Results 81 to 90 of about 55,056 (264)

Spectral Efficiency Considerations in 6G Networks

IEEE Open Journal of the Communications Society
As wireless connectivity continues to evolve toward 6G, the demand to efficiently deliver higher throughput, lower latency, and improved reliability increases.
Joseph Boccuzzi
doaj   +1 more source

Multiscale Coupling From Mastication to Retronasal Aroma Perception: The PG‐DTCFN Model and Multiphysics Simulation

Advanced Science, EarlyView.
Using grilled lamb skewers as a model system, this work builds a multiscale coupling framework from oral processing to retronasal aroma perception, reveals dual‐kinetic release patterns and Electroencephalogram‐characterized central encoding features, and proposes an interpretable physics‐guided deep learning model validated by multiphysics simulation,
Che Shen, Xiongfeng He, Zihao Li, Zidong Chen, Jiajin Sun, Xinyu Jiang, Yunhui Zhang, Lizhang Wu, Ran Wang, Jingnan Lu, Bo Wang, Kezhou Cai, Baocai Xu   +12 more
wiley   +1 more source

Strategy of Triple‐Gradient in Binary Pixels for Flexible Pressure Sensing with High Sensitivity and Wide‐Range Linearity

Advanced Science, EarlyView.
A flexible pressure sensor with triple‐gradient design of conductivity, modulus, and dimension in binary micro‐dome pixels is proposed. Based on precisely‐designed CNT/PDMS matrix, the device exhibits a linear sensitivity of 974.1 kPa−1 across range up to 1.8 MPa (R2 > 0.99), offering an effective strategy for potential applications in healthcare ...
Yifan Liu, Xiao Xu, Fengming Hu, Yuanzhe Liang, Zidong Yin, Biao Qi, Ruolin Liu, Ziyi Dai, Jianyi Luo, Bingpu Zhou   +9 more
wiley   +1 more source

Offloading Post-Quantum Cryptography to Data Processing Units: A Performance Analysis of HQC Key Encapsulation

IEEE Access
The transition to post-quantum cryptography introduces substantial computational overhead that can degrade application performance in datacenter environments, particularly under system contention when there is competition to access shared computational ...
Joseph Meyer, Elad Mentovich, Idelfonso Tafur Monroy, Juan Jose Vegas Olmos   +3 more
doaj   +1 more source

Joint Training on AMD and NVIDIA GPUs

CoRR
As large language models continue to scale, training demands on compute and system capacity grow rapidly, making single-vendor homogeneous clusters insufficient. This paper presents a technical solution for heterogeneous mixed training in AMD-NVIDIA environments.
Jon Hu, Thomas Jia, Jing Zhu, Zhendong Yu   +3 more
openaire   +2 more sources

Enhancing Super‐Resolution Spatial Transcriptomics Data by Transfer Learning

Advanced Science, EarlyView.
SpotZoomer employs a transfer‐learning‐based strategy to enhance the resolution of Visium data by leveraging available high‐resolution priors. The resulting super‐resolved maps enable sharper delineation of cell boundaries and more precise inference of cell–cell communication patterns that would otherwise remain obscured at native resolution.
Xiaoyu Li, Lihua Zhang, Wenwen Min
wiley   +1 more source

Germanium-on-Silicon Waveguide-Integrated Photodiode with Dual Optical Inputs for Datacenter Applications

Micromachines
As the exponential growth in advanced compute workloads drives intra-datacenter interconnects to ever increasing bitrates, optical networking equipment has risen to the challenge by shifting from NRZ signaling to bandwidth efficient modulation methods ...
Itamar-Mano Priel, Shai Cohen, Liron Gantz, Yael Nemirovsky   +3 more
doaj   +1 more source

Artificial Intelligence–Based Surgical Phase Analysis Enables Objective Assessment of Surgeon Skill in Robotic Distal Gastrectomy: A Multicenter Study

Annals of Gastroenterological Surgery, EarlyView.
ABSTRACT Aim Artificial intelligence (AI)–based surgical video analysis can automate time‐consuming manual assessments and enable objective characterization of surgical workflows. We aimed to construct a large, multicenter, fully annotated dataset of robotic distal gastrectomy (RDG) videos and evaluate the feasibility and performance of an AI model for
Masaru Komatsu, Daichi Kitaguchi, Yoichi Ninomiya, Yuya Takabe, Mitsumasa Yoshida, Masahiro Yura, Nobuyoshi Takeshita, Takahiro Kinoshita, Masaaki Ito   +8 more
wiley   +1 more source

Limitations of Foundation Models in Energy Materials Simulations: A Case Study in Polyanion Sodium Cathode Materials

Advanced Intelligent Discovery, EarlyView.
Several simulation techniques are used to explore static and dynamic behavior in polyanion sodium cathode materials. The study reveals that universal machine learning interatomic potentials (MLIPs) struggle with system‐specific chemistry, emphasizing the need for tailored datasets.
Martin Hoffmann Petersen, Chiku Parida, Jonas Busk, Jin Hyun Chang, Arghya Bhowmik, Juan Maria Garcia Lastra   +5 more
wiley   +1 more source

Real‐Time Multicolor Fluorescence Microscopy via Cross‐Channel Acquisition and Deep‐Learning‐Based Inference

Advanced Intelligent Discovery, EarlyView.
Sequential multicolor fluorescence imaging in dynamic microsystems is constrained by acquisition speed and excitation dose. This study introduces a real‐time framework to reconstruct spectrally separated channels from reduced cross‐channel acquisitions (frames containing mixed spectral contributions).
Juan J. Huaroto, Yuxin Jin, Nicholas Roy, Sarthak Misra   +3 more
wiley   +1 more source