Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Molybdenum Content on Mechanical and Tribological Properties of Diamond-Like Carbon Coatings over Titanium β-21S Alloy

Molybdenum-doped diamond-like carbon (Mo-DLC) coatings have been deposited on titanium β-21S alloy (Ti–15Mo–3Nb–3Al–0.2Si) using plasma-enhanced chemical vapor deposition (PECVD) equipped with pulsed-DC magnetron sputtering. Mo contents in the deposited coatings have been controlled with an applied sputtering pulse duty cycle. Chemical composition, structure, morphology, and topography have been studied using X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), and atomic force microscopy (AFM), respectively. XRD pattern of the coating with highest Mo content shows the presence of carbide phase. Smooth features with low roughness values are observed in low Mo content coating, whereas high Mo content coating shows granular characteristics with a high roughness value. Raman spectra reveal the increased graphitic content for the highest metal concentration in the coatings, wherein the nanohardness is also determined to be highest, at about ~18–19 GPa. Furthermore, the ball-on-disk tribometry test on Mo-DLC coating with highest nanohardness shows a low coefficient of friction (COF) of 0.2 with low wear loss compared to that of the substrate (0.62).
A Study on the Relationship Between Burnout and Job Satisfaction of Iranian EFL Teachers Working in Universities and Schools

A teacher plays an important role in the development of the students’ potential and helps to form their future. This research intends to study the degree of burnout and job satisfaction in English as a foreign language (EFL) teachers of universities and Schools in Iran, as well as their association with demographic characteristics. To measure teachers’ burnout, Maslach Burnout Inventory questionnaire was applied, which has also been validated by experienced teachers for the Iranian population and the Employee Satisfaction Inventory questionnaire, prepared for the Iranian population, was applied to estimate job satisfaction. Questionnaires were answered completely by 159 teachers, who work at universities and schools in Iran. After data analysis, the findings showed a negative correlation between teachers’ burnout and their job satisfaction; their experience relatively moderate burnout levels, and their job satisfaction level is high. The findings also represented that the type of workplace influences satisfaction regarding the factor “job conditions”. The study was for the first time that Iranian EFL teachers’ burnout and job satisfaction in universities and schools were investigated and the findings showed that by increasing the level of job satisfaction, the perceived burnout decreases, where burnout and job satisfaction presented medium to high negative correlation.
Target recognition method based on polarization parameters

Traditional target detection must be based on imaging. It costs plenty of calculation but returns poor results. Polarization is a common property of the vector wave. As is known to all, light is electromagnetic wave. Polarization state is the inherent nature of light. After acting on different objects, the polarization state of light will obviously change which can be reflected by Mueller matrix. Therefore analyzing Mueller matrix is an efficient way to attain polarization information. This paper proposes a method of target detection based on Mueller matrix. Firstly, Mueller matrix should be analyzed to extract three parameters: depolarization index DI(M), duplexing attenuation parameter D(M) and polarization parameter P(M), which describe the polarization of targets. By measuring the Mueller matrix of typical artificial target and natural background under different incident angles, corresponding DI(M), D(M) and P(M) trend charts are drawn respectively. According to the trend charts, a reasonable method is proposed to separates each of the three images into two parts—target and background. However, the human eye is not sensitive to gray images, which can only distinguish a dozen grayscale but thousands of colors. Because of the high resolution for colors, we can use false color fusion technique to turn grayscales into colorful images to increase the rate of the human eye observation and recognition effectively. The technology has a broad application prospect in optical constants of inversion, military reconnaissance and camouflage detection. Proved by a mass of experiment, the method has high efficiency and high recognition rate.
Photoinduced renormalization and electronic screening of quasi-two-dimensional Dirac states in 
BaNiS2

