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This paper is a continuation of our paper10,11 and formulates a fuzzy team decision problem of type 2. The concept of fuzzy sets of type 2 is introduced to formulate the team decision processes which contain fuzzy‐fuzzy states, fuzzy‐fuzzy information functions, fuzzy‐fuzzy information signals, fuzzy‐fuzzy decision functions and fuzzy‐fuzzy actions. After some definitions of fuzzy‐fuzzy relations and fuzzy‐fuzzy mappings, a model of fuzzy team decision of type 2 is proposed.

Coronary artery disease (CAD) is developed by an insufficient supply of oxygen-rich blood to the myocardium. Recent studies have shown that increased oxidative stress has implicated in the pathogenesis of coronary atherosclerosis. Anxiety and CAD have a mutual relationship, as the effect of long-lasting anxiety on atherosclerosis and CAD is well known. The purpose of this study is to investigate the relationship between dietary / serum total antioxidant capacity and CAD.

A total of 160 male patients were enrolled in this cross-sectional study. Diagnosis and analysis of angiograms were performed visually by a cardiologist. The subjects were categorized into CAD− (coronary artery obstruction <75 per cent) and CAD+ (coronary artery obstruction ≥ 75 per cent) groups. Anthropometric indices, blood pressure, blood sugar and lipid profile and physical activity (PA) were assessed. Information about anxiety was obtained by Spielberger questionnaire. Dietary total antioxidant capacity (TAC) was obtained by using a semi-quantitative food frequency questionnaire and an oxygen radical absorbance capacity of selected foods.

Mean of dietary TAC was significantly lower in CAD+ than CAD− group (P < 0.001). However, there was not any significant differences about serum TAC (P = 0.28). The mean of body mass index (BMI) (P = 0.04) and triglyceride (TG) level (P = 0.03) and the frequency of smoking (P = 0.03) were significantly higher in the CAD+ than the CAD− group. There was no significant relationship between CAD with apparent (P = 0.33) and hidden anxiety level (P = 0.16). Confounding factors such as smoking and medications were adjusted.

This study had certain limitations. Being a single center cross-sectional design does not permit analysis of causal relationships; the sample size was geographically limited. The authors could not exclude the medication of patients, which could affect the total antioxidant capacity levels. Measurement error in self-reported dietary consumption may results misclassification of exposure.

A diet high in total antioxidant capacity is inversely associated with CAD. Serum TAC does not vary between men with and without CAD when confounders including age, BMI, TG, smoking, SBP, DBP, energy intake, PA, HDL-C, LDL-C, T-C, FBS, family history of CAD, education and anxiety are taken into consideration.

High consumption of vegetables and fruits may play a major role in the prevention of CAD.

The study was approved by the ethics committee of Isfahan University of Medical Sciences (No:394888).

Time to market is the essential aim of any new product introduction process. Performance measures are simple quantities that indicate the state of manufacturing organisations and are used as the basis of decision‐making at this crucial early stage of the process. Fuzzy set theory is a method for using qualitative data and subjective opinion. Fuzzy sets have been used extensively in manufacturing for applications including control, decision‐making, and estimation. Type‐2 fuzzy sets are a novel extension of type‐1 fuzzy sets. Aims to examine this subject.

This research explores the increased use of type‐2 fuzzy sets in manufacturing. In particular, type‐2 fuzzy sets are used to model “the words that mean different things to different people”.

A model that can leverage design process knowledge and predict time to market from performance measures is a potentially valuable tool for decision making and continuous improvement. A number of data sources, such as process maps, from previous research into time to market in a high technology products company, are used to structure and build a type‐2 fuzzy logic model for the prediction of time to market.

This paper presents a demonstration of how the type‐2 fuzzy logic model works and provides directions for further research into the design process for time to market.

In the past decade, three-dimensional (3D) printing has gained attention in areas such as medicine, engineering, manufacturing art and most recently in education. In biomedical, the development of a wide range of biomaterials has catalysed the considerable role of 3D printing (3DP), where it functions as synthetic frameworks in the form of scaffolds, constructs or matrices. The purpose of this paper is to present the state-of-the-art literature coverage of 3DP applications in tissue engineering (such as customized scaffoldings and organs, and regenerative medicine).

This review focusses on various 3DP techniques and biomaterials for tissue engineering (TE) applications. The literature reviewed in the manuscript has been collected from various journal search engines including Google Scholar, Research Gate, Academia, PubMed, Scopus, EMBASE, Cochrane Library and Web of Science. The keywords that have been selected for the searches were 3 D printing, tissue engineering, scaffoldings, organs, regenerative medicine, biomaterials, standards, applications and future directions. Further, the sub-classifications of the keyword, wherever possible, have been used as sectioned/sub-sectioned in the manuscript.

