Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigation of the high-field transport, Joule-heating-driven conductivity improvement and low-field resistivity behaviour in lightly-reduced free-standing graphene oxide papers

Free-standing reduced graphene oxide (rGO) has been gaining popularity for its use in supercapacitors and battery applications due its facile synthesis, multi-layered structure, and high-current carrying capacity. Pertinent to the successful implementation of such applications, however, is the need to develop a thorough understanding of the electrical properties of such materials when subject to high applied electric fields. In this work, we undertake a detailed study of high-field electrical properties of mm-scale, lightly-reduced, rGO papers. Our results reveal that the I–V curves exhibit substantial nonlinearity with associated hysteresis that depends strongly on the applied electric field. The nonlinear behaviour which was interpreted using conventional transport models of Fowler–Nordheim tunnelling and space charge limited conduction revealed that while these models provided good qualitative fits to our data, they were quantitatively lacking, thus leaving the issue of high-field transport mechanisms in rGO open for debate. Careful I–V cycling experiments with measurement time-delay introduced between cycles revealed that the observed hysteresis contained recoverable and non-recoverable parts that we identified as arising from charge trapping and Joule heating effects, respectively. Time-dependent measurements showed that these effects were characterized by two distinct time scales. Importantly, the Joule heating was found to cause a permanent conductivity improvement in the rGO via the ‘current annealing’ effect by effectively eliminating oxygenated groups from the rGO. The analysis of the electrical breakdown in our samples resembled a thermal runaway-like event that resulted in premature damage to the rGO. Finally, we investigated the low-field resistivity in the 80 K–300 K temperature range. The reduced activation energy analysis revealed a robust power law behaviour below 230 K, while deviating from this trend at higher temperatures. For samples that received current annealing treatment, a reduced value for the power law exponent was obtained, confirming the effective lowering of disordered regions.
How Smartness of Leisure-Sports Appliances Influence Tourists Intention to Use

The tourism and hospitality industries emphasize on indoor leisure-sport activities for tourists because these activities are less impacted by weather and provide enjoyment and relaxation to travelers, thereby enhancing their satisfaction. This study used the self-promotion perspective to establish a theoretical model to illustrate how the perceived usefulness of a product (in these cases, leisure-sports appliances) mediates the relationship between a tourist’s self-image and intention to use. Focusing on the users of treadmill, massage chair, Nintendo Wii, and hydrotherapy machine, a sample of 384 effective respondents was collected and analyzed with structural equation modelling by using AMOS 21.0. The study revealed several essential findings. First, product features like multifunctionality and reactivity significantly associate with a user’s self-image and perceived usefulness of a leisure-sports appliance. Product complexity positively relates to self-image but negatively relates to perceived usefulness, whereas automation positively relates to perceived usefulness but negatively relates to perceived self-image. Moreover, individual subjective norms significantly influence perceived usefulness and intention to use. Entertainment is not significant to an individual’s perceived usefulness but is significantly associated with a tourist’s intention to use. This study affirms the mediating role of perceived usefulness that connects self-image and intention to use.
NoC: A New Architecture for System on Chip

The shared or dedicated buses are used in System on Chip(SoC)to interconnect the communicating on-chip resources.But,these buses can not be scalable beyond a certain limit.In this case,the current interconnect infrastructure will become a bottleneck for the development of multi IP chip.In this paper,we will introduce a new design paradigm(Networks on Chip) that has been proposed to counter the inefficiency of buses in future SoC.NoC as a new architecture on chip,can be a solution for the challenges of SoC design and has been received recognition by academe and industry.The research for NoC involves many problems such as system architecture,design methodology,design tools and so on.In this paper,we simply discuss the key problems for NoC from the view of system architecture.
Diversity‐stability relationships in temperate grasslands as a function of soil pH

