High Bone Mass is associated with bone-forming features of osteoarthritis in non-weight bearing joints independent of body mass index.

PubMed

Gregson, C L; Hardcastle, S A; Murphy, A; Faber, B; Fraser, W D; Williams, M; Davey Smith, G; Tobias, J H

2017-04-01

High Bone Mass (HBM) is associated with (a) radiographic knee osteoarthritis (OA), partly mediated by increased BMI, and (b) pelvic enthesophytes and hip osteophytes, suggestive of a bone-forming phenotype. We aimed to establish whether HBM is associated with radiographic features of OA in non-weight-bearing (hand) joints, and whether such OA demonstrates a bone-forming phenotype. HBM cases (BMD Z-scores≥+3.2) were compared with family controls. A blinded assessor graded all PA hand radiographs for: osteophytes (0-3), joint space narrowing (JSN) (0-3), subchondral sclerosis (0-1), at the index Distal Interphalangeal Joint (DIPJ) and 1st Carpometacarpal Joint (CMCJ), using an established atlas. Analyses used a random effects logistic regression model, adjusting a priori for age and gender. Mediating roles of BMI and bone turnover markers (BTMs) were explored by further adjustment. 314 HBM cases (mean age 61.1years, 74% female) and 183 controls (54.3years, 46% female) were included. Osteophytes (grade≥1) were more common in HBM (DIPJ: 67% vs. 45%, CMCJ: 69% vs. 50%), with adjusted OR [95% CI] 1.82 [1.11, 2.97], p=0.017 and 1.89 [1.19, 3.01], p=0.007 respectively; no differences were seen in JSN. Further adjustment for BMI failed to attenuate ORs for osteophytes in HBM cases vs. controls; DIPJ 1.72 [1.05, 2.83], p=0.032, CMCJ 1.76 [1.00, 3.06], p=0.049. Adjustment for BTMs (concentrations lower amongst HBM cases) did not attenuate ORs. HBM is positively associated with OA in non-weight-bearing joints, independent of BMI. HBM-associated OA is characterised by osteophytes, consistent with a bone-forming phenotype, rather than JSN reflecting cartilage loss. Systemic factors (e.g. genetic architecture) which govern HBM may also increase bone-forming OA risk. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Missense Mutations in LRP5 Associated with High Bone Mass Protect the Mouse Skeleton from Disuse- and Ovariectomy-Induced Osteopenia.

PubMed

Niziolek, Paul J; Bullock, Whitney; Warman, Matthew L; Robling, Alexander G

2015-01-01

The low density lipoprotein receptor-related protein-5 (LRP5), a co-receptor in the Wnt signaling pathway, modulates bone mass in humans and in mice. Lrp5 knock-out mice have severely impaired responsiveness to mechanical stimulation whereas Lrp5 gain-of-function knock-in and transgenic mice have enhanced responsiveness to mechanical stimulation. Those observations highlight the importance of Lrp5 protein in bone cell mechanotransduction. It is unclear if and how high bone mass-causing (HBM) point mutations in Lrp5 alter the bone-wasting effects of mechanical disuse. To address this issue we explored the skeletal effects of mechanical disuse using two models, tail suspension and Botulinum toxin-induced muscle paralysis, in two different Lrp5 HBM knock-in mouse models. A separate experiment employing estrogen withdrawal-induced bone loss by ovariectomy was also conducted as a control. Both disuse stimuli induced significant bone loss in WT mice, but Lrp5 A214V and G171V were partially or fully protected from the bone loss that normally results from disuse. Trabecular bone parameters among HBM mice were significantly affected by disuse in both models, but these data are consistent with DEXA data showing a failure to continue growing in HBM mice, rather than a loss of pre-existing bone. Ovariectomy in Lrp5 HBM mice resulted in similar protection from catabolism as was observed for the disuse experiments. In conclusion, the Lrp5 HBM alleles offer significant protection from the resorptive effects of disuse and from estrogen withdrawal, and consequently, present a potential mechanism to mimic with pharmaceutical intervention to protect against various bone-wasting stimuli.

The Health Belief Model: A Qualitative Study to Understand High-risk Sexual Behavior in Chinese Men Who Have Sex With Men.

PubMed

Li, Xianhong; Lei, Yunxiao; Wang, Honghong; He, Guoping; Williams, Ann Bartley

2016-01-01

The Health Belief Model (HBM) has been widely used to explain rationales for health risk-taking behaviors. Our qualitative study explored the applicability of the HBM to understand high-risk sexual behavior in Chinese men who have sex with men (MSM) and to elaborate each component of the model. HIV knowledge and perception of HIV prevalence contributed to perceived susceptibility. An attitude of treatment optimism versus hard life in reality affected perceived severity. Perceived barriers included discomfort using condoms and condom availability. Perceived benefits included prevention of HIV and other sexually transmitted illnesses. Sociocultural cues for Chinese MSM were elaborated according to each component. The results demonstrated that the HBM could be applied to Chinese MSM. When used with this group, it provided information to help develop a population- and disease-specific HBM scale. Results of our study also suggested behavioral interventions that could be used with Chinese MSM to increase condom use. Copyright © 2016 Association of Nurses in AIDS Care. All rights reserved.

Predicting human papillomavirus vaccine uptake in young adult women: Comparing the Health Belief Model and Theory of Planned Behavior

PubMed Central

Gerend, Mary A.; Shepherd, Janet E.

2012-01-01

Background Although theories of health behavior have guided thousands of studies, relatively few studies have compared these theories against one another. Purpose The purpose of the current study was to compare two classic theories of health behavior—the Health Belief Model (HBM) and the Theory of Planned Behavior (TPB)—in their prediction of human papillomavirus (HPV) vaccination. Methods After watching a gain-framed, loss-framed, or control video, women (N=739) ages 18–26 completed a survey assessing HBM and TPB constructs. HPV vaccine uptake was assessed ten months later. Results Although the message framing intervention had no effect on vaccine uptake, support was observed for both the TPB and HBM. Nevertheless, the TPB consistently outperformed the HBM. Key predictors of uptake included subjective norms, self-efficacy, and vaccine cost. Conclusions Despite the observed advantage of the TPB, findings revealed considerable overlap between the two theories and highlighted the importance of proximal versus distal predictors of health behavior. PMID:22547155

Psychological models for development of motorcycle helmet use among students in Vietnam

NASA Astrophysics Data System (ADS)

Kumphong, J.; Satiennam, T.; Satiennam, W.; Trinh, Tu Anh

2018-04-01

A helmet can reduce head accident severity. The aim of this research study was to study the intention for helmet use of students who ride motorcycles in Vietnam, by Structural Equation Modeling (SEM). Questionnaires developed by several traffic psychology modules, including the Theory of Planned Behaviour (TPB), Traffic Locus of Control (T-LOC), and Health Belief Model (HBM), were distributed to students at Ton Thang University and University of Architecture, Ho Chi Minh City. SEM was used to explain helmet use behaviour. The results indicate that TPB, T-LOC and HBM could explain the variance in helmet use behaviour. However, TPB can explain behaviour (helmet use intention) better than T-LOC and HBM. The outcome of this study is useful for the agencies responsible to improve motorcycle safety.

Effect of alcohol on skin permeation and metabolism of an ester-type prodrug in Yucatan micropig skin.

PubMed

Fujii, Makiko; Ohara, Rieko; Matsumi, Azusa; Ohura, Kayoko; Koizumi, Naoya; Imai, Teruko; Watanabe, Yoshiteru

2017-11-15

We studied the effect that three alcohols, ethanol (EA), propanol (PA), and isopropanol (IPA), have on the skin permeation of p-hydroxy benzoic acid methyl ester (HBM), a model ester-type prodrug. HBM was applied to Yucatan micropig skin in a saturated phosphate buffered solution with or without 10% alcohol, and HBM and related materials in receptor fluid and skin were determined with HPLC. In the absence of alcohol, p-hydroxy benzoic acid (HBA), a metabolite of HBM, permeated the skin the most. The three alcohols enhanced the penetration of HBM at almost the same extent. The addition of 10% EA or PA to the HBM solution led to trans-esterification into the ethyl ester or propyl ester of HBA, and these esters permeated skin as well as HBA and HBM did. In contrast, the addition of 10% IPA promoted very little trans-esterification. Both hydrolysis and trans-esterification in the skin S9 fraction were inhibited by BNPP, an inhibitor of carboxylesterase (CES). Western blot and native PAGE showed the abundant expression of CES in micropig skin. Both hydrolysis and trans-esterification was simultaneously catalyzed by CES during skin permeation. Our data indicate that the alcohol used in dermal drug preparations should be selected not only for its ability to enhance the solubility and permeation of the drug, but also for the effect on metabolism of the drug in the skin. Copyright © 2017 Elsevier B.V. All rights reserved.

Estimating the effect of lay knowledge and prior contact with pulmonary TB patients, on health-belief model in a high-risk pulmonary TB transmission population.

PubMed

Zein, Rizqy Amelia; Suhariadi, Fendy; Hendriani, Wiwin

2017-01-01

The research aimed to investigate the effect of lay knowledge of pulmonary tuberculosis (TB) and prior contact with pulmonary TB patients on a health-belief model (HBM) as well as to identify the social determinants that affect lay knowledge. Survey research design was conducted, where participants were required to fill in a questionnaire, which measured HBM and lay knowledge of pulmonary TB. Research participants were 500 residents of Semampir, Asemrowo, Bubutan, Pabean Cantian, and Simokerto districts, where the risk of pulmonary TB transmission is higher than other districts in Surabaya. Being a female, older in age, and having prior contact with pulmonary TB patients significantly increase the likelihood of having a higher level of lay knowledge. Lay knowledge is a substantial determinant to estimate belief in the effectiveness of health behavior and personal health threat. Prior contact with pulmonary TB patients is able to explain the belief in the effectiveness of a health behavior, yet fails to estimate participants' belief in the personal health threat. Health authorities should prioritize males and young people as their main target groups in a pulmonary TB awareness campaign. The campaign should be able to reconstruct people's misconception about pulmonary TB, thereby bringing around the health-risk perception so that it is not solely focused on improving lay knowledge.

Active muscle response using feedback control of a finite element human arm model.

PubMed

Östh, Jonas; Brolin, Karin; Happee, Riender

2012-01-01

Mathematical human body models (HBMs) are important research tools that are used to study the human response in car crash situations. Development of automotive safety systems requires the implementation of active muscle response in HBM, as novel safety systems also interact with vehicle occupants in the pre-crash phase. In this study, active muscle response was implemented using feedback control of a nonlinear muscle model in the right upper extremity of a finite element (FE) HBM. Hill-type line muscle elements were added, and the active and passive properties were assessed. Volunteer tests with low impact loading resulting in elbow flexion motions were performed. Simulations of posture maintenance in a gravity field and the volunteer tests were successfully conducted. It was concluded that feedback control of a nonlinear musculoskeletal model can be used to obtain posture maintenance and human-like reflexive responses in an FE HBM.

'Sink or swim': an evaluation of the clinical characteristics of individuals with high bone mass.

PubMed

Gregson, C L; Steel, S A; O'Rourke, K P; Allan, K; Ayuk, J; Bhalla, A; Clunie, G; Crabtree, N; Fogelman, I; Goodby, A; Langman, C M; Linton, S; Marriott, E; McCloskey, E; Moss, K E; Palferman, T; Panthakalam, S; Poole, K E S; Stone, M D; Turton, J; Wallis, D; Warburton, S; Wass, J; Duncan, E L; Brown, M A; Davey-Smith, G; Tobias, J H

2012-02-01

High bone mineral density on routine dual energy X-ray absorptiometry (DXA) may indicate an underlying skeletal dysplasia. Two hundred fifty-eight individuals with unexplained high bone mass (HBM), 236 relatives (41% with HBM) and 58 spouses were studied. Cases could not float, had mandible enlargement, extra bone, broad frames, larger shoe sizes and increased body mass index (BMI). HBM cases may harbour an underlying genetic disorder. High bone mineral density is a sporadic incidental finding on routine DXA scanning of apparently asymptomatic individuals. Such individuals may have an underlying skeletal dysplasia, as seen in LRP5 mutations. We aimed to characterize unexplained HBM and determine the potential for an underlying skeletal dysplasia. Two hundred fifty-eight individuals with unexplained HBM (defined as L1 Z-score ≥ +3.2 plus total hip Z-score ≥ +1.2, or total hip Z-score ≥ +3.2) were recruited from 15 UK centres, by screening 335,115 DXA scans. Unexplained HBM affected 0.181% of DXA scans. Next 236 relatives were recruited of whom 94 (41%) had HBM (defined as L1 Z-score + total hip Z-score ≥ +3.2). Fifty-eight spouses were also recruited together with the unaffected relatives as controls. Phenotypes of cases and controls, obtained from clinical assessment, were compared using random-effects linear and logistic regression models, clustered by family, adjusted for confounders, including age and sex. Individuals with unexplained HBM had an excess of sinking when swimming (7.11 [3.65, 13.84], p < 0.001; adjusted odds ratio with 95% confidence interval shown), mandible enlargement (4.16 [2.34, 7.39], p < 0.001), extra bone at tendon/ligament insertions (2.07 [1.13, 3.78], p = 0.018) and broad frame (3.55 [2.12, 5.95], p < 0.001). HBM cases also had a larger shoe size (mean difference 0.4 [0.1, 0.7] UK sizes, p = 0.009) and increased BMI (mean difference 2.2 [1.3, 3.1] kg/m(2), p < 0.001). Individuals with unexplained HBM have an excess of clinical characteristics associated with skeletal dysplasia and their relatives are commonly affected, suggesting many may harbour an underlying genetic disorder affecting bone mass.

Effect of a Health Belief Model-based nursing intervention on Chinese patients with moderate to severe chronic obstructive pulmonary disease: a randomised controlled trial.

PubMed

Wang, Ying; Zang, Xiao-Ying; Bai, Jinbing; Liu, Su-Yan; Zhao, Yue; Zhang, Qing

2014-05-01

To test the effect of a Health Belief Model-based nursing intervention on healthcare outcomes in Chinese patients with moderate to severe COPD. The Health Belief Model (HBM) has been internationally validated in a variety of chronic conditions. However, nursing intervention based on the HBM is less explored in Chinese patients with COPD. A randomised controlled trial. Enrolled patients were randomly assigned to the intervention and control groups. Patients in the intervention group received a 20- to 30-minute HBM-based nursing intervention every 2 days during the hospitalisation period after disease conditions were stable, with additional follow-ups after discharge. Patients in the control group received routine nursing care. Patients had significantly increased scores of health belief and self-efficacy after receiving the HBM-based nursing intervention. After receiving the 3-month follow-up, patients in the intervention group had significantly higher mean total scores in the Health Belief Scale and the COPD Self-Efficacy Scale, as well as in all the subscales, than those in the control group except the perceived disease seriousness. Results showed that the value of FEV1 /FVC ratio had a significant difference between study groups before and after the intervention. Results also indicated that mean scores of the Dyspnea Scale, 6-minute walking distance and ADL were significantly different between the groups and between the study time-points. Among patients with moderate to severe COPD, nursing intervention based on the HBM can enhance their health belief and self-efficacy towards the disease management, decrease dyspnoea and improve exercise tolerance and ADL. Nurses can use the HBM-based intervention to enhance patients' health belief and self-efficacy towards the management of COPD, and subsequently benefit healthcare outcomes. © 2013 John Wiley & Sons Ltd.

Breast cancer literacy and health beliefs related to breast cancer screening among American Indian women.

PubMed

Roh, Soonhee; Burnette, Catherine E; Lee, Yeon-Shim; Jun, Jung Sim; Lee, Hee Yun; Lee, Kyoung Hag

2018-08-01

The purpose of this article is to examine the health beliefs and literacy about breast cancer and their relationship with breast cancer screening among American Indian (AI) women. Using the Health Belief Model (HBM) and hierarchical logistic regression with data from a sample of 286 AI female adults residing in the Northern Plains, we found that greater awareness of breast cancer screening was linked to breast cancer screening practices. However, perceived barriers, one of the HBM constructs, prevented such screening practices. This study suggested that culturally relevant HBM factors should be targeted when developing culturally sensitive breast cancer prevention efforts.

Health Belief Factors and Dispositional Optimism as Predictors of STD and HIV Preventive Behavior

ERIC Educational Resources Information Center

Zak-Place, Jennifer; Stern, Marilyn

2004-01-01

Identifying factors predictive of youth's engaging in preventive behaviors related to sexually transmitted diseases (STDs) and HIV remains a prominent public health concern. The utility of the Health Belief Model (HBM) continues to be suggested in identifying preventive behaviors. This study sought to examine the full HBM, including self-efficacy,…

Human biomonitoring in Israel: Recent results and lessons learned.

PubMed

Berman, Tamar; Goldsmith, Rebecca; Levine, Hagai; Grotto, Itamar

2017-03-01

The use of human biomonitoring (HBM) as a tool for environmental health policy and research is developing rapidly in Israel. Despite challenges in securing political and financial support for HBM, the Ministry of Health has initiated national HBM studies and has utilized HBM data in environmental health policy decision making. Currently, the Ministry of Health is collecting urine samples from children and adults in the framework of the National Health and Nutrition Study (MABAT), with the goal of ongoing surveillance of population exposure to pesticides and environmental tobacco smoke, and of combining HBM data with data on diet and health behavior. In academic research studies in Israel, biomarkers are used increasingly in environmental epidemiology, including in three active birth cohort studies on adverse health effects of phthalates, brominated flame retardants, and organophosphate pesticides. Future Ministry of Health goals include establishing HBM analytical capabilities, developing a long term national HBM plan for Israel and participating in the proposed HBM4EU project in order to improve data harmonization. One of the lessons learned in Israel is that even in the absence of a formal HBM program, it is possible to collect meaningful HBM data and use it in an ad hoc fashion to support environmental health policy. Copyright © 2016 Elsevier GmbH. All rights reserved.

Application of the Health Belief Model to U.S. Magazine Text and Image Coverage of Skin Cancer and Recreational Tanning (2000-2012).

PubMed

McWhirter, Jennifer E; Hoffman-Goetz, Laurie

2016-01-01

The health belief model (HBM) has been widely used to inform health education, social marketing, and health communication campaigns. Although the HBM can explain and predict an individual's willingness to engage in positive health behaviors, its application to, and penetration of the underlying constructs into, mass media content has not been well characterized. We examined 574 articles and 905 images about skin cancer and tanning risks, behaviors, and screening from 20 U.S. women's and men's magazines (2000-2012) for the presence of HBM constructs: perceived susceptibility, perceived severity, perceived benefits, perceived barriers, self-efficacy, and cues to action. Susceptibility (48.1%) and severity (60.3%) information was common in text. Perceived benefits (36.4%) and barriers (41.5%) to prevention of skin cancer were fairly equally mentioned in articles. Self-efficacy (48.4%) focused on sunscreen use. There was little emphasis on HBM constructs related to early detection. Few explicit cues to action about skin cancer appeared in text (12.0%) or images (0.1%). HBM constructs were present to a significantly greater extent in text versus images (e.g., severity, 60.3% vs. 11.3%, respectively, χ(2) = 399.51, p < .0001; benefits prevention, 36.4% vs. 8.0%, respectively, χ(2) = 184.80, p < .0001), suggesting that readers are not visually messaged in ways that would effectively promote skin cancer prevention and early detection behaviors.

Parameter study for child injury mitigation in near-side impacts through FE simulations.

PubMed

Andersson, Marianne; Pipkorn, Bengt; Lövsund, Per

2012-01-01

The objective of this study is to investigate the effects of crash-related car parameters on head and chest injury measures for 3- and 12-year-old children in near-side impacts. The evaluation was made using a model of a complete passenger car that was impacted laterally by a barrier. The car model was validated in 2 crash conditions: the Insurance Institute for Highway Safety (IIHS) and the US New Car Assessment Program (NCAP) side impact tests. The Small Side Impact Dummy (SID-IIs) and the human body model 3 (HBM3) (Total HUman Model for Safety [THUMS] 3-year-old) finite element models were used for the parametric investigation (HBM3 on a booster). The car parameters were as follows: vehicle mass, side impact structure stiffness, a head air bag, a thorax-pelvis air bag, and a seat belt with pretensioner. The studied dependent variables were as follows: resultant head linear acceleration, resultant head rotational acceleration, chest viscous criterion, rib deflection, and relative velocity at head impact. The chest measurements were only considered for the SID-IIs. The head air bag had the greatest effect on the head measurements for both of the occupant models. On average, it reduced the peak head linear acceleration by 54 g for the HBM3 and 78 g for the SID-IIs. The seat belt had the second greatest effect on the head measurements; the peak head linear accelerations were reduced on average by 39 g (HBM3) and 44 g (SID-IIs). The high stiffness side structure increased the SID-IIs' head acceleration, whereas it had marginal effect on the HBM3. The vehicle mass had a marginal effect on SID-IIs' head accelerations, whereas the lower vehicle mass caused 18 g higher head acceleration for HBM3 and the greatest rotational acceleration. The thorax-pelvis air bag, vehicle mass, and seat belt pretensioner affected the chest measurements the most. The presence of a thorax-pelvis air bag, high vehicle mass, and a seat belt pretensioner all reduced the chest viscous criterion (VC) and peak rib deflection in the SID-IIs. The head and thorax-pelvis air bags have the potential to reduce injury measurements for both the SID-IIs and the HBM3, provided that the air bag properties are designed to consider these occupant sizes also. The seat belt pretensioner is also effective, provided that the lateral translation of the torso is managed by other features. The importance of lateral movement management is greater the smaller the occupant is. Light vehicles require interior restraint systems of higher performance than heavy vehicles do to achieve the same level of injury measures for a given side structure. Copyright © 2012 Taylor & Francis Group, LLC

Application of the Health Belief Model in a study on parents' intentions to utilize prenatal diagnosis of cleft lip and/or palate.

PubMed

Sagi, M; Shiloh, S; Cohen, T

1992-10-01

Parents of children with cleft lip and/or palate (42 women and 35 men) participated in a study on intentions to use prenatal diagnosis of cleft by ultrasound in subsequent pregnancies. Based on the Health Belief Model (HBM) [Rosenstock, 1974], parents' cognitions on 4 factors were measured by questionnaires: "susceptibility" and "severity perceptions," "benefits" and "barriers" evaluations. Most parents perceived the defect as severe. Over-estimation of recurrence risks was predominant even among parents who had received genetic counseling. Results showed that most parents intend to utilize prenatal diagnosis but do not intend to abort an affected fetus. Subjects' reported reasons represented 3 thematic categories: cognitive (the need to know), emotional, and behavioral. Parents' intentions to diagnose and to terminate were related to the factors predicted by the HBM model. Regression analyses indicated that 38% of the variance in intentions to diagnose and 56% of the variance in intentions to terminate could be explained by the studied variables. The best predictor of both intentions was the perceived benefits of the diagnosis. Implications of these findings for genetic counseling are discussed.

Finite element comparison of human and Hybrid III responses in a frontal impact.

PubMed

Danelson, Kerry A; Golman, Adam J; Kemper, Andrew R; Gayzik, F Scott; Clay Gabler, H; Duma, Stefan M; Stitzel, Joel D

2015-12-01

The improvement of finite element (FE) Human Body Models (HBMs) has made them valuable tools for investigating restraint interactions compared to anthropomorphic test devices (ATDs). The objective of this study was to evaluate the effect of various combinations of safety restraint systems on the sensitivity of thoracic injury criteria using matched ATD and Human Body Model (HBM) simulations at two crash severities. A total of seven (7) variables were investigated: 3-point belt with two (2) load limits, frontal airbag, knee bolster airbag, a buckle pretensioner, and two (2) delta-v's - 40kph and 50kph. Twenty four (24) simulations were conducted for the Hybrid III ATD FE model and repeated with a validated HBM for 48 total simulations. Metrics tested in these conditions included sternum deflection, chest acceleration, chest excursion, Viscous Criteria (V*C) criteria, pelvis acceleration, pelvis excursion, and femur forces. Additionally, chest band deflection and rib strain distribution were measured in the HBM for additional restraint condition discrimination. The addition of a frontal airbag had the largest effect on the occupant chest metrics with an increase in chest compression and acceleration but a decrease in excursion. While the THUMS and Hybrid III occupants demonstrated the same trend in the chest compression measurements, there were conflicting results in the V*C, acceleration, and displacement metrics. Similarly, the knee bolster airbag had the largest effect on the pelvis with a decrease in acceleration and excursion. With a knee bolster airbag the simulated occupants gave conflicting results, the THUMS had a decrease in femur force and the ATD had an increase. Preferential use of dummies or HBM's is not debated; however, this study highlights the ability of HBM metrics to capture additional chest response metrics. Copyright © 2015 Elsevier Ltd. All rights reserved.

The Health Belief Model as an Explanatory Framework in Communication Research: Exploring Parallel, Serial, and Moderated Mediation

PubMed Central

Jones, Christina L.; Jensen, Jakob D.; Scherr, Courtney L.; Brown, Natasha R.; Christy, Katheryn; Weaver, Jeremy

2015-01-01

The Health Belief Model (HBM) posits that messages will achieve optimal behavior change if they successfully target perceived barriers, benefits, self-efficacy, and threat. While the model seems to be an ideal explanatory framework for communication research, theoretical limitations have limited its use in the field. Notably, variable ordering is currently undefined in the HBM. Thus, it is unclear whether constructs mediate relationships comparably (parallel mediation), in sequence (serial mediation), or in tandem with a moderator (moderated mediation). To investigate variable ordering, adults (N = 1,377) completed a survey in the aftermath of an 8-month flu vaccine campaign grounded in the HBM. Exposure to the campaign was positively related to vaccination behavior. Statistical evaluation supported a model where the indirect effect of exposure on behavior through perceived barriers and threat was moderated by self-efficacy (moderated mediation). Perceived barriers and benefits also formed a serial mediation chain. The results indicate that variable ordering in the Health Belief Model may be complex, may help to explain conflicting results of the past, and may be a good focus for future research. PMID:25010519

Performances of the PIPER scalable child human body model in accident reconstruction

PubMed Central

Giordano, Chiara; Kleiven, Svein

2017-01-01

Human body models (HBMs) have the potential to provide significant insights into the pediatric response to impact. This study describes a scalable/posable approach to perform child accident reconstructions using the Position and Personalize Advanced Human Body Models for Injury Prediction (PIPER) scalable child HBM of different ages and in different positions obtained by the PIPER tool. Overall, the PIPER scalable child HBM managed reasonably well to predict the injury severity and location of the children involved in real-life crash scenarios documented in the medical records. The developed methodology and workflow is essential for future work to determine child injury tolerances based on the full Child Advanced Safety Project for European Roads (CASPER) accident reconstruction database. With the workflow presented in this study, the open-source PIPER scalable HBM combined with the PIPER tool is also foreseen to have implications for improved safety designs for a better protection of children in traffic accidents. PMID:29135997

Predictors of condom use behaviors based on the Health Belief Model (HBM) among female sex workers: a cross-sectional study in Hubei Province, China.

PubMed

Zhao, Jinzhu; Song, Fujian; Ren, Shuhua; Wang, Yan; Wang, Liang; Liu, Wei; Wan, Ying; Xu, Hong; Zhou, Tao; Hu, Tian; Bazzano, Lydia; Sun, Yi

2012-01-01

HIV infection related to commercial sexual contact is a serious public health issue in China. The objectives of the present study are to explore the predictors of condom use among female sex workers (FSWs) in China and examine the relationship between Health Belief Model (HBM) constructs. A cross-sectional study was conducted in two cities (Wuhan and Suizhou) in Hubei Province, China, between July 2009 and June 2010. A total of 427 FSWs were recruited through mediators from the 'low-tier' entertainment establishments. Data were obtained by self-administered questionnaires. Structural equation models were constructed to examine the association. We collected 363 valid questionnaires. Within the context of HBM, perceived severity of HIV mediated through perceived benefits of condom use had a weak effect on condom use (r=0.07). Perceived benefits and perceived barriers were proximate determinants of condom use (r=0.23 and r=-0.62, respectively). Self-efficacy had a direct effect on perceived severity, perceived benefits, and perceived barriers, which was indirectly associated with condom use behaviors (r=0.36). The HBM provides a useful framework for investigating predictors of condom use behaviors among FSWs. Future HIV prevention interventions should focus on increasing perceived benefits of condom use, reducing barriers to condoms use, and improving self-efficacy among FSWs.

Foundational workplace safety and health competencies for the emerging workforce.

PubMed

Okun, Andrea H; Guerin, Rebecca J; Schulte, Paul A

2016-12-01

Young workers (aged 15-24) suffer disproportionately from workplace injuries, with a nonfatal injury rate estimated to be two times higher than among workers age 25 or over. These workers make up approximately 9% of the U.S. workforce and studies have shown that nearly 80% of high school students work at some point during high school. Although young worker injuries are a pressing public health problem, the critical knowledge and skills needed to prepare youth for safe and healthy work are missing from most frameworks used to prepare the emerging U.S. workforce. A framework of foundational workplace safety and health knowledge and skills (the NIOSH 8 Core Competencies) was developed based on the Health Belief Model (HBM). The proposed NIOSH Core Competencies utilize the HBM to provide a framework for foundational workplace safety and health knowledge and skills. An examination of how these competencies and the HBM apply to actions that workers take to protect themselves is provided. The social and physical environments that influence these actions are also discussed. The NIOSH 8 Core Competencies, grounded in one of the most widely used health behavior theories, fill a critical gap in preparing the emerging U.S. workforce to be cognizant of workplace risks. Integration of the NIOSH 8 Core Competencies into school curricula is one way to ensure that every young person has the foundational workplace safety and health knowledge and skills to participate in, and benefit from, safe and healthy work. Published by Elsevier Ltd.

[Health promotion. Instrument development for the application of the theory of planned behavior].

PubMed

Lee, Y O

1993-01-01

The purpose of this article is to describe operationalization of the Theory of Planned Behavior (TPB). The quest to understand determinants of health behaviors has intensified as evidence accumulates concerning the impact of personal behavior on health. The majority of theory-based research has used the Health Belief Model(HBM). The HBM components have had limited success in explaining health-related behaviors. There are several advantages of the TPB over the HBM. TPB is an expansion of the Theory of Reasoned Action(TRA) with the addition of the construct, perceived behavioral control. The revised model has been shown to yield greater explanatory power than the original TRA for goal-directed behaviors. The process of TPB instrument development was described, using example form the study of smoking cessation behavior in military smokers. It was followed by a discussion of reliability and validity issues in operationalizing the TPB. The TPB is a useful model for understanding and predicting health-related behaviors when carefully operationalized. The model holds promise in the development of prescriptive nursing approaches.

The health belief model and number of peers with internet addiction as inter-related factors of Internet addiction among secondary school students in Hong Kong.

PubMed

Wang, Yanhong; Wu, Anise M S; Lau, Joseph T F

2016-03-16

Students are vulnerable to Internet addiction (IA). Influences of cognitions based on the Health Belief Model (HBM) and perceived number of peers with IA (PNPIA) affecting students' IA, and mediating effects involved, have not been investigated. This cross-sectional study surveyed 9518 Hong Kong Chinese secondary school students in the school setting. In this self-reported study, the majority (82.6%) reported that they had peers with IA. Based on the Chinese Internet Addiction Scale (cut-off =63/64), the prevalence of IA was 16.0% (males: 17.6%; females: 14.0%). Among the non-IA cases, 7.6% (males: 8.7%; females: 6.3%) perceived a chance of developing IA in the next 12 months. Concurring with the HBM, adjusted logistic analysis showed that the Perceived Social Benefits of Internet Use Scale (males: Adjusted odds ratio (ORa) = 1.19; females: ORa = 1.23), Perceived Barriers for Reducing Internet Use Scale (males: ORa = 1.26; females: ORa = 1.36), and Perceived Self-efficacy for Reducing Internet Use Scale (males: ORa = 0.66; females: ORa = 0.56) were significantly associated with IA. Similarly, PNPIA was significantly associated with IA ('quite a number': males: ORa = 2.85; females: ORa = 4.35; 'a large number': males: ORa = 3.90; females: ORa = 9.09). Controlling for these three constructs, PNPIA remained significant but the strength of association diminished ('quite a number': males: multivariate odds ratio (ORm) = 2.07; females: ORm = 2.44; 'a large number': males: ORm = 2.39; females: ORm = 3.56). Hence, the association between PNPIA and IA was partially mediated (explained) by the three HBM constructs. Interventions preventing IA should change these constructs. In sum, prevalence of IA was relatively high and was associated with some HBM constructs and PNPIA, and PNPIA also partially mediated associations between HBM constructs and IA. Huge challenges are expected, as social relationships and an imbalance of cost-benefit for reducing Internet use are involved. Perceived susceptibility and perceived severity of IA were relatively low and the direction of their associations with IA did not concur with the HBM. Group cognitive-behavioral interventions involving peers with IA or peers recovered from IA are potentially useful to modify the HBM constructs and should be tested for efficacy.

Exposure to Theory-Driven Text Messages is Associated with HIV Risk Reduction Among Methamphetamine-Using Men Who have Sex with Men.

PubMed

Reback, Cathy J; Fletcher, Jesse B; Shoptaw, Steven; Mansergh, Gordon

2015-06-01

Fifty-two non-treatment-seeking methamphetamine-using men who have sex with men were enrolled in Project Tech Support, an open-label pilot study to evaluate whether exposure to theory-based [social support theory (SST), social cognitive theory (SCT), and health belief model (HBM)] text messages could promote reductions in HIV sexual risk behaviors and/or methamphetamine use. Multivariable analyses revealed that increased relative exposure to HBM or SCT (vs. SST) text messages was associated with significant reductions in the number of HIV serodiscordant unprotected (i.e., without a condom) anal sex partners, engagement in sex for money and/or drugs, and frequency of recent methamphetamine use; additionally, increased relative exposure to HBM (vs. SCT or SST) messages was uniquely associated with reductions in the overall number of non-primary anal sex partners (all p ≤ 0.05, two-tailed). Pilot data demonstrated that text messages based on the principles of HBM and SCT reduced sentinel HIV risk and drug use behaviors in active methamphetamine users.

Health Blief Model-based intervention to improve nutritional behavior among elderly women.

PubMed

Iranagh, Jamileh Amirzadeh; Rahman, Hejar Abdul; Motalebi, Seyedeh Ameneh

2016-06-01

Nutrition is a determinant factor of health in elderly people. Independent living in elderly people can be maintained or enhanced by improvement of nutritional behavior. Hence, the present study was conducted to determine the impact of Health Belief Model (HBM)-based intervention on the nutritional behavior of elderly women. Cluster-random sampling was used to assess the sample of this clinical trial study. The participants of this study attended a 12-week nutrition education program consisting of two (2) sessions per week. There was also a follow-up for another three (3) months. Smart PLS 3.5 and SPSS 19 were used for structural equation modeling, determination of model fitness, and hypotheses testing. The findings indicate that intervention had a significant effect on knowledge improvement as well as the behavior of elderly women. The model explained 5 to 70% of the variance in nutritional behavior. In addition, nutritional behavior was positively affected by the HBM constructs comprised of perceived susceptibility, self-efficacy, perceived benefits, and barriers after the intervention program. The results of this study show that HBM-based educational intervention has a significant effect in improving nutritional knowledge and behavior among elderly women.

Policy recommendations and cost implications for a more sustainable framework for European human biomonitoring surveys.

PubMed

Joas, Anke; Knudsen, Lisbeth E; Kolossa-Gehring, Marike; Sepai, Ovnair; Casteleyn, Ludwine; Schoeters, Greet; Angerer, Jürgen; Castaño, Argelia; Aerts, Dominique; Biot, Pierre; Horvat, Milena; Bloemen, Louis; Reis, M Fátima; Lupsa, Ioana-Rodica; Katsonouri, Andromachi; Cerna, Milena; Berglund, Marika; Crettaz, Pierre; Rudnai, Peter; Halzlova, Katarina; Mulcahy, Maurice; Gutleb, Arno C; Fischer, Marc E; Becher, Georg; Fréry, Nadine; Jensen, Genon; Van Vliet, Lisette; Koch, Holger M; Den Hond, Elly; Fiddicke, Ulrike; Esteban, Marta; Exley, Karen; Schwedler, Gerda; Seiwert, Margarete; Ligocka, Danuta; Hohenblum, Philipp; Kyrtopoulos, Soterios; Botsivali, Maria; DeFelip, Elena; Guillou, Claude; Reniero, Fabiano; Grazuleviciene, Regina; Veidebaum, Toomas; Mørck, Thit A; Nielsen, Jeanette K S; Jensen, Janne F; Rivas, Teresa C; Sanchez, Jinny; Koppen, Gudrun; Smolders, Roel; Kozepesy, Szilvia; Hadjipanayis, Adamos; Krskova, Andrea; Mannion, Rory; Jakubowski, Marek; Fucic, J Aleksandra; Pereira-Miguel, Jose; Gurzau, Anca E; Jajcaj, Michal; Mazej, Darja; Tratnik, Janja Snoj; Lehmann, Andrea; Larsson, Kristin; Dumez, Birgit; Joas, Reinhard

2015-08-01

The potential of Human Biomonitoring (HBM) in exposure characterisation and risk assessment is well established in the scientific HBM community and regulatory arena by many publications. The European Environment and Health Strategy as well as the Environment and Health Action Plan 2004-2010 of the European Commission recognised the value of HBM and the relevance and importance of coordination of HBM programmes in Europe. Based on existing and planned HBM projects and programmes of work and capabilities in Europe the Seventh Framework Programme (FP 7) funded COPHES (COnsortium to Perform Human Biomonitoring on a European Scale) to advance and improve comparability of HBM data across Europe. The pilot study protocol was tested in 17 European countries in the DEMOCOPHES feasibility study (DEMOnstration of a study to COordinate and Perform Human biomonitoring on a European Scale) cofunded (50%) under the LIFE+ programme of the European Commission. The potential of HBM in supporting and evaluating policy making (including e.g. REACH) and in awareness raising on environmental health, should significantly advance the process towards a fully operational, continuous, sustainable and scientifically based EU HBM programme. From a number of stakeholder activities during the past 10 years and the national engagement, a framework for sustainable HBM structure in Europe is recommended involving national institutions within environment, health and food as well as European institutions such as ECHA, EEA, and EFSA. An economic frame with shared cost implications for national and European institutions is suggested benefitting from the capacity building set up by COPHES/DEMOCOPHES. Copyright © 2014 Elsevier Inc. All rights reserved.

Perceived risks of HIV/AIDS and first sexual intercourse among youth in Cape Town, South Africa.

PubMed

Tenkorang, Eric Y; Rajulton, Fernando; Maticka-Tyndale, Eleanor

2009-04-01

The 'Health Belief Model' (HBM) identifies perception of HIV/AIDS risks, recognition of its seriousness, and knowledge about prevention as predictors of safer sexual activity. Using data from the Cape Area Panel Survey (CAPS) and hazard models, this study examines the impact of risk perception, considered the first step in HIV prevention, set within the context of the HBM and socio-economic, familial and school factors, on the timing of first sexual intercourse among youth aged 14-22 in Cape Town, South Africa. Of the HBM components, female youth who perceive their risk as 'very small' and males with higher knowledge, experience their sexual debut later than comparison groups, net of other influences. For both males and females socio-economic and familial factors also influence timing of sexual debut, confirming the need to consider the social embeddedness of this sexual behavior as well as the rational components of decision making when designing prevention programs.

Health belief model based evaluation of school health education programme for injury prevention among high school students in the community context.

PubMed

Cao, Zhi-Juan; Chen, Yue; Wang, Shu-Mei

2014-01-10

Although multifaceted community-based programmes have been widely developed, there remains a paucity of evaluation of the effectiveness of multifaceted injury prevention programmes implemented in different settings in the community context. This study was to provide information for the evaluation of community-based health education programmes of injury prevention among high school students. The pre-intervention survey was conducted in November 2009. Health belief model (HBM) based health education for injury prevention started in January 2010 and stopped in the end of 2011 among high school students in the community context in Shanghai, China. A post-intervention survey was conducted six weeks after the completion of intervention. Injury-related health belief indicators were captured by a short questionnaire before and after the intervention. Health belief scores were calculated and compared using the simple sum score (SSS) method and the confirmatory factor analysis weighted score (CFAWS) method, respectively. The average reliability coefficient for the questionnaire was 0.89. The factor structure of HBM was given and the data fit HBM in the confirmatory factor analysis (CFA) very well. The result of CFA showed that Perceived Benefits of Taking Action (BEN) and Perceived Seriousness (SER) had the greatest impact on the health belief, Perceived Susceptibility (SUS) and Cues to Action (CTA) were the second and third most important components of HBM respectively. Barriers to Taking Action (BAR) had no notable impact on HBM. The standardized path coefficient was only 0.35, with only a small impact on CTA. The health belief score was significantly higher after intervention (p < 0.001), which was similar in the CFAWS method and in the SSS method. However, the 95% confidential interval in the CFAWS method was narrower than that in the SSS method. The results of CFA provide further empirical support for the HBM in injury intervention. The CFAWS method can be used to calculate the health belief scores and evaluate the injury related intervention. The community-based school health education might improve injury-related health belief among high school students; however, this preliminary observation needs to be confirmed in further research.

Effect of educational intervention based on the Health Belief Model on promoting self-care behaviors of type-2 diabetes patients.

PubMed

Shabibi, Parisa; Zavareh, Mohammad Sadegh Abedzadeh; Sayehmiri, Kourosh; Qorbani, Mostafa; Safari, Omid; Rastegarimehr, Babak; Mansourian, Morteza

2017-12-01

Diabetes is a chronic disease in which patients require lifelong self-care behaviors. The present study offset to determine the effect of educational intervention based on the Health Belief Model (HBM) on promoting self-care behaviors of type 2 diabetes patients in Ilam, Iran 2014. A quasi-experimental research was conducted based on HBM in which 70 type 2 diabetic patients from Ilam, western Iran in 2014 were selected by multi-stage random sampling. A self-designed questionnaire was used, and pre-test was administered, subsequently, the educational intervention sessions were provided in the form of presentation, questions and answers, group discussion, and practical demonstrations in four sessions over a period of one month. Two months after the intervention, the post-tests were administered. The data were analyzed via SPSS 20 applying independent samples t-test, paired samples t-test, and univariate and multivariate regressions at a significance level of less than 0.05. The mean scores of susceptibility, severity, perceived benefits and barriers, self-efficacy, and self-care behaviors were at average and lower levels before the intervention; nonetheless, after the educational intervention, the mean score of each HBM construct and the self-care behaviors significantly increased (p<0.001). Health education through HBM promotes the self-care behaviors of patients with type 2 diabetes.

Factors influencing healthy eating habits among college students: an application of the health belief model.

PubMed

Deshpande, Sameer; Basil, Michael D; Basil, Debra Z

2009-01-01

Poor eating habits are an important public health issue that has large health and economic implications. Many food preferences are established early, but because people make more and more independent eating decisions as they move through adolescence, the transition to independent living during the university days is an important event. To study the phenomenon of food selection, the heath belief model was applied to predict the likelihood of healthy eating among university students. Structural equation modeling was used to investigate the validity of the health belief model (HBM) among 194 students, followed by gender-based analyses. The data strongly supported the HBM. Social change campaign implications are discussed.

Comparacion de modelos de Educacion Sexual en el conocimiento y cambio de actitudes en practicas sexuales por alumnos de nivel superior en la region de Caguas, Puerto Rico

NASA Astrophysics Data System (ADS)

Juan, Vallejo Ramos L.

In opposition to the Sexual Education Traditional Model (SETM) that is used in the state schools of Puerto Rico, the Health Beliefs Model (HBM) appears. It facilitates a curricular design that improves the ability of the students to respond to the group pressure by means of attitudes that stimulate sexual conducts of smaller risk of propagation of the Sexually Transmitted Diseases (STD). In addition, it provides activities to increase the self-esteem, the communication and the decision making. This investigation had the intention to compare the SETM and the HBM in the increase of knowledge and change of attitudes of high risk of propagation of the STD using a validated questionnaire (Agency of the United States for the International-USAID Development), named "Endesa 2007" and, adapted to Puerto Rico by the Dra.Marta Collazo to a sample of students between the 17 and 19 years of 2 state schools of San Lorenzo, as a pretest, and, selected by convenience. Then, a 10 hours training was administered to half of the students using the SETM to STD and condom use lessons. The other half of the students received additional lessons using the HBM. Finally, both groups took the questionnaire again as a posttest. The sample of students, in average, did not reach the knowledge and basic levels of attitudes towards the STD in the pretest. This reflected 2 possible implications on the SETM. In first place, that the way in which the STD is implemented as part of the Sexual Education curriculum is inefficient. Secondly, the possibility that the acquired information or attitudes does not have permanence. Culminated the questionnaire, the HBM increase the knowledge of the STD in 0.41 points (average) over the SETM. There was not a significant difference between both models, in attitudes, implying that both models are equally effective. The findings suggests that the HBM is more effective increasing the knowledge on the STD, but equally effective than the SETM in attitude change for the Puerto Rican youth.

Foundational workplace safety and health competencies for the emerging workforce☆

PubMed Central

Okun, Andrea H.; Guerin, Rebecca J.; Schulte, Paul A.

2016-01-01

Introduction Young workers (aged 15–24) suffer disproportionately from workplace injuries, with a nonfatal injury rate estimated to be two times higher than among workers age 25 or over. These workers make up approximately 9% of the U.S. workforce and studies have shown that nearly 80% of high school students work at some point during high school. Although young worker injuries are a pressing public health problem, the critical knowledge and skills needed to prepare youth for safe and healthy work are missing from most frameworks used to prepare the emerging U.S. workforce. Methods A framework of foundational workplace safety and health knowledge and skills (the NIOSH 8 Core Competencies)was developed based on the Health Belief Model (HBM). Results The proposed NIOSH Core Competencies utilize the HBM to provide a framework for foundational workplace safety and health knowledge and skills. An examination of how these competencies and the HBM apply to actions that workers take to protect themselves is provided. The social and physical environments that influence these actions are also discussed. Conclusions The NIOSH 8 Core Competencies, grounded in one of the most widely used health behavior theories, fill a critical gap in preparing the emerging U.S. workforce to be cognizant of workplace risks. Practical applications Integration of the NIOSH 8 Core Competencies into school curricula is one way to ensure that every young person has the foundational workplace safety and health knowledge and skills to participate in, and benefit from, safe and healthy work. National Safety Council and Elsevier Ltd. All rights reserved. PMID:27846998

A method to model anticipatory postural control in driver braking events.

PubMed

Östh, Jonas; Eliasson, Erik; Happee, Riender; Brolin, Karin

2014-09-01

Human body models (HBMs) for vehicle occupant simulations have recently been extended with active muscles and postural control strategies. Feedback control has been used to model occupant responses to autonomous braking interventions. However, driver postural responses during driver initiated braking differ greatly from autonomous braking. In the present study, an anticipatory postural response was hypothesized, modelled in a whole-body HBM with feedback controlled muscles, and validated using existing volunteer data. The anticipatory response was modelled as a time dependent change in the reference value for the feedback controllers, which generates correcting moments to counteract the braking deceleration. The results showed that, in 11 m/s(2) driver braking simulations, including the anticipatory postural response reduced the peak forward displacement of the head by 100mm, of the shoulder by 30 mm, while the peak head flexion rotation was reduced by 18°. The HBM kinematic response was within a one standard deviation corridor of corresponding test data from volunteers performing maximum braking. It was concluded that the hypothesized anticipatory responses can be modelled by changing the reference positions of the individual joint feedback controllers that regulate muscle activation levels. The addition of anticipatory postural control muscle activations appears to explain the difference in occupant kinematics between driver and autonomous braking. This method of modelling postural reactions can be applied to the simulation of other driver voluntary actions, such as emergency avoidance by steering. Copyright © 2014. Published by Elsevier B.V.

Rapid Osteogenic Enhancement of Stem Cells in Human Bone Marrow Using a Glycogen-Synthease-Kinase-3-Beta Inhibitor Improves Osteogenic Efficacy In Vitro and In Vivo.

PubMed

Clough, Bret H; Zeitouni, Suzanne; Krause, Ulf; Chaput, Christopher D; Cross, Lauren M; Gaharwar, Akhilesh K; Gregory, Carl A

2018-04-01

Non-union defects of bone are a major problem in orthopedics, especially for patients with a low healing capacity. Fixation devices and osteoconductive materials are used to provide a stable environment for osteogenesis and an osteogenic component such as autologous human bone marrow (hBM) is then used, but robust bone formation is contingent on the healing capacity of the patients. A safe and rapid procedure for improvement of the osteoanabolic properties of hBM is, therefore, sought after in the field of orthopedics, especially if it can be performed within the temporal limitations of the surgical procedure, with minimal manipulation, and at point-of-care. One way to achieve this goal is to stimulate canonical Wingless (cWnt) signaling in bone marrow-resident human mesenchymal stem cells (hMSCs), the presumptive precursors of osteoblasts in bone marrow. Herein, we report that the effects of cWnt stimulation can be achieved by transient (1-2 hours) exposure of osteoprogenitors to the GSK3β-inhibitor (2'Z,3'E)-6-bromoindirubin-3'-oxime (BIO) at a concentration of 800 nM. Very-rapid-exposure-to-BIO (VRE-BIO) on either hMSCs or whole hBM resulted in the long-term establishment of an osteogenic phenotype associated with accelerated alkaline phosphatase activity and enhanced transcription of the master regulator of osteogenesis, Runx2. When VRE-BIO treated hBM was tested in a rat spinal fusion model, VRE-BIO caused the formation of a denser, stiffer, fusion mass as compared with vehicle treated hBM. Collectively, these data indicate that the VRE-BIO procedure may represent a rapid, safe, and point-of-care strategy for the osteogenic enhancement of autologous hBM for use in clinical orthopedic procedures. Stem Cells Translational Medicine 2018;7:342-353. © 2018 The Authors Stem Cells Translational Medicine published by Wiley Periodicals, Inc. on behalf of AlphaMed Press.

Rapid Osteogenic Enhancement of Stem Cells in Human Bone Marrow Using a Glycogen‐Synthease‐Kinase‐3‐Beta Inhibitor Improves Osteogenic Efficacy In Vitro and In Vivo

PubMed Central

Clough, Bret H.; Zeitouni, Suzanne; Krause, Ulf; Chaput, Christopher D.; Cross, Lauren M.; Gaharwar, Akhilesh K.

2018-01-01

Abstract Non‐union defects of bone are a major problem in orthopedics, especially for patients with a low healing capacity. Fixation devices and osteoconductive materials are used to provide a stable environment for osteogenesis and an osteogenic component such as autologous human bone marrow (hBM) is then used, but robust bone formation is contingent on the healing capacity of the patients. A safe and rapid procedure for improvement of the osteoanabolic properties of hBM is, therefore, sought after in the field of orthopedics, especially if it can be performed within the temporal limitations of the surgical procedure, with minimal manipulation, and at point‐of‐care. One way to achieve this goal is to stimulate canonical Wingless (cWnt) signaling in bone marrow‐resident human mesenchymal stem cells (hMSCs), the presumptive precursors of osteoblasts in bone marrow. Herein, we report that the effects of cWnt stimulation can be achieved by transient (1–2 hours) exposure of osteoprogenitors to the GSK3β‐inhibitor (2′Z,3′E)‐6‐bromoindirubin‐3′‐oxime (BIO) at a concentration of 800 nM. Very‐rapid‐exposure‐to‐BIO (VRE‐BIO) on either hMSCs or whole hBM resulted in the long‐term establishment of an osteogenic phenotype associated with accelerated alkaline phosphatase activity and enhanced transcription of the master regulator of osteogenesis, Runx2. When VRE‐BIO treated hBM was tested in a rat spinal fusion model, VRE‐BIO caused the formation of a denser, stiffer, fusion mass as compared with vehicle treated hBM. Collectively, these data indicate that the VRE‐BIO procedure may represent a rapid, safe, and point‐of‐care strategy for the osteogenic enhancement of autologous hBM for use in clinical orthopedic procedures. stem cells translational medicine 2018;7:342–353 PMID:29405665

Doctor-Shopping Behavior among Patients with Eye Floaters

PubMed Central

Tseng, Gow-Lieng; Chen, Cheng-Yu

2015-01-01

Patients suffering from eye floaters often resort to consulting more than one ophthalmologist. The purpose of this study, using the Health Belief Model (HBM), was to identify the factors that influence doctor-shopping behavior among patients with eye floaters. In this cross-sectional survey, 175 outpatients who presented floaters symptoms were enrolled. Data from 143 patients (77 first time visitors and 66 doctor-shoppers) who completed the questionnaire were analyzed. Descriptive and logistic regression analyses were performed. We found that women and non-myopia patients were significantly related with frequent attendance and doctor switching. Though the HBM has performed well in a number of health behaviors studies, but most of the conceptual constructors of HBM did not show significant differences between the first time visitors and true doctor-shoppers in this study. Motivation was the only significant category affecting doctor-shopping behavior of patients with eye floaters. PMID:26184266

Doctor-Shopping Behavior among Patients with Eye Floaters.

PubMed

Tseng, Gow-Lieng; Chen, Cheng-Yu

2015-07-13

Patients suffering from eye floaters often resort to consulting more than one ophthalmologist. The purpose of this study, using the Health Belief Model (HBM), was to identify the factors that influence doctor-shopping behavior among patients with eye floaters. In this cross-sectional survey, 175 outpatients who presented floaters symptoms were enrolled. Data from 143 patients (77 first time visitors and 66 doctor-shoppers) who completed the questionnaire were analyzed. Descriptive and logistic regression analyses were performed. We found that women and non-myopia patients were significantly related with frequent attendance and doctor switching. Though the HBM has performed well in a number of health behaviors studies, but most of the conceptual constructors of HBM did not show significant differences between the first time visitors and true doctor-shoppers in this study. Motivation was the only significant category affecting doctor-shopping behavior of patients with eye floaters.

Application of the Health Belief Model to customers' use of menu labels in restaurants.

PubMed

Jeong, Jin-Yi; Ham, Sunny

2018-04-01

Some countries require the provision of menu labels on restaurant menus to fight the increasing prevalence of obesity and related chronic diseases. This study views customers' use of menu labels as a preventive health behavior and applies the Health Belief Model (HBM) with the aim of determining the health belief factors that influence customers' use of menu labels. A self-administered survey was distributed for data collection. Responses were collected from 335 restaurant customers who experienced menu labels in restaurants within three months prior to the survey. The results of a structural equation model showed that all the HBM variables (perceived threats, perceived benefits, and perceived barriers of using menu labels) positively affected the customers' use of menu labels. Perceived threats were influenced by cues to action and cues to action had an indirect influence on menu label use through perceived threats. In conclusion, health beliefs were good predictors of menu label use on restaurant menus. This study validated the application of the HBM to menu labeling in restaurants, and its findings could offer guidelines for the industry and government in developing strategies to expand the use of menu labels among the public. Copyright © 2017 Elsevier Ltd. All rights reserved.

Readability, Suitability and Health Content Assessment of Cancer Screening Announcements in Municipal Newspapers in Japan.

PubMed

Okuhara, Tsuyoshi; Ishikawa, Hirono; Okada, Hiroko; Kiuchi, Takahiro

2015-01-01

The objective of this study was to assess the readability, suitability, and health content of cancer screening information in municipal newspapers in Japan. Suitability Assessment of Materials (SAM) and the framework of Health Belief Model (HBM) were used for assessment of municipal newspapers that were published in central Tokyo (23 wards) from January to December 2013. The mean domain SAM scores of content, literacy demand, and layout/typography were considered superior. The SAM scores of interaction with readers, an indication of the models of desirable actions, and elaboration to enhance readers' self-efficacy were low. According to the HBM coding, messages of medical/clinical severity, of social severity, of social benefits, and of barriers of fear were scarce. The articles were generally well written and suitable. However, learning stimulation/motivation was scarce and the HBM constructs were not fully addressed. Articles can be improved to motivate readers to obtain cancer screening by increasing interaction with readers, introducing models of desirable actions and devices to raise readers' self-efficacy, and providing statements of perceived barriers of fear for pain and time constraints, perceived severity, and social benefits and losses.

A review of human biomonitoring in selected Southeast Asian countries.

PubMed

Barnett-Itzhaki, Zohar; Esteban López, Marta; Puttaswamy, Naveen; Berman, Tamar

2018-07-01

Rapid development and industrialization in Southeast (SE) Asia has led to environmental pollution, potentially exposing the general population to environmental contaminants. Human biomonitoring (HBM), measurement of chemical and/or their metabolites in human tissues and fluids, is an important tool for assessing cumulative exposure to complex mixtures of chemicals and for monitoring chemical exposures in the general population. While there are national HBM programs in several developed countries, there are no such national programs in most of the SE Asian countries. However, in recent years there has been progress in the field of HBM in many of the SE Asian countries. In this review, we present recent HBM studies in five selected SE Asian countries: Bangladesh, Indonesia, Malaysia, Myanmar and Thailand. While there is extensive HBM research in several SE Asian countries, such as Thailand, in other countries HBM studies are limited and focus on traditional environmental pollutants (such as lead, arsenic and mercury). Further development of this field in SE Asia would be benefited by establishment of laboratory capacity, improving quality control and assurance, collaboration with international experts and consortiums, and sharing of protocols and training both for pre-analytical and analytical phases. This review highlights the impressive progress in HBM research in selected SE Asian countries and provides recommendations for development of this field. Copyright © 2018 Elsevier Ltd. All rights reserved.

Intention of Mothers in Israel to Vaccinate their Sons against the Human Papilloma Virus.

PubMed

Ben Natan, Merav; Midlej, Kareem; Mitelman, Olga; Vafiliev, Katya

This study investigated the intention of mothers in Israel to vaccinate their sons against HPV, using the Health Belief Model (HBM) as a framework, while comparing between Arab and Jewish mothers. The study has a quantitative cross-sectional design. A convenience sample of 200 Jewish and Arab mothers of boys aged 5-18 completed a questionnaire based on the HBM. The research findings indicate that only 14% of the mothers, constituting mostly Arab mothers, vaccinated their sons against HPV. Moreover, mothers showed a moderate level of intention to vaccinate their sons. This level was similar among Arab and Jewish mothers. However, the health beliefs of Jewish and Arab mothers differed. The HBM was found to explain 68% of mothers' intention to vaccinate their sons against HPV, and the perceived benefits of the vaccine were the factor most affecting this intention. Although mothers' health beliefs concerning vaccinating their sons against HPV may vary between sectors, the HBM can be used to explain what motivates mothers to vaccinate their sons. The research findings can assist in designing a national project among mothers of boys aimed at raising HPV vaccination rates, in both the Jewish and the Arab sector. Copyright © 2017 Elsevier Inc. All rights reserved.

Intrinsic material properties of cortical bone.

PubMed

Lopez Franco, Gloria E; Blank, Robert D; Akhter, Mohammed P

2011-01-01

The G171V mutation (high bone mass, HBM) is autosomal dominant and is responsible for high bone mass in humans. Transgenic HBM mice in which the human LRP5 G171V gene is inserted also show a similar phenotype with greater bone mass and biomechanical performance than wild-type mice, as determined by whole bone testing. Whole bone mechanics, however, depend jointly on bone mass, architecture, and intrinsic bone tissue mechanical properties. To determine whether the HBM mutation affects tissue-level biomechanical performance, we performed nano-indentation testing of unembedded cortical bone from HBM mice and their nontransgenic (NTG) littermates. Femora from 17-week-old mice (female, 8 mice/genotype) were subjected to nano-indentation using a Triboscope (Hysitron, Minneapolis, MN, USA). For each femoral specimen, approximately 10 indentations were made on the midshaft anterior surface with a target force of either 3 or 9 mN at a constant loading rate of 400 mN/s. The load-displacement data from each test were used to calculate indentation modulus and hardness for bone tissue. The intrinsic material property that reflected the bone modulus was greater (48%) in the HBM as compared to the NTG mice. Our results of intrinsic properties are consistent with the published structural and material properties of the midshaft femur in HBM and NTG mice. The greater intrinsic modulus in HBM reflects greater bone mineral content as compared to NTG (wild-type, WT) mice. This study suggests that the greater intrinsic property of cortical bone is derived from the greater bone mineral content and BMD, resulting in greater bone strength in HBM as compared to NTG (WT) mice.

Prevalence of radiographic hip osteoarthritis is increased in high bone mass.

PubMed

Hardcastle, S A; Dieppe, P; Gregson, C L; Hunter, D; Thomas, G E R; Arden, N K; Spector, T D; Hart, D J; Laugharne, M J; Clague, G A; Edwards, M H; Dennison, E M; Cooper, C; Williams, M; Davey Smith, G; Tobias, J H

2014-08-01

Epidemiological studies have shown an association between increased bone mineral density (BMD) and osteoarthritis (OA), but whether this represents cause or effect remains unclear. In this study, we used a novel approach to investigate this question, determining whether individuals with High Bone Mass (HBM) have a higher prevalence of radiographic hip OA compared with controls. HBM cases came from the UK-based HBM study: HBM was defined by BMD Z-score. Unaffected relatives of index cases were recruited as family controls. Age-stratified random sampling was used to select further population controls from the Chingford and Hertfordshire cohort studies. Pelvic radiographs were pooled and assessed by a single observer blinded to case-control status. Analyses used logistic regression, adjusted for age, gender and body mass index (BMI). 530 HBM hips in 272 cases (mean age 62.9 years, 74% female) and 1702 control hips in 863 controls (mean age 64.8 years, 84% female) were analysed. The prevalence of radiographic OA, defined as Croft score ≥3, was higher in cases compared with controls (20.0% vs 13.6%), with adjusted odds ratio (OR) [95% CI] 1.52 [1.09, 2.11], P = 0.013. Osteophytes (OR 2.12 [1.61, 2.79], P < 0.001) and subchondral sclerosis (OR 2.78 [1.49, 5.18], P = 0.001) were more prevalent in cases. However, no difference in the prevalence of joint space narrowing (JSN) was seen (OR 0.97 [0.72, 1.33], P = 0.869). An increased prevalence of radiographic hip OA and osteophytosis was observed in HBM cases compared with controls, in keeping with a positive association between HBM and OA and suggesting that OA in HBM has a hypertrophic phenotype. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Factors That Influence Israeli Muslim Arab Parents' Intention to Vaccinate Their Children Against Influenza.

PubMed

Ben Natan, Merav; Kabha, Samih; Yehia, Mamon; Hamza, Omar

2016-01-01

The purpose of the current study was to explore factors related to the intention of parents from the Muslim Arab ethnic minority in Israel to vaccinate their children against influenza, using the Health Belief Model (HBM). This study is a cross sectional quantitative study. A convenience sample of 200 parents of children aged 12 and younger completed a questionnaire based on the HBM. Perceived susceptibility, severity, benefits, and barriers predicted 88% of parents' intention to vaccinate their children. Parents who vaccinated their children in the past year were younger and had fewer children. Community nurses and physicians were identified as important cues to action. The HBM components predicted a high percentage of parents' intention to vaccinate their children Interventions to raise vaccination coverage rates among children belonging to an ethnic minority of Israeli Muslim Arabs should begin on the micro level of the parent-health care professional encounter. Copyright © 2016 Elsevier Inc. All rights reserved.

A Thematic Analysis of Health Care Workers' Adoption of Mindfulness Practices.

PubMed

Valley, Morgan; Stallones, Lorann

2018-05-01

Mindfulness training, which teaches individuals to bring awareness and acceptance to the present moment, has been effective in improving the well-being of health care workers. Limited research examines the adoption of mindfulness practices using health behavior theories. The current study sought to conceptualize hospital health care workers' experiences in adopting mindfulness practices using the Health Belief Model (HBM), a theoretical framework used by health promotion practitioners to design and implement health behavior change interventions. Hospital health care workers in Colorado participated in an 8-week Mindfulness-Based Stress Reduction (MBSR) course. Participants ( n = 19) answered open-ended questions about their experiences adopting mindfulness practices. A theory-driven thematic analysis approach was used to analyze data with key constructs of the HBM acting as the framework for the analysis. Results showed that HBM constructs, including internal cues to action, perceived benefits and barriers, and self-efficacy, helped portray the participants' experiences and challenges in adopting and adhering to the mindfulness practices taught in the MBSR course.

The role of anticipated regret and health beliefs in HPV vaccination intentions among young adults.

PubMed

Christy, Shannon M; Winger, Joseph G; Raffanello, Elizabeth W; Halpern, Leslie F; Danoff-Burg, Sharon; Mosher, Catherine E

2016-06-01

Although cognitions have predicted young adults' human papillomavirus (HPV) vaccine decision-making, emotion-based theories of healthcare decision-making suggest that anticipatory emotions may be more predictive. This study examined whether anticipated regret was associated with young adults' intentions to receive the HPV vaccine above and beyond the effects of commonly studied cognitions. Unvaccinated undergraduates (N = 233) completed a survey assessing Health Belief Model (HBM) variables (i.e., perceived severity of HPV-related diseases, perceived risk of developing these diseases, and perceived benefits of HPV vaccination), anticipatory emotions (i.e., anticipated regret if one were unvaccinated and later developed genital warts or HPV-related cancer), and HPV vaccine intentions. Anticipated regret was associated with HPV vaccine intentions above and beyond the effects of HBM variables among men. Among women, neither anticipated regret nor HBM variables showed consistent associations with HPV vaccine intentions. Findings suggest that anticipatory emotions should be considered when designing interventions to increase HPV vaccination among college men.

The role of anticipated regret and health beliefs in HPV vaccination intentions among young adults

PubMed Central

Christy, Shannon M.; Winger, Joseph G.; Raffanello, Elizabeth W.; Halpern, Leslie F.; Danoff-Burg, Sharon; Mosher, Catherine E.

2016-01-01

Although cognitions have predicted young adults’ human papillomavirus (HPV) vaccine decision-making, emotion-based theories of healthcare decision-making suggest that anticipatory emotions may be more predictive. This study examined whether anticipated regret was associated with young adults’ intentions to receive the HPV vaccine above and beyond the effects of commonly studied cognitions. Unvaccinated undergraduates (N = 233) completed a survey assessing Health Belief Model (HBM) variables (i.e., perceived severity of HPV-related diseases, perceived risk of developing these diseases, and perceived benefits of HPV vaccination), anticipatory emotions (i.e., anticipated regret if one were unvaccinated and later developed genital warts or HPV-related cancer), and HPV vaccine intentions. Anticipated regret was associated with HPV vaccine intentions above and beyond the effects of HBM variables among men. Among women, neither anticipated regret nor HBM variables showed consistent associations with HPV vaccine intentions. Findings suggest that anticipatory emotions should be considered when designing interventions to increase HPV vaccination among college men. PMID:26782668

Familial congenital cyanosis caused by Hb-MYantai(α-76 GAC → TAC, Asp → Tyr)

PubMed Central

2010-01-01

Methemoglobin (Hb-M) is a rare hemoglobinopathy in China. We hereby report on a family living in Yantai, East China, with congenital cyanosis due to Hb-M mutation. The proband, a 65-year-old female, presented 63% oxygen saturation. Both Hb-M concentration and arterial oxygen saturation remained unchanged, even following intravenous treatment with methylene blue. There was also no change in blood-color (chocolate-brown) after adding 0.1% KCN. A fast-moving band (Hb-X) in hemolysates was found by cellulose acetate electrophoresis, the Hb-X/Hb-A ratio exceeding 10%. GT transition at 131nt of exon 2, although present in one of the α2 -globin alleles, was not found in α1 -globin alleles as a whole. This mutation leads to the aspartic acid to tyrosine substitution (Asp76Tyr). In this family, the novel mutation in the α2 -globin gene resulted in a rare form of congenital cyanosis due to Hb-M. This hemoglobin was named Hb-M Yantai . PMID:21637412

Factors affecting nurses' decision to get the flu vaccine.

PubMed

Shahrabani, Shosh; Benzion, Uri; Yom Din, Gregory

2009-05-01

The objective of this study was to identify factors that influence the decision whether or not to get the influenza (flu) vaccine among nurses in Israel by using the health belief model (HBM). A questionnaire distributed among 299 nurses in Israel in winter 2005/2006 included (1) socio-demographic information; (2) variables based on the HBM, including susceptibility, seriousness, benefits, barriers and cues to action; and (3) knowledge about influenza and the vaccine, and health motivation. A probit model was used to analyze the data. In Israel, the significant HBM categories affecting nurses' decision to get a flu shot are the perceived benefits from vaccination and cues to action. In addition, nurses who are vaccinated have higher levels of (1) knowledge regarding the vaccine and influenza, (2) perceived seriousness of the illness, (3) perceived susceptibility, and (4) health motivation than do those who do not get the vaccine. Immunization of healthcare workers may reduce the risk of flu outbreaks in all types of healthcare facilities and reduce morbidity and mortality among high-risk patients. In order to increase vaccination rates among nurses, efforts should be made to educate them regarding the benefits of vaccination and the potential health consequences of influenza for their patients, and themselves.

A Health Belief Model-Social Learning Theory approach to adolescents' fertility control: findings from a controlled field trial.

PubMed

Eisen, M; Zellman, G L; McAlister, A L

1992-01-01

We evaluated an 8- to 12-hour Health Belief Model-Social Learning Theory (HBM-SLT)-based sex education program against several community- and school-based interventions in a controlled field experiment. Data on sexual and contraceptive behavior were collected from 1,444 adolescents unselected for gender, race/ethnicity, or virginity status in a pretest-posttest design. Over 60% completed the one-year follow-up. Multivariate analyses were conducted separately for each preintervention virginity status by gender grouping. The results revealed differential program impacts. First, for preintervention virgins, there were no gender or intervention differences in abstinence maintenance over the follow-up year. Second, female preintervention Comparison program virgins used effective contraceptive methods more consistently than those who attended the HBM-SLT program (p less than 0.01); among males, the intervention programs were equally effective. Third, both interventions significantly increased contraceptive efficiency for teenagers who were sexually active before attending the programs. For males, the HBM-SLT program led to significantly greater follow-up contraceptive efficiency than the Comparison program with preintervention contraceptive efficiency controlled (p less than 0.05); for females, the programs produced equivalent improvement. Implications for program planning and evaluation are discussed.

[Monograph on di-2-propylheptyl phthalate (DPHP) - human biomonitoring (HBM) values for the sum of metabolites oxo-mono-propylheptyl phthalate (oxo-MPHP) and hydroxy-mono-propylheptyl phthalate (OH MPHP) in adult and child urine. Opinion of the Commission "Human Biomonitoring" of the Federal Environment Agency, Germany].

PubMed

2015-07-01

1,2-benzenedicarboxylic acid, bis(2-propylheptyl)ester (bis(2-propylheptyl)phthalate, DPHP) is used as plasticizer for the manufacture of plastics, i.e. mainly polyvinylchloride (PVC). A subchronic feeding study with rats revealed a NOAEL (no observed adverse effect level) of 40 mg/(kg bw · d), which can be used as a point of departure (POD) for the derivation of an HBM-I value. Application of a total assessment factor of 200 leads to an estimation of 200 µg/kg bw as a tolerable daily intake of DPHP. On the basis of the results of metabolism studies with humans it is possible to calculate from the tolerable daily intake of DPHP to the tolerable concentration of specific metabolites in urine. Thus an HBM-I value of 1 mg/L morning urine for children and 1.5 mg/L morning urine for adults was derived for the sum of the oxidized monoesters oxo-MPHP and OH-MPHP, which were identified as robust and conclusive biomarkers for DPHP.

DMI's Baltic Sea Coastal operational forecasting system

NASA Astrophysics Data System (ADS)

Murawski, Jens; Berg, Per; Weismann Poulsen, Jacob

2017-04-01

Operational forecasting is challenged with bridging the gap between the large scales of the driving weather systems and the local, human scales of the model applications. The limit of what can be represented by local model has been continuously shifted to higher and higher spatial resolution, with the aim to better resolve the local dynamic and to make it possible to describe processes that could only be parameterised in older versions, with the ultimate goal to improve the quality of the forecast. Current hardware trends demand a str onger focus on the development of efficient, highly parallelised software and require a refactoring of the code with a solid focus on portable performance. The gained performance can be used for running high resolution model with a larger coverage. Together with the development of efficient two-way nesting routines, this has made it possible to approach the near-coastal zone with model applications that can run in a time effective way. Denmarks Meteorological Institute uses the HBM(1) ocean circulation model for applications that covers the entire Baltic Sea and North Sea with an integrated model set-up that spans the range of horizontal resolution from 1nm for the entire Baltic Sea to approx. 200m resolution in local fjords (Limfjord). For the next model generation, the high resolution set-ups are going to be extended and new high resolution domains in coastal zones are either implemented or tested for operational use. For the first time it will be possible to cover large stretches of the Baltic coastal zone with sufficiently high resolution to model the local hydrodynamic adequately. (1) HBM stands for HIROMB-BOOS-Model, whereas HIROMB stands for "High Resolution Model for the Baltic Sea" and BOOS stands for "Baltic Operational Oceanography System".

The Effect of Health Education Program Based on Health Belief Model on Oral Health Behaviors in Pregnant Women of Fasa City, Fars Province, South of Iran.

PubMed

Jeihooni, Ali Khani; Jamshidi, Hassan; Kashfi, Seyyed Mansour; Avand, Abolghasem; Khiyali, Zahra

2017-01-01

Pregnant women are at risk of dental caries and periodontal disease. The purpose of this study was to assess the effectiveness of health education program based on health belief model (HBM) on oral and dental hygiene behaviors in pregnant women in Fasa city. This is a clinical trial study carried out on 110 pregnant women selected using random sampling method from health centers in Fasa city in 2016 (55 patients in the experimental group and 55 individuals in control group). Data collection with questionnaire was based on construct HBM, as well as their performance about oral health. At first, two groups completed the questionnaires. And then, the intervention was conducted for the experimental group based on HBM. Four months after intervention, two groups completed the questionnaires twice. To analyze the collected data, the researchers used SPSS version 22 and descriptive and analytical statistics tests such as independent t -test and Chi-square and Mann-Whitney test. The age of the pregnant mothers was 28.25 ± 3.02 years in the experimental group and 27.8 ± 4.20 years in the control group. Compared to the control group, the experimental group showed a significant increase in their knowledge, perceived susceptibility, perceived severity, perceived benefits, self-efficacy, cues to action, and performance and decrease in perceived barriers 4 months after the intervention. Applying the HBM is very effective for developing an educational program for oral health in pregnant women. Moreover, in the implementation of these programs, control, monitoring, and follow-up educational are recommended.

Efficacy of HBM-Based Dietary Education Intervention on Knowledge, Attitude, and Behavior in Medical Students.

PubMed

Tavakoli, Hamid Reza; Dini-Talatappeh, Hossein; Rahmati-Najarkolaei, Fatemeh; Gholami Fesharaki, Mohammad

2016-11-01

Using various models of behavior change, a number of studies in the area of nutrition education have confirmed that nutrition habits and behaviors can be improved. This study sought to determine the effects of education on patterns of dietary consumption among medical students at the military university of Tehran, with a view to correcting those patterns. In this quasi-experimental study, 242 medical students from the Military University of Tehran were chosen by convenience sampling and then divided into control (n = 107) and intervention groups (n = 135) by block randomization. The self-administered questionnaire involving six categories of item (knowledge, perceived benefits, perceived barriers, perceived threats, self-efficacy and behavior) has been validated (Cronbach alpha > 0.7 for each). Following the educational intervention, the mean score of knowledge, health belief model (HBM) structure, and behavior of students in relation to healthy patterns of food intake increased significantly (P < 0.05). The mean pre-intervention knowledge score was 6.76 (1.452), referring to threats to HBM constructs including perceived threat 2.93 (1.147), perceived benefits 7.28 (1.07), perceived barriers 5.44 (1.831), self- efficacy 4.28 (1.479), and behavior 8.84 (2.527). The post-intervention scores all improved as follows: knowledge 8.3 (1.503), perceived threats 3.29 (1.196), perceived benefits 7.71 (0.762), perceived barriers 5.9 (1.719), self- efficacy 4.6 (1.472), and behavior 9.45 (2.324). This difference in mean scores for knowledge, health belief structures and employee behavior before and after educational intervention was significant (P ≤ 0.05). The significant improvement in the experimental group's mean knowledge, HBM structures , and behavior scores indicates the positive effect of the intervention.

Application of the health belief model and social cognitive theory for osteoporosis preventive nutritional behaviors in a sample of Iranian women

PubMed Central

Jeihooni, Ali Khani; Hidarnia, Alireza; Kaveh, Mohammad Hossein; Hajizadeh, Ebrahim; Askari, Alireza

2016-01-01

Background: Osteoporosis is the most common metabolic bone disease. The purpose of this study is to investigate the health belief model (HBM) and social cognitive theory (SCT) for osteoporosis preventive nutritional behaviors in women. Materials and Methods: In this quasi-experimental study, 120 patients who were women and registered under the health centers in Fasa City, Fars Province, Iran were selected. A questionnaire consisting of HBM constructs and the constructs of self-regulation and social support from SCT was used to measure nutrition performance. Bone mineral density was recorded at the lumbar spine and femur. The intervention for the experimental group included 10 educational sessions of 55-60 min of speech, group discussion, questions and answers, as well as posters and educational pamphlets, film screenings, and PowerPoint displays. Data were analyzed using SPSS 19 via Chi-square test, independent t-test, and repeated measures analysis of variance (ANOVA) at a significance level of 0.05. Results: After intervention, the experimental group showed a significant increase in the HBM constructs, self-regulation, social support, and nutrition performance, compared to the control group. Six months after the intervention, the value of lumbar spine bone mineral density (BMD) T-score increased to 0.127 in the experimental group, while it reduced to −0.043 in the control group. The value of the hip BMD T-score increased to 0.125 in the intervention group, but it decreased to −0.028 in the control group. Conclusions: This study showed the effectiveness of HBM and constructs of self-regulation and social support on adoption of nutrition behaviors and increase in the bone density to prevent osteoporosis. PMID:27095985

Is the cluster environment quenching the Seyfert activity in elliptical and spiral galaxies?

NASA Astrophysics Data System (ADS)

de Souza, R. S.; Dantas, M. L. L.; Krone-Martins, A.; Cameron, E.; Coelho, P.; Hattab, M. W.; de Val-Borro, M.; Hilbe, J. M.; Elliott, J.; Hagen, A.; COIN Collaboration

2016-09-01

We developed a hierarchical Bayesian model (HBM) to investigate how the presence of Seyfert activity relates to their environment, herein represented by the galaxy cluster mass, M200, and the normalized cluster centric distance, r/r200. We achieved this by constructing an unbiased sample of galaxies from the Sloan Digital Sky Survey, with morphological classifications provided by the Galaxy Zoo Project. A propensity score matching approach is introduced to control the effects of confounding variables: stellar mass, galaxy colour, and star formation rate. The connection between Seyfert-activity and environmental properties in the de-biased sample is modelled within an HBM framework using the so-called logistic regression technique, suitable for the analysis of binary data (e.g. whether or not a galaxy hosts an AGN). Unlike standard ordinary least square fitting methods, our methodology naturally allows modelling the probability of Seyfert-AGN activity in galaxies on their natural scale, I.e. as a binary variable. Furthermore, we demonstrate how an HBM can incorporate information of each particular galaxy morphological type in an unified framework. In elliptical galaxies our analysis indicates a strong correlation of Seyfert-AGN activity with r/r200, and a weaker correlation with the mass of the host cluster. In spiral galaxies these trends do not appear, suggesting that the link between Seyfert activity and the properties of spiral galaxies are independent of the environment.

Community knowledge, health beliefs, practices and experiences related to dengue fever and its association with IgG seropositivity.

PubMed

Wong, Li Ping; AbuBakar, Sazaly; Chinna, Karuthan

2014-05-01

Demographic, economic and behavioural factors are central features underpinning the successful management and biological control of dengue. This study aimed to examine these factors and their association with the seroprevalence of this disease. We conducted a cross-sectional telephone survey of households in a 3 km radius of the schools where we had conducted serological tests on the student population in a previous study. Households were surveyed about their socio-demographics, knowledge, practices, and Health Belief Model (HBM) constructs. The results were then associated with the prevalence rate of dengue in the community, as marked by IgG seropositivity of the students who attended school there. A total of 1,400 complete responses were obtained. The community's IgG seropositivity was significantly positively associated with high household monthly income, high-rise residential building type, high surrounding vegetation density, rural locality, high perceived severity and susceptibility, perceived barriers to prevention, knowing that a neighbour has dengue, frequent fogging and a higher level of knowledge about dengue. In the multivariate analyses, three major correlates of the presence of IgG seropositivity in the community: (1) high-rise residential apartment house type or condominium buildings; (2) the main construct of the HBM, perceived severity and susceptibility; and (3) the additional constructs of the HBM, lack of preventive measures from the community level and having a neighbour with dengue as a cue to action. Weak correlations were found between self-practices to prevent dengue and the level of dengue seropositivity in the community, and between HBM constructs and knowledge (r = 0.09). The residential environment factor and the constructs of the HBM are useful and important elements in developing interventions to prevent and control dengue. The study also sheds light on the importance of the need for approaches that ensure the translation of knowledge into practice.

