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To observe the effects of acupoints, cone numbers and durations of moxibustion with different moxibustion methods on skin surface and inside temperature, and to provide references for the clinical standardization of moxibustion amount. The 42 big-ear white rabbits were divided into 6 groups according to the random number table method, a 1-cone direct moxibustion group, a 2-cone direct moxibustion group, a 3-cone direct moxibustion group, a 1-cone herbal cake-partitioned moxibustion group, a 2-cone herbal cake-partitioned moxibustion group, and a 3-cone herbal cake-partitioned moxibustion group, with 7 rabbits in each group. Shenque (CV 8), Shenshu (BL 23) and Zusanli (ST 36) were used in each group, but the moxibustion methods, cone numbers and durations of moxibustion were different. Rabbits in each group received moxibustion once every other day for 5 times in total. During the intervention, a thermoelectricity coupled probe and a temperature recorder were used to record the real-time acupoint skin temperature and the temperature at different time points, so as to observe, analyze and process the real-time changes in the temperature difference between the surface and inside of acupoint skin. For herbal cake-partitioned moxibustion, the best temperature for cone changing was (46.38±0.51) °C when the highest surface temperature was (49.20±0.52) °C; the multi-factor comparison of acupoint × cone number × time and acupoint × moxibustion method × time showed that time × acupoint, time × moxibustion method and cone number × acupoint had interactive effects (all P

Objective To observe the changes in hepatic histomorphology and the differences in the expression of PD-1 after different moxibustion interventions in the immunosuppressed rabbits caused by cyclophosphamide and analyze the intervention effects of different moxibustion therapies. Methods A total of 40 big-ear white rabbits were randomized into 4 groups, i.e. a blank group, an immunosuppressed model group, a moxibustion group and a herbal-paste isolated moxibustion group, 10 rabbits in each one. In the immunosuppressed model group, the moxibustion group and the herbal-paste isolated moxibustion group, the intraperitoneal injection with cyclophosphamide was administered consecutively for 7 days, 60 mg/kg, and then, the immunosuppressed models were prepared. After the models were established successfully, in the moxibustion group and the herbal-paste isolated moxibustion group, moxibustion was administer at “Shenque (神阙CV 8)” “Guānyuan (关元CV 4)” “Zusānlĭ (足三里ST 36)” “Pishū (脾俞BL20)” and “Shenshū (肾俞BL23)”, once every other day, 10 times in total. In the blank group and the immunosuppressed model group, the rabbits were restricted on the rabbit platform at the same time periods, without intervention. On the second day after the end of intervention, the animals were weighed and anesthetized, and the livers were extracted. After routine HE staining, the changes of hepatic histomorphology were observed under the microscope and the morphometric analysis was conducted in each group. Besides, PD-1 expression was observed with immunohistochemical method. Result Compared with the blank group, after modeling of each animal in three groups, the body mass decreased obviously (all P Conclusion The intervention with different moxibustion therapies improves the condition of body mass reduction and hepatic tissue damage of the immunosuppressed rabbits caused by cyclophosphamide. The effect of herbal-paste isolated moxibustion therapy is better than that of simple moxibustion therapy.

In the absence of GPS signals, Simultaneous Localization and Mapping (SLAM) technology enables unmanned systems to accomplish map construction and autonomous navigation in unknown environments. At present, there are mainly methods for SLAM based on sensors such as lidar, camera, ultrasonic, Inertial Measurement Unit (IMU) and odometer for location environment. However, there are certain limitations in using a single sensor for SLAM in unknown environment. In order to solve the above problems, this paper summarizes the key problems faced by mainstream SLAM at present, and proposes a SLAM method based on multi-sensor fusion, which can make full use of the advantages of various sensors from the hardware structure and make up for the shortcomings of using a single sensor. Finally, the proposed method was verified on the platform of “JAC Electric Vehicle”, and the experimental results show that the proposed method can effectively avoid the influence caused by signal weakening, improve the positioning accuracy, and the system has stronger robustness and better tracking performance.

We propose an improved analysis algorithm based on learning and searching methods in the field of Big Data to optimize TCM information management. We use TF-IDF theory in document clustering to cluster the name of Chinese Medical prescripts, construct word bag model, and combine universal hash with perfect hash, in order to establish a special key-value hashing band between Chinese Medical Data and diseases.

