bluuebunny/crossref_metadata_2025 huggingface dataset:
Decoding Energy Usage Predictions: An Application of XAI Techniques for Enhanced Model Interpretability
Authors: Airlangga Gregorius
Published: September 2024

The growing complexity of machine learning models has heightened the need for interpretability, particularly in applications impacting resource management and sustainability. This study addresses the challenge of interpreting predictions from sophisticated machine learning models used for building energy consumption predictions. By leveraging Explainable AI (XAI) techniques, including Permutation Importance, SHapley Additive exPlanations (SHAP), and Local Interpretable Model-Agnostic Explanations (LIME), we have dissected the predictive features influencing building energy usage. Our research delves into a dataset consisting of various building characteristics and weather conditions, applying an XGBoost model to predict Site Energy Usage Intensity (Site EUI). The Permutation Importance method elucidated the global significance of features across the dataset, while SHAP provided a dual perspective, revealing both the global importance and local impact of features on individual predictions. Complementing these, LIME offered rapid, locally focused interpretations, showcasing its utility for instances where immediate insights are essential. The findings indicate that 'Energy Star Rating', 'Facility Type', and 'Floor Area' are among the top predictors of energy consumption, with environmental factors also contributing to the models' decisions. The application of XAI techniques yielded a nuanced understanding of the model's behavior, enhancing transparency and fostering trust in the predictions. This study contributes to the field of sustainable energy management by demonstrating the application of XAI for insightful model interpretation, reinforcing the significance of interpretable AI in the development of energy policies and efficiency strategies. Our approach exemplifies the balance between predictive accuracy and the necessity for model transparency, advocating for the continued integration of XAI in AI-driven decision-making processes.
Tree Damage Type Classification Based on Forest Health Monitoring Using Mobile-Based Convolutional Neural Network
Authors: Gandadipoera Faishal Hariz Makaarim , Andrian Rico , Safei Rahmat
Published: September 2024

One of the fundamental parts of surveying forest health conditions with Forest Health Monitoring (FHM) is to visually assess the damage experienced by trees under certain conditions. This visual assessment can be facilitated using a Convolutional Neural Network (CNN) which involves building the MobileNetV2 model architecture. The model was trained using 1600 image data with 16 classes. The image data was pre-processed by resizing it to 224x224. The data was categorized into three categories: 80% was allocated for training, 10% for validation, and testing with 10% also. Training was done by changing the values from batches with a maximum of 100 epochs. The model was then incorporated into a mobile application using TensorFlow Lite and testing the application gave satisfactory results.  The model results get the best accuracy rate of 98.75% and a loss of 0.0497. This research concludes that the classification of tree damage types based on FHM with CNN can be done. For accurate results, the image provided by the user must be clear and reflect the actual damage observed on the tree.
Application of the Artificial Neural Network Algorithm to Predict the Realization of the Duty Tax on the Name of Motor Vehicles in Lampung Province
Authors: Kurniasari Dian , Ramadhani Putri Salsabila , Wamiliana Wamiliana , Warsono Warsono
Published: September 2024

Regional taxes, specifically the Motor Vehicle Name Return Tax (BBNKB), provide the primary source of revenue for regions from the several forms of taxes. The BBNKB tax is crucial in funding government and regional development due to its significant annual growth, encompassing four-wheeled and two-wheeled vehicles. Furthermore, the BBNKB tax catalyzes regional economic expansion and significantly contributes to the government's income. Hence, predicting and forecasting the BBNKB Tax in Lampung Province is necessary to monitor future tax rate fluctuations. That will enable the government to devise innovative tax payment systems and establish tax revenue targets. This study utilizes the Artificial Neural Network (ANN) methodology, using many approaches for distributing training and testing data to forecast. In addition, we utilize hyper-tuning on several factors to obtain the most favourable configurations. The ideal model achieved has a training data allocation of 80% and a testing data allocation of 20%. It was trained for 50 epochs and used a batch size of 16. The model has exceptional predictability, attaining an accuracy rating of 96.51%. Additionally, it showcases a low Root Mean Square Error (RMSE) of 0.246 and a minimal Mean Absolute Percentage Error (MAPE) score of 3.48%. Therefore, it is appropriate to predict the next two-year term. As a result, the forecast for the amount of tax collected from motor vehicle name returns in Lampung has fluctuated.
Sentiment Analysis of Brand Ambassador Influence on Product Buyer Interest Using KNN and SVM
Authors: Putri Natasya Kurnia , Vitianingsih Anik Vega , Kacung Slamet , Maukar Anastasia Lidya , Yasin Verdi
Published: September 2024

In the dynamic marketing, companies usually use strategies involving celebrities or influencers to promote their products or brands. The currently popular strategy is using Korean boy bands as brand ambassadors. This collaboration certainly gets a lot of opinion responses through tweets on X app social media. This research aims to analyze sentiment to determine how the product buyer's interest responds to brand suitability, brand image management, and the influence of issues that arise in this collaboration. The research stages consist of data collection, pre-processing, labeling, weighting, and classification with K-Nearest Neighbor and Support Vector Machine and performance evaluation using a confusion matrix. The dataset used was 696 tweets taken using web scrapping techniques. This research uses the Lexicon-based method to divide the dataset into positive, negative, and neutral classes. The SVM method shows superior test results by achieving an accuracy rate of 83.34% compared to the KNN method, which produces an accuracy value of 71.2% in its calculations
Exploring New Frontiers: XCEEMDAN, Bidirectional LSTM, Attention Mechanism, and Spline in Stock Price Forecasting
Authors: Kelvin Kelvin , Sinaga Frans Mikael , Winardi Sunaryo , Susmanto Susmanto
Published: September 2024

