Implementing Blockchain Technology for Secure Data Transactions in Cloud Computing Environments Challenges and Solutions by Dandu Varalakshmi, N Shirisha, K Suresh, Saidhbi Shaik, V Venkatesh, C F Theresa Cenate

“…It also includes quantum-resilient cryptographic algorithms, which provide protection against potential future quantum attacks. …”
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A data management system for precision medicine. by John J L Jacobs, Inés Beekers, Inge Verkouter, Levi B Richards, Alexandra Vegelien, Lizan D Bloemsma, Vera A M C Bongaerts, Jacqueline Cloos, Frederik Erkens, Patrycja Gradowska, Simon Hort, Michael Hudecek, Manel Juan, Anke H Maitland-van der Zee, Sergio Navarro-Velázquez, Lok Lam Ngai, Qasim A Rafiq, Carmen Sanges, Jesse Tettero, Hendrikus J A van Os, Rimke C Vos, Yolanda de Wit, Steven van Dijk

“…MedDMS for precision medicine should be able to process hundreds of parameters from multiple sites, be adaptable while remaining in sync at multiple locations, real-time syncing to analytics and be compliant with international privacy legislation. …”
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Comparative analysis of antibodies and lymphocytes in pulmonary tuberculosis patients with negative and positive cultures by Fernando-Renato Cázares-Sosa, Alejandro Hernández-Solís, Atenea-Estela Andrés-Dionicio, Heliodora González-González, Miguel Ibáñez-Hernández, Raúl Cicero-Sabido, Herón Huerta, Raquel Tapia-Romero, Jorge-Luis de-la-Rosa-Arana

“…Results: IgG and IgA levels were detected in patients with positive culture, while only IgA was found in patients with negative cultures. …”
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An Improved YOLOP Lane-Line Detection Utilizing Feature Shift Aggregation for Intelligent Agricultural Machinery by Cundeng Wang, Xiyuan Chen, Zhiyuan Jiao, Shuang Song, Zhen Ma

“…For lane-line detection tasks, we also propose an improved YOLOP lane-line detection algorithm based on feature shift aggregation. Homemade datasets were used for training and testing. …”
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Identification and validation of hub genes associated with biotic and abiotic stresses by modular gene co-expression analysis in Oryza sativa L. by Izreen Izzati Razalli, Muhammad-Redha Abdullah-Zawawi, Rabiatul Adawiah Zainal Abidin, Sarahani Harun, Muhamad Hafiz Che Othman, Ismanizan Ismail, Zamri Zainal

“…HSP70 showed no changes, while HSP90 was upregulated in susceptible rice during blast and drought. …”
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Improved Inland Water Level Estimates with Sentinel-6 Fully Focused SAR Processing: A Case Study in the Ebre River Basin by Xavier Domingo, Ferran Gibert, Robert Molina, Maria Jose Escorihuela

“…Moreover, we evaluate the application of extended water masks, which exploit nadir–altimeter measurements where water is at nadir or up to 250 <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi mathvariant="normal">m</mi></semantics></math></inline-formula> across-track from nadir to increase the number of acquisitions while maintaining the same level of accuracy, increasing by an average of 48% the number of valid measurements per pass, while maintaining the same level of accuracy as nadir measurements over water. …”
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Deep Learning Models for Detection and Severity Assessment of Cercospora Leaf Spot (<i>Cercospora capsici</i>) in Chili Peppers Under Natural Conditions by Douglas Vieira Leite, Alisson Vasconcelos de Brito, Gregorio Guirada Faccioli, Gustavo Haddad Souza Vieira

“…While Mask R-CNN excels in segmentation accuracy, YOLOv8 offers a compelling balance of speed and reliable severity classification, making it suitable for real-time plant disease assessment in agricultural applications.…”
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Energy and carbon-aware distributed machine learning tasks scheduling scheme for the multi-renewable energy-based edge-cloud continuum by Miao Zicong, Liu Lei, Nan Haijing, Li Weize, Pan Xiaodong, Yang Xin, Yu Mi, Chen Hui, Zhao Yiming

