Miracle-dz/UniFAR-FTUs huggingface dataset:
High Neonatal Leptin Exposure Enhances Brain GR Expression and Feedback Efficacy on the Adrenocortical Axis of Developing Rats.

Leptin modifies the activity of the hypothalamic-pituitary-adrenal axis in adult rodents and inhibits the production of glucocorticoids from human and rat adrenals in vitro. During development, high levels of circulating leptin and low levels of corticosterone secretion are observed together with adrenal hyporesponsiveness to stress. As chronic neonatal leptin administration reduced stress-induced corticotropin-releasing factor mRNA expression and ACTH secretion in pups, we determined whether elevated leptin levels enhanced the feedback effect of glucocorticoids on the hypothalamic-pituitary-adrenal axis. In naive pups we found a highly significant inverse relationship between plasma levels of leptin and corticosterone (P < 0.01) during postnatal d 6–20. We tested the ability of dexamethasone (1 or 10 μg/kg BW, ip,− 3 h before stress) to suppress ether-induced ACTH secretion in 10-d-old pups that were treated during the neonatal period (d 2–9) with either vehicle or leptin (1 or 3 mg/kg BW, ip, daily). Th.
Regulation of Small RNAs and Corresponding Targets in Nod Factor-Induced Phaseolus vulgaris Root Hair Cells

A genome-wide analysis identified the set of small RNAs (sRNAs) from the agronomical important legume Phaseolus vulgaris (common bean), including novel P. vulgaris-specific microRNAs (miRNAs) potentially important for the regulation of the rhizobia-symbiotic process. Generally, novel miRNAs are difficult to identify and study because they are very lowly expressed in a tissue- or cell-specific manner. In this work, we aimed to analyze sRNAs from common bean root hairs (RH), a single-cell model, induced with pure Rhizobium etli nodulation factors (NF), a unique type of signal molecule. The sequence analysis of samples from NF-induced and control libraries led to the identity of 132 mature miRNAs, including 63 novel miRNAs and 1984 phasiRNAs. From these, six miRNAs were significantly differentially expressed during NF induction, including one novel miRNA: miR-RH82. A parallel degradome analysis of the same samples revealed 29 targets potentially cleaved by novel miRNAs specifically in NF-induced RH samples; however, these novel miRNAs were not differentially accumulated in this tissue. This study reveals Phaseolus vulgaris-specific novel miRNA candidates and their corresponding targets that meet all criteria to be involved in the regulation of the early nodulation events, thus setting the basis for exploring miRNA-mediated improvement of the common bean–rhizobia symbiosis.
Software applications toward quantitative metabolic flux analysis and modeling

Metabolites and their pathways are central for adaptation and survival. Metabolic modeling elucidates in silico all the possible flux pathways (flux balance analysis, FBA) and predicts the actual fluxes under a given situation, further refinement of these models is possible by including experimental isotopologue data. In this review, we initially introduce the key theoretical concepts and different analysis steps in the modeling process before comparing flux calculation and metabolite analysis programs such as C13, BioOpt, COBRA toolbox, Metatool, efmtool, FiatFlux, ReMatch, VANTED, iMAT and YANA. Their respective strengths and limitations are discussed and compared to alternative software. While data analysis of metabolites, calculation of metabolic fluxes, pathways and their condition-specific changes are all possible, we highlight the considerations that need to be taken into account before deciding on a specific software. Current challenges in the field include the computation of large-scale networks (in elementary mode analysis), regulatory interactions and detailed kinetics, and these are discussed in the light of powerful new approaches.
MOMA: Visual Mobile Marker Odometry

