Miracle-dz/UniFAR-FTUs huggingface dataset:
Influence of Variables Encoding and Symmetry Breaking on the Performance of Optimization Modulo Theories Tools Applied to Cloud Resource Selection

The problem of Cloud resource provisioning for component-based applications is very important. It consists in the allocation of virtual machines (VMs) from various Cloud Providers (CPs), to a set of applications such that the constraints induced by the interactions between components and by the components hardware/software requirements are satisﬁed and the performance objectives are optimized (e.g. costs are minimized). It can be formulated as a constrained optimization problem and tackled by state-of-the-art optimization modulo theories (OMT) tools. The performance of the OMT tools is highly dependent on the way the problem is formalized as this determines the size of the search space. In the case when the number of VMs oﬀers is large, a naive encoding which does not exploit the symmetries of the underlying problem leads to a huge search space making the optimization problem intractable. We overcame this issue by reducing the search space by using: (1) a heuristic which exploits the particularities of the application by detecting cliques in the conﬂict graph of the application components ﬁxing all components of the clique with the largest number of component instances, and (2) a lex-leader method for breaking variable symmetry where the canonical solution fulﬁlls an order based on either the number of components deployed on VMs, or on the VMs price. As the result, the running time of the optimization problem improves considerably and the optimization problem scales up to hundreds of VM oﬀers. We also observed that by combining the heuristic with the lex-leader method we obtained better computational results than by using them separately, suggesting the fact that symmetry breaking constraints have the advantage of interacting well with the search heuristic being
CONVENIENT METHOD FOR RAPID AND QUANTITATIVE ASSESSMENT OF SALMONELLA ENTERICA CONTAMINATION: THE MINI‐MSRV MPN TECHNIQUE

Direct assessment of Salmonella numeration is still a challenge in cases of numerous number of low Salmonella/competitive flora ratio samples. Nowadays the usable methods provide data with such large confident intervals that the obtained results do not justify the labor and time spent. So we developed a method based on miniaturization of the dilution, preenrichment and selective enrichment on MSRV steps and on automation as the transfers are performed with multichannel pipettes. This so called mini-MSRV method provides a rapid and convenient way to assess the quantification Salmonella in studies providing many samples. After description of the method, this paper presents the results obtained from 3 different types of samples issued from 3 different steps of the production chain where quantitative assessment of the Salmonella risk may be useful.
A Review of Micropterix Hubner, 1825 from Northern and Central Europe (Micropterigidae)

4 Reischenbachweg 2, 5400 Hallein-Rif, Austria; e-mail: michael.kurz@gmx.at Abstract. All known species of the Palaearctic genus Micropterix Hubner, 1825 (Micropterigidae) from northern, north-western, central and north-eastern Europe including the Alps are reviewed. The purpose of this review is to permit reliable identifi cation of the genus in this region. Adults, male and female genitalia are illustrated for eighteen species. For these, taxonomy, adult life history (preferred biotopes, phenology and pollination records) and variability is detailed. Distribution is summarized for each species. Treated species are fully diagnosed and also compared with extralimital taxa. The presently known species diver- sity of Micropterix is assessed and a brief synopsis of diagnostic characters for the genus is given in the context of what is known for the family worldwide. A checklist is provided and a key is presented based on adult wing pattern and characters of the male and female genitalia. Advice on genitalic preparation and information about suitable collection sites is also provided.
Organs development, gene expression and health of Atlantic salmon (Salmo salar L.) fed genetically modified soybeans compared to the near‐isogenic non‐modified parental line

