Setting tolerance limits for statistical project control using earned value management

Project control has been a research topic since decades that attracts both academics and practitioners. Project control systems indicate the direction of change in preliminary planning variables compared with actual performance. In case their current project performance deviates from the planned performance, a warning is indicated by the system in order to take corrective actions.Earned value management/earned schedule (EVM/ES) systems have played a central role in project control, and provide straightforward key performance metrics that measure the deviations between planned and actual performance in terms of time and cost. In this paper, a new statistical project control procedure sets tolerance limits to improve the discriminative power between progress situations that are either statistically likely or less likely to occur under the project baseline schedule. In this research, the tolerance limits are derived from subjective estimates for the activity durations of the project. Using the existing and commonly known EVM/ES metrics, the resulting project control charts will have an improved ability to trigger actions when variation in a project׳s progress exceeds certain predefined thresholdsA computational experiment has been set up to test the ability of these statistical project control charts to discriminate between variations that are either acceptable or unacceptable in the duration of the individual activities. The computational experiments compare the use of statistical tolerance limits with traditional earned value management thresholds and validate their power to report warning signals when projects tend to deviate significantly from the baseline schedule.     

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.     

A Tiered Framework for Risk‐Relevant Characterization and Ranking of Chemical Exposures: Applications to the National Children's Study (NCS)

A challenge for large‐scale environmental health investigations such as the National Children's Study (NCS), is characterizing exposures to multiple, co‐occurring chemical agents with varying spatiotemporal concentrations and consequences modulated by biochemical, physiological, behavioral, socioeconomic, and environmental factors. Such investigations can benefit from systematic retrieval, analysis, and integration of diverse extant information on both contaminant patterns and exposure‐relevant factors. This requires development, evaluation, and deployment of informatics methods that support flexible access and analysis of multiattribute data across multiple spatiotemporal scales. A new “Tiered Exposure Ranking” (TiER) framework, developed to support various aspects of risk‐relevant exposure characterization, is described here, with examples demonstrating its application to the NCS. TiER utilizes advances in informatics computational methods, extant database content and availability, and integrative environmental/exposure/biological modeling to support both “discovery‐driven” and “hypothesis‐driven” analyses. “Tier 1” applications focus on “exposomic” pattern recognition for extracting information from multidimensional data sets, whereas second and higher tier applications utilize mechanistic models to develop risk‐relevant exposure metrics for populations and individuals. In this article, “tier 1” applications of TiER explore identification of potentially causative associations among risk factors, for prioritizing further studies, by considering publicly available demographic/socioeconomic, behavioral, and environmental data in relation to two health endpoints (preterm birth and low birth weight). A “tier 2” application develops estimates of pollutant mixture inhalation exposure indices for NCS counties, formulated to support risk characterization for these endpoints. Applications of TiER demonstrate the feasibility of developing risk‐relevant exposure characterizations for pollutants using extant environmental and demographic/socioeconomic data.     

Replication: Revisiting Tversky and Shafir’s (1992) Disjunction Effect with an extension comparing between and within subject designs

Does uncertainty about an outcome influence decisions? The sure-thing principle (Savage, 1954) posits that it should not, but Tversky and Shafir (1992) found that people regularly violate it in hypothetical gambling and vacation decisions, a phenomenon they termed “disjunction effect”. Very close replications and extensions of Tversky and Shafir (1992) were conducted in this paper (N = 890, MTurk). The target article demonstrated the effect using two paradigms in a between-subject design: here, an extension also testing a within-subject design, with design being randomly assigned was added. These results were consistent with the original findings for the “paying to know“ problem (original: Cramer’s V = 0.22, 95% (CI) [0.14, 0.32]; replication: Cramer’s V = 0.30, 95% CI [0.24, 0.37]), yet not for the “choice under risk” problem (original: Cramer’s V = 0.26, 95% CI [0.14, 0.39]; replication: Cramer’s V = 0.11, 95% CI [−0.07, 0.20]). The within-subject extension showed very similar results. Implications for the disjunction effect and judgment and decision-making theory are discussed, and a call for improvements on the statistical understanding of comparisons of between-subject and within-subject designs is introduced. All materials, data, and code are available on https://osf.io/gu58m/.     

