Decoding with Stretched Pulses in Laser PPM Communications

The design and performance of optical PPM communication systems with ideal (rectangular) pulses have been well documented. However, many optical channels (fibers, atmosphere, clouds) are extremely dispersive to narrow pulses, producing receiver pulses that are spread (stretched) in time. This stretching produces interslot interference within a PPM frame, and if severe enough, can stretch over several frames (intersymbol interference). In this paper, laser pulse stretching in optical PPM formats is investigated in terms of performance degradation and decoder design alternatives. Several methods are considered for combating the pulse stretching, including pulse equalization, extended pulse integration, and pulse shape matching. Performance of these methods is compared for the case of exponential stretching and Gaussian statistics.     

PPM Performance for Reed-Solomon Decoding Over an Optical-RF Relay Link

Consideration is presently being given to an optical-RF relay deep space communication link that transmits optical PPM data from spacecraft to orbital relay, then retransmits the data via microwave to ground. It is generally advantageous to use Reed-Solomon (RS) encoding over the PPM optical link for improved error correction. In this paper several demodulating schemes are considered for generating the RS symbols at the relay photodetector output, and the effect of each on overall RS decoding performance is computed. Both Poisson and Gaussian optical noise models are used in the evaluation. The effect on performance of bit errors in the relay downlink is also examined.     

Building an infrastructure for scientific Grid computing: status and goals of the EGEE project

The state of computer and networking technology today makes the seamless sharing of computing resources on an international or even global scale conceivable. Scientific computing Grids that integrate large, geographically distributed computer clusters and data storage facilities are being developed in several major projects around the world. This article reviews the status of one of these projects, Enabling Grids for E-SciencE, describing the scientific opportunities that such a Grid can provide, while illustrating the scale and complexity of the challenge involved in establishing a scientific infrastructure of this kind.     

PSEN1 Compound Heterozygous Mutations Associated with Cerebral Amyloid Angiopathy and Cognitive Decline Phenotype

Cerebral amyloid angiopathy (CAA) is a cerebrovascular disorder caused by the deposition of amyloid beta-peptide (Aβ) aggregates. Aβ aggregates lead to vessel rupture and intracerebral hemorrhages, detected by magnetic resonance imaging (MRI). Presenile CAA is usually genetically determined by mutations in the amyloid precursor protein (APP) gene. However, mutations after codon 200 in the presenilin 1 (PSEN1) gene have been reported to facilitate CAA onset. Here, we analyzed the genetic bases in a patient of 55 years old affected by CAA and cognitive decline. DNA was isolated and genetic analysis was performed by Next-Generation Sequencing (NGS). RNA was extracted and retro-transcribed to perform segregation analysis by TOPO-TA cloning. WB analysis was carried out to check the impact of the mutations on protein. Two compound heterozygous mutations in PSEN1 exon 10, such as a novel stop-gain mutation (c.1070C > G) and a pathogenic splice variant (c.1129A > T), were found by NGS. Both mutations altered the presenilin 1 protein, truncating its C-terminal portion. This is the first case of CAA and cognitive decline caused by two compound mutations in PSEN1. With this report, we suggest extending the genetic analysis to PSEN1 when cerebral microbleeds are observed by MRI investigation in a patient affected by presenile cognitive decline.     

Tuning the Hydrophobicity of a Mitochondria‐Targeted NO Photodonor

A few compounds in which the nitric oxide (NO) photodonor N‐[4‐nitro‐3‐(trifluoromethyl)phenyl]propane‐1,3‐diamine is joined to the mitochondria‐targeting alkyltriphenylphosphonium moiety via flexible spacers of variable length were synthesized. The lipophilicity of the products was evaluated by measuring their partition coefficients in n‐octanol/water. The obtained values, markedly lower than those calculated, are consistent with the likely collapsed conformation assumed by the compounds in solution, as suggested by molecular dynamics simulations. The capacity of the compounds to release NO under visible light irradiation was evaluated by measuring nitrite production by means of the Griess reaction. The accumulation of compounds in the mitochondria of human lung adenocarcinoma A549 cells was assessed by UPLC–MS. Interestingly, compound 13 [(9‐((3‐((4‐nitro‐3‐(trifluoromethyl)phenyl)amino)propyl)amino)‐9‐oxononyl) triphenylphosphonium bromide] displayed both the highest accumulation value and high toxicity toward A549 cells upon irradiation‐mediated NO release in mitochondria.     

Design of an optimized procedure to predict opposite performances in porthole die extrusion

The main objective of advanced manufacturing control techniques is to provide efficient and accurate tools in order to control the set-up of machines and manufacturing systems. Recent developments and implementations of expert systems and neural networks support this aim. This research explores the combined use of neural networks and Taguchi’s method to enhance the performance of porthole die extrusion process; the energy saving and the quality of the welding line are two conflicting objectives of the process taken into account. The complexity of the analysis, due to the number of the involved variables, does not allow the representation of the specified outputs by means of a simple analytical approach. The implementation of a more accurate and sophisticated tool, such as the neural network, results more efficient and easier to be integrated into a simple “ready to use” procedure for predicting the investigated outputs. The main limit to wider implementation of neural networks is the huge computation resources (times and capacities) required to build the data set; a finite element approach was adopted to overcome the time and money wasting typical of experimental investigations. Satisfactory results in terms of prediction capability of the highlighted outputs were found. Finally, a simple and integrated interface was designed to make easier the application of the proposed procedure and to allow the generalization to other manufacturing processes.     

Graphitized filament plasma enhanced CVD deposition of nanocrystalline diamond

A novel approach to the deposition of polycrystalline diamond is presented. The technique is based on the hot filament chemical vapour deposition technique (HFCVD). While it is similar to a high plasma power “bias enhanced growth” HFCVD, it relies on a graphite filament rather than on a metal one. It was found that with an appropriate choice of the growth parameters, 4–9% CH₄ in H₂, filament temperature > 2200 °C, 25 mBar gas pressure, plasma power > 500 W, a long filament lifetime can be achieved, when a simultaneous deposition of graphitic carbon on the hot graphite filament and of nanocrystalline diamond on a substrate facing the filament assembly is realized. In this paper the growth of nanocrystalline diamond films and their characterization (SEM, XRD, AFM) are presented. While the technique is promising for low cost, large area deposition of nanocrystalline diamond films, also the growth of microcrystalline diamond has been observed.