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In the shortest path planning problem, the old algorithm usually has many defects, such as the robot’s cognition being contrary to reality, the lack of practical operation feasibility, or the limitation of problem processing. Nowadays, with deep learning, artificial intelligence algorithms tend to be mature; it has become a mainstream trend to adopt end-to-end learning system instead of traditional old algorithms. In recent years, with the rise of the Internet of things emerging technology industry and the explosive surge of network data traffic, the drawback is the increasingly severe shortage of wireless spectrum resources. In order to effectively reduce the cochannel interference of D2D communication technology in the system and enhance the useable range of the cellular network, it is necessary to distribute the useful and efficient cellular resources of the system. In this article, we will study the D2D users and the selection scheme of D2D users’ transmission power control mode and allocate the spectrum resources in the uplink of the cellular users in the communication network. In order to reduce the cochannel interference in a cellular network and improve the spectrum utilization of the system, the research direction of this article is to solve the problem of user communication resource allocation in a single-cell hybrid cellular network.

Background: Breast cancer is one of the most common cancers worldwide among women, and angiogenesis has an important effect on its growth and metastasis. Glipizide, which is a widely used drug for type 2 diabetes mellitus, has been reported to inhibit tumor growth and metastasis by upregulating the expression of natriuretic peptide receptor A (NPRA). Atrial natriuretic peptide (ANP), the receptor of NPRA, plays an important role in angiogenesis. The purpose of this study was to explore the effect of glipizide combined with ANP on breast cancer growth and metastasis. Methods: This study aimed at investigating the effect of glipizide combined with ANP on breast cancer. Glipizide, ANP, or glipizide combined with ANP was intraperitoneally injected into MMTV-PyMT mice. To explore whether the anticancer efficacy of glipizide combined with ANP was correlated with angiogenesis, a tube formation assay was performed. Results: Glipizide combined with ANP was found to inhibit breast cancer growth and metastasis in MMTV-PyMT mice, which spontaneously develop breast cancer. Furthermore, the inhibitory effect of ANP combined with glipizide was better than that of glipizide alone. ANP combined with glipizide significantly inhibited tube formation of human umbilical vein endothelial cells (HUVECs) by suppressing vascular endothelial growth factor (VEGF)/VEGFR2 (vascular endothelial growth factor receptor 2) signaling. Conclusions: These results demonstrate that glipizide combined with ANP has a greater potential than glipizide alone to be repurposed as an effective agent for the treatment of breast cancer by targeting tumor-induced angiogenesis.

Illumina MiSeq high-throughput sequencing technology was used to study the microbial community structure of medium-temperature Daqu produced via a digitally managed method and the traditional method. The relationship between the changes in physicochemical properties and microorganisms in Daqu during the fermentation process was analyzed. At the end of fermentation, the bacterial diversity of traditional medium-temperature Daqu was higher than that of digital medium-temperature Daqu, and there was no significant difference in the diversity of fungal communities. The dominant bacteria were Weissella, Lactobacillus, Pediococcus and Saccharopolyspora. The dominant fungi were Thermoascus, Issatchenkia and Candia. On the 25th day of fermentation, the bacterial community distribution in the digital Daqu was more even than that in the traditional Daqu, but the fungal community distribution was the opposite. The results of nonmetric multidimensional scale (NMDS) analysis and canonical correlation analysis (CCA) show that Daqu produced by the two fermentation methods had many similarities.

In order to optimize the deployment of wireless sensor network nodes, and avoid network energy consumption increase due to node redundancy and uneven coverage, the multi-objective mathematical optimization problem of area coverage is transformed into a function problem. Aiming at network coverage rate, node dormancy rate and network coverage uniformity, the idea of genetic algorithm mutation is introduced based on the discrete binary particle swarm optimization and the global optimal speed is mutated to avoid the algorithm falling into the local optimal solution. In order to further improve the optimization ability of the algorithm, the adaptive learning factor and inertia weight are introduced to obtain the optimal deployment algorithm of wireless sensor network nodes. The experimental results show that the algorithm can reduce the number of active nodes efficiently, improve coverage uniformity, reduce network energy consumption and prolong network lifetime under the premise that the coverage rate is greater than 90%, and compared with an algorithm called coverage configuration protocol, an algorithm called finding the minimum working sets in wireless sensor networks, and an algorithm called binary particle swarm optimization-g in literature, the number of active nodes in this algorithm is reduced by about 36%, 30% and 23% respectively.

