Severity of the metabolic syndrome as a predictor of prediabetes and type 2 diabetes in first degree relatives of type 2 diabetic patients:A 15-year prospective cohort study

BACKGROUND Type 2 diabetes mellitus(T2DM)has high morbidity and mortality worldwide,therefore there is of paramount importance to identify the risk factors in the populations at risk early in the course of illness.A strong correlation between severity of metabolic syndrome(MetS)and HbA1c,fasting insulin and insulin resistance has been reported.Accordingly,the MetS severity score(or MestS Zscore)can potentially be used to predict the risk of T2DM progression over time.AIM To evaluate the association the of MestS Z-score in first degree relatives(FDRs)of T2DM with the risk of prediabetes and type 2 diabetes in future.METHODS A prospective open cohort study was conducted between 2003-2018.At baseline,the sample comprised of 1766 FDRs of patients with T2DM who had a normal glucose tolerance test.Relative risk(RR)and 95%confidence interval were calculated based on logistic regression.The receiver-operator characteristic analysis and area under the curve based on MetS Z-score were used to evaluate the risk of prediabetes and diabetes among the FDR population.RESULTS Baseline MetS Z-scores were associated with the its latest values(P<0.0001).Compared with individuals who were T2DM free at the end of follow up,those who developed T2DM had higher MetS Z-score at baseline(P<0.001).In multivariable logistic regression analyses for every unit elevation in MetS Z-score at the baseline,the RR for developing future T2DM and prediabetes was(RR=1.94,RR=3.84),(RR=1.5,RR=2.17)in total population and female group,respectively(P<0.05).The associations remained significant after adjusting the potential confounding variables.A cut off value of 0.97 and 0.94 was defined in the receiver-operator characteristic curve based on the MetS Z-score for differentiating female patients with diabetes and prediabetes from the normal population,respectively.CONCLUSION The MetS Z-score was associated with an increased risk of future T2DM.Appropriate interventions at earlier stages for preventing and attenuating MetS effects may be considered as an effective strategy for FDR as at-risk population.

Algorithmic Design for the Examination Arrangement System on a Large Scale for Universities

It is a multifactor optimization problem to arrange examinations on a large scale for universities. In this paper, a kind of grouped optimization algorithm was proposed. A principle about related degree, which plays a core role in realization, was introduced in the algorithm. According to the algorithm, we worked out a set of software correspondingly and applied it to a certain university in Shanghai to arrange examinations. It shows that the algorithm is very effective.

Novel combinatorial algorithm for the problems of fuzzy grey multi-attribute group decision making

To study the fuzzy and grey information in the problems of multi-attribute group decision making, the basic concepts of both fuzzy grey numbers and grey interval numbers are given firstly, then a new model of fuzzy grey multi-attribute group decision making based on the theories of fuzzy mathematics and grey system is presented. Furthermore, the grey interval relative degree and deviation degree is defined, and both the optimistic algorithm of the grey interval relational degree and the algorithm of deviation degree minimization for solving this new model are also given. Finally, a decision making example to demonstrate the feasibility and rationality of this new method is given, and the results by using these two algorithms are uniform.

Fuzzy Optimum Model of Semi-Structural Decision for Lectotype Optimization of Offshore Platforms

In the process of concept design of offshore platforms, it is necessary to select the best from feasible alternatives through comparison and filter. The criterion set, used to evaluate and select the satisfying alternative, consists of many qualitative and quantitative factors. Therefore, the selection is a problem of multicriteria and semi-structural decision-making. Different from traditional methods in semi-structural decision-making, a new framework and methodology is presented in this paper for evaluation of offshore platform alternatives, First, the criterion set is established for the evaluation of alternatives. Next, the approach is studied to construct the relative membership degree matrix, in which both qualitative and quantitative factors are consistent with the uniform calculating standard. And then a new weight-assessing method is developed for calculation of the weights based on the relative membership degree matrix. Finally, a multi-hierarchy fuzzy optimum model is adopted to select the satisfying offshore platform alternative. A case study shows that the new framework and methodology are scientific, reasonable and easy to use in practice.

Comprehensive security risk factor identification for small reservoirs with heterogeneous data based on grey relational analysis model

Identification of security risk factors for small reservoirs is the basis for implementation of early warning systems.The manner of identification of the factors for small reservoirs is of practical significance when data are incomplete.The existing grey relational models have some disadvantages in measuring the correlation between categorical data sequences.To this end,this paper introduces a new grey relational model to analyze heterogeneous data.In this study,a set of security risk factors for small reservoirs was first constructed based on theoretical analysis,and heterogeneous data of these factors were recorded as sequences.The sequences were regarded as random variables,and the information entropy and conditional entropy between sequences were measured to analyze the relational degree between risk factors.Then,a new grey relational analysis model for heterogeneous data was constructed,and a comprehensive security risk factor identification method was developed.A case study of small reservoirs in Guangxi Zhuang Autonomous Region in China shows that the model constructed in this study is applicable to security risk factor identification for small reservoirs with heterogeneous and sparse data.

