Miracle-dz/UniFAR-FTUs huggingface dataset:
KLT-based classified VQ for the speech signal

If the signal statistics are given, direct vector quantization (DVQ) according to these statistics provides the highest coding efficiency, but requires unmanageable storage requirements. In. code-excited linear predictive (CELP) coding. a single “compromise” codebook is trained in the prediction residual-domain and the space-filling and shape advantages of vector quantization (VQ) are utilized in a non-optimal, average sense. In this paper. we propose a Karhunen-Loève Transform (KLT)-based classified VQ (CVQ), where the space-filling advantage can be utilized since the Voronoi-region shape is not affected by the KLT. The memory and shape advantages can be also used, since each codebook is designed based on a narrow class of KL T -domain statistics. Our experiments show that the KLT-CVQ provides a higher SNR than CELP and (single-codebook) DVQ, and has a computational complexity similar to DVQ and much lower than CELP. Storage requirements are modest because of the energy concentration property of the KL T.
Intraseasonal variability over tropical Africa during northern summer

Abstract The intraseasonal variability over Africa during northern summer was analyzed, using 25 years of NCEP– NCAR reanalysis and satellite data. The dominant pattern of variability was one of enhanced deep convection over the whole African monsoon region. It appeared to arise at least partly as a remote response to the intraseasonal (Madden–Julian) oscillation over the warm pool sector. Twenty days prior to the maximum in convection over Africa, there was no signal over Africa but convection was reduced over the equatorial warm pool. An equatorial Kelvin wave response to this change in warm pool convection propagated eastward and an equatorial Rossby wave response propagated westward and between them they completed a circuit of the equator and met up 20 days later over Africa, where the negative midtropospheric temperature anomalies in the Kelvin and Rossby waves favored deep convection. Over West Africa, the Kelvin wave component contained lower-tropospheric westerly anomalies that acted to increase t.
A framework for generating data to simulate changing environments

A fundamental assumption often made in supervised classification is that the problem is static, i.e. the description of the classes does not change with time. However many practical classification tasks involve changing environments. Thus designing and testing classifiers for changing environments are of increasing interest and importance. A number of benchmark data sets are available for static classification tasks. For example, the UCI machine learning repository is extensively used by researchers to compare algorithms across various domains. No such benchmark datasets are available for changing environments. Also, while generating data for static environments is relatively straightforward, this is not so for changing environments. The reason is that an infinite amount of changes can be simulated, and it is difficult to define which ones will be realistic and hence useful. In this paper we propose a general framework for generating data to simulate changing environments. The paper gives illustrations of how the framework encompasses various types of changes observed in real data and also how the two most popular simulation models (STAGGER and moving hyperplane) are represented within.
An Evaluation of Scalable Application-Level Multicast Built Using Peer-To-Peer Overlay Networks

Peer-to-peer overlay networks such as CAN, Chord, Pastry, and Tapestry can be used to implement Internet-scale application-level multicast. There are two general approaches to accomplishing this: tree building (used by Bayeux and Scribe); and flooding (used by CAN Multicast). This paper presents of an evaluation of these two approaches using CAN and Pastry as the underlying overlay networks. We chose CAN and Pastry as representatives of the two major kinds of peer-to-peer overlays. In particular, Chord, Pastry and Tapestry all use a form of generalized hypercube routing with longest-prefix matching, whereas CAN uses a numerical distance metric to route through a Cartesian hyper-space. To the best of our knowledge, this paper reports the first head-tohead comparison of CAN-style versus Pastry-style overlay networks, using multicast communication workloads running on an identical simulation infrastructure. Furthermore, we observe that the approach to multicast is independent of overlay network choice, and we then provide a head-to-head comparison of flooding versus tree-based multicast on both styles of overlays. We find that the tree-based multicast approach consistently outperforms the flooding approach. We show that the biggest disadvantage of the flooding approach is the cost of constructing a new overlay for each multicast group. Finally, for the tree-based multicast, we show that Pastry can optionally provide higher performance than CAN but
Multicarbohydrase Enzymes for Non-ruminants

