Controlled manipulation of molecular samples with thenanoManipulator

The nanoManipulator system adds a virtual-reality interface to an atomic-force microscope (AFM), thus providing a tool that can be used by scientists to image and manipulate nanometer-sized molecular structures in a controlled manner. As the AFM tip scans the sample, the tip-sample interaction forces are monitored, which, in turn, can yield information about the frictional, mechanical, material, and topological properties of the sample. Computer graphics are used to reconstruct the surface for the user, with color or contours overlaid to indicate additional data sets. Moreover, a force feedback stylus, which is connected to the tip via software, allows the user to directly interact with the macromolecules. This system is being used to investigate carbon nanotubes, DNA, fibrin, adeno- and tobacco mosaic virus. It is now also possible to insert this system into a scanning electron microscope which provides the user with continuous images of the sample, even while the AFM tip is being used for manipulations     

Biomarkers of exposure and dose: state of the art.

Biomarkers provide methods to measure changes in biological systems and to relate them to environmental insults and disease processes. Biomarkers can be classified as markers of exposure and dose, markers of sensitivity, and markers of disease. It is important that the differences and applications of the various types of biomarkers be clearly understood. The military is primarily interested in early biomarkers of exposure and dose that do not require high levels of sensitivity but can be used to rapidly triage war fighters under combat or terrorist conditions and determine which, if any, require medical attention. Biomarkers of long-term radiation risk represent the second area of interest for the military. Biomarkers of risk require high sensitivity and specificity for the disease and insult but do not require rapid data turnaround. Biomarkers will help provide information for quick command decisions in the field, characterise long-term troop risks and identify early stages of radiation-induced diseases. This information provides major positive reassurances about individual exposures and risk that will minimise the physical and psychological impact of wartime radiation exposures.     

A slow wave investigation of working memory biases in mood disorders.

Mood-congruent working memory biases were examined in a delayed matching to sample paradigm using the slow wave (SW) event-related brain potential (ERP) component. Mood-congruent working memory biases, indexed by SW amplitudes, were demonstrated among individuals experiencing a major depressive episode (MDE) and nondepressed controls but not individuals with dysthymia. However, analyses of symptom severity demonstrated that those with dysthymia exhibited significantly less negative SW amplitudes with increasing depressive mood severity, whereas individuals with major depression demonstrated more negative SW amplitudes with increasing depressive mood severity. These results are discussed in the context of diagnostic specificity for cognitive biases associated with working memory of mood-disordered individuals. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Fatigue behavior of Zr52.5Al10Ti5Cu17.9Ni14.6 bulk metallic glass

In the present study, fatigue tests were conducted on a zirconium-based bulk metallic glass (BMG), BMG-11 (Zr–10Al–5Ti–17.9Cu–14.6Ni, atomic percent), in air and vacuum to elucidate the possible environmental effects. In air, the fatigue endurance limit and the fatigue ratio were found to be 907 MPa and 0.53, respectively. These values are better than many conventional high-strength crystalline alloys. Unexpectedly, the fatigue lifetimes in vacuum were found to be lower than in air. Additional testing indicated that dissociation of residual water vapor to atomic hydrogen in the vacuum via a hot-tungsten-filament ionization gauge, and subsequent hydrogen embrittlement of the BMG-11, could have been a factor causing the lower fatigue lifetimes observed in vacuum.     

选择高集成度DSP的关键因素

在系统级上,工程师习惯于在三个“P”即:性能(Performance),功率(Power)消耗和价格(Price)之间权衡利弊。在DSP高度集成的今天,有关外围器件的第四个“P”可能影响和此前三个“P”相关的决定,而且它增加了一套新的设计考虑因素。要选择合适的DSP,设计人员必须选择具备最能满足整个系统要求、最佳外围器件组合的SoC(System-on-Chip)。另外,由于现在可以把模拟和射频电路象数字逻辑电路一样集成在同一个芯片上,则选择片上外围器件的范围比以前更广泛。本文列举了部分关键问题,讨论了可能对工程师在系统设计方面有影响的因素。 系统需求 系统设计的第一项任务就是分析整个系统的需求,这关系到其他所有决定。应用是否支持音频、视频或射频方面的工作?功率是多少?使用哪个标准?需要其他什么功能?是否支持某种电源非常宝贵的移动器件?这些基本的需求经常决定着哪个外围器件满足系统需求。 举例来说,电信基础设施系统需要各种各样用于便携式媒体或者无线手持终端的外围器件。尽管电信系统和其他应用领域存在交集,但电信基础设施设计师主要关注高信道密度和 单通道低成本时的吞吐量。单通道功 率也是电信基础设施的一...     

Predictor@Home: A "Protein Structure Prediction Supercomputer' Based on Global Computing

Predicting the structure of a protein from its amino acid sequence is a complex process, the understanding of which could be used to gain new insight into the nature of protein functions or provide targets for structure-based design of drugs to treat new and existing diseases. While protein structures can be accurately modeled using computational methods based on all-atom physics-based force fields including implicit solvation, these methods require extensive sampling of native-like protein conformations for successful prediction and, consequently, they are often limited by inadequate computing power. To address this problem, we developed Predictor@Home, a "structure prediction supercomputer” powered by the Berkeley Open Infrastructure for Network Computing (BOINC) framework and based on the global computing paradigm (i.e., volunteered computing resources interconnected to the Internet and owned by the public). In this paper, we describe the protocol we employed for protein structure prediction and its integration into a global computing architecture based on public resources. We show how Predictor@Home significantly improved our ability to predict protein structures by increasing our sampling capacity by one to two orders of magnitude.