Universal scalefree non-Hermitian skin effect near the Bloch point

The scalefree non-Hermitian skin effect (NHSE) refers to the phenomenon that the localization length of skin modes scales proportionally with system size in non-Hermitian systems. Authors of recent studies have demonstrated that the scalefree NHSE can be induced through various mechanisms, including the critical NHSE, local non-Hermiticity, and the boundary impurity effect. Nevertheless, these methods require careful modeling and precise parameter tuning. In contrast, in this paper, we suggest that the scalefree NHSE is a universal phenomenon, observable in extensive systems if these systems can be described by non-Bloch band theory and host Bloch points on the energy spectrum in the thermodynamic limit. Crucially, we discover that the geometry of the generalized Brillouin zone determines the scaling rule of the localization length, which can scale either linearly or quadratically with the system size. In this paper, we enriches the phenomenon of the scalefree NHSE

The Relationship Between Speech Features Changes When You Get Depressed: Feature Correlations for Improving Speed and Performance of Depression Detection

This work shows that depression changes the correlation between features extracted from speech. Furthermore, it shows that using such an insight can improve the training speed and performance of depression detectors based on SVMs and LSTMs. The experiments were performed over the Androids Corpus, a publicly available dataset involving 112 speakers, including 58 people diagnosed with depression by professional psychiatrists. The results show that the models used in the experiments improve in terms of training speed and performance when fed with feature correlation matrices rather than with feature vectors. The relative reduction of the error rate ranges between 23.1% and 26.6% depending on the model. The probable explanation is that feature correlation matrices appear to be more variable in the case of depressed speakers. Correspondingly, such a phenomenon can be thought of as a depression marker

Co 3

Co3O4 nanoparticles were prepared from cobalt nitrate that was accommodated in the pores of a metal-organic framework (MOF) ZIF-8 (Zn(MeIM)2, MeIM = 2-methylimidazole) by using a simple liquid-phase method. Analysis by scanning electron microscopy (SEM) and transmission electron microscopy (TEM) showed that the obtained Co3O4 was composed of separate nanoparticles with a mean size of 30 nm. The obtained Co3O4 nanoparticles exhibited superior electrochemical property. Co3O4 electrode exhibited a maximum specific capacitance of 189.1 F g−1 at the specific current of 0.2 A g−1. Meanwhile, the Co3O4 electrode possessed the high specific capacitance retention ratio at the current density ranging from 0.2 to 1.0 A g−1, thereby indicating that Co3O4 electrode suited high-rate charge/discharge

Multi-Local Attention for Speech-Based Depression Detection

This article shows that an attention mechanism, the Multi-Local Attention, can improve a depression detection approach based on Long Short-Term Memory Networks. Besides leading to higher performance metrics (e.g., Accuracy and F1 Score), Multi-Local Attention improves two other aspects of the approach, both important from an application point of view. The first is the effectiveness of a confidence score associated to the detection outcome at identifying speakers more likely to be classified correctly. The second is the amount of speaking time needed to classify a speaker as depressed or non-depressed. The experiments were performed over read speech and involved 109 participants (including 55 diagnosed with depression by professional psychiatrists). The results show accuracies up to 88.0% (F1 Score 88.0%)

Modeling and Bifurcation Research of a Worm Propagation Dynamical System with Time Delay

Both vaccination and quarantine strategy are adopted to control the Internet worm propagation. By considering the interaction infection between computers and external removable devices, a worm propagation dynamical system with time delay under quarantine strategy is constructed based on anomaly intrusion detection system (IDS). By regarding the time delay caused by time window of anomaly IDS as the bifurcation parameter, local asymptotic stability at the positive equilibrium and local Hopf bifurcation are discussed. Through theoretical analysis, a threshold τ0 is derived. When time delay is less than τ0, the worm propagation is stable and easy to predict; otherwise, Hopf bifurcation occurs so that the system is out of control and the containment strategy does not work effectively. Numerical analysis and discrete-time simulation experiments are given to illustrate the correctness of theoretical analysis

