Effect of breast milk olfactory experience on physiological indicators in very low birth weight infants: a randomized clinical trial by Ling Yu, Yibo Tao, Pin Jia, Liling Li, Tianchan Lv, Li Wang, Qinqin Song, Xia Huan, Chan Liu, Yalan Dou, Yan Xuan, Xiao-jing Hu

“…A narrower range of fluctuation was observed across all physiological indicators in the intervention group, indicating a more stable pattern compared to the control group. Although no significant difference was found in heart rate variability (50.35 ± 9.61 vs. 48.03 ± 10.2, t=-1.320, P = 0.187), a significant difference was noted in the average heart rate between the two groups (155.65 ± 6.80 vs. 153.58 ± 4.22, t=-2.141, P = 0.032). …”
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Machine learning and microfluidic integration for oocyte quality prediction by Hassan Saffari, Davood Fathi, Peyman Palay, Hamid Gourabi, Rouhollah Fathi

“…Additionally, oocyte diameter and the critical flow rate (Q)—defined as the minimum flow rate necessary for an oocyte to pass through the channel—were included as predictive variables. …”
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Solar FaultNet: Advanced Fault Detection and Classification in Solar PV Systems Using SwinProba‐GeNet and BaBa Optimizer Models by Praveen Kumar Balachandran, Muhammad Ammirrul Atiqi Mohd Zainuri, Faisal Alsaif

“…It also proposes the Solar FaultNet‐a novel deep learning‐based approach that significantly improves fault detection performance in solar PV systems and integrates the model with state‐of‐the‐art ML techniques like CNN and LSTM to capture inherent complex patterns and interdependencies of fault data. Besides, the proposed model outperforms conventional machine‐learning algorithms and state‐of‐the‐art deep‐ learning models for better performance by yielding higher accuracy, precision, recall, F1‐score, and low error rate on various fault types such as PV array faults, inverter faults, grid synchronization faults, and environmental faults. …”
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Impact of Sodium Ion Stress on the Mechanism of Lead Ion Migration in Electrochemical Treatment of Lead-Contaminated Soil by Yinyin Zhang, Jiangtao Han, Libin Zang

“…This study specifically validates the migration patterns of lead ions under sodium ion stress in soil and concludes that a high concentration of sodium ions, when coexisting with lead ions, diminishes the migration rate of lead ions, consequently reducing the removal efficiency of lead ions. 1. …”
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Combining Autoregressive Models and Phonological Knowledge Bases for Improved Accuracy in Korean Grapheme-to-Phoneme Conversion by Sung-Ki Choi, Hyuk-Chul Kwon, Minho Kim

“…Experimental results show that a BiLSTM-LSTM AR model based on ELECTRA embeddings achieves a phoneme error rate (PER) of 0.2%, word error rate (WER) of 0.68%, and a sentence accuracy of 95.16%, outperforming both a traditional rule-based approach (24.51% sentence accuracy) and non-autoregressive variants implemented on the same dataset (achieving 81.32%–85.72% sentence accuracy). …”
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Multidrug-resistant pulmonary tuberculosis in Esmeraldas, Ecuador (2018–2022): prevalence and clinical–epidemiological profile from a retrospective observational study by Jaime Angamarca-Iguago

“…Treatment outcomes were incomplete in 41% of cases; among reported outcomes, cure rate was 22.4%, and the case fatality rate was 10.2%. …”
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¹³C metabolic flux analysis identifies an unusual route for pyruvate dissimilation in mycobacteria which requires isocitrate lyase and carbon dioxide fixation. by Dany J V Beste, Bhushan Bonde, Nathaniel Hawkins, Jane L Ward, Michael H Beale, Stephan Noack, Katharina Nöh, Nicholas J Kruger, R George Ratcliffe, Johnjoe McFadden

“…Here we show that deletion of one of the two icl genes impairs the replication of Mycobacterium bovis BCG at slow growth rate in a carbon limited chemostat. In order to further understand the role of isocitrate lyase in the central metabolism of mycobacteria the effect of growth rate on the in vivo fluxes was studied for the first time using ¹³C-metabolic flux analysis (MFA). …”
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Radiocleavable rare-earth nanoactivators targeting over-expressed folate receptors induce mitochondrial dysfunction and remodel immune suppressive microenvironment in pancreatic ca... by Tanvi Gupta, Shang-Rung Wu, Li-Chan Chang, Forn-Chia Lin, Yan-Shen Shan, Chen-Sheng Yeh, Wen-Pin Su

“…Abstract Pancreatic cancer is a fatal cancer with poor prognosis and survival rate, often diagnosed usually in the advanced stage of disease. …”
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Identification and Validation of the lncRNA BACE1-AS as Immune-Related Influencing Factor in Tumorigenesis following Pan-Carcinoma Analysis by Mengmeng Wang, Di Chen, Yushuang Xu, Mengjun Qiu, Xin Jiang, Zhifan Xiong

“…Overall, our results suggest that BACE1-AS is associated with the expression, prognosis, and rate of immune cell infiltration of most tumors. …”
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Spatial proximity effects on cognitive processing of multimedia learning among college students: evidence from functional near-infrared spectroscopy by Yan Ma, Yan Ma, Qiuyue Peng, Qiuyue Peng, Bowen Long, Bowen Long

