Miracle-dz/UniFAR-FTUs huggingface dataset:
Chemical, morphological and structural characterisation of electroless duplex NiP/NiB coatings on steel

Duplex electroless nickel coatings constituted of one layer of nickel-phosphorous and one of nickel-boron are a promising solution to provide combined wear and corrosion resistance to parts. Duplex systems were compared to systems of similar thickness constituted of only one material, in one or two layers. Duplex coatings present intermediate surface texture, but each layer keeps its typical cross-section morphology and structural features, even after heat treatment. The interfaces between the separate layers are sharp in the as-deposited state but not as much after heat treatment. When nickel-boron is deposited first, it influences slightly the grain growth of the subsequent nickel-phosphorous layer, but no influence can be observed when nickel-phosphorous is deposited first.
Identifying elephant flows through periodically sampled packets

Identifying elephant flows is very important in developing effective and efficient traffic engineering schemes. In addition, obtaining the statistics of these flows is also very useful for network operation and management. On the other hand, with the rapid growth of link speed in recent years, packet sampling has become a very attractive and scalable means to measure flow statistics; however, it also makes identifying elephant flows become much more difficult. Based on Bayes' theorem, this paper develops techniques and schemes to identify elephant flows in periodically sampled packets. We show that our basic framework is very flexible in making appropriate trade-offs between false positives (misidentified flows) and false negatives (missed elephant flows) with regard to a given sampling frequency. We further validate and evaluate our approach by using some publicly available traces. Our schemes are generic and require <i>no</i> per-packet processing; hence, they allow a very cost-effective implementation for being deployed in large-scale high-speed networks.
Concept drift region identification via competence-based discrepancy distribution estimation

Real-world data analytics often involves cumulative data. While such data contains valuable information, the pattern or concept underlying these data may change over time and is known as concept drift. When learning under concept drift, it is essential to know when, how and where the context has evolved. Most existing drift detection methods focus only on triggering a signal when drift is detected, and little research has endeavored to explain how and where the data changes. To address this issue, we introduce kernel density estimation into competence-based drift detection method, and invent competence-based discrepancy distribution estimation to identify specific regions in the data feature space where drift has occurred. Two experiments demonstrate that our proposed approach, competence-based discrepancy density estimation, can quantitatively highlight drift regions through data feature space, and produce results that are very close to preset drift regions.
Genequiz II: Automatic Function Assignment For Genome Sequence Analysis

GeneQuiz II, a system for large-scale biological sequence analysis, has been improved signiicantly. The most important new features are a module for fully automatic function assignment and a web interface. The automatic function assignment module has been developed on the basis of past experience and a detailed benchmarking for a large number of manually assigned sequences. It is estimated that its performance reaches over 90% accuracy with no false positives. Therefore, the interactive data evaluation step, which in the past has been a serious bottleneck, is becoming increasingly non-essential. We have also modiied the user interface, replacing the previous viewer with a html interface to the relational database, so the results can be accessible through the world wide web. A recent analysis of the complete genome of Haemophilus innuenzae shows the spectacular improvements in speed and accuracy.
Does eXtreme Programming support Collaborative Creativity

In this paper, the Agile method called eXtreme Programming (XP) is analyzed from the perspective of the creativity, in particular the cre- ative performance and structure required at the team- work level. The conclusion is that XP has characteris- tics that ensure the creative performance of the team members, but we believe that it can be fostered from a creativity perspective.
Decoding Reed-Muller Codes over Product Sets

We give a polynomial time algorithm to decode multivariate polynomial codes of degree $d$ up to half their minimum distance, when the evaluation points are an arbitrary product set $S^m$, for every $d 0$. Our result gives an $m$-dimensional generalization of the well known decoding algorithms for Reed-Solomon codes, and can be viewed as giving an algorithmic version of the Schwartz-Zippel lemma.
High-Spatial-Resolution OH PLIF Visualization in a Cavity-Stabilized Ethylene-Air Turbulent Flame

