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In today’s era of innovation and the vigorous development of the digital economy, globalization and antiglobalization are intertwined, and cultural dissemination and integration are gradually expanding the influence and scope of the era; the revival and inheritance of traditional culture have become increasingly important in our country. The development of the creative industry is becoming more and more vigorous and full of vitality. Based on deep learning algorithms, this paper studies the cultural and creative design of Dunhuang frescoes in the Western Xia period. This paper analyzes the shortcomings of the current cultural and creative market and the characteristics of high-quality cultural and creative design, analyzes the principles of cultural and creative design of cultural relics, etc., proposes a generative confrontation network model, establishes a modern cultural and creative design model, and provides a three-level cultural model for cultural and creative design. The process is analyzed. In the evaluation and analysis of users, it is concluded that the integration of traditional culture design factor score is 4.80, conforming to the modern aesthetic situation is 4.63, conforming to the user’s expectation of “elegant” is 4.73, and the comprehensive score is 4.72.

State of health (SOH) is the ratio of the currently available maximum capacity of the battery to the rated capacity. It is an important index to describe the degradation state of a pure electric vehicle battery and has an important reference value in evaluating the health level of the retired battery and estimating the driving range. In this study, the random forest algorithm is first used to find the most important health factors to lithium-ion batteries based on the dataset released by National Aeronautics and Space Administration (NASA). Then the support vector regression (SVR) algorithm is developed to predict the SOH of a lithium-ion battery. The genetic algorithm-particle swarm optimization (GA-PSO) algorithm is brought forward to optimize the parameter values of the SVR, which could improve the estimation accuracy and convergence speed. The proposed SOH estimation method is applied to four batteries and gets a root mean square error (RMSE) of 0.40% and an average absolute percentage error (MAPE) of 0.56%. In addition, the method is also compared with genetic algorithm-support vector regression (GA-SVR) and particle swarm optimization-support vector regression (PSO-SVR), respectively. The results show that (i) compared with the PSO-SVR method, the proposed method can decrease the average RMSE by 0.10%, and the average MAPE by 0.17%; (ii) compared with the GA-PSO method, number of iterations under the proposed method can be reduced by 7 generations.

Bus signal priority (BSP) is an effective strategy to enhance the quality of public transit service, but unfortunately, it also deteriorates the performance of general vehicles. However, th...

Replacing conventional buses with electric buses is in line with the concept of sustainable development. However, electric buses have the disadvantages of short driving range and high purchase price. Many cities must implement a semi-electrification strategy for bus routes. In this paper, a bi-level, multi-objective programming model is established for the collaborative scheduling problem of vehicles and drivers on a bus route served by the mixed bus fleet. The upper-layer model minimizes the operation cost and economic cost of carbon emission to optimize the vehicle and charging scheme; while the lower-layer model tries to optimize the crew-scheduling scheme with the objective of minimizing driver wages and maximizing the degree of bus-driver specificity, considering the impact of drivers’ labor restrictions. Then, the improved multi-objective particle swarm algorithm based on an ε-constraint processing mechanism is used to solve the problem. Finally, an actual bus route is taken as an example to verify the effectiveness of the model. The results show that the established model can reduce the impact of unbalanced vehicle scheduling in mixed fleets on crew scheduling, ensure the degree of driver–bus specificity to standardize operation, and save the operation cost and driver wage.

2,2′,4,4′,6,6′-Hexanitrostilbene (HNS) is an explosive with increased heat resistance, and its mechanism of thermal decomposition is of interest. In this paper, the decomposition processes of HNS at various temperatures (2500, 2750, 3000, 3250, and 3500 K) are calculated by large-scale reactive molecular dynamics simulations. The initial reactions and the evolution of clusters (whose molecular weight is larger than HNS) are analyzed. The reaction kinetics parameters are fitted. The results show that the main initial decomposition mechanisms of HNS are C–NO2 bond dissociation and nitro-nitrite (NO2–ONO) isomerization. During decomposition, O atoms are less likely to be released from the cluster than H and N atoms. Low temperatures tend to produce larger clusters, and clusters at higher temperatures tend to decompose. The thermal decomposition of HNS is a combination of single-molecule and bimolecular decomposition mechanisms. The dimerization reaction is clearly weakened, and the C–N bond cleavage is still...