By means of time- and angle-resolved photoelectron spectroscopy, we give evidence of a remarkable reduction of the Fermi velocity of out-of-equilibrium Dirac bands in the quasi-two-dimensional semimetal BaNiS2. This effect is accompanied by a nonrigid shift of the bands at the center of the Brillouin zone. Analytical and first-principles calculations indicate that this band renormalization is ascribed to a change in nonlocal electron correlations driven by a photoinduced enhancement of screening properties. Our results are explained by a scaling relation between inverse screening length and electronic temperature that is of general relevance for the description of out-of-equilibrium dynamics and screening effects in all layered Dirac materials.
Mech-Health: A Machine Learning Based Fault Detection Using Predictive Analysis For LSTM

Predictive maintenance is a form of maintenance that looks at how well machinery works and how efficient it is during regular operations to reduce the risk of failure. Machinery and other appliances are subjected to less risk due to a sudden failure with the help of predictive maintenance. This form of maintenance device alerts the owner until a malfunction or breakdown is anticipated. Predictive maintenance schedule operations, unlike traditional preventive maintenance, are focused on data obtained from sensors and analysis algorithms. We address the validity of using LSTM instead of conventional approaches such as visual inspection in this paper. Two different models, the Prophet and the Autoencoder LSTM recurrent neural network are used to train the ball-bearing dataset. The prophet method is a forecasting technique implemented with the aid of an encoder-decoder LSTM architecture in R and Python, while Autoencoder LSTM is an autoencoder of sequence data implemented with the help of an encoder-decoder LSTM architecture. Using the two algorithms, and efficient maintenance scheme can be created to limit any potential risk to the assets until they misfire and fully collapse.
A Re-examination of the Validity of the Life Cycle Hypothesis (LCH): Evidence from Emerging Europe

The study aims to empirically explore the dependence of savings behavior on demographic changes in the context of the life cycle hypothesis (LCH) in a sample of 18 European transition and post transition countries. The empirical methodology is based on a multifactor modeling approach. The research estimates heterogeneous panel data models by employing three different heterogeneous coefficient estimators: mean group (MG) estimator, common correlated effects mean group (CCEMG) estimator, and augmented mean group (AMG) estimator. The findings demonstrate that the LCH is confirmed in the case of European post-transition countries and rejected as inappropriate in European transition countries due to inconsistency of regression coefficients (age dependency, unemployment rate, urbanization, and health expenditure). The models and their findings presented in this study can be used in policymaking to predict dynamic interactions and variations among selected demographic variables in the determination of savings behavior.
New biological data for Salaria fluviatilis (Asso, 1801) (Blenniidae) from North of Algeria

The family Blenniidae inhabiting freshwater systems has been scarcely studied, particularly in North Africa. The present study focused on the biology of Salaria fluviatilis (Asso, 1801) from Kabylie region (northern Algeria). A total of 198 specimens were sampled from May 2015 to May 2016. The total length of this fish varied between 4.9 and 12.7 cm and its total weight varied between 1.2 and 23.7 g. The age of this fish species varied between 1 and 3 years. The sex ratio of S. fluviatilis was in balance (SR = 0.98). The results of our investigation of length-weight relationship show highly significant correlation (p > 0.001); the correlation coefficient r varied between 0.966 and 0.985. The specimens of this fish species exhibited positive allometry in males (b = 3.195) and negative allometry in females (b = 2.782). Growth parameters were higher in males than in females, except for the growth rate (K) where the values were close. The growth performance index (Φ) was similar in both sexes, which confirms the same growth potential for males and females. In Kabylie region, the breeding period of S. fluviatilis occurred between April and July. Our results of analysis of the hepatosomatic index (HSI) and Fulton’s K show that liver energy reserves are not devoted for reproduction; however, muscle reserves seem to support this physiological activity. In perspective, more biological studies must be carried out on this rare and poorly studied fish.
Teachers’ Perception of the Influence of the Teaching Context on Cognitive Achievements in General Technology Education

