Search

Intuitionistic fuzzy distance measurement is an effective method to study multi-attribute emergency decision-making (MAEDM) problems. Unfortunately, the traditional intuitionistic fuzzy distance measurement method cannot accurately reflect the difference between membership and non-membership data, where it is easy to cause information confusion. Therefore, from the intuitionistic fuzzy number (IFN), this paper constructs a decision-making model based on intuitionistic fuzzy cross-entropy and a comprehensive grey correlation analysis algorithm. For the MAEDM problems of completely unknown and partially known attribute weights, this method establishes a grey correlation analysis algorithm based on the objective evaluation value and subjective preference value of decision makers (DMs), which makes up for the shortcomings of traditional model information loss and greatly improves the accuracy of MAEDM. Finally, taking the Wenchuan Earthquake on May 12th 2008 as a case study, this paper constructs and solves the ranking problem of shelters. Through the sensitivity comparison analysis, when the grey resolution coefficient increases from 0.4 to 1.0, the ranking result of building shelters remains stable. Compared to the traditional intuitionistic fuzzy distance, this method is shown to be more reliable.

Used as a hardening agent in lead bullets, antimony (Sb) has become a major contaminant in shooting range soils of some countries including Switzerland. Soil contamination by Sb is also an environmental problem in countries with Sb-mining activities such as China and Bolivia. Because of its toxicity and relatively high mobility, there is concern over the risk of Sb transfer from contaminated soils into plants, and thus into the food chain. In particular there is very little information on the environmental behavior of methylated antimony, which can be produced by microbial biomethylation of inorganic Sb in contaminated soils. Using a new extraction and high-performance liquid chromatography inductively coupled plasma mass spectrometry (HPLC-ICP-MS) method, we investigated antimony speciation in roots and shoots of wheat, fescue, rye, and ryegrass plants exposed to trimethyl antimony(V) (TMSb), antimonite (Sb(III)), and antimonate (Sb(V)) in hydroponics. The total root Sb concentrations followed the order Sb(III) treatment > Sb(V) treatment > TMSb treatment, except for fescue. Shoot Sb concentrations, however, did not differ among the three treatments. In the Sb(V) treatment small quantities of TMSb were found in the roots, whereas no TMSb was detected in the roots of Sb(III)-treated plants. In contrast, similar concentrations of TMSb were found in the shoots in both inorganic Sb treatments. The results indicate that biomethylation of Sb may occur in plants. In the TMSb treatment TMSb was the major Sb species, but the two inorganic Sb species were also found both in shoots and roots along with some unknown Sb species, suggesting that also TMSb demethylation may occur within plant tissues. The results furthermore indicate that methylated Sb is more mobile in plants than inorganic Sb species. Knowledge about this is important in risk assessments of Sb-contaminated sites, as methylation may render Sb more toxic than inorganic Sb, as it is known for arsenic (As).

Taking investor’s perception into account, the optimal decisions about the product quality and platform advertisement are investigated in a dynamic model in the context of crowdfunding. Researches in the literature, however, usually set investor’s perception as a fixed value and rarely consider the important phenomenon that the online information has some influences on investor’s perception. Considering the effects of information about product quality and platform advertisement on the investor’s perception, a dynamic decision model is proposed. Firstly, investment desire and reference price of the investor are introduced in two dynamic settings to describe investor’s perception. Then, the optimal decisions about the product quality and platform advertisement are formulated under two circumstances: the sponsor and the platform make decisions independently and they cooperate as a system. Finally, the influences of reference price and cost-sharing ratio on the optimal results are compared and the data simulation experiment verifies the necessity of the study. Some new insights can be drawn for the operations management of the firm in crowdfunding as follows: (i) it is more profitable for the firm to cooperate with the platform when investors pay more attention to their reference price; (ii) it is optimal for the firm to share a larger proportion of platform cost when the profit-sharing ratio is low.

Objective: To evaluate various types of samples from the different marine environments as sources of actinomycetes from the Yalujiang coastal wetland, North China, and to screen their antimicrobial properties. Further, the identified actinomycetes were characterized based on morphological, biochemical, and physiological characteristics. Methods: Eight different production media were used to isolate actinomycetes from different stations of marine soil sediments in Yalujiang coastal wetland and the genotypic positions were established by 16S rDNA. Results: A total of 172 actinomycetal isolates were obtained from 13 samples using five media. The most effective culture media in the isolation of actinobacteria were Gause's Synthetic agar and Starch-casein agar. Among 172 isolates, 46 isolates (26.74%) showed antibacterial activity, 70.93% belonged to the genus Streptomyces, others were Micromonospora spp. and Rhodococcus spp. Out of the 46 isolates, two cultures were further supported by morphological characterization analysis. Conclusions: This is the first report about actinomycetes isolated from Yalujiang coastal wetland and it seems that the promising isolates from the unusual/unexplored wetland may prove to be an important step in the development of microbial natural product research.

