Miracle-dz/UniFAR-FTUs huggingface dataset:
“Is there any time left for walking?” Physical activity implications of suburban commuting in the Barcelona metropolitan region

ABSTRACT The present study delves into the explanatory factors of the walking patterns of residents in metropolitan regions, who tend to be pressed for time when travelling to their daily destinations or activities. We particularly focus on the effects of the commuting distance on the amount of walking that can be achieved, which has health, socioeconomic and environmental implications. This study confirms the potential benefits of using smartphone tracking data to examine walking patterns. To enable this, a smartphone tracking application was developed to obtain accurate mobility data from a group of adults (n = 93) residing in the Barcelona Metropolitan Region (Spain) and have to commute to a suburban university campus that can only be reached by using motorized transport modes. The results highlight the commuting distance and employment status as strong determinants of the amount of walking time achieved by this study group. Moreover, it was determined that among transit users, the commuting distance of male commuters was negatively associated with walking when compared with female transit users, whereas explanatory factors for private transport users bore insignificant results. Smartphone devices proved their potential as an effective and useful source of data in transportation and health research.
Measuring and Understanding the Effectiveness of JIRA Developers Communities

Tools for project management and issues/bugs tracking are becoming useful for governing the development process of Open Source software. Such tools simplify the communications process among developers and ensure the scalability of a project. The more information developers are able to exchange, the clearer are the goals, and the higher is the number of developers keen on joining and actively collaborating on a project. In this paper we present a preliminary empirical analysis of the communities-structure of developers in JIRA by analyzing 7 popular projects hosted in the repository. We analyze how these communities perform in terms of issue-resolution time of any given issue. The main contributions of this work are the confirmation of the existence of communities in developer networks, and the empirical finding that the issue resolution-time of any given issue is not correlated with the dimension of a developer community.
Disambiguating identity through social circles and social data

This paper presents an approach to disambiguate extracted identity information relating to different individuals through the use of social circles. Social circles are generated through the extraction and pruning of social networks using the analysis of existing social data. Social data encompasses information such as images, videos and blogs shared within a social network. Identity information is extracted by involving the user in both selecting their key identity features for disambiguation, and validating the retrieved information. Our approach provides a methodology to monitor existing identity information, applicable to addressing such issues as identity theft, online fraud and lateral surveillance.
A novel mammalian myosin I from rat with an SH3 domain localizes to Con A-inducible, F-actin-rich structures at cell-cell contacts

In an effort to determine diversity and function of mammalian myosin I molecules, we report here the cloning and characterization of myr 3 (third unconventional myosin from rat), a novel mammalian myosin I from rat tissues that is related to myosin I molecules from protozoa. Like the protozoan myosin I molecules, myr 3 consists of a myosin head domain, a single light chain binding motif, and a tail region that includes a COOH-terminal SH3 domain. However, myr 3 lacks the regulatory phosphorylation site present in the head domain of protozoan myosin I molecules. Evidence was obtained that the COOH terminus of the tail domain is involved in regulating F-actin binding activity of the NH2-terminal head domain. The light chain of myr 3 was identified as the Ca(2+)-binding protein calmodulin. Northern blot and immunoblot analyses revealed that myr 3 is expressed in many tissues and cell lines. Immunofluorescence studies with anti-myr 3 antibodies in NRK cells demonstrated that myr 3 is localized in the cytoplasm and in elongated structures at regions of cell-cell contact. These elongated structures contained F-actin and alpha-actinin but were devoid of vinculin. Incubation of NRK cells with Con A stimulated the formation of myr 3-containing structures along cell-cell contacts. These results suggest for myr 3 a function mediated by cell-cell contact.
Software mitigations to hedge AES against cache-based software side channel vulnerabilities

Hardware side channel vulnerabilities have been studied for many years in embedded silicon-security arena including SmartCards, SetTop-boxes, etc. However, because various recent security activities have goals of improving the software isolation properties of PC platforms, software side channels have become a subject of interest. Recent publications discussed cache-based software side channel vulnerabilities of AES and RSA. Thus, following the classical approach — a new side channel vulnerability opens a new mitigation research path — this paper starts to investigate efficient mitigations to protect AES-software against side channel vulnerabilities. First, we will present several mitigation strategies to harden existing AES software against cache-based software side channel attacks and analyze their theoretical protection. Then, we will present a performance and security evaluation of our mitigation strategies. For ease of evaluation we measured the performance of our code against the performance of the openSSL AES implementation. In addition, we also analyzed our code under various existing attacks. Depending on the level of the required side channel protection, the measured performance loss of our mitigations strategies versus openSSL (respectively best assembler) varies between factors of 1.35 (2.66) and 2.85 (5.83).
Use of Propensity Score Technique to Account for Exposure-Related Covariates: An Example and Lesson