A Stem Cell-Based Tool for Small Molecule Screening in Adipogenesis

Techniques for small molecule screening are widely used in biological mechanism study and drug discovery. Here, we reported a novel adipocyte differentiation assay for small molecule selection, based on human mesenchymal stem cells (hMSCs) transduced with fluorescence reporter gene driven by adipogenic specific promoter - adipocyte Protein 2 (aP2; also namely Fatty Acid Binding Protein 4, FABP4). During normal adipogenic induction as well as adipogenic inhibition by Ly294002, we confirmed that the intensity of green fluorescence protein corresponded well to the expression level of aP2 gene. Furthermore, this variation of green fluorescence protein intensity can be read simply through fluorescence spectrophotometer. By testing another two small molecules in adipogenesis –Troglitazone and CHIR99021, we proved that this is a simple and sensitive method, which could be applied in adipocyte biology, drug discovery and toxicological study in the future

Data Augmentation and Dense-LSTM for Human Activity Recognition Using WiFi Signal

Recent research has devoted significant efforts on the utilization of WiFi signals to recognize various human activities. An individual’s limb motions in the WiFi coverage area could interfere with wireless signal propagation, that manifested as unique patterns for activity recognition. Existing approaches though yielding reasonable performance in certain cases, are ignorant of two major challenges. The performed activities of the individual normally have inconsistent speed in different situations and time. Besides that the wireless signal reflected by human bodies normally carries substantial information that is specific to that subject. The activity recognition model trained on a certain individual may not work well when being applied to predict another individual’s activities. Since only recording activities of limited subjects in a certain speed and scale, recent works commonly have a moderate amount of activity data for training the recognition model. The small-size data could often incur the overfitting issue that negative affect the traditional classification model. To address these challenges, we propose a WiFi-based human activity recognition system that synthesizes variant activities data through eight channel state information (CSI) transformation methods to mitigate the impact of activity inconsistency and subject-specific issues, and also design a novel deep-learning model that caters to the small-size WiFi activity data. We conduct extensive experiments and show synthetic data improve performance by up to 34.6% and our system achieves around 90% of accuracy with well robustness in adapting to small-size CSI data

Risk factors of oncogenic HPV infection in HIV-positive men with anal condyloma acuminata in Shenzhen, Southeast China: a retrospective cohort study

BackgroundHuman immunodeficiency virus (HIV)-positive patients with anal condyloma acuminata (CA) present an increased risk of anal cancer progression associated with oncogenic human papillomavirus (HPV) infection. It is essential to explore determinants of anal infection by oncogenic HPV among HIV-positive patients with CA.MethodsA retrospective cohort study was performed in HIV-positive patients with CA between January 2019 to October 2021 in Shenzhen, Southeast China. Exfoliated cells were collected from CA lesions and the anal canal of HPV genotypes detected by fluorescence PCR. Unconditional logistic regression analysis was used to probe associations of independent variables with oncogenic HPV infection.ResultsAmong HIV-positive patients with CA, the most prevalent oncogenic genotypes were HPV52 (29.43%), HPV16 (28.93%), HPV59 (19.20%), and HPV18 (15.96%). Risk of oncogenic HPV infection increased with age at enrollment (COR: 1.04, 95% CI: 1.01–1.07, p = 0.022). In the multivariable analysis, age ≥ 35 years (AOR: 2.56, 95% CI: 1.20–5.70, p = 0.02) and history of syphilis (AOR: 3.46, 95% CI: 1.90–6.79, p < 0.01) were independent risk factors statistically associated with oncogenic HPV infection. History of syphilis (AOR: 1.72, 95% CI: 1.08–2.73, p < 0.02) was also an independent risk factor statistically associated with HPV16 or HPV18 infection.ConclusionIn clinical practice, HIV-positive CA patients aged ≥35 years or with a history of syphilis should carry out HR-HPV testing and even anal cancer-related examinations to prevent the occurrence of anal cancer

Identification of Heat-Tolerant Genes in Non-Reference Sequences in Rice by Integrating Pan-Genome, Transcriptomics, and QTLs.

