Triphenyltin ortho-aminophenyl- and 2-pyridyl-thiolates: synthesis and in vitro antitumour activity

The synthesis, spectroscopic characterization and in vitro antitumour activity of two triorganotin compounds, triphenyltin ortho-aminophenylthiolate (1) and triphenyltin 2-pyridylthiolate, compound (2) are reported. The structure of 1 is confirmed by X-ray diffraction, with the tin atom in a distorted tetrahedral geometry because of monodentate coordination, as a thiolate (Sn-S 2.431(2) A), of the ortho-aminophenylthiolate ligand. The in vitro antitumour activities of 1 and 2, against a number of cell lines, are comparable to those exhibited by methotrexate and doxorubicin, and higher than those of carboplatin and cisplatin.     

Assessing the Attractiveness of Volatile Plant Compounds to Western Flower Thrips Frankliniella occidentalis

The responses of walking adult female western flower thrips, Frankliniella occidentalis, to plant volatiles at several concentrations were investigated in a Y-shaped glass tube olfactometer. The simple experimental design allowed comparing the effect of numerous volatiles and differentiated clearly between attractive and repellent compounds. Western flower thrips were attracted by the benzenoids benzaldehyde and pand o-anisaldehyde; the monoterpenes geraniol, nerol, linalool, and (+)-citronellol; the sesquiterpene (E)--farnesene, eugenol, and 3-phenylpropionaldehyde; two phenylpropanoids; and the nonfloral odor ethyl nicotinate. p-Anisaldehyde, nerol, ethyl nicotinate, and (E)--farnesene elicited positive responses at several concentrations; all other volatiles were attractive at a specific concentration. Salicylaldehyde, a benzenoid, elicited negative responses at two concentrations. Experimental series with several other volatiles belonging to the above mentioned chemical groups and the essential oils from rose and geranium did not result in either clearly positive or negative responses by tested thrips.     

Funktionalität von Lecithinen

Functionality of lecithins. In industry the functional emulsifying power of soya lecithin has a great technical and commercial importance, while egg lecithin has taken an interesting market niche. The requirements on consistent emulsifying, stabilizing and nutritional properties can be achieved by adjustment of standard qualities and a range of lecithin modifications: Enzymatic hydrolysis, acetylation and hydroxylation give lecithins with increased hydrophilicity and subsequently improved oil-in-water emulsifying properties. Alcohol fractionation, sometimes combined with chromatographic isolation, divides crude lecithin in specific phospholipid fractions, yielding an optimal functionality in specific product applications. Oil free “pure” lecithins in powder and granular form are used because of convenient dosage, neutral taste and enhanced O/W emulsifying performance. Combinations of the processes give a vaste range of tailor made special lecithins with different hydrophilic-lipophilic balance properties in food, feed, pharmaceutical, cosmetic and technical industries.     

Role of Grammatical Gender and Semantics in German Word Production.

Semantic substitution errors (e.g., saying "arm" when "leg" is intended) are among the most common types of errors occurring during spontaneous speech. It has been shown that grammatical gender of German target nouns is preserved in the errors (E. Mane, 1999). In 3 experiments, the authors explored different accounts of the grammatical gender preservation effect in German. In all experiments, semantic substitution errors were induced using a continuous naming paradigm. In Experiment 1, it was found that gender preservation disappeared when speakers produced bare nouns. Gender preservation was found when speakers produced phrases with determiners marked for gender (Experiment 2) but not when the produced determiners were not marked for gender (Experiment 3). These results are discussed in the context of models of lexical retrieval during production. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Aurama: caregiver awareness for living independently with an augmented picture frame display

Aurama is a system designed to provide peace of mind and a sense of connectedness to adults who care for elderly parents living alone. Aurama monitors the elders at home using unobtrusive sensor technology and collects data about sleeping patterns, weight trends, cognitive abilities and presence at home. The system provides an unobtrusive ambient information display that presents the status of the elder and lets its users inspect long-term data about the well-being of the elder interactively. Aurama was designed iteratively with substantial user involvement through interviews, prototype evaluation, focus groups and lab tests. The final prototype was evaluated in two field trials each involving an elder and their adult children. The input of users throughout the design process and during these tests demonstrates clearly the potential of awareness systems to support the target user group to obtain peace of mind and feel connected. Furthermore, the users indicate a clear need for information on long-term trends relating to the well-being of aging parents, in contrast to the current emphasis in this field of research on providing instantaneous status information about daily activities and context.     