High achievements in the cognitive domain are the ultimate goal of any education, within it is important to understand the role of the teaching context. In this regard, the purpose of this research was to determine how teachers perceive the role of the teaching context on the pupils’ achievements in the cognitive domain in general technology education. For this purpose, a survey of teachers’ perception towards the influence of isolated elements of the teaching context, specific to technology education, on the achievements of learning objectives was conducted. The study was conducted as a survey on a stratified sample of technology education teachers (N = 194) from Croatia. ANOVA repeated measurements statistical procedure was used to process the research results. The analysis of the results showed that teachers give preference to certain contextual elements over others. These are activities with technological artifacts, models and simulations, service-learning activities, field trips, work in an appropriate space and the student’s presentation of their own results. These elements can be considered as a contextual basis for the cognitive development of pupils in general technology education. Teachers’ perception of the influence of other elements of the teaching context is not negligible, but obviously there is no priority over these elements, which is why further research is needed.
Moderating Role of Financial Market Development on the Relationship between Stock Liquidity and Dividend

This article aims to investigate the relationship between stock liquidity and dividend across emerging market countries as well as examined the moderating role of financial market development on the relationship between stock liquidity and dividend. Data were obtained from the World Bank and DataStream databases. The study examined 3,258 listed firms from 22 emerging markets to be extrapolated in the emerging market context. To analyse the data, this article used the panel data Tobit model and panel logistic regression, both with random effects. The analysis revealed that financial market development has a positive moderating effect on the relationship between stock liquidity and dividend by improving local market liquidity and mitigating information asymmetry. The study findings provide information for managers to devise investment strategy in the emerging markets. This article provides new insights into the financial market development moderating role on the relationship between stock liquidity and dividend.
Machine Learning in Property and Casualty Insurance: A Review for Pricing and Reserving

In the past 25 years, computer scientists and statisticians developed machine learning algorithms capable of modeling highly nonlinear transformations and interactions of input features. While actuaries use GLMs frequently in practice, only in the past few years have they begun studying these newer algorithms to tackle insurance-related tasks. In this work, we aim to review the applications of machine learning to the actuarial science field and present the current state of the art in ratemaking and reserving. We first give an overview of neural networks, then briefly outline applications of machine learning algorithms in actuarial science tasks. Finally, we summarize the future trends of machine learning for the insurance industry.
Promoting Social Entrepreneurship in Poor Socio-Economic Contexts: Evidence from an Action Research Project in Zimbabwe — Southern Africa

Abstract The hopes attached to social entrepreneurship for improving disadvantaged environments have spread throughout Africa, but due to the complexities characterising the continent, additional support is needed. This article analyses the promotion of social entrepreneurship led by a non-governmental development organisations (NGDOs) through an action research project in Zimbabwe, southern Africa. The results suggest the need to consider the particularities of the context prior to carrying out any support measures for social entrepreneurship in disadvantaged rural areas, and the design of measures in the framework of a flexible support system which involves people from the local context.
Future rainfall and temperature changes in Brazil under global warming levels of 1.5ºC, 2ºC and 4ºC

The present study analyzes the impacts of global warming of 1.5oC, 2oC, and 4oC above pre-industrial levels in the Brazilian territory. Climate change projected among the different global warming levels has been analyzed for rainfall, temperature and extreme climate indices. The projections are derived from the global climate model HadGEM3-A, from the High-End cLimate Impacts and eXtremes (HELIX) international project, from the United Kingdom, forced by sea surface temperature and sea ice concentration of a subset of six CMIP5 (Coupled Model Intercomparison Project phase 5) global climate models and considering the RCP 8.5 (Representative Concentration Pathways) emissions scenario throughout the 21st century. Projections indicate robust differences in regional climate characteristics. These differences include changes: in the minimum and maximum air temperature close to the surface to all the country’s regions, in extremes of heat, particularly in northern Brazil, in the occurrence of heavy rainfall (Southern and Southeastern regions), and in the probability of droughts and rain deficits in some regions (Northern and Northeastern Brazil).
Bifurcation of Depression and Bipolar Disorder through Different Modalities using Deep Learning

