磷、硅阻燃协同效应的研究及应用

对磷系阻燃剂、硅系阻燃剂及其协同阻燃体系的阻燃机理进行深入研究,详细叙述了磷硅协同阻燃体系在棉织物中的应用情况,并对其发展前景进行了展望.     

Biofilms and Benign Colonic Diseases

The colon has a very large surface area that is covered by a dense mucus layer. The biomass in the colon includes 500–1000 bacterial species at concentrations of ~10¹² colony-forming units per gram of feces. The intestinal epithelial cells and the commensal bacteria in the colon have a symbiotic relationship that results in nutritional support for the epithelial cells by the bacteria and maintenance of the optimal commensal bacterial population by colonic host defenses. Bacteria can form biofilms in the colon, but the exact frequency is uncertain because routine methods to undertake colonoscopy (i.e., bowel preparation) may dislodge these biofilms. Bacteria in biofilms represent a complex community that includes living and dead bacteria and an extracellular matrix composed of polysaccharides, proteins, DNA, and exogenous debris in the colon. The formation of biofilms occurs in benign colonic diseases, such as inflammatory bowel disease and irritable bowel syndrome. The development of a biofilm might serve as a marker for ongoing colonic inflammation. Alternatively, the development of biofilms could contribute to the pathogenesis of these disorders by providing sanctuaries for pathogenic bacteria and reducing the commensal bacterial population. Therapeutic approaches to patients with benign colonic diseases could include the elimination of biofilms and restoration of normal commensal bacteria populations. However, these studies will be extremely difficult unless investigators can develop noninvasive methods for measuring and identifying biofilms. These methods that might include the measurement of quorum sensing molecules, measurement of bile acids, and identification of bacteria uniquely associated with biofilms in the colon.     

Does the model matter? The relationship between science-practice emphasis in clinical psychology programs and the internship match.

[Correction Notice: An erratum for this article was reported in Vol 1(4) of Training and Education in Professional Psychology (see record 2007-18975-009). The biography for the third author was incorrect. It should read as follows: GREGORY KEILIN is an Assistant Director at the Counseling and Mental Health Center at the University of Texas at Austin and a former Chair of APPIC. He received his doctorate in Counseling Psychology from Colorado State University. His current research interests include supply and demand issues in professional psychology.] Academic training programs in clinical psychology vary in the emphasis that they place on science and practice, and this paper examines whether these differential emphases are linked to distinctive internship outcomes. In a study of 2,130 internship applicants from clinical psychology programs, differences were noted among practice-oriented programs, balanced science-practice programs, and science-oriented programs. Against a backdrop of some similarities, a differential emphasis on science and practice within academic training programs was related to significantly different internship match rates, as well as to successful matching in qualitatively different internship settings. Results provided qualified support for future work that might further address the relationship between academic training programs and outcomes in the field of clinical psychology. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Dyadic spatial resolution reduction transcoding for H.264/AVC

In this paper, we examine spatial resolution downscaling transcoding for H.264/AVC video coding. A number of advanced coding tools limit the applicability of techniques, which were developed for previous video coding standards. We present a spatial resolution reduction transcoding architecture for H.264/AVC, which extends open-loop transcoding with a low-complexity compensation technique in the reduced-resolution domain. The proposed architecture tackles the problems in H.264/AVC and avoids visual artifacts in the transcoded sequence, while keeping complexity significantly lower than more traditional cascaded decoder–encoder architectures. The refinement step of the proposed architecture can be used to further improve rate-distortion performance, at the cost of additional complexity. In this way, a dynamic-complexity transcoder is rendered possible. We present a thorough investigation of the problems related to motion and residual data mapping, leading to a transcoding solution resulting in fully compliant reduced-size H.264/AVC bitstreams.     

Evaluation of the thiamine dose-response relationship for lake trout (Salvelinus namaycush) fry using an individual based model

Substantial natural reproduction of lake trout (Salvelinus namaycush) has not been achieved in the Great Lakes, except for Lake Superior and a few areas in Lake Huron, despite continued stocking efforts. Low thiamine levels in lake trout eggs, which can result in lethal and sublethal impacts (thiamine deficiency complex, TDC) on fry, may contribute to widespread recruitment failure in lake trout populations. We hypothesized that incorporation of sublethal impacts into dose-response curves would result in estimates of EC50s (median lethal concentrations) for fry greater than the estimates that rely only on acute mortality and that predation would exacerbate thiamine effects. To investigate the sublethal effects of TDC (prey capture success and predation mortality) on cohort growth and survival, we developed an individual-based model for lake trout fry. The model tracks daily activities, including consumption, respiration, growth, and mortality, of lake trout from hatch until fry reach a length of 33?mm when we assume fry feed naturally and thiamine effects are minimized. Model output with sublethal impacts resulted in an EC50 (7.3?nmol/g) that was greater than published studies that are limited to acute mortality (1.5?nmol/g). Furthermore, when we included interstitial and pelagic predation, the impact of sublethal effects shifted the EC50 values even higher (7.4–10?nmol/g). Simulation results indicate that low thiamine levels, in combination with moderate to high predation, can eliminate lake trout cohorts. Our simulations suggest that the sublethal effects of low thiamine can contribute to poor lake trout recruitment more than previously suspected.     

