摘要：
Epistasis detection (ED) was widely used for identifying potential risk disease variants in the human genome. A statistically meaningful ED typically requires a more extensive dataset to detect complex disease-associated single nucleotide polymorphisms, but a single institution generally possesses limited genome data. Thus, it is necessary to collect multi-institutional genome data to carry out research together. However, concerns regarding privacy and trustworthiness impede the sharing of massive genome data. Therefore, this article proposes a novel federated ED framework with the sequence perturbation privacy-preserving method to address the limitation of distributed data sharing (FedED-SegNAS). First, to address the lack of interpretability in deep learning models, integrate fuzzy logic into convolutional neural networks (CNNs), promoting the capabilities of CNN to represent the ambiguities of genomic data with high interpretability and reasonable accuracy. Second, consider using the neural architecture search method to optimize the federated neural architecture. Specifically, selecting the particle swarm optimization algorithm to automatically search the optimal neural architecture at different stages in federated learning (FL) based on adaptive multiobjectives decreases the communication cost and improves communication efficiency. Furthermore, to ensure the security of the parameter transfer process, design the sequence perturbation privacy-preserving method, grouping the upload and download parameters of FL and randomly perturbing the group number so that the attacker cannot obtain the corresponding result between the group number and parameters. Its rationality and security have been proven. The experiments conducted on a range of datasets demonstrate the superiority of the framework over state-of-the-art ED methods. FedED-SegNAS can reduce network complexity while protecting genome data security.
摘要：
Plant sterilants are used to control rodent populations due to their minimal environmental risk and other ethical considerations. However, their practical utilization is unsatisfactory due to high costs and processing difficulties. Broussonetia papyrifera is a plant material that has shown the potential to inhibit the reproduction of Microtus fortis, a species that causes serious damage to crops in the Dongting Lake region in China. M. fortis was treated with different doses of B. papyrifera leaf methanol extracts. The results show that the growth of sex organs was inhibited, and the males' testosterone levels and sperm quality were reduced. Though there were some positive effects on females, the reproductive parameters of coupled voles were inferior; the most treated couple exhibited an increased reproductive time, fetal counts, and reduced weight. It was also found that M. fortis responded negatively to the extract after a single treatment or long-term repeated treatment compared to a short-term repeated treatment. B. papyrifera leaves showed a higher application potential as a sterilant for male rodents. These findings enrich the study of plant sterilants and provide insights into the utilization of B. papyrifera and the management of rodents. Owing to the effectiveness and accessibility of the leaves, the derived sterilant may be more economical for controlling rodent pests.
作者机构：
[Li, Ni; Qin, Hua; Deng, Yaqi; Yang, Gelan; Qin, H; Chen, Hao] Hunan City Univ, Coll Informat & Elect Engn, Yiyang 413000, Hunan, Peoples R China.;[Peng, Yang] Univ Washington Bothell, Div Comp & Software Syst, Bothell, WA 98011 USA.
通讯机构：
[Qin, H ] H;Hunan City Univ, Coll Informat & Elect Engn, Yiyang 413000, Hunan, Peoples R China.
关键词：
IoT;Scheduling;Energy;Delay;Network systems
摘要：
With the fast expansion of the Internet of Things (IoT), a vast number of IoT gateways are being deployed and continuously disseminating data to proximate devices. As one of the most prevalent wireless technologies in our daily work and life, WiFi has been extensively used for data dissemination because of the widespread availability of WiFi infrastructures. However, data transmission over high-power WiFi can quickly deplete the batteries of IoT devices. Despite the introduction of numerous power saving protocols in WiFi-based IoT computer network systems, achieving both high energy efficiency and low delay remains a challenge due to the unpredictability of data traffic. To address this, we propose a dual-radio Dual-constraint Node Activation (DNA) scheduling scheme, which leverages an auxiliary low-power ZigBee radio to reactively activate the high-power WiFi radio for energy-efficient data dissemination. Besides the delay constraint required by WiFi upper-layer applications, the dual-radio energy optimization problem studied in this work is also limited by the constrained ZigBee bandwidth for performing radio activation. By jointly scheduling dual-radio duty cycles, DNA dynamically allocates ZigBee bandwidth to balance energy and delay for optimized system performance. Extensive real-world testing was conducted on a prototype dual-radio system equipped with off-the-shelf ZigBee and WiFi radios. Under medium bandwidth and delay constraints, DNA achieves an energy consumption of 7.95 mJ per data packet, which is 95.4% and 36.2% lower than the WiFi’s standard power saving protocol and a contemporary dual-radio scheduling scheme, respectively. Additionally, DNA has demonstrated superior reliability and adaptability in various scenarios.
