Correlation Decay up to Uniqueness in Spin Systems

We give a complete characterization of the two-state anti-ferromagnetic spin systems which are of strong spatial mixing on general graphs. We show that a two-state anti-ferromagnetic spin system is of strong spatial mixing on all graphs of maximum degree at most \Delta if and only if the system has a unique Gibbs measure on infinite regular trees of degree up to \Delta, where \Delta can be either bounded or unbounded. As a consequence, there exists an FPTAS for the partition function of a two-state anti-ferromagnetic spin system on graphs of maximum degree at most \Delta when the uniqueness condition is satisfied on infinite regular trees of degree up to \Delta. In particular, an FPTAS exists for arbitrary graphs if the uniqueness is satisfied on all infinite regular trees. This covers as special cases all previous algorithmic results for two-state anti-ferromagnetic systems on general-structure graphs. Combining with the FPRAS for two-state ferromagnetic spin systems of Jerrum-Sinclair and Goldberg-Jerrum-Paterson, and the very recent hardness results of Sly-Sun and independently of Galanis-Stefankovic-Vigoda, this gives a complete classification, except at the phase transition boundary, of the approximability of all two-state spin systems, on either degree-bounded families of graphs or family of all graphs.Comment: 27 pages, submitted for publicatio

Adaptive DCTNet for Audio Signal Classification

In this paper, we investigate DCTNet for audio signal classification. Its output feature is related to Cohen's class of time-frequency distributions. We introduce the use of adaptive DCTNet (A-DCTNet) for audio signals feature extraction. The A-DCTNet applies the idea of constant-Q transform, with its center frequencies of filterbanks geometrically spaced. The A-DCTNet is adaptive to different acoustic scales, and it can better capture low frequency acoustic information that is sensitive to human audio perception than features such as Mel-frequency spectral coefficients (MFSC). We use features extracted by the A-DCTNet as input for classifiers. Experimental results show that the A-DCTNet and Recurrent Neural Networks (RNN) achieve state-of-the-art performance in bird song classification rate, and improve artist identification accuracy in music data. They demonstrate A-DCTNet's applicability to signal processing problems.Comment: International Conference of Acoustic and Speech Signal Processing (ICASSP). New Orleans, United States, March, 201

SourceP: Smart Ponzi Schemes Detection on Ethereum Using Pre-training Model with Data Flow

As blockchain technology becomes more and more popular, a typical financial scam, the Ponzi scheme, has also emerged in the blockchain platform Ethereum. This Ponzi scheme deployed through smart contracts, also known as the smart Ponzi scheme, has caused a lot of economic losses and negative impacts. Existing methods for detecting smart Ponzi schemes on Ethereum mainly rely on bytecode features, opcode features, account features, and transaction behavior features of smart contracts, and such methods lack interpretability and sustainability. In this paper, we propose SourceP, a method to detect smart Ponzi schemes on the Ethereum platform using pre-training models and data flow, which only requires using the source code of smart contracts as features to explore the possibility of detecting smart Ponzi schemes from another direction. SourceP reduces the difficulty of data acquisition and feature extraction of existing detection methods while increasing the interpretability of the model. Specifically, we first convert the source code of a smart contract into a data flow graph and then introduce a pre-training model based on learning code representations to build a classification model to identify Ponzi schemes in smart contracts. The experimental results show that SourceP achieves 87.2\% recall and 90.7\% F-score for detecting smart Ponzi schemes within Ethereum's smart contract dataset, outperforming state-of-the-art methods in terms of performance and sustainability. We also demonstrate through additional experiments that pre-training models and data flow play an important contribution to SourceP, as well as proving that SourceP has a good generalization ability.Comment: 12 page

