Low-Carbon Dispatch of an Integrated Energy System Considering Confidence Intervals for Renewable Energy Generation

Addressing the insufficiency in down-regulation leeway within integrated energy systems stemming from the erratic and volatile nature of wind and solar renewable energy generation,this study focuses on formulating a coordinated strategy involving the carbon capture unit of the integrated energy system and the resources on the load storage side.A scheduling model is devised that takes into account the confidence interval associated with renewable energy generation,with the overarching goal of optimizing the system for low-carbon operation.To begin with,an in-depth analysis is conducted on the temporal energy-shifting attributes and the low-carbon modulation mechanisms exhibited by the source-side carbon capture power plant within the context of integrated and adaptable operational paradigms.Drawing from this analysis,a model is devised to represent the adjustable resources on the charge-storage side,predicated on the principles of electro-thermal coupling within the energy system.Subsequently,the dissimilarities in the confidence intervals of renewable energy generation are considered,leading to the proposition of a flexible upper threshold for the confidence interval.Building on this,a low-carbon dispatch model is established for the integrated energy system,factoring in the margin allowed by the adjustable resources.In the final phase,a simulation is performed on a regional electric heating integrated energy system.This simulation seeks to assess the impact of source-load-storage coordination on the system’s low-carbon operation across various scenarios of reduction margin reserves.The findings underscore that the proactive scheduling model incorporating confidence interval considerations for reduction margin reserves effectively mitigates the uncertainties tied to renewable energy generation.Through harmonized orchestration of source,load,and storage elements,it expands the utilization scope for renewable energy,safeguards the economic efficiency of system operations under low-carbon emission conditions,and empirically validates the soundness and efficacy of the proposed approach.

Assessing healthcare workers’knowledge and confidence in the diagnosis,management and prevention of Monkeypox

BACKGROUND Monkeypox(Mpox),is a disease of global public health concern,as it does not affect only countries in western and central Africa.AIM To assess Burundi healthcare workers(HCWs)s’level of knowledge and confidence in the diagnosis and management of Mpox.METHODS We conducted a cross-sectional study via an online survey designed mainly from the World Health Organization course distributed among Burundi HCWs from June-July 2023.The questionnaire comprises 8 socioprofessional-related questions,22 questions about Mpox disease knowledge,and 3 questions to assess confidence in Mpox diagnosis and management.The data were analyzed via SPSS software version 25.0.A P value<0.05 was considered to indicate statistical significance.RESULTS The study sample comprised 471 HCWs who were mainly medical doctors(63.9%)and nurses(30.1%).None of the 22 questions concerning Mpox knowledge had at least 50%correct responses.A very low number of HCWs(17.4%)knew that Mpox has a vaccine.The confidence level to diagnose(21.20%),treat(18.00%)or prevent(23.30%)Mpox was low among HCWs.The confidence level in the diagnosis of Mpox was associated with the HCWs’age(P value=0.009),sex(P value<0.001),work experience(P value=0.002),and residence(P value<0.001).The confidence level to treat Mpox was significantly associated with the HCWs’age(P value=0.050),sex(P value<0.001),education(P value=0.033)and occupation(P value=0.005).The confidence level to prevent Mpox was associated with the HCWs’education(P value<0.001),work experience(P value=0.002),residence(P value<0.001)and type of work institution(P value=0.003).CONCLUSION This study revealed that HCWs have the lowest level of knowledge regarding Mpox and a lack of confidence in the ability to diagnose,treat or prevent it.There is an urgent need to organize continuing medical education programs on Mpox epidemiology and preparedness for Burundi HCWs.We encourage future researchers to assess potential hesitancy toward Mpox vaccination and its associated factors.

