Analysis of genetic relationships in the breeding material of <i>Prunus armeniaca</i> L. from the collection of the Mountain Botanical Garden, Dagestan by D. M. Anatov, I. I. Suprun, I. V. Stepanov, R. M. Osmanov, S. V. Tokmakov

“…Background. Dagestan boasts a long tradition of apricot cultivation that resulted in a unique gene pool of this fruit tree. …”
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The Effect of Mesenchymal Stem Cell-Derived Exosomes and miR17-5p Inhibitor on Multicellular Liver Fibrosis Microtissues by Farnaz Sani, Mina Soufi Zomorrod, Negar Azarpira, Masoud Soleimani

“…Furthermore, EXO + anti-miR had the best effects on boosting the fibrotic markers. Therefore, we propose this novel MLM model to understand fibrosis mechanisms better and develop new drugs.…”
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Smart Cities, Smarter land Use? Unveiling the efficiency gains from China’s digital urban transformation by Zhenyu Zhuo, Jiashuo Ye, Yu Wang, Hao Chen, Bin Liang

“…The findings reveal that: (1) Smart city construction significantly enhances ULUE, with increases of 16 %, 11.4 %, and 11.1 % of the three pilot batches; (2) Urban smart transformation improves ULUE through three mechanisms: fostering innovation investment, expanding internet user bases, and optimizing industrial land use efficiency; (3) Urban smart transformation has a more pronounced effect on ULUE in eastern and western cities, while the impact in central cities is not significant; (4) The long-term effects of smart city policy surpass short-term impacts and exhibit synergistic interactions with innovation policies; (5) Urban smart transformation has a spatial spillover effect, benefiting neighboring cities within an 80 km radius by significantly boosting ULUE. This paper employs rigorous empirical methods to analyze the causal relationship between urban smart transformation and ULUE, while also delving into the underlying mechanisms, time lag effects, and spatial spillovers. …”
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Recruitment Challenges and Strategies in a Technology-Based Intervention for Dementia Caregivers: Descriptive Study by Eunjung Ko, Ye Gao, Peng Wang, Lahiru Wijayasingha, Kathy D Wright, Kristina C Gordon, Hongning Wang, John A Stankovic, Karen M Rose

“…Our recruitment strategies included addressing privacy concerns, visualizing collected data through a dashboard, boosting social media presence, increasing the recruitment budget, updating advertisements, and preparing and deploying additional study devices. …”
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Prospects for mine geological work in the intelligence age: Architecture of the intelligent geological guarantee technology system for mine exploitation by Yucheng XIA, Xueyang SUN, Lintian MIAO, Chen GUO, Rongjun DU

“…The technology system will surely become the novel productivity that boosts the quality and efficiency of mine geological work. …”
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Unraveling the Beneficial Role of Resveratrol in Fructose-Induced Non-Alcoholic Steatohepatitis with a Focus on the AMPK/Nrf2 Signaling Axis by Soha S. Zakaria, Safaa M. Hanafy

“…Resveratrol reduces NASH by boosting autophagy and activating the AMPK/Nrf2 pathway. …”
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Predicting pregnancy loss and its determinants among reproductive-aged women using supervised machine learning algorithms in Sub-Saharan Africa by Tirualem Zeleke Yehuala, Sara Beyene Mengesha, Nebebe Demis Baykemagn

“…Python software was used to process the data, and machine learning techniques such as Random Forest, Decision Tree, Logistic Regression, Extreme Gradient Boosting, and Gaussian were applied. The performance of the predictive models was evaluated using several standard metrics, including the ROC curve, accuracy score, precision, recall, and F-measure.ResultThe final experimental results indicated that the Random Forest model performed the best in predicting pregnancy loss, achieving an accuracy of 98%, precision of 98%, F-measure of 83%, ROC curve of 94%, and recall of 77%. …”
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Evaluating empirical and machine learning approaches for reference evapotranspiration estimation using limited climatic variables in Nepal by Erica Shrestha, Suyog Poudyal, Anup Ghimire, Shrena Maharjan, Manoj Lamichhane, Sushant Mehan

