Visible micro-Raman spectroscopy for determining glucose content in beverage industry

The potential of Raman spectroscopy with excitation in the visible as a tool for quantitative determination of single components in food industry products was investigated by focusing the attention on glucose content in commercial sport drinks. At this aim, micro-Raman spectra in the 600–1600 cm⁻¹ wavenumber shift region of four sport drinks were recorded, showing well defined and separated vibrational fingerprints of the various contained sugars (glucose, fructose and sucrose). By profiting of the spectral separation of some peculiar peaks, glucose content was quantified by using a multivariate statistical analysis based on the interval Partial Least Square (iPLS) approach. The iPLS model needed for data analysis procedure was built by using glucose aqueous solutions at known sugar concentrations as calibration data. This model was then applied to sport drink spectra and gave predicted glucose concentrations in good agreement with the values obtained by using a biochemical assay. These results represent a significant step towards the development of a fast and simple method for the on-line glucose quantification in products of food and beverage industry.     

RFCM-PALM: In-Silico Prediction of S-Palmitoylation Sites in the Synaptic Proteins for Male/Female Mouse Data

S-palmitoylation is a reversible covalent post-translational modification of cysteine thiol side chain by palmitic acid. S-palmitoylation plays a critical role in a variety of biological processes and is engaged in several human diseases. Therefore, identifying specific sites of this modification is crucial for understanding their functional consequences in physiology and pathology. We present a random forest (RF) classifier-based consensus strategy (RFCM-PALM) for predicting the palmitoylated cysteine sites on synaptic proteins from male/female mouse data. To design the prediction model, we have introduced a heuristic strategy for selection of the optimum set of physicochemical features from the AAIndex dataset using (a) K-Best (KB) features, (b) genetic algorithm (GA), and (c) a union (UN) of KB and GA based features. Furthermore, decisions from best-trained models of the KB, GA, and UN-based classifiers are combined by designing a three-star quality consensus strategy to further refine and enhance the scores of the individual models. The experiment is carried out on three categorized synaptic protein datasets of a male mouse, female mouse, and combined (male + female), whereas in each group, weighted data is used as training, and knock-out is used as the hold-out set for performance evaluation and comparison. RFCM-PALM shows ~80% area under curve (AUC) score in all three categories of datasets and achieve 10% average accuracy (male—15%, female—15%, and combined—7%) improvements on the hold-out set compared to the state-of-the-art approaches. To summarize, our method with efficient feature selection and novel consensus strategy shows significant performance gains in the prediction of S-palmitoylation sites in mouse datasets.     

Fermi Level Control of Point Defects During Growth of Mg-Doped GaN

In this study, Fermi level control of point defects during metalorganic chemical vapor deposition (MOCVD) of Mg-doped GaN has been demonstrated by above-bandgap illumination. Resistivity and photoluminescence (PL) measurements are used to investigate the Mg dopant activation of samples with Mg concentration of 2 × 10¹⁹ cm^?3 grown with and without exposure to ultraviolet (UV) illumination. Samples grown under UV illumination have five orders of magnitude lower resistivity values compared with typical unannealed GaN:Mg samples. The PL spectra of samples grown with UV exposure are similar to the spectra of those grown without UV exposure that were subsequently annealed, indicating a different incorporation of compensating defects during growth. Based on PL and resistivity measurements we show that Fermi level control of point defects during growth of III-nitrides is feasible.     

Enzyme distribution and secondary structure of sol–gel immobilized glucose oxidase by micro-attenuated total reflection FT-IR spectroscopy

Glucose oxidase (GOD) immobilized into sol–gel matrices was studied by using Micro-Attenuated Total Reflection Fourier Transform Infrared (micro-ATR FT-IR) spectroscopy in order to characterize enzyme distribution and secondary structure in systems with valuable potentialities in amperometric and optical biosensing. Spectra were acquired in the 4000–600 cm^? 1 frequency region and the analysis of specific fingerprints in the FT-IR spectra evidenced that the enzyme was actually immobilized in the matrix. The enzyme spatial distribution was obtained by examining the amide I and amide II band region of spectra from defined sample positions. The deconvolution of the amide I band in terms of lorentzian functions provided information on the secondary structure of the immobilized GOD. By this approach a macroscopic preservation of GOD activity upon immobilization was evidenced along with the existence of some matrix sites with locally inactivated GOD. To our knowledge this is the first example of point-by-point characterization of conformational changes of immobilized enzyme by means of micro-ATR infrared spectroscopy, thus confirming that this technique can be usefully employed for a non- or minimally-invasive detailed micro-characterization of catalytic supports in order to improve their functionality.     

Off-line Bangla handwritten word recognition: a holistic approach

Neural Computing and Applications - Due to the cursive nature, segmentation of handwritten Bangla words into characters and also recognition of the same sometimes become a very challenging problem...     

Nonidealities of Tow-Thomas biquads Using VOA- and CFOA-based Miller integrators

An analysis and comparison of the performance of Tow-Thomas biquadratic filter sections, implemented with Miller integrators based on current feedback opamps (CFOAs) and voltage opamps (VOAs) was carried out. We found that the implementations with CFOAs show less parameter accuracy and an increased tendency to become unstable. Design criteria to partially overcome these drawbacks and to maximally exploit the inherent high-speed potential of CFOAs were also derived. The theoretical derivations and related results were experimentally validated through implementations from commercially available devices.     

Systolic array architecture implementing Berlekamp-Massey-Sakata algorithm for decoding codes on a class of algebraic curves

We construct a two-dimensional systolic array implementing the Berlekamp-Massey-Sakata (BMS) algorithm to provide error-locator polynomials for codes on selected algebraic curves. This array is constructed by introducing some new polynomials in order to increase the parallelism of the algorithm. The introduced polynomials are used in the majority logic scheme by Sakata et al. to correct errors up to the designed minimum distance without affecting its high speed. The arrangement of the nearest local connection of processing units in the systolic array is obtained for the general case. Furthermore, shortened systolic arrays that reduce the circuit scale and have the same function are constructed with only a slight modification of the connections and controls; this enables the adjustment of the circuit scale for different types of systems.     

Direct polymer-transfer lithography for high-throughput fabrication of Cu line patterns

A novel direct polymer-transfer lithography (DPTL) technique is proposed for fabricating fine patterns having feature sizes ranging from ten to several tens of micrometers with extremely high throughput. By means of this technique, a homemade fluorine-containing polymer “ink”, which has good water repellency, was imprinted directly onto a Cu/polyimide sheet by using an elastomeric polydimethylsiloxane (PDMS) stamp; imprinting was followed by wet etching of the Cu layer, with the transferred polymer patterns serving as an etch mask. Under the optimized imprinting conditions, Cu lead patterns with a minimum line width of approximately 10 μm were successfully fabricated with high accuracy and good reproducibility. The DPTL technique will be very useful for manufacturing flexible printed circuit boards (FPCs).     

A fast driver circuit for single-photon sensors

A fast active quenching and recharging circuit (AQRC) for single-photon avalanche diodes (SPAD) is presented in this paper. The proposed driver exhibits a lower than 10 ns overall quenching time allowing a tunable excess voltage from 5 to 12 V. The circuit was designed by using the dielectrically insulated BiCMOS technology supplied by ST Microelectronics. Many post-layout ELDO simulations have validated the high performance of the proposed topology, which is actually the fastest AQRC reported in the literature.