Miracle-dz/UniFAR-FTUs huggingface dataset:
Potential implications of blood flow restriction exercise on patients with chronic kidney disease: a brief review

Combining blood flow restriction (BFR) with exercise is considered a relevant, helpful method in load-compromised individuals and a viable replacement for traditional heavy-load strength training. BFR exercise may be particularly useful for those unable to withstand high mechanical stresses on joints resulting in skeletal muscle dysfunction, such as patients with chronic kidney disease (CKD). Current literature suggests that BFR training displays similar positive health benefits to exercise training alone for CKD patients, including maintenance of muscle strength, glomerular filtration rate maintenance, uremic parameters, inflammatory profile, redox status, glucose homeostasis, blood pressure adjustments, and low adverse reports. In this review of nine studies in CKD patients, we clarify the potential safety and health effects of exercise training with BFR compared to exercise training alone and recommend insights for future research and practical use. Furthermore, we introduce relevant gaps in this emerging field, providing substantial guidance, critical discussion, and valuable preliminary conclusions in this demographic of patients. However, based on the limited studies in this area, more research is necessary to determine the optimal BFR exercise programming.
A study in analysing the role of labour enactment towards employment protection and labour productivity

The current business environment is highly challenging and top management are looking for enhancing the productivity and output to achieve sustainable growth and development. The application of labour enactment is being explored extensively by government, regulators, management and employees so as to support the individuals to possess better employment protection, working condition and support in realising performance and efficiency. The changes in the labour enactment are focused in supporting the employees to possess better job security, enhance working environment conditions, salary and wages, supportive management and other related aspects so that they can enhance their performance and wellbeing. This study is poised to analyse the role of labour enactment towards employment protection and labour productivity. The study intends to support the existing research on the aspect that the enactment tend to support the employees to perform better in their work-related area, it also enables the management to implement clear and collaborative policies so as to achieve the growth and development of the organisation.
Induction of Accelerated Aging in a Mouse Model

With the global increase of the elderly population, the improvement of the treatment for various aging-related diseases and the extension of a healthy lifespan have become some of the most important current medical issues. In order to understand the developmental mechanisms of aging and aging-related disorders, animal models are essential to conduct relevant studies. Among them, mice have become one of the most prevalently used model animals for aging-related studies due to their high similarity to humans in terms of genetic background and physiological structure, as well as their short lifespan and ease of reproduction. This review will discuss some of the common and emerging mouse models of accelerated aging and related chronic diseases in recent years, with the aim of serving as a reference for future application in fundamental and translational research.
The Role of Neutrophil Lymphocyte Ratio in Predicting Acute Appendicitis in Adult

Introduction: Acute appendicitis is one of the most common causes of acute abdomen with lifetime occurrence of approximately 7% and with perforation of 17-20%. There are various scoring systems and investigations which are used to ruling in the conditions but none of these are 100% accurate. The aim of this study was to observe relationship between neutrophil lymphocyte ratio (NLR) and simple and complicated acute appendicitis. Methods: This is a prospective observational study conducted for a period of 12 months. Clinical, laboratory and USG parameters were used to diagnose acute. HPE findings were taken as final diagnosis and the objective of the study compared. Results: Total of 100 patients were evaluated in this study. The mean age of the patients with acute appendicitis in this study was 30 years . The mean Alvarado score in this study was 7 and the mean NLR was 6.6. In this study, 24% of case who had TLC of more than 10000 per cubic millimeter had complicated appendicitis (p=0.685). 16% of total cases had complicated acute appendicitis with neutrophil percentage between 81%-90%, 20% with NLR >8 had complicated acute appendicitis and 20% with NLR >8 had HPE proven complicated acute appendicitis (p=0.001) Conclusion: Both neutrophil percentage and NLR were statistically significant in differentiating complicated acute appendicitis from simple acute appendicitis than total leucocyte count alone as shown by study.
The Nursing Professional Development Practice Model

In the nursing professional development (NPD) specialty, the NPD practice model visually represents the NPD scope of practice and reflects a growing, vibrant specialty. It delineates the who, what, when, why, where, and how of the specialty practice and is approved by the American Nurses Association. This column reflects upon the evolution of the NPD practice model and delineates its updates in the fourth edition of the Nursing Professional Development: Scope and Standards of Practice.
Validity Analysis Based on Multidimensional Pattern Analysis and Machine Learning Theory in Educational Teaching Assessment

