Miracle-dz/UniFAR-FTUs huggingface dataset:
Coagulation of combustion generated nanoparticles and their measurement behind vehicle engines: can they play a role as atmospheric pollutants?

Based on photoionisation mass spectrometry two types of experiments were carried out. (i) In a fast flow reactor coupled to a low pressure flame as a particle source, rate coefficients for the coagulation of primary nanoparticles were measured through variation of the reactor residence time. The results are k c (350K) = 3.5x10 -10 cm 3 /s and k c (573K) = 1.1x10 -9 cm 3 /s, i.e. very high rate coefficients. It was also shown that coagulated nanoparticles can have masses beyond 50ku, corresponding to equivalent diameters between 4 to 5nm. These particles are easily fragmented during photoionisation. (ii) Using a second and mobile photoionisation mass spectrometer equipped with a fast flow inlet system, measurements were carried out behind three different vehicle engines, a two-stroke scooter engine, a four-stroke motorbike engine and a DI (direct injection) gasoline research engine. In all cases ion signals around 1000u were found that are clearly dependent on engine conditions. In the case of the DI engine, they correlate with the smoke number. These signals cannot be explained by PAHs due to their low volatility at the respective masses. Major contributions of soot or droplet fragmentation were ruled out through additional experiments using a heated inlet line and a filter. Consequently, these signals are interpreted as fragments of coagulated nanoparticles.
Contributions to the statistical analysis of contingency tables: Notes on quasi-symmetry, quasi-independence, log-linear models, log-bilinear models, and correspondence analysis models (∗)

Cet article commence par comparer le concept de quasi-symetrie du a Henri Caussinus avec un concept parent mais different que j'appellerai la quasi-symetrie de Karl Pearson; et nous trouverons que le concept de Caussinus est preferable et plus utile que celui de Pearson. J'introduirais alors un ensemble de modeles log-bilineaires quasi symetriques qui sont plus parcimonieux que le modele de quasi-symetrie de Caussinus, et un ensemble de modeles d'analyse des correspondances quasi symetriques qui sont plus parcimonieux que le modele correspondant de Pearson; et nous etablirons que les modeles log-bilineaires quasi symetriques sont preferables et plus utiles que leurs vis-a-vis, les modeles d'analyse des correspondances quasi symetriques. Notre attention est concentree dans cet article sur le modele de quasi-symetrie de Caussinus et sur les modeles qui lui sont apparentes. En addition aux modeles mentionnes ci-dessus, nous commenterons brievement les modeles de quasi-independance, et verrons comment les modeles de quasi-independance et de quasi-symetrie peuvent etre consideres comme des precurseurs directs des modeles log-lineaires et log-bilineaires. Finalement nous etudierons la relation entre quasi-independance et quasi-symetrie; et je citerai ici, pour les lecteurs qui pourraient etre interesses, une serie particuliere d'articles concernant la quasi-independance, publies pendant une periode de trente trois ans commencant en 1961.
Estimation of GPS Carrier Phase Multipath Signals Based on Site Environment

This paper presents a method that is based on Electromagnetic Modeling (EM) technique for modelling GPS carrier phase multipath signals. A commercial software plus modules developed in-house are used for modeling and processing carrier phase multipath error parameters. Static multipath modeling experiments show that up to about 35% carrier phase errors and about 25% 3D positioning errors can be reduced.
FatMan vs. LittleBoy: Scaling Up Linear Algebraic Operations in Scale-Out Data Platforms

Linear algebraic operations such as matrix manipulations form the kernel of many machine learning and other crucial algorithms. Scaling up as well as scaling out such algorithms are highly desirable to enable efficient processing over millions of data points. To this end, we present a matrix manipulation approach to effectively scale-up each node in a scale-out data parallel platform such as Apache Spark. Specifically, we enable hardware acceleration for matrix multiplications in a distributed Spark setup without user intervention. Our approach supports both dense and sparse distributed matrices, and provides flexible control of acceleration by matrix density. We demonstrate the benefit of our approach for generalized matrix multiplication operations over large matrices with up to four billion elements. To connect the effectiveness of our approach with machine learning applications, we performed Gramian matrix computation via generalized matrix multiplications. Our experiments show that our approach achieves more than 2× performance speed-up, and up to 96.1% computation improvement, compared to a state of the art Spark MLlib for dense matrices.
The performance of a precedence-based queuing discipline

