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Characterization of Photonic Temperature Sensors by Comparative Human Body Measurements Using Waveguide Bragg Grating and Microring Resonator-Based Sensors

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IEEE Sensors Journal 2025年第9期25卷 15005-15012页

作者： Li, Xiaolin Li, Hongqiang Xie, Fanglin Han, Ming Zhang, Lizhen Zhang, Shanshan Li, Enbang Tiangong University Tianjin Key Laboratory of Optoelectronic Detection Technology and Systems School of Electronics and Information Engineering Tianjin300387 China Tiangong University Shaoxing Keqiao Institute Zhejiang Shaoxing312030 China Tiangong University Engineering Teaching Practice Training Center Tianjin300387 China Nankai University Tianjin Key Laboratory of Optoelectronic Sensor and Sensing Network Technology Institute of Modern Optics Tianjin300071 China University of Wollongong Centre for Medical Radiation Physics School of Physics Faculty of Engineering and Information Sciences WollongongNSW2522 Australia

Human body temperature is an important indicator of physical health. Waveguide Bragg grating (WBG)- and microring resonator (MRR)-based polymer optical waveguide temperature sensors provide alternative methods for monitoring the human body temperature. In this study, optical waveguide temperature sensors, with a combination of polymethylmethacrylate (PMMA) and polydimethylsiloxane (PDMS) for the formation of waveguide structures, are designed and fabricated via a polymer-based fabrication process to achieve real-time temperature measurements in situ. We experimentally characterized and compared the sensor thermal properties within the temperature range of 35 °C–40 °C. Based on the results from our study, the WBG and MRR temperature sensors had high-sensitivity properties. The temperature sensitivity coefficient of the WBG temperature sensor was −177.6 pm/°C and that of the MRR temperature sensor was −0.03035 mW/°C. The error of these two temperature sensors did not exceed 0.1 °C. These sensors show great promise as basic sensing elements in optical waveguide sensor applications for the early detection and monitoring of heat-related illnesses. © 2001-2012 IEEE.

关键词： Optical waveguides

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Congestion Control Method for Campus Opportunity Network Based on Ant Colony Algorithm

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Chinese Journal of Electronics 2025年第2期34卷 576-585页

作者： Li, Peng Cao, Yumei Jia, Huan Wang, Xiaoming Wu, Xiaojun School of Computer Science Shaanxi Normal University Xi an710119 China Key Lab. of Intelligent Comp. and Service Technology for Folk Song Ministry of Culture and Tourism Xi'an710119 China Key Laboratory of Modern Teaching Technology Ministry of Education Xi'an710062 China Engineering Laboratory of Teaching Information Technology of Shaanxi Province Xi'an710119 China Xi'an Key Laboratory of Cultural Tourism Resources Development and Utilization Xi'an710062 China

Due to the limited storage resources of portable devices, congestion control has become a hot direction in opportunity networks. To address the issue of heavy loads on certain nodes, which can impact routing efficiency and overall network performance, this paper proposes a load-balancing opportunity routing algorithm based on ant colony optimization (LBOR) in a campus environment. The congestion status is represented by the ratio of message drop receptions within a certain period and the occupancy of the cache. Path selection is based on the concentration of pheromones and the pheromones on the path are updated when a data transmission is completed. In the event of congestion, the algorithm prevents a large amount of data from entering the node and unloads the data to other nodes, even if they are not the optimal relay nodes. Experimental results demonstrate that the proposed algorithm effectively improves data transmission success rates, reduces network loads, and decreases the number of packet losses, especially under low latency conditions. © 2015 Chinese Institute of Electronics.