Prediction and evaluation methods have important and extensive applications in college education and teaching. These methods are usually realized by intelligent learning machine based on training method. In this case, a very important question is worth analyzing: are all these methods effective? Therefore, this paper converts the original score into standard score through normal distribution, explains the application of standard score, provides a practical standard score processing method for examination subjects with a full score of 150, and establishes a basic model for comparing the overall score or the overall average score by using standard score when combining the scores of different subjects (including examination), so as to determine the individual score in a group, or deeply analyze the basic model and weighting model to determine the relative position of individual scores in a group or population, and evaluate the effectiveness of various methods. Finally, make a general assertion on the effectiveness of prediction and evaluation using intelligent learning machine. In fact, there are many factors that affect the effectiveness of education and teaching and human ability. There are differences between the data of education and teaching effectiveness and human ability. The distribution of these data is generally more in the middle, less in too large and too small.
Evaluation of demographic characteristics and comorbidities in patients with surgical site infection after gynecological surgeries, 2016-2020

Background: Surgical site infection (SSI) is one of most common infections in the hospital and complications in patients admitted to the surgical ward or outpatient surgery, which increases the duration of treatment, delays wound healing, increases the use of antibiotics, causes unnecessary pain and in severe cases death and imposes a lot of costs on the health care system. The aim of this study was to determine the demographic characteristics and comorbidities in patients with SSI.Methods: The study population included 92 patients who referred to Alavi hospital in Ardabil for gynecological surgeries from June 2016 to the end of April 2020. Their complete hospital records were extracted through the hospital archive system and carefully studied. A special checklist was filled out for each patient. The information in the checklist included age, occupation, place of residence, marriage, education, type of surgery performed, presence or absence of underlying disease, cancer, smoking and alcohol consumption and presence or absence of a history of abdominal and pelvic surgery. All data analyzed by statistical methods in SPSS.Results: Most of patients with SSI were between 30 to 40, rural, married and housewives. Of all patients, 22.8% had diabetes and 13% had hypertension. The type of surgery was caesarean section in 85.9%, laparatomy 8.7% and cystectomy/aforectomy in 5.4% and 18.5% of patients had a history of previous surgery.Conclusions: Due to the high rate of comorbidities and predisposing factors in patients with SSI, control of these factors can play an important role in preventing infection.
A Crop Leaf Disease Image Recognition Method Based on Bilinear Residual Networks

Deep learning models are widely used in crop leaf disease image recognition. These models can be divided into two categories: global model and local model. The global model directly takes the whole leaf disease images as input to training and recognition. It can achieve end-to-end training and recognition, which is very convenient to use. But this kind of model cannot very accurately and completely extract the features from the very small diseased spots in the image. Before training and recognizing, the local model needs to extract the diseased spots part from the image by image segmentation technology. Then the local model takes the disease spots part images as input to training and recognition. Features extracted by local model are more accurate and complete. But this kind of model cannot achieve end-to-end training and recognition, and the image segmentation will bring additional overhead. Considering the disadvantage of global model and local model, we proposed a crop leaf disease image recognition method based on bilinear residual networks (named DIR-BiRN). DIR-BiRN extracts features by two residual networks feature extractors and then integrates the features by a bilinear pooling function. By this way, it can extract features more accurately and completely while achieving end-to-end training and recognition. Experiments on the PlantVillage dataset show that, when compared with the standard ResNet-18 model, the DIR-BiRN improves on accuracy performance, recall performance, precision performance, and F1-measure performance by averages of 0.2918, 0.81641, 0.59185, and 0.52151 percentage points, respectively.
Neural networks for the Recognition of X-ray Images of Ailments for Covid-19

This investigation analyzes the current state of neural networks, considers the available types, optimizers used for training, describes their benefits and disadvantages. The task of computer vision is defined and the answer to the question why the use of neural networks is an important task today is given. The powerful neural network from Google was proposed as an example and its algorithm is described in detail. Studies have shown how to configure models to get high performance.
Inverse Scattering Transform for the Generalized Derivative Nonlinear Schrödinger Equation via Matrix Riemann–Hilbert Problem

The inverse scattering transformation for a generalized derivative nonlinear Schrödinger (GDNLS) equation is studied via the Riemann–Hilbert approach. In the direct scattering process, we perform the spectral analysis of the Lax pair associated with a 2 × 2 matrix spectral problem for the GDNLS equation. Then, the corresponding Riemann–Hilbert problem is constructed. In the inverse scattering process, we obtain an N-soliton solution formula for the GDNLS equation by solving the Riemann–Hilbert problem with the reflection-less case. In addition, we express the N-soliton solution of the GDNLS equation as determinant expression.
Estimation of Jensen’s gap through an integral identity with applications to divergences

