Perceptions of Collaboration and Satisfaction with Collaboration Regarding Care Decision-Making in Intensive Care Units in Japan: A National Survey

Multi-professional collaboration is being promoted worldwide as a response to the need for sophisticated medical care and for catering to patients’ diverse needs. Patients in Intensive Care Units (ICUs) are seriously ill, and their families may be at risk depending on the patient’s situation. Considering these characteristics of patients and families, there is a strong need for multi-professional collaboration within ICUs. The purpose of this descriptive study was to examine recognition and other factors related to collaboration and satisfaction involving care decisions in Japanese ICUs. A mail survey about collaboration of activities and systems was sent to physicians, clinical engineers, and nurses working in ICUs in Japan, 387 consented to participate in this study. Results showed that satisfaction scores were generally high among the three aforementioned professions, but collaboration scores on deciding care for patients showed significant differences (p < 0.05). The total collaboration score was the highest among physicians (36.7 ± 6.7 points), followed by nurses (32.8 ± 7.4 points), and CEs (32.8 ± 7.4 points). The factors that commonly affected collaboration scores were the satisfaction score and the ability to collaborate with other professionals and set team medical care as a goal. Moreover, it is worth noting that the degree of difficulty in collaboration negatively affected this factor. On the other hand, other factors differed among the three professions, suggesting that the purpose and need for collaboration differ depending on the profession.

Aspect based sentiment analysis using multi-criteria decision-making and deep learning under COVID-19 pandemic in India

The COVID-19 pandemic has a significant impact on the global economy and health.While the pandemic continues to cause casualties in millions,many countries have gone under lockdown.During this period,people have to stay within walls and become more addicted towards social networks.They express their emotions and sympathy via these online platforms.Thus,popular social media(Twitter and Facebook)have become rich sources of information for Opinion Mining and Sentiment Analysis on COVID-19-related issues.We have used Aspect Based Sentiment Analysis to anticipate the polarity of public opinion underlying different aspects from Twitter during lockdown and stepwise unlock phases.The goal of this study is to find the feelings of Indians about the lockdown initiative taken by the Government of India to stop the spread of Coronavirus.India-specific COVID-19 tweets have been annotated,for analysing the sentiment of common public.To classify the Twitter data set a deep learning model has been proposed which has achieved accuracies of 82.35%for Lockdown and 83.33%for Unlock data set.The suggested method outperforms many of the contemporary approaches(long shortterm memory,Bi-directional long short-term memory,Gated Recurrent Unit etc.).This study highlights the public sentiment on lockdown and stepwise unlocks,imposed by the Indian Government on various aspects during the Corona outburst.

Clinical decision making on the use of physical restraint in intensive care units

Physical restraint is a common nursing intervention in intensive care units and nurses often use it to ensure patients'safety and to prevent unexpected accidents.However,existing literature indicated that the use of physical restraint is a complex one because of inadequate rationales,the negative physical and emotional effects on patients,but the lack of perceived alternatives.This paper is aimed to interpret the clinical decision-making theories related to the use of physical restraint in intensive care units in order to facilitate our understanding on the use of physical restraint and to evaluate the quality of decisions made by nurses.By reviewing the literature,intuition and heuristics are the main decision-making strategies related to the use of physical restraint in intensive care units because the rapid and reflexive nature of intuition and heuristics allow nurses to have a rapid response to urgent and emergent cases.However,it is problematic if nurses simply count their decision-making on experience rather than incorporate research evidence into clinical practice because of inadequate evidence to support the use of physical restraint.Besides that,such a rapid response may lead nurses to make decisions without adequate assessment and thinking and therefore biases and errors may be generated.Therefore,despite the importance of intuition and heuristics in decision-making in acute settings on the use of physical restraint,it is recommended that nurses should incorporate research evidence with their experience to make decisions and adequate assessment before implementing physical restraint is also necessary.

