Preparing Schrödinger Cat States in a Microwave Cavity Using a Neural Network by Hector Hutin, Pavlo Bilous, Chengzhi Ye, Sepideh Abdollahi, Loris Cros, Tom Dvir, Tirth Shah, Yonatan Cohen, Audrey Bienfait, Florian Marquardt, Benjamin Huard

“…Our experimental results demonstrate more generally how deep neural networks and transfer learning can produce efficient simultaneous solutions to a range of quantum control tasks, which will benefit not only state preparation but also parametrized quantum gates.…”
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LiFi for Industry 4.0: Main Features, Implementation and Initial Testing of IEEE Std 802.15.13 by Kai Lennert Bober, Anselm Ebmeyer, Falko Dressler, Ronald Freund, Volker Jungnickel

“…The standard specifies deterministic medium access control (MAC), based on dynamic time division multiple access (TDMA), as well as two physical layers (PHYs) for extended range and robustness, and for spectral efficiency, respectively. …”
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Does Pelleted Starter Feed Restriction and Provision of Total Mixed Ration Ad Libitum during Weaning Influence the Behavior of Dairy Calves? by Anna Antonella Spina, Marina Tortadès, Domenico Britti, Raffaella Grande, Valeria Maria Morittu

“…During weaning, rationed feeding is a practice used to improve feed efficiency and control the calves’ growth, but it could also have negative consequences associated with hunger and feed restriction behavior. …”
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Universal logical quantum photonic neural network processor via cavity-assisted interactions by Jasvith Raj Basani, Murphy Yuezhen Niu, Edo Waks

“…However, achieving high-fidelity universal control over bosonic encodings using native photonic hardware remains a significant challenge. …”
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A non-electrical pneumatic hybrid oscillator for high-frequency multimodal robotic locomotion by Genliang Chen, Yongzhou Long, Siyue Yao, Shujie Tang, Junjie Luo, Hao Wang, Zhuang Zhang, Hanqing Jiang

“…Abstract Pneumatic oscillators, incorporating soft non-electrical logic gates, offer an efficient means of actuating robots to perform tasks in extreme environments. …”
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A model of thalamo-cortical interaction for incremental binding in mental contour-tracing. by Daniel Schmid, Heiko Neumann

“…By which mechanisms this process is implemented and how it can be interacted with by means of attentional control is not completely understood yet. Incremental binding is a mechanism required in demanding scenarios of object-based attention and is experimentally well investigated. …”
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DA-FIS: A high-speed dynamic adaptive fault injection server framework for reliable FPGA-based embedded systems by Fatimah Alhayan, Gaganjot Kaur, Sultan Alanazi, Mohammed Burhanur Rehman, Wahida Mansouri, Da’ad Albalawneh, Ali Alqazzaz, Hanadi Alkhudhayr

“…Fault injection is a critical technique for assessing the reliability of field programmable gate array (FPGA)-based embedded systems, particularly in radiation-prone and safety-critical applications. …”
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Semantic segmentation of substation tools using an improved ICNet network by Guozhong Liu, Qiongping Tang, Changnian Lin, An Xu, Chonglong Lin, Hao Meng, Mengyu Ruan, Wei Jin

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Phase-pure ferroelectric quantum wells with tunable photoluminescence for multi-state optoelectronic applications by Rui Sun, Yuping Jia, Bo Lai, Zhiming Shi, Mingrui Liu, Weili Yu, Ke Jiang, Shanli Zhang, Shunpeng Lv, Yang Chen, Xiaojuan Sun, Dabing Li

“…These findings enabled the development of a simple system comprising gallium nitride (GaN) light emitting diodes (LEDs) and ferroelectric films to implement multi-state signal encoding and a logic AND gate. This work advances the fabrication of efficient ferroelectric MHP films and highlights their potential for advanced optoelectronic applications.…”
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Synergistic Artificial Intelligence framework for robust multivariate medium-term wind power prediction with uncertainty envelopes by Bo Wu, Xiuli Wang, Bangyan Wang, Yaohong Xie, Shixiong Qi, Wenduo Sun, Qihang Huang, Xiang Ma

“…The vertical–horizontal process integrates the Polar Lights Optimizer with Joint Opposite Selection and a regression model based on the bidirectional long short-term memory and the gated recurrent unit, enabling efficient hyperparameter optimization and yielding a determination coefficient above 0.9996 for training data and a normalized root mean square error of 0.2448 for test data. …”
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A review study on ai-driven robotics and automation in smart manufacturing: applications, challenges, and economic impacts by Timothy Adeyi, Jacob Adebayo, Olakunle Oresegun, Shade Ademokoya, Sunday Jegede, Adrian Cheok

