A scalable multi-modal learning fruit detection algorithm for dynamic environments by Liang Mao, Liang Mao, Zihao Guo, Mingzhe Liu, Yue Li, Linlin Wang, Jie Li

“…A sliding slice method is then employed to predict image targets, thereby reducing the miss rate of small targets.ResultsExperimental results demonstrate that the proposed model improves accuracy, recall, and mean average precision (mAP) by 9.5, 0.9, and 12.3 percentage points, respectively, compared to the original YOLOv5s model. …”
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Penerapan Decision Tree J48 dan Reptree dalam Menentukan Prediksi Produksi Minyak Kelapa Sawit menggunakan Metode Fuzzy Tsukamoto by Tundo Tundo, Shofwatul 'Uyun

“…From the data used the accuracy of the J48 decision tree is 95.2381%, while the REPTree accuracy is 90.4762%, but in this case the REPTree decision tree is more appropriate to be used in the prediction process of palm oil production, because it is tested with actual data in March 2019 uses REPTree obtained 16355835 liters, while using J48 obtained 11844763 liters, where the actual production data is 179,20000 liters. …”
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Identification of a distinctive immunogenomic gene signature in stage-matched colorectal cancer by Pankaj Ahluwalia, Ashis K. Mondal, Ashutosh Vashisht, Harmanpreet Singh, Ahmet Alptekin, Kalyani Ballur, Nivin Omar, Meenakshi Ahluwalia, Kimya Jones, Amanda Barrett, Vamsi Kota, Ravindra Kolhe

“…The development of prognostic and predictive indicators, particularly in the context of personalized medicine, could significantly improve CRC patient management. …”
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IMPACT OF ENERGY PRICES ON PRICES OF BASIC TOURISM SERVICES IN THE EURO AREA by Lachezar Borisov

“…The regression analysis revealed a causal relationship between the prices of hotels and restaurants and the dynamics of energy product prices, thereby enabling the prediction of the former based on the latter. The study reveals the existence of a specific functional relationship. …”
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Dynamics of spatial phase coherence in a dissipative Bose–Hubbard atomic system by Vatré, Rémy, Bouganne, Raphaël, Bosch Aguilera, Manel, Ghermaoui, Alexis, Beugnon, Jérôme, Lopes, Raphael, Gerbier, Fabrice

“…The observed decay exponent $\alpha \approx 0.54(6) $ is in good agreement with the prediction $\alpha =1/2$ from a dissipative Bose–Hubbard model accounting for the fluorescence-induced decoherence. …”
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Identification and Analysis of Key Immune- and Inflammation-Related Genes in Idiopathic Pulmonary Fibrosis by Tan Y, Qian B, Ma Q, Xiang K, Wang S

“…Based on these key genes, we carried out nomogram construction, enrichment and immune analyses, regulatory network mapping, drug prediction, and expression verification.Results: 27 DE-IFRGs were identified by intersecting 256 DEGs, 1793 immune-related genes, and 1019 inflammation-related genes. …”
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Uncovering a novel SERPING1 pathogenic variant: insights into the aggregation of C1-INH in hereditary angioedema by Lingxi Jiang, Chao Dai, Suyang Duan, Tingting Wang, Chunbao Xie, Luhan Zhang, Zimeng Ye, Xiumei Ma, Yi Shi

“…Despite its severity, there is a notable lack of effective methods for predicting and preventing HAE attacks. This study aims to thoroughly investigate the underlying pathological mechanisms of HAE and identify potential biomarkers that could aid in its prediction and prevention. …”
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Whole-transcriptome analysis reveals the characteristics of intramuscular fat circRNA expression and its associated network in grazing yaks of different months of age under cold st... by Yaqian Liu, Yonggang Sun, Yincang Han, Weiqin Ding, Shengwei Jin, Jianyu Chen, Fajie Gou

“…Results: The results showed that 352 differential circRNAs, 86 differential miRNAs and 3981 differential mRNAs were found. miRNAs and mRNAs network regulation maps were successfully constructed through gene expression correlation analysis and target gene prediction. Conclusions: Taking the intersection of the predicted circRNA target genes with the differential miRNAs for intramuscular fat in yaks of different months of age, we obtained two candidate ceRNA pairs that might be related to intramuscular fat deposition in yaks, and found that bta-let-7i might be related to fat deposition in yaks and might be regulated by X_85287959_85291068, and that X_85287959_85291068 could be a candidate circRNA to enhance the quality of yak meat. …”
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Simulation and experimental study on olive drop injury by Weike Lan, Haotian Mu, Di Xin, Shijia Pan, Yuncai Yan, Wen Gao, Zijie Niu, Dongyan Zhang, Jun Zhang, Yongjie Cui

“…In this study, vibration harvesting drop tests and finite element simulations were performed on the olive variety ''Leccio'' to optimize the collision parameters to evaluate and predict the damage level and damage resistance of olives. …”
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Global trends and research frontiers on machine learning in sustainable animal production in times of climate change: Bibliometric analysis aimed at insights and orientations for t... by Robson Mateus Freitas Silveira, Concepta Mcmanus, Iran José Oliveira da Siva

