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To achieve the physics goal of precisely measure the Higgs, Z, W bosons and the top quark, future electron-positron colliders require that their detector system has excellent jet energy resolution. One feasible technical option is the high granular calorimetery based on the particle flow algorithm (PFA). A new high-granularity hadronic calorimeter with glass scintillator tiles (GSHCAL) has been proposed, which focus on the significant improvement of hadronic energy resolution with a notable increase of the energy sampling fraction by using high-density glass scintillator tiles. The minimum ionizing particle (MIP) response of a glass scintillator tile is crucial to the hadronic calorimeter, so a dedicated beamtest setup was developed for testing the first batch of large-size glass scintillators. The maximum MIP response of the first batch of glass scintillator tiles can reach up to 107 p.e./MIP, which essentially meets the design requirements of the CEPC GSHCAL. An optical simulation model of a single glass scintillator tile has been established, and the simulation results are consistent with the beamtest results.

High-frequency gravitational waves (HFGWs) carry a wealth of information on the early Universe with a tiny comoving horizon and astronomical objects of small scale but with dense energy. We demonstrate that the nearby planets, such as Earth and Jupiter, can be utilized as a laboratory for detecting the HFGWs. These GWs are then expected to convert to signal photons in the planetary magnetosphere, across the frequency band of astronomical observation. As a proof of concept, we present the first limits from the existing low-Earth-orbit satellite for specific frequency bands and project the sensitivities for the future more-dedicated detections. The first limits from Juno, the latest mission orbiting Jupiter, are also presented. Attributed to the long path of effective GW-photon conversion and the wide angular distribution of signal flux, we find that these limits are highly encouraging, for a broad frequency range including a large portion unexplored before.

The spread of the Coronavirus disease-2019 epidemic has caused many courses and exams to be conducted online. The cheating behavior detection model in examination invigilation systems plays a pivotal role in guaranteeing the equality of long-distance examinations. However, cheating behavior is rare, and most researchers do not comprehensively take into account features such as head posture, gaze angle, body posture, and background information in the task of cheating behavior detection. In this paper, we develop and present CHEESE, a CHEating detection framework via multiplE inStancE learning. The framework consists of a label generator that implements weak supervision and a feature encoder to learn discriminative features. In addition, the framework combines body posture and background features extracted by 3D convolution with eye gaze, head posture and facial features captured by OpenFace 2.0. These features are fed into the spatio-temporal graph module by stitching to analyze the spatio-temporal changes in video clips to detect the cheating behaviors. Our experiments on three datasets, UCF-Crime, ShanghaiTech and Online Exam Proctoring (OEP), prove the effectiveness of our method as compared to the state-of-the-art approaches, and obtain the frame-level AUC score of 87.58% on the OEP dataset., Comment: 12 pages, 7 figures

We formalize Italian smocking, an intricate embroidery technique that gathers flat fabric into pleats along meandering lines of stitches, resulting in pleats that fold and gather where the stitching veers. In contrast to English smocking, characterized by colorful stitches decorating uniformly shaped pleats, and Canadian smocking, which uses localized knots to form voluminous pleats, Italian smocking permits the fabric to move freely along the stitched threads following curved paths, resulting in complex and unpredictable pleats with highly diverse, irregular structures, achieved simply by pulling on the threads. We introduce a novel method for digital previewing of Italian smocking results, given the thread stitching path as input. Our method uses a coarse-grained mass-spring system to simulate the interaction between the threads and the fabric. This configuration guides the fine-level fabric deformation through an adaptation of the state-of-the-art simulator, C-IPC. Our method models the general problem of fabric-thread interaction and can be readily adapted to preview Canadian smocking as well. We compare our results to baseline approaches and physical fabrications to demonstrate the accuracy of our method.

Wood-leaf classification is an essential and fundamental prerequisite in the analysis and estimation of forest attributes from terrestrial laser scanning (TLS) point clouds,including critical measurements such as diameter at breast height(DBH),above-ground biomass(AGB),wood volume.To address this,we introduce the Wood-Leaf Classification Network(WLC-Net),a deep learning model derived from PointNet++,designed to differentiate between wood and leaf points within tree point clouds.WLC-Net enhances classification accuracy,completeness,and speed by incorporating linearity as an inherent feature,refining the input-output framework,and optimizing the centroid sampling technique.WLC-Net was trained and assessed using three distinct tree species datasets,comprising a total of 102 individual tree point clouds:21 Chinese ash trees,21 willow trees,and 60 tropical trees.For comparative evaluation,five alternative methods,including PointNet++,DGCNN,Krishna Moorthy's method,LeWoS, and Sun's method,were also applied to these datasets.The classification accuracy of all six methods was quantified using three metrics:overall accuracy(OA),mean Intersection over Union(mIoU),and F1-score.Across all three datasets,WLC-Net demonstrated superior performance, achieving OA scores of 0.9778, 0.9712, and 0.9508;mIoU scores of 0.9761, 0.9693,and 0.9141;and F1-scores of 0.8628, 0.7938,and 0.9019,respectively.The time costs of WLC-Net were also recorded to evaluate the efficiency.The average processing time was 102.74s per million points for WLC-Net.In terms of visual inspect,accuracy evaluation and efficiency evaluation,the results suggest that WLC-Net presents a promising approach for wood-leaf classification,distinguished by its high accuracy. In addition,WLC-Net also exhibits strong applicability across various tree point clouds and holds promise for further optimization., Comment: 41 pages, 14 figures, 5 tables

Due to sophisticated deployments of all kinds of wireless networks (e.g., 5G, Wi-Fi, Bluetooth, LEO satellite, etc.), multiband signals distribute in a large bandwidth (e.g., from 70 MHz to 8 GHz). Consequently, for network monitoring and spectrum sharing applications, a sniffer for extracting physical layer information, such as structure of packet, with low sampling rate (especially, sub-Nyquist sampling) can significantly improve their cost- and energy-efficiency. However, to achieve a multiband signals sniffer is really a challenge. To this end, we propose Sums, a system that can sniff and analyze multiband signals in a blind manner. Our Sums takes advantage of hardware and algorithm co-design, multi-coset sub-Nyquist sampling hardware, and a multi-task deep learning framework. The hardware component breaks the Nyquist rule to sample GHz bandwidth, but only pays for a 50 MSPS sampling rate. Our multi-task learning framework directly tackles the sampling data to perform spectrum sensing, physical layer protocol recognition, and demodulation for deep inspection from multiband signals. Extensive experiments demonstrate that Sums achieves higher accuracy than the state-of-theart baselines in spectrum sensing, modulation classification, and demodulation. As a result, our Sums can help researchers and end-users to diagnose or troubleshoot their problems of wireless infrastructures deployments in practice., Comment: 12 pages, 9 figures

