Miracle-dz/UniFAR-FTUs huggingface dataset:
COMPRESSION OF SINUSOIDAL MODELING PARAMETERS

ABSTRACTIn this paper we present a technique for lossless compressio nof the sinusoidal modeling parameters. Compression is inde eduseful for embedding spectral sounds in a synthesizer, broa dcast-ing spectral sounds or simply storing many of them on a medium . This technique consists incompressing the frequency and am -plitude parameters of each partial by adaptively sub-sampl ing andencoding their evolutions with time. It can be easily extend ed tohandle spectral envelopes instead of partials, that is two- dimen-sional structures instead of one-dimensional ones.We have also designed a very compact le format for (com-pressed) spectral sounds based on this compression scheme.1. INTRODUCTIONSpectralmodels provide general representations ofsound i nwhichmany audio effects can be performed in a very natural and musi -cally expressive way. Based on additive synthesis, they con tain adeterministicpartconsistingofaoftenhugenumber ofpa rtials,which are pseudo-sinusoidal tracks for which frequencies a nd am-plitudes evolve slowly with time. The spectral modeling par ame-ters of this deterministic part consist of the evolutions in time ofthe controls of the partials, thus leading to a large amount o f data.In this paper we present a technique for lossless compressio nof these sinusoidal modeling parameters. This technique ca n turnout tobeveryuseful foranalysis /synthesis programs deali ngwithspectral modeling. Section 2 claries the spectral model co nsid-ered here, while Section 3 explains the compression techniq ue forthe model parameters. Finally, Section 4presents some inte restingimprovements that can be made to the compression method.2. SINUSOIDAL MODELINGThe phase vocoder [1] uses the short-time Fourier transform toproduce seriesofshort-termspectratakenonsuccessivewi ndowedtemporal frames. The McAulay-Quatieri analysis [2] looks a crossthese short-term spectra for partials. These partials are p seudo-sinusoidaltracksforwhichfrequenciesandamplitudesvar yslowlyover time. The audio signal
Human-humanoid joint haptic table carrying task with height stabilization using vision

In this paper, a first step is taken towards using vision in human-humanoid haptic joint actions. Haptic joint actions are characterized by physical interaction throughout the execution of a common goal. Because of this, most of the focus is on the use of force/torque-based control. However, force/torque information is not rich enough for some tasks. Here, a particular case is shown: height stabilization during table carrying. To achieve this, a visual servoing controller is used to generate a reference trajectory for the impedance controller. The control law design is fully described along with important considerations for the vision algorithm and a framework to make pose estimation robust during the table carrying task of the humanoid robot. We then demonstrate all this by an experiment where a human and the HRP-2 humanoid jointly transport a beam using combined force and vision data to adjust the interaction impedance while at the same time keeping the inclination of the beam horizontal.
Spatial patterns of atrophy, hypometabolism, and amyloid deposition in Alzheimer's disease correspond to dissociable functional brain networks

Recent neuroimaging studies of Alzheimer's disease (AD) have emphasized topographical similarities between AD‐related brain changes and a prominent cortical association network called the default‐mode network (DMN). However, the specificity of distinct imaging abnormalities for the DMN compared to other intrinsic connectivity networks (ICNs) of the limbic and heteromodal association cortex has not yet been examined systematically. We assessed regional amyloid load using AV45‐PET, neuronal metabolism using FDG‐PET, and gray matter volume using structural MRI in 473 participants from the Alzheimer's Disease Neuroimaging Initiative, including preclinical, predementia, and clinically manifest AD stages. Complementary region‐of‐interest and voxel‐based analyses were used to assess disease stage‐ and modality‐specific changes within seven principle ICNs of the human brain as defined by a standardized functional connectivity atlas. Amyloid deposition in AD dementia showed a preference for the DMN, but high effect sizes were also observed for other neocortical ICNs, most notably the frontoparietal‐control network. Atrophic changes were most specific for an anterior limbic network, followed by the DMN, whereas other neocortical networks were relatively spared. Hypometabolism appeared to be a mixture of both amyloid‐ and atrophy‐related profiles. Similar patterns of modality‐dependent network specificity were also observed in the predementia and, for amyloid deposition, in the preclinical stage. These quantitative data confirm a high vulnerability of the DMN for multimodal imaging abnormalities in AD. However, rather than being selective for the DMN, imaging abnormalities more generally affect higher order cognitive networks and, importantly, the vulnerability profiles of these networks markedly differ for distinct aspects of AD pathology. Hum Brain Mapp 37:35–53, 2016. © 2015 Wiley Periodicals, Inc.
Byzantine agreement in constant expected time

