Miracle-dz/UniFAR-FTUs huggingface dataset:
Spontaneous in vitro release of alveolar-macrophage cytokines after the intratracheal instillation of bleomycin in rats. Characterization and kinetic studies.

The intratracheal administration of bleomycin in rats elicits an acute inflammatory response in the lung followed by the development of pulmonary fibrosis. The alveolar macrophage (AM) is a key effector cell involved in this process because of its potential to release a variety of hormonelike molecules (cytokines) that can modulate systemic responses as well as the local response of other lung cells including the interstitial fibroblast. In this report, we have documented the chronology of the in vitro spontaneous release of AM cytokines after a single instillation of bleomycin. We show that supernatants from AM harvested after the administration of bleomycin but not after saline contain lymphocyte-activating factor (interleukin-1) activity. Maximal activity was detected between 6 and 12 h and was barely detectable by Day 7 after bleomycin. In addition, supernatants showing interleukin-1 (IL-1) activity also inhibited the proliferation of log-phase normal rat lung fibroblasts. Fractionation of supernatants from AM harvested 6 h after bleomycin demonstrated that both lymphocyte-activating factor and fibroblast modulatory activity coelute in the same 18-kDa region, suggesting that IL-1 may demonstrate both activities. We also report here the spontaneous release of a second AM cytokine, hepatocyte-stimulating factor, which we have recently shown in humans to be identical to interferon beta 2 and which initiates the hepatic acute-phase protein response. The release of this 30-kDa cytokine from AM of rats exposed to bleomycin has a different chronology than does IL-1, showing a steady increase over time, with maximal activity at Day 28 after bleomycin. (ABSTRACT TRUNCATED AT 250 WORDS)
Influenza Virus Surveillance in Wild Birds in Italy: Results of Laboratory Investigations in 2003–2005

Abstract Following the avian influenza (AI) epidemics occurring in different areas of the world, a surveillance program funded by the Italian Ministry of Health was implemented. In the framework of this program, an investigation of wild birds was carried out to assess the circulation of AI viruses in their natural reservoir. More than 3000 samples, mainly cloacal swabs, were collected from migratory wild birds belonging to the orders Anseriformes and Charadriiformes. Samples were screened by means of a real-time reverse transcriptase polymerase chain reaction (RRT-PCR), then processed for attempted virus isolation in embryonated fowl's specific pathogen-free eggs. Approximately 5% of the samples were positive for type A influenza viruses by RRT-PCR, and from 14 of those samples AI viruses were isolated and fully characterized. The isolates, belonging to 8 different avian influenza virus subtype combinations (H10N4, H1N1, H4N6, H7N7, H7N4, H5N1, H5N2, and H5N3), were obtained from migratory Anseriformes.
Genome Sequence of an Epidemic Isolate of Mycobacterium abscessus subsp. bolletii from Rio de Janeiro, Brazil

ABSTRACT Multiple isolates of Mycobacterium abscessus subsp. bolletii, collectively called BRA100, were associated with outbreaks of postsurgical skin infections across various regions of Brazil from 2003 to 2009. We announce the draft genome sequence of a newly sequenced BRA100 strain, M. abscessus subsp. bolletii CRM-0020, isolated from a patient in Rio de Janeiro, Brazil.
Learning Uncertain Convolutional Features for Accurate Saliency Detection

Deep convolutional neural networks (CNNs) have delivered superior performance in many computer vision tasks. In this paper, we propose a novel deep fully convolutional network model for accurate salient object detection. The key contribution of this work is to learn deep uncertain convolutional features (UCF), which encourage the robustness and accuracy of saliency detection. We achieve this via introducing a reformulated dropout (R-dropout) after specific convolutional layers to construct an uncertain ensemble of internal feature units. In addition, we propose an effective hybrid upsampling method to reduce the checkerboard artifacts of deconvolution operators in our decoder network. The proposed methods can also be applied to other deep convolutional networks. Compared with existing saliency detection methods, the proposed UCF model is able to incorporate uncertainties for more accurate object boundary inference. Extensive experiments demonstrate that our proposed saliency model performs favorably against state-ofthe-art approaches. The uncertain feature learning mechanism as well as the upsampling method can significantly improve performance on other pixel-wise vision tasks.
IFFTC-Based Procedure for Hidden Tone Detection

In this paper a procedure for the detection of hidden tones in the spectrum of a signal is proposed and experimentally evaluated. It is based on the "Corrected Interpolated FFT" algorithm for the estimation of spectral parameters of nonhidden tones, and on the analysis of the disagreement between measured and expected spectra in order to detect hidden tones. The design of the procedure takes advantage of experimental design techniques in the threshold evaluation
A study of long‐term fMRI reproducibility using data‐driven analysis methods

