bluuebunny/crossref_metadata_2025 huggingface dataset:
Meat Performance of Sheep Balbas Breeds in the Southeastern Part of Azerbaijan
Authors: Bayramov S. , Ganbarov D. , Novruzov G. , Babayeva S.
Published: June 2024

In the Republic of Azerbaijan and, in particular, in the Nakhichevan Autonomous Republic, a transhumance system for keeping sheep has long been adopted, which requires animals with a strong constitution, hardy and well adapted to local climatic conditions. These requirements are best met by the local meat-wool-milk fat-tailed Balbas sheep breed, which produces high-quality white wool for carpet production, lamb with excellent taste, milk and sheepskins. But the quality of meat products from these animals has not yet been sufficiently studied. Based on this, the following tasks were set; obtaining offspring from females of the Balbas breed of the local population and local rams of the same breed; studying the meat productivity and quality of these types of products in offspring, studying the economic efficiency of slaughtering offspring at different age periods. In the process of work, the chemical composition and energy value of the meat was determined, and by looking at the longissimus dorsi muscle, its chemical composition, energy and biological value were determined. The study of the slaughter qualities of animals, determination of the chemical composition, energy and biological value of meat was carried out in accordance with the methodological recommendations of VIZH. In conclusion, the authors concluded that the meat productivity of sheep is quite high. Control slaughters carried out over many years have shown that their slaughter yield under normal economic conditions is on average 46-52%. Sheep of this breed have stable heredity and well pass on their valuable biological and economically useful qualities to their offspring, both when bred pure and when crossing crosses. The greatest economic efficiency was obtained when selling 8-month-old balbas rams.
Optimization of Sodium-Potassium Ratio in Cow Diets
Authors: Ibragimov A. , Maharramov M.
Published: June 2024

In the conditions of the Nakhchivan Autonomous Republic, research has been carried out on the prevention of metabolic disorders and optimization of the sodium-potassium ratio in the feed ration of cows. The diets were identical in composition and nutritional value, but the ratio of sodium and potassium in the groups was different due to different amounts of table salt. During the stall period of the experiment, the ratio of sodium and potassium in group I was 0.36, in group II — 0.43, and in group III — 0.48. It should be noted that this attitude in groups II and III contributed to a greater consumption of roughage and succulent feed than in the control group. During the grazing period, cows of all groups also received the same rations. However, the ratio of sodium and potassium in them was different. Thus, in group II it was 0.32, in group III — 0.41 versus 0.24 in the control. In group I for 1 feed units sodium accounted for 5.7 g, in II — 7.6 and III — 10.0 g. Cows of groups II and III consumed more grass on pasture by 4.8 and 9.6%, and green fertilizer by 3.2 and 7.6% compared to control. The amount of grass eaten on pasture was determined using the reverse calculation method. On average, per lactation in groups II and III there was 1.4 and 3.0 g more sodium per feed unit, respectively, than in group I. The nutritional value of the diets corresponded to the needs and level of productivity of the animals. Thus, optimizing the sodium-potassium ratio in the diets of highly productive cows by increasing the rate of sodium chloride by 40% in the stall and by 100% in the grazing periods with excess potassium in the diets ensures improved mineral metabolism, increases the use of nutrients and increases milk yield by 4%. Fat content by 8,8% on average per lactation.
Science of Cognitive Brain and Quantum Biophysics Homo sapiens 21st Century: hybrid Neuroimaging and Nuclear medicine, 5P Medicine and 5G Technology, Neurobiology and Neurophysiology of Quantum Brains, Psychoanalysis, Art-Medicine, Bioelementology and Nutriciology
Authors: Volobuev A. , Romanchuk T. , Romanchuk N. , Bulgakova S.
Published: June 2024

New discoveries in the field of genetics and epigenetics, the scientific union of neurobiology and neurophysiology of the quantum brain Homo sapiens of the 21st century, the achievements of biophysics, hybrid neuroimaging and nuclear medicine, the introduction of nutritionology and bioelementology technologies, the 5P of Medicine and 5G Technology, the replication of compliance of art medicine and modern psychoanalysis made it possible to manage 21st century Human cognitive brain. Scientific progress and 33 years of experimental experience of biophysics in the field of neurogeriatrics and neurocardiology, neuroendocrinology and psychoneuroimmunology made it possible to argue that “nerve cells are restored”, the quantum human brain is Controlled, high-quality and healthy longevity Homo sapiens of the 21st century is achievable. Humankind needs to know (discover, prove) in the near future the existence of more than 450 trillion neurosynaptic and neurocosmic interactions between the cognitive mind and the universe.
Effect of L-Arginine on the Dynamics of Cardio-specific Enzymes in the Blood in Rabbit with Simulated Atherosclerosis during Short-term Adaptation to High Altitudes
Authors: Akynbekova N. , Makhmudova Zh. , Taalaibekova M. , Imankhodzhaev D. , Baatyrova N.
Published: June 2024

