Miracle-dz/UniFAR-FTUs huggingface dataset:
Conditional Test for Ultrahigh Dimensional Linear Regression Coefficients

This paper is concerned with a conditional test for regression coefficients in ultrahigh dimensional linear models. Conditioning on a subset of important predictors in the model, we test the overall significance of regression coefficients of the remaining ultrahigh dimensional predictors. We first propose a conditional U-statistic test (CUT) based on an estimated U-statistic for a high dimensional linear regression model and prove that its null asymptotic distribution is normal under some mild assumptions. However, the empirical power of the proposed test is inversely affected by the dimensionality of predictors. To this end, we further propose a two-stage CUT with screening (CUTS) procedure to reduce the dimensionality under the sparsity assumption and enhance the empirical power based on random data splitting strategy. In the first stage, we divide data randomly into two equal halves and apply the conditional sure independence screening to the first half to reduce the dimensionality; In the second stage, we apply the proposed CUT test to the second half. To eliminate the effect of random data splitting and further enhance the empirical power, we also develop a powerful ensemble algorithm based on multiple splitting strategy and prove that the family-wise error rate is asymptotically controlled at a given significance level. We demonstrate the excellent finite-sample performances of the proposed conditional test via Monte Carlo simulations and a real data analysis.
Nitrogen and Phosphorus Control Soil Methane Uptake in Tropical Montane Forests

Tropical forests contribute about one third to global annual CH4 uptake by soils. Understanding the factors that control the soil‐atmosphere exchange of CH4 at a large scale is a critical step to improve the CH4 flux estimate for tropical soils, which is presently poorly constrained. Since tropical forest degradation often involves shifts in nutrient availabilities, it is critical to evaluate how this will affect soil CH4 flux. Here, we report how nitrogen (N; 50 kg N ha−1 yr−1), phosphorus (P; 10 kg P ha−1 yr−1), and combined N + P additions affect soil CH4 fluxes across an elevation gradient of tropical montane forests. We measured soil CH4 fluxes in a nutrient application experiment at different elevations over a period of 5 years. Nutrient additions increased soil CH4 uptake after 4–5 years of treatment but effects were not uniform across elevations. At 1,000 m, where total soil P was high, we detected mainly N limitation of soil CH4 uptake. At 2,000 m, where total soil P was low, a strong P limitation of soil CH4 uptake was observed. At 3,000 m, where total P was low in the organic layer but high in mineral soil, we found N limitation of soil CH4 uptake. Our results show that projected increases of N and P depositions may increase soil CH4 uptake in tropical montane forests but the direction, magnitude, and timing of the effects will depend on forests' nutrient status and plant‐microbial competition for N and P.
Effect of COVID-19 lockdown on reproductive activity in Rivers state

Background: Reproductive activity is an important biological process that always take place between married and unmarried couples across the globe. The study was carried out to evaluate the effect of COVID-19 on reproductive activity during and post-lockdown in Rivers state. The aim of the study was to evaluate the effect of COVID-19 on reproductive activity during and post-lockdown in Rivers state.Methods: A well-structured questionnaire containing demographics and effect of COVID-19 on reproductive activity were administered to participants. Each participant had one questionnaire to fill appropriately and independently after instructions were given to them by the researchers.Results: The study revealed that 57.58% (57/99) of the participants were between the ages 16-20, 58.82% (60/102) were single and 99.03% (102/103) of the participants (women) have unprotected sexual intercourse during COVID-19 lockdown. 99.03% (102/103) the participants engaged in unprotected sex because the pharmacist’s stores were closed. The study also shows that 43.69% (103) have the urge for sex due to inactivity and 76.60% (102) of the participants got pregnant and 96.25% (77/80) of the pregnancy were not planned. 51.29% (41/80) of the participants aborted the pregnancy and 92.68% (38/41) 0f the women who got pregnant did not attend antenatal clinic.Conclusions: A total number of 103 respondents participated in the research. 76.6% of the population got pregnant during the lockdown for different reasons and most of the participants were singles and did not plan for the pregnancy.
Online learning in COVID-19 pandemic: an empirical study of Indian and Turkish higher education institutions

