Compared Insights on Machine-Learning Anomaly Detection for Process Control Feature

Anomaly detection is becoming increasingly significant in industrial cyber security, and different machine-learning algorithms have been generally acknowledged as various effective intrusion detection engines to successfully identify cyber attacks. However, different machine-learning algorithms may exhibit their own detection effects even if they analyze the same feature samples. As a sequence, after developing one feature generation approach, the most effective and applicable detection engines should be desperately selected by comparing distinct properties of each machine-learning algorithm. Based on process control features generated by directed function transition diagrams, this paper introduces five different machine-learning algorithms as alternative detection engines to discuss their matching abilities. Furthermore, this paper not only describes some qualitative properties to compare their advantages and disadvantages, but also gives an in-depth and meticulous research on their detection accuracies and consuming time. In the verified experiments, two attack models and four different attack intensities are defined to facilitate all quantitative comparisons, and the impacts of detection accuracy caused by the feature parameter are also comparatively analyzed. All experimental results can clearly explain that SVM (Support Vector Machine) and WNN (Wavelet Neural Network) are suggested as two applicable detection engines under differing cases

WindMill: A Parameterized and Pluggable CGRA Implemented by DIAG Design Flow

With the cross-fertilization of applications and the ever-increasing scale of models, the efficiency and productivity of hardware computing architectures have become inadequate. This inadequacy further exacerbates issues in design flexibility, design complexity, development cycle, and development costs (4-d problems) in divergent scenarios. To address these challenges, this paper proposed a flexible design flow called DIAG based on plugin techniques. The proposed flow guides hardware development through four layers: definition(D), implementation(I), application(A), and generation(G). Furthermore, a versatile CGRA generator called WindMill is implemented, allowing for agile generation of customized hardware accelerators based on specific application demands. Applications and algorithm tasks from three aspects is experimented. In the case of reinforcement learning algorithm, a significant performance improvement of $2.3\times$ compared to GPU is achieved.Comment: 7 pages, 10 figure

Lack of evidence of hepatitis in patients with oral lichen planus in China: a case control study

Background: China has been one of the countries with high prevalence of chronic hepatitis B virus (HBV) and hepatitis C virus (HCV) liver disease. And lichen planus is an extrahepatic manifestation of patients with chronic HCV infection. This case-control study was conducted to investigate the relationship between oral lichen planus (OLP) and HBV/HCV infection in China. Material and Methods: A total of 776 patients, including 150 patients with OLP (Group OLP), 429 inpatients from the Trauma Ward of Oral and Maxillofacial Surgery Department (Group A), 110 patients with other oral mucosal diseases, but without a reported association with HCV infection (Group B) and 87 patients with oral lichenoid lesion (Group OLL), were compared with their seroprevalence of anti-HCV antibody (HCVAb), hepatitis B surface antigen (HBsAg) and the parameters of liver functions. Moreover, the clinical characteristics of OLP were also observed, such as gender, age, chief complaint, course of the disease, clinical type, sites involved and so on. Results: The positive rates of HCVAb and HBsAg in OLP patients were 0.7% and 4%, respectively. Neither HCVAb nor HBsAg was associated with OLP as demonstrated by both the univariate and the multivariate analyses. The clinical features and liver functions of OLP patients with negative or positive HBsAg were nearly the same. Conclusions: Our findings verify that there is no association between OLP and hepatitis and there is no need to run a screening test for HCV or HBV in OLP patients in Chin

Maternal Diet Intervention Before Pregnancy Primes Offspring Lipid Metabolism in Liver

Nonalcoholic fatty liver disease (NAFLD) has a developmental origin and is influenced in utero. We aimed to evaluate if maternal diet intervention before pregnancy would be beneficial to reduce the risk of offspring NAFLD. In our study, female mice were either on a normal-fat diet (NF group), or a high-fat diet for 12 weeks and continued on this diet throughout pregnancy and lactation (HF group), or switched from HF-to-NF diet 1 week (H1N group), or 9 weeks (H9N group) before pregnancy. Compared with the NF offspring, the H1N and HF, but not the H9N offspring, displayed more severe hepatic steatosis and glucose intolerance. More specifically, an abnormal blood lipid panel was seen in the H1N offspring and abnormal hepatic free fatty acid composition was present in both the HF and H1N offspring, while the H9N offspring displayed both at normal levels. These physiological changes were associated with desensitized hepatic insulin/AKT signaling, increased expression of genes and proteins for de novo lipogenesis and cholesterol synthesis, decreased expression of genes and proteins for fatty acid oxidation, increased Pcsk9 expression, and hypoactivation of 5' AMP-activated protein kinase (AMPK) signaling in the HF and H1N offspring. However, these effects were completely or partially rescued in the H9N offspring. In summary, we found that early maternal diet intervention is effective in reducing the risk of offspring NAFLD caused by maternal HF diet. These findings provide significant support to develop effective diet intervention strategies and policies for prevention of obesity and NAFLD to promote optimal health outcomes for mothers and children

Evaluating the efficiency of a nomogram based on the data of neurosurgical intensive care unit patients to predict pulmonary infection of multidrug-resistant Acinetobacter baumannii

