Miracle-dz/UniFAR-FTUs huggingface dataset:
The Association of Increased Oxidative Stress and Tumor Biomarkers Related to Polyaromatic Hydrocarbons Exposure for Different Occupational Workers in Makkah, Saudi Arabia

Introduction: Exposure to occupational polyaromatic hydrocarbons (PAHs) is correlated with several adverse effects on human health, including bladder, lung, and skin cancer. The correlation between PAH exposure and oxidative stress and tumor markers needs to be further explored. Therefore, we conducted this study to examine the effect of acute exposure to PAHs on oxidative stress and tumor marker levels in occupational workers during the Hajj season in Makkah. Methods: We conducted a cross-sectional study of 105 workers during Hajj; 60 workers were employed in the open air for ≥eight hours/day, exposed them to high levels of considerable traffic and huge crowds, and 45 workers served as our control group who were unexposed and working in a rural area. Using high-performance liquid chromatography, we analyzed participants' urinary 1-hydroxypyrene to determine PAH levels. Oxidative stress markers malondialdehyde (MDA), glutathione S-transferase (GST), and lactate dehydrogenase (LDH) were analyzed in serum using a spectrophotometer. The serum p53 and p21 proteins were analyzed using an enzyme-linked immunosorbent assay. We used IBM SPSS Statistics for Windows, Version 21.0 (IBM Corp., Armonk, NY, USA) to calculate multivariate logistic regression analysis for oxidative stress and tumor markers such as age, working period, and smoking status risk factors. Additionally, we evaluated associations between oxidative stress and tumor markers. Results: The mean levels of MDA, GST, and LDH were significantly elevated in exposed workers compared to the control group (p<.001). Also, p53 and p21 protein levels were significantly higher in the occupationally exposed group than in the unexposed control group (p<0.05). No significant correlation between age and increased levels of p53 and p21 was found. Conclusions: In our study, PAH exposure is significantly correlated with higher levels of oxidative stress and tumor marker levels in occupational workers. The evaluation of oxidative stress and tumor marker indicators can efficiently identify workers at high risk of PAH exposure and may assist in preventing future health concerns. More biomarkers should be included in other longitudinal studies to address exposure related to different health risks among workers, especially cancer risk. More prospective studies are required to validate diagnostic utilities and efficiencies of different biomarker combinations.
A theory for the origin of globular clusters

In the present theory for the origin of globular clusters during protogalaxy collapse, a thermal instability promotes the development of a two-phase structure in the gas in those cases where the cooling time is comparable to that of free fall. The hot component, which remains near the virial temperature, compresses the cold component into discrete clouds with temperatures near 10,000 K and mean densities of 1 to 10 solar masses/cu pc. These predictions are compared with the observed properties of globular clusters; satisfactory agreement is obtained. 57 references.
The effect of observation angles on facial age perceptions: A case study of Japanese women

Most conventional aging research has limited its approach concerning the head and face shape and skin condition to the frontal face. However, in our daily lives, we observe facial features from various angles, which may reveal or obscure aging features that could only be identified under limited conditions in the past. This study systematically investigates the effect of facial observation angles—specifically, of horizontal and vertical angles—on age impression. A total of 112 Japanese women aged 20–49 years participated as observers who evaluated the age impressions of 280 Japanese women aged 20–69 years. A two-way analysis of the variance of the age impression score was conducted for two factors: observation angle (five angles with yaw and pitch directions) and age group (five ages, from the 20s to the 60s). The results reveal that, as compared with frontal observation, the perceived age tended to decrease with the facial observation angles and that the effect of the angle on perceived age decreased with increasing age, especially for the profile face. Understanding the effect of the facial observation angle on age impression and clarifying the characteristics of the face and skin not perceived in the frontal face will provide useful knowledge to make people look youthful, look more beautiful, and be happier in all aspects of their lives.
Pharmacokinetics of hydrogen administered intraperitoneally as hydrogen-rich saline and its effect on ischemic neuronal cell death in the brain in gerbils