关键词： Ant colony optimization

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The impact of L2 motivation on bilingual creativity: A serial mediation analysis

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BMC Psychology 2025年第1期13卷 1-13页

作者： Yang, Yilong Li, Yadan Research Center for Linguistics and Applied Linguistics Xi’an International Studies University Xi’an China School of English Studies Xi’an International Studies University Xi’an China MOE Key Laboratory of Modern Teaching Technology Shaanxi Normal University Xi’an China

Previous studies have shown that bilingualism can offer a cognitive advantage in creativity, yet the mechanisms underlying this effect remain unclear. The present study aims to investigate the influence of L2 motivation, language proficiency, and reflection on creativity among bilinguals, examining how these factors may contribute directly and indirectly to creative performance. Two sub-studies were conducted. In Study 1, 54 bilingual participants completed an L2 motivation survey, an L2 proficiency scale, and a creativity test. Results showed positive relationships between motivation, proficiency, and creativity, with proficiency serving as a mediator between motivation and creativity. In Study 2, a larger sample of 218 bilingual participants completed the same surveys along with additional measures of reflection and creativity. Findings reinforced those of Study 1, indicating that L2 motivation positively influenced creativity through both L2 proficiency and reflection, which acted as serial mediators. These results suggest that L2 motivation plays a crucial role in enhancing bilinguals' creative performance, both directly and indirectly, through its effect on L2 proficiency and reflection. The study provides novel insights into the cognitive mechanisms of bilingual creativity and underscores the importance of motivation and proficiency in L2 acquisition for fostering creativity.

关键词： Bilingual advantage Creativity L2 motivation L2 proficiency Reflection

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Hidden Phase Space Reconstruction: A Novel Chaotic Time Series Prediction Method for Speech Signals

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Chinese Journal of Electronics 2018年第6期27卷 1221-1228页

作者： LI Jingjing ZHANG Qijin ZHANG Yumei WU Xiaojun WANG Xiaoming SU Yuping Key Laboratory of Modern Teaching Technology Ministry of Education Shaanxi Normal University School of Computer Science Shaanxi Normal University

Speech signals are nonlinear chaotic time series. This paper proposes a novel speech signal nonlinear prediction model with the hidden phase space reconstruction method. The parameters, embedding dimension m, time delay τ and model structure are solved simultaneously, breaking the restriction of phase space, which needs to be reconstructed before modeling for the existing prediction method. Subsequently, an explicit speech signal prediction model is generated. Meanwhile, the introduction of the frame length parameter k effectively extends the prediction length. Experimental results show that the values of m and τ solved by the proposed method are consistent with the values addressed by the Cao method and mutual information method, respectively. In addition, the optimal value of k is further discussed. The prediction results obtained using the proposed model are more accurate than those of linear prediction coding, the radial basis function neural network model and the long short-term memory network.

关键词： Speech signal Hidden phase space reconstruction Chaotic time series prediction Frame length parameter

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Energy Efficient Forwarding Algorithm in Opportunistic Networks

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Chinese Journal of Electronics 2016年第5期25卷 957-964页

作者： ZHANG Feng WANG Xiaoming JIANG Liping ZHANG Lichen Ministry of Education Key Laboratory for Modern Teaching Technology Shaanxi Normal University School of Computer Science Shaanxi Normal University

In opportunistic networks, a successful message transmission between node pairs depends on the message size, the transmission speed and the connection duration time. This paper proposes a new message forwarding algorithm to improve the message delivery ratio and reduce the energy consumption. Previous encounter characteristics between nodes are used to estimate future connection duration time using a three point estimation method. Furthermore, the buffer utilization of nodes is used as a weight for the likelihoods to meet destinations according to the hop count of messages stored in the *** simulation results show that the proposed forwarding algorithm achieves higher delivery ratio and less overhead ratio than the other four popular routing *** addition, the proposed algorithm gains a better average residual energy performance among all the compared protocols.

关键词： Opportunistic networks Forwarding algorithm Connection duration time Hop count Buffer management

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FMR-GNet: Forward Mix-Hop Spatial-Temporal Residual Graph Network for 3D Pose Estimation

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Chinese Journal of Electronics 2024年第6期33卷 1346-1359页

作者： Honghong YANG Hongxi LIU Yumei ZHANG Xiaojun WU Key Laboratory of Modern Teaching Technology Ministry of Education Shaanxi Normal University Key Laboratory of Intelligent Computing and Service Technology for Folk Song Ministry of Culture and Tourism School of Computer Science Shaanxi Normal University

