bluuebunny/crossref_metadata_2025 huggingface dataset:
The Immunology of Endometriosis and the Therapeutic Potential of Bispecific Antibodies: A Hypothesis
Authors: Mohseni Mahdi , Nasrollahzadeh Saravi Manouchehr , Oskouie Iman Menbari , Majidi Zolbin Masoumeh
Published: January 2025

Endometriosis is a chronic inflammatory disease characterized by the presence of endometrial lesions outside the uterus. Current treatment methods primarily focus on hormone-based therapy or invasive procedures. However, given the crucial role of the immune system in disease initiation and progression, there is an opportunity to explore new treatment approaches. Bispecific antibodies, which bind two different cells using their bivalent arms, have shown promise in treating cancers and autoimmune diseases. This study postulates that, due to the similarities in pathogenesis between endometriosis and the aforementioned diseases, a novel therapeutic method based on this new target could be introduced. This approach could potentially lead to a reduction in the limitations to patients' quality of life. In addition, it is important to highlight that future studies should prioritize the identification of specific binding markers on endometrial cells. This could contribute to the development of new diagnostic tools for the disease. Furthermore, the production of bispecific antibodies that selectively bind to these receptors on immune cells may prove effective in improving the immune response.
Metachronous Gallbladder Metastasis from Clear Cell Renal Cell Carcinoma with Atypical Immunohistochemical Profile: A Case Report and Comprehensive Literature Review
Authors: Moghaddam Nasibeh Sargazi , Germizadeh Bita , Farahangi Mahtab , Dehghani Sima , Mojallal Mehra , Houshdaran Farzad
Published: January 2025

Background: Renal cell carcinoma (RCC) is a malignancy known for its high metastatic potential, commonly spreading to the lungs, bones, brain, liver, and adrenal glands. Gallbladder metastasis from RCC is exceedingly rare and poses significant diagnostic challenges due to its asymptomatic nature and nonspecific imaging findings.
Case Presentation: We report the case of a 58-year-old Persian man with a history of clear cell RCC treated with left radical nephrectomy 34 months prior. The patient presented with right upper quadrant abdominal pain. Imaging studies, including contrast-enhanced computed tomography and ultrasound, revealed two hypervascular polypoid lesions within the gallbladder. An open cholecystectomy was performed due to the suspicion of malignancy. Histopathological examination confirmed metastatic clear cell RCC invading the gallbladder wall. Notably, immunohistochemical analysis showed tumor cells positive for cytokeratin 19, alpha-methylacyl-CoA racemase, and vimentin, but negative for paired box gene 8, cytokeratin 7, cytokeratin 20, and cluster of differentiation 117 (C-Kit). The absence of paired box gene 8 expression is atypical for RCC metastasis and posed a diagnostic challenge. The patient had an uneventful postoperative recovery but unfortunately passed away two months later due to a cerebrovascular accident unrelated to his oncological condition.
Conclusions: This case underscores the importance of considering gallbladder metastasis in the differential diagnosis for patients with a history of RCC presenting with gallbladder lesions. The atypical immunohistochemical profile observed expands the known spectrum of metastatic RCC presentations and highlights the necessity for comprehensive diagnostic evaluation. Surgical intervention through cholecystectomy can lead to favorable outcomes and should be considered in similar cases.
The Pediatric Clinical Pharmacy Practice: From Basic Knowledge to Advanced Clinical Judgment
Authors: Faghihi Toktam
Published: January 2025

The Article Abstract is not available.
Cost Analysis of Pharmacy Education Using Time-Driven Activity-Based Costing (TDABC) at The Pharmacy School of Isfahan University of Medical Sciences
Authors: Mogoei Farimah Rahimi , Amirsadri Mohammadreza , Rezayatmand Mohammadreza , Karimi Mohammadreza
Published: January 2025

Aims: This study aims to calculate the total cost of educational services delivered by the School of Pharmacy at Isfahan University of Medical Sciences, focusing on the cost associated with training pharmacy students using time-driven activity-based costing (TDABC).
Methods: Data were collected through designed forms, interviews, and direct observations. Financial, budgetary, and educational experts ensured compliance with administrative guidelines. A cost accounting system via TDABC was designed and implemented to allocate costs accurately.
Results: In 2019, the Faculty of Pharmacy at Isfahan University of Medical Sciences allocated an average of 2 billion and 50 million and 29 thousand rials per pharmacy student for educational and research purposes. This figure increased to 2 billion and 997 million and 845 thousand rials in 2020 and slightly decreased to 2 billion and 730 million and 260 thousand rials in 2021.
Conclusion: This study delves into a crucial issue of accurately estimating the cost of pharmacy education at the School of Pharmacy, Isfahan University of Medical Sciences. The research emphasizes the optimal utilization of resources, which can be achieved through data analysis and the adjustment of certain costs.
Reflections on the Efficacy of QF-PCR for Prenatal Screening in the Iranian Population: Implications for Global Practices
Authors: Neamatzadeh Hossein , Dastgheib Seyed Alireza
Published: January 2025