The space membrane structure has good application prospects in large spacecraft membrane antenna, solar sail and baffle because it has the advantages of low quality and small folding volume. The modal characteristics of membrane structure directly decide or to a large extent affect the surface accuracy maintenance and vibration control of the structure. The correctness of modal analysis needs to be verified by ground tests. Because the membrane structure is light and flexible, air has an important influence on its modal analysis results, so it is very necessary to carry out modal tests in vacuum environment. In this paper, taking the planar membrane structure as a research object, a set of modal testing system is designed and built, which is suitable for vacuum environment. The modal test under various working conditions is completed, and the effective test data are obtained. Through data processing and comparative analysis in this paper, not only the modal characteristics analysis of planar membrane structure is completed, but also the specific influence of air on the modal test results is summarized. This testing research lays a solid technical foundation for the modal characteristics investigation and design improvement of space membrane structure, which is of great engineering significance.

A new fabric defect detection algorithm base on Gabor filters is proposed. The spectral characteristics of both fabric texture and defects are analyzed. Gabor wavelet which can be considered as a bank of Gabor filters are used for the decomposition of fabric image. Based on spectral characteristics of fabric texture and defects, a new tuning method of Gabor wavelet is proposed to enhance the energy of defective region and attenuate the energy of normal texture. Decomposition images from different scales and orientations are fused into a single one to emphasize the presence of different kinds of defects. For comparison, the performance of proposed method as well as other two other defect detection methods using Gabor filters is evaluated with typical fabric defect samples. The experiment results obtained indicate that the proposed method is more effective than the other two.

With the intelligent development of automobile driving, automatic parking technology is widely concerned by relevant technicians at home and abroad. Automatic parking technology is a method that can realize automatic parking in and out of parking Spaces without manual intervention. At present, automatic parking system has been equipped and used in many models, but there are many problems such as low parking accuracy and unable to effectively identify irregular parking Spaces. In order to solve the above problems, this article is based on a cloud platform developed a driverless car parking method, through the cloud server, GPS (Global Positioning System) and inertial navigation. It can according to the parking information and real-time Positioning planning adjustment path of the vehicle, and controls the complete vehicle posture adjustment, so as to improve the accuracy of parking and parking intelligent identification accuracy and ensure the safety and efficiency in the process of path planning. The effectiveness of the method is verified by simulation experiments with MATLAB software, which can be demonstrated by data.

As online platforms are striving to get more users, a critical challenge is user churn, which is especially concerning for new users. In this paper, by taking the anonymous large-scale real-world data from Snapchat as an example, we develop \textit{ClusChurn}, a systematic two-step framework for interpretable new user clustering and churn prediction, based on the intuition that proper user clustering can help understand and predict user churn. Therefore, \textit{ClusChurn} firstly groups new users into interpretable typical clusters, based on their activities on the platform and ego-network structures. Then we design a novel deep learning pipeline based on LSTM and attention to accurately predict user churn with very limited initial behavior data, by leveraging the correlations among users' multi-dimensional activities and the underlying user types. \textit{ClusChurn} is also able to predict user types, which enables rapid reactions to different types of user churn. Extensive data analysis and experiments show that \textit{ClusChurn} provides valuable insight into user behaviors, and achieves state-of-the-art churn prediction performance. The whole framework is deployed as a data analysis pipeline, delivering real-time data analysis and prediction results to multiple relevant teams for business intelligence uses. It is also general enough to be readily adopted by any online systems with user behavior data., Published at KDD 2018

Simulation capacity is essential to the engineering design of industrial products with complex functions. This paper discusses a numerical algorithm to simulate the multiscale heat and moisture transfer in the thermal smart clothing system. A group of multiscale nonlinear models are proposed to describe the mix-type coupled heat and moisture transfer in the human body, fabrics, fiber material, and phase change material (PCM) particles. The dynamic thermal boundary conditions among individuals are considered and described to integrate the multiscale models. The coupled partial differential equations of the models are discretized by the finite volume method, and the numerical scheme for the thermal smart clothing simulation are developed considering the specification of wearing scenarios. To validate the models and simulation scheme, the simulation results and experimental results with the same clothing and wearing conditions are compared and discussed. Furthermore, a series of simulation cases are made to present the application of this numerical algorithm in practical design by expressing a sequence of design issues through the simulation results for the designers. This simulation scheme is helpful in the engineering design process of thermal smart clothing to identify the thermal quality of the clothing in advance and thus reduce the design cost.