3DP techniques have many applications in biomedical and TE (B-TE), as covered in the literature. Customized structures for B-TE applications are easy and cost-effective to manufacture through 3DP, whereas on many occasions, conventional technologies generally become incompatible. For this, this new class of manufacturing must be explored to further capabilities for many potential applications.

This review paper presents a comprehensive study of the various types of 3DP technologies in the light of their possible B-TE application as well as provides a future roadmap.

Researchers and practitioners of international market entry typically have a difficult task obtaining and processing requisite information to evaluate potential opportunities and risks. Essential analysis is often confounded by inappropriate measures of input requirements, inadequately defined information categories, and the overall complex nature of the decision process. In partial response to these issues, this research introduces a three-stage guiding framework for market-entry decision and presents alternative methodologies for country risk assessment, a principal component in the final stage. A variety of discrete methods are included such as subjective interaction by deliberating experts, scoring models, the analytic hierarchy process, simulation, and statistical designs using regression or factor analysis. New analytic rule-based nondiscrete techniques utilizing fuzzy logic are also introduced. Fuzzy logic simulates natural discourse and analogical reasoning through inference about nebulous facts and inexact concepts, using rules that do not require a perfect match between input data and their antecedental values in order to fire. It provides formal mathematical structure for representing, evaluating, and interpreting linguistic context. It is especially useful for handling problematical issues such as imprecise data, ambiguous information, vague meanings of terms, and inconsistent analyses that characterize the general market-entry problem and risk assessment in particular. Numerical examples demonstrate how discrete and fuzzy models work to integrate political, social, and financial risks.

The widespread introduction of genetically modified (GM) crops may change the effect of agriculture on the environment. The magnitude and direction of expected effects are still being hotly debated, and the interests served in this discussion arena are often far from those of science and social welfare maximization. This chapter proposes that GM crops have net positive environmental effects, while regulatory responses focus mainly on environmental concerns, giving an unbalanced picture of the regulatory context. This unbalance supports the hypothesis that environmental concerns about GM crops have been politically instrumentalized and that more attention should be paid to regulatory responses considering the environmental benefits of this technology. It is also argued that a number of environmental effects have not yet been quantified and more research is needed in this direction.

The purpose of this paper is to design a multi-sensory anthropomorphic prosthetic hand and a grasping controller that can detect the slip and automatically adjust the grasping force to prevent the slip.

To improve the dexterity, sensing, controllability and practicability of a prosthetic hand, a modular and multi-sensory prosthetic hand was presented. In addition, a slip prevention control based on the tactile feedback was proposed to improve the grasp stability. The proposed controller identifies slippages through detecting the high-frequency vibration signal at the sliding surface in real time and the discrete wavelet transform (DWT) was used to extract the eigenvalues to identify slippages. Once the slip is detected, a direct-feedback method of adjusting the grasp force related with the sliding times was used to prevent it. Furthermore, the stiffness of different objects was estimated and used to improve the grasp force control. The performances of the stiffness estimation, slip detection and slip control are experimentally evaluated.

It was found from the experiment of stiffness estimation that the accuracy rate of identification of the hard metal bottle could reach to 90%, while the accuracy rate of identification of the plastic bottles could reach to 80%. There was a small misjudgment rate in the identification of hard and soft plastic bottles. The stiffness of soft plastic bottles, hard plastic bottles and metal bottles were 0.64 N/mm, 1.36 N/mm and 32.55 N/mm, respectively. The results of slip detection and control show that the proposed prosthetic hand with a slip prevention controller can fast and effectively detect and prevent the slip for different disturbances, which has a certain application prospect.

Due to the small size, low weight, high integration and modularity, the prosthetic hand is easily applied to upper-limb amputees. Meanwhile, the method of the slip prevention control can be used for upper-limb amputees to complete more tasks stably in daily lives.

A multi-sensory anthropomorphic prosthetic hand is designed, and a method of stable grasps control based on slip detection by a tactile sensor on the fingertip is proposed. The method combines the stiffness estimation of the object and the real-time slip detection based on DWT with the design of the proportion differentiation robust controller based on a disturbance observer and the force controller to achieve slip prevention and stable grasps. It is verified effectively by the experiments and is easy to be applied to commercial prostheses.

