Modelling human performance within manufacturing systems design:from a theoretical towards a practical framework

Computer-based simulation is frequently used to evaluate the capabilities of proposed manufacturing system designs. Unfortunately, the real systems are often found to perform quite differently from simulation predictions and one possible reason for this is an over-simplistic representation of workers' behaviour within current simulation techniques. The accuracy of design predictions could be improved through a modelling tool that integrates with computer-based simulation and incorporates the factors and relationships that determine workers' performance. This paper explores the viability of developing a similar tool based on our previously published theoretical modelling framework. It focuses on evolving this purely theoretical framework towards a practical modelling tool that can actually be used to expand the capabilities of current simulation techniques. Based on an industrial study, the paper investigates how the theoretical framework works in practice, analyses strengths and weaknesses in its formulation, and proposes developments that can contribute towards enabling human performance modelling in a practical way

Calibration of GENEActiv accelerometer wrist cut-points for the assessment of physical activity intensity of pre-school aged children

This study sought to validate cut-points for use of wrist worn GENEActiv accelerometer data, to analyse preschool children’s (4 to 5 year olds) physical activity (PA) levels via calibration with oxygen consumption values (VO2). This was a laboratory based calibration study. Twenty-one preschool children, aged 4.7 ± 0.5 years old, completed six activities (ranging from lying supine to running) whilst wearing the GENEActiv accelerometers at two locations (left and right wrist), these being the participants’ non-dominant and dominant wrist, and a Cortex face mask for gas analysis. VO2 data was used for the assessment of criterion validity. Location specific activity intensity cut points were established via Receiver Operator Characteristic curve (ROC) analysis. The GENEActiv accelerometers, irrespective of their location, accurately discriminated between all PA intensities (sedentary, light, and moderate and above), with the dominant wrist monitor providing a slightly more precise discrimination at light PA and the non-dominant at the sedentary behaviour and moderate and above intensity levels (Area Under the Curve (AUC) for non-dominant = 0.749-0.993, compared to AUC dominant = 0.760-0.988). Conclusion: This study establishes wrist-worn physical activity cut points for the GENEActiv accelerometer in pre-schoolers.N/

Comparison of imputation methods for handling missing covariate data when fitting a Cox proportional hazards model: a resampling study

<p>Abstract</p> <p>Background</p> <p>The appropriate handling of missing covariate data in prognostic modelling studies is yet to be conclusively determined. A resampling study was performed to investigate the effects of different missing data methods on the performance of a prognostic model.</p> <p>Methods</p> <p>Observed data for 1000 cases were sampled with replacement from a large complete dataset of 7507 patients to obtain 500 replications. Five levels of missingness (ranging from 5% to 75%) were imposed on three covariates using a missing at random (MAR) mechanism. Five missing data methods were applied; a) complete case analysis (CC) b) single imputation using regression switching with predictive mean matching (SI), c) multiple imputation using regression switching imputation, d) multiple imputation using regression switching with predictive mean matching (MICE-PMM) and e) multiple imputation using flexible additive imputation models. A Cox proportional hazards model was fitted to each dataset and estimates for the regression coefficients and model performance measures obtained.</p> <p>Results</p> <p>CC produced biased regression coefficient estimates and inflated standard errors (SEs) with 25% or more missingness. The underestimated SE after SI resulted in poor coverage with 25% or more missingness. Of the MI approaches investigated, MI using MICE-PMM produced the least biased estimates and better model performance measures. However, this MI approach still produced biased regression coefficient estimates with 75% missingness.</p> <p>Conclusions</p> <p>Very few differences were seen between the results from all missing data approaches with 5% missingness. However, performing MI using MICE-PMM may be the preferred missing data approach for handling between 10% and 50% MAR missingness.</p

Application of deep learning in detecting neurological disorders from magnetic resonance images: a survey on the detection of Alzheimer’s disease, Parkinson's disease and schizophrenia

Neuroimaging, in particular magnetic resonance imaging (MRI), has been playing an important role in understanding brain functionalities and its disorders during the last couple of decades. These cutting-edge MRI scans, supported by high-performance computational tools and novel ML techniques, have opened up possibilities to unprecedentedly identify neurological disorders. However, similarities in disease phenotypes make it very difficult to detect such disorders accurately from the acquired neuroimaging data. This article critically examines and compares performances of the existing deep learning (DL)-based methods to detect neurological disorders—focusing on Alzheimer’s disease, Parkinson’s disease and schizophrenia—from MRI data acquired using different modalities including functional and structural MRI. The comparative performance analysis of various DL architectures across different disorders and imaging modalities suggests that the Convolutional Neural Network outperforms other methods in detecting neurological disorders. Towards the end, a number of current research challenges are indicated and some possible future research directions are provided

