Controlled synthesis of nanoporous Au microsheet via surfactant emulsion template

A facile and wet-chemical approach was employed to control synthesis of self-organizing, hyperbranched nanoporous Au microsheet with high quality in bulk quantity. This method produced nanoporous Au microsheets with a thickness of 7-15 nm. The microsheets were composed of irregularly interconnected planar Au nanoplates with interstices, i.e. nanopores of 10-50 nm. And the nanoporous Au microsheets were enveloped in 10-30 nm thick polyaniline (PANI) sheaths. The morphology of the nanostructured Au composites could also be easily tuned by changing the concentration of aniline and chlorauric acid. The dendritic and epitaxial growth of nanoporous Au microsheet was believed as the diffusion-limited process confined in the lamellar emulsion phase through self-assembly of aniline and dodecylsulfate. The solution reaction proceeded at a mild condition (room temperature and aqueous solutions), and less toxic reagents were employed instead of extreme toxic and corrosive chemicals.

Solvent-vapor treatment induced performance enhancement of poly(3-hexylthiophene): methanofullerene bulk-heterojunction photovoltaic cells

The authors report enhanced poly(3-hexylthiophene) (P3HT):methanofullerene (PCBM) bulk-heterojunction photovoltaic cells via 1,2-dichlorobenzene (DCB) vapor treatment and thermal annealing. DCB vapor treatment can induce P3HT self-organizing into ordered structure leading to enhanced absorption and high hole mobility. Further annealing the device at a high temperature, PCBM molecules begin to diffuse into aggregates and together with the ordered P3HT phase form bicontinuous pathways in the entire layer for efficient charge separation and transport. Compared to the control device that is merely annealed, optical absorption, short-circuit current, and power conversion efficiency are increased for the DCB vapor-treated cell.

Role of animal pole protuberance and microtubules during meiosis in sea cucumber Apostichopus japonicus oocytes

Fully grown oocytes of Apostichopus japonicus have a cytoplasmic protuberance where the oocyte attaches to the follicle. The protuberance and the oolamina located on the opposite side of the oocyte indicate the animal-vegetal axis. Two pre-meiotic centrosomes are anchored to the protuberance by microtubules between centrosomes and protuberance. After meiosis reinitiation induced by DTT solution, the germinal vesicle (GV) migrates towards the protuberance. The GV breaks down after it migrates to the oocyte membrane on the protuberance side. The protuberance then contracts back into the oocyte and the first polar body extrudes from the site of the former protuberance. The second polar body forms beneath the first. Thus the oocyte protuberance indicates the presumptive animal pole well before maturation of the oocyte.

Progress of large-scale air-sea interaction studies in China

This paper summarizes the progress of large-scale air-sea interaction studies that has been achieved in China in the four-year period from July 1998 to July 2002, including seven aspects in the area of the air-sea interaction, namely air-sea interaction related to the tropical Pacific Ocean, monsoon-related air-sea interaction, air-sea interaction in the north Pacific Ocean, air-sea interaction in the Indian Ocean, air-sea interactions in the global oceans, field experiments, and oceanic cruise surveys. However more attention has been paid to the first and the second aspects because a large number of papers in the reference literature for preparing and organizing this paper are concentrated in the tropical Pacific Ocean, such as the ENSO process with its climatic effects and dynamics, and the monsoon-related air-sea interaction. The literature also involves various phenomena with their different time and spatial scales such as intraseasonal, annual, interannual, and interdecadal variabilities in the atmosphere/ocean interaction system, reflecting the contemporary themes in the four-year period at the beginning of an era from the post-TOGA to CLIVAR studies. Apparently, it is a difficult task to summarize the great progress in this area, as it is extracted from a large quantity of literature, although the authors tried very hard.

Size dependence of biomass spectra and abundance spectra: the optimal distributions

Based on the hypothesis of self-optimization, we derive four models of biomass spectra and abundance spectra in communities with size-dependent metabolic rates. In Models 1 and 2, the maximum diversity of population abundance in different size classes subject to the constraints of constant mean body mass and constant mean respiration rate is assumed to be the strategy for ecosystems to organize their size structure. In Models 3 and 4, the organizing strategy is defined as the maximum diversity of biomass in different size classes without constraints on mean body mass and subject to the constant mean specific respiration rate of all individuals, i.e. the average specific respiration rate over all individuals of a community or group, which characterizes the mean rate of energy consumption in a community. Models 1 and 2 generate peaked distributions of biomass spectral density whereas Model 3 generates a fiat distribution. In Model 4, the distributions of biomass spectral density and of abundance spectral density depend on the Lagrangian multipler (lambda (2)). When lambda (2) tends to zero or equals zero, the distributions of biomass spectral density and of abundance spectral density correspond to those from Model 3. When lambda (2) has a large negative value, the biomass spectrum is similar to the empirical fiat biomass spectrum organized in logarithmic size intervals. When lambda (2) > 0, the biomass spectral density increases with body mass and the distribution of abundance spectral density is an unimodal curve. (C) 2001 Elsevier Science B.V. All rights reserved.

