Additive Manufacturing represents, by now, a viable alternative for metal-based components production. Therefore the designer, often, has to select among three options at process design stage: ...subtractive, mass conserving, and additive approaches. The selection of a given process, besides affecting the manufacturing step impact, influences significantly the impact related to the material production step. If the process enables a part weight reduction (as the Additive Manufacturing approaches do) even the use phase is affected by the manufacturing approach selection. The present research provides a comprehensive environmental manufacturing approaches comparison for components made of aluminum alloys. Additive manufacturing (Selective Laser Sintering), machining, and forming processes are analyzed and compared by means of Life Cycle Assessment techniques. The effect of weight reduction enabled by additive approach is considered. The paper aims at highlighting the strong link between manufacturing approach selection and material use. In this respect, a thorough environmental analysis of the pre-manufacturing step is developed. Moreover, the influence of eco-attributes aluminium variability on the comparative analysis results is studied. The paper, therefore, contributes to the development of a methodology for manufacturing approaches comparison, providing guidelines for green manufacturing approach selection. Results reveal that, for the analyzed case studies, the Additive Manufacturing is a sustainable solution for aluminium components only under a specific scenario: high complexity shapes, significant weight reduction, and application in transportation systems.
•Environmental manufacturing routes comparison for parts made of aluminum alloys.•Selective Laser Melting vs. machining vs. forming.•A thorough environmental analysis of the pre-manufacturing step is presented.•The variability of aluminum eco-attributes is analyzed.•For the analyzed case studies, AM is a green choice only for specific applications.
The global increase of antibiotic resistance (AR) and resistant infections call for effective surveillance methods for understanding and mitigating (re)-emerging public health risks. Wastewater ...surveillance (WS) of antibiotic resistance is an emerging, but currently under-utilized decision-support tool in public health systems. Recent years have witnessed an increase in evidence linking antibiotic resistance in wastewaters to that of the community. To date, very few comprehensive reviews exist on the application of WS to understand AR and resistant infections in population. Current and emerging AR detection methods, and their merits and limitations are discussed. Wastewater surveillance has several merits relative to individual testing, including; (1) low per capita testing cost, (2) high spatial coverage, (3) low requirement for diagnostic equipment, and (4) detection of health threats ahead of real outbreaks. The applications of WS as an early warning system and decision support tool to understand and mitigate AR are discussed. Wastewater surveillance could be a tool of choice in low-income settings lacking resources and diagnostic facilities for individual testing. To demonstrate the utility of WS, empirical evidence from field case studies is presented. However, constraints still exist, including; (1) lack of standardized protocols, (2) the clinical utility and sensitivity of WS-based data, (3) uncertainties in relating WS data to pathogenic and virulent bacteria, and (4) whether or not AR in stools and ultimately wastewater represent the complete human resistome. Finally, further prospects are presented, include knowledge gaps on; (1) development of low-cost biosensors for AR, (2) development of WS protocols (sampling, processing, interpretation), (3) further pilot scale studies to understand the opportunities and limits of WS, and (4) development of computer-based analytical tools to facilitate rapid data collection, visualization and interpretation. Therefore, the present paper discusses the principles, opportunities, and constraints of wastewater surveillance applications to understand AR and safeguard public health.
The production of energy from waves is gaining attention. In its expansion strategy, technical, environmental and socioeconomic aspects should be taken into account to identify suitable areas for ...development of wave energy projects. In this research we provide a novel approach for suitable site identification for wave energy farms. To achieve this objective, we (i) developed a conceptual framework, considering technical, environmental and conflicts for space aspects that play a role on the development of those projects, and (ii) it was operationalized in a Bayesian Network, by building a spatially explicit model adopting the Spanish and Portuguese Economic Exclusive Zones as case study. The model results indicate that 1723 km2 and 17,409 km2 are highly suitable or suitable for the development of wave energy projects (i.e. low potential conflicts with other activities and low ecological risk). Suitable areas account for a total of 2.5 TWh∙m−1 energy resource. These areas are placed between 82 and 111 m water depth, 18–30 km to the nearest port, 21–29 km to the nearest electrical substation onshore, with 143–170 MWh m−1 mean annual energy resource and having 124–150 of good weather windows per year for construction and maintenance work. The approach proposed supports scientists, managers and industry, reducing uncertainties during the consenting process, by identifying the most relevant technical, environmental and socioeconomic factors when authorising wave energy projects. The model and the suitability maps produced can be used during site identification processes, informing Strategic Environmental Assessment and ecosystem approach to marine spatial planning.