Diversity‐stability relationships in grasslands depend on the environment. Climate change and land degradation potentially alter soil pH and community stability within grassland environments, although it remains unclear how alteration in soil pH affects diversity‐stability relationships. From a three‐year experiment with acidification and alkalization treatments in three types of grasslands (i.e., desert, typical and meadow grasslands) in Northern China, we found that altered soil pH negatively impacted community biodiversity, especially in desert grasslands. Both soil acidification and alkalization reduced community stability in desert grasslands. Soil alkalization reduced community stability in typical grasslands. Altered soil pH did not affect community stability in meadow grasslands. The reduced community stability by soil acidification in desert grasslands could be attributed to the decreased dominant species stability, whereas the soil alkalization‐induced decline of community stability could be attributed to the reducing species asynchrony and dominant species stability. Our results suggest that soil pH‐mediated community stability is mainly driven by dominant species stability rather than diversity in desert grassland. Soil nutrients are affected by soil acidification and alkalization and varied among grasslands. Soil acidification enhanced nutrient availability and soil alkalization reduced soil total nutrients, both of which were negatively correlated with soil pH in desert grassland. Such changes in soil nutrients were associated with species asynchrony and then indirectly affected community stability, indicating the importance of soil nutrients in driving community stability. Our study suggests that drier grasslands might face greater stability risks and challenges than wetter grasslands under altered soil pH across spatial gradients of semiarid grasslands.
Detection of Cardiovascular Diseases in ECG Images Using Machine Learning and Deep Learning Methods

Cardiovascular diseases (heart diseases) are the leading cause of death worldwide. The earlier they can be predicted and classified; the more lives can be saved. Electrocardiogram (ECG) is a common, inexpensive, and noninvasive tool for measuring the electrical activity of the heart and is used to detect cardiovascular disease. In this article, the power of deep learning techniques was used to predict the four major cardiac abnormalities: abnormal heartbeat, myocardial infarction, history of myocardial infarction, and normal person classes using the public ECG images dataset of cardiac patients. First, the transfer learning approach was investigated using the low-scale pretrained deep neural networks SqueezeNet and AlexNet. Second, a new convolutional neural network (CNN) architecture was proposed for cardiac abnormality prediction. Third, the aforementioned pretrained models and our proposed CNN model were used as feature extraction tools for traditional machine learning algorithms, namely support vector machine, K-nearest neighbors, decision tree, random forest, and Naïve Bayes. According to the experimental results, the performance metrics of the proposed CNN model outperform the exiting works; it achieves 98.23% accuracy, 98.22% recall, 98.31% precision, and 98.21% F1 score. Moreover, when the proposed CNN model is used for feature extraction, it achieves the best score of 99.79% using the NB algorithm.
Analysis and Design of a Nonisolated DC Transformer With Fault Current Limiting Capability

The dc–dc converter, also termed as dc transformer, plays an important role in the future dc grids. It is used to interconnect network segments or lines with different voltage levels. A nonisolated modular multilevel dc–dc converter is presented in this article, which can realize bidirectional power regulation and dc fault current limiting. The control strategy is simplified and the current stresses are decreased due to the employment of autotransformers. The nonisolated structure can reduce the requirements of autotransformers, because only part of the transmitted power flowing though the autotransformers. The operation principle and control strategy of this converter are illustrated in detail. The analyzes of power transmission, submodule (SM) capacitor voltage ripple, the optimal configuration, and the efficiency of this converter are also provided. The optimal design methods of the dc transformer are proposed to reduce the costs and power losses according to the analysis results. Simulations performed in power systems computer aided design/electromagnetic transients including DC (PSCAD/EMTDC) and experiments based on a down-scaled prototype verify the operation principle, control strategy, and theoretical analysis. The simulation results and experiment results show the performances of the converter under steady state, power regulation, and fault conditions.
Task Co-Offloading for D2D-Assisted Mobile Edge Computing in Industrial Internet of Things

