Miracle-dz/UniFAR-FTUs huggingface dataset:
Hot rolling bonded multilayered composite steels and varied tensile deformation behaviour

Abstract Multilayered metal composites consisting of alternating metals or alloys have been well developed to obtain the superior mechanical properties different from those in any of the constituent materials. The layer integrated steel and metals research project sponsored by Japan government started from 2006 and aimed to fabricate steel sheets with high strength (>1200 MPa) and superior elongation (>20%), through the composite design of high strength steels and ductile steel layers. In the present work, two kinds of hot rolling bonded multilayered composites consisting of austenitic stainless steel/bainite (martensite) steel are focused. The effects of hot rolled microstructure and the annealed microstructure on the tensile behaviour of a 25-layer laminated composite steel are discussed. On the other hand, the tensile deformation microstructure of the hot rolling bonded and annealed 15-layer composite steel is systematically investigated in order to find the reason for the enhanced plasticity of the brittle layer in the composite.
Distributed learning of multilingual DNN feature extractors using GPUs

Multilingual deep neural networks (DNNs) can act as deep feature extractors and have been applied successfully to crosslanguage acoustic modeling. Learning these feature extractors becomes an expensive task, because of the enlarged multilingual training data and the sequential nature of stochastic gradient descent (SGD). This paper investigates strategies to accelerate the learning process over multiple GPU cards. We propose the DistModel and DistLang frameworks which distribute feature extractor learning by models and languages respectively. The time-synchronous DistModel has the nice property of tolerating infrequent model averaging. With 3 GPUs, DistModel achieves 2.6× speed-up and causes no loss on word error rates. When using DistLang, we observe better acceleration but worse recognition performance. Further evaluations are conducted to scale DistModel to more languages and GPU cards.
Determining Presence, Thickness, and Electrical Properties of Stratified Media Using Swept-Frequency Radar

Abstract : The ability of swept-frequency radar system operating under field conditions to detect the presence and measure the thickness of layered substrata and to determine the electrical properties of the materials in these substrata was studied. Reflectivity on sections of asphaltic concrete pavement structures (i.e. asphalt highway) of various subsurface layer thicknesses was measured by a specially designed microwave system operating over the frequency range of 0.25 to 8.0 GHz at perpendicular incidence. Test results indicated that swept-frequency radar measurements can be used to estimate power reflectance from the surface material of highway structures and to determine the amplitude of the subsurface contribution.
Experimental investigation of the governing parameters in the electrospinning of poly(3-hydroxybutyrate) scaffolds : structural characteristics of the pores

We sought to determine the impact of electrospinning parameters on a trustworthy criterion that could evidently improve the maximum applicability of fibrous scaffolds for tissue regeneration. We used an image analysis technique to elucidate the web permeability index (WPI) by modeling the formation of electrospun scaffolds. Poly(3-hydroxybutyrate) (P3HB) scaffolds were fabricated according to predetermined conditions of levels in a Taguchi orthogonal design. The material parameters were the polymer concentration, conductivity, and volatility of the solution. The processing parameters were the applied voltage and nozzle-to-collector distance. With a law to monitor the WPI values when the polymer concentration or the applied voltage was increased, the pore interconnectivity was decreased. The quality of the jet instability altered the pore numbers, areas, and other structural characteristics, all of which determined the scaffold porosity and aperture interconnectivity. An initial drastic increase was observed in the WPI values because of the chain entanglement phenomenon above a 6 wt % P3HB content. Although the solution mixture significantly (p < 0.05) changed the scaffold architectural characteristics as a function of the solution viscosity and surface tension, it had a minor impact on the WPI values. The solution mixture gained the third place of significance, and the distance was approved as the least important factor.
Selective Scan Slice Grouping Technique for Efficient Test Data Compression

This paper presents a selective scan slice grouping technique for test data compression. In conventional selective encoding methods, the existence of a conflict bit contributes to large encoding data. However, many conflict bits are efficiently removed using the scan slice grouping technique, which leads to a dramatic improvement of encoding efficiency. Experiments performed with large ITC'99 benchmark circuits presents the effectiveness of the proposed technique and the test data volume is reduced up to 92% compared to random-filled test patterns.
Self-adaptive Monte Carlo localization for mobile robots using range sensors

