Intensive care unit-acquired weakness:Unveiling significant risk factors and preemptive strategies through machine learning

This editorial discusses an article recently published in the World Journal of Clinical Cases,focusing on risk factors associated with intensive care unit-acquired weak-ness(ICU-AW).ICU-AW is a serious neuromuscular complication seen in criti-cally ill patients,characterized by muscle dysfunction,weakness,and sensory impairments.Post-discharge,patients may encounter various obstacles impacting their quality of life.The pathogenesis involves intricate changes in muscle and nerve function,potentially leading to significant disabilities.Given its global significance,ICU-AW has become a key research area.The study identified critical risk factors using a multilayer perceptron neural network model,highlighting the impact of intensive care unit stay duration and mechanical ventilation duration on ICU-AW.Recommendations were provided for preventing ICU-AW,empha-sizing comprehensive interventions and risk factor mitigation.This editorial stresses the importance of external validation,cross-validation,and model tran-sparency to enhance model reliability.Moreover,the application of machine learning in clinical medicine has demonstrated clear benefits in improving disease understanding and treatment decisions.While machine learning presents oppor-tunities,challenges such as model reliability and data management necessitate thorough validation and ethical considerations.In conclusion,integrating ma-chine learning into healthcare offers significant potential and challenges.Enhan-cing data management,validating models,and upholding ethical standards are crucial for maximizing the benefits of machine learning in clinical practice.

A Study on the Factors Influencing Consumer Purchase Decision Under the Live-Streaming Sales Model

In recent years,with the rapid development and popularization of Internet information technology,many new media platforms have risen rapidly,and major e-commerce companies have begun to explore the mode of livestreaming.Especially during the COVID-19 pandemic,due to the lockdown,live-streaming has become an important means of economic development in many places.Owing to its remarkable characteristics of timeliness,entertainment,and interactivity,it has become the latest and trendiest sales mode of e-commerce channels,reflecting huge economic potential and commercial value.This article analyzes two models and their characteristics of live-streaming sales from a practical perspective.Based on this,it outlines consumer purchasing decisions and the factors that affect consumer purchasing decisions under the live-streaming sales model.Finally,it discusses targeted suggestions for using the live-streaming sales model to expand the consumer market,hoping to promote the healthy and steady development of the live-streaming sales industry.

An Evaluation of the Critical Success Factors in Sustainable Food Supply Chains in Developing Countries

Food is one of the biggest industries in developed and underdeveloped countries. Supply chain sustainability is essential in established and emerging economies because of the rising acceptance of cost-based outsourcing and the growing technological, social, and environmental concerns. The food business faces serious sustainability and growth challenges in developing countries. A comprehensive analysis of the critical success factors (CSFs) influencing the performance outcome and the sustainable supply chain management (SSCM) process. A theoretical framework is established to explain how they are used to examine the organizational aspect of the food supply chain life cycle analysis. This study examined the CSFs and revealed the relationships between them using a methodology that included a review of literature, interpretative structural modeling (ISM), and cross-impact matrix multiplication applied in classification (MICMAC) tool analysis of soil liquefaction factors. The findings of this research demonstrate that the quality and safety of food are important factors and have a direct effect on other factors. To make sustainable food supply chain management more adequate, legislators, managers, and experts need to pay attention to this factor. In this work. It also shows that companies aiming to create a sustainable business model must make sustainability a fundamental tenet of their organization. Practitioners and managers may devise effective long-term plans for establishing a sustainable food supply chain utilizing the recommended methodology.

Decisive Factors of Conidia Release of Botryosphaeria berengeriana during Growing Season

[ Objective ] The study aimed to explore the release conditions for the conidia of Botryosphaena berengeriana and understand the release dynamic of conidia. [Method] The systematical survey on the release conditions for the conidia of B. berengeriana were conducted in two growing seasons in 2008 and 2009, combined with the collection of meteorological data around conidia release period, the weather conditions causing large amount release of B. berengedana were analyzed. [ Result] During a growing season, the conidia of pathogen appeared several large release peaks. Under the suitable temperature, when the precipitation lasted for 4 h, the conidia of B. berengeriana began to release with large amount, the amount of conidia reached the peak after release and trended to be stable during 4 - 12 h, which significantly reduced after 24 h, tended to dis- appear after 36 h, and completely disappeared after 72 h. [Conclusion] The dominant factor affecting B. berengeriana conidia release in large a- mount was precipitation, while the lasting time of precipitation played a decisive role.

