Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterising the Mechanism of Airway Smooth Muscle β2 Adrenoceptor Desensitization by Rhinovirus Infected Bronchial Epithelial Cells

Rhinovirus (RV) infections account for approximately two thirds of all virus-induced asthma exacerbations and often result in an impaired response to β2 agonist therapy. Using an in vitro model of RV infection, we investigated the mechanisms underlying RV-induced β2 adrenoceptor desensitization in primary human airway smooth muscle cells (ASMC). RV infection of primary human bronchial epithelial cells (HBEC) for 24 hours produced conditioned medium that caused β2 adrenoceptor desensitization on ASMCs without an effect on ASMCs viability. Less than 3 kDa size fractionation together with trypsin digestion of RV-induced conditioned medium did not prevent β2 adrenoceptor desensitization, suggesting it could potentially be mediated by a small peptide or lipid. RV infection of BECs, ASMCs and fibroblasts produced prostaglandins, of which PGE2, PGF2α and PGI2 had the ability to cause β2 adrenoceptor desensitization on ASMCs. RV-induced conditioned medium from HBECs depleted of PGE2 did not prevent ASMC β2 adrenoceptor desensitization; however this medium induced PGE2 from ASMCs, suggesting that autocrine prostaglandin production may be responsible. Using inhibitors of cyclooxygenase and prostaglandin receptor antagonists, we found that β2 adrenoceptor desensitization was mediated through ASMC derived COX-2 induced prostaglandins. Since ASMC prostaglandin production is unlikely to be caused by RV-induced epithelial derived proteins or lipids we next investigated activation of toll-like receptors (TLR) by viral RNA. The combination of TLR agonists poly I:C and imiquimod induced PGE2 and β2 adrenoceptor desensitization on ASMC as did the RNA extracted from RV-induced conditioned medium. Viral RNA but not epithelial RNA caused β2 adrenoceptor desensitization confirming that viral RNA and not endogenous human RNA was responsible. It was deduced that the mechanism by which β2 adrenoceptor desensitization occurs was by pattern recognition receptor activation of COX-2 induced prostaglandins.
A general predictive performance model for wavefront algorithms on clusters of SMPs

We propose and validate a closed-end, analytical, general, predictive performance model for applications based on wavefront algorithms on clusters of SMPs. Wavefront algorithms are ubiquitous in parallel computing, since they represent a means of enabling parallelism in computations that contain recurrences. Our particular interest in wavefront algorithms derives from their use in discrete ordinates neutral particle transport computations representative of ASCI, but other important uses are well known. The proposed model captures the tradeoff between processor utilization and communication requirements characteristics of wavefront algorithms. The general model can predict the performance of this class of applications on distributed architectures with a network of lower dimensionality compared to that of an MPP, of which clusters of SMPs are one example. We validate the model using a compact-application from the ASCI workload on a large-scale cluster of SGI Origin 2000s in existence at the Los Alamos National Laboratory. The proposed model validates well on all clusters configurations utilized.
Inhibiting the Recruitment of PLCγ1 to Kaposi’s Sarcoma Herpesvirus K15 Protein Reduces the Invasiveness and Angiogenesis of Infected Endothelial Cells