The availability of large-scale genomic data resources makes it very convenient to mine and analyze genes that are related to important agricultural traits in rice. Pan-genomes have been constructed to provide insight into the genome diversity and functionality of different plants, which can be used in genome-assisted crop improvement. Thus, a pan-genome comprising all genetic elements is crucial for comprehensive variation study among the heat-resistant and -susceptible rice varieties. In this study, a rice pan-genome was firstly constructed by using 45 heat-tolerant and 15 heat-sensitive rice varieties. A total of 38,998 pan-genome genes were identified, including 37,859 genes in the reference and 1141 in the non-reference contigs. Genomic variation analysis demonstrated that a total of 76,435 SNPs were detected and identified as the heat-tolerance-related SNPs, which were specifically present in the highly heat-resistant rice cultivars and located in the genic regions or within 2 kbp upstream and downstream of the genes. Meanwhile, 3214 upregulated and 2212 downregulated genes with heat stress tolerance-related SNPs were detected in one or multiple RNA-seq datasets of rice under heat stress, among which 24 were located in the non-reference contigs of the rice pan-genome. We then mapped the DEGs with heat stress tolerance-related SNPs to the heat stress-resistant QTL regions. A total of 1677 DEGs, including 990 upregulated and 687 downregulated genes, were mapped to the 46 heat stress-resistant QTL regions, in which 2 upregulated genes with heat stress tolerance-related SNPs were identified in the non-reference sequences. This pan-genome resource is an important step towards the effective and efficient genetic improvement of heat stress resistance in rice to help meet the rapidly growing needs for improved rice productivity under different environmental stresses. These findings provide further insight into the functional validation of a number of non-reference genes and, especially, the two genes identified in the heat stress-resistant QTLs in rice

Dephosphorylated Polymerase I and Transcript Release Factor Prevents Allergic Asthma Exacerbations by Limiting IL-33 Release

BackgroundAsthma is a chronic inflammatory disease characterized by airway inflammation and airway hyperresponsiveness (AHR). IL-33 is considered as one of the most critical molecules in asthma pathogenesis. IL-33 is stored in nucleus and passively released during necrosis. But little is known about whether living cells can release IL-33 and how this process is regulated.ObjectiveWe sought to investigate the role of polymerase I and transcript release factor (PTRF) in IL-33 release and asthma pathogenesis.MethodsOvalbumin (OVA)-induced asthma model in PTRF+/− mice were employed to dissect the role of PTRF in vivo. Then, further in vitro experiments were carried out to unwind the potential mechanism involved.ResultsIn OVA asthma model with challenge phase, PTRF+/− mice showed a greater airway hyper-reaction, with an intense airway inflammation and more eosinophils in bronchoalveolar lavage fluid (BALF). Consistently, more acute type 2 immune response in lung and a higher IL-33 level in BALF were found in PTRF+/− mice. In OVA asthma model without challenge phase, airway inflammation and local type 2 immune responses were comparable between control mice and PTRF+/− mice. Knockdown of PTRF in 16HBE led to a significantly increased level of IL-33 in cell culture supernatants in response to LPS or HDM. Immunoprecipitation assay clarified Y158 as the major phosphorylation site of PTRF, which was also critical for the interaction of IL-33 and PTRF. Overexpression of dephosphorylated mutant Y158F of PTRF sequestered IL-33 in nucleus together with PTRF and limited IL-33 extracellular secretion.ConclusionPartial loss of PTRF led to a greater AHR and potent type 2 immune responses during challenge phase of asthma model, without influencing the sensitization phase. PTRF phosphorylation status determined subcellular location of PTRF and, therefore, regulated IL-33 release