Organizational Twitter Use: Content Analysis of Tweets during Breast Cancer Awareness Month.

PubMed

Diddi, Pratiti; Lundy, Lisa K

2017-03-01

On an average, at least one out of eight women are at risk of falling prey to breast cancer during their lifespan. Amongst varied initiatives to spread awareness about breast cancer, the most well-known campaign is Breast Cancer Awareness Month. This article explored, through content analysis, how four different health-related organizations-Susan G. Komen, U.S. News Health, Woman's Hospital, and Breast Cancer Social Media-used their Twitter accounts to talk about varied aspects of breast cancer during the month of October, which is observed as Breast Cancer Awareness Month. All the tweets by these organizations were analyzed for the presence or absence of the theoretical parameters of the Health Belief Model (HBM). A content analysis of 2916 tweets based on the HBM revealed that the content posted by these organizations reflected the use of varied theoretical constructs of the framework. Overall, the study demonstrated that while different organizations shared valuable breast cancer-related content on Twitter, each used the social media platform in a different fashion, evident through focus on different types of HBM constructs while publishing breast cancer-related tweets.

Cariogenicity and acidogenicity of human milk, plain and sweetened bovine milk: an in vitro study.

PubMed

Prabhakar, A R; Kurthukoti, Ameet J; Gupta, Pranjali

2010-01-01

The objective of the present study was to determine the acidogenicity and cariogenicity of human breast milk and plain and sweetened packaged bovine milk. First all milk specimens were inoculated with a cariogenic strain of Streptococcus mutans (SM). The culture pH and number of colony forming units (cfus) was assessed. Second, the buffer capacity of all milk specimens was evaluated by mixing with acid. Finally, enamel windows were created on extracted primary maxillary incisors and colonized with SM. Enamel demineralization and caries progression were assessed visually, histologically, and radiographically at the end of twelve weeks. Plain and sweetened packaged bovine milk (BM) supported greater bacterial growth and caused more fermentation than human breast milk (HBM). The buffer capacity values for plain and sweetened bovine milk were highest; HBM, however had poor buffering capacity. The progression of the carious lesions into the dentin was most severe for the sweetened bovine milk. HBM and plain bovine milk are relatively cariogenic in an in vitro caries model in the absence of saliva. However, supplementation with sugar exponentially enhances the cariogenic potential of the natural milk.

From Evidence-based Medicine to Human-based Medicine in Psychosomatics.

PubMed

Musalek, Michael

2016-08-23

Human-based medicine (HbM), a form of psychiatry that focuses not only on fragments and constructs but on the whole person, no longer finds its theoretical basis in the positivism of the modern era, but rather owes its central maxims to the post-modernist ideal that ultimate truths or objectivity in identifying the final cause of illness remain hidden from us for theoretical reasons alone. Evidence-based medicine (EbM) and HbM are thus not mutually exclusive opposites; rather, despite superficial differences in methods of diagnosis and treatment, EbM must be integrated into HbM as an indispensable component of the latter. Probably the most important difference between EbM and HbM lies in the aims and methods of treatment. In HbM the goal is no longer simply to make illnesses disappear but rather to allow the patient to return to a life that is as autonomous and happy as possible. The human being with all his or her potential and limitations once again becomes the measure of all things. This also implies, however, that the multidimensional diagnostics of HbM are oriented not only towards symptoms, pathogenesis, process and understanding but also to a greater degree towards the patient's resources. Treatment options and forms of therapy do not put the disease construct at the centre of the diagnostic and therapeutic interest, but have as their primary aim the reopening of the possibility of a largely autonomous and joyful life for the patient.

Factor structure and internal reliability of an exercise health belief model scale in a Mexican population.

PubMed

Villar, Oscar Armando Esparza-Del; Montañez-Alvarado, Priscila; Gutiérrez-Vega, Marisela; Carrillo-Saucedo, Irene Concepción; Gurrola-Peña, Gloria Margarita; Ruvalcaba-Romero, Norma Alicia; García-Sánchez, María Dolores; Ochoa-Alcaraz, Sergio Gabriel

2017-03-01

Mexico is one of the countries with the highest rates of overweight and obesity around the world, with 68.8% of men and 73% of women reporting both. This is a public health problem since there are several health related consequences of not exercising, like having cardiovascular diseases or some types of cancers. All of these problems can be prevented by promoting exercise, so it is important to evaluate models of health behaviors to achieve this goal. Among several models the Health Belief Model is one of the most studied models to promote health related behaviors. This study validates the first exercise scale based on the Health Belief Model (HBM) in Mexicans with the objective of studying and analyzing this model in Mexico. Items for the scale called the Exercise Health Belief Model Scale (EHBMS) were developed by a health research team, then the items were applied to a sample of 746 participants, male and female, from five cities in Mexico. The factor structure of the items was analyzed with an exploratory factor analysis and the internal reliability with Cronbach's alpha. The exploratory factor analysis reported the expected factor structure based in the HBM. The KMO index (0.92) and the Barlett's sphericity test (p < 0.01) indicated an adequate and normally distributed sample. Items had adequate factor loadings, ranging from 0.31 to 0.92, and the internal consistencies of the factors were also acceptable, with alpha values ranging from 0.67 to 0.91. The EHBMS is a validated scale that can be used to measure exercise based on the HBM in Mexican populations.

Effect of health belief model and health promotion model on breast cancer early diagnosis behavior: a systematic review.

PubMed

Ersin, Fatma; Bahar, Zuhal

2011-01-01

Breast cancer is an important public health problem on the grounds that it is frequently seen and it is a fatal disease. The objective of this systematic analysis is to indicate the effects of interventions performed by nurses by using the Health Belief Model (HBM) and Health Promotion Model (HPM) on the breast cancer early diagnosis behaviors and on the components of the Health Belief Model and Health Promotion Model. The reveiw was created in line with the Centre for Reviews and Dissemination guide dated 2009 (CRD) and developed by York University National Institute of Health Researches. Review was conducted by using PUBMED, OVID, EBSCO and COCHRANE databases. Six hundred seventy eight studies (PUBMED: 236, OVID: 162, EBSCO: 175, COCHRANE:105) were found in total at the end of the review. Abstracts and full texts of these six hundred seventy eight studies were evaluated in terms of inclusion and exclusion criteria and 9 studies were determined to meet the criteria. Samplings of the studies varied between ninety four and one thousand six hundred fifty five. It was detected in the studies that educations provided by taking the theories as basis became effective on the breast cancer early diagnosis behaviors. When the literature is examined, it is observed that the experimental researches which compare the concepts of Health Belief Model (HBM) and Health Promotion Model (HPM) preoperatively and postoperatively and show the effect of these concepts on education and are conducted by nurses are limited in number. Randomized controlled studies which compare HBM and HPM concepts preoperatively and postoperatively and show the efficiency of the interventions can be useful in evaluating the efficiency of the interventions.

Qualitative to quantitative: linked trajectory of method triangulation in a study on HIV/AIDS in Goa, India.

PubMed

Bailey, Ajay; Hutter, Inge

2008-10-01

With 3.1 million people estimated to be living with HIV/AIDS in India and 39.5 million people globally, the epidemic has posed academics the challenge of identifying behaviours and their underlying beliefs in the effort to reduce the risk of HIV transmission. The Health Belief Model (HBM) is frequently used to identify risk behaviours and adherence behaviour in the field of HIV/AIDS. Risk behaviour studies that apply HBM have been largely quantitative and use of qualitative methodology is rare. The marriage of qualitative and quantitative methods has never been easy. The challenge is in triangulating the methods. Method triangulation has been largely used to combine insights from the qualitative and quantitative methods but not to link both the methods. In this paper we suggest a linked trajectory of method triangulation (LTMT). The linked trajectory aims to first gather individual level information through in-depth interviews and then to present the information as vignettes in focus group discussions. We thus validate information obtained from in-depth interviews and gather emic concepts that arise from the interaction. We thus capture both the interpretation and the interaction angles of the qualitative method. Further, using the qualitative information gained, a survey is designed. In doing so, the survey questions are grounded and contextualized. We employed this linked trajectory of method triangulation in a study on the risk assessment of HIV/AIDS among migrant and mobile men. Fieldwork was carried out in Goa, India. Data come from two waves of studies, first an explorative qualitative study (2003), second a larger study (2004-2005), including in-depth interviews (25), focus group discussions (21) and a survey (n=1259). By employing the qualitative to quantitative LTMT we can not only contextualize the existing concepts of the HBM, but also validate new concepts and identify new risk groups.

Advancing Data assimilation for Baltic Monitoring and Forecasting Center: implementation and evaluation of HBP-PDAF system

NASA Astrophysics Data System (ADS)

Korabel, Vasily; She, Jun; Huess, Vibeke; Woge Nielsen, Jacob; Murawsky, Jens; Nerger, Lars

2017-04-01

The potential of an efficient data assimilation (DA) scheme to improve model forecast skill was successfully demonstrated by many operational centres around the world. The Baltic-North Sea region is one of the most heavily monitored seas. Ferryboxes, buoys, ADCP moorings, shallow water Argo floats, and research vessels are providing more and more near-real time observations. Coastal altimetry has now providing increasing amount of high resolution sea level observations, which will be significantly expanded by the launch of SWOT satellite in next years. This will turn operational DA into a valuable tool for improving forecast quality in the region. This motivated us to focus on advancing DA for the Baltic Monitoring and Forecasting Centre (BAL MFC) in order to create a common framework for operational data assimilation in the Baltic Sea. We have implemented HBM-PDAF system based on the Parallel Data Assimilation Framework (PDAF), a highly versatile and optimised parallel suit with a choice of sequential schemes originally developed at AWI, and a hydrodynamic HIROMB-BOOS Model (HBM). At initial phase, only the satellite Sea Surface Temperature (SST) Level 3 data has been assimilated. Several related aspects are discussed, including improvements of the forecast quality for both surface and subsurface fields, the estimation of ensemble-based forecast error covariance, as well as possibilities of assimilating new types of observations, such as in-situ salinity and temperature profiles, coastal altimetry, and ice concentration.

A review of Human Biomonitoring studies of trace elements in Pakistan.

PubMed

Waseem, Amir; Arshad, Jahanzaib

2016-11-01

Human biomonitoring (HBM) measures the concentration levels of substances or their metabolites in human body fluids and tissues. HBM of dose and biochemical effect monitoring is an effective way of measuring human exposure to chemical substances. Many countries have conducted HBM studies to develop a data base for many chemicals including trace metals of health concern for their risk assessment and risk management. However, in Pakistan, HBM program on large scale for general population does not exist at present or in the past has been reported. Various individual HBM studies have been reported on the assessment of trace elements (usually heavy metals) from Pakistan; most of them are epidemiological cross sectional surveys. In this current review we tried to develop a data base of HBM studies of trace elements namely arsenic, cadmium, copper, chromium, iron, lead, manganese, nickel, and zinc in biological fluids (blood, urine) and tissues (hair, nails) in general population of Pakistan. Studies from all available sources have been explored, discussed and presented in the form of tables and figures. The results of these studies were critically compared with large scale HBM programs of other countries, (US & European communities etc). It was observed from the present study that the most of the toxic metals in biological fluids/tissues in general population of Pakistan, have higher background values comparatively. For example the mean values of toxic metals like As, Cd, Cr, Ni, and Pb in blood of general population were found as 2.08 μg/L, 4.24 μg/L, 60.5 μg/L, 1.95 μg/L, 198 μg/L respectively. Similarly, the urine mean values of 67.6 μg/L, 3.2 μg/L, 16.4 μg/L, 6.2 μg/L and 86.5 μg/L were observed for As, Cd, Cr, Ni, and Pb respectively. Copyright © 2016 Elsevier Ltd. All rights reserved.

A new treatment for predicting the self-excited vibrations of nonlinear systems with frictional interfaces: The Constrained Harmonic Balance Method, with application to disc brake squeal

NASA Astrophysics Data System (ADS)

Coudeyras, N.; Sinou, J.-J.; Nacivet, S.

2009-01-01

Brake squeal noise is still an issue since it generates high warranty costs for the automotive industry and irritation for customers. Key parameters must be known in order to reduce it. Stability analysis is a common method of studying nonlinear phenomena and has been widely used by the scientific and the engineering communities for solving disc brake squeal problems. This type of analysis provides areas of stability versus instability for driven parameters, thereby making it possible to define design criteria. Nevertheless, this technique does not permit obtaining the vibrating state of the brake system and nonlinear methods have to be employed. Temporal integration is a well-known method for computing the dynamic solution but as it is time consuming, nonlinear methods such as the Harmonic Balance Method (HBM) are preferred. This paper presents a novel nonlinear method called the Constrained Harmonic Balance Method (CHBM) that works for nonlinear systems subject to flutter instability. An additional constraint-based condition is proposed that omits the static equilibrium point (i.e. the trivial static solution of the nonlinear problem that would be obtained by applying the classical HBM) and therefore focuses on predicting both the Fourier coefficients and the fundamental frequency of the stationary nonlinear system. The effectiveness of the proposed nonlinear approach is illustrated by an analysis of disc brake squeal. The brake system under consideration is a reduced finite element model of a pad and a disc. Both stability and nonlinear analyses are performed and the results are compared with a classical variable order solver integration algorithm. Therefore, the objectives of the following paper are to present not only an extension of the HBM (CHBM) but also to demonstrate an application to the specific problem of disc brake squeal with extensively parametric studies that investigate the effects of the friction coefficient, piston pressure, nonlinear stiffness and structural damping.

[Monograph for 3-(4-methylbenzylidene)camphor (4-MBC)--HBM values for the sum of metabolites 3-(4-carboxybenzylidene)camphor (3-4CBC) and 3-(4-carboxybenzylidene)-6-hydroxycamphor (3-4 CBHC) in the urine of adults and children. Statement of the HBM Commission of the German Federal Environment Agency].

PubMed

2016-01-01

The substance 3-(4-methylbenzylidene)camphor (4-MBC, CAS-No. 36861-47-9 as well as 38102-62-4) is used as UV-filter in cosmetics, mainly in sunscreen lotions. National as well as European evaluations are available for the substance, especially from the Scientific Committee on Consumer Products (SCCP). The SCCP did not derive a TDI-value, but used for a MoS assessment a NOAEL of 25 mg/(kg bw · d) based on effects on the thyroid gland of rats in a subchronic study with oral administration. Newer studies, however, indicate lower NOAEL values, leading to tolerable daily intakes of 0,01 mg/kg bw. The HBM Commission established for the metabolite 3-(4-carboxybenzylidene)camphor (3-4CBC) HBM-I values of 0,09 mg/l urine for adults and 0,06 mg/l urine for children. HBM-I values for the metabolite 3-(4-carboxybenzylidene)-6-hydroxycamphor (3-4CBHC) were set at 0,38 mg/l urine for adults and 0,25 mg/l urine for children. The rounded HBM-I value for the sum of metabolites 3-4CBC und 3-4CBHC is accordingly 0,5 mg/l urine for adults and 0,3 mg/l urine for children.

Human biomonitoring: Science and policy for a healthy future, April 17-19, 2016, Berlin, Germany.

PubMed

Joas, Anke; Schwedler, Gerda; Choi, Judy; Kolossa-Gehring, Marike

2017-03-01

Following the success of the 1st International Conference on Human Biomonitoring (HBM) in Berlin in 2010, the 2nd International Conference on Human Biomonitoring took place in Berlin from April 17-19, 2016 for an exchange and updates among participants on all aspects relating to HBM. Entitled "Science and Policy for a Healthy Future", the conference brought together international experts from the scientific sector, politics, authorities, industry, non-governmental organizations (NGOs), and other involved associations. The conference took a critical look at today's chemicals that have a potential impact on human health and should be investigated as a matter of priority. It also discussed current activities and research efforts on HBM occurring worldwide, presented HBM success stories, and emphasized areas, where further research and focus are needed to improve the use of HBM for policy making. In many countries, HBM has been proven to be a useful tool and warning system to indicate problematic human exposure to pollutants and to evaluate the effectiveness of existing chemicals policy and regulations. However, important challenges remain such as exposure assessment of mixtures of chemicals, the development of analytical methods to detect new chemicals of concern (e.g., substitutes for phthalates), the identification of exposure sources, and the assessment of the impact of exposure on health. This brief report summarizes the discussions and contributions from this conference, which was jointly organized by the German Federal Environment Agency (UBA) and the German Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (BMUB). Copyright © 2017.

Reduction of microhemorrhages in the spinal cord of symptomatic ALS mice after intravenous human bone marrow stem cell transplantation accompanies repair of the blood-spinal cord barrier.

PubMed

Eve, David J; Steiner, George; Mahendrasah, Ajay; Sanberg, Paul R; Kurien, Crupa; Thomson, Avery; Borlongan, Cesar V; Garbuzova-Davis, Svitlana

2018-02-13

Blood-spinal cord barrier (BSCB) alterations, including capillary rupture, have been demonstrated in animal models of amyotrophic lateral sclerosis (ALS) and ALS patients. To date, treatment to restore BSCB in ALS is underexplored. Here, we evaluated whether intravenous transplantation of human bone marrow CD34 + (hBM34 + ) cells into symptomatic ALS mice leads to restoration of capillary integrity in the spinal cord as determined by detection of microhemorrhages. Three different doses of hBM34 + cells (5 × 10 4 , 5 × 10 5 or 1 × 10 6 ) or media were intravenously injected into symptomatic G93A SOD1 mice at 13 weeks of age. Microhemorrhages were determined in the cervical and lumbar spinal cords of mice at 4 weeks post-treatment, as revealed by Perls' Prussian blue staining for ferric iron. Numerous microhemorrhages were observed in the gray and white matter of the spinal cords in media-treated mice, with a greater number of capillary ruptures within the ventral horn of both segments. In cell-treated mice, microhemorrhage numbers in the cervical and lumbar spinal cords were inversely related to administered cell doses. In particular, the pervasive microvascular ruptures determined in the spinal cords in late symptomatic ALS mice were significantly decreased by the highest cell dose, suggestive of BSCB repair by grafted hBM34 + cells. The study results provide translational outcomes supporting transplantation of hBM34 + cells at an optimal dose as a potential therapeutic strategy for BSCB repair in ALS patients.

The transtheoretical model, health belief model, and breast cancer screening among Iranian women with a family history of breast cancer.

PubMed

Farajzadegan, Ziba; Fathollahi-Dehkordi, Fariba; Hematti, Simin; Sirous, Reza; Tavakoli, Neda; Rouzbahani, Reza

2016-01-01

Participation of Iranian women with a family history of breast cancer in breast cancer screening programs is low. This study evaluates the compliance of women having a family history of breast cancer with clinical breast exam (CBE) according to the stage of transtheoretical model (TTM) and health belief model (HBM). In this cross-sectional study, we used Persian version of champion's HBM scale to collect factors associated with TTM stages applied to screening from women over 20 years and older. The obtained data were analyzed by SPSS, using descriptive statistics, Chi-square test, independent t -test, and analysis of covariance. Final sample size was 162 women. Thirty-three percent were in action/maintenance stage. Older women, family history of breast cancer in first-degree relatives, personal history of breast disease, insurance coverage, and a history of breast self-examination were associated with action/maintenance stage. Furthermore, women in action/maintenance stages had significantly fewer perceived barriers in terms of CBE in comparison to women in other stages ( P < 0.05). There was no significant difference in other HBM subscales scores between various stages of CBE screening behavior ( P > 0.05). The finding indicates that the rate of women in action/maintenance stage of CBE is low. Moreover, results show a strong association between perceived barriers and having a regular CBE. These clarify the necessity of promoting national target programs for breast cancer screening, which should be considered as the first preference for reducing CBE barriers.

Prediction of safe driving Behaviours based on health belief model: the case of taxi drivers in Bandar Abbas, Iran.

PubMed

Razmara, Asghar; Aghamolaei, Teamur; Madani, Abdoulhossain; Hosseini, Zahra; Zare, Shahram

2018-03-20

Road accidents are among the main causes of mortality. As safe and secure driving is a key strategy to reduce car injuries and offenses, the present research aimed to explore safe driving behaviours among taxi drivers based on the Health Belief Model (HBM). This study was conducted on 184 taxi drivers in Bandar Abbas who were selected based on a multiple stratified sampling method. Data were collected by a questionnaire comprised of a demographic information section along with the constructs of the HBM. Data were analysed by SPSS ver19 via a Pearson's correlation coefficient and multiple regressions. The mean age of the participants was 45.1 years (SD = 11.1). They all had, on average, 10.3 (SD = 7/5) years of taxi driving experience. Among the HBM components, cues to action and perceived benefits were shown to be positively correlated with safe driving behaviours, while perceived barriers were negatively correlated. Cues to action, perceived barriers and perceived benefits were shown to be the strongest predictors of a safe drivers' behaviour. Based on the results of this study in designing health promotion programmes to improve safe driving behaviours among taxi drivers, cues to action, perceived benefits and perceived barriers are important. Therefore, advertising, the design of information campaigns, emphasis on the benefits of safe driving behaviours and modification barriers are recommended.

Local SAR in High Pass Birdcage and TEM Body Coils for Multiple Human Body Models in Clinical Landmark Positions at 3T

PubMed Central

Yeo, Desmond TB; Wang, Zhangwei; Loew, Wolfgang; Vogel, Mika W; Hancu, Ileana

2011-01-01

Purpose To use EM simulations to study the effects of body type, landmark position, and RF body coil type on peak local SAR in 3T MRI. Materials and Methods Numerically computed peak local SAR for four human body models (HBMs) in three landmark positions (head, heart, pelvic) were compared for a high-pass birdcage and a transverse electromagnetic 3T body coil. Local SAR values were normalized to the IEC whole-body average SAR limit of 2.0 W/kg for normal scan mode. Results Local SAR distributions were highly variable. Consistent with previous reports, the peak local SAR values generally occurred in the neck-shoulder area, near rungs, or between tissues of greatly differing electrical properties. The HBM type significantly influenced the peak local SAR, with stockier HBMs, extending extremities towards rungs, displaying the highest SAR. There was also a trend for higher peak SAR in the head-centric and heart-centric positions. The impact of the coil-types studied was not statistically significant. Conclusion The large variability in peak local SAR indicates the need to include more than one HBM or landmark position when evaluating safety of body coils. It is recommended that a HBM with arms near the rungs be included, to create physically realizable high-SAR scenarios. PMID:21509880

Vaccine perception among acceptors and non-acceptors in Sokoto State, Nigeria.

PubMed

Murele, Bola; Vaz, Rui; Gasasira, Alex; Mkanda, Pascal; Erbeto, Tesfaye; Okeibunor, Joseph

2014-05-30

Vaccine perceptions among acceptors and non-acceptors of childhood vaccination were explored. Seventy-two care givers, among them, acceptors and non-acceptors were interviewed in-depth with an interview guide that assessed vaccine acceptance, social and personality factors, and health belief model (HBM) categories in relation to oral polio vaccine (perceived susceptibility, severity, cost barriers, general barriers, benefits, knowledge, and engagement in preventative health behaviours). Community leaders were purposively selected while parents were selected on the basis of availability while ensuring the different attitude to vaccines was covered. Results showed that the HBM framework was found to be appropriate for identifying and distinguishing vaccine acceptors and non-acceptors. In addition, the HBM categories of benefits and susceptibility were found to influence oral polio vaccine acceptance. Second, the opinion of family members about the oral polio vaccine moderated the relationship between number of social ties and vaccine acceptance. Further, oral polio vaccine acceptance was related to outbreaks of paralysis of any sort, but not aggregate scores of other preventative health behaviours. Implications of this study include the investigation of vaccine acceptance in a high risk population. Research was done to investigate vaccine acceptance. Copyright © 2014 Elsevier Ltd. All rights reserved.

Health beliefs and breast self-examination in a sample of Turkish women academicians in a university.

PubMed

Ceber, Esin; Yücel, Ummahan; Mermer, Gülengül; Ozentürk, Gülsün

2009-01-01

The purpose of this study was to evaluate health beliefs and BSE behavior of female academicians in a Turkish university. This descriptive study was conducted at various faculties located in Ege University, Izmir, Turkey, in 2005. The sample consisted of 224 female academicians. Data were collected using a self-administered questionnaire and the Turkish version of Champion's Health Belief Model Scales (HBM). Descriptive statistics, t-test and Mann Whitney u analysis were conducted. The percentage of participants who regularly performed BSE was 27.7 %. Benefits and health motivation related to BSE ranked either first or second, along with confidence. Perceived barriers to BSE had the lowest item mean subscale score in academicians. Single academicians perceived susceptibility and seriousness higher than their married counterparts. Family history of breast cancer of participants affected their health beliefs subscale. BSE performance among participants was more likely in women academicians who exhibited higher confidence and those who perceived fewer barriers related to BSE performance, complying with the conceptual structure of the HBM. Therefore, it is recommended that in order to increase the rates of regular breast cancer screening, mass health protective programs based on the HBM should be executed for women.

Recent Performance Results of VPIC on Trinity

NASA Astrophysics Data System (ADS)

Nystrom, W. D.; Bergen, B.; Bird, R. F.; Bowers, K. J.; Daughton, W. S.; Guo, F.; Le, A.; Li, H.; Nam, H.; Pang, X.; Stark, D. J.; Rust, W. N., III; Yin, L.; Albright, B. J.

2017-10-01

Trinity is a new DOE compute resource now in production at Los Alamos National Laboratory. Trinity has several new and unique features including two compute partitions, one with dual socket Intel Haswell Xeon compute nodes and one with Intel Knights Landing (KNL) Xeon Phi compute nodes, use of on package high bandwidth memory (HBM) for KNL nodes, ability to configure KNL nodes with respect to HBM model and on die network topology in a variety of operational modes at run time, and use of solid state storage via burst buffer technology to reduce time required to perform I/O. An effort is in progress to optimize VPIC on Trinity by taking advantage of these new architectural features. Results of work will be presented on performance of VPIC on Haswell and KNL partitions for single node runs and runs at scale. Results include use of burst buffers at scale to optimize I/O, comparison of strategies for using MPI and threads, performance benefits using HBM and effectiveness of using intrinsics for vectorization. Work performed under auspices of U.S. Dept. of Energy by Los Alamos National Security, LLC Los Alamos National Laboratory under contract DE-AC52-06NA25396 and supported by LANL LDRD program.

Sociopsychological correlates of motivation to quit smoking among low-SES African American women.

PubMed

Manfredi, C; Lacey, L P; Warnecke, R; Petraitis, J

1998-06-01

This article examines correlates of desire and plans to quit smoking among 248 young, low-socioeconomic status African American women, using variables derived from the health belief model (HBM) and the theory of reasoned action. Consistent with these theoretical models, stronger concern about the effect of smoking on one's health and having close others who want the smoker to quit increased motivation to quit smoking. However, motivation was not associated with specific HBM components regarding lung cancer. Heavier smoking and stronger perceptions regarding the functional utility of smoking decreased motivation to quit, but not as much as expected in this study population. Consistent with a process of change approach to smoking cessation, the factors that moved smokers from not planning to planning to ever quit were different from factors associated with further motivation level among the smokers who did plan to ever quit.

Identification of exposure to environmental chemicals in children and older adults using human biomonitoring data sorted by age: Results from a literature review.

PubMed

Choi, Judy; Knudsen, Lisbeth E; Mizrak, Seher; Joas, Anke

2017-03-01

Human biomonitoring (HBM) provides the tools for exposure assessment by direct measurements of biological specimens such as blood and urine. HBM can identify new chemical exposures, trends and changes in exposure, establish distribution of exposure among the general population, and identify vulnerable groups and populations with distinct exposures such as children and older adults. The objective of this review is to demonstrate the use of HBM to identify environmental chemicals that might be of concern for children or older adults due to higher body burden. To do so, an extensive literature search was performed, and using a set of defined criteria, ten large-scale, cross-sectional national HBM programs were selected for data review and evaluation. A comparative analysis of the age-stratified data from these programs and other relevant HBM studies indicated twelve chemicals/classes of chemicals with potentially higher body burden in children or older adults. Children appear to have higher body burden of bisphenol A (BPA), some phytoestrogens, perchlorate, and some metabolites of polycyclic aromatic hydrocarbons and benzene. On the other hand, older adults appear to have higher body burden of heavy metals and organochlorine pesticides. For perfluoroalkyl substances, polybrominated diphenyl ethers, parabens, and phthalates, both children and older adults have higher body burden depending on the specific biomarkers analyzed, and this might be due to the exposure period and/or sources from different countries. Published data from the DEMOCOPHES project (a pilot study to harmonize HBM efforts across Europe) also showed elevated exposures to BPA and some phthalate metabolites in children across several European countries. In summary, age-stratified HBM data can provide useful knowledge of identifying environmental chemicals that might be of concern for children and older adults, which, combined with additional efforts to identify potential sources of exposure, could assist policy makers in prioritizing their actions in order to reduce chemical exposure and potential risks of adverse health effects. Copyright © 2016 Elsevier GmbH. All rights reserved.

Randomized comparison of group versus individual educational interventions for pregnant women to reduce their secondhand smoke exposure.

PubMed

Chi, Ying-Chen; Sha, Feng; Yip, Paul S F; Chen, Jiunn-Liang; Chen, Ying-Yeh

2016-10-01

Secondhand smoke (SHS) exposure is deleterious to pregnant women and their unborn children. The prevalence of SHS exposure among pregnant women is particularly high in many Asian countries where approximately half of the male population smokes. We aim to investigate the efficacy of an intervention based on an expanded Health Belief Model (HBM) incorporating self-efficacy to educate and empower pregnant women to reduce their SHS exposure. We conducted a 3-arm randomized controlled trial (N = 50 in each arm) comparing the effectiveness of group-based and individual-based interventions with a treatment-as-usual group. A questionnaire tapping into constructs of the expanded HBM was administered at baseline and 1- and 2-month follow-ups. Exhaled carbon monoxide was used to determine SHS exposure (>=6 ppm). ANOVA was used to compare HBM construct scores, self-efficacy for rejecting SHS exposure, and SHS rejection behavior among the 3 groups at baseline and the 1- and 2-month follow-ups, while logistic regression analysis was used to compare the risk of exposure to SHS at each follow-up. The group-based intervention significantly improved health beliefs, self-efficacy, and self-reported rejection behaviors. The individual-based intervention effect was limited to some health belief constructs and SHS rejection behaviors. Both group- and individual-based interventions showed significant reductions in SHS exposure 2 months after the intervention (P < 0.0001). Group-based educational interventions based on the HBM are particularly effective in training pregnant women to avoid and refuse exposure to SHS. Policy makers should consider offering group-delivered programs to educate and empower pregnant women to reduce their SHS exposure.

Efficacy of Peer Education for Adopting Preventive Behaviors against Head Lice Infestation in Female Elementary School Students: A Randomised Controlled Trial

PubMed Central

Zamani-Alavijeh, Fereshteh; Mojadam, Mehdi

2017-01-01

Background Pediculosis is a common parasitic infestation in students worldwide, including Iran. This condition is more prevalent in populous and deprived communities with poor personal hygiene. This study sought to assess the efficacy of peer education for adopting preventive behaviors against pediculosis in female elementary school students based on the Health Belief Model (HBM). Methods A total of 179 female fifth grade students were selected using multistage random sampling and were randomly allocated to control and intervention groups. A standard questionnaire was designed and administered to collect baseline information. An educational intervention was then designed based on the conducted needs assessment. The educational program consisted of three sessions, held by peers for the intervention group. The questionnaire was re-administered one month after the intervention. Independent and paired t-test, Pearson’s correlation coefficient, and regression analysis were applied as appropriate. Results The two groups had no significant differences in the scores of knowledge, HBM constructs, or behavior before the intervention. After the intervention, however, the mean scores of all parameters significantly improved in the intervention group. Conclusion Peer education based on HBM is an effective strategy to promote preventive behaviors against pediculosis in among fifth grade female elementary school students in Iran. PMID:28072852

Barriers to Self-Management Behaviors in College Students with Food Allergies

ERIC Educational Resources Information Center

Duncan, Sarah E.; Annunziato, Rachel A.

2018-01-01

Objective: This study examined barriers to engagement in self-management behaviors among food-allergic college students (1) within the frameworks of the health belief model (HBM) and common sense self-regulation model (CS-SRM) and (2) in the context of overall risky behaviors. Participants: Undergraduate college students who reported having a…

Using the Health Belief Model to Predict Bystander Behavior among College Students

ERIC Educational Resources Information Center

Blavos, Alexis A.; Glassman, Tavis; Sheu, Jiunn-Jye; Diehr, Aaron; Deakins, Bethany

2014-01-01

This investigation used the Health Belief Model (HBM) to examine perceived barriers and benefits college students hold concerning medical amnesty. Researchers employed a cross-sectional research design with 369 students completing the survey (97% response rate). A path analysis revealed that college students are more likely to seek help during an…

Managing Dog Waste: Campaign Insights from the Health Belief Model

ERIC Educational Resources Information Center

Typhina, Eli; Yan, Changmin

2014-01-01

Aiming to help municipalities develop effective education and outreach campaigns to reduce stormwater pollutants, such as pet waste, this study applied the Health Belief Model (HBM) to identify perceptions of dog waste and corresponding collection behaviors from dog owners living in a small U.S. city. Results of 455 online survey responses…

Evaluation of 6 and 10 Year-Old Child Human Body Models in Emergency Events.

PubMed

Gras, Laure-Lise; Stockman, Isabelle; Brolin, Karin

2017-01-01

Emergency events can influence a child's kinematics prior to a car-crash, and thus its interaction with the restraint system. Numerical Human Body Models (HBMs) can help understand the behaviour of children in emergency events. The kinematic responses of two child HBMs-MADYMO 6 and 10 year-old models-were evaluated and compared with child volunteers' data during emergency events-braking and steering-with a focus on the forehead and sternum displacements. The response of the 6 year-old HBM was similar to the response of the 10 year-old HBM, however both models had a different response compared with the volunteers. The forward and lateral displacements were within the range of volunteer data up to approximately 0.3 s; but then, the HBMs head and sternum moved significantly downwards, while the volunteers experienced smaller displacement and tended to come back to their initial posture. Therefore, these HBMs, originally intended for crash simulations, are not too stiff and could be able to reproduce properly emergency events thanks, for instance, to postural control.

Conceptual framework for a Danish human biomonitoring program

PubMed Central

Thomsen, Marianne; Knudsen, Lisbeth E; Vorkamp, Katrin; Frederiksen, Marie; Bach, Hanne; Bonefeld-Jorgensen, Eva Cecilie; Rastogi, Suresch; Fauser, Patrik; Krongaard, Teddy; Sorensen, Peter Borgen

2008-01-01

The aim of this paper is to present the conceptual framework for a Danish human biomonitoring (HBM) program. The EU and national science-policy interface, that is fundamental for a realization of the national and European environment and human health strategies, is discussed, including the need for a structured and integrated environmental and human health surveillance program at national level. In Denmark, the initiative to implement such activities has been taken. The proposed framework of the Danish monitoring program constitutes four scientific expert groups, i.e. i. Prioritization of the strategy for the monitoring program, ii. Collection of human samples, iii. Analysis and data management and iv. Dissemination of results produced within the program. This paper presents the overall framework for data requirements and information flow in the integrated environment and health surveillance program. The added value of an HBM program, and in this respect the objectives of national and European HBM programs supporting environmental health integrated policy-decisions and human health targeted policies, are discussed. In Denmark environmental monitoring has been prioritized by extensive surveillance systems of pollution in oceans, lakes and soil as well as ground and drinking water. Human biomonitoring has only taken place in research programs and few incidences of e.g. lead contamination. However an arctic program for HBM has been in force for decades and from the preparations of the EU-pilot project on HBM increasing political interest in a Danish program has developed. PMID:18541069

Acute lung injury after tracheal instillation of acidified soya-based or Enfalac formula or human breast milk in rabbits.

PubMed

Chin, C; Lerman, J; Endo, J

1999-03-01

The aim of this study was to compare the severity of the acute lung injury after tracheal instillation of acidified soya-based or Enfalac infant formula, or human breast milk (HBM) in anesthetized rabbits. Alveolar-arterial oxygen tension gradient (A-aDO2) and dynamic compliance were measured before (baseline) and hourly for four hours after tracheal instillation of 0.8 ml x kg(-1) soya-based or Enfalac infant formula or HBM (all acidified to pH 1.8 with hydrochloric acid) or no fluid (control) in 24 anesthetized and tracheotomized adult rabbits. The A-aDO2, the difference between alveolar and arterial oxygen tensions, was corrected for barometric pressure and carbon dioxide tension. Dynamic compliance was the ratio of the expired tidal volume to the peak inspiratory airway pressure, normalized to body weight. Baseline A-aDO2 and dynamic compliance were similar among the four groups. In the control rabbits, A-aDO2 remained unchanged throughout the four hours, whereas mean A-aDO2 increased 180 mm Hg in the soya-based group (P < 0.0025) and 350 and 275 mm Hg in the Enfalac and HBM groups respectively (P < 0.0002). The order of the A-aDO2 post-instillation was Enfalac approximately/= HBM > soya > control (P < 0.0002). Dynamic compliance decreased 10-12% in the control rabbits during the four post-instillation measurements compared with baseline (P < 0.033), decreased 20% in the soya-based group (P < 0.0002) and 40-50% in the Enfalac and HBM groups (P < 0.0002). The severity of the acute lung injury after intratracheal instillation of infant feeds in a volume of 0.8 ml x kg(-1) and at pH 1.8 in rabbits depends in part, on the type of feed: Enfalac approximately/= HBM > soya > control.

[Substance monograph on bisphenol A (BPA) - reference and human biomonitoring (HBM) values for BPA in urine. Opinion of the Human Biomonitoring Commission of the German Federal Environment Agency (UBA)].

PubMed

2012-09-01

Bisphenol A (BPA) is used for the production of polycarbonates and synthetic resins. Many of the items that contain BPA, for example polycarbonate bottles and coated cans, are commodities from which BPA can migrate into food and drinks, resulting in ubiquitous exposure of the population. Numerous animal studies and in vitro tests have shown that BPA acts as an "endocrine disruptor". Because of the still incomplete understanding of the complex and contradictory effects of BPA at doses below the NOAEL, the toxicological significance of recent findings is uncertain. The German HBM Commission takes notice that the risk assessment is currently in flux and that in the EU and other countries precautionary bans on BPA have been introduced. In the light of the extensive and growing body of literature, the Commission does not see itself in a position to resolve this controversy, nor to answer the question of the relevance of observed effects of low BPA doses on human health. The Commission has derived reference values (RV95) and TDI-based HBM I values for total BPA in urine. The RV95 values are 30 μg/l for 3-5 year olds, 15 μg/l for 6-14 year olds, and 7 μg/l for 20-29 year olds. The HBM I value for children is 1.5 mg/l and 2.5 mg/l for adults, respectively. The Commission emphasizes that the HBM values will require immediate adjustment should the current TDI of 0.05 mg/kg bw/day be changed. For the practical application of HBM, the Commission recommends an assessment based on the RV95. Confirmed exceedance of the RV95 by repeat measurements should prompt a search for the possible source(s), following the ALARA principle.

Research on ethics in two large Human Biomonitoring projects ECNIS and NewGeneris: a bottom up approach.

PubMed

Dumez, Birgit; Van Damme, Karel; Casteleyn, Ludwine

2008-06-05

Assessment of ethical aspects and authorization by ethics committees have become a major constraint for health research including human subjects. Ethical reference values often are extrapolated from clinical settings, where emphasis lies on decisional autonomy and protection of individual's privacy. The question rises if this set of values used in clinical research can be considered as relevant references for HBM research, which is at the basis of public health surveillance. Current and future research activities using human biomarkers are facing new challenges and expectancies on sensitive socio-ethical issues. Reflection is needed on the necessity to balance individual rights against public interest. In addition, many HBM research programs require international collaboration. Domestic legislation is not always easily applicable in international projects. Also, there seem to be considerable inconsistencies in ethical assessments of similar research activities between different countries and even within one country. All this is causing delay and putting the researcher in situations in which it is unclear how to act in accordance with necessary legal requirements. Therefore, analysis of ethical practices and their consequences for HBM research is needed.This analysis will be performed by a bottom-up approach, based on a methodology for comparative analysis of determinants in ethical reasoning, allowing taking into account different social, cultural, political and historical traditions, in view of safeguarding common EU values. Based on information collected in real life complexity, paradigm cases and virtual case scenarios will be developed and discussed with relevant stakeholders to openly discuss possible obstacles and to identify options for improvement in regulation. The material collected will allow developing an ethical framework which may constitute the basis for a more harmonized and consistent socio-ethical and legal approach. This will not only increase the possibilities for comparison between data generated but may also allow for more equality in the protection of the rights of European citizens and establish trustful relationships between science and society, based on firmly rooted ethical values within the EU legislative framework.These considerations outline part of the research on legal, socio-ethical and communication aspects of HBM within the scope of ECNIS (NoE) and NewGeneris (IP).

Research on ethics in two large Human Biomonitoring projects ECNIS and NewGeneris: a bottom up approach

PubMed Central

Dumez, Birgit; Van Damme, Karel; Casteleyn, Ludwine

2008-01-01

Assessment of ethical aspects and authorization by ethics committees have become a major constraint for health research including human subjects. Ethical reference values often are extrapolated from clinical settings, where emphasis lies on decisional autonomy and protection of individual's privacy. The question rises if this set of values used in clinical research can be considered as relevant references for HBM research, which is at the basis of public health surveillance. Current and future research activities using human biomarkers are facing new challenges and expectancies on sensitive socio-ethical issues. Reflection is needed on the necessity to balance individual rights against public interest. In addition, many HBM research programs require international collaboration. Domestic legislation is not always easily applicable in international projects. Also, there seem to be considerable inconsistencies in ethical assessments of similar research activities between different countries and even within one country. All this is causing delay and putting the researcher in situations in which it is unclear how to act in accordance with necessary legal requirements. Therefore, analysis of ethical practices and their consequences for HBM research is needed. This analysis will be performed by a bottom-up approach, based on a methodology for comparative analysis of determinants in ethical reasoning, allowing taking into account different social, cultural, political and historical traditions, in view of safeguarding common EU values. Based on information collected in real life complexity, paradigm cases and virtual case scenarios will be developed and discussed with relevant stakeholders to openly discuss possible obstacles and to identify options for improvement in regulation. The material collected will allow developing an ethical framework which may constitute the basis for a more harmonized and consistent socio-ethical and legal approach. This will not only increase the possibilities for comparison between data generated but may also allow for more equality in the protection of the rights of European citizens and establish trustful relationships between science and society, based on firmly rooted ethical values within the EU legislative framework. These considerations outline part of the research on legal, socio-ethical and communication aspects of HBM within the scope of ECNIS (NoE) and NewGeneris (IP). PMID:18541073

Generation of insulin-producing cells from human bone marrow-derived mesenchymal stem cells: comparison of three differentiation protocols.

PubMed

Gabr, Mahmoud M; Zakaria, Mahmoud M; Refaie, Ayman F; Khater, Sherry M; Ashamallah, Sylvia A; Ismail, Amani M; El-Badri, Nagwa; Ghoneim, Mohamed A

2014-01-01

Many protocols were utilized for directed differentiation of mesenchymal stem cells (MSCs) to form insulin-producing cells (IPCs). We compared the relative efficiency of three differentiation protocols. Human bone marrow-derived MSCs (HBM-MSCs) were obtained from three insulin-dependent type 2 diabetic patients. Differentiation into IPCs was carried out by three protocols: conophylline-based (one-step protocol), trichostatin-A-based (two-step protocol), and β -mercaptoethanol-based (three-step protocol). At the end of differentiation, cells were evaluated by immunolabeling for insulin production, expression of pancreatic endocrine genes, and release of insulin and c-peptide in response to increasing glucose concentrations. By immunolabeling, the proportion of generated IPCs was modest ( ≃ 3%) in all the three protocols. All relevant pancreatic endocrine genes, insulin, glucagon, and somatostatin, were expressed. There was a stepwise increase in insulin and c-peptide release in response to glucose challenge, but the released amounts were low when compared with those of pancreatic islets. The yield of functional IPCs following directed differentiation of HBM-MSCs was modest and was comparable among the three tested protocols. Protocols for directed differentiation of MSCs need further optimization in order to be clinically meaningful. To this end, addition of an extracellular matrix and/or a suitable template should be attempted.

Testicular Self-Examination: A Test of the Health Belief Model and the Theory of Planned Behaviour

ERIC Educational Resources Information Center

McClenahan, Carol; Shevlin, Mark; Adamson, Gary; Bennett, Cara; O'Neill, Brenda

2007-01-01

The aim of this study was to test the utility and efficiency of the theory of planned behaviour (TPB) and the health belief model (HBM) in predicting testicular self-examination (TSE) behaviour. A questionnaire was administered to an opportunistic sample of 195 undergraduates aged 18-39 years. Structural equation modelling indicated that, on the…

The Bicycle Helmet Attitudes Scale: Using the Health Belief Model to Predict Helmet Use among Undergraduates

ERIC Educational Resources Information Center

Ross, Thomas P.; Ross, Lisa Thomson; Rahman, Annalise; Cataldo, Shayla

2010-01-01

Objective: This study examined bicycle helmet attitudes and practices of college undergraduates and developed the Bicycle Helmet Attitudes Scale, which was guided by the Health Belief Model (HBM; Rosenstock, 1974, in Becker MH, ed. "The Health Belief Model and Personal Health Behavior". Thorofare, NJ: Charles B. Slack; 1974:328-335) to predict…

Health beliefs affect the correct replacement of daily disposable contact lenses: Predicting compliance with the Health Belief Model and the Theory of Planned Behaviour.

PubMed

Livi, Stefano; Zeri, Fabrizio; Baroni, Rossella

2017-02-01

To assess the compliance of Daily Disposable Contact Lenses (DDCLs) wearers with replacing lenses at a manufacturer-recommended replacement frequency. To evaluate the ability of two different Health Behavioural Theories (HBT), The Health Belief Model (HBM) and The Theory of Planned Behaviour (TPB), in predicting compliance. A multi-centre survey was conducted using a questionnaire completed anonymously by contact lens wearers during the purchase of DDCLs. Three hundred and fifty-four questionnaires were returned. The survey comprised 58.5% females and 41.5% males (mean age 34±12years). Twenty-three percent of respondents were non-compliant with manufacturer-recommended replacement frequency (re-using DDCLs at least once). The main reason for re-using DDCLs was "to save money" (35%). Predictions of compliance behaviour (past behaviour or future intentions) on the basis of the two HBT was investigated through logistic regression analysis: both TPB factors (subjective norms and perceived behavioural control) were significant (p<0.01); HBM was less predictive with only the severity (past behaviour and future intentions) and perceived benefit (only for past behaviour) as significant factors (p<0.05). Non-compliance with DDCLs replacement is widespread, affecting 1 out of 4 Italian wearers. Results from the TPB model show that the involvement of persons socially close to the wearers (subjective norms) and the improvement of the procedure of behavioural control of daily replacement (behavioural control) are of paramount importance in improving compliance. With reference to the HBM, it is important to warn DDCLs wearers of the severity of a contact-lens-related eye infection, and to underline the possibility of its prevention. Copyright © 2016 British Contact Lens Association. Published by Elsevier Ltd. All rights reserved.

Competitive testing of health behavior theories: how do benefits, barriers, subjective norm, and intention influence mammography behavior?

PubMed Central

Murphy, Caitlin C.; Vernon, Sally W.; Diamond, Pamela M.; Tiro, Jasmin A.

2013-01-01

Background Competitive hypothesis testing may explain differences in predictive power across multiple health behavior theories. Purpose We tested competing hypotheses of the Health Belief Model (HBM) and Theory of Reasoned Action (TRA) to quantify pathways linking subjective norm, benefits, barriers, intention, and mammography behavior. Methods We analyzed longitudinal surveys of women veterans randomized to the control group of a mammography intervention trial (n=704). We compared direct, partial mediation, and full mediation models with Satorra-Bentler χ2 difference testing. Results Barriers had a direct and indirect negative effect on mammography behavior; intention only partially mediated barriers. Benefits had little to no effect on behavior and intention; however, it was negatively correlated with barriers. Subjective norm directly affected behavior and indirectly affected intention through barriers. Conclusions Our results provide empiric support for different assertions of HBM and TRA. Future interventions should test whether building subjective norm and reducing negative attitudes increases regular mammography. PMID:23868613

Use of health services in Hill villages in central Nepal.

PubMed

Niraula, B B

1994-10-01

This paper reports the use and non-use of health care facilities in the Hill villages in central Nepal. The health behaviour model (HBM) is applied to test the significance of socioeconomic variables on the use of the modern health care system. The study finds that all three characteristics of the HBM model, predisposing, enabling and need, are significantly related to use and non-use of the modern health care system. The analysis shows that number of living children, respondent's education, nearness to the road and service centre, value of land, knowledge about health workers and experience of child loss are some of the variables that are positively and significantly related to the use of modern health care. Age of the respondents and household size were found to be negatively associated with health-care use. Contrary to expectation, caste is unimportant. Making use of the qualitative data, this paper argues that the health care system is unnecessarily bureaucratic and patriarchal, which favours the socio-economically well-off.

Enhanced Wnt signaling improves bone mass and strength, but not brittleness, in the Col1a1(+/mov13) mouse model of type I Osteogenesis Imperfecta.

PubMed

Jacobsen, Christina M; Schwartz, Marissa A; Roberts, Heather J; Lim, Kyung-Eun; Spevak, Lyudmila; Boskey, Adele L; Zurakowski, David; Robling, Alexander G; Warman, Matthew L

2016-09-01

Osteogenesis Imperfecta (OI) comprises a group of genetic skeletal fragility disorders. The mildest form of OI, Osteogenesis Imperfecta type I, is frequently caused by haploinsufficiency mutations in COL1A1, the gene encoding the α1(I) chain of type 1 collagen. Children with OI type I have a 95-fold higher fracture rate compared to unaffected children. Therapies for OI type I in the pediatric population are limited to anti-catabolic agents. In adults with osteoporosis, anabolic therapies that enhance Wnt signaling in bone improve bone mass, and ongoing clinical trials are determining if these therapies also reduce fracture risk. We performed a proof-of-principle experiment in mice to determine whether enhancing Wnt signaling in bone could benefit children with OI type I. We crossed a mouse model of OI type I (Col1a1(+/Mov13)) with a high bone mass (HBM) mouse (Lrp5(+/p.A214V)) that has increased bone strength from enhanced Wnt signaling. Offspring that inherited the OI and HBM alleles had higher bone mass and strength than mice that inherited the OI allele alone. However, OI+HBM and OI mice still had bones with lower ductility compared to wild-type mice. We conclude that enhancing Wnt signaling does not make OI bone normal, but does improve bone properties that could reduce fracture risk. Therefore, agents that enhance Wnt signaling are likely to benefit children and adults with OI type 1. Copyright © 2016 Elsevier Inc. All rights reserved.

First reported case of Haemoglobin-M Hyde Park in a Malay family living in Malaysia.

PubMed

Loong, Tang Yee; Chong, Doris Lau Sie; Jamal, A Rahman A; Murad, Nor Azian Abdul; Sabudin, Raja Zahratul Azma Raja; Fun, Leong Chooi

2016-01-01

Haemoglobin (Hb)-M Hyde Park, also known as Hb-M Akita is a rare type of hereditary Hb M due to autosomal dominant mutation of CAC>TAC on codon 92 of β globin gene resulting in the replacement of histidine by tyrosine on β globin chain. This variant Hb has a tendency to form methaemoglobin (metHb). The iron ion in metHb is oxidized to ferric (Fe3+) which is unable to carry oxygen and the patients manifest as cyanosis clinically. A 9-year-old Malay girl was incidentally found to be cyanotic when she presented to a health clinic. Laboratory investigations revealed raised methaemoglobin levels and Hb analysis findings were consistent with Hb-M Hyde Park. β gene sequencing confirmed a point mutation of CAC>TAC on codon 92 in one of the β genes. The family study done on the individuals with cyanosis showed similar findings. A diagnosis of heterozygous Hb-M Hyde Park was made. Patients with this variant Hb usually presented with cyanosis with mild haemolysis and maybe misdiagnosed as congenital heart disease. No further treatment is needed as patients are relatively asymptomatic. Although the disease is harmless in the heterozygous carriers but the offspring of the carriers may suffer severe haemolytic anaemia when the offspring also inherit other β haemoglobinopathies/thalassemia. This can happen due to high prevalence of β thalassemia carrier (3.5-4 %) found in Malaysia. At the time of writing, this is the first case of hereditary Hb-M Hyde Park diagnosed in a Malay family living in Malaysia.

Evaluation of 6 and 10 Year-Old Child Human Body Models in Emergency Events

PubMed Central

2017-01-01

Emergency events can influence a child’s kinematics prior to a car-crash, and thus its interaction with the restraint system. Numerical Human Body Models (HBMs) can help understand the behaviour of children in emergency events. The kinematic responses of two child HBMs–MADYMO 6 and 10 year-old models–were evaluated and compared with child volunteers’ data during emergency events–braking and steering–with a focus on the forehead and sternum displacements. The response of the 6 year-old HBM was similar to the response of the 10 year-old HBM, however both models had a different response compared with the volunteers. The forward and lateral displacements were within the range of volunteer data up to approximately 0.3 s; but then, the HBMs head and sternum moved significantly downwards, while the volunteers experienced smaller displacement and tended to come back to their initial posture. Therefore, these HBMs, originally intended for crash simulations, are not too stiff and could be able to reproduce properly emergency events thanks, for instance, to postural control. PMID:28099505

Storm drains are sources of human fecal pollution during dry weather in three urban southern California watersheds.

PubMed

Sercu, Bram; Van De Werfhorst, Laurie C; Murray, Jill; Holden, Patricia A

2009-01-15

Coastal urbanized areas in Southern California experience frequent beach water quality warnings in summer due to high concentrations of fecal indicator bacteria (FIB). Remediation can be difficult, as sources are often unknown. During two summers, we sampled three urbanized watersheds in Santa Barbara, CA at sites with historically high FIB concentrations to determine if human fecal matter was influencing water quality. By quantification of a human-specific Bacteroides marker (HBM), human waste was evidenced throughout both transects, and concentrations were highest in the discharges of several flowing storm drains. The HBM concentrations in storm drain discharges varied by up to 5 orders of magnitude on the same day. While the exact points of entry into the storm drain systems were not definitively determined, further inspection of the drain infrastructure suggested exfiltrating sanitary sewers as possible sources. The HBM and FIB concentrations were not consistently correlated, although the exclusive occurrence of high HBM concentrations with high FIB concentrations warrants the use of FIB analyses for a first tier of sampling. The association of human fecal pollution with dry weather drainage could be a window into a larger problem for other urbanized coastal areas with Mediterranean-type climates.

Efficacy of topical application of human breast milk on atopic eczema healing among infants: a randomized clinical trial.

PubMed

Kasrae, Hengameh; Amiri Farahani, Leila; Yousefi, Parsa

2015-08-01

Infant atopic eczema is an inflammatory lesion usually involving the epidermis of the skin. About 50% of infants are affected by this lesion in the first years of their lives. Studies show human breast milk (HBM) as a preventive measure and effective treatment of some sores and infections. This article evaluates the short-term efficacy of HBM versus hydrocortisone 1% ointment in infants with mild to moderate atopic dermatitis (AD). We conducted a randomized clinical trial among infants with diagnosed AD within a pediatrics unit. The majority of AD cases in both groups were considered moderate severity. There were no significant differences between these two groups at days 0, 7, 14, and 21, and the interventions of both groups were found to have the same effects. The external validity and consequently the ability to generalize the findings may be diminished as this study was conducted in a single site. Owing to HBM and the hydrocortisone 1% ointment providing the same results in the healing of AD, HBM was used because of low cost and accessibility. © 2015 The International Society of Dermatology.

Use of hand-held computers to determine the relative contribution of different cognitive, attitudinal, social, and organizational factors on health care workers' decision to decontaminate hands.

PubMed

Lee, Karen; Burnett, Emma; Morrison, Kenny; Ricketts, Ian

2014-02-01

Observational and survey methods have limitations in measuring hand hygiene behavior. The ability of a personal digital assistant to anonymously gather data at the point of decision making could potentially address these. Participants were provided with a personal digital assistant to be used for three 2-hour periods and asked to rate influential factors of the Health Belief Model (HBM). Participants were also required to enter what they thought they should do and what they actually did. A total of 741 hand hygiene opportunities was recorded. All HBM constructs were higher for hand hygiene opportunities where there was compliance versus noncompliance, with a significant difference for patient pressure, my risk, perceived benefits, perceived seriousness, and availability of good facilities. Only 20% of doctors, 28% of nurses, and 66% of physiotherapists always did what they thought they should. There was no correlation between self-reported and actual compliance. The HBM appeared to be a useful theoretical framework. Surprisingly, participants rated their compliance as high despite having recorded instances where they did not do what they thought they should do. This suggests that staff may have a different definition of compliance than strict observation of the guidelines. Copyright © 2014 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Mosby, Inc. All rights reserved.

Factors influencing seasonal influenza vaccination behaviour among elderly people: a systematic review.

PubMed

Kan, T; Zhang, J

2018-03-01

To explore the behaviour-related factors influencing influenza vaccination among elderly people using a framework derived from the Health Belief Model (HBM) and the Theory of Reasoned Action (TRA). Systematic review. Five databases were searched using predetermined strategies in March 2016, and 1927 citations were identified. Articles were selected according to inclusion and exclusion criteria. Key information was extracted from selected studies using a predesigned sheet. Both authors assessed study quality using the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) or Critical Appraisal Skills Programme (CASP) checklist. Thirty-six articles were selected. A new framework was proposed that contributes to shared understanding of factors influencing health behaviour. Possible determinants of influenza vaccination among elderly people were knowledge, health promotion factors, all constructs of the HBM, and some concepts of the TRA. Key factors were threat perception, behavioural beliefs, subjective norms, recommendations, past behaviour and perceived barriers. This is the first systematic review to analyse the factors influencing influenza vaccination behaviour of elderly people using a framework integrating the HBM and the TRA. The framework identified key factors of influenza vaccination and presented the inter-relation of behaviour-related variables. However, further well-designed studies are required to explore the inter-relationships accurately and comprehensively. Copyright © 2017 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

A psychosocial approach to dentistry for the underserved: incorporating theory into practice.

PubMed

Flaer, Paul J; Younis, Mustafa Z; Benjamin, Paul L; Al Hajeri, Maha

2010-01-01

Dentistry for the underserved is more than an egalitarian social issue--it is a key factor in the health and social progress of our nation. The first signs or manifestations of several diseases such as varicella (i.e., chicken pox and shingles), STDs, and influenza become apparent in the oral cavity. The value of access to quality dentistry is an immeasurable factor in maintaining general medical health of people and fulfilling their psychosocial needs of pain reduction and enhanced cosmetics. In the United States, for the most part, only the middle and upper classes receive non-extraction, restorative, and prosthetic dentistry that is economically within their ability to pay. In addition, uninsured and poverty-level individuals often must face overwhelming long waiting lists, unnecessary referrals, lack of choice, and bureaucratic hurdles when seeking primary dental care. Therefore, it seems pertinent to put forth the question: What are the critical values and beliefs of psychosocial theory that can underscore the practice of dentistry for underserved populations in the United States? The widely employed public health theory, the health belief model (HBM), is applied to evaluate psychosocial factors in dental care for the underserved. The HBM is used to predict and explain behavioral changes in dental health and associated belief patterns. The HBM as applied to dentistry for the underserved predicts self-perceptions of susceptibility and seriousness of dental disease, health status, cues to action, and self-efficacy. Furthermore, patients can make judgments about benefits, costs, and risks of dental treatment. A theoretical approach to dentistry employing the HBM, mediated by values and culture, can provide significant insights into patient thinking, beliefs, and perceptions. These insights can mediate access to and use of primary care dental services by underserved populations. Evidence-based practice (i.e., based on research using the scientific method) has been put forth as the future of modern dentistry. However, the practice of dentistry need not just be evidence-based, but have its roots clearly grounded in theory.

Integrating health belief model and technology acceptance model: an investigation of health-related internet use.

PubMed

Ahadzadeh, Ashraf Sadat; Pahlevan Sharif, Saeed; Ong, Fon Sim; Khong, Kok Wei

2015-02-19

Today, people use the Internet to satisfy health-related information and communication needs. In Malaysia, Internet use for health management has become increasingly significant due to the increase in the incidence of chronic diseases, in particular among urban women and their desire to stay healthy. Past studies adopted the Technology Acceptance Model (TAM) and Health Belief Model (HBM) independently to explain Internet use for health-related purposes. Although both the TAM and HBM have their own merits, independently they lack the ability to explain the cognition and the related mechanism in which individuals use the Internet for health purposes. This study aimed to examine the influence of perceived health risk and health consciousness on health-related Internet use based on the HBM. Drawing on the TAM, it also tested the mediating effects of perceived usefulness of the Internet for health information and attitude toward Internet use for health purposes for the relationship between health-related factors, namely perceived health risk and health consciousness on health-related Internet use. Data obtained for the current study were collected using purposive sampling; the sample consisted of women in Malaysia who had Internet access. The partial least squares structural equation modeling method was used to test the research hypotheses developed. Perceived health risk (β=.135, t1999=2.676) and health consciousness (β=.447, t1999=9.168) had a positive influence on health-related Internet use. Moreover, perceived usefulness of the Internet and attitude toward Internet use for health-related purposes partially mediated the influence of health consciousness on health-related Internet use (β=.025, t1999=3.234), whereas the effect of perceived health risk on health-related Internet use was fully mediated by perceived usefulness of the Internet and attitude (β=.029, t1999=3.609). These results suggest the central role of perceived usefulness of the Internet and attitude toward Internet use for health purposes for women who were health conscious and who perceived their health to be at risk. The integrated model proposed and tested in this study shows that the HBM, when combined with the TAM, is able to predict Internet use for health purposes. For women who subjectively evaluate their health as vulnerable to diseases and are concerned about their health, cognition beliefs in and positive affective feelings about the Internet come into play in determining the use of health-related Internet use. Furthermore, this study shows that engaging in health-related Internet use is a proactive behavior rather than a reactive behavior, suggesting that TAM dimensions have a significant mediating role in Internet health management.

Integrating Health Belief Model and Technology Acceptance Model: An Investigation of Health-Related Internet Use

PubMed Central

2015-01-01

Background Today, people use the Internet to satisfy health-related information and communication needs. In Malaysia, Internet use for health management has become increasingly significant due to the increase in the incidence of chronic diseases, in particular among urban women and their desire to stay healthy. Past studies adopted the Technology Acceptance Model (TAM) and Health Belief Model (HBM) independently to explain Internet use for health-related purposes. Although both the TAM and HBM have their own merits, independently they lack the ability to explain the cognition and the related mechanism in which individuals use the Internet for health purposes. Objective This study aimed to examine the influence of perceived health risk and health consciousness on health-related Internet use based on the HBM. Drawing on the TAM, it also tested the mediating effects of perceived usefulness of the Internet for health information and attitude toward Internet use for health purposes for the relationship between health-related factors, namely perceived health risk and health consciousness on health-related Internet use. Methods Data obtained for the current study were collected using purposive sampling; the sample consisted of women in Malaysia who had Internet access. The partial least squares structural equation modeling method was used to test the research hypotheses developed. Results Perceived health risk (β=.135, t 1999=2.676) and health consciousness (β=.447, t 1999=9.168) had a positive influence on health-related Internet use. Moreover, perceived usefulness of the Internet and attitude toward Internet use for health-related purposes partially mediated the influence of health consciousness on health-related Internet use (β=.025, t 1999=3.234), whereas the effect of perceived health risk on health-related Internet use was fully mediated by perceived usefulness of the Internet and attitude (β=.029, t 1999=3.609). These results suggest the central role of perceived usefulness of the Internet and attitude toward Internet use for health purposes for women who were health conscious and who perceived their health to be at risk. Conclusions The integrated model proposed and tested in this study shows that the HBM, when combined with the TAM, is able to predict Internet use for health purposes. For women who subjectively evaluate their health as vulnerable to diseases and are concerned about their health, cognition beliefs in and positive affective feelings about the Internet come into play in determining the use of health-related Internet use. Furthermore, this study shows that engaging in health-related Internet use is a proactive behavior rather than a reactive behavior, suggesting that TAM dimensions have a significant mediating role in Internet health management. PMID:25700481

The French human biomonitoring program: First lessons from the perinatal component and future needs.

PubMed

Dereumeaux, Clémentine; Fillol, Clémence; Charles, Marie-Aline; Denys, Sébastien

2017-03-01

This paper presents a progress report of the French human biomonitoring (HBM) program established in 2010. This program has been designed to provide a national representative estimation of the French population's exposure to various environmental chemicals and to study the determinants of exposure. This program currently consists in two surveys: a perinatal component related to a selection of 4145 pregnant women who have been enrolled in the Elfe cohort (the French Longitudinal Study since Childhood) in 2011, and a general population survey related to adults aged 18-74 years and children as from 6 years (Esteban). The aim of this manuscript is to present highlights of the French human biomonitoring program with particular focus on the prioritization of biomarkers to be analyzed in the program and the selection of biomarkers applied to both program components. The Delphi method was used to establish a consensual list of prioritized biomarkers in 2011. First results of the perinatal component of the French HBM program have shown that the biomarkers prioritized were relevant, as almost all pregnant women were exposed to them. However, for some biomarkers, levels' decreases have been observed which may partly be explained by measures taken to prohibit some of these chemicals (e.g. atrazine) and by industrial processes evolutions leading to the substitution of others (e.g. bisphenol A, di-2-ethylhexyl phthalate/DEHP, dialkyl phosphates). Therefore, the list of biomarkers to be monitored in the French HBM program has been implemented to include some substitutes of biomarkers prioritized in the first instance (e.g. bisphenol S, F). Finally, this method combines rigor and flexibility and helped us to build a prioritized list that will be shared and supported by many if not all actors. Copyright © 2016 Elsevier GmbH. All rights reserved.

Integration of Five Health Behaviour Models: Common Strengths and Unique Contributions to Understanding Condom Use

PubMed Central

Reid, Allecia E.; Aiken, Leona S.

2011-01-01

The purpose of this research was to select from the health belief model (HBM), theories of reasoned action (TRA) and planned behaviour (TPB), information-motivation-behavioural skills model (IMB), and social cognitive theory (SCT) the strongest longitudinal predictors of women’s condom use and to combine these constructs into a single integrated model of condom use. The integrated model was evaluated for prediction of condom use among young women who had steady versus casual partners. At Time 1, all constructs of the five models and condom use were assessed in an initial and a replication sample (n= 193, n= 161). Condom use reassessed 8 weeks later (Time 2) served as the main outcome. Information from IMB, perceived susceptibility, benefits, and barriers from HBM, self-efficacy and self-evaluative expectancies from SCT, and partner norm and attitudes from TPB served as indirect or direct predictors of condom use. All paths replicated across samples. Direct predictors of behaviour varied with relationship status: self-efficacy significantly predicted condom use for women with casual partners, while attitude and partner norm predicted for those with steady partners. Integrated psychosocial models, rich in constructs and relationships drawn from multiple theories of behaviour, may provide a more complete characterization of health protective behaviour. PMID:21678166

Neonatal High Bone Mass With First Mutation of the NF-κB Complex: Heterozygous De Novo Missense (p.Asp512Ser) RELA (Rela/p65).

PubMed

Frederiksen, Anja L; Larsen, Martin J; Brusgaard, Klaus; Novack, Deborah V; Knudsen, Peter Juel Thiis; Schrøder, Henrik Daa; Qiu, Weimin; Eckhardt, Christina; McAlister, William H; Kassem, Moustapha; Mumm, Steven; Frost, Morten; Whyte, Michael P

2016-01-01

Heritable disorders that feature high bone mass (HBM) are rare. The etiology is typically a mutation(s) within a gene that regulates the differentiation and function of osteoblasts (OBs) or osteoclasts (OCs). Nevertheless, the molecular basis is unknown for approximately one-fifth of such entities. NF-κB signaling is a key regulator of bone remodeling and acts by enhancing OC survival while impairing OB maturation and function. The NF-κB transcription complex comprises five subunits. In mice, deletion of the p50 and p52 subunits together causes osteopetrosis (OPT). In humans, however, mutations within the genes that encode the NF-κB complex, including the Rela/p65 subunit, have not been reported. We describe a neonate who died suddenly and unexpectedly and was found at postmortem to have HBM documented radiographically and by skeletal histopathology. Serum was not available for study. Radiographic changes resembled malignant OPT, but histopathological investigation showed morphologically normal OCs and evidence of intact bone resorption excluding OPT. Furthermore, mutation analysis was negative for eight genes associated with OPT or HBM. Instead, accelerated bone formation appeared to account for the HBM. Subsequently, trio-based whole exome sequencing revealed a heterozygous de novo missense mutation (c.1534_1535delinsAG, p.Asp512Ser) in exon 11 of RELA encoding Rela/p65. The mutation was then verified using bidirectional Sanger sequencing. Lipopolysaccharide stimulation of patient fibroblasts elicited impaired NF-κB responses compared with healthy control fibroblasts. Five unrelated patients with unexplained HBM did not show a RELA defect. Ours is apparently the first report of a mutation within the NF-κB complex in humans. The missense change is associated with neonatal osteosclerosis from in utero increased OB function rather than failed OC action. These findings demonstrate the importance of the Rela/p65 subunit within the NF-κB pathway for human skeletal homeostasis and represent a new genetic cause of HBM. © 2015 American Society for Bone and Mineral Research.

Predicting intention to attend and actual attendance at a universal parent-training programme: a comparison of social cognition models.

PubMed

Thornton, Sarah; Calam, Rachel

2011-07-01

The predictive validity of the Health Belief Model (HBM) and the Theory of Planned Behaviour (TPB) were examined in relation to 'intention to attend' and 'actual attendance' at a universal parent-training intervention for parents of children with behavioural difficulties. A validation and reliability study was conducted to develop two questionnaires (N = 108 parents of children aged 4-7).These questionnaires were then used to investigate the predictive validity of the two models in relation to 'intention to attend' and 'actual attendance' at a parent-training intervention ( N = 53 parents of children aged 4-7). Both models significantly predicted 'intention to attend a parent-training group'; however, the TPB accounted for more variance in the outcome variable compared to the HBM. Preliminary investigations highlighted that attendees were more likely to intend to attend the groups, have positive attitudes towards the groups, perceive important others as having positive attitudes towards the groups, and report elevated child problem behaviour scores. These findings provide useful information regarding the belief-based factors that affect attendance at universal parent-training groups. Possible interventions aimed at increasing 'intention to attend' and 'actual attendance' at parent-training groups are discussed.

A Framework for Engaging Parents in Prevention

ERIC Educational Resources Information Center

Randolph, Karen A.; Fincham, Frank; Radey, Melissa

2009-01-01

The literature on engaging families in prevention programs is informed by the Health Beliefs Model (HBM), Theory of Reasoned Action (TRA), and Family Systems theory. Although useful, these frameworks have not facilitated the development of prevention-based practice strategies that recognize different levels of prevention (i.e., universal,…

Application of the health belief model in promotion of self-care in heart failure patients.

PubMed

Baghianimoghadam, Mohammad Hosein; Shogafard, Golamreza; Sanati, Hamid Reza; Baghianimoghadam, Behnam; Mazloomy, Seyed Saeed; Askarshahi, Mohsen

2013-01-01

Heart failure (HF) is a condition due to a problem with the structure or function of the heart impairs its ability to supply sufficient blood flow to meet the body's needs. In developing countries, around 2% of adults suffer from heart failure, but in people over the age of 65, this rate increases to 6-10%. In Iran, around 3.3% of adults suffer from heart failure. The Health Belief Model (HBM) is one of the most widely used models in public health theoretical framework. This was a cohort experimental study, in which education as intervention factor was presented to case group. 180 Heart failure patients were randomly selected from patients who were referred to the Shahid Rajaee center of Heart Research in Tehran and allocated to two groups (90 patients in the case group and 90 in the control group). HBM was used to compare health behaviors. The questionnaire included 69 questions. All data were collected before and 2 months after intervention. About 38% of participants don't know what, the heart failure is and 43% don't know that using the salt is not suitable for them. More than 40% of participants didn't weigh any time their selves. There was significant differences between the mean grades score of variables (perceived susceptibility, perceived threat, knowledge, Perceived benefits, Perceived severity, self-efficacy Perceived barriers, cues to action, self- behavior) in the case and control groups after intervention that was not significant before it. Based on our study and also many other studies, HBM has the potential to be used as a tool to establish educational programs for individuals and communities. Therefore, this model can be used effectively to prevent different diseases and their complications including heart failure. © 2013 Tehran University of Medical Sciences. All rights reserved.

Can new passenger cars reduce pedestrian lower extremity injury? A review of geometrical changes of front-end design before and after regulatory efforts.

PubMed

Nie, Bingbing; Zhou, Qing

2016-10-02

Pedestrian lower extremity represents the most frequently injured body region in car-to-pedestrian accidents. The European Directive concerning pedestrian safety was established in 2003 for evaluating pedestrian protection performance of car models. However, design changes have not been quantified since then. The goal of this study was to investigate front-end profiles of representative passenger car models and the potential influence on pedestrian lower extremity injury risk. The front-end styling of sedans and sport utility vehicles (SUV) released from 2008 to 2011 was characterized by the geometrical parameters related to pedestrian safety and compared to representative car models before 2003. The influence of geometrical design change on the resultant risk of injury to pedestrian lower extremity-that is, knee ligament rupture and long bone fracture-was estimated by a previously developed assessment tool assuming identical structural stiffness. Based on response surface generated from simulation results of a human body model (HBM), the tool provided kinematic and kinetic responses of pedestrian lower extremity resulted from a given car's front-end design. Newer passenger cars exhibited a "flatter" front-end design. The median value of the sedan models provided 87.5 mm less bottom depth, and the SUV models exhibited 94.7 mm less bottom depth. In the lateral impact configuration similar to that in the regulatory test methods, these geometrical changes tend to reduce the injury risk of human knee ligament rupture by 36.6 and 39.6% based on computational approximation. The geometrical changes did not significantly influence the long bone fracture risk. The present study reviewed the geometrical changes in car front-ends along with regulatory concerns regarding pedestrian safety. A preliminary quantitative benefit of the lower extremity injury reduction was estimated based on these geometrical features. Further investigation is recommended on the structural changes and inclusion of more accident scenarios.

Novel method for metalloproteins determination in human breast milk by size exclusion chromatography coupled to inductively coupled plasma mass spectrometry.

PubMed

Acosta, Mariano; Torres, Sabier; Mariño-Repizo, Leonardo; Martinez, Luis D; Gil, Raúl A

2018-06-02

Levels of essential metals in human breast milk (HBM) have been determined by different analytical techniques, but there is few woks about human whey milk fractions. However, the current trend lies in metalloproteomic and identification of different metalloproteins. In this sense, native separative techniques (N-PAGE and SEC) coupled to ICP-MS provide us with valuable information. Besides it is necessary the development of new methodologies in order to determine with accuracy and precision the profile of such metals and metalloproteins in the different whey protein fractions of HBM. Thus, the aim of this work was to develop a new method for metals and metalloproteins determination by SEC-ICP-MS in whey protein fractions of HBM. Human whey fractions were obtained of HBM samples by ultracentrifugation. Then, protein fractions of whey milk were separated by SEC coupled to ICP-MS for metalloproteins and Mn, Co, Cu and Se quantification. Besides, protein profile of whey milk was determined by N-PAGE and computer assisted image analysis. SEC-ICP-MS results indicated that first and second protein fractions showed detectable levels of the Mn, Co, Cu, and Se. Protein profile determined by N-PAGE and image analysis showed that molecular weight of protein fractions ranged between 68,878-1,228.277 Da. In this work, metalloproteins were analyzed by SEC coupled to ICP-MS, with adequate sensitivity and accuracy. Our study has shown the presence of Mn, Co, Cu and Se bound to two protein fractions in whey milk of HBM. Metals levels analyzed were within the ranges reported in the literature. Copyright © 2018 Elsevier B.V. All rights reserved.

Predictors of Medication Adherence in an AIDS Clinical Trial: Patient and Clinician Perceptions

ERIC Educational Resources Information Center

Cox, Lisa E.

2009-01-01

This article presents data from an AIDS clinical trial that evaluated 238 (60 percent nonwhite) patients infected with HIV and their clinician's perceptions of medication adherence and visit attendance in relationship to lifestyle, psychosocial, and health belief model (HBM) variables. Twelve sites collected data via a prospective, multisite…

How can the health belief model and self-determination theory predict both influenza vaccination and vaccination intention ? A longitudinal study among university students.

PubMed

Fall, Estelle; Izaute, Marie; Chakroun-Baggioni, Nadia

2018-06-01

Background and objective Seasonal influenza is frequent among students and often responsible for impaired academic performance and lower levels of general health. However, the vaccination rate in this population is very low. As the seasonal influenza vaccine is not compulsory in France, it is important to improve the vaccination uptake by identifying predictors of both intention and behaviour. This study investigated the effect of decisional balance, motivation and self-efficacy on vaccination acceptance using the Extended Health Belief Model (HBM) and Self-Determination Theory (SDT). Design and Main Outcome Measures University students were invited to fill in an online survey to answer questions about their influenza vaccination intention, and HBM and SDT constructs. A one-year longitudinal follow-up study investigated vaccination behaviour. Results Autonomous motivation and self-efficacy significantly influenced the intention to have the influenza vaccine, and vaccine behaviour at one-year follow-up. Intention predicted a significant proportion of variation (51%) in behaviour, and mediated the effect of these predictors on vaccination behaviour. Conclusion These results suggest that motivation concepts of the Self-Determination Theory can be adequately combined with the Health Belief Model to understand vaccination behaviour.

Correlates of Cigarette Smoking among Male Chinese College Students in China--A Preliminary Study

ERIC Educational Resources Information Center

Li, Kaigang; Kay, Noy S.

2009-01-01

The main purpose of this preliminary study was to examine the association between four constructs of the Health Belief Model (HBM) (i.e. perceived severity of smoking-related health problems, perceived susceptibility to smoking-health related problems, perceived barriers to non-smoking and perceived benefits of non-smoking) and cigarette smoking …

Participation in Prevention Programs for Dating Violence: Beliefs about Relationship Violence and Intention to Participate

ERIC Educational Resources Information Center

Cornelius, Tara L.; Sullivan, Kieran T.; Wyngarden, Nicole; Milliken, Jennifer C.

2009-01-01

This study utilizes the Health Belief Model (HBM) to examine the factors related to the intention to participate in prevention programming for dating violence. Perceptions of susceptibility to future violence and the benefits of prevention programming appear to be the strongest predictors of participation in prevention programs. Perceptions of the…

An overview of human biomonitoring of environmental chemicals in the Canadian Health Measures Survey: 2007-2019.

PubMed

Haines, Douglas A; Saravanabhavan, Gurusankar; Werry, Kate; Khoury, Cheryl

2017-03-01

Human biomonitoring (HBM) is used to indicate and quantify exposure by measuring environmental chemicals, their metabolites or reaction products in biological specimens. The biomonitoring component of the Canadian Health Measures Survey (CHMS) is the most comprehensive initiative providing general population HBM data in Canada. The CHMS is an ongoing cross-sectional direct measures survey implemented in 2-year cycles. It provides nationally-representative data on health, nutritional status, environmental exposures, and related risks and protective characteristics. The survey follows a robust planning, design and sampling protocol as well as a comprehensive quality assurance and quality control regime implemented for all aspect of the survey to ensure the validity of the HBM results. HBM blood and urine data are available for CHMS cycles 1 (2007-2009), 2 (2009-2011) and 3 (2012-2013). Field collection has been completed for cycle 4 (2014-2015), with cycle 5 (2016-2017) in progress and cycle 6 planning (2018-2019) being finalized. Biomonitoring results for 279 chemicals are expected over the six cycles of the CHMS (220 in individual blood, urine or hair samples, and 59 in pooled serum samples). The chemicals include metals and trace elements, polychlorinated biphenyls (PCBs), organochlorines, flame retardants, perfluoroalkyl substances, volatile organic compounds (VOCs) and metabolites, environmental phenols, triclocarban, acrylamide, pesticides (e.g., triazines, carbamates, organophosphates, phenoxy, pyrethroids) and/or their metabolites, chlorophenols, polycyclic aromatic hydrocarbon (PAH) metabolites, phthalates and alternate plasticizer metabolites, and tobacco biomarkers. Approximately one half of the chemicals measured in individual blood and urine samples over the first three cycles were detected in more than 60% of samples. CHMS biomonitoring data have been used to establish baseline HBM concentrations in Canadians; inform public health, regulatory risk assessment and management decisions; and fulfil national and international reporting requirements. Concurrent efforts are underway in Canada to develop statistically- and risk-based concepts and tools to interpret biomonitoring data. Crown Copyright © 2016. Published by Elsevier GmbH. All rights reserved.

