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Background: Primary liver cancer (PLC) is a common cancer, and its morbidity and mortality are ranked 6th and 3rd in the world for malignant tumors, respectively. And this number is still on the rise, seriously endangering people's health. In recent years, acupuncture combined with Chinese herbal medicine have been widely used in the treatment of PLC, and there are few restrictions. However, we have not found a meta-analysis of their synergistic effects. Therefore, this systematic review and meta-analysis will evaluate the efficacy and acupuncture combined with Chinese herbal medicine in the treatment of primary liver cancer. Method: We will search the following databases from inception up to August 20, 2021: PubMed, Web of Science, Embase, AMED, Cochrane Library, CNKI, VIP, CBM, and Wanfang. There will be no restrictions regarding publication date or language. We will apply a combination of medical keywords and words, including “acupuncture,” “Chinese herbal medicine” and “primary liver cancer”. Additionally, we will manually search all reference lists from relevant systematic reviews to find other eligible studies. We will use the random effects model in REVMAN v5.3 for meta-analysis. The study for acupuncture combined with Chinese herbal medicine in the treatment of PLC was a randomized controlled study. Two researchers will independently review the research selection, data extraction, and research quality assessments. Finally, we will observe the outcome measures. Results: This study will provide evidence-based medical evidence for the treatment of PLC with a combination of acupuncture and Chinese herbal medicine, and provide new ideas and methods for the treatment of PLC. Registration number: INPLASY202180103

Due to an anti-failure bias, theoretical and practical studies have not focused much on the problem of innovation failure. The literature does not include studies on how the effect of re-innovation input on firm performance can still be explained by existing theories, especially in the case of previous innovation failures. To explore the intrinsic relationship between the re-innovation from failure and firm performance, as well as the influencing mechanism of the institutional environment differences on a firm’s re-innovation activities, using the data of the Listed Companies in China’s pharmaceutical manufacturing industry from 2008 to 2014 and a multiple regression model, the relationships between the re-innovation from failure, institutional environment differences, and firm performance were analyzed from 3 aspects: government intervention, financial development, and legal environment. The results show that the re-innovation input from failure has a significant positive impact on firm performance. The level of government intervention and the level of financial development play significant negative and positive moderating roles in the relationship between the re-innovation input and firm performance, respectively, and the above-mentioned effects are more prominent in eastern China. Moreover, with the improvement of the marketization of the financial industry, the beneficial effect of the re-innovation input from failure on firm performance in state-owned firms will be further strengthened. However, the moderating effect of the legal environment is not obvious.

Reactivation of Epstein-Barr virus (EBV), as indexed by the higher immunoglobulin A (IgA) antibody titers, was reported to be associated with an increased risk of breast cancer. Passive smoking plays a role in host immune responses and may modify the association of EBV with breast cancer. We carried out a case-control study using data from 349 incident breast cancer cases and 500 age-matched controls in the Guangzhou Breast Cancer Study to investigate the interactions of EBV antibodies and passive smoking on breast cancer risk. A higher risk of breast cancer was observed in passive smokers who were seropositive for EBV viral capsid antigen IgA or nuclear antigen-1 IgA in serum compared with those with the seronegativity and no passive smoking [odds ratio 3.13 (95% confidence interval, 1.76-5.56)]. There was a significant linear trend for the risk of breast cancer from IgA seropositivity with passive smoking, only IgA seropositivity, only passive smoking, to seronegativity without passive smoking (P

A novel parallel spectral clustering approach is proposed by exploiting the distributed computing in MATLAB for SAR image segmentation quickly and accurately. For large-scale data applications, most existing spectral clustering algorithms suffer from the bottleneck problems of high computational complexity and large memory use. And in the absence of advanced hardware and software equipments with only the loosely coupled computer resources accessible, the framework of MATLAB Parallel Computing-based sparse spectral clustering is constructed in this paper. In the proposed frame, we use a distributed parallel computing model to accelerate computation, where each partition of data instances is assigned to different processor nodes for the similarity matrix calculation in spectral clustering. Further, by the construction of exact t-nearest neighbor sparse symmetric similarity matrix, the sparseness technique is employed to alleviate the storage stress. Besides, the problems of how to choose the number of nearest neighbors and the scaling parameter are also discussed. The segmentation results on artificial synthesis texture images and SAR images show that the proposed parallel algorithm can effectively handle large-size segmentation cases. Meanwhile, it can obtain better segmentation results compared with Nystrom approximation spectral clustering and k-means clustering algorithm.

