Miracle-dz/UniFAR-FTUs huggingface dataset:
Am selectat un numãr de 53 de pacienåi cu simptome digestive , la care endoscopiile superioare æi inferoare nu au identificat leziuni

Videocapsule endoscopy (VCE) can identify lesions in the small bowel which would otherwise be hard to detect. We have selected 53 patients with digestive symptoms in which upper and lower endoscopy had provided no findings. Patients were classified into three groups, based on their main indication for VCE exploration: group one obscure gastrointestinal bleeding (OGIB); group two unspecific abdominal symptoms; group 3 monitoring of a prior known pathology. We found that VCE has high predictive values, sensibility and specificity in the diagnosis of OGIB. VCE was also useful in the detection and extent evaluation of lesions in Crohn’s and celiac disease. VCE is also able to detect tumors of the small bowel with sufficient accuracy, and can be used to monitor patients with hereditary pre-malignant diseases such as FAP. There were few light adverse effects and no major complications. We conclude that VCE is a safe and effective procedure for the detection of small bowel lesions.
Semantic Support for Model Composition

The essence of systems-level design is the need to integrate models representing different system facets to understand the impacts of local decisions on global requirements. Unfortunately, these models may be defined in disparate semantic systems making composition and integrated analysis challenging. As a part of the Rosetta systems-level design effort, a collection of mechanisms based on coalgebraic semantics has been defined to transform and compose models. Functors define mechanisms for moving models between specification domains; coproducts define mechanisms for composing multiple specifications; and translator functions define mechanisms for structurally compose specifications. Together these techniques provide specification composition support for integrating formal, systems-level analysis activities.
CAPE in Tropical Cyclones

AbstractConvective available potential energy (CAPE) and the vertical distribution of buoyancy were calculated for more than 2000 dropsonde soundings collected by the NOAA Gulfstream-IV aircraft. Calculations were done with and without the effects of condensate loading, entrainment, and the latent heat of fusion. CAPE showed larger values downshear than upshear within 400 km of the center, consistent with the observed variation of convective intensity. The larger downshear CAPE arose from (i) higher surface specific humidity, (ii) lower midtropospheric temperature, and, for entraining CAPE, (iii) larger free-tropospheric relative humidity.Reversible CAPE had only one-half the magnitude of pseudoadiabatic CAPE. As shown previously, reversible CAPE with fusion closely resembled pseudoadiabatic CAPE without fusion. Entrainment had the most dramatic impact. Entraining CAPE was consistent with the observed radial distribution of convective intensity, displaying the largest values downshear at inner radii. With.
Evaluation of Wetland Mitigation in the Greater Yellowstone Ecosystem: Wildlife Population and Community Responses

The 2006‒2013 reconstruction of US Highway 26/287 over Togwotee Pass, Wyoming, impacted or caused the loss of natural wetlands. To comply with U.S. Army Corps of Engineers permit conditions, the Wyoming Department of Transportation (WYDOT) recently completed construction or restoration of 38 mitigation wetlands along the Highway 26/287 corridor and at the aggregate pit site at the U.S. Forest Service Blackrock Ranger Station. This study provides WYDOT information on differences among wetlands created to mitigate for wetland loss (n=10), wetlands impacted but not destroyed (n=7), and natural wetlands (n=16) relative to various aspects of wildlife that use these habitats. We compare characteristics of amphibians, a pathogenic fungus, invertebrates, and birds. Created wetlands in this study area were significantly shallower than natural and impacted wetlands and had shorter hydroperiods; but impacted wetlands were similar in physical habitat characteristics to natural wetlands. Boreal toads (Anaxyrus boreas) rapidly colonized newly created wetlands and annual survival and recruitment rates were similar in created and natural wetlands. Boreal chorus frogs (Pseudacris maculata) were less than half as likely to occupy created wetlands as natural and impacted wetlands but population sizes were high in at least one created wetland. Barred tiger salamanders (Ambystoma mavortium) occurred in natural and impacted wetlands at similar levels, but we observed reproduction by Columbia spotted frogs (Rana luteiventris) at only one created wetland-they were common in natural and impacted wetlands. There was no difference in the prevalence of the pathogenic fungus between created & natural wetlands. Species richness of invertebrates was lower in created wetlands than in natural and impacted wetlands and the community composition of invertebrates differed among wetland types. Communities in created wetlands were more likely to be dominated by flying species compared to communities in natural wetlands that had more passive dispersers such as snails and clams. We recorded bird calls in two created & two natural wetlands; species richness was similar but some riparian specialists (e.g., willow flycatcher, Wilson’s warbler) were not detected at either created wetland. Our results suggest that wetland creation can be an important tool for conserving wetland-dependent wildlife. Understanding how animals use created wetlands sites is a critical component to understanding the efficacy of mitigation efforts and determining alternative (e.g., earlier) “endpoints”. This report highlights characteristics in created sites that are advantageous to species that are perhaps “non-focal”, but important members of the natural community. The data presented here provide support for earlier endpoints for determining success in created wetlands and a baseline for continued monitoring of these or other created sites.
Foveation time measure in Congenital Nystagmus through second order approximation of the slow phases

