The Libra Toolkit for Probabilistic Models

The Libra Toolkit is a collection of algorithms for learning and inference with discrete probabilistic models, including Bayesian networks, Markov networks, dependency networks, and sum-product networks. Compared to other toolkits, Libra places a greater emphasis on learning the structure of tractable models in which exact inference is efficient. It also includes a variety of algorithms for learning graphical models in which inference is potentially intractable, and for performing exact and approximate inference. Libra is released under a 2-clause BSD license to encourage broad use in academia and industry

Inclusion of ethnic minorities in telehealth trials for type 2 diabetes:Protocol for a systematic review examining prevalence and language issues

BACKGROUND: Type 2 diabetes is common, on the rise, and disproportionately affects ethnic minority groups. Telehealth interventions may mitigate diabetes-related complications, but might under-recruit or even exclude ethnic minorities, in part because of English language requirements. The under-representation of minority patients in trials could threaten the generalizability of the findings, whereby the patients who might stand to benefit most from such interventions are not being included in their evaluation. OBJECTIVE: The aims of this systematic review are twofold: (1) to assess the reporting and prevalence of ethnic minorities in published telehealth trials for type 2 diabetes, including identifying trial features associated with successful patient recruitment; and (2) to determine the proportion of such trials that report English language proficiency as an inclusion/exclusion criterion, including how and why they do so. METHODS: Randomized controlled trials (RCTs) of adults with type 2 diabetes in Western, English-speaking countries that included telehealth interventions targeting diabetes as a primary condition, and those that did not specifically recruit minority groups will be included. Search strategies were devised for indexed and keyword terms capturing type 2 diabetes, telehealth/health technology, and RCTs in English language publications from 2000 to July 2015 in MEDLINE, PsycINFO, EMBASE, CINAHL, and CENTRAL. Reference lists of included studies will also be searched. Two reviewers will independently screen abstracts and full-text articles against inclusion criteria, mediated by a third reviewer if consensus cannot be reached. Data extracted from included studies will be checked by a second reviewer and will be summarized using narrative synthesis. RESULTS: This research is in progress, with findings expected by Spring 2016. CONCLUSIONS: This review will address research reporting and recruitment practices of ethnic minorities in telehealth RCTs for type 2 diabetes. Prevalence estimates will elucidate generalizability of existing research, with implications for researchers, health professionals, and policy makers. Identifying trial or intervention features that appear to facilitate ethnic minority recruitment, as well as language barriers that impede it might suggest ways to improve recruitment in future trials. TRIAL REGISTRATION: PROSPERO International Prospective Register of Systematic Reviews: CRD42015024899; http://www.crd.york.ac.uk/PROSPERO/display_record.asp?ID=CRD42015024899 (Archived by WebCite at http://www.webcitation.org/6fUMqbJ0f)

Inclusion of Ethnic Minorities in Telehealth Trials for Type 2 Diabetes: Protocol for a Systematic Review Examining Prevalence and Language Issues

BACKGROUND: Type 2 diabetes is common, on the rise, and disproportionately affects ethnic minority groups. Telehealth interventions may mitigate diabetes-related complications, but might under-recruit or even exclude ethnic minorities, in part because of English language requirements. The under-representation of minority patients in trials could threaten the generalizability of the findings, whereby the patients who might stand to benefit most from such interventions are not being included in their evaluation. OBJECTIVE: The aims of this systematic review are twofold: (1) to assess the reporting and prevalence of ethnic minorities in published telehealth trials for type 2 diabetes, including identifying trial features associated with successful patient recruitment; and (2) to determine the proportion of such trials that report English language proficiency as an inclusion/exclusion criterion, including how and why they do so. METHODS: Randomized controlled trials (RCTs) of adults with type 2 diabetes in Western, English-speaking countries that included telehealth interventions targeting diabetes as a primary condition, and those that did not specifically recruit minority groups will be included. Search strategies were devised for indexed and keyword terms capturing type 2 diabetes, telehealth/health technology, and RCTs in English language publications from 2000 to July 2015 in MEDLINE, PsycINFO, EMBASE, CINAHL, and CENTRAL. Reference lists of included studies will also be searched. Two reviewers will independently screen abstracts and full-text articles against inclusion criteria, mediated by a third reviewer if consensus cannot be reached. Data extracted from included studies will be checked by a second reviewer and will be summarized using narrative synthesis. RESULTS: This research is in progress, with findings expected by Spring 2016. CONCLUSIONS: This review will address research reporting and recruitment practices of ethnic minorities in telehealth RCTs for type 2 diabetes. Prevalence estimates will elucidate generalizability of existing research, with implications for researchers, health professionals, and policy makers. Identifying trial or intervention features that appear to facilitate ethnic minority recruitment, as well as language barriers that impede it might suggest ways to improve recruitment in future trials

