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As a lung cancer biomarker, exosomes were utilized for in vitro diagnosis to overcome the lack of sensitivity of conventional imaging and the potential harm caused by tissue biopsy. However, given the inherent heterogeneity of exosomes, the challenge of accurately and reliably recognizing subtle differences in the composition of exosomes from clinical samples remains significant. Herein, we report an artificial intelligence-assisted surface-enhanced Raman spectroscopy (SERS) strategy for label-free profiling of plasma exosomes for accurate diagnosis of early-stage lung cancer. Specifically, we build a deep learning model using exosome spectral data from lung cancer cell lines and normal cell lines. Then, we extracted the features of cellular exosomes by training a convolutional neural network (CNN) model on the spectral data of cellular exosomes and used them as inputs to a support vector machine (SVM) model. Eventually, the spectral features of plasma exosomes were combined to effectively distinguish adenocarcinoma in situ (AIS) from healthy controls (HC). Notably, the approach demonstrated significant performance in distinguishing AIS from HC samples, with an area under the curve (AUC) of 0.84, sensitivity of 83.3%, and specificity of 83.3%. Together, the results demonstrate the utility of exosomes as a biomarker for the early diagnosis of lung cancer and provide a new approach to prescreening techniques for lung cancer. [ABSTRACT FROM AUTHOR]

Detecting water head is crucial in groundwater utilization, and requires quick and accurate solutions. This study employs a method combining the collocation Trefftz method (CTM) and the fictitious time integration method (FTIM) for groundwater head detection and restoration. The Laplace equation is solved using CTM, and the Trefftz basis function is linearly combined to fit the exact solution while adding characteristics length for numerical stability. The FTIM solves the nonlinear algebraic equations system for water head detection. Numerical examples quantify the method's accuracy, and boundary restoration results are compared with the Picard successive approximation method, showcasing FTIM's advantages in convergence steps and precision. The solution comparison under irregular boundary conditions further verifies the proposed method's efficacy (MAE ≤ 10–15). The CTM–FTIM calculated water level boundary aligns with the actual boundary, and its noise immunity is verified using real observation well data (MAE ≤ 10–2, Itertimes ≤ 5000). The CTM–FTIM method eliminates meshing needs for quick solutions in irregular regions, accurately determining water levels in the study domain using few known boundary points, solving infinite domain groundwater head detection. [ABSTRACT FROM AUTHOR]

In recent years, the field of bionics has attracted the attention of numerous scholars. Some models combined with biological vision have achieved excellent performance in computer vision and image processing tasks. In this paper, we propose a new bio-inspired lightweight contour detection network (BLCDNet) by combining parallel processing mechanisms of bio-visual information with convolutional neural networks. The backbone network of BLCDNet simulates the parallel pathways of ganglion cell–lateral geniculate nucleus and primary visual cortex (V1) area, realizing parallel processing and step-by-step extraction of input information, effectively extracting local features and detailed features in images, and thus improving the overall performance of the model. In addition, we design a depth feature extraction module combining depth separable convolution and residual connection in the decoding network to integrate the output of the backbone network, which further improves the performance of the model. We conducted a large number of experiments on BSDS500 and NYUD datasets, and the experimental results show that the BLCDNet proposed in this paper achieves the best performance compared with traditional methods and previous biologically inspired contour detection methods. In addition, BLCDNet still outperforms some VGG-based contour detection methods without pre-training and with fewer parameters, and it is competitive among all of them. The research in this paper also provides a new idea for the combination of biological vision and convolutional neural networks. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of institutional investors' knowledge acquisition through corporate site visits (IICSV) on stock price crash risk (SPCR) for firms with and without SPCR from a new perspective. We use data from Chinese listed firms and analyze the impact of IICSV on SPCR while considering the difference in visiting objects. Our empirical results show that the impact of IICSV differs across different firms. For firms with SPCR, IICSV enhances SPCR, while for firms without SPCR, IICSV significantly reduces SPCR. We further examine the underlying mechanisms and find that the impact of IICSV is mainly based on information channels and is more pronounced for private firms, non-manufacturing firms, and firms with tradable institutional investors. We also explore the impact of IICSV under different conditions and find that over-investment reduces the governance effect. Based on our findings, we suggest that the behavior of institutional investors during IICSV should be limited and supervised to ensure suitable disclosure of visiting information and stop collusion between institutional investors and managers. We highlight the difference in institutional investors' behavior and strategy at different firms, which should be considered in future research. Additionally, the research could focus on the economic consequences of IICSV and its determinants, such as the reverse causality between IICSV and information disclosure. Our study contributes to the literature on institutional investors' impact on corporate governance and provides insights for regulators and investors. [ABSTRACT FROM AUTHOR]

This study examines the impact of Independent Institutional Investors' (IIs) Equity Trading (IIET) on crash risk from the perspective of IIET governance. Using a sample of Chinese-listed firms from 2008 to 2021, we investigate the role of IIET in inhibiting stock price crash risk and its underlying mechanisms. Our findings demonstrate that IIET can effectively reduce crash risk even after accounting for endogeneity and robustness factors. We identify the improving effect of IIET on information disclosure as a key driver, which mitigates information concealing by managers and contributes to lower crash risk. The research objectives are twofold: first, to explore the influence of IIs' Exit Threat (E.T.) implemented through IIET on stock price crash risk, and second, to examine the economic consequences and governance effect of IIET. Our study makes several contributions by analyzing data from Chinese-listed A-share firms over a 14-year period. Firstly, we extend the literature by providing empirical evidence on the impact of IIET on crash risk, offering novel insights into the relationship between IIET and stock market stability. Secondly, our research highlights the significance of IIET in the governance of listed firms, contributing to the understanding of the economic consequences of IIs' E.T. governance behavior. The findings emphasize the importance of fostering a conducive environment for IIET, establishing effective mechanisms for IIs to voice their concerns and promoting transparent information disclosure. Ultimately, our research contributes to theory development and has practical implications for enhancing the governance of IIET and ensuring the stability and efficiency of the stock market. [ABSTRACT FROM AUTHOR]

Quasi-zero stiffness (QZS) vibration isolators show great advantages in low frequency vibration isolation and often developed by compensating the negative stiffness of the bistable structure by linear spring. To overcome the limitation of the bistable property, this paper utilizes linear stiffness (linear spring) and nonlinear stiffness (repulsive magnets) respectively to compensate the general negative stiffness (rhombus structure), and realizes two types of vibration isolators, the QZS-L and QZS-N isolator. Static models are established to characterize the stiffness property and reveal two basic principles for realizing QZS. The realization of QZS in the QZS-L isolator requires large deformation, but it can be achieved under small deformation in the QZS-N system. Both the QZS-L isolator and QZS-N isolator have weak asymmetry in stiffness, which leads to bias in steady-state response. And the former has stronger asymmetry and greater bias. The adjustment method of the QZS-L and QZS-N isolators for different loads is also elaborated separately. A unified dynamic model is established and the displacement transmissibility is derived to evaluate the vibration isolation performance of the two system. The QZS-L isolator is a softening system with a left-shifted resonance peak, while the QZS-N behave as a hardening system with a right-shifted resonance peak. Both isolators have a low resonant frequency and a wide isolation frequency band. Moreover, the initial isolation frequency can become lower when adjusted for larger loads. Comprehensive comparisons and discussions of static characteristics, isolation band, and zero offset are instructive in designing low frequency vibration isolators. [ABSTRACT FROM AUTHOR]

Evidences are important proofs to support judicial trials. Automatically extracting evidences from judgement documents can be used to assess the trial quality and support "Intelligent Court". Current evidence extraction is primarily depended on sequence labelling models. Despite their success, they can only assign a label to a token, which is difficult to recognize nested evidence entities in judgment documents, where a token may belong to several evidences at the same time. In this paper, we present a novel evidence extraction architecture called ATT-MRC, in which extracting evidence entities is formalized as a question answer problem, where all evidence spans are screened out as possible correct answers. Furthermore, to address the data imbalance problem in the judgement documents, we revised the loss function and combined it with a data enhancement technique. Experimental results demonstrate that our model has better performance than related works in evidence extraction. [ABSTRACT FROM AUTHOR]

