Miracle-dz/UniFAR-FTUs huggingface dataset:
Detecting Wildlife Poaching: Identifying the Origin of Individuals with Bayesian Assignment Tests and Multilocus Genotypes

Abstract: Illegal harvesting is a serious threat to the persistence of many plant and animal taxa. The combination of highly polymorphic DNA markers and new statistical methods called “assignment tests” can potentially help detect and thereby reduce poaching. Assignment tests can identify the population of origin of individuals if populations are genetically differentiated. We evaluated the usefulness of two assignment tests to wildlife forensics by applying them to large empirical (microsatellite DNA) data sets from 10 species. We also conducted computer simulations to assess the influence of genetic polymorphism ( heterozygosity) and population differentiation ( FST ) on the performance of the tests. The fully Bayesian assignment test of Pritchard et al. (2000) performed better than the partially Bayesian exclusion test of Cornuet et al. (1999) , but the fully Bayesian method requires the assumption that the true population of origin was sampled. The median percentage of individuals correctly assigned for the 10 empirical data sets was 61% and 36% for the assignment and exclusion tests, respectively. Both the empirical and simulated data sets suggest that nearly all individuals can be assigned with high statistical certainty (99.9%) for two highly differentiated populations ( FST≈ 0.15–0.2) when 10 loci ( H> 0.6) and samples of 30–50 individuals are used per population. We recommend using both tests when the true population of origin might not have been sampled in the data set.
The Spots of the Spotted Salamander Are Sexually Dimorphic

Brilliant and conspicuous coloration in animals is often thought to signal quality to conspecifics (sexual selection) or to signal unpalatability to predators (aposematic selection). Ambystoma maculatum (spotted salamanders) have bilateral rows of conspicuous bright yellow dorsal spots against dark skin. Although this coloration has been long thought a classic example of warning coloration, to date, there are no quantitative measures of spot coloration. We captured adult male and female A. maculatum as they entered breeding ponds and measured body condition, spectral reflectance of the yellow spots, spot size, and coverage of the dorsal area in spots. We found evidence of sexual dichromatism; males had a larger area of their dorsum covered in spots, and tended to have more chromatic, but less bright yellow color. Moreover, our data suggest a tradeoff between coloration and body condition. Animals in better body condition expressed lower chroma and those with greater spot coverage expressed brighter spots and lower yellow chroma. Although these data are not entirely consistent with the predictions of sexual selection, they suggest a physiological tradeoff associated with coloration that has not been documented in salamanders.
Climate change impacts on mean wind speeds in South Africa

Climate change could potentially affect a number of variables that impact the dispersal of and human exposure to air pollutants, as well as climate dependent sectors such as wind energy. This study attempted to quantify the projected changes in seasonal daily mean wind speeds for South Africa around the mid-21st century (2051-2075) under two different atmospheric heat pathways. Seasonal daily mean wind speed increases rarely reach 6% and decreases occur to a maximum of 3% and are variable between different seasons and areas within the country. In all seasons except December-January-February, wind speeds are projected to increase in the Highveld region, suggesting that air pollution dispersing conditions could increase. Wind direction at the 850hPa-level show minor changes, except over the Western and Eastern Cape provinces.
Error orientation questionnaire (EOQ): Reliability, validity, and different language equivalence

Summary An Error Orientation Questionnaire (EOQ) was developed, consisting of eight scales on attitudes to and on coping with errors at work. In Study I (representative sample of a German city, Na 478) six scales were developed with the help of a confirmatory factor analysis using LISREL techniques. They comprise error competence, learning from errors, error risk taking, error strain, erroranticipation, covering up errors. All constructs were validated. In a second study, items were added to the scales and two additional scales, ‘error communication’ and ‘thinking about errors’, were included. The scales were translated into English and Dutch and 160 students in the Netherlands filled out both language versions (Study II). The 8-factor solutions in English and Dutch were replicated. The issue of language equivalence of these two language versions were taken up (equivalence across correlations exists). Potentially biasing variables did not influence the solutions. Practical uses of the EOQ are pointed out. Copyright #1999 John Wiley & Sons, Ltd.
A New Intrusion Detection Model Based on Artificial Immune Algorithm

This paper introduces artificial immune to intrusion detection system through the analysis of the similarity of artificial immune and intrusion detection and puts forward a model of intrusion detection system based on artificial immune distributed agent. Firstly the system model structure is introduced and a hierarchical structure of intelligent agent is presented as well as a dynamic evolution model. At the same time a kind of vaccine immunization algorithm is put forward and network risk evaluation operator is given to evaluate real-time network security situation. This algorithm can keep the diversity of antibodies, and simultaneously has high convergence speed. The experimental results show that the proposed model has the feature of real-time processing that provides a good solution for heterogeneous fleet high-speed network environment.
Award For 1999 Stereotypes as Dynamic Constructs : Women and Men of the Past , Present , and Future