Jing Ren,1,* Qinhui Wang,1,* Linna Liu,1 Yunfeng Xiao,1 Peigang Ji,2 Hui Du,3 Shan Wang,4 Yao Zheng,1 Qi Yang1 1Department of Pharmacy, the Second Affiliated Hospital of Air Force Medical University, Xi’an, Shaanxi, People’s Republic of China; 2Department of Neurosurgery, the Second Affiliated Hospital of Air Force Medical University, Xi’an, Shaanxi, People’s Republic of China; 3Xi’an Institute for Food and Drug Control, Xi’an, Shaanxi, People’s Republic of China; 4Department of Pharmacy, NYU Langone Hospital – Long Island, Mineola, NY, USA*These authors contributed equally to this workCorrespondence: Qi Yang, Tel +86 15829673096, Fax +86-029-84777154, Email 376230719@qq.comAbstract: Post-neurosurgical infections caused by multidrug-resistant Enterobacterales are difficult to treat due to limited therapeutic options. Ceftazidime-avibactam (CAZ-AVI), a combination of cephalosporin and a novel β-lactamase inhibitor, has exhibited potential activity against multi/extensive drug-resistant (MDR/XDR) gram-negative bacilli. Several reports have described the successful treatment of central infections caused by MDR/XDR Pseudomonas aeruginosa or Enterobacterales. However, data on the efficacy and effective drug distribution of CAZ-AVI in the central nervous system (CNS), particularly in children, are lacking. We report a case of a 4-year-old girl with post-neurosurgical meningitis and abscess caused by extended-spectrum β-lactamase-producing Escherichia coli successfully treated with CAZ-AVI. CAZ-AVI therapeutic drug monitoring was performed to evaluate its efficacy and effective drug distribution in the CNS. We measured CAZ (15.6, 7.1, and 3.5 μg/mL) and AVI (4.0, 2.1, and 1.2 μg/mL) in cerebrospinal fluid (CSF) samples obtained 3, 5, and 7 h after the administration of the 15th CAZ-AVI dose (2.5 g, q8h, iv), respectively. We also measured CAZ (57.0 and 25.8 μg/mL) and AVI (11.3 and 4.5 μg/mL) in serum samples obtained 3 and 5 h

High-frequency gravitational waves (HFGWs) carry a wealth of information on the early Universe with a tiny comoving Hubble horizon and astronomical objects of small scale but with dense energy. We demonstrate that the nearby planets, such as Earth and Jupiter, can be utilized as a laboratory for detecting the HFGWs. These GWs are then expected to convert to signal photons in the planetary magnetosphere, across the frequency band of astronomical observation. As a proof of concept, we present the first limits from the existing low-Earth-orbit satellite for specific frequency bands and project the sensitivities for the future more-dedicated detections. The first limits from Juno, the latest mission orbiting Jupiter, are also presented. Attributed to the long path of effective GW-photon conversion and the wide angular distribution of signal flux, we find that these limits are highly encouraging, for a broad range of frequencies including a large portion unexplored before., Comment: 10 pages, 8 figures. Updated Fig.3 (projected limits) with the extreme UV band. Typos are fixed

Wave dark matter (DM) represents a class of the most representative DM candidates. Due to its periodic perturbation to spacetime, the wave DM can be detected with a galactic interferometer - pulsar timing array (PTA). We perform in this Letter a first analysis of applying the $\gamma$-ray PTA to detect the wave DM, with the data of Fermi Large Area Telescope (Fermi-LAT). Despite the limitation in statistics, the $\gamma$-PTA demonstrates a promising sensitivity potential for a mass $\sim 10^{-23}-10^{-22}$ eV. We show that the upper limits not far from those of the dedicated radio-PTA projects can be achieved. Particularly, we have fulfilled an analysis to cross-correlate the pulsar data, which has been essentially missing so far in real data analysis but is known to be crucial for identifying the nature of potential signals, with the Fermi-LAT data of two pulsars., Comment: 5 pages, 3 figures. Comments welcome!

Cost effectiveness is one of the crucial key factors driving the shipping and trading industry. Nowadays global trade involves multiple parties and sectors across international borders, and numerous paper transport documents, such as paper bills of lading (pBLs), are handled and disseminated around the world. With the advent of digital technology, electronic solutions are arguably ripe for the replacement of pBLs. The key benefits of using an electronic bill of lading have long been identified as the speed of transfer, the avoidance of external costs and removal of need to use Letters of Indemnity. As an alternative to the transfer of physical endorsements, electronic bills of lading (eBLs) are processed and transferred automatically by a computer system that constructs the information electronically using agreed standards. However, the journey of promoting eBLs is not all smooth sailing. Despite the growing number of private and public projects and initiatives during the past 40 years, the maritime world has yet seen the dawn of the electronic age. On the contrary, pBLs remain a staple in international trade, despite years of criticism over delays, costs and security risks. This thesis seeks to identify the underlying reasons for the stagnation in the development of this key legal document. It will demonstrate that, apart from the technical challenges, the real impediment to a true replacement of the pBL is the formidable legal challenges in reproducing the three principal functions of the antique paper-based trade document, for which the existing paperless implementations have failed to provide anything but a piecemeal solution. In coming to this finding, the thesis will also examine the effectiveness of the various legislative efforts, both nationally and internationally, to address the legal issues identified in the thesis. Finally, the author will attempt to speculate on the trends and prospects of the evolution of eBLs in the light of the observation

We propose a new stellar structure of compact stars, the "cross stars"that consist of a hadronic matter core and a quark matter crust, with an inverted structure compared to the conventional hybrid stars. This distinct stellar structure naturally arises from the quark matter to hadronic matter transition associated with the chemical potential crossing, in the context of the quark matter hypothesis that either strange or up-down quark matter is the ground state of baryonic matter at low pressure. We find that the interplay between the hadronic matter and quark matter compositions of cross stars can help to reconcile the small radii constraints indicated by the LIGO/Virgo GW170817 event, the large radii constraints set for massive compact stars by recent NICER x-ray observations, and the recent observation of the most-massive pulsar PSR J0952-0607. This leaves more space open for the equation of states of both hadronic matter and quark matter. © 2023 authors. Published by the American Physical Society. Published by the American Physical Society under the terms of the "https://creativecommons.org/licenses/by/4.0/"Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI. Funded by SCOAP3.

Pulsar timing arrays (PTAs) can detect disturbances in the fabric of spacetime on a galactic scale by monitoring the arrival time of pulses from millisecond pulsars (MSPs). Recent advancements have enabled the use of $\gamma$-ray radiation emitted by MSPs, in addition to radio waves, for PTA experiments. Wave dark matter (DM), a prominent class of DM candidates, can be detected with PTAs due to its periodic perturbations of the spacetime metric. In response to this development, we perform in this Letter a first analysis of applying the $\gamma$-ray PTA to detect the ultralight axion-like wave DM, with the data of Fermi Large Area Telescope (Fermi-LAT). Despite its much smaller collecting area, the Fermi-LAT $\gamma$-ray PTA demonstrates a promising sensitivity potential. We show that the upper limits not far from those of the dedicated radio-PTA projects can be achieved. Moreover, we initiate a cross-correlation analysis using the data of two Fermi-LAT pulsars. The cross-correlation of phases, while carrying key information on the source of the spacetime perturbations, has been ignored in the existing data analyses for the wave DM detection with PTAs. Our analysis indicates that taking this information into account can improve the sensitivity to wave DM by $\gtrsim 50\%$ at masses below $10^{-23}$ eV., Comment: 11 pages, 4 figures. Published version

Pulsar timing arrays (PTAs) consisting of widely distributed and well-timed millisecond pulsars can serve as a galactic interferometer to measure gravitational waves. With the same data acquired for PTAs, we propose to develop pulsar polarization arrays (PPAs), to explore astrophysics and fundamental physics. As in the case of PTAs, PPAs are best suited to reveal temporal and spatial correlations at large scales that are hard to mimic by local noise. To demonstrate the physical potential of PPAs, we consider detection of ultralight axionlike dark matter (ALDM), through cosmic birefringence induced by its Chern-Simons coupling. Because of its tiny mass, the ultralight ALDM can be generated as a Bose-Einstein condensate, characterized by a strong wave nature. Incorporating both temporal and spatial correlations of the signal, we show that PPAs have a potential to probe the Chern-Simons coupling up to ∼10-14-10-17 GeV-1, with a mass range ∼10-27-10-21 eV. © 2023 American Physical Society.

