Miracle-dz/UniFAR-FTUs huggingface dataset:
A Comparative Study on Human Movement
Classification Using Wi-Fi Based Passive
Forward Scattering Radar

Forward scattering radar has been widely used to classify human movements. To reduce concern of prolonged radiation exposure, Wi-Fi based passive scattering radar with bistatic topology is proposed. The movements include walking, bending, sitting, and kneeling. The enveloping algorithm applied to Wi-Fi based passive forward scattering radar signals has produced a comparable pattern to the ones from the active configuration. The features extracted from the frequency spectrum are also similar for both radar topologies. These led to comparable performance when classifying using artificial neural network. Hence, Wi-Fi can effectively reduce the cost of radar sensors.
Energy Consumption Forecasting in Commercial Buildings during the COVID-19 Pandemic: A Multivariate Multilayered Long-Short Term Memory Time-Series Model with Knowledge Injection

The COVID-19 pandemic and the subsequent implementation of lockdown measures have significantly impacted global electricity consumption, necessitating accurate energy consumption forecasts for optimal energy generation and distribution during a pandemic. In this paper, we propose a new forecasting model called the multivariate multilayered long short-term memory (LSTM) with COVID-19 case injection (mv−M−LSTM−CI) for improved energy forecast during the next occurrence of a similar pandemic. We utilized data from commercial buildings in Melbourne, Australia, during the COVID-19 pandemic to predict energy consumption and evaluate the model’s performance against commonly used methods such as LSTM, bidirectional LSTM, linear regression, support vector machine, and multilayered LSTM (M-LSTM). The proposed forecasting model was analyzed using the following metrics: mean percent absolute error (MPAE), normalized root mean square error (NRMSE), and R2 score values. The model mv−M−LSTM−CI demonstrated superior performance, achieving the lowest mean percentage absolute error values of 0.061, 0.093, and 0.158 for DatasetS1, DatasetS2, and DatasetS3, respectively. Our results highlight the improved precision and accuracy of the model, providing valuable information for energy management and decision making during the challenges posed by the occurrence of a pandemic like COVID-19 in the future.
Student Perceptions of Web-based Instruction: A Comparative Analysis

The article presents the findings of a recent longitudinal study that compares student perception of instruction scores between online and regular classes. Participants in the study were campus-based traditional undergraduate students enrolled at a large public U.S. university. The findings suggest that student perceptions of course participation are influenced by matters of convenience. The article concludes with relevant implications for educators who design and teach web-based courses to traditional undergraduate students.
Improving the Classification Result of Rice Varieties Using Gradient Boosting Methods

An accurate identification of rice grain is crucial for classifying rice varieties. This study classifies five distinct rice types that share morphological characteristics using four different machine learning methods. A total of seventy-five thousand records, consisting of fifteen thousand for each variety of rice grains, are collected from previous research. Machine learning methods that are used in this study are the Gradient Boosting method and its variances. The experimental results show that Light Gradient Boosting Machine was the algorithm with the most significant classification success rate compared to other methods, with an accuracy of 98,14%.
Work hour mismatches and sickness absence and the moderating role of human resource practices: Evidence from Germany

Working time mismatches – and especially overemployment – continue to be a highly relevant topic in German legislation, business practice and in research. However, it has been rather neglected in empirical absenteeism research. Therefore, the aim of this study is to examine the relationship between contractual overemployment, that is, the difference between contractual and preferred working hours, and sickness absence in Germany. Furthermore, this study explores the moderating role of HR practices (flexible work arrangements and part-time employment) on this relationship. Therefore, I conduct two-level negative binomial regression analyses, using data from the German Socio-economic panel (GSOEP). In line with the JD-R model, results indicate that overemployment (especially overemployment of 6–10 hours compared to a work hour match) is positively related to sickness absence. However, the moderating role of flexible work arrangements, that is, the buffer effect of working time autonomy on this link cannot be confirmed. Moreover, the results suggest that part-time employment amplifies the relationship between overemployment (1–5 hours) and sickness absence for females only. This study highlights the need to move away from standardised work hour arrangements. Indeed, it is one of the first studies that emphasises the role of preference-based contractual working hours in reducing absenteeism, also and especially because standard HR practices do not mitigate overemployment-related absenteeism, but can in fact exacerbate it. Furthermore, this study contributes to theory and literature, by extending the JD-R model to overemployment.
Decreased Soil Water Content Effects on the Toxicity of Triclosan to Oilseed Rape (Brassica napus L.)

