Miracle-dz/UniFAR-FTUs huggingface dataset:
Model fit and reliability of the Hungarian version of the Revised Exercise Addiction Inventory (EAI-R-HU)

The Exercise Addiction Inventory (EAI) is a brief validated instrument adopted by many to assess the risk of exercise addiction. Its revised version (the EAI-R) has been recently validated in English with a predominantly male sample. The current work examined the model fit, validity and reliability of the Hungarian version of the EAI-R (EAI-R-HU). This cross-sectional study was conducted online. A convenience sample of regular exercisers (n = 253) completed the EAI-R-HU and answered demographic questions. Confirmatory factor analysis revealed a good model fit for the Hungarian version of the instrument. The internal reliability of the EAI-R-HU was (Cronbach’s α) . 71. Considering the top 20% of the EAI-R-HU scores, 5.1% of the sample was at risk of exercise addiction. Team exercisers did not differ from individual exercisers in the risk of exercise addiction. Age and exercise characteristics predicted weakly but statistically significantly the risk of exercise addiction. The EAI-R-HU possesses a good model fit, and its internal reliability is acceptable. These findings complement the original revision of the EAI-R, based on a largely (87.7%) male sample compared to the current research primarily based on female participants (76.7%). While cultural differences might exist, the present results encourage the use of the EAI-R with women too and with Hungarian samples, in general.A Testedzésfüggőség Kérdőív (EAI) egy rövid, validált eszköz, amelyet a testedzésfüggőség kockázatának felmérésére használnak. Az angol nyelvű módosított változatát (EAI-R) nemrégiben egy többségében férfiakból álló mintán validálták. Jelen kutatás a magyar változat (EAI-R-HU) egyfaktoros elméleti struktúrájának illeszkedését, validitását, és a kérdőív belső megbízhatóságát vizsgálta. A hozzáférhetőségi mintavétellel zajló adatgyűjtés online történt. Rendszeresen edző önkéntesek (n = 253) kitöltötték a módosított EAI-t (EAI-R-HU) és megválaszolták a demográfiai kérdéseket. A megerősítő faktoranalízis jó modellillesztést mutatott, a skála belső megbízhatósága (Cronbach-α) pedig 0,71 volt. Az EAI-R-HU pontszámok felső 20%-át figyelembe véve, a jelen minta 5,14%-a volt feltételezhetően a testedzésfüggőség kockázatának kitéve. A csoportban edzők nem különböztek az egyéni edzést végzőktől a testedzésfüggőség kockázatát illetően. Az életkor és a testmozgás egyes jellemzői gyengén, de statisztikailag szignifikánsan prognosztizálták a testedzésfüggőség kockázatát. Az eredmények alapján az EAI-R-HU jó modellalkalmazással rendelkezik és a belső megbízhatósága elfogadható. Ezek a megállapítások kiegészítik az angol EAI-R változatát, amely nagyrészt (87,7%) férfi minta alapján jött létre, szemben a jelen kutatással, amely elsősorban női résztvevőkön alapszik (76,7%). Bár létezhetnek kulturális különbségek, a jelenlegi eredmények ösztönzik az EAI-R alkalmazását a nőknél is és az EAI-R-HU felhasználását magyar kutatásokban.
Three-Dimensional Thermal Analysis of Three-Phase Enclosed GIS Bus Bars

The ampacity of GIS bus bars is limited by the maximum operation temperature of the contacts. This paper employs the coupled eddy current, fluid and thermal finite-element method (FEM) to solve the three-dimensional (3-D) heat transfer problem in a three-phase enclosed GIS bus bar. The contact resistance is considered and described as a resistor between the conductor and the contact finger. In order to avoid convective boundary condition on the tank surface which is not easy to apply, the ambient air is introduced into the solution region. The temperature dependent thermal properties of SF 6 gas and air are considered. The temperatures calculated by proposed model are found to be in good agreement with the experimental data of a 126 kV three-phase enclosed bus bar prototype.
Anomaly based Intrusion Detection using Neural Networks in 5G Network

