Optimization of the distance between source and substrate for device-grade SnS films grown by the thermal evaporation technique

Tin monosulfide (SnS) films with varying distance between the source and substrate (DSS) were prepared by the thermal evaporation technique at a temperature of 300 degrees C to investigate the effect of the DSS on the physical properties. The physical properties of the as-deposited films are strongly influenced by the variation of DSS. The thickness, Sn to S at.% ratio, grain size, and root mean square (rms) roughness of the films decreased with the increase of DSS. The films grown at DSS = 10 and 15 cm exhibited nearly single-crystalline nature with low electrical resistivity. From Hall-effect measurements, it is observed that the films grown at DSS <= 15 cm have p-type conduction and the films grown at higher distances have n-type conduction due to the variation of the Sn/S ratio. The films grown at DSS = 15 cm showed higher optical band gap of 1.36 eV as compared with the films grown at other distances. The effect of the DSS on the physical properties of SnS films is discussed and reported.

Vector evaluated particle swarm optimization (VEPSO) for multi-objective design optimization of composite structures

We present a generic method/model for multi-objective design optimization of laminated composite components, based on vector evaluated particle swarm optimization (VEPSO) algorithm. VEPSO is a novel, co-evolutionary multi-objective variant of the popular particle swarm optimization algorithm (PSO). In the current work a modified version of VEPSO algorithm for discrete variables has been developed and implemented successfully for the, multi-objective design optimization of composites. The problem is formulated with multiple objectives of minimizing weight and the total cost of the composite component to achieve a specified strength. The primary optimization variables are - the number of layers, its stacking sequence (the orientation of the layers) and thickness of each layer. The classical lamination theory is utilized to determine the stresses in the component and the design is evaluated based on three failure criteria; failure mechanism based failure criteria, Maximum stress failure criteria and the Tsai-Wu failure criteria. The optimization method is validated for a number of different loading configurations - uniaxial, biaxial and bending loads. The design optimization has been carried for both variable stacking sequences, as well fixed standard stacking schemes and a comparative study of the different design configurations evolved has been presented. (C) 2007 Elsevier Ltd. All rights reserved.

Visibility volumes for interactive path optimization

We describe a real-time system that supports design of optimal flight paths over terrains. These paths either maximize view coverage or minimize vehicle exposure to ground. A volume-rendered display of multi-viewpoint visibility and a haptic interface assists the user in selecting, assessing, and refining the computed flight path. We design a three-dimensional scalar field representing the visibility of a point above the terrain, describe an efficient algorithm to compute the visibility field, and develop visual and haptic schemes to interact with the visibility field. Given the origin and destination, the desired flight path is computed using an efficient simulation of an articulated rope under the influence of the visibility gradient. The simulation framework also accepts user input, via the haptic interface, thereby allowing manual refinement of the flight path.

Cilengitide combined with cetuximab and platinum-based chemotherapy as first-line treatment in advanced non-small-cell lung cancer (NSCLC) patients: Results of an open-label, randomized, controlled phase II study (CERTO)

Background: This multicentre, open-label, randomized, controlled phase II study evaluated cilengitide in combination with cetuximab and platinum-based chemotherapy, compared with cetuximab and chemotherapy alone, as first-line treatment of patients with advanced non-small-cell lung cancer (NSCLC). Patients and methods: Patients were randomized 1:1:1 to receive cetuximab plus platinum-based chemotherapy alone (control), or combined with cilengitide 2000 mg 1×/week i.v. (CIL-once) or 2×/week i.v. (CIL-twice). A protocol amendment limited enrolment to patients with epidermal growth factor receptor (EGFR) histoscore ≥200 and closed the CIL-twice arm for practical feasibility issues. Primary end point was progression-free survival (PFS; independent read); secondary end points included overall survival (OS), safety, and biomarker analyses. A comparison between the CIL-once and control arms is reported, both for the total cohorts, as well as for patients with EGFR histoscore ≥200. Results: There were 85 patients in the CIL-once group and 84 in the control group. The PFS (independent read) was 6.2 versus 5.0 months for CIL-once versus control [hazard ratio (HR) 0.72; P = 0.085]; for patients with EGFR histoscore ≥200, PFS was 6.8 versus 5.6 months, respectively (HR 0.57; P = 0.0446). Median OS was 13.6 for CIL-once versus 9.7 months for control (HR 0.81; P = 0.265). In patients with EGFR ≥200, OS was 13.2 versus 11.8 months, respectively (HR 0.95; P = 0.855). No major differences in adverse events between CIL-once and control were reported; nausea (59% versus 56%, respectively) and neutropenia (54% versus 46%, respectively) were the most frequent. There was no increased incidence of thromboembolic events or haemorrhage in cilengitide-treated patients. αvβ3 and αvβ5 expression was neither a predictive nor a prognostic indicator. Conclusions: The addition of cilengitide to cetuximab/chemotherapy indicated potential clinical activity, with a trend for PFS difference in the independent-read analysis. However, the observed inconsistencies across end points suggest additional investigations are required to substantiate a potential role of other integrin inhibitors in NSCLC treatment.

