Miracle-dz/UniFAR-FTUs huggingface dataset:
Preparation of Homogeneous Nb-Al Intermetallic Compound Sheet by Multi-Layered Rolling and Subsequent Heat Treatment

The intermetallic compound Nb3Al is widely investigated because of its high temperature strength, superior superconductivity and relatively small density. As Nb3Al has an extremely high melting point and lack of deformability, it is impossible to prepare it by using the conventional metallurgy. In this study, a Nb-Al intermetallic compound was prepared by multi-layered roll-bonding of elemental Nb and Al foils. The process consisted of the accumulative roll-bonding (ARB) for making a laminated Nb/Al sheet and the subsequent heat treatment promoting a solid-phase reaction in the laminated Nb/Al sheet. Accumulated foils were roll-bonded at 573 K. The rolling reduction at 1 pass was ~50%, and the final rolling reduction at 4 passes was ~94%. A pulsed electric current sintering (PECS) process was used for the subsequent heat treatment. The microstructures produced at each processing stage were characterized by X-ray diffraction (XRD), optical microscopy and scanning electron microscopy (SEM) equipped with energy-dispersive X-ray spectroscopy (EDS). A homogeneous intermetallic compound of Nb3Al could be obtained after the subsequent heat treatment for 1.8 ks at 873 K and for 0.9 ks at 1673 K.
Temporally Aligned Segmentation and Clustering (TASC) of Behavioral Time Series

Behavior consists of a series of repeating yet variable discrete motifs across various timescales. We introduce a framework for temporally aligned segmentation and clustering (TASC) of behavioral time series. TASC is designed to extract such motif recurrences in high temporal resolution. This framework operates iteratively in two steps: (1) embedding of time series segments and calculation of linearly aligned distances within the clustered space, and (2) recalculating of the clustered space after alignment. We evaluated TASC on a semi-synthetic experimental and a clinical dataset, and it demonstrated enhanced segmentation performance. TASC may be applied to other domains where analysis of recurring time series patterns with high temporal precision is needed.Clinical Relevance: This framework enables identifying the temporal structure of discrete pathological behaviors, such as tics properties in Tourette’s syndrome.
Robust Semi-Supervised Classification for Multi-Relational Graphs

Graph-regularized semi-supervised learning has been used effectively for classification when (i) instances are connected through a graph, and (ii) labeled data is scarce. If available, using multiple relations (or graphs) between the instances can improve the prediction performance. On the other hand, when these relations have varying levels of veracity and exhibit varying relevance for the task, very noisy and/or irrelevant relations may deteriorate the performance. As a result, an effective weighing scheme needs to be put in place. In this work, we propose a robust and scalable approach for multi-relational graph-regularized semi-supervised classification. Under a convex optimization scheme, we simultaneously infer weights for the multiple graphs as well as a solution. We provide a careful analysis of the inferred weights, based on which we devise an algorithm that filters out irrelevant and noisy graphs and produces weights proportional to the informativeness of the remaining graphs. Moreover, the proposed method is linearly scalable w.r. t. the number of edges in the union of the multiple graphs. Through extensive experiments we show that our method yields superior results under different noise models, and under increasing number of noisy graphs and intensity of noise, as compared to a list of baselines and state-of-the-art approaches.
Relationship between oxidative stress and apoE phenotype in Alzheimer's disease

Objective– To investigate the relationship between oxidative stress and apoE phenotype in dementia of Alzheimer type (DAT). Material and methods– Hydroxyl radical content in blood, superoxide dismutase (SOD) activity in red blood cells (RBC) and plasma, Cu,Zn‐SOD protein content in RBC, and apoE phenotype were determined in 24 DAT patients and 25 controls. Results– DAT patients with the apoE4 phenotype showed higher hydroxyl radical levels than DAT patients without the apoE4 phenotype or controls. SOD activities and Cu,Zn‐SOD protein levels in RBC of DAT patients with and without the apoE4 phenotype showed no significant differences, but values in both patient groups were lower than in controls. The apoE4 phenotype was more prevalent in DAT patients than in controls. DAT patients with the apoE4 phenotype were younger at disease onset than DAT patients without the apoE4 phenotype. Conclusion– Our findings suggest that apoE4 and SOD individually influence oxidative stress in DAT.
Motion estimation for cardiac emission tomography by optical flow methods

This paper describes a new method for estimating the 3D, non-rigid object motion in a time sequence of images. The method is a generalization of a standard optical flow algorithm that is incorporated into a successive quadratic approximation framework. The method was evaluated for gated cardiac emission tomography using images obtained from a mathematical, 4D phantom and a physical, dynamic phantom. The results showed that the proposed method offers improved motion estimation accuracy relative to the standard optical flow method. Convergence of the proposed algorithm was evidenced with a monotonically decreasing objective function value with iteration. Practical application of the motion estimation method in cardiac emission tomography includes quantitative myocardial motion estimation and 4D, motion-compensated image reconstruction.
Multi-walled carbon nanotube filled polypropylene nanocomposites based on masterbatch route: Improvement of dispersion and mechanical properties through PP-g-MA addition