Abstract: Ensuring the organizations of tomorrow is set to be a difficult space due to expanding digital protection dangers and enlarging assault surfaces made by the Internet of Things (IoT), expanded organization heterogeneity, expanded utilization of virtualisation innovations and circulated structures. This paper proposes SDS (Software Defined Security) which is a method gives mechanized, adaptable and versatile framework. SDS will tackle momentum progresses in AI to plan a CNN (Convolutional Neural Network) utilizing NAS (Neural Architecture Search) to distinguish irregular organization traffic. SDS can be applied to an interruption location framework to make a more proactive and start to finish protection for a 5G organization. To test this presumption, ordinary and irregular organization streams from a mimicked climate have been gathered and examined with a CNN. The outcomes from this strategy are promising as the model has recognized harmless traffic with a 100% exactness rate and irregular traffic with a 96.4% identification rate. This exhibits the viability of organization stream investigation for an assortment of normal pernicious assaults and furthermore gives a suitable alternative to discovery of encoded vindictive organization traffic. Keywords: 5G Security, IoT Security, Automated Intrusion Detection Systems, Convolutional Neural Networks, Artificial Intelligence, Software Defined Security
Investigating Relationships Between Vision Components and Hospital Performance: Proposed Model

Surprisingly little research has been conducted on what constitutes an “effective” vision, and yet leaders are widely exhorted to employ visions. A research model is proposed for investigating relationships between “effective” vision components and the performance of hospital wards, as measured by patient and nursing staff satisfaction. The model, expressed both graphically and as three research propositions, proposes that vision attributes of brevity, clarity, abstractness, challenge, future orientation, stability, and desirability, and vision content relating to patient and nursing staff satisfaction, can directly affect performance. However, the model also predicts indirect effects on performance mediated by six intervening variables.
Single-crystal sapphire fiber-based strain sensor for high-temperature applications

Single-crystal sapphire fibers have a very high melting point (up to 2050/spl deg/C), which renders them a very good candidate for sensing applications at a very high temperature. We present in this paper the recent work of developing single-crystal sapphire fiber extrinsic Fabry-Perot interferometric strain sensors based on the white-light interferometric spectrum demodulation technique. Prototype sapphire strain sensors were fabricated and tested at high temperatures up to 1004/spl deg/C. The preliminary experimental results indicate that the sensors are promising to be used under high-temperature environments for making strain measurements with strain measurement resolution of 0.2-/spl mu/ strain.
A novel deep neural network for hidden target detection in images

The significant similarity between the hidden target and the background makes it difficult to find camouflaged people, such as warriors in warfare, or even camouflaged objects in natural environments. Hence, it is hard to ascertain these concealed targets. To address this issue, a novel deep neural network is proposed in this paper that produces an estimated mask within the hidden target for an input image. Our approach consists of two phases: hidden target segmentation and hidden target identification. For the first phase, we propose the Multilevel Attention Network (MA-Net), which generates the camouflaged target mask based on a Multi-Attention Module (MAM) that helps distinguish the hidden people from the background. Later on, the concealed target will be highlighted in the second phase. Experimental results on the camouflaged people dataset demonstrate that our proposed method can achieve state-of-the-art performance for hidden target detection.
Functionalized Fe3O4 Nanoparticles as Glassy Carbon Electrode Modifiers for Heavy Metal Ions Detection—A Mini Review