The Article Abstract is not available.
Applications of Artificial Intelligence Chatbots in Congenital Diplopodia: A Real-World Perspective on a Rare Case of Duplicated Lower Limb
Authors: Masoudi Ali , Omidi Amirhossein , Shams Seyedeh Elham , Yeganegi Maryam , Danaei Mahsa , Shiri Amirmasoud , Aghasipour Maryam , Aghili Kazem , Neamatzadeh Hossein
Published: January 2025

Background: This study examines the effectiveness of AI chatbot technology in assisting patients with congenital diplopia, focusing on a case study of a 16-month-old boy with duplicated lower limbs.
Methods: We assessed the performance of two AI chatbots—Sider Fusion AI and Perplexity AI—by analyzing their discharge summaries against a previously published clinical scenario. An orthopedic specialist, geneticist, and neonatologist evaluated the summaries for competence, accuracy, relevance, informativeness, support capabilities, and overall communication effectiveness.
Results: Both chatbots produced organized summaries that accurately reflected the diagnosis and surgical procedure outlined by Dr. Kitta. However, Sider Fusion AI surpassed Perplexity AI in organization and detail, offering structured summaries with clear headings and bullet points. It included comprehensive information on patient care, dietary advice, genetic testing, family support, follow-up instructions, pain management, and Ankle-Foot Orthosis (AFO) guidelines. In contrast, Perplexity AI's summary, while accurate, was less specific and clear, conflating care instructions with vague mobility information.
Conclusion: The findings suggest that while AI chatbots can aid in clinical documentation, their effectiveness varies significantly, with Sider Fusion AI providing a more structured and practical resource for families and practitioners dealing with congenital orthopedic disorders.
Budesonide-Surfactant Therapy for Neonatal Respiratory Distress Syndrome in Preterm Infants: A Systematic Review and Meta-Analysis of Respiratory Outcomes
Authors: Noorishadkam Mahmood , Ekraminasab Sedigheh , Shams Seyedeh Elham , Neamatzadeh Hossein
Published: January 2025

Background: Neonatal respiratory distress syndrome (NRDS) in preterm infants is a critical condition often necessitating urgent medical intervention. This meta-analysis assesses the efficacy and safety of combining surfactant with budesonide for treating NRDS in preterm neonates, emphasizing respiratory outcomes.
Methods: We performed a systematic review of databases (PubMed, Embase, Cochrane Library) following PRISMA guidelines from inception to July 30, 2024. Studies comparing budesonide-surfactant combination therapy to surfactant alone in NRDS were included. Respiratory outcomes evaluated included duration of mechanical ventilation, continuous positive airway pressure (CPAP), length of hospitalization, and frequency of a second surfactant dose. The outcomes were the incidence of bronchopulmonary dysplasia (BPD) and mortality rates. Data from eligible studies were pooled for meta-analysis using a random-effects model.
Results: Ten articles involving 920 infants in the treatment group and 1167 in the control group were analyzed. The combination therapy significantly reduced mechanical ventilation time, hospitalization duration, and CPAP use and decreased the need for a second surfactant dose. The treatment group also showed significantly lower mortality rates (OR = 0.694, 95% CI: 0.52, 0.927, P < 0.05) and BPD incidence (OR = 0.639, 95% CI: 0.525, 0.778, P < 0.001) compared to controls.
Conclusion: Budesonide-surfactant therapy for NRDS in preterm infants effectively reduces mechanical ventilation time and hospitalization. It also significantly lowers mortality rates, the need for a second surfactant dose, and BPD incidence, indicating its potential for widespread application in NICUs. Further large-scale trials are needed to validate these findings and assess long-term outcomes.
Evaluating Developmental Progress in Preterm Infants (4-12 Months) Following NICU Stay: An ASQ Analysis
Authors: Dehghan Azam , Golmohammadi Sepideh , Ghafarian Zahra , Moazen Homa
Published: January 2025

Background: Premature birth is a principal risk factor for developmental delay in infants. Infants born with a history of hospitalization in the neonatal intensive care unit (NICU) are at higher risk of developmental delay and require close monitoring. This study aimed to investigate and compare the developmental status of preterm infants (4-12 months old) with a history of hospitalization in the NICU using the Ages and Stages Questionnaire (ASQ).
Methods: This cross-sectional study was conducted from October 2016 to September 2020 in the NICU of Shahid Sadoughi Hospital in Yazd, Iran. One hundred preterm infants with a history of hospitalization in the NICU were selected using non-random sampling and were assessed at corrected ages of 4, 8, and 12 months. The data collection tool consisted of demographic information questionnaires and ASQ forms. The data were analyzed using SPSS 22 software and Excel.
Results: Of the 100 infants studied, 55% were boys and 45% were girls. The mean birth weight was 65.1480 ± 59.501 grams, and the mean discharge weight was 35.1746 ± 94.335 grams. At 4, 8, and 12 months, 16%, 14%, and 13% of the infants, respectively, had developmental delays in at least one domain. The mean length of hospital stay after birth was 83.35 ± 43.26 days, and the mean gestational age was 84.30 ± 97.20 weeks. These means differed significantly between infants with and without developmental delay in at least one domain at 12 months.
Conclusion: The presence of developmental delay in preterm infants with a history of NICU hospitalization increases the number of required interventions for these infants. Therefore, regular developmental assessments are essential in the first year of life to detect developmental delay early and provide timely interventions. Moreover, the continuation of growth and development in these infants should be evaluated.
The Complex Relationship between Stress and Gestational Diabetes: Mechanisms and Interventions for Maternal and Fetal Health
Authors: Javaheri Atiyeh , Ekraminasab Sedigheh , Shams Seyedeh Elham , Neamatzadeh Hossein
Published: January 2025

