14 CFR 35.7 - Features and characteristics.

Code of Federal Regulations, 2012 CFR

2012-01-01

... AIRWORTHINESS STANDARDS: PROPELLERS General § 35.7 Features and characteristics. (a) The propeller may not have... propeller. The applicant must make changes to the design and conduct additional tests that the Administrator finds necessary to establish the airworthiness of the propeller. [Amdt. 35-8, 73 FR 63346, Oct. 24, 2008] ...

14 CFR 35.7 - Features and characteristics.

Code of Federal Regulations, 2013 CFR

2013-01-01

... AIRWORTHINESS STANDARDS: PROPELLERS General § 35.7 Features and characteristics. (a) The propeller may not have... propeller. The applicant must make changes to the design and conduct additional tests that the Administrator finds necessary to establish the airworthiness of the propeller. [Amdt. 35-8, 73 FR 63346, Oct. 24, 2008] ...

14 CFR 35.7 - Features and characteristics.

Code of Federal Regulations, 2010 CFR

2010-01-01

... AIRWORTHINESS STANDARDS: PROPELLERS General § 35.7 Features and characteristics. (a) The propeller may not have... propeller. The applicant must make changes to the design and conduct additional tests that the Administrator finds necessary to establish the airworthiness of the propeller. [Amdt. No. 35-8, 73 FR 63346, Oct. 24...

14 CFR 35.7 - Features and characteristics.

Code of Federal Regulations, 2014 CFR

2014-01-01

... AIRWORTHINESS STANDARDS: PROPELLERS General § 35.7 Features and characteristics. (a) The propeller may not have... propeller. The applicant must make changes to the design and conduct additional tests that the Administrator finds necessary to establish the airworthiness of the propeller. [Amdt. 35-8, 73 FR 63346, Oct. 24, 2008] ...

New features of the Moon revealed and identified by CLTM-s01

NASA Astrophysics Data System (ADS)

Huang, Qian; Ping, Jinsong; Su, Xiaoli; Shu, Rong; Tang, Geshi

2009-12-01

Previous analyses showed a clear asymmetry in the topography, geological material distribution, and crustal thickness between the nearside and farside of the Moon. Lunar detecting data, such as topography and gravity, have made it possible to interpret this hemisphere dichotomy. The high-resolution lunar topographic model CLTM-s01 has revealed that there still exist four unknown features, namely, quasi-impact basin Sternfeld-Lewis (20°S, 232°E), confirmed impact basin Fitzgerald-Jackson (25°N, 191°E), crater Wugang (13°N, 189°E) and volcanic deposited highland Yutu (14°N, 308°E). Furthermore, we analyzed and identified about eleven large-scale impact basins that have been proposed since 1994, and classified them according to their circular characteristics.

Characteristic Features and Contributory Factors in Fatal Ciguatera Fish Poisoning—Implications for Prevention and Public Education

PubMed Central

Chan, Thomas Y. K.

2016-01-01

In this review, the main objective was to describe the characteristic features of fatal ciguatera fish poisoning and identify contributory factors, with a view to promote prevention and public education. Ciguatera-related deaths, although rare, have been reported from the Pacific, Caribbean, and Indian Ocean regions. The clinical features were generally dominated by convulsions and coma, with various focal neurological signs. Several contributory factors could be identified, including consumption of ciguatoxin (CTX)-rich fish parts (viscera and head) in larger amounts, the most ciguatoxic fish species (e.g., Gymnothorax flavimarginatus) and reef fish collected after storms and individuals' susceptibility. Mass ciguatera fish poisoning with mortalities also occurred when G. flavimarginatus and other ciguatoxic fish species were shared in gatherings and parties. The characteristic features of fatal ciguatera fish poisoning must be recognized early. The public should be repeatedly reminded to avoid eating the most ciguatoxic fish species and the CTX-rich parts of reef fish. To prevent mass poisoning in gatherings and parties, the most ciguatoxic fish species and potentially toxic fish species must be avoided. Particularly after hits by disastrous storms, it is important to monitor the toxicity of reef fish and the incidence rates of ciguatera. PMID:26787145

Characteristic Features and Contributory Factors in Fatal Ciguatera Fish Poisoning--Implications for Prevention and Public Education.

PubMed

Chan, Thomas Y K

2016-04-01

In this review, the main objective was to describe the characteristic features of fatal ciguatera fish poisoning and identify contributory factors, with a view to promote prevention and public education. Ciguatera-related deaths, although rare, have been reported from the Pacific, Caribbean, and Indian Ocean regions. The clinical features were generally dominated by convulsions and coma, with various focal neurological signs. Several contributory factors could be identified, including consumption of ciguatoxin (CTX)-rich fish parts (viscera and head) in larger amounts, the most ciguatoxic fish species (e.g.,Gymnothorax flavimarginatus) and reef fish collected after storms and individuals' susceptibility. Mass ciguatera fish poisoning with mortalities also occurred when G. flavimarginatus and other ciguatoxic fish species were shared in gatherings and parties. The characteristic features of fatal ciguatera fish poisoning must be recognized early. The public should be repeatedly reminded to avoid eating the most ciguatoxic fish species and the CTX-rich parts of reef fish. To prevent mass poisoning in gatherings and parties, the most ciguatoxic fish species and potentially toxic fish species must be avoided. Particularly after hits by disastrous storms, it is important to monitor the toxicity of reef fish and the incidence rates of ciguatera. © The American Society of Tropical Medicine and Hygiene.

Identifying Creativity during Problem Solving Using Linguistic Features

ERIC Educational Resources Information Center

Skalicky, Stephen; Crossley, Scott A.; McNamara, Danielle S.; Muldner, Kasia

2017-01-01

Creativity is commonly assessed using divergent thinking tasks, which measure the fluency, flexibility, originality, and elaboration of participant output on a variety of different tasks. This study assesses the degree to which creativity can be identified based on linguistic features of participants' language while completing collaborative…

Exploring the limits of identifying sub-pixel thermal features using ASTER TIR data

USGS Publications Warehouse

Vaughan, R.G.; Keszthelyi, L.P.; Davies, A.G.; Schneider, D.J.; Jaworowski, C.; Heasler, H.

2010-01-01

Understanding the characteristics of volcanic thermal emissions and how they change with time is important for forecasting and monitoring volcanic activity and potential hazards. Satellite instruments view volcanic thermal features across the globe at various temporal and spatial resolutions. Thermal features that may be a precursor to a major eruption, or indicative of important changes in an on-going eruption can be subtle, making them challenging to reliably identify with satellite instruments. The goal of this study was to explore the limits of the types and magnitudes of thermal anomalies that could be detected using satellite thermal infrared (TIR) data. Specifically, the characterization of sub-pixel thermal features with a wide range of temperatures is considered using ASTER multispectral TIR data. First, theoretical calculations were made to define a "thermal mixing detection threshold" for ASTER, which quantifies the limits of ASTER's ability to resolve sub-pixel thermal mixing over a range of hot target temperatures and % pixel areas. Then, ASTER TIR data were used to model sub-pixel thermal features at the Yellowstone National Park geothermal area (hot spring pools with temperatures from 40 to 90 ??C) and at Mount Erebus Volcano, Antarctica (an active lava lake with temperatures from 200 to 800 ??C). Finally, various sources of uncertainty in sub-pixel thermal calculations were quantified for these empirical measurements, including pixel resampling, atmospheric correction, and background temperature and emissivity assumptions.

Identifying the relevant features of the National Digital Cadastral Database (NDCDB) for spatial analysis by using the Delphi Technique

NASA Astrophysics Data System (ADS)

Halim, N. Z. A.; Sulaiman, S. A.; Talib, K.; Ng, E. G.

2018-02-01

This paper explains the process carried out in identifying the relevant features of the National Digital Cadastral Database (NDCDB) for spatial analysis. The research was initially a part of a larger research exercise to identify the significance of NDCDB from the legal, technical, role and land-based analysis perspectives. The research methodology of applying the Delphi technique is substantially discussed in this paper. A heterogeneous panel of 14 experts was created to determine the importance of NDCDB from the technical relevance standpoint. Three statements describing the relevant features of NDCDB for spatial analysis were established after three rounds of consensus building. It highlighted the NDCDB’s characteristics such as its spatial accuracy, functions, and criteria as a facilitating tool for spatial analysis. By recognising the relevant features of NDCDB for spatial analysis in this study, practical application of NDCDB for various analysis and purpose can be widely implemented.

An investigation of the psychological characteristics of stalkers: empathy, problem-solving, attachment and borderline personality features.

PubMed

Lewis, S F; Fremouw, W J; Del Ben, K; Farr, C

2001-01-01

This study examined the psychological characteristics of a sample of self-reported stalkers in comparison with a control group, on measures of empathy, problem-solving skills, attachment, and borderline personality features. Stalkers were identified by their endorsement of specific behavioral items, consistent with a widely adopted definition of stalking, denoting behaviors that: (a) are repeatedly directed toward an identified target; (b) are intrusive and unwanted; and (c) evoke fear in the victim. Stalkers scored significantly higher than controls on measures of insecure attachment and borderline personality features, suggesting that the stalking group demonstrates a general pattern of inadequate interpersonal attachment, has limited abilities to form and maintain appropriate relationships, is emotionally labile and unstable, and experiences ambivalence regarding their interpersonal relationships. Treatment implications are discussed herein.

Characteristic features of injuries due to shark attacks: a review of 12 cases.

PubMed

Ihama, Yoko; Ninomiya, Kenji; Noguchi, Masamichi; Fuke, Chiaki; Miyazaki, Tetsuji

2009-09-01

Shark attacks on humans might not occur as often as is believed and the characteristic features of shark injuries on corpses have not been extensively reviewed. We describe the characteristic features of shark injuries on 12 corpses. The analysis of these injuries might reveal the motivation behind the attacks and/or the shark species involved in the attack. Gouge marks on the bones are evidence of a shark attack, even if the corpse is decomposed. Severance of the body part at the joints without a fracture was found to be a characteristic feature of shark injuries.

TCGA study identifies genomic features of cervical cancer

Cancer.gov

Investigators with The Cancer Genome Atlas (TCGA) Research Network have identified novel genomic and molecular characteristics of cervical cancer that will aid in subclassification of the disease and may help target therapies that are most appropriate for each patient.

Pathologic features of metastatic lymph nodes identified from prophylactic central neck dissection in patients with papillary thyroid carcinoma.

PubMed

Lee, Hyoung Shin; Park, Chanwoo; Kim, Sung Won; Noh, Woong Jae; Lim, Soo Jin; Chun, Bong Kwon; Kim, Beom Su; Hong, Jong Chul; Lee, Kang Dae

2016-10-01

The importance of pathologic features of metastatic lymph nodes (LNs), such as size, number, and extranodal extension, has been recently emphasized in patients with papillary thyroid carcinoma (PTC). We evaluated the characteristics of metastatic LNs identified after prophylactic central neck dissection (CND) in patients with PTC. We performed a retrospective review of 1,046 patients who underwent unilateral or bilateral thyroidectomy with ipsilateral prophylactic CND. We reviewed the characteristics of the metastatic LNs and analyzed their correlation to the clinicopathologic characteristics of the primary tumor. Cervical LN metastasis after prophylactic CND was identified in 280 out of 1046 patients (26.8 %). The size of metastatic foci (≥2 mm) was independently correlated with primary tumor size (≥1 cm) (p = 0.016, OR = 1.88). Primary tumor size (≥1 cm) was also correlated to the number of metastatic LNs (≥5) (p = 0.004, OR = 3.14) and extranodal extension (p = 0.021, OR = 2.41) in univariate analysis. The size of the primary tumor affects pathologic features of subclinical LN metastasis in patients with PTC. Patients with primary tumors ≥1 cm have an increased risk of larger LN metastases (≥2 mm), an increased number of LN metastases (≥5), and a higher incidence of ENE, which should be considered in decision for prophylactic CND.

A Novel Feature Extraction Method with Feature Selection to Identify Golgi-Resident Protein Types from Imbalanced Data

PubMed Central

Yang, Runtao; Zhang, Chengjin; Gao, Rui; Zhang, Lina

2016-01-01

The Golgi Apparatus (GA) is a major collection and dispatch station for numerous proteins destined for secretion, plasma membranes and lysosomes. The dysfunction of GA proteins can result in neurodegenerative diseases. Therefore, accurate identification of protein subGolgi localizations may assist in drug development and understanding the mechanisms of the GA involved in various cellular processes. In this paper, a new computational method is proposed for identifying cis-Golgi proteins from trans-Golgi proteins. Based on the concept of Common Spatial Patterns (CSP), a novel feature extraction technique is developed to extract evolutionary information from protein sequences. To deal with the imbalanced benchmark dataset, the Synthetic Minority Over-sampling Technique (SMOTE) is adopted. A feature selection method called Random Forest-Recursive Feature Elimination (RF-RFE) is employed to search the optimal features from the CSP based features and g-gap dipeptide composition. Based on the optimal features, a Random Forest (RF) module is used to distinguish cis-Golgi proteins from trans-Golgi proteins. Through the jackknife cross-validation, the proposed method achieves a promising performance with a sensitivity of 0.889, a specificity of 0.880, an accuracy of 0.885, and a Matthew’s Correlation Coefficient (MCC) of 0.765, which remarkably outperforms previous methods. Moreover, when tested on a common independent dataset, our method also achieves a significantly improved performance. These results highlight the promising performance of the proposed method to identify Golgi-resident protein types. Furthermore, the CSP based feature extraction method may provide guidelines for protein function predictions. PMID:26861308

A novel comparator featured with input data characteristic

NASA Astrophysics Data System (ADS)

Jiang, Xiaobo; Ye, Desheng; Xu, Xiangmin; Zheng, Shuai

2016-03-01

Two types of low-power asynchronous comparators featured with input data statistical characteristic are proposed in this article. The asynchronous ripple comparator stops comparing at the first unequal bit but delivers the result to the least significant bit. The pre-stop asynchronous comparator can completely stop comparing and obtain results immediately. The proposed and contrastive comparators were implemented in SMIC 0.18 μm process with different bit widths. Simulation shows that the proposed pre-stop asynchronous comparator features the lowest power consumption, shortest average propagation delay and highest area efficiency among the comparators. Data path of low-density parity check decoder using the proposed pre-stop asynchronous comparators are most power efficient compared with other data paths with synthesised, clock gating and bitwise competition logic comparators.

Identifying Trajectories of Borderline Personality Features in Adolescence

PubMed Central

Haltigan, John D.

2016-01-01

Objective: To examine trajectories of adolescent borderline personality (BP) features in a normative-risk cohort (n = 566) of Canadian children assessed at ages 13, 14, 15, and 16 and childhood predictors of trajectory group membership assessed at ages 8, 10, 11, and 12. Method: Data were drawn from the McMaster Teen Study, an on-going study examining relations among bullying, mental health, and academic achievement. Participants and their parents completed a battery of mental health and peer relations questionnaires at each wave of the study. Academic competence was assessed at age 8 (Grade 3). Latent class growth analysis, analysis of variance, and logistic regression were used to analyze the data. Results: Three distinct BP features trajectory groups were identified: elevated or rising, intermediate or stable, and low or stable. Parent- and child-reported mental health symptoms, peer relations risk factors, and intra-individual risk factors were significant predictors of elevated or rising and intermediate or stable trajectory groups. Child-reported attention-deficit hyperactivity disorder (ADHD) and somatization symptoms uniquely predicted elevated or rising trajectory group membership, whereas parent-reported anxiety and child-reported ADHD symptoms uniquely predicted intermediate or stable trajectory group membership. Child-reported somatization symptoms was the only predictor to differentiate the intermediate or stable and elevated or rising trajectory groups (OR 1.15, 95% CI 1.04 to 1.28). Associations between child-reported reactive temperament and elevated BP features trajectory group membership were 10.23 times higher among children who were bullied, supporting a diathesis–stress pathway in the development of BP features for these youth. Conclusions: Findings demonstrate the heterogeneous course of BP features in early adolescence and shed light on the potential prodromal course of later borderline personality disorder. PMID:27254092

Identifying sports videos using replay, text, and camera motion features

NASA Astrophysics Data System (ADS)

Kobla, Vikrant; DeMenthon, Daniel; Doermann, David S.

1999-12-01

Automated classification of digital video is emerging as an important piece of the puzzle in the design of content management systems for digital libraries. The ability to classify videos into various classes such as sports, news, movies, or documentaries, increases the efficiency of indexing, browsing, and retrieval of video in large databases. In this paper, we discuss the extraction of features that enable identification of sports videos directly from the compressed domain of MPEG video. These features include detecting the presence of action replays, determining the amount of scene text in vide, and calculating various statistics on camera and/or object motion. The features are derived from the macroblock, motion,and bit-rate information that is readily accessible from MPEG video with very minimal decoding, leading to substantial gains in processing speeds. Full-decoding of selective frames is required only for text analysis. A decision tree classifier built using these features is able to identify sports clips with an accuracy of about 93 percent.

Identifying DNA Methylation Features that Underlie Prostate Cancer Disparities

DTIC Science & Technology

2016-10-01

Report We will continue to recruit African American patients and bank their prostate tissue . We will continue dissecting tumor samples into tumor...in prostate tumors and adjacent normal tissue derived from both AA and EA individuals. We will determine if DNA methylation patterns in prostate... tissue (both cancerous and normal tissue ) differ between AA and EA individuals. We will also identify methylation features that differ between tumor

Personality Characteristics of Leaders Identifying with Different Student Subcultures.

ERIC Educational Resources Information Center

Brainard, Stephen R.

This study was conducted to discover differences in personality characteristics among student leaders. The personality characteristics of presidents of campus organizations affiliated with one of four distinguishable student subcultures, identified by previous research as vocational, academic, collegiate, and nonconformist, were measured by the…

Method of identifying features in indexed data

DOEpatents

Jarman, Kristin H [Richland, WA; Daly, Don Simone [Richland, WA; Anderson, Kevin K [Richland, WA; Wahl, Karen L [Richland, WA

2001-06-26

The present invention is a method of identifying features in indexed data, especially useful for distinguishing signal from noise in data provided as a plurality of ordered pairs. Each of the plurality of ordered pairs has an index and a response. The method has the steps of: (a) providing an index window having a first window end located on a first index and extending across a plurality of indices to a second window end; (b) selecting responses corresponding to the plurality of indices within the index window and computing a measure of dispersion of the responses; and (c) comparing the measure of dispersion to a dispersion critical value. Advantages of the present invention include minimizing signal to noise ratio, signal drift, varying baseline signal and combinations thereof.

An Optimal Mean Based Block Robust Feature Extraction Method to Identify Colorectal Cancer Genes with Integrated Data.

PubMed

Liu, Jian; Cheng, Yuhu; Wang, Xuesong; Zhang, Lin; Liu, Hui

2017-08-17

It is urgent to diagnose colorectal cancer in the early stage. Some feature genes which are important to colorectal cancer development have been identified. However, for the early stage of colorectal cancer, less is known about the identity of specific cancer genes that are associated with advanced clinical stage. In this paper, we conducted a feature extraction method named Optimal Mean based Block Robust Feature Extraction method (OMBRFE) to identify feature genes associated with advanced colorectal cancer in clinical stage by using the integrated colorectal cancer data. Firstly, based on the optimal mean and L 2,1 -norm, a novel feature extraction method called Optimal Mean based Robust Feature Extraction method (OMRFE) is proposed to identify feature genes. Then the OMBRFE method which introduces the block ideology into OMRFE method is put forward to process the colorectal cancer integrated data which includes multiple genomic data: copy number alterations, somatic mutations, methylation expression alteration, as well as gene expression changes. Experimental results demonstrate that the OMBRFE is more effective than previous methods in identifying the feature genes. Moreover, genes identified by OMBRFE are verified to be closely associated with advanced colorectal cancer in clinical stage.

Gene expression profiles of breast biopsies from healthy women identify a group with claudin-low features

PubMed Central

2011-01-01

Background Increased understanding of the variability in normal breast biology will enable us to identify mechanisms of breast cancer initiation and the origin of different subtypes, and to better predict breast cancer risk. Methods Gene expression patterns in breast biopsies from 79 healthy women referred to breast diagnostic centers in Norway were explored by unsupervised hierarchical clustering and supervised analyses, such as gene set enrichment analysis and gene ontology analysis and comparison with previously published genelists and independent datasets. Results Unsupervised hierarchical clustering identified two separate clusters of normal breast tissue based on gene-expression profiling, regardless of clustering algorithm and gene filtering used. Comparison of the expression profile of the two clusters with several published gene lists describing breast cells revealed that the samples in cluster 1 share characteristics with stromal cells and stem cells, and to a certain degree with mesenchymal cells and myoepithelial cells. The samples in cluster 1 also share many features with the newly identified claudin-low breast cancer intrinsic subtype, which also shows characteristics of stromal and stem cells. More women belonging to cluster 1 have a family history of breast cancer and there is a slight overrepresentation of nulliparous women in cluster 1. Similar findings were seen in a separate dataset consisting of histologically normal tissue from both breasts harboring breast cancer and from mammoplasty reductions. Conclusion This is the first study to explore the variability of gene expression patterns in whole biopsies from normal breasts and identified distinct subtypes of normal breast tissue. Further studies are needed to determine the specific cell contribution to the variation in the biology of normal breasts, how the clusters identified relate to breast cancer risk and their possible link to the origin of the different molecular subtypes of breast

Gene expression profiles of breast biopsies from healthy women identify a group with claudin-low features.

PubMed

Haakensen, Vilde D; Lingjaerde, Ole Christian; Lüders, Torben; Riis, Margit; Prat, Aleix; Troester, Melissa A; Holmen, Marit M; Frantzen, Jan Ole; Romundstad, Linda; Navjord, Dina; Bukholm, Ida K; Johannesen, Tom B; Perou, Charles M; Ursin, Giske; Kristensen, Vessela N; Børresen-Dale, Anne-Lise; Helland, Aslaug

2011-11-01

Increased understanding of the variability in normal breast biology will enable us to identify mechanisms of breast cancer initiation and the origin of different subtypes, and to better predict breast cancer risk. Gene expression patterns in breast biopsies from 79 healthy women referred to breast diagnostic centers in Norway were explored by unsupervised hierarchical clustering and supervised analyses, such as gene set enrichment analysis and gene ontology analysis and comparison with previously published genelists and independent datasets. Unsupervised hierarchical clustering identified two separate clusters of normal breast tissue based on gene-expression profiling, regardless of clustering algorithm and gene filtering used. Comparison of the expression profile of the two clusters with several published gene lists describing breast cells revealed that the samples in cluster 1 share characteristics with stromal cells and stem cells, and to a certain degree with mesenchymal cells and myoepithelial cells. The samples in cluster 1 also share many features with the newly identified claudin-low breast cancer intrinsic subtype, which also shows characteristics of stromal and stem cells. More women belonging to cluster 1 have a family history of breast cancer and there is a slight overrepresentation of nulliparous women in cluster 1. Similar findings were seen in a separate dataset consisting of histologically normal tissue from both breasts harboring breast cancer and from mammoplasty reductions. This is the first study to explore the variability of gene expression patterns in whole biopsies from normal breasts and identified distinct subtypes of normal breast tissue. Further studies are needed to determine the specific cell contribution to the variation in the biology of normal breasts, how the clusters identified relate to breast cancer risk and their possible link to the origin of the different molecular subtypes of breast cancer.

Influences of Rhythm- and Timbre-Related Musical Features on Characteristics of Music-Induced Movement

PubMed Central

Burger, Birgitta; Thompson, Marc R.; Luck, Geoff; Saarikallio, Suvi; Toiviainen, Petri

2013-01-01

Music makes us move. Several factors can affect the characteristics of such movements, including individual factors or musical features. For this study, we investigated the effect of rhythm- and timbre-related musical features as well as tempo on movement characteristics. Sixty participants were presented with 30 musical stimuli representing different styles of popular music, and instructed to move along with the music. Optical motion capture was used to record participants’ movements. Subsequently, eight movement features and four rhythm- and timbre-related musical features were computationally extracted from the data, while the tempo was assessed in a perceptual experiment. A subsequent correlational analysis revealed that, for instance, clear pulses seemed to be embodied with the whole body, i.e., by using various movement types of different body parts, whereas spectral flux and percussiveness were found to be more distinctly related to certain body parts, such as head and hand movement. A series of ANOVAs with the stimuli being divided into three groups of five stimuli each based on the tempo revealed no significant differences between the groups, suggesting that the tempo of our stimuli set failed to have an effect on the movement features. In general, the results can be linked to the framework of embodied music cognition, as they show that body movements are used to reflect, imitate, and predict musical characteristics. PMID:23641220

Influences of rhythm- and timbre-related musical features on characteristics of music-induced movement.

PubMed

Burger, Birgitta; Thompson, Marc R; Luck, Geoff; Saarikallio, Suvi; Toiviainen, Petri

2013-01-01

Music makes us move. Several factors can affect the characteristics of such movements, including individual factors or musical features. For this study, we investigated the effect of rhythm- and timbre-related musical features as well as tempo on movement characteristics. Sixty participants were presented with 30 musical stimuli representing different styles of popular music, and instructed to move along with the music. Optical motion capture was used to record participants' movements. Subsequently, eight movement features and four rhythm- and timbre-related musical features were computationally extracted from the data, while the tempo was assessed in a perceptual experiment. A subsequent correlational analysis revealed that, for instance, clear pulses seemed to be embodied with the whole body, i.e., by using various movement types of different body parts, whereas spectral flux and percussiveness were found to be more distinctly related to certain body parts, such as head and hand movement. A series of ANOVAs with the stimuli being divided into three groups of five stimuli each based on the tempo revealed no significant differences between the groups, suggesting that the tempo of our stimuli set failed to have an effect on the movement features. In general, the results can be linked to the framework of embodied music cognition, as they show that body movements are used to reflect, imitate, and predict musical characteristics.

Novel histopathologic feature identified through image analysis augments stage II colorectal cancer clinical reporting

PubMed Central

Caie, Peter D.; Zhou, Ying; Turnbull, Arran K.; Oniscu, Anca; Harrison, David J.

2016-01-01

A number of candidate histopathologic factors show promise in identifying stage II colorectal cancer (CRC) patients at a high risk of disease-specific death, however they can suffer from low reproducibility and none have replaced classical pathologic staging. We developed an image analysis algorithm which standardized the quantification of specific histopathologic features and exported a multi-parametric feature-set captured without bias. The image analysis algorithm was executed across a training set (n = 50) and the resultant big data was distilled through decision tree modelling to identify the most informative parameters to sub-categorize stage II CRC patients. The most significant, and novel, parameter identified was the ‘sum area of poorly differentiated clusters’ (AreaPDC). This feature was validated across a second cohort of stage II CRC patients (n = 134) (HR = 4; 95% CI, 1.5– 11). Finally, the AreaPDC was integrated with the significant features within the clinical pathology report, pT stage and differentiation, into a novel prognostic index (HR = 7.5; 95% CI, 3–18.5) which improved upon current clinical staging (HR = 4.26; 95% CI, 1.7– 10.3). The identification of poorly differentiated clusters as being highly significant in disease progression presents evidence to suggest that these features could be the source of novel targets to decrease the risk of disease specific death. PMID:27322148

Determining local and contextual features describing appearance of difficult to identify mitotic figures

NASA Astrophysics Data System (ADS)

Gandomkar, Ziba; Brennan, Patrick C.; Mello-Thoms, Claudia

2017-03-01

Mitotic count is helpful in determining the aggressiveness of breast cancer. In previous studies, it was shown that the agreement among pathologists for grading mitotic index is fairly modest, as mitoses have a large variety of appearances and they could be mistaken for other similar objects. In this study, we determined local and contextual features that differ significantly between easily identifiable mitoses and challenging ones. The images were obtained from the Mitosis-Atypia 2014 challenge. In total, the dataset contained 453 mitotic figures. Two pathologists annotated each mitotic figure. In case of disagreement, an opinion from a third pathologist was requested. The mitoses were grouped into three categories, those recognized as "a true mitosis" by both pathologists ,those labelled as "a true mitosis" by only one of the first two readers and also the third pathologist, and those annotated as "probably a mitosis" by all readers or the majority of them. After color unmixing, the mitoses were segmented from H channel. Shape-based features along with intensity-based and textural features were extracted from H-channel, blue ratio channel and five different color spaces. Holistic features describing each image were also considered. The Kruskal-Wallis H test was used to identify significantly different features. Multiple comparisons were done using the rank-based version of Tukey-Kramer test. The results indicated that there are local and global features which differ significantly among different groups. In addition, variations between mitoses in different groups were captured in the features from HSL and LCH color space more than other ones.

Identifying the features of an exercise addiction: A Delphi study

PubMed Central

Macfarlane, Lucy; Owens, Glynn; Cruz, Borja del Pozo

2016-01-01

Objectives There remains limited consensus regarding the definition and conceptual basis of exercise addiction. An understanding of the factors motivating maintenance of addictive exercise behavior is important for appropriately targeting intervention. The aims of this study were twofold: first, to establish consensus on features of an exercise addiction using Delphi methodology and second, to identify whether these features are congruous with a conceptual model of exercise addiction adapted from the Work Craving Model. Methods A three-round Delphi process explored the views of participants regarding the features of an exercise addiction. The participants were selected from sport and exercise relevant domains, including physicians, physiotherapists, coaches, trainers, and athletes. Suggestions meeting consensus were considered with regard to the proposed conceptual model. Results and discussion Sixty-three items reached consensus. There was concordance of opinion that exercising excessively is an addiction, and therefore it was appropriate to consider the suggestions in light of the addiction-based conceptual model. Statements reaching consensus were consistent with all three components of the model: learned (negative perfectionism), behavioral (obsessive–compulsive drive), and hedonic (self-worth compensation and reduction of negative affect and withdrawal). Conclusions Delphi methodology allowed consensus to be reached regarding the features of an exercise addiction, and these features were consistent with our hypothesized conceptual model of exercise addiction. This study is the first to have applied Delphi methodology to the exercise addiction field, and therefore introduces a novel approach to exercise addiction research that can be used as a template to stimulate future examination using this technique. PMID:27554504

Research design features and patient characteristics associated with the outcome of antidepressant clinical trials.

PubMed

Khan, Arif; Kolts, Russell L; Thase, Michael E; Krishnan, K Ranga Rama; Brown, Walter

2004-11-01

The authors examined which, if any, research design features and patient characteristics would significantly differ between successful and unsuccessful antidepressant trials. Clinical trial data were reviewed for nine antidepressants approved by the Food and Drug Administration between 1985 and 2000. From the antidepressant research programs on these medications, 52 clinical trials were included in the study. The authors evaluated trial design features, patient characteristics, and difference in response between placebo and antidepressant. Nine trial design features and patient characteristics were present in the research programs for all nine of the antidepressants. The severity of depressive symptoms before patient randomization, the dosing schedule (flexible versus fixed), the number of treatment arms, and the percentage of female patients were significantly associated with the difference in response to antidepressant and placebo. The duration of the antidepressant trial, number of patients per treatment arm, number of sites, and mean age of the patients were similar in successful trials (with a greater antidepressant-placebo difference) and less successful trials (with a smaller antidepressant-placebo difference). These findings may help in the design of future antidepressant trials.

An expert botanical feature extraction technique based on phenetic features for identifying plant species.

PubMed

Kolivand, Hoshang; Fern, Bong Mei; Rahim, Mohd Shafry Mohd; Sulong, Ghazali; Baker, Thar; Tully, David

2018-01-01

In this paper, we present a new method to recognise the leaf type and identify plant species using phenetic parts of the leaf; lobes, apex and base detection. Most of the research in this area focuses on the popular features such as the shape, colour, vein, and texture, which consumes large amounts of computational processing and are not efficient, especially in the Acer database with a high complexity structure of the leaves. This paper is focused on phenetic parts of the leaf which increases accuracy. Detecting the local maxima and local minima are done based on Centroid Contour Distance for Every Boundary Point, using north and south region to recognise the apex and base. Digital morphology is used to measure the leaf shape and the leaf margin. Centroid Contour Gradient is presented to extract the curvature of leaf apex and base. We analyse 32 leaf images of tropical plants and evaluated with two different datasets, Flavia, and Acer. The best accuracy obtained is 94.76% and 82.6% respectively. Experimental results show the effectiveness of the proposed technique without considering the commonly used features with high computational cost.

An expert botanical feature extraction technique based on phenetic features for identifying plant species

PubMed Central

Fern, Bong Mei; Rahim, Mohd Shafry Mohd; Sulong, Ghazali; Baker, Thar; Tully, David

2018-01-01

In this paper, we present a new method to recognise the leaf type and identify plant species using phenetic parts of the leaf; lobes, apex and base detection. Most of the research in this area focuses on the popular features such as the shape, colour, vein, and texture, which consumes large amounts of computational processing and are not efficient, especially in the Acer database with a high complexity structure of the leaves. This paper is focused on phenetic parts of the leaf which increases accuracy. Detecting the local maxima and local minima are done based on Centroid Contour Distance for Every Boundary Point, using north and south region to recognise the apex and base. Digital morphology is used to measure the leaf shape and the leaf margin. Centroid Contour Gradient is presented to extract the curvature of leaf apex and base. We analyse 32 leaf images of tropical plants and evaluated with two different datasets, Flavia, and Acer. The best accuracy obtained is 94.76% and 82.6% respectively. Experimental results show the effectiveness of the proposed technique without considering the commonly used features with high computational cost. PMID:29420568

Learning from patients: Identifying design features of medicines that cause medication use problems.

PubMed

Notenboom, Kim; Leufkens, Hubert Gm; Vromans, Herman; Bouvy, Marcel L

2017-01-30

Usability is a key factor in ensuring safe and efficacious use of medicines. However, several studies showed that people experience a variety of problems using their medicines. The purpose of this study was to identify design features of oral medicines that cause use problems among older patients in daily practice. A qualitative study with semi-structured interviews on the experiences of older people with the use of their medicines was performed (n=59). Information on practical problems, strategies to overcome these problems and the medicines' design features that caused these problems were collected. The practical problems and management strategies were categorised into 'use difficulties' and 'use errors'. A total of 158 use problems were identified, of which 45 were categorized as use difficulties and 113 as use error. Design features that contributed the most to the occurrence of use difficulties were the dimensions and surface texture of the dosage form (29.6% and 18.5%, respectively). Design features that contributed the most to the occurrence of use errors were the push-through force of blisters (22.1%) and tamper evident packaging (12.1%). These findings will help developers of medicinal products to proactively address potential usability issues with their medicines. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Newborn human brain identifies repeated auditory feature conjunctions of low sequential probability.

PubMed

Ruusuvirta, Timo; Huotilainen, Minna; Fellman, Vineta; Näätänen, Risto

2004-11-01

Natural environments are usually composed of multiple sources for sounds. The sounds might physically differ from one another only as feature conjunctions, and several of them might occur repeatedly in the short term. Nevertheless, the detection of rare sounds requires the identification of the repeated ones. Adults have some limited ability to effortlessly identify repeated sounds in such acoustically complex environments, but the developmental onset of this finite ability is unknown. Sleeping newborn infants were presented with a repeated tone carrying six frequent (P = 0.15 each) and six rare (P approximately 0.017 each) conjunctions of its frequency, intensity and duration. Event-related potentials recorded from the infants' scalp were found to shift in amplitude towards positive polarity selectively in response to rare conjunctions. This finding suggests that humans are relatively hard-wired to preattentively identify repeated auditory feature conjunctions even when such conjunctions occur rarely among other similar ones.

Microbiota fingerprints lose individually identifying features over time.

PubMed

Wilkins, David; Leung, Marcus H Y; Lee, Patrick K H

2017-01-09

Humans host individually unique skin microbiota, suggesting that microbiota traces transferred from skin to surfaces could serve as forensic markers analogous to fingerprints. While it is known that individuals leave identifiable microbiota traces on surfaces, it is not clear for how long these traces persist. Moreover, as skin and surface microbiota change with time, even persistent traces may lose their forensic potential as they would cease to resemble the microbiota of the person who left them. We followed skin and surface microbiota within households for four seasons to determine whether accurate microbiota-based matching of individuals to their households could be achieved across long time delays. While household surface microbiota traces could be matched to the correct occupant or occupants with 67% accuracy, accuracy decreased substantially when skin and surface samples were collected in different seasons, and particularly when surface samples were collected long after skin samples. Most OTUs persisted on skin or surfaces for less than one season, indicating that OTU loss was the major cause of decreased matching accuracy. OTUs that were more useful for individual identification persisted for less time and were less likely to be deposited from skin to surface, suggesting a trade-off between the longevity and identifying value of microbiota traces. While microbiota traces have potential forensic value, unlike fingerprints they are not static and may degrade in a way that preferentially erases features useful in identifying individuals.

MO-DE-207B-10: Impact of Morphologic Characteristics On Radiomics Features From Contast-Enhanced CT for Primary Lung Tumors

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

Fried, D; Zhang, L; Fave, X

Purpose: Determine the impact of morphologic characteristics (e.g. necrosis, vascular enhancement, and cavitation) on radiomic features from contrast enhanced CT (CE-CT) in primary lung tumors. Methods: We developed an auto-segmentation algorithm to separate lung tumors on contrast-enhanced CT into cavitation (air), necrosis, tissue, and enhancing vessels using a combination of thresholding and region-growing. An auto-segmentation algorithm was also designed to identify necrosis on FDG-PET scans. Wilcoxon rank-sum tests were used to determine if significant differences existed in radiomics features (histogram-uniformity and Laplacian-of-Gaussian average) from 249 patients, found to prognostic in previous work, based on the presence/absence of morphologic features. Featuremore » values were also compared between the original tumor contours and contours excluding a specific morphologic feature. Comparison of necrosis segmentation on CE-CT versus FDG-PET was performed in 78 patients to assess for agreement using the concordance correlation coefficient (CCC). Results: Tumors with cavitation and enhancing vasculature had lower uniformity values (p = 0.001 and p = 0.03, respectively). Tumors with enhancing vasculature and necrosis had higher Laplacian-of-Gaussian average values (measure of “edges” within the tumor) (p < 0.001). Removing these tissue types from regions-of-interest did not drastically alter either radiomic feature value (all scenarios had R{sup 2} > 0.8). This suggests there may be interactions between morphologic characteristics and the radiomic feature value of tumor tissue. Comparison of necrosis volume and percent necrosis volume of tumor were found to have CCC values of 0.85 and 0.76, respectively between CE-CT and FDG-PET segmentation methods. Conclusions: Tumors with enhancing vasculature, necrosis, and cavitation have higher radiomic feature values that are associated with poor prognosis than tumors without these features. Removing these

Identifying job characteristics related to employed women's breastfeeding behaviors.

PubMed

Spitzmueller, Christiane; Zhang, Jing; Thomas, Candice L; Wang, Zhuxi; Fisher, Gwenith G; Matthews, Russell A; Strathearn, Lane

2018-05-14

For employed mothers of infants, reconciliation of work demands and breastfeeding constitutes a significant challenge. The discontinuation of breastfeeding has the potential to result in negative outcomes for the mother (e.g., higher likelihood of obesity), her employer (e.g., increased absenteeism), and her infant (e.g., increased risk of infection). Given previous research findings identifying return to work as a major risk factor for breastfeeding cessation, we investigate what types of job characteristics relate to women's intentions to breastfeed shortly after giving birth and women's actual breastfeeding initiation and duration. Using job titles and job descriptors contained in a large Australian longitudinal cohort data set (N = 809), we coded job titles using the U.S. Department of Labor (DOL)'s Occupational Information Network (O*NET) database and extracted job characteristics. Hazardous working conditions and job autonomy were identified as significant determinants of women's breastfeeding intentions, their initiation of breastfeeding, and ultimately their breastfeeding continuation. Hence, we recommend that human resource professionals, managers, and public health initiatives provide breastfeeding-supportive resources to women who, based on their job characteristics, are at high risk to prematurely discontinue breastfeeding to ensure these mothers have equal opportunity to reap the benefits of breastfeeding. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Ocular motor characteristics of different subtypes of spinocerebellar ataxia: distinguishing features.

PubMed

Kim, Ji Sun; Kim, Ji Soo; Youn, Jinyoung; Seo, Dae-Won; Jeong, Yuri; Kang, Ji-Hoon; Park, Jeong Ho; Cho, Jin Whan

2013-08-01

Because of frequent involvement of the cerebellum and brainstem, ocular motor abnormalities are key features of spinocerebellar ataxias and may aid in differential diagnosis. Our objective for this study was to distinguish the subtypes by ophthalmologic features after head-shaking and positional maneuvers, which are not yet recognized as differential diagnostic tools in most common forms of spinocerebellar ataxias. Of the 302 patients with a diagnosis of cerebellar ataxia in 3 Korean University Hospitals from June 2011 to June 2012, 48 patients with spinocerebellar ataxia types 1, 2, 3, 6, 7, or 8 or with undetermined spinocerebellar ataxias were enrolled. All patients underwent a video-oculographic recording of fixation abnormalities, gaze-evoked nystagmus, positional and head-shaking nystagmus, and dysmetric saccades. Logistic regression analysis controlling for disease duration revealed that spontaneous and positional downbeat nystagmus and perverted head-shaking nystagmus were strong predictors for spinocerebellar ataxia 6, whereas saccadic intrusions and oscillations were identified as positive indicators of spinocerebellar ataxia 3. In contrast, the presence of gaze-evoked nystagmus and dysmetric saccades was a negative predictor of spinocerebellar ataxia 2. Positional maneuvers and horizontal head shaking occasionally induced or augmented saccadic intrusions/oscillations in patients with spinocerebellar ataxia types 1, 2, and 3 and undetermined spinocerebellar ataxia. The results indicated that perverted head-shaking nystagmus may be the most sensitive parameter for SCA6, whereas saccadic intrusions/oscillations are the most sensitive for spinocerebellar ataxia 3. In contrast, a paucity of gaze-evoked nystagmus and dysmetric saccades is more indicative of spinocerebellar ataxia 2. Head-shaking and positional maneuvers aid in defining ocular motor characteristics in spinocerebellar ataxias. © 2013 Movement Disorder Society. Copyright © 2013 Movement

A survey of mass analyzers. [characteristics and features of various instruments and techniques

NASA Technical Reports Server (NTRS)

Moore, W. W., Jr.; Tashbar, P. W.

1973-01-01

With the increasing applications of mass spectrometry technology to diverse services areas, a need has developed for a consolidated survey of the essential characteristics and features of the various instruments and techniques. This report is one approach to satisfying this need. Information has been collected and consolidated into a format which includes for each approach: (1) a general technique description, (2) instrument features information, and (3) a summary of pertinent advantages and disadvantages. With this information, the potential mass spectrometer user should be able to more efficiently select the most appropriate instrument.

Follicular morphological characteristics may be associated with invasion in follicular thyroid neoplasms with papillary-like nuclear features.

PubMed

Can, Nuray; Celik, Mehmet; Sezer, Yavuz Atakan; Ozyilmaz, Filiz; Ayturk, Semra; Tastekin, Ebru; Sut, Necdet; Gurkan, Hakan; Ustun, Funda; Bulbul, Buket Yilmaz; Guldiken, Sibel; Puyan, Fulya Oz

2017-08-20

The newly proposed nomenclature and diagnostic criteria for encapsulated follicular variant of papillary thyroid carcinoma (EFVPTC), the noninvasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP), could improve the consistency and accuracy of diagnosing this entity. Diagnosis of NIFTP requires evaluation of the complete tumor border or capsule. The presence of tumor invasion in follicular thyroid neoplasms with papillary-like nuclear features has been recently discussed by many authors. In this study, we examined the predictive value and association of follicular morphological characteristics with the tumor invasion. In addition, we analyzed the association between tumor encapsulation and molecular profile in EFVPTC/NIFTP cases. A total of 106 cases of FVPTC were included in the study. The tumors were grouped based on the presence of tumor capsule and characteristics of tumor border, as 1) completely encapsulated tumors without invasion, 2) encapsulated tumors with invasion, 3) infiltrative tumors without a capsule. Clinicopathological features, histomorphological features [nuclear criteria, minor diagnostic features, follicles oriented perpendicular to tumor border/capsule (FOPBC)] and molecular alterations in BRAF, NRAS, and KRAS genes were evaluated. FOPBC were significantly more frequently seen in encapsulated tumors with invasion (p = 0.008). The nuclear features were not associated with the presence of encapsulation and characteristics of tumor border. BRAF mutation was more frequent in infiltrative tumors, while NRAS mutation was more frequent in encapsulated tumors, but the results were not statistically significant (p = 0.917). In conclusion, FOPBC histomorphological feature may be associated with tumor invasion in EFVPTC/NIFTP. Additionally, BRAF/KRAS/NRAS mutation analysis may prevent inadequate treatment in these patients.

A P-Norm Robust Feature Extraction Method for Identifying Differentially Expressed Genes

PubMed Central

Liu, Jian; Liu, Jin-Xing; Gao, Ying-Lian; Kong, Xiang-Zhen; Wang, Xue-Song; Wang, Dong

2015-01-01

In current molecular biology, it becomes more and more important to identify differentially expressed genes closely correlated with a key biological process from gene expression data. In this paper, based on the Schatten p-norm and Lp-norm, a novel p-norm robust feature extraction method is proposed to identify the differentially expressed genes. In our method, the Schatten p-norm is used as the regularization function to obtain a low-rank matrix and the Lp-norm is taken as the error function to improve the robustness to outliers in the gene expression data. The results on simulation data show that our method can obtain higher identification accuracies than the competitive methods. Numerous experiments on real gene expression data sets demonstrate that our method can identify more differentially expressed genes than the others. Moreover, we confirmed that the identified genes are closely correlated with the corresponding gene expression data. PMID:26201006

A P-Norm Robust Feature Extraction Method for Identifying Differentially Expressed Genes.

PubMed

Liu, Jian; Liu, Jin-Xing; Gao, Ying-Lian; Kong, Xiang-Zhen; Wang, Xue-Song; Wang, Dong

2015-01-01

In current molecular biology, it becomes more and more important to identify differentially expressed genes closely correlated with a key biological process from gene expression data. In this paper, based on the Schatten p-norm and Lp-norm, a novel p-norm robust feature extraction method is proposed to identify the differentially expressed genes. In our method, the Schatten p-norm is used as the regularization function to obtain a low-rank matrix and the Lp-norm is taken as the error function to improve the robustness to outliers in the gene expression data. The results on simulation data show that our method can obtain higher identification accuracies than the competitive methods. Numerous experiments on real gene expression data sets demonstrate that our method can identify more differentially expressed genes than the others. Moreover, we confirmed that the identified genes are closely correlated with the corresponding gene expression data.

Identifying marker genes in transcription profiling data using a mixture of feature relevance experts.

PubMed

Chow, M L; Moler, E J; Mian, I S

2001-03-08

Transcription profiling experiments permit the expression levels of many genes to be measured simultaneously. Given profiling data from two types of samples, genes that most distinguish the samples (marker genes) are good candidates for subsequent in-depth experimental studies and developing decision support systems for diagnosis, prognosis, and monitoring. This work proposes a mixture of feature relevance experts as a method for identifying marker genes and illustrates the idea using published data from samples labeled as acute lymphoblastic and myeloid leukemia (ALL, AML). A feature relevance expert implements an algorithm that calculates how well a gene distinguishes samples, reorders genes according to this relevance measure, and uses a supervised learning method [here, support vector machines (SVMs)] to determine the generalization performances of different nested gene subsets. The mixture of three feature relevance experts examined implement two existing and one novel feature relevance measures. For each expert, a gene subset consisting of the top 50 genes distinguished ALL from AML samples as completely as all 7,070 genes. The 125 genes at the union of the top 50s are plausible markers for a prototype decision support system. Chromosomal aberration and other data support the prediction that the three genes at the intersection of the top 50s, cystatin C, azurocidin, and adipsin, are good targets for investigating the basic biology of ALL/AML. The same data were employed to identify markers that distinguish samples based on their labels of T cell/B cell, peripheral blood/bone marrow, and male/female. Selenoprotein W may discriminate T cells from B cells. Results from analysis of transcription profiling data from tumor/nontumor colon adenocarcinoma samples support the general utility of the aforementioned approach. Theoretical issues such as choosing SVM kernels and their parameters, training and evaluating feature relevance experts, and the impact of

Improving Outcomes for Students with Disabilities: Identifying Characteristics of Successful Districts

ERIC Educational Resources Information Center

DeVries, Melissa; Tkatchov, Oran

2017-01-01

The common characteristics among Arizona districts and charters with high academic outcomes for student disabilities were identified in a qualitative study involving site visits and interviews. In 2014, the Arizona Department of Education examined over three years of state testing data to identify districts and charter schools that closed the…

The value of anthropometric indices for identifying women with features of metabolic syndrome

USDA-ARS?s Scientific Manuscript database

BMI is a widely used anthropometric measure for identifying CVD and metabolic syndrome (MetS) risk. Two new anthropometric indices are A Body Shape Index (ABSI) and Body Roundness Index (BRI) that may provide better correlations to features of MetS. Methods: Subject data were obtained from 91 over...

40 CFR 261.10 - Criteria for identifying the characteristics of hazardous waste.

Code of Federal Regulations, 2014 CFR

2014-07-01

... characteristics of hazardous waste. 261.10 Section 261.10 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) SOLID WASTES (CONTINUED) IDENTIFICATION AND LISTING OF HAZARDOUS WASTE Criteria for Identifying the Characteristics of Hazardous Waste and for Listing Hazardous Waste § 261.10 Criteria for...

40 CFR 261.10 - Criteria for identifying the characteristics of hazardous waste.

Code of Federal Regulations, 2013 CFR

2013-07-01

... characteristics of hazardous waste. 261.10 Section 261.10 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) SOLID WASTES (CONTINUED) IDENTIFICATION AND LISTING OF HAZARDOUS WASTE Criteria for Identifying the Characteristics of Hazardous Waste and for Listing Hazardous Waste § 261.10 Criteria for...

40 CFR 261.10 - Criteria for identifying the characteristics of hazardous waste.

Code of Federal Regulations, 2012 CFR

2012-07-01

... characteristics of hazardous waste. 261.10 Section 261.10 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) SOLID WASTES (CONTINUED) IDENTIFICATION AND LISTING OF HAZARDOUS WASTE Criteria for Identifying the Characteristics of Hazardous Waste and for Listing Hazardous Waste § 261.10 Criteria for...

40 CFR 261.10 - Criteria for identifying the characteristics of hazardous waste.

Code of Federal Regulations, 2010 CFR

2010-07-01

... characteristics of hazardous waste. 261.10 Section 261.10 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) SOLID WASTES (CONTINUED) IDENTIFICATION AND LISTING OF HAZARDOUS WASTE Criteria for Identifying the Characteristics of Hazardous Waste and for Listing Hazardous Waste § 261.10 Criteria for...

40 CFR 261.10 - Criteria for identifying the characteristics of hazardous waste.

Code of Federal Regulations, 2011 CFR

2011-07-01

... characteristics of hazardous waste. 261.10 Section 261.10 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) SOLID WASTES (CONTINUED) IDENTIFICATION AND LISTING OF HAZARDOUS WASTE Criteria for Identifying the Characteristics of Hazardous Waste and for Listing Hazardous Waste § 261.10 Criteria for...

Etiological features of borderline personality related characteristics in a birth cohort of 12-year-old children

PubMed Central

BELSKY, DANIEL W.; CASPI, AVSHALOM; ARSENEAULT, LOUISE; BLEIDORN, WIEBKE; FONAGY, PETER; GOODMAN, MARIANNE; HOUTS, RENATE; MOFFITT, TERRIE E.

2012-01-01

It has been reported that borderline personality related characteristics can be observed in children, and that these characteristics are associated with increased risk for the development of borderline personality disorder. It is not clear whether borderline personality related characteristics in children share etiological features with adult borderline personality disorder. We investigated the etiology of borderline personality related characteristics in a longitudinal cohort study of 1,116 pairs of same-sex twins followed from birth through age 12 years. Borderline personality related characteristics measured at age 12 years were highly heritable, were more common in children who had exhibited poor cognitive function, impulsivity, and more behavioral and emotional problems at age 5 years, and co-occurred with symptoms of conduct disorder, depression, anxiety, and psychosis. Exposure to harsh treatment in the family environment through age 10 years predicted borderline personality related characteristics at age 12 years. This association showed evidence of environmental mediation and was stronger among children with a family history of psychiatric illness, consistent with diathesis–stress models of borderline etiology. Results indicate that borderline personality related characteristics in children share etiological features with borderline personality disorder in adults and suggest that inherited and environmental risk factors make independent and interactive contributions to borderline etiology. PMID:22293008

Etiological features of borderline personality related characteristics in a birth cohort of 12-year-old children.

PubMed

Belsky, Daniel W; Caspi, Avshalom; Arseneault, Louise; Bleidorn, Wiebke; Fonagy, Peter; Goodman, Marianne; Houts, Renate; Moffitt, Terrie E

2012-02-01

It has been reported that borderline personality related characteristics can be observed in children, and that these characteristics are associated with increased risk for the development of borderline personality disorder. It is not clear whether borderline personality related characteristics in children share etiological features with adult borderline personality disorder. We investigated the etiology of borderline personality related characteristics in a longitudinal cohort study of 1,116 pairs of same-sex twins followed from birth through age 12 years. Borderline personality related characteristics measured at age 12 years were highly heritable, were more common in children who had exhibited poor cognitive function, impulsivity, and more behavioral and emotional problems at age 5 years, and co-occurred with symptoms of conduct disorder, depression, anxiety, and psychosis. Exposure to harsh treatment in the family environment through age 10 years predicted borderline personality related characteristics at age 12 years. This association showed evidence of environmental mediation and was stronger among children with a family history of psychiatric illness, consistent with diathesis-stress models of borderline etiology. Results indicate that borderline personality related characteristics in children share etiological features with borderline personality disorder in adults and suggest that inherited and environmental risk factors make independent and interactive contributions to borderline etiology.

Identifying Features of Bodily Expression As Indicators of Emotional Experience during Multimedia Learning

PubMed Central

Riemer, Valentin; Frommel, Julian; Layher, Georg; Neumann, Heiko; Schrader, Claudia

2017-01-01

The importance of emotions experienced by learners during their interaction with multimedia learning systems, such as serious games, underscores the need to identify sources of information that allow the recognition of learners’ emotional experience without interrupting the learning process. Bodily expression is gaining in attention as one of these sources of information. However, to date, the question of how bodily expression can convey different emotions has largely been addressed in research relying on acted emotion displays. Following a more contextualized approach, the present study aims to identify features of bodily expression (i.e., posture and activity of the upper body and the head) that relate to genuine emotional experience during interaction with a serious game. In a multimethod approach, 70 undergraduates played a serious game relating to financial education while their bodily expression was captured using an off-the-shelf depth-image sensor (Microsoft Kinect). In addition, self-reports of experienced enjoyment, boredom, and frustration were collected repeatedly during gameplay, to address the dynamic changes in emotions occurring in educational tasks. Results showed that, firstly, the intensities of all emotions indeed changed significantly over the course of the game. Secondly, by using generalized estimating equations, distinct features of bodily expression could be identified as significant indicators for each emotion under investigation. A participant keeping their head more turned to the right was positively related to frustration being experienced, whereas keeping their head more turned to the left was positively related to enjoyment. Furthermore, having their upper body positioned more closely to the gaming screen was also positively related to frustration. Finally, increased activity of a participant’s head emerged as a significant indicator of boredom being experienced. These results confirm the value of bodily expression as an indicator

Discriminative Features Mining for Offline Handwritten Signature Verification

NASA Astrophysics Data System (ADS)

Neamah, Karrar; Mohamad, Dzulkifli; Saba, Tanzila; Rehman, Amjad

2014-03-01

Signature verification is an active research area in the field of pattern recognition. It is employed to identify the particular person with the help of his/her signature's characteristics such as pen pressure, loops shape, speed of writing and up down motion of pen, writing speed, pen pressure, shape of loops, etc. in order to identify that person. However, in the entire process, features extraction and selection stage is of prime importance. Since several signatures have similar strokes, characteristics and sizes. Accordingly, this paper presents combination of orientation of the skeleton and gravity centre point to extract accurate pattern features of signature data in offline signature verification system. Promising results have proved the success of the integration of the two methods.

Features of current-voltage characteristic of nonequilibrium trench MOS barrier Schottky diode

NASA Astrophysics Data System (ADS)

Mamedov, R. K.; Aslanova, A. R.

2018-06-01

The trench MOS barrier Schottky diodes (TMBS diode) under the influence of the voltage drop of the additional electric field (AEF) appearing in the near-contact region of the semiconductor are in a nonequilibrium state and their closed external circuit flows currents in the absence of an external voltage. When an external voltage is applied to the TMBS diode, the current transmission is described by the thermionic emission theory with a specific feature. Both forward and reverse I-V characteristics of the TMBS diode consist of two parts. In the initial first part of the forward I-V characteristic there are no forward currents, but reverse saturation currents flow, in its subsequent second part the currents increase exponentially with the voltage. In the initial first part of the reverse I-V characteristic, the currents increase in an abrupt way and in the subsequent second part the saturation currents flow under the action of the image force. The mathematical expressions for forward and reverse I-V characteristic of the TMBS diode and also narrow or nanostructure Schottky diode are proposed, which are in good agreement with the results of experimental and calculated I-V characteristics.

Identifying protein complex by integrating characteristic of core-attachment into dynamic PPI network.

PubMed

Shen, Xianjun; Yi, Li; Jiang, Xingpeng; He, Tingting; Yang, Jincai; Xie, Wei; Hu, Po; Hu, Xiaohua

2017-01-01

How to identify protein complex is an important and challenging task in proteomics. It would make great contribution to our knowledge of molecular mechanism in cell life activities. However, the inherent organization and dynamic characteristic of cell system have rarely been incorporated into the existing algorithms for detecting protein complexes because of the limitation of protein-protein interaction (PPI) data produced by high throughput techniques. The availability of time course gene expression profile enables us to uncover the dynamics of molecular networks and improve the detection of protein complexes. In order to achieve this goal, this paper proposes a novel algorithm DCA (Dynamic Core-Attachment). It detects protein-complex core comprising of continually expressed and highly connected proteins in dynamic PPI network, and then the protein complex is formed by including the attachments with high adhesion into the core. The integration of core-attachment feature into the dynamic PPI network is responsible for the superiority of our algorithm. DCA has been applied on two different yeast dynamic PPI networks and the experimental results show that it performs significantly better than the state-of-the-art techniques in terms of prediction accuracy, hF-measure and statistical significance in biology. In addition, the identified complexes with strong biological significance provide potential candidate complexes for biologists to validate.

Feature engineering for drug name recognition in biomedical texts: feature conjunction and feature selection.

PubMed

Liu, Shengyu; Tang, Buzhou; Chen, Qingcai; Wang, Xiaolong; Fan, Xiaoming

2015-01-01

Drug name recognition (DNR) is a critical step for drug information extraction. Machine learning-based methods have been widely used for DNR with various types of features such as part-of-speech, word shape, and dictionary feature. Features used in current machine learning-based methods are usually singleton features which may be due to explosive features and a large number of noisy features when singleton features are combined into conjunction features. However, singleton features that can only capture one linguistic characteristic of a word are not sufficient to describe the information for DNR when multiple characteristics should be considered. In this study, we explore feature conjunction and feature selection for DNR, which have never been reported. We intuitively select 8 types of singleton features and combine them into conjunction features in two ways. Then, Chi-square, mutual information, and information gain are used to mine effective features. Experimental results show that feature conjunction and feature selection can improve the performance of the DNR system with a moderate number of features and our DNR system significantly outperforms the best system in the DDIExtraction 2013 challenge.

Growing up with an ill parent: An examination of family characteristics and parental illness features.

PubMed

Stoeckel, Maggie; Weissbrod, Carol

2015-12-01

Existing literature suggests that the children of ill parents are vulnerable to a variety of psychosocial difficulties such as depression and anxiety. The purpose of the current study is to investigate the impact of family characteristics (parental involvement, familial support, stress experienced as a result of parental illness) and parental illness features (severity, duration, recovery status, frequency of symptoms, course) on the psychosocial functioning (depression, anxiety, life satisfaction) of late adolescents who have grown up with an ill parent but no longer live with their parents. Participants were 71 college students with a parent who experienced a chronic medical condition while they were growing up. Participants provided information regarding family characteristics, parental illness features, and the impact of parental illness. Impact of parental illness was assessed using the Impact of Illness Scale. Participants also completed measures of depression, anxiety, and life satisfaction. Participants' reported impact of parent illness was positively correlated with participant depression and anxiety. Several family characteristics and parental illness features were significantly associated with participant psychosocial functioning. In particular, lower parental involvement was correlated with greater participant depression and anxiety, as well as lower life satisfaction. These findings extend our understanding of the impact of parental illness on late adolescents' psychosocial functioning. Results could have clinical applications for psychosocial interventions in children and families coping with chronic illness. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

Windblown Features on Venus and Geological Mapping

NASA Technical Reports Server (NTRS)

Greeley, Ronald

1999-01-01

The objectives of this study were to: 1) develop a global data base of aeolian features by searching Magellan coverage for possible time-variable wind streaks, 2) analyze the data base to characterize aeolian features and processes on Venus, 3) apply the analysis to assessments of wind patterns near the surface and for comparisons with atmospheric circulation models, 4) analyze shuttle radar data acquired for aeolian features on Earth to determine their radar characteristics, and 5) conduct geological mapping of two quadrangles. Wind, or aeolian, features are observed on Venus and aeolian processes play a role in modifying its surface. Analysis of features resulting from aeolian processes provides insight into characteristics of both the atmosphere and the surface. Wind related features identified on Venus include erosional landforms (yardangs), depositional dune fields, and features resulting from the interaction of the atmosphere and crater ejecta at the time of impact. The most abundant aeolian features are various wind streaks. Their discovery on Venus afforded the opportunity to learn about the interaction of the atmosphere and surface, both for the identification of sediments and in mapping near-surface winds.

Shear-wave elastographic features of breast cancers: comparison with mechanical elasticity and histopathologic characteristics.

PubMed

Lee, Su Hyun; Moon, Woo Kyung; Cho, Nariya; Chang, Jung Min; Moon, Hyeong-Gon; Han, Wonshik; Noh, Dong-Young; Lee, Jung Chan; Kim, Hee Chan; Lee, Kyoung-Bun; Park, In-Ae

2014-03-01

The objective of this study was to compare the quantitative and qualitative shear-wave elastographic (SWE) features of breast cancers with mechanical elasticity and histopathologic characteristics. This prospective study was conducted with institutional review board approval, and written informed consent was obtained. Shear-wave elastography was performed for 30 invasive breast cancers in 30 women before surgery. The mechanical elasticity of a fresh breast tissue section, correlated with the ultrasound image, was measured using an indentation system. Quantitative (maximum, mean, minimum, and standard deviation of elasticity in kilopascals) and qualitative (color heterogeneity and presence of signal void areas in the mass) SWE features were compared with mechanical elasticity and histopathologic characteristics using the Pearson correlation coefficient and the Wilcoxon signed rank test. Maximum SWE values showed a moderate correlation with maximum mechanical elasticity (r = 0.530, P = 0.003). There were no significant differences between SWE values and mechanical elasticity in histologic grade I or II cancers (P = 0.268). However, SWE values were significantly higher than mechanical elasticity in histologic grade III cancers (P < 0.001), which have low amounts of fibrosis, high tumor cellularity, and intratumoral necrosis. In addition, color heterogeneity was correlated with intratumoral heterogeneity of mechanical elasticity (r = 0.469, P = 0.009). Signal void areas in the masses were present in 43% of breast cancers (13 of 30) and were correlated with dense collagen depositions (n = 11) or intratumoral necrosis (n = 2). Quantitative and qualitative SWE features reflect both the mechanical elasticity and histopathologic characteristics of breast cancers.

