Effectiveness of an Internet-based program for reducing risk factors for eating disorders.

This study evaluated an Internet-delivered computer-assisted health education (CAHE) program designed to improve body satisfaction and reduce weight/shape concerns—concerns that have been shown to be risk factors for the development of eating disorders in young women. Participants were 60 women at a public university randomly assigned to either an intervention or control condition. Intervention participants completed the CAHE program Student Bodies. Measures of body image and disordered eating attitudes were assessed at baseline, postintervention, and 3-month follow-up. At follow-up, intervention participants, compared with controls, reported a significant improvement in body image and a decrease in drive for thinness. This program provides evidence for the feasibility and effectiveness of providing health education by means of the Internet. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Reducing risk factors for eating disorders: Comparison of an Internet- and a classroom-delivered psychoeducational program.

This controlled trial compared Internet- (Student Bodies [SB]) and classroom-delivered (Body Traps [BT]) psychoeducational interventions for the reduction of body dissatisfaction and disordered eating behaviors/attitudes with a control condition. Participants were 76 women at a private university who were randomly assigned to SB, BT, or a wait-list control (WLC) condition. Measures of body image and eating attitudes and behaviors were measured at baseline, posttreatment, and 4-month follow-up. At posttreatment, participants in SB had significant reductions in weight/shape concerns and disordered eating attitudes compared with those in the WLC condition. At follow-up, disordered behaviors were also reduced. No significant effects were found between the BT and WLC conditions. An Internet-delivered intervention had a significant impact on reducing risk factors for eating disorders. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Tin Oxide Thin-Film Sensors for Aromatic Hydrocarbons Detection: Effect of Aging Time on Film Microstructure

SnO₂ thin films for gas-sensor devices were deposited by pulsed laser ablation on < h 00> silicon wafers and on substrate heater elements with 200 nm thick Si₃N₄ membranes as physical supports of the sensor stack. Microscopic analysis showed that the thin films were polycrystalline, with ∼40-60 nm equiaxial grains, high porosity, and high specific surface area. The sensors were exposed to gas mixtures containing benzene, wet synthetic air, and CO, with 0.5 ppm of benzene added to 30% relative humidity synthetic air and 20 ppm CO. A 100% relative conductance variation, Delta I / I ₀, of the sensing layer was observed. However, this Delta I / I ₀ value consistently decreased after prolonged testing (up to 2 weeks) in a gas-sensor chamber. The sensing layer was studied using several analytical techniques to understand the aging time effects on sensor performance under working conditions. X-ray diffractometry showed a marked decrease of the residual microstrain after prolonged heat treatments, suggesting a substantial reduction of lattice (point and line) defects. Furthermore, photothermal deflection spectroscopy highlighted a consistent decrease of the sensing layer absorption coefficient near 1 eV that could be related to a reduction of carrier concentration. Because structural defects in SnO₂, such as oxygen vacancies or dislocations, are electrically active and variations in the carrier concentration are, at least in part, related with changes in the defect density, the annealing of these defects might have accounted for the observed worsening of sensor performance with the aging time.     

Expert Panel Workshop Consensus Statement on the Role of the Environment in the Development of Autoimmune Disease

Autoimmune diseases include 80 or more complex disorders characterized by self-reactive, pathologic immune responses in which genetic susceptibility is largely insufficient to determine disease onset. In September 2010, the National Institute of Environmental Health Sciences (NIEHS) organized an expert panel workshop to evaluate the role of environmental factors in autoimmune diseases, and the state of the science regarding relevant mechanisms, animal models, and human studies. The objective of the workshop was to analyze the existing data to identify conclusions that could be drawn regarding environmental exposures and autoimmunity and to identify critical knowledge gaps and areas of uncertainty for future study. This consensus document summarizes key findings from published workshop monographs on areas in which “confident” and “likely” assessments were made, with recommendations for further research. Transcribed notes and slides were reviewed to synthesize an overview on exposure assessment and questions addressed by interdisciplinary panels. Critical advances in the field of autoimmune disease research have been made in the past decade. Collaborative translational and interdisciplinary research is needed to elucidate the role of environmental factors in autoimmune diseases. A focus on exposure assessment methodology is needed to improve the effectiveness of human studies, and more experimental studies are needed to focus on causal mechanisms underlying observed associations of environmental factors with autoimmune disease in humans.     

