Critical thoughts on computing atom condensed Fukui functions

Different procedures to obtain atom condensed Fukui functions are described. It is shown how the resulting values may differ depending on the exact approach to atom condensed Fukui functions. The condensed Fukui function can be computed using either the fragment of molecular response approach or the response of molecular fragment approach. The two approaches are nonequivalent; only the latter approach corresponds in general with a population difference expression. The Mulliken approach does not depend on the approach taken but has some computational drawbacks. The different resulting expressions are tested for a wide set of molecules. In practice one must make seemingly arbitrary choices about how to compute condensed Fukui functions, which suggests questioning the role of these indicators in conceptual density-functional theory

Applying recommendations to aligncompetences, methodology and assessment in Telematics, Computing and Electronic Engineering courses

The alignment between competences, teaching-learning methodologies and assessment is a key element of the European Higher Education Area. This paper presents the efforts carried out by six Telematics, Computer Science and Electronic Engineering Education teachers towards achieving this alignment in their subjects. In a joint work with pedagogues, a set of recommended actions were identified. A selection of these actions were applied and evaluated in the six subjects. The cross-analysis of the results indicate that the actions allow students to better understand the methodologies and assessment planned for the subjects, facilitate (self-) regulation and increase students’ involvement in the subjects.

@neurIST infrastructure for advanced disease management through integration of heterogeneous data, computing, and complex processing services

The increasing volume of data describing humandisease processes and the growing complexity of understanding, managing, and sharing such data presents a huge challenge for clinicians and medical researchers. This paper presents the@neurIST system, which provides an infrastructure for biomedical research while aiding clinical care, by bringing together heterogeneous data and complex processing and computing services. Although @neurIST targets the investigation and treatment of cerebral aneurysms, the system’s architecture is generic enough that it could be adapted to the treatment of other diseases.Innovations in @neurIST include confining the patient data pertaining to aneurysms inside a single environment that offers cliniciansthe tools to analyze and interpret patient data and make use of knowledge-based guidance in planning their treatment. Medicalresearchers gain access to a critical mass of aneurysm related data due to the system’s ability to federate distributed informationsources. A semantically mediated grid infrastructure ensures that both clinicians and researchers are able to seamlessly access andwork on data that is distributed across multiple sites in a secure way in addition to providing computing resources on demand forperforming computationally intensive simulations for treatment planning and research.

Computing infinite plans for LTL goals using a classical planner

Classical planning has been notably successful in synthesizing finite plans to achieve states where propositional goals hold. In the last few years, classical planning has also been extended to incorporate temporally extended goals, expressed in temporal logics such as LTL, to impose restrictions on the state sequences generated by finite plans. In this work, we take the next step and consider the computation of infinite plans for achieving arbitrary LTL goals. We show that infinite plans can also be obtained efficiently by calling a classical planner once over a classical planning encoding that represents and extends the composition of the planningdomain and the B¨uchi automaton representingthe goal. This compilation scheme has been implemented and a number of experiments are reported.

Implementing interactive computing in an object-oriented environment

Statistical computing when input/output is driven by a Graphical User Interface is considered. A proposal is made for automatic control ofcomputational flow to ensure that only strictly required computationsare actually carried on. The computational flow is modeled by a directed graph for implementation in any object-oriented programming language with symbolic manipulation capabilities. A complete implementation example is presented to compute and display frequency based piecewise linear density estimators such as histograms or frequency polygons.

Computing congruences of modular forms and Galois representations modulo prime powers

This article starts a computational study of congruences of modular forms and modular Galoisrepresentations modulo prime powers. Algorithms are described that compute the maximum integermodulo which two monic coprime integral polynomials have a root in common in a sensethat is defined. These techniques are applied to the study of congruences of modular forms andmodular Galois representations modulo prime powers. Finally, some computational results withimplications on the (non-)liftability of modular forms modulo prime powers and possible generalisationsof level raising are presented.