Background:. Studies in developed countries reveal that poor lifestyle choices triggering diseases typically cluster among children. However, there is insufficient evidence on the clustering of risk behaviors among children in developing countries. This study aimed to determine the clustering of risk behaviors and their social determinants among 4th-and 5th -grade learners in Beijing, China. Methods:. The sample comprised of 967 learners from six primary schools enrolled migrant and resident learners by two-stage stratified cluster sampling. Prevalence denoted the risk behaviors and their clustering. A log-linear model was used to explore the clustering patterns. Ordinal logistic regression determined the influence of demographic characteristics, school environment, and family context on behavioral clustering. Results:. The prevalence of none, one, two, and three or more risk factors was 61.2%, 20.0%, 10.8%, and 8.1% for infectious diseases and 46.0%, 30.6%, 15.4%, and 8.0% for chronic diseases, respectively. Some behaviors appeared dependent and were more likely to be observed together. The three most influential factors for infectious diseases were school type (odds ratio [OR] =4.47, 95% confidence interval [CI] 3.00-6.66), school located in an inner suburb (OR = 0.27, 95% CI 0.18-0.38), and gender (OR = 0.56, 95% CI 0.42-0.74). Regarding risk behaviors for chronic diseases, clustering was not associated with household registration status and number of appliances, but was significantly associated with school type (OR = 5.36, 95% CI 3.72-7.73), school located in an inner suburb (OR = 0.59, 95% CI 0.43-0.81), and gender (OR = 0.61, 95% CI 0.47-0.78). School environment variables were the most significant contributor to the number of risk behaviors. Conclusions:. The characteristics of schools enrolling migrants and residents influenced the number of risk behaviors. Therefore, improved school conditions and integrated behavioral interventions are particularly recommended for health promotion.

We study a class of multiobjective bilevel programs with the weights of objectives being uncertain and assumed to belong to convex and compact set. To the best of our knowledge, there is no study about this class of problems. We use a worst-case weighted approach to solve this class of problems. Our “worst-case weighted multiobjective bilevel programs” model supposes that each player (leader or follower) has a set of weights to their objectives and wishes to minimize their maximum weighted sum objective where the maximization is with respect to the set of weights. This new model gives rise to a new Pareto optimum concept, which we call “robust-weighted Pareto optimum”; for the worst-case weighted multiobjective optimization with the weight set of each player given as a polytope, we show that a robust-weighted Pareto optimum can be obtained by solving mathematical programing with equilibrium constraints (MPEC). For an application, we illustrate the usefulness of the worst-case weighted multiobjective optimization to a supply chain risk management under demand uncertainty. By the comparison with the existing weighted approach, we show that our method is more robust and can be more efficiently applied to real-world problems.

Driven by the recent advances and applications of smart-grid technologies, our electric power grid is undergoing radical modernization. Microgrid (MG) plays an important role in the course of modernization by providing a flexible way to integrate distributed renewable energy resources (RES) into the power grid. However, distributed RES, such as solar and wind, can be highly intermittent and stochastic. These uncertain resources combined with load demand result in random variations in both the supply and the demand sides, which make it difficult to effectively operate a MG. Focusing on this problem, this paper proposed a novel energy management approach for real-time scheduling of an MG considering the uncertainty of the load demand, renewable energy, and electricity price. Unlike the conventional model-based approaches requiring a predictor to estimate the uncertainty, the proposed solution is learning-based and does not require an explicit model of the uncertainty. Specifically, the MG energy management is modeled as a Markov Decision Process (MDP) with an objective of minimizing the daily operating cost. A deep reinforcement learning (DRL) approach is developed to solve the MDP. In the DRL approach, a deep feedforward neural network is designed to approximate the optimal action-value function, and the deep Q-network (DQN) algorithm is used to train the neural network. The proposed approach takes the state of the MG as inputs, and outputs directly the real-time generation schedules. Finally, using real power-grid data from the California Independent System Operator (CAISO), case studies are carried out to demonstrate the effectiveness of the proposed approach.

In this paper, we propose a worst-case weighted approach to the multi-objective n-person non-zero sum game model where each player has more than one competing objective. Our "worst-case weighted multi-objective game" model supposes that each player has a set of weights to its objectives and wishes to minimize its maximum weighted sum objectives where the maximization is with respect to the set of weights. This new model gives rise to a new Pareto Nash equilibrium concept, which we call "robust-weighted Nash equilibrium". We prove that the robust-weighted Nash equilibria are guaranteed to exist even when the weight sets are unbounded. For the worst-case weighted multi-objective game with the weight sets of players all given as polytope, we show that a robust-weighted Nash equilibrium can be obtained by solving a mathematical program with equilibrium constraints (MPEC). For an application, we illustrate the usefulness of the worst-case weighted multi-objective game to a supply chain risk management problem under demand uncertainty. By the comparison with the existed weighted approach, we show that our method is more robust and can be more efficiently used for the real-world applications.

