Miracle-dz/UniFAR-FTUs huggingface dataset:
Processing the Outcomes of Characters’ Actions: The Impacts of Character Goals and Situational Context

ABSTRACT This study was conducted to investigate two factors that affect the processing of the outcomes of intentional actions. Participants read three-sentence stories that varied the presence of an explicit goal and the semantic association between the outcome and its situational context (i.e., physical or virtual location). The ease of processing outcomes (as measured by sentence reading times) was facilitated by having an explicitly stated goal (e.g., “X wanted a beer”) that causally explained why an action (e.g., “X went to a bar”) took place and by a high degree of contextual constraint between the action (e.g., “X went to a bar” as opposed to “X went to a restaurant”) and the outcome (e.g., “X got a beer”). There was no evidence that the two factors interacted. These results suggest that readers monitor, in parallel, the associations of actions with the intentions of a character and the situational context in which those actions occur.
Imatinib mesylate causes genome-wide transcriptional changes in systemic sclerosis fibroblasts in vitro.

OBJECTIVES Systemic sclerosis (SSc) is a heterogeneous multifactorial disease dominated by progressive skin and internal organ fibrosis that is driven in part by transforming growth factor-beta (TGF-β). An important downstream target of TGF-β is the Abelson (c-Abl) tyrosine kinase, and its inhibition by imatinib mesylate (Gleevec) attenuates fibrosis in mice. Here we examined the effect of c-Abl activation and blockade in explanted healthy control and SSc fibroblasts. METHODS Skin biopsies and explanted fibroblasts from healthy subjects and patients with SSc were studied. Changes in genome-wide expression patterns in imatinib-treated control and SSc fibroblasts were analysed by DNA microarray. RESULTS Treatment of control fibroblasts with TGF-β resulted in activation of c-Abl and stimulation of fibrotic gene expression that was prevented by imatinib. Moreover, imatinib reduced basal collagen gene expression in SSc but not control fibroblasts. No significant differences in tissue levels of c-Abl and phospho-c-Abl were detected between SSc and control skin biopsies. In vitro, imatinib induced dramatic changes in the expression of genes involved in fibrosis, cardiovascular disease, inflammation, and lipid and cholesterol metabolism. Remarkably, of the 587-imatinib-responsive genes, 91% showed significant change in SSc fibroblasts, but only 12% in control fibroblasts. CONCLUSIONS c-Abl plays a key role in fibrotic responses. Imatinib treatment results in dramatic changes in gene expression in SSc fibroblasts but has only modest effects in control fibroblasts. These data provide novel insights into the mechanisms underlying the antifibrotic effect of imatinib in SSc.
Controlling the Intelligibility of Referring Expressions in Dialogue

If speakers articulate clearly enough to meet the perceptual needs of their listeners, clarity should depend on what listeners know about (listener-Given) rather than on what speakers know about (speaker-Given). For words excerpted from spontaneous speech, however, intelligibility to naive adult listeners showed only effects of the speaker's knowledge. Words introducing labeled map landmarks to two successive listeners were less clear on repetition even though the second listener had not heard the original mention (Experiment 1). Repeated mentions became less clear even after the listener reported inability to see the landmark (Experiment 2). Speakers were affected by what they had heard listeners mention: Intelligibility fell equally in coreferential repetitions across and within speakers (Experiment 3), whether or not the repeater could see the referent (Experiment 4). The results are explained via fast priming processes dependent on the speaker's knowledge and slow, optional processes drawing inferences about the listener's.
The Importance of Mouse Models to Define Immunovirologic Determinants of Progressive Multifocal Leukoencephalopathy