The reproducibility of functional magnetic resonance imaging (fMRI) is important for fMRI‐based neuroscience research and clinical applications. Previous studies show considerable variation in amplitude and spatial extent of fMRI activation across repeated sessions on individual subjects even using identical experimental paradigms and imaging conditions. Most existing fMRI reproducibility studies were typically limited by time duration and data analysis techniques. Particularly, the assessment of reproducibility is complicated by a fact that fMRI results may depend on data analysis techniques used in reproducibility studies. In this work, the long‐term fMRI reproducibility was investigated with a focus on the data analysis methods. Two spatial smoothing techniques, including a wavelet‐domain Bayesian method and the Gaussian smoothing, were evaluated in terms of their effects on the long‐term reproducibility. A multivariate support vector machine (SVM)‐based method was used to identify active voxels, and compared to a widely used general linear model (GLM)‐based method at the group level. The reproducibility study was performed using multisession fMRI data acquired from eight healthy adults over 1.5 years' period of time. Three regions‐of‐interest (ROI) related to a motor task were defined based upon which the long‐term reproducibility were examined. Experimental results indicate that different spatial smoothing techniques may lead to different reproducibility measures, and the wavelet‐based spatial smoothing and SVM‐based activation detection is a good combination for reproducibility studies. On the basis of the ROIs and multiple numerical criteria, we observed a moderate to substantial within‐subject long‐term reproducibility. A reasonable long‐term reproducibility was also observed from the inter‐subject study. It was found that the short‐term reproducibility is usually higher than the long‐term reproducibility. Furthermore, the results indicate that brain regions with high contrast‐to‐noise ratio do not necessarily exhibit high reproducibility. These findings may provide supportive information for optimal design/implementation of fMRI studies and data interpretation.
Maternal controlling feeding practices and girls' inhibitory control interact to predict changes in BMI and eating in the absence of hunger from 5 to 7 y.

BACKGROUND Mothers use a range of feeding practices to limit children's intake of palatable snacks (eg, keeping snacks out of reach, not bringing snacks into the home), but less is known about the effects of these practices on children's eating and weight outcomes. OBJECTIVE The objective was to identify distinct feeding practice profiles and evaluate the interactive effects of these profiles and girls' temperament (inhibitory control and approach) on girls' eating behaviors and weight outcomes at 5 and 7 y. DESIGN Participants included 180 mother-daughter dyads; measures were mothers' reports of controlling feeding practices and girls' height and weight, eating in the absence of hunger (EAH) at 5 y, and inhibitory control (a measure of behavioral inhibition) and approach (a measure of appetitive motivation) at 7 y. RESULTS Latent profile analysis of maternal feeding practices showed 4 feeding profiles based on maternal use of limit-setting practices and keeping snacks out of girls' physical reach, a restrictive practice: Unlimited Access to Snacks, Sets Limits+Does Not Restrict Snacks, Sets Limits+Restricts High Fat/Sugar Snacks, and Sets Limits+Restricts All Snacks. Girls whose mothers used Sets Limits+Restricts All Snacks had a higher approach and EAH at 5 y. Low inhibitory control girls whose mothers used Sets Limits+Restricts All Snacks or Unlimited Access to Snacks had greater increases in EAH and body mass index (BMI) from 5 to 7 y. CONCLUSIONS Effects of maternal control on girls' EAH and BMI may differ by the type of practice used (eg, limit-setting or restrictive practices). Girls with low inhibitory control were more susceptible to the negative effects of low and high control.
“Motor circuit” gray matter changes in idiopathic cervical dystonia

Background: Idiopathic cervical dystonia (ICD), the most common adult-onset focal dystonia, is clinically characterized by involuntary uni- or bilateral contractions of head and neck musculature. One crucial criterion for the diagnosis of ICD is normal results on MRI of the brain. Objective: To test the hypothesis whether subtle brain structure changes occur in ICD. Methods: Using voxel-based morphometry, the authors compared the brain structure of 10 patients with ICD with that of 10 healthy sex- and age-matched controls using high-resolution MRI. Results: Patients with ICD showed an increase in gray matter density bilaterally in the motor cortex and in the cerebellar flocculus and unilaterally in the right globus pallidus internus. In addition, a decrease in gray matter density was observed in the right caudal supplementary motor area as well as in the right dorsal lateral prefrontal and visual cortex. Conclusions: These results demonstrate for the first time in vivo subtle morphologic alterations in ICD. These data challenge the principal concept that patients with ICD have no brain structure abnormalities and that this movement disorder is solely due to abnormal cerebral function.
Towards a tighter coupling of visualization and public policy making

The purpose of this ongoing work is to motivate public policy making as an application area for information visualization and visual analytics. Through our expertise gathered in several policy making-related projects, we identified parallels between the benefits of visualization and the needs of evidence-based public policy making. In the following, we will share our previous work consisting of the conceptual introduction of information visualization and visual analytics into the application field of public policy making. Moreover, we will show two real-world cases applying this concept. Finally, we will share identified challenges to be addressed by the information visualization and visual analytics domains in the future.
Performance Analysis of MPSK Phase Detectors for Carrier Synchronization PLLs at Low SNRs

