Task Scheduling Based on Grey Wolf Optimizer Algorithm for Smart Meter Embedded Operating System

In recent years, with the rapid development of electric power informatization, smart meters are gradually developing towards intelligent IOT. Smart meters can not only measure user status, but also interconnect and communicate with cell phones, smart homes and other cloud devices, and these core functions are completed by the smart meter embedded operating system. Due to the dynamic heterogeneity of the user program side and the system processing side of the embedded system, resource allocation and task scheduling is a challenging problem for embedded operating systems of smart meters. Smart meters need to achieve fast response and shortest completion time for user program side requests, and also need to take into account the load balancing of each processing node to ensure the reliability of smart meter embedded systems. In this paper, based on the advanced Grey Wolf Optimizer, we study the scheduling principle of the service program nodes in the smart meter operating system, and analyze the problems of the traditional scheduling algorithm to find the optimal solution. Compared with traditional algorithms and classical swarm intelligence algorithms, the algorithm proposed in this paper avoids the dilemma of local optimization, can quickly allocate operating system tasks, effectively shorten the time consumption of task scheduling, ensure the real-time performance of multi task scheduling, and achieve the system tuning balance. Finally, the effectiveness of the algorithm is verified by simulation experiments

P3OP^{3}O: Transferring Visual Representations for Reinforcement Learning via Prompting

It is important for deep reinforcement learning (DRL) algorithms to transfer their learned policies to new environments that have different visual inputs. In this paper, we introduce Prompt based Proximal Policy Optimization ($P^{3}O$), a three-stage DRL algorithm that transfers visual representations from a target to a source environment by applying prompting. The process of $P^{3}O$ consists of three stages: pre-training, prompting, and predicting. In particular, we specify a prompt-transformer for representation conversion and propose a two-step training process to train the prompt-transformer for the target environment, while the rest of the DRL pipeline remains unchanged. We implement $P^{3}O$ and evaluate it on the OpenAI CarRacing video game. The experimental results show that $P^{3}O$ outperforms the state-of-the-art visual transferring schemes. In particular, $P^{3}O$ allows the learned policies to perform well in environments with different visual inputs, which is much more effective than retraining the policies in these environments.Comment: This paper has been accepted to be presented at the upcoming IEEE International Conference on Multimedia & Expo (ICME) in 202

Discontiguous or Contiguous Spread Patterns Affect the Functional Staging in Patients With Sporadic Amyotrophic Lateral Sclerosis

Objective: This study aimed to investigate whether the spread pattern affects functional staging in amyotrophic lateral sclerosis (ALS). We examined the spreading patterns of disease following symptom onset and the affected regions in ALS using electromyography.Methods: This study reviewed the medical records of 103 patients with sporadic ALS in the Second Hospital of Hebei Medical University from 2012 to 2017. According to the clinical manifestation and the distribution of the affected regions on electromyography, spread patterns were classified as discontiguous or contiguous. The patients were graded according to the ALS-Milano-Torino staging (MITOS) system.Results: The clinical spread patterns were contiguous in 91.5% of patients and discontiguous in 8.5% of patients. The electrophysiological spread patterns were contiguous in 87.4% of patients and discontiguous in 12.6% of patients. Sex, age, or delay in diagnosis did not affect the clinical or electrophysiological spread patterns. No significant correlation was observed between the clinical classification and the ALS-MITOS grade, but the electrophysiological spread was significantly correlated with the ALS-MITOS.Conclusion: This study provides evidence that not all ALS patients show contiguous clinical or electrophysiological spread patterns. The electrophysiological spread pattern can affect the functional staging in ALS patients

Analysis of Time Series Gene Expression and DNA Methylation Reveals the Molecular Features of Myocardial Infarction Progression

Myocardial infarction (MI) is one of the deadliest diseases in the world, and the changes at the molecular level after MI and the DNA methylation features are not clear. Understanding the molecular characteristics of the early stages of MI is of significance for the treatment of the disease. In this study, RNA-seq and MeDIP-seq were performed on heart tissue from mouse models at multiple time points (0 h, 10 min, 1, 6, 24, and 72 h) to explore genetic and epigenetic features that influence MI progression. Analysis based on a single point in time, the number of differentially expressed genes (DEGs) and differentially methylated regions (DMRs) increased with the time of myocardial infarction, using 0 h as a control group. Moreover, within 10 min of MI onset, the cells are mainly in immune response, and as the duration of MI increases, apoptosis begins to occur. Analysis based on time series data, the expression of 1012 genes was specifically downregulated, and these genes were associated with energy metabolism. The expression of 5806 genes was specifically upregulated, and these genes were associated with immune regulation, inflammation and apoptosis. Fourteen transcription factors were identified in the genes involved in apoptosis and inflammation, which may be potential drug targets. Analysis based on MeDIP-seq combined with RNA-seq methodology, focused on methylation at the promoter region. GO revealed that the downregulated genes with hypermethylation at 72 h were enriched in biological processes such as cardiac muscle contraction. In addition, the upregulated genes with hypomethylation at 72 h were enriched in biological processes, such as cell-cell adhesion, regulation of the apoptotic signaling pathway and regulation of angiogenesis. Among these genes, the Tnni3 gene was also present in the downregulated model. Hypermethylation of Tnni3 at 72 h after MI may be an important cause of exacerbation of MI

