Machine Learning Optimization of p-Type Transparent Conducting Films

p-Type transparent conducting materials (p-TCMs) are important components of optoelectronic devices including solar cells, photodetectors, displays, and flexible sensors. Cu-Zn-S thin films prepared by chemical bath deposition (CBD) can have both high transparency in the visible range (>80%) as well as excellent hole conductivity (>1000 S cm-1). However, the interplay between the deposition parameters in the CBD process (metal and sulfur precursor concentrations, temperature, pH, complexing agents, etc.) creates a multidimensional parameter space such that optimization for a specific application is challenging and time-consuming. Here we show that strategic design of experiment combined with machine learning (ML) allows for the efficient optimization of p-TCM performance. The approach is guided by a figure of merit (FOM) calculated from the film conductivity and optical transmission in the desired spectral range. A specific example is shown using two steps of optimization using a selected subset of four experimental CBD factors. The ML model is based on support vector regression employing a radial basis function as the kernel function. 10-fold cross-validation was performed to mitigate overfitting. After the first round of optimization, predicted areas in the parameter space with maximal FOMs were selected for a second round of optimization. Films with optimal FOMs were incorporated into heterojunction solar cells and transparent photodiodes. The optimization approach shown here will be generally applicable to any materials synthesis process with multiple parameters

Universal Vector-Scalar Potential Framework for Inhomogeneous Electromagnetic System and Its Application in Semiclassical Quantum Electromagnetics

In this work, numerical solution to a general electromagnetic (EM) system is studied using a formalism based on the formulas for the E-B-A-φ formulas with different gauge conditions. The finite-difference time-domain (FDTD) method is employed to discretize these formulas. In addition, the convolutional perfectly matched layer (CPML) technique is successfully applied to absorb outgoing scattered waves described by the proposed formulas. The gauge invariance of EM fields in inhomogeneous environment is demonstrated by numerical examples. Moreover, the proposed EM framework integrated with the Schrödinger equation is introduced to investigate the mesoscopic phenomenon for light-matter interaction, which is useful to design laser pulses for controlling discrete quantum states. The work offers a simple and general numerical EM framework, which is essential to bridge the classical EM and quantum mechanical systems

Return to fertility after extended chemical castration with a GnRH antagonist

BACKGROUND: Antagonistic analogues of GnRH for the treatment of prostate cancer may be used clinically in persons for whom return to fertility after such treatment is important or desirable. The purpose of this study was, therefore, to evaluate the effects of a long term treatment with orntide, a GnRH antagonist, on testosterone levels and fertility in male rats. METHODS: Two groups of male rats received either 120-day orntide microspheres (8.8 mg orntide/kg/120 days) or vehicle alone (control group). Serum orntide and testosterone levels in both groups were monitored at certain intervals for 9 months from the initiation of treatment. After recovery of normal serum testosterone levels in the treated animals, each rat was housed with two proven breeder, but drug-naive, females. RESULTS: All mates of treated rats achieved pregnancy as rapidly as the mates of control rats although two of the control rats did not sire a litter with either female and one sired only one litter. The mean size of the litters of treated (12.3 offspring per litter) and control (10.6 offspring per litter) were similar. All offspring were grossly normal morphologically and behaviorally during the time to weaning. CONCLUSIONS: These results suggest that lack of fertility due to testosterone suppression is reversible after cessation of treatment with this GnRH antagonist

ERα inhibits epithelial-mesenchymal transition by suppressing Bmi1 in breast cancer

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ERα inhibits epithelial-mesenchymal transition by suppressing Bmi1 in breast cancer

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Comparison of the effects of pulmonary and extra-pulmonary symptoms on health-related quality of life in patients with severe asthma

Objectives To survey the frequency of extra-pulmonary symptoms reported by a sample of patients with severe asthma, their contribution to quality of life and relationship to treatment pathways. Methods Consenting patients (N = 100) attending a severe asthma clinic completed questionnaire measures of extra-pulmonary symptoms (the General symptom Questionnaire, GSQ), pulmonary symptoms (Asthma Control Test, ACT), quality of life (the Severe Asthma Questionnaire, SAQ) and health status (EQ-5D-5L). Results A median of 21 extra-pulmonary symptoms were reported per week. GSQ correlated -0.65 with the ACT and 0.69 with the SAQ. Linear regression showed that both the ACT and GSQ were significant predictors of SAQ mean score, p < 0.001. In patients not receiving biologics, those with high cumulative OCS exposure (≥1120mg per year) had significantly worse scores (p < 0.05) on all questionnaires except the ACT and GSQ compared to those with low cumulative OCS exposure. Discussion Extra-pulmonary symptoms were common in this sample of people with severe asthma. Extra-pulmonary and pulmonary symptoms contribute equal variance to the score of HRQoL, showing that they are equally important contributors to patients’ experience of severe asthma. Extra-pulmonary symptoms are often overlooked in clinical medicine and in measures of quality of life. Participants receiving biologic treatments had lower extra-pulmonary symptoms possibly indicating that biologics reduce systemic symptoms more effectively than other treatments