: Jensen’s inequality and results related to its gap play a crucial role in the literature of applied mathematics. In this paper, we introduce a new, simple and sharp bound for Jensen’s gap in discrete form by using an integral identity in terms of a certain function. We demonstrate this bound in integral form as well. Also, we illustrate some numerical examples which exhibit the tightness of the bound. The examples show that the bound is better than the existing bound given in a previously obtained result. Furthermore, we derive a new bound for the gap of Hermite-Hadamard inequality and derive two new variants of the H¨older inequality using the main results. At the end, we obtain some new inequalities for various divergences by using the main result. etc. It is used in identiﬁcation of the problems which arise in the modeling of some physical phenomenon. Researchers have obtained many results associated to the gap of Jensen’s inequality. We have also determined a new simple and sharp bound for its gap. We have discussed some numerical examples and then made a comparison with an existing bound [8] in the literature, which veriﬁes the sharpness of our new bound. By utilizing our new results, we have also suggested two new variants of the H¨older inequality and a new estimate for the gap of Hermite-Hadamard inequality. Moreover, we have given some inequalities for various divergences and for Shannon entropy, which are some applications of the main results. The work suggested in this article may motivate the researchers to extend this idea to some other inequalities.
Oral Spray – A Review on Promising Drug Delivery System for Oral Cavity

Aim: This review aims to compile information related to marketed oral spray preparation along with their formulation and clinical application. Objective: The main objective of this overview is to study the marketed oral spray dosage form for treatment of different diseases and learn about its advantages over the other oral dosage forms e.g. tablet, capsule, patches etc. Description: Oral spray with Mucoadhesive polymers forms small droplets that quickly adheres to the mucosal surface and let the drug permeate into the blood circulation easily. The oral mucosa has shown promising results for the systemic absorption of many drugs owing to the highly permeable nature of the mucosal membrane. Oral sprays are very fast, the most effective and easy way to get daily dose vitamins, minerals, and other nutrients ingredients. Due to this advantage oral sprays have emerged as an effective alternative for bypassing extensive first pass effect. Conclusion: It has been a very well known fact that the oral route of administration is the most popular route of drug administration. However the drwabacks like extensive first pass metabolism and drug degradation in stomach makes this route not suitable for all drugs and thus an alternative oral drug delivery systems are necessary to explaoint benefits of oral route. Many researchers are working to develop oral spray formulations for drugs which need quick permeation followed by quick onset of action and also provide an effective alternative of conventional oral drug delivery systems.
Investigating the Effective Factors on Web Browsing of Human Resources in Sport Organizations (Case Study: Ministry of Sport and Youth)

: The purpose of this study was to investigate the effective factors on web browsing (Cyberloafing) of human resources in sport organizations. The research method was descriptive-correlational and based on structural equations and also the data were collected by questionnaire. The statistical population of the study consisted of all employees of the Ministry of Sport and Youth, among whom, 237 were randomly selected as sample and finally 225 (93.74%) questionnaires were analyzed. A 14-question questionnaire was used to collect the data. Finally, the collected data were analyzed in two parts: descriptive and inferential statistics using SPSS and LISREL software. The results showed that the predictive power of this model based on the sum of variance of the three factors was 61.52%. Also, there is a significant priority among the cyberloafing components, according to which the attitude of employees is in the first priority, descriptive norms in the second priority and perceived barriers in the third priority. Considering the way employees use the internet and web browsing, the need for more in-depth research and attention to these types of HR behaviors become more apparent.
Secondary bone grafting for alveolar clefts: surgical timing, graft materials, and evaluation methods

Alveolar cleft belongs to the spectrum of cleft lip and/or palate, affecting 75% of cleft lip/palate patients. The goals of alveolar cleft treatment are stabilizing the maxillary arch, separating the nasal and oral cavities, and providing bony support for both erupting teeth and the nasal base via the piriform aperture. Secondary alveolar bone grafting is a well-established treatment option for alveolar cleft. Secondary alveolar bone grafting is performed during the period of mixed dentition using autologous bone from various donor sites. There are several issues relevant to maximizing the success of secondary alveolar bone grafting, including the surgical timing, graft material, and surgical technique. In this study, we reviewed issues related to surgical timing, graft materials, and evaluation methods in secondary alveolar bone grafting.
Reflective Reading Strategy Training through Google Classroom: A Way for Enhancing EFL Student Teachers' Analytic Writing and Reading Self-Regulation

