Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of the COVID-19 Pandemic on Online Consumer Purchasing Behavior

With the spread of the COVID-19 pandemic and the increasing importance of e-commerce, the study of online consumer behavior is of particular relevance. The purpose of this study was to form a methodological approach to assess the relationships and the level of influence of the factors activating the purchasing behavior of online consumers against the background of the COVID-19 pandemic. The research methodology was based on the transformation of Cattell’s questionnaire and the implementation of correlation analysis. To determine the predisposition of online consumer behavior at the time of making a purchase decision, this study used the questionnaire method. The survey was conducted among online shoppers in the top 10 countries in terms of e-commerce market growth. The scientific contribution is the proposed methodological toolkit to assess the purchasing behavior of online consumers, which identifies the most influential factors in their purchasing behavior and provides an opportunity to assess the dynamics of their activity during the study period, to identify key trends and determine changes in their behavior. The research revealed what changes in online consumer buying behavior are typical in the COVID-19 pandemic. The impact of consumer awareness and experience has increased. Online consumers have become more experienced, which has influenced the activity of their buying behavior. This study proved the shifting influence of online consumer purchasing behavior factors during the pandemic. The increasing importance of the speed of decision making by consumers when purchasing goods and services online was determined.
Difficulties in Solving Non-Routine Problems: Preliminary Analysis and Results

Students have been taught to solve problems since primary school. However, they still have been having difficulties in solving mathematics problems, especially non-routine problems. By searching errors in mathematics skills and cognitive abilities that have been causing difficulties in solving non-routine problems, this study aims to determine the dominant difficulties that high-achieving students commonly face. A problem-solving test (PST) that comprises four non-routine problems involving algebra was distributed to 56 Form Four selected students through purposive sampling. Each problem is followed by a reflection that allows students to describe the difficulties they face while solving the problem. Hence, the qualitative and quantitative analysis of answer scripts as well as students’ reflection shows that the dominant difficulties faced by high-achieving students when solving non-routine problems are language and information management skills. Poor mastery of these two skills has resulted in students being unable to decipher the problem accordingly which then leads to failing to solve the problems. The findings of this study provide important insight for educators and also researchers in assisting students to deal with their difficulties to solve non-routine problems.
Artificial-Intelligence-Based Time-Series Intervention Models to Assess the Impact of the COVID-19 Pandemic on Tomato Supply and Prices in Hyderabad, India

This study’s objective was to assess the impact of the COVID-19 pandemic on tomato supply and prices in Gudimalkapur market in Hyderabad, India. The lockdown imposed by the government of India from 25 March 2020 to 30 June 2020 particularly affected the supply chain of perishable agricultural products, including tomatoes as one of the major vegetable crops in the study area. The classical time series models such as autoregressive integrated moving average (ARIMA) intervention models and artificial intelligence (AI)-based time-series models namely support vector regression (SVR) intervention and artificial neural network (ANN) intervention models were used to predict tomato supplies and prices in the studied market. The modelling results show that the pandemic had a negative impact on supply and a positive impact on tomato prices. Moreover, the ANN intervention model outperformed the other models in both the training and test data sets. The superior performance of the ANN intervention model could be due to its ability to account for the nonlinear and complex nature of the data with exogenous intervention variable.
Relationship between Locus of Control and Academic Achievement of Secondary School Students in Abia State

The study intended to determine the relationship between locus of control and academic achievement of secondary school students. Some students have been observed to achieve higher while some achieve lower even after being exposed to the same subject matter by the same instructor. The objective of the study was to determine if locus of control correlated with academic achievement of students as moderated by gender and school-type. The study was anchored on attribution theory. The study adopted a correlational research design. A total of 388 SS3 students in Aba Education zone were selected using purposive and simple random sampling techniques. Instruments for data collection were an adopted LOC scale and students’ exam scores in Mathematics, English and CRS. To determine the reliability of the instrument, Kuder-Richardson reliability test (KR-20) was employed and an overall coefficient of 0.76 was obtained for LOC scale. Data were analyzed using Pearson Product Moment Correlation Coefficient. Results showed significant relationship between locus of control and academic achievement of male students. Results also showed significant relationship between locus of control and academic achievement of public school students. Based on the findings, it was recommended that school authority should encourage good performance by rewarding students with excellent performance, because when good behaviour is rewarded, the individual is motivated to do better. Also, government should also provide the schools with necessary infrastructures that would make teaching and learning very interesting.
Intransitivity of Consumer Preferences for Privacy