Mobile edge computing (MEC) and device-to-device (D2D) offloading are two promising paradigms in the industrial Internet of Things (IIoT). In this article, we investigate task co-offloading, where computing-intensive industrial tasks can be offloaded to MEC servers via cellular links or nearby IIoT devices via D2D links. This co-offloading delivers small computation delay while avoiding network congestion. However, erratic movements, the selfish nature of devices and incomplete offloading information bring inherent challenges. Motivated by these, we propose a co-offloading framework, integrating migration cost and offloading willingness, in D2D-assisted MEC networks. Then, we investigate a learning-based task co-offloading algorithm, with the goal of minimal system cost (i.e., task delay and migration cost). The proposed algorithm enables IIoT devices to observe and learn the system cost from candidate edge nodes, thereby selecting the optimal edge node without requiring complete offloading information. Furthermore, we conduct simulations to verify the proposed co-offloading algorithm.
Cu(II) and Zn(II) frameworks constructed by directional tuning of diverse substituted groups on a triazine skeleton and supermassive adsorption behavior for iodine and dyes.

The controllable design, synthesis and functional properties of a series of triazine tetratopic carboxylic MOFs have always been hotspots and challenges for research. Based on the characterization of the C-Cl bond on the triazine skeleton being easily substituted by some functional groups, we designed and synthesized a series of triazine tetratopic carboxylic Cu(II) and Zn(II) MOFs via the reaction of Cu(NO3)2·2.5H2O and ZnSO4·7H2O, as well as triazine tetratopic carboxylic H4TDBA-Cl (H4TBDA-Cl = 5,5'-((6-chloro-1,3,5-triazine-2,4-diyl)bis(azanediyl))diisophthalic acid) under hydrothermal conditions. During the process of synthesizing, the C-Cl bond on the triazine skeleton of the ligand was substituted with different groups, which formed the complexes ([Cu2(TBDA-Cl)(H2O)·10DMF·30H2O]n) (DMF = N,N-dimethylformamide) (1), N(Me)2 -[(CH3)2NH2]4·[Zn3(HTBDA-N)2(SO4)2]n (2) and H ([Cu2(TBDA-H)(H2O)]n) (3), respectively. It is worth noting that the in situ substitution reaction occurred for complexes 2 and 3 during the process of synthesis. Also, the structural analysis showed that the molecules in complexes 1-3 were connected with different building blocks to form different three-dimensional structures. We performed iodine adsorption experiments on the three complexes and found that there was a significant relationship between the structural configuration and adsorption behaviour. The results showed that the complex 1 with the Cl atom on the triazine skeleton could have a boosting effect on adsorption with iodine. It displayed a remarkable adsorption effect for iodine (in the solution of water: 7.6 g g-1 and in the solution of cyclohexane: 548.2 mg g-1). In addition, it also displayed the adsorption effect for JGB dye (204.9 mg g-1). For complex 2, it displayed an uptake effect for iodine in the solution of cyclohexane (529 mg g-1). The possible adsorption mechanism was also investigated. By comparison, we found that chlorine atoms could play an important role in the adsorption processes. The adsorption capacity of complex 1 (containing the chlorine atom in the structure) was much higher than that for complex 3.
The Effect of Brand Experience on Brand Loyalty in Indonesian automotive Industry: The Mediating Role of Customer Satisfaction and Brand Trust

The automotive industry is one of the mainstay sectors of national economic growth in Indonesia and the performance of this automotive industry sector always grows and leads in a positive direction every year making business competition dynamic and competitive. Marketers in the automotive industry need to try to increase brand loyalty to get customer repurchase intention and word of mouth. Customer repurchase intention is very important for business continuity in every company and word of mouth as a powerful marketing strategy to increase brand trust which has an impact on increasing sales. Customer satisfaction is an aspect that can create repurchase intention, while brand trust will increase customer word of mouth. The right strategy to achieve customer satisfaction and brand trust is to create a positive brand experience for customers. This research aims to determine the effect of brand experience on brand loyalty directly and indirectly through customer satisfaction and brand trust on Toyota brand car customers in Madiun. This type of research approach uses quantitative descriptive analysis with explanatory research methods and the sample technique uses random sampling, with a total sample of 200 respondents and the determination of the number of samples in this study using purposive sampling technique. The data collection method used a questionnaire and the data was analyzed by SEM-PLS using smartPLS3 software. The findings of this research indicate that brand experience does not have a significant effect on brand loyalty directly. Meanwhile, customer satisfaction and brand trust are able to perfectly mediate the relationship between brand experience and brand loyalty.
Business Start-Up and Growth Motives of Entrepreneurs: A Case in Bradford, United Kingdom