The Attention Mechanism is acknowledged as a machine learning method proficient in managing relationships within sequential data, surpassing traditional models in this regard. However, the unique characteristics of stock data, including substantial volatility, multidimensionality, and non-linear patterns, present challenges in attaining accurate forecasts of stock prices. This research aims to tackle these hurdles by enhancing a prior model through the incorporation of an Attention Mechanism, resulting in an enhanced model. The forecasted data are standardized and prepared for analysis before undergoing signal decomposition into high and low-frequency components. Subsequently, the Attention Mechanism processes the high-frequency signals. Evaluation entails comparing the performance of the proposed model with that of the previous model using identical parameters. The findings indicate that the proposed model achieves a reduced RMSE value of 0.5708777053 compared to the previous model's average RMSE value of 0.5823726212, indicating enhanced accuracy in stock price prediction. This approach is anticipated to make a substantial contribution to the advancement of more dependable and effective stock price prediction models, addressing the limitations of prior methodologies
Sentiment Analysis of Ampera Bridge as a National Tourism Destination
Authors: Purba Mariana , Yadi Yadi
Published: September 2024

Ampera Bridge is one of the leading tourism icons in Palembang which attracts thousands of visitors every year. This research aims to analyze visitors' opinions about the Ampera Bridge using opinion mining techniques in Google Review reviews. Research methods include collecting review data from Google Reviews, data preprocessing, sentiment analysis, and aspect analysis. The data collected includes 307 reviews taken in the period April 2024. These reviews were analyzed using the Support Vector Machine (SVM) algorithm to classify sentiment as positive, negative, or neutral. The analysis results show that 83% of reviews have positive sentiment, 9% are negative, and 8% are neutral. The main aspects often discussed by visitors include the view and beauty of the bridge, historical and cultural value, accessibility and transportation, facilities and cleanliness, as well as tourist experiences and activities. Positive sentiments were mainly related to the beauty of the bridge's architecture and lighting, as well as its historical value. However, negative sentiment was mainly caused by cleanliness issues and traffic jams around the bridge. Based on these findings, several recommendations put forward include improving cleaning facilities, better traffic management, developing public facilities, and diversifying tourist activities. It is hoped that the implementation of these recommendations can improve the quality of the visitor experience and the attractiveness of the Ampera Bridge as a major tourist destination. This research provides valuable insights for tourism managers and local governments to improve the quality of services and facilities at the Ampera Bridge.
Machine Learning Approach for Early Diagnosis of Dyslexia Among Primary School Children: A Scoping Review and Model Development
Authors: Kurniawan Zaqi , Tiaharyadini Rizka
Published: September 2024

Dyslexia, a prevalent learning disorder among primary school children, often goes undetected until later stages, hindering academic progress and socio-emotional development. Early diagnosis is crucial for effective intervention. Machine Learning (ML) offers promise in developing accurate diagnostic tools. However, there's a scarcity of comprehensive reviews focusing on ML approaches for dyslexia diagnosis in this demographic. In this scoping review, we consolidate existing literature and present the development of a novel ML model that was customized for early dyslexia diagnosis. Utilizing Decision Tree, K-Nearest Neighbors (KNN), Logistic Regression, Naive Bayes, and Random Forest. The comparative analysis of ML methods for dyslexia detection in elementary school children reveals distinct strengths. Decision Tree shows robust precision: 92.31% for dyslexia-prone, 90.62% for diagnosed dyslexia, and 86.67% for no dyslexia detected, with corresponding high recall values of 90.57%, 87.88%, and 100%, respectively. KNN excels with an overall accuracy of 94.00% and perfect precision for undetected dyslexia (100%), with high precision and recall for dyslexia-prone and diagnosed dyslexia. Logistic Regression highlights significant predictors and achieves precision of 95.38% for dyslexia-prone and 88.24% for diagnosed dyslexia, with recall rates of 93.34% and 90.91%, respectively. Naive Bayes exhibits outstanding precision for no dyslexia and dyslexia-prone categories (100%), with slightly lower precision for diagnosed dyslexia (82.5%), but perfect recall for undetected and diagnosed dyslexia. Random Forest demonstrates balanced performance with precision ranging from 91.18% to 94.23% and recall from 92.31% to 93.94%, achieving an overall accuracy of 93.00%. These results underscore ML's potential in enabling early dyslexia detection, facilitating timely interventions to improve outcomes for affected children and advancing dyslexia diagnosis.
Fish Detection and Classification using YOLOv8 for Automated Sorting Systems
Authors: Kuswantori Ari , Suroso Dwi Joko
Published: September 2024

