Engineering source/drain extension regions in nanoscale double gate (DG) SOI MOSFETs: Analytical model and design considerations

In this paper, we propose for the first time, an analytical model for short channel effects in nanoscale source/drain extension region engineered double gate (DG) SOI MOSFETs. The impact of (i) lateral source/drain doping gradient (d), (ii) spacer width (s), (iii) spacer to doping gradient ratio (s/d) and (iv) silicon film thickness (T-si), on short channel effects - threshold voltage (V-th) and subthreshold slope (S), on-current (I-on), off-current (I-on) and I-on/I-off is extensively analysed by using the analytical model and 2D device simulations. The results of the analytical model confirm well with simulated data over the entire range of spacer widths, doping gradients and effective channel lengths. Results show that lateral source/drain doping gradient along with spacer width can not only effectively control short channel effects, thus presenting low off-current, but can also be optimised to achieve high values of on-currents. The present work provides valuable design insights in the performance of nanoscale DG Sol devices with optimal source/drain engineering and serves as a tool to optimise important device and technological parameters for 65 nm technology node and below. (c) 2006 Elsevier Ltd. All rights reserved.

Imidazo[4,5-f]-1,10-phenanthrolines: Versatile ligands for the design of metallomesogens

2-Aryl-substituted imidazo[4,5-f]-1,10-phenanthrolines were used as building blocks for metal-containing liquid crystals (metallomesogens). Imidazo[4,5-f]-1,10-phenanthrolines are versatile ligands because they can form stable complexes with various d-block transition metals, including platinum(II) and rhenium(I), as well as with lanthanide(III) and uranyl ions and they can easily be structurally modified by a judicious choice of benzaldehyde precursor. None of the ligands designed for this study were liquid-crystalline. However, mesomorphism could be induced by their coordination to various metallic fragments. The thermal behavior of the metal complexes depended on the metal-to-ligand ratio and the substitution pattern of the coordinating ligands. Complexes with a metal-to-ligand ratio of 1:1 [ML, with M = Pt(II), Re(I)] were not liquid-crystal line. The lanthanide(III) complexes with a metal-to-ligand ratio of 1:2 [ML2 with M = Ln(III)] formed an enantiotropic cubic mesophase or were not liquid-crystalline, depending on the nature of the lanthanide(III) ion and the substitution pattern of the ligands. A 1:3 uranyl complex of the type [ML3](2+) exhibited a hexagonal columnar mesophase over a broad temperature range. Self-assembled monolayers of a europium(III) complex were investigated by scanning tunneling microscopy, which revealed that the complex formed well-ordered structures over long distances at the 1-octanoic acid-graphite interface. The rhenium(I) complexes and the europium(III) complexes with 2-thenoyl-trifluoroacetonate or dibenzoylmethanate and imidazo[4,5-f]-1,10-phenanthroline showed good luminescence properties.

Learning design contingent valuation (LDCV): NOAA guidelines, preference learning and coherent arbitrariness

We extend the contingent valuation (CV) method to test three differing conceptions of individuals' preferences as either (i) a-priori well-formed or readily divined and revealed through a single dichotomous choice question (as per the NOAA CV guidelines [K. Arrow, R. Solow, P.R. Portney, E.E. Learner, R. Radner, H. Schuman, Report of the NOAA panel on contingent valuation, Fed. Reg. 58 (1993) 4601-4614]); (ii) learned or 'discovered' through a process of repetition and experience [J.A. List, Does market experience eliminate market anomalies? Q. J. Econ. (2003) 41-72; C.R. Plott, Rational individual behaviour in markets and social choice processes: the discovered preference hypothesis, in: K. Arrow, E. Colombatto, M. Perleman, C. Schmidt (Eds.), Rational Foundations of Economic Behaviour, Macmillan, London, St. Martin's, New York, 1996, pp. 225-250]; (iii) internally coherent but strongly influenced by some initial arbitrary anchor [D. Ariely, G. Loewenstein, D. Prelec, 'Coherent arbitrariness': stable demand curves without stable preferences, Q. J. Econ. 118(l) (2003) 73-105]. Findings reject both the first and last of these conceptions in favour of a model in which preferences converge towards standard expectations through a process of repetition and learning. In doing so, we show that such a 'learning design CV method overturns the 'stylised facts' of bias and anchoring within the double bound dichotomous choice elicitation format. (C) 2007 Elsevier Inc. All rights reserved.