An Overview of the Capital Raising Activities Among Proptech Firms

This article presents an overview of the capital raising activities among property/real estate technology (i.e. Proptech) firms. This overview highlights the strengths and weaknesses of the Proptech sector in recent years. This article provides a detailed summary and description of how the capital raising activities distribute across different Proptech categories and geographic locations in different market conditions. The authors find that the capital-raising activities in Proptech have cooled down despite the rising real estate prices last year. The authors hope that this review can present a more comprehensive picture of the Proptech development and attract more researchers to investigate the costs and benefits of Proptech to the real estate markets. This research contributes to the understanding of Proptech sector more comprehensively by utilizing a unique hand-collected dataset. The results present a different perspective on the recent trends of Proptech firms as they feature both the promising trends and concerning issues within the field

Hypomethylation of IL10 and IL13 Promoters in CD4+ T Cells of Patients with Systemic Lupus Erythematosus

Interleukin- (IL-)10 and IL-13 play important roles in Th2 cell differentiation and production of autoantibodies in patients with (SLE). However, the mechanisms leading to IL10 and IL13 overexpression in SLE patients are not well understood. In this study, we confirm that the levels of both IL10 and IL13 mRNA in CD4+ T cells and of serum IL10 and IL13 proteins are increased in SLE patients. We show that the DNA methylation levels within IL10 and IL13 gene regulatory domains are reduced in SLE CD4+ T cells relative to healthy controls and negatively correlate with IL10 and IL13 mRNA expression. Moreover, treating healthy CD4+ T cells with the demethylating agent 5-azacytidine (5-azaC) increased IL10 and IL13 mRNA transcription. Together, our results show that promoter methylation is a determinant of IL10 and IL13 expression in CD4+ T cells, and we propose that DNA hypomethylation leads to IL10 and IL13 overexpression in SLE patients

Regulatory effects of IRF4 on immune cells in the tumor microenvironment

The tumor microenvironment (TME) is implicated in tumorigenesis, chemoresistance, immunotherapy failure and tumor recurrence. Multiple immunosuppressive cells and soluble secreted cytokines together drive and accelerate TME disorders, T cell immunodeficiency and tumor growth. Thus, it is essential to comprehensively understand the TME status, immune cells involved and key transcriptional factors, and extend this knowledge to therapies that target dysfunctional T cells in the TME. Interferon regulatory factor 4 (IRF4) is a unique IRF family member that is not regulated by interferons, instead, is mainly induced upon T-cell receptor signaling, Toll-like receptors and tumor necrosis factor receptors. IRF4 is largely restricted to immune cells and plays critical roles in the differentiation and function of effector cells and immunosuppressive cells, particularly during clonal expansion and the effector function of T cells. However, in a specific biological context, it is also involved in the transcriptional process of T cell exhaustion with its binding partners. Given the multiple effects of IRF4 on immune cells, especially T cells, manipulating IRF4 may be an important therapeutic target for reversing T cell exhaustion and TME disorders, thus promoting anti-tumor immunity. This study reviews the regulatory effects of IRF4 on various immune cells in the TME, and reveals its potential mechanisms, providing a novel direction for clinical immune intervention

Decreased Triple Network Connectivity in Patients with Recent Onset Post-Traumatic Stress Disorder after a Single Prolonged Trauma Exposure

The triple network model provides a common framework for understanding affective and neurocognitive dysfunctions across multiple disorders, including central executive network (CEN), default mode network (DMN), and salience network (SN). Considering the effect of traumatic experience on post-traumatic stress disorder (PTSD), this study aims to explore the alteration of triple network connectivity in a specific PTSD induced by a single prolonged trauma exposure. With an arterial spin labeling sequence, three networks were first identified using independent component analysis among 10 PTSD patients and 10 healthy survivors, who experienced the same coal mining flood disaster. Then, the triple network connectivity was analyzed and compared between PTSD and non-PTSD groups. In PTSD patients, decreased connectivity was identified in left middle frontal gyrus of CEN, left precuneus and bilateral superior frontal gyrus of DMN, and right anterior insula of SN. The decreased connectivity in left middle frontal gyrus of CEN was associated with clinical severity. Furthermore, no significant connection of SN with CEN and DMN was found in PTSD patients. The decreased triple network connectivity was found in this study, which not only supports the triple network model, but also suggests a possible neurobiological mechanism for cognitive dysfunction of this type of PTSD