An Ecological Model for Quantitative Risk Assessment for Schistosomiasis: The Case of a Patchy Environment in the Coastal Tropical Area of Northeastern Brazil

We developed a stochastic model for quantitative risk assessment for the Schistosoma mansoni (SM) parasite, which causes an endemic disease of public concern. The model provides answers in a useful format for public health decisions, uses data and expert opinion, and can be applied to any landscape where the snail Biomphalaria glabrata is the main intermediate host (South and Central America, the Caribbean, and Africa). It incorporates several realistic and case‐specific features: stage‐structured parasite populations, periodic praziquantel (PZQ) drug treatment for humans, density dependence, extreme events (prolonged rainfall), site‐specific sanitation quality, environmental stochasticity, monthly rainfall variation, uncertainty in parameters, and spatial dynamics. We parameterize the model through a real‐world application in the district of Porto de Galinhas (PG), one of the main touristic destinations in Brazil, where previous studies identified four parasite populations within the metapopulation. The results provide a good approximation of the dynamics of the system and are in agreement with our field observations, i.e., the lack of basic infrastructure (sanitation level and health programs) makes PG a suitable habitat for the persistence and growth of a parasite metapopulation. We quantify the risk of SM metapopulation explosion and quasi‐extinction and the time to metapopulation explosion and quasi‐extinction. We evaluate the sensitivity of the results under varying scenarios of future periodic PZQ treatment (based on the Brazilian Ministry of Health's plan) and sanitation quality. We conclude that the plan might be useful to slow SM metapopulation growth but not to control it. Additional investments in better sanitation are necessary.     

Bayesian Treatment of Model Uncertainty for Partially Applicable Models

This article discusses how analyst's or expert's beliefs on the credibility and quality of models can be assessed and incorporated into the uncertainty assessment of an unknown of interest. The proposed methodology is a specialization of the Bayesian framework for the assessment of model uncertainty presented in an earlier paper. This formalism treats models as sources of information in assessing the uncertainty of an unknown, and it allows the use of predictions from multiple models as well as experimental validation data about the models’ performances. In this article, the methodology is extended to incorporate additional types of information about the model, namely, subjective information in terms of credibility of the model and its applicability when it is used outside its intended domain of application. An example in the context of fire risk modeling is also provided.     

Human Health Risk Assessment of Penicillin/Aminopenicillin Resistance in Enterococci Due to Penicillin Use in Food Animals

Penicillin and ampicillin drugs are approved for use in food animals in the United States to treat, control, and prevent diseases, and penicillin is approved for use to improve growth rates in pigs and poultry. This article considers the possibility that such uses might increase the incidence of ampicillin-resistant Enterococcus faecium (AREF) of animal origin in human infections, leading to increased hospitalization and mortality due to reduced response to ampicillin or penicillin. We assess the risks from continued use of penicillin-based drugs in food animals in the United States, using several assumptions to overcome current scientific uncertainties and data gaps. Multiplying the total at-risk population of intensive care unit (ICU) patients by a series of estimated factors suggests that not more than 0.04 excess mortalities per year (under conservative assumptions) to 0.14 excess mortalities per year (under very conservative assumptions) might be prevented in the whole U.S. population if current use of penicillin drugs in food animals were discontinued and if this successfully reduced the prevalence of AREF infections among ICU patients. These calculations suggest that current penicillin usage in food animals in the United States presents very low (possibly zero) human health risks.     

基于改进突变级数法的农产品物流产业评估模型研究

对农产品物流产业发展水平进行客观、准确的分析与评估,可为政府部门优化与调整产业发展、合理制定产业规划提供科学依据。运用突变级数法与离差最大化法构建农产品物流产业评估模型,并选取广东和山东两省20102014年相关数据对构建的评估模型进行实例分析。结果表明：广东省农产品物流产业发展的优势主要体现在信息化水平与经济基础两方面,基础设施建设则是当前制约其产业发展的关键因素;而庞大的产业规模是现阶段支撑山东省农产品物流产业发展的重要力量。改进的突变级数评估模型既克服了主观赋权的局限,又不失科学性和合理性,计算简单,具有重要实用价值。     

未焊透缺陷安全尺寸的评价研究

未焊透是压力管道焊接接头常见缺陷之一,严重时会导致管道的承载能力明显降低,进而引发严重的安全事故。 目前我国的《在用工业管道定期检验规程》中对未焊透管道的定级是很保守的,为了减少对未焊透缺陷的返修,文章采 用非线性有限元分析的方法,通过简化未焊透管道的影响因素,并研究在不同载荷工况下管道失效模式与缺陷尺寸的关 系,获得了未焊透管道的极限载荷曲线簇;再运用塑性力学分析方法对有限元分析结果进行筛选,得到了焊接缺陷的安 全尺寸;最终通过试验验证极限载荷数值分析结果的合理性。研究结果表明含有超标焊接缺陷（如未焊透）的管道不通 过复杂应力计算和安全评定即可在保证安全前提下最大限度地使用。     

生命周期评价与环境伦理

评价材料与环境协调性的生命周期评价方法有环境伦理的哲学基础,是环境伦理的核心观点的科学体现。然而,从科学角度来看的生命周期评价方法的局限性则未必真是它的局限性,在对其作出环境伦理学的说明之后,有些局限性不过是哲学与科学的内在矛盾的体现,是科学自身的局限性的折射而已。