Miracle-dz/UniFAR-FTUs huggingface dataset:
Segment-based motion estimation using a block-based engine

Motion estimation is a key function in scan rate conversion, advanced picture quality improvement, 2D-to-3D content conversion, and many other video processing steps. For hardware efficiency reasons, most motion estimation implementations are block-based. As object boundaries commonly do not coincide with block boundaries, artifacts may be visible at object boundaries using the block-based approach. Motion estimation for irregular shapes, such as image segments, can accurately track motion boundaries, but a straightforward translation of block-based motion estimation algorithms to segment-based ones leads to inefficient hardware implementations. Therefore, this paper proposes a modified segment-based motion estimation algorithm utilizing the efficiency of block-based processing. We demonstrates an efficient very large instruction word (VLIW) application-specific instruction-set processor (ASIP) implementation of this algorithm.
Effect of Nanoparticles on Wear Resistance and Surface Hardness of a Dental Glass-ionomer Cement

We have studied the effect of nanoparticles on wear resistance and surface hardness of a dental glass-ionomer cement. The effects of composition, loading ratio, and surface modification of the nanoparticles as well as particle size were investigated as well. Commercially available spherical nanoparticles were incorporated into a commercial dental cement Fuji II. One of the nanoparticles was surface-modified with poly(acrylic acid) via surface-initiated atom-transfer radical polymerization. All the cements were conditioned in distilled water at 37°C for 24 h prior to testing. The results showed that all the particles incorporated (either nano-, micro-, or surface-modified) increased the resistance to attrition of Fuji II by approximately 50% but slightly decreased the resistance to abrasion. Most of the modified cements showed increased surface hardness values as compared to Fuji II. Surface modification significantly increased the loading of the nanoparticles into Fuji II from 10% to 30% as compared to the unmodified ones (only 10% at the maximum). Within the limitations of this study, it seems that incorporation of 1-3% spherical silica nanoparticles can effectively improve both resistance to attrition and surface hardness of Fuji II cement.
Graph Data Management for Molecular Biology

IT IS OUR VIEW that labeled directed graph data models (simple, nested, or hypergraphs) can naturally and usefully capture a wide variety of biological data and queries. We believe that development of general purpose graph data management systems (GDMSs) could become major platforms for development of a wide variety of bioinformatics database systems spanning applications from DNA sequences, chemical structure graphs, to contact graphs and biopathways. The use of a common data model and query language across numerous biological applications is very attractive from both a development and user standpoint. Considerable research and development effort are still required to extend current systems to meet modern requirements.
Neural differentiation of human induced pluripotent stem cells follows developmental principles but with variable potency

For the promise of human induced pluripotent stem cells (iPSCs) to be realized, it is necessary to ask if and how efficiently they may be differentiated to functional cells of various lineages. Here, we have directly compared the neural-differentiation capacity of human iPSCs and embryonic stem cells (ESCs). We have shown that human iPSCs use the same transcriptional network to generate neuroepithelia and functionally appropriate neuronal types over the same developmental time course as hESCs in response to the same set of morphogens; however, they do it with significantly reduced efficiency and increased variability. These results were consistent across iPSC lines and independent of the set of reprogramming transgenes used to derive iPSCs as well as the presence or absence of reprogramming transgenes in iPSCs. These findings, which show a need for improving differentiation potency of iPSCs, suggest the possibility of employing human iPSCs in pathological studies, therapeutic screening, and autologous cell transplantation.
Unsupervised discovery of objects using temporal coherence

We present a novel unsupervised method for discovering objects in image sequences. Instead of using spatial homogeneity to partition pixels into regions, we group pixels into large temporally coherent clusters (TCCs) having a unique temporal signature. Each cluster’s temporal signature is explained by hypothesizing the arrival and departure of a small set of objects. Explanations of less ambiguous clusters are used to disambiguate the explanations of their more complicated neighbors. The recovered objects and arrival/departure events explain each frame in the image sequence by specifying (1) which objects are present, (2) the ways in which they occlude each other, and (3) the pixels in the frame that are not part of the background or the objects. Our framework ignores distracting motion, correctly deals with occlusion (including mutual occlusion), and recovers entire objects even in cases where they are partially occluded in every frame. Because we do not use spatial information in our clustering steps the technique is signi£cantly different from and complements traditional spatially based segmentation algorithms. The recovered 2D object masks are suitable for unsupervised training and initialization of object recognition and tracking systems.
Micrometric displacement measurement using CMOS 0.35µm technology Quad-Cell

Precise displacement estimation has high demands on the measurement system, but permits a wide range of applications. This paper presents a new methodology for precise micrometric displacement measurement utilizing a Quad-Cell (QC), Position Sensitive Detector (PSD) realized in a 0. 35μm CMOS technology. Experimental results indicate high precision in the range of several micrometers for displacements of up to 2,400μm. Further, extracted curves permit the choice of the best trade-off between precision and maximum measureable displacement.
Stochastic Volatility and Seasonality in Commodity Futures and Options: The Case of Soybeans