Consumers frequently exchange their private personal data with companies in return for goods and services, such as access to search results or social networks. The authors provide a normative criterion to help assess whether companies compensate consumers adequately for their private data in these exchanges. Across a series of 11 experiments, they find that individuals place a higher price on their private data when they sell them for money than when they barter them for goods. In an application of the compatibility principle in cognitive psychology, the authors also find in two additional experiments that this effect occurs because money is a more compatible medium for valuing private data than goods are, which increases the weight of the data in monetary valuations, raising the prices that participants demand for their private data in money compared with goods. This discrepancy in valuations constitutes a violation of procedure invariance and amounts to an intransitivity of participants’ preferences for privacy. The findings raise the question of whether companies are compensating consumers adequately for their data and whether the ubiquitous markets for privacy function efficiently. Accordingly, the authors point to a possible consumer welfare argument for antitrust regulation of technology companies.
The Effectiveness of Clerodendrum Paniculatum. L against TNF- α in Rats Induced by S. Aureus

: Staphylococus Aureus is one of the mastitis causes which causes inflammation due to elevated levels of TNF- α . This study aimed to analyze the anti-inflammatory activity of bag flower leaf ( Clerodendrum Paniculatum L ) on TNF- α level in rats that is induced by S. Aureus bacteria. This study used post test only control group design with 15 samples of Strain Sprague Dawley rats divided into 3 groups. K (-) group as normal control group, K (+) was induced by S. Aureus bacteria and the treatment group was administered by extract 150mg / kg BB then it is measured TNF- α levels by the enzyme-linked immunosorbent assay (ELISA) test method. Data were analyzed by using bivariate analysis namely one way ANOVA test. The results showed that Bag Flower Extract contains secondary metabolites in the form of flavonoids and tannins. Giving bag flower leaf extract ( Clerodendrum Paniculatun L ) at 150 mg / kg BB has antiinflammatory action by reducing TNF- α levels in rate which is induced by staphylococcus aureus (P <0, 0). 05). It was concluded that the administration of bag flower leaf extract could reduce TNF- α cytokines due to S. Aureus bacteria. It is expected that future researchers will use human subjects to analyze TNF- α levels so that later bag flower leaves can be used as complementary therapies in mastitis treatment due to S. aureus bacteria.
Consumer Legal Protection: Building Legal Awareness in the Age of Globalization

-Consumers are one of the backbones of the economy. Without consumers, the production sector cannot run smoothly. The large population of Indonesia ensures that the country has large consumption power. However, whether this potential benefit followed by the protection of consumer rights is an important question. This is significant to address because consumers are considered having a weaker bargaining position and therefore vulnerable to being exploited. This article aims to show how the legal protection for consumer. This article applies a normative approach. Data are gathered from a review of consumer protection laws. This study shows that based on legal policies, the state tries to protect consumer rights in order to foster a good transaction climate. This protection of consumer rights is reflected in the rule of law that emphasizes consumer rights, the obligations of business actors, and prohibitions for business actors from actions that can harm consumers. However, consumer protection is acceptable to be normative and must also be built based on the consumer own legal awareness.
Capturing Discriminative Information Using a Deep Architecture in Acoustic Scene Classification

Acoustic scene classification contains frequently misclassified pairs of classes that share many common acoustic properties. Specific details can provide vital clues for distinguishing such pairs of classes. However, these details are generally not noticeable and are hard to generalize for different data distributions. In this study, we investigate various methods for capturing discriminative information and simultaneously improve the generalization ability. We adopt a max feature map method that replaces conventional non-linear activation functions in deep neural networks; therefore, we apply an element-wise comparison between the different filters of a convolution layer’s output. Two data augmentation methods and two deep architecture modules are further explored to reduce overfitting and sustain the system’s discriminative power. Various experiments are conducted using the “detection and classification of acoustic scenes and events 2020 task1-a” dataset to validate the proposed methods. Our results show that the proposed system consistently outperforms the baseline, where the proposed system demonstrates an accuracy of 70.4% compared to the baseline at 65.1%.
Predicting language outcomes for children learning augmentative and alternative communication: child and environmental factors.

PURPOSE To investigate a model of language development for nonverbal preschool-age children learning to communicate with augmentative or alternative communication. METHOD Ninety-three preschool children with intellectual disabilities were assessed at Time 1, and 82 of these children were assessed 1 year later, at Time 2. The outcome variable was the number of different words the children produced (with speech, sign, or speech-generating devices). Children's intrinsic predictor for language was modeled as a latent variable consisting of cognitive development, comprehension, play, and nonverbal communication complexity. Adult input at school and home, and amount of augmentative or alternative communication instruction, were proposed mediators of vocabulary acquisition. RESULTS A confirmatory factor analysis revealed that measures converged as a coherent construct, and a structural equation model indicated that the intrinsic child predictor construct predicted different words children produced. The amount of input received at home, but not at school, was a significant mediator. CONCLUSIONS The hypothesized model accurately reflects a latent construct of Intrinsic Symbolic Factor (ISF). Children who evidenced higher initial levels of ISF and more adult input at home produced more words 1 year later. The findings support the need to assess multiple child variables and suggest interventions directed to the indicators of ISF and input.
Plasma CCL16 Chemokine Secretion and Expression in Liver Tissue of Patients with Autoimmune Hepatitis: A Pilot Study