Congenital Nystagmus (CN) is an ocular-motor disorder characterised by involuntary, conjugated ocular oscillations, and its pathogenesis is still unknown. The pathology is defined as “congenital” from the onset time of its arise which could be at birth or in the first months of life. Visual acuity in CN subjects is often diminished due to nystagmus continuous oscillations, mainly on the horizontal plane, which disturb image fixation on the retina. However, during short periods in which eye velocity slows down while the target image is placed onto the fovea (called foveation intervals) the image of a given target can still be stable, allowing a subject to reach a higher visual acuity. In CN subjects, visual acuity is usually assessed both using typical measurement techniques (e.g. Landolt C test) and with eye movement recording in different gaze positions. The offline study of eye movement recordings allows physicians to analyse nystagmus main features such as waveform shape, amplitude and frequency and to compute estimated visual acuity predictors. This analytical functions estimates the best corrected visual acuity using foveation time and foveation position variability, hence a reliable estimation of this two parameters is a fundamental factor in assessing visual acuity. This work aims to enhance the foveation time estimation in CN eye movement recording, computing a second order approximation of the slow phase components of nystag-mus oscillations. About 19 infrared-oculographic eye-movement recordings from 10 CN subjects were acquired and the visual acuity assessed with an acuity predictor was compared to the one measured in primary position. Results suggest that visual acuity measurements based on foveation time estimation obtained from interpolated data are closer to value obtained during Landolt C tests.
Calcium-mediated changes in gap junction structure: evidence from the low angle X-ray pattern

Rat liver gap junctions were isolated in Ca2+-free media and analyzed in controlled environments by x-ray diffraction of partially oriented pellets. Different treatments of the same preparations were compared. The ordered hexagonal lattices gave rise to detail that was sensitive to low Ca2+ concentrations (0.05 mM), but not to Mg2+ (up to 0.16 mM) or pH (between 6.0 and 8.0). The major Ca2+-mediated responses were reductions in the intensity of the (1, 0) peak and in the off- equatorial contributions to the (2, 1) peak, and changes of scale equivalent to a decrease (approximately 2%) in lattice dimension, but an increase (approximately 4%) in the dimension perpendicular to the lattice. A simple structural interpretation of these findings is that Ca2+ induces the subunits of the channel-forming assembly, the connexon, to align more nearly parallel to the channel, thereby causing the connexon to become slightly longer and more radially compact. The rearrangement is of the same nature as one found under less physiological circumstances by electron microscopy (Unwin, P. N. T., and G. Zampighi, 1980, Nature (Lond.). , 283:545-549), and may be part of a coordinated mechanism by which the channel closes.
0 61 11 44 v 2 6 S ep 2 00 7 N-body Gravity and the Schroedinger Equation

We consider the problem of the motion of N bodies in a self-gravitating system in two spacetime dimensions. We point out that this system can be mapped onto the quantum-mechanical problem of an N-body generalization of the problem of the H+2 molecular ion in one dimension. The canonical gravitational N-body formalism can be extended to include electromagnetic charges. We derive a general algorithm for solving this problem, and show how it reduces to known results for the 2-body and 3-body systems. email: pfarruguia@sciborg.uwaterloo. ca email: rbmann@sciborg.uwaterloo. ca email: scott@pc.rwth-aachen.de
The progress of stochastic resonance in the application of spectrum sensing

Spectrum sensing is a key technology of cognitive radio network. Firstly, the paper introduced the latest research progress of the application of the stochastic resonance in cognitive radio spectrum sensing, including stochastic resonance in the local field of sensing (such as energy detection, covariance matrix spectrum sensing, cyclostationary feature detection) and the application of collaborative sensing, and then it pointed out some problems of the stochastic resonance to be solved in the cognitive radio spectrum sensing. Last but not the least, the next research directions were summarized.
Application of Admission Control and Traffic Shaping for providing TCP Throughput Guarantees

The paper presents an approach for providing requested throughput guarantees, say Rreq, for greedy TCP (Transmission Control Protocol) connections (e.g. ftp). For this purpose, we recommend at the network entry point to shape, with rate R, traffic emitted by each of TCP connections as well as to perform CAC (Connection Admission Control) function to limit number of running connections. By using shaper the TCP traffic submitted to the network tends to the form of constant bit rate (CBR). This feature permits us to apply a well known CAC algorithm relevant for CBR traffic. In the case of CAC limit we observe excellent equal bandwidth sharing between competing TCP connections when R=Rreq. For the case when the system is lightly loaded we discuss some strategies allowing for TCP connections to increase their throughput by setting R>Rreq.
The centrosome–Golgi apparatus nexus

A shared feature among all microtubule (MT)-dependent processes is the requirement for MTs to be organized in arrays of defined geometry. At a fundamental level, this is achieved by precisely controlling the timing and localization of the nucleation events that give rise to new MTs. To this end, MT nucleation is restricted to specific subcellular sites called MT-organizing centres. The primary MT-organizing centre in proliferating animal cells is the centrosome. However, the discovery of MT nucleation capacity of the Golgi apparatus (GA) has substantially changed our understanding of MT network organization in interphase cells. Interestingly, MT nucleation at the Golgi apparently relies on multiprotein complexes, similar to those present at the centrosome, that assemble at the cis-face of the organelle. In this process, AKAP450 plays a central role, acting as a scaffold to recruit other centrosomal proteins important for MT generation. MT arrays derived from either the centrosome or the GA differ in their geometry, probably reflecting their different, yet complementary, functions. Here, I review our current understanding of the molecular mechanisms involved in MT nucleation at the GA and how Golgi- and centrosome-based MT arrays work in concert to ensure the formation of a pericentrosomal polarized continuous Golgi ribbon structure, a critical feature for cell polarity in mammalian cells. In addition, I comment on the important role of the Golgi-nucleated MTs in organizing specialized MT arrays that serve specific functions in terminally differentiated cells.
Fuzzy Entropy-based Object Segmentation with an Inertia-Adaptive PSO

Particle swarm optimization (PSO) has recently emerged as a simple yet very efficient algorithm for global optimization over continuous spaces. This article describes the application of an improved variant of PSO to the segmentation of objects from complicated real life images. The segmentation task amounts to finding a robust and optimal threshold that separates an object from a background frame. It has been formulated as an optimization problem using the maximum fuzzy entropy principle. Experimentation with several real life images and comparison with the state of the art methods for automatic object segmentation reflect the superiority of the proposed approach in terms of accuracy of the final results and fast computational speed.
Weed classification using Decision Tree

In this paper, the potential of Decision Tree specifically the CART algorithm for classification of weed into two categories namely broad and narrow is employed. Six feature vectors extracted via the Gabor wavelet along with the FFT technique serves as the CART inputs. Based on accuracy rate achieved and selection of optimal feature vectors, the CART algorithm is apt as classifier for weed recognition.
Contour Detection Using Cost-Sensitive Convolutional Neural Networks

We address the problem of contour detection via per-pixel classifications of edge point. To facilitate the process, the proposed approach leverages with DenseNet, an efficient implementation of multiscale convolutional neural networks (CNNs), to extract an informative feature vector for each pixel and uses an SVM classifier to accomplish contour detection. The main challenge lies in adapting a pre-trained per-image CNN model for yielding per-pixel image features. We propose to base on the DenseNet architecture to achieve pixelwise fine-tuning and then consider a cost-sensitive strategy to further improve the learning with a small dataset of edge and non-edge image patches. In the experiment of contour detection, we look into the effectiveness of combining per-pixel features from different CNN layers and obtain comparable performances to the state-of-the-art on BSDS500.
The Indris Have Got Rhythm! Timing and Pitch Variation of a Primate Song Examined between Sexes and Age Classes

A crucial, common feature of speech and music is that they show non-random structures over time. It is an open question which of the other species share rhythmic abilities with humans, but in most cases the lack of knowledge about their behavioral displays prevents further studies. Indris are the only lemurs who sing. They produce loud howling cries that can be heard at several kilometers, in which all members of a group usually sing. We tested whether overlapping and turn-taking during the songs followed a precise pattern by analysing the temporal structure of the individuals' contribution to the song. We found that both dominants (males and females) and non-dominants influenced the onset timing one another. We have found that the dominant male and the dominant female in a group overlapped each other more frequently than they did with the non-dominants. We then focused on the temporal and frequency structure of particular phrases occurring during the song. Our results show that males and females have dimorphic inter-onset intervals during the phrases. Moreover, median frequencies of the unit emitted in the phrases also differ between the sexes, with males showing higher frequencies when compared to females. We have not found an effect of age on the temporal and spectral structure of the phrases. These results indicate that singing in indris has a high behavioral flexibility and varies according to social and individual factors. The flexible spectral structure of the phrases given during the song may underlie perceptual abilities that are relatively unknown in other non-human primates, such as the ability to recognize particular pitch patterns.
Kernel Logistic Regression Algorithm for Large-Scale Data Classification

Kernel Logistic Regression (KLR) is a powerful classification technique that has been applied successfully in many classification problems. However, it is often not found in large-scale data classification problems and this is mainly because it is computationally expensive. In this paper, we present a new KLR algorithm based on Truncated Regularized Iteratively Reweighted Least Squares(TR-IRLS) algorithm to obtain sparse large-scale data classification in short evolution time. This new algorithm is called Nystrom Truncated Kernel Logistic Regression (NTR-KLR). The performance achieved using NTR-KLR algorithm is comparable to that of Support Vector Machines (SVMs) methods. The advantage is NTR-KLR can yield probabilistic outputs and its extension to the multi class case is well defined. In addition, its computational complexity is lower than that of SVMs methods and it is easy to implement.
Self-Cancellation Method of OFDM ICI

Orthogonal frequency division multiplexing (OFDM) communication systems, the frequency offsets in mobile radio channels distort the orthogonality between subcarriers resulting in intercarrier interference (ICI). This paper studies an efficient ICI cancellation method termed ICI self-cancellation scheme. The scheme works in two very simple steps. At the transmitter side, one data symbol is modulated onto a group of adjacent subcarriers with a group of weighting coefficients. The weighting coefficients are designed so that the ICI caused by the channel frequency errors can be minimized. At the receiver side, by linearly combining the received signals on these subcarriers with proposed coefficients, the residual ICI contained in the received signals can then be further reduced. The carrier-to-interference power ratio (CIR) can be increased by 15 and 30 dB when the group size is two or three, respectively, for a channel with a constant frequency offset. Although the redundant modulation causes a reduction in bandwidth efficiency, it can be compensated, for example, by using larger signal alphabet sizes. Simulations show that OFDM systems using the proposed ICI self-cancellation scheme perform much better than standard systems while having the same bandwidth efficiency in multipath mobile radio channels with large Doppler frequencies.
Simulation of main plasma parameters of a cylindrical asymmetric capacitively coupled plasma micro-thruster using computational fluid dynamics