Automation plays a crucial role in scaling up freshwater fish cultivation to address the future threat of food scarcity and meet growing nutrition needs. The fish industry, in particular, develops automation in the sorting and selection processes. However, research on this technology's development is still very limited. In this work, we propose an approach for detecting and classifying fish running on conveyors. We use YOLOv8, which is the most popular and newest deep learning model for object detection and classification. We conducted our test using the KMITLFish dataset, a moving conveyor belt recording that encompasses common cultivated freshwater fish in Thailand along with some endemic species. As a result, our proposed method was able to accurately detect and classify eight types of fish at a conveyor speed of 505.08 m/h. Moreover, we developed this work using a ready-to-use AI platform, intending to directly contribute to the advancement of automatic fish sorting system technology in the fish industry.
Data Mining on Women's Clothing Sales in Market Places with the K-Means Clustering Algorithm
Authors: Dalimunthe Rizna Fitriana , Putri Raissa Amanda
Published: September 2024

Clothing is a necessity that must be used to cover the body with the main material made of fiber or textile so that the body is completely covered without gaps. Marketplace is an application or website that provides online buying and selling facilities from various sources. On the Shopee marketplace, there are many shops selling women's clothing from various groups and types of clothing. The K-Means Clustering algorithm in the research was applied to make it easier for sellers and buyers to find out what kind of women's clothing is currently selling well in the marketplace by grouping it into 3 clusters, namely the best-selling, best-selling, and least-selling. Research data was obtained from the Shopee marketplace with 3 variables, namely product price, number of sales, and buyer assessments of 4 types of women's clothing in the form of tunics, dresses, abayas/gamis, and shirts totaling 1200 data. The results of this research make it easier for buyers to make decisions and sellers to develop shop ideas.
Calculated PRA and PIRCHE Algorithm in Kidney Transplant Recipients
Authors: Ivana Dedinska , Andrej Ceres , Martina Schniederova , Karol Granak , Matej Vnucak , Monika Beliancinova , Patricia Kleinova , Timea Blichova , Milos Jesenak
Published: September 2024

Introduction

Calculated PRA testing in kidney transplantation has revolutionized the field by enabling a more accurate assessment of compatibility and risk prediction for AMR. On the other hand, The PIRCHE algorithm aims to identify the potentially immunogenic human leukocyte antigens (HLA) epitopes on the donor graft that are recognized by the recipient's HLA antibodies.

The aim of this analysis was to compare the actual immunological risk at the time of transplantation with the hypothetical risk that would be determined by cPRA and PIRCHE. Another aim was to compare this hypothetical risk also in the context of the development of DSA and the protocol graft biopsy at month 3.

Material and methods

In a group of 20 patients we recorded the real immunological risk determined at the time of transplantation according to the induction immunosuppression protocol of the Transplant-Nephrology Department of the University Hospital Martin and compared it with the hypothetical calculated risk according to cPRA and PIRCHE. We then compared the hypothetical risk with the protocol biopsy result and with any evidence of donor-specific antibodies at month 3 after the kidney transplantation.

Results

Under cPRA, the two patients we assessed as medium risk in real time would be classified as low risk. Both of these patients did not have DSA identified at month 3 and did not have rejection changes in the protocol biopsy. According to PIRCHE, the immunological risk would change from moderate to low in two patients, and even from very high to low in one patient. In none of these patients did we subsequently observe DSA formation at month 3 post-transplantation, and also all three protocol biopsies were free of rejection changes in these patients.

Conclusion

In our analysis we confirmed the importance of both immunological and non-immunological parameters for determining risk at the time of transplantation. For using PIRCHE score larger studies are required to confirm this strategy.
Functions of Adipocytokines and Link with Primary Glomerulonephritis
Authors: Monika Beliancinova , Timea Blichova , Patricia Kleinova , Matej Vnucak , Karol Granak , Ivana Dedinska
Published: September 2024

Adipocytokines are substances with endocrine functions produced by adipose tissue, playing crucial roles in regulating metabolic functions and inflammatory processes. Dysregulation of fatty tissue's endocrine functions and dysregulation of the production of adipocytokines such as adiponectin, leptin, fibroblast-stimulating factor, and others can lead to a low-grade systemic inflammation and an insulin resistance in patients. These conditions contribute to the pathophysiology of type 2 diabetes mellitus, atherosclerosis, arterial hypertension, metabolic syndrome, and other disorders. Conversely, these metabolic disorders exert feedback-regulatory effects on adipocytokines and their functions.

Glomerulonephritis encompasses a group of immune-mediated diseases characterized by inflammation of the glomeruli. Diagnosis can involve examining urine sediment, detecting autoantibodies, and identifying immune complexes in the blood. However, a kidney biopsy is required for definitive confirmation of glomerulonephritis and is considered the gold standard and a necessity in diagnosis.

