Miracle-dz/UniFAR-FTUs huggingface dataset:
Cell mechanics: principles, practices, and prospects

Cells generate and sustain mechanical forces within their environment as part of their normal physiology. They are active materials that can detect mechanical stimulation by the activation of mechanosensitive signaling pathways, and respond to physical cues through cytoskeletal re‐organization and force generation. Genetic mutations and pathogens that disrupt the cytoskeletal architecture can result in changes to cell mechanical properties such as elasticity, adhesiveness, and viscosity. On the other hand, perturbations to the mechanical environment can affect cell behavior. These transformations are often a hallmark and symptom of a variety of pathologies. Consequently, there are now a myriad of experimental techniques and theoretical models adapted from soft matter physics and mechanical engineering to characterize cell mechanical properties. Interdisciplinary research combining modern molecular biology with advanced cell mechanical characterization techniques now paves the way for furthering our fundamental understanding of cell mechanics and its role in development, physiology, and disease. We describe a generalized outline for measuring cell mechanical properties including loading protocols, tools, and data interpretation. We summarize recent advances in the field and explain how cell biomechanics research can be adopted by physicists, engineers, biologists, and clinicians alike. WIREs Syst Biol Med 2014, 6:371–388. doi: 10.1002/wsbm.1275
Instability wave models for the near-field fluctuations of turbulent jets

Abstract Previous work has shown that aspects of the evolution of large-scale structures, particularly in forced and transitional mixing layers and jets, can be described by linear and nonlinear stability theories. However, questions persist as to the choice of the basic (steady) flow field to perturb, and the extent to which disturbances in natural (unforced), initially turbulent jets may be modelled with the theory. For unforced jets, identification is made difficult by the lack of a phase reference that would permit a portion of the signal associated with the instability wave to be isolated from other, uncorrelated fluctuations. In this paper, we investigate the extent to which pressure and velocity fluctuations in subsonic, turbulent round jets can be described as linear perturbations to the mean flow field. The disturbances are expanded about the experimentally measured jet mean flow field, and evolved using linear parabolized stability equations (PSE) that account, in an approximate way, for the weakly non-parallel jet mean flow field. We utilize data from an extensive microphone array that measures pressure fluctuations just outside the jet shear layer to show that, up to an unknown initial disturbance spectrum, the phase, wavelength, and amplitude envelope of convecting wavepackets agree well with PSE solutions at frequencies and azimuthal wavenumbers that can be accurately measured with the array. We next apply the proper orthogonal decomposition to near-field velocity fluctuations measured with particle image velocimetry, and show that the structure of the most energetic modes is also similar to eigenfunctions from the linear theory. Importantly, the amplitudes of the modes inferred from the velocity fluctuations are in reasonable agreement with those identified from the microphone array. The results therefore suggest that, to predict, with reasonable accuracy, the evolution of the largest-scale structures that comprise the most energetic portion of the turbulent spectrum of natural jets, nonlinear effects need only be indirectly accounted for by considering perturbations to the mean turbulent flow field, while neglecting any non-zero frequency disturbance interactions.
Exploring the Differential Influence of Positive Mood on School-Aged Children’s Risk Taking

Exploring the Differential Influence of Positive Mood on School-Aged Children’s Risk Taking Julia K. Stewart Advisor: University of Guelph, 2013 Professor B. A. Morrongiello Children’s intentions to engage in risk taking and actual risk behaviours were compared while in a neutral and positive mood state. Positive mood was reliably and significantly induced experimentally via false positive feedback during the playing of a novel videogame. Withinperson mood comparisons demonstrated that children engaged in more risk taking when in a positive mood compared to a neutral mood. This increase was observed in both measures of intent to risk take, as well as in actual behaviour. Positive urgency did not predict risk taking while in a positive mood. These findings reveal, for the first time, that positive mood is associated with greater risk taking in young children. Implications for injury prevention are discussed.
Octave-dependent Probabilistic Latent Semantic Analysis to Chorus Detection of Popular Song

Content representation of music signal is an essential part of music information retrieval applications, e.g. chorus detection, genre classification, etc. In the paper, we propose the octave-dependent probabilistic latent semantic analysis (OdPlsa) to discover the latent audio patterns (or clusters) through spectral-temporal analysis. Then the audio content of each segment is characterized using the statistical pattern distribution. In OdPlsa, the latent pattern is modeled by multinomial distribution which characterizes the magnitude distribution of 12-dimensional pitch class profiles over a temporal window. It thus effectively models melody information as well as octave relations in music signal. Its efficiency as a feature extraction technique is evaluated on chorus detection of popular songs. In terms of multiple performance metrics such as boundary accuracy, precision, recall and F1, the proposed technique is much superior to the widely accepted chroma feature.
A wireless structural health monitoring system with multithreaded sensing devices: design and validation