In this paper, we present a cooperative visual odometry system based on the detection of mobile markers. To this end, we introduce a simple scheme that realizes visual mobile marker odometry via accurate fixed marker-based camera positioning and we discuss the characteristics of errors inherent to the method compared to classical fixed marker-based navigation and visual odometry. The proposed cooperative scheme has the advantage of not needing any feature or fiducial marker in the environment, which can be used for indoor and underwater applications where it can be harder to extract reliable features. We provide specific configurations of UAV and UGV robots including one that allows continuous movements of the UAV, and a minimal caterpillar-like configuration that works with one UGV alone. Finally, we present a real-world implementation and an evaluation of the proposed configurations.
Music-supported motor training after stroke reveals no superiority of synchronization in group therapy

Background: Music-supported therapy has been shown to be an effective tool for rehabilitation of motor deficits after stroke. A unique feature of music performance is that it is inherently social: music can be played together in synchrony. Aim: The present study explored the potential of synchronized music playing during therapy, asking whether synchronized playing could improve fine motor rehabilitation and mood. Method: Twenty-eight patients in neurological early rehabilitation after stroke with no substantial previous musical training were included. Patients learned to play simple finger exercises and familiar children's songs on the piano for 10 sessions of half an hour. Patients first received three individual therapy sessions and then continued in pairs. The patient pairs were divided into two groups. Patients in one group played synchronously (together group) whereas the patients in the other group played one after the other (in-turn group). To assess fine motor skill recovery the patients performed standard clinical tests such as the nine-hole-pegboard test (9HPT) and index finger-tapping speed and regularity, and metronome-paced finger tapping. Patients' mood was established using the Profile of Mood States (POMS). Results: Both groups showed improvements in fine motor control. In metronome-paced finger tapping, patients in both groups improved significantly. Mood tests revealed reductions in depression and fatigue in both groups. During therapy, patients in the in-turn group rated their partner as more sympathetic than the together-group in a visual-analog scale. Conclusions: Our results suggest that music-supported stroke rehabilitation can improve fine motor control and mood not only individually but also in patient pairs. Patients who were playing in turn rather than simultaneously tended to reveal greater improvement in fine motor skill. We speculate that patients in the former group may benefit from the opportunity to learn from observation.
Cyclicity and Stability in Mother-Infant Face-to-Face Interaction: A Comment on Cohn and Tronick (1988)

Cohn and Tronick (1988) found that the onset times of behavioral change in mother-infant face-toface interaction are stochastic rather than periodic. This comment offers an explanation of why thenresult replicates that of Kaye and Fogel (1980), in spite of important differences in how interactive behavior is conceptualized, coded, and treated statistically. Furthermore, it is suggested that stochastic variability in onset times has profound implications for our understanding of the process of mother-infant interaction and of the ways in which infants develop in the context of that interaction. The social system of mother-infant face-to-face interaction during the first year has attracted the attention of scholars from a variety of disciplines. This dyadic relationship has been examined as a setting for infant development of affect and attention, as a paradigm of changes in bidirectional social influences, and as the source of individual differences in attachment and selfregulation. In these ways, the mother-infant face-to-face interaction partakes of the same conceptual issues that drive inquiry in all human development research. Mother-infant face-to-face interaction studies differ from other social interaction studies because issues of sequence and cyclicity have been brought to the forefront of the inquiry. Research on mother-infant face-to-face interaction uses time as an explicit variable and examines the role of timing in the process of mutual regulation. Although the timing of actions is a general feature of dyadic relationships, it has become salient in studies of early interactions because they are relatively contentfree. In early adult-infant interaction it may matter less what specific actions are performed than when and how frequently those actions occur. Cohn and Tronick (1988) have presented a rigorous analysis of the nature of timing processes in face-to-face interaction. They reject the hypothesis that mutual regulation between mother and infant is achieved by bidirectional entrainment of periodic cycling of each individual's behavior, a view advanced in the work of Condon and Sander (1974) and of Brazelton, Koslowski, and Main (1974). The periodic entrainment hypothesis leaves mother and infant dependent on speeding up or slowing down some presumed internal clocks. Even for the relatively content-free mother-infant face-to-face interaction, this hypothesis oversimplifies and rigidifies the process of mutual adaptation. Cohn and Tronick's (1988) data, instead, supported the hypothesis that mutual regulation is achieved by short-term bidirectional responsiveness to occurrences, the onsets of which
Adaptive Hybrid Agents for Tactical Decisions in Pedestrian Environments

