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Our incomplete understanding of osteoarthritis (OA) pathogenesis has significantly hindered the development of disease-modifying therapy. The functional relationship between subchondral bone (SB) and articular cartilage (AC) is unclear. Here, we found that the changes of SB architecture altered the distribution of mechanical stress on AC. Importantly, the latter is well aligned with the pattern of transforming growth factor beta (TGFβ) activity in AC, which is essential in the regulation of AC homeostasis. Specifically, TGFβ activity is concentrated in the areas of AC with high mechanical stress. A high level of TGFβ disrupts the cartilage homeostasis and impairs the metabolic activity of chondrocytes. Mechanical stress stimulates talin-centered cytoskeletal reorganization and the consequent increase of cell contractile forces and cell stiffness of chondrocytes, which triggers αV integrin–mediated TGFβ activation. Knockout of αV integrin in chondrocytes reversed the alteration of TGFβ activation and subsequent metabolic abnormalities in AC and attenuated cartilage degeneration in an OA mouse model. Thus, SB structure determines the patterns of mechanical stress and the configuration of TGFβ activation in AC, which subsequently regulates chondrocyte metabolism and AC homeostasis., The functional relationship between subchondral bone and articular cartilage is unclear. Here, the authors show that transforming growth factor-beta propagates the mechanical impact of subchondral bone on articular cartilage through αV integrin–talin mechanical transduction system in chondrocytes.

Although promising progress has been made in near-infrared (NIR) electron acceptors for broadening photoresponse of optoelectronics, there are still strong needs for efficient NIR materials with low synthetic complexities. In this work, three simple NIR acceptors are developed with absorption up to 1000 nm and possessing the same dithiophene cores with varied heteroatom linkages to carbon (C) atom for W1, to silicon (Si) for W2, and to nitrogen (N) for W3. It is found that the tuning of only one atom for simple acceptors can surprisingly lead to a large difference in photoelectric properties and solid stacking, as well as the performance in optoelectronics. Although quite simple, these electron acceptors, especially W1 (C), can also perform quite efficiently as organic photovoltaics (OPVs) as well as sensitive organic photodetectors (OPDs) when blended with PTB7-Th polymer. It is worthy to note that, among the representative NIR acceptors with over 950 nm absorption, W1 possesses one of the best figure-of-merit when considering the photoelectric performance versus synthetic complexity of materials. As a result, the PTB7-Th:W1-based OPDs reach a fast temporal response, ultralow-light intensity detection of 1.70 × 10-11 W·cm-2, and a high specific detectivity of 4.28 × 1012 cm·Hz1/2·W-1 at 830 nm, representing a highly sensitive self-powered OPD approach the commercial broadband silicon detectors. These simple structure materials provide a potential example for further application of NIR electron acceptor.

Inference of action potentials (‘spikes’) from neuronal calcium signals is complicated by the scarcity of simultaneous measurements of action potentials and calcium signals (‘ground truth’). In this study, we compiled a large, diverse ground truth database from publicly available and newly performed recordings in zebrafish and mice covering a broad range of calcium indicators, cell types and signal-to-noise ratios, comprising a total of more than 35 recording hours from 298 neurons. We developed an algorithm for spike inference (termed CASCADE) that is based on supervised deep networks, takes advantage of the ground truth database, infers absolute spike rates and outperforms existing model-based algorithms. To optimize performance for unseen imaging data, CASCADE retrains itself by resampling ground truth data to match the respective sampling rate and noise level; therefore, no parameters need to be adjusted by the user. In addition, we developed systematic performance assessments for unseen data, openly released a resource toolbox and provide a user-friendly cloud-based implementation. Rupprecht et al. compiled a large database of simultaneous electrophysiological and calcium recordings from the same neurons. An algorithm (termed CASCADE) trained with this ground truth enables reliable spike inference without the need to tune parameters.

