Big Data Analysis-based Security Situational Awareness for Smart Grid

Advanced communications and data processing technologies bring great benefits to the smart grid. However, cyber-security threats also extend from the information system to the smart grid. The existing security works for smart grid focus on traditional protection and detection methods. However, a lot of threats occur in a very short time and overlooked by exiting security components. These threats usually have huge impacts on smart gird and disturb its normal operation. Moreover, it is too late to take action to defend against the threats once they are detected, and damages could be difficult to repair. To address this issue, this paper proposes a security situational awareness mechanism based on the analysis of big data in the smart grid. Fuzzy cluster based analytical method, game theory and reinforcement learning are integrated seamlessly to perform the security situational analysis for the smart grid. The simulation and experimental results show the advantages of our scheme in terms of high efficiency and low error rate for security situational awareness

Detecting phone-related pedestrian distracted behaviours via a two-branch convolutional neural network

The distracted phone-use behaviours among pedestrians, like Texting, Game Playing and Phone Calls, have caused increasing fatalities and injuries. However, the research of phonerelated distracted behaviour by pedestrians has not been systemically studied. It is desired to improve both the driving and pedestrian safety by automatically discovering the phonerelated pedestrian distracted behaviours. Herein, a new computer vision-based method is proposed to detect the phone-related pedestrian distracted behaviours from a view of intelligent and autonomous driving. Specifically, the first end-to-end deep learning based Two-Branch Convolutional Neural Network (CNN) is designed for this task. Taking one synchronised image pair by two front on-car GoPro cameras as the inputs, the proposed two-branch CNN will extract features for each camera, fuse the extracted features and perform a robust classification. This method can also be easily extended to video-based classification by confidence accumulation and voting. A new benchmark dataset of 448 synchronised video pairs of 53,760 images collected on a vehicle is proposed for this research. The experimental results show that using two synchronised cameras obtained better performance than using one single camera. Finally, the proposed method achieved an overall best classification accuracy of 84.3% on the new benchmark when compared to other methods

A screening identifies harmine as a novel antibacterial compound against Ralstonia solanacearum

Ralstonia solanacearum, the causal agent of bacterial wilt, is a devastating plant pathogenic bacterium that infects more than 450 plant species. Until now, there has been no efficient control strategy against bacterial wilt. In this study, we screened a library of 100 plant-derived compounds for their antibacterial activity against R. solanacearum. Twelve compounds, including harmine, harmine hydrochloride, citral, vanillin, and vincamine, suppressed bacterial growth of R. solanacearum in liquid medium with an inhibition rate higher than 50%. Further focus on harmine revealed that the minimum inhibitory concentration of this compound is 120 mg/L. Treatment with 120 mg/L of harmine for 1 and 2 h killed more than 90% of bacteria. Harmine treatment suppressed the expression of the virulence-associated gene xpsR. Harmine also significantly inhibited biofilm formation by R. solanacearum at concentrations ranging from 20 mg/L to 60 mg/L. Furthermore, application of harmine effectively reduced bacterial wilt disease development in both tobacco and tomato plants. Collectively, our results demonstrate the great potential of plant-derived compounds as antibacterial agents against R. solanacearum, providing alternative ways for the efficient control of bacterial wilt

Impacts of climate change on Tibetan lakes: patterns and processes

High-altitude inland-drainage lakes on the Tibetan Plateau (TP), the earth’s third pole, are very sensitive to climate change. Tibetan lakes are important natural resources with important religious, historical, and cultural significance. However, the spatial patterns and processes controlling the impacts of climate and associated changes on Tibetan lakes are largely unknown. This study used long time series and multi-temporal Landsat imagery to map the patterns of Tibetan lakes and glaciers in 1977, 1990, 2000, and 2014, and further to assess the spatiotemporal changes of lakes and glaciers in 17 TP watersheds between 1977 and 2014. Spatially variable changes in lake and glacier area as well as climatic factors were analyzed. We identified four modes of lake change in response to climate and associated changes. Lake expansion was predominantly attributed to increased precipitation and glacier melting, whereas lake shrinkage was a main consequence of a drier climate or permafrost degradation. These findings shed new light on the impacts of recent environmental changes on Tibetan lakes. They suggest that protecting these high-altitude lakes in the face of further environmental change will require spatially variable policies and management measures

Comparing the efficacy and safety of medications in adults with hypertrophic cardiomyopathy: a systematic review and network meta-analysis

