI)1–2 or parenchymal hematoma (PH) type 1; 0 points: PH2], baseline National Institutes of Health Stroke Scale score (3 points: 0–10; 1 point: 11–20; 0 points: >20), age (2 points: <60 years; 1 point: 60–79 years; 0 points: >79 years), reperfusion (3 points: Thrombolysis In Cerebral Ischemia score 2b or 3) and location of clot (1 point: M2; 0 points: M1 or internal carotid artery). The SNARL score demonstrated good discrimination in the derivation (C statistic 0.79, 95% CI 0.75–0.83) and validation cohorts (C statistic 0.74, 95% CI 0.68–0.81) and was superior to the THRIVE score (derivation cohort: C statistic 0.65, 95% CI 0.60–0.70; validation cohort: C-statistic 0.59, 95% CI 0.52–0.67; p < 0.01 in both cohorts) but was inferior to a score that included age, ASPECTS, reperfusion status and final infarct volume (C statistic 0.86, 95% CI 0.82–0.91; p = 0.04). Compared with the THRIVE score, the SNARL score resulted in a net reclassification improvement of 34.8%. Conclusions Among AIS patients treated with ERT, pretreatment scores such as the THRIVE score provide only fair prognostic information. Inclusion of posttreatment variables such as reperfusion and symptomatic hemorrhage greatly influences outcome and results in improved outcome prediction. PMID:24942008

Artificial intelligence and the space station software support environment

NASA Technical Reports Server (NTRS)

Marlowe, Gilbert

1986-01-01

In a software system the size of the Space Station Software Support Environment (SSE), no one software development or implementation methodology is presently powerful enough to provide safe, reliable, maintainable, cost effective real time or near real time software. In an environment that must survive one of the most harsh and long life times, software must be produced that will perform as predicted, from the first time it is executed to the last. Many of the software challenges that will be faced will require strategies borrowed from Artificial Intelligence (AI). AI is the only development area mentioned as an example of a legitimate reason for a waiver from the overall requirement to use the Ada programming language for software development. The limits are defined of the applicability of the Ada language Ada Programming Support Environment (of which the SSE is a special case), and software engineering to AI solutions by describing a scenario that involves many facets of AI methodologies.

Differential epigenetic reprogramming in response to specific endocrine therapies promotes cholesterol biosynthesis and cellular invasion

PubMed Central

Nguyen, Van T. M.; Barozzi, Iros; Faronato, Monica; Lombardo, Ylenia; Steel, Jennifer H.; Patel, Naina; Darbre, Philippa; Castellano, Leandro; Győrffy, Balázs; Woodley, Laura; Meira, Alba; Patten, Darren K.; Vircillo, Valentina; Periyasamy, Manikandan; Ali, Simak; Frige, Gianmaria; Minucci, Saverio; Coombes, R. Charles; Magnani, Luca

2015-01-01

Endocrine therapies target the activation of the oestrogen receptor alpha (ERα) via distinct mechanisms, but it is not clear whether breast cancer cells can adapt to treatment using drug-specific mechanisms. Here we demonstrate that resistance emerges via drug-specific epigenetic reprogramming. Resistant cells display a spectrum of phenotypical changes with invasive phenotypes evolving in lines resistant to the aromatase inhibitor (AI). Orthogonal genomics analysis of reprogrammed regulatory regions identifies individual drug-induced epigenetic states involving large topologically associating domains (TADs) and the activation of super-enhancers. AI-resistant cells activate endogenous cholesterol biosynthesis (CB) through stable epigenetic activation in vitro and in vivo. Mechanistically, CB sparks the constitutive activation of oestrogen receptors alpha (ERα) in AI-resistant cells, partly via the biosynthesis of 27-hydroxycholesterol. By targeting CB using statins, ERα binding is reduced and cell invasion is prevented. Epigenomic-led stratification can predict resistance to AI in a subset of ERα-positive patients. PMID:26610607

Intelligent Resource Management for Local Area Networks: Approach and Evolution

NASA Technical Reports Server (NTRS)

Meike, Roger

1988-01-01

The Data Management System network is a complex and important part of manned space platforms. Its efficient operation is vital to crew, subsystems and experiments. AI is being considered to aid in the initial design of the network and to augment the management of its operation. The Intelligent Resource Management for Local Area Networks (IRMA-LAN) project is concerned with the application of AI techniques to network configuration and management. A network simulation was constructed employing real time process scheduling for realistic loads, and utilizing the IEEE 802.4 token passing scheme. This simulation is an integral part of the construction of the IRMA-LAN system. From it, a causal model is being constructed for use in prediction and deep reasoning about the system configuration. An AI network design advisor is being added to help in the design of an efficient network. The AI portion of the system is planned to evolve into a dynamic network management aid. The approach, the integrated simulation, project evolution, and some initial results are described.

Situational, partner, and contextual factors associated with level of risk at most recent intercourse among Black men who have sex with men.

PubMed

Kelly, Jeffrey A; DiFranceisco, Wayne J; St Lawrence, Janet S; Amirkhanian, Yuri A; Anderson-Lamb, Michelle

2014-01-01

African American men who have sex with men (MSM) in the United States bear a disproportionate burden of HIV infection and disease incidence. 178 Black MSM provided detailed situational information concerning their most recent act of anal intercourse (AI) with a male partner including condom use, partner characteristics, serostatus disclosure, and substance use. Participants completed scales assessing AIDS-related as well as broader contextual domains. Most recent AI acts occurred with same-race partners outside of main relationships. Over one-third of AI acts were unprotected, and almost half of the unprotected acts were not between known HIV-concordant partners. Nearly half of men reported substance use before sex. In a multiple regression analysis, unprotected AI with a partner not known to be concordant was predicted by low risk reduction intentions and indicators of a casual relationship. The findings highlight issues and partner contexts associated with risk for contracting HIV infection among Black MSM.

Intelligent Image Based Computer Aided Education (IICAE)

NASA Astrophysics Data System (ADS)

David, Amos A.; Thiery, Odile; Crehange, Marion

1989-03-01

Artificial Intelligence (AI) has found its way into Computer Aided Education (CAE), and there are several systems constructed to put in evidence its interesting advantages. We believe that images (graphic or real) play an important role in learning. However, the use of images, outside their use as illustration, makes it necessary to have applications such as AI. We shall develop the application of AI in an image based CAE and briefly present the system under construction to put in evidence our concept. We shall also elaborate a methodology for constructing such a system. Futhermore we shall briefly present the pedagogical and psychological activities in a learning process. Under the pedagogical and psychological aspect of learning, we shall develop areas such as the importance of image in learning both as pedagogical objects as well as means for obtaining psychological information about the learner. We shall develop the learner's model, its use, what to build into it and how. Under the application of AI in an image based CAE, we shall develop the importance of AI in exploiting the knowledge base in the learning environment and its application as a means of implementing pedagogical strategies.

NASA space station automation: AI-based technology review

NASA Technical Reports Server (NTRS)

Firschein, O.; Georgeff, M. P.; Park, W.; Neumann, P.; Kautz, W. H.; Levitt, K. N.; Rom, R. J.; Poggio, A. A.

1985-01-01

Research and Development projects in automation for the Space Station are discussed. Artificial Intelligence (AI) based automation technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics. AI technology will also be developed for the servicing of satellites at the Space Station, system monitoring and diagnosis, space manufacturing, and the assembly of large space structures.

AiGERM: A logic programming front end for GERM

NASA Technical Reports Server (NTRS)

Hashim, Safaa H.

1990-01-01

AiGerm (Artificially Intelligent Graphical Entity Relation Modeler) is a relational data base query and programming language front end for MCC (Mission Control Center)/STP's (Space Test Program) Germ (Graphical Entity Relational Modeling) system. It is intended as an add-on component of the Germ system to be used for navigating very large networks of information. It can also function as an expert system shell for prototyping knowledge-based systems. AiGerm provides an interface between the programming language and Germ.

The Chinese Stroke Association scientific statement: intravenous thrombolysis in acute ischaemic stroke

PubMed Central

Dong, Qiang; Dong, Yi; Liu, Liping; Xu, Anding; Zhang, Yusheng; Zheng, Huaguang; Wang, Yongjun

2017-01-01

The most effective medical treatment for acute ischaemic stroke (AIS) is to offer intravenous thrombolysis during the ultra-early period of time after the onset. Even based on the Consensus of Chinese Experts on Intravenous Thrombolysis for AIS in 2012 and 2014 Chinese Guidelines on the Diagnosis and Treatment of AIS, the rate of thrombolysis for AIS in China remained around 2.4%, and the rate of intravenous tissue plasminogen activator usage was only about 1.6% in real world. The indication of thrombolysis for AIS has been expanded, and contraindications have been reduced with recently published studies. In order to facilitate the standardisation of treating AIS, improve the rate of thrombolysis and benefit patients who had a stroke, Chinese Stroke Association has organised and developed this scientific statement. PMID:28989804

CULTURAL ADAPTATIONS OF EVIDENCE-BASED HOME-VISITATION MODELS IN TRIBAL COMMUNITIES.

PubMed

Hiratsuka, Vanessa Y; Parker, Myra E; Sanchez, Jenae; Riley, Rebecca; Heath, Debra; Chomo, Julianna C; Beltangady, Moushumi; Sarche, Michelle

2018-05-01

The Tribal Maternal, Infant, and Early Childhood Home Visiting (Tribal MIECHV) Program provides federal grants to tribes, tribal consortia, tribal organizations, and urban Indian organizations to implement evidence-based home-visiting services for American Indian and Alaska Native (AI/AN) families. To date, only one evidence-based home-visiting program has been developed for use in AI/AN communities. The purpose of this article is to describe the steps that four Tribal MIECHV Programs took to assess community needs, select a home-visiting model, and culturally adapt the model for use in AI/AN communities. In these four unique Tribal MIECHV Program settings, each program employed a rigorous needs-assessment process and developed cultural modifications in accordance with community strengths and needs. Adaptations occurred in consultation with model developers, with consideration of the conceptual rationale for the program, while grounding new content in indigenous cultures. Research is needed to improve measurement of home-visiting outcomes in tribal and urban AI/AN settings, develop culturally grounded home-visiting interventions, and assess the effectiveness of home visiting in AI/AN communities. © 2018 Michigan Association for Infant Mental Health.

Process evaluation to explore internal and external validity of the "Act in Case of Depression" care program in nursing homes.

PubMed

Leontjevas, Ruslan; Gerritsen, Debby L; Koopmans, Raymond T C M; Smalbrugge, Martin; Vernooij-Dassen, Myrra J F J

2012-06-01

A multidisciplinary, evidence-based care program to improve the management of depression in nursing home residents was implemented and tested using a stepped-wedge design in 23 nursing homes (NHs): "Act in case of Depression" (AiD). Before effect analyses, to evaluate AiD process data on sampling quality (recruitment and randomization, reach) and intervention quality (relevance and feasibility, extent to which AiD was performed), which can be used for understanding internal and external validity. In this article, a model is presented that divides process evaluation data into first- and second-order process data. Qualitative and quantitative data based on personal files of residents, interviews of nursing home professionals, and a research database were analyzed according to the following process evaluation components: sampling quality and intervention quality. Nursing home. The pattern of residents' informed consent rates differed for dementia special care units and somatic units during the study. The nursing home staff was satisfied with the AiD program and reported that the program was feasible and relevant. With the exception of the first screening step (nursing staff members using a short observer-based depression scale), AiD components were not performed fully by NH staff as prescribed in the AiD protocol. Although NH staff found the program relevant and feasible and was satisfied with the program content, individual AiD components may have different feasibility. The results on sampling quality implied that statistical analyses of AiD effectiveness should account for the type of unit, whereas the findings on intervention quality implied that, next to the type of unit, analyses should account for the extent to which individual AiD program components were performed. In general, our first-order process data evaluation confirmed internal and external validity of the AiD trial, and this evaluation enabled further statistical fine tuning. The importance of evaluating the first-order process data before executing statistical effect analyses is thus underlined. Copyright © 2012 American Medical Directors Association, Inc. Published by Elsevier Inc. All rights reserved.

Assessing the role of internal climate variability in Antarctica's contribution to future sea-level rise

NASA Astrophysics Data System (ADS)

Tsai, C. Y.; Forest, C. E.; Pollard, D.

2017-12-01

The Antarctic ice sheet (AIS) has the potential to be a major contributor to future sea-level rise (SLR). Current projections of SLR due to AIS mass loss remain highly uncertain. Better understanding of how ice sheets respond to future climate forcing and variability is essential for assessing the long-term risk of SLR. However, the predictability of future climate is limited by uncertainties from emission scenarios, model structural differences, and the internal variability that is inherently generated within the fully coupled climate system. Among those uncertainties, the impact of internal variability on the AIS changes has not been explicitly assessed. In this study, we quantify the effect of internal variability on the AIS evolutions by using climate fields from two large-ensemble experiments using the Community Earth System Model to force a three-dimensional ice sheet model. We find that internal variability of climate fields, particularly atmospheric fields, among ensemble members leads to significantly different AIS responses. Our results show that the internal variability can cause about 80 mm differences of AIS contribution to SLR by 2100 compared to the ensemble-mean contribution of 380-450 mm. Moreover, using ensemble-mean climate fields as the forcing in the ice sheet model does not produce realistic simulations of the ice loss. Instead, it significantly delays the onset of retreat of the West Antarctic Ice Sheet for up to 20 years and significantly underestimates the AIS contribution to SLR by 0.07-0.11 m in 2100 and up to 0.34 m in the 2250's. Therefore, because the uncertainty caused by internal variability is irreducible, we seek to highlight a critical need to assess the role of internal variability in projecting the AIS loss over the next few centuries. By quantifying the impact of internal variability on AIS contribution to SLR, policy makers can obtain more robust estimates of SLR and implement suitable adaptation strategies.

Felicity Conditions for Human Skill Acquisition: Validating an AI (Artificial Intelligence)-Based Theory.

DTIC Science & Technology

1983-11-01

a stack, and productions are often not grouped into subroutines. For some reason, when psychologists think of temporary memory, whether for control ...Sierra cannot gcncrate. ’I7he third group contains 76 bug sets that have non -empty intersections with at least one bug set from Sierra’s predictions. This...that have non -empty intersections when interesected with at least one observed bug set. ’Ibis third group of bug sets is printed a little differently

Quality of head injury coding from autopsy reports with AIS © 2005 update 2008.

PubMed

Schick, Sylvia; Humrich, Anton; Graw, Matthias

2018-02-28

ABSTACT Objective: Coding injuries from autopsy reports of traffic accident victims according to Abbreviated Injury Scale AIS © 2005 update 2008 [1] is quite time consuming. The suspicion arose, that many issues leading to discussion between coder and control reader were based on information required by the AIS that was not documented in the autopsy reports. To quantify this suspicion, we introduced an AIS-detail-indicator (AIS-DI). To each injury in the AIS Codebook one letter from A to N was assigned indicating the level of detail. Rules were formulated to receive repeatable assignments. This scheme was applied to a selection of 149 multiply injured traffic fatalities. The frequencies of "not A" codes were calculated for each body region and it was analysed, why the most detailed level A had not been coded. As a first finding, the results of the head region are presented. 747 AIS head injury codes were found in 137 traffic fatalities, and 60% of these injuries were coded with an AIS-DI of level A. There are three different explanations for codes of AIS-DI "not A": Group 1 "Missing information in autopsy report" (5%), Group 2 "Clinical data required by AIS" (20%), and Group 3 "AIS system determined" (15%). Groups 1 and 2 show consequences for the ISS in 25 cases. Other body regions might perform differently. The AIS-DI can indicate the quality of the underlying data basis and, depending on the aims of different AIS users it can be a helpful tool for quality checks.

Apyrase inhibitors enhance the ability of diverse fungicides to inhibit the growth of different plant-pathogenic fungi.

PubMed

Kumar Tripathy, Manas; Weeraratne, Gayani; Clark, Greg; Roux, Stanley J

2017-09-01

A previous study has demonstrated that the treatment of Arabidopsis plants with chemical inhibitors of apyrase enzymes increases their sensitivity to herbicides. In this study, we found that the addition of the same or related apyrase inhibitors could potentiate the ability of different fungicides to inhibit the growth of five different pathogenic fungi in plate growth assays. The growth of all five fungi was partially inhibited by three commonly used fungicides: copper octanoate, myclobutanil and propiconazole. However, when these fungicides were individually tested in combination with any one of four different apyrase inhibitors (AI.1, AI.10, AI.13 or AI.15), their potency to inhibit the growth of five fungal pathogens was increased significantly relative to their application alone. The apyrase inhibitors were most effective in potentiating the ability of copper octanoate to inhibit fungal growth, and least effective in combination with propiconazole. Among the five pathogens assayed, that most sensitive to the fungicide-potentiating effects of the inhibitors was Sclerotinia sclerotiorum. Overall, among the 60 treatment combinations tested (five pathogens, four apyrase inhibitors, three fungicides), the addition of apyrase inhibitors increased significantly the sensitivity of fungi to the fungicide treatments in 53 of the combinations. Consistent with their predicted mode of action, inhibitors AI.1, AI.10 and AI.13 each increased the level of propiconazole retained in one of the fungi, suggesting that they could partially block the ability of efflux transporters to remove propiconazole from these fungi. © 2016 BSPP AND JOHN WILEY & SONS LTD.

Cultural Identity among Urban American Indian/Native Alaskan Youth: Implications for Alcohol and Drug Use

PubMed Central

Brown, Ryan A.; Dickerson, Daniel L.; D’Amico, Elizabeth J.

2016-01-01

American Indian and Alaska Native (AI/AN) youth exhibit high rates of alcohol and other drug (AOD) use, which is often linked to the social and cultural upheaval experienced by AI/ANs during the colonization of North America. Urban AI/AN youth may face unique challenges, including increased acculturative stress due to lower concentrations of AI/AN populations in urban areas. Few existing studies have explored cultural identity among urban AI/AN youth and its association with AOD use. Objectives This study used systematic qualitative methods with AI/AN communities in two urban areas within California to shed light on how urban AI/AN youth construct cultural identity and how this relates to AOD use and risk behaviors. Methods We conducted 10 focus groups with a total of 70 youth, parents, providers, and Community Advisory Board members and used team-based structured thematic analysis in the Dedoose software platform. Results We identified 12 themes: intergenerational stressors, cultural disconnection, AI/AN identity as protective, pan-tribal identity, mixed racial-ethnic identity, rural vs. urban environments, the importance of AI/AN institutions, stereotypes and harassment, cultural pride, developmental trajectories, risks of being AI/AN, and mainstream culture clash. Overall, youth voiced curiosity about their AI/AN roots and expressed interest in deepening their involvement in cultural activities. Adults described the myriad ways in which involvement in cultural activities provides therapeutic benefits for AI/AN youth. Conclusions Interventions that provide urban AI/AN youth with an opportunity to engage in cultural activities and connect with positive and healthy constructs in AI/AN culture may provide added impact to existing interventions. PMID:27450682

Space Environment Modelling with the Use of Artificial Intelligence Methods

NASA Astrophysics Data System (ADS)

Lundstedt, H.; Wintoft, P.; Wu, J.-G.; Gleisner, H.; Dovheden, V.

1996-12-01

Space based technological systems are affected by the space weather in many ways. Several severe failures of satellites have been reported at times of space storms. Our society also increasingly depends on satellites for communication, navigation, exploration, and research. Predictions of the conditions in the satellite environment have therefore become very important. We will here present predictions made with the use of artificial intelligence (AI) techniques, such as artificial neural networks (ANN) and hybrids of AT methods. We are developing a space weather model based on intelligence hybrid systems (IHS). The model consists of different forecast modules, each module predicts the space weather on a specific time-scale. The time-scales range from minutes to months with the fundamental time-scale of 1-5 minutes, 1-3 hours, 1-3 days, and 27 days. Solar and solar wind data are used as input data. From solar magnetic field measurements, either made on the ground at Wilcox Solar Observatory (WSO) at Stanford, or made from space by the satellite SOHO, solar wind parameters can be predicted and modelled with ANN and MHD models. Magnetograms from WSO are available on a daily basis. However, from SOHO magnetograms will be available every 90 minutes. SOHO magnetograms as input to ANNs will therefore make it possible to even predict solar transient events. Geomagnetic storm activity can today be predicted with very high accuracy by means of ANN methods using solar wind input data. However, at present real-time solar wind data are only available during part of the day from the satellite WIND. With the launch of ACE in 1997, solar wind data will on the other hand be available during 24 hours per day. The conditions of the satellite environment are not only disturbed at times of geomagnetic storms but also at times of intense solar radiation and highly energetic particles. These events are associated with increased solar activity. Predictions of these events are therefore also handled with the modules in the Lund Space Weather Model. Interesting Links: Lund Space Weather and AI Center

Tailoring a Web-Based Weight Maintenance Intervention for Northern Plains American Indian Public University Students

ERIC Educational Resources Information Center

Hemmingson, Kaitlyn; Lucchesi, Roxanne; Droke, Elizabeth; Kattelmann, Kendra K.

2016-01-01

Objective: High levels of obesity-related health disparities are common among US American Indian (AI) populations. AI public university students often face unique challenges that may contribute to weight gain and related consequences. Few weight maintenance interventions have been developed that meet the needs of AI public university students. The…

A novel hybrid decomposition-and-ensemble model based on CEEMD and GWO for short-term PM2.5 concentration forecasting

NASA Astrophysics Data System (ADS)

Niu, Mingfei; Wang, Yufang; Sun, Shaolong; Li, Yongwu

2016-06-01

To enhance prediction reliability and accuracy, a hybrid model based on the promising principle of "decomposition and ensemble" and a recently proposed meta-heuristic called grey wolf optimizer (GWO) is introduced for daily PM2.5 concentration forecasting. Compared with existing PM2.5 forecasting methods, this proposed model has improved the prediction accuracy and hit rates of directional prediction. The proposed model involves three main steps, i.e., decomposing the original PM2.5 series into several intrinsic mode functions (IMFs) via complementary ensemble empirical mode decomposition (CEEMD) for simplifying the complex data; individually predicting each IMF with support vector regression (SVR) optimized by GWO; integrating all predicted IMFs for the ensemble result as the final prediction by another SVR optimized by GWO. Seven benchmark models, including single artificial intelligence (AI) models, other decomposition-ensemble models with different decomposition methods and models with the same decomposition-ensemble method but optimized by different algorithms, are considered to verify the superiority of the proposed hybrid model. The empirical study indicates that the proposed hybrid decomposition-ensemble model is remarkably superior to all considered benchmark models for its higher prediction accuracy and hit rates of directional prediction.

A New Type of Atom Interferometry for Testing Fundamental Physics

NASA Astrophysics Data System (ADS)

Lorek, Dennis; Lämmerzahl, Claus; Wicht, Andreas

We present a new type of atom interferometer (AI) that provides a tool for ultra-high precision tests of fundamental physics. As an example we present how an AI based on highly charged hydrogen-like atoms is affected by gravitational waves (GW). A qualitative description of the quantum interferometric measurement principle is given, the modifications in the atomic Hamiltonian caused by the GW are presented, and the size of the resulting frequency shifts in hydrogen-like atoms is estimated. For a GW amplitude of h = 10-23 the frequency shift is of the order of 110μHz for an AI based on a 91-fold charged uranium ion. A frequency difference of this size can be resolved by current AIs in 1s.

Avian influenza shedding patterns in waterfowl: implications for surveillance, environmental transmission, and disease spread

USGS Publications Warehouse

Henaux, Viviane; Samuel, Michael D.

2011-01-01

Despite the recognized importance of fecal/oral transmission of low pathogenic avian influenza (LPAI) via contaminated wetlands, little is known about the length, quantity, or route of AI virus shed by wild waterfowl. We used published laboratory challenge studies to evaluate the length and quantity of low pathogenic (LP) and highly pathogenic (HP) virus shed via oral and cloacal routes by AI-infected ducks and geese, and how these factors might influence AI epidemiology and virus detection. We used survival analysis to estimate the duration of infection (from virus inoculation to the last day virus was shed) and nonlinear models to evaluate temporal patterns in virus shedding. We found higher mean virus titer and longer median infectious period for LPAI-infected ducks (10–11.5 days in oral and cloacal swabs) than HPAI-infected ducks (5 days) and geese (7.5 days). Based on the median bird infectious dose, we found that environmental contamination is two times higher for LPAI- than HPAI-infectious ducks, which implies that susceptible birds may have a higher probability of infection during LPAI than HPAI outbreaks. Less environmental contamination during the course of infection and previously documented shorter environmental persistence for HPAI than LPAI suggest that the environment is a less favorable reservoir for HPAI. The longer infectious period, higher virus titers, and subclinical infections with LPAI viruses favor the spread of these viruses by migratory birds in comparison to HPAI. Given the lack of detection of HPAI viruses through worldwide surveillance, we suggest monitoring for AI should aim at improving our understanding of AI dynamics (in particular, the role of the environment and immunity) using long-term comprehensive live bird, serologic, and environmental sampling at targeted areas. Our findings on LPAI and HPAI shedding patterns over time provide essential information to parameterize environmental transmission and virus spread in predictive epizootiologic models of disease risks.

Avian influenza shedding patterns in waterfowl: implications for surveillance, environmentaltransmission, and disease spread

USGS Publications Warehouse

Henaux, V.; Samuel, M.D.

2011-01-01

Despite the recognized importance of fecal/oral transmission of low pathogenic avian influenza (LPAI) via contaminated wetlands, little is known about the length, quantity, or route of AI virus shed by wild waterfowl. We used published laboratory challenge studies to evaluate the length and quantity of low pathogenic (LP) and highly pathogenic (HP) virus shed via oral and cloacal routes by AI-infected ducks and geese, and how these factors might influence AI epidemiology and virus detection. We used survival analysis to estimate the duration of infection(from virus inoculation to the last day virus was shed) and nonlinear models to evaluate temporal patterns in virus shedding. We found higher mean virus titer and longer median infectious period for LPAI-infected ducks (1011.5 days in oral and cloacal swabs) than HPAI-infected ducks(5 days) and geese (7.5 days). Based on the median bird infectious dose, we found that environmental contamination is two times higher for LPAI- than HPAI-infectious ducks, which implies that susceptible birds may have a higher probability of infection during LPAI than HP AIoutbreaks. Less environmental contamination during the course of infection and previously documented shorter environmental persistence for HPAI than LPAI suggest that the environment is a less favorable reservoir for HPAI. The longer infectious period, higher virus titers, and subclinical infections with LPAI viruses favor the spread of these viruses by migratory birds in comparison to HPAI. Given the lack of detection of HPAI viruses through worldwide surveillance,we suggest monitoring for AI should aim at improving our understanding of AI dynamics (inparticular, the role of the environment and immunity) using long-term comprehensive live bird, serologic, and environmental sampling at targeted areas. Our findings on LPAI and HPAIshedding patterns over time provide essential information to parameterize environmental transmission and virus spread in predictive epizootio logic models of disease risks. ?? Wildlife Disease Association 2011.

TBS and BMD at the end of AI-therapy: A prospective study of the B-ABLE cohort.

PubMed

María, Rodríguez-Sanz; Marta, Pineda-Moncusí; Sonia, Servitja; Natalia, Garcia-Giralt; Tamara, Martos; Ignasi, Tusquets; Maria, Martínez-García; Jaime, Rodriguez-Morera; Adolfo, Diez-Perez; Joan, Albanell; Xavier, Nogués

2016-11-01

Patients with breast cancer under aromatase inhibitor (AI) treatment often develop osteoporosis and their average bone loss rate is twice that of natural reduction during menopause, increasing fracture risk. As the current diagnostic technique based on bone mineral density (BMD) provides no information on bone quality, the Trabecular Bone Score (TBS) has been proposed to reflect bone microarchitecture status. The present study was designed to assess prospective changes in TBS and lumbar spine (LS) BMD in postmenopausal women with breast cancer at completion of AI treatment. B-ABLE is a prospective cohort of 735 women with breast cancer treated with AIs according to American Society of Clinical Oncology recommendations: 5years of AI starting within 6weeks post-surgery or 1month after the last cycle of chemotherapy (5y-AI group), or switching to an AI to complete 5-year therapy after 2-3years of tamoxifen (pTMX-AI group). Patients with osteoporosis were treated with oral bisphosphonates (BP). TBS and LS-BMD changes at completion of AI therapy were evaluated by Student t-test for paired samples. Pearson correlation coefficients were computed for correlations between LS-BMD and TBS. AI treatment was completed by 277 women. Of these, 70 (25.3%) were allocated to BP therapy. The non-BP-treated patients (74.7%) showed significant decreases in TBS (-2.94% in pTMX-AI and -2.93% in 5y-AI groups) and in LS-BMD (-4.14% in pTMX-AI and -2.28% in 5y-AI groups) at the end of AI treatment. In BP-treated patients, TBS remained stable at the end of AI treatment, whereas LS-BMD showed significant increases (+2.30% in pTMX-AI and +5.33% in 5y-AI groups). Moderate associations between TBS and LS-BMD values at baseline and at the end of AI treatment (r=0.4; P<0.001) were observed. At the end of treatment, changes in spine BMD and TBS were weakly correlated (r=0.1, P<0.01). AI therapy induces significant decreases in TBS, comparable to BMD loss. BP-treated patients maintained TBS values, whereas BMD increased. AI treatment leads to deterioration of bone microarchitecture, which seems to be attenuated by BP therapy. Copyright © 2016 Elsevier Inc. All rights reserved.

Enhanced fertility prediction of cryopreserved boar spermatozoa using novel sperm function assessment

USDA-ARS?s Scientific Manuscript database

Cryopreserved semen is seldom used for commercial porcine artificial insemination (AI) despite many advantages that cryopreservation provides. Compared to fresh semen, the fertility of frozen-thawed boar sperm is more variable but usually less. Predicting the fertility of individual ejaculates for s...

Methods for Processing and Interpretation of AIS Signals Corrupted by Noise and Packet Collisions

NASA Astrophysics Data System (ADS)

Poļevskis, J.; Krastiņš, M.; Korāts, G.; Skorodumovs, A.; Trokšs, J.

2012-01-01

The authors deal with the operation of Automatic Identification System (AIS) used in the marine traffic monitoring to broadcast messages containing information about the vessel: id, payload, size, speed, destination etc., meant primarily for avoidance of ship collisions. To extend the radius of AIS operation, it is envisaged to dispose its receivers on satellites. However, in space, due to a large coverage area, interfering factors are especially pronounced - such as packet collision, Doppler's shift and noise impact on AIS message receiving, pre-processing and decoding. To assess the quality of an AIS receiver's operation, a test was carried out in which, varying automatically frequency, amplitude, noise, and other parameters, the data on the ability of the receiver's ability to decode AIS signals are collected. In the work, both hardware- and software-based AIS decoders were tested. As a result, quite satisfactory statistics has been gathered - both on the common and the differing features of such decoders when operating in space. To obtain reliable data on the software-defined radio AIS receivers, further research is envisaged.

Advancing differential atom interferometry for space applications

NASA Astrophysics Data System (ADS)

Chiow, Sheng-Wey; Williams, Jason; Yu, Nan

2016-05-01

Atom interferometer (AI) based sensors exhibit precision and accuracy unattainable with classical sensors, thanks to the inherent stability of atomic properties. Dual atomic sensors operating in a differential mode further extend AI applicability beyond environmental disturbances. Extraction of the phase difference between dual AIs, however, typically introduces uncertainty and systematic in excess of that warranted by each AI's intrinsic noise characteristics, especially in practical applications and real time measurements. In this presentation, we report our efforts in developing practical schemes for reducing noises and enhancing sensitivities in the differential AI measurement implementations. We will describe an active phase extraction method that eliminates the noise overhead and demonstrates a performance boost of a gravity gradiometer by a factor of 3. We will also describe a new long-baseline approach for differential AI measurements in a laser ranging assisted AI configuration. The approach uses well-developed AIs for local measurements but leverage the mature schemes of space laser interferometry for LISA and GRACE. This research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a Contract with NASA.

Anterior Insula Volume and Guilt

PubMed Central

Belden, Andy C.; Barch, Deanna M.; Oakberg, Timothy J.; April, Laura M.; Harms, Michael P.; Botteron, Kelly N.; Luby, Joan L.

2016-01-01

IMPORTANCE This is the first study to date to examine volumetric alterations in the anterior insula (AI) as a potential biomarker for the course of childhood major depressive disorder (MDD). OBJECTIVES To examine whether children with a history of preschool-onset (PO) MDD show reduced AI volume, whether a specific symptom of PO MDD (pathological guilt) is related to AI volume reduction (given the known relationship between AI and guilt processing), and whether AI volumes predict subsequent likelihood of having an episode of MDD. DESIGN, SETTING, AND PARTICIPANTS In a prospective longitudinal study, 306 children (age range, 3.00–5.11 years) and caregivers completed DSM diagnostic assessments at 6 annual time points during 10 years as part of the Preschool Depression Study. Magnetic resonance imaging was completed on a subset of 145 school-age children (age range, 6.11–12.11 years). MAIN OUTCOMES AND MEASURES Whole-brain–adjusted AI volume measured using magnetic resonance imaging at school age and children’s diagnosis of MDD any time after their imaging. RESULTS Compared with children without a history of PO MDD, school-age children previously diagnosed as having PO MDD had smaller left and right AI volumes (Wilks Λ = 0.94, F2,124 = 3.37, P = .04, Cohen d = 0.23). However, the effect of PO MDD on reduced AI volumes was better explained by children’s experience of pathological guilt during preschool (Λ = 0.91, F2,120 = 6.17, P = .003, d = .30). When covarying for children’s lifetime history of MDD episodes, their experience of pathological guilt during preschool, as well as their sex and age at the time of imaging, schoolchildren’s right-side AI volume was a significant predictor of being diagnosed as having an MDD episode after imaging (odds ratio, 0.96; 95% CI, 0.01–0.75; P = .03). CONCLUSIONS AND RELEVANCE These results provide evidence that structural abnormalities in AI volume are related to the neurobiology of depressive disorders starting in early childhood. The present findings are consistent with mounting research in adult MDD suggesting that insula function and structure may be a target biomarker for major depression. PMID:25390502

Anterior insula volume and guilt: neurobehavioral markers of recurrence after early childhood major depressive disorder.

PubMed

Belden, Andy C; Barch, Deanna M; Oakberg, Timothy J; April, Laura M; Harms, Michael P; Botteron, Kelly N; Luby, Joan L

2015-01-01

This is the first study to date to examine volumetric alterations in the anterior insula (AI) as a potential biomarker for the course of childhood major depressive disorder (MDD). To examine whether children with a history of preschool-onset (PO) MDD show reduced AI volume, whether a specific symptom of PO MDD (pathological guilt) is related to AI volume reduction (given the known relationship between AI and guilt processing), and whether AI volumes predict subsequent likelihood of having an episode of MDD. In a prospective longitudinal study, 306 children (age range, 3.00-5.11 years) and caregivers completed DSM diagnostic assessments at 6 annual time points during 10 years as part of the Preschool Depression Study. Magnetic resonance imaging was completed on a subset of 145 school-age children (age range, 6.11-12.11 years). Whole-brain-adjusted AI volume measured using magnetic resonance imaging at school age and children's diagnosis of MDD any time after their imaging. Compared with children without a history of PO MDD, school-age children previously diagnosed as having PO MDD had smaller left and right AI volumes (Wilks Λ = 0.94, F2,124 = 3.37, P = .04, Cohen d = 0.23). However, the effect of PO MDD on reduced AI volumes was better explained by children's experience of pathological guilt during preschool (Λ = 0.91, F2,120 = 6.17, P = .003, d = .30). When covarying for children's lifetime history of MDD episodes, their experience of pathological guilt during preschool, as well as their sex and age at the time of imaging, schoolchildren's right-side AI volume was a significant predictor of being diagnosed as having an MDD episode after imaging (odds ratio, 0.96; 95% CI, 0.01-0.75; P = .03). These results provide evidence that structural abnormalities in AI volume are related to the neurobiology of depressive disorders starting in early childhood. The present findings are consistent with mounting research in adult MDD suggesting that insula function and structure may be a target biomarker for major depression.

Gene expression alterations associated with outcome in aromatase inhibitor-treated ER+ early-stage breast cancer patients.

PubMed

Thomsen, Karina G; Lyng, Maria B; Elias, Daniel; Vever, Henriette; Knoop, Ann S; Lykkesfeldt, Anne E; Lænkholm, Anne-Vibeke; Ditzel, Henrik J

2015-12-01

Aromatase inhibitors (AI), either alone or together with chemotherapy, have become the standard adjuvant treatment for postmenopausal, estrogen receptor-positive (ER+) breast cancer. Although AIs improve overall survival, resistance is still a major clinical problem, thus additional biomarkers predictive of outcome of ER+ breast cancer patients treated with AIs are needed. Global gene expression analysis was performed on ER+ primary breast cancers from patients treated with adjuvant AI monotherapy; half experienced recurrence (median follow-up 6.7 years). Gene expression alterations were validated by qRT-PCR, and functional studies evaluating the effect of siRNA-mediated gene knockdown on cell growth were performed. Twenty-six genes, including TFF3, DACH1, RGS5, and GHR, were shown to exhibit altered expression in tumors from patients with recurrence versus non-recurrent (fold change ≥1.5, p < 0.05), and the gene expression alterations were confirmed using qRT-PCR. Ten of these 26 genes could be linked in a network associated with cellular proliferation, growth, and development. TFF3, which encodes for trefoil factor 3 and is an estrogen-responsive oncogene shown to play a functional role in tamoxifen resistance and metastasis of ER+ breast cancer, was also shown to be upregulated in an AI-resistant cell line model, and reduction of TFF3 levels using TFF3-specific siRNAs decreased the growth of both the AI-resistant and -sensitive parental cell lines. Moreover, overexpression of TFF3 in parental AI-sensitive MCF-7/S0.5 cells resulted in reduced sensitivity to the AI exemestane, whereas TFF3 overexpression had no effect on growth in the absence of exemestane, indicating that TFF3 mediates growth and survival signals that abrogate the growth inhibitory effect of exemestane. We identified a panel of 26 genes exhibiting altered expression associated with disease recurrence in patients treated with adjuvant AI monotherapy, including TFF3, which was shown to exhibit a growth- and survival-promoting effect in the context of AI treatment.

Artificial intelligence (AI) based tactical guidance for fighter aircraft

NASA Technical Reports Server (NTRS)

Mcmanus, John W.; Goodrich, Kenneth H.

1990-01-01

A research program investigating the use of artificial intelligence (AI) techniques to aid in the development of a Tactical Decision Generator (TDG) for Within Visual Range air combat engagements is discussed. The application of AI programming and problem solving methods in the development and implementation of the Computerized Logic For Air-to-Air Warfare Simulations (CLAWS), a second generation TDG, is presented. The knowledge-based systems used by CLAWS to aid in the tactical decision-making process are outlined in detail, and the results of tests to evaluate the performance of CLAWS versus a baseline TDG developed in FORTRAN to run in real time in the Langley Differential Maneuvering Simulator, are presented. To date, these test results have shown significant performance gains with respect to the TDG baseline in one-versus-one air combat engagements, and the AI-based TDG software has proven to be much easier to modify and maintain than the baseline FORTRAN TDG programs.

Psychometric analyses to improve the Dutch ICF Activity Inventory.

PubMed

Bruijning, Janna E; van Rens, Ger; Knol, Dirk; van Nispen, Ruth

2013-08-01

In the past, rehabilitation centers for the visually impaired used unstructured or semistructured methods to assess rehabilitation needs of their patients. Recently, an extensive instrument, the Dutch ICF Activity Inventory (D-AI), was developed to systematically investigate rehabilitation needs of visually impaired adults and to evaluate rehabilitation outcomes. The purpose of this study was to investigate the underlying factor structure and other psychometric properties to shorten and improve the D-AI. The D-AI was administered to 241 visually impaired persons who recently enrolled in a multidisciplinary rehabilitation center. The D-AI uses graded scores to assess the importance and difficulty of 65 rehabilitation goals. For high-priority goals (e.g., daily meal preparation), the difficulty of underlying tasks (e.g., read recipes, cut vegetables) was assessed. To reduce underlying task items (>950), descriptive statistics were investigated and factor analyses were performed for several goals. The internal consistency reliability and test-retest reliability of the D-AI were investigated by calculating Cronbach α and Cohen (weighted) κ. Finally, consensus-based discussions were used to shorten and improve the D-AI. Except for one goal, factor analysis model parameters were at least reasonable. Internal consistency reliability was satisfactory (range, 0.74 to 0.93). In total, 60% of the 65 goal importance items and 84.4% of the goal difficulty items showed moderate to almost perfect κ values (≥0.40). After consensus-based discussions, a new D-AI was produced, containing 48 goals and less than 500 tasks. The analyses were an important step in the validation process of the D-AI and to develop a more feasible assessment tool to investigate rehabilitation needs of visually impaired persons in a systematic way. The D-AI is currently implemented in all Dutch rehabilitation centers serving all visually impaired adults with various rehabilitation needs.

