Suboptimum soft-output detection algorithms for coded multiuser systems

In this paper, we consider coded asynchronous multiuser signals in an additive white Gaussian noise channel. Since optimum joint multiuser detection (MUD) and forward error correction (FEC) decoding is characterized with a very high computational complexity, we consider disjoint MUD and FEC decoding. The optimum disjoint multiuser detector is the soft-output maximum a posteriori detector that provides sequences of a posteriori probabilities to the corresponding FEC decoders. It involves backward and forward recursions resulting in high complexity and processing delay. In this paper, we consider several suboptimum soft output disjoint multiuser detectors that involve only forward recursions and have reduced complexity and delay.     

Estimation of Sc3+ solubility in dodecahedral and octahedral sites in YSAG:Yb

A method for synthesizing YSAG:Yb optical ceramics has been developed. Additionally, the phase composition and unit cell parameters for YSAG, YbSAG, and their solid solutions have been determined. The limits of scandium solubility in the dodecahedral and octahedral sites of garnet crystal lattice have been estimated after annealing at 1600°C. The scandium solubility limit in the dodecahedral sites of YSAG:Yb was found to be 66 ± 2 at.%. The limit of scandium solubility in octahedral sites depended upon the type of garnet-forming cations. The solubility limit for Sc³⁺ decreased from 97.5 ± 0.5 to 68.5 ± 1 at.% with simultaneous increase of ytterbium content in the YSAG-YbSAG system. Therefore, the region of solid solutions existing with a garnet structure in the Al₂O₃–Sc₂O₃–Yb₂O₃–Y₂O₃ system was determined. Samples having scandium in both dodecahedral and octahedral sites, which had a Sc³⁺ content of ~30 at.%, were synthesized as a precursor for optical ceramic production.     

Active neural learners for text with dual supervision

Neural Computing and Applications - Dual supervision for text classification and information retrieval, which involves training the machine with class labels augmented with text annotations that...     

Fruit Polyphenols: A Review of Anti-inflammatory Effects in Humans

Underlying etiological factors in the development of obesity-related chronic diseases are long-term imbalances of oxidative and inflammatory stress leading to tissue dysfunction, damage, and ultimately failure. Poor dietary quality contributes significantly to the oxidative and inflammatory status of an individual. Conversely, various dietary approaches, including specific dietary factors can mitigate or prevent the occurrence of these risk-conferring imbalances brought about by modern lifestyle. Plant-derived polyphenolic compounds are well known for their antioxidant properties. Recent evidence indicates these compounds may confer anti-inflammatory and/or inflammatory response stabilizing activities, which would have important implications in health maintenance and disease risk reduction. Commonly consumed fruits, such as grapes, berries, and oranges/orange juice, contain polyphenolic compounds that have been studied for their effects on inflammation, but the nature and extent of their effects in humans remain unclear. Therefore, this article aims to provide a comprehensive overview of human clinical trials investigating the acute and chronic (feeding) effect of polyphenols from commonly consumed fruits or their derived products on inflammation.     

Relevance of ROT control for hot rolled low carbon steels

The need for precision in controlling coiling temperature and cooling profiles on the run out table for hot rolled low carbon steel strips has been investigated. It is claimed in literature that a high degree of automation and control of the run out table is required to control the yield strength variation to within 20 MPa. However, calculations based on models available in literature predict that the variation in strip temperature encountered in a typical run out table does not affect the mechanical property significantly. This has been shown to be true even from experimental data available in literature. Hence even a coarse control over the run out table is adequate to achieve the desired yield strength. A detailed report concentrating on the influence of coiling temperature on the mechanical properties of HSLA steels is under preparation.     

Estimating the maximum growth rate from microbial growth curves: definition is everything

The maximum growth rate (μ_max) is an important parameter in modelling microbial growth under batch conditions. However, there are two definitions of this growth parameter in current use and some of the comparisons of data made in the literature fail to acknowledge this important fact.We compared values of μ_max obtained by applying the Gompertz, logistic and Baranyi–Roberts models to experimental data on the growth of Listeria monocytogenes and Listeria innocua using both absorbance and viable counts measurements of cell concentration. All three models fitted the experimental data well, however, the values of μ_max obtained using the Gompertz and logistic models were similar to each other but substantially different from those predicted by the Baranyi–Roberts model. The latter growth model was used to derive a second estimate of μ_max based on the slope at the inflection point of the growth curve function; this value was in closer agreement with those obtained using the Gompertz or logistic models. Conditions were identified when values of μ_max based on different definitions would converge towards one another.     

Role of catalytic protein and stabilising agents in the transformation of Ag ions to nanoparticles by Pseudomonas aeruginosa

Biological routes of synthesising metal nanoparticles (NPs) using microbes have been gaining much attention due to their low toxicity and eco‐friendly nature. Pseudomonas aeruginosa JP2 isolated from metal contaminated soil was evaluated towards extracellular synthesis of silver NPs (AgNPs). Cell‐free extract (24 h) of the bacterial isolate was reacted with AgNO₃ for 24 h in order to fabricate AgNPs. Preliminary observations were recorded in terms of colour change of the reaction mixture from yellow to greyish black. UV‐visible spectroscopy of the reaction mixture has shown a progressive increase in optical densities that correspond to peaks near 430 nm, depicting reduction of ionic silver (Ag⁺) to atomic silver (Ag⁰) thereby synthesising NPs. X‐ray diffraction spectra exhibited the 2θ values to be 38.4577° confirming the crystalline and spherical nature of NPs [9.6 − 26.7 (Ave. = 17.2 nm)]. Transmission electron microscopy finally confirmed the size of the particles varying from 5 to 60 nm. Moreover, rhamnolipids and proteins were identified as stabilising molecules for the AgNPs through Fourier transform‐infrared spectroscopy. Characterisation of bacterial crude and purified protein fractions confirmed the involvement of nitrate reductase (molecular weight 66 kDa and specific activity = 3.8 U/mg) in the Synthesis of AgNPs.Inspec keywords: microorganisms, silver, nanoparticles, enzymes, molecular biophysics, ultraviolet spectra, visible spectra, X‐ray diffraction, transmission electron microscopy, Fourier transform infrared spectra, catalysis, biochemistry, nanobiotechnologyOther keywords: catalytic protein, stabilising agents, Pseudomonas aeruginosa, metal nanoparticles, UV–visible spectroscopy, optical densities, ionic silver, atomic silver, X‐ray diffraction spectra, transmission electron microscopy, nitrate reductase, rhamnolipids, Fourier transform‐infrared spectroscopy, Ag     

Automation of human behaviors and its prediction using machine learning

Microsystem Technologies - Prediction is a method of detecting a person's behavior toward online buying by evaluating publically available evaluations on the web. Understanding expressive human...     

Linearization design method in class-F power amplifier using artificial neural network

This paper represents the design of a class-F power amplifier (PA), its artificial neural network (ANN) model and a PA linearization method. The designed PA operates at 1.8 GHz with gain of 12 dB and 1dB output compression point (P1dB) of 36 dBm. The proposed ANN model is used to predict the output power of designed class-F PA as a function of input and DC power. This model utilizes the designed class-F PA as a block, which could be used in a desired linearization circuit. In addition, the power added efficiency (PAE) and the other specifications of a PA, related to power can be predicted using the proposed model. A simple feedforward technique is used to improve the linearity of designed PA. For verification, this linearization method is compared with presented neural network model simulations. The results show the improvement of P1dB from 36 to 41 dBm, which is predicted using the proposed model. Also, the PAE of the final linearized circuit PA is predicted.