Miracle-dz/UniFAR-FTUs huggingface dataset:
Toll-Like Receptors 2 and 4 Regulate the Frequency of IFNγ-Producing CD4+ T-Cells during Pulmonary Infection with Chlamydia pneumoniae

TLR2 and TLR4 are crucial for recognition of Chlamydia pneumoniae in vivo, since infected TLR2/4 double-deficient mice are unable to control the infection as evidenced by severe loss of body weight and progressive lethal pneumonia. Unexpectedly, these mice display higher pulmonary levels of the protective cytokine IFNγ than wild type mice. We show here, that antigen-specific CD4+ T-cells are responsible for the observed IFNγ-secretion in vivo and their frequency is higher in TLR2/4 double-deficient than in wild type mice. The capacity of TLR2/4 double-deficient dendritic cells to re-stimulate CD4+ T-cells did not differ from wild type dendritic cells. However, the frequency of CD4+CD25+Foxp3+ T-cells was considerably higher in wild type compared to TLR2/4 double-deficient mice and was inversely related to the number of IFNγ-secreting CD4+ effector T-cells. Despite increased IFNγ-levels, at least one IFNγ-mediated response, protective NO-secretion, could not be induced in the absence of TLR2 and 4. In summary, CD4+CD25+Foxp3+ regulatory T-cells fail to expand in the absence of TLR2 and TLR4 during pulmonary infection with C. pneumoniae, which in turn enhances the frequency of CD4+IFNγ+ effector T-cells. Failure of IFNγ to induce NO in TLR2/4 double-deficient cells represents one possible mechanism why TLR2/4 double-deficient mice are unable to control pneumonia caused by C. pneumoniae and succumb to the infection.
The impact of learners' characteristics on m-learning preferences, and how m-learning preferences form choices in different contexts

v ABSTRACT Students adopt different strategies, show a range of preferences, and make individual choices as they learn to learn effectively and efficiently. Facilitating students to customise their own preferred techniques will maximise students’ learning. Mobile devices allow learning to occur anywhere and at any time. However, the nature of mobile devices, such as the need to access a digital format on devices with small screens, influence students’ e-learning preferences. There is now a growing research effort which aims to understand learners’ mobile learning preferences to deliver digital learning materials that best satisfy learners’ needs. This thesis explores mobile learning (m-learning) preferences and choices in tertiary education to understand the best approaches to deliver digital learning materials (podcasts) in different physical (e.g. quiet, busy, or walking) and social spaces (e.g. alone, family, or with classmates). This study uses two quantitative methods to understand mobile learners’ preferences and choices. First, 345 students completed a survey study concerning the role of mobile learners’ characteristics on podcast preferences in different physical and social spaces. Characteristics which are included in this study are gender, age, nationality (Australian and Saudi), materials status, prior experience of podcasting, learning style, and personality traits. Second, 95 students participated in three experimental studies to examine whether mobile learners’ Thesis template – Mazen Al-Ismail – December 2018 Abstract vi preferences for podcasts reflect their real choices in two different physical spaces which are quiet (e.g. home or library) and busy (e.g. cafe). vi preferences for podcasts reflect their real choices in two different physical spaces which are quiet (e.g. home or library) and busy (e.g. cafe). Overall, the results show that differences in characteristics affect m-learning preferences in some contexts (the result of overlapping physical and social spaces). On the other hand, preferences were reliable in predicting students’ choices only in limited physical spaces. The reason behind these findings are discussed in this thesis. The approaches proposed in the provide ways to understand mobile learners’ preferences and choices, taking in to account a novel method which is a person’s spatial and social contexts.
Graph-Based Segmentation for RGB-D Data Using 3-D Geometry Enhanced Superpixels

With the advances of depth sensing technologies, color image plus depth information (referred to as RGB-D data hereafter) is more and more popular for comprehensive description of 3-D scenes. This paper proposes a two-stage segmentation method for RGB-D data: 1) oversegmentation by 3-D geometry enhanced superpixels and 2) graph-based merging with label cost from superpixels. In the oversegmentation stage, 3-D geometrical information is reconstructed from the depth map. Then, a K-means-like clustering method is applied to the RGB-D data for oversegmentation using an 8-D distance metric constructed from both color and 3-D geometrical information. In the merging stage, treating each superpixel as a node, a graph-based model is set up to relabel the superpixels into semantically-coherent segments. In the graph-based model, RGB-D proximity, texture similarity, and boundary continuity are incorporated into the smoothness term to exploit the correlations of neighboring superpixels. To obtain a compact labeling, the label term is designed to penalize labels linking to similar superpixels that likely belong to the same object. Both the proposed 3-D geometry enhanced superpixel clustering method and the graph-based merging method from superpixels are evaluated by qualitative and quantitative results. By the fusion of color and depth information, the proposed method achieves superior segmentation performance over several state-of-the-art algorithms.
Tumor cell-expressed SerpinB2 is present on microparticles and inhibits metastasis