With the fast expansion of the Internet of Things (IoT), a vast number of IoT gateways are being deployed and continuously disseminating data to proximate devices. As one of the most prevalent wireless technologies in our daily work and life, WiFi has been extensively used for data dissemination because of the widespread availability of WiFi infrastructures. However, data transmission over high-power WiFi can quickly deplete the batteries of IoT devices. Despite the introduction of numerous power saving protocols in WiFi-based IoT computer network systems, achieving both high energy efficiency and low delay remains a challenge due to the unpredictability of data traffic. To address this, we propose a dual-radio Dual-constraint Node Activation (DNA) scheduling scheme, which leverages an auxiliary low-power ZigBee radio to reactively activate the high-power WiFi radio for energy-efficient data dissemination. Besides the delay constraint required by WiFi upper-layer applications, the dual-radio energy optimization problem studied in this work is also limited by the constrained ZigBee bandwidth for performing radio activation. By jointly scheduling dual-radio duty cycles, DNA dynamically allocates ZigBee bandwidth to balance energy and delay for optimized system performance. Extensive real-world testing was conducted on a prototype dual-radio system equipped with off-the-shelf ZigBee and WiFi radios. Under medium bandwidth and delay constraints, DNA achieves an energy consumption of 7.95 mJ per data packet, which is 95.4% and 36.2% lower than the WiFi’s standard power saving protocol and a contemporary dual-radio scheduling scheme, respectively. Additionally, DNA has demonstrated superior reliability and adaptability in various scenarios.
作者机构：
[Zhou, Li; Zhou, L] Hunan City Univ, Sch Mech & Elect Engn, Yiyang 413001, Peoples R China.;[Liu, Yan] Hunan City Univ, Coll Informat & Elect Engn, Yiyang 413001, Peoples R China.
通讯机构：
[Zhou, L ] H;Hunan City Univ, Sch Mech & Elect Engn, Yiyang 413001, Peoples R China.
关键词：
Object detection;generic object tracking using regression networks;tracking learning detection;intelligent robots;Laplace probability density
摘要：
The development of intelligent robot has always been an important research direction in the field of artificial intelligence, and the object detection of robot is the basis of intelligent perception and autonomous action. This study proposes an improved object detection algorithm which integrates two kinds of intelligent robot object detection techniques. In this process, the relationship between the center position of the target in the frame used for object detection and tracking is analyzed. It uses Laplace probability density as the parameter to calculate the center position relationship, and joins the correction network to correct the feature point positioning. The object re-capture function is added to solve the problem of object loss in the long-term object detection task, and the classifier is used to realize the object recognition. The results show that when the number of targets in the image reaches 20, the capture accuracy of the two data sets remains above 98.7%. In the intersection to union ratio test, when the real rectangular box contained 2M pixels, the intersection to union ratio of the method proposed in this study remains at or above 0.989. When conducting actual application memory usage tests, the proposed method maintains a memory usage of less than 2000Mb at runtime. It is shown that this method has better target detection efficiency and quality, and the requirement of hardware is lower.
关键词：
UAV-LiDAR;individual tree segmentation;forest stand volume estimation;Gaussian mixture model
摘要：
The main problems of forest parameter extraction and forest stand volume estimation using unmanned aerial vehicle light detection and ranging (UAV-LiDAR) technology are the lack of precision in individual tree segmentation and the inability to directly obtain the diameter at breast height (DBH) parameter. To address such limitations, the study proposed an improved individual tree segmentation method combined with a DBH prediction model to obtain the tree height (H) and DBH for calculating the volume of trees, thus realizing the accurate estimation of forest stand volume from individual tree segmentation aspect. The method involves the following key steps: (1) The local maximum method with variable window combined with the Gaussian mixture model were used to detect the treetop position using the canopy height model for removing pits. (2) The measured tree DBH and H parameters of the sample trees were used to construct an optimal DBH-H prediction model. (3) The duality standing tree volume model was used to calculate the forest stand volume at the individual tree scale. The results showed that: (1) Individual tree segmentation based on the improved Gaussian mixture model with optimal accuracy, detection rate r, accuracy rate p, and composite score F were 89.10%, 95.21%, and 0.921, respectively. The coefficient of determination R2 of the accuracy of the extracted tree height parameter was 0.88, and the root mean square error RMSE was 0.84 m. (2) The Weibull model had the optimal model fit for DBH-H with predicted DBH parameter accuracy, the R2 and RMSE were 0.84 and 2.28 cm, respectively. (3) Using the correctly detected trees from the individual tree segmentation results combined with the duality standing tree volume model estimated the forest stand volume with an accuracy AE of 90.86%. In conclusion, using UAV-LiDAR technology, based on the individual tree segmentation method and the DBH-H model, it is possible to realize the estimation of forest stand volume at the individual tree scale, which helps to improve the estimation accuracy.