In this paper, we propose a new fast normal-based interpolating subdivision scheme for curve and surface design. Different from the 4-points interpolating subdivision scheme, it is based on cubic Bezier curves and the normal vectors are used to generate a circle. Both a convex edge and an inflexion edge can be subdivided into convex sub-edges and then generate smooth curves. Under proper angle conditions, this subdivision scheme converges and the limit curve will be $$\hbox {G}^{1}$$G1 smoothness. When applying it to subdivide surface on triangle/quadrilateral meshes, we use the normal vectors and have no need to consider the meshes neighboring to the current surface elements. Such advantage leads to that the subdivision scheme has fast rendering speed without changing the topology of the meshes. Subdivision examples and results by our scheme are illustrated and meantime is compared with those generated by other well-known schemes. It shows that this scheme can generate a more smooth curve based on both a convex edge and an inflexion edge, and the limit surface has better smoothness than those of other interpolating schemes.

The aim of this study is to study the clinical, laboratory, imaging pathology, and prognosis features of IgG4-related spinal pachymeningitis. We worked with a 55-year-old man suffering from IgG4-related spinal pachymeningitis who had the most widespread lesion in his dura mater. We also review previous related studies and discuss the clinical characteristics of this rare disease. In total, eight IgG4-related spinal pachymeningitis patients have been reported in the literature since 2009. They were mostly male patients, 51.7 ± 11.9 years old on average. Cervical and thoracic vertebrae were the most common sites for lesions. The most prominent symptom was varying numbness and weakness of the limbs and/or body associated with spinal cord compression. There was one patient (1/5) with elevated serum IgG4 levels and three patients (3/3) with increased cerebrospinal fluid (CSF) IgG4 index. Positive histopathologic findings are the strongest basis for a diagnosis. All the patients with IgG4-related spinal pachymeningitis responded well to glucocorticoid therapy. IgG4-related spinal pachymeningitis is an orphan disease that mainly occurs in cervical and thoracic vertebrae. Older males are the most susceptible group. Serum IgG4 levels were consistently normal in these cases, so analysis of CSF for IgG4 production (IgG4 index) could become a useful tool. Pathological findings remain the gold standard for diagnosis. Most patients responded favorably to glucocorticoid treatment.

In this article, a dual-band narrow bandpass filter using U-shaped stepped-impedance resonator (SIR) for 2.4/5.2 GHz wireless local area network (WLAN) application is proposed. The filter is composed of a simple U-shaped SIR and novel feedlines with two open stubs. Furthermore, this article relatively used the first and second resonances to achieve the dual-band performance. To validate the design and analysis, a prototype filter has been fabricated with two passbands are centered at 2.4 and 5.2 GHz with the fractional bandwidth of 4.9 and 3.5%, respectively. Its excellent selectivity is suitable for WLAN application. The measurement performances show good agreements with the simulated ones. © 2015 Wiley Periodicals, Inc. Microwave Opt Technol Lett 57:1143–1146, 2015

This study evaluated the correlation of UGT1A1, OATP2 gene mutations and hyperbilirubinemia in newborns in Northern China. Gene mutations were analyzed at the 211 locus of UGT1A1 (Gly71Arg) and 388 locus of OATP2 (Asn130Asp). The 226 enrolled infants were divided into high, moderate, and low risk subgroups according to American Academy of Pediatrics guideline. Blood samples of the enrolled infants were collected for the analysis of the PCR-restriction fragment length polymorphism. The genotypes and allele frequencies of the polymorphisms were compared in each group. Both UGT1A1 and OATP2 gene mutations occur more often in high risk group and moderate risk group than in low risk group. The results suggested that Gly71Arg and Asn130Asp mutations in UGT1A1 and OATP2 genes might be involved in the development of hyperbilirubinemia in neonates.

Making friend recommendations is an important task for social networks, as having more friends typically leads to a better user experience. Most current friend recommendations systems grow the existing network at the cost of privacy. In particular, any given user's friend graph may be directly or indirectly leaked as a result of such recommendations. In many situations this is not desirable, as the friend list may reveal much about the user--from their identity to their sexual orientation and interests. In this work, we focus on the "cold start" problem of making friend recommendations for new users while raising the bar on protecting the privacy of the friend list of all users. We propose a practical friend recommendation framework, tested on the Snapchat social network, that preserves the privacy of users' friends lists with respect to brute-force attacks and scales to millions of users.