40 CFR 268.38 - Waste specific prohibitions-newly identified organic toxicity characteristic wastes and newly...

Code of Federal Regulations, 2010 CFR

2010-07-01

... identified organic toxicity characteristic wastes and newly listed coke by-product and chlorotoluene... specific prohibitions—newly identified organic toxicity characteristic wastes and newly listed coke by-product and chlorotoluene production wastes. (a) Effective December 19, 1994, the wastes specified in 40...

Fractal Complexity-Based Feature Extraction Algorithm of Communication Signals

NASA Astrophysics Data System (ADS)

Wang, Hui; Li, Jingchao; Guo, Lili; Dou, Zheng; Lin, Yun; Zhou, Ruolin

How to analyze and identify the characteristics of radiation sources and estimate the threat level by means of detecting, intercepting and locating has been the central issue of electronic support in the electronic warfare, and communication signal recognition is one of the key points to solve this issue. Aiming at accurately extracting the individual characteristics of the radiation source for the increasingly complex communication electromagnetic environment, a novel feature extraction algorithm for individual characteristics of the communication radiation source based on the fractal complexity of the signal is proposed. According to the complexity of the received signal and the situation of environmental noise, use the fractal dimension characteristics of different complexity to depict the subtle characteristics of the signal to establish the characteristic database, and then identify different broadcasting station by gray relation theory system. The simulation results demonstrate that the algorithm can achieve recognition rate of 94% even in the environment with SNR of -10dB, and this provides an important theoretical basis for the accurate identification of the subtle features of the signal at low SNR in the field of information confrontation.

Characteristic Lifetime Of A Polarized Feature In The V=0, J=1-0 Sio Maser VY Canis Majoris

NASA Astrophysics Data System (ADS)

Rislow, Benjamin; McIntosh, G. C.

2008-05-01

A time series cross correlation analysis has been developed for calculating the characteristic lifetime of linearly polarized features in the spectrum of silicon monoxide masers. Our observations of VY CMa in the v=0, J=1→0; transition from June 2003 to March 2006 revealed a highly linearly polarized feature at Vlsr=18.5 km s-1. Applying the cross correlation to this feature gave a characteristic lifetime of 2800 days. This time is much longer than the v=1, J=2→1; transition's lifetime of 645 days and indicates that the two transitions occur under different physical conditions. This research was supported by the University of Minnesota and the University of Minnesota, Morris.

System and method employing a self-organizing map load feature database to identify electric load types of different electric loads

DOEpatents

Lu, Bin; Harley, Ronald G.; Du, Liang; Yang, Yi; Sharma, Santosh K.; Zambare, Prachi; Madane, Mayura A.

2014-06-17

A method identifies electric load types of a plurality of different electric loads. The method includes providing a self-organizing map load feature database of a plurality of different electric load types and a plurality of neurons, each of the load types corresponding to a number of the neurons; employing a weight vector for each of the neurons; sensing a voltage signal and a current signal for each of the loads; determining a load feature vector including at least four different load features from the sensed voltage signal and the sensed current signal for a corresponding one of the loads; and identifying by a processor one of the load types by relating the load feature vector to the neurons of the database by identifying the weight vector of one of the neurons corresponding to the one of the load types that is a minimal distance to the load feature vector.

Identifying local characteristic lengths governing sound wave properties in solid foams

NASA Astrophysics Data System (ADS)

Tan Hoang, Minh; Perrot, Camille

2013-02-01

Identifying microscopic geometric properties and fluid flow through opened-cell and partially closed-cell solid structures is a challenge for material science, in particular, for the design of porous media used as sound absorbers in building and transportation industries. We revisit recent literature data to identify the local characteristic lengths dominating the transport properties and sound absorbing behavior of polyurethane foam samples by performing numerical homogenization simulations. To determine the characteristic sizes of the model, we need porosity and permeability measurements in conjunction with ligament lengths estimates from available scanning electron microscope images. We demonstrate that this description of the porous material, consistent with the critical path picture following from the percolation arguments, is widely applicable. This is an important step towards tuning sound proofing properties of complex materials.

Pathogenic features and characteristics of food borne pathogens biofilm: Biomass, viability and matrix.

PubMed

Lin, Shiqi; Yang, Ling; Chen, Gu; Li, Bing; Chen, Dingqiang; Li, Lin; Xu, Zhenbo

2017-10-01

Biofilm is a ubiquitous growth pattern of bacterial species survival but is notorious for its threat on public health and food contamination. Extensive studies of the biofilm structure, formation, quantification, quorum sensing system and underlying control strategies have been reported during the past decades. Insightful elucidation of the pathogenic features and characteristic of bacterial biofilm can facilitate in devising appropriate control strategies for biofilm eradication. Therefore, this review mainly summarized the pathogenic features of biofilms from food borne microorganisms, including the biomass (which could be quantified using crystal violet and fluorogenic dye Syto9 assays), viability (which could be determined by tetrazolium salts, fluorescein diacetate, resazurin staining and alamar blue assays) and matrix (which are commonly detected by dimethyl methylene blue and wheat germ agglutinin assays). In addition, three features were further compared with its particular benefits in specific application. Copyright © 2017 Elsevier Ltd. All rights reserved.

Characteristics of arachnoids from Magellan data

NASA Technical Reports Server (NTRS)

Dawson, C. B.; Crumpler, L. S.

1993-01-01

Current high resolution Magellan data enables more detailed geological study of arachnoids, first identified by Barsukov et al. as features characterized by a combination of radar-bright, concentric rings and radiating lineations, named 'arachnoids' on the basis of their spider and web-like appearance. Identification of arachnoids in Magellan data has been based on SAR images, in keeping with the original definition. However, there is some overlap by other workers in identification of arachnoids, corona (predominantly bright rings), and novae (predominantly radiating lineations), as all of these features share some common characteristics. Features used in this survey were chosen based on their classification as arachnoids in Head et al.'s catalog and on SAR characteristics matching Barsukov et al.'s original definition. The 259 arachnoids have been currently identified on Venus, all of which were considered in this study. Fifteen arachnoids from different regions, chosen for their 'type' characteristics and lack of deformation by other regional processes, were studied in depth, using SAR and altimetric data to map and profile these arachnoids in an attempt to better determine their geologic and altimetric characteristics and possible formation sequences.

Identifying predictive features in drug response using machine learning: opportunities and challenges.

PubMed

Vidyasagar, Mathukumalli

2015-01-01

This article reviews several techniques from machine learning that can be used to study the problem of identifying a small number of features, from among tens of thousands of measured features, that can accurately predict a drug response. Prediction problems are divided into two categories: sparse classification and sparse regression. In classification, the clinical parameter to be predicted is binary, whereas in regression, the parameter is a real number. Well-known methods for both classes of problems are briefly discussed. These include the SVM (support vector machine) for classification and various algorithms such as ridge regression, LASSO (least absolute shrinkage and selection operator), and EN (elastic net) for regression. In addition, several well-established methods that do not directly fall into machine learning theory are also reviewed, including neural networks, PAM (pattern analysis for microarrays), SAM (significance analysis for microarrays), GSEA (gene set enrichment analysis), and k-means clustering. Several references indicative of the application of these methods to cancer biology are discussed.

Analysis of geometric moments as features for firearm identification.

PubMed

Md Ghani, Nor Azura; Liong, Choong-Yeun; Jemain, Abdul Aziz

2010-05-20

The task of identifying firearms from forensic ballistics specimens is exacting in crime investigation since the last two decades. Every firearm, regardless of its size, make and model, has its own unique 'fingerprint'. These fingerprints transfer when a firearm is fired to the fired bullet and cartridge case. The components that are involved in producing these unique characteristics are the firing chamber, breech face, firing pin, ejector, extractor and the rifling of the barrel. These unique characteristics are the critical features in identifying firearms. It allows investigators to decide on which particular firearm that has fired the bullet. Traditionally the comparison of ballistic evidence has been a tedious and time-consuming process requiring highly skilled examiners. Therefore, the main objective of this study is the extraction and identification of suitable features from firing pin impression of cartridge case images for firearm recognition. Some previous studies have shown that firing pin impression of cartridge case is one of the most important characteristics used for identifying an individual firearm. In this study, data are gathered using 747 cartridge case images captured from five different pistols of type 9mm Parabellum Vektor SP1, made in South Africa. All the images of the cartridge cases are then segmented into three regions, forming three different set of images, i.e. firing pin impression image, centre of firing pin impression image and ring of firing pin impression image. Then geometric moments up to the sixth order were generated from each part of the images to form a set of numerical features. These 48 features were found to be significantly different using the MANOVA test. This high dimension of features is then reduced into only 11 significant features using correlation analysis. Classification results using cross-validation under discriminant analysis show that 96.7% of the images were classified correctly. These results demonstrate

System and method employing a minimum distance and a load feature database to identify electric load types of different electric loads

DOEpatents

Lu, Bin; Yang, Yi; Sharma, Santosh K; Zambare, Prachi; Madane, Mayura A

2014-12-23

A method identifies electric load types of a plurality of different electric loads. The method includes providing a load feature database of a plurality of different electric load types, each of the different electric load types including a first load feature vector having at least four different load features; sensing a voltage signal and a current signal for each of the different electric loads; determining a second load feature vector comprising at least four different load features from the sensed voltage signal and the sensed current signal for a corresponding one of the different electric loads; and identifying by a processor one of the different electric load types by determining a minimum distance of the second load feature vector to the first load feature vector of the different electric load types of the load feature database.

40 CFR 268.38 - Waste specific prohibitions-newly identified organic toxicity characteristic wastes and newly...

Code of Federal Regulations, 2014 CFR

2014-07-01

... identified organic toxicity characteristic wastes and newly listed coke by-product and chlorotoluene... specific prohibitions—newly identified organic toxicity characteristic wastes and newly listed coke by... numbers F037, F038, K107-K112, K117, K118, K123-K126, K131, K132, K136, U328, U353, U359, and soil and...

40 CFR 268.38 - Waste specific prohibitions-newly identified organic toxicity characteristic wastes and newly...

Code of Federal Regulations, 2013 CFR

2013-07-01

... identified organic toxicity characteristic wastes and newly listed coke by-product and chlorotoluene... specific prohibitions—newly identified organic toxicity characteristic wastes and newly listed coke by... numbers F037, F038, K107-K112, K117, K118, K123-K126, K131, K132, K136, U328, U353, U359, and soil and...

40 CFR 268.38 - Waste specific prohibitions-newly identified organic toxicity characteristic wastes and newly...

Code of Federal Regulations, 2012 CFR

2012-07-01

... identified organic toxicity characteristic wastes and newly listed coke by-product and chlorotoluene... specific prohibitions—newly identified organic toxicity characteristic wastes and newly listed coke by... numbers F037, F038, K107-K112, K117, K118, K123-K126, K131, K132, K136, U328, U353, U359, and soil and...

40 CFR 268.38 - Waste specific prohibitions-newly identified organic toxicity characteristic wastes and newly...

Code of Federal Regulations, 2011 CFR

2011-07-01

... identified organic toxicity characteristic wastes and newly listed coke by-product and chlorotoluene... specific prohibitions—newly identified organic toxicity characteristic wastes and newly listed coke by... numbers F037, F038, K107-K112, K117, K118, K123-K126, K131, K132, K136, U328, U353, U359, and soil and...

Features of Household Lexics, Their Characteristics and Structural Analysis in the Modern English Language

ERIC Educational Resources Information Center

Yusifova, Aygun

2014-01-01

The present paper aims to analyze the most inherent features and characteristics of household lexis in English. Special emphasis has been placed on their names of the objects used in everyday life, kitchen utensils, animal and birds. Lexical units concerning ceremonies, habits and traditions are also among the scope of the paper. Moreover, the…

An unusual landslide feature on Mars

NASA Technical Reports Server (NTRS)

Veverka, J.; Liang, T.

1975-01-01

A flow feature on a crater wall, characteristic of a landslide, has been identified in a Mariner 9 high resolution photograph. Although other evidence of mass wasting is common in Mariner 9 photography, the case presented appears unique. A tentative conclusion is that, at least in some cases, Martian soil exhibits significant internal friction in mass movements.

Identifying potential collapse features under highways : research implementation plan.

DOT National Transportation Integrated Search

2005-09-01

There are many unmapped features under the states roadways that threaten them with major localized : collapse. The most common of these features are abandoned underground mines in the eastern part of : the state and sinkholes in portions of limest...

Characteristic Features of Female Employment in the Rural Areas of Hungary.

ERIC Educational Resources Information Center

Repassy, Helga

The study examined the inherences and differences in living conditions and female employment in villages; identified the correlations of the characteristics of female employment; and determined the possible and necessary degree of women manpower's involvement into work. Using the 1970 population census, data were obtained on the: age distribution…

Identifying At-Risk Students in General Chemistry via Cluster Analysis of Affective Characteristics

ERIC Educational Resources Information Center

Chan, Julia Y. K.; Bauer, Christopher F.

2014-01-01

The purpose of this study is to identify academically at-risk students in first-semester general chemistry using affective characteristics via cluster analysis. Through the clustering of six preselected affective variables, three distinct affective groups were identified: low (at-risk), medium, and high. Students in the low affective group…

Identifying Medication Management Smartphone App Features Suitable for Young Adults With Developmental Disabilities: Delphi Consensus Study

PubMed Central

Salgado, Teresa M; Fedrigon, Alexa; Riccio Omichinski, Donna; Meade, Michelle A

2018-01-01

Background Smartphone apps can be a tool to facilitate independent medication management among persons with developmental disabilities. At present, multiple medication management apps exist in the market, but only 1 has been specifically designed for persons with developmental disabilities. Before initiating further app development targeting this population, input from stakeholders including persons with developmental disabilities, caregivers, and professionals regarding the most preferred features should be obtained. Objective The aim of this study was to identify medication management app features that are suitable to promote independence in the medication management process by young adults with developmental disabilities using a Delphi consensus method. Methods A compilation of medication management app features was performed by searching the iTunes App Store, United States, in February 2016, using the following terms: adherence, medication, medication management, medication list, and medication reminder. After identifying features within the retrieved apps, a final list of 42 features grouped into 4 modules (medication list, medication reminder, medication administration record, and additional features) was included in a questionnaire for expert consensus rating. A total of 52 experts in developmental disabilities, including persons with developmental disabilities, caregivers, and professionals, were invited to participate in a 3-round Delphi technique. The purpose was to obtain consensus on features that are preferred and suitable to promote independence in the medication management process among persons with developmental disabilities. Consensus for the first, second, and third rounds was defined as ≥90%, ≥80%, and ≥75% agreement, respectively. Results A total of 75 responses were received over the 3 Delphi rounds—30 in the first round, 24 in the second round, and 21 in the third round. At the end of the third round, cumulative consensus was achieved

What Are the Characteristics of Principals Identified As Effective by Teachers?

ERIC Educational Resources Information Center

Fowler, William J., Jr.

This exploratory study investigated which characteristics of a principal are identified as effective by teachers in the same school setting. The data were obtained from the Schools and Staffing Study of 1988, from the National Center for Education Statistics (NCES). The Teacher Questionnaire of the Schools and Staffing Survey (SASS) questioned…

Identifying 5-methylcytosine sites in RNA sequence using composite encoding feature into Chou's PseKNC.

PubMed

Sabooh, M Fazli; Iqbal, Nadeem; Khan, Mukhtaj; Khan, Muslim; Maqbool, H F

2018-05-01

This study examines accurate and efficient computational method for identification of 5-methylcytosine sites in RNA modification. The occurrence of 5-methylcytosine (m 5 C) plays a vital role in a number of biological processes. For better comprehension of the biological functions and mechanism it is necessary to recognize m 5 C sites in RNA precisely. The laboratory techniques and procedures are available to identify m 5 C sites in RNA, but these procedures require a lot of time and resources. This study develops a new computational method for extracting the features of RNA sequence. In this method, first the RNA sequence is encoded via composite feature vector, then, for the selection of discriminate features, the minimum-redundancy-maximum-relevance algorithm was used. Secondly, the classification method used has been based on a support vector machine by using jackknife cross validation test. The suggested method efficiently identifies m 5 C sites from non- m 5 C sites and the outcome of the suggested algorithm is 93.33% with sensitivity of 90.0 and specificity of 96.66 on bench mark datasets. The result exhibits that proposed algorithm shown significant identification performance compared to the existing computational techniques. This study extends the knowledge about the occurrence sites of RNA modification which paves the way for better comprehension of the biological uses and mechanism. Copyright © 2018 Elsevier Ltd. All rights reserved.

Characteristic Features of Hanging: A Study in Rural District of Central India.

PubMed

Ambade, Vipul Namdeorao; Kolpe, Dayanand; Tumram, Nilesh; Meshram, Satin; Pawar, Mohan; Kukde, Hemant

2015-09-01

The ligature mark is the most relevant feature of hanging. This study was undertaken with a view to determine the characteristic features of hanging and its association with ligature material or mode of suspension. Of a total medicolegal deaths reported at an Apex Medical Centre, hanging was noted in 4.1% cases, all suicidal with mortality rate of 1.5 per 100,000 population per year. The hanging was complete in 67.7% with nylon rope as the commonest type of ligature material used for ligation. The hanging mark was usually single, situated above thyroid cartilage, incomplete, prominent, and directed toward nape of neck. The mark of dribbling of saliva was seen in 11.8% cases. Facial congestion, petechial hemorrhage, and cyanosis were significantly seen in partial hanging. Though occasionally reported, the argent line was noted in 78.7% hanging deaths with neck muscle hemorrhage in 23.6% cases. Fracture of neck structure was predominant in complete hanging. © 2015 American Academy of Forensic Sciences.

Identifying Trajectories of Borderline Personality Features in Adolescence: Antecedent and Interactive Risk Factors.

PubMed

Haltigan, John D; Vaillancourt, Tracy

2016-03-01

To examine trajectories of adolescent borderline personality (BP) features in a normative-risk cohort (n = 566) of Canadian children assessed at ages 13, 14, 15, and 16 and childhood predictors of trajectory group membership assessed at ages 8, 10, 11, and 12. Data were drawn from the McMaster Teen Study, an on-going study examining relations among bullying, mental health, and academic achievement. Participants and their parents completed a battery of mental health and peer relations questionnaires at each wave of the study. Academic competence was assessed at age 8 (Grade 3). Latent class growth analysis, analysis of variance, and logistic regression were used to analyze the data. Three distinct BP features trajectory groups were identified: elevated or rising, intermediate or stable, and low or stable. Parent- and child-reported mental health symptoms, peer relations risk factors, and intra-individual risk factors were significant predictors of elevated or rising and intermediate or stable trajectory groups. Child-reported attention-deficit hyperactivity disorder (ADHD) and somatization symptoms uniquely predicted elevated or rising trajectory group membership, whereas parent-reported anxiety and child-reported ADHD symptoms uniquely predicted intermediate or stable trajectory group membership. Child-reported somatization symptoms was the only predictor to differentiate the intermediate or stable and elevated or rising trajectory groups (OR 1.15, 95% CI 1.04 to 1.28). Associations between child-reported reactive temperament and elevated BP features trajectory group membership were 10.23 times higher among children who were bullied, supporting a diathesis-stress pathway in the development of BP features for these youth. Findings demonstrate the heterogeneous course of BP features in early adolescence and shed light on the potential prodromal course of later borderline personality disorder. © The Author(s) 2015.

Identifying driver characteristics influencing overtaking crashes.

PubMed

Mohaymany, Afshin Shariat; Kashani, Ali Tavakoli; Ranjbari, Andishe

2010-08-01

To identify the most important driver characteristics influencing crash-causing overtaking maneuvers on 2-lane, 2-way rural roads of Iran. Based on the crash data for rural roads of Iran over 3 years from 2006 to 2008, the classification and regression tree (CART) method combined with the quasi-induced exposure concept was applied for 4 independent variables and one target variable of "driver status" with 2 classes of at fault and not at fault. The independent variables were vehicle type, driver's age, driving license, and driving experience of the driver-the latter 2 driver characteristics are relatively new in traffic safety studies. According to the data set, 16,809 drivers were involved in 2-lane, 2-way rural roads overtaking crashes. The analysis revealed that drivers who are younger than 28 years old, whose driving license is type 2--a common driving license that is for driving with passenger car and light vehicles--and whose driving experience is less than 2 years are most probably responsible for overtaking crashes. It was indicated that vehicle type is the most important factor associated with drivers being responsible for the crashes. The results also revealed that younger drivers (18-28 years) are most likely to be at fault in overtaking crashes. Therefore, enforcement and education should be more concentrated on this age group. Due to the incompliant nature of this group, changing the type and amount of traffic fines is essential for more preventing objectives. The research also found 2 relatively new factors of driving license and driving experience to have considerable effects on drivers being at fault, such that type 2 licensed drivers are more responsible compared to type 1 (a driving license for driving with all motor vehicles, which has some age and experience requirements) licensed drivers or drivers with a special license (a driving license with special vehicle types). Moreover, drivers with less than 2 years' driving experience are more

Identifying Novel Transcriptional and Epigenetic Features of Nuclear Lamina-associated Genes.

PubMed

Wu, Feinan; Yao, Jie

2017-03-07

Because a large portion of the mammalian genome is associated with the nuclear lamina (NL), it is interesting to study how native genes resided there are transcribed and regulated. In this study, we report unique transcriptional and epigenetic features of nearly 3,500 NL-associated genes (NL genes). Promoter regions of active NL genes are often excluded from NL-association, suggesting that NL-promoter interactions may repress transcription. Active NL genes with higher RNA polymerase II (Pol II) recruitment levels tend to display Pol II promoter-proximal pausing, while Pol II recruitment and Pol II pausing are not correlated among non-NL genes. At the genome-wide scale, NL-association and H3K27me3 distinguishes two large gene classes with low transcriptional activities. Notably, NL-association is anti-correlated with both transcription and active histone mark levels among genes not significantly enriched with H3K9me3 or H3K27me3, suggesting that NL-association may represent a novel gene repression pathway. Interestingly, an NL gene subgroup is not significantly enriched with H3K9me3 or H3K27me3 and is transcribed at higher levels than the rest of NL genes. Furthermore, we identified distal enhancers associated with active NL genes and reported their epigenetic features.

The effects of droplet characteristics on the surface features in a rain field

NASA Astrophysics Data System (ADS)

Liu, R.; Brown, H.; Liu, X.; Duncan, J. H.

2013-11-01

The characteristics of the shape of a water surface in response to the impact of simulated raindrops are studied experimentally in a 1.22-m-by-1.22-m water pool with a water depth of 0.3 m. A rain generator consisting of an open-surface water tank with an array of 22-gauge hypodermic needles (typical needle-to-needle spacing of about L0 = 3 . 5 cm) attached to holes in the tank bottom is mounted 2 m above the water pool. The tank is connected to a 2D translation stage to provide a small-radius (features, including the crown, stalk and ring waves, due to the impacts of the drops are measured with a cinematic laser-induced- fluorescence (LIF) technique. The dependence of these features on the rain characteristics are discussed. The support of the National Science Foundation, Division of Ocean Sciences, and the assistance of Mr. Larry Gong are gratefully acknowledged.

Mapping soil features from multispectral scanner data

NASA Technical Reports Server (NTRS)

Kristof, S. J.; Zachary, A. L.

1974-01-01

In being able to identify quickly gross variations in soil features, the computer-aided classification of multispectral scanner data can be an effective aid to soil surveying. Variations in soil tone are easily seen as well as variations in features related to soil tone, e.g., drainage patterns and organic matter content. Changes in surface texture also affect the reflectance properties of soils. Inasmuch as conventional soil classes are based on both surface and subsurface soil characteristics, the technique described here can be expected only to augment and not replace traditional soil mapping.

Influence of hot spot features on the initiation characteristics of heterogeneous nitromethane

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

Dattelbaum, Dana M; Sheffield, Stephen A; Stahl, David B

2010-01-01

To gain insights into the critical hot spot features influencing energetic materials initiation characteristics, well-defined micron-scale particles have been intentionally introduced into the homogeneous explosive nitromethane (NM). Two types of potential hot spot origins have been examined - shock impedance mismatches using solid silica beads, and porosity using hollow microballoons - as well as their sizes and inter-particle separations. Here, we present the results of several series of gas gun-driven plate impact experiments on NM/particle mixtures with well-controlled shock inputs. Detailed insights into the nature of the reactive flow during the build-up to detonation have been obtained from the responsemore » of in-situ electromagnetic gauges, and the data have been used to establish Pop-plots (run-distance-to-detonation vs. shock input pressure) for the mixtures. Comparisons of sensitization effects and energy release characteristics relative to the initial shock front between the solid and hollow beads are presented.« less

Vegetation-terrain feature relationships in southeast Arizona

NASA Technical Reports Server (NTRS)

Schrumpf, B. J. (Principal Investigator); Mouat, D. A.

1972-01-01

There are no author-identified significant results in this report. Studies of relationships of vegetation distribution to geomorphic characteristics of the landscape and of plant phenological patterns to vegetation identification of satellite imagery indicate that there exists positive relationships between certain plant species and certain terrain features. Not all species were found to exhibit positive relationships with all terrain feature variables, but enough positive relationships seem to exist to indicate that terrain feature variable-vegetation relationship studies have a definite place in plant ecological investigations. Even more importantly, the vegetation groups examined appeared to be successfully discriminated by the terrain feature variables. This would seem to indicate that spatial interpretations of vegetation groups may be possible. While vegetational distributions aren't determined by terrain feature differences, terrain features do mirror factors which directly influence vegetational response and hence distribution. As a result, those environmental features which can be readily and rapidly ascertained on relatively small-scale imagery may prove to be valuable indicators of vegetation distribution.

kmer-SVM: a web server for identifying predictive regulatory sequence features in genomic data sets.

PubMed

Fletez-Brant, Christopher; Lee, Dongwon; McCallion, Andrew S; Beer, Michael A

2013-07-01

Massively parallel sequencing technologies have made the generation of genomic data sets a routine component of many biological investigations. For example, Chromatin immunoprecipitation followed by sequence assays detect genomic regions bound (directly or indirectly) by specific factors, and DNase-seq identifies regions of open chromatin. A major bottleneck in the interpretation of these data is the identification of the underlying DNA sequence code that defines, and ultimately facilitates prediction of, these transcription factor (TF) bound or open chromatin regions. We have recently developed a novel computational methodology, which uses a support vector machine (SVM) with kmer sequence features (kmer-SVM) to identify predictive combinations of short transcription factor-binding sites, which determine the tissue specificity of these genomic assays (Lee, Karchin and Beer, Discriminative prediction of mammalian enhancers from DNA sequence. Genome Res. 2011; 21:2167-80). This regulatory information can (i) give confidence in genomic experiments by recovering previously known binding sites, and (ii) reveal novel sequence features for subsequent experimental testing of cooperative mechanisms. Here, we describe the development and implementation of a web server to allow the broader research community to independently apply our kmer-SVM to analyze and interpret their genomic datasets. We analyze five recently published data sets and demonstrate how this tool identifies accessory factors and repressive sequence elements. kmer-SVM is available at http://kmersvm.beerlab.org.

kmer-SVM: a web server for identifying predictive regulatory sequence features in genomic data sets

PubMed Central

Fletez-Brant, Christopher; Lee, Dongwon; McCallion, Andrew S.; Beer, Michael A.

2013-01-01

Massively parallel sequencing technologies have made the generation of genomic data sets a routine component of many biological investigations. For example, Chromatin immunoprecipitation followed by sequence assays detect genomic regions bound (directly or indirectly) by specific factors, and DNase-seq identifies regions of open chromatin. A major bottleneck in the interpretation of these data is the identification of the underlying DNA sequence code that defines, and ultimately facilitates prediction of, these transcription factor (TF) bound or open chromatin regions. We have recently developed a novel computational methodology, which uses a support vector machine (SVM) with kmer sequence features (kmer-SVM) to identify predictive combinations of short transcription factor-binding sites, which determine the tissue specificity of these genomic assays (Lee, Karchin and Beer, Discriminative prediction of mammalian enhancers from DNA sequence. Genome Res. 2011; 21:2167–80). This regulatory information can (i) give confidence in genomic experiments by recovering previously known binding sites, and (ii) reveal novel sequence features for subsequent experimental testing of cooperative mechanisms. Here, we describe the development and implementation of a web server to allow the broader research community to independently apply our kmer-SVM to analyze and interpret their genomic datasets. We analyze five recently published data sets and demonstrate how this tool identifies accessory factors and repressive sequence elements. kmer-SVM is available at http://kmersvm.beerlab.org. PMID:23771147

A support vector machine-based method to identify mild cognitive impairment with multi-level characteristics of magnetic resonance imaging.

PubMed

Long, Zhuqing; Jing, Bin; Yan, Huagang; Dong, Jianxin; Liu, Han; Mo, Xiao; Han, Ying; Li, Haiyun

2016-09-07

Mild cognitive impairment (MCI) represents a transitional state between normal aging and Alzheimer's disease (AD). Non-invasive diagnostic methods are desirable to identify MCI for early therapeutic interventions. In this study, we proposed a support vector machine (SVM)-based method to discriminate between MCI patients and normal controls (NCs) using multi-level characteristics of magnetic resonance imaging (MRI). This method adopted a radial basis function (RBF) as the kernel function, and a grid search method to optimize the two parameters of SVM. The calculated characteristics, i.e., the Hurst exponent (HE), amplitude of low-frequency fluctuations (ALFF), regional homogeneity (ReHo) and gray matter density (GMD), were adopted as the classification features. A leave-one-out cross-validation (LOOCV) was used to evaluate the classification performance of the method. Applying the proposed method to the experimental data from 29 MCI patients and 33 healthy subjects, we achieved a classification accuracy of up to 96.77%, with a sensitivity of 93.10% and a specificity of 100%, and the area under the curve (AUC) yielded up to 0.97. Furthermore, the most discriminative features for classification were found to predominantly involve default-mode regions, such as hippocampus (HIP), parahippocampal gyrus (PHG), posterior cingulate gyrus (PCG) and middle frontal gyrus (MFG), and subcortical regions such as lentiform nucleus (LN) and amygdala (AMYG). Therefore, our method is promising in distinguishing MCI patients from NCs and may be useful for the diagnosis of MCI. Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.

[Impedance characteristics of ear acupoints in identifying excess or deficiency syndrome of stroke].

PubMed

Wang, Pin; Yang, Hua-Yuan; Wang, Yi-Qin

2010-06-01

To explore the impedance characteristics of ear acupoints in stroke patients with excess or deficiency syndrome, and to provide basis data for objective study of the syndromes of stroke. The data of electrical characteristics of ear acupoints in stroke patients and healthy people were collected, and excess syndrome and deficiency syndrome of stroke were identified by quantifying the syndromes of stroke using scales. The differences in impedance characteristics of ear acupoints between stroke patients and healthy people were analyzed, and the differences in impedance characteristics of ear acupoints between stroke patients with excess syndrome and stroke patients with deficiency syndrome were analyzed too. The correlation among impedance characteristics of ear acupoints, stroke and the syndromes was also analyzed. There were significant differences in impedance characteristics of ear acupoints between stroke patients and healthy people (P<0.05,P<0.01). The ear acupoints CO12 (Gan) and CO13 (Pi) had a significant role in diagnosing stroke as compared with CO18 (Neifenmi), AT3.4.AH12i (Naogan), CO10 (Shen), TG2p (Shenshangxian), AH6a (Jiaogan), AT4 (Pizhixia), and CO15 (Xin). There were significant differences in impedance characteristics of ear acupoints between stroke patients with excess syndrome and stroke patients with deficiency syndrome (P<0.05, P<0.01). The ear acupoints AH6a (Jiaogan) and CO10 (Shen) played an important role in differentiation diagnosis of excess syndrome and deficiency syndrome of stroke, followed by CO18 (Neifenmi), TF4 (Shenmen) and TG2p (Shenshangxian). Some ear acupoints with diagnostic value for stroke may provide basis of objective research for stroke diagnosis as well as identifying excess syndrome and deficiency syndrome of stroke.

Three Years of TRMM Precipitation Features. Part 1; Radar, Radiometric, and Lightning Characteristics

NASA Technical Reports Server (NTRS)

Cecil, Daniel J.; Goodman, Steven J.; Boccippio, Dennis J.; Zipser, Edward J.; Nesbitt, Stephen W.

2004-01-01

During its first three years, the Tropical Rainfall Measuring Mission (TRMM) satellite observed nearly six million precipitation features. The population of precipitation features is sorted by lightning flash rate, minimum brightness temperature, maximum radar reflectivity, areal extent, and volumetric rainfall. For each of these characteristics, essentially describing the convective intensity or the size of the features, the population is broken into categories consisting of the top 0.001%, top 0.01%, top 0.1%, top 1%, top 2.4%, and remaining 97.6%. The set of 'weakest / smallest' features comprises 97.6% of the population because that fraction does not have detected lightning, with a minimum detectable flash rate 0.7 fl/min. The greatest observed flash rate is 1351 fl/min; the lowest brightness temperatures are 42 K (85-GHz) and 69 K (37- GHz). The largest precipitation feature covers 335,000 sq km and the greatest rainfall from an individual precipitation feature exceeds 2 x 10(exp 12) kg of water. There is considerable overlap between the greatest storms according to different measures of convective intensity. The largest storms are mostly independent of the most intense storms. The set of storms producing the most rainfall is a convolution of the largest and the most intense storms. This analysis is a composite of the global tropics and subtropics. Significant variability is known to exist between locations, seasons, and meteorological regimes. Such variability will be examined in Part II. In Part I, only a crude land / Ocean separation is made. The known differences in bulk lightning flash rates over land and Ocean result from at least two differences in the precipitation feature population: the frequency of occurrence of intense storms, and the magnitude of those intense storms that do occur. Even when restricted to storms with the same brightness temperature, same size, or same radar reflectivity aloft, the storms over water are considerably less likely to

Three Years of TRMM Precipitation Features. Part 1; Radar, Radiometric, and Lightning Characteristics

NASA Technical Reports Server (NTRS)

Cecil, Daniel J.; Goodman, Steven J.; Boccippio, Dennis J.; Zipser, Edward J.; Nesbitt, Stephen W.

2005-01-01

During its first three years, the Tropical Rainfall Measuring Mission (TRMM) satellite observed nearly six million precipitation features. The population of precipitation features is sorted by lightning flash rate, minimum brightness temperature, maximum radar reflectivity. areal extent, and volumetric rainfall. For each of these characteristics, essentially describing the convective intensity or the size of the features, the population is broken into categories consisting of the top 0.001%, top 0.01%, top 0.1%, top 1%, top 2.4%. and remaining 97.6%. The set of weakest/smallest features composes 97.6% of the population because that fraction does not have detected lightning, with a minimum detectable flash rate of 0.7 flashes (fl) per minute. The greatest observed flash rate is 1351 fl per minute; the lowest brightness temperatures are 42 K (85 GHz) and 69 K (37 GHz). The largest precipitation feature covers 335 000 square kilometers and the greatest rainfall from an individual precipitation feature exceeds 2 x 10 kg per hour of water. There is considerable overlap between the greatest storms according to different measures of convective intensity. The largest storms are mostly independent of the most intense storms. The set of storms producing the most rainfall is a convolution of the largest and the most intense storms. This analysis is a composite of the global Tropics and subtropics. Significant variability is known to exist between locations. seasons, and meteorological regimes. Such variability will be examined in Part II. In Part I, only a crude land-ocean separation is made. The known differences in bulk lightning flash rates over land and ocean result from at least two differences in the precipitation feature population: the frequency of occurrence of intense storms and the magnitude of those intense storms that do occur. Even when restricted to storms with the same brightness temperature, same size, or same radar reflectivity aloft, the storms over water

Comparative evaluation of features and techniques for identifying activity type and estimating energy cost from accelerometer data

PubMed Central

Kate, Rohit J.; Swartz, Ann M.; Welch, Whitney A.; Strath, Scott J.

2016-01-01

Wearable accelerometers can be used to objectively assess physical activity. However, the accuracy of this assessment depends on the underlying method used to process the time series data obtained from accelerometers. Several methods have been proposed that use this data to identify the type of physical activity and estimate its energy cost. Most of the newer methods employ some machine learning technique along with suitable features to represent the time series data. This paper experimentally compares several of these techniques and features on a large dataset of 146 subjects doing eight different physical activities wearing an accelerometer on the hip. Besides features based on statistics, distance based features and simple discrete features straight from the time series were also evaluated. On the physical activity type identification task, the results show that using more features significantly improve results. Choice of machine learning technique was also found to be important. However, on the energy cost estimation task, choice of features and machine learning technique were found to be less influential. On that task, separate energy cost estimation models trained specifically for each type of physical activity were found to be more accurate than a single model trained for all types of physical activities. PMID:26862679

Identifying injuries and motor vehicle collision characteristics that together are suggestive of diaphragmatic rupture.

PubMed

Reiff, Donald A; McGwin, Gerald; Metzger, Jesse; Windham, Samuel T; Doss, Marilyn; Rue, Loring W

2002-12-01

Diaphragmatic rupture (DR) remains a diagnostic challenge because of the lack of an accurate test demonstrating the injury. Our purpose was to identify motor vehicle collision (MVC) characteristics and patient injuries that collectively could identify the presence of a DR. The National Automotive Sampling System was used to identify occupants involved in MVCs from 1995 to 1999 who sustained abdominal (Abbreviated Injury Scale score >or= 2) and/or thoracic injuries (Abbreviated Injury Scale score >or= 2). Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to quantify the association between patient injuries, vehicle collision characteristics, and DR. Sensitivity and specificity were also calculated to determine the ability of organ injury and MVC characteristics to correctly classify patients with and without DR. Overall, occupants sustaining a DR had a significantly higher delta-V (DeltaV) (49.8 kilometers per hour [kph] vs. 33.8 kph, p< 0.0001) and a greater degree of occupant compartment intrusion (70.6 cm vs. 48.3 cm, p< 0.0001). Specific abdominal and thoracic organ injuries were associated with DR, including thoracic aortic tears (OR, 5.2; 95% CI, 2.2-12.5), splenic injury (OR, 8.4; 95% CI, 3.9-17.8), pelvic fractures (OR, 4.7; 95% CI, 2.7-8.0), and hepatic injuries (OR, 4.2; 95% CI, 1.7-10.6). Combining frontal or near-side lateral occupant compartment intrusion >or= 30 cm or DeltaV >or= 40 kph with specific organ injuries generated a sensitivity for indicating the likelihood of diaphragm injury ranging from 68% to 89%. Patients with any of the following characteristics had a sensitivity for detecting DR of 91%: splenic injury, pelvic fracture, DeltaV >or= 40 kph, or occupant compartment intrusion from any direction >or= 30 cm. Specific MVC characteristics combined with patient injuries have been identified that are highly suggestive of DR. For this subpopulation, additional invasive procedures including exploratory laparotomy, laparoscopy

Socioemotional Characteristics of Elementary School Children Identified as Exhibiting Social Leadership Qualities

ERIC Educational Resources Information Center

Scharf, Miri; Mayseless, Ofra

2009-01-01

Elementary school teachers identified characteristics in 4 major socioemotional domains associated with children's social leadership: self-perception, social anxiety, attachment orientation with peers, and interpersonal goals and skills in close friendships. Participants were 260 4th- and 5th-grade students (126 boys, 134 girls) from 10 classes in…

Differentiating characteristic microstructural features of cancerous tissues using Mueller matrix microscope.

PubMed

Wang, Ye; He, Honghui; Chang, Jintao; Zeng, Nan; Liu, Shaoxiong; Li, Migao; Ma, Hui

2015-12-01

Polarized light imaging can provide rich microstructural information of samples, and has been applied to the detections of various abnormal tissues. In this paper, we report a polarized light microscope based on Mueller matrix imaging by adding the polarization state generator and analyzer (PSG and PSA) to a commercial transmission optical microscope. The maximum errors for the absolute values of Mueller matrix elements are reduced to 0.01 after calibration. This Mueller matrix microscope has been used to examine human cervical and liver cancerous tissues with fibrosis. Images of the transformed Mueller matrix parameters provide quantitative assessment on the characteristic features of the pathological tissues. Contrast mechanism of the experimental results are backed up by Monte Carlo simulations based on the sphere-cylinder birefringence model, which reveal the relationship between the pathological features in the cancerous tissues at the cellular level and the polarization parameters. Both the experimental and simulated data indicate that the microscopic transformed Mueller matrix parameters can distinguish the breaking down of birefringent normal tissues for cervical cancer, or the formation of birefringent surrounding structures accompanying the inflammatory reaction for liver cancer. With its simple structure, fast measurement and high precision, polarized light microscope based on Mueller matrix shows a good diagnosis application prospect. Copyright © 2015 Elsevier Ltd. All rights reserved.

Featured Image: Identifying Weird Galaxies

NASA Astrophysics Data System (ADS)

Kohler, Susanna

2017-08-01

Hoags Object, an example of a ring galaxy. [NASA/Hubble Heritage Team/Ray A. Lucas (STScI/AURA)]The above image (click for the full view) shows PanSTARRSobservationsof some of the 185 galaxies identified in a recent study as ring galaxies bizarre and rare irregular galaxies that exhibit stars and gas in a ring around a central nucleus. Ring galaxies could be formed in a number of ways; one theory is that some might form in a galaxy collision when a smaller galaxy punches through the center of a larger one, triggering star formation around the center. In a recent study, Ian Timmis and Lior Shamir of Lawrence Technological University in Michigan explore ways that we may be able to identify ring galaxies in the overwhelming number of images expected from large upcoming surveys. They develop a computer analysis method that automatically finds ring galaxy candidates based on their visual appearance, and they test their approach on the 3 million galaxy images from the first PanSTARRS data release. To see more of the remarkable galaxies the authors found and to learn more about their identification method, check out the paper below.CitationIan Timmis and Lior Shamir 2017 ApJS 231 2. doi:10.3847/1538-4365/aa78a3

Feature determination from powered wheelchair user joystick input characteristics for adapting driving assistance.

PubMed

Gillham, Michael; Pepper, Matthew; Kelly, Steve; Howells, Gareth

2017-01-01

Background : Many powered wheelchair users find their medical condition and their ability to drive the wheelchair will change over time. In order to maintain their independent mobility, the powered chair will require adjustment over time to suit the user's needs, thus regular input from healthcare professionals is required. These limited resources can result in the user having to wait weeks for appointments, resulting in the user losing independent mobility, consequently affecting their quality of life and that of their family and carers. In order to provide an adaptive assistive driving system, a range of features need to be identified which are suitable for initial system setup and can automatically provide data for re-calibration over the long term. Methods : A questionnaire was designed to collect information from powered wheelchair users with regard to their symptoms and how they changed over time. Another group of volunteer participants were asked to drive a test platform and complete a course which represented manoeuvring in a very confined space as quickly as possible. Two of those participants were also monitored over a longer period in their normal home daily environment. Features, thought to be suitable, were examined using pattern recognition classifiers to determine their suitability for identifying the changing user input over time. Results : The results are not designed to provide absolute insight into the individual user behaviour, as no ground truth of their ability has been determined, they do nevertheless demonstrate the utility of the measured features to provide evidence of the users' changing ability over time whilst driving a powered wheelchair. Conclusions : Determining the driving features and adjustable elements provides the initial step towards developing an adaptable assistive technology for the user when the ground truths of the individual and their machine have been learned by a smart pattern recognition system.

Feature determination from powered wheelchair user joystick input characteristics for adapting driving assistance

PubMed Central

Gillham, Michael; Pepper, Matthew; Kelly, Steve; Howells, Gareth

2018-01-01

Background: Many powered wheelchair users find their medical condition and their ability to drive the wheelchair will change over time. In order to maintain their independent mobility, the powered chair will require adjustment over time to suit the user's needs, thus regular input from healthcare professionals is required. These limited resources can result in the user having to wait weeks for appointments, resulting in the user losing independent mobility, consequently affecting their quality of life and that of their family and carers. In order to provide an adaptive assistive driving system, a range of features need to be identified which are suitable for initial system setup and can automatically provide data for re-calibration over the long term. Methods: A questionnaire was designed to collect information from powered wheelchair users with regard to their symptoms and how they changed over time. Another group of volunteer participants were asked to drive a test platform and complete a course which represented manoeuvring in a very confined space as quickly as possible. Two of those participants were also monitored over a longer period in their normal home daily environment. Features, thought to be suitable, were examined using pattern recognition classifiers to determine their suitability for identifying the changing user input over time. Results: The results are not designed to provide absolute insight into the individual user behaviour, as no ground truth of their ability has been determined, they do nevertheless demonstrate the utility of the measured features to provide evidence of the users’ changing ability over time whilst driving a powered wheelchair. Conclusions: Determining the driving features and adjustable elements provides the initial step towards developing an adaptable assistive technology for the user when the ground truths of the individual and their machine have been learned by a smart pattern recognition system. PMID:29552641

Characteristics of Self-Harm Behaviour among Identified Self-Harming Youth in Care

ERIC Educational Resources Information Center

Grenville, Jeffrey; Goodman, Deborah; Macpherson, Alison K.

2012-01-01

The objective of this study was to describe deliberate self-harming (DSH) characteristics in a child-welfare population identified as having threatened or completed self-harm. Secondary data from 621 serious occurrence reports (SOR) that documented 2004-2007 DSH incidents and DSH threats with 252 Canadian youth in care (Y-INC) of the Children's…

Cognitive and noncognitive neurological features of young-onset dementia.

PubMed

Kelley, Brendan J; Boeve, Bradley F; Josephs, Keith A

2009-01-01

The rarity of young-onset dementia (YOD), the broad differential diagnosis and unusual clinical presentations present unique challenges to correctly recognize the condition and establish an accurate diagnosis. Limited data exist regarding clinical features associated with dementia prior to the age of 45. We retrospectively assessed cognitive and noncognitive neurological characteristics of 235 patients who presented for evaluation of YOD to investigate the clinical characteristics of YOD compared to later-onset dementias and to identify clinical features associated with specific etiologies that may aid in the evaluation of YOD. Multiple cognitive domains were affected in most patients, and no significant differences in affected domains existed between groups. Early psychiatric and behavioral features occurred at very high frequencies. Nearly 80% of this YOD cohort had additional noncognitive symptoms or signs as a feature of their disease. Chorea was strongly associated with Huntington disease. Parkinsonism was not seen in patients having an autoimmune/inflammatory etiology. The rarity of YOD and the high frequency of early psychiatric features led to frequent misdiagnosis early in the clinical course. The high frequency of noncognitive symptoms and signs may aid clinicians in distinguishing patients requiring a more extensive evaluation for YOD.

Identifying Patients with Atrioventricular Septal Defect in Down Syndrome Populations by Using Self-Normalizing Neural Networks and Feature Selection.

PubMed

Pan, Xiaoyong; Hu, Xiaohua; Zhang, Yu Hang; Feng, Kaiyan; Wang, Shao Peng; Chen, Lei; Huang, Tao; Cai, Yu Dong

2018-04-12

Atrioventricular septal defect (AVSD) is a clinically significant subtype of congenital heart disease (CHD) that severely influences the health of babies during birth and is associated with Down syndrome (DS). Thus, exploring the differences in functional genes in DS samples with and without AVSD is a critical way to investigate the complex association between AVSD and DS. In this study, we present a computational method to distinguish DS patients with AVSD from those without AVSD using the newly proposed self-normalizing neural network (SNN). First, each patient was encoded by using the copy number of probes on chromosome 21. The encoded features were ranked by the reliable Monte Carlo feature selection (MCFS) method to obtain a ranked feature list. Based on this feature list, we used a two-stage incremental feature selection to construct two series of feature subsets and applied SNNs to build classifiers to identify optimal features. Results show that 2737 optimal features were obtained, and the corresponding optimal SNN classifier constructed on optimal features yielded a Matthew's correlation coefficient (MCC) value of 0.748. For comparison, random forest was also used to build classifiers and uncover optimal features. This method received an optimal MCC value of 0.582 when top 132 features were utilized. Finally, we analyzed some key features derived from the optimal features in SNNs found in literature support to further reveal their essential roles.

Utilizing Hierarchical Clustering to improve Efficiency of Self-Organizing Feature Map to Identify Hydrological Homogeneous Regions

NASA Astrophysics Data System (ADS)

Farsadnia, Farhad; Ghahreman, Bijan

2016-04-01

Hydrologic homogeneous group identification is considered both fundamental and applied research in hydrology. Clustering methods are among conventional methods to assess the hydrological homogeneous regions. Recently, Self-Organizing feature Map (SOM) method has been applied in some studies. However, the main problem of this method is the interpretation on the output map of this approach. Therefore, SOM is used as input to other clustering algorithms. The aim of this study is to apply a two-level Self-Organizing feature map and Ward hierarchical clustering method to determine the hydrologic homogenous regions in North and Razavi Khorasan provinces. At first by principal component analysis, we reduced SOM input matrix dimension, then the SOM was used to form a two-dimensional features map. To determine homogeneous regions for flood frequency analysis, SOM output nodes were used as input into the Ward method. Generally, the regions identified by the clustering algorithms are not statistically homogeneous. Consequently, they have to be adjusted to improve their homogeneity. After adjustment of the homogeneity regions by L-moment tests, five hydrologic homogeneous regions were identified. Finally, adjusted regions were created by a two-level SOM and then the best regional distribution function and associated parameters were selected by the L-moment approach. The results showed that the combination of self-organizing maps and Ward hierarchical clustering by principal components as input is more effective than the hierarchical method, by principal components or standardized inputs to achieve hydrologic homogeneous regions.

A comparative hidden Markov model analysis pipeline identifies proteins characteristic of cereal-infecting fungi

PubMed Central

2013-01-01

Background Fungal pathogens cause devastating losses in economically important cereal crops by utilising pathogen proteins to infect host plants. Secreted pathogen proteins are referred to as effectors and have thus far been identified by selecting small, cysteine-rich peptides from the secretome despite increasing evidence that not all effectors share these attributes. Results We take advantage of the availability of sequenced fungal genomes and present an unbiased method for finding putative pathogen proteins and secreted effectors in a query genome via comparative hidden Markov model analyses followed by unsupervised protein clustering. Our method returns experimentally validated fungal effectors in Stagonospora nodorum and Fusarium oxysporum as well as the N-terminal Y/F/WxC-motif from the barley powdery mildew pathogen. Application to the cereal pathogen Fusarium graminearum reveals a secreted phosphorylcholine phosphatase that is characteristic of hemibiotrophic and necrotrophic cereal pathogens and shares an ancient selection process with bacterial plant pathogens. Three F. graminearum protein clusters are found with an enriched secretion signal. One of these putative effector clusters contains proteins that share a [SG]-P-C-[KR]-P sequence motif in the N-terminal and show features not commonly associated with fungal effectors. This motif is conserved in secreted pathogenic Fusarium proteins and a prime candidate for functional testing. Conclusions Our pipeline has successfully uncovered conservation patterns, putative effectors and motifs of fungal pathogens that would have been overlooked by existing approaches that identify effectors as small, secreted, cysteine-rich peptides. It can be applied to any pathogenic proteome data, such as microbial pathogen data of plants and other organisms. PMID:24252298

Correlative feature analysis on FFDM

PubMed Central

Yuan, Yading; Giger, Maryellen L.; Li, Hui; Sennett, Charlene

2008-01-01

Identifying the corresponding images of a lesion in different views is an essential step in improving the diagnostic ability of both radiologists and computer-aided diagnosis (CAD) systems. Because of the nonrigidity of the breasts and the 2D projective property of mammograms, this task is not trivial. In this pilot study, we present a computerized framework that differentiates between corresponding images of the same lesion in different views and noncorresponding images, i.e., images of different lesions. A dual-stage segmentation method, which employs an initial radial gradient index (RGI) based segmentation and an active contour model, is applied to extract mass lesions from the surrounding parenchyma. Then various lesion features are automatically extracted from each of the two views of each lesion to quantify the characteristics of density, size, texture and the neighborhood of the lesion, as well as its distance to the nipple. A two-step scheme is employed to estimate the probability that the two lesion images from different mammographic views are of the same physical lesion. In the first step, a correspondence metric for each pairwise feature is estimated by a Bayesian artificial neural network (BANN). Then, these pairwise correspondence metrics are combined using another BANN to yield an overall probability of correspondence. Receiver operating characteristic (ROC) analysis was used to evaluate the performance of the individual features and the selected feature subset in the task of distinguishing corresponding pairs from noncorresponding pairs. Using a FFDM database with 123 corresponding image pairs and 82 noncorresponding pairs, the distance feature yielded an area under the ROC curve (AUC) of 0.81±0.02 with leave-one-out (by physical lesion) evaluation, and the feature metric subset, which included distance, gradient texture, and ROI-based correlation, yielded an AUC of 0.87±0.02. The improvement by using multiple feature metrics was statistically

Mining the Text: 34 Text Features that Can Ease or Obstruct Text Comprehension and Use

ERIC Educational Resources Information Center

White, Sheida

2012-01-01

This article presents 34 characteristics of texts and tasks ("text features") that can make continuous (prose), noncontinuous (document), and quantitative texts easier or more difficult for adolescents and adults to comprehend and use. The text features were identified by examining the assessment tasks and associated texts in the national…

Gene expression profiling identifies inflammation and angiogenesis as distinguishing features of canine hemangiosarcoma.

PubMed

Tamburini, Beth A; Phang, Tzu L; Fosmire, Susan P; Scott, Milcah C; Trapp, Susan C; Duckett, Megan M; Robinson, Sally R; Slansky, Jill E; Sharkey, Leslie C; Cutter, Gary R; Wojcieszyn, John W; Bellgrau, Donald; Gemmill, Robert M; Hunter, Lawrence E; Modiano, Jaime F

2010-11-09

The etiology of hemangiosarcoma remains incompletely understood. Its common occurrence in dogs suggests predisposing factors favor its development in this species. These factors could represent a constellation of heritable characteristics that promote transformation events and/or facilitate the establishment of a microenvironment that is conducive for survival of malignant blood vessel-forming cells. The hypothesis for this study was that characteristic molecular features distinguish hemangiosarcoma from non-malignant endothelial cells, and that such features are informative for the etiology of this disease. We first investigated mutations of VHL and Ras family genes that might drive hemangiosarcoma by sequencing tumor DNA and mRNA (cDNA). Protein expression was examined using immunostaining. Next, we evaluated genome-wide gene expression profiling using the Affymetrix Canine 2.0 platform as a global approach to test the hypothesis. Data were evaluated using routine bioinformatics and validation was done using quantitative real time RT-PCR. Each of 10 tumor and four non-tumor samples analyzed had wild type sequences for these genes. At the genome wide level, hemangiosarcoma cells clustered separately from non-malignant endothelial cells based on a robust signature that included genes involved in inflammation, angiogenesis, adhesion, invasion, metabolism, cell cycle, signaling, and patterning. This signature did not simply reflect a cancer-associated angiogenic phenotype, as it also distinguished hemangiosarcoma from non-endothelial, moderately to highly angiogenic bone marrow-derived tumors (lymphoma, leukemia, osteosarcoma). The data show that inflammation and angiogenesis are important processes in the pathogenesis of vascular tumors, but a definitive ontogeny of the cells that give rise to these tumors remains to be established. The data do not yet distinguish whether functional or ontogenetic plasticity creates this phenotype, although they suggest that cells

Gene expression profiling identifies inflammation and angiogenesis as distinguishing features of canine hemangiosarcoma

PubMed Central

2010-01-01

Background The etiology of hemangiosarcoma remains incompletely understood. Its common occurrence in dogs suggests predisposing factors favor its development in this species. These factors could represent a constellation of heritable characteristics that promote transformation events and/or facilitate the establishment of a microenvironment that is conducive for survival of malignant blood vessel-forming cells. The hypothesis for this study was that characteristic molecular features distinguish hemangiosarcoma from non-malignant endothelial cells, and that such features are informative for the etiology of this disease. Methods We first investigated mutations of VHL and Ras family genes that might drive hemangiosarcoma by sequencing tumor DNA and mRNA (cDNA). Protein expression was examined using immunostaining. Next, we evaluated genome-wide gene expression profiling using the Affymetrix Canine 2.0 platform as a global approach to test the hypothesis. Data were evaluated using routine bioinformatics and validation was done using quantitative real time RT-PCR. Results Each of 10 tumor and four non-tumor samples analyzed had wild type sequences for these genes. At the genome wide level, hemangiosarcoma cells clustered separately from non-malignant endothelial cells based on a robust signature that included genes involved in inflammation, angiogenesis, adhesion, invasion, metabolism, cell cycle, signaling, and patterning. This signature did not simply reflect a cancer-associated angiogenic phenotype, as it also distinguished hemangiosarcoma from non-endothelial, moderately to highly angiogenic bone marrow-derived tumors (lymphoma, leukemia, osteosarcoma). Conclusions The data show that inflammation and angiogenesis are important processes in the pathogenesis of vascular tumors, but a definitive ontogeny of the cells that give rise to these tumors remains to be established. The data do not yet distinguish whether functional or ontogenetic plasticity creates this

Texture Feature Analysis for Different Resolution Level of Kidney Ultrasound Images

NASA Astrophysics Data System (ADS)

Kairuddin, Wan Nur Hafsha Wan; Mahmud, Wan Mahani Hafizah Wan

2017-08-01

Image feature extraction is a technique to identify the characteristic of the image. The objective of this work is to discover the texture features that best describe a tissue characteristic of a healthy kidney from ultrasound (US) image. Three ultrasound machines that have different specifications are used in order to get a different quality (different resolution) of the image. Initially, the acquired images are pre-processed to de-noise the speckle to ensure the image preserve the pixels in a region of interest (ROI) for further extraction. Gaussian Low- pass Filter is chosen as the filtering method in this work. 150 of enhanced images then are segmented by creating a foreground and background of image where the mask is created to eliminate some unwanted intensity values. Statistical based texture features method is used namely Intensity Histogram (IH), Gray-Level Co-Occurance Matrix (GLCM) and Gray-level run-length matrix (GLRLM).This method is depends on the spatial distribution of intensity values or gray levels in the kidney region. By using One-Way ANOVA in SPSS, the result indicated that three features (Contrast, Difference Variance and Inverse Difference Moment Normalized) from GLCM are not statistically significant; this concludes that these three features describe a healthy kidney characteristics regardless of the ultrasound image quality.

Spectral characteristics and feature selection of satellite remote sensing data for climate and anthropogenic changes assessment in Bucharest area

NASA Astrophysics Data System (ADS)

Zoran, Maria; Savastru, Roxana; Savastru, Dan; Tautan, Marina; Miclos, Sorin; Cristescu, Luminita; Carstea, Elfrida; Baschir, Laurentiu

2010-05-01

Urban systems play a vital role in social and economic development in all countries. Their environmental changes can be investigated on different spatial and temporal scales. Urban and peri-urban environment dynamics is of great interest for future planning and decision making as well as in frame of local and regional changes. Changes in urban land cover include changes in biotic diversity, actual and potential primary productivity, soil quality, runoff, and sedimentation rates, and cannot be well understood without the knowledge of land use change that drives them. The study focuses on the assessment of environmental features changes for Bucharest metropolitan area, Romania by satellite remote sensing and in-situ monitoring data. Rational feature selection from the varieties of spectral channels in the optical wavelengths of electromagnetic spectrum (VIS and NIR) is very important for effective analysis and information extraction of remote sensing data. Based on comprehensively analyses of the spectral characteristics of remote sensing data is possibly to derive environmental changes in urban areas. The information quantity contained in a band is an important parameter in evaluating the band. The deviation and entropy are often used to show information amount. Feature selection is one of the most important steps in recognition and classification of remote sensing images. Therefore, it is necessary to select features before classification. The optimal features are those that can be used to distinguish objects easily and correctly. Three factors—the information quantity of bands, the correlation between bands and the spectral characteristic (e.g. absorption specialty) of classified objects in test area Bucharest have been considered in our study. As, the spectral characteristic of an object is influenced by many factors, being difficult to define optimal feature parameters to distinguish all the objects in a whole area, a method of multi-level feature selection

Ultrasonographic features and clinical characteristics of Warthin-like variant of papillary thyroid carcinoma.

PubMed

Kim, Ga Ram; Shin, Jung Hee; Hahn, Soo Yeon; Ko, Eun Young; Oh, Young Lyun

2016-04-25

Warthin-like variant of papillary thyroid carcinoma (WVPTC) is a rare entity recently characterized. We evaluated ultrasonographic (US) features and clinical characteristics of WVPTC. Nine patients were diagnosed with WVPTC through surgery in our institution from May 2005 to January 2015. Eight of nine patients had available preoperative US images. A retrospective review of the US and clinical characteristics was performed. WVPTC compromised of 0.06% of 14,071 PTCs surgically confirmed. A mean age of nine patients was 53.2 years (range, 32-75 years). The mean nodule size of nine WVPTCs was 0.9 cm (range, 0.5-1.5 cm). Two patients showed central nodal metastasis and one patient with conventional PTC as an index tumor underwent central and lateral neck dissection. No one showed recurrence or distant metastasis during the follow-up period (mean, 4.6 years; range, 0.6-10 years). The most common US features of WVPTCs were solid composition (62.5%), hypoechogenicity (75%), and wider-than-tall shape (100%), respectively. Four (50%) of eight nodules showed well-defined margin and three (37.5%) of them had cystic component. One of eight resembled focal thyroiditis. Three nodules were considered as probably benign with US. All nine cases demonstrated underlying heterogeneous parenchymal echogenicity and accompanied chronic lymphocytic thyroiditis in permanent sections. Thyroid function tests in all patients were normal except for one with subclinical hypothyroidism. WVPTC is an uncommon subtype of PTC and has favorable prognosis, which can be misdiagnosed as a probably benign nodule or focal thyroiditis with US. All cases are associated with heterogeneous parenchyma in the background.

Utilization of spectral-spatial characteristics in shortwave infrared hyperspectral images to classify and identify fungi-contaminated peanuts.

