This study develops a decision-making procedure to help policymakers compare alternative patterns for sustainable diets by reaching a compromise among three criteria: socio-economic perspective, health and environment (including carbon and water footprints). An Analytical Hierarchy Process (AHP) was performed in several stages. First, a total of 25 stakeholders (members of organizations on the Valencia Food Policy Council) evaluated criteria that are relevant to the sustainability of diets. Secondly, a workshop with 14 experts from different backgrounds evaluated by consensus four dietary alternatives: Mediterranean, flexitarian, pescatarian and vegan. In terms of environment, experts gave priority to the vegan diet. However, the Mediterranean diet pattern (MDP) appeared, according to the process, as the most suitable pattern from the holistic perspective that integrates all relevant criteria. The MDP was ranked first in terms of the health criterion and the socio-economic perspective. These include culture, affordability, social impact and local production as decision elements that food policy advisory bodies take into consideration to define sustainable diets.

Many local breeds have become endangered due to their substitution by high-yielding breeds. To conserve local breeds, effective development strategies need to be investigated. The aim of this study was to explore conservation and development strategies based on quantified strengths, weaknesses, opportunities and threats (SWOT) for two local cattle breeds from Northern Germany, namely the German Angler (GA) and Red Dual-Purpose cattle (RDP). The data comprised 158 questionnaires regarding both breeds’ SWOT, which were answered by 78 farmers of GA and 80 farmers of RDP. First, data were analysed using the SWOT-Analytic Hierarchy Process (AHP) method, which combines the qualitative strategic decision tool of SWOT analysis and the quantitative tool of AHP. Second, prioritised SWOT factors were discussed with stakeholders in order to form final conservation and development strategies at breed level. For GA prioritised strengths were daily gain, meat quality, milk production and the usage of new biotechnologies, weaknesses were genetic gain in milk production and inbreeding, opportunities were organic farming and breed-specific characteristics and threats were milk prices and dependency regarding the dairy business. Consequently, three conservation and development strategies were formed: (1) changing relative weights and the relevant breeding goal to drift from milk to meat, (2) increasing genetic gain and control the rate of inbreeding by the implementation of specific selection programs and (3) selection of unique and breed characteristic components on product level, that is, milk-fat and fine muscle fibers. For RDP defined strengths were robustness, high adaptability for different housing systems and a balanced dual-purpose of milk and meat, weaknesses were inbreeding, breed extinction, genomic selection with young bulls and milk yield, opportunities were organic farming and dual-purpose aspects and threats were milk and decreasing beef cattle prices. Thus, three conservation and development strategies were identified: (1) adjust relative weights and the relevant breeding goal to balance milk and meat yield, (2) increasing genetic gain and avoid extinction by implementing targeted selection programs and (3) selection of unique and breed characteristic traits on breed level, that is, environmental robustness. Quantified SWOT establish a basis for the exploration of conservation and development strategies at breed level. Explored strategies are promising even if the stakeholder approach was limited for small populations regarding a small number of stakeholder groups. The used approach reflects farmers’ individual convenience better than existing quantitative strategy decision tools on their own.

Background: Cardiovascular disease is one of the most common causes of death worldwide, with many individuals having experienced acute coronary syndrome (ACS). How patients with a history of ACS value aspects of their medical treatment have been evaluated rarely. The aim of this study was to determine patient priorities for long-term drug therapy after experiencing ACS.

Methods: To identify patient-relevant treatment characteristics, a systematic literature review and qualitative patient interviews were conducted. A questionnaire was developed to elicit patient's priorities for different characteristics of ACS treatment using Analytic Hierarchy Process (AHP). To evaluate the patient-relevant outcomes, the eigenvector method was applied.

Results: Six-hundred twenty-three patients participated in the computer-assisted personal interviews and were included in the final analysis. Patients showed a clear priority for the attribute “reduction of mortality risk” (weight: 0.402). The second most preferred attribute was the “prevention of a new myocardial infarction” (weight: 0.272), followed by “side effect: dyspnea” (weight: 0.165) and “side effect: bleeding” (weight: 0.117). The “frequency of intake” was the least important attribute (weight: 0.044).

Conclusion: In conclusion, this study shows that patients strongly value a reduction of the mortality risk in post-ACS treatment. Formal consideration of patient preferences and priorities can help to inform a patient-centered approach, clinical practice, development of future effective therapies, and health policy for decision makers that best represents the needs and goals of the patient.

