Miracle-dz/UniFAR-FTUs huggingface dataset:
Fundamental statistical features and self-similar properties of tagged networks

We investigate the fundamental statistical features of tagged (or annotated) networks having a rich variety of attributes associated with their nodes. Tags (attributes, annotations, properties, features, etc) provide essential information about the entity represented by a given node, thus, taking them into account represents a significant step towards a more complete description of the structure of large complex systems. Our main goal here is to uncover the relations between the statistical properties of the node tags and those of the graph topology. In order to better characterize the networks with tagged nodes, we introduce a number of new notions, including tag-assortativity (relating link probability to node similarity), and new quantities, such as node uniqueness (measuring how rarely the tags of a node occur in the network) and tag-assortativity exponent. We apply our approach to three large networks representing very different domains of complex systems. A number of the tag related quantities display analogous behaviour (e.g. the networks we studied are tag-assortative, indicating possible universal aspects of tags versus topology), while some other features, such as the distribution of the node uniqueness, show variability from network to network allowing for pin-pointing large scale specific features of real-world complex networks. We also find that for each network the topology and the tag distribution are scale invariant, and this self-similar property of the networks can be well characterized by the tag-assortativity exponent, which is specific to each system.
Monitoring stress level parameters of frequent computer users

The Growth in computer technology in all the facets of the world, and life are growing to the point that everyone needs a computer to carry out their work in everyday life. While using the computer for long hours, little is cared about posture, resulting in body ache and some harmful everlasting effects on the body. Computer users can protect themselves from those health risks by implementing proper workplace design and good posture. Ergonomics is the science of designing the workplace, with respect to the capabilities and limitations of the worker. Computer vision syndrome is a term used specifically to describe vision related problems and the other symptoms caused by continuous computer use. Work stress also results in an increased risk for cardiovascular diseases. Remotely monitoring a patient's health condition is now easily possible with the use of sensors, actuators and mobile communication devices, combined together called as Internet of Things for Medical Devices. The Arduino Yun is a Microcontroller board having built-in Ethernet and Wi-Fi support and can be connected to a vast array of web-based Resource and services with the use of Temboo, a cloud-based platform with processes for APIs, databases, and more. The parameters considered under Ergonomic workspace like distance between user and computer, angle with which the computer screen should be positioned can be analysed using Ultrasonic and Accelerometer sensors; while pulse sensor to analyse heart rate under work pressure. The Microcontroller board processes the received sensor data and can alert the user through an SMS or mail to take certain precautionary measures if the desired threshold limit is not satisfied.
Content-based image retrieval in radiology: analysis of variability in human perception of similarity

Abstract. We aim to develop a better understanding of perception of similarity in focal computed tomography (CT) liver images to determine the feasibility of techniques for developing reference sets for training and validating content-based image retrieval systems. In an observer study, four radiologists and six nonradiologists assessed overall similarity and similarity in 5 image features in 136 pairs of focal CT liver lesions. We computed intra- and inter-reader agreements in these similarity ratings and viewed the distributions of the ratings. The readers’ ratings of overall similarity and similarity in each feature primarily appeared to be bimodally distributed. Median Kappa scores for intra-reader agreement ranged from 0.57 to 0.86 in the five features and from 0.72 to 0.82 for overall similarity. Median Kappa scores for inter-reader agreement ranged from 0.24 to 0.58 in the five features and were 0.39 for overall similarity. There was no significant difference in agreement for radiologists and nonradiologists. Our results show that developing perceptual similarity reference standards is a complex task. Moderate to high inter-reader variability precludes ease of dividing up the workload of rating perceptual similarity among many readers, while low intra-reader variability may make it possible to acquire large volumes of data by asking readers to view image pairs over many sessions.
Noncompact gaugings, chiral reduction and dual sigma models in supergravity

