Miracle-dz/UniFAR-FTUs huggingface dataset:
Psychometric Validation of the Turkish Gaming Disorder Test: A Measure That Evaluates Disordered Gaming According to the World Health Organization Framework

PURPOSE: Previous research on gaming disorder (GD) used psychometric tools, which evaluates according to the American Psychiatric Association (APA) diagnostic framework. The Gaming Disorder Test (GDT), a standardized measure to assess symptoms and prevalence of GD according to the World Health Organization (WHO) diagnostic framework. The main aim of the current study was to adapt GDT to Turkish. METHOD: In the present study participants were assessed with the GDT, the Internet Gaming Disorder ScaleShort-Form (IGDS9-SF), and the CAGE-Problematic Internet Use Questionnaire (CAGE-PIUQ). The factor structure of the scale was tested with Conﬁrmatory Factor Analysis (CFA), and reliability and validity analyses were conducted. The method used in the study, and the scale adaptation, RESULTS: A sample of 932 Turkish gamers (58.3% male, mean age 23.64 years, SD=5.42) was recruited online. Confirmatory factor analyses demonstrated that the unidimensional factor structure of the GDT was satisfactory. The scale was also reliable (i.e., internally consistent with a Cronbach's alpha of 0.879) and showed adequate convergent and criterion-related validity, as indicated by statistically significant positive correlations between average time daily spent playing games (ATDSPG) during last year, IGDS9-SF and CAGE-PIUQ scores. By applying the International Classification of Diseases 11th edition (ICD-11) threshold for diagnosing GD (e.g., meeting all four criteria by answering them either with often [4] or very often [5]), it was found that the prevalence of GD is 1.9% (n = 18). CONCLUSION: Online gaming preference, ATDSPG and probable ADHD predicted the severity of disordered gaming. These findings support the Turkish version of the GDT as a valid and reliable tool for determining the extent of GD related problems among young adults and for the purposes of early GD diagnosis in clinical settings and similar research.
Effects of heat pretreatment on the yield and bioactivity of powdered egg whites hydrolysates by three different proteases

Egg white proteins have already shown great potential to generate bioactive peptides after enzymatic hydrolysis. The present study aimed to verify the influence of heat treatment on the efficiency of the hydrolysis of powdered egg white proteins by different proteases. The results were evaluated based on the hydrolysis yield, the antioxidant capacity against ABTS radical and the SDS-PAGE behavior of the hydrolysates. Heat treatment was indispensable for Alcalase to hydrolyse egg white proteins; increased the yield by pepsin hydrolysis and promoted the formation of peptides of lower molecular mass when papain was applied. Regarding the bioactivities tested, heat treatment was favorable for the hydrolysis by Alcalase, indifferent for the hydrolysis by papain and unfavorable for the hydrolysis by pepsin. The highest hydrolysis yield was obtained with pepsin (85.3%); the highest antioxidant capacity was obtained by Alcalase (5,254 μM Trolox /g sample).
Direct Binding of the Flexible C-Terminal Segment of Periaxin to β4 Integrin Suggests a Molecular Basis for CMT4F

The process of myelination in the nervous system requires coordinated formation of both transient and stable supramolecular complexes. Myelin-specific proteins play key roles in these assemblies, which may link membranes to each other or connect the myelinating cell cytoskeleton to the extracellular matrix. The myelin protein periaxin is known to play an important role in linking the Schwann cell cytoskeleton to the basal lamina through membrane receptors, such as the dystroglycan complex. Mutations that truncate periaxin from the C terminus cause demyelinating peripheral neuropathy, Charcot-Marie-Tooth disease type 4F, indicating a function for the periaxin C-terminal region in myelination. We identified the cytoplasmic domain of β4 integrin as a specific high-affinity binding partner for periaxin. The C-terminal region of periaxin remains unfolded and flexible when bound to the third fibronectin type III domain of β4 integrin. Our data suggest that periaxin is able to link the Schwann cell cytoplasm to the basal lamina through a two-pronged interaction via different membrane protein complexes, which bind close to the N and C terminus of this elongated, flexible molecule.
Antenna Selection for Target Tracking in Collocated MIMO Radar