Affecting the level of adipocytokines could be one of the new strategies for the pharmacological treatment of many diseases. Given a better understanding of their functions and molecular targets, adipocytokines may herald the emergence of new diagnostic approaches (1, 2). Monitoring the level of adipocytokines could contribute to a better patient management and thus become an auxiliary tool for predicting and diagnosing diseases.
IgA Nephropathy – Current and Future Perspectives in Treatment
Authors: Karol Granak , Matej Vnucak , Monika Beliancinova , Patricia Kleinova , Timea Blichova , Margareta Pytliakova , Ivana Dedinska
Published: September 2024

Immunoglobulin A nephropathy (IgAN) is the most common primary glomerulopathy in our adult population and is associated with a high lifetime risk of kidney failure. Recent years have succeeded in describing the pathogenesis of IgAN at the molecular level, where immune complexes containing specific galactose deficient IgA1 play an essential role. The gold standard in the diagnosis of IgAN remains renal biopsy followed by determination of a prognostic score using the Oxford classification.

A fundamental goal in the management of patients with IgAN is to optimize supportive therapy involving active lifestyle modification and renoprotective medications. The reno-protective drug menu has recently been expanded to include effective sodium-glucose cotransporter 2 inhibitors (SGLT2i), and additional agents are on the way. However, despite maximal supportive therapy, a wide range of patients remain at high risk of disease progression and require the deployment of immunomodulatory drugs. To date, however, we do not have high potency agents that are well tolerated and safe. This has led to the initiation of many studies to target the inflammatory process at different pathogenetic levels.

In this article, we summarize the current standards in the treatment of IgAN and present new promising options in the management of this disease.
The Monoclonal Gammopathies of Renal Significance
Authors: Patricia Kleinova , Timea Blichova , Monika Beliancinova , Matej Vnucak , Karol Granak , Ivana Dedinska
Published: September 2024

As a heterogeneous group of diseases, monoclonal gammopathy is typical for older age and is characterized by the presence of paraprotein in serum and urine. In addition to damage to the bone marrow, other organs are also affected, whereas in the case of monoclonal gammopathy of renal significance (MGRS), the kidneys are dominant. The clinical presentation of MGRS is diverse depending on the type of renal monoclonal gammopathy. The basis of the diagnosis is the detection of free light chains in the serum, along with electrophoresis and subsequent serum immunofixation. The kappa and lambda serum light chain ratio is evaluated in patients with MGRS within modified reference parameters. A kidney biopsy provides information on the extent of renal parenchymal involvement. The basis of therapy is chemotherapeutics with possible autologous stem cell transplantation to preserve kidney function.
The Role of the Nephrologist in the Treatment and Prevention of Nephrolithiasis
Authors: Matej Vnucak , Karol Granak , Monika Beliancinova , Patricia Kleinova , Timea Blichova , Ivana Dedinska
Published: September 2024

Nephrolithiasis is a disease with a high risk of recurrence: 50% within five years and up to 80–90 % within 10 years after the first episode. Often, with this diagnosis, there is only symptomatic treatment with the aim of expelling the kidney stone and removing the pain. In such patients, however, initial stratification of the risk of recurrence based on the risk factors present is essential. Every patient with nephrolithiasis, whether it is a single episode or recurrent, should follow general measures to prevent kidney stones. Depending on the results of the kidney stone analysis and the risk of recurrence, it is necessary to carry out a specialised nephrological metabolic examination which is performed by a nephrologist in Slovakia, with subsequent personalised recommendations depending on the cause of recurrent nephrolithiasis. These include dietary and regimen measures, as well as pharmacological treatment.

In the following article we summarize specific measures for individual types of nephrolithiasis, as well as basic preventive measures for the recurrence of kidney stones, with a focus on dietary risk and protective factors.
Development of New Formulation of Inosine Acedoben Dimepranol Powder for Oral Solution in Sachets
Authors: Kafedjiiski K. , Belcheva V. , Radeva-Ilieva M. , Grigorov E.
Published: September 2024

Inosine Acedoben Dimepranol (IAD) has immunomodulatory and antiviral properties and is used in the treatment of viral infections. The aim of the present study was to develop a powder for oral solution in sachets containing high dose IAD (1000 mg). The formulations were prepared by direct dry mixing of the components using the dilution principle. Optimal composition and process parameters for the development of high dosage powder were established. Solubility studies showed pH-dependent solubility of IAD. The prepared powder was characterized by a short reconstitution time. In addition, the oral solution exhibits good organoleptic properties and remains stable for 30 min. Stability studies indicated that the sachets remained stable under accelerated conditions for 3 months. In conclusion, the developed powder for oral solution in sachets containing 1000 mg IAD represents an economical alternative to other solid dosage forms with the advantages of rapid dissolution and convenient intake for the patient.
Ectopic Pancreatic Tissue Presenting as Gastric Tumor – A Case Report
Authors: Chernopolsky P. , Bozhkov V.
Published: September 2024

Heterotopic pancreas is a pancreatic tissue located outside the usual anatomical location of the pancreas. Heterotopic pancreas was first described in 1727 by Schultz in the diverticulum of the ileum. A 61-year-old man was admitted to the Second Department of Surgery with the following complaints: heaviness and pain in the epigastrium and right subcostal area, accompanied by nausea, vomiting, lack of appetite and weight reduction about 20 kg over the last few months. Intraoperatively tumor formation was found located in the pyloro-antral gastric area with approximate size 4/5 cm in diameter. The histological examination of the specimen revealed an uncapsulated formation of pancreatic glandular serine acres and single Langerhans islets among cystic dilated and deformed pancreatic ducts without epithelial cellular atypia.
Sarcoidosis of the Orbit: A Rare Clinical Case and Literature Review
Authors: Cekov A. , Kanev A.
Published: September 2024