Application of a novel phage LPSEYT for biological control of Salmonella in foods

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. Salmonella is a leading cause of foodborne diseases, and in recent years, many isolates have exhibited a high level of antibiotic resistance, which has led to huge pressures on public health. Phages are a promising strategy to control food‐borne pathogens. In this study, one of our environmental phage isolates, LPSEYT, was to be able to restrict the growth of zoonotic Salmonella enterica in vitro over a range of multiplicity of infections. Phage LPSEYT exhibited wide‐ranging pH and thermal stability and rapid reproductive activity with a short latent period and a large burst size. Phage LPSEYT demonstrated potential efficiency as a biological control agent against Salmonella in a variety of food matrices, including milk and lettuce. Morphological observation, comparative genomic, and phylogenetic analysis revealed that LPSEYT does not belong to any of the currently identified genera within the Myoviridae family, and we suggest that LPSEYT represents a new genus, the LPSEYTvirus. This study contributes a phage database, develops beneficial phage resources, and sheds light on the potential application value of phages LPSEYT on food safety

Deviation from the Cosmological Constant or Systematic Errors?

Motivated by the fact that both SNe Ia and GRBs seem to prefer a dark energy EOS greater than -1 at redshifts $z \gtrsim 0.5$, we perform a careful investigation on this situation. We find that the deviation of dark energy from the cosmological constant at redshifts $z \gtrsim 0.5$ is large enough that we should pay close attention to it with future observational data. Such a deviation may arise from some biasing systematic errors in the handling of SNe Ia and/or GRBs or more interestingly from the nature of the dark energy itself.Comment: 4 pages, 4 figures, added reference

Transcriptome-wide identification and characterization of miRNAs from Pinus densata

<p>Abstract</p> <p>Background</p> <p>MicroRNAs (miRNAs) play key roles in diverse developmental processes, nutrient homeostasis and responses to biotic and abiotic stresses. The biogenesis and regulatory functions of miRNAs have been intensively studied in model angiosperms, such as <it>Arabidopsis thaliana</it>, <it>Oryza sativa </it>and <it>Populus trichocarpa</it>. However, global identification of <it>Pinus densata </it>miRNAs has not been reported in previous research.</p> <p>Results</p> <p>Here, we report the identification of 34 conserved miRNAs belonging to 25 miRNA families from a <it>P. densata </it>mRNA transcriptome database using local BLAST and MIREAP programs. The primary and/or precursor sequences of 29 miRNAs were further confirmed by RT-PCR amplification and subsequent sequencing. The average value of the minimal folding free energy indexes of the 34 miRNA precursors was 0.92. Nineteen (58%) mature miRNAs began with a 5' terminal uridine residue. Analysis of miRNA precursors showed that 19 mature miRNAs were novel members of 14 conserved miRNA families, of which 17 miRNAs were further validated by subcloning and sequencing. Using real-time quantitative RT-PCR, we found that the expression levels of 7 miRNAs were more than 2-fold higher in needles than in stems. In addition, 72 <it>P. densata </it>mRNAs were predicted to be targets of 25 miRNA families. Four target genes, including a nodal modulator 1-like protein gene, two GRAS family transcription factor protein genes and one histone deacetylase gene, were experimentally verified to be the targets of 3 <it>P. densata </it>miRNAs, pde-miR162a, pde-miR171a and pde-miR482a, respectively.</p> <p>Conclusions</p> <p>This study led to the discovery of 34 conserved miRNAs comprising 25 miRNA families from <it>Pinus densata</it>. These results lay a solid foundation for further studying the regulative roles of miRNAs in the development, growth and responses to environmental stresses in <it>P. densata</it>.</p