Miracle-dz/UniFAR-FTUs huggingface dataset:
Factors Analysis for Customer Behavior on The E-Commerce Platform in Thailand

To investigate customer behavior on an e-commerce platform in Thailand that was expanding in response to the increasing value of a market in which more people purchase online. Furthermore, e-commerce is an advertising medium since it instantly connects information or user needs to target customers while also responding to market demands by reducing the time it takes to bring products to market, allowing for rapid market expansion. The study aims to study consumer behavior in online shopping through an application or platform and analyze the critical aspects of online shopping of customer behavior in e-commerce. Data were collected and processed using exploratory factor analysis (EFA) techniques, and a sample of 400 general people was chosen for survey research using questionnaires. The study's findings were as follows: Reliability testing; KMO and Bartlett's tests; total variance explained; Scree plot; rotated component matrix. The result of the EFA analysis came down to two components from 21 variables. As a result, they have been extremely positive and have garnered the most attention.
COMPUTER VISION AIDED HOTSPOT CREATION IN VIRTUAL ENVIRONMENTS

Abstract Hotspot creation is one of the most important modules within virtual environments which helps show the navigators of these environments some information about semantic elements within it and facilitate the navigation between the virtual spaces. In this paper, a system for automatic hotspot proposals and creation in virtual environments is proposed. The system uses computer vision modules to automatically propose hotspot locations in addition to identifying and creating these hotspots with candidate labels. Two main modules used in the system are object detection and scene segmentation. The scene segmentation helps give candidate hotspot areas and provides an overall understanding of the semantics of the virtual environment. The object detection module also uses pretrained deep networks for automatic hotspot creation over these objects. The system helps speed up the hotspot creation process and offers a tool for virtual environment users and creators.
Numerical investigation of thermal spallation drilling using an uncoupled quasi-static thermoelastic finite element formulation

ABSTRACT In this work, we examine thermal spallation drilling through finite element modeling of the uncoupled quasi-static thermoelastic problem describing the stresses induced by rapid and localized heating of a uniaxially pre-stressed rock core. The numerical procedure is verified using the method of manufactured solutions, and the optimal order of accuracy is demonstrated. From a series of numerical experiments, we present the temperature and stress profiles along the centerline of the rock core which are discussed qualitatively with respect to the corresponding laboratory experiments. Our numerical results, in agreement with the experiments, emphasize that the efficiency of thermal spallation drilling increases linearly with the vertical stress.
Examining the effectiveness of a group hope intervention program in Syrian refugee children: A pilot study

ABSTRACT The purpose of this study was to investigate the effectiveness of a 6-session hope-based intervention program on the levels of hope and psychological resilience of Syrian refugee children. The pre-test post-test control group design was implemented. A total of 42 Syrian refugee students in 5th grade participated in the study. 2 × 2 mixed ANOVA, independent sample t-test, and dependent sample t-test were conducted for data analysis. Mixed ANOVA revealed that the intervention group had more improvement in hope and psychological resilience scores compared to the control group. Dependent sample t-test revealed that while the hope and resilience scores of the intervention group were maintained, the hope scores of the control group significantly decreased. Independent sample t-test revealed a statistically significant difference between the post-test hope scores of the groups. Research findings supported that hope-oriented approaches can be effective in improving the resilience of Syrian refugee children in the long term.
An empirical study into factors that influence e-learning adoption by medical students in UAE

Aim: The global higher education sector has shown an inclination towards the adoption of technology-based learning for introducing innovation in teaching and learning activities. However, this e-learning environment can only be effective if students have positive perceptions of e-learning. Hence, educational personnel is required to consider how students perceive this concept. This research intends to serve this purpose by identifying factors affecting students' acceptance of e-learning as well as their intention toward the use of e-learning for their learning activities. Methods: The Technology Acceptance Model (TAM) was used in this re-search to formulate a theoretical framework. This research will employ online questionnaires as a data collection tool while the international students enrolled at United Arab Emirates universities will serve as study participants. Results: The research outcomes indicated the most crucial role played by the predictors of “Accessibility" “Perceived Enjoyment", “Social Influence”, “Perceived Usefulness”, and "Perceived Ease of Use" in shaping students’ intention to resort to e-learning platforms for learning purposes. Conclusion: The research indicated that the extended TAM model is applicable in the UAE educational context. The research outcomes also showed the possibility for policymakers in the educational sector to make effective use of e-learning platforms both as a technological solution and as an e-learning platform to support distance learning. The research also highlights the practical implications for the concerned educational developers in the educational sector to help them develop and apply a competent e-learning system.
Bone Awls and Basketry in Tierra del Fuego: Complementarity between Ethnography and Experimentation

