Decision‐Making in Paediatric Rehabilitation: Exploring Professionals' and Children's Views on Decision‐Making Involvement

The article explores the distinction that professionals make between difficult and less difficult decisions in paediatric rehabilitation interventions. This distinction is explored by looking at the involvement of two children in decisions regarding paediatric rehabilitation interventions. The article argues for a clinical practice where children's experiences are extensively used to improve practice and to accommodate the child's right to participate in medical decisions concerning their own body and life. The different ways the children and the professional describe their experiences provide an avenue for a discussion on how medical reasoning can curtail children's involvement in decisions.     

论行政决策中的公众参与权

突破公众参与有效性瓶颈依赖于对公众参与权的依法确认、不断充实及有效保护。鉴于我国对公众参与权的研究比较迟缓、参与权制度发展仍然非常缓慢的现实困境,应当在准确界定公众参与权的性质、明确公众参与权的内容构成基础上,尽快构建起一系列具体的、可操作的法律制度,真正实现公众参与权的民主价值。     

基于ART及多风险规避的交通网络均衡模型

随着对交通系统不确定性认识的深入,以绝对理性为基础的“期望效用理论”在风险环境下的路径选择分析中显示出局限性,而“预期后悔理论”则为之提供了新的分析思路.将预期后悔理论应用到风险环境下的路径选择分析中,将出行者一致风险规避的假设扩展到多风险规避,建立了基于后悔理论及多风险规避出行特征的交通网络随机用户均衡变分不等式模型,并给出了求解算法.通过算例分析发现,后悔心理对出行者的路径选择并不总是显著的.在非风险环境及极端风险环境中,后悔心理对出行者的路径选择影响是微弱的,但是当环境处于极端风险与非风险之间时,后悔心理对出行者路径选择有着较为显著的影响.     

An Integrated Risk Assessment Model of Township‐Scaled Land Subsidence Based on an Evidential Reasoning Algorithm and Fuzzy Set Theory

Land subsidence risk assessment (LSRA) is a multi‐attribute decision analysis (MADA) problem and is often characterized by both quantitative and qualitative attributes with various types of uncertainty. Therefore, the problem needs to be modeled and analyzed using methods that can handle uncertainty. In this article, we propose an integrated assessment model based on the evidential reasoning (ER) algorithm and fuzzy set theory. The assessment model is structured as a hierarchical framework that regards land subsidence risk as a composite of two key factors: hazard and vulnerability. These factors can be described by a set of basic indicators defined by assessment grades with attributes for transforming both numerical data and subjective judgments into a belief structure. The factor‐level attributes of hazard and vulnerability are combined using the ER algorithm, which is based on the information from a belief structure calculated by the Dempster‐Shafer (D‐S) theory, and a distributed fuzzy belief structure calculated by fuzzy set theory. The results from the combined algorithms yield distributed assessment grade matrices. The application of the model to the Xixi‐Chengnan area, China, illustrates its usefulness and validity for LSRA. The model utilizes a combination of all types of evidence, including all assessment information—quantitative or qualitative, complete or incomplete, and precise or imprecise—to provide assessment grades that define risk assessment on the basis of hazard and vulnerability. The results will enable risk managers to apply different risk prevention measures and mitigation planning based on the calculated risk states.     

Community Resilience and Decision Theory Challenges for Catastrophic Events

Extreme and catastrophic events pose challenges for normative models of risk management decision making. They invite development of new methods and principles to complement existing normative decision and risk analysis. Because such events are rare, it is difficult to learn about them from experience. They can prompt both too little concern before the fact, and too much after. Emotionally charged and vivid outcomes promote probability neglect and distort risk perceptions. Aversion to acting on uncertain probabilities saps precautionary action; moral hazard distorts incentives to take care; imperfect learning and social adaptation (e.g., herd‐following, group‐think) complicate forecasting and coordination of individual behaviors and undermine prediction, preparation, and insurance of catastrophic events. Such difficulties raise substantial challenges for normative decision theories prescribing how catastrophe risks should be managed. This article summarizes challenges for catastrophic hazards with uncertain or unpredictable frequencies and severities, hard‐to‐envision and incompletely described decision alternatives and consequences, and individual responses that influence each other. Conceptual models and examples clarify where and why new methods are needed to complement traditional normative decision theories for individuals and groups. For example, prospective and retrospective preferences for risk management alternatives may conflict; procedures for combining individual beliefs or preferences can produce collective decisions that no one favors; and individual choices or behaviors in preparing for possible disasters may have no equilibrium. Recent ideas for building “disaster‐resilient” communities can complement traditional normative decision theories, helping to meet the practical need for better ways to manage risks of extreme and catastrophic events.     