Progressive multifocal leukoencephalopathy (PML) is a severely debilitating and often fatal demyelinating disease of the central nervous system (CNS) in immunosuppressed individuals caused by JC polyomavirus (JCV), a ubiquitous human pathogen. Demyelination results from lytically infected oligodendrocytes, whose clearance is impaired in the setting of depressed JCV-specific T cell-mediated CNS surveillance. Although mutations in the viral capsid and genomic rearrangements in the viral non-coding region appear to set the stage for PML in the immunosuppressed population, mechanisms of demyelination and CNS antiviral immunity are poorly understood in large part due to absence of a tractable animal model that mimics PML neuropathology in humans. Early studies using mouse polyomavirus (MPyV) in T cell-deficient mice demonstrated productive viral replication in the CNS and demyelination; however, these findings were confounded by spinal cord compression by virus-induced vertebral bone tumors. Here, we review current literature regarding animal models of PML, focusing on current trends in antiviral T cell immunity in non-lymphoid organs, including the CNS. Advances in our understanding of polyomavirus lifecycles, viral and host determinants of persistent infection, and T cell-mediated immunity to viral infections in the CNS warrant revisiting polyomavirus CNS infection in the mouse as a bona fide animal model for JCV-PML.
On the influence of self-similarity on optical burst switching traffic

In this paper we provide a characterization of OBS traffic (burst size, interarrival time and scaling behavior) when the input traffic is long-range dependent The analysis shows that the influence of self-similarity on blocking probability is negligible, since the arrival process can be assumed to be Poisson in the timescale of interest for burst blocking. However, the impact for optical buffer dimensioning is significant. On the other hand, the scaling region is shifted to larger timescales while traffic variability at low timescales is increased. These findings serve to accurately dimension number of output ports and optical buffers in OBS routers when the incoming traffic comes from a large population of Internet users.
OPTIMUM SIGNATURE SEQUENCE SETS FOR ASYNCHRONOUS CDMA SYSTEMS

In this paper we characterize the user capacity i e the maximum number of supportable users at a common SIR target level for a xed processing gain of a single cell symbol asynchronous CDMA system Based on the delay pro le of the users we identify a class of optimum signature sequences that achieve a lower bound on the total squared asynchronous correlation TSAC among the users When the users signatures achieve this lower bound the user capacity of a single cell asynchronous CDMA system becomes the same as that of a single cell synchronous CDMA system that is there is no loss in user capacity due to asynchrony Further when the optimum signature sequences are used the users received powers are all equal and the M shot MMSE receiver lters turn out to be scaled matched lters That is the maximum user capacity is achieved by observing only one symbol interval of the received signal and using single user matched lters in that interval It is a signi cant open question whether these optimal sequence sets exist for all delay pro les However we present iterative and distributed signature adaptation algorithms which when executed sequentially by all of the users appear to converge to these optimum signature sequences
Apolipoprotein E genotype and response of carbon monoxide poisoning to hyperbaric oxygen treatment.

RATIONALE Hyperbaric oxygen (HBO2) reduced the incidence of cognitive sequelae 6 weeks after carbon monoxide (CO) poisoning compared with normobaric oxygen (NBO2). The apolipoprotein (APOE) epsilon4 allele predicts unfavorable neurologic outcome after brain injury and stroke. OBJECTIVES To assess the effects of the epsilon4 allele on 6-week cognitive sequelae after CO poisoning. METHODS We tested APOE genotypes in 86 of 152 CO-poisoned patients from our randomized trial. Logistic regression was used to control for risk factors while testing for effects with the epsilon4 allele or interactions with epsilon4 and treatment on 6-week and 6- and 12-month cognitive sequelae. MEASUREMENTS AND MAIN RESULTS We enrolled 86 patients: 44 received HBO2 and 42 NBO2 therapy. A total of 31 (36%) patients had at least one epsilon4 allele. Six-week cognitive sequelae rates for patients treated with HBO2 and NBO2, respectively: epsilon4 allele absent, 11% (3/27) and 43% (12/28); epsilon4 allele present, 35% (6/17) and 29% (4/14). The epsilon4 allele was not associated with 6-week cognitive sequelae, 27% (15/55) without and 32% (10/31) with the epsilon4 allele (P = 0.323). The interaction between the epsilon4 allele and treatment was significantly associated with 6-week cognitive sequelae (P = 0.048). The interaction between the epsilon4 allele and treatment was not associated with 6- and 12-month cognitive sequelae. CONCLUSIONS HBO2 therapy reduces cognitive sequelae after CO poisoning in the absence of the epsilon4 allele. Because apolipoprotein genotype is unknown at the time of poisoning, we recommend that patients with acute CO poisoning receive HBO2.
Evaluating knowledge transfer and zero-shot learning in a large-scale setting