Reversible major histocompatibility complex I-peptide multimers containing Ni(2+)-nitrilotriacetic acid peptides and histidine tags improve analysis and sorting of CD8(+) T cells.

MHC-peptide multimers containing biotinylated MHC-peptide complexes bound to phycoerythrin (PE) streptavidin (SA) are widely used for analyzing and sorting antigen-specific T cells. Here we describe alternative T cell-staining reagents that are superior to conventional reagents. They are built on reversible chelate complexes of Ni(2+)-nitrilotriacetic acid (NTA) with oligohistidines. We synthesized biotinylated linear mono-, di-, and tetra-NTA compounds using conventional solid phase peptide chemistry and studied their interaction with HLA-A*0201-peptide complexes containing a His(6), His(12), or 2×His(6) tag by surface plasmon resonance on SA-coated sensor chips and equilibrium dialysis. The binding avidity increased in the order His(6) < His(12) < 2×His(6) and NTA(1) < NTA(2) < NTA(4), respectively, depending on the configuration of the NTA moieties and increased to picomolar K(D) for the combination of a 2×His(6) tag and a 2×Ni(2+)-NTA(2). We demonstrate that HLA-A2-2×His(6)-peptide multimers containing either Ni(2+)-NTA(4)-biotin and PE-SA- or PE-NTA(4)-stained influenza and Melan A-specific CD8+ T cells equal or better than conventional multimers. Although these complexes were highly stable, they very rapidly dissociated in the presence of imidazole, which allowed sorting of bona fide antigen-specific CD8+ T cells without inducing T cell death as well as assessment of HLA-A2-peptide monomer dissociation kinetics on CD8+ T cells.

Reversible ferromagnetic switching in ZnO:(Co,Mn) powders

We report here on the magnetic properties of ZnO:Mn- and ZnO:Co-doped nanoparticles. We have found that the ferromagnetism of ZnO:Mn can be switched on and off by consecutive low-temperature annealings in O2 and N2, respectively, while the opposite phenomenology was observed for ZnO:Co. These results suggest that different defects (presumably n-type for ZnO:Co and p-type for ZnO:Mn) are required to induce a ferromagnetic coupling in each case. We will argue that ferromagnetism is likely to be restricted to a very thin, nanometric layer at the grain surface. These findings reveal and give insight into the dramatic relevance of surface effects to the occurrence of ferromagnetism in ZnO-doped oxides.

Reversible and irreversible pollutant-induced bacterial cellular stress effects measured by ethidium bromide uptake and efflux.

Chemical pollution is known to affect microbial community composition but it is poorly understood how toxic compounds influence physiology of single cells that may lay at the basis of loss of reproductive fitness. Here we analyze physiological disturbances of a variety of chemical pollutants at single cell level using the bacterium Pseudomonas fluorescens in an oligotrophic growth assay. As a proxy for physiological disturbance we measured changes in geometric mean ethidium bromide (EB) fluorescence intensities in subpopulations of live and dividing cells exposed or not exposed to different dosages of tetradecane, 4-chlorophenol, 2-chlorobiphenyl, naphthalene, benzene, mercury chloride, or water-dissolved oil fractions. Because ethidium bromide efflux is an energy-dependent process any disturbance in cellular energy generation is visible as an increased cytoplasmic fluorescence. Interestingly, all pollutants even at the lowest dosage of 1 nmol/mL culture produced significantly increased ethidium bromide fluorescence compared to nonexposed controls. Ethidium bromide fluorescence intensities increased upon pollutant exposure dosage up to a saturation level, and were weakly (r(2) = 0.3905) inversely correlated to the proportion of live cells at that time point in culture. Temporal increase in EB fluorescence of growing cells is indicative for toxic but reversible effects. Cells displaying high continued EB fluorescence levels experience constant and permanent damage, and no longer contribute to population growth. The procedure developed here using bacterial ethidium bromide efflux pump activity may be a useful complement to screen sublethal toxicity effects of chemicals.