A Wide and Deep Neural Network for Survival Analysis from Anatomical Shape and Tabular Clinical Data

We introduce a wide and deep neural network for prediction of progression from patients with mild cognitive impairment to Alzheimer's disease. Information from anatomical shape and tabular clinical data (demographics, biomarkers) are fused in a single neural network. The network is invariant to shape transformations and avoids the need to identify point correspondences between shapes. To account for right censored time-to-event data, i.e., when it is only known that a patient did not develop Alzheimer's disease up to a particular time point, we employ a loss commonly used in survival analysis. Our network is trained end-to-end to combine information from a patient's hippocampus shape and clinical biomarkers. Our experiments on data from the Alzheimer's Disease Neuroimaging Initiative demonstrate that our proposed model is able to learn a shape descriptor that augments clinical biomarkers and outperforms a deep neural network on shape alone and a linear model on common clinical biomarkers.Comment: Data and Machine Learning Advances with Multiple Views Workshop, ECML-PKDD 201

Predictors of early sexual initiation among a nationally representative sample of Nigerian adolescents

<p>Abstract</p> <p>Background</p> <p>Early sexual debut among adolescents is associated with considerable negative heath and development outcomes. An understanding of the determinants or predictors of the timing of sexual debut is important for effective intervention, but very few studies to date have addressed this issue in the Nigerian context. The aim of the present study is to examine predictors of adolescent sexual initiation among a nationally representative sample of adolescents in Nigeria.</p> <p>Methods</p> <p>Interviewer-collected data of 2,070 never-married adolescents aged 15–19 years were analysed to determine association between age of sexual debut and demographic, psychosocial and community factors. Using Cox proportional hazards regression multivariate analysis was carried out with two different models – one with and the other without psychosocial factors. Hazard ratio (HR) and 95% confidence interval (CI) were calculated separately for males and females.</p> <p>Results</p> <p>A fifth of respondents (18% males; 22% females) were sexually experienced. In the South 24.3% males and 28.7% females had initiated sex compared to 12.1% of males and 13.1% females in the North (p < 0.001). In the first model, only region was significantly associated with adolescent sexual initiation among both males and females; however, educational attainment and age were also significant among males. In the second (psychosocial) model factors associated with adolescent sexual debut for both genders included more positive attitudes regarding condom efficacy (males: HR = 1.28, 95% CI = 1.07–1.53; females: HR = 1.24, 95% CI = 1.05–1.46) and more positive attitudes to family planning use (males: HR = 1.19, 95% CI = 1.09–1.31; females: HR = 1.18, 95% CI = 1.07–1.30). A greater perception of condom access (HR = 1.42, 95% CI = 1.14–1.76) and alcohol use (HR = 1.90, 95% CI = 1.38–2.62) among males and positive gender-related attitudes (HR = 1.13, 95% CI = 1.04–1.23) among females were also associated with increased likelihood of adolescent sexual initiation. Conversely, personal attitudes in favour of delayed sexual debut were associated with lower sexual debut among both males (males: HR = 0.36, 95% CI = 0.25–0.52) and females (HR = 0.38, 95% CI = 0.25–0.57). Higher level of religiosity was associated with lower sexual debut rates only among females (HR = 0.59, 95% CI = 0.37–0.94).</p> <p>Conclusion</p> <p>Given the increased risk for a number of sexually transmitted health problems, understanding the factors that are associated with premarital sexual debut will assist programmes in developing more effective risk prevention interventions.</p

Genome Characteristics of a Novel Phage from Bacillus thuringiensis Showing High Similarity with Phage from Bacillus cereus

Bacillus thuringiensis is an important entomopathogenic bacterium belongs to the Bacillus cereus group, which also includes B. anthracis and B. cereus. Several genomes of phages originating from this group had been sequenced, but no genome of Siphoviridae phage from B. thuringiensis has been reported. We recently sequenced and analyzed the genome of a novel phage, BtCS33, from a B. thuringiensis strain, subsp. kurstaki CS33, and compared the gneome of this phage to other phages of the B. cereus group. BtCS33 was the first Siphoviridae phage among the sequenced B. thuringiensis phages. It produced small, turbid plaques on bacterial plates and had a narrow host range. BtCS33 possessed a linear, double-stranded DNA genome of 41,992 bp with 57 putative open reading frames (ORFs). It had a typical genome structure consisting of three modules: the “late” region, the “lysogeny-lysis” region and the “early” region. BtCS33 exhibited high similarity with several phages, B. cereus phage Wβ and some variants of Wβ, in genome organization and the amino acid sequences of structural proteins. There were two ORFs, ORF22 and ORF35, in the genome of BtCS33 that were also found in the genomes of B. cereus phage Wβ and may be involved in regulating sporulation of the host cell. Based on these observations and analysis of phylogenetic trees, we deduced that B. thuringiensis phage BtCS33 and B. cereus phage Wβ may have a common distant ancestor