Multi-wall carbon nanotubes (MWNTs) filled polypropylene (PP) nanocomposites were prepared through dilut- ing a PP/MWNT masterbatch in a PP matrix by melt compounding with a twin screw extruder. Polypropylene grafted maleic anhydride (PP-g-MA) was used to promote the carbon nanotubes dispersion. The effect of PP-g-MA addition on the rheological, mechanical and morphological properties of the nanocomposites was assessed for different MWNTs loadings. Scanning electron microscopy (SEM) has shown that nanotubes are distributed reasonably uniformly. A better dispersion and good adhesion between the nanotubes and the PP matrix is caused by wrapping of PP-g-MA on MWNTs. When PP-g- MA is added, dynamic moduli and viscosity further increases compared to PP/MWNT nanocomposites. The rheological percolation threshold drops significantly. Tensile and flexural moduli and Charpy impact resistance of the nanocomposites also increases by the addition of PP-g-MA. The present study confirms that PP-g-MA is efficient to promote the dispersion of MWNTs in PP matrix and serves as an adhesive to increase their interfacial strength, hence greatly improving the rheo- logical percolation threshold and mechanical properties of PP/MWNT nanocomposites.
3D segmentation of forest structure using an adaptive mean shift based procedure

Plant communities display a vertical structure based on the size and growth pattern of the dominant species. To a large extent, this pattern, called vertical stratification, depends on the climatic zone. Vertical structure analysis consists in detecting the number of layers and their limits within a forest stand. So far, there is a lack of robust approaches applied to airborne laser scanning (ALS) data that properly segment the different strata of forests having complex structures. In this study, we propose a procedure to characterize vertical forest stratification based on the mean shift (MS) algorithm. The MS is a non-linear filter that searches for local density maxima (modes). It is a non-parametric and unsupervised approach, which only requires a single criterion, the kernel bandwidth. Since the forest point cloud is a multi-modal distribution, the MS is used to find the modes which are supposed to be the barycenters of vegetation features. Once achieved, the modes are grouped together according to height range and the corresponding ALS points are assigned to each vegetation strata. Due to their complex pattern, using a single scale over the whole space is not recommended for the analysis of such environments. On this basis, the modes are computed using a variable kernel bandwidth according to the forest pattern. To depict such a pattern, we propose a new technique that segments the main forest layers at the plot level: overstory, understory, and surface vegetation. The procedure has been carried out on 45 plots of a Portuguese forest mainly composed of eucalyptus (Eucalyptus globulus) and pine (Pinus pinaster) trees that can be strongly populated by understory and surface vegetation. Email: antonio.ferraz@ign.fr
Enabling Polyvocality in Interactive Documentaries through "Structural Participation"

Recent innovations in online, social and interactive media have led to the emergence of new forms of documentary, such as interactive documentaries ('i-Docs'), with qualities that lend themselves to more open and inclusive production structures. Still, little is known about the experience of making and/or participating-in these kinds of documentary. Our two-year in-the-wild study engaged a large community-of-interest in the production of an i-Doc to explore the ethically-desirable yet challenging aim of enabling multiple subjects to have agency and control over their representation in a documentary. Our study reveals insights into the experiences of participating in an i-Doc and highlights key sociotechnical challenges. We argue that new sociotechnical infrastructure is needed, that frames both "executory" and "structural" forms of participation as symbiotic elements of a co-design process.
Development of Anti-Loosening Nuts Using Shape Memory Alloys

A new kind of self-locking nuts which can prevent the fastener from loosening is developed using shape memory alloy The transverse clamping force of SMA nuts on bolts caused by shape memory effect will always exist in the fastener, which can prevent it from vibrational loosening A simplified method is proposed to estimate the loosening moment of the SMA nuts on the bolts. Comparison experiments on the conventional steel and SMA nuts were carried out on a vibration rig. Results show that the SMA nuts have good anti-loosening capability.
Effect of Ultra-Fast Cooling after Rolling in Stable Austenite Region on Grain Refinement of C-Mn Steel

Ferrite grain refinement by hot rolling mostly above Ae3 being followed by an ultra-fast cooling has been investigated. An emphasis has been paid on the interval, Δt, between the finish of rolling and the start of water spray cooling of which cooling rate is more than 1000 °C·s-1. When Δt was nearly equal to zero, ultra-fine ferrite of about 1 or 2 μm in grain diameter was obtained for 1.2 to 1.3 mm thick 0.1%C-1%Mn steel sheets near sheet surfaces or in thickness center regions respectively, although the grain size at Δt of 0.5 s was about 3 μm in both regions. The ferrite grains were almost equiaxed and surrounded by high angle boundaries. This grain refinement is likely to be caused by an increased number of nucleation sites for the transformation from austenite to ferrite due to the ultra-fast cooling. Such a grain refinement mechanism is discussed in terms of prior-austenite structures deduced by the misorientation distribution function analysis.
Dyeing Property of Bamboo Leaves Extract on Hemp and Ramie Fiber