The laser marking system was combined with MES system, the marking setting database was established by sorting out the product specifications, and the products of various specifications were quickly matched by calling the template, so as to realize the control automation of the product marking system and reduce the difficulty of processing non-standard products. Using image recognition technology, the marking area and the marking effect are digitized, the quality monitoring visual window is established, and the backup is stored in the MES system, so that the quality is controllable and can be checked in the later stage. The laser marking system introduced in this paper reduces manual intervention in production data to the greatest extent, improves the accuracy of information, sorts out various types and specifications of products, and sets up marking templates accordingly, which greatly improves the efficiency of cable network production. Finally, image recognition technology is applied to quality control to realize quality management and record, which provides reference for other production and processing system design.

Both diabetes and breast cancer are common diseases worldwide, and diabetes is also linked to higher rates of breast cancer. Epidemiological data also indicate that diabetes may be one of the risk factors for breast cancer. However, the effect of diabetes on breast cancer progression in vivo is rarely reported. We established an ideal animal model of breast cancer using transgenic MMTV-PyMT mice, which spontaneously developed breast cancer. In this model, the animals copresented with diabetes mellitus, which allowed us to study the effect of high glucose on breast cancer. Compared with MMTV-PyMT mice without diabetes, MMTV-PyMT mice with diabetes developed heavier tumors and exhibited greater tumor volumes. Furthermore, high glucose promoted the invasiveness and metastasis of breast cancer in MMTV-PyMT mice. This breast cancer model in which mice copresented with diabetes provides a useful tool to study the effect of diabetes on breast cancer. Anat Rec, 302:269-277, 2019. © 2018 Wiley Periodicals, Inc.

In the digital revolution era the work style of the people changed into real and live communicative systems. Smart cities are evolved from the smart ecosystem with various domains like healthcare, information exchange, transportation, buildings etc., the presence of multiple information system makes these smart cities into a heterogeneous which includes multiple data transfer based on the large no of interconnected sub systems. Since the systems provide data from various terminals to the host the amount of information generates is same as the chances of increasing the challenges and issues in the smart city. These flow data from various sources are handled using cluster computing and this proposed research provides the data flow in the smart city using cluster computing. Apache spark is the tool used to handle the issues in the smart city which is much better than the Hadoop. The results discuss the comparison between the applications in same environment on both the tools.

Breast cancer is the most common malignant tumor among women, and the incidence and mortality of breast cancer has rapidly increased in recent years. Studies have indicated that high mobility group A1 (HMGA1), an important member of the HMGA family, plays a role in the pathogenesis and progression of malignant tumors, including breast cancer. This study aims to evaluate the effect of HMGA1 in breast cancer. Interestingly, we found that HMGA1 expression was significantly higher in breast cancer tissues than in adenoma tissues and closely correlated with the clinical stage and histological grade in breast cancer patients. Further study showed that HMGA1 knockdown inhibited the proliferation and migration of breast cancer cells. Thus, the results demonstrated that HMGA1 could act as an independent prognostic indicator in breast cancer. HMGA1 expression was closely correlated with the clinical stage, histological grade, and tumor size in breast cancer patients and breast cancer progression in transgenic MMTV-PyMT mice. Anat Rec, 301:1061-1067, 2018. © 2018 Wiley Periodicals, Inc.