Ischemia reperfusion injury (IRI) is critical in the pathogenesis of acute renal failure and graft rejection. Regulatory T cells (Tregs) suppress excessive immune responses in IRI. We investigated the role of CD4(+)CD25(high)CD127(low) Tregs in the early phase of renal IRI pathogenesis in a mouse model. CD4(+)CD25(high)CD127(low) Tregs in the kidney, tubular necrosis scores, and renal function were measured 24 or 72 h after reperfusion. PC61, an anti-CD25 monoclonal antibody, was used to deplete Tregs before renal ischemia to confirm the effect of these Tregs. CD4(+)CD25(high)CD127(low) Tregs were expanded 24 and 72 h after reperfusion. Depletion of CD4(+)CD25(high)CD127(low) Tregs was associated with worsening of renal function and histology, particularly at 72 h after reperfusion. These results indicated that expansion of CD4(+)CD25(high)CD127(low) Tregs in the early phase of renal IRI may participate in tissue repair. These data reveal new insights into the pathogenesis of ischemic acute renal failure and a novel therapeutic approach.

The thermal dissipation of radiation is main heat shield mechanism for non-ablative thermal protection materials on hypersonic vehicles withstanding high temperature dynamic heating cycle during endo-atmospheric ascent, cruise and reentry. Therefore, it is necessary to know the thermal radiative properties of the material under the simulated high temperature dynamic heating conditions on the ground. The emissivity depends on the surface state and its temperature. A new simultaneous measurement technology of emissivity and varying surface temperature is proposed under high temperature dynamic heating conditions. This new technology solved synchronous measurement problems by utilizing spectral signal of Fourier transform infrared (FTIR) spectroscopy. The calibration of different temperature ranges, the background disturbances, the influences on temperature measurement by wavelength range and its corresponding fluctuations of measurement signal, were thoroughly investigated. The measured results of steel and graphite as reference materials proved the effectiveness of this simultaneous measurement technology and showed great potential in engineering applications under high temperature dynamic heating conditions.

Independent renewable energy power stations based only on wind or solar power system cannot provide continuous electricity. Wind/solar hybrid power systems can offer a possible solution to this problem. However, there is much more influencing factors in the progress of site selection as the site selection of hybrid power systems is much more complex than of independent ones. To resolve this problem, we use literature statistics to determine the index of site selection scientifically. Therefore, the Matter-Element Extension method and its improved version (Ideal Matter-Element Extension method) are applied to evaluate hybrid renewable sites. We chose three regions with abundant wind and solar energy in China as case studies for these models and obtain the weights of the index by Rank Correlation Analysis. The no difference results of the two models and the installed capacity of these places will prove its effectiveness meanwhile the improved Ideal Matter-Element Model can rank order all evaluation objects. So, this paper will provide a theoretical basis to selection of the sites of wind/solar hybrid power stations.

Users on social networks primarily do two things, connect to existing or new friends and exchange information. Recently, social media apps have become the primary information source for users to consume news stories. Users are inundated with a flood of information from social media networks shared by their friends and other content providers. For social media networks, it is important for us to study users' friendships and interests in order to best serve their need. However, given the nature of online applications, information on both sides is highly incomplete and noisy. Inspired by the well-known homophily phenomenon which found the two properties strongly interleaving, we propose to jointly learn them by leveraging their data redundancy and mutual reinforcement. Specifically, we exploit homophily by iteratively addressing smoothness on the graph in two directions, ie, from closeness to similarity (stronger links lead to more similar attributes), and vice versa. The two processes are done in a unified probabilistic framework through label propagation and graph construction. The refined user links and attributes are immediately useful for various tasks including link recommendation and content targeting on social networks.

Crowdsourcing services make it possible to collect huge amount of annotations from less trained crowd workers in an inexpensive and efficient manner. However, unlike making binary or pairwise judgements, labeling complex structures such as ranked lists by crowd workers is subject to large variance and low efficiency, mainly due to the huge labeling space and the annotators' non-expert nature. Yet ranked lists offer the most informative knowledge for training and testing in various data mining and information retrieval tasks such as learning to rank. In this paper, we propose a novel generative model called "Thurstonian Pairwise Preference" (TPP) to infer the true ranked list out of a collection of crowdsourced pairwise annotations. The key challenges that TPP addresses are to resolve the inevitable incompleteness and inconsistency of judgements, as well as to model variable query difficulty and different labeling quality resulting from workers' domain expertise and truthfulness. Experimental results on both synthetic and real-world datasets demonstrate that TPP can effectively bind pairwise preferences of the crowd into rankings and substantially outperforms previously published methods.

