Miracle-dz/UniFAR-FTUs huggingface dataset:
Dorsalgia rehabilitation in static disorders of the spine by therapeutic swimming
in young adults

The purpose of this paper is to point out and propose the most effective means of therapeutic swimming in the use of work programs for patients with dorsalgia in spinal static disorders. The knowledge degree of therapeutic swimming is not sufficiently promoted and used, which is why we propose the following hypothesis: we start from the premise that therapeutic swimming can reduce the dorsalgia in the spine, improve lung capacity and physical condition in young adults. The objectives of this work are to identify subjects with spinal static dorsalgia and to establish the sample for the experiment; in the selection of therapeutic swimming means for the elaboration of the work program; in the registration and interpretation of the data in the form of tables and charts. The experiment took place at the Kinetic Therapy Practice of Mr. Constantinescu Mihai, as well as at the swimming pool in Cornisa, Botoşani county, with a sample consisting of 15 subjects aged between 18 and 22, all of whom suffered dorsalgia (in the spine). In this respect, we set out to implement a therapeutic swimming program for 6 months to achieve positive results.
A STUDY OF ONLINE CUSTOMERS REPURCHASE INTENTION USING THE 4RS OF MARKETING FRAMEWORK

With increased e-commerce competition, people are now resorting to online shopping instead of traditional stores to do personal shopping. With the current pandemic, there is more reason why shoppers would not step out of their homes. It’s therefore imperative for companies engaged in e-commerce to find ways on how to influence its customers to do a repeat purchase with an eye towards the long-term goal of cultivating long term relationships with them. The main purpose of this study was to investigate the impact of variables based on the framework of the 4Rs of marketing towards trust and online customers repurchase intentions. Ninety-seven customers of Lazada website participated with data collection done mainly using online questionnaire. Findings indicated that the variables assurance, corporate image, customer satisfaction, perceived usefulness, and perceived value significantly predicted trust and online customer repurchase intentions. Furthermore, the study revealed that trust can be a significant mediator between the abovementioned variables and online customer repurchase intentions. Lastly, this study has provided a useful insight to help managers understand how to maintain a long-term relationship by enhancing its customers repurchase intentions. Considering the intense competition, long term marketing relationship is the only way to go to survive.
The Proteus effect on security and safety exergamers

ABSTRACT The Proteus effect of exergames has been widely regarded as a factor that influences human performance and learning. Within the context of security and defense exergames, identification with a digital alter-ego affects students’ task performance as well as their emotional states. In the present study, we examined the influence of the perceived masculinity of male avatars on players who were engaged in gamified military exercises (based on competition and command) in a three-dimensional environment. Analysis of data that were obtained from 51 male learners using semi categorized interviews revealed that, during the game, participants with more masculine avatars were more self-confident, engaged with the task, and obtained higher scores than their counterparts with less masculine avatars. Moreover, when they adopted an avatar that they perceived to be more masculine, they reported improved mood, self-confidence, and decisiveness after the completion of the game.
Optimal Time-Consistent Investment and Reinsurance Strategies with Default Risk and Delay under Heston’s SV Model

Considering the influence of past information on the decision-making of insurers, the correlation between the insurance businesses owned by insurers, and the possible default faced by insurers, we investigate the mean-variance investment and reinsurance problem with the default risk, delay, and common shock dependence. We characterize the insurance market by two-dimensional dependent claims, the financial market by the Heston SV model, and default risk by reduced-form approach and then obtain the evolution equation of the insurer’s wealth. Based on the introduction of time delay, the insurer’s wealth dynamics characterized by a stochastic delay differential equation are obtained. Furthermore, applying stochastic control theory within the game-theoretic framework and stochastic control theory with delay, we derive optimal time-consistent investment and reinsurance strategies, as well as equilibrium value function and equilibrium efficient frontier. Finally, we use a numerical example to analyze the influence of parameters on the time-consistent equilibrium strategies and give an economic explanation.
Protective effect of moringa-based beverages against hyperlipidemia and hyperglycemia in type 2 diabetes-induced rats