Understanding temporal coherence in particulate matter (PM) pollution across East Asian outflow regions is crucial for collaborative efforts in addressing air pollution challenges. In this study, we analyze daily PM exceedance patterns using ground-based measurements over the past two decades, focusing on the influence of El Niño-Southern Oscillation (ENSO) and Asian dust activity. ENSO-related coherent PM exceedance shows lower occurrence during El Niño compared to La Niña in spring, due to weakened continental outflows and increased precipitation. Temporal distribution of dust-related coherent PM exceedance closely mirrors springtime dust activity in source regions, indicating significant dust emission impact on outflow regions. Our findings have implications for climate variability and the assessment of multi-decade model simulations. [ABSTRACT FROM AUTHOR]

Edge detection is a key step in various image processing tasks. Edge detection based on deep learning is usually composed of encoding and decoding networks. Encoding networks are usually built based on classifiers (e.g., VGG16) while focusing on the construction of decoding networks. In this paper, an encoding–decoding network is proposed by simulating the visual pathway of the retina-lateral geniculate nucleus (LGN)- the primary visual cortex (V1)-V2-V4- the inferior temporal cortex. Bio-inspired Feature Cascade Network (BFCN) was designed to simulate the transmission modes of feedforward propagation, horizontal connection, and feedback propagation among neurons in the IT, which is conducive to enhancing the characteristic analysis ability of the decoding network. Firstly, to simulate the information processing model of feedforward propagation, a Feedforward Propagation Network is designed to fully fuse the underlying information. Secondly, to simulate the information processing model of the horizontal connection between neurons, the Inter-Layer Information module (ILI) is designed to process the interlayer information of FPNet, which is beneficial to enhancing the feature extraction ability. Finally, to simulate the feedback propagation, the Proximity Combination Network (PCNet) is designed to integrate the feature prediction of each stage and strengthen the generalization ability of the network. Experimental results show that the proposed contour detection model outperforms current similar models. [ABSTRACT FROM AUTHOR]

A more accurate and efficient millimeter-wave imaging algorithm for a monostatic system is presented in this paper. Firstly, a more precise physical model is implemented, which considers the propagation loss of both the incident wave and scattered wave. However, this physical model cannot be processed using classical mathematical methods such as spherical wave decomposition and Weyl identity. Instead, the method of stationary phase (MSP) is applied to derive the imaging formula. As a result, the proposed algorithm achieves superior imaging results for multiple targets at different ranges. Additionally, the range stacking technique is introduced to avoid time-consuming interpolation, which also contributes to improving computational efficiency comparing to the algorithms employing interpolation. The simulation results show that the proposed algorithm reduces the computation time by half. The proposed algorithm has been further verified through real data collected with our in-house developed prototype. [ABSTRACT FROM AUTHOR]

In the past few years, edge detection models based on convolutional neural networks have made remarkable progress. These models consist of the encoding network and the decoding network. The classification networks (e.g. VGG16) are generally used as the encoding network and the researchers mainly focus on the design of the decoding network. Because natural images contain many edges with different scales, how to make full use of rich and hierarchical convolutional features for edge detection is pivotal. We propose a decoding network that effectively integrates multi-level features from all convolutional layers, named multi-decoding network. Firstly, the side outputs from VGG16 are divided into shallow-, mid-, and deep-level edge features. These edge features are processed separately by multiple independent decoding networks composed of several refinement blocks. Subsequently, to improve the ability of edge fusion, we design a multi-level top-down architecture and a multi-scale attention module, which utilizes the attention mechanism to gradually refine edges. Ultimately, three types of predictions are averaged to produce the final prediction. We evaluate our method on the BSDS500, NYUDv2, and Multicue datasets. Experimental results demonstrate that our model is superior to multiple state-of-the-art edge detection models. [ABSTRACT FROM AUTHOR]

The complete regeneration of deer antlers is based on the proliferation and differentiation of stem cells. Mesenchymal stem cells (MSCs) of antlers have an important role in antler regeneration and rapid growth and development. HGF is mainly synthesized and secreted by mesenchymal cells. After binding to its receptor c-Met, which transduces signals into cells to stimulate cell proliferation and migration in various organs to promote tissue morphogenesis and angiogenesis. However, the role and mechanism of the HGF/c-Met signaling pathway on antler MSCs are still unclear. In this study, we established antler MSCs with overexpression and interference of HGF gene by lentivirus and small interference RNA, observed the effect of HGF/c-Met signal pathway on the proliferation and migration of antler MSCs, and detected the expression of downstream related signal pathway genes, to explore the mechanism of HGF/c-MET signal pathway on the proliferation and migration of antler MSCs. The results showed that the HGF/c-Met signal affects the expression of RAS, ERK and MEK genes, regulates the proliferation of pilose antler MSCs through Ras/Raf, MEK/ERK pathway, affects the expression of Gab1, Grb2, AKT and PI3K genes, and regulates the migration of MSCs of pilose antler through Gab1/Grb2 and PI3K/AKT pathway. [ABSTRACT FROM AUTHOR]

In recent years, deep learning technology has significantly improved the performance of various computer vision tasks. Convolutional neural networks for edge detection tasks are usually composed of two parts: encoding and decoding. Encoding is mainly used for feature extraction and characterization; while decoding is mainly used to effectively integrate the local, detailed features extracted from encoding into global information. The research suggests that convolutional neural networks are a technical replication of biological neural networks in a simplified sense, and the model building of convolutional neural networks relies on the intricate connections and cellular functions of biological neural networks. For visual tasks, the visual "ventral stream" neural pathway plays an essential role. And inspired by the interactive feedback mechanism between cells and tissues in the ventral stream visual pathway, this paper proposes a novel convolutional neural network model for edge detection. We use Visual Geometry Group Net to simulate the visual signal perceptron retina, the relay lateral geniculate nucleus, and the ventral stream neural pathway, and based on the visual neural information transmission mechanism, we build a lateral interactive feedback coding network. Also by using the bottom-up feedback parsing and parallel processing of feature information in the Inferior Temporal layer, the feedforward information, and feedback information are integrated in a longitudinal feedback interactive manner in the decoding network. We conducted experiments on the publicly available datasets BSDS500, NYUD, Multicue-Boundary, and Multicue- Edge, achieving Score 0.824, 0.773, 0.839, and 0.892, respectively. The results show that our method achieves good performance and is highly competitive. [ABSTRACT FROM AUTHOR]

The study of biologically inspired edge detection is one of the hot research topics in the computer vision field. Previous biologically inspired edge detection models are mainly based on X-type ganglion cells. However, according to physiological studies, Y-type and W-type ganglion cells exist in the visual system, playing essential roles in visual information processing. All three types of ganglion cells form their own independent visual channels, and all three channels working parallelly demonstrate a depth-guided stereoscopic mechanism. To model the biological visual mechanism more comprehensively, we propose a biologically inspired edge detection method based on the visual mechanism of the X-, Y-, and W-channels, namely DXYW. In the proposed model, three separate sub-models simulating the X-, Y-, and W-channels are designed to process grayscale images and disparity maps. Furthermore, a depth-guided multi-channel fusion method is introduced to integrate the visual response from different channels. Experimental results show that the multi-channel mechanism modeled in DXYW is consistent with the relevant physiological mechanisms. And DXYW achieves competitive edge detection performance that better maintains the integrity of object contours and suppresses background texture. [ABSTRACT FROM AUTHOR]