This study was conducted to determine the effect of reflective reading strategy training through Google classroom, on EFL student teachers' analytic writing and reading self-regulation. 40 EFL student teachers at the Faculty of Education, Fayoum University, participated in the study. They were randomly assigned into two groups, one treatment group (20 students) and one control group (20 students). The treatment group was exposed to the reflective reading strategy training introduced through Google classroom, while the control group was taught the regular reading course using traditional methods. The training program lasted for eight weeks, during this period the treatment group studied a group of reflective reading strategies and tasks introduced through Google classroom tools. Data were collected through an analytic writing test and a reading self-regulation scale. Scores obtained from the pre and post administration of the study tools were statistically analyzed using SPSS program (version 21). The statistical difference between the treatment and non-treatment groups was calculated using the independent samples t-test. The results of the study showed that the treatment group outperformed the control group in the post administration of the analytic writing test and the reading self-regulation scale. This proved the effectiveness of the reflective reading strategy training through Google classroom in developing the study sample's performance in the targeted skills. In light of the study results, some recommendations and suggestions for further research were given. of the interventions given. Results revealed that high-level thinking abilities developed as a result of the implementation of the interventions given including reflective reading.
A Framework for Identification and Classification of IoT Devices for Security Analysis in Heterogeneous Network

Internet of Things (IoT) is a promising technology enabling physical devices like cameras, home appliances, and other devices to communicate and interoperate with each other. The next wave transforms our homes, society, enterprises, and cities with the massive presence of IoT devices. The devices in the Internet of Things (IoT) may exchange sensitive data, and an important issue for any organization is to get the data secured and protected. The preliminary requirement for this is a mechanism detecting and reporting anomalies automatically to some central controller. Therefore, this mechanism should be able to classify legit IoT devices from unauthorized ones. Malicious IoT devices, non-IoT devices, and other types of man-in-the-middle traffic sources must be quarantined for noncompliance. This helps formulate administrative policies and regulate/police traffic in the network for better QoS management. This work proposed a framework-based hierarchical deep neural network (HDNNs) to distinguish IoT devices from non-IoT devices using a feature set of IoT-specific traffic. A system has been designed based on HDNN that classifies IoT devices to their specific categories and identifies new entrants with reasonable accuracy. The results show that HDNN can distinguish IoT and non-IoT devices with higher accuracy and as well as classify IoT devices into the respective classes with the required accuracy.
Assessment of proprioception improvement after anterior cruciate ligament reconstruction with tibial remnant preservation versus non remnant preservation

Background: The ACL functions both as an anterior stabilizer and as a sensory organ. It is not only provides proprioceptive function, but also initiates protective and stabilizing muscular reflexes. Most ACLs are ruptured in the proximal half and most mechanoreceptors have been reported to be located in the sub-synovial layer near the tibial insertion of the ACL. Therefore, it is reasonable to preserve the remnant tissue. Particularly the tibial side, as a source of reinnervation if impingement and Cyclops can prevented. Objective: To compare proprioception after ACL reconstruction with remnant preservation versus non remnant preservation. Methods: This is a prospective single blind controlled randomized study was done from December 2015 to October 2017, it was conducted on forty patients (40 males). Divided into two groups twenty patients in each one to assess proprioception after anterior cruciate ligament reconstruction. Group (A) consisted of 20 patients with mean age 28±5.57 years who underwent to ACLR with tibial remnant preservation. Group (B) consisted of 20 patients with mean age 29.05±5.596 years who underwent to ACLR with non-remnant preservation were selected on the basis of clinical picture and imaging findings.
THE AMERICAN CONTINENT HYDROPOWER DEVELOPMENT AND THE SUSTAINABILITY: A REVIEW

The present review compares and takes the main ideas around hydropower development in eight countries of the American continent, identifying its advantages and disadvantages, showing a vision concerning sustainability. It is conclusive that there are impacts for each megawatt produced with hydropower, and the generation structure that uses the water resource of natural currents is not highly clean. Moreover, there is the mistaken criterion for developing a renewable hydropower project related to sustainability, a wrong approach, as demonstrated with the review. The examination in the eight countries of America some analyzes and the most concludes that, before considering a construction with thousands of dollars of investment and water contained in dams, the social and environmental analysis must respond to the restrictions on building new hydropower projects, promoting other unconventional renewable energy sources development. It is recommended to determine an objective quantitative approach of hydropower combining hydrology, energy efficiency, and interaction scenarios of future climate change to know the best energy grids diversifying balanced renewable and no renewable sources for each country.