In order to achieve the autonomy of mobile robots, effective localization is a necessary prerequisite. In this paper, we propose an improved Monte Carlo localization using self-adaptive samples, abbreviated as SAMCL. This algorithm employs a pre-caching technique to reduce the on-line computational burden. Further, we define the concept of similar energy region (SER), which is a set of poses (grid cells) having similar energy with the robot in the robot space. By distributing global samples in SER instead of distributing randomly in the map, SAMCL obtains a better performance in localization. Position tracking, global localization and the kidnapped robot problem are the three sub-problems of the localization problem. Most localization approaches focus on solving one of these sub-problems. However, SAMCL solves all these three sub-problems together thanks to self-adaptive samples that can automatically separate themselves into a global sample set and a local sample set according to needs. The validity and the efficiency of our algorithm are demonstrated by experiments carried out with different intentions. Extensive experiment results and comparisons are also given in this paper.
Estimating speaker-specific intonation patterns using the linear alignment model

Modeling speaker-speciﬁc intonation is important in several areas, including speaker identiﬁcation, veriﬁcation, and imitation using text-to-speech synthesis. However the choice of the into-nation model and the estimation of its parameters from sponta-neous speech remains a challenge. We propose a way to estimate speaker-speciﬁc intonation parameters for a particular su-perpositional model, the Simpliﬁed Linear Alignment Model [1], using robust per-utterance and overall statistics of spon-taneous speech. We used this method to compare the intonation of children with autism or language impairment, who often have atypical speech prosody, with that of typically developing children. We found signiﬁcant differences between the groups, which demonstrates the effectiveness of the proposed method.
Exploratory data analysis

Exploratory data analysis, or EDA for short, is a term coined by John W. Tukey for describing the act of looking at data to see what it seems to say. This article gives a description of some typical EDA procedures and discusses some of the principles of EDA. Copyright © 2009 John Wiley & Sons, Inc.
Rebeccamycin and Staurosporine Biosynthesis: Insight into the Mechanisms of the Flavin‐Dependent Monooxygenases RebC and StaC

nistically distinct bioactivities that can be achieved with the indolocarbazole scaffold, the former as a DNA topoisomerase I poison, the latter as a protein kinase inhibitor. Identification of the bacterial biosynthetic genes for 1 and 2, along with in vitro studies on individual enzymes’ activities, has delineated a four-enzyme pathway to assemble the corresponding indolocarbazoles arcyriaflavin A (6) and K252c (7). As summarized in Scheme 1, these enzymes are RebODPC and StaODPC for 6 and 7, respectively. The first three reactions catalyzed by RebODP or StaODP are essentially identical. The flavin-dependent enzyme RebO oxidizes l-tryptophan to indole-3-pyruvate. RebD, a heme-dependent oxidase, subsequently oxidatively couples two equivalents of the imine form of indole-3-pyruvate to form chromopyrrolic acid (3). 7, 9] Compound 3 is moderately stable and slowly oxidizes to form 6, 7, and 7-hydroxyK252c (8) in low yields. A cytochrome P450 enzyme, RebP, is thought to accelerate this spontaneous reaction by oxidatively coupling the 5 and 5’ indole carbons of 3 to generate a labile intermediate 4, 11] which can likewise undergo spontaneous oxidative decarboxylation to form 6–8 in greater yields, with 8 being the major product. 12] In what is an interesting example of biosynthetic evolution, addition of the flavin-dependent monooxygenase RebC to the pathway specifies the formation of dioxygenated 6. 12] By contrast, addition of the homologous enzyme StaC directs forma-
Electronic excitations in organic based nanostructures

