LTAU-FF: Loss Trajectory Analysis for Uncertainty in atomistic Force Fields by Joshua A Vita, Amit Samanta, Fei Zhou, Vincenzo Lordi

“…Our method, which we call LTAU (Loss Trajectory Analysis for Uncertainty), efficiently estimates the full probability distribution function of errors for any test point using the logged training errors, achieving speeds that are 2–3 orders of magnitudes faster than typical ensemble methods and allowing it to be used for tasks where training or evaluating multiple models would be infeasible. …”
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Local head loss caused in connections used in micro-irrigation systems by Wagner W. Á. Bombardelli, Antonio P. de Camargo, José A. Frizzone, Rogério Lavanholi, Hermes S. da Rocha

“…For each connection model evaluated, the following information was obtained: curves of local head loss as a function of flow rate and of local head loss coefficient (KL). …”
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Predicting loss of independence among geriatric patients following gastrointestinal surgery by Michaela R. Cunningham, Christopher L. Cramer, Ruyun Jin, Florence E. Turrentine, Victor M. Zaydfudim

“…Methods This retrospective cohort study included patients age ≥ 65 years enrolled in the American College of Surgeons National Surgical Quality Improvement Program database and Geriatric Pilot Project who underwent pancreatic, colorectal, or hepatic surgery (January 1, 2014- December 31, 2018). Primary outcome was loss of independence – discharge to facility other than home and decline in functional status. …”
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An approach of power loss measurement for converter station and its key equipment by ZHENG Xin, YANG Jianhua, WEI Wei, MA Binqi, LI Shisong, ZHAO Wei

“…By equipping electrical energy metering devices with power monitoring function at the input and output ports of the converter station and the monitoring points of the key equipment inside the converter station and ensuring the time synchronisation to obtain the measurement results. …”
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Research on Lightweight Model of Multi-person Pose Estimation Based on Improved YOLOv8s-Pose by FU Yu, GAO Shuhui

“…A small object detection head is then added to the network to reduce the missed detection of small objects. Lastly, the CIOU loss function is replaced with Focal-EIOU to enhance the accuracy of human key point regression. …”
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A Mean Weighted Squared Error-based Neural Classifier for Intelligent Pattern Recognition in Smart Grids by Mehdi Khashei, Mehrnaz Ahmadi, Fatemeh Chahkoutahi

“…In the proposed MWSE, unequal weights are assigned to each estimated data point, unlike the conventional version. In this paper, Multilayer Perceptron Neural Networks (MLPs) are employed to implement the proposed MWSE loss function. …”
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CALCULATION OF OPERATION MODE OF OUTDOOR LIGHTING LINE WITH BILATERAL SUPPLY. Part 2 by V. B. Kozlovskaya, V. N. Kalechyts

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Vision-Based Localization Method for Picking Points in Tea-Harvesting Robots by Jingwen Yang, Xin Li, Xin Wang, Leiyang Fu, Shaowen Li

“…First, an improved T-YOLOv8n model is proposed, which improves detection and segmentation performance across multi-scale scenes through network architecture and loss function optimizations. In the far-view test set, the detection accuracy of tea buds reached 80.8%; for the near-view test set, the mAP_0.5 values for tea stem detection in bounding boxes and masks reached 93.6% and 93.7%, respectively, showing improvements of 9.1% and 14.1% over the baseline model. …”
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Generic multidimensional economic environmental operation of power systems using equilibrium optimization algorithm by Mohamed T. Mouwafi, Adel A. Abou El-Ela, Amany A. El-Hamoly, Ragab A. El-Sehiemy

“…The OFs are optimized with and without considering valve point effects (VPE) and transmission system loss. …”
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Expression Recognition Algorithm of Deeply Separable Residual Network under Joint Loss by LI Jingyu, CHENG Weiyue, LIN Kezheng, MIAO Zhuang, LI Ao

“… In order to enhance the feature extraction ability of neural network and further improve the accuracy of facial expression recognition, this paper proposes a deep separable residual network model under joint loss DSResNet-Jloss.This network is a lightweight network model based on deep separable convolution and residual learning methods.The method of channel-by-channel convolution and point-by-point convolution is used to replace the conventional convolution operation, which solves the problems of traditional convolutional neural network with large parameter redundancy, long training time, slow convergence, and easy overfitting.And add residual unit to the network, use shortcut connection, through identity mapping, to solve the problem of gradient explosion or attenuation caused by too many layers of the network model.A joint loss function is proposed, which fully combines the advantages of cross-entropy loss, center loss and contrast loss to reduce the intra-class distance of expression features and increase the inter-class distance.Experiments show that the model has achieved good results on the two public data sets of FERPlus and RAF-DB, showing good generalization ability and robustness.…”
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Characteristics of Soil Nutrients Accumulation and Nitrogen and Phosphorus Loss of Greenhouse Vegetable Field by YANG Tao, CHEN Yuanhua, CHEN Feng, XU Changxu, ZHUANG Yanhua, TU Xiangming, CHEN Jingrui

