Copper Immobilization on Fe3O4@Agar: An Efficient Superparamagnetic Nanocatalyst for Green Ullmann-Type Cross-Coupling Reaction of Primary and Secondary Amines with Aryl Iodide Derivatives

Journal of Inorganic and Organometallic Polymers and Materials - Immobility of copper on magnetic nanoparticles was performed using surface rectification of Fe3O4 with Agar. The magnetic...     

Failed empathy--a central theme in the survivor's holocaust experience.

In this article, we concern ourselves with massive traumatic events deliberately inflicted on individuals by fellow human beings. Specifically, we focus on the Holocaust and the fact that massive failure of the environment to mediate needs, as in genocide, will throw into question the existence of empathy, human communication, and ultimately ones own humanity, to which any mirroring ceases to exist. Such a life experience will represent, to the survivor of trauma, failure of a responsive empathic agent or function. Because it is precisely representations of need-satisfying interactions that provide the basis for links between personal existence and social connectedness, undermining the individual's representation of the need-mediating context will deconstruct the link between self and other. Destruction of the victim's representational matrix of interpersonal relatedness results in a vulnerability and loneliness in his or her internal world representation which is the sine qua non of man-made trauma. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Unsupervised image-set clustering using an information theoretic framework.

In this paper, we combine discrete and continuous image models with information-theoretic-based criteria for unsupervised hierarchical image-set clustering. The continuous image modeling is based on mixture of Gaussian densities. The unsupervised image-set clustering is based on a generalized version of a recently introduced information-theoretic principle, the information bottleneck principle. Images are clustered such that the mutual information between the clusters and the image content is maximally preserved. Experimental results demonstrate the performance of the proposed framework for image clustering on a large image set. Information theoretic tools are used to evaluate cluster quality. Particular emphasis is placed on the application of the clustering for efficient image search and retrieval.     

Memory organization of action events and its relationship to memory performance.

Previous research yielded inconsistent results regarding the memory organization of self-performed actions. The authors propose that task performance changes the very basis of memory organization. Enactment during study and test (Experiment 1) yielded stronger enactive clustering (based on motor-movement similarities), whereas verbal encoding yielded stronger conceptual clustering (based on semantic-episodic similarities). Enactment enhanced memory quantity and memory accuracy. Both measures increased with enactive clustering under self-performance instructions but with conceptual clustering under verbal instructions. Enactment only during study (Experiment 2) or only during testing (Experiment 3) also enhanced enactive clustering. It is proposed that different conditions affect the relative salience of different types of memory organization and their relative contribution to recall. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

From conceptual models to schemata: An object-process-based data warehouse construction method

Data warehouse modeling is a complex task, which involves knowledge of business processes of the domain of discourse, understanding the structural and behavioral system's conceptual model, and familiarity with data warehouse technologies. The suitability of current data warehouse modeling methods for large-scale systems is questionable, as they require multiple manual actions to discover measures and relevant dimensional entities and they tend to disregard the system's dynamic aspects. We present an Object-process-based Data Warehouse Construction (ODWC) method that overcomes these limitations of existing methods by utilizing the operational system conceptual model to construct a corresponding data warehouse schema. We specify the ODWC method, apply it on a case study, evaluate it, and compare it to existing methods.     

Smooth Scheduling under Variable Rates or the Analog-Digital Confinement Game

This work considers non-terminating scheduling problems in which a system of multiple resources serves clients having variable needs. The system has m identical resources and n clients; in each time slot each resource may serve at most one client; in each such slot t each client γ has a rate, a real number ρ _γ (t), that specifies his needs in this slot. The rates satisfy the restriction ∑ _γ ρ _γ (t)≤m for any slot t. Except of this restriction, the rates can vary in arbitrary fashion. (This contrasts most prior works in this area in which the rates of the clients are constant.) The schedule is required to be smooth as follows: a schedule is Δ -smooth if for all time intervals I the absolute difference between the amount of service received by each client γ to his nominal needs of ∑ _t∈I ρ _γ (t) is less than Δ. Our objective are online schedulers that produce Δ-smooth schedules where Δ is a small constant which is independent of m and n. Our paper constructs such schedulers; these are the first online Δ-smooth schedulers, with a constant Δ, for clients with arbitrarily variable rates in a single or multiple resource system. Furthermore, the paper also considers a non-concurrent environment in which there is an additional restriction that each client is served at most once in each time slot; it presents the first online smooth schedulers for variable rates under this restriction. The above non-concurrent restriction is crucial in some applications (e.g., CPU scheduling). It has been pointed out that this restriction “adds a surprising amount of difficulty” to the scheduling problem. However, this observation was never formalized and, of course, was never proved. Our paper formalizes and proves some aspects of this observation. Another contribution of this paper is the introduction of a complete information, two player game called the analog-digital confinement game. In such a game pebbles are located on the real line; the two players, the analog player and the digital player, take alternating turns and each one, in his turn, moves some of the pebbles; the digital player moves the pebbles backwards by discrete distances while the analog player moves the pebbles forward by analog distances; the aim of the analog player is to cause one pebble (or more) to escape a pre-defined real interval while the aim of the digital player is to confine the pebbles into the interval. We demonstrate that this game is a convenient framework to study the general question of how to approximate an analog process by a digital one. All the above scheduling results are established via this game. In this derivation, the pebbles represent the clients, the analog player generates the needs of the clients and the digital player generates the schedule. Dedicated to the memory of Professor Shimon Even for his inspiration and encouragement     