This paper presents a hybrid agent architecture for modeling different types of decisions in a pedestrian simulation system. In particular, the present work focuses on tactical level decisions that are essentially related to the choice of a route to follow in an environment comprising several rooms connected by openings. These decisions are then enacted at the operational level by mean of a floor-field based model, in a discrete simulation approach. The described model allows the agent taking decisions based on a static a-priori knowledge of the environment and dynamic perceivable information on the current level of crowdedness of visible path alternatives. The paper presents the model formally, motivating the adopted choices with reference to the relevant state of the art. The model is also experimented in benchmark scenarios showing the adequacy in providing adaptiveness to the contextual situation.
Stimulus tracking in functional magnetic resonance imaging (fMRI)

Functional hia~etic Resonance tiagery (~~ ) is a new’ medical ima=tig technology pro~ti~mg tictional, as opposed to natomicd, mapptig of the human brain. The promise of this non-invasive technique has opened new’ ch~enges for mdtimedia researchers. A the fieId of human functional neurotia=tig e~lodes and the technology of ~W advmces, computational techniques for expertient control, subject stimu~ generation, and joint stimti-activation tiaetig are Iachg. host computational work h= focused on impro~tig the analysis of the brab S=S. Tti paper describes eomputiationa~ mechanisms for the dehery md tiactig of multimedia stimti and a correlation framework for stimti and brain responses. NIediaStim, a new integrated data co~ection fraework for stimuIus tracking $hat k currently under development. NlediaSfi etiends the stimti paradi=m to composite multimedia presentations. To stiulate a real-tie sitiation as reafitica~y as possible, it is tiportant to stidy the brain
Impact of the deep convection of isoprene and other reactive trace species on radicals and ozone in the upper troposphere

Observations of a comprehensive suite of inor- ganic and organic trace gases, including non-methane hy- drocarbons (NMHCs), halogenated organics and oxygenated volatile organic compounds (OVOCs), obtained from the NASA DC-8 over Canada during the ARCTAS aircraft cam- paign in July 2008 illustrate that convection is important for redistributing both long- and short-lived species throughout the troposphere. Convective outflow events were identified by the elevated mixing ratios of organic species in the up- per troposphere relative to background conditions. Several dramatic events were observed in which isoprene and its ox- idation products were detected at hundreds of pptv at alti- tudes higher than 8 km. Two events are studied in detail us- ing detailed experimental data and the NASA Langley Re- search Center (LaRC) box model. One event had no light- ning NOx (NO + NO2) associated with it and the other had substantial lightning NOx (LNOx > 1 ppbv). When convec- tive storms transport isoprene from the boundary layer to the upper troposphere and no LNOx is present, OH is re- duced due to scavenging by isoprene, which serves to slow the chemistry, resulting in longer lifetimes for species that react with OH. Ozone and PAN production is minimal in this case. In the case where isoprene is convected and LNOx is present, there is a large effect on the expected ensuing chemistry: isoprene exerts a dominant impact on HOx and nitrogen-containing species; the relative contribution from other species to HOx, such as peroxides, is insignificant. The isoprene reacts quickly, resulting in primary and secondary products, including formaldehyde and methyl glyoxal. The model predicts enhanced production of alkyl nitrates (ANs) and peroxyacyl nitrate compounds (PANs). PANs persist be- cause of the cold temperatures of the upper troposphere re- sulting in a large change in the NOx mixing ratios which, in turn, has a large impact on the HOx chemistry. Ozone pro- duction is substantial during the first few hours following the convection to the UT, resulting in a net gain of approximately 10 ppbv compared to the modeled scenario in which LNOx is present but no isoprene is present aloft.
Matricellular Protein Periostin Mediates Intestinal Inflammation through the Activation of Nuclear Factor κB Signaling