Managing common infections in Day Care settings : Day Care providers' sickness exclusion beliefs, advice, and their consequences for parents

Background and Aims: Judicial antibiotic prescribing and appropriate use of healthcare resources are public health priorities. Preschool-aged children that attend day care frequently consult general practitioners (GPs) and receive antibiotics, despite experiencing mainly self-limiting and/or viral infections. North-American surveys indicate that day care providers unnecessarily exclude children with infections, and make exceptions to exclusion on the basis of antibiotic treatment. Commentators suggest that this may lead to unnecessary consultations and inappropriate antibiotic requests. This study’s main aim was to explore whether UK-based day care providers’ management of infections encourages parents to unnecessarily consult GPs, and inappropriately seek antibiotics. A secondary aim was to describe the content and nature of written day care sickness exclusion policies. Questionnaire Methods and Results: Questionnaires were distributed to 329 day care providers in three socio-demographically contrasting areas of South-East Wales, to gather descriptive data regarding sickness exclusion policies. 216 (66%) responses were received. Policies were mostly self-written, diverse in content and detail, and often non-evidence-based. Qualitative Methods and Results: Day care providers’ management of infections, and the influence this had on parents’ consulting and antibiotic-seeking behaviours, were explored through semi-structured interviews with 24 purposefully selected day care providers, and 28 opportunistically-selected parents that used their services. Interviews underwent inductive thematic analysis. All day care providers encouraged parents to consult GPs for self-limiting infections, and often inappropriately advised antibiotic treatment through written policies and verbal communication. Some parents felt that day care attendance increased their tendency to consult for symptoms they would usually manage themselves. The purpose of consultation was often to expedite return to day care, rather than alleviate concern. Parents understood that antibiotics were unlikely to be beneficial, but still sought and received treatment in order to appease day care providers’ requirements. Conclusion: Day care providers’ inappropriate advice to parents, together with non-evidence-based exclusion policies, contribute to unnecessary GP consultations and inappropriate antibiotic-seeking behaviour.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Differential Equation Units: Learning Functional Forms of Activation Functions from Data

Most deep neural networks use simple, fixed activation functions, such as sigmoids or rectified linear units, regardless of domain or network structure. We introduce differential equation units (DEUs), an improvement to modern neural networks, which enables each neuron to learn a particular nonlinear activation function from a family of solutions to an ordinary differential equation. Specifically, each neuron may change its functional form during training based on the behavior of the other parts of the network. We show that using neurons with DEU activation functions results in a more compact network capable of achieving comparable, if not superior, performance when is compared to much larger networks.Comment: arXiv admin note: text overlap with arXiv:1905.0768

Managing common infections in Day Care settings: Day Care providers’ sickness exclusion beliefs, advice, and their consequences for parents

Background and Aims: Judicial antibiotic prescribing and appropriate use of healthcare resources are public health priorities. Preschool-aged children that attend day care frequently consult general practitioners (GPs) and receive antibiotics, despite experiencing mainly self-limiting and/or viral infections. North-American surveys indicate that day care providers unnecessarily exclude children with infections, and make exceptions to exclusion on the basis of antibiotic treatment. Commentators suggest that this may lead to unnecessary consultations and inappropriate antibiotic requests. This study’s main aim was to explore whether UK-based day care providers’ management of infections encourages parents to unnecessarily consult GPs, and inappropriately seek antibiotics. A secondary aim was to describe the content and nature of written day care sickness exclusion policies. Questionnaire Methods and Results: Questionnaires were distributed to 329 day care providers in three socio-demographically contrasting areas of South-East Wales, to gather descriptive data regarding sickness exclusion policies. 216 (66%) responses were received. Policies were mostly self-written, diverse in content and detail, and often non-evidence-based. Qualitative Methods and Results: Day care providers’ management of infections, and the influence this had on parents’ consulting and antibiotic-seeking behaviours, were explored through semi-structured interviews with 24 purposefully selected day care providers, and 28 opportunistically-selected parents that used their services. Interviews underwent inductive thematic analysis. All day care providers encouraged parents to consult GPs for self-limiting infections, and often inappropriately advised antibiotic treatment through written policies and verbal communication. Some parents felt that day care attendance increased their tendency to consult for symptoms they would usually manage themselves. The purpose of consultation was often to expedite return to day care, rather than alleviate concern. Parents understood that antibiotics were unlikely to be beneficial, but still sought and received treatment in order to appease day care providers’ requirements. Conclusion: Day care providers’ inappropriate advice to parents, together with non-evidence-based exclusion policies, contribute to unnecessary GP consultations and inappropriate antibiotic-seeking behaviour

