Miracle-dz/UniFAR-FTUs huggingface dataset:
Depressive Symptoms and Drinking to Cope in Relation to Alcohol Use Outcomes among White and Black/African American College Students

Abstract Objective Prior research shows that Black/African American adults experience more negative alcohol use consequences than White adults, despite lower alcohol consumption. Research also shows that Black/African Americans experience higher rates of depression, which can increase risk for alcohol consumption and alcohol use disorder (AUD) through drinking to cope. We examined associations between depressive symptoms and drinking to cope with alcohol consumption and AUD symptoms among White and Black/African American college students. Methods Participants completed an online survey during the fall and spring semester of their first year of college (N = 2,168, 62.8% female, 75.8% White). Path analyses were conducted to examine whether depressive symptoms and drinking to cope mediated the association between race/ethnicity and alcohol use outcomes, and whether race/ethnicity moderated the associations between depressive symptoms, drinking to cope, and alcohol use outcomes. Results Results indicated that Black/African Americans had lower levels of depressive symptoms, which were associated with lower drinking to cope, and in turn associated with lower alcohol consumption and AUD symptoms. Multigroup analysis indicated that the pattern of associations between depressive symptoms, drinking to cope, and alcohol use outcomes were largely similar between White and Black/African American college students and between males and females, except that the association between depressive symptoms and drinking to cope appeared to be stronger for Whites than for Black/African American students. Conclusion Depressive symptoms and drinking to cope are risk factors in relation to alcohol use outcomes among White and Black/African American college students and partially account for the link between race/ethnicity and alcohol use outcomes. Supplemental data for this article is available online at https://doi.org/10.1080/10826084.2022. 2034871 .
Improving the QoS in 5G HetNets Through Cooperative Q-Learning

Heterogeneous networks are an integral part of the 5G cellular networks as they are one of the important enabling technologies for increased coverage and capacity. However, interferences in multi-tiered architecture bottleneck its performance. Although multiple schemes have been proposed for efficient radio resource management to handle the interferences in heterogeneous networks but provision of quality of service to macrocell and small cell user equipment simultaneously, is still an open research problem. Intelligent schemes for radio resource management in heterogeneous networks have proved their effectiveness due to their self-optimization capabilities. In this research article, a cooperative Q-Learning, algorithm is proposed for efficient joint radio resource management in ultra-dense heterogeneous networks to handle interferences by adaptive power allocation to small cell base stations while considering the minimum quality of service requirements. In this proposed cooperative Q-Learning algorithm, small cell base stations interacts with the neighboring small cell base stations to exchange information and performs self-optimization based on a joint reward function. The proposed solution not only provided significant improvement in the capacity of macrocell and small cell user equipment as compared to other state of art Q-Learning based radio resource management schemes but also ensure the provision of quality of service to all macrocell and small cell user equipment simultaneously in the cluster of 16 small cells. The proposed solution provided a minimum capacity of 2 b/s/Hz to macrocell and small cell user equipment which is 100% higher than the minimum quality of service requirements defined in literature where none of recently proposed solution could meet minimum quality of service requirements. The results analysis shows that cooperation among the small cells yields a significant improvement of 48% in capacity of small cell user equipment at the cost of a slight increase in computational time as compared to independent learning.
Investigating the Relationship between Serum Glucose and Inflammatory Markers in Diabetic Rats with Progressive Resistance Exercise

