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This paper aims to evaluate the effect of consumption of a high-fat diet (HFD) rich with total saturated fats on adiposity and serum levels of vascular cell adhesion molecule (sVCAM-1), a biomarker of endothelial inflammation/dysfunction. Another aim is to evaluate whether supplementation of a phytosomal formulation of curcumin would reduce adiposity measures and sVCAM-1 levels in HFD rats.

The study was conducted on 17 male rats which were allocated to one of three feeding regimen groups: normal diet (ND); HFD, or HFD with dietary phytosomal curcumin (HFD-C). Anthropometric measures were recorded weekly up to 20 weeks of feeding intervention, at the end of which, sVCAM-1 levels were also compared with one-way ANOVA and Tukey post-hoc analysis.

The HFD group had the greatest values for raw anthropometric data, and there was a group difference in anthropometric measures, however there was no significant difference between HFD and HFD-C for any measure. The gain at 20 weeks from initial values did reveal significant differences in weight and abdominal circumference between HFD and HFD-C groups. There were significant group differences in sVCAM-1 levels, with only HFD-C displaying significant lower levels than HFD group.

This is the first study that shows the capacity of a phytosomal formulation of curcumin in reducing adiposity and sVCAM-1 levels during daily intake of saturated fats above the recommended level. The results are promising in that this formulation can protect against endothelial inflammation/dysfunction, and can be used as complimentary therapy to suppress dyslipidemia/obesity-related cardiovascular complications.

Intuitionistic linguistic fuzzy information (ILFI), characterized by linguistic terms and intuitionistic fuzzy sets (IFSs), can easily express the fuzzy information in the process of muticriteria decision making (MCDM) and muticriteria group decision making (MCGDM) problems. The purpose of this paper is to provide an overview of aggregation operators (AOs) and applications of ILFI.

First, some meaningful AOs for ILFI are summarized, and some extended MCDM approaches for intuitionistic uncertain linguistic variables (IULVs), such as extended TOPSIS, extended TODIM, extended VIKOR, are discussed. Then, the authors summarize and analyze the applications about the AOs of IULVs.

IULVs, characterized by linguistic terms and IFSs, can more detailed and comprehensively express the criteria values in the process of MCDM and MCGDM. Therefore, lots of researchers pay more and more attention to the MCDM or MCGDM methods with IULVs.

The authors summarize and analyze the applications about the AOs of IULVs Finally, the authors point out some possible directions for future research.

This research aims to demonstrate how the circular economy is employed to drive the sustainability of the tourism industry in Krabi, Thailand, through the concept of mindful consumption and service-dominant logic (hereafter S-D logic).

A seven-year longitudinal study (2013–2020) was conducted through four studies from different perspectives, including macro, meso and micro levels of development in Krabi province.

Krabi tourism stakeholders have collaborated to co-create green culture and behavior whereby the value network among stakeholders plays an important role in driving the circular economy in practice.

This study provides an understanding of how the circular economy society has been co-created. However, further research should be conducted in other tourism cities by focusing on the key success factors that drive the circular economy.

The longitudinal study with multi-perspective micro, macro and meso levels of development in this study has shed the light on how the circular economy (CE) policy can be turned into practice.

Extreme high temperatures are a significant feature of global climate change and have become more frequent and intense in recent years. These pose a significant threat to both human health and economic activity, and thus are receiving increasing research attention. Understanding the hazards posed by extreme high temperatures are important for selecting intervention measures targeted at reducing socioeconomic and environmental damage.

In this study, detrended fluctuation analysis is used to identify extreme high-temperature events, based on homogenized daily minimum and maximum temperatures from nine meteorological stations in a major grassland region, Hulunbuir, China, over the past 56 years.

Compared with the commonly used functions, Weibull distribution has been selected to simulate extreme high-temperature scenarios. It has been found that there was an increasing trend of extreme high temperature, and in addition, the probability of its indices increased significantly, with regional differences. The extreme high temperatures in four return periods exhibited an extreme low hazard in the central region of Hulunbuir, and increased from the center to the periphery. With the increased length of the return period, the area of high hazard and extreme high hazard increased. Topography and anomalous atmospheric circulation patterns may be the main factors influencing the occurrence of extreme high temperatures.

These results may contribute to a better insight in the hazard of extreme high temperatures, and facilitate the development of appropriate adaptation and mitigation strategies to cope with the adverse effects.

