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Due to the intricate chaotic environments encountered in distributed sensor applications, such as sea monitoring, machinery fault diagnosis, and EEG weak signal detection, neural networks often face insufficient data to effectively carry out detection tasks. In contrast to traditional machine learning models, a statistical approach employing multidimensional nonlinear correlation (MNC) exhibits an unparalleled signal pattern prediction capability and possesses a streamlined yet robust framework for signal processing. However, the direct application of MNC to weak pulse signal detection remains constrained. To surmount these challenges and achieve high‐precision signal detection, we explore a novel MNC approach, integrating phase reconstruction and manifold broad learning, specifically tailored for distributed sensor fusion detection amidst chaotic noise. Initially, the distributed observational data undergoes phase space reconstruction, transforming it into fixed‐size arrays. These reconstructed tuples are then processed through the high‐dimensional sequence of manifold broad learning, serving as inputs for the nonlinear correlation module to extract spatiotemporal features. Subsequently, a MNC system augmented with a QRS detector layer is devised to predict and classify the presence of a weak pulse signal. This integrated MNC approach, combining phase reconstruction and broad learning, operates within an enhanced feature space of the source domain, realizing detection fusion across distributed sensors through a majority voting principle. Simulation studies and experiments conducted on sea clutter datasets demonstrate the efficacy and robustness of the proposed MNC method, leveraging phase reconstruction and manifold broad learning strategies, for distributed sensor weak pulse signal fusion detection within chaotic backgrounds.

The rapid advances of the 4th generation mobile networks, social media and the ubiquity of the advanced mobile devices in which GPS modules are embedded have enabled the location-based services, especially the Location-Based Social Networks (LBSNs) such as Foursquare and Facebook Places. LBSNs have been attracting more and more users by providing services that integrate social activities with geographic information. In LBSNs, a user can explore places of interests around his current location, check in at these venues and also selectively share his check-ins with the public or his friends. LBSNs have accumulated large amounts of information related to personal or social activities along with their associated location information. Analyzing and mining LBSN information are important to understand human preferences related to locations and their mobility patterns. Therefore, in this dissertation, we aim to understand the human mobility behavior and patterns based on huge amounts of information available on LBSNs and provide a hybrid trust-based POI recommendation for LBSN users. In this dissertation, we first carry out a comprehensive and quantitative analysis about venue popularity based on a cumulative dataset collected from greater Pittsburgh area in Foursquare. It provides a general understanding of the online population's preferences on locations. Then, we employ a probabilistic graphical model to mine the check-in dataset to discover the local geographic topics that capture the potential and intrinsic relations among the locations in accordance with users' check-in histories. We also investigate the local geographic topics with different temporal aspects. Moreover, we explore the geographic topics based on travelers' check-ins. The proposed approach for mining the latent geographic topics successfully addresses the challenges of understanding location preferences of groups of users. Lastly, we focus on individual user's preferences of locations and propose a hybrid trust-based POI recommendation algorithm in this dissertation. The proposed approach integrates the trust based on both users' social relationship and users' check-in behavior to provide POI recommendations. We implement the proposed hybrid trust-based recommendation algorithm and evaluate it based on the Foursquare dataset and the experimental results show good performances of our proposed algorithm.

In an undirected social graph, a friendship link involves two users and the friendship is visible in both the users' friend lists. Such a dual visibility of the friendship may raise privacy threats. This is because both users can separately control the visibility of a friendship link to other users and their privacy policies for the link may not be consistent. Even if one of them conceals the link from a third user, the third user may find such a friendship link from another user's friend list. In addition, as most users allow their friends to see their friend lists in most social network systems, an adversary can exploit the inconsistent policies to launch privacy attacks to identify and infer many of a targeted user's friends. In this paper, we propose, analyze and evaluate such an attack which is called Friendship Identification and Inference (FII) attack. In a FII attack scenario, we assume that an adversary can only see his friend list and the friend lists of his friends who do not hide the friend lists from him. Then, a FII attack contains two attack steps: 1) friend identification and 2) friend inference. In the friend identification step, the adversary tries to identify a target's friends based on his friend list and those of his friends. In the friend inference step, the adversary attempts to infer the target's friends by using the proposed random walk with restart approach. We present experimental results using three real social network datasets and show that FII attacks are generally efficient and effective when adversaries and targets are friends or 2-distant neighbors. We also comprehensively analyze the attack results in order to find what values of parameters and network features could promote FII attacks. Currently, most popular social network systems with an undirected friendship graph, such as Facebook, LinkedIn and Foursquare, are susceptible to FII attacks.

