Miracle-dz/UniFAR-FTUs huggingface dataset:
S-parameter Determination with Current Probes

This paper introduced a method of determining S-parameters with two current probes.First,current injection and measurement probes were used to clamp lines of input and output ports in order to measure scattering parameters between the two probes.Second,determine the characterization of the injection and measurement probes.which can be assumed to be ideal transformers.After the confirmation of the parameters,the error in test procedure can be calibrated.Third,by using the scattering parameters between the injection and measurement probes and characterization of probes to compute,actual result of the ports can be figured out.The paper compared the new method to traditional method,the new method had an ideal result agreement to traditional method below 10 MHz,and the result difference between two methods from 10 MHz to 100 MHz was smaller than 10 dB.The method can be used in electromagnetic effect analysis of pulse with raise time smaller than 10 ns,of which the main frequency is smaller than 10 MHz.It is fourd that the main cause of the error is the limit of the performance of probes.In topological analysis,using the method can avoid error caused by dismantlement,and provides on-line test and convinient measurement.
Road Rut Measurement Method with Multi-laser-sensors

A roadrut measurement method with 31 laser-displacement-sensors is presented. The formula of rut is derived. TCP/IP protocol is adopted to ensure the data transmitted with a high speed. The test results show that this system can test rut with a range of 3 750 mm and a test speed of 72km/h. This method can be applied for asphalt pavement maintenance with a better accuracy.
Accessing Neuromarketing Scientific Performance: Research Gaps and Emerging Topics

(1) Background: Using neuroscience to understand and influence consumer behavior often leads to ethical controversy. Thus, it is necessary to demystify the use of neuroscience for marketing purposes; the present paper, by accessing the worldwide academic performance in this domain, fulfills this objective. (2) Methods: All extant literature on neuromarketing indexed to the Scopus database—318 articles—was subjected to a bibliometric analysis through a mixed-method approach. (3) Results: The results show that Spain leads the ranks of the most productive countries, while Italian researchers clearly dominate in terms of collaboration. Regarding the most prominent topics, the connection between “Neuroscience” and “Advertising” is highlighted. The findings provide a better understanding of the state-of-the-art in neuromarketing studies, research gaps, and emerging research topics, and additionally provide a new methodological contribution by including SciVal topic prominence in the bibliometric analysis. (4) Conclusions: As practical implications, this study provides useful insights for neuromarketing researchers seeking funding opportunities, which are normally associated with topics within the top prominence percentile or emerging topics. In terms of originality, this study is the first to apply SciVal topic prominence to a bibliometric analysis of neuromarketing, and provides a new bibliometric indicator for neuromarketing research.
Why Should Constant Stimulation of Saccular Afferents Modify the Posture and Gait of Patients with Bilateral Vestibular Dysfunction? The Saccular Substitution Hypothesis

An ongoing EU Horizon 2020 Project called BionicVEST is investigating the effect of constant electrical stimulation (ES) of the inferior vestibular nerve in patients with bilateral vestibular dysfunction (BVD). The evidence is that constant ES results in improved postural stability and gait performance, and so the question of central importance concerns how constant ES of mainly saccular afferents in these BVD patients could cause this improved performance. We suggest that the constant ES substitutes for the absent saccular neural input to the vestibular nuclei and the cerebellum in these BVD patients and indirectly via these structures to other structures, which have been of great recent interest in motor control. One target area, the anterior midline cerebellum (the uvula), has recently been targeted as a location for deep-brain stimulation in human patients to improve postural stability and gait. There are projections from midline cerebellum to basal ganglia, including the striatum, which are structures involved in the initiation of gait. It may be that the effect of this activation of peripheral saccular afferent neurons is analogous to the effect of deep-brain stimulation (DBS) by electrodes in basal ganglia acting to help alleviate the symptoms of patients with Parkinson’s disease.
The Marine Influence Index (MII): A Tool to Assess Estuarine Intertidal Mudflat Environments for the Purpose of Foraminiferal Biomonitoring