Periostin is a matricellular protein that interacts with various integrin molecules on the cell surface. Although periostin is expressed in inflamed colonic mucosa, its role in the regulation of intestinal inflammation remains unclear. We investigated the role of periostin in intestinal inflammation using Postn-deficient (Postn-/-) mice. Intestinal epithelial cells (IECs) were transfected by Postn small interfering RNAs. Periostin expression was determined in colon tissue samples from ulcerative colitis (UC) patients. Oral administration of dextran sulfate sodium (DSS) or rectal administration of trinitrobenzene sulfonic acid, induced severe colitis in wild-type mice, but not in Postn-/- mice. Administration of recombinant periostin induced colitis in Postn-/- mice. The periostin neutralizing-antibody ameliorated the severity of colitis in DSS-treated wild-type mice. Silencing of Postn inhibited inteleukin (IL)-8 mRNA expression and NF-κB DNA-binding activity in IECs. Tumor necrosis factor (TNF)-α upregulated mRNA expression of Postn in IECs, and recombinant periostin strongly enhanced IL-8 expression in combination with TNF-α, which was suppressed by an antibody against integrin αv (CD51). Periostin and CD51 were expressed at significantly higher levels in UC patients than in controls. Periostin mediates intestinal inflammation through the activation of NF-κB signaling, which suggests that periostin is a potential therapeutic target for inflammatory bowel disease.
The effect of interfering ions on search algorithm performance for electron‐transfer dissociation data

Collision‐activated dissociation and electron‐transfer dissociation (ETD) each produce spectra containing unique features. Though several database search algorithms (e.g. SEQUEST, MASCOT, and Open Mass Spectrometry Search Algorithm) have been modified to search ETD data, this consists chiefly of the ability to search for c‐ and z•‐ions; additional ETD‐specific features are often unaccounted for and may hinder identification. Removal of these features via spectral processing increased total search sensitivity by ∼20% for both human and yeast data sets; unique peptide identifications increased by ∼17% for the yeast data sets and ∼16% for the human data set.
Effective computation of biased quantiles over data streams

Skew is prevalent in many data sources such as IP traffic streams. To continually summarize the distribution of such data, a high-biased set of quantiles (e.g., 50th, 90th and 99th percentiles) with finer error guarantees at higher ranks (e.g., errors of 5, 1 and 0.1 percent, respectively) is more useful than uniformly distributed quantiles (e.g., 25th, 50th and 75th percentiles) with uniform error guarantees. In this paper, we address the following two problems. First, can we compute quantiles with finer error guarantees for the higher ranks of the data distribution effectively using less space and computation time than computing all quantiles uniformly at the finest error? Second, if specific quantiles and their error bounds are requested a priori, can the necessary space usage and computation time be reduced? We answer both questions in the affirmative by formalizing them as the "high-biased" and the "targeted" quantiles problems, respectively, and presenting algorithms with provable guarantees, that perform significantly better than previously known solutions for these problems. We implemented our algorithms in the Gigascope data stream management system, and evaluated alternate approaches for maintaining the relevant summary structures. Our experimental results on real and synthetic IP data streams complement our theoretical analyses, and highlight the importance of lightweight, non-blocking implementations when maintaining summary structures over highspeed data streams.
Integrating neuroinformatics tools in TheVirtualBrain