OBJECTIVE:The existing screening batteries assessing multiple neuropsychological functions are not specific to amyotrophic lateral sclerosis (ALS) patients and are limited to their physical dysfunctions, whereas category cognitive tests are too time-consuming to assess all the domains. The Edinburgh Cognitive and Behavioural ALS Screen (ECAS) was recently developed as a fast and easy cognitive screening tool specifically designed for patients. The purpose of the study was to validate the effectiveness of the Chinese version in Chinese ALS populations. METHODS:Eighty-four ALS patients and 84 age-, gender- and education-matched healthy controls were included in this cross-sectional study. All the participants took the ECAS, Mini-Mental State Examination (MMSE) and Frontal Assessment Battery (FAB). Primary caregivers of patients were interviewed for behavioural and psychiatric changes. RESULTS:Significant differences were noted in language (p = 0.01), fluency, executive function, ALS-specific functions, and ECAS total score (p

Migrants usually exhibit similar or better health outcomes than native-born populations despite facing socioeconomic disadvantages and barriers to healthcare use; this is known as the "migrant paradox." The migrant paradox among children is highly complex. This study explores whether the migrant paradox exists in the health of internal migrant children in China and the role of schools in reducing children's health disparities, using a multi-stage stratified cluster sampling method. Participants were 1,641 student and parent pairs from Grades 4, 5, and 6 of eight primary schools in Beijing. The following school types were included: state schools with migrant children comprising over 70% of total children (SMS), private schools with migrant children comprising over 70% (PMS), and state schools with permanent resident children comprising over 70% (SRS). Children were divided into Groups A, B, C or D by the type of school they attended (A and B were drawn from SRSs, C was from SMSs, and D was from PMSs) and whether they were in the migrant population (B, C, and D were, but A was not). Related information was collected through medical examination and questionnaires completed by parents and children. Prevalence of caries, overweight and obesity, poor vision, and self-reported incidence of colds and diarrhea in the previous month were explored as health outcomes. The results partially demonstrated the existence of the migrant paradox and verified the role of schools in lowering health disparities among children; there are theoretical and practical implications for improving the health of migrant children.

In recent years, detection of trace amounts of dissolved lipophilic phycotoxins in coastal waters has been possible using solid phase adsorption toxin tracking (SPATT) samplers. To explore the contribution of dissolved diarrhetic shellfish toxins (DST) to the accumulation of toxins by cultivated bivalves, mussels (Mytilus galloprovincialis) were exposed to different concentrations of purified okadaic acid (OA) and dinophysistoxin-1 (DTX1) in filtered (0.45 µm) seawater for 96 h. Accumulation and esterification of DST by mussels under different experimental conditions, including with and without the addition of the food microalga Isochrysis galbana, and with the addition of different size-fractions of suspended particulate matter (SPM) ( gills > mantle > residual tissues. However, the percentage of total DST in the digestive gland of mussels in filtered seawater (67%) was higher than with the addition of SPM particles (75–150 µm) (51%), whereas the gills showed the opposite trend in filtered seawater with (27%) and without (14.4%) SPM particles. Results presented here will improve our understanding of the mechanisms of DST accumulation by bivalves in marine aquaculture environments.

This paper studies a class of multi-objective n-person non-zero sum games through a robust weighted approach where each player has more than one competing objective. This robust weighted multi-objective game model assumes that each player attaches a set of weights to its objectives instead of accessing accurate weights. Each player wishes to minimize its maximum weighted sum objective where the maximization is pointing to the set of weights. To address this new model, a new equilibrium concept-robust weighted Nash equilibrium is obtained. The existence of this new concept is proven on suitable assumptions about the multi-objective payoffs.

We propose a new method to solve nonlinear semidefinite complementarity problem by combining a continuous method and a trust-region-type method. At every iteration, we need to calculate a second-order cone subproblem. We show the well-definedness of the method. The global convergent result is established.

BACKGROUND: The aim of this study was to investigate the correlation between the expression of hepatitis B surface antigen (HBsAg) in human ovary and placenta and the vertical transmission of hepatitis B virus (HBV). METHODOLOGY/PRINCIPAL FIDNINGS: Ovarian and placental tissue specimens of pregnant women infected with HBV were collected during cesarean section and immunostained for HBsAg. The sera of the corresponding newborns were tested for HBV markers and HBV DNA. HBsAg was detected in 15 out of 33 (45%) placental tissues and was further detected in capillary endothelial cells in 4 specimens (26%), of which 3 (75%) corresponding infants were infected with HBV in utero. Out of the 33 ovarian tissues, 7 (21%) were positive for HBsAg, of which 2 (28%) showed HBsAg in ovarian follicles and the 2 corresponding infants (100%) had intrauterine HBV infection. CONCLUSIONS/SIGNIFICANCE: HBsAg expression in cells of the ovarian follicle or placental capillary endothelium signal a higher risk for intrauterine HBV infection.