This study attempts to investigate start-up and growth motives of entrepreneurs who own small and medium scale enterprises in Bradford, UK. In-depth interviews are conducted using “storytelling” approach and narrative analysis is used for data analysis. The Findings reveal that each entrepreneur is motivated by a combination of “pull” and “push” motives at the start-up stage while they are mainly motivated by “pull” motives at the growth stage. Based on patterns observed between growth motives and entrepreneurial outcomes, three types of entrepreneurs are identified. Practical implications and avenues for future research are highlighted.
Wage Distribution Models

In our article we try to contribute to the discussion of the possibility to predict the trend of the wage distribution. For this purpose we use data from Czech Republic. But our model is useable for all similar data types. Classical models use the probability distribution such as lognormal, Pareto, etc., but their results are not very good. We suggest using a mixture of normal probability distribution (normal mixture) in our model. We focus mainly on the possibility of constructing a mixture of normal distributions based on parameter estimation. We estimate these parameters on the basis of their evolution in time. We work with data collected in the last 15 years. The data are divided into groups with respect to sex, age and regions.
Reduced dietary acid load in U.S. vegetarian adults: Results from the National Health and Nutrition Examination Survey

Abstract Dietary acid load (DAL) is an important determinant of systemic pH and acid–base homeostasis. Diets abundant in acidogenic foods, such as meat and meat products, induce a low‐grade metabolic acidosis state that has been associated with cardiovascular disease, type‐2‐diabetes, and an increased cancer risk. Fruits and vegetables have alkalizing properties and beneficially affect DAL. It has thus been suggested that a plant‐based diet (restricting or excluding animal products) may be a powerful tool in reducing DAL; yet studies in that particular field are scarce. To explore these associations in greater detail, we examined DAL in self‐identified vegetarians from the United States National Health and Nutrition Examination Survey (2007–2010). We compared dietary intake and two widely used markers of DAL (PRAL (potential renal acid load) and NEAP (net endogenous acid production; NEAPF and NEAPR)) among 8,398 nonvegetarians and 191 lacto‐ovo‐vegetarians with reliable dietary intake aged 18 years or older. Vegetarians had a more favorable body mass index and consumed fewer calories (1862.31 kcal/d) than nonvegetarians (2041.12 kcal/d). Vegetarians consumed fewer protein (34.17 g/1000 kcal) and phosphorus compared to nonvegetarians (39.50 g of protein/1000 kcal) but had a higher intake of magnesium and potassium. Nonvegetarians exhibited higher median DAL scores (PRAL: 11.90 mEq/d, NEAPF: 53.59 mEq/d, NEAPR: 55.67 mEq/d) than vegetarians (PRAL: −0.44 mEq/d, NEAPF: 39.60 mEq/d, NEAPR: 41.30 mEq/d). Vegetarians had more favorable DAL scores compared to nonvegetarians in this descriptive epidemiologic study. Future (interventional) trials are warranted to examine the varying acid load in different plant‐based dietary patterns.
Differential Gene Expression of Efflux Pumps and Porins in Clinical Isolates of MDR Acinetobacter baumannii