While knowledge transfer (KT) between object classes has been accepted as a promising route towards scalable recognition, most experimental KT studies are surprisingly limited in the number of object classes considered. To support claims of KT w.r. t. scalability we thus advocate to evaluate KT in a large-scale setting. To this end, we provide an extensive evaluation of three popular approaches to KT on a recently proposed large-scale data set, the ImageNet Large Scale Visual Recognition Competition 2010 data set. In a first setting they are directly compared to one-vs-all classification often neglected in KT papers and in a second setting we evaluate their ability to enable zero-shot learning. While none of the KT methods can improve over one-vs-all classification they prove valuable for zero-shot learning, especially hierarchical and direct similarity based KT. We also propose and describe several extensions of the evaluated approaches that are necessary for this large-scale study.
Activism across the lifecourse: Circumstantial, dormant and embedded activisms

Focusing on the relationship between activism, the individual and the lifecourse, this paper argues for the importance of conceptualising activism as a dynamic temporal, as well as spatial, process. Transferring Nancy Worth's understanding of youth transitions ‘as becoming’ onto activism, and using empirical research with adults who were involved in organisationally mediated activism as young people, three states of activism are offered and considered: circumstantial, dormant and embedded. Firstly activism that is circumstantial, important in the moment, is shown to play a significant role for young people in making possible multiple potential futures. Exploring these connections between the past and future unsettles the recent (over)emphasis in the studies of children and young people and P/politics, of the ‘here and now’. Secondly, it is argued that when involvement in organisationally mediated activism has finished, these experiences of activism have not ended but are dormant. They may be rejuvenated and curated at a different position in the lifecourse or following a new moment of conscientisation. Thirdly, contributing to a growing body of literature within activist geographies, instances where activism has become embedded in everyday spaces are examined. Complex transitions to adulthood are suggested to contribute to the nature of activism in these spaces. Going beyond the documentation of small-scale activisms, these activisms are also presented as entwined with other scales.
Nitric oxide metabolites in the lumbosacral spinal cord interstice and cerebrospinal fluid in female rats with acute cyclophosphamide-induced cystitis. An in vivo microdialysis study

ABSTRACT Objective: To determine the concentration of nitrate/nitrite in the cerebrospinal fluid and in the dorsal horn interstice of the L6-S1 spinal cord boundary in rats with or without cystitis induced by cyclophosphamide. Methods: All experiments were conducted using Wistar female rats. A microdialysis probe was implanted in the subarachnoid space or in the spinal cord tissue at the L6-S1 segments (confirmed histologically). Two days later, the microdialysis probe was perfused with artificial cerebrospinal fluid, containing or not NGmonomethyl-L-arginine. Samples were collected every 15 minutes and kept at −20°C. Nitrite/nitrate concentrations were determined by chemiluminescence. Results: In normal animals, the mean values of nitrite/nitrate concentrations in the first microdialysate sample of the cerebrospinal fluid and of the spinal cord interstice were similar (482.5±90.2pmol/75μL, n=20, and 505.7±11.5pmol/75μL, n=6, respectively), whereas, in the samples from rats with cystitis, these values were significantly greater (955.5±66.3pmol/75μL, n=8, and 926.5±131.7pmol/75μL, n=11, respectively). In both groups, NGmonomethyl-L- arginine caused a significant reduction in the nitrite/nitrate concentration. Interestingly, the maximal reduction of nitrite/nitrate concentration caused by NG-monomethyl-L- arginine was no greater than 30% of the initial values. Conclusions: These results constitute the first demonstration that nitrite/nitrate concentrations in the cerebrospinal fluid and spinal cord interstice are elevated between 20- and 22 hours after cyclophosphamide-induced cystitis, and indicate that cystitis is associated with changes in the production of nitric oxide in the spinal cord segments, where most primary bladder afferents end.
Static shape and vibration control of flexible payloads with applications to robotic assembly

