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The Shanghai Cooperation Organization (SCO), the political and economic alliance of countries in the Eurasian region, has a significant role in the economic development of its member nations. This study examines the research performance of the Shanghai Cooperation Organization, which was assessed using the cite space software, with all data retrieved from the Web of Science (WoS) database. A Total of 810 publications were taken from the Web of Science database for analysis. The study analysed the broad features of economic research output, focusing on Top cited institutions, different subject areas, top country-wise contributors, top authors, journals, etc. The study found that being an economic cooperation treaty like the Shanghai organization, the economic cooperation and economic research output were revealed and discussed for the first time in worldwide references. The analysis of citation counts highlights the dominance of Chinese institutions in terms of research impact. The Chinese Academy of Sciences stands out as the most cited institution, indicating its significant contribution to the economic research output among the SCO countries. The areas of interest within the economic research output of the SCO countries are environmental sciences and studies, followed by green and sustainable science and technology, public and occupational health, economics, and interdisciplinary mathematics applications. JEL Codes: F5, O5, O4 Received: 14/12/2023. Accepted: 26/05/2024. Published: 28/06/2024.

This paper presents a deep neural network (DNN) approach designed to estimate the milk yield of Holstein-Friesian cattle. The DNN comprised stacked dense (fully connected) layers, each hidden layer followed by a dropout layer. Various configurations of the DNN were tested, incorporating 2 and 3 hidden layers containing 8 to 54 neurons. The experiment involved testing the DNN with different activation functions such as the sigmoid, tanh, and rectified linear unit (ReLU). The dropout rates ranging from 0 to 0.3 were employed, with the output layer using a linear activation function. The DNN models were trained using the Adam, SGD, and RMSprop optimizers, with the root mean square error serving as the loss metric. The training dataset comprised information from a unique database containing records of dairy cows in the Republic of Serbia, totaling 3,406 cows. The input parameters (a total of 27) for the DNN included breeding and milk yield data from the cow’s mother, as well as the father’s ID, whereas the output parameters (a total of 8) consisted of milk yield parameters (a total of 3) and breeding parameters of the cow (a total of 5). Training iterations were conducted using a batch size of 8 over 500, 1000, and 5000 epochs.

The Lipizzan horse breed was established in the 16th century in Lipica and later spread throughout Central and Eastern Europe. In addition to six classical stallion lines, 17 classical mare family lines were established in the old Lipica stud. Additional 44 mare family lines, including local lines, were established in other Lipizzan studs. The founders of the classical Lipizzan mare family lines date back to the period between the 18th and 20th century and came from various breeds, including the Karst, Spanish, Italian, Kladruber and Arabian horses. The history of the Lipizzan mare family lines is well described and supported by the availability of 44 nucleotide sequences of the mtDNA control region. In this study, the mtDNA control region of 23 Serbian Lipizzans, representing the established Lippizan mare family lines, as well as the local mare family line Zora, have been sequenced. The objective of this study was to test whether the Zora mare family line could be distinguished from other Lipizzan mare family lines according to the mtDNA sequence. Sequences were aligned to the entire set of mtDNA control region sequences representing 44 Lipizzan mtDNA haplotypes. Based on the alignment, a median-joining network was constructed. The individuals in this study formed a cluster with the existing Lipizzan mare family lines. However, a total of ten individuals belonging to the local Zora mare family line formed a compact cluster close to the mtDNA haplotypes, representing the classical mare family lines Wera, Betalka, and Monteaura. Additional pedigree data are needed to clarify the origin of the mtDNA haplotype variant identified in this study.

This research aims to estimate heritability and repeatability based on the data on milk production traits (MY – milk yield; FY – milk fat yield; FC – milk fat content; PY – milk protein yield and PC – milk protein content) as well as pedigree and genomic information. A total of 6,041 animals were included in the research, while 2,565 of them had data for milk production traits. In order to form a genomic relationship matrix, 58K SNP data were used for a total of 1,491 cows. Several software tools were used in the preparation and analysis of data, which were provided by the Central Breeding Organization, Department of Animal Science, Faculty of Agriculture, University of Novi Sad. PreGSF90, in combination with RENUMF90, was used for quality control of genomic information. Genetic analysis was performed in WOMBAT software by the REML using standard repeatability univariate analysis (BLUPpe) and repeatability models for genomic prediction (GBLUPpe and ssGBLUPpe). In all three analyses, the highest heritability (0.410, 0.378 and 0.389, respectively) and repeatability (0.449, 0.429 and 0.440, respectively) were calculated for FC. Heritability estimates for all other traits were lower. Heritability ranged from 0.158 to 0.185 for MY, from 0.166 to 0.178 for FY, from 0.141 to 0.154 for PY and from 0.135 to 0.221 for PC. Heritability estimates indicate that it is possible to achieve genetic improvement but it is necessary to introduce the best model for prediction of breeding values of cow.