Gestational diabetes mellitus (GDM) is a prevalent complication during pregnancy that poses risks to both maternal and fetal health. This study aims to elucidate the intricate relationship between stress and the development of GDM, highlighting how stress-related hormonal fluctuations and behavioral changes—such as increased cortisol levels, inflammation, disrupted sleep patterns, and poor dietary choices— contribute to insulin resistance and glucose dysregulation. We examine the influence of stress on hormonal and lifestyle factors associated with GDM and evaluate interventions that manage stress-related metabolic disturbances. Elevated levels of stress hormones (like cortisol and adrenaline) and inflammatory markers (such as IL-6 and TNF-α) are linked to an increased risk of GDM due to their detrimental effects on insulin sensitivity. Our findings suggest that effective interventions, including mindfulness practices, cognitive-behavioral therapy, and regular physical activity, can reduce cortisol levels and enhance glucose regulation. This underscores the necessity of addressing both the metabolic and psychological dimensions of GDM. Current evidence supports the integration of stress-reduction strategies—such as mindfulness, cognitive-behavioral therapy, and exercise—into GDM management, as they can improve glycemic control by lowering cortisol and enhancing insulin sensitivity. Recognizing stress as a modifiable risk factor for GDM is crucial for improving maternal and fetal outcomes, emphasizing the importance of incorporating stress management into GDM prevention and treatment protocols.
A Case Report on the Outcome of Infantile Pompe Disease
Authors: Mirhosseini Naser Ali , Behjati-Ardakani Mostafa , Fakhimpour Parisa Sadat
Published: January 2025

Background: Pompe disease, or glycogen storage disease Type II, is an autosomal recessive disorder caused by a deficiency of acid α-1,4- glucosidase, leading to lysosomal glycogen accumulation in muscle tissues. Infantile Pompe disease (IPD) typically presents within the first weeks of life and is often fatal without enzyme replacement therapy (ERT). This report details the clinical course and outcome of a sevenmonth-old male diagnosed with IPD.
Case Presentation: A seven-month-old male infant, born full-term to consanguineous parents, was admitted due to a severe respiratory infection. Clinical features included hypotonia, swallowing difficulties, and failure to thrive (weight: 6 kg, <5th percentile). Laboratory tests showed elevated SGOT (95), SGPT (235), and CPK (700). An ECG revealed a short PR interval and prolonged QRS duration. Echocardiography indicated severe hypertrophic cardiomyopathy with systolic dysfunction. Enzyme assays confirmed critically low α-1,4- glucosidase levels (0.1 μmol/L/h), and genetic testing identified a homozygous mutation (c.1942 G > C), confirming Pompe disease. The infant passed away before ERT could be initiated.
Conclusion: This case highlights the challenges in diagnosing and managing Pompe disease in infants. The child's symptoms and lab results indicated a metabolic disorder, underscoring the multisystem impact of IPD. Rapid disease progression and consanguinity were significant factors. The delayed diagnosis led to a tragic outcome, emphasizing the need for early recognition and intervention. Timely ERT is crucial, as IPD can be fatal without it. This case underscores the importance of increased awareness and improved diagnostic protocols, particularly in consanguineous families and atypical presentations. Early diagnosis and intervention are essential for better outcomes.
STEM Learning Model Implementation Assisted by E-Module on Problem Solving and Mathematical Literacy Abilities
Authors: Nurul Chasanah Aprilia , Fatih 'Adna Syita , Ahza Julia Hanifah , Gunawan
Published: January 2025

This research aims to analyze the effect of STEM model learning on problem-solving ability and mathematical literacy ability. The research uses a quantitative approach with a Quasi-Experimental research design in the form of a Pre-Post Group Design. The research instruments are learning instruments, tests, interviews, and test question validation questionnaires. The data analysis results using the Wilcoxon test show that there is an influence of using the STEM learning model on problem-solving abilities and mathematical literacy with a p-value lower than 0.05. The STEM learning model improves the students' problem-solving abilities in the medium category (N-Gain = 0.4644) and mathematical literacy abilities in the medium category (N-Gain = 0.3889). These results conclude that the STEM learning model can be an alternative solution to improving students' problem-solving abilities and mathematical literacy.
The Role of Technology in Promoting Inclusive and Transparent Governance in Sri Lanka
Authors: Abeywardena Wickramasinghe Thiwankee
Published: January 2025

