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Tobacco (Nicotiana tabacum L.) is a significant cash crop in China. In this study, we investigated the effect of microbial agent application with different rates and application periods on tobacco diseases and soil microorganisms. During the tobacco growing process, the doses of 0, 30 and 60 kg hm-1 were applied at the time of ridging, transplanting and resettling, respectively. 16S rRNA and ITS gene sequencing techniques were utilized to analyze the microbial communities in tobacco fields. The results indicated that the application of microbials significantly decreased the incidence rate and disease index of Ralstonia solanacearum and Phytophthora nicotianae. Moreover, the application of microbial agents resulted in an increase in the abundance of specific fungi (Basidiomycota) and bacteria (Nitrospirae), while reducing the abundance of other fungi (Blastocladiomycota) and bacteria (Spirochaetes). The optimum application dose of microbial agents at the budding stage was recommended as 60 kg.hm-2 for improving tobacco production and soil health, as well as for increasing the economic value of the tobacco leaves of roasted cigarettes significantly. This study emphasizes soil organic matter and pH as key factors influencing tobacco root microbiota. After microbial fertilizer treatment, the relative abundance of various microorganisms in tobacco rhizosphere soil positively correlated with soil enzyme activity and negatively correlated with soil nutrients, which reflected that tobacco rhizosphere microorganisms were regulated by the combination of soil nutrients and enzyme activity. [ABSTRACT FROM AUTHOR]

Under intense industry competition, decision makers must ensure that products demanded by consumers can be quickly produced with minimum production cost. However, because uncertainties are unavoidable and inevitably affect decision makers, numerous studies have discussed how to control uncertainties or minimize their effects. Multiple uncertainties that interact simultaneously may cause a combined effect in actual systems. Therefore, this study presents a robust optimization model with two uncertainties, extending the method of robust optimization with one uncertainty. To demonstrate the applicability of the proposed model with two uncertainties, this study uses the supplier selection problem with component purchase quantity allocation in supply chain management as an analysis case. This considers the reliability of production and transportation and develops a multi-objective robust optimization model with two uncertainties. In addition, a nondominated sorting genetic algorithm is proposed for solving the proposed multi-objective robust optimization model. The relationship between price of robustness and budget parameters is explored by considering the robust optimization model with production and transportation uncertainties proposed in this study. Finally, there is a comparative analysis between the results for price of robustness in the proposed two-uncertainty model and in the one-uncertainty model. [ABSTRACT FROM AUTHOR]

Public safety-related problems exist in all countries, causing the public to fear for their personal safety and that of their property. Maintaining public safety, providing citizens with safe living environments, and realizing sustainable social development are issues that concern not only the public but also local and central governments. Accordingly, this study proposed a measurement model that combines the analytic hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) to obtain public safety ratings. First, this study used the AHP to analyze the contributions of public safety-related criteria, and the relative weights of the criteria were calculated. Subsequently, TOPSIS was used to calculate the relative closeness coefficients between public safety performance and positive-ideal solutions to evaluate public safety performance. The measurement model proposed in this study was used to rate the public safety performance of 22 cities and counties in Taiwan. The results showed that the criterion weights matched the perceptions of the public, and Lienchiang County, Taitung County, and Penghu County had the best public safety performance. The applicability of the proposed measurement model has been confirmed using real-world data. Thus, it can be used to help decision-makers make complex public safety-related decisions. [ABSTRACT FROM AUTHOR]

The parts of a product may be changed over the product life cycle for the purpose of enhancing profits, that is to say, product part change has a direct impact on production efficiency and customer satisfaction. The analysis of product part change can provide producers with related components/part suppliers by analysing the product's configuration. Before performing the physical assembly of a specific product, selected part suppliers are connected and have to verify their ability to assemble. This paper proposes an assessment model consisting of three major phases: (1) analysis of the assembly relationship among the parts; (2) preliminary selection of the appropriate parts and their suppliers; and (3) solution selection for supplier association. The proposed model solves the product part change problem for a given related quality level, operation and cost data. The liaison graph, fuzzy theory and value engineering approaches are employed in phases 1 and 2 to analyse the product's configuration and assembly relationships, to deal with production data and to carry out the preliminary analysis. To solve the solution selection model of phase 3, a genetic algorithm based heuristic approach was developed. Finally, the configuration of the stand module of TFT-LCD is used as an example to demonstrate the application and working of the proposed approach. The results of the illustrated example are used to demonstrate its efficiency and effectiveness in solving the part change problem. [ABSTRACT FROM AUTHOR]