Dynamic stereotypes characterize social groups that are thought to have changed from the attributes they manifested in the past and even to continue to change in the future. According to social role theory’s assumption that the role behavior of group members shapes their stereotype, groups should have dynamic stereotypes to the extent that their typical social roles are perceived to change over time. Applied to men and women, this theory makes two predictions about perceived change: (a) perceivers should think that sex differences are eroding because of increasing similarity of the roles of men and women and (b) the female stereotype should be particularly dynamic because of greater change in the roles of women than of men. This theory was tested and confirmed in five experiments that examined perceptions of the roles and the personality, cognitive, and physical attributes of men and women of the past, present, and future.
Adaptation to climate change in Sub-Saharan agriculture: assessing the evidence and rethinking the drivers

In this paper, after a review of the evolution of the literature on climate change economics in agriculture, I present some evidence of the impact of different moments of the distribution of rainfall on farmers risk aversion. It is found that while more rainfall is negatively associated with the probability of observing risk aversion, rainfall variability is positively correlated. This result highlights an important behavioural dimension of climatic factors.
Distributed Agents for Web Content Filtering

This paper describe Web Content Filtering that aimed to block out offensive material by using Distributed Agents. The proposed system using FCM algorithm and other page's features (Title, Metadata , Warning Message) to classify the websites (using as candidate) into two types:white that considered acceptable, and black that contain harmful material taking the English Pornographic websites as a case study. Keywords—Web Content Filtering; Fuzzy C-Means Algorithm; Agent and MultiAgent System.
The Market for Tractors in the EU: Price Differences and Convergence. Factor Markets Working Documents No. 35, February 2013

This study evaluates the degree of segmentation of the market for agricultural machinery and equipment in the EU. We focus on agricultural tractors, the most common and biggest investment in machinery and equipment in the agricultural sector. By using country price data for individual tractor models, we test the law of one price, i.e. the existence of a common price for tractors across EU member states. We find that significant price differences exist, yet unlike most other studies we find that large price deviations are penalised within a short time. The study also shows that transport costs are an important source of price differences, as domestic production leads to lower prices on the domestic market and as price convergence is negatively correlated with distance. Finally, price differences should not solely be understood from a geographical perspective, as evidence supports the idea that farmers’ buying power is significant in explaining price differences within countries.
Rupture velocity of plane strain shear cracks

Propagation of plane strain shear cracks is calculated numerically by using finite difference equations with second-order accuracy. The rupture model, in which stress drops gradually as slip increases, combines two different rupture criteria: (1) slip begins at a finite stress level; (2) finite energy is absorbed per unit area as the crack advances. Solutions for this model are nonsingular. In some cases there may be a transition from rupture velocity less than Rayleigh velocity to rupture velocity greater than shear wave velocity. The locus of this transition is surveyed in the parameter space of fracture energy, upper yield stress, and crack length. A solution for this model can be represented as a convolution of a singular solution having abrupt stress drop with a ‘rupture distribution function. ’ The convolution eliminates the singularity and spreads out the rupture front in space-time. If the solution for abrupt stress drop has an inverse square root singularity at the crack tip, as it does for sub-Rayleigh rupture velocity, then the rupture velocity of the convolved solution is independent of the rupture distribution function and depends only on the fracture energy and crack length. On the other hand, a crack with abrupt stress drop propagating faster than the shear wave velocity has a lower-order singularity. A supershear rupture front must necessarily be spread out in space-time if a finite fracture energy is absorbed as stress drops.
Original Article Hypoxic conditioned medium of placenta-derived mesenchymal stem cells inhibits TGF-β1-induced up-regulation of collagens and differentiation of skin fibroblasts to myofibroblast through IL-10

Scar formation affects the quality of people's daily lives, and in this study we explored whether hypoxic conditioned medium of placenta-derived mesenchymal stem cells (PMSCs) has a protective effect on scar forma- tion. Our study showed that hypoxic conditioned medium of PMSCs inhibited the transforming growth factor-β1 (TGF- β1)-induced up-regulation of collagens and differentiation of skin fibroblasts to myofibroblast. Mechanism study showed that the level of interleukin-10 (IL-10) was influenced by hypoxic culture condition of PMSCs and further study showed that IL-10 simulated the effects of hypoxic conditioned medium of PMSCs to inhibit TGF-β1-induced up-regulation of collagens and α-smooth muscle actin (α-SMA), whereas, the inhibition effects of hypoxic condi- tioned medium of PMSCs on TGF-β1-induced up-regulation of collagens and α-SMA was reversed by IL-10 antibody. Results of this study suggested that hypoxic conditioned medium of PMSCs performed a protective effect against scar formation through the regulation of IL-10. This study provides further evidence for the possible use of PMSCs as a promising method to treat wounds.
Investigating the role of infant-directed speech with a computer model