Rules for confidence intervals of permeability coefficients for water flow in over-broken rock mass

Based on the steady-state seepage method, we used the Mechanical Testing and Simulation 815.02 System and a self-designed seepage instrument for over-broken stone to measure seepage properties of water flows in three types of crushed rock samples. Three methods of confidence interval in describing permeability coefficients are presented: the secure interval, the calculated interval and the systemic interval. The lower bound of the secure interval can be applied to water-inrush and the upper bound can solve the problem of connectivity. For the calculated interval, as the axial pressure increases, the length of confidence interval is shortened and the upper and lower bounds are reduced. For the systemic interval, the length of its confidence interval, as well as the upper and lower bounds, clearly vary under low axial pressure but are fairly similar under high axial pressure. These three methods provide useful information and references for analyzing the permeability coefficient of over-broken rock.

Moved Score Confidence Intervals for Means of Discrete Distributions

Let X denote a discrete distribution as Poisson, binomial or negative binomial variable. The score confidence interval for the mean of X is obtained based on inverting the hypothesis test and the central limit theorem is discussed and recommended widely. But it has sharp downward spikes for small means. This paper proposes to move the score interval left a little (about 0.04 unit), called by moved score confidence interval. Numerical computation and Edgeworth expansion show that the moved score interval is analogous to the score interval completely and behaves better for moderate means;for small means the moved interval raises the infimum of the coverage probability and improves the sharp spikes significantly. Especially, it has unified explicit formulations to compute easily.

Bootstrap Confidence Intervals for Proportions of Unequal Sized Groups Adjusted for Overdispersion

Group testing is a method of pooling a number of units together and performing a single test on the resulting group. It is an appealing option when few individual units are thought to be infected leading to reduced costs of testing as compared to individually testing the units. Group testing aims to identify the positive groups in all the groups tested or to estimate the proportion of positives (p) in a population. Interval estimation methods of the proportions in group testing for unequal group sizes adjusted for overdispersion have been examined. Lately improvement in statistical methods allows the construction of highly accurate confidence intervals (CIs). The aim here is to apply group testing for estimation and generate highly accurate Bootstrap confidence intervals (CIs) for the proportion of defective or positive units in particular. This study provided a comparison of several proven methods of constructing CIs for a binomial proportion after adjusting for overdispersion in group testing with groups of unequal sizes. Bootstrap resampling was applied on data simulated from binomial distribution, and confidence intervals with high coverage probabilities were produced. This data was assumed to be overdispersed and independent between groups but correlated within these groups. Interval estimation methods based on the Wald, the Logit and Complementary log-log (CLL) functions were considered. The criterion used in the comparisons is mainly the coverage probabilities attained by nominal 95% CIs, though interval width is also regarded. Bootstrapping produced CIs with high coverage probabilities for each of the three interval methods.

Confidence Intervals for Relative Intensity of Collaboration(RIC)Indicators

Purpose:We aim to extend our investigations related to the Relative Intensity of Collaboration(RIC)indicator,by constructing a confidence interval for the obtained values.Design/methodology/approach:We use Mantel-Haenszel statistics as applied recently by Smolinsky,Klingenberg,and Marx.Findings:We obtain confidence intervals for the RIC indicatorResearch limitations:It is not obvious that data obtained from the Web of Science(or any other database)can be considered a random sample.Practical implications:We explain how to calculate confidence intervals.Bibliometric indicators are more often than not presented as precise values instead of an approximation depending on the database and the time of measurement.Our approach presents a suggestion to solve this problem.Originality/value:Our approach combines the statistics of binary categorical data and bibliometric studies of collaboration.

Semi-empiricial Likelihood Confidence Intervals for the Differences of Two Populations Based on Fractional Imputation

Suppose that there are two populations x and y with missing data on both of them, where x has a distribution function F（·） which is unknown and y has a distribution function Gθ（·） with a probability density function gθ（·） with known form depending on some unknown parameter θ. Fractional imputation is used to fill in missing data. The asymptotic distributions of the semi-empirical likelihood ration statistic are obtained under some mild conditions. Then, empirical likelihood confidence intervals on the differences of x and y are constructed.