Background: Acinetobacter baumannii is an opportunistic pathogen associated with healthcare infections and high mortality rates in intensive care units all over the globe. Porins and efflux pumps over-expression have been reported as contributing factors in escalating drug resistance and rendering treatment ineffective. In this study, we investigated the mechanisms of multidrug resistance (MDR) in A. baumannii clinical isolates. Methods: A total of 30 A. baumannii isolates were included in the present study from Nehru Hospital (PGIMER-Chandigarh) located in North India. Kirby Bauer disk diffusion assay and MIC were performed to determine the antimicrobial susceptibility pattern. Screening of beta-lactamases was performed using PCR. Relative gene expression of four RND, one MATE efflux pump, and two outer membrane proteins were determined using RT-PCR. Molecular typing of 22 isolates was carried out using MLST Oxford scheme. Results: CarO porin genes showed over-expression in 63% isolates followed by adeGandabeM efflux pump downregulation/underexpression (<0.5 fold), suggesting the carbapenem-susceptible phenotypic nature of the isolates. High prevalence of VIM-2, NDM-1, and OXA-23 genes was observed in A. baumannii isolates. Interestingly, NDM-1 and OXA-58 were traced in 10 and3 A. baumannii isolates respectively; 13 of 22 (59%) isolates showed novel Sequence Types (STs) in the Multi-Locus Sequence Typing (MLST) analysis. ST 1087 was most commonly found ST among all others (16 STs). Conclusions: This study indicated a possible role of carO porin genes and adeG (RND) andabeM (MATE) efflux pumps in carbapenem susceptibility of A. baumannii. New STs were also reported in the majority of the isolates.
Voting rights and the resilience of Black turnout

The Voting Rights Act of 1965 increased turnout among Black voters, which then generated economic bene ts for Black communities. In Shelby County v. Holder (2013), the Supreme Court invalidated the enforcement mechanism responsible for these improvements, prompting concerns that states with histories of discriminatory election practices would respond by suppressing Black turnout. I estimate the e ect of the Shelby decision on the racial composition of the electorate using triple-di erence comparisons of validated turnout data from the Cooperative Congressional Election Study. The data suggest that the Shelby decision did not widen the Black-white turnout gap in states subject to the ruling.
Characterization on fuzzy soft ordered Banach algebra

In this paper, we define fuzzy soft ordered Banach algebra with fuzzy soft algebra cone, and introduce the character on fuzzy soft ordered Banach algebra in both cases real and complex. Also, we deduce some of its basic properties and we define a new concept which is a maximal fuzzy soft algebra cone and showing that the set of all fuzzy soft character is isomorphism to the set of all maximal fuzzy soft algebra cone. we prove that the set of all real characters is convex and extreme point, we applied Gelfand- Mazur theorem on fuzzy soft Banach algebra, we showed that character (the set of all complex continuous character) is fuzzy soft ordered Banach algebra. with inverse –closed algebra cone ̆ and a non-zero element in ̆ has inverse we have is an isomorphism to Banach space ( ̆)
Black carbon in the Southern Andean snowpack

The Andean snowpack is an important source of water for many communities. As other snow-covered regions around the world, the Andes are sensitive to black carbon (BC) deposition from fossil fuel and biomass combustion. BC darkens the snow surface, reduces the albedo, and accelerates melting. Here, we report on measurements of the BC content conducted by using the meltwater filtration (MF) technique in snow samples collected across a transect of more than 2500 km from the mid-latitude Andes to the southern tip of South America. Addressing some of the key knowledge gaps regarding the effects of the BC deposition on the Andean snow, we identified BC-impacted areas, assessed the BC-related albedo reduction, and estimated the resulting snow losses. We found that BC concentrations in our samples generally ranged from 2 to 15 ng g−1, except for the nearly BC-free Patagonian Icefields and for the BC-impacted sites nearby Santiago (a metropolis of 6 million inhabitants). We estimate that the seasonal snowpack shrinking attributable to the BC deposition ranges from 4 mm water equivalent (w.e.) at relatively clean sites in Patagonia to 241 mm w.e. at heavily impacted sites close to Santiago.