Study the optical fiber's UV transmission performance,utilize the depressed inner clad design,with different doping content of Ge and F in fiber's core,use the Plasma Chemical Vapor Deposition process to develop the sample fiber,and adopt the same drawing process control to fabricate the fiber sample.Through contrast the samples' optical characters,attenuation sprctrum and UV transmission efficiency and stability,get the influence of the fiber's UV transmission performance by the doping content.With the increase of the Ge and F doping content the fiber's 305 nm laser transmission efficiency would decrease obviously.The UV laser transmission efficiency changed from 99.3%~97.8%.This would be caused by the increase of the defects content in the fiber's core,and then it would decrease the UV laser transmission efficiency.However,with the increase of the Ge doping content,the fiber's UV transmission stability would increase from 904%~97.2%.The results indicate that:the fiber's UV transmission efficiency was directly influenced by the Ge doping process,then the transmission stability was influenced by the other doping element,the new defects have been generated.

Entities (e.g., person, movie or place) play an important role in real-world applications and learning entity types has attracted much attention in recent years. Most conventional automatic techniques use large corpora, such as news articles, to learn types of entities. However, such text corpora focus on general knowledge about entities in an objective way. Hence, it is difficult to satisfy those users with specific and personalized needs for an entity. Recent years have witnessed an explosive expansion in the mining of search query logs, which contain billions of entities. The word patterns and click-throughs in search logs are not found in text corpora, thus providing a complemental source for discovering entity types based on user behaviors. In this paper, we study the problem of learning entity types from search query logs and address the following challenges: (1) queries are short texts, and information related to entities is usually very sparse; (2) large amounts of irrelevant information exists in search logs, bringing noise in detecting entity types. In this paper, we first model query logs using a bipartite graph with entities and their auxiliary information, such as contextual words and clicked URLs. Then we propose a graph-based framework called ELP (Ensemble framework based on Lable Propagation) to simultaneously learn the types of both entities and auxiliary signals. In ELP, two separate strategies are designed to fix the problems of sparsity and noise in query logs. Extensive empirical studies are conducted on real search logs to evaluate the effectiveness of the proposed ELP framework.

As a challenging task for bioluminescent tomography simulation, a virtual optical environment is needed to solve the forward problem accurately, that is, to achieve a high precision for bioluminescent signal synthesis on the external body surface of a small animal. The molecular optical simulation environment named MOSE is implemented using the C + + programming language and the OpenGL techniques, including a user-friendly interface with interactive tools facilitating users' operations. The accuracy of the virtual optical environment is verified by error analysis of mesh simplification and comparison between MOSE results and experimental data. This virtual optical environment is accurate, flexible and efficient to simulate the photon propagation in complicated tissues, which has a great potential to become a software platform for bioluminescent tomography studies and other molecular imaging applications.

Objective: To explore changes of neural stem cells (NSCs) following intracerebral hemorrhage (ICH) and the effect of Nao Yi-an granule (NYA) on them, and furthermore, to explore NYA’s therapeutic mechanismMethods: Sixty rats were randomly divided into three groups, the sham operation control group, the ICH group and the NYA-treated group. Except those in the sham operation control group, all other rats were replicated to ICH models by stereotactical injection of collagenase type VU into their globus pallidus. After modeling, the rats in the NYA-treated group were administered with NYA at the dosage of 4.92 g·kg-1·d-1 by gastrogavage, while those in the other two groups, 4 ml distilled water were given instead. The behavioral test was used to evaluate neurological deficit and immunohistochemical method was used to detect Nestin expression, the special marker for neural stem cells.Results: The ICH animals showed notable placing deficit in forlimbs from day 1 to day 28 after modeling. The deficit in the NYA-treated group was similar to that of the ICH group, but the former got recovered better than the latter from day 21 to 28, with significant difference shown (P

