Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of Social Interaction on Live-streaming Shopping Websites

Social interaction (via electronic word of mouth and observational learning) is an essential factor for successful online commerce. The new technology of live-streaming changes how social interaction affects consumers. This ongoing research investigates how instant electronic word of mouth and observational learning influence consumers’ perceptions of a live-streaming shopping website. This study also regards the perceived credibility of the seller and swift guanxi as an initial relationship state and an enhanced relationship state, respectively. Results will contribute toward IS literature by improving our understanding of social interaction and its effect on consumers’ perceptions and behaviors in a live-streaming shopping website. Furthermore, such findings can be leveraged to promote live-streaming technology among retailers planning to stimulate consumers’ purchase behavior.
Antioxidant Activity of Phenolic Compounds Extracted from the Roots and Leaves of Withania somnifera (L.) from Different Geographical Locations in India

Phenolic compounds and antioxidant activity were determined in the extracts of Withania somnifera root (RE) and leaf (LE) from five different geographical locations like Coimbatore, Gujarat, Kambam, Lucknow and Nagappattinam of India. The highest amount of total phenolic compounds at 29.25 mg/g DW (dry weight) of plant tissue and total flavonoids at 6.3 mg/g DW were found in RE-Lucknow. The maximum amount of kaempferol at 4.472 mg/100 g DW and quercetin at 1.340 mg/100 g DW were found in RE-Lucknow and LELucknow, respectively. Kaempferol was found in all root extracts and LE-Lucknow, while quercetin was found in all leaf extracts and two roots extracts like RE-Coimbatore and RE-Gujarat. RE-Lucknow showed the best radical scavenging activity with the IC50 value of 105.06 ± 1.65 g/mL in the DPPH assay. In addition, RE-Lucknow also showed maximum percentage of ABTS absorption inhibition activity with the IC50 value of 204.03 ± 14.88 g/mL. Therefore, the present study reveals that the W. somnifera leaf and root extracts from five geographical locations possess different antioxidant capacities due to various amounts of phenolic compounds. _____________________________________________________________________________________________________________
Using Binary Priority List and Priority Groups to Prioritize Functional Requirements: ODOO ERP as Case Study

- Requirements prioritization is an important activity during requirements collection and management phase of software engineering. Prioritization of small size requirements is not an issue but its importance increases when requirements are large in size. Different prioritization techniques are suggested to prioritize different types of requirements but none of the suggested techniques are applied to prioritize software requirements based on dependencies in functional requirements (FRs) from the perspective of software developers. This study addresses this research gap by applying Cumulative Voting (CV) and Priority Groups based prioritization approach to prioritize FRs. Using spanning trees, all FRs are first inter-related and then CV is applied first to assign priority values to each requirement belong to different spanning trees. Using priority groups, prioritized requirements belong to different spanning trees are assigned to priority groups such that all FRs inside each priority groups have similar priority. To do so, FRs of ODOO ERP as case study are considered for prioritization. Prioritized FRs can be easily managed by parallel development team members without having dependencies in FRs of priority group.
THE PROMISE OF FECAL TRANSPLANTS

THE ANIMAL MICROBIOME The microbiome is a community of microorganisms such as bacteria, fungi and viruses found living on and inside the body, including in the digestive system, and it affects many aspects of host physiology.1,2,3,4 The microbiome of the gastrointestinal tract is genetically unique and specific to each individual host. Members of this complex microbial community can be passed to offspring, and it is influenced by many medications, infectious diseases, the environment, and diet.
Theoretical investigation on the adsorption and diffusion of lithium-ion on and between graphene layers with size and defect effects

Adsorption and diffusion of lithium-ion on and between graphene layers are investigated by an analytical model, employing a pairwise potential, which can be approximated by the Lennard–Jones potential to express the interaction between lithium-ion and each carbon atom of graphene. The equilibrium position and binding energy of lithium-ion at three particular adsorption sites (hollow, bridge, and top) are calculated, and the adsorption stability is discussed. The results show that hollow site is the most stable adsorption site, and top site is the most unstable. The adsorption and diffusion of lithium-ion on different sizes of monolayer graphene are investigated and proved to be size and edge dependent. Moreover, lithium-ion would rather diffuse on the surface of graphene than through a hexagonal carbon ring to the other side no matter what the graphene sheet size is. In addition, two kinds of vacancy defects in graphene are considered to study the diffusion of lithium-ion. The vacancy defect can improve energy barrier, and if a vacancy defect is big enough, lithium-ion migrating through the vacancy area from one layer to another is feasible. The possible applications of present study include rechargeable lithium-ion graphene battery and Li storage in carbon material.
Resilient Arrival Runway Occupancy Time prediction for decision-making tool in Barcelona (LEBL) airport