Dacomitinib versus erlotinib in patients with EGFR-mutated advanced nonsmall-cell lung cancer (NSCLC): Pooled subset analyses from two randomized trials

Background: The irreversible epidermal growth factor receptor (EGFR) inhibitors have demonstrated efficacy in NSCLC patients with activating EGFR mutations, but it is unknown if they are superior to the reversible inhibitors. Dacomitinib is an oral, small-molecule irreversible inhibitor of all enzymatically active HER family tyrosine kinases. Methods: The ARCHER 1009 (NCT01360554) and A7471028 (NCT00769067) studies randomized patients with locally advanced/metastatic NSCLC following progression with one or two prior chemotherapy regimens to dacomitinib or erlotinib. EGFR mutation testing was performed centrally on archived tumor samples. We pooled patients with exon 19 deletion and L858R EGFR mutations from both studies to compare the efficacy of dacomitinib to erlotinib. Results: One hundred twenty-one patients with any EGFR mutation were enrolled; 101 had activating mutations in exon 19 or 21. For patients with exon19/21 mutations, the median progression-free survival was 14.6 months [95% confidence interval (CI) 9.0–18.2] with dacomitinib and 9.6 months (95% CI 7.4–12.7) with erlotinib [unstratified hazard ratio (HR) 0.717 (95% CI 0.458–1.124), two-sided log-rank, P = 0.146]. The median survival was 26.6 months (95% CI 21.6–41.5) with dacomitinib versus 23.2 months (95% CI 16.0–31.8) with erlotinib [unstratified HR 0.737 (95% CI 0.431–1.259), two-sided log-rank, P = 0.265]. Dacomitinib was associated with a higher incidence of diarrhea and mucositis in both studies compared with erlotinib. Conclusions: Dacomitinib is an active agent with comparable efficacy to erlotinib in the EGFR mutated patients. The subgroup with exon 19 deletion had favorable outcomes with dacomitinib. An ongoing phase III study will compare dacomitinib to gefitinib in first-line therapy of patients with NSCLC harboring common activating EGFR mutations (ARCHER 1050; NCT01774721). Clinical trials number: ARCHER 1009 (NCT01360554) and A7471028 (NCT00769067).

Optimization of friction stir welding parameters for dissimilar aluminum alloys

Assembly consisting of cast and wrought aluminum alloys has wide spread application in defense and aero space industries. For the efficacious use of the transition joints, the weld should have adequate strength and formability. In the present investigation, A356 and 6061 aluminum alloys were friction stir welded under tool rotational speed of 1000-1400 rpm and traversing speed of 80-240 mm/min, keeping other parameters same. The variable process window is responsible for the change in total heat input and cooling rate during welding. Structural characterization of the bonded assemblies exhibits recovery-recrystallization in the stirring zone and breaking of coarse eutectic network of Al-Si. Dispersion of fine Si rich particles, refinement of 6061 grain size, low residual stress level and high defect density within weld nugget contribute towards the improvement in bond strength. Lower will be the tool rotational and traversing speed, more dominant will be the above phenomena. Therefore, the joint fabricated using lowest tool traversing and rotational speed, exhibits substantial improvement in bond strength (similar to 98% of that of 6061 alloy), which is also maximum with respect to others. (C) 2010 Elsevier Ltd. All rights reserved.