TheVirtualBrain (TVB) is a neuroinformatics Python package representing the convergence of clinical, systems, and theoretical neuroscience in the analysis, visualization and modeling of neural and neuroimaging dynamics. TVB is composed of a flexible simulator for neural dynamics measured across scales from local populations to large-scale dynamics measured by electroencephalography (EEG), magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI), and core analytic and visualization functions, all accessible through a web browser user interface. A datatype system modeling neuroscientific data ties together these pieces with persistent data storage, based on a combination of SQL and HDF5. These datatypes combine with adapters allowing TVB to integrate other algorithms or computational systems. TVB provides infrastructure for multiple projects and multiple users, possibly participating under multiple roles. For example, a clinician might import patient data to identify several potential lesion points in the patient's connectome. A modeler, working on the same project, tests these points for viability through whole brain simulation, based on the patient's connectome, and subsequent analysis of dynamical features. TVB also drives research forward: the simulator itself represents the culmination of several simulation frameworks in the modeling literature. The availability of the numerical methods, set of neural mass models and forward solutions allows for the construction of a wide range of brain-scale simulation scenarios. This paper briefly outlines the history and motivation for TVB, describing the framework and simulator, giving usage examples in the web UI and Python scripting.
Optimized Schwarz Methods

Optimized Schwarz methods are a new class of Schwarz methods with greatly enhanced convergence properties. They converge uniformly faster than classical Schwarz methods and their convergence rates dare asymptotically much better than the convergence rates of classical Schwarz methods if the overlap is of the order of the mesh parameter, which is often the case in practical applications. They achieve this performance by using new transmission conditions between subdomains which greatly enhance the information exchange between subdomains and are motivated by the physics of the underlying problem. We analyze in this paper these new methods for symmetric positive definite problems and show their relation to other modern domain decomposition methods like the new Finite Element Tearing and Interconnect (FETI) variants.
Change propagation in decentralized composite web services

Every company wants to improve the way it does business, or produce things more efficiently, and make greater profit. Therefore, business processes have become subject to evolutionary changes, which in turn increase the need for an efficient change support. In this sense, many researches were conducted to deal with business process adaptation to changes. The latter may result in the restructuring of the whole or a part of the process. Most of the proposed approaches focus on adaptation to changes in centralized processes. In sharp contrast to these works, our operation of change adaptation that we present in this paper, concerns decentralized orchestrations. Indeed, many recent approaches were proposed to decompose a composite web service into small partitions. Since the activities, the control and data flows are distributed over these partitions, it becomes difficult to specify the changes directly. Moreover, changing a derived partition may affect the way it interacts with others. In order to overcome these deficiencies, we propose a design-time methodology to support changes in decentralized business processes. We mainly demonstrate how to propagate the changes made on a centralized specification of composite web service to its resulting decentralized sub-processes.
Blind Evaluation for Thai Search Engines

This paper compares the effectiveness of two different Thai search engines by using a blind evaluation. The probabilistic-based dictionary-less search engine is evaluated against the traditional word-based indexing method. The web documents from 12 Thai newspaper web sites consisting of 83,453 documents are used as the test collection. The relevance judgment is conducted on the first five returned results from each system. The evaluation process is completely blind. That is, the retrieved documents from both systems are shown to the judges without any information about thesearch techniques. Statistical testing shows that the dictionary-less approach is better than the word-based indexingapproach in terms of the number of found documents and the number of relevance documents.
What Users Actually Do in a Social Tagging System

Social tagging systems have established themselves as an important part in today’s Web and have attracted the interest of our research community in a variety of investigations. Henceforth, several aspects of social tagging systems have been discussed and assumptions have emerged on which our community builds their work. Yet, testing such assumptions has been difficult due to the absence of suitable usage data in the past. In this work, we thoroughly investigate and evaluate four aspects about tagging systems, covering social interaction, retrieval of posted resources, the importance of the three different types of entities, users, resources, and tags, as well as connections between these entities’ popularity in posted and in requested content. For that purpose, we examine live server log data gathered from the real-world, public social tagging system BibSonomy. Our empirical results paint a mixed picture about the four aspects. Although typical assumptions hold to a certain extent for some, other aspects need to be reflected in a very critical light. Our observations have implications for the understanding of social tagging systems and the way they are used on the Web. We make the dataset used in this work available to other researchers.