An Evolutionary Algorithm Using Duality-Base-Enumerating Scheme for Interval Linear Bilevel Programming Problems

Interval bilevel programming problem is hard to solve due to its hierarchical structure as well as the uncertainty of coefficients. This paper is focused on a class of interval linear bilevel programming problems, and an evolutionary algorithm based on duality bases is proposed. Firstly, the objective coefficients of the lower level and the right-hand-side vector are uniformly encoded as individuals, and the relative intervals are taken as the search space. Secondly, for each encoded individual, based on the duality theorem, the original problem is transformed into a single level program simply involving one nonlinear equality constraint. Further, by enumerating duality bases, this nonlinear equality is deleted, and the single level program is converted into several linear programs. Finally, each individual can be evaluated by solving these linear programs. The computational results of 7 examples show that the algorithm is feasible and robust

A new differential evolution using a bilevel optimization model for solving generalized multi-point dynamic aggregation problems

The multi-point dynamic aggregation problem (MPDAP) comes mainly from real-world applications, which is characterized by dynamic task assignation and routing optimization with limited resources. Due to the dynamic allocation of tasks, more than one optimization objective, limited resources, and other factors involved, the computational complexity of both route programming and resource allocation optimization is a growing problem. In this manuscript, a task scheduling problem of fire-fighting robots is investigated and solved, and serves as a representative multi-point dynamic aggregation problem. First, in terms of two optimized objectives, the cost and completion time, a new bilevel programming model is presented, in which the task cost is taken as the leader's objective. In addition, in order to effectively solve the bilevel model, a differential evolution is developed based on a new matrix coding scheme. Moreover, some percentage of high-quality solutions are applied in mutation and selection operations, which helps to generate potentially better solutions and keep them into the next generation of population. Finally, the experimental results show that the proposed algorithm is feasible and effective in dealing with the multi-point dynamic aggregation problem

Study on Unconventional Emergency Scenario Design: Taking Life-Rescuing of Dongfang Turbine Co., Ltd. in Wenchuan Earthquake for Example

Unconventional emergencies have attracted widespread concern in academic field due to its high uncertainty, huge destructiveness and complex management, and studies on unconventional emergencies shall change from “prediction-response” to “scenario-response”. By taking the life-rescuing of Dongfang Turbine Co., Ltd. in Wenchuan Earthquake for example, this paper divides scenarios in accordance with the specific investigations, and proposes several considerations about the unconventional emergency scenario study

Multi-strategy self-learning particle swarm optimization algorithm based on reinforcement learning

The trade-off between exploitation and exploration is a dilemma inherent to particle swarm optimization (PSO) algorithms. Therefore, a growing body of PSO variants is devoted to solving the balance between the two. Among them, the method of self-adaptive multi-strategy selection plays a crucial role in improving the performance of PSO algorithms but has yet to be well exploited. In this research, with the aid of the reinforcement learning technique to guide the generation of offspring, a novel self-adaptive multi-strategy selection mechanism is designed, and then a multi-strategy self-learning PSO algorithm based on reinforcement learning (MPSORL) is proposed. First, the fitness value of particles is regarded as a set of states that are divided into several state subsets non-uniformly. Second, the ε-greedy strategy is employed to select the optimal strategy for each particle. The personal best particle and the global best particle are then updated after executing the strategy. Subsequently, the next state is determined. Thus, the value of the Q-table, as a scheme adopted in self-learning, is reshaped by the reward value, the action and the state in a non-stationary environment. Finally, the proposed algorithm is compared with other state-of-the-art algorithms on two well-known benchmark suites and a real-world problem. Extensive experiments indicate that MPSORL has better performance in terms of accuracy, convergence speed and non-parametric tests in most cases. The multi-strategy selection mechanism presented in the manuscript is effective

Prevalence of lymph node metastases in superficial esophageal squamous cell carcinoma

ObjectiveEndoscopic treatment of superficial esophageal carcinoma has been increasingly conducted around the world. Because no lymph nodes are removed in such a procedure, the risk of lymph node metastases (LNMs) should be clearly understood. The aim of the present study was to accurately clarify the pattern of lymphatic spread in patients with superficial esophageal squamous cell carcinoma and analyze the factors potentially related to LNMs.MethodsThe pattern of lymphatic spread was studied in 189 patients who had undergone radical lymphadenectomy from 2006 to 2011. The risk factors associated with LNMs were determined by multivariate logistic regression analysis. According to the depth of tumor invasion, mucosal tumors were classified as M1, M2, and M3 and submucosal tumors as SM1, SM2, and SM3.ResultsA total of 4252 lymph nodes were resected (average, 23 ± 9; range, 12-68). LNMs occurred in 49 patients (25.9%). The frequency of LNMs was 4.3% in those with mucosal and 33.1% in those with submucosal cancer. LNMs were found in 0%, 0%, 11.8%, 24.0%, 20.5%, and 43.8% of the M1, M2, M3, SM1, SM2, and SM3 cancer, respectively. For submucosal cancer, SM3 cancer (P = .006) and lymphovascular invasion (P = .001) were significant independent risk factors for LNMs. Paratracheal nodes were the most frequently involved. “Skip” metastases occurred in 20 of 49 patients (40.8%).ConclusionsEndoscopic treatment can be attempted when the tumor is limited to the lamina propria mucosa. However, 2-field radical lymphadenectomy with careful upper mediastinal lymph node resection should be conducted for submucosal squamous cell carcinoma