A queuing system with infinitely many servers, and with the following queuing discipline is considered: For any two jobs <italic>i</italic> and <italic>j</italic> in the system, such that <italic>i</italic> arrived later than <italic>j</italic>, there is a fixed probability <italic>p</italic> that <italic>i</italic> will have to wait for <italic>j</italic>'s execution to terminate before <italic>i</italic> starts executing. This queuing system is a very simple model for database concurrency control via “static” locking, as well as of parallel execution of programs consisting of several interdependent processes. The problem of determining the maximum arrival rate (as a function of <italic>p</italic>) that can be sustained before this system becomes unstable is studied. It is shown that this rate is inversely proportional to <italic>p</italic>, and close upper and lower bounds on the constant for the case of deterministic departures are found. The result suggests that the degree of multiprogramming of multiuser databases, or the level of parallelism of concurrent programs, is inversely proportional to the probability of conflict, and that the constant is small and known within a factor of 2. The technique used involves the computation of certain asymptotic parameters of a random infinite directed acyclic graph (dag) that seem of interest by themselves.
Adverse Event Recording and Reporting in Clinical Trials Comparing Lumbar Disk Replacement with Lumbar Fusion: A Systematic Review

Study Design Systematic review. Objectives (1) To compare the quality of adverse event (AE) methodology and reporting among randomized trials comparing lumbar fusion with lumbar total disk replacement (TDR) using established AE reporting systems; (2) to compare the AEs and reoperations of lumbar spinal fusion with those from lumbar TDR; (3) to make recommendations on how to report AEs in randomized controlled trials (RCTs) so that surgeons and patients have more-detailed and comprehensive information when making treatment decisions. Methods A systematic search of PubMed, the Cochrane collaboration database, and the National Guideline Clearinghouse through May 2015 was conducted. Randomized controlled trials with at least 2 years of follow-up comparing lumbar artificial disk replacement with lumbar fusion were included. Patients were required to have axial or mechanical low back pain of ≥3 months’ duration due to degenerative joint disease defined as degenerative disk disease, facet joint disease, or spondylosis. Outcomes included the quality of AE acquisition methodology and results reporting, and AEs were defined as those secondary to the procedure and reoperations. Individual and pooled relative risks and their 95% confidence intervals comparing lumbar TDR with fusion were calculated. Results RCTs demonstrated a generally poor description of methods for assessing AEs. There was a consistent lack of clear definition or grading for these events. Furthermore, there was a high degree of variation in reporting of surgery-related AEs. Most studies lacked adequate reporting of the timing of AEs, and there were no clear distinctions between acute or chronic AEs. Meta-analysis of the pooled data demonstrated a twofold increased risk of AEs in patients having lumbar fusion compared with patients having lumbar TDR at 2-year follow-up, and this relative risk was maintained at 5 years. Furthermore, the pooled data demonstrated a 1.7 times greater relative risk of reoperation in the fusion group compared with lumbar TDR, although this risk decreased to 1.1 at 5-year follow-up. However, given the lack of quality and consistency in the methods of recording and reporting of AEs, we are unable to make a clear recommendation of one treatment over the other. Conclusions Based on the currently available literature, lumbar TDR appears to be comparable in safety to lumbar fusion. However, due to lack of consistency in reporting of AEs, it is difficult to make conclusions regarding the true safety profile of lumbar TDR. Standardization in AE reporting will significantly improve the reliability of the current literature.
Ca II Triplet Spectroscopy of Giants in Small Magellanic Cloud Star Clusters: Abundances, Velocities, and the Age-Metallicity Relation

We have obtained spectra at the Ca II triplet of individual red giants in seven Small Magellanic Cloud (SMC) star clusters whose ages range from ∼4 to 12 Gyr. The spectra have been used to determine mean abundances for six of the star clusters to a typical precision of 0.12 dex. When combined with existing data for other objects, the resulting SMC age-metallicity relation is generally consistent with that for a simple model of chemical evolution, scaled to the present-day SMC mean abundance and gas mass fraction. Two of the clusters (Lindsay 113 and NGC 339), however, have abundances that are ∼0.5 dex lower than that expected from the mean age-metallicity relation. It is suggested that the formation of these clusters, which have ages of ∼5 Gyr, may have involved the infall of unenriched gas, perhaps from the Magellanic Stream. The spectra also yield radial velocities for the seven clusters. The resulting velocity dispersion is 16 ± 4 km s-1, consistent with those of the SMC planetary nebula and carbon star populations.
Remote sensing for evaluating crop water stress at field scale using infra-red thermography : potential and limitations

Over the past few decades, the competition for freshwater resources has substantially increased in arid/semi-arid areas, exacerbating the pressure on the largest user of water, namely agriculture, to consume less water. However, reducing crop consumptive water use or evapotranspiration through water stress can have a negative impact on production economics if not precisely managed. Remote sensing of crop canopy temperature is a scientifically-based and easy-to-apply method that can be used at field scales to evaluate crop water status at or near real-time. In this study, thermal images of maize canopy under two deficit irrigation regimes were acquired using a hand-held thermal camera. The results showed that the low-frequency deficit irrigation treatment resulted in higher maize temperatures compared to the high-frequency deficit irrigation regime. A methodology for converting the temperature value of each pixel into a spatially variable crop water stress index (CWSI) is described. Within the low-frequency deficit irrigation treatment, estimated CWSI values were correlated with spatial variations in soil texture. Finally, the potential of infrared thermography and current limitations are discussed in detail.
Characterizing and Predicting Activity in Semantic MediaWiki Communities

