Copy number analysis of the low-copy repeats at the primate NPHP1 locus by array comparative genomic hybridization

AbstractArray comparative genomic hybridization (aCGH) has been widely used to detect copy number variants (CNVs) in both research and clinical settings. A customizable aCGH platform may greatly facilitate copy number analyses in genomic regions with higher-order complexity, such as low-copy repeats (LCRs). Here we present the aCGH analyses focusing on the 45kb LCRs [1] at the NPHP1 region with diverse copy numbers in humans. Also, the interspecies aCGH analysis comparing human and nonhuman primates revealed dynamic copy number transitions of the human 45kb LCR orthologues during primate evolution and therefore shed light on the origin of complexity at this locus. The original aCGH data are available at GEO under GSE73962

Skin Lesion Analyser: An Efficient Seven-Way Multi-Class Skin Cancer Classification Using MobileNet

Skin cancer, a major form of cancer, is a critical public health problem with 123,000 newly diagnosed melanoma cases and between 2 and 3 million non-melanoma cases worldwide each year. The leading cause of skin cancer is high exposure of skin cells to UV radiation, which can damage the DNA inside skin cells leading to uncontrolled growth of skin cells. Skin cancer is primarily diagnosed visually employing clinical screening, a biopsy, dermoscopic analysis, and histopathological examination. It has been demonstrated that the dermoscopic analysis in the hands of inexperienced dermatologists may cause a reduction in diagnostic accuracy. Early detection and screening of skin cancer have the potential to reduce mortality and morbidity. Previous studies have shown Deep Learning ability to perform better than human experts in several visual recognition tasks. In this paper, we propose an efficient seven-way automated multi-class skin cancer classification system having performance comparable with expert dermatologists. We used a pretrained MobileNet model to train over HAM10000 dataset using transfer learning. The model classifies skin lesion image with a categorical accuracy of 83.1 percent, top2 accuracy of 91.36 percent and top3 accuracy of 95.34 percent. The weighted average of precision, recall, and f1-score were found to be 0.89, 0.83, and 0.83 respectively. The model has been deployed as a web application for public use at (https://saketchaturvedi.github.io). This fast, expansible method holds the potential for substantial clinical impact, including broadening the scope of primary care practice and augmenting clinical decision-making for dermatology specialists.Comment: This is a pre-copyedited version of a contribution published in Advances in Intelligent Systems and Computing, Hassanien A., Bhatnagar R., Darwish A. (eds) published by Chaturvedi S.S., Gupta K., Prasad P.S. The definitive authentication version is available online via https://doi.org/10.1007/978-981-15-3383-9_1

Enabling the Evaluation of Driver Physiology Via Vehicle Dynamics

Driving is a daily routine for many individuals across the globe. This paper presents the configuration and methodologies used to transform a vehicle into a connected ecosystem capable of assessing driver physiology. We integrated an array of commercial sensors from the automotive and digital health sectors along with driver inputs from the vehicle itself. This amalgamation of sensors allows for meticulous recording of the external conditions and driving maneuvers. These data streams are processed to extract key parameters, providing insights into driver behavior in relation to their external environment and illuminating vital physiological responses. This innovative driver evaluation system holds the potential to amplify road safety. Moreover, when paired with data from conventional health settings, it may enhance early detection of health-related complications.Comment: 7 pages, 11 figures, 2023 IEEE International Conference on Digital Health (ICDH

A Best Practice Guide for Community Based Participatory Research (CBPR) in Transgender and Nonbinary (TNB) Health

This guide describes best practices for community-based participatory research (CBPR) with transgender and nonbinary (TNB) communities. We hope it will be a resource for people involved or interested in TNB health research and will make CBPR approachable, actionable and compelling. We anticipate readers of this guide will hold varying identities, experiences, and expertise, including their understanding of or familiarity with research and TNB communities. It is important to explicitly recognize that there are TNB people of varying cultural/language backgrounds already doing this work and to avoid reinforcing assumptions that researchers are not TNB, Black, Indigenous, people of color (BIPOC), or TNB BIPOC. While we believe the best people to initiate and practice TNB health CBPR are TNB people, we also recognize that the majority of people involved in TNB health research are not TNB themselves. This guide is designed to offer insight to all audiences. Our goal is to provide an overview of themes we believe are important and best practices to collaboratively develop and carry-out research with TNB communities