A MICROCOMPUTER PROGRAM FOR CALCULATINGTHE CONFIDENCE INTERVALS OF SURVIVAL PROBABILITY IN MEDICAL FOLLOW－UP STUDIES

In cancer survival analysis, it is very frequently to estimate the confidence intervals for survival probabilities.But this calculation is not commonly involve in most popular computer packages, or only one methods of estimation in the packages. In the present Paper, we will describe a microcomputer Program for estimating the confidence intervals of survival probabilities, when the survival functions are estimated using Kaplan-Meier product-limit or life-table method. There are five methods of estimation in the program (SPCI), which are the classical(based on Greenwood's formula of variance of S(ti), Rothman-Wilson, arcsin transformation, log(-Iog) transformation, Iogit transformation methods. Two example analysis are given for testing the performances of the program running.

Computing Confidence Intervals for the Postal Service’s Cost-Elasticity Estimates

This paper provides methods for assessing the precision of cost elasticity estimates when the underlying regression function is assumed to be polynomial. Specifically, the paper adapts two well-known methods for computing confidential intervals for ratios: the delta-method and the Fieller method. We show that performing the estimation with mean-centered explanatory variables provides a straightforward way to estimate the elasticity and compute a confidence interval for it. A theoretical discussion of the proposed methods is provided, as well as an empirical example based on publicly available postal data. Possible areas of application include postal service providers worldwide, transportation and electricity.

Confidence Intervals for the Binomial Proportion: A Comparison of Four Methods

This paper presents four methods of constructing the confidence interval for the proportion p of the binomial distribution. Evidence in the literature indicates the standard Wald confidence interval for the binomial proportion is inaccurate, especially for extreme values of p. Even for moderately large sample sizes, the coverage probabilities of the Wald confidence interval prove to be erratic for extreme values of p. Three alternative confidence intervals, namely, Wilson confidence interval, Clopper-Pearson interval, and likelihood interval, are compared to the Wald confidence interval on the basis of coverage probability and expected length by means of simulation.

Algorithms of Confidence Intervals of WG Distribution Based on Progressive Type-II Censoring Samples

The purpose of this article offers different algorithms of Weibull Geometric (WG) distribution estimation depending on the progressive Type II censoring samples plan, spatially the joint confidence intervals for the parameters. The approximate joint confidence intervals for the parameters, the approximate confidence regions and percentile bootstrap intervals of confidence are discussed, and several Markov chain Monte Carlo (MCMC) techniques are also presented. The parts of mean square error (MSEs) and credible intervals lengths, the estimators of Bayes depend on non-informative implement more effective than the maximum likelihood estimates (MLEs) and bootstrap. Comparing the models, the MSEs, average confidence interval lengths of the MLEs, and Bayes estimators for parameters are less significant for censored models.

DEA Scores’ Confidence Intervals with Past-Present and Past-Present-Future Based Resampling

In data envelopment analysis (DEA), input and output values are subject to change for several reasons. Such variations differ in their input/output items and their decision-making units (DMUs). Hence, DEA efficiency scores need to be examined by considering these factors. In this paper, we propose new resampling models based on these variations for gauging the confidence intervals of DEA scores. The first model utilizes past-present data for estimating data variations imposing chronological order weights which are supplied by Lucas series (a variant of Fibonacci series). The second model deals with future prospects. This model aims at forecasting the future efficiency score and its confidence interval for each DMU. We applied our models to a dataset composed of Japanese municipal hospitals.

Analysis of the Reform of Ideological and Political Education in College English Curriculum from the Perspective of“Cultural Confidence”

With the rapid development of the education industry,higher requirements have been put forward for college English education and teaching,accelerating the pace of college English reform.Issues such as how to integrate knowledge transmission,language expression skill improvement,cultural element extraction,and ideological and political education,and present the role of curriculum education function have attracted attention.In the era of informatization,college students’thinking has undergone certain changes and gradually developed towards diversification.Therefore,universities should start from the perspective of cultural confidence,extract valuable ideological and political elements,and explore effective tourism ideological and political teaching methods.While helping college students enhance their cultural confidence,it is also beneficial for them to better inherit traditional Chinese culture.This article conducts an in-depth exploration of ideological and political education in college English courses from the perspective of“cultural confidence”and uses scientific and effective measures to solve the problems encountered,aiming to provide valuable guidelines for relevant researchers.

