Conjoint analysis to measure the perceived quality in volume rendering

Visualization algorithms can have a large number of parameters, making the space of possible rendering results rather high-dimensional. Only a systematic analysis of the perceived quality can truly reveal the optimal setting for each such parameter. However, an exhaustive search in which all possible parameter permutations are presented to each user within a study group would be infeasible to conduct. Additional complications may result from possible parameter co-dependencies. Here, we will introduce an efficient user study design and analysis strategy that is geared to cope with this problem. The user feedback is fast and easy to obtain and does not require exhaustive parameter testing. To enable such a framework we have modified a preference measuring methodology, conjoint analysis, that originated in psychology and is now also widely used in market research. We demonstrate our framework by a study that measures the perceived quality in volume rendering within the context of large parameter spaces.     

Mothers' Affect in the Homework Context: The Importance of Staying Positive.

This research investigated mothers' affect in the context of children's homework. Mothers (N=109) of children 8 to 12 years old were interviewed daily about their affect while interacting with children, their assistance with children's homework, and children's behavior while completing homework. At this time and 6 months later, children's motivational and emotional functioning was assessed. Although mothers' negative affect was lower than their positive affect, it was elevated on days their assistance with homework was high. This was accounted for by mothers' perceptions of children as helpless on days they provided heightened assistance. Mothers' positive affect in the homework context buffered children's motivational and emotional functioning against mothers' negative affect as well as children's helplessness. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Developing an Automated Enzyme Immunoassay for High-Throughput Screening of Bovine Serum Antibodies to Neospora Caninum

An enzyme-linked immunosorbent assay (ELISA) for Neospora caninum antibodies was automated with a robotic workstation, the Beckman Coulter Biomek 2000, to screen 200 bovine sera. Comparing these results with manually run ELISA data, a 95.92% agreement (K = 0.9592) between the two assays was obtained. The automated assay was specific and sensitive with excellent positive and negative predictive values. The results were repeatable and reproducible. The automation flexibility was high and the operation complexity was minimal. High-throughput screening (HTS) for bovine antibodies to Neospora caninum was achieved. The assay was developed according to the internationally recognized ISO17025 standard requirements.     

Neural network approach for multicriteria solid transportation problem

In this paper, we propose neural network approach for multicriteria solid transportation problems(STP). First we suggest a neural network architecture to solve single-objective STP according to augmented Lagrange multiplier method. Due to the massive computing unit-neurons and parallel mechanism of neural network approach can solve the large scale problem efficiently and optimal solution can be got. Then we transform the original multicriteria problem into a single objective problem by global criteria method and adopt the neural network approach to solve it. By this way we can get the satisfactory solution of the original problem. The procedure and efficiency of this approach are shown with numerical simulations.     

Neural network technique for fuzzy multiobjective linear programming

Neural Network(NN) is well-known as one of powerful computing tools to solve optimization problems. Due to the massive computing unit-neurons and parallel mechanism of neural network approach we can solve the large-scale problem efficiently and optimal solution can be gotten. In this paper, we intoroduce improvement of the two-phase approach for solving fuzzy multiobjectve linear programming problem with both fuzzy objectives and constraints and we propose a new neural network technique for solving fuzzy multiobjective linear programming problems. The procedure and efficiency of this approach are shown with numerical simulations.     

Feedback passivity of nonlinear discrete-time systems with direct input-output link

This paper is devoted to the study of the feedback passivity property in nonlinear discrete-time systems. The relative degree and zero dynamics of the non-passive system are related to the feedback passivity of the system. Two main results are presented. First, some relative degree-related properties of passive systems in general form are stated. Second, sufficient conditions in order to render a multiple-input multiple-output (MIMO) system passive by means of a static state feedback control law are obtained.     

Daily recovery experiences: The role of volunteer work during leisure time.

This study focused on the role of volunteer work for daily recovery from work. In a 1-week diary study with 166 employees, we assessed the amount of time spent on volunteer work during leisure time, and the recovery facets of psychological detachment from work (i.e., mentally switching off from work), mastery experiences (i.e., pursuing challenging activities), and community experiences (i.e., cultivating relationships) every day before participants went to bed. Results from hierarchical linear modeling (n = 529 days) showed volunteer work during leisure time to be positively related to mastery experiences and community experiences suggesting volunteer work to contribute to successful recovery by creating new resources. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Synthesis and Biological Evaluation of Small Molecules as Potential Anticancer Multitarget Agents

Twenty-six triazole-based derivatives were designed for targeting both PD-L1 (programmed death receptor ligand 1) and VEGFR-2 (vascular endothelial growth factor receptor 2). These compounds were synthetized and biologically evaluated as multitarget inhibitors of VEGFR-2, PD-L1 and c-Myc proteins. The antiproliferative activity of these molecules on several tumor cell lines (HT-29, A-549, and MCF-7) and on the non-tumor cell line HEK-293 was determined. The effects on the abovementioned biological targets were evaluated for some selected compounds. Compound 23, bearing a p-chlorophenyl group, showed better results than sorafenib in regard to the downregulation of VEGFR-2 and a similar effect to BMS-8 on both PD-L1 and c-Myc proteins. The antiangiogenic and antivascular activities of chloro derivatives were also established by endothelial microtube formation assay on Matrigel^®.