Resilient suppliers can reduce supply chain risk, effectively avoid supply chain disruption, and bring profits to enterprises. However, there is no united measuring index system to evaluate the resilient supplier under supply chain environment, and the assessment language sets are usually crisp values. Therefore, in order to fill the research gap, this paper proposes a hybrid method, which combines triangular fuzzy number, the best-worst method (BWM), and the modular TOPSIS in random environments for group decision-making (GMo-RTOPSIS) to solve the above problem. Firstly, the weight of decision-maker is calculated by using fuzzy BWM which can deal with triangular fuzzy numbers. Secondly, triangular fuzzy number is introduced into GMo-RTOPSIS, and combined with fuzzy BWM, alternatives are sorted to select the best resilient supply chain partner. Finally, the feasibility and universality of this method are proved by illustrative examples.

Calcium imaging is a key method to record patterns of neuronal activity across populations of identified neurons. Inference of temporal patterns of action potentials (‘spikes’) from calcium signals is, however, challenging and often limited by the scarcity of ground truth data containing simultaneous measurements of action potentials and calcium signals. To overcome this problem, we compiled a large and diverse ground truth database from publicly available and newly performed recordings. This database covers various types of calcium indicators, cell types, and signal-to-noise ratios and comprises a total of >35 hours from 298 neurons. We then developed a novel algorithm for spike inference (CASCADE) that is based on supervised deep networks, takes advantage of the ground truth database, infers absolute spike rates, and outperforms existing model-based algorithms. To optimize performance for unseen imaging data, CASCADE retrains itself by resampling ground truth data to match the respective sampling rate and noise level. As a consequence, no parameters need to be adjusted by the user. To facilitate routine application of CASCADE we developed systematic performance assessments for unseen data, we openly release all resources, and we provide a user-friendly cloud-based implementation.

Progress in science requires standardized assays whose results can be readily shared, compared, and reproduced across laboratories. Reproducibility, however, has been a concern in neuroscience, particularly for measurements of mouse behavior. Here, we show that a standardized task to probe decision-making in mice produces reproducible results across multiple laboratories. We adopted a task for head-fixed mice that assays perceptual and value-based decision making, and we standardized training protocol and experimental hardware, software, and procedures. We trained 140 mice across seven laboratories in three countries, and we collected 5 million mouse choices into a publicly available database. Learning speed was variable across mice and laboratories, but once training was complete there were no significant differences in behavior across laboratories. Mice in different laboratories adopted similar reliance on visual stimuli, on past successes and failures, and on estimates of stimulus prior probability to guide their choices. These results reveal that a complex mouse behavior can be reproduced across multiple laboratories. They establish a standard for reproducible rodent behavior, and provide an unprecedented dataset and open-access tools to study decision-making in mice. More generally, they indicate a path toward achieving reproducibility in neuroscience through collaborative open-science approaches., eLife digest In science, it is of vital importance that multiple studies corroborate the same result. Researchers therefore need to know all the details of previous experiments in order to implement the procedures as exactly as possible. However, this is becoming a major problem in neuroscience, as animal studies of behavior have proven to be hard to reproduce, and most experiments are never replicated by other laboratories. Mice are increasingly being used to study the neural mechanisms of decision making, taking advantage of the genetic, imaging and physiological tools that are available for mouse brains. Yet, the lack of standardized behavioral assays is leading to inconsistent results between laboratories. This makes it challenging to carry out large-scale collaborations which have led to massive breakthroughs in other fields such as physics and genetics. To help make these studies more reproducible, the International Brain Laboratory (a collaborative research group) et al. developed a standardized approach for investigating decision making in mice that incorporates every step of the process; from the training protocol to the software used to analyze the data. In the experiment, mice were shown images with different contrast and had to indicate, using a steering wheel, whether it appeared on their right or left. The mice then received a drop of sugar water for every correction decision. When the image contrast was high, mice could rely on their vision. However, when the image contrast was very low or zero, they needed to consider the information of previous trials and choose the side that had recently appeared more frequently. This method was used to train 140 mice in seven laboratories from three different countries. The results showed that learning speed was different across mice and laboratories, but once training was complete the mice behaved consistently, relying on visual stimuli or experiences to guide their choices in a similar way. These results show that complex behaviors in mice can be reproduced across multiple laboratories, providing an unprecedented dataset and open-access tools for studying decision making. This work could serve as a foundation for other groups, paving the way to a more collaborative approach in the field of neuroscience that could help to tackle complex research challenges.