Due to the rising amounts of antimicrobial agents in the environment and the lack of knowledge on their ecotoxicity, there is growing concern regarding their effects on the environment. One of the most widely used antibacterial compounds in both personal care and pharmaceutical products is triclosan (TCS), which is also a commonly detected emerging organic contaminant in the environment. Physiological or morphological endpoints of whole-organism analysis are typically used in reported studies of TCS toxicity to terrestrial plants. To identify underlying toxicity mechanisms, more in-depth investigations of TCS-induced effects at the biochemical plant level are required. Furthermore, climate change is an issue that is becoming more and more serious and might have a significant impact on life on the Earth. The influence of climate parameters on the ecotoxicity of antimicrobials, particularly TCS, is little understood. The main objective of this study was to evaluate drought effect on triclosan toxicity to oilseed rape (Brassica napus L.). Brassica napus were grown in TCS-contaminated soil (10-400 mg kg -1) under different soil water contents (5% and 30% SWC). B.napus morphological (dry weight, length of the roots and shoots), biochemical indicators (the activity of enzymes), and the damage of oxidative stress (lipid peroxidation) were detected. Drought enhanced the negative effect of triclosan on the above-ground part of B. napus and led to oxidative stress.
NEWS FRAMEWORK OF THE ARREST OF DJOKO TJANDRA IN KOMPAS.COM AND DETIK.COM

Like conventional media, online media is also active to take part in reporting every reality that is happening around. Online media can influence the meaning and image that results from the reality it constructs. This study aims to identify the news about Djoko Tjandra's arrest in online media Kompas.com and Detik.com. This study uses a qualitative approach with a Robert N. Entman framing analysis method which is carried out with four tools, namely: (1) defining the problem, (2) diagnosing the cause, (3) making moral judgements, (4) treatment recommendations. Object of this research is the news about the arrest of suspect in the corruption case, Djoko Tjandra, by Bareskrim Polri which were uploaded by the two media from 31 July to 7 August 2020. From the research results, Kompas.com uses a frame in the legal field and tends to highlight this case as a legal problem. This is reinforced by the inclusion of legal references, selection of sources with legal backgrounds, and explanations of legal procedures in this case. Meanwhile, Detik.com defines the problem as a violation of the law and presents news related to moral issues such as Djoko Tjandra asking for protection from various parties.
A Novel Framework for Distribution Power Lines Detection

Millions of dollars are spent yearly to trim trees along rights-of-way and guarantee reliable distribution line systems. To reduce these costs, power utilities are embracing a new approach based on light detection and ranging (LiDAR) data. They aim to automatically detect the locations of critical branches/trees and assess their risks. In this paper, we propose a novel and robust power lines detection framework with several LiDAR data processing steps, which combines machine learning and geometric approaches. By combining these methods, we efficiently detect distribution lines with an Intersection-over-Union performance superior to those of deep-learning-based benchmarks, and less complex than most of them. The benefit is that by prescribing the use of geometrical/mathematical approaches for the post-processing of deep-learning/machine-learning outputs, we are able to further improve lines detection. Finally, we expect our novel framework to be generalized to detect various LiDAR objects such as poles, cars, buildings and roads.
Variant Creutzfeldt-Jakob Disease