Over the past few decades, nanoparticles of iron oxide Fe3O4 (magnetite) gained significant attention in both basic studies and many practical applications. Their unique properties such as superparamagnetism, low toxicity, synthesis simplicity, high surface area to volume ratio, simple separation methodology by an external magnetic field, and renewability are the reasons for their successful utilisation in environmental remediation, biomedical, and agricultural applications. Moreover, the magnetite surface modification enables the successful binding of various analytes. In this work, we discuss the usage of core–shell nanoparticles and nanocomposites based on Fe3O4 for the modification of the GC electrode surface. Furthermore, this review focuses on the heavy metal ions electrochemical detection using Fe3O4-based nanoparticles-modified electrodes. Moreover, the most frequently used electrochemical methods, such as differential pulse anodic stripping voltammetry and measurement conditions, including deposition potential, deposition time, and electrolyte selection, are discussed.
Biologically Feasible Generative Neural Network Architecture with Effective Concept Learning Capacity

Representations play an essential role in the learning of artificial and biological systems due to their capacity to identify characteristic patterns in the sensory environment. In this work we examined latent representations of several sets of images, such as basic geometric shapes and handwritten digits, produced by generative models in the process of unsupervised generative learning. A biologically feasible neural network architecture based on bi-directional synaptic connection equivalent in training and processing to a symmetrical autoencoder was proposed and defined. It was demonstrated that conceptual representations with good decoupling of concept regions can be produced with generative models of limited complexity; and that incremental evolution of architecture can result in improved ability to learn data of increasing conceptual complexity, including realistic images such as handwritten digits. The results demonstrate potential of conceptual representations produced as a natural platform for conceptual modeling of sensory environments and other intelligent behaviors.
Rover Mosaic : e-mail communication for a full-function Web browser

The increasing availability and power of mobile computing devices are creating a demand for network applications which can accommodate slow or intermit-tently available network connections. A prototype system for browsing the World Wide Web on such a network was implemented, using caching, prefetching, and queued communications to hide communication latencies. Electronic mail was used as the underlying transport mechanism because of its ubiqui-tousness and fundamentally queued operation. A modified user interface based on NCSA Mosaic was designed to accommodate queued communications. The experimental system was found to be well-suited to the task, as well as to have significant advantages in the areas of reliability and user interface functional-i ty.
Displacement Smoothing and Strain Estimation Using Savitaky-Golay Filters in Digital Image Correlation

Recently, many research works were concentrated on how to improve the accuracy of displacement fields in digital image correlation (DIC). However, the original displacement fields calculated at discrete locations using DIC are unavoidably contaminated by noises. If the strain fields are directly computed by differentiating the original displacement fields, the noises will be amplified even at a higher level and the resulting strain fields are untrustworthy. To acquire reliably estimation of strain fields, in this paper, Savitaky-Golay (SG) filters are introduced to obtain smoothed displacement fields and reasonable strain estimation. The principle of two-dimensional SG filters is described in detail first. Then images of uniaxial tensile and three-point bending experiments were used to verify the proposed approach. The resulting smoothed displacement fields and strain fields clearly show that the proposed method is simple and effective.
Feasibility study on ultralong‐cycle operation and material performance for compact liquid metal‐cooled fast reactors: a review work

This paper reviews the feasibility of ultralong‐cycle operation on a compact liquid metal‐cooled fast reactor (LMR) firstly by assessing the operation of a long‐life fast reactor core and secondly by evaluating material performance in respect to both long‐cycle operation and compact‐size fast reactor. Many kinds of reactor concepts have been proposed, and LMR and small modular reactor (SMR) are the issued leading technologies for generation four (Gen‐IV) reactor system development. The breed‐and‐burn strategy was proposed as a core burning strategy to operate a long cycle, and it has been evaluated in this paper with two reactor concepts: constant axial shape of neutron flux, nuclide densities, and power shape during life of energy and ultralong cycle fast reactor. In addition, Super‐Safe, Small, and Simple and small modular fast reactor, compact LMR concepts, have been simulated to evaluate their long‐life operation strategies. For the other practical issues, the materials for fuel, coolant, and structure have been identified and some of them are selected to have their performance optimized specifically for compact LMR with a long‐cycle operation. It is believed that this comprehensive review will propose a proper direction for future reactor development and will be followed by the next step research for a complete reactor model with the other reactor components. Copyright © 2015 John Wiley & Sons, Ltd.
Prevalence and Predictors for Depression among Medical Students during Coronavirus Disease-19 Pandemic: A Cross-sectional Study