Optimal Selection of Hybrid Renewable Energy System Using Multi-Criteria Decision-Making Algorithms

Several models of multi-criteria decision-making(MCDM)have identified the optimal alternative electrical energy sources to supply certain load in an isolated region in Al-Minya City,Egypt.The load demand consists of water pumping system with a water desalination unit.Various options containing three different power sources:only DG,PV-B system,and hybrid PV-DG-B,two different sizes of reverse osmosis(RO)units;RO-250 and RO-500,two strategies of energy management;load following(LF)and cycle charging(CC),and two sizes of DG;5 and 10 kW were taken into account.Eight attributes,including operating cost,renewable fraction,initial cost,the cost of energy,excess energy,unmet load,breakeven grid extension distance,and the amount of CO_(2),were used during the evaluation process.To estimate these parameters,HOMER®software was employed to perform both the simulation and optimization process.Four different weight estimation methods were considered;no priority of criteria,based on a pairwise comparisons matrix of the criteria,CRITIC-method,and entropy-based method.The main findings(output results)confirmed that the optimal option for the case study was hybrid PV-DG-B with the following specification:5 kW DG,RO-500,and load following control strategy.Under this condition,the annual operating cost and initial costs were$5546 and$161022,respectively,whereas the cost of energy was 0.077$/kWh.The excess energy and unmet loads were 40998 and 2371 kWh,respectively.The breakeven grid extension distance and the amount of CO_(2) were 3.31 km and 5171 kg per year,respectively.Compared with DG only,the amount of CO_(2) has been sharply reduced by 113939 kg per year.

DNA extraction method selection for agricultural soil using TOPSIS multiple criteria decision-making model

There is an increased interest in the extraction of nucleic acids from various environmental samples since culture-independent molecular techniques contribute to deepen and broaden the understanding of a greater portion of uncultivable microorganisms. Due to difficulties to select the optimum DNA extraction method in view of downstream molecular analyses, this article presents a straightforward mathematical framework for comparing some of the most commonly used methods. Four commercial DNA extraction kits and two physical-chemical methods (bead-beating and freeze-thaw) were compared for the extraction of DNA under several quantitative DNA analysis criteria: yield of extraction, purity of extracted DNA (A260/280 and A260/230 ratios), degradation degree of DNA, easiness of PCR amplification, duration of extraction, and cost per extraction. From a practical point of view, it is unlikely that a single DNA extraction strategy can be optimum for all selected criteria. Hence, a systematic Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was employed to compare the methods. The PowerSoil? DNA Isolation Kit was systematically defined as the best performing method for extracting DNA from soil samples. More specifically, for soil:manure and soil:manure:biochar mixtures, the PowerSoil?DNA Isolation Kit method performed best, while for neat soil samples its alternative version gained the first rank.

Vigilance in Nurses Working in Intensive Care Units

Background and Aim: Vigilance is an essential element in intensive care nursing. This study was conducted to determine nursing vigilance in nurses working in the intensive care units of educational and medical centers in Ardabil, Iran. Methods: This was a cross-sectional descriptive-analytical study with 192 ICU nurses as the participants. The data were obtained through questionnaires regarding demographic characteristics and nursing vigilance. SPSS software version 24 was used for the statistical analysis. Results: The mean total vigilance score was 3.86 ± 0.23 of 5. The mean scores of the timely diagnosis of changes, pattern recognition, and clinical decision-making subscales were 4.07 ± 0.26, 04.04 ± 0.41, and 3.44 ± 0.25, respectively. No significant relationships were observed between the total or subscale vigilance scores and other demographic characteristics. Conclusion: We assessed ICU nurses’ vigilance behaviors and found that their mean vigilance score was higher than the expected average, indicating our participants had a high level of clinical vigilance. These results suggest a need for effective educational interventions to boost clinical decision-making skills in ICU nurses, especially younger nurses.

基于逼近理想解和模糊综合评价的机械产品元动作健康状态评估

健康状态评估是机械产品高质量发展不可或缺的一环。从运动层面出发,以机械产品中的元动作单元为研究对象,提出一种基于逼近理想解和模糊综合评价的健康状态评估方法。首先,采用M-FMMECA方法,确定元动作单元的关键性能退化指标,给出元动作单元健康指数这一量化指标;接着,将逼近理想解法运用到元动作健康状态评估中,建立元动作单元健康状态量化模型;然后,在完成健康状态分级后,采用模糊综合评价法确定元动作单元健康状态隶属度函数,完成健康状态评估;最后,以某可靠性试验台锥齿轮转动元动作单元为例,进行健康状态评估方法的实例分析。研究表明,将逼近理想解与模糊综合评价结合,可以定量且更加全面地评估元动作单元健康状态。

Development of a Decision Aid for Family Surrogate Decision Makers of Critically Ill Patients Requiring Renal Replacement Therapy in ICU:A User-Centered Design for Rapid Prototyping

