Constraining the epoch of reionization with the variance statistic: simulations of the LOFAR case

Several experiments are underway to detect the cosmic redshifted 21-cm signal from neutral hydrogen from the Epoch of Reionization (EoR). Due to their very low signal-to-noise ratio, these observations aim for a statistical detection of the signal by measuring its power spectrum. We investigate the extraction of the variance of the signal as a first step towards detecting and constraining the global history of the EoR. Signal variance is the integral of the signal's power spectrum, and it is expected to be measured with a high significance. We demonstrate this through results from a simulation and parameter estimation pipeline developed for the Low Frequency Array (LOFAR)-EoR experiment. We show that LOFAR should be able to detect the EoR in 600 hours of integration using the variance statistic. Additionally, the redshift ($z_r$) and duration ($\Delta z$) of reionization can be constrained assuming a parametrization. We use an EoR simulation of $z_r = 7.68$ and $\Delta z = 0.43$ to test the pipeline. We are able to detect the simulated signal with a significance of 4 standard deviations and extract the EoR parameters as $z_r = 7.72^{+0.37}_{-0.18}$ and $\Delta z = 0.53^{+0.12}_{-0.23}$ in 600 hours, assuming that systematic errors can be adequately controlled. We further show that the significance of detection and constraints on EoR parameters can be improved by measuring the cross-variance of the signal by cross-correlating consecutive redshift bins.Comment: 13 pages, 14 figures, Accepted for publication in MNRA

Examining the Social Determinants of Health in Urban Communities: A Comparative Analysis

This comparative analysis investigates the social determinants of health (SDOH) in urban communities, aiming to discern disparities and inform targeted interventions and policies. With a focus on three key determinants socioeconomic status, housing and neighborhoods, and access to healthcare the study examines selected urban communities to illuminate the intricacies of health disparities within these contexts. The paper commences with an exploration of the background and significance of SDOH, emphasizing the crucial role they play in shaping health outcomes. The literature review provides a comprehensive overview of SDOH, offering insights into historical perspectives and unique challenges faced by urban communities.The methodology section outlines the criteria for selecting urban communities, the sources of data, and the ethical considerations guiding the research. A comparative framework is established, incorporating metrics such as income disparities, educational attainment, housing quality, neighborhood environments, and access to healthcare facilities. The analysis of these determinants reveals patterns, trends, and significant disparities among the selected urban communities, shedding light on the multifaceted nature of health inequalities.The findings section summarizes the key results, emphasizing the implications for public health. Policy recommendations and targeted interventions are discussed, emphasizing the importance of addressing SDOH to enhance overall community well-being. This comparative analysis underscores the imperative of considering SDOH in urban contexts and provides a foundation for future research and action. By delving into the intricacies of health disparities, this study contributes valuable insights to the ongoing discourse on public health, urging a comprehensive and nuanced approach to address the root causes of health inequities in urban communities

A machine learning approach to automate microinfarct and microhemorrhage screening in hematoxylin and eosin-stained human brain tissues

Microinfarcts and microhemorrhages are characteristic lesions of cerebrovascular disease. Although multiple studies have been published, there is no one universal standard criteria for the neuropathological assessment of cerebrovascular disease. In this study, we propose a novel application of machine learning in the automated screening of microinfarcts and microhemorrhages. Utilizing whole slide images (WSIs) from postmortem human brain samples, we adapted a patch-based pipeline with convolutional neural networks. Our cohort consisted of 22 cases from the University of California Davis Alzheimer's Disease Research Center brain bank with hematoxylin and eosin-stained formalin-fixed, paraffin-embedded sections across 3 anatomical areas: frontal, parietal, and occipital lobes (40 WSIs with microinfarcts and/or microhemorrhages, 26 without). We propose a multiple field-of-view prediction step to mitigate false positives. We report screening performance (ie, the ability to distinguish microinfarct/microhemorrhage-positive from microinfarct/microhemorrhage-negative WSIs), and detection performance (ie, the ability to localize the affected regions within a WSI). Our proposed approach improved detection precision and screening accuracy by reducing false positives thereby achieving 100% screening accuracy. Although this sample size is small, this pipeline provides a proof-of-concept for high efficacy in screening for characteristic brain changes of cerebrovascular disease to aid in screening of microinfarcts/microhemorrhages at the WSI level

Analysis and Modeling of Human Body When Exposed to Automotive Vehicle

Vibration is one of the important considerations in design. Nowadays, almost every family has the car. So, it becomes most important to study the vehicle vibrations. Analysis of human body physical model experimentally when situated in automotive vehicle. The model fabrication is done on the basis of comparing real human body parameters with human physical models used in the ISO 10068:2012 standard. This article revealed effect of vibration transferring to the specific parts of human body due to vibration transferring from Seat to Height (STH) and from Hands on steering. The focus of the present study was to determine the vibration output from fabricated model. The vibrations as input to the model are from automotive vehicles. The input verses output vibration characteristics will be useful to study effects of vibration on human health. The human body is considered as a simple spring, mass, damper system for analysis. This multi body model representative of the automotive postures found in the literature were investigated, one with and the other without a backrest support. The model was modified to suitably represent the different automotive postures with and without backrest supports, and validated by various experimental data from the published literature pertaining to the same postural conditions on the basis of the analytical study and the experimental

Co-rotating twin screw process for continuous manufacturing of solid crystal suspension: A promising strategy to enhance the solubility, permeation and oral bioavailability of Carvedilol [version 3; peer review: 1 approved, 2 approved with reservations]

