Investigation of the action of flame retardants in cellulose. I. Investigation of the flame retardant action of 2,2′-oxybis(5,5-dimethyl-1,3,2-dioxaphosphorinane-2,2′-disulfide) in cellulose

Pyrolysis experiments were performed in high vacuum and under reduced air pressure (100 Pa). The volatile products of pure cellulose and cellulose containing various amounts of flame retardant 2,2′-oxybis (5,5-dimethyl-1,3,2-dioxaphosphorinane-2,2′-disulfide), i.e., Sandoflam 5060 of Sandoz AG, were studied by means of gas chromatography in combination with mass spectroscopy. The volatile products were characterized with infrared spectroscopy. The studied revealed that the incorporation of the flame retardant enhanced the water release and shifted the onset of this reaction to lower temperature. On the basis of these findings an explanation for the mechanism of flame retardancy in generated cellulose fibers modified with this particular flame retardant is attempted. From experiments with different residual air pressure the influence of oxygen on the primary processes of the pyrolytic degradation of cellulose is being discussed.     

Influence of Reaction Parameters on the Hydrogenolysis of Hydroxymatairesinol Over Carbon Nanofibre Supported Palladium Catalysts

The density functional theory (DFT/B3LYP) calculations were applied to investigate the interaction of a Pt₆ particle with the ZSM-5 zeolite framework. The electronic structure of the metal particle is strongly affected by the interaction with basic framework oxygens and acid sites of the zeolite support. Adsorption on basic sites (E_ads = 6 kcal/mol) favors the formation of the electron enriched metal cluster. Interaction of the platinum cluster with the acid site characterized by stabilization energy of 47 kcal/mol results in oxidation of the metal particle and suppression of Brønsted acidity of the support. The hypothesis is put forward that the oxidized platinum particle can function as an active site for the alkane isomerisation on platinum supported high silica zeolites.     

Pruning Algorithms for Rule Learning

Pre-pruning and Post-pruning are two standard techniques for handling noise in decision tree learning. Pre-pruning deals with noise during learning, while post-pruning addresses this problem after an overfitting theory has been learned. We first review several adaptations of pre- and post-pruning techniques for separate-and-conquer rule learning algorithms and discuss some fundamental problems. The primary goal of this paper is to show how to solve these problems with two new algorithms that combine and integrate pre- and post-pruning.     

Gain-coupled DFB lasers with a titanium surface Bragg grating

The improved performance of gain-coupled DFB lasers incorporating a titanium surface Bragg grating and a strained layer multiquantum well active region for operation at 1.55 μm is presented. Besides the essentially simplified fabrication process, the incorporation of the metallic, absorptive grating yields stable singlemode operation with a high sidemode suppression     

智能卡IC-电子商务的安全密钥

引言 电子商务是建立在信任基础上的.在现实世界中,信任是通过人际关系、签名及其他证明方式建立起来的.而在电子世界里,信任的创建必须脱离这些书面的证明方式.事实上,电子身份证可提供确凿的证据,表明客户及厂商的真实身份.     

Distilled Collections from Textual Image Queries

We present a distillation algorithm which operates on a large, unstructured, and noisy collection of internet images returned from an online object query. We introduce the notion of a distilled set, which is a clean, coherent, and structured subset of inlier images. In addition, the object of interest is properly segmented out throughout the distilled set. Our approach is unsupervised, built on a novel clustering scheme, and solves the distillation and object segmentation problems simultaneously. In essence, instead of distilling the collection of images, we distill a collection of loosely cutout foreground “shapes”, which may or may not contain the queried object. Our key observation, which motivated our clustering scheme, is that outlier shapes are expected to be random in nature, whereas, inlier shapes, which do tightly enclose the object of interest, tend to be well supported by similar shapes captured in similar views. We analyze the commonalities among candidate foreground segments, without aiming to analyze their semantics, but simply by clustering similar shapes and considering only the most significant clusters representing non‐trivial shapes. We show that when tuned conservatively, our distillation algorithm is able to extract a near perfect subset of true inliers. Furthermore, we show that our technique scales well in the sense that the precision rate remains high, as the collection grows. We demonstrate the utility of our distillation results with a number of interesting graphics applications.     

