scholarly journals Capturing the Spatial Relatedness of Long-Distance Caregiving: A Mixed-Methods Approach

2020 ◽  
Vol 17 (17) ◽  
pp. 6406
Author(s):  
Tatjana Fischer ◽  
Markus Jobst
Keyword(s):  
Elder Care ◽  
Single Case ◽  
Decision Support Tool ◽  
Well Being ◽  
Long Distance ◽  
Policy Makers ◽  
Support Tool ◽  
Starting Point ◽  
Semantic Hierarchies

Long-distance caregiving (LDC) is an issue of growing importance in the context of assessing the future of elder care and the maintenance of health and well-being of both the cared-for persons and the long-distance caregivers. Uncertainty in the international discussion relates to the relevance of spatially related aspects referring to the burdens of the long-distance caregiver and their (longer-term) willingness and ability to provide care for their elderly relatives. This paper is the result of a first attempt to operationalize and comprehensively analyze the spatial relatedness of long-distance caregiving against the background of the international literature by combining a longitudinal single case study of long-distance caregiving person and semantic hierarchies. In the cooperation of spatial sciences and geoinformatics an analysis grid based on a graph-theoretical model was developed. The elaborated conceptual framework should stimulate a more detailed and precise interdisciplinary discussion on the spatial relatedness of long-distance caregiving and, thus, is open for further refinement in order to become a decision-support tool for policy-makers responsible for social and elder care and health promotion. Moreover, it may serve as a starting point for the development of a method for the numerical determination of the long-distance caregivers on different spatial reference scales.

scholarly journals Multiproduct biorefinery optimal design: application to the acetone-butanol-ethanol system

2020 ◽  
Vol 75 ◽  
pp. 9 ◽  
Author(s):  
Ségolène Belletante ◽  
Ludovic Montastruc ◽  
Michel Meyer ◽  
Heri Hermansyah ◽  
Stéphane Negny
Keyword(s):  
Decision Support ◽  
Optimal Design ◽  
Process Simulation ◽  
Decision Support Tool ◽  
Energy Integration ◽  
Support Tool ◽  
Multi Scale ◽  
Acetone Butanol Ethanol ◽  
Ethanol System

The bioproduct from biomass appears to be major interests for future years given the spectacular and fast advances in microbiology. But the industrial developments of the new bioproducts production struggle to follow this constant and massive creation. Therefore, to estimate the potential of new bioproducts is necessary to pre-design biorefineries with the highest relevance. This study proposes a methodology assessing the relevance of such industrialized production. The presented tool is a multi-scale methodology describing a decision-support tool for the determination of an optimal biorefinery from a superstructure through process simulation, and economic and environmental evaluations. To optimize the biorefinery, energy integration is also applied on the selected processes, because a biorefinery needs a large amount of energy to operate, especially in the pretreatment and purification steps of the process due to huge water flowrate. Thus, the tool designs an efficient, profitable and sustainable biorefinery. We demonstrate our methodology capabilities with the acetone, butanol and ethanol production (ABE system) from lignocellulosic biomass, especially from wood wastes.

scholarly journals Joint Optimization of Routes and Container Fleets to Design Sustainable Intermodal Chains in Chile

2020 ◽  
Vol 12 (6) ◽  
pp. 2221
Author(s):  
Alba Martínez-López ◽  
Manuel Chica
Keyword(s):  
Real Life ◽  
Decision Support Tool ◽  
Nsga Ii ◽  
Policy Makers ◽  
Support Tool ◽  
Conflicting Objectives ◽  
Objective Model ◽  
Pareto Fronts ◽  
Geographical Locations

This paper introduces a decision support tool for sustainable intermodal chains with seaborne transport, in which the optimization of a multi-objective model enables conflicting objectives to be handled simultaneously. Through the assessment of ‘door-to-door’ transport in terms of costs, time, and environmental impact, the most suitable maritime route and the optimized fleet are jointly calculated to maximize the opportunities for success of intermodal chains versus trucking. The resolution of the model through NSGA-II algorithms permits to obtain Pareto fronts that offer groups of optimized solutions. This is not only useful to make decisions in the short term, but also to establish long-term strategies through assessment of the frontiers’ behavior obtained when a sensitivity analysis is undertaken. Thus, consequences of transport policies on intermodal performance can be analyzed. A real-life case is studied to test the usefulness of the model. From the application case, not only the most suitable Motorway of the Seas with their optimized fleets are identified for Chile, but also significant general findings are provided for both policy makers and heads of ports to promote the intermodal option regardless of their geographical locations.