We present a novel cryptographic algorithm for Byzantine agreement in a network with l=O(n) faulty processors and in the most adversarial setting. Our algorithm requires, once and for all, O(t) rounds of preprocessing. Afterwards it allows us to reach each individual Byzantine agreement in constant expected time. Our solution does not make use of any trusted party.
Sorosphaerula nom. n. for the Plasmodiophorid Genus Sorosphaera J. Schröter 1886 (Rhizaria: Endomyxa: Phytomyxea: Plasmodiophorida)

ABSTRACT. Sorosphaerula nom. n. is introduced to replace the phytomyxean generic name Sorosphaera J. Schröter, which is preoccupied by the foraminiferan genus Sorosphaera Brady. As it is agreed now that both the Foraminifera and the Phytomyxea belong to the Rhizaria, this homonomy within the same supergroup of eukaryotes needs to be revised. To avoid future homonomy, we recommend that the International Code of Zoological Nomenclature be applied for future taxonomic work on Phytomyxea.
Confirmation of association between autism and the mitochondrial aspartate/glutamate carrier SLC25A12 gene on chromosome 2q31.

OBJECTIVE Autism is a neurodevelopmental disorder with childhood onset and a known major genetic component. A recent study identified a highly significant association between autism and a two-single-nucleotide-polymorphism haplotype in the SLC25A12 gene, with a homozygote genotype relative risk between 2.4 and 4.8. The authors' goal was to investigate this association with autism in Irish affected child-parent trios because replication in an independent sample is essential in the validation of such potentially important findings. METHOD Markers rs2056202 and rs2292813 were genotyped in a total of 158 trios (442 individuals). The Transmission Disequilibrium Test was used to examine these markers for association with autism. RESULTS In agreement with the recent study, the authors found significant association between autism and the C alleles of both rs2056202 and rs2292813 as well as the two-marker haplotype. CONCLUSIONS These findings provide replication of the association between autism and SLC25A12.
Expeditious reconciliation for practical quantum key distribution

The paper proposes algorithmic and environmental modifications to the extant reconciliation algorithms within the BB84 protocol so as to speed up reconciliation and privacy amplification. These algorithms have been known to be a performance bottleneck 1 and can process data at rates that are six times slower than the quantum channel they serve2. As improvements in single-photon sources and detectors are expected to improve the quantum channel throughput by two or three orders of magnitude, it becomes imperative to improve the performance of the classical software. We developed a Cascade-like algorithm that relies on a symmetric formulation of the problem, error estimation through the segmentation process, outright elimination of segments with many errors, Forward Error Correction, recognition of the distinct data subpopulations that emerge as the algorithm runs, ability to operate on massive amounts of data (of the order of 1 Mbit), and a few other minor improvements. The data from the experimental algorithm we developed show that by operating on massive arrays of data we can improve software performance by better than three orders of magnitude while retaining nearly as many bits (typically more than 90%) as the algorithms that were designed for optimal bit retention.
Valuation of energy storage: an optimal switching approach

We consider the valuation of energy storage facilities within the framework of stochastic control. Our two main examples are natural gas dome storage and hydroelectric pumped storage. Focusing on the timing flexibility aspect of the problem we construct an optimal switching model with inventory. Thus, the manager has a constrained compound American option on the inter-temporal spread of the commodity prices. Extending the methodology from Carmona and Ludkovski [Appl. Math. Finance, 2008], we then construct a robust numerical scheme based on Monte Carlo regressions. Our simulation method can handle a generic Markovian price model and easily incorporates many operational features and constraints. To overcome the main challenge of the path-dependent storage levels, two numerical approaches are proposed. The resulting scheme is compared with the traditional quasi-variational framework and illustrated with several concrete examples. We also consider related problems of interest, such as supply guarantees and mines management.
Distinguishing Individuals from Organisations on Twitter