The influence of spirituality and religiosity on breast cancer screening delay in African American women: application of the Theory of Reasoned Action and Planned Behavior (TRA/TPB).

PubMed

Gullate, Mary

2006-01-01

African American women (AAW) are 25% more likely to present with late stage breast cancer and 20% more likely to die from their disease than Caucasian women. Researchers report that a treatment delay of 3 months is a significant factor in breast cancer mortality. Socioeconomic factors, lack of access and knowledge, spiritual and religious beliefs, fear and fatalism are reported as contributing factors to screening delays. Studies have primarily applied the Health Belief Model (HBM) and modified versions like the Champion HBM to preventive health practices. Neither have significant inclusion of spirituality or religiosity. The TRA/TPB focus on beliefs, intent and attitude as individual determinants of the likelihood of performing a specific behavior; but have not had wide utility in studies related to screening delays among AAW. This paper explores the utility of applying the TRA/TPB as the theoretical framework for determining cultural relevance of spirituality and religiosity to screening delays among AAW.

Contribution to harmonic balance calculations of self-sustained periodic oscillations with focus on single-reed instruments.

PubMed

Farner, Snorre; Vergez, Christophe; Kergomard, Jean; Lizée, Aude

2006-03-01

The harmonic balance method (HBM) was originally developed for finding periodic solutions of electronical and mechanical systems under a periodic force, but has been adapted to self-sustained musical instruments. Unlike time-domain methods, this frequency-domain method does not capture transients and so is not adapted for sound synthesis. However, its independence of time makes it very useful for studying any periodic solution, whether stable or unstable, without care of particular initial conditions in time. A computer program for solving general problems involving nonlinearly coupled exciter and resonator, HARMBAL, has been developed based on the HBM. The method as well as convergence improvements and continuation facilities are thoroughly presented and discussed in the present paper. Applications of the method are demonstrated, especially on problems with severe difficulties of convergence: the Helmholtz motion (square signals) of single-reed instruments when no losses are taken into account, the reed being modeled as a simple spring.

Enhancing health knowledge, health beliefs, and health behavior in Poland through a health promoting television program series.

PubMed

Chew, Fiona; Palmer, Sushma; Slonska, Zofia; Subbiah, Kalyani

2002-01-01

This study examined the impact of a health promoting television program series on health knowledge and the key factors of the health belief model (HBM) that have led people to engage in healthy behavior (exercising, losing weight, changing eating habits, and not smoking/quitting smoking). Using data from a posttest comparison field study with 15) viewers and 146 nonviewers in Poland, we found that hierarchical regression analysis showed stronger support for the HBM factors of efficacy, susceptibility, seriousness, and salience in their contribution toward health behavior among television viewers compared with nonviewers. Cues to action variables (including television viewing) and health knowledge boosted efficacy among viewers. Without the advantage of receiving health information from the television series, nonviewers relied on their basic disease fears on one hand, and interest in good health on the other to take steps toward becoming healthier. A health promoting television series can increase health knowledge and enhance health beliefs, which in turn contribute to healthy behaviors.

Analytical approximations for the oscillators with anti-symmetric quadratic nonlinearity

NASA Astrophysics Data System (ADS)

Alal Hosen, Md.; Chowdhury, M. S. H.; Yeakub Ali, Mohammad; Faris Ismail, Ahmad

2017-12-01

A second-order ordinary differential equation involving anti-symmetric quadratic nonlinearity changes sign. The behaviour of the oscillators with an anti-symmetric quadratic nonlinearity is assumed to oscillate different in the positive and negative directions. In this reason, Harmonic Balance Method (HBM) cannot be directly applied. The main purpose of the present paper is to propose an analytical approximation technique based on the HBM for obtaining approximate angular frequencies and the corresponding periodic solutions of the oscillators with anti-symmetric quadratic nonlinearity. After applying HBM, a set of complicated nonlinear algebraic equations is found. Analytical approach is not always fruitful for solving such kinds of nonlinear algebraic equations. In this article, two small parameters are found, for which the power series solution produces desired results. Moreover, the amplitude-frequency relationship has also been determined in a novel analytical way. The presented technique gives excellent results as compared with the corresponding numerical results and is better than the existing ones.

Health belief model perceptions, knowledge of heart disease, and its risk factors in educated African-American women: an exploration of the relationships of socioeconomic status and age.

PubMed

Jones, Deborah E; Weaver, Michael T; Grimley, Diane; Appel, Susan J; Ard, Jamy

2006-12-01

Heart disease is the leading cause of death for African-American women in the United States. Although African-American women experience higher rates of heart disease with earlier onset and more severe consequences than White women do, they are not aware of their risk for the disease. The Health Belief Model (HBM) has been commonly used to guide preventive interventions in cardiovascular health. However, the HBM has not been evaluated for African-American women regarding its effectiveness. This study explored the perceptions of susceptibility and seriousness of heart disease, and the relationships between socioeconomic status (SES), age, and knowledge of heart disease and its risk factors among 194 educated African-American women from the southern United States. Participants did not perceive themselves to be at high risk for developing heart disease while perceiving heart disease as serious. African-American women who were older perceived heart disease to be more serious than their younger counterparts did. Older women and those with higher SES knew more about heart disease and risk factors. Neither SES nor age moderated the relationship between knowledge and perceived susceptibility or seriousness.

Comparacion de Modelos de Educacion Sexual en El Conocimiento y Cambio de Actitudes en Practicas Sexuales por Alumnos de Nivel Superior en La Region De Caguas, Puerto Rico

ERIC Educational Resources Information Center

Juan, Vallejo Ramos L.

2012-01-01

In opposition to the Sexual Education Traditional Model (SETM) that is used in the state schools of Puerto Rico, the Health Beliefs Model (HBM) appears. It facilitates a curricular design that improves the ability of the students to respond to the group pressure by means of attitudes that stimulate sexual conducts of smaller risk of propagation of…

Applying the Health Belief Model and an Integrated Behavioral Model to Promote Breast Tissue Donation Among Asian Americans.

PubMed

Shafer, Autumn; Kaufhold, Kelly; Luo, Yunjuan

2018-07-01

An important part in the effort to prevent, treat, and cure breast cancer is research done with healthy breast tissue. The Susan G. Komen for the Cure Tissue Bank at Indiana University Simon Cancer Center (KTB) encourages women to donate a small amount of healthy breast tissue and then provides that tissue to researchers studying breast cancer. Although KTB has a large donor base, the volume of tissue samples from Asian women is low despite prior marketing efforts to encourage donation among this population. This study builds on prior work promoting breast cancer screenings among Asian women by applying constructs from the Health Belief Model (HBM) and the Integrated Behavioral Model (IBM) to investigate why Asian-American women are less inclined to donate their healthy breast tissue than non-Asian women and how this population may be motivated to donate in the future. A national online survey (N = 1,317) found Asian women had significantly lower perceived severity, some lower perceived benefits, and higher perceived barriers to tissue donation than non-Asian women under HBM and significantly lower injunctive norms supporting breast tissue donation, lower perceived behavioral control, and lower intentions to donate under IBM. This study also compares and discusses similarities and differences among East, Southeast, and South Asian women on these same constructs.

Robust human body model injury prediction in simulated side impact crashes.

PubMed

Golman, Adam J; Danelson, Kerry A; Stitzel, Joel D

2016-01-01

This study developed a parametric methodology to robustly predict occupant injuries sustained in real-world crashes using a finite element (FE) human body model (HBM). One hundred and twenty near-side impact motor vehicle crashes were simulated over a range of parameters using a Toyota RAV4 (bullet vehicle), Ford Taurus (struck vehicle) FE models and a validated human body model (HBM) Total HUman Model for Safety (THUMS). Three bullet vehicle crash parameters (speed, location and angle) and two occupant parameters (seat position and age) were varied using a Latin hypercube design of Experiments. Four injury metrics (head injury criterion, half deflection, thoracic trauma index and pelvic force) were used to calculate injury risk. Rib fracture prediction and lung strain metrics were also analysed. As hypothesized, bullet speed had the greatest effect on each injury measure. Injury risk was reduced when bullet location was further from the B-pillar or when the bullet angle was more oblique. Age had strong correlation to rib fractures frequency and lung strain severity. The injuries from a real-world crash were predicted using two different methods by (1) subsampling the injury predictors from the 12 best crush profile matching simulations and (2) using regression models. Both injury prediction methods successfully predicted the case occupant's low risk for pelvic injury, high risk for thoracic injury, rib fractures and high lung strains with tight confidence intervals. This parametric methodology was successfully used to explore crash parameter interactions and to robustly predict real-world injuries.

Inter- and intra-individual variation in urinary biomarker concentrations over a 6-day sampling period. Part 1: metals.

PubMed

Smolders, Roel; Koch, Holger M; Moos, Rebecca K; Cocker, John; Jones, Kate; Warren, Nick; Levy, Len; Bevan, Ruth; Hays, Sean M; Aylward, Lesa L

2014-12-01

The aim of the current HBM-study is to further the understanding of the impact of inter- and intra-individual variability in HBM surveys as it may have implications for the design and interpretation of the study outcomes. As spot samples only provide a snapshot in time of the concentrations of chemicals in an individual, it remains unclear to what extent intra-individual variability plays a role in the overall variability of population-wide HBM surveys. The current paper describes the results of an intensive biomonitoring study, in which all individual urine samples of 8 individuals were collected over a 6-day sampling period (a total of 352 unique samples). By analyzing different metals (As, Cd, Mn, Ni) in each individual sample, inter- and intra-individual variability for these four metals could be determined, and the relationships between exposure, internal dose, and sampling protocol assessed. Although the range of biomarker values for different metals was well within the normal range reported in large-scale population surveys, large intra-individual differences over a 6-day period could also be observed. Typically, measured biomarker values span at least an order of magnitude within an individual, and more if specific exposure episodes could be identified. Fish consumption for example caused a twenty- to thirty-fold increase in urinary As-levels over a period of 2-6h. Intra-class correlation coefficients (ICC) were typically low for uncorrected biomarker values (between 0.104 and 0.460 for the 4 metals), but improved when corrected for creatinine or specific gravity (SG). The results show that even though urine is a preferred matrix for HBM studies, there are certain methodological issues that need to be taken into account in the interpretation of urinary biomarker data, related to the intrinsic variability of the urination process itself, the relationship between exposure events and biomarker quantification, and the timing of sampling. When setting up HBM-projects, this expected relationship between individual exposure episode and urinary biomarker concentration needs to be taken into account. Copyright © 2014. Published by Elsevier Ireland Ltd.

What Health-Related Information Flows through You Every Day? A Content Analysis of Microblog Messages on Air Pollution

ERIC Educational Resources Information Center

Yang, Qinghua; Yang, Fan; Zhou, Chun

2015-01-01

Purpose: The purpose of this paper is to investigate how the information about haze, a term used in China to describe the air pollution problem, is portrayed on Chinese social media by different types of organizations using the theoretical framework of the health belief model (HBM). Design/methodology/approach: A content analysis was conducted…

Exploring Perceptions about and Behaviors Related to Mental Illness and Mental Health Service Utilization among College Students Using the Health Belief Model (HBM)

ERIC Educational Resources Information Center

Nobiling, Brandye D.; Maykrantz, Sherry Azadi

2017-01-01

Background: Mental health service is underutilized in the United States. Adolescent and young adults, including college students, are especially unlikely to seek professional help for mental illness. This issue presents a concern, because signs and symptoms commonly appear during this part of growth and development. Purpose: The Health Belief…

Sensitive LC-MS/MS Method for the Simultaneous Determination of Bendamustine and its Active Metabolite, γ-Hydroxybendamustine in Small Volume Mice and Dog Plasma and its Application to a Pharmacokinetic Study in Mice and Dogs.

PubMed

Chandrashekar, Devaraj V; Suresh, Ponnayyan S; Kumar, Rajnish; Bhamidipati, Ravi Kanth; Mullangi, Ramesh; Richter, Wolfgang; Srinivas, Nuggehally R

2017-09-01

A highly sensitive, specific and rapid LC-ESI-MS/MS method has been developed and validated for the simultaneous quantification of bendamustine (BM) and γ-hydroxybendamustine (HBM) in small volume (20 µL) mice and dog plasma using phenacetin as an internal standard (IS) as per regulatory guidelines. Both the analytes and IS were extracted from mice and dog plasma using a liquid-liquid extraction method. Chromatography was achieved on Atlantis dC 18 column using an isocratic mobile phase (0.2% formic acid:acetonitrile, 25:75) at a flow rate of 0.40 mL/min. The total chromatographic run time was 3.0 min and the elution of BM, HBM and IS occurred at ~1.2, 1.2 and 2.0 min, respectively. A linear response function was established 0.11-518 ng/mL for both the analytes in mice and dog plasma. The intra- and inter-day accuracy and precisions were in the range of 3.46-12.9 and 3.63-8.23%; 1.15-9.00 and 7.86-9.49% for BM and HBM, respectively in mice plasma and 2.15-6.49 and 1.73-13.1%; 4.35-13.9 and 4.33-10.5% for BM and HBM, respectively in dog plasma. This novel method has been applied to a pharmacokinetic study in mice and dogs. © Georg Thieme Verlag KG Stuttgart · New York.

[Monograph for N-Methyl-pyrrolidone (NMP) and human biomonitoring values for the metabolites 5-Hydroxy-NMP and 2-Hydroxy-N-methylsuccinimide].

PubMed

2015-10-01

1-Methyl-pyrrolidone (NMP) is used as a solvent in many technical applications. The general population may be exposed to NMP from the use as ingredient in paint and graffiti remover, indoors also from use in paints and carpeting. Because of developmental toxic effects, the use of NMP in consumer products in the EU is regulated. The developmental effects accompanied by weak maternally toxic effects in animal experiments are considered as the critical effects by the German HBM Commission. Based on these effects, HBM-I values of 10 mg/l urine for children and of 15 mg/l for adults, respectively, were derived for the metabolites 5-Hydroxy-NMP and 2-Hydroxy-N-methylsuccinimide. HBM-II-values were set to 30 mg/l urine for children and 50 mg/l for adults, respectively. Because of similar effects of the structural analogue 1-ethyl-2-pyrrolidone (NEP), the possible mixed exposure to both compounds has to be taken into account when evaluating the total burden.

Effectiveness of breastfeeding education on the weight of child and self-efficacy of mothers – 2011

PubMed Central

Kamran, Aziz; Shrifirad, Gholamreza; Mirkarimi, Seyed Kamal; Farahani, Abbas

2012-01-01

Background: Breastfeeding is the most natural and essential way for feeding newborn babies. This is an ideal approach for physical and emotional development of babies, as well as for the recovery of mothers. This study was aimed to determine the effect of breastfeeding education based on the health belief model (HBM) toward primiparous women. Materials and Methods: In a case–control group, quasi-experimental study, 88 subjects were allocated in control and experimental groups. Subjects who were assigned to the experimental group were provided a program consisting of group education based on HBM during their prenatal period. Instrument for data gathering was made by the researchers and standard questionnaire from Dennis and Faux for Breastfeeding Self-efficacy Scale (BSES). Baseline interviews were conducted before delivery and follow-up visits were conducted after 30 days and at the fourth month after delivery. Data were analyzed using SPSS (version 16) with c2, independent sample t-tests, and paired t-test. Results: Mean age of pregnant women who participated in the study was 22 ± 3.29 years. After the program, the experimental group had significantly better scores in terms of self-efficacy, knowledge, and attitude scores statistically. In the fourth month, the mean of child weight in the experimental group was significantly higher than that of the control group (P=0.001) and exclusive breastfeeding was significantly higher than in the control group (P=0.007). Conclusion: Prenatal education in this study based on HBM was successful, and knowledge, attitude, self-efficacy, and related indicators improved. The necessity of producing standard education package and education of pregnant mothers, especially in their first pregnancy, by health professionals is perceived. PMID:23555114

Impact behavior of a high viscosity magnetorheological fluid-based energy absorber with a radial flow mode

NASA Astrophysics Data System (ADS)

Fu, Benyuan; Liao, Changrong; Li, Zhuqiang; Xie, Lei; Zhang, Peng; Jian, Xiaochun

2017-02-01

High viscosity linear polysiloxane magnetorheological fluid (HVLP MRF) was demonstrated with excellent suspension stability. Such material is suitable for application in the magnetorheological energy absorbers (MREAs) under axial impact loading conditions. On this basis, a new energy absorber incorporating a radial valve with high magnetic field utilization and a corrugated tube is proposed. In energy absorption applications where the MREA is rarely if ever used, our MREA takes the ultra-stable HVLP MRF as controlled medium in order for a long-term stability. For MREA performing at very high shear rates where the minor losses are important contributing factors to damping, a nonlinear analytical model, based on the Herschel-Bulkley flow model (HB model), is developed taking into account the effects of minor losses (called HBM model). The HB model parameters are determined by rheological experiments with a commercial shear rheometer. Then, continuity equation and governing differential equation of the HVLP MRF in radial flow are established. Based on the HB model, the expressions of radial velocity distribution are deduced. The influences of minor losses on pressure drop are analyzed with mean fluid velocities. Further, mechanical behavior of the corrugated tube is investigated via drop test. In order to verify the theoretical methodology, a MREA is fabricated and tested using a high-speed drop tower facility with a 600 kg mass at different drop heights and in various magnetic fields. The experiment results show that the HBM model is capable of well predicting the impact behavior of the proposed MREA.

Improve Knowledge, Beliefs and Behavior of Undergraduate Female Nursing Students in Al-Alzhar University toward Breast Self-Examination Practice

ERIC Educational Resources Information Center

El-Mohsen, Afaf S. Abd; El-Maksoud, Mona M. Abd

2015-01-01

Breast cancer is a public health problem that is most common form of cancer among females in both developed and developing world, The Health Belief Model (HBM) has been used as a theoretical framework to study Breast Self-Examination and other breast cancer detection behaviors. The aim of this study: Was to improve knowledge, beliefs and behavior…

Effectiveness of self-management promotion educational program among diabetic patients based on health belief model

PubMed Central

Jalilian, Farzad; Motlagh, Fazel Zinat; Solhi, Mahnaz; Gharibnavaz, Hasan

2014-01-01

Introduction: Diabetes is a chronic disease; it can cause serious complications. Diabetes self-management is essential for prevention of disease complications. This study was conducted to evaluate self-management promotion educational program intervention efficiency among diabetic patients in Iran and health belief model (HBM) was applied as a theoretical framework. Materials and Methods: Overall, 120 Type 2 diabetic patients referred to rural health centers in Gachsaran, Iran participated in this study as randomly divided into intervention and control group. This was a longitudinal randomized pre- and post-test series control group design panel study to implement a behavior modification based intervention to promotion self-management among diabetic patients. Cross-tabulation and t-test by using SPSS statistical package, version 16 was used for the statistical analysis. Results: Mean age was 55.07 years (SD = 9.94, range: 30-70). Our result shows significant improvements in average response for susceptibility, severity, benefit and self-management among intervention group. Additionally, after intervention, average response of the barrier to self-management was decreased among intervention group. Conclusion: Our result showed education program based on HBM was improve of self-management and seems implementing these programs can be effective in the and prevention of diabetes complications. PMID:24741654

The Application of the Health Belief Model in Oral Health Education

PubMed Central

Solhi, M; Zadeh, D Shojaei; Seraj, B; Zadeh, S Faghih

2010-01-01

Background: The goal of this study was to determine the application of health belief model in oral health education for 12-year-old children and its effect on oral health behaviors and indexes. Methods: A quasi-experimental study was carried out on twelve-year-old girl students (n-291) in the first grade of secondary school, in the central district of Tehran, Iran. Research sample was selected by a multistage cluster sampling. The data was obtained by using a valid reliable questionnaire for measuring the perceptions, a checklist for observing the quality of brushing and dental flossing and health files and clinical observation. First, a descriptive study was applied to individual perceptions, oral behaviors, Oral Hygiene Index (OHI) and Decayed, Missing and Filled Teeth Index (DMFTI). Then an educational planning based on the results and Health Belief Model (HBM) was applied. The procedure was repeated after six months. Results: After education, based on HBM, all the oral health perceptions increased (P<.05). Correct brushing and flossing are influenced by increased perceptions. A low correlation between the reduction of DMFTI and increased perceived severity and increased perceived barriers are found (r= −0.28, r = 0.43 respectively). In addition, there was a limited correlation between OHI and increased perceived benefits (r = −0.26). Conclusion: Using health belief model in oral health education for increasing the likelihood of taking preventive oral health behaviors is applicable. PMID:23113044

Mercury in Children: Current State on Exposure through Human Biomonitoring Studies

PubMed Central

Ruggieri, Flavia; Majorani, Costanza; Domanico, Francesco; Alimonti, Alessandro

2017-01-01

Mercury (Hg) in children has multiple exposure sources and the toxicity of Hg compounds depends on exposure routes, dose, timing of exposure, and developmental stage (be it prenatal or postnatal). Over the last decades, Hg was widely recognized as a threat to the children’s health and there have been acknowledgements at the international level of the need of a global policy intervention—like the Minamata treaty—aimed at reducing or preventing Hg exposure and protecting the child health. National human biomonitoring (HBM) data has demonstrated that low levels of exposure of Hg are still an important health concern for children, which no one country can solve alone. Although independent HBM surveys have provided the basis for the achievements of exposure mitigation in specific contexts, a new paradigm for a coordinated global monitoring of children’s exposure, aimed at a reliable decision-making tool at global level is yet a great challenge for the next future. The objective of the present review is to describe current HBM studies on Hg exposure in children, taking into account the potential pathways of Hg exposure and the actual Hg exposure levels assessed by different biomarkers. PMID:28498344

Using the Health Belief Model to Explain Mothers' and Fathers' Intention to Participate in Universal Parenting Programs.

PubMed

Salari, Raziye; Filus, Ania

2017-01-01

Using the Health Belief Model (HBM) as a theoretical framework, we studied factors related to parental intention to participate in parenting programs and examined the moderating effects of parent gender on these factors. Participants were a community sample of 290 mothers and 290 fathers of 5- to 10-year-old children. Parents completed a set of questionnaires assessing child emotional and behavioral difficulties and the HBM constructs concerning perceived program benefits and barriers, perceived child problem susceptibility and severity, and perceived self-efficacy. The hypothesized model was evaluated using structural equation modeling. The results showed that, for both mothers and fathers, perceived program benefits were associated with higher intention to participate in parenting programs. In addition, higher intention to participate was associated with lower perceived barriers only in the sample of mothers and with higher perceived self-efficacy only in the sample of fathers. No significant relations were found between intention to participate and perceived child problem susceptibility and severity. Mediation analyses indicated that, for both mothers and fathers, child emotional and behavioral problems had an indirect effect on parents' intention to participate by increasing the level of perceived benefits of the program. As a whole, the proposed model explained about 45 % of the variance in parental intention to participate. The current study suggests that mothers and fathers may be motivated by different factors when making their decision to participate in a parenting program. This finding can inform future parent engagement strategies intended to increase both mothers' and fathers' participation rates in parenting programs.

Skin Cancer Knowledge, Beliefs, Self-Efficacy, and Preventative Behaviors among North Mississippi Landscapers

PubMed Central

Ford, M. Allison; Hallam, Jeffrey S.; Bass, Martha A.; Vice, Michael A.

2013-01-01

There are slightly over one million workers in the landscape service industry in the US. These workers have potential for high levels of solar ultraviolet radiation exposure, increasing their risk of skin cancer. A cross-sectional sample of 109 landscapers completed a self-administered questionnaire based on Health Belief Model (HBM). The participants correctly answered 67.1% of the knowledge questions, 69.7% believed they were more likely than the average person to get skin cancer, and 87.2% perceived skin cancer as a severe disease. Participants believed that the use of wide-brimmed hats, long sleeved shirts/long pants, and sunscreen was beneficial but reported low usage of these and other sun protective strategies. The primary barriers to using sun protection were “I forget to wear it” and “it is too hot to wear.” Of the HBM variables, perceived benefits outweighing perceived barrier (r = .285, P = .003) and self-efficacy (r = .538, P = .001) were correlated with sun protection behaviors. The reasons for absence of the relationship between perceived skin cancer threat and sun protection behaviors could be lack of skin cancer knowledge and low rate of personal skin cancer history. PMID:24223037

Cost and culture: Factors influencing worksite physical activity across three universities.

PubMed

Rinaldi-Miles, Anna I; Das, Bhibha M

2016-11-22

Physical inactivity is a leading cause of morbidity and mortality. Worksites provide an ideal environment for physical activity (PA) interventions. Colleges and universities are a unique work venue, with institutions of higher education of varying scope within every state of the United States and worldwide. To explore the institutional influences on worksite PA across multiple universities. Employees from two large, universities (Midwestern and Southern) and a mid-size, university (Midwestern) participated in exploratory research in March/April 2010 and 2013. The Nominal Group Technique (NGT) methodology and the Health Belief Model (HBM) were used to assess perceived influences on employees' engagement in worksite PA. The findings demonstrate that university employees experienced similar factors that influence PA as employees across the different institutions. Specifically, there was an interesting relationship between opportunities for PA and lack of a supportive work culture to promote it. Emphasis on immediate perceived threats to PA inactivity may improve the utility of the HBM for interventions within this context. Further, campus worksite interventions for employees should address barriers such as cost of campus recreation centers and administrative support for engaging in worksite PA as possible cues to action.

Effect of Planned Follow-up on Married Women's Health Beliefs and Behaviors Concerning Breast and Cervical Cancer Screenings.

PubMed

Kolutek, Rahsan; Avci, Ilknur Aydin; Sevig, Umit

2018-04-01

The objective of this study was to identify the effect of planned follow-up visits on married women's health beliefs and behaviors concerning breast and cervical cancer screenings. The study was conducted using the single-group pre-test/post-test and quasi-experimental study designs. The sample of the study included 153 women. Data were collected using a Personal Information Form, the Health Belief Model (HBM) Scale for Breast Cancer Screening, the HBM Scale for Cervical Cancer Screening, and a Pap smear test. Data were collected using the aforementioned tools from September 2012 to March 2013. Four follow-up visits were conducted, nurses were educated, and telephone reminders were utilized. Friedman's test, McNemar's test, and descriptive statistics were used for data analyzing. The frequency of performing breast self-examination (BSE) at the last visit increased to 84.3 % compared to the pre-training. A statistically significant difference was observed between the pre- and post-training median values in four subscales except for the subscale of perceived seriousness of cervical cancer under "the Health Belief Model Scale for Cervical Cancer and the Pap Smear Test" (p < 0.001). The rate of performing BSE significantly increased after the training and follow-up visits. Also, the rate of having a Pap smear significantly increased after the follow-up visits.

Assessing the effect of an educational intervention program based on Health Belief Model on preventive behaviors of internet addiction

PubMed Central

Maheri, Aghbabak; Tol, Azar; Sadeghi, Roya

2017-01-01

INTRODUCTION: Internet addiction refers to the excessive use of the internet that causes mental, social, and physical problems. According to the high prevalence of internet addiction among university students, this study aimed to determine the effect of an educational intervention on preventive behaviors of internet addiction among Tehran University of Medical Sciences students. MATERIALS AND METHODS: This study was a quasi-experimental study conducted among female college students who live in the dormitories of Tehran University of Medical Sciences. Two-stage cluster sampling was used for selection of eighty participants in each study groups; data were collected using “Young's Internet Addiction” and unstructured questionnaire. Validity and reliability of unstructured questionnaire were evaluated by expert panel and were reported as Cronbach's alpha. Information of study groups before and 4 months after the intervention was compared using statistical methods by SPSS 16. RESULTS: After the intervention, the mean scores of internet addiction, perceived barriers construct, and the prevalence of internet addiction significantly decreased in the intervention group than that in the control group and the mean scores of knowledge and Health Belief Model (HBM) constructs (susceptibility, severity, benefits, self-efficacy) significantly increased. CONCLUSIONS: Education based on the HBM was effective on the reduction and prevention of internet addiction among female college students, and educational interventions in this field are highly recommended. PMID:28852654

Evaluation of kinematics and injuries to restrained occupants in far-side crashes using full-scale vehicle and human body models.

PubMed

Arun, Mike W J; Umale, Sagar; Humm, John R; Yoganandan, Narayan; Hadagali, Prasanaah; Pintar, Frank A

2016-09-01

The objective of the current study was to perform a parametric study with different impact objects, impact locations, and impact speeds by analyzing occupant kinematics and injury estimations using a whole-vehicle and whole-body finite element-human body model (FE-HBM). To confirm the HBM responses, the biofidelity of the model was validated using data from postmortem human surrogate (PMHS) sled tests. The biofidelity of the model was validated using data from sled experiments and correlational analysis (CORA). Full-scale simulations were performed using a restrained Global Human Body Model Consortium (GHBMC) model seated on a 2001 Ford Taurus model using a far-side lateral impact condition. The driver seat was placed in the center position to represent a nominal initial impact condition. A 3-point seat belt with pretensioner and retractor was used to restrain the GHBMC model. A parametric study was performed using 12 simulations by varying impact locations, impacting object, and impact speed using the full-scale models. In all 12 simulations, the principal direction of force (PDOF) was selected as 90°. The impacting objects were a 10-in.-diameter rigid vertical pole and a movable deformable barrier. The impact location of the pole was at the C-pillar in the first case, at the B-pillar in the second case, and, finally, at the A-pillar in the third case. The vehicle and the GHBMC models were defined an initial velocity of 35 km/h (high speed) and 15 km/h (low speed). Excursion of the head center of gravity (CG), T6, and pelvis were measured from the simulations. In addition, injury risk estimations were performed on head, rib cage, lungs, kidneys, liver, spleen, and pelvis. The average CORA rating was 0.7. The shoulder belt slipped in B- and C-pillar impacts but somewhat engaged in the A-pillar case. In the B-pillar case, the head contacted the intruding struck-side structures, indicating higher risk of injury. Occupant kinematics depended on interaction with restraints and internal structures-especially the passenger seat. Risk analysis indicated that the head had the highest risk of sustaining an injury in the B-pillar case compared to the other 2 cases. Higher lap belt load (3.4 kN) may correspond to the Abbreviated Injury Scale (AIS) 2 pelvic injury observed in the B-pillar case. Risk of injury to other soft anatomical structures varied with impact configuration and restraint interaction. The average CORA rating was 0.7. In general, the results indicated that the high-speed impacts against the pole resulted in severe injuries, higher excursions followed by low-speed pole, high-speed moving deformable barrier (MDB), and low-speed MDB impacts. The vehicle and occupant kinematics varied with different impact setups and the latter kinematics were likely influenced by restraint effectiveness. Increased restraint engagement increased the injury risk to the corresponding anatomic structure, whereas ineffective restraint engagement increased the occupant excursion, resulting in a direct impact to the struck-side interior structures.

Using NASA Satellite Aerosol Optical Depth to Enhance PM2.5 Concentration Datasets for Use in Human Health and Epidemiology Studies

NASA Astrophysics Data System (ADS)

Huff, A. K.; Weber, S.; Braggio, J.; Talbot, T.; Hall, E.

2012-12-01

Fine particulate matter (PM2.5) is a criterion air pollutant, and its adverse impacts on human health are well established. Traditionally, studies that analyze the health effects of human exposure to PM2.5 use concentration measurements from ground-based monitors and predicted PM2.5 concentrations from air quality models, such as the U.S. EPA's Community Multi-scale Air Quality (CMAQ) model. There are shortcomings associated with these datasets, however. Monitors are not distributed uniformly across the U.S., which causes spatially inhomogeneous measurements of pollutant concentrations. There are often temporal variations as well, since not all monitors make daily measurements. Air quality model output, while spatially and temporally uniform, represents predictions of PM2.5 concentrations, not actual measurements. This study is exploring the potential of combining Aerosol Optical Depth (AOD) data from the MODIS instrument on NASA's Terra and Aqua satellites with PM2.5 monitor data and CMAQ predictions to create PM2.5 datasets that more accurately reflect the spatial and temporal variations in ambient PM2.5 concentrations on the metropolitan scale, with the overall goal of enhancing capabilities for environmental public health decision-making. AOD data provide regional information about particulate concentrations that can fill in the spatial and temporal gaps in the national PM2.5 monitor network. Furthermore, AOD is a measurement, so it reflects actual concentrations of particulates in the atmosphere, in contrast to PM2.5 predictions from air quality models. Results will be presented from the Battelle/U.S. EPA statistical Hierarchical Bayesian Model (HBM), which was used to combine three PM2.5 concentration datasets: monitor measurements, AOD data, and CMAQ model predictions. The study is focusing on the Baltimore, MD and New York City, NY metropolitan regions for the period 2004-2006. For each region, combined monitor/AOD/CMAQ PM2.5 datasets generated by the HBM are being correlated with data on inpatient hospitalizations and emergency room visits for seven respiratory and cardiovascular diseases using statistical case-crossover analyses. Preliminary results will be discussed regarding the potential for the addition of AOD data to increase the correlation between PM2.5 concentrations and health outcomes. Environmental public health tracking programs associated with the Maryland Department of Health and Mental Hygiene, the New York State Department of Health, the CDC, and the U.S. EPA have expressed interest in using the results of this study to enhance their existing environmental health surveillance activities.

New human biomonitoring methods for chemicals of concern-the German approach to enhance relevance.

PubMed

Kolossa-Gehring, Marike; Fiddicke, Ulrike; Leng, Gabriele; Angerer, Jürgen; Wolz, Birgit

2017-03-01

In Germany strong efforts have been made within the last years to develop new methods for human biomonitoring (HBM). The German Federal Ministry for the Environment, Nature Conservation, Building and Nuclear Safety (BMUB) and the German Chemical Industry Association e. V. (VCI) cooperate since 2010 to increase the knowledge on the internal exposure of the general population to chemicals. The projects aim is to promote human biomonitoring by developing new analytical methods Key partner of the cooperation is the German Environment Agency (UBA) which has been entrusted with the scientific coordination. Another key partner is the "HBM Expert Panel" which each year puts together a list of chemicals of interest to the project from which the Steering Committee of the project choses up to five substances for which method development will be started. Emphasis is placed on substances with either a potential health relevance or on substances to which the general population is potentially exposed to a considerable extent. The HBM Expert Panel also advises on method development. Once a method is developed, it is usually first applied to about 40 non-occupationally exposed individuals. A next step is applying the methods to different samples. Either, if the time trend is of major interest, to samples from the German Environmental Specimen Bank, or, in case exposure sources and distribution of exposure levels in the general population are the focus, the new methods are applied to samples from children and adolescents from the population representative 5th German Environmental Survey (GerES V). Results are expected in late 2018. This article describes the challenges faced during method development and solutions found. An overview presents the 34 selected substances, the 14 methods developed and the 7 HBM-I values derived in the period from 2010 to mid 2016. Copyright © 2016 The Authors. Published by Elsevier GmbH.. All rights reserved.

Associations between human breast milk hormones and adipocytokines and infant growth and body composition in the first 6 months of life.

PubMed

Fields, D A; George, B; Williams, M; Whitaker, K; Allison, D B; Teague, A; Demerath, E W

2017-08-01

Much is to be learnt about human breast milk (HBM). The purpose of this study is to extend our knowledge of HBM by investigating the role of maternal body mass index (BMI), sex and stage of lactation (month 1 vs. 6) on HBM insulin, glucose, leptin, IL-6 and TNF-α and their associations with infant body composition. Thirty-seven exclusively breastfeeding infants (n = 37; 16♀, 21♂), and their mothers (19-47 kg m -2 ) were studied at 1 and 6 months of lactation. Infants had body composition measured (using dual-energy X-ray absorptiometry) and HBM collected. A significant interaction between maternal BMI and infant sex on insulin levels (p = 0.0322) was observed such that insulin was 229% higher in obese mothers nursing female infants than in normal weight mothers nursing female infants and 179% higher than obese mothers nursing male infants. For leptin, a significant association with BMI category was observed (p < 0.0001) such that overweight and obese mothers had 96.5% and 315.1% higher leptin levels than normal weight mothers, respectively. Leptin was also found to have a significant (p = 0.0004) 33.7% decrease from months 1 to 6, controlling for BMI category and sex. A significant inverse relationship between month 1 leptin levels and infant length (p = 0.0257), percent fat (p = 0.0223), total fat mass (p = 0.0226) and trunk fat mass (p = 0.0111) at month 6 was also found. No associations or interactions were observed for glucose, TNF-α or IL-6. These data demonstrate that maternal BMI, infant sex and stage of lactation affect the compositional make-up of insulin and leptin. © 2017 World Obesity Federation.

Normal hematopoiesis and lack of β-catenin activation in osteoblasts of patients and mice harboring Lrp5 gain-of-function mutations.

PubMed

Galán-Díez, Marta; Isa, Adiba; Ponzetti, Marco; Nielsen, Morten Frost; Kassem, Moustapha; Kousteni, Stavroula

2016-03-01

Osteoblasts are emerging regulators of myeloid malignancies since genetic alterations in them, such as constitutive activation of β-catenin, instigate their appearance. The LDL receptor-related protein 5 (LRP5), initially proposed to be a co-receptor for Wnt proteins, in fact favors bone formation by suppressing gut-serotonin synthesis. This function of Lrp5 occurring in the gut is independent of β-catenin activation in osteoblasts. However, it is unknown whether Lrp5 can act directly in osteoblast to influence other functions that require β-catenin signaling, particularly, the deregulation of hematopoiesis and leukemogenic properties of β-catenin activation in osteoblasts, that lead to development of acute myeloid leukemia (AML). Using mice with gain-of-function (GOF) Lrp5 alleles (Lrp5(A214V)) that recapitulate the human high bone mass (HBM) phenotype, as well as patients with the T253I HBM Lrp5 mutation, we show here that Lrp5 GOF mutations in both humans and mice do not activate β-catenin signaling in osteoblasts. Consistent with a lack of β-catenin activation in their osteoblasts, Lrp5(A214V) mice have normal trilinear hematopoiesis. In contrast to leukemic mice with constitutive activation of β-catenin in osteoblasts (Ctnnb1(CAosb)), accumulation of early myeloid progenitors, a characteristic of AML, myeloid-blasts in blood, and segmented neutrophils or dysplastic megakaryocytes in the bone marrow, are not observed in Lrp5(A214V) mice. Likewise, peripheral blood count analysis in HBM patients showed normal hematopoiesis, normal percentage of myeloid cells, and lack of anemia. We conclude that Lrp5 GOF mutations do not activate β-catenin signaling in osteoblasts. As a result, myeloid lineage differentiation is normal in HBM patients and mice. This article is part of a Special Issue entitled: Tumor Microenvironment Regulation of Cancer Cell Survival, Metastasis, Inflammation, and Immune Surveillance edited by Peter Ruvolo and Gregg L. Semenza. Published by Elsevier B.V.

Environmental interventions based on the Health Belief Model and the Ecological-social model in the continuation of consumption of rice, free from toxic metals

PubMed Central

Shafiei, Leili; Maleki, Afshin; Sayehmiri, Kourosh

2018-01-01

Background and aim Continuation of healthy nutritional behaviors is one of the important factors in effectiveness of educational intervention programs. The aim of this research is to compare the Health Belief Model and the Ecological-social model in reducing consumption of rice contaminated with toxic metals after completion of environmental intervention and continuation of consumption of healthy rice. Methods This research was the implementation of a six-month randomized controlled trial interventional program in two groups’ interventions along with a control group, with 80 people for each group totally, amounting to 240 women, between 18 and 50 years of age in Ilam, Iran in 2014. The questionnaires of the three groups consisted of demographic information, knowledge, the constructs of the models, performance of rice consumption. Friedman test and repeated measures used for data analysis with SPSS (version 20), and confidence interval of 95% were considered. Results The results of the Friedman test indicated a significant increase in the number of women consuming healthy rice over six months after intervention in both intervention groups (p<0.001). Women in the ECO group consumed healthy rice 27.5% more than the HBM group (p<0.001). The results of repeated measures analysis of variance suggested greater improvement in the consumption of healthy rice in the ECO group in comparison with the HBM group over six months after intervention (p<0.05). Conclusions Both educational environmental intervention methods caused the altered diet of people regarding consumption of healthy rice over six months after the intervention. Increased social support also probably had a more effective role in continuation of healthy diet among the people. PMID:29588814

Current education versus peer-education on walking in type 2 diabetic patients based on Health Belief Model: a randomized control trial study.

PubMed

Baghianimoghadam, M H; Hadavandkhani, M; Mohammadi, M; Fallahzade, H; Baghianimoghadam, B

2012-01-01

Diabetes is a disease with several metabolic and organic symptoms. Physical activity plays a key role in controlling type 2 diabetes. Several researches confirm that educational strategies can lead to healthy behaviors and its continuation is effective and can indicate what type of relationship with the client is better. The purpose of this study is comparing the Effect of Current Education and Peer-Education on Walking in Type 2 Diabetic Patients based on Health Belief Model (HBM). This was a clinical trial (RCT) study done on 80 people with type 2 diabetes. Patients were divided into two groups, Current education and Peer education groups. Data were collected using a questionnaire based on the health belief model, a checklist related to patients' practice and recording patients' HbA1c, 2HPP and FBS levels. Results were documented before and three months after intervention. The patients participated in 2 educational classes during three months of intervention, as the follow-up of the intervention. Mean scores for HBM Model variables, i.e. perceived susceptibility, perceived severity, perceived benefit and self-efficacy, were significantly increased in the peer education group compared to current education group after intervention. Also, behavioral walking, rates of HbA1c and FBS and 2HPP levels were improved significantly among the peer education group. Applying walking training program developed for diabetic patients and its implementation by the peers in order to control blood sugar using the health belief model is very useful and effective. During implementation of these control programs, monitoring and follow-up training is recommended.

Comparison between the effects of positive noncatastrophic HMB ESD stress in n-channel and p-channel power MOSFET's

NASA Astrophysics Data System (ADS)

Zupac, Dragan; Kosier, Steven L.; Schrimpf, Ronald D.; Galloway, Kenneth F.; Baum, Keith W.

1991-10-01

The effect of noncatastrophic positive human body model (HBM) electrostatic discharge (ESD) stress on n-channel power MOSFETs is radically different from that on p-channel MOSFETs. In n-channel transistors, the stress causes negative shifts of the current-voltage characteristics indicative of positive charge trapping in the gate oxide. In p-channel transistors, the stress increases the drain-to-source leakage current, probably due to localized avalanche electron injection from the p-doped drain.

New technologies - How to assess environmental effects

NASA Technical Reports Server (NTRS)

Sullivan, P. J.; Lavin, M. L.

1981-01-01

A method is provided for assessing the environmental effects of a room-and-pillar mining system (RP) and a new hydraulic borehole mining system (HBM). Before environmental assessment can begin, each technology is defined in terms of its engineering characteristics at both the conceptual and preliminary design stages. The mining sites are also described in order to identify the significant advantages and constraints for each system. This can be a basic physical and biological survey of the region at the conceptual stage, but a more specific representation of site characteristics is required at the preliminary stage. Assessment of potential environmental effects of each system at the conceptual design is critical to its hardware development and application. A checklist can be used to compare and identify the negative impacts of each method, outlining the resource affected, the type of impact involved, and the exact activity causing that impact. At the preliminary design stage, these impacts should be evaluated as a result of either utilization or alteration. Underground coal mining systems have three major utilization impacts - the total area disturbed, the total water resources withdrawn from other uses, and the overall energy efficiency of the process - and one major alteration impact - the degradation of water quality by sedimentation and acid contamination. A comparison of the RP and HBM systems shows the HBM to be an environmentally less desirable system for the Central Appalachia region.

Factors associated with perception of risk of contracting HIV among secondary school female learners in Mbonge subdivision of rural Cameroon.

PubMed

Tarkang, Elvis Enowbeyang

2014-01-01

Since learners in secondary schools fall within the age group hardest hit by HIV/AIDS, it is obvious that these learners might be at high risk of contracting HIV/AIDS. However, little has been explored on the perception of risk of contracting HIV among secondary school learners in Cameroon. This study aimed at examining the perception of risk of contracting HIV among secondary school learners in Mbonge subdivision of rural Cameroon using the Health Belief Model (HBM) as framework. A quantitative, correlational design was adopted, using a self-administered questionnaire to collect data from 210 female learners selected through disproportional, stratified, simple random sampling technique, from three participating senior secondary schools. Statistics were calculated using SPSS version 20 software program. Only 39.4% of the respondents perceived themselves to be at high risk of contracting HIV, though the majority, 54.0% were sexually active. Multinomial logistic regression analyses show that sexual risk behaviours (p=0.000) and the Integrated Value Mapping (IVM) of the perception components of the HBM are the most significant factors associated with perception of risk of contracting HIV at the level p<0.05. The findings of this study can play an instrumental role in the development of effective preventive and interventional messages for adolescents in Cameroon.

Evaluation of Biomonitoring Data from the CDC National ...

EPA Pesticide Factsheets

BACKGROUND: Biomonitoring data reported in the National Report on Human Exposure to Environmental Chemicals (NER) provide information on the presence and concentrations of more than 400 chemicals in human blood and urine. Biomonitoring Equivalents (BEs) and other risk assessment-based values now allow interpretation of these biomonitoring data in a public health risk context. OBJECTIVES: Compare the measured biomarker concentrations in the NER with BEs and similar risk assessment values to provide an across-chemical risk assessment perspective on the measured levels for approximately 130 analytes in the NER. METHODS: Available risk assessment-based biomarker screening values, including BEs and Human Biomonitoring-I (HBM-I) values from the German Human Biomonitoring Commission, were identified. Geometric mean and 95th percentile population biomarker concentrations from the NER were compared to the available screening values to generate chemical-specific hazard quotients (HQ) or cancer risk estimates. CONCLUSIONS: Several analytes in the NER approach or exceed HQ values of 1 or cancer risks greater than 1x 10-4 at the geometric mean or 95th percentile, suggesting exposure levels exceed what is considered safe in a large fraction of the population. Analytes of concern include acrylamide, dioxin-like chemicals, benzene, xylene, several metals, di-2(ethylhexyl)phthalate, and some legacy organochlorine pesticides. This analysis provides for the first time a mean

Seasonal Influenza Vaccine Acceptance among Pregnant Women in Zhejiang Province, China: Evidence Based on Health Belief Model.

PubMed

Hu, Yu; Wang, Ying; Liang, Hui; Chen, Yaping

2017-12-11

Background: Reasons for acceptance of seasonal influenza vaccine (SIV) vaccination among pregnant women in China are poorly understood. We assessed the intention to accept SIV among pregnant women in Zhejiang province, by using a self-administrated structured questionnaire developed on the basis of health belief model (HBM). Methods: From 1 January to 31 March 2014, pregnant women with ≥12 gestational weeks who attended antenatal clinics (ANCs) at public hospitals in 6 out of 90 districts were surveyed using a self-administered questionnaire that covered knowledge, attitudes, and beliefs related to SIV vaccination and influenza infection. We examined the associations between the acceptance of SIV vaccination and the demographic factors and HBM constructs using the logistic regression model, calculating the adjusted odds ratio (AOR). Results: Of the 1252 participants, 76.28% were willing to receive the SIV vaccination during their current pregnancy. High levels of perceived susceptibility of influenza (AOR = 1.75 (95%CI: 1.36-2.08)), high levels of perceived severity of influenza (AOR = 1.62 (95%CI: 1.25-1.95)), high level of perceived benefits of vaccination (AOR = 1.97 (95%CI: 1.76-2.21)), and high levels of cues to action were positively associated with the acceptance of SIV vaccination among pregnant women (AOR = 2.03 (95%CI: 1.70-2.69)), while high level of perceived barriers of vaccination was a negative determinant (AOR = 0.76 (95%CI: 0.62-0.94)). Conclusions: Poor knowledge and negative attitude towards SIV were associated with the poor acceptance of SIV. Health providers' recommendations were important to pregnant women's acceptance of SIV. Health education and direct communication strategies on SIV vaccination and influenza infection are necessary to improve the acceptance of SIV vaccination among pregnant women.

Targeting the LRP5 pathway improves bone properties in a mouse model of Osteogenesis Imperfecta

PubMed Central

Jacobsen, Christina M.; Barber, Lauren A.; Ayturk, Ugur M.; Roberts, Heather J.; Deal, Lauren E.; Schwartz, Marissa A.; Weis, MaryAnn; Eyre, David; Zurakowski, David; Robling, Alexander G.; Warman, Matthew L.

2014-01-01

The cell surface receptor low-density lipoprotein receptor-related protein 5 (LRP5) is a key regulator of bone mass and bone strength. Heterozygous missense mutations in LRP5 cause autosomal dominant high bone mass (HBM) in humans by reducing binding to LRP5 by endogenous inhibitors, such as sclerostin (SOST). Mice heterozygous for a knockin allele (Lrp5p.A214V) that is orthologous to a human HBM-causing mutation have increased bone mass and strength. Osteogenesis Imperfecta (OI) is a skeletal fragility disorder predominantly caused by mutations that affect type I collagen. We tested whether the LRP5 pathway can be used to improve bone properties in animal models of OI. First, we mated Lrp5+/p.A214V mice to Col1a2+/p.G610C mice, which model human type IV OI. We found that Col1a2+/p.G610C;Lrp5+/p.A214V offspring had significantly increased bone mass and strength compared to Col1a2+/p.G610C;Lrp5+/+ littermates. The improved bone properties were not due to altered mRNA expression of type I collagen or its chaperones, nor were they due to changes in mutant type I collagen secretion. Second, we treated Col1a2+/p.G610C mice with a monoclonal antibody that inhibits sclerostin activity (Scl-Ab). We found that antibody treated mice had significantly increased bone mass and strength compared to vehicle treated littermates. These findings indicate increasing bone formation, even without altering bone collagen composition, may benefit patients with OI. PMID:24677211

Targeting the LRP5 pathway improves bone properties in a mouse model of osteogenesis imperfecta.

PubMed

Jacobsen, Christina M; Barber, Lauren A; Ayturk, Ugur M; Roberts, Heather J; Deal, Lauren E; Schwartz, Marissa A; Weis, MaryAnn; Eyre, David; Zurakowski, David; Robling, Alexander G; Warman, Matthew L

2014-10-01

The cell surface receptor low-density lipoprotein receptor-related protein 5 (LRP5) is a key regulator of bone mass and bone strength. Heterozygous missense mutations in LRP5 cause autosomal dominant high bone mass (HBM) in humans by reducing binding to LRP5 by endogenous inhibitors, such as sclerostin (SOST). Mice heterozygous for a knockin allele (Lrp5(p.A214V) ) that is orthologous to a human HBM-causing mutation have increased bone mass and strength. Osteogenesis imperfecta (OI) is a skeletal fragility disorder predominantly caused by mutations that affect type I collagen. We tested whether the LRP5 pathway can be used to improve bone properties in animal models of OI. First, we mated Lrp5(+/p.A214V) mice to Col1a2(+/p.G610C) mice, which model human type IV OI. We found that Col1a2(+/p.G610C) ;Lrp5(+/p.A214V) offspring had significantly increased bone mass and strength compared to Col1a2(+/p.G610C) ;Lrp5(+/+) littermates. The improved bone properties were not a result of altered mRNA expression of type I collagen or its chaperones, nor were they due to changes in mutant type I collagen secretion. Second, we treated Col1a2(+/p.G610C) mice with a monoclonal antibody that inhibits sclerostin activity (Scl-Ab). We found that antibody-treated mice had significantly increased bone mass and strength compared to vehicle-treated littermates. These findings indicate increasing bone formation, even without altering bone collagen composition, may benefit patients with OI. © 2014 American Society for Bone and Mineral Research.

Detection of BRAF V600 Mutations in Melanoma: Evaluation of Concordance between the Cobas® 4800 BRAF V600 Mutation Test and the Methods Used in French National Cancer Institute (INCa) Platforms in a Real-Life Setting

PubMed Central

Mourah, Samia; Denis, Marc G.; Narducci, Fabienne Escande; Solassol, Jérôme; Merlin, Jean-Louis; Sabourin, Jean-Christophe; Scoazec, Jean-Yves; Ouafik, L’Houcine; Emile, Jean-François; Heller, Remy; Souvignet, Claude; Bergougnoux, Loïc; Merlio, Jean-Philippe

2015-01-01

Vemurafenib is approved for the treatment of metastatic melanoma in patients with BRAF V600 mutation. In pivotal clinical trials, BRAF testing has always been done with the approved cobas 4800 BRAF test. In routine practice, several methods are available and are used according to the laboratories usual procedures. A national, multicenter, non-interventional study was conducted with prospective and consecutive collection of tumor samples. A parallel evaluation was performed in routine practice between the cobas 4800 BRAF V600 mutation test and home brew methods (HBMs) of 12 national laboratories, labelled and funded by the French National Cancer Institute (INCa). For 420 melanoma samples tested, the cobas method versus HBM showed a high concordance (93.3%; kappa = 0.86) in BRAF V600 genotyping with similar mutation rates (34.0% versus 35.7%, respectively). Overall, 97.4% and 98.6% of samples gave valid results using the cobas and HBM, respectively. Of the 185 samples strictly fulfilling the cobas guidelines, the concordance rate was even higher (95.7%; kappa = 0.91; 95%CI [0.85; 0.97]). Out of the 420 samples tested, 28 (6.7%) showed discordance between HBM and cobas. This prospective study shows a high concordance rate between the cobas 4800 BRAF V600 test and home brew methods in the routine detection of BRAF V600E mutations. PMID:25789737

A pilot study: the development of a culturally tailored Malaysian Diabetes Education Module (MY-DEMO) based on the Health Belief Model.

PubMed

Ahmad, Badariah; Ramadas, Amutha; Kia Fatt, Quek; Md Zain, Anuar Zaini

2014-04-08

Diabetes education and self-care remains the cornerstone of diabetes management. There are many structured diabetes modules available in the United Kingdom, Europe and United States of America. Contrastingly, few structured and validated diabetes modules are available in Malaysia. This pilot study aims to develop and validate diabetes education material suitable and tailored for a multicultural society like Malaysia. The theoretical framework of this module was founded from the Health Belief Model (HBM). The participants were assessed using 6-item pre- and post-test questionnaires that measured some of the known HBM constructs namely cues to action, perceived severity and perceived benefit. Data was analysed using PASW Statistics 18.0. The pre- and post-test questionnaires were administered to 88 participants (31 males). In general, there was a significant increase in the total score in post-test (97.34 ± 6.13%) compared to pre-test (92.80 ± 12.83%) (p < 0.05) and a significant increase in excellent score (>85%) at post-test (84.1%) compared to pre-test (70.5%) (p < 0.05). There was an improvement in post-test score in 4 of 6 items tested. The remaining 2 items which measured the perceived severity and cues to action had poorer post-test score. The preliminary results from this pilot study suggest contextualised content material embedded within MY DEMO maybe suitable for integration with the existing diabetes education programmes. This was the first known validated diabetes education programme available in the Malay language.

Performance of VPIC on Trinity

NASA Astrophysics Data System (ADS)

Nystrom, W. D.; Bergen, B.; Bird, R. F.; Bowers, K. J.; Daughton, W. S.; Guo, F.; Li, H.; Nam, H. A.; Pang, X.; Rust, W. N., III; Wohlbier, J.; Yin, L.; Albright, B. J.

2016-10-01

Trinity is a new major DOE computing resource which is going through final acceptance testing at Los Alamos National Laboratory. Trinity has several new and unique architectural features including two compute partitions, one with dual socket Intel Haswell Xeon compute nodes and one with Intel Knights Landing (KNL) Xeon Phi compute nodes. Additional unique features include use of on package high bandwidth memory (HBM) for the KNL nodes, the ability to configure the KNL nodes with respect to HBM model and on die network topology in a variety of operational modes at run time, and use of solid state storage via burst buffer technology to reduce time required to perform I/O. An effort is in progress to port and optimize VPIC to Trinity and evaluate its performance. Because VPIC was recently released as Open Source, it is being used as part of acceptance testing for Trinity and is participating in the Trinity Open Science Program which has resulted in excellent collaboration activities with both Cray and Intel. Results of this work will be presented on performance of VPIC on both Haswell and KNL partitions for both single node runs and runs at scale. Work performed under the auspices of the U.S. Dept. of Energy by the Los Alamos National Security, LLC Los Alamos National Laboratory under contract DE-AC52-06NA25396 and supported by the LANL LDRD program.

Knowledge, barriers, and motivators related to cervical cancer screening among Korean-American women. A focus group approach.

PubMed

Lee, M C

2000-06-01

Cervical cancer is a significant health problem for Korean-American women. It currently is the number one female cancer diagnosed among women in South Korea. Despite this fact, Korean-American women have very low rates of cervical cancer screening. The purpose of this research were to gain an understanding of Korean women's knowledge about cervical cancer, and to identify major barriers to early screening for cervical cancer and the motivators for prevention and early detection. It is hoped that the findings will guide the development of community-based cervical cancer education and screening programs for adult Korean-American women. The health belief model (HBM) provided the theoretical basis for the study. A qualitative study with eight focus groups (n = 102) was conducted using 11 questions derived from the HBM. Focus group discussions revealed that there was misinformation and a lack of knowledge about cervical cancer. The women therefore were confused about the causative factors and preventive strategies related to cervical cancer. The findings showed that major structural barriers were economic and time factors along with language problems. Many participants were recent immigrants with no medical insurance and long work hours. The main psychosocial barriers were fear/fatalism, denial, and Confucian thinking. Participants stated that medical advice and education would influence them most to undergo a Pap test. Recommendations were made to reduce certain barriers and to increase knowledge and motivations.

Factors associated with perception of risk of contracting HIV among secondary school female learners in Mbonge subdivision of rural Cameroon

PubMed Central

Tarkang, Elvis Enowbeyang

2014-01-01

Introduction Since learners in secondary schools fall within the age group hardest hit by HIV/AIDS, it is obvious that these learners might be at high risk of contracting HIV/AIDS. However, little has been explored on the perception of risk of contracting HIV among secondary school learners in Cameroon. This study aimed at examining the perception of risk of contracting HIV among secondary school learners in Mbonge subdivision of rural Cameroon using the Health Belief Model (HBM) as framework. Methods A quantitative, correlational design was adopted, using a self-administered questionnaire to collect data from 210 female learners selected through disproportional, stratified, simple random sampling technique, from three participating senior secondary schools. Statistics were calculated using SPSS version 20 software program. Results Only 39.4% of the respondents perceived themselves to be at high risk of contracting HIV, though the majority, 54.0% were sexually active. Multinomial logistic regression analyses show that sexual risk behaviours (p=0.000) and the Integrated Value Mapping (IVM) of the perception components of the HBM are the most significant factors associated with perception of risk of contracting HIV at the level p<0.05. Conclusion The findings of this study can play an instrumental role in the development of effective preventive and interventional messages for adolescents in Cameroon. PMID:25309659

Preventing HIV transmission among Iranian prisoners: Initial support for providing education on the benefits of harm reduction practices

PubMed Central

Eshrati, Babak; Asl, Rahim Taghizadeh; Dell, Colleen Anne; Afshar, Parviz; Millson, Peggy Margaret E; Kamali, Mohammad; Weekes, John

2008-01-01

Background Harm reduction is a health-centred approach that seeks to reduce the health and social harms associated with high-risk behaviors, such as illicit drug use. The objective of this study is to determine the association between the beliefs of a group of adult, male prisoners in Iran about the transmission of HIV and their high-risk practices while in prison. Methods A cross-sectional study was conducted in 2004. The study population was a random selection of 100 men incarcerated at Rajaei-Shahr prison. The data were collected through a self-administered questionnaire. Focus group discussions were held at the prison to guide the design of the questionnaire. The relationship between components of the Health Belief Model (HBM) and prisoners' risky HIV-related behaviors was examined. Results Calculating Pearson's correlation coefficient, a significant, positive association was found between the benefit component of the HBM and prisoners not engaging in HIV high-risk behaviors. Conclusion Educational harm reduction initiatives that promote the effectiveness of strategies designed to reduce the risk of HIV transmission may decrease prisoners' high-risk behaviors. This finding provides initial support for the Iran prison system's current offering of HIV/AIDS harm reduction programming and suggests the need to offer increased education about the effectiveness of HIV prevention practices. PMID:18541032

Health Beliefs Describing Patients Enrolling in Community Pharmacy Disease Management Programs.

PubMed

Luder, Heidi; Frede, Stacey; Kirby, James; King, Keith; Heaton, Pamela

2016-08-01

The purpose of this study was to survey new enrollees in a community pharmacy, employer-based diabetes and hypertension coaching program to describe the characteristics, health beliefs, and cues to action of newly enrolled participants. A 70-question, 5-point Likert-type survey was developed using constructs from the Health Belief Model (HBM), Theory of Planned Behavior (TPB), and Theory of Reasoned Action (TRA). New enrollees in the coaching programs completed the survey. Survey responses between controlled and uncontrolled patients and patient demographics were compared. Between November 2011 and November 2012, 154 patients completed the survey. Patients were fairly well controlled with a mean hemoglobin A1C of 7.3% and a mean blood pressure of 134/82 mm Hg. The strongest cue to action for enrollment was the financial incentives offered by the employer (mean: 3.33, median: 4). White patients were significantly more motivated by financial incentives. More patients indicated they had not enrolled previously in the program because they were unaware it was available (mean: 2.89, median 3.0) and these patients were more likely to have an uncontrolled condition (P ≤ 0.050). A top factor motivating patients to enroll in a disease management coaching program was the receipt of financial incentives. Significant differences in HBM, TPB, and TRA responses were seen for patients with different demographics. © The Author(s) 2015.

Predicting motor vehicle collisions using Bayesian neural network models: an empirical analysis.

PubMed

Xie, Yuanchang; Lord, Dominique; Zhang, Yunlong

2007-09-01

Statistical models have frequently been used in highway safety studies. They can be utilized for various purposes, including establishing relationships between variables, screening covariates and predicting values. Generalized linear models (GLM) and hierarchical Bayes models (HBM) have been the most common types of model favored by transportation safety analysts. Over the last few years, researchers have proposed the back-propagation neural network (BPNN) model for modeling the phenomenon under study. Compared to GLMs and HBMs, BPNNs have received much less attention in highway safety modeling. The reasons are attributed to the complexity for estimating this kind of model as well as the problem related to "over-fitting" the data. To circumvent the latter problem, some statisticians have proposed the use of Bayesian neural network (BNN) models. These models have been shown to perform better than BPNN models while at the same time reducing the difficulty associated with over-fitting the data. The objective of this study is to evaluate the application of BNN models for predicting motor vehicle crashes. To accomplish this objective, a series of models was estimated using data collected on rural frontage roads in Texas. Three types of models were compared: BPNN, BNN and the negative binomial (NB) regression models. The results of this study show that in general both types of neural network models perform better than the NB regression model in terms of data prediction. Although the BPNN model can occasionally provide better or approximately equivalent prediction performance compared to the BNN model, in most cases its prediction performance is worse than the BNN model. In addition, the data fitting performance of the BPNN model is consistently worse than the BNN model, which suggests that the BNN model has better generalization abilities than the BPNN model and can effectively alleviate the over-fitting problem without significantly compromising the nonlinear approximation ability. The results also show that BNNs could be used for other useful analyses in highway safety, including the development of accident modification factors and for improving the prediction capabilities for evaluating different highway design alternatives.

Human biomonitoring pilot study DEMOCOPHES in Germany: Contribution to a harmonized European approach.

PubMed

Schwedler, Gerda; Seiwert, Margarete; Fiddicke, Ulrike; Ißleb, Sissy; Hölzer, Jürgen; Nendza, Julia; Wilhelm, Michael; Wittsiepe, Jürgen; Koch, Holger M; Schindler, Birgit K; Göen, Thomas; Hildebrand, Jörg; Joas, Reinhard; Joas, Anke; Casteleyn, Ludwine; Angerer, Jürgen; Castano, Argelia; Esteban, Marta; Schoeters, Greet; Den Hond, Elly; Sepai, Ovnair; Exley, Karen; Bloemen, Louis; Knudsen, Lisbeth E; Kolossa-Gehring, Marike

2017-06-01

Human biomonitoring (HBM) is an effective tool to assess human exposure to environmental pollutants, but comparable HBM data in Europe are lacking. In order to expedite harmonization of HBM studies on a European scale, the twin projects COPHES (Consortium to Perform Human Biomonitoring on a European Scale) and DEMOCOPHES (Demonstration of a study to Coordinate and Perform Human Biomonitoring on a European Scale) were formed, comprising 35 partners from 27 European countries. In COPHES a research scheme and guidelines were developed to exemplarily measure in a pilot study mercury in hair, cadmium, cotinine and several phthalate metabolites in urine of 6-11year old children and their mothers in an urban and a rural region. Seventeen European countries simultaneously conducted this cross-sectional DEMOCOPHES feasibility study. The German study population was taken in the city of Bochum and in the Higher Sauerland District, comprising 120 mother-child pairs. In the present paper features of the study implementation are presented. German exposure concentrations of the pollutants are reported and compared with European average concentrations from DEMOCOPHES and with those measured in the representative German Environmental Survey (GerES IV). German DEMOCOPHES concentrations for mercury and cotinine were lower than the European average. However, 47% of the children were still exposed to environmental tobacco smoke (ETS) outside their home, which gives further potential for enhancing protection of children from ETS. Compared with samples from the other European countries German participating children had lower concentrations of the phthalate metabolites MEP and of the sum of 3 DEHP-metabolites (MEHP, 5OH-MEHP and 5oxo-MEHP), about the same concentrations of the phthalate metabolites MBzP and MiBP and higher concentrations of the phthalate metabolite MnBP. 2.5% of the German children had concentrations of the sum of 4 DEHP-metabolites and 4.2% had concentrations of MnBP that exceeded health based guidance values, indicating reasons for concern. Continuous HBM is necessary to track changes of pollutant exposure over time. Therefore Germany will continue to cooperate on the harmonisation of European human biomonitoring to support the chemicals regulation with the best possible exposure data to protect Europe's people against environmental health risks. Copyright © 2017 The Authors. Published by Elsevier GmbH.. All rights reserved.

Incidence and predictive factors of Internet addiction among Chinese secondary school students in Hong Kong: a longitudinal study.

PubMed

Lau, Joseph T F; Gross, Danielle L; Wu, Anise M S; Cheng, Kit-Man; Lau, Mason M C

2017-06-01

Internet use has global influences on all aspects of life and has become a growing concern. Cross-sectional studies on Internet addiction (IA) have been reported but causality is often unclear. More longitudinal studies are warranted. We investigated incidence and predictors of IA conversion among secondary school students. A 12-month longitudinal study was conducted among Hong Kong Chinese Secondary 1-4 students (N = 8286). Using the 26-item Chen Internet Addiction Scale (CIAS; cut-off >63), non-IA cases were identified at baseline. Conversion to IA during the follow-up period was detected, with incidence and predictors derived using multi-level models. Prevalence of IA was 16.0% at baseline and incidence of IA was 11.81 per 100 person-years (13.74 for males and 9.78 for females). Risk background factors were male sex, higher school forms, and living with only one parent, while protective background factors were having a mother/father with university education. Adjusted for all background factors, higher baseline CIAS score (ORa = 1.07), longer hours spent online for entertainment and social communication (ORa = 1.92 and 1.63 respectively), and Health Belief Model (HBM) constructs (except perceived severity of IA and perceived self-efficacy to reduce use) were significant predictors of conversion to IA (ORa = 1.07-1.45). Prevalence and incidence of IA conversion were high and need attention. Interventions should take into account risk predictors identified, such as those of the HBM, and time management skills should be enhanced. Screening is warranted to identify those at high risk (e.g. high CIAS score) and provide them with primary and secondary interventions.

A pilot study: the development of a culturally tailored Malaysian Diabetes Education Module (MY-DEMO) based on the Health Belief Model

PubMed Central

2014-01-01

Background Diabetes education and self-care remains the cornerstone of diabetes management. There are many structured diabetes modules available in the United Kingdom, Europe and United States of America. Contrastingly, few structured and validated diabetes modules are available in Malaysia. This pilot study aims to develop and validate diabetes education material suitable and tailored for a multicultural society like Malaysia. Methods The theoretical framework of this module was founded from the Health Belief Model (HBM). The participants were assessed using 6-item pre- and post-test questionnaires that measured some of the known HBM constructs namely cues to action, perceived severity and perceived benefit. Data was analysed using PASW Statistics 18.0. Results The pre- and post-test questionnaires were administered to 88 participants (31 males). In general, there was a significant increase in the total score in post-test (97.34 ± 6.13%) compared to pre-test (92.80 ± 12.83%) (p < 0.05) and a significant increase in excellent score (>85%) at post-test (84.1%) compared to pre-test (70.5%) (p < 0.05). There was an improvement in post-test score in 4 of 6 items tested. The remaining 2 items which measured the perceived severity and cues to action had poorer post-test score. Conclusions The preliminary results from this pilot study suggest contextualised content material embedded within MY DEMO maybe suitable for integration with the existing diabetes education programmes. This was the first known validated diabetes education programme available in the Malay language. PMID:24708715

Applying the health belief model to examine news coverage regarding steroids in sports by ABC, CBS, and NBC between March 1990 and May 2008.

PubMed

Quick, Brian L

2010-04-01

The investigation described here examined ABC, CBS, and NBC news coverage of steroids in sports between March 1990 and May 2008. Employing a framing analysis guided by the health belief model (HBM), coverage of the barriers and benefits of using steroids is reported. Overall, the trend by these three news affiliates was to emphasize the illegality of using steroids, whereas considerably less coverage was devoted to the health costs, in terms of both severity and susceptibility, of using steroids. Furthermore, of the health costs reported, the specific consequences of steroid use varied considerably. The results are reported across four timeframes: 1990-2008, 1990-1996, 1997-2002, and 2003-2008.

Farmers’ Intentions to Implement Foot and Mouth Disease Control Measures in Ethiopia

PubMed Central

Jemberu, Wudu T.; Mourits, M. C. M.; Hogeveen, H.

2015-01-01

The objectives of this study were to explore farmers’ intentions to implement foot and mouth disease (FMD) control in Ethiopia, and to identify perceptions about the disease and its control measures that influence these intentions using the Health Belief Model (HBM) framework. Data were collected using questionnaires from 293 farmers in three different production systems. The influence of perceptions on the intentions to implement control measures were analyzed using binary logistic regression. The effect of socio-demographic and husbandry variables on perceptions that were found to significantly influence the intentions were analyzed using ordinal logistic regression. Almost all farmers (99%) intended to implement FMD vaccination free of charge. The majority of farmers in the pastoral (94%) and market oriented (92%) systems also had the intention to implement vaccination with charge but only 42% of the crop-livestock mixed farmers had the intention to do so. Only 2% of pastoral and 18% of crop-livestock mixed farmers had the intention to implement herd isolation and animal movement restriction continuously. These proportions increased to 11% for pastoral and 50% for crop-livestock mixed farmers when the measure is applied only during an outbreak. The majority of farmers in the market oriented system (>80%) had the intention to implement herd isolation and animal movement restriction measure, both continuously and during an outbreak. Among the HBM perception constructs, perceived barrier was found to be the only significant predictor of the intention to implement vaccination. Perceived susceptibility, perceived benefit and perceived barrier were the significant predictors of the intention for herd isolation and animal movement restriction measure. In turn, the predicting perceived barrier on vaccination control varied significantly with the production system and the age of farmers. The significant HBM perception predictors on herd isolation and animal movement restriction control were significantly influenced only by the type of production system. The results of this study indicate that farmers’ intentions to apply FMD control measures are variable among production systems, an insight which is relevant in the development of future control programs. Promotion programs aimed at increasing farmers’ motivation to participate in FMD control by charged vaccination or animal movement restriction should give attention to the perceived barriers influencing the intentions to apply these measures. PMID:26375391

Farmers' Intentions to Implement Foot and Mouth Disease Control Measures in Ethiopia.

PubMed

Jemberu, Wudu T; Mourits, M C M; Hogeveen, H

2015-01-01

The objectives of this study were to explore farmers' intentions to implement foot and mouth disease (FMD) control in Ethiopia, and to identify perceptions about the disease and its control measures that influence these intentions using the Health Belief Model (HBM) framework. Data were collected using questionnaires from 293 farmers in three different production systems. The influence of perceptions on the intentions to implement control measures were analyzed using binary logistic regression. The effect of socio-demographic and husbandry variables on perceptions that were found to significantly influence the intentions were analyzed using ordinal logistic regression. Almost all farmers (99%) intended to implement FMD vaccination free of charge. The majority of farmers in the pastoral (94%) and market oriented (92%) systems also had the intention to implement vaccination with charge but only 42% of the crop-livestock mixed farmers had the intention to do so. Only 2% of pastoral and 18% of crop-livestock mixed farmers had the intention to implement herd isolation and animal movement restriction continuously. These proportions increased to 11% for pastoral and 50% for crop-livestock mixed farmers when the measure is applied only during an outbreak. The majority of farmers in the market oriented system (>80%) had the intention to implement herd isolation and animal movement restriction measure, both continuously and during an outbreak. Among the HBM perception constructs, perceived barrier was found to be the only significant predictor of the intention to implement vaccination. Perceived susceptibility, perceived benefit and perceived barrier were the significant predictors of the intention for herd isolation and animal movement restriction measure. In turn, the predicting perceived barrier on vaccination control varied significantly with the production system and the age of farmers. The significant HBM perception predictors on herd isolation and animal movement restriction control were significantly influenced only by the type of production system. The results of this study indicate that farmers' intentions to apply FMD control measures are variable among production systems, an insight which is relevant in the development of future control programs. Promotion programs aimed at increasing farmers' motivation to participate in FMD control by charged vaccination or animal movement restriction should give attention to the perceived barriers influencing the intentions to apply these measures.

Pediatricians', obstetricians', gynecologists', and family medicine physicians' experiences with and attitudes about breast-feeding.

PubMed

Anchondo, Inés; Berkeley, Lizabeth; Mulla, Zuber D; Byrd, Theresa; Nuwayhid, Bahij; Handal, Gilbert; Akins, Ralitsa

2012-05-01

Investigate physicians' breast-feeding experiences and attitudes using a survey based on two behavioral theories: theory of reasoned action (TRA) and the health belief model (HBM). There were 73 participants included in the investigation. These participants were resident and faculty physicians from pediatrics, obstetrics/gynecology, and family medicine at a university campus, located on the US-Mexico border. The sample was reduced to 53 and 56 records for the attitude and confidence variables, respectively. Physicians answered a survey about their breast-feeding experiences and attitudes to learn about intention and ability applying constructs from TRA and HBM. An attitude scale, confidence variable (from self-efficacy items), and a lactation training index were created for the analysis. Analysis of the association between physicians' breastfeeding experiences and their attitudes revealed physicians are knowledgeable about breast-feeding and have positive attitudes towards breast-feeding. They did not seem to remember how long they breast-fed their children or whether they enjoyed breast-feeding, but they wanted to continue breast-feeding. Physicians cite work as a main reason for not continuing to breast-feed. Physicians' attitudes toward breast-feeding are positive. They are expected to practice health-promotion behavior including breast-feeding; however, physicians' breast-feeding rates are low and although they are knowledgeable about breast-feeding their training lacks on didactic depth and hands-on experience. If physicians learn more about breast-feeding and breast-feed exclusively and successfully, the rates in the United States would increase naturally.

Energetics of the O-H bond and of intramolecular hydrogen bonding in HOC6H4C(O)Y (Y = H, CH3, CH2CH=CH2, C[triple bond]CH, CH2F, NH2, NHCH3, NO2, OH, OCH3, OCN, CN, F, Cl, SH, and SCH3) compounds.

PubMed

Bernardes, Carlos E S; Minas da Piedade, Manuel E

2008-10-09

The energetics of the phenolic O-H bond in a series of 2- and 4-HOC 6H 4C(O)Y (Y = H, CH3, CH 2CH=CH2, C[triple bond]CH, CH2F, NH2, NHCH 3, NO2, OH, OCH3, OCN, CN, F, Cl, SH, and SCH3) compounds and of the intramolecular O...H hydrogen bond in 2-HOC 6H 4C(O)Y, was investigated by using a combination of experimental and theoretical methods. The standard molar enthalpies of formation of 2-hydroxybenzaldehyde (2HBA), 4-hydroxybenzaldehyde (4HBA), 2'-hydroxyacetophenone (2HAP), 2-hydroxybenzamide (2HBM), and 4-hydroxybenzamide (4HBM), at 298.15 K, were determined by micro- or macrocombustion calorimetry. The corresponding enthalpies of vaporization or sublimation were also measured by Calvet drop-calorimetry and Knudsen effusion measurements. The combination of the obtained experimental data led to Delta f H m (o)(2HBA, g) = -238.3 +/- 2.5 kJ.mol (-1), DeltafHm(o)(4HBA, g) = -220.3 +/- 2.0 kJ.mol(-1), Delta f H m (o)(2HAP, g) = -291.8 +/- 2.1 kJ.mol(-1), DeltafHm(o)(2HBM, g) = -304.8 +/- 1.5 kJ.mol (-1), and DeltafHm(o) (4HBM, g) = -278.4 +/- 2.4 kJ.mol (-1). These values, were used to assess the predictions of the B3LYP/6-31G(d,p), B3LYP/6-311+G(d,p), B3LYP/aug-cc-pVDZ, B3P86/6-31G(d,p), B3P86/6-311+G(d,p), B3P86/aug-cc-pVDZ, and CBS-QB3 methods, for the enthalpies of a series of isodesmic gas phase reactions. In general, the CBS-QB3 method was able to reproduce the experimental enthalpies of reaction within their uncertainties. The B3LYP/6-311+G(d,p) method, with a slightly poorer accuracy than the CBS-QB3 approach, achieved the best performance of the tested DFT models. It was further used to analyze the trends of the intramolecular O...H hydrogen bond in 2-HOC 6H 4C(O)Y evaluated by the ortho-para method and to compare the energetics of the phenolic O-H bond in 2- and 4-HOC 6H 4C(O)Y compounds. It was concluded that the O-H bond "strength" is systematically larger for 2-hydroxybenzoyl than for the corresponding 4-hydroxybenzoyl isomers mainly due to the presence of the intramolecular O...H hydrogen bond in the 2-isomers. The observed differences are, however, significantly dependent on the nature of the substituent Y, in particular, when an intramolecular H-bond can be present in the radical obtained upon cleavage of the O-H bond.

Heliotropium bacciferum Forssk. (Boraginaceae) extracts: chemical constituents, antioxidant activity and cytotoxic effect in human cancer cell lines.

PubMed

Aïssaoui, Hanane; Mencherini, Teresa; Esposito, Tiziana; De Tommasi, Nunziatina; Gazzerro, Patrizia; Benayache, Samir; Benayache, Fadila; Mekkiou, Ratiba

2018-02-12

Heliotropium bacciferum (Boraginaceae) is a perennial herb, growing in the Bechar region of Algeria, where it is traditionally used for skin diseases and tonsillitis. Herein, we report the isolation and characterization of sixteen secondary metabolites from the aerial part extracts. They include a sterol (1), megastigman type nor-isoprenoids (2, 3, 4, 6, 8, 10), C-11 terpene lactones (5 and 9), and a monoterpene (7) from the chloroform extract (HB-C); monoterpene glucoside (14), and phenolic compounds (11-13, 15, 16) from the methanol one (HB-M). Their structures were elucidated by spectroscopic methods including 1D and 2D NMR experiments, and ESIMS analysis. HB-M showed a significant and concentration dependent scavenging activity in vitro against the radicals DPPH and ABTS, related to the phenol derivatives (11-13, and 15-16), and HB-C inhibited the growth of colon cancer cell lines, mainly for the presence of the antiproliferative C-11 terpene lactones (5 and 9).

Sum frequency generation (SFG) vibrational spectroscopy of planar phosphatidylethanolamine hybrid bilayer membranes under water.