In this letter, we analyze the performance of a category of phase detectors (PDs) for carrier synchronization phase-locked loops (PLLs) in M-ary phase shift keying (MPSK) receivers working at low signal-to-noise ratios (SNRs). These PDs have the property that their outputs are functions of the inputs' phase only, and thus, their performance is independent of the automatic gain control (AGC) circuits. We deduce closed-form expressions about the linearized gain and equivalent noise variance of these PDs when SNR goes to zero and sum up simple approximate formulas for three typical PDs at all SNRs. We also prove that the modified Mth-power PD performs asymptotically best in this category of PDs as SNR goes to zero.
Monodispersed metal clusters in solid matrices: A new experimental setup

We describe a new experimental setup for the production of samples of metal clusters embedded in matrices stable at ambient conditions. The cluster ions are generated in the gas phase and codeposited fragmentation-free together with the evaporated matrix. Mean cluster sizes range from a few to many thousands of atoms. For small clusters (n<20) mass selection is possible; larger clusters are deposited in narrow size distributions. Matrix materials include metals (Cu and Ag) and oxides such as quartz. The performance of the apparatus as well as sample characterization procedures are described. We show first results on the magnetic properties of different cobalt cluster size distributions (⟨n⟩=15,600,2300,6500) embedded in copper matrices, demonstrating intercluster as well as cluster-lattice interactions.
Adaptive fuzzy control systems with dynamic structure

This article proposes a novel fuzzy system, referred to as a dynamic structure fuzzy system, to address tracking control problems for unknown nonlinear dynamical systems. The fuzzy system is employed to reconstruct the unknown nonlinearities of dynamic systems. In the dynamic structure fuzzy system, the number of fuzzy rules can be either increased or decreased over time based on the required approximation accuracy. The advantage of the dynamic structure fuzzy system is that a suitable-sized fuzzy system can be found to avoid overfitting or underfitting data sets. By using Gaussian radial basis function (GRBF) as a membership function, adaptation laws are presented for tuning all parameters of the parameterized fuzzy system, including the output weights, the widths and the centers of the GRBF's. Global boundedness of the overall control scheme is guaranteed in the sense of Lyapunov. The tracking error converges to the required precision through the adaptive control scheme derived by the Lyapunov synthesis approach. Simulations performed on an underwater vehicle system demonstrate the effectiveness of our scheme.
Comparison of Salmonella enterica Serovar Enteritidis Levels in Crops of Fed or Fasted Infected Hens

Abstract Long-term feed withdrawal has been shown to increase ileocecal intestinal colonization and fecal shedding of Salmonella enterica serovar Enteritidis in challenged hens. Less information is available regarding effects of fasting on crop colonization. Two trials were conducted to compare effects of 14-day feed withdrawal vs. full feed on crop colonization in hens challenged with Salmonella Enteritidis. The levels of Salmonella Enteritidis in the crops of fasted hens were significantly higher than in nonfasted hens on days 3 and 10 and days 3, 9, and 16 postinfection (PI) in trials 1 and 2, respectively. Fecal shedding of Salmonella Enteritidis was significantly increased in the fasted hens on day 10 PI in trial 1. Analysis of crop IgA anti–Salmonella Enteritidis lipopolysaccharide levels in crop lavage samples of hens in trial 1 revealed a humoral response PI in both treatment groups with no significant differences, although peak response for fasted hens occurred 1 wk later. Histologic evaluation of hematoxylin and eosin–stained crop sections from trial 1 birds revealed mild to moderate heterophilic infiltration within the crop lamina propria (LP) or LP and epithelium of nonfasted infected hens at 24 and 96 hr PI. In comparison, heterophils in crops of fasted hens infected at this time point were sparse, indicating a possible diminished heterophil response in the fasted birds. Multifocal areas of tissue inflammation, as indicated by marked heterophil infiltration, with necrosis and sloughing of epithelium, were observed in crops from fasted hens at day 11 PI (14th day of feed withdrawal) but not in the fed groups. This severe heterophilic inflammation was observed in both challenged and nonchallenged fasted hens, suggesting that some factor other than Salmonella Enteritidis was responsible. These results indicate that feed withdrawal can have a dramatic effect on the integrity of the crop and its ultimate response to infection.
Application of Methyl Orange in the Spectrophotometric Determination of Citalopram and Dapotextine in Pharmaceutical Formulations

