Molecular simulation of temperature-programmed desorption

We use accelerated molecular dynamics to probe the thermal desorption of n-alkanes from the Au(1 1 1) and C(0 0 0 1) surfaces. Studying an alkane series ranging from CH₄ to C₁₆H₃₄, we find that the desorption prefactor increases with increasing chain length for the short chains until a certain chain length is reached when it becomes essentially constant and independent of chain length. We can understand the dependence of the preexponential factor on alkane chain length in terms of conformational changes within the alkane molecules. For the shorter molecules, the desorption temperatures probed in experimental temperature-programmed desorption studies lie below those for which torsional motion is activated. Thus, the short alkanes can be treated as rigid rods, and the loss in translational and rotational entropy upon adsorption leads to a preexponential factor that increases with increasing chain length. As the alkane chain length increases, the binding energy and the experimental desorption temperatures also increase. Thus, torsional motion is activated to an extent that increases with increasing chain length. This torsional activation increases the entropy of adsorption and counteracts the entropy decrease due to a loss of translation and rotation. This leads to a virtually constant prefactor for sufficiently long chains. Our findings are consistent with experimental data for the thermal desorption of alkanes from the Au(1 1 1), Pt(1 1 1), MgO(1 0 0) and C(0 0 0 1) surfaces.     

Flexible and light weight copper indium diselenide solar cells on polyimide substrates

Thin film flexible CuInSe₂ (CIS) solar cells have been fabricated for the first time on light-weight polymeric substrates. Evaporated Cu---In alloy precursors were selenized in H₂Se atmosphere at around 400°C to grow the CIS absorber layers. Low temperature techniques which are compatible with the polymeric substrates were used to deposit the window layers of CdS and ZnO. The demonstrated active area conversion efficiency of 9.3% makes this light-weight device very attractive for many terrestrial and space power generation applications where high specific power and mechanical flexibility are needed.     

An overview of FDA medical device regulation as it relates to deep brain stimulation devices.

The United States Food and Drug Administration (FDA) is charged with assuring the safety and effectiveness of a variety of medical products and the FDA's Center for Devices and Radiological Health is responsible for premarket and postmarket regulation of medical devices. In this paper, we review--from device classification and clinical studies to the final marketing application--FDA's premarket requirements and postmarket requirements as they relate to deep brain stimulation devices.     

Combining teacher-Led and technology-assisted instruction to improve phoneme blending to read words for elementary students with disabilities

Technology-assisted instruction has potential for helping students improve their reading skills. In the current studies, PowerPoint software was used to supplement teacher-led reading instruction for elementary-aged students with disabilities who struggled with phoneme blending to read words. The effectiveness of the intervention was assessed using two multiple probe design studies across sets of words based on an onset-rime (word family) strategy. In Study 1, teacher-led instruction was paired with technology-assisted instruction for all intervention sessions for three students in first and second grade. In Study 2, teacher-led instruction occurred between baseline and technology-assisted intervention sessions for three students in third and fourth grade. During the initial instruction sessions, participants recorded their own voices onto PowerPoint slides so that their technology-assisted instruction included self-modelling. Results of both studies indicated that technology-assisted instruction can be effective for helping students learn how to blend phonemes to read words; however, performance varied and there were limitations in each study that should be addressed in future research. Relevant implications for classroom instruction are emphasized.     

The Importance of Therapeutically Targeting the Binary Toxin from Clostridioides difficile

Novel therapeutics are needed to treat pathologies associated with the Clostridioides difficile binary toxin (CDT), particularly when C. difficile infection (CDI) occurs in the elderly or in hospitalized patients having illnesses, in addition to CDI, such as cancer. While therapies are available to block toxicities associated with the large clostridial toxins (TcdA and TcdB) in this nosocomial disease, nothing is available yet to treat toxicities arising from strains of CDI having the binary toxin. Like other binary toxins, the active CDTa catalytic subunit of CDT is delivered into host cells together with an oligomeric assembly of CDTb subunits via host cell receptor-mediated endocytosis. Once CDT arrives in the host cell’s cytoplasm, CDTa catalyzes the ADP-ribosylation of G-actin leading to degradation of the cytoskeleton and rapid cell death. Although a detailed molecular mechanism for CDT entry and host cell toxicity is not yet fully established, structural and functional resemblances to other binary toxins are described. Additionally, unique conformational assemblies of individual CDT components are highlighted herein to refine our mechanistic understanding of this deadly toxin as is needed to develop effective new therapeutic strategies for treating some of the most hypervirulent and lethal strains of CDT-containing strains of CDI.     