In order to clarify the effect of L-arginine on the course of experimental atherosclerosis in rabbits, we examined the following indicators of cardiac-specific enzymes: high-sensitivity C-reactive protein and troponin I in blood serum. The biological effect of L-arginine, which plays an important role in regulating the functional state of the vascular wall in atherosclerotic lesions, is discussed. It was found that oral administration of L-arginine at a dose of 170 mg/kg body weight once a day for 30 days to animals with experimental atherosclerosis leads to a decrease in the concentration of the studied parameters of cardiac-specific enzymes in the blood.
Post-covid Syndrome in the Form of Venous and Arterial Thrombosis Complicated COVID-19
Authors: Baisekeev T. , Derkembaeva Zh. , Osmonbekova N. , Mamyshov A. , Zholborsov A. , Kochkonbaev Zh. , Emilbekov F. , Muratov K.
Published: June 2024

Post-covid syndrome in the form of thrombosis is a common and dangerous complication of COVID-19. To identify the localization, frequency, timing of thrombosis in patients who have undergone COVID-19, the frequency of surgical treatment methods used. A retrospective observational study of 239 case histories of patients (138 women and 101 men) who had COVID-19 in the Department of Vascular Surgery of the National Hospital of the Ministry of Health of the Kyrgyz Republic within the period from August to December 2020. A 42-year-old patient who underwent COVID-19 in March 2020, which gave a post-covid complication in the form of a chronic aneurysm of the infrarenal abdominal aorta five months later. Venous thrombosis as a post-covid syndrome is 74% more common than arterial thrombosis. The incidence of thrombotic post-covid syndrome in women compared to men is 15.4% higher. This trend is most pronounced in the disabled aged 61 and over. Venous thrombosis was most often localized in the veins of the lower extremities, and open surgical interventions were most often performed. People with concomitant diseases, in particular, with diseases of the cardiovascular system, are more susceptible to post-covid complications in the form of thrombosis and thromboembolism. Out of 239 people, 138 people (58%) had concomitant diseases, 101 people (42%) did not have them. Basically, open surgical interventions were performed. In 50% of cases with arterial thrombosis, thromboembolectomy was performed, with venous thrombi, the ligation of the great saphenous vein according to Troyanov accounted for 78% of operations. In the case of an individual clinical patient, laparotomy, nephrectomy on the right, elimination of an aortic aneurysm, aorto-femoral bifurcation prosthetics with an ECOFLONprosthesis were performed. Post-covid syndrome after COVID-19 is mainly localized in the veins of the lower extremities and is much more common among the female population with concomitant diseases. Open surgical operations can effectively eliminate the post-covid syndrome.
COMMUNICATIVE COMPETENCE OF A PUBLIC RELATIONS SPECIALIST
Authors:   Naberezhnochelninsk Institute of Kazan Federal University, Naberezhnye Chelny, Russian Federation, GORYACHEVA O.N.
Published: June 2024

The article explores communicative preparedness as a fundamental competence of a public relations specialist necessary for achieving professional goals and successful work in the modern world. They are responsible for the strategic management of communications and relations of the organization with the key public, play an important role in shaping and promoting the image and reputation of the organization, as well as in building and maintaining mutually beneficial relationships with key stakeholders. The relevance of the topic is in line with the new age challenges of modern Russia, which have paved the way for the institutionalization of the corpus of advertising and public relations. The purpose of the paper is related to the realization that there is a range of new educational opportunities for PR specialists leading to meaningful formation of communicative competence. The article uses the empirical method of work with the source base of FSES HE in the direction of training 42.04.01 “Advertising and public relations, comparative analysis of competence characteristics of PR-specialist's activity”. Effective communication with the target audience, quality customer service, providing a wide range of media services, social responsibility increases the recognizability of the company and create a positive image that helps to manage reputational risks. The practical significance of the work is manifested in the definition of the competence approach to the professional activity of a public relations specialist through the study of his communicative skills expressed in the strategy of reputational improvement. Communicative investments in image and reputation allow companies to gain a number of benefits, including customer loyalty, employee engagement, investor confidence and enhanced competitive advantage.
Safeguarding Privacy in the Digital Era: Finding the Balance in India
Authors: Jahan Kazi Tasnim , Reyad Zahid Hasan
Published: June 2024

Surveillance in terms of safety is an important activity by any nations national security force. It is done with the proper mechanism to figure out the hidden activity of the intruder. It is true that in many developing or underdeveloped country the prevailing laws are not properly executed., hence there can be personal rights to privacy issue occured. Similarly, in India there mass surveillance prevalent to protect the nation from foreign aggression, internal disturbance etc. In addition, at a prima facie it is protection initiative for the welfare of the citizens, but due to proper execution and other issues it is hampering the rights to privacy. There needs to legal, political role to maintain mechanism of the surveillance project and make balance with personal liberty and rights to privacy. This paper delves with how mass surveillance is hampering the rights to privacy and way to make balance between them.
Cultural symbol value in animated advertisement model: systematic review
Authors: Jingrou Liu , Mat Sin Nur Syuhada , Zhang Ran
Published: June 2024