“…We assessed the performance of six widely used empirical models (Hargreaves Samani, modified Hargreaves Samani, Romanenko, Schendel, Priestley-Taylor, and Makkink) and four ML models (random forest, extreme gradient boosting, deep neural network, and long short-term memory) to estimate ET0 with limited climatic variables in Nepal. …”
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The impact of export market orientation on SME market performance: Exploring the moderating effect of government policy and the mediating effect of information access by Sunday Noya, Stefanus Yufra M. Taneo, Melany

“…The findings demonstrate that export market orientation significantly boosts SME market performance (path coefficient = 0.512, p &lt; 0.001), highlighting its critical role in fostering customer-oriented practices and adaptive marketing strategies. …”
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Evaluation of the effect of 48 weeks of BIC/F/TAF and DRV/c/F/TAF on platelet function in the context of rapid ART start by Akif A. Khawaja, Gary Whitlock, Sarah Fidler, Alfredo Soler-Carracedo, Merle Henderson, Graham P. Taylor, Marta Boffito, Michael Emerson

“…Despite differences in the demographics between treatment arms, the presence of an unboosted integrase inhibitor or boosted protease inhibitor in a test-and-treat setting did not impact platelet function. …”
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Magnetic field influence on heat transfer of NEPCM in a porous triangular cavity with a cold fin and partial heat sources: AI analysis combined with ISPH method by Munirah Aali Alotaibi, Weaam Alhejaili, Abdelraheem M. Aly, Samiyah Almalki

“…A higher nanoparticle concentration boosts the average Nusselt number Nu̅ by 10 %, improving overall heat transfer efficiency. …”
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Using Deep Learning to Identify High-Risk Patients with Heart Failure with Reduced Ejection Fraction by Zhibo Wang, Xin Chen, Xi Tan, Lingfeng Yang, Kartik Kannapur, Justin L. Vincent, Garin N. Kessler, Boshu Ru, Mei Yang

“…For comparison, we also tested multiple traditional machine learning models including logistic regression, random forest, and eXtreme Gradient Boosting (XGBoost). Model performance was assessed by area under the curve (AUC) values, precision, and recall on an independent testing dataset. …”
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Optimal rainwater harvesting locations for arid and semi-arid regions by using MCDM-based GIS techniques by Waqed H. Hassan, Karrar Mahdi, Zahraa K. Kadhim

“…Rainwater collection and effective water resource management are essential for boosting water availability, land productivity, and groundwater levels in dry places like Iraq, which is susceptible to climate change and drought. …”
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Parental singing during kangaroo care: parents' experiences of singing to their preterm infant in the NICU by Pernilla Hugoson, Friederike Barbara Haslbeck, Ulrika Ådén, Ulrika Ådén, Ulrika Ådén, Louise Eulau, Louise Eulau

“…Data were analyzed inductively, followed by deductive categorization within the SOC framework, focusing on its three core components: Manageability, Comprehensibility, and Meaningfulness.ResultsParents in the intervention group reported enhanced understanding of how singing fosters attachment and boosts their self-esteem, aligning with increased manageability and comprehensibility. …”
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Pretreatment of Palm Kernel Cake by Enzyme-Bacteria and Its Effects on Growth Performance in Broilers by Yue Liu, Ying Liu, Yunhe Cao, Chunlin Wang

“…Enzyme-bacteria co-fermentation of palm kernel cake boosts its nutritional value and enhances broiler intestinal health.…”
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Popular English Songs as Motivational Resources and Instructional Aids for Grammar Education by John Arvin V. De Roxas, Daisy O. Casipit, Mercedita M. Reyes, Lyan Mae Micah V. Dela Cruz, Joan C. Ravago