Objective: To observe and compare the effect of traditional Chinese medicine (TCM) combined with chemotherapy (CT) on immune function and quality of life (QOL)of patients with non-small cell lung cancer (NSCLC) in stage III-IV.Methods: One hundred cases with stage III-IV NSCLC were randomly divided into two groups. The treated group (n = 50) received CT combined with TCM, and the control group received CT alone. The percentage of T lymphocyte subset in peripheral blood and the change of natural killer (NK) cell count were observed after treatment. The QOL and tolerance of CT were also compared between the two groups after treatment. Results: In the treated group, CD3 cell count, CD4 cell count, CD4/ CD8 ratio and NK cell activity were higher than those in control group, while CD8 cell count in the treated group was lower than that in the control group (P

In this paper, a hybrid sensor was fabricated using a IR-femtosecond laser to measure the thermal expansion and thermo-optical coefficient of silica-based fiber Bragg gratings (FBGs). The hybrid sensor was composed of an inline fiber Fabry-Perot interferometer (FFPI) cavity and a type-II FBG. Experiment results showed that the type-II FBG had three high reflectivity resonances in the wavelength ranging from 1100 to 1600 nm, showing the peaks in 1.1, 1.3 and 1.5 μm, respectively. The thermal expansion and thermo-optical coefficient (1.3 μm, 1.5 μm) of silica-based FBG, under temperatures ranging from 30 to 1100 °C, had been simultaneously calculated by measuring the wavelength of the type-II FBG and FFPI cavity length.

When hypersonic vehicle flies in the atmosphere at a high altitude with a high speed, plasma sheath is generated around the vehicle, and thus attenuating the electromagnetic wave signals and even interrupting the communication. Therefore the control, guidance, and navigation of hypersonic vehicle can be affected seriously by the plasma sheath. It is necessary to study this problem in reasonable ground experiment. The inductively coupled plasma (ICP) wind tunnel is an ideal equipment for studying electromagnetic transmission characteristics in plasma because it can produce uncontaminated plasma and the electrode cannot be ablated in the process of plasma production. We carry out the experiment in ICP wind tunnel. A thin slice of plasma jet is generated by a rectangular nozzle with an outlet size of m 50 mm250 mm. Plasma jets with different parameters are obtained by adjusting the operating power and inlet flow of the wind tunnel. Four kinds of states are provided with the electron densities of 7.01010, 5.01011, 3.51012 and 1.01013/cm3, and the collision frequencies of 1.5109, 1.6109, 2.0109 and 9.0109 Hz, respectively. The amplitude attenuations and phase changes of the electromagnetic waves are measured with microwave diagnostics system consisting of a vector network analyzer and high gain antennas. And electron density and collision frequency of plasma are obtained according to the transmission characteristics of electromagnetic waves in plasma. The attenuations of the electromagnetic wave in plasmas of different states are measured via microwave transmission system which is composed of a vector network analyzer and pairs of horn antennas covering a frequency range of 2.6-40 GHz. The results show that both the amplitude attenuation and attenuation band increase with the increase of electron density. The classical theory and thin layer theory are used to simulate the transmission attenuation. The results are compared with the experimental ones. The results in this paper provide basic data for further theoretical and numerical study of electromagnetic wave transmission characteristics in plasma.

To achieve more realistic surface design, this paper proposes a new scheme of interpolation subdivision surface, which is extended from interpolation subdivision of Bezier curve. Different from the previous interpolation subdivision schemes, the normal vectors are used to generate a circle from a triangle which results in only 3 vertices and 3 edges. This improvement not only makes a curve smooth, but also can produce sharp angles during subdivision. Furthermore, we make new contributions in the subdivision surface scheme compared to the existing methods. The proposed scheme in this paper avoids solving a large system of linear equations, which can greatly reduce the cost of calculation. Due to the usage of the normal vectors, there is also no need to consider the meshes adjacent to the target. Since it has no change on the topology of the mesh and no update of the vertices, this scheme can also be realized in parallel and thus achieve fast implementation. Finally, examples of subdivision surface by this scheme are illustrated, and the comparison with the results by existing method is also discussed to show the advantages of this scheme.

Domain words clustering have important theoretical and practical significance in text categorization, the ontology research, machine learning and many other research areas. The domain words clustering method in this article is a method based on word2vec and semantic similarity computation. First of all, we get the candidate word set with word2vec tools to preliminary clustering of words. Then we tectonic domain category semantic core word set and screening candidate word set by means of semantic similarity computation. Finally we get new word set belongs to the target domain and get the word set in the field of clustering. Experiments show that this method has higher recall ratio and accuracy.