Bamboo leaves, as natural dye provide unartificial fresh green, are known for expert property at anti-bacterial, anti-aging, anti-oxidation, skin whitening, moisturizing, peeling of horny, deodorizing and some skin disease like as eczema and inflammation without any allergic response. Also, It is quite common to obtain bamboo leaves from our surrounding but most of them were not in use. On purpose of development the way of recycle with common material to dye, bamboo leaves were used to dye on ramie fiber which is valuable for both of apparel and industrial field and investigated their dyeing property. Using extract from bamboo leaves, dyeing property was examined with dyeability, colorimetric property, light fastness and wash fastness under different conditions by extract density, dyeing time, dyeing method and mordants. As results, dyeing was generally colored in yellowish, K/S Value was shown more higher on hemp fiber than ramie. The most optimum dyeing condition was investigated on pre-mordant treatment, dyeing temperature , dyeing time 30min and extract density 400%. On the treatment with mordant(Al, Fe, Cu), dyebility on both of hemp and ramie fiber were increased by mordant. Especially with Copper(Cu) as mordant, dyebility was highly increased than any other mordants and dyeings showed in deep color. Also on the fastness test which is the most important to natural dyeing, wash-fastness showed good performance with 4-5 grade but light-fastness was above 4 grade on both of hemp and ramie fiber, lower than wash-fastness overall.
Individual survival curves comparing subjective and observed mortality risks

We compare individual survival curves constructed from objective (actual mortality) and elicited subjective information (probability of survival to a given target age). We develop a methodology to estimate jointly subjective and objective individual survival curves accounting for rounding on subjective reports of perceived survival. We make use of the long follow-up period in the Health and Retirement Study and the high quality of mortality data to estimate individual survival curves that feature both observed and unobserved heterogeneity. This allows us to compare objective and subjective estimates of remaining life expectancy for various groups and compare welfare effects of objective and subjective mortality risk using the life cycle model of consumption. We find that subjective and objective hazards are not the same. The median welfare loss from misperceptions of mortality risk when annuities are not available is 7% of current wealth at age 65 whereas more than 25% of respondents have losses larger than 60% of wealth. When annuities are available and exogenously given, the welfare loss is substantially lower.
Antibody Prevalence and Isolation of Viable Toxoplasma gondii from Raptors in the Southeastern USA

Abstract Raptors are good indicators of the prevalence of Toxoplasma gondii in the environment because they prey on small mammals and birds. These prey species are a major source of infection in domestic cats (Felis catus), which shed the environmentally resistant oocysts. We assessed T. gondii infection in 281 opportunistically available raptors at a rehabilitation facility between 2012 and 2014. Antibodies to T. gondii were assayed by a modified agglutination test (cutoff 1:25) and found in serum of 22/71 Red-tailed Hawks (Buteo jamaicensis), 25/54 Barred Owls (Strix varia), 9/41 Red-shouldered Hawks (Buteo lineatus), 13/28 Great Horned Owls (Bubo virginianus), 6/20 Broad-winged Hawks (Buteo platypterus), 2/16 Eastern Screech Owls (Megascops asio), 12/13 Bald Eagles (Haliaeetus leucocephalus), 6/12 Cooper's Hawks (Accipiter cooperii), 1/8 Black Vultures (Coragyps atratus), and 1/1 Golden Eagle (Aquila chrysaetos). Antibodies were not detected in 5 Barn Owls (Tyto alba), 3 American Kestrels (Falco sparverius), 1 Mississippi Kite (Ictinia mississippiensis), and 1 Osprey (Pandion haliaetus). Viable T. gondii was isolated from the tissues of 1 antibody-positive Barred Owl and identified as a strain having type II alleles at all 10 loci tested, except one (ToxoDB polymerase chain reaction–restriction fragment length polymorphism genotype 3). Type II strain is the most common strain in the US. Results of this study indicate a high prevalence of T. gondii in some raptor species and the first reported genotyping from a Barred Owl.
Incremental Multi-Source Recognition with Non-Negative Matrix Factorization

