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Background. Manual acupuncture (MA) with different stimulus frequencies may give rise to varying acupuncture effects. However, the intensity-effect relationship and the underlying mechanisms of MA remain unclear. Objective. To compare the analgesic effects of different frequencies of twirling-rotating MA on rats with complete Freund’s adjuvant- (CFA-) induced pain and explore the underlying mechanism via peripheral sensory nerves. Methods. First, 36 healthy male Wistar rats were randomly divided into 6 groups: control group, 2 r/s MA group (twirling-rotating MA with the frequency of 2 revolutions per second), 4 r/s MA group (twirling-rotating MA with the frequency of 4 revolutions per second), CFA group, CFA + 2 r/s MA group, and CFA + 4 r/s MA group. Rats in three CFA groups received an intraplantar injection of CFA to establish a pain model, while the rats in other three groups received an intraplantar injection of saline. Rats in the 2 r/s MA group and 4 r/s MA group were treated with the corresponding frequencies of twirling-rotating MA on bilateral Zusanli (ST36) and Kunlun (BL60) for 7 days. The ipsilateral nociceptive thresholds (paw withdrawal latency; PWL) were tested to evaluate the analgesic effects. Second, 9 healthy male Wistar rats were randomly divided into 3 groups: control group, 2 r/s MA group, and 4 r/s MA group. The proportion of C-fiber neurons (calcitonin gene-related peptide- (CGRP-) positive neurons) and A-fiber neurons (neurofilament 200- (NF200-) positive neurons) in the dorsal root ganglia (DRG) activated by MA were quantitatively analyzed with the morphological immunofluorescence staining method. Third, 30 healthy male Wistar rats were randomly divided into 6 groups: control group, CFA group, CFA + 2 r/s MA group, CFA + 2 r/s MA + RTX group, CFA + 4 r/s MA group, and CFA + 4 r/s MA + RTX group. Resiniferatoxin (RTX) was injected into the acupoints before acupuncture. PWL was evaluated to investigate the analgesic effect. Results. Both types of MA treatment increased the PWL of saline-injecting rats and pain model rats. Moreover, 4 r/s MA was superior to 2 r/s MA in increasing PWL. A higher quantity of excited C-fiber neurons was observed following 4 r/s MA than 2 r/s MA, while the reverse was observed in the activation of A-fiber neurons. Following the injection of RTX to inhibit the activation of C-fibers, the analgesic effect of 4 r/s MA reduced significantly but not of 2 r/s MA. Conclusion. Strong MA (4 r/s MA) has superior analgesic effects to gentle MA (2 r/s MA) on CFA model rats, which is associated with C-fiber activation.

Outsourcing project activities to contractors has become more and more popular in recent years, and activity contractors can increase the revenue of a project through cooperation. In this paper we consider cooperation between activity contractors through resource reallocation, and address two main issues. First, we seek to find the optimal scheme for resource reallocation among contractors. To this end, a linear programming model is established, and some properties of the optimal resource reallocation scheme are discussed. Second, we propose several revenue sharing schemes for contractors based on a cooperative game theory framework. Three schemes are introduced and compared: a scheme in the core, the Shapley value, and a proportional revenue sharing scheme. We show that the cooperative game of activity contractors in a general project network does not necessarily have a nonempty core. However, we identify a special class of project network for which the core of the cooperative game of activity contractors always exists and an allocation in the core is proposed based on shadow prices. The managerial insights we obtain in this paper are as follows. (i) Contractors should cooperate. (ii) Resources should not be transferred between contractors with high transferring costs. (iii) Resources are always transferred from contractors on non-critical paths to contractors on critical paths, and on critical paths, resources are always transferred from low efficiency contractors to high efficiency contractors.

The phase characteristics of gyrotron traveling-wave tubes (gyro-TWTs) for high-resolution imaging radars have been investigated. Determinant equations of output phase are classified into the cold phase and warm phase in the cases of cold-field and hot-field regions, respectively. The phase–frequency characteristics of cold phase are examined regarding single-mode and multimode operations, respectively. The time stability and the sensitivity to external parameters of warm phase are also investigated. The efficient methods to make the output phase of gyro-TWTs controllable are proposed. The measured output phase of the input coupler and output taper of a Ka -band gyro-TWT is linear with respect to the frequency, without any distortion. Moreover, the warm output phase fluctuation introduced by the RF circuit is less than ±8°.