This paper sets up and estimates a continuous-time stochastic volatility model using panel data of soybean futures and options in an integrated time-series study. The model of commodity price dynamics is within the class of affine asset pricing models, and option prices are determined using a standard inversion of characteristic func- tions approach. Our modeling acknowledges that commodities exhibit seasonality patterns in both spot price level and volatility. The estimation method is based on a state space formulation of the model and a quasi maximum likelihood approach. Es- timation results are obtained based on weekly observations of soybean futures prices and options prices from the Chicago Board of Trade in the period October 1984 to March 1999. The empirical results support the conceptual ideas in the theory of storage, but not the view that convenience yields behave like timing options.
RELATIONSHIPS BETWEEN RELATIVE BINDING AFFINITY AND ELECTROPHORETIC BEHAVIOR OF RABBIT ANTIBODIES TO STREPTOCOCCAL CARBOHYDRATES

After repeated intravenous injections with Group C streptococcal vaccine, most rabbit antisera were shown to contain one or more IgG antibody components, as revealed by microzone electrophoresis. A procedure for the fractionation of multiple IgG antibody components from such streptococcal antisera is described. Separation is achieved on the basis of differences in relative binding affinities of the antibody components to immunoabsorbent columns. The evidence suggests that the electrophoretic mobility, and thus the net charge of an antibody, bears a reciprocal relationship to its binding affinity for the streptococcal Group C antigens. Furthermore, the relative binding affinity affords another means to assess the functional homogeneity of streptococcal antibodies. A possible relationship between light chain variable-region subclasses and binding affinities of streptococcal antibodies is discussed.
Intensity Coding in Electric Hearing: Effects of Electrode Configurations and Stimulation Waveforms

Objectives: Current cochlear implants typically stimulate the auditory nerve with biphasic pulses and monopolar electrode configurations. Tripolar stimulation can increase spatial selectivity and potentially improve place pitch related perception but requires higher current levels to elicit the same loudness as monopolar stimulation. The present study combined delayed pseudomonophonasic pulses, which produce lower thresholds, with tripolar stimulation in an attempt to solve the power-performance tradeoff problem. Design: The present study systematically measured thresholds, dynamic range, loudness growth, and intensity discrimination using either biphasic or delayed pseudomonophonasic pulses under both monopolar and tripolar stimulation. Participants were five Clarion cochlear implant users. For each subject, data from apical, middle, and basal electrode positions were collected when possible. Results: Compared with biphasic pulses, delayed pseudomonophonasic pulses increased the dynamic range by lowering thresholds while maintaining comparable maximum allowable levels under both electrode configurations. However, delayed pseudomonophonasic pulses did not change the shape of loudness growth function and actually increased intensity discrimination limens, especially at lower current levels. Conclusions: The present results indicate that delayed pseudomonophonasic pulses coupled with tripolar stimulation cannot provide significant power savings nor can it increase the functional dynamic range. Whether this combined stimulation could improve functional spectral resolution remains to be seen.
Add-On Strategies for Fine-Grained Pedestrian Classification

In this paper, we present four add-on strategies for the fine-grained pedestrian classification task. These strategies are: (1) super-resolution based image preprocessing, which helps to recover the image details; (2) patch dividing based deep feature extraction, which extracts features in a way that preserves the spatial layout of input images; (3) pose- wise classifier sharing, which learns robust classifiers and makes robust predictions using pose information; and (4) graphical model based inference, which utilizes the interdependence between different subcategories to update raw estimations. The proposed strategies are independent and flexible, which make it easy to implement them in practice. We evaluated these strategies on the CRP dataset and confirmed that all of them lead to improvements over the baseline. We also confirmed an improvement over the state-of-the-art when all strategies are combined together.
Adaptive protocols for parallel discrete event simulation

This paper reviews issues concerning the design of adaptive protocols for parallel discrete event simulation (PDES). The need for adaptive protocols are motivated in the background of the classical synchronisation problem that has driven much of the research in this field. Traditional conservative and optimistic protocols and their hybrid variants—that form the basis of adaptive protocols—are also discussed. Adaptive synchronisation protocols are reviewed with special reference to their characteristics regarding the aspects of the simulation state that influence the adaptive decision and the control parameters used. Finally, adaptive load management strategies and their relationship to the synchronisation protocol are discussed.
Evaluation of Large-scale Data to Detect Irregularity in Payment for Medical Services