The present experiment was conducted to study the possible effects of genetically modified (GM), full-fat soybean meal (FFSBM) from Round-up Ready® soybeans compared to its parental, and closest near-isogenic, non-modified (nGM) soybean variety, added at moderate (150 g kg−1) and high (300 g kg−1) inclusion levels. The fish showed a high specific growth rate (SGR 1.27–1.52), and nearly doubled their body weight (BW), with final weights varying from 1009 to 1110 g. Increased levels of dietary FFSBM, independent of the soy being GM or not, significantly decreased mean values of SGR, thermal growth rate, condition factor, final BW, liver somatic index, lipid efficiency ratio, apparent digestibility coefficients (ADC) of protein and gross energy, liver lipid content and plasma cholesterol, and significantly increased ADC of starch and muscle fatty acid levels of 18:3n-3, 20:4n-6, 20:5n-3 and total n-3. Increasing dietary GM FFSBM significantly increased feed conversion ratio, and significantly decreased protein efficiency ratio, ADC of lipid and dry matter and plasma triacylglycerol (TAG) levels. Spleen somatic index was significantly larger in fish groups fed GM FFSBM compared to groups fed nGM FFSBM, which might indicate a possible immune response exerted by the GM soybeans. Mean normalized expression of heat shock protein 70 mRNA in distal intestine was significantly up-regulated while normalized expression of catalase in liver was down-regulated, in fish fed FFSBM compared to fish fed FM. In conclusion, substituting moderate to high levels of GM Round-up Ready® FFSBM in diets for Atlantic salmon and compared to the closest near-isogenic counterpart available, resulted in many effects independent of the soy being GM or not, but with the notable exceptions of enlarged spleen and lowered plasma TAG.
Survival and reproductive potential of gamma irradiated male Glossina pallidipes Austen

Glossina pallidipes Austen is an important vector of both animal and human trypanosomosis in the East and Central African Region where it occurs in discrete pockets either alone or with other species of tsetse. These species of tsetse and the diseases they transmit, are among major factors preventing the establishment of sustainable agricultural systems in these areas. Several control attempts have resulted in dramatic reduction in the target population, but eradication has not been achieved (Allsopp, 1999; Brightwell et al., 1997; Dransfield et al., 1990). This therefore results in continual reliance on inputs to keep the vector population at a low level. Integration of the sterile insect technique (SIT), at the final phase of a control programme, would result in eradication as has recently been clearly demonstrated in Zanzibar (Vreysen et al., 2000) In preparation for an SIT component of the G. pallidipes eradication project in the Southern Rift valley, Ethiopia, the effect of gamma irradiation on laboratory reared sexually mature male G. pallidipes was studied. The effect of gamma irradiation on a number of economically important tsetse species has been investigated (see Vreysen et al., 1996) but not on G. pallidipes except for early work on radiation on field collected pupae (Dean & Clements, 1969). In the present paper, the survival of irradiated males and fecundity of females mated to irradiated males was monitored and a sterilising dose identified.
Choosing Prior Hyperparameters: With Applications to Time-Varying Parameter Models

Time-varying parameter models with stochastic volatility are widely used to study macroeconomic and financial data. These models are almost exclusively estimated using Bayesian methods. A common practice is to focus on prior distributions that themselves depend on relatively few hyperparameters such as the scaling factor for the prior covariance matrix of the residuals governing time variation in the parameters. The choice of these hyperparameters is crucial because their influence is sizeable for standard sample sizes. In this article, we treat the hyperparameters as part of a hierarchical model and propose a fast, tractable, easy-to-implement, and fully Bayesian approach to estimate those hyperparameters jointly with all other parameters in the model. We show via Monte Carlo simulations that, in this class of models, our approach can drastically improve on using fixed hyperparameters previously proposed in the literature. Supplementary materials for this article are available online.
Hybrid G-PRNU: Optimal parameter selection for scale-invariant asymmetric source smartphone identification

The ease in counterfeiting both origin and content of a video necessitates the search for a reliable method to identify the source of a media file a crucial part of forensic investigation. One of the most accepted solutions to identify the source of a digital image involves comparison of its photo-response non-uniformity (PRNU) fingerprint. However, for videos, prevalent methods are not as efficient as image source identification techniques. This is due to the fact that the fingerprint is affected by the postprocessing steps done to generate the video. In this paper, we answer affirmatively to the question of whether one can use images to generate the reference fingerprint pattern to identify a video source. We introduce an approach called “Hybrid G-PRNU” that provides a scale-invariant solution for video source identification by matching its fingerprint with the one extracted from images. Another goal of our work is to find the optimal parameters to reach an optimal identification rate. Experiments performed demonstrate higher identification rate, while doing asymmetric comparison of video PRNU with the reference pattern generated from images, over several test cases. Further the fingerprint extractor used for this paper is being made freely available for scholars and researchers in the domain.
Latent Fingerprint Enhancement via Time Variance Gabor and Sparse Representation