Type 2 Possibility Factor Rotation in No-Data Problem

Uemura [1] discovered a mapping formula that transforms and maps the state of nature into fuzzy events with a membership function that expresses the degree of attribution. In decision theory in no-data problems, sequential Bayesian inference is an example of this mapping formula, and Hori et al. [2] made the mapping formula multidimensional, introduced the concept of time, to Markov (decision) processes in fuzzy events under ergodic conditions, and derived stochastic differential equations in fuzzy events, although in reverse. In this paper, we focus on type 2 fuzzy. First, assuming that Type 2 Fuzzy Events are transformed and mapped onto the state of nature by a quadratic mapping formula that simultaneously considers longitudinal and transverse ambiguity, the joint stochastic differential equation representing these two ambiguities can be applied to possibility principal factor analysis if the weights of the equations are orthogonal. This indicates that the type 2 fuzzy is a two-dimensional possibility multivariate error model with longitudinal and transverse directions. Also, when the weights are oblique, it is a general possibility oblique factor analysis. Therefore, an example of type 2 fuzzy system theory is the possibility factor analysis. Furthermore, we show the initial and stopping condition on possibility factor rotation, on the base of possibility theory.

Initial and Stopping Condition in Possibility Principal Factor Rotation

Uemura [1] discovered the mapping formula for Type 1 Vague events and presented an alternative problem as an example of its application. Since it is well known that the alternative problem leads to sequential Bayesian inference, the flow of subsequent research was to make the mapping formula multidimensional, to introduce the concept of time, and to derive a Markov (decision) process. Furthermore, we formulated stochastic differential equations to derive them [2]. This paper refers to type 2 vague events based on a second-order mapping equation. This quadratic mapping formula gives a certain rotation named as possibility principal factor rotation by transforming a non-mapping function by a relation between two mapping functions. In addition, the derivation of the Type 2 Complex Markov process and the initial and stopping conditions in this rotation are mentioned. .

Ontogeny of expression of transforming growth factor-βand its receptors and their possible relationship with scarless or scar-forming healing in human fetal and postnatal skins

Fetal eutaneous wounds that oeeur in earlygestation heal without sear formation.Althoughmueh work has been done to eharaeterize the roleof transforming growth

Intervention decision-making in MAV/UAV cooperative engagement based on human factors engineering

Aiming at the intervention decision-making problem in manned/unmanned aerial vehicle（MAV/UAV） cooperative engagement, this paper carries out a research on allocation strategy of emergency discretion based on human factors engineering（HFE）.Firstly, based on the brief review of research status of HFE, it gives structural description to emergency in the process of cooperative engagement and analyzes intervention of commanders. After that,constraint conditions of intervention decision-making of commanders based on HFE（IDMCBHFE） are given, and the mathematical model, which takes the overall efficiency value of handling emergencies as the objective function, is established. Then, through combining K-best and variable neighborhood search（VNS） algorithm, a K-best optimization variable neighborhood search mixed algorithm（KBOVNSMA） is designed to solve the model. Finally,through three groups of simulation experiments, effectiveness and superiority of the proposed algorithm are verified.

Investment in deepwater oil and gas exploration projects:a multi-factor analysis with a real options model

Deepwater oil and gas projects embody high risks from geology and engineering aspects, which exert substantial influence on project valuation. But the uncer- tainties may be converted to additional value to the projects in the case of flexible management. Given the flexibility of project management, this paper extends the classical real options model to a multi-factor model which contains oil price, geology, and engineering uncertainties. It then gives an application example of the new model to evaluate deepwater oil and gas projects with a numerical analytical method. Compared with other methods and models, this multi-factor real options model contains more project information. It reflects the potential value deriving not only from oil price variation but also from geology and engi- neering uncertainties, which provides more accurate and reliable valuation information for decision makers.