The objectives of this study were to determine the phenolic profile and potential antioxidant activity of Moringa oleifera leaves (MOL) cultivated in Saudi Arabia and to investigate the protective effect of moringa-based beverages on lipidemic and glycemic parameters in alloxan-induced diabetic rats (DR). The total phenolic content (TPC), chlorophylls, total carotenoids, total flavonoids, total flavonols, ascorbic acid content, and antioxidant activities (AOA) of MOL were determined and HPLC analysis of MOL was quantitatively performed. Moringa beverages as pure moringa (PM) and ginger-flavored moringa (GM) were given to diabetic rats (DR) at a dose of 1 mL 100 g-1 body weight/day for a successive six weeks. Glucose level (GL), lipid profile, and antioxidant parameters including malondialdehyde (MDA), reduced glutathione (GSH), and pancreas histopathological alterations were examined. Results indicated that MOL and prepared moringa-based beverages possess a suppressive amount of phenolics with considerable antioxidant activity in vitro. TPC was 78.72 mg GAE g-1 DW possess AOA as 36.33 μmol TE g-1 DW. Among the eleven identified phenolic acids and six flavonoids in MOL, caffeic acid and catechin were predominant and recorded 151.01 and 736.30 mg/100 g, respectively. Administration of PM or GM beverages significantly decreased GL and significantly improved serum lipid profiles in the DR group. Interestingly, oral administration of PM and GM beverages significantly attenuated the MDA and GSH levels in the DR compared to normal rats. Histopathologically, severe atrophy was noted in the islets of Langerhans in the DR group. However, after six weeks of oral administration of PM beverage, only mild atrophy was recorded in the islets of Langerhans, while with GM beverage, no histopathological alteration in the islets of Langerhans was found. The nutritional and biological evaluation of the moringa-based beverages revealed that both PM and GM beverages exhibit high antioxidant activity, possess antihyperglycemic and antihyperlipidemic effects, and alleviated alloxan-induced pancreatic damage in DR. Moringa could be recommended for diabetes and utilized for its great therapeutic benefits.
Establishing a Multiple-Criteria Decision-Making Model for Stock Investment Decisions Using Data Mining Techniques

This study attempts to integrate the decision tree algorithm with the Apriori algorithm to explore the relationship among financial ratio, corporate governance, and stock returns to establish a stock investment decision model. The sports and leisure related industries are employed as the research target. The data are collected and processed for generating decision tree and association rules. Based on the analysis outcome, an investment decision model is constructed for investors expecting to decrease their investment risks and further increase their profits. This stock investment decision model is one type of multiple-criteria decision-making model. This study makes three critical contributions to investors. (1) It proposes a systematical model of exploring related data through the decision tree algorithm and the Apriori algorithm to reveal the implicit investment knowledge. (2) An effective investment decision model is established and expected to provide a reference basis during stock-picking decisions. (3) The investment decision model is enhanced with implicit rules found among variables using association rules.
Obstructive sleep apnea: A comprehensive review

Obstructive sleep apnea occurs when the patient’s throat muscles intermittently relax and block the airway during sleep, the initial sign of the OSA is snoring or sometimes it may be asymptomatic in the 1st stage of its clinical course. Although, OSA is related to sleep and respiration, but it’s non-surgical as well as surgical management can also be done in dental practice apart from the medical and surgical management, and lifestyle modification. And so, in this article, we are going to study about the obstructive sleep apnea and its management along with its clinical features, classification, complication and also the role of the dentist in OSA. Keywords: Obstructive Sleep Apnea (OSA).
Characterization of Ultralow‐Density Cellular Solids: Lessons from 30 years of Bone Biomechanics Research

Advances in additive manufacturing techniques have enabled the development of microarchitectured materials displaying a combination of low‐density and lightweight structures with high specific strength and toughness. The mechanical performance of microarchitectured materials can be assessed using standard techniques; however, when studying low‐ and ultralow‐density microarchitectured materials, standard characterization techniques can be subject to experimental artifacts. In addition, quantitative assessment and comparisons of microarchitectures with distinct lattice patterns are not always straightforward. Cancellous bone is a natural, ultralow‐density (porosity often exceeding 90%), irregular, cellular solid that has been thoroughly characterized in terms of microarchitecture and mechanical performance over the past 30 years. However, most of the literature on cancellous bone mechanical properties and microstructure–function relationships is in the medical literature and is not immediately accessible to materials designers. Herein, a brief review of state‐of‐the‐art approaches for characterizing the microarchitecture and mechanical performance of ultralow‐density cancellous bone is provided, including methods of addressing experimental artifacts during mechanical characterization of ultralow‐density cellular solids, methods of quantifying microarchitecture, and currently understood structure–function relationships.
Family Firms, Chaebol Affiliations, and Corporate Social Responsibility