Phosphorene has attracted much attention recently as an alternative channel material in nanoscale electronic and optoelectronic devices due to its high carrier mobility and tunable direct bandgap. Compared with monolayer (ML) phosphorene, few-layer (FL) phosphorene is easier to prepare, is more stable in experiments, and is expected to form a smaller Schottky barrier height (SBH) at the phosphorene-metal interface. Using ab initio electronic structure calculations and quantum transport simulations, we perform a systematic study of the interfacial properties of three-layer (3L) phosphorene field effect transistors (FETs) contacted with several common metals (Al, Ag, Au, Cu, Ti, Cr, Ni, and Pd) for the first time. The SBHs obtained in the vertical direction from projecting the band structures of the 3L phosphorene-metal systems to the left bilayer (2L) phosphorenes are comparable with those obtained in the lateral direction from the quantum transport simulations for 2L phosphorene FETs. The quantum transport simulations for the 3L phosphorene FETs show that 3L phosphorene forms n-type Schottky contacts with electron SBHs of 0.16 and 0.28 eV in the lateral direction, when Ag and Cu are used as electrodes, respectively, and p-type Schottky contacts with hole SBHs of 0.05, 0.11, 0.20, 0.30, 0.30, and 0.31 eV in the lateral direction when Cr, Pd, Ni, Ti, Al, and Au are used as electrodes, respectively. The calculated polarity and SBHs of the 3L phosphorene FETs are generally in agreement with the available experiments.

Chondrosarcoma is the second most common primary bone sarcoma. Treatment of chondrosarcoma is limited to surgery due to radiation and chemotherapy resistance of this cancer. An ideal treatment for chondrosarcoma would be a well-tolerated, minimally invasive local or systemic treatment modality to halt or slow tumor growth prior to resection of local, unresectable local, or metastatic disease. Palovarotene, an agonist of nuclear retinoic acid receptor γ (RARγ) has shown therapeutic action for treatment of heterotopic ossification and osteochondroma without serious adverse effects in animal models. We hypothesized that selective agonists of RARγ would have an inhibitory effect on chondrosarcoma. All human chondrosarcoma specimens expressed RARγ as determined by immunohistochemical staining. The ΗCS-2/8 chondrosarcoma cell line, established from low-grade human chondrosarcoma, was used to examine the actions of RARγ agonists. In ΗCS2/8 pellet cultures, RARγ agonist treatment reduced the mass size and significantly decreased total glycosaminoglycan, protein amounts, and gene expression levels of cartilage matrix molecules when compared with control groups. Systemic treatment with RARγ agonists significantly inhibited the growth of ΗCS-2/8 cell transplants in vivo. Furthermore, local injection of RARγ agonist-loaded poly-lactic acid nanoparticles induced regression of the mass size of the transplants. Histologic analysis demonstrated that RARγ agonist treatment inhibited cell proliferation activity and stimulated encapsulation of the tumor. These findings indicate that RARγ agonists, including palovarotene, may have an anti-tumor effect on low-grade chondrosarcomas. © 2019 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 38:1045-1051, 2020.

Chinese Pharmacopoeia is updated every five years, of which traditional Chinese medicine (TCM) is the most important part. The 2015 version completed by the 10th Pharmacopoeia Commission has come into operation since December 1, 2015. Here we introduced the revision and improvement of quality evaluation and control standards of TCMs in Chinese Pharmacopoeia 2015.