Long-term effects of an inpatient weight-loss program in obese children and the role of genetic predisposition-rationale and design of the LOGIC-trial

<p>Abstract</p> <p>Background</p> <p>The prevalence of childhood obesity has increased worldwide, which is a serious concern as obesity is associated with many negative immediate and long-term health consequences. Therefore, the treatment of overweight and obesity in children and adolescents is strongly recommended. Inpatient weight-loss programs have shown to be effective particularly regarding short-term weight-loss, whilst little is known both on the long-term effects of this treatment and the determinants of successful weight-loss and subsequent weight maintenance.</p> <p>The purpose of this study is to evaluate the short, middle and long-term effects of an inpatient weight-loss program for children and adolescents and to investigate the likely determinants of weight changes, whereby the primary focus lies on the potential role of differences in polymorphisms of adiposity-relevant genes.</p> <p>Methods/Design</p> <p>The study involves overweight and obese children and adolescents aged 6 to 19 years, who participate in an inpatient weight-loss program for 4 to 6 weeks. It started in 2006 and it is planned to include 1,500 participants by 2013. The intervention focuses on diet, physical activity and behavior therapy. Measurements are taken at the start and the end of the intervention and comprise blood analyses (DNA, lipid and glucose metabolism, adipokines and inflammatory markers), anthropometry (body weight, height and waist circumference), blood pressure, pubertal stage, and exercise capacity. Physical activity, dietary habits, quality of life, and family background are assessed by questionnaires. Follow-up assessments are performed 6 months, 1, 2, 5 and 10 years after the intervention: Children will complete the same questionnaires at all time points and visit their general practitioner for examination of anthropometric parameters, blood pressure and assessment of pubertal stage. At the 5 and 10 year follow-ups, blood parameters and exercise capacity will be additionally measured.</p> <p>Discussion</p> <p>Apart from illustrating the short, middle and long-term effects of an inpatient weight-loss program, this study will contribute to a better understanding of inter-individual differences in the regulation of body weight, taking into account the role of genetic predisposition and lifestyle factors.</p> <p>Trial Registration</p> <p><a href="http://www.clinicaltrials.gov/ct2/show/NCT01067157">NCT01067157</a>.</p

The DRUID study: racism and self-assessed health status in an indigenous population

BackgroundThere is now considerable evidence from around the world that racism is associated with both mental and physical ill-health. However, little is known about the mediating factors between racism and ill-health. This paper investigates relationships between racism and self-assessed mental and physical health among Indigenous Australians as well as potential mediators of these relationships.MethodsA total of 164 adults in the Darwin Region Urban Indigenous Diabetes (DRUID) study completed a validated instrument assessing interpersonal racism and a separate item on discrimination-related stress. Self-assessed health status was measured using the SF-12. Stress, optimism, lack of control, social connections, cultural identity and reactions/responses to interpersonal racism were considered as mediators and moderators of the relationship between racism/discrimination and self-assessed health status.ResultsAfter adjusting for socio-demographic factors, interpersonal racism was significantly associated with the SF-12 mental (but not the physical) health component. Stress, lack of control and feeling powerless as a reaction to racism emerged as significant mediators of the relationship between racism and general mental health. Similar findings emerged for discrimination-related stress.ConclusionsRacism/discrimination is significantly associated with poor general mental health among this indigenous population. The mediating factors between racism and mental health identified in this study suggest new approaches to ameliorating the detrimental effects of racism on health. In particular, the importance of reducing racism-related stress, enhancing general levels of mastery, and minimising negative social connections in order to ameliorate the negative consequences of racism

Registered Replication Report: Dijksterhuis and van Knippenberg (1998)

Dijksterhuis and van Knippenberg (1998) reported that participants primed with a category associated with intelligence ("professor") subsequently performed 13% better on a trivia test than participants primed with a category associated with a lack of intelligence ("soccer hooligans"). In two unpublished replications of this study designed to verify the appropriate testing procedures, Dijksterhuis, van Knippenberg, and Holland observed a smaller difference between conditions (2%-3%) as well as a gender difference: Men showed the effect (9.3% and 7.6%), but women did not (0.3% and -0.3%). The procedure used in those replications served as the basis for this multilab Registered Replication Report. A total of 40 laboratories collected data for this project, and 23 of these laboratories met all inclusion criteria. Here we report the meta-analytic results for those 23 direct replications (total N = 4,493), which tested whether performance on a 30-item general-knowledge trivia task differed between these two priming conditions (results of supplementary analyses of the data from all 40 labs, N = 6,454, are also reported). We observed no overall difference in trivia performance between participants primed with the "professor" category and those primed with the "hooligan" category (0.14%) and no moderation by gender