: Latent fingerprint images are usually of poor quality with unclear ridge structure. Latent fingerprint identification plays an important role for identifying criminals in law enforcement agencies and resolving various overlapping patterns of fingerprints. Although significant advances and research have been achieved on developing automated fingerprint identification system, it is still challenging to achieve reliable feature extraction and identification for latent fingerprints due to the poor image quality and unclear ridge structure. Earlier to feature extraction, fingerprint enhancement is necessary to minimize various noises and improve the clarity of ridge structures in latent fingerprints. First, the total variation model is used to decompose the latent fingerprint into cartoon and texture components. The cartoon component with most of the non-fingerprint patterns is removed which is known as the structured noise, whereas the texture component consisting of the weak latent fingerprint is enhanced in the next step. Second, we propose a multi scale patch-based sparse representation method for the enhancement of the texture component. Dictionaries are constructed with a set of Gabor elementary functions to capture the characteristics, features and properties of fingerprint ridge structure, and Multi scale patch-based sparse representation is iteratively applied to reconstruct high-quality fingerprint image. The proposed algorithm cannot only remove the overlapping structured noises, but also restore and enhance the corrupted ridge structures. In addition, we present an automatic method to segment the foreground of latent image with the sparse coefficients. On NIST SD27 latent fingerprint database is used to show the effectiveness of the proposed algorithm and its superiority over existing algorithms.
Linear relations in biomechanics: the statistics of scaling functions

The problem of fitting a linear relation to a bivariate data cluster obtained from morphometric measurement or from experiment is formulated rigorously, and a family of solutions (the general structural relation, g.s.r.) is derived. The regression, reduced major axis and major axis models are special cases of this model; it permits a more realistic treatment of the errors in the variates, in particular when the errors are correlated, which is particularly important in the many biological situations in which the variates contain uncontrolled real variation in addition to measurement errors. The analysis is particularly directed to the testing of hypotheses about scaling relations derived from biomechanical theory. By making different assumptions about the configuration of the errors, the g.s. r. can also be used to test for transposition allometry and for the significance of an estimated or hypothesized gradient. The model generalizes simply to multivariate problems. Application is demonstrated with examples drawn from the study of bird flight mechanics. Finally, it is demonstrated that since observed quantities correspond to peaks of adaptation or of selective fitness, scaling relations are determined primarily by scale variation of constraints on adaptation and behaviour, and are the result of a variety of interacting factors rather than a response to a single selective force described by one simple hypothesis.
Population genetic structure of wild rice Oryza glumaepatula distributed in the Amazon flood area influenced by its life‐history traits

Wild plant species develop their own way of living to adapt to the specific environment of their habitats. Their life‐history traits strongly affect the genetic structure of the population. The wild species Oryza glumaepatula Steud. growing in the Amazon basin seems to have characteristic life‐history traits suited for the flood condition. At the vegetative growth stage, the culms frequently break at internodes. With no roots anchoring on the ground, plant bodies floating in the water move downriver by water current and wind. To examine the association between the life‐history traits and genetic population structure of Amazonian O. glumaepatula, we analysed allozyme variability at 29 loci of 16 enzymes using 37 populations from five regions. Allozymes were not so variable (total gene diversity HE = 0.044) compared with Asian wild rice, O. rufipogon Griff. The bottleneck effect and rare opportunity of interspecies gene flow may prevent the development of allozyme variability. Population genotypes tended to be differentiated among geographically isolated regions. Observed heterozygosities were much lower than expected heterozygosities, or gene diversity (HO = 0.003 for whole population) and FIS over polymorphic loci was 0.931, indicating that O. glumaepatula has developed an inbreeding system. But, the intrapopulation gene diversity (HS) was higher than interpopulation gene diversity (DST), as generally observed in outbreeding populations. The migration ability of O. glumaepatula makes long‐distance seed dispersal possible. This might have led to frequent gene flow among populations.
Tandemly Repeated Sequence Families in Micronuclear DNA of the Ciliate Stylonychia pustulata

One third of a collection of cloned Stylonychia pustulata micronuclear DNA PstI fragments were found to be of a similar size, consistent with their being members of a repetitious sequence family with a repeat size of about 160 base pairs. Cross-hybridization experiments confirmed that these small cloned fragments are related by sequence homology. Hybridization of the cloned repetitious sequences to PstI digested micronuclear DNA revealed a “ladder” of bands (step size = 160 base pairs), indicating that the repeats are found in tandem arrays. This is the first demonstration of highly repetitious, tandemly repeated sequences in a ciliated protozoan.
Married Women