The annual regrowth of deer antlers provides a valuable model for studying organ regeneration in mammals. We describe a single-cell atlas of antler regrowth. The earliest-stage antler initiators were mesenchymal cells that express the paired related homeobox 1 gene (PRRX1+ mesenchymal cells). We also identified a population of “antler blastema progenitor cells” (ABPCs) that developed from the PRRX1+ mesenchymal cells and directed the antler regeneration process. Cross-species comparisons identified ABPCs in several mammalian blastema. In vivo and in vitro ABPCs displayed strong self-renewal ability and could generate osteochondral lineage cells. Last, we observed a spatially well-structured pattern of cellular and gene expression in antler growth center during the peak growth stage, revealing the cellular mechanisms involved in rapid antler elongation., The annual regrowth of deer antlers provides a valuable model for studying organ regeneration in mammals. We describe a single-cell atlas of antler regrowth. The earliest-stage antler initiators were mesenchymal cells that express the paired related homeobox 1 gene (PRRX1+ mesenchymal cells). We also identified a population of "antler blastema progenitor cells" (ABPCs) that developed from the PRRX1+ mesenchymal cells and directed the antler regeneration process. Cross-species comparisons identified ABPCs in several mammalian blastema. In vivo and in vitro ABPCs displayed strong self-renewal ability and could generate osteochondral lineage cells. Last, we observed a spatially well-structured pattern of cellular and gene expression in antler growth center during the peak growth stage, revealing the cellular mechanisms involved in rapid antler elongation.

We develop an optimization-based method to model smocking, a surface embroidery technique that provides decorative geometric texturing while maintaining stretch properties of the fabric. During smocking, multiple pairs of points on the fabric are stitched together, creating non-manifold geometric features and visually pleasing textures. Designing smocking patterns is challenging, because the outcome of stitching is unpredictable: the final texture is often revealed only when the whole smocking process is completed, necessitating painstaking physical fabrication and time consuming trial-and-error experimentation. This motivates us to seek a digital smocking design method. Straightforward attempts to compute smocked fabric geometry using surface deformation or cloth simulation methods fail to produce realistic results, likely due to the intricate structure of the designs, the large number of contacts and high-curvature folds. We instead formulate smocking as a graph embedding and shape deformation problem. We extract a coarse graph representing the fabric and the stitching constraints, and then derive the graph structure of the smocked result. We solve for the 3D embedding of this graph, which in turn reliably guides the deformation of the high-resolution fabric mesh. Our optimization based method is simple, efficient, and flexible, which allows us to build an interactive system for smocking pattern exploration. To demonstrate the accuracy of our method, we compare our results to real fabrications on a large set of smocking patterns, Comment: 17 pages, 35 figures

The flea beetle, Altica cirsicola, escapes predators by jumping and landing in a dense maze of leaves. How do they land on such varied surfaces? In this experimental study, we filmed the take-off, flight, and landing of flea beetles on a configurable angled platform. We report three in-flight behaviors: winged, wingless, and an intermediate winged mode. These modes significantly affected take-off speed, acceleration, and the duration that wings were deployed. When wings were closed, flea beetles rolled or pitched up to five times in the air. This work may help to understand how insects can jump and right themselves onto variable surfaces.

Soil respiration in forests contributes to significant carbon dioxide emissions from terrestrial ecosystems but it varies both spatially and seasonally. Both abiotic and biotic factors influence soil respiration but their relative contribution to spatial and seasonal variability remains poorly understood, which leads to uncertainty in models of global C cycling and predictions of future climate change. Here, we hypothesize that tree diversity, soil diversity, and soil properties contribute to local-scale variability of soil respiration but their relative importance changes in different seasons. To test our hypothesis, we conducted seasonal soil respiration measurements along a local-scale environmental gradient in a temperate forest in Northeast China, analyzed spatial variability of soil respiration and tested the relationships between soil respiration and a variety of abiotic and biotic factors including topography, soil chemical properties, and plant and soil diversity. We found that soil respiration varied substantially across the study site, with spatial coefficients of variation (CV) of 29.1%, 27.3% and 30.8% in spring, summer, and autumn, respectively. Soil respiration was consistently lower at high soil water content, but the influence of other factors was seasonal. In spring, soil respiration increased with tree diversity and biomass but decreased with soil fungal diversity. In summer, soil respiration increased with soil temperature, whereas in autumn, soil respiration increased with tree diversity but decreased with increasing soil nutrient content. However, soil nutrient content indirectly enhanced soil respiration via its effect on tree diversity across seasons, and forest stand structure indirectly enhanced soil respiration via tree diversity in spring. Our results highlight that substantial differences in soil respiration at local scales was jointly explained by soil properties (soil water content and soil nutrients), tree diversity, and soil fungal d

We propose a new stellar structure of compact stars, the ``Cross stars" (CrSs) that consist of a hadronic matter core and a quark matter crust, with an inverted structure compared to the conventional hybrid stars. This distinct stellar structure naturally arises from the quark matter to hadronic matter transition associated with the chemical potential crossing, in the context of the quark matter hypothesis that either strange or up-down quark matter is the ground state of baryonic matter at low pressure. We find that the interplay between the hadronic matter and quark matter compositions of CrSs can help to reconcile the small radii constraints indicated by the LIGO/Virgo GW170817 event, the large radii constraints set for massive compact stars by recent NICER X-ray observations, and the recent observation of the most-massive pulsar PSR J0952-0607. This leaves more space open for the equation of states of both hadronic matter and quark matter., Comment: 10 pages, 6 figures