Decoupling Control Method Based on Neural Network for Missiles

In order to make the static state feedback nonlinear decoupling control law for a kind of missile to be easy for implementation in practice, an improvement is discussed. The improvement method is to introduce a BP neural network to approximate the decoupling control laws which are designed for different aerodynamic characteristic points, so a new decoupling control law based on BP neural network is produced after the network training. The simulation results on an example illustrate the approach obtained feasible and effective.

Applying Fuzzy Matter-Element Model Based on AHP to Evaluating Bids of Water Saving Irrigation Project

Owing to overcoming the characteristics that there are many economic and technical indexes which are fuzzy and incompatibility to each other in evaluating investment project,a new method is proposed.The method is based on the matter-element analysis and combined with the concepts of fuzzy mathematics,which is called the method of fuzzy matter-element analysis.It constructs the compound fuzzy matter element with the investment projects,evaluation factors and their fuzzy value.Through establishing the best subjection degree (fuzzy value),complex fuzzy matter element of relational coefficient and weight aggregation of fuzzy matter-element model,the writer achieves on optimum order of the investment projects according to the calculated relational degree and finds the best project.In this paper,the calculation of weight adopts the analytical hierarchy process method(AHP).Through the actual example,it shows that the model is simple and its calculation is reliable.It is very significant for the engineering evaluated bid and investment decision.

Impacts of future climate change(2030-2059)on debris flow hazard:A case study in the Upper Minjiang River basin,China

An increase in extreme precipitation events due to future climate change will have a decisive influence on the formation of debris flows in earthquake-stricken areas. This paper aimed to describe the possible impacts of future climate change on debris flow hazards in the Upper Minjiang River basin in Northwest Sichuan of China, which was severely affected by the 2008 Wenchuan earthquake. The study area was divided into 1285 catchments, which were used as the basic assessment units for debris flow hazards. Based on the current understanding of the causes of debris flows, a binary logistic regression model was used to screen key factors based on local geologic, geomorphologic, soil,vegetation, and meteorological and climatic conditions. We used the weighted summation method to obtain a composite index for debris flow hazards, based on two weight allocation methods: Relative Degree Analysis and rough set theory. Our results showed that the assessment model using the rough set theory resulted in better accuracy. According to the bias corrected and downscaled daily climate model data, future annual precipitation(2030-2059) in the study area are expected to decrease, with an increasing number of heavy rainfall events. Under future climate change, areas with a high-level of debris flow hazard will be even more dangerous, and 5.9% more of the study area was categorized as having a high-level hazard. Future climate change will cause an increase in debris flow hazard levels for 128 catchments, accounting for 10.5% of the total area. In the coming few decades, attention should be paid not only to traditional areas with high-level of debris flow hazards, but also to those areas with an increased hazard level to improve their resilience to debris flow disasters.

Path following control of underactuated ships based on nonswitch analytic model predictive control

A path following controller is developed for underactuated ships with only surge force and yaw moment available to follow a predefined path.The proposed controller is based on nonswitch analytic model predictive control.It is shown that the optimal control law for a nonlinear path following system with ill-defined relative degree is continuous and nonsingular.The problem of ill-defined relative degree is solved.The path-following ability of the nonlinear system is guaranteed.Numerical simulations are provided to demonstrate the effectiveness of the proposed control law.

Pore Size Distribution and Its Quantitative Relationship with Strength of Corundum Based Castables

A series of corundum based castables with 0,2%,4%,6%,and 8% α-Al2O3 micropowders were prepared using tabular alumina aggregates （6-3,3-1 and ≤1 mm） and fines （≤0.088 and ≤0.045 mm）,calcium aluminate cement,and α-Al2O3 micropowders （d50=1.754 μm） as starting materials. Cold mechanical strength and pore size distribution of the castables specimens after heat treatment at 110,1 100 and 1 500 ℃ were tested,respectively. The quantitative relationship between strength and apparent porosity,and that between strength and median pore diameter were verified by Atzeni equation. The correlation between interval of pore size and mechanical strength of specimens was also studied by means of gray relational theory. The results show that：（1） the pore size distribution of castables is strongly influenced by both micropowders filling and matrix sintering; the addition of micropowders decreases median pore diameter while the sintering process increases it; （2） when adding a constant correction term,Atzeni equation can substantially describe the quantitative relationship between median pore diameter and strength of castables specimens after heat treatment at the same temperature; the significant differences of the gray relational degree between the interval of pore size and castables strength are characterized; it is also found that for the same interval of pore size,the gray relational degree isaffected by the heat treatment temperature; the pore size interval 〈0.5 μm has the highest gray relational degree with the strength at 110-1 500 ℃.