“…In addition, the study also explored how disciplinary differences affect the strength of spatial proximity effects and corresponding brain activation patterns.ResultsThe findings revealed that activation levels in the middle temporal gyrus, frontal pole, and dorsolateral prefrontal cortex were significantly higher in the spatial proximity condition compared to the spatial separation condition, accompanied by an improved rate of correct answers. …”
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The 'Antiretrovirals, Sexual Transmission Risk and Attitudes' (ASTRA) study. Design, methods and participant characteristics. by Andrew Speakman, Alison Rodger, Andrew N Phillips, Richard Gilson, Margaret Johnson, Martin Fisher, Ed Wilkins, Jane Anderson, Rebecca O'Connell, Monica Lascar, Kazeem Aderogba, Simon Edwards, Jeffrey McDonnell, Nicky Perry, Lorraine Sherr, Simon Collins, Graham Hart, Anne M Johnson, Alec Miners, Jonathan Elford, Anna-Maria Geretti, William J Burman, Fiona C Lampe

“…In this paper we describe the study rationale, design, methods, response rate and the demographic characteristics of the participants. …”
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Adaptive AI-enhanced computation offloading with machine learning for QoE optimization and energy-efficient mobile edge systems by Dinesh Kumar Nishad, Vandna Rani Verma, Pushkar Rajput, Sandeep Gupta, Anurag Dwivedi, Dharti Raj Shah

“…The system’s security analysis yields a 98% threat detection rate, with response times under 100 ms. Meanwhile, reliability metrics indicate a 99.8% task completion rate and a mean time to failure of 1,200 h. …”
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Effect of water-saving irrigation on the seasonal emission of CH₄ from paddy field by PENG Shi-zhang, LI Dao-xi, JIAO Xi-yun, HE Yan, YU Jin-yuan

“…There is no statistically significant difference on the mean emission rates of CH₄ between two kinds of irrigation patterns during the ponding to the peak tillering stage of rice (0.05<P=0.87); while CH₄ emission rate from PFCI is significantly lower than that from PFFI during the later tillering to ripening stage of rice (0.00=P<0.05). …”
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The effects of annual cycle stages and life-history traits on feather abrasion by Yosef Kiat, Quentin Dupriez, Gina Pyo, Oliver J. L. Fox, Rafi Paz, Hans-Jürgen Eilts, Carlos Talabante, Nir Sapir

“…However, little is known about the underlying mechanisms, patterns and immediate consequences of feather abrasion. …”
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The Role of Intrinsic Factors in Explaining Range Shifts of European Breeding Birds: A Meta‐Analysis by Femke E. M. Warmer, Wessel A. vanVliet, Pim vanHooft, Anouschka R. Hof

“…However, the observed range shift patterns are idiosyncratic in rate and direction. Species traits, such as ecological, life‐history and movement traits, may play an important role in determining range shifts by influencing a species' capacity to shift successfully. …”
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Rehabilitation and Motion Symmetry Analysis With a TACX Smart Cycling Trainer Using Computational Intelligence by Hana Charvatova, Daniel Martynek, Alexandra Molcanova, Ales Prochazka

“…The research objectives include analysis of motion patterns, evaluation of motion symmetry under varying loads, and examination of heart rate responses to load variations. …”
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Prediction of Salinity Based on Meteorological Data Using the Backpropagation Neural Network Method by Anisa Nur Azizah, Dian C.R. Novitasari, Putroue Keumala Intan, Fajar Setiawan, Ghaluh Indah Permata Sari

“…This study conducted several backpropagation architectural experiments, that is the learning rate, hidden layer, and the number of nodes in the hidden layer to obtain the best results. …”
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Research on the disintegration characteristics of fissured loess under water–vibration coupling effect by Tao Lei, Jiading Wang, Shaotong Jiao

“…To reveal the disaster mechanisms, this study conducted water-vibration coupled disintegration tests on fissured loess using the self-developed EDS-600 vibration disintegration apparatus, based on the measured dominant vibration frequencies (12–46 Hz) of the Lanzhou-Qinghai Railway. The influence patterns of vibration frequency (f) and fissure type (t) on disintegration rate (S), disintegration velocity (V), and disintegration velocity growth rate ( $$\alpha_{f - t}$$ ) were systematically investigated, with scanning electron microscopy (SEM) employed to uncover microstructural evolution mechanisms. …”
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Financial Institutions and Agricultural development in Rwanda. A Case Study of Rwanda Development Bank. by Boniface, Kabahizi

“…On the basis of customers’ perception about RDB lending policy, it has been realized from the study that clients prefer RDB because of its attractive lending policy, it has been realized from the study that clients prefer RDB because of its attractive lending policy including reasonable interest rate and repayment patterns. The reasons behind this are the interest rate for agricultural sector and exportation loans is lower compared to other sectors financed by RDB. …”
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Multiple-Fault Diagnosis Method Based on Multiscale Feature Extraction and MSVM_PPA by Min Zhang, Zhenyu Cai, Wenming Cheng

“…MSVM method with PPA parameters optimization will classify the fault patterns. The results of a case study of the rolling bearings faults data from Case Western Reserve University show that (1) the proposed intelligent method (MFE_PPA_MSVM) improves the classification recognition rate; (2) the accuracy will decline when the number of fault patterns increases; (3) prediction accuracy can be the best when the training set size is increased to 70% of the total sample set. …”
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