PubMed

Qiao, Xiaojun; Jiang, Jinbao; Qi, Xiaotong; Guo, Haiqiang; Yuan, Deshuai

2017-04-01

It's well-known fungi-contaminated peanuts contain potent carcinogen. Efficiently identifying and separating the contaminated can help prevent aflatoxin entering in food chain. In this study, shortwave infrared (SWIR) hyperspectral images for identifying the prepared contaminated kernels. Feature selection method of analysis of variance (ANOVA) and feature extraction method of nonparametric weighted feature extraction (NWFE) were used to concentrate spectral information into a subspace where contaminated and healthy peanuts can have favorable separability. Then, peanut pixels were classified using SVM. Moreover, image segmentation method of region growing was applied to segment the image as kernel-scale patches and meanwhile to number the kernels. The result shows that pixel-wise classification accuracies are 99.13% for breed A, 96.72% for B and 99.73% for C in learning images, and are 96.32%, 94.2% and 97.51% in validation images. Contaminated peanuts were correctly marked as aberrant kernels in both learning images and validation images. Copyright © 2016 Elsevier Ltd. All rights reserved.

Using Functional or Structural Magnetic Resonance Images and Personal Characteristic Data to Identify ADHD and Autism

PubMed Central

Ghiassian, Sina; Greiner, Russell; Jin, Ping; Brown, Matthew R. G.

2016-01-01

A clinical tool that can diagnose psychiatric illness using functional or structural magnetic resonance (MR) brain images has the potential to greatly assist physicians and improve treatment efficacy. Working toward the goal of automated diagnosis, we propose an approach for automated classification of ADHD and autism based on histogram of oriented gradients (HOG) features extracted from MR brain images, as well as personal characteristic data features. We describe a learning algorithm that can produce effective classifiers for ADHD and autism when run on two large public datasets. The algorithm is able to distinguish ADHD from control with hold-out accuracy of 69.6% (over baseline 55.0%) using personal characteristics and structural brain scan features when trained on the ADHD-200 dataset (769 participants in training set, 171 in test set). It is able to distinguish autism from control with hold-out accuracy of 65.0% (over baseline 51.6%) using functional images with personal characteristic data when trained on the Autism Brain Imaging Data Exchange (ABIDE) dataset (889 participants in training set, 222 in test set). These results outperform all previously presented methods on both datasets. To our knowledge, this is the first demonstration of a single automated learning process that can produce classifiers for distinguishing patients vs. controls from brain imaging data with above-chance accuracy on large datasets for two different psychiatric illnesses (ADHD and autism). Working toward clinical applications requires robustness against real-world conditions, including the substantial variability that often exists among data collected at different institutions. It is therefore important that our algorithm was successful with the large ADHD-200 and ABIDE datasets, which include data from hundreds of participants collected at multiple institutions. While the resulting classifiers are not yet clinically relevant, this work shows that there is a signal in the (f

Arabic writer identification based on diacritic's features

NASA Astrophysics Data System (ADS)

Maliki, Makki; Al-Jawad, Naseer; Jassim, Sabah A.

2012-06-01

Natural languages like Arabic, Kurdish, Farsi (Persian), Urdu, and any other similar languages have many features, which make them different from other languages like Latin's script. One of these important features is diacritics. These diacritics are classified as: compulsory like dots which are used to identify/differentiate letters, and optional like short vowels which are used to emphasis consonants. Most indigenous and well trained writers often do not use all or some of these second class of diacritics, and expert readers can infer their presence within the context of the writer text. In this paper, we investigate the use of diacritics shapes and other characteristic as parameters of feature vectors for Arabic writer identification/verification. Segmentation techniques are used to extract the diacritics-based feature vectors from examples of Arabic handwritten text. The results of evaluation test will be presented, which has been carried out on an in-house database of 50 writers. Also the viability of using diacritics for writer recognition will be demonstrated.

Diagnostic accuracy of clinical examination features for identifying large rotator cuff tears in primary health care

PubMed Central

Cadogan, Angela; McNair, Peter; Laslett, Mark; Hing, Wayne; Taylor, Stephen

2013-01-01

Objectives: Rotator cuff tears are a common and disabling complaint. The early diagnosis of medium and large size rotator cuff tears can enhance the prognosis of the patient. The aim of this study was to identify clinical features with the strongest ability to accurately predict the presence of a medium, large or multitendon (MLM) rotator cuff tear in a primary care cohort. Methods: Participants were consecutively recruited from primary health care practices (n = 203). All participants underwent a standardized history and physical examination, followed by a standardized X-ray series and diagnostic ultrasound scan. Clinical features associated with the presence of a MLM rotator cuff tear were identified (P<0.200), a logistic multiple regression model was derived for identifying a MLM rotator cuff tear and thereafter diagnostic accuracy was calculated. Results: A MLM rotator cuff tear was identified in 24 participants (11.8%). Constant pain and a painful arc in abduction were the strongest predictors of a MLM tear (adjusted odds ratio 3.04 and 13.97 respectively). Combinations of ten history and physical examination variables demonstrated highest levels of sensitivity when five or fewer were positive [100%, 95% confidence interval (CI): 0.86–1.00; negative likelihood ratio: 0.00, 95% CI: 0.00–0.28], and highest specificity when eight or more were positive (0.91, 95% CI: 0.86–0.95; positive likelihood ratio 4.66, 95% CI: 2.34–8.74). Discussion: Combinations of patient history and physical examination findings were able to accurately detect the presence of a MLM rotator cuff tear. These findings may aid the primary care clinician in more efficient and accurate identification of rotator cuff tears that may require further investigation or orthopedic consultation. PMID:24421626

Learning Crisis Unit through Post-Crisis: Characteristics and Mechanisms

ERIC Educational Resources Information Center

Chebbi, Hela; Pündrich, Aline Pereira

2015-01-01

Purpose: This paper aims to identify the characteristics that a crisis unit should have to achieve effective learning after crisis. Literature has identified many relations between learning organizations and crisis; yet, there is a dearth of research on specific studies about crisis units and their post-crisis learning features. Thus, this paper…

Steel syndrome: dislocated hips and radial heads, carpal coalition, scoliosis, short stature, and characteristic facial features.

PubMed

Flynn, John M; Ramirez, Norman; Betz, Randal; Mulcahey, Mary Jane; Pino, Franz; Herrera-Soto, Jose A; Carlo, Simon; Cornier, Alberto S

2010-01-01

A syndrome of children with short stature, bilateral hip dislocations, radial head dislocations, carpal coalitions, scoliosis, and cavus feet in Puerto Rican children, was reported by Steel et al in 1993. The syndrome was described as a unique entity with dismal results after conventional treatment of dislocated hips. The purpose of this study is to reevaluate this patient population with a longer follow-up and delineate the clinical and radiologic features, treatment outcomes, and the genetic characteristics. This is a retrospective cohort study of 32 patients in whom we evaluated the clinical, imaging data, and genetic characteristics. We compare the findings and quality of life in patients with this syndrome who have had attempts at reduction of the hips versus those who did not have the treatment. Congenital hip dislocations were present in 100% of the patients. There was no attempt at reduction in 39% (25/64) of the hips. In the remaining 61% (39/64), the hips were treated with a variety of modalities fraught with complications. Of those treated, 85% (33/39) remain dislocated, the rest of the hips continue subluxated with acetabular dysplasia and pain. The group of hips that were not treated reported fewer complaints and limitation in daily activities compared with the hips that had attempts at reduction. Steel syndrome is a distinct clinical entity characterized by short stature, bilateral hip and radial head dislocation, carpal coalition, scoliosis, cavus feet, and characteristic facial features with dismal results for attempts at reduction of the hips. Prognostic Study Level II.

Characteristic symptoms and associated features of exploding head syndrome in undergraduates.

PubMed

Sharpless, Brian A

2018-03-01

Background Exploding head syndrome (EHS) is characterized by loud noises or a sense of explosion in the head during sleep transitions. Though relatively common, little is known about its characteristic symptoms or associated features. Methods A cross-sectional study of 49 undergraduates with EHS was performed. A clinical interview established diagnosis. Results The most common accompanying symptoms were tachycardia, fear, and muscle jerks/twitches with the most severe associated with respiration difficulties. Visual phenomena were more common than expected (27%). EHS episodes were perceived as having a random course, but were most likely to occur during wake-sleep transitions and when sleeping in a supine position. Only 11% reported EHS to a professional, and 8% of those with recurrent EHS attempted to prevent episodes. Conclusions EHS episodes are complex (Mean (M) = 4.5 additional symptoms), often multisensorial, and usually associated with clinically-significant fear. They are rarely reported to professionals and treatment approaches are limited.

Synoptic evaluation of scale-dependent metrics for hydrographic line feature geometry

USGS Publications Warehouse

Stanislawski, Larry V.; Buttenfield, Barbara P.; Raposo, Paulo; Cameron, Madeline; Falgout, Jeff T.

2015-01-01

Methods of acquisition and feature simplification for vector feature data impact cartographic representations and scientific investigations of these data, and are therefore important considerations for geographic information science (Haunert and Sester 2008). After initial collection, linear features may be simplified to reduce excessive detail or to furnish a reduced-scale version of the features through cartographic generalization (Regnauld and McMaster 2008, Stanislawski et al. 2014). A variety of algorithms exist to simplify linear cartographic features, and all of the methods affect the positional accuracy of the features (Shahriari and Tao 2002, Regnauld and McMaster 2008, Stanislawski et al. 2012). In general, simplification operations are controlled by one or more tolerance parameters that limit the amount of positional change the operation can make to features. Using a single tolerance value can have varying levels of positional change on features; depending on local shape, texture, or geometric characteristics of the original features (McMaster and Shea 1992, Shahriari and Tao 2002, Buttenfield et al. 2010). Consequently, numerous researchers have advocated calibration of simplification parameters to control quantifiable properties of resulting changes to the features (Li and Openshaw 1990, Raposo 2013, Tobler 1988, Veregin 2000, and Buttenfield, 1986, 1989).This research identifies relations between local topographic conditions and geometric characteristics of linear features that are available in the National Hydrography Dataset (NHD). The NHD is a comprehensive vector dataset of surface 18 th ICA Workshop on Generalisation and Multiple Representation, Rio de Janiero, Brazil 2015 2 water features within the United States that is maintained by the U.S. Geological Survey (USGS). In this paper, geometric characteristics of cartographic representations for natural stream and river features are summarized for subbasin watersheds within entire regions of the

A Novel Feature-Map Based ICA Model for Identifying the Individual, Intra/Inter-Group Brain Networks across Multiple fMRI Datasets.

PubMed

Wang, Nizhuan; Chang, Chunqi; Zeng, Weiming; Shi, Yuhu; Yan, Hongjie

2017-01-01

Independent component analysis (ICA) has been widely used in functional magnetic resonance imaging (fMRI) data analysis to evaluate functional connectivity of the brain; however, there are still some limitations on ICA simultaneously handling neuroimaging datasets with diverse acquisition parameters, e.g., different repetition time, different scanner, etc. Therefore, it is difficult for the traditional ICA framework to effectively handle ever-increasingly big neuroimaging datasets. In this research, a novel feature-map based ICA framework (FMICA) was proposed to address the aforementioned deficiencies, which aimed at exploring brain functional networks (BFNs) at different scales, e.g., the first level (individual subject level), second level (intragroup level of subjects within a certain dataset) and third level (intergroup level of subjects across different datasets), based only on the feature maps extracted from the fMRI datasets. The FMICA was presented as a hierarchical framework, which effectively made ICA and constrained ICA as a whole to identify the BFNs from the feature maps. The simulated and real experimental results demonstrated that FMICA had the excellent ability to identify the intergroup BFNs and to characterize subject-specific and group-specific difference of BFNs from the independent component feature maps, which sharply reduced the size of fMRI datasets. Compared with traditional ICAs, FMICA as a more generalized framework could efficiently and simultaneously identify the variant BFNs at the subject-specific, intragroup, intragroup-specific and intergroup levels, implying that FMICA was able to handle big neuroimaging datasets in neuroscience research.

Characteristics of Reticent and Disruptive Children As Identified by the Barclay Classroom Climate Inventory.

ERIC Educational Resources Information Center

Barclay, James R.

The Barclay Classroom Climate Inventory was employed to identify the psychometric characteristics of reticent and disruptive children. The BCCI utilizes self-competency judgments, peer nominations, vocational interests and teacher adjectival ratings in an effort to measure the various expectations which interact in the elementary classroom. A…

Characteristic features of cutaneous melanoma in a dermatology referral centre in Tehran, Iran.

PubMed

Kamyab, Kambiz; Kazemi, Sheyda; Azimi, Pourya; Azizpour, Arghavan; Ghandi, Narges; Pirooz, Elham; Noormohammadpour, Pedram; Mirshams-Shahshahani, Mostafa; Daneshpazhooh, Maryam

2017-11-01

The characteristics of cutaneous melanoma in the Middle-Eastern countries is poorly described. Therefore we conducted this study to determine the characteristics of melanoma in Iran. A retrospective, cross sectional study of melanoma patients seen at a tertiary referral centre, Iran, from May 2004 to October 2014. Clinical data included age and gender of the patients at the time of diagnosis, tumour location and tumour size. Histological characteristics included Breslow thickness, Clark level and subtype of tumour. A total of 450 cases of melanoma with a male/female ratio of 1.1:1 were reviewed. The mean age of patients was 57.5 years. The most frequent histological subtypes were acral lentiginous melanoma (30%) and lentigo maligna melanoma (29%). In 215 cases (49%) the tumour was located on the extremities. The second most common site was the face. Tumour invasion was mainly at Clark level III and IV. The mean Breslow thickness was 2.8 mm; 143 (38%) melanomas had a Breslow thickness less than 1 mm (T1) and 86 (23%) were more than 4 mm (T4). This study indicates that clinical and histological features of melanoma in Iranians (who are mainly of skin phototypes 3-4) are different from those observed in Western countries. Further cohort studies are required to evaluate the role of ethnic and environmental risk factors for melanoma in different populations. © 2017 The Australasian College of Dermatologists.

Characteristics of Precipitation Features and Annual Rainfall during the TRMM Era in the Central Andes

NASA Technical Reports Server (NTRS)

Mohr, Karen I.; Slayback, Daniel; Yager, Karina

2014-01-01

The central Andes extends from 7 deg to 21 deg S, with its eastern boundary defined by elevation (1000m and greater) and its western boundary by the coastline. The authors used a combination of surface observations, reanalysis, and the University of Utah Tropical Rainfall Measuring Mission (TRMM) precipitation features (PF) database to understand the characteristics of convective systems and associated rainfall in the central Andes during the TRMM era, 1998-2012. Compared to other dry (West Africa), mountainous (Himalayas), and dynamically linked (Amazon) regions in the tropics, the central Andes PF population was distinct from these other regions, with small and weak PFs dominating its cumulative distribution functions and annual rainfall totals. No more than 10% of PFs in the central Andes met any of the thresholds used to identify and define deep convection (minimum IR cloud-top temperatures, minimum 85-GHz brightness temperature, maximum height of the 40-dBZ echo). For most of the PFs, available moisture was limited (less than 35mm) and instability low (less than 500 J kg(exp -1)). The central Andes represents a largely stable, dry to arid environment, limiting system development and organization. Hence, primarily short-duration events (less than 60 min) characterized by shallow convection and light to light-moderate rainfall rates (0.5-4.0 mm h(exp -1)) were found.

Pulmonary nodule characterization, including computer analysis and quantitative features.

PubMed

Bartholmai, Brian J; Koo, Chi Wan; Johnson, Geoffrey B; White, Darin B; Raghunath, Sushravya M; Rajagopalan, Srinivasan; Moynagh, Michael R; Lindell, Rebecca M; Hartman, Thomas E

2015-03-01

Pulmonary nodules are commonly detected in computed tomography (CT) chest screening of a high-risk population. The specific visual or quantitative features on CT or other modalities can be used to characterize the likelihood that a nodule is benign or malignant. Visual features on CT such as size, attenuation, location, morphology, edge characteristics, and other distinctive "signs" can be highly suggestive of a specific diagnosis and, in general, be used to determine the probability that a specific nodule is benign or malignant. Change in size, attenuation, and morphology on serial follow-up CT, or features on other modalities such as nuclear medicine studies or MRI, can also contribute to the characterization of lung nodules. Imaging analytics can objectively and reproducibly quantify nodule features on CT, nuclear medicine, and magnetic resonance imaging. Some quantitative techniques show great promise in helping to differentiate benign from malignant lesions or to stratify the risk of aggressive versus indolent neoplasm. In this article, we (1) summarize the visual characteristics, descriptors, and signs that may be helpful in management of nodules identified on screening CT, (2) discuss current quantitative and multimodality techniques that aid in the differentiation of nodules, and (3) highlight the power, pitfalls, and limitations of these various techniques.

Cemento-osseous dysplasia of the jaw bones: key radiographic features

PubMed Central

Alsufyani, NA; Lam, EWN

2011-01-01

Objective The purpose of this study is to assess possible diagnostic differences between general dentists (GPs) and oral and maxillofacial radiologists (RGs) in the identification of pathognomonic radiographic features of cemento-osseous dysplasia (COD) and its interpretation. Methods Using a systematic objective survey instrument, 3 RGs and 3 GPs reviewed 50 image sets of COD and similarly appearing entities (dense bone island, cementoblastoma, cemento-ossifying fibroma, fibrous dysplasia, complex odontoma and sclerosing osteitis). Participants were asked to identify the presence or absence of radiographic features and then to make an interpretation of the images. Results RGs identified a well-defined border (odds ratio (OR) 6.67, P < 0.05); radiolucent periphery (OR 8.28, P < 0.005); bilateral occurrence (OR 10.23, P < 0.01); mixed radiolucent/radiopaque internal structure (OR 10.53, P < 0.01); the absence of non-concentric bony expansion (OR 7.63, P < 0.05); and the association with anterior and posterior teeth (OR 4.43, P < 0.05) as key features of COD. Consequently, RGs were able to correctly interpret 79.3% of COD cases. In contrast, GPs identified the absence of root resorption (OR 4.52, P < 0.05) and the association with anterior and posterior teeth (OR 3.22, P = 0.005) as the only key features of COD and were able to correctly interpret 38.7% of COD cases. Conclusions There are statistically significant differences between RGs and GPs in the identification and interpretation of the radiographic features associated with COD (P < 0.001). We conclude that COD is radiographically discernable from other similarly appearing entities only if the characteristic radiographic features are correctly identified and then correctly interpreted. PMID:21346079

Cemento-osseous dysplasia of the jaw bones: key radiographic features.

PubMed

Alsufyani, N A; Lam, E W N

2011-03-01

The purpose of this study is to assess possible diagnostic differences between general dentists (GPs) and oral and maxillofacial radiologists (RGs) in the identification of pathognomonic radiographic features of cemento-osseous dysplasia (COD) and its interpretation. Using a systematic objective survey instrument, 3 RGs and 3 GPs reviewed 50 image sets of COD and similarly appearing entities (dense bone island, cementoblastoma, cemento-ossifying fibroma, fibrous dysplasia, complex odontoma and sclerosing osteitis). Participants were asked to identify the presence or absence of radiographic features and then to make an interpretation of the images. RGs identified a well-defined border (odds ratio (OR) 6.67, P < 0.05); radiolucent periphery (OR 8.28, P < 0.005); bilateral occurrence (OR 10.23, P < 0.01); mixed radiolucent/radiopaque internal structure (OR 10.53, P < 0.01); the absence of non-concentric bony expansion (OR 7.63, P < 0.05); and the association with anterior and posterior teeth (OR 4.43, P < 0.05) as key features of COD. Consequently, RGs were able to correctly interpret 79.3% of COD cases. In contrast, GPs identified the absence of root resorption (OR 4.52, P < 0.05) and the association with anterior and posterior teeth (OR 3.22, P = 0.005) as the only key features of COD and were able to correctly interpret 38.7% of COD cases. There are statistically significant differences between RGs and GPs in the identification and interpretation of the radiographic features associated with COD (P < 0.001). We conclude that COD is radiographically discernable from other similarly appearing entities only if the characteristic radiographic features are correctly identified and then correctly interpreted.

Identifying the Family, Job, and Workplace Characteristics of Employees Who Use Work-Family Benefits.

ERIC Educational Resources Information Center

Secret, Mary

2000-01-01

Employs a contextual effects perspective to identify family, job, and workplace characteristics associated with the use of work-family benefits of 527 employees in 83 businesses. Determined that particular family problems predict female employee use of paid leave and mental health benefits. Summarizes that workplace size, sector, and culture are…

Feature-Based Morphometry: Discovering Group-related Anatomical Patterns

PubMed Central

Toews, Matthew; Wells, William; Collins, D. Louis; Arbel, Tal

2015-01-01

This paper presents feature-based morphometry (FBM), a new, fully data-driven technique for discovering patterns of group-related anatomical structure in volumetric imagery. In contrast to most morphometry methods which assume one-to-one correspondence between subjects, FBM explicitly aims to identify distinctive anatomical patterns that may only be present in subsets of subjects, due to disease or anatomical variability. The image is modeled as a collage of generic, localized image features that need not be present in all subjects. Scale-space theory is applied to analyze image features at the characteristic scale of underlying anatomical structures, instead of at arbitrary scales such as global or voxel-level. A probabilistic model describes features in terms of their appearance, geometry, and relationship to subject groups, and is automatically learned from a set of subject images and group labels. Features resulting from learning correspond to group-related anatomical structures that can potentially be used as image biomarkers of disease or as a basis for computer-aided diagnosis. The relationship between features and groups is quantified by the likelihood of feature occurrence within a specific group vs. the rest of the population, and feature significance is quantified in terms of the false discovery rate. Experiments validate FBM clinically in the analysis of normal (NC) and Alzheimer's (AD) brain images using the freely available OASIS database. FBM automatically identifies known structural differences between NC and AD subjects in a fully data-driven fashion, and an equal error classification rate of 0.80 is achieved for subjects aged 60-80 years exhibiting mild AD (CDR=1). PMID:19853047

Integrated feature extraction and selection for neuroimage classification

NASA Astrophysics Data System (ADS)

Fan, Yong; Shen, Dinggang

2009-02-01

Feature extraction and selection are of great importance in neuroimage classification for identifying informative features and reducing feature dimensionality, which are generally implemented as two separate steps. This paper presents an integrated feature extraction and selection algorithm with two iterative steps: constrained subspace learning based feature extraction and support vector machine (SVM) based feature selection. The subspace learning based feature extraction focuses on the brain regions with higher possibility of being affected by the disease under study, while the possibility of brain regions being affected by disease is estimated by the SVM based feature selection, in conjunction with SVM classification. This algorithm can not only take into account the inter-correlation among different brain regions, but also overcome the limitation of traditional subspace learning based feature extraction methods. To achieve robust performance and optimal selection of parameters involved in feature extraction, selection, and classification, a bootstrapping strategy is used to generate multiple versions of training and testing sets for parameter optimization, according to the classification performance measured by the area under the ROC (receiver operating characteristic) curve. The integrated feature extraction and selection method is applied to a structural MR image based Alzheimer's disease (AD) study with 98 non-demented and 100 demented subjects. Cross-validation results indicate that the proposed algorithm can improve performance of the traditional subspace learning based classification.

Contingent negative variation in patients with deficit schizophrenia or bipolar I disorder with psychotic features: measurement and correlation with clinical characteristics.

PubMed

Li, Zhe; Deng, Wei; Liu, Xiang; Zheng, Zhong; Li, Mingli; Li, Yinfei; Han, Yuanyuan; Ma, Xiaohong; Wang, Qiang; Liu, Xiehe; Li, Tao

2015-04-01

Schizophrenia is a highly heterogeneous disease. Event-related potentials have been regarded to establish intermediate phenotypes of schizophrenia. Our previous study found that patients with deficit schizophrenia (DS) are relatively homogeneous and show a significantly longer onset latency of contingent negative variation (CNV) expectancy wave. To further examine CNV in patients with first-episode and drug-naïve DS or bipolar I disorder (BP I) with psychotic features, and also investigate correlations between CNV and clinical characteristics in DS and BP I. We elicited a CNV using an alarm (S1)-imperative (S2) paradigm in 30 DS patients or 33 BP I with psychotic features as well as 40 healthy controls. CNV amplitude was significantly smaller and reaction time significantly longer in the DS and BP I groups than in healthy controls. Post-imperative negative variation (PINV) interval was significantly shorter in the DS group than in healthy controls. The onset latency of CNV expectancy wave was significantly longer and PINV area significantly smaller in the DS group than in the other groups. In the DS group, CNV amplitude and PINV interval correlated negatively with the subscale of negative symptoms on the Positive and Negative Syndrome Scale (PANSS); CNV amplitude also correlated negatively with disease duration. In the BP I group, CNV amplitude and reaction time showed no correlation with clinical features. CNV amplitude is a common trait marker for psychosis. The onset latency of CNV expectancy wave appears to be a specific trait marker and may be used to identify candidate genes for DS.

Comparative analyses of Legionella species identifies genetic features of strains causing Legionnaires' disease.

PubMed

Gomez-Valero, Laura; Rusniok, Christophe; Rolando, Monica; Neou, Mario; Dervins-Ravault, Delphine; Demirtas, Jasmin; Rouy, Zoe; Moore, Robert J; Chen, Honglei; Petty, Nicola K; Jarraud, Sophie; Etienne, Jerome; Steinert, Michael; Heuner, Klaus; Gribaldo, Simonetta; Médigue, Claudine; Glöckner, Gernot; Hartland, Elizabeth L; Buchrieser, Carmen

2014-01-01

The genus Legionella comprises over 60 species. However, L. pneumophila and L. longbeachae alone cause over 95% of Legionnaires’ disease. To identify the genetic bases underlying the different capacities to cause disease we sequenced and compared the genomes of L. micdadei, L. hackeliae and L. fallonii (LLAP10), which are all rarely isolated from humans. We show that these Legionella species possess different virulence capacities in amoeba and macrophages, correlating with their occurrence in humans. Our comparative analysis of 11 Legionella genomes belonging to five species reveals highly heterogeneous genome content with over 60% representing species-specific genes; these comprise a complete prophage in L. micdadei, the first ever identified in a Legionella genome. Mobile elements are abundant in Legionella genomes; many encode type IV secretion systems for conjugative transfer, pointing to their importance for adaptation of the genus. The Dot/Icm secretion system is conserved, although the core set of substrates is small, as only 24 out of over 300 described Dot/Icm effector genes are present in all Legionella species. We also identified new eukaryotic motifs including thaumatin, synaptobrevin or clathrin/coatomer adaptine like domains. Legionella genomes are highly dynamic due to a large mobilome mainly comprising type IV secretion systems, while a minority of core substrates is shared among the diverse species. Eukaryotic like proteins and motifs remain a hallmark of the genus Legionella. Key factors such as proteins involved in oxygen binding, iron storage, host membrane transport and certain Dot/Icm substrates are specific features of disease-related strains.

Identifying the Minimum Model Features to Replicate Historic Morphodynamics of a Juvenile Delta

NASA Astrophysics Data System (ADS)

Czapiga, M. J.; Parker, G.

2017-12-01

We introduce a quasi-2D morphodynamic delta model that improves on past models that require many simplifying assumptions, e.g. a single channel representative of a channel network, fixed channel width, and spatially uniform deposition. Our model is useful for studying long-term progradation rates of any generic micro-tidal delta system with specification of: characteristic grain size, input water and sediment discharges and basin morphology. In particular, we relax the assumption of a single, implicit channel sweeping across the delta topset in favor of an implicit channel network. This network, coupled with recent research on channel-forming Shields number, quantitative assessments of the lateral depositional length of sand (corresponding loosely to levees) and length between bifurcations create a spatial web of deposition within the receiving basin. The depositional web includes spatial boundaries for areas infilling with sands carried as bed material load, as well as those filling via passive deposition of washload mud. Our main goal is to identify the minimum features necessary to accurately model the morphodynamics of channel number, width, depth, and overall delta progradation rate in a juvenile delta. We use the Wax Lake Delta in Louisiana as a test site due to its rapid growth in the last 40 years. Field data including topset/island bathymetry, channel bathymetry, topset/island width, channel width, number of channels, and radial topset length are compiled from US Army Corps of Engineers data for 1989, 1998, and 2006. Additional data is extracted from a DEM from 2015. These data are used as benchmarks for the hindcast model runs. The morphology of Wax Lake Delta is also strongly affected by a pre-delta substrate that acts as a lower "bedrock" boundary. Therefore, we also include closures for a bedrock-alluvial transition and an excess shear rate-law incision model to estimate bedrock incision. The model's framework is generic, but inclusion of individual

Structure and Characteristics of the Stepfamily: Implications for Counseling.

ERIC Educational Resources Information Center

Cobia, Debra C.

1996-01-01

Describes the development, structure, and characteristics of the stepfamily and distinguishes these features from those of traditional, intact families. Identifies stepfamily concerns, addressing these as typical transitional issues rather than as insurmountable problems, and presents four stages of developmental and structural changes for…

User-identified electronic cigarette behavioral strategies and device characteristics for cigarette smoking reduction.

PubMed

Soule, Eric K; Maloney, Sarah F; Guy, Mignonne C; Eissenberg, Thomas; Fagan, Pebbles

2018-04-01

There is limited evidence on how cigarette smokers use electronic cigarettes (ECIGs) for smoking cessation and reduction. This study used concept mapping, a participatory mixed-methods research approach, to identify ECIG use behaviors and device characteristics perceived to be associated with cigarette smoking cessation or reduction. Current ECIG users aged 18-64 were recruited from seven cities selected randomly from U.S. census tract regions. Participants were invited to complete concept mapping tasks: brainstorming, sorting and rating (n=72). During brainstorming, participants generated statements in response to a focus prompt ("A SPECIFIC WAY I HAVE USED electronic cigarettes to reduce my cigarette smoking or a SPECIFIC WAY electronic cigarettes help me reduce my cigarette smoking is…") and then sorted and rated the statements. Multidimensional scaling and hierarchical cluster analyses were used to generate a cluster map that was interpreted by the research team. Eight thematic clusters were identified: Convenience, Perceived Health Effects, Ease of Use, Versatility and Variety, Advantages of ECIGs over Cigarettes, Cigarette Substitutability, Reducing Harms to Self and Others, and Social Benefits. Participants generated several statements that related to specific behavioral strategies used when using ECIGs for smoking reduction/complete switching behaviors such as making rapid transitions from smoking to ECIG use or using certain ECIG liquids or devices. Former smokers rated the Perceived Health Effects cluster and several behavioral strategy statements higher than current smokers. These results help to identify ECIG use behaviors and characteristics perceived by ECIG users to aid in cigarette smoking cessation or reduction. Copyright © 2017 Elsevier Ltd. All rights reserved.

Melancholic depression prediction by identifying representative features in metabolic and microarray profiles with missing values.

PubMed

Nie, Zhi; Yang, Tao; Liu, Yashu; Li, Qingyang; Narayan, Vaibhav A; Wittenberg, Gayle; Ye, Jieping

2015-01-01

Recent studies have revealed that melancholic depression, one major subtype of depression, is closely associated with the concentration of some metabolites and biological functions of certain genes and pathways. Meanwhile, recent advances in biotechnologies have allowed us to collect a large amount of genomic data, e.g., metabolites and microarray gene expression. With such a huge amount of information available, one approach that can give us new insights into the understanding of the fundamental biology underlying melancholic depression is to build disease status prediction models using classification or regression methods. However, the existence of strong empirical correlations, e.g., those exhibited by genes sharing the same biological pathway in microarray profiles, tremendously limits the performance of these methods. Furthermore, the occurrence of missing values which are ubiquitous in biomedical applications further complicates the problem. In this paper, we hypothesize that the problem of missing values might in some way benefit from the correlation between the variables and propose a method to learn a compressed set of representative features through an adapted version of sparse coding which is capable of identifying correlated variables and addressing the issue of missing values simultaneously. An efficient algorithm is also developed to solve the proposed formulation. We apply the proposed method on metabolic and microarray profiles collected from a group of subjects consisting of both patients with melancholic depression and healthy controls. Results show that the proposed method can not only produce meaningful clusters of variables but also generate a set of representative features that achieve superior classification performance over those generated by traditional clustering and data imputation techniques. In particular, on both datasets, we found that in comparison with the competing algorithms, the representative features learned by the proposed

On a distinctive feature of problems of calculating time-average characteristics of nuclear reactor optimal control sets

NASA Astrophysics Data System (ADS)

Trifonenkov, A. V.; Trifonenkov, V. P.

2017-01-01

This article deals with a feature of problems of calculating time-average characteristics of nuclear reactor optimal control sets. The operation of a nuclear reactor during threatened period is considered. The optimal control search problem is analysed. The xenon poisoning causes limitations on the variety of statements of the problem of calculating time-average characteristics of a set of optimal reactor power off controls. The level of xenon poisoning is limited. There is a problem of choosing an appropriate segment of the time axis to ensure that optimal control problem is consistent. Two procedures of estimation of the duration of this segment are considered. Two estimations as functions of the xenon limitation were plot. Boundaries of the interval of averaging are defined more precisely.

Feature-based Morphometry

PubMed Central

Toews, Matthew; Wells, William M.; Collins, Louis; Arbel, Tal

2013-01-01

This paper presents feature-based morphometry (FBM), a new, fully data-driven technique for identifying group-related differences in volumetric imagery. In contrast to most morphometry methods which assume one-to-one correspondence between all subjects, FBM models images as a collage of distinct, localized image features which may not be present in all subjects. FBM thus explicitly accounts for the case where the same anatomical tissue cannot be reliably identified in all subjects due to disease or anatomical variability. A probabilistic model describes features in terms of their appearance, geometry, and relationship to sub-groups of a population, and is automatically learned from a set of subject images and group labels. Features identified indicate group-related anatomical structure that can potentially be used as disease biomarkers or as a basis for computer-aided diagnosis. Scale-invariant image features are used, which reflect generic, salient patterns in the image. Experiments validate FBM clinically in the analysis of normal (NC) and Alzheimer’s (AD) brain images using the freely available OASIS database. FBM automatically identifies known structural differences between NC and AD subjects in a fully data-driven fashion, and obtains an equal error classification rate of 0.78 on new subjects. PMID:20426102

Dysmorphic Facial Features and Other Clinical Characteristics in Two Patients with PEX1 Gene Mutations

PubMed Central

Gunduz, Mehmet

2016-01-01

Peroxisomal disorders are a group of genetically heterogeneous metabolic diseases related to dysfunction of peroxisomes. Dysmorphic features, neurological abnormalities, and hepatic dysfunction can be presenting signs of peroxisomal disorders. Here we presented dysmorphic facial features and other clinical characteristics in two patients with PEX1 gene mutation. Follow-up periods were 3.5 years and 1 year in the patients. Case I was one-year-old girl that presented with neurodevelopmental delay, hepatomegaly, bilateral hearing loss, and visual problems. Ophthalmologic examination suggested septooptic dysplasia. Cranial magnetic resonance imaging (MRI) showed nonspecific gliosis at subcortical and periventricular deep white matter. Case II was 2.5-year-old girl referred for investigation of global developmental delay and elevated liver enzymes. Ophthalmologic examination findings were consistent with bilateral nystagmus and retinitis pigmentosa. Cranial MRI was normal. Dysmorphic facial features including broad nasal root, low set ears, downward slanting eyes, downward slanting eyebrows, and epichantal folds were common findings in two patients. Molecular genetic analysis indicated homozygous novel IVS1-2A>G mutation in Case I and homozygous p.G843D (c.2528G>A) mutation in Case II in the PEX1 gene. Clinical findings and developmental prognosis vary in PEX1 gene mutation. Kabuki-like phenotype associated with liver pathology may indicate Zellweger spectrum disorders (ZSD). PMID:27882258

Unclear-onset intracerebral hemorrhage: Clinical characteristics, hematoma features, and outcomes.

PubMed

Inoue, Yasuteru; Miyashita, Fumio; Koga, Masatoshi; Minematsu, Kazuo; Toyoda, Kazunori

2017-12-01

Background and purpose Although unclear-onset ischemic stroke, including wake-up ischemic stroke, is drawing attention as a potential target for reperfusion therapy, acute unclear-onset intracerebral hemorrhage has been understudied. Clinical characteristics, hematoma features, and outcomes of patients who developed intracerebral hemorrhage during sleep or those with intracerebral hemorrhage who were unconscious when witnessed were determined. Methods Consecutive intracerebral hemorrhage patients admitted within 24 hours after onset or last-known normal time were classified into clear-onset intracerebral hemorrhage and unclear-onset intracerebral hemorrhage groups. Outcomes included initial hematoma volume, initial National Institutes of Health Stroke Scale score, hematoma growth on 24-hour follow-up computed tomography, and vital and functional prognoses at 30 days. Results Of 377 studied patients (122 women, 69 ± 11 years old), 147 (39.0%) had unclear-onset intracerebral hemorrhage. Patients with unclear-onset intracerebral hemorrhage had larger hematoma volumes (p = 0.044) and higher National Institutes of Health Stroke Scale scores (p < 0.001) than those with clear-onset intracerebral hemorrhage after multivariable adjustment for risk factors and comorbidities. Hematoma growth was similarly common between the two groups (p = 0.176). There were fewer patients with modified Rankin Scale (mRS) scores of 0-2 (p = 0.033) and more patients with mRS scores of 5-6 (p = 0.009) and with fatal outcomes (p = 0.049) in unclear-onset intracerebral hemorrhage group compared with clear-onset intracerebral hemorrhage as crude values, but not after adjustment. Conclusions Patients with unclear-onset intracerebral hemorrhage presented with larger hematomas and higher National Institutes of Health Stroke Scale scores at emergent visits than those with clear-onset intracerebral hemorrhage, independent of underlying characteristics. Unclear

Diffuse gliomas with FGFR3-TACC3 fusion have characteristic histopathological and molecular features.

PubMed

Bielle, Franck; Di Stefano, Anna-Luisa; Meyronet, David; Picca, Alberto; Villa, Chiara; Bernier, Michèle; Schmitt, Yohann; Giry, Marine; Rousseau, Audrey; Figarella-Branger, Dominique; Maurage, Claude-Alain; Uro-Coste, Emmanuelle; Lasorella, Anna; Iavarone, Antonio; Sanson, Marc; Mokhtari, Karima

2017-10-04

Adult glioblastomas, IDH-wildtype represent a heterogeneous group of diseases. They are resistant to conventional treatment by concomitant radiochemotherapy and carry a dismal prognosis. The discovery of oncogenic gene fusions in these tumors has led to prospective targeted treatments, but identification of these rare alterations in practice is challenging. Here, we report a series of 30 adult diffuse gliomas with an in frame FGFR3-TACC3 oncogenic fusion (n = 27 WHO grade IV and n = 3 WHO grade II) as well as their histological and molecular features. We observed recurrent morphological features (monomorphous ovoid nuclei, nuclear palisading and thin parallel cytoplasmic processes, endocrinoid network of thin capillaries) associated with frequent microcalcifications and desmoplasia. We report a constant immunoreactivity for FGFR3, which is a valuable method for screening for the FGFR3-TACC3 fusion with 100% sensitivity and 92% specificity. We confirmed the associated molecular features (typical genetic alterations of glioblastoma, except the absence of EGFR amplification, and an increased frequency of CDK4 and MDM2 amplifications). FGFR3 immunopositivity is a valuable tool to identify gliomas that are likely to harbor the FGFR3-TACC3 fusion for inclusion in targeted therapeutic trials. © 2017 International Society of Neuropathology.

Determining Image Processing Features Describing the Appearance of Challenging Mitotic Figures and Miscounted Nonmitotic Objects

PubMed Central

Gandomkar, Ziba; Brennan, Patrick C.; Mello-Thoms, Claudia

2017-01-01

Context: Previous studies showed that the agreement among pathologists in recognition of mitoses in breast slides is fairly modest. Aims: Determining the significantly different quantitative features among easily identifiable mitoses, challenging mitoses, and miscounted nonmitoses within breast slides and identifying which color spaces capture the difference among groups better than others. Materials and Methods: The dataset contained 453 mitoses and 265 miscounted objects in breast slides. The mitoses were grouped into three categories based on the confidence degree of three pathologists who annotated them. The mitoses annotated as “probably a mitosis” by the majority of pathologists were considered as the challenging category. The miscounted objects were recognized as a mitosis or probably a mitosis by only one of the pathologists. The mitoses were segmented using k-means clustering, followed by morphological operations. Morphological, intensity-based, and textural features were extracted from the segmented area and also the image patch of 63 × 63 pixels in different channels of eight color spaces. Holistic features describing the mitoses' surrounding cells of each image were also extracted. Statistical Analysis Used: The Kruskal–Wallis H-test followed by the Tukey-Kramer test was used to identify significantly different features. Results: The results indicated that challenging mitoses were smaller and rounder compared to other mitoses. Among different features, the Gabor textural features differed more than others between challenging mitoses and the easily identifiable ones. Sizes of the non-mitoses were similar to easily identifiable mitoses, but nonmitoses were rounder. The intensity-based features from chromatin channels were the most discriminative features between the easily identifiable mitoses and the miscounted objects. Conclusions: Quantitative features can be used to describe the characteristics of challenging mitoses and miscounted nonmitotic

Characteristics of circular features on comet 67P/Churyumov-Gerasimenko

NASA Astrophysics Data System (ADS)

Deller, J. F.; Güttler, C.; Tubiana, C.; Hofmann, M.; Sierks, H.

2017-09-01

Comet 67P/Churyumov-Gerasimenko shows a large variety of circular structures such as pits, elevated roundish features in Imhotep, and even a single occurrence of a plausible fresh impact crater. Imaging the pits in the Ma'at region, aiming to understand their structure and origin drove the design of the final descent trajectory of the Rosetta spacecraft. The high-resolution images obtained during the last mission phase allow us to study these pits as exemplary circular features. A complete catalogue of circular features gives us the possibility to compare and classify these structures systematically.

Locomotion energetics and gait characteristics of a rat-kangaroo, Bettongia penicillata, have some kangaroo-like features.

PubMed

Webster, K N; Dawson, T J

2003-09-01

The locomotory characteristics of kangaroos and wallabies are unusual, with both energetic costs and gait parameters differing from those of quadrupedal running mammals. The kangaroos and wallabies have an evolutionary history of only around 5 million years; their closest relatives, the rat-kangaroos, have a fossil record of more than 26 million years. We examined the locomotory characteristics of a rat-kangaroo, Bettongia penicillata. Locomotory energetics and gait parameters were obtained from animals exercising on a motorised treadmill at speeds from 0.6 m s(-1) to 6.2 m s(-1). Aerobic metabolic costs increased as hopping speed increased, but were significantly different from the costs for a running quadruped; at the fastest speed, the cost of hopping was 50% of the cost of running. Therefore B. penicillata can travel much faster than quadrupedal runners at similar levels of aerobic output. The maximum aerobic output of B. penicillata was 17 times its basal metabolism. Increases in speed during hopping were achieved through increases in stride length, with stride frequency remaining constant. We suggest that these unusual locomotory characteristics are a conservative feature among the hopping marsupials, with an evolutionary history of 20-30 million years.

Seismic features of Winnipegosis mounds in Saskatchewan

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

Gendzwill, D.J.

1988-07-01

The Winnipegosis Formation of southern Saskatchewan is characterized by reefs or reeflike mounds in its upper member. Several characteristic features of the mounds permit their identification from seismic-reflection data. These features include reflections from the flanks of the mound, a change in the reflection continuity in the middle and base of the mound, a velocity pullup under the mound, and subsidence of strata over the mound. Dissolution of the salt which surrounds the mounds sometimes occurs, resulting in a drape structure. Some or all of these features may be present at the correct seismic stratigraphic level for Winnipegosis mounds, dependingmore » on the local conditions. Subsidence of strata over the mounds indicates compaction and porosity loss from the original mound or possibly the degree of dolomitization or pressure dissolution. Salt-removal features over or adjacent to the mounds indicate fluid movements. Approximate ages can be estimated from stratigraphic thinning and thickening relationships above such features. Complications in identifying Winnipegosis mounds may arise from thin-bed effects if the mounds are not very thick compared to a seismic wavelength. Confusion may also arise from anhydrite, which may encase the mounds or which may form a thick horizontal layer at the tops of the mounds, causing an interfering signal.« less

Characteristic glycopeptides associated with extreme human longevity identified through plasma glycoproteomics.

PubMed

Miura, Yuri; Hashii, Noritaka; Ohta, Yuki; Itakura, Yoko; Tsumoto, Hiroki; Suzuki, Junya; Takakura, Daisuke; Abe, Yukiko; Arai, Yasumichi; Toyoda, Masashi; Kawasaki, Nana; Hirose, Nobuyoshi; Endo, Tamao

2018-06-01

Glycosylation is highly susceptible to changes of the physiological conditions, and accordingly, is a potential biomarker associated with several diseases and/or longevity. Semi-supercentenarians (SSCs; older than 105 years) are thought to be a model of human longevity. Thus, we performed glycoproteomics using plasma samples of SSCs, and identified proteins and conjugated N-glycans that are characteristic of extreme human longevity. Plasma proteins from Japanese semi-supercentenarians (SSCs, 106-109 years), aged controls (70-88 years), and young controls (20-38 years) were analysed by using lectin microarrays and liquid chromatography/mass spectrometry (LC/MS). Peak area ratios of glycopeptides to corresponding normalising peptides were subjected to orthogonal projections to latent structures discriminant analysis (OPLS-DA). Furthermore, plasma levels of clinical biomarkers were measured. We found two lectins such as Phaseolus vulgaris, and Erythrina cristagalli (ECA), of which protein binding were characteristically increased in SSCs. Peak area ratios of ECA-enriched glycopeptides were successfully discriminated between SSCs and controls using OPLS-DA, and indicated that tri-antennary and sialylated N-glycans of haptoglobin at Asn207 and Asn211 sites were characterized in SSCs. Sialylated glycans of haptoglobin are a potential biomarker of several diseases, such as hepatocellular carcinoma, liver cirrhosis, and IgA-nephritis. However, the SSCs analysed here did not suffer from these diseases. Tri-antennary and sialylated N-glycans on haptoglobin at the Asn207 and Asn211 sites were abundant in SSCs and characteristic of extreme human longevity. We found abundant glycans in SSCs, which may be associated with human longevity. Copyright © 2018 Elsevier B.V. All rights reserved.

Identifying key features of early stressful experiences that produce stress vulnerability and resilience in primates

PubMed Central

Parker, Karen J.; Maestripieri, Dario

2010-01-01

This article examines the complex role of early stressful experiences in producing both vulnerability and resilience to later stress-related psychopathology in a variety of primate models of human development. Two types of models are reviewed: Parental Separation Models (e.g., isolate-rearing, peer-rearing, parental separations, and stress inoculation) and Maternal Behavior Models (e.g., foraging demands, variation in maternal style, and maternal abuse). Based on empirical evidence, it is argued that early life stress exposure does not increase adult vulnerability to stress-related psychopathology as a linear function, as is generally believed, but instead reflects a quadratic function. Features of early stress exposure including the type, duration, frequency, ecological validity, sensory modality, and developmental timing, within and between species, are identified to better understand how early stressful experiences alter neurobiological systems to produce such diverse developmental outcomes. This article concludes by identifying gaps in our current knowledge, providing directions for future research, and discussing the translational implications of these primate models for human development and psychopathology. PMID:20851145

Hydro-geomorphic connectivity and landslide features extraction to identifying potential threats and hazardous areas

NASA Astrophysics Data System (ADS)

Tarolli, Paolo; Fuller, Ian C.; Basso, Federica; Cavalli, Marco; Sofia, Giulia

2017-04-01

Hydro-geomorphic connectivity has significantly emerged as a new concept to understand the transfer of surface water and sediment through landscapes. A further scientific challenge is determining how the concept can be used to enable sustainable land and water management. This research proposes an interesting approach to integrating remote sensing techniques, connectivity theory, and geomorphometry based on high-resolution digital terrain model (HR-DTMs) to automatically extract landslides crowns and gully erosion, to determine the different rate of connectivity among the main extracted features and the river network, and thus determine a possible categorization of hazardous areas. The study takes place in two mountainous regions in the Wellington Region (New Zealand). The methodology is a three step approach. Firstly, we performed an automatic detection of the likely landslides crowns through the use of thresholds obtained by the statistical analysis of the variability of landform curvature. After that, the research considered the Connectivity Index to analyse how a complex and rugged topography induces large variations in erosion and sediment delivery in the two catchments. Lastly, the two methods have been integrated to create a unique procedure able to classify the different rate of connectivity among the main features and the river network and thus identifying potential threats and hazardous areas. The methodology is fast, and it can produce a detailed and updated inventory map that could be a key tool for erosional and sediment delivery hazard mitigation. This fast and simple method can be a useful tool to manage emergencies giving priorities to more failure-prone zones. Furthermore, it could be considered to do a preliminary interpretations of geomorphological phenomena and more in general, it could be the base to develop inventory maps. References Cavalli M, Trevisani S, Comiti F, Marchi L. 2013. Geomorphometric assessment of spatial sediment connectivity

A genome-wide association scan in admixed Latin Americans identifies loci influencing facial and scalp hair features

PubMed Central

Adhikari, Kaustubh; Fontanil, Tania; Cal, Santiago; Mendoza-Revilla, Javier; Fuentes-Guajardo, Macarena; Chacón-Duque, Juan-Camilo; Al-Saadi, Farah; Johansson, Jeanette A.; Quinto-Sanchez, Mirsha; Acuña-Alonzo, Victor; Jaramillo, Claudia; Arias, William; Barquera Lozano, Rodrigo; Macín Pérez, Gastón; Gómez-Valdés, Jorge; Villamil-Ramírez, Hugo; Hunemeier, Tábita; Ramallo, Virginia; Silva de Cerqueira, Caio C.; Hurtado, Malena; Villegas, Valeria; Granja, Vanessa; Gallo, Carla; Poletti, Giovanni; Schuler-Faccini, Lavinia; Salzano, Francisco M.; Bortolini, Maria-Cátira; Canizales-Quinteros, Samuel; Rothhammer, Francisco; Bedoya, Gabriel; Gonzalez-José, Rolando; Headon, Denis; López-Otín, Carlos; Tobin, Desmond J.; Balding, David; Ruiz-Linares, Andrés

2016-01-01

We report a genome-wide association scan in over 6,000 Latin Americans for features of scalp hair (shape, colour, greying, balding) and facial hair (beard thickness, monobrow, eyebrow thickness). We found 18 signals of association reaching genome-wide significance (P values 5 × 10−8 to 3 × 10−119), including 10 novel associations. These include novel loci for scalp hair shape and balding, and the first reported loci for hair greying, monobrow, eyebrow and beard thickness. A newly identified locus influencing hair shape includes a Q30R substitution in the Protease Serine S1 family member 53 (PRSS53). We demonstrate that this enzyme is highly expressed in the hair follicle, especially the inner root sheath, and that the Q30R substitution affects enzyme processing and secretion. The genome regions associated with hair features are enriched for signals of selection, consistent with proposals regarding the evolution of human hair. PMID:26926045

The Learner Characteristics, Features of Desktop 3D Virtual Reality Environments, and College Chemistry Instruction: A Structural Equation Modeling Analysis

ERIC Educational Resources Information Center

Merchant, Zahira; Goetz, Ernest T.; Keeney-Kennicutt, Wendy; Kwok, Oi-man; Cifuentes, Lauren; Davis, Trina J.

2012-01-01

We examined a model of the impact of a 3D desktop virtual reality environment on the learner characteristics (i.e. perceptual and psychological variables) that can enhance chemistry-related learning achievements in an introductory college chemistry class. The relationships between the 3D virtual reality features and the chemistry learning test as…

Finger vein recognition based on the hyperinformation feature

NASA Astrophysics Data System (ADS)

Xi, Xiaoming; Yang, Gongping; Yin, Yilong; Yang, Lu

2014-01-01

The finger vein is a promising biometric pattern for personal identification due to its advantages over other existing biometrics. In finger vein recognition, feature extraction is a critical step, and many feature extraction methods have been proposed to extract the gray, texture, or shape of the finger vein. We treat them as low-level features and present a high-level feature extraction framework. Under this framework, base attribute is first defined to represent the characteristics of a certain subcategory of a subject. Then, for an image, the correlation coefficient is used for constructing the high-level feature, which reflects the correlation between this image and all base attributes. Since the high-level feature can reveal characteristics of more subcategories and contain more discriminative information, we call it hyperinformation feature (HIF). Compared with low-level features, which only represent the characteristics of one subcategory, HIF is more powerful and robust. In order to demonstrate the potential of the proposed framework, we provide a case study to extract HIF. We conduct comprehensive experiments to show the generality of the proposed framework and the efficiency of HIF on our databases, respectively. Experimental results show that HIF significantly outperforms the low-level features.

Nosiheptide Biosynthesis Featuring a Unique Indole Side Ring Formation on the Characteristic Thiopeptide Framework

PubMed Central

Yu, Yi; Duan, Lian; Zhang, Qi; Liao, Rijing; Ding, Ying; Pan, Haixue; Wendt-Pienkowski, Evelyn; Tang, Gongli; Shen, Ben; Liu, Wen

2009-01-01

Nosiheptide (NOS), belonging to the e series of thiopeptide antibiotics that exhibit potent activity against various bacterial pathogens, bears a unique indole side ring system and regiospecific hydroxyl groups on the characteristic macrocyclic core. Here, cloning, sequencing and characterization of the nos gene cluster from Streptomyces actuosus ATCC 25421 as a model for this series of thiopeptides has unveiled new insights into their biosynthesis. Bioinformatics-based sequence analysis and in vivo investigation into the gene functions show that NOS biosynthesis shares a common strategy with recently characterized b or c series thiopeptides for forming the characteristic macrocyclic core, which features a ribosomally synthesized precursor peptide with conserved posttranslational modifications. However, it apparently proceeds via a different route for tailoring the thiopeptide framework, allowing the final product to exhibit the distinct structural characteristics of e series thiopeptides, such as the indole side ring system. Chemical complementation supports the notion that the S-adenosylmethionine (AdoMet)-dependent protein NosL may play a central role in converting Trp to the key 3-methylindole moiety by an unusual carbon side chain rearrangement, most likely via a radical-initiated mechanism. Characterization of the indole side ring-opened analog of NOS from the nosN mutant strain is consistent with the proposed methyltransferase activity of its encoded protein, shedding light into the timing of the individual steps for indole side ring biosynthesis. These results also suggest the feasibility of engineering novel thiopeptides for drug discovery by manipulating the NOS biosynthetic machinery. PMID:19678698

Correlative feature analysis of FFDM images

NASA Astrophysics Data System (ADS)

Yuan, Yading; Giger, Maryellen L.; Li, Hui; Sennett, Charlene

2008-03-01

Identifying the corresponding image pair of a lesion is an essential step for combining information from different views of the lesion to improve the diagnostic ability of both radiologists and CAD systems. Because of the non-rigidity of the breasts and the 2D projective property of mammograms, this task is not trivial. In this study, we present a computerized framework that differentiates the corresponding images from different views of a lesion from non-corresponding ones. A dual-stage segmentation method, which employs an initial radial gradient index(RGI) based segmentation and an active contour model, was initially applied to extract mass lesions from the surrounding tissues. Then various lesion features were automatically extracted from each of the two views of each lesion to quantify the characteristics of margin, shape, size, texture and context of the lesion, as well as its distance to nipple. We employed a two-step method to select an effective subset of features, and combined it with a BANN to obtain a discriminant score, which yielded an estimate of the probability that the two images are of the same physical lesion. ROC analysis was used to evaluate the performance of the individual features and the selected feature subset in the task of distinguishing between corresponding and non-corresponding pairs. By using a FFDM database with 124 corresponding image pairs and 35 non-corresponding pairs, the distance feature yielded an AUC (area under the ROC curve) of 0.8 with leave-one-out evaluation by lesion, and the feature subset, which includes distance feature, lesion size and lesion contrast, yielded an AUC of 0.86. The improvement by using multiple features was statistically significant as compared to single feature performance. (p<0.001)

[Ecological and biological characteristics of Drosophila melanogaster features depending on the dose of electromagnetic radiation of various types].

PubMed

Babkina, V V; Chernova, G V; Allenova, E A; Endebera, O P; Naumkina, E N

2013-01-01

Biological effects of exposure to red light (lambda = 660 +/- 10 nm) on the viability and morphophysiological characteristics of Drosophila melanogaster have been studied. The ability of this physical agent to modify these features is shown. The degree of expression and impact of biological effects depend on the dose, functional and genetic status of the organism. The study of the life expectancy of the exposed to EHF and white light D. melanogaster has revealed that expression of the features depends on the radiation doses, genotype, sex, the nature of the position of wings and lighting conditions. It has been found that the dark mode (24 h-night) is more favorable than the artificial lighting. Individuals with the left wing at the top are more sensitive to the external factors.

Valuable Features in Mobile Health Apps for Patients and Consumers: Content Analysis of Apps and User Ratings

PubMed Central

2015-01-01

Background The explosion of mobile phones with app capabilities coupled with increased expectations of the patient-consumers’ role in managing their care presents a unique opportunity to use mobile health (mHealth) apps. Objectives The aim of this paper is to identify the features and characteristics most-valued by patient-consumers (“users”) that contribute positively to the rating of an app. Methods A collection of 234 apps associated with reputable health organizations found in the medical, health, and fitness categories of the Apple iTunes store and Google Play marketplace was assessed manually for the presence of 12 app features and characteristics. Regression analysis was used to determine which, if any, contributed positively to a user’s rating of the app. Results Analysis of these 12 features explained 9.3% (R 2=.093 n=234, P<.001) of the variation in an app’s rating, with only 5 reaching statistical significance. Of the 5 reaching statistical significance, plan or orders, export of data, usability, and cost contributed positively to a user’s rating, while the tracker feature detracted from it. Conclusions These findings suggest that users appreciate features that save time over current methods and identify an app as valuable when it is simple and intuitive to use, provides specific instructions to better manage a condition, and shares data with designated individuals. Although tracking is a core function of most health apps, this feature may detract from a user’s experience when not executed properly. Further investigation into mHealth app features is worthwhile given the inability of the most common features to explain a large portion of an app’s rating. In the future, studies should focus on one category in the app store, specific diseases, or desired behavior change, and methods should include measuring the quality of each feature, both through manual assessment and evaluation of user reviews. Additional investigations into understanding

Hydrate pingoes at Nyegga: some characteristic features

NASA Astrophysics Data System (ADS)

Hovland, M.

2009-04-01

Hydrate pingoes were observed on the seafloor during two different remotely operated vehicle (ROV)-dives, conducted by Statoil at complex-pockmark G11, at Nyegga, off Mid-Norway. Confirmation that these structures actually represent hydrate ice-cored sediment mounds (pingoes), was done by other investigators (Ivanov et al., 2006). Because it is expected that hydrate pingoes represent relatively dynamic seafloor topographic structures and that their shape and size most probably will change over relatively short time, it is important to know how to recognise them visually. Hovland and Svensen (2006) highlighted five different characteristic aspects that define hydrate pingoes on the sea floor: 1) They are dome- or disc-shaped features, which may attain any size from ~0.5 m in height and upwards. Inside pockmark G11, they were up to 1 m high. 2) They are circular or oval in plan view and may attain lateral sizes on the seafloor ranging upwards from ~0.5 m. Inside G11 they had lengths of several metres and widths of up to 4 m. 3) They have dense communities of organisms growing on their surfaces. At G11, they were overgrown with small pogonophoran tube-worms. 4) They have patches of white or grey bacterial mats growing on their surface, indicating advection (seepage) of reduced pore-waters. 5) They have small pits and patches of fluidized sediments on their surface, indicating pit corrosion of the sub-surface gas hydrate. Because gas hydrates often form in high-porosity, near-surface sediments, where water is readily available, it is thought that they will build up at locations where gases are actively migrating upwards from depth. However, gas hydrates are not stable in the presence of ambient seawater, as seawater is deficient in guest molecule gases (normally methane). Therefore, they tend to build up below surface above conduits for gas flow from depth. But, the near-surface hydrate ice-lenses will continually be corroded by seawater circulating into the sediments

Individual Human Brain Areas Can Be Identified from Their Characteristic Spectral Activation Fingerprints

PubMed Central

Keitel, Anne; Gross, Joachim

2016-01-01

The human brain can be parcellated into diverse anatomical areas. We investigated whether rhythmic brain activity in these areas is characteristic and can be used for automatic classification. To this end, resting-state MEG data of 22 healthy adults was analysed. Power spectra of 1-s long data segments for atlas-defined brain areas were clustered into spectral profiles (“fingerprints”), using k-means and Gaussian mixture (GM) modelling. We demonstrate that individual areas can be identified from these spectral profiles with high accuracy. Our results suggest that each brain area engages in different spectral modes that are characteristic for individual areas. Clustering of brain areas according to similarity of spectral profiles reveals well-known brain networks. Furthermore, we demonstrate task-specific modulations of auditory spectral profiles during auditory processing. These findings have important implications for the classification of regional spectral activity and allow for novel approaches in neuroimaging and neurostimulation in health and disease. PMID:27355236

Individual Human Brain Areas Can Be Identified from Their Characteristic Spectral Activation Fingerprints.

PubMed

Keitel, Anne; Gross, Joachim

2016-06-01

The human brain can be parcellated into diverse anatomical areas. We investigated whether rhythmic brain activity in these areas is characteristic and can be used for automatic classification. To this end, resting-state MEG data of 22 healthy adults was analysed. Power spectra of 1-s long data segments for atlas-defined brain areas were clustered into spectral profiles ("fingerprints"), using k-means and Gaussian mixture (GM) modelling. We demonstrate that individual areas can be identified from these spectral profiles with high accuracy. Our results suggest that each brain area engages in different spectral modes that are characteristic for individual areas. Clustering of brain areas according to similarity of spectral profiles reveals well-known brain networks. Furthermore, we demonstrate task-specific modulations of auditory spectral profiles during auditory processing. These findings have important implications for the classification of regional spectral activity and allow for novel approaches in neuroimaging and neurostimulation in health and disease.

Veterans' voices: use of the American Customer Satisfaction Index (ACSI) Survey to identify My HealtheVet personal health record users' characteristics, needs, and preferences.

PubMed

Nazi, Kim M

2010-01-01

Consumer research reveals considerable interest in the use of Personal Health Records (PHRs), yet adoption remains relatively low. Both adopters and nonadopters represent important perspectives from which to understand this paradox. This study focuses on direct feedback from adopters obtained using the American Customer Satisfaction Index (ACSI) survey on the My HealtheVet PHR portal (http://www.myhealth.va.gov) of the Veterans Health Administration (VHA). The results represent a source of direct feedback with which to better understand veterans' needs and preferences. The ACSI Survey was implemented in October 2007 to measure satisfaction and elicit information about characteristics and preferences of My HealtheVet PHR adopters. The data represent a continuous random sample of site visitors who have navigated at least four pages on the site. A total of 100 617 surveys were completed (17.2%). Satisfaction with My HealtheVet is high (8.3/10.0), and users are highly likely to return to the site (8.6/10.0) and recommend the site to other veterans (9.1/10.0). The majority of system adopters are male (91%), between the ages of 51 and 70 (68%), and served in the Vietnam War (60%). Most veterans currently visit the site to utilize pharmacy-related features. VHA has used the ACSI to monitor satisfaction, and to better understand the characteristics, needs, and preferences of early adopters. The data provide an important source of direct feedback to inform program development. Future research will include monitoring the impact of enhancements and new features on satisfaction, and conducting additional research with nonadopters to identify barriers to adoption and use.