作者机构：
[Lei, Shan; Li, Zhuang; Gao, Yi] Hunan City Univ, Dept Phys, Yiyang 413000, Hunan, Peoples R China.;[Lei, Shan; Li, Zhuang] Hunan City Univ, All Solid state Energy Storage Mat & Devices Key L, Yiyang 413000, Peoples R China.;[Zhang, Zhongde] Xiangtan Univ, Sch Mat Sci & Engn, Xiangtan 411105, Hunan, Peoples R China.
通讯机构：
[Li, Z; Lei, S ] H;Hunan City Univ, Dept Phys, Yiyang 413000, Hunan, Peoples R China.;Hunan City Univ, All Solid state Energy Storage Mat & Devices Key L, Yiyang 413000, Peoples R China.
摘要：
beta-type Zirconium alloys are promising biomedical implant materials, the elastic and magnetic properties of which are of great importance to be studied. In this work, beta-type Zr1-xTax binary alloys (x = 0.0625, 0.125, 0.1875, 0.25, 0.3125, 0.375, 0.4375, 0.50, 0.5625, 0.625, 0.6875, 0.75, 0.8125, 0.875, 0.9375) were established. The effects of Ta content on lattice constant, elastic properties and magnetic properties of beta-type Zr-Ta alloys were investigated via first-principles calculations, the calculated results were also verified through experiments. The results shown that with the increase of Ta content, the lattice constant and total energy of beta-type Zr-Ta alloys gradually decreased, the elastic moduli of E, K and G increased on the whole, and the magnetic moment generally increased first and then decreased. The changing trend of elastic and magnetic properties were consistent between experimental and calculated results. Notably, Zr0.875Ta0.125 exhibited the lowest Young's modulus and magnetic susceptibility among the beta-type Zr-Ta alloys, which was one-third that of Ti-6Al-4V, meeting the requirements for low Young's modulus and low magnetism, and can be anticipated to be promising biomedical implant materials.
作者机构：
[Zhou, Shuang-shuang] Hunan City Univ, Sch Informat Sci & Engn, Yiyang 413000, Hunan, Peoples R China.;[Khan, Muhammad Ijaz; Khan, Sami Ullah] Prince Mohammad Bin Fahd Univ, Dept Mech Engn, POB,1664, Al Khobar 31952, Saudi Arabia.;[Khan, Sami Ullah] Namal Univ, Dept Math, Mianwali 42250, Pakistan.;[Qayyum, Sumaira] Quaid I Azam Univ, Dept Math, Islamabad 44000, Pakistan.
通讯机构：
[Khan, MI ] P;Prince Mohammad Bin Fahd Univ, Dept Mech Engn, POB,1664, Al Khobar 31952, Saudi Arabia.
关键词：
heat generation;surface reaction;CNTs based nanofluid;stretching/shrinking sheet;thermal radiation;76Wxx
摘要：
The investigation endorsed the convective flow of Carreau nanofluid over a stretched surface in presence of entropy generation optimization. The novel dynamic of viscous dissipation is utilized to analyze the thermal mechanism of magnetized flow. The convective boundary assumptions are directed in order to examine the heat and mass transportation of nanofluid. The thermal concept of thermophoresis and Brownian movements has been re-called with the help of Buongiorno model. The problem formulated in dimensionless form is solved by NDSolve MATHEMATICA. The graphical analysis for parameters governed by the problem is performed with physical applications. The affiliation of entropy generation and Bejan number for different parameters is inspected in detail. The numerical data for illustrating skin friction, heat and mass transfer rate is also reported. The motion of the fluid is highest for the viscosity ratio parameter. The temperature of the fluid rises via thermal Biot number. Entropy generation rises for greater Brinkman number and diffusion parameter.