Computer generated security concerns have become more modern and complex. Intrusion detection(ID) is a practical issue in the field of computer security whose primary objective is to detect rare attack or assaults and to ensure the security of interior systems. This paper also proposes a semi-class intrusion detection method that combines multiple classifiers to arrange exceptions and typical exercises in a computer system. The abuse detection model is constructed in the light of the decision tree learning-iterative dichotomise 3(DTL-ID3) and is assembled by utilizing the gathered data based on anomaly detection model executed by one class-support vector machine(OC-SVM). In recent years, people have paid more attention to ID/intrusion prevention system (IDS / IPS), which is closely related to the protection and utilization of system management. A few machine-learning standards including neural system, direct hereditary programming, and advanced support vector machines(ASVMs), Bayesian system, multivariate versatile relapse splines, fluffy derivation systems(FIS) and other analogical systems have been researched for the outline of intrusion detection system. In this paper, we build up an amalgam method based on DTL-ID3 and OC-SVM(A-DT and SVM) and evaluate the performance of the projected methodology by using a specific dataset and a crossover method in order to enhance the accuracy of IDS/IPS when contrasted with a singular support vector machine.

Breast cancer is one of the most common cancers worldwide with a rising incidence, and is the leading cause of cancer-related death among females. Angiogenesis plays an important role in breast cancer growth and metastasis. In this study, we identify decylubiquinone (DUb), a coenzyme Q10 analog, as a promising anti-breast cancer agent through suppressing tumor-induced angiogenesis. We screened a library comprising FDA-approved drugs and found that DUb significantly inhibits blood vessel formation using in vivo chick embryo chorioallantoic membrane (CAM) and yolk sac membrane (YSM) models. DUb was further identified to inhibit angiogenesis in the rat aortic ring and Matrigel plug assay. Moreover, DUb was found to suppress breast cancer growth and metastasis in the MMTV-PyMT transgenic mouse and human xenograft tumor models. To explore whether the anticancer efficacy of DUb was directly corrected with tumor-induced angiogenesis, the MDA-MB-231 breast cancer assay on the CAM was performed. Interestingly, DUb significantly inhibits the angiogenesis of breast cancer on the CAM. Brain angiogenesis inhibitor 1 (BAI1), a member of the G protein-coupled receptor (GPCR) adhesion subfamily, has an important effect on the inhibition of angiogenesis. Further studies demonstrate that DUb suppresses the formation of tubular structures by regulating the reactive oxygen species (ROS)/p53/BAI1 signaling pathway. These results uncover a novel finding that DUb has the potential to be an effective agent for the treatment of breast cancer by inhibiting tumor-induced angiogenesis.

Breast cancer (BC) is one of the most common cancers among women in both developed and developing countries with a rising incidence. Using the MMTV-PyMT transgenic mouse model and xenografted breast cancer model, we found that R5, a neutralizing antibody to Robo1, significantly inhibited BC growth and metastasis. Angiogenesis is involved in the growth and metastasis of BC. Interestingly, R5 significantly decreases microvessel density in BC tissues, and inhibits blood vessel formation and development in in vivo chick embryo chorioallantoic membrane (CAM), yolk sac membrane (YSM) and Matrigel plug models. To investigate whether its anti-breast cancer efficacy is ascribed to its direct antiangiogenic properties, xenografted breast cancer model on CAM was established. Furthermore, R5 significantly reduces the tube formation of the vascular plexus on xenografted breast tumor on CAM. R5 also suppresses the migration and the tubular structure formation of human umbilical vein endothelial cells (HUVECs) by down-regulating the expression of filamin A (FLNA). These findings show that R5 has the potential to be a promising agent for the treatment of BC by suppressing the tumor-induced angiogenesis.

This paper introduces a novel control strategy into the insulation space for liquid natural gas carriers. The control strategy proposed can improve the effects of control for differential pressure and reduce the energy consumption of nitrogen. The method combines a nonlinear feedback technique with a closed-loop gain shaping algorithm (CGSA). It is designed for the pressure control system which is vital for liquid natural gas carriers (LNGCs) in marine transportation. The control error is modulated using nonlinear function. The deviation signal is replaced with a nonlinear feedback signal. Comparison experiments are conducted under different conditions to prove the effectiveness of this strategy. This paper compares three control strategies: a control strategy with nonlinear feedback based on CGSA, a control strategy without nonlinear feedback based on CGSA, and a two-degree-of-freedom (DOF) control strategy. The simulation results show that this control strategy with nonlinear feedback performs better than the other two. The average reduction of control input is about 38.8%. The effect of pressure control is satisfactory.

