Finite-difference vector-potential solution of transient electromagnetic field problems

A finite-difference time–space numerical algorithm for the analysis of transient electromagnetic fields is proposed based on the expression of the field vectors in terms of vector potential functions. The method allows for both integral and finite-difference calculation of the potential functions (PF). Both approaches can be applied in combination. Since it is based on the time-domain integral-equation approach, it reduces the 3D problem to a 2D one, and only the tangential vector potential components are involved in the calculation. The consistency of the method has been proved by simulations of Gaussian pulse propagation in a homogeneous and an open-end microstripline and a thin-plate scattering problem. © 1998 John Wiley & Sons, Inc. Int J RF and Microwave CAE 8: 56–67, 1998.     

Annotation of sentence structure

The focus of this article is on the creation of a collection of sentences manually annotated with respect to their sentence structure. We show that the concept of linear segments—linguistically motivated units, which may be easily detected automatically—serves as a good basis for the identification of clauses in Czech. The segment annotation captures such relationships as subordination, coordination, apposition and parenthesis; based on segmentation charts, individual clauses forming a complex sentence are identified. The annotation of a sentence structure enriches a dependency-based framework with explicit syntactic information on relations among complex units like clauses. We have gathered a collection of 3,444 sentences from the Prague Dependency Treebank, which were annotated with respect to their sentence structure (these sentences comprise 10,746 segments forming 6,341 clauses). The main purpose of the project is to gain a development data—promising results for Czech NLP tools (as a dependency parser or a machine translation system for related languages) that adopt an idea of clause segmentation have been already reported. The collection of sentences with annotated sentence structure provides the possibility of further improvement of such tools.     

Educational affordances of PDAs: A study of a teacher’s exploration of this technology

This paper reports on a case study of a teacher from a technical education institution who explored the educational affordances of PDA technology over a period of six months. Based on this teacher’s perspectives, the study was designed to inform our own understanding of educational affordances of this new and emerging technology. Understanding of educational affordances is important in the context of planning a suitable intervention to support pedagogically effective integration of PDA technology. The study explicated a set of five affordances of PDA technology: as a multimedia-access tool, connectivity tool, capture tool, representational tool and analytical tool. We call on further research to expand this set into a more comprehensive collage of educational affordances of PDA technology.     

Urinary proteomic analysis of chronic allograft nephropathy

The pathogenesis of progressive renal allograft injury, which is termed chronic allograft nephropathy (CAN), remains obscure and is currently defined by histology. Prospective protocol-biopsy trials have demonstrated that clinical and standard laboratory tests are insufficiently sensitive indicators of the development and progression of CAN. The study aim was to determine if CAN could be characterized by urinary proteomic data and identify the proteins associated with disease. The urinary proteome of 75 renal transplant recipients and 20 healthy volunteers was analyzed using surface enhanced laser desorption and ionization MS. Patients could be classified into subgroups with normal histology and Banff CAN grades 2-3 with a sensitivity of 86% and a specificity of 92% by applying the classification algorithm Adaboost to urinary proteomic data. Several urinary proteins associated with advanced CAN were identified including α1-microglobulin, β2-microglobulin, prealbumin, and endorepellin, the antiangiogenic C-terminal fragment of perlecan. Increased urinary endorepellin was confirmed by ELISA and increased tissue expression of the endorepellin/perlecan ratio by immunofluoresence analysis of renal biopsies. In conclusion, analysis of urinary proteomic data has further characterized the more severe CAN grades and identified urinary endorepellin, as a potential biomarker of advanced CAN.     

A coherence maximisation process for solving normative inconsistencies

Norms can be used in multi-agent systems for defining patterns of behaviour in terms of permissions, prohibitions and obligations that are addressed to agents playing a specific role. Agents may play different roles during their execution and they may even play different roles simultaneously. As a consequence, agents may be affected by inconsistent norms; e.g., an agent may be simultaneously obliged and forbidden to reach a given state of affairs. Dealing with this type of inconsistency is one of the main challenges of normative reasoning. Existing approaches tackle this problem by using a static and predefined order that determines which norm should prevail in the case where two norms are inconsistent. One main drawback of these proposals is that they allow only pairwise comparison of norms; it is not clear how agents may use the predefined order to select a subset of norms to abide by from a set of norms containing multiple inconsistencies. Furthermore, in dynamic and non-deterministic environments it can be difficult or even impossible to specify an order that resolves inconsistencies satisfactorily in all potential situations. In response to these two problems, we propose a mechanism with which an agent can dynamically compute a preference order over subsets of its competing norms by considering the coherence of its cognitive and normative elements. Our approach allows flexible resolution of normative inconsistencies, tailored to the current circumstances of the agent. Moreover, our solution can be used to determine norm prevalence among a set of norms containing multiple inconsistencies.     

