Miracle-dz/UniFAR-FTUs huggingface dataset:
HV dielectric strength of shielding electrodes in vacuum circuit-breakers

The subject of this paper is the HV dielectric strength of shielding and field-grading electrodes in vacuum circuit-breakers. It describes the effects exerted by various geometrical parameters, the surface area and the material of the shielding on the breakdown behavior of shielding. The experiments were performed with a shielding electrodes model and were carried out under lightning impulse voltage. The dielectric results are discussed by means of field simulations.
Prevention of Carbody Vibration of Railway Vehicles Induced by Imbalanced Wheelsets with Displacement-Dependent Rubber Bush

This paper discusses the issue of carbody excitation of railway vehicles due to rotation of imbalanced wheelsets and proposes a simple and cost-effective countermeasure. The basic mechanisms of the carbody excitation are first described, then a displacement-dependent rubber bush, which is used for the connection between bogie frame and carbody, is proposed. The displacement-dependent property is realized by introducing a small gap between the rubber and the inner fixture, and the transmission of excitation force with high-frequency and small displacement are isolated by the gap. The small gap can be created naturally just by skipping the bonding process of rubber and inner fixture, so it is very simple and cost-effective countermeasure against this issue. The stiffness property can be tailored to meet the requirements from motional properties of the bogie by applying a Finite Element Analysis (FEA). The effectiveness and validity of the displacement-dependent rubber bushes applied for traction links are investigated and confirmed by both numerical calculation and excitation test using a full-scale test vehicle in the rolling stock testing plant.
List of Species and Conservation Status of Avifauna and Small mammal around Bade Segment Area of River Yobe, Yobe State, Nigeria

The study was carried out to assess a Checklist of avifauna and small mammal species along Bade catchment area of Yobe State, Nigeria. Preliminary survey was conducted around the river, three (3) habitat types were identified; (river bank, farm lands and flood plain). The line transect was 8 km in length. Two (2) transects were established per habitat type, making a total of six (6) transects. The transects were 100 m apart to the left or right in order to avoid double counting of species. A distance of 200m was maintained between each habitat. The data obtained were analyses using descriptive statistics (Frequency tables and Charts were used to portrayed the findings. The result of the study; showed that a total of 50 bird species in 28 families were recorded. RB had the highest individuals of Fifty (50) species while FP has the lowest with ten (10) species. The Bird family Columbidae has the highest number with six (6) of species, while the lowest were Ardeidae, Sturnidae and Tytonidae with one species in each of the habitat types. However, checklist of small mammal species also indicated that a total of 6 species of small mammals belonging to 4 families were identified. The result of the study shows that the family Muridae has 3 species which was the highest number of per family identified in the study area, this is due to the fact that Muridae family are the most common small mammals in the study area. And both bird small species fell under least concern (LC) category except Pallid Harrier Circus macrourus which felled under near threatened (NT) species. However, awareness campaign should also be organize for the residents around the study area on the presence, distribution of bird and small mammal species and also disturbing effect of their activities on bird and small mammal around the segment area of river Yobe.
Impact of psychological safety on supply chain operational performance

ABSTRACT This study examines the relationship between psychological safety and operational performance in the context of supply chain partners, i.e. an inter-organisational setting. While collaboration among supply chain partners enables effective problem solving and generates innovation, such collaborations may result in superior performance improvements when a psychologically safe business environment is created along the supply chain. The analysis of this study is based on data collected from 241 manufacturing companies in China using a survey questionnaire. A confirmatory factor analysis (CFA) was conducted to assess the validity of the measures, and an ordinary least squares (OLS) regression was used to test the hypotheses. Study results indicate that there is a significant positive association between psychological safety and operational performance in the context of supply chain partners. The results further show the relationship to be moderated by the learning orientation and inter-functional coordination. While the effect of psychological safety on performance has been studied in intra-organisational settings, studies on the psychological safety – performance relationship in an inter-organisational setting are scant. This study contributes to the literature in psychological safety and supply chain management as it extends the relationship to the context of supply chain partners.
Low-stiffness silicon cantilevers with integrated heaters and piezoresistive sensors for high-density AFM thermomechanical data storage

