Dysprosium doped Ga:La:S glass for an efficient optical fibreamplifier operating at 1.3 μm

The authors present experimental results which indicate that a Dy ³⁺-doped Ga:La:S glass fibre amplifier may be operated efficiently at 1.3 μm with an optimum device length significantly shorter than a comparable Pr³⁺-doped glass fibre amplifier. Moreover, the efficiency exceeds that obtained from the Pr³⁺-doped ZBLAN devices currently available     

Chirp compensation capability of a semiconductor laser amplifier

Performance improvement is reported resulting from incorporating a semiconductor laser amplifier (SLA) as a post-transmitter-amplifier in long-haul directly modulated optical systems operating in the 1.5 mu m region. This improvement arises from reduction of the chirp produced by the semiconductor laser as the signal passes through the SLA. Eye closure penalty improvements in excess of 5 dB are observed for an illustrative long-haul 4.8 Gbit/s system.<>     

Experimental design to evaluate properties of electrospun fibers of zein/poly (ethylene oxide) for biomaterial applications

The production of polymer fibers from the combination of zein and PEO might have great potential in the field of biomaterial. Zein/PEO fibers were obtained in this work through solution electrospinning. An experimental design, 2^4-1, was used for evaluating the influences of PEO content in the blend, distance from the needle tip to the collector, applied electric voltage and solution flow for average fiber diameter and relative-yield process. Beyond this, the relationship between PEO content in the blend and the fiber properties were evaluated through FTIR, DSC, TG, tensile tests, and cytotoxic tests. The factor that exerts the greatest effect on the average fiber diameter response was the electrical voltage. The increase in PEO content in the blend decreased the thermal stability and increased the degree of the fibers' crystallinity. The mechanical tests showed that fibers with higher elongation were obtained at richer PEO blends. The fibers presented cytocompatible characteristics.     

An adaptive learning approach for 3-D surface reconstruction from point clouds.

In this paper, we propose a multiresolution approach for surface reconstruction from clouds of unorganized points representing an object surface in 3-D space. The proposed method uses a set of mesh operators and simple rules for selective mesh refinement, with a strategy based on Kohonen's self-organizing map (SOM). Basically, a self-adaptive scheme is used for iteratively moving vertices of an initial simple mesh in the direction of the set of points, ideally the object boundary. Successive refinement and motion of vertices are applied leading to a more detailed surface, in a multiresolution, iterative scheme. Reconstruction was experimented on with several point sets, including different shapes and sizes. Results show generated meshes very close to object final shapes. We include measures of performance and discuss robustness.     

A hybrid linear-neural model for time series forecasting

This paper considers a linear model with time varying parameters controlled by a neural network to analyze and forecast nonlinear time series. We show that this formulation, called neural coefficient smooth transition autoregressive model, is in close relation to the threshold autoregressive model and the smooth transition autoregressive model with the advantage of naturally incorporating linear multivariate thresholds and smooth transitions between regimes. In our proposal, the neural-network output is used to induce a partition of the input space, with smooth and multivariate thresholds. This also allows the choice of good initial values for the training algorithm.     

Effect of chitosan and Dysphania ambrosioides on the bone regeneration process: A randomized controlled trial in an animal model

The focus of this triple‐blind study was on evaluating the effect of chitosan combined with Dysphania ambrosioides (A) extract on the bone repair process in vivo. In total, 60 male Wistar rats (Rattus norvegicus albinus) weighing between 260 and 270 g were randomly selected for this study and distributed into four groups (n = 15). Group C (chitosan), Group CA5 (chitosan + 5% of D. ambrosioides), Group CA20 (chitosan + 20% of D. ambrosioides), and Group CO (Control‐Blood clot). In each animal, bone defects measuring 2 mm in diameter were performed in both tibias for placement of the substances. After 7, 15, and 30 days, the animals were sedated and sacrificed using the cervical dislocation technique and the tissues were analyzed under optical microscope relative to the following events: inflammatory infiltrate, necrosis, osteoclasts, osteoblasts, fibroblasts, periosteal, and endosteal bone formation. The data were evaluated to verify distribution using the Kolmogorov–Smirnov test, and variance, using the Levene test; as distribution was not normal, data were subjected to the Kruskal–Wallis and Dunn nonparametric tests (p < .05). A significant inflammatory infiltrate was observed in Group CA5 (p = .008) in the time interval of 7 days, and in Group C at 15 (p = .009) and 30 (p = .017) days. Osteoblastic activity was more significant in Group CA20 (p = .027) compared with CA5 in the time interval of 7 days. Group CA20 demonstrated a significantly higher endosteal and periosteal bone formation value in the time interval of 7 (p = .013), 15 (p = .004), and 30 days (p = .008) compared with the other groups. The null hypothesis was refuted, bone regeneration was faster in spheres with an association of chitosan and 20% extract, and complete bone repair occurred clinically at 15 days and histologically at 30 days. The spheres proved to be a promising method for the biostimulation of alveolar bone repair and bone fractures.     