At present, the development of NB-IoT technology is changing every day, and leads to a large amount of data exchange, analysis and storage issues, which brings many challenges to the traditional computing model--cloud computing. At the same time, it also points out the shortcomings and disadvantages of cloud computing in big data calculation and analysis. Based on this, the NB-IoT model based on fog computing was proposed and its main technologies and applications are analyzed to reduce the delay of NB-IoT data calculation, improve the response speed of application system, save network bandwidth, accelerate data exchange, ensure the quality of data analysis and improve the efficiency of data storage space and meanwhile, it is studied how to apply theory and technology to practice, and the application of NB-IoT main technology based on fog computing is also analyzed.

Fog computing based on big data is a hot topic in the research of computing technology at home and abroad. With the wide application and popularity of IoT (Internet of Things), the big data generated by edge devices is exploding, and cloud computing models are becoming increasingly inadequate to meet the needs of big data processing and communication, which is mainly manifested as follows. Slow data processing, insufficient storage space, prolonged communication and many other issues. Fog computing, of which the advantage is distributed computing, namely the „de-centralized„ mode calculation, is the suitable solution to solve these problems. In the IoT system, fog computing model based on big data is constructed to distribute the big data computing, storage and communication in the system to the edge device. The purpose is to make the system structure simpler, more modular and intelligent, duce network congestion, exploit advantages of edge devices and improve high quality intelligence of IoT applications, and moreover, to reduce the deployment of IoT hardware and operating costs. Taking the cloud robotics as an example, it is proposed to embed the fog computing technology in the cloud robotics system, which greatly improves the computing function of the cloud robotics system. In short, it provides theoretical support and scientific experimental basis for the informationization and intelligence of all walks of life, and its research has certain value and significance.

Background Surgical resection combined with adjuvant chemotherapy is considered as the gold-standard treatment for advanced colorectal cancer patients. These patients have a poor 5-year survival rate of 5% or less. Furthermore, a large dose of chemotherapy can produce adverse side effects and severe toxicity. Therefore, this retrospective study aimed to evaluate the efficacy of dendritic cell-cytokine-induced killer (DC-CIK) cell infusion as an adjuvant therapy in patients with advanced colorectal cancer combined with first-line treatment. Methods A total of 142 patients with stage III/IV colorectal carcinoma who had been treated with first-line therapy were included in this study. Among these patients, 71 patients received first-line treatment only (non-DC-CIK group), while the other 71 patients who had similar demographic and clinical characteristics received a DC-CIK cell infusion combined with first-line treatment (DC-CIK group). These patients were followed up until August 2014. Data were analyzed by Kaplan-Meier and Cox regression. Results Our results showed that the 5-year overall survival (OS) rate for the DC-CIK group versus the non-DC-CIK group was 41.3 versus 19.4% (p = 0.001) and the 5-year progression-free survival (PFS) rate for the DC-CIK group versus the non-DC-CIK group was 57.4 versus 33.6% (p = 0.022). Conclusions Our results showed that patients with advanced colorectal cancer might benefit from DC-CIK immunotherapy combined with first-line therapy by significantly prolonging 5-year OS and PFS.

Type 2 diabetes mellitus is a risk factor for Alzheimer's disease (AD). The glucagon-like peptide-1 analog liraglutide, a novel long-lasting incretin hormone, has been used to treat type 2 diabetes mellitus. In addition, liraglutide has been shown to be neurotrophic and neuroprotective. Here, we investigated the effects of liraglutide on amyloid β protein (Aβ)-induced AD in mice and explored its mechanism of action. The results showed that subcutaneous administration of liraglutide (25nmol/day), once daily for 8 weeks, prevented memory impairments in the Y Maze and Morris Water Maze following Aβ1-42 intracerebroventricular injection, and alleviated the ultra-structural changes of pyramidal neurons and chemical synapses in the hippocampal CA1 region. Furthermore, liraglutide reduced Aβ1-42-induced tau phosphorylation via the protein kinase B and glycogen synthase kinase-3β pathways. Thus liraglutide may alleviate cognitive impairment in AD by at least decreasing the phosphorylation of tau.

