Outer Approximations of Coherent Lower Probabilities Using Belief Functions

We investigate the problem of outer approximating a coherent lower probability with a more tractable model. In particular, in this work we focus on the outer approximations made by belief functions. We show that they can be obtained by solving a linear programming problem. In addition, we consider the subfamily of necessity measures, and show that in that case we can determine all the undominated outer approximations in a simple manner

Surface-enhanced Raman spectroscopy study of 4-ATP on gold nanoparticles for basal cell carcinoma fingerprint detection

The surface-enhanced Raman signals of 4-aminothiophenol (4-ATP) attached to the surface of colloidal gold nanoparticles with size distribution of 2 to 5 nm were used as a labeling agent to detect basal cell carcinoma (BCC) of the skin. The enhanced Raman band at 1075 cm-1 corresponding to the C-S stretching vibration in 4-ATP was observed during attachment to the surface of the gold nanoparticles. The frequency and intensity of this band did not change when the colloids were conjugated with BerEP4 antibody, which specifically binds to BCC. We show the feasibility of imaging BCC by surface-enhanced Raman spectroscopy, scanning the 1075 cm-1 band to detect the distribution of 4ATP-coated gold nanoparticles attached to skin tissue ex vivo

Fuzzy-rough-learn 0.1 : a Python library for machine learning with fuzzy rough sets

We present fuzzy-rough-learn, the first Python library of fuzzy rough set machine learning algorithms. It contains three algorithms previously implemented in R and Java, as well as two new algorithms from the recent literature. We briefly discuss the use cases of fuzzy-rough-learn and the design philosophy guiding its development, before providing an overview of the included algorithms and their parameters

Limited contribution of non-intensive chicken farming to ESBL-producing Escherichia coli colonization in humans in Vietnam: an epidemiological and genomic analysis.

OBJECTIVES: To investigate the risk of colonization with ESBL-producing Escherichia coli (ESBL-Ec) in humans in Vietnam associated with non-intensive chicken farming. METHODS: Faecal samples from 204 randomly selected farmers and their chickens, and from 306 age- and sex-matched community-based individuals who did not raise poultry were collected. Antimicrobial usage in chickens and humans was assessed by medicine cabinet surveys. WGS was employed to obtain a high-resolution genomic comparison between ESBL-Ec isolated from humans and chickens. RESULTS: The adjusted prevalence of ESBL-Ec colonization was 20.0% (95% CI 10.8%-29.1%) and 35.2% (95% CI 30.4%-40.1%) in chicken farms and humans in Vietnam, respectively. Colonization with ESBL-Ec in humans was associated with antimicrobial usage (OR = 2.52, 95% CI = 1.08-5.87) but not with involvement in chicken farming. blaCTX-M-55 was the most common ESBL-encoding gene in strains isolated from chickens (74.4%) compared with blaCTX-M-27 in human strains (47.0%). In 3 of 204 (1.5%) of the farms, identical ESBL genes were detected in ESBL-Ec isolated from farmers and their chickens. Genomic similarity indicating recent sharing of ESBL-Ec between chickens and farmers was found in only one of these farms. CONCLUSIONS: The integration of epidemiological and genomic data in this study has demonstrated a limited contribution of non-intensive chicken farming to ESBL-Ec colonization in humans in Vietnam and further emphasizes the importance of reducing antimicrobial usage in both human and animal host reservoirs

Reevaluation of the Value of Autoparasitoids in Biological Control

Autoparasitoids with the capacity of consuming primary parasitoids that share the same hosts to produce males are analogous to intraguild predators. The use of autoparasitoids in biological control programs is a controversial matter because there is little evidence to support the view that autoparasitoids do not disrupt and at times may promote suppression of insect pests in combination with primary parasitoids. We found that Encarsia sophia, a facultative autoparasitoid, preferred to use heterospecific hosts as secondary hosts for producing males. The autoparasitoids mated with males originated from heterospecifics may parasitize more hosts than those mated with males from conspecifics. Provided with an adequate number of males, the autoparasitoids killed more hosts than En. formosa, a commonly used parasitoid for biological control of whiteflies. This study supports the view that autoparasitoids in combination with primary parasitoids do not disrupt pest management and may enhance such programs. The demonstrated preference of an autoparasitoid for heterospecifics and improved performance of males from heterospecifics observed in this study suggests these criteria should be considered in strategies that endeavor to mass-produce and utilize autoparasitoids in the future

β3-adrenergic receptor gene, body mass index, bone mineral density and fracture risk in elderly men and women: the Dubbo Osteoporosis Epidemiology Study (DOES)

BACKGROUND: Recent studies have suggested that the Arg allele of β3-adrenergic receptor (ADRB3) gene is associated with body mass index (BMI), which is an important predictor of bone mineral density (BMD) and fracture risk. However, whether the ADRB3 gene polymorphism is associated with fracture risk has not been investigated. The aim of study was to examine the inter-relationships between ADRB3 gene polymorphisms, BMI, BMD and fracture risk in elderly Caucasians. METHODS: Genotypes of the ADRB3 gene were determined in 265 men and 446 women aged 60+ in 1989 at entry into the study, whose BMD were measured by DXA (GE Lunar, WI USA) at baseline. During the follow-up period (between 1989 and 2004), fractures were ascertained by reviewing radiography reports and personal interviews. RESULTS: The allelic frequencies of the Trp and the Arg alleles were 0.925 and 0.075 respectively, and the relative frequencies of genotypes Trp/Trp, Trp/Arg and Arg/Arg 0.857, 0.138 and 0.006 respectively. There was no significant association between BMI and ADRB3 genotypes (p = 0.10 in women and p = 0.68 in men). There was also no significant association between ADRB3 genotypes and lumbar spine or femoral neck BMD in either men and women. Furthermore, there were no significant association between ADRB3 genotypes and fracture risk in both women and men, either before or after adjusting for and, BMD and BMI. CONCLUSION: The present data suggested that in Caucasian population the contribution of ADRB3 genotypes to the prediction of BMI, BMD and fracture risk is limited