PubMed

Kett, Peter J N; Casford, Michael T L; Davies, Paul B

2010-06-15

Sum frequency generation (SFG) spectroscopy has been used to study the structure of phosphatidylethanolamine hybrid bilayer membranes (HBMs) under water at ambient temperatures. The HBMs were formed using a modified Langmuir-Schaefer technique and consisted of a layer of dipalmitoyl phosphatidylethanolamine (DPPE) physisorbed onto an octadecanethiol (ODT) self-assembled monolayer (SAM) at a series of surface pressures from 1 to 40 mN m(-1). The DPPE and ODT were selectively deuterated so that the contributions to the SFG spectra from the two layers could be determined separately. SFG spectra in both the C-H and C-D stretching regions confirmed that a monolayer of DPPE had been adsorbed to the ODT SAM and that there were gauche defects within the alkyl chains of the phospholipid. On adsorption of a layer of DPPE, methylene modes from the ODT SAM were detected, indicating that the phospholipid had partially disordered the alkanethiol monolayer. SFG spectra recorded in air indicated that removal of water from the surface of the HBM resulted in disruption of the DPPE layer and the formation of phospholipid bilayers.

Adherence barriers and facilitators for cervical screening amongst currently disadvantaged women in the greater Cape Town region of South Africa

PubMed Central

De Abreu, Chantelle; Horsfall, Hannah

2013-01-01

Abstract Background In South Africa cervical cancer is the second most commonly occurring cancer amongst women, and black African women have the highest risk of developing this disease. Unfortunately, the majority of South African women do not adhere to recommended regular cervical screening. Objectives The purpose of this research was to explore the perceptions, experiences and knowledge regarding cervical screening of disadvantaged women in two informal settlements in South African urban areas. Method The Health Belief Model (HBM) provided a theoretical framework for this study. Four focus groups (n = 21) were conducted, using questions derived from the HBM, and thematic analysis was used to analyse the data. The ages of the women who participated ranged from 21 to 53 years. Results The analysis revealed lack of knowledge about screening as a key structural barrier to treatment. Other structural barriers were: time, age at which free screening is available, and health education. The psychosocial barriers that were identified included: fear of the screening procedure and of the stigmatisation in attending screening. The presence of physical symptoms, the perception that screening provides symptom relief, HIV status, and the desire to know one's physical health status were identified as facilitators of cervical screening adherence. Conclusion This knowledge has the potential to inform healthcare policy and services in South Africa. As globalisation persists and individuals continue to immigrate or seek refugee status in foreign countries, increased understanding and knowledge is required for successful acculturation and integration. Developed countries may therefore also benefit from research findings in developing countries.

Correlates of mammography utilization among working Muslim Iranian women.

PubMed

Hatefnia, Effat; Niknami, Shamsaddin; Bazargan, Mohsen; Mahmoodi, Mahmood; Lamyianm, Minoor; Alavi, Nasrien

2010-06-01

Most countries in Middle East have been successful in establishing and furthering basic facilities for screening, diagnosis, and treatment of breast cancer. The rate of compliance with mammography screening, however, remains well below North American and Western European countries. We utilized the Health Belief Model (HBM) to explore factors associated with mammography screening behavior among a sample of 320 Muslim women aged > or = 35. Carrying out this cross-sectional study, we found that screening behavior was associated with older age, higher perceived benefit of breast cancer screening, and lower perceived barrier. Additionally, we demonstrate the importance of religious beliefs in influencing mammography screening behavior and explaining the link between religious involvement and mammography behavior.

Assessment of Dietary Mercury Intake and Blood Mercury Levels in the Korean Population: Results from the Korean National Environmental Health Survey 2012–2014

PubMed Central

Kim, Seong-Ah; Kwon, YoungMin; Kim, Suejin; Joung, Hyojee

2016-01-01

From a public health perspective, there is growing concern about dietary mercury intake as the most important source of mercury exposure. This study was performed to estimate dietary mercury exposure and to analyze the association between mercury intake and blood mercury levels in Koreans. The study subjects were 553 adults, comprising a 10% representative subsample of the Korean National Environmental Health Survey (KoNEHS) 2012–2014, who completed a health examination, a face-to-face interview, and a three-day food record. Dietary mercury and methylmercury intakes were assessed from the three-day food record, and blood mercury concentration was measured using a mercury analyzer. The association between dietary mercury intake and blood mercury levels was analyzed by comparing the odds ratios for the blood mercury levels above the Human BioMonitoring (HBM) I value (5 μg/L) among the three groups with different mercury intakes. The average total mercury intake was 4.74 and 3.07 μg/day in males and females, respectively. The food group that contributed most to mercury intake was fish and shellfish, accounting for 77.8% of total intake. The geometric mean of the blood mercury concentration significantly and linearly increased with the mercury and methylmercury intakes (p < 0.001). The odds ratios for blood mercury levels above the HBM I value in the highest mercury and methyl mercury intake group were 3.27 (95% Confidence Interval (CI) 1.79–5.95) and 3.20 (95% CI 1.77–5.79) times higher than that of the lowest intake group, respectively. Our results provide compelling evidence that blood mercury level has a strong positive association with dietary intake, and that fish and shellfish contribute most to the dietary mercury exposure. PMID:27598185

The Danish contribution to the European DEMOCOPHES project: A description of cadmium, cotinine and mercury levels in Danish mother-child pairs and the perspectives of supplementary sampling and measurements.

PubMed

Mørck, Thit A; Nielsen, Flemming; Nielsen, Jeanette K S; Jensen, Janne F; Hansen, Pernille W; Hansen, Anne K; Christoffersen, Lea N; Siersma, Volkert D; Larsen, Ida H; Hohlmann, Linette K; Skaanild, Mette T; Frederiksen, Hanne; Biot, Pierre; Casteleyn, Ludwine; Kolossa-Gehring, Marike; Schwedler, Gerda; Castaño, Argelia; Angerer, Jürgen; Koch, Holger M; Esteban, Marta; Schoeters, Greet; Den Hond, Elly; Exley, Karen; Sepai, Ovnair; Bloemen, Louis; Joas, Reinhard; Joas, Anke; Fiddicke, Ulrike; Lopez, Ana; Cañas, Ana; Aerts, Dominique; Knudsen, Lisbeth E

2015-08-01

Human biomonitoring (HBM) is an important tool, increasingly used for measuring true levels of the body burdens of environmental chemicals in the general population. In Europe, a harmonized HBM program was needed to open the possibility to compare levels across borders. To explore the prospect of a harmonized European HBM project, DEMOCOPHES (DEMOnstration of a study to COordinate and Perform Human biomonitoring on a European Scale) was completed in 17 European countries. The basic measurements performed in all implemented countries of DEMOCOPHES included cadmium, cotinine and phthalate metabolites in urine and mercury in hair. In the Danish participants, significant correlations between mothers and children for mercury in hair and cotinine in urine were found. Mercury in hair was further significantly associated with intake of fish and area of residence. Cadmium was positively associated with BMI in mothers and an association between cadmium and cotinine was also found. As expected high cotinine levels were found in smoking mothers. For both mercury and cadmium significantly higher concentrations were found in the mothers compared to their children. In Denmark, the DEMOCOPHES project was co-financed by the Danish ministries of health, environment and food safety. The co-financing ministries agreed to finance a number of supplementary measurements of substances of current toxicological, public and regulatory interest. This also included blood sampling from the participants. The collected urine and blood samples were analyzed for a range of other persistent and non-persistent environmental chemicals as well as two biomarkers of effect. The variety of supplementary measurements gives the researchers further information on the exposure status of the participants and creates a basis for valuable knowledge on the pattern of exposure to various chemicals. Copyright © 2014 Elsevier Inc. All rights reserved.

Identification and isolation from either adult human bone marrow or G-CSF-mobilized peripheral blood of CD34(+)/CD133(+)/CXCR4(+)/ Lin(-)CD45(-) cells, featuring morphological, molecular, and phenotypic characteristics of very small embryonic-like (VSEL) stem cells.

PubMed

Sovalat, Hanna; Scrofani, Maurice; Eidenschenk, Antoinette; Pasquet, Stéphanie; Rimelen, Valérie; Hénon, Philippe

2011-04-01

Recently, we demonstrated that normal human bone marrow (hBM)-derived CD34(+) cells, released into the peripheral blood after granulocyte colony-stimulating factor mobilization, contain cell subpopulations committed along endothelial and cardiac differentiation pathways. These subpopulations could play a key role in the regeneration of post-ischemic myocardial lesion after their direct intracardiac delivery. We hypothesized that these relevant cells might be issued from very small embryonic-like stem cells deposited in the BM during ontogenesis and reside lifelong in the adult BM, and that they could be mobilized into peripheral blood by granulocyte colony-stimulating factor. Samples of normal hBM and leukapheresis products harvested from cancer patients after granulocyte colony-stimulating factor mobilization were analyzed and sorted by multiparameter flow cytometry strategy. Immunofluorescence and reverse transcription quantitative polymerase chain reaction assays were performed to analyze the expression of typical pluripotent stem cells markers. A population of CD34(+)/CD133(+)/CXCR4(+)/Lin(-) CD45(-) immature cells was first isolated from the hBM or from leukapheresis products. Among this population, very small (2-5 μm) cells expressing Oct-4, Nanog, and stage-specific embryonic antigen-4 at protein and messenger RNA levels were identified. Our study supports the hypothesis that very small embryonic-like stem cells constitute a "mobile" pool of primitive/pluripotent stem cells that could be released from the BM into the peripheral blood under the influence of various physiological or pathological stimuli. In order to fully support that hBM- and leukapheresis product-derived very small embryonic-like stem cells are actually pluripotent, we are currently testing their ability to differentiate in vitro into cells from all three germ layers. Copyright © 2011 ISEH - Society for Hematology and Stem Cells. Published by Elsevier Inc. All rights reserved.

Modeling SMAP Spacecraft Attitude Control Estimation Error Using Signal Generation Model

NASA Technical Reports Server (NTRS)

Rizvi, Farheen

2016-01-01

Two ground simulation software are used to model the SMAP spacecraft dynamics. The CAST software uses a higher fidelity model than the ADAMS software. The ADAMS software models the spacecraft plant, controller and actuator models, and assumes a perfect sensor and estimator model. In this simulation study, the spacecraft dynamics results from the ADAMS software are used as CAST software is unavailable. The main source of spacecraft dynamics error in the higher fidelity CAST software is due to the estimation error. A signal generation model is developed to capture the effect of this estimation error in the overall spacecraft dynamics. Then, this signal generation model is included in the ADAMS software spacecraft dynamics estimate such that the results are similar to CAST. This signal generation model has similar characteristics mean, variance and power spectral density as the true CAST estimation error. In this way, ADAMS software can still be used while capturing the higher fidelity spacecraft dynamics modeling from CAST software.

Predictors of Smoking among the Secondary High School Boy Students Based on the Health Belief Model

PubMed Central

Mohammadi, Samira; Ghajari, Haydeh; Valizade, Rohollah; Ghaderi, Naseh; Yousefi, Fayegh; Taymoori, Parvaneh; Nouri, Bejan

2017-01-01

Background: Smoking is one of the most important risk factors for health and also health problems, such as heart diseases, especially for young people. This study aimed to investigate the effect of factors related to smoking among the secondary high school students in the city of Marivan (Kurdistan-Iran), in 2015, based on the constructs of health belief model (HBM). Methods: This cross-sectional study was conducted in 470 secondary high school students in Marivan in 2015. The samples were selected by random cluster sampling. A question with four sections was used to collect data (demographic questions, knowledge section, attitude section, and questions related to e constructs of HBM). Results: According to the results, the correlation of smoking was stronger with attitude (r = 0.269 and odds ratio = 0.89) but weaker with perceived barriers (r = 0.101). There was not a significant correlation between smoking behavior and knowledge of the harms of smoking (r = −0.005). Moreover, Cues to action was effective predictor of smoking behavior (r = 0.259). Conclusions: The findings of this study show that the prevalence of smoking in the studied sample is somewhat lower than other regions of Iran, but it should be noted that if no interventions are done to prevent smoking in this age group. The findings of the study also showed that the structure of attitudes, self-efficacy, and Cues to action are the strongest predictors of smoking among students. Albeit, attitude was strongest predictor of smoking that shows the prevalence of smoking can be reduced by focusing in this part. Considering the mean age of participants (16/2 ± 0.25 years), that shows the riskiest period for smoking is 16 years and authorities can make change in policies of cigarette selling only for over 18 years. PMID:28479966

Psychosocial predictors of breast self-examination behavior among female students: an application of the health belief model using logistic regression.

PubMed

Didarloo, Alireza; Nabilou, Bahram; Khalkhali, Hamid Reza

2017-11-03

Breast cancer is a life-threatening condition affecting women around the world. The early detection of breast lumps using a breast self-examination (BSE) is important for the prevention and control of this disease. The aim of this study was to examine BSE behavior and its predictive factors among female university students using the Health Belief Model (HBM). This investigation was a cross-sectional survey carried out with 334 female students at Urmia University of Medical Sciences in the northwest of Iran. To collect the necessary data, researchers applied a valid and reliable three-part questionnaire. The data were analyzed using descriptive statistics and a chi-square test, in addition to multivariate logistic regression statistics in SPSS software version 16.0 (SPSS Inc., Chicago, IL, USA). The results indicated that 82 of the 334 participants (24.6%) reported practicing BSEs. Multivariate logistic regression analyses showed that high perceived severity [OR = 2.38, 95% CI = (1.02-5.54)], high perceived benefits [OR = 1.94, 95% CI = (1.09-3.46)], and high perceived self-efficacy [OR = 13.15, 95% CI = (3.64-47.51)] were better predictors of BSE behavior (P < 0.05) than low perceived severity, benefits, and self-efficacy. The findings also showed that a high level of knowledge compared to a low level of knowledge [OR = 5.51, 95% CI = (1.79-16.86)] and academic undergraduate and graduate degrees compared to doctoral degrees [OR = 2.90, 95% CI = (1.42-5.92)] of the participants were predictors of BSE performance (P < 0.05). The study revealed that the HBM constructs are able to predict BSE behavior. Among these constructs, self-efficacy was the most important predictor of the behavior. Interventions based on the constructs of perceived self-efficacy, benefits, and severity are recommended for increasing women's regular screening for breast cancer.

Analysis of multiple bone responses to graded strains above functional levels, and to disuse, in mice in vivo show that the human Lrp5 G171V High Bone Mass mutation increases the osteogenic response to loading but that lack of Lrp5 activity reduces it

PubMed Central

Saxon, Leanne K.; Jackson, Brendan F.; Sugiyama, Toshihiro; Lanyon, Lance E.; Price, Joanna S.

2011-01-01

Introduction To investigate the role of the low-density lipoprotein receptor-related protein 5 (Lrp5) in bones' responses to loading, we analysed changes in multiple measures of bone architecture in tibias subjected to loading or disuse in male and female mice with the Lrp5 loss of function mutation (Lrp5−/−) or heterozygous for the Lrp5 G171V High Bone Mass (HBM) mutation (Lrp5HBM+). Materials and methods The right tibias of these 17 week old male and female mice and their Wild Type (WT) littermates were subjected to short periods of loading three days a week for two weeks. Each tibia was loaded for 40 cycles, to produce peak strains at the midshaft within the low, medium or high physiological range (~ 1500, 2400 and 3000 microstrain, respectively). In similar groups of mice the right sciatic nerve was severed causing disuse of the right tibia for 3 weeks. Data from microCT of loaded, neurectomised and contra-lateral control tibias were analysed to quantify changes in the cortical and cancellous regions of the bone in the absence of functional strains and in response to graded strains in addition to those derived from function. Results and conclusion Male WT+/+ controls showed significant strain:response curves for cortical area and trabecular thickness, but Lrp5−/− mice showed no detectable strain:response in those same outcomes. Female mice of either WT+/+ or Lrp5−/− genotype did not show significant strain:response curves for cortical or trabecular parameters, the one exception being Tb.Th in Lrp5−/− mice. Since female WT+/+ mice did not respond to loading in a significant dose:responsive manner, the similar lack of responsiveness of the Lrp5−/− females could not be ascribed to their Lrp5 status. Cortical bone loss associated with disuse showed no differences between Lrp5−/− mice and WT+/+ controls, but in cancellous bone of both male and females of these mice, there was a greater loss than in WT+/+ controls. In contrast, the tibias of male and female mice heterozygous for the Lrp5 G171V HBM mutation showed greater osteogenic responsiveness to loading and less bone loss associated with disuse than their WTHBM− controls. These data indicate that the presence of the Lrp5 G171V HBM mutation is associated with an increased osteogenic response to loading but support only a marginal gender-related role for normal Lrp5 function in this loading-related response. PMID:21419885

Implementing an exercise-training programme to prevent lower-limb injuries: considerations for the development of a randomised controlled trial intervention delivery plan.

PubMed

Finch, Caroline F; White, Peta; Twomey, Dara; Ullah, Shahid

2011-08-01

To identify important considerations for the delivery of an exercise training intervention in a randomised controlled trial to maximise subsequent participation in that randomised controlled trial and intervention uptake. A cross-sectional survey, with a theoretical basis derived from the Health Belief Model (HBM) and the Reach, Efficacy/Effectiveness, Adoption, Implementation and Maintenance (RE-AIM) framework. 374 male senior Australian Football players, aged 17-38 years. Beliefs about lower-limb injury causation/prevention, and the relative value of exercise training for performance and injury prevention. The data are interpreted within HBM constructs and implications for subsequent intervention implementation considered within the RE-AIM framework. Ordinal logistic regression compared belief scores across player characteristics. 74.4% of players agreed that doing specific exercises during training would reduce their risk of lower-limb injury and would be willing to undertake them. However, 64.1% agreed that training should focus more on improving game performance than injury prevention. Younger players (both in terms of age and playing experience) generally had more positive views. Players were most supportive of kicking (98.9%) and ball-handling (97.0%) skills for performance and warm-up runs and cool-downs (both 91.5%) for injury prevention. Fewer than three-quarters of all players believed that balance (69.2%), landing (71.3%) or cutting/stepping (72.8) training had injury-prevention benefits. Delivery of future exercise training programmes for injury prevention aimed at these players should be implemented as part of routine football activities and integrated with those as standard practice, as a means of associating them with training benefits for this sport.

The Impact of Health Education Intervention for Prevention and Early Detection of Type 2 Diabetes in Women with Gestational Diabetes.

PubMed

Tawfik, Mirella Youssef

2017-06-01

This study aims to investigate the impact of a health belief model (HBM)-based educational intervention on knowledge, beliefs, self-reported practices, gestational and postpartum weight in women with gestational diabetes mellitus (GDM). A cluster randomized controlled trial was performed, with randomization at the level of Primary Health Care centers in three Egyptian cities. Eligible women with GDM were enrolled at 24 weeks pregnancy. The intervention group (n = 103) received health education intervention based on the HBM construct. Control subjects (n = 98) received the usual care. The outcomes measured were: women's knowledge, beliefs, self-reported practices, gestational weight gain (GWG), and postpartum weight retention. Patients were investigated at baseline, at end of pregnancy, and at 6 weeks postpartum. After the intervention, percentages of women who had high knowledge and beliefs scores had significantly increased from less than 50 % to more than 70 % in the intervention group (p < 0.001). More women in the intervention group reported practicing exclusive breast feeding (85.4 %) and screening for T2DM (43.7 %) at 6 weeks postpartum compared to the control group (63.3 and 19.4 % respectively) (p < 0.001). More women with excessive body mass index in the intervention group (65 %) compared to the control group (11.6 %) were meeting recommended GWG (p < 0.001), and postpartum weight (37.7, and 20.3 % respectively) (p < 0.01). This intervention significantly improved knowledge, beliefs, self-reported practices, and gestational and postpartum weight in patients with GDM. Further research is needed for investigating the effectiveness of applying early, multi-phase, and longer intervention.

Factors that influence utilisation of HIV/AIDS prevention methods among university students residing at a selected university campus.

PubMed

Ndabarora, Eléazar; Mchunu, Gugu

2014-01-01

Various studies have reported that university students, who are mostly young people, rarely use existing HIV/AIDS preventive methods. Although studies have shown that young university students have a high degree of knowledge about HIV/AIDS and HIV modes of transmission, they are still not utilising the existing HIV prevention methods and still engage in risky sexual practices favourable to HIV. Some variables, such as awareness of existing HIV/AIDS prevention methods, have been associated with utilisation of such methods. The study aimed to explore factors that influence use of existing HIV/AIDS prevention methods among university students residing in a selected campus, using the Health Belief Model (HBM) as a theoretical framework. A quantitative research approach and an exploratory-descriptive design were used to describe perceived factors that influence utilisation by university students of HIV/AIDS prevention methods. A total of 335 students completed online and manual questionnaires. Study findings showed that the factors which influenced utilisation of HIV/AIDS prevention methods were mainly determined by awareness of the existing university-based HIV/AIDS prevention strategies. Most utilised prevention methods were voluntary counselling and testing services and free condoms. Perceived susceptibility and perceived threat of HIV/AIDS score was also found to correlate with HIV risk index score. Perceived susceptibility and perceived threat of HIV/AIDS showed correlation with self-efficacy on condoms and their utilisation. Most HBM variables were not predictors of utilisation of HIV/AIDS prevention methods among students. Intervention aiming to improve the utilisation of HIV/AIDS prevention methods among students at the selected university should focus on removing identified barriers, promoting HIV/AIDS prevention services and providing appropriate resources to implement such programmes.

Is Internet addiction transitory or persistent? Incidence and prospective predictors of remission of Internet addiction among Chinese secondary school students.

PubMed

Lau, Joseph T F; Wu, Anise M S; Gross, Danielle L; Cheng, Kit-Man; Lau, Mason M C

2017-11-01

Internet addiction (IA) is prevalent among adolescents but it is potentially revertible. Only three Taiwan adolescent studies reported IA remission and a few related factors. We investigated incidence and predictors of remission among Hong Kong Chinese secondary school students with a 12-month longitudinal study. IA was defined as Chen Internet Addiction Scale (CIAS) score>63. Validated measures were used to assess students' psychosocial wellbeing at baseline and follow-up. Of 1545 students with IA at baseline, 1296 (83.9%) provided matched baseline/12-month follow-up data; their data were analyzed. Incidence of remission (CIAS≤63 at follow-up) was 59.29/100 person-years. Significant predictors included: 1) baseline CIAS score (ORa=.95), 2) baseline health belief model (HBM) constructs [perception of having severe IA (ORa=.34), perceived susceptibility to IA (ORa=0.82), perceived barrier (ORa=0.95), cue to action from parents (ORa=0.82), and self-efficacy for reducing Internet use (ORa=1.13)], and 3) baseline psychosocial health measures [self-esteem (ORa=1.03), severe depression (ORa=0.72) and social anxiety (ORa=0.96)] and their changes over time [depression (ORa=.95), anxiety (ORa=.94), loneliness (ORa=.93), self-esteem (ORa=1.07), positive affect (ORa=1.10) and family support (ORa=1.03)]. Two-thirds (64.3%) of the remission group presented reduced CIAS score>1.5 SD, and recorded larger improvements in psychosocial status over time than the non-remission group. Without noticeable interventions, incidence of remission was high and related to improvements in psychosocial health. Most of the HBM constructs, and baseline/changes in psychosocial measures predicted remission. Interventions to increase remission should modify these factors. Copyright © 2017 Elsevier Ltd. All rights reserved.

The use of biomarkers to describe plasma-, red cell-, and blood volume from a simple blood test.

PubMed

Lobigs, Louisa Margit; Sottas, Pierre-Edouard; Bourdon, Pitre Collier; Nikolovski, Zoran; El-Gingo, Mohamed; Varamenti, Evdokia; Peeling, Peter; Dawson, Brian; Schumacher, Yorck Olaf

2017-01-01

Plasma volume and red cell mass are key health markers used to monitor numerous disease states, such as heart failure, kidney disease, or sepsis. Nevertheless, there is currently no practically applicable method to easily measure absolute plasma or red cell volumes in a clinical setting. Here, a novel marker for plasma volume and red cell mass was developed through analysis of the observed variability caused by plasma volume shifts in common biochemical measures, selected based on their propensity to present with low variations over time. Once a month for 6 months, serum and whole blood samples were collected from 33 active males. Concurrently, the CO-rebreathing method was applied to determine target levels of hemoglobin mass (HbM) and blood volumes. The variability of 18 common chemistry markers and 27 Full Blood Count variables was investigated and matched to the observed plasma volume variation. After the removal of between-subject variations using a Bayesian model, multivariate analysis identified two sets of 8 and 15 biomarkers explaining 68% and 69% of plasma volume variance, respectively. The final multiparametric model contains a weighting function to allow for isolated abnormalities in single biomarkers. This proof-of-concept investigation describes a novel approach to estimate absolute vascular volumes, with a simple blood test. Despite the physiological instability of critically ill patients, it is hypothesized the model, with its multiparametric approach and weighting function, maintains the capacity to describe vascular volumes. This model has potential to transform volume management in clinical settings. Am. J. Hematol. 92:62-67, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Effects of sociodemographic characteristics and patients' health beliefs on tuberculosis treatment adherence in Ethiopia: a structural equation modelling approach.

PubMed

Tola, Habteyes Hailu; Karimi, Mehrdad; Yekaninejad, Mir Saeed

2017-12-15

Patients' beliefs are a major factor affecting tuberculosis (TB) treatment adherence. However, there has been little use of Health Belief Model (HBM) in determining the pathway effect of patients' sociodemographic characteristics and beliefs on TB treatment adherence. Therefore, this study was aimed at determining the effect of sociodemographic characteristics and patients' health beliefs on TB treatment adherence based on the HBM concept in Ethiopia. A cross-sectional study was conducted in Addis Ababa, Ethiopia among TB patients undertaking treatment. Thirty health centres were randomly selected and one hospital was purposely chosen. Six hundred and ninety-eight TB patients who had been on treatment for 1-2 month, were aged 18 years or above, and had the mental capability to provide consent were enrolled consecutively with non-probability sampling technique from the TB registration book until required sample size achieved. Structured questionnaires were used to collect data. Structural equation modelling was employed to assess the pathway relationship between sociodemographic characteristics, patients' beliefs, and treatment adherence. Of the 698 enrolled participants, 401 (57.4%) were male and 490 (70.2%) were aged 35 years and below. The mean age of participants was 32 (± 11.7) and the age range was 18-90 years. Perceived barrier/benefit was shown to be a significant direct negative effect on TB treatment adherence (ß = -0.124, P = 0.032). In addition, cue to action (ß = -0.68, P ≤ 0.001) and psychological distress (ß = 0.08, P < 0.001) were shown significant indirect effects on TB treatment adherence through perceived barrier/benefit. Interventions intended to decrease perceived barriers and maximize perceived benefits should be implemented to enhance TB treatment adherence. In addition, it is crucial that counselling is incorporated with the regular directly observed therapy program. Motivators (cue to actions) such as friends, family, healthcare workers, and the media could be used to promote TB treatment adherence.

The Effect of Educational Intervention Based on Health Belief Model and Social Support on Promoting Skin Cancer Preventive Behaviors in a Sample of Iranian Farmers.

PubMed

Jeihooni, Ali Khani; Rakhshani, Tayebeh

2018-01-08

Skin cancer is one of the most common cancers in Iran. Farmers are exposed to the sun's ultraviolet radiation due to their job and are susceptible to skin cancer. The aim of this study is to survey the effect of educational intervention based on health belief model and social support on promoting skin cancer preventive behaviors in farmers of Fasa City, Fars province, Iran. In this quasi-experimental study, 200 farmers (100 in experimental group and 100 in control group) in Fasa City, Fars, Iran, were selected in 2017. The educational intervention for the experimental group consisted of eight training sessions (introduction to skin cancer, risk factors, complications, benefits and barriers to proper use of sunscreen, UV sunglasses and physical protection, self-efficacy in applying preventive behaviors, role of social support). A questionnaire consisting of demographic information, knowledge, HBM constructs (perceived susceptibility, severity, benefits, barriers, self-efficacy and cues to action), and social support was used to measure skin cancer preventive behaviors before, 3 months after the intervention, and 6 months later. Data were analyzed using SPSS-22 via chi-squared, independent samples t test, Mann-Whitney, and repeated measures ANOVA at a significance level of 0.5. The mean age of the farmers was 42.21 ± 10.52 years in the experimental group and 44.28 ± 10.16 years in the control group. Three months after the intervention and 6 months after the intervention, the experimental group showed a significant increase in the knowledge, perceived susceptibility, perceived severity, perceived benefits, self-efficacy, cues to action, social support, and skin cancer preventive behaviors compared to the control group. This study showed the effectiveness of the intervention based on the HBM constructs and social support in adoption of skin cancer preventive behaviors in 3 and 6 months post intervention in farmers. Hence, these models can act as a framework for designing and implementing educational interventions for the prevention of skin cancer.

Psychological and Educational Intervention to Improve Tuberculosis Treatment Adherence in Ethiopia Based on Health Belief Model: A Cluster Randomized Control Trial.

PubMed

Tola, Habteyes Hailu; Shojaeizadeh, Davoud; Tol, Azar; Garmaroudi, Gholamreza; Yekaninejad, Mir Saeed; Kebede, Abebaw; Ejeta, Luche Tadesse; Kassa, Desta; Klinkenberg, Eveline

2016-01-01

Treatment non-adherence results in treatment failure, prolonged transmission of disease and emergence of drug resistance. Although the problem widely investigated, there remains an information gap on the effectiveness of different methods to improve treatment adherence and the predictors of non-adherence in resource limited countries based on theoretical models. This study aimed to evaluate the impact of psychological counseling and educational intervention on tuberculosis (TB) treatment adherence based on Health Belief Model (HBM). A cluster randomized control trial was conducted in Addis Ababa from May to December, 2014. Patients were enrolled into study consecutively from 30 randomly selected Health Centers (HCs) (14 HCs intervention and 16 HCs control groups). A total of 698 TB patients, who were on treatment for one month to two months were enrolled. A structured questionnaire was administered to both groups of patients at baseline and endpoint of study. Control participants received routine directly-observed anti-TB therapy and the intervention group additionally received combined psychological counseling and adherence education. Treatment non-adherence level was the main outcome of the study, and multilevel logistic regression was employed to assess the impact of intervention on treatment adherence. At enrollment, the level of non-adherence among intervention (19.4%) and control (19.6%) groups was almost the same. However, after intervention, non-adherence level decreased among intervention group from 19.4 (at baseline) to 9.5% (at endpoint), while it increased among control group from 19.4% (baseline) to 25.4% (endpoint). Psychological counseling and educational interventions resulted in significant difference with regard to non-adherence level between intervention and control groups (Adjusted OR = 0.31, 95% Confidence Interval (CI) (0.18-0.53), p < 0.001)). Psychological counseling and educational interventions, which were guided by HBM, significantly decreased treatment non-adherence level among intervention group. Provision of psychological counseling and health education to TB patients who are on regular treatment is recommended. This could be best achieved if these interventions are guided by behavioral theories and incorporated into the routine TB treatment strategy. Pan African Clinical Trials Registry PACTR201506001175423.

Effect of Education Based on Health Belief Model on the Behavior of Breast Cancer Screening in Women.

PubMed

Masoudiyekta, Leila; Rezaei-Bayatiyani, Hojat; Dashtbozorgi, Bahman; Gheibizadeh, Mahin; Malehi, Amal Saki; Moradi, Mehrnaz

2018-01-01

The purpose of this study was to determine the effect of education based on health belief model (HBM) on the behavior of breast cancer screening (bCS) in women. This quasi-experimental study was conducted on 226 women who were selected with cluster sampling method from those referred to Dezful health centers. Data collection tool was a researcher-made questionnaire. Demographic questionnaire bCS- scale, and the Knowledge about questionnaire, all given before and 3 months after the intervention. According to the findings of the study, there was a significant relationship between women's performance and variables of knowledge, perceived sensitivity, perceived benefits, perceived barriers, self-efficacy, and cues to action. Poor knowledge of women indicates a crucial need for formal educational programs to sensitize women regarding the importance of bCS. These educational programs should consider factors affecting bCS behaviors.

Factors Affecting Intention among Students to Be Vaccinated against A/H1N1 Influenza: A Health Belief Model Approach

PubMed Central

Teitler-Regev, Sharon; Shahrabani, Shosh; Benzion, Uri

2011-01-01

The outbreak of A/H1N1 influenza (henceforth, swine flu) in 2009 was characterized mainly by morbidity rates among young people. This study examined the factors affecting the intention to be vaccinated against the swine flu among students in Israel. Questionnaires were distributed in December 2009 among 387 students at higher-education institutions. The research questionnaire included sociodemographic characteristics and Health Belief Model principles. The results show that the factors positively affecting the intention to take the swine flu vaccine were past experience with seasonal flu shot and three HBM categories: higher levels of perceived susceptibility for catching the illness, perceived seriousness of illness, and lower levels of barriers. We conclude that offering the vaccine at workplaces may raise the intention to take the vaccine among young people in Israel. PMID:22229099

Differential efficacy of human mesenchymal stem cells based on source of origin

PubMed Central

Collins, Erin; Gu, Fei; Qi, Maosong; Molano, Ivan; Ruiz, Phillip; Sun, Linyun; Gilkeson, Gary S.

2014-01-01

Mesenchymal stem cells (MSCs) are useful in tissue repair, but also possess immunomodulatory properties. Murine and uncontrolled human trials suggest efficacy of MSCs in treating lupus. Autologous cells are preferable, however, recent studies suggest that lupus derived MSCs lack efficacy in treating disease. Thus, the optimum derivation of MSCs for use in lupus is unknown. It is also unknown which in vitro assays of MSC function predict in vivo efficacy. The objectives for this study were to provide insight into the optimum source of MSCs and to identify in vitro assays that predict in vivo efficacy. We derived MSCs from four umbilical cords (UC), four healthy bone marrows (HBM) and four lupus bone marrows (LBM). In diseased MRL/lpr mice, MSCs from HBM and UC significantly decreased renal disease, while LBM-MSCs only delayed disease. Current in vitro assays did not differentiate efficacy of the different MSCs. Inhibition of B cell proliferation did differentiate based on efficacy. Our results suggest that autologous MSCs from lupus patients are not effective in treating disease. Furthermore, standard in vitro assays for MSC licensing are not predictive of in vivo efficacy, while inhibiting B cell proliferation appears to differentiate effective from ineffective MSCs. PMID:25274529

Prenatal exposure to lead in France: Cord-blood levels and associated factors: Results from the perinatal component of the French Longitudinal Study since Childhood (Elfe).

PubMed

Saoudi, Abdessattar; Dereumeaux, Clémentine; Goria, Sarah; Berat, Bénédicte; Brunel, Serge; Pecheux, Marie; de Crouy-Chanel, Perrine; Zeghnoun, Abdelkrim; Rambaud, Loïc; Wagner, Vérène; le Tertre, Alain; Fillol, Clémence; Vandentorren, Stéphanie; Guldner, Laurence

2018-04-01

As a result of the ban on lead in gasoline on 2nd January 2000, the French population's exposure to lead has decreased in recent years. However, because of the acknowledged harmful cognitive effects of lead even at low levels, lead exposure remains a major public health issue. In France, few biomonitoring data are available for exposure to lead in pregnant women and newborn. The purpose of the perinatal component of the French human biomonitoring (HBM) program was to describe levels of various biomarkers of exposure to several environmental pollutants, including lead, among mother-baby pairs. In this paper, we aimed to describe the distribution of cord blood lead levels (CBLL) in French mother-baby pairs, and to estimate the contribution of the main lead exposure risk factors to these levels. A total of 1968 mother-baby pairs selected from the participants of the perinatal component of the French HBM program were included in the study on lead. Lead levels were analyzed in cord blood collected at child delivery by inductively coupled plasma-mass spectrometry (ICP-MS). The data collected included biological sample, socio-demographic characteristics, environmental and occupational exposure, and information on dietary factors. CBLL were quantified for 99.5% of the sample. The CBLL geometric mean was 8.30 μg/l (95% CI [7.94-8.68]) with a 95th percentile of 24.3 μg/l (95% CI [20.7-27.1]). Factors significantly associated with CBLL were tap water consumption, alcohol consumption, shellfish consumption, vegetable consumption, bread consumption, smoking, and the mother being born in countries where lead is often used. This study provides the first reference value for CBLL in a random sample of mother-baby pairs not particularly exposed to high levels of lead (24.3 μg/l). A substantial decrease in CBLL over time was observed, which confirms the decrease of exposure to lead among the general population. CBLL observed in this French study were in the range of those found in recent surveys conducted in other countries. Copyright © 2018 Elsevier GmbH. All rights reserved.

Predicting the effectiveness of road safety campaigns through alternative research designs.

PubMed

Adamos, Giannis; Nathanail, Eftihia

2016-12-01

A large number of road safety communication campaigns have been designed and implemented in the recent years; however their explicit impact on driving behavior and road accident rates has been estimated in a rather low proportion. Based on the findings of the evaluation of three road safety communication campaigns addressing the issues of drinking and driving, seat belt usage, and driving fatigue, this paper applies different types of research designs (i.e., experimental, quasi-experimental, and non-experimental designs), when estimating the effectiveness of road safety campaigns, implements a cross-design assessment, and conducts a cross-campaign evaluation. An integrated evaluation plan was developed, taking into account the structure of evaluation questions, the definition of measurable variables, the separation of the target audience into intervention (exposed to the campaign) and control (not exposed to the campaign) groups, the selection of alternative research designs, and the appropriate data collection methods and techniques. Evaluating the implementation of different research designs in estimating the effectiveness of road safety campaigns, results showed that the separate pre-post samples design demonstrated better predictability than other designs, especially in data obtained from the intervention group after the realization of the campaign. The more constructs that were added to the independent variables, the higher the values of the predictability were. The construct that most affects behavior is intention, whereas the rest of the constructs have a lower impact on behavior. This is particularly significant in the Health Belief Model (HBM). On the other hand, behavioral beliefs, normative beliefs, and descriptive norms, are significant parameters for predicting intention according to the Theory of Planned Behavior (TPB). The theoretical and applied implications of alternative research designs and their applicability in the evaluation of road safety campaigns are provided by this study. Copyright © 2016 Elsevier Ltd and National Safety Council. All rights reserved.

Analysis of response to 20 generations of selection for body composition in mice: fit to infinitesimal model assumptions

PubMed Central

Martinez, Victor; Bünger, Lutz; Hill, William G

2000-01-01

Data were analysed from a divergent selection experiment for an indicator of body composition in the mouse, the ratio of gonadal fat pad to body weight (GFPR). Lines were selected for 20 generations for fat (F), lean (L) or were unselected (C), with three replicates of each. Selection was within full-sib families, 16 families per replicate for the first seven generations, eight subsequently. At generation 20, GFPR in the F lines was twice and in the L lines half that of C. A log transformation removed both asymmetry of response and heterogeneity of variance among lines, and so was used throughout. Estimates of genetic variance and heritability (approximately 50%) obtained using REML with an animal model were very similar, whether estimated from the first few generations of selection, or from all 20 generations, or from late generations having fitted pedigree. The estimates were also similar when estimated from selected or control lines. Estimates from REML also agreed with estimates of realised heritability. The results all accord with expectations under the infinitesimal model, despite the four-fold changes in mean. Relaxed selection lines, derived from generation 20, showed little regression in fatness after 40 generations without selection. PMID:14736404

A model for estimation of potential generation of waste electrical and electronic equipment in Brazil

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

Araujo, Marcelo Guimaraes, E-mail: marcel_g@uol.com.br; Magrini, Alessandra; Mahler, Claudio Fernando

2012-02-15

Highlights: Black-Right-Pointing-Pointer Literature of WEEE generation in developing countries is reviewed. Black-Right-Pointing-Pointer We analyse existing estimates of WEEE generation for Brazil. Black-Right-Pointing-Pointer We present a model for WEEE generation estimate. Black-Right-Pointing-Pointer WEEE generation of 3.77 kg/capita year for 2008 is estimated. Black-Right-Pointing-Pointer Use of constant lifetime should be avoided for non-mature market products. - Abstract: Sales of electrical and electronic equipment are increasing dramatically in developing countries. Usually, there are no reliable data about quantities of the waste generated. A new law for solid waste management was enacted in Brazil in 2010, and the infrastructure to treat this waste mustmore » be planned, considering the volumes of the different types of electrical and electronic equipment generated. This paper reviews the literature regarding estimation of waste electrical and electronic equipment (WEEE), focusing on developing countries, particularly in Latin America. It briefly describes the current WEEE system in Brazil and presents an updated estimate of generation of WEEE. Considering the limited available data in Brazil, a model for WEEE generation estimation is proposed in which different methods are used for mature and non-mature market products. The results showed that the most important variable is the equipment lifetime, which requires a thorough understanding of consumer behavior to estimate. Since Brazil is a rapidly expanding market, the 'boom' in waste generation is still to come. In the near future, better data will provide more reliable estimation of waste generation and a clearer interpretation of the lifetime variable throughout the years.« less

Predictors of Bovine TB Risk Behaviour amongst Meat Handlers in Nigeria: A Cross-Sectional Study Guided by the Health Belief Model

PubMed Central

Hambolu, Dupe; Freeman, Jenny; Taddese, Henock B.

2013-01-01

Background Bovine Tuberculosis (bTB) is still a serious public health threat in developing countries. The aim of this study is to determine the social and cognitive factors predicting one of the risk behaviours amongst meat handlers in Nigeria, namely, eating Fuku Elegusi. This is the practice of eating the visibly infected parts of the lung in-order to convince customers to buy meat. The study is guided by the health belief model (HBM). Methods This is a cross-sectional study of 349 randomly selected meat handlers in Oko-Oba Abattoir, in Lagos State. Descriptive statistics and multiple logistic regression analysis were employed to determine perceptions and prevalence of risk behaviours and to identify predictors of eating Fuku Elegusi. Results Just over a quarter (28.1%) of the study participants knew that eating Fuku Elegusi could be a source of bTB in humans. The prevalence of eating Fuku Elegusi was found to be 22%. Across all knowledge indicators related to bTB, those who don't eat Fuku Elegusi exhibited better knowledge. Strong predictors of eating Fuku Elegusi were: being male (OR: 2.39, 95% CI: 1.10 to 5.19; p = 0.03), not knowing that eating Fuku Elegusi exposes to bTB (OR: 3.72, 95% CI: 1.69 to 8.22; p = 0.001), and the perception that one cannot sell meat without tasting it (perceived barrier) (OR: 1.35, 95% CI: 1.13 to 1.60; p = 0.001). Lower risk of eating Fuku Elegusi was predicted by perceived susceptibility to bTB due to another risk behaviour, namely, not washing hands after handling meat (OR: 0.78, 95% CI: 0.64 to 0.96; p-value = 0.021). Television and radio were the most acceptable media for TB prevention messages (78.5% and 75.6% respectively). Conclusion Meat handlers in developing countries bear high risk to bTB owing to prevailing social and cognition determinants. Findings were largely consistent with the propositions of HBM. PMID:23409127

1. Adorni (Cheng 1997a, Sawyer 1981a)

Treesearch

Sheauchi Cheng

2004-01-01

This established RNA is on the Six Rivers National Forest. It lies about 3 miles (5 km) N. of Weitchpec, Humboldt County, covering portions of sects. 25 and 26 T10N, R4E HBM (41°14'N., 123°41'W.), USGS Weitchpec quad (fig. 3). Ecological subsections – Gasquet Mountain Ultramafics (M261Ab) and Eastern Franciscan (M261Ba).

Current Mercury Exposure from Artisanal and Small-Scale Gold Mining in Bombana, Southeast Sulawesi, Indonesia-Future Significant Health Risks.

PubMed

Sakakibara, Masayuki; Sera, Koichiro

2017-02-08

The rapid expansion of the artisanal and small-scale gold mining (ASGM) industry in developing countries has marginalized the local communities in poverty, and resulted in occupational exposure to mercury via the gold extraction process. We investigated the mercury exposure of the mining workers lived inside and outside the mining area. Based on the occupations of the contributors, the hair samples were divided into three subgroups: directly exposed, indirectly exposed, and a control. A total of 81 hair samples were analyzed by particle-induced X-ray emission spectrometry. The median mercury concentration was highest in the hair from the directly exposed group (12.82 μg/g hair) (control group median: 4.8 μg/g hair, p < 0.05), and the concentrations in hair from 45 respondents exceeded the Human Biomonitoring I (HBM I) threshold limit. Mercury concentrations were also elevated in the hair from the indirectly exposed group (median 7.64 μg/g hair, p < 0.05), and concentrations in hair from 24 respondents exceeded the HBM I threshold limits. Exposure to mercury during ASGM presents health risks and is harmful for the miners; mercury is also at hazardous levels for people who live in the mining area but who are not engaged in mercury-based gold extraction.

Concentrations of Environmental Chemicals in Urine and Blood Samples of Children from San Luis Potosí, Mexico.

PubMed

Perez-Maldonado, Ivan N; Ochoa-Martinez, Angeles C; Orta-Garcia, Sandra T; Ruiz-Vera, Tania; Varela-Silva, Jose A

2017-08-01

Human biomonitoring (HBM) is an appreciated tool used to evaluate human exposure to environmental, occupational or lifestyle chemicals. Therefore, the aim of this study was to evaluate the exposure levels for environmental chemicals in urine and blood samples of children from San Luis Potosí, Mexico (SLP). This study identifies environmental chemicals of concern such as: arsenic (45.0 ± 15.0 µg/g creatinine), lead (5.40 ± 2.80 µg/dL), t,t-muconic acid (266 ± 220 µg/g creatinine), 1-hydroxypyrene (0.25 ± 0.15 µmol/mol creatinine), PBDEs (28.0 ± 15.0 ng/g lipid), and PCBs (33.0 ± 16.0 ng/g lipid). On the other hand, low mercury (1.25 ± 1.00 µg/L), hippuric acid (0.38 ± 0.15 µg/g creatinine) and total DDT (130 ± 35 ng/g lipid) exposure levels were found. This preliminary study showed the tool's utility, as the general findings revealed chemicals of concern. Moreover, this screening exhibited the need for HBM in the general population of SLP.

Accuracy of latent-variable estimation in Bayesian semi-supervised learning.

PubMed

Yamazaki, Keisuke

2015-09-01

Hierarchical probabilistic models, such as Gaussian mixture models, are widely used for unsupervised learning tasks. These models consist of observable and latent variables, which represent the observable data and the underlying data-generation process, respectively. Unsupervised learning tasks, such as cluster analysis, are regarded as estimations of latent variables based on the observable ones. The estimation of latent variables in semi-supervised learning, where some labels are observed, will be more precise than that in unsupervised, and one of the concerns is to clarify the effect of the labeled data. However, there has not been sufficient theoretical analysis of the accuracy of the estimation of latent variables. In a previous study, a distribution-based error function was formulated, and its asymptotic form was calculated for unsupervised learning with generative models. It has been shown that, for the estimation of latent variables, the Bayes method is more accurate than the maximum-likelihood method. The present paper reveals the asymptotic forms of the error function in Bayesian semi-supervised learning for both discriminative and generative models. The results show that the generative model, which uses all of the given data, performs better when the model is well specified. Copyright © 2015 Elsevier Ltd. All rights reserved.

Evaluation and application of site-specific data to revise the first-order decay model for estimating landfill gas generation and emissions at Danish landfills.

PubMed

Mou, Zishen; Scheutz, Charlotte; Kjeldsen, Peter

2015-06-01

Methane (CH₄) generated from low-organic waste degradation at four Danish landfills was estimated by three first-order decay (FOD) landfill gas (LFG) generation models (LandGEM, IPCC, and Afvalzorg). Actual waste data from Danish landfills were applied to fit model (IPCC and Afvalzorg) required categories. In general, the single-phase model, LandGEM, significantly overestimated CH₄generation, because it applied too high default values for key parameters to handle low-organic waste scenarios. The key parameters were biochemical CH₄potential (BMP) and CH₄generation rate constant (k-value). In comparison to the IPCC model, the Afvalzorg model was more suitable for estimating CH₄generation at Danish landfills, because it defined more proper waste categories rather than traditional municipal solid waste (MSW) fractions. Moreover, the Afvalzorg model could better show the influence of not only the total disposed waste amount, but also various waste categories. By using laboratory-determined BMPs and k-values for shredder, sludge, mixed bulky waste, and street-cleaning waste, the Afvalzorg model was revised. The revised model estimated smaller cumulative CH₄generation results at the four Danish landfills (from the start of disposal until 2020 and until 2100). Through a CH₄mass balance approach, fugitive CH₄emissions from whole sites and a specific cell for shredder waste were aggregated based on the revised Afvalzorg model outcomes. Aggregated results were in good agreement with field measurements, indicating that the revised Afvalzorg model could provide practical and accurate estimation for Danish LFG emissions. This study is valuable for both researchers and engineers aiming to predict, control, and mitigate fugitive CH₄emissions from landfills receiving low-organic waste. Landfill operators use the first-order decay (FOD) models to estimate methane (CH₄) generation. A single-phase model (LandGEM) and a traditional model (IPCC) could result in overestimation when handling a low-organic waste scenario. Site-specific data were important and capable of calibrating key parameter values in FOD models. The comparison study of the revised Afvalzorg model outcomes and field measurements at four Danish landfills provided a guideline for revising the Pollutants Release and Transfer Registers (PRTR) model, as well as indicating noteworthy waste fractions that could emit CH₄at modern landfills.

Estimating methane emissions from landfills based on rainfall, ambient temperature, and waste composition: The CLEEN model.

PubMed

Karanjekar, Richa V; Bhatt, Arpita; Altouqui, Said; Jangikhatoonabad, Neda; Durai, Vennila; Sattler, Melanie L; Hossain, M D Sahadat; Chen, Victoria

2015-12-01

Accurately estimating landfill methane emissions is important for quantifying a landfill's greenhouse gas emissions and power generation potential. Current models, including LandGEM and IPCC, often greatly simplify treatment of factors like rainfall and ambient temperature, which can substantially impact gas production. The newly developed Capturing Landfill Emissions for Energy Needs (CLEEN) model aims to improve landfill methane generation estimates, but still require inputs that are fairly easy to obtain: waste composition, annual rainfall, and ambient temperature. To develop the model, methane generation was measured from 27 laboratory scale landfill reactors, with varying waste compositions (ranging from 0% to 100%); average rainfall rates of 2, 6, and 12 mm/day; and temperatures of 20, 30, and 37°C, according to a statistical experimental design. Refuse components considered were the major biodegradable wastes, food, paper, yard/wood, and textile, as well as inert inorganic waste. Based on the data collected, a multiple linear regression equation (R(2)=0.75) was developed to predict first-order methane generation rate constant values k as functions of waste composition, annual rainfall, and temperature. Because, laboratory methane generation rates exceed field rates, a second scale-up regression equation for k was developed using actual gas-recovery data from 11 landfills in high-income countries with conventional operation. The Capturing Landfill Emissions for Energy Needs (CLEEN) model was developed by incorporating both regression equations into the first-order decay based model for estimating methane generation rates from landfills. CLEEN model values were compared to actual field data from 6 US landfills, and to estimates from LandGEM and IPCC. For 4 of the 6 cases, CLEEN model estimates were the closest to actual. Copyright © 2015 Elsevier Ltd. All rights reserved.

Modelling ultrasound guided wave propagation for plate thickness measurement

NASA Astrophysics Data System (ADS)

Malladi, Rakesh; Dabak, Anand; Murthy, Nitish Krishna

2014-03-01

Structural Health monitoring refers to monitoring the health of plate-like walls of large reactors, pipelines and other structures in terms of corrosion detection and thickness estimation. The objective of this work is modeling the ultrasonic guided waves generated in a plate. The piezoelectric is excited by an input pulse to generate ultrasonic guided lamb waves in the plate that are received by another piezoelectric transducer. In contrast with existing methods, we develop a mathematical model of the direct component of the signal (DCS) recorded at the terminals of the piezoelectric transducer. The DCS model uses maximum likelihood technique to estimate the different parameters, namely the time delay of the signal due to the transducer delay and amplitude scaling of all the lamb wave modes due to attenuation, while taking into account the received signal spreading in time due to dispersion. The maximum likelihood estimate minimizes the energy difference between the experimental and the DCS model-generated signal. We demonstrate that the DCS model matches closely with experimentally recorded signals and show it can be used to estimate thickness of the plate. The main idea of the thickness estimation algorithm is to generate a bank of DCS model-generated signals, each corresponding to a different thickness of the plate and then find the closest match among these signals to the received signal, resulting in an estimate of the thickness of the plate. Therefore our approach provides a complementary suite of analytics to the existing thickness monitoring approaches.

Theory-based interventions in STIs/HIV Prevention: A systematic review of the literature in Iran

PubMed Central

Latifi, Arman; Merghati-Khoei, Effat; Shojaeizadeh, Davood; Nedjat, Saharnaz; Mehri, Ali; Garmaroudi, Gholamreza

2017-01-01

Background: Various theory-based interventions (TBIs) have been done to prevent STI/HIV. The current study aimed at reviewing the TBIs for STI/HIV prevention in Iran. Methods: We systematically searched 6 English and Persian electronic databases to identify TBIs conducted for STI/HIV prevention in Iran. General searches were conducted using PubMed MeSH terms. Articles were included if they were interventional and conducted using models and theories, aimed at reducing the risk of STIs, were quasi-experimental or experimental, and if their full text was available. Results: Overall, 1042 studies were found. Finally, 13 original studies met our inclusion criteria. The findings indicated that HBM and TPB were the most frequently used theory/models. High school students and drug abusers were the most common target groups in the included studies. Conclusion: The results revealed that the majority of the conducted TBIs contained a methodological weakness. Conducting randomized controlled trials is needed to evaluate the effectiveness of the TBIs.

Developing content for a mHealth intervention to promote postpartum retention in prevention of mother-to-child HIV transmission programs and early infant diagnosis of HIV: a qualitative study.

PubMed

Odeny, Thomas A; Newman, Maya; Bukusi, Elizabeth A; McClelland, R Scott; Cohen, Craig R; Camlin, Carol S

2014-01-01

Maternal attendance at postnatal clinic visits and timely diagnosis of infant HIV infection are important steps for prevention of mother-to-child transmission (PMTCT) of HIV. We aimed to use theory-informed methods to develop text messages targeted at facilitating these steps. We conducted five focus group discussions with health workers and women attending antenatal, postnatal, and PMTCT clinics to explore aspects of women's engagement in postnatal HIV care and infant testing. Discussion topics were informed by constructs of the Health Belief Model (HBM) and prior empirical research. Qualitative data were coded and analyzed according to the construct of the HBM to which they related. Themes were extracted and used to draft intervention messages. We carried out two stages of further messaging development: messages were presented in a follow-up focus group in order to develop optimal phrasing in local languages. We then further refined the messages, pretested them in individual cognitive interviews with selected health workers, and finalized the messages for the intervention. Findings indicated that brief, personalized, caring, polite, encouraging, and educational text messages would facilitate women bringing their children to clinic after delivery, suggesting that text messages may serve as an important "cue to action." Participants emphasized that messages should not mention HIV due to fear of HIV testing and disclosure. Participants also noted that text messages could capitalize on women's motivation to attend clinic for childhood immunizations. Applying a multi-stage content development approach to crafting text messages--informed by behavioral theory--resulted in message content that was consistent across different focus groups. This approach could help answer "why" and "how" text messaging may be a useful tool to support maternal and child health. We are evaluating the effect of these messages on improving postpartum PMTCT retention and infant HIV testing in a randomized trial.

Examination of value of the future and health beliefs to explain dietary and physical activity behaviors.

PubMed

Garza, Kimberly Bosworth; Harris, Carole V; Bolding, Mark S

2013-01-01

Studies have shown a negative association between value of the future (preference for long-term vs. short-term rewards) and harmful addictive behaviors; however, research in the area of preventive behaviors is limited and has shown conflicting results. The primary objectives were: (1) to examine the association among value of the future and diet and physical activity (PA) behaviors, and (2) to assess whether value of the future explained additional variance in behaviors after controlling for theory-based health beliefs related to coronary heart disease (CHD). An online survey was conducted in adults (N = 172) with no prior history of CHD. A delay discounting task was administered to measure value of the future. Questionnaire items were based on the Health Belief Model (HBM) and included CHD knowledge, perceived risk, perceived severity, perceived benefits of and barriers to behavior change, self-efficacy, cues to action, diet and PA behaviors and demographic variables. High value of the future was associated with younger age, lower BMI, more healthful diet, and increased PA. After controlling for HBM components and demographics, value of the future did not explain any additional variance in diet or PA behaviors. Significant predictors of healthful diet included female gender (P = .013), increased age (P = .029), greater than high school education (P = .023), greater diet-related self-efficacy (P = .021), and not having received a healthcare provider recommendation to improve diet (P = .018). Significant predictors of PA level included income between $20,000 and $69,999 (P = .014), greater exercise-related self-efficacy (P < .001) and not having received a healthcare provider recommendation to increase levels of PA (P = .015). Behaviors to prevent CHD may be associated with a person's outlook on the future; however, self-efficacy was a stronger predictor of behavior. These findings support recommendations for enhancement of diet- and PA-related self-efficacy and problem-solving to address myopia in terms of long-term health benefits. Copyright © 2013 Elsevier Inc. All rights reserved.

Is there a single best estimator? selection of home range estimators using area- under- the-curve

USGS Publications Warehouse

Walter, W. David; Onorato, Dave P.; Fischer, Justin W.

2015-01-01

Comparisons of fit of home range contours with locations collected would suggest that use of VHF technology is not as accurate as GPS technology to estimate size of home range for large mammals. Estimators of home range collected with GPS technology performed better than those estimated with VHF technology regardless of estimator used. Furthermore, estimators that incorporate a temporal component (third-generation estimators) appeared to be the most reliable regardless of whether kernel-based or Brownian bridge-based algorithms were used and in comparison to first- and second-generation estimators. We defined third-generation estimators of home range as any estimator that incorporates time, space, animal-specific parameters, and habitat. Such estimators would include movement-based kernel density, Brownian bridge movement models, and dynamic Brownian bridge movement models among others that have yet to be evaluated.

Top-down systems biology integration of conditional prebiotic modulated transgenomic interactions in a humanized microbiome mouse model

PubMed Central

Martin, Francois-Pierre J; Wang, Yulan; Sprenger, Norbert; Yap, Ivan K S; Rezzi, Serge; Ramadan, Ziad; Peré-Trepat, Emma; Rochat, Florence; Cherbut, Christine; van Bladeren, Peter; Fay, Laurent B; Kochhar, Sunil; Lindon, John C; Holmes, Elaine; Nicholson, Jeremy K

2008-01-01

Gut microbiome–host metabolic interactions affect human health and can be modified by probiotic and prebiotic supplementation. Here, we have assessed the effects of consumption of a combination of probiotics (Lactobacillus paracasei or L. rhamnosus) and two galactosyl-oligosaccharide prebiotics on the symbiotic microbiome–mammalian supersystem using integrative metabolic profiling and modeling of multiple compartments in germ-free mice inoculated with a model of human baby microbiota. We have shown specific impacts of two prebiotics on the microbial populations of HBM mice when co-administered with two probiotics. We observed an increase in the populations of Bifidobacterium longum and B. breve, and a reduction in Clostridium perfringens, which were more marked when combining prebiotics with L. rhamnosus. In turn, these microbial effects were associated with modulation of a range of host metabolic pathways observed via changes in lipid profiles, gluconeogenesis, and amino-acid and methylamine metabolism associated to fermentation of carbohydrates by different bacterial strains. These results provide evidence for the potential use of prebiotics for beneficially modifying the gut microbial balance as well as host energy and lipid homeostasis. PMID:18628745

Modelling of a bridge-shaped nonlinear piezoelectric energy harvester

NASA Astrophysics Data System (ADS)

Gafforelli, G.; Xu, R.; Corigliano, A.; Kim, S. G.

2013-12-01

Piezoelectric MicroElectroMechanical Systems (MEMS) energy harvesting is an attractive technology for harvesting small magnitudes of energy from ambient vibrations. Increasing the operating frequency bandwidth of such devices is one of the major issues for real world applications. A MEMS-scale doubly clamped nonlinear beam resonator is designed and developed to demonstrate very wide bandwidth and high power density. In this paper a first complete theoretical discussion of nonlinear resonating piezoelectric energy harvesting is provided. The sectional behaviour of the beam is studied through the Classical Lamination Theory (CLT) specifically modified to introduce the piezoelectric coupling and nonlinear Green-Lagrange strain tensor. A lumped parameter model is built through Rayleigh-Ritz Method and the resulting nonlinear coupled equations are solved in the frequency domain through the Harmonic Balance Method (HBM). Finally, the influence of external load resistance on the dynamic behaviour is studied. The theoretical model shows that nonlinear resonant harvesters have much wider power bandwidth than that of linear resonators but their maximum power is still bounded by the mechanical damping as is the case for linear resonating harvesters.

The Danish contribution to the European DEMOCOPHES project: A description of cadmium, cotinine and mercury levels in Danish mother-child pairs and the perspectives of supplementary sampling and measurements

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

Mørck, Thit A.; Nielsen, Flemming; Nielsen, Jeanette K.S.

Human biomonitoring (HBM) is an important tool, increasingly used for measuring true levels of the body burdens of environmental chemicals in the general population. In Europe, a harmonized HBM program was needed to open the possibility to compare levels across borders. To explore the prospect of a harmonized European HBM project, DEMOCOPHES (DEMOnstration of a study to COordinate and Perform Human biomonitoring on a European Scale) was completed in 17 European countries. The basic measurements performed in all implemented countries of DEMOCOPHES included cadmium, cotinine and phthalate metabolites in urine and mercury in hair. In the Danish participants, significant correlationsmore » between mothers and children for mercury in hair and cotinine in urine were found. Mercury in hair was further significantly associated with intake of fish and area of residence. Cadmium was positively associated with BMI in mothers and an association between cadmium and cotinine was also found. As expected high cotinine levels were found in smoking mothers. For both mercury and cadmium significantly higher concentrations were found in the mothers compared to their children. In Denmark, the DEMOCOPHES project was co-financed by the Danish ministries of health, environment and food safety. The co-financing ministries agreed to finance a number of supplementary measurements of substances of current toxicological, public and regulatory interest. This also included blood sampling from the participants. The collected urine and blood samples were analyzed for a range of other persistent and non-persistent environmental chemicals as well as two biomarkers of effect. The variety of supplementary measurements gives the researchers further information on the exposure status of the participants and creates a basis for valuable knowledge on the pattern of exposure to various chemicals. - Highlights: • Levels of cadmium, mercury and cotinine in the Danish subpopulation are comparable to levels in the total DEMOCOPHES population with mercury in hair above the European median. • Supplementary sample collection and measurements in Denmark gave valuable exposure information on a variety of other chemicals of current toxicological, public and regulatory interest, such as persistent organic pollutants. • It is highly valuable to obtain as much exposure information as possible once you have established the study cohort.« less

A multi-harmonic generalized energy balance method for studying autonomous oscillations of nonlinear conservative systems

NASA Astrophysics Data System (ADS)

Balaji, Nidish Narayanaa; Krishna, I. R. Praveen; Padmanabhan, C.

2018-05-01

The Harmonic Balance Method (HBM) is a frequency-domain based approximation approach used for obtaining the steady state periodic behavior of forced dynamical systems. Intrinsically these systems are non-autonomous and the method offers many computational advantages over time-domain methods when the fundamental period of oscillation is known (generally fixed as the forcing period itself or a corresponding sub-harmonic if such behavior is expected). In the current study, a modified approach, based on He's Energy Balance Method (EBM), is applied to obtain the periodic solutions of conservative systems. It is shown that by this approach, periodic solutions of conservative systems on iso-energy manifolds in the phase space can be obtained very efficiently. The energy level provides the additional constraint on the HBM formulation, which enables the determination of the period of the solutions. The method is applied to the linear harmonic oscillator, a couple of nonlinear oscillators, the elastic pendulum and the Henon-Heiles system. The approach is used to trace the bifurcations of the periodic solutions of the last two, being 2 degree-of-freedom systems demonstrating very rich dynamical behavior. In the process, the advantages offered by the current formulation of the energy balance is brought out. A harmonic perturbation approach is used to evaluate the stability of the solutions for the bifurcation diagram.

Mucopolysaccharidosis enzyme production by bone marrow and dental pulp derived human mesenchymal stem cells.

PubMed

Jackson, Matilda; Derrick Roberts, Ainslie; Martin, Ellenore; Rout-Pitt, Nathan; Gronthos, Stan; Byers, Sharon

2015-04-01

Mucopolysaccharidoses (MPS) are inherited metabolic disorders that arise from a complete loss or a reduction in one of eleven specific lysosomal enzymes. MPS children display pathology in multiple cell types leading to tissue and organ failure and early death. Mesenchymal stem cells (MSCs) give rise to many of the cell types affected in MPS, including those that are refractory to current treatment protocols such as hematopoietic stem cell (HSC) based therapy. In this study we compared multiple MPS enzyme production by bone marrow derived (hBM) and dental pulp derived (hDP) MSCs to enzyme production by HSCs. hBM MSCs produce significantly higher levels of MPS I, II, IIIA, IVA, VI and VII enzyme than HSCs, while hDP MSCs produce significantly higher levels of MPS I, IIIA, IVA, VI and VII enzymes. Higher transfection efficiency was observed in MSCs (89%) compared to HSCs (23%) using a lentiviral vector. Over-expression of four different lysosomal enzymes resulted in up to 9303-fold and up to 5559-fold greater levels in MSC cell layer and media respectively. Stable, persistent transduction of MSCs and sustained over-expression of MPS VII enzyme was observed in vitro. Transduction of MSCs did not affect the ability of the cells to differentiate down osteogenic, adipogenic or chondrogenic lineages, but did partially delay differentiation down the non-mesodermal neurogenic lineage. Copyright © 2015 Elsevier Inc. All rights reserved.

Generating Health Estimates by Zip Code: A Semiparametric Small Area Estimation Approach Using the California Health Interview Survey.

PubMed

Wang, Yueyan; Ponce, Ninez A; Wang, Pan; Opsomer, Jean D; Yu, Hongjian

2015-12-01

We propose a method to meet challenges in generating health estimates for granular geographic areas in which the survey sample size is extremely small. Our generalized linear mixed model predicts health outcomes using both individual-level and neighborhood-level predictors. The model's feature of nonparametric smoothing function on neighborhood-level variables better captures the association between neighborhood environment and the outcome. Using 2011 to 2012 data from the California Health Interview Survey, we demonstrate an empirical application of this method to estimate the fraction of residents without health insurance for Zip Code Tabulation Areas (ZCTAs). Our method generated stable estimates of uninsurance for 1519 of 1765 ZCTAs (86%) in California. For some areas with great socioeconomic diversity across adjacent neighborhoods, such as Los Angeles County, the modeled uninsured estimates revealed much heterogeneity among geographically adjacent ZCTAs. The proposed method can increase the value of health surveys by providing modeled estimates for health data at a granular geographic level. It can account for variations in health outcomes at the neighborhood level as a result of both socioeconomic characteristics and geographic locations.

Dual gait generative models for human motion estimation from a single camera.

PubMed

Zhang, Xin; Fan, Guoliang

2010-08-01

This paper presents a general gait representation framework for video-based human motion estimation. Specifically, we want to estimate the kinematics of an unknown gait from image sequences taken by a single camera. This approach involves two generative models, called the kinematic gait generative model (KGGM) and the visual gait generative model (VGGM), which represent the kinematics and appearances of a gait by a few latent variables, respectively. The concept of gait manifold is proposed to capture the gait variability among different individuals by which KGGM and VGGM can be integrated together, so that a new gait with unknown kinematics can be inferred from gait appearances via KGGM and VGGM. Moreover, a new particle-filtering algorithm is proposed for dynamic gait estimation, which is embedded with a segmental jump-diffusion Markov Chain Monte Carlo scheme to accommodate the gait variability in a long observed sequence. The proposed algorithm is trained from the Carnegie Mellon University (CMU) Mocap data and tested on the Brown University HumanEva data with promising results.

A simple topography-driven, calibration-free runoff generation model

NASA Astrophysics Data System (ADS)

Gao, H.; Birkel, C.; Hrachowitz, M.; Tetzlaff, D.; Soulsby, C.; Savenije, H. H. G.

2017-12-01

Determining the amount of runoff generation from rainfall occupies a central place in rainfall-runoff modelling. Moreover, reading landscapes and developing calibration-free runoff generation models that adequately reflect land surface heterogeneities remains the focus of much hydrological research. In this study, we created a new method to estimate runoff generation - HAND-based Storage Capacity curve (HSC) which uses a topographic index (HAND, Height Above the Nearest Drainage) to identify hydrological similarity and partially the saturated areas of catchments. We then coupled the HSC model with the Mass Curve Technique (MCT) method to estimate root zone storage capacity (SuMax), and obtained the calibration-free runoff generation model HSC-MCT. Both the two models (HSC and HSC-MCT) allow us to estimate runoff generation and simultaneously visualize the spatial dynamic of saturated area. We tested the two models in the data-rich Bruntland Burn (BB) experimental catchment in Scotland with an unusual time series of the field-mapped saturation area extent. The models were subsequently tested in 323 MOPEX (Model Parameter Estimation Experiment) catchments in the United States. HBV and TOPMODEL were used as benchmarks. We found that the HSC performed better in reproducing the spatio-temporal pattern of the observed saturated areas in the BB catchment compared with TOPMODEL which is based on the topographic wetness index (TWI). The HSC also outperformed HBV and TOPMODEL in the MOPEX catchments for both calibration and validation. Despite having no calibrated parameters, the HSC-MCT model also performed comparably well with the calibrated HBV and TOPMODEL, highlighting the robustness of the HSC model to both describe the spatial distribution of the root zone storage capacity and the efficiency of the MCT method to estimate the SuMax. Moreover, the HSC-MCT model facilitated effective visualization of the saturated area, which has the potential to be used for broader geoscience studies beyond hydrology.

Incorporating structure from motion uncertainty into image-based pose estimation

NASA Astrophysics Data System (ADS)

Ludington, Ben T.; Brown, Andrew P.; Sheffler, Michael J.; Taylor, Clark N.; Berardi, Stephen

2015-05-01

A method for generating and utilizing structure from motion (SfM) uncertainty estimates within image-based pose estimation is presented. The method is applied to a class of problems in which SfM algorithms are utilized to form a geo-registered reference model of a particular ground area using imagery gathered during flight by a small unmanned aircraft. The model is then used to form camera pose estimates in near real-time from imagery gathered later. The resulting pose estimates can be utilized by any of the other onboard systems (e.g. as a replacement for GPS data) or downstream exploitation systems, e.g., image-based object trackers. However, many of the consumers of pose estimates require an assessment of the pose accuracy. The method for generating the accuracy assessment is presented. First, the uncertainty in the reference model is estimated. Bundle Adjustment (BA) is utilized for model generation. While the high-level approach for generating a covariance matrix of the BA parameters is straightforward, typical computing hardware is not able to support the required operations due to the scale of the optimization problem within BA. Therefore, a series of sparse matrix operations is utilized to form an exact covariance matrix for only the parameters that are needed at a particular moment. Once the uncertainty in the model has been determined, it is used to augment Perspective-n-Point pose estimation algorithms to improve the pose accuracy and to estimate the resulting pose uncertainty. The implementation of the described method is presented along with results including results gathered from flight test data.

Pedigree-based estimation of covariance between dominance deviations and additive genetic effects in closed rabbit lines considering inbreeding and using a computationally simpler equivalent model.

PubMed

Fernández, E N; Legarra, A; Martínez, R; Sánchez, J P; Baselga, M

2017-06-01

Inbreeding generates covariances between additive and dominance effects (breeding values and dominance deviations). In this work, we developed and applied models for estimation of dominance and additive genetic variances and their covariance, a model that we call "full dominance," from pedigree and phenotypic data. Estimates with this model such as presented here are very scarce both in livestock and in wild genetics. First, we estimated pedigree-based condensed probabilities of identity using recursion. Second, we developed an equivalent linear model in which variance components can be estimated using closed-form algorithms such as REML or Gibbs sampling and existing software. Third, we present a new method to refer the estimated variance components to meaningful parameters in a particular population, i.e., final partially inbred generations as opposed to outbred base populations. We applied these developments to three closed rabbit lines (A, V and H) selected for number of weaned at the Polytechnic University of Valencia. Pedigree and phenotypes are complete and span 43, 39 and 14 generations, respectively. Estimates of broad-sense heritability are 0.07, 0.07 and 0.05 at the base versus 0.07, 0.07 and 0.09 in the final generations. Narrow-sense heritability estimates are 0.06, 0.06 and 0.02 at the base versus 0.04, 0.04 and 0.01 at the final generations. There is also a reduction in the genotypic variance due to the negative additive-dominance correlation. Thus, the contribution of dominance variation is fairly large and increases with inbreeding and (over)compensates for the loss in additive variation. In addition, estimates of the additive-dominance correlation are -0.37, -0.31 and 0.00, in agreement with the few published estimates and theoretical considerations. © 2017 Blackwell Verlag GmbH.

Assessment of the Value, Impact, and Validity of the Jobs and Economic Development Impacts (JEDI) Suite of Models

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

Billman, L.; Keyser, D.

The Jobs and Economic Development Impacts (JEDI) models, developed by the National Renewable Energy Laboratory (NREL) for the U.S. Department of Energy (DOE) Office of Energy Efficiency and Renewable Energy (EERE), use input-output methodology to estimate gross (not net) jobs and economic impacts of building and operating selected types of renewable electricity generation and fuel plants. This analysis provides the DOE with an assessment of the value, impact, and validity of the JEDI suite of models. While the models produce estimates of jobs, earnings, and economic output, this analysis focuses only on jobs estimates. This validation report includes an introductionmore » to JEDI models, an analysis of the value and impact of the JEDI models, and an analysis of the validity of job estimates generated by JEDI model through comparison to other modeled estimates and comparison to empirical, observed jobs data as reported or estimated for a commercial project, a state, or a region.« less

Fusion of Hard and Soft Information in Nonparametric Density Estimation

DTIC Science & Technology

2015-06-10

and stochastic optimization models, in analysis of simulation output, and when instantiating probability models. We adopt a constrained maximum...particular, density estimation is needed for generation of input densities to simulation and stochastic optimization models, in analysis of simulation output...an essential step in simulation analysis and stochastic optimization is the generation of probability densities for input random variables; see for

Modelling the initial phase of an epidemic using incidence and infection network data: 2009 H1N1 pandemic in Israel as a case study

PubMed Central

Katriel, G.; Yaari, R.; Huppert, A.; Roll, U.; Stone, L.

2011-01-01

This paper presents new computational and modelling tools for studying the dynamics of an epidemic in its initial stages that use both available incidence time series and data describing the population's infection network structure. The work is motivated by data collected at the beginning of the H1N1 pandemic outbreak in Israel in the summer of 2009. We formulated a new discrete-time stochastic epidemic SIR (susceptible-infected-recovered) model that explicitly takes into account the disease's specific generation-time distribution and the intrinsic demographic stochasticity inherent to the infection process. Moreover, in contrast with many other modelling approaches, the model allows direct analytical derivation of estimates for the effective reproductive number (Re) and of their credible intervals, by maximum likelihood and Bayesian methods. The basic model can be extended to include age–class structure, and a maximum likelihood methodology allows us to estimate the model's next-generation matrix by combining two types of data: (i) the incidence series of each age group, and (ii) infection network data that provide partial information of ‘who-infected-who’. Unlike other approaches for estimating the next-generation matrix, the method developed here does not require making a priori assumptions about the structure of the next-generation matrix. We show, using a simulation study, that even a relatively small amount of information about the infection network greatly improves the accuracy of estimation of the next-generation matrix. The method is applied in practice to estimate the next-generation matrix from the Israeli H1N1 pandemic data. The tools developed here should be of practical importance for future investigations of epidemics during their initial stages. However, they require the availability of data which represent a random sample of the real epidemic process. We discuss the conditions under which reporting rates may or may not influence our estimated quantities and the effects of bias. PMID:21247949

Estimation of future outflows of e-waste in India.

PubMed

Dwivedy, Maheshwar; Mittal, R K

2010-03-01

The purpose of this study is to construct an approach and a methodology to estimate the future outflows of electronic waste (e-waste) in India. Consequently, the study utilizes a time-series multiple lifespan end-of-life model proposed by Peralta and Fontanos for estimating the current and future quantities of e-waste in India. The model estimates future e-waste generation quantities by modeling their usage and disposal. The present work considers two scenarios for the approximation of e-waste generation based on user preferences to store or to recycle the e-waste. This model will help formal recyclers in India to make strategic decisions in planning for appropriate recycling infrastructure and institutional capacity building. Also an extension of the model proposed by Peralta and Fontanos is developed with the objective of helping decision makers to conduct WEEE estimates under a variety of assumptions to suit their region of study. During 2007-2011, the total WEEE estimates will be around 2.5 million metric tons which include waste from personal computers (PC), television, refrigerators and washing machines. During the said period, the waste from PC will account for 30% of total units of WEEE generated. Copyright 2009 Elsevier Ltd. All rights reserved.

Estimation of future outflows of e-waste in India

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

Dwivedy, Maheshwar, E-mail: dwivedy_m@bits-pilani.ac.i; Mittal, R.K.

2010-03-15

The purpose of this study is to construct an approach and a methodology to estimate the future outflows of electronic waste (e-waste) in India. Consequently, the study utilizes a time-series multiple lifespan end-of-life model proposed by Peralta and Fontanos for estimating the current and future quantities of e-waste in India. The model estimates future e-waste generation quantities by modeling their usage and disposal. The present work considers two scenarios for the approximation of e-waste generation based on user preferences to store or to recycle the e-waste. This model will help formal recyclers in India to make strategic decisions in planningmore » for appropriate recycling infrastructure and institutional capacity building. Also an extension of the model proposed by Peralta and Fontanos is developed with the objective of helping decision makers to conduct WEEE estimates under a variety of assumptions to suit their region of study. During 2007-2011, the total WEEE estimates will be around 2.5 million metric tons which include waste from personal computers (PC), television, refrigerators and washing machines. During the said period, the waste from PC will account for 30% of total units of WEEE generated.« less

Parents’ Perception and their Decision on their Children's Vaccination Against Seasonal Influenza in Guangzhou

PubMed Central

He, Lei; Liao, Qiu-Yan; Huang, You-Qi; Feng, Shuo; Zhuang, Xiao-Ming

2015-01-01

Background: Seasonal influenza epidemic occurs every year in Guangzhou, which can affect all age groups. Young children are the most susceptible targets. Parents can decide whether to vaccinate their children or not based on their own consideration in China. The aim of this study was to identify factors that are important for parental decisions on vaccinating their children against seasonal influenza based on a modified health belief model (HBM). Methods: A cross-sectional study was conducted in Guangzhou, China. A total of 335 parents who had at least on child aged between 6 months and 3 years were recruited from women and children's hospital in Guangzhou, China. Each eligible subject was invited for a face-to-face interview based on a standardized questionnaire. Results: Uptake of seasonal influenza within the preceding 12 months among the target children who aged between 6 months and 36 months was 47.7%. Around 62.4% parents indicated as being “likely/very likely” to take their children for seasonal influenza vaccination in the next 12 months. The hierarchical logistic regression model showed that children's age (odds ratio [OR] =2.59, 95% confidence interval [CI]: 1.44–4.68), social norm (OR = 2.08, 95% CI: 1.06–4.06) and perceived control (OR = 2.96, 95% CI: 1.60–5.50) were significantly and positively associated with children's vaccination uptake within the preceding 12 months; children with a history of taking seasonal influenza vaccine (OR = 2.50, 95% CI: 1.31–4.76), perceived children's health status (OR = 3.36, 95% CI: 1.68–6.74), worry/anxious about their children influenza infection (OR = 2.31, 95% CI: 1.19–4.48) and perceived control (OR = 3.21, 95% CI: 1.65–6.22) were positively association with parental intention to vaccinate their children in the future 12 months. However, anticipated more regret about taking children for the vaccination was associated with less likely to vaccinate children within the preceding 12 months (OR = 0.21, 95% CI: 0.08–0.52). Conclusions: The modified HBM provided a good theoretical basic for understanding factors associated with parents’ decisions on their children's vaccination against seasonal influenza. PMID:25635428

Parameter estimation of the Farquhar-von Caemmerer-Berry biochemical model from photosynthetic carbon dioxide response curves

USDA-ARS?s Scientific Manuscript database

The methods of Sharkey and Gu for estimating the eight parameters of the Farquhar-von Caemmerer-Berry (FvBC) model were examined using generated photosynthesis versus intercellular carbon dioxide concentration (A/Ci) datasets. The generated datasets included data with (A) high accuracy, (B) normal ...