The first book devoted to a systematic consideration of electronic excitations and electronic energy transfer in organic crystalline multilayers and organics based nanostructures(quantum wells, quantum wires, quantum dots, microcavities). The ingenious combination of organic with inorganic materials in one and the same hybrid structure is shown to give qualitatively new opto-electronic phenomena, potentially important for applications in nonlinear optics, light emitting devices, photovoltaic cells, lasers and so on. The book will be useful not only for physicists but also for chemists and biologists. To help the nonspecialist reader, three Chapters which contain a tutorial and updated introduction to the physics of electronic excitations in organic and inorganic solids have been included.
Cold sprayed copper coatings on ASTM B 221 alloy – characterisation and corrosion study in simulated marine and industrial environment

In the current investigation copper powder was deposited on ASTM B 221 aluminium alloy by low pressure cold spray process. The coating deposition was carried out by varying process parameters. The corrosion performance of bare and coated aluminium alloy was evaluated in aggressive simulated marine (NaCl) and industrial (Na2SO4) environments. The kinetics of the corrosion was approximated by the weight change measurements made after every 24 hrs for a total period of 30 days. X-ray diffraction (XRD), scanning electron microscopy/energy dispersive X-ray analysis/electron probe micro analysis (SEM/EDAX/EPMA) techniques were used to analyse the corrosion products. The copper coated Al alloy showed lesser weight change and the coating remained intact till the end of the experiment. The phases revealed in the scales of coated specimens were mainly copper and aluminium copper, which are reported to be conductive and protective against corrosion.
Echocardiographic evaluation of heart in chronic obstructive pulmonary disease patient and its co-relation with the severity of disease

BACKGROUND Chronic obstructive pulmonary disease (COPD) has considerable effects on cardiac functions, including those of the right ventricle, left ventricle, and pulmonary blood vessels. Most of the increased mortality associated with COPD is due to cardiac involvement. Echocardiography provides a rapid, noninvasive, portable, and accurate method to evaluate the cardiac changes. AIMS To assess the cardiac changes secondary to COPD by echocardiography and to find out the correlation between echocardiographic findings and severity of COPD, if there is any. MATERIALS AND METHODS A total 40 of patients of COPD were selected and staged by pulmonary function test (PFT) and evaluated byechocardiography. RESULTS On echocardiographic evaluation of COPD, 50% cases had normal echocardiographic parameters. Measurable tricuspid regurgitation (TR) was observed in 27/40 cases (67.5%). Pulmonary hypertension (PH), which is defined as systolic pulmonary arterial pressure (sPAP)> 30 mmHg was observed in 17/27 (63%) cases in which prevalence of mild, moderate, and severe PH were 10/17 (58.82%), 4/17 (23.53%), and 3/17 (17.65%), respectively. The frequencies of PH in mild, moderate, severe, and very severe COPD were 16.67%, 54.55%, 60.00%, and 83.33%, respectively. Right atrial pressure was 10 mmHg in 82.5% cases and 15 mmHg in 17.5% cases. Cor pulmonale was observed in 7/17 (41.17%) cases; 7.50% cases had left ventricle (LV) systolic dysfunction and 47.5% cases had evidence of LV diastolic dysfunction defined as A ≥ E (peak mitral flow velocity of the early rapid filling wave (E), peak velocity of the late filling wave caused by atrial contraction (A) on mitral valve tracing) Left ventricle hypertrophy was found in 22.5% cases. CONCLUSION Prevalence of PH has a linear relationship with severity of COPD and severe PH is almost associated with cor pulmonale. Echocardiography helps in early detection of cardiac complications in COPD cases giving time for early interventions.
Collapsed variational bayesian inference of the author-topic model: application to large-scale coordinate-based meta-analysis

The author-topic (AT) model has been recently used to discover the relationships between brain regions, cognitive components and behavioral tasks in the human brain. In this work, we propose a novel Collapsed Variational Bayesian (CVB) inference algorithm for the AT model. The proposed algorithm is compared with the Expectation-Maximization (EM) algorithm on the large-scale BrainMap database of brain activation coordinates and behavioral tasks. Experiments suggest that the proposed CVB algorithm produces parameter estimates with better generalization power than the EM algorithm.
Synchronization-Inspired Partitioning and Hierarchical Clustering