Semantic MediaWikis represent shared and discretionary databases that allow a community of contributors to capture knowledge and to specify semantic features, such as properties for articles, relationships between articles, or concepts that filter articles for certain property values. Today, Semantic MediaWikis have received a lot of attention by a range of different groups that aim to organize an array of different subjects and domain knowledge. However, while some Semantic MediaWiki projects have been thriving, others have failed to reach critical mass. We have collected and analyzed a total of 79 publicly available Semantic MediaWiki instances to learn more about these projects and how they differ from each other. Further, we conducted an empirical analysis using critical mass theory on Semantic MediaWiki communities to investigate whether activity or the number of registered users (or a mixture of both) are important for achieving critical mass. In addition, we conduct experiments aiming to predict user activity and the number of registered users at certain points in time. Our work provides new insights into Semantic MediaWiki communities, how they evolve and first insights into how they can be studied using critical mass theory.
Auto-Pipe: Streaming Applications on Architecturally Diverse Systems

Architecturally diverse systems can improve streaming application performance by orders of magnitude, albeit with enormous programmer effort. To simplify the programming of such systems, we have constructed the Auto-Pipe application development environment, which supports the flexible mapping of application components onto computational resources and the automatic delivery of data between these computational resources. In addition to the computational finance application, Auto-Pipe has been used to implement applications ranging from cryptography to astrophysics. Auto-Pipe currently supports applications deployed on chip multiprocessors and FPGAs, and we are expanding its scope to include graphics engines.
On the simulation of multi-path vectorial channels for the evaluation of antenna array systems

We present a new computationally efficient time-varying multi-path vectorial channel simulator that can be used to evaluate the performance of antenna array wireless receivers challenged by fast fading. The development of the simulator is based on the emulation of the spatio-temporal correlation properties of the vector channel. The channel is modeled as a multi-channel FIR system with time-varying coefficients which are obtained via the application of a space-time correlation shaping transformation on some, independent random sequences. The various parts of the new simulator are described and chained simulation realizations are presented and commented on.
Does the European country-specific context alter the fatherhood premium?

This paper contributes to the discussion on the effects of childbearing on fathers’ labour market opportunities in Europe. We use instrumental variable models and data from EU-SILC to examine the cross-country variation in the causal effects of family size on the labour market outcomes of fathers. We provide an overview of the impact of family size on the employment careers of fathers, as measured on a range of dimensions: the probability of work, the number of working hours, the job rank and level of pay, and the degree of job stability based on the type of employment contract. Our findings indicate that men increase their number of working hours and earnings in response to having more children, but that the stability of men’s employment contracts does not change. These effects are prevalent across all European countries, but they are somewhat stronger in more conservative societies in which men are expected to be the main breadwinners, and they are weaker in egalitarian societies in which men are expected to participate in household and family duties.
Fast Metric Acquisition with Mobile Devices

We present a novel algorithm for fast metric reconstruction on mobile devices using a combination of image and inertial acceleration data. In contrast to previous approaches to this problem, our algorithm does not require a long acquisition time or intensive data processing and can be implemented entirely on common IMU-enabled tablet and smartphones. The method recovers real world units by comparing the acceleration values from the inertial sensors with the ones inferred from images. In order to cope with IMU signal noise, we propose a novel RANSAC-like strategy which helps to remove the outliers. We demonstrate the effectiveness and the accuracy of our method through an integrated mobile system returning point clouds in metric scale.
A Tractable Class of σ-stable Poisson-Kingman Processes and an Effective Marginalized Sampler

We explore the use of a class of random probability measures, which we refer to as the Q class, for Bayesian nonparametric mixture modeling. This class of processes encompasses both the normalised generalised gamma and the two-parameter Poisson-Dirichlet processes allowing us to comparatively study the inferential advantages of these two processes. We propose novel marginal and conditional characterisations which allow for the development of tractable inference algorithms for the whole class. Using these characterisations we develop an efficient marginal sampler which can be used for posterior simulation in the mixture model framework. We demonstrate the efficacy of our modeling framework and sampler on both one and multidimensional data sets.
Continuous Driver Intention Recognition with Hidden Markov Models

