Myostatin-driven muscle hypertrophy: a double-edged sword in muscle physiology by Ghisaram Dewasi, Parikshit Nagda, Gurusha Bahl, Vivek Jain, Sanjay Kumar Gupta

“…While targeting myostatin holds clinical promise, optimizing its therapeutic index requires a precise balance between muscle anabolism and functional integrity.…”
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MaskDGNets: Masked-attention guided dynamic graph aggregation network for event extraction. by Guangwei Zhang, Fei Xie, Lei Yu

“…We designed a reconstructed weighted loss function to supervise and adjust each module individually to ensure the optimal feature representation. …”
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Time-Series Interval Forecasting with Dual-Output Monte Carlo Dropout: A Case Study on Durian Exports by Unyamanee Kummaraka, Patchanok Srisuradetchai

“…Hyperparameter optimization is performed through a grid search exploring activation functions, dropout rates, epochs, and batch sizes. …”
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Emphysematous pyelonephritis: classification, management, and prognosis by Shu-Yu Wu, Stephen Shei-Dei Yang, Shang-Jen Chang, Chun-Kai Hsu

“…They defined EPN into four different class (1–4), with the higher number the more severe disease. Optimal EPN treatment is controversial, with emergent nephrectomy suggested during early studies, whereas more recent evidence favors more conservative approaches. …”
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Research on the Wetland Vegetation Classification Method Based on Cross-Satellite Hyperspectral Images by Min Yang, Jing Qin, Xiaodan Wang, Yanfeng Gu

“…Domain discrimination and domain-invariant characteristics are considered. We optimize the generator and discriminator using inter-class and intra-class contrast loss functions. …”
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Transforming lemon Peel into a sustainable reservoir of bioactives: A green osmotic dehydration strategy by Priyanka Prajapati, Chhavi Porwal, Meenakshi Garg, Neha Singh, Susmita Dey Sadhu, Rajni Chopra, Eram S. Rao, Aparna Agarwal, Mohd Saeed, Safia Obaidur Rab, Dipendra Kumar Mahato, Pradeep Kumar, Madhu Kamle, Abhishek Dutt Tripathi

“…Employing Response Surface Methodology (RSM) framework, pivotal variables—temperature (30–60 °C), exposure time (60–180 min), and sucrose concentration (50–70°Brix)—were optimized to enhance water loss (WL) and solid gain (SG) while safeguarding bioactive retention. …”
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Improved Ferroelectric and Magnetic Properties of Bismuth Ferrite-Based Ceramics by Introduction of Non-Isovalent Ions and Grain Engineering by Ting Wang, Huojuan Ye, Xiaoling Wang, Yuhan Cui, Haijuan Mei, Shenhua Song, Zhenting Zhao, Meng Wang, Pitcheri Rosaiah, Qing Ma

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Biomarker Evolution in Pediatric SMA: Insights from CSF pNF-H Dynamics and SMN2 Copy Number During Nusinersen Therapy by Mihaela Badina, Gabriel Cristian Bejan, Andrada Mirea, Corina Sporea, Madalina Cristina Leanca, Georgiana Nicolae, Ioana Elena Cioca, Maria Veronica Morcov, Angelo Pellegrini, Elena-Nicoleta Bordea

“…Spinal muscular atrophy (SMA) is a severe neurodegenerative disorder caused by insufficient survival motor neuron (SMN) protein synthesis, leading to progressive motor neuron loss and debilitating symptoms. This study evaluates cerebrospinal fluid (CSF) phosphorylated neurofilament-heavy chain (pNF-H) levels as predictive markers of motor function in 73 pediatric SMA patients undergoing nusinersen treatment. pNF-H, a structural component of neurons, is released into the CSF and serum during neuronal damage or degeneration. …”
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Multi-Site Air Quality Index Forecasting Based on Spatiotemporal Distribution and PatchTST-Enhanced: Evidence From Hebei Province in China by Wenyi Cao, Rufei Zhang, Wenxin Cao

“…The new model demonstrates robust performance in Hebei’s air quality forecasting (PreLen =96: MSE =0.5408, MAE =0.5408, RSE =0.5408; PreLen =192: MSE =0.2795, MAE =0.2795, RSE =0.2795; PreLen =336: MSE =0.6779, MAE =0.6779, RSE =0.6779; PreLen =720: MSE =0.6779, MAE =0.6779, RSE =0.6779), and the prediction accuracy has been significantly improved compared to both the pre-optimization model and other existing models. The PatchTST-Enhanced outperforms the PatchTST and improves it through four optimization modules: CGAttention, SiLU activation, AdamW optimizer, and SmoothL1 Loss function. …”
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Privacy-Preserving SGD on Shuffle Model by Lingjie Zhang, Hai Zhang

“…In this paper, we consider an exceptional study of differentially private stochastic gradient descent (SGD) algorithms in the stochastic convex optimization (SCO). The majority of the existing literature requires that the losses have additional assumptions, such as the loss functions with Lipschitz, smooth and strongly convex, and uniformly bounded of the model parameters, or focus on the Euclidean (i.e. l2d) setting. …”
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Urgent liver retransplantation in patient with sepsis, multiple organ failure and unstable hemodynamics by D. A. Granov, I. I. Tileubergenov, V. N. Zhuikov, A. R. Sheraliev, D. N. Maistrenko, V. V. Borovik, F. K. Zherebcov, A. V. Moiseenko, S. V. Shapoval