Learning Kernels for Unsupervised Domain Adaptation with Applications to Visual Object Recognition

Domain adaptation aims to correct the mismatch in statistical properties between the source domain on which a classifier is trained and the target domain to which the classifier is to be applied. In this paper, we address the challenging scenario of unsupervised domain adaptation, where the target domain does not provide any annotated data to assist in adapting the classifier. Our strategy is to learn robust features which are resilient to the mismatch across domains and then use them to construct classifiers that will perform well on the target domain. To this end, we propose novel kernel learning approaches to infer such features for adaptation. Concretely, we explore two closely related directions. In the first direction, we propose unsupervised learning of a geodesic flow kernel (GFK). The GFK summarizes the inner products in an infinite sequence of feature subspaces that smoothly interpolates between the source and target domains. In the second direction, we propose supervised learning of a kernel that discriminatively combines multiple base GFKs. Those base kernels model the source and the target domains at fine-grained granularities. In particular, each base kernel pivots on a different set of landmarks—the most useful data instances that reveal the similarity between the source and the target domains, thus bridging them to achieve adaptation. Our approaches are computationally convenient, automatically infer important hyper-parameters, and are capable of learning features and classifiers discriminatively without demanding labeled data from the target domain. In extensive empirical studies on standard benchmark recognition datasets, our appraches yield state-of-the-art results compared to a variety of competing methods.     

Polyurethane‐infiltrated carbon foams: A coupling of thermal and mechanical properties

The thermal and mechanical properties of polyurethane‐infiltrated carbon foam of various densities were investigated. By combining the high thermal conductivity of the carbon foam with the mechanical toughness of the pure polyurethane, a mechanically tough composite (relative to the unfilled foam) that could be used at higher temperatures than the polyurethane's degradation was formed. Both the tensile strength and the modulus increased by an order of magnitude for the composites compared to unfilled foam, while the compressive and shear strengths and moduli of the composites approached values exhibited by pure polyurethane. At both 300 and 400°C, the rectangular blocks of pure polyurethane lost their mechanical integrity due to decomposition in air. Thermogravimetric analysis confirms substantial initial weight loss above 290°C. Filled carbon foam blocks, however, maintain their mechanical integrity at both 300 and 400°C indefinitely, although the bulk of the rectangular block mass is polyurethane. Three different carbon foam densities are examined. As expected, the higher density foams show greater heat transfer. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 87: 2348–2355, 2003     

Linking air quality and watershed models for environmental assessments: Analysis of the effects of model-specific precipitation estimates on calculated water flux

Directly linking air quality and watershed models could provide an effective method for estimating spatially-explicit inputs of atmospheric contaminants to watershed biogeochemical models. However, to adequately link air and watershed models for wet deposition estimates, each model’s temporal and spatial representation of precipitation needs to be consistent. We explore how precipitation implemented within the Community Multi-Scale Air Quality Model (CMAQ) model algorithms, and multiple spatially-explicit precipitation datasets that could be used to improve the CMAQ model deposition estimates, links with the standard precipitation sources used to calibrate watershed models (i.e., rain gage data) via modeled water fluxes. Simulations are run using a grid-based watershed mercury model (GBMM) in two watersheds. Modeled monthly runoff suggests that multiple resolution Parameter-elevations Regressions on Independent Slopes Model (PRISM) and National Multi-sensor Precipitation Analysis Stage IV (NPA) data generate similar monthly runoff estimates, with comparable or greater accuracy when evaluated against stream gage data than that produced by the base rain gage data. However, across longer time periods, simulated water balances using 36 km Pennsylvania State University/National Center for Atmospheric Research mesoscale model (MM5) data are similar to that of base data. The investigation also examines the implications our results, providing suggestions for linking air quality and watershed fate and transport models.     

The acculturation gap-distress hypothesis among high-risk Mexican American families.

The authors tested the acculturation gap-distress hypothesis by examining whether parent-adolescent acculturation gaps were associated with greater conflict and youth conduct problems among 260 high-risk Mexican American families. The authors operationalized acculturation gaps in 2 ways: parent-youth mismatches in acculturation style, and parent-youth discrepancies in acculturation toward both mainstream and heritage cultures. Acculturation gaps were common, but results of hierarchical regression analyses indicated that parent-youth discrepancies in acculturation toward mainstream and heritage cultures were not related to increased conflict or youth conduct problems. Conduct problems were no higher in families in which the adolescent was more aligned with mainstream culture than the parent. Unexpectedly, the authors found more youth conduct problems in families in which the youth was more aligned with traditional culture than the parent. The results call into question the assumption that the more rapid acculturation of adolescents to American culture inevitably leads to distress in minority families. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Traumatic Stress, Perceived Global Stress, and Life Events: Prospectively Predicting Quality of Life in Breast Cancer Patients.

The authors investigated the relationship between stress at initial cancer diagnosis and treatment and subsequent quality of life (QoL). Women (n = 112) randomized to the assessment-only arm of a clinical trial were initially assessed after breast cancer diagnosis and surgery and then reassessed at 4 months (during adjuvant treatment) and 12 months (postadjuvant treatment). There were 3 types of stress measured: number of stressful life events (K. A. Matthews et al., 1997), cancer-related traumatic stress symptoms (M. J. Horowitz, N. Wilner, & W. Alvarez, 1979), and perceived global stress (S. Cohen, T. Kamarck, & R. Mermelstein, 1983). Using hierarchical multiple regressions, the authors found that stress predicted both psychological and physical QoL (J. E. Ware, K. K. Snow, & M. Kosinski, 2000) at the follow-ups (all ps