For most uncooled infrared imager, there locates a baffle between the window of detector and the last lens of the optical system to block the internal stray radiation produced by lens cone and other structural parts. On the other hand, the baffle itself also brings another infrared radiation, and it has long been identified as a serious issue. Optimizing the surface shape of the baffle by modeling and calculating the distribution of stray energy on image plane is necessary to minimize the effects of the scattered radiation on the focal plane array (FPA). The Monte Carlo (MC) method has been verified to be an effective ray tracing technology in the computation of stray light, but for the baffle with complex heterotypic surface, the calculation by this way is very complicated and costs much time. Based on previous studies, this paper will present a MC method to trace the amount of rays radiated from the outer surface of detector, scattered by baffle and directly transmitted back to the FPA. Compared with the conventional MC rays tracing method, the way of spatial mesh discretization and gradual mesh reduction is proposed to replace the way of solving equations to search the intersection point between rays and complex surface on the baffle. As a result, it has higher computational efficiency and applicability to different shape of surfaces. Accordingly, it can be applied to the optimization calculation of baffle’s surface structure.

Acoustic emission (AE) technique is a common approach to identify the damage of the refractories; however, there is a complex problem since there are as many as fifteen involved parameters, which calls for effective data processing and classification algorithms to reduce the level of complexity. In this paper, experiments involving three-point bending tests of refractories were conducted and AE signals were collected. A new data processing method of merging the similar parameters in the description of the damage and reducing the dimension was developed. By means of the principle component analysis (PCA) for dimension reduction, the fifteen related parameters can be reduced to two parameters. The parameters were the linear combinations of the fifteen original parameters and taken as the indexes for damage classification. Based on the proposed approach, the Gaussian mixture model was integrated with the Bayesian information criterion to group the AE signals into two damage categories, which accounted for 99% of all damage. Electronic microscope scanning of the refractories verified the two types of damage.

Multi-layer Artificial Neural Networks (ANN) has caught widespread attention as a new method for time series forecasting due to the ability of approximating any nonlinear function. In this paper, a new local time series prediction model is established with the nearest neighbor domain theory, in which the hybrid Euclidean distance is used as the similarity measurement between two sets of time series. In order to improve the efficiency, prediction performance, as well as the ability of real-time updating of the model, in this paper, the recombination samples of the model is derived by Deep Extreme Learning Machine (DELM). The experiments show that local prediction model gets accurate results in one-step and multi-step forecasting, and the model has good generalization performance through the test on the five data sets selected from Time Series Database Library (TSDL).

This paper presents a novel method for fault diagnosis based on an improved adaptive resonance theory (ART) neural network and ensemble technique. The method consists of three stages. Firstly, the improved ART neural network is comprised of the soft competition technique based on fuzzy competitive learning (FCL) and ART based on Yu’s norm, the neural nodes in the competition layer are trained according to the degree of membership between the mode node and the input, and then fault samples are classified in turn. Secondly, with the distance evaluation technique, the optimal features are obtained from the statistical characteristics of original signals and wavelet coefficients. Finally, the optimal features are input into the neural network ensemble (NNE) based on voting method to identify the different fault categories. The proposed method is applied to the fault diagnosis of rolling element bearings, and testing results show that the neural network ensemble can reliably classify different fault categories and the degree of faults, which has a better classification performance compared with the single neural network.

This paper reported a low-temperature thin film encapsulation (TFE) process based on atomic layer deposition Al2O3 layer for top-emission organic light-emitting devices (TE-OLEDs). The barrier characteristics of both H2O-based and O3-based Al2O3 films were investigated. O3-based Al2O3 TFE showed lower water vapor transmission rate (WVTR) of 8.7 × 10−6 g/m2 day and longer continuous operation lifetime of 5 folds compared to the device with H2O-based Al2O3 TFE under identical environmental and driving conditions. Furthermore, the extraction of emitting light of the devices with barrier layer was enhanced compared to the bared one. The theory simulation data were consistent with our experimental results and showed the potential for the design of TFE structures optimized for enhancing light transmission.

