Dynamic Circular Network-Based Federated Dual-View Learning for Multivariate Time Series Anomaly Detection

Multivariate time-series data exhibit intricate correlations in both temporal and spatial dimensions. However, existing network architectures often overlook dependencies in the spatial dimension and struggle to strike a balance between long-term and short-term patterns when extracting features from the data. Furthermore, industries within the business community are hesitant to share their raw data, which hinders anomaly prediction accuracy and detection performance. To address these challenges, the authors propose a dynamic circular network-based federated dual-view learning approach. Experimental results from four open-source datasets demonstrate that the method outperforms existing methods in terms of accuracy, recall, and F1_score for anomaly detection

The androgen receptor plays different roles in macrophage-induced proliferation in prostate stromal cells between transitional and peripheral zones of benign prostatic hypertrophy

Macrophages play a critical role in the process of excessive stromal proliferation of benign prostatic hyperplasia (BPH). In our previous study, we used a BPH mouse model to elucidate a potential mechanism whereby macrophage infiltration promotes stromal cell proliferation in the prostate via the androgen receptor (AR)/inflammatory cytokine CCL3-dependent pathway. In our present study, we used the co-culture system of human macrophages and various prostatic zone stromal cells to further demonstrate that infiltrating macrophages promote prostatic stromal cell proliferation through stromal AR-dependent pathways, and we show that the stroma of TZ and PZ respond to macrophages differently because of differences in stromal AR signaling; this could possibly be one of the key pathways for stromal expansion during BPH development and progression. We hypothesize that AR and different downstream inflammatory mediators between TZ and PZ could serve as potential targets for the future design of therapeutic agents for BPH and our results provide significant insights into the search for targeted therapeutic approaches to battle BPH

COVID-19 in Japan: What could happen in the future? (Recent developments on inverse problems for partial differential equations and their applications)

This paper was finished in February, 2020 and posted in MedRxiv on Feb. 28th, 2020.COVID-19 has been impacting on the whole world critically and constantly Since December 2019. We have independently developed a novel statistical time delay dynamic model on the basis of the distribution models from CCDC. Based only on the numbers of confirmed cases in different regions in China, the model can clearly reveal that the containment of the epidemic highly depends on early and effective isolation. We apply the model on the epidemic in Japan and conclude that there could be a rapid outbreak in Japan if no effective quarantine measures are carried out immediately

Evaluating Alternative Ebullition Models for Predicting Peatland Methane Emission and Its Pathways via Data–Model Fusion

Understanding the dynamics of peatland methane (CH4) emissions and quantifying sources of uncertainty in estimating peatland CH4 emissions are critical for mitigating climate change. The relative contributions of CH4 emission pathways through ebullition, plant-mediated transport, and diffusion, together with their different transport rates and vulnerability to oxidation, determine the quantity of CH4 to be oxidized before leaving the soil. Notwithstanding their importance, the relative contributions of the emission pathways are highly uncertain. In particular, the ebullition process is more uncertain and can lead to large uncertainties in modeled CH4 emissions. To improve model simulations of CH4 emission and its pathways, we evaluated two model structures: (1) the ebullition bubble growth volume threshold approach (EBG) and (2) the modified ebullition concentration threshold approach (ECT) using CH4 flux and concentration data collected in a peatland in northern Minnesota, USA. When model parameters were constrained using observed CH4 fluxes, the CH4 emissions simulated by the EBG approach (RMSE = 0.53) had a better agreement with observations than the ECT approach (RMSE = 0.61). Further, the EBG approach simulated a smaller contribution from ebullition but more frequent ebullition events than the ECT approach. The EBG approach yielded greatly improved simulations of pore water CH4 concentrations, especially in the deep soil layers, compared to the ECT approach. When constraining the EBG model with both CH4 flux and concentration data in model–data fusion, uncertainty of the modeled CH4 concentration profiles was reduced by 78 % to 86 % in comparison to constraints based on CH4 flux data alone. The improved model capability was attributed to the well-constrained parameters regulating the CH4 production and emission pathways. Our results suggest that the EBG modeling approach better characterizes CH4 emission and underlying mechanisms. Moreover, to achieve the best model results both CH4 flux and concentration data are required to constrain model parameterization

Evaluating alternative ebullition models for predicting peatland methane emission and its pathways via data–model fusion