Twitter is a popular public platform for individuals to share information and express opinions. It is also widely used as an active communication channel by many organisations. Analysis results about public opinion could thus be misrepresented and distorted if the posts generated by non-individuals are appropriately handled motivating the need to identify the type of user accounts for social media analytics. In this paper, we demonstrate the utility of a joint text and network representation for classifying if a profile belongs to an individual or organisation. Crucially, combining the two feature types has not been shown before for this task. Our experimental results show that performance gains are possible but only when using our novel adaptation of the Text-Associated DeepWalk(TADW) method.
Sampling Techniques for Kernel Methods

We propose randomized techniques for speeding up Kernel Principal Component Analysis on three levels: sampling and quantization of the Gram matrix in training, randomized rounding in evaluating the kernel expansions, and random projections in evaluating the kernel itself. In all three cases, we give sharp bounds on the accuracy of the obtained approximations. Rather intriguingly, all three techniques can be viewed as instantiations of the following idea: replace the kernel function k by a "randomized kernel" which behaves like k in expectation.
Influence of Ca2+ and Mg2+ Supplementation on In VitroBiological Properties of Hydroxyapatite/Collagen Nanocomposite Membrane

Hydroxyapatite/collagen (HAp/Col) nanocomposites with bone-like self-organized nanostructure show excellent bioactivity in vivo. However, they show quite high absorbability for cationic ions and lower culture medium ionic concentrations which adversely affects bone cell proliferation and osteogenic differentiation in in vitro cell culture condition. To address this limitation, in this study we have supplemented Ca2+ and Mg2+ ions to the HAp/Col nanocomposite membrane sample prior to cell culture to improve it’s in vitro biological properties. The HAp/Col nanocomposite membrane samples were fabricated by the simultaneous titration method using Ca(OH)2, type-I atelocollagen and H3PO4 as starting precursor materials. Prior to in vitro cell culture experiments, the HAp/Col samples were pretreated with Ca2+ and/or Mg2+ ions by immersing in 10 ml of 20 mM CaCl2 solution, 20 mM MgCl2 solution, or a solution containing 20 mM CaCl2 and 20 mM MgCl2 for 7 days. In vitro bone cell-material interactions on the pretreated and untreated HAp/Col samples were studied by culturing MC3T3-E1 cells up to 7 days. Enhanced bone cell proliferation was found on all the pretreated HAp/col samples as confirmed by the CCK-8 assay. Interestingly, the HAp/Col samples pretreated with both Ca2+ and Mg2+ ions showed the maximum viable bone cell density.
Cancellation of the maternal and extraction of the fetal ECG in noninvasive recordings

No signal processing technique has been able to reliably deliver an undistorted fetal electrocardiographic (fECG) signal from electrodes placed on the maternal abdomen because of the low signal-to-noise ratio of the fECG recorded from the maternal body surface, resulting in increased rates of Caesarean deliveries of healthy infants. In an attempt to solve the problem a Physionet/Computing in Cardiology announced the 2013 Challenge: Noninvasive fetal ECG. We are suggesting a method for cancellation of the maternal ECG consisting of maternal QRS detection, heart rate dependant P-QRS-T interval selection, location of the fiducial points inside this interval for best matching by cross correlation, superimposition of the intervals, calculation of the mean signal of the P-QRS-T interval, and sequential subtraction of the mean signal from the whole jECG recording. A combined lead of all the 4 channels was synthesized and fetal QRS detection was performed on it. All 100 recordings of test set B were processed, the times of occurrence of the fetal QRSs were recorded and sent as results to the Organizers of the Challenge. The calculated average scores are: 285.132 for Events 1 and 4: Fetal heart rate measurement; 19. 962 for Events 2 and 5: Fetal RR interval measurement.
Dynamic and hierarchical multi-structure geometric model fitting