Expression of SerpinB2 (plasminogen activator inhibitor type 2/PAI‐2) by certain cancers is associated with a favorable prognosis. Although tumor‐associated host tissues can express SerpinB2, no significant differences in the growth of a panel of different tumors in SerpinB2−/− and SerpinB2+/+ mice were observed. SerpinB2 expression by cancer cells (via lentiviral transduction) also had no significant effect on the growth of panel of mouse and human tumor lines in vivo or in vitro. SerpinB2 expression by cancer cells did, however, significantly reduce the number of metastases in a B16 metastasis model. SerpinB2‐expressing B16 cells also showed reduced migration and increased length of invadopodia‐like structures, supporting the classical view that that tumor‐derived SerpinB2 is inhibiting extracellular urokinase. Importantly, although SerpinB2 is usually poorly secreted, we found that SerpinB2 effectively reaches the extracellular milieu on the surface of 0.5–1 μm microparticles (MPs), where it was able to inhibit urokinase. We also provide evidence that annexins mediate the binding of SerpinB2 to phosphatidylserine, a lipid characteristically exposed on the surface of MPs. The presence of SerpinB2 on the surface of MPs provides a physiological mechanism whereby cancer cell SerpinB2 can reach the extracellular milieu and access urokinase plasminogen activator (uPA). This may then lead to inhibition of metastasis and a favorable prognosis.
Multi-channel speech dereverberation based on a statistical model of late reverberation

Speech signals recorded with a distant microphone usually contain reverberation, which degrades the fidelity and intelligibility of speech, and the recognition performance of automatic speech recognition systems. A multi-channel speech dereverberation algorithm is presented which reduces spectral coloration and late reverberation. A spatially averaged amplitude spectrum is used to estimate the instantaneous amplitude spectrum of the clean speech signal, which is then further enhanced using an estimate of the power spectrum of the late reverberant signal. The power spectrum of the late reverberant signal is constructed from multiple microphone signals and a statistical model of late reverberation. The algorithm is tested using synthetic reverberated signals. The performances for different room impulse responses with reverberation times ranging from approximately 150 ms to 350 ms show significant reverberation reduction with little signal distortion.
European Conference on Information Systems ( ECIS ) 2008 Using Levels of Difficulty to Judge Computer Ability : An Empirical Comparison of the Structure of Self-Efficacy

Although self-efficacy (SE) and computer self-efficacy (CSE) in particular has received much research interest in recent years, organizations have been deterred from using it because of the confusing number of extant instruments and the lack of publicity by researchers. CSE is an extremely useful construct in that it provides not only a measure of competence, but more importantly it is an indication of employee motivation to learn and use technology. Two problems have exacerbated this condition: a misunderstanding of how individuals actually judge their computing efficacy and conceptual confusion regarding task versus domain SE. While most extant CSE instruments include the structural dimension of magnitude (degree of task difficulty), this study questions this inclusion both conceptually and empirically. We compare four CSE measures (one without magnitude), in three computing domains, in their relationship with four common outcomes of CSE. Using a sample of over 300 and structural equation modeling, the findings are surprising in that for three outcomes, the CSE measure which did not include magnitude was significantly better. This suggests that perhaps magnitude is not as important as cognitive researchers have conjectured and further clarifies how individuals judge their computing ability. Other implications and directions for further study are presented.
Complication Rates Associated With Pacemaker or Implantable Cardioverter-Defibrillator Generator Replacements and Upgrade Procedures: Results From the REPLACE Registry