Sarcoidosis is a systemic disease of still-unknown etiology in which characteristic granulomas develop in various parts of the body. Symptoms depend on the localization of the formations. The isolated orbital form, in which granulomas develop only in the orbit of the eye, is very rare and presents a challenge in terms of differential diagnosis. Treatment for the orbital form may include a conservative, surgical, or combined approach. The goal of surgical treatment is to completely remove the tumour formation, which achieves excellent results in many cases. The current article presents a clinical case of an isolated orbital form of sarcoidosis, in which surgical treatment was undertaken with complete removal of the granulomatous formation. In the postoperative follow-up, a complete reversal of the symptoms was observed without residual disturbances in vision or eye movements.
Current Aspects in the Diagnosis and Management of Catheter-Related Sepsis, Observed in Patients Undergoing Hemodialysis with a Tunneled Catheter
Authors: Borisov B. , Borisov D.
Published: September 2024

Tunnelled catheters have become established as a common vascular access in the last few decades. Besides the convenience associated with their use, we also reap the bitter fruits of their complications. Catheter-associated infections are part of daily life in dialysis units and we must know them well – early diagnosis, adequate behaviour and prevention. The aim of this short review is to highlight some modern aspects of diagnosis and treatment of catheter-associated infections, while also sharing our modest experience.
Determinants of the expression of sexual behaviour in mammals
Authors: Kondracki Stanisław , Górski Krzysztof , Iwanina Maria , Wysokińska Anna , Pietruszka Arkadiusz , Gaczarzewicz Dariusz , Stasiak Karolina
Published: September 2024

The article contains a literature review of facts and views on the strategies of sexual behaviour in mammals, taking into account the role of the animal’s species, sex, and position in the herd. The role of the senses, brain, and hormones in the expression of animals’ sexual behaviour is discussed, as well as the role of induction of the coitus reflex and social behaviour in the reproduction of present-day wild and domesticated animals. The analysis shows that the predominant strategy of sexual behaviour in females is to attract multiple potential partners to acquire the best male. The predominant strategies in the sexual behaviour of males of most mammalian species are aimed at fertilizing as many females as possible. Expression of sexual behaviour requires the generation of a set of characteristic sexual reflexes that indicate readiness to copulate and are sexually stimulating. Animals are differ in expressing their sexual behaviour. Some individuals react quickly and dynamically to sexual stimuli and immediately begin coitus, while others require longer preparation for successful coitus. Sexual behaviour influences the status of individuals in some species. Wild mammals with high expression of the sexual behaviour typical of a given species usually occupy a dominant position, which gives them an advantage in the search for breeding partners, access to food, and the expression of preferred social behaviour. Expression of sexual behaviour is stimulated by stimuli from potential sexual partners, which induce copulatory reflexes. These reflexes have been described in numerous animal species. They should be generated in the proper order and proceed without disruption for successful coitus and fertilization to occur.
Enhancing the feed efficiency of crop residues in ruminants: a comprehensive review
Authors: Kamal Mahmoud , Aldhalmi Ahmed K. , Abd El-Hack Mohamed E. , Elsherbeni Ahmed I. , Youssef Islam. M. , Hussein Saddam , Bai Binqiang , Xu Zhenhua , Hao Lizhuang , Mahrose Khalid M. , Taha Ayman , Cheng Yanfen
Published: September 2024

Worldwide, the production of agricultural residues exceeds five billion metric tons per year. Regardless of their many applications and substantial potential to increase crop and animal productivity, many crop residues, particularly in Asian, African, and Arabian nations, are burned. This detrimental practice limits the recycling of soil nutrients while increasing air pollution and wellness risks. Enhancing feed efficiency while simultaneously lowering production costs and increasing animal protein is a key objective of nutritional supplements in livestock feeding. Antibiotics have been utilized in farm animals at sub-therapeutic levels to increase feed use effectiveness and digestion, as well as animal welfare and performance. However, the present ban on antibiotics as nutritional supplements has boosted the search for substitutes, with natural feed additives considered cutting-edge options. On the other hand, feed that has undergone biological treatment improves animal productivity, feed intake, and digestibility. Nevertheless, the absence of agents and expertise and substrate weight decrease may result in a 40% dry matter loss limits application. In this review, we look at the importance of detrimental residue administration and the advancement and adoption of technologies to handle surplus residue.
Aquaculture and climate change: a data-driven analysis
Authors: Moss Amina , Peh Jia Hui , Afiqah-Aleng Nor , Segaran Thirukanthan Chandra , Gao Huan , Wang Panpan , Handayani Kiki Syaputri , Lananan Fathurrahman , Wei Lee Seong , Fitzer Susan , Azra Mohamad Nor
Published: September 2024

