Cross-disciplinary collaboration versus coexistence in LIS serials: analysis of authorship affiliations in four European countries

Scientometrics - The interdisciplinary nature of library and information science (LIS) research has been highlighted for some time now. The term “interdisciplinary” is used primarily in...     

Improvement of the deflocculating power of polyacrylates in ceramic slips by small additions of quaternary ammonium salts

In this work, we examine the effect of small additions of cationic quaternary ammonium salts (QAS) of different molecular weight on the rheology of an industrial ceramic suspension deflocculated with sodium polyacrylate and sodium metasilicate. The observed shear thinning behaviors obey the typical power law of fluid rheology. In order to characterize the rheological behavior of these slurries, three new parameters are introduced: a low shear rate consistency index and two transient viscosities, distant from the equilibrium, after increasing and decreasing the shear rates. These parameters vary with polyacrylate molecular weight and on additions of small quantities of QAS, which we found to be useful for decreasing the slurry viscosity.     

Adenosine Signaling in Mast Cells and Allergic Diseases

Adenosine is a nucleoside involved in the pathogenesis of allergic diseases. Its effects are mediated through its binding to G protein-coupled receptors: A1, A2a, A2b and A3. The receptors differ in the type of G protein they recruit, in the effect on adenylyl cyclase (AC) activity and the downstream signaling pathway triggered. Adenosine can produce both an enhancement and an inhibition of mast cell degranulation, indicating that adenosine effects on these receptors is controversial and remains to be clarified. Depending on the study model, A1, A2b, and A3 receptors have shown anti- or pro-inflammatory activity. However, most studies reported an anti-inflammatory activity of A2a receptor. The precise knowledge of the adenosine mechanism of action may allow to develop more efficient therapies for allergic diseases by using selective agonist and antagonist against specific receptor subtypes.     

Speeding up the spatial adiabatic passage of matter waves in optical microtraps by optimal control

We numerically investigate the performance of atomic transport in optical microtraps via the so called spatial adiabatic passage technique. Our analysis is carried out by means of optimal control methods, which enable us to determine suitable transport control pulses. We investigate the ultimate limits of the optimal control in speeding up the transport process in a triple well configuration for both a single atomic wave packet and a Bose-Einstein condensate within a regime of experimental parameters achievable with current optical technology.     

A SIMD-efficient 14 instruction shader program for high-throughput microtriangle rasterization

This paper shows that breaking the barrier of 1 triangle/clock rasterization rate for microtriangles in modern GPU architectures in an efficient way is possible. The fixed throughput of the special purpose culling and triangle setup stages of the classic pipeline limits the GPU scalability to rasterize many triangles in parallel when these cover very few pixels. In contrast, the shader core counts and increasing GFLOPs in modern GPUs clearly suggests parallelizing this computation entirely across multiple shader threads, making use of the powerful wide-ALU instructions. In this paper, we present a very efficient SIMD-like rasterization code targeted at very small triangles that scales very well with the number of shader cores and has higher performance than traditional edge equation based algorithms. We have extended the ATTILA GPU shader ISA (del Barrioet al. in IEEE International Symposium on Performance Analysis of Systems and Software, pp. 231–241, 2006) with two fixed point instructions to meet the rasterization precision requirement. This paper also introduces a novel subpixel Bounding Box size optimization that adjusts the bounds much more finely, which is critical for small triangles, and doubles the 2×2-pixel stamp test efficiency. The proposed shader rasterization program can run on top of the original pixel shader program in such a way that selected fragments are rasterized, attribute interpolated and pixel shaded in the same pass. Our results show that our technique yields better performance than a classic rasterizer at 8 or more shader cores, with speedups as high as 4× for 16 shader cores.     

A UML/OCL framework for the analysis of graph transformation rules

In this paper we present an approach for the analysis of graph transformation rules based on an intermediate OCL representation. We translate different rule semantics into OCL, together with the properties of interest (like rule applicability, conflicts or independence). The intermediate representation serves three purposes: (1) it allows the seamless integration of graph transformation rules with the MOF and OCL standards, and enables taking the meta-model and its OCL constraints (i.e. well-formedness rules) into account when verifying the correctness of the rules; (2) it permits the interoperability of graph transformation concepts with a number of standards-based model-driven development tools; and (3) it makes available a plethora of OCL tools to actually perform the rule analysis. This approach is especially useful to analyse the operational semantics of Domain Specific Visual Languages. We have automated these ideas by providing designers with tools for the graphical specification and analysis of graph transformation rules, including a back-annotation mechanism that presents the analysis results in terms of the original language notation.     

EEG signal preprocessing for biometric recognition

Electroencephalography (EEG) has been recently investigated as a biometric modality for automatic people recognition purposes. Several studies have shown that brain signals possess subject-specific traits that allow distinguishing people. Nonetheless, extracting discriminative characteristics from EEG recordings may be a challenging task, due to the significant presence of artifacts in the acquired data. In order to cope with such issue, in this paper we evaluate the effectiveness of some preprocessing techniques in automatically removing undesired EEG contributions, with the aim of improving the achievable recognition rates. Specifically, methods based on blind source separation and sample entropy estimation are here investigated. An extensive set of experimental tests, performed over a large database comprising recordings taken from 50 healthy subjects during three distinct sessions spanning a period of about one month, in both eyes-closed and eyes-open conditions, is carried out to analyze the performance of the proposed approaches.