Recent ten years, the teaching learning based optimization algorithm (TLBO) has been widely concerned and successfully applied to solve various constraints and non-constraints problems. However, its convergence accuracy and convergence speed should be further improved. Therefore, a novel chaotic teaching learning based optimization algorithm (called CTLBO) is proposed. Firstly, chaotic variables are applied to initialize population individuals for increasing the diversity of population. Secondly, a kind of self-adaptive acceleration coefficient is introduced into teaching phase to enhance the convergence speed and solution quality. Finally, two population updating mechanisms are proposed to balance the exploration and exploitation capabilities in the learning phase. One is neighbor elitist search mechanism, another is chaos optimization mechanism. The performance of CTLBO is compared with five state-of-the-art optimization algorithms by several CEC mathematical problems. The experiment results show that the CTLBO yields better convergence rate than other algorithms on most testing functions. Additionally, the proposed CTLBO is applied to optimize the model parameters of extreme learning machine(ELM) and the tuned ELM is adopted to establish the NOx emissions model. Experiment results reveal that the NOx emissions model has good accuracy and meets the engineering requirement.

Background While prostate cancer can often manifest as an indolent disease, the development of locally-advanced or metastatic disease can cause significant morbidity or mortality. Elucidation of molecular mechanisms contributing to disease progression is crucial for more accurate prognostication and effective treatments. R-Spondin 3 (RSPO3) is a protein previously implicated in the progression of colorectal and lung cancers. However, a role for RSPO3 in prostate cancer prognosis and behaviour has not been explored. Methods We compare the relative levels of RSPO3 expression between normal prostate tissue and prostate cancer in two independent patient cohorts (Taylor and GSE70768—Cambridge). We also examine the association of biochemical relapse with RSPO3 levels in these cohorts. For elucidation of the biological effect of RSPO3, we use siRNA technology to reduce the levels of RSPO3 in established prostate cancer cell lines, and perform in vitro proliferation, invasion, western blotting for EMT markers and clonogenic survival assays for radiation resistance. Furthermore, we show consequences of RSPO3 knockdown in an established chick chorioallantoic membrane (CAM) assay model of metastasis. Results RSPO3 levels are lower in prostate cancer than normal prostate, with a tendency for further loss in metastatic disease. Patients with lower RSPO3 expression have lower rates of biochemical relapse-free survival. SiRNA-mediated loss of RSPO3 results in no change to clonogenic survival and a lower proliferative rate, but increased invasiveness in vitro with induction of epithelial–mesenchymal transition (EMT) markers. Consistent with these results, lower RSPO3 expression translates to greater metastatic capacity in the CAM assay. Together, our preclinical findings identify a role of RSPO3 downregulation in prostate cancer invasiveness, and provide a potential explanation for how RSPO3 functions as a positive prognostic marker in prostate cancer. Electronic supplementary material The online version of this article (10.1186/s12967-019-1878-3) contains supplementary material, which is available to authorized users.

This work has been retracted at the request of the authors as it contains some potentially misleading information. The retracted Work remains in the ACM Digital Library for archiving purposes only and should not be used for further research or citation purposes. Brian Harrington, Marzieh Ahmadzadeh, Nick Cheng, Eric Heqi Wang, and Vladimir Efimov. 2018. TA Marking Parties: Worth the Price of Pizza? In Proceedings of the 2018 ACM Conference on International Computing Education Research (ICER '18). Association for Computing Machinery, New York, NY, USA, 232-240. DOI:https://doi.org/10.1145/3230977.3230997

A novel robust meta-heuristic optimization algorithm, which can be considered as an improvement of the recently developed firefly algorithm, is proposed to solve global numerical optimization problems. The improvement includes the addition of information exchange between the top fireflies, or the optimal solutions during the process of the light intensity updating. The detailed implementation procedure for this improved meta-heuristic method is also described. Standard benchmarking functions are applied to verify the effects of these improvements and it is illustrated that, in most situations, the performance of this improved firefly algorithm (IFA) is superior to or at least highly competitive with the standard firefly algorithm, a differential evolution method, a particle swarm optimizer, and a biogeography-based optimizer. Especially, this new method can accelerate the global convergence speed to the true global optimum while preserving the main feature of the basic FA.

A novel robust hybrid meta-heuristic optimization approach, which can be considered as an improvement of the recently developed biogeography based optimization, namely HSBBO, is proposed to solve global numerical optimization problem. HSBBO combines the exploration of harmony search (HS) with the exploitation of BBO effectively, and hence it can generate the promising candidate solutions. The detailed implementation procedure for this improved meta-heuristic method is also described. Fourteen standard benchmark functions are applied to verify the effects of these improvements and it is demonstrated that, in most situations, the performance of this hybrid meta-heuristic method (HSBBO) is superior to or at least highly competitive with the standard BBO and other population-based optimization methods, such as ACO, BBO, DE, ES, GA, HS, PBIL, PSO and SGA. The effect of the HSBBO parameters is also analyzed. Copyright 2013 American Scientific Publishers.