As climate change increasingly impacts the aquaculture industry, it poses challenges to production quality, management, and sustainability. This study provides a scientometric analysis of 47 years of research on aquaculture and climate change, analysing 4,785 articles and 224,895 references through CiteSpace software. The study highlights enduring themes such as “ocean acidification” and “global warming,” alongside emerging concerns like “deforestation” and “nutrient runoff,” reflecting new research directions. Notably, “seasonal variations” persist as a key focus due to their significant impact on aquaculture practices. Fourteen research clusters were identified, revealing a diverse array of topics from environmental performance to the effects of blue food systems and ocean acidification on marine life. Clusters related to “carbon sequestration,” “seaweed farming,” and “integrated multi-trophic aquaculture (IMTA)” emphasise the shift toward innovative practices aimed at mitigating climate impacts and enhancing sustainability. The analysis shows a need for more collaborative research, particularly from leading contributors such as the USA, Europe and Australia with underrepresented regions like Southeast Asia and Africa, to develop resilient aquaculture systems capable of adapting to climatic challenges. It advocates for the integration of new technologies and the exploration of sustainable aquaculture practices that minimise environmental impacts while enhancing global food security. This approach sets a direction for future research to promote adaptive strategies and technological innovations in aquaculture.
Streptomyces kunmingensis XK9 and galactooligosaccharide synergistically enhance growth performance, nonspecific immunity and disease resistance in striped catfish (Pangasianodon hypophthalmus)
Authors: Hien Nguyen Thi Thu , Huyen Vu Thi Bich , Trung Nguyen Thi , Phong Truong Quoc , Phuoc Man Hong , Hoa Bui Thi Hai , Hang Trinh Thi Thu , Le Dinh Thi Thu , Ha Le Thanh Hai , Hai Le Minh , Binh Ta Thi , Tam Pham Thi
Published: September 2024

The present study evaluated the effectiveness of the synergy of Streptomyces kunmingensis XK9 and galactooligosaccharides (GOS) in improving growth performance, nonspecific immunity, and protection of striped catfish (Pangasianodon hypophthalmus). Seven feed regimens were tested in striped catfish fingerlings, including commercial pellets supplemented with preparations S7, S8, and S9 containing XK9 at 107 CFU/mL, 108 CFU/mL, and 109 CFU/mL, respectively; G5 containing 5% GOS; S7G5, S8G5, and S9G5 including 5% GOS and XK9 at different doses of 107 CFU/mL, 108 CFU/mL, and 109 CFU/mL, respectively. After 3 months of treatment with different dietary regimens, weight gain, specific growth rate, weight gain rate, and feed conversion ratio were greatly improved in fish-fed diets containing S9, S8G5, and S9G5 (p<0.05). Nonspecific immune parameters, including total white blood cell, phagocytic activity, and phagocytic index, increased consistently in fish that were fed diets containing synbiotics S8G5 and S9G5 (p<0.05). Lysozyme and complement activity increased substantially in fish that were fed diets supplemented with S9G5 (p<0.05). The protective effect of XK9 and GOS on striped catfish was evaluated after 15 days of challenge with Edwardsiella ictaluri. The results achieved show that the cumulative mortality rate sharply decreased in fish fed a diet containing the synbiotic S9G5, down 2.17 times compared to the control group; pathogen density was lowest in tanks of fish that were fed regimens containing S8G5, S9G5, and S9 (p<0.05). The results suggest that synbiotics, including S. kunmingensis XK9 and GOS, have the potential to be applied in sustainable farming for the striped catfish industry.
Antibiotic alternatives to produce organic poultry meat as a safe food source and the impact of its consumption on human health: A review
Authors: Abd El-Hack Mohamed E. , Aldhalmi Ahmed K. , Abu-Hiamed Hind A. , Almarkhan Wafa D. , Alharbi Nouf A. , Alhassani Walaa E. , Alkholy Sarah O. , Kamal Mahmoud , Youssef Islam M. , Khalifa Norhan E. , Taha Ayman E. , Swelum Ayman A.
Published: September 2024

The scientific evidence on the effects of consuming organic chicken meat on human health is examined in this review article. Few studies particularly look at the effects of eating organic chicken meat on people’s health. Although the evidence is conflicting, they speculate that consuming organic chicken meat may reduce the incidence of obesity and allergy-related illnesses. Customers who purchase organic chicken meat generally have healthier eating habits. The significance of these discoveries for human health is unclear. Still, animal and poultry studies suggest that whether agriculture produces food from conventional or organic sources has different effects on early development and physiology. Omega-3 fatty acids and meat are more abundant in organic than in common meat. However, this is not nutritionally relevant compared to other dietary sources. The widespread use of pharmaceuticals is one of the primary drivers of antimicrobial resistance in traditional animal agriculture. It is possible to reduce this risk and potentially have significant positive effects on public health by preventing animal sickness and using antibiotics more sparingly, as is done in organic farming. The review highlights the importance of organic feeds as an effective and vital alternative to antibiotics in the poultry industry and their impact on human health.
Comparison of the Quality of Yoghurt Produced from Milk Containing A1 and A2 β-Casein
Authors: Radkowska Iwona , Najgebauer-Lejko Dorota , Filipczak-Fiutak Magda , Duda Iwona
Published: September 2024

