Scientific African最新文献

{"title":"Spatiotemporal variability and trends in rainfall and temperature in the central highlands of Ethiopia","authors":"Marshet Tefera ,&nbsp;Engdawork Assefa ,&nbsp;Shiferaw Muleta","doi":"10.1016/j.sciaf.2026.e03198","DOIUrl":"10.1016/j.sciaf.2026.e03198","url":null,"abstract":"<div><div>This study investigates the spatiotemporal variability and trends of rainfall and temperature in the Ejerie district, Ethiopia, focusing on the Dega and Weyina Dega agroecological zones. Gridded monthly rainfall data (1990–2020) and temperature records (1990–2018) from the Ethiopian Meteorology Institute were analyzed at a 4 × 4 km resolution. Variability was assessed using mean, standard deviation, coefficient of variation (CV), precipitation concentration index (PCI), and standardized rainfall anomaly (SRA). Trend analysis was conducted using the Mann–Kendall test (MK test) and innovative trend analysis (ITA). Results showed that Dega receives 1245 mm of annual rainfall, while Weyina Dega receives 907.8 mm, with both regions exhibiting low rainfall variability. Rainfall is concentrated in the summer season, followed by Belg and Bega, with notable monthly variability in November and December. The PCI analysis indicated irregular rainfall distributions, with Dega showing 87.09% irregular and 9.68% strongly irregular distributions, while Weyina Dega showed 83.87% irregular and 3.23% strongly irregular distributions. SRA analysis revealed that 83.27% of Dega and 84.48% of Weyina Dega did not experience drought, with minor drought occurrences observed in both regions. Temperature analysis showed significant seasonal differences, with Dega experiencing cooler temperatures than Weyina Dega, which has a warmer climate. Both the MK test and ITA methods yielded consistent temperature trends, with the exception of minor discrepancies in Bega season temperatures. These findings emphasize the importance of localized climate studies to inform area-specific adaptation strategies for agriculture and water resource management in the region and climate resilient livelihood.</div></div>","PeriodicalId":21690,"journal":{"name":"Scientific African","volume":"31 ","pages":"Article e03198"},"PeriodicalIF":3.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146188170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparative evaluation of composting and solarization techniques for mitigating antibiotic residues, and resistance genes in poultry manure","authors":"Paul Appiah Sekyere ,&nbsp;David Azanu ,&nbsp;Osei Akoto","doi":"10.1016/j.sciaf.2026.e03228","DOIUrl":"10.1016/j.sciaf.2026.e03228","url":null,"abstract":"<div><div>The improper management of poultry waste poses a growing environmental and public health threat due to accumulation of antibiotic residues, pathogenic microorganisms, and antimicrobial resistance genes (ARGs). This study investigated the effectiveness of composting, open solarization, and closed solarization in transforming poultry manure into safer, nutrient-rich material for agricultural use. Poultry waste mixed with sawdust (2:1 w/w) was treated over 60 days, with weekly monitoring of physicochemical properties, microbial load, and concentrations of tetracycline, sulfamethoxazole, ampicillin, and neomycin sulphate. Composting achieved complete degradation (100%) of all antibiotics within 50 days. For closed solarisation, ampicillin was completely removed within 60 days, while the remaining antibiotics showed varying removal efficiencies. Antibiotic removal efficiencies for open solarization ranged from 93% to 97% within 60 days. Microbial loads declined significantly under composting and closed solarization, with composting reducing counts of <em>Escherichia coli</em> isolates from 1.15 × 10¹¹ CFU/mL to 9.29 × 10¹⁰ CFU/mL from untreated and early-stage compost samples. Antibiotic sensitivity tests revealed a reduction in ticarcillin-resistant <em>E. coli</em> from 50% to 17% post-treatment, and no new resistance was observed for amikacin, meropenem, and norfloxacin in composted samples. All treatments improved nutrient content, particularly potassium, which rose from 1.52% to 6.03% under composting. Statistical correlations show temperature and moisture significantly influenced antibiotic degradation and microbial reduction (<em>p</em> &lt; 0.05). Closed solarization maintained better thermal and moisture conditions than open solarization, enhancing treatment efficacy. These results confirm composting and closed solarization as robust, climate-sensitive strategies for antibiotic residue mitigation, microbial safety, and sustainable nutrient recovery in poultry waste management.