Gaps in Survey Data on Cancer in American Indian and Alaska Native Populations: Examination of US Population Surveys, 1960–2010

PubMed Central

Duran, Tinka; Stimpson, Jim P.; Smith, Corey

2013-01-01

Introduction Population-based data are essential for quantifying the problems and measuring the progress made by comprehensive cancer control programs. However, cancer information specific to the American Indian/Alaska Native (AI/AN) population is not readily available. We identified major population-based surveys conducted in the United States that contain questions related to cancer, documented the AI/AN sample size in these surveys, and identified gaps in the types of cancer-related information these surveys collect. Methods We conducted an Internet query of US Department of Health and Human Services agency websites and a Medline search to identify population-based surveys conducted in the United States from 1960 through 2010 that contained information about cancer. We used a data extraction form to collect information about the purpose, sample size, data collection methods, and type of information covered in the surveys. Results Seventeen survey sources met the inclusion criteria. Information on access to and use of cancer treatment, follow-up care, and barriers to receiving timely and quality care was not consistently collected. Estimates specific to the AI/AN population were often lacking because of inadequate AI/AN sample size. For example, 9 national surveys reviewed reported an AI/AN sample size smaller than 500, and 10 had an AI/AN sample percentage less than 1.5%. Conclusion Continued efforts are needed to increase the overall number of AI/AN participants in these surveys, improve the quality of information on racial/ethnic background, and collect more information on treatment and survivorship. PMID:23517582

Accurate tracking of tumor volume change during radiotherapy by CT-CBCT registration with intensity correction

NASA Astrophysics Data System (ADS)

Park, Seyoun; Robinson, Adam; Quon, Harry; Kiess, Ana P.; Shen, Colette; Wong, John; Plishker, William; Shekhar, Raj; Lee, Junghoon

2016-03-01

In this paper, we propose a CT-CBCT registration method to accurately predict the tumor volume change based on daily cone-beam CTs (CBCTs) during radiotherapy. CBCT is commonly used to reduce patient setup error during radiotherapy, but its poor image quality impedes accurate monitoring of anatomical changes. Although physician's contours drawn on the planning CT can be automatically propagated to daily CBCTs by deformable image registration (DIR), artifacts in CBCT often cause undesirable errors. To improve the accuracy of the registration-based segmentation, we developed a DIR method that iteratively corrects CBCT intensities by local histogram matching. Three popular DIR algorithms (B-spline, demons, and optical flow) with the intensity correction were implemented on a graphics processing unit for efficient computation. We evaluated their performances on six head and neck (HN) cancer cases. For each case, four trained scientists manually contoured the nodal gross tumor volume (GTV) on the planning CT and every other fraction CBCTs to which the propagated GTV contours by DIR were compared. The performance was also compared with commercial image registration software based on conventional mutual information (MI), VelocityAI (Varian Medical Systems Inc.). The volume differences (mean±std in cc) between the average of the manual segmentations and automatic segmentations are 3.70+/-2.30 (B-spline), 1.25+/-1.78 (demons), 0.93+/-1.14 (optical flow), and 4.39+/-3.86 (VelocityAI). The proposed method significantly reduced the estimation error by 9% (B-spline), 38% (demons), and 51% (optical flow) over the results using VelocityAI. Although demonstrated only on HN nodal GTVs, the results imply that the proposed method can produce improved segmentation of other critical structures over conventional methods.

Assessment of glucocorticoid therapy with salivary cortisol in secondary adrenal insufficiency.

PubMed

Ceccato, Filippo; Albiger, Nora; Reimondo, Giuseppe; Frigo, Anna Chiara; Ferasin, Sergio; Occhi, Gianluca; Mantero, Franco; Terzolo, Massimo; Scaroni, Carla

2012-12-01

Appropriate glucocorticoid replacement therapy in adrenal insufficiency (AI) is crucial, given the risks of chronic under- or overtreatment, particularly in patients on multiple medications. Salivary sampling allows for non-invasive, stress-free cortisol measurement. To determine whether salivary cortisol measurement is helpful in assessing the adequacy of glucocorticoid therapy with cortisone acetate (CA) in patients with secondary AI. A prospective cohort study at the Endocrinology Unit of Padua University Hospital. Six samples of salivary cortisol were collected from 28 patients with secondary AI on CA treatment and from 36 healthy volunteers at fixed times of the day, and used to calculate salivary cortisol levels at each time point and the area under the curve (AUC) across the different sampling times. Salivary cortisol levels were lower in patients than in controls in the morning but no differences were found in the afternoon or at night before resting. Salivary cortisol levels were higher in patients immediately following CA administration. Ten patients showed an AUC above the 97.5th percentile of controls, without clinical signs of hypercortisolism, and salivary cortisol levels 90 min after each dose of CA predict the AUC. All patients had severe GH deficiency and there were no differences in salivary cortisol levels or AUC between patients treated or not with GH. Two salivary cortisol determinations, able to predict the daily AUC, may allow for assessing the adequacy of glucocorticoid replacement therapy in secondary AI and for identifying cases of over- or undertreatment.

MiR-153 Regulates Amelogenesis by Targeting Endocytotic and Endosomal/lysosomal Pathways–Novel Insight into the Origins of Enamel Pathologies

PubMed Central

Yin, Kaifeng; Lin, Wenting; Guo, Jing; Sugiyama, Toshihiro; Snead, Malcolm L.; Hacia, Joseph G.; Paine, Michael L.

2017-01-01

Amelogenesis imperfecta (AI) is group of inherited disorders resulting in enamel pathologies. The involvement of epigenetic regulation in the pathogenesis of AI is yet to be clarified due to a lack of knowledge about amelogenesis. Our previous genome-wide microRNA and mRNA transcriptome analyses suggest a key role for miR-153 in endosome/lysosome-related pathways during amelogenesis. Here we show that miR-153 is significantly downregulated in maturation ameloblasts compared with secretory ameloblasts. Within ameloblast-like cells, upregulation of miR-153 results in the downregulation of its predicted targets including Cltc, Lamp1, Clcn4 and Slc4a4, and a number of miRNAs implicated in endocytotic pathways. Luciferase reporter assays confirmed the predicted interactions between miR-153 and the 3′-UTRs of Cltc, Lamp1 (in a prior study), Clcn4 and Slc4a4. In an enamel protein intake assay, enamel cells transfected with miR-153 show a decreased ability to endocytose enamel proteins. Finally, microinjection of miR-153 in the region of mouse first mandibular molar at postnatal day 8 (PN8) induced AI-like pathologies when the enamel development reached maturity (PN12). In conclusion, miR-153 regulates maturation-stage amelogenesis by targeting key genes involved in the endocytotic and endosomal/lysosomal pathways, and disruption of miR-153 expression is a potential candidate etiologic factor contributing to the occurrence of AI. PMID:28287144

MiR-153 Regulates Amelogenesis by Targeting Endocytotic and Endosomal/lysosomal Pathways-Novel Insight into the Origins of Enamel Pathologies.

PubMed

Yin, Kaifeng; Lin, Wenting; Guo, Jing; Sugiyama, Toshihiro; Snead, Malcolm L; Hacia, Joseph G; Paine, Michael L

2017-03-13

Amelogenesis imperfecta (AI) is group of inherited disorders resulting in enamel pathologies. The involvement of epigenetic regulation in the pathogenesis of AI is yet to be clarified due to a lack of knowledge about amelogenesis. Our previous genome-wide microRNA and mRNA transcriptome analyses suggest a key role for miR-153 in endosome/lysosome-related pathways during amelogenesis. Here we show that miR-153 is significantly downregulated in maturation ameloblasts compared with secretory ameloblasts. Within ameloblast-like cells, upregulation of miR-153 results in the downregulation of its predicted targets including Cltc, Lamp1, Clcn4 and Slc4a4, and a number of miRNAs implicated in endocytotic pathways. Luciferase reporter assays confirmed the predicted interactions between miR-153 and the 3'-UTRs of Cltc, Lamp1 (in a prior study), Clcn4 and Slc4a4. In an enamel protein intake assay, enamel cells transfected with miR-153 show a decreased ability to endocytose enamel proteins. Finally, microinjection of miR-153 in the region of mouse first mandibular molar at postnatal day 8 (PN8) induced AI-like pathologies when the enamel development reached maturity (PN12). In conclusion, miR-153 regulates maturation-stage amelogenesis by targeting key genes involved in the endocytotic and endosomal/lysosomal pathways, and disruption of miR-153 expression is a potential candidate etiologic factor contributing to the occurrence of AI.

Rapid prototyping facility for flight research in artificial-intelligence-based flight systems concepts

NASA Technical Reports Server (NTRS)

Duke, E. L.; Regenie, V. A.; Deets, D. A.

1986-01-01

The Dryden Flight Research Facility of the NASA Ames Research Facility of the NASA Ames Research Center is developing a rapid prototyping facility for flight research in flight systems concepts that are based on artificial intelligence (AI). The facility will include real-time high-fidelity aircraft simulators, conventional and symbolic processors, and a high-performance research aircraft specially modified to accept commands from the ground-based AI computers. This facility is being developed as part of the NASA-DARPA automated wingman program. This document discusses the need for flight research and for a national flight research facility for the rapid prototyping of AI-based avionics systems and the NASA response to those needs.

Evidence-Based Practices, Attitudes, and Beliefs in Substance Abuse Treatment Programs Serving American Indians and Alaska Natives: A Qualitative Study

PubMed Central

Larios, Sandra E.; Wright, Serena; Jernstrom, Amanda; Lebron, Dorothy; Sorensen, James L.

2012-01-01

Substance abuse disproportionately impacts American Indian/Alaska Native (AI/AN) communities in the United States. For the increasing numbers of AI/AN individuals who enter and receive treatment for their alcohol or other drug problem it is imperative that the service they receive be effective. This study used qualitative methodology to examine attitudes toward evidence-based practices, also known as evidence-based treatments (EBTs) in minority-serving substance abuse treatment programs in the San Francisco Bay area. Twenty-two interviews were conducted in the study, of which seven were with program directors and substance abuse counselors at two urban AI/AN focused sites. These clinics were more likely than other minority-focused programs to have experience with research and knowledge about adapting EBTs. Only in the AI/AN specific sites did an issue arise concerning visibility, that is, undercounting AI/AN people in national and state databases. Similar to other minority-focused programs, these clinics described mistrust, fear of exploitation from the research community, and negative attitudes towards EBTs. The underutilization of EBTs in substance abuse programs is prevalent and detrimental to the health of patients who would benefit from their use. Future research should explore how to use this research involvement and experience with adaptation to increase the adoption of EBTs in AI/AN serving clinics. PMID:22400469

Designer cells programming quorum-sensing interference with microbes.

PubMed

Sedlmayer, Ferdinand; Hell, Dennis; Müller, Marius; Ausländer, David; Fussenegger, Martin

2018-05-08

Quorum sensing is a promising target for next-generation anti-infectives designed to address evolving bacterial drug resistance. The autoinducer-2 (AI-2) is a key quorum-sensing signal molecule which regulates bacterial group behaviors and is recognized by many Gram-negative and Gram-positive bacteria. Here we report a synthetic mammalian cell-based microbial-control device that detects microbial chemotactic formyl peptides through a formyl peptide sensor (FPS) and responds by releasing AI-2. The microbial-control device was designed by rewiring an artificial receptor-based signaling cascade to a modular biosynthetic AI-2 production platform. Mammalian cells equipped with the microbial-control gene circuit detect formyl peptides secreted from various microbes with high sensitivity and respond with robust AI-2 production, resulting in control of quorum sensing-related behavior of pathogenic Vibrio harveyi and attenuation of biofilm formation by the human pathogen Candida albicans. The ability to manipulate mixed microbial populations through fine-tuning of AI-2 levels may provide opportunities for future anti-infective strategies.

Artificial intelligence based models for stream-flow forecasting: 2000-2015

NASA Astrophysics Data System (ADS)

Yaseen, Zaher Mundher; El-shafie, Ahmed; Jaafar, Othman; Afan, Haitham Abdulmohsin; Sayl, Khamis Naba

2015-11-01

The use of Artificial Intelligence (AI) has increased since the middle of the 20th century as seen in its application in a wide range of engineering and science problems. The last two decades, for example, has seen a dramatic increase in the development and application of various types of AI approaches for stream-flow forecasting. Generally speaking, AI has exhibited significant progress in forecasting and modeling non-linear hydrological applications and in capturing the noise complexity in the dataset. This paper explores the state-of-the-art application of AI in stream-flow forecasting, focusing on defining the data-driven of AI, the advantages of complementary models, as well as the literature and their possible future application in modeling and forecasting stream-flow. The review also identifies the major challenges and opportunities for prospective research, including, a new scheme for modeling the inflow, a novel method for preprocessing time series frequency based on Fast Orthogonal Search (FOS) techniques, and Swarm Intelligence (SI) as an optimization approach.

The Power of Protection: A Population-Based Comparison of Native and Non-Native Youth Suicide Attempters

ERIC Educational Resources Information Center

Mackin, Juliette; Perkins, Tamara; Furrer, Carrie

2012-01-01

This study provides actionable information about intervening with American Indian/Alaska Native (AI/AN) youth to prevent suicide. Statewide school survey data were used to model the impact of risk and protective factors on self-reported suicide attempts (both AI/AN and non-AI/AN). The cumulative risk and protective model worked similarly for both…

Using Abbreviated Injury Scale (AIS) codes to classify Computed Tomography (CT) features in the Marshall System.

PubMed

Lesko, Mehdi M; Woodford, Maralyn; White, Laura; O'Brien, Sarah J; Childs, Charmaine; Lecky, Fiona E

2010-08-06

The purpose of Abbreviated Injury Scale (AIS) is to code various types of Traumatic Brain Injuries (TBI) based on their anatomical location and severity. The Marshall CT Classification is used to identify those subgroups of brain injured patients at higher risk of deterioration or mortality. The purpose of this study is to determine whether and how AIS coding can be translated to the Marshall Classification Initially, a Marshall Class was allocated to each AIS code through cross-tabulation. This was agreed upon through several discussion meetings with experts from both fields (clinicians and AIS coders). Furthermore, in order to make this translation possible, some necessary assumptions with regards to coding and classification of mass lesions and brain swelling were essential which were all approved and made explicit. The proposed method involves two stages: firstly to determine all possible Marshall Classes which a given patient can attract based on allocated AIS codes; via cross-tabulation and secondly to assign one Marshall Class to each patient through an algorithm. This method can be easily programmed in computer softwares and it would enable future important TBI research programs using trauma registry data.

Using Abbreviated Injury Scale (AIS) codes to classify Computed Tomography (CT) features in the Marshall System

PubMed Central

2010-01-01

Background The purpose of Abbreviated Injury Scale (AIS) is to code various types of Traumatic Brain Injuries (TBI) based on their anatomical location and severity. The Marshall CT Classification is used to identify those subgroups of brain injured patients at higher risk of deterioration or mortality. The purpose of this study is to determine whether and how AIS coding can be translated to the Marshall Classification Methods Initially, a Marshall Class was allocated to each AIS code through cross-tabulation. This was agreed upon through several discussion meetings with experts from both fields (clinicians and AIS coders). Furthermore, in order to make this translation possible, some necessary assumptions with regards to coding and classification of mass lesions and brain swelling were essential which were all approved and made explicit. Results The proposed method involves two stages: firstly to determine all possible Marshall Classes which a given patient can attract based on allocated AIS codes; via cross-tabulation and secondly to assign one Marshall Class to each patient through an algorithm. Conclusion This method can be easily programmed in computer softwares and it would enable future important TBI research programs using trauma registry data. PMID:20691038

Multisensor system and artificial intelligence in housing for the elderly.

PubMed

Chan, M; Bocquet, H; Campo, E; Val, T; Estève, D; Pous, J

1998-01-01

To improve the safety of a growing proportion of elderly and disabled people in the developed countries, a multisensor system based on Artificial Intelligence (AI), Advanced Telecommunications (AT) and Information Technology (IT) has been devised and fabricated. Thus, the habits and behaviours of these populations will be recorded without disturbing their daily activities. AI will diagnose any abnormal behavior or change and the system will warn the professionals. Gerontology issues are presented together with the multisensor system, the AI-based learning and diagnosis methodology and the main functionalities.

Re-assess Vector Indices Threshold as an Early Warning Tool for Predicting Dengue Epidemic in a Dengue Non-endemic Country

PubMed Central

Hsu, Pi-Shan; Chen, Chaur-Dong; Lian, Ie-Bin; Chao, Day-Yu

2015-01-01

Background Despite dengue dynamics being driven by complex interactions between human hosts, mosquito vectors and viruses that are influenced by climate factors, an operational model that will enable health authorities to anticipate the outbreak risk in a dengue non-endemic area has not been developed. The objectives of this study were to evaluate the temporal relationship between meteorological variables, entomological surveillance indices and confirmed dengue cases; and to establish the threshold for entomological surveillance indices including three mosquito larval indices [Breteau (BI), Container (CI) and House indices (HI)] and one adult index (AI) as an early warning tool for dengue epidemic. Methodology/Principal Findings Epidemiological, entomological and meteorological data were analyzed from 2005 to 2012 in Kaohsiung City, Taiwan. The successive waves of dengue outbreaks with different magnitudes were recorded in Kaohsiung City, and involved a dominant serotype during each epidemic. The annual indigenous dengue cases usually started from May to June and reached a peak in October to November. Vector data from 2005–2012 showed that the peak of the adult mosquito population was followed by a peak in the corresponding dengue activity with a lag period of 1–2 months. Therefore, we focused the analysis on the data from May to December and the high risk district, where the inspection of the immature and mature mosquitoes was carried out on a weekly basis and about 97.9% dengue cases occurred. The two-stage model was utilized here to estimate the risk and time-lag effect of annual dengue outbreaks in Taiwan. First, Poisson regression was used to select the optimal subset of variables and time-lags for predicting the number of dengue cases, and the final results of the multivariate analysis were selected based on the smallest AIC value. Next, each vector index models with selected variables were subjected to multiple logistic regression models to examine the accuracy of predicting the occurrence of dengue cases. The results suggested that Model-AI, BI, CI and HI predicted the occurrence of dengue cases with 83.8, 87.8, 88.3 and 88.4% accuracy, respectively. The predicting threshold based on individual Model-AI, BI, CI and HI was 0.97, 1.16, 1.79 and 0.997, respectively. Conclusion/Significance There was little evidence of quantifiable association among vector indices, meteorological factors and dengue transmission that could reliably be used for outbreak prediction. Our study here provided the proof-of-concept of how to search for the optimal model and determine the threshold for dengue epidemics. Since those factors used for prediction varied, depending on the ecology and herd immunity level under different geological areas, different thresholds may be developed for different countries using a similar structure of the two-stage model. PMID:26366874

Enhanced fertility prediction of cryopreserved boar spermatozoa using novel sperm function assessment.

PubMed

Daigneault, B W; McNamara, K A; Purdy, P H; Krisher, R L; Knox, R V; Rodriguez-Zas, S L; Miller, D J

2015-05-01

Due to reduced fertility, cryopreserved semen is seldom used for commercial porcine artificial insemination (AI). Predicting the fertility of individual frozen ejaculates for selection of higher quality semen prior to AI would increase overall success. Our objective was to test novel and traditional laboratory analyses to identify characteristics of cryopreserved spermatozoa that are related to boar fertility. Traditional post-thaw analyses of motility, viability, and acrosome integrity were performed on each ejaculate. In vitro fertilization, cleavage, and blastocyst development were also determined. Finally, spermatozoa-oviduct binding and competitive zona-binding assays were applied to assess sperm adhesion to these two matrices. Fertility of the same ejaculates subjected to laboratory assays was determined for each boar by multi-sire AI and defined as (i) the mean percentage of the litter sired and (ii) the mean number of piglets sired in each litter. Means of each laboratory evaluation were calculated for each boar and those values were applied to multiple linear regression analyses to determine which sperm traits could collectively estimate fertility in the simplest model. The regression model to predict the percent of litter sired by each boar was highly effective (p < 0.001, r(2) = 0.87) and included five traits; acrosome-compromised spermatozoa, percent live spermatozoa (0 and 60 min post-thaw), percent total motility, and the number of zona-bound spermatozoa. A second model to predict the number of piglets sired by boar was also effective (p < 0.05, r(2) = 0.57). These models indicate that the fertility of cryopreserved boar spermatozoa can be predicted effectively by including traditional and novel laboratory assays that consider functions of spermatozoa. © 2015 American Society of Andrology and European Academy of Andrology.

Artificial insemination of Holstein heifers with sex-sorted semen during the hot season in a subtropical region.

PubMed

Chang, Lian-Ben; Chou, Chih-Jen; Shiu, Jia-Shian; Tu, Po-An; Gao, Shi-Xuan; Peng, Shao-Yu; Wu, Shinn-Chih

2017-08-01

Our aim was to investigate insemination techniques in order to improve pregnancy rates of artificial insemination (AI) using sex-sorted semen (sexed AI) in cattle in tropical and subtropical (T/ST) regions. In T/ST regions, the pregnancy rates by sexed AI are reportedly the lowest in the hottest months of the year, with less than 15% in cows and 35-40% in heifers (PMID 24048822). We compared sexed AI by depositing the semen into the uterine body (UB-AI, n = 12) versus the unilateral uterine horn (UUH-AI, n = 14) of pre-ovulation heifers. The ovary and follicle were assessed by rectal ultrasound before AI. After insemination, pregnancy was determined by ultrasound at approximately 40 days and approximately 70 days. In the present study, we demonstrated that high pregnancy rates (>70%) by sexed AI in the hottest season in a subtropical region such as Taiwan can be achieved when heifers with pre-ovulation follicles are used. The overall pregnancy rates were 54% higher in the UUH-AI (71%) group than in the UB-AI (42%) group (P = 0.06), examined on approximately 40 days post-sexed AI. Surprisingly, however, the pregnancy outcome appeared to be higher in the hot season (62%) than in the cool season (46%) although this difference was not statistically significant. Based on the present study, we recommend that cattle breeders perform UUH-AI using sex-sorted semen for heifers with pre-ovulation follicles in order to achieve satisfactory pregnancy outcome in the hot seasons in T/ST regions.

Influence of temperament score and handling facility on stress, reproductive hormone concentrations, and fixed time AI pregnancy rates in beef heifers.

PubMed

Kasimanickam, R; Schroeder, S; Assay, M; Kasimanickam, V; Moore, D A; Gay, J M; Whittier, W D

2014-10-01

The objectives were (i) to evaluate the effect of temperament, determined by modified 2-point chute exit and gait score, on artificial insemination (AI) pregnancy rates in beef heifers following fixed time AI and (ii) to determine the effect of temperament on cortisol, substance-P, prolactin and progesterone at initiation of synchronization and at the time of AI. Angus beef heifers (n = 967) at eight locations were included in this study. At the initiation of synchronization (Day 0 = initiation of synchronization), all heifers received a body condition score (BCS), and temperament score (0 = calm; slow exit and walk or 1 = excitable; fast exit or jump or trot or run). Blood samples were collected from a sub-population of heifers (n = 86) at both synchronization initiation and the time of AI to determine the differences in serum progesterone, cortisol, prolactin and substance-P concentrations between temperament groups. Heifers were synchronized with 5-day CO-Synch+ controlled internal drug release (CIDR) protocol and were inseminated at 56 h after CIDR removal. Heifers were examined for pregnancy by ultrasound 70 days after AI to determine AI pregnancy. Controlling for synchronization treatment (p = 0.03), facility design (p = 0.05), and cattle handling facility design by temperament score interaction (p = 0.02), the AI pregnancy differed between heifers with excitable and calm temperament (51.9% vs 60.3%; p = 0.01). The alley-way with acute bends and turns, and long straight alley-way had lower AI pregnancy rate than did the semicircular alley-way (53.5%, 56.3% and 67.0% respectively; p = 0.05). The serum hormone concentrations differed significantly between different types of cattle handling facility (p < 0.05). The cattle handling facility design by temperament group interactions significantly influenced progesterone (p = 0.01), cortisol (p = 0.01), prolactin (p = 0.02) and substance-P (p = 0.04) both at the initiation of synchronization and at the time of AI. Inter- and intra-rater agreement for temperament scoring were moderate and good (Kappa = 0.596 ± 0.07 and 0.797 ± 0.11) respectively. The predictive value for calm and pregnant to AI was 0.87, and excited and non-pregnant to AI was 0.76. In conclusion, the modified 2-point temperament scoring method can be used to identify heifers with excitable temperament. Heifers with excitable temperament had lower AI pregnancy. Further, cattle handling facility design influenced the temperament and AI pregnancy. © 2014 Blackwell Verlag GmbH.

Diverter AI based decision aid, phases 1 and 2

NASA Technical Reports Server (NTRS)

Sexton, George A.; Bayles, Scott J.; Patterson, Robert W.; Schulke, Duane A.; Williams, Deborah C.

1989-01-01

It was determined that a system to incorporate artificial intelligence (AI) into airborne flight management computers is feasible. The AI functions that would be most useful to the pilot are to perform situational assessment, evaluate outside influences on the contemplated rerouting, perform flight planning/replanning, and perform maneuver planning. A study of the software architecture and software tools capable of demonstrating Diverter was also made. A skeletal planner known as the Knowledge Acquisition Development Tool (KADET), which is a combination script-based and rule-based system, was used to implement the system. A prototype system was developed which demonstrates advanced in-flight planning/replanning capabilities.

Role of Clavicle Chest Cage Angle Difference in Predicting Postoperative Shoulder Balance in Lenke 5C Adolescent Idiopathic Scoliosis Patients after Selective Posterior Fusion.

PubMed

Liu, Zhen; Hu, Zong-Shan; Qiu, Yong; Zhang, Zhen; Zhao, Zhi-Hui; Han, Xiao; Zhu, Ze-Zhang

2017-02-01

To evaluate the role of preoperative clavicle chest cage angle difference (CCAD) on postoperative radiographic shoulder imbalance, patient's satisfaction and surgeon's fulfillment in Lenke 5 adolescent idiopathic scoliosis (AIS). CCAD, as a novel radiographic parameter, has proven to be a reliable predictor for postoperative shoulder imbalance in Lenke 1 AIS patients. However, the value of CCAD in predicting shoulder balance has never been evaluated in Lenke 5 AIS patients. A total of 42 Lenke 5C AIS patients aged from 10 to 18 years old with a minimum 2-year follow-up were enrolled for evaluation. All patients underwent selective posterior spinal instrumentation and fusion using the all segmental pedicle screw technique by the same surgical team. The fusion levels were determined according to the Lenke criteria. Shoulder height difference (SHD) and CCAD were measured on anteroposterior (AP) standing radiographs. The patients' satisfaction and the surgeons' fulfillment were evaluated using a questionnaire. A receiver operative characteristic curve analysis was performed to explore the threshold values of preoperative CCAD in the prediction of the final follow-up radiographic shoulder imbalance, patients' satisfaction and surgeons' fulfillment. The average preoperative Cobb angle of the main curve was 46.8° ± 4.8°, and the average immediate postoperative Cobb angle was 13.3° ± 2.6°, representing an average surgical correction rate of 75.6% ± 8.5%. The average follow-up time was 29.2 months. At the last follow-up, the value of preoperative CCAD was significantly higher in patients with unbalanced shoulders (SHD ≥ 10 mm). At the final follow-up, 66.7% (28/42) of the patients were satisfied with their appearance, while 33.3% (14/42) of the patients were not satisfied with their appearance. At the final follow-up, 61.9% (26/42) of the surgeons were fulfilled with their operation, while 38.1% (16/42) of the surgeons were not. For patients' satisfaction and surgeons' fulfillment, the preoperative CCAD was significantly greater in patients with unsatisfied outcomes. Clavicle chest cage angle difference could be a reliable predictor for evaluating postoperative shoulder imbalance in AIS patients undergoing selective posterior fusion for Lenke 5C curves. A greater preoperative CCAD was significantly correlated with a postoperative radiographic imbalance of shoulders and dissatisfaction, which will guide spine surgeons in their preoperative planning and in the surgical management of AIS to reduce postoperative shoulder imbalance. © 2017 Chinese Orthopaedic Association and John Wiley & Sons Australia, Ltd.

A prospective study of children aged <16 years in motor vehicle collisions in Norway: severe injuries are observed predominantly in older children and are associated with restraint misuse.

PubMed

Skjerven-Martinsen, Marianne; Naess, Paal Aksel; Hansen, Trond Boye; Gaarder, Christine; Lereim, Inggard; Stray-Pedersen, Arne

2014-12-01

The implementation of the compulsory wearing of seat belts (SBs) for children and improvements in child restraint systems have reduced the number of deaths and severe injuries among children involved in motor vehicle (MV) collisions (MVCs). Establishing the characteristics predictive of such injuries may provide the basis for targeted safety campaigns and lead to a further reduction in mortality and morbidity among children involved in MVCs. This study performed a multidisciplinary investigation among child occupants involved in MVCs to elucidate injury mechanisms, evaluate the safety measures used and determine the characteristics that are predictive of injury. A prospective study was conducted of all child occupants aged <16 years involved in severe MVCs in south-eastern Norway during 2009-2013. The exterior and interior of the MVs were investigated and the injured children were medically examined. Supplementary information was obtained from witnesses, the crash victims, police reports, medical records and reconstructions. Each case was reviewed by a multidisciplinary team to assess the mechanism of injury. In total, 158 child occupants involved in 100 MVCs were investigated, of which 27 (17%) exhibited Abbreviated Injury Scale (AIS) scores of 2+ injuries and 15 (9%) exhibited AIS 3+ injuries. None of the children died. Of those with AIS 2+ injuries (n=27), 89% (n=24) were involved in frontal impact collisions and 11% (3/27) were involved in side impacts. Multivariate analysis revealed that restraint misuse, age, the prevailing lighting conditions and ΔV were all independently correlated with AIS 2+ injuries. Safety errors were found in 74% (20/27) of those with AIS 2+ injuries and 93% (14/15) of those with AIS 3+ injuries. The most common safety error was misuse of restraints, and in particular loose and/or improperly positioned SBs. The risk of injury among child occupants is significantly higher when the child occupants are exposed to safety errors within the interior of the vehicle. Future campaigns should focus on the prevention of restraint misuse and unsecured objects in the passenger compartment or boot. Copyright © 2014. Published by Elsevier Ltd.

Early pregnancy diagnosis on days 18 to 21 postinsemination using high-resolution imaging in lactating dairy cows.

PubMed

Scully, S; Butler, S T; Kelly, A K; Evans, A C O; Lonergan, P; Crowe, M A

2014-01-01

The aim was to assess the ability of corpus luteum (CL) and uterine ultrasound characteristics on d 18 to 21 to predict pregnancy status in lactating dairy cows. Ultrasound examinations were carried out on cows (n = 164) on d 18 to 21 following artificial insemination (AI). Images of the uterus and CL were captured using a Voluson i ultrasound device (General Electric Healthcare Systems, Vienna, Austria) equipped with a 12-MHz, multi frequency, linear array probe. Serum concentrations of progesterone were determined from blood samples collected at each ultrasound examination. Images of the CL were captured and stored for calculation of CL tissue area and echotexture. Images of the CL and associated blood flow area were captured and stored for analysis of luteal blood flow ratio. Longitudinal B-mode images of the uterine horns were stored for analysis of echotexture. Diagnosis of pregnancy was made at each ultrasound examination based on CL blood flow, CL size, and uterine echotexture. Pregnancy was confirmed by ultrasonography on d 30 after AI. The relationship between ultrasound measures and pregnancy outcome, as well as the accuracy of the pregnancy diagnosis made at each ultrasound examination was assessed. Progesterone concentrations and CL tissue area were greater in pregnant compared with nonpregnant cows on all days. The CL blood flow ratio was higher in pregnant compared with nonpregnant cows on d 20 and 21 after AI. Echotexture measures of the CL and uterus were not different between pregnant and nonpregnant cows on any day of examination. The best logistic regression model to predict pregnancy included scores for CL blood flow, CL size, and uterine echotexture on d 21 following AI. Accuracy of pregnancy diagnosis was highest on d 21, with sensitivity and specificity being 97.6 and 97.5%, respectively. Uterine echotexture scores were similar for pregnant and nonpregnant cows from d 18 to 20. On d 21, pregnant cows had higher uterine echotexture scores compared with nonpregnant cows. The logistic regression equation most likely to provide a correct pregnancy diagnosis in lactating dairy cows included the visual score for CL blood flow, CL size, and uterine echotexture on d 21 after AI. In support of this finding, the diagnostic accuracy for visual scores of CL blood flow, CL size, and uterine echotexture were also highest on d 21. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Experimental and AI-based numerical modeling of contaminant transport in porous media

NASA Astrophysics Data System (ADS)

Nourani, Vahid; Mousavi, Shahram; Sadikoglu, Fahreddin; Singh, Vijay P.

2017-10-01

This study developed a new hybrid artificial intelligence (AI)-meshless approach for modeling contaminant transport in porous media. The key innovation of the proposed approach is that both black box and physically-based models are combined for modeling contaminant transport. The effectiveness of the approach was evaluated using experimental and real world data. Artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) were calibrated to predict temporal contaminant concentrations (CCs), and the effect of noisy and de-noised data on the model performance was evaluated. Then, considering the predicted CCs at test points (TPs, in experimental study) and piezometers (in Myandoab plain) as interior conditions, the multiquadric radial basis function (MQ-RBF), as a meshless approach which solves partial differential equation (PDE) of contaminant transport in porous media, was employed to estimate the CC values at any point within the study area where there was no TP or piezometer. Optimal values of the dispersion coefficient in the advection-dispersion PDE and shape coefficient of MQ-RBF were determined using the imperialist competitive algorithm. In temporal contaminant transport modeling, de-noised data enhanced the performance of ANN and ANFIS methods in terms of the determination coefficient, up to 6 and 5%, respectively, in the experimental study and up to 39 and 18%, respectively, in the field study. Results showed that the efficiency of ANFIS-meshless model was more than ANN-meshless model up to 2 and 13% in the experimental and field studies, respectively.

Chloride in diet

MedlinePlus

... level based on scientific research evidence. Adequate Intake (AI): This level is established when there is not ... that is thought to ensure enough nutrition. Infants (AI) 0 to 6 months old: 0.18 grams ...

MANAGEMENT OF ENDOCRINE DISEASE: Fertility, pregnancy and lactation in women with adrenal insufficiency.

PubMed

Anand, Gurpreet; Beuschlein, Felix

2018-02-01

With the introduction of hormonal substitution therapy in the 1950s, adrenal insufficiency (AI) has been turned into a manageable disease in pregnant women. In fact, in the light of glucocorticoid replacement therapy and improved obstetric care, it is realistic to expect good maternal and fetal outcomes in patients with AI. However, there are still a number of challenges such as establishing the diagnosis of AI in pregnant women and optimizing the treatment of AI and related comorbidities prior to as well as during pregnancy. Clinical and biochemical diagnoses of a new-onset AI may be challenging because of overlapping symptoms of normal pregnancy as well as pregnancy-induced changes in cortisol values. Physiological changes occurring during pregnancy should be taken into account while adjusting the substitution therapy. The high proportion of reported adrenal crisis in pregnant women with AI highlights persistent problems in this particular clinical situation. Due to the rarity of the disease, there is no prospective data-guiding management of pregnancy in patients with known AI. The aim of this review is to summarize the maternal and fetal outcomes based on recently published case reports in patients with AI and to suggest a practical approach to diagnose and manage AI in pregnancy. © 2018 European Society of Endocrinology.

[T'ai chi in the elderly: practical aspects].

PubMed

Kressig, Reto W; Beauchet, Olivier; Tharicharu, Jai

2003-11-01

New approaches to health promotion for the growing geriatric population are needed. Low to moderately intense exercise programs, such as T'ai Chi seem particularly appropriate for older individuals because of many worthwhile physiological and psychological long-term benefits. T'ai Chi reduces falls and improves postural stability in older adults. It also has a positive impact on muscle strength and cardiovascular fitness and can improve mobility in patients with rheumatoid arthritis. It imparts a sense of well-being and confidence, and can reduce fear of falling in older adults. This article reviews the current medical literature regarding the multiple effects of T'ai Chi. Historical aspects of T'ai Chi and its current adaptation for practice by healthy older adults are presented. Finally, a set of modified exercises is proposed that is based on underlying principles of T'ai Chi and can be applied to patients with mild to moderate cognitive impairment.

Building Capacity to Increase Health Promotion Funding to American Indian Communities: Recommendations From Community Members.

PubMed

Pedersen, Maja; Held, Suzanne Christopher; Brown, Blakely

2016-11-01

Foundations and government agencies have historically played a critical role in supporting community-based health promotion programs. Increased access to health promotion funding may help address significant health issues existing within American Indian (AI) communities, such as childhood obesity, type 2 diabetes, and cardiovascular disease. Understanding the capacity of AI communities to successfully apply for and receive funding may serve to increase resources for health promotion efforts within AI communities in Montana. This exploratory qualitative study completed 17 semistructured interviews across three AI reservations in the state of Montana. Dimensions of community capacity within the context of the funding application process and partnership with funding agencies were identified, including resources, leadership, community need, networks, and relationship with the funding agency. Dimensions of AI community capacity were then used to suggest capacity-building strategies for improved partnership between AI communities in Montana and the funding agencies. © 2016 Society for Public Health Education.

Association between genetic determinants of peak height velocity during puberty and predisposition to adolescent idiopathic scoliosis.

PubMed

Mao, Saihu; Xu, Leilei; Zhu, Zezhang; Qian, Bangping; Qiao, Jun; Yi, Long; Qiu, Yong

2013-05-20

An association study to comprehensively clarify variations of genetic determinants of peak height velocity (PHV) during puberty in adolescent idiopathic scoliosis (AIS). To investigate whether the genetic determinants of timing and magnitude of PHV during puberty are associated with the susceptibility or curve progression of the female patients with AIS. An involvement of abnormal pubertal growth pattern in the etiopathogenesis of AIS has been implicated in previous studies. However, there is no clear consensus on the anthropometric variations of stature or growth rate. The recent advance in the longitudinally identified genetic determinants of PHV offers new opportunities to facilitate analysis of the association of pubertal growth with the susceptibility or curve severity of AIS. A gene-based association study was conducted using 9 single nucleotide polymorphisms (SNPs) in or near SOCS2, SF3B4/SV2A, C17orf67, CABLES1, DOT1L, CDK6, C6orf106, and LIN28B with confirmed association with PHV, peak growth age, or adult height. A total of 500 patients with AIS and 494 age-matched healthy controls were genotyped using the PCR-based Invader assay. Case-control study and case-only study were performed to define the contribution of the 9 SNPs to predisposition and curve severity of AIS. Strong associations between rs12459350 in DOT1L, rs4794665 in C17orf67, and susceptibility of AIS were found, with the PHV increasing allele G of rs12459350 and PHV/adult height increasing allele A of rs4794665 both being significant predisposition alleles of AIS (P = 0.001 for rs12459350, odds ratio = 1.16, 95% confidence interval = 1.06-1.27; P = 0.006 for rs4794665, odd ratio = 1.33, 95% confidence interval = 1.09-1.62). None of the genotyped SNPs was associated with curve severity in patients with AIS. Polymorphisms of the rs4794665 in C17orf67 and rs12459350 in DOT1L were associated with combined predisposition to AIS susceptibility and higher pubertal PHV, which strongly mirrored the anthropometric findings of taller pubertal stature and accelerated growth rate described in AIS.

Tangent function transformation of the Abbreviated Injury Scale improves accuracy and simplifies scoring.

PubMed

Wang, Muding; Qiu, Wusi; Qiu, Fang; Mo, Yinan; Fan, Wenhui

2015-03-16

The Injury Severity Score (ISS) and the New Injury Severity Score (NISS) are widely used for anatomic severity assessments after trauma. We present here the Tangent Injury Severity Score (TISS), which transforms the Abbreviated Injury Scale (AIS) as a predictor of mortality. The TISS is defined as the sum of the tangent function of AIS/6 to the power 3.04 multiplied by 18.67 of a patient's three most severe AIS injuries regardless of body regions. TISS values were calculated for every patient in two large independent data sets: 3,908 and 4,171 patients treated during a 6-year period at level-3 first-class comprehensive hospitals: the Affiliated Hospital of Hangzhou Normal University and Fengtian Hospital Affiliated to Shenyang Medical College, China. The power of TISS to predict mortality was compared with previously calculated NISS values for the same patients in each data set. The TISS is more predictive of survival than NISS (Hangzhou: receiver operating characteristic (ROC): NISS = 0.929, TISS = 0.949; p = 0.002; Shenyang: ROC: NISS = 0.924, TISS = 0.942; p = 0.008). Moreover, TISS provides a better fit throughout its entire range of prediction (Hosmer Lemeshow statistic for Hangzhou NISS = 29.71; p < 0.001, TISS = 19.59; p = 0.003; Hosmer Lemeshow statistic for Shenyang NISS = 33.49; p < 0.001, TISS = 21.19; p = 0.002). The TISS shows more accurate prediction of prognosis and a linear relation to mortality. The TISS might be a better injury scoring tool with simple computation.