Intraperitoneal administration of hydrogen (H2)-containing saline inhibited neuronal cell death in ischemic stroke in a number of animal models, but it is unknown whether H2 is absorbed from the abdominal cavity into the blood and reaches the brain. In this study, we investigated whether intraperitoneal administration of saline containing H2 inhibits neuronal cell death caused by cerebral ischemia and measured the concentration of H2 in the carotid artery and inferior vena cava (IVC). Gerbils were subjected to transient unilateral cerebral ischemia twice, and saline or H2-rich saline was administered intraperitoneally three or seven times every 12 hours. We evaluated the number of apoptotic cells in the hippocampus and cerebral cortex on day 3 and the number of viable neurons in the hippocampus and cerebral cortex on day 7. In addition, a single dose of saline or H2-rich saline was administered intraperitoneally, and blood H2 levels in the carotid artery and IVC were measured. On day 3 of ischemia/reperfusion, the number of neurons undergoing apoptosis in the cortex was significantly lower in the H2-rich saline group than in the saline group, and on day 7, the number of viable neurons in the hippocampus and cerebral cortex was significantly higher in the H2-rich saline group. Intraperitoneal administration of H2-rich saline resulted in large increases in H2 concentration in the IVC ranging from 0.00183 mg/L (0.114%) to 0.00725 mg/L (0.453%). In contrast, carotid H2 concentrations remained in the range of 0.00008 mg/L (0.0049%) to 0.00023 (0.0146%). On average, H2 concentrations in carotid artery were 0.04 times lower than in IVC. These results indicate that intraperitoneal administration of H2-rich saline significantly suppresses neuronal cell death after cerebral ischemia, even though H2 hardly reaches the brain.
Bounds for quantities of interest and adaptivity in the element‐free Galerkin method

A novel approach to implicit residual‐type error estimation in mesh‐free methods and an adaptive refinement strategy are presented. This allows computing upper and lower bounds of the error in energy norm with the ultimate goal of obtaining bounds for outputs of interest. The proposed approach precludes the main drawbacks of standard residual‐type estimators circumventing the need of flux‐equilibration and resulting in a simple implementation that avoids integrals on edges/sides of a domain decomposition (mesh). This is especially interesting for mesh‐free methods. The adaptive strategy proposed leads to a fast convergence of the bounds to the desired precision. Copyright © 2008 John Wiley & Sons, Ltd.
Challenges in evaluating the accuracy of AI-containing digital triage systems: A systematic review

Introduction Patient-operated digital triage systems with AI components are becoming increasingly common. However, previous reviews have found a limited amount of research on such systems’ accuracy. This systematic review of the literature aimed to identify the main challenges in determining the accuracy of patient-operated digital AI-based triage systems. Methods A systematic review was designed and conducted in accordance with PRISMA guidelines in October 2021 using PubMed, Scopus and Web of Science. Articles were included if they assessed the accuracy of a patient-operated digital triage system that had an AI-component and could triage a general primary care population. Limitations and other pertinent data were extracted, synthesized and analysed. Risk of bias was not analysed as this review studied the included articles’ limitations (rather than results). Results were synthesized qualitatively using a thematic analysis. Results The search generated 76 articles and following exclusion 8 articles (6 primary articles and 2 reviews) were included in the analysis. Articles’ limitations were synthesized into three groups: epistemological, ontological and methodological limitations. Limitations varied with regards to intractability and the level to which they can be addressed through methodological choices. Certain methodological limitations related to testing triage systems using vignettes can be addressed through methodological adjustments, whereas epistemological and ontological limitations require that readers of such studies appraise the studies with limitations in mind. Discussion The reviewed literature highlights recurring limitations and challenges in studying the accuracy of patient-operated digital triage systems with AI components. Some of these challenges can be addressed through methodology whereas others are intrinsic to the area of inquiry and involve unavoidable trade-offs. Future studies should take these limitations in consideration in order to better address the current knowledge gaps in the literature.
Dynamic Image-Based Visual Servo Control Using Centroid and Optic Flow Features

This paper considers the question of designing a fully image-based visual servo control for a class of dynamic systems. The work is motivated by the ongoing development of image-based visual servo control of small aerial robotic vehicles. The kinematics and dynamics of a rigid-body dynamical system (such as a vehicle airframe) maneuvering over a flat target plane with observable features are expressed in terms of an unnormalized spherical centroid and an optic flow measurement. The image-plane dynamics with respect to force input are dependent on the height of the camera above the target plane. This dependence is compensated by introducing virtual height dynamics and adaptive estimation in the proposed control. A fully nonlinear adaptive control design is provided that ensures asymptotic stability of the closed-loop system for all feasible initial conditions. The choice of control gains is based on an analysis of the asymptotic dynamics of the system. Results from a realistic simulation are presented that demonstrate the performance of the closed-loop system. To the author's knowledge, this paper documents the first time that an image-based visual servo control has been proposed for a dynamic system using vision measurement for both position and velocity.
Book Reviews: Multivariate Statistics: A Practical Approach Bernhard Flury and Hans Riedwyl New York: Chapman and Hall, 1988. v + 296 pp

Given the plethora of multivariate statistics books available to the educational community, a natural question emerges: What can the educational researcher gain from this book? Although it has some distinguishing features, in many respects it falls short of the goal of providing a practical approach to the subject of multivariate statistics. My critique centers around the following three points: First, because of the choice of data used to illustrate the procedures, this book may not capture the interest of the educational community. Second, it is organized around a highly selected set of topics and, as such, is not representative of the domain of multivariate statistics. Finally, the treatment of topics is terse and incomplete.
Testing for a Unit Root in ARIMA Processes