Real-time Embedded Person Detection and Tracking for Shopping Behaviour Analysis

Shopping behaviour analysis through counting and tracking of people in shop-like environments offers valuable information for store operators and provides key insights in the stores layout (e.g. frequently visited spots). Instead of using extra staff for this, automated on-premise solutions are preferred. These automated systems should be cost-effective, preferably on lightweight embedded hardware, work in very challenging situations (e.g. handling occlusions) and preferably work real-time. We solve this challenge by implementing a real-time TensorRT optimized YOLOv3-based pedestrian detector, on a Jetson TX2 hardware platform. By combining the detector with a sparse optical flow tracker we assign a unique ID to each customer and tackle the problem of loosing partially occluded customers. Our detector-tracker based solution achieves an average precision of 81.59% at a processing speed of 10 FPS. Besides valuable statistics, heat maps of frequently visited spots are extracted and used as an overlay on the video stream

The role of childhood social position in adult type 2 diabetes: Evidence from the English Longitudinal Study of Ageing

Copyright @ 2014 Pikhartova et al. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.This article has been made available through the Brunel Open Access Publishing Fund.Background: Socioeconomic circumstances in childhood and early adulthood may influence the later onset of chronic disease, although such research is limited for type 2 diabetes and its risk factors at the different stages of life. The main aim of the present study is to examine the role of childhood social position and later inflammatory markers and health behaviours in developing type 2 diabetes at older ages using a pathway analytic approach. Methods. Data on childhood and adult life circumstances of 2,994 men and 4,021 women from English Longitudinal Study of Ageing (ELSA) were used to evaluate their association with diabetes at age 50 years and more. The cases of diabetes were based on having increased blood levels of glycated haemoglobin and/or self-reported medication for diabetes and/or being diagnosed with type 2 diabetes. Father's job when ELSA participants were aged 14 years was used as the measure of childhood social position. Current social characteristics, health behaviours and inflammatory biomarkers were used as potential mediators in the statistical analysis to assess direct and indirect effects of childhood circumstances on diabetes in later life. Results: 12.6 per cent of participants were classified as having diabetes. A disadvantaged social position in childhood, as measured by father's manual occupation, was associated at conventional levels of statistical significance with an increased risk of type 2 diabetes in adulthood, both directly and indirectly through inflammation, adulthood social position and a risk score constructed from adult health behaviours including tobacco smoking and limited physical activity. The direct effect of childhood social position was reduced by mediation analysis (standardised coefficient decreased from 0.089 to 0.043) but remained statistically significant (p = 0.035). All three indirect pathways made a statistically significantly contribution to the overall effect of childhood social position on adulthood type 2 diabetes. Conclusions: Childhood social position influences adult diabetes directly and indirectly through inflammatory markers, adulthood social position and adult health behaviours. © 2014Pikhartova et al.; licensee BioMed Central Ltd.Economic and Social Research Council-funded International Centre for Life Course Studies in Society and Health (RES-596-28-0001)

Estimating the Relevance of World Disturbances to Explain Savings, Interference and Long-Term Motor Adaptation Effects

Recent studies suggest that motor adaptation is the result of multiple, perhaps linear processes each with distinct time scales. While these models are consistent with some motor phenomena, they can neither explain the relatively fast re-adaptation after a long washout period, nor savings on a subsequent day. Here we examined if these effects can be explained if we assume that the CNS stores and retrieves movement parameters based on their possible relevance. We formalize this idea with a model that infers not only the sources of potential motor errors, but also their relevance to the current motor circumstances. In our model adaptation is the process of re-estimating parameters that represent the body and the world. The likelihood of a world parameter being relevant is then based on the mismatch between an observed movement and that predicted when not compensating for the estimated world disturbance. As such, adapting to large motor errors in a laboratory setting should alert subjects that disturbances are being imposed on them, even after motor performance has returned to baseline. Estimates of this external disturbance should be relevant both now and in future laboratory settings. Estimated properties of our bodies on the other hand should always be relevant. Our model demonstrates savings, interference, spontaneous rebound and differences between adaptation to sudden and gradual disturbances. We suggest that many issues concerning savings and interference can be understood when adaptation is conditioned on the relevance of parameters