We show that the half-maximal SU(2) gauged supergravity with a topological mass term admits coupling of an arbitrary number of n vector multiplets. The chiral circle reduction of the ungauged theory in the dual 2-form formulation gives N = (1, 0) supergravity in 6D coupled to 3p scalars that parametrize the coset SO(p, 3)/SO(p) × SO(3), a dilaton and (p + 3) axions with p ⩽ n. Demanding that R-symmetry gauging survive in 6D is shown to put severe restrictions on the 7D model, in particular requiring noncompact gaugings. We find that the SO(2, 2) and SO(3, 1) gauged 7D supergravities give a U(1)R, and the SO(2, 1) gauged 7D supergravity gives an Sp(1)R gauged chiral 6D supergravity coupled to certain matter multiplets. In the 6D models obtained, with or without gauging, we show that the scalar fields of the matter sector parametrize the coset SO(p + 1, 4)/SO(p + 1) × SO(4), with the (p + 3) axions corresponding to its Abelian isometries. In the ungauged 6D models, upon dualizing the axions to 4-form potentials, we obtain coupling of p linear multiplets and one special linear multiplet to chiral 6D supergravity.
Oligomerization of a molecular chaperone modulates its activity

Molecular chaperones alter the folding properties of cellular proteins via mechanisms that are not well understood. Here, we show that Trigger Factor (TF), an ATP-independent chaperone, exerts strikingly contrasting effects on the folding of non-native proteins as it transitions between a monomeric and a dimeric state. We used NMR spectroscopy to determine the atomic resolution structure of the 100 kDa dimeric TF. The structural data show that some of the substrate-binding sites are buried in the dimeric interface, explaining the lower affinity for protein substrates of the dimeric compared to the monomeric TF. Surprisingly, the dimeric TF associates faster with proteins and it exhibits stronger anti-aggregation and holdase activity than the monomeric TF. The structural data show that the dimer assembles in a way that substrate-binding sites in the two subunits form a large contiguous surface inside a cavity, thus accounting for the observed accelerated association with unfolded proteins. Our results demonstrate how the activity of a chaperone can be modulated to provide distinct functional outcomes in the cell.
Evaluating Multipollutant Exposure and Urban Air Quality: Pollutant Interrelationships, Neighborhood Variability, and Nitrogen Dioxide as a Proxy Pollutant

Background: Although urban air pollution is a complex mix containing multiple constituents, studies of the health effects of long-term exposure often focus on a single pollutant as a proxy for the entire mixture. A better understanding of the component pollutant concentrations and interrelationships would be useful in epidemiological studies that exploit spatial differences in exposure by clarifying the extent to which measures of individual pollutants, particularly nitrogen dioxide (NO2), represent spatial patterns in the multipollutant mixture. Objectives: We examined air pollutant concentrations and interrelationships at the intraurban scale to obtain insight into the nature of the urban mixture of air pollutants. Methods: Mobile measurements of 23 air pollutants were taken systematically at high resolution in Montreal, Quebec, Canada, over 34 days in the winter, summer, and autumn of 2009. Results: We observed variability in pollution levels and in the statistical correlations between different pollutants according to season and neighborhood. Nitrogen oxide species (nitric oxide, NO2, nitrogen oxides, and total oxidized nitrogen species) had the highest overall spatial correlations with the suite of pollutants measured. Ultrafine particles and hydrocarbon-like organic aerosol concentration, a derived measure used as a specific indicator of traffic particles, also had very high correlations. Conclusions: Our findings indicate that the multipollutant mix varies considerably throughout the city, both in time and in space, and thus, no single pollutant would be a perfect proxy measure for the entire mix under all circumstances. However, based on overall average spatial correlations with the suite of pollutants measured, nitrogen oxide species appeared to be the best available indicators of spatial variation in exposure to the outdoor urban air pollutant mixture. Citation: Levy I, Mihele C, Lu G, Narayan J, Brook JR. 2014. Evaluating multipollutant exposure and urban air quality: pollutant interrelationships, neighborhood variability, and nitrogen dioxide as a proxy pollutant. Environ Health Perspect 122:65–72; http://dx.doi. org/10.1289/ehp.1306518
Induction of Endoplasmic Reticulum-Derived Replication-Competent Membrane Structures by West Nile Virus Non-Structural Protein 4B

