Miracle-dz/UniFAR-FTUs huggingface dataset:
Intrapleural delivery of MSCs attenuates acute lung injury by paracrine/endocrine mechanism

Two different repair mechanisms of mesenchymal stem cells (MSCs) are suggested to participate in the repair of acute lung injury (ALI): (i) Cell engraftment mechanism, (ii) Paracrine/endocrine mechanism. However, the exact roles they play in the repair remain unclear. The aim of the study was to evaluate the role of paracrine/endocrine mechanism using a novel intrapleural delivery method of MSCs. Either 1 × 106 MSCs in 300 μl of PBS or 300 μl PBS alone were intrapleurally injected into rats with endotoxin‐induced ALI. On days 1, 3 or 7 after injections, samples of lung tissues and bronchoalveolar lavage fluid (BALF) were collected from each rat for assessment of lung injury, biochemical analysis and histology. The distribution of MSCs was also traced by labelling the cells with 4′,6‐diamidino‐2‐phenylindole dihydrochloride (DAPI). MSCs intrapleural injection significantly improved LPS‐induced lung histopathology compared with PBS‐treated group at day 3. There was also a significant decrease in total cell counts and protein concentration in BALF at day 7 in the MSCs ‐treated rats compared to PBS control group. Tracking the DAPI‐marked MSCs showed that there were no exotic MSCs in the lung parenchyma. MSCs administration resulted in a down‐regulation of pro‐inflammatory response to endotoxin by reducing TNF‐α both in the BALF and in the lung, while up‐regulating the anti‐inflammatory cytokine IL‐10 in the lung. In conclusion, treatment with intrapleural MSCs administration markedly attenuates the severity of endotoxin‐induced ALI. This role is mediated by paracrine/endocrine repair mechanism of MSCs rather than by the cell engraftment mechanism.
Informing design by recording tangible interaction

Evaluating tangible user interfaces is challenging. Despite the wealth of research describing the design of tangible systems, there is little empirical evidence highlighting the benefits they can confer. This paper presents a toolkit that logs the manipulation of tangible objects as a step towards creating specific empirical methods for the study of tangible systems. The paper argues that the data derived from toolkit can be used in three ways. Firstly: to compare tangible interaction with other interaction paradigms. Secondly: to compare among different tangible interfaces performing the same tasks. Thirdly: via integration into a structured design process. This paper focuses on this last topic and discusses how detailed data regarding object use the data could be integrated into classifications and frameworks such as the Shaer's et al's TAC paradigm.
A Novel Tensor RPCA approach for Background Subtraction from Compressive Measurements

Background subtraction has been a fundamental and widely studied task in video analysis, with a wide range of applications in video surveillance, teleconferencing and 3D modeling. Recently, motivated by compressive imaging, background subtraction from compressive measurements (BSCM) is becoming an active research task in video surveillance. In this paper, we propose a novel tensor-based robust PCA (TenRPCA) approach for BSCM by decomposing video frames into backgrounds with spatial-temporal correlations and foregrounds with spatio-temporal continuity in a tensor framework. In this approach, we use 3D total variation to enhance the spatiotemporal continuity of foregrounds, and Tucker decomposition to model the spatio-temporal correlations of video background. Based on this idea, we design a basic tensor RPCA model over the video frames, dubbed holistic TenRPCA model (HTenRPCA). To characterize the correlations among the groups of similar 3D patches of video background, we further design a patch-group-based tensor RPCA model (PG-TenRPCA) by joint tensor Tucker decompositions of 3D patch groups for modeling the video background. Efficient algorithms using alternating direction method of multipliers (ADMM) are developed to solve the proposed models. Extensive experiments on simulated and real-world videos demonstrate the superiority of the proposed models over the existing state-of-the-art approaches.
Molecular phylogenetic position of the New Zealand sentinel crab, Macrophthalmus ( Hemiplax ) hirtipes (Jacquinot, in Hombron & Jacquinot, 1846) (Decapoda, Brachyura, Macrophthalmidae)