This study investigates the distribution patterns, interspecific relationships, and community stability mechanisms of phytoplankton functional groups, aiming to elucidate the ecological processes that drive phytoplankton communities in aquatic ecosystems of arid regions. We conducted seasonal sampling from 2023 to 2024 at four auxiliary reservoirs in the Tarim River Basin, namely Shangyou Reservoir (SY), Shengli Reservoir (SL), Duolang Reservoir (DL), and Xinjingzi Reservoir (XJZ). In recent years, researchers have grouped phytoplankton into functional groups based on their shared morphological, physiological, and ecological characteristics—with these three types of traits serving as the core criteria for distinguishing different functional groups. A total of 18 functional groups were identified from the phytoplankton collected across four seasons, among which eight (A, D, H1, L0, M, MP, P, and S1) are dominant. Redundancy Analysis (RDA) indicated that environmental factors such as pH, electrical conductivity (COND), and dissolved oxygen (DO) are key driving factors affecting phytoplankton functional groups. Interspecific association analysis showed that the phytoplankton communities in DL, SL, and XJZ reservoirs were dominated by positive associations, reflecting stable community structures that are less prone to drastic fluctuations under stable environmental conditions. In contrast, the SY Reservoir was dominated by negative associations, indicating that it is in the early stage of succession with an unstable community. This may be related to intense human disturbance to the reservoir and its role in replenishing the Tarim River, which leads to significant water level fluctuations. The results of the Chi-square test and Pearson correlation analysis showed consistent trends but also differences: constrained by the requirement for continuous normal distribution, Pearson correlation analysis identified more pairs of negative associations, reflecting its limitations in analysing clumped-distributed species. Random forest models further indicated that functional groups M, MP, L0, and S1 are the main positive drivers of interspecific relationships. Among them, the increase in S1 can promote the growth of functional groups dominated by Navicula sp. and Chroococcus sp. by reducing resource competition. Conversely, the expansion of functional group H1 inhibits other groups, which is related to its adaptive strategy of resisting photo-oxidation in eutrophic environments. This study reveals the patterns of interspecific interactions and stability mechanisms of phytoplankton functional groups in arid-region reservoirs, providing a scientific basis for the management and conservation of aquatic ecosystems in similar extreme environments.

This study investigates the mechanisms of zooplankton community assembly and their relationship to environmental factors in high-latitude arid regions. We conducted seasonal sampling at four reservoirs in the upper Tarim River Basin from 2023 to 2024: Shangyou Reservoir (SY), Shengli Reservoir (SL), Duolang Reservoir (DL) and Xinjingzi Reservoir (XJZ). The zooplankton community was categorized into five functional groups based on the predominant species, with small crustacean filter feeders (SCF) in all reservoirs except XJZ, where a seasonal shift between rotifer collectors (RC) in the wet season and SCF in the dry season was observed. Pearson correlation and canonical correspondence analysis (CCA) revealed that interspecific competition, pH, conductivity (COND), and salinity (SALIN) were the main determinants of zooplankton community composition. Significant correlations (p < 0.05) were detected among functional groups RC (rotifers carnivora), RF (rotifers filter feeders), SCF (small copepods and claocera filter feeders), and MCC (middle copepods and claocera carnivora). Environmental factors showed significant spatial heterogeneity, while zooplankton biomass was positively correlated with pH and COND. Cluster similarity analyses indicated complex interactions between 29 zooplankton species, with RF identified as an important positive predictor for larger groups. The network of co-occurrences showed predominantly positive relationships, emphasizing the mutual facilitation between the species. Our results suggest that interspecific interactions have stronger effects on community structuring than environmental factors, with mutual facilitation emerging as an important survival strategy. This study provides important insights into the dynamics of zooplankton communities in dry reservoirs and establishes a framework for understanding ecological patterns and assembly mechanisms under drought conditions.