When trying to maximise the use of the airport airside, it becomes a key factor for tower Air Traffic Controllers (ATCos) to optimise the runway occupancy time for landing aircraft (AROT) while maintaining the required safety levels and/or reducing unsafe events such as missed approaches and runway incursions. Accurate tools to detect and predict unsafe events are becoming necessary in order to assist ATCos in their tasks. In aviation, there are many different data sources and the paradigm of data sharing between different stakeholders is not fully implemented. This paper proposes the use of novel machine learning techniques to model AROT prediction in Barcelona airport (LEBL), using ten models trained with more than 270.000 flights, exploiting different airport and Air Navigation Service Provider (ANSP) data sources to design a resilient decisionmaking tool that assists tower ATCos in real operation environment to optimize runway occupancy while increasing the safety level by decreasing human error. Keywords-component; machine learning; AROT; neural network; prediction; airport; capacity; safety.
Analysis of Medical Markets and Use of Mechanism Design Physician-Patient Interactions and Role of Organizations

This paper has been written after a seminar at the Soton business school (University of Southampton), discussing how market design mechanism can be useful for some medical markets, especially in combination with the reversed algorithm, called reversed conjoint model on physicians’ choices (Huttin, 2014, 2017); this first paper provides a description of two cases, one at the micro level of physician and patient interaction and a second one to integrate the organizational level of primary care groups. The first case is a micro representation of a physician-patient interaction, which can be expanded to integrate various types of heterogeneity of demand for care. The second case introduces the organizational level of primary care, with the example of the fundholding system; it leads to opt for a cooperative approach and to integrate variations between over spenders and lower spenders’ physicians. This paper uses the formalization of a game approach and proposes a stream of research for policy design in decision tools for financing reforms in health care. It explores how market failures in health care can be addressed with engineering economics and implementation of rules for different types of interactions in medical markets. Moreover, the limits to address the sources of heterogeneity between practices with tools such as yardstick competition may be addressed with the fast digitalization of the health system.
Exploring age, gender and area differences of teachers as regards mobile teaching

Introducing mobile teaching and learning in schools represents a real challenge in nowadays education. Mobile devices are able to support a diversity of tasks such as communication, interaction, collaboration, information, and resource sharing. Although mobile devices are widely used for e-learning, but also very present in non-formal and informal learning, there are many barriers against the adoption of mobile technology by teachers, for teaching purposes. This paper analyzes the perceptions of Romanian teachers as regards the use of mobile technology in the teaching and learning process. The purpose of the paper is to explore the influence of gender differences, age, and area (urban vs. rural) on the perceptions of mobile teaching and learning. The results illustrate an important influence of such variables when considering the integration of mobile technology in education, as well as of a variable that has to be taken into consideration seriously: the teache r’ s attitude concerning the use of technology.
The Feasibility of Automated Topic Analysis: An Empirical Evaluation of Deep Learning Techniques Applied to Skew-Distributed Chinese Text Classification

Text classification (TC) is the task of assigning predefined categories (or labels) to texts for information organization, knowledge management, and many other applications. Normally the categories are topical in library science applications, although they can be any labels suitable for an application. Thus, TC often requires topical analysis which relies on human knowledge. However, in recent decades, machine learning (ML) techniques have been applied to TC for efficiency, as long as a sufficient number of training texts are available for each category. Nevertheless, in real-world cases, the number of texts (documents) for each category is often highly skewed for a certain TC task. This leads to the problem of predicting labels for small categories, which is viable for humans but challenging for machines. Deep learning (DL) is an emerging class of machine learning (ML) which was inspired by human neural networks. This study aims to evaluate whether DL techniques are feasible for the mentioned problem by comparing the performance of four off-the-shelf DL methods (CNN, RCNN, fastText, and BERT) with four traditional ML techniques on five skew-distributed datasets (four in Chinese, and one in English for comparison). Our results show that BERT is effective for moderately skewed datasets, but is still not feasible for highly skewed TC tasks. The other three DL-aware methods (CNN, RCNN, fastText) do not show any advantage in comparison with traditional methods such as SVM for the five TC tasks, although they captured extra language knowledge in the pretrained word representation. To facilitate future study, all of the Chinese datasets used in this study have been released publicly, together with all of the adapted machine learning and evaluation source codes for verification and for further study at https:
Control and Optimization of Air Tra � c Networks

The air transportation system connects the world through the transport of goods and people. However, operational ine � ciencies such as ﬂight delays and cancellations are prevalent, resulting in economic and environmental impacts. In the ﬁrst part of this article, we review recent advances in using network analysis techniques to model the interdependencies observed in the air transportation system, and to understand the role of airports in connecting populations, serving air tra � c demand, and spreading delays. In the second part of the article, we present some of our recent work on using operational data to build dynamical system models of air tra � c delay networks. We show that Markov Jump Linear System (MJLS) models capture many of the salient characteristics of these networked systems. We illustrate how these models can be validated, and then used to analyze system properties such as stability, and to design optimal control strategies that limit the propagation of disruptions in air tra � c networks.
Concept of violence in jurisprudence