10 cases was confirmed the diagnosis of autoimmune hepatitis and in 4 cases the biopsy was compatible with steatosis/ steatohepatitis. Twenty-two patients were included in the control group. No statistically significant differences were found between the groups in terms of plasma CCL16 levels (p = NS). Its concentration was not associated with the presence of liver fibrosis in the biopsy (p = 0.28) or with the response after 6 months of treatment (p = 0.90). Conclu-sion . This is a study that has determined the expression of chemokine CCL16 in patients with autoimmune hepatitis. It was observed that the plasma secretion of CCL16 decreased in the autoimmune hepatitis group, compared to the control group, but this difference was not statistically significant.
Antimycotic efficiency of essential oils and ethanol extracts of some medicinal plants in Egypt

The antimycotic activity of essential oils and ethanol extracts of seven species of medicinal plants namely; garlic, galangal, cinnamon, eucalyptus, elecampane, basil and clove were assayed against the growth of five pathogenic fungi; Aspergillus flavus, A. niger, A. ostianus, Alternaria alternata and Fusarium solani in addition to Candida albicans (pathogenic yeast) by disc diffusion method. The results revealed that garlic essential oil had broad-spectrum activity against all tested fungi followed by clove, cinnamon, elecampane, basil, galangal and eucalyptus. Clove ethanol extract had broad-spectrum activity against all tested fungi followed by elecampane and cinnamon. Minimum inhibitory concentration (MIC) and qualitative phytochemical screening were carried out for the wide spectrum highly active antimycotic extracts. Garlic, cinnamon, elecampane and clove essential oils and cinnamon, elecampane and clove ethanol extracts were chosen to undergo the minimum inhibitory concentration (MIC) determination and qualitative phytochemical screening. Both clove essential oil and ethanol extract, compared to the other extracts, exhibited the best antimycotic activity and lowest MIC in concentration.
When Will MISR Detect Rising High Clouds?

It is predicted by both theory and models that high‐altitude clouds will occur higher in the atmosphere as a result of climate warming. This produces a positive longwave feedback and has a substantial impact on the Earth's response to warming. This effect is well established by theory, but is poorly constrained by observations, and there is large spread in the feedback strength between climate models. We use the NASA Multi‐angle Imaging SpectroRadiometer (MISR) to examine changes in Cloud‐Top‐Height (CTH). MISR uses a stereo‐imaging technique to determine CTH. This approach is geometric in nature and insensitive to instrument calibration and therefore is well suited for trend analysis and studies of variability on long time scales. In this article we show that the current MISR record does have an increase in CTH for high‐altitude cloud over Southern Hemisphere (SH) oceans but not over Tropical or the Northern Hemisphere (NH) oceans. We use climate model simulations to estimate when MISR might be expected to detect trends in CTH, that include the NH. The analysis suggests that according to the models used in this study MISR should detect changes over the SH ocean earlier than the NH, and if the model predictions are correct should be capable of detecting a trend over the Tropics and NH very soon (3–10 years). This result highlights the potential value of a follow‐on mission to MISR, which no longer maintains a fixed equator crossing time and is unlikely to be making observations for another 10 years.
The Influence of Company’s Characteristics to Propensity to Pay Dividend

: The study aims at describing and analizing the influence of company’s characteristics to propensity to pay dividen. The units of observation were 4530 companies recorded by Indonesia Stock Exchange from 2008 up to 2017. In analizing the data, logit regression was implemented. The finding shows that the greater the company’s profitability, the greater the propensity to pay dividend will be. Further, the lower the asset growth and market to book ratio, the greater the propensity to pay dividen will be.
Mixture of Experts of Neural Networks and Kalman Filters for Optical Belt Sorting

In optical sorting of bulk material, the composition of particles may frequently change. State-of-the-art sorting approaches rely on tuning physical models of the particle motion. The aim of this work is to increase the prediction accuracy in complex fast-changing sorting scenarios with data-driven approaches. In this article, we propose two neural network (NN) experts for accurate prediction of a priori known particle types. To handle the large variety of particle types that can occur in real-world sorting scenarios, we introduce a simple but effective mixture of experts’ approach that combines NNs with hand-crafted motion models. Our new method not only improves the prediction accuracy for bulk material consisting of many particle classes, but also proves to be very adaptive and robust to new particle types.
Digital Readiness for Social Educators in Health Care and Online Learning During COVID-19 Pandemic: A Bibliometric Analysis

