Technical note: Advantages and limitations of authenticating Palmera goat dairy products by pyrosequencing the melanocortin 1 receptor (MC1R) gene

Inferring the breed of origin of dairy products can be achieved through molecular analysis of genetic markers with a population-specific pattern of segregation. The goal of the current work was to generate such markers in goats by resequencing several pigmentation genes [melanocortin 1 receptor (MC1R), v-kit Hardy-Zuckerman 4 feline sarcoma viral oncogene homolog (KIT), tyrosinase (TYR), and tyrosinase-related protein 2 (TYRP2)]. This experiment revealed 10 single nucleotide polymorphisms (SNP), including 5 missense mutations and 1 nonsense mutation. These markers were genotyped in 560 goats from 18 breeds originally from Italy, the Iberian Peninsula, the Canary Islands, and North Africa. Although the majority of SNP segregated at moderate frequencies in all populations (including 2 additional markers that were used as a source of information), we identified a c.764G>A SNP in MC1R that displayed highly divergent allelic frequencies in the Palmera breed compared with the Majorera and Tinerfeña breeds from the Canary Islands. Thus, we optimized a pyrosequencing-based technique that allowed us to estimate, very accurately, the allele frequencies of this marker in complex DNA mixtures from different individuals. Once validated, we applied this method to generating breed-specific DNA profiles that made it possible to detect fraudulent cheeses in which Palmero cheese was manufactured with milk from Majorera goats. One limitation of this approach, however, is that it cannot be used to detect illegal manufacturing where Palmero dairy products are produced by mixing milk from Palmera and Majorera goats, because the c.764G>A SNP segregates in both breeds.     

Rainwater and greywater harvesting for urban food security in La Soukra,Tunisia

This paper presents the findings of an integrated household water treatment and reuse system for agriculture in La Soukra, Tunisia. The researchers found that the system has an internal rate of return of 17% and a net present value range from USD 26,000 (at a 5% discount rate) to USD 11,000 (for a 10% discount rate). Benefits included more water for irrigation, reduced costs to service providers, increased agricultural production from greenhouses and expanded agricultural options. These results suggest that investments in rainwater harvesting and greywater treatment at the farm level can increase the financial feasibility of peri-urban farms, which are often faced with pressure from urban growth. The systems can also help build household resilience to broader environmental change by lowering the exposure of farmers to burdens associated with infrequent access to water and poor-quality soil.     

Fuzzy VA-Files for multi-label image annotation based on visual content of regions

In this work, we propose an efficient image annotation approach based on visual content of regions. We assume that regions can be described using low-level features as well as high-level ones. Indeed, given a labeled dataset, we adopt a probabilistic semantic model to capture relationships between low-level features and semantic clusters of regions. Moreover, since most previous works on image annotation do not deal with the curse of dimensionality, we solve this problem by introducing a fuzzy version of the Vector Approximation Files (VA-Files). Indeed, the main contribution of this work resides in the association of the generative model with fuzzy VA-Files, which offer an accurate multi-dimensional indexing, to estimate relationships between low-level features and semantic concepts. In fact, the proposed approach reduces the computation complexity while optimizing the annotation quality. Preliminary experiments highlight that the suggested approach outperforms other state-of-the-art approaches.     

An efficient design of CORDIC in Quantum-dot cellular automata technology

Power dissipation of future-integrated systems, consisting of a numberless of devices, is a challenge that cannot be easily solved by classical technologies. Quantum-dot Cellular Automata (QCA) is a Field-Coupled Nanotechnology (FCN) and a potential alternative to traditional CMOS technologies. It offers various features like extremely low-power dissipation, very high operating frequency and nanoscale feature size. This study presents a novel design of CORDIC circuit based on QCA technology. The proposed circuit is based on several proposed QCA sub-modules as adder and Flip-Flop. To design and verify the proposed architecture, QCADesigner tool is employed and power consumption is estimated using QCAPro software. The proposed QCA CORDIC achieves about 69% reduction in power and area compared to previous existing designs. The outcome of this work can open up a new window of opportunity for the design of the CORDIC module and can be used in low-power signal and image processing systems.     