Veterans' voices: use of the American Customer Satisfaction Index (ACSI) Survey to identify My HealtheVet personal health record users' characteristics, needs, and preferences

PubMed Central

2010-01-01

Background Consumer research reveals considerable interest in the use of Personal Health Records (PHRs), yet adoption remains relatively low. Both adopters and nonadopters represent important perspectives from which to understand this paradox. Objective This study focuses on direct feedback from adopters obtained using the American Customer Satisfaction Index (ACSI) survey on the My HealtheVet PHR portal (http://www.myhealth.va.gov) of the Veterans Health Administration (VHA). The results represent a source of direct feedback with which to better understand veterans' needs and preferences. Methods The ACSI Survey was implemented in October 2007 to measure satisfaction and elicit information about characteristics and preferences of My HealtheVet PHR adopters. The data represent a continuous random sample of site visitors who have navigated at least four pages on the site. A total of 100 617 surveys were completed (17.2%). Results Satisfaction with My HealtheVet is high (8.3/10.0), and users are highly likely to return to the site (8.6/10.0) and recommend the site to other veterans (9.1/10.0). The majority of system adopters are male (91%), between the ages of 51 and 70 (68%), and served in the Vietnam War (60%). Most veterans currently visit the site to utilize pharmacy-related features. Conclusion VHA has used the ACSI to monitor satisfaction, and to better understand the characteristics, needs, and preferences of early adopters. The data provide an important source of direct feedback to inform program development. Future research will include monitoring the impact of enhancements and new features on satisfaction, and conducting additional research with nonadopters to identify barriers to adoption and use. PMID:20190065

Intracranial suprasellar angiolipoma: ultrastructural and immunohistochemical features.

PubMed

Lach, B; Lesiuk, H

1994-01-01

The authors present ultrastructural and immunohistochemical characteristics of an intracranial suprasellar tumor displaying features of cavernous angioma with islets of adipose tissue. Electron microscopy revealed thin-walled vessels separated by a loose collagenous stroma containing nests of mature adipocytes as well as fibroblasts, myofibroblasts, mast cells, and a few macrophages. Intracytoplasmic lipid droplets were also identified in scattered pericytes and smooth muscle cells of vascular walls and in the transitional cells resembling smooth muscle cells and adipocytes. Many adipose tissue cells were positive for S-100 protein with polyclonal antibodies. Other lipidized tumor cells were immunoreactive for some or all of the following: smooth muscle-specific actin, factor XIIIa, vimentin, and, occasionally, for desmin. Ultrastructure and immunohistochemistry indicate that in addition to typical adipocytes, lipidized cells of another nature contribute to the characteristic appearance of the adipose tissue component of angiolipoma.

Features of Coping with Disease in Iranian Multiple Sclerosis Patients: a Qualitative Study.

PubMed

Dehghani, Ali; Dehghan Nayeri, Nahid; Ebadi, Abbas

2018-03-01

Introduction: Coping with disease is of the main components improving the quality of life in multiple sclerosis patients. Identifying the characteristics of this concept is based on the experiences of patients. Using qualitative research is essential to improve the quality of life. This study was conducted to explore the features of coping with the disease in patients with multiple sclerosis. Method: In this conventional content analysis study, eleven multiple sclerosis patients from Iran MS Society in Tehran (Iran) participated. Purposive sampling was used to select participants. Data were gathered using semi structured interviews. To analyze data, a conventional content analysis approach was used to identify meaning units and to make codes and categories. Results: Results showed that features of coping with disease in multiple sclerosis patients consists of (a) accepting the current situation, (b) maintenance and development of human interactions, (c) self-regulation and (d) self-efficacy. Each of these categories is composed of sub-categories and codes that showed the perception and experience of patients about the coping with disease. Conclusion: Accordingly, a unique set of features regarding features of coping with the disease were identified among the patients with multiple sclerosis. Therefore, working to ensure the emergence of, and subsequent reinforcement of these features in MS patients can be an important step in improving the adjustment and quality of their lives.

Identifying clinical features in primary care electronic health record studies: methods for codelist development.

PubMed

Watson, Jessica; Nicholson, Brian D; Hamilton, Willie; Price, Sarah

2017-11-22

Analysis of routinely collected electronic health record (EHR) data from primary care is reliant on the creation of codelists to define clinical features of interest. To improve scientific rigour, transparency and replicability, we describe and demonstrate a standardised reproducible methodology for clinical codelist development. We describe a three-stage process for developing clinical codelists. First, the clear definition a priori of the clinical feature of interest using reliable clinical resources. Second, development of a list of potential codes using statistical software to comprehensively search all available codes. Third, a modified Delphi process to reach consensus between primary care practitioners on the most relevant codes, including the generation of an 'uncertainty' variable to allow sensitivity analysis. These methods are illustrated by developing a codelist for shortness of breath in a primary care EHR sample, including modifiable syntax for commonly used statistical software. The codelist was used to estimate the frequency of shortness of breath in a cohort of 28 216 patients aged over 18 years who received an incident diagnosis of lung cancer between 1 January 2000 and 30 November 2016 in the Clinical Practice Research Datalink (CPRD). Of 78 candidate codes, 29 were excluded as inappropriate. Complete agreement was reached for 44 (90%) of the remaining codes, with partial disagreement over 5 (10%). 13 091 episodes of shortness of breath were identified in the cohort of 28 216 patients. Sensitivity analysis demonstrates that codes with the greatest uncertainty tend to be rarely used in clinical practice. Although initially time consuming, using a rigorous and reproducible method for codelist generation 'future-proofs' findings and an auditable, modifiable syntax for codelist generation enables sharing and replication of EHR studies. Published codelists should be badged by quality and report the methods of codelist generation including

Characteristics Identified for Success by Restorative Dental Science Department Chairpersons.

PubMed

Wee, Alvin G; Weiss, Robert O; Wichman, Christopher S; Sukotjo, Cortino; Brundo, Gerald C

2016-03-01

The primary aim of this study was to determine the characteristics that current chairpersons in restorative dentistry, general dentistry, prosthodontics, and operative dentistry departments in U.S. dental schools feel are most relevant in contributing to their success. The secondary aim was to determine these individuals' rankings of the importance of a listed set of characteristics for them to be successful in their position. All 82 current chairs of the specified departments were invited to respond to an electronic survey. The survey first asked respondents to list the five most essential characteristics to serve as chair of a department and to rank those characteristics based on importance. Participants were next given a list of ten characteristics in the categories of management and leadership and, without being aware of the category of each individual item, asked to rank them in terms of importance for their success. A total of 39 chairpersons completed the survey (47.6% response rate; 83.3% male and 16.2% female). In section one, the respondents reported that leadership, vision, work ethic, integrity, communication, and organization were the most essential characteristics for their success. In section two, the respondents ranked the leadership characteristics as statistically more important than the management characteristics (p<0.0001) for being successful in their positions.

On the identifiability of inertia parameters of planar Multi-Body Space Systems

NASA Astrophysics Data System (ADS)

Nabavi-Chashmi, Seyed Yaser; Malaek, Seyed Mohammad-Bagher

2018-04-01

This work describes a new formulation to study the identifiability characteristics of Serially Linked Multi-body Space Systems (SLMBSS). The process exploits the so called "Lagrange Formulation" to develop a linear form of Equations of Motion w.r.t the system Inertia Parameters (IPs). Having developed a specific form of regressor matrix, we aim to expedite the identification process. The new approach allows analytical as well as numerical identification and identifiability analysis for different SLMBSSs' configurations. Moreover, the explicit forms of SLMBSSs identifiable parameters are derived by analyzing the identifiability characteristics of the robot. We further show that any SLMBSS designed with Variable Configurations Joint allows all IPs to be identifiable through comparing two successive identification outcomes. This feature paves the way to design new class of SLMBSS for which accurate identification of all IPs is at hand. Different case studies reveal that proposed formulation provides fast and accurate results, as required by the space applications. Further studies might be necessary for cases where planar-body assumption becomes inaccurate.

Bisphosphonate-related osteonecrosis of the jaw in a multiple myeloma patient: A case report with characteristic radiographic features.

PubMed

Lee, Byung-Do; Park, Moo-Rim; Kwon, Kyung-Hwan

2015-09-01

A 59-year-old male who had suffered from multiple myeloma for nine years and had been administered bisphosphonates for seven years visited a dental hospital for pain relief due to extensive caries in his left maxillary molars. The molars were extracted, leaving an exposed wound for three months. The radiograph showed sequestra formation and irregular bone destruction in the left maxilla. Sudden pain and gingival swelling in the right mandibular molar area occurred six months later. The interseptum of the right lower second molar was observed to be necrotic during surgery. These findings coincided with the features of bisphosphonate-related osteonecrosis of the jaw (BRONJ). In this case, the long intravenous administration of bisphosphonates and tooth extraction were likely the etiologic factors of BRONJ in a patient with multiple myeloma; moreover, the bilateral occurrence of BRONJ is a characteristic feature.

[Influence of human personal features on acoustic correlates of speech emotional intonation characteristics].

PubMed

Dmitrieva, E S; Gel'man, V Ia; Zaĭtseva, K A; Orlov, A M

2009-01-01

Comparative study of acoustic correlates of emotional intonation was conducted on two types of speech material: sensible speech utterances and short meaningless words. The corpus of speech signals of different emotional intonations (happy, angry, frightened, sad and neutral) was created using the actor's method of simulation of emotions. Native Russian 20-70-year-old speakers (both professional actors and non-actors) participated in the study. In the corpus, the following characteristics were analyzed: mean values and standard deviations of the power, fundamental frequency, frequencies of the first and second formants, and utterance duration. Comparison of each emotional intonation with "neutral" utterances showed the greatest deviations of the fundamental frequency and frequencies of the first formant. The direction of these deviations was independent of the semantic content of speech utterance and its duration, age, gender, and being actor or non-actor, though the personal features of the speakers affected the absolute values of these frequencies.

Gastric adenocarcinoma in common variable immunodeficiency: features of cancer and associated gastritis may be characteristic of the condition.

PubMed

De Petris, Giovanni; Dhungel, Bal M; Chen, Longwen; Chang, Yu-Hui H

2014-10-01

Common variable immunodeficiency (CVID) is associated with an increased risk of gastric cancer. The aim of the study was to determine the morphological features of CVID-associated gastric adenocarcinoma (CAGA) and of the background gastritis. The population of gastric cancer patients with CVID of Mayo Clinic in the period 2000-2010 was studied; 6 cases of CVID (2 males, 4 females, average age 47 years, age range 26-71 years) were found in 5793 patients with gastric cancer in the study period. Each patient underwent gastric resection for which histology slides were reviewed. Chronic gastritis variables, CVID-related findings, and features of the adenocarcinoma were recorded. CAGA was of intestinal type, with high number of intratumoral lymphocytes (ITLs). Cancer was diagnosed in younger patients than in the overall population of gastric cancer. Severe atrophic metaplastic pangastritis with extensive dysplasia was present in the background in 4 cases, with features of lymphocytic gastritis in 2 cases. Features of CVID (plasma cells paucity in 4 of 6 cases, lymphoid nodules prominent in four cases) could be detected. In summary, gastric adenocarcinoma at young age with ITLs, accompanied by atrophic metaplastic pangastritis, should alert the pathologist of the possibility of CAGA. It follows that, in presence of those characteristics, the search of CVID-associated abnormalities should be undertaken in the nonneoplastic tissues. © The Author(s) 2014.

Investigation of kinematic features for dismount detection and tracking

NASA Astrophysics Data System (ADS)

Narayanaswami, Ranga; Tyurina, Anastasia; Diel, David; Mehra, Raman K.; Chinn, Janice M.

2012-05-01

With recent changes in threats and methods of warfighting and the use of unmanned aircrafts, ISR (Intelligence, Surveillance and Reconnaissance) activities have become critical to the military's efforts to maintain situational awareness and neutralize the enemy's activities. The identification and tracking of dismounts from surveillance video is an important step in this direction. Our approach combines advanced ultra fast registration techniques to identify moving objects with a classification algorithm based on both static and kinematic features of the objects. Our objective was to push the acceptable resolution beyond the capability of industry standard feature extraction methods such as SIFT (Scale Invariant Feature Transform) based features and inspired by it, SURF (Speeded-Up Robust Feature). Both of these methods utilize single frame images. We exploited the temporal component of the video signal to develop kinematic features. Of particular interest were the easily distinguishable frequencies characteristic of bipedal human versus quadrupedal animal motion. We examine limits of performance, frame rates and resolution required for human, animal and vehicles discrimination. A few seconds of video signal with the acceptable frame rate allow us to lower resolution requirements for individual frames as much as by a factor of five, which translates into the corresponding increase of the acceptable standoff distance between the sensor and the object of interest.

Clinical characteristics and outcomes of septic bursitis.

PubMed

Lieber, Sarah B; Fowler, Mary Louise; Zhu, Clara; Moore, Andrew; Shmerling, Robert H; Paz, Ziv

2017-12-01

Limited data guide practice in evaluation and treatment of septic bursitis. We aimed to characterize clinical characteristics, microbiology, and outcomes of patients with septic bursitis stratified by bursal involvement, presence of trauma, and management type. We conducted a retrospective cohort study of adult patients admitted to a single center from 1998 to 2015 with culture-proven olecranon and patellar septic bursitis. Baseline characteristics, clinical features, microbial profiles, operative interventions, hospitalization lengths, and 60-day readmission rates were determined. Patients were stratified by bursitis site, presence or absence of trauma, and operative or non-operative management. Of 44 cases of septic bursitis, patients with olecranon and patellar bursitis were similar with respect to age, male predominance, and frequency of bursal trauma; patients managed operatively were younger (p = 0.05). Clinical features at presentation and comorbidities were similar despite bursitis site, history of trauma, or management. The most common organism isolated from bursal fluid was Staphylococcus aureus. Patients managed operatively were discharged to rehabilitation less frequently (p = 0.04). This study of septic bursitis is among the largest reported. We were unable to identify presenting clinical features that differentiated patients treated surgically from those treated conservatively. There was no clear relationship between preceding trauma or bursitis site and clinical course, management, or outcomes. Patients with bursitis treated surgically were younger. Additional study is needed to identify patients who would benefit from early surgical intervention for septic bursitis.

Glycine receptor antibodies in PERM and related syndromes: characteristics, clinical features and outcomes

PubMed Central

Carvajal-González, Alexander; Leite, M. Isabel; Waters, Patrick; Woodhall, Mark; Coutinho, Ester; Balint, Bettina; Lang, Bethan; Pettingill, Philippa; Carr, Aisling; Sheerin, Una-Marie; Press, Raomand; Lunn, Michael P.; Lim, Ming; Maddison, Paul; Meinck, H.-M.; Vandenberghe, Wim

2014-01-01

The clinical associations of glycine receptor antibodies have not yet been described fully. We identified prospectively 52 antibody-positive patients and collated their clinical features, investigations and immunotherapy responses. Serum glycine receptor antibody endpoint titres ranged from 1:20 to 1:60 000. In 11 paired samples, serum levels were higher than (n = 10) or equal to (n = 1) cerebrospinal fluid levels; there was intrathecal synthesis of glycine receptor antibodies in each of the six pairs available for detailed study. Four patients also had high glutamic acid decarboxylase antibodies (>1000 U/ml), and one had high voltage-gated potassium channel-complex antibody (2442 pM). Seven patients with very low titres (<1:50) and unknown or alternative diagnoses were excluded from further study. Three of the remaining 45 patients had newly-identified thymomas and one had a lymphoma. Thirty-three patients were classified as progressive encephalomyelitis with rigidity and myoclonus, and two as stiff person syndrome; five had a limbic encephalitis or epileptic encephalopathy, two had brainstem features mainly, two had demyelinating optic neuropathies and one had an unclear diagnosis. Four patients (9%) died during the acute disease, but most showed marked improvement with immunotherapies. At most recent follow-up, (2–7 years, median 3 years, since first antibody detection), the median modified Rankin scale scores (excluding the four deaths) decreased from 5 at maximal severity to 1 (P < 0.0001), but relapses have occurred in five patients and a proportion are on reducing steroids or other maintenance immunotherapies as well as symptomatic treatments. The glycine receptor antibodies activated complement on glycine receptor-transfected human embryonic kidney cells at room temperature, and caused internalization and lysosomal degradation of the glycine receptors at 37°C. Immunoglobulin G antibodies bound to rodent spinal cord and brainstem co-localizing with

A diagnosis model for early Tourette syndrome children based on brain structural network characteristics

NASA Astrophysics Data System (ADS)

Wen, Hongwei; Liu, Yue; Wang, Jieqiong; Zhang, Jishui; Peng, Yun; He, Huiguang

2016-03-01

Tourette syndrome (TS) is a childhood-onset neurobehavioral disorder characterized by the presence of multiple motor and vocal tics. Tic generation has been linked to disturbed networks of brain areas involved in planning, controlling and execution of action. The aim of our work is to select topological characteristics of structural network which were most efficient for estimating the classification models to identify early TS children. Here we employed the diffusion tensor imaging (DTI) and deterministic tractography to construct the structural networks of 44 TS children and 48 age and gender matched healthy children. We calculated four different connection matrices (fiber number, mean FA, averaged fiber length weighted and binary matrices) and then applied graph theoretical methods to extract the regional nodal characteristics of structural network. For each weighted or binary network, nodal degree, nodal efficiency and nodal betweenness were selected as features. Support Vector Machine Recursive Feature Extraction (SVM-RFE) algorithm was used to estimate the best feature subset for classification. The accuracy of 88.26% evaluated by a nested cross validation was achieved on combing best feature subset of each network characteristic. The identified discriminative brain nodes mostly located in the basal ganglia and frontal cortico-cortical networks involved in TS children which was associated with tic severity. Our study holds promise for early identification and predicting prognosis of TS children.

Clinical features that identify children with primary immunodeficiency diseases.

PubMed

Subbarayan, Anbezhil; Colarusso, Gloria; Hughes, Stephen M; Gennery, Andrew R; Slatter, Mary; Cant, Andrew J; Arkwright, Peter D

2011-05-01

The 10 warning signs of primary immunodeficiency diseases (PID) have been promoted by various organizations in Europe and the United States to predict PID. However, the ability of these warning signs to identify children with PID has not been rigorously tested. The main goal of this study was to determine the effectiveness of these 10 warning signs in predicting defined PID among children who presented to 2 tertiary pediatric immunodeficiency centers in the north of England. A retrospective survey of 563 children who presented to 2 pediatric immunodeficiency centers was undertaken. The clinical records of 430 patients with a defined PID and 133 patients for whom detailed investigations failed to establish a specific PID were reviewed. Overall, 96% of the children with PID were referred by hospital clinicians. The strongest identifiers of PID were a family history of immunodeficiency disease in addition to use of intravenous antibiotics for sepsis in children with neutrophil PID and failure to thrive in children with T-lymphocyte PID. With these 3 signs, 96% of patients with neutrophil and complement deficiencies and 89% of children with T-lymphocyte immunodeficiencies could be identified correctly. Family history was the only warning sign that identified children with B-lymphocyte PID. PID awareness initiatives should be targeted at hospital pediatricians and families with a history of PID rather than the general public. Our results provide the general pediatrician with a simple refinement of 10 warning signs for identifying children with underlying immunodeficiency diseases.

Identifying Structural Flow Defects in Disordered Solids Using Machine-Learning Methods

NASA Astrophysics Data System (ADS)

Cubuk, E. D.; Schoenholz, S. S.; Rieser, J. M.; Malone, B. D.; Rottler, J.; Durian, D. J.; Kaxiras, E.; Liu, A. J.

2015-03-01

We use machine-learning methods on local structure to identify flow defects—or particles susceptible to rearrangement—in jammed and glassy systems. We apply this method successfully to two very different systems: a two-dimensional experimental realization of a granular pillar under compression and a Lennard-Jones glass in both two and three dimensions above and below its glass transition temperature. We also identify characteristics of flow defects that differentiate them from the rest of the sample. Our results show it is possible to discern subtle structural features responsible for heterogeneous dynamics observed across a broad range of disordered materials.

Microscopic histological characteristics of soft tissue sarcomas: analysis of tissue features and electrical resistance.

PubMed

Tosi, A L; Campana, L G; Dughiero, F; Forzan, M; Rastrelli, M; Sieni, E; Rossi, C R

2017-07-01

Tissue electrical conductivity is correlated with tissue characteristics. In this work, some soft tissue sarcomas (STS) excised from patients have been evaluated in terms of histological characteristics (cell size and density) and electrical resistance. The electrical resistance has been measured using the ex vivo study on soft tissue tumors electrical characteristics (ESTTE) protocol proposed by the authors in order to study electrical resistance of surgical samples excised by patients in a fixed measurement setup. The measurement setup includes a voltage pulse generator (700 V, 100 µs long at 5 kHz, period 200 µs) and an electrode with 7 needles, 20 mm-long, with the same distance arranged in a fixed hexagonal geometry. In the ESTTE protocol, the same voltage pulse sequence is applied to each different tumor mass and the corresponding resistance has been evaluated from voltage and current recorded by the equipment. For each tumor mass, a histological sample of the volume treated by means of voltage pulses has been taken for histological analysis. Each mass has been studied in order to identify the sarcoma type. For each histological sample, an image at 20× or 40× of magnification was acquired. In this work, the electrical resistance measured for each tumor has been correlated with tissue characteristics like the type, size and density of cells. This work presents a preliminary study to explore possible correlations between tissue characteristics and electrical resistance of STS. These results can be helpful to adjust the pulse voltage intensity in order to improve the electrochemotherapy efficacy on some histotype of STS.

A general purpose feature extractor for light detection and ranging data.

PubMed

Li, Yangming; Olson, Edwin B

2010-01-01

Feature extraction is a central step of processing Light Detection and Ranging (LIDAR) data. Existing detectors tend to exploit characteristics of specific environments: corners and lines from indoor (rectilinear) environments, and trees from outdoor environments. While these detectors work well in their intended environments, their performance in different environments can be poor. We describe a general purpose feature detector for both 2D and 3D LIDAR data that is applicable to virtually any environment. Our method adapts classic feature detection methods from the image processing literature, specifically the multi-scale Kanade-Tomasi corner detector. The resulting method is capable of identifying highly stable and repeatable features at a variety of spatial scales without knowledge of environment, and produces principled uncertainty estimates and corner descriptors at same time. We present results on both software simulation and standard datasets, including the 2D Victoria Park and Intel Research Center datasets, and the 3D MIT DARPA Urban Challenge dataset.

A General Purpose Feature Extractor for Light Detection and Ranging Data

PubMed Central

Li, Yangming; Olson, Edwin B.

2010-01-01

Feature extraction is a central step of processing Light Detection and Ranging (LIDAR) data. Existing detectors tend to exploit characteristics of specific environments: corners and lines from indoor (rectilinear) environments, and trees from outdoor environments. While these detectors work well in their intended environments, their performance in different environments can be poor. We describe a general purpose feature detector for both 2D and 3D LIDAR data that is applicable to virtually any environment. Our method adapts classic feature detection methods from the image processing literature, specifically the multi-scale Kanade-Tomasi corner detector. The resulting method is capable of identifying highly stable and repeatable features at a variety of spatial scales without knowledge of environment, and produces principled uncertainty estimates and corner descriptors at same time. We present results on both software simulation and standard datasets, including the 2D Victoria Park and Intel Research Center datasets, and the 3D MIT DARPA Urban Challenge dataset. PMID:22163474

Shifting the Focus to Student Learning: Characteristics of Effective Teaching Practice as Identified by Experienced Pre-Service Faculty Advisors

ERIC Educational Resources Information Center

Maynes, Nancy; Hatt, Blaine E.

2012-01-01

Cochrane-Smith and Power identify trends in teacher education programs with some relating to heightened teacher accountability for students' learning. In this paper we provide a model that identifies characteristics believed to be critical elements related to a teacher's conceptual focus shifting from an emphasis on their teaching to their…

A multi-approach feature extractions for iris recognition

NASA Astrophysics Data System (ADS)

Sanpachai, H.; Settapong, M.

2014-04-01

Biometrics is a promising technique that is used to identify individual traits and characteristics. Iris recognition is one of the most reliable biometric methods. As iris texture and color is fully developed within a year of birth, it remains unchanged throughout a person's life. Contrary to fingerprint, which can be altered due to several aspects including accidental damage, dry or oily skin and dust. Although iris recognition has been studied for more than a decade, there are limited commercial products available due to its arduous requirement such as camera resolution, hardware size, expensive equipment and computational complexity. However, at the present time, technology has overcome these obstacles. Iris recognition can be done through several sequential steps which include pre-processing, features extractions, post-processing, and matching stage. In this paper, we adopted the directional high-low pass filter for feature extraction. A box-counting fractal dimension and Iris code have been proposed as feature representations. Our approach has been tested on CASIA Iris Image database and the results are considered successful.

An Automatic Gait Feature Extraction Method for Identifying Gait Asymmetry Using Wearable Sensors

PubMed Central

Vassallo, Michael

2018-01-01

This paper aims to assess the use of Inertial Measurement Unit (IMU) sensors to identify gait asymmetry by extracting automatic gait features. We design and develop an android app to collect real time synchronous IMU data from legs. The results from our method are validated using a Qualisys Motion Capture System. The data are collected from 10 young and 10 older subjects. Each performed a trial in a straight corridor comprising 15 strides of normal walking, a turn around and another 15 strides. We analyse the data for total distance, total time, total velocity, stride, step, cadence, step ratio, stance, and swing. The accuracy of detecting the stride number using the proposed method is 100% for young and 92.67% for older subjects. The accuracy of estimating travelled distance using the proposed method for young subjects is 97.73% and 98.82% for right and left legs; and for the older, is 88.71% and 89.88% for right and left legs. The average travelled distance is 37.77 (95% CI ± 3.57) meters for young subjects and is 22.50 (95% CI ± 2.34) meters for older subjects. The average travelled time for young subjects is 51.85 (95% CI ± 3.08) seconds and for older subjects is 84.02 (95% CI ± 9.98) seconds. The results show that wearable sensors can be used for identifying gait asymmetry without the requirement and expense of an elaborate laboratory setup. This can serve as a tool in diagnosing gait abnormalities in individuals and opens the possibilities for home based self-gait asymmetry assessment. PMID:29495299

Modeling resident error-making patterns in detection of mammographic masses using computer-extracted image features: preliminary experiments

NASA Astrophysics Data System (ADS)

Mazurowski, Maciej A.; Zhang, Jing; Lo, Joseph Y.; Kuzmiak, Cherie M.; Ghate, Sujata V.; Yoon, Sora

2014-03-01

Providing high quality mammography education to radiology trainees is essential, as good interpretation skills potentially ensure the highest benefit of screening mammography for patients. We have previously proposed a computer-aided education system that utilizes trainee models, which relate human-assessed image characteristics to interpretation error. We proposed that these models be used to identify the most difficult and therefore the most educationally useful cases for each trainee. In this study, as a next step in our research, we propose to build trainee models that utilize features that are automatically extracted from images using computer vision algorithms. To predict error, we used a logistic regression which accepts imaging features as input and returns error as output. Reader data from 3 experts and 3 trainees were used. Receiver operating characteristic analysis was applied to evaluate the proposed trainee models. Our experiments showed that, for three trainees, our models were able to predict error better than chance. This is an important step in the development of adaptive computer-aided education systems since computer-extracted features will allow for faster and more extensive search of imaging databases in order to identify the most educationally beneficial cases.

A Search Engine Features Comparison.

ERIC Educational Resources Information Center

Vorndran, Gerald

Until recently, the World Wide Web (WWW) public access search engines have not included many of the advanced commands, options, and features commonly available with the for-profit online database user interfaces, such as DIALOG. This study evaluates the features and characteristics common to both types of search interfaces, examines the Web search…

Colorectal cancer patient-derived xenografted tumors maintain characteristic features of the original tumors.

PubMed

Cho, Yong Beom; Hong, Hye Kyung; Choi, Yoon-La; Oh, Ensel; Joo, Kyeung Min; Jin, Juyoun; Nam, Do-Hyun; Ko, Young-Hyeh; Lee, Woo Yong

2014-04-01

Despite significant improvements in colon cancer outcomes over the past few decades, preclinical development of more effective therapeutic strategies is still limited by the availability of clinically relevant animal models. To meet those clinical unmet needs, we generated a well-characterized in vivo preclinical platform for colorectal cancer using fresh surgical samples. Primary and metastatic colorectal tumor tissues (1-2 mm(3)) that originate from surgery were implanted into the subcutaneous space of nude mice and serially passaged in vivo. Mutation status, hematoxylin and eosin staining, short tandem repeat profiling, and array comparative genomic hybridization were used to validate the similarity of molecular characteristics between the patient tumors and tumors obtained from xenografts. From surgical specimens of 143 patients, 97 xenograft models were obtained in immunodeficient mice (establish rate = 67%). Thirty-nine xenograft models were serially expanded further in mice with a mean time to reach a size of 1000-1500 mm(3) of 90 ± 20 d. Histologic and immunohistochemical analyses revealed a high degree of pathologic similarity including histologic architecture and expression of CEA, CK7, and CD20 between the patient and xenograft tumors. Molecular analysis showed that genetic mutations, genomic alterations, and gene expression patterns of each patient tumor were also well conserved in the corresponding xenograft tumor. Xenograft animal models derived from fresh surgical sample maintained the key characteristic features of the original tumors, suggesting that this in vivo platform can be useful for preclinical development of novel therapeutic approaches to colorectal cancers. Copyright © 2014 Elsevier Inc. All rights reserved.

Identifying Epigenetic Biomarkers using Maximal Relevance and Minimal Redundancy Based Feature Selection for Multi-Omics Data.

PubMed

Mallik, Saurav; Bhadra, Tapas; Maulik, Ujjwal

2017-01-01

Epigenetic Biomarker discovery is an important task in bioinformatics. In this article, we develop a new framework of identifying statistically significant epigenetic biomarkers using maximal-relevance and minimal-redundancy criterion based feature (gene) selection for multi-omics dataset. Firstly, we determine the genes that have both expression as well as methylation values, and follow normal distribution. Similarly, we identify the genes which consist of both expression and methylation values, but do not follow normal distribution. For each case, we utilize a gene-selection method that provides maximal-relevant, but variable-weighted minimum-redundant genes as top ranked genes. For statistical validation, we apply t-test on both the expression and methylation data consisting of only the normally distributed top ranked genes to determine how many of them are both differentially expressed andmethylated. Similarly, we utilize Limma package for performing non-parametric Empirical Bayes test on both expression and methylation data comprising only the non-normally distributed top ranked genes to identify how many of them are both differentially expressed and methylated. We finally report the top-ranking significant gene-markerswith biological validation. Moreover, our framework improves positive predictive rate and reduces false positive rate in marker identification. In addition, we provide a comparative analysis of our gene-selection method as well as othermethods based on classificationperformances obtained using several well-known classifiers.

In Search of Commonalities: Some Linguistic and Rhetorical Features of Business Reports as a Genre

ERIC Educational Resources Information Center

Yeung, Lorrita

2007-01-01

The present study analyzes 22 authentic business reports in an attempt to identify textual features that are typical of business reports as a genre. The analysis shows that there are certain characteristics which distinguish business reports from other related genres such as scientific reports, of which RAs are a typical example. There are also…

Morphological features of IFN-γ–stimulated mesenchymal stromal cells predict overall immunosuppressive capacity

PubMed Central

Klinker, Matthew W.; Marklein, Ross A.; Lo Surdo, Jessica L.; Wei, Cheng-Hong

2017-01-01

Human mesenchymal stromal cell (MSC) lines can vary significantly in their functional characteristics, and the effectiveness of MSC-based therapeutics may be realized by finding predictive features associated with MSC function. To identify features associated with immunosuppressive capacity in MSCs, we developed a robust in vitro assay that uses principal-component analysis to integrate multidimensional flow cytometry data into a single measurement of MSC-mediated inhibition of T-cell activation. We used this assay to correlate single-cell morphological data with overall immunosuppressive capacity in a cohort of MSC lines derived from different donors and manufacturing conditions. MSC morphology after IFN-γ stimulation significantly correlated with immunosuppressive capacity and accurately predicted the immunosuppressive capacity of MSC lines in a validation cohort. IFN-γ enhanced the immunosuppressive capacity of all MSC lines, and morphology predicted the magnitude of IFN-γ–enhanced immunosuppressive activity. Together, these data identify MSC morphology as a predictive feature of MSC immunosuppressive function. PMID:28283659

Identifying the characteristic of SundaParahiyangan landscape for a model of sustainable agricultural landscape

NASA Astrophysics Data System (ADS)

Dahlan, M. Z.; Nurhayati, H. S. A.; Mugnisjah, W. Q.

2017-10-01

This study was an explorative study of the various forms of traditional ecological knowledge (TEK) of Sundanese people in the context of sustainable agriculture. The qualitative method was used to identify SundaParahiyangan landscape by using Rapid Participatory Rural Appraisal throughsemi-structured interviews, focus group discussions, and field survey. The Landscape Characteristic Assessment and Community Sustainability Assessment were used to analyze the characteristic of landscape to achieve the sustainable agricultural landscape criteria proposed by US Department of Agriculture. The results revealed that the SundaParahiyangan agricultural landscape has a unique characteristic as a result of the long-term adaptation of agricultural society to theirlandscape through a learning process for generations. In general, this character was reflected in the typical of Sundanese’s agroecosystems such as forest garden, mixed garden, paddy field, and home garden. In addition, concept of kabuyutan is one of the TEKs related to understanding and utilization of landscape has been adapted on revitalizing the role of landscape surrounding the agroecosystem as the buffer zone by calculating and designating protected areas. To support the sustainability of production area, integrated practices of agroforestry with low-external-input and sustainable agriculture (LEISA) system can be applied in utilizing and managing agricultural resources.

Characteristic clinical features of Aspergillus appendicitis: Case report and literature review.

PubMed

Gjeorgjievski, Mihajlo; Amin, Mitual B; Cappell, Mitchell S

2015-11-28

This work aims to facilitate diagnosing Aspergillus appendicitis, which can be missed clinically due to its rarity, by proposing a clinical pentad for Aspergillus appendicitis based on literature review and one new case. The currently reported case of pathologically-proven Aspergillus appendicitis was identified by computerized search of pathology database at William Beaumont Hospital, 1999-2014. Prior cases were identified by computerized literature search. Among 10980 pathology reports of pathologically-proven appendicitis, one case of Aspergillus appendicitis was identified (rate = 0.01%). A young boy with profound neutropenia, recent chemotherapy, and acute myelogenous leukemia presented with right lower quadrant pain, pyrexia, and generalized malaise. Abdominal computed tomography scan showed a thickened appendiceal wall and periappendiceal inflammation, suggesting appendicitis. Emergent laparotomy showed an inflamed, thickened appendix, which was resected. The patient did poorly postoperatively with low-grade-fevers while receiving antibacterial therapy, but rapidly improved after initiating amphotericin therapy. Microscopic examination of a silver stain of the appendectomy specimen revealed fungi with characteristic Aspergillus morphology, findings confirmed by immunohistochemistry. Primary Aspergillus appendicitis is exceptionally rare, with only 3 previously reported cases. All three cases presented with (1)-neutropenia, (2)-recent chemotherapy, (3)-acute leukemia, and (4)-suspected appendicitis; (5)-the two prior cases initially treated with antibacterial therapy, fared poorly before instituting anti-Aspergillus therapy. The current patient satisfied all these five criteria. Based on these four cases, a clinical pentad is proposed for Aspergillus appendicitis: clinically-suspected appendicitis, neutropenia, recent chemotherapy, acute leukemia, and poor clinical response if treated solely by antibacterial/anti-candidial therapy. Patients presenting with

The use of deconvolution techniques to identify the fundamental mixing characteristics of urban drainage structures.

PubMed

Stovin, V R; Guymer, I; Chappell, M J; Hattersley, J G

2010-01-01

Mixing and dispersion processes affect the timing and concentration of contaminants transported within urban drainage systems. Hence, methods of characterising the mixing effects of specific hydraulic structures are of interest to drainage network modellers. Previous research, focusing on surcharged manholes, utilised the first-order Advection-Dispersion Equation (ADE) and Aggregated Dead Zone (ADZ) models to characterise dispersion. However, although systematic variations in travel time as a function of discharge and surcharge depth have been identified, the first order ADE and ADZ models do not provide particularly good fits to observed manhole data, which means that the derived parameter values are not independent of the upstream temporal concentration profile. An alternative, more robust, approach utilises the system's Cumulative Residence Time Distribution (CRTD), and the solute transport characteristics of a surcharged manhole have been shown to be characterised by just two dimensionless CRTDs, one for pre- and the other for post-threshold surcharge depths. Although CRTDs corresponding to instantaneous upstream injections can easily be generated using Computational Fluid Dynamics (CFD) models, the identification of CRTD characteristics from non-instantaneous and noisy laboratory data sets has been hampered by practical difficulties. This paper shows how a deconvolution approach derived from systems theory may be applied to identify the CRTDs associated with urban drainage structures.

Feature genes predicting the FLT3/ITD mutation in acute myeloid leukemia

PubMed Central

LI, CHENGLONG; ZHU, BIAO; CHEN, JIAO; HUANG, XIAOBING

2016-01-01

In the present study, gene expression profiles of acute myeloid leukemia (AML) samples were analyzed to identify feature genes with the capacity to predict the mutation status of FLT3/ITD. Two machine learning models, namely the support vector machine (SVM) and random forest (RF) methods, were used for classification. Four datasets were downloaded from the European Bioinformatics Institute, two of which (containing 371 samples, including 281 FLT3/ITD mutation-negative and 90 mutation-positive samples) were randomly defined as the training group, while the other two datasets (containing 488 samples, including 350 FLT3/ITD mutation-negative and 138 mutation-positive samples) were defined as the test group. Differentially expressed genes (DEGs) were identified by significance analysis of the micro-array data by using the training samples. The classification efficiency of the SCM and RF methods was evaluated using the following parameters: Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and the area under the receiver operating characteristic curve. Functional enrichment analysis was performed for the feature genes with DAVID. A total of 585 DEGs were identified in the training group, of which 580 were upregulated and five were downregulated. The classification accuracy rates of the two methods for the training group, the test group and the combined group using the 585 feature genes were >90%. For the SVM and RF methods, the rates of correct determination, specificity and PPV were >90%, while the sensitivity and NPV were >80%. The SVM method produced a slightly better classification effect than the RF method. A total of 13 biological pathways were overrepresented by the feature genes, mainly involving energy metabolism, chromatin organization and translation. The feature genes identified in the present study may be used to predict the mutation status of FLT3/ITD in patients with AML. PMID:27177049

Feature genes predicting the FLT3/ITD mutation in acute myeloid leukemia.

PubMed

Li, Chenglong; Zhu, Biao; Chen, Jiao; Huang, Xiaobing

2016-07-01

In the present study, gene expression profiles of acute myeloid leukemia (AML) samples were analyzed to identify feature genes with the capacity to predict the mutation status of FLT3/ITD. Two machine learning models, namely the support vector machine (SVM) and random forest (RF) methods, were used for classification. Four datasets were downloaded from the European Bioinformatics Institute, two of which (containing 371 samples, including 281 FLT3/ITD mutation-negative and 90 mutation‑positive samples) were randomly defined as the training group, while the other two datasets (containing 488 samples, including 350 FLT3/ITD mutation-negative and 138 mutation-positive samples) were defined as the test group. Differentially expressed genes (DEGs) were identified by significance analysis of the microarray data by using the training samples. The classification efficiency of the SCM and RF methods was evaluated using the following parameters: Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and the area under the receiver operating characteristic curve. Functional enrichment analysis was performed for the feature genes with DAVID. A total of 585 DEGs were identified in the training group, of which 580 were upregulated and five were downregulated. The classification accuracy rates of the two methods for the training group, the test group and the combined group using the 585 feature genes were >90%. For the SVM and RF methods, the rates of correct determination, specificity and PPV were >90%, while the sensitivity and NPV were >80%. The SVM method produced a slightly better classification effect than the RF method. A total of 13 biological pathways were overrepresented by the feature genes, mainly involving energy metabolism, chromatin organization and translation. The feature genes identified in the present study may be used to predict the mutation status of FLT3/ITD in patients with AML.

Performance comparison of phenomenology-based features to generic features for false alarm reduction in UWB SAR imagery

NASA Astrophysics Data System (ADS)

Marble, Jay A.; Gorman, John D.

1999-08-01

A feature based approach is taken to reduce the occurrence of false alarms in foliage penetrating, ultra-wideband, synthetic aperture radar data. A set of 'generic' features is defined based on target size, shape, and pixel intensity. A second set of features is defined that contains generic features combined with features based on scattering phenomenology. Each set is combined using a quadratic polynomial discriminant (QPD), and performance is characterized by generating a receiver operating characteristic (ROC) curve. Results show that the feature set containing phenomenological features improves performance against both broadside and end-on targets. Performance against end-on targets, however, is especially pronounced.

Identifying play characteristics of pre-school children with developmental coordination disorder via parental questionnaires.

PubMed

Rosenblum, Sara; Waissman, Pola; Diamond, Gary W

2017-06-01

Motor coordination deficits that characterize children with Developmental Coordination Disorder (DCD) affect their quality of participation. The aim of the current study was to identify play characteristics of young children with DCD, compared to those of children with typical development in three dimensions: activity and participation, environmental factors and children's impairments. Sixty-four children, aged four to six years, participated. Thirty were diagnosed as having DCD; the remaining 34 children were age, gender and socioeconomic level matched controls with typical development. The children were evaluated by the M-ABC. In addition, their parents completed a demographic questionnaire, the Children's Activity Scale for Parents (CHAS-P), the Children's Leisure Assessment Scale for preschoolers (CLASS-Pre), and My Child's Play Questionnaire (MCP). Children with DCD performed significantly poorer in each of the four play activity and participation domains: variety, frequency, sociability, and preference (CLASS-Pre). Furthermore, their environmental characteristics were significantly different (MCP). They displayed significantly inferior performance (impairments) in interpersonal interaction and executive functioning during play, in comparison to controls (MCP). Moreover, the children's motor and executive control as reflected in their daily function as well as their activities of daily living (ADL) performance level, contributed to the prediction of their global play participation. The results indicate that the use of both the CLASS-Pre and the MCP questionnaires enables the identification of unique play characteristics of pre-school children with DCD via parents' reports. A better insight into these characteristics may contribute to theoretical knowledge and clinical practice to improve the children's daily participation. Copyright © 2016 Elsevier B.V. All rights reserved.

Hypothesis testing for differentially correlated features.

PubMed

Sheng, Elisa; Witten, Daniela; Zhou, Xiao-Hua

2016-10-01

In a multivariate setting, we consider the task of identifying features whose correlations with the other features differ across conditions. Such correlation shifts may occur independently of mean shifts, or differences in the means of the individual features across conditions. Previous approaches for detecting correlation shifts consider features simultaneously, by computing a correlation-based test statistic for each feature. However, since correlations involve two features, such approaches do not lend themselves to identifying which feature is the culprit. In this article, we instead consider a serial testing approach, by comparing columns of the sample correlation matrix across two conditions, and removing one feature at a time. Our method provides a novel perspective and favorable empirical results compared with competing approaches. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Analysis of Nearly One Thousand Mammalian Mirtrons Reveals Novel Features of Dicer Substrates

PubMed Central

Shenker, Sol; Mohammed, Jaaved; Lai, Eric C.

2015-01-01

Mirtrons are microRNA (miRNA) substrates that utilize the splicing machinery to bypass the necessity of Drosha cleavage for their biogenesis. Expanding our recent efforts for mammalian mirtron annotation, we use meta-analysis of aggregate datasets to identify ~500 novel mouse and human introns that confidently generate diced small RNA duplexes. These comprise nearly 1000 total loci distributed in four splicing-mediated biogenesis subclasses, with 5'-tailed mirtrons as, by far, the dominant subtype. Thus, mirtrons surprisingly comprise a substantial fraction of endogenous Dicer substrates in mammalian genomes. Although mirtron-derived small RNAs exhibit overall expression correlation with their host mRNAs, we observe a subset with substantial differences that suggest regulated processing or accumulation. We identify characteristic sequence, length, and structural features of mirtron loci that distinguish them from bulk introns, and find that mirtrons preferentially emerge from genes with larger numbers of introns. While mirtrons generate miRNA-class regulatory RNAs, we also find that mirtrons exhibit many features that distinguish them from canonical miRNAs. We observe that conventional mirtron hairpins are substantially longer than Drosha-generated pre-miRNAs, indicating that the characteristic length of canonical pre-miRNAs is not a general feature of Dicer substrate hairpins. In addition, mammalian mirtrons exhibit unique patterns of ordered 5' and 3' heterogeneity, which reveal hidden complexity in miRNA processing pathways. These include broad 3'-uridylation of mirtron hairpins, atypically heterogeneous 5' termini that may result from exonucleolytic processing, and occasionally robust decapitation of the 5' guanine (G) of mirtron-5p species defined by splicing. Altogether, this study reveals that this extensive class of non-canonical miRNA bears a multitude of characteristic properties, many of which raise general mechanistic questions regarding the processing

Featured Image: Identifying a Glowing Shell

NASA Astrophysics Data System (ADS)

Kohler, Susanna

2018-05-01

New nebulae are being discovered and classified every day and this false-color image reveals one of the more recent objects of interest. This nebula, IPHASX J210204.7+471015, was recently imaged by the Andalucia Faint Object Spectrograph and Camera mounted on the 2.5-m Nordic Optical Telescope in La Palma, Spain. J210204 was initially identified as a possible planetary nebula a remnant left behind at the end of a red giants lifetime. Based on the above imaging, however, a team of authors led by Martn Guerrero (Institute of Astrophysics of Andalusia, Spain) is arguing that this shell of glowing gas was instead expelled around a classical nova. In a classical nova eruption, a white dwarf and its binary companion come very close together, and mass transfers to form a thin atmosphere of hydrogen around the white dwarf. When this hydrogen suddenly ignites in runaway fusion, this outer atmosphere can be expelled, forming a short-lived nova remnant which is what Guerrero and collaborators think were seeing with J210204. If so, this nebula can reveal information about the novathat caused it. To find out more about what the authors learned from this nebula, check out the paper below.CitationMartn A. Guerrero et al 2018 ApJ 857 80. doi:10.3847/1538-4357/aab669

The extraction and use of facial features in low bit-rate visual communication.

PubMed

Pearson, D

1992-01-29

A review is given of experimental investigations by the author and his collaborators into methods of extracting binary features from images of the face and hands. The aim of the research has been to enable deaf people to communicate by sign language over the telephone network. Other applications include model-based image coding and facial-recognition systems. The paper deals with the theoretical postulates underlying the successful experimental extraction of facial features. The basic philosophy has been to treat the face as an illuminated three-dimensional object and to identify features from characteristics of their Gaussian maps. It can be shown that in general a composite image operator linked to a directional-illumination estimator is required to accomplish this, although the latter can often be omitted in practice.

What does the cryopreserved oocyte look like? A fresh look at the characteristic oocyte features following cryopreservation.

PubMed

Hosseini, Sayyed Morteza; Nasr-Esfahani, Mohammad Hossein

2016-04-01

In October 2012, the American Society for Reproductive Medicine (ASRM) and, in March 2012, the European Society of Human Reproduction and Embryology (ESHRE), lifted the categorization of oocyte cryopreservation as being "experimental" and endorsed its entrance into the mainstream of assisted reproductive techniques. This change in policy, with the considerable advantages that oocytes offer over embryos for cryopreservation, has increased applications of oocyte cryopreservation in assisted reproduction techniques. A deep understanding of oocyte cryobiology, however, is lagging behind the forces propelling the clinical application of oocyte cryopreservation. We have drawn attention to this shortcoming by initiating a debate on whether a vitrified-warmed oocyte has the same characteristics as its fresh sibling. The answer to this question may explain why the oocyte cryopreservation success rate is as yet far from satisfactory and why cryopreserved oocytes should be treated differently from their fresh siblings. A fresh look at the characteristic features of oocytes after cryopreservation is the main scope of this review as a stimulus to further improvement of oocyte cryopreservation. Copyright © 2016. Published by Elsevier Ltd.

In-depth investigations of adolescents and adults with holoprosencephaly identify unique characteristics.

PubMed

Weiss, Karin; Kruszka, Paul; Guillen Sacoto, Maria J; Addissie, Yonit A; Hadley, Donald W; Hadsall, Casey K; Stokes, Bethany; Hu, Ping; Roessler, Erich; Solomon, Beth; Wiggs, Edythe; Thurm, Audrey; Hufnagel, Robert B; Zein, Wadih M; Hahn, Jin S; Stashinko, Elaine; Levey, Eric; Baldwin, Debbie; Clegg, Nancy J; Delgado, Mauricio R; Muenke, Maximilian

2018-01-01

PurposeWith improved medical care, some individuals with holoprosencephaly (HPE) are surviving into adulthood. We investigated the clinical manifestations of adolescents and adults with HPE and explored the underlying molecular causes.MethodsParticipants included 20 subjects 15 years of age and older. Clinical assessments included dysmorphology exams, cognitive testing, swallowing studies, ophthalmic examination, and brain magnetic resonance imaging. Genetic testing included chromosomal microarray, Sanger sequencing for SHH, ZIC2, SIX3, and TGIF, and whole-exome sequencing (WES) of 10 trios.ResultsSemilobar HPE was the most common subtype of HPE, seen in 50% of the participants. Neurodevelopmental disabilities were found to correlate with HPE subtype. Factors associated with long-term survival included HPE subtype not alobar, female gender, and nontypical facial features. Four participants had de novo pathogenic variants in ZIC2. WES analysis of 11 participants did not reveal plausible candidate genes, suggesting complex inheritance in these cases. Indeed, in two probands there was a history of uncontrolled maternal type 1 diabetes.ConclusionIndividuals with various HPE subtypes can survive into adulthood and the neurodevelopmental outcomes are variable. Based on the facial characteristics and molecular evaluations, we suggest that classic genetic causes of HPE may play a smaller role in this cohort.

Identifying Chinese Microblog Users With High Suicide Probability Using Internet-Based Profile and Linguistic Features: Classification Model.

PubMed

Guan, Li; Hao, Bibo; Cheng, Qijin; Yip, Paul Sf; Zhu, Tingshao

2015-01-01

Traditional offline assessment of suicide probability is time consuming and difficult in convincing at-risk individuals to participate. Identifying individuals with high suicide probability through online social media has an advantage in its efficiency and potential to reach out to hidden individuals, yet little research has been focused on this specific field. The objective of this study was to apply two classification models, Simple Logistic Regression (SLR) and Random Forest (RF), to examine the feasibility and effectiveness of identifying high suicide possibility microblog users in China through profile and linguistic features extracted from Internet-based data. There were nine hundred and nine Chinese microblog users that completed an Internet survey, and those scoring one SD above the mean of the total Suicide Probability Scale (SPS) score, as well as one SD above the mean in each of the four subscale scores in the participant sample were labeled as high-risk individuals, respectively. Profile and linguistic features were fed into two machine learning algorithms (SLR and RF) to train the model that aims to identify high-risk individuals in general suicide probability and in its four dimensions. Models were trained and then tested by 5-fold cross validation; in which both training set and test set were generated under the stratified random sampling rule from the whole sample. There were three classic performance metrics (Precision, Recall, F1 measure) and a specifically defined metric "Screening Efficiency" that were adopted to evaluate model effectiveness. Classification performance was generally matched between SLR and RF. Given the best performance of the classification models, we were able to retrieve over 70% of the labeled high-risk individuals in overall suicide probability as well as in the four dimensions. Screening Efficiency of most models varied from 1/4 to 1/2. Precision of the models was generally below 30%. Individuals in China with high suicide

Physical characteristics and evolutionary trends of continental rifts

NASA Technical Reports Server (NTRS)

Ramberg, I. B.; Morgan, P.

1984-01-01

Rifts may be defined as zones beneath which the entire lithosphere has ruptured in extension. They are widespread and occur in a variety of tectonic settings, and range up to 2,600 m.y. in age. The object of this review is to highlight characteristic features of modern and ancient rifts, to emphasize differences and similarities in order to help characterize evolutionary trends, to identify physical conditions favorable for initiation as well as termination of rifting, and to provide constraints for future modeling studies of rifting. Rifts are characterized on the basis of their structural, geomorphic, magmatic and geophysical features and the diverse character of these features and their evolutionary trends through time are discussed. Mechanisms of rifting are critically examined in terms of the physical characteristics and evolutionary trends of rifts, and it is concluded that while simple models can give valuable insight into specific processes of rifting, individual rifts can rarely, if ever, be characterized by well defined trends predicted by these models. More data are required to clearly define evolutionary trends, and the models require development to incorporate the effects of lithospheric heterogeneities and complex geologic histories.

A newly recognized syndrome of severe growth deficiency, microcephaly, intellectual disability, and characteristic facial features.

PubMed

Vinkler, Chana; Leshinsky-Silver, Esther; Michelson, Marina; Haas, Dorothea; Lerman-Sagie, Tally; Lev, Dorit

2014-01-01

Genetic syndromes with proportionate severe short stature are rare. We describe two sisters born to nonconsanguineous parents with severe linear growth retardation, poor weight gain, microcephaly, characteristic facial features, cutaneous syndactyly of the toes, high myopia, and severe intellectual disability. During infancy and early childhood, the girls had transient hepatosplenomegaly and low blood cholesterol levels that normalized later. A thorough evaluation including metabolic studies, radiological, and genetic investigations were all normal. Cholesterol metabolism and transport were studied and no definitive abnormality was found. No clinical deterioration was observed and no metabolic crises were reported. After due consideration of other known hereditary causes of post-natal severe linear growth retardation, microcephaly, and intellectual disability, we propose that this condition represents a newly recognized autosomal recessive multiple congenital anomaly-intellectual disability syndrome. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

Data driven analysis of rain events: feature extraction, clustering, microphysical /macro physical relationship

NASA Astrophysics Data System (ADS)

Djallel Dilmi, Mohamed; Mallet, Cécile; Barthes, Laurent; Chazottes, Aymeric

2017-04-01

that a rain time series can be considered by an alternation of independent rain event and no rain period. The five selected feature are used to perform a hierarchical clustering of the events. The well-known division between stratiform and convective events appears clearly. This classification into two classes is then refined in 5 fairly homogeneous subclasses. The data driven analysis performed on whole rain events instead of fixed length samples allows identifying strong relationships between macrophysics (based on rain rate) and microphysics (based on raindrops) features. We show that among the 5 identified subclasses some of them have specific microphysics characteristics. Obtaining information on microphysical characteristics of rainfall events from rain gauges measurement suggests many implications in development of the quantitative precipitation estimation (QPE), for the improvement of rain rate retrieval algorithm in remote sensing context.

New biometric modalities using internal physical characteristics

NASA Astrophysics Data System (ADS)

Mortenson, Juliana (Brooks)

2010-04-01

Biometrics is described as the science of identifying people based on physical characteristics such as their fingerprints, facial features, hand geometry, iris patterns, palm prints, or speech recognition. Notably, all of these physical characteristics are visible or detectable from the exterior of the body. These external characteristics can be lifted, photographed, copied or recorded for unauthorized access to a biometric system. Individual humans are unique internally, however, just as they are unique externally. New biometric modalities have been developed which identify people based on their unique internal characteristics. For example, "BoneprintsTM" use acoustic fields to scan the unique bone density pattern of a thumb pressed on a small acoustic sensor. Thanks to advances in piezoelectric materials the acoustic sensor can be placed in virtually any device such as a steering wheel, door handle, or keyboard. Similarly, "Imp-PrintsTM" measure the electrical impedance patterns of a hand to identify or verify a person's identity. Small impedance sensors can be easily embedded in devices such as smart cards, handles, or wall mounts. These internal biometric modalities rely on physical characteristics which are not visible or photographable, providing an added level of security. In addition, both the acoustic and impedance methods can be combined with physiologic measurements such as acoustic Doppler or impedance plethysmography, respectively. Added verification that the biometric pattern came from a living person can be obtained. These new biometric modalities have the potential to allay user concerns over protection of privacy, while providing a higher level of security.*

Automated discovery of structural features of the optic nerve head on the basis of image and genetic data

NASA Astrophysics Data System (ADS)

Christopher, Mark; Tang, Li; Fingert, John H.; Scheetz, Todd E.; Abramoff, Michael D.

2014-03-01

Evaluation of optic nerve head (ONH) structure is a commonly used clinical technique for both diagnosis and monitoring of glaucoma. Glaucoma is associated with characteristic changes in the structure of the ONH. We present a method for computationally identifying ONH structural features using both imaging and genetic data from a large cohort of participants at risk for primary open angle glaucoma (POAG). Using 1054 participants from the Ocular Hypertension Treatment Study, ONH structure was measured by application of a stereo correspondence algorithm to stereo fundus images. In addition, the genotypes of several known POAG genetic risk factors were considered for each participant. ONH structural features were discovered using both a principal component analysis approach to identify the major modes of variance within structural measurements and a linear discriminant analysis approach to capture the relationship between genetic risk factors and ONH structure. The identified ONH structural features were evaluated based on the strength of their associations with genotype and development of POAG by the end of the OHTS study. ONH structural features with strong associations with genotype were identified for each of the genetic loci considered. Several identified ONH structural features were significantly associated (p < 0.05) with the development of POAG after Bonferroni correction. Further, incorporation of genetic risk status was found to substantially increase performance of early POAG prediction. These results suggest incorporating both imaging and genetic data into ONH structural modeling significantly improves the ability to explain POAG-related changes to ONH structure.

Identifying in vivo DCE MRI markers associated with microvessel architecture and gleason grades of prostate cancer.

PubMed

Singanamalli, Asha; Rusu, Mirabela; Sparks, Rachel E; Shih, Natalie N C; Ziober, Amy; Wang, Li-Ping; Tomaszewski, John; Rosen, Mark; Feldman, Michael; Madabhushi, Anant

2016-01-01

To identify computer extracted in vivo dynamic contrast enhanced (DCE) MRI markers associated with quantitative histomorphometric (QH) characteristics of microvessels and Gleason scores (GS) in prostate cancer. This study considered retrospective data from 23 biopsy confirmed prostate cancer patients who underwent 3 Tesla multiparametric MRI before radical prostatectomy (RP). Representative slices from RP specimens were stained with vascular marker CD31. Tumor extent was mapped from RP sections onto DCE MRI using nonlinear registration methods. Seventy-seven microvessel QH features and 18 DCE MRI kinetic features were extracted and evaluated for their ability to distinguish low from intermediate and high GS. The effect of temporal sampling on kinetic features was assessed and correlations between those robust to temporal resolution and microvessel features discriminative of GS were examined. A total of 12 microvessel architectural features were discriminative of low and intermediate/high grade tumors with area under the receiver operating characteristic curve (AUC) > 0.7. These features were most highly correlated with mean washout gradient (WG) (max rho = -0.62). Independent analysis revealed WG to be moderately robust to temporal resolution (intraclass correlation coefficient [ICC] = 0.63) and WG variance, which was poorly correlated with microvessel features, to be predictive of low grade tumors (AUC = 0.77). Enhancement ratio was the most robust (ICC = 0.96) and discriminative (AUC = 0.78) kinetic feature but was moderately correlated with microvessel features (max rho = -0.52). Computer extracted features of prostate DCE MRI appear to be correlated with microvessel architecture and may be discriminative of low versus intermediate and high GS. © 2015 Wiley Periodicals, Inc.

Controls on the spatial variability of supraglacial channel morphology and network characteristics

NASA Astrophysics Data System (ADS)

King, L.

2015-12-01

Supraglacial streams are widespread and ubiquitous features of glacial ice surfaces around the world. They play an important role in the spatial and temporal distribution of meltwater on a glacier, moderating the flux of meltwater to the bed. They are themselves unique fluvial features in which erosion and deposition is achieved through thermal erosion of ice rather than alluvial substrate. As such, they are of both glaciological and fluvial geomorphological interest for both practical and theoretical reasons. However, little is known about their characteristics through space and time, or how these characteristics reflect external driving forces. This research aims to address these gaps by characterizing the spatial variability of supraglacial stream morphology across a range of glacier types and environmental conditions and identifying forcings that control channel form. Topographic data was analyzed from a range of glacier surface types including icesheets, pocket alpine glaciers, and outlet valley glaciers spanning a range of latitudes and elevations, comprising glaciers from Greenland, British Columbia, Alaska, Iceland and Sweden. Channels were extracted from the topographic data using an automated approach based on identifying topographic depressions at different size scales, in which the method was tested relative to manually digitized stream networks. Channel geomorphology was subsequently characterized according to planimetric and drainage network geometries. Resulting morphometric characteristics were analyzed with regards to endo and exogenic environmental forcings such as ice topography and characteristics and climatic forcings to identify the primary controls on supraglacial channel morphology and the response of these channels with respect to these controls.

Study on identifying deciduous forest by the method of feature space transformation

NASA Astrophysics Data System (ADS)

Zhang, Xuexia; Wu, Pengfei

2009-10-01

The thematic remotely sensed information extraction is always one of puzzling nuts which the remote sensing science faces, so many remote sensing scientists devotes diligently to this domain research. The methods of thematic information extraction include two kinds of the visual interpretation and the computer interpretation, the developing direction of which is intellectualization and comprehensive modularization. The paper tries to develop the intelligent extraction method of feature space transformation for the deciduous forest thematic information extraction in Changping district of Beijing city. The whole Chinese-Brazil resources satellite images received in 2005 are used to extract the deciduous forest coverage area by feature space transformation method and linear spectral decomposing method, and the result from remote sensing is similar to woodland resource census data by Chinese forestry bureau in 2004.

Mobile personal health records: an evaluation of features and functionality.

PubMed

Kharrazi, Hadi; Chisholm, Robin; VanNasdale, Dean; Thompson, Benjamin

2012-09-01

To evaluate stand-alone mobile personal health record (mPHR) applications for the three leading cellular phone platforms (iOS, BlackBerry, and Android), assessing each for content, function, security, and marketing characteristics. Nineteen stand-alone mPHR applications (8 for iOS, 5 for BlackBerry, and 6 for Android) were identified and evaluated. Main criteria used to include mPHRs were: operating standalone on a mobile platform; not requiring external connectivity; and covering a wide range of health topics. Selected mPHRs were analyzed considering product characteristics, data elements, and application features. We also reviewed additional features such as marketing tactics. Within and between the different mobile platforms attributes for the mPHR were highly variable. None of the mPHRs contained all attributes included in our evaluation. The top four mPHRs contained 13 of the 14 features omitting only the in-case-of emergency feature. Surprisingly, seven mPHRs lacked basic security measures as important as password protection. The mPHRs were relatively inexpensive: ranging from no cost to $9.99. The mPHR application cost varied in some instances based on whether it supported single or multiple users. Ten mPHRs supported multiple user profiles. Notably, eight mPHRs used scare tactics as marketing strategy. mPHR is an emerging health care technology. The majority of existing mPHR apps is limited by at least one of the attributes considered for this study; however, as the mobile market continues to expand it is likely that more comprehensive mPHRs will be developed in the near future. New advancements in mobile technology can be utilized to enhance mPHRs by long-term patient empowerment features. Marketing strategies for mPHRs should target specific subpopulations and avoid scare tactics. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Features of resilience

DOE PAGES

Connelly, Elizabeth B.; Allen, Craig R.; Hatfield, Kirk; ...