</div></div>","PeriodicalId":21690,"journal":{"name":"Scientific African","volume":"31 ","pages":"Article e03228"},"PeriodicalIF":3.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146188191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine Learning– driven discovery and optimization of PI3Kδ inhibitors for diffuse large B-cell lymphoma","authors":"Josiah Joseph Isah ,&nbsp;Adamu Uzairu ,&nbsp;Sani Uba ,&nbsp;Muhammad Tukur Ibrahim","doi":"10.1016/j.sciaf.2026.e03206","DOIUrl":"10.1016/j.sciaf.2026.e03206","url":null,"abstract":"<div><div>Diffuse large B-cell lymphoma (DLBCL) remains difficult to treat, as current PI3Kδ inhibitors are limited by toxicity and poor metabolic stability. To address these challenges, we applied a machine learning (ML)–guided design framework integrating predictive quantitative structure–activity relationship (QSAR) modelling, absorption, distribution, metabolism, excretion, and toxicity (ADMET) profiling, molecular docking, and molecular dynamics simulations. A curated dataset of 3268 compounds was reduced to 9 descriptors, supporting a robust Random Forest model that achieved strong predictive performance on an external test set (R² ≈ 0.63; concordance correlation coefficient (CCC) ≈ 0.76), while maintaining high training set fit (R² = 0.94). This indicates good generalization to unseen compounds. Scaffold prioritization nominated Compound 9, which showed strong docking affinity (–9.5 kcal/mol) and favourable pharmacokinetic predictions. Guided optimization produced analogues 9a–9c, of which 9b demonstrated superior absorption (96.6%), reduced CNS penetration, and stable hydrogen bonding with VAL828 in 100-ns molecular dynamics (MD) simulations (root-mean-square deviation [RMSD] ∼1.2–1.8 Å). Molecular mechanics–generalized Born surface area (MM-GBSA) analysis confirmed favourable binding free energy (–77.6 kcal/mol), with 9b achieving enhanced stability through balanced energetic contributions. Collectively, these results highlight Compound 9b as a computationally prioritized lead for further experimental evaluation and illustrate the power of machine learning–driven, simulation-validated pipelines in accelerating kinase inhibitor discovery for aggressive lymphomas. Experimental validation is needed to confirm these predictions.</div></div>","PeriodicalId":21690,"journal":{"name":"Scientific African","volume":"31 ","pages":"Article e03206"},"PeriodicalIF":3.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146188302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clean coal technologies as transitional buffers in South Africa’s just energy transition: Safeguarding livelihood amid decarbonisation","authors":"Chandima Gomes","doi":"10.1016/j.sciaf.2026.e03210","DOIUrl":"10.1016/j.sciaf.2026.e03210","url":null,"abstract":"<div><div>South Africa’s heavy dependence on coal, which supplies more than 85% of electricity generation and sustains over 90,000 direct mining jobs, places the country at the centre of the global challenge of reconciling decarbonisation with socioeconomic stability. This paper critically examines the role of Clean Coal Technologies (CCTs) as transitional buffers within South Africa’s Just Energy Transition (JET) framework. Using comparative case studies from China, the United States, India, and Australia, and integrating techno-economic indicators, lifecycle emissions, and employment metrics, the analysis evaluates the extent to which CCTs can moderate job losses while reducing carbon intensity. The technologies assessed include amine-based carbon capture (efficiency loss of approximately 9.5 percentage points and costs around USD 61/tCO₂), calcium looping (efficiency penalty of about 6.7–7.9%), and coal-to-hydrogen hybrid systems achieving up to 90% CO₂ removal under specific configurations. The results indicate that although CCTs can deliver short-term emissions reductions and employment continuity, their contribution is constrained by high retrofit costs (USD 500–1,200/kW), partial decarbonisation, and limited scalability. Renewable energy pathways, by comparison, offer higher employment multipliers, lower levelised costs of electricity, and substantial environmental and health co-benefits, but require extensive reskilling and institutional reform. The study concludes that CCTs may serve a strictly time-bound strategic role in coal-dependent regions such as Mpumalanga and Limpopo, provided they are embedded within explicit exit strategies and complemented by investments in workforce transition, decentralised renewables, and economic diversification.