Kaposi’s sarcoma (KS), caused by Kaposi’s sarcoma herpesvirus (KSHV), is a highly vascularised tumour of endothelial origin. KSHV infected endothelial cells show increased invasiveness and angiogenesis. Here, we report that the KSHV K15 protein, which we showed previously to contribute to KSHV-induced angiogenesis, is also involved in KSHV-mediated invasiveness in a PLCγ1-dependent manner. We identified βPIX, GIT1 and cdc42, downstream effectors of PLCγ1 in cell migration, as K15 interacting partners and as contributors to KSHV-triggered invasiveness. We mapped the interaction between PLCγ1, PLCγ2 and their individual domains with two K15 alleles, P and M. We found that the PLCγ2 cSH2 domain, by binding to K15P, can be used as dominant negative inhibitor of the K15P-PLCγ1 interaction, K15P-dependent PLCγ1 phosphorylation, NFAT-dependent promoter activation and the increased invasiveness and angiogenic properties of KSHV infected endothelial cells. We increased the binding of the PLCγ2 cSH2 domain for K15P by substituting two amino acids, thereby creating an improved dominant negative inhibitor of the K15P-dependent PLCγ1 activation. Taken together, these results demonstrate a necessary role of K15 in the increased invasiveness and angiogenesis of KSHV infected endothelial cells and suggest the K15-PLCγ1 interaction as a possible new target for inhibiting the angiogenic and invasive properties of KSHV.
The Mixing Approach as a Unifying Framework for Dynamic Multivariate Analysis

We argue that many models for multivariate longitudinal and cross-sectional data analysis have a common ancestry. They all are based on the qualitative idea that if we knew the actual state of the world, the relations between the observed quantities would be truly simple. This is shown to lead directly to factor analysis, IRT, state space models, mixture densities, latent Markov chains, MIMIC, LISREL, and various other common models and techniques. We show how our approach provides a convenient framework for looking at these models. The EM algorithm can be used to estimate the unknown parameters. An additional advantage of our approach is that it can incorporate continuous as well as interval, ordinal and categorical variables .
A Complete Generalization of Atkin's Square Root Algorithm

Atkin's algorithm [2] for computing square roots in $Z^*_p$, where p is a prime such that p ≡ 5 mod 8, has been extended by Muller [15] for the case p ≡ 9 mod 16. In this paper we extend Atkin's algorithm to the general case p ≡ 2s + 1 mod 2s + 1, for any s ≥ 2, thus providing a complete solution for the case p ≡ 1 mod 4. Complexity analysis and comparisons with other methods are also provided.
Real-time Wearable Computer Vision System for Improved Museum Experience

The goal of this work is to implement a real-time computer vision system that can run on wearable devices to perform object classification and artwork recognition, to improve the experience of a museum visit through understanding the interests of users. Object classification helps to understand the context of the visit, e.g. differentiating when a visitor is talking with people, or just wandering through the museum, or if he is looking at an exhibit that interests him. Artwork recognition allows to provide automatically information of the observed item or to create a user profile based on what and how long a user has observed artworks.
Noise robust speech recognition using parallel model compensation and voice activity detection methods

The main purpose of this study is to increase the performance of a speech recognition system under noisy environments. In this study Voice Activity Detection (VAD) methods is used for estimating the noise model, and Parallel Model Compensation (PMC) is used for estimating the noisy speech model using the clean speech model and noise model which is estimated using a VAD method. Performances of the baseline and four well known VAD methods have been compared for noisy speech recognition. In addition to this, a new VAD method is proposed to estimate parameters of the noise model. The proposed VAD method's speech recognition performance is better than the most of the well-known VAD methods despite less computational requirement of the proposed VAD method compared to these well-known VAD methods.
Advantages in synchronization for wireless sensor networks

Providing efficient mechanisms to reduce consuming power and optimize computing resources is one of the most important goals to be pursued when an efficient utilization of sensor networks has to be addressed. To reduce power consumption at the MAC level, sensor networks usually make use of a scheduled contention protocol that adopts listen/sleep cycles. Cycles synchronization can improve performance, although in a sensor network with hundreds of nodes a predefined synchronization degree will determine a huge power consumption due to messages overhead. This paper aims to analyze advantages and disadvantages of cycles synchronization. It provides some rules that help to select and configure a MAC level protocol or a synchronization algorithm with the aim to maximize the network performance.
L1 fault tolerant adaptive control of a hexacopter with control degradation