This study investigates the role of e-governance in promoting more transparency and inclusiveness in the public sector of Sri Lanka. This paper evaluates the effectiveness of such initiatives, like the e-Sri Lanka program, based on semi-structured interviews with policymakers, ICT experts, and citizens in Sri Lanka, supported by secondary data analysis. These findings indicate that automation cuts down corruption and, consequently, greatly improves the aspects of transparency, while significant digital literacy divides exist, along with other forms of infrastructure and questions of trust, especially among rural populations and other deprived groups of citizens. The study thus calls for holistic policy reforms, selective infrastructure development, and capacity-building programs as a prerequisite for overcoming these barriers. Emphasizing data protection and public-private partnership, the research underlines the need to align technological solutions with socio-economic realities across diverse populations. By addressing these gaps, Sri Lanka can unlock the full power of e-governance to enable effective, equitable, and transparent governance.
HIV/AIDS and Family Socio-Economic Development: An Insight from Stakeholders in Metropolitan Gusau, Zamfara State, Nigeria
Authors: Yahaya Maigemu Ahmad , Sani Adamu Rufai
Published: January 2025

Human Immune Deficiency Virus (HIV) and Acquired Immune Deficiency Syndrome (AIDS) is a social problem that affects the life of people in different sphere of human existence. This paper seeks to examine the impact of HIV/AIDS on socio-economic development an insight from stakeholders in Gusau metropolis. Specifically the paper explores how HIV/AIDS disrupt family as a social system; examine the impact of costs treatment on family and proffer solution to mitigate the impact of HIV/AIDS on family. Qualitative method of research was used in the course of this study. This research relies heavily on the open-ended tradition of participatory and qualitative research tools, using specifically In-depth Interviews (IDI). Interview was conducted with ten (10) stakeholders; three (3) from community; two (4) from Non Governmental organisations and three (3) from medical personnel.  The study finds out that HIV/AIDS disrupt family system in various ways. It is also finding out that cost of HIV/AIDS treatment negatively affect family income and consequently the study proffer recommendation on way out to HIV/AIDS. The study recommends poverty reduction, public enlightenment as major solution to HIV/AIDS.
Energy Consumption Prediction in the Steel Industry Using Principal Component Analysis and Regression Tree Methods
Authors: Septiani Mery , Hoendarto Genrawan , Tjen Jimmy
Published: January 2025

The steel industry is a major contributor to global energy consumption and greenhouse gas emissions, driving the need for enhanced efficiency. This study explore the use of Principal Component Analysis (PCA) combined with Regression tree (RT) techniques to predict energy consumption in the steel industry. PCA reduces data dimensionality, while RT addresses complex, non-linear relationships. Tested on a Kaggle dataset, the PCA and RT model achieved high accuracy, with a Root Mean Square Error (RMSE) of 0.67 and an accuracy rate of 90.82%, outperforming other methods in a comparative analysis. The model’s moderate training time of 1.18 seconds highlights its efficiency. Visual and comparative analysis confirmed the model’s strong alignment with observed energy consumption values and its balance between accuracy and computational efficiency. The PCA and RT model is an effective tool for predicting energy consumption in the steel industry, offering a practical approach to improving energy efficiency and sustainability. Future research could explore advanced techniques to further enhance predictive accuracy and model robustness.
The Effect of Risk Management and Leverage Towards Corporate Sustainability with Corporate Governance Mechanisms as a Moderation Variable
Authors: Tangke Paulus
Published: January 2025

This research analyzes whether Corporate Governance mechanisms can moderate the relationship between Risk Management and Leverage on Corporate Sustainability. This research is explanatory research that will test the causality relationship between variables using a Stakeholder theory approach. The population and sample for this research are non-financial companies listed on the Indonesia Stock Exchange for the period 2020 - 2022. The purposive sampling method was used for the sample selection in this research. The data analysis technique in this research uses moderated regression analysis and statistical test tools in the form of a normality test, classical assumption test, coefficient of determination test, F test, and t-test.
The results of this research show that Risk Management and Leverage both have a negative and significant effect on Corporate Sustainability. Corporate Governance can moderate the relationship between Risk Management and Corporate Sustainability. Corporate Governance can also moderate the relationship between Leverage and Corporate Sustainability.
Promoting green life for Viet Nam University students
Authors: Vu Thi Le Giang
Published: January 2025

This article focuses on the green lifestyle among university students, aiming to protect the environment and develop sustainable habits. International studies demonstrate that sustainable education, combined with practical community projects, is an effective way to change student behavior. In Vietnam, although awareness of green living has improved, limited infrastructure and financial difficulties remain significant barriers. To promote a green lifestyle, the article proposes solutions such as enhancing environmental education, investing in infrastructure, applying technology, and fostering international cooperation. Implementing these solutions can create a generation of environmentally conscious students, contributing to the sustainable development of society.
Random Forest Analysis for Predicting the Probability of Earthquake in Indonesia
Authors: Puspita Delastrada Dian , Steffi Sylvia , Hoendarto Genrawan , Tjen Jimmy
Published: January 2025