The ability to generate good model hypotheses is instrumental to accurate and robust geometric model fitting. We present a novel dynamic hypothesis generation algorithm for robust fitting of multiple structures. Underpinning our method is a fast guided sampling scheme enabled by analysing correlation of preferences induced by data and hypothesis residuals. Our method progressively accumulates evidence in the search space, and uses the information to dynamically (1) identify outliers, (2) filter unpromising hypotheses, and (3) bias the sampling for active discovery of multiple structures in the data—All achieved without sacrificing the speed associated with sampling-based methods. Our algorithm yields a disproportionately higher number of good hypotheses among the sampling outcomes, i.e., most hypotheses correspond to the genuine structures in the data. This directly supports a novel hierarchical model fitting algorithm that elicits the underlying stratified manner in which the structures are organized, allowing more meaningful results than traditional “flat” multi-structure fitting.
The WW Domain-Containing Proteins Interact with the Early Spliceosome and Participate in Pre-mRNA Splicing In Vivo

ABSTRACT A growing body of evidence supports the coordination of mRNA synthesis and its subsequent processing events. Nuclear proteins harboring both WW and FF protein interaction modules bind to splicing factors as well as RNA polymerase II and may serve to link transcription with splicing. To understand how WW domains coordinate the assembly of splicing complexes, we used glutathione S-transferase fusions containing WW domains from CA150 or FBP11 in pull-down experiments with HeLa cell nuclear extract. The WW domains associate preferentially with the U2 small nuclear ribonucleoprotein and with splicing factors SF1, U2AF, and components of the SF3 complex. Accordingly, WW domain-associating factors bind to the 3′ part of a pre-mRNA to form a pre-spliceosome-like complex. We performed both in vitro and in vivo splicing assays to explore the role of WW/FF domain-containing proteins in this process. However, although CA150 is associated with the spliceosome, it appears to be dispensable for splicing in vitro. Nevertheless, in vivo depletion of CA150 substantially reduced splicing efficiency of a reporter pre-mRNA. Moreover, overexpression of CA150 fragments containing both WW and FF domains activated splicing and modulated alternative exon selection, probably by facilitating 3′ splice site recognition. Our results suggest an essential role of WW/FF domain-containing factors in pre-mRNA splicing that likely occurs in concert with transcription in vivo.
Catalytic ozonation of 2,4-Dichlorophenoxyacetic acid using alumina in the presence of a radical scavenger

Using a laboratory-scale mixed reactor, the performance of alumina in degrading 2,4-Dichlorophenoxyacetic acid with ozone in the presence of tert-butyl alcohol radical scavenger was studied. The operating variables investigated were the dose of alumina catalyst and solution pH. Results showed that using ozone and alumina leads to a significant increase in 2,4-D removal in comparison to non-catalytic ozonation and adsorption processes. The observed reaction rate constants (kobs ) for 2,4-D during ozonation were found to increase linearly with increasing catalyst dose. At pH 5, the kobs value increased from 19.3 to 26 M−1 s−1 and 67 M−1 s−1 when varying the alumina dose from 1 to 2 and 4 g L−1, respectively. As pH was increased, higher reaction rates were observed for both non-catalytic ozonation and catalytic ozonation processes. Thus, at pH 3 and using a catalyst dose of 8 g L−1, the kobs values for non-catalytic ozonation and catalytic ozonation processes were 3.4 and 58.9 M−1 s−1, respectively, whereas at pH 5 reaction rate constants of 6.5 and 128.5 M−1 s−1 were observed, respectively. Analysis of total organic carbon suggested that catalytic ozonation with alumina achieved a considerable level of mineralization of 2,4-D. Adsorption of 2,4-D on alumina was found to play an important role in the catalytic ozonation process.
GEMINI SPECTROSCOPY OF THE SHORT-HARD GAMMA-RAY BURST GRB 130603B AFTERGLOW AND HOST GALAXY