The purpose of this study is to identify and classify the ecological risks in land consolidation, and to develop a framework of the theory and method to assess the change of ecological risk degree before and after land consolidation. Environmental impacts and ecological risks of land consolidation have recently drawn much attention, and there are two opposing viewpoints to assess these impacts and risks in the academia of China. Both viewpoints result from the bias of assessment anticipation. Land consolidation includes four main engineering aspects in China, and ecological succession from start of land consolidation to ecosystem stabilization should pass three phases. Different ecological impacts and risks of land consolidation rise from different phases of ecological successions. According to the climax theory of ecology, we developed a framework of the ecological risk assessment based on the anticipation of ecosystem stabilization (ERABAES) for land consolidation. We applied analytical hierarchical processing (AHP) method to the data resources from the land consolidation project in Southern China to allocate weightings to the indices of ecological risk (ER), and to set up an integrated index system for the ecological risk identification. This integrated index system encompasses the ecological risks with three factors (water, soil and biology) and 14 indices. The results of the project show: (1) The ER is reduced from 58.02 to 28.8 after land consolidation and the degree of ecological risk is down from Degree III to Degree IV. (2) According to the element analysis, the water ER is reduced from 21.53 to 6.16, its contribution to reduce the ecological risk is 53%; the reduced ERs of soil and biology are respectively 12.79 and 1.06, their contribution of ecological risk reduce is lower than water.

Neural network has been popular in time series prediction in financial areas because of their advantages in handling nonlinear systems. This paper presents a study of using a novel recurrent neural network-echo state network (ESN) to predict the next closing price in stock markets. The Hurst exponent is applied to adaptively determine initial transient and choose sub-series with greatest predictability during training. The experiment results on nearly all stocks of S&P 500 demonstrate that ESN outperforms other conventional neural networks in most cases. Experiments also indicate that if we include principle component analysis (PCA) to filter noise in data pretreatment and choose appropriate parameters, we can effectively prevent coarse prediction performance. But in most cases PCA improves the prediction accuracy only a little.

The purpose of this paper is to develop a framework of ecological vulnerability assessment, and to assess the ecological vulnerability by this framework in the middle and lower reaches of the Hanjiang River Basin. Based on the theory of cause - and - consequence, we proposed an indicator system of ecological vulnerability assessment at basin scale. Twelve indicators are selected to constitute the proposed framework of ecological vulnerability assessment. Based on the Landsat TM images acquired in 2000 and technical support of ERDAS & GIS software, an empirical study was carried out. The results of study show that the general characteristics of ecological vulnerability in spatial differences in the Hanjiang River Basin are as follows: the expression of ecological vulnerability is the most vulnerable in the plain regions, the middle vulnerable in hilly regions, and the weakest vulnerable in mountainous regions.

With the project planning and design of land consolidation, an index system for the ecological risks assessment is set up based on the identification of the ecological risks with 14 indexes and three factors as water, soil and biology. The index standard is studied out, and the weighting allocation of the index system is workout by AHP. The integrated index of ecological evaluation (ER) is established. The results of the trial use of the suggested index system indicate that, (1) The ER is reduced 28.94 after land consolidation, and the ecological risk is down from level III to level IV; (2) By the element analysis, the water ER is reduced from 21.53 to 6.16, its contribution to the ecological risk is 53%; The ERs of soil and biology are respectively 12.97 and 0.79, their contribution of ecological risk are lower than water.

The measurement of device thermal resistance is a common approach to junction temperature determination given a set of environmental conditions and the device power dissipation. This paper introduces a novel instrument that can measure the thermal resistance of high brightness LED quickly using electrical test method (ETM). According to the international JEDEC standard, the instrument uses the LED itself as a temperature sensor. DAQ6221mx PCI data acquiring card was used to build the system and the related software is Labview. Various measurements are carried out by choosing different samples, and the result shows it takes about 10 seconds to get the thermal resistance of the LED under the condition the K factor is known