“…The soil layers within 0—20 and 20—40 cm under surface showed pH values of 5.44 and 5.56, respectively. 2) The soil nutrient content in 0—20 cm soil layer was at the medium fertility level, and the soil nutrient increased with the extension of planting time when the planting years were less than 10 years, and began to decline when the planting years were 11—20 years (except for available phosphorus). 3) The runoff from greenhouse vegetable is mainly driven by rainfall and has the characteristics of high volume and low concentration; runoff occurs in the period from February to June accounts for more than 75% of the annual runoff amount and more than 60% of the annual nitrogen and phosphorus loss. ［Conclusion］ The 6—10 years might be a “turning point” for the cumulative contents of nutrients in greenhouse vegetable plots. …”
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Effect of withering temperature on water loss of fresh leaves and quality of white tea by LIN Qingxia, XIANG Lihui, WANG Lili, YANG Junguo, SONG Zhenshuo, CHEN Lin

“…The results showed that the water loss rates of all tea shoots tended to decelerate gradually under the different withering temperatures, the higher the withering temperature, the faster the water loss rate. …”
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Impact of Anchoring, Herding and Loss-Aversion on Working Women’s Investment Decision-Making by H. Srivastava, S. Moid, N. J. Rushdi

“…A structured questionnaire is used for the collection of data, which is based on a five-point Likert scale. The SPSS (Version 22) software is used to analyze data employing the linear regression function. …”
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Improved YOLOv8-Based Algorithm for Citrus Leaf Disease Detection by Zhengbing Zheng, Yibang Zhang, Luchao Sun

“…To further enhance adaptability, the traditional Intersection over Union (IoU) is replaced with the Wise-IoU loss function, improving the model’s performance across different disease types. …”
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Clopidogrel and Aspirin Resistance and Its Interaction with Peripheral Arterial Disease Outcomes in the Indian Population by Vikram Patra, Rohit Mehra, C V N M Dattatraya, Rishi Dhillan, Anuka Sharma, Varun Sharma, Brijesh Biswas, Ajay Kumar Dabas, Rahul Merkhed

“…Limited efficacy of clopidogrel was observed in 52.38% of patients with loss of function (LOF) variations in the CYP2C19 gene. …”
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Effects of acute weight loss on serum mineral homeostasis in elite male judoka by Burcu Yenturk, Mihrac Koroglu, Nuri Muhammet Celik, Cuneyt Sensoy, Fıkret Soyer

“…Maintaining optimal serum mineral levels is critical for both physiological function and athletic performance. This study aimed to examine the effect of acute weight loss on serum mineral concentrations in elite male judoka. …”
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LSOD-YOLOv8: Enhancing YOLOv8n with New Detection Head and Lightweight Module for Efficient Cigarette Detection by Yijie Huang, Huimin Ouyang, Xiaodong Miao

“…Finally, we propose a new loss function, WIMIoU (Weighted Intersection over Union with Inner, Multi-scale, and Proposal-aware Optimization), by combining the ideas of WiseIoU (Wise Intersection over Union), InnerIoU (Inner Intersection over Union), and MPDIoU (Mean Pairwise Distance Intersection over Union), resulting in a significant accuracy improvement without any loss in performance. …”
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Global analysis of forest tipping points leading to changing water cycle dynamics by Marisol Domínguez-Tuda, Hugo A. Gutiérrez-Jurado

“…However, quantification of the tipping points of forest cover loss before hydrologic changes manifest and their impact in water yield and climatic conditions has remained elusive. …”
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Kratopenia as an indicator of sarcopenia in smokers: Cut-off points for peak knee torque. by Paolla Sanches, Karina A de S Souza, Alexandre R P Ambrozin, André R Pereira, Leandro L da Silva, Amanda S Cano, Luciana Pinato, Tiago V Barreira, Dionei Ramos, Mahara Proença

“…ROC analysis revealed acceptable discrimination for detecting kratopenia from functional limitation: AUC of 70% for knee extension (p < 0.01) from the cut-off points identified for knee extension lower than 214.8Nw and 273.6Nw; and 70% for knee flexion (p < 0.01) lower than 125 Nw and 156.2Nw, women and men, respectively, to be loss of muscle strength and power. …”
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DANC-Net: Dual-Attention and Negative Constraint Network for Point Cloud Classification by Hang Sun, Yuanyue Zhang, Jinmei Shi, Shuifa Sun, Guanqun Sheng, Yirong Wu

“…Moreover, during the training of the DANC-Net, the negative constraint loss function ensures that the features in the same categories are close and those in the different categories are far away from each other in the representation space, so as to improve the feature extraction capability of the network. …”
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