Late L2ers can acquire grammatical features that do not occur in their L1: Evidence from the effect of animacy on verb agreement in L1 Chinese.

PubMed

Lempert, Henrietta

2016-05-01

Second language (L2) learners often have persistent difficulty with agreement between the number of the subject and the number of the verb. This study tested whether deviant L2 verb number agreement reflects maturational constraints on acquiring new grammatical features or resource limitations that impede access to the representations of L2 grammatical features. L1-Chinese undergraduate students at three age of arrival (AoA) levels were tested for online verb agreement accuracy by completing preambles in three animacy combinations: animate-inanimate [AI; e.g., The officer(s) from the station(s)], inanimate-animate [IA; e.g., The letters from the lawyer(s)], and inanimate-inanimate [II; e.g., The poster(s) from the museum(s)]. AI should be less costly to process than IA or II sequences, because animacy supports the subject in AI but competes with the subject for control of agreement in IA sequences, and is neutralized in II. Agreement accuracy was greater overall for AI than for IA or II, and although an AoA-related increase in erroneous agreement after plural subjects occurred for IA and II, there were no AoA effects for AI. Higher scores on memory tasks were associated with greater agreement accuracy, and the memory tasks significantly predicted variance in erroneous agreement when AoA was partialed out. The fact that even late learners can do verb agreement in the case of AI demonstrates that they can acquire new grammatical features. The greater difficulty with agreement in the case of IA or II than of AI, in conjunction with the results for the memory tasks, supports the resource limitation hypothesis.

Using palaeoclimate data to improve models of the Antarctic Ice Sheet

NASA Astrophysics Data System (ADS)

Phipps, Steven; King, Matt; Roberts, Jason; White, Duanne

2017-04-01

Ice sheet models are the most descriptive tools available to simulate the future evolution of the Antarctic Ice Sheet (AIS), including its contribution towards changes in global sea level. However, our knowledge of the dynamics of the coupled ice-ocean-lithosphere system is inevitably limited, in part due to a lack of observations. Furthemore, to build computationally efficient models that can be run for multiple millennia, it is necessary to use simplified descriptions of ice dynamics. Ice sheet modelling is therefore an inherently uncertain exercise. The past evolution of the AIS provides an opportunity to constrain the description of physical processes within ice sheet models and, therefore, to constrain our understanding of the role of the AIS in driving changes in global sea level. We use the Parallel Ice Sheet Model (PISM) to demonstrate how palaeoclimate data can improve our ability to predict the future evolution of the AIS. A 50-member perturbed-physics ensemble is generated, spanning uncertainty in the parameterisations of three key physical processes within the model: (i) the stress balance within the ice sheet, (ii) basal sliding and (iii) calving of ice shelves. A Latin hypercube approach is used to optimally sample the range of uncertainty in parameter values. This perturbed-physics ensemble is used to simulate the evolution of the AIS from the Last Glacial Maximum ( 21,000 years ago) to present. Palaeoclimate records are then used to determine which ensemble members are the most realistic. This allows us to use data on past climates to directly constrain our understanding of the past contribution of the AIS towards changes in global sea level. Critically, it also allows us to determine which ensemble members are likely to generate the most realistic projections of the future evolution of the AIS.

Using paleoclimate data to improve models of the Antarctic Ice Sheet

NASA Astrophysics Data System (ADS)

King, M. A.; Phipps, S. J.; Roberts, J. L.; White, D.

2016-12-01

Ice sheet models are the most descriptive tools available to simulate the future evolution of the Antarctic Ice Sheet (AIS), including its contribution towards changes in global sea level. However, our knowledge of the dynamics of the coupled ice-ocean-lithosphere system is inevitably limited, in part due to a lack of observations. Furthemore, to build computationally efficient models that can be run for multiple millennia, it is necessary to use simplified descriptions of ice dynamics. Ice sheet modeling is therefore an inherently uncertain exercise. The past evolution of the AIS provides an opportunity to constrain the description of physical processes within ice sheet models and, therefore, to constrain our understanding of the role of the AIS in driving changes in global sea level. We use the Parallel Ice Sheet Model (PISM) to demonstrate how paleoclimate data can improve our ability to predict the future evolution of the AIS. A large, perturbed-physics ensemble is generated, spanning uncertainty in the parameterizations of four key physical processes within ice sheet models: ice rheology, ice shelf calving, and the stress balances within ice sheets and ice shelves. A Latin hypercube approach is used to optimally sample the range of uncertainty in parameter values. This perturbed-physics ensemble is used to simulate the evolution of the AIS from the Last Glacial Maximum ( 21,000 years ago) to present. Paleoclimate records are then used to determine which ensemble members are the most realistic. This allows us to use data on past climates to directly constrain our understanding of the past contribution of the AIS towards changes in global sea level. Critically, it also allows us to determine which ensemble members are likely to generate the most realistic projections of the future evolution of the AIS.

Usefulness of the abbreviated injury score and the injury severity score in comparison to the Glasgow Coma Scale in predicting outcome after traumatic brain injury.

PubMed

Foreman, Brandon P; Caesar, R Ruth; Parks, Jennifer; Madden, Christopher; Gentilello, Larry M; Shafi, Shahid; Carlile, Mary C; Harper, Caryn R; Diaz-Arrastia, Ramon R

2007-04-01

Assessment of injury severity is important in the management of patients with brain trauma. We aimed to analyze the usefulness of the head abbreviated injury score (AIS), the injury severity score (ISS), and the Glasgow Coma Scale (GCS) as measures of injury severity and predictors of outcome after traumatic brain injury (TBI). Data were prospectively collected from 410 patients with TBI. AIS, ISS, and GCS were recorded at admission. Subjects' outcomes after TBI were measured using the Glasgow Outcome Scale (GOS-E) at 12 months postinjury. Uni- and multivariate analyses were performed. Outcome information was obtained from 270 patients (66%). ISS was the best predictor of GOS-E (rs = -0.341, p < 0.001), followed by GCS score (rs = 0.227, p < 0.001), and head AIS (rs = -0.222, p < 0.001). When considered in combination, GCS score and ISS modestly improved the correlation with GOS-E (R = 0.335, p < 0.001). The combination of GCS score and head AIS had a similar effect (R = 0.275, p < 0.001). Correlations were stronger from patients 8). GCS score, AIS, and ISS are weakly correlated with 12-month outcome. However, anatomic measures modestly outperform GCS as predictors of GOS-E. The combination of GCS and AIS/ISS correlate with outcome better than do any of the three measures alone. Results support the addition of anatomic measures such as AIS and ISS in clinical studies of TBI. Additionally, most of the variance in outcome is not accounted for by currently available measures of injury severity.

AI-2 quorum-sensing inhibitors affect the starvation response and reduce virulence in several Vibrio species, most likely by interfering with LuxPQ.

PubMed

Brackman, Gilles; Celen, Shari; Baruah, Kartik; Bossier, Peter; Van Calenbergh, Serge; Nelis, Hans J; Coenye, Tom

2009-12-01

The increase of disease outbreaks caused by Vibrio species in aquatic organisms as well as in humans, together with the emergence of antibiotic resistance in Vibrio species, has led to a growing interest in alternative disease control measures. Quorum sensing (QS) is a mechanism for regulating microbial gene expression in a cell density-dependent way. While there is good evidence for the involvement of auto-inducer 2 (AI-2)-based interspecies QS in the control of virulence in multiple Vibrio species, only few inhibitors of this system are known. From the screening of a small panel of nucleoside analogues for their ability to disturb AI-2-based QS, an adenosine derivative with a p-methoxyphenylpropionamide moiety at C-3' emerged as a promising hit. Its mechanism of inhibition was elucidated by measuring the effect on bioluminescence in a series of Vibrio harveyi AI-2 QS mutants. Our results indicate that this compound, as well as a truncated analogue lacking the adenine base, block AI-2-based QS without interfering with bacterial growth. The active compounds affected neither the bioluminescence system as such nor the production of AI-2, but most likely interfered with the signal transduction pathway at the level of LuxPQ in V. harveyi. The most active nucleoside analogue (designated LMC-21) was found to reduce the Vibrio species starvation response, to affect biofilm formation in Vibrio anguillarum, Vibrio vulnificus and Vibrio cholerae, to reduce pigment and protease production in V. anguillarum, and to protect gnotobiotic Artemia from V. harveyi-induced mortality.

Predicting Treatment Response to Intra-arterial Therapies for Hepatocellular Carcinoma with the Use of Supervised Machine Learning-An Artificial Intelligence Concept.

PubMed

Abajian, Aaron; Murali, Nikitha; Savic, Lynn Jeanette; Laage-Gaupp, Fabian Max; Nezami, Nariman; Duncan, James S; Schlachter, Todd; Lin, MingDe; Geschwind, Jean-François; Chapiro, Julius

2018-06-01

To use magnetic resonance (MR) imaging and clinical patient data to create an artificial intelligence (AI) framework for the prediction of therapeutic outcomes of transarterial chemoembolization by applying machine learning (ML) techniques. This study included 36 patients with hepatocellular carcinoma (HCC) treated with transarterial chemoembolization. The cohort (age 62 ± 8.9 years; 31 men; 13 white; 24 Eastern Cooperative Oncology Group performance status 0, 10 status 1, 2 status 2; 31 Child-Pugh stage A, 4 stage B, 1 stage C; 1 Barcelona Clinic Liver Cancer stage 0, 12 stage A, 10 stage B, 13 stage C; tumor size 5.2 ± 3.0 cm; number of tumors 2.6 ± 1.1; and 30 conventional transarterial chemoembolization, 6 with drug-eluting embolic agents). MR imaging was obtained before and 1 month after transarterial chemoembolization. Image-based tumor response to transarterial chemoembolization was assessed with the use of the 3D quantitative European Association for the Study of the Liver (qEASL) criterion. Clinical information, baseline imaging, and therapeutic features were used to train logistic regression (LR) and random forest (RF) models to predict patients as treatment responders or nonresponders under the qEASL response criterion. The performance of each model was validated using leave-one-out cross-validation. Both LR and RF models predicted transarterial chemoembolization treatment response with an overall accuracy of 78% (sensitivity 62.5%, specificity 82.1%, positive predictive value 50.0%, negative predictive value 88.5%). The strongest predictors of treatment response included a clinical variable (presence of cirrhosis) and an imaging variable (relative tumor signal intensity >27.0). Transarterial chemoembolization outcomes in patients with HCC may be predicted before procedures by combining clinical patient data and baseline MR imaging with the use of AI and ML techniques. Copyright © 2018 SIR. Published by Elsevier Inc. All rights reserved.

Intravenous Recombinant Tissue Plasminogen Activator and Ischemic Stroke: Focused Update of 2010 Clinical Practice Advisory From the American Academy of Emergency Medicine.

PubMed

Meurer, William J; Barth, Bradley; Abraham, Michael; Hoffman, Jerome R; Vilke, Gary M; DeMers, Gerard

2018-05-01

Stroke treatment is a continuum that begins with the rapid identification of symptoms and treatment with transition to successful rehabilitation. Therapies for acute ischemic stroke (AIS) may vary based on anatomic location, interval from symptom onset, and coexisting health conditions. Successful therapy requires a seamless systematic approach with coordination from prehospital environment through acute management at medical facilities to disposition and long-term care of the patient. The emergency physician must balance the benefits and risks of alteplase recombinant tissue plasminogen activator (rtPA) for AIS management. We review the recent medical literature on the topic of AIS and assess intravenous rtPA for the following questions: 1) is there any applicable, new, high-quality evidence that the benefits of intravenous rtPA are justified in light of the harms associated with it, and 2) if so, does the evidence clarify which patients, if any, are most likely to benefit from the treatment. A MEDLINE literature search from January 2010 to October 2016 and limited to human studies written in English for articles with keywords of cerebrovascular accident and (thromboly* OR alteplase). Guideline statements and nonsystematic reviews were excluded. Studies targeting differences between specific populations (males vs. females) were excluded. Studies identified then underwent a structured review from which results could be evaluated. Three hundred twenty-two papers on thrombolytic use were screened and nine appropriate articles were rigorously reviewed and recommendations given. No new studies published between 2010 and 2016 meaningfully reduced uncertainty regarding our understanding of the benefits and harms of intravenous rtPA for AIS. Discussions regarding benefit and harm should occur for patients, and risk prediction scores may facilitate the conversation. Published by Elsevier Inc.

Brainstem leukoaraiosis independently predicts poor outcome after ischemic stroke.

PubMed

Giralt-Steinhauer, E; Medrano, S; Soriano-Tárraga, C; Mola-Caminal, M; Rasal, R; Cuadrado-Godia, E; Rodríguez-Campello, A; Ois, A; Capellades, J; Jimenez-Conde, J; Roquer, J

2018-04-16

Increased supratentorial white matter hyperintensities volume (S-WMHV) has been reported to be a predictor of worse outcome in patients with acute ischemic stroke (AIS). However, few studies have focused on less common locations, such as brainstem white matter hyperintensities (B-WMH), and their relationship to S-WMHV. This study aimed to examine whether B-WMH affect clinical outcome after AIS or transient ischemic attack (TIA). Based on magnetic resonance imaging evidence, B-WMH were evaluated in 313 prospectively identified patients with AIS/TIA and registered as absent or present. Standardized S-WMHV was quantified using a validated volumetric image analysis and natural log-transformed (Log_S-WMHV). Poor outcome was defined as a modified Rankin Scale score of 3-6 at 3 months after the index event. Brainstem white matter hyperintensities were detected in 57 (18.2%) patients. In unadjusted analyses for outcome, the presence of B-WMH was associated with worse outcome, compared with patients without B-WMH (P = 0.034). In multivariate analysis controlling for age, atrial fibrillation, stroke severity, reperfusion therapies and Log_S-WMHV, only B-WMH [odds ratio (OR), 2.46; P = 0.021] and stroke severity (OR, 1.23; P < 0.001) remained independently associated with unfavourable 90-day modified Rankin Scale score. Patients with B-WMH were older (OR, 1.06; P < 0.001) and tended to have more hyperlipidaemia (OR, 2.21; P = 0.023) and peripheral arterial disease (OR, 2.57; P = 0.031). Brainstem white matter hyperintensities are an independent predictor of poor outcome after AIS/TIA and this relationship persists after adjustment for important prognostic factors. Our results also show that leukoaraiosis in this location identifies patients with a specific risk factor profile, suggesting differences in the underlying pathogenesis. © 2018 EAN.

Using computerised surface wound mapping to compare the potential medical effectiveness of Enhanced Protection Under Body Armour Combat Shirt collar designs.

PubMed

Breeze, John; Allanson-Bailey, L C; Hunt, N C; Delaney, R; Hepper, A E; Lewis, E A

2015-03-01

Protecting the neck from explosively propelled fragments has traditionally been achieved through a collar attached to the ballistic vest. An Enhanced Protection Under Body Armour Combat Shirt (EP-UBACS) collar has been identified as an additional method of providing neck protection but limited evidence as to its potential medical effectiveness exists to justify its procurement. Entry wound locations and resultant medical outcomes were determined using Abbreviated Injury Scale (AIS) for all fragmentation neck wounds sustained by UK soldiers between 01 January 2010 and 31 December 2011. Data were prospectively entered into a novel computerised tool base and comparisons made between three EP-UBACS neck collar designs in terms of predicted reduction in AIS scores. All collars reduced AIS scores, with the greatest reduction provided by designs incorporating increased standoff from the neck and an additional semi-circle of ballistic material underneath the collar at the front and back. This technique confirms that reinforcing the neck collar of an EP-UBACS would be expected to reduce injury severity from neck wounds. However, without knowledge of entry wound locations for injuries to other body areas as well as the use of AIS scores without clinical or pathological verification its further use in the future may be limited. The ability to overlay any armour design onto a standardised human was potentially the most useful part of this tool and we would recommend developing this technique using underlying anatomical structures and not just the skin surface. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Effect of audio instruction on tracking errors using a four-dimensional image-guided radiotherapy system.

PubMed

Nakamura, Mitsuhiro; Sawada, Akira; Mukumoto, Nobutaka; Takahashi, Kunio; Mizowaki, Takashi; Kokubo, Masaki; Hiraoka, Masahiro

2013-09-06

The Vero4DRT (MHI-TM2000) is capable of performing X-ray image-based tracking (X-ray Tracking) that directly tracks the target or fiducial markers under continuous kV X-ray imaging. Previously, we have shown that irregular respiratory patterns increased X-ray Tracking errors. Thus, we assumed that audio instruction, which generally improves the periodicity of respiration, should reduce tracking errors. The purpose of this study was to assess the effect of audio instruction on X-ray Tracking errors. Anterior-posterior abdominal skin-surface displacements obtained from ten lung cancer patients under free breathing and simple audio instruction were used as an alternative to tumor motion in the superior-inferior direction. First, a sequential predictive model based on the Levinson-Durbin algorithm was created to estimate the future three-dimensional (3D) target position under continuous kV X-ray imaging while moving a steel ball target of 9.5 mm in diameter. After creating the predictive model, the future 3D target position was sequentially calculated from the current and past 3D target positions based on the predictive model every 70 ms under continuous kV X-ray imaging. Simultaneously, the system controller of the Vero4DRT calculated the corresponding pan and tilt rotational angles of the gimbaled X-ray head, which then adjusted its orientation to the target. The calculated and current rotational angles of the gimbaled X-ray head were recorded every 5 ms. The target position measured by the laser displacement gauge was synchronously recorded every 10 msec. Total tracking system errors (ET) were compared between free breathing and audio instruction. Audio instruction significantly improved breathing regularity (p < 0.01). The mean ± standard deviation of the 95th percentile of ET (E95T ) was 1.7 ± 0.5 mm (range: 1.1-2.6mm) under free breathing (E95T,FB) and 1.9 ± 0.5 mm (range: 1.2-2.7 mm) under audio instruction (E95T,AI). E95T,AI was larger than E95T,FB for five patients; no significant difference was found between E95T,FB and E95T,AI (p = 0.21). Correlation analysis revealed that the rapid respiratory velocity significantly increased E95T. Although audio instruction improved breathing regularity, it also increased the respiratory velocity, which did not necessarily reduce tracking errors.

Effect of audio instruction on tracking errors using a four‐dimensional image‐guided radiotherapy system

PubMed Central

Sawada, Akira; Mukumoto, Nobutaka; Takahashi, Kunio; Mizowaki, Takashi; Kokubo, Masaki; Hiraoka, Masahiro

2013-01-01

The Vero4DRT (MHI‐TM2000) is capable of performing X‐ray image‐based tracking (X‐ray Tracking) that directly tracks the target or fiducial markers under continuous kV X‐ray imaging. Previously, we have shown that irregular respiratory patterns increased X‐ray Tracking errors. Thus, we assumed that audio instruction, which generally improves the periodicity of respiration, should reduce tracking errors. The purpose of this study was to assess the effect of audio instruction on X‐ray Tracking errors. Anterior‐posterior abdominal skin‐surface displacements obtained from ten lung cancer patients under free breathing and simple audio instruction were used as an alternative to tumor motion in the superior‐inferior direction. First, a sequential predictive model based on the Levinson‐Durbin algorithm was created to estimate the future three‐dimensional (3D) target position under continuous kV X‐ray imaging while moving a steel ball target of 9.5 mm in diameter. After creating the predictive model, the future 3D target position was sequentially calculated from the current and past 3D target positions based on the predictive model every 70 ms under continuous kV X‐ray imaging. Simultaneously, the system controller of the Vero4DRT calculated the corresponding pan and tilt rotational angles of the gimbaled X‐ray head, which then adjusted its orientation to the target. The calculated and current rotational angles of the gimbaled X‐ray head were recorded every 5 ms. The target position measured by the laser displacement gauge was synchronously recorded every 10 msec. Total tracking system errors (ET) were compared between free breathing and audio instruction. Audio instruction significantly improved breathing regularity (p < 0.01). The mean ± standard deviation of the 95th percentile of ET (E95T) was 1.7 ± 0.5 mm (range: 1.1–2.6 mm) under free breathing (E95T,FB) and 1.9 ± 0.5 mm (range: 1.2–2.7 mm) under audio instruction (E95T,AI). E95T,AI was larger than E95T,FB for five patients; no significant difference was found between E95T,FB and ET,AI95(p = 0.21). Correlation analysis revealed that the rapid respiratory velocity significantly increased E95T. Although audio instruction improved breathing regularity, it also increased the respiratory velocity, which did not necessarily reduce tracking errors. PACS number: 87.55.ne, 87.57.N‐, 87.59.C‐, PMID:24036880

Autonomously generating operations sequences for a Mars Rover using AI-based planning

NASA Technical Reports Server (NTRS)

Sherwood, Rob; Mishkin, Andrew; Estlin, Tara; Chien, Steve; Backes, Paul; Cooper, Brian; Maxwell, Scott; Rabideau, Gregg

2001-01-01

This paper discusses a proof-of-concept prototype for ground-based automatic generation of validated rover command sequences from highlevel science and engineering activities. This prototype is based on ASPEN, the Automated Scheduling and Planning Environment. This Artificial Intelligence (AI) based planning and scheduling system will automatically generate a command sequence that will execute within resource constraints and satisfy flight rules.

Functional specifications for AI software tools for electric power applications. Final report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Faught, W.S.

1985-08-01

The principle barrier to the introduction of artificial intelligence (AI) technology to the electric power industry has not been a lack of interest or appropriate problems, for the industry abounds in both. Like most others, however, the electric power industry lacks the personnel - knowledge engineers - with the special combination of training and skills AI programming demands. Conversely, very few AI specialists are conversant with electric power industry problems and applications. The recent availability of sophisticated AI programming environments is doing much to alleviate this shortage. These products provide a set of powerful and usable software tools that enablemore » even non-AI scientists to rapidly develop AI applications. The purpose of this project was to develop functional specifications for programming tools that, when integrated with existing general-purpose knowledge engineering tools, would expedite the production of AI applications for the electric power industry. Twelve potential applications, representative of major problem domains within the nuclear power industry, were analyzed in order to identify those tools that would be of greatest value in application development. Eight tools were specified, including facilities for power plant modeling, data base inquiry, simulation and machine-machine interface.« less

Cortical mechanisms for afterimage formation: evidence from interocular grouping

PubMed Central

Dong, Bo; Holm, Linus; Bao, Min

2017-01-01

Whether the retinal process alone or retinal and cortical processes jointly determine afterimage (AI) formation has long been debated. Based on the retinal rebound responses, recent work proposes that afterimage signals are exclusively generated in the retina, although later modified by cortical mechanisms. We tested this notion with the method of “indirect proof”. Each eye was presented with a 2-by-2 checkerboard of horizontal and vertical grating patches. Each corresponding patch of the two checkerboards was perpendicular to each other, which produces binocular rivalry, and can generate percepts ranging from complete interocular grouping to either monocular pattern. The monocular percepts became more frequent with higher contrast. Due to adaptation, the visual system is less sensitive during the AIs than during the inductions with AI-similar contrast. If the retina is the only origin of AIs, comparable contrast appearance would require stronger retinal signals in the AIs than in the inductions, thus leading to more frequent monocular percepts in the AIs than in the inductions. Surprisingly, subjects saw the fully coherent stripes significantly more often in AIs. Our results thus contradict the retinal generation notion, and suggest that in addition to the retina, cortex is directly involved in the generation of AI signals. PMID:28112230

Risk of head-and-neck cancer following a diagnosis of severe cervical intraepithelial neoplasia: a nationwide population-based cohort study in Denmark.

PubMed

Svahn, M F; Munk, C; Jensen, S M; von Buchwald, C; Frederiksen, K; Kjaer, S K

2016-07-01

Women with a history of cervical intraepithelial neoplasia grade 3 including adenocarcinoma in situ (CIN3/AIS) may be more prone to develop cancers of the ano-genital region and head-and-neck cancers. The current literature is, however, limited. We established a nationwide cohort of approximately 2,500,000 Danish women born in 1918-1990. By linking the cohort to population-based health registries, we obtained information on CIN3/AIS, cancer, migration, death, education, and smoking. Cox proportional hazards models were used to estimate hazard ratios (HRs) and confidence intervals (CIs) for the association between CIN3/AIS and risk of head-and-neck squamous cell carcinoma (HNSCC). HRs were presented for any HNSCC and for four subgroups categorized by their anticipated degree of association with human papillomavirus (HPV). A history of CIN3/AIS was significantly associated with an increased overall relative risk of HNSCC after adjustment for year of birth, attained age, and length of education. The risk was especially high for sites anticipated to be strongly associated with HPV (e.g. base of tongue, tonsils) (HR, 2.49; 95% CI, 1.84-3.36). Lower risks were found for sites anticipated to be not or weakly associated with HPV (e.g. nasal cavity, middle ear, sinuses) (HR, 1.29; 95% CI, 0.61-2.76). Women with a history of CIN3/AIS have a significantly higher risk of HNSCC than women without such a history. The increased relative risk persisted for at least 20years after the CIN3/AIS diagnosis. Women with CIN3/AIS may be more susceptible to the consequences of HPV and/or may have higher risk behavior, such as smoking. Copyright © 2016 Elsevier Inc. All rights reserved.

Design of integrated ship monitoring system using SAR, RADAR, and AIS

NASA Astrophysics Data System (ADS)

Yang, Chan-Su; Kim, Tae-Ho; Hong, Danbee; Ahn, Hyung-Wook

2013-06-01

When we talk about for the ship detection, identification and its classification, we need to go for the wide area of monitoring and it may be possible only through satellite based monitoring approach which monitors and covers coastal as well as the oceanic zone. Synthetic aperture radar (SAR) has been widely used to detect targets of interest with the advantage of the operating capability in all weather and luminance free condition (Margarit and Tabasco, 2011). In EU waters, EMSA(European Maritime Safety Agency) is operating the SafeSeaNet and CleanSeaNet systems which provide the current positions of all ships and oil spill monitoring information in and around EU waters in a single picture to Member States using AIS, LRIT and SAR images. In many countries, a similar system has been developed and the key of the matter is to integrate all available data. This abstract describes the preliminary design concept for an integration system of RADAR, AIS and SAR data for vessel traffic monitoring. SAR sensors are used to acquire image data over large coverage area either through the space borne or airborne platforms in UTC. AIS reports should be also obtained on the same date as of the SAR acquisition for the purpose to perform integration test. Land-based RADAR can provide ships positions detected and tracked in near real time. In general, SAR are used to acquire image data over large coverage area, AIS reports are obtained from ship based transmitter, and RADAR can monitor continuously ships for a limited area. In this study, we developed individual ship monitoring algorithms using RADAR(FMCW and Pulse X-band), AIS and SAR(RADARSAT-2 Full-pol Mode). We conducted field experiments two times for displaying the RADAR, AIS and SAR integration over the Pyeongtaek Port, South Korea.

Accretion in Radiative Equipartition (AiRE) Disks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yazdi, Yasaman K.; Afshordi, Niayesh, E-mail: yyazdi@pitp.ca, E-mail: nafshordi@pitp.ca

2017-07-01

Standard accretion disk theory predicts that the total pressure in disks at typical (sub-)Eddington accretion rates becomes radiation pressure dominated. However, radiation pressure dominated disks are thermally unstable. Since these disks are observed in approximate steady state over the instability timescale, our accretion models in the radiation-pressure-dominated regime (i.e., inner disk) need to be modified. Here, we present a modification to the Shakura and Sunyaev model, where the radiation pressure is in equipartition with the gas pressure in the inner region. We call these flows accretion in radiative equipartition (AiRE) disks. We introduce the basic features of AiRE disks andmore » show how they modify disk properties such as the Toomre parameter and the central temperature. We then show that the accretion rate of AiRE disks is limited from above and below, by Toomre and nodal sonic point instabilities, respectively. The former leads to a strict upper limit on the mass of supermassive black holes as a function of cosmic time (and spin), while the latter could explain the transition between hard and soft states of X-ray binaries.« less

A functional relation for field-scale nonaqueous phase liquid dissolution developed using a pore network model

USGS Publications Warehouse

Dillard, L.A.; Essaid, H.I.; Blunt, M.J.

2001-01-01

A pore network model with cubic chambers and rectangular tubes was used to estimate the nonaqueous phase liquid (NAPL) dissolution rate coefficient, Kdissai, and NAPL/water total specific interfacial area, ai. Kdissai was computed as a function of modified Peclet number (Pe???) for various NAPL saturations (SN) and ai during drainage and imbibition and during dissolution without displacement. The largest contributor to ai was the interfacial area in the water-filled corners of chambers and tubes containing NAPL. When Kdissai was divided by ai, the resulting curves of dissolution coefficient, Kdiss versus Pe??? suggested that an approximate value of Kdiss could be obtained as a weak function of hysteresis or SN. Spatially and temporally variable maps of Kdissai calculated using the network model were used in field-scale simulations of NAPL dissolution. These simulations were compared to simulations using a constant value of Kdissai and the empirical correlation of Powers et al. [Water Resour. Res. 30(2) (1994b) 321]. Overall, a methodology was developed for incorporating pore-scale processes into field-scale prediction of NAPL dissolution. Copyright ?? 2001 .

Accretion in Radiative Equipartition (AiRE) Disks

NASA Astrophysics Data System (ADS)

Yazdi, Yasaman K.; Afshordi, Niayesh

2017-07-01

Standard accretion disk theory predicts that the total pressure in disks at typical (sub-)Eddington accretion rates becomes radiation pressure dominated. However, radiation pressure dominated disks are thermally unstable. Since these disks are observed in approximate steady state over the instability timescale, our accretion models in the radiation-pressure-dominated regime (I.e., inner disk) need to be modified. Here, we present a modification to the Shakura & Sunyaev model, where the radiation pressure is in equipartition with the gas pressure in the inner region. We call these flows accretion in radiative equipartition (AiRE) disks. We introduce the basic features of AiRE disks and show how they modify disk properties such as the Toomre parameter and the central temperature. We then show that the accretion rate of AiRE disks is limited from above and below, by Toomre and nodal sonic point instabilities, respectively. The former leads to a strict upper limit on the mass of supermassive black holes as a function of cosmic time (and spin), while the latter could explain the transition between hard and soft states of X-ray binaries.

Decoding the Charitable Brain: Empathy, Perspective Taking, and Attention Shifts Differentially Predict Altruistic Giving.

PubMed

Tusche, Anita; Böckler, Anne; Kanske, Philipp; Trautwein, Fynn-Mathis; Singer, Tania

2016-04-27

Altruistic behavior varies considerably across people and decision contexts. The relevant computational and motivational mechanisms that underlie its heterogeneity, however, are poorly understood. Using a charitable giving task together with multivariate decoding techniques, we identified three distinct psychological mechanisms underlying altruistic decision-making (empathy, perspective taking, and attentional reorienting) and linked them to dissociable neural computations. Neural responses in the anterior insula (AI) (but not temporoparietal junction [TPJ]) encoded trial-wise empathy for beneficiaries, whereas the TPJ (but not AI) predicted the degree of perspective taking. Importantly, the relative influence of both socio-cognitive processes differed across individuals: participants whose donation behavior was heavily influenced by affective empathy exhibited higher predictive accuracies for generosity in AI, whereas those who strongly relied on cognitive perspective taking showed improved predictions of generous donations in TPJ. Furthermore, subject-specific contributions of both processes for donations were reflected in participants' empathy and perspective taking responses in a separate fMRI task (EmpaToM), suggesting that process-specific inputs into altruistic choices may reflect participants' general propensity to either empathize or mentalize. Finally, using independent attention task data, we identified shared neural codes for attentional reorienting and generous donations in the posterior superior temporal sulcus, suggesting that domain-general attention shifts also contribute to generous behavior (but not in TPJ or AI). Overall, our findings demonstrate highly specific roles of AI for affective empathy and TPJ for cognitive perspective taking as precursors of prosocial behavior and suggest that these discrete routes of social cognition differentially drive intraindividual and interindividual differences in altruistic behavior. Human societies depend on the altruistic behavior of their members, but teasing apart its underlying motivations and neural mechanisms poses a serious challenge. Using multivariate decoding techniques, we delineated three distinct processes for altruistic decision-making (affective empathy, cognitive perspective taking, and domain-general attention shifts), linked them to dissociable neural computations, and identified their relative influence across individuals. Distinguishing process-specific computations both behaviorally and neurally is crucial for developing complete theoretical and neuroscientific accounts of altruistic behavior and more effective means of increasing it. Moreover, information on the relative influence of subprocesses across individuals and its link to people's more general propensity to engage empathy or perspective taking can inform training programs to increase prosociality, considering their "fit" with different individuals. Copyright © 2016 the authors 0270-6474/16/364719-14$15.00/0.

Characterization of the apolipoprotein AI and CIII genes in the domestic pig

DOE Office of Scientific and Technical Information (OSTI.GOV)

Birchbauer, A.; Knipping, G.; Juritsch, B.

1993-03-01

The apolipoproteins (apo) AI and CIII are important constituents of triglyceride-rich lipoproteins and high-density lipoproteins. In humans, apo AI is believed to play an important protective role in the pathogenesis of arteriosclerosis, whereas apo CIII might be involved in the development of hypertriglyceridemia. Both human genes are located within a gene cluster on chromosome 11. Although the domestic pig has been widely used as an animal model in arteriosclerosis and lipid research, the porcine apolipoproteins genes are poorly characterized. In this report, the complete nucleotide sequences of the porcine apo AI and CIII genes are presented and the authors demonstrate,more » for the first time, apo CIII expression in the pig. Both genes are composed of four exons and three introns and resemble closely their human counterparts with regard to the transcriptional start sites, exon sizes, intron sizes, exon-intron borders, and the size of the intergenic region. The predicted pig apo AI is a protein of 241 amino acids, which is 2 amino acids shorter than human apo AI. The protein sequence was found to be very homologous to apo AI sequences in other mammalian species. Apo AI expression was detected on the mRNA level in porcine liver and intestine. The apo CIII gene encodes a protein with 73 amino acids, which is 6 amino acids shorter than human apo CIII. In contrast to the three isoforms of apo CIII found in humans, only one major isoform was detected in the pig. Presumably this isoform is unglycosylated. In addition to apo CIII expression in the liver and the intestine, a truncated form of apo CIII mRNA was also found in porcine kidney. The studies demonstrate the presence of an apo CIII gene, an apo CIII mRNA, and an apo CIII protein in the pig and, therefore, exclude a hypothesized apo CIII deficiency in these animals. 53 refs., 5 figs.« less

A method to identify the areas at risk for the introduction of avian influenza virus into poultry flocks through direct contact with wild ducks.

PubMed

Galletti, G; Santi, A; Guberti, V; Paternoster, G; Licata, E; Loli Piccolomini, L; Procopio, A; Tamba, M

2018-02-22

Wild dabbling ducks are the main reservoir for avian influenza (AI) viruses and pose an ongoing threat to commercial poultry flocks. Combining the (i) size of that population, (ii) their flight distances and (iii) their AI prevalence, the density of AI-infected dabbling ducks (DID) was calculated as a risk factor for the introduction of AI viruses into poultry holdings of Emilia-Romagna region, Northern Italy. Data on 747 poultry holdings and on 39 AI primary outbreaks notified in Emilia-Romagna between 2000 and 2017 were used to validate that risk factor. A multivariable Bayesian logistic regression was performed to assess whether DID could be associated with the occurrence of AI primary outbreaks. DID value, being an outdoor flock, hobby poultry trading, species reared, length of cycle and flock size were used as explanatory variables. Being an outdoor poultry flock was significantly associated with a higher risk of AI outbreak occurrence. The probability of DID to be a risk factor for AI virus introduction was estimated to be 90%. A DID cut-off of 0.23 was identified to define high-risk areas for AI virus introduction. Using this value, the high-risk area covers 43% of the region. Seventy-four per cent of the primary AI outbreaks have occurred in that area, containing 39% of the regional poultry holdings. Poultry holdings located in areas with a high DID value should be included in a risk-based surveillance programme aimed at AI early detection. © 2018 Blackwell Verlag GmbH.

ApoA-I/A-II-HDL positively associates with apoB-lipoproteins as a potential atherogenic indicator.

PubMed

Kido, Toshimi; Kondo, Kazuo; Kurata, Hideaki; Fujiwara, Yoko; Urata, Takeyoshi; Itakura, Hiroshige; Yokoyama, Shinji

2017-11-29

We recently reported distinct nature of high-density lipoproteins (HDL) subgroup particles with apolipoprotein (apo) A-I but not apoA-II (LpAI) and HDL having both (LpAI:AII) based on the data from 314 Japanese. While plasma HDL level almost exclusively depends on concentration of LpAI having 3 to 4 apoA-I molecules, LpAI:AII appeared with almost constant concentration regardless of plasma HDL levels having stable structure with two apoA-I and one disulfide-dimeric apoA-II molecules (Sci. Rep. 6; 31,532, 2016). The aim of this study is further characterization of LpAI:AII with respect to its role in atherogenesis. Association of LpAI, LpAI:AII and other HDL parameters with apoB-lipoprotein parameters was analyzed among the cohort data above. ApoA-I in LpAI negatively correlated with the apoB-lipoprotein parameters such as apoB, triglyceride, nonHDL-cholesterol, and nonHDL-cholesterol + triglyceride, which are apparently reflected in the relations of the total HDL parameters to apoB-lipoproteins. In contrast, apoA-I in LpAI:AII and apoA-II positively correlated to the apoB-lipoprotein parameters even within their small range of variation. These relationships are independent of sex, but may slightly be influenced by the activity-related CETP mutations. The study suggested that LpAI:AII is an atherogenic indicator rather than antiatherogenic. These sub-fractions of HDL are to be evaluated separately for estimating atherogenic risk of the patients.

Prediction of blast-induced air overpressure: a hybrid AI-based predictive model.

PubMed

Jahed Armaghani, Danial; Hajihassani, Mohsen; Marto, Aminaton; Shirani Faradonbeh, Roohollah; Mohamad, Edy Tonnizam

2015-11-01

Blast operations in the vicinity of residential areas usually produce significant environmental problems which may cause severe damage to the nearby areas. Blast-induced air overpressure (AOp) is one of the most important environmental impacts of blast operations which needs to be predicted to minimize the potential risk of damage. This paper presents an artificial neural network (ANN) optimized by the imperialist competitive algorithm (ICA) for the prediction of AOp induced by quarry blasting. For this purpose, 95 blasting operations were precisely monitored in a granite quarry site in Malaysia and AOp values were recorded in each operation. Furthermore, the most influential parameters on AOp, including the maximum charge per delay and the distance between the blast-face and monitoring point, were measured and used to train the ICA-ANN model. Based on the generalized predictor equation and considering the measured data from the granite quarry site, a new empirical equation was developed to predict AOp. For comparison purposes, conventional ANN models were developed and compared with the ICA-ANN results. The results demonstrated that the proposed ICA-ANN model is able to predict blast-induced AOp more accurately than other presented techniques.

Expected net present value of pure and mixed sexed semen artificial insemination strategies in dairy heifers.

PubMed

Olynk, N J; Wolf, C A

2007-05-01

Sexed semen has been a long-anticipated tool for dairy farmers to obtain more heifer calves, but challenges exist for integrating sexed semen into commercial dairy farm reproduction programs. The decreased conception rates (CR) experienced with sexed semen make virgin heifers better suited for insemination with sexed semen than lactating dairy cows. This research sought to identify when various sexed semen breeding strategies provided higher expected net present value (NPV) than conventional artificial insemination (AI) breeding schemes, indicating which breeding scheme is advisable under various scenarios. Budgets were developed to calculate the expected NPV of various AI breeding strategies incorporating conventional (non-sexed) and sexed semen. In the base budgets, heifer and bull calf values were held constant at $500 and $110, respectively. The percentage of heifers expected to be born after breeding with conventional and sexed semen used was 49.2 and 90%, respectively. Breeding costs per AI were held constant at $15.00 per AI for conventional semen and $45.00 per AI for sexed semen of approximately the same genetic value. Conventional semen CR of 58 and 65% were used, and an AI submission rate was set at 100%. Breeding strategies with sexed semen were assessed for breakeven heifer calf values and sexed semen costs to obtain a NPV equal to that achieved with conventional semen. Breakeven heifer calf values for pure sexed semen strategies with a constant 58 and 65% base CR in which sexed semen achieved 53% of the base CR are $732.11 and $664.26, respectively. Breakeven sexed semen costs per AI of $17.16 and $22.39, compared with $45.00 per AI, were obtained to obtain a NPV equal to that obtained with pure conventional semen for base CR of 58 and 65%, respectively. The strategy employing purely sexed semen, with base CR of both 58 and 65%, yielded a lower NPV than purely conventional semen in all but the best-case scenario in which sexed semen provides 90% of the CR of conventional semen. Other potential advantages of sexed semen that were not quantified in the scenarios include biosecurity-related concerns, decreased dystocia due to increased numbers of heifer calves, and implications for internal herd growth.