Soil respiration in forests contributes to significant carbon dioxide emissions from terrestrial ecosystems but it varies both spatially and seasonally. Both abiotic and biotic factors influence soil respiration but their relative contribution to spatial and seasonal variability remains poorly understood, which leads to uncertainty in models of global C cycling and predictions of future climate change. Here, we hypothesize that tree diversity, soil diversity, and soil properties contribute to local-scale variability of soil respiration but their relative importance changes in different seasons. To test our hypothesis, we conducted seasonal soil respiration measurements along a local-scale environmental gradient in a temperate forest in Northeast China, analyzed spatial variability of soil respiration and tested the relationships between soil respiration and a variety of abiotic and biotic factors including topography, soil chemical properties, and plant and soil diversity. We found that soil respiration varied substantially across the study site, with spatial coefficients of variation (CV) of 29.1%, 27.3% and 30.8% in spring, summer, and autumn, respectively. Soil respiration was consistently lower at high soil water content, but the influence of other factors was seasonal. In spring, soil respiration increased with tree diversity and biomass but decreased with soil fungal diversity. In summer, soil respiration increased with soil temperature, whereas in autumn, soil respiration increased with tree diversity but decreased with increasing soil nutrient content. However, soil nutrient content indirectly enhanced soil respiration via its effect on tree diversity across seasons, and forest stand structure indirectly enhanced soil respiration via tree diversity in spring. Our results highlight that substantial differences in soil respiration at local scales was jointly explained by soil properties (soil water content and soil nutrients), tree diversity, and soil fungal d

Anomaly analytics is a popular and vital task in various research contexts, which has been studied for several decades. At the same time, deep learning has shown its capacity in solving many graph-based tasks like, node classification, link prediction, and graph classification. Recently, many studies are extending graph learning models for solving anomaly analytics problems, resulting in beneficial advances in graph-based anomaly analytics techniques. In this survey, we provide a comprehensive overview of graph learning methods for anomaly analytics tasks. We classify them into four categories based on their model architectures, namely graph convolutional network (GCN), graph attention network (GAT), graph autoencoder (GAE), and other graph learning models. The differences between these methods are also compared in a systematic manner. Furthermore, we outline several graph-based anomaly analytics applications across various domains in the real world. Finally, we discuss five potential future research directions in this rapidly growing field.

We introduce pointwise map smoothness via the Dirichlet energy into the functional map pipeline, and propose an algorithm for optimizing it efficiently, which leads to high-quality results in challenging settings. Specifically, we first formulate the Dirichlet energy of the pulled-back shape coordinates, as a way to evaluate smoothness of a pointwise map across discrete surfaces. We then extend the recently proposed discrete solver and show how a strategy based on auxiliary variable reformulation allows us to optimize pointwise map smoothness alongside desirable functional map properties such as bijectivity. This leads to an efficient map refinement strategy that simultaneously improves functional and point-to-point correspondences, obtaining smooth maps even on non-isometric shape pairs. Moreover, we demonstrate that several previously proposed methods for computing smooth maps can be reformulated as variants of our approach, which allows us to compare different formulations in a consistent framework. Finally, we compare these methods both on existing benchmarks and on a new rich dataset that we introduce, which contains non-rigid, non-isometric shape pairs with inter-category and cross-category correspondences. Our work leads to a general framework for optimizing and analyzing map smoothness both conceptually and in challenging practical settings., Comment: Main Manuscript: 10 pages, 5 Figures, 3 Tables // Supplementary: 4 pages, 3 Figures, 5 Tables

Line clouds, though under-investigated in the previous work, potentially encode more compact structural information of buildings than point clouds extracted from multi-view images. In this work, we propose the first network to process line clouds for building wireframe abstraction. The network takes a line cloud as input , i.e., a nonstructural and unordered set of 3D line segments extracted from multi-view images, and outputs a 3D wireframe of the underlying building, which consists of a sparse set of 3D junctions connected by line segments. We observe that a line patch, i.e., a group of neighboring line segments, encodes sufficient contour information to predict the existence and even the 3D position of a potential junction, as well as the likelihood of connectivity between two query junctions. We therefore introduce a two-layer Line-Patch Transformer to extract junctions and connectivities from sampled line patches to form a 3D building wireframe model. We also introduce a synthetic dataset of multi-view images with ground-truth 3D wireframe. We extensively justify that our reconstructed 3D wireframe models significantly improve upon multiple baseline building reconstruction methods. The code and data can be found at https://github.com/Luo1Cheng/LC2WF., Comment: 10 pages, 6 figures

The evaluation of 3D face reconstruction results typically relies on a rigid shape alignment between the estimated 3D model and the ground-truth scan. We observe that aligning two shapes with different reference points can largely affect the evaluation results. This poses difficulties for precisely diagnosing and improving a 3D face reconstruction method. In this paper, we propose a novel evaluation approach with a new benchmark REALY, consists of 100 globally aligned face scans with accurate facial keypoints, high-quality region masks, and topology-consistent meshes. Our approach performs region-wise shape alignment and leads to more accurate, bidirectional correspondences during computing the shape errors. The fine-grained, region-wise evaluation results provide us detailed understandings about the performance of state-of-the-art 3D face reconstruction methods. For example, our experiments on single-image based reconstruction methods reveal that DECA performs the best on nose regions, while GANFit performs better on cheek regions. Besides, a new and high-quality 3DMM basis, HIFI3D++, is further derived using the same procedure as we construct REALY to align and retopologize several 3D face datasets. We will release REALY, HIFI3D++, and our new evaluation pipeline at https://realy3dface.com., Comment: Accepted to ECCV 2022, camera-ready version; Project page: https://realy3dface.com; Code: https://github.com/czh-98/REALY

Anomaly detection is one of the most active research areas in various critical domains, such as healthcare, fintech, and public security. However, little attention has been paid to scholarly data, i.e., anomaly detection in a citation network. Citation is considered as one of the most crucial metrics to evaluate the impact of scientific research, which may be gamed in multiple ways. Therefore, anomaly detection in citation networks is of significant importance to identify manipulation and inflation of citations. To address this open issue, we propose a novel deep graph learning model, namely GLAD (Graph Learning for Anomaly Detection), to identify anomalies in citation networks. GLAD incorporates text semantic mining to network representation learning by adding both node attributes and link attributes via graph neural networks. It exploits not only the relevance of citation contents but also hidden relationships between papers. Within the GLAD framework, we propose an algorithm called CPU (Citation PUrpose) to discover the purpose of citation based on citation texts. The performance of GLAD is validated through a simulated anomalous citation dataset. Experimental results demonstrate the effectiveness of GLAD on the anomalous citation detection task.

In this work, we demonstrate a novel system, namely Web of Scholars, which integrates state-of-the-art mining techniques to search, mine, and visualize complex networks behind scholars in the field of Computer Science. Relying on the knowledge graph, it provides services for fast, accurate, and intelligent semantic querying as well as powerful recommendations. In addition, in order to realize information sharing, it provides an open API to be served as the underlying architecture for advanced functions. Web of Scholars takes advantage of knowledge graph, which means that it will be able to access more knowledge if more search exist. It can be served as a useful and interoperable tool for scholars to conduct in-depth analysis within Science of Science.