In this paper we present a nonlinear control framework for the attitude of a hexacopter system, which is able to cope with motor degradation. Approximate model inversion transforms the plant into an equivalent linear form. A linear error controller enables tracking of a designer chosen reference model. The control framework is augmented by an L1 adaptive controller, in order to cope with uncertainties. Due to the nature of the L1 controller, performance and robustness are decoupled, which allows for a fast and reliable compensation of faults. We present a condition on the control allocation in order to achieve attitude stabilization during hover. The performance of the control architecture is corroborated in numerical simulation using a high fidelity simulation model of a hexacopter system. After that flight test results with motor degradation are presented.
Early Effects of P-15 on Human Bone Marrow Stem Cells

ABSTRACT Objectives Peptide-15 (P-15) is an analogue of the cell binding domain of collagen. P-15 has been shown to facilitate physiological to process in a way similar to collagen, to serve as anchorage for cells, and to promote the binding, migration and differentiation of cells. However, how P-15 alters osteoblast activity to promote bone formation is poorly understood. To study the osteoinductive properties of peptide P-15, we analyzed the expression levels of bone related genes in human mesenchymal stem cells treated with this biomaterial. Material and Methods Using real time Reverse Transcription-Polymerase Chain Reaction the quantitative expression of specific genes, like transcriptional factors (RUNX2 and SP7), bone related genes (SPP1, COL1A1, COL3A1, BGLAP, ALPL, and FOSL1) and mesenchymal stem cells marker (ENG) were examined. Results P-15 causes a considerable induction of osteoblast transcriptional factor like osterix (SP7) and of the bone related genes osteopontin (SPP1) and osteocalcin (BGLAP). In contrast the expression of endoglin (ENG) was markedly decreased in stem cells treated with P-15 respect to untreated cells, indicating the differentiation effect of this biomaterial on stem cells. Conclusions The present study shows the effect of P-15 on mesenchymal stem cells in the early differentiation stages: P-15 is an inducer of osteogenesis on human stem cells as indicated by the activation of bone related markers SP7, SPP1 and BGLAP.The results may allow a better understanding of the molecular mechanism of bone regeneration and as a model for comparing other materials with similar clinical effects.
On the (im)possibility of denial of service attacks exploiting authentication overhead in WSNs

The cryptographic operations used in security protocols like data security and authentication will always impose a certain overhead on the amount of time required to process received data. Cautious balance must be maintained between the amount of security required in an application and its overhead. Starting from the random jamming/MAC flooding Denial of Service attacks we examine the possibility of mounting an attack that exploits the overhead required to authenticate received packets. The tests show a resilient protocol and a vulnerable one.
Similarities in Acquired Factors Related to Postmenopausal Osteoporosis and Sarcopenia

Postmenopausal population is at increased risk of musculoskeletal impairments. Sarcopenia and osteoporosis are associated with significant morbidity and social and health-care costs. These two conditions are uniquely linked with similarities in pathophysiology and diagnostic methods. Uniform diagnostic criteria for sarcopenia are still evolving. Postmenopausal sarcopenia and osteoporosis share many environmental risk- and preventive factors. Moreover, geriatric frailty syndrome may result from interaction of osteoporosis and sarcopenia and may lead to increased mortality. The present paper reviews the factors in evolution of postmenopausal sarcopenia and osteoporosis.
TRPM7 Regulates Cell Adhesion by Controlling the Calcium-dependent Protease Calpain*

m-Calpain is a protease implicated in the control of cell adhesion through focal adhesion disassembly. The mechanism by which the enzyme is spatially and temporally controlled is not well understood, particularly because the dependence of calpain on calcium exceeds the submicromolar concentrations normally observed in cells. Here we show that the channel kinase TRPM7 localizes to peripheral adhesion complexes with m-calpain, where it regulates cell adhesion by controlling the activity of the protease. Our research revealed that overexpression of TRPM7 in cells caused cell rounding with a concomitant loss of cell adhesion that is dependent upon the channel of the protein but not its kinase activities. Knockdown of m-calpain blocked TRPM7-induced cell rounding and cell detachment. Silencing of TRPM7 by RNA interference, however, strengthened cell adhesion and increased the number of peripheral adhesion complexes in the cells. Together, our results suggest that the ion channel TRPM7 regulates cell adhesion through m-calpain by mediating the local influx of calcium into peripheral adhesion complexes.
The song remains the same: identifying versions of the same piece using tonal descriptors