Purpose: To investigate the effects of two types of anesthesia on postoperative recovery of patients with gastric cancer (GC), and to assess changes in the levels of their T lymphocyte subsets. Methods: Patients with GC (200 cases) were randomly assigned to two groups of 100 patients each: general anesthesia (GA) group and GA + epidural anesthesia (GAEP) group. Fasting venous blood samples (2 mL) were collected from the patients before anesthesia, and at different time-points: zero time (T0), 1 h (T1), day 1 (T2), and day 3 (T3) after surgery. CD3+, CD4+, CD8+T, and regulatory T cells (Tregs) were determined using a flow cytometer. Results: Percent CD3+, CD4+, CD8+T, and ratio of CD4+ to CD8+ in both groups at 1 h and day 1 after operation were significantly lower than their values before anesthesia ( p < 0.05). There were significant differences in CD3+ and CD4+ levels between the two groups on day 3 ( p < 0.05). Percent peripheral CD4+ CD25+T, and ratio of CD4+ CD25+ to CD4+ in both groups also significantly increased at 1 h and day 1 after operation, while percent peripheral CD4+, CD25+T and CD4+ CD25+ to CD4+ ratio in GAEP group on day 1 after operation were significantly lower than those of GA group ( p < 0.05). Conclusion: These results suggest that combination of general and epidural anesthesia partly controls the expressions of Tregs, thereby enhancing postoperative recovery of GC patients. Keywords: Gastric cancer, T-lymphocyte subsets, Regulatory T-lymphocytes, Epidural, Anesthesia

Aimed at the lack of methods to describe image semantics and map low level semantics to high level semantics, Hiberarchy Model of Image Semantic is designed to extract image features from inherent information and stratify image semantics according to abstract degree, and Ontology based Hiberarchy Model of Image Semantic is produced by applying Ontology with repository and rule base to figure the high level semantics obtained by HMIS, and then Description Logics System for Ontology based Hiberarchy Model of Image Semantic is put forward by taking description logics as illation to produce and manage image semantics, and finally the image semantics recognition system based on OHMIS and DLS-OHMIS is developed to recognize image by semantics.

We try to design the lattice with 2 super periods and 4-DBA structure in order to provide more drifts for the future development of the TTX source. Due to the space limitation in the lab, the 4-DBA lattice is suitable. In the paper, we present the lattice design with a 4-DBA structure mainly for the pulse mode of the compact laser-electron storage ring (LESR). Element parameters of the lattice are optimized with the help of the professional software and beam dynamics such as intra-beam scattering (IBS) and Compton scattering (CS) are calculated. Besides, the fringe field effect is analyzed with the numerical method.

The original version of this article unfortunately contained a mistake. The presentation of the title was incorrect. The corrected title is given below. Promotion of Chondrogenesis of Marrow Stromal Stem Cells by TGF-β3 Fusion Protein In Vivo

Modern information technology has become an indispensable tools for the knowledge work. The optimization and standardization of work process from the industrial era to the post-industrial society are realized by the major means of information technology. The rapid development of information technology provided an effective means for the knowledge work. However, the effects mechanism of different kinds of information technology on the knowledge work productivity has not been clear. From the literature review we found that, software system and networks, as the most frequently used information technology tools, have the different effects at the level of the individual end-user. The empirical study indicates that, software systems and network technology have become the essential aids for knowledge work. On the five dimensions of knowledge work productivity (efficiency, quality, innovation, customer satisfaction and collaboration), the impacts of software systems and network technology show the significant differences. In terms of efficiency and quality, the role of software is significantly better than network. While in the dimensions of customer satisfaction, innovation and collaboration, the role of the network is significantly better than software. This paper seeks the different “focal point” of software systems and networks on knowledge work productivity.

Three-level inverter brushless doubly-fed motor control system have obtained widespread concern because of its advantages such as high pressure, good reliability, high efficiency and low current harmonics. Aiming at three-level Neutral Point Clamped inverter Brushless Doubly-Fed Machine direct torque control system, a three-level fixed resultant vector BDFM Direct Torque Control method is proposed based on midpoint voltage hysteresis control. The stability and dynamic characteristics of the proposed control method were analyzed in MATLAB / SIMULINK. Finally, the system's hardware platform was built and the experimental results verify the feasibility and effectiveness of the proposed method.