Background:In observational research, propensity score techniques can be used to account for baseline differences between compared therapies. Although propensity scores are used increasingly often, their limitations in settings without complete data may not be recognized. Objectives:We sought to evaluate the ability of propensity score matching to mitigate confounding by indication in an observational study of the effect of statin therapy on acute myocardial infarction (AMI). Matching was performed at random, and with propensity scores that incorporated a reduced or expanded set of variables. Research Design/Subjects:This was a propensity score matched cohort study using members of a health insurer database. Measures:Exposure to statin therapy was assessed at the beginning of follow-up with all cohort members being statin initiators or noninitiators, and the outcome of AMI was identified on the basis of claims codes. Results:Matching on the basis of the propensity score provided results that are similar in magnitude to randomized clinical trials, suggesting that confounding was mitigated. However, matching on a propensity score created on a reduced set of variables yielded a result that suggested no effect of statin therapy, and demonstrated substantial imbalance on some variables that were not part of the propensity score. Conclusions:Propensity score matching can balance with respect to variables not explicitly included in the score, but external data are required to evaluate this.
Intent focused summarization of caller-agent conversations

In this paper, we propose a conditional random field (CRF) based to identify segments within call center conversations that convey caller intent. A distinguishing aspect of our approach is the use of context information of the intent bearing segments to predict the presence or absence of intents within various segments. The context is represented through a set of phrase features that are frequently present in and around the intent bearing segments. These phrases, identified in a data-driven manner, are used along with conventional word features in a CRF based sequence labeling framework to assign intent/non-intent labels to each utterance in a conversation. Another distinguishing aspect of our approach is that instead of using 1-best label alignment, we extract N-best label alignments at the output of CRF and combine evidences from them to rank the utterances according to their intent bearing potential, so that top ranked utterances can be chosen as the intent summary. To demonstrate the effectiveness of our approach and to evaluate the influence of automatic speech recognition (ASR) errors we evaluated our approach using manually transcribed and ASR transcribed conversations. Experimental results show improved summarization accuracy using our approach. Specifically, in 92% of the manually transcribed conversations accurate summaries of just one utterance length can be extracted using the proposed approach.
Volume Phase Transitions of Slide-Ring Gels

The volume phase transition of slide-ring gels with freely-movable cross-linking junctions was investigated. Ionic chemical gels with fixed cross-linking junctions undergo volume phase transitions when they have higher than the critical degree of ionization. However, the experimentally-observed critical ionization value for slide-ring gels is much higher than theoretical values for chemical gels. This difference indicates that the volume phase transition is significantly suppressed in slide-ring gels. The mesoscale structure at various swollen or shrunken states was also investigated by small angle X-ray scattering. Changes in the scattering patterns with shrinking slide-ring gels suggest microphase separation due to the sliding of cyclic molecules threaded along the axis of the polymer chains, which may suppress the volume phase transition. In addition, slide-ring gels absorbed/desorbed greater than equilibrium volumes in the shrinking/swelling processes and showed slow dynamics; these observations are also related to their sliding properties.
Hypoxia Induces Autophagic Cell Death through Hypoxia-Inducible Factor 1α in Microglia

As phagocytic cells of central nervous system, excessive activation or cell death of microglia is involved in a lot of nervous system injury and degenerative disease, such as stroke, epilepsy, Parkinson's disease, Alzheimer's disease. Accumulating evidence indicates that hypoxia upregulates HIF-1α expression leading to cell death of microglia. However, the exact mechanism of cell death induced by hypoxia in microglia is not clear. In the current study, we showed that hypoxia induced cell death and autophagy in microglia. The suppression of autophagy using either pharmacologic inhibitors (3-methyladenine, bafilomycin A1) or RNA interference in essential autophagy genes (BECN1 and ATG5) decreased the cell death induced by hypoxia in microglia cells. Moreover, the suppression of HIF-1α using either pharmacologic inhibitors (3-MA, Baf A1) or RNA interference decreased the microglia death and autophagy in vitro. Taken together, these data indicate that hypoxia contributes to autophagic cell death of microglia through HIF-1α, and provide novel therapeutic interventions for cerebral hypoxic diseases associated with microglia activation.
Sensitivity assessment of PM2.5 simulation to the below-cloud washout schemes in an atmospheric chemical transport model