High-spatial-resolution OH planar laser-induced fluorescence was measured for a premixed ethylene-air turbulent flame in an electrically-heated Mach 2 continuous-flow facility (University of Virginia Supersonic Combustion Facility, Configuration E.) The facility comprised a Mach 2 nozzle, an isolator with flush-wall fuel injectors, a combustor with optical access, and an extender. The flame was anchored at a cavity flameholder with a backward-facing step of height 9 mm. The temperature-insensitive Q 1 (8) transition of OH was excited using laser light of wavelength 283.55 nm. A spatial filter was used to create a laser sheet approximately 25 μm thick based on full-width at half maximum (FWHM). Extension tubes increased the magnification of an intensified camera system, achieving in-plane resolution of 40 μm based on a 50% modulation transfer function (MTF). The facility was tested with total temperature 1200 K, total pressure 300 kPa, local fuel/air equivalence ratios of approximately 0.4, and local Mach number of approximately 0.73 in the combustor. A test case with reduced total temperature and another with reduced equivalence ratio were also tested. PLIF images were acquired along a streamwise plane bisecting the cavity flameholder, from the backward facing step to 120 mm downstream of the step. The smallest observed features in the flow had width of approximately 110 μm. Flame surface density was calculated for OH PLIF images.
First Kepler results on compact pulsators – VI. Targets in the final half of the survey phase

We present results from the final 6 months of a survey to search for pulsations in white dwarfs (WDs) and hot subdwarf stars with the Kepler spacecraft. Spectroscopic observations are used to separate the objects into accurate classes, and we explore the physical parameters of the subdwarf B (sdB) stars and white dwarfs in the sample. From the Kepler photometry and our spectroscopic data, we find that the sample contains five new pulsators of the V1093 Her type, one AMCVn type cataclysmic variable and a number of other binary systems. This completes the survey for compact pulsators with Kepler. No V361 Hya type of short-period pulsating sdB stars were found in this half, leaving us with a total of one single multiperiodic V361 Hya and 13 V1093 Her pulsators for the full survey. Except for the sdB pulsators, no other clearly pulsating hot subdwarfs or white dwarfs were found, although a few low-amplitude candidates still remain. The most interesting targets discovered in this survey will be observed throughout the remainder of the Kepler mission, providing the most long-term photometric data sets ever made on such compact, evolved stars. Asteroseismic investigations of these data sets will be invaluable in revealing the interior structure of these stars and will boost our understanding of their evolutionary history.
Modelling and characterisation for the responsive performance of CF/PLA and CF/PEEK smart materials fabricated by 4D printing

ABSTRACT 4D printing, which is the combination of 3D printing technology and printable smart materials, provides the potential of automating actuation devices. In this paper, we have used a modified-fused deposition modelling 3D printing technology to fabricate a double-layer laminate smart material, which can be activated by temperature directly or by an electric circuit indirectly. A double-layer laminate mathematical model has been developed to describe the bending behaviour caused by the mismatch strain between the surface layer and the basal layer. The electrocaloric deformation testings were performed to find the different bending rules of this low-cost printed active composite in different physical states. The considerable maximal deformation values and deformation force (7 mm and 100 mN for these carbon fibre (CF)/polylactic acid specimens, and 10 mm and 200 mN for these CF/polyether-ether-ketone specimens in the paper) provide this double-layer smart material and 4D printing method the prospective to be applied in biomimetic sensors, actuators, transducers, and artificial muscles.
Clustering of Web Search Results Based on Combination of Links and In-Snippets

