Miracle-dz/UniFAR-FTUs huggingface dataset:
Purposeful physical activity-Basic strategy for the prophylaxis and treatment of diabetes and diabetic polyneuropathy.

Diabetes mellitus type 2 is a socially significant disease due to its high incidence rate on a global scale. The causes are rooted mainly in the changes in eating habits, the sedentary way of life, the low energy expenditure leading to obesity, the ageing population, as well as urbanization. Diabetes mellitus type 2 is a chronic, lifelong condition that requires continuous complex health care and the motivated involvement of a well-trained patient in order for the risk of long-term complications to be reduced. The first step in the treatment entails a change in the way of life. The most significant preconditions in the strategy for prophylaxis and treatment of diabetes mellitus type 2 and the long-term complications include systematic medicamentous therapy in combination with a good control of the condition, physical rehabilitation and physiotherapy with an active exercise routine, strict control of the body weight and healthy eating habits through a balanced diet, as well as limiting any bad habits for the purpose of optimizing the patient’s way of life. The aim of the primary and secondary physiotherapeutic prophylaxis is the strengthening of the organism achieved through adequate physical exercise, sports, heliotherapy and air procedures, aquatic therapy and balneotherapy. The medical and social impact of diabetic polyneuropathy and the effect of exercise on the condition call for basic physical rehabilitation routine designed to improve the quality of life of patients with diabetes mellitus.
Autoimmune Thyroid Disease and Differentiated Thyroid Carcinoma: A Review of the Mechanisms That Explain an Intriguing and Exciting Relationship

Autoimmune thyroid disease is a complex and highly frequent disease, where a wide variety of genetic, epigenetic and environmental factors (among others) come together and interact, and is characterized by the presence of two clinical outcomes: hypothyroidism (in Hashimoto’s thyroiditis) and hyperthyroidism (in Graves-Basedow disease). For its part, differentiated thyroid carcinoma (mainly papillary carcinoma) is the most common type of cancer affecting the thyroid (and one of the most prevalent worldwide). An important co-occurrence between autoimmune thyroid disease and differentiated thyroid carcinoma has been documented. In this article, studies that have evaluated possible associations and relationships between autoimmune thyroid disease and differentiated thyroid cancer are systematically described and summarized. To date, the underlying mechanism that explains this association is inflammation; however, the characteristics and designs of the studies evaluated do not yet allow a causal relationship between the two entities to be established. These aspects have made it difficult to establish “causality” in the continuum of the pathogenesis between both conditions.
The Effect of Gender Mixed Groups and Collaborative Interaction on Learners’ Achievements in Reading Comprehension

Several studies have examined the impact of both gender mixed groups and collaborative learning on the process of language learning. Some studies found that females were better than males whereas others showed that males were better than females. As for collaborative learning, most studies have shown that this type of learning improves and accelerates the process of learning. The present study intended to investigate (1) the effect of gender mixed groups on learners’ interaction in reading comprehension, and (2) the influence of collaborative learning activities on learners' achievements. In order to achieve these goals, 45 male and female high school students from Benghazi, Libya were divided into three groups. Each group included 15 students. One group (GIRLS GROUP) contained only girls; the second group (BOYS GROUP) included only boys whereas the third group (MIXED GROUP) was a mixture of both girls and boys. They were all taught by the same instructor in order to emphasize equality of teaching. The treatment lasted for five weeks, two hours a day, three days a week. Instructional tasks based on collaborative learning techniques and activities were provided to the students. A pre-test and post-test design was utilized in this study. Regarding the effectiveness of gender mixed groups on reading comprehension , the results revealed that Group (GIRLS GROUP) achieved the best results. For the influence of collaborative learning techniques, the findings showed remarkable development in the students’ achievements when using collaborative learning.
Application of Internet-Based Language Learning in Teaching English Classes at Faculty of Languages at the University of Benghazi in Post-Pandemic Coronavirus