Structural health monitoring (SHM) has become an important research problem which has the potential to monitor and ensure the performance and safety of civil structures. Traditional wire-based SHM systems require significant time and cost for cable installation. With the recent advances in wireless communication technology, wireless SHM systems have emerged as a promising alternative solution for rapid, accurate and low-cost structural monitoring. This paper presents a newly designed integrated wireless monitoring system that supports real-time data acquisition from multiple wireless sensing units. The selected wireless transceiver consumes relatively low power and supports long-distance peer-to-peer communication. In addition to hardware, embedded multithreaded software is also designed as an integral component of the proposed wireless monitoring system. A direct result of the multithreaded software paradigm is a wireless sensing unit capable of simultaneous data collection, data interrogation and wireless transmission. A reliable data communication protocol is designed and implemented, enabling robust real-time and near-synchronized data acquisition from multiple wireless sensing units. An integrated prototype system has been fabricated, assembled, and validated in both laboratory tests and in a large-scale field test conducted upon the Geumdang Bridge in Icheon, South Korea.
G3BP–Caprin1–USP10 complexes mediate stress granule condensation and associate with 40S subunits

Stress granule condensation (SGC) of translationally arrested mRNAs requires G3BP, and G3BP-mediated SGC is inhibited by serine 149 phosphorylation, regulated by mutually exclusive binding of Caprin1 and USP10, and requires its RGG region for SGC and for interactions with 40S ribosomal subunits.
Random sampling ADC for sparse spectrum sensing

Scanning large bandwidths (spectrum sensing) pushes today's analog hardware to its limits since periodic sampling at Nyquist rate with sufficient resolution is often prohibitively complex. In this paper, we consider a scenario where the signal to be acquired is sparse in the frequency domain (e.g., spectrum sensing in cognitive radio applications) and we are interested in identifying the sparse support of the signal. For this type of applications, we describe a new analog-to-digital converter (ADC) architecture that acquires unequally spaced samples based on a slope ADC, which is one of the least complex ADC architectures available. For the signal reconstruction, we employ algorithms from compressed sensing for the recovery of the dominant spectral components. The performance of the proposed design is compared to more traditional designs with comparable or higher hardware complexity.
An Unbalanced Dataset Classification Approach Based on v-Support Vector Machine

Support vector machine (SVM) has been extensively studied and has shown remarkable success in many applications. However, when faced with unbalanced datasets, the SVM can not get ideal classification result and even in some cases the classification ability was very bad and unaccepted. The V-support vector machine (V-SVM) is a new formulation of the regular SVM, and its parameter V has intuitive meanings compared with C (the penalty constant in SVM). By investigating the relation between SVM and V-SVM, we gave an equation between V and C, meanwhile we analyzed the factor behind the classification failure of SVM on unbalanced dataset. Then a classification algorithm based on V-SVM was addressed to overcome this inconvenience. Experimental results show the effectiveness of the proposed algorithm
A robust audio watermarking based-on multiwavelet transform

In this paper, a robust watermarking scheme for digital audio signal is proposed. The watermarks are embedded into the low frequency coefficients in discrete multiwavelet transform domain to achieve robust performance against common signal processing procedures and compression. The embedding technique is based on quantization process which does not require the original audio signal in the watermark extraction. The experimental results demonstrate that watermark is imperceptible and the algorithm is robust to many common signal processing procedures, such as re-sampling, cropping, low-pass filtering and MPEG 1 Layer III compression.
A PRACTICAL FLOATING-GATE MULLER-C ELEMENT USING ν MOS THRESHOLD

This paper presents the rationale for νMOS-based realizations of digital circuits when logic design techniques based on threshold logic gates (TGs) are used. Some practical problems in the νMOS implementation of threshold gates have been identified and solved. The feasibility and versatility of the proposed technique as well as its potential as a low-cost design technique for CMOS technologies have been shown by experimental results from a multi-input Muller C-element. The proposed new realization exhibits better performance related to delay, area and power consumption than the traditional logic implementation.
Mining Maximal Hyperclique Pattern: A Hyperclique Pattern Growth Strategy

Mining of confident patterns from the datasets with skewed support distributions is a very important problem in the pattern discovery field. A hyperclique pattern is presented as a new type of association pattern for mining such datasets, in which items are highly affiliated with each other. The maximal hyperclique pattern is a more compact representation of a group of hyperclique patterns. In this paper, we present a fast algorithm of mining maximal hyperclique pattern called hyperclique pattern growth (HCP-growth) based on frequent pattern tree (FP-tree). The algorithm adopts recursive mining method without any candidate generation and exploits many efficient pruning strategies. The experimental results demonstrate that our algorithm is more effective than the standard maximal hyperclique pattern mining algorithm, particularly for the large-scale datasets.
Music Pitch Representation by Periodicity Measures Based on Combined Temporal and Spectral Representations