Graph convolutional networks that leverage spatial-temporal information from skeletal data have emerged as a popular approach for 3D human pose estimation. However, comprehensively modeling consistent spatialtemporal dependencies among the body joints remains a challenging task. Current approaches are limited by performing graph convolutions solely on immediate neighbors, deploying separate spatial or temporal modules, and utilizing single-pass feedforward architectures. To solve these limitations, we propose a forward multi-scale residual graph convolutional network(FMR-GNet) for 3D pose estimation from monocular video. First, we introduce a mix-hop spatialtemporal attention graph convolution layer that effectively aggregates neighboring features with learnable weights over large receptive fields. The attention mechanism enables dynamically computing edge weights at each layer. Second,we devise a cross-domain spatial-temporal residual module to fuse multi-scale spatial-temporal convolutional features through residual connections, explicitly modeling interdependencies across spatial and temporal domains. Third, we integrate a forward dense connection block to propagate spatial-temporal representations across network layers, enabling high-level semantic skeleton information to enrich lower-level features. Comprehensive experiments conducted on two challenging 3D human pose estimation benchmarks, namely Human3.6M and MPI-INF-3DHP, demonstrate that the proposed FMR-GNet achieves superior performance, surpassing the most state-of-the-art methods.

关键词： Location awareness Three-dimensional displays Correlation Graph convolutional networks Fuses Aggregates Pose estimation Semantics Benchmark testing Skeleton

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Combined influence of healthy lifestyles, nutritional and inflammatory status on mortality among US adults with depression

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Journal of Psychosomatic Research 2025年 193卷 112131-112131页

作者： Yin, Jumei Jiang, Lan Zhang, Huan Zhang, Jinming Zhang, Ju Yao, Nuo Shi, Yongquan Han, Zheyi Air Force Medical Center Department of Gastroenterology Air Force Medical University Beijing China State Key Laboratory of Holistic Integrative Management of Gastrointestinal Cancers and National Clinical Research Center for Digestive Diseases Xijing Hospital of Digestive Diseases Fourth Military Medical University Xi’ an 710032 China Key Laboratory of Modern Teaching Technology (Ministry of Education) Shaanxi Normal University No. 199 Chang'an Road Yanta District Xi'an 710062 China

Objective: Healthy lifestyles, nutritional and inflammatory status are interrelated and influence mortality. This study aimed to evaluate their separate and combined effects on all-cause and cause-specific mortality in individuals exhibiting depression. Methods: 6143 individuals with depression (median age 47) were recruited from the US National Health and Nutrition Examination Survey (NHANES 2005–2018), with mortality followed up through December 31, 2019. A healthy lifestyle score (0–5) was constructed based on current non-smoking, low-to-moderate alcohol consumption, adequate sleep, sufficient physical activity and healthy diet. Higher scores indicated healthier lifestyles. The Advanced Lung Cancer Inflammation Index (ALI), a composite marker of inflammation and nutritional status, was calculated as Body Mass Index (BMI) (kg/m²) × albumin (g/dl)/Neutrophil-to-Lymphocyte Ratio (NLR). Higher ALI values denoted lower inflammation and better nutrition. Weighted Cox proportional-hazards models were used to estimate mortality hazard ratios. Results: Healthier lifestyles significantly lowered all-cause (hazard ratio [HR] 0.72, 95 % confidence interval [CI] 0.66–0.78), cardiovascular (HR 0.70, 95 % CI 0.58–0.83), and non-cardiovascular mortality (HR 0.72, 95 % CI 0.64–0.81). High ALI reduced all-cause (HR 0.70, 95 % CI 0.54–0.91) and cardiovascular mortality (HR 0.46, 95 % CI 0.28–0.77) compared with low ALI. Joint analyses showed that individuals with both healthy lifestyle scores ≥3 and high ALI had the lowest risk of all-cause, cardiovascular, and non-cardiovascular mortality (HR 0.44, 95 % CI 0.33–0.60;0.32, 95 % CI 0.16–0.63;0.49, 95 % CI 0.35–0.68). Conclusion: The joint presence of healthy lifestyles and high ALI was significantly associated with lower risk of mortality among individuals with depression. © 2025 Elsevier Inc.