This paper handles the application of Internet-Based Language Learning (IBLL) in teaching English classes at Faculty of Languages at the University of Benghazi, Libya. Teaching English at Libyan universities in general is based on teacher-centered lecturing, in which students sit passively take whatever provided to them from their instructors. This traditional strategy of teaching had encountered challenges due to closure of the university because of the pandemic of Coronavirus by the beginning of 2020, which required shifting to virtual online teaching. The researcher of this paper has conducted this paper to investigate about this new experience of learning and teaching at the Faculty of Languages at the University of Benghazi. The researcher uses qualitative research method, in which he uses literature review as secondary resources and interviewing a sample of students from Faculty of Languages at the University of Benghazi as primary resources. Findings of the study reveal that students and teacher encounter challenging in applying IBLL, the biggest challenges are represented in weakness of the Internet and black out of the power. The researcher presents recommendations based on the findings obtained.
Changes in Intestinal Flora and Serum Metabolites Pre- and Post-Antitumor Drug Therapy in Patients with Non-Small Cell Lung Cancer

Objective: this study aimed to identify the relationships between gut microbiota, metabolism, and non-small cell lung cancer (NSCLC) treatment outcomes, which are presently unclear. Methods: in this single-center prospective cohort study, we investigated changes in the gut microbiota and serum metabolite profile in 60 patients with NSCLC after four cycles of anticancer therapy. Results: The microbial landscape of the gut exhibited a surge in Proteobacteria and Verrucomicrobiota populations, alongside a decline in Firmicutes, Actinobacteriota, and Bacteroidota. Furthermore, a significant shift in the prevalence of certain bacterial genera was noted, with an increase in Escherichia/Shigella and Klebsiella, contrasted by a reduction in Bifidobacterium. Metabolomic analysis uncovered significant changes in lipid abundances, with certain metabolic pathways markedly altered post-treatment. Correlation assessments identified strong links between certain gut microbial genera and serum metabolite concentrations. Despite these findings, a subgroup analysis delineating patient responses to therapy revealed no significant shifts in the gut microbiome’s composition after four cycles of treatment. Conclusions: This study emphasizes the critical role of gut microbiota changes in NSCLC patients during anticancer treatment. These insights pave the way for managing treatment complications and inform future research to improve patient care by understanding and addressing these microbiota changes.
Development of deep reinforcement learning for maximum power point tracking of photovoltaic systems

The use of renewable energy systems, specifically photovoltaic (PV) systems (PVs) that convert solar energy into electricity, has become a popular solution to address global environmental concerns by reducing the utilization of non-renewable energy sources, which contribute to pollution. Efforts to increase the power transfer effectiveness of PV systems include the advancement of controllers for maximizing power point tracking (MPPT). These controllers guarantee optimal system operation at the maximum power point (MPP) in diverse environmental conditions. The paper proposes an improved deep reinforcement learning (DRL) method, namely deep deterministic policy gradient (DDPG), to capture the MPP in PV systems, particularly when dealing with partial shading conditions (PSCs). Unlike reinforcement learning methods that only work with discrete state and action spaces, the proposed DDPG method can handle continuous action state spaces. Feasibility analysis is conducted using MATLAB/Simulink simulations, and the findings demonstrate the efficiency and superior performance of the suggested solutions, highlighting their potential for future use.
The Effect of Information Quality, System Quality and Organizational Capability on the Implementation of HMIS at Regional public hospital Pambalah Batung, Hulu Sungai Utara Regency

