An Interactive Approach Based on Alternative Achievement Scale and Alternative Comprehensive Scale for Multiple Attribute Decision Making under Linguistic Environment

The aim of this paper is to develop an interactive approach for multiple attribute decision making with incomplete weight information under linguistic environment. Some of the concepts are defined, such as the distance between two 2-tuple linguistic variables, the expectation level of alternative, the achievement scale, the alternative comprehensive scale under linguistic environment. Based on these concepts, we establish some linear programming models, through which the decision maker interacts with the analyst. Furthermore, we establish a practical interactive approach for selecting the most desirable alternative(s). The interactive process can be realized by giving and revising the achievement scale and comprehensive scale of alternatives till the achievement scale and the comprehensive scale are achieved to the decision maker’s request. Finally, an illustrative example is also given.The author is very grateful to the associated editor and two anonymous referees for their insightful and constructive comments and suggestions that have led to an improved version of this paper. This work was partly supported by the National Natural Science Foundation of China (No. 90924027, No. 71101043), National Basic Research Program of China (973 Program, No. 2010C B951104), Key Program of National Social Science Foundation of China (No. 10AJY005), College Philosophy and Social Science Research Project of Jiangsu Province under Grant 2011SJD630007.Xu, Y.; Wang, H.; Palacios Marqués, D. (2013). An Interactive Approach Based on Alternative Achievement Scale and Alternative Comprehensive Scale for Multiple Attribute Decision Making under Linguistic Environment. International Journal of Computational Intelligence Systems. 6(1):87-95. https://doi.org/10.1080/18756891.2013.756226S87956

Regular dietary intake of palmitate causes vascular and valvular calcification in a rabbit model

Aims: Palmitic acid (PA) and oleic acid (OA) are two main dietary fatty acids. Dietary intake of PA has been associated with cardiovascular disease risk, and the effect of OA remains uncertain. Our study aimed to assess the effect of a short-term intake of lard, as source of PA and OA, on aorta and aortic valve.Methods and Results: Rabbits were fed with two lard-enriched diets, containing either elevated levels of PA or of both PA and OA as compared to chow diet. After 16 weeks of each diet, calcification was observed in the aortic intima and in the aortic valve. The extent of calcification did not differ between the two diets. In contrast, rabbits fed chow diet did not develop any calcification. In blood, PA enrichment resulted in decreased lymphocyte and monocyte counts and increased levels of hemoglobin and haematocrit. Levels of the calcification inhibitor fetuin-A were also diminished, whereas creatinine levels were raised. Of note, none of the diets changed cholesterol levels in LDL or HDL. Comprehensive quantitative lipidomics analysis identified diet-related changes in plasma lipids. Dietary PA enrichment led to a drop of polyunsaturated fatty acids (PUFA), in particular of linoleic acid in cholesteryl esters, triglycerides and diacylglycerols (DAG). Ratios of PA to 18-carbon PUFA in DAG were positively correlated with the extent of aortic valve calcification, and inversely with monocyte counts. PA content in blood correlated with aorta calcification.Conclusions: Regular dietary PA intake induces vascular and valvular calcification independently of traditional risk factors. Our findings raise awareness about PA-rich food consumption and its potential deleterious effect on cardiovascular health.Proteomic

Modeling, optimizing and simulating robot calibration with accuracy improvement

This work describes techniques for modeling, optimizing and simulating calibration processes ofrobots using off-line programming. The identification of geometric parameters of the nominalkinematic model is optimized using techniques of numerical optimization of the mathematicalmodel. The simulation of the actual robot and the measurement system is achieved by introducingrandom errors representing their physical behavior and its statistical repeatability. An evaluationof the corrected nominal kinematic model brings about a clear perception of the influence ofdistinct variables involved in the process for a suitable planning, and indicates a considerableaccuracy improvement when the optimized model is compared to the non-optimized one

Clustering Algorithms: Their Application to Gene Expression Data

Gene expression data hide vital information required to understand the biological process that takes place in a particular organism in relation to its environment. Deciphering the hidden patterns in gene expression data proffers a prodigious preference to strengthen the understanding of functional genomics. The complexity of biological networks and the volume of genes present increase the challenges of comprehending and interpretation of the resulting mass of data, which consists of millions of measurements; these data also inhibit vagueness, imprecision, and noise. Therefore, the use of clustering techniques is a first step toward addressing these challenges, which is essential in the data mining process to reveal natural structures and iden-tify interesting patterns in the underlying data. The clustering of gene expression data has been proven to be useful in making known the natural structure inherent in gene expression data, understanding gene functions, cellular processes, and subtypes of cells, mining useful information from noisy data, and understanding gene regulation. The other benefit of clustering gene expression data is the identification of homology, which is very important in vaccine design. This review examines the various clustering algorithms applicable to the gene expression data in order to discover and provide useful knowledge of the appropriate clustering technique that will guarantee stability and high degree of accuracy in its analysis procedure

The burden of unintentional drowning: Global, regional and national estimates of mortality from the Global Burden of Disease 2017 Study

__Background:__ Drowning is a leading cause of injury-related mortality globally. Unintentional drowning (International Classification of Diseases (ICD) 10 codes W65-74 and ICD9 E910) is one of the 30 mutually exclusive and collectively exhaustive causes of injury-related mortality in the Global Burden of Disease (GBD) study. This study's objective is to describe unintentional drowning using GBD estimates from 1990 to 2017. __Methods:__ Unintentional drowning from GBD 2017 was estimated for cause-specific mortality and years of life lost (YLLs), age, sex, country, region, Socio-demographic Index (SDI) quintile, and trends from 1990 to 2017. GBD 2017 used standard GBD methods for estimating mortality from drowning. __Results:__ Globally, unintentional drowning mortality decreased by 44.5% between 1990 and 2017, from 531 956 (uncertainty interval (UI): 484 107 to 572 854) to 295 210 (284 493 to 306 187) deaths. Global age-standardised mortality rates decreased 57.4%, from 9.3 (8.5 to 10.0) in 1990 to 4.0 (3.8 to 4.1) per 100 000 per annum in 2017. Unintentional drowning-associated mortality was generally higher in children, males and in low-SDI to middle-SDI countries. China, India, Pakistan and Bangladesh accounted for 51.2% of all drowning deaths in 2017. Oceania was the region with the highest rate of age-standardised YLLs in 2017, with 45 434 (40 850 to 50 539) YLLs per 100 000 across both sexes. __Conclusions:__ There has been a decline in global drowning rates. This study shows that the decline was not consistent across countries. The results reinforce the need for continued and improved policy, prevention and research efforts, with a focus on low-and middle-income countries

Search for leptophobic Z ' bosons decaying into four-lepton final states in proton-proton collisions at root s=8 TeV

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Search for black holes and other new phenomena in high-multiplicity final states in proton-proton collisions at root s=13 TeV

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Search for heavy resonances decaying into a vector boson and a Higgs boson in final states with charged leptons, neutrinos, and b quarks

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