SummaryNeuronal receptive fields (RFs) play crucial roles in visual processing. While the linear RFs of early neurons have been well studied, RFs of cortical complex cells are nonlinear and therefore difficult to characterize, especially in the context of natural stimuli. In this study, we used a nonlinear technique to compute the RFs of complex cells from their responses to natural images. We found that each RF is well described by a small number of subunits, which are oriented, localized, and bandpass. These subunits contribute to neuronal responses in a contrast-dependent, polarity-invariant manner, and they can largely predict the orientation and spatial frequency tuning of the cell. Although the RF structures measured with natural images were similar to those measured with random stimuli, natural images were more effective for driving complex cells, thus facilitating rapid identification of the subunits. The subunit RF model provides a useful basis for understanding cortical processing of natural stimuli.

It has been proposed that sensory neurons are adapted to the statistical structure of the natural environment in order to encode natural stimuli efficiently. While spatiotemporal correlations in luminance signals may be decorrelated by neurons in early visual processing stages, higher-order correlations, such as those in the orientation domain, are likely to persist in the input representation until the cortical level. In this study, we first examine orientation correlations in natural stimuli across brief time intervals and across nearby regions of space, and find strong correlations in both domains. We then examine contextual modulation of orientation tuning. We find that both temporal and spatial contexts exert a common influence on orientation tuning, shifting tuning away from the orientation of either the adapting (temporal) or surrounding (spatial) grating. Finally, we incorporate this context-mediated repulsive shift in orientation tuning into a model of cortical responses. We find that a direct result of the shift is a reduction of the redundancy in the population responses evoked by the orientation configurations that are most common in natural stimuli. Thus, cortical neurons may be adapted to the statistics of orientation in natural stimuli in order to increase the efficiency of natural stimulus representation.

Motion signals in the visual field can cause strong biases in the perceived positions of stationary objects. Local motion signal within an object induces a shift in the perceived object position in the direction of motion, whereas adaptation to motion stimuli causes a perceptual shift in the opposite direction. The neural mechanisms underlying these illusions are poorly understood. Here we report two novel receptive field (RF) properties in cat primary visual cortex that may account for these motion-position illusions. First, motion signal in a stationary test stimulus causes a displacement of the RF in the direction opposite to motion. Second, motion adaptation induces a shift of the RF in the direction of adaptation. Comparison with human psychophysical measurements under similar conditions indicates that these RF properties can primarily account for the motion-position illusions. Importantly, both RF properties indicate a spatial asymmetry in the synaptic connections from direction-selective cells, and this circuit feature can be predicted by spike-timing-dependent synaptic plasticity, a widespread phenomenon in the nervous system. Thus, motion-induced perceptual mislocalization may be mediated by asymmetric cortical circuits, as a natural consequence of experience-dependent synaptic modification during circuit development.

This work presents a new method of fabricating implantable multielectrode arrays on lightly doped single-crystal silicon. Such arrays are essential tools for electrical stimulation and recording of nerve signals. Our new microfabrication process, based on silicon-on-insulator (SOI) technology, inherently has excellent control over the final probe thickness without wet etching. The needle shanks are 6 mm long and 80 /spl mu/m wide. Here the thickness of the probe, 25 /spl mu/m, is defined by the device layer thickness on the SOI wafer. Our new sprinkler fluidic channel, which has holes spaced 50 /spl mu/m apart along its 6 mm length, permits the perfusion of a large area of tissue with any desired neurotransmitter or other drug. The probes fabricated here are tested in the cat primary visual cortex; data recorded from adjacent neurons was used to characterize their orientation tuning. The sprinkler channel was characterized, and flowrate through the channel is a linear function of the applied pressure.