基于速度矢量可行度的移动机器人多行为综合决策方法

为了提高机器人对真实环境的适应能力 ,基于行为思想越来越多地被用于自主机器人的在线运动决策 .由此 ,产生了多行为综合管理问题 .本文分析了常用的基于矢量合成的并行行为的综合方法 .在此基础上 ,提出基于速度矢量可行度的自主移动机器人多行为综合决策方法 .该方法可较完整地保留子行为的决策意图 ,得到更合理的行为综合结果 .

基于LabVIEW的自组织网络的实现与应用

文章介绍了自组织神经网络在故障诊断方面的应用原理,针对自组织神经网络实现问题提出了一种通过在LabVIEW调用MATLAB应用程序实现自组织神经网络的方法。并通过轴承故障诊断的实例,证明了这种方法的有效性。

基于独立分量分析的地震属性分析方法研究

Conventional seismic attribute analysis is not only time consuming, but also has several possible results. Therefore, seismic attribute optimization and multi-attribute analysis are needed. In this paper, Fuyu oil layer in Daqing oil field is our main studying object. And there is much difference between seismic attributes and well logs. So under this condition, Independent Component Analysis (ICA) and Kohonen neural net are introduced to seismic attribute optimization and multi-attribute analysis. The main contents are as follows: (1) Now the method of seismic attribute compression is mainly principal component analysis (PCA). In this article, independent component analysis (ICA), which is superficially related to PCA, but much more powerful, is used to seismic reservoir characterizeation. The fundamental, algorithms and applications of ICA are surveyed. And comparation of ICA with PCA is stydied. On basis of the ne-entropy measurement of independence, the FastICA algorithm is implemented. (2) Two parts of ICA application are included in this article: First, ICA is used directly to identify sedimentary characters. Combined with geology and well data, ICA results can be used to predict sedimentary characters. Second, ICA treats many attributes as multi-dimension random vectors. Through ICA transform, a few good new attributes can be got from a lot of seismic attributes. Attributes got from ICA optimization are independent. (3) In this paper, Kohonen self-organizing neural network is studied. First, the characteristics of neural network’s structure and algorithm is analyzed in detail, and the traditional algorithm is achieved which has been used in seism. From experimental results, we know that the Kohonen self-organizing neural network converges fast and classifies accurately. Second, the self-organizing feature map algorithm needs to be improved because the result of classification is not very exact, the boundary is not quite clear and the velocity is not fast enough, and so on. Here frequency sensitive principle is introduced. Combine it with the self-organizing feature map algorithm, then get frequency sensitive self-organizing feature map algorithm. Experimental results show that it is really better. (4) Kohonen self-organizing neural network is used to classify seismic attributes. And it can be avoided drawing confusing conclusions because the algorithm’s characteristics integrate many kinds of seismic features. The result can be used in the division of sand group’s seismic faces, and so on. And when attributes are extracted from seismic data, some useful information is lost because of difference and deriveative. But multiattributes can make this lost information compensated in a certain degree.

