Miracle-dz/UniFAR-FTUs huggingface dataset:
Using climatically based random forests to downscale coarse-grained potential natural vegetation maps in tropical Mexico: Using climatically based random forests

Questions: Can the accuracy of coarse resolution potential vegetation maps be improved through downscaling to finer resolution climatic grids? Can output from random forests produce new insight into the climatic characteristics that are associated with the structural characteristics of the vegetation? Location: Southern Mexico. Methods: A potential vegetation map (National Atlas of Mexico) at a 1:4 000 000 scale, was downscaled to a 1 km2 grid resolution using climatically based random forests models. The resulting map was then evaluated against 256 inventory plots sampled at the transition between different vegetation types in Southern Mexico. Results: Downscaling increased accuracy up to 0.40, as measured by the Kappa Index of Agreement. Multivariate analysis of the results allowed the association between Rzedowski's classification and climatic variation to be explored. This confirmed that many of the structural aspects of the vegetation that are used by the Rzedowski classification are closely associated with climate, but it also revealed weaknesses in the underlying basis of this classification system. Conclusions: Rzedowski's scheme for vegetation classification may require further modification in order to be an effective tool for research into vegetation–climate relationships.
Religion and the Attentional Blink: Depth of Faith Predicts Depth of the Blink

Religion is commonly defined as a set of rules, developed as part of a culture. Here we provide evidence that practice in following these rules systematically changes the way people allocate their attention, as indicated by the attentional blink (AB), a deficit in reporting the second of two target stimuli presented in close succession in a rapid sequence of distracters. We provide evidence that Dutch Calvinists and Atheists, brought up in the same country and culture and controlled for race, intelligence, mood, personality traits, and age, differ with respect to the amount of resources invested into processing AB targets. Calvinists showed a larger AB than Atheists, which is consistent with the notion that people's attentional processing style reflects biases rewarded by their religious beliefs.
D-Sieve: A Novel Data Processing Engine for Efficient Handling of Crises-Related Social Messages

Existing literature demonstrates the usefulness of system-mediated algorithms, such as supervised machine learning for detecting classes of messages in the social-data stream (e.g., topically relevant vs. irrelevant). The classification accuracies of these algorithms largely depend upon the size of labeled samples that are provided during the learning phase. Other factors such as class distribution, term distribution among the training set also play an important role on classifier's accuracy. However, due to several reasons (money / time constraints, limited number of skilled labelers etc.), a large sample of labeled messages is often not available immediately for learning an efficient classification model. Consequently, classifier trained on a poor model often mis-classifies data and hence, the applicability of such learning techniques (especially for the online setting) during ongoing crisis response remains limited. In this paper, we propose a post-classification processing step leveraging upon two additional content features-stable hashtag association and stable named entity association, to improve the classification accuracy for a classifier in realistic settings. We have tested our algorithms on two crisis datasets from Twitter (Hurricane Sandy 2012 and Queensland Floods 2013), and compared our results against the results produced by a "best-in-class'' baseline online classifier. By showing the consistent better quality results than the baseline algorithm i.e., by correctly classifying the misclassified data points from the prior step (false negative and false positive to true positive and true negative classes, respectively), we demonstrate the applicability of our approach in practice.
Creating Raster Omnimax Images from Multiple Perspective Views Using the Elliptical Weighted Average Filter

Creation of Omnimax animation by computer opens up fantastic new visual possibilities. Unfortunately, the fish-eye distortion of Omnimax film images complicates synthesis by computer, since most image-synthesis programs can create only perspective views. As an alternative to modifying existing image-synthesis programs to produce Omnimax projections directly, we present a method for creating them from multiple perspective views. Four perspective views of the environment are created, each a projection onto a face of a cube centered at the camera, and then a mapping program creates an Omnimax projection from them. To minimize aliasing during resampling, the mapping program uses the elliptical weighted average filter, a space-variant filter we developed for this application that computes a weighted average over an arbitrarily oriented elliptical area. This filter can also be used for texture mapping 3D surfaces.
Optimization and Learning in F ACTORIE

We present the optimization package in the FACTORIE library for machine learning, graphical models, and natural language processing in Scala. The library is designed with an eye towards the way practitioners naturally break down the structure of a learning problem, giving first-class status to, for example, training examples, update rules, and regularization. It supports flexible mixing and matching of parameter representation, update rules, loss functions, online-vs-batch training schedules, and serial-vs-parallel processing.
Response of distance measures to the equation of state