Analysis on Factors Influencing Supply of Rapeseed in Provinces of China

From the perspective of micro-subjects of rapeseed planting,namely,the rape seed planting farmers,this paper made an analysis on factors influencing supply of rapeseed in provinces of China on the basis of panel data of 14 provinces producing rapeseed. Analysis indicates that decision of rapeseed planting area is influenced by planting area of the previous year and comparative benefits of rapeseed and the substitute crop wheat,while the local non-agricultural employment level exerts little influence on decision of rapeseed planting area. Finally,it came up with pertinent policy recommendations: since lagging influence of previous planting decisions and selection of planting decisions are a long period,formulation and implementation of any policy should consider long-term subsequent effect,instead of excessively focusing on policy objectives; strengthening new technological researches of new rapeseed varieties relying on scientific and technological innovation,enhancing construction of rapeseed production infrastructure,and improving integrated rapeseed production capacity,so as to increase relative income of rapeseed planting.

Marketing Factors Affecting Middle Class Consumer’s Buying Decision in Housing Market in Nanning City

It is important to study the relationship between marketing factors and purchase decisions of middle-class consumers in Nanning housing market.This study will investigate the factors influencing people decision to purchase houses in Nanning City.The extrinsic housing attributes at this study consist of environmental attributes and location attributes.I have a limited understanding of the purchase behavior of Nanning home buyers in Nanning City.This study adopts the data collection methods of e-mail and field survey.Based on 509 questionnaires,the data were analyzed using descriptive statistics analysis and logistic regression.The results show that location attributes,such as school districts,positively influence housing purchase decisions in Nanning City.This study contributes to an improved understanding of home buyers’decision making in Nanning City.The beneficiaries of this study include home buyers and marketers and academic institutions.To better meet home buyers’needs and achieve a competitive advantage,marketers can use the research outcomes to focus more on those housing purchase factors that significantly influence house buyers’purchase decision making.

The Marketing Factors Affecting Customer Decision-Making of Xiaomi Smart Wearable Devices in Guangxi,China

From an empirical point of view,this paper proposes research hypotheses and models based on the market situation of Xiaomi smart wearable devices in Guangxi,as well as the research status of consumers’purchasing decisions,combined with the empirical research of some researchers.This paper designs questionnaires and scales.The sampling survey method is used to investigate and analyze the influencing factors of Guangxi consumers’decision to purchase Xiaomi smart wearable devices.Questionnaires were distributed through Questionnaire Star,and 385 valid questionnaires were collected for descriptive statistics and correlation analysis.Conclusions are as follow:(1)Consumers in Guangxi who purchase Xiaomi smart wearable devices are between 19 and 32 years old,and most of them have a bachelor’s degree.Among the five factors of demographic characteristics,only income and marketing mix satisfaction have a positive correlation,indicating that customers are sensitive to Xiaomi smart wearable products.And among the customers of Xiaomi smart wearable products,the monthly income of less than 5,000 yuan accounted for 30.91%of the total number of surveys;the monthly income was 5,000-7,000 yuan,accounting for 34.29%.(2)The satisfaction of the marketing mix is positively correlated with the satisfaction of customer decision-making.The satisfaction of the marketing mix varies with the age,gender,education,income,and working years of each population,and only the income is positively correlated with the satisfaction of the marketing mix.Relationships,age,gender,education,and years of employment were not associated with marketing mix satisfaction.According to the above conclusions,relevant and reasonable product development and marketing suggestions are put forward for the enterprise,which provides a reference for the enterprise’s brand building and market development.Therefore,on the basis of comparing with other scholars at home and abroad,through the 7P marketing theory and purchasing decision theory and the research on the current situation of influencing factors for customers to purchase Xiaomi smart wearable devices in Guangxi,this paper compiled a questionnaire for 385 private colleges and universities in Guangxi.A questionnaire survey was carried out with customers,and the current situation of customers’purchasing decision-making behavior was obtained and analyzed and the following suggestions were put forward:continuously innovating products,targeting target customers,reasonably setting product prices,improving marketing mix.

