n/a

n/a

Cement bonded particle board (CBPB) is a composite material produced in plates consisting mainly of wood and cement, and may contain additives. This material is currently used in cladding, raised floors, dropped ceilings, prefabricated houses, office containers and various supplies to the building industry such as kitchens, bathrooms and furniture. It is composed of a type of wood Pinus pinaster and/or Pinus pinea, Portland cement type II, sodium silicate and aluminium sulphate. CBPB has been the subject of several studies with the purpose of enabling the use of other types of wood or even vegetable biomass, as the chemical compounds from wood (extractives and sugars) tend to inhibit of cement hydration. A study on the behaviour of short CBPB elements under compression was carried out in the Department of Civil Engineering of Universidade NOVA de Lisboa with the aim of enabling its use in structural elements. The study was supported by VIROC, the company which produces CBPB in Portugal. This paper presents and analyses the most significant results of a campaign of axial compression tests performed on 111 specimens of different heights and cross sections. The behaviour of CBPB specimens of varying slenderness was subjected to a more detailed analysis.

The goal of this paper is to present a comparison among three known metaheuristics: Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Simulated Annealing (SA). For the comparison, the design of an LC - Voltage Controlled Oscillator (LC-VCO) is considered, where the minimization of both VCO phase noise and power consumption is envisaged. The objective of this comparison is to find the algorithm yielding the best solution. The validity of the solution obtained with each metaheuristic algorithm is checked against HSPICE/RF simulation results. Robustness checks for each algorithm are presented at the end of this paper.

The present work focuses on a qualitative analysis of localised I-V characteristics based on the nanostructure morphology of highly dense arrays of p-type NiO nano-pillars (NiO-NPs). Vertically aligned NiO-NPs have been grown on different substrates by using a glancing angle deposition (GLAD) technique. The preferred orientation of as grown NiO-NPs was controlled by the deposition pressure. The NiO-NPs displayed a polar surface with a microscopic dipole moment along the (111) plane (Tasker's type III). Consequently, the crystal plane dependent surface electron accumulation layer and the lattice disorder at the grain boundary interface showed a non-uniform current distribution throughout the sample surface, demonstrated by a conducting AFM technique (c-AFM). The variation in I-V for different points in a single current distribution grain (CD-grain) has been attributed to the variation of Schottky barrier height (SBH) at the metal-semiconductor (M-S) interface. Furthermore, we observed that the strain produced during the NiO-NPs growth can modulate the SBH. Inbound strain acts as an external field to influence the local electric field at the M-S interface causing a variation in SBH with the NPs orientation. This paper shows that vertical arrays of NiO-NPs are potential candidates for nanoscale devices because they have a great impact on the local current transport mechanism due to its nanostructure morphology.

The effect of post-deposition annealing temperature on the pH sensitivity of room temperature RF sputtered Ta₂O₅ was investigated. Structural and morphological features of these films were analyzed before and after annealing at various temperatures. The deposited films are amorphous up to 600 °C and crystallize at 700 °C in an orthorhombic phase. Electrolyte-insulator-semiconductor (EIS) field effect based sensors with an amorphous Ta2O5 sensing layer showed pH sensitivity above 50 mV/pH. For sensors annealed above 200 °C pH sensitivity decreased with increasing temperature. Stabilized sensor response and maximum pH sensitivity was achieved after low temperature annealing at 200 °C, which is compatible with the use of polymeric substrates and application as sensitive layer in oxides TFT-based sensors.

The Graphics Processing Unit (GPU) is gaining popular- ity as a co-processor to the Central Processing Unit (CPU). However, harnessing its capabilities is a non-trivial exercise that requires good knowledge of parallel programming, more so when the complexity of these applications is increasingly rising. Languages such as StreamIt [1] and Lime [2] have addressed the offloading of composed computations to GPUs. However, to the best of our knowledge, no support exists at library level. To this extent, we propose Marrow, an algorithmic skeleton frame- work for the orchestration of OpenCL computations. Marrow expands the set of skeletons currently available for GPU computing, and enables their combination, through nesting, into complex structures. Moreover, it introduces optimizations that overlap communication and computa- tion, thus conjoining programming simplicity with performance gains in many application scenarios. We evaluated the framework from a perfor- mance perspective, comparing it against hand-tuned OpenCL programs. The results are favourable, indicating that Marrow’s skeletons are both flexible and efficient in the context of GPU computing.

This paper proposes a set of metrics for the assessment of the complexity of models defining the business logic of spreadsheets. This set can be considered the first step in the direction of building a quality standard for spreadsheet models, that is still to be defined. The computation of concrete metric values has further been integrated under a well-established model-driven spreadsheet development environment, providing a framework for the analysis of spreadsheet models under spreadsheets themselves.

n/a