BACKGROUND: Since the declaration of the World Health Organization of the coronavirus (SARS-COV-2) as a pandemic, several countries have locked down and quarantined their residents with restrictive procedures to control spread of the disease. Due to pandemic related stressors, concerns and worries have developed regarding negative psychological impact on the mental well-being of the general population, particularly those known to have higher levels of psychological impairment with high vulnerability to mental health diseases such as medical students. AIM: The objectives of the study were to assess the prevalence of self-reported depression and to explore its predictors during the period of Coronavirus Disease 2019 first lock down among medical students. METHODS: This was a cross-sectional study design. The study was conducted at Kasr Alainy Medical School, Faculty of Medicine, Cairo University, Egypt, in June 2020. A simple random sample was picked of one subgroup of 4th year medical students (No. = 300) at faculty of medicine during the academic year 2019–2020. Self-administered questionnaires including Beck’s Depression Inventory scoring were distributed using Google form through communication social media such as WhatsApp. RESULTS: Out of the 300 participants, 238 responses were received with response rate 79.3%. Results indicated that 38.2% of the respondents were experiencing depression with different degrees with Beck’s Depression Inventory mean scores was 19.4 ± 11.6. Multiple logistic regression analysis point out that gender (odds ratio [OR] = 2.4 and p = 0.022) and “Good” grade level of academic performance (OR = 7.2 and p = 0.045) are significant predictors for developing depression among the participating medical students. CONCLUSION: A significantly high prevalence of depression is detected among medical students during the first wave of the SARS-COV-2 pandemic. The prevalence of depression is more among females than males and more with medical students achieving “Good” grade level.
Ultra-energy-efficient CMOS/magnetic nonvolatile flip-flop based on spin-orbit torque device

The spin-orbit-torque magnetic tunnel junction (SOT-MTJ) is a promising device for data storage. Most of the issues encountered with scalable spin transfer-torque (STT) devices are visibly moved. Thanks to a three-terminal architecture, the reliability is increased by separating the read and the write paths. Furthermore, SOT-induced magnetisation switching can be very fast, thanks to a low-resistive writing path. The writing operation is symmetrical. Thus, it requires the same current density to switch between the parallel and antiparallel states. All these advantages make the SOT-MTJ device an ultimate candidate for introducing non-volatility in ultra-fast and power-efficient integrated circuits. A mixed CMOS/magnetic non-volatile flip-flop (NVFF) is described. The proposed architecture offers the possibility to use the usual CMOS flip-flop functionality with possible magnetic data store and restore operations while keeping non-volatility when the circuit is powered off. With a 135 nm dimension, the SOT-MTJ-based NVFF demonstrated a very high switching with a 5× decrease in terms of writing energy/bit when compared with an STT device.
Multichannel adaptive filtering for signal enhancement

An adaptive technique for enhancing a signal against additive noise is described. It makes use of two or more input channels containing correlated signal components but uncorrelated noise components. The various input signals need not be of the same waveshape, since the adaptive enhancer filters the inputs before summing them. The output is a best least squares estimate of the underlying signal in a chosen input channel. Adaptivity allows optimal performance even though the signal and noise characteristics differ from channel to channel and are unknown a priori. Formulas for signal distortion and output noise power are developed. The more input channels available containing correlated signal components, the better will be the system performance. Excellent performance is obtained when the sum of the filter input signal-to-noise ratios (SNR's), defined as functions of frequency, is large compared to unity at all frequencies of interest. In this case the output noise is small, the output signal distortion is small, and the output SNR is approximately equal to the sum of the filter input SNR's. As such, the multichannel adaptive signal enhancer is a generalization of the classic time-delay-and-sum beamforming antenna.
Bio-Based Bisbenzoxazines with Flame Retardant Linker