Background & Objective: Diabetes Mellitus (DM) is a condition that is associated with an increase in inflammatory markers and studies show that resistance exercise with appropriate intensity can reduce inflammation generally. The aim of this study was to investigate the relationship of serum glucose with Interlekin18 (IL-18) and Tumor Necrosis Factor-alpha (TNF-α) in Diabetic rats with progressive resistance exercise. Materials & Methods: In this experimental study, 32 Wistar male rats were distributed to sedentary control, trained control, sedentary diabetic, and trained diabetic groups of 8. Diabetes was induced by Streptozotocin (55 mcg/bw-i.v.). The resistance training protocol consisted of elevating upward from a ladder with weight, supporting an overload equivalent to 5% of body weight, during 6 weeks. The data obtained were analyzed by ANOVA and Tukey's posthoc multiple comparison tests, and a significance level of 5% was considered. Results: According to results, serum concentrations of TNF-α and IL-18 decreased significantly in trained diabetic group compared to sedentary diabetic group after resistance training. While in the amount of TNF-α in the trained control group compared to the sedentary control group, a significant increase was observed, and in the amount of IL-18 in trained control group compared to the sedentary control group, a significant decrease was observed. But regarding the correlation between serum IL-18 concentration and glucose, only in sedentary control group, a significant correlation was observed. Conclusions: Resistance training was able to reduce TNF-α and IL-18 inflammatory markers in trained diabetic rats and improve metabolic and immune aspects in diabetes mellitus.
A Shot at Economic Prosperity

Routine childhood vaccinations are among the most cost-effective child health interventions. In recent years, the broader benefits of vaccines, which include improved cognitive and schooling outcomes, have also been established. This paper evaluates the long-term economic benefits of India’s national program of childhood vaccinations, known as the Universal Immunization Programme (UIP). We combine individual-level data from the 68th round of the National Sample Survey of India (2011–12) with district-wise data on the rollout of UIP from 1985 to 1990. We employ age-district fixed-effects regression models to compare the earnings and per capita household consumer spending of 21- to 26-year-old adults who were born in UIP-covered districts vis-à-vis non-UIP districts between 1985 and 1990. We find that exposure to UIP in infancy increases weekly wages by 13.8 percent (95 percent CI: 7.6–20.3 percent, p<0.01) and monthly per capita household consumption expenditure by 2.9 percent (95 percent CI: 0.7–5.0 percent, p<0.01). Program exposure also reduces the probability that an individual’s household relies on agriculture as the main source of income by 1.9 percent (95 percent CI: 0.0–3.5 percent, p<0.01). The findings are robust to several specifications including varying study duration and accounting for potential migration. The effects vary by sex, location, and caste group.
A Precise CMOS Bandgap Voltage Reference

A bandgap voltage reference using 06 μm digital CMOS process is described The circuit is used for smart power control integrated circuits HSPICE simulation shows that the average drift of the circuit is 15 ppm/°C from -40 °C to 100 °C and 18 μV/V with supply voltages from 6 V to 14 V at 25 °C The circuit features a simple structure and excellent performance
Influence of the preparation of the cylindrical specimen surface and approach analysis on the test value of compressive strength

The worldwide use of the axial compressive strength test makes it fundamental to identify the concrete class. However, this test presents dispersion of results which, consequently, reduces the reliability of the test. The surface of the tops of the specimens influences the values of strength measured, since the lack of flatness impairs the uniform application of the load. Different types of procedures can be used to ensure the flatness of the surfaces. Besides, there are different approaches for data analysis, namely to detect outliers. Thus, this research aimed to study and evaluate, the influence of sulfur capping, capping with confined neoprene sheet and noncapping of the test specimens, and the influence of the approach to detect outliers in order to understand the interference in the results. The sulfur cap presented the lowest dispersion values and the cap with confined neoprene sheet obtained the highest strength. In addition, the results showed that the lack of regularization of the tops of the specimens increased dispersion as it causes an important decrease of the resistance in the concrete.
Getting to the Core of Credit Transfer: How Do Pre-Transfer Core Credits Predict Baccalaureate Attainment for Community College Transfer Students?

