Using the Reliability Theory for Assessing the Decision Confidence Probability for Comparative Life Cycle Assessments.

Comparative decision making process is widely used to identify which option (system, product, service, etc.) has smaller environmental footprints and for providing recommendations that help stakeholders take future decisions. However, the uncertainty problem complicates the comparison and the decision making. Probability-based decision support in LCA is a way to help stakeholders in their decision-making process. It calculates the decision confidence probability which expresses the probability of a option to have a smaller environmental impact than the one of another option. Here we apply the reliability theory to approximate the decision confidence probability. We compare the traditional Monte Carlo method with a reliability method called FORM method. The Monte Carlo method needs high computational time to calculate the decision confidence probability. The FORM method enables us to approximate the decision confidence probability with fewer simulations than the Monte Carlo method by approximating the response surface. Moreover, the FORM method calculates the associated importance factors that correspond to a sensitivity analysis in relation to the probability. The importance factors allow stakeholders to determine which factors influence their decision. Our results clearly show that the reliability method provides additional useful information to stakeholders as well as it reduces the computational time.

How to conduct a proper sensitivity analysis in life cycle assessment: taking into account correlations within LCI data and interactions within the LCA calculation model.

Sensitivity analysis (SA) is a significant tool for studying the robustness of results and their sensitivity to uncertainty factors in life cycle assessment (LCA). It highlights the most important set of model parameters to determine whether data quality needs to be improved, and to enhance interpretation of results. Interactions within the LCA calculation model and correlations within Life Cycle Inventory (LCI) input parameters are two main issues among the LCA calculation process. Here we propose a methodology for conducting a proper SA which takes into account the effects of these two issues. This study first presents the SA in an uncorrelated case, comparing local and independent global sensitivity analysis. Independent global sensitivity analysis aims to analyze the variability of results because of the variation of input parameters over the whole domain of uncertainty, together with interactions among input parameters. We then apply a dependent global sensitivity approach that makes minor modifications to traditional Sobol indices to address the correlation issue. Finally, we propose some guidelines for choosing the appropriate SA method depending on the characteristics of the model and the goals of the study. Our results clearly show that the choice of sensitivity methods should be made according to the magnitude of uncertainty and the degree of correlation.

Factors Associated With Clinical Improvement and the Disappearance of Calcifications After Ultrasound-Guided Percutaneous Lavage of Rotator Cuff Calcific Tendinopathy: A Post Hoc Analysis of a Randomized Controlled Trial.

BACKGROUND: Calcific tendinitis of the rotator cuff is a frequent cause of shoulder pain. Ultrasound-guided percutaneous lavage (UGPL) is an effective treatment, but factors associated with good clinical and radiological outcomes still need to be identified. PURPOSE: To study the clinical, procedural, and radiological characteristics associated with improved shoulder function and the disappearance of calcification on radiograph after UGPL. STUDY DESIGN: Case-control study; Level of evidence, 3. METHODS: This is a post hoc analysis of the CALCECHO trial, a double-blinded randomized controlled trial conducted on 132 patients. The trial assessed the effect of corticosteroid injections after UGPL, and patients were randomly assigned to receive either corticosteroid or saline solution in the subacromial bursa. We analyzed all patients included in the randomized controlled trial as 1 cohort. We collected the patients' clinical, procedural, and radiological characteristics at baseline and during follow-up (3, 6, and 12 months). Univariable analysis, followed by multivariable stepwise regression through forward elimination, was performed to identify the factors associated with clinical success (Disabilities of the Arm, Shoulder and Hand [DASH] score <15) or the disappearance of calcification. RESULTS: Good clinical outcomes at 3 months were associated with steroid injections after the procedure (odd ratio [OR], 3.143; 95% CI, 1.105-8.94). At 6 months, good clinical evolution was associated with a lower DASH score at 3 months (OR, 0.92; 95% CI, 0.890-0.956) and calcium extraction (OR, 10.7; 95% CI, 1.791-63.927). A lower DASH at 6 months was also associated with a long-term favorable outcome at 12 months (OR, 0.939; 95% CI, 0.912-0.966). Disappearance of calcification at 3 and 12 months occurred more frequently in patients in whom communication was created between the calcification and the subacromial bursa during the procedure (OR, 2.728 [95% CI, 1.194-6.234] at 3 months; OR, 9.835 [95% CI, 1.977-48.931] at 12 months). Importantly, an association between calcification resorption and good clinical outcome was found at each time point. CONCLUSION: Assessing patients at 3 months seems to be an essential part of their management strategy. Calcium extraction and creating a communication between the calcific deposits and subacromial bursa are procedural characteristics associated with good clinical and radiological evolution.

The Combined Use of Correlative and Mechanistic Species Distribution Models Benefits Low Conservation Status Species.

Species can respond to climate change by tracking appropriate environmental conditions in space, resulting in a range shift. Species Distribution Models (SDMs) can help forecast such range shift responses. For few species, both correlative and mechanistic SDMs were built, but allis shad (Alosa alosa), an endangered anadromous fish species, is one of them. The main purpose of this study was to provide a framework for joint analyses of correlative and mechanistic SDMs projections in order to strengthen conservation measures for species of conservation concern. Guidelines for joint representation and subsequent interpretation of models outputs were defined and applied. The present joint analysis was based on the novel mechanistic model GR3D (Global Repositioning Dynamics of Diadromous fish Distribution) which was parameterized on allis shad and then used to predict its future distribution along the European Atlantic coast under different climate change scenarios (RCP 4.5 and RCP 8.5). We then used a correlative SDM for this species to forecast its distribution across the same geographic area and under the same climate change scenarios. First, projections from correlative and mechanistic models provided congruent trends in probability of habitat suitability and population dynamics. This agreement was preferentially interpreted as referring to the species vulnerability to climate change. Climate change could not be accordingly listed as a major threat for allis shad. The congruence in predicted range limits between SDMs projections was the next point of interest. The difference, when noticed, required to deepen our understanding of the niche modelled by each approach. In this respect, the relative position of the northern range limit between the two methods strongly suggested here that a key biological process related to intraspecific variability was potentially lacking in the mechanistic SDM. Based on our knowledge, we hypothesized that local adaptations to cold temperatures deserved more attention in terms of modelling, but further in conservation planning as well.