A V-Diagram for the Design of Integrated Health Management for Unmanned Aerial Systems

Designing Integrated Vehicle Health Management (IVHM) for Unmanned Aerial Systems (UAS) is inherently complex. UAS are a system of systems (SoS) and IVHM is a product-service, thus the designer has to take into account many factors, such as: the design of the other systems of the UAS (e.g. engines, structure, communications), the split of functions between elements of the UAS, the intended operation/mission of the UAS, the cost verses benefit of monitoring a system/component/part, different techniques for monitoring the health of the UAS, optimizing the health of the fleet and not just the individual UAS, amongst others. The design of IVHM cannot sit alongside, or after, the design of UAS, but itself be integrated into the overall design to maximize IVHM’s potential. Many different methods exist to help design complex products and manage the process. One method used is the V-diagram which is based on three concepts: decomposition & definition; integration & testing; and verification & validation. This paper adapts the V-diagram so that it can be used for designing IVHM for UAS. The adapted v-diagram splits into different tracks for the different system elements of the UAS and responses to health states (decomposition and definition). These tracks are then combined into an overall IVHM provision for the UAS (integration and testing), which can be verified and validated. The stages of the adapted V-diagram can easily be aligned with the stages of the V-diagram being used to design the UAS bringing the design of the IVHM in step with the overall design process. The adapted V-diagram also allows the design IVHM for a UAS to be broken down in to smaller tasks which can be assigned to people/teams with the relevant competencies. The adapted V-diagram could also be used to design IVHM for other SoS and other vehicles or products

Inferring meta-covariates in classification

This paper develops an alternative method for gene selection that combines model based clustering and binary classification. By averaging the covariates within the clusters obtained from model based clustering, we define “meta-covariates” and use them to build a probit regression model, thereby selecting clusters of similarly behaving genes, aiding interpretation. This simultaneous learning task is accomplished by an EM algorithm that optimises a single likelihood function which rewards good performance at both classification and clustering. We explore the performance of our methodology on a well known leukaemia dataset and use the Gene Ontology to interpret our results

Subthreshold characteristics of pentacene field-effect transistors influenced by grain boundaries.

Grain boundaries in polycrystalline pentacene films significantly affect the electrical characteristics of pentacene field-effect transistors (FETs). Upon reversal of the gate voltage sweep direction, pentacene FETs exhibited hysteretic behaviours in the subthreshold region, which was more pronounced for the FET having smaller pentacene grains. No shift in the flat-band voltage of the metal-insulator-semiconductor capacitor elucidates that the observed hysteresis was mainly caused by the influence of localized trap states existing at pentacene grain boundaries. From the results of continuous on/off switching operation of the pentacene FETs, hole depletion during the off period is found to be limited by pentacene grain boundaries. It is suggested that the polycrystalline nature of a pentacene film plays an important role on the dynamic characteristics of pentacene FETs

Primal-Dual 2-Approximation Algorithm for the Monotonic Multiple Depot Heterogeneous Traveling Salesman Problem

We study a Multiple Depot Heterogeneous Traveling Salesman Problem (MDHTSP) where the cost of the traveling between any two targets depends on the type of the vehicle. The travel costs are assumed to be symmetric, satisfy the triangle inequality, and are monotonic, i.e., the travel costs between any two targets monotonically increases with the index of the vehicles. Exploiting the monotonic structure of the travel costs, we present a 2-approximation algorithm based on the primal-dual method

Unusual Higgs or Supersymmetry from Natural Electroweak Symmetry Breaking

This review provides an elementary discussion of electroweak symmetry breaking in the minimal and the next-to-minimal supersymmetric models with the focus on the fine-tuning problem -- the tension between natural electroweak symmetry breaking and the direct search limit on the Higgs boson mass. Two generic solutions of the fine-tuning problem are discussed in detail: models with unusual Higgs decays; and models with unusual pattern of soft supersymmetry breaking parameters.Comment: 23 pages, 6 figures; invited review by MPL

Definition of valid proteomic biomarkers: a bayesian solution

Clinical proteomics is suffering from high hopes generated by reports on apparent biomarkers, most of which could not be later substantiated via validation. This has brought into focus the need for improved methods of finding a panel of clearly defined biomarkers. To examine this problem, urinary proteome data was collected from healthy adult males and females, and analysed to find biomarkers that differentiated between genders. We believe that models that incorporate sparsity in terms of variables are desirable for biomarker selection, as proteomics data typically contains a huge number of variables (peptides) and few samples making the selection process potentially unstable. This suggests the application of a two-level hierarchical Bayesian probit regression model for variable selection which assumes a prior that favours sparseness. The classification performance of this method is shown to improve that of the Probabilistic K-Nearest Neighbour model

Magnitude of the Difference Between Clinic and Ambulatory Blood Pressures and Risk of Adverse Outcomes in Patients With Chronic Kidney Disease.