INTRODUCTION Creutzfeldt–Jakob Disease (CJD) has been the focus of much attention in recent years due to the identification of a new variant now known as variant CJD (vCJD). Experimental evidence has shown that vCJD is due to human infection with the causative agent of Bovine Spongiform Encephalopathy (BSE), which was epidemic in UK cattle in the 1980s and early 1990s. Although vCJD remains rare, its existence has many implications. Clinicians have to face many questions from patients, relatives and other health care professionals. This review aims to present some of the scientific background, help health care professionals recognize the typical clinical picture and thus aid diagnosis. CJD is a human transmissible spongiform encephalopathy (TSE). Uniquely, it is a disease that exists in sporadic, inherited and infectious forms. It is a rare, invariably fatal neurodegenerative disease that can be difficult to diagnose during life, and neuropathological examination of the brain
Unilateral versus bilateral percutaneous pedicle screw fixation in minimally invasive transforaminal lumbar interbody

Lumbar fusion is a common surgical procedure for the treatment of symptomatic spinal pathologies, such as degenerative spinal disease, trauma, spondylolisthesis, and deformity.15,22 Among various spinal fusion techniques, TLIF has become a popular and wellestablished technique since its description by Harms et al.10 Transforaminal lumbar interbody fusion can avoid injury of anterior abdominal structures such as the vessel, sympathetic nerve, and retroperitoneal and peritoneal structures.16,17,20 In addition, TLIF does not require retraction of the dura or nerve roots, eliminates epidural scarring, and reduces intraoperative bleeding.2,7,14,15 Recently, advances in MIS have allowed TLIF to reduce the complications associated with the open technique.18–20 When compared with the open procedure, MIS TLIF with a tubular retractor appears to achieve similar fusion rates while reducing blood loss, reducing soft tissue and muscle trauma, causing smaller wounds, increasing the speed of recovery, and reducing postoperative pain.18–20 However, TLIF requires a complete facetectomy, so iatrogenic instability can occur and additional posterior screw fixation is essential.2,7,14,15 Generally, bilateral pedicle screw fixation after MIS TLIF is accepted as standard procedure and provides rigid fixation and biomechanical and clinical advantages.23,27,28 Unilateral versus bilateral percutaneous pedicle screw fixation in minimally invasive transforaminal lumbar interbody fusion
Analiza performansi protokola usmjeravanja u mobilnim ad hoc mreama

SadrajMobilna ad hoc mrea (engl. Mobile Ad hoc Network, MANET) je skupina beinih pokretnih vorova koji meusobno komuniciraju bez mrene infrastrukture ili centralizovanog upravljanja. Izbor protokola usmjeravanja u mobilnim ad hoc mre ama je veliki izazov za razliku od inih mrea, jer se vorovi neprestano kre uig eneriu nekorisni teret usmjeravanja. Cilj ovog rada je izvriti ocjenu performansi DSDV, AODV i DSR protokola usmjeravanja na osnovu rezultata analize dobivenih koristei simulacije sa razliitim scenarijima pokretljivosti i optereenja, koje su izvedene u mrenom simulatoru NS-2 (engl. Network Simulator 2). Parametri koriteni za poreenje su prosjeno kanjenje s kraja na kraj, odnos uspjeno prenesenih paketa i ukupnog broja paketa (engl. Packet Delivery Ratio, PDR), te normalizirano optereenje usmjeravanja (engl. Normalized Routing Load, NRL). Protokoli DSDV, AODV i DSR u situacijama slabe pokretljivosti i optereenja imaju sline performanse. Meutim, sa poveanjem pokretljivosti DSR protokol nadmauje AODV i DSDV protokole.
Explaining Machine Learning Models in Natural Conversations: Towards a Conversational XAI Agent

—The goal of Explainable AI (XAI) is to design methods to provide insights into the reasoning process of black-box models, such as deep neural networks, in order to explain them to humans. Social science research states that such explanations should be conversational, similar to human-to-human explanations. In this work, we show how to incorporate XAI in a conversational agent, using a standard design for the agent comprising natural language understanding and generation components. We build upon an XAI question bank which we extend by quality-controlled paraphrases to understand the user’s information needs. We further systematically survey the literature for suitable explanation methods that provide the information to answer those questions, and present a comprehensive list of suggestions. Our work is the ﬁrst step towards truly natural conversations about machine learning models with an explanation agent. The comprehensive list of XAI questions and the corresponding explanation methods may support other researchers in providing the necessary information to address users’ demands.
A Theory of Challenge and Threat States in Athletes

