Comparison of gene nature used in real-time PCR for porcine identification and quantification: A review

Pork adulteration has been a major concern nowadays for Halal verification. Unintentional pork inclusion by contamination in highly processed food materials involves a minute amount of porcine DNA to be detected, emphasizing the need of specific and sensitive method for porcine detection. Real-time PCR is a widely used technique for species identification that can serve this purpose besides providing a powerful quantification method. Incorporation of a highly sensitive and specific probe can greatly improve the specificity and sensitivity of the assay. However, derivation of PCR primers, either from nuclear DNA (nDNA) or mitochondrial DNA (mtDNA) can relatively affect the sensitivity and specificity of the reaction as well as the quantitative measurement. In this review, both types of DNA are compared in terms of their characteristics and their influence on species identification and quantification using real-time PCR.     

Partial information basis for agent-based collaborative dialogue

We propose a partial information state-based framework for collaborative dialogue and argument between agents. We employ a three-valued based nonmonotonic logic, NML3, for representing and reasoning about Partial Information States (PIS). NML3 formalizes some aspects of revisable reasoning and it is sound and complete. Within the framework of NML3, we present a formalization of some basic dialogue moves and the rules of protocols of some types of dialogue. The rules of a protocol are nonmonotonic in the sense that the set of propositions to which an agent is committed and the validity of moves vary from one move to another. The use of PIS allows an agent to expand consistently its viewpoint with some of the propositions to which another agent, involved in a dialogue, is overtly committed. A proof method for the logic NML3 has been successfully implemented as an automatic theorem prover. We show, via some examples, that the tableau method employed to implement the theorem prover allows an agent, absolute access to every stage of a proof process. This access is useful for constructive argumentation and for finding cooperative and/or informative answers.     

Changes in EEG activity before and after exhaustive exercise in sedentary women in neutral and hot environments

This study examined the effect of hyperthermia on brain electrical activity measured with encephalography during prolonged exhaustive exercise in a group of sedentary women (VO₂max = 35 ± 4 mL kg min⁻¹). Two strenuous cycling exercises were performed either in neutral (N-Ex) or in heat (H-Ex) conditions. Tympanic temperature (Tty), heart rate (HR), body mass loss (BML), plasma volume decrease, and brain electrical activity [EEG: α (8–13 Hz) and β(13–30 Hz)-band and α/β index of fatigue: the ratio between EEG activity in the α band and β-band] were recorded throughout the cycling sessions. The Tty increase 1.0 °C in the N-Ex and 1.8 °C in H-Ex. HR increased in both sessions but with significantly higher values during the H-Ex session when compared with the N-Ex session (p < 0.001) (from 85 ± 4 beats min⁻¹ to 164 ± 6 beats min⁻¹ and from 83 ± 6 beats min⁻¹ to 181 ± 8 beats min⁻¹, respectively in N-Ex and in H-Ex). This was associated with a significantly higher BML (p < 0.05) and a higher plasma volume decrease in the H-Ex session (p < 0.01). The α/β index increased significantly during both trials particularly during the H-Ex session (p < 0.05). This was associated with a significant decrease of time to exhaustion (−34%). We suggest that exhausting work in the heat induced a change in gross brain activity (alpha/beta ratio) compared to a longer, less thermally demanding exposure. Fatigue in the heat could be attributed to central factors as well as thermal, cardiac and hydro-electrolytic impairment.     

Improved bounds for hybrid flow shop scheduling with multiprocessor tasks

In this paper, we investigate the problem of minimizing makespan in a multistage hybrid flow-shop scheduling with multiprocessor tasks. To generate high-quality approximate solutions to this challenging NP-hard problem, we propose a discrepancy search heuristic that is based on the new concept of adjacent discrepancies. Moreover, we describe a new lower bound based on the concept of dual feasible functions. The proposed lower and upper bounds are assessed through computational experiments conducted on 300 benchmark instances with up to 100 jobs and 8 stages. For these instances, we provide evidence that the proposed bounds consistently outperform the best existing ones. In particular, the proposed heuristic successfully improved the best known solution of 75 benchmark instances.     