High-power repetitively-pulsed TEA CO2 lasers are excited by a glow discharge, and it turns out to be the arc discharge under some conditions. The arc-discharge is a disadvantageous condition and must be avoided. According to the Faraday electromagnetism induction principle, the arc-discharge monitoring system with a magnetic-field probe is designed for high-power repetitively-pulsed TEA CO2 lasers. The magnetic-field variation induced by the discharge current can be tested, and the discharge state can be distinguished according to the output induction voltage. Experimental results show that the magnetic-field induction voltages generated by a glow discharge and an arc discharge are very different ones. The maximum induction voltage of the glow discharge is 2.0 V, while the minimum induction voltage of the arc discharge is 2.5–4 V. Three alarm levels are set by measuring the arc-discharge intensities. At the first level, automatic filling–exhausting equipment starts to refresh the gas media, at the second level, the laser repetition rate is reduced, and at the third level the laser operation stops immediately. As a result, the working reliability of a high-power repetitively-pulsed TEA CO2 laser system can be improved significantly by using the arc-discharge monitoring system.

In order to improve the design reliability of retracting actuator, the reliability analysis is taken by NESSUS software based on the stress — strength interference theory. The design reliability value was obtained. The sensitivity and importance analysis on random variables which affect the design reliability were done. The result shows that the design reliability value is 0.99999999986, and the relative error between the test value is 1.3E-10, which is acceptable in engineering. The parameters that have relatively greater effect on the reliability and ordered by influence degree are diameter of shear pin, active area of output pressure, gunpowder impetus and density of detonator output charge. The consistency of these parameters should be guaranteed in material selection and product processing.

A hybrid metaheuristic approach by hybridizing harmony search (HS) and firefly algorithm (FA), namely, HS/FA, is proposed to solve function optimization. In HS/FA, the exploration of HS and the exploitation of FA are fully exerted, so HS/FA has a faster convergence speed than HS and FA. Also, top fireflies scheme is introduced to reduce running time, and HS is utilized to mutate between fireflies when updating fireflies. The HS/FA method is verified by various benchmarks. From the experiments, the implementation of HS/FA is better than the standard FA and other eight optimization methods.

From the system perspective, this paper classifies the open courseware organization mechanism into seven parts, which include course selection mechanism, teaching contents and methods design mechanism, video fabricating mechanism, intellectual property protection mechanism, service & feedback mechanism, publicity & promotion mechanism, and operation mechanism, aimed at constituting a structural equation model composed of such seven first-order factors. The analysis of questionnaire data using confirmatory factor analysis method indicates the first-order structural model is tenable, and there is higher correlation between factor constructs; the second-order factor model is also tenable and gives an interpretation of the correlation between the first-order factors. The research outcome will serve as a reference for developing an open courseware organization mechanism for China's higher education institutions.

To investigate and evaluate prevention and treatment of seroma by transposition of tissue flaps and Arista hemostatic powder after regional lymph node resection in patients with malignant tumors.Twelve patients (6 males, 6 females; aged 31-81 years, with metastatic tumors underwent prevention and treatment of seroma with the tissue flaps and Arista hemostatic powder spray after regional lymph node resection. The metastatic tumors involved the axilla in 1 patient with breast carcinoma, the iliac and inguinal regions in 2 patients with carcinomas of the uterine cervix and the rectum, and the inguinal region in 9 patients, including 4 patients with malignant fibrous histiocytoma(3 in the thigh, 1 in the leg), 2 patients with squamous carcinomas in the leg, 1 patient with synovial sarcoma in the knee, 1 patient with epithelioid sarcoma in the leg, and 1 patient with malignant melanoma in the foot. As for the lymph node removal therapy. 1 patient underwent axillary lymph node removal, 2 patients underwent lymph node removal in theiliac and inguinal regions, and 9 patients underwent lymph node removal in the inguinal region. Meanwhile, of the 12 patients, 6 patients underwent transposition of sartorius flaps with Arista hemostatic powder, 3 patients underwent transposition of the rectus abdominis myocutaneous flaps (including 2 patients treated with Arista spray befor the wound closure and 1 patient treated by transposition of local skin flaps with Arista spray used again),and 3 patients underwent only the suturing of the wounds combined with Arista. At the same time, of the 12 patients,only 4 patient underwent the transplantation of artificial blood vessels.The follow-up for 2-10 months after operation revealed that 10 patients, who had received the transposition of tissue flaps and the spray of Arista hemostatic powder, had the first intention of the incision heal with seroma cured. Nine patients were given a preventive use of Arista hemostatic powder and therefore no seroma developed. The combined use of the transposition of tissue flaps and Arista hemostatic powder spray achieved a success rate of 100% in the prevention or treatment of seroma. However, 1 patient developed microcirculation disturbance 24 hours after operation and underwent disarticulation of the hip; 1 patient developed pelvic cavity hydrops and died 10 months after operation.The combined use of transposition of tissue flaps and Arista hemostatic powder spray can effectively prevent or treat seroma after regional lymph node removal in a patient with malignant tumor.