This paper addresses the simultaneous control of vibration and static shape deformation of arbitrarily shaped thin-walled flexible payloads. During robotic assembly of these thin-walled parts, gravity and inertial forces acting on the parts may induce both static shape deformation and vibrations in the part sufficiently large that accurate and high speed assembly of these parts is hindered. Static deformations, which arise due to deformation of the part caused by its own weight under the influence of gravity, lead to misalignment of mating points of the parts. Unwanted vibrations, arising from inertial forces acting on the thin-walled parts as they are positioned for assembly, must damp out before parts can be mated, further hindering the process. In this work, a smart gripper with actuated contact points to grasp the flexible thin-walled parts is proposed to solve this problem. The smart gripper is capable of both part reshaping and active damping of unwanted vibrations of the part. It is fixed to a robotic manipulator and is comprised of multiple linearly actuated fingers with laser-based noncontact proximity sensors, and associated signal processing and controllers. In this paper, a simultaneous vibration and static shape controller is developed. The proposed controller is a composite modal controller in conjunction with a quasi-static modal filter and a bias Kalman filter, which is synthesized based on the reduced-order dynamic model of the flexible payload. A near industrial practice demonstration of the feasibility of the proposed approach is carried out using a proof-of-concept smart gripper to manipulate an automotive fender. Experimental results indicate that unwanted vibrations are successfully damped out, allowing faster cycle times for an assembly process, and static shape deformations are corrected, allowing accurate positioning of parts for assembly.
Performance Evaluation of SVM and K-Nearest Neighbor Algorithm over Medical Data set

this age of computer science each and every thing becomes intelligent and perform task as human. For that purpose there are various tools, techniques and methods are proposed. Support vector machine is a model for statistics and computer science, to perform supervised learning, methods that are used to make analysis of data and recognize patterns. SVM is mostly used for classification and regression analysis. And in the same way k-nearest neighbor algorithm is a classification algorithm used to classify data using training examples. In this paper we use SVM and KNN algorithm to classify data and get prediction (find hidden patterns) for target. Here we use medical patients nominal data to classify and discover the data pattern to predict future disease, Uses data mining which is use to classify text analysis in future. KeywordsKNN, Patterns, Analysis, Classification.
A Variational Bayes Framework for Sparse Adaptive Estimation

Recently, a number of mostly l1-norm regularized least-squares-type deterministic algorithms have been proposed to address the problem of sparse adaptive signal estimation and system identification. From a Bayesian perspective, this task is equivalent to maximum a posteriori probability estimation under a sparsity promoting heavy-tailed prior for the parameters of interest. Following a different approach, this paper develops a unifying framework of sparse variational Bayes algorithms that employ heavy-tailed priors in conjugate hierarchical form to facilitate posterior inference. The resulting fully automated variational schemes are first presented in a batch iterative form. Then, it is shown that by properly exploiting the structure of the batch estimation task, new sparse adaptive variational Bayes algorithms can be derived, which have the ability to impose and track sparsity during real-time processing in a time-varying environment. The most important feature of the proposed algorithms is that they completely eliminate the need for computationally costly parameter fine-tuning, a necessary ingredient of sparse adaptive deterministic algorithms. Extensive simulation results are provided to demonstrate the effectiveness of the new sparse adaptive variational Bayes algorithms against state-of-the-art deterministic techniques for adaptive channel estimation. The results show that the proposed algorithms are numerically robust and exhibit in general superior estimation performance compared to their deterministic counterparts.
A Defensin from the Model Beetle Tribolium castaneum Acts Synergistically with Telavancin and Daptomycin against Multidrug Resistant Staphylococcus aureus