关键词：
Reviews;Fake news;Feature extraction;Semantics;Long short term memory;Accuracy;Task analysis;Attention;deceptive review detection;feature representation;long short-term memory (LSTM) network.
摘要：
User reviews on online consumption platforms are crucial for both consumers and merchants, serving as a reference for purchase decisions and product improvement. However, fake reviews can mislead consumers and harm merchant profits and reputation. Developing effective methods for detecting deceptive reviews is crucial to protecting the interests of both parties. In recent years, research on fake review detection has focused on improving machine learning and neural network methods to enhance the accuracy of fake review detection, neglecting the fundamental and necessary work of text feature representation for reviews. High-quality review text feature representation affects or even determines the quality and performance of fake review detection methods. The increasing prevalence of fake reviews results in a more complex distribution within the feature space of review texts, thus necessitating review embedding methods that exhibit comprehensive semantic comprehension and contextual awareness of review texts. To improve the quality of textual feature representation, we propose a review-embedding attention-based long short-term memory (A-LSTM) method that can encode the global semantics of reviews and detect the deception of the review content. A-LSTM uses attention gates to discover the importance of words, and by analyzing the importance of words, it can help distinguish the characteristics of real and fake reviews, and we propose an attention loss function to solve the problem of class imbalance. On the Yelp dataset, the accuracy of deceptive review detection has increased to 90.9%.
作者机构：
[Leng, Xiaoling; Zhou, Jing; Zhang, Saiwen; Zhou, J] Hunan City Univ, Dept Phys, Yiyang 413000, Hunan, Peoples R China.;[Leng, Xiaoling; Zhou, Jing; Zhang, Saiwen; Zhou, J] Hunan City Univ, All Solid State Energy Storage Mat & Devices Key L, Yiyang 413000, Peoples R China.
通讯机构：
[Zhou, J ] H;Hunan City Univ, Dept Phys, Yiyang 413000, Hunan, Peoples R China.;Hunan City Univ, All Solid State Energy Storage Mat & Devices Key L, Yiyang 413000, Peoples R China.
摘要：
We study Jeans instability with generalized Maxwellian distribution. The results reveal two significant features of the modified Jeans instability. First, the Jeans wavelength of the system covers the original lambda J {\lambda }_{J} when k = 1 k=1 . Second, as k k approaches 0, the modified Jeans wavelength approaches infinity. This means that the system is always gravitationally stable. Furthermore, we examine the implications of the modified Maxwellian distribution on the Friedmann equation. Our analysis suggests that the effective gravitational constant should incorporate the contribution of temperature T T in order to describe the system dynamics.
作者机构：
[Ni, Li] Hunan City Univ, Coll Informat & Elect Engn, Yiyang 413000, Peoples R China.;[Qiang, Wu; Manman, Peng] Hunan Univ, Coll Informat & Engineer, Changsha 410008, Peoples R China.
通讯机构：
[Ni, L ] H;Hunan City Univ, Coll Informat & Elect Engn, Yiyang 413000, Peoples R China.
关键词：
information networks;spectral clustering;deep embedding
摘要：
With the development of network technology, information networks have become one of the most important means for people to understand society. As the scale of information networks expands, the construction of network graphs and high-dimensional feature representation will become major factors affecting the performance of spectral clustering algorithms. To address this issue, in this paper, we propose a spectral clustering algorithm based on similarity graphs and non-linear deep embedding, named SEG_SC. This algorithm introduces a new spectral clustering model that explores the underlying structure of graphs through sparse similarity graphs and deep graph representation learning, thereby enhancing graph clustering performance. Experimental analysis with multiple types of real datasets shows that the performance of this model surpasses several advanced benchmark algorithms and performs well in clustering on medium- to large-scale information networks.
