Fine-Grained Multivariate Time Series Anomaly Detection in IoT

Sensors produce a large amount of multivariate time series data to record the states of Internet of Things(IoT)systems.Multivariate time series timestamp anomaly detection(TSAD)can identify timestamps of attacks and malfunctions.However,it is necessary to determine which sensor or indicator is abnormal to facilitate a more detailed diagnosis,a process referred to as fine-grained anomaly detection(FGAD).Although further FGAD can be extended based on TSAD methods,existing works do not provide a quantitative evaluation,and the performance is unknown.Therefore,to tackle the FGAD problem,this paper first verifies that the TSAD methods achieve low performance when applied to the FGAD task directly because of the excessive fusion of features and the ignoring of the relationship’s dynamic changes between indicators.Accordingly,this paper proposes a mul-tivariate time series fine-grained anomaly detection(MFGAD)framework.To avoid excessive fusion of features,MFGAD constructs two sub-models to independently identify the abnormal timestamp and abnormal indicator instead of a single model and then combines the two kinds of abnormal results to detect the fine-grained anomaly.Based on this framework,an algorithm based on Graph Attention Neural Network(GAT)and Attention Convolutional Long-Short Term Memory(A-ConvLSTM)is proposed,in which GAT learns temporal features of multiple indicators to detect abnormal timestamps and A-ConvLSTM captures the dynamic relationship between indicators to identify abnormal indicators.Extensive simulations on a real-world dataset demonstrate that the proposed algorithm can achieve a higher F1 score and hit rate than the extension of existing TSAD methods with the benefit of two independent sub-models for timestamp and indicator detection.

Connectome-based predictive modelling can predict follow-up craving after abstinence in individuals with opioid use disorders

Background Individual differences have been detected in individuals with opioid use disorders(OUD)in rehabilitation following protracted abstinence.Recent studies suggested that prediction models were effective for individual-level prognosis based on neuroimage data in substance use disorders(SUD).Aims This prospective cohort study aimed to assess neuroimaging biomarkers for individual response to protracted abstinence in opioid users using connectome-based predictive modelling(CPM).Methods One hundred and eight inpatients with OUD underwent structural and functional magnetic resonance imaging(fMRI)scans at baseline.The Heroin Craving Questionnaire(HCQ)was used to assess craving levels at baseline and at the 8-month follow-up of abstinence.CPM with leave-one-out cross-validation was used to identify baseline networks that could predict follow-up HCQ scores and changes in HCQ(HCQtolow V-up-HCQpa baseline).Then,the follow-up aseline predictive ability of identified networks was tested in a separate,heterogeneous sample of methamphetamine individuals who underwent MRI scanning before abstinence for SUD.Results CPM could predict craving changes induced by long-term abstinence,as shown by a significant correlation between predicted and actual HCQ fllow-up(r=0.417,p<0.001)and changes in HCQ(negative:r=0.334,p=0.002;positive:r=0.233,p=0.038).Identified craving-related prediction networks included the somato-motor network(SMN),salience network(SALN),default mode network(DMN),medial frontal network,visual network and auditory network.In addition,decreased connectivity of frontal-parietal network(FPN)-SMN,FPN-DMN and FPN-SALN and increased connectivity of subcortical network(SCN)-DMN,SCN-SALNandSCN-SMN were positively correlated with craving levels.Conclusions These findings highlight the potential applications of CPM to predict the craving level of individuals after protracted abstinence,as well as the generalisation ability;the identified brain networks might be the focus of innovative therapies in the future.

DFT Studies on the Stoichiometric Thorium Oxide Clusters（ThO2）n（n = 1～5）: Electronic and Structural Properties

Density functional theory(DFT) calculations are performed to investigate the electronic and structural properties of the stoichiometric thorium oxide clusters(ThO2)n-/0(n = 1~5). Generalized Koopmans' theorem is applied to predict the vertical detachment energies(VDEs)which are used to simulate the anionic photoelectron spectra(PES). Molecular orbital analyses are performed as well to analyze the chemical bonding in these thorium oxide clusters. The results show that the ground states of(ThO2)_n-/0(n = 1~5) clusters prefer the low-spin structures. With increasing of the cluster size(n), the structure parameters of(ThO2)n-/0(n = 1~5) gradually evolve toward bulk thorium oxide species. It shows that both the coordination number and the average bond length increase gradually in(ThO2)n-/0(n = 1~5) to approach that of ThO2 bulk. What's more, the vibration frequencies of Th=O double bonds are found to be decreasing along with the increased cluster size.

