Circulator based on spoof surface plasmon polaritons

Circulators based on spoof surface plasmon polaritons are designed and analyzed. In the letter, we use blade structure to realize the propagation of SSPPs wave and a matching transition is used to feed energy from coplanar waveguide to the SSPPs. And the circulator shows good nonreciprocal transmission characteristics. The simulation results indicate that in the frequency band from 5 to 6.6 GHz, the isolation degree and return loss basically reaches 15dB and the insertion loss is less than 0.5dB. Moreover, the use of confinement electromagnetic waves can decrease the size of the ferrite and show a broadband characteristic.Comment: 3 pages, 6 figures, submitted to IEEE antennas and wireless propagation letters on 27-Mar-201

GREASE: A Generative Model for Relevance Search over Knowledge Graphs

Relevance search is to find top-ranked entities in a knowledge graph (KG) that are relevant to a query entity. Relevance is ambiguous, particularly over a schema-rich KG like DBpedia which supports a wide range of different semantics of relevance based on numerous types of relations and attributes. As users may lack the expertise to formalize the desired semantics, supervised methods have emerged to learn the hidden user-defined relevance from user-provided examples. Along this line, in this paper we propose a novel generative model over KGs for relevance search, named GREASE. The model applies to meta-path based relevance where a meta-path characterizes a particular type of semantics of relating the query entity to answer entities. It is also extended to support properties that constrain answer entities. Extensive experiments on two large-scale KGs demonstrate that GREASE has advanced the state of the art in effectiveness, expressiveness, and efficiency.Comment: 9 pages, accepted to WSDM 202

Job burnout among primary healthcare workers during COVID-19 pandemic: cross-sectional study in China

ObjectiveThis study evaluated job burnout among primary healthcare workers (PHCWs) in China during the COVID-19 pandemic, explored its influencing factors, and examined PHCWs' preferences for reducing job burnout.MethodWe conducted a multicenter cross-sectional study in Heilongjiang, Sichuan, Anhui, Gansu, and Shandong Provinces. An electronic questionnaire survey was conducted through convenience sampling in communities from May to July 2022. We collected sociodemographic characteristics, job burnout level, job satisfaction, and preferred ways to reduce job burnout among PHCWs.ResultsThe job burnout rate among PHCWs in China was 59.87% (937/1565). Scores for each dimension of job burnout were lower among PHCWs who had a better work environment (emotional exhaustion OR: 0.60; depersonalization OR: 0.73; personal accomplishment OR: 0.76) and higher professional pride (emotional exhaustion OR: 0.63; depersonalization OR: 0.70; personal accomplishment OR: 0.44). PHCWs with higher work intensity (emotional exhaustion OR: 2.37; depersonalization OR: 1.34; personal accomplishment OR: 1.19) had higher scores in all job burnout dimensions. Improving work environments and raising salaries were the preferred ways for PHCWs to reduce job burnout.ConclusionStrategies should be developed to improve job satisfaction among PHCWs, enhance their professional identity, and alleviate burnout to ensure the effective operation of the healthcare system, especially during periods of overwork

Direct field-to-pattern monolithic design of holographic metasurface via residual encoder-decoder convolutional neural network

Complex-amplitude holographic metasurfaces (CAHMs) with the flexibility in modulating phase and amplitude profiles have been used to manipulate the propagation of wavefront with an unprecedented level, leading to higher image-reconstruction quality compared with their natural counterparts. However, prevailing design methods of CAHMs are based on Huygens-Fresnel theory, meta-atom optimization, numerical simulation and experimental verification, which results in a consumption of computing resources. Here, we applied residual encoder-decoder convolutional neural network to directly map the electric field distributions and input images for monolithic metasurface design. A pretrained network is firstly trained by the electric field distributions calculated by diffraction theory, which is subsequently migrated as transfer learning framework to map the simulated electric field distributions and input images. The training results show that the normalized mean pixel error is about 3% on dataset. As verification, the metasurface prototypes are fabricated, simulated and measured. The reconstructed electric field of reverse-engineered metasurface exhibits high similarity to the target electric field, which demonstrates the effectiveness of our design. Encouragingly, this work provides a monolithic field-to-pattern design method for CAHMs, which paves a new route for the direct reconstruction of metasurfaces

A compendium of genetic regulatory effects across pig tissues

The Farm Animal Genotype-Tissue Expression (FarmGTEx) project has been established to develop a public resource of genetic regulatory variants in livestock, which is essential for linking genetic polymorphisms to variation in phenotypes, helping fundamental biological discovery and exploitation in animal breeding and human biomedicine. Here we show results from the pilot phase of PigGTEx by processing 5,457 RNA-sequencing and 1,602 whole-genome sequencing samples passing quality control from pigs. We build a pig genotype imputation panel and associate millions of genetic variants with five types of transcriptomic phenotypes in 34 tissues. We evaluate tissue specificity of regulatory effects and elucidate molecular mechanisms of their action using multi-omics data. Leveraging this resource, we decipher regulatory mechanisms underlying 207 pig complex phenotypes and demonstrate the similarity of pigs to humans in gene expression and the genetic regulation behind complex phenotypes, supporting the importance of pigs as a human biomedical model.</p

The impact of companies’using of new technologies on the quality of customer relationships : A study within logistics industry