Regional air quality impacts of increased natural gas production and use in Texas.

PubMed

Pacsi, Adam P; Alhajeri, Nawaf S; Zavala-Araiza, Daniel; Webster, Mort D; Allen, David T

2013-04-02

Natural gas use in electricity generation in Texas was estimated, for gas prices ranging from $1.89 to $7.74 per MMBTU, using an optimal power flow model. Hourly estimates of electricity generation, for individual electricity generation units, from the model were used to estimate spatially resolved hourly emissions from electricity generation. Emissions from natural gas production activities in the Barnett Shale region were also estimated, with emissions scaled up or down to match demand in electricity generation as natural gas prices changed. As natural gas use increased, emissions decreased from electricity generation and increased from natural gas production. Overall, NOx and SO2 emissions decreased, while VOC emissions increased as natural gas use increased. To assess the effects of these changes in emissions on ozone and particulate matter concentrations, spatially and temporally resolved emissions were used in a month-long photochemical modeling episode. Over the month-long photochemical modeling episode, decreases in natural gas prices typical of those experienced from 2006 to 2012 led to net regional decreases in ozone (0.2-0.7 ppb) and fine particulate matter (PM) (0.1-0.7 μg/m(3)). Changes in PM were predominantly due to changes in regional PM sulfate formation. Changes in regional PM and ozone formation are primarily due to decreases in emissions from electricity generation. Increases in emissions from increased natural gas production were offset by decreasing emissions from electricity generation for all the scenarios considered.

Theory-based interventions for contraception.

PubMed

Lopez, Laureen M; Tolley, Elizabeth E; Grimes, David A; Chen, Mario; Stockton, Laurie L

2013-08-07

The explicit use of theory in research helps expand the knowledge base. Theories and models have been used extensively in HIV-prevention research and in interventions for preventing sexually transmitted infections (STIs). The health behavior field uses many theories or models of change. However, educational interventions addressing contraception often have no stated theoretical base. Review randomized controlled trials (RCTs) that tested a theoretical approach to inform contraceptive choice; encourage contraceptive use; or promote adherence to, or continuation of, a contraceptive regimen. Through June 2013, we searched computerized databases for trials that tested a theory-based intervention for improving contraceptive use (MEDLINE, POPLINE, CENTRAL, PsycINFO, ClinicalTrials.gov, and ICTRP). Previous searches also included EMBASE. For the initial review, we wrote to investigators to find other trials. Trials tested a theory-based intervention for improving contraceptive use. We excluded trials focused on high-risk groups and preventing sexually transmitted infections or HIV. Interventions addressed the use of one or more contraceptive methods for contraception. The reports provided evidence that the intervention was based on a specific theory or model. The primary outcomes were pregnancy, contraceptive choice or use, and contraceptive adherence or continuation. The primary author evaluated abstracts for eligibility. Two authors extracted data from included studies. For the dichotomous outcomes, the Mantel-Haenszel odds ratio (OR) with 95% CI was calculated using a fixed-effect model. Cluster randomized trials used various methods of accounting for the clustering, such as multilevel modeling. Most reports did not provide information to calculate the effective sample size. Therefore, we presented the results as reported by the investigators. No meta-analysis was conducted due to differences in interventions and outcome measures. We included three new trials for a total of 17. Ten randomly assigned individuals and seven were cluster-randomized. Eight trials showed some intervention effect.Two of 12 trials with pregnancy or birth data showed some effect. A theory-based group was less likely than the comparison group to have a second birth (OR 0.41; 95% CI 0.17 to 1.00) or to report a pregnancy (OR 0.24 (95% CI 0.10 to 0.56); OR 0.27 (95% CI 0.11 to 0.66)). The theoretical bases were social cognitive theory (SCT) and another social cognition model.Of 12 trials with data on contraceptive use (non-condom), six showed some effect. A theory-based group was more likely to consistently use oral contraceptives (OR 1.41; 95% CI 1.06 to 1.87), hormonal contraceptives (reported relative risk (RR) 1.30; 95% CI 1.06 to 1.58) or dual methods (reported RR 1.36; 95% CI 1.01 to 1.85); to use an effective contraceptive method (reported effect size 1.76; OR 2.04 (95% CI 1.47 to 2.83)) or use more habitual contraception (reported P < 0.05); and were less likely to use ineffective contraception (OR 0.56; 95% CI 0.31 to 0.98). Theories and models included the Health Belief Model (HBM), SCT, SCT plus another theory, other social cognition, and motivational interviewing (MI).For condom use, a theory-based group had favorable results in 5 of 11 trials. The main differences were reporting more consistent condom use (reported RR 1.57; 95% CI 1.28 to 1.94) and more condom use during last sex (reported results: risk ratio 1.47 (95% CI 1.12 to 1.93); effect size 1.68; OR 2.12 (95% CI 1.24 to 3.56); OR 1.45 (95% CI 1.03 to 2.03)). The theories were SCT, SCT plus another theory, and HBM.Nearly all trials provided multiple sessions or contacts. SCT provided the basis for seven trials focused on adolescents, of which five reported some effectiveness. Two others based on other social cognition models had favorable results with adolescents. Of six trials including adult women, five provided individual sessions. Some effect was seen in two using MI and one using the HBM. Two based on the Transtheoretical Model did not show any effect. Eight trials provided evidence of high or moderate quality. Family planning researchers and practitioners could adapt the effective interventions, although most provided group sessions for adolescents. Three were conducted outside the USA. Clinics and low-resource settings need high-quality evidence on changing behavior. Thorough use of single theories would help in identifying what works, as would better reporting on research design and intervention implementation.

Shared Mechanisms in the Estimation of Self-Generated Actions and the Prediction of Other's Actions by Humans.

PubMed

Ikegami, Tsuyoshi; Ganesh, Gowrishankar

2017-01-01

The question of how humans predict outcomes of observed motor actions by others is a fundamental problem in cognitive and social neuroscience. Previous theoretical studies have suggested that the brain uses parts of the forward model (used to estimate sensory outcomes of self-generated actions) to predict outcomes of observed actions. However, this hypothesis has remained controversial due to the lack of direct experimental evidence. To address this issue, we analyzed the behavior of darts experts in an understanding learning paradigm and utilized computational modeling to examine how outcome prediction of observed actions affected the participants' ability to estimate their own actions. We recruited darts experts because sports experts are known to have an accurate outcome estimation of their own actions as well as prediction of actions observed in others. We first show that learning to predict the outcomes of observed dart throws deteriorates an expert's abilities to both produce his own darts actions and estimate the outcome of his own throws (or self-estimation). Next, we introduce a state-space model to explain the trial-by-trial changes in the darts performance and self-estimation through our experiment. The model-based analysis reveals that the change in an expert's self-estimation is explained only by considering a change in the individual's forward model, showing that an improvement in an expert's ability to predict outcomes of observed actions affects the individual's forward model. These results suggest that parts of the same forward model are utilized in humans to both estimate outcomes of self-generated actions and predict outcomes of observed actions.

Electron-hole pairs generation rate estimation irradiated by isotope Nickel-63 in silicone using GEANT4

NASA Astrophysics Data System (ADS)

Kovalev, I. V.; Sidorov, V. G.; Zelenkov, P. V.; Khoroshko, A. Y.; Lelekov, A. T.

2015-10-01

To optimize parameters of beta-electrical converter of isotope Nickel-63 radiation, model of the distribution of EHP generation rate in semiconductor must be derived. By using Monte-Carlo methods in GEANT4 system with ultra-low energy electron physics models this distribution in silicon calculated and approximated with Gauss function. Maximal efficient isotope layer thickness and maximal energy efficiency of EHP generation were estimated.

Kalman filter estimation of human pilot-model parameters

NASA Technical Reports Server (NTRS)

Schiess, J. R.; Roland, V. R.

1975-01-01

The parameters of a human pilot-model transfer function are estimated by applying the extended Kalman filter to the corresponding retarded differential-difference equations in the time domain. Use of computer-generated data indicates that most of the parameters, including the implicit time delay, may be reasonably estimated in this way. When applied to two sets of experimental data obtained from a closed-loop tracking task performed by a human, the Kalman filter generated diverging residuals for one of the measurement types, apparently because of model assumption errors. Application of a modified adaptive technique was found to overcome the divergence and to produce reasonable estimates of most of the parameters.

The effectiveness of nutrition education: Applying the Health Belief Model in child-feeding practices to use pulses for complementary feeding in Southern Ethiopia.

PubMed

Mulualem, Demmelash; Henry, Carol J; Berhanu, Getenesh; Whiting, Susan J

2016-01-01

Complementary foods (CFs) in Ethiopia are cereal based and adding locally grown pulses (legumes) to CF would provide needed nutrients. To assess the effects of nutrition education (NEd) using Health Belief Model (HBM) in promoting pulses for CF, a 6-month quasi-experimental study was conducted in 160 mother-child pairs. Knowledge, attitude, and practice (KAP) questions were given to mothers at baseline, midline, and endline, along with anthropometric measurements of children. NEd involving discussions and recipe demonstrations was given twice monthly for 6 months to the intervention group (n = 80) while control mothers received usual education. At baseline, mothers' KAP scores were low at both sites; at 3 and 6 months of NEd, mean KAP scores of mothers increased (p < 0.05) compared to the control site. Significant improvements in children's mean weight, weight for height, and weight for age occurred in the intervention site only. Nutritional status of children improved after providing mothers with pulse-based NEd.

WE-D-303-02: Applications of Volumetric Images Generated with a Respiratory Motion Model Based On An External Surrogate Signal

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

Hurwitz, M; Williams, C; Dhou, S

Purpose: Respiratory motion can vary significantly over the course of simulation and treatment. Our goal is to use volumetric images generated with a respiratory motion model to improve the definition of the internal target volume (ITV) and the estimate of delivered dose. Methods: Ten irregular patient breathing patterns spanning 35 seconds each were incorporated into a digital phantom. Ten images over the first five seconds of breathing were used to emulate a 4DCT scan, build the ITV, and generate a patient-specific respiratory motion model which correlated the measured trajectories of markers placed on the patients’ chests with the motion ofmore » the internal anatomy. This model was used to generate volumetric images over the subsequent thirty seconds of breathing. The increase in the ITV taking into account the full 35 seconds of breathing was assessed with ground-truth and model-generated images. For one patient, a treatment plan based on the initial ITV was created and the delivered dose was estimated using images from the first five seconds as well as ground-truth and model-generated images from the next 30 seconds. Results: The increase in the ITV ranged from 0.2 cc to 6.9 cc for the ten patients based on ground-truth information. The model predicted this increase in the ITV with an average error of 0.8 cc. The delivered dose to the tumor (D95) changed significantly from 57 Gy to 41 Gy when estimated using 5 seconds and 30 seconds, respectively. The model captured this effect, giving an estimated D95 of 44 Gy. Conclusion: A respiratory motion model generating volumetric images of the internal patient anatomy could be useful in estimating the increase in the ITV due to irregular breathing during simulation and in assessing delivered dose during treatment. This project was supported, in part, through a Master Research Agreement with Varian Medical Systems, Inc. and Radiological Society of North America Research Scholar Grant #RSCH1206.« less

National Assessment of Energy Storage for Grid Balancing and Arbitrage: Phase 1, WECC

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

Kintner-Meyer, Michael CW; Balducci, Patrick J.; Colella, Whitney G.

2012-06-01

To examine the role that energy storage could play in mitigating the impacts of the stochastic variability of wind generation on regional grid operation, the Pacific Northwest National Laboratory (PNNL) examined a hypothetical 2020 grid scenario in which additional wind generation capacity is built to meet renewable portfolio standard targets in the Western Interconnection. PNNL developed a stochastic model for estimating the balancing requirements using historical wind statistics and forecasting error, a detailed engineering model to analyze the dispatch of energy storage and fast-ramping generation devices for estimating size requirements of energy storage and generation systems for meeting new balancingmore » requirements, and financial models for estimating the life-cycle cost of storage and generation systems in addressing the future balancing requirements for sub-regions in the Western Interconnection. Evaluated technologies include combustion turbines, sodium sulfur (Na-S) batteries, lithium ion batteries, pumped-hydro energy storage, compressed air energy storage, flywheels, redox flow batteries, and demand response. Distinct power and energy capacity requirements were estimated for each technology option, and battery size was optimized to minimize costs. Modeling results indicate that in a future power grid with high-penetration of renewables, the most cost competitive technologies for meeting balancing requirements include Na-S batteries and flywheels.« less

Municipal solid waste characterization and its assessment for potential methane generation: a case study.

PubMed

Mor, Suman; Ravindra, Khaiwal; De Visscher, Alex; Dahiya, R P; Chandra, A

2006-12-01

There has been a significant increase in municipal solid waste (MSW) generation in India during the last few decades and its management has become a major issue because the poor waste management practices affect the health and amenity of the cities. In the present study, various physico-chemical parameters of the MSW were analyzed to characterize the waste dumped at Gazipur landfill site in Delhi, India, which shows that it contains a high fraction of degradable organic components. The decomposition of organic components produces methane, a significant contributor to global warming. Based on the waste composition, waste age and the total amount dumped, a first-order decay model (FOD) was applied to estimate the methane generation potential of the Gazipur landfill site, which yields an estimate of 15.3 Gg/year. This value accounts to about 1-3% of existing Indian landfill methane emission estimates. Based on the investigation of Gazipur landfill, we estimate Indian landfill methane emissions at 1.25 Tg/year or 1.68 Tg/year of methane generation potential. These values are within the range of existing estimates. A comparison of FOD with a recently proposed triangular model was also performed and it shows that both models can be used for the estimation of methane generation. However, the decrease of the emission after closure is more gradual in the case of the first-order model, leading to larger gas production predictions after more than 10 years of closure. The regional and global implications of national landfill methane emission are also discussed.

Shared Mechanisms in the Estimation of Self-Generated Actions and the Prediction of Other’s Actions by Humans

PubMed Central

Ganesh, Gowrishankar

2017-01-01

Abstract The question of how humans predict outcomes of observed motor actions by others is a fundamental problem in cognitive and social neuroscience. Previous theoretical studies have suggested that the brain uses parts of the forward model (used to estimate sensory outcomes of self-generated actions) to predict outcomes of observed actions. However, this hypothesis has remained controversial due to the lack of direct experimental evidence. To address this issue, we analyzed the behavior of darts experts in an understanding learning paradigm and utilized computational modeling to examine how outcome prediction of observed actions affected the participants’ ability to estimate their own actions. We recruited darts experts because sports experts are known to have an accurate outcome estimation of their own actions as well as prediction of actions observed in others. We first show that learning to predict the outcomes of observed dart throws deteriorates an expert’s abilities to both produce his own darts actions and estimate the outcome of his own throws (or self-estimation). Next, we introduce a state-space model to explain the trial-by-trial changes in the darts performance and self-estimation through our experiment. The model-based analysis reveals that the change in an expert’s self-estimation is explained only by considering a change in the individual’s forward model, showing that an improvement in an expert’s ability to predict outcomes of observed actions affects the individual’s forward model. These results suggest that parts of the same forward model are utilized in humans to both estimate outcomes of self-generated actions and predict outcomes of observed actions. PMID:29340300

The Model Averaging for Dichotomous Response Benchmark Dose (MADr-BMD) Tool

EPA Pesticide Factsheets

Providing quantal response models, which are also used in the U.S. EPA benchmark dose software suite, and generates a model-averaged dose response model to generate benchmark dose and benchmark dose lower bound estimates.

Uptake of a new meningitis vaccination programme amongst first-year undergraduate students in the United Kingdom: A cross-sectional study.

PubMed

Blagden, Sarah; Seddon, Daniel; Hungerford, Daniel; Stanistreet, Debbi

2017-01-01

In 2015 meningococcal group W was declared endemic in the UK, with the meningococcal ACWY vaccination (MenACWY) subsequently introduced amongst adolescents and first-year university students. This study aimed to determine MenACWY uptake amongst students and to evaluate how this was influenced by demographics and via the Health Belief Model (HBM). This was a cross-sectional study conducted at a British university amongst first-year undergraduate students aged 18-25 years. Data collection was via an electronic questionnaire encompassing demographics, the HBM and vaccination status. Univariable analysis of the associations between demographics, health beliefs and vaccination was performed, followed by multiple logistic regression. 401 participants were included in analysis. Vaccine uptake was 68.1%. Variables independently associated with vaccination upon multiple regression were age, gap-year, perceived effectiveness of the vaccine and knowledge about risk of meningitis. Compared to 18 year-olds, the odds of vaccination were reduced for 19 year-olds (aOR = 0.087, 95% CI = 0.010-0.729), 20 year-olds (aOR = 0.019, 95% CI = 0.002-0.161) and 21-25 year-olds (aOR = 0.003, 95% CI = <0.001-0.027). In contrast, taking a gap year (aOR = 2.939, 95% CI = 1.329-6.501), higher perceived vaccine effectiveness (aOR = 3.555, 95% CI = 1.787-7.073) and knowledge about meningitis risk (aOR = 2.481, 95% CI = 1.165-5.287) were independently associated with increased uptake. MenACWY uptake amongst students in this study and in other sources is above the national coverage for all adolescents (35.3%), indicating that this vaccination programme may be increasing health inequalities. Older students are less likely to become vaccinated due to differing vaccination policy in this age-group. In future, strategies that focus on specific student cohorts and that highlight vaccine effectiveness and the risk of meningitis should be considered. National evaluation of this vaccination programme is recommended to clarify its impact on health inequalities.

Uptake of a new meningitis vaccination programme amongst first-year undergraduate students in the United Kingdom: A cross-sectional study

PubMed Central

Seddon, Daniel; Hungerford, Daniel; Stanistreet, Debbi

2017-01-01

Background In 2015 meningococcal group W was declared endemic in the UK, with the meningococcal ACWY vaccination (MenACWY) subsequently introduced amongst adolescents and first-year university students. This study aimed to determine MenACWY uptake amongst students and to evaluate how this was influenced by demographics and via the Health Belief Model (HBM). Methods This was a cross-sectional study conducted at a British university amongst first-year undergraduate students aged 18–25 years. Data collection was via an electronic questionnaire encompassing demographics, the HBM and vaccination status. Univariable analysis of the associations between demographics, health beliefs and vaccination was performed, followed by multiple logistic regression. Results 401 participants were included in analysis. Vaccine uptake was 68.1%. Variables independently associated with vaccination upon multiple regression were age, gap-year, perceived effectiveness of the vaccine and knowledge about risk of meningitis. Compared to 18 year-olds, the odds of vaccination were reduced for 19 year-olds (aOR = 0.087, 95% CI = 0.010–0.729), 20 year-olds (aOR = 0.019, 95% CI = 0.002–0.161) and 21–25 year-olds (aOR = 0.003, 95% CI = <0.001–0.027). In contrast, taking a gap year (aOR = 2.939, 95% CI = 1.329–6.501), higher perceived vaccine effectiveness (aOR = 3.555, 95% CI = 1.787–7.073) and knowledge about meningitis risk (aOR = 2.481, 95% CI = 1.165–5.287) were independently associated with increased uptake. Conclusions MenACWY uptake amongst students in this study and in other sources is above the national coverage for all adolescents (35.3%), indicating that this vaccination programme may be increasing health inequalities. Older students are less likely to become vaccinated due to differing vaccination policy in this age-group. In future, strategies that focus on specific student cohorts and that highlight vaccine effectiveness and the risk of meningitis should be considered. National evaluation of this vaccination programme is recommended to clarify its impact on health inequalities. PMID:28767667

"A Somali girl is Muslim and does not have premarital sex. Is vaccination really necessary?" A qualitative study into the perceptions of Somali women in the Netherlands about the prevention of cervical cancer.

PubMed

Salad, Jihan; Verdonk, Petra; de Boer, Fijgje; Abma, Tineke A

2015-08-21

Participation in Human Papillomavirus (HPV) vaccination and Papanicolaou Screening (Pap smears) is low among ethnic minorities in the Netherlands and hardly any information is available about the cervical cancer prevention methods of Somali women living in the diaspora. This qualitative study, based on the Health Belief Model (HBM) and an intersectionality-based framework, explores the perceptions of Somali women living in the Netherlands regarding measures to prevent cervical cancer. Semi-structured interviews have been conducted with young Somali women aged 17-21 years (n = 14) and Somali mothers aged 30-46 years (n = 6). Two natural group discussions have been conducted with 12 and 14 Somali mothers aged 23-66 years. The collected data has been analyzed thematically for content. In this study, we have identified perceived barriers to the use of preventive measures across three major themes: (1) Somali women and preventive healthcare; (2) Language, knowledge, and negotiating decisions; and (3) Sexual standards, culture, and religion. Many issues have been identified across these themes, e.g., distrust of the Dutch health care system or being embarrassed to get Pap smears due to Female Genital Mutilation (FGM) and having a Dutch, male practitioner; or a perceived low susceptibility to HPV and cancer because of the religious norms that prohibit sex before marriage. Current measures in the Netherlands to prevent women from developing cervical cancer hardly reach Somali women because these women perceive these kinds of preventative measures as not personally relevant. Dutch education strategies about cervical cancer deviate from ways of exchanging information within the Somali community. Teachers can provide culturally sensitive information to young Somali women in schools. For Somali mothers, oral education (e.g., poetry or theater) about the Dutch health care system and men's roles in HPV transmission may be useful. An intersectional approach, grounded in the HBM, is recommended to promote equal access to preventive health care for Somali women.

HIV/AIDS among youth in urban informal (slum) settlements in Kenya: what are the correlates of and motivations for HIV testing?

PubMed

Kabiru, Caroline W; Beguy, Donatien; Crichton, Joanna; Zulu, Eliya M

2011-09-03

Although HIV counseling and testing (HCT) is widely considered an integral component of HIV prevention and treatment strategies, few studies have examined HCT behavior among youth in sub-Saharan Africa-a group at substantial risk for HIV infection. In this paper we examine: the correlates of HIV testing, including whether associations differ based on the context under which a person gets tested; and the motivations for getting (or not getting) an HIV test. Drawing on data collected in 2007 from 4028 (51% male) youth (12-22 years) living in Korogocho and Viwandani slum settlements in Nairobi (Kenya), we explored the correlates of and motivations for HIV testing using the Health Belief Model (HBM) as a theoretical framework. Multinomial and binary logistic regression analyses were employed to examine correlates of HIV testing. Bivariate analyses were employed to assess reasons for or against testing. Nineteen percent of males and 35% of females had been tested. Among tested youth, 74% of males and 43% of females had requested for their most recent HIV test while 7% of males and 32% of females reported that they were required to take their most recent HIV test (i.e., the test was mandatory). About 60% of females who had ever had sex received an HIV test because they were pregnant. We found modest support for the HBM in explaining variation in testing behavior. In particular, we found that perceived risk for HIV infection may drive HIV testing among youth. For example, about half of youth who had ever had sex but had never been tested reported that they had not been tested because they were not at risk. Targeted interventions to help young people correctly assess their level of risk and to increase awareness of the potential value of HIV testing may help enhance uptake of testing services. Given the relative success of Prevention of Mother-to-Child Transmission (PMTCT) services in increasing HIV testing rates among females, routine provider-initiated testing and counseling among all clients visiting medical facilities may provide an important avenue to increase HIV status awareness among the general population and especially among males.

A qualitative study on caretakers' perceived need of bed-nets after reduced malaria transmission in Zanzibar, Tanzania

PubMed Central

2012-01-01

Background The elimination of malaria in Zanzibar is highly dependent on sustained effective coverage of bed-nets to avoid malaria resurgence. The Health Belief Model (HBM) framework was used to explore the perceptions of malaria and bed-net use after a noticeable reduction in malaria incidence. Methods Nineteen in-depth interviews were conducted with female and male caretakers of children under five in North A district, Zanzibar. Deductive content analysis was used to identify meaning units that were condensed, coded and assigned to pre-determined elements of the HBM. Results Awareness of malaria among caretakers was high but the illness was now seen as easily curable and uncommon. In addition to the perceived advantage of providing protection against malaria, bed-nets were also thought to be useful for avoiding mosquito nuisance, especially during the rainy season when the malaria and mosquito burden is high. The discomfort of sleeping under a net during the hot season was the main barrier that interrupted consistent bed-net usage. The main cue to using a bed-net was high mosquito density, and children were prioritized when it came to bed-net usage. Caretakers had high perceived self-efficacy and did not find it difficult to use bed-nets. Indoor Residual Spraying (IRS), which was recognized as an additional means of mosquito prevention, was not identified as an alternative for bed-nets. A barrier to net ownership was the increasingly high cost of bed-nets. Conclusions Despite the reduction in malaria incidence and the resulting low malaria risk perceptions among caretakers, the benefit of bed-nets as the most proficient protection against mosquito bites upholds their use. This, in combination with the perceived high self-efficacy of caretakers, supports bed-net usage, while seasonality interrupts consistent use. High effective coverage of bed-nets could be further improved by reinforcing the benefits of bed-nets, addressing the seasonal heat barrier by using nets with larger mesh sizes and ensuring high bed-net ownership rates through sustainable and affordable delivery mechanisms. PMID:22863188

An Alternative Procedure for Estimating Unit Learning Curves,

DTIC Science & Technology

1985-09-01

the model accurately describes the real-life situation, i.e., when the model is properly applied to the data, it can be a powerful tool for...predicting unit production costs. There are, however, some unique estimation problems inherent in the model . The usual method of generating predicted unit...production costs attempts to extend properties of least squares estimators to non- linear functions of these estimators. The result is biased estimates of

Lidar-Based Estimates of Above-Ground Biomass in the Continental US and Mexico Using Ground, Airborne, and Satellite Observations

NASA Technical Reports Server (NTRS)

Nelson, Ross; Margolis, Hank; Montesano, Paul; Sun, Guoqing; Cook, Bruce; Corp, Larry; Andersen, Hans-Erik; DeJong, Ben; Pellat, Fernando Paz; Fickel, Thaddeus;

Bootstrap Estimation of Sample Statistic Bias in Structural Equation Modeling.

ERIC Educational Resources Information Center

Thompson, Bruce; Fan, Xitao

This study empirically investigated bootstrap bias estimation in the area of structural equation modeling (SEM). Three correctly specified SEM models were used under four different sample size conditions. Monte Carlo experiments were carried out to generate the criteria against which bootstrap bias estimation should be judged. For SEM fit indices,…

Power Management and Distribution (PMAD) Model Development: Final Report

NASA Technical Reports Server (NTRS)

Metcalf, Kenneth J.

2011-01-01

Power management and distribution (PMAD) models were developed in the early 1990's to model candidate architectures for various Space Exploration Initiative (SEI) missions. They were used to generate "ballpark" component mass estimates to support conceptual PMAD system design studies. The initial set of models was provided to NASA Lewis Research Center (since renamed Glenn Research Center) in 1992. They were developed to estimate the characteristics of power conditioning components predicted to be available in the 2005 timeframe. Early 90's component and device designs and material technologies were projected forward to the 2005 timeframe, and algorithms reflecting those design and material improvements were incorporated into the models to generate mass, volume, and efficiency estimates for circa 2005 components. The models are about ten years old now and NASA GRC requested a review of them to determine if they should be updated to bring them into agreement with current performance projections or to incorporate unforeseen design or technology advances. This report documents the results of this review and the updated power conditioning models and new transmission line models generated to estimate post 2005 PMAD system masses and sizes. This effort continues the expansion and enhancement of a library of PMAD models developed to allow system designers to assess future power system architectures and distribution techniques quickly and consistently.

Bayesian estimation of extreme flood quantiles using a rainfall-runoff model and a stochastic daily rainfall generator

NASA Astrophysics Data System (ADS)

Costa, Veber; Fernandes, Wilson

2017-11-01

Extreme flood estimation has been a key research topic in hydrological sciences. Reliable estimates of such events are necessary as structures for flood conveyance are continuously evolving in size and complexity and, as a result, their failure-associated hazards become more and more pronounced. Due to this fact, several estimation techniques intended to improve flood frequency analysis and reducing uncertainty in extreme quantile estimation have been addressed in the literature in the last decades. In this paper, we develop a Bayesian framework for the indirect estimation of extreme flood quantiles from rainfall-runoff models. In the proposed approach, an ensemble of long daily rainfall series is simulated with a stochastic generator, which models extreme rainfall amounts with an upper-bounded distribution function, namely, the 4-parameter lognormal model. The rationale behind the generation model is that physical limits for rainfall amounts, and consequently for floods, exist and, by imposing an appropriate upper bound for the probabilistic model, more plausible estimates can be obtained for those rainfall quantiles with very low exceedance probabilities. Daily rainfall time series are converted into streamflows by routing each realization of the synthetic ensemble through a conceptual hydrologic model, the Rio Grande rainfall-runoff model. Calibration of parameters is performed through a nonlinear regression model, by means of the specification of a statistical model for the residuals that is able to accommodate autocorrelation, heteroscedasticity and nonnormality. By combining the outlined steps in a Bayesian structure of analysis, one is able to properly summarize the resulting uncertainty and estimating more accurate credible intervals for a set of flood quantiles of interest. The method for extreme flood indirect estimation was applied to the American river catchment, at the Folsom dam, in the state of California, USA. Results show that most floods, including exceptionally large non-systematic events, were reasonably estimated with the proposed approach. In addition, by accounting for uncertainties in each modeling step, one is able to obtain a better understanding of the influential factors in large flood formation dynamics.

Barriers to human immunodeficiency virus related risk reduction among male street prostitutes.

PubMed

Simon, P M; Morse, E V; Balson, P M; Osofsky, H J; Gaumer, H R

1993-01-01

Two hundred eleven male street prostitutes between the ages of 18 and 51 years were interviewed and tested for antibodies to the human immunodeficiency virus (HIV). Economic, social, and emotional barriers to the reduction of HIV-related risk behavior were examined within the context of several concepts present in the Health Belief Model (HBM). Three lifestyle factors were found to function as barriers to engaging in risk reduction behavior. Subjects who were more economically dependent on prostitution, perceived less control over the hustling encounter, and reported increased pleasure from sexual activity with their customers were more likely to engage in risk-taking behavior. Prostitutes' perception of the severity of HIV infection was not significantly associated with their risk behavior. Unexpected findings indicated that increases in perceived susceptibility to HIV and perceived benefit of condom use for HIV prevention were significantly related to increased risk-taking behavior. Practical applications of findings in the design and implementation of future HIV-related preventive health education programs are discussed.

Race/Ethnicity and Primary Language: Health Beliefs about Colorectal Cancer Screening in a Diverse, Low-Income Population.

PubMed

Brenner, Alison Tytell; Ko, Linda K; Janz, Nancy; Gupta, Shivani; Inadomi, John

2015-08-01

Colorectal cancer (CRC) is an important cause of cancer death in adults in the U.S.; screening is effective but underutilized, particularly among minorities. The purpose of this paper was to explore whether health belief model (HBM) constructs pertaining to CRC screening differ by race/ethnicity and primary language. Data were from the baseline surveys of 933 participants (93.5%) in a randomized trial promoting CRC screening in San Francisco. Composite scores for each construct were created from multiple items, dichotomized for analysis, and analyzed using multivariate logistic regression. Most participants were Asian (29.7%) or Hispanic (34.3%), and many were non-English speakers. Non-English speaking Hispanics (p<.001) and English-speaking Asians (p=.002) reported lower perceived susceptibility than non-Hispanic Whites (NHW). Non-English speaking Hispanics reported more and non-English speaking Asians fewer perceived barriers (psychological and structural) than NHW. Understanding how different populations think about CRC screening may be critical in promoting screening in diverse populations.

Current data on the background burden to the persistent organochlorine pollutants HCB, p,p'-DDE as well as PCB 138, PCB 153 and PCB 180 in plasma of the general population in Germany.

PubMed

Schettgen, Thomas; Alt, Anne; Esser, Andre; Kraus, Thomas

2015-06-01

Despite their long-term ban, persistent organochlorine compounds like hexachlorobenzene (HCB), p,p'-dichlorodiphenylethylene (DDE) as well as polychlorinated biphenyls (PCBs) are still of environmental concern. For the evaluation of potential occupational or environmental exposures to these substances, it is essential to know the current background burden of the general population. As representative and up-to-date information is missing for Germany, we have analysed a large dataset generated in studies on potential exposure to lower chlorinated PCBs to fill this gap for the levels of HCB, DDE as well as PCB 138, PCB 153 and PCB 180. We have investigated n=2750 plasma samples of persons of the general population living in North Rhine-Westfalia and Hesse aged 6-65 years and sampled between September 2010 and March 2014. For evaluation of the age-dependent accumulation in the general population we have generated seven age groups in the collective. Our laboratory used a validated and quality controlled procedure using GC/MS for quantification of the organochlorine compounds in plasma (LOQ: 0.01μg/L). The median (95th percentile) levels for ∑ PCB 138+PCB 153+PCB 180 were 0.14 (0.73); 0.30 (0.82); 0.38 (0.88); 0.50 (1.14); 0.92; 1.58 (3.54) and 2.41 (4.82)μg/L plasma in the age groups 6-10 years (n=102), 11-17 years (n=499), 18-25 years (n=157), 26-35 years (n=710), 36-45 years (n=400), 46-55 years (n=525) and 56-65 years (n=357), respectively. Similarly, the median (95th percentile) levels of p,p'-DDE were 0.18 (1.24); 0.18 (0.74); 0.24 (0.85); 0.30 (1.20); 0.45 (1.74); 0.64 (3.25) and 0.94 (4.7)μg/L plasma. Finally, the median (95th percentile) of HCB in plasma in these age groups was 0.05 (0.10); 0.06 (0.11); 0.08 (0.15); 0.08 (0.15); 0.11 (0.22); 0.14 (0.42) and 0.20 (0.68)μg/L plasma. Our results prove an overall substantial reduction in the body burden to organochlorine compounds in Germany compared to earlier studies. However, 15% and 3.6% of the examined collective exceeded the HBM-I- and HBM-II-values for PCBs established by the German Human Biomonitoring Commission. Due to a large sample size and a collection period from 2010 to 2014, our data might be suitable for the evaluation of additional exposures to these POPs and may serve as reference values. Copyright © 2015 The Authors. Published by Elsevier GmbH.. All rights reserved.

JEDI Natural Gas Model | Jobs and Economic Development Impact Models | NREL

Science.gov Websites

Natural Gas Model JEDI Natural Gas Model The Jobs and Economic Development Impacts (JEDI) Natural Gas model allows users to estimate economic development impacts from natural gas power generation -specific data should be used to obtain the best estimate of economic development impacts. This model has

Thermal Aspects of Lithium Ion Cells

NASA Technical Reports Server (NTRS)

Frank, H.; Shakkottai, P.; Bugga, R.; Smart, M.; Huang, C. K.; Timmerman, P.; Surampudi, S.

2000-01-01

This viewgraph presentation outlines the development of a thermal model of Li-ion cells in terms of heat generation, thermal mass, and thermal resistance. Intended for incorporation into battery model. The approach was to estimate heat generation: with semi-theoretical model, and then to check accuracy with efficiency measurements. Another objective was to compute thermal mass from component weights and specific heats, and to compute the thermal resistance from component dimensions and conductivities. Two lithium batteries are compared, the Cylindrical lithium battery, and the prismatic lithium cell. It reviews methodology for estimating the heat generation rate. Graphs of the Open-circuit curves of the cells and the heat evolution during discharge are given.

New Methodology for Estimating Fuel Economy by Vehicle Class

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

Chin, Shih-Miao; Dabbs, Kathryn; Hwang, Ho-Ling

2011-01-01

Office of Highway Policy Information to develop a new methodology to generate annual estimates of average fuel efficiency and number of motor vehicles registered by vehicle class for Table VM-1 of the Highway Statistics annual publication. This paper describes the new methodology developed under this effort and compares the results of the existing manual method and the new systematic approach. The methodology developed under this study takes a two-step approach. First, the preliminary fuel efficiency rates are estimated based on vehicle stock models for different classes of vehicles. Then, a reconciliation model is used to adjust the initial fuel consumptionmore » rates from the vehicle stock models and match the VMT information for each vehicle class and the reported total fuel consumption. This reconciliation model utilizes a systematic approach that produces documentable and reproducible results. The basic framework utilizes a mathematical programming formulation to minimize the deviations between the fuel economy estimates published in the previous year s Highway Statistics and the results from the vehicle stock models, subject to the constraint that fuel consumptions for different vehicle classes must sum to the total fuel consumption estimate published in Table MF-21 of the current year Highway Statistics. The results generated from this new approach provide a smoother time series for the fuel economies by vehicle class. It also utilizes the most up-to-date and best available data with sound econometric models to generate MPG estimates by vehicle class.« less

Power system observability and dynamic state estimation for stability monitoring using synchrophasor measurements

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

Sun, Kai; Qi, Junjian; Kang, Wei

2016-08-01

Growing penetration of intermittent resources such as renewable generations increases the risk of instability in a power grid. This paper introduces the concept of observability and its computational algorithms for a power grid monitored by the wide-area measurement system (WAMS) based on synchrophasors, e.g. phasor measurement units (PMUs). The goal is to estimate real-time states of generators, especially for potentially unstable trajectories, the information that is critical for the detection of rotor angle instability of the grid. The paper studies the number and siting of synchrophasors in a power grid so that the state of the system can be accuratelymore » estimated in the presence of instability. An unscented Kalman filter (UKF) is adopted as a tool to estimate the dynamic states that are not directly measured by synchrophasors. The theory and its computational algorithms are illustrated in detail by using a 9-bus 3-generator power system model and then tested on a 140-bus 48-generator Northeast Power Coordinating Council power grid model. Case studies on those two systems demonstrate the performance of the proposed approach using a limited number of synchrophasors for dynamic state estimation for stability assessment and its robustness against moderate inaccuracies in model parameters.« less

Lactational changes in concentration and distribution of ganglioside molecular species in human breast milk from Chinese mothers.

PubMed

Ma, Lin; Liu, Xihong; MacGibbon, Alastair K H; Rowan, Angela; McJarrow, Paul; Fong, Bertram Y

2015-11-01

Gangliosides play a critical role in human brain development and function. Human breast milk (HBM) is an important dietary source of gangliosides for the growing infant. In this study, ganglioside concentrations were measured in the breast milk from a cross-sectional sample of Chinese mothers over an 8-month lactation period. The average total ganglioside concentration increased from 13.1 mg/l during the first month to 20.9 mg/l by 8 months of lactation. The average concentration during the typically solely breast-feeding period of 1‒6 months was 18.9 mg/l. This is the first study to report the relative distribution of the individual ganglioside molecular species through lactation for any population group. The ganglioside molecular species are made up of different fatty acid moieties that influence the physical properties of these gangliosides, and hence affect their function. The GM(3) molecular species containing long-chain acyl fatty acids had the most prominent changes, increasing in both concentration and relative distribution. The equivalent long-chain acyl fatty acid GD(3) molecular species typically decreased in concentration and relative distribution. The lactational trends for both concentration and relative distribution for the very long-chain acyl fatty acid molecular species were more varied. The major GM(3) and GD(3) molecular species during lactation were d40:1 and d42:1, respectively. An understanding of ganglioside molecular species distribution in HBM is essential for accurate application of mass spectrometry methods for ganglioside quantification.

Pollution gets personal! A first population-based human biomonitoring study in Austria.

PubMed

Hohenblum, Philipp; Steinbichl, Philipp; Raffesberg, Wolfgang; Weiss, Stefan; Moche, Wolfgang; Vallant, Birgit; Scharf, Sigrid; Haluza, Daniela; Moshammer, Hanns; Kundi, Michael; Piegler, Brigitte; Wallner, Peter; Hutter, Hans-Peter

2012-02-01

Humans are exposed to a broad variety of man-made chemicals. Human biomonitoring (HBM) data reveal the individual body burden irrespective of sources and routes of uptake. A first population-based study was started in Austria in 2008 and was finished at the end of May 2011. This cross sectional study aims at documenting the extent, the distribution and the determinants of human exposure to industrial chemicals as well as proving the feasibility of a representative HBM study. Overall, 150 volunteers (50 families) were selected by stratified random sampling. Exposure to phthalates, trisphosphates, polybrominated diphenyl ethers (PBDE), bisphenol A (along with nonyl- and octyl phenol) and methyl mercury was assessed. Sixteen of 18 PBDE determined were detected above the limit of quantification (LOQ) in blood samples with #153 and #197 the most abundant species. Bisphenol A in urine was measured in a subsample of 25 with only 4 samples found above the LOQ. In 3 of 100 urine samples at least one of 8 trisphosphate compounds assessed was above the LOQ. These first analytical results of the human biomonitoring data show that the body burden of the Austrian population with respect to the assessed compounds is comparable to or even lower than in other European countries. Overall, the study revealed that in order to develop a feasible protocol for representative human biomonitoring studies procedures have to be optimized to allow for non-invasive sampling of body tissues in accordance with the main metabolic pathways. Procedures of participants' recruitment were, however, labor intensive and have to be improved. Copyright © 2011 Elsevier GmbH. All rights reserved.

Reaction Mechanism Generator: Automatic construction of chemical kinetic mechanisms

NASA Astrophysics Data System (ADS)

Gao, Connie W.; Allen, Joshua W.; Green, William H.; West, Richard H.

2016-06-01

Reaction Mechanism Generator (RMG) constructs kinetic models composed of elementary chemical reaction steps using a general understanding of how molecules react. Species thermochemistry is estimated through Benson group additivity and reaction rate coefficients are estimated using a database of known rate rules and reaction templates. At its core, RMG relies on two fundamental data structures: graphs and trees. Graphs are used to represent chemical structures, and trees are used to represent thermodynamic and kinetic data. Models are generated using a rate-based algorithm which excludes species from the model based on reaction fluxes. RMG can generate reaction mechanisms for species involving carbon, hydrogen, oxygen, sulfur, and nitrogen. It also has capabilities for estimating transport and solvation properties, and it automatically computes pressure-dependent rate coefficients and identifies chemically-activated reaction paths. RMG is an object-oriented program written in Python, which provides a stable, robust programming architecture for developing an extensible and modular code base with a large suite of unit tests. Computationally intensive functions are cythonized for speed improvements.

Improved trip generation data for Texas using work place and special generator survey data.

DOT National Transportation Integrated Search

2015-05-01

Travel estimates from models and manuals developed from trip attraction rates having high variances due to few : survey observations can reduce confidence and accuracy in estimates. This project compiled and analyzed data from : more than a decade of...

An open-population hierarchical distance sampling model

USGS Publications Warehouse

Sollmann, Rachel; Beth Gardner,; Richard B Chandler,; Royle, J. Andrew; T Scott Sillett,

2015-01-01

Modeling population dynamics while accounting for imperfect detection is essential to monitoring programs. Distance sampling allows estimating population size while accounting for imperfect detection, but existing methods do not allow for direct estimation of demographic parameters. We develop a model that uses temporal correlation in abundance arising from underlying population dynamics to estimate demographic parameters from repeated distance sampling surveys. Using a simulation study motivated by designing a monitoring program for island scrub-jays (Aphelocoma insularis), we investigated the power of this model to detect population trends. We generated temporally autocorrelated abundance and distance sampling data over six surveys, using population rates of change of 0.95 and 0.90. We fit the data generating Markovian model and a mis-specified model with a log-linear time effect on abundance, and derived post hoc trend estimates from a model estimating abundance for each survey separately. We performed these analyses for varying number of survey points. Power to detect population changes was consistently greater under the Markov model than under the alternatives, particularly for reduced numbers of survey points. The model can readily be extended to more complex demographic processes than considered in our simulations. This novel framework can be widely adopted for wildlife population monitoring.

An open-population hierarchical distance sampling model.

PubMed

Sollmann, Rahel; Gardner, Beth; Chandler, Richard B; Royle, J Andrew; Sillett, T Scott

2015-02-01

Modeling population dynamics while accounting for imperfect detection is essential to monitoring programs. Distance sampling allows estimating population size while accounting for imperfect detection, but existing methods do not allow for estimation of demographic parameters. We develop a model that uses temporal correlation in abundance arising from underlying population dynamics to estimate demographic parameters from repeated distance sampling surveys. Using a simulation study motivated by designing a monitoring program for Island Scrub-Jays (Aphelocoma insularis), we investigated the power of this model to detect population trends. We generated temporally autocorrelated abundance and distance sampling data over six surveys, using population rates of change of 0.95 and 0.90. We fit the data generating Markovian model and a mis-specified model with a log-linear time effect on abundance, and derived post hoc trend estimates from a model estimating abundance for each survey separately. We performed these analyses for varying numbers of survey points. Power to detect population changes was consistently greater under the Markov model than under the alternatives, particularly for reduced numbers of survey points. The model can readily be extended to more complex demographic processes than considered in our simulations. This novel framework can be widely adopted for wildlife population monitoring.

Process-based Cost Estimation for Ramjet/Scramjet Engines

NASA Technical Reports Server (NTRS)

Singh, Brijendra; Torres, Felix; Nesman, Miles; Reynolds, John

2003-01-01

Process-based cost estimation plays a key role in effecting cultural change that integrates distributed science, technology and engineering teams to rapidly create innovative and affordable products. Working together, NASA Glenn Research Center and Boeing Canoga Park have developed a methodology of process-based cost estimation bridging the methodologies of high-level parametric models and detailed bottoms-up estimation. The NASA GRC/Boeing CP process-based cost model provides a probabilistic structure of layered cost drivers. High-level inputs characterize mission requirements, system performance, and relevant economic factors. Design alternatives are extracted from a standard, product-specific work breakdown structure to pre-load lower-level cost driver inputs and generate the cost-risk analysis. As product design progresses and matures the lower level more detailed cost drivers can be re-accessed and the projected variation of input values narrowed, thereby generating a progressively more accurate estimate of cost-risk. Incorporated into the process-based cost model are techniques for decision analysis, specifically, the analytic hierarchy process (AHP) and functional utility analysis. Design alternatives may then be evaluated not just on cost-risk, but also user defined performance and schedule criteria. This implementation of full-trade study support contributes significantly to the realization of the integrated development environment. The process-based cost estimation model generates development and manufacturing cost estimates. The development team plans to expand the manufacturing process base from approximately 80 manufacturing processes to over 250 processes. Operation and support cost modeling is also envisioned. Process-based estimation considers the materials, resources, and processes in establishing cost-risk and rather depending on weight as an input, actually estimates weight along with cost and schedule.

Estimating organ doses from tube current modulated CT examinations using a generalized linear model.

PubMed

Bostani, Maryam; McMillan, Kyle; Lu, Peiyun; Kim, Grace Hyun J; Cody, Dianna; Arbique, Gary; Greenberg, S Bruce; DeMarco, John J; Cagnon, Chris H; McNitt-Gray, Michael F

2017-04-01

Currently, available Computed Tomography dose metrics are mostly based on fixed tube current Monte Carlo (MC) simulations and/or physical measurements such as the size specific dose estimate (SSDE). In addition to not being able to account for Tube Current Modulation (TCM), these dose metrics do not represent actual patient dose. The purpose of this study was to generate and evaluate a dose estimation model based on the Generalized Linear Model (GLM), which extends the ability to estimate organ dose from tube current modulated examinations by incorporating regional descriptors of patient size, scanner output, and other scan-specific variables as needed. The collection of a total of 332 patient CT scans at four different institutions was approved by each institution's IRB and used to generate and test organ dose estimation models. The patient population consisted of pediatric and adult patients and included thoracic and abdomen/pelvis scans. The scans were performed on three different CT scanner systems. Manual segmentation of organs, depending on the examined anatomy, was performed on each patient's image series. In addition to the collected images, detailed TCM data were collected for all patients scanned on Siemens CT scanners, while for all GE and Toshiba patients, data representing z-axis-only TCM, extracted from the DICOM header of the images, were used for TCM simulations. A validated MC dosimetry package was used to perform detailed simulation of CT examinations on all 332 patient models to estimate dose to each segmented organ (lungs, breasts, liver, spleen, and kidneys), denoted as reference organ dose values. Approximately 60% of the data were used to train a dose estimation model, while the remaining 40% was used to evaluate performance. Two different methodologies were explored using GLM to generate a dose estimation model: (a) using the conventional exponential relationship between normalized organ dose and size with regional water equivalent diameter (WED) and regional CTDI vol as variables and (b) using the same exponential relationship with the addition of categorical variables such as scanner model and organ to provide a more complete estimate of factors that may affect organ dose. Finally, estimates from generated models were compared to those obtained from SSDE and ImPACT. The Generalized Linear Model yielded organ dose estimates that were significantly closer to the MC reference organ dose values than were organ doses estimated via SSDE or ImPACT. Moreover, the GLM estimates were better than those of SSDE or ImPACT irrespective of whether or not categorical variables were used in the model. While the improvement associated with a categorical variable was substantial in estimating breast dose, the improvement was minor for other organs. The GLM approach extends the current CT dose estimation methods by allowing the use of additional variables to more accurately estimate organ dose from TCM scans. Thus, this approach may be able to overcome the limitations of current CT dose metrics to provide more accurate estimates of patient dose, in particular, dose to organs with considerable variability across the population. © 2017 American Association of Physicists in Medicine.

Constructing stage-structured matrix population models from life tables: comparison of methods

PubMed Central

Diaz-Lopez, Jasmin

2017-01-01

A matrix population model is a convenient tool for summarizing per capita survival and reproduction rates (collectively vital rates) of a population and can be used for calculating an asymptotic finite population growth rate (λ) and generation time. These two pieces of information can be used for determining the status of a threatened species. The use of stage-structured population models has increased in recent years, and the vital rates in such models are often estimated using a life table analysis. However, potential bias introduced when converting age-structured vital rates estimated from a life table into parameters for a stage-structured population model has not been assessed comprehensively. The objective of this study was to investigate the performance of methods for such conversions using simulated life histories of organisms. The underlying models incorporate various types of life history and true population growth rates of varying levels. The performance was measured by comparing differences in λ and the generation time calculated using the Euler-Lotka equation, age-structured population matrices, and several stage-structured population matrices that were obtained by applying different conversion methods. The results show that the discretization of age introduces only small bias in λ or generation time. Similarly, assuming a fixed age of maturation at the mean age of maturation does not introduce much bias. However, aggregating age-specific survival rates into a stage-specific survival rate and estimating a stage-transition rate can introduce substantial bias depending on the organism’s life history type and the true values of λ. In order to aggregate survival rates, the use of the weighted arithmetic mean was the most robust method for estimating λ. Here, the weights are given by survivorship curve after discounting with λ. To estimate a stage-transition rate, matching the proportion of individuals transitioning, with λ used for discounting the rate, was the best approach. However, stage-structured models performed poorly in estimating generation time, regardless of the methods used for constructing the models. Based on the results, we recommend using an age-structured matrix population model or the Euler-Lotka equation for calculating λ and generation time when life table data are available. Then, these age-structured vital rates can be converted into a stage-structured model for further analyses. PMID:29085763

Constructing stage-structured matrix population models from life tables: comparison of methods.

PubMed

Fujiwara, Masami; Diaz-Lopez, Jasmin

2017-01-01

A matrix population model is a convenient tool for summarizing per capita survival and reproduction rates (collectively vital rates) of a population and can be used for calculating an asymptotic finite population growth rate ( λ ) and generation time. These two pieces of information can be used for determining the status of a threatened species. The use of stage-structured population models has increased in recent years, and the vital rates in such models are often estimated using a life table analysis. However, potential bias introduced when converting age-structured vital rates estimated from a life table into parameters for a stage-structured population model has not been assessed comprehensively. The objective of this study was to investigate the performance of methods for such conversions using simulated life histories of organisms. The underlying models incorporate various types of life history and true population growth rates of varying levels. The performance was measured by comparing differences in λ and the generation time calculated using the Euler-Lotka equation, age-structured population matrices, and several stage-structured population matrices that were obtained by applying different conversion methods. The results show that the discretization of age introduces only small bias in λ or generation time. Similarly, assuming a fixed age of maturation at the mean age of maturation does not introduce much bias. However, aggregating age-specific survival rates into a stage-specific survival rate and estimating a stage-transition rate can introduce substantial bias depending on the organism's life history type and the true values of λ . In order to aggregate survival rates, the use of the weighted arithmetic mean was the most robust method for estimating λ . Here, the weights are given by survivorship curve after discounting with λ . To estimate a stage-transition rate, matching the proportion of individuals transitioning, with λ used for discounting the rate, was the best approach. However, stage-structured models performed poorly in estimating generation time, regardless of the methods used for constructing the models. Based on the results, we recommend using an age-structured matrix population model or the Euler-Lotka equation for calculating λ and generation time when life table data are available. Then, these age-structured vital rates can be converted into a stage-structured model for further analyses.

Investigation of the dependence of joint contact forces on musculotendon parameters using a codified workflow for image-based modelling.

PubMed

Modenese, Luca; Montefiori, Erica; Wang, Anqi; Wesarg, Stefan; Viceconti, Marco; Mazzà, Claudia

2018-05-17

The generation of subject-specific musculoskeletal models of the lower limb has become a feasible task thanks to improvements in medical imaging technology and musculoskeletal modelling software. Nevertheless, clinical use of these models in paediatric applications is still limited for what concerns the estimation of muscle and joint contact forces. Aiming to improve the current state of the art, a methodology to generate highly personalized subject-specific musculoskeletal models of the lower limb based on magnetic resonance imaging (MRI) scans was codified as a step-by-step procedure and applied to data from eight juvenile individuals. The generated musculoskeletal models were used to simulate 107 gait trials using stereophotogrammetric and force platform data as input. To ensure completeness of the modelling procedure, muscles' architecture needs to be estimated. Four methods to estimate muscles' maximum isometric force and two methods to estimate musculotendon parameters (optimal fiber length and tendon slack length) were assessed and compared, in order to quantify their influence on the models' output. Reported results represent the first comprehensive subject-specific model-based characterization of juvenile gait biomechanics, including profiles of joint kinematics and kinetics, muscle forces and joint contact forces. Our findings suggest that, when musculotendon parameters were linearly scaled from a reference model and the muscle force-length-velocity relationship was accounted for in the simulations, realistic knee contact forces could be estimated and these forces were not sensitive the method used to compute muscle maximum isometric force. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Monte Carlo simulation of single accident airport risk profile

NASA Technical Reports Server (NTRS)

1979-01-01

A computer simulation model was developed for estimating the potential economic impacts of a carbon fiber release upon facilities within an 80 kilometer radius of a major airport. The model simulated the possible range of release conditions and the resulting dispersion of the carbon fibers. Each iteration of the model generated a specific release scenario, which would cause a specific amount of dollar loss to the surrounding community. By repeated iterations, a risk profile was generated, showing the probability distribution of losses from one accident. Using accident probability estimates, the risks profile for annual losses was derived. The mechanics are described of the simulation model, the required input data, and the risk profiles generated for the 26 large hub airports.

Modeling in Real Time During the Ebola Response.

PubMed

Meltzer, Martin I; Santibanez, Scott; Fischer, Leah S; Merlin, Toby L; Adhikari, Bishwa B; Atkins, Charisma Y; Campbell, Caresse; Fung, Isaac Chun-Hai; Gambhir, Manoj; Gift, Thomas; Greening, Bradford; Gu, Weidong; Jacobson, Evin U; Kahn, Emily B; Carias, Cristina; Nerlander, Lina; Rainisch, Gabriel; Shankar, Manjunath; Wong, Karen; Washington, Michael L

2016-07-08

To aid decision-making during CDC's response to the 2014-2016 Ebola virus disease (Ebola) epidemic in West Africa, CDC activated a Modeling Task Force to generate estimates on various topics related to the response in West Africa and the risk for importation of cases into the United States. Analysis of eight Ebola response modeling projects conducted during August 2014-July 2015 provided insight into the types of questions addressed by modeling, the impact of the estimates generated, and the difficulties encountered during the modeling. This time frame was selected to cover the three phases of the West African epidemic curve. Questions posed to the Modeling Task Force changed as the epidemic progressed. Initially, the task force was asked to estimate the number of cases that might occur if no interventions were implemented compared with cases that might occur if interventions were implemented; however, at the peak of the epidemic, the focus shifted to estimating resource needs for Ebola treatment units. Then, as the epidemic decelerated, requests for modeling changed to generating estimates of the potential number of sexually transmitted Ebola cases. Modeling to provide information for decision-making during the CDC Ebola response involved limited data, a short turnaround time, and difficulty communicating the modeling process, including assumptions and interpretation of results. Despite these challenges, modeling yielded estimates and projections that public health officials used to make key decisions regarding response strategy and resources required. The impact of modeling during the Ebola response demonstrates the usefulness of modeling in future responses, particularly in the early stages and when data are scarce. Future modeling can be enhanced by planning ahead for data needs and data sharing, and by open communication among modelers, scientists, and others to ensure that modeling and its limitations are more clearly understood. The activities summarized in this report would not have been possible without collaboration with many U.S. and international partners (http://www.cdc.gov/vhf/ebola/outbreaks/2014-west-africa/partners.html).

Planning Inmarsat's second generation of spacecraft

NASA Astrophysics Data System (ADS)

Williams, W. P.

1982-09-01

The next generation of studies of the Inmarsat service are outlined, such as traffic forecasting studies, communications capacity estimates, space segment design, cost estimates, and financial analysis. Traffic forecasting will require future demand estimates, and a computer model has been developed which estimates demand over the Atlantic, Pacific, and Indian ocean regions. Communications estimates are based on traffic estimates, as a model converts traffic demand into a required capacity figure for a given area. The Erlang formula is used, requiring additional data such as peak hour ratios and distribution estimates. Basic space segment technical requirements are outlined (communications payload, transponder arrangements, etc), and further design studies involve such areas as space segment configuration, launcher and spacecraft studies, transmission planning, and earth segment configurations. Cost estimates of proposed design parameters will be performed, but options must be reduced to make construction feasible. Finally, a financial analysis will be carried out in order to calculate financial returns.

Magma ocean formation due to giant impacts

NASA Technical Reports Server (NTRS)

Tonks, W. B.; Melosh, H. J.

1993-01-01

The thermal effects of giant impacts are studied by estimating the melt volume generated by the initial shock wave and corresponding magma ocean depths. Additionally, the effects of the planet's initial temperature on the generated melt volume are examined. The shock pressure required to completely melt the material is determined using the Hugoniot curve plotted in pressure-entropy space. Once the melting pressure is known, an impact melting model is used to estimate the radial distance melting occurred from the impact site. The melt region's geometry then determines the associated melt volume. The model is also used to estimate the partial melt volume. Magma ocean depths resulting from both excavated and retained melt are calculated, and the melt fraction not excavated during the formation of the crater is estimated. The fraction of a planet melted by the initial shock wave is also estimated using the model.

Using local multiplicity to improve effect estimation from a hypothesis-generating pharmacogenetics study.

PubMed

Zou, W; Ouyang, H

2016-02-01

We propose a multiple estimation adjustment (MEA) method to correct effect overestimation due to selection bias from a hypothesis-generating study (HGS) in pharmacogenetics. MEA uses a hierarchical Bayesian approach to model individual effect estimates from maximal likelihood estimation (MLE) in a region jointly and shrinks them toward the regional effect. Unlike many methods that model a fixed selection scheme, MEA capitalizes on local multiplicity independent of selection. We compared mean square errors (MSEs) in simulated HGSs from naive MLE, MEA and a conditional likelihood adjustment (CLA) method that model threshold selection bias. We observed that MEA effectively reduced MSE from MLE on null effects with or without selection, and had a clear advantage over CLA on extreme MLE estimates from null effects under lenient threshold selection in small samples, which are common among 'top' associations from a pharmacogenetics HGS.

Mars Rover/Sample Return - Phase A cost estimation

NASA Technical Reports Server (NTRS)

Stancati, Michael L.; Spadoni, Daniel J.

1990-01-01

This paper presents a preliminary cost estimate for the design and development of the Mars Rover/Sample Return (MRSR) mission. The estimate was generated using a modeling tool specifically built to provide useful cost estimates from design parameters of the type and fidelity usually available during early phases of mission design. The model approach and its application to MRSR are described.

Rasch Model Parameter Estimation in the Presence of a Nonnormal Latent Trait Using a Nonparametric Bayesian Approach

ERIC Educational Resources Information Center

Finch, Holmes; Edwards, Julianne M.

2016-01-01

Standard approaches for estimating item response theory (IRT) model parameters generally work under the assumption that the latent trait being measured by a set of items follows the normal distribution. Estimation of IRT parameters in the presence of nonnormal latent traits has been shown to generate biased person and item parameter estimates. A…

Future trends in computer waste generation in India.

PubMed

Dwivedy, Maheshwar; Mittal, R K

2010-11-01

The objective of this paper is to estimate the future projection of computer waste in India and to subsequently analyze their flow at the end of their useful phase. For this purpose, the study utilizes the logistic model-based approach proposed by Yang and Williams to forecast future trends in computer waste. The model estimates future projection of computer penetration rate utilizing their first lifespan distribution and historical sales data. A bounding analysis on the future carrying capacity was simulated using the three parameter logistic curve. The observed obsolete generation quantities from the extrapolated penetration rates are then used to model the disposal phase. The results of the bounding analysis indicate that in the year 2020, around 41-152 million units of computers will become obsolete. The obsolete computer generation quantities are then used to estimate the End-of-Life outflows by utilizing a time-series multiple lifespan model. Even a conservative estimate of the future recycling capacity of PCs will reach upwards of 30 million units during 2025. Apparently, more than 150 million units could be potentially recycled in the upper bound case. However, considering significant future investment in the e-waste recycling sector from all stakeholders in India, we propose a logistic growth in the recycling rate and estimate the requirement of recycling capacity between 60 and 400 million units for the lower and upper bound case during 2025. Finally, we compare the future obsolete PC generation amount of the US and India. Copyright © 2010 Elsevier Ltd. All rights reserved.

Anatomy guided automated SPECT renal seed point estimation

NASA Astrophysics Data System (ADS)

Dwivedi, Shekhar; Kumar, Sailendra

2010-04-01

Quantification of SPECT(Single Photon Emission Computed Tomography) images can be more accurate if correct segmentation of region of interest (ROI) is achieved. Segmenting ROI from SPECT images is challenging due to poor image resolution. SPECT is utilized to study the kidney function, though the challenge involved is to accurately locate the kidneys and bladder for analysis. This paper presents an automated method for generating seed point location of both kidneys using anatomical location of kidneys and bladder. The motivation for this work is based on the premise that the anatomical location of the bladder relative to the kidneys will not differ much. A model is generated based on manual segmentation of the bladder and both the kidneys on 10 patient datasets (including sum and max images). Centroid is estimated for manually segmented bladder and kidneys. Relatively easier bladder segmentation is followed by feeding bladder centroid coordinates into the model to generate seed point for kidneys. Percentage error observed in centroid coordinates of organs from ground truth to estimated values from our approach are acceptable. Percentage error of approximately 1%, 6% and 2% is observed in X coordinates and approximately 2%, 5% and 8% is observed in Y coordinates of bladder, left kidney and right kidney respectively. Using a regression model and the location of the bladder, the ROI generation for kidneys is facilitated. The model based seed point estimation will enhance the robustness of kidney ROI estimation for noisy cases.

Using the MCPLXS Generator for Technology Transfer

NASA Technical Reports Server (NTRS)

Moore, Arlene A.; Dean, Edwin B.

1987-01-01

The objective of this paper is to acquaint you with some of the approaches we are taking at Langley to incorporate escalations (or de-escalations) of technology when modeling futuristic systems. Since we have a short turnaround between the time we receive enough descriptive information to start estimating the project and when the estimate is needed (the "we-want-it-yesterday syndrome"), creativity is often necessary. There is not much time available for tool development. It is expedient to use existing tools in an adaptive manner to model the situation at hand. Specifically, this paper describes the use of the RCA PRICE MCPLXS Generator to incorporate technology transfer and technology escalation in estimates for advanced space systems such as Shuttle II and NASA advanced technology vehicles. It is assumed that the reader is familiar with the RCA PRICE family of models as well as the RCA PRICE utility programs such as SCPLX, PARAM, PARASYN, and the MCPLXS Generator.

Generating large-scale estimates from sparse, in-situ networks: multi-scale soil moisture modeling at ARS watersheds for NASA’s soil moisture active passive (SMAP) calibration/validation mission

USDA-ARS?s Scientific Manuscript database

NASA’s SMAP satellite, launched in November of 2014, produces estimates of average volumetric soil moisture at 3, 9, and 36-kilometer scales. The calibration and validation process of these estimates requires the generation of an identically-scaled soil moisture product from existing in-situ networ...

Visual Persons Behavior Diary Generation Model based on Trajectories and Pose Estimation

NASA Astrophysics Data System (ADS)

Gang, Chen; Bin, Chen; Yuming, Liu; Hui, Li

2018-03-01

The behavior pattern of persons was the important output of the surveillance analysis. This paper focus on the generation model of visual person behavior diary. The pipeline includes the person detection, tracking, and the person behavior classify. This paper adopts the deep convolutional neural model YOLO (You Only Look Once)V2 for person detection module. Multi person tracking was based on the detection framework. The Hungarian assignment algorithm was used to the matching. The person appearance model was integrated by HSV color model and Hash code model. The person object motion was estimated by the Kalman Filter. The multi objects were matching with exist tracklets through the appearance and motion location distance by the Hungarian assignment method. A long continuous trajectory for one person was get by the spatial-temporal continual linking algorithm. And the face recognition information was used to identify the trajectory. The trajectories with identification information can be used to generate the visual diary of person behavior based on the scene context information and person action estimation. The relevant modules are tested in public data sets and our own capture video sets. The test results show that the method can be used to generate the visual person behavior pattern diary with certain accuracy.

The health belief model and determinants of oral hygiene practices and beliefs in preteen children: a pilot study.

PubMed

Walker, Kimberly; Jackson, Richard

2015-01-01

There is limited understanding of children's behavioral decisions for practicing good oral hygiene. The purpose of this study was to identify factors that may motivate children to practice good oral hygiene. Guided by the Health Belief Model (HBM), eight focus groups of 42 American children (second through fifth graders) were interviewed concerning their histories with caries, perceived confidence in brushing, self-perceived susceptibility and vulnerability for caries and/or poor oral health, and perceived benefits and barriers to practicing oral hygiene. Most children equated good oral health as being central to their overall health; however, some viewed poor oral health as occurring only in the elderly while others believed poor oral health could begin at any age. Children cited esthetic appearance of teeth and the desire to please others by brushing without reminders as motivators of good oral hygiene. The greatest barriers to performing oral hygiene were a perceived lack of time and limited access to toothbrushes and dentifrice when away. To motivate children in this age range, emphasis should be placed on the positive aspects of maintaining good oral hygiene for its contribution to appearance and its implication for an overall healthy body and self-image.

Evaluation of high myopia complications prevention program in university freshmen

PubMed Central

Tseng, Gow-Lieng; Chen, Cheng-Yu

2016-01-01

Abstract High myopia is a global eye health problem because of its high incidence of sight-threatening complications. Due to the role of awareness, self-examination, and preventive behavior in prevention of morbidity of high myopia complications, promoting knowledge, capabilities, and attitude of high myopic personnel are required in this regard. In this quasi-experiment study, 31 freshmen with high myopia in a national university were enrolled in 2014. The data were collected by validated and reliable questionnaire based on health belief model (HBM) and self-efficacy theory. The intervention program consisted of 1 educational session lasting 150 minutes by lecturing of high myopia complications, virtual reality experiencing, similarity modeling, and quibbling a film made on high myopia complications preventive concepts. Implementing the educational program showed immediate effect in knowledge, perceived susceptibility, perceived severity, self-efficacy, and preventive behavior intention. While 6 weeks after the educational program, significant increases were observed in cues to action, self-efficacy, and preventive behavior intention. This article provided that, after a single session, there was positive improvement in high myopia complication prevention behavior intention among participants. These positive effects confirmed the efficacy of the education program and will probably induce behavior change. PMID:27749586

Evaluation of high myopia complications prevention program in university freshmen.

PubMed

Tseng, Gow-Lieng; Chen, Cheng-Yu

2016-10-01

High myopia is a global eye health problem because of its high incidence of sight-threatening complications. Due to the role of awareness, self-examination, and preventive behavior in prevention of morbidity of high myopia complications, promoting knowledge, capabilities, and attitude of high myopic personnel are required in this regard.In this quasi-experiment study, 31 freshmen with high myopia in a national university were enrolled in 2014. The data were collected by validated and reliable questionnaire based on health belief model (HBM) and self-efficacy theory. The intervention program consisted of 1 educational session lasting 150 minutes by lecturing of high myopia complications, virtual reality experiencing, similarity modeling, and quibbling a film made on high myopia complications preventive concepts.Implementing the educational program showed immediate effect in knowledge, perceived susceptibility, perceived severity, self-efficacy, and preventive behavior intention. While 6 weeks after the educational program, significant increases were observed in cues to action, self-efficacy, and preventive behavior intention.This article provided that, after a single session, there was positive improvement in high myopia complication prevention behavior intention among participants. These positive effects confirmed the efficacy of the education program and will probably induce behavior change.

Paleogeothermal gradients and timing of oil generation in the Belden Formation, Eagle Basin, northwestern Colorado

USGS Publications Warehouse

Nuccio, V.F.; Johnson, S.Y.; Schenk, C.J.

1989-01-01

Paleogeothermal gradients and timing of oil generation for the Lower and Middle Pennsylvanian Belden Formation have been estimated for four locations in the Eagle Basin of northwestern Colorado, by comparing measured vitrinite reflectance with maturity modeling. Two thermal models were made for each location: one assumes a constant paleogeothermal gradient through time while the other is a two-stage model with changing paleogeothermal gradients. The two-stage paleogeothermal gradient scenario is considered more geologically realistic and is used to estimate the timing of oil generation throughout the Eagle basin. From the data and interpretations, one would expect Belden oil to be found in either upper Paleozoic or Mesozoic reservoir rocks. -Authors

Automation of reliability evaluation procedures through CARE - The computer-aided reliability estimation program.

NASA Technical Reports Server (NTRS)

Mathur, F. P.

1972-01-01

Description of an on-line interactive computer program called CARE (Computer-Aided Reliability Estimation) which can model self-repair and fault-tolerant organizations and perform certain other functions. Essentially CARE consists of a repository of mathematical equations defining the various basic redundancy schemes. These equations, under program control, are then interrelated to generate the desired mathematical model to fit the architecture of the system under evaluation. The mathematical model is then supplied with ground instances of its variables and is then evaluated to generate values for the reliability-theoretic functions applied to the model.

Design of a Low-Power, Small-Area AEC-Q100-Compliant SENT Transmitter in Signal Conditioning IC for Automotive Pressure and Temperature Complex Sensors in 180 Nm CMOS Technology.

PubMed

Ali, Imran; Rikhan, Behnam Samadpoor; Kim, Dong-Gyu; Lee, Dong-Soo; Rehman, Muhammad Riaz Ur; Abbasizadeh, Hamed; Asif, Muhammad; Lee, Minjae; Hwang, Keum Cheol; Yang, Youngoo; Lee, Kang-Yoon

2018-05-14

In this paper, a low-power and small-area Single Edge Nibble Transmission (SENT) transmitter design is proposed for automotive pressure and temperature complex sensor applications. To reduce the cost and size of the hardware, the pressure and temperature information is processed with a single integrated circuit (IC) and transmitted at the same time to the electronic control unit (ECU) through SENT. Due to its digital nature, it is immune to noise, has reduced sensitivity to electromagnetic interference (EMI), and generates low EMI. It requires only one PAD for its connectivity with ECU, and thus reduces the pin requirements, simplifies the connectivity, and minimizes the printed circuit board (PCB) complexity. The design is fully synthesizable, and independent of technology. The finite state machine-based approach is employed for area efficient implementation, and to translate the proposed architecture into hardware. The IC is fabricated in 1P6M 180 nm CMOS process with an area of (116 μm × 116 μm) and 4.314 K gates. The current consumption is 50 μA from a 1.8 V supply with a total 90 μW power. For compliance with AEC-Q100 for automotive reliability, a reverse and over voltage protection circuit is also implemented with human body model (HBM) electro-static discharge (ESD) of +6 kV, reverse voltage of -16 V to 0 V, over voltage of 8.2 V to 16 V, and fabricated area of 330 μm × 680 μm. The extensive testing, measurement, and simulation results prove that the design is fully compliant with SAE J2716 standard.

Design of a Low-Power, Small-Area AEC-Q100-Compliant SENT Transmitter in Signal Conditioning IC for Automotive Pressure and Temperature Complex Sensors in 180 Nm CMOS Technology

PubMed Central

Rikhan, Behnam Samadpoor; Kim, Dong-Gyu; Lee, Dong-Soo; Rehman, Muhammad Riaz Ur; Abbasizadeh, Hamed; Asif, Muhammad; Lee, Minjae; Yang, Youngoo; Lee, Kang-Yoon

2018-01-01

In this paper, a low-power and small-area Single Edge Nibble Transmission (SENT) transmitter design is proposed for automotive pressure and temperature complex sensor applications. To reduce the cost and size of the hardware, the pressure and temperature information is processed with a single integrated circuit (IC) and transmitted at the same time to the electronic control unit (ECU) through SENT. Due to its digital nature, it is immune to noise, has reduced sensitivity to electromagnetic interference (EMI), and generates low EMI. It requires only one PAD for its connectivity with ECU, and thus reduces the pin requirements, simplifies the connectivity, and minimizes the printed circuit board (PCB) complexity. The design is fully synthesizable, and independent of technology. The finite state machine-based approach is employed for area efficient implementation, and to translate the proposed architecture into hardware. The IC is fabricated in 1P6M 180 nm CMOS process with an area of (116 μm × 116 μm) and 4.314 K gates. The current consumption is 50 μA from a 1.8 V supply with a total 90 μW power. For compliance with AEC-Q100 for automotive reliability, a reverse and over voltage protection circuit is also implemented with human body model (HBM) electro-static discharge (ESD) of +6 kV, reverse voltage of −16 V to 0 V, over voltage of 8.2 V to 16 V, and fabricated area of 330 μm × 680 μm. The extensive testing, measurement, and simulation results prove that the design is fully compliant with SAE J2716 standard. PMID:29757996

Technical Note: Approximate Bayesian parameterization of a process-based tropical forest model

NASA Astrophysics Data System (ADS)

Hartig, F.; Dislich, C.; Wiegand, T.; Huth, A.

2014-02-01

Inverse parameter estimation of process-based models is a long-standing problem in many scientific disciplines. A key question for inverse parameter estimation is how to define the metric that quantifies how well model predictions fit to the data. This metric can be expressed by general cost or objective functions, but statistical inversion methods require a particular metric, the probability of observing the data given the model parameters, known as the likelihood. For technical and computational reasons, likelihoods for process-based stochastic models are usually based on general assumptions about variability in the observed data, and not on the stochasticity generated by the model. Only in recent years have new methods become available that allow the generation of likelihoods directly from stochastic simulations. Previous applications of these approximate Bayesian methods have concentrated on relatively simple models. Here, we report on the application of a simulation-based likelihood approximation for FORMIND, a parameter-rich individual-based model of tropical forest dynamics. We show that approximate Bayesian inference, based on a parametric likelihood approximation placed in a conventional Markov chain Monte Carlo (MCMC) sampler, performs well in retrieving known parameter values from virtual inventory data generated by the forest model. We analyze the results of the parameter estimation, examine its sensitivity to the choice and aggregation of model outputs and observed data (summary statistics), and demonstrate the application of this method by fitting the FORMIND model to field data from an Ecuadorian tropical forest. Finally, we discuss how this approach differs from approximate Bayesian computation (ABC), another method commonly used to generate simulation-based likelihood approximations. Our results demonstrate that simulation-based inference, which offers considerable conceptual advantages over more traditional methods for inverse parameter estimation, can be successfully applied to process-based models of high complexity. The methodology is particularly suitable for heterogeneous and complex data structures and can easily be adjusted to other model types, including most stochastic population and individual-based models. Our study therefore provides a blueprint for a fairly general approach to parameter estimation of stochastic process-based models.

Transportation Sector Model of the National Energy Modeling System. Volume 1

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

NONE

1998-01-01

This report documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Transportation Model (TRAN). The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated by the model. The NEMS Transportation Model comprises a series of semi-independent models which address different aspects of the transportation sector. The primary purpose of this model is to provide mid-term forecasts of transportation energy demand by fuel type including, but not limited to, motor gasoline, distillate, jet fuel, and alternative fuels (such as CNG) not commonly associated with transportation. Themore » current NEMS forecast horizon extends to the year 2010 and uses 1990 as the base year. Forecasts are generated through the separate consideration of energy consumption within the various modes of transport, including: private and fleet light-duty vehicles; aircraft; marine, rail, and truck freight; and various modes with minor overall impacts, such as mass transit and recreational boating. This approach is useful in assessing the impacts of policy initiatives, legislative mandates which affect individual modes of travel, and technological developments. The model also provides forecasts of selected intermediate values which are generated in order to determine energy consumption. These elements include estimates of passenger travel demand by automobile, air, or mass transit; estimates of the efficiency with which that demand is met; projections of vehicle stocks and the penetration of new technologies; and estimates of the demand for freight transport which are linked to forecasts of industrial output. Following the estimation of energy demand, TRAN produces forecasts of vehicular emissions of the following pollutants by source: oxides of sulfur, oxides of nitrogen, total carbon, carbon dioxide, carbon monoxide, and volatile organic compounds.« less

Modeled occupational exposures to gas-phase medical laser-generated air contaminants.

PubMed

Lippert, Julia F; Lacey, Steven E; Jones, Rachael M

2014-01-01

Exposure monitoring data indicate the potential for substantive exposure to laser-generated air contaminants (LGAC); however the diversity of medical lasers and their applications limit generalization from direct workplace monitoring. Emission rates of seven previously reported gas-phase constituents of medical laser-generated air contaminants (LGAC) were determined experimentally and used in a semi-empirical two-zone model to estimate a range of plausible occupational exposures to health care staff. Single-source emission rates were generated in an emission chamber as a one-compartment mass balance model at steady-state. Clinical facility parameters such as room size and ventilation rate were based on standard ventilation and environmental conditions required for a laser surgical facility in compliance with regulatory agencies. All input variables in the model including point source emission rates were varied over an appropriate distribution in a Monte Carlo simulation to generate a range of time-weighted average (TWA) concentrations in the near and far field zones of the room in a conservative approach inclusive of all contributing factors to inform future predictive models. The concentrations were assessed for risk and the highest values were shown to be at least three orders of magnitude lower than the relevant occupational exposure limits (OELs). Estimated values do not appear to present a significant exposure hazard within the conditions of our emission rate estimates.

A simulation of water pollution model parameter estimation

NASA Technical Reports Server (NTRS)

Kibler, J. F.

1976-01-01

A parameter estimation procedure for a water pollution transport model is elaborated. A two-dimensional instantaneous-release shear-diffusion model serves as representative of a simple transport process. Pollution concentration levels are arrived at via modeling of a remote-sensing system. The remote-sensed data are simulated by adding Gaussian noise to the concentration level values generated via the transport model. Model parameters are estimated from the simulated data using a least-squares batch processor. Resolution, sensor array size, and number and location of sensor readings can be found from the accuracies of the parameter estimates.

Nest survival modelling using a multi-species approach in forests managed for timber and biofuel feedstock

USGS Publications Warehouse

Loman, Zachary G.; Monroe, Adrian; Riffell, Samuel K.; Miller, Darren A.; Vilella, Francisco; Wheat, Bradley R.; Rush, Scott A.; Martin, James A.

2018-01-01

Switchgrass (Panicum virgatum) intercropping is a novel forest management practice for biomass production intended to generate cellulosic feedstocks within intensively managed loblolly pine‐dominated landscapes. These pine plantations are important for early‐successional bird species, as short rotation times continually maintain early‐successional habitat. We tested the efficacy of using community models compared to individual surrogate species models in understanding influences on nest survival. We analysed nest data to test for differences in habitat use for 14 bird species in plots managed for switchgrass intercropping and controls within loblolly pine (Pinus taeda) plantations in Mississippi, USA.We adapted hierarchical models using hyper‐parameters to incorporate information from both common and rare species to understand community‐level nest survival. This approach incorporates rare species that are often discarded due to low sample sizes, but can inform community‐level demographic parameter estimates. We illustrate use of this approach in generating both species‐level and community‐wide estimates of daily survival rates for songbird nests. We were able to include rare species with low sample size (minimum n = 5) to inform a hyper‐prior, allowing us to estimate effects of covariates on daily survival at the community level, then compare this with a single‐species approach using surrogate species. Using single‐species models, we were unable to generate estimates below a sample size of 21 nests per species.Community model species‐level survival and parameter estimates were similar to those generated by five single‐species models, with improved precision in community model parameters.Covariates of nest placement indicated that switchgrass at the nest site (<4 m) reduced daily nest survival, although intercropping at the forest stand level increased daily nest survival.Synthesis and applications. Community models represent a viable method for estimating community nest survival rates and effects of covariates while incorporating limited data for rarely detected species. Intercropping switchgrass in loblolly pine plantations slightly increased daily nest survival at the research plot scale (0.1 km2), although at a local scale (50 m2) switchgrass negatively influenced nest survival. A likely explanation is intercropping shifted community composition, favouring species with greater disturbance tolerance.