With the explosive growth of new graduates with research degrees every year, unprecedented challenges arise for early-career researchers to find a job at a suitable institution. This study aims to understand the behavior of academic job transition and hence recommend suitable institutions for PhD graduates. Specifically, we design a deep learning model to predict the career move of early-career researchers and provide suggestions. The design is built on top of scholarly/academic networks, which contains abundant information about scientific collaboration among scholars and institutions. We construct a heterogeneous scholarly network to facilitate the exploring of the behavior of career moves and the recommendation of institutions for scholars. We devise an unsupervised learning model called HAI (Heterogeneous graph Attention InfoMax) which aggregates attention mechanism and mutual information for institution recommendation. Moreover, we propose scholar attention and meta-path attention to discover the hidden relationships between several meta-paths. With these mechanisms, HAI provides ordered recommendations with explainability. We evaluate HAI upon a real-world dataset against baseline methods. Experimental results verify the effectiveness and efficiency of our approach., Comment: 8 pages, 5 figures

5G/B5G is envisioned to support various services with the assistance of network slices, each slice instance asks for adequate resources to provide the pre-negotiated service quality to its subscribers. Slice Admission Control (SAC) algorithm is a necessity for Slice Providers (SPs) to guarantee the QoS and QoE of each admitted request with limited resources. In that circumstance, the priority concern of services and the fairness of resource allocation arise as meaningful topics for researchers. The former originates from the innate characteristics of various services supported by 5G networks, and the latter matters because slices are instantiated on shared physical equipment. However, the two issues are mainly investigated separately in the literature or do not receive sufficient research simultaneously. In this work, we study the SAC problem in 5G/B5G networks, aiming at enhancing the fairness degree on the premise of satisfying the necessary priority requirements. We first reinterpret priority as a higher cumulative service acceptance ratio (CSAR), and adopt the uniformity of adjacent CSAR gaps to reflect the fairness. Based on these adjustments, the SAC problem is formulated as a non-linear and non-convex multi-objective optimization. Thus, we propose a heuristic algorithm called Prioritized Slice Admission Control Considering Fairness (PSACCF) to solve it. It introduces the resource efficiency of services to amend priority violations, then promotes fairness by setting the target CSARs for each service type and pushing their actual CSARs toward. Numerous simulations are carried out to compare the performance of PSACCF with two existing algorithms, termed MHPF and AHPF. Results show that our algorithm can achieve a nearly identical priority indicator to the comparisons, as well as at least a 33.6% improvement in fairness degree and a higher minimum average resource utilization.

We propose a new stellar structure of compact stars, the ``cross stars" that consist of a hadronic matter core and a quark matter crust, with an inverted structure compared to the conventional hybrid stars. This distinct stellar structure naturally arises from the quark matter to hadronic matter transition associated with the chemical potential crossing, in the context of the quark matter hypothesis that either strange or up-down quark matter is the ground state of baryonic matter at low pressure. We find that the interplay between the hadronic matter and quark matter compositions of cross stars can help to reconcile the small radii constraints indicated by the LIGO/Virgo GW170817 event, the large radii constraints set for massive compact stars by recent NICER X-ray observations, and the recent observation of the most-massive pulsar PSR J0952-0607. This leaves more space open for the equation of states of both hadronic matter and quark matter., Comment: 10 pages, 6 figures. Published version. Typo fixed

Among the various approaches for producing point distributions with blue noise spectrum, we argue for an optimization framework using Gaussian kernels. We show that with a wise selection of optimization parameters, this approach attains unprecedented quality, provably surpassing the current state of the art attained by the optimal transport (BNOT) approach. Further, we show that our algorithm scales smoothly and feasibly to high dimensions while maintaining the same quality, realizing unprecedented high-quality high-dimensional blue noise sets. Finally, we show an extension to adaptive sampling.

Previous studies have shown that building greenery systems could provide passive cooling for buildings. However, window gardens, a type of building greenery system that extends along the width of the building façade, have received little attention. In this study, a field experiment of building-integrated window gardens was conducted in Xiamen, a subtropical city in China. The passive cooling effect of window gardens during a daytime in summer was analyzed based on the measured data. The results showed that the local time-averaged surface temperature at the windowpane shaded by plant canopy was 1.1 °C lower than that was not shaded. This local temperature at the bottom wall can be 2.6 °C lower than the time-averaged indoor air temperature. The heat was transferred from the interior space to the window-garden-adjacent envelope with a time-averaged heat flux of 6.9 W·m−2. The variation in the passive cooling effect of the window garden along the vertical direction was quantified. The cooling performance of the window garden was found to be significantly affected by the irrigation system. A strategy to maximize the cooling effect by implementing a soil temperature sensor to control the smart drip irrigation system was proposed, which can be further investigated in the future. Given that window gardens can provide aesthetical and thermal benefits, there is a great potential for the practical use of window gardens for buildings in subtropical climate regions. © 2021 Elsevier Ltd

Yuncui Gan,1,* Jing Ren,2,* Jinghong Xian,3,* He Yu,1 Jing Jin,1 Dan Li,1 Weimin Li1 1Department of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, People’s Republic of China; 2Integrated Care Management Center, West China Hospital, Sichuan University, Chengdu, People’s Republic of China; 3Department of Clinical Research, West China Hospital, Sichuan University, Chengdu, People’s Republic of China*These authors contributed equally to this workCorrespondence: Weimin Li, Department of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Chengdu, 610041, Sichuan Province, People’s Republic of China, Tel/Fax +86 288 558 2944, Email weimin003@163.comBackground: Resistance inevitably develops in epidermal growth factor receptor (EGFR)-mutated advanced non-small-cell lung cancer (NSCLC) patients after treatment of EGFR tyrosine kinase inhibitors (EGFR-TKIs). The albumin-to-alkaline phosphatase ratio (AAPR), a novel index, has been reported to be associated with survival in various cancers. In this study, we explored the prognostic value of AAPR in EGFR-mutated advanced NSCLC patients treated with first-line EGFR-TKIs.Methods: The clinical and pretreatment laboratory data were retrospectively extracted from hospital medical system. The Log-rank and Kaplan–Meier analyses were adopted to detect differences in survival between groups. Univariate and multivariate Cox’s proportional hazard regression models were applied to assess the prognostic value of AAPR for progression-free survival (PFS) and overall survival (OS).Results: Totally, 598 EGFR-mutated NSCLC patients with stage IIIB-IV were enrolled into this study. The median age of all patients was 60 years, and 56.9% were women. About 97% patients had common EGFR gene mutations of deletions in exon 19 (19 del) or a point mutation in exon 21 (L858R). Using receiver operating characteristic (RO

With the recent progress in observations of astrophysical black holes, it has become more important to understand in detail the physics of strongly gravitating horizonless objects. If the objects identified in the observations are indeed horizonless and ultracompact, high curvature effects may become important, and their explorations may be intimately related to new physics beyond General Relativity (GR). In this paper, we revisit the concept of statistical thermodynamics in curved spacetime, focusing on self-gravitating compact systems without event horizons. In the literature, gravitational field equations are in general assumed a priori in the thermodynamic treatment, which may lead to difficulties for theories of modified gravity, given the more complicated structure of field equations. Here, we consider thermodynamic behavior of the matter source, instead of the physical mass, hence avoiding the explicit input of field equations in the derivation of thermodynamic laws. We show that the conventional first law of thermodynamics is retrieved once the thermodynamic volume, which is in general different from the geometric volume, is appropriately identified. For demonstrations of our approach, we consider familiar examples of self-gravitating gas in GR, where the connection to previous studies becomes clear. We also discuss 2-2-holes in quadratic gravity, a novel example of black hole mimickers that features super-Planckian curvatures in the interior. These objects exhibit universal high curvature effects in thermodynamics, which happen to be conveniently encoded in the thermodynamic volume. Interesting connections to black hole thermodynamics also emerge when the physical mass is treated as the total internal energy., Comment: 28 pages, 3 figures; Typos corrected, clarifications added, and discussions improved. Published version