The majority of community college entrants aspire to earn a bachelor’s degree; yet fewer than a third do. States use several strategies to support community college’s transfer function, including a transferrable core curriculum, a block of pre-major coursework universally accepted at public postsecondary institutions. In this study, we used statewide administrative data from Texas—a state with a transferable core—to examine pre-transfer credit accumulation and how pre-transfer core credits predict bachelor’s degree attainment and time to degree for community college transfer students. Our results illuminate high variation in pre-transfer core credit accumulation among community college transfer students. Each additional pre-transfer core credit improves students’ probability of earning a bachelor’s degree, but only up to core completion status. Soon after students are core complete—at which point universities are no longer required to transfer in additional core credits, students experience a negative relationship between core credits and bachelor’s degree attainment.
Detection of Mycobacterium Tuberculosis IgM and IgG Antibodies and Associated Risk Factors Among Apparently Healthy Undergraduate Students of a Private University in South-West Nigeria

Background: Infection with Mycobacterium tuberculosis (TB) is frequent among Nigerians. Many people are infected without realizing it (asymptomatic) and thus provide a risk of transmission to others. Not only will early treatment prevent TB complications, but it will also help to break the infection cycle in a community. Objective: The study was conducted to determine the prevalence of Mycobacterium tuberculosis IgM and IgG antibodies and associated risk factors among apparently healthy undergraduate Students of Babcock University, Ilishan-Remo, Ogun State. Methodology: The serum samples of 100 consenting participants were collected randomly and screened for TB antibodies using Aria TB IgG/IgM Combo Rapid Antibody Test Cassette (CTK Biotech Inc. Poway, CA 92064, USA). A structured questionnaire was administered to consenting students to obtain information on their bio-data (e.g, the age, sex, study level etc.), as well as clinical information regarding their health (History of TB, history of BCG vaccination, use of anti-TB medications, alcohol consumption, smoking habits etc.). Results: The outcome of this study shows that 15 (15%) out of the 100 participants screened, were positive for TB IgG antibody, while, only 1 (1%) person was positive for TB IgM antibody. There was no significant association (P>0.05) between percentage TB IgG positivity and the socio-demographic characteristics of the study participants (gender, age, study level and tribe), except for religion. The percentage of TB IgG positivity among the study participants was found to be significantly higher than of TB IgM positivity (P<0.05). None of the 15 participants who tested positive to TB IgG indicated any of the signs and symptoms (persistent cough, chest pain, nausea, fever, chills, loss of appetite, fatigue and night sweat) associated with TB), however the only person who tested positive for TB IgM indicated all, except night sweat. Identified risk factors associated with the occurrence of TB IgM include history of TB, lack of BCG vaccination, history of diabetes and physical unfitness. Conclusion: The findings of this study show that asymptomatic and latent tuberculosis infection exists among the study participants, and that if left untreated, it will progress to active tuberculosis with all of its associated complications, including death. This emphasizes the importance of ongoing public health education, BCG vaccination, and periodic screening to detect asymptomatic cases in the study population in order to break the infection cycle.
Joint Offloading Decision and Resource Allocation for Vehicular Fog-Edge Computing Networks: A Contract-Stackelberg Approach

With the popularity of mobile devices and development of computationally intensive applications, researchers are focusing on offloading computation to the mobile-edge computing (MEC) server due to its high computational efficiency and low communication delay. As the computing resources of an MEC server are limited, vehicles in the urban area who have abundant idle resources should be fully utilized. However, offloading computing tasks to vehicles faces many challenging issues. In this article, we introduce a vehicular fog-edge computing paradigm and formulate it as a multistage Stackelberg game to deal with these issues. Specifically, vehicles are not obligated to share resources, and let alone disclose their private information (e.g., stay time and the amount of resources). Therefore, in the first stage, we design a contract-based incentive mechanism to motivate vehicles to contribute their idle resources. Next, due to the complicated interactions among vehicles, roadside unit (RSU), MEC server, and mobile device users, it is challenging to coordinate the resources of all parties and design a transaction mechanism to make all entities benefit. In the second and third stages, based on the Stackelberg game, we develop pricing strategies that maximize the utilities of all parties. The analytical forms of optimal strategies for each stage are given. Simulation results demonstrate the effectiveness of our proposed incentive mechanism, reveal the trends of energy consumption and offloading decisions of users with various parameters, and present the performance comparison between our framework and existing MEC offloading paradigm in vehicular networks.
A Study of the Effects of Total Quality Management (TQM) Practices on Quality Achievements According to European Foundation for Quality Management (EFQM)