Background Obtaining 24-hour ambulatory blood pressure ( BP ) is recommended for the detection of masked or white-coat hypertension. Our objective was to determine whether the magnitude of the difference between ambulatory and clinic BP s has prognostic implications. Methods and Results We included 610 participants of the AASK (African American Study of Kidney Disease and Hypertension) Cohort Study who had clinic and ambulatory BPs performed in close proximity in time. We used Cox models to determine the association between the absolute systolic BP ( SBP ) difference between clinic and awake ambulatory BPs (primary predictor) and death and end-stage renal disease. Of 610 AASK Cohort Study participants, 200 (32.8%) died during a median follow-up of 9.9 years; 178 (29.2%) developed end-stage renal disease. There was a U-shaped association between the clinic and ambulatory SBP difference with risk of death, but not end-stage renal disease. A 5- to <10-mm Hg higher clinic versus awake SBP (white-coat effect) was associated with a trend toward higher (adjusted) mortality risk (adjusted hazard ratio, 1.84; 95% CI, 0.94-3.56) compared with a 0- to <5-mm Hg clinic-awake SBP difference (reference group). A ≥10-mm Hg clinic-awake SBP difference was associated with even higher mortality risk (adjusted hazard ratio, 2.31; 95% CI, 1.27-4.22). A ≥-5-mm Hg clinic-awake SBP difference was also associated with higher mortality (adjusted hazard ratio, 1.82; 95% CI, 1.05-3.15) compared with the reference group. Conclusions A U-shaped association exists between the magnitude of the difference between clinic and ambulatory SBP and mortality. Higher clinic versus ambulatory BPs (as in white-coat effect) may be associated with higher risk of death in black patients with chronic kidney disease

Increased Risk of Childhood Brain Tumors Among Children Whose Parents Had Farm-Related Pesticide Exposures During Pregnancy

Malignant brain tumors rank second in both incidence and mortality by cancer in children, and they are the leading cause of cancer death in children. Relatively little is known about the etiology of childhood brain tumor (CBT). While there are several studies which link pesticide exposure to increased risk of CBT, findings have been inconsistent. We performed a meta-analysis on 15 published epidemiological studies to test that in utero exposure to pesticides may be involved in the development of brain cancer in children. Meta-analysis was performed using the general variance-based method and homogeneity was tested by means of the Q statistic. Summary relative risk (RR) estimates were calculated for childhood brain cancer from (1) paternal exposure to pesticides prior to conception, (2) both maternal and paternal exposure to pesticides during pregnancy, (3) maternal exposure during pregnancy to: (a) agricultural and (b) non-agricultural activities, and (4) childhood exposure to: (a) agricultural and (b) nonagricultural activities up to date of diagnosis with CBT. The comparative toxicogenomics database (CTD) was used to identify gene-pesticide-CBT interactions. Findings of meta-analyses revealed a significantly increased risk of CBT among children whose mothers had farm-related exposures during pregnancy (RR=1.48, 95% CI=1.18–1.84). A dose response was recognized when this risk estimate was compared to those for risk of CBT from maternal exposure to non-agricultural pesticides (e.g., home extermination, pest strips) during pregnancy (RR=1.36, 1.10–1.68), and risk of CBT among children exposed to agricultural activities (RR=1.32, 1.04–1.67). Three studies combined for the paternal exposure to pesticides during preconception produced a calculated summary risk estimate of odds ratio (OR) = 2.29 (95% CI: 1.39–3.78). Meta-analysis of five studies of paternal exposure to pesticides during pregnancy produced a final calculated summary risk estimate of OR = 1.63 (95% CI: 1.16–2.31). The search of the CTD databases revealed association between herbicide and astrocytoma and more than 300 genes are altered by exposure to herbicide, fungicide, insecticide or pesticides. In summary, comparing results from our categories of exposure, preconception and pregnancy exposure estimates were slightly higher than childhood exposure estimates, paternal exposures produced slightly higher risk estimates compared to maternal exposures, agricultural exposures produced slightly higher risk estimates compared to non-agricultural exposures and CTD search revealed potential genes-pesticides-astrocytoma interactions. Based on the collective results of these meta-analyses, it appears that pesticide exposure may increase risk of CBT, with preconception and prenatal exposures being especially important factors in increasing risk of its development. Interestingly, paternal exposure may be as important, if not more important than maternal exposures, particularly during the preconception period. Whether this is a result of paternal exposures being more prevalent than maternal exposures or the consequence of a biological process, is a question that deserves further attention in future investigations of CBT etiology

The Effect of the Uniform Bar Examination on Admissions, Diversity, Affordability, and Employment across Law Schools in the United States

The Uniform Bar Examination (UBE), first implemented in February 2011 in Missouri and North Dakota, is a multijurisdictional or cross-state test designed to assess a minimum shared core of legal knowledge and lawyering skills. Since its implementation, UBE has now reached 37 states and territories, including the District of Columbia. Despite this prevalence, no empirical evidence exists regarding its effects on law schools’ admissions, diversity, affordability, and employment mobility of law students and graduates or of its effects on law schools’ application volumes or average bar passage rates. This study addresses this gap by providing a comprehensive examination of the effects of UBE adoption. Specifically, we apply rigorous quasi-experimental and causal-inference methods to a law-school level dataset to test whether UBE adoption influenced admissions, enrollment, affordability, degree production, bar passage rates, and employment mobility for law schools in UBE states. Our findings indicate that institutions located in states participating in UBE (compared to institutions located in states where no UBE has been implemented) realized higher applications (nearly 9% increase) and higher enrollments (reaching increases over 6% in total JD enrollments). We also found that these increases were driven predominantly by White student enrollments and women enrollees. With respect to affordability, no changes were observed in neither tuition increases and net price changes. Despite increase in enrollment, we found no evidence of increases in neither degree production nor in Bar passing rates. Based on this findings, we can conclude that UBE has had an effect in applications and enrollment, but if UBE aims to affect the diversification of the law profession, this program alone may be falling short in expanding access for minoritized students