Single-crystal silicon cantilevers 1 /spl mu/m thick have been demonstrated for use in high-density atomic-force microscopy (AFM) thermomechanical data storage. Cantilevers with integrated piezoresistive sensors were fabricated with measured sensitivities /spl Delta/R/R up to 7.5/spl times/10/sup -7/ per /spl Aring/ in close agreement with theoretical predictions. Separate cantilevers with integrated resistive heaters were fabricated using the same basic process. Electrical and thermal measurements on these heating devices produced results consistent with ANSYS simulations. Geometric variants of the cantilever were also tested in order to study the dependence of the thermal time constant on device parameters. Depending on the design, time constants as low as 1 /spl mu/s were achieved. A thermodynamic model was developed based on the cantilevers geometry and material properties, and the model was shown to predict device behavior accurately. A comprehensive understanding of cantilever functionality enabled us to optimize the cantilever for high-speed thermomechanical recording.
Denial-of-Service Attack Detection over IPv6 Network Based on KNN Algorithm

With the rapid increase and complexity of IPv6 network traffic, the traditional intrusion detection system Snort detects DoS attacks based on specific rules, which reduces the detection performance of IDS. To solve the DoS intrusion detection problem in the IPv6 network environment, the lightweight KNN optimization algorithm in machine learning is adopted. First, the double dimensionality reduction of features is achieved through the information gain rate, and discrete features with more subfeatures are selected and aggregated to further dimensionality reduction and feature dimension of the actual operation. Secondly, the information gain rate is used as the weight to optimize the sample Euclidean distance measurement. Based on the proposed measure of the reverse distance influence, the classification decision algorithm of the KNN algorithm is optimized to make the detection technology better. The effect is further improved. The experimental results show that the traditional TAD-KNN algorithm based on average distance and the GR-KNN algorithm that only optimizes the distance definition, the GR-AD-KNN algorithm can not only improve the overall detection performance in the detection of IPv6 network traffic characteristics but also for small groups of samples. As a result, classification has better detection results.
Highway Regional Classification Method Based on Traffic Flow Characteristics for Highway Safety Assessment

Accurate regional classification of highways is a critical prerequisite to implement a tailored safety assessment. However, there has been inadequate research on objective classification considering traffic flow characteristics for highway safety assessment purposes. We propose an objective and easily applicable classification method that considers the administrative divisions of South Korea. We evaluated the feasibility of this method through various theoretical analysis techniques using the data collected from 536 permanent traffic volume counting stations for the national highways in South Korea in 2019. The ratio of the annual average hourly traffic volume to the annual average daily traffic was used as the explanatory variable. The corresponding results of factor and cluster analyses with this ratio showed a 61% concordance with the urban, suburban, and rural areas classified by the administrative divisions. The results of two-sample goodness-of-fit tests also confirmed that the difference in the three distributions of hourly volume ratios was statistically significant. The results of this study can help enhance highway safety and facilitate the development and application of more appropriate highway safety assessment tools, such as Road Assessment Programs or crash prediction models, for specific regions using the proposed method.
Effects of Inclusion of N-Carbamylglutamate in the Non-Protein Diet on Growth and Slaughter Performance, Meat Quality, Nitrogen Metabolism and Antioxidant of Holstein Bulls

Simple Summary Using dietary non-protein nitrogen is an effective way to decrease the dependence on protein resources in cattle production. N-carbamylglutamate (NCG) is a structural analogue of N-acetylglutamate (NAG), which is a precursor of endogenous Arg synthesis. NCG improves urea cycling and enhances the endogenous synthesis of Arg, nitric oxide synthase and NO. The present study showed that beef benefited from being fed NCG product in the urea diet by enhancing its growth and slaughter performance, meat quality, nitrogen metabolism and plasma amino acids. Abstract The objectives of this experiment were to investigate the effects of N-carbamylglutamate (NCG) on growth and slaughter performance, meat quality, nitrogen utilization, plasma antioxidant and amino acids of Holstein bulls. In this case, 24 Holstein bulls (490 ± 29.0 kg of body weights and 540 ± 6.1 d of age) were blocked by body weights and age and randomly assigned to 1 of 4 groups: (1) CON group: bulls were fed the control diet, (2) CON + NCG group: bulls were fed the control diet with 40 mg/kg BW NCG, (3) Urea group: bulls were fed the urea diet, and (4) Urea + NCG group: bulls were fed the urea diet with 40 mg/kg BW NCG. Feeding NCG significantly improved ADG, FCR, DM and CP digestibility, carcass weight, slaughter weight, DOP, eye muscle area, shear force (p = 0.001) and reduced L* of color, drip loss and cooking loss. Concurrently, feeding the urea diet induced a decreased ADG, carcass weight and slaughter weight, DOP, eye muscle area and shear force. NCG decreased contents of fecal N and urinary N, plasma urea in bulls and ammonia but increased N retention and utilization, plasma NO, plasma Arg, Leu, Ile and Tyr. On the other hand, feeding the urea diet increased urinary N, plasma urea and ammonia. Thus the study efficiently demonstrates that beef benefited from being fed a NCG product in the urea diet by enhancing its growth and slaughter performance, meat quality, nitrogen metabolism and plasma amino acids.
Mediating Role of Computer Experience in the Association between MOOC-efficacy and Meaningful Learning