Understanding the dynamics of peatland methane (CH4) emissions and quantifying sources of uncertainty in estimating peatland CH4 emissions are critical for mitigating climate change. The relative contributions of CH4 emission pathways through ebullition, plant-mediated transport, and diffusion, together with their different transport rates and vulnerability to oxidation, determine the quantity of CH4 to be oxidized before leaving the soil. Notwithstanding their importance, the relative contributions of the emission pathways are highly uncertain. In particular, the ebullition process is more uncertain and can lead to large uncertainties in modeled CH4 emissions. To improve model simulations of CH4 emission and its pathways, we evaluated two model structures: (1) the ebullition bubble growth volume threshold approach (EBG) and (2) the modified ebullition concentration threshold approach (ECT) using CH4 flux and concentration data collected in a peatland in northern Minnesota, USA. When model parameters were constrained using observed CH4 fluxes, the CH4 emissions simulated by the EBG approach (RMSE = 0.53) had a better agreement with observations than the ECT approach (RMSE = 0.61). Further, the EBG approach simulated a smaller contribution from ebullition but more frequent ebullition events than the ECT approach. The EBG approach yielded greatly improved simulations of pore water CH4 concentrations, especially in the deep soil layers, compared to the ECT approach. When constraining the EBG model with both CH4 flux and concentration data in model–data fusion, uncertainty of the modeled CH4 concentration profiles was reduced by 78 % to 86 % in comparison to constraints based on CH4 flux data alone. The improved model capability was attributed to the well-constrained parameters regulating the CH4 production and emission pathways. Our results suggest that the EBG modeling approach better characterizes CH4 emission and underlying mechanisms. Moreover, to achieve the best model results both CH4 flux and concentration data are required to constrain model parameterization

Evaluating Alternative Ebullition Models for Predicting Peatland Methane Emission and Its Pathways via Data–Model Fusion

Understanding the dynamics of peatland methane (CH4) emissions and quantifying sources of uncertainty in estimating peatland CH4 emissions are critical for mitigating climate change. The relative contributions of CH4 emission pathways through ebullition, plant-mediated transport, and diffusion, together with their different transport rates and vulnerability to oxidation, determine the quantity of CH4 to be oxidized before leaving the soil. Notwithstanding their importance, the relative contributions of the emission pathways are highly uncertain. In particular, the ebullition process is more uncertain and can lead to large uncertainties in modeled CH4 emissions. To improve model simulations of CH4 emission and its pathways, we evaluated two model structures: (1) the ebullition bubble growth volume threshold approach (EBG) and (2) the modified ebullition concentration threshold approach (ECT) using CH4 flux and concentration data collected in a peatland in northern Minnesota, USA. When model parameters were constrained using observed CH4 fluxes, the CH4 emissions simulated by the EBG approach (RMSE = 0.53) had a better agreement with observations than the ECT approach (RMSE = 0.61). Further, the EBG approach simulated a smaller contribution from ebullition but more frequent ebullition events than the ECT approach. The EBG approach yielded greatly improved simulations of pore water CH4 concentrations, especially in the deep soil layers, compared to the ECT approach. When constraining the EBG model with both CH4 flux and concentration data in model–data fusion, uncertainty of the modeled CH4 concentration profiles was reduced by 78 % to 86 % in comparison to constraints based on CH4 flux data alone. The improved model capability was attributed to the well-constrained parameters regulating the CH4 production and emission pathways. Our results suggest that the EBG modeling approach better characterizes CH4 emission and underlying mechanisms. Moreover, to achieve the best model results both CH4 flux and concentration data are required to constrain model parameterization

Contemporary survival and anticoagulation of patients with atrial fibrillation: A community based cohort study in China

BackgroundsThe understanding of death in patients with atrial fibrillation (AF) in China is limited. This study aimed to assess the contemporary survival of AF patients in China and to explore risk factors for deaths.MethodsThis was a prospective community-based cohort study including 559 AF patients, who were followed-up from July 2015 to December 2020.ResultsDuring 66-month follow-up, there were 200 deaths (56.5% cardiovascular, 40.0% non-cardiovascular, and 3.5% unknown causes) among 559 AF patients with the median age of 76 years. The top three causes of death were heart failure (33.0%), ischemic stroke (17.0%) and cancer (16.5%). Multivariate Cox regression analysis indicated baseline variables positively associated with all-cause death were age (HR: 1.10, 95% CI: 1.08–1.13), AF subtype (HR: 1.37, 95% CI: 1.08–1.73), prior myocardial infarction (HR: 3.40, 95% CI: 1.48–7.78), previous tumor (HR: 2.61, 95% CI: 1.37–4.98), hypoglycemic therapy at baseline (HR: 1.81, 95% CI: 1.13–2.91), but body weight (HR: 0.98, 95% CI: 0.97–1.00) and use of calcium channel blocker (CCB) (HR: 0.62, 95% CI: 0.41–0.95) played a protective role to all-cause death. Of patients who were alive at the end of follow-up, 24.0% were on oral anticoagulants (OAC) alone, 4.5% on dual antithrombotic therapy, 33.1% on antiplatelet agents alone and 38.4% weren't on any antithrombotic medication.ConclusionIschemic stroke still remains one of the leading causes of death and OAC is seriously underused in AF patients in China. Independent risk factors for death are age, AF subtype, previous tumor, prior myocardial infarction, hypoglycemic therapy, low body weight and no CCB use.Clinical Trial Registrationhttp://www.chictr.org.cn/ (ChiCTR-ICR-15007036)