Convolutional Neural Network (CNN) has been widely used in various tasks of computer vision. For contour detection, the encoding network and decoding network structure are mainly used. The encoding network mainly uses existing networks such as VGG, and the decoding network that effectively integrates the features extracted from the encoding network has become a research hotspot in this field. To effectively integrate features, this paper proposes a Center-Far periphery and Center-Near periphery information recombination network (CFCN) based on the VGG encoding network. The decoding network is divided into three parts, Center-Far Periphery Layer (CF), Center-Near Periphery Layer (CN) and Central Base Layer (CB), the CF part aims to highlight the contour features of the main body, the CN part aims to highlight the contour details, and the CB provides benchmark information for the decoding network. Ultimately, the CF, CN, and CB are combined. On the basis of ensuring the complete contour of the main body, some detailed features are further retained. We used the F-measure for performance evaluation, and have achieved good performance on the BSDS and NYUD datasets. ODS = 0.818 on the BSDS dataset; the experimental result on the NYUD dataset is ODS = 0.764. The results show that it surpassed the human-level performance in each dataset. [ABSTRACT FROM AUTHOR]

As the basis of mid-level and high-level vision tasks, edge detection has great significance in the field of computer vision. Edge detection methods based on deep learning usually adopt the structure of the encoding-decoding network, among which the deep convolutional neural network is generally adopted in the encoding network, and the decoding network is designed by researchers. In the design of the encoding-decoding network, researchers pay more attention to the design of the decoding network and ignore the influence of the encoding network, which makes the existing edge detection methods have the problems of weak feature extraction ability and insufficient edge information extraction. To improve the existing methods, this work combines the information transmission mechanism of the retina/lateral geniculate nucleus with an edge detection network based on convolutional neural network and proposes a bionic feature enhancement network. It consists of a pre-enhanced network, an encoding network, and a decoding network. By simulating the information transfer mechanism of the retina/lateral geniculate nucleus, we designed the pre-enhanced network to enhance the ability of the encoding network to extract details and local features. Based on the hierarchical structure of the visual pathway and the integrated feature function of the inferior temporal (IT) cortex, we designed a novel feature fusion network as a decoding network. In a feature fusion network, a down-sampling enhancement module is introduced to boost the feature integration ability of the decoding network. Experimental results demonstrate that we achieve state-of-the-art performance on several available datasets. [ABSTRACT FROM AUTHOR]

Solid–liquid phase change materials (PCMs) are a kind of important heat energy storage materials that can store/release great amounts of latent heat at a specific temperature or within a narrow temperature range and thus can be applied in a lot of fields related to heat energy storage or thermal management. However, their practical applications are still limited due to formidable challenges such as the risk of leakage, easy phase separation and low thermal conductivity, etc. Silica possesses the merits of cheap, high chemical and physical stability, flame retardancy and relatively high thermal conductivity. It can be applied as both shell material and supporting materials to obtain form-stable PCMs and thus address the aforementioned challenges. In this review, the recent progresses of silica-based form-stable PCMs were summarized. We introduced the main methods for the preparation of the silica-confined composite form-stable PCMs at first. Then, the physical and chemical properties of the reported silica-confined composite form-stable PCMs were summarized and discussed. Finally, some emerging research topics and challenges on silica-based composite form-stable PCMs are proposed. [ABSTRACT FROM AUTHOR]

Dinitrogen pentoxide (N2O5) plays an important role in nighttime chemistry. A field campaign was conducted to measure N2O5 by cavity ring-down spectroscopy method from November 13 to December 3, 2016, in an urban site in Beijing. During the campaign, there were only 4 days that N2O5 concentrations were above the detection limit due to high NO emissions near the ground. The average N2O5 concentration in these 4 days was 23.4 ± 25.9 pptv. The calculated NO3 production rate varied between 0.03 and 6.26 ppbv/h, with a mean value of 0.94 ± 0.83 ppbv/h, and the average N2O5 lifetime was 2.5 ± 2.5 min, indicating the N2O5 chemistry in urban Beijing during winter time was active. The different loss pathways of N2O5 were discussed. The results show that the loss of N2O5 in winter urban area mainly attributed to the direct heterogeneous uptake reaction of N2O5, and indirect loss of NO3 reaction with NO, which contributed 28–89.6% and 9.8–65% to the overall N2O5 loss, respectively. Indirect loss reaction of NO3 with VOC was of lesser importance. Biogenic VOCs were the dominant NO3 reaction partners, and alkenes along with aromatics contributed less to NO3 reactivity. [ABSTRACT FROM AUTHOR]

Biological vision mechanism plays a very important role in detecting object contour information, so the research of bio-inspired contour detection has attracted widespread attention. In the visual physiological mechanism of contour detection, complex cells in the primary visual cortex (V1) receive the target edges output by simple cells, and subsequently aggregate and integrate the edges into contours. Inspired by the receptive field properties of complex cells in the V1 area, we design a contour detection network with an encoder-decoder structure, called the clustered suppression network. In the encoding network, we propose a feature aggregation encoding framework inspired by the clustered distribution properties of complex cells. At the same time, based on the inhibition mechanism properties of the non-classical receptive field of complex cells and the response properties to motion edges, we propose a suppression module and a spatial motion detection module, which are integrated into the encoding network. In the decoding network, we propose a highly aggregated decoding network inspired by the horizontal connection properties of complex cells. Choosing the BSDS500 natural scene dataset as the experimental object, the F-score is selected as the evaluation index. The average optimal F-score on a single-scale of the proposed method is 0.802. Concurrently, the NYUD-v2 dataset and BIPED dataset are used for further verification and achieved good results. The codes are available at https://github.com/smallsunq/CSNet-Contour-detection. [ABSTRACT FROM AUTHOR]

The human visual system has efficient architecture for information reception and integration for effectively performing visual tasks like detecting contours. Physiological evidence has shown that most neuronal responses in the classical receptive field (CRF) of the primary visual cortex are modulated, generally suppressed by the non-CRF surround. These center-surround interactions are thought to inhibit or facilitate responses to edges according to other similar edges in the surroundings, which is useful for suppressing textures and enhancing contours. A biologically motivated model with subfield-based inhibition is proposed in this paper to improve the performance of perceptually salient contour detection relative to the existing single-neuron based inhibition model. A novel subfield based inhibition framework is presented, where the inhibition terms are combined with center-surround and surround-surround differences using multiple cues, including orientation based energy distribution and directional saliency within regions. Extensive experimental evaluation demonstrates that the proposed method outperforms most of competing methods, especially biological motivated ones. [ABSTRACT FROM AUTHOR]

Particulate lead (Pb) is a primary air pollutant that affects society because of its health impacts. This study investigates the source sectors of Pb associated with ambient fine particulate matter (PM2.5) over central-western Taiwan (CWT) with new constraints on the Pb-isotopic composition. We demonstrate that the contribution of coal-fired facilities is overwhelming, which is estimated to reach 35 ± 16% in the summertime and is enhanced to 57 ± 24% during the winter monsoon seasons. Moreover, fossil-fuel vehicles remain a major source of atmospheric Pb, which accounts for 12 ± 5%, despite the current absence of a leaded gasoline supply. Significant seasonal and geographical variations in the Pb-isotopic composition are revealed, which suggest that the impact of East Asian (EA) pollution outflows is important in north CWT and drastically declines toward the south. We estimate the average contribution of EA outflows as accounting for 35 ± 15% (3.6 ± 1.5 ng/m3) of the atmospheric Pb loading in CWT during the winter monsoon seasons. [ABSTRACT FROM AUTHOR]