Search engine is a common tool to retrieve the information in the Web. But the current status of returned results is still far from satisfaction. Users have to be confronted with searching for a long result list to get the information really wanted. Many works focused on the post processing search results to facilitate users to examine the results. One of the common ways of post processing search result is clustering. Term-based clustering appears as first way to cluster the results. But this method is suffering from the poor quality while the processed pages have little text. Link-based clustering can conquer this problem. But the quality of clusters heavily depends on the number of in-links and out-links in common. In this paper, we propose that the short text attached to in-link is valuable information and it is helpful to reach high clustering quality. To distinguish them with general snippet, we name it as in-snippet. Based on the in-snippet, we propose a new clustering method that combines the links and the in-snippets together. In our method, similarity between pages consists of two parts : link similarity and term similarity. We designed related algorithm to implement clustering. In order to prevent bias from human judgments, the experiment datasets are collected from Open Directory Project(DMOZ). Due to DMOZ is human-edited directory, the datasets from DMOZ has higher quality and larger scale. We use entropy and f-measure to evaluate the quality of the final clusters. By being compared with the link-based and the pure term-based algorithms, our method outperforms others in clustering quality.
A study of data partitioning on OpenCL-based FPGAs

A lot of research efforts have been devoted to accelerating relational database applications on FPGAs, due to their high energy efficiency and high throughput. Most of the existing studies are based on hardware description languages (HDLs). Recently, FPGA vendors have started to develop OpenCL SDKs for much better programmability. In this paper, we investigate the performance of relational database applications on OpenCL-based FPGAs. As a start, we study the performance of data partitioning, a core operation widely used in relational databases. Due to random memory accesses, data partitioning is time-consuming and can become a major bottleneck for database operators such as hash join. We start with the state-of-the-art OpenCL implementation which was originally designed for CPUs/GPUs, and find that it suffers from lock overheads and memory bandwidth overheads. To reduce lock overheads, we develop a simple yet efficient multi-kernel approach to leverage two emerging features of Altera OpenCL SDK, namely task kernel and channel. Moreover, on-chip buckets are employed to reduce the number of memory transactions. We further develop a cost model to guide the parameter configuration. We evaluate the proposed design on a recent Altera Stratix V FPGA. Our results demonstrate 1) our cost model can accurately predict the performance of data partitioning under different parameter settings; 2) our proposed multi-kernel approach can achieve 10.7X; speedup over the existing OpenCL implementation. Also, the experiments with three case studies show that the optimized implementations can achieve 4-12X performance improvement over the original implementations.
Quantitative analysis of cobblestone area-forming cells in bone marrow of patients with aplastic anemia by limiting dilution assay.

In the past, the analysis of primitive human hematopoietic progenitor cells with repopulating activity was limited by lack of appropriate in vitro assay systems. It was recently shown that cobblestone area-forming cells (CAFC) giving rise to cobblestone areas after 5 weeks in long-term marrow cultures (LTMC) represent a population of pluripotent progenitor cells with long-term marrow-repopulating activity. We have used a microtiter limiting dilution-type human LTMC system to quantitate the frequency of CAFC (week 5) in aplastic anemia (AA). In bone marrow mononuclear cells (BM-MNC) of healthy donors (n = 36) we observed a mean frequency of 84.4 CAFC per 10(5) BM-MNC (95% confidence interval limits, 66.4 to 102.4). The mean frequency of CAFC in BM of 31 AA patients was 6.6 per 10(5) BM-MNC (95% confidence interval limits, 5.3 to 7.9; n = 47). This frequency is significantly lower as compared with controls (P < .0001). The frequency of CAFC was reduced not only in pancytopenic AA patients (6.2 per 10(5) BM-MNC; P < . 0001 v control), but also in patients in remission after immunosuppression (7.6; P < .0001 v control; P = .1 v pancytopenic AA patients). The CAFC frequency did not correlate with the severity or duration of the disease and did not predict response to immunosuppressive treatment. In summary, the frequency of primitive hematopoietic progenitor cells, as measured by the CAFC assay, is significantly reduced in AA. CAFC remain severely reduced even after hematologic recovery after immunosuppressive treatment. The low frequency of CAFC in remission patients is in keeping with other data pointing to a persisting defect of hematopoiesis in patients in remission after immunosuppressive treatment.
Similarity of XML-Schema Elements: A Structural and Information Content Approach