The Hospital Management Information System (HMIS) is an integral part of overall hospital services and has even become one of the main joints in daily activities. Evaluation of HMIS implementation is carried out because it will assess the benefits derived from HMIS implementation and find potential problems faced by users and organizations. The results of this evaluation can be used as a reference for improving or perfecting the HMIS and minimizing the potential for existing problems, so that HMIS becomes better, perfect and can support the vision, mission and goals of the organization. The find out the quality of information, system quality and organizational capabilities in implementing HMIS at Pambalah Batung Hospital. This research is an associative research with a quantitative paradigm. The sample in this research is 150 respondents. The data analysis technique used a simple and multiple linear regression analysis test. There is an influence between information quality (p=0.000), system quality (p=0.000) and organizational capability (p=0.000) on HMIS implementation. Information quality, system quality and organizational capability simultaneously influence HMIS implementation (p=0.000). Information quality is the most dominant in HMIS implementation with a constant value (b = 0.387) (4.680). There is influence between information quality, system quality and organizational capability partially and simultaneously on HMIS implementation. Information quality has a dominant significant effect on HMIS implementation at Pambalah Batung Hospital. Pambalah Batung Amuntai Hospital, Hulu Sungai Utara Regency, further improves the information system for HMIS employees and must pay more attention to information systems by always improving good information systems and also providing information to Pambalah Batung Hospital.
Modeling of Rainfall-Runoff Correlations Using Artificial Neural Network-A Case Study of Dharoi Watershed of a Sabarmati River Basin, India

The use of an Artificial Neural Network (ANN) is becoming common due to its ability to analyse complex nonlinear events. An ANN has a flexible, convenient and easy mathematical structure to identify the nonlinear relationships between input and output data sets. This capability could efficiently be employed for the different hydrological models such as rainfall-runoff models, which are inherently nonlinear in nature. Artificial Neural Networks (ANN) can be used in cases where the available data is limited. The present work involves the development of an ANN model using Feed-Forward Back Propagation algorithm for establishing monthly and annual rainfall runoff correlations. The hydrologic variables used were monthly and annual rainfall and runoff for monthly and annual time period of monsoon season. The ANN model developed in this study is applied to Dharoi reservoir watersheds of Sabarmati river basin of India. The hydrologic data were available for twenty-nine years at Dharoi station at Dharoi dam project. The model results yielding into the least error is recommended for simulating the rainfall-runoff characteristics of the watersheds. The obtained results can help the water resource managers to operate the reservoir properly in the case of extreme events such as flooding and drought.
Exploring the employees’ behavioral intention towards disruptive technologies: A study in Malaysia

The study focuses on the employees’ behavioral intentions towards the usage of disruptive technology in the industry. The digital technology application in consumer, retail, and hospitality, education and training, financial services, the health sector, infrastructure, government, and airports. The study objectives were to explore the possible adoption of innovation and creativity changes and their acceptance by the employees in the organization. To identify the variables impacting behavioral intention and analyze how these variables relate to perceived usefulness, attitude, perceived ease of use, facilitating conditions, and technology optimism. A structured questionnaire was used to collect data from 335 respondents, who were selected based on their relevance to the study objectives. The questionnaires were distributed through the Google Forms application, and the data were collected and analyzed periodically. The findings of the study provide valuable insights into the behavioral intention towards disruptive technologies in Kuala Lumpur and Putrajaya locations in Malaysia and highlight the significance of factors such as perceived usefulness, attitude, perceived ease of use, facilitating conditions, and technology optimism. The research contributes to the existing body of knowledge on Industry 4.0 by providing empirical evidence and practical implications for organizations seeking to leverage disruptive technologies in their operations management.
Aeromonas, un microorganismo ambiental de importancia en salud humana y animal