This research focuses on identifying risk zones by applying the Random Forest algorithm to predict the probability of earthquakes in Indonesia. The selection of this algorithm is based on its capacity to process voluminous, intricate, and non-linear data, which is frequently encountered in the context of seismic studies. In this study, a predictive model is constructed using historical earthquake data and geographic coordinates. The primary objective is to evaluate the effectiveness of the Random Forest algorithm in predicting earthquake probabilities across different regions of Indonesia. The analysis results indicate that the highest likelihood of earthquakes occurs in Maluku at 24.77%, followed by Nusa Tenggara at 18.34% and Sulawesi at 18.68%. The Random Forest algorithm achieved an accuracy rate of 90.78% in the prediction model, demonstrating its effectiveness in forecasting earthquake probabilities. These findings are expected to provide valuable insights for the government and stakeholders to develop improved disaster mitigation strategies in Indonesia. Furthermore, the methods used in this study can be applied to predict the probabilities of various types of natural disasters across different regions. on using larger datasets and examining the specific regions from which the data is collected.
Classifying AI-Generated and Original Images Using a Convolutional Neural Network Algorithm
Authors: Purba Ario Tua , Suparwito Hari
Published: January 2025

This The bread industry has seen advancements in distribution, making bread products easier to transport. With the implementation of delivery orders and effective picking processes, the bread industry can streamline the shipping process and make it easier for customers to obtain bread products. To address inefficiencies in distribution, companies can manage data related to bread, orders, and sales. In this context, Toko Roti XYZ, which has three branches (Branch A, Branch B, and Branch C), faces challenges in the distribution process. The unpredictability of bread demand at these branches is a major cause of repetitive distribution. Forecasting bread demand from these branches was performed using fuzzy time series, moving average, and exponential smoothing methods to determine the quantity of products to be distributed. Subsequently, distribution optimization was carried out using the Vehicle Routing Problem (VRP) method to achieve an optimal delivery schedule that affects distribution costs with a minimum result. The forecasting results with the smallest Mean Absolute Percentage Error (MAPE) were obtained using the moving average method, with an error of 23% for large bread and 9% for small bread from Branch A, an error of 17% for large bread and 14% for small bread from Branch B, and an error of 22% for large bread and 14% for small bread from Branch C. In the VRP method, number 1 represents the depot/production place, number 2 represents Branch A, number 3 represents Branch B, and number 4 represents Branch C. The scheduling routes obtained were 1-3-2-1 and 1-4-1, with a maximum of two distributions for the two available vehicles. With these optimizations, Toko Roti XYZ was able to save distribution costs by Rp. 35,492 and reduce distribution time by 116 minutes per day compared to the previous condition. Additionally, the optimization allowed Toko Roti XYZ to reduce total carbon emissions by 5,342 kg CO₂ per year.
Examining the Effect of Some Parameters Applied in Entrance Exams to Sport High Schools on Achievement
Authors: Altıntaş Sebahattin , Uzun Rıdvan , Sadat Tahir , Karadağ Hüseyin , Eriş Fatih
Published: January 2025

Aim: This study aims to examine certain parameters considered during the admission exams for sports high schools in relation to students’ success or failure in gaining admission.
Method: The study was conducted with 420 candidates (251 males, 169 females) who participated in the 2023-2024 academic year talent exam for Van Sports High School. Among them, 90 candidates (57 males, 42 females) were admitted, while 330 candidates (197 males, 133 females) were not. The candidates’ performance in the talent exam was evaluated based on their scores in a coordination course, 30-meter sprint, standing long jump, rhythm tests, and secondary school grade point averages (SGPAs). The data obtained were analyzed, and the results were considered statistically significant at the p0.05). Similarly, no significant difference was observed in sprint performance (Admitted = 10.27; Not Admitted = 9.93) (p>0.05). Although the standing long jump performance (Admitted = 5.91; Not Admitted = 5.54) showed a borderline difference, it was not statistically significant (p>0.05).
Conclusion: Among the parameters evaluated during admission to sports high schools, sports background and secondary school grade point averages stand out as the most significant in determining the success of candidates. It can be concluded that sports experience and SGPAs have a direct impact on success in gaining admission to sports high schools.
Heavy metal accumulation in soil and leafy vegetables irrigated with domestic wastewater in Vietnam
Authors: Thom Pham Thi , Khoi Nguyen Tuan , Na Phan Le
Published: January 2025

This study was conducted to evaluate the accumulation of heavy metals, including copper (Cu), lead (Pb), and cadmium (Cd), in soil and leafy vegetables irrigated with domestic wastewater. The surveyed vegetables included water spinach (Ipomoea aquatica), Chinese mustard greens (Brassica integrifolia), and Malabar spinach (Basella alba), grown over three consecutive seasons. Results showed that Cu accumulation in the vegetables ranged from 4.41 mg/kg to 5.62 mg/kg, Pb from 0.11 mg/kg to 0.13 mg/kg, and Cd from 0.02 mg/kg to 0.03 mg/kg. All values were below the safety limits set by Vietnam’s National Technical Regulation (QCVN), with thresholds of 30 mg/kg for Cu, 0.3 mg/kg for Pb, and 0.2 mg/kg for Cd. Similarly, heavy metal accumulation in the soil remained within the permissible limits under QCVN standards. The analysis further indicated that seasonal variations had minimal impact on heavy metal concentrations, suggesting that consistent wastewater management practices contributed to maintaining soil and crop safety. In addition, the research highlighted that water spinach accumulated slightly higher levels of heavy metals compared to the other vegetables, likely due to its faster growth rate and higher water absorption capacity. Despite this, the concentrations remained well within safety thresholds, affirming the viability of these crops for safe consumption. The study concludes that using domestic wastewater for vegetable irrigation does not lead to heavy metal accumulation beyond safe thresholds, supporting sustainable and safe agricultural practices. However, continued monitoring and appropriate wastewater treatment remain essential to ensure long-term safety, particularly as environmental and anthropogenic factors evolve.
Properties of boiled or steamed Procambarus clarkii girard and Procambarus zonangulus crawfish tail meat during refrigerated and frozen storage
Authors: Shackelford John B , McMillin Kenneth W , Bankston J David , Janes Marlene E , Lampila Lucina E
Published: January 2025