基于MRF模型的油气储层属性随机建模方法研究

Stochastic reservoir modeling is a technique used in reservoir describing. Through this technique, multiple data sources with different scales can be integrated into the reservoir model and its uncertainty can be conveyed to researchers and supervisors. Stochastic reservoir modeling, for its digital models, its changeable scales, its honoring known information and data and its conveying uncertainty in models, provides a mathematical framework or platform for researchers to integrate multiple data sources and information with different scales into their prediction models. As a fresher method, stochastic reservoir modeling is on the upswing. Based on related works, this paper, starting with Markov property in reservoir, illustrates how to constitute spatial models for catalogued variables and continuum variables by use of Markov random fields. In order to explore reservoir properties, researchers should study the properties of rocks embedded in reservoirs. Apart from methods used in laboratories, geophysical means and subsequent interpretations may be the main sources for information and data used in petroleum exploration and exploitation. How to build a model for flow simulations based on incomplete information is to predict the spatial distributions of different reservoir variables. Considering data source, digital extent and methods, reservoir modeling can be catalogued into four sorts: reservoir sedimentology based method, reservoir seismic prediction, kriging and stochastic reservoir modeling. The application of Markov chain models in the analogue of sedimentary strata is introduced in the third of the paper. The concept of Markov chain model, N-step transition probability matrix, stationary distribution, the estimation of transition probability matrix, the testing of Markov property, 2 means for organizing sections-method based on equal intervals and based on rock facies, embedded Markov matrix, semi-Markov chain model, hidden Markov chain model, etc, are presented in this part. Based on 1-D Markov chain model, conditional 1-D Markov chain model is discussed in the fourth part. By extending 1-D Markov chain model to 2-D, 3-D situations, conditional 2-D, 3-D Markov chain models are presented. This part also discusses the estimation of vertical transition probability, lateral transition probability and the initialization of the top boundary. Corresponding digital models are used to specify, or testify related discussions. The fifth part, based on the fourth part and the application of MRF in image analysis, discusses MRF based method to simulate the spatial distribution of catalogued reservoir variables. In the part, the probability of a special catalogued variable mass, the definition of energy function for catalogued variable mass as a Markov random field, Strauss model, estimation of components in energy function are presented. Corresponding digital models are used to specify, or testify, related discussions. As for the simulation of the spatial distribution of continuum reservoir variables, the sixth part mainly explores 2 methods. The first is pure GMRF based method. Related contents include GMRF model and its neighborhood, parameters estimation, and MCMC iteration method. A digital example illustrates the corresponding method. The second is two-stage models method. Based on the results of catalogued variables distribution simulation, this method, taking GMRF as the prior distribution for continuum variables, taking the relationship between catalogued variables such as rock facies, continuum variables such as porosity, permeability, fluid saturation, can bring a series of stochastic images for the spatial distribution of continuum variables. Integrating multiple data sources into the reservoir model is one of the merits of stochastic reservoir modeling. After discussing how to model spatial distributions of catalogued reservoir variables, continuum reservoir variables, the paper explores how to combine conceptual depositional models, well logs, cores, seismic attributes production history.

Paradigms for Structure in an Amorphous Computer

Recent developments in microfabrication and nanotechnology will enable the inexpensive manufacturing of massive numbers of tiny computing elements with sensors and actuators. New programming paradigms are required for obtaining organized and coherent behavior from the cooperation of large numbers of unreliable processing elements that are interconnected in unknown, irregular, and possibly time-varying ways. Amorphous computing is the study of developing and programming such ultrascale computing environments. This paper presents an approach to programming an amorphous computer by spontaneously organizing an unstructured collection of processing elements into cooperative groups and hierarchies. This paper introduces a structure called an AC Hierarchy, which logically organizes processors into groups at different levels of granularity. The AC hierarchy simplifies programming of an amorphous computer through new language abstractions, facilitates the design of efficient and robust algorithms, and simplifies the analysis of their performance. Several example applications are presented that greatly benefit from the AC hierarchy. This paper introduces three algorithms for constructing multiple levels of the hierarchy from an unstructured collection of processors.

Learning Classes Correlated to a Hierarchy

Trees are a common way of organizing large amounts of information by placing items with similar characteristics near one another in the tree. We introduce a classification problem where a given tree structure gives us information on the best way to label nearby elements. We suggest there are many practical problems that fall under this domain. We propose a way to map the classification problem onto a standard Bayesian inference problem. We also give a fast, specialized inference algorithm that incrementally updates relevant probabilities. We apply this algorithm to web-classification problems and show that our algorithm empirically works well.

Near-Optimal Distributed Failure Circumscription

Small failures should only disrupt a small part of a network. One way to do this is by marking the surrounding area as untrustworthy --- circumscribing the failure. This can be done with a distributed algorithm using hierarchical clustering and neighbor relations, and the resulting circumscription is near-optimal for convex failures.

Utilização da contagem de tosse e espirro como indicadores da ocorrência e severidade de pneumonias e rinite atrófica, respectivamente.

1999

Qualitative Knowledge, Casual Reasoning and the Localization of Failures

This report investigates some techinques appropriate to representing the knowledge necessary for understanding a class of electronic machines -- radio receivers. A computational performance model - WATSON - is presented. WATSONs task is to isolate failures in radio receivers whose principles of operation have been appropriately described in his knowledge base. The thesis of the report is that hierarchically organized representational structures are essential to the understanding of complex mechanisms. Such structures lead not only to descriptions of machine operation at many levels of detail, but also offer a powerful means of organizing "specialist" knowledge for the repair of machines when they are broken.