Synchronization is a powerful and inherently hierarchical concept regulating a large variety of complex processes ranging from the metabolism in a cell to opinion formation in a group of individuals. Synchronization phenomena in nature have been widely investigated and models concisely describing the dynamical synchronization process have been proposed, e.g., the well-known Extensive Kuramoto Model. We explore the potential of the Extensive Kuramoto Model for data clustering. We regard each data object as a phase oscillator and simulate the dynamical behavior of the objects over time. By interaction with similar objects, the phase of an object gradually aligns with its neighborhood, resulting in a nonlinear object movement naturally driven by the local cluster structure. We demonstrate that our framework has several attractive benefits: 1) It is suitable to detect clusters of arbitrary number, shape, and data distribution, even in difficult settings with noise points and outliers. 2) Combined with the Minimum Description Length (MDL) principle, it allows partitioning and hierarchical clustering without requiring any input parameters which are difficult to estimate. 3) Synchronization faithfully captures the natural hierarchical cluster structure of the data and MDL suggests meaningful levels of abstraction. Extensive experiments demonstrate the effectiveness and efficiency of our approach.
Impact of Glucocorticoid Receptor Density on Ligand-Independent Dimerization, Cooperative Ligand-Binding and Basal Priming of Transactivation: A Cell Culture Model

Glucocorticoid receptor (GR) levels vary between tissues and individuals and are altered by physiological and pharmacological effectors. However, the effects and implications of differences in GR concentration have not been fully elucidated. Using three statistically different GR concentrations in transiently transfected COS-1 cells, we demonstrate, using co-immunoprecipitation (CoIP) and fluorescent resonance energy transfer (FRET), that high levels of wild type GR (wtGR), but not of dimerization deficient GR (GRdim), display ligand-independent dimerization. Whole-cell saturation ligand-binding experiments furthermore establish that positive cooperative ligand-binding, with a concomitant increased ligand-binding affinity, is facilitated by ligand-independent dimerization at high concentrations of wtGR, but not GRdim. The down-stream consequences of ligand-independent dimerization at high concentrations of wtGR, but not GRdim, are shown to include basal priming of the system as witnessed by ligand-independent transactivation of both a GRE-containing promoter-reporter and the endogenous glucocorticoid (GC)-responsive gene, GILZ, as well as ligand-independent loading of GR onto the GILZ promoter. Pursuant to the basal priming of the system, addition of ligand results in a significantly greater modulation of transactivation potency than would be expected solely from the increase in ligand-binding affinity. Thus ligand-independent dimerization of the GR at high concentrations primes the system, through ligand-independent DNA loading and transactivation, which together with positive cooperative ligand-binding increases the potency of GR agonists and shifts the bio-character of partial GR agonists. Clearly GR-levels are a major factor in determining the sensitivity to GCs and a critical factor regulating transcriptional programs.
3-D integration and the limits of silicon computation

The intrinsic computational efficiency (ICE) of silicon defines the upper limit of the amount of computation within a given technology and power envelope. The effective computational efficiency (ECE) and the effective computational density (ECD) of silicon, by taking computation, memory and communication into account, offer a more realistic upper bound for computation of a given technology. Among other factors, they consider how distributed the memory is, how much area is occupied by computation, memory and interconnect, and the geometric properties of 3-D stacked technology with through silicon vias (TSV) as vertical links. We use the ECE and ECD to study the limits of performance under different memory distribution, power, thermal and cost constraints for various 2-D and 3-D topologies, in current and future technology nodes.
Real-time, pseudo real-time and stroboscopic sampling in time-domain GPRs

GPR performance rapidly decreases with time propagation depending on soil characteristics, thus the dynamic range of the system plays a key role in subsurface visibility. Dynamic range mainly depends on Analog-to-Digital Converter (ADC) number of bits and receiver sampling efficiency, but it can be increased by averaging multiple traces (under the condition of uncorrelated external noise). Most time-domain GPRs use stroboscopic sampling to collect high bandwidth signals and this limits the averaging factor. Therefore, high-speed ADCs are very attractive for time-domain GPRs as they enable a large stacking factor. However, the low number of significant bits limits the Signal-to-Noise Ratio (SNR) or renders this advantage negligible. A further alternative is pseudo real-time sampling which combines fast ADCs with trace averaging; in this case, multiple samples are acquired from each radar trace by shifting the sampling trigger, and then re-assembled by a logic circuit.
Suppression of EGFR endocytosis by dynamin depletion reveals that EGFR signaling occurs primarily at the plasma membrane