BackgroundPulmonary infection caused by multidrug-resistant Acinetobacter baumannii (MDR-AB) is a common and serious complication after brain injury. There are no definitive methods for its prediction and it is usually accompanied by a poor prognosis. This study aimed to construct and evaluate a nomogram based on patient data from the neurosurgical intensive care unit (NSICU) to predict the probability of MDR-AB pulmonary infection.MethodsIn this study, we retrospectively collected patient clinical profiles, early laboratory test results, and doctors’ prescriptions (66 variables). Univariate and backward stepwise regression analyses were used to screen the variables to identify predictors, and a nomogram was built in the primary cohort based on the results of a logistic regression model. Discriminatory validity, calibration validity, and clinical utility were evaluated using validation cohort 1 based on receiver operating characteristic curves, calibration curves, and decision curve analysis (DCA). For external validation based on predictors, we prospectively collected information from patients as validation cohort 2.ResultsAmong 2115 patients admitted to the NSICU between December 1, 2019, and December 31, 2021, 217 were eligible for the study, including 102 patients with MDR-AB infections (102 cases) and 115 patients with other bacterial infections (115 cases). We randomly categorized the patients into the primary cohort (70%, N=152) and validation cohort 1 (30%, N=65). Validation cohort 2 consisted of 24 patients admitted to the NSICU between January 1, 2022, and March 31, 2022, whose clinical information was prospectively collected according to predictors. The nomogram, consisting of only six predictors (age, NSICU stay, Glasgow Coma Scale, meropenem, neutrophil to lymphocyte ratio, platelet to lymphocyte ratio), had significantly high sensitivity and specificity (primary cohort AUC=0.913, validation cohort 1 AUC=0.830, validation cohort 2 AUC=0.889) for early identification of infection and had great calibration (validation cohort 1,2 P=0.3801, 0.6274). DCA confirmed that the nomogram is clinically useful.ConclusionOur nomogram could help clinicians make early predictions regarding the onset of pulmonary infection caused by MDR-AB and implement targeted interventions

Genetic Associations and Architecture of Asthma-COPD Overlap

BACKGROUND: Some people have characteristics of both asthma and COPD (asthma-COPD overlap), and evidence suggests they experience worse outcomes than those with either condition alone. RESEARCH QUESTION: What is the genetic architecture of asthma-COPD overlap, and do the determinants of risk for asthma-COPD overlap differ from those for COPD or asthma? STUDY DESIGN AND METHODS: We conducted a genome-wide association study in 8,068 asthma-COPD overlap case subjects and 40,360 control subjects without asthma or COPD of European ancestry in UK Biobank (stage 1). We followed up promising signals (P < 5 x 10(-6)) that remained associated in analyses comparing (1) asthma-COPD overlap vs asthma-only control subjects, and (2) asthma-COPD overlap vs COPD-only control subjects. These variants were analyzed in 12 independent cohorts (stage 2). RESULTS: We selected 31 independent variants for further investigation in stage 2, and discovered eight novel signals (P < 5 x 10(-8)) for asthma-COPD overlap (meta-analysis of stage 1 and 2 studies). These signals suggest a spectrum of shared genetic influences, some predominantly influencing asthma (FAM105A, GLB1, PHB, TSLP), others predominantly influencing fixed airflow obstruction (IL17RD, C5orf56, HLA-DQB1). One intergenic signal on chromosome 5 had not been previously associated with asthma, COPD, or lung function. Subgroup analyses suggested that associations at these eight signals were not driven by smoking or age at asthma diagnosis, and in phenome-wide scans, eosinophil counts, atopy, and asthma traits were prominent. INTERPRETATION: We identified eight signals for asthma-COPD overlap, which may represent loci that predispose to type 2 inflammation, and serious long-term consequences of asthma.Peer reviewe

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals &lt;1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Genetic Associations and Architecture of Asthma-COPD Overlap

BackgroundSome people have characteristics of both asthma and COPD (asthma-COPD overlap), and evidence suggests they experience worse outcomes than those with either condition alone.Research QuestionWhat is the genetic architecture of asthma-COPD overlap, and do the determinants of risk for asthma-COPD overlap differ from those for COPD or asthma?Study Design and MethodsWe conducted a genome-wide association study in 8,068 asthma-COPD overlap case subjects and 40,360 control subjects without asthma or COPD of European ancestry in UK Biobank (stage 1). We followed up promising signals (P –6) that remained associated in analyses comparing (1) asthma-COPD overlap vs asthma-only control subjects, and (2) asthma-COPD overlap vs COPD-only control subjects. These variants were analyzed in 12 independent cohorts (stage 2).ResultsWe selected 31 independent variants for further investigation in stage 2, and discovered eight novel signals (P –8) for asthma-COPD overlap (meta-analysis of stage 1 and 2 studies). These signals suggest a spectrum of shared genetic influences, some predominantly influencing asthma (FAM105A, GLB1, PHB, TSLP), others predominantly influencing fixed airflow obstruction (IL17RD, C5orf56, HLA-DQB1). One intergenic signal on chromosome 5 had not been previously associated with asthma, COPD, or lung function. Subgroup analyses suggested that associations at these eight signals were not driven by smoking or age at asthma diagnosis, and in phenome-wide scans, eosinophil counts, atopy, and asthma traits were prominent.InterpretationWe identified eight signals for asthma-COPD overlap, which may represent loci that predispose to type 2 inflammation, and serious long-term consequences of asthma.</p