2017-02-20

The National Academy of Sciences (NAS) definition of resilience is used here to organize common concepts and synthesize a set of key features of resilience that can be used across diverse application domains. The features in common include critical functions (services), thresholds, cross-scale (both space and time) interactions, and memory and adaptive management. We propose a framework for linking these features to the planning, absorbing, recovering, and adapting phases identified in the NAS definition. As a result, the proposed delineation of resilience can be important in understanding and communicating resilience concepts.

Features of resilience

USGS Publications Warehouse

Connelly, Elizabeth B.; Allen, Craig R.; Hatfield, Kirk; Palma-Oliveira, José M.; Woods, David D.; Linkov, Igor

2017-01-01

The National Academy of Sciences (NAS) definition of resilience is used here to organize common concepts and synthesize a set of key features of resilience that can be used across diverse application domains. The features in common include critical functions (services), thresholds, cross-scale (both space and time) interactions, and memory and adaptive management. We propose a framework for linking these features to the planning, absorbing, recovering, and adapting phases identified in the NAS definition. The proposed delineation of resilience can be important in understanding and communicating resilience concepts.

Line fitting based feature extraction for object recognition

NASA Astrophysics Data System (ADS)

Li, Bing

2014-06-01

Image feature extraction plays a significant role in image based pattern applications. In this paper, we propose a new approach to generate hierarchical features. This new approach applies line fitting to adaptively divide regions based upon the amount of information and creates line fitting features for each subsequent region. It overcomes the feature wasting drawback of the wavelet based approach and demonstrates high performance in real applications. For gray scale images, we propose a diffusion equation approach to map information-rich pixels (pixels near edges and ridge pixels) into high values, and pixels in homogeneous regions into small values near zero that form energy map images. After the energy map images are generated, we propose a line fitting approach to divide regions recursively and create features for each region simultaneously. This new feature extraction approach is similar to wavelet based hierarchical feature extraction in which high layer features represent global characteristics and low layer features represent local characteristics. However, the new approach uses line fitting to adaptively focus on information-rich regions so that we avoid the feature waste problems of the wavelet approach in homogeneous regions. Finally, the experiments for handwriting word recognition show that the new method provides higher performance than the regular handwriting word recognition approach.

Comparison between flood prone areas' geomorphic features in the Abruzzo region

NASA Astrophysics Data System (ADS)

Orlando, D.; Giglioni, M.; Magnaldi, S.

2017-07-01

Flood risk maps are one of the main non-structural measures for risk mitigation, but, as the risk knowledge degree is directly proportional to the community interest and financial capability, many sites are devoid of flood inundation areas studies. Recently many authors have investigated the capability of flood prone areas individuation with geomorphological DIGITAL ELEVATION MODEL(DEM) based approaches. These approaches highlight the role of geomorphic features derived from DEM, in this case slope, curvature, elevation, and topographic wetness index, to preliminary inundated areas' identification, without using hydraulic simulations. The present studies aim to analyze the geomorphic features of different hazard levels that lie under the identified inundated areas that have been carried out by the Abruzzo Region Basin Authority. The Aterno-Pescara and Foro river basins have been investigated. The results show that the characteristics of the flooded areas can be clearly distinguished from those of the entire basin,however, the difficultly of geomorphic features in individuatingthe areas of different hazard classifications is obvious.

Improved Measurement of Blood Pressure by Extraction of Characteristic Features from the Cuff Oscillometric Waveform

PubMed Central

Lim, Pooi Khoon; Ng, Siew-Cheok; Jassim, Wissam A.; Redmond, Stephen J.; Zilany, Mohammad; Avolio, Alberto; Lim, Einly; Tan, Maw Pin; Lovell, Nigel H.

2015-01-01

We present a novel approach to improve the estimation of systolic (SBP) and diastolic blood pressure (DBP) from oscillometric waveform data using variable characteristic ratios between SBP and DBP with mean arterial pressure (MAP). This was verified in 25 healthy subjects, aged 28 ± 5 years. The multiple linear regression (MLR) and support vector regression (SVR) models were used to examine the relationship between the SBP and the DBP ratio with ten features extracted from the oscillometric waveform envelope (OWE). An automatic algorithm based on relative changes in the cuff pressure and neighbouring oscillometric pulses was proposed to remove outlier points caused by movement artifacts. Substantial reduction in the mean and standard deviation of the blood pressure estimation errors were obtained upon artifact removal. Using the sequential forward floating selection (SFFS) approach, we were able to achieve a significant reduction in the mean and standard deviation of differences between the estimated SBP values and the reference scoring (MLR: mean ± SD = −0.3 ± 5.8 mmHg; SVR and −0.6 ± 5.4 mmHg) with only two features, i.e., Ratio2 and Area3, as compared to the conventional maximum amplitude algorithm (MAA) method (mean ± SD = −1.6 ± 8.6 mmHg). Comparing the performance of both MLR and SVR models, our results showed that the MLR model was able to achieve comparable performance to that of the SVR model despite its simplicity. PMID:26087370

Data-driven modeling of sleep EEG and EOG reveals characteristics indicative of pre-Parkinson's and Parkinson's disease.

PubMed

Christensen, Julie A E; Zoetmulder, Marielle; Koch, Henriette; Frandsen, Rune; Arvastson, Lars; Christensen, Søren R; Jennum, Poul; Sorensen, Helge B D

2014-09-30

Manual scoring of sleep relies on identifying certain characteristics in polysomnograph (PSG) signals. However, these characteristics are disrupted in patients with neurodegenerative diseases. This study evaluates sleep using a topic modeling and unsupervised learning approach to identify sleep topics directly from electroencephalography (EEG) and electrooculography (EOG). PSG data from control subjects were used to develop an EOG and an EEG topic model. The models were applied to PSG data from 23 control subjects, 25 patients with periodic leg movements (PLMs), 31 patients with idiopathic REM sleep behavior disorder (iRBD) and 36 patients with Parkinson's disease (PD). The data were divided into training and validation datasets and features reflecting EEG and EOG characteristics based on topics were computed. The most discriminative feature subset for separating iRBD/PD and PLM/controls was estimated using a Lasso-regularized regression model. The features with highest discriminability were the number and stability of EEG topics linked to REM and N3, respectively. Validation of the model indicated a sensitivity of 91.4% and a specificity of 68.8% when classifying iRBD/PD patients. The topics showed visual accordance with the manually scored sleep stages, and the features revealed sleep characteristics containing information indicative of neurodegeneration. This study suggests that the amount of N3 and the ability to maintain NREM and REM sleep have potential as early PD biomarkers. Data-driven analysis of sleep may contribute to the evaluation of neurodegenerative patients. Copyright © 2014 Elsevier B.V. All rights reserved.

Ambient response of a unique performance-based design building with dynamic response modification features

USGS Publications Warehouse

Çelebi, Mehmet; Huang, Moh; Shakal, Antony; Hooper, John; Klemencic, Ron

2012-01-01

A 64-story, performance-based design building with reinforced concrete core shear-walls and unique dynamic response modification features (tuned liquid sloshing dampers and buckling-restrained braces) has been instrumented with a monitoring array of 72 channels of accelerometers. Ambient vibration data recorded are analyzed to identify modes and associated frequencies and damping. The low-amplitude dynamic characteristics are considerably different than those computed from design analyses, but serve as a baseline against which to compare with future strong shaking responses. Such studies help to improve our understanding of the effectiveness of the added features to the building and help improve designs in the future.

Magnetic resonance characteristics and susceptibility weighted imaging of the brain in gadolinium encephalopathy.

PubMed

Samardzic, Dejan; Thamburaj, Krishnamoorthy

2015-01-01

To report the brain imaging features on magnetic resonance imaging (MRI) in inadvertent intrathecal gadolinium administration. A 67-year-old female with gadolinium encephalopathy from inadvertent high dose intrathecal gadolinium administration during an epidural steroid injection was studied with multisequence 3T MRI. T1-weighted imaging shows pseudo-T2 appearance with diffusion of gadolinium into the brain parenchyma, olivary bodies, and membranous labyrinth. Nulling of cerebrospinal fluid (CSF) signal is absent on fluid attenuation recovery (FLAIR). Susceptibility-weighted imaging (SWI) demonstrates features similar to subarachnoid hemorrhage. CT may demonstrate a pseudo-cerebral edema pattern given the high attenuation characteristics of gadolinium. Intrathecal gadolinium demonstrates characteristic imaging features on MRI of the brain and may mimic subarachnoid hemorrhage on susceptibility-weighted imaging. Identifying high dose gadolinium within the CSF spaces on MRI is essential to avoid diagnostic and therapeutic errors. Copyright © 2013 by the American Society of Neuroimaging.

Nonlinear features for product inspection

NASA Astrophysics Data System (ADS)

Talukder, Ashit; Casasent, David P.

1999-03-01

Classification of real-time X-ray images of randomly oriented touching pistachio nuts is discussed. The ultimate objective is the development of a system for automated non-invasive detection of defective product items on a conveyor belt. We discuss the extraction of new features that allow better discrimination between damaged and clean items (pistachio nuts). This feature extraction and classification stage is the new aspect of this paper; our new maximum representation and discriminating feature (MRDF) extraction method computes nonlinear features that are used as inputs to a new modified k nearest neighbor classifier. In this work, the MRDF is applied to standard features (rather than iconic data). The MRDF is robust to various probability distributions of the input class and is shown to provide good classification and new ROC (receiver operating characteristic) data.

Phenotypic characterization of glioblastoma identified through shape descriptors

NASA Astrophysics Data System (ADS)

Chaddad, Ahmad; Desrosiers, Christian; Toews, Matthew

2016-03-01

This paper proposes quantitatively describing the shape of glioblastoma (GBM) tissue phenotypes as a set of shape features derived from segmentations, for the purposes of discriminating between GBM phenotypes and monitoring tumor progression. GBM patients were identified from the Cancer Genome Atlas, and quantitative MR imaging data were obtained from the Cancer Imaging Archive. Three GBM tissue phenotypes are considered including necrosis, active tumor and edema/invasion. Volumetric tissue segmentations are obtained from registered T1˗weighted (T1˗WI) postcontrast and fluid-attenuated inversion recovery (FLAIR) MRI modalities. Shape features are computed from respective tissue phenotype segmentations, and a Kruskal-Wallis test was employed to select features capable of classification with a significance level of p < 0.05. Several classifier models are employed to distinguish phenotypes, where a leave-one-out cross-validation was performed. Eight features were found statistically significant for classifying GBM phenotypes with p <0.05, orientation is uninformative. Quantitative evaluations show the SVM results in the highest classification accuracy of 87.50%, sensitivity of 94.59% and specificity of 92.77%. In summary, the shape descriptors proposed in this work show high performance in predicting GBM tissue phenotypes. They are thus closely linked to morphological characteristics of GBM phenotypes and could potentially be used in a computer assisted labeling system.

Identifying characteristics and practices of multidisciplinary team reviews for patients with severe mental illness: a systematic review.

PubMed

Woody, Charlotte A; Baxter, Amanda J; Harris, Meredith G; Siskind, Dan J; Whiteford, Harvey A

2018-06-01

Multidisciplinary teams in mental health receive limited guidance, leading to inconsistent practices. We undertook a systematic review of the characteristics and practices of multidisciplinary team reviews for patients with severe mental illness or in relevant mental health service settings. Sources published since 2000 were located via academic database and web searches. Results were synthesised narratively. A total of 14 sources were analysed. Important characteristics and practices identified included routine monitoring and evaluation, good communication, equality between team members, and clear documentation practices. Success factors included defined leadership and clear team goals. Four sources described considerations for patients with complex clinical needs, including allocating sufficient time for discussion, maintaining connections with community providers, and ensuring culturally sensitive practices. No single best practice model was found, due to variations in team caseload, casemix, and resourcing levels. However, key ingredients for success were proposed. Sources were mostly descriptive; there remains a lack of evidence-based guidance regarding multidisciplinary team review characteristics and practices.

The building blocks of a 'Liveable Neighbourhood': Identifying the key performance indicators for walking of an operational planning policy in Perth, Western Australia.

PubMed

Hooper, Paula; Knuiman, Matthew; Foster, Sarah; Giles-Corti, Billie

2015-11-01

Planning policy makers are requesting clearer guidance on the key design features required to build neighbourhoods that promote active living. Using a backwards stepwise elimination procedure (logistic regression with generalised estimating equations adjusting for demographic characteristics, self-selection factors, stage of construction and scale of development) this study identified specific design features (n=16) from an operational planning policy ("Liveable Neighbourhoods") that showed the strongest associations with walking behaviours (measured using the Neighbourhood Physical Activity Questionnaire). The interacting effects of design features on walking behaviours were also investigated. The urban design features identified were grouped into the "building blocks of a Liveable Neighbourhood", reflecting the scale, importance and sequencing of the design and implementation phases required to create walkable, pedestrian friendly developments. Copyright © 2015 Elsevier Ltd. All rights reserved.

Prediction of BRAF mutation status of craniopharyngioma using magnetic resonance imaging features.

PubMed

Yue, Qi; Yu, Yang; Shi, Zhifeng; Wang, Yongfei; Zhu, Wei; Du, Zunguo; Yao, Zhenwei; Chen, Liang; Mao, Ying

2017-10-06

OBJECTIVE Treatment with a BRAF mutation inhibitor might shrink otherwise refractory craniopharyngiomas and is a promising preoperative treatment to facilitate tumor resection. The aim of this study was to investigate the noninvasive diagnosis of BRAF-mutated craniopharyngiomas based on MRI characteristics. METHODS Fifty-two patients with pathologically diagnosed craniopharyngioma were included in this study. Polymerase chain reaction was performed on tumor tissue specimens to detect BRAF and CTNNB1 mutations. MRI manifestations-including tumor location, size, shape, and composition; signal intensity of cysts; enhancement pattern; pituitary stalk morphology; and encasement of the internal carotid artery-were analyzed by 2 neuroradiologists blinded to patient identity and clinical characteristics, including BRAF mutation status. Results were compared between the BRAF-mutated and wild-type (WT) groups. Characteristics that were significantly more prevalent (p < 0.05) in the BRAF-mutated craniopharyngiomas were defined as diagnostic features. The minimum number of diagnostic features needed to make a diagnosis was determined by analyzing the receiver operating characteristic (ROC) curve. RESULTS Eight of the 52 patients had BRAF-mutated craniopharyngiomas, and the remaining 44 had BRAF WT tumors. The clinical characteristics did not differ significantly between the 2 groups. Interobserver agreement for MRI data analysis was relatively reliable, with values of Cohen κ ranging from 0.65 to 0.97 (p < 0.001). A comparison of findings in the 2 patient groups showed that BRAF-mutated craniopharyngiomas tended to be suprasellar (p < 0.001), spherical (p = 0.005), predominantly solid (p = 0.003), and homogeneously enhancing (p < 0.001), and that patients with these tumors tended to have a thickened pituitary stalk (p = 0.014). When at least 3 of these 5 features were present, a tumor might be identified as BRAF mutated with a sensitivity of 1.00 and a specificity of 0

Tumor recognition in wireless capsule endoscopy images using textural features and SVM-based feature selection.

PubMed

Li, Baopu; Meng, Max Q-H

2012-05-01

Tumor in digestive tract is a common disease and wireless capsule endoscopy (WCE) is a relatively new technology to examine diseases for digestive tract especially for small intestine. This paper addresses the problem of automatic recognition of tumor for WCE images. Candidate color texture feature that integrates uniform local binary pattern and wavelet is proposed to characterize WCE images. The proposed features are invariant to illumination change and describe multiresolution characteristics of WCE images. Two feature selection approaches based on support vector machine, sequential forward floating selection and recursive feature elimination, are further employed to refine the proposed features for improving the detection accuracy. Extensive experiments validate that the proposed computer-aided diagnosis system achieves a promising tumor recognition accuracy of 92.4% in WCE images on our collected data.

Automated Feature Identification and Classification Using Automated Feature Weighted Self Organizing Map (FWSOM)

NASA Astrophysics Data System (ADS)

Starkey, Andrew; Usman Ahmad, Aliyu; Hamdoun, Hassan

2017-10-01

This paper investigates the application of a novel method for classification called Feature Weighted Self Organizing Map (FWSOM) that analyses the topology information of a converged standard Self Organizing Map (SOM) to automatically guide the selection of important inputs during training for improved classification of data with redundant inputs, examined against two traditional approaches namely neural networks and Support Vector Machines (SVM) for the classification of EEG data as presented in previous work. In particular, the novel method looks to identify the features that are important for classification automatically, and in this way the important features can be used to improve the diagnostic ability of any of the above methods. The paper presents the results and shows how the automated identification of the important features successfully identified the important features in the dataset and how this results in an improvement of the classification results for all methods apart from linear discriminatory methods which cannot separate the underlying nonlinear relationship in the data. The FWSOM in addition to achieving higher classification accuracy has given insights into what features are important in the classification of each class (left and right-hand movements), and these are corroborated by already published work in this area.

Decoding and Reading Comprehension: A Meta-Analysis to Identify Which Reader and Assessment Characteristics Influence the Strength of the Relationship in English

ERIC Educational Resources Information Center

García, J. Ricardo; Cain, Kate

2014-01-01

The twofold purpose of this meta-analysis was to determine the relative importance of decoding skills to reading comprehension in reading development and to identify which reader characteristics and reading assessment characteristics contribute to differences in the decoding and reading comprehension correlation. A meta-analysis of 110 studies…

Phosphatization Associated Features of Ferromanganese Crusts at Lemkein Seamount, Marshall Islands

NASA Astrophysics Data System (ADS)

Choi, J.; Lee, I.; Park, B. K.; Kim, J.

2014-12-01

Old layers of ferromanganese crusts, especially in the Pacific Ocean, have been affected by phosphatization. Ferromanganese crusts on Lemkein seamount in Marshall Islands also are phosphatized (3.3 to 4.2 wt % of P concentration). Furthermore, they have characteristic features that are different from other ferromanganese crusts. These features occur near the phosphorite, which were thought to fill the pore spaces of ferromanganese crusts. Inside the features, ferromanganese crusts are botryoidally precipitated from the round-boundary. The features of the phosphatized lower crusts of Lemkein seamount are observed using microscope and SEM. Elemental compositions of the selected samples were analyzed by SEM-EDS. Based on the observation and analysis of samples, three characteristic structures are identified: (1) phosphate-filled circles, (2) tongue-shaped framboidal crust, and (3) massive framboidal crust. The phosphate-filled circles are mostly composed of phosphorite, and they include trace fossils such as foraminifera. Phosphatized ferromanganese crusts exist at the boundary of this structure. The tongue-shaped crust is connected with the lips downward, and ferromanganese crusts inside the tongue show distinct growth rim. The massive framboidal crust is located below the tongue. Ferromanganese crusts in the massive framboidal crust are enveloped by phosphate, and some of the crusts are phosphatized. Around the structures, Mn oxide phase is concentrated as a shape of corona on BSE image. All of the structures are in the phosphatized crusts that show columnar growth of ferromanganese crusts and have sub-parallel lamination. These observation and chemical analysis of the ferromanganese crusts can provide a clue of diagenetic processes during the formation of ferromanganese crusts.

Identifying Chinese Microblog Users With High Suicide Probability Using Internet-Based Profile and Linguistic Features: Classification Model

PubMed Central

Guan, Li; Hao, Bibo; Cheng, Qijin; Yip, Paul SF

2015-01-01

Background Traditional offline assessment of suicide probability is time consuming and difficult in convincing at-risk individuals to participate. Identifying individuals with high suicide probability through online social media has an advantage in its efficiency and potential to reach out to hidden individuals, yet little research has been focused on this specific field. Objective The objective of this study was to apply two classification models, Simple Logistic Regression (SLR) and Random Forest (RF), to examine the feasibility and effectiveness of identifying high suicide possibility microblog users in China through profile and linguistic features extracted from Internet-based data. Methods There were nine hundred and nine Chinese microblog users that completed an Internet survey, and those scoring one SD above the mean of the total Suicide Probability Scale (SPS) score, as well as one SD above the mean in each of the four subscale scores in the participant sample were labeled as high-risk individuals, respectively. Profile and linguistic features were fed into two machine learning algorithms (SLR and RF) to train the model that aims to identify high-risk individuals in general suicide probability and in its four dimensions. Models were trained and then tested by 5-fold cross validation; in which both training set and test set were generated under the stratified random sampling rule from the whole sample. There were three classic performance metrics (Precision, Recall, F1 measure) and a specifically defined metric “Screening Efficiency” that were adopted to evaluate model effectiveness. Results Classification performance was generally matched between SLR and RF. Given the best performance of the classification models, we were able to retrieve over 70% of the labeled high-risk individuals in overall suicide probability as well as in the four dimensions. Screening Efficiency of most models varied from 1/4 to 1/2. Precision of the models was generally below 30

Employing an ethnographic approach: key characteristics.

PubMed

Lambert, Veronica; Glacken, Michele; McCarron, Mary

2011-01-01

Nurses are increasingly embracing ethnography as a useful research methodology. This paper presents an overview of some of the main characteristics we considered and the challenges encountered when using ethnography to explore the nature of communication between children and health professionals in a children's hospital. There is no consensual definition or single procedure to follow when using ethnography. This is largely attributable to the re-contextualisation of ethnography over time through diversification in and across many disciplines. Thus, it is imperative to consider some of ethnography's trademark features. To identify core trademark features of ethnography, we collated data following a scoping review of pertinent ethnographic textbooks, journal articles, attendance at ethnographic workshops and discussions with principle ethnographers. This is a methodological paper. Essentially, ethnography is a field-orientated activity that has cultural interpretations at its core, although the levels of those interpretations vary. We identified six trademark features to be considered when embracing an ethnographic approach: naturalism; context; multiple data sources; small case numbers; 'emic' and 'etic' perspectives, and ethical considerations. Ethnography has an assortment of meanings, so it is not often used in a wholly orthodox way and does not fall under the auspices of one epistemological belief. Yet, there are core criteria and trademark features that researchers should take into account alongside their particular epistemological beliefs when embracing an ethnographic inquiry. We hope this paper promotes a clearer vision of the methodological processes to consider when embarking on ethnography and creates an avenue for others to disseminate their experiences of and challenges encountered when applying ethnography's trademark features in different healthcare contexts.

Automated Recognition of 3D Features in GPIR Images

NASA Technical Reports Server (NTRS)

Park, Han; Stough, Timothy; Fijany, Amir

2007-01-01

A method of automated recognition of three-dimensional (3D) features in images generated by ground-penetrating imaging radar (GPIR) is undergoing development. GPIR 3D images can be analyzed to detect and identify such subsurface features as pipes and other utility conduits. Until now, much of the analysis of GPIR images has been performed manually by expert operators who must visually identify and track each feature. The present method is intended to satisfy a need for more efficient and accurate analysis by means of algorithms that can automatically identify and track subsurface features, with minimal supervision by human operators. In this method, data from multiple sources (for example, data on different features extracted by different algorithms) are fused together for identifying subsurface objects. The algorithms of this method can be classified in several different ways. In one classification, the algorithms fall into three classes: (1) image-processing algorithms, (2) feature- extraction algorithms, and (3) a multiaxis data-fusion/pattern-recognition algorithm that includes a combination of machine-learning, pattern-recognition, and object-linking algorithms. The image-processing class includes preprocessing algorithms for reducing noise and enhancing target features for pattern recognition. The feature-extraction algorithms operate on preprocessed data to extract such specific features in images as two-dimensional (2D) slices of a pipe. Then the multiaxis data-fusion/ pattern-recognition algorithm identifies, classifies, and reconstructs 3D objects from the extracted features. In this process, multiple 2D features extracted by use of different algorithms and representing views along different directions are used to identify and reconstruct 3D objects. In object linking, which is an essential part of this process, features identified in successive 2D slices and located within a threshold radius of identical features in adjacent slices are linked in a

Deep Learning Identifies High-z Galaxies in a Central Blue Nugget Phase in a Characteristic Mass Range

NASA Astrophysics Data System (ADS)

Huertas-Company, M.; Primack, J. R.; Dekel, A.; Koo, D. C.; Lapiner, S.; Ceverino, D.; Simons, R. C.; Snyder, G. F.; Bernardi, M.; Chen, Z.; Domínguez-Sánchez, H.; Lee, C. T.; Margalef-Bentabol, B.; Tuccillo, D.

2018-05-01

We use machine learning to identify in color images of high-redshift galaxies an astrophysical phenomenon predicted by cosmological simulations. This phenomenon, called the blue nugget (BN) phase, is the compact star-forming phase in the central regions of many growing galaxies that follows an earlier phase of gas compaction and is followed by a central quenching phase. We train a convolutional neural network (CNN) with mock “observed” images of simulated galaxies at three phases of evolution— pre-BN, BN, and post-BN—and demonstrate that the CNN successfully retrieves the three phases in other simulated galaxies. We show that BNs are identified by the CNN within a time window of ∼0.15 Hubble times. When the trained CNN is applied to observed galaxies from the CANDELS survey at z = 1–3, it successfully identifies galaxies at the three phases. We find that the observed BNs are preferentially found in galaxies at a characteristic stellar mass range, 109.2–10.3 M ⊙ at all redshifts. This is consistent with the characteristic galaxy mass for BNs as detected in the simulations and is meaningful because it is revealed in the observations when the direct information concerning the total galaxy luminosity has been eliminated from the training set. This technique can be applied to the classification of other astrophysical phenomena for improved comparison of theory and observations in the era of large imaging surveys and cosmological simulations.

Remote health monitoring: predicting outcome success based on contextual features for cardiovascular disease.

PubMed

Alshurafa, Nabil; Eastwood, Jo-Ann; Pourhomayoun, Mohammad; Liu, Jason J; Sarrafzadeh, Majid

2014-01-01

Current studies have produced a plethora of remote health monitoring (RHM) systems designed to enhance the care of patients with chronic diseases. Many RHM systems are designed to improve patient risk factors for cardiovascular disease, including physiological parameters such as body mass index (BMI) and waist circumference, and lipid profiles such as low density lipoprotein (LDL) and high density lipoprotein (HDL). There are several patient characteristics that could be determining factors for a patient's RHM outcome success, but these characteristics have been largely unidentified. In this paper, we analyze results from an RHM system deployed in a six month Women's Heart Health study of 90 patients, and apply advanced feature selection and machine learning algorithms to identify patients' key baseline contextual features and build effective prediction models that help determine RHM outcome success. We introduce Wanda-CVD, a smartphone-based RHM system designed to help participants with cardiovascular disease risk factors by motivating participants through wireless coaching using feedback and prompts as social support. We analyze key contextual features that secure positive patient outcomes in both physiological parameters and lipid profiles. Results from the Women's Heart Health study show that health threat of heart disease, quality of life, family history, stress factors, social support, and anxiety at baseline all help predict patient RHM outcome success.

Spectral EEG Features of a Short Psycho-physiological Relaxation

NASA Astrophysics Data System (ADS)

Teplan, Michal; Krakovská, Anna; Špajdel, Marián

2014-08-01

Short-lasting psycho-physiological relaxation was investigated through an analysis of its bipolar electroencephalographic (EEG) characteristics. In 8 subjects, 6-channel EEG data of 3-minute duration were recorded during 88 relaxation sessions. Time course of spectral EEG features was examined. Alpha powers were decreasing during resting conditions of 3-minute sessions in lying position with eyes closed. This was followed by a decrease of total power in centro-parietal cortex regions and an increase of beta power in fronto-central areas. Represented by EEG coherences the interhemispheric communication between the parieto-occipital regions was enhanced within a frequency range of 2-10 Hz. In order to discern between higher and lower levels of relaxation distinguished according to self-rated satisfaction, EEG features were assessed and discriminating parameters were identified. Successful relaxation was determined mainly by the presence of decreased delta-1 power across the cortex. Potential applications for these findings include the clinical, pharmacological, and stress management fields.

High voltage characteristics of the electrodynamic tether and the generation of power and propulsion

NASA Technical Reports Server (NTRS)

Williamson, P. R.

1986-01-01

The Tethered Satellite System (TSS) will deploy and retrieve a satellite from the Space Shuttle orbiter with a tether of up to 100 km in length attached between the satellite and the orbiter. The characteristics of the TSS which are related to high voltages, electrical currents, energy storage, power, and the generation of plasma waves are described. A number of specific features of the tether system of importance in assessing the operational characteristics of the electrodynamic TSS are identified.

Simulate the volcanic radiation features in medium wave infrared channels

NASA Astrophysics Data System (ADS)

Gong, Cailan; Jiang, Shan; Liu, Fengyi; Hu, Yong

2015-10-01

There are different scales and intensities of the volcanic eruption in the world every year. Existing medium wave infrared (MWI) remote sensing channels are often at atmospheric window in 3-5μm, lack of water vapor and carbon dioxide(CO2) absorption channels data, such as 2.2μm, 2.7μm and so on, however the 2.7μm absorption bands can be used as volcanoes, forest fires and other hot target identification. In order to obtain the high-temperature targets (HTT)radiation features, such as volcanic eruptions and forest fires in the water vapor absorption channels, Firstly, the HTT should be identified from the existing bands based on the temperature differences between the objects and the surrounding environment. Then, the HTT radiation features were simulated, and the correlation between the radiations of different bands were established with statistical analysis method. The HTT reorganization from remote sensing data, radiation characteristics simulation in different atmospheric models were described, then the bands transformed models were set up. The volcanic HTT radiation characteristics were simulated in wavelength 2.7μm and 4.433-4.498μm (band 24 of MODIS) based on the known bands of 3.55 -3.93μm (band 3 of FengYun-3 Visible and Infrared Scanning Radiometer (VIRR)). The simulated results were tested by the volcanic HTT radiation characteristics with 4.433-4.498μm by known bands of MODIS image and the simulated 4.433-4.498μm image. The causes of errors generated were analyzed. The study methods were useful to the new remote sensor bands imaging characteristics simulation analysis.

The cytologic features of NUT midline carcinoma.

PubMed

Bellizzi, Andrew M; Bruzzi, Cynthia; French, Christopher A; Stelow, Edward B

2009-12-25

Nuclear protein in testis (NUT) midline carcinoma (NMC) represents an aggressive, high-grade carcinoma typically involving the upper aerodigestive tract or mediastinum. Although the tumor was originally noted in young persons, we have subsequently identified 5 adult cases. To our knowledge, the cytology of NMC has not been systematically described. We recently published a series of NMCs identified by fluorescent in situ hybridization for characteristic NUT rearrangement. Three of these patients had undergone fine-needle aspiration. Patient age, sex, primary tumor location, and aspiration site were noted. Cases were assessed for the following: cellularity, architecture, cytoplasm, cell size, nuclear contours, nucleoli, chromatin, anisonucleosis/cytosis, mitotic activity, background, and nuclear crush. The 3 cases occurred in 2 women and 1 man, ages 31-79 years. Primaries involved the sinonasal tract (2) and larynx. Aspirates were of right neck masses (2) and supraclavicular lymph node. Smears were highly cellular and generally noncohesive. Cytoplasm was scant/delicate, although occasional cells with denser cytoplasm were noted in 1 case. Cells were 2-3 times the diameter of a small lymphocyte with irregular nuclear contours, discrete nucleoli, and fine/granular to vesicular chromatin. Anisonucleosis/cytosis was slight to moderate. Mitotic figures were noted in each case. The background contained naked nuclei and karyorrhectic debris; nuclear crush was noted. NMCs exhibit cytologic features of a poorly differentiated or undifferentiated carcinoma. Although reports mention squamous differentiation as a histologic feature, it is typically focal, and overt squamous differentiation was not identified in our cases. Given morphologic overlap with other high-grade carcinomas, diagnosis requires a high index of suspicion. (c) 2009 American Cancer Society.

Constraining Cometary Crystal Shapes from IR Spectral Features

NASA Technical Reports Server (NTRS)

Wooden, Diane H.; Lindsay, Sean; Harker, David E.; Kelley, Michael S. P.; Woodward, Charles E.; Murphy, James Richard

2013-01-01

A major challenge in deriving the silicate mineralogy of comets is ascertaining how the anisotropic nature of forsterite crystals affects the spectral features' wavelength, relative intensity, and asymmetry. Forsterite features are identified in cometary comae near 10, 11.05-11.2, 16, 19, 23.5, 27.5 and 33 microns [1-10], so accurate models for forsterite's absorption efficiency (Qabs) are a primary requirement to compute IR spectral energy distributions (SEDs, lambdaF lambda vs. lambda) and constrain the silicate mineralogy of comets. Forsterite is an anisotropic crystal, with three crystallographic axes with distinct indices of refraction for the a-, b-, and c-axis. The shape of a forsterite crystal significantly affects its spectral features [13-16]. We need models that account for crystal shape. The IR absorption efficiencies of forsterite are computed using the discrete dipole approximation (DDA) code DDSCAT [11,12]. Starting from a fiducial crystal shape of a cube, we systematically elongate/reduce one of the crystallographic axes. Also, we elongate/reduce one axis while the lengths of the other two axes are slightly asymmetric (0.8:1.2). The most significant grain shape characteristic that affects the crystalline spectral features is the relative lengths of the crystallographic axes. The second significant grain shape characteristic is breaking the symmetry of all three axes [17]. Synthetic spectral energy distributions using seven crystal shape classes [17] are fit to the observed SED of comet C/1995 O1 (Hale-Bopp). The Hale-Bopp crystalline residual better matches equant, b-platelets, c-platelets, and b-columns spectral shape classes, while a-platelets, a-columns and c-columns worsen the spectral fits. Forsterite condensation and partial evaporation experiments demonstrate that environmental temperature and grain shape are connected [18-20]. Thus, grain shape is a potential probe for protoplanetary disk temperatures where the cometary crystalline

Analysis of recently identified prostate cancer susceptibility loci in a population-based study: Associations with family history and clinical features

PubMed Central

FitzGerald, Liesel M.; Kwon, Erika M.; Koopmeiners, Joseph S.; Salinas, Claudia A.; Stanford, Janet L.; Ostrander, Elaine A.

2009-01-01

Purpose Two recent genome-wide association studies have highlighted several SNPs purported to be associated with prostate cancer risk. We investigated the significance of these SNPs in a population-based study of Caucasian men, testing the effects of each SNP in relation to family history of prostate cancer and clinicopathological features of disease. Experimental Design We genotyped 13 SNPs in 1,308 prostate cancer patients and 1,267 unaffected controls frequency matched to cases by five-year age groups. The association of each SNP with disease risk and stratified by family history of prostate cancer and clinicopathological features of disease was calculated using logistic and polytomous regression. Results These results confirm the importance of multiple previously reported SNPs in relation to prostate cancer susceptibility; 11 of the 13 SNPs were significantly associated with risk of developing prostate cancer. However, none of the SNP associations were of comparable magnitude to that associated with having a first-degree family history of the disease. Risk estimates associated with SNPs rs4242382 and rs2735839 varied by family history, while risk estimates for rs10993994 and rs5945619 varied by Gleason score. Conclusions Our results confirm that several recently identified SNPs are associated with prostate cancer risk; however the variant alleles only confer a low to moderate relative risk of disease and are generally not associated with more aggressive disease features. PMID:19366831

Multi-dimension feature fusion for action recognition

NASA Astrophysics Data System (ADS)

Dong, Pei; Li, Jie; Dong, Junyu; Qi, Lin

2018-04-01

Typical human actions last several seconds and exhibit characteristic spatio-temporal structure. The challenge for action recognition is to capture and fuse the multi-dimension information in video data. In order to take into account these characteristics simultaneously, we present a novel method that fuses multiple dimensional features, such as chromatic images, depth and optical flow fields. We built our model based on the multi-stream deep convolutional networks with the help of temporal segment networks and extract discriminative spatial and temporal features by fusing ConvNets towers multi-dimension, in which different feature weights are assigned in order to take full advantage of this multi-dimension information. Our architecture is trained and evaluated on the currently largest and most challenging benchmark NTU RGB-D dataset. The experiments demonstrate that the performance of our method outperforms the state-of-the-art methods.

Social Network Analysis Identifies Key Participants in Conservation Development.

PubMed

Farr, Cooper M; Reed, Sarah E; Pejchar, Liba

2018-05-01

Understanding patterns of participation in private lands conservation, which is often implemented voluntarily by individual citizens and private organizations, could improve its effectiveness at combating biodiversity loss. We used social network analysis (SNA) to examine participation in conservation development (CD), a private land conservation strategy that clusters houses in a small portion of a property while preserving the remaining land as protected open space. Using data from public records for six counties in Colorado, USA, we compared CD participation patterns among counties and identified actors that most often work with others to implement CDs. We found that social network characteristics differed among counties. The network density, or proportion of connections in the network, varied from fewer than 2 to nearly 15%, and was higher in counties with smaller populations and fewer CDs. Centralization, or the degree to which connections are held disproportionately by a few key actors, was not correlated strongly with any county characteristics. Network characteristics were not correlated with the prevalence of wildlife-friendly design features in CDs. The most highly connected actors were biological and geological consultants, surveyors, and engineers. Our work demonstrates a new application of SNA to land-use planning, in which CD network patterns are examined and key actors are identified. For better conservation outcomes of CD, we recommend using network patterns to guide strategies for outreach and information dissemination, and engaging with highly connected actor types to encourage widespread adoption of best practices for CD design and stewardship.

Common features of periocular tinea.

PubMed

Basak, S Alison Finger; Berk, David R; Lueder, Gregg T; Bayliss, Susan J

2011-03-01

To present the common features of periocular tinea to aid physicians in future diagnosis and therapy of this condition, because superficial fungal infections on the face are often misdiagnosed owing to the diverse morphologies that they manifest. This is especially true of dermatophytoses involving the periocular region. A retrospective review was performed of patients with a diagnosis of periocular tinea who were seen between January 2003 and September 2009 in the pediatric dermatology clinic at St. Louis Children's Hospital. Ten cases of periocular tinea were identified (6 male patients and 4 female patients). Common features included prolonged misdiagnosis (all 10 cases), a normal ophthalmologic examination (all 10 cases), and inappropriate corticosteroid application (7 cases). Loss of the eyelashes occurred in all 10 patients. No cases had evidence of other tinea infections on examination. Only 2 cases had the central clearing classically associated with tinea corporis. Seven patients had a potassium hydroxide preparation and/or culture positive for fungal elements. Lesions improved with topical and oral antifungal treatment in all cases, and patients were able to regrow their eyelashes. Periocular tinea should be considered in the differential diagnosis for periocular inflammation, especially in those patients refractory to therapy for more common conditions. Loss of the eyelashes is characteristic of these fungal infections, similar to the hair loss that occurs in kerions associated with tinea capitis.

Trajectory analysis via a geometric feature space approach

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

Rintoul, Mark D.; Wilson, Andrew T.

This study aimed to organize a body of trajectories in order to identify, search for and classify both common and uncommon behaviors among objects such as aircraft and ships. Existing comparison functions such as the Fréchet distance are computationally expensive and yield counterintuitive results in some cases. We propose an approach using feature vectors whose components represent succinctly the salient information in trajectories. These features incorporate basic information such as the total distance traveled and the distance between start/stop points as well as geometric features related to the properties of the convex hull, trajectory curvature and general distance geometry. Additionally,more » these features can generally be mapped easily to behaviors of interest to humans who are searching large databases. Most of these geometric features are invariant under rigid transformation. Furthermore, we demonstrate the use of different subsets of these features to identify trajectories similar to an exemplar, cluster a database of several hundred thousand trajectories and identify outliers.« less

Trajectory analysis via a geometric feature space approach

DOE PAGES

Rintoul, Mark D.; Wilson, Andrew T.

2015-10-05

This study aimed to organize a body of trajectories in order to identify, search for and classify both common and uncommon behaviors among objects such as aircraft and ships. Existing comparison functions such as the Fréchet distance are computationally expensive and yield counterintuitive results in some cases. We propose an approach using feature vectors whose components represent succinctly the salient information in trajectories. These features incorporate basic information such as the total distance traveled and the distance between start/stop points as well as geometric features related to the properties of the convex hull, trajectory curvature and general distance geometry. Additionally,more » these features can generally be mapped easily to behaviors of interest to humans who are searching large databases. Most of these geometric features are invariant under rigid transformation. Furthermore, we demonstrate the use of different subsets of these features to identify trajectories similar to an exemplar, cluster a database of several hundred thousand trajectories and identify outliers.« less

Permafrost features on Earth and Mars: Similarities, differences

NASA Technical Reports Server (NTRS)

Joens, H. P.

1985-01-01

Typical permafrost features on Earth are polygonal structures, pingos and soli-/gelifluxion features. In areas around the poles and in mountain ranges the precipitation accumulates to inland ice or ice streams. On Mars the same features were identified: polygonal features cover the larger part of the northern lowlands indicating probably an ice wedge-/sand wedge system or desiccation cracks. These features indicate the extend of large mud accumulations which seem to be related to large outflow events of the chaotic terrains. The shore line of this mud accumulation is indicated by a special set of relief types. In some areas large pingo-like hills were identified. In the vicinity of the largest martian volcano, Olympus Mons, the melting of underlying permafrost and/or ground ice led to the downslope sliding of large parts of the primary shield which formed the aureole around Olympus Mons. Glacier-like features are identified along the escarpment which separates the Southern Uplands from the Northern Lowlands.

Characterizing facial features in individuals with craniofacial microsomia: A systematic approach for clinical research.

PubMed

Heike, Carrie L; Wallace, Erin; Speltz, Matthew L; Siebold, Babette; Werler, Martha M; Hing, Anne V; Birgfeld, Craig B; Collett, Brent R; Leroux, Brian G; Luquetti, Daniela V

2016-11-01

Craniofacial microsomia (CFM) is a congenital condition with wide phenotypic variability, including hypoplasia of the mandible and external ear. We assembled a cohort of children with facial features within the CFM spectrum and children without known craniofacial anomalies. We sought to develop a standardized approach to assess and describe the facial characteristics of the study cohort, using multiple sources of information gathered over the course of this longitudinal study and to create case subgroups with shared phenotypic features. Participants were enrolled between 1996 and 2002. We classified the facial phenotype from photographs, ratings using a modified version of the Orbital, Ear, Mandible, Nerve, Soft tissue (OMENS) pictorial system, data from medical record abstraction, and health history questionnaires. The participant sample included 142 cases and 290 controls. The average age was 13.5 years (standard deviation, 1.3 years; range, 11.1-17.1 years). Sixty-one percent of cases were male, 74% were white non-Hispanic. Among cases, the most common features were microtia (66%) and mandibular hypoplasia (50%). Case subgroups with meaningful group definitions included: (1) microtia without other CFM-related features (n = 24), (2) microtia with mandibular hypoplasia (n = 46), (3) other combinations of CFM- related facial features (n = 51), and (4) atypical features (n = 21). We developed a standardized approach for integrating multiple data sources to phenotype individuals with CFM, and created subgroups based on clinically-meaningful, shared characteristics. We hope that this system can be used to explore associations between phenotype and clinical outcomes of children with CFM and to identify the etiology of CFM. Birth Defects Research (Part A) 106:915-926, 2016.© 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Informal settlement classification using point-cloud and image-based features from UAV data

NASA Astrophysics Data System (ADS)

Gevaert, C. M.; Persello, C.; Sliuzas, R.; Vosselman, G.

2017-03-01

Unmanned Aerial Vehicles (UAVs) are capable of providing very high resolution and up-to-date information to support informal settlement upgrading projects. In order to provide accurate basemaps, urban scene understanding through the identification and classification of buildings and terrain is imperative. However, common characteristics of informal settlements such as small, irregular buildings with heterogeneous roof material and large presence of clutter challenge state-of-the-art algorithms. Furthermore, it is of interest to analyse which fundamental attributes are suitable for describing these objects in different geographic locations. This work investigates how 2D radiometric and textural features, 2.5D topographic features, and 3D geometric features obtained from UAV imagery can be integrated to obtain a high classification accuracy in challenging classification problems for the analysis of informal settlements. UAV datasets from informal settlements in two different countries are compared in order to identify salient features for specific objects in heterogeneous urban environments. Findings show that the integration of 2D and 3D features leads to an overall accuracy of 91.6% and 95.2% respectively for informal settlements in Kigali, Rwanda and Maldonado, Uruguay.

A novel approach for fire recognition using hybrid features and manifold learning-based classifier

NASA Astrophysics Data System (ADS)

Zhu, Rong; Hu, Xueying; Tang, Jiajun; Hu, Sheng

2018-03-01

Although image/video based fire recognition has received growing attention, an efficient and robust fire detection strategy is rarely explored. In this paper, we propose a novel approach to automatically identify the flame or smoke regions in an image. It is composed to three stages: (1) a block processing is applied to divide an image into several nonoverlapping image blocks, and these image blocks are identified as suspicious fire regions or not by using two color models and a color histogram-based similarity matching method in the HSV color space, (2) considering that compared to other information, the flame and smoke regions have significant visual characteristics, so that two kinds of image features are extracted for fire recognition, where local features are obtained based on the Scale Invariant Feature Transform (SIFT) descriptor and the Bags of Keypoints (BOK) technique, and texture features are extracted based on the Gray Level Co-occurrence Matrices (GLCM) and the Wavelet-based Analysis (WA) methods, and (3) a manifold learning-based classifier is constructed based on two image manifolds, which is designed via an improve Globular Neighborhood Locally Linear Embedding (GNLLE) algorithm, and the extracted hybrid features are used as input feature vectors to train the classifier, which is used to make decision for fire images or non fire images. Experiments and comparative analyses with four approaches are conducted on the collected image sets. The results show that the proposed approach is superior to the other ones in detecting fire and achieving a high recognition accuracy and a low error rate.

Identifying molecular markers associated with stigma characteristics in rice

USDA-ARS?s Scientific Manuscript database

Stigma characteristics play essential roles in hybrid seed production of rice and marker-assisted breeding plays essential role because they are quantitatively inherited with single-flowered perfect spikelet. Ninety four accessions originated from 47 countries were selected from the USDA rice core c...

Skin cancer texture analysis of OCT images based on Haralick, fractal dimension, Markov random field features, and the complex directional field features

NASA Astrophysics Data System (ADS)

Raupov, Dmitry S.; Myakinin, Oleg O.; Bratchenko, Ivan A.; Zakharov, Valery P.; Khramov, Alexander G.

2016-10-01

In this paper, we propose a report about our examining of the validity of OCT in identifying changes using a skin cancer texture analysis compiled from Haralick texture features, fractal dimension, Markov random field method and the complex directional features from different tissues. Described features have been used to detect specific spatial characteristics, which can differentiate healthy tissue from diverse skin cancers in cross-section OCT images (B- and/or C-scans). In this work, we used an interval type-II fuzzy anisotropic diffusion algorithm for speckle noise reduction in OCT images. The Haralick texture features as contrast, correlation, energy, and homogeneity have been calculated in various directions. A box-counting method is performed to evaluate fractal dimension of skin probes. Markov random field have been used for the quality enhancing of the classifying. Additionally, we used the complex directional field calculated by the local gradient methodology to increase of the assessment quality of the diagnosis method. Our results demonstrate that these texture features may present helpful information to discriminate tumor from healthy tissue. The experimental data set contains 488 OCT-images with normal skin and tumors as Basal Cell Carcinoma (BCC), Malignant Melanoma (MM) and Nevus. All images were acquired from our laboratory SD-OCT setup based on broadband light source, delivering an output power of 20 mW at the central wavelength of 840 nm with a bandwidth of 25 nm. We obtained sensitivity about 97% and specificity about 73% for a task of discrimination between MM and Nevus.

Realistic Free-Spins Features Increase Preference for Slot Machines.

PubMed

Taylor, Lorance F; Macaskill, Anne C; Hunt, Maree J

2017-06-01

Despite increasing research into how the structural characteristics of slot machines influence gambling behaviour there have been no experimental investigations into the effect of free-spins bonus features-a structural characteristic that is commonly central to the design of slot machines. This series of three experiments investigated the free-spins feature using slot machine simulations to determine whether participants allocate more wagers to a machine with free spins, and, which components of free-spins features drive this preference. In each experiment, participants were exposed to two computer-simulated slot machines-one with a free-spins feature or similar bonus feature and one without. Participants then completed a testing phase where they could freely switch between the two machines. In Experiment 1, participants did not prefer the machine with a simple free-spins feature. In Experiment 2 the free-spins feature incorporated additional elements such as sounds, animations, and an increased win frequency; participants preferred to gamble on this machine. The Experiment 3 "bonus feature" machine resembled the free spins machine in Experiment 2 except spins were not free; participants showed a clear preference for this machine also. These findings indicate that (1) free-spins features have a major influence over machine choice and (2) the "freeness" of the free-spins bonus features is not an important driver of preference, contrary to self-report and interview research with gamblers.

Socioemotional characteristics of elementary school children identified as exhibiting social leadership qualities.

PubMed

Scharf, Miri; Mayseless, Ofra

2009-03-01

Elementary school teachers identified characteristics in 4 major socioemotional domains associated with children's social leadership: self-perception, social anxiety, attachment orientation with peers, and interpersonal goals and skills in close friendships. Participants were 260 4th- and 5th-grade students (126 boys, 134 girls) from 10 classes in a school in northern Israel. Social leadership skills were associated with positive self-perceptions in various domains, low social anxiety, secure orientation to peers, higher levels of relationship-maintenance goal, lower levels of revenge goal in close friendships, and-unexpectedly-lower levels of accommodation as a strategy to solve conflicts with a friend. Positive self-concept and attachment security were indirectly associated with leadership qualities through their significant association with prosocial orientation skills. The authors discuss these findings as reflecting an internalization of positive model of self and positive model of others in children who exhibit social leadership qualities. The authors also discuss implications of these qualities for school and class ecology, as well as the importance of culture.

A characteristic energy scale in glasses

NASA Astrophysics Data System (ADS)

Lerner, Edan; Bouchbinder, Eran

2018-06-01

Intrinsically generated structural disorder endows glassy materials with a broad distribution of various microscopic quantities—such as relaxation times and activation energies—without an obvious characteristic scale. At the same time, macroscopic glassy responses—such as Newtonian (linear) viscosity and nonlinear plastic deformation—are widely interpreted in terms of a characteristic energy scale, e.g., an effective temperature-dependent activation energy in Arrhenius relations. Nevertheless, despite its fundamental importance, such a characteristic energy scale has not been robustly identified. Inspired by the accumulated evidence regarding the crucial role played by disorder- and frustration-induced soft quasilocalized excitations in determining the properties and dynamics of glasses, we propose that the bulk average of the glass response to a localized force dipole defines such a characteristic energy scale. We show that this characteristic glassy energy scale features remarkable properties: (i) It increases dramatically in underlying inherent structures of equilibrium supercooled states approaching the glass transition temperature Tg, significantly surpassing the corresponding increase in the macroscopic shear modulus, dismissing the common view that structural variations in supercooled liquids upon vitrification are minute. (ii) Its variation with annealing and system size is very similar in magnitude and form to that of the energy of the softest non-phononic vibrational mode, thus establishing a nontrivial relation between a rare glassy fluctuation and a bulk average response. (iii) It exhibits striking dependence on spatial dimensionality and system size due to the long-ranged fields associated with quasilocalization, which are speculated to be related to peculiarities of the glass transition in two dimensions. In addition, we identify a truly static growing lengthscale associated with the characteristic glassy energy scale and discuss possible

A characteristic energy scale in glasses.

PubMed

Lerner, Edan; Bouchbinder, Eran

2018-06-07

Intrinsically generated structural disorder endows glassy materials with a broad distribution of various microscopic quantities-such as relaxation times and activation energies-without an obvious characteristic scale. At the same time, macroscopic glassy responses-such as Newtonian (linear) viscosity and nonlinear plastic deformation-are widely interpreted in terms of a characteristic energy scale, e.g., an effective temperature-dependent activation energy in Arrhenius relations. Nevertheless, despite its fundamental importance, such a characteristic energy scale has not been robustly identified. Inspired by the accumulated evidence regarding the crucial role played by disorder- and frustration-induced soft quasilocalized excitations in determining the properties and dynamics of glasses, we propose that the bulk average of the glass response to a localized force dipole defines such a characteristic energy scale. We show that this characteristic glassy energy scale features remarkable properties: (i) It increases dramatically in underlying inherent structures of equilibrium supercooled states approaching the glass transition temperature T g , significantly surpassing the corresponding increase in the macroscopic shear modulus, dismissing the common view that structural variations in supercooled liquids upon vitrification are minute. (ii) Its variation with annealing and system size is very similar in magnitude and form to that of the energy of the softest non-phononic vibrational mode, thus establishing a nontrivial relation between a rare glassy fluctuation and a bulk average response. (iii) It exhibits striking dependence on spatial dimensionality and system size due to the long-ranged fields associated with quasilocalization, which are speculated to be related to peculiarities of the glass transition in two dimensions. In addition, we identify a truly static growing lengthscale associated with the characteristic glassy energy scale and discuss possible

A multi-resolution analysis of lidar-DTMs to identify geomorphic processes from characteristic topographic length scales

NASA Astrophysics Data System (ADS)

Sangireddy, H.; Passalacqua, P.; Stark, C. P.

2013-12-01

Characteristic length scales are often present in topography, and they reflect the driving geomorphic processes. The wide availability of high resolution lidar Digital Terrain Models (DTMs) allows us to measure such characteristic scales, but new methods of topographic analysis are needed in order to do so. Here, we explore how transitions in probability distributions (pdfs) of topographic variables such as (log(area/slope)), defined as topoindex by Beven and Kirkby[1979], can be measured by Multi-Resolution Analysis (MRA) of lidar DTMs [Stark and Stark, 2001; Sangireddy et al.,2012] and used to infer dominant geomorphic processes such as non-linear diffusion and critical shear. We show this correlation between dominant geomorphic processes to characteristic length scales by comparing results from a landscape evolution model to natural landscapes. The landscape evolution model MARSSIM Howard[1994] includes components for modeling rock weathering, mass wasting by non-linear creep, detachment-limited channel erosion, and bedload sediment transport. We use MARSSIM to simulate steady state landscapes for a range of hillslope diffusivity and critical shear stresses. Using the MRA approach, we estimate modal values and inter-quartile ranges of slope, curvature, and topoindex as a function of resolution. We also construct pdfs at each resolution and identify and extract characteristic scale breaks. Following the approach of Tucker et al.,[2001], we measure the average length to channel from ridges, within the GeoNet framework developed by Passalacqua et al.,[2010] and compute pdfs for hillslope lengths at each scale defined in the MRA. We compare the hillslope diffusivity used in MARSSIM against inter-quartile ranges of topoindex and hillslope length scales, and observe power law relationships between the compared variables for simulated landscapes at steady state. We plot similar measures for natural landscapes and are able to qualitatively infer the dominant geomorphic

Computer-Aided Diagnosis for Breast Ultrasound Using Computerized BI-RADS Features and Machine Learning Methods.

PubMed

Shan, Juan; Alam, S Kaisar; Garra, Brian; Zhang, Yingtao; Ahmed, Tahira

2016-04-01

This work identifies effective computable features from the Breast Imaging Reporting and Data System (BI-RADS), to develop a computer-aided diagnosis (CAD) system for breast ultrasound. Computerized features corresponding to ultrasound BI-RADs categories were designed and tested using a database of 283 pathology-proven benign and malignant lesions. Features were selected based on classification performance using a "bottom-up" approach for different machine learning methods, including decision tree, artificial neural network, random forest and support vector machine. Using 10-fold cross-validation on the database of 283 cases, the highest area under the receiver operating characteristic (ROC) curve (AUC) was 0.84 from a support vector machine with 77.7% overall accuracy; the highest overall accuracy, 78.5%, was from a random forest with the AUC 0.83. Lesion margin and orientation were optimum features common to all of the different machine learning methods. These features can be used in CAD systems to help distinguish benign from worrisome lesions. Copyright © 2016 World Federation for Ultrasound in Medicine & Biology. All rights reserved.

TU-CD-BRB-10: 18F-FDG PET Image-Derived Tumor Features Highlight Altered Pathways Identified by Trancriptomic Analysis in Head and Neck Cancer

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

Tixier, F; INSERM UMR1101 LaTIM, Brest; Cheze-Le-Rest, C

2015-06-15

Purpose: Several quantitative features can be extracted from 18F-FDG PET images, such as standardized uptake values (SUVs), metabolic tumor volume (MTV), shape characterization (SC) or intra-tumor radiotracer heterogeneity quantification (HQ). Some of these features calculated from baseline 18F-FDG PET images have shown a prognostic and predictive clinical value. It has been hypothesized that these features highlight underlying tumor patho-physiological processes at smaller scales. The objective of this study was to investigate the ability of recovering alterations of signaling pathways from FDG PET image-derived features. Methods: 52 patients were prospectively recruited from two medical centers (Brest and Poitiers). All patients underwentmore » an FDG PET scan for staging and biopsies of both healthy and primary tumor tissues. Biopsies went through a transcriptomic analysis performed in four spates on 4×44k chips (Agilent™). Primary tumors were delineated in the PET images using the Fuzzy Locally Adaptive Bayesian algorithm and characterized using 10 features including SUVs, SC and HQ. A module network algorithm followed by functional annotation was exploited in order to link PET features with signaling pathways alterations. Results: Several PET-derived features were found to discriminate differentially expressed genes between tumor and healthy tissue (fold-change >2, p<0.01) into 30 co-regulated groups (p<0.05). Functional annotations applied to these groups of genes highlighted associations with well-known pathways involved in cancer processes, such as cell proliferation and apoptosis, as well as with more specific ones such as unsaturated fatty acids. Conclusion: Quantitative features extracted from baseline 18F-FDG PET images usually exploited only for diagnosis and staging, were identified in this work as being related to specific altered pathways and may show promise as tools for personalizing treatment decisions.« less

Synthesis, characteristics and thermoluminescent dosimetry features of γ-irradiated Ce doped CaF2 nanophosphor.

PubMed

Zahedifar, M; Sadeghi, E; Mozdianfard, M R; Habibi, E

2013-08-01

Nanoparticles of cerium doped calcium fluoride (CaF2:Ce) were synthesized for the first time using the hydrothermal method. The formation of nanostructures was confirmed by X-ray diffraction (XRD) patterns, indicating cubic lattice structure for the particles produced. Their shape and size were observed by scanning electron microscopy (SEM). Thermoluminescence characteristics were studied by having the samples irradiated by gamma rays of (60)Co source. The optimum thermal treatment of 400 °C for 30 min was found for the produced nanoparticles. The Tm-Tstop and computerized glow curve deconvolution (CGCD) methods, used to determine the number of component glow peaks and kinetic parameters, indicated seven overlapping glow peaks on the TL glow curve at approximately 394, 411, 425, 445, 556, 594 and 632 K. A linear dose response of up to 2000 Gy, was observed for the prepared nanoparticles. Maximum TL sensitivity was found at 0.4 mol% of Ce impurity. Other TL dosimetry features, including reusability and fading, were also presented and discussed. Copyright © 2013 Elsevier Ltd. All rights reserved.

CT colonography: influence of 3D viewing and polyp candidate features on interpretation with computer-aided detection.

PubMed

Shi, Rong; Schraedley-Desmond, Pamela; Napel, Sandy; Olcott, Eric W; Jeffrey, R Brooke; Yee, Judy; Zalis, Michael E; Margolis, Daniel; Paik, David S; Sherbondy, Anthony J; Sundaram, Padmavathi; Beaulieu, Christopher F

2006-06-01

To retrospectively determine if three-dimensional (3D) viewing improves radiologists' accuracy in classifying true-positive (TP) and false-positive (FP) polyp candidates identified with computer-aided detection (CAD) and to determine candidate polyp features that are associated with classification accuracy, with known polyps serving as the reference standard. Institutional review board approval and informed consent were obtained; this study was HIPAA compliant. Forty-seven computed tomographic (CT) colonography data sets were obtained in 26 men and 10 women (age range, 42-76 years). Four radiologists classified 705 polyp candidates (53 TP candidates, 652 FP candidates) identified with CAD; initially, only two-dimensional images were used, but these were later supplemented with 3D rendering. Another radiologist unblinded to colonoscopy findings characterized the features of each candidate, assessed colon distention and preparation, and defined the true nature of FP candidates. Receiver operating characteristic curves were used to compare readers' performance, and repeated-measures analysis of variance was used to test features that affect interpretation. Use of 3D viewing improved classification accuracy for three readers and increased the area under the receiver operating characteristic curve to 0.96-0.97 (P<.001). For TP candidates, maximum polyp width (P=.038), polyp height (P=.019), and preparation (P=.004) significantly affected accuracy. For FP candidates, colonic segment (P=.007), attenuation (P<.001), surface smoothness (P<.001), distention (P=.034), preparation (P<.001), and true nature of candidate lesions (P<.001) significantly affected accuracy. Use of 3D viewing increases reader accuracy in the classification of polyp candidates identified with CAD. Polyp size and examination quality are significantly associated with accuracy. Copyright (c) RSNA, 2006.

Thermal feature extraction of servers in a datacenter using thermal image registration

NASA Astrophysics Data System (ADS)

Liu, Hang; Ran, Jian; Xie, Ting; Gao, Shan

2017-09-01

Thermal cameras provide fine-grained thermal information that enhances monitoring and enables automatic thermal management in large datacenters. Recent approaches employing mobile robots or thermal camera networks can already identify the physical locations of hot spots. Other distribution information used to optimize datacenter management can also be obtained automatically using pattern recognition technology. However, most of the features extracted from thermal images, such as shape and gradient, may be affected by changes in the position and direction of the thermal camera. This paper presents a method for extracting the thermal features of a hot spot or a server in a container datacenter. First, thermal and visual images are registered based on textural characteristics extracted from images acquired in datacenters. Then, the thermal distribution of each server is standardized. The features of a hot spot or server extracted from the standard distribution can reduce the impact of camera position and direction. The results of experiments show that image registration is efficient for aligning the corresponding visual and thermal images in the datacenter, and the standardization procedure reduces the impacts of camera position and direction on hot spot or server features.

Vessel Classification in Cosmo-Skymed SAR Data Using Hierarchical Feature Selection

NASA Astrophysics Data System (ADS)

Makedonas, A.; Theoharatos, C.; Tsagaris, V.; Anastasopoulos, V.; Costicoglou, S.