“…In the presented case, the patient after orthotopic liver transplantation from an optimal cadaveric donor against the background of a smooth postoperative period and satisfactory graft function was followed by a series of biliary complications in the form of ongoing necrosis of the bile ducts of the graft, which required repeated surgical interventions, which led to the formation of a separate bicholangiostomy. …”
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Patellar Tendon Avulsion at the Tibial Tubercle at Subacute Stage: A Case Report by Hamza Özer, Asım Ahmadov, Tayfun Özel, Ramazan Düzgün, Gökberk Baki, Salih Erdem

“…This report contributes valuable insights into the treatment of distal patellar tendon avulsion in pediatric patients and emphasizes the importance of appropriate management of such injuries to ensure optimal recovery and knee function. Further research and prospective studies are warranted to validate the efficacy of this surgical approach in larger cohorts.…”
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Bioactives and Other Nutritional Components in the Jaggery Production Process by Nisha Pujari, Nirali Dedhia, Sanjay Mahajani, Narendra Shah, Amit Arora

“…In order to retain maximum mineral content in jaggery and to ensure the removal of appropriate amounts of scum, technological upgrades must be studied and the clarification step must be optimized and standardized.…”
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RDRM-YOLO: A High-Accuracy and Lightweight Rice Disease Detection Model for Complex Field Environments Based on Improved YOLOv5 by Pan Li, Jitao Zhou, Huihui Sun, Jian Zeng

“…We propose RDRM-YOLO, an enhanced YOLOv5-based network, integrating four key improvements: (i) a cross-stage partial network fusion module (Hor-BNFA) is integrated within the backbone network’s feature extraction stage to enhance the model’s ability to capture disease-specific features; (ii) a spatial depth conversion convolution (SPDConv) is introduced to expand the receptive field, enhancing the extraction of fine-grained features, particularly from small disease spots; (iii) SPDConv is also integrated into the neck network, where the standard convolution is replaced with a lightweight GsConv to increase the accuracy of disease localization, category prediction, and inference speed; and (iv) the WIoU Loss function is adopted in place of CIoU Loss to accelerate convergence and enhance detection accuracy. …”
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Bioinspired synthetic peptide-based biomaterials regenerate bone through biomimicking of extracellular matrix by Sareh Azadi, Mohammad Ali Yazdanpanah, Ali Afshari, Niloofar Alahdad, Solmaz Chegeni, Abdolhamid Angaji, Seyed Mahdi Rezayat, Shima Tavakol

“…There have been remarkable advancements in regenerative medicine for bone regeneration, tackling the worldwide health concern of tissue loss. Tissue engineering uses the body’s natural capabilities and applies biomaterials and bioactive molecules to replace damaged or lost tissues and restore their functionality. …”
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TopoRSNet: A Unique Approach to Maintaining Topological Features for Digital Rock Image Rescaling With Minimal Quality Degradation by Kunning Tang, Yufu Niu, Ying DaWang, Vanessa Robins, Peyman Mostaghimi, Mark Lindsay, Ryan T. Armstrong

“…Feature preservation is ensured by introducing three feature‐based loss functions: adversarial loss, a new feature consistency loss, and a novel persistent homology loss (PH loss). …”
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Comprehensive quality detection method for tomatoes combining machine vision and spectral techniques by GUO Dechao, RAO Yuanli, ZHANG Hao, LI Chunfeng, ZHAO Qiang

“…ObjectiveTo realize rapid and accurate measurement of both internal and external quality of tomatoes, and improve the efficiency and quality of tomato grading.MethodsBased on machine vision and spectroscopy technology, proposed a tomato comprehensive quality grading method which combined external and internal quality. By optimizing the YOLOv8 model in four aspects (lightweight convolution, small object detection layer, CBAM attention mechanism, and loss function), external defect detection was completed, and external quality grading was achieved by combining fruit shape index and tomato size. …”
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Efficacy of aerobic exercises for knee osteoarthritis: a network meta analysis of randomized clinical trials by Yuan Luo, Xiao Chen, Haibo Gong, Li Chen, Liyue Zhang, Shuqiang Li

“…Surface under the cumulative ranking curve (SUCRA) probability analyses yielded the following results: Pilates (PT) demonstrated the highest probability of being optimal for WOMAC pain score (SUCRA = 0.8%), WOMAC stiffness (SUCRA = 15.7%), physical function (SUCRA = 0.0%), and total WOMAC score (SUCRA = 7.8%). …”
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Compensation of acetabular defects in primary and revision hip arthroplasty by Maria Yu. Udintseva, Elena A. Volokitina, Denis A. Kolotigin, Sergey M. Kutepov

“…Conclusion Long-term and painless functioning of the hip joint after arthroplasty performed for acetabular defects is possible with restoration of the spherical shape of the acetabulum and the center of joint rotation in the true acetabulum, adequate elimination of bone tissue loss, reliable primary fixation of the cup with provision of conditions due to restoration and osteointegration. …”

An automated adaptive trading system for enhanced performance of emerging market portfolios by Cristiana Tudor, Robert Sova

“…This is done by implementing a recursive window technique and running a user-specified fitness function to dynamically optimize the mean equation parameters throughout the lead time. …”
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