Using agricultural preservation priorities derived from an analytical hierarchy process by 23 conservation experts from 18 agencies in the state of Delaware, this research uses weighted benefit measures to evaluate the historical success of Delaware's agricultural protection fund, which spent nearly $100 million in its first decade. This research demonstrates how these operation research techniques can be used in concert to address relevant conservation questions. Results suggest that the state's sealed-bid-offer auction, which determines the yearly conservation selections, is superior to benefit-targeting approaches frequently employed by conservation organizations, but is inferior to the optimization technique of binary linear programming that could have provided additional benefits to the state, such as 12,000 additional acres worth an estimated $25 million.

Large carnivores are recolonizing parts of North America and Europe as a result of modern management and conservation policy. In the midwestern USA, black bears Ursus americanus, cougars Puma concolor and grey wolves Canis lupus have the potential to recolonize provided there is suitable habitat. Understanding where large carnivores may become re-established will prepare resource professionals for the inevitable ecosystem effects and potential human–carnivore conflicts associated with these species. We developed individual and combined models of suitable habitat for black bears, cougars and wolves in 18 midwestern states, using geospatial data, expert-opinion surveys, and multi-criteria evaluation. Large, contiguous areas of suitable habitat comprised 35, 21 and 13% of the study region for wolves, bears and cougars, respectively. Approximately 12% of the region was considered suitable for all three species. Arkansas, Minnesota, Texas and Wisconsin had the highest proportions (> 40%) of suitable habitat for black bears; Arkansas, Michigan, Missouri, Texas and Wisconsin had the highest proportions (≥ 20%) of suitable habitat for cougars; and only in four states in the study region was < 29% of land suitable wolf habitat. Models performed well when validated by comparing suitability values of independent sets of known carnivore locations to those of random locations. Contiguous areas of suitable habitat typically spanned multiple states, thus coordination across boundaries and among agencies will be vital to successful conservation of these species. Our models highlight differences in habitat requirements and geographical distribution of potential habitat among these carnivores, as well as areas vital to their persistence in the Midwest.

Grasshopper plagues have seriously disturbed grassland ecosystems in Inner Mongolia, China. The accurate prediction of grasshopper infestations and control of grasshopper plagues have become urgent needs. We sampled 234, 342, 335, and 369 plots in Xianghuangqi County of Xilingol League in 2010, 2011, 2012, and 2013, respectively, and measured the density of the most dominant grasshopper species, Oedaleus decorus asiaticus, and the latitude, longitude, and associated relatively stable habitat factors at each plot. We used Excel–GeogDetector software to explore the effects of individual habitat factors and the two-factor interactions on grasshopper density. We estimated the membership of each grasshopper density rank and determined the weights of each habitat category. These results were used to construct a model system evaluating grasshopper habitat suitability. The results showed that our evaluation system was reliable and the fuzzy evaluation scores of grasshopper habitat suitability were good indicators of potential occurrence of grasshoppers. The effects of the two-factor interactions on grasshopper density were greater than the effects of any individual factors. O. d. asiaticus was most likely to be found at elevations of 1300–1400 m, flat terrain or slopes of 4–6°, typical chestnut soil with 70–80% sand content in the top 5 cm of soil, and medium-coverage grassland. The species preferred temperate bunchgrass steppe dominated by Stipa krylovii and Cleistogenes squarrosa. These findings may be used to improve models to predict grasshopper occurrence and to develop management guidelines to control grasshopper plagues by changing habitats.

The goal of machining scheme selection (MSS) is to select the most appropriate machining scheme for a previously designed part, for which the decision maker must take several aspects into consideration. Because many of these aspects may be conflicting, such as time, cost, quality, profit, resource utilization, and so on, the problem is rendered as a multiobjective one. Consequently, we consider a multiobjective optimization problem of MSS in this study, where production profit and machining quality are to be maximized while production cost and production time must be minimized, simultaneously. This paper presents a new discrete method for particle swarm optimization, which can be widely applied in MSS to find out the set of Pareto-optimal solutions for multiobjective optimization. To deal with multiple objectives and enable the decision maker to make decisions according to different demands on each evaluation index, an analytic hierarchy process is implemented to determine the weight value of evaluation indices. Case study is included to demonstrate the feasibility and robustness of the hybrid algorithm. It is shown from the case study that the multiobjective optimization model can simply, effectively, and objectively select the optimal machining scheme according to the different demands on evaluation indices.