EXtensible Markup Language (XML)-Schemas are the emerging standards for describing and validating semi-structured documents across the Internet, due to the rich set of modeling constructors, types and constraints they provide. Semantic similarity is growing in importance in different settings, such as digital libraries, heterogeneous databases and, in particular, the Semantic Web. The focus of this paper is the definition of a method for determining semantic similarity of XML-Schema elements in the presence of type hierarchies. Such a method has been defined by combining and revisiting: (i) the information content approach, and (ii) a method for comparing the structural components of type declarations, inspired by the maximum weighted matching problem in bipartite graphs.
The impact of missing data and how it is handled on the rate of false‐positive results in drug development

In drug development, a common choice for the primary analysis is to assess mean changes via analysis of (co)variance with missing data imputed by carrying the last or baseline observations forward (LOCF, BOCF). These approaches assume that data are missing completely at random (MCAR). Multiple imputation (MI) and likelihood‐based repeated measures (MMRM) are less restrictive as they assume data are missing at random (MAR). Nevertheless, LOCF and BOCF remain popular, perhaps because it is thought that the bias in these methods lead to protection against falsely concluding that a drug is more effective than the control. We conducted a simulation study that compared the rate of false positive results or regulatory risk error (RRE) from BOCF, LOCF, MI, and MMRM in 32 scenarios that were generated from a 25 full factorial arrangement with data missing due to a missing not at random (MNAR) mechanism. Both BOCF and LOCF inflated RRE were compared to MI and MMRM. In 12 of the 32 scenarios, BOCF yielded inflated RRE compared with eight scenarios for LOCF, three scenarios for MI and four scenarios for MMRM. In no situation did BOCF or LOCF provide adequate control of RRE when MI and MMRM did not. Both MI and MMRM are better choices than either BOCF or LOCF for the primary analysis. Copyright © 2007 John Wiley & Sons, Ltd.
PLI Cancellation in ECG Signal Based on Adaptive Filter by Using Wiener-Hopf Equation for Providing Initial Condition

This paper presents a technique for finding the optimal initial weight for adaptive filter by using difference equation. The obtained analytical response of the system identifies the appropriate weights for the system and shows that the MSE depends on the initial weight. The proposed technique is applied to eliminate the known frequency power line interference (PLI) signal in the electrocardiogram (ECG) signal. The PLI signal is considered as a combination of cosine and sine signals. The adaptive filter, therefore, attempts to adjust the amplitude of cosine and sine signals to synthesize a reference signal very similar to the contaminated PLI signal. To compare the potential of the proposed technique to other techniques, the system is simulated by using the Matlab program and the TMS320C6713 digital board. The simulation results demonstrate that the proposed technique enables the system to eliminate the PLI signal with the fastest time and gains the superior results of the recovered ECG signal.
High-Accuracy Digital-to-Analog Actuators Using Load Springs Compensating Fabrication Errors

We present a high-accuracy digital-to-analog (DA) actuator using a linear load spring capable of compensating the output displacement errors caused by fabrication errors. The load spring is designed to modify the modulation line slope in the presence of fabrication errors, thus reducing the output displacement errors. We compare three prototypes including the uncompensated design, the compensated design at the fabrication error of delta=0, and the compensated design in the fabrication error range of -0.3 mum<delta< 0, respectively. The two different compensated linear DA actuators generate the output displacement errors of -0.20plusmn0. 23 mum and -0.13plusmn0. 18 mum, respectively, thus reducing their output errors by 64.3% and 76.8% of the errors, i.e., 0.56plusmn0. 20 mum, produced by the conventional uncompensated linear DA actuator. The dynamic characteristics of the compensated linear DA actuators show the response time below 1.5 ms, the resonant frequency of 3.7 kHz, and the lifetime of 107 cycles. Consequently, we experimentally verify the fabrication error compensation function of the compensated linear DA actuators for applications to high-accuracy actuators insensitive to fabrication errors.
Extracting strctural land cover components using small-footprint waveform lidar data