Replication of flaviviruses (family Flaviviridae) occurs in specialized virus-induced membrane structures (IMS). The cellular composition of these IMS varies for different flaviviruses implying different organelle origins for IMS biogenesis. The role of flavivirus non-structural (NS) proteins for the alteration of IMS remains controversial. In this report, we demonstrate that West Nile virus strain New York 99 (WNVNY99) remodels the endoplasmic reticulum (ER) membrane to generate specialized IMS. Within these structures, we observed an element of the cis-Golgi, viral double-stranded RNA, and viral-envelope, NS1, NS4A and NS4B proteins using confocal immunofluorescence microscopy. Biochemical analysis and microscopy revealed that NS4B lacking the 2K-signal peptide associates with the ER membrane where it initiates IMS formation in WNV-infected cells. Co-transfection studies indicated that NS4A and NS4B always remain co-localized in the IMS and are associated with the same membrane fractions, suggesting that these proteins function cooperatively in virus replication and may be an ideal target for antiviral drug discovery.
Using startle probe to compare affect and engagement between a serious game and an online intervention program

The widespread popularity of computer games have led to their expanded use in more serious applications for training and education. In many cases serious games are being advanced as more compelling than traditional face-to-face or interactive online training. A typically reported motivation for developing serious games is to try and increase engagement of participants and thus ultimately the effectiveness of the training experience. In this paper we discuss the relation of affect to engagement. The training reported in this study relates to a psychological counseling program developed to assist patients with comorbidity in depression and alcohol use disorders. A pre-existing online intervention program, called "SHADE", had been found to provide effective treatment when participants completed the program. However, a significant number of participants failed to complete the program, with most exits occurring when Cognitive Based Training (CBT) was integrated into the online program. To try and increase the number of participants completing the program a serious game, called "Shadow" is being developed to cover similar material. This paper reports on a study that uses the startle reflex modulation measure to try and objectively quantify the affective engagement of players in the two treatment approaches, Shadow, the serious game, versus SHADE, the online intervention program. Also reported are the issues associated with using affective processing, as measured by the startle probe technique, as a means of evaluating engagement in serious games.
Impact Of Solar Irradiance Data On MPC Performance Of Multizone Buildings

Local solar irradiation data has been used for Model Predictive Control (MPC) in supervisory level building control systems, with significant influence demonstrated on perimeter building zones with a high fraction of window area. This work investigates the impact of uncertain solar estimation on MPC performance with respect to energy consumption and comfort by comparing MPC responses for a multi-zone building based on two solar data sources: measured local Plane of Array (POA) solar data and satellite Global Horizontal Irradiance (GHI) based modeled POA solar data. Hourly solar irradiation on tilted surfaces can be calculated from local or offsite GHI measurements by a common algorithm that includes an empirical correlation to decompose the beam and diffuse components, followed by the application of an anisotropic sky model. Real-time control decisions based on the modeled solar data have been found to violate comfort conditions within zones, particularly if off-site or satellite derived GHI data is employed. The presented case study results inform the value of information, revealing that MPC decisions based on satellite derived solar data cause comfort violations that depend strongly on the building system characteristics, such as HVAC and internal gains.
Madness and method in stress echo reading.