Killer cell immunoglobulin-like receptor (KIR) genes are variably distributed among populations from distinct geographic areas and ethnic origins. We describe, for the first time, KIR gene diversity in 152 unrelated and healthy Drung individuals, as measured by sequence-specific polymerase chain reaction. All 16 known KIR genes were detected. Of these, the framework genes KIR2DL4, 3DL2, 3DL3, and 3DP1 were present in all individuals as expected, along with the non-framework genes KIR2DL1, 2DL3, and 2DP1. In contrast, KIR2DL2, 2DS2, and 2DS5 were unusually rare, suggesting that KIR gene distribution was relatively concentrated. Ten different KIR genotypes were found, of which the most common consisted of nine genes ( KIR2DL1, 2DL3, 2DL4, 2DS4, 3DL1, 3DL2, 3DL3, 2DP1, and 3DP1) and accounted for 66.4% of participants. There were eight different haplotypes present, of which the A haplotype was the most common (81.9%). Principal components and dendrogram analysis confirmed that the Drung Chinese are most closely related to the Japanese, the Zhejiang Han, and the Yunnan Han. In conclusion, distinctive frequencies of KIR genes, haplotypes, and genotypes are observed in Chinese Drung. [ABSTRACT FROM AUTHOR]

Supplier selection is a critical multi-criterion decision-making activity for suc- cessful supply chain management. This study involved developing an integrated supplier selection methodology, which is constructed using analytic network process, data envelop- ment analysis, and multiple objective particle swarm optimization. The proposed integrated methodology can account for multiple supplier selection criteria and set boundaries on weight value for multiple objective data envelopment analysis inputs and outputs. To solve the data envelopment analysis model, a new algorithm based on multiple objective particle swarm optimization is introduced, which embeds with tabu list and group mechanisms, and then, it is found to be superior to the compared algorithms in solving performance on three test functions and the illustrative case. In addition, the proposed integrated method- ology was applied to a supplier selection problem of sphygmomanometer manufacturer in Taiwan to verify its applicability of decision-making process. The results show that the methodology can be implemented as an effective decision aid for supplier selection under multiple criteria with weight restrictions. [ABSTRACT FROM AUTHOR]

This study designed a cross-stage reverse logistics course for defective products so that damaged products generated in downstream partners can be directly returned to upstream partners throughout the stages of a supply chain for rework and maintenance. To solve this reverse supply chain design problem, an optimal cross-stage reverse logistics mathematical model was developed. In addition, we developed a genetic algorithm (GA) and three particle swarm optimization (PSO) algorithms: the inertia weight method (PSOA_IWM), VMax method (PSOA_VMM), and constriction factor method (PSOA_CFM), which we employed to find solutions to support this mathematical model. Finally, a real case and five simulative cases with different scopes were used to compare the execution times, convergence times, and objective function values of the four algorithms used to validate the model proposed in this study. Regarding system execution time, the GA consumed more time than the other three PSOs did. Regarding objective function value, the GA, PSOA_IWM, and PSOA CFM could obtain a lower convergence value than PSOA_VMM could. Finally, PSOA_IWM demonstrated a faster convergence speed than PSOA_VMM, PSOA_CFM, and the GA did. [ABSTRACT FROM AUTHOR]

In consideration of capacity constraints, fuzzy defect ratio, and fuzzy transport loss ratio, this paper attempted to establish an optimized decision model for production planning and distribution of a multiphase, multiproduct reverse supply chain, which addresses defects returned to original manufacturers, and in addition, develops hybrid algorithms such as Particle Swarm Optimization-Genetic Algorithm (PSO-GA), Genetic Algorithm-Simulated Annealing (GA-SA), and Particle Swarm Optimization-SimulatedAnnealing (PSO-SA) for solving the optimizedmodel. During a case study of amulti-phase, multi-product reverse supply chain network, this paper explained the suitability of the optimized decision model and the applicability of the algorithms. Finally, the hybrid algorithms showed excellent solving capability when compared with original GA and PSOmethods. [ABSTRACT FROM AUTHOR]

To improve coal recovery rate of open pit coal mines, according to the conditions of coal seams at flat dipping open pit coal mines in China, a new mining system for recovering remaining coal around end-slopes was proposed. This system can extract the end-slopes coal remnants which are normally abandoned in traditional mining systems by using existing open pit mining and transportation systems. In this system, lower initial investment, mining and transportation costs are available, so the economic benefits are good. Moreover, the main mining parameters were discussed, and all of these results can be referred by the other open pit mines with similar geological conditions. [ABSTRACT FROM AUTHOR]

