How to enhance the dynamic range of excitatory-inhibitory excitable networks

We investigate the collective dynamics of excitatory-inhibitory excitable networks in response to external stimuli. How to enhance dynamic range, which represents the ability of networks to encode external stimuli, is crucial to many applications. We regard the system as a two-layer network (E-Layer and I-Layer) and explore the criticality and dynamic range on diverse networks. Interestingly, we find that phase transition occurs when the dominant eigenvalue of E-layer's weighted adjacency matrix is exactly one, which is only determined by the topology of E-Layer. Meanwhile, it is shown that dynamic range is maximized at critical state. Based on theoretical analysis, we propose an inhibitory factor for each excitatory node. We suggest that if nodes with high inhibitory factors are cut out from I-Layer, dynamic range could be further enhanced. However, because of the sparseness of networks and passive function of inhibitory nodes, the improvement is relatively small compared tooriginal dynamic range. Even so, this provides a strategy to enhance dynamic range.Comment: 7 pages, 9 figure

The development of a calling by hospitality employees during an extreme event

This study explores the development of a calling by hospitality employees during extreme events. Despite the importance of a calling in the hospitality industry, the process of its cultivation has not been explored. Using event system theory and research on sensegiving and sensemaking, we explore the evolution of employee perceptions of an extreme event and the impact of this evolution on the development of a calling. Our interviews with hotel employees who worked during a lockdown due to COVID-19 demonstrate that extreme events can stimulate and develop a calling among employees, particularly when their perceptions of the event converge. This study contributes to the literature on hospitality and organizational behavior by revealing that an extreme event can shape, transmit, and communalize a calling among employees.publishedVersio

ATFNet: Adaptive Time-Frequency Ensembled Network for Long-term Time Series Forecasting

The intricate nature of time series data analysis benefits greatly from the distinct advantages offered by time and frequency domain representations. While the time domain is superior in representing local dependencies, particularly in non-periodic series, the frequency domain excels in capturing global dependencies, making it ideal for series with evident periodic patterns. To capitalize on both of these strengths, we propose ATFNet, an innovative framework that combines a time domain module and a frequency domain module to concurrently capture local and global dependencies in time series data. Specifically, we introduce Dominant Harmonic Series Energy Weighting, a novel mechanism for dynamically adjusting the weights between the two modules based on the periodicity of the input time series. In the frequency domain module, we enhance the traditional Discrete Fourier Transform (DFT) with our Extended DFT, designed to address the challenge of discrete frequency misalignment. Additionally, our Complex-valued Spectrum Attention mechanism offers a novel approach to discern the intricate relationships between different frequency combinations. Extensive experiments across multiple real-world datasets demonstrate that our ATFNet framework outperforms current state-of-the-art methods in long-term time series forecasting

A hybrid Forecasting Model of Discharges based on Support Vector Machine

AbstractForecasting is one of the important research topics in the analysis of the hydrological time series. In order to improve the prediction accuracy for complex flood process, this paper presents a hybrid prediction method, which is based on combining multiple support vector machine (SVM) models. According to different discharge levels, multiple sub-models are established respectively, from which the final result is integrated. For each sub-model, the input is optimally determined by elaborate correlation analysis. Experimental results on the discharge prediction of Wangjiaba station on Huaihe River of China show that the hybrid model can significantly improve the prediction accuracy, compared to the single model without partitioning of the discharge

Evidence for cross-species transmission of human coronavirus OC43 through bioinformatics and modeling infections in porcine intestinal organoids

Cross-species transmission of coronaviruses has been continuously posing a major challenge to public health. Pigs, as the major animal reservoirs for many zoonotic viruses, frequently mediate viral transmission to humans. This study comprehensively mapped the relationship between human and porcine coronaviruses through in-depth bioinformatics analysis. We found that human coronavirus OC43 and porcine coronavirus PHEV share a close phylogenetic relationship, evidenced by high genomic homology, similar codon usage patterns and comparable tertiary structure in spike proteins. Inoculation of infectious OC43 viruses in organoids derived from porcine small and large intestine demonstrated that porcine intestinal organoids (pIOs) are highly susceptible to human coronavirus OC43 infection and support infectious virus production. Using transmission electron microscopy, we visualized OC43 viral particles in both intracellular and extracellular compartments, and observed abnormalities of multiple organelles in infected organoid cells. Robust OC43 infections in pIOs result in a significant reduction of organoids viability and widespread cell death. This study bears essential implications for better understanding the evolutionary origin of human coronavirus OC43, and provides a proof-of-concept for using pIOs as a model to investigate cross-species transmission of human coronavirus.</p