The social policy of any law-based state should be focused on creating decent living conditions and a high standard of well-being not only for the present but also for future generations. The demographic crisis that exists today in Ukraine is not a positive phenomenon for the Ukrainian people, which is why public authorities should promote both the education of a new healthy generation and the preservation of the existing gene pool. Having proclaimed that the person, his/her life and health, honor and dignity, inviolability and security are recognized as the highest social value in Ukraine (Article 3 of the Constitution of Ukraine), the state has committed to protect the individual, especially the child, with all available means. Articles 51-52 of the Constitution of Ukraine provide for state protection of childhood, equality of children in their rights irrespective of their origin, as well as whether they are born in or out of wedlock, and it states that any violence against the child and his/her exploitation are prosecuted by law. The Law of Ukraine “On the Protection of Childhood” notes that every child is guaranteed the right to liberty, personal integrity and protection of dignity. An important step towards the implementation of international standards for the protection of the rights of the child in the national legislation of Ukraine was the adoption of the “National Plan of Action for the implementation of the UN Convention on the Rights of the Child, approved by the Law of Ukraine “On the National Program “National Action Plan for the Implementation of the UN Convention on the Rights of the Child” for the period up to 2016 year”, the purpose of which is to ensure the functioning of the system of protection of children's rights in accordance with the requirements of the UN Convention on the Rights of the Child. But despite the extensive system of state and international legal protection, the number of criminal offenses committed against children has increased significantly recently.
Stress induced cavitation for the irrotational streaming motion of a viscous liquid past a sphere

Cavitation induced by stresses in the irrotational streaming flow of a viscous liquid past a stationary sphere is studied here using the theory of viscous potential flow. The maximum tension criterion for cavitation used here was proposed by Joseph 1995, 1998: “Liquids at atmospheric pressure which cannot withstand tension will cavitate when and where tensile stresses due to motion exceed one atmosphere. A cavity will open in the direction of the maximum tensile stress which is 45◦ from the plane of shearing in pure shear of a Newtonian fluid. ” The analysis leads to a dimensionless expression for the maximum tensile stress as a function of position which depends on the cavitation and Reynolds numbers. The main conclusion is that at a fixed cavitation number the cavitation threshold decreases with the Reynolds number and the extent of the region of flow at risk to cavitation increases as the Reynolds number decreases. This prediction that more viscous liquids at a fixed cavitation number are at greater risk to cavitation seems not to be addressed, affirmed or denied, in the cavitation literature known to us.
Effect of Self-Care Educational Intervention Based on Orem’s Self Care Theory on Self- Care Management and Fasting Blood Glucose among Patients with Type 2 Diabetes

Diabetes is one of the most common chronic health problems with alarming rapid increase worldwide. It is associated with many serious complications and self-management is essential to prevent or delay such complication. Aim: Examine the effectiveness of self-care education intervention based on Orem Self Care theory on self-care management and level of fasting blood sugar among patients with type 2diabetes and determine the relationship between appraisal of diabetes and self-care management among patients with type 2 diabetes. Design: Quasi-experimental design. Subjects and setting: A purposive sample consisted of 110 patients with type 2 diabetes, attending the diabetes outpatient clinic in Menouf's General Hospital at Menouf City, Menoufia Governorate, Egypt. Tools: Structured interview questionnaire sheet that concerned with socio-demographic data and patient’s clinical data. Appraisal of Diabetes Scale used to determine diabetic patient’s self-appraisal of diabetes. Diabetes Knowledge Questionnaire that concerned with assessing of patients' knowledge about type2 diabetes. Diabetes Self-Management Questionnaire that was used to assess diabetes self-care management activities over the last eight weeks. Results: Most of patients with type 2 diabetes had no previous education about diabetes, 42.7% had diabetes related complications, 64.5% appraised their diabetes as stressful and harmful for their daily life. The majority of diabetics had unsatisfactory level of knowledge and about half had low self-care management. Diabetics with satisfactory level of knowledge were significantly increased from 25.5% to 84.5% after the educational intervention based on Orem Self Care theory and increased the level of good self-management as well. The educational intervention resulted in significant control of the mean fasting blood sugar from 171 mg/dL ± 42.52 to 131 mg/dL ±27.37. Negative appraisal of diabetes associated with decreased diabetes self-care management. Conclusion: The implemented educational intervention based on Orem Self Care theory has significant effects in improving on self-care management, diabetes related knowledge and reducing level of fasting blood sugar among patients with type 2diabetes. Patient's appraisal of diabetes affects their self-care management. Accordingly, designing and implementing Orem-based self-care management program can be used for improving self-care management of patients with type 2diabetes and thereby improving the disease outcomes.
Calculation of the Flux Density Function for Protein Crystals from Small Scale Settling and Filtration Experiments