“…Conclusion: In conclusion, incorporating popular English songs into grammar instruction significantly boosts student motivation and performance in English language learning. …”
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Predicting the environmental suitability for onchocerciasis in Africa as an aid to elimination planning. by Elizabeth A Cromwell, Joshua C P Osborne, Thomas R Unnasch, Maria-Gloria Basáñez, Katherine M Gass, Kira A Barbre, Elex Hill, Kimberly B Johnson, Katie M Donkers, Shreya Shirude, Chris A Schmidt, Victor Adekanmbi, Olatunji O Adetokunboh, Mohsen Afarideh, Ehsan Ahmadpour, Muktar Beshir Ahmed, Temesgen Yihunie Akalu, Ziyad Al-Aly, Fahad Mashhour Alanezi, Turki M Alanzi, Vahid Alipour, Catalina Liliana Andrei, Fereshteh Ansari, Mustafa Geleto Ansha, Davood Anvari, Seth Christopher Yaw Appiah, Jalal Arabloo, Benjamin F Arnold, Marcel Ausloos, Martin Amogre Ayanore, Atif Amin Baig, Maciej Banach, Aleksandra Barac, Till Winfried Bärnighausen, Mohsen Bayati, Krittika Bhattacharyya, Zulfiqar A Bhutta, Sadia Bibi, Ali Bijani, Somayeh Bohlouli, Mahdi Bohluli, Oliver J Brady, Nicola Luigi Bragazzi, Zahid A Butt, Felix Carvalho, Souranshu Chatterjee, Vijay Kumar Chattu, Soosanna Kumary Chattu, Natalie Maria Cormier, Saad M A Dahlawi, Giovanni Damiani, Farah Daoud, Aso Mohammad Darwesh, Ahmad Daryani, Kebede Deribe, Samath Dhamminda Dharmaratne, Daniel Diaz, Hoa Thi Do, Maysaa El Sayed Zaki, Maha El Tantawi, Demelash Abewa Elemineh, Anwar Faraj, Majid Fasihi Harandi, Yousef Fatahi, Valery L Feigin, Eduarda Fernandes, Nataliya A Foigt, Masoud Foroutan, Richard Charles Franklin, Mohammed Ibrahim Mohialdeen Gubari, Davide Guido, Yuming Guo, Arvin Haj-Mirzaian, Kanaan Hamagharib Abdullah, Samer Hamidi, Claudiu Herteliu, Hagos Degefa de Hidru, Tarig B Higazi, Naznin Hossain, Mehdi Hosseinzadeh, Mowafa Househ, Olayinka Stephen Ilesanmi, Milena D Ilic, Irena M Ilic, Usman Iqbal, Seyed Sina Naghibi Irvani, Ravi Prakash Jha, Farahnaz Joukar, Jacek Jerzy Jozwiak, Zubair Kabir, Leila R Kalankesh, Rohollah Kalhor, Behzad Karami Matin, Salah Eddin Karimi, Amir Kasaeian, Taras Kavetskyy, Gbenga A Kayode, Ali Kazemi Karyani, Abraham Getachew Kelbore, Maryam Keramati, Rovshan Khalilov, Ejaz Ahmad Khan, Md Nuruzzaman Nuruzzaman Khan, Khaled Khatab, Mona M Khater, Neda Kianipour, Kelemu Tilahun Kibret, Yun Jin Kim, Soewarta Kosen, Kris J Krohn, Dian Kusuma, Carlo La Vecchia, Van Charles Lansingh, Paul H Lee, Kate E LeGrand, Shanshan Li, Joshua Longbottom, Hassan Magdy Abd El Razek, Muhammed Magdy Abd El Razek, Afshin Maleki, Abdullah A Mamun, Ali Manafi, Navid Manafi, Mohammad Ali Mansournia, Francisco Rogerlândio Martins-Melo, Mohsen Mazidi, Colm McAlinden, Birhanu Geta Meharie, Walter Mendoza, Endalkachew Worku Mengesha, Desalegn Tadese Mengistu, Seid Tiku Mereta, Tomislav Mestrovic, Ted R Miller, Mohammad Miri, Masoud Moghadaszadeh, Abdollah Mohammadian-Hafshejani, Reza Mohammadpourhodki, Shafiu Mohammed, Salahuddin Mohammed, Masoud Moradi, Rahmatollah Moradzadeh, Paula Moraga, Jonathan F Mosser, Mehdi Naderi, Ahamarshan Jayaraman Nagarajan, Gurudatta Naik, Ionut Negoi, Cuong Tat Nguyen, Huong Lan Thi Nguyen, Trang Huyen Nguyen, Rajan Nikbakhsh, Bogdan Oancea, Tinuke O Olagunju, Andrew T Olagunju, Ahmed Omar Bali, Obinna E Onwujekwe, Adrian Pana, Hadi Pourjafar, Fakher Rahim, Mohammad Hifz Ur Rahman, Priya Rathi, Salman Rawaf, David Laith Rawaf, Reza Rawassizadeh, Serge Resnikoff, Melese Abate Reta, Aziz Rezapour, Enrico Rubagotti, Salvatore Rubino, Ehsan Sadeghi, Abedin Saghafipour, S Mohammad Sajadi, Abdallah M Samy, Rodrigo Sarmiento-Suárez, Monika Sawhney, Megan F Schipp, Amira A Shaheen, Masood Ali Shaikh, Morteza Shamsizadeh, Kiomars Sharafi, Aziz Sheikh, B Suresh Kumar Shetty, B Suresh Kumar Shetty, Jae Il Shin, K M Shivakumar, Biagio Simonetti, Jasvinder A Singh, Eirini Skiadaresi, Amin Soheili, Shahin Soltani, Emma Elizabeth Spurlock, Mu'awiyyah Babale Sufiyan, Takahiro Tabuchi, Leili Tapak, Robert L Thompson, Alan J Thomson, Eugenio Traini, Bach Xuan Tran, Irfan Ullah, Saif Ullah, Chigozie Jesse Uneke, Bhaskaran Unnikrishnan, Olalekan A Uthman, Natalie V S Vinkeles Melchers, Francesco S Violante, Haileab Fekadu Wolde, Tewodros Eshete Wonde, Tomohide Yamada, Sanni Yaya, Vahid Yazdi-Feyzabadi, Paul Yip, Naohiro Yonemoto, Hebat-Allah Salah A Yousof, Chuanhua Yu, Yong Yu, Hasan Yusefzadeh, Leila Zaki, Sojib Bin Zaman, Maryam Zamanian, Zhi-Jiang Zhang, Yunquan Zhang, Arash Ziapour, Simon I Hay, David M Pigott