Using agency data for evidence-based programming: a university-agency collaboration

Agencies providing residential treatment are encouraged, or even mandated, to collect outcomes data and to implement evidence based practices, yet little guidance has been provided on how to do so using agency administrative data that are collected on an ongoing basis. We examined data on Child and Adolescent Functional Assessment Scale (CAFAS) scores for 1608 admissions to a residential treatment center from 2002 through 2008. CAFAS scores were measured every 90 days, providing multiple CAFAS scores for each individual. Results demonstrated that on average residents improved in functioning over time. Sensitive to the evolving needs of residents who had been entering the program, the treatment center made significant program changes in 2006 to attempt to better serve residents through a broad array of specialized programming. Compared to the overall results, the analysis suggested that residents who entered the program since October 2006 appeared to have made larger improvements in their CAFAS scores. Results were derived by employing multilevel models appropriate for estimating growth trajectories with repeated measures data. Conversations with agency staff suggested that using administrative data, and advanced statistical models, were extremely helpful for organizational decision making and evidence-based programming.     

Testing for parameter constancy in the time series direction in panel data models

We propose tests for parameter constancy in the time series direction in panel data models. We construct a locally best invariant test based on Tanaka [Time series analysis: nonstationary and noninvertible distribution theory. New York: Wiley; 1996] and an asymptotically point optimal test based on Elliott and Müller [Efficient tests for general persistent time variation in regression coefficients. Rev Econ Stud. 2006;73:907–940]. We derive the limiting distributions of the test statistics as T→∞ while N is fixed, and calculate the critical values by applying numerical integration and response surface regression. Simulation results show that the proposed tests perform well if we apply them appropriately.     

股权众筹投融资方的最优策略分析

分析了股权众筹融资方和投资方的最优策略.依据股权众筹的流程,构建了股权众筹过程中投融资方利益博弈的3阶段模型,并在同时满足融资方与投资方预期收益最大化的条件下,求解了相应的最优化问题并给出了投融资方最优策略的解析式.研究结果表明,在参数满足一定条件时,股权众筹投融资方均存在最优策略,且最优策略受边际收益、项目成功概率、预期回报率等因素的影响.     

“载道”的乌鸟——辞赋中的乌意象论略

由于地区和时代风俗的不同,人们对乌鸦的喜恶或有差异。但乌鸟意象作为中国文学中较为复杂的意象之一,却一直为文人墨客所喜爱。此意象不仅涵义丰富,而且在辞赋中又和其在诗词中有显著的区别。唐前,辞赋中的乌鸟是作者借以表达"出"、"处"生存观念的寄托,乌意象亦随辞赋作者表情达意的需要"出""处"儒道两家,其中《神乌傅》正反映了作者在"出"、"处"间的徘徊和抉择。有唐一代,乌意象的灵异祥瑞成为辞赋书写的重要内容。宋以降,辞赋中的乌鸟渐渐摆脱了其作为祥瑞之兆的使命,而被赋予了更多的儒家道德品性。此时的乌意象集忠、孝、仁等儒家大加称扬的道德于一身,堪称"奉行"儒家伦理道德的典范。而明代《孝乌赋》,凸显乌鸟意象的"孝"德,是彰扬乌意象孝行的典型作品。     

Optimal financing and dividend policy with Markovian switching regimes

This work investigates an optimal financing and dividend problem for an insurer whose surplus process is modulated by an observable continuous-time and finite-state Markov chain. We assume that the insurer should never go bankrupt by issuing new equity. The goal of the insurer is to maximize the expected present value of the dividends payout minus the discounted cost of equity issuance. We obtain the optimal policies and explicit expressions for the value functions when the risk reserve process is modeled by both upward jump model and its diffusion approximation. Numerical illustrations of the sensitivities of the model parameters are provided.