How to utilize the limited antennas for tracking multiple targets plays a critical role in the collocated multiple-input multiple-output radar. A dynamic antenna selection strategy is proposed to address this problem. The basis of our strategy is to achieve the optimal antenna selection under the constraint of limited active antennas using the feedback information in the tracking recursion cycle, improving the worst case of estimate accuracy among multiple targets. Since the posterior Cramer–Rao lower bound quantifies the target tracking performance, it is derived and utilized as the optimization criterion. We then propose an efficient algorithm which integrates the convex relaxation technique with the local search to solve the problem. Simulation results show its superior performance compared with the random antenna selection strategy and the heuristic search algorithm. Moreover, the proposed strategy can provide the performance close to the exhaustive search method while maintaining reasonable runtime.
Fabrication of a Bioimpedance Sensor via Inkjet Printing and Selective Metallization

The significant incidence of cancer on public health in the modern industrialized world is pushing the research on novel therapeutic techniques and diagnosis tools. The latter, in particular, are of vital importance, since in many cases a prompt cancer diagnosis can significantly decrease patient’s mortality. Bioimpedance tissue analysis, in particular, is gaining attention as a promising methodology to identify tumor. Manufacturing technologies for bioimpedance probes are however still not completely adapt for cost effective mass production. In this context, the present work aims at producing a costless bioimpedance sensor by employing inkjet printing and electrolytic metal deposition. The probe manufactured in this way is successfully employed for bioimpedance testing of three animal tissues, demonstrating ability to successfully distinguish between them.
An Efficient Deep Learning Framework for Intelligent Energy Management in IoT Networks

Green energy management is an economical solution for better energy usage, but the employed literature lacks focusing on the potentials of edge intelligence in controllable Internet of Things (IoT). Therefore, in this article, we focus on the requirements of todays’ smart grids, homes, and industries to propose a deep-learning-based framework for intelligent energy management. We predict future energy consumption for short intervals of time as well as provide an efficient way of communication between energy distributors and consumers. The key contributions include edge devices-based real-time energy management via common cloud-based data supervising server, optimal normalization technique selection, and a novel sequence learning-based energy forecasting mechanism with reduced time complexity and lowest error rates. In the proposed framework, edge devices relate to a common cloud server in an IoT network that communicates with the associated smart grids to effectively continue the energy demand and response phenomenon. We apply several preprocessing techniques to deal with the diverse nature of electricity data, followed by an efficient decision-making algorithm for short-term forecasting and implement it over resource-constrained devices. We perform extensive experiments and witness 0.15 and 3.77 units reduced mean-square error (MSE) and root MSE (RMSE) for residential and commercial datasets, respectively.
Neuromuscular Password-Based User Authentication

In this article, we propose a novel neuromuscular password-based user authentication method. The method consists of two parts: surface electromyogram (sEMG) based finger muscle isometric contraction password (FMICP) and neuromuscular biometrics. FMICP can be entered through isometric contraction of different finger muscles in a prescribed order without actual finger movement, which makes it difficult for observers to obtain the password. In our study, the isometric contraction patterns of different finger muscles were recognized through high-density sEMG signals acquired from the right dorsal hand. Moreover, both time–frequency–space domain features at macroscopic level (interference-pattern EMG) and motor neuron firing rate features at microscopic level (via decomposition) were extracted to represent neuromuscular biometrics, serving as a second defense. The FMICP and macro–micro neuromuscular biometrics together form a neuromuscular password. The proposed neuromuscular password achieved an equal error rate (EER) of 0.0128 when impostors entered a wrong FMICP. Even when impostors entered the correct FMICP, the neuromuscular biometrics, as the second defense, inhibited impostors with an EER of 0.1496. To the best of our knowledge, this is the first study to use individually unique neuromuscular information during unobservable muscle isometric contractions for user authentication, with training and testing data acquired on different days.
Effects of Price Model Copycats in the Ski Industry