“…To achieve continental elimination of transmission, mapping surveys will need to be conducted across all implementation units (IUs) for which endemicity status is currently unknown. Using boosted regression tree models with optimised hyperparameter selection, we estimated environmental suitability for onchocerciasis at the 5 × 5-km resolution across Africa. …”
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Spatiotemporal changes of ecosystem health and the impact of its driving factors on the Loess Plateau in China by Xuepeng Zhang, Taixia Wu, Qiqi Du, Ninglei Ouyang, Wei Nie, Yang Liu, Peng Gou, Guangchao Li

“…The efficient machine learning model (light gradient boosting machine model) and the variable explanation model (SHapley Additive exPlanation model) are combined to quantify the functional relationships between various driving factors and EH, thereby exploring the impacts of climatic factors, socioeconomic development (SED), and ecological restoration projects (ERP) on EH. …”
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The effects of Fraxini cortex and Andrographis herba on Escherichia coli-induced diarrhea in chicken by Yunying Wang, Zhenwei Sheng, Huicong Li, Xuewen Tan, Yingqiu Liu, Weimin Zhang, Wuren Ma, Lin Ma, Yunpeng Fan

“…Fraxini cortex and Andrographis herba significantly boosted the abundance of Bacteroidetes (P < 0.05) and mainly enhanced cysteine and methionine metabolic pathways. …”
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Machine learning assisted radiomics in predicting postoperative occurrence of deep venous thrombosis in patients with gastric cancer by Yuan Zeng, Yuhao Chen, Dandan Zhu, Jun Xu, Xiangting Zhang, Huiya Ying, Xian Song, Ruoru Zhou, Yixiao Wang, Fujun Yu

“…Four machine learning algorithms, known as random forest (RF), extreme gradient boosting (XGBoost), support vector machine (SVM) and naive Bayes (NB), were used to develop models for predicting the risk of lower extremity DVT occurrence in GC patients. …”
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