The role of endocytosis in the control of EGF receptor (EGFR) activation and cell signaling was explored by using mouse fibroblasts in which dynamin was conditionally depleted. Dynamin is a GTPase shown to play an important role in the control clathrin mediated endocytosis of EGFR and other cell surface receptors. In this report, we demonstrate that EGF binding activity and the display of high and low affinity EGFRs on the cell surface are not affected by dynamin depletion. By contrast, dynamin depletion leads to a strong inhibition of EGFR endocytosis, robust enhancement of EGFR autophosphorylation and ubiquitination, and slower kinetics of EGFR degradation. Surprisingly, MAPK stimulation induced by either low or high EGF concentrations is not affected by dynamin depletion. While a similar initial Akt response is detected in control or dynamin depleted fibroblasts, a somewhat more sustained Akt stimulation is detected in the dynamin depleted cells. These experiments demonstrate that dynamin-mediated endocytosis leads to attenuation of EGFR activation and degradation and that stimulation of the MAPK response and Akt activation are primarily mediated by activated EGFR located in the plasma membrane.
Extended x-ray-absorption fine-structure study of copper under high pressure.

We examine copper as a pressure calibrant for extended x-ray-absorptionfine-structure (EXAFS) measurements of solids under pressures ranging from 0 to10 GPa. Great care must be exercised both in the theoretical formulation ofEXAFS and in the data analysis in order to achieve the high precision requiredto make copper a useful pressure marker. From the first-shell /ital k/-spacedata, phase and amplitude information is extracted both with the ratio methodand from fitting parameters with the help of theoretically calculatedcentral-atom phase shifts (B.-K. Teo and P. A. Lee, J. Am. Chem. Soc.101, 2815 (1979)) and curved-wave backscattering phase shiftsand amplitudes (A. G. McKale /ital et/ /ital al/., J. Am. Chem. Soc.110, 3763 (1988)). Both techniques yield practically identicalresults confirming the reliability of the phase and amplitude tabulations. Butboth techniques suffer from the ambiguity that the results depend on how manyEXAFS parameters are kept variable. It is shown that, for copper, onlynearest-neighbor distances and second cumulants (EXAFS Debye-Waller factors)have to be taken into account. Then pressures can be determined with anaccuracy of about 0.5 GPa. We also present two models for the pressuredependence of the second cumulant: (1) a correlated Debye model along withsimple parametrizations of the isothermal equation of state and theGr/umlt u/neisen parameter,more » and (2) a model for the calculation of the moments ofthe nearest-neighbor distance distribution from an expansion to third order ofthe potential energy. Both models confirm our data analysis. « less
Time-Symmetric Physics: A Radical Approach to the Decoherence Problem

The most powerful form of quantum learning system possible would somehow learn the parameters W of a quantum system f(X, W), for f representing the largest, most powerful set of possible input-output relations. This paper addresses the issue of how to enlarge the set represented by f, by using a new formulation of time-symmetric physics to model analog quantum computers based on spin and by exploring possible sources of backwards-time free energy so as to address problems of decoherence and dissipation.
Discovering Implicit Redundancies in Network Communications for Detecting Inconsistent Values

Detecting inconsistent values received in a communication is a challenging problem faced in networked systems. Inconsistent values occur when a message contains incorrect data, even though the syntax is correct and there is no corruption due to transmission errors. In many cases, traditional schemes based on voting protocols or error detection codes cannot be used. An alternative is discovering implicit redundancies, or patterns that model a correct communication, and using these patterns to detect inconsistent values. However, existing techniques do not cover the inputs and sequential patterns needed by this problem. In this paper, we propose a novel technique that considers messages with multiple types and attributes, events involving variables, and a heuristic for reducing redundant information. Experiments show that the discovered redundancies can achieve reasonable error detection coverage in fields where sequential relations exist, without implying in a large number of false alarms or a high latency.