This article investigates the impact of the introduction of a greatly reduced seasonal ski pass for overnight stays in winter destinations. The analysis covers 59 winter sports destinations in Switzerland for the winter seasons 2012/2013 to 2017/2018, of which 11 introduced the "Magic Pass. " Winter destinations without the reduced ski pass constituted the control group. Panel difference-in-differences estimates show that the Magic Pass in 2017/2018 led to an increase in domestic overnight stays in the winter season of 31%. However, foreign overnight stays in the same period were not affected by the price discount. Overall, the magnitude of the discount price effect was lower than that of a previous attempt. Control variables such as average snow depth and temperature for the winter months of December to March were not or only marginally significant. Since the positive effects of price reductions were limited to domestic overnight stays, price reductions should be viewed critically.
NLOS Error Mitigation in Hybrid RSS-TOA-Based Localization Through Semi-Definite Relaxation

This letter focuses on the accurate target localization in non-line of sight (NLOS) environment through effective hybridization of time of arrival (TOA) and received signal strength (RSS) measurements. A non-linear weighted least square (NLWLS) problem is formulated from general approximation of hybrid maximum-likelihood (ML) estimation problem using balancing parameter i.e., mean NLOS effect. The NLWLS problem is then solved using semi-definite relaxation (SDR) technique which employs a novel convex hull constraint. The proposed method requires neither prior NLOS statistics nor NLOS path identification. The numerical simulations validate that the proposed method significantly outperforms the existing methods and achieves the performance comparatively closer to that of Cramer-Rao lower bound (CRLB).
Eignung der high throughput Version des Comet Assays als Screening-Verfahren

Es besteht ein hoher Bedarf, die steigende Anzahl an gentoxischen Verbindungen in der Umwelt und bei der Entwicklung neuer Substanzen zu erfassen. Hierzu wurde der haufig angewandte Comet Assay als high throughput-Verfahren weiterentwickelt. In der vorliegenden Arbeit wurde untersucht, inwieweit sich dieses neue high throughput Verfahren fur ein Screening auf Gentoxizitat von Umweltproben und Chemikalien wahrend der Wirkstoffentwicklung eignet. Hierzu wurde in 4 Teilarbeiten ein Vergleich zum konventionellen Comet Assay durchgefuhrt, eine automatische Auswertung entwickelt, die Anwendbarkeit verschiedenster Zellarten uberpruft und eine Studie zur Uberprufung der Gentoxizitat von Wasserproben durchgefuhrt. Die Ergebnisse zeigen, dass das entwickelte high throughput-Verfahren sich sehr gut fur das Screening einer Vielzahl von Verbindungen eignet und so eine Vereinfachung der Gentoxizitatsprufung darstellt.
Continuous Finger Gesture Spotting and Recognition Based on Similarities Between Start and End Frames

Touchless in-car devices controlled by single and continuous finger gestures can provide comfort and safety on driving while manipulating secondary devices. Recognition of finger gestures is a challenging task due to (i) similarities between gesture and non-gesture frames, and (ii) the difficulty in identifying the temporal boundaries of continuous gestures. In addition, (iii) the intraclass variability of gestures’ duration is a critical issue for recognizing finger gestures intended to control in-car devices. To address difficulties (i) and (ii), we propose a gesture spotting method where continuous gestures are segmented by detecting boundary frames and evaluating hand similarities between the start and end boundaries of each gesture. Subsequently, we introduce a gesture recognition based on a temporal normalization of features extracted from the set of spotted frames, which overcomes difficulty (iii). This normalization enables the representation of any gesture with the same limited number of features. We ensure real-time performance by proposing an approach based on compact deep neural networks. Moreover, we demonstrate the effectiveness of our proposal with a second approach based on hand-crafted features performing in real-time, even without GPU requirements. Furthermore, we present a realistic driving setup to capture a dataset of continuous finger gestures, which includes more than 2,800 instances on untrimmed videos covering safety driving requirements. With this dataset, our both approaches can run at 53 fps and 28 fps on GPU and CPU, respectively, around 13 fps faster than previous works, while achieving better performance (at least 5% higher mean tIoU).
Role of ventral subiculum neuronal ensembles in incubation of oxycodone craving after electric barrier–induced voluntary abstinence