The red flour beetle Tribolium castaneum is a common insect pest and has been established as a model beetle to study insect development and immunity. This study demonstrates that defensin 1 from T. castaneum displays in vitro and in vivo antimicrobial activity against drug resistant Staphylococcus aureus strains. The minimum inhibitory concentration (MIC) of defensin 1 against 11 reference and clinical staphylococcal isolates was between 16–64 μg/ml. The putative mode of action of the defensin peptide is disruption of the bacterial cell membrane. The antibacterial activity of defensin 1 was attenuated by salt concentrations of 1.56 mM and 25 mM for NaCl and CaCl2 respectively. Treatment of defensin 1 with the reducing agent dithiothreitol (DTT) at concentrations 1.56 to 3.13 mM abolished the antimicrobial activity of the peptide. In the presence of subinhibitory concentrations of antibiotics that also target the bacterial cell envelope such as telavancin and daptomycin, the MIC of the peptide was as low as 1 μg/ml. Moreover, when tested against an S. aureus strain that was defective in D-alanylation of the cell wall, the MIC of the peptide was 0.5 μg/ml. Defensin 1 exhibited no toxicity against human erythrocytes even at 400 μg/ml. The in vivo activity of the peptide was validated in a Caenorhabditis elegans-MRSA liquid infection assay. These results suggest that defensin 1 behaves similarly to other cationic AMPs in its mode of action against S. aureus and that the activity of the peptide can be enhanced in combination with other antibiotics with similar modes of action or with compounds that have the ability to decrease D-alanylation of the bacterial cell wall.
Does Bipolar Disorder Exist in Children? A Selected Review

Although there is increasing recognition that a substantial proportion of patients with bipolar disorder (BD) experience an onset of illness in adolescence, significant controversy remains over the validity of the diagnosis in very young children. In careful studies of adult patients dating from Kraepelin, first mood episodes not uncommonly occurred during adolescence. Some of these early-onset patients experienced subthreshold mood disturbances or predisposing temperaments earlier in childhood. Earlier onsets of BD have been reported in more recent clinical and community samples of children. Several factors possibly contributed to these earlier onsets, including exposure to psychotropics, bias in favour of a mood rather than a psychotic diagnosis, and recognition of softer-spectrum BDs. However, the validity of the diagnosis of BD in impulsive, irritable, labile, or behaviourally dysregulated children remains to be proven. Studies of high-risk children of well-characterized parents with BD have demonstrated that BD most often debuts as a depressive episode in mid to late adolescence and that activated episodes are rare prior to age 12 years. Some children manifest antecedent nonspecific psychopathology in early childhood. Therefore, as currently diagnosed, BD does not manifest as such typically until at least adolescence.
The Effect of Dissolved Organic Matter on Zeta Potential During the Coagulation Process

During the municipal wastewater reclamation process, the Zeta potential presented significant difference between the particle in the surface water and in the secondary effluent of WWTP with the increasing of PAC. Dissolved organic matter(DOM) in effluent from conventional sewage treatment plant was isolated into five classes using adsorbent resins: hydrophobic bases(HoB), hydrophobic acids(HoA);hydrophilic bases(HiB), hydrophilic acids(HiA) and hydrophilic neutrals(HiN). The Zeta potential of different organic fractions was examined when PAC was injected. The results showed that the concentration and composition of DOM were main reasons for the Zeta potential difference between surface water and secondary effluent during the coagulation process. And, hydrophobic organic was the main component leading to the slow change on Zeta potential.