Abstract
A study on the influence of titanium on the diffusion kinetics of erbium in lithium niobate is presented. An empirical linear relation between the diffusion coefficient of erbium and the initial film thickness of titanium was obtained from secondary ion mass spectrometry data. An improvement in the diffusion coefficient by a factor of two was measured for a 200-nm titanium film. Furthermore, the erbium and titanium codiffusion process not only enhances the diffusion of erbium, leading to smaller diffusion time, but also improves the device visibility for further fabrication procedures. This letter is envisioned to clarify in a quantitative way the process of simultaneous codiffusion of erbium and titanium ions into lithium niobate, which has been studied by several authors; nevertheless, no definitive conclusion can be found in the literature.

Abstract
This paper presents a local search, based on a new neighborhood for the job-shop scheduling problem, and its application within a biased random-key genetic algorithm. Schedules are constructed by decoding the chromosome supplied by the genetic algorithm with a procedure that generates active schedules. After an initial schedule is obtained, a local search heuristic, based on an extension of the 1956 graphical method of Akers, is applied to improve the solution. The new heuristic is tested on a set of 205 standard instances taken from the job-shop scheduling literature and compared with results obtained by other approaches. The new algorithm improved the best-known solution values for 57 instances.

Abstract
Natural user interfaces are becoming widespread as a focus of research in human-computer interaction. Gestural interaction is an important part of this field, but generally done by mimicry. This raises concerns such as the necessity of creating abstractions for non-imitable commands and the difficulty of finding gestures that are meaningful for a worldwide audience. Cultural backgrounds impart different meanings to gestures. In this research , we explore the concept of allowing individuals to interact with computer systems using gesture from the individual’s own culture, focusing on a software engineering approach to support this idea. The aim is to leverage the rich semantics of non-mimicry cultural gestures to expand gestural interaction to support abstract commands for instructions that do not have a matching gestural imitation. This approach also holds the potential to support the learning of gestural commands, by linking them to the cultural background of each user. The proposed software engineering approach demonstrates the feasibility of planning applications with commands in mind, not specific gestures, separating concerns between gestural identification (which can include cultural background elements) and actual commands.

Abstract
Linear Meld is a concurrent forward-chaining linear logic programming language where logical facts can be asserted and retracted in a structured way. In Linear Meld, a program is seen as a database of logical facts and a set of derivation rules. The database of facts is partitioned by the nodes of a graph structure which leads to parallelism when nodes are executed simultaneously. Due to the foundations on linear logic, rules can retract facts in a declarative and structured fashion, leading to more expressive programs. We present the design and implementation of the virtual machine that we implemented to run Linear Meld on multicores, with particular focus on thread management, code organization, fact indexing, rule execution, and database organization for efficient fact insertion, lookup and deletion. Our results show that the virtual machine is capable of scaling programs with up to 16 threads and also exhibits interesting scalar performance results due to our indexing optimizations.

Abstract

Abstract
The accuracy and precision of air quality models are usually associated with the emission inventories. Thus, in order to assess if there are any improvements on air quality regional simulations using detailed methodology of road traffic emission estimation, a regional air quality modelling system was applied. For this purpose, a combination of top-down and bottom-up approaches was used to build an emission inventory. To estimate the road traffic emissions, the bottom-up approach was applied using an instantaneous emission model (Vehicle Specific Power - VSP methodology), and an average emission model (CORINAIR methodology), while for the remaining activity sectors the top-down approach was used. Weather Research and Forecasting (WRF) and Comprehensive Air quality (CAMx) models were selected to assess two emission scenarios: (i) scenario 1, which includes the emissions from the top-down approach; and (ii) scenario 2, which includes the emissions resulting from integration of top-down and bottom-up approaches. The results show higher emission values for PM10, NOx and HC, for scenario 1, and an inverse behaviour to CO. The highest differences between these scenarios were observed for PM10 and HC, about 55% and 75% higher (respectively for each pollutant) than emissions provided by scenario 2. This scenario gives better results for PM10, CO and O-3. For NO2 concentrations better results were obtained with scenario 1. Thus, the results obtained suggest that with the combination of the top-down and bottom-up approaches to emission estimation several improvements in the air quality results can be achieved, mainly for PM10, CO and O-3.