The first purpose of this review is to outline some of the background information necessary to understand the mechanisms of action of fibre-degrading enzymes in non-ruminants. Secondly, the well-known and understood mechanisms are described, i) eliminating the nutrient encapsulating effect of the cell wall and ii) ameliorating viscosity problems associated with certain Non Starch Polysaccharides, particularly arabinoxylans and β-glucans. A third, indirect mechanism is then discussed: the activity of such enzymes in producing prebiotic oligosaccharides and promoting beneficial cecal fermentation. The literature contains a wealth of information on various non starch polysaccharide degrading enzyme (NSPase) preparations and this review aims to conclude by discussing this body of work, with reference to the above mechanisms. It is suggested that the way in which multi- versus single-component products are compared is often flawed and that some continuity should be employed in methods and terminology.
Case study of two brothers, one with Down syndrome: minute level relationship between displacement and expressive and receptive vocabulary

brothers, level relationship between displacement and expressive and receptive Abstract The purpose of this study is two-fold. First, to investigate the occurrence of displacement, adult word count (AWC), and child vocalization (CV), for two brothers, one with Down syndrome and one who is typically developing, on a minute level basis, in an inclusive play setting, over the course of two years. Second, to investigate to co-occurrence of displacement and CV. Data regarding displacement, AWC, and CV was collected and analyzed over two different study periods, one in 2016 and one in 2017. Over the two years, the child with typical development (TD) and the child with Down syndrome (DS) showed an increase in displacement from 2016 to 2017. Both brothers demonstrated no change in AWC over time. The TD child saw an increase in CV while the child with DS demonstrated no change in CV over time. Furthermore, there seemed to be no relationship between displacement and CV for both the brothers.
Efficient incremental map segmentation in dense RGB-D maps

In this paper we present a method for incrementally segmenting large RGB-D maps as they are being created. Recent advances in dense RGB-D mapping have led to maps of increasing size and density. Segmentation of these raw maps is a first step for higher-level tasks such as object detection. Current popular methods of segmentation scale linearly with the size of the map and generally include all points. Our method takes a previously segmented map and segments new data added to that map incrementally online. Segments in the existing map are re-segmented with the new data based on an iterative voting method. Our segmentation method works in maps with loops to combine partial segmentations from each traversal into a complete segmentation model. We verify our algorithm on multiple real-world datasets spanning many meters and millions of points in real-time. We compare our method against a popular batch segmentation method for accuracy and timing complexity.
Exploring anterograde associative memory in London taxi drivers

London taxi drivers are renowned for their navigation ability, spending a number of years acquiring ‘The Knowledge’ of London’s complex layout and having to pass stringent examinations to obtain an operating licence. In several studies, this navigation skill has been associated with increased posterior but also decreased anterior hippocampal grey matter volume. Neuropsychologically, gain and loss has also been documented in taxi drivers; while very skilled at navigation in London, they are significantly poorer than controls at learning and recalling new object–location associations. Here we tested a group of London taxi drivers and matched control participants on this object–location associations task, while also subjecting them to a battery of challenging anterograde associative memory tests involving verbal, visual and auditory material both within and across modalities. Our aim was to assess whether their difficulty in previous studies reflected a general problem with associative memory, or was restricted to the spatial domain. We replicated previous findings of poor learning and memory of object–location associations. By contrast, their performance on the other anterograde associative memory tasks was comparable with controls. This resolves an outstanding question in the memory profile of London taxi drivers following hippocampal plasticity, and underlines the close relationship between space and the hippocampus.
Partial Human Data in Design of Human-Like Walking Control in Humanoid Robotics

In this paper a human-based control strategy is proposed for walking of humanoid robots. Its basic idea lies in the control of the CoM as well as the relative position of robot's feet. Through the proposed study, it is shown that this reduced set of data allows to fully describe and reproduce a whole body human-like walking. In addition of reducing the number of controlled variables, the proposed control strategy has the advantage of not requiring a complete walking cycle decomposition due to its continuous character. Simulations results are presented to show the e®ectiveness of the proposed control scheme.
Dynamic Drop Models

We follow the dynamic evolution of a cluster of Ising spins pointing up surrounded by other spins pointing down, on a lattice. The cluster represents a liquid drop. Under a microscopic point of view, the short range ferromagnetic coupling between these spins plays the role of the van der Waals attraction. Alternatively, under a macroscopic point of view, the same ferromagnetic coupling gives rise to the surface tension along the drop boundary. This naive model is applied to the study of different systems, out of thermodynamic equilibrium. For each such a system, other interaction terms can be included, for instance an external magnetic field with a downwards uniform gradient, representing Earth's gravity. Also, for each system, proper dynamic rules and boundary conditions are adopted. The behaviour of such a drop is monitored as a function of time, through computer simulations. Many quantities of interest, in particular those related to drop fragmentation, were measured and the results were compared with available experimental data. The real systems we have in mind are exemplified by water drops falling from a leaky faucet, nuclear multifragmentation, mercury drops falling on the ground, magnetic hysteresis curves, and interface roughness.
The Timing of Redistribution