This work explores the strategy of incorporating a highly substituted reactive flame retardant into a benzoxazine moiety. For this purpose, a DOPO-based flame retardant received a chain extension via reaction with ethylene carbonate. It was then reacted with phloretic acid to obtain a diphenol end-capped molecule, and further reacted with furfurylamine and paraformaldehyde to obtain a benzoxazine monomer via a Mannich-like ring closure reaction. This four-step synthesis yielded a partly bio-based halogen-free flame retardant benzoxazine monomer (DOPO-PA-fa). The successful synthesis was proven via NMR, IR and MS analysis. The polymerization behavior was monitored by DSC and rheological analysis both showing the polymerization starts at 200 °C to yield pDOPO-PA-fa. pDOPO-PA-fa has a significant thermal stability with a residual mass of 30% at 800 °C under ambient atmosphere. Furthermore, it reached a V-0 rating against small flames and an OI of 35%. Blended with other benzoxazines, it significantly improves their thermal stability and fire resistance. It emphasizes its potential as flame retardant agent.
Evaluation of reliability worth in composite systems based on pseudo-sequential Monte Carlo simulation

This work describes a new methodology for calculating total system interruption costs in composite generation and transmission systems. The proposed approach, called pseudo-sequential simulation, is based on the nonsequential Monte Carlo sampling of system states and on the chronological simulation of only the sub-sequences associated with failed states. Case studies with the IEEE Modified Reliability Test System (MRTS) and a 415-bus system derived from the Brazilian Southeastern region are presented and discussed. >
Investigations on the Accumulation, Tissue Distribution and Toxicity of Silver Nanoparticles in Amammalian Model

The current work aimed to investigate the potential toxicity of Ag-NPs in male rabbits as a mammalian model, following acute and sub-acute dermal exposure terms. The rabbits were topically exposed to a single acute dose of 2.0% Ag-NPs and the assessments were conducted4 days latter, while a dose of 0.5% was administered every other day for the sub-acute exposure in two time periods (7 and 14 days). The accumulation and retention of Ag+ ions in the skin and their distribution in other vital tissues were measured. In addition, the concentrations of total proteins, lipidparameters and levels of different oxidative stress biomarkers in the skin were also evaluated. The results demonstrated the ability of Ag-NPs to penetrate the skin and accumulate rapidly in the dermal skin, then spread out to the blood and other vital organs. The spleen and liver seemed to be the main target organs. The high levels of Ag+ tissue accumulation affected the concentration of total proteins and acted as a stressor stimulus within the skin, thereby, initiating oxidative stress. The liberated ROS caused disruption of the activities of the antioxidant enzymes GST, GSH, GR, GPx, SOD and CAT as well as increased levels of H2O2 and MDA. The current work showed that the toxicity of Ag-NPs could be attributed to the release of Ag+ ions and the subsequent excessive generation of ROS.
Frontiers in Dentistry

Article type: Case Report Dens invagination (DI) is a dental anomaly that can cause pulpal and periapical pathoses of the affected tooth. We describe the treatment of a healthy 18-year-old female with a chief complaint of recurrent facial swelling pertaining to a peg-shaped maxillary lateral incisor with DI. Examinations showed necrosis of the involved tooth with symptomatic apical periodontitis. Cone-beam computed tomography corresponded to Oehlers type II DI. Orthograde endodontic treatment was performed. To completely debride the canal and resolve the persistent purulent discharge, various methods and medicaments were used in separate sessions including passive ultrasonic activation of 5.25% sodium hypochlorite solution, calcium hydroxide mixed with 2% chlorhexidine, and double antibiotic paste as intracanal medicament. After resolution of the symptoms, the root canal and the invaginated space were filled by a mineral trioxide aggregate plug and backfilled with thermoplasticized gutta-percha. At the one-year follow-up, complete bone healing was noted in the affected periradicular area.