Abstract This study analyses the sensitivity of PM2.5 simulation and source apportionment results by integrating different below-cloud washout (BCW) schemes from various models into the CAMx model during the rainy days (3–13 September 2010). Furthermore, this study has also considered the influence of different raindrop size distribution parameterizations on the simulation. PM2.5 time series, spatial maps and the average concentration of the study region using different BCW schemes are presented. Our results show that different BCW schemes can cause over 50 μg m−3 discrepancies in a PM2.5 simulation during the heavy rain periods. The source apportionment (, and ) results for some cities (e.g. Hong Kong) are also sensitive to the choice of the BCW scheme. After implementing the composition dependent BCW coefficients calculated by using the field observation data, the PM2.5 simulation performance was improved and mean bias was reduced to 0.5 μg m−3 during the study period. Future BCW studies should focus on the effects caused by aerosol compositions and raindrop size distributions in order to produce reliable simulation results for the rainy season.
Errors due to sampling frequency of the electrocardiogram in spectral analysis of heart rate signals with low variability

Spectral analysis of the heart rate signal was studied in patients with low heart rate variability regarding an error that may occur when there is a specific relation between the averaged heart rate and the sampling frequency of the electrocardiogram. ECG waveforms were recorded from healthy subjects and from patients after heart transplant, digitized with different sampling rates and analyzed for spectral analysis of heart rate variability. It was found that in healthy subjects with high heart rate variability, accurate results can be obtained when the sampling rate of the ECG is greater than 125 Hz. In heart transplant patients, up to 100% error may occur when the sampling rate is below 1 kHz. It is concluded that for spectral analysis of the heart rate signal recorded from patients that are characterized with low heart rate variability, high sampling rate of the ECG signal is necessary (1 kHz).
Hyper, a Hydrogen Peroxide Sensor, Indicates the Sensitivity of the Arabidopsis Root Elongation Zone to Aluminum Treatment

Emerging evidence indicates that some reactive oxygen species (ROS), such as the superoxide anion radical and hydrogen peroxide (H2O2), are central regulators of plant responses to biotic and abiotic stresses. Thus, the cellular levels of ROS are thought to be tightly regulated by an efficient and elaborate pro- and antioxidant system that modulates the production and scavenging of ROS. Until recently, studies of ROS in plant cells have been limited to biochemical assays and the use of fluorescent probes; however, the irreversible oxidation of these fluorescent probes makes it impossible to visualize dynamic changes in ROS levels. In this work, we describe the use of Hyper, a recently developed live cell probe for H2O2 measurements in living cells, to monitor oxidative stress in Arabidopsis roots subjected to aluminum treatment. Hyper consists of a circularly permuted YFP (cpYFP) inserted into the regulatory domain of the Escherichia coli hydrogen peroxide-binding protein (OxyR), and is a H2O2-specific ratiometric, and therefore quantitative, probe that can be expressed in plant and animal cells. Now we demonstrate that H2O2 levels drop sharply in the elongation zone of roots treated with aluminum. This response could contribute to root growth arrest and provides evidence that H2O2 is involved in early Al sensing.
Stereo vision–based depth of field rendering on a mobile device

Abstract. The depth of field (DoF) effect is a useful tool in photography and cinematography because of its aesthetic value. However, capturing and displaying dynamic DoF effect were until recently a quality unique to expensive and bulky movie cameras. A computational approach to generate realistic DoF effects for mobile devices such as tablets is proposed. We first calibrate the rear-facing stereo cameras and rectify the stereo image pairs through FCam API, then generate a low-res disparity map using graph cuts stereo matching and subsequently upsample it via joint bilateral upsampling. Next, we generate a synthetic light field by warping the raw color image to nearby viewpoints, according to the corresponding values in the upsampled high-resolution disparity map. Finally, we render dynamic DoF effect on the tablet screen with light field rendering. The user can easily capture and generate desired DoF effects with arbitrary aperture sizes or focal depths using the tablet only, with no additional hardware or software required. The system has been examined in a variety of environments with satisfactory results, according to the subjective evaluation tests.
A Novel Feature Extraction for Robust EMG Pattern Recognition

Varieties of noises are major problem in recognition of Electromyography (EMG) signal. Hence, methods to remove noise become most significant in EMG signal analysis. White Gaussian noise (WGN) is used to represent interference in this paper. Generally, WGN is difficult to be removed using typical filtering and solutions to remove WGN are limited. In addition, noise removal is an important step before performing feature extraction, which is used in EMG-based recognition. This research is aimed to present a novel feature that tolerate with WGN. As a result, noise removal algorithm is not needed. Two novel mean and median frequencies (MMNF and MMDF) are presented for robust feature extraction. Sixteen existing features and two novelties are evaluated in a noisy environment. WGN with various signal-to-noise ratios (SNRs), i.e. 20-0 dB, was added to the original EMG signal. The results showed that MMNF performed very well especially in weak EMG signal compared with others. The error of MMNF in weak EMG signal with very high noise, 0 dB SNR, is about 5-10% and closed by MMDF and Histogram, whereas the error of other features is more than 20%. While in strong EMG signal, the error of MMNF is better than those from other features. Moreover, the combination of MMNF, Histrogram of EMG and Willison amplitude is used as feature vector in classification task. The experimental result shows the better recognition result in noisy environment than other success feature candidates. From the above results demonstrate that MMNF can be used for new robust feature extraction. Index Terms—Electromyography (EMG), Feature extraction, Pattern recognition, Robustness, Man-machine interfaces. —————————— a ——————————
Empirical study of customer relationship proneness in hairdresser's context