We investigate whether late redistribution programs that can be targeted toward low income families, but that may distort savings decisions, can “dominate” early redistribution programs that cannot be targeted as a result of information constraints. We use simple two-period overlapping generations models with heterogeneous agents under six policy regimes: a model calibrated to the U.S. economy (benchmark), two early redistribution (lump sum) regimes, two (targeted) late redistribution regimes, and finally a model without taxes and redistribution. Redistribution programs are financed by a labor tax on the young generation and a capital tax on the old generation. We argue that if the programs are small in size, late redistribution can dominate early redistribution in terms of welfare but not in terms of real output. Better targeting of low income households cannot completely offset savings distortions. In addition, we find that the optimal transfer and tax policy implies a capital tax of 100% and transfers exclusively to the young generation.
Self-Tuning Systems: Control and Signal Processing

From the Publisher: Geared to the users' needs, this work provides comprehensive coverage of the main techniques and methods necessary to construct a self-tuning and self-adaptive system. Eliminating a lot of theoretical rigor, it provides the reader with a fundamental understanding of basic algorithms and techniques useful in self-tuning control and signal processing. Every aspect of adaptive engineering is thoroughly covered including extensive descriptions of applications, commercial instruments and current research. Besides offering sections on advanced and detailed topics, the book provides a wide selection of tutorial problems that will aid and stimulate the reader.
Composition, Buoyancy Regulation and Fate of Ice Algal Aggregates in the Central Arctic Ocean

Sea-ice diatoms are known to accumulate in large aggregates in and under sea ice and in melt ponds. There is recent evidence from the Arctic that such aggregates can contribute substantially to particle export when sinking from the ice. The role and regulation of microbial aggregation in the highly seasonal, nutrient- and light-limited Arctic sea-ice ecosystem is not well understood. To elucidate the mechanisms controlling the formation and export of algal aggregates from sea ice, we investigated samples taken in late summer 2011 and 2012, during two cruises to the Eurasian Basin of the Central Arctic Ocean. Spherical aggregates densely packed with pennate diatoms, as well as filamentous aggregates formed by Melosira arctica showed sign of different stages of degradation and physiological stoichiometries, with carbon to chlorophyll a ratios ranging from 110 to 66700, and carbon to nitrogen molar ratios of 8–35 and 9–40, respectively. Sub-ice algal aggregate densities ranged between 1 and 17 aggregates m−2, maintaining an estimated net primary production of 0.4–40 mg C m−2 d−1, and accounted for 3–80% of total phototrophic biomass and up to 94% of local net primary production. A potential factor controlling the buoyancy of the aggregates was light intensity, regulating photosynthetic oxygen production and the amount of gas bubbles trapped within the mucous matrix, even at low ambient nutrient concentrations. Our data-set was used to evaluate the distribution and importance of Arctic algal aggregates as carbon source for pelagic and benthic communities.
A predictive speller controlled by a brain-computer interface based on motor imagery

Persons suffering from motor disorders have limited possibilities for communicating and normally require assistive technologies to fulfill this primary need. Promising means of providing basic communication abilities to subjects affected by severe motor impairments include brain-computer interfaces (BCIs), that is, systems that directly translate brain signals into device commands, bypassing any muscle or nerve mediation. To date, the use of BCIs for effective verbal communication is yet an open issue, primarily due to the low rates of information transfer that can be achieved with this technology. Still, performance of BCI spelling applications could be considerably improved by a smart user interface design and by the adoption of natural language processing (NLP) techniques for text prediction. The objective of this work is to suggest an approach and a user interface for BCI spelling applications combining state-of-the-art BCI and NLP techniques to maximize the overall communication rate of the system. The BCI paradigm adopted is motor imagery, that is, when the subject imagines moving a certain part of the body, he/she produces modifications to specific brain rhythms that are detected in real-time through an electroencephalogram and translated into commands for a spelling application. By maximizing the overall communication rate, our approach is twofold: on one hand, we maximize the information transfer rate from the control signal, on the other hand, we optimize the way this information is employed for the purpose of verbal communication. The achieved results are satisfactory and comparable with the latest works reported in literature on motor-imagery BCI spellers. For the three subjects tested, we obtained a spelling rate of respectively 3 char/min, 2.7 char/min, and 2 char/min.
Improving the Performance of the Sparse Matrix Vector Product with GPUs

Sparse matrices are involved in linear systems, eigensystems and partial differential equations from a wide spectrum of scientific and engineering disciplines. Hence, sparse matrix vector product (SpMV) is considered as key operation in engineering and scientific computing. For these applications the optimization of the sparse matrix vector product (SpMV) is very relevant. However, the irregular computation involved in SpMV prevents the optimum exploitation of computational architectures when the sparse matrices are very large. Graphics Processing Units (GPUs) have recently emerged as platforms that yield outstanding acceleration factors. SpMV implementations for GPUs have already appeared on the scene. This work proposes and evaluates new implementations of SpMV for GPUs called ELLR-T. They are based on the format ELLPACK-R, which allows storage of the sparse matrix in a regular manner. A comparative evaluation against a variety of storage formats previously proposed has been carried out based on a representative set of test matrices. The results show that: (1) the SpMV is highly accelerated with GPUs; (2) the performance strongly depends on the specific pattern of the matrix; and (3) the implementations ELLR-T achieve higher overall performance. Consequently, the new implementations of SpMV, ELLR-T, described in this paper can help to exploit the GPUs, because, they achieve high performance and they can be easily joined in the engineering and scientific computing.
Resolving fluid boundary layers with particle strength exchange and weak adaptivity