Wind is one of the cleanest renewable energy resources. Through the "Thousand Wind Turbines Project", Taiwan is planning to increase the proportion of power generation from renewable energy and has set a target of 5.7 GW for offshore wind by 2025. The effects of future offshore wind farms (OWFs) over the Taiwan Strait on the atmospheric environment have not been evaluated. This study examined the potential effects of proposed OWFs on the atmospheric environment if the OWFs had existed during Tropical Storm Haitang (2017) by using Weather Research and Forecasting (WRF) model. A small set of ensemble simulations was conducted for studying the sensitivity of the ambient conditions in the region to the wind farm locations, the number and density of the turbines, and the initial time of simulations. Following the landfall and northward movement of Tropical Storm Haitang, a series of complex interactions between the typhoon circulation and the wind farm emerged, including small time slots of wake effect and mountain blocking effect. The combination of these rapidly changing OWFs-related effects contributed to a weak reduction in precipitation (− 1.08 mm) and hub-height wind speed (− 0.25 m s−1), as well as minimal warming near the surface (+ 0.13 °C) over southern Taiwan. [ABSTRACT FROM AUTHOR]

The time-dependent mild-slope equation (MSE) is a second-order hyperbolic equation, which is adopted to consider the irregularity of waves. For the difficulty of directly solving the partial derivative terms and the second-order time derivative term, a novel mesh-free numerical scheme, based on the generalized finite difference method (GFDM) and the Houbolt finite difference method (HFDM), is developed to promote the precision and efficiency of the solution to time-dependent MSE. Based on the local characteristics of the GFDM, as a new domain-type meshless method, the linear combinations of nearby function values can be straightforwardly and efficiently implemented to compute the partial derivative term. It is worth noting that the application of the HFDM, an unconditionally stable finite difference time marching scheme, to solve the second-order time derivative term is critical. The results obtained from four examples show that the propagation of waves can be successfully simulated by the proposed numerical scheme in complex seabed terrain. In addition, the energy conversion of waves in long-distance wave propagation can be accurately captured using fast Fourier transform (FFT) analysis, which investigates the energy conservation in wave shoaling problems. [ABSTRACT FROM AUTHOR]

We are concerned with the issue of detecting changes and their signs from a data stream. For example, when given time series of COVID-19 cases in a region, we may raise early warning signals of an epidemic by detecting signs of changes in the data. We propose a novel methodology to address this issue. The key idea is to employ a new information-theoretic notion, which we call the differential minimum description length change statistics (D-MDL), for measuring the scores of change sign. We first give a fundamental theory for D-MDL. We then demonstrate its effectiveness using synthetic datasets. We apply it to detecting early warning signals of the COVID-19 epidemic using time series of the cases for individual countries. We empirically demonstrate that D-MDL is able to raise early warning signals of events such as significant increase/decrease of cases. Remarkably, for about 64 % of the events of significant increase of cases in studied countries, our method can detect warning signals as early as nearly six days on average before the events, buying considerably long time for making responses. We further relate the warning signals to the dynamics of the basic reproduction number R0 and the timing of social distancing. The results show that our method is a promising approach to the epidemic analysis from a data science viewpoint. [ABSTRACT FROM AUTHOR]

Since the Internet is currently being utilized in initial public offerings (IPOs), there has been a fundamental change in how IPOs can be distributed. Through the Internet, firms issue shares to a wider range of smaller investors. From the perspective of online marketing, we focus on the influences of information disclosure on IPO performance and corporate governance. We analyze if a higher degree of IPO firm performance in the IPO aftermarket is related to corporate governance. We build a corporate governance index CG for IPO firms, composed of equity structure, board characteristics, management style and disclosure quality. Through empirical evidence, we confirm that the threshold of information disclosure has positively effect on IPO firms performance. In particular, IPO firms with higher CG experience significant increases in EPS and ROA in the post-marketing. The impact of corporate governance on IPO firm performance is significant in the economic boom and non-significant in the economic recession. [ABSTRACT FROM AUTHOR]

Purpose: Intracranial atherosclerosis disease (ICAD) is an essential cause of stroke. The characteristics of effective treatment include low periprocedural risk and a sustained treatment effect. Angioplasty with a conventional balloon for ICAD is safe but has a dauntingly high restenosis rate. Drug-coated balloon (DCB) angioplasty might reduce the risk of restenosis while maintaining the overall safety of the procedure. Methods: This study included symptomatic ICAD patients with more than 70% stenosis. Intermediate catheters were placed distally, and the lesions were predilated with a conventional balloon, followed by a DCB (SeQuent Please, B Braun, Melsungen, Germany). The primary endpoint was any stroke or death within 30 days or ipsilateral ischemic stroke thereafter. The secondary endpoint was arterial restenosis of more than 50% during follow-up. Results: A total of 39 sessions of DCB angioplasty were performed for 39 lesions in 35 patients between October 2015 and April 2018 in a single center. All of the DCBs could be navigated to the lesions. Major periprocedural complications were noted in two patients (5.7%, 2/35), and minor periprocedural complications were also noted in two patients (5.7%, 2/35). The average percentages of stenosis of the lesions were 76.6% ± 7% before treatment, 32.4% ± 11.2% after DCB angioplasty, and 25% ± 16% at follow-up. Stenosis over 50% was present in 3 lesions during the follow-up period (8.3%, 3/36). Conclusion: In this study, the application of DCBs to treat ICAD patients was feasible and safe. A larger scale clinical trial is warranted to further evaluate the safety and efficacy of this treatment. [ABSTRACT FROM AUTHOR]

Projection adjustment is a technique that improves the rate of convergence, as measured by the number of iterations needed to achieve a given level of performance, of the Kaczmarz algorithm (KA) for iteratively solving a system of consistent linear equations, however at the cost of requiring additional time per iteration and increased storage. This hinders the applicability of the previously published Kaczmarz algorithm with projection adjustment (KAPA) to large-scale problems. An enhancement EKAPA of KAPA that uses projection adjustment only for a small subset of the equations is proposed for significantly reducing the time and storage requirements. An analysis of the behavior of EKAPA is provided. An illustration is given to show that EKAPA using a small subset of the equations for projection adjustment can achieve a speed-up over KA similar to that of KAPA in terms of the number of iterations, but requires much less computer time and storage; hence, it is more suitable for large-scale problems. [ABSTRACT FROM AUTHOR]

This is the twelfth contribution to the Fungal Diversity Notes series on fungal taxonomy, based on materials collected from many countries which were examined and described using the methods of morphology, anatomy, and strain culture, combined with DNA sequence analyses. 110 taxa are described and illustrated, including five new genera, 92 new species, eight new combinations and other taxonomic contributions (one new sequenced species, one new host and three new records) which are accommodated in 40 families and 1 incertae sedis in Dothideomycetes. The new genera are Amyloceraceomyces, Catenuliconidia, Hansenopezia, Ionopezia and Magnopulchromyces. The new species are Amyloceraceomyces angustisporus, Amylocorticium ellipsosporum, Arthrinium sorghi, Catenuliconidia uniseptata, Clavulina sphaeropedunculata, Colletotrichum parthenocissicola, Coniothyrium triseptatum, Cortinarius indorusseus, C. paurigarhwalensis, C. sinensis, C. subsanguineus, C. xiaojinensis, Diaporthe pimpinellae, Dictyosporella guizhouensis, Diplodia torilicola, Fuscoporia marquesiana, F. semiarida, Hansenopezia decora, Helicoarctatus thailandicus, Hirsutella hongheensis, Humidicutis brunneovinacea, Lentaria gossypina, L. variabilis, Lycoperdon lahorense, L. pseudocurtisii, Magnopulchromyces scorpiophorus, Moelleriella gracilispora, Neodevriesia manglicola, Neodidymelliopsis salvia, N. urticae, Neoroussoella magnoliae, Neottiella gigaspora, Ophiosphaerella chiangraiensis, Phaeotremella yunnanensis, Podosphaera yulii, Rigidoporus juniperinus, Rhodofomitopsis pseudofeei, Russula benghalensis, Scleroramularia vermispora, Scytinopogon minisporus, Sporormurispora paulsenii, Thaxteriellopsis obliqus, Tomentella asiae-orientalis, T. atrobadia, T. atrocastanea, T. aureomarginata, T. brevis, T. brunneoflava, T. brunneogrisea, T. capitatocystidiata, T. changbaiensis, T. citrinocystidiata, T. coffeae, T. conclusa, T. cystidiata, T. dimidiata, T. duplexa, T. efibulata, T. efibulis, T. farinosa, T. flavidobadia, T. fuscocrustosa, T. fuscofarinosa, T. fuscogranulosa, T. fuscopelliculosa, T. globospora, T. gloeocystidiata, T. griseocastanea, T. griseofusca, T. griseomarginata, T. inconspicua, T. incrustata, T. interrupta, T. liaoningensis, T. longiaculeifera, T. longiechinuli, T. megaspora, T. olivacea, T. olivaceobrunnea, T. pallidobrunnea, T. pallidomarginata, T. parvispora, T. pertenuis, T. qingyuanensis, T. segregata, T. separata, T. stipitata, T. storea, Trichoderma ceratophylletum, Tyromyces minutulus, Umbelopsis heterosporus and Xylolentia reniformis. The new combinations are Antrodiella descendena, Chloridium macrocladum, Hansenopezia retrocurvata, Rhodofomitopsis monomitica, Rh. oleracea, Fuscoporia licnoides, F. scruposa and Ionopezia gerardii. A new sequenced species (Graphis supracola), one new host (Aplosporella prunicola) and three new geographical records (Golovinomyces monardae, Paradictyoarthrinium diffractum and Prosthemium betulinum), are reported. [ABSTRACT FROM AUTHOR]