AIM To assess whether 'eye education' through short-term, high-intensity joint reading sessions may improve diagnostic accuracy and inter-observer agreement among beginners. METHODS AND RESULTS Seventeen cardiologists with absent to minimal (<100 studies performed) previous stress echo experience independently and blindly read 18 stress echo studies, nine at the beginning ('pre-training' set) and nine at the end ('post-training' set) of a 2 day stress echo school which included a joint reading session of 50 tapes. The two sets were balanced as far as type of stress and image quality. The 17 observers had an average accuracy score of 51+/-16.4 before and 64.3+/-8.7% after the training (P<0.005). Concordant (i.e. >14 readers giving the same response) interpretation occurred in three out of nine studies before and in eight out of nine studies after the training (33% vs 88%, P<0.01). Kappa values went from 0.14 (poor) before to 0.39 (fair, close to moderate) after the training. CONCLUSION Short-term, high-intensity dedicated training in stress echo, with joint reading sessions and consensus development of reading criteria significantly increased accuracy and markedly reduced the inter-observer variability in the reading of stress echoes by beginners. If there is a Shakespearean madness in stress echo reading, 'yet there is a method in't' (Hamlet, II, II, 205-206).
Cost-Effective Recruitment Strategies That Attract Underrepresented Minority Undergraduates Who Persist to STEM Doctorates

The paucity of underrepresented minorities (URMs) earning science, technology, engineering, and mathematics (STEM) degrees remains an issue in revitalizing the U.S. biomedical workforce. Due to reductions in federal funding, maintaining the integrity of programs that focus on URM retention and recruitment is crucial. We present data on the mechanisms used to recruit URM students to our program (e.g., email, events, referrals, website), which individually were equally effective in attracting applicants to the program. Recruitment mechanisms were grouped and further classified relative to their cost to implement as lower and higher cost. Our results indicate that lower cost mechanisms, statistically, were as effective as higher cost mechanisms in recruiting students who persisted to PhD programs. Using a binary logistic regression model to predict PhD matriculation, higher cost mechanisms were not significant predictors of PhD matriculation. Collectively, these data demonstrate for the first time that lower cost mechanisms can be as successful in recruiting URM students to summer programs who pursue PhDs in STEM fields.
Dynamic Time Course of Typical Childhood Absence Seizures: EEG, Behavior, and Functional Magnetic Resonance Imaging

Absence seizures are 5–10 s episodes of impaired consciousness accompanied by 3–4 Hz generalized spike-and-wave discharge on electroencephalography (EEG). The time course of functional magnetic resonance imaging (fMRI) changes in absence seizures in relation to EEG and behavior is not known. We acquired simultaneous EEG–fMRI in 88 typical childhood absence seizures from nine pediatric patients. We investigated behavior concurrently using a continuous performance task or simpler repetitive tapping task. EEG time–frequency analysis revealed abrupt onset and end of 3–4 Hz spike-wave discharges with a mean duration of 6.6 s. Behavioral analysis also showed rapid onset and end of deficits associated with electrographic seizure start and end. In contrast, we observed small early fMRI increases in the orbital/medial frontal and medial/lateral parietal cortex >5 s before seizure onset, followed by profound fMRI decreases continuing >20 s after seizure end. This time course differed markedly from the hemodynamic response function (HRF) model used in conventional fMRI analysis, consisting of large increases beginning after electrical event onset, followed by small fMRI decreases. Other regions, such as the lateral frontal cortex, showed more balanced fMRI increases followed by approximately equal decreases. The thalamus showed delayed increases after seizure onset followed by small decreases, most closely resembling the HRF model. These findings reveal a complex and long-lasting sequence of fMRI changes in absence seizures, which are not detectable by conventional HRF modeling in many regions. These results may be important mechanistically for seizure initiation and termination and may also contribute to changes in EEG and behavior.
Impact of Synthesis Constraints on Error Propagation Probability of Digital Circuits

Optimization algorithms for the synthesis of digital logic circuits have been used to automate the process of meeting design constraints like area and timing. These algorithms affect a circuit's topology and therefore its vulnerability to soft errors. This paper investigates the impact that these optimizations have on the error propagation probability of various circuit benchmarks. Results indicate that a decrease in delay and area corresponds with an increase in error propagation probability. Additionally, an increase in mapping effort corresponds to an increase in error propagation probability.
Anytime Local Search for Distributed Constraint Optimization