A2 milk, characterised by the presence of only the A2 β-casein genotype, has recently been of great interest due to its potential health benefits, which are the subject of intensive scientific research. From the dairy industry standpoint, it is crucial to ascertain its functional and technological attributes. The objective of this study was to compare two types of yoghurt (A1 and A2 yoghurts), produced respectively from cows’ milk containing exclusively β-casein (β-CN) A1 (A1/A1) or A2 (A2/A2) genotypes, in terms of basic chemical composition, protein profile, amino acid composition, antioxidant capacity, sensory quality, acidity, instrumental texture and colour profiles, as well as rheological characteristics. The obtained results indicate that the β-CN polymorphism had no significant impact on the basic chemical composition, acidity, DPPH radical scavenging activity, ferric reducing antioxidant power (FRAP) or colour properties of the yoghurts. Nonetheless, the β-CN genotype did affect the textural, rheological, and sensory qualities of the acidic gels, with A2 yoghurt yielding gels exhibiting higher hardness, gumminess, improved consistency and viscosity, and overall sensory quality compared to the corresponding A1 treatment. These results indicate that A2 milk serves as a good raw material for fermented milk production, warranting further investigation.
Architects from Different Fields of Activities in Lithuania and their Specific Mindsets
Authors: Riaubienė Edita , Navickienė Eglė
Published: September 2024

The paper focuses on the heterogeneity of the Lithuanian architects’ community across different fields of practice, including building design, building design and other projects, urban design, interior design, and other underrepresented design or non-design activities. It is based on a sociological survey involving 450 practising architects in Lithuania. The study identifies the distinct attitudes of each activity group towards architecture, architectural practice, and professional paths, generalises the profiles of these activity groups, and detects shared similarities or discrepancies among them.

Architects involved in building design and those working on building design and other projects tend to share similar attitudes, forming the foundational worldview of the architectural community due to their quantitative prevalence. Interior designers and architects engaged in underrepresented design or non-design activities demonstrate relatively autonomous approaches. The latter group may either stand-alone or cluster with urban designers. The divergences in attitudes may lead to miscommunication within the professional community.
Solving Equations Systems Using the Penguins Search Optimization
Authors: Mafteiu-Scai Liviu Octavian , Mursa Andrei , Mafteiu-Scai Roxana-Teodora
Published: September 2024

The Penguin Search Optimization (PeSOA) is an optimization method based on collaborative hunting strategy of penguins. In this work, a solving linear equation systems method based on PeSOA is proposed. A dual population for PeSOA part was also tested. Experimental results obtained with our proposed method compared with those obtained with classical math methods, showed positive perspectives regarding possible extensions of the proposed method for systems of equations of larger dimensions. Conclusions as well as future research directions are also included.
Budget Deficit in a Growing Economy and Impossibility of Fiscal Collapse: A Continuous Time Analysis
Authors: Tanaka Yasuhito
Published: September 2024

Using a continuous time dynamic model of growing economy we will show the following results. 1) When people derive utility from their money holding (or government bond holding) along with their consumption, a budget deficit is essential to achieve and maintain full employment under stable prices or inflation in a growing economy. 2) If we take into account that government spending due to budget deficits increases financial assets held by the private sector, and then consumption will occur from assets in addition to consumption from income, even when the interest rate on government bonds is higher than the real economic growth rate, the ratio of government debt to GDP can not diverge and the divergence is naturally prevented by mild inflation. The required inflation rate is such that the interest rate of the government bonds is smaller than the weighted average of the rate of return on capital and the nominal growth rate. Since the interest rate of the government bonds is usually considered smaller than the rate of return on capital, this is not a very demanding requirement. Thus, we need not worry at all about the accumulation of government debt or about the divergence of the debt to GDP ratio, which is often taken as an indicator of fiscal collapse.
The effect of ethyl acetate extract from Atractylis flava Desf. on the gene expression of pro-inflammatory cytokines and oxidative stress markers in NR8383 alveolar rat macrophage cells
Authors: Melakhessou Mohamed Akram , Eddine Marref Salah , Zahra Doumandji , Ramia Safar , Marref Cherine , Imene Becheker , Olivier Joubert
Published: September 2024

Atractylis flava Desf. (AF) is common plant that is widely used for its anti- inflammatory and antioxidant properties. The purpose of this study was, therefore, to evaluate the cytotoxic effect and the molecular basis of antioxidant and anti-inflammatory effects of the ethyl acetate extract (AFEAE) obtained from the whole plant A. flava. This was accomplished through the use of NR8383 alveolar rat macrophage cells. Cultures of alveolar rat macrophage cells were treated with AFEAE (25–800 μg/mL), and cell viability was determined via WST-1 and LDH tests. In turn, the gene expression levels of nuclear factor κB (NF-κB), tumor necrosis factor-alpha (TNFα), interleukin 1 beta (IL1-β), interleukin 6 (IL-6), mitochondrial dynamin like GTPase (OPA1), Succinate dehydrogenase complex subunit A (SDHA) and neutrophil cytosolic factor 1 (NCF1) were assessed by applying RT-qPCR. The results show that ethyl acetate extracts of A. flava have non-cytotoxic effects, and the gene expression analysis demonstrates that AFEAF extracts generate significant downregulation of NF-κB, TNFα, IL-1 β, IL-6, NCF1, OPA1 and SDHA, compared to untreated cells. This study reveals that Atractylis flava ethyl acetate extract administration may be considered as a potential therapeutic strategy for inflammatory related diseases.
The influence of military actions on the Ukrainian territory on the work of the healthсare system
Authors: Gutor Taras , Kovalska Oksana , Zaremba Nataliya , Herasymovych Iryna , Diachyschyn Vira , Mysak Zoriana , Timchenko Nataliia , Negrych Nazar , Kovalska Iryna , Lysiuk Roman
Published: September 2024