Objective: To investigate the curative effect of auricular-plaster therapy on heroin addiction.Methods: Sixty cases of heroin addiction were treated by auricular-plaster therapy in cooperation with methadone and another 60 cases with methadone as a control. The treatment lasted 10 days.Results and conclusion: The results showed that the curative effect of auricular-plaster therapy plus methadone on heroin addiction was significantly better than that of methadone in the control group (P

Different from the 4-points interpolation subdivision curve scheme, the proposed subdivision curve scheme in this paper is based on cube Bezier curve. More importantly, the normal vectors are used to generate a circle from a triangle with the advantages of only 3 vertices and 3 edges. Furthermore, we make new contributions in the subdivision surface scheme compared to the existing methods. It has excellent smoothness and also can be fast implemented.

We report enhanced upconversion (UC) fluorescence in Tm3+ doped tellurite microstructured fibers (TDTMFs) fabricated by using a rod-in-tube method. Under the pumping of a 1560 nm femtosecond fiber laser, ultrabroadband supercontinuum light expanding from ∼1050 to ∼2700 nm was generated in a 4 cm long TDTMF. Simultaneously, intense 800 nm UC emission from the 3H4 → 3H6 transition of Tm3+ was observed in the same TDTMF. Compared to that pumped by a 1560 nm continuous wave fiber laser, the UC emission intensity was enhanced by ∼4.1 times. The enhancement was due to the spectral broadening in the TDTMF under the pumping of the 1560 nm femtosecond fiber laser.

This paper presents an alternative method, which is economical and easy-to-operate, to visualize the 3D skin temperature distribution of the body based on the data of skin temperature of available body points. The interpolation and mapping functions is presented in detail, and the visualization cases based on the data of skin temperature measured in previous researches are demonstrated. It enables the user to have more direct and effective observation of the skin temperature of the body without infrared photography.

The FlexRay bus is a promising automotive standard communication system with high-speed, high-bandwidth and high robustness. In this paper, based on Flexray Version 3.0.1, it is allowed to put the signals from different nodes to a slot. Because the static segment of FlexRay is based on Time Division Multiple Access (TDMA) in the static segment, the real-timing scheduling of static segment is critical for an efficient system. To save more slots for the potential addition of tasks and improve the network utilization is significant to the further development of the vehicle area. Therefore, combination bin-packing algorithm is employed to merge those messages in the slots which are not fully used, despite that those messages come from different nodes, which is to improve the bandwidth utilization and minimize the number of used-slots and balance the every slot occupied rate. Finally, with the repeat rate unlimited to 2n, through comparing the experimental results of before and after combination of simulated static scheduling and the results do decrease the number of used slot and balance occupied rate. The solution of combining the tasks before sending to the network and segmenting them after receiving from the network will be a feasible method to the constrained network.

The vast majority of transfer learning methods proposed in the visual recognition domain over the last years ad- dresses the problem of object category detection, assuming a strong control over the priors from which transfer is done. This is a strict condition, as it concretely limits the use of this type of approach in several settings: for instance, it does not allow in general to use off-the-shelf models as priors. Moreover, the lack of a multiclass formulation for most of the existing transfer learning algorithms prevents using them for object categorization problems, where their use might be beneficial, especially when the number of categories grows and it becomes harder to get enough annotated data for training standard learning methods. This paper presents a multiclass transfer learning algorithm that allows to take advantage of priors built over different features and with different learning methods than the one used for learning the new task. We use the priors as experts, and transfer their outputs to the new incoming samples as additional information. We cast the learning problem within the Multi Kernel Learning framework. The resulting formulation solves efficiently a joint optimization problem that determines from where and how much to trans- fer, with a principled multiclass formulation. Extensive experiments illustrate the value of this approach.

We propose an online learning algorithm to tackle the problem of learning under limited computational resources in a teacher-student scenario, over multiple visual cues. For each separate cue, we train an online learning algorithm that sacrifices performance in favor of bounded memory growth and fast update of the solution. We then recover back performance by using multiple cues in the online setting. To this end, we use a two-layers structure. In the first layer, we use a budget online learning algorithm for each single cue. Thus, each classifier provides confidence interpretations for target categories. On top of these classifiers, a linear online learning algorithm is added to learn the combination of these cues. As in standard online learning setups, the learning takes place in rounds. On each round, a new hypothesis is estimated as a function of the previous one. We test our algorithm on two student-teacher experimental scenarios and in both cases results show that the algorithm learns the new concepts in real time and generalizes well.