摘要：
With the advancements in low-power and miniature electronics, various smart devices are deployed and interconnected as the Internet of Things (IoT), collecting a massive amount of data from surrounding environments. Despite the popularity of ZigBee for low-power communications in IoT, WiFi has recently been recommended for data collection in IoT for its high data rate, high reliability, native IP compatibility, and vastly-deployed infrastructures. However, it is well known that WiFi is energy-consuming. Although many schemes have been designed to reduce WiFi energy consumption, they usually suffer from the dilemma that a longer (shorter) sleep of WiFi gives a lower (higher) energy consumption but a larger (smaller) latency, hindering the use of WiFi in a wide range of IoT applications that require a certain level of quality of service (QoS). To this end, we propose a Heterogeneity-aware Dual-interface Scheduling (HDS) scheme to fully exploit the heterogeneity between ZigBee and WiFi to realize energy-efficient and delay-constrained data collection in a tree-based IoT network, where each device is equipped with a ZigBee and a WiFi interface. The low-power feature of ZigBee is utilized as much as possible for high energy efficiency, while the high-reliability advantage of WiFi is leveraged when the ZigBee link quality is low for delay guarantee. Under network dynamics, HDS jointly allocates ZigBee and WiFi schedules to strike a balance between energy and delay for optimized performance. A prototype system is built atop an IoT platform integrated with commercial off-the-shelf ZigBee and WiFi modules. Experiment results show that the energy consumption of HDS is 80.3% and 43.6% lower than the standard power saving protocol and a state-of-the-art dual-interface scheme, respectively, under a moderate delay constraint. Additionally, the percentage of data packets that satisfy the delay constraint is above 98.6%.
期刊：
Journal of Materials Science: Materials in Electronics,2024年35(16):1-9 ISSN：0957-4522
通讯作者：
Wang, HO;Tan, WS
作者机构：
[Lu, Gefei; Su, Kunpeng; Wang, Haiou; Wang, Haochen; Yang, Lin; Huang, Shuai] Hangzhou Dianzi Univ, Coll Mat & Environm Engn, Key Lab Novel Mat Sensor Zhejiang Prov, Hangzhou 310018, Peoples R China.;[Tan, Weishi] Hunan City Univ, Coll Informat & Elect Engn, All Solid State Energy Storage Mat & Devices Key L, Yiyang 413002, Peoples R China.;[Tan, Weishi] Nanjing Univ Sci & Technol, Key Lab Soft Chem & Funct Mat, Minist Educ, Dept Appl Phys, Nanjing 210094, Peoples R China.
通讯机构：
[Wang, HO ; Tan, WS ] H;Hangzhou Dianzi Univ, Coll Mat & Environm Engn, Key Lab Novel Mat Sensor Zhejiang Prov, Hangzhou 310018, Peoples R China.;Hunan City Univ, Coll Informat & Elect Engn, All Solid State Energy Storage Mat & Devices Key L, Yiyang 413002, Peoples R China.;Nanjing Univ Sci & Technol, Key Lab Soft Chem & Funct Mat, Minist Educ, Dept Appl Phys, Nanjing 210094, Peoples R China.
摘要：
Magnetoresistance and temperature coefficient of resistance (TCR) of manganites with ferromagnetism have been reported extensively, but the magnetoresistance and TCR of antiferromagnetic manganites are scarce. The transport properties, TCR, and magnetoresistance effect of antiferromagnetic NdMnO3 have been studied in this work. NdMnO3 samples exhibit semiconductor conductivity, and with the different applied magnetic fields, they still maintain semiconductor characteristics and have considerable stability. Under an applied magnetic field of 6 T, a small negative magnetoresistance of 8% appears near 150 K. Moreover, the conduction mechanism and TCR of NdMnO3 are studied. Three models, thermal activation (TA) model, small polaron (SP) model, and variable range jump (VRH) model, are used to analyze the electrical transport of NdMnO3 samples. The results show that the transport behavior of NdMnO3 samples is more consistent with the TA model. The maximum TCR is 9.4% K-1 within the low temperature region (above liquid nitrogen temperature). The TCR decreases with increasing temperature and it remains 2.5% K-1 near room temperature. Antiferromagnetic NdMnO3 has good TCR performance, which can be applied to temperature sensing field and has good application prospect in antiferromagnetic insulating electronic devices.