An architecture for efficient gravitational wave parameter estimation with multimodal linear surrogate models

NASA Astrophysics Data System (ADS)

O'Shaughnessy, Richard; Blackman, Jonathan; Field, Scott E.

2017-07-01

The recent direct observation of gravitational waves has further emphasized the desire for fast, low-cost, and accurate methods to infer the parameters of gravitational wave sources. Due to expense in waveform generation and data handling, the cost of evaluating the likelihood function limits the computational performance of these calculations. Building on recently developed surrogate models and a novel parameter estimation pipeline, we show how to quickly generate the likelihood function as an analytic, closed-form expression. Using a straightforward variant of a production-scale parameter estimation code, we demonstrate our method using surrogate models of effective-one-body and numerical relativity waveforms. Our study is the first time these models have been used for parameter estimation and one of the first ever parameter estimation calculations with multi-modal numerical relativity waveforms, which include all \\ell ≤slant 4 modes. Our grid-free method enables rapid parameter estimation for any waveform with a suitable reduced-order model. The methods described in this paper may also find use in other data analysis studies, such as vetting coincident events or the computation of the coalescing-compact-binary detection statistic.

INTEGRATED PROBABILISTIC AND DETERMINISTIC MODELING TECHNIQUES IN ESTIMATING EXPOSURE TO WATER-BORNE CONTAMINANTS: PART 2 PHARMACOKINETIC MODELING

EPA Science Inventory

The Total Exposure Model (TEM) uses deterministic and stochastic methods to estimate the exposure of a person performing daily activities of eating, drinking, showering, and bathing. There were 250 time histories generated, by subject with activities, for the three exposure ro...

Multilevel Analysis of Structural Equation Models via the EM Algorithm.

ERIC Educational Resources Information Center

Jo, See-Heyon

The question of how to analyze unbalanced hierarchical data generated from structural equation models has been a common problem for researchers and analysts. Among difficulties plaguing statistical modeling are estimation bias due to measurement error and the estimation of the effects of the individual's hierarchical social milieu. This paper…

An Estimation of Construction and Demolition Debris in Seoul, Korea: Waste Amount, Type, and Estimating Model.

PubMed

Seo, Seongwon; Hwang, Yongwoo

1999-08-01

Construction and demolition (C&D) debris is generated at the site of various construction activities. However, the amount of the debris is usually so large that it is necessary to estimate the amount of C&D debris as accurately as possible for effective waste management and control in urban areas. In this paper, an effective estimation method using a statistical model was proposed. The estimation process was composed of five steps: estimation of the life span of buildings; estimation of the floor area of buildings to be constructed and demolished; calculation of individual intensity units of C&D debris; and estimation of the future C&D debris production. This method was also applied in the city of Seoul as an actual case, and the estimated amount of C&D debris in Seoul in 2021 was approximately 24 million tons. Of this total amount, 98% was generated by demolition, and the main components of debris were concrete and brick.

Parameters of oscillation generation regions in open star cluster models

NASA Astrophysics Data System (ADS)

Danilov, V. M.; Putkov, S. I.

2017-07-01

We determine the masses and radii of central regions of open star cluster (OCL) models with small or zero entropy production and estimate the masses of oscillation generation regions in clustermodels based on the data of the phase-space coordinates of stars. The radii of such regions are close to the core radii of the OCL models. We develop a new method for estimating the total OCL masses based on the cluster core mass, the cluster and cluster core radii, and radial distribution of stars. This method yields estimates of dynamical masses of Pleiades, Praesepe, and M67, which agree well with the estimates of the total masses of the corresponding clusters based on proper motions and spectroscopic data for cluster stars.We construct the spectra and dispersion curves of the oscillations of the field of azimuthal velocities v φ in OCL models. Weak, low-amplitude unstable oscillations of v φ develop in cluster models near the cluster core boundary, and weak damped oscillations of v φ often develop at frequencies close to the frequencies of more powerful oscillations, which may reduce the non-stationarity degree in OCL models. We determine the number and parameters of such oscillations near the cores boundaries of cluster models. Such oscillations points to the possible role that gradient instability near the core of cluster models plays in the decrease of the mass of the oscillation generation regions and production of entropy in the cores of OCL models with massive extended cores.

Reaction Mechanism Generator: Automatic construction of chemical kinetic mechanisms

DOE PAGES

Gao, Connie W.; Allen, Joshua W.; Green, William H.; ...

2016-02-24

Reaction Mechanism Generator (RMG) constructs kinetic models composed of elementary chemical reaction steps using a general understanding of how molecules react. Species thermochemistry is estimated through Benson group additivity and reaction rate coefficients are estimated using a database of known rate rules and reaction templates. At its core, RMG relies on two fundamental data structures: graphs and trees. Graphs are used to represent chemical structures, and trees are used to represent thermodynamic and kinetic data. Models are generated using a rate-based algorithm which excludes species from the model based on reaction fluxes. RMG can generate reaction mechanisms for species involvingmore » carbon, hydrogen, oxygen, sulfur, and nitrogen. It also has capabilities for estimating transport and solvation properties, and it automatically computes pressure-dependent rate coefficients and identifies chemically-activated reaction paths. RMG is an object-oriented program written in Python, which provides a stable, robust programming architecture for developing an extensible and modular code base with a large suite of unit tests. Computationally intensive functions are cythonized for speed improvements.« less

Additive effect of mesenchymal stem cells and defibrotide in an arterial rat thrombosis model.

PubMed

Dilli, Dilek; Kılıç, Emine; Yumuşak, Nihat; Beken, Serdar; Uçkan Çetinkaya, Duygu; Karabulut, Ramazan; Zenciroğlu, Ayşegu L

2017-06-01

In this study, we aimed to investigate the additive effect of mesenchymal stem cells (MSC) and defibrotide (DFT) in a rat model of femoral arterial thrombosis. Thirty Sprague Dawley rats were included. An arterial thrombosis model by ferric chloride (FeCl3) was developed in the left femoral artery. The rats were equally assigned to 5 groups: Group 1-Sham-operated (without arterial injury); Group 2-Phosphate buffered saline (PBS) injected; Group 3-MSC; Group 4-DFT; Group 5-MSC + DFT. All had two intraperitoneal injections of 0.5 ml: the 1st injection was 4 h after the procedure and the 2nd one 48 h after the 1st injection. The rats were sacrificed 7 days after the 2nd injection. Although the use of human bone marrow-derived (hBM) hBM-MSC or DFT alone enabled partial resolution of the thrombus, combining them resulted in near-complete resolution. Neovascularization was two-fold better in hBM-MSC + DFT treated rats (11.6 ± 2.4 channels) compared with the hBM-MSC (3.8 ± 2.7 channels) and DFT groups (5.5 ± 1.8 channels) (P < 0.0001 and P= 0.002, respectively). The combined use of hBM-MSC and DFT in a rat model of arterial thrombosis showed additive effect resulting in near-complete resolution of the thrombus.

Comparison of Methods for Estimating Prevalence of Chronic Diseases and Health Behaviors for Small Geographic Areas: Boston Validation Study, 2013

PubMed Central

Holt, James B.; Zhang, Xingyou; Lu, Hua; Shah, Snehal N.; Dooley, Daniel P.; Matthews, Kevin A.; Croft, Janet B.

2017-01-01

Introduction Local health authorities need small-area estimates for prevalence of chronic diseases and health behaviors for multiple purposes. We generated city-level and census-tract–level prevalence estimates of 27 measures for the 500 largest US cities. Methods To validate the methodology, we constructed multilevel logistic regressions to predict 10 selected health indicators among adults aged 18 years or older by using 2013 Behavioral Risk Factor Surveillance System (BRFSS) data; we applied their predicted probabilities to census population data to generate city-level, neighborhood-level, and zip-code–level estimates for the city of Boston, Massachusetts. Results By comparing the predicted estimates with their corresponding direct estimates from a locally administered survey (Boston BRFSS 2010 and 2013), we found that our model-based estimates for most of the selected health indicators at the city level were close to the direct estimates from the local survey. We also found strong correlation between the model-based estimates and direct survey estimates at neighborhood and zip code levels for most indicators. Conclusion Findings suggest that our model-based estimates are reliable and valid at the city level for certain health outcomes. Local health authorities can use the neighborhood-level estimates if high quality local health survey data are not otherwise available. PMID:29049020

CAN A MODEL TRANSFERABILITY FRAMEWORK IMPROVE ECOSYSTEM SERVICE ESTIMATES? A CASE STUDY OF SOIL FOREST CARBON SEQUESTRATION IN TILLAMOOK BAY, OR, USA

EPA Science Inventory

Budget constraints and policies that limit primary data collection have fueled a practice of transferring estimates (or models to generate estimates) of ecological endpoints from sites where primary data exists to sites where little to no primary data were collected. Whereas bene...

Estimating Contraceptive Prevalence Using Logistics Data for Short-Acting Methods: Analysis Across 30 Countries.

PubMed

Cunningham, Marc; Bock, Ariella; Brown, Niquelle; Sacher, Suzy; Hatch, Benjamin; Inglis, Andrew; Aronovich, Dana

2015-09-01

Contraceptive prevalence rate (CPR) is a vital indicator used by country governments, international donors, and other stakeholders for measuring progress in family planning programs against country targets and global initiatives as well as for estimating health outcomes. Because of the need for more frequent CPR estimates than population-based surveys currently provide, alternative approaches for estimating CPRs are being explored, including using contraceptive logistics data. Using data from the Demographic and Health Surveys (DHS) in 30 countries, population data from the United States Census Bureau International Database, and logistics data from the Procurement Planning and Monitoring Report (PPMR) and the Pipeline Monitoring and Procurement Planning System (PipeLine), we developed and evaluated 3 models to generate country-level, public-sector contraceptive prevalence estimates for injectable contraceptives, oral contraceptives, and male condoms. Models included: direct estimation through existing couple-years of protection (CYP) conversion factors, bivariate linear regression, and multivariate linear regression. Model evaluation consisted of comparing the referent DHS prevalence rates for each short-acting method with the model-generated prevalence rate using multiple metrics, including mean absolute error and proportion of countries where the modeled prevalence rate for each method was within 1, 2, or 5 percentage points of the DHS referent value. For the methods studied, family planning use estimates from public-sector logistics data were correlated with those from the DHS, validating the quality and accuracy of current public-sector logistics data. Logistics data for oral and injectable contraceptives were significantly associated (P<.05) with the referent DHS values for both bivariate and multivariate models. For condoms, however, that association was only significant for the bivariate model. With the exception of the CYP-based model for condoms, models were able to estimate public-sector prevalence rates for each short-acting method to within 2 percentage points in at least 85% of countries. Public-sector contraceptive logistics data are strongly correlated with public-sector prevalence rates for short-acting methods, demonstrating the quality of current logistics data and their ability to provide relatively accurate prevalence estimates. The models provide a starting point for generating interim estimates of contraceptive use when timely survey data are unavailable. All models except the condoms CYP model performed well; the regression models were most accurate but the CYP model offers the simplest calculation method. Future work extending the research to other modern methods, relating subnational logistics data with prevalence rates, and tracking that relationship over time is needed. © Cunningham et al.

Estimating Contraceptive Prevalence Using Logistics Data for Short-Acting Methods: Analysis Across 30 Countries

PubMed Central

Cunningham, Marc; Brown, Niquelle; Sacher, Suzy; Hatch, Benjamin; Inglis, Andrew; Aronovich, Dana

2015-01-01

Background: Contraceptive prevalence rate (CPR) is a vital indicator used by country governments, international donors, and other stakeholders for measuring progress in family planning programs against country targets and global initiatives as well as for estimating health outcomes. Because of the need for more frequent CPR estimates than population-based surveys currently provide, alternative approaches for estimating CPRs are being explored, including using contraceptive logistics data. Methods: Using data from the Demographic and Health Surveys (DHS) in 30 countries, population data from the United States Census Bureau International Database, and logistics data from the Procurement Planning and Monitoring Report (PPMR) and the Pipeline Monitoring and Procurement Planning System (PipeLine), we developed and evaluated 3 models to generate country-level, public-sector contraceptive prevalence estimates for injectable contraceptives, oral contraceptives, and male condoms. Models included: direct estimation through existing couple-years of protection (CYP) conversion factors, bivariate linear regression, and multivariate linear regression. Model evaluation consisted of comparing the referent DHS prevalence rates for each short-acting method with the model-generated prevalence rate using multiple metrics, including mean absolute error and proportion of countries where the modeled prevalence rate for each method was within 1, 2, or 5 percentage points of the DHS referent value. Results: For the methods studied, family planning use estimates from public-sector logistics data were correlated with those from the DHS, validating the quality and accuracy of current public-sector logistics data. Logistics data for oral and injectable contraceptives were significantly associated (P<.05) with the referent DHS values for both bivariate and multivariate models. For condoms, however, that association was only significant for the bivariate model. With the exception of the CYP-based model for condoms, models were able to estimate public-sector prevalence rates for each short-acting method to within 2 percentage points in at least 85% of countries. Conclusions: Public-sector contraceptive logistics data are strongly correlated with public-sector prevalence rates for short-acting methods, demonstrating the quality of current logistics data and their ability to provide relatively accurate prevalence estimates. The models provide a starting point for generating interim estimates of contraceptive use when timely survey data are unavailable. All models except the condoms CYP model performed well; the regression models were most accurate but the CYP model offers the simplest calculation method. Future work extending the research to other modern methods, relating subnational logistics data with prevalence rates, and tracking that relationship over time is needed. PMID:26374805

Advances in Time Estimation Methods for Molecular Data.

PubMed

Kumar, Sudhir; Hedges, S Blair

2016-04-01

Molecular dating has become central to placing a temporal dimension on the tree of life. Methods for estimating divergence times have been developed for over 50 years, beginning with the proposal of molecular clock in 1962. We categorize the chronological development of these methods into four generations based on the timing of their origin. In the first generation approaches (1960s-1980s), a strict molecular clock was assumed to date divergences. In the second generation approaches (1990s), the equality of evolutionary rates between species was first tested and then a strict molecular clock applied to estimate divergence times. The third generation approaches (since ∼2000) account for differences in evolutionary rates across the tree by using a statistical model, obviating the need to assume a clock or to test the equality of evolutionary rates among species. Bayesian methods in the third generation require a specific or uniform prior on the speciation-process and enable the inclusion of uncertainty in clock calibrations. The fourth generation approaches (since 2012) allow rates to vary from branch to branch, but do not need prior selection of a statistical model to describe the rate variation or the specification of speciation model. With high accuracy, comparable to Bayesian approaches, and speeds that are orders of magnitude faster, fourth generation methods are able to produce reliable timetrees of thousands of species using genome scale data. We found that early time estimates from second generation studies are similar to those of third and fourth generation studies, indicating that methodological advances have not fundamentally altered the timetree of life, but rather have facilitated time estimation by enabling the inclusion of more species. Nonetheless, we feel an urgent need for testing the accuracy and precision of third and fourth generation methods, including their robustness to misspecification of priors in the analysis of large phylogenies and data sets. © The Author(s) 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

eHealth Use Among First-Generation Immigrants From Pakistan in the Oslo Area, Norway, With Focus on Diabetes: Survey Protocol

PubMed Central

Kjøllesdal, Marte Karoline Råberg; Mirkovic, Jelena; Andreassen, Hege Kristin

2016-01-01

Background A variety of eHealth services are available and commonly used by the general public. eHealth has the potential to engage and empower people with managing their health. The prerequisite is, however, that eHealth services are adapted to the sociocultural heterogeneity of the user base and are available in a language and with contents that fit the users’ preference, skills, and abilities. Pakistani immigrants in the Oslo area, Norway, have a much higher risk of Type-2 diabetes (T2D) than their Norwegian counterparts do. In spite of having access to information and communication technology (ICT) and the Internet, ICT skills in this population are reported to be relatively low. Further, there is insufficient information about their use of and attitudes toward eHealth services, necessitating investigation of this group in particular. Objective This study targets first-generation immigrants from Pakistan living in the Oslo area and examines their use of and attitudes toward eHealth services, specifically: information searches, communication using ICT, and use of ICT for self-management or decision making, all concerning T2D. Methods Due to a high prevalence of low literacy among the target population, we employed questionnaire-based individual interviews. The questionnaire was developed by implementing potentially relevant theoretical constructs (technology acceptance model (TAM) and health belief model (HBM)) as measures. To explore issues around language, culture, and general ICT skills, we also implemented questions that we assume were particularly relevant in the context studied but do not appear in any theoretical frameworks. The questionnaire was revised to reflect results of a pilot study involving 10 participants. We employed culturally sensitive sampling methods to reach informants who could otherwise fail to be included in the survey. Results This paper presents a survey protocol. The data collection is ongoing. The aim is to collect 200 responses in total by March 2016. Conclusions For eHealth to become an influential social innovation, equal access to eHealth services regardless of users’ language, culture, and ICT skills is a prerequisite. Results from this study will be of importance for understanding how people who may not maximally benefit from eHealth services today could be targeted in the future. PMID:27113854

First-order kinetic gas generation model parameters for wet landfills.

PubMed

Faour, Ayman A; Reinhart, Debra R; You, Huaxin

2007-01-01

Landfill gas collection data from wet landfill cells were analyzed and first-order gas generation model parameters were estimated for the US EPA landfill gas emissions model (LandGEM). Parameters were determined through statistical comparison of predicted and actual gas collection. The US EPA LandGEM model appeared to fit the data well, provided it is preceded by a lag phase, which on average was 1.5 years. The first-order reaction rate constant, k, and the methane generation potential, L(o), were estimated for a set of landfills with short-term waste placement and long-term gas collection data. Mean and 95% confidence parameter estimates for these data sets were found using mixed-effects model regression followed by bootstrap analysis. The mean values for the specific methane volume produced during the lag phase (V(sto)), L(o), and k were 33 m(3)/Megagrams (Mg), 76 m(3)/Mg, and 0.28 year(-1), respectively. Parameters were also estimated for three full scale wet landfills where waste was placed over many years. The k and L(o) estimated for these landfills were 0.21 year(-1), 115 m(3)/Mg, 0.11 year(-1), 95 m(3)/Mg, and 0.12 year(-1) and 87 m(3)/Mg, respectively. A group of data points from wet landfills cells with short-term data were also analyzed. A conservative set of parameter estimates was suggested based on the upper 95% confidence interval parameters as a k of 0.3 year(-1) and a L(o) of 100 m(3)/Mg if design is optimized and the lag is minimized.

Lessons learnt on recruitment and fieldwork from a pilot European human biomonitoring survey.

PubMed

Fiddicke, Ulrike; Becker, Kerstin; Schwedler, Gerda; Seiwert, Margarete; Joas, Reinhard; Joas, Anke; Biot, Pierre; Aerts, Dominique; Casteleyn, Ludwine; Dumez, Birgit; Castaño, Argelia; Esteban, Marta; Angerer, Jürgen; Koch, Holger M; Schoeters, Greet; Den Hond, Elly; Sepai, Ovnair; Exley, Karen; Knudsen, Lisbeth E; Horvat, Milena; Bloemen, Louis; Katsonouri, Andromachi; Hadjipanayis, Adamos; Cerna, Milena; Krsková, Andrea; Jensen, Janne Fangel; Nielsen, Jeanette K S; Rudnai, Peter; Közepésy, Szilvia; Gutleb, Arno C; Fischer, Marc E; Ligocka, Danuta; Kamińska, Joanna; Reis, M Fátima; Namorado, Sónia; Lupsa, Ioana-Rodica; Gurzau, Anca E; Halzlová, Katarína; Mazej, Darja; Tratnik, Janja Snoj; Rivas, Teresa C; Gómez, Silvia; Berglund, Marika; Larsson, Kristin; Lehmann, Andrea; Crettaz, Pierre; Dewolf, Marie-Christine; Burns, Damien; Kellegher, Anne; Kolossa-Gehring, Marike

2015-08-01

Within the European Environment and Health Action Plan an initiative to establish a coherent human biomonitoring approach in Europe was started. The project COPHES (COnsortium to Perform Human biomonitoring on a European Scale ) developed recommendations for a harmonized conduct of a human biomonitoring (HBM) survey which came into action as the pilot study DEMOCOPHES (DEMOnstration of a study to COordinate and Perform Human biomonitoring on a European Scale). Seventeen European countries conducted a survey with harmonized instruments for, inter alia, recruitment, fieldwork and sampling, in autumn/winter 2011/2012. Based on the countries' experiences of conducting the pilot study, following lessons learnt were compiled: the harmonized fieldwork instruments (basic questionnaire, urine and hair sampling) turned out to be very valuable for future HBM surveys on the European scale. A school approach was favoured by most of the countries to recruit school-aged children according to the established guidelines and country specific experiences. To avoid a low participation rate, intensive communication with the involved institutions and possible participants proved to be necessary. The communication material should also include information on exclusion criteria and offered incentives. Telephone contact to the participants the day before fieldwork during the survey can prevent the forgetting of appointments and first morning urine samples. To achieve comparable results on the European scale, training of interviewers in all issues of recruitment, fieldwork and sampling through information material and training sessions is crucial. A survey involving many European countries needs time for preparation and conduct. Materials for quality control prepared for all steps of recruitment, fieldwork and sampling proved to be important to warrant reliable results. Copyright © 2014 Elsevier Inc. All rights reserved.

Interaction of MYC with host cell factor-1 is mediated by the evolutionarily conserved Myc box IV motif.

PubMed

Thomas, L R; Foshage, A M; Weissmiller, A M; Popay, T M; Grieb, B C; Qualls, S J; Ng, V; Carboneau, B; Lorey, S; Eischen, C M; Tansey, W P

2016-07-07

The MYC family of oncogenes encodes a set of three related transcription factors that are overexpressed in many human tumors and contribute to the cancer-related deaths of more than 70,000 Americans every year. MYC proteins drive tumorigenesis by interacting with co-factors that enable them to regulate the expression of thousands of genes linked to cell growth, proliferation, metabolism and genome stability. One effective way to identify critical co-factors required for MYC function has been to focus on sequence motifs within MYC that are conserved throughout evolution, on the assumption that their conservation is driven by protein-protein interactions that are vital for MYC activity. In addition to their DNA-binding domains, MYC proteins carry five regions of high sequence conservation known as Myc boxes (Mb). To date, four of the Mb motifs (MbI, MbII, MbIIIa and MbIIIb) have had a molecular function assigned to them, but the precise role of the remaining Mb, MbIV, and the reason for its preservation in vertebrate Myc proteins, is unknown. Here, we show that MbIV is required for the association of MYC with the abundant transcriptional coregulator host cell factor-1 (HCF-1). We show that the invariant core of MbIV resembles the tetrapeptide HCF-binding motif (HBM) found in many HCF-interaction partners, and demonstrate that MYC interacts with HCF-1 in a manner indistinguishable from the prototypical HBM-containing protein VP16. Finally, we show that rationalized point mutations in MYC that disrupt interaction with HCF-1 attenuate the ability of MYC to drive tumorigenesis in mice. Together, these data expose a molecular function for MbIV and indicate that HCF-1 is an important co-factor for MYC.

PIMS: Memristor-Based Processing-in-Memory-and-Storage.

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

Cook, Jeanine

Continued progress in computing has augmented the quest for higher performance with a new quest for higher energy efficiency. This has led to the re-emergence of Processing-In-Memory (PIM) ar- chitectures that offer higher density and performance with some boost in energy efficiency. Past PIM work either integrated a standard CPU with a conventional DRAM to improve the CPU- memory link, or used a bit-level processor with Single Instruction Multiple Data (SIMD) control, but neither matched the energy consumption of the memory to the computation. We originally proposed to develop a new architecture derived from PIM that more effectively addressed energymore » efficiency for high performance scientific, data analytics, and neuromorphic applications. We also originally planned to implement a von Neumann architecture with arithmetic/logic units (ALUs) that matched the power consumption of an advanced storage array to maximize energy efficiency. Implementing this architecture in storage was our original idea, since by augmenting storage (in- stead of memory), the system could address both in-memory computation and applications that accessed larger data sets directly from storage, hence Processing-in-Memory-and-Storage (PIMS). However, as our research matured, we discovered several things that changed our original direc- tion, the most important being that a PIM that implements a standard von Neumann-type archi- tecture results in significant energy efficiency improvement, but only about a O(10) performance improvement. In addition to this, the emergence of new memory technologies moved us to propos- ing a non-von Neumann architecture, called Superstrider, implemented not in storage, but in a new DRAM technology called High Bandwidth Memory (HBM). HBM is a stacked DRAM tech- nology that includes a logic layer where an architecture such as Superstrider could potentially be implemented.« less

Integration of Process Models and Remote Sensing for Estimating Productivity, Soil Moisture, and Energy Fluxes in a Tallgrass Prairie Ecosystem

EPA Science Inventory

We describe a research program aimed at integrating remotely sensed data with an ecosystem model (VELMA) and a soil-vegetation-atmosphere transfer (SVAT) model (SEBS) for generating spatially explicit, regional scale estimates of productivity (biomass) and energy\\mass exchanges i...

Modelling small-area inequality in premature mortality using years of life lost rates

NASA Astrophysics Data System (ADS)

Congdon, Peter

2013-04-01

Analysis of premature mortality variations via standardized expected years of life lost (SEYLL) measures raises questions about suitable modelling for mortality data, especially when developing SEYLL profiles for areas with small populations. Existing fixed effects estimation methods take no account of correlations in mortality levels over ages, causes, socio-ethnic groups or areas. They also do not specify an underlying data generating process, or a likelihood model that can include trends or correlations, and are likely to produce unstable estimates for small-areas. An alternative strategy involves a fully specified data generation process, and a random effects model which "borrows strength" to produce stable SEYLL estimates, allowing for correlations between ages, areas and socio-ethnic groups. The resulting modelling strategy is applied to gender-specific differences in SEYLL rates in small-areas in NE London, and to cause-specific mortality for leading causes of premature mortality in these areas.

CLIGEN: Addressing deficiencies in the generator and its databases

USDA-ARS?s Scientific Manuscript database

CLIGEN is a stochastic generator that estimates daily temperatures, precipitation and other weather related phenomena. It is an intermediate model used by the Water Erosion Prediction Program (WEPP), the Wind Erosion Prediction System (WEPS), and other models that require daily weather observations....

HIV/AIDS among youth in urban informal (slum) settlements in Kenya: What are the correlates of and motivations for HIV testing?

PubMed Central

2011-01-01

Background Although HIV counseling and testing (HCT) is widely considered an integral component of HIV prevention and treatment strategies, few studies have examined HCT behavior among youth in sub-Saharan Africa-a group at substantial risk for HIV infection. In this paper we examine: the correlates of HIV testing, including whether associations differ based on the context under which a person gets tested; and the motivations for getting (or not getting) an HIV test. Methods Drawing on data collected in 2007 from 4028 (51% male) youth (12-22 years) living in Korogocho and Viwandani slum settlements in Nairobi (Kenya), we explored the correlates of and motivations for HIV testing using the Health Belief Model (HBM) as a theoretical framework. Multinomial and binary logistic regression analyses were employed to examine correlates of HIV testing. Bivariate analyses were employed to assess reasons for or against testing. Results Nineteen percent of males and 35% of females had been tested. Among tested youth, 74% of males and 43% of females had requested for their most recent HIV test while 7% of males and 32% of females reported that they were required to take their most recent HIV test (i.e., the test was mandatory). About 60% of females who had ever had sex received an HIV test because they were pregnant. We found modest support for the HBM in explaining variation in testing behavior. In particular, we found that perceived risk for HIV infection may drive HIV testing among youth. For example, about half of youth who had ever had sex but had never been tested reported that they had not been tested because they were not at risk. Conclusions Targeted interventions to help young people correctly assess their level of risk and to increase awareness of the potential value of HIV testing may help enhance uptake of testing services. Given the relative success of Prevention of Mother-to-Child Transmission (PMTCT) services in increasing HIV testing rates among females, routine provider-initiated testing and counseling among all clients visiting medical facilities may provide an important avenue to increase HIV status awareness among the general population and especially among males. PMID:21888666

JEDI: Jobs and Economic Development Impacts Model, National Renewable Energy Laboratory (NREL) (Fact Sheet)

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

Not Available

2009-12-01

The Jobs and Economic Development Impact (JEDI) models are user-friendly tools that estimate the economic impacts of constructing and operating power generation and biofuel plants at the local (usually state) level. First developed by NREL's Wind Powering America program to model wind energy jobs and impacts, JEDI has been expanded to biofuels, concentrating solar power, coal, and natural gas power plants. Based on project-specific and default inputs (derived from industry norms), JEDI estimates the number of jobs and economic impacts to a local area (usually a state) that could reasonably be supported by a power generation project. For example, JEDImore » estimates the number of in-state construction jobs from a new wind farm. This fact sheet provides an overview of the JEDI model as it pertains to wind energy projects.« less

Estimating the remaining useful life of bearings using a neuro-local linear estimator-based method.

PubMed

Ahmad, Wasim; Ali Khan, Sheraz; Kim, Jong-Myon

2017-05-01

Estimating the remaining useful life (RUL) of a bearing is required for maintenance scheduling. While the degradation behavior of a bearing changes during its lifetime, it is usually assumed to follow a single model. In this letter, bearing degradation is modeled by a monotonically increasing function that is globally non-linear and locally linearized. The model is generated using historical data that is smoothed with a local linear estimator. A neural network learns this model and then predicts future levels of vibration acceleration to estimate the RUL of a bearing. The proposed method yields reasonably accurate estimates of the RUL of a bearing at different points during its operational life.

Modeling the Hyperdistribution of Item Parameters To Improve the Accuracy of Recovery in Estimation Procedures.

ERIC Educational Resources Information Center

Matthews-Lopez, Joy L.; Hombo, Catherine M.

The purpose of this study was to examine the recovery of item parameters in simulated Automatic Item Generation (AIG) conditions, using Markov chain Monte Carlo (MCMC) estimation methods to attempt to recover the generating distributions. To do this, variability in item and ability parameters was manipulated. Realistic AIG conditions were…

Sub-sampling genetic data to estimate black bear population size: A case study

USGS Publications Warehouse

Tredick, C.A.; Vaughan, M.R.; Stauffer, D.F.; Simek, S.L.; Eason, T.

2007-01-01

Costs for genetic analysis of hair samples collected for individual identification of bears average approximately US$50 [2004] per sample. This can easily exceed budgetary allowances for large-scale studies or studies of high-density bear populations. We used 2 genetic datasets from 2 areas in the southeastern United States to explore how reducing costs of analysis by sub-sampling affected precision and accuracy of resulting population estimates. We used several sub-sampling scenarios to create subsets of the full datasets and compared summary statistics, population estimates, and precision of estimates generated from these subsets to estimates generated from the complete datasets. Our results suggested that bias and precision of estimates improved as the proportion of total samples used increased, and heterogeneity models (e.g., Mh[CHAO]) were more robust to reduced sample sizes than other models (e.g., behavior models). We recommend that only high-quality samples (>5 hair follicles) be used when budgets are constrained, and efforts should be made to maximize capture and recapture rates in the field.

Uncertainties of flood frequency estimation approaches based on continuous simulation using data resampling

NASA Astrophysics Data System (ADS)

Arnaud, Patrick; Cantet, Philippe; Odry, Jean

2017-11-01

Flood frequency analyses (FFAs) are needed for flood risk management. Many methods exist ranging from classical purely statistical approaches to more complex approaches based on process simulation. The results of these methods are associated with uncertainties that are sometimes difficult to estimate due to the complexity of the approaches or the number of parameters, especially for process simulation. This is the case of the simulation-based FFA approach called SHYREG presented in this paper, in which a rainfall generator is coupled with a simple rainfall-runoff model in an attempt to estimate the uncertainties due to the estimation of the seven parameters needed to estimate flood frequencies. The six parameters of the rainfall generator are mean values, so their theoretical distribution is known and can be used to estimate the generator uncertainties. In contrast, the theoretical distribution of the single hydrological model parameter is unknown; consequently, a bootstrap method is applied to estimate the calibration uncertainties. The propagation of uncertainty from the rainfall generator to the hydrological model is also taken into account. This method is applied to 1112 basins throughout France. Uncertainties coming from the SHYREG method and from purely statistical approaches are compared, and the results are discussed according to the length of the recorded observations, basin size and basin location. Uncertainties of the SHYREG method decrease as the basin size increases or as the length of the recorded flow increases. Moreover, the results show that the confidence intervals of the SHYREG method are relatively small despite the complexity of the method and the number of parameters (seven). This is due to the stability of the parameters and takes into account the dependence of uncertainties due to the rainfall model and the hydrological calibration. Indeed, the uncertainties on the flow quantiles are on the same order of magnitude as those associated with the use of a statistical law with two parameters (here generalised extreme value Type I distribution) and clearly lower than those associated with the use of a three-parameter law (here generalised extreme value Type II distribution). For extreme flood quantiles, the uncertainties are mostly due to the rainfall generator because of the progressive saturation of the hydrological model.

ESTIMATING TREATMENT EFFECTS ON HEALTHCARE COSTS UNDER EXOGENEITY: IS THERE A ‘MAGIC BULLET’?

PubMed Central

Polsky, Daniel; Manning, Willard G.

2011-01-01

Methods for estimating average treatment effects, under the assumption of no unmeasured confounders, include regression models; propensity score adjustments using stratification, weighting, or matching; and doubly robust estimators (a combination of both). Researchers continue to debate about the best estimator for outcomes such as health care cost data, as they are usually characterized by an asymmetric distribution and heterogeneous treatment effects,. Challenges in finding the right specifications for regression models are well documented in the literature. Propensity score estimators are proposed as alternatives to overcoming these challenges. Using simulations, we find that in moderate size samples (n= 5000), balancing on propensity scores that are estimated from saturated specifications can balance the covariate means across treatment arms but fails to balance higher-order moments and covariances amongst covariates. Therefore, unlike regression model, even if a formal model for outcomes is not required, propensity score estimators can be inefficient at best and biased at worst for health care cost data. Our simulation study, designed to take a ‘proof by contradiction’ approach, proves that no one estimator can be considered the best under all data generating processes for outcomes such as costs. The inverse-propensity weighted estimator is most likely to be unbiased under alternate data generating processes but is prone to bias under misspecification of the propensity score model and is inefficient compared to an unbiased regression estimator. Our results show that there are no ‘magic bullets’ when it comes to estimating treatment effects in health care costs. Care should be taken before naively applying any one estimator to estimate average treatment effects in these data. We illustrate the performance of alternative methods in a cost dataset on breast cancer treatment. PMID:22199462

Model-based mean square error estimators for k-nearest neighbour predictions and applications using remotely sensed data for forest inventories

Treesearch

Steen Magnussen; Ronald E. McRoberts; Erkki O. Tomppo

2009-01-01

New model-based estimators of the uncertainty of pixel-level and areal k-nearest neighbour (knn) predictions of attribute Y from remotely-sensed ancillary data X are presented. Non-parametric functions predict Y from scalar 'Single Index Model' transformations of X. Variance functions generated...

A generative probabilistic model and discriminative extensions for brain lesion segmentation – with application to tumor and stroke

PubMed Central

Menze, Bjoern H.; Van Leemput, Koen; Lashkari, Danial; Riklin-Raviv, Tammy; Geremia, Ezequiel; Alberts, Esther; Gruber, Philipp; Wegener, Susanne; Weber, Marc-André; Székely, Gabor; Ayache, Nicholas; Golland, Polina

2016-01-01

We introduce a generative probabilistic model for segmentation of brain lesions in multi-dimensional images that generalizes the EM segmenter, a common approach for modelling brain images using Gaussian mixtures and a probabilistic tissue atlas that employs expectation-maximization (EM) to estimate the label map for a new image. Our model augments the probabilistic atlas of the healthy tissues with a latent atlas of the lesion. We derive an estimation algorithm with closed-form EM update equations. The method extracts a latent atlas prior distribution and the lesion posterior distributions jointly from the image data. It delineates lesion areas individually in each channel, allowing for differences in lesion appearance across modalities, an important feature of many brain tumor imaging sequences. We also propose discriminative model extensions to map the output of the generative model to arbitrary labels with semantic and biological meaning, such as “tumor core” or “fluid-filled structure”, but without a one-to-one correspondence to the hypo-or hyper-intense lesion areas identified by the generative model. We test the approach in two image sets: the publicly available BRATS set of glioma patient scans, and multimodal brain images of patients with acute and subacute ischemic stroke. We find the generative model that has been designed for tumor lesions to generalize well to stroke images, and the generative-discriminative model to be one of the top ranking methods in the BRATS evaluation. PMID:26599702

A prototype data assimilation framework for generating spatiotemporally continuous SWOT data products

NASA Astrophysics Data System (ADS)

Andreadis, K.; Margulis, S. A.; Li, D.; Lettenmaier, D. P.

2017-12-01

The Surface Water and Ocean Topography (SWOT) satellite will provide critical surface water observations for the hydrologic community. However, production of key SWOT variables, such as river discharge and surface inundation, as well as lake, reservoir, and wetland storage change will be complicated by the discontinuity of the observations in space and time. A methodology that generates products with spatially and temporally continuous fields based on SWOT observables would be highly desirable. Data assimilation provides a mechanism for merging observations from SWOT with model predictions in order to produce estimates of quantities such as river discharge, storage change, and water heights for locations and times when there is no satellite overpass or other constraints (such as layover) render the measurement unusable. We describe here a prototype assimilation system with application to the Upper Mississippi basin, implemented using synthetic SWOT observations. We use a hydrologic model (VIC) coupled with a hydrodynamic model (LISFLOOD-FP) which generates "true" fields of surface water variables. The true fields are then used to generate synthetic SWOT observations using the SWOT Instrument Simulator. We also perform a "first-guess" (or open-loop) simulation with the coupled model using a configuration that contains errors representative of the imperfect knowledge of parameters and input data, including channel topography, bankfull widths and depths, and inflows, to create an ensemble of 20 model trajectories. Subsequently we assimilate the synthetic SWOT observations into the open-loop model results to estimate water surface elevation, discharge, and storage change. Our preliminary results using three data assimilation strategies show that all improve the water surface elevation estimate accuracy by 25% - 35% for a river reach of the upper Mississippi River. Ongoing work is examining whether the improved water surface elevation estimates propagate to improvements in river discharge.

A Comparison of Turbidity-Based and Streamflow-Based Estimates of Suspended-Sediment Concentrations in Three Chesapeake Bay Tributaries

USGS Publications Warehouse

Jastram, John D.; Moyer, Douglas; Hyer, Kenneth

2009-01-01

Fluvial transport of sediment into the Chesapeake Bay estuary is a persistent water-quality issue with major implications for the overall health of the bay ecosystem. Accurately and precisely estimating the suspended-sediment concentrations (SSC) and loads that are delivered to the bay, however, remains challenging. Although manual sampling of SSC produces an accurate series of point-in-time measurements, robust extrapolation to unmeasured periods (especially highflow periods) has proven to be difficult. Sediment concentrations typically have been estimated using regression relations between individual SSC values and associated streamflow values; however, suspended-sediment transport during storm events is extremely variable, and it is often difficult to relate a unique SSC to a given streamflow. With this limitation for estimating SSC, innovative approaches for generating detailed records of suspended-sediment transport are needed. One effective method for improved suspended-sediment determination involves the continuous monitoring of turbidity as a surrogate for SSC. Turbidity measurements are theoretically well correlated to SSC because turbidity represents a measure of water clarity that is directly influenced by suspended sediments; thus, turbidity-based estimation models typically are effective tools for generating SSC data. The U.S. Geological Survey, in cooperation with the U.S. Environmental Protection Agency Chesapeake Bay Program and Virginia Department of Environmental Quality, initiated continuous turbidity monitoring on three major tributaries of the bay - the James, Rappahannock, and North Fork Shenandoah Rivers - to evaluate the use of turbidity as a sediment surrogate in rivers that deliver sediment to the bay. Results of this surrogate approach were compared to the traditionally applied streamflow-based approach for estimating SSC. Additionally, evaluation and comparison of these two approaches were conducted for nutrient estimations. Results demonstrate that the application of turbidity-based estimation models provides an improved method for generating a continuous record of SSC, relative to the classical approach that uses streamflow as a surrogate for SSC. Turbidity-based estimates of SSC were found to be more accurate and precise than SSC estimates from streamflow-based approaches. The turbidity-based SSC estimation models explained 92 to 98 percent of the variability in SSC, while streamflow-based models explained 74 to 88 percent of the variability in SSC. Furthermore, the mean absolute error of turbidity-based SSC estimates was 50 to 87 percent less than the corresponding values from the streamflow-based models. Statistically significant differences were detected between the distributions of residual errors and estimates from the two approaches, indicating that the turbidity-based approach yields estimates of SSC with greater precision than the streamflow-based approach. Similar improvements were identified for turbidity-based estimates of total phosphorus, which is strongly related to turbidity because total phosphorus occurs predominantly in particulate form. Total nitrogen estimation models based on turbidity and streamflow generated estimates of similar quality, with the turbidity-based models providing slight improvements in the quality of estimations. This result is attributed to the understanding that nitrogen transport is dominated by dissolved forms that relate less directly to streamflow and turbidity. Improvements in concentration estimation resulted in improved estimates of load. Turbidity-based suspended-sediment loads estimated for the James River at Cartersville, VA, monitoring station exhibited tighter confidence interval bounds and a coefficient of variation of 12 percent, compared with a coefficient of variation of 38 percent for the streamflow-based load.

Characterizing the reproduction number of epidemics with early subexponential growth dynamics

PubMed Central

Viboud, Cécile; Simonsen, Lone; Moghadas, Seyed M.

2016-01-01

Early estimates of the transmission potential of emerging and re-emerging infections are increasingly used to inform public health authorities on the level of risk posed by outbreaks. Existing methods to estimate the reproduction number generally assume exponential growth in case incidence in the first few disease generations, before susceptible depletion sets in. In reality, outbreaks can display subexponential (i.e. polynomial) growth in the first few disease generations, owing to clustering in contact patterns, spatial effects, inhomogeneous mixing, reactive behaviour changes or other mechanisms. Here, we introduce the generalized growth model to characterize the early growth profile of outbreaks and estimate the effective reproduction number, with no need for explicit assumptions about the shape of epidemic growth. We demonstrate this phenomenological approach using analytical results and simulations from mechanistic models, and provide validation against a range of empirical disease datasets. Our results suggest that subexponential growth in the early phase of an epidemic is the rule rather the exception. Mechanistic simulations show that slight modifications to the classical susceptible–infectious–removed model result in subexponential growth, and in turn a rapid decline in the reproduction number within three to five disease generations. For empirical outbreaks, the generalized-growth model consistently outperforms the exponential model for a variety of directly and indirectly transmitted diseases datasets (pandemic influenza, measles, smallpox, bubonic plague, cholera, foot-and-mouth disease, HIV/AIDS and Ebola) with model estimates supporting subexponential growth dynamics. The rapid decline in effective reproduction number predicted by analytical results and observed in real and synthetic datasets within three to five disease generations contrasts with the expectation of invariant reproduction number in epidemics obeying exponential growth. The generalized-growth concept also provides us a compelling argument for the unexpected extinction of certain emerging disease outbreaks during the early ascending phase. Overall, our approach promotes a more reliable and data-driven characterization of the early epidemic phase, which is important for accurate estimation of the reproduction number and prediction of disease impact. PMID:27707909

Compensating for estimation smoothing in kriging

USGS Publications Warehouse

Olea, R.A.; Pawlowsky, Vera

1996-01-01

Smoothing is a characteristic inherent to all minimum mean-square-error spatial estimators such as kriging. Cross-validation can be used to detect and model such smoothing. Inversion of the model produces a new estimator-compensated kriging. A numerical comparison based on an exhaustive permeability sampling of a 4-fr2 slab of Berea Sandstone shows that the estimation surface generated by compensated kriging has properties intermediate between those generated by ordinary kriging and stochastic realizations resulting from simulated annealing and sequential Gaussian simulation. The frequency distribution is well reproduced by the compensated kriging surface, which also approximates the experimental semivariogram well - better than ordinary kriging, but not as well as stochastic realizations. Compensated kriging produces surfaces that are more accurate than stochastic realizations, but not as accurate as ordinary kriging. ?? 1996 International Association for Mathematical Geology.

Bayesian switching factor analysis for estimating time-varying functional connectivity in fMRI.

PubMed

Taghia, Jalil; Ryali, Srikanth; Chen, Tianwen; Supekar, Kaustubh; Cai, Weidong; Menon, Vinod

2017-07-15

There is growing interest in understanding the dynamical properties of functional interactions between distributed brain regions. However, robust estimation of temporal dynamics from functional magnetic resonance imaging (fMRI) data remains challenging due to limitations in extant multivariate methods for modeling time-varying functional interactions between multiple brain areas. Here, we develop a Bayesian generative model for fMRI time-series within the framework of hidden Markov models (HMMs). The model is a dynamic variant of the static factor analysis model (Ghahramani and Beal, 2000). We refer to this model as Bayesian switching factor analysis (BSFA) as it integrates factor analysis into a generative HMM in a unified Bayesian framework. In BSFA, brain dynamic functional networks are represented by latent states which are learnt from the data. Crucially, BSFA is a generative model which estimates the temporal evolution of brain states and transition probabilities between states as a function of time. An attractive feature of BSFA is the automatic determination of the number of latent states via Bayesian model selection arising from penalization of excessively complex models. Key features of BSFA are validated using extensive simulations on carefully designed synthetic data. We further validate BSFA using fingerprint analysis of multisession resting-state fMRI data from the Human Connectome Project (HCP). Our results show that modeling temporal dependencies in the generative model of BSFA results in improved fingerprinting of individual participants. Finally, we apply BSFA to elucidate the dynamic functional organization of the salience, central-executive, and default mode networks-three core neurocognitive systems with central role in cognitive and affective information processing (Menon, 2011). Across two HCP sessions, we demonstrate a high level of dynamic interactions between these networks and determine that the salience network has the highest temporal flexibility among the three networks. Our proposed methods provide a novel and powerful generative model for investigating dynamic brain connectivity. Copyright © 2017 Elsevier Inc. All rights reserved.

A statistical approach for generating synthetic tip stress data from limited CPT soundings

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

Basalams, M.K.

CPT tip stress data obtained from a Uranium mill tailings impoundment are treated as time series. A statistical class of models that was developed to model time series is explored to investigate its applicability in modeling the tip stress series. These models were developed by Box and Jenkins (1970) and are known as Autoregressive Moving Average (ARMA) models. This research demonstrates how to apply the ARMA models to tip stress series. Generation of synthetic tip stress series that preserve the main statistical characteristics of the measured series is also investigated. Multiple regression analysis is used to model the regional variationmore » of the ARMA model parameters as well as the regional variation of the mean and the standard deviation of the measured tip stress series. The reliability of the generated series is investigated from a geotechnical point of view as well as from a statistical point of view. Estimation of the total settlement using the measured and the generated series subjected to the same loading condition are performed. The variation of friction angle with depth of the impoundment materials is also investigated. This research shows that these series can be modeled by the Box and Jenkins ARMA models. A third degree Autoregressive model AR(3) is selected to represent these series. A theoretical double exponential density function is fitted to the AR(3) model residuals. Synthetic tip stress series are generated at nearby locations. The generated series are shown to be reliable in estimating the total settlement and the friction angle variation with depth for this particular site.« less

[The effects of a sex education program on knowledge related to sexually transmitted diseases and sexual autonomy among university students].

PubMed

Shin, YunHee; Chun, YoungKyung; Cho, SungMi; Cho, YeRyung

2005-12-01

The purpose of this study was to evaluate the effects of a sex education program, which was based on the Health Belief Model, on knowledge related to sexually transmitted diseases and sexual autonomy among university students. A non-equivalent control group, pretest-posttest design was used. The four session program was delivered to 18 students during 4 weeks; the control group consisted of 23 students. The theme of the first session was "sex, gender, and sexuality: all our concern", "dangerous sex" for the second session, "safe sex" for the third session, and "right sex for you and me" for the fourth session. At follow-up, the knowledge related to sexually transmitted diseases and sexual autonomy were significantly greater in the intervention group than in the control group. A sex education program with several sessions within the theoretical frame of HBM was effective to improve knowledge related to sexually transmitted diseases and sexual autonomy. The results suggest the potential of a systematic sexual education program to teach healthy sex and to extend the program for other various populations.

Efficacy of time-lapse photography and repeated counts abundance estimation for white-tailed deer populations

USGS Publications Warehouse

Keever, Allison; McGowan, Conor P.; Ditchkoff, Stephen S.; Acker, S.A.; Grand, James B.; Newbolt, Chad H.

2017-01-01

Automated cameras have become increasingly common for monitoring wildlife populations and estimating abundance. Most analytical methods, however, fail to account for incomplete and variable detection probabilities, which biases abundance estimates. Methods which do account for detection have not been thoroughly tested, and those that have been tested were compared to other methods of abundance estimation. The goal of this study was to evaluate the accuracy and effectiveness of the N-mixture method, which explicitly incorporates detection probability, to monitor white-tailed deer (Odocoileus virginianus) by using camera surveys and a known, marked population to collect data and estimate abundance. Motion-triggered camera surveys were conducted at Auburn University’s deer research facility in 2010. Abundance estimates were generated using N-mixture models and compared to the known number of marked deer in the population. We compared abundance estimates generated from a decreasing number of survey days used in analysis and by time periods (DAY, NIGHT, SUNRISE, SUNSET, CREPUSCULAR, ALL TIMES). Accurate abundance estimates were generated using 24 h of data and nighttime only data. Accuracy of abundance estimates increased with increasing number of survey days until day 5, and there was no improvement with additional data. This suggests that, for our system, 5-day camera surveys conducted at night were adequate for abundance estimation and population monitoring. Further, our study demonstrates that camera surveys and N-mixture models may be a highly effective method for estimation and monitoring of ungulate populations.

A unified internal model theory to resolve the paradox of active versus passive self-motion sensation

PubMed Central

Angelaki, Dora E

2017-01-01

Brainstem and cerebellar neurons implement an internal model to accurately estimate self-motion during externally generated (‘passive’) movements. However, these neurons show reduced responses during self-generated (‘active’) movements, indicating that predicted sensory consequences of motor commands cancel sensory signals. Remarkably, the computational processes underlying sensory prediction during active motion and their relationship to internal model computations during passive movements remain unknown. We construct a Kalman filter that incorporates motor commands into a previously established model of optimal passive self-motion estimation. The simulated sensory error and feedback signals match experimentally measured neuronal responses during active and passive head and trunk rotations and translations. We conclude that a single sensory internal model can combine motor commands with vestibular and proprioceptive signals optimally. Thus, although neurons carrying sensory prediction error or feedback signals show attenuated modulation, the sensory cues and internal model are both engaged and critically important for accurate self-motion estimation during active head movements. PMID:29043978

Regional PV power estimation and forecast to mitigate the impact of high photovoltaic penetration on electric grid.

NASA Astrophysics Data System (ADS)

Pierro, Marco; De Felice, Matteo; Maggioni, Enrico; Moser, David; Perotto, Alessandro; Spada, Francesco; Cornaro, Cristina

2017-04-01

The growing photovoltaic generation results in a stochastic variability of the electric demand that could compromise the stability of the grid and increase the amount of energy reserve and the energy imbalance cost. On regional scale, solar power estimation and forecast is becoming essential for Distribution System Operators, Transmission System Operator, energy traders, and aggregators of generation. Indeed the estimation of regional PV power can be used for PV power supervision and real time control of residual load. Mid-term PV power forecast can be employed for transmission scheduling to reduce energy imbalance and related cost of penalties, residual load tracking, trading optimization, secondary energy reserve assessment. In this context, a new upscaling method was developed and used for estimation and mid-term forecast of the photovoltaic distributed generation in a small area in the north of Italy under the control of a local DSO. The method was based on spatial clustering of the PV fleet and neural networks models that input satellite or numerical weather prediction data (centered on cluster centroids) to estimate or predict the regional solar generation. It requires a low computational effort and very few input information should be provided by users. The power estimation model achieved a RMSE of 3% of installed capacity. Intra-day forecast (from 1 to 4 hours) obtained a RMSE of 5% - 7% while the one and two days forecast achieve to a RMSE of 7% and 7.5%. A model to estimate the forecast error and the prediction intervals was also developed. The photovoltaic production in the considered region provided the 6.9% of the electric consumption in 2015. Since the PV penetration is very similar to the one observed at national level (7.9%), this is a good case study to analyse the impact of PV generation on the electric grid and the effects of PV power forecast on transmission scheduling and on secondary reserve estimation. It appears that, already with 7% of PV penetration, the distributed PV generation could have a great impact both on the DSO energy need and on the transmission scheduling capability. Indeed, for some hours of the days in summer time, the photovoltaic generation can provide from 50% to 75% of the energy that the local DSO should buy from Italian TSO to cover the electrical demand. Moreover, mid-term forecast can reduce the annual energy imbalance between the scheduled transmission and the actual one from 10% of the TSO energy supply (without considering the PV forecast) to 2%. Furthermore, it was shown that prediction intervals could be used not only to estimate the probability of a specific PV generation bid on the energy market, but also to reduce the energy reserve predicted for the next day. Two different methods for energy reserve estimation were developed and tested. The first is based on a clear sky model while the second makes use of the PV prediction intervals with the 95% of confidence level. The latter reduces the amount of the day-ahead energy reserve of 36% with respect the clear sky method.

A comparison of observation-level random effect and Beta-Binomial models for modelling overdispersion in Binomial data in ecology & evolution.

PubMed

Harrison, Xavier A

2015-01-01

Overdispersion is a common feature of models of biological data, but researchers often fail to model the excess variation driving the overdispersion, resulting in biased parameter estimates and standard errors. Quantifying and modeling overdispersion when it is present is therefore critical for robust biological inference. One means to account for overdispersion is to add an observation-level random effect (OLRE) to a model, where each data point receives a unique level of a random effect that can absorb the extra-parametric variation in the data. Although some studies have investigated the utility of OLRE to model overdispersion in Poisson count data, studies doing so for Binomial proportion data are scarce. Here I use a simulation approach to investigate the ability of both OLRE models and Beta-Binomial models to recover unbiased parameter estimates in mixed effects models of Binomial data under various degrees of overdispersion. In addition, as ecologists often fit random intercept terms to models when the random effect sample size is low (<5 levels), I investigate the performance of both model types under a range of random effect sample sizes when overdispersion is present. Simulation results revealed that the efficacy of OLRE depends on the process that generated the overdispersion; OLRE failed to cope with overdispersion generated from a Beta-Binomial mixture model, leading to biased slope and intercept estimates, but performed well for overdispersion generated by adding random noise to the linear predictor. Comparison of parameter estimates from an OLRE model with those from its corresponding Beta-Binomial model readily identified when OLRE were performing poorly due to disagreement between effect sizes, and this strategy should be employed whenever OLRE are used for Binomial data to assess their reliability. Beta-Binomial models performed well across all contexts, but showed a tendency to underestimate effect sizes when modelling non-Beta-Binomial data. Finally, both OLRE and Beta-Binomial models performed poorly when models contained <5 levels of the random intercept term, especially for estimating variance components, and this effect appeared independent of total sample size. These results suggest that OLRE are a useful tool for modelling overdispersion in Binomial data, but that they do not perform well in all circumstances and researchers should take care to verify the robustness of parameter estimates of OLRE models.

ESTIMATING CHILDREN'S DERMAL AND NON-DIETARY INGESTION EXPOSURE AND DOSE WITH EPA'S SHEDS MODEL

EPA Science Inventory

A physically-based stochastic model (SHEDS) has been developed to estimate pesticide exposure and dose to children via dermal residue contact and non-dietary ingestion. Time-location-activity data are sampled from national survey results to generate a population of simulated ch...

Spatial interpolation schemes of daily precipitation for hydrologic modeling

USGS Publications Warehouse

Hwang, Y.; Clark, M.R.; Rajagopalan, B.; Leavesley, G.

2012-01-01

Distributed hydrologic models typically require spatial estimates of precipitation interpolated from sparsely located observational points to the specific grid points. We compare and contrast the performance of regression-based statistical methods for the spatial estimation of precipitation in two hydrologically different basins and confirmed that widely used regression-based estimation schemes fail to describe the realistic spatial variability of daily precipitation field. The methods assessed are: (1) inverse distance weighted average; (2) multiple linear regression (MLR); (3) climatological MLR; and (4) locally weighted polynomial regression (LWP). In order to improve the performance of the interpolations, the authors propose a two-step regression technique for effective daily precipitation estimation. In this simple two-step estimation process, precipitation occurrence is first generated via a logistic regression model before estimate the amount of precipitation separately on wet days. This process generated the precipitation occurrence, amount, and spatial correlation effectively. A distributed hydrologic model (PRMS) was used for the impact analysis in daily time step simulation. Multiple simulations suggested noticeable differences between the input alternatives generated by three different interpolation schemes. Differences are shown in overall simulation error against the observations, degree of explained variability, and seasonal volumes. Simulated streamflows also showed different characteristics in mean, maximum, minimum, and peak flows. Given the same parameter optimization technique, LWP input showed least streamflow error in Alapaha basin and CMLR input showed least error (still very close to LWP) in Animas basin. All of the two-step interpolation inputs resulted in lower streamflow error compared to the directly interpolated inputs. ?? 2011 Springer-Verlag.

Passive acoustic measurement of bedload grain size distribution using self-generated noise

NASA Astrophysics Data System (ADS)

Petrut, Teodor; Geay, Thomas; Gervaise, Cédric; Belleudy, Philippe; Zanker, Sebastien

2018-01-01

Monitoring sediment transport processes in rivers is of particular interest to engineers and scientists to assess the stability of rivers and hydraulic structures. Various methods for sediment transport process description were proposed using conventional or surrogate measurement techniques. This paper addresses the topic of the passive acoustic monitoring of bedload transport in rivers and especially the estimation of the bedload grain size distribution from self-generated noise. It discusses the feasibility of linking the acoustic signal spectrum shape to bedload grain sizes involved in elastic impacts with the river bed treated as a massive slab. Bedload grain size distribution is estimated by a regularized algebraic inversion scheme fed with the power spectrum density of river noise estimated from one hydrophone. The inversion methodology relies upon a physical model that predicts the acoustic field generated by the collision between rigid bodies. Here we proposed an analytic model of the acoustic energy spectrum generated by the impacts between a sphere and a slab. The proposed model computes the power spectral density of bedload noise using a linear system of analytic energy spectra weighted by the grain size distribution. The algebraic system of equations is then solved by least square optimization and solution regularization methods. The result of inversion leads directly to the estimation of the bedload grain size distribution. The inversion method was applied to real acoustic data from passive acoustics experiments realized on the Isère River, in France. The inversion of in situ measured spectra reveals good estimations of grain size distribution, fairly close to what was estimated by physical sampling instruments. These results illustrate the potential of the hydrophone technique to be used as a standalone method that could ensure high spatial and temporal resolution measurements for sediment transport in rivers.

Implementation and validation of the extended Hill-type muscle model with robust routing capabilities in LS-DYNA for active human body models.

PubMed

Kleinbach, Christian; Martynenko, Oleksandr; Promies, Janik; Haeufle, Daniel F B; Fehr, Jörg; Schmitt, Syn

2017-09-02

In the state of the art finite element AHBMs for car crash analysis in the LS-DYNA software material named *MAT_MUSCLE (*MAT_156) is used for active muscles modeling. It has three elements in parallel configuration, which has several major drawbacks: restraint approximation of the physical reality, complicated parameterization and absence of the integrated activation dynamics. This study presents implementation of the extended four element Hill-type muscle model with serial damping and eccentric force-velocity relation including [Formula: see text] dependent activation dynamics and internal method for physiological muscle routing. Proposed model was implemented into the general-purpose finite element (FE) simulation software LSDYNA as a user material for truss elements. This material model is verified and validated with three different sets of mammalian experimental data, taken from the literature. It is compared to the *MAT_MUSCLE (*MAT_156) Hill-type muscle model already existing in LS-DYNA, which is currently used in finite element human body models (HBMs). An application example with an arm model extracted from the FE ViVA OpenHBM is given, taking into account physiological muscle paths. The simulation results show better material model accuracy, calculation robustness and improved muscle routing capability compared to *MAT_156. The FORTRAN source code for the user material subroutine dyn21.f and the muscle parameters for all simulations, conducted in the study, are given at https://zenodo.org/record/826209 under an open source license. This enables a quick application of the proposed material model in LS-DYNA, especially in active human body models (AHBMs) for applications in automotive safety.

A preliminary estimate of future communications traffic for the electric power system

NASA Technical Reports Server (NTRS)

Barnett, R. M.

1981-01-01

Diverse new generator technologies using renewable energy, and to improve operational efficiency throughout the existing electric power systems are presented. A description of a model utility and the information transfer requirements imposed by incorporation of dispersed storage and generation technologies and implementation of more extensive energy management are estimated. An example of possible traffic for an assumed system, and an approach that can be applied to other systems, control configurations, or dispersed storage and generation penetrations is provided.

Estimating rooftop solar technical potential across the US using a combination of GIS-based methods, lidar data, and statistical modeling

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

Gagnon, Pieter; Margolis, Robert; Melius, Jennifer

We provide a detailed estimate of the technical potential of rooftop solar photovoltaic (PV) electricity generation throughout the contiguous United States. This national estimate is based on an analysis of select US cities that combines light detection and ranging (lidar) data with a validated analytical method for determining rooftop PV suitability employing geographic information systems. We use statistical models to extend this analysis to estimate the quantity and characteristics of roofs in areas not covered by lidar data. Finally, we model PV generation for all rooftops to yield technical potential estimates. At the national level, 8.13 billion m 2 ofmore » suitable roof area could host 1118 GW of PV capacity, generating 1432 TWh of electricity per year. This would equate to 38.6% of the electricity that was sold in the contiguous United States in 2013. This estimate is substantially higher than a previous estimate made by the National Renewable Energy Laboratory. The difference can be attributed to increases in PV module power density, improved estimation of building suitability, higher estimates of total number of buildings, and improvements in PV performance simulation tools that previously tended to underestimate productivity. Also notable, the nationwide percentage of buildings suitable for at least some PV deployment is high—82% for buildings smaller than 5000 ft 2 and over 99% for buildings larger than that. In most states, rooftop PV could enable small, mostly residential buildings to offset the majority of average household electricity consumption. Even in some states with a relatively poor solar resource, such as those in the Northeast, the residential sector has the potential to offset around 100% of its total electricity consumption with rooftop PV.« less

Estimating rooftop solar technical potential across the US using a combination of GIS-based methods, lidar data, and statistical modeling

DOE PAGES

Gagnon, Pieter; Margolis, Robert; Melius, Jennifer; ...

2018-01-05

We provide a detailed estimate of the technical potential of rooftop solar photovoltaic (PV) electricity generation throughout the contiguous United States. This national estimate is based on an analysis of select US cities that combines light detection and ranging (lidar) data with a validated analytical method for determining rooftop PV suitability employing geographic information systems. We use statistical models to extend this analysis to estimate the quantity and characteristics of roofs in areas not covered by lidar data. Finally, we model PV generation for all rooftops to yield technical potential estimates. At the national level, 8.13 billion m 2 ofmore » suitable roof area could host 1118 GW of PV capacity, generating 1432 TWh of electricity per year. This would equate to 38.6% of the electricity that was sold in the contiguous United States in 2013. This estimate is substantially higher than a previous estimate made by the National Renewable Energy Laboratory. The difference can be attributed to increases in PV module power density, improved estimation of building suitability, higher estimates of total number of buildings, and improvements in PV performance simulation tools that previously tended to underestimate productivity. Also notable, the nationwide percentage of buildings suitable for at least some PV deployment is high—82% for buildings smaller than 5000 ft 2 and over 99% for buildings larger than that. In most states, rooftop PV could enable small, mostly residential buildings to offset the majority of average household electricity consumption. Even in some states with a relatively poor solar resource, such as those in the Northeast, the residential sector has the potential to offset around 100% of its total electricity consumption with rooftop PV.« less

Estimating rooftop solar technical potential across the US using a combination of GIS-based methods, lidar data, and statistical modeling

NASA Astrophysics Data System (ADS)

Gagnon, Pieter; Margolis, Robert; Melius, Jennifer; Phillips, Caleb; Elmore, Ryan

2018-02-01

We provide a detailed estimate of the technical potential of rooftop solar photovoltaic (PV) electricity generation throughout the contiguous United States. This national estimate is based on an analysis of select US cities that combines light detection and ranging (lidar) data with a validated analytical method for determining rooftop PV suitability employing geographic information systems. We use statistical models to extend this analysis to estimate the quantity and characteristics of roofs in areas not covered by lidar data. Finally, we model PV generation for all rooftops to yield technical potential estimates. At the national level, 8.13 billion m2 of suitable roof area could host 1118 GW of PV capacity, generating 1432 TWh of electricity per year. This would equate to 38.6% of the electricity that was sold in the contiguous United States in 2013. This estimate is substantially higher than a previous estimate made by the National Renewable Energy Laboratory. The difference can be attributed to increases in PV module power density, improved estimation of building suitability, higher estimates of total number of buildings, and improvements in PV performance simulation tools that previously tended to underestimate productivity. Also notable, the nationwide percentage of buildings suitable for at least some PV deployment is high—82% for buildings smaller than 5000 ft2 and over 99% for buildings larger than that. In most states, rooftop PV could enable small, mostly residential buildings to offset the majority of average household electricity consumption. Even in some states with a relatively poor solar resource, such as those in the Northeast, the residential sector has the potential to offset around 100% of its total electricity consumption with rooftop PV.

Estimation of methane emission rate changes using age-defined waste in a landfill site.

PubMed

Ishii, Kazuei; Furuichi, Toru

2013-09-01

Long term methane emissions from landfill sites are often predicted by first-order decay (FOD) models, in which the default coefficients of the methane generation potential and the methane generation rate given by the Intergovernmental Panel on Climate Change (IPCC) are usually used. However, previous studies have demonstrated the large uncertainty in these coefficients because they are derived from a calibration procedure under ideal steady-state conditions, not actual landfill site conditions. In this study, the coefficients in the FOD model were estimated by a new approach to predict more precise long term methane generation by considering region-specific conditions. In the new approach, age-defined waste samples, which had been under the actual landfill site conditions, were collected in Hokkaido, Japan (in cold region), and the time series data on the age-defined waste sample's methane generation potential was used to estimate the coefficients in the FOD model. The degradation coefficients were 0.0501/y and 0.0621/y for paper and food waste, and the methane generation potentials were 214.4 mL/g-wet waste and 126.7 mL/g-wet waste for paper and food waste, respectively. These coefficients were compared with the default coefficients given by the IPCC. Although the degradation coefficient for food waste was smaller than the default value, the other coefficients were within the range of the default coefficients. With these new coefficients to calculate methane generation, the long term methane emissions from the landfill site was estimated at 1.35×10(4)m(3)-CH(4), which corresponds to approximately 2.53% of the total carbon dioxide emissions in the city (5.34×10(5)t-CO(2)/y). Copyright © 2013 Elsevier Ltd. All rights reserved.

Implementing Generalized Additive Models to Estimate the Expected Value of Sample Information in a Microsimulation Model: Results of Three Case Studies.

PubMed

Rabideau, Dustin J; Pei, Pamela P; Walensky, Rochelle P; Zheng, Amy; Parker, Robert A

2018-02-01

The expected value of sample information (EVSI) can help prioritize research but its application is hampered by computational infeasibility, especially for complex models. We investigated an approach by Strong and colleagues to estimate EVSI by applying generalized additive models (GAM) to results generated from a probabilistic sensitivity analysis (PSA). For 3 potential HIV prevention and treatment strategies, we estimated life expectancy and lifetime costs using the Cost-effectiveness of Preventing AIDS Complications (CEPAC) model, a complex patient-level microsimulation model of HIV progression. We fitted a GAM-a flexible regression model that estimates the functional form as part of the model fitting process-to the incremental net monetary benefits obtained from the CEPAC PSA. For each case study, we calculated the expected value of partial perfect information (EVPPI) using both the conventional nested Monte Carlo approach and the GAM approach. EVSI was calculated using the GAM approach. For all 3 case studies, the GAM approach consistently gave similar estimates of EVPPI compared with the conventional approach. The EVSI behaved as expected: it increased and converged to EVPPI for larger sample sizes. For each case study, generating the PSA results for the GAM approach required 3 to 4 days on a shared cluster, after which EVPPI and EVSI across a range of sample sizes were evaluated in minutes. The conventional approach required approximately 5 weeks for the EVPPI calculation alone. Estimating EVSI using the GAM approach with results from a PSA dramatically reduced the time required to conduct a computationally intense project, which would otherwise have been impractical. Using the GAM approach, we can efficiently provide policy makers with EVSI estimates, even for complex patient-level microsimulation models.

Transfer Function Identification Using Orthogonal Fourier Transform Modeling Functions

NASA Technical Reports Server (NTRS)

Morelli, Eugene A.

2013-01-01

A method for transfer function identification, including both model structure determination and parameter estimation, was developed and demonstrated. The approach uses orthogonal modeling functions generated from frequency domain data obtained by Fourier transformation of time series data. The method was applied to simulation data to identify continuous-time transfer function models and unsteady aerodynamic models. Model fit error, estimated model parameters, and the associated uncertainties were used to show the effectiveness of the method for identifying accurate transfer function models from noisy data.

Equilibrium sensitivities of the Greenland ice sheet inferred from the adjoint of the three- dimensional thermo-mechanical model SICOPOLIS

NASA Astrophysics Data System (ADS)

Heimbach, P.; Bugnion, V.

2008-12-01

We present a new and original approach to understanding the sensitivity of the Greenland ice sheet to key model parameters and environmental conditions. At the heart of this approach is the use of an adjoint ice sheet model. MacAyeal (1992) introduced adjoints in the context of applying control theory to estimate basal sliding parameters (basal shear stress, basal friction) of an ice stream model which minimize a least-squares model vs. observation misfit. Since then, this method has become widespread to fit ice stream models to the increasing number and diversity of satellite observations, and to estimate uncertain model parameters. However, no attempt has been made to extend this method to comprehensive ice sheet models. Here, we present a first step toward moving beyond limiting the use of control theory to ice stream models. We have generated an adjoint of the three-dimensional thermo-mechanical ice sheet model SICOPOLIS of Greve (1997). The adjoint was generated using the automatic differentiation (AD) tool TAF. TAF generates exact source code representing the tangent linear and adjoint model of the parent model provided. Model sensitivities are given by the partial derivatives of a scalar-valued model diagnostic or "cost function" with respect to the controls, and can be efficiently calculated via the adjoint. An effort to generate an efficient adjoint with the newly developed open-source AD tool OpenAD is also under way. To gain insight into the adjoint solutions, we explore various cost functions, such as local and domain-integrated ice temperature, total ice volume or the velocity of ice at the margins of the ice sheet. Elements of our control space include initial cold ice temperatures, surface mass balance, as well as parameters such as appear in Glen's flow law, or in the surface degree-day or basal sliding parameterizations. Sensitivity maps provide a comprehensive view, and allow a quantification of where and to which variables the ice sheet model is most sensitive to. The model used in the present study includes simplifications in the model physics, parameterizations which rely on uncertain empirical constants, and is unable to capture fast ice streams. Nevertheless, as a proof-of-concept, this method can readily be extended to incorporate higher-order physics or parameterizations (or be applied to other models). It also opens the door to ice sheet state estimation: using the model's physics jointly with field and satellite observations to estimate a best estimate of the state of the ice sheets.

Intergenerational Long-Term Effects of Preschool - Structural Estimates from a Discrete Dynamic Programming Model*

PubMed Central

Heckman, James J.; Raut, Lakshmi K.

2015-01-01

This paper formulates a structural dynamic programming model of preschool investment choices of altruistic parents and then empirically estimates the structural parameters of the model using the NLSY79 data. The paper finds that preschool investment significantly boosts cognitive and non-cognitive skills, which enhance earnings and school outcomes. It also finds that a standard Mincer earnings function, by omitting measures of non-cognitive skills on the right-hand side, overestimates the rate of return to schooling. From the estimated equilibrium Markov process, the paper studies the nature of within generation earnings distribution, intergenerational earnings mobility, and schooling mobility. The paper finds that a tax-financed free preschool program for the children of poor socioeconomic status generates positive net gains to the society in terms of average earnings, higher intergenerational earnings mobility, and schooling mobility. PMID:26709326

Repositioning the knee joint in human body FE models using a graphics-based technique.

PubMed

Jani, Dhaval; Chawla, Anoop; Mukherjee, Sudipto; Goyal, Rahul; Vusirikala, Nataraju; Jayaraman, Suresh

2012-01-01

Human body finite element models (FE-HBMs) are available in standard occupant or pedestrian postures. There is a need to have FE-HBMs in the same posture as a crash victim or to be configured in varying postures. Developing FE models for all possible positions is not practically viable. The current work aims at obtaining a posture-specific human lower extremity model by reconfiguring an existing one. A graphics-based technique was developed to reposition the lower extremity of an FE-HBM by specifying the flexion-extension angle. Elements of the model were segregated into rigid (bones) and deformable components (soft tissues). The bones were rotated about the flexion-extension axis followed by rotation about the longitudinal axis to capture the twisting of the tibia. The desired knee joint movement was thus achieved. Geometric heuristics were then used to reposition the skin. A mapping defined over the space between bones and the skin was used to regenerate the soft tissues. Mesh smoothing was then done to augment mesh quality. The developed method permits control over the kinematics of the joint and maintains the initial mesh quality of the model. For some critical areas (in the joint vicinity) where element distortion is large, mesh smoothing is done to improve mesh quality. A method to reposition the knee joint of a human body FE model was developed. Repositions of a model from 9 degrees of flexion to 90 degrees of flexion in just a few seconds without subjective interventions was demonstrated. Because the mesh quality of the repositioned model was maintained to a predefined level (typically to the level of a well-made model in the initial configuration), the model was suitable for subsequent simulations.

Transportation Sector Module - NEMS Documentation

EIA Publications

2017-01-01

Documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Transportation Model (TRAN). The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated by the model.

Estimating Alarm Thresholds for Process Monitoring Data under Different Assumptions about the Data Generating Mechanism

DOE PAGES

Burr, Tom; Hamada, Michael S.; Howell, John; ...

2013-01-01

Process monitoring (PM) for nuclear safeguards sometimes requires estimation of thresholds corresponding to small false alarm rates. Threshold estimation dates to the 1920s with the Shewhart control chart; however, because possible new roles for PM are being evaluated in nuclear safeguards, it is timely to consider modern model selection options in the context of threshold estimation. One of the possible new PM roles involves PM residuals, where a residual is defined as residual = data − prediction. This paper reviews alarm threshold estimation, introduces model selection options, and considers a range of assumptions regarding the data-generating mechanism for PM residuals.more » Two PM examples from nuclear safeguards are included to motivate the need for alarm threshold estimation. The first example involves mixtures of probability distributions that arise in solution monitoring, which is a common type of PM. The second example involves periodic partial cleanout of in-process inventory, leading to challenging structure in the time series of PM residuals.« less

Model verification of large structural systems. [space shuttle model response

NASA Technical Reports Server (NTRS)

Lee, L. T.; Hasselman, T. K.

1978-01-01

A computer program for the application of parameter identification on the structural dynamic models of space shuttle and other large models with hundreds of degrees of freedom is described. Finite element, dynamic, analytic, and modal models are used to represent the structural system. The interface with math models is such that output from any structural analysis program applied to any structural configuration can be used directly. Processed data from either sine-sweep tests or resonant dwell tests are directly usable. The program uses measured modal data to condition the prior analystic model so as to improve the frequency match between model and test. A Bayesian estimator generates an improved analytical model and a linear estimator is used in an iterative fashion on highly nonlinear equations. Mass and stiffness scaling parameters are generated for an improved finite element model, and the optimum set of parameters is obtained in one step.

A combined surface/volume scattering retracking algorithm for ice sheet satellite altimetry

NASA Technical Reports Server (NTRS)

Davis, Curt H.

1992-01-01

An algorithm that is based upon a combined surface-volume scattering model is developed. It can be used to retrack individual altimeter waveforms over ice sheets. An iterative least-squares procedure is used to fit the combined model to the return waveforms. The retracking algorithm comprises two distinct sections. The first generates initial model parameter estimates from a filtered altimeter waveform. The second uses the initial estimates, the theoretical model, and the waveform data to generate corrected parameter estimates. This retracking algorithm can be used to assess the accuracy of elevations produced from current retracking algorithms when subsurface volume scattering is present. This is extremely important so that repeated altimeter elevation measurements can be used to accurately detect changes in the mass balance of the ice sheets. By analyzing the distribution of the model parameters over large portions of the ice sheet, regional and seasonal variations in the near-surface properties of the snowpack can be quantified.

A Nuclear Interaction Model for Understanding Results of Single Event Testing with High Energy Protons

NASA Technical Reports Server (NTRS)

Culpepper, William X.; ONeill, Pat; Nicholson, Leonard L.

2000-01-01

An internuclear cascade and evaporation model has been adapted to estimate the LET spectrum generated during testing with 200 MeV protons. The model-generated heavy ion LET spectrum is compared to the heavy ion LET spectrum seen on orbit. This comparison is the basis for predicting single event failure rates from heavy ions using results from a single proton test. Of equal importance, this spectra comparison also establishes an estimate of the risk of encountering a failure mode on orbit that was not detected during proton testing. Verification of the general results of the model is presented based on experiments, individual part test results, and flight data. Acceptance of this model and its estimate of remaining risk opens the hardware verification philosophy to the consideration of radiation testing with high energy protons at the board and box level instead of the more standard method of individual part testing with low energy heavy ions.

Lift estimation of Half-Rotating Wing in hovering flight

NASA Astrophysics Data System (ADS)

Wang, X. Y.; Dong, Y. P.; Qiu, Z. Z.; Zhang, Y. Q.; Shan, J. H.

2016-11-01

Half-Rotating Wing (HRW) is a new kind of flapping wing system with rotating flapping instead of oscillating flapping. Estimating approach of hovering lift which generated in hovering flight was important theoretical foundation to design aircraft using HRW. The working principle of HRW based on Half-Rotating Mechanism (HRM) was firstly introduced in this paper. Generating process of lift by HRW was also given. The calculating models of two lift mechanisms for HRW, including Lift of Flow Around Wing (LFAW) and Lift of Flow Dragging Wing (LFDW), were respectively established. The lift estimating model of HRW was further deduced, by which hovering lift for HRW with different angular velocity could be calculated. Case study using XFLOW software simulation indicates that the above estimating method was effective and feasible to predict roughly the hovering lift for a new HRW system.

An artificial EMG generation model based on signal-dependent noise and related application to motion classification

PubMed Central

Hayashi, Hideaki; Nakamura, Go; Chin, Takaaki; Tsuji, Toshio

2017-01-01

This paper proposes an artificial electromyogram (EMG) signal generation model based on signal-dependent noise, which has been ignored in existing methods, by introducing the stochastic construction of the EMG signals. In the proposed model, an EMG signal variance value is first generated from a probability distribution with a shape determined by a commanded muscle force and signal-dependent noise. Artificial EMG signals are then generated from the associated Gaussian distribution with a zero mean and the generated variance. This facilitates representation of artificial EMG signals with signal-dependent noise superimposed according to the muscle activation levels. The frequency characteristics of the EMG signals are also simulated via a shaping filter with parameters determined by an autoregressive model. An estimation method to determine EMG variance distribution using rectified and smoothed EMG signals, thereby allowing model parameter estimation with a small number of samples, is also incorporated in the proposed model. Moreover, the prediction of variance distribution with strong muscle contraction from EMG signals with low muscle contraction and related artificial EMG generation are also described. The results of experiments conducted, in which the reproduction capability of the proposed model was evaluated through comparison with measured EMG signals in terms of amplitude, frequency content, and EMG distribution demonstrate that the proposed model can reproduce the features of measured EMG signals. Further, utilizing the generated EMG signals as training data for a neural network resulted in the classification of upper limb motion with a higher precision than by learning from only measured EMG signals. This indicates that the proposed model is also applicable to motion classification. PMID:28640883

A Review of Operational Water Consumption and Withdrawal Factors for Electricity Generating Technologies

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

Macknick, Jordan; Newmark, Robin; Heath, Garvin

2011-03-01

This report provides estimates of operational water withdrawal and water consumption factors for electricity generating technologies in the United States. Estimates of water factors were collected from published primary literature and were not modified except for unit conversions. The presented water factors may be useful in modeling and policy analyses where reliable power plant level data are not available.