Most former studies of Distributed Constraint Optimization Problems (DisCOPs) search considered only complete search algorithms, which are practical only for relatively small problems. Distributed local search algorithms can be used for solving DisCOPs. However, because of the differences between the global evaluation of a system's state and the private evaluation of states by agents, agents are unaware of the global best state which is explored by the algorithm. Previous attempts to use local search algorithms for solving DisCOPs reported the state held by the system at the termination of the algorithm, which was not necessarily the best state explored. A general framework for implementing distributed local search algorithms for DisCOPs is proposed. The proposed framework makes use of a BFS-tree in order to accumulate the costs of the system's state in its different steps and to propagate the detection of a new best step when it is found. The resulting framework enhances local search algorithms for DisCOPs with the anytime property. The proposed framework does not require additional network load. Agents are required to hold a small (linear) additional space (beside the requirements of the algorithm in use). The proposed framework preserves privacy at a higher level than complete Dis-COP algorithms which make use ofa pseudo-tree (ADOPT, DPOP).
Bayes-Stein Estimation for Portfolio Analysis

Abstract In portfolio analysis, uncertainty about parameter values leads to suboptimal portfolio choices. The resulting loss in the investor's utility is a function of the particular estimator chosen for expected returns. So, this is a problem of simultaneous estimation of normal means under a well-specified loss function. In this situation, as Stein has shown, the classical sample mean is inadmissible. This paper presents a simple empirical Bayes estimator that should outperform the sample mean in the context of a portfolio. Simulation analysis shows that these Bayes-Stein estimators provide significant gains in portfolio selection problems.
Self‐Tiling Monocrystalline Silicon; a Process to Produce Electrically Connected Domains of Si and Microconcentrator Solar Cell Modules on Plastic Supports

The emerging fi elds of macro and printable electronics aim to realize large-area-integration of semiconductor devices on curved, fl exible, and inexpensive substrates. Current processes to deliver active materials include inkjet printing, parallel transfer, robotic pick-and-place, and fl uidic self-assembly. Inkjet printing is most suited to produce low performance organic semiconductors and hybrid organic/inorganic structures, while parallel transfer [ 1–4 ] and self-assembly techniques [ 5–9 ] target the integration of higher performance inorganic devices that may undergo high temperature processing on fl exible, low temperature substrates in a massively parallel fashion. Applications include fl exible [ 10 ] and curved displays, [ 8 ] curved focal plane arrays, [ 2 ] oscillators, [ 3 ] RFID tags [ 11 ] and solar cells [ 4 ] incorporating ZnO, [ 12 ] GaAs, [ 7 , 13 ] InP, [ 14 ] GaN, [ 15 , 16 ] and Si. [ 2 , 3 , 8 , 17 , 18 ]
Augmented Reality for remote education

Remote education is a new type of education mode in comparison with the conventional face-to-face education. It enables the teacher to teach students at remote sites by live broadcasting the teaching course over the network, but students usually participate in the course with the need of collaboratively referring and operating the 3D geometric models of educational objects in the live video scene of real environment. Augmented Reality (AR) technology has the potential to overcome these deficiencies and enable more natural communication between teacher and students. This paper surveys the functions of AR in education and describes a shared AR environment for remote education (ARERE) to build a typical AR-based remote education system, which overlays computer generated educational information on the live video scene of real education locale and shares the augmented video scene among all participant students, providing the opportunity for students to interactively and collaboratively participate in the AR-based study environment. The potential of ARERE is illustrated through a simulation scenario and the results prove that it yields superior quality compared to the traditional form of remote education.
A Psychoacoustic Noise Reduction Approach for Stereo Hands-Free Systems

One demand for comfortable high quality hands-free video conferencing systems is the transmission of a spatial acoustical impression. Therefore a major task is the transmission of stereo speech signals from a noisy environment. The suppression of the noise components must not corrupt the stereo effect. In this context different single channel, multi-channel and hybrid speech enhancement systems will be evaluated in this contribution. The problem of musical noise in post-filter-algorithms is addressed. Therefore a psychoacoustic masking threshold for the noise reduction algorithms is considered.