In this paper, we propose a marine influence index (MII), which is thought to give an integrated quantitative description of the complex of the environmental parameters controlling the foraminiferal fauna in estuarine intertidal mudflats. The MII contains three components, as follows: (1) the relative distance along the salinity gradient, (2) the emergence time relative to a reference tidal cycle, and (3) the relative importance of river outflow in the 30 days before sampling the foraminiferal fauna. Although these three parameters all have a strong relation with salinity, they also implicitly include other environmental parameters, such as the introduction of marine and continental organic matter and biota, hydrodynamic energy, or temperature. In order to show the functioning of this new index, MII is calculated for 28 stations in the Auray and Vie estuaries, for two different periods. The next step will be to compare the MII with faunal data sets. Ideally, this comparison should allow us to find strong correlations between some characteristics of the foraminiferal assemblages and the MII. If such strong correlations were indeed found, any major deviation of this relationship could then be interpreted as being due to strong anthropogenic disturbance.
RELATIONS BETWEEN INTERNAL FORCES AND DEFORMATION OF A BOLT JOINT WITH THEIR APPLICATION TO DESIGN BASED ON 3D FEM SIMULATION

A 3D FE(finite element) model for a connecting structure (bolted joint) consisting of a threaded bolt,a nut and two connected parts was developed by using software MSC.Marc in which the 3D spiral line geometry of screws and interfacial friction contact between parts were taken into consideration. Through 3D calculation,the nonlinear curves of axial force vs. axial deformation of the joint,residual pre-tightening force in the joint and the maximum equivalent stress on the bolt vs. external axial force acted on the connected parts were obtained and the fields of deformation of and stresses on the whole combined structure were shown. The nonlinear laws of the obtained curves were analyzed and the related conclusions were drawn. Further more,based on the obtained results,a new method of designing pre-tightening force and permitted external force was presented.
Eco-Entrepreneurs Organizational Attitude towards Sustainable Community Ecotourism Development

Ecotourism is one of the most popular sectors in the modern tourism industry. Eco-entrepreneurship is a recent development in entrepreneurial society. These two sectors together attempt to solve the environmental and socio-economic problems. This paper analyzes eco-entrepreneurs organizational factors for community ecotourism development in the case of Kabani community ecotourism organization. The study comprised of both secondary and primary data. For primary data, the author conducted a field study research with community members of a small-scale eco-entrepreneurial organization, Kabani Community Tourism between October to December 2017. For secondary data, the author engaged in an extensive literature review process to identify eco-entrepreneurship research conducted in the tourism industry. Quantitative primary data were collected through questionnaires among 56 local communities employed by Kabani ecotourism organization. The well-known classified technique, Principle Component Analysis has been performed to find the factors of eco-entrepreneurship organization for local communities development. These factors are named as a social, economic, and environmental development factors. Findings show that local communities see eco-entrepreneur organizational factors socio-economic, environmental and local communities age and environmental educational awareness programmes influence the development of ecotourism.
COVID-19 Identification from Low-Quality Computed Tomography Using a Modified Enhanced Super-Resolution Generative Adversarial Network Plus and Siamese Capsule Network