The systematic position of the New Zealand sentinel crab Macrophthalmus ( Hemiplax ) hirtipes (Jacquinot, in Hombron & Jacquinot, 1846) has been questioned because the zoeal morphology is incongruent with that of other species assigned to the genus. A molecular phylogeny based on the mitochondrial large subunit (16S) rRNA gene indicates M. hirtipes is distinct from other macrophthalmid species, and found to be more closely related to the New Zealand varunids Austrohelice crassa, Hemigrapsus crenulatus , and Hemigrapsus sexdentatus . This indicates that the genus Macrophthalmus Desmarest, 1823 needs to be revised. La position systematique du crabe sentinelle Macrophthalmus ( Hemiplax ) hirtipes (Jacquinot, in Hombron & Jacquinot, 1846) a ete mise en doute car la morphologie de la zoe n'est pas satisfaisante par rapport aux autres especes de ce genre. Une phylogenie moleculaire basee sur L'ARNr de la grande sous-unite (16S) mitochondriale indique que M. hirtipes est distinct des autres especes macrophtalmides, et est plus proche des varunides de Nouvelle Zelande Austrohelice crassa, Hemigrapsus crenulatus et Hemigrapsus sexdentatus . Ceci indique que le genre Macrophthalmus Desmarest, 1823 doit etre revise.
United Kingdom “top 5” pop music lyrics

The present research conducted a computerised analysis of the content of all lyrics from the United Kingdom’s weekly top 5 singles sales charts (Study 1, 1962–2011), and considered their macroeconomic correlates (Study 2, 1960–2011). Study 1 showed that coverage of interpersonal relationships consistently reflected a self-centred and unsophisticated approach; coverage of violence featured predominantly anti-authoritarian denial rather than overt depictions; and more recent lyrics were more stimulating. Study 2 showed no evidence that variations in lyrical optimism predicted future variations in economic optimism and subsequently Gross Domestic Product; but, consistent with the environmental security hypothesis, economic turbulence (defined as volatility in the closing price of the London Stock Exchange) was associated with the later popularity of lyrics concerning certainty and succour. These findings are discussed in terms of the advantages and limitations of computerised coding of lyrics.
A Fault Injection Method for Testing Dependable Web Service Systems

Testing Web services performance and their Fault Tolerance Mechanisms (FTMs) are crucial for the development of today's applications. Testing the performance and FTMs of composed service systems is hard to measure at design time because service instability is often caused by the nature of the network. Using a real internet environment for testing is difficult to set up and control. We have developed a fault injection toolkit that emulates a WAN within a LAN environment between composed service components and offers full control over the emulated environments in addition to the ability to inject network-related and application specific faults. The tool also generates background workloads on the tested system for producing more realistic results. We describe an experiment that has been carried out to test the impact of fault tolerance protocols deployed at a service client by using our fault injection toolkit.
Moving Type Detection without Time Information

Today location technologies are integrated into many devices enabling location-based services. Movement data recorded with these devices can be uploaded to web sites and shared with others. Movement data can be organized using keywords and semantic tags, e.g. walking and running. Our main goal is to automatically classify movement data as walking, cycling or driving. In contrast to other work we use real world GPS data without time information. Users delete time information to protect their privacy. Over a period of two months we collected movement data from a popular track sharing platform and classified the GPS tracks using Decision Tree, Naive Bayes, Support Vector Machine and Naive Bayes Tree. Our results show that users can expect reasonable results from tag suggestion services detecting moving type even without time information. A second result of our work indicates that angle-based features are insignificant for classification using real world GPS tracks. Distance was the only significant feature in our study.
AOAB: automated optimization algorithm benchmarking

