Research on Innovation Efficiency of Listed Companies in Development Zone Based on the Three-Stage DEA-Tobit Model: A Case Study of Hubei Province by Peng Xu, Fan Luo, Ziyue Zhang, Hongyi Xu

“…This study applies 3-stage data envelopment (DEA) of 24 listed companies in the development zone of Hubei Province from 2012 to 2017 based on the panel data; we used the DEA-Tobit model and regression analysis method on the sample in order to measure the factors affecting the innovation efficiency of listed companies and the efficiency of corporate innovation. …”
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Energy-efficient neuromorphic system using novel tunnel FET based LIF neuron design for adaptable threshold logic and image analysis applications by Faisal Bashir, Furqan Zahoor, Ali Alzahrani, Haider Abbas

“…This offers a solution for the design of highly scalable and energy efficient threshold logic circuits for future neuromorphic computing systems. …”
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Efficient Extraction of Lithium, Cobalt, and Nickel from Nickel-Manganese-Cobalt Oxide Cathodes with Cholin Chloride/Pyrogallol-Based Deep Eutectic Solvent by Aisulu Batkal, Kaster Kamunur, Lyazzat Mussapyrova, Yerzhan Mukanov, Rashid Nadirov

“…The DES exhibits moderate viscosity, intrinsic redox activity, and strong complexation ability, enabling efficient metal dissolution under mild conditions. …”
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Analysis of technology innovation efficiency and its impact factors based on DEA-fsQCA method: Evidence from listed seed companies in China by Ming Mo, Lidanting Zeng

“…This study utilizes micro-data from listed seed companies in China spanning the years 2019–2023 to conduct a comprehensive analysis of enterprise innovation efficiency. The research aims to identify strategies for enhancing innovation efficiency and ultimately fostering development within these seed companies. …”
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The Adsorption of Ru-Based Dyes on the TiO₂ Surface to Enhance the Photovoltaic Efficiency of Dye-Sensitized Solar Cell Devices by Malgorzata Makowska-Janusik, Katarzyna Filipecka-Szymczyk, Daniel Pelczarski, Waldemar Stampor, Maciej Zalas

“…It was shown that the adsorption efficiency of the ruthenium-based dyes on the TiO₂ surface depends on the position of the anchoring -COOH group in the molecular structure. …”
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Research on the Measurement, Evolution, and Driving Factors of Green Innovation Efficiency in Yangtze River Economic Belt: A Super-SBM and Spatial Durbin Model by Renyan Long, Hangyuan Guo, Danting Zheng, Ronghua Chang, Sanggyun Na

“…In order to implement the concept of sustainable development, the improvement of logistics ecological efficiency is related to the quality of ecological civilization construction. …”
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Face autistic classification based on thermal using image ensemble learning of VGG-19, ResNet50v2, and EfficientNet by Junidar Junidar, Melinda Melinda, Dinda D. Diannuari, Donata D. Acula, Zulfan Zainal

“…The results revealed that ResNet50V2 achieved the highest accuracy of 98.82%, followed by VGG-19 and EfficientNet with accuracies of 96.47% and 96.07%, respectively. …”
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Efficient removal of sulfamethoxazole antibiotic from aqueous solution using red mud/layered double hydroxide nanocomposite: Optimization, kinetic, and isotherm studies by Ahmed A. Mohammed, Zahraa Ali Hammood

“…Maximum sequestration efficiency was seen at 87.33 % under the most favorable conditions (pH = 7, dose = 0.5 g/100 ml, concentration = 70 mg/l, time = 90 min). …”
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ScaleViM-PDD: Multi-Scale EfficientViM with Physical Decoupling and Dual-Domain Fusion for Remote Sensing Image Dehazing by Hao Zhou, Yalun Wang, Wanting Peng, Xin Guan, Tao Tao

“…State-space models (SSMs) have recently emerged as a powerful paradigm for vision tasks, showing great promise due to their computational efficiency and robust capacity to model global dependencies. …”
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Lightweight convolutional neural networks using nonlinear Lévy chaotic moth flame optimisation for brain tumour classification via efficient hyperparameter tuning by Amin Abdollahi Dehkordi, Mehdi Neshat, Alireza Khosravian, Menasha Thilakaratne, Ali Safaa Sadiq, Seyedali Mirjalili

“…The findings demonstrate that the lightweight CNN combined with NLCMFO provides a computationally efficient yet highly accurate solution for medical image classification, addressing the challenges associated with traditional deep CNNs.…”
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SUBCELLULAR, MOLECULAR AND SUBMOLECULAR MECHANISMS OF ALTERED CONTRACTILITY AND EFFICIENCY OF ENERGY TRANSFORMATION BY MYOCARDIAL MYOFIBRILS IN CHRONIC HEART FAILURE AND MODE OF AC... by N. V. Karsanov, G. V. Sukoyan, T. G. Samsonidze, D. R. Tatulashvili, N. E. Guledani, L. T. Kuchava, V. N. Karsanov