Amorphization and crystalline grain boundary engineering are adopted separately in improving the catalytic kinetics for water electrolysis. Yet, the synergistic effect and advance in the cooperated form of crystalline/amorphous interfaces (CAI) have rarely been elucidated insightfully. Herein, a trimetallic FeCo(NiS2)4 catalyst with numerous CAI (FeCo(NiS2)4‐C/A) is presented, which shows highly efficient catalytic activity toward both hydrogen and oxygen evolution reactions (HER and OER). Density functional theory (DFT) studies reveal that CAI plays a significant role in accelerating water electrolysis kinetics, in which Co atoms on the CAI of FeCo(NiS2)4‐C/A catalyst exhibit the optimal binding energy of 0.002 eV for H atoms in HER while it also has the lowest reaction barrier of 1.40 eV for the key step of OER. H2O molecules are inclined to be absorbed on the interfacial Ni atoms based on DFT calculations. As a result, the heterostructural CAI‐containing catalyst shows a low overpotential of 82 and 230 mV for HER and OER, respectively. As a bifunctional catalyst, it delivers a current density of 10 mA cm−2 at a low cell voltage of 1.51 V, which enables it a noble candidate as metal‐based catalysts for water splitting. This work explores the role of CAI in accelerating the HER and OER kinetics for water electrolysis, which sheds light on the development of efficient, stable, and economical water electrolysis systems by facile interface‐engineering implantations. The FeCo(NiS2)4‐C/A electrocatalyst with sufficient crystalline/amorphous interfaces is designed and prepared as a bifunctional electrode, showing a low overpotential of 82 and 230 mV for hydrogen and oxygen evolution reactions, respectively.

The polysaccharide of Atractylodes macrocephala Koidz (PAMK) is recognized as an immune enhancer, with anti-cancer, anti-tumour, lymphocyte-activating and lymphocytes proliferation-inducing effects. For investigating the mechanism that PAMK alleviates the decline in T cell activation induced by CTX, 24 6-week-old BALB/c female mice were randomly divided into four groups (C, PAMK, CTX, PAMK + CTX). The spleen index, splenocytes morphology and death, cytokine concentration, T cell activating factors (CD25, CD69, CD71), mRNA expression levels related to the CD28 signal pathway were detected. Furthermore, the lymphocytes of mice was isolated and cultured, and then the Th1/Th2 ratio, activating factors, mRNA levels related to the CD28 signal pathway were detected. The results showed that PAMK significantly improved the spleen index, alleviated abnormal splenocytes morphology and death, maintained the balance of Th1/Th2 cells, increased the levels of IL-2, IL-6, TNF-α, and IFN-γ, and increased the mRNA levels of CD28, PLCγ-1, IP3R, NFAT, and AP-1. In conclusion, PAMK increased cytokines levels and alleviated the decline in activation level of lymphocytes induced by CTX through CD28/IP3R/PLCγ-1/AP-1/NFAT signal pathway.

Hyperglycemia exposure results in the dysfunction of endothelial cells (ECs) and the development of diabetic complications. Circular RNAs (circRNAs) have been demonstrated to play critical roles in EC dysfunction. The current study aimed to explore the role and mechanism of circRNA CLIP–associating protein 2 (circ_CLASP2, hsa_circ_0064772) on HG-induced dysfunction in human umbilical vein endothelial cells (HUVECs). Quantitative real-time polymerase chain reaction (qRT-PCR) was used to assess the levels of circ_CLASP2, miR-140-5p and F-box, and WD repeat domain-containing 7 (FBXW7). The stability of circ_CLASP2 was identified by the actinomycin D and ribonuclease (RNase) R assays. Cell colony formation, proliferation, and apoptosis were measured by a standard colony formation assay, colorimetric 3-(4, 5-dimethylthiazol-2-yl)-2, 5-diphenyl-2H-tetrazolium bromide (MTT) assay, and flow cytometry, respectively. Western blot analysis was performed to determine the expression of related proteins. Targeted correlations among circ_CLASP2, miR-140-5p, and FBXW7 were confirmed by dual-luciferase reporter assay. High glucose (HG) exposure downregulated the expression of circ_CLASP2 in HUVECs. Circ_CLASP2 overexpression or miR-140-5p knockdown promoted proliferation and inhibited apoptosis of HUVECs under HG conditions. Circ_CLASP2 directly interacted with miR-140-5p via pairing to miR-140-5p. The regulation of circ_CLASP2 overexpression on HG-induced HUVEC dysfunction was mediated by miR-140-5p. Moreover, FBXW7 was a direct target of miR-140-5p, and miR-140-5p regulated HG-induced HUVEC dysfunction via FBXW7. Furthermore, circ_CLASP2 mediated FBXW7 expression through sponging miR-140-5p. Our current study suggested that the overexpression of circ_CLASP2 protected HUVEC from HG-induced dysfunction at least partly through the regulation of the miR-140-5p/FBXW7 axis, highlighting a novel therapeutic approach for the treatment of diabetic-associated vascular injury.

