The thermal stability of nickel monosilicide (NiSi) is one of the important research topics in the area of nano-complementary metal oxide semiconductor. This paper reports the effect of germanium (Ge) ion implantation on the thermal stability of the NiSi/Si structure. High dose Ge ion implantation (>5x10(15) cm(-2)) can improve the thermal stability of the NiSi/Si structure. Ge ion implantation before NiSi formation results in a very smooth NiSi/Si interface due to Ge atom pileup at the NiSi/Si interface. This high concentration Ge layer reduces the interface energy so that the thermal stability can be improved. Both the phase-transformation temperature and agglomeration temperature are improved by 50-100 degrees C. The effects of Ge ion implantation on the NiSi-contacted n(+)-p and p(+)-n shallow junctions are also examined. Although fast Ni diffusion via the ion implantation induced defects is observed, better thermal stability can still be observed on the n(+)-p junction.

*Abstract*We, participants in the Translational Medicine Ontology activity of the World Wide Web Consortium’s Health Care and Life Sciences Interest Group ("http://esw.w3.org/topic/HCLSIG":http://esw.w3.org/topic/HCLSIG) and members of the National Center for Biomedical Ontology ("http://bioontology.org/":http://bioontology.org/), are developing a high-level, patient-centric ontology for translational medicine which will draw on existing domain ontologies and allow the integration of data throughout the drug development process.*Introduction*The pharmaceutical industry has historically focused on the development of novel blockbuster drugs. There is now an increasing focus on personalized medicines, requiring the right patients to receive the right drug at the right dose. In order to develop a tailored drug, manufacturers need to identify biomarkers that will indicate how a given patient will respond to a particular treatment. Biomarkers can also be used to demonstrate the comparative effectiveness of drugs, which is increasingly required by payers. Such translational medicine strategies require that traditionally separate data sets from early drug discovery through to patients in the clinical setting be integrated, and presented, queried and analyzed collectively. Ontologies can be used to drive such data integration and analysis; however, at present few ontologies exist that bridge genomics, chemistry and the medical domain.The Translational Medicine Ontology, an application ontology that bridges the diverse areas of translational medicine, draws on existing domain ontologies where appropriate and will provide a framework centered on less than 50 types of entities.*Goals*The Translational Medicine Ontology will facilitate data integration from diverse areas of translational medicine such as discovery research, hypothesis management, formulation, clinical trials, and clinical research. It will serve as a template for further ontology development, enabling scientists to answer interesting and currently difficult questions more easily, especially those about data that are typically hosted by different functional areas. The ontology will provide a framework for the modeling of patient-centric information, which is essential for tailoring drugs.*Methodology* We have identified a set of 17 roles played by people across health care and the life sciences and collected (1) relevant questions, (2) the entities that those questions involve, and (3) applicable extant domain ontologies.^1^ Types of entities include: disease, drug, patient, target, gene, risk, pathway, population, compound, phenotype, and treatment.Next steps will involve identifying use cases based on those questions, determining which entities to build into the ontology and aligning them with BFO,^2^ an upper-level ontology, to aid interoperability between domain ontologies. We will use one use case to test the Translational Medicine Ontology by building a data integration application based on it.*Conclusion*This project seeks to develop a patient-centric application ontology for translational medicine, as a collaborative effort between groups in industry and academia. The presentation will highlight our methodology, work to date, and future steps. ^1^. "W3C Site":http://esw.w3.org/topic/HCLSIG/PharmaOntology/Roles ^2^. "iformis":http://www.ifomis.org/bfo

The Western Wind and Solar Integration Study (WWSIS) is one of the world's largest regional integration studies to date. This paper discusses the creation of the wind dataset that will be the basis for assessing the operating impacts and mitigation options due to the variability and uncertainty of wind power on the utility grids. The dataset is based on output from a mesoscale numerical weather prediction (NWP) model, covering over 4 million square kilometers with a spatial resolution of approximately two-kilometers over a period of three years with a temporal resolution of 10 minutes. The mesoscale model dataset includes all the meteorological variables necessary to calculate wind energy production. Individual time series were produced for over 30 thousand locations representing more than 900 GW of potential wind power generation.

The effect of germanium (Ge) ion implantation on the thermal stability of NiSi/Si structure is studied. Ge implantation before NiSi formation results in a very smooth NiSi/Si interface. Both scanning electron microscope inspection and sheet resistance measurement proof that the sustainable process temperature of NiSi/Si structure can be improved by 50-100oC with high dosage Ge implantation at suitable energy. Ge implantation after NiSi formation has similar effect. These observations can be explained by the stress balance due to Ge pile-up at the NiSi/Si interface. Shallow n/p and p/n junctions with high thermal stability were also demonstrated using Ge implantation process.

The purpose of this article is to evaluate color Doppler imaging (CDI) as an adjunctive tool to gray-scale ultrasound (US) in the diagnosis of prostate cancer and to correlate CDI-positive lesions to cancer grade. We retrospectively analyzed 619 consecutive patients who underwent prostate US, CDI, and biopsy because of abnormal digital rectal examination results or prostate-specific antigen levels. All had directed (into a specific lesion) biopsies or directed biopsies along with systematic four-quadrant or sextant biopsies, or systematic biopsy alone. Color Doppler imaging was compared with gray-scale findings and histologic results. There were 222 (35.9%) biopsy-proven cancers (n = 197) or prostatic intraepithelial neoplasia (n = 25). Of these, 106 (47.7%) had color-flow abnormalities. Of these 106 patients, 26 (24.5%), or 11.7% of all cancer patients, had relatively normal gray-scale US findings but had focal CDI abnormalities as the method of identification. Overall, 76.9% of these were moderate to high Gleason grades and were considered clinically significant lesions. Color Doppler imaging can identify a large number (11.7%) of clinically significant prostate cancers that are poorly seen by gray-scale US. Positive lesions on CDI are of clinical importance because 76.9% are histologically, moderately, or poorly differentiated. We recommend that CDI be used in all diagnostic and biopsy-guided US examinations of the prostate.