The multi-sided damages caused by the large-scale invasion of Russia has become a great challenge for the medical care system of Ukraine. This research is aimed at studying, analyzing and summarizing data from scientific publications, personal experience, and open sources of relevant information concerning changes that occur in the work within Ukraine’s healthcare system and the activity of medical staff due to the Russian invasion. Special attention has been paid to processes related to relocations of medical staff and health care establishments, field hospitals as an important tool during martial law, as well as for the different types of support provided by the international partners of Ukraine. Data concerning demographic shifts in Ukraine due to the 2022 Russia-Ukraine war are also presented. Moreover, SWOT analysis of changes in the system of health care in Ukraine during martial law has been performed.
Risk factors in children with recurrent urinary tract infection among patients attending Al Zahra Teaching Hospital in Iraq
Authors: Khudhair Asmaa Hassan , Majeed Zahraa Mohammed , Mosa Heba Yehia , Mushin Hidhab Jawad , Nasrawi Alaa Jumaah Manji , Dhiaa Sara Fadhel , Rufaie Mohauman Mohammed Majeed Al
Published: September 2024

Urinary tract infections (UTI) are considered one of the most common infections that occur in the pediatric age group, leading to very serious morbidity and mortality. The detection of risk factors for urinary tract infection helps in the management and prevention of the recurrence of the infection. This study attempts to review current information on UTIs and determine different risk factors in association. To study the risk factors that are associated with recurrent urinary tract infection in different age groups of childhood among children attending AL Zahra Teaching Hospital.

A case-control study was conducted in AL Zahra Teaching Hospital during the period from October 1st, 2021, to July 30th, 2022. It included 76 children with highly suggestive histories, their examination, and results of the investigations (e.g. urine cultures), as well as 150 healthy children who were taken as controls. The controls were without a history of recurrent UTI and were similar to patients in age, sex and other risk factors that were mentioned in the study. A completed questionnaire was given to each child’s mother, and then the results were analyzed.

The study showed that non educated mothers OR (3.2), vesicouetrerall reflux OR (3), uncircumcised male OR (2.94), female gender OR (2.7), age groups below than 6 years OR (2.4), low social class OR (2.1) and residency in rural area (OR 2.5) contributed to UTI issues.

When compared to control groups, non educated mothers and vesicoureteral reflux were highly significant risk factors, and other risk factors such as female gender, uncircumcised male, age less than 6 years, low social class and rural area were significant for febrile recurrent urinary tract infection in children.
Exploring the synergistic effect in polyherbal chewable antacid tablets: formulation and evaluation study
Authors: Mankar Someshwar D. , Musale Prerana , Bhawar Sanjay B. , Siddheshwar Suhas S. , Dighe Santosh B.
Published: September 2024

Polyherbal chewable tablets of Phyllanthus emblica and Glycyrrhiza glabra were developed with the objective to formulate an effective, safe and convenient dosage form for acid-related disorders. A standard calibration curve was constructed for Polyherbal extracts through UV-Spectrophotometry, achieving an absorbance maximum at 275 nm. Compatibility between the drug and excipients was examined through FTIR studies. Various pre-compression parameters, like bulk density, tapped density, compressibility index, Hausner’s ratio and angle of repose, were assessed for the powder blend. The tablets were evaluated for post-compression parameters, such as thickness, hardness, friability, and weight variation and disintegration time. The drug release study was conducted in vitro. The acid-neutralizing capacity of the formulated batches was compared with marketed formulations. The calibration curve showed a high correlation coefficient (r2=0.9972), suggesting accuracy and reliability. FTIR analysis confirmed the compatibility between the drug and excipients. Pre-compression studies revealed an acceptable range for all parameters, indicating good flow properties. For instance, Carr’s Index for all batches varied from 14.31% to 24.41%, and the angle of repose ranged from 33.7 to 35.21 degrees. Post-compression parameters were within the standard limits with hardness between 4.9 to 6.1 kg/cm2 and friability less than 1% for all batches. In vitro drug release showed a gradual increase over time with PF9 achieving 98.63% release at 60 min. The acid-neutralization capacity was highest for the combined extract at 27.83±0.34 mEq/g and PF9 batch at 28.12±0.43 mEq/g, demonstrating their effectiveness in neutralizing acid.

The study successfully formulated a Polyherbal chewable tablet with optimized pre and post-compression parameters. The tablet exhibited promising in vitro drug release and an efficient acid-neutralizing capacity. It holds potential as an effective treatment option for acid-related disorders.