69 research outputs found

    On the Sustainability of Lightweight Cryptography Based on PUFs Implemented on NAND Flash Memories Using Programming Disturbances

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    In this work, we examine the potential of Physical Unclonable Functions (PUFs) that have been implemented on NAND Flash memories using programming disturbances to act as sustainable primitives for the purposes of lightweight cryptography. In particular, we investigate the ability of such PUFs to tolerate temperature and voltage variations, and examine the current shortcomings of existing NAND-Flash-memory PUFs that are based on programming disturbances as well as how these could potentially be addressed in order to provide more robust and more sustainable security solutions.Comment: This work was accepted for and presented at the Workshop on Sustainability in Security, Security for Sustainability, which took place on 18 March 2022 and was co-located with the 25th Design, Automation and Test in Europe Conference & Exhibition (DATE 2022

    Quantum model prediction for frequency regulation of novel power systems which includes a high proportion of energy storage

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    As the proportion of renewable energy generation continues to increase, the participation of new energy stations with high-proportion energy storage in power system frequency regulation is of significant importance for stable and secure operation of the new power system. To address this issue, an energy storage control method based on quantum walks and model predictive control (MPC) has been proposed. First, historical frequency deviation signals and energy storage charge–discharge state signals are collected. Simulation data are generated through amplitude encoding and quantum walks, followed by quantum decoding. Subsequently, the decoded data are inputted into the MPC framework for real-time control, with parameters of the predictive model continuously adjusted through a feedback loop. Finally, a novel power system frequency regulation model with high-proportion new energy storage stations is constructed on the MATLAB/Simulink platform. Simulation verification is conducted with the proportional–integral–derivative (PID) and MPC methods as comparative approaches. Simulation results under step disturbances and random disturbances demonstrate that the proposed method exhibits stronger robustness and better control accuracy

    Present and Future: Crosstalks Between Polycystic Ovary Syndrome and Gut Metabolites Relating to Gut Microbiota

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    Polycystic ovary syndrome (PCOS) is a common disease, affecting 8%–13% of the females of reproductive age, thereby compromising their fertility and long-term health. However, the pathogenesis of PCOS is still unclear. It is not only a reproductive endocrine disease, dominated by hyperandrogenemia, but also is accompanied by different degrees of metabolic abnormalities and insulin resistance. With a deeper understanding of its pathogenesis, more small metabolic molecules, such as bile acids, amino acids, and short-chain fatty acids, have been reported to be involved in the pathological process of PCOS. Recently, the critical role of gut microbiota in metabolism has been focused on. The gut microbiota-related metabolic pathways can significantly affect inflammation levels, insulin signaling, glucose metabolism, lipid metabolism, and hormonal secretions. Although the abnormalities in gut microbiota and metabolites might not be the initial factors of PCOS, they may have a significant role in the pathological process of PCOS. The dysbiosis of gut microbiota and disturbance of gut metabolites can affect the progression of PCOS. Meanwhile, PCOS itself can adversely affect the function of gut, thereby contributing to the aggravation of the disease. Inhibiting this vicious cycle might alleviate the symptoms of PCOS. However, the role of gut microbiota in PCOS has not been fully explored yet. This review aims to summarize the potential effects and modulative mechanisms of the gut metabolites on PCOS and suggests its potential intervention targets, thus providing more possible treatment options for PCOS in the future

    Toxicity of microplastics and nanoplastics: invisible killers of female fertility and offspring health

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    Microplastics (MPs) and nanoplastics (NPs) are emergent pollutants, which have sparked widespread concern. They can infiltrate the body via ingestion, inhalation, and cutaneous contact. As such, there is a general worry that MPs/NPs may have an impact on human health in addition to the environmental issues they engender. The threat of MPs/NPs to the liver, gastrointestinal system, and inflammatory levels have been thoroughly documented in the previous research. With the detection of MPs/NPs in fetal compartment and the prevalence of infertility, an increasing number of studies have put an emphasis on their reproductive toxicity in female. Moreover, MPs/NPs have the potential to interact with other contaminants, thus enhancing or diminishing the combined toxicity. This review summarizes the deleterious effects of MPs/NPs and co-exposure with other pollutants on female throughout the reproduction period of various species, spanning from reproductive failure to cross-generational developmental disorders in progenies. Although these impacts may not be directly extrapolated to humans, they do provide a framework for evaluating the potential mechanisms underlying the reproductive toxicity of MPs/NPs

    Bone marrow mesenchymal stem cells in premature ovarian failure: Mechanisms and prospects