A unit root has important long-run implications for many time series in economics and finance. This paper develops a unit-root test of an ARIMA(p−1, 1, q) with drift null process against a trend-stationary ARMA(p, q) alternative process, where the order of the time series is assumed known through previous statistical testing or relevant theory. This test uses a point-optimal test statistic, but it estimates the null and alternative variance-covariance matrices that are used in the test statistic. Consequently, this test approximates a point-optimal test. Simulations show that its small-sample size is close to the nominal test level for a variety of unit-root processes, that it has a robust power curve against a variety of stationary alternatives, that its combined small-sample size and power properties are highly competitive with previous unit-root tests, and that it is robust to conditional heteroskedasticity. An application to post-Second World War real per capita gross domestic product is provided.
Evidence for X-ray scattering by interstellar dust

X ray images of distant point sources obtained with the Einstein Observatory have been examined for the presence of halos produced by X-ray scattering from interstellar dust. Evidence for detection of dust halos has been obtained by comparing the apparent surface brightness in images of four low-latitude galactic center sources with the surface brightness predicted from the telescope point response function and the simultaneously measured source spectra. This evidence is considerably strengthened by the same comparison using images of two sources at higher galactic latitude, where the column density of dust is expected to be far lower. Simple assumptions indicate the observed scattering halos are consistent with production by the population of dust grains inferred from optical extinction measurements.
Equivariant $K$-theory of flag Bott manifolds of general Lie type

The aim of this paper is to describe the equivariant and ordinary Grothendieck ring and the equivariant and ordinary topological K -ring of ﬂag Bott manifolds of general Lie type. This will generalize the results on the equivariant and ordinary cohomology of ﬂag Bott manifolds of general Lie type due to Kaji
Effect of Contactor Area on the Vibrotactile Threshold

Vibrotactile thresholds were determined as a function of frequency, contactor configuration, and contactor area. It was found that contactor area is a more important stimulus parameter than the gradient or curvature of displacement. The absolute threshold for vibration seems to be independent of frequency when very small contactors are used and independent of area at low frequencies. For higher values of these parameters, it strongly depends on both. It seems reasonable to conclude that responses to mechanical displacement of the skin are mediated by more than one receptor system, although direct evidence is still lacking.
Heterogeneous Graph Contrastive Learning with Meta-path Contexts and Weighted Negative Samples

Heterogeneous graph contrastive learning has received wide attention recently. Some existing methods use meta-paths, which are sequences of object types that capture semantic relationships between objects, to construct contrastive views. However, most of them ignore the rich meta-path context information that describes how two objects are connected by meta-paths. On the other hand, they fail to distinguish hard negatives from false negatives, which could adversely aﬀect the model performance. To address the problems, we propose MEOW, a heterogeneous graph contrastive learning model that considers both meta-path contexts and weighted negative samples. Speciﬁcally, MEOW constructs a coarse view and a ﬁne-grained view for contrast. The former reﬂects which objects are connected by meta-paths, while the latter uses meta-path contexts and characterizes the details on how the objects are connected. We take node embeddings in the coarse view as anchors, and construct positive and negative samples from the ﬁne-grained view. Further, to distinguish hard negatives from false negatives, we learn weights of negative samples based on node clustering. We also use prototypical contrastive learning to pull close embeddings of nodes in the same cluster. Finally, we conduct extensive experiments to show the superiority of MEOW against other state-of-the-art methods.
Understanding Business Users' Data-Driven Decision-Making: Practices, Challenges, and Opportunities

Business users perform data analysis to inform decisions for improving business processes and outcomes despite having limited formal technical training. While earlier work has focused on data analysts' and data scientists' practices and challenges, little is known about business users' decision-making practices and how they incorporate data and visual analytics into their workflows. To address this gap, we first conduct an interview study with 22 business users to understand the general practices and challenges in their data-driven decision-making processes. We contribute an end-to-end model of business users' data-driven decision-making processes elaborating the tasks, tools, and challenges at each stage. We find that business users analyze data without relying on data analysts due to various practical constraints and considerations. However, their existing tools are inadequate, particularly in helping understand the relationship between data variables and business goals and facilitating the exploration of what-if scenarios. These findings suggest a need for advanced predictive and prescriptive analytics (PPA) tools to support what-if analysis. Motivated by this need, we perform a follow-up, task-based study to understand PPA's role and potential in business users' decision-making processes. We find that PPA helps improve efficiency and confidence in decision-making. However, business users also believe that PPA-powered what-if analysis tools are currently in their nascent stages and report improvements before fully integrating them into their decision-making processes. Building upon these findings, we discuss the opportunities and challenges in incorporating PPA into data-driven decision-making and its implications for future data and visual analytics systems.
End-to-End Application Cloning for Distributed Cloud Microservices with Ditto