Real-Time Monitoring of Intercity Passenger Flows Based on Big Data

2017 ◽  
Vol 8 (4) ◽  
pp. 120-128 ◽  
Author(s):  
Zheng Li ◽  
Yan Wang ◽  
Qin Chen
Keyword(s):  
Big Data ◽  
Real Time ◽  
Public Transport ◽  
Low Cost ◽  
Decision Support Tool ◽  
Population Mobility ◽  
Population Movements ◽  
Policy Makers ◽  
Support Tool ◽  
Passenger Flows

Managing population mobility is a key to urban growth and sustainable development. This study uses administrative and business data from a number of trustworthy and publicly-available websites for public transport to access passenger flows in a real-time manner. A case study is used to illustrate the application, with intercity passenger flows by public transport mode (rail or air), by rail service type and by time. Moreover, a model is developed for monitoring the implications of population movements, which can be a decision support tool for governments and policy makers to manage population mobility. The big-data approach to accessing public transport passenger movement has the following characteristics: (1) low cost, (2) a population scale, (3) instantaneous data collection/update, and (4) high quality.

scholarly journals Well-being Indicators: a Review and Comparison in the Context of Italy

2021 ◽  
Author(s):  
Silvia Facchinetti ◽  
Elena Siletti
Keyword(s):  
Social Policy ◽  
Theoretical Approach ◽  
Well Being ◽  
Theoretical Framework ◽  
Policy Makers ◽  
Starting Point ◽  
Detailed Outline

AbstractInterest in the well-being measurement is constantly increasing worldwide, especially due to the Stiglitz Commission suggestions, which opened several questions about its assessment and theoretical framework. This paper focuses on the Italian scenario due to the central role given to this topic by the Italian Parliament, which introduces equitable and sustainable well-being among the objectives of the government’s economic and social policy. Significant differences exist among the proposed Italian well-being indices in terms of theoretical approach, statistical rigour and aims. We propose a detailed outline of these indices useful for policy-makers, practitioners, economists and statistics scholars, with the awareness that for a good analysis, a complete and conscious description of the data is the starting point to further improve their usefulness, to maximise their advantages and to cut down their limitations.

scholarly journals P494 Can Patients Monitor Response To Ustekinumab In The Real World?

2021 ◽  
Vol 15 (Supplement_1) ◽  
pp. S477-S478
Author(s):  
A J Walsh ◽  
L Matini ◽  
A Kormilitzin ◽  
J Wilson ◽  
S Lyden ◽  
...  
Keyword(s):  
Abdominal Pain ◽  
Real Time ◽  
Decision Support Tool ◽  
Well Being ◽  
Patient Reported Outcome Measures ◽  
Patient Reported Outcome ◽  
Support Tool ◽  
Patient Reported ◽  
Reported Data ◽  
Over Time