Most fluid scenarios in graphics have a high Reynolds number, where viscosity is dominated by inertial effects, thus most solvers drop viscosity altogether: numerical damping from coarse grids is generally stronger than physical viscosity while resembling it in character. However, viscosity remains crucial near solid boundaries, in the boundary layer, to a large extent determining the look of the flow as a function of Reynolds number. Typical graphics simulations do not resolve boundary layer dynamics, so their look is determined mostly by numerical errors with the given grid size and time step, rather than physical parameters. We introduce two complementary techniques to capture boundary layer dynamics, bringing more physical control and predictability. We extend the FLIP particle-grid method with viscous particle strength exchange[Rivoalen and Huberson 2001] to better transfer momentum at solid boundaries, dubbed VFLIP. We also introduce Weakly Higher Resolution Regional Projection (WHIRP), a cheap and simple way to increase grid resolution where important by overlaying high resolution grids on the global coarse grid.
Targeting Src in Mucinous Ovarian Carcinoma

Purpose: Mucinous ovarian carcinomas have a distinct clinical pattern compared with other subtypes of ovarian carcinoma. Here, we evaluated (i) stage-specific clinical significance of mucinous ovarian carcinomas in a large cohort and (ii) the functional role of Src kinase in preclinical models of mucinous ovarian carcinoma. Experimental Design: A total of 1,302 ovarian cancer patients including 122 (9.4%) cases of mucinous carcinoma were evaluated for survival analyses. Biological effects of Src kinase inhibition were tested using dasatinib-based therapy in a novel orthotopic mucinous ovarian cancer model (RMUG-S-ip2). Results: Patients with advanced-stage mucinous ovarian cancer had significantly worse survival than those with serous histology: median overall survival, 1.67 versus 3.41 years, P = 0.002; median survival time after recurrence of 0.53 versus 1.66 years, P < 0.0001. Among multiple ovarian cancer cell lines, RMUG-S-ip2 mucinous ovarian cancer cells showed the highest Src kinase activity. Moreover, oxaliplatin treatment induced phosphorylation of Src kinase. This induced activity by oxaliplatin therapy was inhibited by concurrent administration of dasatinib. Targeting Src with dasatinib in vivo showed significant antitumor effects in the RMUG-S-ip2 model but not in the serous ovarian carcinoma (SKOV3-TR) model. Combination therapy of oxaliplatin with dasatinib further showed significant effects on reducing cell viability, increasing apoptosis, and in vivo antitumor effects in the RMUG-S-ip2 model. Conclusions: Our results suggest that poor survival of women with mucinous ovarian carcinoma is associated with resistance to cytotoxic therapy. Targeting Src kinase with a combination of dasatinib and oxaliplatin may be an attractive approach for this disease. Clin Cancer Res; 17(16); 5367–78. ©2011 AACR.
A dynamic request dispatching system for IT service management

IT service delivery becomes an increasingly challenging business as customers demand improved quality of service while providers are driven to reduce the cost of delivery. While effective service delivery requires advances in many areas including workload management and workforce optimization, in this paper we focus on service request dispatching decision-making. Specifically, we propose an implementation of a dynamic request dispatching system that continually adjusts the priority of service requests considering both (static) contractual service attainment targets and (dynamic) attainment levels achieved.
Doctoral studies as an initiatory trial: expected and taken-for-granted practices that impede PhD students’ progress

ABSTRACT Intellectual abilities alone are not sufficient to successfully progress through doctoral studies. Research indicates that modes of training and the context and conditions in which doctoral studies take place also have a significant impact on the process. However, few studies examine how taken-for-granted and self-evident practices in academia likely impede students’ progress. To address this gap, a qualitative inquiry was conducted according to an instrumental case study design. Six human and social sciences faculties at a Canadian university were selected to define the case. In addition to analysing institutional documents pertaining to doctoral studies in this specific context, semi-structured interviews were conducted with 36 PhD students, 14 thesis supervisors and five academic administrators. Based on Giddens’ theory of structuration, the analysis revealed an enduring perception of doctoral studies as an ‘initiatory trial’ that affects both the formal and tacit organisation of the process, and consequently its underlying challenges.