We present early optical photometry and spectroscopy of the afterglow and host galaxy of the bright short-duration gamma-ray burst GRB 130603B discovered by the Swift satellite. Using our Target of Opportunity program on the Gemini South telescope, our prompt optical spectra reveal a strong trace from the afterglow superimposed on continuum and emission lines from the z = 0.3568 ± 0.0005 host galaxy. The combination of a relatively bright optical afterglow (r′ = 21.52 at Δt = 8.4 hr), together with an observed offset of 0. ″9 from the host nucleus (4.8 kpc projected distance at z = 0.3568), allow us to extract a relatively clean spectrum dominated by afterglow light. Furthermore, the spatially resolved spectrum allows us to constrain the properties of the explosion site directly, and compare these with the host galaxy nucleus, as well as other short-duration GRB host galaxies. We find that while the host is a relatively luminous (), star-forming (SFR = 1.84 M☉ yr−1) galaxy with almost solar metallicity, the spectrum of the afterglow exhibits weak Ca ii absorption features but negligible emission features. The explosion site therefore lacks evidence of recent star formation, consistent with the relatively long delay time distribution expected in a compact binary merger scenario. The star formation rate (SFR; both in an absolute sense and normalized to the luminosity) and metallicity of the host are both consistent with the known sample of short-duration GRB hosts and with recent results which suggest GRB 130603B emission to be the product of the decay of radioactive species produced during the merging process of a neutron-star–neutron-star binary (“kilonova”). Ultimately, the discovery of more events similar to GRB 130603B and their rapid follow-up from 8 m class telescopes will open new opportunities for our understanding of the final stages of compact-objects binary systems and provide crucial information (redshift, metallicity, and chemical content of their explosion site) to characterize the environment of one of the most promising gravitational wave sources.
COBALT: constraint-based alignment tool for multiple protein sequences

MOTIVATION A tool that simultaneously aligns multiple protein sequences, automatically utilizes information about protein domains, and has a good compromise between speed and accuracy will have practical advantages over current tools. RESULTS We describe COBALT, a constraint based alignment tool that implements a general framework for multiple alignment of protein sequences. COBALT finds a collection of pairwise constraints derived from database searches, sequence similarity and user input, combines these pairwise constraints, and then incorporates them into a progressive multiple alignment. We show that using constraints derived from the conserved domain database (CDD) and PROSITE protein-motif database improves COBALT's alignment quality. We also show that COBALT has reasonable runtime performance and alignment accuracy comparable to or exceeding that of other tools for a broad range of problems. AVAILABILITY COBALT is included in the NCBI C++ toolkit. A Linux executable for COBALT, and CDD and PROSITE data used is available at: ftp://ftp.ncbi. nlm.nih. gov/pub/agarwala/cobalt
A robust video based license plate recognition system

License plate recognition system (LPRS) is a difficult problem in the field of machine vision and is of substantial interest because of its applications to areas such as cross border security, law enforcement and various other automation applications. Previous methods used plate specific details such as aspect ratio, color or dimensions of the plate in the complex task of plate localization. In this paper, license plate localization process is carried out by weight based density map (WBDM) method, which is independent of such constraints. The proposed method also relaxes constraints in lighting conditions. The robustness of this method is well suited for application in countries like India where the appearance of plates varies widely. 1750 images were captured in different background scenes under various lighting conditions. This method has been tested with different types of vehicles such as buses, care, trucks etc. The overall identification rate of this algorithm is 98.63% in different conditions.
Microfiltration, Nano-filtration and Reverse Osmosis for the Removal of Toxins (LPS Endotoxins) from Wastewater

Lipopolysaccharide (LPS) endotoxin, a bacterial byproduct abundantly present in wastewater, is more and more representing a major concern in wastewater treatment sector for the potential health risk it represents. It is, therefore, more urgent than before to protect consumers from contaminating their fresh potable water reserves with LPS endotoxin through aquifer replenishment using reclaimed wastewater or by supplying reclaimed wastewater as potable water. Membrane treatment is an alternative to activated sludge process and is the most commonly used to treat wastewater. Moreover, nano-filtration and reverse osmosis are the most advanced technologies used to treat wastewater to a potable level. Removal efficiency of LPS endotoxin using Membrane bioreactors (MBRs) and Nanofiltration (NF) and Reverse Osmosis (RO) is subject of this paper. It revealed that these advanced technologies could remove a significant amount of endotoxin. However, levels of concentration in the product water are still much higher than the one found in tap water and it is not advisable to supply this water directly to consumers. Further investigations are required to determine the best management practices for a safe supply of potable water from reclaimed wastewater.