Periodicity estimation of an audio signal, for applications such as pitch, multiple pitch or tempo estimation is often problematic due to the presence of multiple harmonics in the audio signal producing octave errors. While pitch models or rhythm models can be used, they remain often dedicated to a specific problem. In this paper, we propose a straightforward approach for periodicity estimation based on the combination of a spectral representation and a temporal representation. This method allows a better emphasis on the frequencies corresponding to the various pitches. We show the ability of this representation to adequately estimate pitch and visualize signals with multiple pitch content
Identification of serious and reportable events in home care: a Delphi survey to develop consensus.

OBJECTIVE To assess which client events should be considered reportable and preventable in home care (HC) settings in the opinion of HC safety experts. BACKGROUND Patient safety in acute care settings has been well documented; however, there are limited data about this issue in HC. While many organizations collect information about 'incidents', there are no standards for reporting and it is challenging to compare incident rates among organizations. DESIGN A 29-item electronic survey that included potential HC safety issues was used in a two-round Delphi study. SETTING AND PARTICIPANTS Twenty-four pan-Canadian HC safety experts participated in an electronic survey. MAIN OUTCOME MEASURES Perceived reportability and preventability of patient safety events, HC. RESULTS The events that were perceived as being most reportable and preventable included the following: a serious injury related to inappropriate client service plan (e.g. incomplete/inaccurate assessments, poor care plan design, flawed implementation); an adverse reaction requiring emergency room visit or hospitalization related to a medication-related event; a catheter-site infection (e.g. a new peritoneal dialysis infection or peritonitis); any serious event related to care or services that are contrary to current professional or other practice standards (e.g. incorrect treatment regimen, theft, retention of a foreign object in a wound, individual practicing outside scope or competence). CONCLUSION These data represent an important step in the development and validation of standard metrics about client safety in HC. The results address an expanding area of health services where there is a need to improve standardization and reporting.
Approximate Reasoning about Actions in Presence of Sensing and Incomplete Information

Sensing actions are important for planning with incomplete information. A solution for the frame problem for sensing actions was proposed by Scherl and Levesque. They adapt the possible world model of knowledge to situation calculus. In this paper we propose a high level language in the spirit of the language A, that allows sensing actions. We then present two approximation semantics of this language and their translation to logic programs. Unlike, A, where states are two valued interpretations, and unlike the approach in Scherl and Levesque where states are Kripke models, in our approach states are three valued interpretations.
Backscatter Analysis Using Multi-Temporal and Multi-Frequency SAR Data in the Context of Flood Mapping at River Saale, Germany

In this study, an analysis of multi-temporal and multi-frequency Synthetic Aperture Radar data is performed to investigate the backscatter behavior of various semantic classes in the context of flood mapping in central Europe. The focus is mainly on partially submerged vegetation such as forests and agricultural fields. The test area is located at River Saale, Saxony-Anhalt, Germany, which is covered by a time series of 39 TerraSAR-X data acquired within the time interval December 2009 to June 2013. The data set is supplemented by ALOS PALSAR L-band and RADARSAT-2 C-band data. The time series covers two inundations in January 2011 and June 2013 which allows evaluating backscatter variations between flood periods and normal water level conditions using different radar wavelengths. According to the results, there is potential in detecting flooding beneath vegetation in all microwave wavelengths, even in X-band for sparse vegetation or leaf-off forests.
Perceived Effectiveness of Social Media as an English Language Learning Tool

Little is known about the potential effects of social media usage on the learning performance of undergraduates, especially female students in some Arab/Islamic cultures, where sex-segregated education is the norm, and the freedom of expression of women may be suppressed. The purpose of the current study was to test the correlation between the independent variables (including, level of social media use, interactivity with peers, interactivity with teachers, active cooperative learning, engagement) and the dependent variable (i.e., learning performance) of female Saudi students in a sex-segregated educational system. A cross-sectional survey was administered to 283 participants, representing 15.8% of the target population of female Saudi students enrolled on a distance learning course at King Abdulaziz University. The data were analyzed by partial least squares structural equation modeling, to generate and validate the Social Media-Learning Performance (SM-LP) model. The SM-LP model predicted with a substantial effect size (R2 = 67.7%) that female Saudi students perceived that they could potentially improve their learning performance, in a sex-segregated education system, through high levels of social media use, stimulating inter activity with peers and teachers, as well as active collaborative learning, and engagement. All the path coefficients were statistically significant (p < .05) reflecting a strong endorsement of the use of social media as an effective learning tool. The findings have important implications for sex-segregated educational context.
Incorporating covariance estimation uncertainty in spatial sampling design for prediction with trans-Gaussian random fields