Abstract Background Real time monitoring of patients with Crohn’s disease (CD) gives us the opportunity to examine disease trajectory. We have demonstrated the feasibility of using a monitoring platform with patient reported data, collected prospectively and routinely in clinical practice. The question is whether it can be used for specific drugs Methods TrueColours-IBD (TC-IBD)is a real time, web based platform that through email prompts linked to questionnaires, collects longitudinal patient reported outcome measures (for CD, symptoms measured by Harvey Bradshaw Index (HBI) and quality of life by IBD Control-8). It is routinely used by >2000 patients in Oxford. This study examined 114 patients with Crohn’s: 45 males (median age 36, IQR 28–51) and 69 females (median age 34.8, IQR 28–47), treated with ustekinumab for a maximum of 16 months (range -2 months to 14 months). A linear mixed-effects model was used to approximate longitudinal trends of HBI and IBD Control-8. 3 individual items of the HBI scale (general well-being, abdominal pain & stool frequency) were also assessed. The TC-IBD platform has the capacity to analyse and show patients’ data automatically, using customised models and algorithms through the feedback loop (Fig 1). Model coefficients, intercept and slope were estimated using the restricted maximum likelihood (REML) approach. The intercept corresponds to the expected cohort mean value of the scale (e.g. HBI, IBD Control-8) at baseline (time zero) and the slope describes the rate of the change over time Results The models’ coefficients, the intercept and slope of both HBI and IBD Control-8 scales were statistically significant and are summarised in Table 1 with confidence intervals. Both linear trends (slopes) describing HBI (p<0.001) and IBD Control-8 (p<0.001) confirmed improvements for patients. The bowel movement component of the HBI dominated over general well-being and abdominal pain, while keeping a similar downward trend over time ( Fig 2 and Fig 3a,b) Conclusion Patient reported data through the TC-IBD platform can be used for statistical analyses and continuous monitoring of drug effect over time. This analysis is limited by a lack of comparator group, but the models may be used with the TrueColours platform as a decision support tool for other drugs

scholarly journals A systematic conservation planning approach to maintaining ecosystem service provision in working landscapes

FACETS ◽  
2021 ◽  
Vol 6 ◽  
pp. 1570-1600
Author(s):  
Jérôme Cimon-Morin ◽  
Jean-Olivier Goyette ◽  
Poliana Mendes ◽  
Stéphanie Pellerin ◽  
Monique Poulin
Keyword(s):  
Land Use ◽  
Decision Support ◽  
Conservation Planning ◽  
Decision Support Tool ◽  
Well Being ◽  
Efficient Production ◽  
Systematic Conservation Planning ◽  
Support Tool ◽  
Working Landscapes ◽  
Trade Offs

Balancing human well-being with the maintenance of ecosystem services (ES) for future generations has become one of the central sustainability challenges of the 21st century. In working landscapes, past and ongoing production-centered objectives have resulted in the conversion of ecosystems into simple land-use types, which has also altered the provision of most ES. These inevitable trade-offs between the efficient production of individual provisioning ES and the maintenance of regulating and cultural ES call for the development of a land-use strategy based on the multifunctional use of the landscape. Due to the heterogeneous nature of working landscapes, both protection and restoration actions are needed to improve their multifunctionality. Systematic conservation planning (SCP) offers a decision support framework that can support landscape multifunctionality by indicating where ES management efforts should be implemented. We describe an approach that we developed to include ES provision protection and restoration objectives in SCP with the goal of providing ongoing benefits to society. We explain the general framework of this approach and discuss concepts, challenges, innovations, and prospects for the further development of a comprehensive decision support tool. We illustrate our approach with two case studies implemented in the pan-Canadian project ResNet.

Real-Time Monitoring of Intercity Passenger Flows Based on Big Data

2019 ◽  
pp. 793-801
Author(s):  
Zheng Li ◽  
Yan Wang ◽  
Qin Chen
Keyword(s):  
Big Data ◽  
Real Time ◽  
Public Transport ◽  
Low Cost ◽  
Decision Support Tool ◽  
Population Mobility ◽  
Population Movements ◽  
Policy Makers ◽  
Support Tool ◽  
Passenger Flows

Managing population mobility is a key to urban growth and sustainable development. This study uses administrative and business data from a number of trustworthy and publicly-available websites for public transport to access passenger flows in a real-time manner. A case study is used to illustrate the application, with intercity passenger flows by public transport mode (rail or air), by rail service type and by time. Moreover, a model is developed for monitoring the implications of population movements, which can be a decision support tool for governments and policy makers to manage population mobility. The big-data approach to accessing public transport passenger movement has the following characteristics: (1) low cost, (2) a population scale, (3) instantaneous data collection/update, and (4) high quality.