The recent realistic estimate of fungal numbers which used various algorithms was between 2.2 and 3.8 million. There are nearly 100,000 accepted species of Fungi and fungus-like taxa, which is between 2.6 and 4.5% of the estimated species. Several forums such as Botanica Marina series, Fungal Diversity notes, Fungal Biodiversity Profiles, Fungal Systematics and Evolution—New and Interesting Fungi, Mycosphere notes and Fungal Planet have enhanced the introduction of new taxa and nearly 2000 species have been introduced in these publications in the last decade. The need to define a fungal species more accurately has been recognized, but there is much research needed before this can be better clarified. We address the evidence that is needed to estimate the numbers of fungi and address the various advances that have been made towards its understanding. Some genera are barely known, whereas some plant pathogens comprise numerous species complexes and numbers are steadily increasing. In this paper, we examine ten genera as case studies to establish trends in fungal description and introduce new species in each genus. The genera are the ascomycetes Colletotrichum and Pestalotiopsis (with many species or complexes), Atrocalyx, Dothiora, Lignosphaeria, Okeanomyces, Rhamphoriopsis, Thozetella, Thyrostroma (relatively poorly studied genera) and the basidiomycete genus Lepiota. We provide examples where knowledge is incomplete or lacking and suggest areas needing further research. These include (1) the need to establish what is a species, (2) the need to establish how host-specific fungi are, not in highly disturbed urban areas, but in pristine or relatively undisturbed forests, and (3) the need to establish if species in different continents, islands, countries or regions are different, or if the same fungi occur worldwide? Finally, we conclude whether we are anywhere near to flattening the curve in new species description. [ABSTRACT FROM AUTHOR]

Recent years has seen Chinese enterprises competing to broaden the scope of business through the internationalization strategy. The proliferation of the strategy is attributable to the favorable environment created by the Chinese government with the increasingly stringent requirements on corporate social responsibility. The external pressure of social responsibility has also stimulated the fulfillment of social responsibility within the enterprises. Against this backdrop, this paper constructs a mathematical model with the constraint of external social responsibility pressure and applies the model to examine the effect of the internationalization strategy of Chinese enterprises on enterprise value. The research finds that: First, the internationalization strategy enhances the enterprise value; the stakeholders will jointly promote the strategy once they are aware of its significance. Second, with the increase in the external pressure of social responsibility, the enterprises will promote enterprise value through the implementation of social responsibility. Third, the fulfillment of corporate social responsibility contributes to the proliferation of internationalization strategy and further enhances the long-term enterprise value. These modeling conclusions are validated through an empirical test. This research enriches the exploration into the internationalization strategy of enterprises in emerging markets and pioneers the study on the fulfillment of corporate social responsibility from the external angle. [ABSTRACT FROM AUTHOR]

Physiological evidence has shown that classical receptive field (CRF) responses in the primary visual cortex (V1) can be suppressed by its surrounding region, called the non-classical receptive field (nCRF). Currently, the contour detection model based on the physiological characteristics of the V1 region is mainly used to suppress texture and highlight contour information through the inhibition of nCRF features. However, the effect of eye movement on inhibition is not considered in the inhibition calculation of such models. Inspired by the fixational eye movement (FEyeM) mechanism, we propose a multi-scale contour detection model based on fixational eye movement (MsFem) and the surrounding suppression mechanism. A bank of filters was proposed to simulate the influence of FEyeMs on nCRF, and multi-scale cues were utilized to improve the fine and coarse contour extraction and texture inhibition. The experiments showed that MsFem outperformed some biologically motivated ones in retaining the small-scale target contour information and suppressing the large-scale background textures. [ABSTRACT FROM AUTHOR]

The displacement at various measurement points is a critical indicator that can intuitively reflect the operational properties of a dam. It is important to analyse displacement monitoring data in a timely manner and make reliable predictions of dam safety. This paper proposes a GPR-based model for dam displacement forecasting. The input variables of the monitoring model consider hydraulic factors, thermal factors and irreversible factors, and the output variables are the observed displacements of the dam. An example analysis based on the proposed method is performed on a prototype gravity dam, and the performance of different simple/combined covariance functions is investigated to obtain the optimal choice. Compared to multiple linear regression, radial basis function network (RBFN) and support vector machine (SVM) methods, the results indicate that the GPR-based model with a combined covariance function significantly improves the prediction accuracy. The proposed model can effectively overcome the over-learning and poor robustness issues of approaches such as RBFN and SVM. In addition, the GPR-based forecasting model has the advantages of simplicity in the training process and the capacity to provide a probabilistic output. [ABSTRACT FROM AUTHOR]

In this work, a two-layer depth-integrated smoothed particle hydrodynamics (SPH) model is applied to investigate the effects of landslide propagation on the impulsive waves generated when entering a water body. In order to deal with the open boundary in practical engineering problems, an absorbing boundary method, based on Riemann invariants which can be applied to arbitrary geometries, is implemented. In order to examine the accuracy of the proposed formulation, the model is tested against both available laboratory tests and numerical examples from the literature. Then, it is adopted to model the characteristics of the impulse waves generated by the Halaowo landslide in the Jinsha River, China. The results provide a technical basis for the emergency plan to the Halaowo landslide and benefit the disaster prevention policy, which helps mitigating future hazards in similar reservoir areas. [ABSTRACT FROM AUTHOR]

