53 research outputs found

    Robust Federated Contrastive Recommender System against Model Poisoning Attack

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    Federated Recommender Systems (FedRecs) have garnered increasing attention recently, thanks to their privacy-preserving benefits. However, the decentralized and open characteristics of current FedRecs present two dilemmas. First, the performance of FedRecs is compromised due to highly sparse on-device data for each client. Second, the system's robustness is undermined by the vulnerability to model poisoning attacks launched by malicious users. In this paper, we introduce a novel contrastive learning framework designed to fully leverage the client's sparse data through embedding augmentation, referred to as CL4FedRec. Unlike previous contrastive learning approaches in FedRecs that necessitate clients to share their private parameters, our CL4FedRec aligns with the basic FedRec learning protocol, ensuring compatibility with most existing FedRec implementations. We then evaluate the robustness of FedRecs equipped with CL4FedRec by subjecting it to several state-of-the-art model poisoning attacks. Surprisingly, our observations reveal that contrastive learning tends to exacerbate the vulnerability of FedRecs to these attacks. This is attributed to the enhanced embedding uniformity, making the polluted target item embedding easily proximate to popular items. Based on this insight, we propose an enhanced and robust version of CL4FedRec (rCL4FedRec) by introducing a regularizer to maintain the distance among item embeddings with different popularity levels. Extensive experiments conducted on four commonly used recommendation datasets demonstrate that CL4FedRec significantly enhances both the model's performance and the robustness of FedRecs

    Pyramidal cell types drive functionally distinct cortical activity patterns during decision-making

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    Understanding how cortical circuits generate complex behavior requires investigating the cell types that comprise them. Functional differences across pyramidal neuron (PyN) types have been observed within cortical areas, but it is not known whether these local differences extend throughout the cortex, nor whether additional differences emerge when larger-scale dynamics are considered. We used genetic and retrograde labeling to target pyramidal tract, intratelencephalic and corticostriatal projection neurons and measured their cortex-wide activity. Each PyN type drove unique neural dynamics, both at the local and cortex-wide scales. Cortical activity and optogenetic inactivation during an auditory decision task revealed distinct functional roles. All PyNs in parietal cortex were recruited during perception of the auditory stimulus, but, surprisingly, pyramidal tract neurons had the largest causal role. In frontal cortex, all PyNs were required for accurate choices but showed distinct choice tuning. Our results reveal that rich, cell-type-specific cortical dynamics shape perceptual decisions

    Antenatal depression is associated with perceived stress, family relations, educational and professional status among women in South of China: a multicenter cross-sectional survey

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    BackgroundAntenatal depression is a commonly seen mental health concern for women. This study introduced a multicenter cross-sectional survey with a large sample to provide new insights into pregnant women’s depression, its socio-demographic and obstetric characteristics correlates, and its perceived stress among Chinese pregnant women.MethodsThis study conducted an observational survey according to the STROBE checklist. The multicenter cross-sectional survey was performed from August 2020 to January 2021 by distributing paper questionnaires among pregnant women from five tertiary hospitals in South China. The questionnaire included socio-demographic and obstetrics information, the Edinburgh Postnatal Depression Scale, and the 10-item Perceived Stress Scale. For the analyses, the Chi-square test and Multivariate logistic regression were utilized.ResultsAmong 2014 pregnant women in their second/third trimester, the prevalence of antenatal depression was 36.3%. 34.4% of pregnant women reported AD in their second trimester of pregnancy, and 36.9% suffered from AD in third trimester of pregnancy. A multivariate logistic regression model indicated that unemployed women, lower levels of education, poor marital relationships, poor parents-in-law relationships, concerns about contracting COVID-19, and higher perceived stress could aggravate antenatal depression among participants (p<0.05).ConclusionThere is a high proportion of antenatal depression among pregnant women in South China, so integrating depression screening into antenatal care services is worthwhile. Maternal and child health care providers need to evaluate pregnancy-related risk factors (perceived stress), socio-demographic factors (educational and professional status), and interpersonal risk factors (marital relations and relationship with Parents-in-law). In future research, the study also emphasized the importance of providing action and practical support to reduce the experience of antenatal depression among disadvantaged sub-groups of pregnant women

    Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

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    Funder: European Society of Intensive Care Medicine; doi: http://dx.doi.org/10.13039/501100013347Funder: Flemish Society for Critical Care NursesAbstract: Purpose: Intensive care unit (ICU) patients are particularly susceptible to developing pressure injuries. Epidemiologic data is however unavailable. We aimed to provide an international picture of the extent of pressure injuries and factors associated with ICU-acquired pressure injuries in adult ICU patients. Methods: International 1-day point-prevalence study; follow-up for outcome assessment until hospital discharge (maximum 12 weeks). Factors associated with ICU-acquired pressure injury and hospital mortality were assessed by generalised linear mixed-effects regression analysis. Results: Data from 13,254 patients in 1117 ICUs (90 countries) revealed 6747 pressure injuries; 3997 (59.2%) were ICU-acquired. Overall prevalence was 26.6% (95% confidence interval [CI] 25.9–27.3). ICU-acquired prevalence was 16.2% (95% CI 15.6–16.8). Sacrum (37%) and heels (19.5%) were most affected. Factors independently associated with ICU-acquired pressure injuries were older age, male sex, being underweight, emergency surgery, higher Simplified Acute Physiology Score II, Braden score 3 days, comorbidities (chronic obstructive pulmonary disease, immunodeficiency), organ support (renal replacement, mechanical ventilation on ICU admission), and being in a low or lower-middle income-economy. Gradually increasing associations with mortality were identified for increasing severity of pressure injury: stage I (odds ratio [OR] 1.5; 95% CI 1.2–1.8), stage II (OR 1.6; 95% CI 1.4–1.9), and stage III or worse (OR 2.8; 95% CI 2.3–3.3). Conclusion: Pressure injuries are common in adult ICU patients. ICU-acquired pressure injuries are associated with mainly intrinsic factors and mortality. Optimal care standards, increased awareness, appropriate resource allocation, and further research into optimal prevention are pivotal to tackle this important patient safety threat

    WSN Data Transmission Algorithm Based on Spatial Data Aggregation

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    In this paper, considering the high energy consumption, loss of network lifetime and data leak in transmission during the data aggregation of the wireless sensor network, we propose an improved spatial data aggregation algorithm. Through comparison with traditional data aggregation algorithms, we verify the feasibility and rationality of the proposed algorithm and obtain the following conclusions: the proposed algorithm carries out node sensing and data aggregation within a certain area based on multiple dynamic routes. The calculation process does not require encryption and decryption, and is not affected by network topology, so it can better address the data aggregation problems in the dynamic change of network structure. Compared with other traditional data aggregation algorithms, the proposed algorithm has the advantages of low traffic, low energy consumption in data transmission, low probability of data leakage and high transmission accuracy. In data aggregation, 3 slices is the optimal quantity

    WSN Data Transmission Algorithm Based on Spatial Data Aggregation

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    Beyond ENO1, emerging roles and targeting strategies of other enolases in cancers

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    Aerobic glycolysis is a hallmark property of cancer metabolism. Enolase is a glycolytic enzyme that catalyzes the conversion of 2-phosphoglycerate into phosphoenolpyruvate. In mammals, enolases exist in three isoforms, encoded by the genes ENO1, ENO2, and ENO3. The altered expression of enolases is a common occurrence in various types of cancer. Although most published studies on enolases have predominantly focused on the role of ENO1 in cancer, ENO2 and ENO3 have recently emerged as crucial regulatory molecules in cancer development. Significant progress has been made in understanding their multifaceted roles in oncogenesis. In this comprehensive review, we provide an overview of the structure, subcellular localization, diagnostic and prognostic significance, biological functions, and molecular mechanisms of ENO2 and ENO3 in cancer progression. The importance of enolase in cancer development makes it a novel therapeutic target for clinical applications. Furthermore, we discuss anticancer agents designed to target enolases and summarize their anticancer efficacy in both in vitro and in vivo studies
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