scholarly journals Automatic determination of lung features of CF patients in CT scans

2016 ◽  
Vol 2 (1) ◽  
pp. 519-522
Author(s):  
Tanusree Chaudhuri ◽  
Bo Gong ◽  
Sabine Krueger-Ziolek ◽  
Benjamin Schullcke ◽  
Knut Moeller
Keyword(s):  
Automatic System ◽  
Decision Support Tool ◽  
Ct Scans ◽  
Automatic Determination ◽  
High Resolution Computed Tomography ◽  
Support Tool ◽  
High Attenuation ◽  
Disease Stages ◽  
Ct Slices

AbstractThis paper describes a prototype of an automatic system for the detection and evaluation of Cystic fibrosis features (CF) in High resolution computed tomography (HRCT) Scans. The aim of this study lies in presenting this system as a decision support tool for radiologists in future. The CF features that have been detected and evaluated are Bronchiectasis and Mucus Plugging. This system recognizes Bronchiectasis as the presence of enlarged airways in pulmonary CF-CT slices whereas, Mucus Plugging has been recognized as clusters of high attenuation pixels. The dataset of this study consists of HRCT Scans of five CF patients of varying disease stages. Mean percentages of these CF features that were computed for each intercostal space, starting from the first to the fifth, fairly accurately match the different stages of the disease.

scholarly journals A decomposition solution approach to the troops-to-tasks assignment in military peacekeeping operations

2019 ◽  
Vol 17 (4) ◽  
pp. 357-371
Author(s):  
Nadia Chaudry ◽  
Ingunn Vermedal ◽  
Kjetil Fagerholt ◽  
Maria Fleischer Fauske ◽  
Magnus Stålhane
Keyword(s):  
Computational Study ◽  
A Priori ◽  
Real Life ◽  
Decision Support Tool ◽  
Compact Model ◽  
Support Tool ◽  
Solution Approach ◽  
Peacekeeping Operations ◽  
Starting Point ◽  
Commercial Solver

This paper considers the Peacekeeping Troops-to-Tasks Problem (PTTP). The PTTP deals with assigning battlegroup resources to a set of tasks associated with a given peacekeeping mission. The tasks may be spread across several locations, and have requirements regarding the time at which they can be handled, and the skills and skill levels needed to complete them. There is also a utility value related to each completed task that reflects its importance. The resources are bound by a hierarchy of command, limiting their movement in relation to one another. The aim is to decide which tasks to complete, when, and by whom. We present a mathematical compact model for the PTTP, which includes a number of complicating real-life factors. Due to the complexity of the compact model, it is difficult to solve large instances using a commercial solver. Therefore, we also propose a decomposition-based solution approach, with a decomposed model where possible travel routes for the resources are generated a priori. The computational study shows that the decomposed model has better performance than the compact model, and that it can be used as a good starting point for developing a useful decision support tool for military peacekeeping operations planning.

scholarly journals Cardiac well-being indexes: a decision support tool to monitor cardiovascular health

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Ana Duarte ◽  
Orlando Belo
Keyword(s):  
Data Warehouse ◽  
Continuous Monitoring ◽  
Cardiovascular Health ◽  
Healthy Lifestyle ◽  
Decision Support Tool ◽  
Well Being ◽  
Self Assessment ◽  
Support Tool ◽  
Balanced Diet ◽  
Implementation Data

Abstract Despite the increasing awareness about its severity and the importance of adopting preventive habits, cardiovascular disease remains the leading cause of death worldwide. Most people already recognize that a healthy lifestyle, which includes a balanced diet and the practice of physical activity, is essential to prevent this disease. However, since few simple mechanisms allow a self-assessment and a continuous monitoring of the level of cardiac well-being, people are not conscious enough about their own cardiovascular health status. In this context, this paper presents and describes a tool related to the creation of cardiac well-being indexes that allow a quick and intuitive monitoring and visualization of the users’ cardiovascular health level over time. For its implementation, data mining techniques were used to calculate the indexes, and a data warehouse was built to archive the data and to support the construction of dashboards for presenting the results.

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