Post-stroke depression (PSD) represents a prevalent and debilitating sequela following cerebrovascular accidents, with its underlying pathophysiology intricately linked to neuroinflammatory processes. Emerging evidence implicates glial cell pyroptosis depending on Caspase-gasdermin D (Casp-GSDMD), orchestrated by the NLR family pyrin domain containing 3 (NLRP3) inflammasome-mediated inflammatory cascades, as a central mechanism in PSD pathogenesis. This review provides a comprehensive analysis of the molecular mechanisms governing glial cell pyroptosis and its dual role in PSD. Specifically, ischemia and hypoxia induce mitochondrial dysfunction and reactive oxygen species (ROS) accumulation, thereby promoting the release of pro-inflammatory cytokines, including IL-1β and IL-18, via the NLRP3/Caspase-1/GSDMD axis. This subsequently exacerbates neuroinflammation and disrupts the blood-brain barrier (BBB) integrity. Furthermore, aberrant activation of pyroptosis-related molecules can trigger neuronal death and impair synaptic plasticity, directly contributing to depressive symptoms. Consequently, therapeutic interventions targeting key nodes within the pyroptosis pathway, such as NLRP3, Caspase-1/4/11, and GSDMD, hold considerable promise, encompassing small molecule inhibitors, natural compounds, and combination therapies. This review synthesizes the multifaceted mechanisms of glial cell pyroptosis in PSD, highlighting the unique therapeutic potential of targeting the pyroptosis pathway to enhance post-stroke neurorepair and mitigate emotional disturbances. These findings may facilitate the identification of novel therapeutic targets and strategies for the diagnosis and management of PSD.

Background Sapria himalayana (Rafflesiaceae) is an endoparasitic plant characterized by a greatly reduced vegetative body and giant flowers; however, the mechanisms underlying its special lifestyle and greatly altered plant form remain unknown. To illustrate the evolution and adaptation of S. himalayasna , we report its de novo assembled genome and key insights into the molecular basis of its floral development, flowering time, fatty acid biosynthesis, and defense responses. Results The genome of S. himalayana is ~ 1.92 Gb with 13,670 protein-coding genes, indicating remarkable gene loss (~ 54%), especially genes involved in photosynthesis, plant body, nutrients, and defense response. Genes specifying floral organ identity and controlling organ size were identified in S. himalayana and Rafflesia cantleyi , and showed analogous spatiotemporal expression patterns in both plant species. Although the plastid genome had been lost, plastids likely biosynthesize essential fatty acids and amino acids (aromatic amino acids and lysine). A set of credible and functional horizontal gene transfer (HGT) events (involving genes and mRNAs) were identified in the nuclear and mitochondrial genomes of S. himalayana , most of which were under purifying selection. Convergent HGTs in Cuscuta , Orobanchaceae, and S. himalayana were mainly expressed at the parasite–host interface. Together, these results suggest that HGTs act as a bridge between the parasite and host, assisting the parasite in acquiring nutrients from the host. Conclusions Our results provide new insights into the flower development process and endoparasitic lifestyle of Rafflesiaceae plants. The amount of gene loss in S. himalayana is consistent with the degree of reduction in its body plan. HGT events are common among endoparasites and play an important role in their lifestyle adaptation.