At present, animation has a wide range of applications in the field of advertising, and more cultural levels drive greater advertising effects. Cultural value with different cultural backgrounds, there are different consumer behaviors for advertising. Therefore, we conducted a systematic review to identify the most common dimensions of animated advertising presented in recent publications and to determine whether there is sufficient evidence for the effectiveness of cultural values in animated advertising. Through electronic search of the database, a total of 1829 citations were identified, of which 14 publications included models. Empirical data were included in 13 studies, and the focus of the review was around the visual perspective, the challenges faced due to the growing cultural diversity, but the lack of cultural value, which led to the dilemma in the cultural perspective of animated advertisement. This review will help researchers explore cultural value as one of the research variables that influenced the results of the study.
Review of Modern Approaches to 3D Digitization of Tangible Cultural Heritage
Authors: Rybenská Klára , Borůvková Barbora
Published: June 2024

This review highlights modern technologies‘ pose in cultural heritage, digitization and accessibility. It provides a comprehensive view of the issue from the perspective of the digitisation centre, at the Czech University and cooperates with organizations of different sizes. Technology and Innovation offer countless possibilities, but not all are suitable for working with cultural heritage. Several rules must be followed to avoid damaging it while respecting the ethics related to the heritage in question. In addition, it is important to consider copyright law and other regulations that vary from state to state. However, these aspects are not the main concern of this study.
Early childhood development strategy for the world’s children with disabilities
Authors: Olusanya Bolajoko O. , Wright Scott M. , Smythe Tracey , Khetani Mary A. , Moreno-Angarita Marisol , Gulati Sheffali , Brinkman Sally A. , Almasri Nihad A. , Figueiredo Marta , Giudici Lidia B. , Olorunmoteni Oluwatosin , Lynch Paul , Berman Brad , Williams Andrew N. , Olusanya Jacob O. , Wertlieb Donald , Davis Adrian C. , Hadders-Algra Mijna , Gladstone Melissa J.
Published: June 2024

Early childhood is foundational for optimal and inclusive lifelong learning, health and well-being. Young children with disabilities face substantial risks of sub-optimal early childhood development (ECD), requiring targeted support to ensure equitable access to lifelong learning opportunities, especially in low- and middle-income countries. Although the Sustainable Development Goals, 2015–2030 (SDGs) emphasise inclusive education for children under 5 years with disabilities, there is no global strategy for achieving this goal since the launch of the SDGs. This paper explores a global ECD framework for children with disabilities based on a review of national ECD programmes from different world regions and relevant global ECD reports published since 2015. Available evidence suggests that any ECD strategy for young children with disabilities should consists of a twin-track approach, strong legislative support, guidelines for early intervention, family involvement, designated coordinating agencies, performance indicators, workforce recruitment and training, as well as explicit funding mechanisms and monitoring systems. This approach reinforces parental rights and liberty to choose appropriate support pathway for their children. We conclude that without a global disability-focussed ECD strategy that incorporates these key features under a dedicated global leadership, the SDGs vision and commitment for the world’s children with disabilities are unlikely to be realised.
Development of a Fast Running Equivalent Circuit Model with Thermal Predictions for Battery Management Applications
Authors: Damodaran Vijayakanthan , Paramadayalan Thiyagarajan , Natarajan Diwakar , Kumar C Ramesh , Kanna P. Rajesh , Taler Dawid , Sobota Tomasz , Taler Jan , Szymkiewicz Magdalena , Ahamed Mohammed Jalal
Published: June 2024

Equivalent circuit modelling (ECM) is a powerful tool to study the dynamic and non-linear characteristics of Li-ion cells and is widely used for the development of the battery management system (BMS) of electric vehicles. The dynamic parameters described by the ECM are used by the BMS to estimate the battery state of charge (SOC), which is crucial for efficient charging/discharging, range calculations, and the overall safe operation of electric vehicles. Typically, the ECM approach represents the dynamic characteristics of the battery in a mathematical form with a limited number of unknown parameters. Then, the parameters are calculated from voltage and current information of the lithium-ion cell obtained from controlled experiments. In the current work, a faster and simplified first-order resistance–capacitance (RC) equivalent circuit model was developed for a commercial cylindrical cell (LGM50 21700). An analytical solution was developed for the equivalent circuit model incorporating SOC and temperature-dependent RC parameters. The solution to the RC circuit model was derived using multiple expressions for different components like open circuit voltage (OCV), instantaneous resistance (R0), and diffusional parameters (R1 and C1) as a function of the SOC and operating temperature. The derived parameters were validated against the virtual HPPC test results of a validated physics-based electrochemical model for the voltage behavior. Using the developed RC circuit model, a polynomial expression is derived to estimate the temperature increase of the cell including both irreversible and reversible heat generation components. The temperature predicted by the proposed RC circuit model at different battery operating temperatures is in good agreement with the values obtained from the validated physics model. The developed method can find applications in (i) onboard energy management by the BMS and (ii) quicker evaluation of cell performance early in the product development cycle.
Performance Analysis of Distributed Reconfigurable-Intelligent-Surface-Assisted Air–Ground Fusion Networks with Non-Ideal Environments
Authors: Yao Yuanyuan , Liu Qi , Yu Kan , Huang Sai , Yue Xinwei
Published: June 2024