Prioritized assertional-based removed sets revision of <Emphasis Type="Italic">DL</Emphasis>-<Emphasis Type="Italic">Lite</Emphasis> belief bases

In real world applications, information is often provided by multiple sources having different priority levels reflecting for instance their reliability. This paper investigates ”Prioritized Removed Sets Revision” (PRSR) for revising stratified DL-Lite knowledge bases when a new sure piece of information, called the input, is added. The strategy of revision is based on inconsistency minimization and consists in determining smallest subsets of assertions (prioritized removed sets) that should be dropped from the current stratified knowledge base in order to restore consistency and accept the input. We consider different forms of input: A membership assertion, a positive or a negative inclusion axiom. To characterize our revision approach, we first rephrase Hansson’s postulates for belief bases revision within a DL-Lite setting, we then give logical properties of PRSR operators. In some situations, the revision process leads to several possible revised knowledge bases where defining a selection function is required to keep results within DL-Lite fragment. The last part of the paper shows how to use the notion of hitting set in order to compute the PRSR outcome. We also study the complexity of PRSR operators, and show that, in some cases, the computational complexity of the result can be performed in polynomial time.     

Search-based detection of model level changes

Software models, defined as code abstractions, are iteratively refined, restructured, and evolved due to many reasons such as reflecting changes in requirements or modifying a design to enhance existing features. For understanding the evolution of a model a-posteriori, change detection approaches have been proposed for models. The majority of existing approaches are successful to detect atomic changes. However, composite changes, such as refactorings, are difficult to detect due to several possible combinations of atomic changes or eventually hidden changes in intermediate model versions that may be no longer available. Moreover, a multitude of refactoring sequences may be used to describe the same model evolution. In this paper, we propose a multi-objective approach to detect model changes as a sequence of refactorings. Our approach takes as input an exhaustive list of possible types of model refactoring operations, the initial model, and the revised model, and generates as output a list of refactoring applications representing a good compromise between the following two objectives (i) maximize the similarity between the expected revised model and the generated model after applying the refactoring sequence on the initial model, and (ii) minimize the number of atomic changes used to describe the evolution. In fact, minimizing the number of atomic changes can important since it is maybe easier for a designer to understand and analyze a sequence of refactorings (composite model changes) rather than an equivalent large list of atomic changes (Weissgerber and Diehl 2006). Due to the huge number of possible refactoring sequences, a metaheuristic search method is used to explore the space of possible solutions. To this end, we use the non-dominated sorting genetic algorithm (NSGA-II) to find the best trade-off between our two objectives. The paper reports on the results of an empirical study of our multi-objective model changes detection technique as applied on various versions of real-world models taken from open source projects and one industrial project. We compared our approach to the simple deterministic greedy algorithm, multi-objective particle swarm optimization (MOPSO), an existing mono-objective changes detection approach, and two model changes detection tools not based on computational search. The statistical test results provide evidence to support the claim that our proposal enables the generation of changes detection solutions with correctness higher than 85 %, in average, using a variety of real-world scenarios.     

Tensile properties of a Fe-32Mn-6Si shape memory alloy

The tensile properties of a Fe-32Mn-6Si shape memory alloy were investigated. It was found that tensile properties depend on temperature, heat treatment and material structure. The relationships of martensitic transformation, tensile properties, and shape memory effect are discussed. Finally, we propose a macroscopic one-dimensional constitutive law describing the thermomechanical behavior in tensile loading. Numerically obtained results are close to the experimental ones. __________ Translated from Problemy Prochnosti, No. 2, pp. 55–65, March–April, 2008.     

Long term change of nutrient concentrations of rivers discharging in European seas

Cases of severe eutrophication are still observed in European surface waters even though tough regulation has been in place since the beginning of the 1990s to control nutrient losses and inputs in the environment. The purpose of this paper is to evaluate the evolution since 1991 of the quality of the water entering European seas in terms of the concentration of major nutrients (nitrogen and phosphorus), and to analyze the effectiveness of implemented national/international measures and EU legislation in reducing water nutrient pollution. Despite the reduction in large portions of the European territory of agricultural nutrient applications and nutrient point source emissions, the impact on water quality is limited. It is shown using two large river basins that this lack of response for nitrogen, and nitrate in particular, between the reduction of the nitrogen surplus and the recovery of water quality is partly explained by the lag time due to transfer of nitrates in the unsaturated and saturated zones and storage in the soils and aquifers. In order to monitor efficiently the impact of policy implementation on water quality, the Nitrates Directive and the Urban Waste Water Treatment Directive in particular, it is recommended to use long term permanent monitoring stations to be able to separate the impact of climate variability from that of policy implementation. It is also recommended to investigate and develop harmonized methodologies for estimating the lag time in order to come up with realistic estimates of response time of water bodies due to the implementation of measures.