The pressure control for a liquid nature gas (LNG) ship is vital for the cargo handling system which is a nonlinear, unstable, and controllable complex system accompanied by the dynamics of time delay. To improve the control effect, this article proposed a robust controller based on closed-loop gain shaping algorithm by mirror-mapping approach. In addition, the complete mechanism models for the system are established to predict the changes of temperature, pressure, and liquid inventory in the cargo tank. The heat exchanges and evaporation of liquid are also considered. By collecting the data from the LNG ship “Dapeng,” the system models are validated. At the same time, the comparative experiment is introduced to verify the reliability and effectiveness. The scheme has been compared with the 2-DOF structure control law of modified Smith predictor. The comparative experimental results show that the scheme proposed in this note has a strong disturbance rejection ability and steady-state performance. The controller designed in this note has advantages of simplified construction method, satisfactory control effect and robustness.

This paper presents a UIR-Miner system for emotion and sentiment analysis evaluation in Twitter in SemEval 2018. Our system consists of three main modules: preprocessing module, stacking module to solve the intensity prediction of emotion and sentiment, LSTM network module to solve multi-label classification, and the hierarchical attention network module for solving emotion and sentiment classification problem. According to the metrics of SemEval 2018, our system gets the final scores of 0.636, 0.531, 0.731, 0.708, and 0.408 on 5 subtasks, respectively.

Breast cancer is the most common malignant tumor among women, and the incidence and mortality of breast cancer has rapidly increased in recent years. Studies have indicated that high mobility group A1 (HMGA1), an important member of the HMGA family, plays a role in the pathogenesis and progression of malignant tumors, including breast cancer. This study aims to evaluate the effect of HMGA1 in breast cancer. Interestingly, we found that HMGA1 expression was significantly higher in breast cancer tissues than in adenoma tissues and closely correlated with the clinical stage and histological grade in breast cancer patients. Further study showed that HMGA1 knockdown inhibited the proliferation and migration of breast cancer cells. Thus, the results demonstrated that HMGA1 could act as an independent prognostic indicator in breast cancer. HMGA1 expression was closely correlated with the clinical stage, histological grade, and tumor size in breast cancer patients and breast cancer progression in transgenic MMTV-PyMT mice. Anat Rec, 301:1061-1067, 2018. © 2018 Wiley Periodicals, Inc.

The tumor suppressor gene tissue inhibitor of metalloproteinase-3 (TIMP-3) has been reported to be frequently and significantly downregulated in gastric cancer, and its downregulation is correlated with hypermethylation in its promoter region. However, the association between TIMP-3 methylation and gastric cancer risk remains unclear.In this study, we assessed the relationship between TIMP-3 promoter methylation and gastric cancer risk by performance of a meta-analysis.Relevant studies were identified in a comprehensive literature search using PubMed, Embase, and Web of Science databases. The strength of the association between TIMP-3 methylation and the risk of gastric cancer was assessed by odds ratio (OR) with the corresponding 95% confidence interval (CI). The heterogeneity among studies was tested using the Q-statistics and I(2) metric. The publication bias was examined by Begg's funnel plots and Egger's linear regression test.A total of 1096 subjects from eight studies were included in the present meta-analysis. Overall, a significant association between TIMP-3 methylation and gastric cancer risk was observed (OR = 8.65; 95% CI 4.31-17.37; p 0.001). Stratified analyses by ethnicity, sample materials, and detection methods also revealed increased gastric cancer risk in individuals harboring methylated TIMP-3. Moreover, no publication bias was detected in the present meta-analysis.Our results show a positive correlation between TIMP-3 promoter methylation and gastric cancer risk and indicated that TIMP-3 promoter methylation may be used as a molecular marker for gastric cancer.