Summary Background: Sophisticated anti-fraud systems for the healthcare sector have been built based on several statistical methods. Although existing methods have been developed to detect fraud in the healthcare sector, these algorithms consume considerable time and cost, and lack a theoretical basis to handle large-scale data. Objectives: Based on mathematical theory, this study proposes a new approach to using Benford’s Law in that we closely examined the individual-level data to identify specific fees for in-depth analysis. Methods: We extended the mathematical theory to demonstrate the manner in which large-scale data conform to Benford’s Law. Then, we empirically tested its applicability using actual large-scale healthcare data from Korea’s Health Insurance Review and Assessment (HIRA) National Patient Sample (NPS). For Benford’s Law, we considered the mean absolute deviation (MAD) formula to test the large-scale data. Results: We conducted our study on 32 diseases, comprising 25 representative diseases and 7 DRG-regulated diseases. We performed an empirical test on 25 diseases, showing the applicability of Benford’s Law to large-scale data in the healthcare industry. For the seven DRG-regulated diseases, we examined the individual-level data to identify specific fees to carry out an in-depth analysis. Among the eight categories of medical costs, we considered the strength of certain irregularities based on the details of each DRG-regulated disease. Conclusions: Using the degree of abnormality, we propose priority action to be taken by government health departments and private insurance institutions to bring unnecessary medical expenses under control. However, when we detect deviations from Benford’s Law, relatively high contamination ratios are required at conventional significance levels.
Method of Non-reference Image Quality Assessment of SSIM Based on Regional Weighted Entropy

The traditional SSIM haven't considered the limitation of the Human Visual System, which different attention paid to different area in the same picture, and information of the picture itself, leading to the final results are inconsistent between objective and subjective evaluating effects. A new image weighted index, which is regional weighted information entropy index, is put forward to solve this problem. This method divide image into visual region of interest based on the image edge features. By calculated space influence factor and regional entropy of each interest area, formulating regional weighted entropy. The weighted value of each visual interest region is generated after normalization of regional weighted information entropy, and the average weighted structural similarity of all visual interest areas is used as the image assessing index. Test results show that the new method fits human visual system characteristics, and correlates well with subjective perception scores.
Surface and biocompatibility study of electropolished Co-Cr Alloy L605

SURFACE AND BIOCOMPATIBILITY STUDY OF ELECTROPOLISHED Co-Cr Alloy L605 by Hokuto Aihara Electropolishing has been widely used as a surface-modification technique to enhance tissue-to-material interaction by generating a smooth hydrophilic surface and forming a new protective oxide layer. The current study was undertaken to investigate the effect of temperature and time on the surface characteristics and biocompatibility of Co-Cr alloy electropolished in 15% (v/v) phosphoric acid. As the bath temperature was decreased from 35°C to 0°C, a lower and wider current plateau was generated on the characteristic I-V curve. The electropolishing rate decreased proportionally with a decrease in bath temperature. As the electropolishing time increased, the surface roughness decreased with an increase in the contact angle. CT2O3 and Cr(OH)3, as detected by XPS analysis, and cell density (cells/ml) increased proportionally with an increase in electropolishing time. Controlled electropolishing was found at a lower bath temperature, and the formation of Cr203 increased with respect to electropolishing time, resulting in no cytotoxic effects.
A soft lithography route to nanopatterned photovoltaic devices

We have fabricated bulk heterojunction photovoltaic (PV) cells using a perfluoropolyether (PFPE) elastomeric stamp to control the morphology of the donor-acceptor interface within devices. Devices were fabricated using the Pattern Replication In Non-wetting Templates (PRINT) process to have nanoscale control over the bulk heterojunction device architecture. The low-surface energy, chemically resistant, variable modulus, fluoropolymer based molds used in PRINT provide a route to patterning, with nanometer resolution, general polymeric donor materials such as polythiophene and polyphenylenevinylene derivatives and 'hard' inorganic oxide structures typically used as acceptor materials in hybrid organic solar cells such as TiO2, ZnO, and CdSe. This "top-down" approach allows for patterning over large areas and for the functionalization of the donor/acceptor interface. Specifically, nanostructured anatase titania with post-like features ranging from 30-100 nm in diameter and 30-65 nm in height was fabricated to form the ordered bulk heterojunction of a titania-poly(3-hexylthiophene) (P3HT) PV-cell. Nanostructured devices showed a two-fold improvement in both short-circuit current (Jsc) and power conversion efficiency (PCE) relative to reference bilayer cells. Additionally, we will discuss devices fabricated with other organic and inorganic materials in order to investigate the effect on cell performance of controlling the nanoscale architecture of the bulk heterojunction via patterning.
Iterative grapheme-to-phoneme alignment for the training of WFST-based phonetic conversion