Reachability-Based Confidence-Aware Probabilistic Collision Detection in Highway Driving

Risk assessment is a crucial component of collision warning and avoidance systems for intelligent vehicles.Reachability-based formal approaches have been developed to ensure driving safety to accurately detect potential vehicle collisions.However,they suffer from over-conservatism,potentially resulting in false–positive risk events in complicated real-world applications.In this paper,we combine two reachability analysis techniques,a backward reachable set(BRS)and a stochastic forward reachable set(FRS),and propose an integrated probabilistic collision–detection framework for highway driving.Within this framework,we can first use a BRS to formally check whether a two-vehicle interaction is safe;otherwise,a prediction-based stochastic FRS is employed to estimate the collision probability at each future time step.Thus,the framework can not only identify non-risky events with guaranteed safety but also provide accurate collision risk estimation in safety-critical events.To construct the stochastic FRS,we develop a neural network-based acceleration model for surrounding vehicles and further incorporate a confidence-aware dynamic belief to improve the prediction accuracy.Extensive experiments were conducted to validate the performance of the acceleration prediction model based on naturalistic highway driving data.The efficiency and effectiveness of the framework with infused confidence beliefs were tested in both naturalistic and simulated highway scenarios.The proposed risk assessment framework is promising for real-world applications.

China Continues to Bring Confidence to Global Economy Recovery

Looking forward to 2024,what opportunities and challenges will global development face?In particular,how can the global economy get rid of the“sequelae”of the pandemic?At the 170th“Monthly Talk on the Economy”held recently by the China Center for International Economic Exchange,experts analyzed the world’s economy since the outbreak of COVID-19,and made clear the context of and provided suggestions for global development in 2024.

Ministry of Commerce:Full of confidence,clear direction,strong motivation

On March 12,the official account of the International Business Daily of the Ministry of Commerce published an article titled“Foreign trade enterprises:full of confidence,clear direction,strong motivation”.The content is as follows:This year,China is still facing a tough foreign trade situation.On the one hand,many international organizations predict that global economic growth in 2024 will still be lower than the historical average and the pressure on external demand will increase;on the other hand,trade protectionism and unilateralism are on the rise,geopolitical conflicts,the global“super election year”and other spillover factors have created many uncertainties.

中华民族现代文明:理论内涵、时代要求与世界意义

建设中华民族现代文明谱写了全面推进强国建设、民族复兴的新篇章,“新”就新在它既是一个新概念、一种新问题,也代表着一种新思维,彰显了习近平总书记对文化建设的深入思考。中华民族现代文明作为中国式现代化的文明成果,是党的百年文化建设的宏阔升华,它厚植于中华文明与马克思主义融通结合的沃土,体现了对全人类共同价值的时代追寻。习近平文化思想为建设中华民族现代文明提供根本的理论指引、思想指引、精神指引和使命指引。建设中华民族现代文明,是对时代问题的积极回应,必须坚定文化自信、深化文明互鉴、推进文化传播,推动中华文明焕发时代荣光。

PMMA和Confidence高粘度骨水泥在老年胸腰椎骨折椎体成形术中的应用效果对比分析

目的比较PMMA和Confidence高粘度骨水泥在老年胸腰椎骨折椎体成形术中的应用效果。方法选取2014年12月~2016年5月我院收治的116例老年胸腰椎骨折行椎体成形术患者,按照随机数字表法将患者分为研究组和对照组,每组58例。研究组使用Confidence高粘度骨水泥填充,对照组使用PMMA骨水泥填充。比较两组手术时间、术中出血量、住院时间、手术前后VAS评分、生活质量水平、椎体前缘高度及Cobb角的差异。结果研究组手术时间、术中出血量、住院时间分别为（73.36±14.83）min、（25.82±6.15）ml、（6.82±2.17）d,与对照组的（78.12±15.19）min、（28.10±6.39）ml、（7.08±2.09）d比较均无显著差异（P〉0.05）。术前,两组VAS评分比较无统计学差异（P〉0.05）。术后3 d、术后10 d、术后30 d,研究组VAS评分分别为（3.06±0.53）分、（1.87±0.42）分、（1.04±0.25）分,均显著低于对照组的（3.56±0.57）分、（2.33±0.51）分、（1.80±0.31）分（P〈0.05）。研究组手术后SF-36各维度评分均较对照组的为优（P〈0.05）;两组椎体前缘高度及Cobb角比较无显著差异（P〉0.05）。结论 Confidence高粘度骨水泥用于老年胸腰椎骨折椎体成形术效果好,在减轻疼痛和提高生活质量方面比PMMA骨水泥更优,二者在改善椎体前缘高度及Cobb角方面效果相当。