“…Compared with existing competing algorithms, the proposed method exhibits significant improvements with an achieved average response time of 12.6 ms, and a task failure rate of 1.25%.…”
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LSTM‐based real‐time stress detection using PPG signals on raspberry Pi by Amin Rostami, Koorosh Motaman, Bahram Tarvirdizadeh, Khalil Alipour, Mohammad Ghamari

“…The authors have developed an advanced AI algorithm that achieves high accuracy in real‐time stress detection using photoplethysmography (PPG) sensors while significantly reducing computational demands. …”
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Rethinking Conservation and Restoration Strategies of Endangered and Key Medicinal Clavicarpa Plants in Yunnan‐Kweichow Plateau's Karst Areas Under Climate Change by Chao Luo, Baiyang He, Yulu Wu, Yuteng Xue, Huang Deng, Shanman Li, Xianghong Dong, Litang Lu

“…Conversely, climate change projections suggest a habitat expansion for Impatiens claviger, Impatiens tubulosa, Impatiens pritzelii, and Impatiens apalophylla, while Impatiens guizhouensis and Impatiens wilsonii face increased extinction risks. …”
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Spatial Heterogeneity and Hierarchy of Metropolitan Area Expansion and Land Surface Temperature Evolution: A Twin City Perspective by Mengqiu Cui, Liang Zhou, Wenda Wang, Dongqi Sun, Bo Yuan, Wei Wei

“…Besides, its structure tends to be more complex, which develops from 3 levels and 8 centers to 10 levels and 33 centers from 2000 to 2020. 2) The heat islands of XXMA tend to connect and reach the maximum area of 547.43 km² in 2015, while the LST evolution in two cities is not synchronized. …”
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Utilização de redes neurais artificiais na classificação de níveis de degradação em pastagens Use of artificial neural networks in the classification of degradation levels of pastu... by César S. Chagas, Carlos A. O. Vieira, Elpídio I. Fernandes Filho, Waldir de C. Júnior

“…The neural networks simulator used was the "Neural Java Network Simulator", with a feed forward model and the learning algorithm of back propagation. The obtained results show that the classification using neural networks, while presenting a slightly superior result, had a statistically similar performance compared to the maximum likelihood, getting a Kappa index of 0.80, against 0.79, respectively. …”
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Revealing long-term dynamics and spatiotemporal drivers of anthropogenic nutrients inputs in China: The effects of dietary and socioeconomic factors by Jia Liu, Wei Gao, Fen Guo, Yuan Zhang, Yanpeng Cai

“…Urbanization and GDP were dominant drivers in developed areas (Type I), while population was key in less–developed regions (Type II). …”
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SCL-YOLOv11: A Lightweight Object Detection Network for Low-Illumination Environments by Shulong Zhuo, Hao Bai, Lifeng Jiang, Xiaojian Zhou, Xu Duan, Yiqun Ma, Zihan Zhou

“…Experimental results on the ExDark dataset demonstrate that the proposed algorithm achieves 67.6% mAP@0.5 and 42.4% mAP@0.5:0.95, while reducing parameter count by 38.5% and computational cost by 25.4%. …”
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Human-Aware Robot Collaborative Task Planning Using Artificial Potential Field and DQN Reinforcement Learning by Jayesh Prakash, Sam Altnji, Karthick Thiyagarajan, Jogesh S. Nanda, Abhijit Biswas, Abhra Roy Chowdhury

“…A Deep Q Network (DQN) reinforcement learning model is used to train the robot to perform the goal reaching task while avoiding obstacles to ensure safety. The DQN algorithm makes use of the end-effector position and the relative positions with the goal and obstacles to train a policy that guides the robot arm safely. …”
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Optimization of microwave-assisted polyphenol extraction and antioxidant activity from papaya peel using response surface methodology and artificial neural network by Md. Waziur Rahman Chy, Tanvir Ahmed, Junaid Iftekhar, Md. Zohurul Islam, Md. Rahmatuzzaman Rana