“…The main insights generated in the bibliometric analysis were (i) sustainable animal production changed from unidisciplinary science to multidisciplinary science linked to agricultural, environmental and engineering sciences, mainly to genetics and computing; (ii) the concept of sustainable animal production emerged from animal welfare and climate change concepts found in UN's 2030 Agenda; (iii) omics sciences, greenhouse gases, energy efficiency and animal welfare are the main keywords for bibliometric analyses in future studies related to sustainable animal production in the coming centuries; (iii) prediction and classification analyses, i.e., supervised machine learning models used as main tools in animal production; (iv) residual feed intake applied to measure sustainable feed efficiency in animal farming in the past and nowadays; and (v) The United States, China, Brazil and Australia are the main countries publishing studies on sustainability in animal production, but only China has been gaining prominence in publications in this field, in recent years, and it will turn this country into an emerging leader in future publications on this topic. …”
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Bergapten alleviates senescence of chondrocytes in osteoarthritis by YE Yuanlan, LIU Kaiwen, PAN Yiming

“…Methods‍　‍The functional targets of bergapten and the related targets of OA disease were obtained by searching Super-Pred， Swiss Target Prediction， Drug Bank. The obtained targets were intersected with Venny2.1.0, protein-protein interaction (PPI) analysis was performed using the STRING database, and molecular docking was conducted by AutoDock Vina. …”
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Overlying strata movement law and rockburst prevention & control for fully mechanized top coal caving face in extra-thick coal seams by Hai Rong, Longyue He, Yadi Wang, Xiangzhi Wei, Shilong Wei, Suihan Yang, Jincheng Li, Linlin Chen

“…The research results provide theoretical support for roof pre-splitting and rock burst prevention of the 12,240 working face in Gengcun Coal Mine and can offer guidance for the prediction and prevention and control of rock burst risk in mines and working faces under similar conditions.…”
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The value of inflammation-related indicators in chemotherapy efficacy and disease-free survival of triple-negative breast cancer by Jie Zhu, Jiale Cheng, Yuyuan Ma, Ying Wang, Zhonghua Zou, Wenjie Wang, Haihua Shi, You Meng

“…A nomogram was used for the prediction of 1-, 2-, and 3-year disease-free survival (DFS). …”
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Integration of ground-based and remote sensing data with deep learning algorithms for mapping habitats in Natura 2000 protected oak forests by Lucia Čahojová, Ivan Jarolímek, Barbora Klímová, Michal Kollár, Michaela Michalková, Karol Mikula, Aneta A. Ožvat, Denisa Slabejová, Mária Šibíková

“…This algorithm aims to create a prediction map of habitats dominated by Quercus cerris, which is also known as the relevancy map.Through the utilisation of the Natural Numerical Network, a training accuracy of 95.24% was achieved. …”
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Prognostic Value of Inflammatory and Nutritional Indicators in Non-Metastatic Soft Tissue Sarcomas by Yan Y, Zhang Y, Chen Y, Zhong G, Huang W, Zhang Y

“…The combination index of the SIRI+AGR+Enneking stage provides a more robust prediction of clinical prognosis in STS patients.Keywords: soft tissue sarcoma, prognostic index, inflammatory, survival analysis…”
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Peningkatan Performa Ensemble Learning pada Segmentasi Semantik Gambar dengan Teknik Oversampling untuk Class Imbalance by Arie Nugroho, M. Arief Soeleman, Ricardus Anggi Pramunendar, Affandy Affandy, Aris Nurhindarto

“…In reality, a lot of data has unbalanced classes or labels, of course, it will affect the accuracy of a prediction. This research discusses how to improve the accuracy of image semantic segmentation in the ensemble learning method to deal with the problem of unbalanced data in image segmentation. …”
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Impaired hippocampal neurogenesis associated with regulatory ceRNA network in a mouse model of postoperative cognitive dysfunction by Jingrun Lin, Xiaoqiu Zhu, Xuan Li, Yu Hong, Yaohui Liang, Siqi Chen, Chenzhuo Feng, Lin Cao

“…Additionally, drugs were predicted as potential therapeutic candidates for POCD treatment. …”
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Machine learning-based plasma metabolomics for improved cirrhosis risk stratification by Jingru Song, Ziwei Gao, Liqun Lai, Jie Zhang, Binbin Liu, Yi Sang, Siqi Chen, Jiachen Qi, Yujun Zhang, Huang Kai, Wei Ye

“…Similarly, the combination of metabolomics with APRI also improved predictive performance compared to APRI alone (Harrell’s C: 0.747 vs. 0.718, ΔC = 0.029, 95% CI 0.022–0.035, NRI: 0.378 [0.366–0.389]). …”
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Perbandingan Prediksi Penggunaan Listrik dengan Menggunakan Metode Long Short Term Memory (LSTM) dan Recurrent Neural Network (RNN) by Nurfatima Selle, Novanto Yudistira, Candra Dewi

“…Therefore, we need a system that can predict the use of electricity by leveraging historical data on previous electricity usage. …”
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Multiomics identify the gene expression signature of the spinal cord during aging process by Lintao Xu, Jingyu Wang, Jinjie Zhong, Weiwei Lin, Gerong Shen, Ning He, Xingjia Mao, Chunyan Fu, Zhaobo Huang, Fengdong Zhao, Xin Ye, Yongjian Zhu, Mingzhi Zheng, Hui Li, Lin-lin Wang, Kai Zhong, Lijun Zhu, Ying-ying Chen

“…Pathway enrichment analysis of differentially expressed genes shows that senescence in spinal cords is related to phagosome function, neuroinflammation, ferroptosis, and necroptosis. Prediction of upstream transcription factors and interactome analysis identify Spi1 as a transcription factor that potentially plays a core role in senescent spinal cords. …”
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