Myocardial tissue and metabolism characterization in men with alcohol consumption by cardiovascular magnetic resonance and 11C-acetate PET/CT

Background: Chronic alcohol consumption initially leads to asymptomatic left ventricular dysfunction, but can result in myocardial impairment and heart failure if ongoing. This study sought to characterize myocardial tissues and oxidative metabolism in asymptomatic subjects with chronic alcohol consumption by quantitative cardiovascular magnetic resonance (CMR) and 11C-acetate positron emission tomography (PET)/computed tomography (CT). Methods: Thirty-four male subjects (48.8 +/- 9.1 years) with alcohol consumption > 28 g/day for > 10 years and 35 age-matched healthy male subjects (49.5 +/- 9.7 years) underwent CMR and 11C-acetate PET/CT. Native and post T1 values and extracellular volume (ECV) from CMR and Kmono and K1 from PET imaging were measured. Quantitative measurements by CMR and PET imaging were compared between subjects with moderate to heavy alcohol consumption and healthy controls, and their correlations were also analyzed. Results: Compared to healthy controls, subjects with alcohol consumption showed significantly shorter native T1 (1133 +/- 65 ms vs. 1186 +/- 31 ms, p 0.05). In contrast, subjects with heavy alcohol consumption showed significantly lower Kmono values compared to those with moderate alcohol consumption (52.9 +/- 12.1 min(- 1) x 10(- 3) vs. 63.7 +/- 9.2 min(- 1) x 10(- 3), p = 0.012). Strong and moderate correlations were found between K1 and ECV in healthy controls (r = 0.689, p = 0.013) and subjects with moderate alcohol consumption (r = 0.518, p = 0.048), respectively. Conclusion: Asymptomatic men with heavy alcohol consumption have detectable structural and metabolic changes in myocardium on CMR and 11C-acetate PET/CT. Compared with quantitative CMR, 11C-acetate PET/CT imaging may be more sensitive for detecting differences in myocardial damage among subjects with moderate to heavy alcohol consumption.</div

Global sensitivity analysis in hydrological modeling: Review of concepts, methods, theoretical framework, and applications

Sensitivity analysis (SA) aims to identify the key parameters that affect model performance and it plays important roles in model parameterization, calibration, optimization, and uncertainty quantification. However, the increasing complexity of hydrological models means that a large number of parameters need to be estimated. To better understand how these complex models work, efficient SA methods should be applied before the application of hydrological modeling. This study provides a comprehensive review of global SA methods in the field of hydrological modeling. The common definitions of SA and the typical categories of SA methods are described. A wide variety of global SA methods have been introduced to provide a more efficient evaluation framework for hydrological modeling. We review, analyze, and categorize research into global SA methods and their applications, with an emphasis on the research accomplished in the hydrological modeling field. The advantages and disadvantages are also discussed and summarized. An application framework and the typical practical steps involved in SA for hydrological modeling are outlined. Further discussions cover several important and often overlooked topics, including the relationship between parameter identification, uncertainty analysis, and optimization in hydrological modeling, how to deal with correlated parameters, and time-varying SA. Finally, some conclusions and guidance recommendations on SA in hydrological modeling are provided, as well as a list of important future research directions that may facilitate more robust analyses when assessing hydrological modeling performance

Mechanical Effects of Solid Water on the Particle Skeleton of Soil: Mechanism Analysis

It is generally accepted that the adsorbed water layer on the surface of the mineral particle has significant effects on the mechanical properties of soils. By defining the concepts of “solid water” and “particle skeleton” after a brief review on adsorbed water, therefore, the mechanical mechanism about how solid water affects the deformation and strength of particle skeleton is theoretically clarified, which could be the physical basis of the reasonability of two assumptive conditions for effective stress equation. Considering solid water as a two-dimensional liquid with appreciable normal strength and lubricity, if soil particles are always wrapped by solid-water layer, the only mechanical effect due to water pressure is to compress particles; while if the interparticle solid water could be extruded undergoing enough force with suitable confinement, the mechanical effects due to increasing water pressure are not only to compress particles more but also to enhance interparticle friction because the indirect interparticle contact could be changed into direct contact to consequently alter the interparticle friction. Because solid water is not likely to be extruded by pressure alone, if the particle compression is negligible relative to the soil-mass compression, two assumptive conditions for effective stress equation are reasonable. Moreover, a simple monitoring test on water content is conducted to certify that the solid-water layer should always exist in soils under ambient conditions, so the ordinarily oven-dried soil samples used in conventional geotechnical tests carried out under ambient conditions could be just “nominally dry” samples with the effects due to solid water