This paper investigates the impact of non-ideal environmental factors, including hardware impairments, random user distributions, and imperfect channel conditions, on the performance of distributed reconfigurable intelligent surface (RIS)-assisted air–ground fusion networks. Using an unmanned aerial vehicle (UAV) as an aerial base station, performance metrics such as the outage probability, ergodic rate, and energy efficiency are analyzed with Nakagami-m fading channels. To highlight the superiority of RIS-assisted air–ground networks, comparisons are made with point-to-point links, amplify-and-forward (AF) relay scenarios, conventional centralized RIS deployment, and fusion networks without hardware impairments. Monte Carlo simulations are employed to validate theoretical analyses, demonstrating that in non-ideal environmental conditions, distributed RIS-assisted air–ground fusion networks outperform benchmark scenarios. This model offers some insights into the improvement of wireless communication networks in emerging smart cities.
Arginine-Vasotocin Neuronal System in Steindachneridion parahybae (Siluriformes: Pimelodidae) and Its Influence on Artificially Induced Spawning in Captivity
Authors: Honji Renato M. , Araújo Bruno C. , de Mello Paulo H. , Ramallo Martín R. , Morandini Leonel , Caneppele Danilo , Moreira Renata G.
Published: June 2024

This study summarizes new data on induced spawning of Steindachneridion parahybae, focusing on the aggressive behavior of females. This study characterizes the vasotocinergic system using immunohistochemistry, highlighting the potential influence of arginine-vasotocin (AVT) on reproductive physiology. Two experimental groups were proposed: (A) control, with one female in the aquarium, and (B) experimental, with two females in the same aquarium. Dominant (D) females presented a more aggressive behavior and did not show any injury. They apparently had a length and body mass higher than injured nondominant (ND) females. The analysis identified positive AVT immunoreactive (ir) neurons exclusively within the preoptic area, including parvocellular, magnocellular, and gigantocellular subpopulations, containing fibers-ir extending into the pituitary gland. Cellular and nuclear areas were greater in D compared to ND in the magnocellular subpopulation. There were no differences between parvocellular and gigantocellular subpopulations. There was a difference on the steroid plasma profile of cortisol (more in ND than in D) and 17α,20β-dihydroxy-4-pregnen-3-one (more in D than in ND). Furthermore, control and D females presented higher optical densities for AVT-ir, gonadotropin-releasing hormone-ir, and luteinizing hormone-ir than ND. In general, there were no differences in the results of female (control group) with D females. The AVT system is highly complex, possibly counting multiple sites of action during artificial reproduction and acting directly and/or indirectly associated with behavioral and physiological changes in S. parahybae females when induced to spawning.
Fractional-Order Modeling and Nonlinear Dynamic Analysis of Forward Converter
Authors: Wang Xiaogang , Zhang Zetian
Published: June 2024

To accurately investigate the nonlinear dynamic characteristics of a forward converter, a fractional-order state-space averaged model of a forward converter in continuous conduction mode (CCM) is established based on the fractional calculus theory. And nonlinear dynamical bifurcation maps which use PI controller parameters and a reference current as bifurcation parameters are obtained. The nonlinear dynamic behavior is analyzed and compared with that of an integral-order forward converter. The results show that under certain operating conditions, the fractional-order forward converter exhibits bifurcations characterized by low-frequency oscillations and period-doubling as certain circuit and control parameters change. Under the same circuit conditions, there is a difference in the stable parameter region between the fractional and integral-order models of the forward converter. The stable zone of the fractional-order forward converter is larger than that of the integral-order one. Therefore, the circuit struggles to enter states of bifurcation and chaos. The stability domain for low-frequency oscillations and period-doubling bifurcations can be accurately predicted by using a small signal model and a predictive correction model of the fractional-order forward converter, respectively. Finally, by performing circuit simulations and hardware-in-the-loop experiments, the rationality and correctness of the theoretical analysis are verified.
Affordances and Borderscapes: Language Ideologies, Nationalisms, Generations and Geographies of Resistance in Cyprus
Authors: Karayianni Christiana , Christou Anastasia
Published: June 2024

In this article, we explore the ways language has been used in Cyprus during different historical periods as a means of a dividing power, with the use of Cypriot dialects as a form of resistance and reunification of the island. We situate these translanguaging themes within a context of affective biopolitics that impacts Cypriot generations in shaping their everyday life through borderscapes and nationalisms. More specifically, we first examine how the official languages of the island (Greek and Turkish) have been used in the dominant public sphere(s) of Cyprus to marginalise Cypriot dialects, which, in turn, have been used as an oral means of communication, but also to impose symbolic signifiers of the biopolitics of borders and nationalisms in dividing communities. Secondly, we explore ways in which Cypriot dialects have been used as forms of linguistic resistance to nationalism, offering an alternative collective identity for generations of both communities, even during periods when nationalism was dominant in both communities. The translanguaging exploration centres on a close discourse analysis of one particular radio programme—the ‘Cypriot radio sketch’—that has been very popular among Cypriots since the appearance of radio in Cyprus in 1953. Finally, we analytically and discursively contextualise attempts of revival of the Cypriot dialects by younger generations as communicative forms of resistance to powers of partition, as well as translanguaging pathways to actualise their desire for the reunification of the island. We eclectically draw on a multi-method approach to combine datasets from interviews, media and social media while combining critical discourse analysis to theorise the affordances, borderscapes and affective biopolitics of generational language use within geographies of nationalism and resistance in the borderscapes of a divided Cyprus.
Gestión de mantenimiento de maquinaria y equipos en diferentes sectores agroindustriales: Revisión sistemática
Authors: Vasquez Caceres Jaime Eduardo , Orellana Pardave Jose Antonio , Rebaza Pino Alfredo Carlos , Altamirano Chunga Luis Alberto
Published: June 2024