Influencing Factors of Personal Retirement Decision： Perspective of Research Summary

Because the policy of delay retirement is facing demand differences widely, research workers retirement needs and the basic law from the micro perspective will become increasingly important. Based on the demographic characteristics, family relationships, social and economic factors and professional environment, such as in four dimensions, the article has reviewed the individual retirement decisions affecting factors and its mechanism of action, and summed up the consensus theory and some controversy. In future research, we need to strengthen the cross disciplines and integration, to explore more available research variables, provide a new starting point for further theoretical research and policy making.

基于多模态超声建构胎儿先天性心脏病决策树模型及其应用价值

目的:分析基于多模态超声建构胎儿先天性心脏病决策树模型及其应用价值。方法:随机选取2021年4月-2023年7月在本院产前超声检查孕中期孕妇300例,常规产科超声检查确定胎儿生长程度,核实孕周,采用超声多断面模式方法对胎儿心脏进行多断面检测,包括四腔心断面、三血管断面、主动脉弓断面、左室流出道断面、右室流出道断面。对正常分娩的新生儿进行心脏多断面超声检测。对300例胎儿进行多断面模式超声检测,分析胎儿是否伴有先天性心脏畸形,对比超声检查与随访结果符合情况。结果:超声检出21例先天性心脏畸形胎儿,8例选择引产,余13例正常分娩。超声诊断与随访结果对比,卵圆孔直径增大、法洛四联症、完全型心内膜垫缺损、二尖瓣闭锁、右室发育不良综合征、左室发育不良综合征、大动脉转位、永存动脉干、单心室、三尖瓣下移符合率均为100%,超声诊断室间隔缺损7例,随访发现室间隔诊断5例,诊断符合率71.4%。279例超声诊断无先天性心脏畸形胎儿出生后经超声诊断发现有1例卵圆孔未闭、3例室间隔缺损,共4例漏诊患儿,漏诊率0.54%。四腔心断面、三血管断面、主动脉弓断面、左室流出道断面、右室流出道断面诊断胎儿畸形率分别为3.95%、0.63%、2.76%、3.27%、3.25%。由决策树模型可得,产前超声检查发现胎儿心脏可疑异常、高龄孕妇、孕妇接受药物治疗或射线暴露、孕妇有先天性心脏病家族史是胎儿存在先天性心脏病的独立危险因素,其中产前超声检查发现胎儿心脏可疑异常的影响最为显著。结论:孕中期胎儿产前超声多断面模式筛查胎儿先天性心脏病,能够对多数胎儿先天性心脏病进行诊断。

含大规模分布式光伏接入电网的无功电压控制降损方法研究

大规模分布式光伏(distributed photovoltaic,DP)接入电网后,电网电压易出现大幅度波动,导致电网损失问题越来越突出。当前已有的电网降损方法没有考虑光伏发电自身的无功调节能力,应用效果不理想。为此,设计一种含大规模DP接入电网的无功电压控制降损方法。通过建立目标函数,设定约束条件,采用敏感性分析方法分析电压稳定性,将敏感度较高的值作为无功补偿位置,并对当前负荷进行预测,确定最佳的补偿容量,实现电网降损。试验结果表明:所提方法降损后较降损前基准电压更趋于1 pu,更为稳定,所提方法能够针对光伏控制接入分布特性,有效控制无功功率变化情况,相对于其他方法,无功功率波动较小,表现出较好的降损效果。

基于装置运行平稳性的石油化工安全管理策略研究

为了找出并评价石化装置支配性风险因素,实现安全生产风险源头控制和管理,满足石化装置安全生产风险控制的高效性要求,通过建立石化装置事故风险影响模型,运用决策试验与评估实验室方法(DEMATEL)从“现代事故因果连锁理论”视角分析发现人、机(物)等风险因素都受管理因素支配。进而,基于工艺稳定性、工艺稳定性修正、非计划停工3个指标建立石化装置平稳性模型,对装置运行平稳率进行追踪统计,并通过实例对该模型进行了分析和验证。结果表明:该石化装置运行平稳性模型可以量化追踪事故风险支配性因素的控制效果,可展示石化装置不同阶段下的风险特点,可作为装置事故风险预警指标和安全管理绩效指标,可提高装置的安全管理水平。