</div></div>","PeriodicalId":21690,"journal":{"name":"Scientific African","volume":"31 ","pages":"Article e03210"},"PeriodicalIF":3.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146188268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploration of novel molecular inhibitors for Monkeypox virus with a fragment-based drug design approach","authors":"Amine Ballari ,&nbsp;Rachid Haloui ,&nbsp;Khadija Khaddam Allah ,&nbsp;Kaouakeb El Khattabi ,&nbsp;Abdelmoula El Abbouchi ,&nbsp;Samir Chtita ,&nbsp;Souad El khattabi","doi":"10.1016/j.sciaf.2026.e03223","DOIUrl":"10.1016/j.sciaf.2026.e03223","url":null,"abstract":"<div><div>In August 2024, the world health organization declared Monkeypox virus (MPXV) a public health emergency of international interest due to a significant increase in reported cases and the number of deaths. The MPXV is a transmissible disease spreading from animals to people via scratches, bites, or as food, then people spread it to other people by close contact including sexual activities, massages, kissing, day-to-day household contact, and caring for people with MPXV. This work aims to find novel MPXV receptor inhibitors with an application of fragment-based drug design strategy. A screening of &gt;269,000 fragments from various online data bases has been conducted to determine their affinity for binding MPXV. Employing the 2022 version of Schrödinger software, a total number of 1600 fragments with the highest docking scores have been submitted to a fragment linking to generate 100 new molecules. The MPXV binding affinity and ADMET features of the top10 docking score ligands were then examined in more comprehensive detail. Lastly, the appropriate ligands were chosen for a molecular dynamics study in order to evaluate the stability of the ligand-receptor complex in the best three molecules. The discovered ligands might be investigated further in the field of Monkeypox inhibitor drug development.</div></div>","PeriodicalId":21690,"journal":{"name":"Scientific African","volume":"31 ","pages":"Article e03223"},"PeriodicalIF":3.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146187812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of simultaneous frying of food items on the concentrations and risks of PAHs in edible oils","authors":"Ufuoma A. Igbuku ,&nbsp;Eze W. Odali ,&nbsp;Beatrice O. Peretiemo-Clarke ,&nbsp;Chinedu J. Ossai ,&nbsp;Chukwujindu M.A. Iwegbue ,&nbsp;Godwin E. Nwajei ,&nbsp;Bice S. Martincigh","doi":"10.1016/j.sciaf.2026.e03209","DOIUrl":"10.1016/j.sciaf.2026.e03209","url":null,"abstract":"<div><div>This study evaluated the effect of simultaneous frying of food items on the concentrations and risks of PAHs in different types of frying oils. The PAH concentrations of these oils were quantified prior to frying and after each frying cycle by gas chromatography-mass spectrometry (GC–MS). The Ʃ16 PAH concentrations in the oils before and after frying ranged from 20 to 120 µg kg^-1 and 30 to 250 µg kg^-1 respectively. There were substantial changes in the concentrations of individual PAHs and homologues in these edible oils after four frying cycles. The changes in the PAH concentrations after the frying series were in the sequence of palm olien (POL) &gt; soybean oil (SBO) &gt; groundnut oil (GNO) &gt; coconut oil (CNO) &gt; canola oil (CAO) &gt; sunflower oil. (SFO) &gt; olive oil (OLO) &gt; palm oil (PMO). The observed order is controlled by the interplay among antioxidant composition, degree of unsaturation, and smoke point of the oils. The average changes in the Σ16 PAH concentrations of oil used repetitively for simultaneous frying of different food items were by far higher than the average changes in the PAH concentrations of oil used repetitively for frying of a single food item. The concentrations of the high molecular weight PAHs in the unfried and fried oils were above the limits of 2 µg kg^-1 and 5 µg kg^-1 for the individual PAHs and their sum, respectively, set by the European Union. The incremental lifetime carcinogenic risk (ILCR) assessment resulting from the ingestion of the unfried and fried edible oils indicates low carcinogenic risk.