Feature selection using Bayesian and multiclass Support Vector Machines approaches: Application to bank risk prediction

This paper presents methods of banks discrimination according to the rate of NonPerforming Loans (NPLs), using Gaussian Bayes models and different approaches of multiclass Support Vector Machines (SVM). This classification problem involves many irrelevant variables and comparatively few training instances. New variable selection strategies are proposed. They are based on Gaussian marginal densities for Bayesian models and ranking scores derived from multiclass SVM. The results on both toy data and real-life problem of banks classification demonstrate a significant improvement of prediction performance using only a few variables. Moreover, Support Vector Machines approaches are shown to be superior to Gaussian Bayes models.     

Multi-objective exploration of architectural designs by composition of model transformations

Software and Systems Modeling - Designing software architectures and optimizing them based on extra-functional properties (EFPs) require to identify appropriate design decisions and to apply them...     

Antioxidant and antithrombotic effects of green mussels (Perna canaliculus) in rats

In the past decade, the use of marine mussels as seafood is being more popular. They considered being a rich source of various nutritional bioactive compounds that aroused the scientific community's interest. This study investigated the antioxidant and the antithrombotic consequences on Sprague-Dawley male rats after adding dried New Zealand mussel Perna canaliculus in their diet. The biochemical, hematological and histopathological changes were also observed. Forty rats were divided into four groups according to the amount of dried mussels in their diet, in addition to a control group that consumed a basal diet only. Group 1 consumed 25% dried mussels in its basal diet; Group 2 consumed 35% dried mussels in its basal diet, and Group 3 was consumed 45% dried mussels in its basal diet. The biochemical parameters showed improvements in liver function. Interestingly, the lipid profile decreased, especially the low-density lipoprotein cholesterol (LDL-C) levels which were reduced significantly in Group 3 (p < .01). These observations were accompanied by a decrease in iron levels significantly as the amount of dried mussels increased (p < .01). Furthermore, the noticed changes in the hematological profile prove that there is an increase in antithrombotic activity. Dried mussels had potent antioxidant effects in the liver as shown by increased lipid peroxide (p < .05), reduced glutathione (p < .05), and glutathione peroxidase (GSH-Px; p < .05). Additionally, antioxidant activity in the kidney was shown to increase through GSH-Px activity (p < .01). In conclusion, these results indicate that consuming dried mussels resulted in improved biochemical and antioxidants activities and could be used as an antithrombotic agent.     

Near‐infrared spectroscopy and data analysis for predicting milk powder quality attributes

Near‐infrared (NIR) spectroscopy is a rapid analytical method for food products. In this study, NIR spectroscopy, data pretreatment techniques and multivariate data analysis were used to predict fine particle size fraction, dispersibility and bulk density of various milk powder samples, which are believed to have a significant impact on milk powder quality. Predictive models using partial least‐squares (PLS) regression were developed using NIR spectra and milk powder physical and functional properties, and it was concluded that the PLS models predicted milk powder quality with an accuracy of 88‐90 per cent.     

Survivability of probiotics encapsulated in alginate gel microbeads using a novel impinging aerosols method

Encapsulation of probiotic bacteria in cross-linked alginate beads is of major interest for improving the survivability in harsh acid and bile environment and also in food matrices. Alginate micro beads (10-40 μm) containing the probiotics Lactobacillus rhamnosus GG and Lactobacillus acidophilus NCFM were produced by a novel technique based on dual aerosols of alginate solution and CaCl₂ cross linking solution. Extruded macro beads (approximately 2 mm diameter) produced by the conventional method and micro beads produced by novel aerosols technique offered comparable protection to L. rhamnosus in high acid and bile environment. Chitosan coating of micro beads resulted in a significant increase in survival time of L. rhamnosus from 40 to 120 min in acid condition and the reduction in cell numbers was confined to 0.94 log over this time. Alginate macro beads are more effective than micro beads in protecting L. acidophilus against high acid and bile. Chitosan coating of micro beads resulted in similar protection to L. acidophilus in macro beads in acid and extended the survival time from 90 to at least 120 min. Viability of this organism in micro beads was 3.5 log after 120 min. The continuous processing capability and scale-up potential of the dual aerosol technique offers potential for an efficient encapsulation of probiotics in very small alginate micro beads below sensorial detection limits while still being able to confer effective protection in acid and bile environment.