This research was conducted to address the different cooking methods of crawfish processors and determine the refrigerated or frozen shelf-life of cooked product. Live crawfish, (Procambarus clarkii girard and Procambarus zonangulus), were either boiled or steamed before storage of 11 days in refrigerated (3°C) conditions or six months in frozen storage (-18°C). There were minimal moisture, ash, protein, and fat differences with cooking type or storage type. There were no E.coli/coliforms in samples and aerobic plate counts were less than 3 log10 colony forming untis (CFU)/g after 6 mo frozen storage and higher than 3 log10 CFU/g after 3 days of refrigerated storage. Lipid oxidation by TBARS increased, but was less than 0.53 mg MDA/kg during storage. Peak force, total shear work, pH, L*, a*, b* color values were variable during storage, but not different between cooking treatments at each storage period. Mineral and fatty acid analyses were similarly variable. There were no differences between boiling and cooking crawfish for most variables and natural variation among the samples might explain variability in refrigerated and frozen storage. Processors can use either boiling or steaming to cook crawfish and store cooked crawfish for 3 days in refrigerated storage and for 6 weeks in frozen storage with minimal changes in properties.
Banknotes residues and thermoplastic starch as sustainable reinforcements for LDPE-based agricultural composites
Authors: Fialho Martins Marcela , Gabriel Trindade Julio , Pacheco Boaventura Tulio , Brey Gil Camila Silva
Published: January 2025

This study examines the development and characterization of composites comprising low-density polyethylene (LDPE), thermoplastic starch (TPS), and cellulose fibers sourced from recycled banknotes (BR). The composites were fabricated using extrusion and injection molding techniques, followed by an evaluation of their morphological, thermal, mechanical, and water absorption properties. The inclusion of BR fibers enhanced the mechanical performance of LDPE, notably improving tensile strength and elastic modulus, while the hydrophobic treatment of the fibers ensured minimal water absorption. The incorporation of TPS increased the composites' biodegradability potential but reduced tensile strength and increased water absorption due to its hydrophilic nature. Scanning electron microscopy revealed strong interfacial adhesion between the fibers and matrix and confirmed the complete dispersion of starch in TPS-containing samples. Thermogravimetric analysis highlighted the thermal stability of the composites and identified distinct degradation stages corresponding to the matrix, TPS, and fibers. These results indicate that the developed composites offer a viable solution for agricultural applications, balancing mechanical performance and environmental sustainability.
Genomic selection strategies in crop science for sustainable agriculture in Korea
Authors: Han Sang Hoon , Kim Yu-Na , Park Soo-Kwon , Lee Jung Jae
Published: January 2025

Genomic selection (GS) is an effective approach to address the growing need for increasing and improving food production and quality, respectively, under challenging environmental conditions. In Korea, GS significantly advanced major crops such as rice and wheat by improving critical agronomic traits. However, minor crops such as mung bean and sesame still require development because of limited resources and breeding infrastructure. These crops, though less prioritized, are vital for their nutritional and functional properties and contribute significantly to agricultural diversity and rural livelihoods. Addressing the research gap in minor crops is essential to prevent the loss of genetic diversity and to enhance their resilience to environmental changes. Unlike traditional selection methods, GS enhances the accuracy of complex trait selection, accelerates breeding cycles, and boosts genetic gain. It leverages genome-wide markers to predict genomic estimated breeding values (GEBVs) with high precision, enabling faster and more effective breeding strategies, especially for traits controlled by multiple genes. Genotyping techniques, such as Genotyping by Sequencing and Whole Genome Resequencing, are integral to GS, each offering specific benefits and limitations. Multispecies single nucleotide polymorphism arrays present a cost-effective solution for improving GS in minor crops by capturing the genetic diversity across species and enabling cross-species data integration. Expanding the GS in minor crops is essential for preserving genetic diversity, improving adaptability, and supporting sustainable agriculture and food security in South Korea. By addressing these challenges, GS can transform breeding programs, ensuring a sustainable and resilient agricultural system for the future.
Nanotechnology: A double-edged sword for future smart agriculture and phytopathological management in plants
Authors: Adhikari Dipan , Khatun Parvin , Koley Satyajit , Sen Moutushi , Ghosh Sudip Kumar
Published: January 2025