Optimized gene editing technology for Drosophila melanogaster using germ line-specific Cas9

The ability to engineer genomes in a specific, systematic, and cost-effective way is critical for functional genomic studies. Recent advances using the CRISPR-associated single-guide RNA system (Cas9/sgRNA) illustrate the potential of this simple system for genome engineering in a number of organisms. Here we report an effective and inexpensive method for genome DNA editing in Drosophila melanogaster whereby plasmid DNAs encoding short sgRNAs under the control of the U6b promoter are injected into transgenic flies in which Cas9 is specifically expressed in the germ line via the nanos promoter. We evaluate the off-targets associated with the method and establish a Web-based resource, along with a searchable, genome-wide database of predicted sgRNAs appropriate for genome engineering in flies. Finally, we discuss the advantages of our method in comparison with other recently published approaches.Multidisciplinary SciencesSCI(E)46ARTICLE4719012-1901711

The influence of abusive supervision on workplace cheating behavior

The paper presents a mediated model based on the self-determination theory, focusing on enterprise management practices, need fulfillment. A total of 204 questionnaires were collected through a survey method, and data analysis was conducted using SPSS 26. The results indicate a significant positive influence of abusive supervision on employee’ cheating behavior. Need fulfillment mediates the relationship between abusive supervision and employee’ cheating behavior. Based on the research findings, leaders should pay attention to their own behavior, treat subordinates well, and prevent the occurrence of employee cheating behavior to enhance organizational effectiveness

HIGH RESOLUTION ASSIGNMENT OF ν14\nu_{14} AND ν16\nu_{16} BANDS IN THE 10 μ\muM FOR TRANS-ACROLEIN

Author Institution: Centre for Laser, Atomic and Molecular Sciences (CLAMS), Dept. of Physical Sciences, Univ. of New Brunswick, Canada E2L 4L5; Steacie Institute for Molecular Sciences, National Research Council of Canada, Ottawa, Canada\hspace{1cm} Acrolein (CH$_2$CHCHO) is one of the four (in addition to methanol CH$_3$OH, acetaldehyde CH$_3$CHO, and 1,3-butadiene CH$_2$CHCHCH$_2$) 2004 target molecules from main- and side-stream (MS and SS) cigarette smoke$^{[1]}$. The present work is aimed at extending the database of high resolution laboratory spectroscopic information on the molecule in the 10 $\mu$m region. \hspace{1cm} We have obtained 10 $\mu$m high resolution spectra from NRC both at room and cooled temperatures at 0.002 cm$^{-1}$ resolution. The spectra cover several vibrational bands including the two dominant ones, the $\nu_{16}$ CH$_2$ out-of-plane rocking and $\nu_{14}$ CH2 twisting. Analyses of the $\nu_{16}$ and $\nu_{14}$ bands are now at advanced stages. More specifically, about 1085 lines have been assigned to the $\nu_{16}$ band for transitions to upper state Ka' = 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 and 10, and about 800 lines have been assigned to the $\nu_{14}$ band for transitions to upper state Ka' = 1, 2, 3, 4, 5, 6, 7 and 8. We have applied an isolated band model to each band using Maki's asymmetric rotor Hamiltonian in which some assigned transitions were removed from our fits. In our analysis, we have encountered challenges due to high line density as well as perturbations. For the latter, J-reduced upper state term values have been obtained and plotted as a function of J, indicating possible interactions among the two states. \hspace{1cm} For intensity information, we have carried out ${ab initio}$ dipole derivative calculations using the procedure explained in Ref. [2] for 1,3-butadiene. A line list with position and intensity has been compiled using the ${ab initio}$ dipole derivatives and the rotational constants obtained from the present work. \hrule \hspace{1cm} \item{[1]} Private communication from Aerodyne Research, Inc., and Phillip Morris Research Center. \item{[2]} Z.D. Sun, Li-Hong Xu, R.M. Lees, X.J. Jiang, S. Perry, N.C. Craig, J. Mol. Struct. 742 (2005) 69-76