Modelling the spread of American foulbrood in honeybees

We investigate the spread of American foulbrood (AFB), a disease caused by the bacterium Paenibacillus larvae, that affects bees and can be extremely damaging to beehives. Our dataset comes from an inspection period carried out during an AFB epidemic of honeybee colonies on the island of Jersey during the summer of 2010. The data include the number of hives of honeybees, location and owner of honeybee apiaries across the island. We use a spatial SIR model with an underlying owner network to simulate the epidemic and characterize the epidemic using a Markov chain Monte Carlo (MCMC) scheme to determine model parameters and infection times (including undetected ‘occult’ infections). Likely methods of infection spread can be inferred from the analysis, with both distance- and owner-based transmissions being found to contribute to the spread of AFB. The results of the MCMC are corroborated by simulating the epidemic using a stochastic SIR model, resulting in aggregate levels of infection that are comparable to the data. We use this stochastic SIR model to simulate the impact of different control strategies on controlling the epidemic. It is found that earlier inspections result in smaller epidemics and a higher likelihood of AFB extinction

Expert-Augmented Machine Learning

Machine Learning is proving invaluable across disciplines. However, its success is often limited by the quality and quantity of available data, while its adoption by the level of trust that models afford users. Human vs. machine performance is commonly compared empirically to decide whether a certain task should be performed by a computer or an expert. In reality, the optimal learning strategy may involve combining the complementary strengths of man and machine. Here we present Expert-Augmented Machine Learning (EAML), an automated method that guides the extraction of expert knowledge and its integration into machine-learned models. We use a large dataset of intensive care patient data to predict mortality and show that we can extract expert knowledge using an online platform, help reveal hidden confounders, improve generalizability on a different population and learn using less data. EAML presents a novel framework for high performance and dependable machine learning in critical applications

Implementing a 48 h EWTD-compliant rota for junior doctors in the UK does not compromise patients’ safety : assessor-blind pilot comparison

Background: There are currently no field data about the effect of implementing European Working Time Directive (EWTD)-compliant rotas in a medical setting. Surveys of doctors’ subjective opinions on shift work have not provided reliable objective data with which to evaluate its efficacy. Aim: We therefore studied the effects on patient's safety and doctors’ work-sleep patterns of implementing an EWTD-compliant 48 h work week in a single-blind intervention study carried out over a 12-week period at the University Hospitals Coventry & Warwickshire NHS Trust. We hypothesized that medical error rates would be reduced following the new rota. Methods: Nineteen junior doctors, nine studied while working an intervention schedule of <48 h per week and 10 studied while working traditional weeks of <56 h scheduled hours in medical wards. Work hours and sleep duration were recorded daily. Rate of medical errors (per 1000 patient-days), identified using an established active surveillance methodology, were compared for the Intervention and Traditional wards. Two senior physicians blinded to rota independently rated all suspected errors. Results: Average scheduled work hours were significantly lower on the intervention schedule [43.2 (SD 7.7) (range 26.0–60.0) vs. 52.4 (11.2) (30.0–77.0) h/week; P < 0.001], and there was a non-significant trend for increased total sleep time per day [7.26 (0.36) vs. 6.75 (0.40) h; P = 0.095]. During a total of 4782 patient-days involving 481 admissions, 32.7% fewer total medical errors occurred during the intervention than during the traditional rota (27.6 vs. 41.0 per 1000 patient-days, P = 0.006), including 82.6% fewer intercepted potential adverse events (1.2 vs. 6.9 per 1000 patient-days, P = 0.002) and 31.4% fewer non-intercepted potential adverse events (16.6 vs. 24.2 per 1000 patient-days, P = 0.067). Doctors reported worse educational opportunities on the intervention rota. Conclusions: Whilst concerns remain regarding reduced educational opportunities, our study supports the hypothesis that a 48 h work week coupled with targeted efforts to improve sleep hygiene improves patient safety

Extending scientific computing system with structural quantum programming capabilities

We present a basic high-level structures used for developing quantum programming languages. The presented structures are commonly used in many existing quantum programming languages and we use quantum pseudo-code based on QCL quantum programming language to describe them. We also present the implementation of introduced structures in GNU Octave language for scientific computing. Procedures used in the implementation are available as a package quantum-octave, providing a library of functions, which facilitates the simulation of quantum computing. This package allows also to incorporate high-level programming concepts into the simulation in GNU Octave and Matlab. As such it connects features unique for high-level quantum programming languages, with the full palette of efficient computational routines commonly available in modern scientific computing systems. To present the major features of the described package we provide the implementation of selected quantum algorithms. We also show how quantum errors can be taken into account during the simulation of quantum algorithms using quantum-octave package. This is possible thanks to the ability to operate on density matrices

Dialectic tensions in the financial markets: a longitudinal study of pre- and post-crisis regulatory technology

This article presents the findings from a longitudinal research study on regulatory technology in the UK financial services industry. The financial crisis with serious corporate and mutual fund scandals raised the profile of compliance as governmental bodies, institutional and private investors introduced a ‘tsunami’ of financial regulations. Adopting a multi-level analysis, this study examines how regulatory technology was used by financial firms to meet their compliance obligations, pre- and post-crisis. Empirical data collected over 12 years examine the deployment of an investment management system in eight financial firms. Interviews with public regulatory bodies, financial institutions and technology providers reveal a culture of compliance with increased transparency, surveillance and accountability. Findings show that dialectic tensions arise as the pursuit of transparency, surveillance and accountability in compliance mandates is simultaneously rationalized, facilitated and obscured by regulatory technology. Responding to these challenges, regulatory bodies continue to impose revised compliance mandates on financial firms to force them to adapt their financial technologies in an ever-changing multi-jurisdictional regulatory landscape

What difference does ("good") HRM make?