Computational methods for efficient structural reliability and reliability sensitivity analysis

NASA Technical Reports Server (NTRS)

Wu, Y.-T.

1993-01-01

This paper presents recent developments in efficient structural reliability analysis methods. The paper proposes an efficient, adaptive importance sampling (AIS) method that can be used to compute reliability and reliability sensitivities. The AIS approach uses a sampling density that is proportional to the joint PDF of the random variables. Starting from an initial approximate failure domain, sampling proceeds adaptively and incrementally with the goal of reaching a sampling domain that is slightly greater than the failure domain to minimize over-sampling in the safe region. Several reliability sensitivity coefficients are proposed that can be computed directly and easily from the above AIS-based failure points. These probability sensitivities can be used for identifying key random variables and for adjusting design to achieve reliability-based objectives. The proposed AIS methodology is demonstrated using a turbine blade reliability analysis problem.

Creation of metal-independent hyperthermophilic L-arabinose isomerase by homologous recombination.

PubMed

Hong, Young-Ho; Lee, Dong-Woo; Pyun, Yu-Ryang; Lee, Sung Haeng

2011-12-28

Hyperthermophilic L-arabinose isomerases (AIs) are useful in the commercial production of D-tagatose as a low-calorie bulk sweetener. Their catalysis and thermostability are highly dependent on metals, which is a major drawback in food applications. To study the role of metal ions in the thermostability and catalysis of hyperthermophilic AI, four enzyme chimeras were generated by PCR-based hybridization to replace the variable N- and C-terminal regions of hyperthermophilic Thermotoga maritima AI (TMAI) and thermophilic Geobacillus stearothermophilus AI (GSAI) with those of the homologous mesophilic Bacillus halodurans AI (BHAI). Unlike Mn(2+)-dependent TMAI, the GSAI- and TMAI-based hybrids with the 72 C-terminal residues of BHAI were not metal-dependent for catalytic activity. By contrast, the catalytic activities of the TMAI- and GSAI-based hybrids containing the N-terminus (residues 1-89) of BHAI were significantly enhanced by metals, but their thermostabilities were poor even in the presence of Mn(2+), indicating that the effects of metals on catalysis and thermostability involve different structural regions. Moreover, in contrast to the C-terminal truncate (Δ20 residues) of GSAI, the N-terminal truncate (Δ7 residues) exhibited no activity due to loss of its native structure. The data thus strongly suggest that the metal dependence of the catalysis and thermostability of hyperthermophilic AIs evolved separately to optimize their activity and thermostability at elevated temperatures. This may provide effective target regions for engineering, thereby meeting industrial demands for the production of d-tagatose.

A rapid prototyping facility for flight research in advanced systems concepts

NASA Technical Reports Server (NTRS)

Duke, Eugene L.; Brumbaugh, Randal W.; Disbrow, James D.

1989-01-01

The Dryden Flight Research Facility of the NASA Ames Research Facility of the NASA Ames Research Center is developing a rapid prototyping facility for flight research in flight systems concepts that are based on artificial intelligence (AI). The facility will include real-time high-fidelity aircraft simulators, conventional and symbolic processors, and a high-performance research aircraft specially modified to accept commands from the ground-based AI computers. This facility is being developed as part of the NASA-DARPA automated wingman program. This document discusses the need for flight research and for a national flight research facility for the rapid prototyping of AI-based avionics systems and the NASA response to those needs.

Artificial Intelligence in Autonomous Telescopes

NASA Astrophysics Data System (ADS)

Mahoney, William; Thanjavur, Karun

2011-03-01

Artificial Intelligence (AI) is key to the natural evolution of today's automated telescopes to fully autonomous systems. Based on its rapid development over the past five decades, AI offers numerous, well-tested techniques for knowledge based decision making essential for real-time telescope monitoring and control, with minimal - and eventually no - human intervention. We present three applications of AI developed at CFHT for monitoring instantaneous sky conditions, assessing quality of imaging data, and a prototype for scheduling observations in real-time. Closely complementing the current remote operations at CFHT, we foresee further development of these methods and full integration in the near future.

Neural signatures of social conformity: A coordinate-based activation likelihood estimation meta-analysis of functional brain imaging studies.

PubMed

Wu, Haiyan; Luo, Yi; Feng, Chunliang

2016-12-01

People often align their behaviors with group opinions, known as social conformity. Many neuroscience studies have explored the neuropsychological mechanisms underlying social conformity. Here we employed a coordinate-based meta-analysis on neuroimaging studies of social conformity with the purpose to reveal the convergence of the underlying neural architecture. We identified a convergence of reported activation foci in regions associated with normative decision-making, including ventral striatum (VS), dorsal posterior medial frontal cortex (dorsal pMFC), and anterior insula (AI). Specifically, consistent deactivation of VS and activation of dorsal pMFC and AI are identified when people's responses deviate from group opinions. In addition, the deviation-related responses in dorsal pMFC predict people's conforming behavioral adjustments. These are consistent with current models that disagreement with others might evoke "error" signals, cognitive imbalance, and/or aversive feelings, which are plausibly detected in these brain regions as control signals to facilitate subsequent conforming behaviors. Finally, group opinions result in altered neural correlates of valuation, manifested as stronger responses of VS to stimuli endorsed than disliked by others. Copyright © 2016 Elsevier Ltd. All rights reserved.

Subtyping pathological gamblers based on impulsivity, depression, and anxiety.

PubMed

Ledgerwood, David M; Petry, Nancy M

2010-12-01

This study examined putative subtypes of pathological gamblers (PGs) based on the Pathways model, and it also evaluated whether the subtypes would benefit differentially from treatment. Treatment-seeking PGs (N = 229) were categorized into Pathways subtypes based on scores from questionnaires assessing anxiety, depression, and impulsivity. The Addiction Severity Index-Gambling assessed severity of gambling problems at baseline, posttreatment, and 12-month follow-up. Compared with behaviorally conditioned (BC) gamblers, emotionally vulnerable (EV) gamblers had higher psychiatric and gambling severity, and were more likely to have a parent with a psychiatric history. Antisocial impulsive (AI) gamblers also had elevated gambling and psychiatric severity relative to BC gamblers. They were more likely to have antisocial personality disorder and had the highest legal and family/social severity scores. They were also most likely to have a history of substance abuse treatment, history of inpatient psychiatric treatment, and a parent with a substance use or gambling problem. AI and EV gamblers experienced greater gambling severity throughout treatment than BC gamblers, but all three subtypes demonstrated similar patterns of treatment response. Thus, the three Pathways subtypes differ on some baseline characteristics, but subtyping did not predict treatment outcomes beyond a simple association with problem gambling severity. (PsycINFO Database Record (c) 2010 APA, all rights reserved).

Issues in management of artificial intelligence based projects

NASA Technical Reports Server (NTRS)

Kiss, P. A.; Freeman, Michael S.

1988-01-01

Now that Artificial Intelligence (AI) is gaining acceptance, it is important to examine some of the obstacles that still stand in the way of its progress. Ironically, many of these obstacles are related to management and are aggravated by the very characteristcs that make AI useful. The purpose of this paper is to heighten awareness of management issues in AI development and to focus attention on their resolution.

Automatic Publication of a MIS Product to GeoNetwork: Case of the AIS Indexer

DTIC Science & Technology

2012-11-01

installation and configuration The following instructions are for installing and configuring the software packages Java 1.6 and MySQL 5.5 which are...An Automatic Identification System (AIS) reception indexer Java application was developed in the summer of 2011, based on the work of Lapinski and...release; distribution unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT An Automatic Identification System (AIS) reception indexer Java application was

Computer algorithms and applications used to assist the evaluation and treatment of adolescent idiopathic scoliosis: a review of published articles 2000-2009.

PubMed

Phan, Philippe; Mezghani, Neila; Aubin, Carl-Éric; de Guise, Jacques A; Labelle, Hubert

2011-07-01

Adolescent idiopathic scoliosis (AIS) is a complex spinal deformity whose assessment and treatment present many challenges. Computer applications have been developed to assist clinicians. A literature review on computer applications used in AIS evaluation and treatment has been undertaken. The algorithms used, their accuracy and clinical usability were analyzed. Computer applications have been used to create new classifications for AIS based on 2D and 3D features, assess scoliosis severity or risk of progression and assist bracing and surgical treatment. It was found that classification accuracy could be improved using computer algorithms that AIS patient follow-up and screening could be done using surface topography thereby limiting radiation and that bracing and surgical treatment could be optimized using simulations. Yet few computer applications are routinely used in clinics. With the development of 3D imaging and databases, huge amounts of clinical and geometrical data need to be taken into consideration when researching and managing AIS. Computer applications based on advanced algorithms will be able to handle tasks that could otherwise not be done which can possibly improve AIS patients' management. Clinically oriented applications and evidence that they can improve current care will be required for their integration in the clinical setting.

2-aminoimidazoles potentiate ß-lactam antimicrobial activity against Mycobacterium tuberculosis by reducing ß-lactamase secretion and increasing cell envelope permeability

PubMed Central

Obregón-Henao, Andrés; Ackart, David F.; Podell, Brendan K.; Belardinelli, Juan M.; Jackson, Mary; Nguyen, Tuan V.; Blackledge, Meghan S.; Melander, Roberta J.; Melander, Christian; Johnson, Benjamin K.; Abramovitch, Robert B.

2017-01-01

There is an urgent need to develop new drug treatment strategies to control the global spread of drug-sensitive and multidrug-resistant Mycobacterium tuberculosis (M. tuberculosis). The ß-lactam class of antibiotics is among the safest and most widely prescribed antibiotics, but they are not effective against M. tuberculosis due to intrinsic resistance. This study shows that 2-aminoimidazole (2-AI)-based small molecules potentiate ß-lactam antibiotics against M. tuberculosis. Active 2-AI compounds significantly reduced the minimal inhibitory and bactericidal concentrations of ß-lactams by increasing M. tuberculosis cell envelope permeability and decreasing protein secretion including ß-lactamase. Metabolic labeling and transcriptional profiling experiments revealed that 2-AI compounds impair mycolic acid biosynthesis, export and linkage to the mycobacterial envelope, counteracting an important defense mechanism reducing permeability to external agents. Additionally, other important constituents of the M. tuberculosis outer membrane including sulfolipid-1 and polyacyltrehalose were also less abundant in 2-AI treated bacilli. As a consequence of 2-AI treatment, M. tuberculosis displayed increased sensitivity to SDS, increased permeability to nucleic acid staining dyes, and rapid binding of cell wall targeting antibiotics. Transcriptional profiling analysis further confirmed that 2-AI induces transcriptional regulators associated with cell envelope stress. 2-AI based small molecules potentiate the antimicrobial activity of ß-lactams by a mechanism that is distinct from specific inhibitors of ß-lactamase activity and therefore may have value as an adjunctive anti-TB treatment. PMID:28749949

Mapping Fishing Effort through AIS Data

PubMed Central

Natale, Fabrizio; Gibin, Maurizio; Alessandrini, Alfredo; Vespe, Michele; Paulrud, Anton

2015-01-01

Several research initiatives have been undertaken to map fishing effort at high spatial resolution using the Vessel Monitoring System (VMS). An alternative to the VMS is represented by the Automatic Identification System (AIS), which in the EU became compulsory in May 2014 for all fishing vessels of length above 15 meters. The aim of this paper is to assess the uptake of the AIS in the EU fishing fleet and the feasibility of producing a map of fishing effort with high spatial and temporal resolution at European scale. After analysing a large AIS dataset for the period January-August 2014 and covering most of the EU waters, we show that AIS was adopted by around 75% of EU fishing vessels above 15 meters of length. Using the Swedish fleet as a case study, we developed a method to identify fishing activity based on the analysis of individual vessels’ speed profiles and produce a high resolution map of fishing effort based on AIS data. The method was validated using detailed logbook data and proved to be sufficiently accurate and computationally efficient to identify fishing grounds and effort in the case of trawlers, which represent the largest portion of the EU fishing fleet above 15 meters of length. Issues still to be addressed before extending the exercise to the entire EU fleet are the assessment of coverage levels of the AIS data for all EU waters and the identification of fishing activity in the case of vessels other than trawlers. PMID:26098430

Mapping Fishing Effort through AIS Data.

PubMed

Natale, Fabrizio; Gibin, Maurizio; Alessandrini, Alfredo; Vespe, Michele; Paulrud, Anton

2015-01-01

Several research initiatives have been undertaken to map fishing effort at high spatial resolution using the Vessel Monitoring System (VMS). An alternative to the VMS is represented by the Automatic Identification System (AIS), which in the EU became compulsory in May 2014 for all fishing vessels of length above 15 meters. The aim of this paper is to assess the uptake of the AIS in the EU fishing fleet and the feasibility of producing a map of fishing effort with high spatial and temporal resolution at European scale. After analysing a large AIS dataset for the period January-August 2014 and covering most of the EU waters, we show that AIS was adopted by around 75% of EU fishing vessels above 15 meters of length. Using the Swedish fleet as a case study, we developed a method to identify fishing activity based on the analysis of individual vessels' speed profiles and produce a high resolution map of fishing effort based on AIS data. The method was validated using detailed logbook data and proved to be sufficiently accurate and computationally efficient to identify fishing grounds and effort in the case of trawlers, which represent the largest portion of the EU fishing fleet above 15 meters of length. Issues still to be addressed before extending the exercise to the entire EU fleet are the assessment of coverage levels of the AIS data for all EU waters and the identification of fishing activity in the case of vessels other than trawlers.

Evaluation of an expert system for fault detection, isolation, and recovery in the manned maneuvering unit

NASA Technical Reports Server (NTRS)

Rushby, John; Crow, Judith

1990-01-01

The authors explore issues in the specification, verification, and validation of artificial intelligence (AI) based software, using a prototype fault detection, isolation and recovery (FDIR) system for the Manned Maneuvering Unit (MMU). They use this system as a vehicle for exploring issues in the semantics of C-Language Integrated Production System (CLIPS)-style rule-based languages, the verification of properties relating to safety and reliability, and the static and dynamic analysis of knowledge based systems. This analysis reveals errors and shortcomings in the MMU FDIR system and raises a number of issues concerning software engineering in CLIPs. The authors came to realize that the MMU FDIR system does not conform to conventional definitions of AI software, despite the fact that it was intended and indeed presented as an AI system. The authors discuss this apparent disparity and related questions such as the role of AI techniques in space and aircraft operations and the suitability of CLIPS for critical applications.

The AI Bus architecture for distributed knowledge-based systems

NASA Technical Reports Server (NTRS)

Schultz, Roger D.; Stobie, Iain

1991-01-01

The AI Bus architecture is layered, distributed object oriented framework developed to support the requirements of advanced technology programs for an order of magnitude improvement in software costs. The consequent need for highly autonomous computer systems, adaptable to new technology advances over a long lifespan, led to the design of an open architecture and toolbox for building large scale, robust, production quality systems. The AI Bus accommodates a mix of knowledge based and conventional components, running on heterogeneous, distributed real world and testbed environment. The concepts and design is described of the AI Bus architecture and its current implementation status as a Unix C++ library or reusable objects. Each high level semiautonomous agent process consists of a number of knowledge sources together with interagent communication mechanisms based on shared blackboards and message passing acquaintances. Standard interfaces and protocols are followed for combining and validating subsystems. Dynamic probes or demons provide an event driven means for providing active objects with shared access to resources, and each other, while not violating their security.

Organizational Climate and Emotional Intelligence: An Appreciative Inquiry into a "Leaderful" Community College

ERIC Educational Resources Information Center

Yoder, Debra Marie

2005-01-01

In an era of unprecedented challenges and rapid change, community colleges need effective leadership that brings out the best in people, organizations, and communities. This qualitative study was based on interpretive research using appreciative inquiry (AI). AI is based on social constructivist theory and is a collaborative and highly…

Urban Indian Voices: A Community-Based Participatory Research Health and Needs Assessment

ERIC Educational Resources Information Center

Johnson, Chad V.; Bartgis, Jami; Worley, Jody A.; Hellman, Chan M.; Burkhart, Russell

2010-01-01

This community-based participatory research (CBPR) project utilized a mixed-methods survey design to identify urban (Tulsa, OK) American Indian (AI) strengths and needs. Six hundred fifty AIs (550 adults and 100 youth) were surveyed regarding their attitudes and beliefs about their community. These results were used in conjunction with other…

IDENTIFYING SEXUAL HEALTH PROTECTIVE FACTORS AMONG NORTHERN PLAINS AMERICAN INDIAN YOUTH: AN ECOLOGICAL APPROACH UTILIZING MULTIPLE PERSPECTIVES

PubMed Central

Griese, Emily R.; Kenyon, DenYelle Baete; McMahon, Tracey R.

2017-01-01

This study examined aspects of the sociocultural context in which American Indian (AI) teen pregnancy occurs, focusing specifically on protective factors for Northern Plains AI youth. Principles of community-based participatory research guided the qualitative data collection from 185 community members (focus groups with AI youth, youth parents, and elders; interviews with health care providers and school personnel) from a reservation and an urban community. Results indicated three protective systems impacted the sexual health and behaviors of AI youth: school, family, and enculturation. These findings provide a better understanding of how specific protective factors within these systems may buffer AI youth from involvement in risky sexual behaviors and work to inform culturally relevant prevention and intervention efforts. PMID:27536896

Moving Forward: Breaking the Cycle of Mistrust Between American Indians and Researchers

PubMed Central

Daley, Sean M.; Brown, Travis; Filippi, Melissa; Greiner, K. Allen; Daley, Christine M.

2013-01-01

American Indians (AIs) have some of the poorest documented health outcomes of any racial/ethnic group. Research plays a vital role in addressing these health disparities. Historical and recent instances of unethical research, specifically the Havasupai diabetes project, have generated mistrust in AI communities. To address the concerns about unethical research held by some AIs in the Heartland (Midwest), the Center for American Indian Community Health (CAICH) has launched a series of efforts to inform AIs about research participants’ rights. CAICH educates health researchers about the importance of learning and respecting a community’s history, culture, values, and wishes when engaging in research with that community. Through community-based participatory research, CAICH is also empowering AIs to assert their rights as research participants. PMID:24134368

Internally directed cognition and mindfulness: an integrative perspective derived from predictive and reactive control systems theory

PubMed Central

Tops, Mattie; Boksem, Maarten A. S.; Quirin, Markus; IJzerman, Hans; Koole, Sander L.

2013-01-01

In the present paper, we will apply the predictive and reactive control systems (PARCS) theory as a framework that integrates competing theories of neural substrates of awareness by describing the “default mode network” (DMN) and anterior insula (AI) as parts of two different behavioral and homeostatic control systems. The DMN, a network that becomes active at rest when there is no external stimulation or task to perform, has been implicated in self-reflective awareness and prospection. By contrast, the AI is associated with awareness and task-related attention. This has led to competing theories stressing the role of the DMN in self-awareness vs. the role of interoceptive and emotional information integration in the AI in awareness of the emotional moment. In PARCS, the respective functions of the DMN and AI in a specific control system explains their association with different qualities of awareness, and how mental states can shift from one state (e.g., prospective self-reflection) to the other (e.g., awareness of the emotional moment) depending on the relative dominance of control systems. These shifts between reactive and predictive control are part of processes that enable the intake of novel information, integration of this novel information within existing knowledge structures, and the creation of a continuous personal context in which novel information can be integrated and understood. As such, PARCS can explain key characteristics of mental states, such as their temporal and spatial focus (e.g., a focus on the here and now vs. the future; a first person vs. a third person perspective). PARCS further relates mental states to brain states and functions, such as activation of the DMN or hemispheric asymmetry in frontal cortical functions. Together, PARCS deepens the understanding of a broad range of mental states, including mindfulness, mind wandering, rumination, autobiographical memory, imagery, and the experience of self. PMID:24904455

Sleep disturbance as a proximal predictor of suicidal intent in recently hospitalized attempters.

PubMed

Ferentinos, Panagiotis; Porichi, Evgenia; Christodoulou, Christos; Dikeos, Dimitris; Papageorgiou, Charalambos; Douzenis, Athanassios

2016-03-01

Insomnia and short self-reported sleep duration are associated with suicidality, adjusting for concurrent depression. Yet, it is unknown whether they correlate with attempters' suicidal intent and the lethality of suicidal acts. This cross-sectional study in hospitalized suicide attempters aimed to investigate whether temporally proximal self-reported sleep disturbance predicts suicidal intent or exerts mediatory effects. Attempters were retrospectively assessed for insomnia severity (Athens Insomnia Scale [AIS]) and average night sleep duration (ANSD) for 2 weeks preceding attempt. The effects of insomnia or ANSD on suicidal intent (Beck's Suicide Intent Scale [BSIS]) were explored in multiple regressions. Mediatory effects were investigated in structural equation models (SEMs). A total of 127 adults (59.8% females) were interviewed within two weeks post-suicide attempt. Major psychiatric diagnoses included affective, psychotic, and alcohol-related disorders. Of the participants, 38.6% had current major depression (MDE). A total of 62.2% reported insomnia (AIS ≥ 6); 42.5% reported short ANSD (≤5 hours). BSIS was predicted by AIS (p = 0.034), short ANSD (p = 0.015), or insomnia with short ANSD (p = 0.006). In SEMs, indirect effects of current MDE, affective disorder, and alcohol-related disorder diagnoses on BSIS via AIS tested significant; both AIS and short ANSD partially mediated the effect of age on BSIS. Insomnia, short ANSD, and, in particular, insomnia with short ANSD proximally predicted suicidal intent in recent attempters. The effects of current depression and affective and alcohol-related disorder diagnoses on suicidal intent were partially mediated by insomnia; both insomnia and short ANSD partially mediated the effect of age on suicidal intent. Therefore, management of sleep disturbance in at-risk subjects is important, as it may reduce unfavorable outcomes of suicidal acts. Copyright © 2015 Elsevier B.V. All rights reserved.

Artificial Intelligence-Based Semantic Internet of Things in a User-Centric Smart City

PubMed Central

Guo, Kun; Lu, Yueming; Gao, Hui; Cao, Ruohan

2018-01-01

Smart city (SC) technologies can provide appropriate services according to citizens’ demands. One of the key enablers in a SC is the Internet of Things (IoT) technology, which enables a massive number of devices to connect with each other. However, these devices usually come from different manufacturers with different product standards, which confront interactive control problems. Moreover, these devices will produce large amounts of data, and efficiently analyzing these data for intelligent services. In this paper, we propose a novel artificial intelligence-based semantic IoT (AI-SIoT) hybrid service architecture to integrate heterogeneous IoT devices to support intelligent services. In particular, the proposed architecture is empowered by semantic and AI technologies, which enable flexible connections among heterogeneous devices. The AI technology can support very implement efficient data analysis and make accurate decisions on service provisions in various kinds. Furthermore, we also present several practical use cases of the proposed AI-SIoT architecture and the opportunities and challenges to implement the proposed AI-SIoT for future SCs are also discussed. PMID:29701679

Artificial Intelligence-Based Semantic Internet of Things in a User-Centric Smart City.

PubMed

Guo, Kun; Lu, Yueming; Gao, Hui; Cao, Ruohan

2018-04-26

Smart city (SC) technologies can provide appropriate services according to citizens’ demands. One of the key enablers in a SC is the Internet of Things (IoT) technology, which enables a massive number of devices to connect with each other. However, these devices usually come from different manufacturers with different product standards, which confront interactive control problems. Moreover, these devices will produce large amounts of data, and efficiently analyzing these data for intelligent services. In this paper, we propose a novel artificial intelligence-based semantic IoT (AI-SIoT) hybrid service architecture to integrate heterogeneous IoT devices to support intelligent services. In particular, the proposed architecture is empowered by semantic and AI technologies, which enable flexible connections among heterogeneous devices. The AI technology can support very implement efficient data analysis and make accurate decisions on service provisions in various kinds. Furthermore, we also present several practical use cases of the proposed AI-SIoT architecture and the opportunities and challenges to implement the proposed AI-SIoT for future SCs are also discussed.

Evaluation of criteria for optimal time AI postulated by estrous signs in lactating dairy cows kept in tie-stalls

PubMed Central

SUMIYOSHI, Toshiaki; ENDO, Natsumi; TANAKA, Tomomi; KAMOMAE, Hideo

2017-01-01

Relaxation of the intravaginal part of the uterus is obvious around 6 to 18 h before ovulation, and this is considered the optimal time for artificial insemination (AI), as demonstrated in recent studies. Estrous signs have been suggested as useful criteria for determining the optimal time for AI. Therefore, this study evaluated the usefulness of estrous signs, particularly the relaxation of the intravaginal part of the uterus, as criteria for determining the optimal time for AI. A Total of 100 lactating Holstein-Friesian cows kept in tie-stall barns were investigated. AI was carried out based on the criterion for the optimal time for AI (optimal group), and earlier (early group) and later (late group) than the optimal time for AI, determined on the basis of estrous signs. After AI, ovulation was assessed by rectal palpation and ultrasonographic observation at 6-h intervals. For 87.5% (35/40) of cows in the optimal group, AI was carried out 24-6 h before ovulation, which was previously accepted as the optimal time for AI. AI was carried out earlier (early group) and later (late group) than optimal time for AI in 62.1% (18/29) and 71.0% (22/31) of cows, respectively. The conception rate for the optimal group was 60.0%, and this conception rate was higher than that for the early group (44.8%) and late group (32.2%), without significance. Further, the conception rate of the optimal group was significantly higher than the sum of the conception rates of the early and late groups (38.3%; 23/60) (P < 0.05). These results indicate that the criteria postulated, relaxation of the intravaginal part of the uterus and other estrous signs are useful in determining the optimal time for AI. Furthermore, these estrous signs enable the estimations of stages in the periovulatory period. PMID:29081451

Anomalous yield reduction in direct-drive DT implosions due to 3He addition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Herrmann, Hans W; Langenbrunner, James R; Mack, Joseph M

2008-01-01

Glass capsules were imploded in direct drive on the OMEGA laser [T. R. Boehly et aI., Opt. Commun. 133, 495, 1997] to look for anomalous degradation in deuterium/tritium (DT) yield (i.e., beyond what is predicted) and changes in reaction history with {sup 3}He addition. Such anomalies have previously been reported for D/{sup 3}He plasmas, but had not yet been investigated for DT/{sup 3}He. Anomalies such as these provide fertile ground for furthering our physics understanding of ICF implosions and capsule performance. A relatively short laser pulse (600 ps) was used to provide some degree of temporal separation between shock andmore » compression yield components for analysis. Anomalous degradation in the compression component of yield was observed, consistent with the 'factor of two' degradation previously reported by MIT at a 50% {sup 3}He atom fraction in D{sub 2} using plastic capsules [Rygg et aI., Phys. Plasmas 13, 052702 (2006)]. However, clean calculations (i.e., no fuel-shell mixing) predict the shock component of yield quite well, contrary to the result reported by MIT, but consistent with LANL results in D{sub 2}/{sup 3}He [Wilson, et aI., lml Phys: Conf Series 112, 022015 (2008)]. X-ray imaging suggests less-than-predicted compression ofcapsules containing {sup 3}He. Leading candidate explanations are poorly understood Equation-of-State (EOS) for gas mixtures, and unanticipated particle pressure variation with increasing {sup 3}He addition.« less

Supporting Accomplished Facilitation: Examining the Use of Sppreciative Inquiry to Inform the Development of Learning Resources for Medical Educators

ERIC Educational Resources Information Center

McIntosh, Paul; Freeth, Della; Berridge, Emma Jane

2013-01-01

This paper examines the use of appreciative inquiry (AI) to guide development of web-based learning resources for medical educators who facilitate simulation-based learning experiences for doctors-in-training. AI can be viewed as a positive form of action research, which seeks to avoid deficit-based analyses and solutions, and commonly associated…

Critical Shoulder Angle and Acromial Index Do Not Influence 24-Month Functional Outcome After Arthroscopic Rotator Cuff Repair.

PubMed

Lee, Merrill; Chen, Jerry Yongqian; Liow, Ming Han Lincoln; Chong, Hwei Chi; Chang, Paul; Lie, Denny

2017-11-01

Recent studies have shown a correlation between scapular geometry and the development of atraumatic rotator cuff tears. However, a paucity of literature is available on the effects of critical shoulder angle (CSA) and acromial index (AI) on functional outcomes after arthroscopic rotator cuff repair. Hypothesis/Purpose: The purpose was to investigate the influence of CSA and AI on 24-month functional outcomes after arthroscopic rotator cuff repair. The hypothesis was that a larger CSA or AI would result in poorer postoperative outcomes. Cohort study; Level of evidence, 3. The study included 147 patients who underwent arthroscopic double-row rotator cuff repair for radiologically documented full-thickness supraspinatus tears. An independent reviewer measured the CSA and AI on preoperative radiographs. These patients were prospectively enrolled and were evaluated preoperatively as well as at 3, 6, 12, and 24 months postoperatively. Functional outcome was assessed with the Constant Shoulder Score (CSS), Oxford Shoulder Score (OSS), and University of California at Los Angeles (UCLA) Shoulder Rating Scale. The patients were first divided based on CSA: (1) ≤35° (control CSA) and (2) >35° (increased CSA); and then based on AI: (1) ≤0.7 and (2) >0.7. The Student unpaired t test, Pearson chi-square test, and Pearson correlation were performed to examine the influence of CSA and AI on postoperative functional outcome scores. At 6 months of follow-up, the CSS, OSS, and UCLA Shoulder Rating Scale were 10 ± 1, 4 ± 2, and 3 ± 1 points poorer in the increased CSA group compared with the control CSA group ( P = .005, P = .030, and P = .035, respectively). These scores were not significantly different between both AI groups. By 24 months of follow-up, all outcome scores were comparable between both CSA groups as well as between both AI groups. No significant correlation was found between either CSA or AI when compared with CSS, OSS, or UCLA Shoulder Rating Scale at 24 months of follow-up. CSA and AI do not appear to influence 24-month functional outcomes postoperatively and hence are not contraindications to arthroscopic rotator cuff repair.

Epilepsy after perinatal stroke with different vascular subtypes.

PubMed

Laugesaar, Rael; Vaher, Ulvi; Lõo, Silva; Kolk, Anneli; Männamaa, Mairi; Talvik, Inga; Õiglane-Shlik, Eve; Loorits, Dagmar; Talvik, Tiina; Ilves, Pilvi

2018-06-01

With an incidence up to 63 per 100,000 live births, perinatal stroke is an important cause of childhood epilepsy. The aim of the study was to find the prevalence of and predictive factors for epilepsy, and to describe the course of epilepsy in children with perinatal stroke with different vascular subtypes. Patients were retrieved from the Estonian Paediatric Stroke Database with follow-up time at least 24 months. Patients were divided into 5 perinatal stroke syndromes: neonatal arterial ischemic stroke (AIS), neonatal hemorrhagic stroke, neonatal cerebral sinovenous thrombosis, presumed AIS, and presumed periventricular venous infarction. The final study group included 73 children with perinatal stroke (39 boys). With a median follow-up time of 8.6 years, epilepsy was diagnosed in 21/73 (29%) children, most of whom had AIS (17/21, 81%). The 18-year cumulative poststroke epilepsy risk according to the Kaplan-Meier estimator was 40.8% (95% confidence interval [CI] 20.7-55.9%). The median age at epilepsy diagnosis was 50 months (range 1 month to 18.4 years). Children with neonatal AIS had the highest risk of epilepsy, but children with presumed AIS more often had severe epilepsy syndromes. Cortical lesions (odds ratio [OR] 19.7, 95% CI 2.9-133), and involvement of thalamus (OR 9.8, 95% CI 1.8-53.5) and temporal lobe (OR 8.3, 95% CI 1.8-39.6) were independently associated with poststroke epilepsy. The risk for poststroke epilepsy after perinatal stroke depends on the vascular subtype. Patients with perinatal AIS need close follow-up to detect epilepsy and start with antiepileptic treatment on time.

Prevalence of avian influenza virus in wild birds before and after the HPAI H5N8 outbreak in 2014 in South Korea.

PubMed

Shin, Jeong-Hwa; Woo, Chanjin; Wang, Seung-Jun; Jeong, Jipseol; An, In-Jung; Hwang, Jong-Kyung; Jo, Seong-Deok; Yu, Seung Do; Choi, Kyunghee; Chung, Hyen-Mi; Suh, Jae-Hwa; Kim, Seol-Hee

2015-07-01

Since 2003, highly pathogenic avian influenza (HPAI) virus outbreaks have occurred five times in Korea, with four HPAI H5N1 outbreaks and one HPAI H5N8 outbreak. Migratory birds have been suggested to be the first source of HPAI in Korea. Here, we surveyed migratory wild birds for the presence of AI and compared regional AI prevalence in wild birds from September 2012 to April 2014 for birds having migratory pathways in South Korea. Finally, we investigated the prevalence of AI in migratory birds before and after HPAI H5N8 outbreaks. Overall, we captured 1617 migratory wild birds, while 18,817 feces samples and 74 dead birds were collected from major wild bird habitats. A total of 21 HPAI viruses were isolated from dead birds, and 86 low pathogenic AI (LPAI) viruses were isolated from captured birds and from feces samples. Spatiotemporal distribution analysis revealed that AI viruses were spread southward until December, but tended to shift north after January, consistent with the movement of migratory birds in South Korea. Furthermore, we found that LPAI virus prevalences within wild birds were notably higher in 2013-2014 than the previous prevalence during the northward migration season. The data from our study demonstrate the importance of the surveillance of AI in wild birds. Future studies including in-depth genetic analysis in combination with evaluation of the movement and ecology of migratory birds might help us to bridge the gaps in our knowledge and better explain, predict, and ultimately prevent future HPAI outbreaks.

Temporal and spatial variabilities of Antarctic ice mass changes inferred by GRACE in a Bayesian framework

NASA Astrophysics Data System (ADS)

Wang, L.; Davis, J. L.; Tamisiea, M. E.

2017-12-01

The Antarctic ice sheet (AIS) holds about 60% of all fresh water on the Earth, an amount equivalent to about 58 m of sea-level rise. Observation of AIS mass change is thus essential in determining and predicting its contribution to sea level. While the ice mass loss estimates for West Antarctica (WA) and the Antarctic Peninsula (AP) are in good agreement, what the mass balance over East Antarctica (EA) is, and whether or not it compensates for the mass loss is under debate. Besides the different error sources and sensitivities of different measurement types, complex spatial and temporal variabilities would be another factor complicating the accurate estimation of the AIS mass balance. Therefore, a model that allows for variabilities in both melting rate and seasonal signals would seem appropriate in the estimation of present-day AIS melting. We present a stochastic filter technique, which enables the Bayesian separation of the systematic stripe noise and mass signal in decade-length GRACE monthly gravity series, and allows the estimation of time-variable seasonal and inter-annual components in the signals. One of the primary advantages of this Bayesian method is that it yields statistically rigorous uncertainty estimates reflecting the inherent spatial resolution of the data. By applying the stochastic filter to the decade-long GRACE observations, we present the temporal variabilities of the AIS mass balance at basin scale, particularly over East Antarctica, and decipher the EA mass variations in the past decade, and their role in affecting overall AIS mass balance and sea level.

Smartphone-Based Fluorescent Diagnostic System for Highly Pathogenic H5N1 Viruses.

PubMed

Yeo, Seon-Ju; Choi, Kyunghan; Cuc, Bui Thi; Hong, Nguyen Ngoc; Bao, Duong Tuan; Ngoc, Nguyen Minh; Le, Mai Quynh; Hang, Nguyen Le Khanh; Thach, Nguyen Co; Mallik, Shyam Kumar; Kim, Hak Sung; Chong, Chom-Kyu; Choi, Hak Soo; Sung, Haan Woo; Yu, Kyoungsik; Park, Hyun

2016-01-01

Field diagnostic tools for avian influenza (AI) are indispensable for the prevention and controlled management of highly pathogenic AI-related diseases. More accurate, faster and networked on-site monitoring is demanded to detect such AI viruses with high sensitivity as well as to maintain up-to-date information about their geographical transmission. In this work, we assessed the clinical and field-level performance of a smartphone-based fluorescent diagnostic device with an efficient reflective light collection module using a coumarin-derived dendrimer-based fluorescent lateral flow immunoassay. By application of an optimized bioconjugate, a smartphone-based diagnostic device had a two-fold higher detectability as compared to that of the table-top fluorescence strip reader for three different AI subtypes (H5N3, H7N1, and H9N2). Additionally, in a clinical study of H5N1-confirmed patients, the smartphone-based diagnostic device showed a sensitivity of 96.55% (28/29) [95% confidence interval (CI): 82.24 to 99.91] and a specificity of 98.55% (68/69) (95% CI: 92.19 to 99.96). The measurement results from the distributed individual smartphones were wirelessly transmitted via short messaging service and collected by a centralized database system for further information processing and data mining. Smartphone-based diagnosis provided highly sensitive measurement results for H5N1 detection within 15 minutes. Because of its high sensitivity, portability and automatic reporting feature, the proposed device will enable agile identification of patients and efficient control of AI dissemination.

Smartphone-Based Fluorescent Diagnostic System for Highly Pathogenic H5N1 Viruses

PubMed Central

Yeo, Seon-Ju; Choi, Kyunghan; Cuc, Bui Thi; Hong, Nguyen Ngoc; Bao, Duong Tuan; Ngoc, Nguyen Minh; Le, Mai Quynh; Hang, Nguyen Le Khanh; Thach, Nguyen Co; Mallik, Shyam Kumar; Kim, Hak Sung; Chong, Chom-Kyu; Choi, Hak Soo; Sung, Haan Woo; Yu, Kyoungsik; Park, Hyun

2016-01-01

Field diagnostic tools for avian influenza (AI) are indispensable for the prevention and controlled management of highly pathogenic AI-related diseases. More accurate, faster and networked on-site monitoring is demanded to detect such AI viruses with high sensitivity as well as to maintain up-to-date information about their geographical transmission. In this work, we assessed the clinical and field-level performance of a smartphone-based fluorescent diagnostic device with an efficient reflective light collection module using a coumarin-derived dendrimer-based fluorescent lateral flow immunoassay. By application of an optimized bioconjugate, a smartphone-based diagnostic device had a two-fold higher detectability as compared to that of the table-top fluorescence strip reader for three different AI subtypes (H5N3, H7N1, and H9N2). Additionally, in a clinical study of H5N1-confirmed patients, the smartphone-based diagnostic device showed a sensitivity of 96.55% (28/29) [95% confidence interval (CI): 82.24 to 99.91] and a specificity of 98.55% (68/69) (95% CI: 92.19 to 99.96). The measurement results from the distributed individual smartphones were wirelessly transmitted via short messaging service and collected by a centralized database system for further information processing and data mining. Smartphone-based diagnosis provided highly sensitive measurement results for H5N1 detection within 15 minutes. Because of its high sensitivity, portability and automatic reporting feature, the proposed device will enable agile identification of patients and efficient control of AI dissemination. PMID:26877781

HER2 status predicts for upfront AI benefit: A TRANS-AIOG meta-analysis of 12,129 patients from ATAC, BIG 1-98 and TEAM with centrally determined HER2.

PubMed

Bartlett, John M S; Ahmed, Ikhlaaq; Regan, Meredith M; Sestak, Ivana; Mallon, Elizabeth A; Dell'Orto, Patrizia; Thürlimann, Beat; Seynaeve, Caroline; Putter, Hein; Van de Velde, Cornelis J H; Brookes, Cassandra L; Forbes, John F; Viale, Giuseppe; Cuzick, Jack; Dowsett, Mitchell; Rea, Daniel W

2017-07-01

A meta-analysis of the effects of HER2 status, specifically within the first 2-3 years of adjuvant endocrine therapy, has the potential to inform patient selection for upfront aromatase inhibitor (AI) therapy or switching strategy tamoxifen followed by AI. The pre-existing standardisation of methodology for HER2 (immunohistochemistry/fluorescence in situ hybridization) facilitates analysis of existing data for this key marker. Following a prospectively designed statistical analysis plan, patient data from 3 phase III trials Arimidex, Tamoxifen, Alone or in Combination Trial (ATAC), Breast International Group (BIG) 1-98 and Tamoxifen Exemestane Adjuvant Multicentre Trial (TEAM)] comparing an AI to tamoxifen during the first 2-3 years of adjuvant endocrine treatment were collected and a treatment-by-marker analysis of distant recurrence-free interval-censored at 2-3 years treatment - for HER2 status × AI versus tamoxifen treatment was performed to address the clinical question relating to efficacy of 'upfront' versus 'switch' strategies for AIs. A prospectively planned, patient-level data meta-analysis across 3 trials demonstrated a significant treatment (AI versus tamoxifen) by marker (HER2) interaction in a multivariate analysis; (interaction hazard ratio [HR] = 1.61, 95% CI 1.01-2.57; p < 0.05). Heterogeneity between trials did not reach statistical significance. The HER2 negative (HER2-ve) group gained greater benefit from AI versus tamoxifen (HR = 0.70, 95% CI 0.56-0.87) than the HER2-positive (HER2+ve) group (HR = 1.13, 95% CI 0.75-1.71). However, the small number of HER2+ve cases (n = 1092 across the 3 trials) and distant recurrences (n = 111) may explain heterogeneity between trials. A patient-level data meta-analysis demonstrated a significant interaction between HER2 status and treatment with AI versus tamoxifen in the first 2-3 years of adjuvant endocrine therapy. Patients with HER2-ve cancers experienced improved outcomes (distant relapse) when treated with upfront AI rather than tamoxifen, whilst patients with HER2+ve cancers fared no better or slightly worse in the first 2-3 years. However, the small number of HER2+ve cancers/events may explain a large degree of heterogeneity in the HER2+ve groups across all 3 trials. Other causes, perhaps related to subtle differences between AIs, cannot be excluded and warrant further exploration. Copyright © 2017 Elsevier Ltd. All rights reserved.