A computer model (expectation maximization of a mixture of Gaussians) is used to learn the positions of vowel categories from two sets of recorded words. The number of vowels is known beforehand. The results show that vowel positions learned on the basis of infant-directed (ID) speech correspond better to those in the input than those learned on the basis of adult-directed (AD) speech.
Ã¢ÂÂComparison between Electrical Stimulation over Motor Point and TENS overAcupuncture Point in Reducing Spasticity and Improving Function after Stroke:Randomized Clinical TrialÃ¢ÂÂ

Purpose: To compare the effectiveness of electrical stimulation over motor point and TENS over acupuncture point for reducing spasticity and improving function in stroke patients. Methodology: This was an experimental study of 30 stroke patients having first ever unilateral stroke. The subjects were divided into three groups: group A (ES + Conventional PT), group B (TENS + Conventional PT) and group C (Control group with Conventional PT), comprising 10 in each group. All the groups received training 5 times a week for 4 weeks. Outcome measurements included Modified Ashworth Scale, Timed up and go test and Dynamic gait index. Results: At baseline, patients in each group were closely similar in all important prognostic variables. All groups, Group A, Group B and Group C showed statistically significant improvement (p < 0.05). But Electrical Stimulation with Conventional PT and TENS with Conventional PT showed significant improvement when compared with Control group. Whereas Electrical stimulation with conventional PT was more significant when compared with TENS with conventional PT. Conclusions: Electrical stimulation over motor point is more effective than TENS over acupuncture point in reduction of spasticity in stroke rehabilitation.
A skewer survey of the Galactic halo from deep CFHT and INT images

We study the density profile and shape of the Galactic halo using deep multicolour images from the MENeaCS and CCCP projects, over 33 fields selected to avoid overlap with the Galactic plane. Using multicolour selection and point spread function homogenization techniques we obtain catalogues of F stars (near-main sequence turnoff stars) out to Galactocentric distances up to 60 kpc. Grouping nearby lines of sight, we construct the stellar density profiles through the halo in eight different directions by means of photometric parallaxes. Smooth halo models are then fitted to these profiles. We find clear evidence for a steepening of the density profile power law index around R = 20 kpc, from -2.50 ± 0.04 to -4.85 ± 0.04, and for a flattening of the halo towards the poles with best-fit axis ratio 0.79 ± 0.02. Furthermore, we cannot rule out a mild triaxiality (w ≥ 0.88 ± 0.07). We recover the signatures of well-known substructure and streams that intersect our lines of sight. These results are consistent with those derived from wider but shallower surveys, and augur well for upcoming, wide-field surveys of comparable depth to our pencil beam surveys.
Particle size segregation in granular flow in silos

Segregation and layering of alumina in storage silos are investigated, with a view to predicting output quality versus time, given known variations in input quality on emplacement. A variety of experiments were conducted, existing relevant publications were reviewed, and the basis for an algorithm for predicting the effect of withdrawing from a central flowing region, in combination with variations in quality due to geometric, layering and segregation effects, is described in this report.
Comparative Study on Machine Learning Algorithms for Sentiment Classification

Sentiment Analysis is the study of people’s opinions and emotional feedbacks towards an entity which can be products, services, individuals or events. The opinions are most presumably be expressed as reviews or comments. With the advent of social networks, forums and blogs, these reviews emerged as an important factor for the customers’ decision for the purchase or choice of any item. Nowadays, a vast scalable computing environment provides us with very sophisticated way of carrying out various data-intensive natural language processing (NLP) and machine-learning tasks to analyze these reviews. One such task is text classification, a very effective way of predicting customers’ sentiment. This paper investigates the different ways of sentiment analysis from customers’ review using machine learning algorithms. For classifying text from overall sentiment, we considered two class, i.e. predicting whether a comment or review is positive or negative. In our study, we used two popular public datasets and six different machine learning algorithms – Naïve Bayes (Multinomial and Bernoulli), Logistic Regression, SGD (Stochastic Gradient Descent), Linear SVM (Support Vector Machine) and RF (Random Forest). Moreover, we applied parameter optimization on SVM and SGD classifiers on
A SEMIPARAMETRIC BAYESIAN APPROACH TO EPIDEMICS WITH LIKELIHOOD-IGNORABLE INCOMPLETE-DATA MECHANISMS