Recent years have witnessed the rapid development of massive open online courses (MOOCs). With more and more courses being produced by instructors and being participated by learners all over the world, unprecedented massive educational resources are aggregated. The educational resources include videos, subtitles, lecture notes, quizzes, etc., on the teaching side, and forum contents, Wiki, log of learning behavior, log of homework, etc., on the learning side. However, the data are both unstructured and diverse. To facilitate knowledge management and mining on MOOCs, extracting keywords from the resources is important. This paper aims to adapt the state-of-the-art techniques to MOOC settings and evaluate the effectiveness on real data. In terms of practice, this paper also tries to answer the questions for the first time that to what extend can the MOOC resources support keyword extraction models, and how many human efforts are required to make the models work well.

Based on which side generates the data, i.e instructors or learners, the data are classified to teaching resources and learning resources, respectively. The approach used on teaching resources is based on machine learning models with labels, while the approach used on learning resources is based on graph model without labels.

From the teaching resources, the methods used by the authors can accurately extract keywords with only 10 per cent labeled data. The authors find a characteristic of the data that the resources of various forms, e.g. subtitles and PPTs, should be separately considered because they have the different model ability. From the learning resources, the keywords extracted from MOOC forums are not as domain-specific as those extracted from teaching resources, but they can reflect the topics which are lively discussed in forums. Then instructors can get feedback from the indication. The authors implement two applications with the extracted keywords: generating concept map and generating learning path. The visual demos show they have the potential to improve learning efficiency when they are integrated into a real MOOC platform.

Conducting keyword extraction on MOOC resources is quite difficult because teaching resources are hard to be obtained due to copyrights. Also, getting labeled data is tough because usually expertise of the corresponding domain is required.

The experiment results support that MOOC resources are good enough for building models of keyword extraction, and an acceptable balance between human efforts and model accuracy can be achieved.

This paper presents a pioneer study on keyword extraction on MOOC resources and obtains some new findings.

This study aims to compare the physical fitness test results of Japanese children in 2008 and 2018 to narrow the gap between life expectancy and healthy life expectancy and extend healthy life expectancy. In addition, this paper sought to explore the potential of implementing health education programs as a new social context to promote race equality and human rights in health and social care.

This study was conducted in 2008 and 2018 in Nagano Prefecture, Japan. Physical fitness tests related to growth and development were administered to participants aged 6–17 years.

Physical fitness measurements in 2018, specifically those for walking ability and endurance, were significantly inferior to those in 2008. In a gender-specific analysis, boys outperformed girls in muscle strength, muscle endurance, walking ability and endurance tests, while girls outperformed boys in the balance test.

Most of the junior and senior high school students who participated in the EO test exceeded the upper limit of 120 s, suggesting that the load of the measurement method is low and improvement is necessary. In 2018, a large variation in 6M results was observed among participants, possibly due to the differences in the level of seriousness during the 6M test. Therefore, to ensure that junior and senior high school students properly perform the EO and 6M tests, it is necessary to devise an effective method of implementation, such as changing the physical fitness test load.

Mere health education is ineffective to address health inequalities. Addressing structural factors is essential to avoid unintended consequences such as increasing the gap between groups of people. However, one way to extend healthy life expectancy is to improve overall health, including differences in the health status of groups due to differences in region and socioeconomic status.

This study aims to evaluate a human rights-informed dementia prevention program promoting better health and social care among older adults. In this study, the authors examined whether a dual-task training would improve cognition in healthy older adults.

Individuals attending the systematic health education program for older adults based in Japan were recruited for study inclusion, and divided into a dual-task training group (TG) and a control group (CG). The TG underwent 90 min of a weekly dual-task training for 12 weeks. Severity of dementia was measured using the Mini-Mental State Examination (MMSE) test. Brain function was assessed using a go/no-go task paradigm, during which cerebral blood flow was additionally measured using functional near-infrared spectroscopy to quantify oxyhemoglobin (oxy-Hb).

MMSE total score, number of errors in the go/no-go tasks and oxy-Hb values showed significant improvements in the TG.

Owing to the small number of participants allocated to the CG, the results must be interpreted with caution. Replication and further validation based on large-scale, randomized-controlled trials is warranted.

This study highlights potential benefits of incorporating an early prevention training for dementia into a human rights-friendly health education program.

This study suggests a potential means to reduce costs of social security and health care by introducing a human rights-informed dementia prevention program.

The results suggest that dual-task training may improve cognitive function in healthy older adults, thereby contributing to better health and improvement of social health care, based on a human rights-informed health education program for the prevention of dementia.