This paper mainly analyzes the system level concept of public service productivity, as well as identified the potential issues affecting system level pension service productivity. This approach aims at optimizing the performance of the whole system and to avoid sub optimizing the production of individual services or organizations. First, a literature based definition of public service system productivity is produced. This definition is applied empirically in a case of a service system. Empirical data were collected at the civil affairs department and the external service provider organizations. The findings show that the effects influencing the system level productivity include awareness of the importance of the customer, System level objectives and clear network roles, cooperation and benefit segmentation of participants. In addition, the system level productivity concept is also a challenging phenomenon in practice. The practitioners representing different parts of the system could not easily see things the same way.

Namboodiri and Hussain Shuler (1) propose an alternative explanation for the timing-related firing rate modulation of medial prefrontal cortex (mPFC) neurons, suggesting that our finding can be simply explained by mPFC neuronal activity evoked by port exit (2). To illustrate their argument, the authors describe a thought experiment in which a flash of light is presented to the animal at the time of port exit. The authors predict that the visually evoked responses, when aligned to the sound onset and averaged across trials, will give rise to peri-event time histogram with an apparent scaling property because of the scaled variability of exit times across trials. This prediction is incorrect, as a crucial step was included in our analysis designed specifically to eliminate this confound. As described in the Materials and Methods of ref. 2, spike rate in each individual trial was temporally scaled to the mean exit time to remove variability introduced by the variation in the exit time (Fig. 1). Using this analysis, the peri-event time histogram obtained from the above thought experiment should not exhibit the scaling property as that shown in figure 3 of ref. 2, because the visually evoked activity (occurring after the exit) will fall outside of our analysis window. For the same reason, although some mPFC neurons do exhibit transient firing at port exit, our temporal scaling of individual trials before averaging means that these peaks fall outside of the analysis window, because most of the spike occurred after port exit. To further minimize the potential confound by the transient activity associated with port exit, the period of 100-ms before the port exit was also excluded from our analysis window (figure 3D of ref. 2). Together, these steps preclude the trivial explanation proposed by Namboodiri and Hussain Shuler (1).

A medical image segmentation based on global variables differential level set is proposed in this paper for medical images with complex topological structure, strong contrast and low noise characteristics. It make full use of the image area information, build a energy model, and using variation gradient information to establish a global energy model to get the minimization value, which is geodesic active contour (GAC) model. Experimental results show that the method set in the initial outline of the evolution without success to avoid the re-initialization and correction process, thus saving computing time. With traditional methods and TV and CV method, the method convergence stable segmentation accuracy is good, easy parameter adjustment and split speed, better medical treatment of low contrast, blurred image.

Ballistocardiogram signal monitoring system based on GSM network was put forward in this paper. The system included a BCG signal acquisition module, a data processing module, a display module and a GSM module. The STM32F103VB microprocessor was used as the controlling core of the signal acquisition module. BCG signal acquisition, amplification, filtering and A/D conversion were completed by the resistance strain sensor and high precision A/D conversion chip of TM7708; VB6.0 software was used to realize the BCG signal analysis and processing; the SD card and LCD completed data storage and waveform display; the BCG data remote transmission and alarm function were realized through the GSM module. The system can not only real-time monitor the changes of heart rate of patients by non-contact means, and can process data automatically, timely detection of arrhythmia and automatic alarm. The system is particularly suitable for heart patients receiving long-term home care; therefore, it has the broad application prospect.

A recent computational theory suggests that visual processing in the retina and the lateral geniculate nucleus (LGN) serves to recode information into an efficient form (Atick and Redlich, 1990). Information theoretic analysis showed that the representation of visual information at the level of the photoreceptors is inefficient, primarily attributable to a high degree of spatial and temporal correlation in natural scenes. It was predicted, therefore, that the retina and the LGN should recode this signal into a decorrelated form or, equivalently, into a signal with a “white” spatial and temporal power spectrum. In the present study, we tested directly the prediction that visual processing at the level of the LGN temporally whitens the natural visual input. We recorded the responses of individual neurons in the LGN of the cat to natural, time-varying images (movies) and, as a control, to white-noise stimuli. Although there is substantial temporal correlation in natural inputs (Dong and Atick, 1995b), we found that the power spectra of LGN responses were essentially white. Between 3 and 15 Hz, the power of the responses had an average variation of only ±10.3%. Thus, the signals that the LGN relays to visual cortex are temporarily decorrelated. Furthermore, the responses of X-cells to natural inputs can be well predicted from their responses to white-noise inputs. We therefore conclude that whitening of natural inputs can be explained largely by the linear filtering properties (Enroth-Cugell and Robson, 1966). Our results suggest that the early visual pathway is well adapted for efficient coding of information in the natural visual environment, in agreement with the prediction of the computational theory.