Information technology is in an era of rapid development, many new technologies such as artificial intelligence, big data, blockchain technology and so on have begun to be applied in many industries, many logistics companies are also beginning to apply these technologies in the logistics system. As a logistics company, the quality of the relationship between the company and its customers is extremely important for the company's performance and future development, but there are still few studies on the impact of the application of new technologies on the quality of customer relationship. This paper mainly predicts the impact of technology application on customer relationship quality by observing the impact of technology application on logistics service quality. Service quality in this paper is divided into four aspects, namely logistics service efficiency and accuracy, customer service customization, information transparency and communication efficiency, and protection of customer privacy data. In this paper, a semi-structured interview was conducted with seven managers of logistics enterprises using stereotyped case studies and purposeful sampling. The research results of this paper show that large-scale logistics companies are more likely to improve the service quality of logistics through the application of new technologies and thus enhance the quality of the relationship with customers, while small-scale logistics companies may reduce the service quality due to improper technology application due to capital, technology accumulation and other reasons, and thus have a negative impact on the quality of customer relationship. In addition, the research results also show that logistics companies believe that improving service quality in information transparency and communication efficiency, as well as improving the level of customer privacy and data protection is more important for the company, and the benefits brought to the company are also more obvious

A Survey of Local Differential Privacy and Its Variants

The introduction and advancements in Local Differential Privacy (LDP) variants have become a cornerstone in addressing the privacy concerns associated with the vast data produced by smart devices, which forms the foundation for data-driven decision-making in crowdsensing. While harnessing the power of these immense data sets can offer valuable insights, it simultaneously poses significant privacy risks for the users involved. LDP, a distinguished privacy model with a decentralized architecture, stands out for its capability to offer robust privacy assurances for individual users during data collection and analysis. The essence of LDP is its method of locally perturbing each user's data on the client-side before transmission to the server-side, safeguarding against potential privacy breaches at both ends. This article offers an in-depth exploration of LDP, emphasizing its models, its myriad variants, and the foundational structure of LDP algorithms

Image Security Based on Three-Dimensional Chaotic System and Random Dynamic Selection

Image encryption based on a chaos system can effectively protect the privacy of digital images. It is said that a 3D chaotic system has a larger parameter range, better unpredictability and more complex behavior compared to low-dimension chaotic systems. Motivated by this fact, we propose a new image cryptosystem that makes use of a 3D chaotic system. There are three main steps in our scheme. In the first step, the chaotic system uses the hash value of the plaintext image to generate three sequences. In step two, one of the sequences is used to dynamically select confusion and diffusion methods, where confusion and diffusion have three algorithms, respectively, and will produce 32n (n &gt; 100) combinations for encryption. In step three, the image is divided into hundreds of overlapping subblocks, along with the other two sequences, and each block is encrypted in the confusion and diffusion process. Information entropy, NPCR, UACI results and various security analysis results show that the algorithm has a better security performance than existing, similar algorithms, and can better resist clipping, noise, statistical analysis and other attacks

Effects of Pulsed Jet Intensities on the Performance of the S-Duct

The high curvature of modern S-ducts causes a strong secondary flow, which seriously affects the uniformity of the compressor inlet flow. In this study, the flow control method of a pulsed jet was applied in the S-duct at an incoming Mach number of 0.4. The jet holes were with an angle of 45° and were symmetrically distributed on the upper wall. Three jet intensities of 0.16%, 0.24%, and 0.31% were simulated using the unsteady Reynolds-averaged Navier–Stokes equations (URANS) and were validated by experiments. The mechanism of the pulsed jet, with respect to controlling the flow separation in the S-duct, was analyzed through secondary flow behaviors and boundary layer characteristics. The results indicated that the radial and axial pressure gradients were crucial to the formation of the large-scale vortices and reversed fluids in the S-duct. The pulsed jets were found to resist the adverse pressure gradient by exciting the turbulent kinetic energy of the boundary layer fluids. In addition, the dissipation process of vorticity was accelerated due to the promotion of the mixing effect by these devices. Moreover, in the current study, the area with high total pressure loss coefficients decreased gradually along with the intensity increase. Specifically, a maximum loss reduction of 5.9% was achieved when the pulse jet intensity was set to 0.31%, which means that the pulsed jet has great potential in controlling the flow separation in the S-duct

Design and Control of a Series&ndash;Parallel Elastic Actuator for a Weight-Bearing Exoskeleton Robot

Weight-bearing exoskeletons are robots that need to carry loads and interact with humans frequently. Therefore, the actuators of these exoskeletons are supposed to be capable of outputting sufficient force with high compliance and little weight. A series&ndash;parallel elastic actuator (SPEA) is designed, in this work, to meet the demanding requirements of an exoskeleton robot called PALExo. A gas spring is installed in parallel with an electric cylinder to adjust the force output range of the actuator according to the needs of the exoskeleton. A series elastic module (SEM) is installed in series with the electric cylinder and gas spring to improve the compliance of the actuator, the stiffness of which is variable to adapt to the different stiffness requirements of the exoskeleton&rsquo;s legs in the standing phase and swinging phase. A force controller combining dynamic compensation and a cascade control with an inner velocity loop and a disturbance observer is designed for the SPEA. The performance of the force controller is verified by experiments and the results demonstrate that the controller has good adaptability to the stiffness of the SEM