L'objectiu general va ser determinar la prevalenca de Aeromonas spp en les 1365 soques identificades, 543 provenien d’aigua, 416 de mostres cliniques humanes i 203 procedents de peixos (carpes i truites), hortalisses i mariscs. S’investiga la seva presencia en agua regenerada procedent d’un tractament terciari per llacunatge i per llum UV i clor (UV + Cl). aquesta ultima utilitzades per el re d’hortalisses. El llacunatge nomes va reduir en un 82% la concentracio de Aeromonas que s’eliminaren totalment despres del tractament UV + Cl. No obstant aixo, es va observar recreixement en aquesta l'aigua emmagatzemada utilitzada per al reg. La mateixa soca de A. caviae s’ailla en l'aigua de rec i en l'enciam regat amb aquesta aigua, i el mateix va passa amb una soca de A. saranelli trobada en el julivert i en els tomaquet. Es fa pales per tant que l'aigua regenerada utilitzada per al rec es la fon de dispersio d’ especies patogenes de Aeromonas. L'especie A. schubertii va ser recuperada per primer cop de musclos i l'especie A. dhakensis del d'un dofi mort per una pneumonia. La identificacio dels aillats clinics en el MALDI-TOF va mostrar menys d'un 10% d'identificacions erronies. Aixo es degut a que la base de dades esta poc actualitzada e inclou, a mes, soques erroniament etiquetades. Les soques cliniques corresponien a 9 especies A. caviae (61,6%), A. veronii (21,6%), A. hydrophila (6,4%), A. media (4,5%) i A. dhakensis (1,2%), seguides de A. allosaccharophila, A. salmonicida i A. bestiarum (amb una incidencia de 0,5% o inferior) i a 2 noves especies recuperades de femta humana. A mes, es van descobrir 5 noves especies, 4 a partir d'aigua de llac i una a partir de mol•luscs bivalves.
Radiofrequency absorption of coated ellipsoidal gold nanoparticles in human tissue

Electromagnetic radiofrequency heating of gold nanoparticles for use in remote hyperthermia cancer treatment has seen rapidly growing interest in the last decade. While most of the focus has been on studying spherical nanoparticles, recent research suggests that using ellipsoidal particles can significantly increase the Joule heating. However, it is still unclear how the presence of ligands affects the electromagnetic absorption in this context. In the present paper, we study the effects of adding a surface coating to ellipsoidal gold nanoparticles, and investigate the change in absorption with respect to coating properties, particle aspect-ratio, and frequency. Both the case of a single nanoparticle and the case of a suspension of nanoparticles are studied. The introduction of a dielectric coating increases the absorption rate for particles with lower aspect ratios and at lower frequencies, potentially improving the flexibility of parameter configurations that can be used in treatment. A thermal analysis reveals that the absorption in the parameter space of lower aspect ratios translate to negligible differential temperature increase, even with the addition of coating. Furthermore, nanoparticles with very large aspect ratios (nanowires) generate less heat with coating compared to no coating. Thus, it is shown that the presence of coating and choice of aspect ratio, have significant impact on the absorption response and must be accounted for in the analysis of ligand-capped nanoparticles. The findings in the present paper provide a valuable tool to optimize the coated gold nanoparticle design parameters, in order to secure clinically useful differential heating.
Monitoring Genomic Structural Rearrangements Resulting from Gene Editing

The cytogenomics-based methodology of directional genomic hybridization (dGH) enables the detection and quantification of a more comprehensive spectrum of genomic structural variants than any other approach currently available, and importantly, does so on a single-cell basis. Thus, dGH is well-suited for testing and/or validating new advancements in CRISPR-Cas9 gene editing systems. In addition to aberrations detected by traditional cytogenetic approaches, the strand specificity of dGH facilitates detection of otherwise cryptic intra-chromosomal rearrangements, specifically small inversions. As such, dGH represents a powerful, high-resolution approach for the quantitative monitoring of potentially detrimental genomic structural rearrangements resulting from exposure to agents that induce DNA double-strand breaks (DSBs), including restriction endonucleases and ionizing radiations. For intentional genome editing strategies, it is critical that any undesired effects of DSBs induced either by the editing system itself or by mis-repair with other endogenous DSBs are recognized and minimized. In this paper, we discuss the application of dGH for assessing gene editing-associated structural variants and the potential heterogeneity of such rearrangements among cells within an edited population, highlighting its relevance to personalized medicine strategies.
The Comparison of Patient Characteristics, Therapy Outcome, and Sexual Functions in Vaginismus Patients Prior to and During the COVID-19 Pandemic