Computed Tomography has become a vital screening method for the detection of coronavirus 2019 (COVID-19). With the high mortality rate and overload for domain experts, radiologists, and clinicians, there is a need for the application of a computerized diagnostic technique. To this effect, we have taken into consideration improving the performance of COVID-19 identification by tackling the issue of low quality and resolution of computed tomography images by introducing our method. We have reported about a technique named the modified enhanced super resolution generative adversarial network for a better high resolution of computed tomography images. Furthermore, in contrast to the fashion of increasing network depth and complexity to beef up imaging performance, we incorporated a Siamese capsule network that extracts distinct features for COVID-19 identification.The qualitative and quantitative results establish that the proposed model is effective, accurate, and robust for COVID-19 screening. We demonstrate the proposed model for COVID-19 identification on a publicly available dataset COVID-CT, which contains 349 COVID-19 and 463 non-COVID-19 computed tomography images. The proposed method achieves an accuracy of 97.92%, sensitivity of 98.85%, specificity of 97.21%, AUC of 98.03%, precision of 98.44%, and F1 score of 97.52%. Our approach obtained state-of-the-art performance, according to experimental results, which is helpful for COVID-19 screening. This new conceptual framework is proposed to play an influential task in the issue facing COVID-19 and related ailments, with the availability of few datasets.
Thalamic T-Type Calcium Channels as Targets for Hypnotics and General Anesthetics

General anesthetics mainly act by modulating synaptic inhibition on the one hand (the potentiation of GABA transmission) or synaptic excitation on the other (the inhibition of NMDA receptors), but they can also have effects on numerous other proteins, receptors, and channels. The effects of general anesthetics on ion channels have been the subject of research since the publication of reports of direct actions of these drugs on ion channel proteins. In particular, there is considerable interest in T-type voltage-gated calcium channels that are abundantly expressed in the thalamus, where they control patterns of cellular excitability and thalamocortical oscillations during awake and sleep states. Here, we summarized and discussed our recent studies focused on the CaV3.1 isoform of T-channels in the nonspecific thalamus (intralaminar and midline nuclei), which acts as a key hub through which natural sleep and general anesthesia are initiated. We used mouse genetics and in vivo and ex vivo electrophysiology to study the role of thalamic T-channels in hypnosis induced by a standard general anesthetic, isoflurane, as well as novel neuroactive steroids. From the results of this study, we conclude that CaV3.1 channels contribute to thalamocortical oscillations during anesthetic-induced hypnosis, particularly the slow-frequency range of δ oscillations (0.5–4 Hz), by generating “window current” that contributes to the resting membrane potential. We posit that the role of the thalamic CaV3.1 isoform of T-channels in the effects of various classes of general anesthetics warrants consideration.
Macroeconomic Determinants of International Migration of Overseas Filipino Workers

This study focuses on the econometric analysis of determinants of international migration of overseas Filipino workers across different countries. The number of overseas Filipino workers as the regressand, while the regressors are remittances, unemployment, and wage rate, using time-series data from years 1990 to 2019. The selected variables are considered as a few of the major economic factors why Filipino workers migrate. Other determinants or factors of migration were not examined by the researchers. This study discovered that remittances, wage rate, and unemployment rate are statistically significant and positively correlated to the parameters of overseas Filipino workers in the Philippines. It is determined that remittances are positively correlated with the number of overseas Filipino workers. In addition, it was discovered that the unemployment rate and the number of overseas Filipino workers are negatively correlated in the absence of the wage rate and remittances in the simple linear regression. However, due to the influence of the wage rate and remittances in the model, the relationship of the unemployment rate with the number of overseas Filipino workers proves to be positively correlated. The obtained value of the model suggests that 91.21% of the variability in overseas Filipino workers can be explained by the variability of all independent variables. Furthermore, as indicated by the diagnostic tests' result, including the Pearson R correlation coefficient, the overall model is significant and shows no evidence of multicollinearity, serial correlation, heteroscedasticity, and irregular distribution of residuals.
Mapping smart experiences in tourism: A bibliometric approach

There has been a significant increase in the number of studies addressing smart experiences in the context of tourism (SET). Nevertheless, no previous work has systematically and critically analysed the literature on this subject. To fulfil this gap, this paper examines the evolution of SET as a research topic by mapping the scientific production on it. To this end, 84 papers published from 2011 to April 2019 were retrieved from Scopus. To map this data, a blend of bibliometric analysis techniques, including the analysis of evaluative measures (productivity and impact metrics) and relational techniques (word frequency analysis and key theme analysis), was employed. Evaluative metrics were carried out using Plotly, Excel, and DB Gnosis software. The reviewed papers were then visually analysed through mind maps using BizAgi Process Modeler. The study presents an original theoretical insight, as well as a significant methodological contribution, as it employs an integrative approach of bibliometric analysis that relies on a set of rigorous techniques and can be implemented in future studies.
Perovskite Semiconductor Nanocrystals