External validation of a forest inventory and analysis volume equation and comparisons with estimates from multiple stem-profile models

Treesearch

Christopher M. Oswalt; Adam M. Saunders

2009-01-01

Sound estimation procedures are desideratum for generating credible population estimates to evaluate the status and trends in resource conditions. As such, volume estimation is an integral component of the U.S. Department of Agriculture, Forest Service, Forest Inventory and Analysis (FIA) program's reporting. In effect, reliable volume estimation procedures are...

Technical Note: Approximate Bayesian parameterization of a complex tropical forest model

NASA Astrophysics Data System (ADS)

Hartig, F.; Dislich, C.; Wiegand, T.; Huth, A.

2013-08-01

Inverse parameter estimation of process-based models is a long-standing problem in ecology and evolution. A key problem of inverse parameter estimation is to define a metric that quantifies how well model predictions fit to the data. Such a metric can be expressed by general cost or objective functions, but statistical inversion approaches are based on a particular metric, the probability of observing the data given the model, known as the likelihood. Deriving likelihoods for dynamic models requires making assumptions about the probability for observations to deviate from mean model predictions. For technical reasons, these assumptions are usually derived without explicit consideration of the processes in the simulation. Only in recent years have new methods become available that allow generating likelihoods directly from stochastic simulations. Previous applications of these approximate Bayesian methods have concentrated on relatively simple models. Here, we report on the application of a simulation-based likelihood approximation for FORMIND, a parameter-rich individual-based model of tropical forest dynamics. We show that approximate Bayesian inference, based on a parametric likelihood approximation placed in a conventional MCMC, performs well in retrieving known parameter values from virtual field data generated by the forest model. We analyze the results of the parameter estimation, examine the sensitivity towards the choice and aggregation of model outputs and observed data (summary statistics), and show results from using this method to fit the FORMIND model to field data from an Ecuadorian tropical forest. Finally, we discuss differences of this approach to Approximate Bayesian Computing (ABC), another commonly used method to generate simulation-based likelihood approximations. Our results demonstrate that simulation-based inference, which offers considerable conceptual advantages over more traditional methods for inverse parameter estimation, can successfully be applied to process-based models of high complexity. The methodology is particularly suited to heterogeneous and complex data structures and can easily be adjusted to other model types, including most stochastic population and individual-based models. Our study therefore provides a blueprint for a fairly general approach to parameter estimation of stochastic process-based models in ecology and evolution.

Study on Commercialization of Biogasification Systems in Ishikari Bay New Port Area - Proposal of Estimation Method of Collectable Amount of Food Waste by using Binary Logit Model -

NASA Astrophysics Data System (ADS)

Watanabe, Sho; Furuichi, Toru; Ishii, Kazuei

This study proposed an estimation method for collectable amount of food waste considering the food waste generator's cooperation ratio ant the amount of food waste generation, and clarified the factors influencing the collectable amount of food waste. In our method, the cooperation ratio was calculated by using the binary logit model which is often used for the traffic multiple choice question. In order to develop a more precise binary logit model, the factors influencing on the cooperation ratio were extracted by a questionnaire survey asking food waste generator's intention, and the preference investigation was then conducted at the second step. As a result, the collectable amount of food waste was estimated to be 72 [t/day] in the Ishikari bay new port area under a condition of current collection system by using our method. In addition, the most critical factor influencing on the collectable amount of food waste was the treatment fee for households, and was the permitted mixture degree of improper materials for retail trade and restaurant businesses

The Role of Safety Culture in Influencing Provider Perceptions of Patient Safety.

PubMed

Bishop, Andrea C; Boyle, Todd A

2016-12-01

To determine how provider perceptions of safety culture influence their involvement in patient safety practices. Health-care providers were surveyed in 2 tertiary hospitals located in Atlantic Canada, composed of 4 units in total. The partial least squares (PLS) approach to structural equation modeling was used to analyze the data. Latent variables provider PLS model encompassed the hypothesized relationships between provider characteristics, safety culture, perceptions of patient safety practices, and actual performance of patient safety practices, using the Health Belief Model (HBM) as a guide. Data analysis was conducted using SmartPLS. A total of 113 health-care providers completed a survey out of an eligible 318, representing a response rate of 35.5%. The final PLS model showed acceptable internal consistency with all four latent variables having a composite reliability score above the recommended 0.70 cutoff value (safety culture = 0.86, threat = 0.76, expectations = 0.83, PS practices = 0.75). Discriminant validity was established, and all path coefficients were found to be significant at the α = 0.05 level using nonparametric bootstrapping. The survey results show that safety culture accounted for 34% of the variance in perceptions of threat and 42% of the variance in expectations. This research supports the role that safety culture plays in the promotion and maintenance of patient safety activities for health-care providers. As such, it is recommended that the introduction of new patient safety strategies follow a thorough exploration of an organization's safety culture.

Real time estimation of generation, extinction and flow of muscle fibre action potentials in high density surface EMG.

PubMed

Mesin, Luca

2015-02-01

Developing a real time method to estimate generation, extinction and propagation of muscle fibre action potentials from bi-dimensional and high density surface electromyogram (EMG). A multi-frame generalization of an optical flow technique including a source term is considered. A model describing generation, extinction and propagation of action potentials is fit to epochs of surface EMG. The algorithm is tested on simulations of high density surface EMG (inter-electrode distance equal to 5mm) from finite length fibres generated using a multi-layer volume conductor model. The flow and source term estimated from interference EMG reflect the anatomy of the muscle, i.e. the direction of the fibres (2° of average estimation error) and the positions of innervation zone and tendons under the electrode grid (mean errors of about 1 and 2mm, respectively). The global conduction velocity of the action potentials from motor units under the detection system is also obtained from the estimated flow. The processing time is about 1 ms per channel for an epoch of EMG of duration 150 ms. A new real time image processing algorithm is proposed to investigate muscle anatomy and activity. Potential applications are proposed in prosthesis control, automatic detection of optimal channels for EMG index extraction and biofeedback. Copyright © 2014 Elsevier Ltd. All rights reserved.

Logs Analysis of Adapted Pedagogical Scenarios Generated by a Simulation Serious Game Architecture

ERIC Educational Resources Information Center

Callies, Sophie; Gravel, Mathieu; Beaudry, Eric; Basque, Josianne

2017-01-01

This paper presents an architecture designed for simulation serious games, which automatically generates game-based scenarios adapted to learner's learning progression. We present three central modules of the architecture: (1) the learner model, (2) the adaptation module and (3) the logs module. The learner model estimates the progression of the…

A Generative Probabilistic Model and Discriminative Extensions for Brain Lesion Segmentation--With Application to Tumor and Stroke.

PubMed

Menze, Bjoern H; Van Leemput, Koen; Lashkari, Danial; Riklin-Raviv, Tammy; Geremia, Ezequiel; Alberts, Esther; Gruber, Philipp; Wegener, Susanne; Weber, Marc-Andre; Szekely, Gabor; Ayache, Nicholas; Golland, Polina

2016-04-01

We introduce a generative probabilistic model for segmentation of brain lesions in multi-dimensional images that generalizes the EM segmenter, a common approach for modelling brain images using Gaussian mixtures and a probabilistic tissue atlas that employs expectation-maximization (EM), to estimate the label map for a new image. Our model augments the probabilistic atlas of the healthy tissues with a latent atlas of the lesion. We derive an estimation algorithm with closed-form EM update equations. The method extracts a latent atlas prior distribution and the lesion posterior distributions jointly from the image data. It delineates lesion areas individually in each channel, allowing for differences in lesion appearance across modalities, an important feature of many brain tumor imaging sequences. We also propose discriminative model extensions to map the output of the generative model to arbitrary labels with semantic and biological meaning, such as "tumor core" or "fluid-filled structure", but without a one-to-one correspondence to the hypo- or hyper-intense lesion areas identified by the generative model. We test the approach in two image sets: the publicly available BRATS set of glioma patient scans, and multimodal brain images of patients with acute and subacute ischemic stroke. We find the generative model that has been designed for tumor lesions to generalize well to stroke images, and the extended discriminative -discriminative model to be one of the top ranking methods in the BRATS evaluation.

System-of-Systems Technology-Portfolio-Analysis Tool

NASA Technical Reports Server (NTRS)

O'Neil, Daniel; Mankins, John; Feingold, Harvey; Johnson, Wayne

2012-01-01

Advanced Technology Life-cycle Analysis System (ATLAS) is a system-of-systems technology-portfolio-analysis software tool. ATLAS affords capabilities to (1) compare estimates of the mass and cost of an engineering system based on competing technological concepts; (2) estimate life-cycle costs of an outer-space-exploration architecture for a specified technology portfolio; (3) collect data on state-of-the-art and forecasted technology performance, and on operations and programs; and (4) calculate an index of the relative programmatic value of a technology portfolio. ATLAS facilitates analysis by providing a library of analytical spreadsheet models for a variety of systems. A single analyst can assemble a representation of a system of systems from the models and build a technology portfolio. Each system model estimates mass, and life-cycle costs are estimated by a common set of cost models. Other components of ATLAS include graphical-user-interface (GUI) software, algorithms for calculating the aforementioned index, a technology database, a report generator, and a form generator for creating the GUI for the system models. At the time of this reporting, ATLAS is a prototype, embodied in Microsoft Excel and several thousand lines of Visual Basic for Applications that run on both Windows and Macintosh computers.

Bayesian Parameter Estimation for Heavy-Duty Vehicles

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

Miller, Eric; Konan, Arnaud; Duran, Adam

2017-03-28

Accurate vehicle parameters are valuable for design, modeling, and reporting. Estimating vehicle parameters can be a very time-consuming process requiring tightly-controlled experimentation. This work describes a method to estimate vehicle parameters such as mass, coefficient of drag/frontal area, and rolling resistance using data logged during standard vehicle operation. The method uses Monte Carlo to generate parameter sets which is fed to a variant of the road load equation. Modeled road load is then compared to measured load to evaluate the probability of the parameter set. Acceptance of a proposed parameter set is determined using the probability ratio to the currentmore » state, so that the chain history will give a distribution of parameter sets. Compared to a single value, a distribution of possible values provides information on the quality of estimates and the range of possible parameter values. The method is demonstrated by estimating dynamometer parameters. Results confirm the method's ability to estimate reasonable parameter sets, and indicates an opportunity to increase the certainty of estimates through careful selection or generation of the test drive cycle.« less

A model of human decision making in multiple process monitoring situations

NASA Technical Reports Server (NTRS)

Greenstein, J. S.; Rouse, W. B.

1982-01-01

Human decision making in multiple process monitoring situations is considered. It is proposed that human decision making in many multiple process monitoring situations can be modeled in terms of the human's detection of process related events and his allocation of attention among processes once he feels event have occurred. A mathematical model of human event detection and attention allocation performance in multiple process monitoring situations is developed. An assumption made in developing the model is that, in attempting to detect events, the human generates estimates of the probabilities that events have occurred. An elementary pattern recognition technique, discriminant analysis, is used to model the human's generation of these probability estimates. The performance of the model is compared to that of four subjects in a multiple process monitoring situation requiring allocation of attention among processes.

Utility Estimates of Disease-Specific Health States in Prostate Cancer from Three Different Perspectives.

PubMed

Gries, Katharine S; Regier, Dean A; Ramsey, Scott D; Patrick, Donald L

2017-06-01

To develop a statistical model generating utility estimates for prostate cancer specific health states, using preference weights derived from the perspectives of prostate cancer patients, men at risk for prostate cancer, and society. Utility estimate values were calculated using standard gamble (SG) methodology. Study participants valued 18 prostate-specific health states with the five attributes: sexual function, urinary function, bowel function, pain, and emotional well-being. Appropriateness of model (linear regression, mixed effects, or generalized estimating equation) to generate prostate cancer utility estimates was determined by paired t-tests to compare observed and predicted values. Mixed-corrected standard SG utility estimates to account for loss aversion were calculated based on prospect theory. 132 study participants assigned values to the health states (n = 40 men at risk for prostate cancer; n = 43 men with prostate cancer; n = 49 general population). In total, 792 valuations were elicited (six health states for each 132 participants). The most appropriate model for the classification system was a mixed effects model; correlations between the mean observed and predicted utility estimates were greater than 0.80 for each perspective. Developing a health-state classification system with preference weights for three different perspectives demonstrates the relative importance of main effects between populations. The predicted values for men with prostate cancer support the hypothesis that patients experiencing the disease state assign higher utility estimates to health states and there is a difference in valuations made by patients and the general population.

Variable selection models for genomic selection using whole-genome sequence data and singular value decomposition.

PubMed

Meuwissen, Theo H E; Indahl, Ulf G; Ødegård, Jørgen

2017-12-27

Non-linear Bayesian genomic prediction models such as BayesA/B/C/R involve iteration and mostly Markov chain Monte Carlo (MCMC) algorithms, which are computationally expensive, especially when whole-genome sequence (WGS) data are analyzed. Singular value decomposition (SVD) of the genotype matrix can facilitate genomic prediction in large datasets, and can be used to estimate marker effects and their prediction error variances (PEV) in a computationally efficient manner. Here, we developed, implemented, and evaluated a direct, non-iterative method for the estimation of marker effects for the BayesC genomic prediction model. The BayesC model assumes a priori that markers have normally distributed effects with probability [Formula: see text] and no effect with probability (1 - [Formula: see text]). Marker effects and their PEV are estimated by using SVD and the posterior probability of the marker having a non-zero effect is calculated. These posterior probabilities are used to obtain marker-specific effect variances, which are subsequently used to approximate BayesC estimates of marker effects in a linear model. A computer simulation study was conducted to compare alternative genomic prediction methods, where a single reference generation was used to estimate marker effects, which were subsequently used for 10 generations of forward prediction, for which accuracies were evaluated. SVD-based posterior probabilities of markers having non-zero effects were generally lower than MCMC-based posterior probabilities, but for some regions the opposite occurred, resulting in clear signals for QTL-rich regions. The accuracies of breeding values estimated using SVD- and MCMC-based BayesC analyses were similar across the 10 generations of forward prediction. For an intermediate number of generations (2 to 5) of forward prediction, accuracies obtained with the BayesC model tended to be slightly higher than accuracies obtained using the best linear unbiased prediction of SNP effects (SNP-BLUP model). When reducing marker density from WGS data to 30 K, SNP-BLUP tended to yield the highest accuracies, at least in the short term. Based on SVD of the genotype matrix, we developed a direct method for the calculation of BayesC estimates of marker effects. Although SVD- and MCMC-based marker effects differed slightly, their prediction accuracies were similar. Assuming that the SVD of the marker genotype matrix is already performed for other reasons (e.g. for SNP-BLUP), computation times for the BayesC predictions were comparable to those of SNP-BLUP.

Check Firing of Master and Reference Propellants

DTIC Science & Technology

2014-12-08

estimate amount and color of smoke generated. s. Visually estimate amount and color of muzzle flash generated. TOP 04-2-607A 8 December 2014 10...Stargauge. TOP 04-2-607A 8 December 2014 3 e. Pressure gauge (piezoelectric preferred, and/or crusher). f. Muzzle velocity radar unit...firing: a. Provide electronics personnel with the weapon caliber and type, the weight and model of projectile, and expected muzzle velocities. b

The effects of missing data on global ozone estimates

NASA Technical Reports Server (NTRS)

Drewry, J. W.; Robbins, J. L.

1981-01-01

The effects of missing data and model truncation on estimates of the global mean, zonal distribution, and global distribution of ozone are considered. It is shown that missing data can introduce biased estimates with errors that are not accounted for in the accuracy calculations of empirical modeling techniques. Data-fill techniques are introduced and used for evaluating error bounds and constraining the estimate in areas of sparse and missing data. It is found that the accuracy of the global mean estimate is more dependent on data distribution than model size. Zonal features can be accurately described by 7th order models over regions of adequate data distribution. Data variance accounted for by higher order models appears to represent climatological features of columnar ozone rather than pure error. Data-fill techniques can prevent artificial feature generation in regions of sparse or missing data without degrading high order estimates over dense data regions.

Assimilating a synthetic Kalman filter leaf area index series into the WOFOST model to improve regional winter wheat yield estimation

USDA-ARS?s Scientific Manuscript database

The scale mismatch between remotely sensed observations and crop growth models simulated state variables decreases the reliability of crop yield estimates. To overcome this problem, we used a two-step data assimilation phases: first we generated a complete leaf area index (LAI) time series by combin...

Inclusion of unsteady aerodynamics in longitudinal parameter estimation from flight data. [use of vortices and mathematical models for parameterization from flight characteristics

NASA Technical Reports Server (NTRS)

Queijo, M. J.; Wells, W. R.; Keskar, D. A.

1979-01-01

A simple vortex system, used to model unsteady aerodynamic effects into the rigid body longitudinal equations of motion of an aircraft, is described. The equations are used in the development of a parameter extraction algorithm. Use of the two parameter-estimation modes, one including and the other omitting unsteady aerodynamic modeling, is discussed as a means of estimating some acceleration derivatives. Computer generated data and flight data, used to demonstrate the use of the parameter-extraction algorithm are studied.

Distributed PV Adoption in Maine Through 2021

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

Gagnon, Pieter; Sigrin, Ben

2015-11-06

NREL has used its dSolar (distributed solar) model to generate low-medium-high estimates of distributed PV adoption in Maine through 2021. This presentation gives a high-level overview of the model and modeling results.

Model synthesis in frequency analysis of Missouri floods

USGS Publications Warehouse

Hauth, Leland D.

1974-01-01

Synthetic flood records for 43 small-stream sites aided in definition of techniques for estimating the magnitude and frequency of floods in Missouri. The long-term synthetic flood records were generated by use of a digital computer model of the rainfall-runoff process. A relatively short period of concurrent rainfall and runoff data observed at each of the 43 sites was used to calibrate the model, and rainfall records covering from 66 to 78 years for four Missouri sites and pan-evaporation data were used to generate the synthetic records. Flood magnitude and frequency characteristics of both the synthetic records and observed long-term flood records available for 109 large-stream sites were used in a multiple-regression analysis to define relations for estimating future flood characteristics at ungaged sites. That analysis indicated that drainage basin size and slope were the most useful estimating variables. It also indicated that a more complex regression model than the commonly used log-linear one was needed for the range of drainage basin sizes available in this study.

True and apparent scaling: The proximity of the Markov-switching multifractal model to long-range dependence

NASA Astrophysics Data System (ADS)

Liu, Ruipeng; Di Matteo, T.; Lux, Thomas

2007-09-01

In this paper, we consider daily financial data of a collection of different stock market indices, exchange rates, and interest rates, and we analyze their multi-scaling properties by estimating a simple specification of the Markov-switching multifractal (MSM) model. In order to see how well the estimated model captures the temporal dependence of the data, we estimate and compare the scaling exponents H(q) (for q=1,2) for both empirical data and simulated data of the MSM model. In most cases the multifractal model appears to generate ‘apparent’ long memory in agreement with the empirical scaling laws.

Automatic Generation of Cycle-Approximate TLMs with Timed RTOS Model Support

NASA Astrophysics Data System (ADS)

Hwang, Yonghyun; Schirner, Gunar; Abdi, Samar

This paper presents a technique for automatically generating cycle-approximate transaction level models (TLMs) for multi-process applications mapped to embedded platforms. It incorporates three key features: (a) basic block level timing annotation, (b) RTOS model integration, and (c) RTOS overhead delay modeling. The inputs to TLM generation are application C processes and their mapping to processors in the platform. A processor data model, including pipelined datapath, memory hierarchy and branch delay model is used to estimate basic block execution delays. The delays are annotated to the C code, which is then integrated with a generated SystemC RTOS model. Our abstract RTOS provides dynamic scheduling and inter-process communication (IPC) with processor- and RTOS-specific pre-characterized timing. Our experiments using a MP3 decoder and a JPEG encoder show that timed TLMs, with integrated RTOS models, can be automatically generated in less than a minute. Our generated TLMs simulated three times faster than real-time and showed less than 10% timing error compared to board measurements.

High copy and stable expression of the xylanase XynHB in Saccharomyces cerevisiae by rDNA-mediated integration.

PubMed

Fang, Cheng; Wang, Qinhong; Selvaraj, Jonathan Nimal; Zhou, Yuling; Ma, Lixin; Zhang, Guimin; Ma, Yanhe

2017-08-18

Xylanase is a widely-used additive in baking industry for enhancing dough and bread quality. Several xylanases used in baking industry were expressed in different systems, but their expression in antibiotic free vector system is highly essential and safe. In the present study, an alternative rDNA-mediated technology was developed to increase the copy number of target gene by integrating it into Saccharomyces cerevisiae genome. A xylanase-encoding gene xynHB from Bacillus sp. was cloned into pHBM367H and integrated into S. cerevisiae genome through rDNA-mediated recombination. Exogenous XynHB expressed by recombinant S. cerevisiae strain A13 exhibited higher degradation activity towards xylan than other transformants. The real-time PCR analysis on A13 genome revealed the presence of 13.64 copies of xynHB gene. Though no antibiotics have been used, the genetic stability and the xylanase activity of xynHB remained stable up to 1,011 generations of cultivation. S. cerevisiae strain A13 expressing xylanase reduced the required kneading time and increased the height and diameter of the dough size, which would be safe and effective in baking industry as no antibiotics-resistance risk. The new effective rDNA-mediated technology without using antibiotics here provides a way to clone other food related industrial enzymes for applications.

The Impact of Different Missing Data Handling Methods on DINA Model

ERIC Educational Resources Information Center

Sünbül, Seçil Ömür

2018-01-01

In this study, it was aimed to investigate the impact of different missing data handling methods on DINA model parameter estimation and classification accuracy. In the study, simulated data were used and the data were generated by manipulating the number of items and sample size. In the generated data, two different missing data mechanisms…

E-Area LLWF Vadose Zone Model: Probabilistic Model for Estimating Subsided-Area Infiltration Rates

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

Dyer, J.; Flach, G.

A probabilistic model employing a Monte Carlo sampling technique was developed in Python to generate statistical distributions of the upslope-intact-area to subsided-area ratio (Area UAi/Area SAi) for closure cap subsidence scenarios that differ in assumed percent subsidence and the total number of intact plus subsided compartments. The plan is to use this model as a component in the probabilistic system model for the E-Area Performance Assessment (PA), contributing uncertainty in infiltration estimates.

Ensemble Kalman Filter for Dynamic State Estimation of Power Grids Stochastically Driven by Time-correlated Mechanical Input Power

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

Rosenthal, William Steven; Tartakovsky, Alex; Huang, Zhenyu

State and parameter estimation of power transmission networks is important for monitoring power grid operating conditions and analyzing transient stability. Wind power generation depends on fluctuating input power levels, which are correlated in time and contribute to uncertainty in turbine dynamical models. The ensemble Kalman filter (EnKF), a standard state estimation technique, uses a deterministic forecast and does not explicitly model time-correlated noise in parameters such as mechanical input power. However, this uncertainty affects the probability of fault-induced transient instability and increased prediction bias. Here a novel approach is to model input power noise with time-correlated stochastic fluctuations, and integratemore » them with the network dynamics during the forecast. While the EnKF has been used to calibrate constant parameters in turbine dynamical models, the calibration of a statistical model for a time-correlated parameter has not been investigated. In this study, twin experiments on a standard transmission network test case are used to validate our time-correlated noise model framework for state estimation of unsteady operating conditions and transient stability analysis, and a methodology is proposed for the inference of the mechanical input power time-correlation length parameter using time-series data from PMUs monitoring power dynamics at generator buses.« less

Ensemble Kalman Filter for Dynamic State Estimation of Power Grids Stochastically Driven by Time-correlated Mechanical Input Power

DOE PAGES

Rosenthal, William Steven; Tartakovsky, Alex; Huang, Zhenyu

2017-10-31

State and parameter estimation of power transmission networks is important for monitoring power grid operating conditions and analyzing transient stability. Wind power generation depends on fluctuating input power levels, which are correlated in time and contribute to uncertainty in turbine dynamical models. The ensemble Kalman filter (EnKF), a standard state estimation technique, uses a deterministic forecast and does not explicitly model time-correlated noise in parameters such as mechanical input power. However, this uncertainty affects the probability of fault-induced transient instability and increased prediction bias. Here a novel approach is to model input power noise with time-correlated stochastic fluctuations, and integratemore » them with the network dynamics during the forecast. While the EnKF has been used to calibrate constant parameters in turbine dynamical models, the calibration of a statistical model for a time-correlated parameter has not been investigated. In this study, twin experiments on a standard transmission network test case are used to validate our time-correlated noise model framework for state estimation of unsteady operating conditions and transient stability analysis, and a methodology is proposed for the inference of the mechanical input power time-correlation length parameter using time-series data from PMUs monitoring power dynamics at generator buses.« less

A novel methodology to estimate the evolution of construction waste in construction sites.

PubMed

Katz, Amnon; Baum, Hadassa

2011-02-01

This paper focuses on the accumulation of construction waste generated throughout the erection of new residential buildings. A special methodology was developed in order to provide a model that will predict the flow of construction waste. The amount of waste and its constituents, produced on 10 relatively large construction sites (7000-32,000 m(2) of built area) was monitored periodically for a limited time. A model that predicts the accumulation of construction waste was developed based on these field observations. According to the model, waste accumulates in an exponential manner, i.e. smaller amounts are generated during the early stages of construction and increasing amounts are generated towards the end of the project. The total amount of waste from these sites was estimated at 0.2m(3) per 1m(2) floor area. A good correlation was found between the model predictions and actual data from the field survey. Copyright © 2010 Elsevier Ltd. All rights reserved.

Study of parameter identification using hybrid neural-genetic algorithm in electro-hydraulic servo system

NASA Astrophysics Data System (ADS)

Moon, Byung-Young

2005-12-01

The hybrid neural-genetic multi-model parameter estimation algorithm was demonstrated. This method can be applied to structured system identification of electro-hydraulic servo system. This algorithms consist of a recurrent incremental credit assignment(ICRA) neural network and a genetic algorithm. The ICRA neural network evaluates each member of a generation of model and genetic algorithm produces new generation of model. To evaluate the proposed method, electro-hydraulic servo system was designed and manufactured. The experiment was carried out to figure out the hybrid neural-genetic multi-model parameter estimation algorithm. As a result, the dynamic characteristics were obtained such as the parameters(mass, damping coefficient, bulk modulus, spring coefficient), which minimize total square error. The result of this study can be applied to hydraulic systems in industrial fields.

SU-F-T-479: Estimation of the Accuracy in Respiratory-Gated Radiotherapy

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

Kurosawa, T; Miyakawa, S; Sato, M

Purpose: Irregular respiratory patterns affects dose outputs in respiratorygated radiotherapy and there is no commercially available quality assurance (QA) system for it. We designed and developed a patient specific QA system for respiratory-gated radiotherapy to estimate irradiated output. Methods: Our in-house QA system for gating was composed of a personal computer with the USB-FSIO electronic circuit connecting to the linear accelerator (ONCOR-K, Toshiba Medical Systems). The linac implements a respiratory gating system (AZ-733V, Anzai Medical). During the beam was on, 4.2 V square-wave pulses were continually sent to the system. Our system can receive and count the pulses. At first,more » our system and an oscilloscope were compared to check the performance of our system. Next, basic estimation models were generated when ionization-chamber measurements were performed in gating using regular sinusoidal wave patterns (2.0, 2.5, 4.0, 8.0, 15 sec/cycle). During gated irradiation with the regular patterns, the number of the pulses per one gating window was measured using our system. Correlation between the number of the pulses per one gating and dose per the gating window were assessed to generate the estimation model. Finally, two irregular respiratory patterns were created and the accuracy of the estimation was evaluated. Results: Compared to the oscilloscope, our system worked similarly. The basic models were generated with the accuracy within 0.1%. The results of the gated irradiations with two irregular respiratory patterns show good agreement within 0.4% estimation accuracy. Conclusion: Our developed system shows good estimation for even irregular respiration patterns. The system would be a useful tool to verify the output for respiratory-gated radiotherapy.« less

Wheat productivity estimates using LANDSAT data

NASA Technical Reports Server (NTRS)

Nalepka, R. F.; Colwell, J. E. (Principal Investigator); Rice, D. P.; Bresnahan, P. A.

1977-01-01

The author has identified the following significant results. Large area LANDSAT yield estimates were generated. These results were compared with estimates computed using a meteorological yield model (CCEA). Both of these estimates were compared with Kansas Crop and Livestock Reporting Service (KCLRS) estimates of yield, in an attempt to assess the relative and absolute accuracy of the LANDSAT and CCEA estimates. Results were inconclusive. A large area direct wheat prediction procedure was implemented. Initial results have produced a wheat production estimate comparable with the KCLRS estimate.

Estimating Water and Heat Fluxes with a Four-dimensional Weak-constraint Variational Data Assimilation Approach

NASA Astrophysics Data System (ADS)

Bateni, S. M.; Xu, T.

2015-12-01

Accurate estimation of water and heat fluxes is required for irrigation scheduling, weather prediction, and water resources planning and management. A weak-constraint variational data assimilation (WC-VDA) scheme is developed to estimate water and heat fluxes by assimilating sequences of land surface temperature (LST) observations. The commonly used strong-constraint VDA systems adversely affect the accuracy of water and heat flux estimates as they assume the model is perfect. The WC-VDA approach accounts for structural and model errors and generates more accurate results via adding a model error term into the surface energy balance equation. The two key unknown parameters of the WC-VDA system (i.e., CHN, the bulk heat transfer coefficient and EF, evaporative fraction) and the model error term are optimized by minimizing the cost function. The WC-VDA model was tested at two sites with contrasting hydrological and vegetative conditions: the Daman site (a wet site located in an oasis area and covered by seeded corn) and the Huazhaizi site (a dry site located in a desert area and covered by sparse grass) in middle stream of Heihe river basin, northwest China. Compared to the strong-constraint VDA system, the WC-VDA method generates more accurate estimates of water and energy fluxes over the desert and oasis sites with dry and wet conditions.

Estimating and validating ground-based timber harvesting production through computer simulation

Treesearch

Jingxin Wang; Chris B. LeDoux

2003-01-01

Estimating ground-based timber harvesting systems production with an object oriented methodology was investigated. The estimation model developed generates stands of trees, simulates chain saw, drive-to-tree feller-buncher, swing-to-tree single-grip harvester felling, and grapple skidder and forwarder extraction activities, and analyzes costs and productivity. It also...

Economic modeling and energy policy planning. [technology transfer, market research

NASA Technical Reports Server (NTRS)

Thompson, R. G.; Schwartz, A., Jr.; Lievano, R. J.; Stone, J. C.

1974-01-01

A structural economic model is presented for estimating the demand functions for natural gas and crude oil in industry and in steam electric power generation. Extensions of the model to other commodities are indicated.

Estimating Software-Development Costs With Greater Accuracy

NASA Technical Reports Server (NTRS)

Baker, Dan; Hihn, Jairus; Lum, Karen

2008-01-01

COCOMOST is a computer program for use in estimating software development costs. The goal in the development of COCOMOST was to increase estimation accuracy in three ways: (1) develop a set of sensitivity software tools that return not only estimates of costs but also the estimation error; (2) using the sensitivity software tools, precisely define the quantities of data needed to adequately tune cost estimation models; and (3) build a repository of software-cost-estimation information that NASA managers can retrieve to improve the estimates of costs of developing software for their project. COCOMOST implements a methodology, called '2cee', in which a unique combination of well-known pre-existing data-mining and software-development- effort-estimation techniques are used to increase the accuracy of estimates. COCOMOST utilizes multiple models to analyze historical data pertaining to software-development projects and performs an exhaustive data-mining search over the space of model parameters to improve the performances of effort-estimation models. Thus, it is possible to both calibrate and generate estimates at the same time. COCOMOST is written in the C language for execution in the UNIX operating system.

Fuels planning: science synthesis and integration; environmental consequences fact sheet 12: Water Erosion Prediction Project (WEPP) Fuel Management (FuMe) tool

Treesearch

William Elliot; David Hall

2005-01-01

The Water Erosion Prediction Project (WEPP) Fuel Management (FuMe) tool was developed to estimate sediment generated by fuel management activities. WEPP FuMe estimates sediment generated for 12 fuel-related conditions from a single input. This fact sheet identifies the intended users and uses, required inputs, what the model does, and tells the user how to obtain the...

Lifetime earnings for physicians across specialties.

PubMed

Leigh, J Paul; Tancredi, Daniel; Jerant, Anthony; Romano, Patrick S; Kravitz, Richard L

2012-12-01

Earlier studies estimated annual income differences across specialties, but lifetime income may be more relevant given physicians' long-term commitments to specialties. Annual income and work hours data were collected from 6381 physicians in the nationally representative 2004-2005 Community Tracking Study. Data regarding years of residency were collected from AMA FREIDA. Present value models were constructed assuming 3% discount rates. Estimates were adjusted for demographic and market covariates. Sensitivity analyses included 4 alternative models involving work hours, retirement, exogenous variables, and 1% discount rate. Estimates were generated for 4 broad specialty categories (Primary Care, Surgery, Internal Medicine and Pediatric Subspecialties, and Other), and for 41 specific specialties. The estimates of lifetime earnings for the broad categories of Surgery, Internal Medicine and Pediatric Subspecialties, and Other specialties were $1,587,722, $1,099,655, and $761,402 more than for Primary Care. For the 41 specific specialties, the top 3 (with family medicine as reference) were neurological surgery ($2,880,601), medical oncology ($2,772,665), and radiation oncology ($2,659,657). The estimates from models with varying rates of retirement and including only exogenous variables were similar to those in the preferred model. The 1% discount model generated estimates that were roughly 150% larger than the 3% model. There was considerable variation in the lifetime earnings across physician specialties. After accounting for varying residency years and discounting future earnings, primary care specialties earned roughly $1-3 million less than other specialties. Earnings' differences across specialties may undermine health reform efforts to control costs and ensure adequate numbers of primary care physicians.

Comparing alternative tree canopy cover estimates derived from digital aerial photography and field-based assessments

Treesearch

Tracey S. Frescino; Gretchen G. Moisen

2012-01-01

A spatially-explicit representation of live tree canopy cover, such as the National Land Cover Dataset (NLCD) percent tree canopy cover layer, is a valuable tool for many applications, such as defining forest land, delineating wildlife habitat, estimating carbon, and modeling fire risk and behavior. These layers are generated by predictive models wherein their accuracy...

Battery Pack Life Estimation through Cell Degradation Data and Pack Thermal Modeling for BAS+ Li-Ion Batteries. Cooperative Research and Development Final Report, CRADA Number CRD-12-489

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

Smith, Kandler

Battery Life estimation is one of the key inputs required for Hybrid applications for all GM Hybrid/EV/EREV/PHEV programs. For each Hybrid vehicle program, GM has instituted multi-parameter Design of Experiments generating test data at Cell level and also Pack level on a reduced basis. Based on experience, generating test data on a pack level is found to be very expensive, resource intensive and sometimes less reliable. The proposed collaborative project will focus on a methodology to estimate Battery life based on cell degradation data combined with pack thermal modeling. NREL has previously developed cell-level battery aging models and pack-level thermal/electricalmore » network models, though these models are currently not integrated. When coupled together, the models are expected to describe pack-level thermal and aging response of individual cells. GM and NREL will use data collected for GM's Bas+ battery system for evaluation of the proposed methodology and assess to what degree these models can replace pack-level aging experiments in the future.« less

Predictors of refusal of provider initiated HIV testing among clients visiting adult outpatient departments in Jimma town, Oromia Region, Ethiopia: unmatched case control study

PubMed Central

Lemu, Yohannes Kebede; Koricha, Zewdie Birhanu; Gebretsadik, Lakew Abebe; Roro, Ameyu Godesso

2012-01-01

Background Currently, provider-initiated human immunodeficiency virus (HIV) testing (PIHT) in health facilities is one of the strategies to advance HIV testing and related services. However, many HIV infected clients are missing the opportunities. This study intends to identify predictors of refusal of PIHT among clients visiting adult outpatient departments (OPDs) in Jimma town. Methods An unmatched case control study was conducted among 296 clients: 149 cases refusing HIV testing and 147 controls accepting HIV testing. The study recruited clients from OPDs of four public health facilities between March 6 and April 8, 2011 using consecutive sampling. The study instrument was adapted mainly considering health belief model (HBM). Jimma University ethical committee reviewed the study protocol. Data were collected by face-to-face interview and analyzed using SPSS Statistics (IBM Corporation, Somers, NY) software, version 16.0. Data were subjected to factor and reliability analysis. For prediction analysis, the study used logistic regression and odds ratio (OR) with 95% confidence interval (CI). To see the effects among HBM constructs, the study used standardized beta (β) coefficients at P < 0.05. Results The study findings showed adjusted protective effects on refusal of PIHT for residence outside study town [adjusted OR (AOR) (95% CI) = 0.41 (0.22–0.79)] and higher scores of perceived benefit of early testing [AOR (95% CI)] = 0.86 (0.69–0.99)], self efficacy to live with HIV [AOR (95% CI) = 0.79 (0.66–0.93)], nondisclosure agreement [AOR (95% CI) = 0.74 (0.58–0.93)], perceived explicitness of opt-out right during initiation [AOR (95% CI) = 0.74 (0.56–0.98)] and clients’ perceptions of selective initiation of HIV suspected [AOR (95% CI) = 0.54 (0.41–0.73)]. On the other hand, report of recent testing [AOR (95% CI) = 3.82 (1.71–8.55)] and perceived unpreparedness for testing [AOR (95% CI) = 1.86 (1.57–2.21)] aggravated refusal of PIHT. Exposure to cues to testing significantly reduced perceived barriers [β (P) = −0.05 (0.037)]. Conclusion Clients’ perceived barriers: feeling of unpreparedness for testing strongly aggravated refusal of test. Enhanced self-efficacy to live with HIV and presence of cues to HIV testing would reduce unpreparedness and protect from refusing PIHT. PMID:22904647

Enhancing e-waste estimates: Improving data quality by multivariate Input–Output Analysis

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

Wang, Feng, E-mail: fwang@unu.edu; Design for Sustainability Lab, Faculty of Industrial Design Engineering, Delft University of Technology, Landbergstraat 15, 2628CE Delft; Huisman, Jaco

2013-11-15

Highlights: • A multivariate Input–Output Analysis method for e-waste estimates is proposed. • Applying multivariate analysis to consolidate data can enhance e-waste estimates. • We examine the influence of model selection and data quality on e-waste estimates. • Datasets of all e-waste related variables in a Dutch case study have been provided. • Accurate modeling of time-variant lifespan distributions is critical for estimate. - Abstract: Waste electrical and electronic equipment (or e-waste) is one of the fastest growing waste streams, which encompasses a wide and increasing spectrum of products. Accurate estimation of e-waste generation is difficult, mainly due to lackmore » of high quality data referred to market and socio-economic dynamics. This paper addresses how to enhance e-waste estimates by providing techniques to increase data quality. An advanced, flexible and multivariate Input–Output Analysis (IOA) method is proposed. It links all three pillars in IOA (product sales, stock and lifespan profiles) to construct mathematical relationships between various data points. By applying this method, the data consolidation steps can generate more accurate time-series datasets from available data pool. This can consequently increase the reliability of e-waste estimates compared to the approach without data processing. A case study in the Netherlands is used to apply the advanced IOA model. As a result, for the first time ever, complete datasets of all three variables for estimating all types of e-waste have been obtained. The result of this study also demonstrates significant disparity between various estimation models, arising from the use of data under different conditions. It shows the importance of applying multivariate approach and multiple sources to improve data quality for modelling, specifically using appropriate time-varying lifespan parameters. Following the case study, a roadmap with a procedural guideline is provided to enhance e-waste estimation studies.« less

Near Real-time GNSS-based Ionospheric Model using Expanded Kriging in the East Asia Region

NASA Astrophysics Data System (ADS)

Choi, P. H.; Bang, E.; Lee, J.

2016-12-01

Many applications which utilize radio waves (e.g. navigation, communications, and radio sciences) are influenced by the ionosphere. The technology to provide global ionospheric maps (GIM) which show ionospheric Total Electron Content (TEC) has been progressed by processing GNSS data. However, the GIMs have limited spatial resolution (e.g. 2.5° in latitude and 5° in longitude), because they are generated using globally-distributed and thus relatively sparse GNSS reference station networks. This study presents a near real-time and high spatial resolution TEC model over East Asia by using ionospheric observables from both International GNSS Service (IGS) and local GNSS networks and the expanded kriging method. New signals from multi-constellation (e.g,, GPS L5, Galileo E5) were also used to generate high-precision TEC estimates. The newly proposed estimation method is based on the universal kriging interpolation technique, but integrates TEC data from previous epochs to those from the current epoch to improve the TEC estimation performance by increasing ionospheric observability. To propagate previous measurements to the current epoch, we implemented a Kalman filter whose dynamic model was derived by using the first-order Gauss-Markov process which characterizes temporal ionospheric changes under the nominal ionospheric conditions. Along with the TEC estimates at grids, the method generates the confidence bounds on the estimates using resulting estimation covariance. We also suggest to classify the confidence bounds into several categories to allow users to recognize the quality levels of TEC estimates according to the requirements for user's applications. This paper examines the performance of the proposed method by obtaining estimation results for both nominal and disturbed ionospheric conditions, and compares these results to those provided by GIM of the NASA Jet propulsion Laboratory. In addition, the estimation results based on the expanded kriging method are compared to the results from the universal kriging method for both nominal and disturbed ionospheric conditions.

Constitutive Modeling of Porcine Liver in Indentation Using 3D Ultrasound Imaging

PubMed Central

Jordan, P.; Socrate, S.; Zickler, T.E.; Howe, R.D.

2009-01-01

In this work we present an inverse finite-element modeling framework for constitutive modeling and parameter estimation of soft tissues using full-field volumetric deformation data obtained from 3D ultrasound. The finite-element model is coupled to full-field visual measurements by regularization springs attached at nodal locations. The free ends of the springs are displaced according to the locally estimated tissue motion and the normalized potential energy stored in all springs serves as a measure of model-experiment agreement for material parameter optimization. We demonstrate good accuracy of estimated parameters and consistent convergence properties on synthetically generated data. We present constitutive model selection and parameter estimation for perfused porcine liver in indentation and demonstrate that a quasilinear viscoelastic model with shear modulus relaxation offers good model-experiment agreement in terms of indenter displacement (0.19 mm RMS error) and tissue displacement field (0.97 mm RMS error). PMID:19627823

Method and system to estimate variables in an integrated gasification combined cycle (IGCC) plant

DOEpatents

Kumar, Aditya; Shi, Ruijie; Dokucu, Mustafa

2013-09-17

System and method to estimate variables in an integrated gasification combined cycle (IGCC) plant are provided. The system includes a sensor suite to measure respective plant input and output variables. An extended Kalman filter (EKF) receives sensed plant input variables and includes a dynamic model to generate a plurality of plant state estimates and a covariance matrix for the state estimates. A preemptive-constraining processor is configured to preemptively constrain the state estimates and covariance matrix to be free of constraint violations. A measurement-correction processor may be configured to correct constrained state estimates and a constrained covariance matrix based on processing of sensed plant output variables. The measurement-correction processor is coupled to update the dynamic model with corrected state estimates and a corrected covariance matrix. The updated dynamic model may be configured to estimate values for at least one plant variable not originally sensed by the sensor suite.

An allograft generated from adult stem cells and their secreted products efficiently fuses vertebrae in immunocompromised athymic rats and inhibits local immune responses

PubMed Central

Clough, Bret H.; McNeill, Eoin P.; Palmer, Daniel; Krause, Ulf; Bartosh, Thomas J.; Chaput, Christopher D.; Gregory, Carl A.

2016-01-01

BACKGROUND CONTEXT Spine pain and the disability associated with it are epidemic in the United States. According to the National Center for Health Statistics, more than 650,000 spinal fusion surgeries are performed annually in the United States, and yet there is a failure rate of 15%–40% when standard methods employing current commercial bone substitutes are used. Autologous bone graft is the gold standard in terms of fusion success, but the morbidity associated with the procedure and the limitations in the availability of sufficient material have limited its use in the majority of cases. A freely available and immunologically compatible bone mimetic with the properties of live tissue is likely to substantially improve the outcome of spine fusion procedures without the disadvantages of autologous bone graft. PURPOSE This study aimed to compare a live human bone tissue analog with autologous bone grafting in an immunocompromised rat model of posterolateral fusion. DESIGN/SETTING This is an in vitro and in vivo preclinical study of a novel human stem cell–derived construct for efficacy in posterolateral lumbar spine fusion. METHODS Osteogenically enhanced human mesenchymal stem cells (OEhMSCs) were generated by exposure to conditions that activate the early stages of osteogenesis. Immunologic characteristics of OEhMSCs were evaluated in vitro. The secreted extracellular matrix from OEhMSCs was deposited on a clinical-grade gelatin sponge, resulting in bioconditioned gelatin sponge (BGS). Bioconditioned gelatin sponge was used alone, with live OEhMSCs (BGS+OEhMSCs), or with whole human bone marrow (BGS+hBM). Efficacy for spine fusion was determined by an institutionally approved animal model using 53 nude rats. RESULTS Bioconditioned gelatin sponge with live OEhMSCs did not cause cytotoxicity when incubated with immunologically mismatched lymphocytes, and OEhMSCs inhibited lymphocyte expansion in mixed lymphocyte assays. Bioconditioned gelatin sponge with live OEhMSC and BGS+hBM constructs induced profound bone growth at fusion sites in vivo, with a comparable rate of fusion with syngeneic bone graft (negative [0 of 10], BGS alone [0 of 10], bone graft [7 of 10], BGS+OEhMSC [10 of 15], and BGS+hBM [8 of 8]). CONCLUSIONS Collectively, these studies demonstrate that BGS+OEhMSC constructs possess low immunogenicity and drive vertebral fusion with efficiency matching syngeneic bone graft in rodents. We also demonstrate that BGS serves as a promising scaffold for spine fusion when combined with hBM. PMID:27765715

An allograft generated from adult stem cells and their secreted products efficiently fuses vertebrae in immunocompromised athymic rats and inhibits local immune responses.

PubMed

Clough, Bret H; McNeill, Eoin P; Palmer, Daniel; Krause, Ulf; Bartosh, Thomas J; Chaput, Christopher D; Gregory, Carl A

2017-03-01

Spine pain and the disability associated with it are epidemic in the United States. According to the National Center for Health Statistics, more than 650,000 spinal fusion surgeries are performed annually in the United States, and yet there is a failure rate of 15%-40% when standard methods employing current commercial bone substitutes are used. Autologous bone graft is the gold standard in terms of fusion success, but the morbidity associated with the procedure and the limitations in the availability of sufficient material have limited its use in the majority of cases. A freely available and immunologically compatible bone mimetic with the properties of live tissue is likely to substantially improve the outcome of spine fusion procedures without the disadvantages of autologous bone graft. This study aimed to compare a live human bone tissue analog with autologous bone grafting in an immunocompromised rat model of posterolateral fusion. This is an in vitro and in vivo preclinical study of a novel human stem cell-derived construct for efficacy in posterolateral lumbar spine fusion. Osteogenically enhanced human mesenchymal stem cells (OEhMSCs) were generated by exposure to conditions that activate the early stages of osteogenesis. Immunologic characteristics of OEhMSCs were evaluated in vitro. The secreted extracellular matrix from OEhMSCs was deposited on a clinical-grade gelatin sponge, resulting in bioconditioned gelatin sponge (BGS). Bioconditioned gelatin sponge was used alone, with live OEhMSCs (BGS+OEhMSCs), or with whole human bone marrow (BGS+hBM). Efficacy for spine fusion was determined by an institutionally approved animal model using 53 nude rats. Bioconditioned gelatin sponge with live OEhMSCs did not cause cytotoxicity when incubated with immunologically mismatched lymphocytes, and OEhMSCs inhibited lymphocyte expansion in mixed lymphocyte assays. Bioconditioned gelatin sponge with live OEhMSC and BGS+hBM constructs induced profound bone growth at fusion sites in vivo, with a comparable rate of fusion with syngeneic bone graft (negative [0 of 10], BGS alone [0 of 10], bone graft [7 of 10], BGS+OEhMSC [10 of 15], and BGS+hBM [8 of 8]). Collectively, these studies demonstrate that BGS+OEhMSC constructs possess low immunogenicity and drive vertebral fusion with efficiency matching syngeneic bone graft in rodents. We also demonstrate that BGS serves as a promising scaffold for spine fusion when combined with hBM. Copyright © 2016 Elsevier Inc. All rights reserved.

Estimation of regional building-related C&D debris generation and composition: case study for Florida, US.

PubMed

Cochran, Kimberly; Townsend, Timothy; Reinhart, Debra; Heck, Howell

2007-01-01

Methodology for the accounting, generation, and composition of building-related construction and demolition (C&D) at a regional level was explored. Six specific categories of debris were examined: residential construction, nonresidential construction, residential demolition, nonresidential demolition, residential renovation, and nonresidential renovation. Debris produced from each activity was calculated as the product of the total area of activity and waste generated per unit area of activity. Similarly, composition was estimated as the product of the total area of activity and the amount of each waste component generated per unit area. The area of activity was calculated using statistical data, and individual site studies were used to assess the average amount of waste generated per unit area. The application of the methodology was illustrated using Florida, US approximately 3,750,000 metric tons of building-related C&D debris were estimated as generated in Florida in 2000. Of that amount, concrete represented 56%, wood 13%, drywall 11%, miscellaneous debris 8%, asphalt roofing materials 7%, metal 3%, cardboard 1%, and plastic 1%. This model differs from others because it accommodates regional construction styles and available data. The resulting generation amount per capita is less than the US estimate - attributable to the high construction, low demolition activity seen in Florida.

New Flutter Analysis Technique for Time-Domain Computational Aeroelasticity

NASA Technical Reports Server (NTRS)

Pak, Chan-Gi; Lung, Shun-Fat

2017-01-01

A new time-domain approach for computing flutter speed is presented. Based on the time-history result of aeroelastic simulation, the unknown unsteady aerodynamics model is estimated using a system identification technique. The full aeroelastic model is generated via coupling the estimated unsteady aerodynamic model with the known linear structure model. The critical dynamic pressure is computed and used in the subsequent simulation until the convergence of the critical dynamic pressure is achieved. The proposed method is applied to a benchmark cantilevered rectangular wing.

Advanced risk assessment of the effects of graphite fibers on electronic and electric equipment, phase 1. [simulating vulnerability to airports and communities from fibers released during aircraft fires

NASA Technical Reports Server (NTRS)

Pocinki, L. S.; Kaplan, L. D.; Cornell, M. E.; Greenstone, R.

1979-01-01

A model was developed to generate quantitative estimates of the risk associated with the release of graphite fibers during fires involving commercial aircraft constructed with graphite fiber composite materials. The model was used to estimate the risk associated with accidents at several U.S. airports. These results were then combined to provide an estimate of the total risk to the nation.

Quantification of landfill methane using modified Intergovernmental Panel on Climate Change's waste model and error function analysis.

PubMed

Govindan, Siva Shangari; Agamuthu, P

2014-10-01

Waste management can be regarded as a cross-cutting environmental 'mega-issue'. Sound waste management practices support the provision of basic needs for general health, such as clean air, clean water and safe supply of food. In addition, climate change mitigation efforts can be achieved through reduction of greenhouse gas emissions from waste management operations, such as landfills. Landfills generate landfill gas, especially methane, as a result of anaerobic degradation of the degradable components of municipal solid waste. Evaluating the mode of generation and collection of landfill gas has posted a challenge over time. Scientifically, landfill gas generation rates are presently estimated using numerical models. In this study the Intergovernmental Panel on Climate Change's Waste Model is used to estimate the methane generated from a Malaysian sanitary landfill. Key parameters of the model, which are the decay rate and degradable organic carbon, are analysed in two different approaches; the bulk waste approach and waste composition approach. The model is later validated using error function analysis and optimum decay rate, and degradable organic carbon for both approaches were also obtained. The best fitting values for the bulk waste approach are a decay rate of 0.08 y(-1) and degradable organic carbon value of 0.12; and for the waste composition approach the decay rate was found to be 0.09 y(-1) and degradable organic carbon value of 0.08. From this validation exercise, the estimated error was reduced by 81% and 69% for the bulk waste and waste composition approach, respectively. In conclusion, this type of modelling could constitute a sensible starting point for landfills to introduce careful planning for efficient gas recovery in individual landfills. © The Author(s) 2014.

Graphical Models for Ordinal Data

PubMed Central

Guo, Jian; Levina, Elizaveta; Michailidis, George; Zhu, Ji

2014-01-01

A graphical model for ordinal variables is considered, where it is assumed that the data are generated by discretizing the marginal distributions of a latent multivariate Gaussian distribution. The relationships between these ordinal variables are then described by the underlying Gaussian graphical model and can be inferred by estimating the corresponding concentration matrix. Direct estimation of the model is computationally expensive, but an approximate EM-like algorithm is developed to provide an accurate estimate of the parameters at a fraction of the computational cost. Numerical evidence based on simulation studies shows the strong performance of the algorithm, which is also illustrated on data sets on movie ratings and an educational survey. PMID:26120267

Estimation of inhalation flow profile using audio-based methods to assess inhaler medication adherence.

PubMed

Taylor, Terence E; Lacalle Muls, Helena; Costello, Richard W; Reilly, Richard B

2018-01-01

Asthma and chronic obstructive pulmonary disease (COPD) patients are required to inhale forcefully and deeply to receive medication when using a dry powder inhaler (DPI). There is a clinical need to objectively monitor the inhalation flow profile of DPIs in order to remotely monitor patient inhalation technique. Audio-based methods have been previously employed to accurately estimate flow parameters such as the peak inspiratory flow rate of inhalations, however, these methods required multiple calibration inhalation audio recordings. In this study, an audio-based method is presented that accurately estimates inhalation flow profile using only one calibration inhalation audio recording. Twenty healthy participants were asked to perform 15 inhalations through a placebo Ellipta™ DPI at a range of inspiratory flow rates. Inhalation flow signals were recorded using a pneumotachograph spirometer while inhalation audio signals were recorded simultaneously using the Inhaler Compliance Assessment device attached to the inhaler. The acoustic (amplitude) envelope was estimated from each inhalation audio signal. Using only one recording, linear and power law regression models were employed to determine which model best described the relationship between the inhalation acoustic envelope and flow signal. Each model was then employed to estimate the flow signals of the remaining 14 inhalation audio recordings. This process repeated until each of the 15 recordings were employed to calibrate single models while testing on the remaining 14 recordings. It was observed that power law models generated the highest average flow estimation accuracy across all participants (90.89±0.9% for power law models and 76.63±2.38% for linear models). The method also generated sufficient accuracy in estimating inhalation parameters such as peak inspiratory flow rate and inspiratory capacity within the presence of noise. Estimating inhaler inhalation flow profiles using audio based methods may be clinically beneficial for inhaler technique training and the remote monitoring of patient adherence.

Estimation of inhalation flow profile using audio-based methods to assess inhaler medication adherence

PubMed Central

Lacalle Muls, Helena; Costello, Richard W.; Reilly, Richard B.

2018-01-01

Asthma and chronic obstructive pulmonary disease (COPD) patients are required to inhale forcefully and deeply to receive medication when using a dry powder inhaler (DPI). There is a clinical need to objectively monitor the inhalation flow profile of DPIs in order to remotely monitor patient inhalation technique. Audio-based methods have been previously employed to accurately estimate flow parameters such as the peak inspiratory flow rate of inhalations, however, these methods required multiple calibration inhalation audio recordings. In this study, an audio-based method is presented that accurately estimates inhalation flow profile using only one calibration inhalation audio recording. Twenty healthy participants were asked to perform 15 inhalations through a placebo Ellipta™ DPI at a range of inspiratory flow rates. Inhalation flow signals were recorded using a pneumotachograph spirometer while inhalation audio signals were recorded simultaneously using the Inhaler Compliance Assessment device attached to the inhaler. The acoustic (amplitude) envelope was estimated from each inhalation audio signal. Using only one recording, linear and power law regression models were employed to determine which model best described the relationship between the inhalation acoustic envelope and flow signal. Each model was then employed to estimate the flow signals of the remaining 14 inhalation audio recordings. This process repeated until each of the 15 recordings were employed to calibrate single models while testing on the remaining 14 recordings. It was observed that power law models generated the highest average flow estimation accuracy across all participants (90.89±0.9% for power law models and 76.63±2.38% for linear models). The method also generated sufficient accuracy in estimating inhalation parameters such as peak inspiratory flow rate and inspiratory capacity within the presence of noise. Estimating inhaler inhalation flow profiles using audio based methods may be clinically beneficial for inhaler technique training and the remote monitoring of patient adherence. PMID:29346430

Dual respiratory and cardiac motion estimation in PET imaging: Methods design and quantitative evaluation.

PubMed

Feng, Tao; Wang, Jizhe; Tsui, Benjamin M W

2018-04-01

The goal of this study was to develop and evaluate four post-reconstruction respiratory and cardiac (R&C) motion vector field (MVF) estimation methods for cardiac 4D PET data. In Method 1, the dual R&C motions were estimated directly from the dual R&C gated images. In Method 2, respiratory motion (RM) and cardiac motion (CM) were separately estimated from the respiratory gated only and cardiac gated only images. The effects of RM on CM estimation were modeled in Method 3 by applying an image-based RM correction on the cardiac gated images before CM estimation, the effects of CM on RM estimation were neglected. Method 4 iteratively models the mutual effects of RM and CM during dual R&C motion estimations. Realistic simulation data were generated for quantitative evaluation of four methods. Almost noise-free PET projection data were generated from the 4D XCAT phantom with realistic R&C MVF using Monte Carlo simulation. Poisson noise was added to the scaled projection data to generate additional datasets of two more different noise levels. All the projection data were reconstructed using a 4D image reconstruction method to obtain dual R&C gated images. The four dual R&C MVF estimation methods were applied to the dual R&C gated images and the accuracy of motion estimation was quantitatively evaluated using the root mean square error (RMSE) of the estimated MVFs. Results show that among the four estimation methods, Methods 2 performed the worst for noise-free case while Method 1 performed the worst for noisy cases in terms of quantitative accuracy of the estimated MVF. Methods 4 and 3 showed comparable results and achieved RMSE lower by up to 35% than that in Method 1 for noisy cases. In conclusion, we have developed and evaluated 4 different post-reconstruction R&C MVF estimation methods for use in 4D PET imaging. Comparison of the performance of four methods on simulated data indicates separate R&C estimation with modeling of RM before CM estimation (Method 3) to be the best option for accurate estimation of dual R&C motion in clinical situation. © 2018 American Association of Physicists in Medicine.

Censored rainfall modelling for estimation of fine-scale extremes

NASA Astrophysics Data System (ADS)

Cross, David; Onof, Christian; Winter, Hugo; Bernardara, Pietro

2018-01-01

Reliable estimation of rainfall extremes is essential for drainage system design, flood mitigation, and risk quantification. However, traditional techniques lack physical realism and extrapolation can be highly uncertain. In this study, we improve the physical basis for short-duration extreme rainfall estimation by simulating the heavy portion of the rainfall record mechanistically using the Bartlett-Lewis rectangular pulse (BLRP) model. Mechanistic rainfall models have had a tendency to underestimate rainfall extremes at fine temporal scales. Despite this, the simple process representation of rectangular pulse models is appealing in the context of extreme rainfall estimation because it emulates the known phenomenology of rainfall generation. A censored approach to Bartlett-Lewis model calibration is proposed and performed for single-site rainfall from two gauges in the UK and Germany. Extreme rainfall estimation is performed for each gauge at the 5, 15, and 60 min resolutions, and considerations for censor selection discussed.

A Methodology for Calculating EGS Electricity Generation Potential Based on the Gringarten Model for Heat Extraction From Fractured Rock

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

Augustine, Chad

Existing methodologies for estimating the electricity generation potential of Enhanced Geothermal Systems (EGS) assume thermal recovery factors of 5% or less, resulting in relatively low volumetric electricity generation potentials for EGS reservoirs. This study proposes and develops a methodology for calculating EGS electricity generation potential based on the Gringarten conceptual model and analytical solution for heat extraction from fractured rock. The electricity generation potential of a cubic kilometer of rock as a function of temperature is calculated assuming limits on the allowed produced water temperature decline and reservoir lifetime based on surface power plant constraints. The resulting estimates of EGSmore » electricity generation potential can be one to nearly two-orders of magnitude larger than those from existing methodologies. The flow per unit fracture surface area from the Gringarten solution is found to be a key term in describing the conceptual reservoir behavior. The methodology can be applied to aid in the design of EGS reservoirs by giving minimum reservoir volume, fracture spacing, number of fractures, and flow requirements for a target reservoir power output. Limitations of the idealized model compared to actual reservoir performance and the implications on reservoir design are discussed.« less

Projecting changes in annual hydropower generation using regional runoff data: An assessment of the United States federal hydropower plants

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

Kao, Shih -Chieh; Sale, Michael J.; Ashfaq, Moetasim

Federal hydropower plants account for approximately half of installed US conventional hydropower capacity, and are an important part of the national renewable energy portfolio. Utilizing the strong linear relationship between the US Geological Survey WaterWatch runoff and annual hydropower generation, a runoff-based assessment approach is introduced in this study to project changes in annual and regional hydropower generation in multiple power marketing areas. Future climate scenarios are developed with a series of global and regional climate models, and the model output is bias-corrected to be consistent with observed data for the recent past. Using this approach, the median decrease inmore » annual generation at federal projects is projected to be less than –2 TWh, with an estimated ensemble uncertainty of ±9 TWh. Although these estimates are similar to the recently observed variability in annual hydropower generation, and may therefore appear to be manageable, significantly seasonal runoff changes are projected and it may pose significant challenges in water systems with higher limits on reservoir storage and operational flexibility. Lastly, future assessments will be improved by incorporating next-generation climate models, by closer examination of extreme events and longer-term change, and by addressing the interactions among hydropower and other water uses.« less

Projecting changes in annual hydropower generation using regional runoff data: An assessment of the United States federal hydropower plants

DOE PAGES

Kao, Shih -Chieh; Sale, Michael J.; Ashfaq, Moetasim; ...

2014-12-18

Federal hydropower plants account for approximately half of installed US conventional hydropower capacity, and are an important part of the national renewable energy portfolio. Utilizing the strong linear relationship between the US Geological Survey WaterWatch runoff and annual hydropower generation, a runoff-based assessment approach is introduced in this study to project changes in annual and regional hydropower generation in multiple power marketing areas. Future climate scenarios are developed with a series of global and regional climate models, and the model output is bias-corrected to be consistent with observed data for the recent past. Using this approach, the median decrease inmore » annual generation at federal projects is projected to be less than –2 TWh, with an estimated ensemble uncertainty of ±9 TWh. Although these estimates are similar to the recently observed variability in annual hydropower generation, and may therefore appear to be manageable, significantly seasonal runoff changes are projected and it may pose significant challenges in water systems with higher limits on reservoir storage and operational flexibility. Lastly, future assessments will be improved by incorporating next-generation climate models, by closer examination of extreme events and longer-term change, and by addressing the interactions among hydropower and other water uses.« less

Predicting fundamental and realized distributions based on thermal niche: A case study of a freshwater turtle

NASA Astrophysics Data System (ADS)

Rodrigues, João Fabrício Mota; Coelho, Marco Túlio Pacheco; Ribeiro, Bruno R.

2018-04-01

Species distribution models (SDM) have been broadly used in ecology to address theoretical and practical problems. Currently, there are two main approaches to generate SDMs: (i) correlative, which is based on species occurrences and environmental predictor layers and (ii) process-based models, which are constructed based on species' functional traits and physiological tolerances. The distributions estimated by each approach are based on different components of species niche. Predictions of correlative models approach species realized niches, while predictions of process-based are more akin to species fundamental niche. Here, we integrated the predictions of fundamental and realized distributions of the freshwater turtle Trachemys dorbigni. Fundamental distribution was estimated using data of T. dorbigni's egg incubation temperature, and realized distribution was estimated using species occurrence records. Both types of distributions were estimated using the same regression approaches (logistic regression and support vector machines), both considering macroclimatic and microclimatic temperatures. The realized distribution of T. dorbigni was generally nested in its fundamental distribution reinforcing theoretical assumptions that the species' realized niche is a subset of its fundamental niche. Both modelling algorithms produced similar results but microtemperature generated better results than macrotemperature for the incubation model. Finally, our results reinforce the conclusion that species realized distributions are constrained by other factors other than just thermal tolerances.

Aspects of Hydrological Modelling In The Punjab Himalayan and Karakoram Ranges, Pakistan

NASA Astrophysics Data System (ADS)

Loukas, A.; Khan, M. I.; Quick, M. C.

Various aspects of hydrologic modelling of high mountainous basins in the Punjab Hi- malayan and Karakoram ranges of Northern Pakistan were studied. The runoff from three basins in this region was simulated using the U.B.C. watershed model, which re- quires limited meteorological data of minimum and maximum daily temperature and precipitation. The structure of the model is based on the concept that the hydrolog- ical behavior is a function of elevation and thus, a watershed is conceptualized as a number of elevational zones. A simplified energy budget approach, which is based on daily maximum and minimum temperature and can account for forested and open areas, and aspect and latitude, is used in the U.B.C. model for the estimation of the snowmelt and glacier melt. The studied basins have different hydrological responses and limited data. The runoff from the first basin, the Astore basin, is mainly gener- ated by snowmelt. In the second basin, the Kunhar basin, the runoff is generated by snowmelt but significant redistribution of snow, caused by snow avalanches, affect the runoff generation. The third basin, the Hunza basin, is a highly glacierized basin and its runoff is mainly generated by glacier melt. The application of the U.B.C. watershed model to these three basins showed that the model could estimate reasonably well the runoff generated by the different components.

Small area estimation of proportions with different levels of auxiliary data.

PubMed

Chandra, Hukum; Kumar, Sushil; Aditya, Kaustav

2018-03-01

Binary data are often of interest in many small areas of applications. The use of standard small area estimation methods based on linear mixed models becomes problematic for such data. An empirical plug-in predictor (EPP) under a unit-level generalized linear mixed model with logit link function is often used for the estimation of a small area proportion. However, this EPP requires the availability of unit-level population information for auxiliary data that may not be always accessible. As a consequence, in many practical situations, this EPP approach cannot be applied. Based on the level of auxiliary information available, different small area predictors for estimation of proportions are proposed. Analytic and bootstrap approaches to estimating the mean squared error of the proposed small area predictors are also developed. Monte Carlo simulations based on both simulated and real data show that the proposed small area predictors work well for generating the small area estimates of proportions and represent a practical alternative to the above approach. The developed predictor is applied to generate estimates of the proportions of indebted farm households at district-level using debt investment survey data from India. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Partitioning Detectability Components in Populations Subject to Within-Season Temporary Emigration Using Binomial Mixture Models

PubMed Central

O’Donnell, Katherine M.; Thompson, Frank R.; Semlitsch, Raymond D.

2015-01-01

Detectability of individual animals is highly variable and nearly always < 1; imperfect detection must be accounted for to reliably estimate population sizes and trends. Hierarchical models can simultaneously estimate abundance and effective detection probability, but there are several different mechanisms that cause variation in detectability. Neglecting temporary emigration can lead to biased population estimates because availability and conditional detection probability are confounded. In this study, we extend previous hierarchical binomial mixture models to account for multiple sources of variation in detectability. The state process of the hierarchical model describes ecological mechanisms that generate spatial and temporal patterns in abundance, while the observation model accounts for the imperfect nature of counting individuals due to temporary emigration and false absences. We illustrate our model’s potential advantages, including the allowance of temporary emigration between sampling periods, with a case study of southern red-backed salamanders Plethodon serratus. We fit our model and a standard binomial mixture model to counts of terrestrial salamanders surveyed at 40 sites during 3–5 surveys each spring and fall 2010–2012. Our models generated similar parameter estimates to standard binomial mixture models. Aspect was the best predictor of salamander abundance in our case study; abundance increased as aspect became more northeasterly. Increased time-since-rainfall strongly decreased salamander surface activity (i.e. availability for sampling), while higher amounts of woody cover objects and rocks increased conditional detection probability (i.e. probability of capture, given an animal is exposed to sampling). By explicitly accounting for both components of detectability, we increased congruence between our statistical modeling and our ecological understanding of the system. We stress the importance of choosing survey locations and protocols that maximize species availability and conditional detection probability to increase population parameter estimate reliability. PMID:25775182

Effect of material constants on power output in piezoelectric vibration-based generators.

PubMed

Takeda, Hiroaki; Mihara, Kensuke; Yoshimura, Tomohiro; Hoshina, Takuya; Tsurumi, Takaaki

2011-09-01

A possible power output estimation based on material constants in piezoelectric vibration-based generators is proposed. A modified equivalent circuit model of the generator was built and was validated by the measurement results in the generator fabricated using potassium sodium niobate-based and lead zirconate titanate (PZT) ceramics. Subsequently, generators with the same structure using other PZT-based and bismuth-layered structure ferroelectrics ceramics were fabricated and tested. The power outputs of these generators were expressed as a linear functions of the term composed of electromechanical coupling coefficients k(sys)(2) and mechanical quality factors Q*(m) of the generator. The relationship between device constants (k(sys)(2) and Q*(m)) and material constants (k(31)(2) and Q(m)) was clarified. Estimation of the power output using material constants is demonstrated and the appropriate piezoelectric material for the generator is suggested.

TSARINA: A Computer Model for Assessing Conventional and Chemical Attacks on Airbases

DTIC Science & Technology

1990-09-01

IV, and has been updated to FORTRAN 77; it has been adapted to various computer systems, as was the widely used AIDA model and the previous versions of...conventional and chemical attacks on sortie generation. In the first version of TSARINA [1 2], several key additions were made to the AIDA model so that (1...various on-base resources, in addition to the estimates of hits and facility damage that are generated by the original AIDA model . The second version

Wind speed reductions by large-scale wind turbine deployments lower turbine efficiencies and set low generation limits.

PubMed

Miller, Lee M; Kleidon, Axel

2016-11-29

Wind turbines generate electricity by removing kinetic energy from the atmosphere. Large numbers of wind turbines are likely to reduce wind speeds, which lowers estimates of electricity generation from what would be presumed from unaffected conditions. Here, we test how well wind power limits that account for this effect can be estimated without explicitly simulating atmospheric dynamics. We first use simulations with an atmospheric general circulation model (GCM) that explicitly simulates the effects of wind turbines to derive wind power limits (GCM estimate), and compare them to a simple approach derived from the climatological conditions without turbines [vertical kinetic energy (VKE) estimate]. On land, we find strong agreement between the VKE and GCM estimates with respect to electricity generation rates (0.32 and 0.37 W e m -2 ) and wind speed reductions by 42 and 44%. Over ocean, the GCM estimate is about twice the VKE estimate (0.59 and 0.29 W e m -2 ) and yet with comparable wind speed reductions (50 and 42%). We then show that this bias can be corrected by modifying the downward momentum flux to the surface. Thus, large-scale limits to wind power use can be derived from climatological conditions without explicitly simulating atmospheric dynamics. Consistent with the GCM simulations, the approach estimates that only comparatively few land areas are suitable to generate more than 1 W e m -2 of electricity and that larger deployment scales are likely to reduce the expected electricity generation rate of each turbine. We conclude that these atmospheric effects are relevant for planning the future expansion of wind power.

Wind speed reductions by large-scale wind turbine deployments lower turbine efficiencies and set low generation limits

PubMed Central

Miller, Lee M.; Kleidon, Axel

2016-01-01

Wind turbines generate electricity by removing kinetic energy from the atmosphere. Large numbers of wind turbines are likely to reduce wind speeds, which lowers estimates of electricity generation from what would be presumed from unaffected conditions. Here, we test how well wind power limits that account for this effect can be estimated without explicitly simulating atmospheric dynamics. We first use simulations with an atmospheric general circulation model (GCM) that explicitly simulates the effects of wind turbines to derive wind power limits (GCM estimate), and compare them to a simple approach derived from the climatological conditions without turbines [vertical kinetic energy (VKE) estimate]. On land, we find strong agreement between the VKE and GCM estimates with respect to electricity generation rates (0.32 and 0.37 We m−2) and wind speed reductions by 42 and 44%. Over ocean, the GCM estimate is about twice the VKE estimate (0.59 and 0.29 We m−2) and yet with comparable wind speed reductions (50 and 42%). We then show that this bias can be corrected by modifying the downward momentum flux to the surface. Thus, large-scale limits to wind power use can be derived from climatological conditions without explicitly simulating atmospheric dynamics. Consistent with the GCM simulations, the approach estimates that only comparatively few land areas are suitable to generate more than 1 We m−2 of electricity and that larger deployment scales are likely to reduce the expected electricity generation rate of each turbine. We conclude that these atmospheric effects are relevant for planning the future expansion of wind power. PMID:27849587

Extended Kalman Filter framework for forecasting shoreline evolution

USGS Publications Warehouse

Long, Joseph; Plant, Nathaniel G.

2012-01-01

A shoreline change model incorporating both long- and short-term evolution is integrated into a data assimilation framework that uses sparse observations to generate an updated forecast of shoreline position and to estimate unobserved geophysical variables and model parameters. Application of the assimilation algorithm provides quantitative statistical estimates of combined model-data forecast uncertainty which is crucial for developing hazard vulnerability assessments, evaluation of prediction skill, and identifying future data collection needs. Significant attention is given to the estimation of four non-observable parameter values and separating two scales of shoreline evolution using only one observable morphological quantity (i.e. shoreline position).

Estimation of Aboveground Biomass Change for Tropical Deciduous Forest in Bago Yoma, Myanmar between year 2000 and 2014 using Landsat Images and Ground Measurements

NASA Astrophysics Data System (ADS)

Kim, H. S.; Wynn, K. Z.; Ryu, Y.

2015-12-01

Even with recently increased awareness of the environmental conservation, the degradation of tropical forests are still one of the major sources of global carbon emission. Especially in Myanmar, the pressure to develop natural forest is growing rapidly after the change from socialism to capitalism in 2010. As the initial step of the forest conservation, the aboveground biomass(AGB) of South Zarmani Reserved Forest in Bago Yoma region were estimated using Landsat 8 OLI after the evaluation with 100 sample plot measurements. Multiple linear regression (MLR) model of band values and their principal component analysis (PCA) model were developed to estimate the AGB using the spectral reflectance from Landsat images and elevation as the input variables. The MLR model had r2 = 0.43, RMSE = 60.2 tons/ha, relative RMSE = 70.1%, Bias = -9.1 tons/ha, Bias (%) = -10.6%, and p < 0.0001, while the PCA model showed r2 = 0.45, RMSE = 55.1 tons/ha, relative RMSE = 64.1%, Bias = -8.3 tons/ha, Bias (%) = -9.7%, and p < 0.0001. The AGB maps of the study area were generated based on both MLR and PCA models. The estimated mean AGB values were 74.74±22.3 tons/ha and 73.04±17.6 tons/ha and the total AGB of the study area are about 5.7 and 5.6 million tons from MLR and PCA, respectively. Then, Landsat 7 ETM+ image acquired on 2000 was also used to compare the changing of AGB between year 2000 and 2014. The estimated mean AGB value generated from the Landsat 7 ETM+ image was 78.9±16.9 tons/ha, which is substantially decreased about 7.5% compared to year 2014. The reduction of AGB increased with closeness to village, however AGB in distant areas showed steady increases. In conclusion, we were able to generate solid regression models from Landsat 8 OLI image after ground truth and two regression models gave us very similar AGB estimation (less than 2%) of the study area. We were also able to estimate the changing of AGB from year 2000 to 2014 of South Zarmani Reserved Forest, Bago Yoma, Myanmar.

Study of the back recombination processes of PbS quantum dots sensitized solar cells

NASA Astrophysics Data System (ADS)

Badawi, Ali; Al-Hosiny, N.; Merazga, Amar; Albaradi, Ateyyah M.; Abdallah, S.; Talaat, H.

2016-12-01

In this study, the back recombination processes of PbS quantum dots sensitized solar cells (QDSSCs) has been investigated. PbS QDs were adsorbed onto titania electrodes to act the role of sensitizers using successive ionic layer adsorption and reaction (SILAR) technique. The energy band gaps of the synthesized PbS QDs/titania are ranged from 1.64 eV (corresponding to 756 nm) to 3.12 eV (397 nm) matching the whole visible solar spectrum. The hyperbolic band model (HBM) was used to calculate PbS QDs size and it ranges from 1.76 to 3.44 nm. The photovoltaic parameters (open circuit voltage Voc, short circuit current density Jsc, fill factor FF and efficiency η) of the assembled PbS QDs sensitized solar cells (QDSSCs) were determined under a solar illumination of 100 mW/cm2 (AM 1.5 conditions). The open circuit voltage-decay (OCVD) rates of the assembled PbS QDSSCs were measured. The time constant (τ) for PbS QDSSCs (4 SILAR cycles) shows one order of magnitude larger than that of PbS QDSSCs (8 SILAR cycles) as a result of a decreased electron-hole back recombination.

Developing a Motion Comic for HIV/STD Prevention for Young People Ages 15-24, Part 1: Listening to Your Target Audience.

PubMed

Willis, Leigh A; Kachur, Rachel; Castellanos, Ted J; Spikes, Pilgrim; Gaul, Zaneta J; Gamayo, Ashley C; Durham, Marcus; Jones, Sandra; Nichols, Kristen; Han Barthelemy, Solange; LaPlace, Lisa; Staatz, Colleen; Hogben, Matthew; Robinson, Susan; Brooks, John T; Sutton, Madeline Y

2018-02-01

Young people (15-24 years) in the United States are disproportionately affected by infection with human immunodeficiency virus (HIV) and sexually transmitted diseases (STD). Shortfalls in HIV/STD-related knowledge, attitudes, beliefs, and behavioral intentions (KABI) likely contribute to this discrepancy. In this report we describe our experience developing a novel means of health communication combining entertainment-education theory and recent technological advances to create a HIV/STD-focused "motion comic." We also report the audience satisfaction and acceptance of the intervention. We used the Health Belief Model (HBM), entertainment-education (EE) principles, and the Sabido Method (SM) and conducted three rounds of focus groups to develop a 38-minute HIV/STD focused motion comic for young people between the ages 15 and 24 years. Participants indicated that motion comics were an acceptable method of delivering HIV/STD prevention messages. They also expressed satisfaction with motion comics plot, story settings, the tone of humor, and drama. Our results suggest that motion comics are a viable new method of delivering health communication messages about HIV/STD and other public health issues, and warrant further development and broader evaluation.

A forward model-based validation of cardiovascular system identification

NASA Technical Reports Server (NTRS)

Mukkamala, R.; Cohen, R. J.

2001-01-01

We present a theoretical evaluation of a cardiovascular system identification method that we previously developed for the analysis of beat-to-beat fluctuations in noninvasively measured heart rate, arterial blood pressure, and instantaneous lung volume. The method provides a dynamical characterization of the important autonomic and mechanical mechanisms responsible for coupling the fluctuations (inverse modeling). To carry out the evaluation, we developed a computational model of the cardiovascular system capable of generating realistic beat-to-beat variability (forward modeling). We applied the method to data generated from the forward model and compared the resulting estimated dynamics with the actual dynamics of the forward model, which were either precisely known or easily determined. We found that the estimated dynamics corresponded to the actual dynamics and that this correspondence was robust to forward model uncertainty. We also demonstrated the sensitivity of the method in detecting small changes in parameters characterizing autonomic function in the forward model. These results provide confidence in the performance of the cardiovascular system identification method when applied to experimental data.

