Piezoelectrically and Capacitively Transduced Hybrid MEMS Resonator with Superior RF Performance and Enhanced Parasitic Mitigation by Low-Temperature Batch Fabrication by Adnan Zaman, Ugur Guneroglu, Abdulrahman Alsolami, Jing Wang

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Semi-supervised contrastive learning variational autoencoder Integrating single-cell multimodal mosaic datasets by Zihao Wang, Zeyu Wu, Minghua Deng

“…To address this issue, researchers began simultaneously collect multi-modal single-cell omics data. But different sequencing technologies often result in datasets where one or more data modalities are missing. …”
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Enhanced expression of full-length human cytomegalovirus fusion protein in non-swelling baculovirus-infected cells with a minimal fed-batch strategy. by Marco Patrone, Nuno Carinhas, Marcos Q Sousa, Cristina Peixoto, Claudio Ciferri, Andrea Carfì, Paula M Alves

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Purification of Biodiesel Polluted by Copper Using an Activated Carbon Prepared from Spent Coffee Grounds: Adsorption Property Tailoring, Batch and Packed-Bed Studies by Daniel Eduardo Cárdenas-Piñeros, Hilda Elizabeth Reynel-Ávila, Lizbeth Liliana Díaz-Muñoz, Adrián Bonilla-Petriciolet, Carlos Javier Durán-Valle, Marta Adame-Pereira

“…Adsorbent characterization and adsorption modeling indicated that copper removal was driven by multi-cationic interactions, where carboxylic groups from carbon surface acted as key active sites. …”
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HarmonizR: blocking and singular feature data adjustment improve runtime efficiency and data preservation by Simon Schlumbohm, Julia E. Neumann, Philipp Neumann

“…Abstract Background Data adjustment is an essential tool for increasing statistical power during analysis, for example in case of complex multi-experiment data from (single-cell) RNA, proteomics and other omics data. …”
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A Multi-Machine and Multi-Modal Drift Detection (M2D2) Framework for Semiconductor Manufacturing by Chin-Yi Lin, Tzu-Liang (Bill) Tseng, Tsung-Han Tsai

“…To surmount these challenges, we present M2D2 (Multi-Machine and Multi-Modal Drift Detection), an end-to-end framework that integrates data preprocessing, baseline modeling, short- and long-term drift detection, interpretability, and a drift-aware federated paradigm. …”
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Bi-Level Collaborative Optimization for Medical Consumable Order Splitting and Reorganization Considering Multi-Dimensional and Multi-Scale Characteristics by Peng Jiang, Shunsheng Guo, Xu Luo

“…To address these challenges, this study proposes a bi-level optimization model for order splitting and reorganization considering multi-dimensional and multi-scale characteristics. …”
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Multi-Domain Features and Multi-Task Learning for Steady-State Visual Evoked Potential-Based Brain–Computer Interfaces by Yeou-Jiunn Chen, Shih-Chung Chen, Chung-Min Wu

“…In this study, a steady-state visual evoked potential-based BCI (SSVEP-based BCI) with multi-domain features and multi-task learning is developed. …”
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OPTIMIZING THE PLACEMENT OF A WORK-PIECE AT A MULTI-POSITION ROTARY TABLE OF TRANSFER MACHINE WITH VERTICAL MULTI-SPINDLE HEAD by N. N. Guschinski, V. E. Zdanovich, B. M. Rozin

“…The problem of minimizing the weight of transfer machine with a multi-position rotary table by placing of a work-piece at the table for processing of homogeneous batch of work-pieces is considered. …”
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Research on multi-objective energy optimization design for multi-story residential buildings in Suzhou region based on artificial neural networks by Zhongcheng Duan, Leilei Wang, Binhao Li, Gang Yao