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    Premature ovarian failure (POF) is a common female reproductive disorder and characterized by menopause, increased gonadotropin levels and estrogen deficiency before the age of 40 years old. The etiologies and pathogenesis of POF are not fully clear. At present, hormone replacement therapy (HRT) is the main treatment options for POF. It helps to ameliorate perimenopausal symptoms and related health risks, but can’t restore ovarian function and fertility fundamentally. With the development of regenerative medicine, bone marrow mesenchymal stem cells (BMSCs) have shown great potential for the recovery of ovarian function and fertility based on the advantages of abundant sources, high capacity for self-renewal and differentiation, low immunogenicity and less ethical considerations. This systematic review aims to summarize the possible therapeutic mechanisms of BMSCs for POF. A detailed search strategy of preclinical studies and clinical trials on BMSCs and POF was performed on PubMed, MEDLINE, Web of Science and Embase database. A total of 21 studies were included in this review. Although the standardization of BMSCs need more explorations, there is no doubt that BMSCs transplantation may represent a prospective therapy for POF. It is hope to provide a theoretical basis for further research and treatment for POF

    Expression and clinical value of CXCR4 in high grade gastroenteropancreatic neuroendocrine neoplasms

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    BackgroundCXC chemokine receptor 4 (CXCR4) is associated with the progression and metastasis of numerous malignant tumors. However, its relationship with Gastroenteropancreatic Neuroendocrine Neoplasms Grade 3 (GEP-NENs G3) is unclear. The aim of this study was to characterize the expression of CXCR4 in GEP-NENS and to explore the clinical and prognostic value of CXCR4.MethodsThis study retrospectively collected clinical and pathological data from patients with GEP-NENs who receiving surgery in Qilu Hospital of Shandong University from January 2013 to April 2021, and obtained the overall survival of the patients based on follow-up. Immunohistochemistry (IHC) was performed on pathological paraffin sections to observe CXCR4 staining. Groups were made according to pathological findings. Kaplan-Meier (K-M) curve was used to evaluate prognosis. SPSS 26.0 was used for statistical analysis.Results100 GEP-NENs G3 patients were enrolled in this study. There was a significant difference in primary sites (P=0.002), Ki-67 index (P<0.001), and Carcinoembryonic Antigen (CEA) elevation (P=0.008) between neuroendocrine tumor (NET) G3 and neuroendocrine carcinoma (NEC). CXCR4 was highly expressed only in tumors, low or no expressed in adjacent tissues (P<0.001). The expression level of CXCR4 in NEC was significantly higher than that in NET G3 (P=0.038). The K-M curves showed that there was no significant difference in overall survival between patients with high CXCR4 expression and patients with low CXCR4 expression, either in GEP-NEN G3 or NEC (P=0.920, P=0.842. respectively).ConclusionDifferential expression of CXCR4 was found between tumor and adjacent tissues and between NET G3 and NEC. Our results demonstrated that CXCR4 can be served as a new IHC diagnostic indicator in the diagnosis and differential diagnosis of GEP-NENs G3. Further studies with multi-center, large sample size and longer follow-up are needed to confirm the correlation between CXCR4 expression level and prognosis

    Interrelation between the lipid accumulation product index and diabetic kidney disease in patients with type 2 diabetes mellitus

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    ObjectiveThe purpose of this study was to determine the relation between the lipid accumulation product index (LAPI) and diabetic kidney disease (DKD) in patients with type 2 diabetes mellitus (T2DM).MethodsHerein, 931 patients were enrolled and their data were collected. Then the interrelation between LAPI and DKD was assessed using multivariate logistic regression analyses (LRAs) and by a restricted cubic spline (RCS).ResultsIn total, 931 participants (352 females and 579 males) aged 55 years on average were included in the study. After adjusting for several confounders, the odds ratio for DKD was increased evidently in the third LAPI tertile compared with that in the first LAPI tertile. In addition, the RCS revealed a positive interrelation between LAPI and DKD. In the subgroup analyses, age, sex, hyperlipidemia, hypertension, and HbA1c did not significantly interact with LAPI.ConclusionsLAPI was higher in the DKD group than in the no-DKD group, and LAPI is positively linked with DKD, which may have potential value to diagnose DKD in clinical practice

    Decentralized Eigendecomposition for Online Learning over Graphs

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    We address the problem of decentralized eigenvalue decomposition of a general symmetric matrix that is important, e.g., in Principal Component Analysis. The proposed algorithm only uses local interactions among neighboring agents and is based on the representation of the matrix as a recursive update of rank-one components. This makes the algorithm attractive for online eigenvalue and eigenvector tracking applications. We study the performance of the proposed algorithm in two important application examples: First, we consider the online eigendecomposition of a sample covariance matrix over the network. Then, we investigate the online computation of the spectra of the graph Laplacian that is important in, e.g., graph Fourier analysis and graph-dependent filter design. Simulation results reveal that the proposed algorithm outperforms existing decentralized algorithms both in terms of estimation accuracy as well as communication cost
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