Pretreatment conditions of geniposide and conversion process conditions of gardenia red pigment were optimized, gardenia red pigment was refined by acid precipitation or resin, and the effects of refining were compared, conversion process of high color value gardenia red pigment was studied, the results suggested that 5 g sodium hydroxide was added to the 50 mL concentrated geniposide at 40 °C and stirred for 3 h, 12.5 g citric acid was added with stirring until it was dissolved, then 30 mL pretreated geniposide and 6 g sodium glutamate were added to 50 mL fermentation broth of Aspergillus niger, it was kept at 50 °C in vacuum incubator for 25 h, then the fermentation broth was put into the boiling water for 2 h. Under the above conditions, the color value of gardenia red pigment which refined by acid precipitation or resin was 53 and 63, respectively. It was improved significantly when compared with color value was 4 under the initial conditions.

Basicneeds Foundation as an international charitable organization，after years of efforts，it explores a suitable for the development of mental health services and the development model and developed countries.It makes the majority of mental health patients recover their health, social function and the ability to work has been restored.Since 2012, carried out in China, also made a lot of results.This article starts from Basicneeds’s five modules, which were summarized in China Baoding Shunping rural areas, for mental illness research progress.At the same time, the Basicneeds group also hopes to improve its model, making it more suitable for the situation in China, and in more places be promoted.

A real time algorithm embedded in single chip computer (MCU) is presented to count steps precisely. According to the features of the step wave, Chain Code is adopted to encode the signal. Then the Freeman Chain Code is analyzed and modified for signal processing. Steps are detected through recognition of wave group after encoding. The experimental result shows that this algorithm can significantly improve the pedometer's accuracy.

A new kind of material for oil adsorption was prepared by melt blend with EPDM as the matrix and MgO as the filler. The effects of Dicumyl peroxide (DCP) and MgO contents on the oil absorbency were studied. Comparing the two samples with the highest oil adsorption rates, the experimental result indicates that the oil absorbency of EPDM (cross linked) is 51% more than that of EPDM the oil absorbency of MgO/EPDM composite is 886.54% more than that of EPDM (cross linked), the oil absorbency of MgO/EPDM composite is 198.22% more than that of MgO (coupling agent)/EPDM composite. The absorbent characteristics of MgO/EPDM are better than these of MgO (coupling agent)/EPDM.

The rapid development of Networks and distributed computing technologies enables inter process communication mechanism more and more important, semaphore has many advantages in the distributed inter-process communication mechanism. This article is based on the daemon and provides implements of semaphore mechanism in the distributed system inter process communication, then associates it with the traditional method of the socket. The experiment results show, distributed semaphore has better practicality and transparency than socket method.

According to the classic controllers, this paper designs a PID controller based on the BP neural network theory. Having adopted the training method of the BP neural network, a model of worktable driving for the concentration of black liquor is simulated with MATLAB software, and the results prove the feasibility of the method.

In general, using kernel function to solve problems of non-linear and recognition ratio, as is done in human face recognition, is particularly effectively. Firstly, a hybrid kernel function is constructed, and then a modified human face recognition algorithm about Kernel-based KICA and Kernel-based improved PSVM methods is presented. The traditional ICA methods have limitations for non-linear image in facial feature extraction process. Using kernel-based non-linear image characteristics, KICA method analyses data in the high-dimensional feature space. As a machine learning algorithm, SVM also has some limitations. This article presents an improved Non-linear PSVM algorithm to get a better recognition ratio and a little time consuming. Eventually the tests for feasibility are performed.

Participants bring expertise and ideas from diverse scientific backgrounds to the CAKFoS symposia, which are designed to promote cross-disciplinary discussion and generate new ideas. Each symposium is organized around eight topics, jointly selected by a committee of CAS and NAS delegates, and based largely on feedback from the previous year's meeting. Session chairs and speakers highlight the major challenges, methodologies, and limitations in their fields without using technical jargon to ensure that nonspecialists are able to understand and contribute to the meeting. Speakers and participants pose and field challenging questions that probe into and across traditional boundaries of research disciplines.