Pressure support versus T-tube for weaning from mechanical ventilation in adults

BackgroundMechanical ventilation is important in caring for patients with critical illness. Clinical complications, increased mortality, and high costs of health care are associated with prolonged ventilatory support or premature discontinuation of mechanical ventilation. Weaning refers to the process of gradually or abruptly withdrawing mechanical ventilation. the weaning process begins after partial or complete resolution of the underlying pathophysiology precipitating respiratory failure and ends with weaning success (successful extubation in intubated patients or permanent withdrawal of ventilatory support in tracheostomized patients).ObjectivesTo evaluate the effectiveness and safety of two strategies, a T-tube and pressure support ventilation, for weaning adult patients with respiratory failure that required invasive mechanical ventilation for at least 24 hours, measuring weaning success and other clinically important outcomes.Search methodsWe searched the following electronic databases: Cochrane Central Register of Controlled Trials (CENTRAL) (The Cochrane Library 2012, Issue 6); MEDLINE (via PubMed) (1966 to June 2012); EMBASE (January 1980 to June 2012); LILACS (1986 to June 2012); CINAHL (1982 to June 2012); SciELO (from 1997 to August 2012); thesis repository of CAPES (Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior) (http://capesdw.capes.gov.br/capesdw/) (August 2012); and Current Controlled Trials (August 2012).We reran the search in December 2013. We will deal with any studies of interest when we update the review.Selection criteriaWe included randomized controlled trials (RCTs) that compared a T-tube with pressure support (PS) for the conduct of spontaneous breathing trials and as methods of gradual weaning of adult patients with respiratory failure of various aetiologies who received invasive mechanical ventilation for at least 24 hours.Data collection and analysisTwo authors extracted data and assessed the methodological quality of the included studies. Meta-analyses using the random-effects model were conducted for nine outcomes. Relative risk (RR) and mean difference (MD) or standardized mean difference (SMD) were used to estimate the treatment effect, with 95% confidence intervals (CI).Main resultsWe included nine RCTs with 1208 patients; 622 patients were randomized to a PS spontaneous breathing trial (SBT) and 586 to a T-tube SBT. the studies were classified into three categories of weaning: simple, difficult, and prolonged. Four studies placed patients in two categories of weaning. Pressure support ventilation (PSV) and a T-tube were used directly as SBTs in four studies (844 patients, 69.9% of the sample). in 186 patients (15.4%) both interventions were used along with gradual weaning from mechanical ventilation; the PS was gradually decreased, twice a day, until it was minimal and periods with a T-tube were gradually increased to two and eight hours for patients with difficult and prolonged weaning. in two studies (14.7% of patients) the PS was lowered to 2 to 4 cm H2O and 3 to 5 cm H2O based on ventilatory parameters until the minimal PS levels were reached. PS was then compared to the trial with the T-tube (TT).We identified 33 different reported outcomes in the included studies; we took 14 of them into consideration and performed meta-analyses on nine. With regard to the sequence of allocation generation, allocation concealment, selective reporting and attrition bias, no study presented a high risk of bias. We found no clear evidence of a difference between PS and TT for weaning success (RR 1.07, 95% CI 0.97 to 1.17, 9 studies, low quality of evidence), intensive care unit (ICU) mortality (RR 0.81, 95% CI 0.53 to 1.23, 5 studies, low quality of evidence), reintubation (RR 0.92, 95% CI 0.66 to 1.26, 7 studies, low quality evidence), ICU and long-term weaning unit (LWU) length of stay (MD -7.08 days, 95% CI -16.26 to 2.1, 2 studies, low quality of evidence) and pneumonia (RR 0.67, 95% CI 0.08 to 5.85, 2 studies, low quality of evidence). PS was significantly superior to the TT for successful SBTs (RR 1.09, 95% CI 1.02 to 1.17, 4 studies, moderate quality of evidence). Four studies reported on weaning duration, however we were unable to combined the study data because of differences in how the studies presented their data. One study was at high risk of other bias and four studies were at high risk for detection bias. Three studies reported that the weaning duration was shorter with PS, and in one study the duration was shorter in patients with a TT.Authors' conclusionsTo date, we have found evidence of generally low quality from studies comparing pressure support ventilation (PSV) and with a T-tube. the effects on weaning success, ICU mortality, reintubation, ICU and LWU length of stay, and pneumonia were imprecise. However, PSV was more effective than a T-tube for successful spontaneous breathing trials (SBTs) among patients with simple weaning. Based on the findings of single trials, three studies presented a shorter weaning duration in the group undergoing PS SBT, however a fourth study found a shorter weaning duration with a T-tube.