We recently developed a rat model of incubation of oxycodone craving where opioid seeking progressively increases after voluntary suppression of drug self-administration by adverse consequences of drug seeking. Here, we studied the role of ventral subiculum (vSub) neuronal ensembles in this incubation, using the activity marker Fos, muscimol-baclofen (GABAergic agonists) inactivation, and Daun02 chemogenetic inactivation. We trained Sprague-Dawley or Fos-lacZ transgenic male and female rats to self-administer oxycodone (0.1 mg/kg/infusion, 6-h/d) for 14 days. The rats were then exposed for 14 days to an electric barrier of increasing intensity (0.1 to 0.4 mA) near the drug-paired lever that caused voluntary abstinence or were exposed to 14 days of forced abstinence. We tested Sprague-Dawley rats for relapse to oxycodone seeking without shock and drug on abstinence day 15 and extracted their brains for Fos-immunohistochemistry, or tested them after vSub vehicle or muscimol-baclofen injections on abstinence days 1 and 15. We performed Daun02 inactivation of relapse-activated vSub Fos neurons in Fos-lacZ transgenic rats on abstinence day 15 and then tested them for relapse on abstinence day 18. Relapse after electric barrier-induced abstinence increased Fos expression in vSub. Muscimol-baclofen inactivation or Daun02 selective inactivation of vSub Fos-expressing neuronal ensembles decreased “incubated” oxycodone seeking after voluntary abstinence. Muscimol-baclofen vSub inactivation had no effect on non-incubated opioid seeking on abstinence day 1 or incubation after forced abstinence. Our results demonstrate a selective role of vSub neuronal ensembles in incubation of opioid craving after cessation of drug self-administration by adverse consequences of drug seeking. Significance statement High relapse rate is a cardinal feature of opioid addiction and a major impediment for successful treatment. In humans, abstinence is often self-imposed, and relapse typically involves a conflict situation between the desire to experience the drug’s rewarding effects and negative consequences of drug seeking. To mimic this human condition, we recently introduced a rat model of incubation of oxycodone craving after electric barrier-induced voluntary abstinence. Here, we used the activity marker Fos, muscimol-baclofen (GABAergic agonists) inactivation, and Daun02 chemogenetic inactivation to demonstrate a selective role of vSub neuronal ensembles in incubation of oxycodone craving after electric barrier-induced voluntary abstinence, but not in incubation of opioid craving after forced abstinence or non-incubated opioid seeking during early abstinence.
GluonTS: Probabilistic and Neural Time Series Modeling in Python

We introduce the Gluon Time Series Toolkit (GluonTS), a Python library for deep learning based time series modeling for ubiquitous tasks, such as forecasting and anomaly detection. GluonTS simpliﬁes the time series modeling pipeline by providing the necessary components and tools for quick model development, eﬃcient experimentation and evaluation. In addition, it contains reference implementations of state-of-the-art time series models that enable simple benchmarking of new algorithms.
SEMIPARAMETRIC ESTIMATION OF DYNAMIC BINARY CHOICE PANEL DATA MODELS

We propose a new approach to the semiparametric analysis of panel data binary choice models with fixed effects and dynamics (lagged dependent variables). The model under consideration has the same random utility framework as in Honoré and Kyriazidou (2000, Econometrica 68, 839–874). We demonstrate that, with additional serial dependence conditions on the process of deterministic utility and tail restrictions on the error distribution, the (point) identification of the model can proceed in two steps, and requires matching only the value of an index function of explanatory variables over time, rather than the value of each explanatory variable. Our identification method motivates an easily implementable, two-step maximum score (2SMS) procedure – producing estimators whose rates of convergence, in contrast to Honoré and Kyriazidou’s (2000, Econometrica 68, 839–874) methods, are independent of the model dimension. We then analyze the asymptotic properties of the 2SMS procedure and propose bootstrap-based distributional approximations for inference. Evidence from Monte Carlo simulations indicates that our procedure performs satisfactorily in finite samples.
Spatiotemporal co-occurrence and overlap of two sympatric mongoose species in an urban environment