In this paper we present AOAB, the Automated Optimization Algorithm Benchmarking system. AOAB can be used to automatically conduct experiments with numerical optimization algorithms by applying them to different benchmarks with different parameter settings. Based on the results, AOAB can automatically perform comparisons between different algorithms and settings. It can aid the researcher to identify trends for good parameter settings and to find which algorithms are suitable for which type of problem. We introduce the system structure of AOAB (the server and the graphical client interface), define the way in which optimizers and benchmark functions can be implemented for the use in AOAB, and conduct an illustrative example experiment with our system: a comparison between Random Search and two Hill Climbers.
An Expectation-Maximization Algorithm to Compute a Stochastic Factorization From Data

When a transition probability matrix is represented as the product of two stochastic matrices, swapping the factors of the multiplication yields another transition matrix that retains some fundamental characteristics of the original. Since the new matrix can be much smaller than its precursor, replacing the former for the latter can lead to significant savings in terms of computational effort. This strategy, dubbed the "stochastic-factorization trick," can be used to compute the stationary distribution of a Markov chain, to determine the fundamental matrix of an absorbing chain, and to compute a decision policy via dynamic programming or reinforcement learning. In this paper we show that the stochastic-factorization trick can also provide benefits in terms of the number of samples needed to estimate a transition matrix. We introduce a probabilistic interpretation of a stochastic factorization and build on the resulting model to develop an algorithm to compute the factorization directly from data. If the transition matrix can be well approximated by a low-order stochastic factorization, estimating its factors instead of the original matrix reduces significantly the number of parameters to be estimated. Thus, when compared to estimating the transition matrix directly via maximum likelihood, the proposed method is able to compute approximations of roughly the same quality using less data. We illustrate the effectiveness of the proposed algorithm by using it to help a reinforcement learning agent learn how to play the game of blackjack.
Magnetic Fe3O4-Based Sandwich-Type Biosensor Using Modified Gold Nanoparticles as Colorimetric Probes for the Detection of Dopamine

In this work, we designed a visual biosensor for dopamine (DA) detection using magnetic Fe3O4 particles and dithiobis(sulfosuccinimidylpropionate)-modified gold nanoparticles (DTSSP-AuNPs) as the recognition elements. Specifically, DA molecules were assembled onto the surface of DTSSP-AuNPs via the amine coupling reaction between the amino group of DA and activated carboxyl group of DTSSP. Accordingly, DA-anchored DTSSP-AuNPs were captured by Fe3O4 through the interaction of catechol and iron. In a magnetic field, the formed Fe3O4-DA-DTSSP-AuNPs conjugates were easily removed from the solution, leading to fading of the AuNPs suspension and decrease of the UV/Vis signal. As a result, a detection limit of 10 nM for DA was achieved. The theoretical simplicity and high selectivity demonstrated that the sandwich-type strategy based on Fe3O4 and AuNPs would lead to many colorimetric detection applications in clinical study by rationally designing the surface chemistry of AuNPs and Fe3O4.
Jumping to conclusions in delusional and non-delusional schizophrenic patients.

OBJECTIVE Several studies have provided evidence for the claim that a subgroup of (schizophrenic) patients with current delusions share a jumping to conclusions (JTC) bias. The primary aim of the present study was to investigate whether currently deluded and non-deluded schizophrenic patients perform differently on three tasks tapping probabilistic reasoning. METHOD Probabilistic reasoning was assessed in 31 schizophrenic patients, 28 psychiatric controls, and 17 healthy controls. In addition to the traditional draws to decision procedure, we employed two tasks for which participants had to judge, at each stage, the likelihood that beads come from either container (graded estimates procedure). Reaction times were recorded for the graded estimates procedure. RESULTS A JTC bias was displayed by 42% of the schizophrenic patients in the draws to decision condition, while 7% of the psychiatric patients and none of the healthy controls reached a decision after only one bead. A similar pattern of results was observed for the graded estimates procedure. This bias was more pronounced in deluded schizophrenic patients, although currently non-deluded patients also showed evidence for earlier decisions. A bias to over-adjust when confronted with potentially disconfirmatory evidence was confined to deluded schizophrenic participants. There was also evidence for an increase in JTC in the deluded group over the course of the tasks. No substantial group differences occurred with respect to reaction time parameters indicating that results are not attributable to impulsivity. DISCUSSION The findings provide further evidence for state and trait characteristics of abnormal reasoning in paranoid schizophrenia. Results are discussed in light of several competing explanations for JTC in schizophrenia.
A Simple Bayesian Modelling Approach to Event Extraction from Twitter