This study aims at identifying the relationships between TQM practices and testing the effects of these practices on quality achievements and outcomes. The intended practices include: leadership, process management, human resources management and learning, quality planning, supplier management and customer focus; and the quality achievements include: customer outcomes, individual outcomes, society outcomes and quality performance. In this respect, the path analysis method was applied using the Lisrel software; and the research model was tested using the data collected from 303 manufacturing and service firms in Khuzestan Province (Iran) with ISO: 9000 standard. The findings indicate that among all the hypotheses formulated based on research objective, only the two hypotheses dealing with the links between human resources management and continuous improvement on one hand, and process management and continuous improvement on the other were rejected, supporting the remaining 17 hypotheses which speculated that TQM practices would have a positive effect on quality achievements .
Impact of Financial Decisions on Firm Performance: Path Analysis Approach

This study intended to explore causal relationships between the corporate performance and financial decisions of the firms which are listed on the Pakistan stock exchange (PSX). This study has used Return on assets and Tobin's Q as the measures of accounting performance and market performance respectively. To effectively examine the causal structure of corporate financing, investment, dividend payout decisions, and the firm performance simultaneously this study has used path analysis approach. The sample comprises 292 non-financial firms which are listed on the Pakistan Stock Exchange (PSX). The findings clearly show that debt financing has positive effect on the investment and dividend has negative effect on the investment decisions. The debt financing and investment has a negative impact on corporate performance while dividend decisions has a positive impact on corporate performance. This study helps to understand the corporate decision making process of Pakistani firms. To the author's knowledge this is the first study attempted to check the application of path analysis in emerging economies to study the causal structure of corporate financial decisions and corporate performance.
Artificial-Neural-Network-Assisted Sensor Clustering for Robust Communication Network in IoT-Based Electricity Transmission Line Monitoring

As an Internet of Things (IoT) application in the smart grid, dynamic thermal rating (DTR) requires real-time measurement of conductor temperature from field sensors that are installed at remote transmission lines. For such IoT-based transmission line monitoring, we need a robust communication network. This article proposes to group sensors with similar measurement characteristics into a cluster such that each member can accurately represent the entire cluster. Then, communication robustness can be achieved by establishing multiple routes to the control center, where each route may originate from a different member in the cluster. First, we formulate a global constrained optimization for sensor clustering. We use the optimization solutions to train a set of artificial neural networks (ANNs), where each ANN is deployed to make a local decision at one sensor. Specifically, we propose the novel usage of ANN as a tool to transfer knowledge from a global decision maker to a set of local decision makers. Evaluation results show that there remains a noticeable knowledge gap between global and local decision makers, where in average, the global decision maker and an ANN make an identical decision in only about 70% of the times. Despite this less than ideal success probability, the number of clusters produced by the ANN-assisted local scheme is only 1.9 more than that by the global scheme.
Comparison of Enzyme-Linked Immunosorbent Assay and Chemiluminescence Immunoassay for Thyroid Stimulating Hormone Analysis in Tertiary Care Hospital Lahore