Previous studies have shown that building greenery systems could provide passive cooling for buildings. However, window gardens, a type of building greenery system that extends along the width of the building façade, have received little attention. In this study, a field experiment of building-integrated window gardens was conducted in Xiamen, a subtropical city in China. The passive cooling effect of window gardens during a daytime in summer was analyzed based on the measured data. The results showed that the local time-averaged surface temperature at the windowpane shaded by plant canopy was 1.1 °C lower than that was not shaded. This local temperature at the bottom wall can be 2.6 °C lower than the time-averaged indoor air temperature. The heat was transferred from the interior space to the window-garden-adjacent envelope with a time-averaged heat flux of 6.9 W·m−2. The variation in the passive cooling effect of the window garden along the vertical direction was quantified. The cooling performance of the window garden was found to be significantly affected by the irrigation system. A strategy to maximize the cooling effect by implementing a soil temperature sensor to control the smart drip irrigation system was proposed, which can be further investigated in the future. Given that window gardens can provide aesthetical and thermal benefits, there is a great potential for the practical use of window gardens for buildings in subtropical climate regions. © 2021 Elsevier Ltd

Pulsar timing arrays (PTAs) consisting of widely distributed and well-timed millisecond pulsars can serve as a galactic interferometer to measure gravitational waves. With the same data acquired for PTAs, we propose to develop pulsar polarization arrays (PPAs), to explore astrophysics and fundamental physics. As in the case of PTAs, PPAs are best suited to reveal temporal and spatial correlations at large scales that are hard to mimic by local noise. To demonstrate the physical potential of PPAs, we consider detection of ultralight axion-like dark matter (ALDM), through cosmic birefringence induced by its Chern-Simon coupling. Because of its tiny mass, the ultralight ALDM can be generated as a Bose-Einstein condensate, characterized by a strong wavy nature. Incorporating both temporal and spatial correlations of the signal, we show that PPAs have a potential to probe the Chern-Simon coupling up to $\sim 10^{-14}-10^{-17}$GeV$^{-1}$, with a mass range $\sim 10^{-27} - 10^{-21}$eV., Comment: 8 pages, 2 figures; comments welcome

Gravitational wave echoes may provide a smoking gun signal for new physics in the immediate vicinity of black holes. As a quasiperiodic signal in time, echoes are characterized by the nearly constant time delay, and its precise measurement can help reveal a Planck-scale deviation outside of the would-be horizon. Different search methods have been developed for this quasiperiodic signal, while the searches suffer from large theoretical uncertainties of the echo waveform associated with the near-horizon physics. On the other hand, a coherent combination of a large number of pulses gives rise to a generic narrow resonance structure for the echo amplitude in frequency. The quasiperiodic resonance structure sets a complementary search target for echoes, and the time delay is inversely related to the average resonance spacing. A uniform comb has been proposed to look for the resonance structure in a rather model-independent way. In this paper, we develop a Bayesian algorithm to search for the resonance structure based on combs, where a phase-marginalized likelihood plays an essential role. The algorithm is validated with signal injections in detector noise from Advanced LIGO. With special treatments of the non-Gaussian artifacts, the noise outliers of the log Bayes factor distribution are properly removed. An echo signal not significantly below noise is detectable, and the time delay can be determined to very high precision. We perform the proposed search on real gravitational wave strain data of the first observing run of Advanced LIGO. We find no clear evidence of a comblike structure for GW150914 and GW151012., Comment: 25 pages, 10 figures, 2 tables; v2: matches version to be published in PRD, new plots in Figs.5 and 6 added to show the robustness of the algorithm in detecting echo signals of different shapes, bottom right panel in Fig.7 updated after correcting a typo (other results unchanged), appendix expanded for more on analysis of Advanced LIGO data

Pulsar timing arrays (PTAs) consisting of widely distributed and well-timed millisecond pulsars can serve as a galactic interferometer to measure gravitational waves. With the same data acquired for PTAs, we propose to develop pulsar polarization arrays (PPAs), to explore astrophysics and fundamental physics. As in the case of PTAs, PPAs are best suited to reveal temporal and spatial correlations at large scales that are hard to mimic by local noise. To demonstrate the physical potential of PPAs, we consider detection of ultralight axion-like dark matter (ALDM), through cosmic birefringence induced by its Chern-Simon coupling. Because of its tiny mass, the ultralight ALDM can be generated as a Bose-Einstein condensate, characterized by a strong wavy nature. Incorporating both temporal and spatial correlations of the signal, we show that PPAs have a potential to probe the Chern-Simon coupling up to $\sim 10^{-14}-10^{-17}$GeV$^{-1}$, with a mass range $\sim 10^{-27} - 10^{-21}$eV., Comment: 8 pages, 2 figures; comments welcome

With the recent progress in observations of astrophysical black holes, it has become more important to understand in detail the physics of strongly gravitating horizonless objects. If the objects identified in the observations are indeed horizonless and ultracompact, high curvature effects may come into play, and their explorations may be intimately related to new physics beyond General Relativity (GR). In this paper, we revisit the concept of statistical thermodynamics in curved spacetime, focusing on self-gravitating compact systems without event horizons. Differently from the previous studies in this context, we develop a generic framework with no explicit dependence on the gravitational field equations, which is then applicable to a general theory of gravity. Defining the global variables directly from the local counterparts, the conventional thermodynamics follows for a generic curved spacetime. The key step is the appropriate identification of thermodynamic volume to ensure the first law of thermodynamics, which is in general different from the geometric volume. For demonstration, we consider familiar examples of self-gravitating gas in GR, where the connection to previous studies becomes clear. We also discuss 2-2-holes in quadratic gravity, a novel example of black hole mimickers that features super-Planckian curvatures in the interior. When the physical mass is treated as the total internal energy, interesting connections to black hole thermodynamics emerge. We find universal high curvature effects in thermodynamics for these objects, and the dominant effects happen to be conveniently encoded in the thermodynamic volume., Comment: 26 pages, 3 figures