</div></div>","PeriodicalId":21690,"journal":{"name":"Scientific African","volume":"31 ","pages":"Article e03209"},"PeriodicalIF":3.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147395171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Synergistic in vitro anticancer activity of doxorubicin-betulinic acid against neuroblastoma (SH-SY5Y) and lung carcinoma (A549) supported by in silico targeting of ALK","authors":"Joel Ojogbane Onoja ,&nbsp;Pirun Mikled ,&nbsp;Jude Y. Betow ,&nbsp;Warinthorn Chavasiri","doi":"10.1016/j.sciaf.2026.e03285","DOIUrl":"10.1016/j.sciaf.2026.e03285","url":null,"abstract":"<div><div>Neuroblastoma, a heterogeneous pediatric malignancy of neural crest origin, continues to exhibit poor prognosis in high-risk cases despite advances in multimodal therapy. Likewise, lung cancer, particularly non–small-cell lung carcinoma (NSCLC), frequently develops resistance to conventional chemotherapeutic agents. These challenges highlight the urgent need for novel therapeutic strategies with improved safety, selectivity, and the ability to target key molecular drivers of tumor progression. Combination approaches involving standard chemotherapeutics and bioactive phytochemicals represent a promising avenue for enhancing anticancer efficacy. In this study, betulinic acid (BA) was isolated for the first time from the ethyl acetate extract of <em>Erythrophleum suaveolens</em> (Guill. &amp; Perr.) Brenan using column chromatography and thin-layer chromatography. Structural characterization was achieved through spectroscopic analyses, including ¹H-2D NMR and EI-MS. The cytotoxic activity of BA was evaluated using cell viability assays against SH-SY5Y human neuroblastoma and A549 human lung carcinoma cell lines, with doxorubicin (DOX) employed as a reference drug. Furthermore, molecular docking studies were conducted to investigate the interaction of BA with human anaplastic lymphoma kinase (ALK) in complex with crizotinib (PDB ID: <span><span>2XP2</span><svg><path></path></svg></span>). Betulinic acid (3β‑hydroxy-lup-20(29)-en-28-oic acid) exhibited significant cytotoxic activity against both cancer cell lines. In SH-SY5Y cells, BA demonstrated an IC₅₀ value of 61.65 ± 2.74 µM, markedly lower than that of doxorubicin (212.9 ± 32.63 µM), indicating superior potency. In A549 cells, BA showed an IC₅₀ of 26.86 ± 1.41 µM, comparable to doxorubicin (22.02 ± 3.14 µM). Notably, BA significantly potentiated DOX-induced cytotoxicity, particularly in SH-SY5Y cells, suggesting a strong chemosensitizing effect. Molecular docking revealed that BA binds within the ALK active site with a moderate binding energy (−5.149 kcal/mol), compared with crizotinib (−9.784 kcal/mol) and doxorubicin (−7.119 kcal/mol) supporting ALK as a potential molecular target. Overall, these findings highlight betulinic acid as a promising natural-product scaffold with chemosensitizing potential and warrant further mechanistic and <em>in vivo</em> investigations toward its development for pediatric and adult oncology.</div></div>","PeriodicalId":21690,"journal":{"name":"Scientific African","volume":"31 ","pages":"Article e03285"},"PeriodicalIF":3.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147395181","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MultiModal-ArabicNER: A deep learning framework for semantic knowledge extraction from degraded historical arabic manuscripts","authors":"Hassan Hazimze,&nbsp;Salma Gaou,&nbsp;Khalid Akhlil","doi":"10.1016/j.sciaf.2026.e03257","DOIUrl":"10.1016/j.sciaf.2026.e03257","url":null,"abstract":"<div><div>Historical Arabic manuscripts represent invaluable cultural heritage that remains computationally inaccessible due to physical degradation and linguistic complexity. Existing approaches treat document enhancement and semantic analysis as separate stages, limiting their effectiveness on severely degraded texts. This paper introduces a novel multimodal framework that uniquely integrates degradation-aware feature fusion with hierarchical Arabic morphological analysis throughout the entire processing pipeline. Our methodology combines multi-scale document enhancement, specialized named entity recognition, and graph-based relation extraction specifically adapted for Classical Arabic texts. Extensive experiments on the VML-HD dataset demonstrate significant improvements: document enhancement achieves 32.4 dB PSNR and 0.891 SSIM, hierarchical NER attains F1-score of 0.792 (5.5 % improvement), and relation extraction reaches F1-score of 0.683 (4.1 % improvement over baselines). Cross-dataset evaluation shows performance variation across different manuscript collections, with domain adaptation techniques helping to maintain reasonable effectiveness. Our findings indicate that integrating visual and textual features at multiple processing stages supports the analysis of historical Arabic manuscripts. This approach facilitates computational analysis of Arabic manuscript collections, supporting digital humanities and cultural heritage preservation efforts.