Giant heat dissipation at the low temperature reversible-irreversible transition in Gd5Ge4

The heat exchanged at the low-temperature first-order magnetostructural transition is directly measured in Gd5Ge4 . Results show that the origin and the temperature dependence of the heat exchanged varies with the reversible/irreversible character of the first-order transition. In the reversible regime, the heat exchanged by the sample is mostly due to the latent heat at the transition and decreases with decreasing temperature, while in the irreversible regime, the heat is irreversibly dissipated and increases strongly with decreasing temperature, reaching a value of 237 J/kg at 4 K.

Comparative performance of supertree algorithms in large data sets using the soapberry family (Sapindaceae) as a case study.

For the last 2 decades, supertree reconstruction has been an active field of research and has seen the development of a large number of major algorithms. Because of the growing popularity of the supertree methods, it has become necessary to evaluate the performance of these algorithms to determine which are the best options (especially with regard to the supermatrix approach that is widely used). In this study, seven of the most commonly used supertree methods are investigated by using a large empirical data set (in terms of number of taxa and molecular markers) from the worldwide flowering plant family Sapindaceae. Supertree methods were evaluated using several criteria: similarity of the supertrees with the input trees, similarity between the supertrees and the total evidence tree, level of resolution of the supertree and computational time required by the algorithm. Additional analyses were also conducted on a reduced data set to test if the performance levels were affected by the heuristic searches rather than the algorithms themselves. Based on our results, two main groups of supertree methods were identified: on one hand, the matrix representation with parsimony (MRP), MinFlip, and MinCut methods performed well according to our criteria, whereas the average consensus, split fit, and most similar supertree methods showed a poorer performance or at least did not behave the same way as the total evidence tree. Results for the super distance matrix, that is, the most recent approach tested here, were promising with at least one derived method performing as well as MRP, MinFlip, and MinCut. The output of each method was only slightly improved when applied to the reduced data set, suggesting a correct behavior of the heuristic searches and a relatively low sensitivity of the algorithms to data set sizes and missing data. Results also showed that the MRP analyses could reach a high level of quality even when using a simple heuristic search strategy, with the exception of MRP with Purvis coding scheme and reversible parsimony. The future of supertrees lies in the implementation of a standardized heuristic search for all methods and the increase in computing power to handle large data sets. The latter would prove to be particularly useful for promising approaches such as the maximum quartet fit method that yet requires substantial computing power.

Acute reversible Charles Bonnet syndrome precipitated by sudden severe anemia.

PURPOSE: To report the sudden onset of reversible Charles Bonnet syndrome precipitated byacute severe anemia. METHODS: The charts of three patients (Usher syndrome, bilateral macular degeneration, and bilateral retinal vein occlusion) with acute Charles Bonnet syndrome in the setting of severe anemia were reviewed. RESULTS: Anemia resulted from bladder surgery, recto-colitis, and severe urinary tract infection. Hemoglobin ranged from 78 to 86 g/L. Decreased visual acuity and formed visual hallucinations (giants, flowers, animals) were present in all three patients. Rapid reversal of Charles Bonnet syndrome and visual acuity improvement followed blood transfusion. CONCLUSIONS: Acute severe anemia can precipitate Charles Bonnet syndrome, which may be reversible by blood transfusion.

Memory-based scheduling of scientific computing clusters

This study looks at how increased memory utilisation affects throughput and energy consumption in scientific computing, especially in high-energy physics. Our aim is to minimise energy consumed by a set of jobs without increasing the processing time. The earlier tests indicated that, especially in data analysis, throughput can increase over 100% and energy consumption decrease 50% by processing multiple jobs in parallel per CPU core. Since jobs are heterogeneous, it is not possible to find an optimum value for the number of parallel jobs. A better solution is based on memory utilisation, but finding an optimum memory threshold is not straightforward. Therefore, a fuzzy logic-based algorithm was developed that can dynamically adapt the memory threshold based on the overall load. In this way, it is possible to keep memory consumption stable with different workloads while achieving significantly higher throughput and energy-efficiency than using a traditional fixed number of jobs or fixed memory threshold approaches.