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Research on dynamic prediction and optimization of high altitude photovoltaic power generation efficiency using GVSAO-CNN Model under 8-climate modes by Xiaoming Xiong, Heng Hu, Qiangfu Jia, Rongjian Zhang, Chongan Huang, Qingyuan Lu

“…The GVSAO-CNN model, with its demonstrated ability to effectively capture dynamic efficiency changes in complex high-altitude climates, shows promise for enhancing smart grid integration, policy-making, and disaster preparedness in high-altitude regions, as evidenced by similar applications of CNN-based models in smart grid technologies. …”
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Constructing of Ni-Nx Active Sites in Self-Supported Ni Single-Atom Catalysts for Efficient Reduction of CO₂ to CO by Xuemei Zhou, Chunxia Meng, Wanqiang Yu, Yijie Wang, Luyun Cui, Tong Li, Jingang Wang

“…Carbon-based materials featuring single-atom transition metal-nitrogen coordination (M-N_x) have attracted considerable research attention due to their ability to maximize catalytic efficiency while minimizing metal atom usage. …”
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Novel Solution‐Processed Fe2O3/WS2 Hybrid Nanocomposite Dynamic Memristor for Advanced Power Efficiency in Neuromorphic Computing by Faisal Ghafoor, Honggyun Kim, Bilal Ghafoor, Zaheer Ahmed, Muhammad Farooq Khan, Muhammad Rabeel, Muhammad Faheem Maqsood, Sobia Nasir, Wajid Zulfiqar, Ghulam Dastageer, Myoung‐Jae Lee, Deok‐kee Kim

“…Abstract Non‐volatile memory (NVM) based neuromorphic computing, which is inspired by the human brain, is a compelling paradigm in regard to building energy‐efficient computing hardware that is tailored for artificial intelligence. …”
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Advancing ship automatic navigation strategy with prior knowledge and hierarchical penalty in irregular obstacles: a reinforcement learning approach to enhanced efficiency and safe... by Hao Zhang, Jiawen Li, Jiawen Li, Jiawen Li, Jiawen Li, Liang Cao, Liang Cao, Liang Cao, Shucan Wang, Ronghui Li, Ronghui Li, Ronghui Li

“…The experimental results show that the GEPA model outperforms the existing methods in terms of navigating efficiency, training convergence speed, path smoothness, obstacle avoidance ability and safety, with the number of training rounds to complete the task reduced by 24.85%, the path length reduced by up to about 70 pixels, the safety distance improved by 70.6%, and the number of collisions decreased significantly. …”
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Influence of substrate particle size and detention time on mycelium-colonized sawdust efficiency for removal of faecal bacteria from slaughterhouse wastewater in batch treatment by Osayomwanbo OSARENOTOR, Isoken Tito AIGHEWI, Helen Michelle Korkor ESSANDOH, Juan Cruz TUBIO

“…Salmonella spp. removal efficiency ranged from 0.66 – 71 % with the highest efficiency recorded in the system with 1.16 mm also at 72 hours (0.4 log removal). …”
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A data-efficient deep transfer learning framework for methane super-emitter detection in oil and gas fields using the Sentinel-2 satellite by S. Zhao, S. Zhao, Y. Zhang, Y. Zhang, S. Zhao, S. Zhao, X. Wang, X. Wang, D. J. Varon

“…<p>Efficiently detecting large methane point sources (super-emitters) in oil and gas fields is crucial for informing stakeholder decisions about mitigation actions. …”
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New understanding of microbial growth cycle for efficient waste-activated sludge disposal by preserving microbial self-degradation activity during the decline phase by Xiqi Li, Aijie Wang, Zhe Yu, Hualin Wang, Hengzhi You, Jifei Xu, Jingyu Zhang, Wenzong Liu

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Probing the Pitfalls: Understanding SVD’s Shortcomings in Language Model Compression by Сергей Александрович Плетенев

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MapSAM: adapting segment anything model for automated feature detection in historical maps by Xue Xia, Daiwei Zhang, Wenxuan Song, Wei Huang, Lorenz Hurni

“…Despite this, directly applying SAM in a zero-shot manner to historical map segmentation poses significant challenges, including poor recognition of certain geospatial features and a reliance on input prompts, which limits its ability to be fully automated. To address these challenges, we introduce MapSAM, a parameter-efficient fine-tuning strategy that adapts SAM into a prompt-free and versatile solution for various downstream historical map segmentation tasks. …”
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