Purpose Online learning is essential in today’s world. The COVID-19 has resulted in shutting down all the universities across the globe. Countries like India and Turkey (lower-income countries) are suffering a lot in giving the best classroom practice to their students through online mode. The entire way of teaching-learning has changed drastically, and it is a need of an hour. Research suggests that online learning has been shown to increase retention of information, and take less time, meaning the changes coronavirus have caused might be here to stay. It is therefore important to understand from student’s perspectives about learning online. The paper systematically surveys the perception of learning online for Indian and Turkan students. Design/methodology/approach To achieve this goal, 594 samples of students (from India and Turkey country) have been taken into considerations, and through statistical measures, the results were analyzed. The set of four research questions comprising of effect of study on COVID-19 pandemic, perception of learning online in COVID-19 pandemic, perception of different genders in learning online and perception of Indians over Turkan students in learning online were analyzed through statistical measures such as mean, standard deviation and so on. Findings The descriptive statistics of various responses across various dimensions (gender, country) reveals that there is no effect in learning online as compared to classroom-based teaching. On the other hand, there is no significant difference in gender and country in learning online. Originality/value Online learning has become crucial in higher education as far as pandemic situation is concerned. Many higher education institutions across different countries are suffering various problems from student point of view. Middle-income countries who are with limited assets and less advancements in higher education need to adhere to certain guidelines in online learning. This empirical study will help to understand the perception of students in online learning across India and Turkey.
Non-Chemical Control of Annual Bluegrass (Poa annua) in Bermudagrass (Cynodon spp.) via Fraise Mowing: Efficacy and Barriers to Adoption

Fraise mowing is a maintenance practice that may serve as a non-chemical means of controlling the problematic weed annual bluegrass (Poa annua L.) in bermudagrass (Cynodon spp.) given reports of efficacy on other turfgrass species. However, an understanding of practitioner decision-making in implementing fraise mowing as a weed-control measure remains unknown. A field study was conducted in Knoxville, TN and repeated in space in Jay, FL during summer 2019 to assess bermudagrass regrowth and subsequent annual bluegrass control, following fraise mowing at depths of 1.5 and 3.0 cm compared to a non-treated check (0 cm). Bermudagrass recovered more quickly at the 1.5 cm depth than the 3.0 cm depth and was the swiftest in Florida. Fraise mowing at either depth resulted in a 41–97% reduction in annual bluegrass populations. A qualitative study was conducted in spring 2021, which engaged eight turfgrass managers from Tennessee and Florida via individual interviews in order to understand barriers and challenges to fraise mowing application. Turfgrass managers had positive views of fraise mowing but described challenges in implementation for weed control including cost, labor, area closure, and debris removal.
Effect of Gas-Liquid Contact Intensification on Heat and Mass Transfer in Deflector and Rod Bank Desulfurization Spray Tower

The deflector and the rod bank are commonly used to optimize flue gas distribution in the original spray tower (OST) of a wet flue gas desulfurization system (WFGD). In this paper, the internal optimization mechanism of the deflector desulfurization spray tower (DST) and the rod bank desulfurization spray tower (RBST) are studied. Based on the Euler–Lagrange method, the standard k-ε turbulence model, an SO2 absorption model and a porous media model, the numerical simulation of the desulfurization spray tower is carried out with the verification of the model rationality. The results show that there are gas-liquid contact intensification effects in DST and RBST. Compared with OST, gas-liquid contact intensification enhances the heat and mass transfer effects of DST and RBST. The temperature difference between inlet and outlet of flue gas increased by 3.3 K and the desulfurization efficiency of DST increased by 1.8%; the pressure drop decreased by 37 Pa. In RBST, the temperature difference between the flue gas inlet and outlet increased by 5.3 K and the desulfurization efficiency increased by 3.6%; the pressure drop increased by 33 Pa.
Rectenna with non-linear adaptive load capable of operating over a broad range of input power levels

A rectenna design is introduced which is capable of effectively operating over a broad input power level at 915 MHz. Silicon Schottky diodes with low forward voltage and low zero-bias junction capacitance are applied to construct a bridge-rectifier. A novel non-linear adaptive load, of which the equivalent impedance changes when the input power varies, is proposed and applied at the terminal of the rectenna. The circuit is simulated using Advanced Design System (ADS), demonstrating an overall RF-to-DC conversion efficiency greater than 50% for an input power ranging from -13.5 dBm to 0 dBm.
Mucormycosis an avoidable complication of COVID-19: a case report