Sordariomycetes is one of the largest classes of Ascomycota that comprises a highly diverse range of fungi mainly characterized by perithecial ascomata and inoperculate unitunicate asci. Freshwater Sordariomycetes play an important role in ecosystems and some of them have the potential to produce bioactive compounds. This study documents and reviews the freshwater Sordariomycetes, which is one of the largest and important groups of fungi in aquatic habitats. Based on evidence from DNA sequence data and morphology, we introduce a new order Distoseptisporales, two new families, viz. Ceratosphaeriaceae and Triadelphiaceae, three new genera, viz. Aquafiliformis, Dematiosporium and Neospadicoides, 47 new species, viz. Acrodictys fluminicola, Aquafiliformis lignicola, Aquapteridospora fusiformis, Arthrinium aquaticum, Ascosacculus fusiformis, Atractospora aquatica, Barbatosphaeria lignicola, Ceratosphaeria aquatica, C. lignicola, Chaetosphaeria aquatica, Ch. catenulata, Ch. guttulata, Ch. submersa, Codinaea yunnanensis, Conioscypha aquatica, C. submersa, Cordana aquatica, C. lignicola, Cosmospora aquatica, Cylindrotrichum submersum, Dematiosporium aquaticum, Dictyochaeta cangshanensis, D. ellipsoidea, D. lignicola, D. submersa, Distoseptispora appendiculata, D. lignicola, D. neorostrata, D. obclavata, Hypoxylon lignicola, Lepteutypa aquatica, Myrmecridium aquaticum, Neospadicoides aquatica, N. lignicola, N. yunnanensis, Ophioceras submersum, Peroneutypa lignicola, Phaeoisaria filiformis, Pseudostanjehughesia lignicola, Rhodoveronaea aquatica, Seiridium aquaticum, Sporidesmiella aquatica, Sporidesmium lageniforme, S. lignicola, Tainosphaeria lunata, T. obclavata, Wongia aquatica, two new combinations, viz. Acrodictys aquatica, Cylindrotrichum aquaticum, and 9 new records, viz. Chaetomium globosum, Chaetosphaeria cubensis, Ch. myriocarpa, Cordana abramovii, Co. terrestris, Cuspidatispora xiphiago, Sporidesmiella hyalosperma, Stachybotrys chartarum,S. chlorohalonata. A comprehensive classification of the freshwater Sordariomycetes is presented based on updated literature. Phylogenetic inferences based on DNA sequence analyses of a combined LSU, SSU, RPB2 and TEF1α dataset comprising species of freshwater Sordariomycetes are provided. Detailed information including their habitats distribution, diversity, holotype, specimens collected and classification are provided. [ABSTRACT FROM AUTHOR]

Physiological studies have revealed that the center–surround mechanism widely exists in the primary stages of the human visual system, such as the retina, lateral geniculate nucleus (LGN), and primary visual cortex (V1). In retina ganglion cells (RGC) and the LGN, the mechanism is well known to have two types: center "on" and center "off." However, this mechanism in V1 is shown as classical receptive field (CRF) stimulation and surrounding non-CRF suppression. Although these two manifestations differ in function and appear in different areas of the visual pathway, from the perspective of computational simulation, they simply compute the differences between the center and its surrounding information. In the past decade, many bio-inspired computational models have demonstrated that the center–surround mechanism is good at extracting salient contours while suppressing textures. Based on this mechanism, we propose a method for extracting local center–surround contrast information from nature images by using a normalized difference of Gaussian (DoG) function and a sigmoid activated function. Compared with previous contour detection models (especially bio-motivated ones), the proposed method can efficiently suppress textures more quickly and accurately. More importantly, the proposed algorithm yields even better contour detection, yet the computational complexity is similar to the classical Canny operator. [ABSTRACT FROM AUTHOR]

Aims/hypothesis: Information on the associations of long-term exposure to fine particulate matter (with an aerodynamic diameter less than 2.5 μm; PM2.5) with the development of type 2 diabetes is scarce, especially for south-east Asia, where most countries are experiencing serious air pollution. This study aimed to investigate the long-term effects of exposure to ambient PM2.5 on the incidence of type 2 diabetes in a population of Taiwanese adults. Methods: A total of 147,908 participants without diabetes, at least 18 years of age, were recruited in a standard medical examination programme between 2001 and 2014. They were encouraged to take medical examinations periodically and underwent at least two measurements of fasting plasma glucose (FPG). Incident type 2 diabetes was identified as FPG ≥7 mmol/l or self-reported physician-diagnosed diabetes in the subsequent medical visits. The PM2.5 concentration at each participant's address was estimated using a satellite-based spatiotemporal model with a resolution of 1 × 1 km2. The 2 year average of PM2.5 concentrations (i.e. the year of and the year before the medical examination) was treated as an indicator of long-term exposure to ambient PM2.5 air pollution. We performed Cox regression models with time-dependent covariates to analyse the long-term effects of exposure to PM2.5 on the incidence of type 2 diabetes. A wide range of covariates were introduced in the models to control for potential effects, including age, sex, education, season, year, smoking status, alcohol drinking, physical activity, vegetable intake, fruit intake, occupational exposure, BMI, hypertension and dyslipidaemia (all were treated as time-dependent covariates except for sex). Results: Compared with the participants exposed to the first quartile of ambient PM2.5, participants exposed to the second, third and fourth quartiles of ambient PM2.5 had HRs of 1.28 (95% CI 1.18, 1.39), 1.27 (95% CI 1.17, 1.38) and 1.16 (95% CI 1.07, 1.26), respectively, for the incidence of type 2 diabetes. Participants who drank occasionally or regularly (more than once per week) or who had a lower BMI (<23 kg/m2) were more sensitive to the long-term effects of exposure to ambient PM2.5. Conclusions/interpretation: Long-term exposure to ambient PM2.5 appears to be associated with a higher risk of developing type 2 diabetes in this Asian population experiencing high levels of air pollution. [ABSTRACT FROM AUTHOR]

Li metal has the highest specific capacity (3860 mA h g−1) and the lowest electrochemical potential (− 3.04 V vs. SHE) of available metal anodes. Together with the high specific capacity of sulfur cathodes (1670 mA h g−1), Li metal-S batteries are a promising candidate to achieve high energy density batteries for electric vehicles and future industry. However, Li metal anodes suffer from corrosive reactions with electrolytes, a theoretically infinite volume change, and the growth of dendrites during electrochemical cycling. To realize the practical application of Li metal-S batteries, protective layers or artificial solid-electrolyte interphase (ASEI) layers have been applied to the surface of Li metal. These ASEI layers demonstrate capabilities to suppress the growth of dendrites and mitigate side reactions, which enhance the performance and safety of Li metal anodes in liquid-electrolyte systems, though there are still limitations and challenges. The development of solid-state electrolytes as artificial SEIs provides a promising route to suppress the issues of dendrite formation and the polysulfide "shuttle effect" in Li-S chemistry; however, the improvement in the interfacial compatibility and stability between the Li metal and the solid-state electrolyte is crucially needed. In this review, we summarize different types of ASEI layers used to protect Li metal, especially in Li-S batteries, with both liquid- and solid-electrolyte systems. We also briefly introduce the concept of anode protection of Mg metal and its application in Mg-S batteries. Perspectives regarding the further development and improvement of ASEI layers for Li metal and Mg metal are discussed. [ABSTRACT FROM AUTHOR]