People are experiencing mental health problems and abnormalities as a result of the stress and pressure that come with modern living. This paper focuses on detecting mental illnesses like Depression or Bipolar Disorder which has affected around 3.7% and 0.3% respectively, of the entire Indian Population. The majority of current methods of diagnosing psychopathology rely on verbal accounts (clinical interview or questionnaire) from patients, their loved ones, or caretakers. They lack organized and effective methods for incorporating behavioral observations that are clear signs of psychiatric disease and that frequently happen without either person's knowledge. In patients receiving treatment for depression and bipolar disorder, we contrasted the clinical diagnosis of significant depression with automatically recorded facial actions and voice prosody.
Towards a New Oxidation Process Using Ozone to Regenerate Coked Catalysts

ABSTRACT This work focuses on the regeneration of a zeolite catalyst from industry deactivated by fouling with coke. To replace high temperature combustion, a common and energy intensive process, an oxidation process under milder conditions (50 °C–200 °C) has been investigated using ozone. Coked zeolite has been oxidized by an ozone stream in a fixed bed reactor, and regeneration kinetics was followed by analyzing carbon content of the particles and ozone concentration at the outlet. The effects of temperature, time on stream and ozone inlet concentration on carbon removal efficiency were studied. Moreover, elemental analysis showed that a maximum of 74.3% of carbon could be removed from the coked catalyst after 6.5 h. Moreover, the total specific surface area, the pore size distribution and the total pore volume (mainly mesopores) have been evaluated on coked and regenerated samples.
INTERDEPENDENCY BETWEEN ECONOMIC PERFORMANCE AND HIV PREVALENCE IN COUNTRIES OF SUB-SAHARAN AFRICA

The HIV/AIDS threat, as a development obstacle in the underdeveloped world, has persisted for years. Globally, 37.9 million people are HIV positive and the majority, or 70% of them, live in Sub-Saharan Africa, a region with insufficient resources to fight the infection. HIV infection, if it progresses to AIDS, reduces labor force, decreases productivity, increases costs of health services and thus has a negative impact on a country’s economic performance. The research presented in the paper analyzed HIV prevalence and GDP per capita of all SubSaharan countries, disproving the initial hypothesis that the highest HIV prevalence is found among the poorest counties. Paradoxically, HIV incidence is higher in countries with higher middle income like Botswana and the Republic of South Africa. Of the ten most affected countries, only four are ranked in the least developed category. Inverse dependency between the rate of Human Development Index and HIV prevalence, examined using the regression model in the gretl statistical software, was not confirmed and thus high HIV prevalence in population does not automatically lead to extreme poverty. HIV and AIDS form one of several factors affecting economic development of the region of Sub-Saharan Africa. The main aim of the paper is to assess the influence of HIV/AIDS on the economic development of Sub-Saharan nations, using the OLS regression model in gretl, interdependency between the economic performance of a country (GDP per capita) and HIV prevalence in its active population (aged 15–45) to find out whether HIV is among the major factors negatively affecting development in the region of Sub-Saharan Africa.
Physico-chemical properties of three-component mixtures based on chitosan, hyaluronic acid and collagen

ABSTRACT The aim of this work was preparation of biopolymer materials based on blends of chitosan, hyaluronic acid and collagen. The properties of blend films have been investigated by contact angle measurements and atomic force microscopy. The contact angle measurements showed that chitosan films are more polar after addition of hyaluronic acid and collagen. The AFM results showed that the addition of chitosan to hyaluronic acid led to the increase of surface roughness. Moreover, miscibility studies of biopolymeric blends were also done using the viscometric method. Viscometric studies indicated that two-component and three-component blends are partially miscible.
Live Demonstration: Bio-inspired implementation of a sparse-learning spike-based hippocampus memory model

The hippocampus acts as a short-term memory capable of recalling a previously-learned complete memory from a fragment of it. Inspired by the hippocampus and taking into account its input from the visual stream, a neuromorphic system capable of learning images and remembering them from a fragment of it in real time was developed. The system contains a bio-inspired hippocampal spiking memory that acts as an autoassociative network that, for each input image, associates the spatial activation patterns of the pixels of the image. A monitor has been designed to visualize the internal spiking activity of the network during the simulation.
Biodiesel from kernel oil of sweet cherry (Prunus avium L.) seed