In this paper we propose an algorithm for grapheme-to-phoneme (G2P) alignment. Such alignment is needed mainly for the data-driven training of G2P conversion tools. Our approach utilizes a given phonetic alphabet and a set of given orthographic-phonetic word pairs as a source of prior knowledge. The development data are taken from a manually created pronunciation lexicon for a large vocabulary speech recognition system for Czech. The alignment method is based on extended Minimum Edit Distance algorithm. Moreover, we propose an approach to avoid the creation of reference alignments - we evaluate the improvements through a specially designed G2P converter, i.e. we compare the phonetic transcription directly to a set of test orthographic-phonetic word pairs. Results of our approach are comparable or even slightly better than the state-of-the-art.
Restoration of atmospheric turbulent video containing real motion using rank filtering and elastic image registration

Atmospheric turbulence causes a random blur in images due to random fluctuations of the refraction index of the air through which the light propagates. An algorithm is described that compensates image distortion due to the atmospheric turbulence in video while keeping the real moving objects in the video unharmed. The result of the restoration of the video sequence is a much more “stable” sequence where real moving objects are easier to detect and track. This algorithm is based on Differential Elastic Image Registration which maps each turbulent image to a one good reference image derived from the sequence of the turbulent images. To preserve real motion in the scene, the moving objects are located and the compensation for the distortion of the turbulence is applied only to the static areas of images. The algorithm provides also a smooth transition between the static and the moving areas in the image.
On the efficient evaluation of array joins

Array Databases close a gap in the database ecosystem by adding modeling, storage, and processing support on multi-dimensional arrays. Declarative queries provide processing of arrays of regularly massive size, such as Tera-to Petabyte datacubes, while allowing internal degrees of freedom in partitioning the large arrays into tractable sub-arrays. Among the important new operations is the array Theta-Join, such as overlaying two images. Evaluation of such joins is complicated by the fact that the participating arrays likely do not align in their partitioning schemes. This can lead to inefficient multiple reads of sub-arrays. We introduce array joins and present an efficient way of pairing corresponding sub-arrays. As a byproduct, this technique delivers information on optimal data placement for parallel join evaluation. The method is implemented in the Array DBMS rasdaman which is in operational use at data centers and mapping agencies.
The ribosomal protein Asc1/RACK1 is required for efficient translation of short mRNAs

Translation is a core cellular process carried out by a highly conserved macromolecular machine, the ribosome. There has been remarkable evolutionary adaptation of this machine through the addition of eukaryote-specific ribosomal proteins whose individual effects on ribosome function are largely unknown. Here we show that eukaryote-specific Asc1/RACK1 is required for efficient translation of mRNAs with short open reading frames that show greater than average translational efficiency in diverse eukaryotes. ASC1 mutants in S. cerevisiae display compromised translation of specific functional groups, including cytoplasmic and mitochondrial ribosomal proteins, and display cellular phenotypes consistent with their gene-specific translation defects. Asc1-sensitive mRNAs are preferentially associated with the translational ‘closed loop’ complex comprised of eIF4E, eIF4G, and Pab1, and depletion of eIF4G mimics the translational defects of ASC1 mutants. Together our results reveal a role for Asc1/RACK1 in a length-dependent initiation mechanism optimized for efficient translation of genes with important housekeeping functions. DOI: http://dx.doi. org/10.7554/eLife.11154. 001
Draft Genome Sequence of Calothrix Strain 336/3, a Novel H2-Producing Cyanobacterium Isolated from a Finnish Lake

ABSTRACT We announce the draft genome sequence of Calothrix strain 336/3, an N2-fixing heterocystous filamentous cyanobacterium isolated from a natural habitat. Calothrix 336/3 produces higher levels of hydrogen than Nostoc punctiforme PCC 73102 and Anabaena strain PCC 7120 and, therefore, is of interest for potential technological applications.
Flight data recorder: monitoring persistent-state interactions to improve systems management

Mismanagement of the persistent state of a system---all the executable files, configuration settings and other data that govern how a system functions---causes reliability problems, security vulnerabilities, and drives up operation costs. Recent research traces persistent state interactions---how state is read, modified, etc.---to help troubleshooting, change management and malware mitigation, but has been limited by the difficulty of collecting, storing, and analyzing the 10s to 100s of millions of daily events that occur on a single machine, much less the 1000s or more machines in many computing environments. We present the Flight Data Recorder (FDR) that enables always-on tracing, storage and analysis of persistent state interactions. FDR uses a domain-specific log format, tailored to observed file system workloads and common systems management queries. Our lossless log format compresses logs to only 0.5--0.9 bytes per interaction. In this log format, 1000 machine-days of logs---over 25 billion events---can be analyzed in less than 30 minutes. We report on our deployment of FDR to 207 production machines at MSN, and show that a single centralized collection machine can potentially scale to collecting and analyzing the complete records of persistent state interactions from 4000+ machines. Furthermore, our tracing technology is shipping as part of the Windows Vista OS.