Empirical Analysis on the Relations between Rural Residents' Consumption and Economic Growth——A Case of Liaoning Province

Liaoning is a granary province with a large agricultural population and great market potential. Expanding rural residents' consumption becomes a necessity for enlarging domestic demand, solving three agriculture problems and promoting sustainable and rapid economic development. The research shows that since invigorating old industrial base in Liaoning, the contribution rate of rural residents' consumption to economic motivation is low and unstable, which has become one of the choke points for the development of economy. By using the grey correlation method, the influences of rural residents' consumption in different periods to GDP per capita are analyzed, the results show that the consumption level of rural residents were increasing, but their contribution rate on economic growth showed the descending tend. The residential expenses stay in the major position of consumption expenses; the education and entertainment products and service consumption play an important role; the growth of transportation and telecommunication is slow; the expenses on medical care are low and its contribution rate on economic growth is relatively weak. The countermeasures on developing rural economy, increasing rural residents' income, improving rural consumption environment, accelerating rural infrastructure construction, constructing and perfecting rural social security system and expanding rural consumption credit market are put forward to expand rural residents' consumption demand and realize the sustainable development of economy.

Interactive group decision making procedure based on uncertain multiplicative linguistic preference relations

Group decision making problems are investigated with uncertain multiplicative linguistic preference relations.An unbalanced multiplicative linguistic label set is introduced,which can be used by the experts to express their linguistic preference information over alternatives.The uncertain linguistic weighted geometric mean operator is utilized to aggregate all the individual uncertain multiplicative linguistic preference relations into a collective one,and then a simple approach is developed to determine the experts＇ weights by utilizing the consensus degrees among the individual uncertain multiplicative linguistic preference relations and the collective uncertain multiplicative linguistic preference relations.Furthermore,a practical interactive procedure for group decision making is proposed based on uncertain multiplicative linguistic preference relations,in which a possibility degree formula and a complementary matrix are used to rank the given alternatives.Finally,the proposed procedure is applied to solve the group decision making problem of a manufacturing company searching the best global supplier for one of its most critical parts used in assembling process.

Ill-conditioned stable inversion arising from singularly perturbed zero dynamics

The ill-conditioned stable inversion is studied for slightly nonminimum phase systems whose zero dynam- ics is singularly perturbed, that is, the relative degree is ill-defined. For these systems, we show that there exists an inherent limitation in the bandwidth of a reference trajectory to be tracked when a well-conditioned feedforward input via stable inversion is sought. We assert that, when the violation of this limitation occurs, the so-called reference trajectory redesign is called for. Our analysis results can provide an explicit assessment as well as useful guidance for the reference trajectory redesign if needed.

Method for Risky Multiobjective Group Decision-Making and Its Application

The multiobjective group decision-making problem under risk is common in reality. This paper focuses on the study about risky multiobjective group decision-making problem where the index value is not certain. We give indexes classifying method and index normalizing formula of this type problem. By building objective function that minimizes general weighted distance from every alternative to the relatively best and worst alternative, the optimal membership degree of every decision-maker to every alternative can be obtained, and by building another objective function that minimizes general weighted distance from the optimal membership degree of every decision-maker to every alternative to the group optimal alternative and the group inferior alternative, the optimal membership degree of every decision-maker to every alternative can be obtained, which are both based on probability theory and fuzzy theory. Aftermost a model is established which collects group preferences. This method provides a new idea and approach for solving multiobjective decision-making problem among uncertain system, which is applicable for practical problem. Finally a case study shows a satisfactory result.

Characterization of the pairwise correlations in different quantum networks consisting of four-wave mixers and beamsplitters

We investigate the performances of the pairwise correlations（PCs） in different quantum networks consisting of fourwave mixers（FWMs） and beamsplitters（BSs）. PCs with quantum correlation in different quantum networks can be verified by calculating the degree of relative intensity squeezing for any pair of all the output fields. More interestingly, the quantum correlation recovery and enhancement are present in the FWM＋BS network and the repulsion effect phenomena（signal（idler）-frequency mode cannot be quantum correlated with the other two idler（signal）-frequency modes simultaneously）between the PCs with quantum correlation are predicted in the FWM ＋ FWM and FWM ＋ FWM ＋ FWM networks. Our results presented here pave the way for the manipulation of the quantum correlation in quantum networks.