Nanochemistry Department, Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genova, Italy Advanced Membranes and Porous Materials Center, KAUST Catalysis Center, Division of Physical Science and Engineering, King Abdullah University of Science and Technology, Thuwal 23955-6900, Saudi Arabia Dipartimento di Scienza dei Materiali, Università degli Studi di Milano-Bicocca, Via Cozzi 55, IT-20125 Milano, Italy Beijing Key Laboratory of Construction-Tailorable Advanced Functional, Materials and Green Applications, Experimental Center of Advanced Materials School of Materials Science and Engineering, Beijing Institute of Technology, Beijing 100081, China
Automated Customer Complaint Processing for Water Utilities Based on Natural Language Processing—Case Study of a Dutch Water Utility

Most water utilities have to handle a substantial number of customer complaints every year. Traditionally, complaints are handled by skilled staff who know how to identify primary issues, classify complaints, find solutions, and communicate with customers. The effort associated with complaint processing is often great, depending on the number of customers served by a water utility. However, the rise of natural language processing (NLP), enabled by deep learning, and especially the use of deep recurrent and convolutional neural networks, has created new opportunities for comprehending and interpreting text complaints. As such, we aim to investigate the value of the use of NLP for processing customer complaints. Through a case study about the Water Utility Groningen in the Netherlands, we demonstrate that NLP can parse language structures and extract intents and sentiments from customer complaints. As a result, this study represents a critical and fundamental step toward fully automating consumer complaint processing for water utilities.
Detection performance of MIMO radar

The spatial diversity of multiple input multiple output(MIMO) radar was analyzed based on a distributed source model under the Neyman-Pearson criterion when the observation paths were not strictly independent of each other.The detector was then simplified based on the primary component analysis.An eigenvector analysis of the covariance of the received signal vectors was used to extract the independent components of the vectors from M received signals,which were combined by the detector.Simulations show that as long as more than 2 independent components are obtained,the MIMO radar is still able to counter the target's radar cross section(RCS) scintillation compared with conventional phase radar,even if the observation paths were not entirely independent.In addition,MIMO radar can efficiently detect fading targets using the spatial diversity when the distance between the transmitter elements is decreased to 1/4 that for the ideal conditions.
Correlation between liver lipidosis, body condition score variation, and hepatic analytes in dairy cows

Abstract Liver lipidosis is a metabolic disorder mostly observed in high yielding dairy cattle, especially during the transition period. The aim of this study was to determine the correlation between hepatic lipid infiltration, biochemical indicators of liver function, and body condition score (BCS) variation in dairy cows. Fifty-one multiparous Holstein cows raised in a confined system were evaluated. Liver biopsies and blood samples were collected, and BCS was measured on days 3 and 28 postpartum. Lipid infiltration was determined by histologic examination. The plasma activity of aspartate aminotransferase, alkaline phosphatase, and gamma-glutamyl transferase and concentration of beta-hydroxybutyrate, non-esterified fatty acids, albumin, total bilirubin, and cholesterol were determined. BCS was measured using objective (camera) and subjective (visual) methods. Mild lipid infiltration was found in 3.92% of cows sampled on day 3 and 5.88% on day 28. Bilirubin was significantly higher on day 3 than on day 28 postpartum, and cholesterol was significantly higher on day 28 than on day 3 in all cows. There was no difference in biochemical analytes between cows with and without lipidosis. On day 3, mean subjective BCS was 3.10 and objective BCS was 3.16, while on day 28, these scores were 2.91 and 2.99, respectively. The calculated liver function index (LFI) was found to be a more sensitive indicator of liver function than the hepatic analytes evaluated. No correlation between BCS variation and lipid infiltration was found. Cholesterol and bilirubin levels showed the most remarkable changes during the early postpartum period. LFI is a potential indicator of postpartum liver function.
Key Issues in Vocabulary Teaching: A Brief Overview