Background The objective of this study conducted at one center is to compare the demographic features and female sexual functions of patients treated for vaginismus before the COVID-19 pandemic to those treated for vaginismus during the pandemic. Aim Additionally, the study intends to evaluate the results of vaginismus therapy and assess the post-treatment sexual functioning of women. Methods A retrospective analysis was conducted on the medical records of patients diagnosed with vaginismus who sought treatment between March 2018 and March 2022. The enrolled patients were categorized into two groups: the pre-COVID-19 group and the COVID-19 group. The following data have been collected: age, education level, occupation, and marriage duration. After three months of treatment, the patients were called for a follow-up examination and evaluation of their sexual functions. Outcomes Compared to the pre-COVID-19 group, an increase of 52.51% was observed in the number of patients admitted for treatment in the COVID-19 group. Results The severity of vaginismus in the patients was similar in both groups. There were no statistically significant changes observed in any of the areas of the Female Sexual Function Index (FSFI) scale. Clinical implications According to our findings, there was no significant difference in female sexual functioning between women who had vaginismus treatment during the pandemic and those who underwent pre-pandemic treatment. Strengths and limitations The research sample comprised women who sought medical care at our women's health clinic. Conclusions We believe that vaginismus patients who had previously avoided seeking treatment are now seeking it during the pandemic.
Effect of Fracture Dip on Petrophysical Evaluation of Naturally Fractured Reservoirs

Recent models show the means of estimating the petrophysical porosity exponent (m) of a reservoir when it is composed of different combinations of matrix, fractures and vugs. For both dual and triple porosity reservoirs, the system is modelled as a parallel resistance network (for matrix and fractures), a series resistance network (for matrix and non-connected vugs) or a combination of parallel/series resistance networks (for matrix, fractures and non-connected vugs). In the case of matrix/fractures, it has been assumed that the flow of the current is parallel to the fractures. This paper shows the effect on m of current flow that is not parallel to the fractures. This type of anisotropy is co-relatable with fracture dip. Maxwell Garnett mixing formula for calculating ef- fective permittivity of a system with aligned ellipsoids and depolarization factors of 0 and 1 leads to the parallel and series resistance networks used in the paper. It is concluded that the change in fracture dip can have a significant effect on the value of m. Not taking this into account can lead, in some cases, to significant errors. The effect of the change of fracture dip on water saturation calculations is illustrated using two examples.
Automatic Pseudo-LiDAR Annotation: Generation of Training Data for 3D Object Detection Networks

Object detection in 3D is a key ingredient of various autonomous systems. Many 3D object detection methods rely on LiDAR, as it is robust to illumination conditions and provides accurate distance measurements. To apply LiDAR-based 3D object detection networks for new objects, we need new training datasets. However, because labeling target objects with 3D bounding boxes in LiDAR point clouds requires significant resources and open datasets contain annotations of only car-related classes, it is challenging to deploy LiDAR-based 3D object detectors for detecting objects not related to cars. We propose a system that automatically generates annotated pseudo-LiDAR (APL) data, which requires only stereo images to synthesize 3D bounding box annotations and pseudo-LiDAR points. Using the proposed method, we can dramatically reduce efforts and time for generating a LiDAR-based 3D object detection dataset. By utilizing classes in 2D image datasets, the proposed framework can annotate diverse objects beyond limited classes of existing LiDAR-based 3D object detection datasets. To verify the capability of the synthesized training data, we train 3D object detection networks with the APL data of new classes. The experiments show that the 3D object detection networks trained on the APL data can detect objects of the new classes in LiDAR point clouds, which demonstrates that the proposed method can help LiDAR-based 3D object detectors operate for various objects not covered in existing LiDAR-based 3D object detection datasets.