Prognostic Significance of TRAIL Signaling Molecules in Stage II and III Colorectal Cancer

Purpose: We previously found that cellular FLICE-inhibitory protein (c-FLIP), caspase 8, and tumor necrosis factor–related apoptosis-inducing ligand (TRAIL) receptor 2 (DR5) are major regulators of cell viability and chemotherapy-induced apoptosis in colorectal cancer. In this study, we determined the prognostic significance of c-FLIP, caspase 8, TRAIL and DR5 expression in tissues from patients with stage II and III colorectal cancer.

Experimental Design: Tissue microarrays were constructed from matched normal and tumor tissue derived from patients (n = 253) enrolled in a phase III trial of adjuvant 5-fluorouracil–based chemotherapy versus postoperative observation alone. TRAIL, DR5, caspase 8, and c-FLIP expression levels were determined by immunohistochemistry.

Results: Colorectal tumors displayed significantly higher expression levels of c-FLIP (P < 0.001), caspase 8 (P = 0.01), and DR5 (P < 0.001), but lower levels of TRAIL (P < 0.001) compared with matched normal tissue. In univariate analysis, higher TRAIL expression in the tumor was associated with worse overall survival (P = 0.026), with a trend to decreased relapse-free survival (RFS; P = 0.06), and higher tumor c-FLIP expression was associated with a significantly decreased RFS (P = 0.015). Using multivariate predictive modeling for RFS in all patients and including all biomarkers, age, treatment, and stage, we found that the model was significant when the mean tumor c-FLIP expression score and disease stage were included (P < 0.001). As regards overall survival, the overall model was predictive when both TRAIL expression and disease stage were included (P < 0.001).

Conclusions: High c-FLIP and TRAIL expression may be independent adverse prognostic markers in stage II and III colorectal cancer and might identify patients most at risk of relapse.

Tissue biomarker development in a multicentre trial context: a feasibility study on the PETACC3 stage II and III colon cancer adjuvant treatment trial.

Purpose: We evaluated the feasibility of biomarker development in the context of multicenter clinical trials.

Experimental Design: Formalin-fixed, paraffin-embedded (FFPE) tissue samples were collected from a prospective adjuvant colon cancer trial (PETACC3). DNA was isolated from tumor as well as normal tissue and used for analysis of microsatellite instability, KRAS and BRAF genotyping, UGT1A1 genotyping, and loss of heterozygosity of 18 q loci. Immunohistochemistry was used to test expression of TERT, SMAD4, p53, and TYMS. Messenger RNA was retrieved and tested for use in expression profiling experiments.

Results: Of the 3,278 patients entered in the study, FFPE blocks were obtained from 1,564 patients coming from 368 different centers in 31 countries. In over 95% of the samples, genomic DNA tests yielded a reliable result. Of the immmunohistochemical tests, p53 and SMAD4 staining did best with reliable results in over 85% of the cases. TERT was the most problematic test with 46% of failures, mostly due to insufficient tissue processing quality. Good quality mRNA was obtained, usable in expression profiling experiments.

Conclusions: Prospective clinical trials can be used as framework for biomarker development using routinely processed FFPE tissues. Our results support the notion that as a rule, translational studies based on FFPE should be included in prospective clinical trials.

Oligomerisation of linear 1-olefins using a chlorogallate(III) ionic liquid

A Lewis acidic chlorogallate(III) ionic liquid, 1-ethyl-3-methylimidazolium hepta-chlorodigallate(III), [C(2)mim][Ga2Cl7], was successfully used to oligomerise 1-pentene. The influence of temperature, time, catalyst concentration, and stirring rate on conversion and product distribution was modelled using a design of experiment (DoE) approach (chemometrics). The process was optimised for lubricant base oils production; the C20-C50 fraction (where Cn indicates the number of carbons in the oligomer) was maximised, while the heavier oligomer fraction (>C50) was minimised.

Design and implementation of the symmetrically extended 2-D wavelet transform

The inclusion of the Discrete Wavelet Transform in the JPEG-2000 standard has added impetus to the research of hardware architectures for the two-dimensional wavelet transform. In this paper, a VLSI architecture for performing the symmetrically extended two-dimensional transform is presented. This architecture conforms to the JPEG-2000 standard and is capable of near-optimal performance when dealing with the image boundaries. The architecture also achieves efficient processor utilization. Implementation results based on a Xilinx Virtex-2 FPGA device are included.

Influence of the experimental design of gene expression studies on the inference of gene regulatory networks: environmental factors

The inference of gene regulatory networks gained within recent years a considerable interest in the biology and biomedical community. The purpose of this paper is to investigate the influence that environmental conditions can exhibit on the inference performance of network inference algorithms. Specifically, we study five network inference methods, Aracne, BC3NET, CLR, C3NET and MRNET, and compare the results for three different conditions: (I) observational gene expression data: normal environmental condition, (II) interventional gene expression data: growth in rich media, (III) interventional gene expression data: normal environmental condition interrupted by a positive spike-in stimulation. Overall, we find that different statistical inference methods lead to comparable, but condition-specific results. Further, our results suggest that non-steady-state data enhance the inferability of regulatory networks.

Evaluating Many Treatments and Biomarkers in Oncology: A New Design

There is a pressing need for more-efficient trial designs for biomarker-stratified clinical trials. We suggest a new approach to trial design that links novel treatment evaluation with the concurrent evaluation of a biomarker within a confirmatory phase II/III trial setting. We describe a new protocol using this approach in advanced colorectal cancer called FOCUS4. The protocol will ultimately answer three research questions for a number of treatments and biomarkers: (1) After a period of first-line chemotherapy, do targeted novel therapies provide signals of activity in different biomarker-defined populations? (2) If so, do these definitively improve outcomes? (3) Is evidence of activity restricted to the biomarker-defined groups? The protocol randomizes novel agents against placebo concurrently across a number of different biomarker-defined population-enriched cohorts: BRAF mutation; activated AKT pathway: PI3K mutation/absolute PTEN loss tumors; KRAS and NRAS mutations; and wild type at all the mentioned genes. Within each biomarker-defined population, the trial uses a multistaged approach with flexibility to adapt in response to planned interim analyses for lack of activity. FOCUS4 is the first test of a protocol that assigns all patients with metastatic colorectal cancer to one of a number of parallel population-enriched, biomarker-stratified randomized trials. Using this approach allows questions regarding efficacy and safety of multiple novel therapies to be answered in a relatively quick and efficient manner, while also allowing for the assessment of biomarkers to help target treatment.

Experimental design and batch experiments for optimization of Cr(VI) removal from aqueous solutions by hydrous cerium oxide nanoparticles

Hydrous cerium oxide (HCO) was synthesized by intercalation of solutions of cerium(III) nitrate and sodium hydroxide and evaluated as an adsorbent for the removal of hexavalent chromium from aqueous solutions. Simple batch experiments and a 2⁵ factorial experimental design were employed to screen the variables affecting Cr(VI) removal efficiency. The effects of the process variables; solution pH, initial Cr(VI) concentration, temperature, adsorbent dose and ionic strength were examined. Using the experimental results, a linear mathematical model representing the influence of the different variables and their interactions was obtained. Analysis of variance (ANOVA) demonstrated that Cr(VI) adsorption significantly increases with decreased solution pH, initial concentration and amount of adsorbent used (dose), but slightly decreased with an increase in temperature and ionic strength. The optimization study indicates 99% as the maximum removal at pH 2, 20 °C, 1.923 mM of metal concentration and a sorbent dose of 4 g/dm³. At these optimal conditions, Langmuir, Freundlich and Redlich–Peterson isotherm models were obtained. The maximum adsorption capacity of Cr(VI) adsorbed by HCO was 0.828 mmol/g, calculated by the Langmuir isotherm model. Desorption of chromium indicated that the HCO adsorbent can be regenerated using NaOH solution 0.1 M (up to 85%). The adsorption interactions between the surface sites of HCO and the Cr(VI) ions were found to be a combined effect of both anion exchange and surface complexation with the formation of an inner-sphere complex.

Testing preference formation in learning design contingent valuation (LDCV) using advanced information and repetitive treatments

Policymakers have largely replaced Single Bounded Discrete Choice (SBDC) valuation by the more statistically efficient repetitive methods; Double Bounded Discrete Choice (DBDC) and Discrete Choice Experiments (DCE) . Repetitive valuation permits classification into rational preferences: (i) a priori well-formed; (ii) consistent non-arbitrary values “discovered” through repetition and experience; (Plott, 1996; List 2003) and irrational preferences; (iii) consistent but arbitrary values as “shaped” by preceding bid level (Tufano, 2010; Ariely et al., 2003) and (iv) inconsistent and arbitrary values. Policy valuations should demonstrate behaviorally rational preferences. We outline novel methods for testing this in DBDC applied to renewable energy premiums in Chile.