Development of flip-chip technology for the optical drive of superconducting circuits [version 2; peer review: 1 approved, 2 approved with reservations] by Shekhar Priyadarshi, Marco Kraus, Alexander Fernandez Scarioni, Judith Felgner, Mark Bieler, Johannes Kohlmann, Hao Tian, Oliver Kieler

“…To further increase the yield and success rate of the flip-chip procedure, the size of the gold stud bumps, and flip-chip parameters were optimized. Moreover, to connect optical fibers to the photodiodes in an optimal position, the fiber sleeves were aligned with specially fabricated alignment circles before applying thermocompression with the flip-chip machine. …”
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A survey of GNSS receiver autonomous integrity monitoring: Research status and opportunities by Zhen Huang, Zhen Huang, Weihua Mou, Weihua Mou, Rui Wang, Pengpeng Li, Pengpeng Li, Zhicheng Lyu, Zhicheng Lyu, Gang Ou, Gang Ou

“…The paper provides a comprehensive review of RAIM algorithms for global navigation satellite system (GNSS) positioning applications. The parameters related to integrity assessment and typical fault detection and exclusion methods are reviewed, and RAIM is categorized into three types of methods: error probability distribution model-based, set representation-based, and machine learning-based. …”
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Construction of a predictive model for rebleeding risk in upper gastrointestinal bleeding patients based on clinical indicators such as Helicobacter pylori infection by Wei Zang, Ze Lin, Yanduo Zhao, Tianshi Jia, Xinglong Zhang

“…The rebleeding detection rates of Rockall score, AIMS65 score and Glasgow Blatchford score were 16.14%, 0 and 77.17%, respectively. Of the four machine learning models, Random Forest (RF) had the highest accuracy on the test set at 0.68. …”
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Study on Point Spread Function of Perovskite Fast Neutron Scintillation Imaging Screen by FENG Zhelin1, LIU Linyue2, , SONG Yan2, DUAN Baojun2, BAO Zizhen3, OUYANG Xiaoping2

“…Additionally, the limited availability of experimental machines for fast neutron imaging and the high cost of imaging systems hinders the efficient detection of large number of materials by using common fast neutron sources. …”

An Integrated Mycobacterial CT Imaging Dataset with Multispecies Information by Zhilin Han, Yuyang Zhang, Wenlong Ding, Xiaoting Zhao, Bingzhen Jia, Tingting Liu, Liang Wan, Zhiheng Xing

“…This resource aims to catalyze AI algorithm development for differential diagnosis, ultimately enhancing precision in NTM management through advanced machine learning applications.…”
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Design of Compliant Components in Linkage-Driven Prosthetic Fingers: A Multi-Material Printing-Based Method by Ludovica Nini, Lucia Tontini, Nevio Luigi Tagliamonte, Loredana Zollo, Fabrizio Taffoni

“…The proposed method is tested on a specific link and validated using an Instron Universal Testing machine to experimentally identify the best manufacturing parameters. …”
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Advanced Computational Methods for Mitigating Shock and Vibration Hazards in Deep Mines Gas Outburst Prediction Using SVM Optimized by Grey Relational Analysis and APSO Algorithm by Xiang Wu, Zhen Yang, Dongdong Wu

“…Moreover, adaptive particle swarm optimization (APSO) was used to optimize the penalty factor and kernel parameters of the support vector machine to improve the global search ability and avoid the occurrence of the local optimal solutions. …”
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Electric discharge process modelling when piston pins recovery in internal combustion engines by E. S. Savenko, E. S. Savenko, S. A. Matvienko, A. G. Kasparyants

“…The calculation method determines the modes and parameters of the process of electrohydraulic distribution of piston pins while maintaining their fatigue life, static strength and wear resistance.Results. …”
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Application of 3D printing technology to the components subjected to significant mechanical loads, using the example of a prosthetic climbing foot prototype by Kamil Warchoł, Monika Szuba, Anna Kopeć, Adam Martowicz, Jakub Bryła

“…The paper describes the results of a study aimed at identifying the mechanical parameters of a prosthetic foot designed for wall climbing. …”
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BAFL-SVM: A blockchain-assisted federated learning-driven SVM framework for smart agriculture by Ruiyao Shen, Hongliang Zhang, Baobao Chai, Wenyue Wang, Guijuan Wang, Biwei Yan, Jiguo Yu