Reduced Carbon and Energy Footprint in Highway Operations: The Highway Energy Assessment (HERA) Methodology

Global demand for mobility is increasing and the environmental impact of transport has become an important issue in transportation network planning and decision-making, as well as in the operational management phase. Suitable methods are required to assess emissions and fuel consumption reduction strategies that seek to improve energy efficiency and furthering decarbonization. This study describes the development and application of an improved modeling framework – the HERA (Highway EneRgy Assessment) methodology – that enables to assess the energy and carbon footprint of different highways and traffic flow scenarios and their comparison. HERA incorporates an average speed consumption model adjusted with a correction factor which takes into account the road gradient. It provides a more comprehensive method for estimating the footprint of particular highway segments under specific traffic conditions. It includes the application of the methodology to the Spanish highway network to validate it. Finally, a case study shows the benefits from using this methodology and how to integrate the objective of carbon footprint reductions into highway design, operation and scenario comparison.     

An industry experiment on the effects of test-driven development on external quality and productivity

Existing empirical studies on test-driven development (TDD) report different conclusions about its effects on quality and productivity. Very few of those studies are experiments conducted with software professionals in industry. We aim to analyse the effects of TDD on the external quality of the work done and the productivity of developers in an industrial setting. We conducted an experiment with 24 professionals from three different sites of a software organization. We chose a repeated-measures design, and asked subjects to implement TDD and incremental test last development (ITLD) in two simple tasks and a realistic application close to real-life complexity. To analyse our findings, we applied a repeated-measures general linear model procedure and a linear mixed effects procedure. We did not observe a statistical difference between the quality of the work done by subjects in both treatments. We observed that the subjects are more productive when they implement TDD on a simple task compared to ITLD, but the productivity drops significantly when applying TDD to a complex brownfield task. So, the task complexity significantly obscured the effect of TDD. Further evidence is necessary to conclude whether TDD is better or worse than ITLD in terms of external quality and productivity in an industrial setting. We found that experimental factors such as selection of tasks could dominate the findings in TDD studies.     

Spatial generalization and aggregation of massive movement data

Movement data (trajectories of moving agents) are hard to visualize: numerous intersections and overlapping between trajectories make the display heavily cluttered and illegible. It is necessary to use appropriate data abstraction methods. We suggest a method for spatial generalization and aggregation of movement data, which transforms trajectories into aggregate flows between areas. It is assumed that no predefined areas are given. We have devised a special method for partitioning the underlying territory into appropriate areas. The method is based on extracting significant points from the trajectories. The resulting abstraction conveys essential characteristics of the movement. The degree of abstraction can be controlled through the parameters of the method. We introduce local and global numeric measures of the quality of the generalization, and suggest an approach to improve the quality in selected parts of the territory where this is deemed necessary. The suggested method can be used in interactive visual exploration of movement data and for creating legible flow maps for presentation purposes.     

Design of Porous Alginate Hydrogels by Sacrificial CaCO3 Templates: Pore Formation Mechanism

Fabrication of porous alginate hydrogels with a well‐controlled architecture useful for tissue engineering is still a challenge. Here, CaCO₃‐based templating is utilized to design stable alginate gels with controlled pore dimensions in the range of 5–50 μm. The mechanism of pore formation is studied considering two factors affecting the pore size: i) osmotic pressure generated during the dissolution of sacrificial CaCO₃ templates and ii) alginate gel network density. Osmotic pressure can achieve an upper limit of 100 MPa but does not affect the gel porosity. Additional osmotic pressure (range of kPa) induced by dextrans pre‐encapsulated into CaCO₃ vaterite is also insufficient for pore enlargement. Pore stability depends merely on the gel network density and on the number of crosslinking calcium ions provided locally per unit time; pores are collapsed when template dissolution is too slow or if there is insufficient alginate concentration (below 2%). Young's modulus indicates the soft nature of the prepared hydrogels (tens of kPa) applicable as soft porous scaffolds with a tuned internal structure.     

Influence of the reaction time and the Triton x-100/Cyclohexane/Methanol/H2O ratio on the morphology and size of silica nanoparticles synthesized via sol–gel assisted by reverse micelle microemulsion

The present paper describes the synthesis of silica nanoparticles via the sol–gel method assisted by reverse micelle microemulsion, using reagents as Triton x-100/Cyclohexane/Methanol/H₂O, and also the effect on particle size of some synthesis parameters such as the water-surfactant molar ratio (R), Co-surfactant-surfactant (ρ), and synthesis time (t). The structure, morphology, and size of the silica nanoparticles were characterized with transmission electron microscopy and scanning electron microscopy. A variation of ρ = [Methanol]/[Triton X-100] affects the size, morphology, and dispersion of the particles. An increase in the concentration of methanol produces a decrease in particle size. The condition that resulted in smaller particle size, better spherical morphology, and monodispersity was when ρ = 7.6, which generated an approximate size of 83 ± 7 nm. The parameter R = [H₂O]/[Triton X-100] affects not only the size of the particles, but also their morphology. Higher values of R result in a decrease in the amount of catalyst present in the interior of the micelle, but in turn generate a greater amount of water, which results in a decrease in particle size and polydispersity. Time is a parameter that directly affects the size of the silica particles. The optimal time for the synthesis of nanoparticles was 2 h, resulting in silica nanoparticles of 25 ± 3 nm, monodisperse, with spherical morphology and without the presence of agglomerations.