Objectives Renal replacement therapy(RRT)is increasingly adopted for critically ill patients diagnosed with acute kidney injury,but the optimal time for initiation remains unclear and prognosis is uncertain,leading to medical complexity,ethical conflicts,and decision dilemmas in intensive care unit(ICU)settings.This study aimed to develop a decision aid(DA)for the family surrogate of critically ill patients to support their engagement in shared decision-making process with clinicians.Methods Development of DA employed a systematic process with user-centered design(UCD)principle,which included:(i)competitive analysis:searched,screened,and assessed the existing DAs to gather insights for design strategies,developmental techniques,and functionalities;(ii)user needs assessment:interviewed family surrogates in our hospital to explore target user group's decision-making experience and identify their unmet needs;(iii)evidence syntheses:integrate latest clinical evidence and pertinent information to inform the content development of DA.Results The competitive analysis included 16 relevant DAs,from which we derived valuable insights using existing resources.User decision needs were explored among a cohort of 15 family surrogates,revealing four thematic issues in decision-making,including stuck into dilemmas,sense of uncertainty,limited capacity,and delayed decision confirmation.A total of 27 articles were included for evidence syntheses.Relevant decision making knowledge on disease and treatment,as delineated in the literature sourced from decision support system or clinical guidelines,were formatted as the foundational knowledge base.Twenty-one items of evidence were extracted and integrated into the content panels of benefits and risks of RRT,possible outcomes,and reasons to choose.The DA was drafted into a web-based phototype using the elements of UCD.This platform could guide users in their preparation of decision-making through a sequential four-step process:identifying treatment options,weighing the benefits and risks,clarifying personal preferences and values,and formulating a schedule for formal shared decision-making with clinicians.Conclusions We developed a rapid prototype of DA tailored for family surrogate decision makers of critically ill patients in need of RRT in ICU setting.Future studies are needed to evaluate its usability,feasibility,and clinical effects of this intervention.

An integrated framework for assessing renewable-energy supply chains using multicriteria decision-making:a study on Bangladesh

The depletion in non-renewable energy sources and a fast-growing population in Bangladesh are exacerbating the already existing energy scarcity,highlighting the need for an efficient and robust renewable-energy supply chain.The primary goal of this study is to evaluate the most optimized renewable-energy supply chain based on natural resource availability and government policies of Bangladesh.In the present study,four renewable energy resources,including solar,biomass,wind and hydropower,are studied and nine subcriteria are defined under four primary criteria for each supply chain.Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)and VIseKriterijumska Optimizacija I Kompromisno Resenje(VIKOR)are multicriteria decision-making approaches used in this study to compare and choose the best renewable-energy supply chain.The relative significance of four supply-chain criteria for primary renewable energy in this study,namely energy procurement,production,operations and maintenance costs,and social and environmental impact,is gathered via a survey.The results of this research,supported by a comprehensive sensitivity analysis,indicate that hydropower is the best renewable-energy supply chain,followed by wind as a compromise solution,biomass and solar.The study also demonstrates that no energy source can satisfy all supply-chain criteria alone;each resource is better for a specific criterion-solar is better for procurement,hydropower is significant for production and wind is remarkable for operations and social impact.Therefore,to maximize output,renewable energy sources must be integrated.From Bangladesh’s perspective,for the first time,by using TOPSIS and VIKOR together,this study offers significant insights to establish an efficient and sustainable renewable-energy supply chain for practitioners,academics and policymakers.

不可压缩流体与可压缩流体的阀门流量系数之间的联系

每个阀门最重要的内在参数应该是流量系数C_(v)(或K_(v)),由于存在两种流体——不可压缩流体(液体)和可压缩流体(气体),相应地建立了两个公式用于C_(v)的计算。然而这两个公式似乎是独立的,甚至在两个计算公式中C_(v)的物理单位和量纲都不相同,让人怀疑同一个阀门可能需要两个流量系数来表征。本文详细讨论了两个公式之间的关系,发现它们之间存在简单联系:只要把可压缩流体(气体)近似为理想气体,那么就可以由不可压缩流体的C_(v)计算公式推导出可压缩流体的C_(v)计算公式,这也意味着同一个阀门只需要一个流量系数C_(v)来表征。本文针对C_(v)计算公式中单位制混乱的问题,对涉及到的所有物理量单位进行了讨论,并在文章最后改进了以往使用的常数N因子,使C_(v)成为一个无量纲的物理量。