Exploring the Formation Mechanism of Radical Technological Innovation: An MLP Approach

This paper identifies three stages in the radical technological innovation process, namely formation process in niches, breaking out of niches and entering regimes, and new regime formation. It then adopts Multi-level Perspective (MLP) to explore the formation process, operating mechanism, breakthrough path, and impact factors of radical technological innovation. A three-phase model, which includes formation of radical innovation, breakout of radical innovation, and new regimes construction, is proposed to analyze radical technological innovation. The model is adopted in a case study to analyze the leapfrogging development of technologies in China’s mobile communication industry. This paper enriches technological innovation theory and provides supports for policy making and guidance for industries/enterprises practices regarding technological innovation in emerging economies

Technological Innovation Research: A Structural Equation Modelling Approach

The paper explores the relationship among technological innovation, technological trajectory transition, and firms’ innovation performance. Technological innovation is studied from the perspectives of innovation novelty and innovation openness. Technological trajectory transition is categorized into creative cumulative technological trajectory transition and creative disruptive technological trajectory transition. A structural equation model is developed and tested with data collected by surveying 366 Chinese firms. The results indicate that both innovation novelty and innovation openness positively affects creative cumulative technological trajectory transition as well as creative disruptive technological trajectory transition. Innovation openness and creative disruptive technological trajectory transition both positively affect firms’ innovation performance. However, neither innovation novelty nor creative cumulative technological trajectory transition positively affects firms’ innovation performance. Implications for managers and directions for future studies are discussed

Treatment with high-dose antidepressants severely exacerbates the pathological outcome of experimental <i>Escherichia coli</i> infections in poultry

There is an urgent need for novel antibiotics as the current antibiotics are losing their value due to increased resistance among clinically important bacteria. Sertraline, an on-marked anti-depressive drug, has been shown to modify bacterial activity in vitro, including increasing the susceptibility of Escherichia coli to antibiotics. The aim of the present study was to investigate if the antimicrobial activity of sertraline could be documented under clinical settings, hereunder if sertraline could potentiate the effect of tetracycline in treatment of an experimentally induced ascending infection in poultry. A total of 40 chickens were divided in four groups of 10 chickens each. All chickens were challenged with 4x103 colony forming units (CFU) of a tetracycline resistant E. coli strain using a surgical infection model, and subsequently treated with either high-dose sertraline, tetracycline, a combination hereof or received no treatment. Seven days post challenge all birds were submitted to necropsy and scored pathologically for lesions. The average lesion scores were significantly higher (P<0.05) in the groups that were treated with high-dose sertraline or high-dose sertraline combined with tetracycline. In conclusion high-dose treatments (four times the maximum therapeutic dose for treating human depression) with sertraline as an adjuvant for treatment of antibiotic resistant E. coli infections exacerbate the pathological outcome of infection in chickens

Classification related to immunogenic cell death predicts prognosis, immune microenvironment characteristics, and response to immunotherapy in lower-grade gliomas

BackgroundImmunogenic cell death (ICD) is a form of cell death that elicits immune responses against the antigens found in dead or dying tumor cells. Growing evidence implies that ICD plays a significant role in triggering antitumor immunity. The prognosis for glioma remains poor despite many biomarkers being reported, and identifying ICD-related biomarkers is imminent for better-personalized management in patients with lower-grade glioma (LGG).Materials and methodsWe identified ICD-related differentially expressed genes (DEGs) by comparing gene expression profiles obtained across Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) cohorts. On the foundation of ICD-related DEGs, two ICD-related clusters were identified through consensus clustering. Then, survival analysis, functional enrichment analysis, somatic mutation analysis, and immune characteristics analysis were performed in the two ICD-related subtypes. Additionally, we developed and validated a risk assessment signature for LGG patients. Finally, we selected one gene (EIF2AK3) from the above risk model for experimental validation.Results32 ICD-related DEGs were screened, dividing the LGG samples from the TCGA database into two distinct subtypes. The ICD-high subgroup showed worse overall survival (OS), greater immune infiltration, more active immune response process, and higher expression levels of HLA genes than the ICD-low subgroup. Additionally, nine ICD-related DEGs were identified to build the prognostic signature, which was highly correlated with the tumor-immune microenvironment and could unambiguously be taken as an independent prognostic factor and further verified in an external dataset. The experimental results indicated that EIF2AK3 expression was higher in tumors than paracancerous tissues, and high-expression EIF2AK3 was enriched in WHO III and IV gliomas by qPCR and IHC, and Knockdown of EIF2AK3 suppressed cell viability and mobility in glioma cells.ConclusionWe established novel ICD-related subtypes and risk signature for LGG, which may be beneficial to improving clinical outcome prediction and guiding individualized immunotherapy