作者机构：
[Zhou, Xinshao; Wang, Yonghong] Hunan City Univ, Coll Informat & Elect Engn, Yiyang 413000, Peoples R China.;[Zhou, Xinshao; Wang, Yonghong] Hunan City Univ, Hunan Engn Res Ctr Intelligent Monitoring & Disast, Yiyang 413000, Peoples R China.;[Shao, Chunchen; Yang, Susu; Shao, Shuyao; Ge, Weiting; Zuo, Yangyan; Yang, G; Yang, Gang; Sun, Weiwei] Ningbo Univ, Dept Geog & Spatial Informat Tech, Ningbo 315211, Peoples R China.;[Zheng, Ke] Ningbo Vehicle Emiss Control Ctr, Task Dept, Ningbo 315100, Peoples R China.
通讯机构：
[Yang, G ] N;Ningbo Univ, Dept Geog & Spatial Informat Tech, Ningbo 315211, Peoples R China.
关键词：
Spartina alterniflora;phenological characteristics;Landsat time series images;Yangtze River Delta
摘要：
Spartina alterniflora (S. alterniflora) has grown rapidly in China since its introduction in 1979, showing the trend of alien species invasion, which has seriously affected the ecosystem balance of coastal wetlands. The temporal and spatial expansion law of S. alterniflora can be obtained through remote sensing monitoring, which can provide a reference and basis for S. alterniflora management. This paper presents a method for extracting and mapping S. alterniflora based on phenological characteristics. The coastal areas of the Yangtze River Delta Urban Agglomeration are selected as the research area, and the Landsat time series data from 1990 to 2022 on the Google Earth Engine (GEE) platform are used to support the experiment in this paper. Firstly, the possible growing area of S. alterniflora was extracted using the normalized differential moisture index (NDMI), normalized differential vegetation index (NDVI), and normalized differential water index (NDWI); Then, the time series curve characterizing the phenological characteristics of vegetation was constructed using the vegetation index to determine the difference phase of phenological characteristics between S. alterniflora and other vegetation. Finally, a decision tree was constructed based on the phenological feature difference phase data to extract S. alterniflora, and it is applied to the analysis of temporal and spatial changes of S. alterniflora in the study area from 1990 to 2022. The results show that the area of S. alterniflora increased from similar to 1426 ha in 1990 to similar to 44,508 ha in 2022. However, the area of S. alterniflora began to show negative growth in 2015 due to the construction of nature reserves and ecological management. The results of correlation analysis showed that the growth of C. japonicum was significantly affected by temperature stress and weakly affected by precipitation. This study verified that Landsat time series images can effectively extract vegetation phenological information, which has strong feasibility for extraction and dynamic monitoring of S. alterniflora and provides technical support for the management and monitoring of invasive plants in coastal wetlands.
期刊：
Frontiers in Marine Science,2024年11:1336783 ISSN：2296-7745
通讯作者：
Wang, YH
作者机构：
[Zhang, Shuai; Wang, Yanhui; Zhao, Peng; Wu, Sheng; Jiang, Nian; Zhang, Pingping] Harbin Engn Univ, Yantai Grad Sch, Yantai, Peoples R China.;[Liu, Yang] Hunan City Univ, Coll Informat Sci & Engn, Yiyang, Peoples R China.
通讯机构：
[Wang, YH ] H;Harbin Engn Univ, Yantai Grad Sch, Yantai, Peoples R China.
关键词：
Floating photovoltaic;offshore;Marine environment protection;Technological feasibility;life cycle of photovoltaic;potential impacts
摘要：
The development of solar energy is one of the most effective means to deal with the environmental and energy crisis. The floating photovoltaic (PV) system is an attractive type because of its multiple advantages and has been well developed based on fresh water areas on land. This paper focuses on the expansion of this sector towards the ocean, offshore floating PV plants, which is the new growth point with huge potential for the future PV sector. For this new field, the technology readiness level is really low and research to understand the interaction between offshore floating PV plants and marine environment are proceeding. In this paper, we aim to discuss the technological feasibility of offshore floating PV plants as well as analyze potential impacts on the marine environment during the life cycle of PV from manufacturing until disposal.
期刊：
EUROPEAN PHYSICAL JOURNAL C,2024年84(1):1-7 ISSN：1434-6044
通讯作者：
Chen, X
作者机构：
[Zhou, Jing] Hunan City Univ, Dept Phys, Yiyang 413000, Hunan, Peoples R China.;[Zhou, Jing] Hunan City Univ, All solid state Energy Storage Mat & Devices Key L, Yiyang 413000, Peoples R China.;[Zhou, Jing; Ping, Jialun] Nanjing Normal Univ, Dept Phys, Nanjing 210097, Jiangsu, Peoples R China.;[Chen, Jun] Hubei Minzu Univ, Dept Phys, Enshi 445000, Peoples R China.;[Zhang, Le] Hubei Normal Univ, Coll Phys & Elect Sci, Huangshi 435002, Peoples R China.