We propose a Theory of Challenge and Threat States in Athletes (TCTSA) which is an amalgamation and extension of the biopsychosocial model of challenge and threat, the model of adaptive approaches to competition and the debilitative and facilitative competitive state anxiety model. In the TCTSA we posit that self-efficacy, perceptions of control, and achievement goals determine challenge or threat states in response to competition. Distinct patterns of neuroendocrine and cardiovascular responses are indicative of a challenge or threat state. Increases in epinephrine and cardiac activity, and a decrease in total peripheral vascular resistance (TPR) characterise a challenge state and increases in cortisol, smaller increases in cardiac activity and either no change or an increase in TPR characterise a threat state. Positive and negative emotions can occur in a challenge state while a threat state is associated with negative emotions only. Emotions are perceived as helpful to performance in a challenge state but not in a threat state. Challenge and threat states influence effort, attention, decision–making and physical functioning and accordingly sport performance. The TCTSA provides a framework for practitioners to enhance performance, through developing a challenge state, and encourages researchers to explore the mechanisms underlying performance in competition.
Gulf Stream Sea Surface Temperature Anomalies Associated With the Extratropical Transition of North Atlantic Tropical Cyclones

This study investigates Gulf Stream (GS) sea surface temperature (SST) anomalies associated with the extratropical transition (ET) of tropical cyclones (TCs) in the North Atlantic. Composites of western North Atlantic TCs indicate that GS SSTs are warmer, and both large‐ and fine‐scale SST gradients are weaker than average, for TCs that begin the ET process but do not complete it, compared with TCs that do. Further analysis suggests that the associated fine‐scale GS SST gradient anomalies are related to atmospheric processes but not the same as those that are typically associated with the onset of ET. As sensible heat flux gradients and surface diabatic frontogenesis are shown to generally scale with the local SST gradient strength, these results suggest that knowledge of the fine‐scale GS SST gradient in the weeks prior to the arrival of a TC might potentially provide additional information regarding the likelihood of that system completing ET.
Affect regulation training reduces symptom severity in depression #_#x2013; A randomized controlled trial

Deficits in general emotion regulation skills have been shown to be associated with various mental disorders. Thus, general affect-regulation training has been proposed as promising transdiagnostic approach to the treatment of psychopathology. In the present study, we aimed to evaluate the efficacy of a general affect-regulation as a stand-alone, group-based treatment for depression. For this purpose, we randomly assigned 218 individuals who met criteria for major depressive disorder (MDD) to the Affect Regulation Training (ART), to a waitlist control condition (WLC), or to a condition controlling for common factors (CFC). The primary outcome was the course of depressive symptom severity as assessed with the Hamilton Rating Scale for Depression and the Beck Depression Inventory. Multi-level analyses indicated that participation in ART was associated with a greater reduction of depressive symptom severity than was participation in WLC (d = 0.56), whereas the slight superiority of ART over CFC (d = 0.25) was not statistically significant. Mediation analyses indicated that changes in emotion regulation skills mediated the differences between ART/CFC and WLC. Thus, the findings provide evidence for enhancing emotion regulation skills as a common mechanism of change in psychological treatments for depression. The study was registered with ClinicalTrials.gov (NCT01330485) and was supported by grants from the German Research Association (DFG; BE 4510/3-1; HI 456/6-2). Future research should compare the (cost-) efficacy of ART with that of disorder-specific interventions.
Dispersal of San Joaquin kit foxes, Vulpes macrotis mutica, on Naval Petroleum Reserve No. 1, Kern County, California