We show that the distance measures (such as the luminosity and angular diameter distances) are linear functionals of the equation of state function w(z) of the dark energy to a fair degree of accuracy in the regimes of interest. That is, the distance measures can be expressed as a sum of (i) a constant and (ii) an integral of a weighting function multiplied by the equation of state parameter w(z). The existence of such an accurate linear response approximation has several important implications. (1) Fitting a constant-w model to the data drawn from an evolving model has a simple interpretation as a weighted average of w(z). (2) Any polynomial (or other expansion coefficients) can also be expressed as weighted sums of the true w. (3) A replacement for the commonly used heuristic equation for the effective w, as determined by the cosmic microwave background, can be derived and the result is found to be quite close to the heuristic expression commonly used. (4) The reconstruction of w(z) by Huterer & Starkman can be expressed as a matrix inversion. In each case the limitations of the linear response approximation are explored and found to be surprisingly small.
Extending and Formalizing the Framework for Information Systems Architecture

John Zachman introduced a framework for information systems architecture (ISA) that has been widely adopted by systems analysts and database designers. It provides a taxonomy for relating the concepts that describe the real work to the concepts that describe an information system and its implementation. The ISA framework has a simple elegance that makes it easy to remember, yet it draws attention to fundamental distinctions that are often overlooked in systems design. This paper presents the framework and its recent extensions and shows how it can be formalized in the notation of conceptual graphs.
Role of the Dorsal Medial Habenula in the Regulation of Voluntary Activity, Motor Function, Hedonic State, and Primary Reinforcement

The habenular complex in the epithalamus consists of distinct regions with diverse neuronal populations. Past studies have suggested a role for the habenula in voluntary exercise motivation and reinforcement of intracranial self-stimulation but have not assigned these effects to specific habenula subnuclei. Here, we have developed a genetic model in which neurons of the dorsal medial habenula (dMHb) are developmentally eliminated, via tissue-specific deletion of the transcription factor Pou4f1 (Brn3a). Mice with dMHb lesions perform poorly in motivation-based locomotor behaviors, such as voluntary wheel running and the accelerating rotarod, but show only minor abnormalities in gait and balance and exhibit normal levels of basal locomotion. These mice also show deficits in sucrose preference, but not in the forced swim test, two measures of depression-related phenotypes in rodents. We have also used Cre recombinase-mediated expression of channelrhodopsin-2 and halorhodopsin to activate dMHb neurons or silence their output in freely moving mice, respectively. Optical activation of the dMHb in vivo supports intracranial self-stimulation, showing that dMHb activity is intrinsically reinforcing, whereas optical silencing of dMHb outputs is aversive. Together, our findings demonstrate that the dMHb is involved in exercise motivation and the regulation of hedonic state, and is part of an intrinsic reinforcement circuit.
Determination of the exact value of the regularization parameter in smoothness priors method with respect to the corresponding cut-off frequencies for designing filters

A filter is an electrical network or software that alters the amplitude and/or phase characteristics of a signal with respect to frequency. Recently, a new detrending method has been presented to remove the slow nonstationary trends from biomedical signals, which is equivalent to high-pass filtering that removes very low frequency components from the given signal. Although many recently published papers, related to the analysis of biomedical signals like the heart rate variability signal, have used the smoothness priors detrending method, there is no given exact relationship between the regularization parameter and the cut-off frequency of the corresponding high pass filter. In this study, we present this relationship by an empirical formula which would allow the researchers to calculate the parameter from the desired frequency response for not only a high pass filter but also other filter types.
Research Article Shear Wave Elastography May Add a New Dimension to Ultrasound Evaluation of Thyroid Nodules: Case Series with Comparative Evaluation

Although elastography can enhance the differential diagnosis of thyroid nodules, its diagnostic performance is not ideal at present. Further improvements in the technique and creation of robust diagnostic criteria are necessary. The purpose of this study was to compare the usefulness of strain elastography and a new generation of elasticity imaging called supersonic shear wave elastography (SSWE) in differential evaluation of thyroid nodules. Six thyroid nodules in 4 patients were studied. SSWE yielded 1 true-positive and 5 true-negative results. Strain elastography yielded 5 false-positive results and 1 false-negative result. A novel finding appreciated with SSWE, were punctate foci of increased stiffness corresponding to microcalcifications in 4 nodules, some not visible on B-mode ultrasound, as opposed to soft, colloid-inspissated areas visible on B-mode ultrasound in 2 nodules. This preliminary paper indicates that SSWE may outperform strain elastography in differentiation of thyroid nodules with regard to their stiffness. SSWE showed the possibility of differentiation of high echogenic foci into microcalcifications and inspissated colloid, adding a new dimension to thyroid elastography. Further multicenter large-scale studies of thyroid nodules evaluating different elastographic methods are warranted.
Rate-splitting and successive decoding for Gaussian interference channels