ABSTRACT The use of rushes and bone awls for indigenous basketry is mentioned in ethnohistoric and ethnographic sources from across the Americas, including Tierra del Fuego. Our research aimed to reproduce and record the technical process of basketry and how bone awls are involved in it, according to hypotheses derived from the ethnographic data. For this study, a techno-functional approach was adopted that combines the ethnographic record, community-based research, experimentation, and microscopic functional analysis. The chaine opératoire was reproduced for basket making, from the technical processes involved in collecting and processing rushes to completion of the basket. Results confirmed the effectiveness of techniques described in the documentary sources for the manufacture of baskets of Marsippospermum grandiflorum, including the use of bone awls. Functional analysis demonstrated the formation of characteristic use-wear traces produced by this activity.
A Hierarchical Vehicle Behavior Prediction Framework With Traffic Signals and Interactive Agents

Vehicle behavior prediction in complex urban scenarios with traffic signals and interactive agents is an important yet complicated task for autonomous vehicles (AVs). In this work, a hierarchical vehicle behavior prediction framework is proposed to incorporate the traffic signal information and model the interaction between vehicles. The framework predicts vehicle behaviors in two stages, discrete intention prediction and continuous trajectory prediction. In the discrete intention prediction stage, Bayesian network is adopted to provide a high-level behavior prediction of the principle other vehicle. The discrete prediction results are forwarded to the second stage, where a continuous trajectory is predicted with maximum entropy inverse reinforcement learning and potential game. The framework is designed to be able to capture the difference among human drivers with parameterized driver characteristics. The proposed predictor is validated in two scenarios: the yellow light running scenario and the right-turn scenario. The trajectory prediction average displacement error of the yellow light running scenario is 0.695m for a 3-second prediction interval, and the prediction accuracy of the right-turn vehicle in the right-turn scenario is 0.51m for a 2-second prediction interval.
A Supervised Learning Approach to Assessing Accounts Receivable Risk in Small-to-Medium Enterprises

Information technology, e-commerce, and data analytics have drastically changed the way companies do business. Few data related practices are more important than assessing risk; for example, the risk inherent in a firm’s accounts receivable (AR). While small-to-medium enterprises (SMEs) comprise a large portion of the global economy, they may be too small to devote extensive internal resources to risk analysis. At the same time, readily available risk related information may be ill suited to the needs of diverse SMEs. We explore the potential for readily available machine learning techniques, accessible to SMEs at modest cost, to assess the AR risk faced by a medium sized transportation brokerage, John J. Jerue Truck Broker. Of the models considered, linear discriminant analysis performed best when risk is modeled with three categories and decision trees performed best when there were two categories. Our results demonstrate the potential for SMEs to develop risk assessments to flexibly meet their own diverse needs.
Genome-Wide Analysis of MAMSTR Transcription Factor-Binding Sites via ChIP-Seq in Porcine Skeletal Muscle Fibroblasts

Simple Summary Skeletal muscle is the most abundant tissue in animals, accounting for 45–60% of the body weight of meat animals, and the growth and development of skeletal muscle has the most direct impact on lean meat percentage and muscle quality. Therefore, exploring the molecular regulation mechanism of skeletal muscle growth and development is an important basis for improving pig meat production performance, and it has also been a research focus in animal genetics in recent years. In this study, ChIP-seq and other methods were used to explore the transcriptional regulation mechanism of new transcription factor MAMSTR in pig skeletal muscle development, The results of this study can further reveal the regulatory mechanism of pig skeletal muscle growth and development, identify new genes related to pig skeletal muscle growth and development, and provide a better reference for pig-farming practices and breeding of high-quality meat pig breeds. Abstract Myocyte enhancer factor-2-activating motif and SAP domain-containing transcriptional regulator (MAMSTR) regulates its downstream through binding in its promoter regions. However, its molecular mechanism, particularly the DNA-binding sites, and coregulatory genes are quite unexplored. Therefore, to identify the genome-wide binding sites of the MAMSTR transcription factors and their coregulatory genes, chromatin immunoprecipitation sequencing was carried out. The results showed that MAMSTR was associated with 1506 peaks, which were annotated as 962 different genes. Most of these genes were involved in transcriptional regulation, metabolic pathways, and cell development and differentiation, such as AMPK signaling pathway, TGF-beta signaling pathway, transcription coactivator activity, transcription coactivator binding, adipocytokine signaling pathway, fat digestion and absorption, skeletal muscle fiber development, and skeletal muscle cell differentiation. Lastly, the expression levels and transcriptional activities of PID1, VTI1B, PRKAG1, ACSS2, and SLC28A3 were screened and verified via functional markers and analysis. Overall, this study has increased our understanding of the regulatory mechanism of MAMSTR during skeletal muscle fibroblast development and provided a reference for analyzing muscle development mechanisms.
Method and Algorithm for solving the Bicriterion Network Problem