Jing Ren,1 Dongfang Han,2 Jingjun Zhang,1 Yingli Wang,3 Qiaoqiao Huang,4 Tian Tian,1 Xiaomei Li1 1School of Nursing, Health Science Center, Xi’an Jiaotong University, Xi’an City, People’s Republic of China; 2Department of Obstetrics and Gynecology, First Affiliated Hospital of Xi’an Jiaotong University, Xi’an City, People’s Republic of China; 3Department of Internal Medicine of Tuberculosis, Fourth Hospital of Inner Mongolia Autonomous Region, Hohhot City, People’s Republic of China; 4Department of Nursing, Fourth Hospital of Inner Mongolia Autonomous Region, Huhhot City, People’s Republic of ChinaCorrespondence: Xiaomei LiSchool of Nursing, Health Science Center, Xi’an Jiaotong University, No. 76 Yanta West Road, Yanta District, Xi’an City, Shanxi, 710061, People’s Republic of ChinaTel/Fax +86 29 82657017Email roselee8825@126.comPurpose: Patients affected by tuberculosis have diverse unmet supportive care needs (SCN) that may seriously affect their treatment adherence. Accurately assessing patients’ SCN is important for providing efficient patient-centred care, but few instruments are suitable for use in clinical practice. Therefore, the purpose of this study was to develop an SCN scale for patients with tuberculosis (SCN-TB) and to evaluate its psychometrical properties.Patients and Methods: Based on the SCN framework, the SCN-TB was designed via a literature review, Delphi consultation and pilot study. Then, 550 patients from four tuberculosis specialist hospitals in Shaanxi Province were enrolled by convenience sampling to further test the validity and reliability of the SCN-TB.Results: A total of 518 patients completed the survey. The final scale encompasses 25 items in five domains: physical, practical, psycho-emotional, social, and informational. The content validity for the scale was 0.93, with that for each item ranging from 0.80 to 1.00. Five factors that explained 80.38% of the variance were identified in exploratory factor analysi

Anomaly detection is a popular and vital task in various research contexts, which has been studied for several decades. To ensure the safety of people's lives and assets, video surveillance has been widely deployed in various public spaces, such as crossroads, elevators, hospitals, banks, and even in private homes. Deep learning has shown its capacity in a number of domains, ranging from acoustics, images, to natural language processing. However, it is non-trivial to devise intelligent video anomaly detection systems cause anomalies significantly differ from each other in different application scenarios. There are numerous advantages if such intelligent systems could be realised in our daily lives, such as saving human resources in a large degree, reducing financial burden on the government, and identifying the anomalous behaviours timely and accurately. Recently, many studies on extending deep learning models for solving anomaly detection problems have emerged, resulting in beneficial advances in deep video anomaly detection techniques. In this paper, we present a comprehensive review of deep learning-based methods to detect the video anomalies from a new perspective. Specifically, we summarise the opportunities and challenges of deep learning models on video anomaly detection tasks, respectively. We put forth several potential future research directions of intelligent video anomaly detection system in various application domains. Moreover, we summarise the characteristics and technical problems in current deep learning methods for video anomaly detection., Comment: 8 pages, 2 figures

Pulsar timing arrays (PTAs) consisting of widely distributed and well-timed millisecond pulsars can serve as a galactic interferometer to measure gravitational waves. With the same data acquired for PTAs, we propose to develop pulsar polarization arrays (PPAs), to explore astrophysics and fundamental physics. As in the case of PTAs, PPAs are best suited to reveal temporal and spatial correlations at large scales that are hard to mimic by local noise. To demonstrate the physical potential of PPAs, we consider detection of ultralight axion-like dark matter (ALDM), through cosmic birefringence induced by its Chern-Simon coupling. Because of its tiny mass, the ultralight ALDM can be generated as a Bose-Einstein condensate, characterized by a strong wavy nature. Incorporating both temporal and spatial correlations of the signal, we show that PPAs have a potential to probe the Chern-Simon coupling up to $\sim 10^{-14}-10^{-17}$GeV$^{-1}$, with a mass range $\sim 10^{-27} - 10^{-21}$eV., Comment: 11 pages, 4 figures; v2: matches version published in Physical Review Letters, pulsar number for the optimal PPA changed, Fig.2 updated, Supplementary Materials added

Gravitational wave echoes may provide a smoking gun signal for new physics in the immediate vicinity of black holes. As a quasiperiodic signal in time, echoes are characterized by the nearly constant time delay, and its precise measurement can help reveal a Planck-scale deviation outside of the would-be horizon. Different search methods have been developed for this quasiperiodic signal, while the searches suffer from large theoretical uncertainties of the echo waveform associated with the near-horizon physics. On the other hand, a coherent combination of a large number of pulses gives rise to a generic narrow resonance structure for the echo amplitude in frequency. The quasiperiodic resonance structure sets a complementary search target for echoes, and the time delay is inversely related to the average resonance spacing. A uniform comb has been proposed to look for the resonance structure in a rather model-independent way. In this paper, we develop a Bayesian algorithm to search for the resonance structure based on combs, where a phase-marginalized likelihood plays an essential role. The algorithm is validated with signal injections in detector noise from Advanced LIGO. With special treatments of the non-Gaussian artifacts, the noise outliers of the log Bayes factor distribution are properly removed. An echo signal not significantly below noise is detectable, and the time delay can be determined to very high precision. We perform the proposed search on real gravitational wave strain data of the first observing run of Advanced LIGO. We find no clear evidence of a comblike structure for GW150914 and GW151012., Comment: 25 pages, 10 figures, 2 tables; v2: matches version to be published in PRD, new plots in Figs.5 and 6 added to show the robustness of the algorithm in detecting echo signals of different shapes, bottom right panel in Fig.7 updated after correcting a typo (other results unchanged), appendix expanded for more on analysis of Advanced LIGO data

We propose a novel and flexible roof modeling approach that can be used for constructing planar 3D polygon roof meshes. Our method uses a graph structure to encode roof topology and enforces the roof validity by optimizing a simple but effective planarity metric we propose. This approach is significantly more efficient than using general purpose 3D modeling tools such as 3ds Max or SketchUp, and more powerful and expressive than specialized tools such as the straight skeleton. Our optimization-based formulation is also flexible and can accommodate different styles and user preferences for roof modeling. We showcase two applications. The first application is an interactive roof editing framework that can be used for roof design or roof reconstruction from aerial images. We highlight the efficiency and generality of our approach by constructing a mesh-image paired dataset consisting of 2539 roofs. Our second application is a generative model to synthesize new roof meshes from scratch. We use our novel dataset to combine machine learning and our roof optimization techniques, by using transformers and graph convolutional networks to model roof topology, and our roof optimization methods to enforce the planarity constraint.

The ACM A.M. Turing Award is commonly acknowledged as the highest distinction in the realm of computer science. Since 1960s, it has been awarded to computer scientists who made outstanding contributions. The significance of this award is far-reaching to the laureates as well as their research teams. However, unlike the Nobel Prize that has been extensively investigated, little research has been done to explore this most important award. To this end, we propose the Turing Number (TN) index to measure how far a specific scholar is to this award. Inspired by previous works on Erdos Number and Bacon Number, this index is defined as the shortest path between a given scholar to any Turing Award Laureate. Experimental results suggest that TN can reflect the closeness of collaboration between scholars and Turing Award Laureates. With the correlation analysis between TN and metrics from the bibliometric-level and network-level, we demonstrate that TN has the potential of reflecting a scholar's academic influence and reputation., Comment: 8 pages, 3 figures

The integration of Mobile Edge Computing (MEC) and Wireless Power Transfer (WPT), which is usually referred to as Wireless Powered Mobile Edge Computing (WP-MEC), has been recognized as a promising technique to enhance the lifetime and computation capacity of wireless devices (WDs). Compared to the conventional battery-powered MEC networks, WP-MEC brings new challenges to the computation scheduling problem because we have to jointly optimize the resource allocation in WPT and computation offloading. In this paper, we consider the energy minimization problem for WP-MEC networks with multiple WDs and multiple access points. We design an online algorithm by transforming the original problem into a series of deterministic optimization problems based on the Lyapunov optimization theory. To reduce the time complexity of our algorithm, the optimization problem is relaxed and decomposed into several independent subproblems. After solving each subproblem, we adjust the computed values of variables to obtain a feasible solution. Extensive simulations are conducted to validate the performance of the proposed algorithm.