Joint decoding is employed in many coding schemes to achieve a larger rate region. However, decoding complexity escalates considerably when joint decoding is used. This paper studies the achievable sum-rate of the two-user Gaussian interference channel when joint decoding is replaced by successive decoding. When interference is weak, it is shown that, for a wide range of transmitters' powers, rate-splitting and joint decoding are not required. A single split scheme with successive decoding achieves the Han-Kobayashi sum-rate. When rate-splitting is required, a novel rate-splitting scheme is proposed that does not use joint decoding. The number of required splits and the amount of power allocated to each split are expressed in closed forms. It is proved that the difference between the sum-rate of this scheme and that of the Han-Kobayashi scheme is bounded, even when transmitters' powers approach infinity.
The V510D Suppressor Mutation Stabilizes ΔF508-CFTR at the Cell Surface†

Deletion of Phe508 (ΔF508) in the first nucleotide-binding domain (NBD1) of CFTR causes cystic fibrosis. The mutation severely reduces the stability and folding of the protein by disrupting interactions between NBD1 and the second transmembrane domain (TMD2). We found that replacement of Val510 with acidic residues (but not neutral or positive residues) promoted maturation of ΔF508-CFTR with V510D more efficiently than V510E. Promotion of ΔF508-CFTR maturation did not require NBD2 as introduction of V510D into a ΔNBD2/ΔF508-CFTR mutant restored maturation to levels similar to that of full-length protein. The V510D mutation increased the half-life of mature ΔF508-CFTR at the cell surface by about 5-fold to resemble the half-life of wild-type CFTR. It was also observed that introduction of the V510R/R1070D mutations into ΔF508-CFTR also promoted maturation whereas the V510D/R1070A mutations did not. We propose that the V510D mutation in NBD1 promotes maturation and stabilizes ΔF508-CFTR at the cell surface through formation of a salt bridge with Arg1070 in TMD2.
Adjectives and boundedness

Abstract This article examines the significance of the schematic domain of boundedness in adjectives. It is proposed that boundedness in adjectives is a fundamental characteristic associated with gradability. Cross-categorial correspondences are made to nouns and verbs, where boundedness is a feature of countability and aktionsart respectively. Two basic types of gradable adjectives are distinguished: those which are associated with a boundary and those which are not. It is also shown that it is possible to change the configuration of adjectives in terms of boundedness through contextual modulation. Finally, it is demonstrated that the configuration of adjectives in terms of boundaries may dominate their interpretation at the expense of the content proper, and the adjectives become more like function words than content words.
An iterative convex approximation approach for transmit beamforming in multi-group multicasting

We propose a novel algorithm for transmit beamforming to multiple cochannel multicast groups. The problem of minimizing the total power transmitted by the antenna array subject to quality-of-service (QoS) constraints at the receivers is considered. We show that this problem, which is known to be NP-hard, can be approximated by a second-order cone programming (SOCP) problem. We propose an iterative scheme in which the SOCP approximation is successively improved in each iteration. Earlier state-of-the-art techniques for this problem are based on semidefinite relaxation (SDR) and require randomization and power scaling which is avoided in our approach. Computer simulations show that the proposed technique exhibits superior performance in terms of total transmitted power and feasibility at a reduced computational complexity as compared to the SDR method.
Global Numerical Constraints on Trees

We introduce a logical foundation to reason on tree structures with constraints on the number of node occurrences. Related formalisms are limited to express occurrence constraints on particular tree regions, as for instance the children of a given node. By contrast, the logic introduced in the present work can concisely express numerical bounds on any region, descendants or ancestors for instance. We prove that the logic is decidable in single exponential time even if the numerical constraints are in binary form. We also illustrate the usage of the logic in the description of numerical constraints on multi-directional path queries on XML documents. Furthermore, numerical restrictions on regular languages (XML schemas) can also be concisely described by the logic. This implies a characterization of decidable counting extensions of XPath queries and XML schemas. Moreover, as the logic is closed under negation, it can thus be used as an optimal reasoning framework for testing emptiness, containment and equivalence.
Learning sparse kernel machines with biometric similarity functions for identity recognition

We investigate the application of similarity-based classification to biometric recognition, interpreting similarity functions used in biometric systems (i.e., matching algorithms) as kernel functions. This leads us to formulate biometric recognition as a distinct two-class classification problem for each client, which can be solved even when no representation of biometric samples in a feature space of fixed dimensionality is available. We discuss the relationship of our approach with cohort-based methods, and show that using support vector machines exhibits several advantages, in terms of the automatic selection of the cohort size and elements, and of the possible update of each user model. A biometric verification setting is considered for the formulation of the approach, but experimental results with face and fingerprint data sets are reported for both verification and identification settings.
High nutrient availability reduces the diversity and stability of the equine caecal microbiota