通讯机构：
[Chen, X ] U;Univ South China, Sch Nucl Sci & Technol, Hengyang 421001, Peoples R China.
摘要：
<jats:title>Abstract</jats:title><jats:p>According to gauge/gravity correspondence, we study the holographic Schwinger effect within an anisotropic background. Firstly, the separate length of the particle–antiparticle pairs is computed within the context of an anisotropic background which is parameterized by dynamical exponent <jats:inline-formula><jats:alternatives><jats:tex-math>$$\nu $$</jats:tex-math><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML">
<mml:mi>ν</mml:mi>
</mml:math></jats:alternatives></jats:inline-formula>. It is found that the maximum separate length <jats:italic>x</jats:italic> increases with the increase of dynamical exponent <jats:inline-formula><jats:alternatives><jats:tex-math>$$\nu $$</jats:tex-math><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML">
<mml:mi>ν</mml:mi>
</mml:math></jats:alternatives></jats:inline-formula>. By analyzing the potential energy, we find that the potential barrier increases with the dynamical exponent <jats:inline-formula><jats:alternatives><jats:tex-math>$$\nu $$</jats:tex-math><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML">
<mml:mi>ν</mml:mi>
</mml:math></jats:alternatives></jats:inline-formula> at a small separate distance. This observation implies that the Schwinger effect within an anisotropic background is comparatively weaker when contrasted with its manifestation in an isotropic background. Finally, we also find that the Schwinger effect in the transverse direction is weakened compared to the parallel direction in the anisotropic background, which is consistent with the top-down model.</jats:p>
期刊：
EUROPEAN PHYSICAL JOURNAL C,2024年84(7):1-10 ISSN：1434-6044
通讯作者：
Chen, X
作者机构：
[Zhou, Jing] Hunan City Univ, Dept Phys, Yiyang 413000, Hunan, Peoples R China.;[Zhou, Jing] Hunan City Univ, Key Lab Hunan Prov, All Solid State Energy Storage Mat & Devices, Yiyang 413000, Peoples R China.;[Fadafan, Kazem Bitaghsir] Shahrood Univ Technol, Fac Phys, POB 3619995161, Shahrood, Iran.;[Chen, Xun; Chen, X] Univ South China, Sch Nucl Sci & Technol, Hengyang 421001, Peoples R China.
通讯机构：
[Chen, X ] U;Univ South China, Sch Nucl Sci & Technol, Hengyang 421001, Peoples R China.
摘要：
In this work, we use the AdS/CFT correspondence to study the behavior of a triply heavy baryon within anisotropic backgrounds. Beginning with the total action of the three quarks, we derive the balance equation for the three-quark system and compute the separation distance and potential energy. Our results reveal a consistent decrease in both the separation distance and potential energy for the A configuration and the B configuration as the anisotropy coefficient a increases. This suggests that the presence of an anisotropic background promotes the dissolution of the three-quark system. Additionally, we compare the potential energies of the A and B configurations and observe that the A configuration has a slightly smaller potential energy, suggesting greater stability compared to the B configuration.
摘要：
Fatigue driving is a serious threat to road safety, which is why accurately identifying fatigue driving behavior and warning drivers in time are of great significance in improving traffic safety. However, accurately recognizing fatigue driving is still challenging due to large intra-class variations in facial expression, continuity of behaviors, and illumination conditions. A fatigue driving recognition method based on feature parameter images and a residual Swin Transformer is proposed in this paper. First, the face region is detected through spatial pyramid pooling and a multi-scale feature output module. Then, a multi-scale facial landmark detector is used to locate 23 key points on the face. The aspect ratios of the eyes and mouth are calculated based on the coordinates of these key points, and a feature parameter matrix for fatigue driving recognition is obtained. Finally, the feature parameter matrix is converted into an image, and the residual Swin Transformer network is presented to recognize fatigue driving. Experimental results on the HNUFD dataset show that the proposed method achieves an accuracy of 96.512%, thus outperforming state-of-the-art methods.