Modern technology that would boost agricultural outputs might therefore preserve the country's sustainable living standards by enhancing food security. With nanotechnology, it’s possible to produce foods of exceptional quality that also could increase the bioavailability of nutrients during the third decade of the twenty-first century which found usage in a variety of industries such as medical science, pharmaceuticals, food, and energy conservation. Nanotechnology is the synthesis, designing, characterizing, and utilization of assemblies, tools, and systems via directing the morphology and size variation at nanometer level (1 - 100 nm). Nanochemicals, nanopesticides, and nanofertilizers do increase yielding capacity without damaging agricultural land or irrigation water. Nanomaterials (NMs) are aimed protect crops from pests, microbial and fungal pathogens thereby lowering nutrient losses. Nanotechnology holds the potential to monitor soil quality in agricultural fields and sense crop health. Metallic Nanoparticles (Cu, Zn, Ni, Zn Fe, Ag, Al, Ti, and Al) can impinge on plant development, metabolism, and stress tolerance. This paper examines the role that nanoparticles (NPs) be playing while regulating oxidative stress, ROS turnover to mitigate abiotic stress in plants thereby emphasizing the advantages and of nanotechnology for better sustenance of future agriculture practices.
A review of the role of lectins in animal gametes and embryo development
Authors: Nadri Touba , Gambini Andres
Published: January 2025

Lectins are carbohydrate binding proteins found in most of the plants and in some animals. Sperm glycocalyx modifications are known to occur during capacitation and the acrosome reaction. These changes are very important for gamete recognition and fertilization in mammals but are not fully understood. Moreover, studies on lectin treatment of oocytes have yielded inconsistent effects on fertilization rates, suggesting a complex interplay of mechanisms. Beyond fertilization, the mitogenic properties of lectins are associated with germinal vesicle breakdown and cumulus cell expansion, indicating their involvement in oocyte maturation. Lectins have been also implicated in modulating cell adhesion, cell surface remodeling, and signaling pathways during early embryonic cleavage stages, influencing successful preimplantation embryo development. This article discusses the roof lectins in sperm, oocyte and embryo biology.
Digitalization of the professional training of foreign students in a Russian educational institution
Authors: Pozdnyakova Alina Aleksandrovna , Kolyadina Tatiana Evgenievna , Morozova Larisa Yurevna , Kalita Marina Evgenevna , Düzgün Fatih
Published: January 2025

The professional training of foreign students is currently strongly influenced by the "mobility factor", which is why digital technologies are pivotal for shaping a future specialist. The methodological possibilities of the digital environment allow not only to provide foreign students with the necessary knowledge and skills for interaction in a multicultural space, but also systematically build various aspects of professional competence, bringing it to the level of prolonged self-development. In this study, we analyzed the current concepts of digitalization of professional training of students to select practices that are suitable for integration into the Russian higher education system. The aim of this work is to challenge the negative view of digitalization of higher professional education and define conditions for the reform of the content of the professional training of foreign students. The following research methods were used: 1) review of the relevant literature; 2) analysis of modern pedagogical practices of teaching foreign students in remote conditions; 3) analysis of statistical data evaluating the state of digitalization of professional training in a university. As a result, we identified three groups of concepts for the digitalization of professional training: 1) self-regulated learning; 2) supportive learning; 3) generating learning. Despite the existing practical and methodological limitations, the latter appears to be the most promising.
Transformational teacher leadership: Self-perception of primary education teachers in Indonesia
Authors: Hariri Hasan , Mukhlis Hamid , Nurwahidin Muhammad , Rusdiani Atik , Ridwan
Published: January 2025

This study examines the self-perceptions of Indonesian primary education teachers as transformational leaders. A quantitative survey was conducted with 400 randomly selected teachers from Lampung Province, Indonesia to assess their transformational leadership (TL) practices using the Transformational Teaching Questionnaire (TTQ) adapted and validated for use in the Indonesian context. The instrument's reliability and validity were confirmed ensuring its robustness. This study found that 15 out of 16 items demonstrated strong factor loadings indicating good construct validity while one item was excluded due to low factor loading. Overall, teachers rated themselves highly on TL scales emphasizing the importance of respect and adherence to cultural norms within their educational practices. These results highlight the potential of TL in improving student outcomes and fostering school improvement. Promoting TL among teachers can create a more effective teaching environment positively impacting student success and overall school quality. The study also emphasizes the need for continuous professional development in TL for teachers. The study supports the integration of TL training in teacher development programs highlighting its relevance to educational policy and practice. Future research should include diverse educational contexts employ longitudinal designs to observe changes over time and incorporate multiple data sources to enhance the robustness of findings.
Challenges of learning speaking skills in online learning environments: A study of Jordanian EFL teachers’ perceptions
Authors: Alhumsi Mohammad Husam
Published: January 2025

E-learning opens a new horizon within educational contexts worldwide. Previous studies showed a dearth of research identifying EFL teachers’ perceptions of EFL learners’ hardships in speaking skills. Hence, this article investigates the Jordanian EFL teachers’ perceptions of the current challenges of learning speaking skills EFL learners experience in an e-learning environment. The research instrument was a cross-sectional questionnaire delivered to 218 Jordanian EFL teachers. Descriptive statistics, one-way ANOVA and an independent sample paired t-test were employed for data analysis. The results revealed that most Jordanian EFL teachers are aware of the current challenges of learning speaking skills in an e-learning environment. Such challenges involve a lack of vocabulary, motivation and self-confidence, grammatical mistakes, stress, anxiety and problems in pronunciation. Moreover, concerning research independent variables, the effect of gender and age did not record any significant differences whereas the academic degree and years of experience showed significant differences among Jordanian EFL teachers’ perceptions in favor of those who hold bachelor’s degrees (BA) and those who fall within the category of 5-10 years of experience. This paper recommends implementing remedial programs related to developing speaking skills.
Measuring front-liners’ perceived risks, benefits, practice, and misinformation on COVID-19
Authors: Hadid Wasfi Al
Published: January 2025