“…To address the issues of high energy consumption, low thermal comfort, and excessive greenhouse gas emissions in residential buildings, this study optimizes multi-story residential buildings in the Suzhou region using a multi-objective Non-dominated Sorting Genetic Algorithm III (NSGA-III) coupled with an Artificial Neural Network (ANN). …”
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GDnet-IP: Grouped Dropout-Based Convolutional Neural Network for Insect Pest Recognition by Dongcheng Li, Yongqi Xu, Zheming Yuan, Zhijun Dai

“…Additionally, we replaced ReLU with PReLU and added BatchNorm layers after each Inception layer, enhancing the model’s nonlinear expression and training stability. …”
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Efficient Orchestration of Distributed Workloads in Multi-Region Kubernetes Cluster by Radoslav Furnadzhiev, Mitko Shopov, Nikolay Kakanakov

“…However, default scheduling mechanisms primarily optimize for resource availability, often neglecting network topology, inter-node latency, and global resource efficiency, leading to suboptimal task placement in multi-region deployments. This paper proposes network-aware scheduling plugins that integrate heuristic, metaheuristic, and linear programming methods to optimize resource utilization and inter-zone communication latency for containerized workloads, particularly Apache Spark batch-processing tasks. …”
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Multi-level residual network VGGNet for fish species classification by Eko Prasetyo, Nanik Suciati, Chastine Fatichah

“…In this paper, we proposed Multi-Level Residual (MLR) as a new residual network strategy by combining low-level features of the initial block with high-level features of the last block by applying Depthwise Separable Convolution. …”
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Shanshan: a question-answering system for computer general courses with high throughput and low latency by YANG Yun, LIU Tianyang, WANG Shuo, SU Bin, PU Peng, LU Xuesong

“…Performance evaluation experiments indicated that the system achieved superior performance in terms of concurrency, response time, and multi-turn dialogue compared to alternative methods.…”
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BIT*+TD3 Hybrid Algorithm for Energy-Efficient Path Planning of Unmanned Surface Vehicles in Complex Inland Waterways by Yunze Xie, Yiping Ma, Yiming Cheng, Zhiqian Li, Xiaoyu Liu

“…This research proposes a hybrid path planning framework for intelligent inland waterway Unmanned Surface Vehicles (USVs), which integrates the enhanced BIT* (Batch Informed Trees) algorithm with the TD3 (Twin Delayed Deep Deterministic Policy Gradient) deep reinforcement learning method. …”
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IMpc-PyrYOLO: Hybrid YOLO Based Feature Pyramidal Network for Pest Detection in Rice Leaves by Ramesh Shunmugam, Sumendra Yogarayan, Siti Fatimah Abdul Razak, Md. Shohel Sayeed

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A User-Priority-Driven Multi-UAV Cooperative Reconnaissance Strategy by Zeyuan Liu, Cuntao Liu, Wendong Zhao, Aijing Li

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Autonomous multi-robot synthesis and optimization of metal halide perovskite nanocrystals by Jinge Xu, Christopher H. J. Moran, Arup Ghorai, Fazel Bateni, Jeffrey A. Bennett, Nikolai Mukhin, Koray Latif, Andrew Cahn, Pragyan Jha, Fernando Delgado Licona, Sina Sadeghi, Lior Politi, Milad Abolhasani

“…Herein, we introduce Rainbow, a multi-robot self-driving laboratory that integrates automated NC synthesis, real-time characterization, and machine learning (ML)-driven decision-making to efficiently navigate MHP NCs’ mixed-variable high-dimensional landscape. …”
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Detection of human activities using multi-layer convolutional neural network by Essam Abdellatef, Rasha M. Al-Makhlasawy, Wafaa A. Shalaby

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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

“…Next, we incorporate a P2 layer (Pyramid Pooling Layer 2) in the neck of YOLOv8, blending the concepts of shared convolutional information and independent batch normalization to design a P2-LSCSBD (P2 Layer-Lightweight Shared Convolutional and Batch Normalization-based Small Object Detection) detection head. …”
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