A simple, rapid and sensitive spectrophotometric method has been proposed for the assay of citalopram (CIT) and dapotextine (DPT) in bulk and pharmaceutical formulations. The method based on the reaction of the selected drugs with methyl orange (MO) in buffered aqueous solution at pH = 5.0 and pH = 3.0 for CIT and DPT, respectively. The formed yellow ion-pair complexes were extracted with dichloromethane and their absorbance was measured at 422 nm. The best conditions of the reaction were studied and optimized. The extracts are intensely colored and very stable at room temperature. The calibration graphs were linear over the concentration range of 1.2 – 4.8 mg/ml for CIT and 0.4 – 4.0 mg/ml for DPT. The drug–dye stoichiometric ratio as determined by the Job’s method was found to be 1:1. The proposed method was successfully applied for determination of the drugs in tablets with good accuracy and precision. Excipients used as additive in commercial formulations did not interfere in the analysis. The proposed method can be recommended for quality control and routine analysis where time, cost effectiveness and high specificity of analytical technique are of great importance.
Interaction of estrogen receptor‐α ligand binding domain with nuclear proteins of aging mouse brain

After the interaction of estrogen with the ligand binding domain (LBD) of mouse estrogen receptor‐α (mERα) and hormone‐responsive elements of target genes, many nuclear proteins are recruited to regulate the expression of specific genes. Because it is not known which brain proteins interact with LBD or whether these proteins vary with age and sex, we used pull‐down assay and far Western blotting to detect five nuclear proteins of 160, 140, 87, 60, and 46 kD in the mouse brain. These interacting proteins were identified as PELP1, RIP140, PGC1α, BAF60, and ADA3, respectively. The level of PELP1, RIP140, PGC1α, and BAF60 decreased drastically in old compared with adult male mice, whereas the ADA3 level showed no significant change. PELP1, PGC1α, and BAF60 levels were lower in old male compared with female mice. Thus we report the identification and interaction of five nuclear proteins with mERα‐LBD, indicating their role in estrogen signaling and brain functions during aging. © 2009 Wiley‐Liss, Inc.
GOST R 34.11-94: Hash Function Algorithm

This document is intended to be a source of information about the Russian Federal standard hash function (GOST R 34.11-94), which is one of the Russian cryptographic standard algorithms (called GOST algorithms). Recently, Russian cryptography is being used in Internet applications, and this document has been created as information for developers and users of GOST R 34.11-94 for hash computation. This document is not an Internet Standards Track specification; it is published for informational purposes.
Control and system identification for the Berkeley lower extremity exoskeleton (BLEEX)

The Berkeley lower extremity exoskeleton (BLEEX) is an autonomous robotic device whose function is to increase the strength and endurance of a human pilot. In order to achieve an exoskeleton controller which reacts compliantly to external forces, an accurate model of the dynamics of the system is required. In this report, a series of system identification experiments was designed and carried out for BLEEX. As well as determining the mass and inertia properties of the segments of the legs, various non-ideal elements, such as friction, stiffness and damping forces, are identified. The resulting dynamic model is found to be significantly more accurate than the original model predicted from the designs of the robot.
Using Human-Inspired Models for Guiding robot locomotion. (Utilisation des modèles InspiréS de l'humain pour le guidage de la locomotion de robots)

This thesis has been done within the framework of the European Project Koroibot which aims at developing advanced algorithms to improve the humanoid robots locomotion. It is organized in three parts. With the aim of steering robots in a safe and efficient manner among humans it is required to understand the rules, principles and strategies of human during locomotion and transfer them to robots. The goal of this thesis is to investigate and identify the human locomotion strategies and create algorithms that could be used to improve robot capabilities. A first contribution is the analysis on pedestrian principles which guide collision avoidance strategies. In particular, we observe how humans adapt a goal-direct locomotion task when they have to interfere with a moving obstacle crossing their way. We show differences both in the strategy set by humans to avoid a non-collaborative obstacle with respect to avoid another human, and the way humans interact with an object moving in human-like way. Secondly, we present a work done in collaboration with computational neuroscientists. We propose a new approach to synthetize realistic complex humanoid robot movements with motion primitives. Human walking-to-grasp trajectories have been recorded. The whole body movements are retargeted and scaled in order to match the humanoid robot kinematics. Based on this database of movements, we extract the motion primitives. We prove that these sources signals can be expressed as stable solutions of an autonomous dynamical system, which can be regarded as a system of coupled central pattern generators (CPGs). Based on this approach, reactive walking-to-grasp strategies have been developed and successfully experimented on the humanoid robot HRP at LAAS-CNRS. In the third part of the thesis, we present a new approach to the problem of vision-based steering of robot subject to non-holonomic constrained to pass through a door. The door is represented by two landmarks located on its vertical supports. The planar geometry that has been built around the door consists of bundles of hyperbolae, ellipses, and orthogonal circles. We prove that this geometry can be directly measured in the camera image plane and that the proposed vision-based control strategy can also be related to human. Realistic simulation and experiments are reported to show the effectiveness of our solutions.