Between 1980-1986, the movements of 332 pups and 267 adult San Joaquin kit foxes (Vulpes macrotis mutica) were analyzed to determine which animals had dispersed. Of 129 foxes radiocollared as pups and whose parental den ranges were known, 48 (33 males, 15 females) dispersed; about 51% dispersed between July-September, and all but 11 dispersed as pups. There was no sex-specific difference in the average date that dispersal commenced. The number of days between dispersal and death was greater for pups that delayed dispersing until they became adults. Of the 90 radiocollared adults, 23 (14 males, 9 females) dispersed. Adults were found dispersing nearly equally in all months. Foxes less than 1 y old dispersed more frequently than older animals. When dispersal distances of radiocollared pups and adults were combined, no sex-specific differences were found in the average dispersal distance of 4.0 +- 0.5 miles. However, pups dispersed 5.0 +- 0.9 miles, while adults dispersed 3.0 +- 0.5 miles. An adult male traveled 29 miles. No evidence gathered demonstrated that petroleum development activities were responsible for a tendency for more foxes to disperse from developed habitat than from undeveloped habitat. Of the dispersing radiocollared foxes that were recovered dead, 47.9% were more » killed by predators, 15.1% were killed by vehicles, 1.4% died from other causes, and 35.6% died from unknown causes. These proportions were similar to those observed for nondispersers. 35 refs., 3 figs., 15 tabs. « less
Modeling and Prediction of Large‐Scale Climate Variability by Inferring Causal Structure

This study addresses how to model and predict large‐scale climate variability, such as the El Niño–Southern Oscillation (ENSO). We introduce a framework for inferring the macroscale causal structure of the climate system using a spatial‐dimension reduction and high‐dimensional variable selection. The framework encodes the causal structure into a structural causal model, which captures the mechanisms and diversity of ENSO. It thus has a potential to reveal other physical processes within the climate system. The model predicts ENSO at a 1‐month lead time with high accuracy, and the recursive predictions at multi‐month leads are still reliable, even in a different climate state. The stand‐alone oceanic experiments capture the observed oceanic response, proving the model's capability to predict large‐scale climate variability using fragmentary information. This study demonstrates the potential for inferring causal structures to explain, model, and predict large‐scale climate variability such as ENSO.
Climatic variation in Africa and Europe has combined effects on timing of spring migration in a long-distance migrant Willow Warbler [i]Phylloscopus trochilus[i]

Background. The arrival of many species of migrant passerine in the European spring has shifted earlier over recent decades, attributed to climate change and rising temperatures in Europe and west Africa. Few studies have shown the effects of climate change in both hemispheres though many long-distance migrants use wintering grounds which span Africa. The migrants’ arrival in Europe thus potentially reflects a combination of the conditions they experience across Africa. We examine if the timing of spring migration of a long-distance migrant, the Willow Warbler, is related to large-scale climate indices across Africa and Europe.
Expression and cellular distribution of the alpha 1 gap junction gene product in the ocular pigmented ciliary epithelium.

The expression of four different gap junction (GJ) transcripts, corresponding to the alpha 1, alpha 3, beta 1 and beta 2 gene products, has been examined in the ciliary epithelium of human and bovine eyes, and in cultures of ciliary epithelial cells. Northern blot analysis revealed that alpha 1 mRNA, 3.6-kb in size, was the predominant transcript expressed in intact tissue and in cultures of pigmented ciliary epithelial cells (PE). No transcripts from the alpha 3, beta 1 or beta 2 gap junction genes were detected in intact tissue or ciliary epithelial cells as demonstrated by Northern blotting. When the levels of alpha 1 gap junction mRNA were compared between PE and NPE in primary cultures, a striking difference was observed in the level of alpha 1 transcripts: there was about a 6 to 8-fold increase in alpha 1 levels in PE cells, relative to the NPE cells. To verify the differential level of expression of alpha 1 GJ mRNA in the two cell types, indirect immunofluorescence localization studies were performed on semithin cryostat sections of ciliary processes. These studies revealed that alpha 1 gap junctions are present at the apical and lateral borders of PE cells, i.e. at the apical plasma membranes domains of PE-NPE cells, and at the lateral plasma membrane regions of PE-PE cells borders. Further analysis by immunoblotting confirmed that the 43 kD alpha 1 gap junction protein was the major gap junction gene product in the ciliary epithelium.