Antibiotic Impregnated External Ventricular Drains: Meta and Cost Analysis.

PubMed

Root, Brandon K; Barrena, Benjamin G; Mackenzie, Todd A; Bauer, David F

2016-02-01

To determine whether antibiotic impregnated external ventricular drains (AI-EVDs) are effective in preventing ventriculostomy associated infection (VAI), and to examine their cost effectiveness. A comprehensive literature search was performed for published data through May 2014, including randomized controlled trials and observational cohort studies comparing AI-EVDs with nonimpregnated controls. A meta-analysis of included studies was performed using a random effects model. Historical data at the authors' institution were used to estimate both the incremental price of AI-EVDs and the hospital expenses associated with VAI. Three randomized controlled trials and 5 observational studies met inclusion criteria. The analysis demonstrated a statistically significant protective effect of AI-EVDs against VAI (risk ratio = 0.31 [0.15-0.64]; P = 0.002), although there was significant heterogeneity (χ(2) = 18.08; P = 0.01; I(2) = 61%). The number of AI-EVDs needed to prevent one infection (Number needed to treat [NNT]) was 19. Based on $100 as the incremental price, and $30,000 as the estimated expense of one episode of VAI, AI-EVDs would result in an overall savings estimate of $28,100 (range, $26,400-$28,500) per NNT. If a hospital places 150 AI-EVDs annually, savings could range from $109,292 to $278,577 per year. Meta-analysis demonstrated a significant protective benefit of AI-EVDs against VAI, and this benefit is likely associated with cost savings. However, current data on AI-EVDs are limited, and overall hospital costs will vary among institutions. Although both the efficacy and cost effectiveness of AI-EVDs are supported by this analysis, further study of AI-EVDs is clearly warranted. Copyright © 2016 Elsevier Inc. All rights reserved.

Scoring of anatomic injury after trauma: AIS 98 versus AIS 90--do the changes affect overall severity assessment?

PubMed

Skaga, Nils O; Eken, Torsten; Hestnes, Morten; Jones, J Mary; Steen, Petter A

2007-01-01

Although several changes were implemented in the 1998 update of the abbreviated injury scale (AIS 98) versus the previous AIS 90, both are still used worldwide for coding of anatomic injury in trauma. This could possibly invalidate comparisons between systems using different AIS versions. Our aim was to evaluate whether the use of different coding dictionaries affected estimation of Injury Severity Score (ISS), New Injury Severity Score (NISS) and probability of survival (Ps) according to TRISS in a hospital-based trauma registry. In a prospective study including 1654 patients from Ulleval University Hospital, a Norwegian trauma referral centre, patients were coded according to both AIS 98 and AIS 90. Agreement between the classifications of ISS, NISS and Ps according to TRISS methodology was estimated using intraclass correlation coefficients (ICC) with 95% CI. ISS changed for 378 of 1654 patients analysed (22.9%). One hundred and forty seven (8.9%) were coded differently due to different injury descriptions and 369 patients (22.3%) had a change in ISS value in one or more regions due to the different scoring algorithm for skin injuries introduced in AIS 98. This gave a minimal change in mean ISS (14.74 versus 14.54). An ICC value of 0.997 (95% CI 0.9968-0.9974) for ISS indicates excellent agreement between the scoring systems. There were no significant changes in NISS and Ps. There was excellent agreement for the overall population between ISS, NISS and Ps values obtained using AIS 90 and AIS 98 for injury coding. Injury descriptions for hypothermia were re-introduced in the recently published AIS 2005. We support this change as coding differences due to hypothermia were encountered in 4.3% of patients in the present study.

Deceleration energy and change in velocity on impact: key factors in fatal versus potentially survivable motor vehicle crash (mvc) aortic injuries (AI): the role of associated injuries as determinants of outcome.

PubMed

Siegel, John H; Smith, Joyce A; Tenenbaum, Nadegda; McCammon, Laurie; Siddiqi, Shabana Q; Presswalla, Faruk; Pierre-Louis, Phito; Williams, Wayne; Zaretski, Leonard; Hutchins, Kenneth; Perez, Lyla; Shaikh, J; Natarajan, Geetha

2002-01-01

To examine the difference in force mechanisms between fatal and potentially survivable MVC aortic injuries (AI) compared to non-AI severe thoracic injuries (ST). Of 324 autopsied MVC driver or front seat passenger fatalities (1997-2000), there were 43 fatal AI (36 scene deaths, 7 hospital deaths) and 5 additional AI survivors. Of the 48 AI, there was only a 42% survival for those reaching hospital alive. 80% of AI survivors had isthmus lesions and all had no or minimal brain injury (GCS >= 13), no cardiac injury and only 20% ribs 1-4 fx or shock; of AI non-survivors reaching hospital alive, 67% had GCS <= 12, 50% cardiac injury, 83% ribs 1-4 fx and 83% shock; AI scene deaths had 78% severe brain injury, 56% cardiac injury, 69% lung injury and 78% ribs 1-4 fx. Quantifying forces in AI scene mortality: the Instantaneous Velocity on Impact of the subject vehicle (delta V1) and the Impact Energy Dissipated (IE) on the subject vehicle (V1) in joules demonstrated a linear regression in fatal car MVC AIs: Energy dissipated (joules) = -56.65 x (delta V1)(2) + 15972 x delta V1 - 454661, r(2) = 0.83. However, for 27 patients with non-AI but severe thoracic (ST) injury (AIS>=3), the relationship of IE to delta V1 had a linear regression of Energy dissipated (joules) = -5.0787 x (delta V1)(2) + 4282.1 x delta V1 - 57182 1, r(2) = 0.84, with the slope difference between the regression for AI scene deaths and that of ST and AI survivors being significant (p<0.05). Based on these relationships, a Critical Zone limited by MVC Impact Energy level of 336000 joules and a delta V1 of 64 kph appears to be the limit of potential survivability in MVCs producing aortic injuries. All AI above these thresholds died. In contrast, ST had greater use of seatbelts (AI 10% vs all ST 60%) and airbags (AI 50% vs all ST 72%), and an 83% survival. The data suggest different mechanisms of force delivery and injury patterns in fatal vs potentially survivable AI, and vs ST MVCs. They suggest that an approach to improving vehicle safety measures for AI may involve better safety devices and mechanisms for reducing that fraction of Impact Energy dissipated on V1 for a given delta V1 which is focused on the upper portion of the subject's thoracic cage between the levels of ribs1-8.

A novel approach for the elimination of artefacts from EEG signals employing an improved Artificial Immune System algorithm

NASA Astrophysics Data System (ADS)

Suja Priyadharsini, S.; Edward Rajan, S.; Femilin Sheniha, S.

2016-03-01

Electroencephalogram (EEG) is the recording of electrical activities of the brain. It is contaminated by other biological signals, such as cardiac signal (electrocardiogram), signals generated by eye movement/eye blinks (electrooculogram) and muscular artefact signal (electromyogram), called artefacts. Optimisation is an important tool for solving many real-world problems. In the proposed work, artefact removal, based on the adaptive neuro-fuzzy inference system (ANFIS) is employed, by optimising the parameters of ANFIS. Artificial Immune System (AIS) algorithm is used to optimise the parameters of ANFIS (ANFIS-AIS). Implementation results depict that ANFIS-AIS is effective in removing artefacts from EEG signal than ANFIS. Furthermore, in the proposed work, improved AIS (IAIS) is developed by including suitable selection processes in the AIS algorithm. The performance of the proposed method IAIS is compared with AIS and with genetic algorithm (GA). Measures such as signal-to-noise ratio, mean square error (MSE) value, correlation coefficient, power spectrum density plot and convergence time are used for analysing the performance of the proposed method. From the results, it is found that the IAIS algorithm converges faster than the AIS and performs better than the AIS and GA. Hence, IAIS tuned ANFIS (ANFIS-IAIS) is effective in removing artefacts from EEG signals.

Artificial Intelligence (AI), Operations Research (OR), and Decision Support Systems (DSS): A conceptual framework

NASA Technical Reports Server (NTRS)

Parnell, Gregory S.; Rowell, William F.; Valusek, John R.

1987-01-01

In recent years there has been increasing interest in applying the computer based problem solving techniques of Artificial Intelligence (AI), Operations Research (OR), and Decision Support Systems (DSS) to analyze extremely complex problems. A conceptual framework is developed for successfully integrating these three techniques. First, the fields of AI, OR, and DSS are defined and the relationships among the three fields are explored. Next, a comprehensive adaptive design methodology for AI and OR modeling within the context of a DSS is described. These observations are made: (1) the solution of extremely complex knowledge problems with ill-defined, changing requirements can benefit greatly from the use of the adaptive design process, (2) the field of DSS provides the focus on the decision making process essential for tailoring solutions to these complex problems, (3) the characteristics of AI, OR, and DSS tools appears to be converging rapidly, and (4) there is a growing need for an interdisciplinary AI/OR/DSS education.

Field evaluation of commercial repellents against the floodwater mosquito Psorophora columbiae (Diptera: Culicidae) in St. Johns County, Florida.

PubMed

Qualls, Whitney A; Xue, Rui-De; Holt, J Adam; Smith, Mike L; Moeller, Jeanne J

2011-11-01

Three plant-based repellents-REPEL LEMON Eucalyptus Insect Repellent Lotion (active ingredient [AI] 30% oil of eucalyptus), Bite Blocker Xtreme Sportsman Organic Insect Repellent ([AI] 3% soybean oil, 6% geranium oil, and 8% castor oil), and Bite Blocker BioUD Insect Repellent ([AI] 7.75% 2-undecanone)--were evaluated against OFF! ([AI] 15% N,N-diethyl-m-toluamide or N,N-diethyl-3-methyl-benzamide, also called DEET) at a field site in Elkton, FL, to determine the mean protection time provided against Psorophora columbiae (Dyar & Knab). These products provided different protection times against biting Ps. columbiae. REPEL provided the longest protection time (330 min) followed by Bite Blocker Xtreme Sportsman (163 min), Bite Blocker BioUD (140 min), and OFF! (130 min). This study provides the first information about plant-based insect repellent protection times against Ps. columbiae.

Acceptability of a Web-based Community Reinforcement Approach for Substance Use Disorders with Treatment-seeking American Indians/Alaska Natives

PubMed Central

Campbell, Aimee N. C.; Turrigiano, Eva; Moore, Michelle; Miele, Gloria M.; Rieckmann, Traci; Hu, Mei-Chen; Kropp, Frankie; Ringor-Carty, Roz; Nunes, Edward V.

2014-01-01

Longstanding disparities in substance use disorders and treatment access exist among American Indian/Alaska Natives (AI/AN). Computerized, web-delivered interventions have potential to increase access to quality treatment and improve patient outcomes. Prior research supports the efficacy of a web-based version (Therapeutic Education System [TES]) of the Community Reinforcement Approach to improve outcomes among outpatients in substance abuse treatment; however, TES has not been tested among AI/AN. The results from this mixed method acceptability study among a diverse sample of urban AI/AN (N=40) show that TES was acceptable across seven indices (range=7.8 to 9.4 on 0 to 10 scales with 10 indicating highest acceptability). Qualitative interviews suggest adaptation specific to AI/AN culture could improve adoption. Additional efforts to adapt TES and conduct a larger effectiveness study are warranted. PMID:25022913

Acceptability of a web-based community reinforcement approach for substance use disorders with treatment-seeking American Indians/Alaska Natives.

PubMed

Campbell, Aimee N C; Turrigiano, Eva; Moore, Michelle; Miele, Gloria M; Rieckmann, Traci; Hu, Mei-Chen; Kropp, Frankie; Ringor-Carty, Roz; Nunes, Edward V

2015-05-01

Longstanding disparities in substance use disorders and treatment access exist among American Indians/Alaska Natives (AI/AN). Computerized, web-delivered interventions have potential to increase access to quality treatment and improve patient outcomes. Prior research supports the efficacy of a web-based version [therapeutic education system (TES)] of the community reinforcement approach to improve outcomes among outpatients in substance abuse treatment; however, TES has not been tested among AI/AN. The results from this mixed method acceptability study among a diverse sample of urban AI/AN (N = 40) show that TES was acceptable across seven indices (range 7.8-9.4 on 0-10 scales with 10 indicating highest acceptability). Qualitative interviews suggest adaptation specific to AI/AN culture could improve adoption. Additional efforts to adapt TES and conduct a larger effectiveness study are warranted.

Advances in Breeding Management and Use of Ovulation Induction for Fixed-time AI.

PubMed

Kirkwood, R N; Kauffold, J

2015-07-01

The objective of the breeding herd is the predictable and consistent production of high quality pigs. To achieve this objective, an appropriate number of females need to be mated in each breeding week and they should maintain their pregnancy and deliver large litters. Many factors can impact achievement of optimal sow productivity, particularly breeding management. Most matings will involve artificial insemination (AI), and successful AI requires deposition into the cervix (or beyond) of sufficient viable high quality sperm at an appropriate time relative to ovulation. This is facilitated by improved knowledge of the sow's ovarian function prior to and during her oestrous period. Realization of the importance of establishing an adequate sperm reservoir in the oviduct at an appropriate time relative to ovulation has led to advances in the management of AI. The future of AI will likely involve insemination of single doses of high genetic merit semen, potentially having a reduced sperm concentration which is made possible by knowledge of the effect of site of sperm deposition on sow fertility. In particular, knowledge of when a sow is likely to ovulate during a natural or induced oestrous period will prove invaluable in the maintenance of herd productivity. This review will examine options for breeding management, including the control of oestrus and ovulation, on sow herd reproductive performance. © 2015 Blackwell Verlag GmbH.

Recent Advances in Boar Sperm Cryopreservation: State of the Art and Current Perspectives.

PubMed

Yeste, M

2015-07-01

While sperm cryopreservation is the best technology to store boar semen for long-term periods, only 1% of all artificial inseminations (AI) conducted worldwide are made using frozen-thawed boar sperm. With the emergence of long-term extenders for liquid storage, the use of cryopreserved sperm in routine AI is less required. However, banks of boar semen contain cryopreserved sperm and planning inseminations in AI centres may benefit from the use of frozen-thawed semen. Therefore, there is an interest in the use of this technology to preserve boar sperm. In this regard, although the first attempts to cryopreserve boar semen date back to the seventies and this technology is still considered as optimal, some relevant improvements have been made in the last decade. After giving a general picture about boar sperm cryodamage, the present review seeks to shed light on these recent cryopreservation advances. These contributions regard to protein markers for predicting ejaculate freezability, sperm selection prior to start cryopreservation procedures, additives to freezing and thawing extenders, relevance of the AI-technique and insemination-to-ovulation interval. In conclusion, most of these progresses have allowed counteracting better boar sperm cryodamage and are thus considered as forward steps for this storage method. It is also worth noting that, despite being lower than fresh/extended semen, reproductive performance outcomes following AI with frozen-thawed boar sperm are currently acceptable. © 2015 Blackwell Verlag GmbH.

The influence of self-awareness on emotional memory formation: an fMRI study

PubMed Central

Wing, Erik A.; Cabeza, Roberto

2016-01-01

Evidence from functional neuroimaging studies of emotional perception shows that when attention is focused on external features of emotional stimuli (external perceptual orienting—EPO), the amygdala is primarily engaged, but when attention is turned inwards towards one’s own emotional state (interoceptive self-orienting—ISO), regions of the salience network, such as the anterior insula (AI) and the dorsal anterior cingulate cortex (dACC), also play a major role. Yet, it is unknown if ISO boosts the contributions of AI and dACC not only to emotional ‘perception’ but also to emotional ‘memory’. To investigate this issue, participants were scanned with functional magnetic resonance imaging (fMRI) while viewing emotional and neutral pictures under ISO or EPO, and memory was tested several days later. The study yielded three main findings: (i) emotion boosted perception-related activity in the amygdala during both ISO and EPO and in the right AI exclusively during ISO; (ii) emotion augmented activity predicting subsequent memory in AI and dACC during ISO but not during EPO and (iii) high confidence memory was associated with increased amygdala–dACC connectivity, selectively for ISO encoding. These findings show, for the first time, that ISO promotes emotional memory formation via regions associated with interoceptive awareness of emotional experience, such as AI and dACC. PMID:26645274

Simulation of a severe convective storm using a numerical model with explicitly incorporated aerosols

NASA Astrophysics Data System (ADS)

Lompar, Miloš; Ćurić, Mladjen; Romanic, Djordje

2017-09-01

Despite an important role the aerosols play in all stages of cloud lifecycle, their representation in numerical weather prediction models is often rather crude. This paper investigates the effects the explicit versus implicit inclusion of aerosols in a microphysics parameterization scheme in Weather Research and Forecasting (WRF) - Advanced Research WRF (WRF-ARW) model has on cloud dynamics and microphysics. The testbed selected for this study is a severe mesoscale convective system with supercells that struck west and central parts of Serbia in the afternoon of July 21, 2014. Numerical products of two model runs, i.e. one with aerosols explicitly (WRF-AE) included and another with aerosols implicitly (WRF-AI) assumed, are compared against precipitation measurements from surface network of rain gauges, as well as against radar and satellite observations. The WRF-AE model accurately captured the transportation of dust from the north Africa over the Mediterranean and to the Balkan region. On smaller scales, both models displaced the locations of clouds situated above west and central Serbia towards southeast and under-predicted the maximum values of composite radar reflectivity. Similar to satellite images, WRF-AE shows the mesoscale convective system as a merged cluster of cumulonimbus clouds. Both models over-predicted the precipitation amounts; WRF-AE over-predictions are particularly pronounced in the zones of light rain, while WRF-AI gave larger outliers. Unlike WRF-AI, the WRF-AE approach enables the modelling of time evolution and influx of aerosols into the cloud which could be of practical importance in weather forecasting and weather modification. Several likely causes for discrepancies between models and observations are discussed and prospects for further research in this field are outlined.

Future Antarctic bed topography and its implications for ice sheet dynamics

NASA Astrophysics Data System (ADS)

Adhikari, Surendra; Ivins, Erik; Larour, Eric; Seroussi, Helene; Morlighem, Mathieu; Nowicki, Sophie

2014-05-01

A recently improved ice loading history suggests that the Antarctic Ice Sheet (AIS) has been generally losing its mass since the last glacial maximum. In a sustained warming climate, the AIS is predicted to retreat at a greater pace primarily via melting beneath the ice shelves. We employ the glacial isostatic adjustment (GIA) capability of the Ice Sheet System Model (ISSM) to combine these past and future ice loadings and provide the new solid Earth computations for the AIS. We find that the past loading is relatively less important than future loading on the evolution of the future bed topography. Our computations predict that the West Antarctic Ice Sheet (WAIS) may uplift by a few meters and a few tens of meters at years 2100 and 2500 AD, respectively, and that the East Antarctic Ice Sheet (EAIS) is likely to remain unchanged or subside minimally except around the Amery Ice Shelf. The Amundsen Sea Sector of WAIS in particular is predicted to rise at the greatest rate; one hundred years of ice evolution in this region, for example, predicts that the coastline of Pine Island Bay approaches roughly 45 mm/yr in viscoelastic vertical motion. Of particular importance, we systematically demonstrate that the effect of a pervasive and large GIA uplift in the WAIS is associated with the flattening of reverse bed, reduction of local sea depth, and thus the extension of grounding line (GL) towards the continental shelf. Using the 3-D higher-order ice flow capability of ISSM, such a migration of GL is shown to inhibit the ice flow. This negative feedback between the ice sheet and the solid Earth may promote the stability to marine portions of the ice sheet in the future.

The short Synacthen (corticotropin) test can be used to predict recovery of hypothalamo-pituitary-adrenal axis function.

PubMed

Pofi, Riccardo; Feliciano, Chona; Sbardella, Emilia; Argese, Nicola; Woods, Conor P; Grossman, Ashley B; Jafar-Mohammadi, Bahram; Gleeson, Helena; Lenzi, Andrea; Isidori, Andrea M; Tomlinson, Jeremy W

2018-05-25

The 250μg Short Synacthen (corticotropin) Test (SST) is the most commonly used tool to assess hypothalamo-pituitary-adrenal (HPA) axis function. There are many potentially reversible causes of adrenal insufficiency (AI), but currently no data to guide clinicians as to the frequency of repeat testing or likelihood of HPA axis recovery. To use the SST results to predict recovery of adrenal function. A retrospective analysis of data from 1912 SSTs. 776 patients with reversible causes of AI were identified who had at least two SSTs performed. A subgroup analysis was performed on individuals previously treated with suppressive doses of glucocorticoids (n=110). Recovery of HPA axis function. SST 30-minute cortisol levels above or below 350nmol/L (12.7μg/dL) best predicted HPA axis recovery (AUC ROC=0.85; median recovery time 334 vs. 1368 days, p=8.5x10-13): 99% of patients with a 30-minute cortisol >350nmol/L recovered adrenal function within 4-years, compared with 49% in those with cortisol levels <350nmol/L. In patients exposed to suppressive doses of glucocorticoids, delta cortisol (30-minute - basal) was the best predictor of recovery (AUC ROC = 0.77; median recovery time 262 vs. 974 days, p=7.0x10-6). No patient with a delta cortisol <100nmol (3.6μg/dL) and a subsequent random cortisol <200nmol/L (7.3μg/dL) measured approximately 1-year later recovered HPA axis function. Cortisol levels across an SST can be used to predict recovery of AI and may guide the frequency of repeat testing and inform both clinicians and patients as to the likelihood of restoration of HPA axis function.

NASA space station automation: AI-based technology review. Executive summary

NASA Technical Reports Server (NTRS)

Firschein, O.; Georgeff, M. P.; Park, W.; Cheeseman, P. C.; Goldberg, J.; Neumann, P.; Kautz, W. H.; Levitt, K. N.; Rom, R. J.; Poggio, A. A.

1985-01-01

Research and Development projects in automation technology for the Space Station are described. Artificial Intelligence (AI) based technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics.

Entrepreneurship education: A strength-based approach to substance use and suicide prevention for American Indian adolescents.

PubMed

Tingey, Lauren; Larzelere-Hinton, Francene; Goklish, Novalene; Ingalls, Allison; Craft, Todd; Sprengeler, Feather; McGuire, Courtney; Barlow, Allison

2016-01-01

American Indian (AI) adolescents suffer the largest disparities in substance use and suicide. Predominating prevention models focus primarily on risk and utilize deficit-based approaches. The fields of substance use and suicide prevention research urge for positive youth development frameworks that are strength based and target change at individual and community levels. Entrepreneurship education is an innovative approach that reflects the gap in available programs. This paper describes the development and evaluation of a youth entrepreneurship education program in partnership with one AI community. We detail the curriculum, process evaluation results, and the randomized controlled trial evaluating its efficacy for increasing protective factors. Lessons learned may be applicable to other AI communities.

Internet-Based Delivery of Evidence-Based Health Promotion Programs Among American Indian and Alaska Native Youth: A Case Study

PubMed Central

Craig Rushing, Stephanie; Jessen, Cornelia; Gorman, Gwenda; Torres, Jennifer; Lambert, William E; Prokhorov, Alexander V; Miller, Leslie; Allums-Featherston, Kelly; Addy, Robert C; Peskin, Melissa F; Shegog, Ross

2016-01-01

Background American Indian and Alaska Native (AI/AN) youth face multiple health challenges compared to other racial/ethnic groups, which could potentially be ameliorated by the dissemination of evidence-based adolescent health promotion programs. Previous studies have indicated that limited trained personnel, cultural barriers, and geographic isolation may hinder the reach and implementation of evidence-based health promotion programs among AI/AN youth. Although Internet access is variable in AI/AN communities across the United States, it is swiftly and steadily improving, and it may provide a viable strategy to disseminate evidence-based health promotion programs to this underserved population. Objective We explored the potential of using the Internet to disseminate evidence-based health promotion programs on multiple health topics to AI/AN youth living in diverse communities across 3 geographically dispersed regions of the United States. Specifically, we assessed the Internet’s potential to increase the reach and implementation of evidence-based health promotion programs for AI/AN youth, and to engage AI/AN youth. Methods This randomized controlled trial was conducted in 25 participating sites in Alaska, Arizona, and the Pacific Northwest. Predominantly AI/AN youth, aged 12-14 years, accessed 6 evidence-based health promotion programs delivered via the Internet, which focused on sexual health, hearing loss, alcohol use, tobacco use, drug use, and nutrition and physical activity. Adult site coordinators completed computer-based education inventory surveys, connectivity and bandwidth testing to assess parameters related to program reach (computer access, connectivity, and bandwidth), and implementation logs to assess barriers to implementation (program errors and delivery issues). We assessed youths’ perceptions of program engagement via ratings on ease of use, understandability, credibility, likeability, perceived impact, and motivational appeal, using previously established measures. Results Sites had sufficient computer access and Internet connectivity to implement the 6 programs with adequate fidelity; however, variable bandwidth (ranging from 0.24 to 93.5 megabits per second; mean 25.6) and technical issues led some sites to access programs via back-up modalities (eg, uploading the programs from a Universal Serial Bus drive). The number of youth providing engagement ratings varied by program (n=40-191; 48-60% female, 85-90% self-identified AI/AN). Across programs, youth rated the programs as easy to use (68-91%), trustworthy (61-89%), likeable (59-87%), and impactful (63-91%). Most youth understood the words in the programs (60-83%), although some needed hints to complete the programs (16-49%). Overall, 37-66% of the participants would recommend the programs to a classmate, and 62-87% found the programs enjoyable when compared to other school lessons. Conclusions Findings demonstrate the potential of the Internet to enhance the reach and implementation of evidence-based health promotion programs, and to engage AI/AN youth. Provision of back-up modalities is recommended to address possible connectivity or technical issues. The dissemination of Internet-based health promotion programs may be a promising strategy to address health disparities for this underserved population. Trial Registration Clinicaltrials.gov NCT01303575; https://clinicaltrials.gov/ct2/show/NCT01303575 (Archived by WebCite at http://www.webcitation.org/6m7DO4g7c) PMID:27872037

Internet-Based Delivery of Evidence-Based Health Promotion Programs Among American Indian and Alaska Native Youth: A Case Study.

PubMed

Markham, Christine M; Craig Rushing, Stephanie; Jessen, Cornelia; Gorman, Gwenda; Torres, Jennifer; Lambert, William E; Prokhorov, Alexander V; Miller, Leslie; Allums-Featherston, Kelly; Addy, Robert C; Peskin, Melissa F; Shegog, Ross

2016-11-21

American Indian and Alaska Native (AI/AN) youth face multiple health challenges compared to other racial/ethnic groups, which could potentially be ameliorated by the dissemination of evidence-based adolescent health promotion programs. Previous studies have indicated that limited trained personnel, cultural barriers, and geographic isolation may hinder the reach and implementation of evidence-based health promotion programs among AI/AN youth. Although Internet access is variable in AI/AN communities across the United States, it is swiftly and steadily improving, and it may provide a viable strategy to disseminate evidence-based health promotion programs to this underserved population. We explored the potential of using the Internet to disseminate evidence-based health promotion programs on multiple health topics to AI/AN youth living in diverse communities across 3 geographically dispersed regions of the United States. Specifically, we assessed the Internet's potential to increase the reach and implementation of evidence-based health promotion programs for AI/AN youth, and to engage AI/AN youth. This randomized controlled trial was conducted in 25 participating sites in Alaska, Arizona, and the Pacific Northwest. Predominantly AI/AN youth, aged 12-14 years, accessed 6 evidence-based health promotion programs delivered via the Internet, which focused on sexual health, hearing loss, alcohol use, tobacco use, drug use, and nutrition and physical activity. Adult site coordinators completed computer-based education inventory surveys, connectivity and bandwidth testing to assess parameters related to program reach (computer access, connectivity, and bandwidth), and implementation logs to assess barriers to implementation (program errors and delivery issues). We assessed youths' perceptions of program engagement via ratings on ease of use, understandability, credibility, likeability, perceived impact, and motivational appeal, using previously established measures. Sites had sufficient computer access and Internet connectivity to implement the 6 programs with adequate fidelity; however, variable bandwidth (ranging from 0.24 to 93.5 megabits per second; mean 25.6) and technical issues led some sites to access programs via back-up modalities (eg, uploading the programs from a Universal Serial Bus drive). The number of youth providing engagement ratings varied by program (n=40-191; 48-60% female, 85-90% self-identified AI/AN). Across programs, youth rated the programs as easy to use (68-91%), trustworthy (61-89%), likeable (59-87%), and impactful (63-91%). Most youth understood the words in the programs (60-83%), although some needed hints to complete the programs (16-49%). Overall, 37-66% of the participants would recommend the programs to a classmate, and 62-87% found the programs enjoyable when compared to other school lessons. Findings demonstrate the potential of the Internet to enhance the reach and implementation of evidence-based health promotion programs, and to engage AI/AN youth. Provision of back-up modalities is recommended to address possible connectivity or technical issues. The dissemination of Internet-based health promotion programs may be a promising strategy to address health disparities for this underserved population. Clinicaltrials.gov NCT01303575; https://clinicaltrials.gov/ct2/show/NCT01303575 (Archived by WebCite at http://www.webcitation.org/6m7DO4g7c). ©Christine M Markham, Stephanie Craig Rushing, Cornelia Jessen, Gwenda Gorman, Jennifer Torres, William E Lambert, Alexander V Prokhorov, Leslie Miller, Kelly Allums-Featherston, Robert C Addy, Melissa F Peskin, Ross Shegog. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 21.11.2016.

Preventing Fusion Mass Shift Avoids Postoperative Distal Curve Adding-on in Adolescent Idiopathic Scoliosis.

PubMed

Shigematsu, Hideki; Cheung, Jason Pui Yin; Bruzzone, Mauro; Matsumori, Hiroaki; Mak, Kin-Cheung; Samartzis, Dino; Luk, Keith Dip Kei

2017-05-01

Surgery for adolescent idiopathic scoliosis (AIS) is only complete after achieving fusion to maintain the correction obtained intraoperatively. The instrumented or fused segments can be referred to as the "fusion mass". In patients with AIS, the ideal fusion mass strategy has been established based on fulcrum-bending radiographs for main thoracic curves. Ideally, the fusion mass should achieve parallel endplates of the upper and lower instrumented vertebra and correct any "shift" for truncal balance. Distal adding-on is an important element to consider in AIS surgery. This phenomenon represents a progressive increase in the number of vertebrae included distally in the primary curvature and it should be avoided as it is associated with unsatisfactory cosmesis and an increased risk of revision surgery. However, it remains unknown whether any fusion mass shift, or shift in the fusion mass or instrumented segments, affects global spinal balance and distal adding-on after curve correction surgery in patients with AIS. (1) To investigate the relationship among postoperative fusion mass shift, global balance, and distal adding-on phenomenon in patients with AIS; and (2) to identify a cutoff value of fusion mass shift that will lead to distal adding-on. This was a retrospective study of patients with AIS from a single institution. Between 2006 and 2011 we performed 69 selective thoracic fusions for patients with main thoracic AIS. All patients were evaluated preoperatively and at 2 years postoperatively. The Cobb angle between the cranial and caudal endplates of the fusion mass and the coronal shift between them, which was defined as "fusion mass shift", were measured. Patients with a fusion mass Cobb angle greater than 20° were excluded to specifically determine the effect of fusion mass shift on distal adding-on phenomenon. Fusion mass shift was empirically set as 20 mm for analysis. Therefore, of the 69 patients who underwent selective thoracic fusion, only 52 with a fusion mass Cobb angle of 20° or less were recruited for study. We defined patients with a fusion mass shift of 20 mm or less as the balanced group and those with a fusion mass shift greater than 20 mm as the unbalanced group. A receiver operating characteristic (ROC) curve was used to determine the cutoff point of fusion mass shift for adding-on. Of the 52 patients studied, fusion mass shift (> 20 mm) was noted in 11 (21%), and six of those patients had distal adding-on at final followup. Although global spinal balance did not differ significantly between patients with or without fusion mass shift, the occurrence of adding-on phenomenon was significantly higher in the unbalanced group (55% (six of 11 patients), odds ratio [OR], 8.6; 95% CI, 2-39; p < 0.002) than the balanced group (12% [five of 41 patients]). Based on the ROC curve analysis, a fusion mass shift more than 18 mm was observed as the cutoff point for distal adding-on phenomenon (area under the curve, 0.70; 95% CI, 0.5-0.9; likelihood ratio, 5.0; sensitivity, 0.64; specificity, 0.73; positive predictive value, 39% [seven of 18 patients]; negative predictive value, 88% [30 of 34 patients]; OR, 4.8; 95% CI, 1-20; p = 0.02). Our study illustrates the substantial utility of the fulcrum-bending radiograph in determining fusion levels that can avoid fusion mass shift; thereby, underlining its importance in designing personalized surgical strategies for patients with scoliosis. Preoperatively, determining fusion levels by fulcrum-bending radiographs to avoid residual fusion mass shift is imperative. Intraoperatively, any fusion mass shift should be corrected to avoid distal adding-on, reoperation, and elevated healthcare costs. Level II, prognostic study.

Potentially Missed Diagnosis of Ischemic Stroke in the Emergency Department in the Greater Cincinnati/Northern Kentucky Stroke Study.

PubMed

Madsen, Tracy E; Khoury, Jane; Cadena, Rhonda; Adeoye, Opeolu; Alwell, Kathleen A; Moomaw, Charles J; McDonough, Erin; Flaherty, Matthew L; Ferioli, Simona; Woo, Daniel; Khatri, Pooja; Broderick, Joseph P; Kissela, Brett M; Kleindorfer, Dawn

2016-10-01

Missed diagnoses of acute ischemic stroke (AIS) in the ED may result in lost opportunities to treat AIS. Our objectives were to describe the rate and clinical characteristics of missed AIS in the ED, to determine clinical predictors of missed AIS, and to report tissue plasminogen (tPA) eligibility among those with missed strokes. Among a population of 1.3 million in a five-county region of southwest Ohio and northern Kentucky, cases of AIS that presented to 16 EDs during 2010 were identified using ICD-9 codes followed by physician verification of cases. Missed ED diagnoses were physician-verified strokes that did not receive a diagnosis indicative of stroke in the ED. Bivariate analyses were used to compare clinical characteristics between patients with and without an ED diagnosis of AIS. Logistic regression was used to evaluate predictors of missed AIS diagnoses. Alternative diagnoses given to those with missed AIS were codified. Eligibility for tPA was reported between those with and without a missed stroke diagnosis. Of 2,027 AIS cases, 14.0% (n = 283) were missed in the ED. Race, sex, and stroke subtypes were similar between those with missed AIS diagnoses and those identified in the ED. Hospital length of stay was longer in those with a missed diagnosis (5 days vs. 3 days, p < 0.0001). Younger age (adjusted odds ratio [aOR] = 0.94, 95% confidence interval [CI] = 0.89 to 0.98) and decreased level of consciousness (LOC) (aOR = 3.58, 95% CI = 2.63 to 4.87) were associated with higher odds of missed AIS. Altered mental status was the most common diagnosis among those with missed AIS. Only 1.1% of those with a missed stroke diagnosis were eligible for tPA. In a large population-based sample of AIS cases, one in seven cases were not diagnosed as AIS in the ED, but the impact on acute treatment rates is likely small. Missed diagnosis was more common among those with decreased LOC, suggesting the need for improved diagnostic approaches in these patients. © 2016 by the Society for Academic Emergency Medicine.

Predicting adsorptive removal of chlorophenol from aqueous solution using artificial intelligence based modeling approaches.

PubMed

Singh, Kunwar P; Gupta, Shikha; Ojha, Priyanka; Rai, Premanjali

2013-04-01

The research aims to develop artificial intelligence (AI)-based model to predict the adsorptive removal of 2-chlorophenol (CP) in aqueous solution by coconut shell carbon (CSC) using four operational variables (pH of solution, adsorbate concentration, temperature, and contact time), and to investigate their effects on the adsorption process. Accordingly, based on a factorial design, 640 batch experiments were conducted. Nonlinearities in experimental data were checked using Brock-Dechert-Scheimkman (BDS) statistics. Five nonlinear models were constructed to predict the adsorptive removal of CP in aqueous solution by CSC using four variables as input. Performances of the constructed models were evaluated and compared using statistical criteria. BDS statistics revealed strong nonlinearity in experimental data. Performance of all the models constructed here was satisfactory. Radial basis function network (RBFN) and multilayer perceptron network (MLPN) models performed better than generalized regression neural network, support vector machines, and gene expression programming models. Sensitivity analysis revealed that the contact time had highest effect on adsorption followed by the solution pH, temperature, and CP concentration. The study concluded that all the models constructed here were capable of capturing the nonlinearity in data. A better generalization and predictive performance of RBFN and MLPN models suggested that these can be used to predict the adsorption of CP in aqueous solution using CSC.

The Preparation of (Al2O3)x(SiO2)y Thin Films Using (Al(OSiEt3)3)2 as a Single Source Precursor

DTIC Science & Technology

1992-05-12

point AI(OSiEt 3)3(NH3 ) cannot itself readily be used as a volatile precursor. If, however, NH 3 is used as the carrier gas [AI(OSiEt3)3]2 rapidly melts ...situ formation of the low melting Lewis acid-base adduct Al(OSiEt 3)3(NH 3), however, no nitrogen incorporation was observed in these deposited films...in situ formation of the low melting Lewis acid-base adduct AI(OSiEt3)3(NH3), however, no nitrogen incorporation was observed in these deposited

ARGES: an Expert System for Fault Diagnosis Within Space-Based ECLS Systems

NASA Technical Reports Server (NTRS)

Pachura, David W.; Suleiman, Salem A.; Mendler, Andrew P.

1988-01-01

ARGES (Atmospheric Revitalization Group Expert System) is a demonstration prototype expert system for fault management for the Solid Amine, Water Desorbed (SAWD) CO2 removal assembly, associated with the Environmental Control and Life Support (ECLS) System. ARGES monitors and reduces data in real time from either the SAWD controller or a simulation of the SAWD assembly. It can detect gradual degradations or predict failures. This allows graceful shutdown and scheduled maintenance, which reduces crew maintenance overhead. Status and fault information is presented in a user interface that simulates what would be seen by a crewperson. The user interface employs animated color graphics and an object oriented approach to provide detailed status information, fault identification, and explanation of reasoning in a rapidly assimulated manner. In addition, ARGES recommends possible courses of action for predicted and actual faults. ARGES is seen as a forerunner of AI-based fault management systems for manned space systems.

American Society of Clinical Oncology Clinical Practice Guideline: Update on Adjuvant Endocrine Therapy for Women With Hormone Receptor–Positive Breast Cancer

PubMed Central

Burstein, Harold J.; Prestrud, Ann Alexis; Seidenfeld, Jerome; Anderson, Holly; Buchholz, Thomas A.; Davidson, Nancy E.; Gelmon, Karen E.; Giordano, Sharon H.; Hudis, Clifford A.; Malin, Jennifer; Mamounas, Eleftherios P.; Rowden, Diana; Solky, Alexander J.; Sowers, MaryFran R.; Stearns, Vered; Winer, Eric P.; Somerfield, Mark R.; Griggs, Jennifer J.