Digital technologies have been earsplittingly discussed for a long time with multi-sides of enormous benefits and challenges in educational application. When the Covid19 pandemic has outbreak worldwide, global governments have popularly employed the movement control order (MCO) and social distances policies, international borders closed, schools and higher education applied for fully online courses. Several studies show that digital readiness is the crucial factor that significantly impacts students' satisfaction and success in online learning. This study will analyze the overall resources and digital readiness in multi-sides to enhance student learning and development outcomes through an online learning environment. For this purpose, Scopus and web of science databases are used to find the literature. The final 32 articles are select for the S.L. R. (systematic literature review). The bibliometric analysis will conduct for text frequency co-occurrence to identify the cluster themes. The vital step of data classification will process according to the author's segmentation and published research settings. In the last findings of the study, reports will explain past literature and recent outbreak. The findings cover three main themes: digital readiness in learning management, digital readiness for learners, and digital readiness for educators. During the covid19 pandemic, the concept of digital readiness for educators concealed in both healthcare advising and lesson teaching in home-based learning models. These findings are expected to benefit stakeholders involved in online teaching and learning during and resilient post-Covid-19 pandemic.
Self-reported Reasons for Changes in Performance of Daily Activities During a 2-Year Multidisciplinary Multiple Sclerosis Rehabilitation.

Background Few multidisciplinary rehabilitation studies with a heterogeneous design have focused on individuals with multiple sclerosis (MS). This study compared subjective-reported changes in performance and satisfaction with daily activities among moderately and severely disabled individuals with MS during a 2-year, multidisciplinary, group-based, outpatient rehabilitation program comprising education in self-management and compensatory techniques, exercise, and guided peer support. Methods Thirty-eight adults with moderate disability (Expanded Disability Status Scale [EDSS] score of 4.0-5.5, 74% women, mean age of 48) and 41 individuals with severe disability (EDSS 6.0-8.5, 63% women, mean age of 48) were assessed at baseline and after 12 and 21 months of outpatient rehabilitation using the Canadian Occupational Performance Measure (COPM). Group × time interactions were analyzed using mixed analysis of variance. Participants' explanations of reasons for changes in activity performance were collected via semistructured interviews and analyzed content. Results Statistically significant improvements in COPM performance and satisfaction scores were reported in both groups from baseline to 21 months of rehabilitation. No significant between-group differences in improvement were observed. The self-reported reasons for improvement were mainly linked to environmental factors. Conclusions The outpatient rehabilitation program, including 4 themes-cognition, mood, energy conservation, and body control-improved the self-reported performance of patients with MS with moderate and severe disabilities. Environmental factors warrant consideration during rehabilitation.
Maternal exposure to work schedule unpredictability and child behavior

Abstract Objective This article estimates the association between maternal exposure to unpredictable work schedules in the service sector and child internalizing and externalizing behavior. Background Precarious work is widespread and characterized by low wages, few benefits, and nonstandard schedules. But working parents, especially in the service sector, contend with unpredictable work schedules as well. These schedules have negative consequences for workers, but may also perpetuate inequality across generations by negatively affecting children. Method This article takes advantage of novel survey data from The Shift Project, covering 2,613 mothers (surveyed 2017–2019) working in the service sector with children (mean child age of 7.5), to examine the association between maternal work schedules and child behavior as well as the mediators of this relationship. Results Maternal exposure to unpredictable work schedules is associated with children's externalizing and internalizing behavior. Mediation analysis shows that for parents with the most unpredictable schedules, this aspect of job quality operates on children's behavior by increasing household economic insecurity, reducing developmental parenting time, and diminishing maternal well‐being. Conclusion These results demonstrate that work scheduling conditions may have consequences not just for workers themselves but also for their children.
TARGETING INTERLEUKIN 17 IN THE TREATMENT OF RHEUMATOID ARTHRITIS

Interleukin 17 (IL-17) is a family of pro-inflammatory cytokines discovered in 1993. IL-17 drives an important pathogenic pathway in rheumatoid arthritis (RA), leading to and sustaining chronic inflammation. The recognition of this role made IL17 a potential therapeutic target of biological drugs. In the current study, meta-analytical data on the effect of anti-IL-17 therapy in RA revealed that secukinumab and ixekizumab were effective in generating significant responses, but brodalumab was not. In terms of safety, anti-IL-17 therapy did not significantly increase the overall risk of any side effects compared to placebo, but the analysis of individual side effects revealed an increased risk of infection. Evidence suggests that the involvement of IL-17 which can be sensitive to treatment occurs early in the disease process. This would explain the seemingly limited success of anti-IL-17 targeted therapy found by RA studies so far. Trials recruiting asymptomatic and early symptomatic RA patients are needed to confirm this hypothesis.