Diagnostics for regression dependence in tables re-ordered by the dominant correspondence analysis solution

Correspondence analysis is an exploratory technique for analyzing the interaction in a contingency table. Tables with meaningful orders of the rows and columns may be analyzed using a model-based correspondence analysis that incorporates order constraints. However, if there exists a permutation of the rows and columns of the contingency table so that the rows are regression dependent on the columns and, vice versa, the columns are regression dependent on the rows, then both implied orders are reflected in the first dimension of the unconstrained correspondence analysis [Schriever, B.F., 1983. Scaling of order dependent categorical variables with correspondence analysis. International Statistical Review 51, 225-238]. Thus, using unconstrained correspondence analysis, we may still find that the data fit an ordinal stochastic model. Fit measures are formulated that may be used to verify whether the re-ordered contingency table is regression dependent in either the rows or columns. Using several data examples, it is shown that the fit indices may complement the usual geometric interpretation of the unconstrained correspondence analysis solution in low-dimensional space.     

How shall we meet? Understanding the importance of meeting mode capabilities for different meeting objectives

Distributed business meetings can be conducted in a variety of modes, such as audio-conferencing, video-conferencing, and telepresence, and can have different objectives, ranging from routine information sharing to relationship building. This paper examines whether and how differences in meeting mode effectiveness can be explained by the differing functional capabilities offered by each meeting mode (e.g., discerning facial expressions, experiencing co-location). Using data from the organizers of 612 business meetings, we identify the meeting capabilities perceived as important for different meeting objectives, and find multiple sets of meeting objectives that require the same combinations of capabilities. In addition, we examine whether the importance of different capabilities is affected by meeting size and duration. Using the results of the study, guidelines are developed to help meeting organizers select effective meeting modes based on meeting objectives.     

Symbolic PathFinder: integrating symbolic execution with model checking for Java bytecode analysis

Symbolic PathFinder (SPF) is a software analysis tool that combines symbolic execution with model checking for automated test case generation and error detection in Java bytecode programs. In SPF, programs are executed on symbolic inputs representing multiple concrete inputs and the values of program variables are represented by expressions over those symbolic inputs. Constraints over these expressions are generated from the analysis of different paths through the program. The constraints are solved with off-the-shelf solvers to determine path feasibility and to generate test inputs. Model checking is used to explore different symbolic program executions, to systematically handle aliasing in the input data structures, and to analyze the multithreading present in the code. SPF incorporates techniques for handling input data structures, strings, and native calls to external libraries, as well as for solving complex mathematical constraints. We describe the tool and its application at NASA, in academia, and in industry.     

An empirical study of the effectiveness of telepresence as a business meeting mode

Telepresence is a technology that has emerged as a promising mode for conducting business meetings with distributed participants, since it enables an immersive lifelike experience. However, telepresence meetings are substantially more expensive than audio- and video-conferencing meetings. This paper examines the justification of using telepresence for meetings. Based on an extensive literature review, two research questions about the effectiveness of telepresence for achieving meeting objectives are formulated. These are then addressed in an empirical study consisting of two phases, conducted in a large multinational corporation in which telepresence is widely used. In Phase 1, a list of meeting objectives is compiled. In Phase 2, the effectiveness of telepresence is analyzed relative to audio-conferencing, video-conferencing, and face-to-face for these objectives, based on input from 392 meeting organizers. The results of the analysis indicate that although the effectiveness of telepresence is higher than the effectiveness of audio- and video-conferencing for several meeting objectives, it is not significantly different from the effectiveness of face-to-face for any objective.     

Exact and efficient top-<Emphasis Type="Italic">K</Emphasis> inference for multi-target prediction by querying separable linear relational models

Many complex multi-target prediction problems that concern large target spaces are characterised by a need for efficient prediction strategies that avoid the computation of predictions for all targets explicitly. Examples of such problems emerge in several subfields of machine learning, such as collaborative filtering, multi-label classification, dyadic prediction and biological network inference. In this article we analyse efficient and exact algorithms for computing the top-K predictions in the above problem settings, using a general class of models that we refer to as separable linear relational models. We show how to use those inference algorithms, which are modifications of well-known information retrieval methods, in a variety of machine learning settings. Furthermore, we study the possibility of scoring items incompletely, while still retaining an exact top-K retrieval. Experimental results in several application domains reveal that the so-called threshold algorithm is very scalable, performing often many orders of magnitude more efficiently than the naive approach.