La importancia del mantenimiento en el sector agroindustrial requiere un plan estratégico para garantizar el rendimiento óptimo de la maquinaria. Esta investigación tiene como objetivo analizar la producción científica sobre la gestión eficiente del mantenimiento de maquinaria y equipos en diferentes sectores agroindustriales. Se utilizó el método PRISMA para reducir el sesgo, realizando una búsqueda exhaustiva en Scopus y Google Scholar que arrojó 535 artículos. Después de un proceso de filtrado, se seleccionaron 14 estudios que aportaron información sobre cálculos económicos, modelos de registro, categorización de riesgos y medición de tiempos de falla. Los hallazgos resaltan estrategias clave como la gestión por procesos, el mantenimiento predictivo, la modelización Markov, la externalización de trabajos complejos, la medición de capacidad eléctrica, la capacitación de operarios y la gestión de recursos técnicos. Estas prácticas innovadoras, que incluyen la digitalización y el uso de tecnologías avanzadas, permiten optimizar la operatividad, reducir costos y aumentar la productividad en entornos agroindustriales, anticipando y previniendo fallas, mejorando la eficiencia operativa y mitigando riesgos laborales.
Educación ambiental, currículo, estrategias y políticas para la sostenibilidad: una revisión sistemática
Authors: Farfán Pimentel Johnny Félix , Delgado Arenas Raúl , Farfán Pimentel Diana Eulogia
Published: June 2024

La Educación Ambiental es esencial en el sistema educativo global para promover una sociedad comprometida con la preservación ambiental y el desarrollo sostenible. Este artículo revisa investigaciones recientes en instituciones educativas, sus propuestas curriculares, políticas y estrategias de enseñanza. La metodología utilizada fue una revisión sistemática cualitativa con el método PRISMA, seleccionando 19 artículos de 2015 a 2023 en la base de datos Scopus. Se destaca una concentración en artículos recientes, principalmente en 2023, evidenciando una evolución constante en la investigación, con el año 2020 como destacado; la distribución desigual de años sugiere cambios en el enfoque investigativo. Los estudios subrayan la importancia de políticas ambientales a diferentes niveles, la vinculación con los Objetivos de Desarrollo Sostenible y la necesidad de integrar la Educación Ambiental en el currículo para contribuir a la formación de valores, desarrollar competencias y formar individuos conscientes y comprometidos con la sostenibilidad ambiental y la transformación social.
Análisis de datos agro-meteorológicos en la gestión de actividades de producción de cultivos transitorios en el litoral ecuatoriano
Authors: Bermeo Almeida Oscar Xavier , Dávila Vargas William Jair , Guevara Arias Verónica Isabel , Arevalo Gamboa Lissett Margarita
Published: June 2024

La modificación del clima se expresa a través del incremento en cantidad e intensidad de fenómenos como sequías, lluvias y huracanes. Estas modificaciones climáticas tienen consecuencias importantes para la sociedad, principalmente para las poblaciones más vulnerables, caracterizadas por la pobreza y la exclusión de espacios de toma de decisiones. Con el objetivo de la investigación es la de analizar los datos agro-meteorológicos masivos aplicando metodologías adecuadas de tratamiento de información para mejorar las actividades en la producción de cultivos transitorios en el litoral ecuatoriano. La metodología empleada con enfoque inductivo que se nutrió principalmente de fuentes provenientes de plataformas académicas reconocidas como Science Direct y Springer, Scielo, Scopus y Redalyc con el empleo de la herramienta Google Académico, para lo que se seleccionaron estudios publicados entre los años 2016 y 2022 como marco temporal de referencia. La selección de literatura se rigió por un criterio de relevancia, priorizando aquellos estudios que proporcionaran una comprensión más profunda de la interrelación existente entre los datos agro-meteorológicos y rendimiento productivo de los cultivos transitorios en la zona costera del Ecuador. Se conoce según estudios, que la población rural en el Ecuador consta de un 50% en cuanto a actividad agronómica, donde se puede observar un mayor porcentaje en la Provincia de Los Ríos. Las empresas Facundo, Semvra Veconsa, Arrocera Portilla (PortiArroz), Arrocera SylviaMaria (AgroSylma) y ProArroz utilizan agro-meteorología para planificar la producción, con 14 estaciones climatológicas que brindan información actualizada para que se realicen correctamente la planeación estratégica de las siembras y cosechas. Se concluye que, se muestra como beneficia el uso de la agro-meteorología en la planeación de las diferentes actividades agrícolas, lo que las mismas realizan para la caracterización en tiempo y espacio de las relaciones entre el clima, para mejorar el rendimiento de los cultivos transitorios.
Diagnosis of COVID -19 Disease in X -ray Images Based on Deep Learning Methods and Combining Classifiers
Authors: Roustaei Mohammad , Giveki Davar
Published: June 2024