Objective: To compare enzyme-linked immunosorbent assay and Chemiluminescence immunoassay for thyroid stimulating hormone analysis in human serum. Methodology: This cross-sectional study conducted from 17th March till 13th June. In Punjab Rangers Teaching Hospital, Lahore after approval from Institutional Review Board. Random samples from both genders, between 18-70 years of age were included. Haemolysed, lipemic or icteric specimens were excluded. The sera were assayed for thyroid stimulating hormone (TSH) by enzyme-linked immunosorbent assay (ELISA) and Chemiluminescence immunoassay (CLIA). Data was analyzed by SPSS 24. Results: A total of one hundred and ninety-eight serum samples were processed by ELISA and CLIA in all the samples, with more females as compared to males (1:1.3). ELISA technique identified 134 subjects as Euthyroid, 40 Hypothyroid and 24 Hyperthyroid, while 122 Euthyroid, 48 hypothyroid and 28 hyperthyroid subjects by CLIA. Thyroid stimulating hormone (TSH) levels reference range was taken 0.4-4.5mU/L according to American Thyroid Association. Mean ± SD of TSH was 1.45 ± 0.79; 12.27 ± 11.03 and 0.23 ± 0.17 mU/L respectively by ELISA whereas CLIA indicated Mean ± SD to be 1.93 ± 0.936, 16.04 ± 14.68 and 0.393 ± 0.375 mU/L respectively for Euthyroid, hypothyroid and hyperthyroid. Correlation of coefficient (R2 =0.89) was found significantly positive between both methods. There was a significant difference in hypothyroid and Euthyroid groups. Conclusion: TSH assay by CLIA has shown a wider range of functionality, throughout and borderline cases were identified better as compared to ELISA. Turn-around-time (TAT) decreased, physician satisfaction increased and indirectly benefitting patient treatment and prognosis.
Professional Quality of Life and Its Association with Work Experience and Income among Healthcare Worker

Objective: The objective of the study is to assess job satisfaction between groups of healthcare workers based on their work experience and monthly salary.Methodology: Healthcare workers (n=81) including clinicians, nurses and medical teachers were recruited from a private medical institute at Lahore. Job Satisfaction Survey (JSS) and Professional Quality of Life (ProQOL) Scale including its component scales of Compassion Satisfaction (CS), Burnout (BO) and Secondary Traumatic Stress (STS) were used to determine aspects of vocational quality of life and satisfaction. Kruskal-Wallis test was used to assess group differences. Spearman correlational analysis was done to assess correlation between income, work experience and job satisfaction.Results: Significantly higher professional satisfaction, lower burnout and stress scores were observed in experienced healthcare workers as compared to less-experienced ones (p value =0.039* for JSS, p value =0.011* for CS, p value =0.055* for BO and p value =0.027* for STS). Significantly higher satisfaction scores were found in workers with higher monthly income as compared to those with lower monthly salary (p value =0.006* for JSS and p value =0.032* for CS). Significant positive correlation was observed between healthcare workers’ job satisfaction and their experience and monthly salary.Conclusion: More experience at work is particularly associated with lower burnout and reduced occupational stress.
CORRELATING RESILIENT MODULI FROM PRESSUREMETER TESTS TO LABORATORY CALIFORNIA BEARING RATIO TESTS

In order to increase the usefulness of the pressuremeter (PMT) in the area of pavement design and evaluation, resilient moduli, determined from a special PMT test, were correlated to California Bearing Ratio (CBR) test results. The PMT resilient moduli-CBR correlations developed compared well with existing resilient moduli-CBR correlations. The special PMT test, called the resilient modulus PMT test, was developed to enable six resilient moduli to be determined from six unload-reload cycles conducted for various load durations along the linear portion of the in situ stress-strain response. The various cycle lengths enabled resilient moduli to be determined as a function of the load durations typically encountered during the traffic loading of a pavement. The cycle lengths used were 10, 20, 30, 60, 120, and 240 sec. The PMT used was the monocell TEXAM pressuremeter built by Roctest, Inc. It was concluded that the current TEXAM PMT cannot be used to accurately conduct 10-sec unload-reload loops to determine resilient moduli, but can be used to accurately determine resilient moduli for the remaining cycle lengths and that the resilient moduli from these cycles are reasonable for use in design.