High follicule-stimulating hormone (FSH), luteinizing hormone (LH) and low estrogen levels that occurred in women in peri-menopausal stage (PMS, including those after ovariectomy and natural menopausal) usually induce a series of clinical symptoms, such as hot flush, sweatiness, insomnia and restlessness. It has been reported that patients without ovulation can be treated by acupuncture through regulating hypothalamic-pituitary-ovarian axis (H-P-O)(I~. Could acupuncture also regulate the H-P-O axis in patients with PMS? This study was designed to explore the effects of acupuncture on PMS through applying ear-acupressing (EAP) on women after ovariectomy. METHODS

Apparent motion quartet is an ambiguous stimulus that elicits bistable perception, with the perceived motion alternating between two orthogonal paths. In human psychophysical experiments, the probability of perceiving motion in each path is greatly enhanced by a brief exposure to real motion along that path. To examine the neural mechanism underlying this priming effect, we used voltage-sensitive dye (VSD) imaging to measure the spatiotemporal activity in the primary visual cortex (V1) of awake mice. We found that a brief real motion stimulus transiently biased the cortical response to subsequent apparent motion toward the spatiotemporal pattern representing the real motion. Furthermore, intracellular recording from V1 neurons in anesthetized mice showed a similar increase in subthreshold depolarization in the neurons representing the path of real motion. Such short-term plasticity in early visual circuits may contribute to the priming effect in bistable visual perception.

In recent years, dust explosion is occurred more and more in Chinese coal industry and the loss is enormous. However, to prevent coal dust explosion, coal dust explosion powerful and characteristics must be determined at first, but the studies has less about coal dust explosion. ZhunGeer coal washery was used for research establishment. Using numerical emulation technique, the coal dust particle movement law in the guide-chute was simulated. Gas-solid two-phase flow theory was used to analyze the experimental result. Combined with the actual test data, the coal dust concentration distribution in the guide-chute was gained. Adopting concentration analysis method, hazard of coal dust explosion in the guide-chute was analyzed. Conclusions are drawn that dust removal equipment in the coal washery is safe and reliable and the coal dust in the guide-chute does not have the risk of explosion. The conclusions provide useful theoretical and practical reference for coal dust explosion hazard analysis.

A consensus has been formed that information technology as an indispensable tool for enhancing the efficiency and quality of knowledge work. However, knowledge workers have their own utility evaluation for kinds of information technology as for the diversity of working properties and technical composition. By the empirical research on knowledge worker's usage of software systems and networks, this paper concluded that, a significant difference existed in the utility evaluation of information technology for different knowledge workers, and this difference is largely due to the different usage frequencies of information technology in the work process. The higher usage frequency of software systems and networks, the higher evaluation for them, and information technology is regarded as a "necessity" for knowledge work. While a lower usage frequency of software systems and networks, the evaluations for information technology are relatively conservative, and the role of information technology in support of their work is limited. The conclusion provides a reference for the focused investment, development and application of information technology for different work fields. Moreover, it also puts forward a perspective for the efficiency improvement of knowledge work.

The paper presents detailed modeling and simulation of cascaded H-bridge multilevel inverter with active front end (AFE). The purpose of the AFE is to balance the DC bus voltage and put the returning power back to the source instead of the breaking chopper and the capacitor. A simulation model has been built to demonstrate the inverter system and the simulation result validate the proposed control method.