This study analyzes the corporate social responsibility (CSR) activities of family-owned firms by investigating public companies in Korea. By nature of their governance structures, which are aligned with the interests of their shareholders and management, family firms are managed from a long-term perspective based on a sense of ownership. While CSR implementation entails investment costs, it ultimately increases firm value by enhancing the firm’s reputation and brand image. As such, family firms are expected to be more active than non-family firms regarding CSR investments. We conducted an empirical analysis based on the Korean Economic Justice Institute Index (KEJI Index) from the Citizens’ Coalition for Economic Justice and found that family firms’ CSR scores were higher than those of non-family firms. This indicates that family firms are relatively more active in their CSR activities, as they are managed from a long-term viewpoint. However, family firms classified as large-scale corporate groups (chaebols) had lower CSR activity levels. This is because when family firms are classified as corporate groups, they can enjoy monopolistic market positioning through their subsidiaries, and are thus more likely to utilize the resources originally required for CSR in other projects that conform to the pursuit of firm interests.
Study of B40 Schoolchildren Lifestyles and Academic Performance using Association Rule Mining

B40 community school children experience many underprivileged lifestyles which impacted their academic performance. Through data trends and patterns, the education top management can observe the progress of academic performance and the lifestyle relationships of students in a school or nearby school. It can also help to identify the causes of progress or deterioration of the performance of B40 community students. Therefore, a data analytics framework is essential to help decision-makers to see and analyze the changing trends and patterns of academic progress in data and related lifestyles of B40 community students more effectively and accurately. The objective of this study is to design and develop association rules analysis to deduce the relevance of academic achievement and lifestyle among schoolchildren from the B40 family. The analysis framework is established in several stages that involve data collection and processing and transformation, then the design, application and evaluate of the association rules algorithms. The framework is expected to benefit students, teachers and Education Ministry. This study foresees whether educational programs and healthy lifestyle awareness can be designed specifically for the B40 children so as to improve their academic achievement as desired by the government.
Implementing land evaluation and site assessment (LESA system) in farmland protection: A case‐study in northeastern China

Farmland evaluation has become a major topic in farmland protection research. Due to the lack of reasonable and scientifically reliable evaluation methods for farmland protection, the farmland of quality and covering a wide area are at high risk of degradation and destruction in China due mainly to rapid industrialization and urbanization. The land evaluation and site assessment (LESA) system has been successfully applied to protect important farmland globally. To better understand and testify the flexibility and suitability of the LESA system for farmland protection in different geomorphic regions in China, we investigated the delineation of basic farmland by applying and testing the LESA system in Liaoning Province of China. In this study, the LESA system was constructed and comprehensively evaluated through the land evaluation (LE) and site assessment (SA) subsystems; soil conditions suitable for agriculture and site conditions feasible for other land uses were selected in the LE and SA subsystems, respectively. The results demonstrated that the ratios of the LE and SA subsystems were 6:4, 5:5, and 4:6 in the middle plain area (MPA), eastern mountainous area (EMA), and western hilly area (WHA), respectively. Farmlands with LE scores over 80 accounted for 80.7%, 34.7%, and 28.6% in the MPA, WHA, and EMA, respectively. Moreover, 37.2% of farmland with high SA scores (over 50) was primarily distributed in the WHA, and only 7.1% and 0.4% in the MPA and EMA, respectively. The farmland ratios with LESA scores over 60 were 74.8%, 52.2%, and 30.2% in the MPA, EMA, and WHA, respectively. In particular, the total farmland was grouped into three primary categories, which scientifically demonstrated the suitability and compatibility of the farmland features and also provided guidance for the implementation of farmland consolidation and remediation techniques.
Application of machine learning to predict visitors’ green behavior in marine protected areas: evidence from Cyprus

Abstract Interpretive marine turtle tours in Cyprus yields an alluring ground to unfold the complex nature of pro-environmental behavior among travelers in nature-based destinations. Framing on Collins (2004) interaction ritual concept and the complexity theory, the current study proposes a configurational model and probes the interactional effect of visitors’ memorable experiences with environmental passion and their demographics to identify the causal recipes leading to travelers’ sustainable behaviors. Data was collected from tourists in the marine protected areas located in Cyprus. Such destinations are highly valuable not only for their function as an economic source for locals but also as a significant habitat for biodiversity preservation. Using fuzzy-set Qualitative Comparative Analysis (fsQCA), this empirical study revealed that three recipes predict the high score level of visitors’ environmentally friendly behavior. Additionally, an adaptive neuro-fuzzy inference system (ANFIS) method was applied to train and test the patterns of visitors’ pro-environmental behavior in a machine learning environment to come up with a model which can best predict the outcome variable. The unprecedented implications on the use of technology to simulate and encourage pro-environmental behaviors in sensitive protected areas are discussed accordingly.
Neural guided visual slam system with Laplacian of Gaussian operator