Investigating the effect of Eye Movement Desensitization and Reprocessing (EMDR) on postoperative pain intensity in adolescents undergoing surgery: A randomized controlled trial

Aim To investigate the efficacy of Eye Movement Desensitization and Reprocessing for postoperative pain management in adolescents. Background Eye Movement Desensitization and Reprocessing is an inexpensive, non-pharmacological intervention that has successfully been used to treat chronic pain. It holds promise in the treatment of acute, postsurgical pain based on its purported effects on the brain and nervous system. Design A randomized controlled trial was used. Methods Fifty-six adolescent surgical patients aged between 12-18 years were allocated to gender-balanced Eye Movement Desensitization and Reprocessing (treatment) or non-Eye Movement Desensitization and Reprocessing (control) groups. Pain was measured using the Wong-Baker FACES® Pain Rating Scale (WBFS) before and after the intervention (or non-intervention for the control group). Findings A Wilcoxon signed-rank test demonstrated that the Eye Movement Desensitization and Reprocessing group experienced a significant reduction in pain intensity after treatment intervention, whereas the control group did not. Additionally, a Mann–Whitney U-test showed that, while there was no significant difference between the two groups at time 1, there was a significant difference in pain intensity between the two groups at time 2, with the Eye Movement Desensitization and Reprocessing group experiencing lower levels of pain. Conclusion These results suggest that Eye Movement Desensitization and Reprocessing may be an effective treatment modality for postoperative pain.

Vector Evaluated Particle Swarm Optimization (VEPSO) of Supersonic Ejector for Hydrogen Fuel Cells

Fuel cells are emerging as alternate green power producers for both large power production and for use in automobiles. Hydrogen is seen as the best option as a fuel; however, hydrogen fuel cells require recirculation of unspent hydrogen. A supersonic ejector is an apt device for recirculation in the operating regimes of a hydrogen fuel cell. Optimal ejectors have to be designed to achieve best performances. The use of the vector evaluated particle swarm optimization technique to optimize supersonic ejectors with a focus on its application for hydrogen recirculation in fuel cells is presented here. Two parameters, compression ratio and efficiency, have been identified as the objective functions to be optimized. Their relation to operating and design parameters of ejector is obtained by control volume based analysis using a constant area mixing approximation. The independent parameters considered are the area ratio and the exit Mach number of the nozzle. The optimization is carried out at a particularentrainment ratio and results in a set of nondominated solutions, the Pareto front. A set of such curves can be used for choosing the optimal design parameters of the ejector.

The selection, optimization, and compensation model in the work context: A systematic review and meta-analysis of two decades of research

Over the past two decades, the selection, optimization, and compensation (SOC) model has been applied in the work context to investigate antecedents and outcomes of employees' use of action regulation strategies. We systematically review, meta-analyze, and critically discuss the literature on SOC strategy use at work and outline directions for future research and practice. The systematic review illustrates the breadth of constructs that have been studied in relation to SOC strategy use, and that SOC strategy use can mediate and moderate relationships of person and contextual antecedents with work outcomes. Results of the meta-analysis show that SOC strategy use is positively related to age (rc = .04), job autonomy (rc = .17), self-reported job performance (rc = .23), non-self-reported job performance (rc = .21), job satisfaction (rc = .25), and job engagement (rc = .38), whereas SOC strategy use is not significantly related to job tenure, job demands, and job strain. Overall, our findings underline the importance of the SOC model for the work context, and they also suggest that its measurement and reporting standards need to be improved to become a reliable guide for future research and organizational practice.

Strength design of composite beam using gradient and particle swarm optimization

This work addresses the optimum design of a composite box-beam structure subject to strength constraints. Such box-beams are used as the main load carrying members of helicopter rotor blades. A computationally efficient analytical model for box-beam is used. Optimal ply orientation angles are sought which maximize the failure margins with respect to the applied loading. The Tsai-Wu-Hahn failure criterion is used to calculate the reserve factor for each wall and ply and the minimum reserve factor is maximized. Ply angles are used as design variables and various cases of initial starting design and loadings are investigated. Both gradient-based and particle swarm optimization (PSO) methods are used. It is found that the optimization approach leads to the design of a box-beam with greatly improved reserve factors which can be useful for helicopter rotor structures. While the PSO yields globally best designs, the gradient-based method can also be used with appropriate starting designs to obtain useful designs efficiently. (C) 2006 Elsevier Ltd. All rights reserved.

Pareto-optimal solutions for multi-objective optimization of fed-batch bioreactors using nondominated sorting genetic algorithm

Many optimal control problems are characterized by their multiple performance measures that are often noncommensurable and competing with each other. The presence of multiple objectives in a problem usually give rise to a set of optimal solutions, largely known as Pareto-optimal solutions. Evolutionary algorithms have been recognized to be well suited for multi-objective optimization because of their capability to evolve a set of nondominated solutions distributed along the Pareto front. This has led to the development of many evolutionary multi-objective optimization algorithms among which Nondominated Sorting Genetic Algorithm (NSGA and its enhanced version NSGA-II) has been found effective in solving a wide variety of problems. Recently, we reported a genetic algorithm based technique for solving dynamic single-objective optimization problems, with single as well as multiple control variables, that appear in fed-batch bioreactor applications. The purpose of this study is to extend this methodology for solution of multi-objective optimal control problems under the framework of NSGA-II. The applicability of the technique is illustrated by solving two optimal control problems, taken from literature, which have usually been solved by several methods as single-objective dynamic optimization problems. (C) 2004 Elsevier Ltd. All rights reserved.