Introduction: COVID -19 is a new virus that causes infection in the upper respiratory tract and lungs, and the number of deaths due to the disease has increased daily on the scale of a global epidemic. Chest X -ray images have been useful for monitoring various lung diseases and have recently been used to monitor COVID -19 disease. Method: In this research, a multi -stage process was used to recognize COVID -19 from X - ray images. In the first stage, pre -processing was done to normalize the data. In the second step, which is the most important step of the proposed method, feature extraction was done. The feature extraction operation was based on deep learning networks. After feature extraction, machine learning algorithms were used to classify images. The algorithms used in this section are support vector machine, nearest neighbor, and decision tree algorithms. The results of these categories are combined in the fourth step based on the majority vote. Results: The parameters used in this research are among the classification parameters, including precision, accuracy, recall, and F -criterion, which were obtained as 96.5, 92.25, 94, and 93, respectively. Conclusion: The results of the experiments show the acceptable efficiency of the proposed method because, in addition to reducing the calculations by the separable layer, the combination of categories and their weighting has been used to obtain the final result.
A Pipeline -based Framework for Early Prediction of Diabetes
Authors: Abnoosian Karlo , Farnoosh Rahman , Behzadi Mohammad Hassan
Published: June 2024

Introduction: Diabetes is a chronic disease worldwide, with an increasing annual death rate. Many health professionals seek innovative ways to detect and treat it early. Rapid advances in machine learning have improved disease diagnosis. However, because of the small amount of labeled data, the frequency of null and missing values, and the imbalance of databases, creating an optimal predictor for disease diagnosis has become a great challenge. This study aimed to present a pipeline -based classification framework for predicting diabetes on two datasets of Indian diabetic patients with two classes (patient and healthy groups) and Iraqi with three classes (patient, healthy, and prediabetes groups). Method: An important part of this framework is preprocessing. Different ML models based on the One -Vs -One approach for the three -class mode are implemented in the framework. Because of the imbalance of the data set, besides the accuracy evaluation criterion, the area under the receiver operating characteristic (ROC) curve is also used. To increase the level of these two criteria, the Hyper -parameters of each model are optimized using optimization methods to build a powerful model with less training and testing time through various feature selection methods. Results: The proposed framework was assessed for diabetes prediction on two datasets of Indian and Iraqi diabetic patients. It was revealed that using AdaBoost for the Indian dataset (ACC=89.98, AUC=94.11) and random forest for the Iraqi dataset (ACC=98.66, AUC= 98.62), good accuracy and performance were obtained. Conclusion: Regarding ACC parameters, precision, accuracy, recall, and F1 -Score, the pipeline -based framework has an optimal performance in predicting diabetes, therefore, it can be used in clinical decision support systems.
Early Prediction of Alzheimer’s Disease Using Interpretable Machine Learning Algorithms
Authors: Sorayaie Azar Amir , Rezaei Samaneh , Bagherzadeh Mohasefi Jamshid , Niazkhani Zahra , Pirnejad Habibollah
Published: June 2024

Introduction: Alzheimer’s disease is one of the most common neurodegenerative diseases in adults. The progressive nature of Alzheimer’s disease causes widespread damage to the brain, and early diagnosis can manage the disease and slow down its progression effectively. Method: In this study, a dataset related to the early prediction of Alzheimer’s was used. Spark framework was used for data management and three machine learning algorithms including Naïve Bayes, Decision Tree, and Artificial Neural Networks with the best hyperparameters were implemented and compared. To prevent overfitting and measure the efficiency of the models, a 5 -fold cross -validation method was utilized. Furthermore, a method was used for interpreting machine learning black box models. Results: The decision tree and artificial neural network models obtained 98.61% accuracy and 98.60% F1 -Score in the Spark framework including one or three computers. Important features in the decision -making process of the artificial neural network were identified using the interpretability technique. In addition, the computational time required for training the proposed models was calculated through different approaches, and the use of multiple computers was 35.95% faster than a single computer. Conclusion: With increasing the number of Alzheimer’s disease patients around the world, the need for a decision support system using machine learning algorithms, which can predict the disease early in a huge amount of data, is felt more. Therefore, the machine learning models proposed in this study for early prediction of Alzheimer’s disease as an interpretable auxiliary tool in the decision -making process can help clinicians .
Design and Evaluation of a Mobile Phone -based Recommender System for Patients with Cardiac Arrhythmia
Authors: Langarizadeh Mostafa , Rostampour Amir Homayoun , Noshirvan Rahat Abad Fereydon , Langarizadeh Mohammad Hossein , Sarpourian Fatemeh , Fatemi Aghda Seyed Ali
Published: June 2024