Small carnivores are becoming increasingly common in urban areas. What has received less attention is whether and how resource partitioning among sympatric species in urban areas facilitates their coexistence. We examined the spatial, temporal and combined spatiotemporal occurrence and overlap of co-existing yellow mongoose Cynictis penicillata and slender mongoose Galerella sanguinea in an urban estate in South Africa. The reserve comprised two parts, an Eco-Estate where human residential and natural areas are interspersed and wildlife has greater contact with people, and a Nature Estate, where contact is reduced by palisade fencing between people and natural areas. Using photographic data from camera traps collected over 11 consecutive months, we found a moderate level of spatial overlap between the mongoose species. Differences between the species occurred at a finer habitat scale: yellow mongooses were more common in open habitats located near human residents whereas the slender mongooses were more common in covered areas further away from human residents. The detection probability of the yellow mongoose, however, was greater than that of the slender mongoose, and the occupancy probability of the slender mongoose was reduced in the presence of the yellow mongoose. Although both species demonstrated bimodal diurnal peaks in activity, they varied in their active periods, with temporal overlap being greater during colder than warmer months. No complete spatiotemporal overlap (occurrence in the same place at the same time/within a 10-min period) occurred. This may have been as a result of the difference in detection and occupancy probabilities of the two species. Resource availability (food), however, appears to influence the different habitat selection, space use, and activity patterns of yellow and slender mongoose in the study area. Therefore, we conclude that partitioning along the spatial and somewhat on the temporal dimensions aids in the coexistence of these mongoose species in an urban environment.
Effects of leaves extract of Eichhornia crassipes on seed germination and seedling growth of Pinus roxburghii and Bauhinia purpurea

E. crassipes is threatening the aquatic diversity in famous lakes of Nepal. Thus, this study was objectively carried out to evaluate the effects of extract of E. crassipes on seed germination and seedling growth of Pinus roxburghii and Bauhinia purpurea, assess the soil nutrients according to proportion of extract and distilled water. Leaves of E. crassipes were collected from Phewa lake. Next, laboratory techniques were applied for oven drying, soaking, shaking incubator, centrifuging, filtering and dilution. Altogether 120 polypots, 60 each from Pinus roxburghii and Bauhinia purpurea were used for seed germination. So, 15 replicates for each block representing concentration of extract: distilled water (75:25, 50:50, 25:75 and control). Records were taken between 18 th March and 24 th April, 2018. Temperature and humidity were recorded on 0700, 1300 and 1900 hours. Soil N, P, K, C and pH of different concentrations were analyzed in the lab. It was found that the highest germination in 25:75 concentration specifically 14 and 11 in P. roxburghii and B. purpurea respectively. The diameter of P. roxburghii was the highest in 25:75 with 1.52 mm while it was the highest in 75:25 with 1.34 mm of B. purpurea. The average height of seedling growth of P. roxburghii was the highest in 25:75 concentration having 8.24 cm. The highest record of needles 12 was found in 75:25 concentration. The repeated measures ANOVA showed that there were significant differences in seed germination and seedling growth at 95% confidence level. The nutrient analysis showed that, the highest N%, P 2 O 5 kg/ha, K 2 O kg/ha and C% were 0.22, 30.30,1359.60 and 2.56 respectively in P. roxburghii at 75:25 concentration. The R 2 values of temperature vs germination was 0.16 and this was 0.01 for P. roxburghii and B. purpurea respectively. This research will be useful tool to utilize this for efficient organic fertilizer for forest nursery work.