Background It is well known that nutrient availability can alter the gut microbiota composition, while the effect on diversity and temporal stability remains largely unknown. Methods Here we address the equine caecal microbiota temporal stability, diversity, and functionality in response to diets with different levels of nutrient availability. Hay (low and slower nutrient availability) versus a mixture of hay and whole oats (high and more rapid nutrient availability) were used as experimental diets. Results We found major effects on the microbiota despite that the caecal pH was far from sub-clinical acidosis. We found that the low nutrient availability diet was associated with a higher level of both diversity and temporal stability of the caecal microbiota than the high nutrient availability diet. These observations concur with general ecological theories, suggesting a stabilising effect of biological diversity and that high nutrient availability has a destabilising effect through reduced diversity. Conclusion Nutrient availability does not only change the composition but also the ecology of the caecal microbiota.
Spatial partitioning of geometry images using locality masks

The advantages of using geometry images as surface representations largely depend on their regular sampling distribution and strictly ordered 2D storage arrangement. Traditional 3D spatial partitioning techniques often compromise these attractive properties when building hierarchical data structures. We present a modification to traditional partitioning methods using locality masks, which maintain the original sampling and storage structure of geometry images. Applications using spatial hierarchies can then take advantage of the sequential memory access and simplified sampling neighbourhoods associated with geometry images without an intermediate sorting phase. The method uses traditional principles for creation, storage and processing of internal hierarchy nodes, but treats the referencing of primitives at leaf nodes differently. Locality masks are presented with future geometry image processing techniques in mind and handle both single and multi-chart geometry images.
Group Avoiding Errors In Progressive Tetrahedralizations

This paper describes some fundamental issues for robust implementations of progressively refined tetrahedralizations generated through sequences of edge collapses. We address the definition of appropriate cost functions and explain on various tests which are necessary to preserve the consistency of the mesh when collapsing edges. Although being considered a special case of progressive simplicial complexes [4], the results of our method are of high practical importance and can be used in many different applications, such as finite element meshing, scattered data interpolation or rendering of irregular volume data. CR Categories: I.3. 5 [Computer Graphics]: Computational Geometry and Object Modeling – surfaces and object representations.
CHARACTERIZATION OF STOCHASTIC PROPERTIES OF EMBEDDED MESSAGE AND THE LSB PATTERN IN COLOUR AND GRAYSCALE IMAGES

LSB steganography is one of the popular ways of message embedding in different multimedia cover objects. A number of commercial steganography software tools use LSB insertion as a method of message packing. In the present work the detailed study has been made regarding the stochastic properties of the embedded message and LSB pattern in colour and gray scale images. The influence of the initial noise already existing within the LSB pattern of the cover image on the embedded bit stream has been studied experimentally. A higher order statistic based method has been proposed to eliminate the initial noise level to estimate the extracted bit stream length robustly.
BER Analysis to Increase Capacity of A Cellular System Using SDMA Over a Multipath Rayleigh Fading Channel

In this paper, we have presented how the capacity of cellular system can be enhanced by using Space Division Multiple Access (SDMA) with directive antenna in mobile communication systems. One of the biggest draw back of wireless environment is the limited bandwidth. However, the users sharing this limited bandwidth have been increased considerably. SDMA is a technology by which the capacity of the existing mobile communication system can economically be increased. Adaptive Antenna provides a spot beam for each users in the cells as it moves. This paper analysis the comparison of average Bit Error Rate (BER) of SDMA and Code Division Multiple Access (CDMA) technique and the way in which SDMA can be introduced to increase the capacity of a cellular system in Frequency Selective Multipath Rayleigh Fading Channel. The BER is found for a standard omni directional base station antenna, and the another set of curve is found for flat top beam having a directivity of 8 dB. We see that SDMA offers improved capacity in wireless communication system.
Comparison of pregnancy predictive models applied to women who received IVF/ICSI in Valencia (Spain) using ROC curves

One of the main objectives of Assisted Reproductive Tech- nology (ART) is the reduction of the number of multiple pregnancies to obtain the highest number of full term pregnancies. Therefore, ART has to select the best quality embryos for transfer. This paper proposes several generalized linear models for the prediction of the implantation potential of embryos taking into account the morphological variables of the embryos and clinical and cycle variables of the woman. Some morpho- logical variables are considered factors for the evaluation of dierences between the eect of each variable value on the embryo implantation po- tential. With this aim in mind, we considered only two embryo transfers for women under 35 who received IVF-ICSI treatment at the \La Fe" Hospital in Valencia from 2001 to 2006. Model validation was carried out using ROC curves. In short, we propose statistical tools which provide a clear framework for decision support for embryologists.