A novel approach for large-scale polypeptide folding based on elastic networks using continuous optimization

We present a new computationally efficient method for large-scale polypeptide folding using coarse-grained elastic networks and gradient-based continuous optimization techniques. The folding is governed by minimization of energy based on Miyazawa–Jernigan contact potentials. Using this method we are able to substantially reduce the computation time on ordinary desktop computers for simulation of polypeptide folding starting from a fully unfolded state. We compare our results with available native state structures from Protein Data Bank (PDB) for a few de-novo proteins and two natural proteins, Ubiquitin and Lysozyme. Based on our simulations we are able to draw the energy landscape for a small de-novo protein, Chignolin. We also use two well known protein structure prediction software, MODELLER and GROMACS to compare our results. In the end, we show how a modification of normal elastic network model can lead to higher accuracy and lower time required for simulation.

A four-timescale algorithm for constrained stochastic optimization of RED

The overall performance of random early detection (RED) routers in the Internet is determined by the settings of their associated parameters. The non-availability of a functional relationship between the RED performance and its parameters makes it difficult to implement optimization techniques directly in order to optimize the RED parameters. In this paper, we formulate a generic optimization framework using a stochastically bounded delay metric to dynamically adapt the RED parameters. The constrained optimization problem thus formulated is solved using traditional nonlinear programming techniques. Here, we implement the barrier and penalty function approaches, respectively. We adopt a second-order nonlinear optimization framework and propose a novel four-timescale stochastic approximation algorithm to estimate the gradient and Hessian of the barrier and penalty objectives and update the RED parameters. A convergence analysis of the proposed algorithm is briefly sketched. We perform simulations to evaluate the performance of our algorithm with both barrier and penalty objectives and compare these with RED and a variant of it in the literature. We observe an improvement in performance using our proposed algorithm over RED, and the above variant of it.

Scheduling parallel batch processors with incompatible job families using ant colony optimization

The present work concerns with the static scheduling of jobs to parallel identical batch processors with incompatible job families for minimizing the total weighted tardiness. This scheduling problem is applicable in burn-in operations and wafer fabrication in semiconductor manufacturing. We decompose the problem into two stages: batch formation and batch scheduling, as in the literature. The Ant Colony Optimization (ACO) based algorithm called ATC-BACO algorithm is developed in which ACO is used to solve the batch scheduling problems. Our computational experimentation shows that the proposed ATC-BACO algorithm performs better than the available best traditional dispatching rule called ATC-BATC rule.

Protein sequence design on the basis of topology optimization techniques -Using continuous modeling of discrete amino acid types

The notion of optimization is inherent in protein design. A long linear chain of twenty types of amino acid residues are known to fold to a 3-D conformation that minimizes the combined inter-residue energy interactions. There are two distinct protein design problems, viz. predicting the folded structure from a given sequence of amino acid monomers (folding problem) and determining a sequence for a given folded structure (inverse folding problem). These two problems have much similarity to engineering structural analysis and structural optimization problems respectively. In the folding problem, a protein chain with a given sequence folds to a conformation, called a native state, which has a unique global minimum energy value when compared to all other unfolded conformations. This involves a search in the conformation space. This is somewhat akin to the principle of minimum potential energy that determines the deformed static equilibrium configuration of an elastic structure of given topology, shape, and size that is subjected to certain boundary conditions. In the inverse-folding problem, one has to design a sequence with some objectives (having a specific feature of the folded structure, docking with another protein, etc.) and constraints (sequence being fixed in some portion, a particular composition of amino acid types, etc.) while obtaining a sequence that would fold to the desired conformation satisfying the criteria of folding. This requires a search in the sequence space. This is similar to structural optimization in the design-variable space wherein a certain feature of structural response is optimized subject to some constraints while satisfying the governing static or dynamic equilibrium equations. Based on this similarity, in this work we apply the topology optimization methods to protein design, discuss modeling issues and present some initial results.