Mucormycosis is caused by the fungi belonging to the order Mucorales. There has been an increasing trend of rising fungal infection during the second wave of COVID in India, seen among patients recovering from COVID-19. A 37-years-old middle-aged adult, with the diagnosis of left paranasal sinus mucormycosis, left side pneumothorax (intercostal drainage tube in-situ) with COVID pneumonia reported to the emergency department (ED) during the COVID-19 pandemic in our hospital in India. The patient presented in the ED on oxygen support via a non-rebreathing mask at rate of 10 l/min with a history of progressive left eye redness, pain, and tenderness, periorbital swelling, sudden onset, and mild shortness of breath from 8 days. The patient had a history of taking steroids during the management of COVID-19, also had left intercostal drainage tube (ICD) in-situ, and underwent post endoscopic sinus surgery in the private hospital. The patient was clinically examined by multispeciality experts and subjected to laboratory investigations. The patient was diagnosed with left PNS mucormycosis and planned for debridement. The patient developed renal failure secondary to antifungal therapy had sudden deterioration and could not be saved. The mortality rate of mucormycosis is very high due to delayed presentation, toxicity associated with the antifungal therapy, etc. There is a need to identify risk factors, perform specific laboratory tests, and initiation of prompt treatment. Monitoring and competent nursing care are required during antifungal therapy and prolonged hospital stay.
Analysis of Fine Gained Air Quality Using Deep Learning

With the rapid development of industrialization and urbanization, air pollution is increasing at an alarming rate in many developing countries. The four air pollutants which are becoming a concerning threat to human health are namely respirable particulate matter, nitrogen oxides, particulate matter and sulphur dioxide. The models which are currently used for air quality prediction by comparing to the AQI indexes do not give satisfactory results, which inspired us to examine the methods of predicting air quality based on deep learning using the K-Mean Clustering algorithm and Image Processing Technique. The interpolation, prediction, and feature analysis of fine-gained air quality are three important topics in the area of air computing. A good interpolation helps to estimate the limited air quality monitoring stations whose distribution is uneven in a city; an accurate prediction provides valuable information to protect humans and take necessary measures to reduce the effect of air pollution; a reasonable feature analysis is used to provide a more effective and general model. Overall, finding solutions to these topics can bring out extremely useful information to support air pollution control, and consequently generate great societal and technical impacts.
The Role of Educational Communication in Promoting a Student-Centered Learning Style in Multicultural Classrooms: A Reflective Essay on Learning and Teaching in Higher Education

This is a reflective essay on my own experience while learning and teaching in multicultural classroom in higher education in the UK. It emphasizes the indispensable relationship between the two fields of teaching–learning and communication processes in such heterogeneous environment. The essay focuses on how, in such context, teachers are key players, focused on excellent critical learning and teaching skills; these involve more than content expertise, or traditional methods, but becoming a student-centred, flexible and innovative teacher, going beyond the evaluation of feedback, to constantly exploring gaps in the learning and teaching process, and adjusting their teaching methods accordingly. Key emphasize is on how two-way, open communication endorses teachers’ awareness of discrepancies within their student groups and offers alternative individualized learning styles. Reflecting on my own experience, outcomes form focus groups, and qualitative interviews, the paper concludes with that, by meeting essential physiological, pedagogical as well as belonging needs and esteem, educational communication leads our efforts in optimizing teaching technique in class management, students engagement, also guide our efforts to attain a motivational climate for interactive learning. Best practices in educational communication can boost teachers’ efforts in employing the educational goals of HE, and recognize their societal impact.
Influence of hydrogen in silicon nitride films on the surface reactions during hydrofluorocarbon plasma etching

The influence of the amount of hydrogen (H) in hydrogenated silicon nitride films (SixNy:Hz) on the etching properties and etching mechanism are unclear for hydrofluorocarbon plasma etching. Therefore, the authors have investigated the effect of H in SixNy:Hz films on the surface reactions during CH2F2/Ar/O2 plasma etching by experimental and numerical simulation techniques. The experimental etch yield (EY) and polymer layer thickness (TC−F) values for SixNy:Hz films with different H concentrations of 2.6% (low-SiN), 16.8% (mod-SiN), and 21.9% (high-SiN) show different trends with the CH2F2/(CH2F2 + O2) flow rate ratio. To understand the mechanism of the different etching properties, the authors estimated the chemical reaction probabilities of the H outflux between F, O, N, C, and Si dangling bonds using first principles calculations and the results of Fourier transform infrared spectroscopy. Based on the estimated reaction probabilities, the authors modeled the surface reactions of SixNy:Hz films under t.
How Multitasking during Video Content Decreases Ad Effectiveness: The Roles of Task Relevance, Video Involvement, and Visual Attention

Abstract In a 3 (secondary task: none, related, unrelated) x 2 (ad-video congruence: high/low) between-subjects eye-tracking experiment, participants (N = 153) watched a 9-minute video documentary segment containing one mid-roll video ad while their visual attention to the screen was recorded. Participants in two-thirds of the conditions also read two online articles on a mobile device during the video. Results show effects for both multitasking and task relatedness on attention to the ad and attitudes toward the ad, through distinct pathways. Specifically, multitasking reduced attention to the ad. Moreover, multitasking on an unrelated task lowered attitudes toward the ad by decreasing program involvement and the subsequent attention to the ad.
Pharmacy Impact on Covid-19 Vaccination Progress Using Machine Learning Approach