With the proliferation of social media sites, social streams have proven to contain the most up-to-date information on current events. Therefore, it is crucial to extract events from the social streams such as tweets. However, it is not straightforward to adapt the existing event extraction systems since texts in social media are fragmented and noisy. In this paper we propose a simple and yet effective Bayesian model, called Latent Event Model (LEM), to extract structured representation of events from social media. LEM is fully unsupervised and does not require annotated data for training. We evaluate LEM on a Twitter corpus. Experimental results show that the proposed model achieves 83% in F-measure, and outperforms the state-of-the-art baseline by over 7%.
ACSys TREC-7 Experiments

Experiments relating to TREC-7 Ad Hoc, HP and VLC tasks are described and results reported. Minor re nements of last year's Ad Hoc methods do not appear to have resulted in worthwile improvements in performance. However, larger bene ts were gained from automatic feedback than last year and concept scoring was very bene cial in the Manual Ad Hoc category. In the Automatic Ad Hoc category title-only performance seems to have su ered more severely than long-topic from a number of lexical scanning shortcomings and from an excessive stopword list. The HP track was used to validate the usibility of the combination of PADRE and the Quokka GUI. In the VLC track, the 100 gigabyte collection was indexed in under eight hours and moderately e ective queries were processed in less than two seconds.
ADAPTIVE CRITIC DESIGN BASED NEUROCONTROLLERS FOR TURBOGENERATOR CONTROL

Nonlinear non-stationary large scale (NNLS) systems such as power system networks, telecommunication networks, financial and transportation systems are difficult to control and manage. Mathematical models of such systems are typically derived based on linear techniques, and wide margins of safety are allowed in order to ensure stable operation. In the era of a deregulated electricity industry, and an emphasis on competitive pricing, it will become necessary to reduce these safety margins as much as possible while still maintaining reliable service. Advanced intelligent identification and control schemes are therefore required in order to maximize the throughput/performance of such systems by reducing the otherwise wide safety margins. Neurocontrollers offer such a possibility.
Measuring the impact of a new faculty program using institutional data

Abstract This paper presents a quasi-experimental evaluation of a required, teaching-focused, new faculty program at a large research university. The study makes use of institutional data, including student evaluations of teaching and faculty participation in educational development activities, which are available on many campuses yet rarely used in program evaluation. Results show positive impacts. Faculty found the program valuable and reported increases in their preparation for a range of teaching tasks. In comparison to earlier cohorts, program participants received stronger student evaluations on two global items, and demonstrated significantly more connections with the teaching center in their early careers.
Impact of Query Sample Selection Bias on Information Retrieval System Ranking

Information Retrieval (IR) effectiveness measures commonly assume that the experimental query sets consist of randomly drawn queries that represent the population of queries submitted to IR systems. In many practical situations, however, this assumption is violated, in a problem known as sample selection bias. It follows that the systems participating in evaluation campaigns are ranked by biased estimators of effectiveness. In this paper, we address the problem of query sample selection bias in machine learning terms and study experimentally how retrieval system rankings are affected by it. To this end, we apply a number of retrieval effectiveness measures and query probability estimation methods useful to correct sample selection bias. We report that the ranking of the most effective systems and that of the least effective systems is fairly affected by query sample selection bias, while the ranking of the average systems is much more affected. We also report that the measure of bias depends on the retrieval measure used to rank systems and eventually on the search task being evaluated.
Cross-Presentation of Synthetic Long Peptides by Human Dendritic Cells: A Process Dependent on ERAD Component p97/VCP but Not sec61 and/or Derlin-1

