Plasmon hybridization engineering in self-organized anisotropic metasurfaces

Nano Research - The engineering of self-organized plasmonic metasurfaces is demonstrated using a maskless technique with defocused ion-beam sputtering and kinetically controlled deposition. The...     

Proof Lengths for Equational Completion

We first show that ground term-rewriting systems can be completed in a polynomial number of rewriting steps, if the appropriate data structure for terms is used. We then apply this result to study the lengths of critical pair proofs in non-ground systems, and obtain bounds on the lengths of critical pair proofs in the non-ground case. We show how these bounds depend on the types of inference steps that are allowed in the proofs.     

In vivo characterization of renal auto-antigens involved in human auto-immune diseases: the case of membranous glomerulonephritis

Renal auto-immune diseases represent a major source of morbidity in humans. For many years the knowledge on mechanisms of auto-immunity involving the kidney has been uniquely based on animal models. However, these findings often could not be readily translated to humans owing to notably difference in antigen expression by human podocytes. One example is Heymann nephritis (HN), the experimental model of human membranous glomerulonephritis (MGN), which is obtained in rats by injecting antibodies against megalin, a protein that is not present in human glomeruli. Human studies could not be done in the past since sequencing required too much material exceeding what obtainable from tissue biopsies in vivo. Research is now on the way to identify auto-antigens and isolate specific auto-antibodies in humans. New technology developments based on tissue microdissection and proteomical analysis have facilitated the recent discoveries, allowing direct analysis of human tissue in vivo. Major advances on the pathogenesis of MGN, the prototype for the formation and glomerular deposition of auto-antibodies, are now in progress. Two independent groups have, in fact, demonstrated the existence of specific IgG(4) against phospholipase A2 receptor, aldose reductase and Mn-superoxide dismutase in glomerular eluates and in plasma of a prominent part of patients with MGN, suggesting a major role of these proteins as auto-antigens in human MGN. This review will focalize these aspects outlining the contribution of proteomics in most recent developments.     

Assessing canopy mortality during a mountain pine beetle outbreak using GeoEye-1 high spatial resolution satellite data

Continuing, severe outbreaks of mountain pine beetle (Dendroctonus ponderosae) across western North America have resulted in widespread mortality of lodgepole pine (Pinus contorta). Multiple studies have used high spatial resolution satellite data to map areas of beetle kill; these studies have largely focused on mapping red canopy cover associated with recent tree mortality and have not examined mapping gray canopy cover that occurs after red needles have dropped. The work presented here examines the use of newly available GeoEye-1 data for mapping both red and gray canopy area in southeastern Wyoming lodgepole pine forest. A 0.5 m spatial resolution, pan-sharpened GeoEye-1 image was used to classify areas of green, red, and gray canopy cover. Reference data were collected at twelve 500 m² field plots. Shadow-normalized green, red, and gray canopy area from classified GeoEye-1 data closely agreed with field-estimated green, red, and gray canopy area. Mean absolute error in canopy cover for the twelve sample plots was 8.3% for the green class, 5.4% for the red class, and 7.2% for the gray class. When all twelve plots were aggregated, remotely sensed estimates of green, red, and gray cover were within 1.7% of the field-estimated cover. Our results demonstrate that high spatial resolution spaceborne multispectral data are a promising tool for mapping canopy mortality caused by mountain pine beetle outbreaks.     

An online tool to identify white-collar worker profiles in relation to their ICT skills and mental strain