Development and engineering of protein crystals regarding mechanical stability and crystallizability occurs on a small scale. Later in the process chain of industrial production however, filtration properties are important to separate the crystals from mother liquor. Many protein crystals are sensitive to mechanical stress which is why it is important to know the filtration behavior early on. In this study we analyze settling and filtration behavior of isometric, rod-like and needle shaped lysozyme and rod-like alcohol dehydrogenase (ADH) crystals on a small scale using an optical analytical centrifuge. Needle shaped lysozyme and rod-like ADH crystals show compressible material behavior. With the results from settling and filtration experiments the flux density function is calculated and modeled which can be used to describe the whole settling and permeation process in dependency of the solids volume fraction. This is also an issue for simulations of industrial processes.
Community resilience and posttraumatic growth in the aftermath of collective disaster and trauma

Resilience and posttraumatic growth have aroused a growing interest in recent decades. As the next step in theoretical and applied progression, the stress and coping researchers should attempt to advance conceptual definitions and empirical research on community resilience and posttraumatic growth to adequately evaluate it in different contexts of collective disadvantage. Across two studies, we examined whether community resilience can be used as a potential tool that, by reinforcing in-group interaction, might foster individual posttraumatic growth and social well-being among people affected by collective traumatic events. In a context of collective disaster (community sample of 1075 adults from Argentina and Chile), we found positive and significant correlations of Community Resilience with Individual Resilience, Communal Mastery, Social Integration, and Subjective Wellbeing. Subsequently, we confirmed that collective traumatic experience such as a natural disaster can result in perceptions of benefits not only at personal but also at communal and societal levels. In sum, this research contributes to the study of the sense of togetherness, which can be translated into high community resilience. Also, it represents the attempts to identify the ways to promote community resilience with the purpose of empowering communities and generate sustainable community intervention.
Comparison of Two Ensemble Kalman-Based Methods for Estimating Aquifer Parameters from Virtual 2-D Hydraulic and Tracer Tomographic Tests

We compare two ensemble Kalman-based methods to estimate the hydraulic conductivity field of an aquifer from data of hydraulic and tracer tomographic experiments: (i) the Ensemble Kalman Filter (EnKF) and (ii) the Kalman Ensemble Generator (KEG). We generated synthetic drawdown and tracer data by simulating two pumping tests, each followed by a tracer test. Parameter updating with the EnKF is performed using the full transient signal. For hydraulic data, we use the standard update scheme of the EnKF with damping, whereas for concentration data, we apply a restart scheme, in which solute transport is resimulated from time zero to the next measurement time after each parameter update. In the KEG, we iteratively assimilate all observations simultaneously, here inverting steady-state heads and mean tracer arrival times. The inversion with the dampened EnKF worked well for the transient pumping-tests, but less for the tracer tests. The KEG produced similar estimates of hydraulic conductivity but at significantly lower costs. We conclude that parameter estimation in well-defined hydraulic tests can be done very efficiently by iterative ensemble Kalman methods, and ambiguity between state and parameter updates can be completely avoided by assimilating temporal moments of concentration data rather than the time series themselves.
The Determinants of Selecting Appropriate Accounting Software that meets User’s Satisfaction: Empirical Evidence from Lebanon

The selection of an appropriate accounting software package is crucial factor in doing business. Today, accounting software is considered an essential part that enhances the accountants in doing their duties; it also creates satisfaction to the accountants. (Arranya, J., 2016). Thus, accounting software package is a software that is specially developed to be enhance the accountants while achieving their tasks. The software is able to create accounting information effectively, to produce financial reports and to serve users in accordance to their needs. (Arranya, 2016).
An Alternative Test of the Hedonic Theory of Housing Markets

In this paper the hedonic theory of housing markets is used to generate a multinomial logit model of household behavior in an urban housing market. Application of hedonic theory to housing markets is by now fairly familiar and a link to multinomial logit has also been established. However, by emphasizing more heavily the bid price interpretation of hedonic theory, this paper develops a new connection to econometric estimation that essentially involves running the usual logit equations in reverse. One advantage of this approach is that the link between the logit equations and hedonic theory involves bid price rather than utility functions, and this in turn permits the empirical results to be given an extremely clear interpretation. Furthermore, in contrast to the standard logit model, the extreme value distribution required to justify the estimation technique emerges endogenously as part of the analysis.