This chapter presents recommended strategies for incorporating gender concerns in the major subsectors in agriculture. Each section also contains a chart outlining the key gender-related information needs for each subsector and boxes illustrating good practices from project experience. 1. Issues In most countries, ownership of farmland is vested primarily in men. Women often have usufruct rather than ownership rights to land. Usufruct rights often entail less secure tenure and less ease in disposing of those rights by sale, lending, bequest, or mortgage. Where women own land, female-headed households tend to have smaller farms on average than male-headed households. Women who are not household heads are even less likely to have title to land than those who are. In some countries, women are not able to inherit land; in others, although they have the legal right, custom dictates that they do not inherit or should pass inherited land on to their husbands or a male relative. In many African countries, when a man dies, rights to the house, land, tools, and equipment customarily revert to his ancestral family. Land ownership and legal title to land for women producers can sometimes be helpful in overcoming production constraints; however, experience suggests that agrarian reform, land tenure and registration, as well as settlement schemes have often permanently consolidated male ownership rights to land at the expense of women's usufruct and ownership rights under traditional and customary law. Usufruct rights entail less secure tenure and less ease in disposing of those rights by sale, lending, bequest , or mortgage. Whether land is allocated by traditional or government authority, ownership rights usually go to men. Many agrarian reform programs have failed to recognize the land ownership rights of: • Married women • Women household heads • Women producers with partial or temporary land rights. For men as well as women, lack of title usually implies lower productivity levels and yields because of: • Weak incentives for land maintenance and improvement activities, such as irrigation • Little interest in investing in permanent crops • Lack of collateral for credit for improved inputs and fertilizer.
Double decision-feedback multiple differential detection for double differential encoding

: This paper proposes double decision-feedback multiple di ﬀ erential detection (DDFMDD) of double di ﬀ erential encoding (DDE) for fast time-varying Rayleigh fading. DDE can improve tracking capability at a large modulation alphabet size. In order to improve performance in the required signal to noise power ratio (SNR) and tracking capability aiming at higher frequency e ﬃ ciency, the proposed DDFMDD employs decision-feedback multiple di ﬀ erential detection (DFMDD) with channel averaging and DFMDD with channel prediction. Finally, computer simulation results con ﬁ rm that the proposed DDFMDD has excellent bit error rate (BER) performance for fast time-varying Rayleigh fading at a larger modulation alphabet size.
Field parametric geostatistics - An alternative to tackle gold grade estimations

High anomalous grades are very common in gold deposits, whose presence requires careful treatment to prevent overestimation of metal content. Mineral resource analysts have worked on the estimation of several gold deposits, and none of the classical methods were able to avoid manual interventions, such as cutting high grades for local estimation or using more information beyond the data for the variogram inference. The Field Parametric Geostatistics (FPG) is presented as an alternative for the application of linear kriging methods to estimate highly skewed distributions, proposing a mathematical model which incorporates the grades and its representativeness into a new variable, reducing the influence of high grades without empirical manual interventions. In this article, the mathematical formulation of the FPG theory is presented, as well as its application in datasets with outliers and high skewed distributions: the Walker Lake dataset and the Amapari gold deposit. The results are compared to results obtained by the application of standard techniques, demonstrating that FPG is a feasible alternative to estimate local grades and local reserves for highly skewed variables.
Improved Context-aware YouTube Recommender System with User Feedback Analysis

YouTube is one of the most popular video sharing website being used by the users throughout the world. For providing ease to the user it offers a list of recommended videos every time the user searches some content. But many times the provided or recommended videos are not related to context that the user had searched. This is due to the title and the description of the videos which are although related to the keyword that the user had searched but the content of the video may be different. Moreover, the videos are recommended on the premise of users’ interest irrespective of the context they are in. Therefore, the recommended videos cover different interests of the user altogether. The existing approaches are predominantly based on content and collaborative recommendations. So in this research work, the proposed and recommended approach is context based. The recommended videos are to be positioned on the basis of association and comment feedback. Moreover, for improving the quality of ranking, structural analysis (i.e. Meta information about the videos) is also performed on each video to get high relativity videos.
Analysis of coconut cultivars and hybrids using isozyme polymorphism

The coconut (Cocos nucifera L.) is one of the major oilseeds of India. In the present study, an attempt has been made to analyse coconut diversity using isozyme banding data. Cluster analysis was performed using the banding patterns obtained from polyacrylamide gel electrophoresis for 11 isozyme systems in 40 different coconut cultivars and six hybrids and their parents. The cultivars grouped mainly into six clusters. In case of hybrids and their parents, the hybrids clustered intermediate between parents.