Antitumor vaccination using synthetic long peptides (SLP) is an additional therapeutic strategy currently under development. It aims to activate tumor-specific CD8+ CTL by professional APCs such as DCs. DCs can activate T lymphocytes by MHC class I presentation of exogenous antigens - a process referred to as “cross-presentation”. Until recently, the intracellular mechanisms involved in cross-presentation of soluble antigens have been unclear. Here, we characterize the cross-presentation pathway of SLP Melan-A16–40 containing the HLA-A2-restricted epitope26–35 (A27L) in human DCs. Using confocal microscopy and specific inhibitors, we show that SLP16–40 is rapidly taken up by DC and follows a classical TAP- and proteasome-dependent cross-presentation pathway. Our data support a role for the ER-associated degradation machinery (ERAD)-related protein p97/VCP in the transport of SLP16–40 from early endosomes to the cytoplasm but formally exclude both sec61 and Derlin-1 as possible retro-translocation channels for cross-presentation. In addition, we show that generation of the Melan-A26–35 peptide from the SLP16–40 was absolutely not influenced by the proteasome subunit composition in DC. Altogether, our findings propose a model for cross-presentation of SLP which tends to enlarge the repertoire of potential candidates for retro-translocation of exogenous antigens to the cytosol.
Efficient subpace based channel estimation for time variant OFDM systems

Subspace based time domain channel estimation can separate signal subspace and noise subspace using channel statistic information to reduce noise with low complexity. In this paper, an improved threshold is deduced based on MSE criterion, which average the successive (orthogonal frequency division multiplexing) OFDM symbols in time domain efficiently reducing the addictive white Gaussian noise (AWON) and Inter-carrier Interference (ICI). Using the statistic feature of Gaussian noise, the Gaussian probability threshold (GPT) algorithm is proposed. To be adaptive with fading signals, robust Time OFDM symbol average adaptive threshold (TAAT) algorithm is proposed. The two algorithm proposed in this paper can achieve high resolution of signals without channel information. Also it is not subject to frequency leakage. Simulations under VA30 channel shows the algorithm can almost remove the entire noise path and achieve 2.5dB over the discrete Fourier transform(DFT)based method.
Vulnerability to cavitation, hydraulic efficiency, growth and survival in an insular pine (Pinus canariensis).

BACKGROUND AND AIMS It is widely accepted that hydraulic failure due to xylem embolism is a key factor contributing to drought-induced mortality in trees. In the present study, an attempt is made to disentangle phenotypic plasticity from genetic variation in hydraulic traits across the entire distribution area of a tree species to detect adaptation to local environments. METHODS A series of traits related to hydraulics (vulnerability to cavitation and hydraulic conductivity in branches), growth performance and leaf mass per area were assessed in eight Pinus canariensis populations growing in two common gardens under contrasting environments. In addition, the neutral genetic variability (FST) and the genetic differentiation of phenotypic variation (QST) were compared in order to identify the evolutionary forces acting on these traits. KEY RESULTS The variability for hydraulic traits was largely due to phenotypic plasticity. Nevertheless, the vulnerability to cavitation displayed a significant genetic variability (approx. 5 % of the explained variation), and a significant genetic × environment interaction (between 5 and 19 % of the explained variation). The strong correlation between vulnerability to cavitation and survival in the xeric common garden (r = -0·81; P < 0·05) suggests a role for the former in the adaptation to xeric environments. Populations from drier sites and higher temperature seasonality were less vulnerable to cavitation than those growing at mesic sites. No trade-off between xylem safety and efficiency was detected. QST of parameters of the vulnerability curve (0·365 for P50 and the slope of the vulnerability curve and 0·452 for P88) differed substantially from FST (0·091), indicating divergent selection. In contrast, genetic drift alone was found to be sufficient to explain patterns of differentiation for xylem efficiency and growth. CONCLUSIONS The ability of P. canariensis to inhabit a wide range of ecosystems seemed to be associated with high phenotypic plasticity and some degree of local adaptations of xylem and leaf traits. Resistance to cavitation conferred adaptive potential for this species to adapt successfully to xeric conditions.