Laminar burning characteristics of 2-methylfuran and isooctane blend fuels

Abstract2-Methylfuran (MF) has become very attractive due to the recent breakthrough in its production method using the process of dehydration and hydrogenolysis of fructose. MF–gasoline blended fuel has been considered as a potential choice of alternative fuel pathway for spark ignition (SI) engines, as have other biofuel blends. Isooctane is used to represent gasoline in fundamental studies of gasoline blended fuels, however, little is known about the laminar burning characteristics of MF–isooctane blended fuels. In this study, high-speed schlieren photography is used to investigate the laminar burning characteristics of gaseous MF–isooctane at varying temperatures and equivalence ratios with an initial pressure of 0.1MPa in a constant-volume vessel. The outwardly spherical flame method is used to determine the stretched flame speeds. The un-stretched flame speeds, Markstein lengths, Markstein number, laminar burning velocities and laminar burning flux of MF20 (20% MF and 80% isooctane) and MF50 (50% MF and 50% isooctane) under different equivalence ratios and temperatures are then deduced and compared to MF and isooctane. The results show that the un-stretched flame speeds and laminar burning velocities of MF20 and MF50 are between those of MF and isooctane under all conditions. The peak un-stretched flame speeds of the blends occur in an equivalence ratio range of 1.1–1.2 at all temperatures, closer to the case of MF at higher temperatures. Both blended fuels have Markstein lengths closer to isooctane at an equivalence ratio lower than 1.2 at all temperatures. The burning velocities of MF50 are very close to the average values for MF and isooctane, particularly at 393K. MF in the blended fuel presents larger effects on burning velocities at higher temperatures

KP177R-based visual assay integrating RPA and CRISPR/Cas12a for the detection of African swine fever virus

IntroductionEarly detection of the virus in the environment or in infected pigs is a critical step to stop African swine fever virus (ASFV) transmission. The p22 protein encoded by ASFV KP177R gene has been shown to have no effect on viral replication and virulence and can serve as a molecular marker for distinguishing field virus strains from future candidate KP177R deletion vaccine strains.MethodsThis study established an ASFV detection assay specific for the highly conserved ASFV KP177R gene based on recombinase polymerase amplification (RPA) and the CRISPR/Cas12 reaction system. The KP177R gene served as the initial template for the RPA reaction to generate amplicons, which were recognized by guide RNA to activate the trans-cleavage activity of Cas12a protein, thereby leading to non-specific cleavage of single-stranded DNA as well as corresponding color reaction. The viral detection in this assay could be determined by visualizing the results of fluorescence or lateral flow dipstick (LFD) biotin blotting for color development, and was respectively referred to as fluorescein-labeled RPA-CRISPR/Cas12a and biotin-labeled LFD RPA-CRISPR/Cas12a. The clinical samples were simultaneously subjected to the aforementioned assay, while real-time quantitative PCR (RT-qPCR) was employed as a control for determining the diagnostic concordance rate between both assays.ResultsThe results showed that fluorescein- and biotin-labeled LFD KP177R RPA-CRISPR/Cas12a assays specifically detected ASFV, did not cross-react with other swine pathogens including PCV2, PEDV, PDCoV, and PRV. The detection assay established in this study had a limit of detection (LOD) of 6.8 copies/μL, and both assays were completed in 30 min. The KP177R RPA-CRISPR/Cas12a assay demonstrated a diagnostic coincidence rate of 100% and a kappa value of 1.000 (p &lt; 0.001), with six out of ten clinical samples testing positive for ASFV using both KP177R RPA-CRISPR/Cas12a and RT-qPCR, while four samples tested negative in both assays.DiscussionThe rapid, sensitive and visual detection assay for ASFV developed in this study is suitable for field application in swine farms, particularly for future differentiation of field virus strains from candidate KP177R gene-deleted ASFV vaccines, which may be a valuable screening tool for ASF eradication

Structural and Functional Diversity of Acidic Scorpion Potassium Channel Toxins

Background: Although the basic scorpion K + channel toxins (KTxs) are well-known pharmacological tools and potential drug candidates, characterization the acidic KTxs still has the great significance for their potential selectivity towards different K + channel subtypes. Unfortunately, research on the acidic KTxs has been ignored for several years and progressed slowly. Principal Findings: Here, we describe the identification of nine new acidic KTxs by cDNA cloning and bioinformatic analyses. Seven of these toxins belong to three new a-KTx subfamilies (a-KTx28, a-KTx29, and a-KTx30), and two are new members of the known k-KTx2 subfamily. ImKTx104 containing three disulfide bridges, the first member of the a-KTx28 subfamily, has a low sequence homology with other known KTxs, and its NMR structure suggests ImKTx104 adopts a modified cystine-stabilized a-helix-loop-b-sheet (CS-a/b) fold motif that has no apparent a-helixs and b-sheets, but still stabilized by three disulfide bridges. These newly described acidic KTxs exhibit differential pharmacological effects on potassium channels. Acidic scorpion toxin ImKTx104 was the first peptide inhibitor found to affect KCNQ1 channel, which is insensitive to the basic KTxs and is strongly associated with human cardiac abnormalities. ImKTx104 selectively inhibited KCNQ1 channel with a Kd of 11.69 mM, but was less effective against the basic KTxs-sensitive potassium channels. In addition to the ImKTx104 toxin, HeTx204 peptide, containing a cystine-stabilized a-helix-loop-helix (CS-a/a) fold scaffold motif