The introduction of Internet and Information and communication Technologies (ICT) in offices is a global phenomenon that transformed white-collar worker job demands. Although there are several studies of e-skills and mental workload for central countries, there is a lack of similar studies for the Latin American context. An online snowball sampled (n = 352) survey was developed and validated by the authors (internal consistency = 0.7). We characterized ICT worker profiles from e-skills and these dimensions: attitudes toward, resources usage and technology dependency. Mental Strain was assessed with raw task load index (RTLX) and correlated with the proposed profiles by means of paired T-tests and Mann–Whitney Tests. The sample was characterized by 7.2% of non visual display terminal users and 92.8% of visual display terminal, ICT skilled users. Of the latter, 30.7% were ICT practitioners, 30.4% were ICT Users and 27.2% were E-Business Users. Non VDT users’ mental strain was statistically meaningful smaller than VDT–ICT skilled users’ mental workload. No statistical differences were found in RTLX results when comparing ICT skilled user profiles. Non VDT users can be identified from ICT skilled Users by their lower ITC Dependency and minor use of ICT resources. There were no differences in those dimensions among ICT skilled Profiles. Attitude toward these technologies was a distinct factor for ICT Users in relation to ICT Practitioners and ITC Business Users. The application of this tool in peripheral and central countries would allow a complete ergonomical characterization of white-collar workers within the Information Society.     

HLA_ACTOR_REPAST: An approach to distributing RePast models for high-performance simulations

RePast is a popular agent toolkit with proven capabilities to fulfil the modelling challenges of large multi-agent systems (MASs). The toolkit, though, is normally used on a standalone workstation and therefore its practical use can be constrained (in space and time) by the limited available computing resources. This paper proposes an original approach – HLA_ACTOR_REPAST – aimed to distributing RePast models for high-performance simulation of complex scalable models. Novel in HLA_ACTOR_REPAST is an exploitation of a lean actor infrastructure implemented in Java. Actors bring to RePast agents such features as migration, location-transparent naming, efficient communications, and a control-centric framework. Actors can be orchestrated by an in-the-large custom control structure which is in charge of ensuring the necessary message causality constraints. Distribution and time management concerns depend on the IEEE standard HLA middleware. The paper first discusses details of the software engineering process underlying the development of HLA_ACTOR_REPAST. The mapping techniques, assisted by Java text annotations and aspect-oriented programming, try to minimize “code intrusions” in the original model and favour model transparency. The paper then furnishes some experimental data which witness the good performance results achieved by applying HLA_ACTOR_REPAST to a distributed version of a classic MAS benchmark model.     

Minutia Cylinder-Code: a new representation and matching technique for fingerprint recognition

In this paper, we introduce the Minutia Cylinder-Code (MCC): a novel representation based on 3D data structures (called cylinders), built from minutiae distances and angles. The cylinders can be created starting from a subset of the mandatory features (minutiae position and direction) defined by standards like ISO/IEC 19794-2 (2005). Thanks to the cylinder invariance, fixed-length, and bit-oriented coding, some simple but very effective metrics can be defined to compute local similarities and to consolidate them into a global score. Extensive experiments over FVC2006 databases prove the superiority of MCC with respect to three well-known techniques and demonstrate the feasibility of obtaining a very effective (and interoperable) fingerprint recognition implementation for light architectures.     

A Formal Logic Approach to Constrained Combinatorial Testing

Combinatorial testing is as an effective testing technique to reveal failures in a given system, based on input combinations coverage and combinatorial optimization. Combinatorial testing of strength t (t ≥ 2) requires that each t-wise tuple of values of the different system input parameters is covered by at least one test case. Combinatorial test suite generation algorithms aim at producing a test suite covering all the required tuples in a small (possibly minimal) number of test cases, in order to reduce the cost of testing. The most used combinatorial technique is the pairwise testing (t = 2) which requires coverage of all pairs of input values. Constrained combinatorial testing takes also into account constraints over the system parameters, for instance forbidden tuples of inputs, modeling invalid or not realizable input values combinations. In this paper a new approach to combinatorial testing, tightly integrated with formal logic, is presented. In this approach, test predicates are used to formalize combinatorial testing as a logical problem, and an external formal logic tool is applied to solve it. Constraints over the input domain are expressed as logical predicates too, and effectively handled by the same tool. Moreover, inclusion or exclusion of select tuples is supported, allowing the user to customize the test suite layout. The proposed approach is supported by a prototype tool implementation and results of experimental assessment are also presented.