2010-01-01

Purpose To develop evidence-based guidelines, based on a systematic review, for endocrine therapy for postmenopausal women with hormone receptor–positive breast cancer. Methods A literature search identified relevant randomized trials. Databases searched included MEDLINE, PREMEDLINE, the Cochrane Collaboration Library, and those for the Annual Meetings of the American Society of Clinical Oncology (ASCO) and the San Antonio Breast Cancer Symposium (SABCS). The primary outcomes of interest were disease-free survival, overall survival, and time to contralateral breast cancer. Secondary outcomes included adverse events and quality of life. An expert panel reviewed the literature, especially 12 major trials, and developed updated recommendations. Results An adjuvant treatment strategy incorporating an aromatase inhibitor (AI) as primary (initial endocrine therapy), sequential (using both tamoxifen and an AI in either order), or extended (AI after 5 years of tamoxifen) therapy reduces the risk of breast cancer recurrence compared with 5 years of tamoxifen alone. Data suggest that including an AI as primary monotherapy or as sequential treatment after 2 to 3 years of tamoxifen yields similar outcomes. Tamoxifen and AIs differ in their adverse effect profiles, and these differences may inform treatment preferences. Conclusion The Update Committee recommends that postmenopausal women with hormone receptor–positive breast cancer consider incorporating AI therapy at some point during adjuvant treatment, either as up-front therapy or as sequential treatment after tamoxifen. The optimal timing and duration of endocrine treatment remain unresolved. The Update Committee supports careful consideration of adverse effect profiles and patient preferences in deciding whether and when to incorporate AI therapy. PMID:20625130

Modeling of ablation threshold dependence on pulse duration for dielectrics with ultrashort pulsed laser

NASA Astrophysics Data System (ADS)

Sun, Mingying; Zhu, Jianqiang; Lin, Zunqi

2017-01-01

We present a numerical model of plasma formation in ultrafast laser ablation on the dielectrics surface. Ablation threshold dependence on pulse duration is predicted with the model and the numerical results for water agrees well with the experimental data for pulse duration from 140 fs to 10 ps. Influences of parameters and approximations of photo- and avalanche-ionization on the ablation threshold prediction are analyzed in detail for various pulse lengths. The calculated ablation threshold is strongly dependent on electron collision time for all the pulse durations. The complete photoionization model is preferred for pulses shorter than 1 ps rather than the multiphoton ionization approximations. The transition time of inverse bremsstrahlung absorption needs to be considered when pulses are shorter than 5 ps and it can also ensure the avalanche ionization (AI) coefficient consistent with that in multiple rate equations (MREs) for pulses shorter than 300 fs. The threshold electron density for AI is only crucial for longer pulses. It is reasonable to ignore the recombination loss for pulses shorter than 100 fs. In addition to thermal transport and hydrodynamics, neglecting the threshold density for AI and recombination could also contribute to the disagreements between the numerical and the experimental results for longer pulses.

Artificial Intelligence and Information Management

NASA Astrophysics Data System (ADS)

Fukumura, Teruo

After reviewing the recent popularization of the information transmission and processing technologies, which are supported by the progress of electronics, the authors describe that by the introduction of the opto-electronics into the information technology, the possibility of applying the artificial intelligence (AI) technique to the mechanization of the information management has emerged. It is pointed out that althuogh AI deals with problems in the mental world, its basic methodology relies upon the verification by evidence, so the experiment on computers become indispensable for the study of AI. The authors also describe that as computers operate by the program, the basic intelligence which is concerned in AI is that expressed by languages. This results in the fact that the main tool of AI is the logical proof and it involves an intrinsic limitation. To answer a question “Why do you employ AI in your problem solving”, one must have ill-structured problems and intend to conduct deep studies on the thinking and the inference, and the memory and the knowledge-representation. Finally the authors discuss the application of AI technique to the information management. The possibility of the expert-system, processing of the query, and the necessity of document knowledge-base are stated.

Analysis of cognitive theories in artificial intelligence and psychology in relation to the qualitative process of emotion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Semrau, P.

The purpose of this study was to analyze selected cognitive theories in the areas of artificial intelligence (A.I.) and psychology to determine the role of emotions in the cognitive or intellectual processes. Understanding the relationship of emotions to processes of intelligence has implications for constructing theories of aesthetic response and A.I. systems in art. Psychological theories were examined that demonstrated the changing nature of the research in emotion related to cognition. The basic techniques in A.I. were reviewed and the A.I. research was analyzed to determine the process of cognition and the role of emotion. The A.I. research emphasized themore » digital, quantifiable character of the computer and associated cognitive models and programs. In conclusion, the cognitive-emotive research in psychology and the cognitive research in A.I. emphasized quantification methods over analog and qualitative characteristics required for a holistic explanation of cognition. Further A.I. research needs to examine the qualitative aspects of values, attitudes, and beliefs on influencing the creative thinking processes. Inclusion of research related to qualitative problem solving in art provides a more comprehensive base of study for examining the area of intelligence in computers.« less

Experimental and AI-based numerical modeling of contaminant transport in porous media.

PubMed

Nourani, Vahid; Mousavi, Shahram; Sadikoglu, Fahreddin; Singh, Vijay P

2017-10-01

This study developed a new hybrid artificial intelligence (AI)-meshless approach for modeling contaminant transport in porous media. The key innovation of the proposed approach is that both black box and physically-based models are combined for modeling contaminant transport. The effectiveness of the approach was evaluated using experimental and real world data. Artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) were calibrated to predict temporal contaminant concentrations (CCs), and the effect of noisy and de-noised data on the model performance was evaluated. Then, considering the predicted CCs at test points (TPs, in experimental study) and piezometers (in Myandoab plain) as interior conditions, the multiquadric radial basis function (MQ-RBF), as a meshless approach which solves partial differential equation (PDE) of contaminant transport in porous media, was employed to estimate the CC values at any point within the study area where there was no TP or piezometer. Optimal values of the dispersion coefficient in the advection-dispersion PDE and shape coefficient of MQ-RBF were determined using the imperialist competitive algorithm. In temporal contaminant transport modeling, de-noised data enhanced the performance of ANN and ANFIS methods in terms of the determination coefficient, up to 6 and 5%, respectively, in the experimental study and up to 39 and 18%, respectively, in the field study. Results showed that the efficiency of ANFIS-meshless model was more than ANN-meshless model up to 2 and 13% in the experimental and field studies, respectively. Copyright © 2017. Published by Elsevier B.V.

Rare variants in FBN1 and FBN2 are associated with severe adolescent idiopathic scoliosis

PubMed Central

Buchan, Jillian G.; Alvarado, David M.; Haller, Gabe E.; Cruchaga, Carlos; Harms, Matthew B.; Zhang, Tianxiao; Willing, Marcia C.; Grange, Dorothy K.; Braverman, Alan C.; Miller, Nancy H.; Morcuende, Jose A.; Tang, Nelson Leung-Sang; Lam, Tsz-Ping; Ng, Bobby Kin-Wah; Cheng, Jack Chun-Yiu; Dobbs, Matthew B.; Gurnett, Christina A.

2014-01-01

Adolescent idiopathic scoliosis (AIS) causes spinal deformity in 3% of children. Despite a strong genetic basis, few genes have been associated with AIS and the pathogenesis remains poorly understood. In a genome-wide rare variant burden analysis using exome sequence data, we identified fibrillin-1 (FBN1) as the most significantly associated gene with AIS. Based on these results, FBN1 and a related gene, fibrillin-2 (FBN2), were sequenced in a total of 852 AIS cases and 669 controls. In individuals of European ancestry, rare variants in FBN1 and FBN2 were enriched in severely affected AIS cases (7.6%) compared with in-house controls (2.4%) (OR = 3.5, P = 5.46 × 10−4) and Exome Sequencing Project controls (2.3%) (OR = 3.5, P = 1.48 × 10−6). Scoliosis severity in AIS cases was associated with FBN1 and FBN2 rare variants (P = 0.0012) and replicated in an independent Han Chinese cohort (P = 0.0376), suggesting that rare variants may be useful as predictors of curve progression. Clinical evaluations revealed that the majority of AIS cases with rare FBN1 variants do not meet diagnostic criteria for Marfan syndrome, though variants are associated with tall stature (P = 0.0035) and upregulation of the transforming growth factor beta pathway. Overall, these results expand our definition of fibrillin-related disorders to include AIS and open up new strategies for diagnosing and treating severe AIS. PMID:24833718

Autoinducer-2-like activity associated with foods and its interaction with food additives.

PubMed

Lu, Lingeng; Hume, Michael E; Pillai, Suresh D

2004-07-01

The autoinducer-2 (AI-2) molecule produced by bacteria as part of quorum sensing is considered to be a universal inducer signal in bacteria because it reportedly influences gene expression in a variety of both gram-negative and gram-positive bacteria. The objective of this study was to determine whether selected fresh produce and processed foods have AI-2-like activity and whether specific food additives can act as AI-2 mimics and result in AI-2-like activity. The luminescence-based response of the reporter strain Vibrio harveyi BB170 was used as the basis for determining AI-2 activity in the selected foods and food ingredients. Maximum AI-2 activity was seen on the frozen fish sample (203-fold, compared with the negative control) followed by tomato, cantaloupe, carrots, tofu, and milk samples. Interestingly, some samples were capable of inhibiting AI-2 activity. Turkey patties showed the highest inhibition (99.8% compared with the positive control) followed by chicken breast (97.5%), homemade cheeses (93.7%), beef steak (90.6%), and beef patties (84.4%). AI-2 activity was almost totally inhibited by sodium propionate, whereas sodium benzoate caused 93.3% inhibition, compared with 75% inhibition by sodium acetate. Sodium nitrate did not have any appreciable effect, even at 200 ppm. Understanding the relationships that exist between AI-2 activity on foods and the ecology of pathogens and food spoilage bacteria on foods could yield clues about factors controlling food spoilage and pathogen virulence.

Enacting the Semantic Web: Ontological Orderings, Negotiated Standards, and Human-Machine Translations

ERIC Educational Resources Information Center

McCarthy, Matthew T.

2017-01-01

Artificial intelligence (AI) that is based upon semantic search has become one of the dominant means for accessing information in recent years. This is particularly the case in mobile contexts, as search-based AI are embedded in each of the major mobile operating systems. The implications are such that information is becoming less a matter of…

Functional recovery patterns in seriously injured automotive crash victims.

PubMed

McMurry, Timothy L; Poplin, Gerald S; Crandall, Jeff

2016-09-01

The functional capacity index (FCI) is designed to predict functional loss 12 months post-injury for each injury in the 2008 Abbreviated Injury Scale (AIS) manual on a scale from 0 (death) to 100 (full recovery), but FCI has never been validated. This study compared FCI predicted loss with patient-reported 12-month outcomes as measured through the Short Form 36 (SF-36) health assessment survey. Using follow-up data collected on 2,858 adult car crash occupants in the Crash Injury Research and Engineering Network (CIREN) database, we compared FCI predicted outcomes to occupants' Physical Component Summary (PCS) scores, which are weighted averages of the SF-36 items addressing physical function. Our analyses included descriptive statistics, plots of typical recovery patterns, and a mixed effects regression model that describes PCS as a function of FCI, demographics, comorbidities, and injury pattern while also adjusting for the occupants' pre-crash physical capabilities. We further examined injuries in patients who report a significant drop in PCS 12 months post-crash despite being predicted to fully recover. At baseline, the CIREN population exhibited PCS scores similar to the overall population (mean = 51.1, SD = 10.3). Twelve months post-crash, occupants with predicted impairment (FCI < 100) report a substantial decrease in physical function, and those who were predicted to fully recover still report some, albeit less, impairment. In the multivariate mixed-effects regression model, FCI is a strongly significant (P-value <.0001) predictor of PCS, with each 1-point drop in FCI predicting a 0.27-point drop in PCS. Maximum AIS severities in the head, spine, and lower extremity body regions were also significantly associated with PCS (P-values <.05). Among occupants who were expected to fully recover but who report a significant drop in PCS at 12 months, spinal fractures without cord involvement account for 5 of the 10 most common AIS 2+ injuries. FCI was associated with 12-month outcomes but may not adequately describe the recovery from some head, spine, and lower extremity injuries. Some occupants who were expected to recover still report functional loss 12 months post-injury.

Artificial Intelligence (AI) Based Tactical Guidance for Fighter Aircraft

NASA Technical Reports Server (NTRS)

McManus, John W.; Goodrich, Kenneth H.

1990-01-01

A research program investigating the use of Artificial Intelligence (AI) techniques to aid in the development of a Tactical Decision Generator (TDG) for Within Visual Range (WVR) air combat engagements is discussed. The application of AI programming and problem solving methods in the development and implementation of the Computerized Logic For Air-to-Air Warfare Simulations (CLAWS), a second generation TDG, is presented. The Knowledge-Based Systems used by CLAWS to aid in the tactical decision-making process are outlined in detail, and the results of tests to evaluate the performance of CLAWS versus a baseline TDG developed in FORTRAN to run in real-time in the Langley Differential Maneuvering Simulator (DMS), are presented. To date, these test results have shown significant performance gains with respect to the TDG baseline in one-versus-one air combat engagements, and the AI-based TDG software has proven to be much easier to modify and maintain than the baseline FORTRAN TDG programs. Alternate computing environments and programming approaches, including the use of parallel algorithms and heterogeneous computer networks are discussed, and the design and performance of a prototype concurrent TDG system are presented.

Still-Born Autonomy Insurance Plan in Quebec: An Example of a Public Long-Term Care Insurance System in Canada.

PubMed

Hébert, Réjean

2016-01-01

Funding long-term care (LTC) is a challenge under the existing Beveridgean universal healthcare system. The Autonomy Insurance (AI) plan developed in Quebec was an attempt to introduce public LTC insurance into our healthcare system. The AI benefit was based on an assessment of the needs of older people and those with disabilities using a disability scale (SMAF) and case-mix classification system (Iso-SMAF Profiles). Under the plan, the benefit would be used to fund public institutions or purchase services from private organizations. Case managers were responsible for assessments and helping users and their families plan services and decide how to use the AI benefit. Funding AI was based on general tax revenues without capitalized funding, under a separate protected budget program. Projections were made for the additional budget needed to support AI, which would have mitigated the forecast increase in LTC spending due to population aging. All the legal, administrative, funding, training and contractual issues were dealt with, for implementation of the plan in April 2015. Unfortunately, the project was still-born for political reasons, but it demonstrates the feasibility of this essential innovation for Canada.

Compact atom interferometer using single laser

NASA Astrophysics Data System (ADS)

Chiow, Sheng-Wey; Yu, Nan

2017-04-01

Atom interferometer (AI) based sensors exhibit precision and accuracy unattainable with classical sensors, thanks to the inherent stability of atomic properties. The complexity of required laser system and the size of vacuum chamber driven by optical access requirement limit the applicability of such technology in size, weight, and power (SWaP) challenging environments, such as in space. For instance, a typical physics package of AI includes six viewports for laser cooling and trapping, two for AI beams, and two more for detection and a vacuum pump. Similarly, a typical laser system for an AI includes two lasers for cooling and repumping, and two for Raman transitions as AI beam splitters. In this presentation, we report our efforts in developing a miniaturized atomic accelerometer for planetary exploration. We will describe a physics package configuration having minimum optical access (thus small volume), and a laser and optics system utilizing a single laser for the sensor operation. Preliminary results on acceleration sensitivity will be discussed. We will also illustrate a path for further packaging and integration based on the demonstrated concepts. This research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration.

Atom Interferometry with Ultracold Quantum Gases in a Microgravity Environment

NASA Astrophysics Data System (ADS)

Williams, Jason; D'Incao, Jose; Chiow, Sheng-Wey; Yu, Nan

2015-05-01

Precision atom interferometers (AI) in space promise exciting technical capabilities for fundamental physics research, with proposals including unprecedented tests of the weak equivalence principle, precision measurements of the fine structure and gravitational constants, and detection of gravity waves and dark energy. Consequently, multiple AI-based missions have been proposed to NASA, including a dual-atomic-species interferometer that is to be integrated into the Cold Atom Laboratory (CAL) onboard the International Space Station. In this talk, I will discuss our plans and preparation at JPL for the proposed flight experiments to use the CAL facility to study the leading-order systematics expected to corrupt future high-precision measurements of fundamental physics with AIs in microgravity. The project centers on the physics of pairwise interactions and molecular dynamics in these quantum systems as a means to overcome uncontrolled shifts associated with the gravity gradient and few-particle collisions. We will further utilize the CAL AI for proof-of-principle tests of systematic mitigation and phase-readout techniques for use in the next-generation of precision metrology experiments based on AIs in microgravity. This research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration.

Opportunities for Maturing Precision Metrology with Ultracold Gas Studies Aboard the ISS

NASA Astrophysics Data System (ADS)

Williams, Jason; D'Incao, Jose

2017-04-01

Precision atom interferometers (AI) in space are expected to become an enabling technology for future fundamental physics research, with proposals including unprecedented tests of the validity of the weak equivalence principle, measurements of the fine structure and gravitational constants, and detection of gravity waves and dark matter/dark energy. We will discuss our preparation at JPL to use NASA's Cold Atom Lab facility (CAL) to mature the technology of precision, space-based, AIs. The focus of our flight project is three-fold: a) study the controlled dynamics of heteronuclear Feshbach molecules, at temperatures of nano-Kelvins or below, as a means to overcome uncontrolled density-profile-dependent shifts in differential AIs, b) demonstrate unprecedented atom-photon coherence times with spatially constrained AIs, c) use the imaging capabilities of CAL to detect and analyze spatial fringe patterns written onto the clouds after AI and thereby measure the rotational noise of the ISS. The impact from this work, and potential for follow-on studies, will also be reviewed in the context of future space-based fundamental physics missions. This research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration.

Understanding gender roles in teen pregnancy prevention among American Indian youth.

PubMed

Hanson, Jessica D; McMahon, Tracey R; Griese, Emily R; Kenyon, DenYelle Baete

2014-11-01

To examine the impact of gender norms on American Indian (AI) adolescents' sexual health behavior. The project collected qualitative data at a reservation site and an urban site through 24 focus groups and 20 key informant interviews. The reasons that AI youth choose to abstain or engage in sexual intercourse and utilize contraception vary based on gender ideologies defined by the adolescent's environment. These include social expectations from family and peers, defined roles within relationships, and gender empowerment gaps. Gender ideology plays a large role in decisions about contraception and sexual activity for AI adolescents, and it is vital to include redefinitions of gender norms within AI teen pregnancy prevention program.

The Additional Secondary Phase Correction System for AIS Signals

PubMed Central

Wang, Xiaoye; Zhang, Shufang; Sun, Xiaowen

2017-01-01

This paper looks at the development and implementation of the additional secondary phase factor (ASF) real-time correction system for the Automatic Identification System (AIS) signal. A large number of test data were collected using the developed ASF correction system and the propagation characteristics of the AIS signal that transmits at sea and the ASF real-time correction algorithm of the AIS signal were analyzed and verified. Accounting for the different hardware of the receivers in the land-based positioning system and the variation of the actual environmental factors, the ASF correction system corrects original measurements of positioning receivers in real time and provides corrected positioning accuracy within 10 m. PMID:28362330

Developing adaptive interventions for adolescent substance use treatment settings: protocol of an observational, mixed-methods project.

PubMed

Grant, Sean; Agniel, Denis; Almirall, Daniel; Burkhart, Q; Hunter, Sarah B; McCaffrey, Daniel F; Pedersen, Eric R; Ramchand, Rajeev; Griffin, Beth Ann

2017-12-19

Over 1.6 million adolescents in the United States meet criteria for substance use disorders (SUDs). While there are promising treatments for SUDs, adolescents respond to these treatments differentially in part based on the setting in which treatments are delivered. One way to address such individualized response to treatment is through the development of adaptive interventions (AIs): sequences of decision rules for altering treatment based on an individual's needs. This protocol describes a project with the overarching goal of beginning the development of AIs that provide recommendations for altering the setting of an adolescent's substance use treatment. This project has three discrete aims: (1) explore the views of various stakeholders (parents, providers, policymakers, and researchers) on deciding the setting of substance use treatment for an adolescent based on individualized need, (2) generate hypotheses concerning candidate AIs, and (3) compare the relative effectiveness among candidate AIs and non-adaptive interventions commonly used in everyday practice. This project uses a mixed-methods approach. First, we will conduct an iterative stakeholder engagement process, using RAND's ExpertLens online system, to assess the importance of considering specific individual needs and clinical outcomes when deciding the setting for an adolescent's substance use treatment. Second, we will use results from the stakeholder engagement process to analyze an observational longitudinal data set of 15,656 adolescents in substance use treatment, supported by the Substance Abuse and Mental Health Services Administration, using the Global Appraisal of Individual Needs questionnaire. We will utilize methods based on Q-learning regression to generate hypotheses about candidate AIs. Third, we will use robust statistical methods that aim to appropriately handle casemix adjustment on a large number of covariates (marginal structural modeling and inverse probability of treatment weights) to compare the relative effectiveness among candidate AIs and non-adaptive decision rules that are commonly used in everyday practice. This project begins filling a major gap in clinical and research efforts for adolescents in substance use treatment. Findings could be used to inform the further development and revision of influential multi-dimensional assessment and treatment planning tools, or lay the foundation for subsequent experiments to further develop or test AIs for treatment planning.

Spatiotemporal variations of potential evapotranspiration and aridity index in relation to influencing factors over Southwest China during 1960-2013

NASA Astrophysics Data System (ADS)

Zhao, Yifei; Zou, Xinqing; Cao, Liguo; Yao, Yulong; Fu, Guanghe

2017-07-01

This study investigated the spatial-temporal patterns and trends of potential evapotranspiration (ET0) and aridity index (AI) over Southwest China during 1960-2013 based on daily temperature, precipitation, wind speed, sunshine duration, total solar radiation, and relative humidity data from 108 meteorological stations. The Penman-Monteith model, Mann-Kendall (M-K) test, moving t test, and Morlet wavelet method were used. The results indicated that ET0 and AI across the region displayed decreasing trends, but the former was significant. After 2000, regionally average trends in ET0 and AI increased rapidly, indicating that droughts increased over Southwest China in recent years. Spatially, the changes of ET0 and AI were dissimilar and not clustered, either. Temporally, both ET0 and AI displayed obvious abrupt change points over different timescales and that of AI was during the winter monsoon period. Significant periodic variations with periods of 27, 13, and 5 years were found in ET0, but only of 13 and 5 years existed in AI. Correlation analysis revealed that the sunshine duration and wind speed were the dominant factors affecting ET0 and that AI showed strong negative correlation with precipitation. The findings of this study enhance the understanding of the relationship between climate change and drought in Southwest China, while the mechanism controlling the variation in drought requires further study.

Alfvén ionization in an MHD-gas interactions code

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wilson, A. D.; Diver, D. A.

A numerical model of partially ionized plasmas is developed in order to capture their evolving ionization fractions as a result of Alfvén ionization (AI). The mechanism of, and the parameter regime necessary for, AI is discussed and an expression for the AI rate based on fluid parameters, from a gas-MHD model, is derived. This AI term is added to an existing MHD-gas interactions' code, and the result is a linear, 2D, two-fluid model that includes momentum transfer between charged and neutral species as well as an ionization rate that depends on the velocity fields of both fluids. The dynamics ofmore » waves propagating through such a partially ionized plasma are investigated, and it is found that AI has a significant influence on the fluid dynamics as well as both the local and global ionization fraction.« less

Combat sports practice favors bone mineral density among adolescent male athletes.

PubMed

Nasri, Raouf; Hassen Zrour, Saoussen; Rebai, Haithem; Neffeti, Fadoua; Najjar, Mohamed Fadhel; Bergaoui, Naceur; Mejdoub, Hafedh; Tabka, Zouhair

2015-01-01

The aim of this study was to determine the impact of combat sports practice on bone mineral density (BMD) and to analyze the relationship between bone parameters and anthropometric measurements, bone markers, and activity index (AI). In other words, to detect the most important determinant of BMD in the adolescent period among combat sports athletes. Fifty athletes engaged in combat sports, mean age 17.1±0.2 yr, were compared with 30 sedentary subjects who were matched for age, height, and pubertal stage. For all subjects, the whole-body BMD, lumbar spine BMD (L2-L4), and BMD in the pelvis, arms, and legs was measured by dual-energy X-ray absorptiometry, and anthropometric measurements were evaluated. Daily calcium intake, bone resorption, and formation markers were measured. BMD measurements were greater in the combat sports athletes than in the sedentary group (p<0.01). Weight, body mass index, and lean body mass were significantly correlated with BMD in different sites. Daily calcium consumption lower than daily calcium intake recommended in both athletes and sedentary group. AI was strongly correlated with all BMD measurements particularly with the whole body, legs, and arms. Negative correlations were observed between bone markers and BMD in different sites. The common major predictor of BMD measurements was AI (p<0.0001). AI associated to lean body mass determined whole-body BMD until 74%. AI explained both BMD in arms and L2-L4 at 25%. AI associated to height can account for 63% of the variance in BMD legs. These observations suggested that the best model predicting BMD in different sites among adolescent combat sports athletes was the AI. Children and adolescents should be encouraged to participate in combat sports to maximize their bone accrual. Copyright © 2015 The International Society for Clinical Densitometry. Published by Elsevier Inc. All rights reserved.

Adventures in supercomputing, a K-12 program in computational science: An assessment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oliver, C.E.; Hicks, H.R.; Iles-Brechak, K.D.

1994-10-01

In this paper, the authors describe only those elements of the Department of Energy Adventures in Supercomputing (AiS) program for high school teachers, such as school selection, which have a direct bearing on assessment. Schools submit an application to participate in the AiS program. They propose a team of at least two teachers to implement the AiS curriculum. The applications are evaluated by selection committees in each of the five participating states to determine which schools are the most qualified to carry out the program and reach a significant number of women, minorities, and economically disadvantaged students, all of whommore » have historically been underrepresented in the sciences. Typically, selected schools either have a large disadvantaged student population, or the applying teachers propose specific means to attract these segments of their student body into AiS classes. Some areas with AiS schools have significant numbers of minority students, some have economically disadvantaged, usually rural, students, and all areas have the potential to reach a higher proportion of women than technical classes usually attract. This report presents preliminary findings based on three types of data: demographic, student journals, and contextual. Demographic information is obtained for both students and teachers. Students have been asked to maintain journals which include replies to specific questions that are posed each month. An analysis of the answers to these questions helps to form a picture of how students progress through the course of the school year. Onsite visits by assessment professionals conducting student and teacher interviews, provide a more in depth, qualitative basis for understanding student motivations.« less

Variation characteristics and influences of climate factors on aridity index and its association with AO and ENSO in northern China from 1961 to 2012

NASA Astrophysics Data System (ADS)

Zhang, Kexin; Qian, Xiaoqing; Liu, Puxing; Xu, Yihong; Cao, Liguo; Hao, Yongpei; Dai, Shengpei

2017-10-01

Analyses of the variation characteristics for aridity index (AI) can further enhance the understanding of climate change and have effect on hydrology and agriculture. In this paper, based on the data of 283 standard meteorological stations, the temporal-spatial variations and the influences of climate factors on AI were investigated and the relationship between AI and two climate indices (the Arctic Oscillation (AO); El Nino-Southern Oscillation (ENSO)) were also assessed in northern China (NC) during the period from 1961 to 2012. The results revealed that the annual mean AI decreased at the rate of -0.031 per decade in the past 52 years and the trend was statistically significant at the 0.01 level. The Mann-Kendall (M-K) test presented that the percentages of stations with positive trends and negative trends for AI were 10 and 81.9 % (22.6 % statistically significant), respectively. Spatially, in the western part of 100° E, the extremely dry area declined and the climate tended to become wet obviously. In the eastern part of 100° E, dry area moved toward the east and the south, which resulted in the enhancement of semiarid area and the shrinkage of subhumid area. The contributions of sunshine duration and precipitation to the decline of AI are more than those of other meteorological variables in NC. Moreover, the average temperature has risen significantly and AI decreased in NC, which indicated the existence of "paradox." Relationship between climate indices (AO and ENSO) and AI demonstrated that the influence of ENSO on AI overweight the AO on AI in NC.

Fever Control Management Is Preferable to Mild Therapeutic Hypothermia in Traumatic Brain Injury Patients with Abbreviated Injury Scale 3-4: A Multi-Center, Randomized Controlled Trial.

PubMed

Hifumi, Toru; Kuroda, Yasuhiro; Kawakita, Kenya; Yamashita, Susumu; Oda, Yasutaka; Dohi, Kenji; Maekawa, Tsuyoshi

2016-06-01

In our prospective, multi-center, randomized controlled trial (RCT)-the Brain Hypothermia (B-HYPO) study-we could not show any difference on neurological outcomes in patients probably because of the heterogeneity in the severity of their traumatic condition. We therefore aimed to clarify and compare the effectiveness of the two therapeutic temperature management regimens in severe (Abbreviated Injury Scale [AIS] 3-4) or critical trauma patients (AIS 5). In the present post hoc B-HYPO study, we re-evaluated data based on the severity of trauma as AIS 3-4 or AIS 5 and compared Glasgow Outcome Scale score and mortality at 6 months by per-protocol analyses. Consequently, 135 patients were enrolled. Finally, 129 patients, that is, 47 and 31 patients with AIS 3-4 and 36 and 15 patients with AIS 5 were allocated to the mild therapeutic hypothermia (MTH) and fever control groups, respectively. No significant intergroup differences were observed with regard to age, gender, scores on head computed tomography (CT) scans, and surgical operation for traumatic brain injury (TBI), except for Injury Severity Score (ISS) in AIS 5. The fever control group demonstrated a significant reduction of TBI-related mortality compared with the MTH group (9.7% vs. 34.0%, p = 0.02) and an increase of favorable neurological outcomes (64.5% vs. 51.1%, p = 0.26) in patients with AIS 3-4, although the latter was not statistically significant. There was no difference in mortality or favorable outcome in patients with AIS 5. Fever control may be considered instead of MTH in patients with TBI (AIS 3-4).

Fever Control Management Is Preferable to Mild Therapeutic Hypothermia in Traumatic Brain Injury Patients with Abbreviated Injury Scale 3–4: A Multi-Center, Randomized Controlled Trial

PubMed Central

Kuroda, Yasuhiro; Kawakita, Kenya; Yamashita, Susumu; Oda, Yasutaka; Dohi, Kenji; Maekawa, Tsuyoshi

2016-01-01

Abstract In our prospective, multi-center, randomized controlled trial (RCT)—the Brain Hypothermia (B-HYPO) study—we could not show any difference on neurological outcomes in patients probably because of the heterogeneity in the severity of their traumatic condition. We therefore aimed to clarify and compare the effectiveness of the two therapeutic temperature management regimens in severe (Abbreviated Injury Scale [AIS] 3–4) or critical trauma patients (AIS 5). In the present post hoc B-HYPO study, we re-evaluated data based on the severity of trauma as AIS 3–4 or AIS 5 and compared Glasgow Outcome Scale score and mortality at 6 months by per-protocol analyses. Consequently, 135 patients were enrolled. Finally, 129 patients, that is, 47 and 31 patients with AIS 3–4 and 36 and 15 patients with AIS 5 were allocated to the mild therapeutic hypothermia (MTH) and fever control groups, respectively. No significant intergroup differences were observed with regard to age, gender, scores on head computed tomography (CT) scans, and surgical operation for traumatic brain injury (TBI), except for Injury Severity Score (ISS) in AIS 5. The fever control group demonstrated a significant reduction of TBI-related mortality compared with the MTH group (9.7% vs. 34.0%, p = 0.02) and an increase of favorable neurological outcomes (64.5% vs. 51.1%, p = 0.26) in patients with AIS 3–4, although the latter was not statistically significant. There was no difference in mortality or favorable outcome in patients with AIS 5. Fever control may be considered instead of MTH in patients with TBI (AIS 3–4). PMID:26413933

The Impact of a Sexual and Reproductive Health Intervention for American Indian Adolescents on Predictors of Condom Use Intention.

PubMed

Tingey, Lauren; Chambers, Rachel; Rosenstock, Summer; Lee, Angelita; Goklish, Novalene; Larzelere, Francene

2017-03-01

American Indian (AI) adolescents experience inequalities in sexual health, in particular, early sexual initiation. Condom use intention is an established predictor of condom use and is an important construct for evaluating interventions among adolescents who are not yet sexually active. This analysis evaluated the impact of Respecting the Circle of Life (RCL), a sexual and reproductive health intervention for AI adolescents, on predictors of condom use intention. We utilized a cluster randomized controlled trial design to evaluate RCL among 267 AIs ages 13-19. We examined baseline psychosocial and theoretical variables associated with condom use intention. Generalized estimating equation regression models determined which baseline variables predictive of condom use intention were impacted. Mean sample age was 15.1 years (standard deviation 1.7) and 56% were female; 22% had initiated sex. A larger proportion of RCL versus control participants had condom use intention post intervention (relative risk [RR] = 1.39, p = .008), especially younger (ages 13-15; RR = 1.42, p = .007) and sexually inexperienced adolescents (RR = 1.44, p = .01); these differences attenuated at additional follow-up. Baseline predictors of condom use intention included being sexually experienced, having condom use self-efficacy, as well as response efficacy and severity (both theoretical constructs). Of these, the RCL intervention significantly impacted condom use self-efficacy and response efficacy. Results demonstrate RCL intervention efficacy impacting variables predictive of condom use intention at baseline, with greater differences among younger, sexually inexperienced adolescents. To sustain intervention impact, future RCL implementation should reinforce education and training in condom use self-efficacy and response efficacy and recruit younger, sexually inexperienced AI adolescents. Copyright © 2016 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

A Genetic Test Predicts Providence Brace Success for Adolescent Idiopathic Scoliosis When Failure Is Defined as Progression to >45 Degrees.

PubMed

Bohl, Daniel D; Telles, Connor J; Ruiz, Ferrin K; Badrinath, Raghav; DeLuca, Peter A; Grauer, Jonathan N

2016-04-01

Retrospective cohort. To determine whether a genetic test is associated with successful Providence bracing for adolescent idiopathic scoliosis (AIS). Genetic factors have been defined that predict the risk of progression of AIS in a polygenic fashion. From these data, a commercially available genetic test, ScoliScore, was developed. It is now used in clinical practice for counseling and to guide clinical management. Bracing is a mainstay of treatment for AIS. Large efforts have been made recently to reduce potential confounding across studies of different braces; however, none of these have considered genetics as a potential confounder. In particular, ScoliScore has not been evaluated in a population undergoing bracing. We conducted a retrospective cohort study in which we identified a population of AIS patients who were initiated with Providence bracing and followed over time. Although these patients did not necessarily fit the commercial indications for ScoliScore, we contacted the patients and obtained a saliva sample from each for genetic analysis. We then tested whether ScoliScore correlated with the outcome of their bracing therapy. We were able to contact and invite 25 eligible subjects, of whom 16 (64.0%) returned samples for laboratory analysis. Patients were followed for an average of 2.3 years (range, 1.1-4 y) after initiation of the Providence brace. Eight patients (50.0%) progressed to >45 degrees, whereas the other 8 patients (50.0%) did not. The mean ScoliScore among those who progressed to >45 degrees was higher than that among those who did not (176 vs. 112, P=0.030). We demonstrate that a genetic test correlates with bracing outcome. It may be appropriate for future bracing studies to include analysis of genetic predisposition to limit potential confounding.

Tidal Analysis and Arrival Process Mining Using Automatic Identification System (AIS) Data

DTIC Science & Technology

2017-01-01

elevation at the time of vessel movement and calculating the tidal dependence (TD) parameter to 23 U.S. port areas for the years 2012– 2014. Tidal prediction...predictions, obtained from the National Oceanographic and Atmospheric Administration, are used to rank relative tidal dependence for arriving cargo and...sector traffic percentages and tidal dependence metric ............................. 11 Arrival process mining

Recognising promoter sequences using an artificial immune system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cooke, D.E.; Hunt, J.E.

1995-12-31

We have developed an artificial immune system (AIS) which is based on the human immune system. The AIS possesses an adaptive learning mechanism which enables antibodies to emerge which can be used for classification tasks. In this paper, we describe how the AIS has been used to evolve antibodies which can classify promoter containing and promoter negative DNA sequences. The DNA sequences used for teaching were 57 nucleotides in length and contained procaryotic promoters. The system classified previously unseen DNA sequences with an accuracy of approximately 90%.

Temporal variability of the Antarctic Ice sheet observed from space-based geodesy

NASA Astrophysics Data System (ADS)

Memin, A.; King, M. A.; Boy, J. P.; Remy, F.

2017-12-01

Quantifying the Antarctic Ice Sheet (AIS) mass balance still remains challenging as several processes compete to differing degrees at the basin scale with regional variations, leading to multiple mass redistribution patterns. For instance, analysis of linear trends in surface-height variations from 1992-2003 and 2002-2006 shows that the AIS is subject to decimetric scale variability over periods of a few years. Every year, snowfalls in Antarctica represent the equivalent of 6 mm of the mean sea level. Therefore, any fluctuation in precipitation can lead to changes in sea level. Besides, over the last decade, several major glaciers have been thinning at an accelerating rate. Understanding the processes that interact on the ice sheet is therefore important to precisely determine the response of the ice sheet to a rapid changing climate and estimate its contribution to sea level changes. We estimate seasonal and interannual changes of the AIS between January 2003 and October 2010 and to the end of 2016 from a combined analysis of surface-elevation and surface-mass changes derived from Envisat data and GRACE solutions, and from GRACE solutions only, respectively. While we obtain a good correlation for the interannual signal between the two techniques, important differences (in amplitude, phase, and spatial pattern) are obtained for the seasonal signal. We investigate these discrepancies by comparing the crustal motion observed by GPS and those predicted using monthly surface mass balance derived from the regional atmospheric climate model RACMO.

Associations between genetic variants and the effect of letrozole and exemestane on bone mass and bone turnover.

PubMed

Oesterreich, Steffi; Henry, N Lynn; Kidwell, Kelley M; Van Poznak, Catherine H; Skaar, Todd C; Dantzer, Jessica; Li, Lang; Hangartner, Thomas N; Peacock, Munro; Nguyen, Anne T; Rae, James M; Desta, Zeruesenay; Philips, Santosh; Storniolo, Anna M; Stearns, Vered; Hayes, Daniel F; Flockhart, David A

2015-11-01

Adjuvant therapy for hormone receptor (HR) positive postmenopausal breast cancer patients includes aromatase inhibitors (AI). While both the non-steroidal AI letrozole and the steroidal AI exemestane decrease serum estrogen concentrations, there is evidence that exemestane may be less detrimental to bone. We hypothesized that single nucleotide polymorphisms (SNP) predict effects of AIs on bone turnover. Early stage HR-positive breast cancer patients were enrolled in a randomized trial of exemestane versus letrozole. Effects of AI on bone mineral density (BMD) and bone turnover markers (BTM), and associations between SNPs in 24 candidate genes and changes in BMD or BTM were determined. Of the 503 enrolled patients, paired BMD data were available for 123 and 101 patients treated with letrozole and exemestane, respectively, and paired BTM data were available for 175 and 173 patients, respectively. The mean change in lumbar spine BMD was significantly greater for letrozole-treated (-3.2 %) compared to exemestane-treated patients (-1.0 %) (p = 0.0016). Urine N-telopeptide was significantly increased in patients treated with exemestane (p = 0.001) but not letrozole. Two SNPs (rs4870061 and rs9322335) in ESR1 and one SNP (rs10140457) in ESR2 were associated with decreased BMD in letrozole-treated patients. In the exemestane-treated patients, SNPs in ESR1 (Rs2813543) and CYP19A1 (Rs6493497) were associated with decreased bone density. Exemestane had a less negative impact on bone density compared to letrozole, and the effects of AI therapy on bone may be impacted by genetic variants in the ER pathway.

Phosphorylated neurofilament subunit NF-H as a biomarker for evaluating the severity of spinal cord injury patients, a pilot study.

PubMed

Hayakawa, K; Okazaki, R; Ishii, K; Ueno, T; Izawa, N; Tanaka, Y; Toyooka, S; Matsuoka, N; Morioka, K; Ohori, Y; Nakamura, K; Akai, M; Tobimatsu, Y; Hamabe, Y; Ogata, T

2012-07-01

A pilot cross-sectional study of patients with acute cervical spinal cord injury (SCI). The precise evaluation of the severity of SCI is important for developing novel therapies. Although several biomarkers in cerebrospinal fluid have been tested, few analyses of blood samples have been reported. A novel biomarker for axonal injury, phosphorylated form of the high-molecular-weight neurofilament subunit NF-H (pNF-H), has been reported to be elevated in blood from rodent SCI model. The aim of this study is to investigate whether pNF-H values in blood can serve as a biomarker to evaluate the severity of patients with SCI. Tokyo Metropolitan Bokutoh Hospital and National Rehabilitation Center, Japan. This study enrolled 14 patients with acute cervical SCI. Sequential plasma samples were obtained from 6 h to 21 days after injury. Patients were classified according to American Spinal Injury Association impairment scale (AIS) at the end of the follow-up (average, 229.1 days). Plasma pNF-H values were compared between different AIS grades. In patients with complete SCI, pNF-H became detectable at 12 h after injury and remained elevated at 21 days after injury. There was a statistically significant difference between AIS A (complete paralysis) patients and AIS C (incomplete paralysis) patients. Plasma pNF-H was elevated in accordance with the severity of SCI and reflected a greater magnitude of axonal damage. Therefore, pNF-H is a potential biomarker to independently distinguish AIS A patients (complete SCI) from AIS C-E patients (incomplete SCI). However, further studies are required to evaluate its utility in predicting prognosis of patients in the incomplete category.

Mission activities planning for a Hermes mission by means of AI-technology

NASA Technical Reports Server (NTRS)

Pape, U.; Hajen, G.; Schielow, N.; Mitschdoerfer, P.; Allard, F.