Identifying versions of the same song by means of automatically extracted audio features is a complex task for a music information retrieval system, even though it may seem very simple for a human listener. The design of a system to perform this task gives the opportunity to analyze which features are relevant for music similarity. This paper focuses on the analysis of tonal similarity and its application to the identification of different versions of the same piece. This work formulates the situations where a song is versioned and several musical aspects are transformed with respect to the canonical version. A quantitative evaluation is made using tonal descriptors, including chroma representations and tonality. A simple similarity measure, based on Dynamic Time Warping over transposed chroma features, yields around 55% accuracy, which exceeds by far the expected random baseline rate.
Higher likelihood of multiple bit-flips due to neutron-induced strikes on logic gates

High energy particles from cosmic rays or packaging materials can generate a glitch or a current transient (single event transient or SET) in a logic circuit. This SET can eventually get captured in a register resulting in a flip of the register content, which is known as soft error or single-event upset (SEU). A soft error is typically modeled as a probabilistic single bi t-flip model. In developing such abstract fault models, an importa nt issue to consider is the likelihood of multiple bit errors caused by particle strikes. In an earlier related work, we performed a characterization study of the impact of an SET on a logic circuit to quantify the extent to which this model is accurate. We found that, a substantial fraction of SEU outcomes had multi ple register flips. In this paper, we perform a deeper analysis to understand the individual contributions of, ‘strike on a register’ and ‘strike on a logic gate’, on multiple flips. We use postlayout circuit simulations and Monte Carlo sampling scheme to study the impact of an SET. We perform our simulations on ISCAS’85, ISCAS’89 and ITC’99 benchmarks in 180nm and 65nm technologies. We find that, amongst the erroneous outcomes, the probability of multiple bit-flips for ‘gate-strike’ cases was substantial and went up to 50%, where as those for ‘register-strike’ cases was just about 2%. This implies that, if we were to do hardened flip-flop designs to eliminate the flips due to register strikes, in such designs, out of the remainin g flips which are going to be due to ‘gate strikes’, a large fraction will be multiple flips. Hardening the flip-flops is not going to help in this scenario. Thus, gate strikes are problematic and complex er ror correction schemes at the circuit level are needed to elimin ate the multiple errors due to ‘gate strikes’.
How Does the Granularity of an Annotation Scheme Influence Dependency Parsing Performance?

The common use of a single de facto standard annotation scheme for dependency treebank creation leaves the question open to what extent the performance of an application trained on a treebank depends on this annotation scheme and whether a linguistically richer scheme would imply a decrease of the performance of the application. We investigate the effect of the variation of the number of grammatical relations in a tagset on the performance of dependency parsers. In order to obtain several levels of granularity of the annotation, we design a hierarchical annotation scheme exclusively based on syntactic criteria. The richest annotation contains 60 relations. The more coarse-grained annotations are derived from the richest. As a result, all annotations and thus also the performance of a parser trained on different annotations remain comparable. We carried out experiments with four state-of-the-art dependency parsers. The results support the claim that annotating with more fine-grained syntactic relations does not necessarily imply a significant loss of accuracy. We also show the limits of this approach by giving details on the fine-grained relations that do have a negative impact on the performance of the parsers.
Transformative Learning in Developing as an Engaged Global Citizen