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•Integrated model for suitable site identification for future wave energy farms.•A spatially explicit model for the Spanish and Portuguese Economic Exclusive Zones.•Technical, environmental and socioeconomic aspects have been considered.•17.7% of the area is suitable, accounting for 2.5 TWh∙m−1 energy resource.•Suitability maps can reduce uncertainties when authorising wave energy projects.
Marine renewable energy has considerable potential for enhancing the diversity of renewable sources, to reduce our reliance on fossil fuels and combat climate change. While the technological ...development of wave energy converters is progressing rapidly, their environmental impacts are still largely unknown, which is a barrier that could hinder their deployment. This research contributes to the state-of-the-art by introducing a framework for quantifying and analysing the ecological risks of three technologies (oscillating water columns, oscillating wave surge converters, and wave turbines). Based on a literature review, expert consultation process, and the development of a web tool, the potential pressures and the ecosystem elements that might be affected during the life cycle of a generic wave farm (an array of wave energy converters) are investigated. The main pressures are found to be physical disturbance, physical loss, hydrological change, and noise. The ecosystem elements sustaining the largest number of pressures and, therefore, at higher ecological risk are fish and cephalopods species, and benthic and pelagic habitats. The ecological risk assessment framework is operationalized into a free-access web tool (https://aztidata.es/wec-era/) for the interactive assessment and visualisation of the pressures and ecological risks. The tool is intended to be used by managers, decision makers, scientists or promoters during the Strategic Environmental Assessment and Environmental Impact Assessment of wave energy projects. The novel approach presented in this work is more sophisticated than previous risk assessment matrices, enabling to better capture the complexity of the interactions between a wave farm and the environment.
•A novel approach for the assessment of ecological risk of wave energy converters.•Captures the complexity of the interactions between a wave farm and the environment.•The pressures and ecosystem elements that might be affected are investigated.•The framework is operationalized into a free access web tool.
In the vast majority of airports where demand exceeds capacity, landing and take-off slots are allocated according to the process established by the Worldwide Slot Guidelines (WSG). An ...optimization-based decision-support tool is introduced in this paper to assist slot coordinators in the initial slot allocation – the most important stage of that process. The WSG comprises both primary and additional criteria to be taken into account by slot coordinators at this stage. Considering all additional criteria specified in the WSG, this tool generates, in an acceptable amount of time, alternative efficient slot allocations against which the coordinators can evaluate the solutions obtained through the heuristic methods they apply. The decision-support tool also offers solution analysis features, such as visualization, ranking, comparison of multiple optimal solutions, and comparison of solutions regarding important characteristics not reflected in the WSG additional criteria. The tool is being tested at one of the largest airports worldwide – Guarulhos (Sao Paulo, Brazil) – with results that clearly illustrate its usefulness in practice.
To evaluate and improve “Making Alternative Treatment Choices Intuitive and Trustworthy” (MATCH-IT)—a digital, interactive decision support tool displaying structured evidence summaries for multiple ...comparisons—to help physicians interpret and apply evidence from network meta-analysis (NMA) for their clinical decision-making.
We conducted a qualitative user testing study, applying principles from user-centered design in an iterative development process. We recruited a convenience sample of practicing physicians in Norway, Belgium, and Canada, and asked them to interpret structured evidence summaries for multiple comparisons—linked to clinical guideline recommendations—displayed in MATCH-IT. User testing included (a) introduction of a clinical scenario, (b) a think-aloud session with participant–tool interaction, and (c) a semistructured interview. We video recorded, transcribed, and analyzed user tests using directed content analysis. The results informed new updates in MATCH-IT.
Distributed across 5 development cycles we tested MATCH-IT with 26 physicians. Of these, 24 (94%) reported either no or sparse prior experience with interpretation of NMA. Physicians perceived MATCH-IT as easy to interpret and navigate, and appreciated its ability to provide an overview of the evidence. Visualization of effects in pictograms and inclusion of information on burden of treatment (“practical issues”) were highlighted as potentially useful features in interacting with patients. We also identified problems, including undiscovered functionalities (drag and drop), suboptimal tutorial, and cumbersome navigation of the tool. In addition, physicians wanted definition/explanation of key terms (eg, outcomes and “certainty”), and there were concerns that overwhelming evidence from a large NMA would complicate applicability to clinical practice. This led to several updates with development of a new start page, tutorial, updated user interface for more efficient maneuvering, solutions to display definition of key terms and a “frequently asked questions” section. To facilitate interpretation of large networks, we improved categorization of results using color coding and added filtering functionality. These modifications allowed physicians to focus on interventions of interest and reduce information overload.