The most common cause of accidents in individual road traffic is human failure. Accidents often arise from misbehavior of one or several drivers when inducing a driving manoeuvre. Dangers can occur either when the intented manoeuvre is not well adjusted to the current traffic situation, or when the manoeuvre is not properly announced to the environment so that the intention is misinterpreted. When designing advanced driver assistance systems, it is beneficial to gather information about driver behaviors as accurately and early as possible. This work investigates early driver intention inference with hidden Markov models by observing easily accessible vehicle and environment signals such as pedal positions or global vehicle position on a digital map in real traffic.
Health Information Text Characteristics

Millions of people search online for medical text, but these texts are often too complicated to understand. Readability evaluations are mostly based on surface metrics such as character or words counts and sentence syntax, but content is ignored. We compared four types of documents, easy and difficult WebMD documents, patient blogs, and patient educational material, for surface and content-based metrics. The documents differed significantly in reading grade levels and vocabulary used. WebMD pages with high readability also used terminology that was more consumer-friendly. Moreover, difficult documents are harder to understand due to their grammar and word choice and because they discuss more difficult topics. This indicates that we can simplify many documents by focusing on word choice in addition to sentence structure, however, for difficult documents this may be insufficient.
Laser-based detection and tracking of multiple people in crowds q

Laser-based people tracking systems have been developed for mobile robotic, and intelligent surveillance areas. Existing systems rely on laser point clustering method to extract object locations. However, for dense crowd tracking, laser points of different objects are often interlaced and undistinguishable due to measurement noise and they can not provide reliable features. It causes current systems quite fragile and unreliable. This paper presents a novel and robust laser-based dense crowd tracking method. Firstly, we introduce a stable feature extraction method based on accumulated distribution of successive laser frames. With this method, the noise that generates split and merged measurements is smoothed away and the pattern of rhythmic swing legs is utilized to extract each leg of persons. And then, a region coherency property is introduced to construct an efficient measurement likelihood model. The final tracker is based on the combination of independent Kalman filter and Rao-Blackwellized Monte Carlo data association filter (RBMC-DAF). In real experiments, we obtain raw data from multiple registered laser scanners, which measure two legs for each people on the height of 16 cm from horizontal ground. Evaluation with real data shows that the proposed method is robust and effective. It achieves a significant improvement compared with existing laser-based trackers. In addition, the proposed method is much faster than previous works, and can overcome tracking errors resulted from mixed data of two closely situated persons. 2006 Elsevier Inc. All rights reserved.
Matched multiwindow methods for the estimation and filtering of nonstationary processes

The short-time Fourier transform (STFT) and its squared magnitude, the spectrogram, are classical tools for linear and quadratic time-frequency signal representation. The choice of the STFT window entails a well-known duration-bandwidth tradeoff. Multi-window methods, as originally introduced by Thompson for spectrum estimation, help to overcome this tradeoff at the cost of a more complicated concept. The present paper extends multiwindow methods from spectral estimation to filtering of nonstationary processes. By using the Kohn-Nirenberg correspondence, new results about STFT-based filter design are obtained. For quasistationary processes with small product of temporal and spectral correlation width (underspread processes), it is shown that one and the same set of orthogonal windows is appropriate for both the estimation and the nonstationary Wiener filtering. This fact makes the present theory suitable to a numerically efficient, parallel concept for on-line signal enhancement.
Mean shift face tracking with dynamic target model update using Bayesian skin classifier

Mean shift based face tracking is able to track face nicely under controlled conditions. It usually fails when there is noise and rapid illumination variations over face. The main reason for failure is that mean shift employs fixed histogram based target model representation. In this paper we present a novel technique of continuously updating the target model histogram for more robust mean shift based face tracking using a Bayesian skin classifier. We used Bayesian skin classifier to learn new skin color features from face templates in successive frames. The classifier use likelihood ratio for extracting new skin color features from each new face template. The Bayesian skin classifier had been used mainly for detection of skin parts in images but we extend this idea to continuously update the target model histogram with learned features to accommodate the dynamics of pose change and illumination in a video sequence for more robust face tracking.
Watermarking Scheme Based on DCT and DHT

A new watermarking scheme based on DCT and DHT is presented. First,the host image is transformed as a whole by DCT. Second, the low and middle frequency region of the coefficient matrix is transformed by DHT. At last the watermarking image is embedded into the region of the DHT coefficient block. The experimental results show that the scheme is easy to be realized and the embedded watermark is effectively robust against various image processing operations such as JPEG lossy compression, noise, cropping, scaling, filtering etc.
Anti-phase coupled bistable transducers: A review of recent progress

This paper provides an overview of the state of the art and the progress of novel nonlinear behaviors in MEMS devices useful as wide-band vibration energy harvesters, power converters, integrated signal conditioning circuits and filters. Remarkable progress has been made in the field of nonlinear systems and integrated coupled structures, in particular a novel family of device named anti-phase bistable architecture has been developed and patented by authors, here a brief overview will be provided and several aspects, such methodologies and microscale fabrication based on PZT layers, will be exploited.