Relational Analysis of Yanbian's Primary Industry of Forestry and Forestry Industry

In this paper,we use grey relational analysis method to systematically analyze the relational degree between Yanbian's forestry industry and three industries of forestry,and conclude that Yanbian's primary industry of forestry shows a downward trend in the development of forestry industry,so it is necessary to transform the traditional primary industry of forestry for the better development.

Correlative Analysis of Yanbian’s Primary Forestry Industry and Sub-industries

By selecting three indicators(timber cultivating and planting,timber harvesting,forest products),this paper uses grey relational degree to analyze the correlation between Yanbian’s primary forestry industry and sub-industries. Results show that there is a decline in the relational degree of three indicators concerning Yanbian’s primary forestry industry,but the relational degree of timber harvesting is still high and the relational degree of forest products is slightly increased.

NUMERICAL ANALYSIS OF BIFURCATION BUCKLING FOR ROTATIONALLY PERIODIC STRUCTURES UNDER ROTATIONALLY PERIODIC LOADS

By considering the characteristics of deformation of rotationally periodic structures under rotationally periodic loads, the periodic structure is divided into some identical substructures in this study. The degrees-of-freedom (DOFs) of joint nodes between the neighboring substructures are classified as master and slave ones. The stress and strain conditions of the whole structure are obtained by solving the elastic static equations for only one substructure by introducing the displacement constraints between master and slave DOFs. The complex constraint method is used to get the bifurcation buckling load and mode for the whole rotationally periodic structure by solving the eigenvalue problem for only one substructure without introducing any additional approximation. The finite element (FE) formulation of shell element of relative degrees of freedom (SERDF) in the buckling analysis is derived. Different measures of tackling internal degrees of freedom for different kinds of buckling problems and different stages of numerical analysis are presented. Some numerical examples are given to illustrate the high efficiency and validity of this method.

A relative feasibility degree based approach for constrained optimization problems

Based on the ratio of the size of the feasible region of constraints to the size of the feasible region of a constrained optimization problem,we propose a new constraint handling approach to improve the efficiency of heuristic search methods in solving the constrained optimization problems.In the traditional classification of a solution candidate,it is either a feasible or an infeasible solution.To refine this classification,a new concept about the relative feasibility degree of a solution candidate is proposed to represent the amount by which the 'feasibility' of the solution candidate exceeds that of another candidate.Relative feasibility degree based selection rules are also proposed to enable evolutionary computation techniques to accelerate the search process of reaching a feasible region.In addition,a relative feasibility degree based differential evolution algorithm is derived to solve constraint optimization problems.The proposed approach is tested with nine benchmark problems.Results indicate that our approach is very competitive compared with four existing state-of-the-art techniques,though still sensitive to the intervals of control parameters of the differential evolution.

Thyroid dysfunction and developmental anomalies in first degree relatives of children with thyroid dysgenesis

Background: Familial clustering in patients withpermanent congenital hypothyroidism (CH) caused bythyroid dysgenesis (TD) has been reported in developedcountries. There is no information on familial TD fromdeveloping countries.Methods: A total of 312 first degree relativesbelonging to 80 families of children with TD (group 1)and 40 families of age-matched normal children (group2) were screened by thyroid ultrasonography, serum totalthyroxine (T4) and thyroid stimulating hormone (TSH).Results: Thyroid scintigraphy revealed agenesis in78.7% of the patients, ectopic gland in 15%, and hypoplasiain 6.2%. The mean thyroid volumes were similar in parentsand siblings of both groups. Eight (10.6%) mothers in group1 were identified to have thyroid hypoplasia as comparedwith none in group 2 (P=0.03). Serum TSH was signifi cantlyhigher in group 1 than in group 2 (P=0.004). Sixteen (7.8%)subjects (6 mothers, 5 fathers, and 5 siblings) in group 1were found to have subclinical hypothyroidism as comparedto none in group 2 (P<0.05). Four families were identifiedto have thyroid developmental anomalies and abnormalthyroid functions accounting for 5% of cases of familial TDin our cohort.Conclusions: Thyroid developmental anomalies andthyroid function abnormalities are more frequent in firstdegree relatives of children with TD as compared with acontrol population. These findings suggest that possiblythere is a genetic component of TD in Indian patients.