This study provides proof of concept that physicians can use MATCH-IT to understand NMA evidence. Key features of MATCH-IT in a clinical context include providing an overview of the evidence, visualization of effects, and the display of information on burden of treatments. However, unfamiliarity with the Grading of Recommendations Assessment, Development and Evaluation concepts, time constraints, and accessibility at the point of care may be challenges for use. To what extent our results are transferable to real-world clinical contexts remains to be explored.
New product development (NPD) is a crucial process in maintaining a company’s competitive position and succeeding in dynamic markets. One of contemporary trends in the global economy is mass ...customisation that bases on modifications of existing products instead of designing everything anew. The advancement of information technology helps today’s enterprises in managing business processes and collecting data in enterprise systems that can be a potential source of information. Specifications of previous products deliver information of design, cost and time of past NPD projects that can be the basis for developing new products. A promising methodology for assisting conceptual product design and monitoring a NPD project is case-based reasoning. This paper is concerned with developing a case-based reasoning approach towards using neural networks to estimate the cost of NPD in one-of-a-kind production companies.
Approximately 40% of the European energy consumption and a large proportion of environmental impacts are related to the building sector. However, the selection of adequate and correct designs can ...provide considerable energy savings and reduce environmental impacts. To achieve this objective, a simultaneous energy and environmental assessment of a building's life cycle is necessary. To date, the resolution of this complex problem is entrusted to numerous software and calculation algorithms that are often complex to use. They involve long diagnosis phases and are characterised by the lack of a common language. Despite the efforts by the scientific community in the building sector, there is no simple and reliable tool that simultaneously solves the energy and environmental balance of buildings. In this work, the authors address this challenge by proposing the application of an Artificial Neural Network. Due to the high reliability of learning algorithms in the resolution of complex and non-linear problems, it was possible to simultaneously solve two different but strongly dependent aspects after a deep training phase. In previous researches, the authors applied several topologies of neural networks, which were trained on a large and representative database and developed for the Italian building stock. The database, characterised by several building models simulated in different climatic conditions, collects 29 inputs (13 energy data and 16 environmental data) and provides 7 outputs, 1 for heating energy demand and 6 of the most used indicators in life cycle assessment of buildings. A statistical analysis of the results confirmed that the proposed method is appropriate to achieve the goal of the study. The best artificial neural network for each output presented low Root Mean Square Error, Mean Absolute Error lower than 5%, and determination coefficient close to 1. The excellent results confirmed that this methodology can be extended in any context and to any condition (other countries and building stocks). Furthermore, the implementation of this solution algorithm in a software program can enable the development of a suitable decision support tool, which is simple, reliable, and easy to use even for a non-expert user. The possibility to use an instrument to predict a building's performance in its design and planning phase, represent an important result to support decision-making processes toward more sustainable choices.
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•Implementation of a representative energy and environmental building stock database.•Artificial Neural Network to forecast energy and environmental building performance.•A decision support tool to contemporary solve energy and environmental aspects.•A new tool easy to use and with high reliability degree.•Methodology proposal extendible for any building and climatic conditions.
To evaluate the use of a contraceptive decision support tool in the abortion care setting.
In 2019, Mississippi residents aged 18 to 45 used a tablet-based decision support tool at the consultation ...visit and completed a survey about their satisfaction with the tool.
Among the 325 participants, the majority found the tool “very helpful” for method decision-making (86%) and considered the amount of information provided to be “just right” (95%). Nearly all (98%) reported it was acceptable to get contraception information at their visit.
Decision support tools are a promising, person-centered strategy to support postabortion contraceptive information needs.
This article showcases a personal decision support tool (PDST) called HOPLITE, for performing insightful and actionable quantitative assessments of hospital capacity, to support hospital planners and ...health care managers. The tool is user-friendly and intuitive, automates tasks, provides instant reporting, and is extensible. It has been developed as an Excel Visual Basic for Applications (VBA) due to its perceived ease of deployment, ease of use, Office's vast installed user base, and extensive legacy in business. The methodology developed in this article bridges the gap between mathematical theory and practice, which our inference suggests, has restricted the uptake and or development of advanced hospital planning tools and software. To the best of our knowledge, no personal decision support tool (PDST) has yet been created and installed within any existing hospital IT systems, to perform the aforementioned tasks. This article demonstrates that the development of a PDST for hospitals is viable and that optimization methods can be embedded quite simply at no cost. The results of extensive development and testing indicate that HOPLITE can automate many nuanced tasks. Furthermore, there are few limitations and only minor scalability issues with the application of free to use optimization software. The functionality that HOPLITE provides may make it easier to calibrate hospitals strategically and/or tactically to demands. It may give hospitals more control over their case mix and their resources, helping them to operate more proactively and more efficiently.
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