This paper describes a novel offering of a US- based course in Computer Science at a Chinese university. A senior-level Algorithms course from the University of Washington was offered at Beihang University in Beijing, China through Tutored Video Instruction, whereby lectures recorded in class at the University of Washington were subsequently shown at Beihang and facilitated by local teaching assistants. In this mode of instruction, the Chinese teaching assistants conducted interactive classes using both the video materials and a classroom interaction system (Classroom Presenter) for electronically supported student activities. These activities were done using a system of networked Tablet PCs, which allowed the students to electronically submit their work to the instructor, and enabled the instructor to display student submissions as well as ink on the lecture slides. This work has two main contributions: it demonstrates that Tutored Video Instruction coupled with classroom interaction technology is a viable strategy for offering asynchronous distance versions of courses while maintaining the interactivity of classroom environments. It also shows how language and cultural barriers can be overcome by combining recorded materials with facilitated delivery.

In this paper, the principle of PCVD process was introduced briefly. The material composition and structure design combining with waveguide design of PCVD preform were analyzed. Besides, the application, key features and advantages of some specialty fibers fabricated by PCVD process were introduced.

The effects of back gate bias (BGEs) on radio-frequency (RF) performances in PD SOI nMOSFETs are presented in this paper. Floating body (FB) device, T-gate body-contact (TB) device, and tunnel diode body-contact (TDBC) device, of which the supply voltages are all 1.2 V, are compared under different back gate biases by different figures of merit, such as cut-off frequency (fT), maximum frequency of oscillation (fmax), etc. Because of the lack of a back gate conducting channel, the drain conductance (gd) of TDBC transistor shows a smaller degradation than those of the others, and the trans-conductance (gm) of TDBC is almost independent of back gate bias. The values of fT of TDBC are also kept nearly constant under different back gate biases. However, RF performances of FB and TB each show a significant degradation when the back gate bias is larger than ~20 V. The results indicate that TDBC structures could effectively improve the back gate bias in RF performance.

In this paper, the DGD (Differential Group Delay) method for beat length measurement of PANDA polarization maintaining (PM) fibers is theoretically analyzed in detailed. And the analysis indicates, regarding the series of silica optical fibers, the error of beat length at different testing wavelength can be ensured less than 2% based on present fiber designs and germanium-doped concentration level. Presently the PMD400 (Polarization Mode Dispersion) analyzer is applied to measure the beat length of polarization maintaining fibers at Yangtze Optical Fiber and Cable Company. Lots of test results shows the DGD method is very reliable, convenient and nondestructive. In practical, the relative deviation of beat length at different wavelength can be kept under 1.5% below based on a number of experimental data. Therefore, the DGD of a PM fiber can be tested at a definite wavelength, such as 1550nm, and then the beat lengths at other operating wavelength can be got according to the relationship between beat length and operating wavelength.

The performance dependence of 10 Gbit/s single channel transmission system on the optimal residual dispersion and the fiber input optical power is simulated and compared with 400-km SMF and various kinds of NZ-DSFs. We have shown that optimal residual dispersion depends on the type of the optical fiber and optical power launched into it. The optimal residual dispersion region for 10 Gbit/s DWDM system with SMF and NZ-DSFs is deduced at last.

The relation between the dispersion characteristics of W-profile broadband dispersion compensation fiber and its structural parameters is simulated using the finite element method in this paper. It is found that it is the depressed cladding that makes dispersion slope negative and increasing the waveguide dispersion to the total dispersion. There exists an optimum depressed cladding width, which gives the highest negative dispersion or maximum relative dispersion slope. Any modifications of the structural parameters, which make fiber operating close to cutoff, will result in large negative dispersion, high negative dispersion slope and high relative dispersion slope.

We investigate on a multi-wavelength operation erbium-doped fiber laser Q-switched by a graphene-based saturable absorber. Stable pulses were generated with the widths from 6.9 to 1.5 μs, energies from 40.4 to 130.2 nJ and repetition rates from 68.32 to 132.9 kHz, when the pump power increased from 142.32 to 441.86 mW. A fiber Bragg grating with five reflective peaks was inserted into the fiber ring through an optical circulator, resulting in a stable output of five- lasing-wavelength output. The laser can perform as a low-cost and easy-built all fiber light source, and has potential applications in the fields where pulses at multi-wavelength operation are needed, i.e., temperature or strain fiber sensors. © 2012 Society of Photo-Optical Instrumentation Engineers