“…These models were combined with the desirability function (DF) and/or genetic algorithm (GA) optimization approaches. Maximizing TPC and DPPH activity while maintaining MWP, I-time, EtOH%, and S/S within their respective ranges using hybrid optimization approaches (RSM-DF: TPC = 1058 mgGAE/100 g, and DPPH = 83 %, RSM-GA: TPC = 1064 mgGAE/100 g and DPPH = 79 %, and ANN-GA: TPC = 1086 mgGAE/100 g, and DPPH = 83 %,) yielded consistent optimal results. …”
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MRI-based 2.5D deep learning radiomics nomogram for the differentiation of benign versus malignant vertebral compression fractures by Wenhua Liang, Hong Yu, Lisha Duan, Xiaona Li, Ming Wang, Bing Wang, Jianling Cui

“…Radiomics (Rad) features were extracted using traditional Rad techniques, while 2.5-dimensional (2.5D) deep learning (DL) features were obtained using the ResNet50 model. …”
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APG mergence and topological potential optimization based heuristic user association strategy by Zhirui HU, Meihua BI, Fangmin XU, Meilin HE, Changliang ZHENG

“…Therefore, it is reasonable to model the problem of improving network scalable degree as minimizing network coupling degree,and it is feasible to improve network scalable degree by reducing network coupling degree.2)The upper limit of computational complexity of the proposed algorithm is <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML"> <mi mathvariant="script">O</mi><mo stretchy="false">(</mo><mi>K</mi><mi>N</mi><msub> <mi>log</mi> <mn>2</mn> </msub> <mi>N</mi><mo>+</mo><msup> <mi>k</mi> <mn>2</mn> </msup> <mo>+</mo><mi>N</mi><mi>N</mi><msub> <mover accent="true"> <mi>N</mi> <mo>¯</mo> </mover> <mtext>p</mtext> </msub> <mo stretchy="false">)</mo></math></inline-formula>,while that of directly solving the optimization problem is<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML"><mi mathvariant="script">O</mi><mo stretchy="false">(</mo><msup> <mi>N</mi> <mrow> <msub> <mover accent="true"> <mi>N</mi> <mo>¯</mo> </mover> <mtext>u</mtext> </msub> <mi>K</mi></mrow> </msup> <mo stretchy="false">)</mo></math></inline-formula>.3)For theoretical analysis of the network scalable degree,take Fig.3 as an example.If AP2 changes,12 APs in Fig. 3(a)are affected and the network scalable degree is η₂=0.51,while 4 APs in Fig.3(c)are affected and the network scalable degree is η₂=0.79.4)Fig.5 shows the simulation results of network scalable degree.Compared with the traditional strategy,the network scalable degree is improved by 9.59% with 4.43% user rate loss.Compared with the strategy in[10],the network scalable degree is improved by 22.15% with 4.99% user rate loss. 5) The algorithm parameters, the threshold β₀of overlap rate and the upper limit number N₀of AP associated, effect the performance.As shown in Fig.6,with β₀or N₀decreases,η increases and the total user rate decreases. …”
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Pengembangan Deep Learning untuk Sistem Deteksi Dini Komplikasi Kaki Diabetik Menggunakan Citra Termogram by Medycha Emhandyksa, Indah Soesanti, Rina Susilowati

“…In addition to the deep convolutional neural network architecture model 4, the research contribution obtained from this research is the use of filter size variations of 3x3, 2x2, and 1x1 with a fixed number of convolutional layers and a reduction in the number of hidden layers in the algorithm structure can reduce the number of model parameters while maintaining high detection capability. …”
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Introgression of chromosomal segments conferring early heading date from wheat diploid progenitor, Aegilops tauschii Coss., into Japanese elite wheat cultivars. by Shigeo Takumi, Seito Mitta, Shoya Komura, Tatsuya M Ikeda, Hitoshi Matsunaka, Kazuhiro Sato, Kentaro Yoshida, Koji Murai

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