In this paper, a bicriterion shortest route problem is formulated as a two criterion linear programming problem. A method and algorithm are presented for solving bicriterion network problem, which are based on introducing the fuzzy sets of the value “near to the optimal values” for each criterion, and transforming the initial problem into a mixed integer linear programming problem. The applicability of the algorithm is demonstrated by considering an example.
Resolution and optimal regularity for a biharmonic equation withimpedance boundary conditions and some generalizations

In this work, a biharmonic equation with an impedance (non standard) boundary condition and more general equations are considered. The study is performed in the space $L^{p}(-1,0$ $;$ $X)$, $1 0}$ set in a domain having a thin layer. The limiting problem models, for instance, the bending of a thin plate with a stiffness on a part of its boundary (see Favini et al. [13]). We build an explicit representation of the solution, then we study its regularity and give a meaning to the non standard boundary condition.
Association between diet quality and type of meal companion: the 2013–2015 Korea National Health and Nutrition Examination Survey (KNHANES)

BACKGROUND/OBJECTIVES A meal companion is an important social determinant of eating behaviors and is related to what and how much a person will eat within the social context. This study examined the difference in diet quality according to the type of dining companion. SUBJECTS/METHODS This study included 15,074 adults (6,180 men and 8,894 women, ≥ 19 years) who participated in the 6th (2013–2015) Korea National Health and Nutrition Examination Survey. Korean Healthy Eating Index (KHEI) scores were calculated using the food frequency questionnaire data. Survey multivariate linear regression analysis was used to assess the association of dining companions (ordinary type, eating with family members, eating alone, and eating with others) and the total and component scores of KHEI. RESULTS People who exclusively ate with someone other than family or exclusively ate alone had lower total KHEI scores in both men (57.23 ± 0.67, 58.56 ± 0.73 vs. 62.71 ± 0.26) and women (57.6 3±0.97, 63.89±0.58 vs. 65.79±0.22) compared to people with the ordinary type (all P < 0.05). Both men and women who ate exclusively with someone other than family had lower KHEI component scores for breakfast, whole grains, and fruit, excluding juice, compared to the ordinary type and family eating group. Compared to the eating alone group, the component scores for breakfast and whole grains were lower in the eating with others group. CONCLUSION The diet quality differed according to the meal companion type. People who always ate with someone other than family members and men who ate alone showed lower diet quality scores than the ordinary type. More research will be needed to improve their adherence to dietary recommendations.
NEW SPARSE MATRIX SOLVER in the KIKO3D 3-DIMENSIONAL REACTOR DYNAMICS CODE

The goal of this paper is to present a more effective method Bi-CGSTAB for accelerating the large sparse matrix equation solution in the KIKO3D code. This equation system is obtained by using the factorization of the improved quasi static (IQS) method for the time dependent nodal kinetic equations. In the old methodology standard large sparse matrix techniques were considered, where Gauss-Seidel preconditioning and a GMRES-type solver were applied. The validation of KIKO3D using Bi-CGSTAB has been performed by solving of a VVER-1000 kinetic benchmark problem. Additionally, the convergence characteristics were investigated in given macro time steps of Control Rod Ejection transients. The results have been obtained by the old GMRES and new Bi-CGSTAB methods are
Differences in Outcomes Between Human Epidermal Growth Factor Receptor 2 (HER2)-Positive Metastatic Breast Cancer Patients in Upper Middle-Income versus High-Income Countries: A Retrospective Study from 4 Oncology Centers

Background Therapeutic options for human epidermal growth factor 2 (HER2)-positive metastatic breast cancer (mBC) are developing rapidly. This study aimed to determine the differences in the survival outcomes of patients with HER2-positive mBC in relation to access to anti-HER therapy at 3 oncology centers in upper-middle-income countries (UMICs) and 1 oncology center in a high-income country (HIC). Material/Methods We retrospectively identified 42 patients from Croatia (HIC), 71 patients from Serbia (UMIC), and 57 from Bosnia and Herzegovina (UMIC) diagnosed with HER2-positive mBC who were treated between January 2015 and December 2020. The pathohistological features of the tumors were obtained from the pathological findings, which were made according to standard procedures for each center. Patients were treated depending on the availability of therapy, which differed for centers in different countries. We evaluated disease-free survival, progression-free survival, and overall survival (OS) based on the availability of first- and second-line anti-HER2 therapy in UMICs vs HIC. Results OS in first-line therapy was better in patients treated with dual HER2 blockade than in patients treated without dual HER2 blockade, P<0.001. OS in second-line therapy was significantly better in patients treated with trastuzumab emtansine than in patients treated with other reported regimens, P=0.004. Conclusions Results of our study showed superior survival among patients who were treated with dual first-line HER2 therapy as well as second-line trastuzumab emtansine therapy than in those patients in other centers where these drugs were not available. Raising awareness about this could help improve the situation.
Signal Phasing and Timing Prediction Using Connected Vehicle Data