Introduction: Cardiovascular disease is one of the main causes of death worldwide. One of the important factors is readmission due to the lack of training. Considering the widespread use of mobile phones, this study aimed to design a recommender system for patients with cardiac arrhythmia. Method: This is an applied -developmental study that was conducted in a quantitative (descriptive) method and in 2 stages. First, the recommended educational parameters and application requirements of the software were determined based on literature review. Then, the obtained contents were provided to 16 cardiologists working in Shahid Rajaei and Hazrat Rasool Akram Hospitals in Tehran. To evaluate the usability, the application was given to 50 patients with cardiac arrhythmia and was checked with the quiz questionnaire version 5.5 . Results: In the recommendations section, experts deemed all items except "Omega -3 consumption" necessary. In the usability evaluation section, the items "Identifying the nearest emergency center, sending the patient’s geographic location to the doctor, finding the nearest medical center, and the possibility of changing color, and calculating BMI" were not confirmed. The usability evaluation of the application with an average score of 7.98±0.62 indicates a good level . Conclusion: The mobile -based recommender application can cause the patients to play a greater role in their treatment and acquire skills in the field of training after hospital discharge and lead to a reduction in re -hospitalization and cost.
A Narrative Review of the Frameworks, Challenges, and Applications of Interoperability in E -Health
Authors: Moshiri Fatemeh , Asosheh Abbas
Published: June 2024

Introduction: Integrated Health Information Systems (HIS) are necessary to achieve national and international goals in health and development, which are facing cooperation problems due to diversity and heterogeneity. Interoperability as a key characteristic of data sharing and the main prerequisite of integration enables healthcare providers to make timely decisions for diagnosis, treatment, action, and patient care. Therefore, this research aimed to provide a category of interoperability concepts in electronic health ( E -Health). Method: This research is a narrative review to categorize the interoperability concepts in E - Health. For this purpose, Scopus, Google Scholar, PubMed, Science Direct, and IEEE databases were searched using the keywords "Interoperability framework" and "Integration" with the combination of AND along with "E -Health". Therefore, all the articles referring to the concepts of interoperability were selected. Results: The result of the search in the aforementioned databases was 304 articles. By removing duplicate, out -of-reach, and unrelated articles, only 40 articles were examined, and topics related to the concepts of interoperability were classified based on six axes (dimensions, levels, obstacles, integration, architecture, and measurement). Finally, its applications and challenges were described in a narrative review. Conclusion: Due to the nature of the health system, integrity and intelligence are very important in this area. Therefore, to facilitate the exchange of information and the use of health information systems from each other’s services, paying attention to the presented classification has an undeniable effect, and also, an important role in the integrity and intelligence of the environment, and increases the efficiency and effectiveness in the quality of providing health care services.
Introduction of an Efficient Multiepitopic Vaccine Against Different SARS -CoV -2 Strains: Reverse Vaccinology
Authors: Sarvmeili Javad , Baghban Kohnehrouz Bahram , Gholizadeh Ashraf , Ofoghi Hamideh , Shanehbandi Dariush
Published: June 2024

Introduction: In recent years, COVID -19 has been recognized as a health threat. Despite vaccination, people still get the disease because the new variants have mutations in their genomes that allow them to bind to host receptors and evade the immune system’s responses. Therefore, the main aim of this study was to use bioinformatics tools to introduce a rapid and practical vaccine to fight against these diverse mutations in different SARS -CoV-2 strains. Method: To epitopes mapping, 32 different spike protein variants were retrieved. We then used the Immune Epitope Database (IEDB), NetCTL, and NetMHCIIpan to predict T and B cell epitopes. The vaccine based on protected epitopes was evaluated in terms of antigenicity, allergenicity, toxicity, solubility, physicochemical properties, population coverage, and secondary structure with relevant servers. Modeling using Robetta and docking with Toll -like receptor (TLR3) were performed using Cluspro, PatchDock, and FireDock, respectively. Results: After detailed evaluations, all the results confirmed the optimal quality of the vaccine. According to further investigations, this structure is similar to native proteins and there is a stable and strong interaction between the vaccine and the receptor. Based on molecular dynamics simulation, structural compactness and stability in binding were also observed. In addition, the immune simulation showed that the vaccine can stimulate immune responses similar to real conditions. Finally, codon optimization and in silico cloning confirmed efficient expression in Escherichia coli . Conclusion: Based on the obtained results, the designed multi -epitope vaccine can serve as a prophylactic candidate against SARS -CoV-2.
Conceptual Model and Requirements of An Electronic Case Report Form to Collect a Minimum Data Set of Complications of the COVID -19
Authors: Nasiri Khoshroudi Seyyed Hamzeh , Safaei Ali Asghar , Soleimanjahi Hoorieh
Published: June 2024

Introduction: In recent years, the collection of data from the monitoring of clinical trials in the form of electronic case report forms (eCRF) has been increasingly used, because avoiding mistakes, reducing the duration of clinical studies, and preventing increasing data collection costs can affect the success of the study. Accordingly, this research aimed to present the conceptual model and requirements of the proposed eCRF, which is based on NoSQL database to achieve complications caused by the COVID -19 vaccine. Method: In this study, using the descriptive -applicative method, the conceptual model of the eCRF system was first designed to collect the minimum set of data on the complications of the COVID -19 vaccine. Then, the functional and non -functional requirements of the proposed system were identified using the methods of observation, thinking and reflection, and questionnaire. Results: This research has two main parts: the proposed conceptual model and the functional and non -functional requirements of the eCRF system. A conceptual model was proposed based on the components, modules, and objectives of the eCRF core, which can be used by researchers and clinical trial specialists. Requirements including the ability to register, insert, delete, and edit the case report form, were also calculated for four groups of patients, health care workers, disease experts, and the executive manager. Conclusion: The proposed system provides researchers and experts of clinical trials with classified and valid data regarding the registration of complications caused by the COVID -19 vaccine in an integrated manner. Therefore, some eCRF stakeholders such as patients, healthcare workers, disease experts, and executive managers and researchers can achieve a vaccine with acceptable safety and effectiveness by analyzing, interpreting, and sharing the recorded information.
Presenting an Intelligent Algorithm to Predict Heart Attack
Authors: Hosseinpoor Mohammadjavad
Published: June 2024