</div></div>","PeriodicalId":21690,"journal":{"name":"Scientific African","volume":"31 ","pages":"Article e03257"},"PeriodicalIF":3.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147395288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using factor analysis and regression technique to predict cost overrun in road network construction projects","authors":"Taher Ammar ,&nbsp;Mohamed Abdel-Monem ,&nbsp;Karim El-Dash","doi":"10.1016/j.sciaf.2025.e03172","DOIUrl":"10.1016/j.sciaf.2025.e03172","url":null,"abstract":"<div><div>Road construction projects in Egypt, as in many other developing African countries, frequently experience significant cost overruns. This study systematically analyzes the causes of such overruns to enhance understanding and improve risk management practices in the field. The research identifies key factors contributing to cost overruns and examines their relationships. A prediction model was developed to help estimate appropriate contingency costs by evaluating the impact of these factors on the overall project cost. Using Factor Analysis (FA), Regression Analysis (RA), and Regression Model (RM), the study assessed the significance of various cost overrun factors. The findings indicate that poor material quality, scope-of-work changes, and quantity variations are the primary causes of cost overruns in road construction projects. This study benefits both local and international researchers and practitioners by providing actionable insights. It highlights the practical implications of the findings and emphasizes key features that decision-makers should consider to improve the performance of the road network construction sector. As a critical driver of urban development and modern community establishment, enhancing the efficiency of road construction is essential for sustainable growth and infrastructure development. The study also helps the government address the risks associated with road network projects during the pre-tendering phase, enabling it to better manage its financial resources.</div></div>","PeriodicalId":21690,"journal":{"name":"Scientific African","volume":"31 ","pages":"Article e03172"},"PeriodicalIF":3.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146037479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Short-term PV plant power forecasting model using CNN-GRU with XGBoost algorithm","authors":"Lahoucine Oumiguil,&nbsp;Ali Nejmi","doi":"10.1016/j.sciaf.2026.e03184","DOIUrl":"10.1016/j.sciaf.2026.e03184","url":null,"abstract":"<div><div>Accurate short-term forecasting of photovoltaic (PV) power output is crucial for the efficient integration and operation of PV systems in smart grids. However, the intrinsic unpredictability and hierarchical discontinuity of PV data complicate the attainment of good predictive accuracy through conventional regression procedures. This research introduces a combined deep learning and gradient boosting model for short-term PV power forecasting. A convolutional neural network (CNN) is initially utilized to get important spatial features from input variables. Then, these features are coupled with historical PV power measurements in a gated recurrent unit (GRU) to capture temporal dependencies. The XGBoost technique is also used to represent complex nonlinear relationships in the data, which makes predictions even more accurate. The model is tested using actual PV plant data and gets a R² of 0.79, an RMSE of 23.30 MW, and a MAPE of 16.68%. These improvements show that the hybrid model works well to make predictions more accurate and reliable for real-world use.</div></div>","PeriodicalId":21690,"journal":{"name":"Scientific African","volume":"31 ","pages":"Article e03184"},"PeriodicalIF":3.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145976860","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}