2015-04-01

SAR based ship detection and classification are important elements of maritime monitoring applications. Recently, high-resolution SAR data have opened new possibilities to researchers for achieving improved classification results. In this work, a hierarchical vessel classification procedure is presented based on a robust feature extraction and selection scheme that utilizes scale, shape and texture features in a hierarchical way. Initially, different types of feature extraction algorithms are implemented in order to form the utilized feature pool, able to represent the structure, material, orientation and other vessel type characteristics. A two-stage hierarchical feature selection algorithm is utilized next in order to be able to discriminate effectively civilian vessels into three distinct types, in COSMO-SkyMed SAR images: cargos, small ships and tankers. In our analysis, scale and shape features are utilized in order to discriminate smaller types of vessels present in the available SAR data, or shape specific vessels. Then, the most informative texture and intensity features are incorporated in order to be able to better distinguish the civilian types with high accuracy. A feature selection procedure that utilizes heuristic measures based on features' statistical characteristics, followed by an exhaustive research with feature sets formed by the most qualified features is carried out, in order to discriminate the most appropriate combination of features for the final classification. In our analysis, five COSMO-SkyMed SAR data with 2.2m x 2.2m resolution were used to analyse the detailed characteristics of these types of ships. A total of 111 ships with available AIS data were used in the classification process. The experimental results show that this method has good performance in ship classification, with an overall accuracy reaching 83%. Further investigation of additional features and proper feature selection is currently in progress.

Identification and characteristics of victims of violence identified by emergency physicians, triage nurses, and the police

PubMed Central

Howe, A; Crilly, M

2002-01-01

Objectives: The objectives of the study were threefold—to evaluate the identification and characteristics of victims of assault who attend an accident and emergency (A&E) department; to compare the total number of assaults recorded in the A&E department with the number recorded by the police; and to assess a system for collecting the location and method of assault. Setting: The A&E department of Chorley and South Ribble Hospital Trust, Lancashire, England. Methods: A three month prospective study was performed. Victims of violence recorded on computer by doctors at discharge were compared with those identified at initial nurse triage. A comparison of police data with the A&E data relating to Chorley residents was performed. Additional information on the method and location of assault was also collected. Results: During the period 305 (2.6%) of the patients attending A&E were identified as having been assaulted. Of the 305 individuals, 236 (77%) were identified by a doctor while 173 (57%) such patients were identified by a triage nurse. A&E identified twice the number of assaults involving Chorley residents as the police. Both men and women were most likely to have been injured on the street (44% and 37% respectively), although a greater proportion of women were injured at home (24%) than men (10%). The majority of injuries were sustained by blows from fists, feet, and heads (73%). Conclusions: A&E doctors identify significantly more patients as the victims of violence than do nurses at triage. Using A&E data identifies assaulted individuals not identified by the police. Computer systems can be used in A&E to provide a more complete picture of the occurrence of violence in the community. PMID:12460971

Analysis of wheezes using wavelet higher order spectral features.

PubMed

Taplidou, Styliani A; Hadjileontiadis, Leontios J

2010-07-01

Wheezes are musical breath sounds, which usually imply an existing pulmonary obstruction, such as asthma and chronic obstructive pulmonary disease (COPD). Although many studies have addressed the problem of wheeze detection, a limited number of scientific works has focused in the analysis of wheeze characteristics, and in particular, their time-varying nonlinear characteristics. In this study, an effort is made to reveal and statistically analyze the nonlinear characteristics of wheezes and their evolution over time, as they are reflected in the quadratic phase coupling of their harmonics. To this end, the continuous wavelet transform (CWT) is used in combination with third-order spectra to define the analysis domain, where the nonlinear interactions of the harmonics of wheezes and their time variations are revealed by incorporating instantaneous wavelet bispectrum and bicoherence, which provide with the instantaneous biamplitude and biphase curves. Based on this nonlinear information pool, a set of 23 features is proposed for the nonlinear analysis of wheezes. Two complementary perspectives, i.e., general and detailed, related to average performance and to localities, respectively, were used in the construction of the feature set, in order to embed trends and local behaviors, respectively, seen in the nonlinear interaction of the harmonic elements of wheezes over time. The proposed feature set was evaluated on a dataset of wheezes, acquired from adult patients with diagnosed asthma and COPD from a lung sound database. The statistical evaluation of the feature set revealed discrimination ability between the two pathologies for all data subgroupings. In particular, when the total breathing cycle was examined, all 23 features, but one, showed statistically significant difference between the COPD and asthma pathologies, whereas for the subgroupings of inspiratory and expiratory phases, 18 out of 23 and 22 out of 23 features exhibited discrimination power, respectively

Low complexity feature extraction for classification of harmonic signals

NASA Astrophysics Data System (ADS)

William, Peter E.

In this dissertation, feature extraction algorithms have been developed for extraction of characteristic features from harmonic signals. The common theme for all developed algorithms is the simplicity in generating a significant set of features directly from the time domain harmonic signal. The features are a time domain representation of the composite, yet sparse, harmonic signature in the spectral domain. The algorithms are adequate for low-power unattended sensors which perform sensing, feature extraction, and classification in a standalone scenario. The first algorithm generates the characteristic features using only the duration between successive zero-crossing intervals. The second algorithm estimates the harmonics' amplitudes of the harmonic structure employing a simplified least squares method without the need to estimate the true harmonic parameters of the source signal. The third algorithm, resulting from a collaborative effort with Daniel White at the DSP Lab, University of Nebraska-Lincoln, presents an analog front end approach that utilizes a multichannel analog projection and integration to extract the sparse spectral features from the analog time domain signal. Classification is performed using a multilayer feedforward neural network. Evaluation of the proposed feature extraction algorithms for classification through the processing of several acoustic and vibration data sets (including military vehicles and rotating electric machines) with comparison to spectral features shows that, for harmonic signals, time domain features are simpler to extract and provide equivalent or improved reliability over the spectral features in both the detection probabilities and false alarm rate.

SU-F-R-24: Identifying Prognostic Imaging Biomarkers in Early Stage Lung Cancer Using Radiomics

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

Zeng, X; Wu, J; Cui, Y

2016-06-15

Purpose: Patients diagnosed with early stage lung cancer have favorable outcomes when treated with surgery or stereotactic radiotherapy. However, a significant proportion (∼20%) of patients will develop metastatic disease and eventually die of the disease. The purpose of this work is to identify quantitative imaging biomarkers from CT for predicting overall survival in early stage lung cancer. Methods: In this institutional review board-approved HIPPA-compliant retrospective study, we retrospectively analyzed the diagnostic CT scans of 110 patients with early stage lung cancer. Data from 70 patients were used for training/discovery purposes, while those of remaining 40 patients were used for independentmore » validation. We extracted 191 radiomic features, including statistical, histogram, morphological, and texture features. Cox proportional hazard regression model, coupled with the least absolute shrinkage and selection operator (LASSO), was used to predict overall survival based on the radiomic features. Results: The optimal prognostic model included three image features from the Law’s feature and wavelet texture. In the discovery cohort, this model achieved a concordance index or CI=0.67, and it separated the low-risk from high-risk groups in predicting overall survival (hazard ratio=2.72, log-rank p=0.007). In the independent validation cohort, this radiomic signature achieved a CI=0.62, and significantly stratified the low-risk and high-risk groups in terms of overall survival (hazard ratio=2.20, log-rank p=0.042). Conclusion: We identified CT imaging characteristics associated with overall survival in early stage lung cancer. If prospectively validated, this could potentially help identify high-risk patients who might benefit from adjuvant systemic therapy.« less

Characteristic Features of Double Layers in Rotating, Magnetized Plasma Contaminated with Dust Grains with Varying Charges

NASA Astrophysics Data System (ADS)

Paul, Jaydeep; Nag, Apratim; Devi, Karabi; Das, Himadri Sekhar

2018-03-01

The evolution and the characteristic features of double layers in a plasma under slow rotation and contaminated with dust grains with varying charges under the effect of an external magnetic field are studied. The Coriolis force resulting from the slow rotation is responsible for the generation of an equivalent magnetic field. A comparatively new pseudopotential approach has been used to derive the small amplitude double layers. The effect of the relative electron-ion concentration, as well as the temperature ratio, on the formation of the double layers has also been investigated. The study reveals that compressive, as well as rarefactive, double layers can be made to co-exist in plasma by controlling the dust charge fluctuation effect supplemented by variations of the plasma constituents. The effectiveness of slow rotation in causing double layers to exist has also emanated from the study. The results obtained could be of interest because of their possible applications in both laboratories and space.

Natural and Artificial Playing Fields: Characteristics and Safety Features.

ERIC Educational Resources Information Center

Schmidt, Roger C., Ed.; Hoerner, Earl F., Ed.; Milner, Edward M., Ed.; Morehouse, C. A., Ed.

These papers are on the subjects of playing field standards, surface traction, testing and correlation to actual field experience, and state-of-the-art natural and artificial surfaces. The papers, presented at the Symposium on the Characteristics and Safety of Playing Surfaces (Artificial and Natural) for Field Sports in 1998, cover the…

Feature-opinion pair identification of product reviews in Chinese: a domain ontology modeling method

NASA Astrophysics Data System (ADS)

Yin, Pei; Wang, Hongwei; Guo, Kaiqiang

2013-03-01

With the emergence of the new economy based on social media, a great amount of consumer feedback on particular products are conveyed through wide-spreading product online reviews, making opinion mining a growing interest for both academia and industry. According to the characteristic mode of expression in Chinese, this research proposes an ontology-based linguistic model to identify the basic appraisal expression in Chinese product reviews-"feature-opinion pair (FOP)." The product-oriented domain ontology is constructed automatically at first, then algorithms to identify FOP are designed by mapping product features and opinions to the conceptual space of the domain ontology, and finally comparative experiments are conducted to evaluate the model. Experimental results indicate that the performance of the proposed approach in this paper is efficient in obtaining a more accurate result compared to the state-of-art algorithms. Furthermore, through identifying and analyzing FOPs, the unstructured product reviews are converted into structured and machine-sensible expression, which provides valuable information for business application. This paper contributes to the related research in opinion mining by developing a solid foundation for further sentiment analysis at a fine-grained level and proposing a general way for automatic ontology construction.

2-DE combined with two-layer feature selection accurately establishes the origin of oolong tea.

PubMed

Chien, Han-Ju; Chu, Yen-Wei; Chen, Chi-Wei; Juang, Yu-Min; Chien, Min-Wei; Liu, Chih-Wei; Wu, Chia-Chang; Tzen, Jason T C; Lai, Chien-Chen

2016-11-15

Taiwan is known for its high quality oolong tea. Because of high consumer demand, some tea manufactures mix lower quality leaves with genuine Taiwan oolong tea in order to increase profits. Robust scientific methods are, therefore, needed to verify the origin and quality of tea leaves. In this study, we investigated whether two-dimensional gel electrophoresis (2-DE) and nanoscale liquid chromatography/tandem mass spectroscopy (nano-LC/MS/MS) coupled with a two-layer feature selection mechanism comprising information gain attribute evaluation (IGAE) and support vector machine feature selection (SVM-FS) are useful in identifying characteristic proteins that can be used as markers of the original source of oolong tea. Samples in this study included oolong tea leaves from 23 different sources. We found that our method had an accuracy of 95.5% in correctly identifying the origin of the leaves. Overall, our method is a novel approach for determining the origin of oolong tea leaves. Copyright © 2016 Elsevier Ltd. All rights reserved.

Distinct features distinguishing IgG4-related disease from multicentric Castleman’s disease

PubMed Central

Sasaki, Takanori; Akiyama, Mitsuhiro; Kaneko, Yuko; Mori, Takehiko; Yasuoka, Hidekata; Suzuki, Katsuya; Yamaoka, Kunihiro; Okamoto, Shinichiro; Takeuchi, Tsutomu

2017-01-01

Objectives Differentiating IgG4-related disease (IgG4-RD) from multicentric Castleman’s disease (MCD) is challenging because both diseases present high serum IgG4. The objective of this study is to clarify the differences in characteristics and identify a clinically useful approach to differentiate these two diseases. Methods Forty-five consecutive patients with untreated active IgG4-RD and 33 patients with MCD were included in this study, who visited our institution from January 2000 to August 2016. The clinical and laboratory findings for the patients of the two diseases were compared. Various combinations of the distinctive findings were evaluated to identify the most efficient differentiating features between IgG4-RD and MCD. Results The levels of serum IgG4 were not different between the two diseases. Orbits, lacrimal glands, salivary glands or pancreas were involved in 88.9% of IgG4-RD cases and only in 3.0% of MCD cases. All MCD cases involved lymph nodes. Atopic history was characteristic for IgG4-RD. The levels of C reactive protein (CRP) with a cut-off of 0.80 mg/dL and IgA with a cut-off of 330 mg/dL were the most distinctive. The combination of ‘Orbits, lacrimal glands, salivary glands or pancreas involvement, atopic history, or non-involvement of lymph node’ and ‘CRP ≤ 0.8 mg/dL or IgA ≤ 330 mg/dL’ yielded the probability of 97.8% in IgG4-RD, while that of 3.0 % in patients with MCD. Conclusions Our study revealed distinct features between IgG4-RD and MCD. Differentiating between the diseases based on those distinct features, including distribution of organ involvement, atopic history, levels of IgA and CRP, was a useful approach. PMID:28959455

The method for froth floatation condition recognition based on adaptive feature weighted

NASA Astrophysics Data System (ADS)

Wang, Jieran; Zhang, Jun; Tian, Jinwen; Zhang, Daimeng; Liu, Xiaomao

2018-03-01

The fusion of foam characteristics can play a complementary role in expressing the content of foam image. The weight of foam characteristics is the key to make full use of the relationship between the different features. In this paper, an Adaptive Feature Weighted Method For Froth Floatation Condition Recognition is proposed. Foam features without and with weights are both classified by using support vector machine (SVM).The classification accuracy and optimal equaling algorithm under the each ore grade are regarded as the result of the adaptive feature weighting algorithm. At the same time the effectiveness of adaptive weighted method is demonstrated.

[Premature outflow tract ventricular contraction combined with complete bundle branch block: the characteristic electrocardiographic and ablation target potential features].

PubMed

Di, C Y; Wan, Z; Li, K; Ding, Y S; Lin, W H

2017-12-01

Objective: To explore the characteristics of electrocardiogram(ECG) and target potential features of premature ventricular contraction (PVC) in patients with complete left/right bundle branch block (CL/RBBB) and compare with those without CL/RBBB. Methods: A retrospective analysis was done in 8 outflow tract PVC patients with CL/RBBB, who successfully underwent radiofrequency ablation from August 2009 to June 2017. According to the bundle branch block chamber, patients were divided into the complete right bundle branch block (CRBBB) group ( n= 4) and the complete left bundle branch block (CLBBB) group ( n= 4). The control group were those who successfully underwent ablation at the same position as the above two groups but without CL/RBBB. The characteristics of ECG and target potential features were compared among groups. Results: One case in the CRBBB group was successfully ablated in the great cardiac vein with precordial R/S>1 transition at V(1) and one case in the CLBBB group was successfully ablated in the right coronary cusp with precordial R/S>1 transition at V(2), while other 6 cases were all with precordial R/S>1 transition at lead V(4). Precordial R/S>1 transition was not later than sinus rhythm (SR) in the CLBBB group. No statistical difference was found in the QRS complex duration between SR and PVC in the CL/RBBB patients [(134.38±23.80)ms vs (156.75±25.93)ms, P> 0.05], while statistical difference was shown in the control group [(92.63±5.76)ms vs (140.25±15.97)ms, P< 0.05]. Conclusion: Bundle branch block can lead to misjudgment of PVC origin with CL/RBBB during sinus rhythm, thus the origin chamber of the PVC should be determined according to the mapping and ablation result.

Identifying individual- and population-level characteristics that influence rates of risky alcohol consumption in regional communities.

PubMed

Breen, Courtney; Shakeshaft, Anthony; Sanson-Fisher, Rob; D'Este, Catherine; Mattick, Richard P; Gilmour, Stuart

2014-02-01

To examine the extent to which individual- and community- level characteristics account for differences in risky alcohol consumption. A cross-sectional postal survey of 2,977 randomly selected individuals from 20 regional communities in NSW, Australia. Individuals drinking at harmful levels on the AUDIT and for risk of harm in the short term and long-term were identified. Multi-level modelling of the correlates of risky alcohol consumption at the individual and community level was conducted. There were differences between communities in alcohol consumption patterns. Being male, unmarried and reporting worse health were significant individual-level correlates for drinking at levels for risk of harm in the long term. The number of GPs (+) and police (-) were significant community characteristics. Being younger (≤25), unmarried, Australian born and with a larger income was associated with drinking at levels for risk of harm in the short term and harmful drinking on the AUDIT. The number of hotels and clubs was positively associated with drinking at levels for risk of harm in the short term. Rates of risky drinking vary significantly between communities and both individual and community characteristics are significantly associated with risky alcohol consumption. A combination of individual- and population-level interventions, tailored to the risk profile of individual communities, is most likely to be optimally effective. © 2014 The Authors. ANZJPH © 2014 Public Health Association of Australia.

Characteristics and Prognosis of Pacemaker-Identified New-Onset Atrial Fibrillation in Japanese People.

PubMed

Ogino, Yutaka; Ishikawa, Toshiyuki; Ishigami, Tomoaki; Matsumoto, Katsumi; Hosoda, Junya; Iguchi, Kouhei; Matsushita, Hirooki; Taguchi, Yuka; Horiguchi, Yoriko; Kimura, Kazuo

2017-05-25

The characteristics and prognosis of implanted pacemaker-identified new-onset atrial fibrillation (AF) in Japanese people has not been well evaluated.Methods and Results:A total of 395 consecutive patients with newly implanted pacemakers were retrospectively analyzed between January 2010 and December 2015 at Yokohama City University Hospital. Patients with a prior history of AF, VVI mode pacemaker, congenital heart disease, severe valvular heart disease, and cardiovascular surgery before pacemaker implantation were excluded. Among the remaining patients, 44 (21.3%) developed new AF during follow-up (mean follow-up, 1,115±651 days; range, 9-2,176 days). Patients with new-onset AF had a significantly higher CHADS 2 score (2.09±1.27 vs. 1.31±1.08, P<0.001) and CHA 2 DS 2 -VASc score (3.00±1.39 vs. 2.26±1.19, P<0.001) compared with those without new-onset AF. On Cox regression analysis only age at implantation was significantly correlated with new-onset AF. Interestingly, the incidence of hospitalization due to heart failure was significantly higher in the new-onset AF than in the without new-onset AF group. A total of 21.3% of pacemaker-implanted patients with high CHADS 2 and CHA 2 DS 2 -VASc scores developed new-onset AF during a mean follow-up of 3.1 years; and pacemaker-identified AF was associated with an increased risk of worsening heart failure.

A Pilot Study Using a Web Survey to Identify Characteristics That Influence Hypogonadal Men to Initiate Testosterone Replacement Therapy.

PubMed

Rosen, Raymond C; Seftel, Allen D; Ruff, Dustin D; Muram, David

2018-05-01

Men with hypogonadism (HG) who choose testosterone replacement therapy (TRT) may have distinct characteristics that provide insight as to why they may/may not initiate therapy. The aim of the current study was to identify trends in patient characteristics and attitudes in men diagnosed with HG who initiated TRT (TRT+) compared with men who were diagnosed with HG but did not initiate TRT (TRT-). The market research-based online survey conducted between 2012 and 2013 included patients from a Federated Sample, a commercially available panel of patients with diverse medical conditions. The current analysis was composed of two groups: TRT+ ( n = 155) and TRT- ( n = 157). Patient demographics, clinical characteristics, and attitudes toward HG and TRT were examined as potential predictors of primary adherence in men with HG; cohorts were compared by using Fisher's exact test. Significant associations among sexual orientation, relationship status, educational level, presence of comorbid erectile dysfunction, area of residence, and TRT initiation were present ( p ≤ .05). College-educated, heterosexual, married men with comorbid erectile dysfunction living in suburban and urban areas were more likely to initiate treatment. The most bothersome symptoms reported were lack of energy (90% vs. 81%, p = .075), decreased strength and endurance (86% vs. 76%, p = .077), and deterioration in work performance (52% vs. 31%, p = .004); lack of energy prompted men to seek help. Patients (48%) in the TRT+ group were more knowledgeable regarding HG as compared with TRT- respondents (14%, p < .001), and most men obtained their information from a health care professional (89% vs. 82%, p = .074). The current analysis identified distinct demographic and clinical characteristics and attitudes among TRT users compared with men who were diagnosed with HG yet remained untreated.

Textural features for radar image analysis

NASA Technical Reports Server (NTRS)

Shanmugan, K. S.; Narayanan, V.; Frost, V. S.; Stiles, J. A.; Holtzman, J. C.

1981-01-01

Texture is seen as an important spatial feature useful for identifying objects or regions of interest in an image. While textural features have been widely used in analyzing a variety of photographic images, they have not been used in processing radar images. A procedure for extracting a set of textural features for characterizing small areas in radar images is presented, and it is shown that these features can be used in classifying segments of radar images corresponding to different geological formations.

Designing attractive gamification features for collaborative storytelling websites.

PubMed

Hsu, Shang Hwa; Chang, Jen-Wei; Lee, Chun-Chia

2013-06-01

Gamification design is considered as the predictor of collaborative storytelling websites' success. Although aforementioned studies have mentioned a broad range of factors that may influence gamification, they neither depicted the actual design features nor relative attractiveness among them. This study aims to identify attractive gamification features for collaborative storytelling websites. We first constructed a hierarchical system structure of gamification design of collaborative storytelling websites and conducted a focus group interview with eighteen frequent users to identify 35gamification features. After that, this study determined the relative attractiveness of these gamification features by administrating an online survey to 6333 collaborative storytelling websites users. The results indicated that the top 10 most attractive gamification features could account for more than 50% of attractiveness among these 35 gamification features. The feature of unpredictable time pressure is important to website users, yet not revealed in previous relevant studies. Implications of the findings were discussed.

Plaque echodensity and textural features are associated with histologic carotid plaque instability.

PubMed

Doonan, Robert J; Gorgui, Jessica; Veinot, Jean P; Lai, Chi; Kyriacou, Efthyvoulos; Corriveau, Marc M; Steinmetz, Oren K; Daskalopoulou, Stella S

2016-09-01

Carotid plaque echodensity and texture features predict cerebrovascular symptomatology. Our purpose was to determine the association of echodensity and textural features obtained from a digital image analysis (DIA) program with histologic features of plaque instability as well as to identify the specific morphologic characteristics of unstable plaques. Patients scheduled to undergo carotid endarterectomy were recruited and underwent carotid ultrasound imaging. DIA was performed to extract echodensity and textural features using Plaque Texture Analysis software (LifeQ Medical Ltd, Nicosia, Cyprus). Carotid plaque surgical specimens were obtained and analyzed histologically. Principal component analysis (PCA) was performed to reduce imaging variables. Logistic regression models were used to determine if PCA variables and individual imaging variables predicted histologic features of plaque instability. Image analysis data from 160 patients were analyzed. Individual imaging features of plaque echolucency and homogeneity were associated with a more unstable plaque phenotype on histology. These results were independent of age, sex, and degree of carotid stenosis. PCA reduced 39 individual imaging variables to five PCA variables. PCA1 and PCA2 were significantly associated with overall plaque instability on histology (both P = .02), whereas PCA3 did not achieve statistical significance (P = .07). DIA features of carotid plaques are associated with histologic plaque instability as assessed by multiple histologic features. Importantly, unstable plaques on histology appear more echolucent and homogeneous on ultrasound imaging. These results are independent of stenosis, suggesting that image analysis may have a role in refining the selection of patients who undergo carotid endarterectomy. Copyright © 2016 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

Feature Extraction Assessment Study.

DTIC Science & Technology

1984-11-01

base in the form of orthophotos , control manuscripts, . or maps or charts; aids to feature identification such as im- agery (rectified and unrectified...manually delineated (i.e. , drawn by * hand) on a feature manuscript which may be a mylar overlay on an orthophoto or other control base. Once delineated...partition of tiled constant gray level regions, with addi- tive noise in each, it is not clear that any segmentation tech- nique would identify each

The Association Between CMV Viremia or Endoscopic Features and Histopathological Characteristics of CMV Colitis in Patients with Underlying Ulcerative Colitis.

PubMed

Yang, Hong; Zhou, Weixun; Lv, Hong; Wu, Dongsheng; Feng, Yunlu; Shu, Huijun; Jin, Meng; Hu, Lingling; Wang, Qiang; Wu, Dong; Chen, Jie; Qian, Jiaming

2017-05-01

Cytomegalovirus (CMV) infection has been shown to be related to severe or steroid-refractory ulcerative colitis (UC) flare-ups. The aim of this study was to evaluate the endoscopic and pathological characteristics of CMV colitis in patients with UC and to assess the predictive value of the endoscopic and pathological features of CMV colitis. A total of 50 consecutive UC patients with CMV infection who were admitted to Peking Union Medical College Hospital from 2010 to 2015 were enrolled in this study. Twenty-five UC patients with CMV infection (50.0%) had concurrent CMV colitis. When the cutoff value was set at 1150 copies, the sensitivity and specificity of blood CMV DNAq polymerase chain reaction for predicting CMV colitis were 44.4% and 78.9%, respectively. A higher proportion of endoscopic punched-out ulcers, irregular ulcers, and cobblestone-like appearance were observed among the patients in the CMV colitis group than those in the non-CMV colitis group (52.0% versus 20.0%, 60.0% versus 16.0%, and 20.0% versus 0%, respectively, P < 0.05). The number of CMV inclusion bodies per high-power field was significantly higher in those with punch-out ulcerations (25.7% versus 60.0%, P < 0.05). A higher grade of pathological inflammation was observed in the CMV colitis group than in the control group (68.0% versus 44.0%). Characteristic endoscopic features with punch-out ulcers and high CMV viremia load may be useful for predicting the presence of CMV colitis in histology. Punch-out ulcers were found to be associated with a higher number of inclusion bodies on histology, suggesting a role of targeted biopsy for endoscopist.

Innovation in Aerodynamic Design Features of Soviet Missiles

NASA Technical Reports Server (NTRS)

Spearman, M. Leroy

2006-01-01

Wind tunnel investigations of some tactical and strategic missile systems developed by the former Soviet Union have been included in the basic missile research programs of the NACA/NASA. Studies of the Soviet missiles sometimes revealed innovative design features that resulted in unusual or unexpected aerodynamic characteristics. In some cases these characteristics have been such that the measured performance of the missile exceeds what might have been predicted. In other cases some unusual design features have been found that would alleviate what might otherwise have been a serious aerodynamic problem. In some designs, what has appeared to be a lack of refinement has proven to be a matter of expediency. It is a purpose of this paper to describe some examples of unusual design features of some Soviet missiles and to illustrate the effectiveness of the design features on the aerodynamic behavior of the missile. The paper draws on the experience of the author who for over 60 years was involved in the aerodynamic wind tunnel testing of aircraft and missiles with the NACA/NASA.

Histogram of gradient and binarized statistical image features of wavelet subband-based palmprint features extraction

NASA Astrophysics Data System (ADS)

Attallah, Bilal; Serir, Amina; Chahir, Youssef; Boudjelal, Abdelwahhab

2017-11-01

Palmprint recognition systems are dependent on feature extraction. A method of feature extraction using higher discrimination information was developed to characterize palmprint images. In this method, two individual feature extraction techniques are applied to a discrete wavelet transform of a palmprint image, and their outputs are fused. The two techniques used in the fusion are the histogram of gradient and the binarized statistical image features. They are then evaluated using an extreme learning machine classifier before selecting a feature based on principal component analysis. Three palmprint databases, the Hong Kong Polytechnic University (PolyU) Multispectral Palmprint Database, Hong Kong PolyU Palmprint Database II, and the Delhi Touchless (IIDT) Palmprint Database, are used in this study. The study shows that our method effectively identifies and verifies palmprints and outperforms other methods based on feature extraction.

The characteristic ultrasound features of specific types of ovarian pathology (Review)

PubMed Central

SAYASNEH, AHMAD; EKECHI, CHRISTINE; FERRARA, LAURA; KAIJSER, JEROEN; STALDER, CATRIONA; SUR, SHYAMALY; TIMMERMAN, DIRK; BOURNE, TOM

2015-01-01

Characterizing ovarian masses enables patients with malignancy to be appropriately triaged for treatment by subspecialist gynecological oncologists, which has been shown to optimize care and improve survival. Furthermore, correctly classifying benign masses facilitates the selection of patients with ovarian pathology that may either not require intervention, or be suitable for minimal access surgery if intervention is required. However, predicting whether a mass is benign or malignant is not the only clinically relevant information that we need to know before deciding on appropriate treatment. Knowing the specific histology of a mass is becoming of increasing importance as management options become more tailored to the individual patient. For example predicting a mucinous borderline tumor gives the opportunity for fertility sparing surgery, and will highlight the need for further gastrointestinal assessment. For benign disease, predicting the presence of an endometrioma and possible deeply infiltrating endometriosis is important when considering both who should perform and the extent of surgery. An examiner’s subjective assessment of the morphological and vascular features of a mass using ultrasonography has been shown to be highly effective for predicting whether a mass is benign or malignant. Many masses also have features that enable a reliable diagnosis of the specific pathology of a particular mass to be made. In this narrative review we aim to describe the typical morphological features seen on ultrasound of different adnexal masses and illustrate these by showing representative ultrasound images. PMID:25406094

Tensor-driven extraction of developmental features from varying paediatric EEG datasets.

PubMed

Kinney-Lang, Eli; Spyrou, Loukianos; Ebied, Ahmed; Chin, Richard Fm; Escudero, Javier

2018-05-21

Constant changes in developing children's brains can pose a challenge in EEG dependant technologies. Advancing signal processing methods to identify developmental differences in paediatric populations could help improve function and usability of such technologies. Taking advantage of the multi-dimensional structure of EEG data through tensor analysis may offer a framework for extracting relevant developmental features of paediatric datasets. A proof of concept is demonstrated through identifying latent developmental features in resting-state EEG. Approach. Three paediatric datasets (n = 50, 17, 44) were analyzed using a two-step constrained parallel factor (PARAFAC) tensor decomposition. Subject age was used as a proxy measure of development. Classification used support vector machines (SVM) to test if PARAFAC identified features could predict subject age. The results were cross-validated within each dataset. Classification analysis was complemented by visualization of the high-dimensional feature structures using t-distributed Stochastic Neighbour Embedding (t-SNE) maps. Main Results. Development-related features were successfully identified for the developmental conditions of each dataset. SVM classification showed the identified features could accurately predict subject at a significant level above chance for both healthy and impaired populations. t-SNE maps revealed suitable tensor factorization was key in extracting the developmental features. Significance. The described methods are a promising tool for identifying latent developmental features occurring throughout childhood EEG. © 2018 IOP Publishing Ltd.

Sensor-oriented feature usability evaluation in fingerprint segmentation

NASA Astrophysics Data System (ADS)

Li, Ying; Yin, Yilong; Yang, Gongping

2013-06-01

Existing fingerprint segmentation methods usually process fingerprint images captured by different sensors with the same feature or feature set. We propose to improve the fingerprint segmentation result in view of an important fact that images from different sensors have different characteristics for segmentation. Feature usability evaluation, which means to evaluate the usability of features to find the personalized feature or feature set for different sensors to improve the performance of segmentation. The need for feature usability evaluation for fingerprint segmentation is raised and analyzed as a new issue. To address this issue, we present a decision-tree-based feature-usability evaluation method, which utilizes a C4.5 decision tree algorithm to evaluate and pick the best suitable feature or feature set for fingerprint segmentation from a typical candidate feature set. We apply the novel method on the FVC2002 database of fingerprint images, which are acquired by four different respective sensors and technologies. Experimental results show that the accuracy of segmentation is improved, and time consumption for feature extraction is dramatically reduced with selected feature(s).

Strategy of Trade-Reliable Featured Product Supporting Regional Innovation Systems

NASA Astrophysics Data System (ADS)

Riskiawan, H. Y.; Purnomo, B. H.; Abdurahman, A.; Hariono, B.; Puspitasari, T. D.

2018-01-01

Pacitan, Ponorogo, and Magetan had planned the development of featured products as contained in the Medium Term Development Plan (MTDP) until 2020. The focus of development is almost similar to featured products derived from agribusiness, food processing, handycrafts, and tourism. The geographical proximity results characteristics of natural resources and social culture have similarities, including the type of featured products, constraints, problems, and opportunities for development. Given the characteristics and the support system of some featured products contained in these three regions have a lot in common and their functional interactions involving actors from across the region, it is necessary to develop cross-jurisdictional policy. The resulting strategy should be able to support the development of Regional Innovation System (RIS). The purpose of this research is 1) Determining featured product cross-regional between Pacitan regency; Ponorogo and Magetan districts in support of RIS development; and 2) Designing a featured product development strategy using supply chain management in order to drive the local economy. Based on the results of research conducted, featured products across the region that have potentiality to be developed are: processed products of “janggelan” leather products, and woven bamboo.

The growth of optically variable features on banknotes

NASA Astrophysics Data System (ADS)

Lancaster, Ian M.; Mitchell, Astrid

2004-06-01

Public verification features are part of a matrix of security features on banknotes which allow the authenticity of legitimate banknotes to be established. They are characterised by being overt and easy to verify -- no examination tool or equipment is required even though the devices themselves are invariably highly sophisticated. Recent developments, though, combine overt and covert elements which may reqire inspection tools. Traditionally, banknote issuers were reluctant to involve the general public in the checking of banknotes, preferring to rely on those employed to handle them, experts and machinery to authenticate the various (normally undisclosed) features. This has now changed as the ability to counterfeit has moved from those highly skilled in printing to anyone with a scanner and computer -- the incidence of counterfeiting has grown exponentially in the last decade. Three techniques for what can be categorized as public verification features have been used for banknotes for many decades and continue to provide a barrier to counterfeiting: (1) the optical effects of watermarks; (2) the appearance and tactile characteristics of cylinder mould-made paper; (3) the tactile characteristics of intaglio print. Since the 1980s the emergence of threads and optically variable features have added to the available features which can be utilized on banknotes for public verification purposes. OVDs fall broadly into the two categories of diffraction and color shift. Products which utilize the former include holograms, kinegrams and other devices originated with similar techniques and bearing a variety of proprietary names, but collectively known as diffractive optically variable image devices (DOVIDs). All share the fundamental characteristic of changing in appearance according to the viewing angle, providing an effective barrier to the increasingly common use of digital reprographic technology as a counterfeiting tool as well as a simple means for verification by the

Robustness of radiomic breast features of benign lesions and luminal A cancers across MR magnet strengths

NASA Astrophysics Data System (ADS)

Whitney, Heather M.; Drukker, Karen; Edwards, Alexandra; Papaioannou, John; Giger, Maryellen L.

2018-02-01

Radiomics features extracted from breast lesion images have shown potential in diagnosis and prognosis of breast cancer. As clinical institutions transition from 1.5 T to 3.0 T magnetic resonance imaging (MRI), it is helpful to identify robust features across these field strengths. In this study, dynamic contrast-enhanced MR images were acquired retrospectively under IRB/HIPAA compliance, yielding 738 cases: 241 and 124 benign lesions imaged at 1.5 T and 3.0 T and 231 and 142 luminal A cancers imaged at 1.5 T and 3.0 T, respectively. Lesions were segmented using a fuzzy C-means method. Extracted radiomic values for each group of lesions by cancer status and field strength of acquisition were compared using a Kolmogorov-Smirnov test for the null hypothesis that two groups being compared came from the same distribution, with p-values being corrected for multiple comparisons by the Holm-Bonferroni method. Two shape features, one texture feature, and three enhancement variance kinetics features were found to be potentially robust. All potentially robust features had areas under the receiver operating characteristic curve (AUC) statistically greater than 0.5 in the task of distinguishing between lesion types (range of means 0.57-0.78). The significant difference in voxel size between field strength of acquisition limits the ability to affirm more features as robust or not robust according to field strength alone, and inhomogeneities in static field strength and radiofrequency field could also have affected the assessment of kinetic curve features as robust or not. Vendor-specific image scaling could have also been a factor. These findings will contribute to the development of radiomic signatures that use features identified as robust across field strength.

The use of mobile applications to support self-management for people with asthma: a systematic review of controlled studies to identify features associated with clinical effectiveness and adherence.

PubMed

Hui, Chi Yan; Walton, Robert; McKinstry, Brian; Jackson, Tracy; Parker, Richard; Pinnock, Hilary

2017-05-01

Telehealth is promoted as a strategy to support self-management of long-term conditions. The aim of this systematic review is to identify which information and communication technology features implemented in mobile apps to support asthma self-management are associated with adoption, adherence to usage, and clinical effectiveness. We systematically searched 9 databases, scanned reference lists, and undertook manual searches (January 2000 to April 2016). We include randomized controlled trials (RCTs) and quasiexperimental studies with adults. All eligible papers were assessed for quality, and we extracted data on the features included, health-related outcomes (asthma control, exacerbation rate), process/intermediate outcomes (adherence to monitoring or treatment, self-efficacy), and level of adoption of and adherence to use of technology. Meta-analysis and narrative synthesis were used. We included 12 RCTs employing a range of technologies. A meta-analysis (n = 3) showed improved asthma control (mean difference -0.25 [95% CI, -0.37 to -0.12]). Included studies incorporated 10 features grouped into 7 categories (education, monitoring/electronic diary, action plans, medication reminders/prompts, facilitating professional support, raising patient awareness of asthma control, and decision support for professionals). The most successful interventions included multiple features, but effects on health-related outcomes were inconsistent. No studies explicitly reported adoption of and adherence to the technology system. Meta-analysis of data from 3 trials showed improved asthma control, though overall the clinical effectiveness of apps, typically incorporating multiple features, varied. Further studies are needed to identify the features that are associated with adoption of and adherence to use of the mobile app and those that improve health outcomes. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All

An evaluation of applicability of seismic refraction method in identifying shallow archaeological features A case study at archaeological site

NASA Astrophysics Data System (ADS)

Jahangardi, Morteza; Hafezi Moghaddas, Naser; Keivan Hosseini, Sayyed; Garazhian, Omran

2015-04-01

We applied the seismic refraction method at archaeological site, Tepe Damghani located in Sabzevar, NE of Iran, in order to determine the structures of archaeological interests. This pre-historical site has special conditions with respect to geographical location and geomorphological setting, so it is an urban archaeological site, and in recent years it has been used as an agricultural field. In spring and summer of 2012, the third season of archaeological excavation was carried out. Test trenches of excavations in this site revealed that cultural layers were often disturbed adversely due to human activities such as farming and road construction in recent years. Conditions of archaeological cultural layers in southern and eastern parts of Tepe are slightly better, for instance, in test trench 3×3 m²1S03, third test trench excavated in the southern part of Tepe, an adobe in situ architectural structure was discovered that likely belongs to cultural features of a complex with 5 graves. After conclusion of the third season of archaeological excavation, all of the test trenches were filled with the same soil of excavated test trenches. Seismic refraction method was applied with12 channels of P geophones in three lines with a geophone interval of 0.5 meter and a 1.5 meter distance between profiles on test trench 1S03. The goal of this operation was evaluation of applicability of seismic method in identification of archaeological features, especially adobe wall structures. Processing of seismic data was done with the seismic software, SiesImager. Results were presented in the form of seismic section for every profile, so that identification of adobe wall structures was achieved hardly. This could be due to that adobe wall had been built with the same materials of the natural surrounding earth. Thus, there is a low contrast and it has an inappropriate effect on seismic processing and identifying of archaeological features. Hence the result could be that application of

An energy ratio feature extraction method for optical fiber vibration signal

NASA Astrophysics Data System (ADS)

Sheng, Zhiyong; Zhang, Xinyan; Wang, Yanping; Hou, Weiming; Yang, Dan

2018-03-01

The intrusion events in the optical fiber pre-warning system (OFPS) are divided into two types which are harmful intrusion event and harmless interference event. At present, the signal feature extraction methods of these two types of events are usually designed from the view of the time domain. However, the differences of time-domain characteristics for different harmful intrusion events are not obvious, which cannot reflect the diversity of them in detail. We find that the spectrum distribution of different intrusion signals has obvious differences. For this reason, the intrusion signal is transformed into the frequency domain. In this paper, an energy ratio feature extraction method of harmful intrusion event is drawn on. Firstly, the intrusion signals are pre-processed and the power spectral density (PSD) is calculated. Then, the energy ratio of different frequency bands is calculated, and the corresponding feature vector of each type of intrusion event is further formed. The linear discriminant analysis (LDA) classifier is used to identify the harmful intrusion events in the paper. Experimental results show that the algorithm improves the recognition rate of the intrusion signal, and further verifies the feasibility and validity of the algorithm.

Semantic Feature Distinctiveness and Frequency

ERIC Educational Resources Information Center

Lamb, Katherine M.

2012-01-01

Lexical access is the process in which basic components of meaning in language, the lexical entries (words) are activated. This activation is based on the organization and representational structure of the lexical entries. Semantic features of words, which are the prominent semantic characteristics of a word concept, provide important information…

Evaluation of wavelet spectral features in pathological detection and discrimination of yellow rust and powdery mildew in winter wheat with hyperspectral reflectance data

NASA Astrophysics Data System (ADS)

Shi, Yue; Huang, Wenjiang; Zhou, Xianfeng

2017-04-01

Hyperspectral absorption features are important indicators of characterizing plant biophysical variables for the automatic diagnosis of crop diseases. Continuous wavelet analysis has proven to be an advanced hyperspectral analysis technique for extracting absorption features; however, specific wavelet features (WFs) and their relationship with pathological characteristics induced by different infestations have rarely been summarized. The aim of this research is to determine the most sensitive WFs for identifying specific pathological lesions from yellow rust and powdery mildew in winter wheat, based on 314 hyperspectral samples measured in field experiments in China in 2002, 2003, 2005, and 2012. The resultant WFs could be used as proxies to capture the major spectral absorption features caused by infestation of yellow rust or powdery mildew. Multivariate regression analysis based on these WFs outperformed conventional spectral features in disease detection; meanwhile, a Fisher discrimination model exhibited considerable potential for generating separable clusters for each infestation. Optimal classification returned an overall accuracy of 91.9% with a Kappa of 0.89. This paper also emphasizes the WFs and their relationship with pathological characteristics in order to provide a foundation for the further application of this approach in monitoring winter wheat diseases at the regional scale.

Acute erythroblastic leukemia presenting as acute undifferentiated leukemia: a report of two cases with ultrastructural features.

PubMed

Reiffers, J; Bernard, P; Larrue, J; Dachary, D; David, B; Boisseau, M; Broustet, A

1985-01-01

This report describes two elderly patients with acute leukemia in which blast cells were undifferentiated with conventional light microscopy (L.M.) and cytochemistry. Blast cells were identified as belonging to the erythroblastic line by their ultrastructural features: glycogen deposits, lipidic vacuoles, cytoplasmic ferritin molecules and rhopheocytotic invagination. Moreover, blast cells were surrounding a central macrophage. Thus, these two patients had acute erythroblastic leukemia which differs from erythroleukemia (M6 of FAB classification) in which blast cells present myeloblastic characteristics.

Unsupervised consensus cluster analysis of [18F]-fluoroethyl-L-tyrosine positron emission tomography identified textural features for the diagnosis of pseudoprogression in high-grade glioma

PubMed Central

Kebir, Sied; Khurshid, Zain; Gaertner, Florian C.; Essler, Markus; Hattingen, Elke; Fimmers, Rolf; Scheffler, Björn; Herrlinger, Ulrich; Bundschuh, Ralph A.; Glas, Martin

2017-01-01

Rationale Timely detection of pseudoprogression (PSP) is crucial for the management of patients with high-grade glioma (HGG) but remains difficult. Textural features of O-(2-[18F]fluoroethyl)-L-tyrosine positron emission tomography (FET-PET) mirror tumor uptake heterogeneity; some of them may be associated with tumor progression. Methods Fourteen patients with HGG and suspected of PSP underwent FET-PET imaging. A set of 19 conventional and textural FET-PET features were evaluated and subjected to unsupervised consensus clustering. The final diagnosis of true progression vs. PSP was based on follow-up MRI using RANO criteria. Results Three robust clusters have been identified based on 10 predominantly textural FET-PET features. None of the patients with PSP fell into cluster 2, which was associated with high values for textural FET-PET markers of uptake heterogeneity. Three out of 4 patients with PSP were assigned to cluster 3 that was largely associated with low values of textural FET-PET features. By comparison, tumor-to-normal brain ratio (TNRmax) at the optimal cutoff 2.1 was less predictive of PSP (negative predictive value 57% for detecting true progression, p=0.07 vs. 75% with cluster 3, p=0.04). Principal Conclusions Clustering based on textural O-(2-[18F]fluoroethyl)-L-tyrosine PET features may provide valuable information in assessing the elusive phenomenon of pseudoprogression. PMID:28030820

Unsupervised consensus cluster analysis of [18F]-fluoroethyl-L-tyrosine positron emission tomography identified textural features for the diagnosis of pseudoprogression in high-grade glioma.

PubMed

Kebir, Sied; Khurshid, Zain; Gaertner, Florian C; Essler, Markus; Hattingen, Elke; Fimmers, Rolf; Scheffler, Björn; Herrlinger, Ulrich; Bundschuh, Ralph A; Glas, Martin

2017-01-31

Timely detection of pseudoprogression (PSP) is crucial for the management of patients with high-grade glioma (HGG) but remains difficult. Textural features of O-(2-[18F]fluoroethyl)-L-tyrosine positron emission tomography (FET-PET) mirror tumor uptake heterogeneity; some of them may be associated with tumor progression. Fourteen patients with HGG and suspected of PSP underwent FET-PET imaging. A set of 19 conventional and textural FET-PET features were evaluated and subjected to unsupervised consensus clustering. The final diagnosis of true progression vs. PSP was based on follow-up MRI using RANO criteria. Three robust clusters have been identified based on 10 predominantly textural FET-PET features. None of the patients with PSP fell into cluster 2, which was associated with high values for textural FET-PET markers of uptake heterogeneity. Three out of 4 patients with PSP were assigned to cluster 3 that was largely associated with low values of textural FET-PET features. By comparison, tumor-to-normal brain ratio (TNRmax) at the optimal cutoff 2.1 was less predictive of PSP (negative predictive value 57% for detecting true progression, p=0.07 vs. 75% with cluster 3, p=0.04). Clustering based on textural O-(2-[18F]fluoroethyl)-L-tyrosine PET features may provide valuable information in assessing the elusive phenomenon of pseudoprogression.

Feasibility of feature-based indexing, clustering, and search of clinical trials: A case study of breast cancer trials from ClinicalTrials.gov

PubMed Central

Boland, Mary Regina; Miotto, Riccardo; Gao, Junfeng; Weng, Chunhua

2013-01-01

Summary Background When standard therapies fail, clinical trials provide experimental treatment opportunities for patients with drug-resistant illnesses or terminal diseases. Clinical Trials can also provide free treatment and education for individuals who otherwise may not have access to such care. To find relevant clinical trials, patients often search online; however, they often encounter a significant barrier due to the large number of trials and in-effective indexing methods for reducing the trial search space. Objectives This study explores the feasibility of feature-based indexing, clustering, and search of clinical trials and informs designs to automate these processes. Methods We decomposed 80 randomly selected stage III breast cancer clinical trials into a vector of eligibility features, which were organized into a hierarchy. We clustered trials based on their eligibility feature similarities. In a simulated search process, manually selected features were used to generate specific eligibility questions to filter trials iteratively. Results We extracted 1,437 distinct eligibility features and achieved an inter-rater agreement of 0.73 for feature extraction for 37 frequent features occurring in more than 20 trials. Using all the 1,437 features we stratified the 80 trials into six clusters containing trials recruiting similar patients by patient-characteristic features, five clusters by disease-characteristic features, and two clusters by mixed features. Most of the features were mapped to one or more Unified Medical Language System (UMLS) concepts, demonstrating the utility of named entity recognition prior to mapping with the UMLS for automatic feature extraction. Conclusions It is feasible to develop feature-based indexing and clustering methods for clinical trials to identify trials with similar target populations and to improve trial search efficiency. PMID:23666475

Feasibility of feature-based indexing, clustering, and search of clinical trials. A case study of breast cancer trials from ClinicalTrials.gov.

PubMed

Boland, M R; Miotto, R; Gao, J; Weng, C

2013-01-01

When standard therapies fail, clinical trials provide experimental treatment opportunities for patients with drug-resistant illnesses or terminal diseases. Clinical Trials can also provide free treatment and education for individuals who otherwise may not have access to such care. To find relevant clinical trials, patients often search online; however, they often encounter a significant barrier due to the large number of trials and in-effective indexing methods for reducing the trial search space. This study explores the feasibility of feature-based indexing, clustering, and search of clinical trials and informs designs to automate these processes. We decomposed 80 randomly selected stage III breast cancer clinical trials into a vector of eligibility features, which were organized into a hierarchy. We clustered trials based on their eligibility feature similarities. In a simulated search process, manually selected features were used to generate specific eligibility questions to filter trials iteratively. We extracted 1,437 distinct eligibility features and achieved an inter-rater agreement of 0.73 for feature extraction for 37 frequent features occurring in more than 20 trials. Using all the 1,437 features we stratified the 80 trials into six clusters containing trials recruiting similar patients by patient-characteristic features, five clusters by disease-characteristic features, and two clusters by mixed features. Most of the features were mapped to one or more Unified Medical Language System (UMLS) concepts, demonstrating the utility of named entity recognition prior to mapping with the UMLS for automatic feature extraction. It is feasible to develop feature-based indexing and clustering methods for clinical trials to identify trials with similar target populations and to improve trial search efficiency.

Neighbourhood typology based on virtual audit of environmental obesogenic characteristics.

PubMed

Feuillet, T; Charreire, H; Roda, C; Ben Rebah, M; Mackenbach, J D; Compernolle, S; Glonti, K; Bárdos, H; Rutter, H; De Bourdeaudhuij, I; McKee, M; Brug, J; Lakerveld, J; Oppert, J-M

2016-01-01

Virtual audit (using tools such as Google Street View) can help assess multiple characteristics of the physical environment. This exposure assessment can then be associated with health outcomes such as obesity. Strengths of virtual audit include collection of large amount of data, from various geographical contexts, following standard protocols. Using data from a virtual audit of obesity-related features carried out in five urban European regions, the current study aimed to (i) describe this international virtual audit dataset and (ii) identify neighbourhood patterns that can synthesize the complexity of such data and compare patterns across regions. Data were obtained from 4,486 street segments across urban regions in Belgium, France, Hungary, the Netherlands and the UK. We used multiple factor analysis and hierarchical clustering on principal components to build a typology of neighbourhoods and to identify similar/dissimilar neighbourhoods, regardless of region. Four neighbourhood clusters emerged, which differed in terms of food environment, recreational facilities and active mobility features, i.e. the three indicators derived from factor analysis. Clusters were unequally distributed across urban regions. Neighbourhoods mostly characterized by a high level of outdoor recreational facilities were predominantly located in Greater London, whereas neighbourhoods characterized by high urban density and large amounts of food outlets were mostly located in Paris. Neighbourhoods in the Randstad conurbation, Ghent and Budapest appeared to be very similar, characterized by relatively lower residential densities, greener areas and a very low percentage of streets offering food and recreational facility items. These results provide multidimensional constructs of obesogenic characteristics that may help target at-risk neighbourhoods more effectively than isolated features. © 2016 World Obesity.

Identifying Evolutionary Patterns of SMBHS Using Characteristic Variables of the Quasar AGNs of eBOSS

NASA Astrophysics Data System (ADS)

Martens, Sarah Katherine; Wilcots, Eric M.

2017-01-01

We investigate the redshift distribution and environmental conditions of quasar AGNs. The importance of studying these relationships is to use the evolutionary patterns of QSOs (features with many quantifiable characteristics) to gain insight into the evolutionary paths and environmental dependencies of their host super massive black holes (SMBHs), which are more difficult to study directly. We employ specific redshift bins within Data Release 13 of the Sloan Digital Sky Survey's (SDSS) Extended Baryonic Oscillation Spectroscopic Survey (eBOSS) and begin with a sample of 595,025 QSOs. We then incorporate overlapping data sets: The Very Large Array Faint Images of the Radio Sky at Twenty-Centimeters (FIRST) which provides the HI detected QSOs in our sample, along with the galaxy group and cluster sample from Tempel, Tago, Liivamägi 2012 which we cross referenced with our QSO sample to see which of them exist in group environments. The addition of these data sets allows us to create a more holistic view of the processes at work within our sample of QSOs. Understanding the HI presence in different evolutionary phases will allow us to draw conclusions on potential star formation rates or quenching, and by understanding the populations of QSOs in galaxy groups we can determine if QSOs exist overwhelmingly in one particular environment and how environmental conditions effect the other characteristics of QSOs. Overall we provide a multi-faceted analysis of some of the evolutionary patterns and cycles of the eBOSS Data Release 13 QSOs and their implications on the evolutionary paths of SMBHs. This work was supported by the SDSS Research Experience for Undergraduates program, which is funded by a grant from Sloan Foundation to the Astrophysical Research Consortium.

Classification of Informal Settlements Through the Integration of 2d and 3d Features Extracted from Uav Data

NASA Astrophysics Data System (ADS)

Gevaert, C. M.; Persello, C.; Sliuzas, R.; Vosselman, G.

2016-06-01

Unmanned Aerial Vehicles (UAVs) are capable of providing very high resolution and up-to-date information to support informal settlement upgrading projects. In order to provide accurate basemaps, urban scene understanding through the identification and classification of buildings and terrain is imperative. However, common characteristics of informal settlements such as small, irregular buildings with heterogeneous roof material and large presence of clutter challenge state-of-the-art algorithms. Especially the dense buildings and steeply sloped terrain cause difficulties in identifying elevated objects. This work investigates how 2D radiometric and textural features, 2.5D topographic features, and 3D geometric features obtained from UAV imagery can be integrated to obtain a high classification accuracy in challenging classification problems for the analysis of informal settlements. It compares the utility of pixel-based and segment-based features obtained from an orthomosaic and DSM with point-based and segment-based features extracted from the point cloud to classify an unplanned settlement in Kigali, Rwanda. Findings show that the integration of 2D and 3D features leads to higher classification accuracies.

Exploring the e-cigarette e-commerce marketplace: Identifying Internet e-cigarette marketing characteristics and regulatory gaps.

PubMed

Mackey, Tim K; Miner, Angela; Cuomo, Raphael E

2015-11-01

The electronic cigarette (e-cigarette) market is maturing into a billion-dollar industry. Expansion includes new channels of access not sufficiently assessed, including Internet sales of e-cigarettes. This study identifies unique e-cigarette Internet vendor characteristics, including geographic location, promotional strategies, use of social networking, presence/absence of age verification, and consumer warning representation. We performed structured Internet search engine queries and used inclusion/exclusion criteria to identify e-cigarette vendors. We then conducted content analysis of characteristics of interest. Our examination yielded 57 e-cigarette Internet vendors including 54.4% (n=31) that sold exclusively online. The vast majority of websites (96.5%, n=55) were located in the U.S. Vendors used a variety of sales promotion strategies to market e-cigarettes including 70.2% (n=40) that used more than one social network service (SNS) and 42.1% (n=24) that used more than one promotional sales strategies. Most vendors (68.4%, n=39) displayed one or more health warnings on their website, but often displayed them in smaller font or in their terms and conditions. Additionally, 35.1% (n=20) of vendors did not have any detectable age verification process. E-cigarette Internet vendors are actively engaged in various promotional activities to increase the appeal and presence of their products online. In the absence of FDA regulations specific to the Internet, the e-cigarette e-commerce marketplace is likely to grow. This digital environment poses unique challenges requiring targeted policy-making including robust online age verification, monitoring of SNS marketing, and greater scrutiny of certain forms of marketing promotional practices. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Identifying epibenthic habitats on the Seco de los Olivos Seamount: Species assemblages and environmental characteristics

NASA Astrophysics Data System (ADS)

De la Torriente, A.; Serrano, A.; Fernández-Salas, L. M.; García, M.; Aguilar, R.

2018-05-01

High habitat diversity was observed on the Seco de los Olivos Seamount (SW Mediterranean Sea), a Site of Community Importance belonging to the Spanish marine Natura 2000 Network. Thirteen epibenthic habitats were identified by analysing 55 Remotely Operated Vehicle (ROV) transects from 76 m to 700 m depth and derived data from multibeam bathymetry and high resolution seismic profiles. Habitat identification was based on a combination of assemblages of habitat-forming species and the environmental characteristics supporting their distribution. Depth and slope were identified as the main significant factors structuring epibenthic assemblages. The high diversity and patchiness of habitats found on the Seco de los Olivos Seamount can be explained by the high environmental variability resulting from its wide geomorphologic diversity, where flat summits, steep flanks, rocky outcrops and sedimentary moats are combined. The distribution of benthic habitats at this seamount is likely a combination of suitable ecological conditions, local recruitment, feeding strategies and attachment mechanisms. Knowledge on the occurrence of habitats in areas of natural importance is crucial to species and habitats conservation and to develop proper monitoring and management programs aimed at fulfilling European regulation requirements.

Automatic Extraction of Planetary Image Features

NASA Technical Reports Server (NTRS)

Troglio, G.; LeMoigne, J.; Moser, G.; Serpico, S. B.; Benediktsson, J. A.

2009-01-01

With the launch of several Lunar missions such as the Lunar Reconnaissance Orbiter (LRO) and Chandrayaan-1, a large amount of Lunar images will be acquired and will need to be analyzed. Although many automatic feature extraction methods have been proposed and utilized for Earth remote sensing images, these methods are not always applicable to Lunar data that often present low contrast and uneven illumination characteristics. In this paper, we propose a new method for the extraction of Lunar features (that can be generalized to other planetary images), based on the combination of several image processing techniques, a watershed segmentation and the generalized Hough Transform. This feature extraction has many applications, among which image registration.

Palm Vein Verification Using Multiple Features and Locality Preserving Projections

PubMed Central

Bu, Wei; Wu, Xiangqian; Zhao, Qiushi

2014-01-01

Biometrics is defined as identifying people by their physiological characteristic, such as iris pattern, fingerprint, and face, or by some aspects of their behavior, such as voice, signature, and gesture. Considerable attention has been drawn on these issues during the last several decades. And many biometric systems for commercial applications have been successfully developed. Recently, the vein pattern biometric becomes increasingly attractive for its uniqueness, stability, and noninvasiveness. A vein pattern is the physical distribution structure of the blood vessels underneath a person's skin. The palm vein pattern is very ganglion and it shows a huge number of vessels. The attitude of the palm vein vessels stays in the same location for the whole life and its pattern is definitely unique. In our work, the matching filter method is proposed for the palm vein image enhancement. New palm vein features extraction methods, global feature extracted based on wavelet coefficients and locality preserving projections (WLPP), and local feature based on local binary pattern variance and locality preserving projections (LBPV_LPP) have been proposed. Finally, the nearest neighbour matching method has been proposed that verified the test palm vein images. The experimental result shows that the EER to the proposed method is 0.1378%. PMID:24693230

Palm vein verification using multiple features and locality preserving projections.

PubMed

Al-Juboori, Ali Mohsin; Bu, Wei; Wu, Xiangqian; Zhao, Qiushi

2014-01-01

Biometrics is defined as identifying people by their physiological characteristic, such as iris pattern, fingerprint, and face, or by some aspects of their behavior, such as voice, signature, and gesture. Considerable attention has been drawn on these issues during the last several decades. And many biometric systems for commercial applications have been successfully developed. Recently, the vein pattern biometric becomes increasingly attractive for its uniqueness, stability, and noninvasiveness. A vein pattern is the physical distribution structure of the blood vessels underneath a person's skin. The palm vein pattern is very ganglion and it shows a huge number of vessels. The attitude of the palm vein vessels stays in the same location for the whole life and its pattern is definitely unique. In our work, the matching filter method is proposed for the palm vein image enhancement. New palm vein features extraction methods, global feature extracted based on wavelet coefficients and locality preserving projections (WLPP), and local feature based on local binary pattern variance and locality preserving projections (LBPV_LPP) have been proposed. Finally, the nearest neighbour matching method has been proposed that verified the test palm vein images. The experimental result shows that the EER to the proposed method is 0.1378%.

Information Technology-Based Interventions to Improve Drug-Drug Interaction Outcomes: A Systematic Review on Features and Effects.

PubMed

Nabovati, Ehsan; Vakili-Arki, Hasan; Taherzadeh, Zhila; Saberi, Mohammad Reza; Medlock, Stephanie; Abu-Hanna, Ameen; Eslami, Saeid

2017-01-01

The purpose of this systematic review was to identify features and effects of information technology (IT)-based interventions on outcomes related to drug-drug interactions (DDI outcomes). A literature search was conducted in Medline, EMBASE, and the Cochrane Library for published English-language studies. Studies were included if a main outcome was related to DDIs, the intervention involved an IT-based system, and the study design was experimental or observational with controls. Study characteristics, including features and effects of IT-based interventions, were extracted. Nineteen studies comprising five randomized controlled trials (RCT), five non-randomized controlled trials (NRCT) and nine observational studies with controls (OWC) were included. Sixty-four percent of prescriber-directed interventions, and all non-prescriber interventions, were effective. Each of the following characteristics corresponded to groups of studies of which a majority were effective: automatic provision of recommendations within the providers' workflow, intervention at the time of decision-making, integration into other systems, and requiring the reason for not following the recommendations. Only two studies measured clinical outcomes: an RCT that showed no significant improvement and an OWC that showed improvement, but did not statistically assess the effect. Most studies that measured surrogate outcomes (e.g. potential DDIs) and other outcomes (e.g. adherence to alerts) showed improvements. IT-based interventions improve surrogate clinical outcomes and adherence to DDI alerts. However, there is lack of robust evidence about their effectiveness on clinical outcomes. It is recommended that researchers consider the identified features of effective interventions in the design of interventions and evaluate the effectiveness on DDI outcomes, particularly clinical outcomes.

Neuroimaging Feature Terminology: A Controlled Terminology for the Annotation of Brain Imaging Features

PubMed Central

Iyappan, Anandhi; Younesi, Erfan; Redolfi, Alberto; Vrooman, Henri; Khanna, Shashank; Frisoni, Giovanni B.; Hofmann-Apitius, Martin

2017-01-01

Ontologies and terminologies are used for interoperability of knowledge and data in a standard manner among interdisciplinary research groups. Existing imaging ontologies capture general aspects of the imaging domain as a whole such as methodological concepts or calibrations of imaging instruments. However, none of the existing ontologies covers the diagnostic features measured by imaging technologies in the context of neurodegenerative diseases. Therefore, the Neuro-Imaging Feature Terminology (NIFT) was developed to organize the knowledge domain of measured brain features in association with neurodegenerative diseases by imaging technologies. The purpose is to identify quantitative imaging biomarkers that can be extracted from multi-modal brain imaging data. This terminology attempts to cover measured features and parameters in brain scans relevant to disease progression. In this paper, we demonstrate the systematic retrieval of measured indices from literature and how the extracted knowledge can be further used for disease modeling that integrates neuroimaging features with molecular processes. PMID:28731430

Neuroimaging Feature Terminology: A Controlled Terminology for the Annotation of Brain Imaging Features.