1993-01-01

Mission Activities Planning is a complex task to be performed by mission control centers. AI technology can offer attractive solutions to the planning problem. This paper presents the use of a new AI-based Mission Planning System for crew activity planning. Based on a HERMES servicing mission to the COLUMBUS Man Tended Free Flyer (MTFF) with complex time and resource constraints, approximately 2000 activities with 50 different resources have been generated, processed, and planned with parametric variation of operationally sensitive parameters. The architecture, as well as the performance of the mission planning system, is discussed. An outlook to future planning scenarios, the requirements, and how a system like MARS can fulfill those requirements is given.

Enabling Autonomous Space Mission Operations with Artificial Intelligence

NASA Technical Reports Server (NTRS)

Frank, Jeremy

2017-01-01

For over 50 years, NASA's crewed missions have been confined to the Earth-Moon system, where speed-of-light communications delays between crew and ground are practically nonexistent. This ground-centered mode of operations, with a large, ground-based support team, is not sustainable for NASAs future human exploration missions to Mars. Future astronauts will need smarter tools employing Artificial Intelligence (AI) techniques make decisions without inefficient communication back and forth with ground-based mission control. In this talk we will describe several demonstrations of astronaut decision support tools using AI techniques as a foundation. These demonstrations show that astronauts tasks ranging from living and working to piloting can benefit from AI technology development.

Stress Exposure and Physical, Mental, and Behavioral Health among American Indian Adults with Type 2 Diabetes.

PubMed

Walls, Melissa L; Sittner, Kelley J; Aronson, Benjamin D; Forsberg, Angie K; Whitbeck, Les B; al'Absi, Mustafa

2017-09-16

American Indian (AI) communities experience disproportionate exposure to stressors and health inequities including type 2 diabetes. Yet, we know little about the role of psychosocial stressors for AI diabetes-related health outcomes. We investigated associations between a range of stressors and psychological, behavioral, and physical health for AIs with diabetes. This community-based participatory research with 5 AI tribes includes 192 AI adult type 2 diabetes patients recruited from clinical records at tribal clinics. Data are from computer-assisted interviews and medical charts. We found consistent bivariate relationships between chronic to discrete stressors and mental and behavioral health outcomes; several remained even after accounting for participant age, gender, and income. Fewer stressors were linked to physical health. We also document a dose-response relationship between stress accumulation and worse health. Findings underscore the importance of considering a broad range of stressors for comprehensive assessment of stress burden and diabetes. Policies and practices aimed at reducing stress exposure and promoting tools for stress management may be mechanisms for optimal health for AI diabetes patients.

Circulating ESR1 mutations at the end of aromatase inhibitor adjuvant treatment and after relapse in breast cancer patients.

PubMed

Allouchery, Violette; Beaussire, Ludivine; Perdrix, Anne; Sefrioui, David; Augusto, Laetitia; Guillemet, Cécile; Sarafan-Vasseur, Nasrin; Di Fiore, Frédéric; Clatot, Florian

2018-05-16

Detection of circulating ESR1 mutations is associated with acquired resistance to aromatase inhibitor (AI) in metastatic breast cancer. Until now, the presence of circulating ESR1 mutations at the end of adjuvant treatment by AI in early breast cancer had never been clearly established. In this context, the aim of the present study was to evaluate the circulating ESR1 mutation frequency at the end of adjuvant treatment and after relapse. This monocentric retrospective study was based on available stored plasmas and included all early breast cancer patients who completed at least 2 years of AI adjuvant treatment and experienced a documented relapse after the end of their treatment. Circulating ESR1 mutations (D538G, Y537S/N/C) were assessed by droplet digital PCR in plasma samples taken at the end of adjuvant treatment, at time of relapse and at time of progression under first line metastatic treatment. A total of 42 patients were included, with a median adjuvant AI exposure of 60 months (range 41-85). No circulating ESR1 mutation was detectable at the end of AI adjuvant therapy. At first relapse, 5.3% of the patients (2/38) had a detectable circulating ESR1 mutation. At time of progression on first-line metastatic treatment, 33% of the patients (7/21) under AI had a detectable circulating ESR1 mutation compared to none of the patients under chemotherapy (0/10). The two patients with a detectable ESR1 mutation at relapse were treated by AI and had an increase of their variant allele fraction at time of progression on first-line metastatic treatment. Circulating ESR1 mutation detection at the end of AI-based adjuvant treatment is not clinically useful. Circulating ESR1 mutation could be assessed as soon as first relapse to guide interventional studies.

Substance Use Prevention for Urban American Indian Youth: A Efficacy Trial of the Culturally Adapted Living in 2 Worlds Program.

PubMed

Kulis, Stephen S; Ayers, Stephanie L; Harthun, Mary L

2017-04-01

This article describes a small efficacy trial of the Living in 2 Worlds (L2W) substance use prevention curriculum, a culturally adapted version of keepin' it REAL (kiR) redesigned for urban American Indian (AI) middle school students. Focused on strengthening resiliency and AI cultural engagement, L2W teaches drug resistance skills, decision making, and culturally grounded prevention messages. Using cluster random assignment, the research team randomized three urban middle schools with enrichment classes for AI students. AI teachers of these classes delivered the L2W curriculum in two schools; the remaining school implemented kiR, unadapted, and became the comparison group. AI students (N = 107) completed a pretest questionnaire before they received the manualized curriculum lessons, and a posttest (85% completion) 1 month after the final lesson. We assessed the adapted L2W intervention, compared to kiR, with paired t tests, baseline adjusted general linear models, and effect size estimates (Cohen's d). Differences between the L2W and kiR groups reached statistically significant thresholds for four outcomes. Youth receiving L2W, compared to kiR, reported less growth in cigarette use from pretest to posttest, less frequent use of the Leave drug resistance strategy, and less loss of connections to AI spirituality and cultural traditions. For other substance use behaviors and antecedents, the direction of the non-significant effects in small sample tests was toward more positive outcomes in L2W and small to medium effect sizes. Results suggest that evidence-based substance use prevention programs that are culturally adapted for urban AI adolescents, like L2W, can be a foundation for prevention approaches to help delay initiation and slow increases in substance use. In addition to study limitations, we discuss implementation challenges in delivering school-based interventions for urban AI populations.

Allergy-immunology practice parameters and strength of recommendation data: an evolutionary perspective.

PubMed

Park, Matthew H; Banks, Taylor A; Nelson, Michael R

2016-03-01

The practice parameters for allergy and immunology (A/I) are a valuable tool guiding practitioners' clinical practice. The A/I practice parameters have evolved over time in the context of evidence-based medicine milestones. To identify evolutionary trends in the character, scope, and evidence underlying recommendations in the A/I practice parameters. Practice parameters that have guided A/I from 1995 through 2014 were analyzed. Statements and recommendations with strength of recommendation categories A and B were considered to have a basis in evidence from controlled trials. Forty-three publications and updates covering 25 unique topics were identified. There was great variability in the number of recommendations made and the proportion of statements with controlled trial evidence. The mean number of recommendations made per practice parameter has decreased significantly, from 95.8 to a mean of 38.3. There also is a trend toward an increased proportion of recommendations based on controlled trial evidence in practice parameters with fewer recommendations, with a mean of 30.7% in practice parameters with at least 100 recommendations based on controlled trial evidence compared with 48.3% in practice parameters with 30 to 100 recommendations and 51.0% in those with fewer than 30 recommendations. The A/I practice parameters have evolved significantly over time. Encouragingly, greater controlled trial evidence is associated with updated practice parameters and a recent trend of more narrowly focused topics. These findings should only bolster and inspire confidence in the utility of the A/I practice parameters in assisting practitioners to navigate through the uncertainty that is intrinsic to medicine in making informed decisions with patients. Published by Elsevier Inc.

2H2O-Based HDL Turnover Method for the Assessment of Dynamic HDL Function in Mice

PubMed Central

Kasumov, Takhar; Willard, Belinda; Li, Ling; Li, Min; Conger, Heather; Buffa, Jennifer A.; Previs, Stephen; McCullough, Arthur; Hazen, Stanley L.; Smith, Jonathan D.

2014-01-01

Objective High-density lipoprotein (HDL) promotes reverse cholesterol transport (RCT) from peripheral tissues to the liver for clearance. Reduced HDL-cholesterol (HDLc) is associated with atherosclerosis; however, as a predictor of cardiovascular disease, HDLc has limitations as it is not a direct marker of HDL functionality. Our objective was to develop a mass spectrometry based method for the simultaneous measurement of HDLc and ApoAI kinetics in mice using a single 2H2O tracer, and use it to examine genetic and drug perturbations on HDL turnover in vivo. Approach and Results Mice were given 2H2O in the drinking water and serial blood samples were collected at different time points. HDLc and ApoAI gradually incorporated 2H, allowing experimental measurement of fractional catabolic rates (FCR) and production rates (PR) for HDLc and ApoA1. ApoE−/− mice displayed increased FCR (p<0.01) and reduced PR of both HDLc and ApoAI (p<0.05) compared to controls. In human ApoAI transgenic mice, levels and PRs of HDLc and human ApoAI were strikingly higher than in wild type mice. Myriocin, an inhibitor of sphingolipid synthesis, significantly increased both HDL flux and macrophage-to-feces RCT, indicating compatibility of this HDL turnover method with the macrophage specific RCT assay. Conclusions 2H2O-labeling can be used to measure HDLc and ApoAI flux in vivo, and to assess the role of genetic and pharmacological interventions on HDL turnover in mice. Safety, simplicity, and low cost of the 2H2O-based HDL turnover approach suggest that this assay can be scaled for human use to study effects of HDL targeted therapies on dynamic HDL function. PMID:23766259

Neck injury criteria formulation and injury risk curves for the ejection environment: a pilot study.

PubMed

Parr, Jeffrey C; Miller, Michael E; Pellettiere, Joseph A; Erich, Roger A

2013-12-01

Helmet mounted displays provide increased pilot capability, but can also increase the risk of injury during ejection. The National Highway Transportation Safety Administration's (NHTSA's) neck injury criteria (Nij) metric is evaluated for understanding the impact of helmet mass on the risk of injury and modified risk curves are developed which are compatible with the needs of the aviation community. Existent human subject data collected under various accelerative and head loading conditions were applied to understand the sensitivity of the Nij construct to changes in acceleration and helmet mass, as well as its stability with respect to gender, body mass, neck circumference, and sitting height. A portion of this data was combined with data from an earlier postmortem human subject study to create pilot study modified risk curves. These curves were compared and contrasted with the NHTSA risk curves. A statistically significant difference in the peak mean Nij was observed when seat acceleration increased by 2 G, but not when helmet mass was varied from 1.6 kg to 2 kg at a constant seat acceleration of 8 G. Although NHTSA risk curves predict a 13% risk of AIS 2+ injury for the 8-G, 2-kg helmet condition mean Nij of 0.138, no AIS 2+ injuries were observed. Modified risk curves were produced which predict a 0.91% risk of AIS 2+ injury under these conditions. The Nij was shown to be sensitive to changes in acceleration and generally robust to anthropometric differences between individuals. Modified risk curves are proposed which improve risk prediction at lower Nij values.

Conjunction of wavelet transform and SOM-mutual information data pre-processing approach for AI-based Multi-Station nitrate modeling of watersheds

NASA Astrophysics Data System (ADS)

Nourani, Vahid; Andalib, Gholamreza; Dąbrowska, Dominika

2017-05-01

Accurate nitrate load predictions can elevate decision management of water quality of watersheds which affects to environment and drinking water. In this paper, two scenarios were considered for Multi-Station (MS) nitrate load modeling of the Little River watershed. In the first scenario, Markovian characteristics of streamflow-nitrate time series were proposed for the MS modeling. For this purpose, feature extraction criterion of Mutual Information (MI) was employed for input selection of artificial intelligence models (Feed Forward Neural Network, FFNN and least square support vector machine). In the second scenario for considering seasonality-based characteristics of the time series, wavelet transform was used to extract multi-scale features of streamflow-nitrate time series of the watershed's sub-basins to model MS nitrate loads. Self-Organizing Map (SOM) clustering technique which finds homogeneous sub-series clusters was also linked to MI for proper cluster agent choice to be imposed into the models for predicting the nitrate loads of the watershed's sub-basins. The proposed MS method not only considers the prediction of the outlet nitrate but also covers predictions of interior sub-basins nitrate load values. The results indicated that the proposed FFNN model coupled with the SOM-MI improved the performance of MS nitrate predictions compared to the Markovian-based models up to 39%. Overall, accurate selection of dominant inputs which consider seasonality-based characteristics of streamflow-nitrate process could enhance the efficiency of nitrate load predictions.

Modeling the binding affinity of structurally diverse industrial chemicals to carbon using the artificial intelligence approaches.

PubMed

Gupta, Shikha; Basant, Nikita; Rai, Premanjali; Singh, Kunwar P

2015-11-01

Binding affinity of chemical to carbon is an important characteristic as it finds vast industrial applications. Experimental determination of the adsorption capacity of diverse chemicals onto carbon is both time and resource intensive, and development of computational approaches has widely been advocated. In this study, artificial intelligence (AI)-based ten different qualitative and quantitative structure-property relationship (QSPR) models (MLPN, RBFN, PNN/GRNN, CCN, SVM, GEP, GMDH, SDT, DTF, DTB) were established for the prediction of the adsorption capacity of structurally diverse chemicals to activated carbon following the OECD guidelines. Structural diversity of the chemicals and nonlinear dependence in the data were evaluated using the Tanimoto similarity index and Brock-Dechert-Scheinkman statistics. The generalization and prediction abilities of the constructed models were established through rigorous internal and external validation procedures performed employing a wide series of statistical checks. In complete dataset, the qualitative models rendered classification accuracies between 97.04 and 99.93%, while the quantitative models yielded correlation (R(2)) values of 0.877-0.977 between the measured and the predicted endpoint values. The quantitative prediction accuracies for the higher molecular weight (MW) compounds (class 4) were relatively better than those for the low MW compounds. Both in the qualitative and quantitative models, the Polarizability was the most influential descriptor. Structural alerts responsible for the extreme adsorption behavior of the compounds were identified. Higher number of carbon and presence of higher halogens in a molecule rendered higher binding affinity. Proposed QSPR models performed well and outperformed the previous reports. A relatively better performance of the ensemble learning models (DTF, DTB) may be attributed to the strengths of the bagging and boosting algorithms which enhance the predictive accuracies. The proposed AI models can be useful tools in screening the chemicals for their binding affinities toward carbon for their safe management.

Overcoming barriers to population-based injury research: development and validation of an ICD-10–to–AIS algorithm

PubMed Central

Haas, Barbara; Xiong, Wei; Brennan-Barnes, Maureen; Gomez, David; Nathens, Avery B.

2012-01-01

Background Hospital administrative databases are a useful source of population-level data on injured patients; however, these databases use the International Classification of Diseases (ICD) system, which does not provide a direct means of estimating injury severity. We created and validated a crosswalk to derive Abbreviated Injury Scale (AIS) scores from injury-related diagnostic codes in the tenth revision of the ICD (ICD-10). Methods We assessed the validity of the crosswalk using data from the Ontario Trauma Registry Comprehensive Data Set (OTR-CDS). The AIS and Injury Severity Scores (ISS) derived using the algorithm were compared with those assigned by expert abstractors. We evaluated the ability of the algorithm to identify patients with AIS scores of 3 or greater. We used κ and intraclass correlation coefficients (ICC) as measures of concordance. Results In total, 10 431 patients were identified in the OTR-CDS. The algorithm accurately identified patients with at least 1 AIS score of 3 or greater (κ 0.65), as well as patients with a head AIS score of 3 or greater (κ 0.78). Mapped and abstracted ISS were similar; ICC across the entire cohort was 0.83 (95% confidence interval 0.81–0.84), indicating good agreement. When comparing mapped and abstracted ISS, the difference between scores was 10 or less in 87% of patients. Concordance between mapped and abstracted ISS was similar across strata of age, mechanism of injury and mortality. Conclusion Our ICD-10–to–AIS algorithm produces reliable estimates of injury severity from data available in administrative databases. This algorithm can facilitate the use of administrative data for population-based injury research in jurisdictions using ICD-10. PMID:22269308

Overcoming barriers to population-based injury research: development and validation of an ICD10-to-AIS algorithm.

PubMed

Haas, Barbara; Xiong, Wei; Brennan-Barnes, Maureen; Gomez, David; Nathens, Avery B

2012-02-01

Hospital administrative databases are a useful source of population-level data on injured patients; however, these databases use the International Classification of Diseases (ICD) system, which does not provide a direct means of estimating injury severity. We created and validated a crosswalk to derive Abbreviated Injury Scale (AIS) scores from injury-related diagnostic codes in the tenth revision of the ICD (ICD-10). We assessed the validity of the crosswalk using data from the Ontario Trauma Registry Comprehensive Data Set (OTRCDS). The AIS and Injury Severity Scores (ISS) derived using the algorithm were compared with those assigned by expert abstractors. We evaluated the ability of the algorithm to identify patients with AIS scores of 3 or greater. We used κ and intraclass correlation coefficients (ICC) as measures of concordance. In total, 10 431 patients were identified in the OTRCDS. The algorithm accurately identified patients with at least 1 AIS score of 3 or greater (κ 0.65), as well as patients with a head AIS score of 3 or greater (κ 0.78). Mapped and abstracted ISS were similar; ICC across the entire cohort was 0.83 (95% confidence interval 0.81-0.84), indicating good agreement. When comparing mapped and abstracted ISS, the difference between scores was 10 or less in 87% of patients. Concordance between mapped and abstracted ISS was similar across strata of age, mechanism of injury and mortality. Our ICD-10-to-AIS algorithm produces reliable estimates of injury severity from data available in administrative databases. This algorithm can facilitate the use of administrative data for population-based injury research in jurisdictions using ICD-10.

Disparities of Cancer Incidence in Michigan’s American Indians: Spotlight on Breast Cancer

PubMed Central

Roen, Emily L.; Copeland, Glenn E.; Pinagtore, Noel L.; Meza, Rafael; Soliman, Amr S.

2014-01-01

Introduction In American Indians (AI), cancer is a leading cause of mortality, yet their disease burden is not fully understood due to unaddressed racial misclassification in cancer registries. This study describes cancer trends among AIs in Michigan, focusing on breast cancer, in a linked data set of Indian Health Service (IHS), tribal and state cancer registry data adjusted for misclassification. Methods AI status was based upon reported race and linkage to IHS data and tribal registries. Data with complete linkage on all incident cancer cases in Michigan from 1995-2004 was used to calculate age-standardized incidence estimates for invasive all-site and female breast cancers stratified by racial group. For female breast cancers, stage and age-specific incidence and percent distributions of early versus late-stage cancers and age of diagnosis were calculated. Results Over 50% of all AI cases were identified through IHS and/or tribal linkage. In the linked data, AIs had the lowest rates of all-sites and breast cancer. For breast cancers, AI women had a greater late-stage cancer burden and a younger mean age of diagnosis as compared to whites. Although the age-specific rate for whites was greater than for AI women in nearly all age groups, the difference in hazard ratio increased with increasing age. Conclusions Our state-specific information will help formulate effective, tailored cancer prevention strategies to this population in Michigan. The data linkages used in our study are crucial for generating accurate rates and can be effective in addressing misclassification of the AI population and formulating cancer prevention strategies for AI nationwide. PMID:24676851

Reconsidering American Indian historical trauma: lessons from an early Gros Ventre war narrative.

PubMed

Gone, Joseph P

2014-06-01

Professional clinicians and human services providers are increasingly attributing the mental health problems of American Indians (AIs) to historical trauma (HT). As an alternative to established psychiatric disorders, AI HT was formulated to explain enduring mental health disparities as originating in tribal experiences of Euro-American colonization. As a result, AI HT has been described as the collective, cumulative, and intergenerational psychosocial disability resulting from massive group-based oppression, such as forced relocation, political subjugation, cultural domination, and genocide. One objective of the HT construct is to frame AI distress and dysfunction in social and historical terms. Given widespread indigenous experiences of colonization, the debilitating effects of HT are presumed to affect most AI communities today. With this background in mind, I explore AI HT with specific reference to a "war narrative" obtained by an anthropologist in 1901 from an elderly Gros Ventre woman. In this account, Watches All described her participation in a historic intertribal battle, and her subsequent captivity and escape from the enemy during the late 1860s. This historical narrative references many first-hand experiences that would today be identified as traumatogenic. Interestingly, however, this account complicates several assumptions underlying AI HT, leading to vexing questions of whether Watches All's ordeal actually qualifies as an instance of AI HT. No matter how one answers these questions, such ambiguity highlights serious theoretical confusions requiring elaboration and refinement if AI HT is to remain a useful construct in the behavioral health sciences. © The Author(s) 2013 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Successful Targeted Therapies for Breast Cancer, The Worcester Foundation and Future Opportunities in Women's Health.

PubMed

Abderrahman, Balkees; Jordan, V Craig

2018-06-19

The signing of the National Cancer Act in 1971, was designed to take laboratory discoveries rapidly from the bench to the bedside. A "war on cancer" had been declared. Combination cytotoxic chemotherapy was predicted to cure all cancers based on the stunning success in treating childhood leukemia. Breast cancer treatments were primitive; radical mastectomy and radiation was standard of care for disease that had not spread. Ablative endocrine surgery (oophorectomy, hypophysectomy, and adrenalectomy) was a palliative last option for metastatic breast cancer. However, only 30% responded for a year or two: everybody died. The discovery of the estrogen receptor (ER), and translation to breast cancer treatment triggered a revolution in women's health. Two important, but interconnected events occurred at the Worcester Foundation for Experimental Biology (WFEB), which would exploit the breast tumor ER as the first target to save lives and prevent breast cancer development. Two new groups of medicines: Selective Estrogen Receptor Modulators (SERMs) and aromatase inhibitors (AIs) would continue the momentum of research at the WFEB to improve women's health. Here we recount the important progress made in women's health based upon knowledge of the endocrinology of breast cancer. We propose future opportunities in SERM therapeutics to "refresh" the current standards of care for breast cancer treatment. The opportunity is based upon emerging knowledge about acquired resistance to long term adjuvant AI therapy used to treat breast cancer.

Adolescent idiopathic scoliosis screening for school, community, and clinical health promotion practice utilizing the PRECEDE-PROCEED model

PubMed Central

Mirtz, Timothy A; Thompson, Mark A; Greene, Leon; Wyatt, Lawrence A; Akagi, Cynthia G

2005-01-01

Background Screening for adolescent idiopathic scoliosis (AIS) is a commonly performed procedure for school children during the high risk years. The PRECEDE-PROCEDE (PP) model is a health promotion planning model that has not been utilized for the clinical diagnosis of AIS. The purpose of this research is to study AIS in the school age population using the PP model and its relevance for community, school, and clinical health promotion. Methods MEDLINE was utilized to locate AIS data. Studies were screened for relevance and applicability under the auspices of the PP model. Where data was unavailable, expert opinion was utilized based on consensus. Results The social assessment of quality of life is limited with few studies approaching the long-term effects of AIS. Epidemiologically, AIS is the most common form of scoliosis and leading orthopedic problem in children. Behavioral/environmental studies focus on discovering etiologic relationships yet this data is confounded because AIS is not a behavioral. Illness and parenting health behaviors can be appreciated. The educational diagnosis is confounded because AIS is an orthopedic disorder and not behavioral. The administration/policy diagnosis is hindered in that scoliosis screening programs are not considered cost-effective. Policies are determined in some schools because 26 states mandate school scoliosis screening. There exists potential error with the Adam's test. The most widely used measure in the PP model, the Health Belief Model, has not been utilized in any AIS research. Conclusion The PP model is a useful tool for a comprehensive study of a particular health concern. This research showed where gaps in AIS research exist suggesting that there may be problems to the implementation of school screening. Until research disparities are filled, implementation of AIS screening by school, community, and clinical health promotion will be compromised. Lack of data and perceived importance by school/community health planners may influence clinical health promotion practices. PMID:16318632

Integrating NASA Earth Science Enterprise (ESE) Data Into Global Agricultural Decision Support Systems

NASA Astrophysics Data System (ADS)

Teng, W.; Kempler, S.; Chiu, L.; Doraiswamy, P.; Liu, Z.; Milich, L.; Tetrault, R.

2003-12-01

Monitoring global agricultural crop conditions during the growing season and estimating potential seasonal production are critically important for market development of U.S. agricultural products and for global food security. Two major operational users of satellite remote sensing for global crop monitoring are the USDA Foreign Agricultural Service (FAS) and the U.N. World Food Programme (WFP). The primary goal of FAS is to improve foreign market access for U.S. agricultural products. The WFP uses food to meet emergency needs and to support economic and social development. Both use global agricultural decision support systems that can integrate and synthesize a variety of data sources to provide accurate and timely information on global crop conditions. The Goddard Space Flight Center Earth Sciences Distributed Active Archive Center (GES DAAC) has begun a project to provide operational solutions to FAS and WFP, by fully leveraging results from previous work, as well as from existing capabilities of the users. The GES DAAC has effectively used its recently developed prototype TRMM Online Visualization and Analysis System (TOVAS) to provide ESE data and information to the WFP for its agricultural drought monitoring efforts. This prototype system will be evolved into an Agricultural Information System (AIS), which will operationally provide ESE and other data products (e.g., rainfall, land productivity) and services, to be integrated into and thus enhance the existing GIS-based, decision support systems of FAS and WFP. Agriculture-oriented, ESE data products (e.g., MODIS-based, crop condition assessment product; TRMM derived, drought index product) will be input to a crop growth model in collaboration with the USDA Agricultural Research Service, to generate crop condition and yield prediction maps. The AIS will have the capability for remotely accessing distributed data, by being compliant with community-based interoperability standards, enabling easy access to agriculture-related products from other data producers. The AIS? system approach will provide a generic mechanism for easily incorporating new products and making them accessible to users.

Laser-Based Fuel Cell Manufacturing for Thermal Management

DTIC Science & Technology

2005-10-12

r IMITA T O 6 1 i I1 .114 141-" n. 14 F . I #1 l i f II 0I0 1(P ,1 L P ER I II I U-ABSTRACT- ------- U inr I L nEron ; . A , wl "t . Tills rAI Ou 1 0...concentration is too low to form a connecting network of conductive sites. On the other hand, the material undergoes a sharp transition from...carbon black loading due to the development of a network of closely-seated CB particles. The predicted very high electrical resistivity for 1 and 2 Vol

A tool for modeling concurrent real-time computation

NASA Technical Reports Server (NTRS)

Sharma, D. D.; Huang, Shie-Rei; Bhatt, Rahul; Sridharan, N. S.

1990-01-01

Real-time computation is a significant area of research in general, and in AI in particular. The complexity of practical real-time problems demands use of knowledge-based problem solving techniques while satisfying real-time performance constraints. Since the demands of a complex real-time problem cannot be predicted (owing to the dynamic nature of the environment) powerful dynamic resource control techniques are needed to monitor and control the performance. A real-time computation model for a real-time tool, an implementation of the QP-Net simulator on a Symbolics machine, and an implementation on a Butterfly multiprocessor machine are briefly described.

Decision Aids for Airborne Intercept Operations in Advanced Aircrafts

NASA Technical Reports Server (NTRS)

Madni, A.; Freedy, A.

1981-01-01

A tactical decision aid (TDA) for the F-14 aircrew, i.e., the naval flight officer and pilot, in conducting a multitarget attack during the performance of a Combat Air Patrol (CAP) role is presented. The TDA employs hierarchical multiattribute utility models for characterizing mission objectives in operationally measurable terms, rule based AI-models for tactical posture selection, and fast time simulation for maneuver consequence prediction. The TDA makes aspect maneuver recommendations, selects and displays the optimum mission posture, evaluates attackable and potentially attackable subsets, and recommends the 'best' attackable subset along with the required course perturbation.

Methodology Investigation of AI Test Officer Support Tool II

DTIC Science & Technology

1989-10-01

request. B-1 This page intentionally blank B-2 APPENDIX C. ACRONYM AND AB9EVIATIONS ADP ............ Autmated Data Processing AI...longer needed. Do not return it to the originator. DISCLAIMER Information and data contained in this document are based on input available at the time...infrastructure, with subsequent incorporation of common requirements into a supporting structure (i.e., data bases, networks, geographic information

Feasibility, Acceptability, and Initial Findings from a Community-Based Cultural Mental Health Intervention for American Indian Youth and Their Families

ERIC Educational Resources Information Center

Goodkind, Jessica; LaNoue, Marianna; Lee, Christopher; Freeland, Lance; Freund, Rachel

2012-01-01

Through a CBPR partnership, university and American Indian (AI) tribal members developed and tested "Our Life" intervention to promote mental health of AI youth and their families by addressing root causes of violence, trauma, and substance abuse. Based on premises that well-being is built on a foundation of traditional cultural beliefs and…

Integrating an automated activity monitor into an artificial insemination program and the associated risk factors affecting reproductive performance of dairy cows.

PubMed

Burnett, Tracy A; Madureira, Augusto M L; Silper, Bruna F; Fernandes, A C C; Cerri, Ronaldo L A

2017-06-01

The aim of this study was to compare 2 reproductive programs for the management of first postpartum artificial insemination (AI) based on activity monitors and timed AI, as well as to determine the effect of health-related factors on detection and expression of estrus. Lactating Holstein cows (n = 918) from 2 commercial farms were enrolled. Estrous cycles of all cows were presynchronized with 2 injections of PGF 2α administered 2 wk apart. Treatments were (1) first insemination performed by timed AI (TAI) and (2) first insemination based upon the detection of estrus by activity monitors (ACT; Heatime, SCR Engineering, Netanya, Israel) after the presynchronization, whereas cows not inseminated by the detection of estrus were enrolled in the Ovsynch protocol. Body condition score (BCS; scale 1 to 5), hock score (scale: 1 to 4), gait score (scale: 1 to 4), and corpus luteum presence detected by ovarian ultrasonography were recorded twice during the presynchronization. On the ACT treatment, 50.5% of cows were inseminated based on detected estrus, whereas 83.2% of the cows on the TAI treatment were inseminated appropriately after the timed AI protocol. Pregnancy per AI did not differ by treatment (30.8 vs. 33.5% for ACT and TAI, respectively). Success of pregnancy was affected by parity, cyclicity, BCS, milk production, and a tendency for leg health. In addition, treatment × cyclicity and treatment × parity interactions were found to affect pregnancy success, where anovulatory cows and older cows had compromised pregnancy outcomes on the ACT treatment but not on the TAI treatment. Factors affecting pregnancy outcomes varied among farms. Hazard of pregnancy by 300 DIM was affected by farm, parity, BCS, a treatment × cyclicity interaction, and a tendency for an interaction between leg health and farm. Detection of estrus was affected by farm, parity, cyclicity, and leg health, but not BCS or milk production. Expression of estrus was compromised in anovular and older cows, and by the timing of the estrus event, but not by gait score, BCS, or milk production. Increased duration of estrus, but not intensity of estrus, improved pregnancy per AI. In conclusion, using an automated activity monitor for the detection of estrus within a Presynch-Ovsynch program resulted in similar pregnancy per AI and days open compared with a reproduction program that was strictly based on timed AI for first postpartum AI. In contrast, notable variations in reproductive outcomes were detected between farms, suggesting that the use of automated activity monitors is prone to individual farm management. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

The benefits and tradeoffs for varied high-severity injury risk thresholds for advanced automatic crash notification systems.

PubMed

Bahouth, George; Graygo, Jill; Digges, Kennerly; Schulman, Carl; Baur, Peter

2014-01-01

The objectives of this study are to (1) characterize the population of crashes meeting the Centers for Disease Control and Prevention (CDC)-recommended 20% risk of Injury Severity Score (ISS)>15 injury and (2) explore the positive and negative effects of an advanced automatic crash notification (AACN) system whose threshold for high-risk indications is 10% versus 20%. Binary logistic regression analysis was performed to predict the occurrence of motor vehicle crash injuries at both the ISS>15 and Maximum Abbreviated Injury Scale (MAIS) 3+ level. Models were trained using crash characteristics recommended by the CDC Committee on Advanced Automatic Collision Notification and Triage of the Injured Patient. Each model was used to assign the probability of severe injury (defined as MAIS 3+ or ISS>15 injury) to a subset of NASS-CDS cases based on crash attributes. Subsequently, actual AIS and ISS levels were compared with the predicted probability of injury to determine the extent to which the seriously injured had corresponding probabilities exceeding the 10% and 20% risk thresholds. Models were developed using an 80% sample of NASS-CDS data from 2002 to 2012 and evaluations were performed using the remaining 20% of cases from the same period. Within the population of seriously injured (i.e., those having one or more AIS 3 or higher injuries), the number of occupants whose injury risk did not exceed the 10% and 20% thresholds were estimated to be 11,700 and 18,600, respectively, each year using the MAIS 3+ injury model. For the ISS>15 model, 8,100 and 11,000 occupants sustained ISS>15 injuries yet their injury probability did not reach the 10% and 20% probability for severe injury respectively. Conversely, model predictions suggested that, at the 10% and 20% thresholds, 207,700 and 55,400 drivers respectively would be incorrectly flagged as injured when their injuries had not reached the AIS 3 level. For the ISS>15 model, 87,300 and 41,900 drivers would be incorrectly flagged as injured when injury severity had not reached the ISS>15 injury level. This article provides important information comparing the expected positive and negative effects of an AACN system with thresholds at the 10% and 20% levels using 2 outcome metrics. Overall, results suggest that the 20% risk threshold would not provide a useful notification to improve the quality of care for a large number of seriously injured crash victims. Alternately, a lower threshold may increase the over triage rate. Based on the vehicle damage observed for crashes reaching and exceeding the 10% risk threshold, we anticipate that rescue services would have been deployed based on current Public Safety Answering Point (PSAP) practices.

Dissociable Fronto-Operculum-Insula Control Signals for Anticipation and Detection of Inhibitory Sensory Cue.

PubMed

Cai, Weidong; Chen, Tianwen; Ide, Jaime S; Li, Chiang-Shan R; Menon, Vinod

2017-08-01

The ability to anticipate and detect behaviorally salient stimuli is important for virtually all adaptive behaviors, including inhibitory control that requires the withholding of prepotent responses when instructed by external cues. Although right fronto-operculum-insula (FOI), encompassing the anterior insular cortex (rAI) and inferior frontal cortex (rIFC), involvement in inhibitory control is well established, little is known about signaling mechanisms underlying their differential roles in detection and anticipation of salient inhibitory cues. Here we use 2 independent functional magnetic resonance imaging data sets to investigate dynamic causal interactions of the rAI and rIFC, with sensory cortex during detection and anticipation of inhibitory cues. Across 2 different experiments involving auditory and visual inhibitory cues, we demonstrate that primary sensory cortex has a stronger causal influence on rAI than on rIFC, suggesting a greater role for the rAI in detection of salient inhibitory cues. Crucially, a Bayesian prediction model of subjective trial-by-trial changes in inhibitory cue anticipation revealed that the strength of causal influences from rIFC to rAI increased significantly on trials in which participants had higher anticipation of inhibitory cues. Together, these results demonstrate the dissociable bottom-up and top-down roles of distinct FOI regions in detection and anticipation of behaviorally salient cues across multiple sensory modalities. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Knowledge-based geographic information systems (KBGIS): New analytic and data management tools

USGS Publications Warehouse

Albert, T.M.

1988-01-01

In its simplest form, a geographic information system (GIS) may be viewed as a data base management system in which most of the data are spatially indexed, and upon which sets of procedures operate to answer queries about spatial entities represented in the data base. Utilization of artificial intelligence (AI) techniques can enhance greatly the capabilities of a GIS, particularly in handling very large, diverse data bases involved in the earth sciences. A KBGIS has been developed by the U.S. Geological Survey which incorporates AI techniques such as learning, expert systems, new data representation, and more. The system, which will be developed further and applied, is a prototype of the next generation of GIS's, an intelligent GIS, as well as an example of a general-purpose intelligent data handling system. The paper provides a description of KBGIS and its application, as well as the AI techniques involved. ?? 1988 International Association for Mathematical Geology.

A comparative study of artificial intelligent-based maximum power point tracking for photovoltaic systems

NASA Astrophysics Data System (ADS)

Hussain Mutlag, Ammar; Mohamed, Azah; Shareef, Hussain

2016-03-01

Maximum power point tracking (MPPT) is normally required to improve the performance of photovoltaic (PV) systems. This paper presents artificial intelligent-based maximum power point tracking (AI-MPPT) by considering three artificial intelligent techniques, namely, artificial neural network (ANN), adaptive neuro fuzzy inference system with seven triangular fuzzy sets (7-tri), and adaptive neuro fuzzy inference system with seven gbell fuzzy sets. The AI-MPPT is designed for the 25 SolarTIFSTF-120P6 PV panels, with the capacity of 3 kW peak. A complete PV system is modelled using 300,000 data samples and simulated in the MATLAB/SIMULINK. The AI-MPPT has been tested under real environmental conditions for two days from 8 am to 18 pm. The results showed that the ANN based MPPT gives the most accurate performance and then followed by the 7-tri-based MPPT.

[Fundamental aspects for accrediting medical equipment calibration laboratories in Colombia].

PubMed

Llamosa-Rincón, Luis E; López-Isaza, Giovanni A; Villarreal-Castro, Milton F

2010-02-01

Analysing the fundamental methodological aspects which should be considered when drawing up calibration procedure for electro-medical equipment, thereby permitting international standard-based accreditation of electro-medical metrology laboratories in Colombia. NTC-ISO-IEC 17025:2005 and GTC-51-based procedures for calibrating electro-medical equipment were implemented and then used as patterns. The mathematical model for determining the estimated uncertainty value when calibrating electro-medical equipment for accreditation by the Electrical Variable Metrology Laboratory's Electro-medical Equipment Calibration Area accredited in compliance with Superintendence of Industry and Commerce Resolution 25771 May 26th 2009 consists of two equations depending on the case; they are: E = (Ai + sigmaAi) - (Ar + sigmaAr + deltaAr1) and E = (Ai + sigmaAi) - (Ar + sigmaA + deltaAr1). The mathematical modelling implemented for measuring uncertainty in the Universidad Tecnológica de Pereira's Electrical Variable Metrology Laboratory (Electro-medical Equipment Calibration Area) will become a good guide for calibration initiated in other laboratories in Colombia and Latin-America.

SAR-based sea traffic monitoring: a reliable approach for maritime surveillance

NASA Astrophysics Data System (ADS)

Renga, Alfredo; Graziano, Maria D.; D'Errico, M.; Moccia, A.; Cecchini, A.

2011-11-01

Maritime surveillance problems are drawing the attention of multiple institutional actors. National and international security agencies are interested in matters like maritime traffic security, maritime pollution control, monitoring migration flows and detection of illegal fishing activities. Satellite imaging is a good way to identify ships but, characterized by large swaths, it is likely that the imaged scenes contain a large number of ships, with the vast majority, hopefully, performing legal activities. Therefore, the imaging system needs a supporting system which identifies legal ships and limits the number of potential alarms to be further monitored by patrol boats or aircrafts. In this framework, spaceborne Synthetic Aperture Radar (SAR) sensors, terrestrial AIS and the ongoing satellite AIS systems can represent a great potential synergy for maritime security. Starting from this idea the paper develops different designs for an AIS constellation able to reduce the time lag between SAR image and AIS data acquisition. An analysis of SAR-based ship detection algorithms is also reported and candidate algorithms identified.

Application of Artificial Intelligence (AI) Programming Techniques to Tactical Guidance for Fighter Aircraft

NASA Technical Reports Server (NTRS)

McManus, John W.; Goodrich, Kenneth H.

1989-01-01

A research program investigating the use of Artificial Intelligence (AI) techniques to aid in the development of a Tactical Decision Generator (TDG) for Within-Visual-Range (WVR) air combat engagements is discussed. The application of AI methods for development and implementation of the TDG is presented. The history of the Adaptive Maneuvering Logic (AML) program is traced and current versions of the AML program are compared and contrasted with the TDG system. The Knowledge-Based Systems (KBS) used by the TDG to aid in the decision-making process are outlined in detail and example rules are presented. The results of tests to evaluate the performance of the TDG versus a version of AML and versus human pilots in the Langley Differential Maneuvering Simulator (DMS) are presented. To date, these results have shown significant performance gains in one-versus-one air combat engagements, and the AI-based TDG software has proven to be much easier to modify than the updated FORTRAN AML programs.

Application of Species Distribution Modeling for Avian Influenza surveillance in the United States considering the North America Migratory Flyways

NASA Astrophysics Data System (ADS)

Belkhiria, Jaber; Alkhamis, Moh A.; Martínez-López, Beatriz

2016-09-01

Highly Pathogenic Avian Influenza (HPAI) has recently (2014-2015) re-emerged in the United States (US) causing the largest outbreak in US history with 232 outbreaks and an estimated economic impact of $950 million. This study proposes to use suitability maps for Low Pathogenic Avian Influenza (LPAI) to identify areas at high risk for HPAI outbreaks. LPAI suitability maps were based on wild bird demographics, LPAI surveillance, and poultry density in combination with environmental, climatic, and socio-economic risk factors. Species distribution modeling was used to produce high-resolution (cell size: 500m x 500m) maps for Avian Influenza (AI) suitability in each of the four North American migratory flyways (NAMF). Results reveal that AI suitability is heterogeneously distributed throughout the US with higher suitability in specific zones of the Midwest and coastal areas. The resultant suitability maps adequately predicted most of the HPAI outbreak areas during the 2014-2015 epidemic in the US (i.e. 89% of HPAI outbreaks were located in areas identified as highly suitable for LPAI). Results are potentially useful for poultry producers and stakeholders in designing risk-based surveillance, outreach and intervention strategies to better prevent and control future HPAI outbreaks in the US.