BackgroundHypertrophic cardiomyopathy (HCM) is the most common genetic heart disease. The purpose of this study was to evaluate the efficacy and safety of several medications and recommend better drug treatments for adults with HCM.MethodsA review of PubMed, Embase, the Cochrane Controlled Register of Trials (CENTRAL), ClinicalTrials.gov and CNKI databases was conducted for studies on the efficacy and safety of drugs for adults with HCM. A frequentist random effects model was used in this network analysis.ResultsThis network meta-analysis included 7 studies assessing seven medications, 6 studies evaluating monotherapy and 1 study evaluating combination therapy. Based on the network meta-analysis results, xiaoxinbi formula plus metoprolol (MD −56.50% [−72.43%, −40.57%]), metoprolol (MD −47.00% [−59.07%, −34.93%]) and mavacamten (MD −34.50% [−44.75%, −24.25%]) significantly reduced the resting left ventricular outflow tract gradient (LVOTG) in comparison with placebo. Resting LVOTG could also be reduced with N-acetylcysteine (NAC). The incidence of adverse drug reactions was not significantly different between the placebo group and the treatment group.ConclusionFor adults with HCM, the top 4 treatments included xiaoxinbi formula plus metoprolol, metoprolol, mavacamten and NAC.Systematic Review Registration: [https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=374222], identifier [CRD42022374222]

What makes efficient circularly polarised luminescence in the condensed phase: aggregation-induced circular dichroism and light emission

In this contribution, we conceptually present a new avenue to construction of molecular functional materials with high performance of circularly polarised luminescence (CPL) in the condensed phase. A molecule (1) containing luminogenic silole and chiral sugar moieties was synthesized and thoroughly characterized. In a solution of 1, no circular dichroism (CD) and fluorescence emission are observed, but upon molecular aggregation, both the CD and fluorescence are simultaneously turned on, showing aggregation-induced CD (AICD) and emission (AIE) effects. The AICD effect is supported by the fact that the molecules readily assemble into right-handed helical nanoribbons and superhelical ropes when aggregated. The AIE effect boosts the fluorescence quantum efficiency (ΦF) by 136 fold (ΦF, ∼0.6% in the solution versus ∼81.3% in the solid state), which surmounts the serious limitations of aggregation-caused quenching effect encountered by conventional luminescent materials. Time-resolved fluorescence study and theoretical calculation from first principles conclude that restriction of the low-frequency intramolecular motions is responsible for the AIE effect. The helical assemblies of 1 prefer to emit right-handed circularly polarised light and display large CPL dissymmetry factors (gem), whose absolute values are in the range of 0.08–0.32 and are two orders of magnitude higher than those of commonly reported organic materials. We demonstrate for the first time the use of a Teflon-based microfluidic technique for fabrication of the fluorescent pattern. This shows the highest gem of −0.32 possibly due to the enhanced assembling order in the confined microchannel environment. The CPL performance was preserved after more than half year storage under ambient conditions, revealing the excellent spectral stability. Computational simulation was performed to interpret how the molecules in the aggregates interact with each other at the molecular level. Our designed molecule represents the desired molecular functional material for generating efficient CPL in the solid state, and the current study shows the best results among the reported organic conjugated molecular systems in terms of emission efficiency, dissymmetry factor, and spectral stability

Association between dietary habits and the risk of migraine: a Mendelian randomization study

ObjectiveThe important contribution of dietary triggers to migraine pathogenesis has been recognized. However, the potential causal roles of many dietary habits on the risk of migraine in the whole population are still under debate. The objective of this study was to determine the potential causal association between dietary habits and the risk of migraine (and its subtypes) development, as well as the possible mediator roles of migraine risk factors.MethodsBased on summary statistics from large-scale genome-wide association studies, we conducted two-sample Mendelian randomization (MR) and bidirectional MR to investigate the potential causal associations between 83 dietary habits and migraine and its subtypes, and network MR was performed to explore the possible mediator roles of 8 migraine risk factors.ResultsAfter correcting for multiple testing, we found evidence for associations of genetically predicted coffee, cheese, oily fish, alcohol (red wine), raw vegetables, muesli, and wholemeal/wholegrain bread intake with decreased risk of migraine, those odds ratios ranged from 0.78 (95% CI: 0.63–0.95) for overall cheese intake to 0.61 (95% CI: 0.47–0.80) for drinks usually with meals among current drinkers (yes + it varies vs. no); while white bread, cornflakes/frosties, and poultry intake were positively associated with the risk of migraine. Additionally, genetic liability to white bread, wholemeal/wholegrain bread, muesli, alcohol (red wine), cheese, and oily fish intake were associated with a higher risk of insomnia and (or) major depression disorder (MDD), each of them may act as a mediator in the pathway from several dietary habits to migraine. Finally, we found evidence of a negative association between genetically predicted migraine and drinking types, and positive association between migraine and cups of tea per day.SignificanceOur study provides evidence about association between dietary habits and the risk of migraine and demonstrates that some associations are partly mediated through one or both insomnia and MDD. These results provide new insights for further nutritional interventions for migraine prevention

TileProbe: modeling tiling array probe effects using publicly available data

Motivation: Individual probes on an Affymetrix tiling array usually behave differently. Modeling and removing these probe effects are critical for detecting signals from the array data. Current data processing techniques either require control samples or use probe sequences to model probe-specific variability, such as with MAT. Although the MAT approach can be applied without control samples, residual probe effects continue to distort the true biological signals