Embedding Principal Component Analysis for Data Reductionin Structural Health Monitoring on Low-Cost IoT Gateways

Principal component analysis (PCA) is a powerful data reductionmethod for Structural Health Monitoring. However, its computa-tional cost and data memory footprint pose a significant challengewhen PCA has to run on limited capability embedded platformsin low-cost IoT gateways. This paper presents a memory-efficientparallel implementation of the streaming History PCA algorithm.On our dataset, it achieves 10x compression factor and 59x memoryreduction with less than 0.15 dB degradation in the reconstructedsignal-to-noise ratio (RSNR) compared to standard PCA. More-over, the algorithm benefits from parallelization on multiple cores,achieving a maximum speedup of 4.8x on Samsung ARTIK 710

The inclusion of ethnic minority patients and the role of language in telehealth trials for type 2 diabetes: A systematic review

BACKGROUND: Type 2 diabetes is a serious, pervasive metabolic condition that disproportionately affects ethnic minority patients. Telehealth interventions can facilitate type 2 diabetes monitoring and prevent secondary complications. However, trials designed to test the effectiveness of telehealth interventions may underrecruit or exclude ethnic minority patients, with language a potential barrier to recruitment. The underrepresentation of minorities in trials limits the external validity of the findings for this key patient demographic. OBJECTIVE: This systematic review examines (1) the research reporting practices and prevalence of ethnic minority patients included in telehealth randomized controlled trials (RCTs) targeting type 2 diabetes and the trial characteristics associated with recruiting a high proportion of minority patients, and (2) the proportion of included RCTs that report using English language proficiency as a patient screening criterion and how and why they do so. METHODS: Telehealth RCTs published in refereed journals targeting type 2 diabetes as a primary condition for adults in Western majority English-speaking countries were included. Ethnically targeted RCTs were excluded from the main review, but were included in a post hoc subgroup analysis. Abstract and full-text screening, risk of bias assessment, and data extraction were independently conducted by two reviewers. RESULTS: Of 3358 records identified in the search, 79 articles comprising 58 RCTs were included. Nearly two-thirds of the RCTs (38/58) reported on the ethnic composition of participants, with a median proportion of 23.5% patients (range 0%-97.7%). Fourteen studies (24%) that included at least 30% minority patients were all US-based, predominantly recruited from urban areas, and described the target population as underserved, financially deprived, or uninsured. Eight of these 14 studies (57%) offered intervention materials in a language other than English or employed bilingual staff. Half of all identified RCTs (29/58) included language proficiency as a participant-screening criterion. Language proficiency was operationalized using nonstandardized measures (eg, having sufficient "verbal fluency"), with only three studies providing reasons for excluding patients on language grounds. CONCLUSIONS: There was considerable variability across studies in the inclusion of ethnic minority patients in RCTs, with higher participation rates in countries with legislation to mandate their inclusion (eg, United States) than in those without such legislation (eg, United Kingdom). Less than 25% of the RCTs recruited a sizeable proportion of ethnic minorities, which raises concerns about external validity. The lack of objective measures or common procedures for assessing language proficiency across trials implies that language-related eligibility decisions are often based on trial recruiters' impressionistic judgments, which could be subject to bias. The variability and inconsistent reporting on ethnicity and other socioeconomic factors in descriptions of research participants could be more specifically emphasized in trial reporting guidelines to promote best practice