MR Analysis of Regional Brain Volume in Adolescent Idiopathic Scoliosis: Neurological Manifestation of a Systemic Disease

PubMed Central

Liu, Tianming; Chu, Winnie C.W.; Young, Geoffrey; Li, Kaiming; Yeung, Benson H.Y.; Guo, Lei; Man, Gene C.W.; Lam, Wynnie W.M.; Wong, Stephen T.C.; Cheng, Jack C.Y.

2008-01-01

Purpose To investigate whether regional brain volumes in adolescent idiopathic scoliosis (AIS) patients differ from matched control subjects as AIS subjects are reported to have poor performance on combined visual and proprioceptive testing and impaired postural balance in previous studies. Materials and Methods Twenty AIS female patients with typical right-convex thoracic curve (age range,11−18 years; mean, 14.1 years) and 26 female controls (mean age, 14.8 years) underwent three-dimensional magnetization prepared rapid acquisition gradient echo (3D-MPRAGE) MR imaging. Volumes of 99 preselected neuroanatomical regions were compared by statistical parametric mapping and atlas-based hybrid warping. Results Analysis of variance statistics revealed significant mean volumetric differences in 22 brain regions between AIS and controls. Ten regions were larger in AIS including the left frontal gyri and white matter in left frontal, parietal, and temporal regions, corpus callosum and brainstem. Twelve regions were smaller in AIS, including right-sided descending white matter tracts (anterior and posterior limbs of the right internal capsule and the cerebral peduncle) and deep nucleus (caudate), bilateral perirhinal cortices, left hippocampus and amygdala, bilateral precuneus gyri, and left middle and inferior occipital gyri. Conclusion Regional brain volume difference in AIS subjects may help to explain neurological abnormalities in this group. PMID:18302230

A novel AMELX mutation causes hypoplastic amelogenesis imperfecta.

PubMed

Kim, Young-Jae; Kim, Youn Jung; Kang, Jenny; Shin, Teo Jeon; Hyun, Hong-Keun; Lee, Sang-Hoon; Lee, Zang Hee; Kim, Jung-Wook

2017-04-01

Amelogenesis imperfecta (AI) is a hereditary genetic defect affecting tooth enamel. AI is heterogeneous in clinical phenotype as well as in genetic etiology. To date, more than 10 genes have been associated with the etiology of AI. Amelogenin is the most abundant enamel matrix protein, most of which is encoded by the amelogenin gene in the X-chromosome (AMELX). More than 16 alternative splicing transcripts have been identified in the murine Amelx gene. The purpose of this study was to identify the genetic cause of an AI family. We recruited a family with hypoplastic AI and performed mutational analysis on the candidate gene based on the clinical phenotype. Mutational analysis revealed a missense mutation in exon 6 (NM_182680.1; c.242C > T), which changes a sequence in a highly conserved amino acid (NP_872621.1; p.Pro81Leu). Furthermore, a splicing assay using a minigene displayed that the mutation changed the mRNA splicing repertory. In this study, we identified a novel AMELX missense mutation causing hypoplastic AI, and this mutation also resulted in altered mRNA splicing. These results will not only expand the mutation spectrum causing AI but also broaden our understanding of the biological mechanism of enamel formation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Accelerated iTBS treatment in depressed patients differentially modulates reward system activity based on anhedonia.

PubMed

Duprat, Romain; Wu, Guo-Rong; De Raedt, Rudi; Baeken, Chris

2017-08-09

Accelerated intermittent theta-burst stimulation (aiTBS) anti-depressive working mechanisms are still unclear. Because aiTBS may work through modulating the reward system and the level of anhedonia may influence this modulation, we investigated the effect of aiTBS on reward responsiveness in high and low anhedonic MDD patients. In this registered RCT (NCT01832805), 50 MDD patients were randomised to a sham-controlled cross-over aiTBS treatment protocol over the left dorsolateral prefrontal cortex (DLPFC). Patients performed a probabilistic learning task in fMRI before and after each week of stimulation. Task performance analyses did not show any significant effects of aiTBS on reward responsiveness, nor differences between both groups of MDD patients. However, at baseline, low anhedonic patients displayed higher neural activity in the caudate and putamen. After the first week of aiTBS treatment, in low anhedonic patients we found a decreased neural activity within the reward system, in contrast to an increased activity observed in high anhedonic patients. No changes were observed in reward related neural regions after the first week of sham stimulation. Although both MDD groups showed no differences in task performance, our brain imaging findings suggest that left DLPFC aiTBS treatment modulates the reward system differently according to anhedonia severity.

Effects of different five-day progesterone-based fixed-time AI protocols on follicular/luteal dynamics and fertility in dairy cows

PubMed Central

GARCIA-ISPIERTO, Irina; LÓPEZ-GATIUS, Fernando

2014-01-01

This study compares in two experiments the responses of lactating dairy cows to four different progesterone-based protocols for fixed-time artificial insemination (FTAI) in terms of their effects on follicular/luteal dynamics and fertility. The protocols consisted of a progesterone intravaginal device fitted for five days, along with the administration of different combinations of gonadotropin releasing hormone, equine chorionic gonadotropin and a single or double dose (24 h apart) of prostaglandin F2α. In Experiment I, the data were derived from 232 lactating cows. Binary logistic regression identified no effects of treatment on ovulation failure or multiple ovulation 10 days post artificial insemination (AI). Based on the odds ratio, the likelihood of ovulation failure was lower (by a factor of 0.1) in cows showing at least one corpus luteum (CL) upon treatment than in cows lacking a CL; repeat breeders (> 3 AI) and cows with multiple CLs at treatment showed lower (by a factor of 0.44) and higher (by a factor of 9.0) risks of multiple ovulation, respectively, than the remaining animals. In Experiment II, the data were derived from 5173 AIs. The independent variable treatment failed to affect the conception rate 28–34 days post AI, twin pregnancy or early fetal loss 58–64 days post AI. The results of this study demonstrate the efficacy of 5-day progesterone-based protocols for FTAI. All four protocols examined were able to induce ovulation in both cyclic and non-cyclic animals so that FTAI returned a similar pregnancy rate to spontaneous estrus. Our results suggest that the ovarian response and fertility resulting from each treatment are due more to the effect of ovarian structures at treatment than to the different combinations of hormones investigated. PMID:25196275

Development of an expert based ICD-9-CM and ICD-10-CM map to AIS 2005 update 2008.

PubMed

Loftis, Kathryn L; Price, Janet P; Gillich, Patrick J; Cookman, Kathy J; Brammer, Amy L; St Germain, Trish; Barnes, Jo; Graymire, Vickie; Nayduch, Donna A; Read-Allsopp, Christine; Baus, Katherine; Stanley, Patsye A; Brennan, Maureen

2016-09-01

This article describes how maps were developed from the clinical modifications of the 9th and 10th revisions of the International Classification of Diseases (ICD) to the Abbreviated Injury Scale 2005 Update 2008 (AIS08). The development of the mapping methodology is described, with discussion of the major assumptions used in the process to map ICD codes to AIS severities. There were many intricacies to developing the maps, because the 2 coding systems, ICD and AIS, were developed for different purposes and contain unique classification structures to meet these purposes. Experts in ICD and AIS analyzed the rules and coding guidelines of both injury coding schemes to develop rules for mapping ICD injury codes to the AIS08. This involved subject-matter expertise, detailed knowledge of anatomy, and an in-depth understanding of injury terms and definitions as applied in both taxonomies. The official ICD-9-CM and ICD-10-CM versions (injury sections) were mapped to the AIS08 codes and severities, following the rules outlined in each coding manual. The panel of experts was composed of coders certified in ICD and/or AIS from around the world. In the process of developing the map from ICD to AIS, the experts created rules to address issues with the differences in coding guidelines between the 2 schemas and assure a consistent approach to all codes. Over 19,000 ICD codes were analyzed and maps were generated for each code to AIS08 chapters, AIS08 severities, and Injury Severity Score (ISS) body regions. After completion of the maps, 14,101 (74%) of the eligible 19,012 injury-related ICD-9-CM and ICD-10-CM codes were assigned valid AIS08 severity scores between 1 and 6. The remaining 4,911 codes were assigned an AIS08 of 9 (unknown) or were determined to be nonmappable because the ICD description lacked sufficient qualifying information for determining severity according to AIS rules. There were also 15,214 (80%) ICD codes mapped to AIS08 chapter and ISS body region, which allow for ISS calculations for patient data sets. This mapping between ICD and AIS provides a comprehensive, expert-designed solution for analysts to bridge the data gap between the injury descriptions provided in hospital codes (ICD-9-CM, ICD-10-CM) and injury severity codes (AIS08). By applying consistent rules from both the ICD and AIS taxonomies, the expert panel created these definitive maps, which are the only ones endorsed by the Association for the Advancement of Automotive Medicine (AAAM). Initial validation upheld the quality of these maps for the estimation of AIS severity, but future work should include verification of these maps for MAIS and ISS estimations with large data sets. These ICD-AIS maps will support data analysis from databases with injury information classified in these 2 different systems and open new doors for the investigation of injury from traumatic events using large injury data sets.

Understanding Gender Roles in Teen Pregnancy Prevention among American Indian Youth

PubMed Central

Hanson, Jessica D.; McMahon, Tracey R.; Griese, Emily R.; Kenyon, DenYelle Baete

2014-01-01

Objectives To examine the impact of gender norms on American Indian (AI) adolescents' sexual health behavior. Methods The project collected qualitative data at a reservation site and an urban site through 24 focus groups and 20 key informant interviews. Results The reasons that AI youth choose to abstain or engage in sexual intercourse and utilize contraception vary based on gender ideologies defined by the adolescent's environment. These include social expectations from family and peers, defined roles within relationships, and gender empowerment gaps. Conclusions Gender ideology plays a large role in decisions about contraception and sexual activity for AI adolescents, and it is vital to include re-definitions of gender norms within AI teen pregnancy prevention program. PMID:25207506

Artificial intelligence technology assessment for the US Army Depot System Command

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pennock, K A

1991-07-01

This assessment of artificial intelligence (AI) has been prepared for the US Army's Depot System Command (DESCOM) by Pacific Northwest Laboratory. The report describes several of the more promising AI technologies, focusing primarily on knowledge-based systems because they have been more successful in commercial applications than any other AI technique. The report also identifies potential Depot applications in the areas of procedural support, scheduling and planning, automated inspection, training, diagnostics, and robotic systems. One of the principal objectives of the report is to help decisionmakers within DESCOM to evaluate AI as a possible tool for solving individual depot problems. Themore » report identifies a number of factors that should be considered in such evaluations. 22 refs.« less

International utilization of the SRS-22 instrument to assess outcomes in adolescent idiopathic scoliosis: what can we learn from a medical outreach group in Ghana?

PubMed

Verma, Kushagra; Lonner, Baron; Toombs, Courtney S; Ferrise, Paige; Wright, Bettye; King, Akilah B; Boachie-Adjei, Oheneba

2014-01-01

Cross-cultural studies on adolescent idiopathic scoliosis (AIS) populations are limited. This study evaluated the discriminate validity of the Scoliosis Research Society Questionnaire (SRS-22) in Ghana between adolescents with and without AIS. SRS-22 outcomes from AIS and normal adolescents in Ghana were also compared with scores from AIS and normal adolescents in America. A retrospective review of preoperative SRS-22 questionnaires from Ghana and New York City was completed. In Ghana, 84 adolescents without scoliosis (healthy-G) (32 female adolescents; mean age, 13.3 y) and 61 patients with AIS (AIS-G) (76 female adolescents; mean age, 15.4 y) were administered with the SRS-22 questionnaire. From the New York City, 450 healthy adolescents (healthy-US) (279 female adolescents; mean age, 16 y) and 302 patients with AIS (AIS-US) (227 female adolescents; mean age, 14.9 y) also completed the SRS-22 questionnaire. Patients with curve magnitudes <40 (nonoperative) were then excluded. All 4 groups were matched based on age and sex, resulting in 4 groups of 40 subjects (25 female adolescents; mean age, 14.5 y for all groups). Differences in SRS-22 scores across the groups were analyzed using analysis of variance and analysis of covariance, with the Bonferroni post hoc tests, to control for differences in curve magnitude. Mean curve magnitude for the matched groups was larger for the AIS-G group [67.2 degrees (range, 42 to 130 degrees)] as compared with the AIS-US group [52 degrees (range, 40 to 76 degrees)] (P<0.01). When controlling for the curve magnitude, a significant difference between all 4 study groups was found within all domains and total score (P<0.01). AIS-G displayed significantly lower scores in the activity, image, pain, and mental health domains (P<0.01); this reached the minimal clinically importance difference for these domains. Healthy-US and healthy-G had better overall and domain-specific scores than AIS-US and AIS-G, respectively (P<0.05). These findings illustrate the affect of AIS within a culture as well as across cultures. Healthy adolescents had significantly better scores than scoliotic adolescents. Ghanaian adolescents had significantly worse Health-Related Quality-of-Life scores than American adolescents, especially those suffering from AIS. These differences should be kept in mind by those treating this already emotionally vulnerable adolescent population. Level II Prognostic.

Efficacy of plain radiography and computer tomography in localizing the site of pelvic arterial bleeding in trauma patients.

PubMed

Dormagen, Johann B; Tötterman, Anna; Røise, Olav; Sandvik, Leiv; Kløw, Nils-E

2010-02-01

Immediate angiography is warranted in pelvic trauma patients with suspected arterial injury (AI) in order to stop ongoing bleeding. Prior to angiography, plain pelvic radiography (PPR) and abdominopelvic computer tomography (CT) are performed to identify fracture and hematoma sites. To investigate if PPR and CT can identify the location of AI in trauma patients undergoing angiography. 95 patients with pelvic fractures on PPR (29 women, 66 men), at a mean age of 44 (9-92) years, underwent pelvic angiography for suspected AI. Fifty-six of them underwent CT additionally. Right and left anterior and posterior fractures on PPR were registered, and fracture displacement was recorded for each quadrant. Arterial blush on CT was registered, and the size of the hematoma in each region was measured in cm(2). AIs were registered for anterior and posterior segments of both internal iliac arteries. Presence of fractures, arterial blush, and hematomas were correlated with AI. Presence of fracture in the corresponding skeletal segment on PPR showed sensitivity and specificity of 0.86 and 0.58 posteriorly, and 0.87 and 0.44 anteriorly. The area under the curve (AUC) was 0.77 and 0.69, respectively. Fracture displacement on PPR >0.9 cm posteriorly and >1.9 cm anteriorly revealed specificity of 0.84. Sensitivities of arterial blush and hematoma on CT were 0.38 and 0.82 posteriorly, and 0.24 and 0.82 anteriorly. The specificities were 0.96 and 0.58 posteriorly, and 0.79 and 0.53 anteriorly, respectively. For hematomas, the AUC was 0.79 posteriorly and 0.75 anteriorly. Size of hematoma >22 cm(2) posteriorly and >29 cm(2) anteriorly revealed specificity of 0.85 and 0.86, respectively. CT findings of arterial blush and hematoma predicted site of arterial bleeding on pelvic angiography. Also, PPR predicted the site of bleeding using location of fracture and size of displacement. In the hemodynamically unstable patient, PPR may contribute equally to effective assessment of injured arteries.

Effect of season, late embryonic mortality and progesterone production on pregnancy rates in pluriparous buffaloes (Bubalus bubalis) after artificial insemination with sexed semen.

PubMed

Campanile, Giuseppe; Vecchio, Domenico; Neglia, Gianluca; Bella, Antonino; Prandi, Alberto; Senatore, Elena M; Gasparrini, Bianca; Presicce, Giorgio A

2013-03-01

The use of sexed semen technology in buffaloes is nowadays becoming more and more accepted by farmers, to overcome the burden of unwanted male calves with related costs and to more efficiently improve production and genetic gain. The aim of this study was to verify the coupling of some variables on the efficiency of pregnancy outcome after deposition of sexed semen through AI. Pluriparous buffaloes from two different farms (N = 152) were screened, selected, and subjected to Ovsynch protocol for AI using nonsexed and sexed semen from four tested bulls. AI was performed in two distinct periods of the year: September to October and January to February. Neither farms nor bulls had a significant effect on pregnancy rates pooled from the two periods. The process for sexing sperm cells did not affect pregnancy rates at 28 days after AI, for nonsexed and sexed semen, respectively 44/73 (60.2%) and 50/79 (63.2%), P = 0.70, and at 45 days after AI, for nonsexed and sexed semen, respectively 33/73 (45.2%) and 33/79 (49.3%), P = 0.60. Pregnancy rate at 28 days after AI during the transitional period of January to February was higher when compared with September to October, respectively 47/67 (70.1%) versus 47/85 (55.2%), P = 0.06. When the same pregnant animals were checked at Day 45 after AI, the difference disappeared between the two periods, because of a higher embryonic mortality, respectively 32/67 (47.7%) versus 40/85 (47.0%), P = 0.93. Hematic progesterone concentration at Day 10 after AI did not distinguish animals pregnant at Day 28 that would or would not maintain pregnancy until Day 45 (P = 0.21). On the contrary, when blood samples were taken at Day 20 after AI, the difference in progesterone concentration between pregnant animals that would maintain their pregnancy until Day 45 was significant for both pooled (P = 0.00) and nonsexed (P = 0.00) and sexed semen (P = 0.09). A similar trend was reported when blood samples were taken at Day 25, being highly significant for pooled, nonsexed, and sexed semen (P = 0.00). Hematic progesterone concentration between the two periods of the year was highly significant for pregnant animals at 28 days from AI when blood samples were taken at Day 20 after AI for pooled, nonsexed, and sexed semen, respectively P = 0.00, 0.00, and 0.06, and for pregnant animals at Day 45 for pooled, nonsexed, and sexed semen, respectively P = 0.00, 0.00, and 0.01. From these results, it can be stated that hematic progesterone concentration measurement since Day 20 after AI can be predictive of possible pregnancy maintenance until Day 45. Furthermore, the transitional period of January to February, although characterized by a higher pregnancy outcome when compared with September to October, suffers from a higher late embryonic mortality as evidenced by a significant different hematic progesterone concentration between the two periods at Day 20 after AI. Copyright © 2013 Elsevier Inc. All rights reserved.

Mechanism-based Categorization of Aromatase Inhibitors: A Potential Discovery and Screening Tool

EPA Science Inventory

Cytochrome P450 aromatase is a key steroidogenic enzyme that converts androgens to estrogens in vertebrates. There is much interest in aromatase inhibitors (AIs) because a number of environmental contaminants can act as AIs, thereby disrupting endocrine function in humans and wil...

Utilizing drumming for American Indians/Alaska Natives with substance use disorders: a focus group study.

PubMed

Dickerson, Daniel; Robichaud, Francis; Teruya, Cheryl; Nagaran, Kathleen; Hser, Yih-Ing

2012-09-01

Drumming has been utilized among American Indian/Alaska Native (AI/AN) tribes for centuries to promote healing and self-expression. Drum-Assisted Recovery Therapy for Native Americans (DARTNA), currently under development, is a substance abuse treatment utilizing drumming as a core component. Focus groups were conducted to assist in the development of the DARTNA protocol. Feedback obtained from these focus groups will inform a subsequent pretest of DARTNA and an empirical study analyzing its effectiveness. Three focus groups were conducted among AIs/ANs with substance use disorders (n = 6), substance abuse treatment providers (n = 8), and a community advisory board (n = 4) to solicit feedback prior to a pretest of the DARTNA protocol. Overall, participants indicated that DARTNA could be beneficial for AIs/ANs with substance use disorders. Four overarching conceptual themes emerged across the focus groups: (1) benefits of drumming, (2) importance of a culture-based focus, (3) addressing gender roles in drumming activities, and (4) providing a foundation of common AI/AN traditions. The DARTNA protocol is a potentially beneficial and culturally appropriate substance abuse treatment strategy for AIs/ANs. In order to optimize the potential benefits of a substance abuse treatment protocol utilizing drumming for AIs/ANs, adequate attention to tribal diversity and gender roles is needed. Due to the shortage of substance abuse treatments utilizing traditional healing activities for AIs/ANs, including drumming, results from this study provide an opportunity to develop an intervention that may meet the unique treatment needs of AIs/ANs.

Dry eyes and AIs: If you don't ask you won't find out.

PubMed

Inglis, Holly; Boyle, Frances M; Friedlander, Michael L; Watson, Stephanie L

2015-12-01

Our objective was to investigate the hypothesis that women on adjuvant aromatase inhibitors (AIs) for treatment of breast cancer have a higher prevalence of dry eye syndrome (DES) compared with controls. Exposure and control groups were recruited. A cross sectional questionnaire-based study was performed. Demographic data and medical histories were collected. The presence of dry eye syndrome was determined by the ocular surface disease index (OSDI). The Functional Assessment of Cancer Treatment - Endocrine Subscale (FACT-ES) was performed to investigate correlations with other side effects of AIs. 93 exposure group and 100 control group questionnaires were included. The groups were similar in all demographic variables. The prevalence of dry eye syndrome was 35% (exposure) and 18% (control) (p < 0.01, OR 2.5). AIs were the only factor associated with dry eyes. The OSDI score was negatively correlated with the total FACT-ES score and positively correlated with duration of treatment. Our study is the first to use a validated questionnaire to assess for DES in this population. DES is significantly more prevalent in women on AIs compared with controls. This is a newly emerging, and easily treated side effect of AIs. Self-reporting of dry eye symptoms underestimates the prevalence of DES with AIs. We recommend routine screening of patients on AIs with the OSDI with the aim of improving patient quality of life and possibly adherence. Copyright © 2015 Elsevier Ltd. All rights reserved.

Targeted next-generation sequencing for analyzing the genetic alterations in atypical adenomatous hyperplasia and adenocarcinoma in situ.

PubMed

Xu, Xuan; Li, Na; Zhao, Ruiying; Zhu, Lei; Shao, Jinchen; Zhang, Jie

2017-12-01

Atypical adenomatous hyperplasia (AAH) and adenocarcinoma in situ (AIS) have been defined as preinvasive pulmonary adenocarcinoma lesions according to the 2015 World Health Organization lung adenocarcinoma classification. We aimed to search for the most common gene mutations in patients with AAH and AIS and investigate the distinctions between the two groups at the molecular level. We performed targeted next-generation sequencing on 18 cases with AAH and 28 cases with AIS to screen for mutations with the Ion Torrent Oncomine Solid Tumor DNA panel. ALK and ROS1 fusions were detected by real-time PCR. Forty-six mutations were identified in 29 cases (76.1%), including 9 (50%) of 18 cases with AAH and 20 (71.4%) of 28 cases with AIS, in the following genes: EGFR, BRAF, KRAS, ERBB2, TP53, and FGFR3. The mutations in EGFR, BRAF, KRAS, ERBB2, and TP53 genes were more common in AIS lesions than in AAH lesions, whereas the FGFR3 gene was more frequently mutated in AAH compared to AIS. ALK and ROS1 fusions were not detected in any of the lesions. Based on the molecular evidence, the proposal that AAH and AIS are preinvasive lesions of pulmonary adenocarcinomas is of great significance, and it is necessary to distinguish AAH from AIS. Our study provided insights into the genetic alterations in the early stage of lung adenocarcinoma, which could be beneficial for the pathologic diagnosis and early detection of these lesions.

Clavicle Chest Cage Angle Difference: Is It a Radiographic and Clinical Predictor of Postoperative Shoulder Imbalance in Lenke I Adolescent Idiopathic Scoliosis?

PubMed

Han, Xiao; Liu, Zhen; Qiu, Yong; Sha, Shifu; Yan, Huang; Jin, Mengran; Zhu, Zezhang

2016-09-01

A retrospective study. To evaluate the effect of preoperative clavicle chest cage angle difference (CCAD) on postoperative radiographic shoulder imbalance, cosmetic shoulder balance, patient's satisfaction, and surgeon's fulfillment in Lenke I adolescent idiopathic scoliosis (AIS). CCAD is a novel predictor of postoperative radiographic shoulder imbalance in AIS. However, radiographic shoulder balance does not always correspond to cosmetic shoulder balance. Forty-four Lenke I AIS patients treated with posterior spinal fusion with a minimum 2-year follow-up were analyzed. Shoulder height difference (SHD) and CCAD were measured on anteroposterior standing radiographs. The inner shoulder height (SHi) and the outer shoulder height (SHo) were measured using the patients' photographs. The patients' satisfaction and the surgeons' fulfillment were evaluated using a questionnaire. A receiver operative characteristic curve analysis was performed to explore the threshold values of preoperative CCAD in the prediction of the final follow-up radiographic shoulder imbalance, patients' satisfaction, and surgeons' fulfillment. At the final follow-up, the preoperative CCAD was significantly greater in patients with unbalanced shoulders (SHD ≥1 cm). For cosmetic shoulder balance at the final follow-up, there was no significant difference in preoperative CCAD between Group 1i (SHi ≥1 cm, n = 14) and Group 2i (SHi <1 cm, n = 30), and the preoperative CCAD was also similar between Group 1o (SHo ≥1 cm, n = 17) and Group 2o (SHo <1 cm, n = 27). For patients' satisfaction and surgeons' fulfillment, the preoperative CCAD was significantly greater in patients with unsatisfied outcomes. The threshold value of preoperative CCAD to predict the final follow-up radiographic shoulder imbalance, patients' satisfaction, and surgeons' fulfillment was 5.5°. CCAD is a good radiographic predictor for postoperative radiographic shoulder imbalance in Lenke I AIS patients. Moreover, it is also associated with the patients' satisfaction and surgeons' fulfillment postoperatively. However, CCAD cannot predict postoperative cosmetic shoulder balance. 4.

Mapping Abbreviated Injury Scale data from 1990 to 1998 versions: a stepping-stone in the contemporary evaluation of trauma.

PubMed

Palmer, Cameron S; Lang, Jacelle; Russell, Glen; Dallow, Natalie; Harvey, Kathy; Gabbe, Belinda; Cameron, Peter

2013-11-01

Many trauma registries have used the 1990 revision of the Abbreviated Injury Scale (AIS; AIS90) to code injuries sustained by trauma patients. Due to changes made to the AIS codeset since its release, AIS90-coded data lacks currency in the assessment of injury severity. The ability to map between the 1998 revision of AIS (AIS98) and the current (2008) AIS version (AIS08) already exists. The development of a map for transforming AIS90-coded data into AIS98 would therefore enable contemporary injury severity estimates to be derived from AIS90-coded data. Differences between the AIS90 and AIS98 codesets were identified, and AIS98 maps were generated for AIS90 codes which changed or were not present in AIS98. The effectiveness of this map in describing the severity of trauma using AIS90 and AIS98 was evaluated using a large state registry dataset, which coded injury data using AIS90 over several years. Changes in Injury Severity Scores (ISS) calculated using AIS90 and mapped AIS98 codesets were assessed using three distinct methods. Forty-nine codes (out of 1312) from the AIS90 codeset changed or were not present in AIS98. Twenty-four codes required the assignment of maps to AIS98 equivalents. AIS90-coded data from 78,075 trauma cases were used to evaluate the map. Agreement in calculated ISS between coded AIS90 data and mapped AIS98 data was very high (kappa=0.971). The ISS changed in 1902 cases (2.4%), and the mean difference in ISS across all cases was 0.006 points. The number of cases classified as major trauma using AIS98 decreased by 0.8% compared with AIS90. A total of 3102 cases (4.0%) sustained at least one AIS90 injury which required mapping to AIS98. This study identified the differences between the AIS90 and AIS98 codesets, and generated maps for the conversion process. In practice, the differences between AIS90- and AIS98-coded data were very small. As a result, AIS90-coded data can be mapped to the current AIS version (AIS08) via AIS98, with little apparent impact on the functional accuracy of the mapped dataset produced. Copyright © 2012 Elsevier Ltd. All rights reserved.

Effects of Episodic Variations in Web-Based Avian Influenza Education: Influence of Fear and Humor on Perception, Comprehension, Retention and Behavior

ERIC Educational Resources Information Center

Kim, Paul; Sorcar, Piya; Um, Sujung; Chung, Heedoo; Lee, Young Sung

2009-01-01

In order to provide empirical evidence on the role of a web-based avian influenza (AI) education program for mass communication and also ultimately help young children learn and develop healthy behaviors against AI and all types of influenza, an education program with two episodic variations (i.e. fear and humor) has been developed and examined…

Creating a Culturally Appropriate Web-Based Behavioral Intervention for American Indian/Alaska Native Women in Southern California: The Healthy Women Healthy Native Nation Study

ERIC Educational Resources Information Center

Gorman, Jessica R.; Clapp, John D.; Calac, Daniel; Kolander, Chelsea; Nyquist, Corinna; Chambers, Christina D.

2013-01-01

Health disparities in fetal alcohol spectrum disorders (FASD) are of high importance to American Indian/Alaska Native (AI/AN) communities. We conducted focus groups and interviews with 21 AI/AN women and key informants in Southern California to modify a brief, Web-based program for screening and prevention of prenatal alcohol use. This process…

Serum leptin level and waist-to-hip ratio (WHR) predict the overall survival of metastatic breast cancer (MBC) patients treated with aromatase inhibitors (AIs).

PubMed

Artac, Mehmet; Bozcuk, Hakan; Kiyici, Aysel; Eren, Orhan Onder; Boruban, Melih Cem; Ozdogan, Mustafa

2013-04-01

Our objective was to determine whether serum leptin levels and obesity-related factors could affect outcome for metastatic breast cancer (MBC) patients treated with aromatase inhibitors (AIs). Sixty MBC patients treated with first line hormonal therapy were enrolled in this study. Median age was 51 years (range 28-75). Median leptin level was 19400 pg/ml (1970-91900) and estradiol level 29.6 pg/ml (4.0-181.9). Factors associated with overall survival in univariate analysis were age and waist-to-hip ratio (WHR), whereas only WHR retained significance in the multivariate analysis. However, no factor was associated with progression-free survival. However, WHR was found to be a significant prognostic marker only if the leptin level was ≥19400 pg/ml (HR = 0.38; 95% CI: 0.16-0.91). This study suggests that serum leptin levels and WHR together may serve as potential prognostic markers in MBC patients treated with AIs.

Recent developments of artificial intelligence in drying of fresh food: A review.

PubMed

Sun, Qing; Zhang, Min; Mujumdar, Arun S

2018-03-01

Intellectualization is an important direction of drying development and artificial intelligence (AI) technologies have been widely used to solve problems of nonlinear function approximation, pattern detection, data interpretation, optimization, simulation, diagnosis, control, data sorting, clustering, and noise reduction in different food drying technologies due to the advantages of self-learning ability, adaptive ability, strong fault tolerance and high degree robustness to map the nonlinear structures of arbitrarily complex and dynamic phenomena. This article presents a comprehensive review on intelligent drying technologies and their applications. The paper starts with the introduction of basic theoretical knowledge of ANN, fuzzy logic and expert system. Then, we summarize the AI application of modeling, predicting, and optimization of heat and mass transfer, thermodynamic performance parameters, and quality indicators as well as physiochemical properties of dried products in artificial biomimetic technology (electronic nose, computer vision) and different conventional drying technologies. Furthermore, opportunities and limitations of AI technique in drying are also outlined to provide more ideas for researchers in this area.

The quest for a universal definition of polytrauma: a trauma registry-based validation study.

PubMed

Butcher, Nerida E; D'Este, Catherine; Balogh, Zsolt J

2014-10-01

A pilot validation recommended defining polytrauma as patients with an Abbreviated Injury Scale (AIS) score greater than 2 in at least two Injury Severity Score (ISS) body regions (2 × AIS score > 2). This study aimed to validate this definition on larger data set. We hypothesized that patients defined by the 2 × AIS score > 2 cutoff have worse outcomes and use more resources than those without 2 × AIS score > 2 and that this would therefore be a better definition of polytrauma. Patients injured between 2009 and 2011, with complete documentation of AIS by New South Wales Trauma Registry and 16 years and older were selected. Age and sex were obtained in addition to outcomes of ISS, hospital length of stay (LOS), intensive care unit (ICU) admission, ICU LOS, and mortality. We compared demographic characteristics and outcomes between patients with ISS greater than 15 who did and did not meet the 2 × AIS score > 2 definition. We then undertook regression analyses (logistic regression for binary outcomes [ICU admission and death] and linear regression for hospital and ICU LOS) to compare outcomes for patients with and without 2 × AIS score > 2, adjusting for sex and age categories. In the adjusted analyses, patients with 2 × AIS score > 2 had twice the odds of being admitted to the ICU compared with those without 2 × AIS score > 2 (odds ratio, 2.5; 95% confidence interval [CI], 2.2-2.8) and 1.7 times the odds of dying (95% CI, 1.4-2.0; p < 0.001 for both models). Patients with 2 × AIS score > 2 also had a mean difference of 1.5 days longer stay in the hospital compared with those without 2 × AIS score > 2 (95% CI, 1.4-1.7) and 1.6 days longer ICU stay (95% CI, 1.4-1.8; p < 0.001 for all models). Patients with 2 × AIS score > 2 had higher mortality, more frequent ICU admissions, and longer hospital and ICU stay than those without 2 × AIS score > 2 and represents a superior definition to the definitions for polytrauma currently in use. Diagnostic test/ criteria, level III.

Amelogenesis imperfecta caused by N-terminal enamelin point mutations in mice and men is driven by endoplasmic reticulum stress

PubMed Central

Barron, Martin J.; Smith, Claire E.L.; Poulter, James A.; Mighell, Alan J.; Inglehearn, Chris F.; Brown, Catriona J.; Rodd, Helen; Kirkham, Jennifer; Dixon, Michael J.

2017-01-01

Abstract ‘Amelogenesis imperfecta’ (AI) describes a group of inherited diseases of dental enamel that have major clinical impact. Here, we identify the aetiology driving AI in mice carrying a p.S55I mutation in enamelin; one of the most commonly mutated proteins underlying AI in humans. Our data indicate that the mutation inhibits the ameloblast secretory pathway leading to ER stress and an activated unfolded protein response (UPR). Initially, with the support of the UPR acting in pro-survival mode, Enamp.S55I heterozygous mice secreted structurally normal enamel. However, enamel secreted thereafter was structurally abnormal; presumably due to the UPR modulating ameloblast behaviour and function in an attempt to relieve ER stress. Homozygous mutant mice failed to produce enamel. We also identified a novel heterozygous ENAMp.L31R mutation causing AI in humans. We hypothesize that ER stress is the aetiological factor in this case of human AI as it shared the characteristic phenotype described above for the Enamp.S55I mouse. We previously demonstrated that AI in mice carrying the Amelxp.Y64H mutation is a proteinopathy. The current data indicate that AI in Enamp.S55I mice is also a proteinopathy, and based on comparative phenotypic analysis, we suggest that human AI resulting from the ENAMp.L31R mutation is another proteinopathic disease. Identifying a common aetiology for AI resulting from mutations in two different genes opens the way for developing pharmaceutical interventions designed to relieve ER stress or modulate the UPR during enamel development to ameliorate the clinical phenotype. PMID:28334996

Anti-inflammatory activity of polyphenolics from açai (Euterpe oleracea Martius) in intestinal myofibroblasts CCD-18Co cells.

PubMed

Dias, Manoela Maciel dos Santos; Martino, Hércia Stampini Duarte; Noratto, Giuliana; Roque-Andrade, Andrea; Stringheta, Paulo César; Talcott, Stephen; Ramos, Afonso Mota; Mertens-Talcott, Susanne U

2015-10-01

The demand for tropical fruits high in polyphenolics including açai (Euterpe oleracea Mart.) has been increasing based on ascribed health benefits and antioxidant properties. This study evaluated the anti-inflammatory activities of açai polyphenolics in human colon myofibroblastic CCD-18Co cells to investigate the suppression of reactive oxygen species (ROS), and mRNA and protein expression of inflammatory proteins. Non-cytotoxic concentrations of açai extract, 1-5 mg gallic acid equivalent L(-1), were selected. The generation of ROS was induced by lipopolysaccharide (LPS) and açai extract partially reversed this effect to 0.53-fold of the LPS-control. Açai extract (5 mg GAE L(-1)) down-regulated LPS-induced mRNA-expression of tumor necrosis factor alpha, TNF-α (to 0.42-fold), cyclooxygenase 2, COX-2 (to 0.61-fold), toll-like receptor-4, TLR-4 (to 0.52-fold), TNF receptor-associated factor 6, TRAF-6 (to 0.64-fold), nuclear factor kappa-B, NF-κB (to 0.76-fold), vascular cell adhesion molecule 1, VCAM-1 (to 0.71-fold) and intercellular adhesion molecule 1, ICAM-1 (to 0.68-fold). The protein levels of COX-2, TLR-4, p-NF-κB and ICAM-1 were induced by LPS and the açai extract partially reversed this effect in a dose-dependent manner. These results suggest the anti-inflammatory effect of açai polyphenolic extract in intestinal cells are at least in part mediated through the inhibition of ROS and the expression of TLR-4 and NF-κB. Results indicate the potential for açai polyphenolics in the prevention of intestinal inflammation.

Amelogenesis imperfecta caused by N-terminal enamelin point mutations in mice and men is driven by endoplasmic reticulum stress.

PubMed

Brookes, Steven J; Barron, Martin J; Smith, Claire E L; Poulter, James A; Mighell, Alan J; Inglehearn, Chris F; Brown, Catriona J; Rodd, Helen; Kirkham, Jennifer; Dixon, Michael J

2017-05-15

'Amelogenesis imperfecta' (AI) describes a group of inherited diseases of dental enamel that have major clinical impact. Here, we identify the aetiology driving AI in mice carrying a p.S55I mutation in enamelin; one of the most commonly mutated proteins underlying AI in humans. Our data indicate that the mutation inhibits the ameloblast secretory pathway leading to ER stress and an activated unfolded protein response (UPR). Initially, with the support of the UPR acting in pro-survival mode, Enamp.S55I heterozygous mice secreted structurally normal enamel. However, enamel secreted thereafter was structurally abnormal; presumably due to the UPR modulating ameloblast behaviour and function in an attempt to relieve ER stress. Homozygous mutant mice failed to produce enamel. We also identified a novel heterozygous ENAMp.L31R mutation causing AI in humans. We hypothesize that ER stress is the aetiological factor in this case of human AI as it shared the characteristic phenotype described above for the Enamp.S55I mouse. We previously demonstrated that AI in mice carrying the Amelxp.Y64H mutation is a proteinopathy. The current data indicate that AI in Enamp.S55I mice is also a proteinopathy, and based on comparative phenotypic analysis, we suggest that human AI resulting from the ENAMp.L31R mutation is another proteinopathic disease. Identifying a common aetiology for AI resulting from mutations in two different genes opens the way for developing pharmaceutical interventions designed to relieve ER stress or modulate the UPR during enamel development to ameliorate the clinical phenotype. © The Author 2017. Published by Oxford University Press.

Long-Term Effects of Untreated Adolescent Idiopathic Scoliosis: A Review of the Literature

PubMed Central

Karavidas, Nikos; Moramarco, Marc; Moramarco, Kathryn

2016-01-01

Currently, adolescent idiopathic scoliosis (AIS) is principally regarded as benign, but some researchers have cited serious or extreme effects, including severe pain, cardiopulmonary compromise, social isolation, and even early death. Therefore, exploration of the long-term effects of AIS, the most common type of idiopathic scoliosis, is warranted. The purpose of this review was to examine the long-term studies on the natural history of AIS and/or reviews concerning the long-term effects of untreated AIS. A PubMed search was conducted using the key words idiopathic scoliosis, long-term effects and idiopathic scoliosis, natural history. For further analysis, references cited in those studies were reviewed for additional, related evidence not retrieved in the initial PubMed search. A review of the pertinent bibliography showed that older natural history studies did not distinguish between late-onset scoliosis (referred to in this paper as AIS) and early-onset scoliosis (EOS). The more recent studies offer such important distinction and reach to the general conclusion that untreated AIS does not lead to severe consequences with respect to signs and symptoms of scoliosis. It is possible that earlier studies may have included patient populations with EOS, leading to the perception of untreated scoliosis as having an unusually high morbidity rate. Studies on the long-term effects of AIS that specifically excluded EOS patients conclude that AIS is a benign disorder. This indicates that for research and reporting purposes, it is important to distinguishing between AIS and EOS. This will allow the practitioner and patient and their families to decide on an optimal treatment plan based on the most appropriate prognosis. PMID:27994795