关键词： Depression Health lifestyle score Mortality The advanced lung Cancer inflammation index

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YOLO-Drone:A Scale-Aware Detector for Drone Vision

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Chinese Journal of Electronics 2024年第4期33卷 1034-1045页

作者： Yutong LI Miao MA Shichang LIU Chao YAO Longjiang GUO School of Computer Science Shaanxi Normal University Key Laboratory of Modern Teaching Technology Ministry of Education College of Computer Science Sichuan University

Object detection is an important task in drone vision. Since the number of objects and their scales always vary greatly in the drone-captured video, small object-oriented feature becomes the bottleneck of model performance, and most existing object detectors tend to underperform in drone-vision scenes. To solve these problems, we propose a novel detector named YOLO-Drone. In the proposed detector, the backbone of YOLO is firstly replaced with ConvNeXt, which is the state-of-the-art one to extract more discriminative features. Then, a novel scale-aware attention(SAA) module is designed in detection head to solve the large disparity scale problem. A scale-sensitive loss(SSL) is also introduced to put more emphasis on object scale to enhance the discriminative ability of the proposed detector. Experimental results on the latest VisDrone 2022 test-challenge dataset(detection track) show that our detector can achieve average precision(AP) of 39.43%, which is tied with the previous state-of-the-art, meanwhile,reducing 39.8% of the computational cost.

关键词： YOLO Costs Object oriented modeling Computational modeling Detectors Feature extraction Data models

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Optimization-Based Fragmental Transmission Method for Video Data in Opportunistic Networks

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Tsinghua Science and technology 2017年第4期22卷 389-399页

作者： Peng Li Xiaoming Wang Junling Lu Lichen Zhang Zaobo He the Key Laboratory Modern Teaching Technology Ministry of Education School of Computer Science Shaanxi Normal University Department of Computer Science Georgia State University

Multimedia data have become popularly transmitted content in opportunistic networks. A large amount of video data easily leads to a low delivery ratio. Breaking up these big data into small pieces or fragments is a reasonable option. The size of the fragments is critical to transmission efficiency and should be adaptable to the communication capability of a network. We propose a novel communication capacity calculation model of opportunistic network based on the classical random direction mobile model, define the restrain facts model of overhead, and present an optimal fragment size algorithm. We also design and evaluate the methods and algorithms with video data fragments disseminated in a simulated environment. Experiment results verified the effectiveness of the network capability and the optimal fragment methods.

关键词： opportunistic network communication capabilities fragment video data

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CPI-17-mediated contraction of vascular smooth muscle is essential for the development of hypertension in obese mice

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Journal of Genetics and Genomics 2019年第3期46卷 109-118页

作者： Jie Sun Tao Tao Wei Zhao Lisha Wei Fan She Pei Wang Yeqiong Li Yanyan Zheng Xin Chen Wei Wang Yanning Qiao Xue-Na Zhang Min-Sheng Zhu Model Animal Research Center and MOE Key Laboratory of Model Animal and Disease Study Nanjing University Key Laboratory of MOE for Modern Teaching Technology Shaanxi Normal University

Several factors have been implicated in obesity-related hypertension, but the genesis of the hypertension is largely unknown. In this study, we found a significantly upregulated expression of CPI-17(C-kinasepotentiated protein phosphatase 1 inhibitor of 17 kDa) and protein kinase C(PKC) isoforms in the vascular smooth muscles of high-fat diet(HFD)-fed obese mice. The obese wild-type mice showed a significant elevation of blood pressure and enhanced calcium-sensitized contraction of vascular smooth muscles. However, the obese CPI-17-deficient mice showed a normotensive blood pressure, and the calcium-sensitized contraction was consistently reduced. In addition, the mutant muscle displayed an abolished responsive force to a PKC activator and a 30%-50% reduction in both the initial peak force and sustained force in response to various G protein-coupled receptor(GPCR) agonists. Our observations showed that CPI-17-mediated calcium sensitization is mediated through a GPCR/PKC/CPI-17/MLCP/RLC signaling pathway. We therefore propose that the upregulation of CPI-17-mediated calcium-sensitized vasocontraction by obesity contributes to the development of obesity-related hypertension.

关键词： CPI-17 Calcium sensitization Obesity-related hypertension

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