This article investigates students’ experiences of learning about privilege and oppression in the context of an introductory university course in civic engagement and global citizenship. Participants included 24 students enrolled in the course during either the 2013–2014 or the 2014–2015 academic year. The authors collected data through pretests, students’ course work, posttests, and focus groups administered at the end of the course. Using Mezirow’s theory of transformative learning combined with Curry-Stevens’s pedagogy for the privileged, and employing thematic analysis to interpret data, the authors found that several students experienced transformative learning specifically in relation to philosophical, psychological, epistemic, and moral–ethical habits of mind. We provide examples of this learning while also considering limitations of students’ learning.
An Efficient Load Balancing Algorithm in Distributed Systems

In this paper, an algorithm for load balancing in the parallel and distributed systems is proposed. Firstly, all jobs are assigned to the machines according to classical Min-min algorithm. Then performance of the algorithm is evaluated by computing the fairness index. If the value of the fairness index is not within the proper range, an improvement algorithm can be executed over the intermedial results. During the process of the improvement algorithm, the machines are orgnized into pairs according to the total load of the tasks on them. Then each time no more than two tasks are allowed to be exchanged between each pair of machines to achieve better effect. The experimental results show that our algorithm performs efficiently and suffices the specific requirements of real-time systems.
Weight-Aware Multidimensional Advertising for TV Programs

Given ongoing developments in the digital television industry, the consumption habits of consumers are substantially influenced by advertisements, which become the main revenue source for TV broadcasters. Therefore, the effective deployment of advertisements is necessary. Digital television is a thriving sector and the number of channels continues to increase, so that the various dimension information of data on electronic programming guides overwhelm the advertisement recommendation systems for TV programs. In this paper, considering the viewing scenarios the users viewed in the different types of television program, the authors present a weight-aware multidimensional model approach that focuses on the different weights of advertisement or program content parameters and their interrelationship. Furthermore this study is the first attempt at applying the approach to advertisement recommendation. The authors introduce an empirical measure for obtaining the weight values of dimensions, and present the similarity measure model, which enhances accuracy and convergence in advertisement recommendations. The experiment and evaluation show that our approach outperforms the previously reported fuzzy clustering technique.
A NOVEL TECHNIQUE FOR HUMAN FACE DETECTION BASED ON COLOR SEGMENTATION AND TEMPLATE MATCHING

This paper presents a novel face detection algorithm. Face Detection is the process of locating faces in the image. Our aim is to locate all faces in the image irrespective of various challenges usually faced by researchers. Image including faces is the further key to intelligent vision-based human computer interaction & research attempts in face processing including face recognition, face motion tracking, pose estimation, and feature recognition. Various approaches have been employed to detect faces in images. There are various challenges associated with the different techniques. The challenges usually accustomed by researchers are the facial gestures, texture, pose and lighting conditions while taking an image. Procedure used by us does not impinge on the cited challenges. The technique used for identifying the face in an image includes skin colour segmentation to reject the non-skin region, removal of noise and clutters in the segmented image through a series of morphological operations, masking the morphological operated image over the gray scale image, rejection of non-face region like hands, arms, etc based on geometry and Euler number, convolving our last output image with the templates to get final gray image containing only faces. Skin colour segmentation is done by plotting the histogram of HSV colour image and thus separating the skin region from the image. Non-face skin region is then rejected by convolving the morphological output with the templates that are representatives of human faces. Various efficient face detection techniques uses neural network scanning of test image and executes exhaustive search in every part of the image, so increases the search time and complexity. With this technique we have overcome the challenge faced by the previous techniques, i.e. time factor. In experiments on images, our algorithm has achieved high detection rates and less false detection due to the application of the new algorithm.
Efficient Sentence Parsing with Language Specific Features: A Case Study of Czech

The paper presents two optimalizations of standard parsing techniques applied to Czech as a representative of a free word order language with rich morphology. Our approach is based on features that take advantage of particular knowledge of language specific properties. The first method involves a special type of merging possible due to the agreement fulfillment. Another use of language specific features lies in the exploitation of verb valency frames for probabilistic ordering of parsing output.