Signal phasing and timing can be adaptive and actuated in practice. This makes it challenging to understand what the cycle length and phase duration of the next few cycles will be. Many innovative applications can be designed based on the knowledge of future signal timing states such as dilemma zone warning, efficient route planning, and so forth. This work proposes a long short-term memory model capable of predicting both cycle length and phase duration prediction up to six cycles in the future. GPS information of several vehicles are merged with signal timing information of eight intersections. Several key features such as waiting time, approach speed and acceleration, departing speed and acceleration, are calculated based on the geolocation of individual journeys. The results show that cycle length prediction can reach mean absolute error (MAE) of about 7 s while phase prediction MAE is about 9 s.
Real-time modification of collision-free paths

The modification of collision-free paths is proposed as the basis for a new framework to close the gap between global path planning and real-time sensor-based robot control. A physically-based model of a flexible string-like object, called an elastic band, is used to determine the modification of a path. The initial shape of the elastic is the free path generated by a planner. Subjected to artificial forces, the elastic band deforms in real time to a short and smooth path that maintains clearance from the obstacles. The elastic continues to deform as changes in the environment are detected by sensors, enabling the robot to accommodate uncertainties and react to unexpected and moving obstacles. While providing a tight connection between the robot and its environment, the elastic band preserves the global nature of the planned path. The greater part of this thesis deals with the design and implementation of elastic bands, with emphasis on achieving real-time performance even for robots with many degrees of freedom. To achieve these goals, we propose the concept of bubbles of free-space---a region of free-space around a given configuration of the robot generated from distance information. We also develop a novel algorithm for efficiently computing the distance between non-convex objects and a real-time algorithm for calculating a discrete approximation to the time-optimal parameterization of a path. These various developments are combined in a system that demonstrates the elastic band framework for a Puma 560 manipulator.
A Systematic Review and Meta-Analysis of Trifluridine/Tipiracil plus Bevacizumab for the Treatment of Metastatic Colorectal Cancer: Evidence from Real-World Series

Background: Colorectal cancer is the most prevalent gastrointestinal neoplasm. When metastatic, the disease has limited systemic treatment options. Novel targeted therapies have expanded these options for subsets with specific molecular alterations, such as microsatellite instability (MSI)-high cancers, but additional treatments and combinations are in urgent need to improve outcomes and improve survival of this incurable disease. The fluoropyrimidine-derivative trifluridine, in combination with tipiracil, has been introduced as a third-line treatment, and more recently, it was studied in combination with bevacizumab. This meta-analysis reports on studies with this combination in clinical practice outside clinical trials. Methods: A literature search in the Medline/PubMed and Embase databases was executed for finding series of trifluridine/tipiracil with bevacizumab in metastatic colorectal cancer. Criteria for inclusion in the meta-analysis were English or French language of the report, inclusion of twenty or more patients with metastatic colorectal cancer treated with trifluridine/tipiracil in combination with bevacizumab outside of a trial and containing information regarding response rates, progression-free survival (PFS), and overall survival (OS). Information on the demographics of the patients and on adverse effects of treatment was also collected. Results: Eight series with a total of 437 patients were eligible for the meta-analysis. The performed meta-analysis discovered a summary response rate (RR) of 2.71% (95% confidence interval (CI): 1.11–4.32%) and a disease control rate (DCR) of 59.63% (95% CI: 52.06–67.21%). Summary PFS was 4.56 months (95% CI: 3.57–5.55 months), and summary OS was 11.17 months (95% CI: 10.15–12.19 months). Common adverse effects identified mirrored the adverse-effect profile of the two components of the combination. Conclusion: The current systematic review and meta-analysis reports the efficacy of trifluridine/tipiracil with bevacizumab in advanced lines of therapy for metastatic colorectal cancer in the setting of clinical practice outside clinical trials. Discovery of predictive biomarkers of response to trifluridine/tipiracil with bevacizumab will promote the tailoring of this treatment to individual patients to maximize clinical benefit.
Noise analysis and noise reduction for low-dose CT sinogram

The improvement of the SNR of the low-dose CT image is a crucial issue for the low-dose CT application.As studied before,the noise in the calibrated and log-transformed projection data of low-mA(or low-dose) CT protocol follows approximately a non-stationary Gaussian distribution.In this study,we further demonstrate that some isolated noise points would not satisfy the above observation.Hence,we propose a noise reduction scheme for low-dose CT sinograms,which includes isolated datum detection and removal,MAP estimation and FBP reconstruction.The effectiveness of the proposed method is validated by both computer simulations and experimental studies.