Recently, Spock and Pilz [38], demonstrated that the spatial sampling design problem for the Bayesian linear kriging predictor can be transformed to an equivalent experimental design problem for a linear regression model with stochastic regression coefficients and uncorrelated errors. The stochastic regression coefficients derive from the polar spectral approximation of the residual process. Thus, standard optimal convex experimental design theory can be used to calculate optimal spatial sampling designs. The design functionals considered in Spock and Pilz [38] did not take into account the fact that kriging is actually a plug-in predictor which uses the estimated covariance function. The resulting optimal designs were close to space-filling configurations, because the design criterion did not consider the uncertainty of the covariance function. In this paper we also assume that the covariance function is estimated, e.g., by restricted maximum likelihood (REML). We then develop a design criterion that fully takes account of the covariance uncertainty. The resulting designs are less regular and space- filling compared to those ignoring covariance uncertainty. The new designs, however, also require some closely spaced samples in order to improve the estimate of the covariance function. We also relax the assumption of Gaussian observations and assume that the data is transformed to Gaussianity by means of the Box-Cox transformation. The resulting prediction method is known as trans-Gaussian kriging. We apply the Smith and Zhu [37] approach to this kriging method and show that resulting optimal designs also depend on the available data. We illustrate our results with a data set of monthly rainfall measurements from Upper Austria.
On the formalization of aggregate relation based on ontology and its implement of OWL

In order to represent aggregate relation based on ontology clearly and correctly, the rich semantic properties of aggregate relation in addition to composition and aggregation are elaborated and formalized based on ontology in algebra theory in the paper. However, OWL, as an ontology modeling language, does not provide support for these semantic properties of aggregate relation directly. How to represent such the properties of aggregate relation in OWL is discussed and presented.
An Empirical Study of Design Patterns and Software Quality

We present an empirical study of the impact of design patterns on quality attributes in the context of software maintenance and evolution. Our first hypothesis verifies software engineering lore: design patterns impact software quality positively. We show that, contrary to popular beliefs, design patterns in practice impact negatively several quality attributes, thus providing concrete evidence against common lore. We then study design patterns and object-oriented best practices by formulating a second hypothesis on the impact of these principles on quality. We show that results for some design patterns cannot be explained and conclude on the need for further studies on the relation between design patterns and object-oriented best practices. Thus, we bring further evidence that design patterns should be used with caution during development because they may actually impede maintenance and evolution.
Chapter 23 Architectural Elements of Resource Sharing Networks

Since the formulation of the early ideas on meta-computing (Smarr & Catlett, 1992), several research activities have focused on mechanisms to connect worldwide distributed resources. Advances in distributed computing have enabled the creation of Grid-based resource sharing networks such as TeraGrid (Catlett, Beckman, Skow, & Foster, 2006) and Open Science Grid (2005). These networks, composed of multiple resource providers, enable collaborative work and sharing of resources such as computers, ABSTRACT
Further Evidence that Human Endogenous Retrovirus K102 is a Replication Competent Foamy Virus that may Antagonize HIV-1 Replication

Objective: The goals of the research were to determine if a foamy effect on macrophages was due to human endogenous retrovirus K102 (HERV-K102) replication, and to further address its potential significance in HIV-1 infection. Methods: An RT-PCR HERV-K HML-2 pol method was used to screen the unknown HERV, and isolated bands were sent for sequencing. Confirmation of RNA expression was performed by a real time quantitative PCR (qPCR) pol ddCt method. Rabbit antibodies to Env peptides were used to assess expression by immunohistology and processing of Env by western blots. A qPCR pol ddCt method to ascertain genomic copy number was performed on genomic DNA isolated from plasma comparing HIV-1 exposed seronegative (HESN) commercial sex workers (CSW) to normal controls and contrasted with HIV-1 patients. Results: HERV-K102 expression, particle production and replication were associated with foamy macrophage generation in the cultures of cord blood mononuclear cells under permissive conditions. A five-fold increased HERV-K102 pol genomic copy number was found in the HESN cohort over normal which was not found in HIV-1 positive patients (p=0.0005). Conclusions: This work extends the evidence that HERV-K102 has foamy virus attributes, is replication competent, and is capable of high replication rate in vivo and in vitro. This may be the first characterization of a replication-competent, foamy-like virus of humans. High particle production inferred by increased integration in the HESN cohort over HIV-1 patients raises the issue of the clinical importance of HERV-K102 particle production as an early protective innate immune response against HIV-1 replication.