Previous work has shown the ability of waveform LiDAR sensors to accurately describe various land cover types [1] and biomass estimates made in the field [2]. What is lacking, however, is a way to describe the different structural components that are embedded in the digitized backscattered energy from the LiDAR pulse. This study aims to extract structural components from waveform LiDAR data in terms of woody, herbaceous, and bare ground components from data collected over a savanna environment in and around Kruger National Park (KNP), South Africa. These components are comprised of metrics extracted from the waveforms and validated using biomass measurements made in field plots. Different size windows around plot centers, 3×3 pixels and 9×9 pixels (resulting in 1.5m and 4.5 m footprint, respectively), were used to examine scale effects of larger footprints. It was found that composite waveforms resembling plot sizes (9×9) most often are able to describe more than 80% of the woody biomass variability across the entire study site, and individually for two of the three land uses within the area. However, the herbaceous component of the waveform did not correlate well with the field measurements, while the bare ground component was verified visually in a side-by-side comparison with optical imagery.
A renewable SERS substrate prepared by cyclic depositing and stripping of silver shells on gold nanoparticle microtubes.

State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, Jilin 130022, People’s Republic of China, and Graduate School of the Chinese Academy of Sciences, Beijing, 100039, People’s Republic of China We also examine the influence of the amount of reducing agent and the diameter of nanoparticles on SERS spectra. When the concentration of ascorbic acid was decreased from 7.6 mM to 3.6 mM, the SERS spectra collected from the silver/gold microtubes contained dominant a1 vibrational modes even with a deposition time for silver atoms of only 3 min, indicating that an uniform and complete silver shell on gold nanoparticles can be prepared easily by decreasing in the deposition rate of the silver atoms. As the deposition time of silver shells increases, the SERS intensity of 4-ATP also increases (Figure S1 shown in supporting information), which can be due to an increased nanoparticles diameter.
The Müller-Lyer Illusion in a Computational Model of Biological Object Recognition

Studying illusions provides insight into the way the brain processes information. The Müller-Lyer Illusion (MLI) is a classical geometrical illusion of size, in which perceived line length is decreased by arrowheads and increased by arrowtails. Many theories have been put forward to explain the MLI, such as misapplied size constancy scaling, the statistics of image-source relationships and the filtering properties of signal processing in primary visual areas. Artificial models of the ventral visual processing stream allow us to isolate factors hypothesised to cause the illusion and test how these affect classification performance. We trained a feed-forward feature hierarchical model, HMAX, to perform a dual category line length judgment task (short versus long) with over 90% accuracy. We then tested the system in its ability to judge relative line lengths for images in a control set versus images that induce the MLI in humans. Results from the computational model show an overall illusory effect similar to that experienced by human subjects. No natural images were used for training, implying that misapplied size constancy and image-source statistics are not necessary factors for generating the illusion. A post-hoc analysis of response weights within a representative trained network ruled out the possibility that the illusion is caused by a reliance on information at low spatial frequencies. Our results suggest that the MLI can be produced using only feed-forward, neurophysiological connections.
The influence of parameters in evolutionary based rule extraction method from neural network

In the paper the experimental study of the influence of parameters on the final results of the rule extraction method from neural network for classification problem is described. The method is based on evolutionary approach, where for each class evolves separate population. The paper starts on the presentation of the basic concepts of the method. Next, the results of experiments are described. They examine the influence of genetic parameters. Then, the parameters that affect the rule extraction efficiency are tested. All experiments are made with using UCI data sets. At the end, some general conclusion concerning the role of the parameters and their influence on the final results are formulated.