This master's thesis is dedicated to incremental multi-source recognition using non-negative matrix factorization. A particular attention is paid to providing a mathematical framework for sparse coding schemes in this context. The applications of non-negative matrix factorization problems to sound recognition are discussed to give the outlines, positions and contributions of the present work with respect to the literature. The problem of incremental recognition is addressed within the framework of non-negative decomposition, a modified non-negative matrix factorization scheme where the incoming signal is projected onto a basis of templates learned off-line prior to the decomposition. As it appears that sparsity is one of the main issue in this context, a theoretical approach is followed to overcome the problem. The main contribution of the present work is in the formulation of a sparse non-negative matrix factorization framework. This formulation is motivated and illustrated with a synthetic experiment, and then addressed with convex optimization techniques such as gradient optimization, convex quadratic programming and second-order cone programming. Several algorithms are proposed to address the question of sparsity. To provide results and validations, some of these algorithms are applied to preliminary evaluations, notably that of incremental multiple-pitch and multiple-instrument recognition, and that of incremental analysis of complex auditory scenes. Cette thèse de master est dédiée à la factorisation en matrices non-négatives pour la reconnaissance incrémentale multi-source. Une attention toute particulière est attachée à fournir un cadre mathématique pour contrôler la parcimonie dans ce contexte. Les applications des problèmes de factorisation en matrices non-négatives à la reconnaissance des sons sont discutées pour dessiner les grandes lignes ainsi que la position et les contributions du présent travail par rapport à la littérature. Le problème de la reconnaissance incrémentale est attaqué dans un cadre de décomposition non-négative, une modification du problème standard de factorisation en matrices non-négatives où le signal est projeté sur une base de modèles apprise avant la dé-composition. La question de parcimonie ressortant comme l'un des principaux problèmes dans ce contexte, elle est abordée par une approche théorique. La contribution principale de ce travail consiste en la formulation d'un cadre de factorisation parcimonieuse en matrices non-négatives. Cette formulation est motivée et illustrée par une expérience synthétique, et approchée par des techniques d'optimisation convexe comme l'optimisation par gradient, la programmation quadratique convexe et la programmation conique de second ordre. Plusieurs algorithmes sont proposés pour attaquer le problème de la parcimonie. Des résultats et validations sont pro-posés …
Using Component Metadata to Regression Test Component-based Software * Based on " Using Component Metacontents to Support the Regression Testing of Component-based Software "

Increasingly, modern-day software systems are being built by combining externally-developed software components with application-specific code. For such systems, existing program-analysis-based software-engineering techniques may not directly apply, due to lack of information about components. To address this problem, the use of component metadata has been proposed. Component metadata are metadata and metamethods provided with components, that retrieve or calculate information about those components. In particular, two component-metadata-based approaches for regression test selection are described: one using code-based component metadata and the other using specification-based component metadata. The results of empirical studies that illustrate the potential of these techniques to provide savings in re-testing effort are provided.
The impact of residential broadband traffic on Japanese ISP backbones

This paper investigates the effects of the rapidly-growing residential broadband traffic on commercial ISP backbone networks. We collected month-long aggregated traffic logs for different traffic groups from seven major ISPs in Japan in order to analyze the macro-level impact of residential broad-band traffic. These traffic groups are carefully selected to be summable, and not to count the same traffic multiple times.Our results show that (1) the aggregated residential broad-band customer traffic in our data exceeds 100Gbps on average. Our data is considered to cover 41% of the total customer traffic in Japan, thus we can estimate that the total residential broadband traffic in Japan is currently about 250Gbps in total. (2) About 70% of the residential broadband traffic is constant all the time. The rest of the traffic has a daily fluctuation pattern with the peak in the evening hours. The behavior of residential broadband traffic deviates considerably from academic or office traffic. (3) The total traffic volume of the residential users is much higher than that of office users, so backbone traffic is dominated by the behavior of the residential user traffic. (4) The traffic volume exchanged through domestic private peering is comparable with the volume exchanged through the major IXes. (5) Within external traffic of ISPs, international traffic is about 23% for inbound and about 17% for outbound. (6) The distribution of the regional broadband traffic is roughly proportional to the regional population.We expect other countries will experience similar traffic patterns as residential broadband access becomes widespread.
Adaptively Exploring Population Mobility Patterns in Flow Visualization

Thanks to the ubiquitous cell phone use, we have never been so close to uncover population mobility patterns in urban area. While some researches utilize cellphone call records to mine population patterns, few works aim to depict population movement in adaptively spatial and temporal representations, i.e., from a community, a district in the city over an hour, a day to a week. In this paper, we construct a system which deciphers, transforms, queries, and visualizes the records from the millions of users in a city. In particular, we design a data structure, namely MobiHash, which collects phone call records over base stations and indexes them by utilizing a Voronoi division of the urban space. MobiHash supports responsive data queries so that users can interactively retrieve trajectories reflecting population flows in areas of interest. Moreover, population movement is represented as vector fields to reduce visual clutter and occlusions. Because of sparse moving points, a novel radiation model is proposed to interpolate population passing zones. Case studies and experts’ feedback validate the utility and efficiency by comparing population moving patterns in different times by using our system.