A methodology for screening of microalgae as a decision making tool for energy and green chemical process applications

The increasing interest for biotechnological use of microalgae demands a methodology for selection of species suitable to support the development of technologies based on the use of such non-conventional renewable raw material, i.e., green industrial applications. The vast and expanding collection of experimental data on both cell growth and biomass composition available in the literature can be used to reduce the cost of the experimental investigations required to support process engineering and optimization. Selecting the appropriate organism requires extracting useful information from such data, a cumbersome task since various multidisciplinary factors must be considered. This paper presents a computer-aided methodology for selecting appropriate algal species given an energy or green chemical process application employing microalgae as a renewable raw material. The approach is “system oriented”, based on biomass composition and chemical processing of the biomass downstream of the CO₂ biofixation and harvesting operations. Quantitative performance results are supported by professional process simulation. Besides comparison of a set of species performances, the proposed methodology also allows the discrimination among distinct algal compositions resulting from different growth conditions for a given species. Furthermore, three categories of screening metrics are proposed to be maximized by the decision making procedure in order to elicit the relevant information. To demonstrate the potential of the proposed methodology, a databank of both biochemical and elemental compositions of microalgal biomass was used in three green applications: Assessment of biomass heating value; production of syngas by gasification of the biomass; and production of Bio-H₂. Within the accuracy of the databank employed to illustrate the procedure, the methodology selected Botryococcus braunii and Isochrysis galbana as potential promising candidates, for the three examined applications.     

Relationship between solar radiation and surface distribution of vegetation in Fildes Peninsula and Ardley Island,Maritime Antarctica

The aim of this work is to produce a simplified vegetation map of ice-free areas of the Fildes Peninsula (FP) and Ardley Island (AI) thought object-oriented classification using a QuickBird satellite image and to evaluate the influence of the global solar radiation (GSR) over the vegetation distribution. The vegetation data were generated from multiresolution segmentation using the panchromatic and infrared layers, and for the classification we calculated the normalized vegetative difference index (NVDI) and the green NVDI. Two classes were created – Lichen and Moss Cushion SubFormation and Moss Subformation – with 48 vegetation samples collected on surveys during the austral summers of 2008 and 2009. We used a kappa index to evaluate the classification efficiency using 100 sampled points obtained in austral summer of 2013. The GSR was estimated, and in order to evaluate the effect of meteorological phenomena and cloudless, we measured the GSR using a net radiometer model CNR4 installed in FP between 2014 and 2016. The estimate of GSR was done for seasons of 2015, in order to estimate the light compensation point and the saturation point for the plant communities in FP and AI. The kappa index was 0.73 and the global accuracy was 0.78, showing consistency between the classification and ground truth. The area was covered by vegetation in FP was 16.7% and in AI is 59.1%. The vegetation cover is distributed differently at FP and AI, and our results suggest GSR plays an important role in vegetation distribution and these tendencies could be related to greater GSR demand by mosses when compared to lichens.     

Dual joints for 3D-structures

The increasing popularity of 3D printing is drawing the interest of the research community to the possibilities and challenges of this manufacturing method. Amongst its many uncertainties, we are concerned here with one of its certainties—that reduction of the material required in 3D printing is critical for efficiency and affordability. In this paper, we propose a solution to the computer graphics problem of, given a volume boundary, automatically defining the mesh of a low density internal structure that is 3D-printable. The proposed solution involves two steps. The first step is to define a cell complex partition for the internal space of a volume defined by its boundaries. The second step, is to apply the Skin4Skeleton algorithm, which uses the cell complex dual to produce a 3D-printable cell-complex mesh with a parametrised thickness.