A Smart Sensor System for Carbon Monoxide Detection

This paper illustrates a smart sensor system for carbonmonoxide detection. An innovative technological approach hasbeen pursued to fabricate gas sensors on silicon substrate, compatiblewith IC fabrication. A mixed analog-digital electronic interfaceprocesses the outputs of three sensors to compensate relativehumidity and interfering gases. Sigma-delta signal processingand low-frequency noise reduction techniques are used to minimizesilicon area and to meet the required performance in a standardCMOS technology.     

The model multiplicity problem: experimenting with real-timespecification methods

The object-process methodology (OPM) specifies both graphically and textually the system's static-structural and behavioral-procedural aspects through a single unifying model. This model singularity is contrasted with the multimodel approach applied by existing object oriented system analysis methods. These methods usually employ at least three distinct models for specifying various system aspects: mainly structure, function, and behavior. Object modeling technique (OMT), the main ancestor of the unified modeling language (UML), extended with timed statecharts, represents a family of such multimodal object oriented methods. Two major open questions related to model multiplicity vs. model singularity have been: 1) whether or not a single model, rather than a combination of several models, enables the synthesis of a better system specification; and 2) which of the two alternative approaches yields a specification that is easier to comprehend. The authors address these questions through a double-blind controlled experiment. To obtain conclusive results, real time systems, which exhibit a more complex dynamic behavior than nonreal time systems were selected as the focus of the experiment. We establish empirically that a single model methodology, OPM, is more effective than a multimodel one, OMT, in terms of synthesis. We pinpoint specific issues in which significant diiferences between the two methodologies were found. The specification comprehension results show that there were significant differences between the two methods in specific issues     

OPM vs. UML--Experimenting with Comprehension and Construction of Web Application Models

Object-Process Methodology (OPM), which is a holistic approach to modeling and evolving systems, views objects and processes as two equally important entities that describe the system's structure and behavior in a single model. Unified Modeling Language (UML), which is the standard object-oriented modeling language for software systems, separates the system model into various aspects, each of which is represented in a different view (diagram type).The exponential growth of the Web and the progress of Internet-based architectures have set the stage for the proliferation of a variety of Web applications, which are classified as hybrids between hypermedia and information systems. Such applications require a modeling approach that is capable of clearly specifying aspects of their architecture, communication, and distributive nature. Since UML and OPM are two candidates for this task, this study has been designed to establish the level of comprehension and the quality of the constructed Web application models using each one of these two approaches.In the experiment we carried out, third year undergraduate information systems engineering students were asked to respond to comprehension and construction questions about two representative Web application models. The comprehension questions related to the system's structure, dynamics, and distribution aspects. The results suggest that OPM is better than UML in modeling the dynamics aspect of the Web applications. In specifying structure and distribution aspects, there were no significant differences. The results further suggest that the quality of the OPM models students built in the construction part was superior to that of the corresponding UML models.     

Electrically controlled molecular recognition harnessed to activate a cellular response

Seamless embedment of electronic devices in biological systems is expected to add the outstanding computing power, memory, and speed of electronics to the biochemical toolbox of nature. Such amalgamation requires transduction of electronic signals into biochemical cues that affect cells. Inspired by biology, where pathways are directed by molecular recognition, we propose and demonstrate a generic electrical-to-biological transducer comprising a two-state electronic antigen and a chimeric cell receptor engineered to bind the antigen exclusively in its "on" state. T-cells expressing these receptors remain inactivated with the antigen in its "off" state. Switching the antigen to its "on" state by an electrical signal leads to its recognition by the T-cells and correspondingly to cell activation.     

一种在矢量基础上进行图形识别的通用方法

本文描述了一种在矢量基础上进行图形识别的通用方法．该方法包括２个步骤：第１步,寻找组成该图形的第１个关键图素;第２步,根据该图形的构造模式,从第１个关键图素出发,不断在其周围区域寻找组成该图形的其它图素．本文还提出了一种新的平面空间数据结构——位置索引．这种数据结构把平面图上的图形及图素用它们的平面位置索引组织起来,从而提高了按区域位置查找的效率．本文还介绍了该方法的２个应用实例：虚线识别和剖面线识别.