From object-process analysis to object-process design

The object-process methodology incorporates the system static-structural and dynamic-procedural aspects into a single, unified model. This unification bridges the gap that separates the static, object model from the dynamic, behavior, state, or function-oriented models found in many current object oriented methodologies. In this work we concentrate on the transition from object-process analysis to design within the development of information systems. We use a detailed case study as a running example throughout the paper to demonstrate how the structure-behavior unification, which characterizes object-process analysis, is carried on to object-process design. The case study first applies object-process analysis to perform the analysis stage. The sequence of steps that constitutes the design is then discussed and demonstrated through the case study. The design is divided into two phases: the analysis refinement phase and the implementation-dependent phase. Analysis refinement is concerned with adding details to the analysis results which are beyond the interest of the analysis itself, yet they are not related with a particular implementation. The implementation-dependent phase is concerned with code-level design, which takes place after specific implementation details, such as programming language, data organization, and user interface, have been made during the strategic design.     

Learning science via animated movies: Its effect on students’ thinking and motivation

Some researchers claim that animations may hinder students’ meaningful learning or evoke misunderstandings. In order to examine these assertions, our study investigated the effect of animated movies on students’ learning outcomes and motivation to learn. Applying the quantitative methodology, two pre- and post-questionnaires were administered: Science thinking skills and Motivation to learn science. Students’ overall achievement in science was examined by their report card scores. The research population (N = 1335) was divided into experimental (N = 926) and control (N = 409) groups from 11 elementary schools. Findings indicated that the use of animated movies promoted students’ explanation ability and their understanding of scientific concepts. Findings also indicated that students who studied science with the use of animated movies developed higher motivation to learn science, in terms of: self-efficacy, interest and enjoyment, connection to daily life, and importance to their future, compared to the control students. Following the definition of multimedia, the students who study with the use of animated movies, applied all three learning styles: visual, auditory and kinesthetic. The use of multimedia and the fact that the students were engaged in exploring new concepts, that were relevant to their daily life experiences, can explain the positive results.     

Distributed topology control algorithm based on one- and two-hop neighbors’ information for ad hoc networks

In this paper, we present a topology control algorithm for ad hoc networks. By considering the weight of the links, each node orders its one-hop neighbors in an ordered list and then the ordered lists are exchanged between the neighbors. This information enables the nodes to compute their transmission radius on the basis of its one- and two-hop neighbors’ information. We demonstrate that compared to the best known algorithms, the degree and transmission radius of the nodes in the topology produced by the proposed algorithm are smaller. In addition to Euclidean graphs, the algorithm works correctly on general weighted graphs. Also an extension of our algorithm is proposed which adapts its topology to network changes. Finally, we use the four metrics, node degree, transmission radius, the power stretch factor and, packet loss ratio to measure the performance improvements of the presented algorithms through simulations.     

Pan Evaporation Modeling Using Neural Computing Approach for Different Climatic Zones

The purpose of this study was to develop and apply the neural networks models to estimate daily pan evaporation (PE) for different climatic zones such as temperate and arid climatic zones, Republic of Korea and Iran. Three kinds of the neural networks models, namely multilayer perceptron-neural networks model (MLP-NNM), generalized regression neural networks model (GRNNM), and support vector machine-neural networks model (SVM-NNM), were used to estimate daily PE. The available climatic variables, consisted of mean air temperature (T_mean), mean wind speed (U_mean), sunshine duration (SD), mean relative humidity (RH_mean), and extraterrestrial radiation (R_a) were used to estimate daily PE using the various input combinations of climate variables. The measurements for the period of January 1985?CDecember 1990 (Republic of Korea) and January 2002?CDecember 2008 (Iran) were used for training and testing the employed neural networks models. The results obtained by SVM-NNM indicated that it performs better than MLP-NNM and GRNNM for estimating daily PE. A comparison was also made among the employed models, which demonstrated the superiority of MLP-NNM, GRNNM, and SVM-NNM over Linacre model and multiple linear regression model (MLRM).