This article discusses the influence of customer relationship proneness in hairdresser's context. Data are collected using online survey. A conceptual model about customer relationship proneness, relational benefits, customer commitment and customer loyalty is proposed to explain the influence. Structural equation modelling is used to analyze the data. Empirical results show that customer relationship proneness is directly and positively related to perception of relational benefits, customer commitment and customer loyalty. Relational benefits have significant influence on customer commitment and loyalty. The direct effect form customer commitment to customer loyalty is also confirmed.
Learning Relations by Pathfinding

First-order learning systems (e.g., FOIL, FOCL, FORTE) generally rely on hill-climbing heuristics in order to avoid the combinatorial explosion inherent in learning first-order concepts. However, hill-climbing leaves these systems vulnerable to local maxima and local plateaus. We present a method, called relational pathfinding, which has proven highly effective in escaping local maxima and crossing local plateaus. We present our algorithm and provide learning results in two domains: family relationships and qualitative model building.
Supporting Software Development with Organizational Memory Tools

Software development is no longer a homogeneous field. Software is being developed for an increasingly diverse set of applications and user populations, each with different characteristics and development constraints. As a consequence, researchers and practitioners have begun to realize the importance of identifying and understanding the characteristics and special development needs of application domains. But domain analysis methods have largely focused on identifying and isolating a domain to organize source code components. A broader view is needed that defines “domains” to be problem with similar characteristics and that captures the various knowledge needed to develop software applications, such as application domain knowledge and tips and techniques for development tools. This paper describes a software development support system for collecting, organizing, and disseminating project experiences that provides the basis for domain analysis techniques supporting the re-use of development knowledge and software artifacts. Subsequent projects benefit from these experiences by using tools to locate similar projects and reusing the knowledge accumulated in the repository. We develop a framework for a system to capture relationships between development projects and resources for developing software, including process models, methods, technologies, and tools. We then show how this information can be reused to improve the productivity and quality of software development efforts. Organizational Memory Tools Henninger -1
Structure‐function analysis of hepatocyte growth factor: identification of variants that lack mitogenic activity yet retain high affinity receptor binding.

Hepatocyte growth factor (HGF) is a potent mitogen for parenchymal liver, epithelial and endothelial cells. Structurally, it has similarities to kringle‐containing serine proteases, although it does not possess proteolytic activity. A structure‐activity relationship study of human HGF was performed by functional analysis of HGF substitution and deletion variants. Analysis of HGF variants was accomplished by defining their ability to induce DNA synthesis on hepatocytes in primary culture and to compete with wild‐type HGF for binding to a soluble form of the HGF receptor. Three groups of variants were made: (i) substitutions at the cleavage site, (ii) substitutions within the protease‐like domain and (iii) deletions of the beta‐chain and/or kringle domains. Our results show that: (i) single‐chain HGF is a zymogen‐like promitogen in that cleavage into a two‐chain form is required for biological activity, however, the single chain form of HGF still retains substantial receptor binding capacity; (ii) certain mutations in the protease‐like domain result in variants that are completely defective for mitogenic activity, yet exhibit apparent receptor binding affinities similar to wild‐type HGF (Kd approximately 50–70 pM); and (iii) a variant containing the N‐terminal 272 residues of mature HGF showed only a 4‐fold increase in Kd when compared with wild‐type HGF indicating that a primary receptor binding determinant is located within this sequence.
Evaluation of Semantic Similarity Using Vector Space Model Based on Textual Corpus

In this work, we have created a semantic similarity calculation system between text documents to contribute to their semantic clustering. Indeed, semantic clustering of documents is a promising field of research, since it guarantees a quick and targeted access to information. The aim of document clustering is to put together similar documents. We used the algebraic model VSM (Vector Space Model) [2] to represent text documents and the WordNet [1] lexical database, in that it groups words together based on their meanings. In this paper, we will present an overview of the static and semantic methods for calculating the similarity measure and the appropriateness of these methods. As our research is focusing on the treatment of text documents on e-learning systems. We worked on a corpus of a set of text documents from the computer science textbook for high school students in Morocco. To evaluate our system, an experiment has been conducted among students who produced text documents. Experimental evaluations using WordNet prove that the system presented in this work improves the accuracy of semantic similarity between the text documents.