Introduction: Today, heart attack is one of the most common causes of death in adults all over the world. According to the announcement of the Ministry of Health, Treatment, and Medical Education, 11 to 15 percent of deaths in Iran are caused by heart attacks, and in the world, Iran has the highest number of deaths due to heart disease in 2022. It has been estimated that deaths from these diseases will increase to 20 million people. Therefore, predicting this disease is one of the most challenging topics in the medical field, and today most prediction systems are created using artificial intelligence and machine learning algorithms. Method: This applied and descriptive research was conducted in 2022 using the information of 600 people who referred to Peymaniyeh and Motahari hospitals in Jahrom city. In this research, data were collected based on the available sources from both hospitals. To implement and evaluate the results, MATLAB programming language was used. Results: The parameters used in this research are among the classification parameters, including classification rate, precision, recall, and F -measure, which were obtained as 90.7, 90.2, 91.5, and 90.8, respectively. Conclusion: The results show that the proposed model will be able to predict the probability of stroke with a high percentage.
Determining the Minimum Data Set for Electronic Health Records of Tuberculosis Patients
Authors: Bahador Fatemeh , Jovanmard Zohre , Sabahi Azam , Salehi Fatemeh , Shahabi Shirin , Fateh Behari Reza
Published: June 2024

Introduction: The minimum data set is considered an important tool in the registration systems and monitoring programs, which provides the possibility of collecting and transferring data at the country level. Considering the importance of tuberculosis in Iran and especially the high incidence of this disease in the marginal provinces of the country, the present study was designed and implemented to determine the minimum data set for the electronic health records of tuberculosis patients. Method: This descriptive study was conducted in two phases. In the first phase, a comprehensive review was conducted in PubMed, Science Direct, SID, and Magiran databases to identify data elements. The data were collected using the data extraction form and polled using the Delphi method. Descriptive statistics and SPSS version 16 were used for data analysis. Results: The minimum data set of tuberculosis was divided into two categories: administrative data with five classes and 35 data elements, and clinical data with five classes and 43 data elements. Conclusion: The minimum data set of tuberculosis is an effective tool for managing and recording the information of patients suffering from this disease. The results of this study can help researchers and developers in the process of designing and implementing an integrated information system for registering the information of patients with tuberculosis.
Pengaruh Pertumbuhan Laba, Suku Bunga, Payout Ratio dan PE t-1 Ratio Terhadap Harga Saham/Earning
Authors: Maulana Dede Yusuf
Published: June 2024

Stock are securities that are signs of a person or entity ownership of a company. In certain market conditions the stock price can be undervalued or overvalued in which both can be analysed by using stock valuation models. The purpose of this study is to test some of the stock price valuation models on the shipping company listed on the Indonesian Stock Exchange. The are is PE. The analysing conducted by multiple regression to the sample companies listed on the Indonesia Stock Exchange during 2019-2023, at shipping company. P/E model variable payout Ratio and P/Et-1 a positif significant influence on the P/E, while the Growth and Beta have no effect on the P/E. PE model have the R Squared of 22,22%.
Pengaruh Kualitas Produk Terhadap Keputusan Pembelian Produk Clay Mask Skintific (Survei Pada Pengguna Clay Mask Skintific di Marketplace Shopee)
Authors: Eva Amalia Nuralifah  , Alya Abidatul Maula  , Yusuf Abdul
Published: June 2024

Penelitian ini mengkaji bagaimana Kualitas Produk mempengaruhi Keputusan Pembelian Produk Clay Mask Skintific (Survei pada pengguna Clay Mask Skintific di Marketplace Shopee). Penelitian ini menggunakan metode kuantitatif dengan pendekatan deskriptif dan verifikatif. Populasi dalam penelitian ini adalah para pengguna produk Clay Mask Skintific. Dan jumlah sampel yang telah terkumpul yaitu sebanyak 108 responden. Metode sampling digunakan dalam penelitian ini adalah non-probability sampling dengan teknik purposive sampling. Penelitian ini menggunakan teknik analisis rentang skala dan analisis regresi linear sederhana dengan alat bantu SPSS 25 dan Microsoft. Hasil dari penelitian ini terdapat pengaruh parsial Kualitas Produk terhadap Keputusan Pembelian yang memiliki nilai sebesar 93,8%. Berdasarkan hasil analisis bahwa Kualitas Produk secara simultan berpengaruh positif dan signifikan terhadap Keputusan Pembelian. Hal ini dibuktikan dengan nilai fhitung (193.599) > ftabel (3.93) dan memiliki nilai Sig. sebesar 0.000 < 0.05 maka Ho ditolak dan H1 diterima.