Secure logarithmic audio watermarking scheme based on the human auditory system

Peer-reviewed

Z2Z4-Additive Perdect Codes in Steganography

Steganography is an information hiding application which aims tohide secret data imperceptibly into a cover object. In this paper, we describe anovel coding method based on Z2Z4-additive codes in which data is embeddedby distorting each cover symbol by one unit at most (+-1-steganography). Thismethod is optimal and solves the problem encountered by the most e cientmethods known today, concerning the treatment of boundary values. Theperformance of this new technique is compared with that of the mentionedmethods and with the well-known rate-distortion upper bound to conclude thata higher payload can be obtained for a given distortion by using the proposedmethod.

Nutrimetabolomics fingerprinting to identify biomarkers of bread exposure in a free-living population from the PREDIMED study cohort

Bread is one of the most widely consumed foods. Its impact on human health is currently of special interest for researchers. We aimed to identify biomarkers of bread consumption by applying a nutrimetabolomic approach to a free-living population. An untargeted HPLC q-TOF-MS and multivariate analysis was applied to human urine from 155 subjects stratified by habitual bread consumption in three groups: non-consumers of bread (n = 56), white-bread consumers (n = 48) and whole-grain bread consumers (n = 51). The most differential metabolites (variable importance for projection ≥1.5) included compounds originating from cereal plant phytochemicals such as benzoxazinoids and alkylresorcinol metabolites, and compounds produced by gut microbiota (such as enterolactones, hydroxybenzoic and dihydroferulic acid metabolites). Pyrraline, riboflavin, 3-indolecarboxylic acid glucuronide, 2,8-dihydroxyquinoline glucuronide and N-α-acetylcitrulline were also tentatively identified. In order to combine multiple metabolites in a model to predict bread consumption, a stepwise logistic regression analysis was used. Receiver operating curves were constructed to evaluate the global performance of individual metabolites and their combination. The area under the curve values [AUC (95 % CI)] of combined models ranged from 77.8 % (69.1 86.4 %) to 93.7 % (89.4 98.1 %), whereas the AUC for the metabolites included in the models had weak values when they were evaluated individually: from 58.1 % (46.6 69.7 %) to 78.4 % (69.8 87.1 %). Our study showed that a daily bread intake significantly impacted on the urinary metabolome, despite being examined under uncontrolled free-living conditions. We further concluded that a combination of several biomarkers of exposure is better than a single biomarker for the predictive ability of discriminative analysis.

Nutrimetabolomics fingerprinting to identify biomarkers of bread exposure in a free-living population from the PREDIMED study cohort

Bread is one of the most widely consumed foods. Its impact on human health is currently of special interest for researchers. We aimed to identify biomarkers of bread consumption by applying a nutrimetabolomic approach to a free-living population. An untargeted HPLC q-TOF-MS and multivariate analysis was applied to human urine from 155 subjects stratified by habitual bread consumption in three groups: non-consumers of bread (n = 56), white-bread consumers (n = 48) and whole-grain bread consumers (n = 51). The most differential metabolites (variable importance for projection ≥1.5) included compounds originating from cereal plant phytochemicals such as benzoxazinoids and alkylresorcinol metabolites, and compounds produced by gut microbiota (such as enterolactones, hydroxybenzoic and dihydroferulic acid metabolites). Pyrraline, riboflavin, 3-indolecarboxylic acid glucuronide, 2,8-dihydroxyquinoline glucuronide and N-α-acetylcitrulline were also tentatively identified. In order to combine multiple metabolites in a model to predict bread consumption, a stepwise logistic regression analysis was used. Receiver operating curves were constructed to evaluate the global performance of individual metabolites and their combination. The area under the curve values [AUC (95 % CI)] of combined models ranged from 77.8 % (69.1 86.4 %) to 93.7 % (89.4 98.1 %), whereas the AUC for the metabolites included in the models had weak values when they were evaluated individually: from 58.1 % (46.6 69.7 %) to 78.4 % (69.8 87.1 %). Our study showed that a daily bread intake significantly impacted on the urinary metabolome, despite being examined under uncontrolled free-living conditions. We further concluded that a combination of several biomarkers of exposure is better than a single biomarker for the predictive ability of discriminative analysis.

Combined dielectrophoretic and impedance system for on-chip controlled bacteria concentration: Application to Escherichia coli

The present paper reports a bacteria autonomous controlled concentrator prototype with a user-friendly interface for bench-top applications. It is based on a micro-fluidic lab-on-a-chip and its associated custom instrumentation, which consists in a dielectrophoretic actuator, to pre-concentrate the sample, and an impedance analyser, to measure concentrated bacteria levels. The system is composed by a single micro-fluidic chamber with interdigitated electrodes and a instrumentation with custom electronics. The prototype is supported by a real-time platform connected to a remote computer, which automatically controls the system and displays impedance data used to monitor the status of bacteria accumulation on-chip. The system automates the whole concentrating operation. Performance has been studied for controlled volumes of Escherichia coli (E. coli) samples injected into the micro-fluidic chip at constant flow rate of 10 μL/min. A media conductivity correcting protocol has been developed, as the preliminary results showed distortion of the impedance analyser measurement produced by bacterial media conductivity variations through time. With the correcting protocol, the measured impedance values were related to the quantity of bacteria concentrated with a correlation of 0.988 and a coefficient of variation of 3.1%. Feasibility of E. coli on-chip automated concentration, using the miniaturized system, has been demonstrated. Furthermore, the impedance monitoring protocol had been adjusted and optimized, to handle changes in the electrical properties of the bacteria media over time.