Background— Prospective studies defining the risk associated with pacemaker or implantable cardioverter-defibrillator replacement surgeries do not exist. These procedures are generally considered low risk despite results from recent retrospective series reporting higher rates. Methods and Results— We prospectively assessed predefined procedure-related complication rates associated with elective pacemaker or implantable cardioverter-defibrillator generator replacements over 6 months of follow-up. Two groups were studied: those without (cohort 1) and those with (cohort 2) a planned transvenous lead addition for replacement or upgrade to a device capable of additional therapies. Complications were adjudicated by an independent events committee. Seventy-two US academic and private practice centers participated. Major complications occurred in 4.0% (95% confidence interval, 2.9 to 5.4) of 1031 cohort 1 patients and 15.3% (95% confidence interval, 12.7 to 18.1) of 713 cohort 2 patients. In both cohorts, major complications were higher with implantable cardioverter-defibrillator compared with pacemaker generator replacements. Complications were highest in patients who had an upgrade to or a revised cardiac resynchronization therapy device (18.7%; 95% confidence interval, 15.1 to 22.6). No periprocedural deaths occurred in either cohort, although 8 later procedure-related deaths occurred in cohort 2. The 6-month infection rates were 1.4% (95% confidence interval, 0.7 to 2.3) and 1.1% (95% confidence interval, 0.5 to 2.2) for cohorts 1 and 2, respectively. Conclusions— Pacemaker and implantable cardioverter-defibrillator generator replacements are associated with a notable complication risk, particularly those with lead additions. These data support careful decision making before device replacement, when managing device advisories, and when considering upgrades to more complex systems. Clinical Trial Registration— URL: http://www.clinicaltrials. gov. Unique identifier: NCT00395447.
Acute effects of passive muscle stretching on sprint performance

The results of previous research have shown that passive muscle stretching can diminish the peak force output of subsequent maximal isometric, concentric and stretch-shortening contractions. The aim of this study was to establish whether the deleterious effects of passive stretching seen in laboratory settings would be manifest in a performance setting. Sixteen members (11 males, 5 females) of a Division I NCAA track athletics team performed electronically timed 20 m sprints with and without prior stretching of the legs. The experiment was done as part of each athlete's Monday work-out programme. Four different stretch protocols were used, with each protocol completed on a different day. Hence, the test period lasted 4 weeks. The four stretching protocols were no-stretch of either leg (NS), both legs stretched (BS), forward leg in the starting position stretched (FS) and rear leg in the starting position stretched (RS). Three stretching exercises (hamstring stretch, quadriceps stretch, calf stretch) were used for the BS, FS and RS protocols. Each stretching exercise was performed four times, and each time the stretch was maintained for 30 s. The BS, FS and RS protocols induced a significant (P < 0.05) increase (∼0.04 s) in the 20 m time. Thus, it appears that pre-event stretching might negatively impact the performance of high-power short-term exercise.
Maximum Strength in Squats Determines Jumping Height in Young Female Volleyball Players

Few data exist on the relationship between maximum strength and power performance, such as jumping ability in low-level female volleyball players. The aim of the present study was to determine the relationship between maximum strength and jumping performance in young female non-elite volleyball players before and after an in-season resistance- training protocol. A 26-week, in-season resistance-training program was carried out on ten female volleyball players, aged 19 (±2). The 1 RM squat test was used to evaluate the players' maximum strength in the lower extremities and a vertical jump (VJ) test was used to assess functional performance and power. There was a significant enhancement of 69% (p=0.005) for the squat test and 9% for the VJ test (p=0.008). A strong significant relationship was found between the VJ test and the 1 RM squat test (r=0.68, r 2 =0.47, p=0.0014) at the pre-test and post-test (r=0.88, r 2 =0.77, p=0.001). When comparing the coefficients of correlation (r=0.68 and r=0.88) between the squat tests and VJ tests, the difference that was noted was significant (p<0.001). A strong significant relationship was also noted between the 1RM squat and VJ test relative to body weight at pre-test (r=0.89, r 2 =0.79, p=0.001) and post-test (r=0.95, r 2 =0.90), p<0.001). This study demonstrates that maximum strength in squats is a major predictive factor for jumping height in young female volleyball players. Female volleyball players might therefore consider focusing on maximum strength training to improve their jumping performance.
Response of the Kuroshio Extension to Rossby Waves Associated with the 1970s Climate Regime Shift in a High-Resolution Ocean Model*

The response of the Kuroshio Extension (KE) to large-scale Rossby waves remotely excited by wind stress changes associated with the 1970s climate regime shift is studied using a high-resolution regional ocean model. Two ensemble simulations are conducted: The control run uses monthly climatological forcing while, in the second ensemble, anomalous forcing is imposed at the model eastern boundary around 165°E derived from a hindcast of decadal changes in subsurface temperature and salinity using a coarser-resolution model of the Pacific basin. Near the KE, ocean adjustment deviates strongly from the linear Rossby wave dynamics. Most notably, the eastward acceleration of the KE is much narrower in meridional extent than that associated with the incoming Rossby waves imposed on the eastern boundary. This KE acceleration is associated with an enhanced potential vorticity (PV) gradient across the front that is consistent with the inertial western boundary layer theory: the arrival of the Rossby waves at the western boundary causes the eastward current to accelerate, leading to enhanced advection of low (high) PV water of subtropical (subarctic) origin along the western boundary layer. The meridional dipole of PV anomalies results in a pair of anomalous recirculations with a narrow eastward jet in between. A three-layer quasigeostrophic model is used to demonstrate this inertial adjustment mechanism. Finally, transient eddy activity increases significantly and the eddy momentum transport acts to strengthen the mean flow response. The result that ocean physical response to broad-scale atmospheric forcing is large near the KE front has important implications for fisheries research.
Thread Cleaning and Merging for Microblog Topic Detection