上游调压室理想阻抗孔面积选择的影响因素分析

针对设置上游阻抗式调压室的引水发电系统,利用特征线法进行大波动过渡过程计算,模拟并分析了引水隧洞长度、两种导叶关闭规律、输水管道糙率以及机组转动惯量对水力过渡过程中调压室理想阻抗孔面积取值的影响。结果表明:在保证其他条件不变的情况下,引水隧洞长度、机组转动惯量以及管道糙率的取值越大,理想阻抗孔的面积越小;先慢后快的导叶关闭规律对阻抗孔面积取值的影响较先快后慢的关闭规律更大。结论对实际工程设计具有参考价值。

An ideal interval method of multi-objective decision-making for comprehensive assessment of water resources renewability

In order to estimate water resources renewability scientifically, an Ideal Interval Method of Multiple Objective Decision-Making (IIMMODM) is presented. This method is developed through improving an ideal point method of multiple objective decision-making. The ideal interval is obtained with assessment standard instead of ideal points. The weights are decided by using the basic point and gray code accelerating genetic algorithm. This method has synthesized the expert’s suggestion and avoided giving a mark for the objective again. It could solve the complicated problem of compatible or incompatible multi-objective assessment. The principle of IIMMODM is presented in this paper. It is used to assess the water resources renewability for nine administrative divisions in the Yellow River basin. The result shows that the water resources renewability in the Yellow River basin is very low. Compared with the gray associate analysis method, fuzzy synthesis method and genetic projection pursuit method, the IIMMODM is easier to use. Compared with the ideal point method of multiple objective decision-making, the IIMMODM has good robustness, which is applicable to the comprehensive assessments of water resources.

基于改进逼近理想法的水电机组过渡过程风险评估

基于数据驱动划分水电机组不推荐运行区和推荐运行区对水电机组的安全稳定运行具有重大意义。对于运行区的划分关键是机组运行风险的量化,故围绕准确量化机组整体运行风险的关键科学问题展开研究,以S电站机组动平衡实验数据为研究对象,提出了基于改进逼近理想法(TOPSIS)的机组运行区划分方法。通过改进TOPSIS计算机组运行风险率,利用信息熵确定各评价指标权重并且给出中高风险运行区内各评价指标危险度排序,在准确量化机组运行风险率的基础上给出了机组运行区划分优化方案,为机组安全稳定运行及增大机组调节灵活性提供依据。

Two-Sided Matching Decision Making with Multi-Attribute Probabilistic Hesitant Fuzzy Sets

In previous research on two-sided matching(TSM)decision,agents’preferences were often given in the form of exact values of ordinal numbers and linguistic phrase term sets.Nowdays,the matching agent cannot perform the exact evaluation in the TSM situations due to the great fuzziness of human thought and the complexity of reality.Probability hesitant fuzzy sets,however,have grown in popularity due to their advantages in communicating complex information.Therefore,this paper develops a TSM decision-making approach with multi-attribute probability hesitant fuzzy sets and unknown attribute weight information.The agent attribute weight vector should be obtained by using the maximum deviation method and Hamming distance.The probabilistic hesitancy fuzzy information matrix of each agent is then arranged to determine the comprehensive evaluation of two matching agent sets.The agent satisfaction degree is calculated using the technique for order preference by similarity to ideal solution(TOPSIS).Additionally,the multi-object programming technique is used to establish a TSM method with the objective of maximizing the agent satisfaction of two-sided agents,and the matching schemes are then established by solving the built model.The study concludes by providing a real-world supply-demand scenario to illustrate the effectiveness of the proposed method.The proposed method is more flexible than prior research since it expresses evaluation information using probability hesitating fuzzy sets and can be used in scenarios when attribute weight information is unclear.