We consider incomplete observations of stochastic processes governing the spread of infectious diseases through finite populations by way of contact. We propose a network-based modeling framework with two important advantages. First, the framework, which is based on semiparametric models, can model both shortand longtailed degree distributions and can detect potential superspreaders, which represent an important public health concern. Second, the framework addresses the important issue of incomplete data and can deal with a wide range of missing data and sample data. We show under which conditions the incomplete-data generating process is likelihood-ignorable, i.e., can be ignored for the purpose of estimating the parameters of the population model. In addition, we discuss likelihood-ignorable sampling designs for collecting data on contacts with a view to reducing the posterior uncertainty about the population contact network and its generating mechanism. We demonstrate the added value of the proposed framework by simulations and an application to the partially observed outbreak of MERS in South Korea in 2015.
Multiscale Manufacturing of Three-Dimensional Polymer-Based Nanocomposite Structures

There is currently a worldwide effort for advances in micro and nanotechnologies due to their high potential for technological applications in fields such as microelectromechanical systems (MEMS), organic electronics and high-performance structures for aerospace. In these fields, nanoparticle-filled composites, i.e. nanocomposites, represent an interesting material option compared to conventional resins due to their enhanced properties and multi-functional potential. However, several significant scientific and technological challenges must be first overcome in order to fabricate nanocomposite-based structures and devices rapidly and cost-effectively. Various fabrication techniques of one or twodimensional (1D/2D) nanocomposite structures have been developed, but few techniques are available for three-dimensional (3D) nanocomposite structures. The capability to manufacture complex 3D structures will greatly expand the practical applications of nanocomposite materials and enable the development of novel devices such as a 3D nanocomposite micro-coil spring. This chapter will present an overview of the challenges in multiscale fabrication and the current manufacturing techniques available to create 3D structures of polymer-based nanocomposites.
Health Risks Assessment for Heavy Elements Suspended in Dusty Air along Murree Highway, Pakistan

2 Abstract: The anthropogenic and natural emissions of heavy metal pollutants in the atmospheric environment adversely affect the health of people exposed to the pollutants in different parts of the world. The concentration values of the heavy elements in suspended dust, trapped in Air conditioner's filters, along the Murree Highway were measured using Flame Atomic Absorption Spectrometer (FAAS). Health risk assessments for non-carcinogenic and carcinogenic effects, due to the heavy element contaminants, have been calculated for both children and adults. The risk assessments in case of children for non-carcinogenic effects showed that As has values greater than the safe level of Hazard Index (HI=1), the threshold value, however in case of adults the value of risk for As is also higher in comparison to the rest of the elements but lies within the safe range of Hazard Index (HI<1). The carcinogenic effects lie within the range of threshold values for all the investigated elements in case of children as well as adults.
Automatic Road Digitizing of Segmented Aerial Images for Urban Areas Based on K-means and Hough Transformation

In Geographical Information System (GIS), digitizing is an exhausting and time consuming process which is used for digital mapping and map updating. Popularity of mobile services and autonomous vehicles technology based on roads network increase the need for road automatic digitizing. Last years, deep-learning gave excellent results on roads segmentation from aerial and satellite imagery [1], that highlighted the automatic digitizing. In this paper statistical method is applied to extract roads from segmented images, and tested with images for three different scenes and gave an average accuracy of 86 percent.
Stereo Correspondence with Local Descriptors for Object Recognition

Stereo correspondence refers to the matches between two images with different viewpoints looking at the same object or scene. It is one of the most active research topics in computer vision as it plays a central role in 3D object recognition, object categorization, view synthesis, scene reconstruction, and many other applications. The image pair with different viewpoints is known as stereo images when the baseline and camera parameters are given. Given stereo images, the approaches for finding stereo correspondences are generally split into two categories: one based on sparse local features found matched between the images, and the other based on dense pixel-to-pixel matched regions found between the images. The former is proven effective for 3D object recognition and categorization, while the latter is better for view synthesis and scene reconstruction. This chapter focuses on the former because of the increasing interests in 3D object recognition in recent years, also because the feature-based methods have recently made a substantial progress by several state-of-the-art local (feature) descriptors. The study of object recognition using stereo vision often requires a training set which offers stereo images for developing the model for each object considered, and a test set which offers images with variations in viewpoint, scale, illumination, and occlusion conditions for evaluating the model. Many methods on local descriptors consider each image from stereo or multiple views a single instance without exploring much of the relationship between these instances, ending up with models of multiple independent instances. Using such a model for object recognition is like matching between a training image and a test image. It is, however, especially interested in this chapter that models are developed integrating the information across multiple training images. The central concern is how to extract local features from stereo or multiple images so that the information from different views can be integrated in the modeling phase, and applied in the recognition phase. This chapter is composed of the following contents: