Miracle-dz/UniFAR-FTUs huggingface dataset:
N-acetylcysteine protects against renal injury following bilateral ureteral obstruction

Background. Obstructive nephropathy decreases renal blood flow (RBF) and glomerular filtration rate (GFR), causing tubular abnormalities, such as urinary concentrating defect, as well as increasing oxidative stress. This study aimed to evaluate the effects of N-acetylcysteine (NAC) on renal function, as well as on the protein expression of aquaporin 2 (AQP2) and endothelial nitric oxide synthase (eNOS), after the relief of bilateral ureteral obstruction (BUO). Methods. Adult male Wistar rats were divided into four groups: sham (sham operated); sham operated + 440 mg/kg body weight (BW) of NAC daily in drinking water, started 2 days before and maintained until 48 h after the surgery; BUO (24-h BUO only); BUO + NAC-pre (24-h BUO plus 440 mg/kg BW of NAC daily in drinking water started 2 days before BUO); and BUO + NAC-post (24-h BUO plus 440 mg/kg BW of NAC daily in drinking water started on the day of BUO relief). Experiments were conducted 48 h after BUO relief. Results. Serum levels of thiobarbituric reactive substances, which are markers of lipid peroxidation, were significantly lower in NAC-treated rats than in the BUO group rats. The administration of NAC provided significant protection against post-BUO GFR drops and reductions in RBF. Renal cortices and BUO rats presented decreased eNOS protein expression of eNOS in the renal cortex of BUO group rats, whereas it was partially recovered in BUO + NAC-pre group rats. Urine osmolality was significantly lower in BUO rats than in sham group rats or NAC-treated rats, the last also presenting less interstitial fibrosis. Post-BUO downregulation of AQP2 protein expression was averted in the BUO + NAC-pre group rats. Conclusions. This study demonstrates that NAC administration ameliorates the renal function impairment observed 48 h after the relief of 24-h BUO. Oxidative stress is important for the suppression of GFR, RBF, tissue AQP2 and eNOS in the polyuric phase after the release of BUO.
Mass spectrometry imaging: linking molecule profiles to tissue spatial distribution

Advances in Bioanalytical Mass Spectrometry: 5th Symposium of the Göttingen Proteomics Forum Mass Spectrometry with Spatial Resolution: MALDI-Imaging and Laser Capture Microscopy Göttingen, Germany, 22 November 2012 MALDI mass spectrometry imaging (MSI) combines the speed and molecular specificity of MALDI-MS detection with information on spatial organization. In the last years, MSI found large application in proteomics research for determining the spatial distribution of compounds in biological tissues and started to draw increasing interest in clinical research. To shed light on the new developments in the field of MSI, the Göttingen Proteomics Forum organized a symposium that was held in Göttingen as part of the series of regular symposia organized by the members of the Göttingen Proteomics Forum. The symposium was on 22 November 2012, with more than 80 delegates that attended the event entitled ‘Mass spectrometry with spatial resolution: MALDI-imaging and laser capture microscopy’. The one-day agenda consisted of nine oral presentations from renowned experts in the field with subsequent discussion sessions. As usual, the meeting was fruitful and offered a good platform for discussion between the delegates and proteomics specialists.
The feasibility of information dissemination in vehicular ad-hoc networks

In this paper we consider information dissemination in vehicular ad-hoc networks (VANETs) in city scenarios. Information dissemination is an important building block of many proposed VANET applications. These applications need a certain dissemination performance to work satisfactorily. This is critical during the rollout of VANETs, when only few cars participate. After analytical considerations, we focus on simulations using a detailed model of a whole city. We assess the dissemination performance depending on the amount of equipped vehicles on the road. For few equipped vehicles, we show that dissemination speed and coverage will not be sufficient. Therefore, we propose to use specialized, but simple and cheap infrastructure, stationary supporting units (SSUs). If a small number of SSUs is installed in a city and connected via some backbone network, the dissemination performance improves dramatically, especially during the VANET rollout phase. Thus, SSUs allow for a faster and earlier rollout of working, dissemination-based VANET applications
ANALYSIS OF OSCILLATORY CONTROL SYSTEMS

Abstract This paper presents analysis results for control systems subject to oscillatory inputs, i.e., inputs of large amplitude and high frequency. The key results are a series expansion characterizing the averaged system and various Lie-algebraic conditions that guarantee the series can be summed. Some illustrative example systems provide insight into the results; control design applications are discussed in a companion paper.
Black hole accretion discs and jets at super-Eddington luminosity

Super-Eddington accretion discs with 3 ˙ ME and 15 ˙ ME around black holes with mass 10 M� are examined by two-dimensional radiation hydrodynamical calculations extending from the inner disc edge to 5 × 10 4 r g and lasting up to ∼10 6 rg/c. The dominant radiation pressure force in the inner region of the disc accelerates the gas vertically to the disc plane, and jets with 0.2‐0.4c are formed along the rotational axis. In the case of the lower accretion rate, the initially anisotropic high-velocity jet expands outward and becomes gradually isotropic flow in the distant region. The mass-outflow rate from the outer boundary is as large as ∼10 19 ‐10 23 gs −1 ,b ut it is variable and intermittent with time; that is, the outflow switches occasionally to inflow in the distant region. The luminosity also varies as ∼10 40 ‐10 42 erg s −1 on a long time-scale. On the other hand, the jet in the case of the higher accretion rate maintains its initial anisotropic shape even after it goes far away. The mass-outflow rate and the luminosity attain steady values of 3 × 10 19 gs −1 and 1.3 × 10 40 erg s −1 , respectively. In accordance with the local analysis of the slim accretion disc model, the disc is thermally unstable in the case of 3 ˙ ME but stable in the case of 15 ˙ ME. The super-Eddington model with 15 ˙
Auto-pooling: Learning to Improve Invariance of Image Features from Image Sequences

Learning invariant representations from images is one of the hardest challenges facing computer vision. Spatial pooling is widely used to create invariance to spatial shifting, but it is restricted to convolutional models. In this paper, we propose a novel pooling method that can learn soft clustering of features from image sequences. It is trained to improve the temporal coherence of features, while keeping the information loss at minimum. Our method does not use spatial information, so it can be used with non-convolutional models too. Experiments on images extracted from natural videos showed that our method can cluster similar features together. When trained by convolutional features, auto-pooling outperformed traditional spatial pooling on an image classification task, even though it does not use the spatial topology of features.
Muon simulations based on a realistic CBM muon detector system

The actual design of the muon detector system consists of 6 hadron absorber layers (iron plates of thickness 20, 20, 20, 30, 35, 100 cm) and 15-18 gaseous tracking chambers located in triplets behind each iron slab. The geometry of the muon system is presented in figure 1: the side view of the full system (top), the side wiew of one gap with detector layers (bottom left), and the side view of one detector layer with detector moduls (bottom right). The modular design of the muon system was described in detail in [2].
Retrieval from memory and cue complexity both trigger exemplar-based processes in judgment*

ABSTRACT Judgments and decisions can be achieved by a rule-based integration of cues or by retrieving similar exemplars from memory. In judgments based on currently available object descriptions (on-line judgments), people tend to rely on rules unless the cue-criterion relations are difficult to extract. In memory-based decisions, more evidence for exemplarbased reasoning has been found, but hitherto restricted to conditions with unknown cue polarity. These conclusions are threatened by methodological confounds concerning materials, training regime, and type of judgment task. In a factorial experiment, memory-based vs. on-line judgments as well as obvious vs. unknown cue polarity conditions were pitted against each other. Participants judged disease severity based on symptoms. Using the measurement model RulEx-J, we confirmed that both memory retrieval and unknown cue polarity have additive effects on the use of exemplar-based processes. This corroborates the idea that exemplar-based strategies are used as a backup if cue abstraction is unfeasible.
Quantitative comparison of DNA looping in vitro and in vivo: chromatin increases effective DNA flexibility at short distances

The probability that two sites on a linear DNA molecule will contact each other by looping depends on DNA flexibility. Although the flexibility of naked DNA in vitro is well characterized, looping in chromatin is poorly understood. By extending existing theory, we present a single equation that describes DNA looping over all distances. We also show that DNA looping in vitro can be measured accurately by FLP recombination between sites from 74 bp to 15 kb apart. In agreement with previous work, a persistence length of 50 nm was determined. FLP recombination of the same substrates in mammalian cells showed that chromatin increases the flexibility of DNA at short distances, giving an apparent persistence length of 27 nm.
Clinical gait analysis by neural networks: issues and experiences

Clinical gait analysis is an area aimed at the provision of support for diagnoses and therapy considerations, the development of bio-feedback systems to train patients, and the recognition of effects of multiple diseases and still active compensation. The data recorded with ground reaction force measurement platforms is a convenient starting point for gait analysis. The authors argue in favor of using the raw data from such force platforms and apply artificial neural networks for gait malfunction identification. They discuss their latest results in this line of research by using a supervised learning rule. The employed classification approach is learning vector quantization which proved to be highly robust in the training process yielding a remarkably high recognition accuracy of gait patterns.
A Context-Oriented Extension of F#

Context-Oriented programming languages provide us with primitive constructs to adapt program behaviour depending on the evolution of their operational environment, namely the context. In previous work we proposed ML_CoDa, a context-oriented language with two-components: a declarative constituent for programming the context and a functional one for computing. This paper describes the implementation of ML_CoDa as an extension of F#.
On physical layer-oriented routing with power control in ad hoc wireless networks

Routing in ad hoc wireless networks does not simply consist in finding a route with shortest length (as in wired networks with virtually error-free communication links), but it requires the creation of a stable and good quality communication route to avoid any unnecessary packet loss. In this paper,we discuss physical layer-oriented routing in ad hoc wireless networks, and we analyse the potential advantages of combining the use of power control (PC) with the chosen routing strategy. More precisely, we propose a modified ad hoc on-demand distance vector (MAODV) routing protocol, with and without PC, derived from the AODV-routing protocol by considering the bit error rate at the end of a multi-hop path as the metric to be minimised for route selection. In other words, we consider routing with a physical layer-oriented quality of service criterion, and we analyse the system performance in scenarios with either strong line-of-sight (LOS) or shadowed communications. Although in a scenario with strong LOS communications there are a few cases where the MAODV-PC protocol offers the best performance, in the presence of shadowed communications the proposed physical layer-oriented strategy is not attractive.
Effective Anomaly Detection in Sensor Networks Data Streams

—This paper addresses a major challenge in data mining applications where the full information about the underlying processes, such as sensor networks or large online database, cannot be practically obtained due to physical limitations such as low bandwidth or memory, storage, or computing power. Motivated by the recent theory on direct information sampling called compressed sensing (CS), we propose a framework for detecting anomalies from these large-scale data mining applications where the full information is not practically possible to obtain. Exploiting the fact that the intrinsic dimension of the data in these applications are typically small relative to the raw dimension and the fact that compressed sensing is capable of capturing most information with few measurements, our work show that spectral methods that used for volume anomaly detection can be directly applied to the CS data with guarantee on performance. Our theoretical contributions are supported by extensive experimental results on large datasets which show satisfactory performance.
Modeling Of Seismoelectric Effects In A Borehole

We present a method to simulate the propagation of seismic and converted electromagnetic waves generated by a mechanical borehole source embedded in a layered poroelastic medium. The electroseismic conversions occur at both the borehole wall and the layer boundaries. Most studies in electroseismic effects have been modelled and tested with seismic sources and detectors (geophones and antennas) at the surface. In this paper, we investigate the case of a seismic source in a borehole and receivers either at the surface or embedded in the medium. The method is formulated as a boundary element technique (where the poroelastic displacement and relative flow Green's functions are calculated by the discrete wavenumber method. The singular properties of the Green's functions are determined analytically using static Green's functions to regularize the integrals. This is necessary to calculate the element's self interaction. The borehole is cylindrical and its axis rulls normal to the interfaces. The coupled electroseismic effects in the layered media are included by using the global matrix technique. The developed method is an extension of the model of Biot-Rosenbaum, who applied the wavenumber integration technique to investigate the effect of formation permeability on Stoneley waves, using Biot's theory to model the wave propagation effects of a homogeneous permeable formation surrounding a borehole. We extend the Biot-Rosenbaum model by including the effect of a heterogeneous permeable formation surrounding the borehole. The effect of formation permeable zones (or fractured zones) on Stoneley waves can now be investigated. The other modification is the inclusion of conversions of mechanical into electromagnetic waves at mechanical and/or electrical contrasts in the poroelastic formation. The converted electromagnetic fields are sensitive to large perme-ability contrasts and fluid chemistry contrasts inside a reservoir. Using the electroseis-mic method downhole will provide more information about permeability/permeability 14-1 Haartsen and Toksiiz contrasts in the formation, as well as additional lithological information (salinity of the fluids).
A Cascade Framework for a Real-Time Statistical Plate Recognition System

This paper describes a plate recognition system that can process images rapidly at high accuracy rates. This system is designed to meet the requirements of performance, computational speed, and adaptation for vehicle surveillance applications, such as stolen car detection systems. These requirements are satisfied by adopting a cascade framework, utilizing plate characteristics, and developing fast one-pass algorithms. Our system is composed of three main cascading modules for plate detection, character segmentation, and postprocessing. Each module is further decomposed into several cascading procedures, which are composed of successively more complex rejecters. The first module rapidly rejects a majority of nonplate regions by using low computational gradient features and a one-pass scanning algorithm followed by heavy computational statistical rejecters. The second module rejects a majority of noncharacter regions in a similar manner. A peak-valley analysis algorithm is proposed to rapidly detect all promising candidates of character regions. The third module eliminates the plate characters that do not satisfy the plate specifications. In our experiments, the system can recognize plates over 38 frames per second with a resolution of 640 times 480 pixels on a 3-GHz Intel Pentium 4 personal computer
Spatial reasoning for human robot interaction

Robots' interaction with humans raises new issues for geometrical reasoning where the humans must be taken explicitly into account. We claim that a human-aware motion system must not only elaborate safe robot motions, but also synthesize good, socially acceptable and legible movement. This paper focuses on a manipulation planner and a placement mechanism that take explicitly into account its human partners by reasoning about their accessibility, their vision field and their preferences. This planner is part of a human-aware motion and manipulation planning and control system that we aim to develop in order to achieve motion and manipulation tasks in presence or in synergy with humans.
Cascaded ABC-LM algorithm based optimization and nonlinear system identification

In this paper, the well-known heuristic Artificial Bee Colony algorithm (ABC) and deterministic Levenberg-Marquardt (LM) optimization method are unified to get better performance of nonlinear optimization. In the proposed cascaded ABC-LM algorithm, the power of the ABC and LM algorithms are synergized to reduce computational-time and get rid of the problem “stucking at local minima” of some nonlinear functions. Then, the proved power of the cascaded optimization is also tested on the training of Artificial Neural Network (ANN) for classification of XOR data and nonlinear system identification of real-time inverted pendulum set-up. The comparisons in function optimization and system identification using ABC, LM and ABC-LM showed that ABC-LM optimized nonlinear functions and ABC-LM trained ANN has resulted smaller cost functions and mean-squared-error (MSE) values, respectively.
Accurate display of tensor product isosurfaces

A general method for rendering isosurfaces of multivariate rational and polynomial tensor products is described. The method is robust up to degree 15, handling singularities without introducing spurious rendering artifacts. The approach does not solve the problem of singularities in general, but it removes the problem from the rendering domain to the interpolation/approximation domain. It is based on finding real roots of a polynomial in Bernstein form. This makes it particularly suitable for parallel and pipelined processing. It is envisioned that the tensor products will be used as approximants or interpolants for empirical data or scalar fields. An interpolation scheme is given as an example. <<ETX>>
Greedy confidence bound techniques for restless multi-armed bandit based Cognitive Radio

In this paper, we deal with Bayesian restless multi-armed bandit (RMAB) techniques which are appliced to Cognitive Radio. We assume there are multiple arms, each of which evolves as a Markov chain with known parameters. A player seeks to activate more than one arms at each time in order to maximize the expected total reward with multiple plays. We consider non-Bayesian RMAB where the parameters of the Markov chain are unknown. We propose a simple but effective algorithm called two-slot greedy confidence bound algorithm (Two-slot GCB), which perform better than existing upper confidence bound (UCB) algorithms.
Automatic Assessment of Children’s Speech with Cleft Lip and Palate

Cleft lip and palate (CLP) may cause functional limitations even after adequate surgical and non-surgical treatment, speech disorder being one of them. Until now, an automatic, objective means to determine and quantify the intelligibility did not exist. We have created an automatic evaluation system that assesses speech, based on the result of an automatic speech recognizer. It was applied to 35 recordings of children with CLP. A subjective evaluation of the intelligibility was performed by two experts and confronted to the automatic speech evaluation. It complied with experts’ rating of intelligibility. Furthermore we present the results obtained on a control group of 45 recordings of normal children and compare these results with those of the CLP children. Samodejna ocena govora otrok z zajčjo ustnico in volčjim žrelom Zajčja ustnica in volčje žrelo lahko povzročata funkcijske omejitve tudi po ustreznem operativnem ali neoperativnem zdravljenju, med njimi so tudi motnje govora. Do sedaj ni obstajal samodejni objektivni način ugotavljanja razumljivosti. Razvili smo sistem za samodejno vrednotenje, ki ocenjuje govor na podlagi rezultatov samodejnega razpoznavalnika govora. Uporabljen je bil pri 35 posnetkih otrok z zajčjo ustnico in volčjim žrelom. Subjektivno vrednotenje razumljivosti, ki sta ga opravila dva strokovnjaka, je bilo soočeno s samodejnim vrednotenjem govora. Slednje se je ujemalo z oceno razumljivosti strokovnjakov. Poleg tega predstavljamo rezultate, pridobljene pri kontrolni skupini s 45 posnetki govora otrok brez motenj govora, in jih primerjamo z rezultati posnetkov govora otrok z zajčjo ustnico in volčjim žrelom.
Enhancing mucosal immunity in mice by recombinant adenovirus expressing major epitopes of porcine circovirus-2 capsid protein delivered with cytosine-phosphate-guanosine oligodeoxynucleotides

A recombinant replication-defective adenovirus expressing the major epitopes of porcine circovirus-2 (PCV-2) capsid protein (rAd/Cap/518) was previously constructed and shown to induce mucosal immunity in mice following intranasal delivery. In the present study, immune responses induced by intranasal immunization with a combination of rAd/Cap/518 and cytosine-phosphate-guanosine oligodeoxynucleotides (CpG ODN) were evaluated in mice. The levels of PCV-2-specific IgG in serum and IgA in saliva, lung, and intestinal fluids were significantly higher in the group immunized with rAd/Cap/518 and CpG ODN than animals immunized with rAd/Cap/518 alone. The frequencies of IL-2-secreting CD4+ T cells and IFN-γ-producing CD8+ T cells were significantly higher in the combined immunization group than mice immunized with rAd/Cap/518 alone. The frequencies of CD3+, CD3+CD4+CD8-, and CD3+CD4-CD8+ T cells in the combined immunization group were similar to that treated with CpG ODN alone, but significantly higher than mice that did not receive CpG ODN. PCV-2 load after challenge in the combined immunization group was significantly lower than that in the phosphate-buffered saline placebo group and approximately 7-fold lower in the group treated with CpG ODN alone. These results indicate that rAd/Cap/518 combined with CpG ODN can enhance systemic and local mucosal immunity in mice, and represent a promising synergetic mucosal vaccine against PCV-2.