This study deals with an extensive taxonomic reevaluation focusing on phylogenetic relationships and morphological characterization of Tubeufiales, especially those helicosporous hyphomycetes which are difficult to identify. Based on evidence from DNA sequence data and morphology, we introduce 13 new genera in the family Tubeufiaceae, viz. Acanthotubeufia, Dematiohelicoma, Dematiohelicomyces, Dematiohelicosporum, Dematiotubeufia, Helicoarctatus, Helicohyalinum, Helicotruncatum, Neochlamydotubeufia, Neohelicoma, Pleurohelicosporium, Pseudohelicomyces and Pseudohelicoon; transfer Chaetosphaerulina from Dothideomycetes genera incertae sedis, and Artocarpomyces and Helicodochium from Ascomycetes genera incertae sedis into Tubeufiaceae; introduce 52 new species, viz. Berkleasmium fusiforme, B. longisporum, Chlamydotubeufia cylindrica, Dematiohelicosporum guttulatum, Helicoarctatus aquaticus, Helicodochium aquaticum, Helicohyalinum infundibulum, Helicoma aquaticum, H. brunneisporum, H. cocois, H. rufum, H. fusiforme, H. longisporum, H. multiseptatum, H. rubriappendiculatum, H. septoconstrictum, H. tectonae, Helicomyces hyalosporus, Helicosporium aquaticum, H. flavisporum, H. setiferum, H. vesicarium, H. viridiflavum, Neochlamydotubeufia fusiformis, Neohelicomyces hyalosporus, Neohelicosporium acrogenisporum, N. astrictum, N. ellipsoideum, N. irregulare, N. krabiense, N. laxisporum, N. ovoideum, Pleurohelicosporium parvisporum, Pseudohelicomyces aquaticus, P. hyalosporus, Tubeufia abundata, T. bambusicola, T. brevis, T. brunnea, T. chlamydospora, T. dictyospora, T. eccentrica, T. fangchengensis, T. hechiensis, T. inaequalis, T. krabiensis, T. rubra, T. sessilis, T. sympodihylospora, T. sympodilaxispora, T. taiwanensis and T. tratensis; provide 43 new combinations, viz. Acanthohelicospora guianensis, Acanthotubeufia filiforme, Berkleasmium aquatica, B. guangxiense, B. latisporum, B. thailandicum, Dematiohelicoma perelegans, D. pulchrum, Dematiohelicomyces helicosporus, Dematiotubeufia chiangraiensis, Helicohyalinum aquaticum, Helicoma elinorae, H. gigasporum, H. hongkongense, H. linderi, H. nematosporum, H. pannosum, H. serpentinum, Helicomyces chiayiensis, Helicotruncatum palmigenum, Neochlamydotubeufia khunkornensis, Neohelicoma fagacearum, Neohelicomyces pallidus, Neohelicosporium abuense, N. aurantiellum, N. griseum, N. morganii, N. myrtacearum, N. nizamabadense, N. sympodiophorum, N. taiwanense, N. vesiculiferum, Pseudohelicomyces indicus, P. paludosus, P. talbotii, Pseudohelicoon gigantisporum, P. subglobosum, Tubeufia dentophora, T. geniculata, T. lilliputea, T. machaerinae, T. sympodiophora and T. xylophila; introduce 16 new records, viz. Dictyospora thailandica, Helicomyces colligatus, H. torquatus, Neohelicosporium guangxiense, N. hyalosporum, N. parvisporum, Thaxteriellopsis lignicola, Tubeufia aquatica, T. chiangmaiensis, T. cylindrothecia, T. filiformis, T. guangxiensis, T. laxispora, T. parvispora, T. roseohelicospora and T. tectonae. The taxonomy of Helicoma, Helicomyces and Helicosporium is revisited based on phylogenetic analyses and morphological evidence. Neorhamphoria is transferred to Bezerromycetaceae. Three species are excluded from the genus Chlamydotubeufia, twelve species from Helicoma, four species from Helicomyces, 25 species from Helicosporium, six species from Neoacanthostigma and one species from Tubeufia. A multi-gene phylogenetic tree based on maximum likelihood and Bayesian analyses of ITS, LSU, RPB2 and TEF1α sequence data of species of Tubeufiales is provided. Detailed descriptions and illustrations are provided, as well as the morphological comparison with similar taxa are explored. The checklist of accepted Tubeufiales species and re-organised Tubeufiales species are provided. [ABSTRACT FROM AUTHOR]

A new compact design of CPW-fed wideband (WB) spiral-shaped slot antenna is proposed. The proposed antenna has a compact size with overall dimensions 37-33 mm and is fabricated on FR4 substrate with dielectric constant ɛr = 4.4 and thickness h = 1.6 mm. With the different length of the spiral-shaped slots, simulated and experimental results of the antenna are suitable for WB operations. The-10 dB bandwidth of the WB antenna from measurement is approximately 115.2% (2.36-8.53 GHz). The proposed antenna provides nearly omni-directional radiation characteristics. The new antenna configuration operates in several different bands: 2.4, 3.5, 5.2, 5.5, and 5.8 GHz covering 2.4/5.2/5.8 GHz WLAN bands and 2.5/3.5/5.5 GHz WiMAX bands. The results for S11, far-field H- and E-plane radiation patterns and gain of the proposed antennas are presented and discussed. The agreement between measured results and full-wave simulation validates the feasible configuration of the proposed antennas. [ABSTRACT FROM AUTHOR]

This study examined the climate variability of heat wave (HW) according to air temperature and relative humidity to determine trends of variation and stress threshold in three major cities of Taiwan, Taipei (TP), Taichung (TC), and Kaohsiung (KH), in the past four decades (1971-2010). According to the data availability, the wet-bulb globe temperature (WBGT) heat stress for the three studied cities was also calculated for the past (2003-2012) and simulated under the future warming scenario for the end of this century (2075-2099) using ECHAM5/MPIOM-WRF (ECW) dynamic downscaling 5-km resolution. Analysis showed that past decade (2001-2010) saw increase not only in the number of HW days in all three cities but also in the duration of each HW event in TP and KH. Simulation results revealed that ECW well captures the characteristics of data distribution in these three cities during 2003-2012. Under the A1B projection, ECW yielded higher WBGT in all three cities for 2075-2099. The WBGT in TP indicated that the heat stress for 50% of the days in July and August by 2075-2099 will be at danger level (WBGT ≥ 31 °C). Even the median of WBGT in TC and KH (30.91 and 30.88 °C, respectively) are close to 31 °C. Hence, the heat stress in all three cities will either exceed or approach the danger level by the end of this century. Such projection under the global warming trend would necessitate adaptation and mitigation, and the huge impact of dangerous heat stress on public health merits urgent attention for Taiwan. [ABSTRACT FROM AUTHOR]

Extracellular nucleotides can modulate the immunological response by activating purinergic receptors (P2Rs) on the cell surface of macrophages, dendritic, and other immune cells. In particular, the activation of P2X7R can induce release of cytokines and cell death as well as the uptake of large molecules through the cell membrane by a mechanism still poorly understood. Polyoxotungstate-1 (POM-1) has been proposed as a potent inhibitor of ecto-nucleotidases, enzymes that hydrolyze extracellular nucleotides, regulating the activity of P2Rs. However, the potential impact of POM-1 on P2Rs has not been evaluated. Here, we used fluorescent dye uptake, cytoplasmic free Ca concentration measurement, patch-clamp recordings, scanning electron microscopy, and quantification of inflammatory mediators to investigate the effects of POM-1 on P2Rs of murine macrophages. We observed that POM-1 blocks the P2YR-dependent cytoplasmic Ca increase and has partial effects on the cytoplasmic Ca, increasing dependence on P2XRs. POM-1 can inhibit the events related with ATP-dependent inflammasome activation, anionic dye uptake, and also the opening of large conductance channels, which are associated with P2X7R-dependent pannexin-1 activation. On the other hand, this compound has no effects on cationic fluorescent dye uptake, apoptosis, and bleb formation, also dependent on P2X7R. Moreover, POM-1 can be considered an anti-inflammatory compound, because it prevents TNF-α and nitric oxide release from LPS-treated macrophages. [ABSTRACT FROM AUTHOR]