The lack of representative, publicly-available cloud services has been a recurring problem in the architecture and systems communi-ties. While open-source benchmarks exist, they do not capture the full complexity of cloud services. Application cloning is a promising way to address this, however, prior work is limited to CPU-/cache-centric, single-node services, operating at user level. We present Ditto, an automated framework for cloning end-to-end cloud applications, both monolithic and microservices, which captures I/O and network activity, as well as kernel operations, in addition to application logic. Ditto takes a hierarchical approach to application cloning, starting with capturing the dependency graph across distributed services, to recreating each tier’s control/data flow, and finally generating system calls and assembly that mim-ics the individual applications. Ditto does not reveal the logic of the original application, facilitating publicly sharing clones of production services with hardware vendors, cloud providers, and the research community. We show that across a diverse set of single- and multi-tier applications, Ditto accurately captures their CPU and memory characteristics as well as their high-level performance metrics, is portable across platforms, and facilitates a wide range of system studies.
Timing jitter removers of photon detectors

Among various performances of photon detectors, the timing jitter is difﬁ-cult to improve because of its trade-offs with other important performances such as detection efﬁciency. Such trade-offs have been an issue in applications, especially for high-purity non-Gaussian-state generation necessary in optical quantum computation. Here, we introduce a method using an external fast optical switch —Timing Jitter Remover (TJR)— whose time window limits the photon-detectable time of photon detectors and improve the timing jitter without sacriﬁcing other performances. By using a TJR, we experimentally improve the timing jitter of a photon-number-resolving detector based on a transition edge sensor, from 50 ns to 10 ns. Using this improved detector, we
Statistical-CSI-Based Antenna Selection and Precoding in Uplink MIMO

Classical antenna selection schemes require instantaneous channel state information (CSI). This leads to high signaling overhead in the system. This work proposes a novel joint receive antenna selection and precoding scheme for multiuser multiple-input multiple-output uplink transmission that relies only on the long-term statistics of the CSI. The proposed scheme designs the switching network and the uplink precoders, such that the expected throughput of the system in the long term is maximized. Invoking results from the random matrix theory, we derive a closed-form expression for the expected throughput of the system. We then develop a tractable iterative algorithm to tackle the throughput maximization problem, capitalizing on the alternating optimization and majorization-maximization (MM) techniques. Numerical results substantiate the efficiency of the proposed approach and its superior performance as compared with the baseline.
Escaping Saddle Points for Effective Generalization on Class-Imbalanced Data

Real-world datasets exhibit imbalances of varying types and degrees. Several techniques based on re-weighting and margin adjustment of loss are often used to enhance the performance of neural networks, particularly on minority classes. In this work, we analyze the class-imbalanced learning problem by examining the loss landscape of neural networks trained with re-weighting and margin-based techniques. Specifically, we examine the spectral density of Hessian of class-wise loss, through which we observe that the network weights converge to a saddle point in the loss landscapes of minority classes. Following this observation, we also find that optimization methods designed to escape from saddle points can be effectively used to improve generalization on minority classes. We further theoretically and empirically demonstrate that Sharpness-Aware Minimization (SAM), a recent technique that encourages convergence to a flat minima, can be effectively used to escape saddle points for minority classes. Using SAM results in a 6.2\% increase in accuracy on the minority classes over the state-of-the-art Vector Scaling Loss, leading to an overall average increase of 4\% across imbalanced datasets. The code is available at: https://github.com/val-iisc/Saddle-LongTail.
Redirected Walking in Infinite Virtual Indoor Environment Using Change-blindness

Abstract —We present a change-blindness based redirected walking algorithm that allows a user to explore on foot a virtual indoor environment consisting of an inﬁnite number of rooms while at the same time ensuring collision-free walking for the user in real space. This method uses change blindness to scale and translate the room without the user’s awareness by moving the wall while the user is not looking. Consequently, the virtual room containing the current user always exists in the valid real space. We measured the detection threshold for whether the user recognizes the movement of the wall outside the ﬁeld of view. Then, we used the measured detection threshold to determine the amount of changing the dimension of the room by moving that wall. We conducted a live-user experiment to navigate the same virtual environment using the proposed method and other existing methods. As a result, users reported higher usability, presence, and immersion when using the proposed method while showing reduced motion sickness compared to other methods. Hence, our approach can be used to implement applications to allow users to explore an inﬁnitely large virtual indoor environment such as virtual museum and virtual model house while simultaneously walking in a small real space, giving users a more realistic experience.