Vocabulary is still neglected in EFL classrooms. Many language educators consider the teaching of vocabulary to be challenging; therefore, they do not devote their teaching time to exposing their students to this vital skill. This article attempts to shed light on some of the vital issues related to the teaching of vocabulary to help teachers who are not yet ready to teach this skill. It begins with a discussion on the importance of teaching vocabulary by addressing the main reasons why vocabulary needs to be taught. Then, it gives a brief account of the different aspects that language educators need to take into account when teaching vocabulary to their learners. Besides, it introduces a list of the most useful strategies that language instructors can incorporate into their classrooms to teach vocabulary effectively. Finally, it sheds light on the different ways teachers can utilize to assess their students’ vocabulary learning. Results of the study provide insights on how language educators, who encountered difficulties in teaching vocabulary and decided to neglect it in their classrooms, can make teaching vocabulary effective
Is business formation driven by sentiment or fundamentals?

The creation of a new business is an act of entrepreneurship. It is also a financial undertaking. Hence it is admissible to apply the apparatus of behavioral finance to study the determinants of business formation. Our results show that aggregate US business formation, nationally and regionally, is jointly predicted by economic fundamentals and sentiment. There is evidence of both ‘pull’ and ‘push’ motives for entrepreneurship. Yet this simple structure does not survive decomposition by payroll propensity. High-payroll-propensity entrepreneurs respond primarily to pull-motive fundamentals, with sentiment accounting for a small fraction of explained variance. Low-payroll-propensity entrepreneurs, on the other hand, respond to both sentiment and fundamentals, representing both pull and push motives, with sentiment accounting for a large fraction of explained variance. Low-payroll-propensity business formation is twice as volatile as high-payroll-propensity entrepreneurship, and similarly to noise-based decision making in behavioral finance, it is substantially driven by sentiment.
Personalizing Environmental Awareness through Smartphones Using AHP and PROMETHEE II

Environmental awareness refers to the understanding of the importance of protecting the natural environment. Digital technologies can play an important role in raising awareness of environmental issues. In view of this compelling need, this paper presents a novel way to promote environmental awareness with the use of smartphones. To achieve this, it employs personalization techniques, and specifically the Analytic Hierarchy Process (AHP) and PROMETHEE II. In more detail, the mobile application incorporates a user model that holds information, such as location (city, mountain, sea, etc.), age, interests, needs and indicators of waste management, economy of natural resources, general environmental protection, and biodiversity. At the first interaction of the user with the application, the user model is initialized; then, the system uses AHP and PROMETHEE II to provide personalized advice to users in order to help them raise their environmental awareness. The criteria, used to evaluate environmental advice, include the current location, living environment, habits, interests, needs, age, and seasonal suitability of the user. The novelty of this paper is the combination of AHP and PROMETHEE II for personalizing the environmental awareness using mobile technologies, taking into consideration the user profile as well as the surrounding area where the user is at the time that the advice is provided. The presented application has been evaluated regarding the system usefulness and environmental awareness. The findings indicate the high acceptance of this approach and its positive impact on users’ attitude and behavior with regard to reducing their environmental footprint.
Research on an inverted pendulum optimal control system based on LQR

An LQR-based on single inverted pendulums optimal control system is designed.The paper makes a study and analysis of the weighted matrix Q and R through some inverted pendulum experiments to determine the Q and R.The basic laws have been found out between the system response performance and the matrix Q and R.The experimental results show that the conclusion is right and practical,thus providing references for choosing the Q and R to design other control systems.