Model for Increasing the Power Obtained from a Thermoelectric Generator Module

NASA Astrophysics Data System (ADS)

Huang, Gia-Yeh; Hsu, Cheng-Ting; Yao, Da-Jeng

2014-06-01

We have developed a model for finding the most efficient way of increasing the power obtained from a thermoelectric generator (TEG) module with a variety of operating conditions and limitations. The model is based on both thermoelectric principles and thermal resistance circuits, because a TEG converts heat into electricity consistent with these two theories. It is essential to take into account thermal contact resistance when estimating power generation. Thermal contact resistance causes overestimation of the measured temperature difference between the hot and cold sides of a TEG in calculation of the theoretical power generated, i.e. the theoretical power is larger than the experimental power. The ratio of the experimental open-loop voltage to the measured temperature difference, the effective Seebeck coefficient, can be used to estimate the thermal contact resistance in the model. The ratio of the effective Seebeck coefficient to the theoretical Seebeck coefficient, the Seebeck coefficient ratio, represents the contact conditions. From this ratio, a relationship between performance and different variables can be developed. The measured power generated by a TEG module (TMH400302055; Wise Life Technology, Taiwan) is consistent with the result obtained by use of the model; the relative deviation is 10%. Use of this model to evaluate the most efficient means of increasing the generated power reveals that the TEG module generates 0.14 W when the temperature difference is 25°C and the Seebeck coefficient ratio is 0.4. Several methods can be used triple the amount of power generated. For example, increasing the temperature difference to 43°C generates 0.41 W power; improving the Seebeck coefficient ratio to 0.65 increases the power to 0.39 W; simultaneously increasing the temperature difference to 34°C and improving the Seebeck coefficient ratio to 0.5 increases the power to 0.41 W. Choice of the appropriate method depends on the limitations of system, the cost, and the environment.

Prediction of spectral acceleration response ordinates based on PGA attenuation

USGS Publications Warehouse

Graizer, V.; Kalkan, E.

2009-01-01

Developed herein is a new peak ground acceleration (PGA)-based predictive model for 5% damped pseudospectral acceleration (SA) ordinates of free-field horizontal component of ground motion from shallow-crustal earthquakes. The predictive model of ground motion spectral shape (i.e., normalized spectrum) is generated as a continuous function of few parameters. The proposed model eliminates the classical exhausted matrix of estimator coefficients, and provides significant ease in its implementation. It is structured on the Next Generation Attenuation (NGA) database with a number of additions from recent Californian events including 2003 San Simeon and 2004 Parkfield earthquakes. A unique feature of the model is its new functional form explicitly integrating PGA as a scaling factor. The spectral shape model is parameterized within an approximation function using moment magnitude, closest distance to the fault (fault distance) and VS30 (average shear-wave velocity in the upper 30 m) as independent variables. Mean values of its estimator coefficients were computed by fitting an approximation function to spectral shape of each record using robust nonlinear optimization. Proposed spectral shape model is independent of the PGA attenuation, allowing utilization of various PGA attenuation relations to estimate the response spectrum of earthquake recordings.

When Can Categorical Variables Be Treated as Continuous? A Comparison of Robust Continuous and Categorical SEM Estimation Methods under Suboptimal Conditions

ERIC Educational Resources Information Center

Rhemtulla, Mijke; Brosseau-Liard, Patricia E.; Savalei, Victoria

2012-01-01

A simulation study compared the performance of robust normal theory maximum likelihood (ML) and robust categorical least squares (cat-LS) methodology for estimating confirmatory factor analysis models with ordinal variables. Data were generated from 2 models with 2-7 categories, 4 sample sizes, 2 latent distributions, and 5 patterns of category…

From discrete auroral arcs to the magnetospheric generator: numerical model and case study

NASA Astrophysics Data System (ADS)

Lamy, H.; Echim, M.; Cessateur, G.; Simon Wedlund, C.; Gustavsson, B.; Maggiolo, R.; Gunell, H.; Darrouzet, F.; De Keyser, J.

2017-12-01

We discuss an analysis method developed to estimate some of the properties of auroral generators (electron density, ne and temperature, Te), from ionospheric observations of the energy flux of precipitating electrons, e, measured across an auroral arc. The method makes use of a quasi-static magnetosphere-ionosphere coupling model. Assuming that the generator is a magnetospheric plasma interface, one obtains a parametric description of the generator electric field as a function of the kinetic and MHD properties of the interface. This description of the generator is introduced in a stationary M-I coupling model based on the current continuity in the topside ionosphere (Echim et al, 2007). The model is run iteratively for typical values of the magnetospheric ne and Te that are adjusted until the precipitating energy flux ɛ provided by the model at ionospheric altitudes fits the observations. The latter can be provided either in-situ by spacecraft measurements or remotely from optical ground-based observations. The method is illustrated by using the precipitating energy flux observed in-situ by DMSP on April 28, 2001, above a discrete auroral arc. For this particular date we have been able to compare the generator properties determined with our method with actual magnetospheric in-situ data provided by Cluster. The results compare very well and hence validate the method. The methodology is then applied on the energy flux of precipitating electrons estimated from optical images of a discrete auroral arc obtained simultaneously with the CCD cameras of the ALIS (Auroral Large Imaging System) network located in Scandinavia on 5 March 2008 (Simon Wedlund et al, 2013). Tomography-like techniques are used to retrieve the three-dimensional volume emission rates at 4278 Å from which the energy spectra of precipitating magnetospheric electrons can be further derived. These spectra are obtained along and across the arc, with a spatial resolution of approximately 3 km and provide E0, the characteristic energy and ɛ, the total flux energy of precipitating electrons. The generator properties are then estimated using the iterative technique validated with data from the DMSP-Cluster conjunction.

Accessing and constructing driving data to develop fuel consumption forecast model

NASA Astrophysics Data System (ADS)

Yamashita, Rei-Jo; Yao, Hsiu-Hsen; Hung, Shih-Wei; Hackman, Acquah

2018-02-01

In this study, we develop a forecasting models, to estimate fuel consumption based on the driving behavior, in which vehicles and routes are known. First, the driving data are collected via telematics and OBDII. Then, the driving fuel consumption formula is used to calculate the estimate fuel consumption, and driving behavior indicators are generated for analysis. Based on statistical analysis method, the driving fuel consumption forecasting model is constructed. Some field experiment results were done in this study to generate hundreds of driving behavior indicators. Based on data mining approach, the Pearson coefficient correlation analysis is used to filter highly fuel consumption related DBIs. Only highly correlated DBI will be used in the model. These DBIs are divided into four classes: speed class, acceleration class, Left/Right/U-turn class and the other category. We then use K-means cluster analysis to group to the driver class and the route class. Finally, more than 12 aggregate models are generated by those highly correlated DBIs, using the neural network model and regression analysis. Based on Mean Absolute Percentage Error (MAPE) to evaluate from the developed AMs. The best MAPE values among these AM is below 5%.

Sensitivity Analysis and Parameter Estimation for a Reactive Transport Model of Uranium Bioremediation

NASA Astrophysics Data System (ADS)

Meyer, P. D.; Yabusaki, S.; Curtis, G. P.; Ye, M.; Fang, Y.

2011-12-01

A three-dimensional, variably-saturated flow and multicomponent biogeochemical reactive transport model of uranium bioremediation was used to generate synthetic data . The 3-D model was based on a field experiment at the U.S. Dept. of Energy Rifle Integrated Field Research Challenge site that used acetate biostimulation of indigenous metal reducing bacteria to catalyze the conversion of aqueous uranium in the +6 oxidation state to immobile solid-associated uranium in the +4 oxidation state. A key assumption in past modeling studies at this site was that a comprehensive reaction network could be developed largely through one-dimensional modeling. Sensitivity analyses and parameter estimation were completed for a 1-D reactive transport model abstracted from the 3-D model to test this assumption, to identify parameters with the greatest potential to contribute to model predictive uncertainty, and to evaluate model structure and data limitations. Results showed that sensitivities of key biogeochemical concentrations varied in space and time, that model nonlinearities and/or parameter interactions have a significant impact on calculated sensitivities, and that the complexity of the model's representation of processes affecting Fe(II) in the system may make it difficult to correctly attribute observed Fe(II) behavior to modeled processes. Non-uniformity of the 3-D simulated groundwater flux and averaging of the 3-D synthetic data for use as calibration targets in the 1-D modeling resulted in systematic errors in the 1-D model parameter estimates and outputs. This occurred despite using the same reaction network for 1-D modeling as used in the data-generating 3-D model. Predictive uncertainty of the 1-D model appeared to be significantly underestimated by linear parameter uncertainty estimates.

Methods in Computational Cosmology

NASA Astrophysics Data System (ADS)

Vakili, Mohammadjavad

State of the inhomogeneous universe and its geometry throughout cosmic history can be studied by measuring the clustering of galaxies and the gravitational lensing of distant faint galaxies. Lensing and clustering measurements from large datasets provided by modern galaxy surveys will forever shape our understanding of the how the universe expands and how the structures grow. Interpretation of these rich datasets requires careful characterization of uncertainties at different stages of data analysis: estimation of the signal, estimation of the signal uncertainties, model predictions, and connecting the model to the signal through probabilistic means. In this thesis, we attempt to address some aspects of these challenges. The first step in cosmological weak lensing analyses is accurate estimation of the distortion of the light profiles of galaxies by large scale structure. These small distortions, known as the cosmic shear signal, are dominated by extra distortions due to telescope optics and atmosphere (in the case of ground-based imaging). This effect is captured by a kernel known as the Point Spread Function (PSF) that needs to be fully estimated and corrected for. We address two challenges a head of accurate PSF modeling for weak lensing studies. The first challenge is finding the centers of point sources that are used for empirical estimation of the PSF. We show that the approximate methods for centroiding stars in wide surveys are able to optimally saturate the information content that is retrievable from astronomical images in the presence of noise. The fist step in weak lensing studies is estimating the shear signal by accurately measuring the shapes of galaxies. Galaxy shape measurement involves modeling the light profile of galaxies convolved with the light profile of the PSF. Detectors of many space-based telescopes such as the Hubble Space Telescope (HST) sample the PSF with low resolution. Reliable weak lensing analysis of galaxies observed by the HST camera requires knowledge of the PSF at a resolution higher than the pixel resolution of HST. This PSF is called the super-resolution PSF. In particular, we present a forward model of the point sources imaged through filters of the HST WFC3 IR channel. We show that this forward model can accurately estimate the super-resolution PSF. We also introduce a noise model that permits us to robustly analyze the HST WFC3 IR observations of the crowded fields. Then we try to address one of the theoretical uncertainties in modeling of galaxy clustering on small scales. Study of small scale clustering requires assuming a halo model. Clustering of halos has been shown to depend on halo properties beyond mass such as halo concentration, a phenomenon referred to as assembly bias. Standard large-scale structure studies with halo occupation distribution (HOD) assume that halo mass alone is sufficient to characterize the connection between galaxies and halos. However, assembly bias could cause the modeling of galaxy clustering to face systematic effects if the expected number of galaxies in halos is correlated with other halo properties. Using high resolution N-body simulations and the clustering measurements of Sloan Digital Sky Survey (SDSS) DR7 main galaxy sample, we show that modeling of galaxy clustering can slightly improve if we allow the HOD model to depend on halo properties beyond mass. One of the key ingredients in precise parameter inference using galaxy clustering is accurate estimation of the error covariance matrix of clustering measurements. This requires generation of many independent galaxy mock catalogs that accurately describe the statistical distribution of galaxies in a wide range of physical scales. We present a fast and accurate method based on low-resolution N-body simulations and an empirical bias model for generating mock catalogs. We use fast particle mesh gravity solvers for generation of dark matter density field and we use Markov Chain Monti Carlo (MCMC) to estimate the bias model that connects dark matter to galaxies. We show that this approach enables the fast generation of mock catalogs that recover clustering at a percent-level accuracy down to quasi-nonlinear scales. Cosmological datasets are interpreted by specifying likelihood functions that are often assumed to be multivariate Gaussian. Likelihood free approaches such as Approximate Bayesian Computation (ABC) can bypass this assumption by introducing a generative forward model of the data and a distance metric for quantifying the closeness of the data and the model. We present the first application of ABC in large scale structure for constraining the connections between galaxies and dark matter halos. We present an implementation of ABC equipped with Population Monte Carlo and a generative forward model of the data that incorporates sample variance and systematic uncertainties. (Abstract shortened by ProQuest.).

Use of LANDSAT 8 images for depth and water quality assessment of El Guájaro reservoir, Colombia

NASA Astrophysics Data System (ADS)

González-Márquez, Luis Carlos; Torres-Bejarano, Franklin M.; Torregroza-Espinosa, Ana Carolina; Hansen-Rodríguez, Ivette Renée; Rodríguez-Gallegos, Hugo B.

2018-03-01

The aim of this study was to evaluate the viability of using Landsat 8 spectral images to estimate water quality parameters and depth in El Guájaro Reservoir. On February and March 2015, two samplings were carried out in the reservoir, coinciding with the Landsat 8 images. Turbidity, dissolved oxygen, electrical conductivity, pH and depth were evaluated. Through multiple regression analysis between measured water quality parameters and the reflectance of the pixels corresponding to the sampling stations, statistical models with determination coefficients between 0.6249 and 0.9300 were generated. Results indicate that from a small number of measured parameters we can generate reliable models to estimate the spatial variation of turbidity, dissolved oxygen, pH and depth, as well the temporal variation of electrical conductivity, so models generated from Landsat 8 can be used as a tool to facilitate the environmental, economic and social management of the reservoir.

Human Migration Patterns in Yemen and Implications for Reconstructing Prehistoric Population Movements

PubMed Central

Miró-Herrans, Aida T.; Al-Meeri, Ali; Mulligan, Connie J.

2014-01-01

Population migration has played an important role in human evolutionary history and in the patterning of human genetic variation. A deeper and empirically-based understanding of human migration dynamics is needed in order to interpret genetic and archaeological evidence and to accurately reconstruct the prehistoric processes that comprise human evolutionary history. Current empirical estimates of migration include either short time frames (i.e. within one generation) or partial knowledge about migration, such as proportion of migrants or distance of migration. An analysis of migration that includes both proportion of migrants and distance, and direction over multiple generations would better inform prehistoric reconstructions. To evaluate human migration, we use GPS coordinates from the place of residence of the Yemeni individuals sampled in our study, their birthplaces and their parents' and grandparents' birthplaces to calculate the proportion of migrants, as well as the distance and direction of migration events between each generation. We test for differences in these values between the generations and identify factors that influence the probability of migration. Our results show that the proportion and distance of migration between females and males is similar within generations. In contrast, the proportion and distance of migration is significantly lower in the grandparents' generation, most likely reflecting the decreasing effect of technology. Based on our results, we calculate the proportion of migration events (0.102) and mean and median distances of migration (96 km and 26 km) for the grandparent's generation to represent early times in human evolution. These estimates can serve to set parameter values of demographic models in model-based methods of prehistoric reconstruction, such as approximate Bayesian computation. Our study provides the first empirically-based estimates of human migration over multiple generations in a developing country and these estimates are intended to enable more precise reconstruction of the demographic processes that characterized human evolution. PMID:24759992

A coupled weather generator - rainfall-runoff approach on hourly time steps for flood risk analysis

NASA Astrophysics Data System (ADS)

Winter, Benjamin; Schneeberger, Klaus; Dung Nguyen, Viet; Vorogushyn, Sergiy; Huttenlau, Matthias; Merz, Bruno; Stötter, Johann

2017-04-01

The evaluation of potential monetary damage of flooding is an essential part of flood risk management. One possibility to estimate the monetary risk is to analyze long time series of observed flood events and their corresponding damages. In reality, however, only few flood events are documented. This limitation can be overcome by the generation of a set of synthetic, physically and spatial plausible flood events and subsequently the estimation of the resulting monetary damages. In the present work, a set of synthetic flood events is generated by a continuous rainfall-runoff simulation in combination with a coupled weather generator and temporal disaggregation procedure for the study area of Vorarlberg (Austria). Most flood risk studies focus on daily time steps, however, the mesoscale alpine study area is characterized by short concentration times, leading to large differences between daily mean and daily maximum discharge. Accordingly, an hourly time step is needed for the simulations. The hourly metrological input for the rainfall-runoff model is generated in a two-step approach. A synthetic daily dataset is generated by a multivariate and multisite weather generator and subsequently disaggregated to hourly time steps with a k-Nearest-Neighbor model. Following the event generation procedure, the negative consequences of flooding are analyzed. The corresponding flood damage for each synthetic event is estimated by combining the synthetic discharge at representative points of the river network with a loss probability relation for each community in the study area. The loss probability relation is based on exposure and susceptibility analyses on a single object basis (residential buildings) for certain return periods. For these impact analyses official inundation maps of the study area are used. Finally, by analyzing the total event time series of damages, the expected annual damage or losses associated with a certain probability of occurrence can be estimated for the entire study area.

CONTROL FUNCTION ASSISTED IPW ESTIMATION WITH A SECONDARY OUTCOME IN CASE-CONTROL STUDIES.

PubMed

Sofer, Tamar; Cornelis, Marilyn C; Kraft, Peter; Tchetgen Tchetgen, Eric J

2017-04-01

Case-control studies are designed towards studying associations between risk factors and a single, primary outcome. Information about additional, secondary outcomes is also collected, but association studies targeting such secondary outcomes should account for the case-control sampling scheme, or otherwise results may be biased. Often, one uses inverse probability weighted (IPW) estimators to estimate population effects in such studies. IPW estimators are robust, as they only require correct specification of the mean regression model of the secondary outcome on covariates, and knowledge of the disease prevalence. However, IPW estimators are inefficient relative to estimators that make additional assumptions about the data generating mechanism. We propose a class of estimators for the effect of risk factors on a secondary outcome in case-control studies that combine IPW with an additional modeling assumption: specification of the disease outcome probability model. We incorporate this model via a mean zero control function. We derive the class of all regular and asymptotically linear estimators corresponding to our modeling assumption, when the secondary outcome mean is modeled using either the identity or the log link. We find the efficient estimator in our class of estimators and show that it reduces to standard IPW when the model for the primary disease outcome is unrestricted, and is more efficient than standard IPW when the model is either parametric or semiparametric.

Transient Stability Output Margin Estimation Based on Energy Function Method

NASA Astrophysics Data System (ADS)

Miwa, Natsuki; Tanaka, Kazuyuki

In this paper, a new method of estimating critical generation margin (CGM) in power systems is proposed from the viewpoint of transient stability diagnostic. The proposed method has the capability to directly compute the stability limit output for a given contingency based on transient energy function method (TEF). Since CGM can be directly obtained by the limit output using estimated P-θ curves and is easy to understand, it is more useful rather than conventional critical clearing time (CCT) of energy function method. The proposed method can also estimate CGM as its negative value that means unstable in present load profile, then negative CGM can be directly utilized as generator output restriction. The proposed method is verified its accuracy and fast solution ability by applying to simple 3-machine model and IEEJ EAST10-machine standard model. Furthermore the useful application to severity ranking of transient stability for a lot of contingency cases is discussed by using CGM.

An extensible framework for capturing solvent effects in computer generated kinetic models.

PubMed

Jalan, Amrit; West, Richard H; Green, William H

2013-03-14

Detailed kinetic models provide useful mechanistic insight into a chemical system. Manual construction of such models is laborious and error-prone, which has led to the development of automated methods for exploring chemical pathways. These methods rely on fast, high-throughput estimation of species thermochemistry and kinetic parameters. In this paper, we present a methodology for extending automatic mechanism generation to solution phase systems which requires estimation of solvent effects on reaction rates and equilibria. The linear solvation energy relationship (LSER) method of Abraham and co-workers is combined with Mintz correlations to estimate ΔG(solv)°(T) in over 30 solvents using solute descriptors estimated from group additivity. Simple corrections are found to be adequate for the treatment of radical sites, as suggested by comparison with known experimental data. The performance of scaled particle theory expressions for enthalpic-entropic decomposition of ΔG(solv)°(T) is also presented along with the associated computational issues. Similar high-throughput methods for solvent effects on free-radical kinetics are only available for a handful of reactions due to lack of reliable experimental data, and continuum dielectric calculations offer an alternative method for their estimation. For illustration, we model liquid phase oxidation of tetralin in different solvents computing the solvent dependence for ROO• + ROO• and ROO• + solvent reactions using polarizable continuum quantum chemistry methods. The resulting kinetic models show an increase in oxidation rate with solvent polarity, consistent with experiment. Further work needed to make this approach more generally useful is outlined.

Developing tolled-route demand estimation capabilities for Texas : opportunities for enhancement of existing models.

DOT National Transportation Integrated Search

2014-08-01

The travel demand models developed and applied by the Transportation Planning and Programming Division : (TPP) of the Texas Department of Transportation (TxDOT) are daily three-step models (i.e., trip generation, trip : distribution, and traffic assi...

Future projection of design storms using a GCM-informed weather generator

NASA Astrophysics Data System (ADS)

KIm, T. W.; Wi, S.; Valdés-Pineda, R.; Valdés, J. B.

2017-12-01

The rainfall Intensity-Duration-Frequency (IDF) curves are one of the most common tools used to provide planners with a description of the frequency of extreme rainfall events of various intensities and durations. Therefore deriving appropriate IDF estimates is important to avoid malfunctions of water structures that cause huge damage. Evaluating IDF estimates in the context of climate change has become more important because projections from climate models suggest that the frequency of intense rainfall events will increase in the future due to the increase in greenhouse gas emissions. In this study, the Bartlett-Lewis (BL) stochastic rainfall model is employed to generate annual maximum series of various sub-daily durations for test basins of the Model Parameter Estimation Experiment (MOPEX) project, and to derive the IDF curves in the context of climate changes projected by the North American Regional Climate Change (NARCCAP) models. From our results, it has been found that the observed annual rainfall maximum series is reasonably represented by the synthetic annual maximum series generated by the BL model. The observed data is perturbed by change factors to incorporate the NARCCAP climate change scenarios into the IDF estimates. The future IDF curves show a significant difference from the historical IDF curves calculated for the period 1968-2000. Overall, the projected IDF curves show an increasing trend over time. The impacts of changes in extreme rainfall on the hydrologic response of the MOPEX basins are also explored. Acknowledgement: This research was supported by a grant [MPSS-NH-2015-79] through the Disaster and Safety Management Institute funded by Ministry of Public Safety and Security of Korean government.

A performance model for GPUs with caches

DOE PAGES

Dao, Thanh Tuan; Kim, Jungwon; Seo, Sangmin; ...

2014-06-24

To exploit the abundant computational power of the world's fastest supercomputers, an even workload distribution to the typically heterogeneous compute devices is necessary. While relatively accurate performance models exist for conventional CPUs, accurate performance estimation models for modern GPUs do not exist. This paper presents two accurate models for modern GPUs: a sampling-based linear model, and a model based on machine-learning (ML) techniques which improves the accuracy of the linear model and is applicable to modern GPUs with and without caches. We first construct the sampling-based linear model to predict the runtime of an arbitrary OpenCL kernel. Based on anmore » analysis of NVIDIA GPUs' scheduling policies we determine the earliest sampling points that allow an accurate estimation. The linear model cannot capture well the significant effects that memory coalescing or caching as implemented in modern GPUs have on performance. We therefore propose a model based on ML techniques that takes several compiler-generated statistics about the kernel as well as the GPU's hardware performance counters as additional inputs to obtain a more accurate runtime performance estimation for modern GPUs. We demonstrate the effectiveness and broad applicability of the model by applying it to three different NVIDIA GPU architectures and one AMD GPU architecture. On an extensive set of OpenCL benchmarks, on average, the proposed model estimates the runtime performance with less than 7 percent error for a second-generation GTX 280 with no on-chip caches and less than 5 percent for the Fermi-based GTX 580 with hardware caches. On the Kepler-based GTX 680, the linear model has an error of less than 10 percent. On an AMD GPU architecture, Radeon HD 6970, the model estimates with 8 percent of error rates. As a result, the proposed technique outperforms existing models by a factor of 5 to 6 in terms of accuracy.« less

Forecasting extinction risk with nonstationary matrix models.

PubMed

Gotelli, Nicholas J; Ellison, Aaron M

2006-02-01

Matrix population growth models are standard tools for forecasting population change and for managing rare species, but they are less useful for predicting extinction risk in the face of changing environmental conditions. Deterministic models provide point estimates of lambda, the finite rate of increase, as well as measures of matrix sensitivity and elasticity. Stationary matrix models can be used to estimate extinction risk in a variable environment, but they assume that the matrix elements are randomly sampled from a stationary (i.e., non-changing) distribution. Here we outline a method for using nonstationary matrix models to construct realistic forecasts of population fluctuation in changing environments. Our method requires three pieces of data: (1) field estimates of transition matrix elements, (2) experimental data on the demographic responses of populations to altered environmental conditions, and (3) forecasting data on environmental drivers. These three pieces of data are combined to generate a series of sequential transition matrices that emulate a pattern of long-term change in environmental drivers. Realistic estimates of population persistence and extinction risk can be derived from stochastic permutations of such a model. We illustrate the steps of this analysis with data from two populations of Sarracenia purpurea growing in northern New England. Sarracenia purpurea is a perennial carnivorous plant that is potentially at risk of local extinction because of increased nitrogen deposition. Long-term monitoring records or models of environmental change can be used to generate time series of driver variables under different scenarios of changing environments. Both manipulative and natural experiments can be used to construct a linking function that describes how matrix parameters change as a function of the environmental driver. This synthetic modeling approach provides quantitative estimates of extinction probability that have an explicit mechanistic basis.

Contribution of different generations of the brown shrimp Crangon crangon (L.) in the Dutch Wadden Sea to commercial fisheries: A dynamic energy budget approach

NASA Astrophysics Data System (ADS)

Campos, Joana; Van der Veer, Henk W.; Freitas, Vânia; Kooijman, Sebastiaan A. L. M.

2009-08-01

In this paper a contribution is made to the ongoing debate on which brown shrimp generation mostly sustains the autumn peak in coastal North Sea commercial fisheries: the generation born in summer, or the winter one. Since the two perspectives are based on different considerations on the growth timeframe from settlement till commercial size, the Dynamic Energy Budget (DEB) theory was applied to predict maximum possible growth under natural conditions. First, the parameters of the standard DEB model for Crangon crangon L. were estimated using available data sets. These were insufficient to allow a direct estimation, requiring a special protocol to achieve consistency between parameters. Next, the DEB model was validated by comparing simulations with published experimental data on shrimp growth in relation to water temperatures. Finally, the DEB model was applied to simulate growth under optimal food conditions using the prevailing water temperature conditions in the Wadden Sea. Results show clear differences between males and females whereby the fastest growth rates were observed in females. DEB model simulations of maximum growth in the Wadden Sea suggest that it is not the summer brood from the current year as Boddeke claimed, nor the previous winter generation as Kuipers and Dapper suggested, but more likely the summer generation from the previous year which contributes to the bulk of the fisheries recruits in autumn.

Stochastic Generation of Monthly Rainfall Data

NASA Astrophysics Data System (ADS)

Srikanthan, R.

2009-03-01

Monthly rainfall data is generally needed in the simulation of water resources systems, and in the estimation of water yield from large catchments. Monthly streamflow data generation models are usually applied to generate monthly rainfall data, but this presents problems for most regions, which have significant months of no rainfall. In an earlier study, Srikanthan et al. (J. Hydrol. Eng., ASCE 11(3) (2006) 222-229) recommended the modified method of fragments to disaggregate the annual rainfall data generated by a first-order autoregressive model. The main drawback of this approach is the occurrence of similar patterns when only a short length of historic data is available. Porter and Pink (Hydrol. Water Res. Symp. (1991) 187-191) used synthetic fragments from a Thomas-Fiering monthly model to overcome this drawback. As an alternative, a new two-part monthly model is nested in an annual model to generate monthly rainfall data which preserves both the monthly and annual characteristics. This nested model was applied to generate rainfall data from seven rainfall stations located in eastern and southern parts of Australia, and the results showed that the model performed satisfactorily.

An Improved Analysis of Forest Carbon Dynamics using Data Assimilation

NASA Technical Reports Server (NTRS)

Williams, Mathew; Schwarz, Paul A.; Law, Beverly E.; Kurpius, Meredith R.

2005-01-01

There are two broad approaches to quantifying landscape C dynamics - by measuring changes in C stocks over time, or by measuring fluxes of C directly. However, these data may be patchy, and have gaps or biases. An alternative approach to generating C budgets has been to use process-based models, constructed to simulate the key processes involved in C exchange. However, the process of model building is arguably subjective, and parameters may be poorly defined. This paper demonstrates why data assimilation (DA) techniques - which combine stock and flux observations with a dynamic model - improve estimates of, and provide insights into, ecosystem carbon (C) exchanges. We use an ensemble Kalman filter (EnKF) to link a series of measurements with a simple box model of C transformations. Measurements were collected at a young ponderosa pine stand in central Oregon over a 3-year period, and include eddy flux and soil C02 efflux data, litterfall collections, stem surveys, root and soil cores, and leaf area index data. The simple C model is a mass balance model with nine unknown parameters, tracking changes in C storage among five pools; foliar, wood and fine root pools in vegetation, and also fresh litter and soil organic matter (SOM) plus coarse woody debris pools. We nested the EnKF within an optimization routine to generate estimates from the data of the unknown parameters and the five initial conditions for the pools. The efficacy of the DA process can be judged by comparing the probability distributions of estimates produced with the EnKF analysis vs. those produced with reduced data or model alone. Using the model alone, estimated net ecosystem exchange of C (NEE)= -251 f 197g Cm-2 over the 3 years, compared with an estimate of -419 f 29gCm-2 when all observations were assimilated into the model. The uncertainty on daily measurements of NEE via eddy fluxes was estimated at 0.5gCm-2 day-1, but the uncertainty on assimilated estimates averaged 0.47 g Cm-2 day-1, and only exceeded 0.5gC m-2 day-1 on days where neither eddy flux nor soil efflux data were available. In generating C budgets, the assimilation process reduced the uncertainties associated with using data or model alone and the forecasts of NEE were statistically unbiased estimates. The results of the analysis emphasize the importance of time series as constraints. Occasional, rare measurements of stocks have limited use in constraining the estimates of other components of the C cycle. Long time series are particularly crucial for improving the analysis of pools with long time constants, such as SOM, woody biomass, and woody debris. Long-running forest stem surveys, and tree ring data, offer a rich resource that could be assimilated to provide an important constraint on C cycling of slow pools. For extending estimates of NEE across regions, DA can play a further important role, by assimilating remote-sensing data into the analysis of C cycles. We show, via sensitivity analysis, how assimilating an estimate of photosynthesis - which might be provided indirectly by remotely sensed data - improves the analysis of NEE.

Implementation of an Integrated On-Board Aircraft Engine Diagnostic Architecture

NASA Technical Reports Server (NTRS)

Armstrong, Jeffrey B.; Simon, Donald L.

2012-01-01

An on-board diagnostic architecture for aircraft turbofan engine performance trending, parameter estimation, and gas-path fault detection and isolation has been developed and evaluated in a simulation environment. The architecture incorporates two independent models: a realtime self-tuning performance model providing parameter estimates and a performance baseline model for diagnostic purposes reflecting long-term engine degradation trends. This architecture was evaluated using flight profiles generated from a nonlinear model with realistic fleet engine health degradation distributions and sensor noise. The architecture was found to produce acceptable estimates of engine health and unmeasured parameters, and the integrated diagnostic algorithms were able to perform correct fault isolation in approximately 70 percent of the tested cases

Valuation of preference-based measures: can existing preference data be used to generate better estimates?

PubMed

Kharroubi, Samer A

2018-06-05

Experimental studies to develop valuations of health state descriptive systems like EQ-5D or SF-6D need to be conducted in different countries, because social and cultural differences are likely to lead to systematically different valuations. There is a scope utilize the evidence in one country to help with the design and the analysis of a study in another, for this to enable the generation of utility estimates of the second country much more precisely than would have been possible when collecting and analyzing the country's data alone. We analyze SF-6D valuation data elicited from representative samples corresponding to the Hong Kong (HK) and United Kingdom (UK) general adult populations through the use of the standard gamble technique to value 197 and 249 health states respectively. We apply a nonparametric Bayesian model to estimate a HK value set using the UK dataset as informative prior to improve its estimation. Estimates are compared to a HK value set estimated using HK values alone using mean predictions and root mean square error. The novel method of modelling utility functions permitted the UK valuations to contribute significant prior information to the Hong Kong analysis. The results suggest that using HK data alongside the existing UK data produces HK utility estimates better than using the HK study data by itself. The promising results suggest that existing preference data could be combined with valuation study in a new country to generate preference weights, making own country value sets more achievable for low and middle income countries. Further research is encouraged.

APPLICATION OF TRAVEL TIME RELIABILITY FOR PERFORMANCE ORIENTED OPERATIONAL PLANNING OF EXPRESSWAYS

NASA Astrophysics Data System (ADS)

Mehran, Babak; Nakamura, Hideki

Evaluation of impacts of congestion improvement scheme s on travel time reliability is very significant for road authorities since travel time reliability repr esents operational performance of expressway segments. In this paper, a methodology is presented to estimate travel tim e reliability prior to implementation of congestion relief schemes based on travel time variation modeling as a function of demand, capacity, weather conditions and road accident s. For subject expressway segmen ts, traffic conditions are modeled over a whole year considering demand and capacity as random variables. Patterns of demand and capacity are generated for each five minute interval by appl ying Monte-Carlo simulation technique, and accidents are randomly generated based on a model that links acci dent rate to traffic conditions. A whole year analysis is performed by comparing de mand and available capacity for each scenario and queue length is estimated through shockwave analysis for each time in terval. Travel times are estimated from refined speed-flow relationships developed for intercity expressways and buffer time index is estimated consequently as a measure of travel time reliability. For validation, estimated reliability indices are compared with measured values from empirical data, and it is shown that the proposed method is suitable for operational evaluation and planning purposes.

Multivariate statistical approach to estimate mixing proportions for unknown end members

USGS Publications Warehouse

Valder, Joshua F.; Long, Andrew J.; Davis, Arden D.; Kenner, Scott J.

2012-01-01

A multivariate statistical method is presented, which includes principal components analysis (PCA) and an end-member mixing model to estimate unknown end-member hydrochemical compositions and the relative mixing proportions of those end members in mixed waters. PCA, together with the Hotelling T2 statistic and a conceptual model of groundwater flow and mixing, was used in selecting samples that best approximate end members, which then were used as initial values in optimization of the end-member mixing model. This method was tested on controlled datasets (i.e., true values of estimates were known a priori) and found effective in estimating these end members and mixing proportions. The controlled datasets included synthetically generated hydrochemical data, synthetically generated mixing proportions, and laboratory analyses of sample mixtures, which were used in an evaluation of the effectiveness of this method for potential use in actual hydrological settings. For three different scenarios tested, correlation coefficients (R2) for linear regression between the estimated and known values ranged from 0.968 to 0.993 for mixing proportions and from 0.839 to 0.998 for end-member compositions. The method also was applied to field data from a study of end-member mixing in groundwater as a field example and partial method validation.

Estimation of vegetative mercury emissions in China.

PubMed

Quan, Jiannong; Zhang, Xiaoshan; Shim, Shang Gyoo

2008-01-01

Vegetative mercury emissions were estimated within the framework of Biogenic Emission Inventory System (BEIS3 V3.11). In this estimation, the 19 categories of U.S. Geological Survey landcover data were incorporated to generate the vegetation-specific mercury emissions in a 81-km Lambert Conformal model grid covering the total Chinese continent. The surface temperature and cloud-corrected solar radiation from a Mesoscale Meteorological model (MM5) were retrieved and used for calculating the diurnal variation. The implemented emission factors were either evaluated from the measured mercury flux data for forest, agriculture and water, or assumed for other land fields without available flux data. Annual simulations using the MM5 data were performed to investigate the seasonal emission variation. From the sensitivity analysis using two sets of emission factors, the vegetative mercury emissions in China domain were estimated to range from a lower limit of 79 x 10(3) kg/year to an upper limit of 177 x 10(3) kg/year. The modeled vegetative emissions were mainly generated from the eastern and southern China. Using the estimated data, it is shown that mercury emissions from vegetation are comparable to that from anthropogenic sources during summer. However, the vegetative emissions decrease greatly during winter, leaving anthropogenic sources as the major sources of emission.

Multi-Scale Soil Moisture Monitoring and Modeling at ARS Watersheds for NASA's Soil Moisture Active Passive (SMAP) Calibration/Validation Mission

NASA Astrophysics Data System (ADS)

Coopersmith, E. J.; Cosh, M. H.

2014-12-01

NASA's SMAP satellite, launched in November of 2014, produces estimates of average volumetric soil moisture at 3, 9, and 36-kilometer scales. The calibration and validation process of these estimates requires the generation of an identically-scaled soil moisture product from existing in-situ networks. This can be achieved via the integration of NLDAS precipitation data to perform calibration of models at each ­in-situ gauge. In turn, these models and the gauges' volumetric estimations are used to generate soil moisture estimates at a 500m scale throughout a given test watershed by leveraging, at each location, the gauge-calibrated models deemed most appropriate in terms of proximity, calibration efficacy, soil-textural similarity, and topography. Four ARS watersheds, located in Iowa, Oklahoma, Georgia, and Arizona are employed to demonstrate the utility of this approach. The South Fork watershed in Iowa represents the simplest case - the soil textures and topography are relative constants and the variability of soil moisture is simply tied to the spatial variability of precipitation. The Little Washita watershed in Oklahoma adds soil textural variability (but remains topographically simple), while the Little River watershed in Georgia incorporates topographic classification. Finally, the Walnut Gulch watershed in Arizona adds a dense precipitation network to be employed for even finer-scale modeling estimates. Results suggest RMSE values at or below the 4% volumetric standard adopted for the SMAP mission are attainable over the desired spatial scales via this integration of modeling efforts and existing in-situ networks.

Interpreting JEDI Results | Jobs and Economic Development Impact Models |

Science.gov Websites

NREL Interpreting JEDI Results Interpreting JEDI Results The Jobs and Economic Development Impact (JEDI) models estimate the number of jobs and economic impacts associated with power generation Economic activity in input-output models is typically assessed in three categories. NREL's JEDI models

Estimating municipal solid waste generation by different activities and various resident groups: a case study of Beijing.

PubMed

Li, Zhen-shan; Fu, Hui-zhen; Qu, Xiao-yan

2011-09-15

Reliable and accurate determinations of the quantities and composition of wastes is required for the planning of municipal solid waste (MSW) management systems. A model, based on the interrelationships of expenditure on consumer goods, time distribution, daily activities, residents groups, and waste generation, was developed and employed to estimate MSW generation by different activities and resident groups in Beijing. The principle is that MSW is produced by consumption of consumer goods by residents in their daily activities: 'Maintenance' (meeting the basic needs of food, housing and personal care), 'Subsistence' (providing the financial requirements) and 'Leisure' (social and recreational pursuits) activities. Three series of important parameters - waste generation per unit of consumer expenditure, consumer expenditure distribution to activities in unit time, and time assignment to activities by different resident groups - were determined using a statistical analysis, a sampling survey and the Analytic Hierarchy Process, respectively. Data for analysis were obtained from the Beijing Statistical Yearbook (2004-2008) and questionnaire survey. The results reveal that 'Maintenance' activity produced the most MSW, distantly followed by 'Leisure' and 'Subsistence' activities. In 2008, in descending order of MSW generation the different resident groups were floating population, non-civil servants, retired people, civil servants, college students (including both undergraduates and graduates), primary and secondary students, and preschoolers. The new estimation model, which was successful in fitting waste generation by different activities and resident groups over the investigated years, was amenable to MSW prediction. Copyright © 2011 Elsevier B.V. All rights reserved.

Automatic Aircraft Structural Topology Generation for Multidisciplinary Optimization and Weight Estimation

NASA Technical Reports Server (NTRS)

Sensmeier, Mark D.; Samareh, Jamshid A.

2005-01-01

An approach is proposed for the application of rapid generation of moderate-fidelity structural finite element models of air vehicle structures to allow more accurate weight estimation earlier in the vehicle design process. This should help to rapidly assess many structural layouts before the start of the preliminary design phase and eliminate weight penalties imposed when actual structure weights exceed those estimated during conceptual design. By defining the structural topology in a fully parametric manner, the structure can be mapped to arbitrary vehicle configurations being considered during conceptual design optimization. A demonstration of this process is shown for two sample aircraft wing designs.

`Inverse Crime' and Model Integrity in Lightcurve Inversion applied to unresolved Space Object Identification

NASA Astrophysics Data System (ADS)

Henderson, Laura S.; Subbarao, Kamesh

2017-12-01

This work presents a case wherein the selection of models when producing synthetic light curves affects the estimation of the size of unresolved space objects. Through this case, "inverse crime" (using the same model for the generation of synthetic data and data inversion), is illustrated. This is done by using two models to produce the synthetic light curve and later invert it. It is shown here that the choice of model indeed affects the estimation of the shape/size parameters. When a higher fidelity model (henceforth the one that results in the smallest error residuals after the crime is committed) is used to both create, and invert the light curve model the estimates of the shape/size parameters are significantly better than those obtained when a lower fidelity model (in comparison) is implemented for the estimation. It is therefore of utmost importance to consider the choice of models when producing synthetic data, which later will be inverted, as the results might be misleadingly optimistic.

A Variance Distribution Model of Surface EMG Signals Based on Inverse Gamma Distribution.

PubMed

Hayashi, Hideaki; Furui, Akira; Kurita, Yuichi; Tsuji, Toshio

2017-11-01

Objective: This paper describes the formulation of a surface electromyogram (EMG) model capable of representing the variance distribution of EMG signals. Methods: In the model, EMG signals are handled based on a Gaussian white noise process with a mean of zero for each variance value. EMG signal variance is taken as a random variable that follows inverse gamma distribution, allowing the representation of noise superimposed onto this variance. Variance distribution estimation based on marginal likelihood maximization is also outlined in this paper. The procedure can be approximated using rectified and smoothed EMG signals, thereby allowing the determination of distribution parameters in real time at low computational cost. Results: A simulation experiment was performed to evaluate the accuracy of distribution estimation using artificially generated EMG signals, with results demonstrating that the proposed model's accuracy is higher than that of maximum-likelihood-based estimation. Analysis of variance distribution using real EMG data also suggested a relationship between variance distribution and signal-dependent noise. Conclusion: The study reported here was conducted to examine the performance of a proposed surface EMG model capable of representing variance distribution and a related distribution parameter estimation method. Experiments using artificial and real EMG data demonstrated the validity of the model. Significance: Variance distribution estimated using the proposed model exhibits potential in the estimation of muscle force. Objective: This paper describes the formulation of a surface electromyogram (EMG) model capable of representing the variance distribution of EMG signals. Methods: In the model, EMG signals are handled based on a Gaussian white noise process with a mean of zero for each variance value. EMG signal variance is taken as a random variable that follows inverse gamma distribution, allowing the representation of noise superimposed onto this variance. Variance distribution estimation based on marginal likelihood maximization is also outlined in this paper. The procedure can be approximated using rectified and smoothed EMG signals, thereby allowing the determination of distribution parameters in real time at low computational cost. Results: A simulation experiment was performed to evaluate the accuracy of distribution estimation using artificially generated EMG signals, with results demonstrating that the proposed model's accuracy is higher than that of maximum-likelihood-based estimation. Analysis of variance distribution using real EMG data also suggested a relationship between variance distribution and signal-dependent noise. Conclusion: The study reported here was conducted to examine the performance of a proposed surface EMG model capable of representing variance distribution and a related distribution parameter estimation method. Experiments using artificial and real EMG data demonstrated the validity of the model. Significance: Variance distribution estimated using the proposed model exhibits potential in the estimation of muscle force.

Assessment of Wind Resource in the Palk Strait using Different Methods

NASA Astrophysics Data System (ADS)

Gupta, T.; Khan, F.; Baidya Roy, S.; Miller, L.

2017-12-01

The Government of India has proposed a target of 60 GW in grid power from the wind by the year 2022. The Palk Strait is one of the potential offshore wind power generation sites in India. It is a 65-135 km wide and 135 km long channel lying between the south eastern tip of India and northern Sri Lanka. The complex terrain bounding the two sides of the strait leads to enhanced wind speed and reduced variability in the wind direction. Here, we compare 3 distinct methodologies for estimating the generation rates for a hypothetical offshore wind farm array located in the strait. The methodologies include: 1) traditional wind power density model that ignores the effect of turbine interactions on generation rates; 2) the PARK wake model; and 3) a high resolution weather model (WRF) with a wind turbine parameterization. Using the WRF model as our baseline, we find that the simple model overestimates generation by an order-of-magnitude, while the wake model underestimates generation rates by about 5%. The reason for these differences relates to the influence of wind turbines on the atmospheric flow, wherein, the WRF model is able to capture the effect of both the complex terrain and wind turbine atmospheric boundary layer interactions. Lastly, a model evaluation is conducted which shows that 10m wind speeds and directions from WRF are comparable with the satellite data. Hence, we conclude from the study that each of these methodologies may have merit, but should a wind farm is deployed in such a complex terrain, we expect the WRF method to give better estimates of wind resource assessment capturing the physical processes emerging due to the interactions between offshore wind farm and the surrounding terrain.

Observations and modelling of a meteotsunami across the English Channel on 23rd June 2016

NASA Astrophysics Data System (ADS)

Williams, David; Horsburgh, Kevin; Schultz, David; Hughes, Chris

2017-04-01

Meteotsunami are shallow water waves in the tsunami frequency band, which are generated by sub-mesoscale pressure and wind velocity fluctuations. Whilst documented meteotsunami on the north-western European shelf have not been hazardous, around the world they have caused fatalities and significant economic losses. Previous observational studies suggest that across Western Europe strongly convective storms are meteotsunami-generating. We give evidence for a meteotsunami on 23rd June 2016 along the northern coastline of France, following strongly convective storms. This includes 1-minute temporal resolution tide gauge data, in situ pressure and wind velocities, and infrared satellite images. With an estimated wave height of 0.8 m at Boulogne, this meteotsunami is particularly large compared to previous observations in Western Europe. The tsunami travel times have been estimated using the wavefront method, showing that a single, instantaneous source for the waves is highly unlikely. Using the ocean model Telemac2D, idealised models of pressure and wind have been used to simulate the meteotsunami. The model supports that across the English Channel thunderstorms with north-easterly tracks, moving at the shallow water wave speed, can generate wave amplification through Proudman resonance. The Weather Research and Forecasting (WRF) model has been used to produce numerically simulated thunderstorms, which have been used to force the Telemac2D ocean model with idealised bathymetries. The WRF-Telemac2D model results also support meteotsunami generation by thunderstorms. To the author's knowledge this is the first time a thunderstorm simulation has been used to produce a meteotsunami-like wave, and indicates that non-hydrostatic, convective atmospheric processes are important for meteotsunami generation. This suggests that with combined high resolution observations and modelling, a meteotsunami forecasting system may become possible in Western Europe.

Creating an anthropomorphic digital MR phantom—an extensible tool for comparing and evaluating quantitative imaging algorithms

NASA Astrophysics Data System (ADS)

Bosca, Ryan J.; Jackson, Edward F.

2016-01-01

Assessing and mitigating the various sources of bias and variance associated with image quantification algorithms is essential to the use of such algorithms in clinical research and practice. Assessment is usually accomplished with grid-based digital reference objects (DRO) or, more recently, digital anthropomorphic phantoms based on normal human anatomy. Publicly available digital anthropomorphic phantoms can provide a basis for generating realistic model-based DROs that incorporate the heterogeneity commonly found in pathology. Using a publicly available vascular input function (VIF) and digital anthropomorphic phantom of a normal human brain, a methodology was developed to generate a DRO based on the general kinetic model (GKM) that represented realistic and heterogeneously enhancing pathology. GKM parameters were estimated from a deidentified clinical dynamic contrast-enhanced (DCE) MRI exam. This clinical imaging volume was co-registered with a discrete tissue model, and model parameters estimated from clinical images were used to synthesize a DCE-MRI exam that consisted of normal brain tissues and a heterogeneously enhancing brain tumor. An example application of spatial smoothing was used to illustrate potential applications in assessing quantitative imaging algorithms. A voxel-wise Bland-Altman analysis demonstrated negligible differences between the parameters estimated with and without spatial smoothing (using a small radius Gaussian kernel). In this work, we reported an extensible methodology for generating model-based anthropomorphic DROs containing normal and pathological tissue that can be used to assess quantitative imaging algorithms.

JEDI Wind Models | Jobs and Economic Development Impact Models | NREL

Science.gov Websites

Wind Models JEDI Wind Models The Jobs and Economic Development Impacts (JEDI) Wind model allows the user to estimate economic development impacts from wind power generation projects. JEDI Wind has default information that can be used to run a generic impacts analysis assuming wind industry averages

Commercial Demand Module - NEMS Documentation

EIA Publications

2017-01-01

Documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Commercial Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated through the synthesis and scenario development based on these components.

Improved Parameter-Estimation With MRI-Constrained PET Kinetic Modeling: A Simulation Study

NASA Astrophysics Data System (ADS)

Erlandsson, Kjell; Liljeroth, Maria; Atkinson, David; Arridge, Simon; Ourselin, Sebastien; Hutton, Brian F.

2016-10-01

Kinetic analysis can be applied both to dynamic PET and dynamic contrast enhanced (DCE) MRI data. We have investigated the potential of MRI-constrained PET kinetic modeling using simulated [ 18F]2-FDG data for skeletal muscle. The volume of distribution, Ve, for the extra-vascular extra-cellular space (EES) is the link between the two models: It can be estimated by DCE-MRI, and then used to reduce the number of parameters to estimate in the PET model. We used a 3 tissue-compartment model with 5 rate constants (3TC5k), in order to distinguish between EES and the intra-cellular space (ICS). Time-activity curves were generated by simulation using the 3TC5k model for 3 different Ve values under basal and insulin stimulated conditions. Noise was added and the data were fitted with the 2TC3k model and with the 3TC5k model with and without Ve constraint. One hundred noise-realisations were generated at 4 different noise-levels. The results showed reductions in bias and variance with Ve constraint in the 3TC5k model. We calculated the parameter k3", representing the combined effect of glucose transport across the cellular membrane and phosphorylation, as an extra outcome measure. For k3", the average coefficient of variation was reduced from 52% to 9.7%, while for k3 in the standard 2TC3k model it was 3.4%. The accuracy of the parameters estimated with our new modeling approach depends on the accuracy of the assumed Ve value. In conclusion, we have shown that, by utilising information that could be obtained from DCE-MRI in the kinetic analysis of [ 18F]2-FDG-PET data, it is in principle possible to obtain better parameter estimates with a more complex model, which may provide additional information as compared to the standard model.

Lunar PMAD technology assessment

NASA Technical Reports Server (NTRS)

Metcalf, Kenneth J.

1992-01-01

This report documents an initial set of power conditioning models created to generate 'ballpark' power management and distribution (PMAD) component mass and size estimates. It contains converter, rectifier, inverter, transformer, remote bus isolator (RBI), and remote power controller (RPC) models. These models allow certain studies to be performed; however, additional models are required to assess a full range of PMAD alternatives. The intent is to eventually form a library of PMAD models that will allow system designers to evaluate various power system architectures and distribution techniques quickly and consistently. The models in this report are designed primarily for space exploration initiative (SEI) missions requiring continuous power and supporting manned operations. The mass estimates were developed by identifying the stages in a component and obtaining mass breakdowns for these stages from near term electronic hardware elements. Technology advances were then incorporated to generate hardware masses consistent with the 2000 to 2010 time period. The mass of a complete component is computed by algorithms that calculate the masses of the component stages, control and monitoring, enclosure, and thermal management subsystem.

Enhancing e-waste estimates: improving data quality by multivariate Input-Output Analysis.

PubMed

Wang, Feng; Huisman, Jaco; Stevels, Ab; Baldé, Cornelis Peter

2013-11-01

Waste electrical and electronic equipment (or e-waste) is one of the fastest growing waste streams, which encompasses a wide and increasing spectrum of products. Accurate estimation of e-waste generation is difficult, mainly due to lack of high quality data referred to market and socio-economic dynamics. This paper addresses how to enhance e-waste estimates by providing techniques to increase data quality. An advanced, flexible and multivariate Input-Output Analysis (IOA) method is proposed. It links all three pillars in IOA (product sales, stock and lifespan profiles) to construct mathematical relationships between various data points. By applying this method, the data consolidation steps can generate more accurate time-series datasets from available data pool. This can consequently increase the reliability of e-waste estimates compared to the approach without data processing. A case study in the Netherlands is used to apply the advanced IOA model. As a result, for the first time ever, complete datasets of all three variables for estimating all types of e-waste have been obtained. The result of this study also demonstrates significant disparity between various estimation models, arising from the use of data under different conditions. It shows the importance of applying multivariate approach and multiple sources to improve data quality for modelling, specifically using appropriate time-varying lifespan parameters. Following the case study, a roadmap with a procedural guideline is provided to enhance e-waste estimation studies. Copyright © 2013 Elsevier Ltd. All rights reserved.

A Bayes linear Bayes method for estimation of correlated event rates.

PubMed

Quigley, John; Wilson, Kevin J; Walls, Lesley; Bedford, Tim

2013-12-01

Typically, full Bayesian estimation of correlated event rates can be computationally challenging since estimators are intractable. When estimation of event rates represents one activity within a larger modeling process, there is an incentive to develop more efficient inference than provided by a full Bayesian model. We develop a new subjective inference method for correlated event rates based on a Bayes linear Bayes model under the assumption that events are generated from a homogeneous Poisson process. To reduce the elicitation burden we introduce homogenization factors to the model and, as an alternative to a subjective prior, an empirical method using the method of moments is developed. Inference under the new method is compared against estimates obtained under a full Bayesian model, which takes a multivariate gamma prior, where the predictive and posterior distributions are derived in terms of well-known functions. The mathematical properties of both models are presented. A simulation study shows that the Bayes linear Bayes inference method and the full Bayesian model provide equally reliable estimates. An illustrative example, motivated by a problem of estimating correlated event rates across different users in a simple supply chain, shows how ignoring the correlation leads to biased estimation of event rates. © 2013 Society for Risk Analysis.

Incorporating GIS building data and census housing statistics for sub-block-level population estimation

USGS Publications Warehouse

Wu, S.-S.; Wang, L.; Qiu, X.

2008-01-01

This article presents a deterministic model for sub-block-level population estimation based on the total building volumes derived from geographic information system (GIS) building data and three census block-level housing statistics. To assess the model, we generated artificial blocks by aggregating census block areas and calculating the respective housing statistics. We then applied the model to estimate populations for sub-artificial-block areas and assessed the estimates with census populations of the areas. Our analyses indicate that the average percent error of population estimation for sub-artificial-block areas is comparable to those for sub-census-block areas of the same size relative to associated blocks. The smaller the sub-block-level areas, the higher the population estimation errors. For example, the average percent error for residential areas is approximately 0.11 percent for 100 percent block areas and 35 percent for 5 percent block areas.

Pose estimation of teeth through crown-shape matching

NASA Astrophysics Data System (ADS)

Mok, Vevin; Ong, Sim Heng; Foong, Kelvin W. C.; Kondo, Toshiaki

2002-05-01

This paper presents a technique for determining a tooth's pose given a dental plaster cast and a set of generic tooth models. The ultimate goal of pose estimation is to obtain information about the sizes and positions of the roots, which lie hidden within the gums, without the use of X-rays, CT or MRI. In our approach, the tooth of interest is first extracted from the 3D dental cast image through segmentation. 2D views are then generated from the extracted tooth and are matched against a target view generated from the generic model with known pose. Additional views are generated in the vicinity of the best view and the entire process is repeated until convergence. Upon convergence, the generic tooth is superimposed onto the dental cast to show the position of the root. The results of applying the technique to canines demonstrate the excellent potential of the algorithm for generic tooth fitting.

Photovoltaic-Model-Based Solar Irradiance Estimators: Performance Comparison and Application to Maximum Power Forecasting

NASA Astrophysics Data System (ADS)

Scolari, Enrica; Sossan, Fabrizio; Paolone, Mario

2018-01-01

Due to the increasing proportion of distributed photovoltaic (PV) production in the generation mix, the knowledge of the PV generation capacity has become a key factor. In this work, we propose to compute the PV plant maximum power starting from the indirectly-estimated irradiance. Three estimators are compared in terms of i) ability to compute the PV plant maximum power, ii) bandwidth and iii) robustness against measurements noise. The approaches rely on measurements of the DC voltage, current, and cell temperature and on a model of the PV array. We show that the considered methods can accurately reconstruct the PV maximum generation even during curtailment periods, i.e. when the measured PV power is not representative of the maximum potential of the PV array. Performance evaluation is carried out by using a dedicated experimental setup on a 14.3 kWp rooftop PV installation. Results also proved that the analyzed methods can outperform pyranometer-based estimations, with a less complex sensing system. We show how the obtained PV maximum power values can be applied to train time series-based solar maximum power forecasting techniques. This is beneficial when the measured power values, commonly used as training, are not representative of the maximum PV potential.

Potential effects of climate change on ground water in Lansing, Michigan

USGS Publications Warehouse

Croley, T.E.; Luukkonen, C.L.

2003-01-01

Computer simulations involving general circulation models, a hydrologic modeling system, and a ground water flow model indicate potential impacts of selected climate change projections on ground water levels in the Lansing, Michigan, area. General circulation models developed by the Canadian Climate Centre and the Hadley Centre generated meteorology estimates for 1961 through 1990 (as a reference condition) and for the 20 years centered on 2030 (as a changed climate condition). Using these meteorology estimates, the Great Lakes Environmental Research Laboratory's hydrologic modeling system produced corresponding period streamflow simulations. Ground water recharge was estimated from the streamflow simulations and from variables derived from the general circulation models. The U.S. Geological Survey developed a numerical ground water flow model of the Saginaw and glacial aquifers in the Tri-County region surrounding Lansing, Michigan. Model simulations, using the ground water recharge estimates, indicate changes in ground water levels. Within the Lansing area, simulated ground water levels in the Saginaw aquifer declined under the Canadian predictions and increased under the Hadley.

Recent Progress on the Second Generation CMORPH: A Prototype Operational Processing System

NASA Astrophysics Data System (ADS)

Xie, Pingping; Joyce, Robert; Wu, Shaorong

2016-04-01

As reported at the EGU General Assembly of 2015, a conceptual test system was developed for the second generation CMORPH to produce global analyses of 30-min precipitation on a 0.05deg lat/lon grid over the entire globe from pole to pole through integration of information from satellite observations as well as numerical model simulations. The second generation CMORPH is built upon the Kalman Filter based CMORPH algorithm of Joyce and Xie (2011). Inputs to the system include both rainfall and snowfall rate retrievals from passive microwave (PMW) measurements aboard all available low earth orbit (LEO) satellites, precipitation estimates derived from infrared (IR) observations of geostationary (GEO) as well as LEO platforms, and precipitation simulations from numerical global models. Sub-systems were developed and refined to derive precipitation estimates from the GEO and LEO IR observations and to compute precipitating cloud motion vectors. The results were reported at the EGU of 2014 and the AGU 2015 Fall Meetings. In this presentation, we report our recent work on the construction of a prototype operational processing system for the second generation CMORPH. The second generation CMORPH prototype operational processing system takes in the passive microwave (PMW) retrievals of instantaneous precipitation rates from all available sensors, the full-resolution GEO and LEO IR data, as well as the hourly precipitation fields generated by the NOAA/NCEP Climate Forecast System (CFS) Reanalysis (CFS). First, a combined field of PMW based precipitation retrievals (MWCOMB) is created on a 0.05deg lat/lon grid over the entire globe through inter-calibrating retrievals from various sensors against a common reference. For this experiment, the reference field is the GMI based retrievals with climatological adjustment against the TMI retrievals using data over the overlapping period. Precipitation estimation is then derived from the GEO and LEO IR data through calibration against the global MWCOMB and the CloudSat CPR based estimates. At the meantime, precipitating cloud motion vectors are derived through the combination of vectors computed from the GEO IR based precipitation estimates and the CFSR precipitation with a 2DVAR technique. A prototype system is applied to generate integrated global precipitation estimates over the entire globe for a three-month period from June 1 to August 31 of 2015. Preliminary tests are conducted to optimize the performance of the system. Specific efforts are made to improve the computational efficiency of the system. The second generation CMORPH test products are compared to the first generation CMORPH and ground observations. Detailed results will be reported at the EGU.

Evaluation of the Webler-Brown model for estimating tetrachloroethylene exposure from vinyl-lined asbestos-cement pipes

PubMed Central

Spence, Lisa A; Aschengrau, Ann; Gallagher, Lisa E; Webster, Thomas F; Heeren, Timothy C; Ozonoff, David M

2008-01-01

Background From May 1968 through March 1980, vinyl-lined asbestos-cement (VL/AC) water distribution pipes were installed in New England to avoid taste and odor problems associated with asbestos-cement pipes. The vinyl resin was applied to the inner pipe surface in a solution of tetrachloroethylene (perchloroethylene, PCE). Substantial amounts of PCE remained in the liner and subsequently leached into public drinking water supplies. Methods Once aware of the leaching problem and prior to remediation (April-November 1980), Massachusetts regulators collected drinking water samples from VL/AC pipes to determine the extent and severity of the PCE contamination. This study compares newly obtained historical records of PCE concentrations in water samples (n = 88) with concentrations estimated using an exposure model employed in epidemiologic studies on the cancer risk associated with PCE-contaminated drinking water. The exposure model was developed by Webler and Brown to estimate the mass of PCE delivered to subjects' residences. Results The mean and median measured PCE concentrations in the water samples were 66 and 0.5 μg/L, respectively, and the range extended from non-detectable to 2432 μg/L. The model-generated concentration estimates and water sample concentrations were moderately correlated (Spearman rank correlation coefficient = 0.48, p < 0.0001). Correlations were higher in samples taken at taps and spigots vs. hydrants (ρ = 0.84 vs. 0.34), in areas with simple vs. complex geometry (ρ = 0.51 vs. 0.38), and near pipes installed in 1973–1976 vs. other years (ρ = 0.56 vs. 0.42 for 1968–1972 and 0.37 for 1977–1980). Overall, 24% of the variance in measured PCE concentrations was explained by the model-generated concentration estimates (p < 0.0001). Almost half of the water samples had undetectable concentrations of PCE. Undetectable levels were more common in areas with the earliest installed VL/AC pipes, at the beginning and middle of VL/AC pipes, at hydrants, and in complex pipe configurations. Conclusion PCE concentration estimates generated using the Webler-Brown model were moderately correlated with measured water concentrations. The present analysis suggests that the exposure assessment process used in prior epidemiological studies could be improved with more accurate characterization of water flow. This study illustrates one method of validating an exposure model in an epidemiological study when historical measurements are not available. PMID:18518975

Evaluation of the Webler-Brown model for estimating tetrachloroethylene exposure from vinyl-lined asbestos-cement pipes.

PubMed

Spence, Lisa A; Aschengrau, Ann; Gallagher, Lisa E; Webster, Thomas F; Heeren, Timothy C; Ozonoff, David M

2008-06-02

From May 1968 through March 1980, vinyl-lined asbestos-cement (VL/AC) water distribution pipes were installed in New England to avoid taste and odor problems associated with asbestos-cement pipes. The vinyl resin was applied to the inner pipe surface in a solution of tetrachloroethylene (perchloroethylene, PCE). Substantial amounts of PCE remained in the liner and subsequently leached into public drinking water supplies. Once aware of the leaching problem and prior to remediation (April-November 1980), Massachusetts regulators collected drinking water samples from VL/AC pipes to determine the extent and severity of the PCE contamination. This study compares newly obtained historical records of PCE concentrations in water samples (n = 88) with concentrations estimated using an exposure model employed in epidemiologic studies on the cancer risk associated with PCE-contaminated drinking water. The exposure model was developed by Webler and Brown to estimate the mass of PCE delivered to subjects' residences. The mean and median measured PCE concentrations in the water samples were 66 and 0.5 microg/L, respectively, and the range extended from non-detectable to 2432 microg/L. The model-generated concentration estimates and water sample concentrations were moderately correlated (Spearman rank correlation coefficient = 0.48, p < 0.0001). Correlations were higher in samples taken at taps and spigots vs. hydrants (rho = 0.84 vs. 0.34), in areas with simple vs. complex geometry (rho = 0.51 vs. 0.38), and near pipes installed in 1973-1976 vs. other years (rho = 0.56 vs. 0.42 for 1968-1972 and 0.37 for 1977-1980). Overall, 24% of the variance in measured PCE concentrations was explained by the model-generated concentration estimates (p < 0.0001). Almost half of the water samples had undetectable concentrations of PCE. Undetectable levels were more common in areas with the earliest installed VL/AC pipes, at the beginning and middle of VL/AC pipes, at hydrants, and in complex pipe configurations. PCE concentration estimates generated using the Webler-Brown model were moderately correlated with measured water concentrations. The present analysis suggests that the exposure assessment process used in prior epidemiological studies could be improved with more accurate characterization of water flow. This study illustrates one method of validating an exposure model in an epidemiological study when historical measurements are not available.

Real-time hydraulic interval state estimation for water transport networks: a case study

NASA Astrophysics Data System (ADS)

Vrachimis, Stelios G.; Eliades, Demetrios G.; Polycarpou, Marios M.

2018-03-01

Hydraulic state estimation in water distribution networks is the task of estimating water flows and pressures in the pipes and nodes of the network based on some sensor measurements. This requires a model of the network as well as knowledge of demand outflow and tank water levels. Due to modeling and measurement uncertainty, standard state estimation may result in inaccurate hydraulic estimates without any measure of the estimation error. This paper describes a methodology for generating hydraulic state bounding estimates based on interval bounds on the parametric and measurement uncertainties. The estimation error bounds provided by this method can be applied to determine the existence of unaccounted-for water in water distribution networks. As a case study, the method is applied to a modified transport network in Cyprus, using actual data in real time.

Intracranial EEG potentials estimated from MEG sources: A new approach to correlate MEG and iEEG data in epilepsy.

PubMed

Grova, Christophe; Aiguabella, Maria; Zelmann, Rina; Lina, Jean-Marc; Hall, Jeffery A; Kobayashi, Eliane

2016-05-01

Detection of epileptic spikes in MagnetoEncephaloGraphy (MEG) requires synchronized neuronal activity over a minimum of 4cm2. We previously validated the Maximum Entropy on the Mean (MEM) as a source localization able to recover the spatial extent of the epileptic spike generators. The purpose of this study was to evaluate quantitatively, using intracranial EEG (iEEG), the spatial extent recovered from MEG sources by estimating iEEG potentials generated by these MEG sources. We evaluated five patients with focal epilepsy who had a pre-operative MEG acquisition and iEEG with MRI-compatible electrodes. Individual MEG epileptic spikes were localized along the cortical surface segmented from a pre-operative MRI, which was co-registered with the MRI obtained with iEEG electrodes in place for identification of iEEG contacts. An iEEG forward model estimated the influence of every dipolar source of the cortical surface on each iEEG contact. This iEEG forward model was applied to MEG sources to estimate iEEG potentials that would have been generated by these sources. MEG-estimated iEEG potentials were compared with measured iEEG potentials using four source localization methods: two variants of MEM and two standard methods equivalent to minimum norm and LORETA estimates. Our results demonstrated an excellent MEG/iEEG correspondence in the presumed focus for four out of five patients. In one patient, the deep generator identified in iEEG could not be localized in MEG. MEG-estimated iEEG potentials is a promising method to evaluate which MEG sources could be retrieved and validated with iEEG data, providing accurate results especially when applied to MEM localizations. Hum Brain Mapp 37:1661-1683, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Planning additional drilling campaign using two-space genetic algorithm: A game theoretical approach

NASA Astrophysics Data System (ADS)

Kumral, Mustafa; Ozer, Umit

2013-03-01

Grade and tonnage are the most important technical uncertainties in mining ventures because of the use of estimations/simulations, which are mostly generated from drill data. Open pit mines are planned and designed on the basis of the blocks representing the entire orebody. Each block has different estimation/simulation variance reflecting uncertainty to some extent. The estimation/simulation realizations are submitted to mine production scheduling process. However, the use of a block model with varying estimation/simulation variances will lead to serious risk in the scheduling. In the medium of multiple simulations, the dispersion variances of blocks can be thought to regard technical uncertainties. However, the dispersion variance cannot handle uncertainty associated with varying estimation/simulation variances of blocks. This paper proposes an approach that generates the configuration of the best additional drilling campaign to generate more homogenous estimation/simulation variances of blocks. In other words, the objective is to find the best drilling configuration in such a way as to minimize grade uncertainty under budget constraint. Uncertainty measure of the optimization process in this paper is interpolation variance, which considers data locations and grades. The problem is expressed as a minmax problem, which focuses on finding the best worst-case performance i.e., minimizing interpolation variance of the block generating maximum interpolation variance. Since the optimization model requires computing the interpolation variances of blocks being simulated/estimated in each iteration, the problem cannot be solved by standard optimization tools. This motivates to use two-space genetic algorithm (GA) approach to solve the problem. The technique has two spaces: feasible drill hole configuration with minimization of interpolation variance and drill hole simulations with maximization of interpolation variance. Two-space interacts to find a minmax solution iteratively. A case study was conducted to demonstrate the performance of approach. The findings showed that the approach could be used to plan a new drilling campaign.

Runoff load estimation of particulate and dissolved nitrogen in Lake Inba watershed using continuous monitoring data on turbidity and electric conductivity.

PubMed

Kim, J; Nagano, Y; Furumai, H

2012-01-01

Easy-to-measure surrogate parameters for water quality indicators are needed for real time monitoring as well as for generating data for model calibration and validation. In this study, a novel linear regression model for estimating total nitrogen (TN) based on two surrogate parameters is proposed based on evaluation of pollutant loads flowing into a eutrophic lake. Based on their runoff characteristics during wet weather, electric conductivity (EC) and turbidity were selected as surrogates for particulate nitrogen (PN) and dissolved nitrogen (DN), respectively. Strong linear relationships were established between PN and turbidity and DN and EC, and both models subsequently combined for estimation of TN. This model was evaluated by comparison of estimated and observed TN runoff loads during rainfall events. This analysis showed that turbidity and EC are viable surrogates for PN and DN, respectively, and that the linear regression model for TN concentration was successful in estimating TN runoff loads during rainfall events and also under dry weather conditions.

Uncertainty estimation of long-range ensemble forecasts of snowmelt flood characteristics

NASA Astrophysics Data System (ADS)

Kuchment, L.

2012-04-01

Long-range forecasts of snowmelt flood characteristics with the lead time of 2-3 months have important significance for regulation of flood runoff and mitigation of flood damages at almost all large Russian rivers At the same time, the application of current forecasting techniques based on regression relationships between the runoff volume and the indexes of river basin conditions can lead to serious errors in forecasting resulted in large economic losses caused by wrong flood regulation. The forecast errors can be caused by complicated processes of soil freezing and soil moisture redistribution, too high rate of snow melt, large liquid precipitation before snow melt. or by large difference of meteorological conditions during the lead-time periods from climatologic ones. Analysis of economic losses had shown that the largest damages could, to a significant extent, be avoided if the decision makers had an opportunity to take into account predictive uncertainty and could use more cautious strategies in runoff regulation. Development of methodology of long-range ensemble forecasting of spring/summer floods which is based on distributed physically-based runoff generation models has created, in principle, a new basis for improving hydrological predictions as well as for estimating their uncertainty. This approach is illustrated by forecasting of the spring-summer floods at the Vyatka River and the Seim River basins. The application of the physically - based models of snowmelt runoff generation give a essential improving of statistical estimates of the deterministic forecasts of the flood volume in comparison with the forecasts obtained from the regression relationships. These models had been used also for the probabilistic forecasts assigning meteorological inputs during lead time periods from the available historical daily series, and from the series simulated by using a weather generator and the Monte Carlo procedure. The weather generator consists of the stochastic models of daily temperature and precipitation. The performance of the probabilistic forecasts were estimated by the ranked probability skill scores. The application of Monte Carlo simulations using weather generator has given better results then using the historical meteorological series.

Monte Carlo Approach for Reliability Estimations in Generalizability Studies.

ERIC Educational Resources Information Center

Dimitrov, Dimiter M.

A Monte Carlo approach is proposed, using the Statistical Analysis System (SAS) programming language, for estimating reliability coefficients in generalizability theory studies. Test scores are generated by a probabilistic model that considers the probability for a person with a given ability score to answer an item with a given difficulty…

Analytical flow duration curves for summer streamflow in Switzerland

NASA Astrophysics Data System (ADS)

Santos, Ana Clara; Portela, Maria Manuela; Rinaldo, Andrea; Schaefli, Bettina

2018-04-01

This paper proposes a systematic assessment of the performance of an analytical modeling framework for streamflow probability distributions for a set of 25 Swiss catchments. These catchments show a wide range of hydroclimatic regimes, including namely snow-influenced streamflows. The model parameters are calculated from a spatially averaged gridded daily precipitation data set and from observed daily discharge time series, both in a forward estimation mode (direct parameter calculation from observed data) and in an inverse estimation mode (maximum likelihood estimation). The performance of the linear and the nonlinear model versions is assessed in terms of reproducing observed flow duration curves and their natural variability. Overall, the nonlinear model version outperforms the linear model for all regimes, but the linear model shows a notable performance increase with catchment elevation. More importantly, the obtained results demonstrate that the analytical model performs well for summer discharge for all analyzed streamflow regimes, ranging from rainfall-driven regimes with summer low flow to snow and glacier regimes with summer high flow. These results suggest that the model's encoding of discharge-generating events based on stochastic soil moisture dynamics is more flexible than previously thought. As shown in this paper, the presence of snowmelt or ice melt is accommodated by a relative increase in the discharge-generating frequency, a key parameter of the model. Explicit quantification of this frequency increase as a function of mean catchment meteorological conditions is left for future research.

Development of a Trip Energy Estimation Model Using Real-World Global Positioning System Driving Data: Preprint

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

Holden, Jacob; Wood, Eric W; Zhu, Lei

A data-driven technique for estimation of energy requirements for a proposed vehicle trip has been developed. Based on over 700,000 miles of driving data, the technique has been applied to generate a model that estimates trip energy requirements. The model uses a novel binning approach to categorize driving by road type, traffic conditions, and driving profile. The trip-level energy estimations can easily be aggregated to any higher-level transportation system network desired. The model has been tested and validated on the Austin, Texas, data set used to build this model. Ground-truth energy consumption for the data set was obtained from Futuremore » Automotive Systems Technology Simulator (FASTSim) vehicle simulation results. The energy estimation model has demonstrated 12.1 percent normalized total absolute error. The energy estimation from the model can be used to inform control strategies in routing tools, such as change in departure time, alternate routing, and alternate destinations, to reduce energy consumption. The model can also be used to determine more accurate energy consumption of regional or national transportation networks if trip origin and destinations are known. Additionally, this method allows the estimation tool to be tuned to a specific driver or vehicle type.« less

Pros and cons of estimating the reproduction number from early epidemic growth rate of influenza A (H1N1) 2009.

PubMed

Nishiura, Hiroshi; Chowell, Gerardo; Safan, Muntaser; Castillo-Chavez, Carlos

2010-01-07

In many parts of the world, the exponential growth rate of infections during the initial epidemic phase has been used to make statistical inferences on the reproduction number, R, a summary measure of the transmission potential for the novel influenza A (H1N1) 2009. The growth rate at the initial stage of the epidemic in Japan led to estimates for R in the range 2.0 to 2.6, capturing the intensity of the initial outbreak among school-age children in May 2009. An updated estimate of R that takes into account the epidemic data from 29 May to 14 July is provided. An age-structured renewal process is employed to capture the age-dependent transmission dynamics, jointly estimating the reproduction number, the age-dependent susceptibility and the relative contribution of imported cases to secondary transmission. Pitfalls in estimating epidemic growth rates are identified and used for scrutinizing and re-assessing the results of our earlier estimate of R. Maximum likelihood estimates of R using the data from 29 May to 14 July ranged from 1.21 to 1.35. The next-generation matrix, based on our age-structured model, predicts that only 17.5% of the population will experience infection by the end of the first pandemic wave. Our earlier estimate of R did not fully capture the population-wide epidemic in quantifying the next-generation matrix from the estimated growth rate during the initial stage of the pandemic in Japan. In order to quantify R from the growth rate of cases, it is essential that the selected model captures the underlying transmission dynamics embedded in the data. Exploring additional epidemiological information will be useful for assessing the temporal dynamics. Although the simple concept of R is more easily grasped by the general public than that of the next-generation matrix, the matrix incorporating detailed information (e.g., age-specificity) is essential for reducing the levels of uncertainty in predictions and for assisting public health policymaking. Model-based prediction and policymaking are best described by sharing fundamental notions of heterogeneous risks of infection and death with non-experts to avoid potential confusion and/or possible misuse of modelling results.

Assessing Interval Estimation Methods for Hill Model ...

EPA Pesticide Factsheets

The Hill model of concentration-response is ubiquitous in toxicology, perhaps because its parameters directly relate to biologically significant metrics of toxicity such as efficacy and potency. Point estimates of these parameters obtained through least squares regression or maximum likelihood are commonly used in high-throughput risk assessment, but such estimates typically fail to include reliable information concerning confidence in (or precision of) the estimates. To address this issue, we examined methods for assessing uncertainty in Hill model parameter estimates derived from concentration-response data. In particular, using a sample of ToxCast concentration-response data sets, we applied four methods for obtaining interval estimates that are based on asymptotic theory, bootstrapping (two varieties), and Bayesian parameter estimation, and then compared the results. These interval estimation methods generally did not agree, so we devised a simulation study to assess their relative performance. We generated simulated data by constructing four statistical error models capable of producing concentration-response data sets comparable to those observed in ToxCast. We then applied the four interval estimation methods to the simulated data and compared the actual coverage of the interval estimates to the nominal coverage (e.g., 95%) in order to quantify performance of each of the methods in a variety of cases (i.e., different values of the true Hill model paramet

Estimating the "impact" of out-of-home placement on child well-being: approaching the problem of selection bias.

PubMed

Berger, Lawrence M; Bruch, Sarah K; Johnson, Elizabeth I; James, Sigrid; Rubin, David

2009-01-01

This study used data on 2,453 children aged 4-17 from the National Survey of Child and Adolescent Well-Being and 5 analytic methods that adjust for selection factors to estimate the impact of out-of-home placement on children's cognitive skills and behavior problems. Methods included ordinary least squares (OLS) regressions and residualized change, simple change, difference-in-difference, and fixed effects models. Models were estimated using the full sample and a matched sample generated by propensity scoring. Although results from the unmatched OLS and residualized change models suggested that out-of-home placement is associated with increased child behavior problems, estimates from models that more rigorously adjust for selection bias indicated that placement has little effect on children's cognitive skills or behavior problems.

Are dialysis adequacy indices independent of solute generation rate?

PubMed

Waniewski, Jacek; Debowska, Malgorzata; Lindholm, Bengt

2014-01-01

KT/V is by definition independent of solute generation rate. Alternative dialysis adequacy indices (DAIs) such as equivalent renal clearance (EKR), standard KT/V (stdKT/V), and solute removal index (SRI) are estimated as the ratio of solute mass removed to an average solute mass in the body or solute concentration in blood; both nominator and denominator in these formulas depend on the solute generation rate. Our objective was to investigate whether and under which conditions the alternative DAIs are independent of solute generation rate. By using general compartment modeling, we show that for the metabolically stable patient (in whom the solute generated during the dialysis cycle, typically, 1 week, is equal to the solute removed from the body), DAIs estimated for the dialysis cycle are in general independent of the average solute generation rate (although they may depend on the pattern of oscillations in the generation rate). However, the alternative adequacy parameters (such as EKR, stdKT/V, and SRI) may depend on solute generation rate for metabolically unstable patients.

Selecting the best stable isotope mixing model to estimate grizzly bear diets in the Greater Yellowstone Ecosystem

PubMed Central

Hopkins, John B.; Ferguson, Jake M.; Tyers, Daniel B.; Kurle, Carolyn M.

2017-01-01

Past research indicates that whitebark pine seeds are a critical food source for Threatened grizzly bears (Ursus arctos) in the Greater Yellowstone Ecosystem (GYE). In recent decades, whitebark pine forests have declined markedly due to pine beetle infestation, invasive blister rust, and landscape-level fires. To date, no study has reliably estimated the contribution of whitebark pine seeds to the diets of grizzlies through time. We used stable isotope ratios (expressed as δ13C, δ15N, and δ34S values) measured in grizzly bear hair and their major food sources to estimate the diets of grizzlies sampled in Cooke City Basin, Montana. We found that stable isotope mixing models that included different combinations of stable isotope values for bears and their foods generated similar proportional dietary contributions. Estimates generated by our top model suggest that whitebark pine seeds (35±10%) and other plant foods (56±10%) were more important than meat (9±8%) to grizzly bears sampled in the study area. Stable isotope values measured in bear hair collected elsewhere in the GYE and North America support our conclusions about plant-based foraging. We recommend that researchers consider model selection when estimating the diets of animals using stable isotope mixing models. We also urge researchers to use the new statistical framework described here to estimate the dietary responses of grizzlies to declines in whitebark pine seeds and other important food sources through time in the GYE (e.g., cutthroat trout), as such information could be useful in predicting how the population will adapt to future environmental change. PMID:28493929