PubMed

Iyappan, Anandhi; Younesi, Erfan; Redolfi, Alberto; Vrooman, Henri; Khanna, Shashank; Frisoni, Giovanni B; Hofmann-Apitius, Martin

2017-01-01

Ontologies and terminologies are used for interoperability of knowledge and data in a standard manner among interdisciplinary research groups. Existing imaging ontologies capture general aspects of the imaging domain as a whole such as methodological concepts or calibrations of imaging instruments. However, none of the existing ontologies covers the diagnostic features measured by imaging technologies in the context of neurodegenerative diseases. Therefore, the Neuro-Imaging Feature Terminology (NIFT) was developed to organize the knowledge domain of measured brain features in association with neurodegenerative diseases by imaging technologies. The purpose is to identify quantitative imaging biomarkers that can be extracted from multi-modal brain imaging data. This terminology attempts to cover measured features and parameters in brain scans relevant to disease progression. In this paper, we demonstrate the systematic retrieval of measured indices from literature and how the extracted knowledge can be further used for disease modeling that integrates neuroimaging features with molecular processes.

Social-cognitive functioning and schizotypal characteristics.

PubMed

Meyer, Joseph; Shean, Glenn

2006-05-01

The authors examined the relationship between social cognition and a feature of schizotypal personality referred to as magical ideation, defined broadly as the presence and intensity of illogical beliefs about causality and the nature of reality. The measures of social cognition used in this study were the Character Intention Task (CIT) and the adult version of the Reading the Mind in the Eyes Test. Regression analyses indicated that understanding of character intentions, as measured by CIT scores, and ability to identify emotions on the Eyes test were related to non-realistic beliefs. Principal components analysis of the Magical Ideation Scale generated 3 factors: Occult Beliefs, Non-Realism, and New Age Ideas. Results indicated that impaired understanding of character intentions and ability to identify emotions on the Eyes test were related to non-realistic beliefs. Understanding the cognitive impairments associated with schizotypal characteristics can facilitate development of more targeted therapeutic interventions.

LICRE: unsupervised feature correlation reduction for lipidomics.

PubMed

Wong, Gerard; Chan, Jeffrey; Kingwell, Bronwyn A; Leckie, Christopher; Meikle, Peter J

2014-10-01

Recent advances in high-throughput lipid profiling by liquid chromatography electrospray ionization tandem mass spectrometry (LC-ESI-MS/MS) have made it possible to quantify hundreds of individual molecular lipid species (e.g. fatty acyls, glycerolipids, glycerophospholipids, sphingolipids) in a single experimental run for hundreds of samples. This enables the lipidome of large cohorts of subjects to be profiled to identify lipid biomarkers significantly associated with disease risk, progression and treatment response. Clinically, these lipid biomarkers can be used to construct classification models for the purpose of disease screening or diagnosis. However, the inclusion of a large number of highly correlated biomarkers within a model may reduce classification performance, unnecessarily inflate associated costs of a diagnosis or a screen and reduce the feasibility of clinical translation. An unsupervised feature reduction approach can reduce feature redundancy in lipidomic biomarkers by limiting the number of highly correlated lipids while retaining informative features to achieve good classification performance for various clinical outcomes. Good predictive models based on a reduced number of biomarkers are also more cost effective and feasible from a clinical translation perspective. The application of LICRE to various lipidomic datasets in diabetes and cardiovascular disease demonstrated superior discrimination in terms of the area under the receiver operator characteristic curve while using fewer lipid markers when predicting various clinical outcomes. The MATLAB implementation of LICRE is available from http://ww2.cs.mu.oz.au/∼gwong/LICRE © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Histopathological features of Proteus syndrome.

PubMed

Hoey, S E H; Eastwood, D; Monsell, F; Kangesu, L; Harper, J I; Sebire, N J

2008-05-01

Proteus syndrome is a rare, sporadic overgrowth disorder for which the underlying genetic defect remains unknown. Although the clinical course is well-described there is no systematic histopathological description of the lesional pathology. To describe the histopathological features encountered in a series of patients with Proteus syndrome from a single centre. Patients with Proteus syndrome who had undergone therapeutic surgical resection or biopsy were identified from a database and the histopathological findings were reviewed, with particular regard to descriptive features of the underlying tissue abnormality. There were 18 surgical specimens from nine patients, median age 4 years (range 1-9), classified into four main categories: soft-tissue swellings (lipomatous lesions), vascular anomalies (vascular malformation and haemangioma), macrodactyly (hamartomatous overgrowth) and others (sebaceous naevus and nonspecific features). In all cases, the clinical features of overgrowth were due to increased amounts of disorganized tissue, indicating a hamartomatous-type defect in which normal tissue constituents were present, but with an abnormal distribution and architecture. Vascular malformations represented a prominent category of lesions, accounting for 50% of the specimens, predominantly comprising lymphatic and lymphovascular malformations. No malignancy or cytological atypia was identified in any case. The histopathological features of lesions resected from children with Proteus syndrome predominantly include hamartomatous mixed connective tissue lesions, benign neoplasms such as lipomata, and lymphatic-rich vascular malformations.

Clinical characteristics of 150 consecutive fibromyalgia patients attending an Australian public hospital clinic.

PubMed

Guymer, Emma K; Maruff, Paul; Littlejohn, Geoffrey O

2012-08-01

To describe clinical characteristics of fibromyalgia in an Australian population. Data was collected from 150 consecutive patients with clinical features of fibromyalgia seen in an Australian public hospital clinic. Demographic information and clinical characteristics were recorded. Significant correlations between clinical characteristics were identified, then used in multiple regression analyses to identify factors influencing outcome in physical function, pain, fatigue and sleep disturbance. Clinical features in groups who were or were not using different treatment strategies were compared. Most patients were female and Caucasian. The majority reported a recognizable trigger factor and many had associated conditions, most commonly headache and irritable bowel syndrome. Physical function was significantly accounted for by pain levels (P = 0.001); pain score was significantly predicted by tenderness (P = 0.002) and physical function level (P = 0.001); fatigue levels were significantly influenced by age (P = 0.007) and sleep disturbance (P < 0.001), and sleep disturbance was significantly predicted by fatigue (P < 0.001). Just over one-third (34%) of patients were using fibromyalgia medications (low-dose tricyclic antidepressant, pregabalin or duloxetine); however, they had less anxiety (P = 0.006) and better reported physical function (P = 0.04) than those who were not. Less than half (43.6%) of the patients were regularly exercising; however, they had reduced overall illness impact scores (P = 0.004), better physical function (P = 0.01) and less fatigue (P = 0.03), anxiety (P = 0.02) and depressive features (P = 0.008) than non-exercisers. Baseline clinical characteristics in this group were comparable to other study populations. The use of management modalities with proven benefit in fibromyalgia was limited; however, those patients who were engaged in regular exercise or using medication had better self-reported outcome measures than

Histogram-based adaptive gray level scaling for texture feature classification of colorectal polyps

NASA Astrophysics Data System (ADS)

Pomeroy, Marc; Lu, Hongbing; Pickhardt, Perry J.; Liang, Zhengrong

2018-02-01

Texture features have played an ever increasing role in computer aided detection (CADe) and diagnosis (CADx) methods since their inception. Texture features are often used as a method of false positive reduction for CADe packages, especially for detecting colorectal polyps and distinguishing them from falsely tagged residual stool and healthy colon wall folds. While texture features have shown great success there, the performance of texture features for CADx have lagged behind primarily because of the more similar features among different polyps types. In this paper, we present an adaptive gray level scaling and compare it to the conventional equal-spacing of gray level bins. We use a dataset taken from computed tomography colonography patients, with 392 polyp regions of interest (ROIs) identified and have a confirmed diagnosis through pathology. Using the histogram information from the entire ROI dataset, we generate the gray level bins such that each bin contains roughly the same number of voxels Each image ROI is the scaled down to two different numbers of gray levels, using both an equal spacing of Hounsfield units for each bin, and our adaptive method. We compute a set of texture features from the scaled images including 30 gray level co-occurrence matrix (GLCM) features and 11 gray level run length matrix (GLRLM) features. Using a random forest classifier to distinguish between hyperplastic polyps and all others (adenomas and adenocarcinomas), we find that the adaptive gray level scaling can improve performance based on the area under the receiver operating characteristic curve by up to 4.6%.

Perceptual Characteristics of Female Voices.

ERIC Educational Resources Information Center

Batstone, Susan; Tuomi, Seppo K.

1981-01-01

Male and females listeners rated 21 young female voices on seven scales representing unique vocal features. Voices were described as "passive", or traditionally female, and "active," characterized as "lively,""colorful," and "sexy." Females found active characteristics more salient; males preferred the passive characteristics. Implications for…

ToNER: A tool for identifying nucleotide enrichment signals in feature-enriched RNA-seq data.

PubMed

Promworn, Yuttachon; Kaewprommal, Pavita; Shaw, Philip J; Intarapanich, Apichart; Tongsima, Sissades; Piriyapongsa, Jittima

2017-01-01

Biochemical methods are available for enriching 5' ends of RNAs in prokaryotes, which are employed in the differential RNA-seq (dRNA-seq) and the more recent Cappable-seq protocols. Computational methods are needed to locate RNA 5' ends from these data by statistical analysis of the enrichment. Although statistical-based analysis methods have been developed for dRNA-seq, they may not be suitable for Cappable-seq data. The more efficient enrichment method employed in Cappable-seq compared with dRNA-seq could affect data distribution and thus algorithm performance. We present Transformation of Nucleotide Enrichment Ratios (ToNER), a tool for statistical modeling of enrichment from RNA-seq data obtained from enriched and unenriched libraries. The tool calculates nucleotide enrichment scores and determines the global transformation for fitting to the normal distribution using the Box-Cox procedure. From the transformed distribution, sites of significant enrichment are identified. To increase power of detection, meta-analysis across experimental replicates is offered. We tested the tool on Cappable-seq and dRNA-seq data for identifying Escherichia coli transcript 5' ends and compared the results with those from the TSSAR tool, which is designed for analyzing dRNA-seq data. When combining results across Cappable-seq replicates, ToNER detects more known transcript 5' ends than TSSAR. In general, the transcript 5' ends detected by ToNER but not TSSAR occur in regions which cannot be locally modeled by TSSAR. ToNER uses a simple yet robust statistical modeling approach, which can be used for detecting RNA 5'ends from Cappable-seq data, in particular when combining information from experimental replicates. The ToNER tool could potentially be applied for analyzing other RNA-seq datasets in which enrichment for other structural features of RNA is employed. The program is freely available for download at ToNER webpage (http://www4a.biotec.or.th/GI/tools/toner) and Git

ToNER: A tool for identifying nucleotide enrichment signals in feature-enriched RNA-seq data

PubMed Central

Promworn, Yuttachon; Kaewprommal, Pavita; Shaw, Philip J.; Intarapanich, Apichart; Tongsima, Sissades

2017-01-01

Background Biochemical methods are available for enriching 5′ ends of RNAs in prokaryotes, which are employed in the differential RNA-seq (dRNA-seq) and the more recent Cappable-seq protocols. Computational methods are needed to locate RNA 5′ ends from these data by statistical analysis of the enrichment. Although statistical-based analysis methods have been developed for dRNA-seq, they may not be suitable for Cappable-seq data. The more efficient enrichment method employed in Cappable-seq compared with dRNA-seq could affect data distribution and thus algorithm performance. Results We present Transformation of Nucleotide Enrichment Ratios (ToNER), a tool for statistical modeling of enrichment from RNA-seq data obtained from enriched and unenriched libraries. The tool calculates nucleotide enrichment scores and determines the global transformation for fitting to the normal distribution using the Box-Cox procedure. From the transformed distribution, sites of significant enrichment are identified. To increase power of detection, meta-analysis across experimental replicates is offered. We tested the tool on Cappable-seq and dRNA-seq data for identifying Escherichia coli transcript 5′ ends and compared the results with those from the TSSAR tool, which is designed for analyzing dRNA-seq data. When combining results across Cappable-seq replicates, ToNER detects more known transcript 5′ ends than TSSAR. In general, the transcript 5′ ends detected by ToNER but not TSSAR occur in regions which cannot be locally modeled by TSSAR. Conclusion ToNER uses a simple yet robust statistical modeling approach, which can be used for detecting RNA 5′ends from Cappable-seq data, in particular when combining information from experimental replicates. The ToNER tool could potentially be applied for analyzing other RNA-seq datasets in which enrichment for other structural features of RNA is employed. The program is freely available for download at ToNER webpage (http://www4a

An Eye-Tracking Study of Multiple Feature Value Category Structure Learning: The Role of Unique Features

PubMed Central

Liu, Zhiya; Song, Xiaohong; Seger, Carol A.

2015-01-01

We examined whether the degree to which a feature is uniquely characteristic of a category can affect categorization above and beyond the typicality of the feature. We developed a multiple feature value category structure with different dimensions within which feature uniqueness and typicality could be manipulated independently. Using eye tracking, we found that the highest attentional weighting (operationalized as number of fixations, mean fixation time, and the first fixation of the trial) was given to a dimension that included a feature that was both unique and highly typical of the category. Dimensions that included features that were highly typical but not unique, or were unique but not highly typical, received less attention. A dimension with neither a unique nor a highly typical feature received least attention. On the basis of these results we hypothesized that subjects categorized via a rule learning procedure in which they performed an ordered evaluation of dimensions, beginning with unique and strongly typical dimensions, and in which earlier dimensions received higher weighting in the decision. This hypothesis accounted for performance on transfer stimuli better than simple implementations of two other common theories of category learning, exemplar models and prototype models, in which all dimensions were evaluated in parallel and received equal weighting. PMID:26274332

An Eye-Tracking Study of Multiple Feature Value Category Structure Learning: The Role of Unique Features.

PubMed

Liu, Zhiya; Song, Xiaohong; Seger, Carol A

2015-01-01

We examined whether the degree to which a feature is uniquely characteristic of a category can affect categorization above and beyond the typicality of the feature. We developed a multiple feature value category structure with different dimensions within which feature uniqueness and typicality could be manipulated independently. Using eye tracking, we found that the highest attentional weighting (operationalized as number of fixations, mean fixation time, and the first fixation of the trial) was given to a dimension that included a feature that was both unique and highly typical of the category. Dimensions that included features that were highly typical but not unique, or were unique but not highly typical, received less attention. A dimension with neither a unique nor a highly typical feature received least attention. On the basis of these results we hypothesized that subjects categorized via a rule learning procedure in which they performed an ordered evaluation of dimensions, beginning with unique and strongly typical dimensions, and in which earlier dimensions received higher weighting in the decision. This hypothesis accounted for performance on transfer stimuli better than simple implementations of two other common theories of category learning, exemplar models and prototype models, in which all dimensions were evaluated in parallel and received equal weighting.

Radiomics analysis of DWI data to identify the rectal cancer patients qualified for local excision after neoadjuvant chemoradiotherapy

NASA Astrophysics Data System (ADS)

Tang, Zhenchao; Liu, Zhenyu; Zhang, Xiaoyan; Shi, Yanjie; Wang, Shou; Fang, Mengjie; Sun, Yingshi; Dong, Enqing; Tian, Jie

2018-02-01

The Locally advanced rectal cancer (LARC) patients were routinely treated with neoadjuvant chemoradiotherapy (CRT) firstly and received total excision afterwards. While, the LARC patients might relieve to T1N0M0/T0N0M0 stage after the CRT, which would enable the patients be qualified for local excision. However, accurate pathological TNM stage could only be obtained by the pathological examination after surgery. We aimed to conduct a Radiomics analysis of Diffusion weighted Imaging (DWI) data to identify the patients in T1N0M0/T0N0M0 stages before surgery, in hope of providing clinical surgery decision support. 223 routinely treated LARC patients in Beijing Cancer Hospital were enrolled in current study. DWI data and clinical characteristics were collected after CRT. According to the pathological TNM stage, the patients of T1N0M0 and T0N0M0 stages were labelled as 1 and the other patients were labelled as 0. The first 123 patients in chronological order were used as training set, and the rest patients as validation set. 563 image features extracted from the DWI data and clinical characteristics were used as features. Two-sample T test was conducted to pre-select the top 50% discriminating features. Least absolute shrinkage and selection operator (Lasso)-Logistic regression model was conducted to further select features and construct the classification model. Based on the 14 selected image features, the area under the Receiver Operating Characteristic (ROC) curve (AUC) of 0.8781, classification Accuracy (ACC) of 0.8432 were achieved in the training set. In the validation set, AUC of 0.8707, ACC (ACC) of 0.84 were observed.

Research on the feature extraction and pattern recognition of the distributed optical fiber sensing signal

NASA Astrophysics Data System (ADS)

Wang, Bingjie; Sun, Qi; Pi, Shaohua; Wu, Hongyan

2014-09-01

In this paper, feature extraction and pattern recognition of the distributed optical fiber sensing signal have been studied. We adopt Mel-Frequency Cepstral Coefficient (MFCC) feature extraction, wavelet packet energy feature extraction and wavelet packet Shannon entropy feature extraction methods to obtain sensing signals (such as speak, wind, thunder and rain signals, etc.) characteristic vectors respectively, and then perform pattern recognition via RBF neural network. Performances of these three feature extraction methods are compared according to the results. We choose MFCC characteristic vector to be 12-dimensional. For wavelet packet feature extraction, signals are decomposed into six layers by Daubechies wavelet packet transform, in which 64 frequency constituents as characteristic vector are respectively extracted. In the process of pattern recognition, the value of diffusion coefficient is introduced to increase the recognition accuracy, while keeping the samples for testing algorithm the same. Recognition results show that wavelet packet Shannon entropy feature extraction method yields the best recognition accuracy which is up to 97%; the performance of 12-dimensional MFCC feature extraction method is less satisfactory; the performance of wavelet packet energy feature extraction method is the worst.

Characteristics of health plans that treat psychiatric patients.

PubMed

Zarin, D A; West, J C; Pincus, H A; Tanielian, T L

1999-01-01

Nationally representative data regarding the organizational, financial, and procedural features of health plans in which psychiatric patients receive treatment indicate that fewer privately insured, Medicaid, and Medicare managed care enrollees receive care from a psychiatrist than is true for "nonmanaged" enrollees. Financial considerations were reported to adversely affect treatment for one-third of all patients. Although utilization management techniques and financial/resource constraints commonly applied to patients in both managed and nonmanaged plans, performance-based incentives were rare in nonmanaged plans. The traditional health plan categories provide limited information to identify salient plan characteristics and guide policy decisions regarding the provision of care.

Pediatric Eosinophilic Esophagitis Symptom Scores (PEESS® v2.0) identify histologic and molecular correlates of the key clinical features of disease

PubMed Central

Martin, Lisa J.; Franciosi, James P.; Collins, Margaret H.; Abonia, J. Pablo; Lee, James J.; Hommel, Kevin A.; Varni, James W.; Grotjan, J. Tommie; Eby, Michael; He, Hua; Marsolo, Keith; Putnam, Philip E.; Garza, Jose M.; Kaul, Ajay; Wen, Ting; Rothenberg, Marc E.

2015-01-01

Background The Pediatric Eosinophilic Esophagitis Symptom Score (PEESS® v2.0) measures patient-relevant outcomes. However, whether patient-identified domains (dysphagia, gastrointestinal reflux disease (GERD), nausea/vomiting, and pain) align with clinical symptomology and histopathologic and molecular features of eosinophilic esophagitis (EoE) is unclear. Objective The purpose of this study was to determine if clinical features of EoE, measured through the PEESS® v2.0, associate with histopathologic and molecular features of EoE. This represents a novel approach for analysis of allergic diseases, given the availability of allergic tissue biopsy specimens. Methods We systematically recruited treated and untreated, pediatric patients with EoE (aged 2–18 years) and examined parent proxy–reported symptoms using the PEESS® v2.0. Clinical symptomology was collected by questionnaire. Esophageal biopsy samples were quantified for levels of eosinophils, eosinophil peroxidase (EPX) immunohistochemical staining, and mast cells. Molecular features were assessed by the EoE Diagnostic Panel (94 EoE-related gene transcripts). Associations between domain scores and clinical symptoms and biologic features were analyzed using Wilcoxon Rank Sum and Spearman correlation. Results The PEESS® v2.0 domains correlated to specific parent-reported symptoms: dysphagia (p = 0.0012), GERD (p = 0.0001), and nausea/vomiting (p < 0.0001). Pain correlated with multiple symptoms (p < 0.0005). Dysphagia correlated most strongly with overall histopathology, particularly in the proximal esophagus (p ≤ 0.0049). Markers of esophageal activity (EPX) were significantly associated with dysphagia (strongest r = .37; p = 0.02). Eosinophil levels were more associated with pain (r = 0.27; p=0.06) than for dysphagia (r = 0.24; p = 0.13). The dysphagia domain correlated the most with esophageal gene transcript levels, predominantly with mast cell–specific genes. Conclusion We have 1) established a

GATOR: Requirements capturing of telephony features

NASA Technical Reports Server (NTRS)

Dankel, Douglas D., II; Walker, Wayne; Schmalz, Mark

1992-01-01

We are developing a natural language-based, requirements gathering system called GATOR (for the GATherer Of Requirements). GATOR assists in the development of more accurate and complete specifications of new telephony features. GATOR interacts with a feature designer who describes a new feature, set of features, or capability to be implemented. The system aids this individual in the specification process by asking for clarifications when potential ambiguities are present, by identifying potential conflicts with other existing features, and by presenting its understanding of the feature to the designer. Through user interaction with a model of the existing telephony feature set, GATOR constructs a formal representation of the new, 'to be implemented' feature. Ultimately GATOR will produce a requirements document and will maintain an internal representation of this feature to aid in future design and specification. This paper consists of three sections that describe (1) the structure of GATOR, (2) POND, GATOR's internal knowledge representation language, and (3) current research issues.

Identifying elemental genomic track types and representing them uniformly

PubMed Central

2011-01-01

Background With the recent advances and availability of various high-throughput sequencing technologies, data on many molecular aspects, such as gene regulation, chromatin dynamics, and the three-dimensional organization of DNA, are rapidly being generated in an increasing number of laboratories. The variation in biological context, and the increasingly dispersed mode of data generation, imply a need for precise, interoperable and flexible representations of genomic features through formats that are easy to parse. A host of alternative formats are currently available and in use, complicating analysis and tool development. The issue of whether and how the multitude of formats reflects varying underlying characteristics of data has to our knowledge not previously been systematically treated. Results We here identify intrinsic distinctions between genomic features, and argue that the distinctions imply that a certain variation in the representation of features as genomic tracks is warranted. Four core informational properties of tracks are discussed: gaps, lengths, values and interconnections. From this we delineate fifteen generic track types. Based on the track type distinctions, we characterize major existing representational formats and find that the track types are not adequately supported by any single format. We also find, in contrast to the XML formats, that none of the existing tabular formats are conveniently extendable to support all track types. We thus propose two unified formats for track data, an improved XML format, BioXSD 1.1, and a new tabular format, GTrack 1.0. Conclusions The defined track types are shown to capture relevant distinctions between genomic annotation tracks, resulting in varying representational needs and analysis possibilities. The proposed formats, GTrack 1.0 and BioXSD 1.1, cater to the identified track distinctions and emphasize preciseness, flexibility and parsing convenience. PMID:22208806

Automated feature extraction and classification from image sources

USGS Publications Warehouse

,

1995-01-01

The U.S. Department of the Interior, U.S. Geological Survey (USGS), and Unisys Corporation have completed a cooperative research and development agreement (CRADA) to explore automated feature extraction and classification from image sources. The CRADA helped the USGS define the spectral and spatial resolution characteristics of airborne and satellite imaging sensors necessary to meet base cartographic and land use and land cover feature classification requirements and help develop future automated geographic and cartographic data production capabilities. The USGS is seeking a new commercial partner to continue automated feature extraction and classification research and development.

Identifying Program Characteristics for Preparing Pre-Service Teachers for Diversity

ERIC Educational Resources Information Center

Akiba, Motoko

2011-01-01

Background/Context: Educating pre-service teachers to develop multicultural awareness, knowledge, and skills for teaching diverse students is a major responsibility of teacher education program coordinators and teacher educators. Numerous studies have discussed and explored the characteristics of teacher preparation that improve pre-service…

Land cover change detection using a GIS-guided, feature-based classification of Landsat thematic mapper data. [Geographic Information System

NASA Technical Reports Server (NTRS)

Enslin, William R.; Ton, Jezching; Jain, Anil

1987-01-01

Landsat TM data were combined with land cover and planimetric data layers contained in the State of Michigan's geographic information system (GIS) to identify changes in forestlands, specifically new oil/gas wells. A GIS-guided feature-based classification method was developed. The regions extracted by the best image band/operator combination were studied using a set of rules based on the characteristics of the GIS oil/gas pads.

An Ensemble Method with Integration of Feature Selection and Classifier Selection to Detect the Landslides

NASA Astrophysics Data System (ADS)

Zhongqin, G.; Chen, Y.

2017-12-01

Abstract Quickly identify the spatial distribution of landslides automatically is essential for the prevention, mitigation and assessment of the landslide hazard. It's still a challenging job owing to the complicated characteristics and vague boundary of the landslide areas on the image. The high resolution remote sensing image has multi-scales, complex spatial distribution and abundant features, the object-oriented image classification methods can make full use of the above information and thus effectively detect the landslides after the hazard happened. In this research we present a new semi-supervised workflow, taking advantages of recent object-oriented image analysis and machine learning algorithms to quick locate the different origins of landslides of some areas on the southwest part of China. Besides a sequence of image segmentation, feature selection, object classification and error test, this workflow ensemble the feature selection and classifier selection. The feature this study utilized were normalized difference vegetation index (NDVI) change, textural feature derived from the gray level co-occurrence matrices (GLCM), spectral feature and etc. The improvement of this study shows this algorithm significantly removes some redundant feature and the classifiers get fully used. All these improvements lead to a higher accuracy on the determination of the shape of landslides on the high resolution remote sensing image, in particular the flexibility aimed at different kinds of landslides.

Extraneural metastases of primary central nervous system tumors identified by fine needle aspiration: a retrospective analysis.

PubMed

Vandenbussche, Christopher J; Ho, Cheng-Ying; Nugent, Summer L; Ali, Syed Z

2014-01-01

Extraneural metastasis (EM) of primary central nervous system (PCNS) neoplasms is rare and signifies a poor clinical outcome. Due to its infrequent occurrence, relatively few reports on the cytomorphology of these neoplasms have been published. We describe a series of 19 cases from 16 patients at a single, large tertiary care center. A retrospective analysis of 19 cases of metastases from PCNS neoplasms identified on fine needle aspiration (FNA) in 8 male and 8 female patients aged 14-72 years (mean age 39.6) from 1989 to 2013 was conducted to further characterize the cytomorphologic features identified at metastatic sites. Six different PCNS neoplasms were identified: meningioma, glioblastoma, hemangiopericytoma (HPC), oligodendroglioma, medulloblastoma, and retinoblastoma. The mean latency period between the diagnoses of the primary and first metastatic tumors was 7.4 years (range 0-15). The most common PCNS malignancy responsible for EM was HPC. The most common metastatic sites were the lung (31%) and soft tissue/bone (31%). EM of PCNS tumors is extremely rare. FNA allows for quick, safe and accurate diagnosis. Cytomorphologic features are characteristic, and in conjunction with the clinical history and immunohistochemistry, an accurate diagnosis was obtained in 100% of the cases.

Targeted Feature Detection for Data-Dependent Shotgun Proteomics.

PubMed

Weisser, Hendrik; Choudhary, Jyoti S

2017-08-04

Label-free quantification of shotgun LC-MS/MS data is the prevailing approach in quantitative proteomics but remains computationally nontrivial. The central data analysis step is the detection of peptide-specific signal patterns, called features. Peptide quantification is facilitated by associating signal intensities in features with peptide sequences derived from MS2 spectra; however, missing values due to imperfect feature detection are a common problem. A feature detection approach that directly targets identified peptides (minimizing missing values) but also offers robustness against false-positive features (by assigning meaningful confidence scores) would thus be highly desirable. We developed a new feature detection algorithm within the OpenMS software framework, leveraging ideas and algorithms from the OpenSWATH toolset for DIA/SRM data analysis. Our software, FeatureFinderIdentification ("FFId"), implements a targeted approach to feature detection based on information from identified peptides. This information is encoded in an MS1 assay library, based on which ion chromatogram extraction and detection of feature candidates are carried out. Significantly, when analyzing data from experiments comprising multiple samples, our approach distinguishes between "internal" and "external" (inferred) peptide identifications (IDs) for each sample. On the basis of internal IDs, two sets of positive (true) and negative (decoy) feature candidates are defined. A support vector machine (SVM) classifier is then trained to discriminate between the sets and is subsequently applied to the "uncertain" feature candidates from external IDs, facilitating selection and confidence scoring of the best feature candidate for each peptide. This approach also enables our algorithm to estimate the false discovery rate (FDR) of the feature selection step. We validated FFId based on a public benchmark data set, comprising a yeast cell lysate spiked with protein standards that provide a known

Identification of dynamic characteristics of flexible rotors as dynamic inverse problem

NASA Technical Reports Server (NTRS)

Roisman, W. P.; Vajingortin, L. D.

1991-01-01

The problem of dynamic and balancing of flexible rotors were considered, which were set and solved as the problem of the identification of flexible rotor systems, which is the same as the inverse problem of the oscillation theory dealing with the task of the identifying the outside influences and system parameters on the basis of the known laws of motion. This approach to the problem allows the disclosure the picture of disbalances throughout the rotor-under-test (which traditional methods of flexible rotor balancing, based on natural oscillations, could not provide), and identify dynamic characteristics of the system, which correspond to a selected mathematical model. Eventually, various methods of balancing were developed depending on the special features of the machines as to their design, technology, and operation specifications. Also, theoretical and practical methods are given for the flexible rotor balancing at far from critical rotation frequencies, which does not necessarily require the knowledge forms of oscillation, dissipation, and elasticity and inertia characteristics, and to use testing masses.

The semiology of febrile seizures: Focal features are frequent.

PubMed

Takasu, Michihiko; Kubota, Tetsuo; Tsuji, Takeshi; Kurahashi, Hirokazu; Numoto, Shingo; Watanabe, Kazuyoshi; Okumura, Akihisa

2017-08-01

To clarify the semiology of febrile seizures (FS) and to determine the frequency of FS with symptoms suggestive of focal onset. FS symptoms in children were reported within 24h of seizure onset by the parents using a structured questionnaire consisting principally of closed-ended questions. We focused on events at seizure commencement, including changes in behavior and facial expression, and ocular and oral symptoms. We also investigated the autonomic and motor symptoms developing during seizures. The presence or absence of focal and limbic features was determined for each patient. The associations of certain focal and limbic features with patient characteristics were assessed. Information was obtained on FS in 106 children. Various events were recorded at seizure commencement. Behavioral changes were observed in 35 children, changes in facial expression in 53, ocular symptoms in 78, and oral symptoms in 90. In terms of events during seizures, autonomic symptoms were recognized in 78, and convulsive motor symptoms were recognized in 68 children. Focal features were evident in 81 children; 38 children had two or more such features. Limbic features were observed in 44 children, 9 of whom had two or more such features. There was no significant relationship between any patient characteristic and the numbers of focal or limbic features. The semiology of FS varied widely among children, and symptoms suggestive of focal onset were frequent. FS of focal onset may be more common than is generally thought. Copyright © 2017 Elsevier Inc. All rights reserved.

Which ante mortem clinical features predict progressive supranuclear palsy pathology?

PubMed

Respondek, Gesine; Kurz, Carolin; Arzberger, Thomas; Compta, Yaroslau; Englund, Elisabet; Ferguson, Leslie W; Gelpi, Ellen; Giese, Armin; Irwin, David J; Meissner, Wassilios G; Nilsson, Christer; Pantelyat, Alexander; Rajput, Alex; van Swieten, John C; Troakes, Claire; Josephs, Keith A; Lang, Anthony E; Mollenhauer, Brit; Müller, Ulrich; Whitwell, Jennifer L; Antonini, Angelo; Bhatia, Kailash P; Bordelon, Yvette; Corvol, Jean-Christophe; Colosimo, Carlo; Dodel, Richard; Grossman, Murray; Kassubek, Jan; Krismer, Florian; Levin, Johannes; Lorenzl, Stefan; Morris, Huw; Nestor, Peter; Oertel, Wolfgang H; Rabinovici, Gil D; Rowe, James B; van Eimeren, Thilo; Wenning, Gregor K; Boxer, Adam; Golbe, Lawrence I; Litvan, Irene; Stamelou, Maria; Höglinger, Günter U

2017-07-01

Progressive supranuclear palsy (PSP) is a neuropathologically defined disease presenting with a broad spectrum of clinical phenotypes. To identify clinical features and investigations that predict or exclude PSP pathology during life, aiming at an optimization of the clinical diagnostic criteria for PSP. We performed a systematic review of the literature published since 1996 to identify clinical features and investigations that may predict or exclude PSP pathology. We then extracted standardized data from clinical charts of patients with pathologically diagnosed PSP and relevant disease controls and calculated the sensitivity, specificity, and positive predictive value of key clinical features for PSP in this cohort. Of 4166 articles identified by the database inquiry, 269 met predefined standards. The literature review identified clinical features predictive of PSP, including features of the following 4 functional domains: ocular motor dysfunction, postural instability, akinesia, and cognitive dysfunction. No biomarker or genetic feature was found reliably validated to predict definite PSP. High-quality original natural history data were available from 206 patients with pathologically diagnosed PSP and from 231 pathologically diagnosed disease controls (54 corticobasal degeneration, 51 multiple system atrophy with predominant parkinsonism, 53 Parkinson's disease, 73 behavioral variant frontotemporal dementia). We identified clinical features that predicted PSP pathology, including phenotypes other than Richardson's syndrome, with varying sensitivity and specificity. Our results highlight the clinical variability of PSP and the high prevalence of phenotypes other than Richardson's syndrome. The features of variant phenotypes with high specificity and sensitivity should serve to optimize clinical diagnosis of PSP. © 2017 International Parkinson and Movement Disorder Society. © 2017 International Parkinson and Movement Disorder Society.

Wavelet feature extraction for reliable discrimination between high explosive and chemical/biological artillery

NASA Astrophysics Data System (ADS)

Hohil, Myron E.; Desai, Sachi V.; Bass, Henry E.; Chambers, Jim

2005-03-01

Feature extraction methods based on the discrete wavelet transform and multiresolution analysis are used to develop a robust classification algorithm that reliably discriminates between conventional and simulated chemical/biological artillery rounds via acoustic signals produced during detonation. Distinct characteristics arise within the different airburst signatures because high explosive warheads emphasize concussive and shrapnel effects, while chemical/biological warheads are designed to disperse their contents over large areas, therefore employing a slower burning, less intense explosive to mix and spread their contents. The ensuing blast waves are readily characterized by variations in the corresponding peak pressure and rise time of the blast, differences in the ratio of positive pressure amplitude to the negative amplitude, and variations in the overall duration of the resulting waveform. Unique attributes can also be identified that depend upon the properties of the gun tube, projectile speed at the muzzle, and the explosive burn rates of the warhead. In this work, the discrete wavelet transform is used to extract the predominant components of these characteristics from air burst signatures at ranges exceeding 2km. Highly reliable discrimination is achieved with a feedforward neural network classifier trained on a feature space derived from the distribution of wavelet coefficients and higher frequency details found within different levels of the multiresolution decomposition.

Multiscale Feature Analysis of Salivary Gland Branching Morphogenesis

PubMed Central

Baydil, Banu; Daley, William P.; Larsen, Melinda; Yener, Bülent

2012-01-01

Pattern formation in developing tissues involves dynamic spatio-temporal changes in cellular organization and subsequent evolution of functional adult structures. Branching morphogenesis is a developmental mechanism by which patterns are generated in many developing organs, which is controlled by underlying molecular pathways. Understanding the relationship between molecular signaling, cellular behavior and resulting morphological change requires quantification and categorization of the cellular behavior. In this study, tissue-level and cellular changes in developing salivary gland in response to disruption of ROCK-mediated signaling by are modeled by building cell-graphs to compute mathematical features capturing structural properties at multiple scales. These features were used to generate multiscale cell-graph signatures of untreated and ROCK signaling disrupted salivary gland organ explants. From confocal images of mouse submandibular salivary gland organ explants in which epithelial and mesenchymal nuclei were marked, a multiscale feature set capturing global structural properties, local structural properties, spectral, and morphological properties of the tissues was derived. Six feature selection algorithms and multiway modeling of the data was performed to identify distinct subsets of cell graph features that can uniquely classify and differentiate between different cell populations. Multiscale cell-graph analysis was most effective in classification of the tissue state. Cellular and tissue organization, as defined by a multiscale subset of cell-graph features, are both quantitatively distinct in epithelial and mesenchymal cell types both in the presence and absence of ROCK inhibitors. Whereas tensor analysis demonstrate that epithelial tissue was affected the most by inhibition of ROCK signaling, significant multiscale changes in mesenchymal tissue organization were identified with this analysis that were not identified in previous biological studies. We

Radiological features of late-onset lymphoedema in Noonan's syndrome.

PubMed

Ho, Wan-Ling; Wang, Jou-Kou; Li, Yiu-Wah

2003-03-01

Noonan's syndrome is a multiple congenital anomaly syndrome with diverse manifestations. Lymphatic abnormalities occur in less than 20% of patients. We report a 14-year-old boy who presented with swollen lower limbs and dysmorphic features characteristic of Noonan's syndrome. The radiological features of this unusual case of late-onset lymphoedema in association with Noonan's syndrome are presented.

Clinical characteristics of ocular toxocariasis in Eastern China.

PubMed

Zhou, Min; Chang, Qing; Gonzales, John A; Chen, Qian; Zhang, Yanqiong; Huang, Xin; Xu, Gezhi; Wang, Wenji; Jiang, Rui

2012-09-01

To explore the clinical characteristics of patients with ocular toxocariasis in eastern China. The medical records of 35 cases of ocular toxocariasis in Fudan University Eye & ENT Hospital between May 2009 and April 2011 were retrospectively reviewed and analyzed. UBM, RetCam or fundus imaging, and high-frequency or conventional ultrasonography were performed in these patients. The mean patient age in our series of ocular toxocariasis was 11.86 ± 8.80 years. There were 28 children and seven adults, the majority residing in a rural area (88.57%). All cases were classified into three clinical subtypes: granuloma in the peripheral retina (60% of cases); granuloma in the posterior pole (28.57% of cases); and vitreous inflammation mimicking chronic endophthalmitis (5.71% of cases). We also identified an additional subtype with unique clinical features that we termed "combined type" presenting in 5.71% of our patients. This subtype exhibited granulomas in both the posterior pole and peripheral retina. RetCam fundus imaging was able to identify granulomas in the posterior and peripheral subtypes, 100% and 80.95% of cases respectively. Moreover, UBM combined with conventional ultrasonography identified granulomas in 95% of the peripheral subtype cases and in 100% of the posterior pole subtype cases. This is the first ocular toxocariasis series described in Chinese patients. Compared with reports from developed countries, the ocular features in our series were more severe and complicated, presenting with poorer visual acuity and a high rate of retinal detachment (45.7%). The application of RetCam and UBM during examination in ocular toxocariasis can provide valuable information in determining the severity of disease and features important in considering surgical procedures in such patients.

FIR signature verification system characterizing dynamics of handwriting features

NASA Astrophysics Data System (ADS)

Thumwarin, Pitak; Pernwong, Jitawat; Matsuura, Takenobu

2013-12-01

This paper proposes an online signature verification method based on the finite impulse response (FIR) system characterizing time-frequency characteristics of dynamic handwriting features. First, the barycenter determined from both the center point of signature and two adjacent pen-point positions in the signing process, instead of one pen-point position, is used to reduce the fluctuation of handwriting motion. In this paper, among the available dynamic handwriting features, motion pressure and area pressure are employed to investigate handwriting behavior. Thus, the stable dynamic handwriting features can be described by the relation of the time-frequency characteristics of the dynamic handwriting features. In this study, the aforesaid relation can be represented by the FIR system with the wavelet coefficients of the dynamic handwriting features as both input and output of the system. The impulse response of the FIR system is used as the individual feature for a particular signature. In short, the signature can be verified by evaluating the difference between the impulse responses of the FIR systems for a reference signature and the signature to be verified. The signature verification experiments in this paper were conducted using the SUBCORPUS MCYT-100 signature database consisting of 5,000 signatures from 100 signers. The proposed method yielded equal error rate (EER) of 3.21% on skilled forgeries.

Molecular Cloning and Characteristic Features of a Novel Extracellular Tyrosinase from Aspergillus niger PA2.

PubMed

Agarwal, Pragati; Singh, Jyoti; Singh, R P

2017-05-01

Aspergillus niger PA2, a novel strain isolated from waste effluents of food industry, is a potential extracellular tyrosinase producer. Enzyme activity and L-DOPA production were maximum when glucose and peptone were employed as C source and nitrogen source respectively in the medium and enhanced notably when the copper was supplemented, thus depicting the significance of copper in tyrosinase activity. Tyrosinase-encoding gene from the fungus was cloned, and amplification of the tyrosinase gene yielded a 1127-bp DNA fragment and 374 amino acid residue long product that encoded for a predicted protein of 42.3 kDa with an isoelectric point of 4.8. Primary sequence analysis of A. niger PA2 tyrosinase had shown that it had approximately 99% identity with that of A. niger CBS 513.88, which was further confirmed by phylogenetic analysis. The inferred amino acid sequence of A. niger tyrosinase contained two putative copper-binding sites comprising of six histidines, a characteristic feature for type-3 copper proteins, which were highly conserved in all tyrosinases throughout the Aspergillus species. When superimposed onto the tertiary structure of A. oryzae tyrosinase, the conserved residues from both the organisms occupied same spatial positions to provide a di-copper-binding peptide groove.

Carpal valgus in llamas and alpacas: Retrospective evaluation of patient characteristics, radiographic features and outcomes following surgical treatment

PubMed Central

Hunter, Barbara; Duesterdieck-Zellmer, Katja F.; Huber, Michael J.; Parker, Jill E.; Semevolos, Stacy A.

2014-01-01

This study evaluated outcomes of surgical treatment for carpal valgus in New World camelids and correlated successful outcome (absence of carpal valgus determined by a veterinarian) with patient characteristics and radiographic features. Univariable and multivariable analyses of retrospective case data in 19 camelids (33 limbs) treated for carpal valgus between 1987 and 2010 revealed that procedures incorporating a distal radial transphyseal bridge were more likely (P = 0.03) to result in success after a single surgical procedure. A greater degree of angulation (> 19°, P = 0.02) and younger age at surgery (< 4 months, P = 0.03) were associated with unsuccessful outcome. Overall, 74% of limbs straightened, 15% overcorrected, and 11% had persistent valgus following surgical intervention. To straighten, 22% of limbs required multiple procedures, not including implant removal. According to owners, valgus returned following implant removal in 4 limbs that had straightened after surgery. PMID:25477542

The method of micro-motion cycle feature extraction based on confidence coefficient evaluation criteria

NASA Astrophysics Data System (ADS)

Tang, Chuanzi; Ren, Hongmei; Bo, Li; Jing, Huang

2017-11-01

In radar target recognition, the micro motion characteristics of target is one of the characteristics that researchers pay attention to at home and abroad, in which the characteristics of target precession cycle is one of the important characteristics of target movement characteristics. Periodic feature extraction methods have been studied for years, the complex shape of the target and the scattering center stack lead to random fluctuations of the RCS. These random fluctuations also exist certain periodicity, which has a great influence on the target recognition result. In order to solve the problem, this paper proposes a extraction method of micro-motion cycle feature based on confidence coefficient evaluation criteria.

Microdeletions are a general feature of adult and adolescent acute lymphoblastic leukemia: Unexpected similarities with pediatric disease

PubMed Central

Paulsson, Kajsa; Cazier, Jean-Baptiste; MacDougall, Finlay; Stevens, Jane; Stasevich, Irina; Vrcelj, Nikoletta; Chaplin, Tracy; Lillington, Debra M.; Lister, T. Andrew; Young, Bryan D.

2008-01-01

We present here a genome-wide map of abnormalities found in diagnostic samples from 45 adults and adolescents with acute lymphoblastic leukemia (ALL). A 500K SNP array analysis uncovered frequent genetic abnormalities, with cryptic deletions constituting half of the detected changes, implying that microdeletions are a characteristic feature of this malignancy. Importantly, the pattern of deletions resembled that recently reported in pediatric ALL, suggesting that adult, adolescent, and childhood cases may be more similar on the genetic level than previously thought. Thus, 70% of the cases displayed deletion of one or more of the CDKN2A, PAX5, IKZF1, ETV6, RB1, and EBF1 genes. Furthermore, several genes not previously implicated in the pathogenesis of ALL were identified as possible recurrent targets of deletion. In total, the SNP array analysis identified 367 genetic abnormalities not corresponding to known copy number polymorphisms, with all but two cases (96%) displaying at least one cryptic change. The resolution level of this SNP array study is the highest used to date to investigate a malignant hematologic disorder. Our findings provide insights into the leukemogenic process and may be clinically important in adult and adolescent ALL. Most importantly, we report that microdeletions of key genes appear to be a common, characteristic feature of ALL that is shared among different clinical, morphological, and cytogenetic subgroups. PMID:18458336

Feature Statistics Modulate the Activation of Meaning during Spoken Word Processing

ERIC Educational Resources Information Center

Devereux, Barry J.; Taylor, Kirsten I.; Randall, Billi; Geertzen, Jeroen; Tyler, Lorraine K.

2016-01-01

Understanding spoken words involves a rapid mapping from speech to conceptual representations. One distributed feature-based conceptual account assumes that the statistical characteristics of concepts' features--the number of concepts they occur in ("distinctiveness/sharedness") and likelihood of co-occurrence ("correlational…

Identification of influencing municipal characteristics regarding household waste generation and their forecasting ability in Biscay

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

Oribe-Garcia, Iraia, E-mail: iraia.oribe@deusto.es; Kamara-Esteban, Oihane; Martin, Cristina

Highlights: • We have modelled household waste generation in Biscay municipalities. • We have identified relevant characteristics regarding household waste generation. • Factor models are used in order to identify the best subset of explicative variables. • Biscay’s municipalities are grouped by means of hierarchical clustering. - Abstract: The planning of waste management strategies needs tools to support decisions at all stages of the process. Accurate quantification of the waste to be generated is essential for both the daily management (short-term) and proper design of facilities (long-term). Designing without rigorous knowledge may have serious economic and environmental consequences. The presentmore » works aims at identifying relevant socio-economic features of municipalities regarding Household Waste (HW) generation by means of factor models. Factor models face two main drawbacks, data collection and identifying relevant explanatory variables within a heterogeneous group. Grouping similar characteristics observations within a group may favour the deduction of more robust models. The methodology followed has been tested with Biscay Province because it stands out for having very different municipalities ranging from very rural to urban ones. Two main models are developed, one for the overall province and a second one after clustering the municipalities. The results prove that relating municipalities with specific characteristics, improves the results in a very heterogeneous situation. The methodology has identified urban morphology, tourism activity, level of education and economic situation as the most influencing characteristics in HW generation.« less

Toward high-throughput phenotyping: unbiased automated feature extraction and selection from knowledge sources.

PubMed

Yu, Sheng; Liao, Katherine P; Shaw, Stanley Y; Gainer, Vivian S; Churchill, Susanne E; Szolovits, Peter; Murphy, Shawn N; Kohane, Isaac S; Cai, Tianxi

2015-09-01

Analysis of narrative (text) data from electronic health records (EHRs) can improve population-scale phenotyping for clinical and genetic research. Currently, selection of text features for phenotyping algorithms is slow and laborious, requiring extensive and iterative involvement by domain experts. This paper introduces a method to develop phenotyping algorithms in an unbiased manner by automatically extracting and selecting informative features, which can be comparable to expert-curated ones in classification accuracy. Comprehensive medical concepts were collected from publicly available knowledge sources in an automated, unbiased fashion. Natural language processing (NLP) revealed the occurrence patterns of these concepts in EHR narrative notes, which enabled selection of informative features for phenotype classification. When combined with additional codified features, a penalized logistic regression model was trained to classify the target phenotype. The authors applied our method to develop algorithms to identify patients with rheumatoid arthritis and coronary artery disease cases among those with rheumatoid arthritis from a large multi-institutional EHR. The area under the receiver operating characteristic curves (AUC) for classifying RA and CAD using models trained with automated features were 0.951 and 0.929, respectively, compared to the AUCs of 0.938 and 0.929 by models trained with expert-curated features. Models trained with NLP text features selected through an unbiased, automated procedure achieved comparable or slightly higher accuracy than those trained with expert-curated features. The majority of the selected model features were interpretable. The proposed automated feature extraction method, generating highly accurate phenotyping algorithms with improved efficiency, is a significant step toward high-throughput phenotyping. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All

Genetic Programming and Frequent Itemset Mining to Identify Feature Selection Patterns of iEEG and fMRI Epilepsy Data

PubMed Central

Smart, Otis; Burrell, Lauren

2014-01-01

Pattern classification for intracranial electroencephalogram (iEEG) and functional magnetic resonance imaging (fMRI) signals has furthered epilepsy research toward understanding the origin of epileptic seizures and localizing dysfunctional brain tissue for treatment. Prior research has demonstrated that implicitly selecting features with a genetic programming (GP) algorithm more effectively determined the proper features to discern biomarker and non-biomarker interictal iEEG and fMRI activity than conventional feature selection approaches. However for each the iEEG and fMRI modalities, it is still uncertain whether the stochastic properties of indirect feature selection with a GP yield (a) consistent results within a patient data set and (b) features that are specific or universal across multiple patient data sets. We examined the reproducibility of implicitly selecting features to classify interictal activity using a GP algorithm by performing several selection trials and subsequent frequent itemset mining (FIM) for separate iEEG and fMRI epilepsy patient data. We observed within-subject consistency and across-subject variability with some small similarity for selected features, indicating a clear need for patient-specific features and possible need for patient-specific feature selection or/and classification. For the fMRI, using nearest-neighbor classification and 30 GP generations, we obtained over 60% median sensitivity and over 60% median selectivity. For the iEEG, using nearest-neighbor classification and 30 GP generations, we obtained over 65% median sensitivity and over 65% median selectivity except one patient. PMID:25580059

Cytomorphological features of ALK-positive lung adenocarcinomas: psammoma bodies and signet ring cells.

PubMed

Pareja, Fresia; Crapanzano, John P; Mansukhani, Mahesh M; Bulman, William A; Saqi, Anjali

2015-03-01

Correlation between histology and genotype has been described in lung adenocarcinomas. For example, studies have demonstrated that adenocarcinomas with an anaplastic lymphoma kinase (ALK) gene rearrangement may have mucinous features. The objective of the current study was to determine whether a similar association can be identified in cytological specimens. A retrospective search for ALK-rearranged cytopathology (CP) and surgical pathology (SP) lung carcinomas was conducted. Additional ALK-negative (-) lung adenocarcinomas served as controls. For CP and SP cases, the clinical data (i.e., age, sex, and smoking history), architecture, nuclear features, presence of mucin-containing cells (including signet ring cells), and any additional salient characteristics were evaluated. The search yielded 20 ALK-positive (+) adenocarcinomas. Compared with patients with ALK(-) lung adenocarcinomas (33 patients; 12 with epidermal growth factor receptor [EGFR]-mutation, 11 with Kristen rat sarcoma [KRAS]-mutation, and 10 wild-type adenocarcinomas), patients with ALK(+) adenocarcinoma presented at a younger age; and there was no correlation noted with sex or smoking status. The most common histological pattern in SP was papillary/micropapillary. Mucinous features were associated with ALK rearrangement in SP specimens. Signet ring cells and psammoma bodies were evident in and significantly associated with ALK(+) SP and CP specimens. However, psammoma bodies were observed in rare adenocarcinomas with an EGFR mutation. Both the ALK(+) and ALK(-) groups had mostly high nuclear grade. Salient features, including signet ring cells and psammoma bodies, were found to be significantly associated with ALK(+) lung adenocarcinomas and are identifiable on CP specimens. Recognizing these may be especially helpful in the molecular triage of scant CP samples. © 2014 American Cancer Society.

[Non-identified antinuclear antibodies in systemic sclerosis].

PubMed

Margot, A; Smet, J; Soyfoo, S

Systemic sclerosis is a rare auto immune disease characterized by a local or diffuse skin condition and a variable visceral impairment. Anti nuclear antibodies (ANA) can be found in 95 % of patients. The most frequent are the anti topoisomerase 1 or anti Scl 70 and the anti-centromeres. Other antibodies have been reported but they are not conventionally sought in clinical practice. They are referred to as " non identified " ANA. To seek the " non identified " antibodies in patients with scleroderma at Erasme Hospital, to assess their prevalence in this cohort and to correlate their presence with the clinical characteristics. 89 patients out of the cohort of Erasme hospital patients with scleroderma have been looked at. Their clinical and biological data have been identified and a detection of antibodies have been performed by first an immonudot technique and second an EliA technique. 17 out of the 89 patients of our cohort had " non identified " ANA. Among them, antibodies in 11 patients have been identified by the immunodot, among which 7 anti-PmScl 75 and/or 100,3 RNA polymerase III and 1 antifibrillarin. The EliA technique identif ied antibodies in 10 patients among which 5 anti- PmScl, 2 anti RNA polymerase, 2 anti-fibrillarin and 1 anti-centromere. Auto antibodies other than the antitopoisomerase and anti-centromere have been found in patients with scleroderma in our cohort. Certain links exist between the presence of a given antibody and clinical features. We still have to define whether there exist other auto antibodies of which we still are unaware since in some patient no antibodies were detected.

Characteristics of self-identified sexual addicts in a behavioral addiction outpatient clinic

PubMed Central

Wéry, Aline; Vogelaere, Kim; Challet-Bouju, Gaëlle; Poudat, François-Xavier; Caillon, Julie; Lever, Delphine; Billieux, Joël; Grall-Bronnec, Marie

2016-01-01

Background and aims Research on sexual addiction flourished during the last decade, promoted by the development of an increased number of online sexual activities. Despite the accumulation of studies, however, evidence collected in clinical samples of treatment-seeking people remains scarce. The aim of this study was to describe the characteristics (socio-demographics, sexual habits, and comorbidities) of self-identified “sexual addicts.” Methods The sample was composed of 72 patients who consulted an outpatient treatment center regarding their sexual behaviors. Data were collected through a combination of structured interviewing and self-report measures. Results Most patients were males (94.4%) aged 20–76 years (mean 40.3 ± 10.9). Endorsement of sexual addiction diagnosis varied from 56.9% to 95.8% depending on the criteria used. The sexual behaviors reported to have the highest degree of functional impairment were having multiple sexual partners (56%), having unprotected sexual intercourse (51.9%), and using cybersex (43.6%). Ninety percent of patients endorsed a comorbid psychiatric diagnosis, and 60.6% presented at least one paraphilia. Conclusions Results showed highly different profiles in terms of sexual preferences and behaviors, as well as comorbidities involved. These findings highlight the need to develop tailored psychotherapeutic interventions by taking into account the complexity and heterogeneity of the disorder. PMID:27774812

Computerized macular pathology diagnosis in spectral domain optical coherence tomography scans based on multiscale texture and shape features.

PubMed

Liu, Yu-Ying; Ishikawa, Hiroshi; Chen, Mei; Wollstein, Gadi; Duker, Jay S; Fujimoto, James G; Schuman, Joel S; Rehg, James M

2011-10-21

To develop an automated method to identify the normal macula and three macular pathologies (macular hole [MH], macular edema [ME], and age-related macular degeneration [AMD]) from the fovea-centered cross sections in three-dimensional (3D) spectral-domain optical coherence tomography (SD-OCT) images. A sample of SD-OCT macular scans (macular cube 200 × 200 or 512 × 128 scan protocol; Cirrus HD-OCT; Carl Zeiss Meditec, Inc., Dublin, CA) was obtained from healthy subjects and subjects with MH, ME, and/or AMD (dataset for development: 326 scans from 136 subjects [193 eyes], and dataset for testing: 131 scans from 37 subjects [58 eyes]). A fovea-centered cross-sectional slice for each of the SD-OCT images was encoded using spatially distributed multiscale texture and shape features. Three ophthalmologists labeled each fovea-centered slice independently, and the majority opinion for each pathology was used as the ground truth. Machine learning algorithms were used to identify the discriminative features automatically. Two-class support vector machine classifiers were trained to identify the presence of normal macula and each of the three pathologies separately. The area under the receiver operating characteristic curve (AUC) was calculated to assess the performance. The cross-validation AUC result on the development dataset was 0.976, 0.931, 0939, and 0.938, and the AUC result on the holdout testing set was 0.978, 0.969, 0.941, and 0.975, for identifying normal macula, MH, ME, and AMD, respectively. The proposed automated data-driven method successfully identified various macular pathologies (all AUC > 0.94). This method may effectively identify the discriminative features without relying on a potentially error-prone segmentation module.

Image Recognition and Feature Detection in Solar Physics

NASA Astrophysics Data System (ADS)

Martens, Petrus C.

2012-05-01

The Solar Dynamics Observatory (SDO) data repository will dwarf the archives of all previous solar physics missions put together. NASA recognized early on that the traditional methods of analyzing the data -- solar scientists and grad students in particular analyzing the images by hand -- would simply not work and tasked our Feature Finding Team (FFT) with developing automated feature recognition modules for solar events and phenomena likely to be observed by SDO. Having these metadata available on-line will enable solar scientist to conduct statistical studies involving large sets of events that would be impossible now with traditional means. We have followed a two-track approach in our project: we have been developing some existing task-specific solar feature finding modules to be "pipe-line" ready for the stream of SDO data, plus we are designing a few new modules. Secondly, we took it upon us to develop an entirely new "trainable" module that would be capable of identifying different types of solar phenomena starting from a limited number of user-provided examples. Both approaches are now reaching fruition, and I will show examples and movies with results from several of our feature finding modules. In the second part of my presentation I will focus on our “trainable” module, which is the most innovative in character. First, there is the strong similarity between solar and medical X-ray images with regard to their texture, which has allowed us to apply some advances made in medical image recognition. Second, we have found that there is a strong similarity between the way our trainable module works and the way our brain recognizes images. The brain can quickly recognize similar images from key characteristics, just as our code does. We conclude from that that our approach represents the beginning of a more human-like procedure for computer image recognition.

Common structural features of cholesterol binding sites in crystallized soluble proteins

PubMed Central

Bukiya, Anna N.; Dopico, Alejandro M.

2017-01-01

Cholesterol-protein interactions are essential for the architectural organization of cell membranes and for lipid metabolism. While cholesterol-sensing motifs in transmembrane proteins have been identified, little is known about cholesterol recognition by soluble proteins. We reviewed the structural characteristics of binding sites for cholesterol and cholesterol sulfate from crystallographic structures available in the Protein Data Bank. This analysis unveiled key features of cholesterol-binding sites that are present in either all or the majority of sites: i) the cholesterol molecule is generally positioned between protein domains that have an organized secondary structure; ii) the cholesterol hydroxyl/sulfo group is often partnered by Asn, Gln, and/or Tyr, while the hydrophobic part of cholesterol interacts with Leu, Ile, Val, and/or Phe; iii) cholesterol hydrogen-bonding partners are often found on α-helices, while amino acids that interact with cholesterol’s hydrophobic core have a slight preference for β-strands and secondary structure-lacking protein areas; iv) the steroid’s C21 and C26 constitute the “hot spots” most often seen for steroid-protein hydrophobic interactions; v) common “cold spots” are C8–C10, C13, and C17, at which contacts with the proteins were not detected. Several common features we identified for soluble protein-steroid interaction appear evolutionarily conserved. PMID:28420706

Intrinsic and contextual features in object recognition.

PubMed

Schlangen, Derrick; Barenholtz, Elan

2015-01-28

The context in which an object is found can facilitate its recognition. Yet, it is not known how effective this contextual information is relative to the object's intrinsic visual features, such as color and shape. To address this, we performed four experiments using rendered scenes with novel objects. In each experiment, participants first performed a visual search task, searching for a uniquely shaped target object whose color and location within the scene was experimentally manipulated. We then tested participants' tendency to use their knowledge of the location and color information in an identification task when the objects' images were degraded due to blurring, thus eliminating the shape information. In Experiment 1, we found that, in the absence of any diagnostic intrinsic features, participants identified objects based purely on their locations within the scene. In Experiment 2, we found that participants combined an intrinsic feature, color, with contextual location in order to uniquely specify an object. In Experiment 3, we found that when an object's color and location information were in conflict, participants identified the object using both sources of information equally. Finally, in Experiment 4, we found that participants used whichever source of information-either color or location-was more statistically reliable in order to identify the target object. Overall, these experiments show that the context in which objects are found can play as important a role as intrinsic features in identifying the objects. © 2015 ARVO.

Secondary psychotic features in refugees diagnosed with post-traumatic stress disorder: a retrospective cohort study.

PubMed

Nygaard, Mette; Sonne, Charlotte; Carlsson, Jessica

2017-01-05

A substantial amount of refugees (10-30%) suffer from Post-Traumatic Stress Disorder (PTSD). In Denmark there are different facilities specialised in psychiatric treatment of trauma-affected refugees. A previously published case report from such a facility in Denmark shows that some patients suffer from secondary psychotic symptoms alongside their PTSD. The aim of this study was to illustrate the characteristics and estimate the prevalence of psychotic features in a clinical population of trauma-affected refugees with PTSD. Psychiatric records from 220 consecutive patients at Competence Centre for Transcultural Psychiatry (CTP) were examined, and all the PTSD patients were divided into two groups; one group with secondary psychotic features (PTSD-SP group) and one without (PTSD group). A categorisation and description of the secondary psychotic features was undertaken. One hundred eighty-one patients were diagnosed with PTSD among which psychotic symptoms were identified in 74 (40.9, 95% CI 33.7-48.1%). The majority of symptoms identified were auditory hallucinations (66.2%) and persecutory delusions (50.0%). There were significantly more patients diagnosed with enduring personality change after catastrophic experience in the PTSD-SP group than in the PTSD group (P = 0.009). Furthermore the PTSD-SP group included significantly more patients exposed to torture (P = 0.001) and imprisonment (P = 0.005). This study provides an estimation of PTSD-SP prevalence in a clinical refugee population with PTSD. The study points to the difficulties distinguishing psychotic features from flashbacks and the authors call for attention to psychotic features in PTSD patients in order to improve documentation and understanding of the disorder.