“…To address the above problems, we propose a blockchain-assisted federated learning-driven support vector machine (BAFL-SVM) framework to realize efficient data sharing and privacy protection. …”
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Evaluation of the Morphology and Malachite Green Absorption Capacity of Modified Electrospun Chitosan Nanofibers by Hien Thi Thanh Nguyen, Thao Thi Ngoc Dang, Tan Minh Ha, Nhi Tran Yen Nguyen

“…This result is due to the interaction between the functional group of the polymers that increases entanglement. Machine operating and polymer solution parameters affect the nanofiber morphology. …”
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Securing the Shared Kernel: Exploring Kernel Isolation and Emerging Challenges in Modern Cloud Computing by Sehar Zehra, Hassan Jamil Syed, Fahad Samad, Ummay Faseeha, Hamza Ahmed, Muhammad Khurram Khan

“…However, unlike Virtual Machines (VMs), containers share the underlying machine’s operating system (OS) kernel, which introduces unique security challenges alongside speed and efficiency benefits. …”
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Processing and Quality Evaluation of Additive Manufacturing Monolayer Specimens by Christiane Wendt, Severo Raúl Fernández-Vidal, Álvaro Gómez-Parra, Moisés Batista, Mariano Marcos

“…This work also studies the effect of some manufacturing parameters such as the gap between print head and machine bed, trajectory strategy, bed leveling, and temperatures on part quality. …”
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A road hypnosis identification method for drivers based on fusion of biological characteristics by Longfei Chen, Jingheng Wang, Xiaoyuan Wang, Bin Wang, Han Zhang, Kai Feng, Gang Wang, Junyan Han, Huili Shi

“…In this paper, vehicle and virtual driving experiments are designed to collect the biological characteristics including eye movement and bioelectric parameters. Typical scenes in tunnels and highways are used as experimental scenes. …”
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Biosensors integrated within wearable devices for monitoring chronic wound status by Sabine Szunerits, Rabah Boukherroub, Christoph Kleber, Wolfgang Knoll, Jhonny Yunda, José Rumipamba, Guido Torres, Sorin Melinte

“…The state-of-the-art of time-resolved monitoring of the wound status by quantifying key physiological parameters as well as wound biomarkers' concentration is presented herewith. …”
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Efficient automated detection of power quality disturbances using nonsubsampled contourlet transform & PCA-SVM by Pampa Sinha, Kaushik Paul, Asit Mohanty, IM Elzein, Chandra Sekhar Mishra, Mohamed Metwally Mahmoud, Daniel Eutyche Mbadjoun Wapet, Abdulrahman Al Ayidh, Ahmed Althobaiti, Hany S Hussein, Thamer AH Alghamdi, Ahmed M Ewais

“…These optimized features are used for training a multi-class support vector machine, with its parameters further optimized for enhanced classification accuracy. …”
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Mechanical properties of human spinal dura mater show rate dependency by Tomasz Wiczenbach, Radosław Wolny, Dawid Bruski, Karol Daszkiewicz, Wiktoria Kolczyk, Jan Henryk Spodnik, Ilya Krypets, Lukasz Pachocki

“…The experiments utilized a custom-built uniaxial testing machine. The test enabled the determination of ultimate tensile strength, stretch at failure, and elastic modulus. …”
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An integrated AI-driven framework for maximizing the efficiency of heterostructured nanomaterials in photocatalytic hydrogen production by Pramod N. Belkhode, Shrikant M. Awatade, Chander Prakash, Sagar D. Shelare, Deepali Marghade, Sameer Sheshrao Gajghate, Muhamad M. Noor, Milon Selvam Dennison

“…Reinforcement Learning optimises synthesis parameters, reducing experimental iterations by 40% and boosting hydrogen yield by 15–20%. …”
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Artificial intelligence-driven clinical decision support systems for early detection and precision therapy in oral cancer: a mini review by Manoj Kumar Karuppan Perumal, Remya Rajan Renuka, Suresh Kumar Subbiah, Prabhu Manickam Natarajan

“…Moreover, the AI-CDSS also optimizes treatment plans on the basis of unique patient parameters, tumor stages and risk factors, providing personalized therapy.…”
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Viral particle prediction in wastewater treatment plants using nonlinear lifelong learning models by Jianxu Chen, Ibrahima N’Doye, Yevhen Myshkevych, Fahad Aljehani, Mohammad Khalil Monjed, Taous-Meriem Laleg-Kirati, Pei-Ying Hong

“…This paper proposes lifelong learning approaches that integrate long short-term memory (LSTM), gated recurrent unit (GRU) and tree-based machine learning models with knowledge-based dictionaries for real-time viral prediction across various wastewater treatment plants (WWTPs) in Saudi Arabia. …”
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