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

A Novel Energy based Model Mechanism for Multi-modal Aspect-Based Sentiment Analysis

Multi-modal aspect-based sentiment analysis (MABSA) has recently attracted increasing attention. The span-based extraction methods, such as FSUIE, demonstrate strong performance in sentiment analysis due to their joint modeling of input sequences and target labels. However, previous methods still have certain limitations: (i) They ignore the difference in the focus of visual information between different analysis targets (aspect or sentiment). (ii) Combining features from uni-modal encoders directly may not be sufficient to eliminate the modal gap and can cause difficulties in capturing the image-text pairwise relevance. (iii) Existing span-based methods for MABSA ignore the pairwise relevance of target span boundaries. To tackle these limitations, we propose a novel framework called DQPSA for multi-modal sentiment analysis. Specifically, our model contains a Prompt as Dual Query (PDQ) module that uses the prompt as both a visual query and a language query to extract prompt-aware visual information and strengthen the pairwise relevance between visual information and the analysis target. Additionally, we introduce an Energy-based Pairwise Expert (EPE) module that models the boundaries pairing of the analysis target from the perspective of an Energy-based Model. This expert predicts aspect or sentiment span based on pairwise stability. Experiments on three widely used benchmarks demonstrate that DQPSA outperforms previous approaches and achieves a new state-of-the-art performance.Comment: AAAI202

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

FSUIE: A Novel Fuzzy Span Mechanism for Universal Information Extraction

Universal Information Extraction (UIE) has been introduced as a unified framework for various Information Extraction (IE) tasks and has achieved widespread success. Despite this, UIE models have limitations. For example, they rely heavily on span boundaries in the data during training, which does not reflect the reality of span annotation challenges. Slight adjustments to positions can also meet requirements. Additionally, UIE models lack attention to the limited span length feature in IE. To address these deficiencies, we propose the Fuzzy Span Universal Information Extraction (FSUIE) framework. Specifically, our contribution consists of two concepts: fuzzy span loss and fuzzy span attention. Our experimental results on a series of main IE tasks show significant improvement compared to the baseline, especially in terms of fast convergence and strong performance with small amounts of data and training epochs. These results demonstrate the effectiveness and generalization of FSUIE in different tasks, settings, and scenarios.Comment: ACL202

Unlock Multi-Modal Capability of Dense Retrieval via Visual Module Plugin

This paper proposes Multi-modAl Retrieval model via Visual modulE pLugin (MARVEL) to learn an embedding space for queries and multi-modal documents to conduct retrieval. MARVEL encodes queries and multi-modal documents with a unified encoder model, which helps to alleviate the modality gap between images and texts. Specifically, we enable the image understanding ability of a well-trained dense retriever, T5-ANCE, by incorporating the image features encoded by the visual module as its inputs. To facilitate the multi-modal retrieval tasks, we build the ClueWeb22-MM dataset based on the ClueWeb22 dataset, which regards anchor texts as queries, and exact the related texts and image documents from anchor linked web pages. Our experiments show that MARVEL significantly outperforms the state-of-the-art methods on the multi-modal retrieval dataset WebQA and ClueWeb22-MM. Our further analyses show that the visual module plugin method is tailored to enable the image understanding ability for an existing dense retrieval model. Besides, we also show that the language model has the ability to extract image semantics from image encoders and adapt the image features in the input space of language models. All codes are available at https://github.com/OpenMatch/MARVEL

Water-gas masking effect of the primary active sites in coal and room temperature oxidation of coal after desorption

The oxidation of coal at room temperature provides the initial heat source for spontaneous coal combustion (CSC). In the CSC theoretical study, exploring the active substances in coal that can be oxidized at room temperature is a complex problem. Previous thermal decomposition experiments have found that coal after pyrolysis contains active sites that can exist stably in inert gases and be oxidized at room temperature. Thus it is speculated that there may also be primary active sites that are forced to be stored under inert media in coal. In order to explore the primary active sites of coal, the vacuum drying technology is applied. Based on that, the water in the raw coal can reach the boiling point under the low-temperature environment of negative vacuum pressure to complete the removal of water and gas. Under different experimental conditions (coal, desorption temperature, oxidation temperature, particle size), the cyclic oxidation online monitoring technology is used to design and implement the room temperature oxidation experiment of the desorbed coal samples. At the same time, the reaction mechanism is analyzed by the corresponding low-temperature nitrogen adsorption, XPS, ESR experiments. After vacuum desorbed, the oxidation experiments under cyclic conditions show that the massive gaseous oxidation products such as CO and CO2 will be formed in the process of raw oxidation at room temperature, and the gases appear and accumulate soon after oxygen is introduced, which proves that coal oxidation can occur at room temperature. The room temperature oxidation experiment after the desorption of raw coal indicates that there are a large number of active sites affected by water-gas masking in the raw coal. They are unable to undergo the oxidation exothermic processes, while the coal after the desorption of water and gas under negative pressure exposes massive active sites and forms a channel conducive to oxygen transport and reaction, which rapidly occur oxidation exothermic phenomenon and lead to the rise of coal temperature. Therefore, the active structure leading to the spontaneous warming of the raw coal is found, and the experiments extend the view of room temperature oxidation of the active sites from the particular case state of the pyrolysis to the general state. From the comparison of gas product generation, it can be seen that CO, which is not easy to be adsorbed by pores, is produced quickly at the moment of contact between the primary active site and oxygen. Therefore, it can be concluded that CO is more suitable as an intuitive gas evaluation index of the concentration of the active sites compared with CO2. The room temperature oxidation of the primary active sites of coal helps reveal the mechanism of coal spontaneous combustion and provides a solution to the problem of spontaneous combustion during gas extraction in high-gas mines and the problem of CO over-limit in low-rank coal mines