The COVID-19 pandemic has hit hard on many countries around the world and the numbers of infected patients and deaths secondary to this condition are increasing every day. These numbers included the healthcare workers, who provide care to needy patients. The knowledge and experience of those workers about the virus and its characteristics are very important to maintain good practices and decrease the rate of cross-infection with the virus. Assessing elements influencing healthcare professionals’ safe practice, including perceived risks-benefits, knowledge, and practice about COVID-19 of 187 healthcare workers from different Jordanian hospitals currently providing care to patients infected with the virus. The online questionnaire addressed perceived risk benefits, knowledge, and practices, which were endorsed by the Centre for Disease Control and Prevention and are necessary for safe practice among healthcare front liners. All participants were providing care to patients with COVID-19 and were at work during the data collection. The whole recruitment and filling of the study survey were completed using online services, including emails and WhatsApp. Front liners have ambiguity regarding the nature of the virus. Limitations were found in the knowledge of healthcare workers in virulence and biological characteristics of the virus, the personal safety spacing, and how to prevent cross-infections. Skills and practices also reflect some deficits, which might influence safety practices. Front liners should be provided with the needed training and knowledge before caring for a patient with COVID-19. More efforts are needed to ensure meeting these objectives.
Discovering polyimides and their composites with targeted mechanical properties through explainable machine learning
Authors: Hu Weilong , Jing Enzhe , Qiu Haoke , Sun Zhao-Yan
Published: January 2025

Polyimides (PIs) are widely used in industries for their exceptional mechanical properties and thermal resilience. Despite their benefits, the traditional development process for PIs is time-consuming, often lagging behind the increasing demand for materials with tailored properties. In this study, we introduce a machine learning-based approach to predict and optimize the mechanical properties of PI materials and their composites. We developed six predictive models to assess PI structures under various conditions, aiming to enhance our understanding of PI mechanical behavior and facilitate the discovery of high-performance PI structures. By analyzing the substructures within top-performing PIs, we identified key structural motifs that contribute to improved tensile strength, modulus, and elongation at break. Furthermore, we examined the influence of fillers on PI composites, revealing that rigid fillers such as SiO2 and graphene oxide (GO) significantly improve mechanical properties, with GO showing versatile enhancement across multiple mechanical properties. We then screened 800,000 virtual PI structures by using our predictive models, identifying several candidates with targeted mechanical properties. These findings provide a basis for the future experimental validation of optimal PI structures and fillers, offering an efficient pathway to accelerate the design of PI materials with targeted mechanical properties. Our study can also be extended to other materials research, serving as a valuable paradigm for the design of polymers and their composites.
A Novel Multi-Spindle Machine Tool Configuration Design
Authors: Rossoli Kianoosh , Ibaraki Soichi , Fujii Kazuki , Kawahara Kengo
Published: January 2025

To drastically enhance the efficiency of conventional machine tool configurations, a novel multi-spindle configuration is proposed. The key advantage of this configuration is that all spindles can simultaneously machine a single workpiece, whereas in conventional multi-spindle machine tools, each spindle is able to machine only a separate workpiece. To avoid the risk of collision among the spindles during machining operation, parallel linear axes, each of which has a vertical axis and a spindle, are regulated synchronously with a rotary table to follow arbitrarily given 2.5-dimensional tool paths. The command trajectory generation algorithm is presented as well as example numerical simulations. A possible problematic issue with the proposed multi-spindle machine tool configuration is discussed, and a practical solution with a case study simulation is presented.
Development of Shape-Mimetics Wireless Monitoring System by 3D Printer and its Application to Grasp-Less Handling Based on Ball Rolling Motion with a Dual-Arm Robot and Egg Washing Inspection Process
Authors: Hanai Hiroaki , Mita Yuma , Wada Yuiga , Nakagawa Masao , Hirogaki Toshiki , Aoyama Eiichi
Published: January 2025

This study focuses on the development and implementation of a shape-mimetics wireless monitoring system. A 3D printer is used to monitoring device, which mimics these shapes, is referred to as a shape-mimetics wireless monitoring robot. The effectiveness of this system depends on the complexity of both the shape and the environment. When both factors are relatively simple, trajectory estimation can be performed using mathematical modeling. This was validated through experiments involving the motion of a ball on a horizontal plane using grasp-less handling. In contrast, when both factors are complex, vibrations and external forces can be directly monitored as raw data in a straightforward manner. This was demonstrated during the egg washing and inspection process, which served as a complex, real-world application. These results show that the shape-mimetics wireless monitoring system can achieve continuous trajectory estimation and monitor vibrations and external forces at a higher sampling frequency compared to conventional vision-based monitoring systems. The findings suggest that the proposed system could be beneficial in a wide range of industries, including manufacturing and food processing.