基于粗糙集理论的均匀设计阿魏酸合成工艺因素规律的方法研究

目的利用粗糙集理论研究药物合成生产过程中生产因素之间的内在规律,探求最优合成工艺方案的方法。方法采用粗糙集理论方法,以阿魏酸合成工艺为案例,利用均匀设计试验预处理,形成基于粗糙集的决策表,建立粗糙集规则模型。通过决策规则分析工艺因素对试验指标的影响,优选最佳合成工艺。结果阿魏酸合成工艺的反应时间水平与阿魏酸收率水平呈线性增加的趋势(P<0.01),原料配比、吡啶量因素水平与阿魏酸收率水平并没有线性增加的趋势(P>0.05)。当试验三因素都取7水平时,试验结果最好,为最佳组合。结论粗糙集理论方法能够全面地分析药物合成工艺因素与试验结果之间的内在动态规律,为提高药物合成工艺质量,提出了一种独特的优选方法和思路以供参考。

基于前因因素的建筑工人安全行为评价模型与应用

建筑项目中的事故主要与建筑工人的不安全行为有关,因此对建筑工人安全行为进行事前评价是预防事故发生的关键。首先通过文献可视化分析初步筛选建筑工人安全行为前因因素,结合专家意见构建建筑工人安全行为评价的指标体系;然后采用群决策改进的层次分析法确定各评价指标的综合权重,并建立可拓物元评价模型;最后对某施工项目建筑工人安全行为进行评价与分析,以验证模型的合理性和可靠性。结果表明:建筑工人安全行为评价指标中安全意识所占权重较高,是事故预防的重要因素;实例应用结果表明该项目建筑工人总体安全行为等级处于“Ⅲ级”为一般安全,说明该项目施工作业人员整体处于比较安全的水平;建筑工人个体安全行为的维度指标评价结果为正态分布或偏正态分布,表明该评价模型能够有效识别建筑工人的安全行为水平,可为建筑安全管理的研究和实践提供参考。

基于CART决策树的分布式数据离群点检测算法

在分布式计算环境中,离群点通常表示数据中的异常情况,例如故障、欺诈、攻击等。通过检测分布式数据的离群点,可以对这些异常数据进行集中处理,保护系统和数据的安全。而进行离群点检测时,不仅要考虑数据的规模和复杂性,还要在分布式环境下高效地发现离群点。因此,提出一种基于CART决策树的分布式数据离群点检测算法。在构建CART决策树时,使用类间中心距离作为分裂准则,根据分离类别对训练数据进行分类,从而确定数据的类型。在上述基础上,考虑到离群点的分布模式与其周围数据对象不同,使用空间局部偏离因子(SLDF)对空间内各个数据对象之间的离群程度展开度量,同时在高维空间内展开网格划分,引入SLDF算法检测剩余离群点集,最终实现分布式数据离群点检测。实验结果表明,所提方法的离散点检测错误率在0.010以内,可以更加精准地实现分布式数据离群点检测,具有良好的检测性能。

弹性退休制度对经济增长和社会福利的影响研究——基于新古典增长模型

当今世界人口问题日趋严重,中国作为世界人口大国,面临的挑战更是前所未有:在长期人口增长的背景下,中国当前进入人口发展的新时期;同时,还面临1962-1975年高生育率时期出生人口逐渐老龄化所带来的社会老龄化问题。这两个因素迅速加重了现有养老体系的负担。参考已实施弹性退休政策的OECD国家的相关安排,立足现有中国基本养老保险制度,在新古典增长模型中引入老年人退休决策因子,模拟中国实行弹性退休制度,并确定相应的经济动态均衡状态。通过调整模型中各政策参数,探究老年人退休决策对经济增长和福利差距的影响机制。基于研究结果,建议未来应实施弹性退休制度,进一步推行结构性减税和结构性调整养老保险缴费率。