Selecting suitable key supplier for core components during smart complex equipment central-private enterprises collaborative development process:from two different forms of evaluation information and matching perspective

With the development of central-private enterprises integration,selecting suitable key suppliers are able to provide core components for smart complex equipment.We consider selecting suitable key suppliers from matching perspective,for it not only satisfies natural development of smart complex equipment,it is also a good implementation of equipment project in central-private enterprises integration context.In in this paper,we carry out two parts of research,one is evaluation attributes based on comprehensive analysis,and the other is matching process between key suppliers and core components based on the matching attribute.In practical analysis process,we employ comprehensive evaluated analysis methods to acquire relevant attributes for the matching process that follows.In the analysis process,we adopt entropy-maximum deviation method(MDM)-decision-making trial and evaluation laboratory(DEMATEL)-technique for order preference by similarity to an ideal solution(TOPSIS)to obtain a comprehensive analysis.The entropy-MDM is applied to get weight value,DEMATEL is utilized to obtain internal relations,and TOPSIS is adopted to get ideal evaluated solution.We consider aggregating two types of evaluation information according to similarities of smart complex equipment based on the combination between geometric mean and arithmetic mean.Moreover,based on the aforementioned attributes and generalized power Heronian mean operator,we aggregate preference information to acquire relevant satisfaction degree,then combine the constructed matching model to get suitable key supplier.Through comprehensive analysis of selecting suitable suppliers,we know that two-sided matching and information aggregation can provide more research perspectives for smart complex equipment.Through analysis for relevant factors,we find that leading role and service level are also significant for the smart complex equipment development process.

基于单位线反演的产流误差修正

为提高实时洪水预报的精度,将单位线引入实时洪水预报修正中,建立一种向信息源头追溯的反馈修正模型。用最小二乘估计原理,通过推求产流量误差,用理想模型对误差修正模型进行了验证,并对不同范围的产流量误差修正效果进行对比。在浙江长潭流域对11场历史洪水进行修正验证,效果明显,对预报精度有一定的提高。该方法结构简单,且不增加参数,物理概念清晰,又不损失预见期,可以在实际流域洪水预报中推广应用。

用于机械系统精度预测的理想表面法

为了实现复杂机械系统的精度预测,提出了一种能够综合考虑尺寸、形位公差的精度预测方法.将零部件的实际配合面抽象为理想配合面,用单位法矢量表示位置和方向,在刚体条件下从设计信息中获取理想配合面的单位法矢量.采用齐次转换矩阵的方法,得到各零件坐标系之间的转换矩阵,根据系统末端功能面在基准坐标系下单位法矢量的变动范围,分析系统末端功能面的空间位置分布范围和分布规律,从而实现了对机械系统的精度预测.以某型圆柱磨齿机的砂轮修整器为例,进行了3 000次的模拟公差分析计算,得到了工作点位置分布云图和概率密度曲线,与不考虑形位公差精度预测结果的对比表明,该方法能够综合考虑尺寸和形位公差,得到的公差分析结果更接近实际生产情况.

单位稳定秩1环的推广

本文研究了较单位稳定秩1环条件更弱的两种情形.利用研究单位稳定秩1环的方法,获得了这两种情形的许多判定定理,并分别介绍了它们的一般线性群的基本形式,类似的,还研究了具有理想-弱稳定秩1的exchange环和具有单位弱理想稳定秩的环以及它们的一般线性群,推广了单位稳定秩1环的结果.

大型液化天然气船船体极限强度研究

船体极限强度是大型液化天然气(LNG)船海洋环境适应能力的显示指标,而薄膜型LNG船的船体结构具有大舱容和较强的箱形凸起甲板等特点。为了精确评估大型LNG船的船体极限承载能力,文中采用具有代表性的解析方法、简化方法、理想结构单元法和非线性有限元法进行比较研究。首先介绍了上述方法的基本原理和计算步骤。然后以大型LNG船的船中肋骨间结构为研究对象建立了精细的计算模型,并对计算结果进行了比较分析。最后,按法国船级社规范要求对大型LNG船极限强度进行了校核。研究结果表明,文中给出的计算方法适合于大型LNG船的船体极限强度评估,而凸起的箱形甲板显著提高了大型LNG船中垂和中拱极限弯矩比值。

“观念统领”的单元教学:促进学生的理解与迁移

数学教学需要发挥结构的力量,促进学生的理解与迁移。数学大观念是内容、过程和价值的融合,“观念统领”的单元教学是发展学生数学素养的重要途径。以多边形面积为例,“观念统领”的单元教学的基本过程如下:确定单元学习主题及具体观念;制定TUK学习目标及成果表现;评估学生先期学习经验;形成学生思考的关键问题;分解关键问题的子问题,设计有意义的单元学习任务;开展持续性评估。这些过程并不是线性的,它们交织在一起,共同促进学生的意义理解和自主迁移。