Matching plays a vital role in the rational allocation of resources in many areas, ranging from market operation to people's daily lives. In economics, the term matching theory is coined for pairing two agents in a specific market to reach a stable or optimal state. In computer science, all branches of matching problems have emerged, such as the question-answer matching in information retrieval, user-item matching in a recommender system, and entity-relation matching in the knowledge graph. A preference list is the core element during a matching process, which can either be obtained directly from the agents or generated indirectly by prediction. Based on the preference list access, matching problems are divided into two categories, i.e., explicit matching and implicit matching. In this paper, we first introduce the matching theory's basic models and algorithms in explicit matching. The existing methods for coping with various matching problems in implicit matching are reviewed, such as retrieval matching, user-item matching, entity-relation matching, and image matching. Furthermore, we look into representative applications in these areas, including marriage and labor markets in explicit matching and several similarity-based matching problems in implicit matching. Finally, this survey paper concludes with a discussion of open issues and promising future directions in the field of matching., Comment: 20 pages, 5 figures

The triple-helix stereocomplex of poly(methyl methacrylate) (PMMA) is a unique example of a multistranded synthetic helix that has significant utility and promise in materials science and nanotechnology. To gain a fundamental understanding of the underlying assembly process, discrete stereoregular oligomer libraries were prepared by combining stereospecific polymerization techniques with automated flash chromatography purification. Stereocomplex assembly of these discrete building blocks enabled the identification of (1) the minimum degree of polymerization required for the stereocomplex formation and (2) the dependence of the helix crystallization mode on the length of assembling precursors. More significantly, our experiments resolved binding selectivity between helical strands with similar molecular weights. This presents new opportunities for the development of next-generation polymeric materials based on a triple-helix motif.

Quark matter with only $u$ and $d$ quarks ($ud$QM) might be the ground state of baryonic matter at large baryon number $A>A_{\rm min}$. With $A_{\rm min}\gtrsim 300$, this has no direct conflict with the stability of ordinary nuclei. An intriguing test of this scenario is to look for quantum nucleation of $ud$QM inside neutron stars due to their large baryon densities. In this paper, we study the transition rate of cold neutron stars to $ud$ quark stars ($ud$QSs) and the astrophysical implications, considering the relevant theoretical uncertainties and observational constraints. It turns out that a large portion of parameter space predicts an instantaneous transition, and so the observed neutron stars are mostly $ud$QSs. We find this possibility still viable under the recent gravitational wave and pulsar observations, although there are debates on its compatibility with some observations that involve complicated structure of quark matter. The tension could be partially relieved in the two-families scenario, where the high-mass stars ($M\gtrsim2 M_{\odot}$) are all $ud$QSs and the low-mass ones ($M\sim1.4\, M_{\odot}$) are mostly hadronic stars. In this case, the slow transition of the low-mass hadronic stars points to a very specific class of hadronic models with moderately stiff EOSs, and $ud$QM properties are also strongly constrained., Comment: 26 pages, 11 figures

Primordial black holes that survive until the present have been considered as a dark matter candidate. In this paper we argue that primordial 2-2-hole remnants provide a more promising and testable option. 2-2-holes arise in quadratic gravity as a new family of classical solutions for ultracompact matter distributions and they possess the black hole exterior without an event horizon. They may serve as the endpoint of gravitational collapse, providing a resolution for the information loss problem. Intriguing thermodynamic behavior is found for these objects when sourced by a thermal gas. A large 2-2-hole radiates with a Hawking-like temperature and exhibits an entropy-area law. At a late stage, the evaporation slows down and essentially stops as the mass asymptotically approaches a minimal value. This remnant mass is determined by a fundamental scale in quadratic gravity. We study the cosmological and astrophysical implications of having these remnants as dark matter and derive the corresponding constraints. A distinctive phenomenon associated with remnant mergers occurs, predicting fluxes of high-energy astrophysical particles due to the spectacular evaporation of the merger product. Measurements of high-energy photon and neutrino fluxes could possibly bound the remnant mass to be not far above the Planck mass. Early-universe physics, on the other hand, requires that 2-2-holes quickly evolve into the remnant state after formation, putting an upper bound on the formation mass., Comment: 33 pages, 10 figures

Primordial black holes that survive until the present have been considered as a dark matter candidate. In this paper we argue that primordial 2-2-hole remnants provide a more promising and testable option. 2-2-holes arise in quadratic gravity as a new family of classical solutions for ultracompact matter distributions and they possess the black hole exterior without an event horizon. They may serve as the endpoint of gravitational collapse, providing a resolution for the information loss problem. Intriguing thermodynamic behavior is found for these objects when sourced by a thermal gas. A large 2-2-hole radiates with a Hawking-like temperature and exhibits an entropy-area law. At a late stage, the evaporation slows down and essentially stops as the mass asymptotically approaches a minimal value. This remnant mass is determined by a fundamental scale in quadratic gravity. We study the cosmological and astrophysical implications of having these remnants as dark matter and derive the corresponding constraints. A distinctive phenomenon associated with remnant mergers occurs, predicting fluxes of high-energy astrophysical particles due to the spectacular evaporation of the merger product. Measurements of high-energy photon and neutrino fluxes could possibly bound the remnant mass to be not far above the Planck mass. Early-universe physics, on the other hand, requires that 2-2-holes quickly evolve into the remnant state after formation, putting an upper bound on the formation mass., Comment: 33 pages, 10 figures

Primordial black holes have been considered as an attractive dark matter candidate, whereas some of the predictions heavily rely on the near-horizon physics that remains to be tested experimentally. As a concrete alternative, thermal 2-2-holes closely resemble black holes without event horizons. Being a probable endpoint of gravitational collapse, they not only provide a resolution to the information loss problem, but also naturally give rise to stable remnants. Previously, we have considered primordial 2-2-hole remnants as dark matter. Due to the strong constraints from a novel phenomenon associated with remnant mergers, only small remnants with close to the Planck mass can constitute all of dark matter. In this paper, we examine the scenario that the majority of dark matter consists of particles produced by the evaporation of primordial 2-2-holes, whereas the remnant contribution is secondary. The products with light enough mass may contribute to the number of relativistic degrees of freedom in the early universe, which we also calculate. Moreover, 2-2-hole evaporation can produce particles that are responsible for the baryon asymmetry. We find that baryogenesis through direct B-violating decays or through leptogenesis can both be realized. Overall, the viable parameter space for the Planck remnant case is similar to primordial black holes with Planck remnants. Heavier remnants, on the other hand, lead to different predictions, and the viable parameter space remains large even when the remnant abundance is small., Comment: 34 pages, 8 figures; more added for discussion, matches version to be published in CPC