Increasing environmental awareness and stringent environmental regulations have motivated many companies to incorporate ecodesign into product development. To assist companies to address the challenge, this research presents a design for environment (DfE) methodology to evaluate and improve derivative consumer electronic product development using a back-propagation neural network (BPNN) model and a technique for order preference by similarity to ideal solution (TOPSIS) method. Based on use of a BPNN, the life cycle assessment (LCA) models are developed to estimate quantities of hazardous chemical substances and energy consumption for a derivative consumer electronic product throughout the product life cycle. A performance evaluation and improvement model for DfE is then devised based on the TOPSIS method to analyze the ecodesign performance and provide concrete improvement strategies. With the aforementioned analysis of environmental performance, an enterprise can profoundly understand and significantly enhance the relative DfE performance of a new product compared to the similar competitive products. Finally, we apply an optical mouse development project as a case to elaborate and demonstrate the effectiveness of the proposed methodology. These analytical results can let us understand the DfE performance ranking and acquire the maximum reduced quantity of each DfE criterion for each module of a new product. Meanwhile, to enhance the green competitiveness of the new product, we recommend that the engineers should decrease the area of the circuit board of the new product. In addition, the material of the USB cable for the new product should be switched from the PVC material to the PE material. [ABSTRACT FROM AUTHOR]

In this paper, a novel multi-phase mathematical approach is presented for the design of a complex supply chain network. From the point of network design, customer demands, and for maximum overall utility, the important issues are to find suitable and quality companies, and to decide upon an appropriate production/distribution strategy. The proposed approach is based on the genetic algorithm (GA), the analytical hierarchy process (AHP), and the multi- attribute utility theory (MAUT) to satisfy simultaneously the preferences of the suppliers and the customers at each level in the network. A case study with a good quality solution is provided to confirm the efficiency and effectiveness of the proposed approach. Finally, to demonstrate the performance of the proposed approach, a comparative numerical experiment is performed by using the proposed approach and the common single-phase genetic algorithm (SGA). Empirical analysis results demonstrate that the proposed approach can outperform the SGA in partner selection and production/distribution planning for network design. [ABSTRACT FROM AUTHOR]

A retraction statement from the first author of the article "Targeting of the C-Jun/BCL-XL/P21 Axis Accelerates the Switch from Senescence to Apoptosis Upon ROC1 Knockdown in Gastric Cancer Cells" is presented.

The evaporation of a liquid drop on a solid substrate is a remarkably common phenomenon. Yet, the complexity of the underlying mechanisms has constrained previous studies to spherically symmetric configurations. Here we investigate well-defined, non-spherical evaporating drops of pure liquids and binary mixtures. We deduce a universal scaling law for the evaporation rate valid for any shape and demonstrate that more curved regions lead to preferential localized depositions in particle-laden drops. Furthermore, geometry induces well-defined flow structures within the drop that change according to the driving mechanism. In the case of binary mixtures, geometry dictates the spatial segregation of the more volatile component as it is depleted. Our results suggest that the drop geometry can be exploited to prescribe the particle deposition and evaporative dynamics of pure drops and the mixing characteristics of multicomponent drops, which may be of interest to a wide range of industrial and scientific applications. [ABSTRACT FROM AUTHOR]

A novel allele HLA-A*02:482 differs from the closest allele HLA-A*02:01:01:01 by a nucleotide change at codon 57. [ABSTRACT FROM AUTHOR]

In consideration of capacity constraints, fuzzy defect ratio, and fuzzy transport loss ratio, this paper attempted to establish an optimized decision model for production planning and distribution of a multiphase, multiproduct reverse supply chain, which addresses defects returned to original manufacturers, and in addition, develops hybrid algorithms such as Particle Swarm Optimization-Genetic Algorithm (PSO-GA), Genetic Algorithm-Simulated Annealing (GA-SA), and Particle Swarm Optimization-Simulated Annealing (PSO-SA) for solving the optimized model. During a case study of a multi-phase, multi-product reverse supply chain network, this paper explained the suitability of the optimized decision model and the applicability of the algorithms. Finally, the hybrid algorithms showed excellent solving capability when compared with original GA and PSO methods. [ABSTRACT FROM AUTHOR]

The structure, composition, and mechanical response of Australian bamboo were investigated. The graded structure, composition, and mechanical properties were confirmed by depth profiles obtained using synchrotron radiation diffraction and Vickers indentation. The mechanical performance of bamboo was strongly dependent on age. Results indicated that young bamboo has a higher strength, elastic stiffness, and fracture toughness than its older counterpart does. In addition, the hardness of bamboo is both load dependent and time dependent as a result of an expanding interfacial damage zone and indentation creep, respectively. In addition to fiber debonding, crack deflection and crack-bridging are the major energy dissipative processes for imparting a high toughness in bamboo. [ABSTRACT FROM AUTHOR]