It was summarized that the basic knowledge and principles of the Hilbert-Huang transform (HHT), and realized HHT pairs of EMR signal analysis and processing. Using Ensemble Empirical Mode Decomposition (EEMD) to decompose coal or rock electromagnetic radiation signals which obtained with the various stages of coal or rock failure process under uniaxial compression deformation, rupture, crack propagation, destruction, get some intrinsic mode functions (IMF) with the independently physical meaning; from these IMFs determine the valid signal waveforms of EMR signal; lay the foundations of field application of EMR prediction method.

Web applications have made a significant impact on computer system.Among them mining useful information from web logs is is important and challenging research topics. In this paper, the time durations of the paged browsed. are computed from web logs. Since the time durations are numeric, fuzzy concepts are used here to process them and to form linguistic terms. Besides different pages in web sites may have different interest to users, and some factors (i.e. the design of web pages) may affect users' browsing interest. So interest measures of web pages are evaluated by managers according to the judgment factors, and comprehensive fuzzy evaluation methods are used to evaluate the interest measure of each page. Then a new fuzzy web-mining algorithm is proposed, which can process to mine fuzzy browsing interest patterns with linguistic variables from web logs effectively. An example is given to clearly illustrate the proposed approach.

Base on the characteristics of the shunt active power filter, we uses the power electronic devices of the MATLAB/Simulink to model the system, uses self-compiled S-function to carry out the ip-iq current detection algorithm. In order to compensate the harmonic currents generated by the non-linear load and the reactive power of the process, the PWM signal is generated to drive the IGBT by the way of hysteretic current-tracking control. The simulation results show that the system simulation effectively simulate the establishing process of the DC side capacitor voltage at different stages and the harmonic current's compensation status in the corresponding stages, which is an important guiding significance to the shunt active power filter in the practical application.

A novel clustering algorithm is proposed, which is derived from physical intuition of quantum mechanics and biological principle based on immune clonal selection. As extension ideas of scale-space clustering and support vector clustering, quantum clustering method deduces the clustering allocation by gradient descent, which is prone to getting stuck in local extremes. By designing a novel and high-efficiency affinity function, we adopt an immune clonal selection algorithm with elite preservation strategy to search the global optimum. The experimental results on texture images and SAR images segmentation we demonstrate show that quantum clonal selection clustering method performs well both in precision and efficiency.

A time division multiple access (TDMA) scheduling protocol is proposed for solving the inter-cluster interference of medium access control (MAC) in cluster-based wireless sensor networks (WSN). Through each cluster-head snooping into the neighbor nodes' networking packets and creating the TDMA schedule based on these packets, the protocol can avoid inter-cluster interference. The protocol is implemented in an assumed single-physical-channel network, thus its implementation does not depend on specific hardware, and has the advantage of generality. The implementation of the protocol is based on TinyOS software platform and MICA2 hardware platform. The generation of the cluster-heads, the networking cost, the networking packet loss rate and the accuracy of sensing data transmission are tested, and the results show that the protocol can avoid the inter-cluster interference and has moderate reliability.

In this paper, a new and efficient method is proposed by using wireless sensor networks in on-line monitoring of large electrical equipment to solve the problems of existing on-line monitoring system that wiring too complicated, causing fault diagnosing, maintaining difficulty and so on. The features are described range from CC2431 system-on-chip to TinyOS which is a wireless sensor networks operating system, and nesC which is programming language of TinyOS. The hardware design for wireless sensor network node and base station based on the CC2431 chip and the program design of transplanting TinyOS into the sensorspsila nodes and base stations are discussed in detail. Finally a data multi-hop system is achieved.