Computational fluid dynamics (CFD) simulations of a radio-frequency (13.56 MHz) electro-thermal capacitively coupled plasma (CCP) micro-thruster have been performed using the commercial CFD-ACE+ package. Standard operating conditions of a 10 W, 1.5 Torr argon discharge were used to compare with previously obtained experimental results for validation. Results show that the driving force behind plasma production within the thruster is ion-induced secondary electrons ejected from the surface of the discharge tube, accelerated through the sheath to electron temperatures up to 33.5 eV. The secondary electron coefficient was varied to determine the effect on the discharge, with results showing that full breakdown of the discharge did not occur for coefficients coefficients less than or equal to 0.01.
Employing correlation clustering for the identification of piecewise affine models

To analyze and control a system, a model is build which describes the relationship between the inputs and the corresponding outputs. While simple systems can be described by a single linear model, more complex systems can be approximated through an assembly of linear submodels. Such piecewise affine (PWA) models consists of several convex regions and linear submodels describing the input output relationship for each such region. The more regions are considered in the PWA model, the more accurate it describes the system. Still, in real world applications, simple models are necessary for performance reasons, hence a trade-off has to be made between the model complexity and its accuracy. In this paper we discuss the employment of correlation clustering algorithms for a robust identification of PWA models with reduced complexity.
Fuzzy pulmonary vessel segmentation in contrast enhanced CT data

Pulmonary vascular tree segmentation has numerous applications in medical imaging and computer-aided diagnosis (CAD), including detection and visualization of pulmonary emboli (PE), improved lung nodule detection, and quantitative vessel analysis. We present a novel approach to pulmonary vessel segmentation based on a fuzzy segmentation concept, combining the strengths of both threshold and seed point based methods. The lungs of the original image are first segmented and a threshold-based approach identifies core vessel components with a high specificity. These components are then used to automatically identify reliable seed points for a fuzzy seed point based segmentation method, namely fuzzy connectedness. The output of the method consists of the probability of each voxel belonging to the vascular tree. Hence, our method provides the possibility to adjust the sensitivity/specificity of the segmentation result a posteriori according to application-specific requirements, through definition of a minimum vessel-probability required to classify a voxel as belonging to the vascular tree. The method has been evaluated on contrast-enhanced thoracic CT scans from clinical PE cases and demonstrates overall promising results. For quantitative validation we compare the segmentation results to randomly selected, semi-automatically segmented sub-volumes and present the resulting receiver operating characteristic (ROC) curves. Although we focus on contrast enhanced chest CT data, the method can be generalized to other regions of the body as well as to different imaging modalities.
On the occurrence of oscillatory modulations in the power law behavior of dynamic and kinetic processes in fractals

The dynamic and kinetic behavior of processes occurring in fractals with spatial discrete scale invariance (DSI) is considered. Spatial DSI implies the existence of a fundamental scaling ratio (b1). We address time-dependent physical processes which, as a consequence of the time evolution, develop a characteristic length of the form ξ∝t1/z, where z is the dynamic exponent. So, we conjecture that the interplay between the physical process and the symmetry properties of the fractal leads to the occurrence of time DSI evidenced by soft log-periodic modulations of physical observables, with a fundamental time scaling ratio given by τ=b1z. The conjecture is tested numerically for single random walks, annihilating random walks, and representative systems of broad universality classes in the fields of irreversible and equilibrium critical phenomena.