Lateral epicondylitis, commonly known as Tennis Elbow, affects approximately 1-3% of the population. Despite the absence of histological evidence of inflammation in the affected tissue, the term “epicondylitis” implies inflammation. The Extensor Carpi Radialis Brevis (ECRB) muscle is primarily affected, and the condition is attributed to excessive use of this muscle. Non surgical treatment options, such as rest, physiotherapy, cortisone injection, platelet-based therapies, and restricted movements, are recommended. Surgical intervention is suggested for cases involving physical impairment or chronic pain. This review aims to provide healthcare professionals with an understanding of the condition, including its causes, symptoms, diagnosis, and treatment planning options.

The common neuropathy Cubital Tunnel Syndrome (CuTS) causes sensory impairment. Numerous patients also exhibit muscle atrophy as a symptom of severe and persistent nerve damage, which typically portends a poor prognosis. In the majority of individuals with minor nerve dysfunction, nonsurgical treatment aimed at reducing both compression and traction on the ulnar nerve at the elbow is successful. The optimum care for a patient with this pathology requires prompt and accurate evaluation, diagnosis, and testing, as well as evidence-based therapy choices. The goal of this review article was to offer an updated summary of the most recent research on the results of several surgical procedures for CuTS. A clinician must use the available information to develop a diagnosis and treatment plan that are unique to the patient. The most effective surgical methods for CuTS need to be discovered through more in-depth scientific investigation.

In our aging culture, neurodegenerative disorders like Parkinson's disease (PD) are among the most serious health issues. It is a neurological condition that has social and economic effects on individuals. It happens because the brain's dopamine-producing cells are unable to produce enough of the chemical to support the body's motor functions. The main symptoms of this illness are eyesight, excretion activity, speech, and mobility issues, followed by depression, anxiety, sleep issues, and panic attacks. The main aim of this research is to develop a workable clinical decision-making framework that aids the physician in diagnosing patients with PD influence. In this research, the authors propose a technique to classify Parkinson’s disease by MRI brain images. Initially, the input data is normalized using the min-max normalization method, and then noise is removed from the input images using a median filter. The Binary Dragonfly algorithm is then used to select features. In addition, the Dense-UNet technique is used to segment the diseased part from brain MRI images. The disease is then classified as Parkinson's disease or health control using the Deep Residual Convolutional Neural Network (DRCNN) technique along with the Enhanced Whale Optimization Algorithm (EWOA) to achieve better classification accuracy. In this work, the Parkinson's Progression Marker Initiative (PPMI) public dataset for Parkinson's MRI images is used. Indicators of accuracy, sensitivity, specificity and precision are used with manually collected data to evaluate the effectiveness of the proposed methodology.

The application of nanobiotechnology is an emerging area of nanoscience and nanotechnology. Nanodiamond has been a potent antibacterial, antifungal, antioxidant, and antiplatelet agent. In the present study, nanodiamonds were reduced by green synthesis and characterization was done through SEM, TEM, FTIR, and XRD. Further they were tested for their biological applications. The antimicrobial activity was investigated/studied/examined? through well diffusion method. The best activity was observed against Trichoderma reesei (16 mm) at 140 µg/ml. The antioxidant activity was investigated through DPPH and FRAPS method. It was observed that the biologically reduced nanodiamonds reduce the Fe3+ ions to Fe2+ ions at 600 mM/l/g concentration. In DPPH assay, inhibitory concentration was found to be 4.58 µg/ml. Further the antiplatelet activity was investigated by prothrombin time (PT) and activated partial thromboplastin time (APTT) assay, and it was observed that biologically reduced nanodiamonds have potent antiplatelet activity. [ABSTRACT FROM AUTHOR]

Agri-preneurship is a solution to many economic problems faced by India in general and agriculturists in particular. It can significantly contribute to rural development. This study seeks to understand the factors which motivate people to start and lead to the success of agripreneurship. Primary data were collected from 60 respondents using a structured interview schedule. It was found that the highest motivational factor for entering into the agripreneurship field was ‘Knowledge about the business’ followed by ‘self-satisfaction’. There was no significant difference among motivational factors with regard to age group.