Autonomous ports and digital ports are a modern trend of global commercial ports that are established to develop toward smart ports in many ports. Smart port indicators (SPIs) are used as important tools for measuring, encouraging, and indicating smart port performance. These are the main indicators to operate smart port management as the practical direction and port development planning are enclosed. This research aims to identify the SPIs and to develop a conceptual model of smart port performance in a case study of The Eastern Economic Corridor (EEC) in Thailand. Triangulation data are used in the data collection with three sources: the reviewed literature of five international databases in 2016–2021, participant observations, and in-depth interviews. Content analysis is utilized to analyze these data to develop a conceptual model approach. The findings of this research are shown in three main domains classified as smart port operation, smart port environment/energy, and smart port safety/security. These indicators represent 29 SPIs for developing smart port performance, which can be explained with a conceptual model. This information will exist as the foundation framework guiding Thai smart ports towards international standards of smart port efficiency.

The purpose of this paper is to identify the structural similarities between stricto sensu post-graduation programs in management through the formation of clusters, with the strategy tripod as a backdrop (Peng, 2002; Peng et al., 2009).

The co-plot method was used as a tool. It was chosen because it simultaneously enables joint and individual observations of comments and variables.

The results showed the formation of clusters among the programs, identifying a series of similarities between their components. The age and number of lines of research of the programs were the determining variables to identify isomorphism among the clusters.

The main limitation of the study lies in the updating of information at the source of the data collection. All the data were collected from the Sucupira Platform for CAPES Triennial Evaluation of 2013. However, when the authors accessed the portals of the programs, the authors found that some data were outdated. Nevertheless, the authors limited themselves to using official data. Therefore, even if the authors found divergences or inconsistencies regarding the published information, the authors decided to use the official data made available by CAPES on the Sucupira Platform for the period in question.

Understanding that the results through the approaches of the industry-based view, resource-based view and institution-based view were insufficient for a thorough analysis, it is demonstrated in isolation that none of these succeeds in explaining the organizational context that permeates Brazilian stricto sensu post-graduation institutions. In this organizational field, the three views are not at the same theoretical level. The institutional view overlaps with the strategic competitive views. Therefore, the study contributes to reorganizing the strategy tripod and the proposed articulation between the arrangement of theory, method and field research.

The typical approach of modeling the aerodynamics of an aircraft is to develop a complete database through testing or computational fluid dynamics (CFD). The database will be huge if it has a reasonable resolution and requires an unacceptable CFD effort during the conceptional design. Therefore, this paper aims to reduce the computing effort required via establishing a general aerodynamic model that needs minor parameters.

The model structure was a preconfigured polynomial model, and the parameters were estimated with a recursive method to further reduce the calculation effort. To uniformly disperse the sample points through each step, a unique recursive sampling method based on a Voronoi diagram was presented. In addition, a multivariate orthogonal function approach was used.

A case study of a flying wing aircraft demonstrated that generating a model with acceptable precision (0.01 absolute error or 5% relative error) costs only 1/54 of the cost of creating a database. A series of six degrees of freedom flight simulations shows that the model’s prediction was accurate.

This method proposed a new way to simplify the model and recursive sampling. It is a low-cost way of obtaining high-fidelity models during primary design, allowing for more precise flight dynamics analysis.

This study aims to examine the impact of the decision makers’ risk preference on logistics routing problem, contributing to logistics behavior analysis and route integration optimization under uncertain environment. Due to the unexpected events and complex environment in modern logistics operations, the logistics process is full of uncertainty. Based on the chance function of satisfying the transportation time and cost requirements, this paper focuses on the fourth party logistics routing integrated optimization problem considering the chance preference of decision makers from the perspective of satisfaction.

This study used the quantitative method to investigate the relationship between route decision making and human behavior. The cumulative prospect theory is used to describe the loss, gain and utility function based on confidence levels. A mathematical model and an improved ant colony algorithm are employed to solve the problems. Numerical examples show the effectiveness of the proposed model and algorithm.

The study’s findings reveal that the dual-population improvement strategy enhances the algorithm’s global search capability and the improved algorithm can solve the risk model quickly, verifying the effectiveness of the improvement method. Moreover, the decision-maker is more sensitive to losses, and the utility obtained when considering decision-makers' risk attitudes is greater than that obtained when the decision-maker exhibits risk neutrality.

In an uncertain environment, the logistics decision maker’s risk preference directly affects decision making. Different parameter combinations in the proposed model could be set for decision-makers with different risk attitudes to fit their needs more accurately. This could help managers design effective transportation plans and improve service levels. In addition, the improved algorithm can solve the proposed problem quickly, stably and effectively, so as to help the decision maker to make the logistics path decision quickly according to the required confidence level.

Considering the uncertainty in logistics and the risk behavior of decision makers, this paper studies integrated routing problem from the perspective of opportunity preference. Based on the chance function of satisfying the transportation time and cost requirements, a fourth party logistics routing integrated optimization problem model considering the chance preference of decision makers is established. According to the characteristics of the problem, an improved dual-population ant colony algorithm is designed to solve the proposed model. Numerical examples show the effectiveness the proposed methods.