This is the sixth in a series of papers where we bring collaborating mycologists together to produce a set of notes of several taxa of fungi. In this study we introduce a new family Fuscostagonosporaceae in Dothideomycetes. We also introduce the new ascomycete genera Acericola, Castellaniomyces, Dictyosporina and Longitudinalis and new species Acericola italica, Alternariaster trigonosporus, Amarenomyces dactylidis, Angustimassarina coryli, Astrocystis bambusicola, Castellaniomyces rosae, Chaetothyrina artocarpi, Chlamydotubeufia krabiensis, Colletotrichum lauri, Collodiscula chiangraiensis, Curvularia palmicola, Cytospora mali- sylvestris, Dictyocheirospora cheirospora, Dictyosporina ferruginea, Dothiora coronillae, Dothiora spartii, Dyfrolomyces phetchaburiensis, Epicoccum cedri, Epicoccum pruni, Fasciatispora calami, Fuscostagonospora cytisi, Grandibotrys hyalinus, Hermatomyces nabanheensis, Hongkongmyces thailandica, Hysterium rhizophorae, Jahnula guttulaspora, Kirschsteiniothelia rostrata, Koorchalomella salmonispora, Longitudinalis nabanheensis, Lophium zalerioides, Magnibotryascoma mali, Meliola clerodendri- infortunati, Microthyrium chinense, Neodidymelliopsis moricola, Neophaeocryptopus spartii, Nigrograna thymi, Ophiocordyceps cossidarum, Ophiocordyceps issidarum, Ophiosimulans plantaginis, Otidea pruinosa, Otidea stipitata, Paucispora kunmingense, Phaeoisaria microspora, Pleurothecium floriforme, Poaceascoma halophila, Periconia aquatica, Periconia submersa, Phaeosphaeria acaciae, Phaeopoacea muriformis, Pseudopithomyces kunmingnensis, Ramgea ozimecii, Sardiniella celtidis, Seimatosporium italicum, Setoseptoria scirpi, Torula gaodangensis and Vamsapriya breviconidiophora. We also provide an amended account of Rhytidhysteron to include apothecial ascomata and a J+ hymenium. The type species of Ascotrichella hawksworthii ( Xylariales genera incertae sedis), Biciliopsis leptogiicola ( Sordariomycetes genera incertae sedis), Brooksia tropicalis ( Micropeltidaceae), Bryochiton monascus ( Teratosphaeriaceae), Bryomyces scapaniae ( Pseudoperisporiaceae), Buelliella minimula ( Dothideomycetes genera incertae sedis), Carinispora nypae ( Pseudoastrosphaeriellaceae), Cocciscia hammeri ( Verrucariaceae), Endoxylina astroidea ( Diatrypaceae), Exserohilum turcicum ( Pleosporaceae), Immotthia hypoxylon ( Roussoellaceae), Licopolia franciscana ( Vizellaceae), Murispora rubicunda ( Amniculicolaceae) and Doratospora guianensis (synonymized under Rizalia guianensis, Trichosphaeriaceae) were re-examined and descriptions, illustrations and discussion on their familial placement are given based on phylogeny and morphological data. New host records or new country reports are provided for Chlamydotubeufia huaikangplaensis, Colletotrichum fioriniae, Diaporthe subclavata, Diatrypella vulgaris, Immersidiscosia eucalypti, Leptoxyphium glochidion, Stemphylium vesicarium, Tetraploa yakushimensis and Xepicula leucotricha. Diaporthe baccae is synonymized under Diaporthe rhusicola. A reference specimen is provided for Periconia minutissima. Updated phylogenetic trees are provided for most families and genera. We introduce the new basidiomycete species Agaricus purpurlesquameus, Agaricus rufusfibrillosus, Lactifluus holophyllus, Lactifluus luteolamellatus, Lactifluus pseudohygrophoroides, Russula benwooii, Russula hypofragilis, Russula obscurozelleri, Russula parapallens, Russula phoenicea, Russula pseudopelargonia, Russula pseudotsugarum, Russula rhodocephala, Russula salishensis, Steccherinum amapaense, Tephrocybella constrictospora, Tyromyces amazonicus and Tyromyces angulatus and provide updated trees to the genera. We also introduce Mortierella formicae in Mortierellales, Mucoromycota and provide an updated phylogenetic tree. [ABSTRACT FROM AUTHOR]

End-to-End delay is an important performance metric to evaluate the performance of many Internet multimedia applications such as, Voice Over IP (VOIP), online gaming, cloud computing etc. Especially, the delays at some bottleneck-links of a path account for a large proportion of the End-to-End delay. To accurately identify the delays at bottleneck-links is a fundamental approach to study the delay feature of Internet, and is beneficial to the design of some efficient distributed algorithms. In this paper, we utilize real measured probing data to conduct a statistical analysis of the relationship between one-way delay and bottleneck-delay, and demonstrate that bottleneck-delay appears in 70 % of the paths in Internet. In order to further study the features of bottleneck-delay, we propose an IP united mapping scheme which combines the IP centralized mapping with the IP geographic mapping. Experiment results show that two ends of a bottleneck-link are usually located in the same country, and the links with a large number of entrances (in-degrees) and few number of exits (out-degrees) or the average shallower links are prone to leading to bottleneck-delays. Based on the structural properties of the bottleneck-links, we also give a deep discussion about the factors of bottleneck-delays at last, which demonstrates queuing delay is a key factor of bottleneck-delay. [ABSTRACT FROM AUTHOR]

Information flow among auditory and language processing-related regions implicated in the pathophysiology of auditory verbal hallucinations (AVHs) in schizophrenia (SZ) remains unclear. In this study, we used stochastic dynamic causal modeling (sDCM) to quantify connections among the left dorsolateral prefrontal cortex (inner speech monitoring), auditory cortex (auditory processing), hippocampus (memory retrieval), thalamus (information filtering), and Broca's area (language production) in 17 first-episode drug-naïve SZ patients with AVHs, 15 without AVHs, and 19 healthy controls using resting-state functional magnetic resonance imaging. Finally, we performed receiver operating characteristic (ROC) analysis and correlation analysis between image measures and symptoms. sDCM revealed an increased sensitivity of auditory cortex to its thalamic afferents and a decrease in hippocampal sensitivity to auditory inputs in SZ patients with AVHs. The area under the ROC curve showed the diagnostic value of these two connections to distinguish SZ patients with AVHs from those without AVHs. Furthermore, we found a positive correlation between the strength of the connectivity from Broca's area to the auditory cortex and the severity of AVHs. These findings demonstrate, for the first time, augmented AVH-specific excitatory afferents from the thalamus to the auditory cortex in SZ patients, resulting in auditory perception without external auditory stimuli. Our results provide insights into the neural mechanisms underlying AVHs in SZ. This thalamic-auditory cortical-hippocampal dysconnectivity may also serve as a diagnostic biomarker of AVHs in SZ and a therapeutic target based on direct in vivo evidence. [ABSTRACT FROM AUTHOR]

A new monotypic Beltrania-like genus, Subsessila, with its type species S. turbinata, is described, illustrated and compared with similar genera. The new genus is introduced in the family Beltraniaceae based on phylogenetic analysis and morphological characters. Subsessila can be easily distinguished from other Beltrania-like genera by dark setae arising from radially lobed basal cells, mostly lacking macronematous conidiophores. Conidiogenous cells are ampulliform or doliiform and produce turbinate to clavate conidia with rostrate proximal end and rounded distal end. Evidence for establishment of the new genus is provided based on morphological comparison and DNA sequence data analyses. [ABSTRACT FROM AUTHOR]

The genus Fusariella, typified by F. atrovirens, is characterised by semi- to macronematous, mononematous conidiophores, with cylindrical, subulate or lageniform phialidic conidiogenous cells that produce catenate, septate, curved to straight, subhyaline to brown conidia. During a survey of hyaline-spored hyphomycetes from karst areas in Thailand, we collected a new species of Fusariella with curved conidia and introduce it in this paper as Fusariella curvata sp. nov. In addition, all hitherto described species of Fusariella are reviewed. The result of phylogenetic analyses, based on combined SSU, LSU, TEF and RPB2 sequence data, indicates that the genus belongs in the family Bionectriaceae (Hypocreales, Sordariomycetes). [ABSTRACT FROM AUTHOR]

In this paper, we propose a new algorithm in reversible data hiding, with the characteristics of ease of implementation, based on the alteration of difference values relating to original image. Three major categories can make reversible data hiding possible, one is to modify the histogram of original images, the second is to alter the difference between neighboring pixels, and the third is to apply prediction method to modify the difference between original and predicted pixels. By integrating the advantages from the these categories, and by extending the flexibility to acquire the difference values for data hiding, we employ the block-based, multi-round prediction to look for enhanced performances. Simulations with conventional and medical images have presented the superiority with our algorithm over existing ones in literature. With our algorithm, enhanced amount of capacity, in addition to the better image quality, and most important of all, the reversibility of algorithm, can be reached. It is also famous for its ease of implementation for medical applications in hospitals. [ABSTRACT FROM AUTHOR]