Evaluation of Sensors and Mapping Approaches for Disasters in Tunnels

Ground or aerial robots equipped with advanced sensing technologies, such as three‐dimensional laser scanners and advanced mapping algorithms, are deemed useful as a supporting technology for first responders. A great deal of excellent research in the field exists, but practical applications at real disaster sites are scarce. Many projects concentrate on equipping robots with advanced capabilities, such as autonomous exploration or object manipulation. In spite of this, realistic application areas for such robots are limited to teleoperated reconnaissance or search. In this paper, we investigate how well state‐of‐the‐art and off‐the‐shelf components and algorithms are suited for reconnaissance in current disaster‐relief scenarios. The basic idea is to make use of some of the most common sensors and deploy some widely used algorithms in a disaster situation, and to evaluate how well the components work for these scenarios. We acquired the sensor data from two field experiments, one from a disaster‐relief operation in a motorway tunnel, and one from a mapping experiment in a partly closed down motorway tunnel. Based on these data, which we make publicly available, we evaluate state‐of‐the‐art and off‐the‐shelf mapping approaches. In our analysis, we integrate opinions and replies from first responders as well as from some algorithm developers on the usefulness of the data and the limitations of the deployed approaches, respectively. We discuss the lessons we learned during the two missions. These lessons are interesting for the community working in similar areas of urban search and rescue, particularly reconnaissance and search.     

Physically Meaningful Rendering using Tristimulus Colours

In photorealistic image synthesis the radiative transfer equation is often not solved by simulating every wavelength of light, but instead by computing tristimulus transport, for instance using sRGB primaries as a basis. This choice is convenient, because input texture data is usually stored in RGB colour spaces. However, there are problems with this approach which are often overlooked or ignored. By comparing to spectral reference renderings, we show how rendering in tristimulus colour spaces introduces colour shifts in indirect light, violation of energy conservation, and unexpected behaviour in participating media. Furthermore, we introduce a fast method to compute spectra from almost any given XYZ input colour. It creates spectra that match the input colour precisely. Additionally, like in natural reflectance spectra, their energy is smoothly distributed over wide wavelength bands. This method is both useful to upsample RGB input data when spectral transport is used and as an intermediate step for corrected tristimulus‐based transport. Finally, we show how energy conservation can be enforced in RGB by mapping colours to valid reflectances.     

Towards long term monitoring of electrodermal activity in daily life

Manic depression, also known as bipolar disorder, is a common and severe form of mental disorder. The European research project MONARCA aims at developing and validating mobile technologies for multi-parametric, long term monitoring of physiological and behavioral information relevant to bipolar disorder. One aspect of MONARCA is to investigate the long term monitoring of Electrodermal activity (EDA) to support the diagnosis and treatment of bipolar disorder patients. EDA is known as an indicator of the emotional state and the stress level of a person. To realize a long-term monitoring of the EDA, the integration of the sensor system in the shoe or sock is a promising approach. This paper presents a first step towards such a sensor system. In a feasibility study including 8 subjects, we investigate the correlation between EDA measurements at the fingers, which is the most established sensing site, with measurements of the EDA at the feet. The results indicate that 88% of the evoked skin conductance responses (SCRs) occur at both sensing sites. When using an action movie as psychophysiologically activating stimulus, we have found weaker reactivity in the foot than in the hand EDA. The results also suggest that the influence of moderate physical activity on EDA measurements is low and has a similar effect for both recording sites. This suggests that the foot recording location is suitable for recordings in daily life even in the presence of moderate movement.     

Matrix Interpretations for Proving Termination of Term Rewriting

We present a new method for automatically proving termination of term rewriting. It is based on the well-known idea of interpretation of terms where every rewrite step causes a decrease, but instead of the usual natural numbers we use vectors of natural numbers, ordered by a particular nontotal well-founded ordering. Function symbols are interpreted by linear mappings represented by matrices. This method allows us to prove termination and relative termination. A modification of the latter, in which strict steps are only allowed at the top, turns out to be helpful in combination with the dependency pair transformation. By bounding the dimension and the matrix coefficients, the search problem becomes finite. Our implementation transforms it to a Boolean satisfiability problem (SAT), to be solved by a state-of-the-art SAT solver.