Strained graphene structures: from valleytronics to pressure sensing

Due to its strong bonds graphene can stretch up to 25% of its original size without breaking. Furthermore, mechanical deformations lead to the generation of pseudo-magnetic fields (PMF) that can exceed 300 T. The generated PMF has opposite direction for electrons originating from different valleys. We show that valley-polarized currents can be generated by local straining of multi-terminal graphene devices. The pseudo-magnetic field created by a Gaussian-like deformation allows electrons from only one valley to transmit and a current of electrons from a single valley is generated at the opposite side of the locally strained region. Furthermore, applying a pressure difference between the two sides of a graphene membrane causes it to bend/bulge resulting in a resistance change. We find that the resistance changes linearly with pressure for bubbles of small radius while the response becomes non-linear for bubbles that stretch almost to the edges of the sample. This is explained as due to the strong interference of propagating electronic modes inside the bubble. Our calculations show that high gauge factors can be obtained in this way which makes graphene a good candidate for pressure sensing.Comment: to appear in proceedings of the NATO Advanced Research Worksho

Odour-mediated orientation of beetles is influenced by age, sex and morph

The behaviour of insects is dictated by a combination of factors and may vary considerably between individuals, but small insects are often considered en masse and thus these differences can be overlooked. For example, the cowpea bruchid Callosobruchus maculatus F. exists naturally in two adult forms: the active (flight) form for dispersal, and the inactive (flightless), more fecund but shorter-lived form. Given that these morphs show dissimilar biology, it is possible that they differ in odour-mediated orientation and yet studies of this species frequently neglect to distinguish morph type, or are carried out only on the inactive morph. Along with sex and age of individual, adult morph could be an important variable determining the biology of this and similar species, informing studies on evolution, ecology and pest management. We used an olfactometer with motion-tracking to investigate whether the olfactory behaviour and orientation of C. maculatus towards infested and uninfested cowpeas and a plant-derived repellent compound, methyl salicylate, differed between morphs or sexes. We found significant differences between the behaviour of male and female beetles and beetles of different ages, as well as interactive effects of sex, morph and age, in response to both host and repellent odours. This study demonstrates that behavioural experiments on insects should control for sex and age, while also considering differences between adult morphs where present in insect species. This finding has broad implications for fundamental entomological research, particularly when exploring the relationships between physiology, behaviour and evolutionary biology, and the application of crop protection strategies

Early detection of COVID-19 in the UK using self-reported symptoms: a large-scale, prospective, epidemiological surveillance study

Background Self-reported symptoms during the COVID-19 pandemic have been used to train artificial intelligence models to identify possible infection foci. To date, these models have only considered the culmination or peak of symptoms, which is not suitable for the early detection of infection. We aimed to estimate the probability of an individual being infected with SARS-CoV-2 on the basis of early self-reported symptoms to enable timely self-isolation and urgent testing. Methods In this large-scale, prospective, epidemiological surveillance study, we used prospective, observational, longitudinal, self-reported data from participants in the UK on 19 symptoms over 3 days after symptoms onset and COVID-19 PCR test results extracted from the COVID-19 Symptom Study mobile phone app. We divided the study population into a training set (those who reported symptoms between April 29, 2020, and Oct 15, 2020) and a test set (those who reported symptoms between Oct 16, 2020, and Nov 30, 2020), and used three models to analyse the selfreported symptoms: the UK’s National Health Service (NHS) algorithm, logistic regression, and the hierarchical Gaussian process model we designed to account for several important variables (eg, specific COVID-19 symptoms, comorbidities, and clinical information). Model performance to predict COVID-19 positivity was compared in terms of sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) in the test set. For the hierarchical Gaussian process model, we also evaluated the relevance of symptoms in the early detection of COVID-19 in population subgroups stratified according to occupation, sex, age, and body-mass index. Findings The training set comprised 182 991 participants and the test set comprised 15 049 participants. When trained on 3 days of self-reported symptoms, the hierarchical Gaussian process model had a higher prediction AUC (0·80 [95% CI 0·80–0·81]) than did the logistic regression model (0·74 [0·74–0·75]) and the NHS algorithm (0·67 [0·67–0·67]). AUCs for all models increased with the number of days of self-reported symptoms, but were still high for the hierarchical Gaussian process model at day 1 (0·73 [95% CI 0·73–0·74]) and day 2 (0·79 [0·78–0·79]). At day 3, the hierarchical Gaussian process model also had a significantly higher sensitivity, but a non-statistically lower specificity, than did the two other models. The hierarchical Gaussian process model also identified different sets of relevant features to detect COVID-19 between younger and older subgroups, and between health-care workers and non-health-care workers. When used during different pandemic periods, the model was robust to changes in populations. Interpretation Early detection of SARS-CoV-2 infection is feasible with our model. Such early detection is crucial to contain the spread of COVID-19 and efficiently allocate medical resources. Funding ZOE, the UK Government Department of Health and Social Care, the Wellcome Trust, the UK Engineering and Physical Sciences Research Council, the UK National Institute for Health Research, the UK Medical Research Council, the British Heart Foundation, the Alzheimer’s Society, the Chronic Disease Research Foundation, and the Massachusetts Consortium on Pathogen Readiness