As a classic natural language processing technology, topic detection recently attracts more research interests due largely to the rapid development of microblog. The most challenging issue in microblog topic detection is sparse data problem. In this paper, the temporal-author-topic (TAT) model is designed to accomplish microblog topic detection in two phases. In the first phase, the TAT model is applied to clean the thread, namely, to filter noisy microblog texts out of each thread. In the second phase, microblog texts within each thread are merged to form the thread text so that the TAT model is applied to find global topics. The new approach differs from the Hierarchical Agglomerative Clustering (HAC) algorithm by making use of microblog threads to overcome the sparse data problem. Experimental results justify our claims.
Fast Image Classification for Monument Recognition

Content-based image classification is a wide research field that addresses the landmark recognition problem. Among the many classification techniques proposed, the k-nearest neighbor (kNN) is one of the most simple and widely used methods. In this article, we use kNN classification and landmark recognition techniques to address the problem of monument recognition in images. We propose two novel approaches that exploit kNN classification technique in conjunction with local visual descriptors. The first approach is based on a relaxed definition of the local feature based image to image similarity and allows standard kNN classification to be efficiently executed with the support of access methods for similarity search. The second approach uses kNN classification to classify local features rather than images. An image is classified evaluating the consensus among the classification of its local features. In this case, access methods for similarity search can be used to make the classification approach efficient. The proposed strategies were extensively tested and compared against other state-of-the-art alternatives in a monument and cultural heritage landmark recognition setting. The results proved the superiority of our approaches. An additional relevant contribution of this work is the exhaustive comparison of various types of local features and image matching solutions for recognition of monuments and cultural heritage related landmarks.
Effects of Proactive Personality and Conscientiousness on Training Motivation

Training transfer is a ubiquitous but frequently unmet goal of training initiatives amounting to billions of dollars lost annually and masses of under‐skilled workers due to the lack of application of training content to their job. Although research supports the impact trainee proactive personality, conscientiousness and motivation have on training transfer processes, their interrelationships remain understudied. To fill this gap, we utilized data from a multinational sample of trainees and examined a conditional, indirect process model, where proactive personality interacts with conscientiousness to influence transfer intentions through their effects on motivation to learn. Our results suggest that trainee proactive personality positively influences transfer intentions partially through its influence on motivation to learn and that higher levels of conscientiousness weakens this relationship. Our findings provide further evidence supporting the importance of proactive personality and conscientiousness as factors that need to be accounted for in the design of talent development solutions.
Evolutionary History of the Photolyase/Cryptochrome Superfamily in Eukaryotes

Background Photolyases and cryptochromes are evolutionarily related flavoproteins, which however perform distinct physiological functions. Photolyases (PHR) are evolutionarily ancient enzymes. They are activated by light and repair DNA damage caused by UV radiation. Although cryptochromes share structural similarity with DNA photolyases, they lack DNA repair activity. Cryptochrome (CRY) is one of the key elements of the circadian system in animals. In plants, CRY acts as a blue light receptor to entrain circadian rhythms, and mediates a variety of light responses, such as the regulation of flowering and seedling growth. Results We performed a comprehensive evolutionary analysis of the CRY/PHR superfamily. The superfamily consists of 7 major subfamilies: CPD class I and CPD class II photolyases, (6–4) photolyases, CRY-DASH, plant PHR2, plant CRY and animal CRY. Although the whole superfamily evolved primarily under strong purifying selection (average ω = 0.0168), some subfamilies did experience strong episodic positive selection during their evolution. Photolyases were lost in higher animals that suggests natural selection apparently became weaker in the late stage of evolutionary history. The evolutionary time estimates suggested that plant and animal CRYs evolved in the Neoproterozoic Era (~1000–541 Mya), which might be a result of adaptation to the major climate and global light regime changes occurred in that period of the Earth’s geological history.