The novel coronavirus disease (COVID-19) has created immense threats to public health on various levels around the globe. The unpredictable outbreak of this disease and the pandemic situation are causing severe depression, anxiety and other mental as physical health related problems among the human beings. This deadly disease has put social, economic condition of the entire world into an enormous challenge. To combat against this disease, vaccination is essential as it will boost the immune system of human beings while being in the contact with the infected people. The vaccination process is thus necessary to confront the outbreak of COVID-19. The worldwide vaccination progress should be tracked to identify how fast the entire economic as well as social life will be stabilized. The monitor of the vaccination progress, a machine learning based Regressor model is approached in this study. This vaccination tracking process has been applied on the data starting from 14th December, 2020 to 24th April, 2021. A couple of ensemble based machine learning Regressor models such as Random Forest, Extra Trees, Gradient Boosting, AdaBoost and Extreme Gradient Boosting are implemented and their predictive performance are compared. The comparative study reveals that the Extra trees Regressor outperforms with minimized mean absolute error (MAE) of 6.465 and root mean squared error (RMSE) of 8.127. The uniqueness of this study relies on assessing as well as predicting vaccination intake progress by utilizing automated process offered by machine learning techniques. The innovative idea of the method is that the vaccination process and their priority are considered in the paper. Among several existing machine learning approaches, the ensemble based learning paradigms are employed in this study so that improved prediction efficiency can be delivered.
Delay-Dependent Stability Analysis of Haptic Systems via an Auxiliary Function-Based Integral Inequality

In this paper, the delay-dependent stability of haptic systems is studied by developing a new stability criterion. Firstly, the haptic system inevitably introduces time delays by using communication networks to transmit information between the controller and the haptic device. When discussing the stability of the haptic system near its operating point, the original nonlinear system is modeled as a linear system with the time delay mentioned above. In addition, a suitable augmented Lyapunov–Krasovskii functional (LKF) with more integral forms is constructed and an auxiliary function-based integral inequality is applied to estimate the derivative of the proposed LKF. Then, a less conservative delay-dependent criterion in terms of the linear matrix inequality (LMI) is derived to calculate the delay margin for the haptic system. Finally, case studies are carried out based on a one degree of freedom haptic system. The results show that, compared with criteria in existing works, the proposed criterion can obtain more accurate results and require less calculation complexity, and, with the increase in virtual damping in a certain range, the stable upper bound of the haptic system increases at first and then decreases.
On CSI and Passive Wi-Fi Radar for Opportunistic Physical Activity Recognition

The use of Wi-Fi signals for human sensing has gained significant interest over the past decade. Such techniques provide affordable and reliable solutions for healthcare-focused events such as vital sign detection, prevention of falls and long-term monitoring of chronic diseases, among others. Currently, there are two major approaches for Wi-Fi sensing: (1) passive Wi-Fi radar (PWR) which uses well established techniques from bistatic radar, and channel state information (CSI) based wireless sensing (SENS) which exploits human-induced variations in the communication channel between a pair of transmitter and receiver. However, there has not been a comprehensive study to understand and compare the differences in terms of effectiveness and limitations in real-world deployment. In this paper, we present the fundamentals of the two systems with associated methodologies and signal processing. A thorough measurement campaign was carried out to evaluate the human activity detection performance of both systems. Experimental results show that SENS system provides better detection performance in a line-of-sight (LoS) condition, whereas PWR system performs better in a non-LoS (NLoS) setting. Furthermore, based on our findings, we recommend that future Wi-Fi sensing applications should leverage the advantages from both PWR and SENS systems.
Repositório ISCTE-IUL

Drawing on an ecological approach with multiple informants, this study investigated the mediating role of youth-caregiver relationship quality in associations between different features of residential care settings’ organizational social context and youth’s psychopathology. Participants were 378 youth aged between 12 and 25 years old, and 54 caregivers aged between 24 and 57 years old, from 29 generalist residential youth care settings in Portugal. Given the hierarchical structure of data, analyses were performed using multilevel modelling. Results revealed that organizational social contexts characterized by higher levels of engagement, stress, and centralization, as perceived by the caregivers, were associated with lower levels of youth’s externalizing problems (e.g., aggressive behavior, delinquency), reported by the caregivers, via better youth-caregiver relationship quality, perceived by the youth in care. These findings highlight the relevance of creating an organizational social context in residential care settings that supports caregivers in establishing high-quality relationships with the youth in care, thereby promoting their mental health. This study contributes to the clarification of conflicting findings in previous studies of this field, by offering further empirical investigation of these issues.