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Balancing Complexity and Performance of Machine Learning Models for Avian Pests Sound Detection in Agricultural Environments by Micheline Kazeneza, Anna Sergeevna Bosman, Destiny Kwabla Amenyedzi, Damien Hanyurwimfura, Emmanuel Ndashimye, Anthony Vodacek

“…We evaluated convolutional neural networks (CNNs), recurrent neural networks (RNNs), and traditional ML models by comparing standalone and knowledge-distilled versions of EfficientNetB0 and gated recurrent unity (GRU) against EfficientNetB4, Long short-term memory (LSTM), MobileNetV2, LightGBM, and support vector machine (SVM). …”
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Non‐linear activation function approximation using a REMEZ algorithm by Samba Raju Chiluveru, Manoj Tripathy, Bibhudutta

“…It utilizes a precision‐controlled recursive algorithm to predict a sub‐range; after that, the REMEZ algorithm is used to find the corresponding approximation function. …”
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High-Precision Optimization of BIM-3D GIS Models for Digital Twins: A Case Study of Santun River Basin by Zhengbing Yang, Mahemujiang Aihemaiti, Beilikezi Abudureheman, Hongfei Tao

“…Applied to the Santun River Basin digital twin project, experiments with 10 water gate models show that the AW-QEM algorithm reduces average loading time by 15% compared to traditional QEM, while maintaining 97% geometric accuracy, demonstrating the method’s efficiency in balancing precision and rendering performance.…”
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Innovative reliable nanoscale QCA circuits for advanced morphological image processing by Mohammad Abdullah-Al-Shafi

“…The proposed design incorporates two majority gates and a control line to seamlessly perform dilation and erosion. …”
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High-Performance Carbon Nanotube Electronic Devices: Progress and Challenges by Zirui Zhang, Nie Zhang, Zhiyong Zhang

“…As silicon-based complementary metal-oxide-semiconductor (CMOS) technology approaches its physical and scaling limits at sub-3-nanometer nodes, critical challenges including the short-channel effect (SCE), surging power consumption, and aggravated parasitic effects have severely constrained further improvements in device performance, integration density, and energy efficiency. Carbon nanotubes (CNTs), with their superior electrical properties, exceptional gate controllability enabled by one-dimensional nanostructure, and compatibility with existing semiconductor processes, have emerged as an ideal candidate material for post-silicon high-performance electronics. …”
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Scalable Architecture for Trapped-Ion Quantum Computing Using rf Traps and Dynamic Optical Potentials by David Schwerdt, Lee Peleg, Yotam Shapira, Nadav Priel, Yanay Florshaim, Avram Gross, Ayelet Zalic, Gadi Afek, Nitzan Akerman, Ady Stern, Amit Ben Kish, Roee Ozeri

“…We show that these cells behave as nearly independent quantum registers, allowing for parallel entangling gates on all cells. The ability to reconfigure the optical potentials guarantees connectivity across the full ion crystal and also enables efficient midcircuit measurements. …”
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Effects of Standardized Natural Citrus Extract on Growth, Gut Health, Carcass Quality, and Welfare of Broiler Chickens by Sekhou Cisse, Arkadiusz Matuszewski, Damian Bień, Patrycja Ciborowska, Anna Zalewska, Jakub Urban, Monika Michalczuk, Marta Mendel, Urszula Latek, Joanna Polak, Małgorzata Sobczak-Filipiak, Paweł Konieczka, Mohammed El Amine Benarbia

“…The feed conversion ratio (FCR) and European Efficiency Index (EEI) of broiler chickens were also calculated weekly. …”
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Leveraging Neural Trojan Side-Channels for Output Exfiltration by Vincent Meyers, Michael Hefenbrock, Dennis Gnad, Mehdi Tahoori

“…To achieve low latency and high efficiency, field-programmable gate arrays (FPGAs) are increasingly being employed as accelerators for neural network inference in cloud and edge devices. …”
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LDAGM: prediction lncRNA-disease asociations by graph convolutional auto-encoder and multilayer perceptron based on multi-view heterogeneous networks by Bing Zhang, Haoyu Wang, Chao Ma, Hai Huang, Zhou Fang, Jiaxing Qu

“…To enhance the performance and stability of the Multilayer Perceptron model, we introduce a hidden layer called the aggregation layer in the Multilayer Perceptron model. Through a gate mechanism, it controls the flow of information between each hidden layer in the Multilayer Perceptron model, aiming to achieve optimal feature extraction from each hidden layer. …”
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