高压氧可消除高强度间歇冲击微周期训练中的运动性疲劳

背景:高压氧作为新兴的疲劳消除手段之一,在体育领域中得到越来越多的重视和应用。高压氧干预对高强度间歇冲击微周期训练疲劳消除的研究较少。目的:探究高压氧干预对高强度间歇冲击微周期训练运动性疲劳消除效果的影响,并从血液生化指标和代谢组学方面进行相应机制研究。方法:在首都体育学院招募20名男性大学生,随机分为对照组(n=10)和高压氧组(n=10),均进行高强度间歇冲击微周期训练,为期2周,共12次,具体训练方案为先以50%HR_(max)的强度热身10 min,再以90%-95%HR_(max)强度蹬车4 min,重复5组,组间休息2.5 min,最后再进行50%HR_(max)强度蹬车30 min。对照组受试者训练后自然恢复,高压氧组受试者训练后进行高压氧恢复,每次干预60 min,压力为131.722 kPa。在试验前、试验中期、试验后1 d和试验后3 d采集血液分析生化指标及代谢组学指标,并进行主观感觉疲劳量表评分,其中氧化应激指标与疲劳监控指标进行Pearson相关性分析。结果与结论:①运动性疲劳指标变化:与训练前相比,对照组训练后血尿酸、肌酸激酶、白细胞介素6和主观感觉疲劳量表评分均有不同程度的上调,而高压氧组在高压氧干预后血尿酸、肌酸激酶、白细胞介素6和主观感觉疲劳量表评分变化不大;组间相比,对照组试验后1 d血尿酸、肌酸激酶和白细胞介素6水平显著高于高压氧组;②氧化应激指标变化:与训练前相比,对照组训练后超氧化物歧化酶活性降低、丙二醛水平升高,而高压氧组在高压氧干预后超氧化物歧化酶活性升高、丙二醛水平降低;③超氧化物歧化酶与血尿酸、白细胞介素6和主观感觉疲劳量表评分呈负相关;丙二醛与白细胞介素6和主观感觉疲劳量表评分呈正相关;④代谢组学指标变化:显著变化的代谢通路是花生四烯酸代谢和氧化磷酸化代谢,富集通路上差异代谢物质有花生四烯酸、前列腺素D2、白三烯D4等。结果表明,高强度间歇冲击微周期训练导致机体发生氧化应激,促进了运动性疲劳的产生;高压氧可以一定程度改善氧化应激水平,以及引起花生四烯酸代谢和氧化磷酸化代谢,从而减少氧化损伤,调节炎症反应,促进组织修复和运动性疲劳消除。

Time-varying confidence interval forecasting of travel time for urban arterials using ARIMA-GARCH model

To improve the forecasting reliability of travel time, the time-varying confidence interval of travel time on arterials is forecasted using an autoregressive integrated moving average and generalized autoregressive conditional heteroskedasticity （ARIMA-GARCH） model. In which, the ARIMA model is used as the mean equation of the GARCH model to model the travel time levels and the GARCH model is used to model the conditional variances of travel time. The proposed method is validated and evaluated using actual traffic flow data collected from the traffic monitoring system of Kunshan city. The evaluation results show that, compared with the conventional ARIMA model, the proposed model cannot significantly improve the forecasting performance of travel time levels but has advantage in travel time volatility forecasting. The proposed model can well capture the travel time heteroskedasticity and forecast the time-varying confidence intervals of travel time which can better reflect the volatility of observed travel times than the fixed confidence interval provided by the ARIMA model.