The importance of human resources management (HRM) to the success or failure of health system performance has, until recently, been generally overlooked. In recent years it has been increasingly recognised that getting HR policy and management "right" has to be at the core of any sustainable solution to health system performance. In comparison to the evidence base on health care reform-related issues of health system finance and appropriate purchaser/provider incentive structures, there is very limited information on the HRM dimension or its impact. Despite the limited, but growing, evidence base on the impact of HRM on organisational performance in other sectors, there have been relatively few attempts to assess the implications of this evidence for the health sector. This paper examines this broader evidence base on HRM in other sectors and examines some of the underlying issues related to "good" HRM in the health sector. The paper considers how human resource management (HRM) has been defined and evaluated in other sectors. Essentially there are two sub-themes: how have HRM interventions been defined? and how have the effects of these interventions been measured in order to identify which interventions are most effective? In other words, what is "good" HRM? The paper argues that it is not only the organisational context that differentiates the health sector from many other sectors, in terms of HRM. Many of the measures of organisational performance are also unique. "Performance" in the health sector can be fully assessed only by means of indicators that are sector-specific. These can focus on measures of clinical activity or workload (e.g. staff per occupied bed, or patient acuity measures), on measures of output (e.g. number of patients treated) or, less frequently, on measures of outcome (e.g. mortality rates or rate of post-surgery complications). The paper also stresses the need for a "fit" between the HRM approach and the organisational characteristics, context and priorities, and for recognition that so-called "bundles" of linked and coordinated HRM interventions will be more likely to achieve sustained improvements in organisational performance than single or uncoordinated interventions

Chromosphere of K giant stars Geometrical extent and spatial structure detection

We aim to constrain the geometrical extent of the chromosphere of non-binary K giant stars and detect any spatial structures in the chromosphere. We performed observations with the CHARA interferometer and the VEGA beam combiner at optical wavelengths. We observed seven non-binary K giant stars. We measured the ratio of the radii of the photosphere to the chromosphere using the interferometric measurements in the Halpha and the Ca II infrared triplet line cores. For beta Ceti, spectro-interferometric observations are compared to an non-local thermal equilibrium (NLTE) semi-empirical model atmosphere including a chromosphere. The NLTE computations provide line intensities and contribution functions that indicate the relative locations where the line cores are formed and can constrain the size of the limb-darkened disk of the stars with chromospheres. We measured the angular diameter of seven K giant stars and deduced their fundamental parameters: effective temperatures, radii, luminosities, and masses. We determined the geometrical extent of the chromosphere for four giant stars. The chromosphere extents obtained range between 16% to 47% of the stellar radius. The NLTE computations confirm that the Ca II/849 nm line core is deeper in the chromosphere of ? Cet than either of the Ca II/854 nm and Ca II/866 nm line cores. We present a modified version of a semi-empirical model atmosphere derived by fitting the Ca II triplet line cores of this star. In four of our targets, we also detect the signature of a differential signal showing the presence of asymmetries in the chromospheres. Conclusions. It is the first time that geometrical extents and structure in the chromospheres of non-binary K giant stars are determined by interferometry. These observations provide strong constrains on stellar atmosphere models.Comment: 10 pages, 12 figure

Education, income, and incident heart failure in post-menopausal women: the Women\u27s Health Initiative Hormone Therapy Trials

OBJECTIVES: The purpose of this study is to estimate the effect of education and income on incident heart failure (HF) hospitalization among post-menopausal women. BACKGROUND: Investigations of socioeconomic status have focused on outcomes after HF diagnosis, not associations with incident HF. We used data from the Women\u27s Health Initiative Hormone Trials to examine the association between socioeconomic status levels and incident HF hospitalization. METHODS: We included 26,160 healthy, post-menopausal women. Education and income were self-reported. Analysis of variance, chi-square tests, and proportional hazards models were used for statistical analysis, with adjustment for demographics, comorbid conditions, behavioral factors, and hormone and dietary modification assignments. RESULTS: Women with household incomes $50,000 a year (16.7/10,000 person-years; p \u3c 0.01). Women with less than a high school education had higher HF hospitalization incidence (51.2/10,000 person-years) than college graduates and above (25.5/10,000 person-years; p \u3c 0.01). In multivariable analyses, women with the lowest income levels had 56% higher risk (hazard ratio: 1.56, 95% confidence interval: 1.19 to 2.04) than the highest income women; women with the least amount of education had 21% higher risk for incident HF hospitalization (hazard ratio: 1.21, 95% confidence interval: 0.90 to 1.62) than the most educated women. CONCLUSIONS: Lower income is associated with an increased incidence of HF hospitalization among healthy, post-menopausal women, whereas multivariable adjustment attenuated the association of education with incident HF. Elsevier Inc. All rights reserved

Rab3D is critical for secretory granule maturation in PC12 cells.

Neuropeptide- and hormone-containing secretory granules (SGs) are synthesized at the trans-Golgi network (TGN) as immature secretory granules (ISGs) and complete their maturation in the F-actin-rich cell cortex. This maturation process is characterized by acidification-dependent processing of cargo proteins, condensation of the SG matrix and removal of membrane and proteins not destined to mature secretory granules (MSGs). Here we addressed a potential role of Rab3 isoforms in these maturation steps by expressing their nucleotide-binding deficient mutants in PC12 cells. Our data show that the presence of Rab3D(N135I) decreases the restriction of maturing SGs to the F-actin-rich cell cortex, blocks the removal of the endoprotease furin from SGs and impedes the processing of the luminal SG protein secretogranin II. This strongly suggests that Rab3D is implicated in the subcellular localization and maturation of ISGs