Controlling the dopant profile for SRH suppression at low current densities in λ ≈ 1330 nm GaInAsP light-emitting diodes

The quantum efficiency of double hetero-junction light-emitting diodes (LEDs) can be significantly enhanced at low current density by tailoring the spatial profile of dopants to suppress Shockley–Read–Hall recombination. To demonstrate this effect, we model, design, grow, fabricate, and test a GaInAsP LED (λ≈ 1330 nm) with an unconventional dopant profile. Compared against that of our control design, which is a conventional n⁺-n-p⁺ double hetero-junction LED, the dopant profile near the n-p⁺ hetero-structure of the design displaces the built-in electric field in such a way that the J₀₂ space charge recombination current is suppressed. The design principle generalizes to other material systems and could be applicable to efforts to observe and exploit electro-luminescent refrigeration at practical power densities

Perpendicular Ion Heating by Low-Frequency Alfven-Wave Turbulence in the Solar Wind

We consider ion heating by turbulent Alfven waves (AWs) and kinetic Alfven waves (KAWs) with perpendicular wavelengths comparable to the ion gyroradius and frequencies smaller than the ion cyclotron frequency. When the turbulence amplitude exceeds a certain threshold, an ion's orbit becomes chaotic. The ion then interacts stochastically with the time-varying electrostatic potential, and the ion's energy undergoes a random walk. Using phenomenological arguments, we derive an analytic expression for the rates at which different ion species are heated, which we test by simulating test particles interacting with a spectrum of randomly phased AWs and KAWs. We find that the stochastic heating rate depends sensitively on the quantity epsilon = dv/vperp, where vperp is the component of the ion velocity perpendicular to the background magnetic field B0, and dv (dB) is the rms amplitude of the velocity (magnetic-field) fluctuations at the gyroradius scale. In the case of thermal protons, when epsilon << eps1, where eps1 is a constant, a proton's magnetic moment is nearly conserved and stochastic heating is extremely weak. However, when epsilon > eps1, the proton heating rate exceeds the cascade power that would be present in strong balanced KAW turbulence with the same value of dv, and magnetic-moment conservation is violated. For the random-phase waves in our test-particle simulations, eps1 is approximately 0.2. For protons in low-beta plasmas, epsilon is approximately dB/B0 divided by the square root of beta, and epsilon can exceed eps1 even when dB/B0 << eps1. At comparable temperatures, alpha particles and minor ions have larger values of epsilon than protons and are heated more efficiently as a result. We discuss the implications of our results for ion heating in coronal holes and the solar wind.Comment: 14 pages, 5 figures, submitted to Ap

Process dependent Sivers function and implications for single spin asymmetry in inclusive hadron production

We study the single transverse spin asymmetries in the single inclusive particle production within the framework of the generalized parton model (GPM). By carefully analyzing the initial- and final-state interactions, we include the process-dependence of the Sivers functions into the GPM formalism. The modified GPM formalism has a close connection with the collinear twist-3 approach. Within the new formalism, we make predictions for inclusive $\pi^0$ and direct photon productions at RHIC energies. We find the predictions are opposite to those in the conventional GPM approach.Comment: 12 pages, 5 figures, extended discussion on connection with twist three approach, references adde

Twist-three Fragmentation Function Contribution to the Single Spin Asymmetry in pp Collisions

We study the twist-three fragmentation function contribution to the single transverse spin asymmetries in inclusive hadron production in pp collisions, pp->h+X. In particular, we evaluate the so-called derivative contribution which dominates the spin asymmetry in the forward direction of the polarized proton. With certain parametrizations for the twist-three fragmentation function, we estimate its contribution to the asymmetry of pi0 production at RHIC energy. We find that the contribution is sizable and might be responsible for the big difference between the asymmetries in eta and pi0 productions observed by the STAR collaboration at RHIC.Comment: 10 pages, 3 ps figure