Background In the current work, co-rotating twin-screw processor (TSP) was utilized to formulate solid crystal suspension (SCS) of carvedilol (CAR) for enhancing its solubility, dissolution rate, permeation and bioavailability using mannitol as a hydrophilic carrier. Methods In-silico molecular dynamics (MD) studies were done to simulate the interaction of CAR with mannitol at different kneading zone temperatures (KZT). Based on these studies, the optimal CAR: mannitol ratios and the kneading zone temperatures for CAR solubility enhancement were assessed. The CAR-SCS was optimized utilizing Design-of-Experiments (DoE) methodology using the Box-Behnken design. Saturation solubility studies and in vitro dissolution studies were performed for all the formulations. Physicochemical characterization was performed using differential scanning calorimetry , Fourier transform infrared spectroscopy, X-ray diffraction studies, and Raman spectroscopy analysis. Ex vivo permeation studies and in vivo pharmacokinetic studies for the CAR-SCS were performed. Stability studies were performed for the DoE-optimized CAR-SCS at accelerated stability conditions at 40 ºC/ 75% RH for three months. Results Experimentally, the formulation with CAR: mannitol ratio of 20:80, prepared using a KZT of 120 ºC at 100 rpm screw speed showed the highest solubility enhancement accounting for 50-fold compared to the plain CAR. Physicochemical characterization confirmed the crystalline state of DoE-optimized CAR-SCS. In-vitro dissolution studies indicated a 6.03-fold and 3.40-fold enhancement in the dissolution rate of optimized CAR-SCS in pH 1.2 HCl solution and phosphate buffer pH 6.8, respectively, as compared to the pure CAR. The enhanced efficacy of the optimized CAR-SCS was indicated in the ex vivo and in vivo pharmacokinetic studies wherein the apparent permeability was enhanced 1.84-fold and bioavailability enhanced 1.50-folds compared to the plain CAR. The stability studies showed good stability concerning the drug content. Conclusions TSP technology could be utilized to enhance the solubility, bioavailability and permeation of poor soluble CAR by preparing the SCS

Applying machine learning to assist in the morphometric assessment of brain arteriolosclerosis through automation

Objective quantification of brain arteriolosclerosis remains an area of ongoing refinement in neuropathology, with current methods primarily utilizing semi-quantitative scales completed through manual histological examination. These approaches offer modest inter-rater reliability and do not provide precise quantitative metrics. To address this gap, we present a prototype end-to-end machine learning (ML)-based algorithm, Arteriolosclerosis Segmentation (ArtSeg), followed by Vascular Morphometry (VasMorph) – to assist persons in the morphometric analysis of arteriolosclerotic vessels on whole slide images (WSIs). We digitized hematoxylin and eosin-stained glass slides (13 participants, total 42 WSIs) of human brain frontal or occipital lobe cortical and/or periventricular white matter collected from three brain banks (University of California, Davis, Irvine, and Los Angeles Alzheimer’s Disease Research Centers). ArtSeg comprises three ML models for blood vessel detection, arteriolosclerosis classification, and segmentation of arteriolosclerotic vessel walls and lumens. For blood vessel detection, ArtSeg achieved area under the receiver operating characteristic curve (AUC-ROC) values of 0.79 (internal hold-out testing) and 0.77 (external testing), Dice scores of 0.56 (internal hold-out) and 0.74 (external), and Hausdorff distances of 2.53 (internal hold-out) and 2.15 (external). Arteriolosclerosis classification demonstrated accuracies of 0.94 (mean, 3-fold cross-validation), 0.86 (internal hold-out), and 0.77 (external), alongside AUC-ROC values of 0.69 (mean, 3-fold cross-validation), 0.87 (internal hold-out), and 0.83 (external). For arteriolosclerotic vessel segmentation, ArtSeg yielded Dice scores of 0.68 (mean, 3-fold cross-validation), 0.73 (internal hold-out), and 0.71 (external); Hausdorff distances of 7.63 (mean, 3-fold cross-validation), 6.93 (internal hold-out), and 7.80 (external); and AUC-ROC values of 0.90 (mean, 3-fold cross-validation), 0.92 (internal hold-out), and 0.87 (external). VasMorph successfully derived sclerotic indices, vessel wall thicknesses, and vessel wall to lumen area ratios from ArtSeg-segmented vessels, producing results comparable to expert assessment. This integrated approach shows promise as an assistive tool to enhance current neuropathological evaluation of brain arteriolosclerosis, offering potential for improved inter-rater reliability and quantification

Foreign ownership, bank information environments, and the international mobility of corporate governance

This paper investigates how foreign ownership shapes bank information environments. Using a sample of listed banks from 60 countries over 1997–2012, we show that foreign ownership is significantly associated with greater (lower) informativeness (synchronicity) in bank stock prices. We also find that stock returns of foreign-owned banks reflect more information about future earnings. In addition, the positive association between price informativeness and foreign ownership is stronger for foreign-owned banks in countries with stronger governance, stronger banking supervision, and lower monitoring costs. Overall, our evidence suggests that foreign ownership reduces bank opacity by exporting governance, yielding important implications for regulators and governments

The Role of Information and Financial Reporting in Corporate Governance and Debt Contracting

We review recent literature on the role of financial reporting transparency in reducing governance-related agency conflicts among managers, directors, and shareholders, as well as in reducing agency conflicts between shareholders and creditors, and offer researchers some suggested avenues for future research. Key themes include the endogenous nature of debt contracts and governance mechanisms with respect to information asymmetry between contracting parties, the heterogeneous nature of the informational demands of contracting parties, and the heterogeneous nature of the resulting governance and debt contracts. We also emphasize the role of a commitment to financial reporting transparency in facilitating informal multiperiod contracts among managers, directors, shareholders, and creditors