This study examines three critical constructs in twenty-first-century e-education — MOOC-efficacy, meaningful learning, and computing experience — among undergraduate students at selected public universities in Malaysia. Its primary purpose is to investigate the mediating function of computer experience in the link between MOOC-efficacy and meaningful learning. This study defines MOOC-efficacy based on four aspects (information searching, making queries, MOOC learning, and MOOC usability). Meanwhile, meaningful learning is conceptualised in five dimensions (i.e.cooperative learning, active learning, authentic learning, constructive learning, and intentional learning). This study incorporated a cross-sectional survey design. The data were acquired using a 52-item questionnaire whose reliability indices for the dimensions ranged from 0.822 to 0.890. The study’s population comprises university students with prior experience using MOOCs and volunteered to participate in the study. Simple random selection was used to get a sample of 603 students. The Structural Equation Modeling (SEM) test of bootstrapping for mediation was used for data analysis. The findings suggest no evidence of a mediation impact of computer experience on MOOC-efficacy and meaningful learning. The findings add to our understanding of how an open online ecosystem function. This study provides insights that could be used to meet the requirements and preferences of learners. MOOC-efficacy interventions are critical for motivating students to engage in meaningful learning on the e-learning platform.
Evaluation of the Multiplex Real-Time PCR DermaGenius® Assay for the Detection of Dermatophytes in Hair Samples from Senegal

For the successful treatment of dermatophytoses, especially tinea capitis, there is a need for accurate and rapid diagnostic methods. A lot of recent literature has focused on the detection of dermatophytes directly on sample material such as nails, hair and skin scrapings. Molecular tools offer the ability to rapidly diagnose dermatophytosis within 48 h. This study aimed to compare the results of a commercial real-time PCR (real-time PCR) assay DermaGenius®(DG) 2.0 complete multiplex kit with those of conventional diagnostic methods (direct microscopy and culture). A total of 129 hair samples were collected in Dakar (Senegal) from patients suspected of dermatophytosis. DG was applied for the molecular detection of Candida albicans, Trichophyton rubrum/soudanense, T. interdigitale, T. tonsurans, T. mentagrophytes, T. violaceum, Microsporum canis, M. audouinii, Epidermophyton floccosum, T. benhamiae and T. verrucosum. Dermatophytes species and C. albicans were differentiated by melting curve analysis. The sensitivity and specificity of the PCR assay were 89.3% and 75.3%, respectively. DG PCR was significantly more sensitive than culture (p < 0.001). DG PCR is fast and robust to contamination. In this paper, the main questions discussed were the replacement of culture by a broad-spectrum fungal real-time PCR and the implementation of DG PCR into a routine laboratory in Senegal.
Transient Nonisothermal Fully Coupled Wellbore/Reservoir Model for Gas-Well Testing, Part 1: Modelling

A numerical fully implicit nonisothermal wellbore/reservoir simulator is developed. The model entails simultaneous solution of transient coupled mass-, momentum-, and energy-balance equations within the wellbore; energy-balance equations for the tubular and cement materials and the formation surrounding the wellbore; and mass-balance and flow-rate/pressure equations for the reservoir formation. A wellbore heat-loss model that is a strong feature of this study is developed and employed in the model to improve the accuracy of the simulator and to be able to estimate the casing temperature and formation-temperature distribution. The model formulation is completed with an equation of state (EOS) to estimate fluid properties and appropriate friction-factor correlations in the wellbore tubing to compute the frictional pressure drop for different flow regimes. The developed model has several applications in the petroleum industry, particularly in the gas-well testing design and interpretation of both isothermal and nonisothermal gas reservoirs. This nonisothermal simulator is validated through comparisons to both analytical models and an equivalent numerical isothermal coupled wellbore/reservoir simulator that is also developed in this paper. Applications of this simulator to analyzing gas-well testing problems, in addition to several important observations, are extensively studied in Part 2 of this research work (Bahonar et al. 2010). Currently, it has been well accepted that the applicability and significance of a reservoir simulator depend on the behaviour of the wellbore and interaction between the wellbore and reservoir. A robust, accurate coupled wellbore and reservoir simulator is an invaluable tool for the petroleum engineer to help the petroleum industry understand production behaviour, make a meaningful prediction, and make correct decisions in all field-development and production stages.
Growth-limiting drought stress induces time-of-day-dependent transcriptome and physiological responses in hybrid poplar