A precise forest spatial structure investigation using the SLAM+AR technology

IntroductionForest spatial structures are the foundations of the structure and function of forest ecosystems. Quantitative descriptions and analyses of forest spatial structure have recently become common tools for digitalized forest management. Therefore, the accuracy and intelligence of acquiring forest spatial structure information are of great significance.MethodsIn this study, we developed a forest measurement system using a mobile phone. Through this system, the following tree measurements can be achieved: (1) point cloud of tree and chest diameter circle to measure tree diameter at breast height (DBH) and position coordinates of tree by using simultaneous localization and mapping (SLAM) technology, (2) virtual boundary creation of the sample plot, and the auxiliary measurement function of tree with the augmented reality (AR) interactive module, and (3) position coordinates and single-tree volume factor to calculate the spatial structural parameters of the forest (e.g., Mingling degree, Dominance index, Uniform angle index, and Crowdedness index).The system was tested in three 32 x 32 martificial forest plots.ResultsThe average DBH estimations showed BIAS of -0.47 to 0.45 cm and RMSEs of 0.57 to 0.95 cm. Its accuracy level met the requirements of forestry sample surveys. The tree position estimates for the three plots had relatively small RMSEs with 0.17 to 0.22 m on the x-axis and 0.16 to 0.26 m on the y-axis. The spatial structural parameters were as follows: the mingling degree of plot 1 was 0.32, and the overall mixing degree of tree species was low. The trees in plots 2 and 3 were all single species, and the mixing degree of both plots was 0. The dominance index of the three plots was 0.56, 0.51, and 0.51, indicating that the competitive advantage of the whole orest species was not obvious. The uniform angle index of the three plots was 0.55, 0.59, and 0.61, indicating that the positions of trees in the three plots were randomly distributed. The crowdedness index of plot 1 was 1.03, indicating that the degree of aggregation of the trees was low and showed a random distribution trend. The crowdedness index of the other plots were 1.36 and 1.40, indicating that the trees in the plots show a trend of uniform distribution, and the uniformity of plot 3 is higher than that of plot 2, but the overall uniformity is relatively weak.DiscussionThe findings of this study provide support for the optimization of forest structures and improve our conceptual understanding of forest community succession and restoration, in addition to the informatization and precision of forest spatial structure surveys

Research and development of Hg-CEMS flue gas pre-treatment technology

In view of the natural endowment of mercury in fossil fuels and mineral resources, as well as the mercury emission controlling and regulating in the energy and resource utilization processes, the research and development on the mercury continuous emissions monitoring system (Hg-CEMS) with proprietary intellectual property rights is the most important requirement in science and technology in China. As a critical component of the Hg-CEMS system, the flue gas pretreatment system is a core technology that limits the development and application of the Hg-CEMS technology in China. This paper presents a comprehensive review of the research progress in the four key modules of the Hg-CEMS flue gas pretreatment technology, including the dilution sampling, Hg0/Hg2+ separation, Hg2+ reduction and Hg2+ calibration gas generation. Firstly, the dilution sampling techniques are highlighted in their characteristics and principles. The working principles, structures, and design considerations of the critical parameters for both critical hole and thermal dilution injectors are summarized. Emphasis is focused on the connection of numerical simulation with the optimal design methodology for the thermal dilution injector and critical hole. Secondly, regarding the Hg0/Hg2+ separation technology, various partitioning methodologies encompassing the wet absorption separation, physical adsorption separation and chemical adsorption separation are discussed. Particular attention is given to the separation and adsorption efficiency of the advanced dry chemical adsorption techniques involving the novel selective adsorbents of KCl and CaO with their updated theoretical and experimental outcomes under practical operating conditions. Thirdly, in aspect of the Hg2+ reduction technology, a comparative analysis of wet chemical reduction, low-temperature reduction and high-temperature reduction techniques is expatiated. Particular focus is on the active components of solid-state reducing agents, the impact of temperature on the reduction of divalent mercury, and the detrimental influences of flue gas components on the re-oxidation of the reduced elemental mercury in the low-temperature reduction techniques. An in-depth investigation of the impact of filler materials, acidic gas components and acid removal techniques on the reduction of divalent mercury in the high-temperature reduction techniques is highlighted. Finally, facing the technical problems, a solid generation method of the Hg2+ calibration gas is invented and its industrial utilization feasibility is verified in chemistry and experiments. In conjunction with the current status of research and application of the Hg-CEMS technology, the research technical routs, the solutions to some problems and development prospect for the above-mentioned four key modules are put forward

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

Virtual Collection for Distributed Photovoltaic Data: Challenges, Methodologies, and Applications

In recent years, with the rapid development of distributed photovoltaic systems (DPVS), the shortage of data monitoring devices and the difficulty of comprehensive coverage of measurement equipment has become more significant, bringing great challenges to the efficient management and maintenance of DPVS. Virtual collection is a new DPVS data collection scheme with cost-effectiveness and computational efficiency that meets the needs of distributed energy management but lacks attention and research. To fill the gap in the current research field, this paper provides a comprehensive and systematic review of DPVS virtual collection. We provide a detailed introduction to the process of DPVS virtual collection and identify the challenges faced by virtual collection through problem analogy. Furthermore, in response to the above challenges, this paper summarizes the main methods applicable to virtual collection, including similarity analysis, reference station selection, and PV data inference. Finally, this paper thoroughly discusses the diversified application scenarios of virtual collection, hoping to provide helpful information for the development of the DPVS industry