Evaluating accuracy of Hessian-based predictor-corrector integrators

Direct dynamics simulations are a useful and general approach for studying the atomistic properties of complex chemical systems because they do not require fitting an analytic potential energy function.Hessian-based predictor-corrector integrators are a widely used approach for calculating the trajectories of moving atoms in direct dynamics simulations.We employ a monodromy matrix to propose a tool for evaluating the accuracy of integrators in the trajectory calculation.We choose a general velocity Verlet as a different object.We also simulate molecular with hydrogen(CO_2) and molecular with hydrogen(H_2O) motions.Comparing the eigenvalues of monodromy matrix,many simulations show that Hessian-based predictor-corrector integrators perform well for Hessian updates and non-Hessian updates.Hessian-based predictor-corrector integrator with Hessian update has a strong performance in the H_2O simulations.Hessian-based predictor-corrector integrator with Hessian update has a strong performance when the integrating step of the velocity Verlet approach is tripled for the predicting step.In the CO_2 simulations,a strong performance occurs when the integrating step is a multiple of five.

A Broadcast Storm Detection and Treatment Method Based on Situational Awareness

At present,the research of blockchain is very popular,but the practical application of blockchain is very few.The main reason is that the concurrency of blockchain is not enough to support application scenarios.After that,applications such as Intervalue increase the concurrency of blockchain transactions.However,due to the problems of network bandwidth and algorithm performance,there is always a broadcast storm,which affects the normal use of nodes in the whole network.However,the emergence of broadcast storms needs to rely on the node itself,which may be very slow.Even if developers debug the corresponding code,they cannot conduct an effective test in the whole network.Broadcast storm problem mainly occurs in scenarios with large transaction volume,such as the financial industry.Due to its characteristics,the concurrency of transactions in the financial industry will increase at a certain time.If there is no effective algorithm to deal with it,the broadcast storm will be triggered and the whole network will be paralyzed.To solve the problem of the broadcast storm,this paper combines blockchain,peer-to-peer network,artificial intelligence,and other technologies,and proposes a broadcast storm detection and processing method based on situation awareness.The purpose is to cut off the further spread of broadcast storms from the node itself and maintain the normal operation of the whole network nodes.

Reflections on “Human Rights” and “Sense of Well-being”

Since the conceptual germination of 'human rights' in the modern age,the controversy over it and its connotations have been constant.Scholars at home and abroad either attempt to interpret the connotation of human rights by emphasizing the real social foundation of human rights from a political and economic perspective,or elaborate on the essence of human rights by focusing

Photoinduced bismuth vanadate-catalyzed C(sp^(2))-H functionalization

Visible light-induced organic reactions have gained much attention in recent years due to their mild conditions and high efficiency[1,2].In this context,many efficient photocatalysts including transition metal complexes and organic dyes have been developed for various organic transformations.

Digital Trade Rules and the Position of Chinese Enterprises in the Global Value Chain

Digital trade rules and higher positions of enterprises in the global value chain(GVC)are both important topics in the context of high-quality economic development.This paper refers to the data of RTA digital trade rules concluded by China in the TAPED database in 2000-2014 and the matched data in the WIOD database,the China Customs Import and Export Database and the China Industrial Enterprise Database to investigate the effects of digital trade rules on Chinese enterprises as to their ascending GVC positions.It finds that signing the RTA digital trade rules can steadily and significantly promote the position ascendance;compared with the digitalization rules on trading objects,signing the digitalization rules on trade modes produces greater effects of driving up the positions,which are realized mainly via the three channels of advancing cross-border flow of R&D factors,promoting corporate digital transformation,and improving professional management.Digital trade rules that are horizontally broader and vertically deeper are in greater favor of Chinese enterprises for ascending in the global value chain,which is especially evident among those in digital industry and processing trade.During the negotiations of digital trade rules,it's imperative to pay close attention to the rules on e-commerce cooperation,awareness of e-commerce importance,intellectual property protection,attempts in big data-related trade in goods,and cross-border data flow,so as to secure the core interests of Chinese enterprises in gaining higher positions.This paper offers great policy implications as to how to sign digital trade rules by China in the future and how to select partners in greater support for Chinese enterprises to ascend to the middle and high end of the global value chain.