Simultaneous localization and mapping (SLAM) addresses the problem of constructing the map from noisy sensor data and tracking the robot's path within the built map. After decades of development, a lot of mature systems achieve competent results in feature ‐ based implementations. However, there are still problems when migrating the technology to practical applications. One typical example is the accuracy and robustness of SLAM in environment with illuminance and texture variations. To this end, two modules in the existing systems are improved here namely tracking and camera relocalization. In tracking module, image pyramid is processed with Laplacian of Gaussian (LoG) operator in feature extraction for enhanced edges and details. A majority voting mechanism is proposed to dynamically evaluate and redetermine the zero ‐ mean sum of square difference threshold according to thematching error estimationinpatchsearch. Incamera relocalization module, full convolutional neural network which focuses on certain parts of the input data is utilized in guiding for accurate output predictions. The authors implement the two modules into OpenvSLAM and propose a neural guided visual SLAM system named LoG ‐ SLAM. Experiments on publicly available datasets show that the accuracy and efficiency increase with LoG ‐ SLAM when compared with other feature ‐ based
A Multiple Gradient Descent Design for Multi-Task Learning on Edge Computing: Multi-Objective Machine Learning Approach

Multi-task learning technique is widely utilized in machine learning modeling where commonalities and differences across multiple tasks are exploited. However, multiple conflicting objectives often occur in multi-task learning. Conventionally, a common compromise is to minimize the weighted sum of multiple objectives which may be invalid if the objectives are competing. In this paper, a novel multi-objective machine learning approach is proposed to solve this challenging issue, which reformulates the multi-task learning as multi-objective optimization. To address the issues contributed by existing multi-objective optimization algorithms, a multi-gradient descent algorithm is introduced for the multi-objective machine learning problem by which an innovative gradient-based optimization is leveraged to converge to an optimal solution of the Pareto set. Moreover, the gradient surgery for the multi-gradient descent algorithm is proposed to obtain a stable Pareto optimal solution. As most of the edge computing devices are computational resource-constrained, the proposed method is implemented for optimizing the edge device's memory, computation and communication demands. The proposed method is applied to the multiple license plate recognition problem. The experimental results show that the proposed method outperforms state-of-the-art learning methods and can successfully find solutions that balance multiple objectives of the learning task over different datasets.
Haematological and biochemical changes associated with male rats deprived of feed and water

Overnight food and water restriction protocols are common in animal research, however information about the haematological and biochemical changes due to food and water deprivation over longer periods can provide information about the stress experience by these animals. This study was conducted using ten (n = 10) male albino rats housed in metallic cage. The rats were deprived of feed and water consecutively for six days. On the third and sixth days blood samples were obtained for haematological studies while serum was used for biochemical studies. There were significant increases in red cell counts, packed cell volume, haemoglobin concentration and mean corpuscular volume while significant decreases were observed in the mean corpuscular haemoglobin and mean corpuscular haemoglobin concentration as compared to the basal parameters. The white blood cells, neutrophils, eosinophils, monocytes and lymphocytes were significantly increased as compared with the basal parameters. Activities of aspartate and alanine aminotransferase in post feed and water deprivation condition are elevated compared to basal parameters. There were significant decreases in serum glucose, triglyceride, cholesterol concentrations while the total protein, albumin, creatinine, blood urea were significantly elevated. It can be concluded that rats deprived of feed and water predisposes to starvation, dehydration and stress with perturbation of haematological and biochemical parameters.
On the assignability of LTI systems with arbitrary control structures

ABSTRACT In this paper, the assignability of linear time-invariant (LTI) systems with respect to arbitrary control structures is addressed. It is well established that the closed-loop spectrum of an LTI system with an arbitrary control structure is confined to the set containing the fixed-modes of the system with respect to that control structure. However, the assignment of the closed-loop spectrum is not merely limited by the existence of fixed-modes in practical scenarios. The pole assignment may require excessive control effort or even become infeasible due to the presence of small perturbations in the system dynamics. To offer more insights in such more realistic scenarios, a continuous measure known as fixed-mode radius is developed. However, its evaluation is confronted with a highly non-convex optimization problem combined with the need for a combinatorial search. This study utilises properties of positive-definite cones and duality theory to formulate the assignability assessment as an optimization problem with linear matrix inequality (LMI) constraints. Based on the suggested formulation, three alternative methods are proposed to evaluate the distance to unassignability. The first two methods offer alternative non-iterative and convex programs. The third method proposes an iterative convex optimization while updating the binary variables based on the dual variables. All the proposed methods rely on convex optimization, do not involve gridding over the complex plane and circumvent the combinatorial nature of the problem by using properties of positive definite cones. Simulation results confirm the effectiveness of the proposed methods in the assessment of fixed-mode radius with respect to arbitrary control structures.