ABSTRACT Kernel oil of sweet cherry seed (Prunus avium L.) was extracted with hexane in a Soxhlet extractor. Sweet cherry kernel oil contains more than 87% unsaturated fatty acids, such as oleic acid (43.7% by weight), linoleic acid (41.8% by weight), and linolenic acid. The biodiesel from kernel oil of sweet cherry seed in itself is not significantly different from biodiesel produced from common vegetable oils.
Self-congruity and domestic tourists’ attitude: the role of involvement and age

ABSTRACT This study focuses on the relationship between self-congruity, tourism involvement, age and tourists’ attitude towards a destination. Two hundred and twelve French tourists took part in a survey conducted in the city of Aix-en-Provence. The data were analysed using PLS Structural Equation Modelling (PLS-SEM). The findings indicate that the positive effect of self-congruity on destination attitude is moderated by tourism involvement and age. The findings also replicate past studies in which destination attitude is positively related to behavioural outcomes (i.e. recommendations, revisits). Suggestions for future research and managerial implications are provided in the final section.
5 th International Congress on Cell Membranes and Oxidative Stress: Focus on Calcium Signaling and TRP Channels

Neuropathic pain can arise from a wide variety injury to peripheral, including metabolic disorders, traumatic injury, inflammation, and neurotoxicity, and is characterized by spontaneous pain, hyperalgesia and allodynia which can persist long after the initial injury is resolved. TRPV1 is a Ca2+ permeable non-selective channel expressed in sensory neurons. Moreover, activation of TRPV1 during oxidative stress has been linked to cell death. Selenium has been considered a potent antioxidant that detoxifies a variety of reactive oxygen species in many neurological diseases. In addtion recently we observed modulator role of selenium on TRP channels in dorsal root ganglin (DRG) neuron of rtas. In order to better characterize the actions of selenium in the peripheral pain, we tested the effects of selenium on apoptosis, oxidative stress and calcium entry through TRPV1 channel in the DRG neuron of streptozotcin (STZ)induced diabetic rats. Sixty rats were randomly divided into four groups. First group was used as control. Second group used as diabetic. Third and fourth groups received selenium and melatonin, respectively. Melatonin and selenium were intraperitonealy given to diabetic rats constituting the fifth (STZ+melatonin) and sixth (STZ+Se) group. Diabetes was induced using a single dose of intraperitoneal STZ. On 14th day of DRG samples were freshly taken from all animals. The neurons were stimulated through TRPV1 channel agonist, capsaicin. We observed modulator role of selenium on apoptosis, caspase 3, caspase 9, mitochondrial depolarization and cytosolic ROS production values in the DRG neurons. In conclusion, in our diabetes experimental model, TRPV1 channels are involved in the Ca2+ entry-induced neuronal death, and modulation of this channel activity by selenium pretreatment may account for their neuroprotective activity against apoptosis and the Ca2+ entry.
THE PRAKTIKALITAS PENGEMBANGAN E-BOOK FISIKA BERBANTUAN EDMODO BERBASIS DISCOVERY LEARNING DALAM PROSES PEMBELAJARAN FISIKA

Tujuan penelitian pengembangan ini adalah untuk mengetahui tingkat kepraktisan penggunaan e-book Fisika berbantuan edmodo berbasis discovery learning dalam prosese pembelajaran. Jenis penelitian ini adalah Research and Development (R&D). Metode yang digunakan dalam penelitian yaitu metode deskriptif dengan instrumen pengumpulan data yakni angket praktikalitas yang dinilai oleh guru. Penelitian ini dilakukan di Sekolah Menengah Atas Negeri 14 Padang Tahun Ajaran 2019/2020 pada materi gelombang mekanik. Hasil penelitian ini menunjukkan bahwa e-book Fisika berbantuan edmodo berbasis discovery learning sangat praktis digunakan dalam proses pembelajaran dengan persentase rata-rata praktikalitas sebesar 90%.