Sparse Feature Selection Identifies H2A.Z as a Novel, Pattern-Specific Biomarker for Asymmetrically Self-Renewing Distributed Stem Cells

PubMed Central

Huh, Yang Hoon; Noh, Minsoo; Burden, Frank R.; Chen, Jennifer C.; Winkler, David A.; Sherley, James L.

2015-01-01

There is a long-standing unmet clinical need for biomarkers with high specificity for distributed stem cells (DSCs) in tissues, or for use in diagnostic and therapeutic cell preparations (e.g., bone marrow). Although DSCs are essential for tissue maintenance and repair, accurate determination of their numbers for medical applications has been problematic. Previous searches for biomarkers expressed specifically in DSCs were hampered by difficulty obtaining pure DSCs and by the challenges in mining complex molecular expression data. To identify DSC such useful and specific biomarkers, we combined a novel sparse feature selection method with combinatorial molecular expression data focused on asymmetric self-renewal, a conspicuous property of DSCs. The analysis identified reduced expression of the histone H2A variant H2A.Z as a superior molecular discriminator for DSC asymmetric self-renewal. Subsequent molecular expression studies showed H2A.Z to be a novel “pattern-specific biomarker” for asymmetrically self-renewing cells with sufficient specificity to count asymmetrically self-renewing DSCs in vitro and potentially in situ. PMID:25636161

Breast Cancer Detection with Reduced Feature Set.

PubMed

Mert, Ahmet; Kılıç, Niyazi; Bilgili, Erdem; Akan, Aydin

2015-01-01

This paper explores feature reduction properties of independent component analysis (ICA) on breast cancer decision support system. Wisconsin diagnostic breast cancer (WDBC) dataset is reduced to one-dimensional feature vector computing an independent component (IC). The original data with 30 features and reduced one feature (IC) are used to evaluate diagnostic accuracy of the classifiers such as k-nearest neighbor (k-NN), artificial neural network (ANN), radial basis function neural network (RBFNN), and support vector machine (SVM). The comparison of the proposed classification using the IC with original feature set is also tested on different validation (5/10-fold cross-validations) and partitioning (20%-40%) methods. These classifiers are evaluated how to effectively categorize tumors as benign and malignant in terms of specificity, sensitivity, accuracy, F-score, Youden's index, discriminant power, and the receiver operating characteristic (ROC) curve with its criterion values including area under curve (AUC) and 95% confidential interval (CI). This represents an improvement in diagnostic decision support system, while reducing computational complexity.

Feature Vector Construction Method for IRIS Recognition

NASA Astrophysics Data System (ADS)

Odinokikh, G.; Fartukov, A.; Korobkin, M.; Yoo, J.

2017-05-01

One of the basic stages of iris recognition pipeline is iris feature vector construction procedure. The procedure represents the extraction of iris texture information relevant to its subsequent comparison. Thorough investigation of feature vectors obtained from iris showed that not all the vector elements are equally relevant. There are two characteristics which determine the vector element utility: fragility and discriminability. Conventional iris feature extraction methods consider the concept of fragility as the feature vector instability without respect to the nature of such instability appearance. This work separates sources of the instability into natural and encodinginduced which helps deeply investigate each source of instability independently. According to the separation concept, a novel approach of iris feature vector construction is proposed. The approach consists of two steps: iris feature extraction using Gabor filtering with optimal parameters and quantization with separated preliminary optimized fragility thresholds. The proposed method has been tested on two different datasets of iris images captured under changing environmental conditions. The testing results show that the proposed method surpasses all the methods considered as a prior art by recognition accuracy on both datasets.

Identification of important image features for pork and turkey ham classification using colour and wavelet texture features and genetic selection.

PubMed

Jackman, Patrick; Sun, Da-Wen; Allen, Paul; Valous, Nektarios A; Mendoza, Fernando; Ward, Paddy

2010-04-01

A method to discriminate between various grades of pork and turkey ham was developed using colour and wavelet texture features. Image analysis methods originally developed for predicting the palatability of beef were applied to rapidly identify the ham grade. With high quality digital images of 50-94 slices per ham it was possible to identify the greyscale that best expressed the differences between the various ham grades. The best 10 discriminating image features were then found with a genetic algorithm. Using the best 10 image features, simple linear discriminant analysis models produced 100% correct classifications for both pork and turkey on both calibration and validation sets. 2009 Elsevier Ltd. All rights reserved.

Towards a Bayesian evaluation of features in questioned handwritten signatures.

PubMed

Gaborini, Lorenzo; Biedermann, Alex; Taroni, Franco

2017-05-01

In this work, we propose the construction of a evaluative framework for supporting experts in questioned signature examinations. Through the use of Bayesian networks, we envision to quantify the probative value of well defined measurements performed on questioned signatures, in a way that is both formalised and part of a coherent approach to evaluation. At the current stage, our project is explorative, focusing on the broad range of aspects that relate to comparative signature examinations. The goal is to identify writing features which are both highly discriminant, and easy for forensic examiners to detect. We also seek for a balance between case-specific features and characteristics which can be measured in the vast majority of signatures. Care is also taken at preserving the interpretability at every step of the reasoning process. This paves the way for future work, which will aim at merging the different contributions to a single probabilistic measure of strength of evidence using Bayesian networks. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Crowding with conjunctions of simple features.

PubMed

Põder, Endel; Wagemans, Johan

2007-11-20

Several recent studies have related crowding with the feature integration stage in visual processing. In order to understand the mechanisms involved in this stage, it is important to use stimuli that have several features to integrate, and these features should be clearly defined and measurable. In this study, Gabor patches were used as target and distractor stimuli. The stimuli differed in three dimensions: spatial frequency, orientation, and color. A group of 3, 5, or 7 objects was presented briefly at 4 deg eccentricity of the visual field. The observers' task was to identify the object located in the center of the group. A strong effect of the number of distractors was observed, consistent with various spatial pooling models. The analysis of incorrect responses revealed that these were a mix of feature errors and mislocalizations of the target object. Feature errors were not purely random, but biased by the features of distractors. We propose a simple feature integration model that predicts most of the observed regularities.

[Application of ICP-MS to Identify the Botanic Source of Characteristic Honey in South Yunnan].

PubMed

Wei, Yue; Chen, Fang; Wang, Yong; Chen, Lan-zhen; Zhang, Xue-wen; Wang, Yan-hui; Wu, Li-ming; Zhou, Qun

2016-01-01

By adopting inductively coupled plasma mass spectrometry (ICP-MS) combined with chemometric analysis technology, 23 kinds of minerals in four kinds of characteristic honey derived from Yunnan province were analyzed. The result showed that 21 kinds of mineral elements, namely Na, Mg, K, Ca, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Sr, Mo, Cd, Sb, Ba, Tl and Pb, have significant differences among different varieties of honey. The results of principal component analysis (PCA) showed that the cumulative variance contribution rate of the first four main components reached 77.74%, seven kinds of elements (Mg, Ca, Mn, Co, Sr, Cd, Ba) from the first main component contained most of the honey information. Through the stepwise discriminant analysis, seven kinds of elements (Mg, K, Ca, Cr, Mn, Sr, Pb) were filtered. out and used to establish the discriminant function model, and the correct classification rates of the proposed model reached 90% and 86.7%, respectively, which showed elements contents could be effectively indicators to discriminate the four kinds characteristic honey in southern Yunnan Province. In view of all the honey samples were harvested from apiaries located at south Yunnan Province where have similar climate, soil and other environment conditions, the differences of the mineral elements contents for the honey samples mainly due to their corresponding nectariferous plant. Therefore, it is feasible to identify honey botanical source through the differences of mineral elements.

Leperditicopid ostracodes from Ordovician rocks of Kentucky and nearby states and characteristic features of the order Leperditicopida

USGS Publications Warehouse

Berdan, J.M.

1984-01-01

Leperditicopid ostracodes from the Ordovician formations of Kentucky occur in micritic to fine-grained carbonate rocks believed to represent shallow-water facies. They are found at widely separated horizons in the Middle Ordovician High Bridge Group, the Middle and Upper Ordovician Lexington Limestone, and the Upper Ordovician Ashlock, Bull Fork, and Drakes Formations. In this sequence, the leperditicopes are represented by two genera of leperditiids, Eoleperditia Swartz, 1949 and Bivia Berdan, 1976, and six isochilinid genera, Isochilina Jones, 1858, Teichochilina Swartz, 1949, Ceratoleperditia Harris, 1960, Parabriartina n. gen., Kenodontochilina n. gen., and Saffordellina Bassler and Kellett, 1934; the type species of the hitherto poorly known genus Saffordellina, S. muralis (Ulrich and Bassler, 1923), is redescribed and refigured. In all, 18 taxa, of which 2 are in open nomenclature, are described and illustrated. In addition, the family Isochilinidae Swartz, 1949 is redefined to include genera without marginal brims and with straight ventral contact margins. The morphological characteristics of leperditicopid genera are discussed, and a table listing described genera and their diagnostic features is included.

Discriminating Induced-Microearthquakes Using New Seismic Features

NASA Astrophysics Data System (ADS)

Mousavi, S. M.; Horton, S.

2016-12-01

We studied characteristics of induced-microearthquakes on the basis of the waveforms recorded on a limited number of surface receivers using machine-learning techniques. Forty features in the time, frequency, and time-frequency domains were measured on each waveform, and several techniques such as correlation-based feature selection, Artificial Neural Networks (ANNs), Logistic Regression (LR) and X-mean were used as research tools to explore the relationship between these seismic features and source parameters. The results show that spectral features have the highest correlation to source depth. Two new measurements developed as seismic features for this study, spectral centroids and 2D cross-correlations in the time-frequency domain, performed better than the common seismic measurements. These features can be used by machine learning techniques for efficient automatic classification of low energy signals recorded at one or more seismic stations. We applied the technique to 440 microearthquakes-1.7Reference: Mousavi, S.M., S.P. Horton, C. A. Langston, B. Samei, (2016) Seismic features and automatic discrimination of deep and shallow induced-microearthquakes using neural network and logistic regression, Geophys. J. Int. doi: 10.1093/gji/ggw258.

The Role of Interaction Patterns with Hybrid Electric Vehicle Eco-Features for Drivers' Eco-Driving Performance.

PubMed

Arend, Matthias G; Franke, Thomas

2017-03-01

The objective of the present research was to understand drivers' interaction patterns with hybrid electric vehicles' (HEV) eco-features (electric propulsion, regenerative braking, neutral mode) and their relationship to fuel efficiency and driver characteristics (technical system knowledge, eco-driving motivation). Eco-driving (driving behaviors performed to achieve higher fuel efficiency) has the potential to reduce CO 2 emissions caused by road vehicles. Eco-driving in HEVs is particularly challenging due to the systems' dynamic energy flows. As a result, drivers are likely to show diverse eco-driving behaviors, depending on factors like knowledge and motivation. The eco-features represent an interface for the control of the systems' energy flows. A sample of 121 HEV drivers who had constantly logged their fuel consumption prior to the study participated in an online questionnaire. Drivers' interaction patterns with the eco-features were related to fuel efficiency. A common factor was identified in an exploratory factor analysis, characterizing the intensity of actively dealing with electric energy, which was also related to fuel efficiency. Driver characteristics were not related to this factor, yet they were significant predictors of fuel efficiency. From the perspective of user-energy interaction, the relationship of the aggregated factor to fuel efficiency emphasizes the central role of drivers' perception of and interaction with energy conversions in determining HEV eco-driving success. To arrive at an in-depth understanding of drivers' eco-driving behaviors that can guide interface design, authors of future research should be concerned with the psychological processes that underlie drivers' interaction patterns with eco-features.

Targeted Feature Detection for Data-Dependent Shotgun Proteomics

PubMed Central

2017-01-01

Label-free quantification of shotgun LC–MS/MS data is the prevailing approach in quantitative proteomics but remains computationally nontrivial. The central data analysis step is the detection of peptide-specific signal patterns, called features. Peptide quantification is facilitated by associating signal intensities in features with peptide sequences derived from MS2 spectra; however, missing values due to imperfect feature detection are a common problem. A feature detection approach that directly targets identified peptides (minimizing missing values) but also offers robustness against false-positive features (by assigning meaningful confidence scores) would thus be highly desirable. We developed a new feature detection algorithm within the OpenMS software framework, leveraging ideas and algorithms from the OpenSWATH toolset for DIA/SRM data analysis. Our software, FeatureFinderIdentification (“FFId”), implements a targeted approach to feature detection based on information from identified peptides. This information is encoded in an MS1 assay library, based on which ion chromatogram extraction and detection of feature candidates are carried out. Significantly, when analyzing data from experiments comprising multiple samples, our approach distinguishes between “internal” and “external” (inferred) peptide identifications (IDs) for each sample. On the basis of internal IDs, two sets of positive (true) and negative (decoy) feature candidates are defined. A support vector machine (SVM) classifier is then trained to discriminate between the sets and is subsequently applied to the “uncertain” feature candidates from external IDs, facilitating selection and confidence scoring of the best feature candidate for each peptide. This approach also enables our algorithm to estimate the false discovery rate (FDR) of the feature selection step. We validated FFId based on a public benchmark data set, comprising a yeast cell lysate spiked with protein standards

Characteristic features of a high-energy x-ray spectra estimation method based on the Waggener iterative perturbation principle

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

Iwasaki, Akira; Kubota, Mamoru; Hirota, Junichi

2006-11-15

We have redeveloped a high-energy x-ray spectra estimation method reported by Iwasaki et al. [A. Iwasaki, H. Matsutani, M. Kubota, A. Fujimori, K. Suzaki, and Y. Abe, Radiat. Phys. Chem. 67, 81-91 (2003)]. The method is based on the iterative perturbation principle to minimize differences between measured and calculated transmission curves, originally proposed by Waggener et al. [R. G. Waggener, M. M. Blough, J. A. Terry, D. Chen, N. E. Lee, S. Zhang, and W. D. McDavid, Med. Phys. 26, 1269-1278 (1999)]. The method can estimate spectra applicable for media at least from water to lead using only about tenmore » energy bins. Estimating spectra of 4-15 MV x-ray beams from a linear accelerator, we describe characteristic features of the method with regard to parameters including the prespectrum, number of transmission measurements, number of energy bins, energy bin widths, and artifactual bipeaked spectrum production.« less

Whole genome sequencing of Gyeongbuk Araucana, a newly developed blue-egg laying chicken breed, reveals its origin and genetic characteristics.

PubMed

Jeong, Hyeonsoo; Kim, Kwondo; Caetano-Anollés, Kelsey; Kim, Heebal; Kim, Byung-Ki; Yi, Jun-Koo; Ha, Jae-Jung; Cho, Seoae; Oh, Dong Yep

2016-05-24

Chicken, Gallus gallus, is a valuable species both as a food source and as a model organism for scientific research. Here, we sequenced the genome of Gyeongbuk Araucana, a rare chicken breed with unique phenotypic characteristics including flight ability, large body size, and laying blue-shelled eggs, to identify its genomic features. We generated genomes of Gyeongbuk Araucana, Leghorn, and Korean Native Chicken at a total of 33.5, 35.82, and 33.23 coverage depth, respectively. Along with the genomes of 12 Chinese breeds, we identified genomic variants of 16.3 million SNVs and 2.3 million InDels in mapped regions. Additionally, through assembly of unmapped reads and selective sweep, we identified candidate genes that fall into heart, vasculature and muscle development and body growth categories, which provided insight into Gyeongbuk Araucana's phenotypic traits. Finally, genetic variation based on the transposable element insertion pattern was investigated to elucidate the features of transposable elements related to blue egg shell formation. This study presents results of the first genomic study on the Gyeongbuk Araucana breed; it has potential to serve as an invaluable resource for future research on the genomic characteristics of this chicken breed as well as others.

Classification of product inspection items using nonlinear features

NASA Astrophysics Data System (ADS)

Talukder, Ashit; Casasent, David P.; Lee, H.-W.

1998-03-01

Automated processing and classification of real-time x-ray images of randomly oriented touching pistachio nuts is discussed. The ultimate objective is the development of a system for automated non-invasive detection of defective product items on a conveyor belt. This approach involves two main steps: preprocessing and classification. Preprocessing locates individual items and segments ones that touch using a modified watershed algorithm. The second stage involves extraction of features that allow discrimination between damaged and clean items (pistachio nuts). This feature extraction and classification stage is the new aspect of this paper. We use a new nonlinear feature extraction scheme called the maximum representation and discriminating feature (MRDF) extraction method to compute nonlinear features that are used as inputs to a classifier. The MRDF is shown to provide better classification and a better ROC (receiver operating characteristic) curve than other methods.

Features and characterization needs of rubber composite structures

NASA Technical Reports Server (NTRS)

Tabaddor, Farhad

1989-01-01

Some of the major unique features of rubber composite structures are outlined. The features covered are those related to the material properties, but the analytical features are also briefly discussed. It is essential to recognize these features at the planning stage of any long-range analytical, experimental, or application program. The development of a general and comprehensive program which fully accounts for all the important characteristics of tires, under all the relevant modes of operation, may present a prohibitively expensive and impractical task at the near future. There is therefore a need to develop application methodologies which can utilize the less general models, beyond their theoretical limitations and yet with reasonable reliability, by proper mix of analytical, experimental, and testing activities.

Clinical predictors of conversion to bipolar disorder in a prospective longitudinal familial high-risk sample: focus on depressive features.

PubMed

Frankland, Andrew; Roberts, Gloria; Holmes-Preston, Ellen; Perich, Tania; Levy, Florence; Lenroot, Rhoshel; Hadzi-Pavlovic, Dusan; Breakspear, Michael; Mitchell, Philip B

2017-11-07

Identifying clinical features that predict conversion to bipolar disorder (BD) in those at high familial risk (HR) would assist in identifying a more focused population for early intervention. In total 287 participants aged 12-30 (163 HR with a first-degree relative with BD and 124 controls (CONs)) were followed annually for a median of 5 years. We used the baseline presence of DSM-IV depressive, anxiety, behavioural and substance use disorders, as well as a constellation of specific depressive symptoms (as identified by the Probabilistic Approach to Bipolar Depression) to predict the subsequent development of hypo/manic episodes. At baseline, HR participants were significantly more likely to report ⩾4 Probabilistic features (40.4%) when depressed than CONs (6.7%; p < .05). Nineteen HR subjects later developed either threshold (n = 8; 4.9%) or subthreshold (n = 11; 6.7%) hypo/mania. The presence of ⩾4 Probabilistic features was associated with a seven-fold increase in the risk of 'conversion' to threshold BD (hazard ratio = 6.9, p < .05) above and beyond the fourteen-fold increase in risk related to major depressive episodes (MDEs) per se (hazard ratio = 13.9, p < .05). Individual depressive features predicting conversion were psychomotor retardation and ⩾5 MDEs. Behavioural disorders only predicted conversion to subthreshold BD (hazard ratio = 5.23, p < .01), while anxiety and substance disorders did not predict either threshold or subthreshold hypo/mania. This study suggests that specific depressive characteristics substantially increase the risk of young people at familial risk of BD going on to develop future hypo/manic episodes and may identify a more targeted HR population for the development of early intervention programs.

An Educational System to Help Students Assess Website Features and Identify High-Risk Websites

ERIC Educational Resources Information Center

Kajiyama, Tomoko; Echizen, Isao

2015-01-01

Purpose: The purpose of this paper is to propose an effective educational system to help students assess Web site risk by providing an environment in which students can better understand a Web site's features and determine the risks of accessing the Web site for themselves. Design/methodology/approach: The authors have enhanced a prototype…

Diabetes insipidus in pediatric germinomas of the suprasellar region: characteristic features and significance of the pituitary bright spot.

PubMed

Kilday, John-Paul; Laughlin, Suzanne; Urbach, Stacey; Bouffet, Eric; Bartels, Ute

2015-01-01

The pituitary bright spot is acknowledged to indicate functional integrity of the posterior pituitary gland, whilst its absence supports a diagnosis of central diabetes insipidus (DI). This feature was evaluated, together with the incidence and clinical characteristics of DI in children with suprasellar/neurohypophyseal germinomas. We performed a review of all suprasellar (SS) or bifocal (BF) germinoma pediatric patients treated in Toronto since 2000. Demographics, symptomatology, treatment outcome and imaging were evaluated. Nineteen patients fulfilled inclusion criteria (10 SS, 9 BF; median age 12.5 years (6.2-16.8 years)). All remained alive at 6.4 years median follow-up (1.2-13.7 years) after receiving chemotherapy and radiotherapy (13 focal/ventricular, four whole brain, two neuraxis), with only one progression. All had symptoms of DI at presentation with a symptom interval above one year in eight cases (42 %). Desmopressin was commenced and maintained in 16 patients (84 %). The pituitary bright spot was lost in most diagnostic interpretable cases, but was appreciated in three patients (18 %) who had normal serum sodium values compared to 'absent' cases (p = 0.013). For two such cases, spots remained visible until last follow-up (range 0.4-3.3 years), with one still receiving desmopressin. No case of bright spot recovery was observed following therapy. Protracted symptom intervals for germinoma-induced central DI may reflect poor clinical awareness. Explanations for persistence of the pituitary bright spot in symptomatic patients remain elusive. Desmopressin seldom reverses the clinical features of germinoma-induced DI to allow discontinuation, nor does treatment cause bright spot recovery.

Higher Growth Rate of Branch Duct Intraductal Papillary Mucinous Neoplasms Associates With Worrisome Features.

PubMed

Kolb, Jennifer M; Argiriadi, Pamela; Lee, Karen; Liu, Xiaoyu; Bagiella, Emilia; Lucas, Aimee L; Kim, Michelle Kang; Kumta, Nikhil A; Nagula, Satish; Sarpel, Umut; DiMaio, Christopher J

2018-03-11

For patients with branch duct intraductal papillary mucinous neoplasms (BD-IPMNs, cysts), it is a challenge to identify those at high risk for malignant lesions. We sought to identify factors associated with development of pancreatic cancer, focusing on neoplasm growth rate. We performed a retrospective study of 189 patients with BD-IPMNs who underwent at least 2 contrast-enhanced cross-sectional imaging studies, 1 year or more apart, at a tertiary referral center from January 2003 through 2013. Patients with cysts that had Fukuoka worrisome or high-risk features were excluded. Two radiologists reviewed all images. Cyst size was recorded at the initial and final imaging studies and growth rate was calculated. We collected patient demographic data, cyst characteristics, and clinical outcomes; univariate logistic regression models were used to determine the odds of developing worrisome features. The primary outcomes were to determine growth rate of low-risk BD-IPMNs and to assess whether cyst growth rate correlates high-risk features of IPMNs. Based on image analyses, cysts were initially a median 11 mm (range, 3-31 mm) and their final size was 12.5 mm (range, 3-42 mm). After a median follow-up time of 56 months (range, 12-163 months), the median cyst growth rate was 0.29 mm/year. Twelve patients developed worrisome features, no patients developed high-risk features, 4 patients had surgical resection, and no cancers developed. The rate of BD-IPMN growth was greater in patients who developed worrisome features than those who did not (2.84 mm/year vs 0.23 mm/year; P < .001). The odds of developing worrisome features increased for each unit (mm) increase in cyst size (odds ratio, 1.149; 95% CI, 1.035-1.276, P = .009). In a retrospective analysis of images from patients with BD-IPMN, we found low-risk BD-IPMNs to grow at an extremely low rate (less than 0.3 mm/year). BD-IPMNs in only about 6% of patients developed worrisome features, and none developed high-risk features

Sexual behaviors and situational characteristics of most recent male-partnered sexual event among gay and bisexually identified men in the United States.

PubMed

Rosenberger, Joshua G; Reece, Michael; Schick, Vanessa; Herbenick, Debby; Novak, David S; Van Der Pol, Barbara; Fortenberry, J Dennis

2011-11-01

Recent nationally representative studies documenting event-level sexual behavior have included samples that are predominantly heterosexual, resulting in limited information on the sexual repertoire of gay and bisexually identified men. This study sought to document the sexual behaviors that gay and bisexually identified men report during their most recent male-partnered sexual event and to describe the situational characteristics and participants' evaluation of these events. Via an internet-based survey, data were collected from 24,787 gay and bisexually identified men (ages 18-87 years) from 50 US states and the District of Columbia. Measures included items related to sociodemographics, recent sexual behavior history, situational characteristics, orgasm, and ratings of arousal and pleasure. Participants' mean age was 39.2 years; ethnicities included white (84.6%), Latino (6.4%), and African American (3.6%); and most men (79.9%) identified as homosexual. The most commonly reported behavior was kissing a partner on the mouth (74.5%), followed by oral sex (72.7%), and partnered masturbation (68.4%). Anal intercourse occurred among less than half of participants (37.2%) and was most common among men ages 18-24 (42.7%). Sex was most likely to occur in the participant's home (46.8%), with less frequently reported locations including hotels (7.4%) and public spaces (3.1%). The number of behaviors engaged in during last sexual event varied with most (63.2%) including 5-9 different sexual behaviors. These data provide one of the first examinations of sexual behaviors during the most recent male-partnered sexual event among gay and bisexually identified men in the United States. Findings from this study suggest that gay and bisexually identified men have a diverse sexual repertoire and that partnered sexual behaviors are not limited solely to acts of penile insertion. © 2011 International Society for Sexual Medicine.

Dynamics of feature categorization.

PubMed

Martí, Daniel; Rinzel, John

2013-01-01

In visual and auditory scenes, we are able to identify shared features among sensory objects and group them according to their similarity. This grouping is preattentive and fast and is thought of as an elementary form of categorization by which objects sharing similar features are clustered in some abstract perceptual space. It is unclear what neuronal mechanisms underlie this fast categorization. Here we propose a neuromechanistic model of fast feature categorization based on the framework of continuous attractor networks. The mechanism for category formation does not rely on learning and is based on biologically plausible assumptions, for example, the existence of populations of neurons tuned to feature values, feature-specific interactions, and subthreshold-evoked responses upon the presentation of single objects. When the network is presented with a sequence of stimuli characterized by some feature, the network sums the evoked responses and provides a running estimate of the distribution of features in the input stream. If the distribution of features is structured into different components or peaks (i.e., is multimodal), recurrent excitation amplifies the response of activated neurons, and categories are singled out as emerging localized patterns of elevated neuronal activity (bumps), centered at the centroid of each cluster. The emergence of bump states through sequential, subthreshold activation and the dependence on input statistics is a novel application of attractor networks. We show that the extraction and representation of multiple categories are facilitated by the rich attractor structure of the network, which can sustain multiple stable activity patterns for a robust range of connectivity parameters compatible with cortical physiology.

Features of computerized clinical decision support systems supportive of nursing practice: a literature review.

PubMed

Lee, Seonah

2013-10-01

This study aimed to organize the system features of decision support technologies targeted at nursing practice into assessment, problem identification, care plans, implementation, and outcome evaluation. It also aimed to identify the range of the five stage-related sequential decision supports that computerized clinical decision support systems provided. MEDLINE, CINAHL, and EMBASE were searched. A total of 27 studies were reviewed. The system features collected represented the characteristics of each category from patient assessment to outcome evaluation. Several features were common across the reviewed systems. For the sequential decision support, all of the reviewed systems provided decision support in sequence for patient assessment and care plans. Fewer than half of the systems included problem identification. There were only three systems operating in an implementation stage and four systems in outcome evaluation. Consequently, the key steps for sequential decision support functions were initial patient assessment, problem identification, care plan, and outcome evaluation. Providing decision support in such a full scope will effectively help nurses' clinical decision making. By organizing the system features, a comprehensive picture of nursing practice-oriented computerized decision support systems was obtained; however, the development of a guideline for better systems should go beyond the scope of a literature review.

Hadoop neural network for parallel and distributed feature selection.

PubMed

Hodge, Victoria J; O'Keefe, Simon; Austin, Jim

2016-06-01

In this paper, we introduce a theoretical basis for a Hadoop-based neural network for parallel and distributed feature selection in Big Data sets. It is underpinned by an associative memory (binary) neural network which is highly amenable to parallel and distributed processing and fits with the Hadoop paradigm. There are many feature selectors described in the literature which all have various strengths and weaknesses. We present the implementation details of five feature selection algorithms constructed using our artificial neural network framework embedded in Hadoop YARN. Hadoop allows parallel and distributed processing. Each feature selector can be divided into subtasks and the subtasks can then be processed in parallel. Multiple feature selectors can also be processed simultaneously (in parallel) allowing multiple feature selectors to be compared. We identify commonalities among the five features selectors. All can be processed in the framework using a single representation and the overall processing can also be greatly reduced by only processing the common aspects of the feature selectors once and propagating these aspects across all five feature selectors as necessary. This allows the best feature selector and the actual features to select to be identified for large and high dimensional data sets through exploiting the efficiency and flexibility of embedding the binary associative-memory neural network in Hadoop. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Distribution and Characteristics of Seafloor Seepage Features in the Active Margin Offshore of SW Taiwan

NASA Astrophysics Data System (ADS)

Chen, T. T.; Hsu, H. H.; Liu, C. S.; Su, C. C.; Paull, C. K.; Chen, Y. H.; Caress, D. W.; Gwiazda, R.; Lundsten, E. M.

2017-12-01

In the active margin offshore of southwest (SW) Taiwan, west-vergent imbricated thrusts, folds and dipping strata are the main structural features. This is also the area where gas hydrates are widely distributed beneath the seafloor. Fluids from deep strata may migrate upwards along porous dipping layers or faults and then vent out to form seafloor seepage features in many of the gas hydrate prospects. A joint survey was conducted in May 2017 using MBARI mapping AUV and miniROV to investigate the seafloor seepage features. Numerous comet-shaped depressions (CSD) are mapped along flanks of several anticlinal ridges, and four carbonate mounds around CSD are observed from the ultra-high-resolution (1-m lateral resolution) bathymetry data collected by AUV. Samples of the carbonate mounds were collected by the mini-ROV, and their mineral compositions contain dolomite and ankerite. The AUV collected chirp sonar profiles and previously collected surface ship multichannel seismic reflection profiles across these seafloor features show that potential fluid migration pathways connect free gas trapped below the base of gas hydrate stability zone and the seafloor in the vicinity of these features. Our study suggests that the CSD could be an indicator of seafloor seepage and may be distribution widely in the active margin setting.

Identifying childhood characteristics that underlie premorbid risk for substance use disorders: socialization and boldness.

PubMed

Hicks, Brian M; Iacono, William G; McGue, Matt

2014-02-01

We utilized a longitudinal twin study (N = 2,510) to identify the child characteristics present prior to initiation of substance use that best predicted later substance use disorders. Two independent traits accounted for the majority of premorbid risk: socialization (conformity to rules and conventional values) and boldness (sociability and social assurance, stress resilience, and thrill seeking). Low socialization was associated with disruptive behavior disorders, parental externalizing disorders, and environmental adversity and exhibited moderate genetic (0.45) and shared environmental influences (0.30). Boldness was highly heritable (0.71) and associated with less internalizing distress and environmental adversity. In combination, these traits exhibited robust associations with adolescent and young adult substance use disorders (R = .48 and .50, respectively) and incremental prediction over disruptive behavior disorders, parental externalizing disorders, and environmental adversity. The results were replicated in an independent sample. Socialization and boldness offer a novel conceptualization of underlying risk for substance use disorders that has the potential to improve prediction and theory with implications for basic research, prevention, and intervention.

Duodenal L cell density correlates with features of metabolic syndrome and plasma metabolites.

PubMed

van Baar, Annieke C G; Prodan, Andrei; Wahlgren, Camilla D; Poulsen, Steen S; Knop, Filip K; Groen, Albert K; Bergman, Jacques J; Nieuwdorp, Max; Levin, Evgeni

2018-05-01

Enteroendocrine cells are essential for the regulation of glucose metabolism, but it is unknown whether they are associated with clinical features of metabolic syndrome (MetS) and fasting plasma metabolites. We aimed to identify fasting plasma metabolites that associate with duodenal L cell, K cell and delta cell densities in subjects with MetS with ranging levels of insulin resistance. In this cross-sectional study, we evaluated L, K and delta cell density in duodenal biopsies from treatment-naïve males with MetS using machine-learning methodology. We identified specific clinical biomarkers and plasma metabolites associated with L cell and delta cell density. L cell density was associated with increased plasma metabolite levels including symmetrical dimethylarginine, 3-aminoisobutyric acid, kynurenine and glycine. In turn, these L cell-linked fasting plasma metabolites correlated with clinical features of MetS. Our results indicate a link between duodenal L cells, plasma metabolites and clinical characteristics of MetS. We conclude that duodenal L cells associate with plasma metabolites that have been implicated in human glucose metabolism homeostasis. Disentangling the causal relation between L cells and these metabolites might help to improve the (small intestinal-driven) pathophysiology behind insulin resistance in human obesity. © 2018 The authors.

Intraosseous mucoepidermoid carcinoma: a review of the diagnostic imaging features of four jaw cases.

PubMed

Chan, K C; Pharoah, M; Lee, L; Weinreb, I; Perez-Ordonez, B

2013-01-01

The purpose of this case series is to present the common features of intraosseous mucoepidermoid carcinoma (IMC) of the jaws in plain film and CT imaging. Two oral and maxillofacial radiologists reviewed and characterized the common features of four biopsy-proven cases of IMC in the jaws in plain film and CT imaging obtained from the files of the Department of Oral Radiology, Faculty of Dentistry, University of Toronto, Toronto, Canada. The common features are a well-defined sclerotic periphery, the presence of internal amorphous sclerotic bone and numerous small loculations, lack of septae bordering many of the loculations, and expansion and perforation of the outer cortical plate with extension into surrounding soft tissue. Other characteristics include tooth displacement and root resorption. The four cases of IMC reviewed have common imaging characteristics. All cases share some diagnostic imaging features with other multilocular-appearing entities of the jaws. However, the presence of amorphous sclerotic bone and malignant characteristics can be useful in the differential diagnosis.

A Tale of Two Methods: Chart and Interview Methods for Identifying Delirium

PubMed Central

Saczynski, Jane S.; Kosar, Cyrus M.; Xu, Guoquan; Puelle, Margaret R.; Schmitt, Eva; Jones, Richard N.; Marcantonio, Edward R.; Wong, Bonnie; Isaza, Ilean; Inouye, Sharon K.

2014-01-01

Background Interview and chart-based methods for identifying delirium have been validated. However, relative strengths and limitations of each method have not been described, nor has a combined approach (using both interviews and chart), been systematically examined. Objectives To compare chart and interview-based methods for identification of delirium. Design, Setting and Participants Participants were 300 patients aged 70+ undergoing major elective surgery (majority were orthopedic surgery) interviewed daily during hospitalization for delirium using the Confusion Assessment Method (CAM; interview-based method) and whose medical charts were reviewed for delirium using a validated chart-review method (chart-based method). We examined rate of agreement on the two methods and patient characteristics of those identified using each approach. Predictive validity for clinical outcomes (length of stay, postoperative complications, discharge disposition) was compared. In the absence of a gold-standard, predictive value could not be calculated. Results The cumulative incidence of delirium was 23% (n= 68) by the interview-based method, 12% (n=35) by the chart-based method and 27% (n=82) by the combined approach. Overall agreement was 80%; kappa was 0.30. The methods differed in detection of psychomotor features and time of onset. The chart-based method missed delirium in CAM-identified patients laacking features of psychomotor agitation or inappropriate behavior. The CAM-based method missed chart-identified cases occurring during the night shift. The combined method had high predictive validity for all clinical outcomes. Conclusions Interview and chart-based methods have specific strengths for identification of delirium. A combined approach captures the largest number and the broadest range of delirium cases. PMID:24512042

Metric and morphological assessment of facial features: a study on three European populations.

PubMed

Ritz-Timme, S; Gabriel, P; Tutkuviene, J; Poppa, P; Obertová, Z; Gibelli, D; De Angelis, D; Ratnayake, M; Rizgeliene, R; Barkus, A; Cattaneo, C

2011-04-15

Identification from video surveillance systems is becoming more and more frequent in the forensic practice. In this field, different techniques have been improved such as height estimation and gait analysis. However, the most natural approach for identifying a person in everyday life is based on facial characteristics. Scientifically, faces can be described using morphological and metric assessment of facial features. The morphological approach is largely affected by the subjective opinion of the observer, which can be mitigated by the application of descriptive atlases. In addition, this approach requires one to investigate which are the most common and rare facial characteristics in different populations. For the metric approach further studies are necessary in order to point out possible metric differences within and between different populations. The acquisition of statistically adequate population data may provide useful information for the reconstruction of biological profiles of unidentified individuals, particularly concerning ethnic affiliation, and possibly also for personal identification. This study presents the results of the morphological and metric assessment of the head and face of 900 male subjects between 20 and 31 years from Italy, Germany and Lithuania. The evaluation of the morphological traits was performed using the DMV atlas with 43 pre-defined facial characteristics. The frequencies of the types of facial features were calculated for each population in order to establish the rarest characteristics which may be used for the purpose of a biological profile and consequently for personal identification. Metric analysis performed in vivo included 24 absolute measurements and 24 indices of the head and face, including body height and body weight. The comparison of the frequencies of morphological facial features showed many similarities between the samples from Germany, Italy and Lithuania. However, several characteristics were rare or

Clinical features of movement disorders.

PubMed

Yung, C Y

1983-08-01

The descriptive aspects of all types of movement disorders and their related syndromes and terminologies used in the literature are reviewed and described. This comprises the features of (a) movement disorders secondary to neurological diseases affecting the extrapyramidal motor system, such as: athetosis, chorea, dystonia, hemiballismus, myoclonus, tremor, tics and spasm, (b) drug induced movement disorders, such as: akathisia, akinesia, hyperkinesia, dyskinesias, extrapyramidal syndrome, and tardive dyskinesia, and (c) abnormal movements in psychiatric disorders, such as: mannerism, stereotyped behaviour and psychomotor retardation. It is intended to bring about a more comprehensive overview of these movement disorders from a phenomenological perspective, so that clinicians can familiarize with these features for diagnosis. Some general statements are made in regard to some of the characteristics of movement disorders.

Ability of Slovakian Pupils to Identify Birds

ERIC Educational Resources Information Center

Prokop, Pavol; Rodak, Rastislav

2009-01-01

A pupil's ability to identify common organisms is necessary for acquiring further knowledge of biology. We investigated how pupils were able to identify 25 bird species following their song, growth habits, or both features presented simultaneously. Just about 19% of birds were successfully identified by song, about 39% by growth habit, and 45% of…

qFeature

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

2015-09-14

This package contains statistical routines for extracting features from multivariate time-series data which can then be used for subsequent multivariate statistical analysis to identify patterns and anomalous behavior. It calculates local linear or quadratic regression model fits to moving windows for each series and then summarizes the model coefficients across user-defined time intervals for each series. These methods are domain agnostic-but they have been successfully applied to a variety of domains, including commercial aviation and electric power grid data.

Dermoscopic features of nail psoriasis treated with biologics.

PubMed

Hashimoto, Yuki; Uyama, Miki; Takada, Yuko; Yoshida, Kenji; Ishiko, Akira

2017-05-01

Although psoriatic nail lesions are small, they cause considerable discomfort for patients and adversely affect quality of life. Few studies have evaluated the dermoscopic features of psoriatic nails. The aim of this study was to clarify the dermoscopic features of nail psoriasis and identify those that reflect psoriatic activity. During biologic treatment of psoriasis, six patients with psoriatic nails twice underwent dermoscopic examination, with an interval of 17-42 weeks. We used the modified Nail Psoriasis Severity Index score and Psoriasis Area and Severity Index score to identify and assess dermoscopic features. We identified 10 dermoscopic findings, of which disappearance of diffuse scaling of the nail plate, transverse step-like notches and splinter hemorrhages of the nail bed, and appearance of erythematous borders of the onycholytic area were associated with improvement in Psoriasis Area and Severity Index score. Dermoscopy can detect nail changes during psoriasis treatment and should be used to evaluate treatment success. © 2017 Japanese Dermatological Association.

Interpretation of Appearance: The Effect of Facial Features on First Impressions and Personality

PubMed Central

Wolffhechel, Karin; Fagertun, Jens; Jacobsen, Ulrik Plesner; Majewski, Wiktor; Hemmingsen, Astrid Sofie; Larsen, Catrine Lohmann; Lorentzen, Sofie Katrine; Jarmer, Hanne

2014-01-01

Appearance is known to influence social interactions, which in turn could potentially influence personality development. In this study we focus on discovering the relationship between self-reported personality traits, first impressions and facial characteristics. The results reveal that several personality traits can be read above chance from a face, and that facial features influence first impressions. Despite the former, our prediction model fails to reliably infer personality traits from either facial features or first impressions. First impressions, however, could be inferred more reliably from facial features. We have generated artificial, extreme faces visualising the characteristics having an effect on first impressions for several traits. Conclusively, we find a relationship between first impressions, some personality traits and facial features and consolidate that people on average assess a given face in a highly similar manner. PMID:25233221

Interpretation of appearance: the effect of facial features on first impressions and personality.

PubMed

Wolffhechel, Karin; Fagertun, Jens; Jacobsen, Ulrik Plesner; Majewski, Wiktor; Hemmingsen, Astrid Sofie; Larsen, Catrine Lohmann; Lorentzen, Sofie Katrine; Jarmer, Hanne

2014-01-01

Appearance is known to influence social interactions, which in turn could potentially influence personality development. In this study we focus on discovering the relationship between self-reported personality traits, first impressions and facial characteristics. The results reveal that several personality traits can be read above chance from a face, and that facial features influence first impressions. Despite the former, our prediction model fails to reliably infer personality traits from either facial features or first impressions. First impressions, however, could be inferred more reliably from facial features. We have generated artificial, extreme faces visualising the characteristics having an effect on first impressions for several traits. Conclusively, we find a relationship between first impressions, some personality traits and facial features and consolidate that people on average assess a given face in a highly similar manner.

Computerized Macular Pathology Diagnosis in Spectral Domain Optical Coherence Tomography Scans Based on Multiscale Texture and Shape Features

PubMed Central

Liu, Yu-Ying; Chen, Mei; Wollstein, Gadi; Duker, Jay S.; Fujimoto, James G.; Schuman, Joel S.; Rehg, James M.

2011-01-01

Purpose. To develop an automated method to identify the normal macula and three macular pathologies (macular hole [MH], macular edema [ME], and age-related macular degeneration [AMD]) from the fovea-centered cross sections in three-dimensional (3D) spectral-domain optical coherence tomography (SD-OCT) images. Methods. A sample of SD-OCT macular scans (macular cube 200 × 200 or 512 × 128 scan protocol; Cirrus HD-OCT; Carl Zeiss Meditec, Inc., Dublin, CA) was obtained from healthy subjects and subjects with MH, ME, and/or AMD (dataset for development: 326 scans from 136 subjects [193 eyes], and dataset for testing: 131 scans from 37 subjects [58 eyes]). A fovea-centered cross-sectional slice for each of the SD-OCT images was encoded using spatially distributed multiscale texture and shape features. Three ophthalmologists labeled each fovea-centered slice independently, and the majority opinion for each pathology was used as the ground truth. Machine learning algorithms were used to identify the discriminative features automatically. Two-class support vector machine classifiers were trained to identify the presence of normal macula and each of the three pathologies separately. The area under the receiver operating characteristic curve (AUC) was calculated to assess the performance. Results. The cross-validation AUC result on the development dataset was 0.976, 0.931, 0939, and 0.938, and the AUC result on the holdout testing set was 0.978, 0.969, 0.941, and 0.975, for identifying normal macula, MH, ME, and AMD, respectively. Conclusions. The proposed automated data-driven method successfully identified various macular pathologies (all AUC > 0.94). This method may effectively identify the discriminative features without relying on a potentially error-prone segmentation module. PMID:21911579

A stereo remote sensing feature selection method based on artificial bee colony algorithm

NASA Astrophysics Data System (ADS)

Yan, Yiming; Liu, Pigang; Zhang, Ye; Su, Nan; Tian, Shu; Gao, Fengjiao; Shen, Yi

2014-05-01

To improve the efficiency of stereo information for remote sensing classification, a stereo remote sensing feature selection method is proposed in this paper presents, which is based on artificial bee colony algorithm. Remote sensing stereo information could be described by digital surface model (DSM) and optical image, which contain information of the three-dimensional structure and optical characteristics, respectively. Firstly, three-dimensional structure characteristic could be analyzed by 3D-Zernike descriptors (3DZD). However, different parameters of 3DZD could descript different complexity of three-dimensional structure, and it needs to be better optimized selected for various objects on the ground. Secondly, features for representing optical characteristic also need to be optimized. If not properly handled, when a stereo feature vector composed of 3DZD and image features, that would be a lot of redundant information, and the redundant information may not improve the classification accuracy, even cause adverse effects. To reduce information redundancy while maintaining or improving the classification accuracy, an optimized frame for this stereo feature selection problem is created, and artificial bee colony algorithm is introduced for solving this optimization problem. Experimental results show that the proposed method can effectively improve the computational efficiency, improve the classification accuracy.

Neuropathologic features associated with Alzheimer disease diagnosis

PubMed Central

Grinberg, L.T.; Miller, B.; Kawas, C.; Yaffe, K.

2011-01-01

Objective: To examine whether the association between clinical Alzheimer disease (AD) diagnosis and neuropathology and the precision by which neuropathology differentiates people with clinical AD from those with normal cognition varies by age. Methods: We conducted a cross-sectional analysis of 2,014 older adults (≥70 years at death) from the National Alzheimer's Coordinating Center database with clinical diagnosis of normal cognition (made ≤1 year before death, n = 419) or AD (at ≥65 years, n = 1,595) and a postmortem neuropathologic examination evaluating AD pathology (neurofibrillary tangles, neuritic plaques) and non-AD pathology (diffuse plaques, amyloid angiopathy, Lewy bodies, macrovascular disease, microvascular disease). We used adjusted logistic regression to analyze the relationship between clinical AD diagnosis and neuropathologic features, area under the receiver operating characteristic curve (c statistic) to evaluate how precisely neuropathology differentiates between cognitive diagnoses, and an interaction to identify effect modification by age group. Results: In a model controlling for coexisting neuropathologic features, the relationship between clinical AD diagnosis and neurofibrillary tangles was significantly weaker with increasing age (p < 0.001 for interaction). The aggregate of all neuropathologic features more strongly differentiated people with clinical AD from those without in younger age groups (70–74 years: c statistic, 95% confidence interval: 0.93, 0.89–0.96; 75–84 years: 0.95, 0.87–0.95; ≥85 years: 0.83, 0.80–0.87). Non-AD pathology significantly improved precision of differentiation across all age groups (p < 0.004). Conclusion: Clinical AD diagnosis was more weakly associated with neurofibrillary tangles among the oldest old compared to younger age groups, possibly due to less accurate clinical diagnosis, better neurocompensation, or unaccounted pathology among the oldest old. PMID:22031532

Computation and evaluation of features of surface electromyogram to identify the force of muscle contraction and muscle fatigue.

PubMed

Arjunan, Sridhar P; Kumar, Dinesh K; Naik, Ganesh

2014-01-01

The relationship between force of muscle contraction and muscle fatigue with six different features of surface electromyogram (sEMG) was determined by conducting experiments on thirty-five volunteers. The participants performed isometric contractions at 50%, 75%, and 100% of their maximum voluntary contraction (MVC). Six features were considered in this study: normalised spectral index (NSM5), median frequency, root mean square, waveform length, normalised root mean square (NRMS), and increase in synchronization (IIS) index. Analysis of variance (ANOVA) and linear regression analysis were performed to determine the significance of the feature with respect to the three factors: muscle force, muscle fatigue, and subject. The results show that IIS index of sEMG had the highest correlation with muscle fatigue and the relationship was statistically significant (P < 0.01), while NSM5 associated best with level of muscle contraction (%MVC) (P < 0.01). Both of these features were not affected by the intersubject variations (P > 0.05).

Computation and Evaluation of Features of Surface Electromyogram to Identify the Force of Muscle Contraction and Muscle Fatigue

PubMed Central

Arjunan, Sridhar P.; Kumar, Dinesh K.; Naik, Ganesh

2014-01-01

The relationship between force of muscle contraction and muscle fatigue with six different features of surface electromyogram (sEMG) was determined by conducting experiments on thirty-five volunteers. The participants performed isometric contractions at 50%, 75%, and 100% of their maximum voluntary contraction (MVC). Six features were considered in this study: normalised spectral index (NSM5), median frequency, root mean square, waveform length, normalised root mean square (NRMS), and increase in synchronization (IIS) index. Analysis of variance (ANOVA) and linear regression analysis were performed to determine the significance of the feature with respect to the three factors: muscle force, muscle fatigue, and subject. The results show that IIS index of sEMG had the highest correlation with muscle fatigue and the relationship was statistically significant (P < 0.01), while NSM5 associated best with level of muscle contraction (%MVC) (P < 0.01). Both of these features were not affected by the intersubject variations (P > 0.05). PMID:24995275

Online feature selection with streaming features.

PubMed

Wu, Xindong; Yu, Kui; Ding, Wei; Wang, Hao; Zhu, Xingquan

2013-05-01

We propose a new online feature selection framework for applications with streaming features where the knowledge of the full feature space is unknown in advance. We define streaming features as features that flow in one by one over time whereas the number of training examples remains fixed. This is in contrast with traditional online learning methods that only deal with sequentially added observations, with little attention being paid to streaming features. The critical challenges for Online Streaming Feature Selection (OSFS) include 1) the continuous growth of feature volumes over time, 2) a large feature space, possibly of unknown or infinite size, and 3) the unavailability of the entire feature set before learning starts. In the paper, we present a novel Online Streaming Feature Selection method to select strongly relevant and nonredundant features on the fly. An efficient Fast-OSFS algorithm is proposed to improve feature selection performance. The proposed algorithms are evaluated extensively on high-dimensional datasets and also with a real-world case study on impact crater detection. Experimental results demonstrate that the algorithms achieve better compactness and higher prediction accuracy than existing streaming feature selection algorithms.

ASL, Total Communication and Oralism: Identifying Shared Characteristics of School-Based Writing Intervention Programs for Deaf and Hard-of-Hearing Students, K-6

ERIC Educational Resources Information Center

Reed, Carolyn Mascia

2009-01-01

To be effective in providing a writing literacy program, regardless of communication approaches, educators should establish program-wide conditions that promote English writing literacy over time. The researcher's purpose for this study was to identify shared characteristics of writing intervention programs in three different communication school…

Low-Dimensional Feature Representation for Instrument Identification

NASA Astrophysics Data System (ADS)

Ihara, Mizuki; Maeda, Shin-Ichi; Ikeda, Kazushi; Ishii, Shin

For monophonic music instrument identification, various feature extraction and selection methods have been proposed. One of the issues toward instrument identification is that the same spectrum is not always observed even in the same instrument due to the difference of the recording condition. Therefore, it is important to find non-redundant instrument-specific features that maintain information essential for high-quality instrument identification to apply them to various instrumental music analyses. For such a dimensionality reduction method, the authors propose the utilization of linear projection methods: local Fisher discriminant analysis (LFDA) and LFDA combined with principal component analysis (PCA). After experimentally clarifying that raw power spectra are actually good for instrument classification, the authors reduced the feature dimensionality by LFDA or by PCA followed by LFDA (PCA-LFDA). The reduced features achieved reasonably high identification performance that was comparable or higher than those by the power spectra and those achieved by other existing studies. These results demonstrated that our LFDA and PCA-LFDA can successfully extract low-dimensional instrument features that maintain the characteristic information of the instruments.

Rotation invariant features for wear particle classification

NASA Astrophysics Data System (ADS)

Arof, Hamzah; Deravi, Farzin

1997-09-01

This paper investigates the ability of a set of rotation invariant features to classify images of wear particles found in used lubricating oil of machinery. The rotation invariant attribute of the features is derived from the property of the magnitudes of Fourier transform coefficients that do not change with spatial shift of the input elements. By analyzing individual circular neighborhoods centered at every pixel in an image, local and global texture characteristics of an image can be described. A number of input sequences are formed by the intensities of pixels on concentric rings of various radii measured from the center of each neighborhood. Fourier transforming the sequences would generate coefficients whose magnitudes are invariant to rotation. Rotation invariant features extracted from these coefficients were utilized to classify wear particle images that were obtained from a number of different particles captured at different orientations. In an experiment involving images of 6 classes, the circular neighborhood features obtained a 91% recognition rate which compares favorably to a 76% rate achieved by features of a 6 by 6 co-occurrence matrix.

Recovering faces from memory: the distracting influence of external facial features.

PubMed

Frowd, Charlie D; Skelton, Faye; Atherton, Chris; Pitchford, Melanie; Hepton, Gemma; Holden, Laura; McIntyre, Alex H; Hancock, Peter J B

2012-06-01

Recognition memory for unfamiliar faces is facilitated when contextual cues (e.g., head pose, background environment, hair and clothing) are consistent between study and test. By contrast, inconsistencies in external features, especially hair, promote errors in unfamiliar face-matching tasks. For the construction of facial composites, as carried out by witnesses and victims of crime, the role of external features (hair, ears, and neck) is less clear, although research does suggest their involvement. Here, over three experiments, we investigate the impact of external features for recovering facial memories using a modern, recognition-based composite system, EvoFIT. Participant-constructors inspected an unfamiliar target face and, one day later, repeatedly selected items from arrays of whole faces, with "breeding," to "evolve" a composite with EvoFIT; further participants (evaluators) named the resulting composites. In Experiment 1, the important internal-features (eyes, brows, nose, and mouth) were constructed more identifiably when the visual presence of external features was decreased by Gaussian blur during construction: higher blur yielded more identifiable internal-features. In Experiment 2, increasing the visible extent of external features (to match the target's) in the presented face-arrays also improved internal-features quality, although less so than when external features were masked throughout construction. Experiment 3 demonstrated that masking external-features promoted substantially more identifiable images than using the previous method of blurring external-features. Overall, the research indicates that external features are a distractive rather than a beneficial cue for face construction; the results also provide a much better method to construct composites, one that should dramatically increase identification of offenders.

A feature-based approach to modeling protein–protein interaction hot spots

PubMed Central

Cho, Kyu-il; Kim, Dongsup; Lee, Doheon

2009-01-01

Identifying features that effectively represent the energetic contribution of an individual interface residue to the interactions between proteins remains problematic. Here, we present several new features and show that they are more effective than conventional features. By combining the proposed features with conventional features, we develop a predictive model for interaction hot spots. Initially, 54 multifaceted features, composed of different levels of information including structure, sequence and molecular interaction information, are quantified. Then, to identify the best subset of features for predicting hot spots, feature selection is performed using a decision tree. Based on the selected features, a predictive model for hot spots is created using support vector machine (SVM) and tested on an independent test set. Our model shows better overall predictive accuracy than previous methods such as the alanine scanning methods Robetta and FOLDEF, and the knowledge-based method KFC. Subsequent analysis yields several findings about hot spots. As expected, hot spots have a larger relative surface area burial and are more hydrophobic than other residues. Unexpectedly, however, residue conservation displays a rather complicated tendency depending on the types of protein complexes, indicating that this feature is not good for identifying hot spots. Of the selected features, the weighted atomic packing density, relative surface area burial and weighted hydrophobicity are the top 3, with the weighted atomic packing density proving to be the most effective feature for predicting hot spots. Notably, we find that hot spots are closely related to π–related interactions, especially π · · · π interactions. PMID:19273533

A feature-based approach to modeling protein-protein interaction hot spots.

PubMed

Cho, Kyu-il; Kim, Dongsup; Lee, Doheon

2009-05-01

Identifying features that effectively represent the energetic contribution of an individual interface residue to the interactions between proteins remains problematic. Here, we present several new features and show that they are more effective than conventional features. By combining the proposed features with conventional features, we develop a predictive model for interaction hot spots. Initially, 54 multifaceted features, composed of different levels of information including structure, sequence and molecular interaction information, are quantified. Then, to identify the best subset of features for predicting hot spots, feature selection is performed using a decision tree. Based on the selected features, a predictive model for hot spots is created using support vector machine (SVM) and tested on an independent test set. Our model shows better overall predictive accuracy than previous methods such as the alanine scanning methods Robetta and FOLDEF, and the knowledge-based method KFC. Subsequent analysis yields several findings about hot spots. As expected, hot spots have a larger relative surface area burial and are more hydrophobic than other residues. Unexpectedly, however, residue conservation displays a rather complicated tendency depending on the types of protein complexes, indicating that this feature is not good for identifying hot spots. Of the selected features, the weighted atomic packing density, relative surface area burial and weighted hydrophobicity are the top 3, with the weighted atomic packing density proving to be the most effective feature for predicting hot spots. Notably, we find that hot spots are closely related to pi-related interactions, especially pi . . . pi interactions.

Geomorphic domains and linear features on Landsat images, Circle Quadrangle, Alaska

USGS Publications Warehouse

Simpson, S.L.

1984-01-01

A remote sensing study using Landsat images was undertaken as part of the Alaska Mineral Resource Assessment Program (AMRAP). Geomorphic domains A and B, identified on enhanced Landsat images, divide Circle quadrangle south of Tintina fault zone into two regional areas having major differences in surface characteristics. Domain A is a roughly rectangular, northeast-trending area of relatively low relief and simple, widely spaced drainages, except where igneous rocks are exposed. In contrast, domain B, which bounds two sides of domain A, is more intricately dissected showing abrupt changes in slope and relatively high relief. The northwestern part of geomorphic domain A includes a previously mapped tectonostratigraphic terrane. The southeastern boundary of domain A occurs entirely within the adjoining tectonostratigraphic terrane. The sharp geomorphic contrast along the southeastern boundary of domain A and the existence of known faults along this boundary suggest that the southeastern part of domain A may be a subdivision of the adjoining terrane. Detailed field studies would be necessary to determine the characteristics of the subdivision. Domain B appears to be divisible into large areas of different geomorphic terrains by east-northeast-trending curvilinear lines drawn on Landsat images. Segments of two of these lines correlate with parts of boundaries of mapped tectonostratigraphic terranes. On Landsat images prominent north-trending lineaments together with the curvilinear lines form a large-scale regional pattern that is transected by mapped north-northeast-trending high-angle faults. The lineaments indicate possible lithlogic variations and/or structural boundaries. A statistical strike-frequency analysis of the linear features data for Circle quadrangle shows that northeast-trending linear features predominate throughout, and that most northwest-trending linear features are found south of Tintina fault zone. A major trend interval of N.64-72E. in the linear

Identifying Childhood Characteristics that Underlie Pre-Morbid Risk for Substance Use Disorders: Socialization and Boldness

PubMed Central

Hicks, Brian M.; Iacono, William G.; McGue, Matt

2013-01-01

Utilizing a longitudinal twin study (N = 2510), we identified the child characteristics present prior to initiation of substance use that best predicted later substance use disorders. Two independent traits accounted for the majority of pre-morbid risk: socialization (conformity to rules and conventional values) and boldness (sociability and social assurance, stress resilience, and thrill seeking). Low socialization was associated with disruptive behavior disorders, parental externalizing disorders, and environmental adversity, and exhibited moderate genetic (.45) and shared environmental influences (.30). Boldness was highly heritable (.71) and associated with less internalizing distress and environmental adversity. Together, these traits exhibited robust associations with adolescent and young adult substance use disorders (R = .48 and .50, respectively), and incremental prediction over disruptive behavior disorders, parental externalizing disorders, and environmental adversity. Results were replicated in an independent sample. Socialization and boldness offer a novel conceptualization of underlying risk for substance use disorders that has the potential to improve prediction and theory with implications for basic research, prevention, and intervention. PMID:24280373

Controllable Edge Feature Sharpening for Dental Applications

PubMed Central

2014-01-01

This paper presents a new approach to sharpen blurred edge features in scanned tooth preparation surfaces generated by structured-light scanners. It aims to efficiently enhance the edge features so that the embedded feature lines can be easily identified in dental CAD systems, and to avoid unnatural oversharpening geometry. We first separate the feature regions using graph-cut segmentation, which does not require a user-defined threshold. Then, we filter the face normal vectors to propagate the geometry from the smooth region to the feature region. In order to control the degree of the sharpness, we propose a feature distance measure which is based on normal tensor voting. Finally, the vertex positions are updated according to the modified face normal vectors. We have applied the approach to scanned tooth preparation models. The results show that the blurred edge features are enhanced without unnatural oversharpening geometry. PMID:24741376

Controllable edge feature sharpening for dental applications.

PubMed

Fan, Ran; Jin, Xiaogang

2014-01-01

This paper presents a new approach to sharpen blurred edge features in scanned tooth preparation surfaces generated by structured-light scanners. It aims to efficiently enhance the edge features so that the embedded feature lines can be easily identified in dental CAD systems, and to avoid unnatural oversharpening geometry. We first separate the feature regions using graph-cut segmentation, which does not require a user-defined threshold. Then, we filter the face normal vectors to propagate the geometry from the smooth region to the feature region. In order to control the degree of the sharpness, we propose a feature distance measure which is based on normal tensor voting. Finally, the vertex positions are updated according to the modified face normal vectors. We have applied the approach to scanned tooth preparation models. The results show that the blurred edge features are enhanced without unnatural oversharpening geometry.

Bottlenose dolphins perceive object features through echolocation.

PubMed

Harley, Heidi E; Putman, Erika A; Roitblat, Herbert L

2003-08-07

How organisms (including people) recognize distant objects is a fundamental question. The correspondence between object characteristics (distal stimuli), like visual shape, and sensory characteristics (proximal stimuli), like retinal projection, is ambiguous. The view that sensory systems are 'designed' to 'pick up' ecologically useful information is vague about how such mechanisms might work. In echolocating dolphins, which are studied as models for object recognition sonar systems, the correspondence between echo characteristics and object characteristics is less clear. Many cognitive scientists assume that object characteristics are extracted from proximal stimuli, but evidence for this remains ambiguous. For example, a dolphin may store 'sound templates' in its brain and identify whole objects by listening for a particular sound. Alternatively, a dolphin's brain may contain algorithms, derived through natural endowments or experience or both, which allow it to identify object characteristics based on sounds. The standard method used to address this question in many species is indirect and has led to equivocal results with dolphins. Here we outline an appropriate method and test it to show that dolphins extract object characteristics directly from echoes.

A keyword spotting model using perceptually significant energy features

NASA Astrophysics Data System (ADS)

Umakanthan, Padmalochini

The task of a keyword recognition system is to detect the presence of certain words in a conversation based on the linguistic information present in human speech. Such keyword spotting systems have applications in homeland security, telephone surveillance and human-computer interfacing. General procedure of a keyword spotting system involves feature generation and matching. In this work, new set of features that are based on the psycho-acoustic masking nature of human speech are proposed. After developing these features a time aligned pattern matching process was implemented to locate the words in a set of unknown words. A word boundary detection technique based on frame classification using the nonlinear characteristics of speech is also addressed in this work. Validation of this keyword spotting model was done using widely acclaimed Cepstral features. The experimental results indicate the viability of using these perceptually significant features as an augmented feature set in keyword spotting.