Balance between model detail and experimental information in steam methane reforming over a Ni/MgO-SiO2 catalyst

The optimization and full understanding of chemical reactions is aided by the construction of an adequate kinetic model. The development of such a kinetic model remains a challenging task. To tackle this challenge in the most efficient way, an iterative, systematic methodology, originally demonstrated for n-hexane hydroisomerization, is now extended aiming at finding the balance between the envisaged model detail and available information, often originating from time-consuming and expensive experiments. Steam methane reforming on the Ni/MgO-SiO₂ case study is used for this purpose, that is, the construction of a kinetic model that embeds a maximum amount of information contained in the dataset. The kinetic model is expanded stepwise from a power law model over a model with reactant adsorption toward a Langmuir–Hinshelwood–Hougen–Watson model. The performance of the initially underparameterized model improved significantly by adding reactant adsorption, yet including product adsorption led to overparameterization rather than enhanced model performance. © 2019 American Institute of Chemical Engineers AIChE J, 65: 1222–1233, 2019     

On Data Integration Problems With Manifolds

This article focuses on data integration problems where the predictor variables for some response variable partition into known subsets. This type of data is often referred to as multi-view data, and each subset of the predictors is called a data view. Accounting for data views can add practical value in terms of both interpretation and predictive performance. Many existing approaches for multi-view data rely on view-agreement principles, strong smoothness assumptions, or regularization penalties. The former approaches can be sensitive to modest noise in the response or predictor variables, while the latter approach is linear and can usually be out-performed. We develop semiparametric data integration methods to span key tradeoffs including the bias-variance tradeoff on prediction error, the possibility that the data may be fully viewed with no appreciable view relationships, and the use of sparse anchor point methods to detect and use manifolds (i.e., possibly nonelliptical structures) within views if they enhance performance. Theoretical results help justify the new technique, and its effectiveness and computational feasibility are demonstrated empirically. This new semiparametric methodology is available for public use through the supplemental R package mvltools. Additional supplementary material for this article is also available online.     

First-principles modeling for optimal design,operation, and integration of energy conversion and storage systems

Energy and electricity consumption is expected to increase in the foreseeable future. Concurrently, sustainability concerns of fossil-based energy resources have motivated the use of renewable and reusable energy resources, and the use of more efficient energy-converting and energy-consuming systems. Consequently, for the past decade, there have been major theoretical and experimental advances in (1) energy generation from renewable and reusable resources and (2) energy-consuming and energy-converting devices. This review article focuses on the recent theoretical advances in renewable energy conversion devices such as photovoltaic and fuel cells, and in energy storage devices such as rechargeable batteries, flow batteries, and supercapacitors. Due to similar chemistry, electrochemistry, and physics of these systems, modeling similarities between different energy systems are highlighted. This review puts into perspective how first-principles mathematical modeling has contributed to systematic advances in the optimal design, operation, and integration of these systems. © 2018 American Institute of Chemical Engineers AIChE J, 65: e16482 2019     

Acute health effects from exposure to indoor ultrafine particles—A randomized controlled crossover study among young mild asthmatics

Particulate matter is linked to adverse health effects, however, little is known about health effects of particles emitted from typical indoor sources. We examined acute health effects of short-term exposure to emissions from cooking and candles among asthmatics. In a randomized controlled double-blinded crossover study, 36 young non-smoking asthmatics attended three exposure sessions lasting 5 h: (a) air mixed with emissions from cooking (fine particle mass concentration): (PM_2.5: 96.1 μg/m³), (b) air mixed with emissions from candles (PM_2.5: 89.8 μg/m³), and c) clean filtered air (PM_2.5: 5.8 μg/m³). Health effects (spirometry, fractional exhaled Nitric Oxide [FeNO], nasal volume and self-reported symptoms) were evaluated before exposure start, then 5 and 24 h after. During exposures volatile organic compounds (VOCs), particle size distributions, number concentrations and optical properties were measured. Generally, no statistically significant changes were observed in spirometry, FeNO, or nasal volume comparing cooking and candle exposures to clean air. In males, nasal volume and FeNO decreased after exposure to cooking and candles, respectively. Participants reported additional and more pronounced symptoms during exposure to cooking and candles compared to clean air. The results indicate that emissions from cooking and candles exert mild inflammation in asthmatic males and decrease comfort among asthmatic males and females.