Drought stress negatively impacts the health of long-lived trees. Understanding the genetic mechanisms that underpin response to drought stress is requisite for selecting or enhancing climate change resilience. We aimed to determine how hybrid poplars respond to prolonged and uniform exposure to drought; how responses to moderate and more severe growth-limiting drought stresses differed; and, how drought responses change throughout the day. We established hybrid poplar trees (Populus x ‘Okanese’) from unrooted stem cutting with abundant soil moisture for six weeks. We then withheld water to establish well-watered, moderate, and severe growth-limiting drought conditions. These conditions were maintained for three weeks during which growth was monitored. We then measured photosynthetic rates and transcriptomes of leaves that had developed during the drought treatments at two times of day. The moderate and severe drought treatments elicited distinct changes in growth and development, photosynthetic rates, and global transcriptome profiles. Notably, the time of day of sampling produced the strongest signal in the transcriptome data. The moderate drought treatment elicited global transcriptome changes that were intermediate to the severe and well-watered treatments in the early evening, but did not elicit a strong drought response in the morning, emphasizing the complex nature of drought regulation in long-lived trees. Highlight Poplar drought transcriptome is defined by the time of day of sampling and by the extent of water deficit.
Experimental CDMA data overlay of GSM network

A broadband 64 Kbit/s DS-CDMA overlay which operates on the same carrier frequency as a downlink GSM signal is proposed. Error free operation of both systems has been demonstrated over a 70 dB power range. A novel CDMA receiver architecture allowed programmable digital notch filters to be implemented directly at RF. It is shown that the overall network capacity is increased by a factor of 3.3 compared to the case of a single GSM carrier only, as detailed in a previous theoretical analysis. This represents the first experimental demonstration of a CDMA overlay of a GSM network.
A Hierarchical Hybrid Subtask Scheduling Algorithm in UAV-Assisted MEC Emergency Network

As a technique to buffer the conflict between computation-intensive tasks and capability-limited devices, unmanned aerial vehicle-enabled mobile-edge computing (UAV-MEC) has been witnessed as a promising approach, especially in the post-disaster scenario where the infrastructure is limited or unavailable. In this article, we consider a joint optimization of topology reconstruction and subtask scheduling to minimize the average completion time of the subtask. To address this problem, we propose a hierarchical hybrid subtask scheduling algorithm (H-HSS). First, a topology reconstruction game algorithm for energy-efficient control (TRGE) is investigated to get optimal power and node-to-node connection decision, in which the interaction between the node with its neighbors is modeled as a single-leader–multifollowers Stackelberg game. Second, by analyzing the dependency between subtasks, a hierarchical-dependent subgraph extraction scheme (HDSE) is proposed, which transforms the subtask call graph into a hierarchical tree diagram to obtain a hierarchical scheduling list. Finally, a hybrid subtask scheduling scheme is presented to make optimal task scheduling decisions. Numerical results show that H-HSS can significantly outperform the other representative benchmarks with low complexity, in subtask completion time, energy consumption, or weighted sum. In addition, the tolerance capability of our proposed TRGE algorithm is increased by 66%.
Expected and observed in‐hospital mortality in heart failure patients before and during the COVID‐19 pandemic: Introduction of the machine learning‐based standardized mortality ratio at Helios hospitals

Reduced hospital admission rates for heart failure (HF) and evidence of increased in‐hospital mortality were reported during the COVID‐19 pandemic. The aim of this study was to apply a machine learning (ML)‐based mortality prediction model to examine whether the latter is attributable to differing case mixes and exceeds expected mortality rates.
Visual domain knowledge-based multimodal zoning for textual region localization in noisy historical document images

Abstract. Document layout analysis, or zoning, is important for textual content analysis such as optical character recognition. Zoning document images such as digitized historical newspaper pages are challenging due to noise and quality of the document images. Recently, effective data-driven approaches, such as leveraging deep learning, have been proposed, albeit with the concern of requiring larger training data and thus incurring additional cost of ground truthing. We propose a zoning solution by incorporating a knowledge-driven document representation, gravity map, into a multimodal deep learning framework to reduce the amount of time and data required for training. We first generate a gravity map for each image, considering the centroid distance and area between a cell in a Voronoi tessellation and its content to encode visual domain knowledge of a zoning task. Second, we inject the gravity maps into a deep convolution neural network (DCNN) during training, as an additional modality to boost performance. We report on two investigations using two state-of-the-art DCNN architectures and three datasets: two sets of historical newspapers and a set of born-digital contemporary documents. Evaluations show that our solution achieved comparable segmentation accuracy using fewer training epochs and less training data compared to a naïve training scheme.