Miracle-dz/UniFAR-FTUs huggingface dataset:
Processing operations with restrictions in RDBMS without external sorting: the Tetris algorithm

Most operations of the relational algebra or SQL require a sorted stream of tuples for efficient processing. Therefore, processing complex relational queries relies on efficient access to a table in some sort order. In principle, indexes could be used, but they are superior to a full table scan only if the result set is sufficiently restricted in the index attribute. We present the Tetris algorithm, which utilizes restrictions to process a table in sort order of any attribute without the need for external sorting. The algorithm relies on the space partitioning of a multidimensional access method. A sweep line technique is used to read data in sort order of any attribute, while accessing each disk page of a table only once. Results are produced earlier than with traditional sorting techniques allowing better response times for interactive applications and pipelined processing of the result set. We describe a prototype implementation of the Tetris algorithm using UB-Trees on top of Oracle 8, define a cost model and present performance measurements for some queries of the TPC-D benchmark.
Fast Gaussian process regression using representative data

Gaussian process regression is a Bayesian nonparametric regression model. Although the Gaussian process regression has shown good performance in various experiments, it suffers from O(N/sup 3/) computational cost, where N is the number of training data. We propose a method using representative data for the Gaussian process regression. The representative data are modified so that the regression model fits the original training data. The proposed method requires O(NM/sup 2/) computational cost, where M(<N) is the number of the representative data. According to our experiments, the results of the proposed method are comparable to those of the original method, although it requires only much smaller number of the representative data than the number of the original training data.
Happiness Across the Life Cycle : Exploring Age-Specific Preferences by Orsolya Lelkes Aims

Existing evidence suggests that there is a u-shaped relationship between age and happiness, where happiness is the lowest in the middle age, when controlling for income and education and other personal characteristics. on the other hand, there is no clear pattern between old age and happiness without the use of controls. thus, it is not ageing as such, which results in declining happiness, but rather the circumstances associated with ageing. had the elderly not been confronted with these circumstances, they would live a much happier period of their lives than in their middle ages. in an ageing society the question arises: which of these circumstances could be averted in order to provide a high wellbeing for the old? in order to answer these questions, we also need to explore whether the attitudes and preferences of the elderly are similar to others. the paper aims to explore these issues, using a cross-country survey.
A Description of Tucumán Spanish Intonation in Argentina

Abstract This paper documents for the first time the intonation system of Tucumán Spanish, an understudied variety of Argentinian Spanish. Semi-spontaneous speech illustrating the intonation of main sentence types, i.e. broad focus statements, partial and absolute interrogatives, and imperatives and vocatives, was elicited from 31 native speakers of Tucumán Spanish via an adapted version of the Argentinian Intonation Survey (Prieto and Roseano, 2009-2013). The two authors listened to the recordings and transcribed them using the Tones and Break Indexes conventions (ToBI) (Beckman et al. 2002, Prieto and Roseano 2010, Hualde and Prieto 2015). Transcriptions of prenuclear and nuclear configurations together with their respective frequencies allowed both an appreciation of the most used configurations within each sentence type along with detailed variation at the phonetic level. For example, yes/no questions were consistently realized with a low nuclear pitch accent L* and an ascending boundary tone. However, there was variation in the height of the boundary tones yielding the frequent contour L* ¡H%, and the less frequent L* H%. Altogether, these detailed patterns document the systematic phonetic variation of the intonation system of TS and provide a basis for future research to determine the phonological status of this variation.
The Role of Lymphatic Transport on the Systemic Bioavailability of the Bcl-2 Protein Family Inhibitors Navitoclax (ABT-263) and ABT-199

Navitoclax (ABT-263), a Bcl-2 family inhibitor and ABT-199, a Bcl-2 selective inhibitor, are high molecular weight, high logP molecules that show low solubility in aqueous media. While these properties are associated with low oral bioavailability (F), both navitoclax and ABT-199 showed moderate F in preclinical species. The objective of the described study was to determine if lymphatic transport contributes to the systemic availability of navitoclax and ABT-199 in dogs. The intravenous pharmacokinetics of navitoclax and ABT-199 were determined in intact (noncannulated) dogs. In oral studies, tablets (100 mg) of navitoclax and ABT-199 were administered to both intact and thoracic lymph duct–cannulated (TDC) dogs. The clearance of navitoclax and ABT-199 was low; 0.673 and 0.779 ml/min per kilogram, respectively. The volume of distribution of both compounds was low (0.5-0.7 l/kg). The half-lives of navitoclax and ABT-199 were 22.2 and 12.9 hours, respectively. The F of navitoclax and ABT-199 were 56.5 and 38.8%, respectively, in fed intact dogs. In fed TDC dogs, 13.5 and 4.67% of the total navitoclax and ABT-199 doses were observed in lymph with the % F of navitoclax and ABT-199 of 21.7 and 20.2%, respectively. The lower lymphatic transport of ABT-199 corresponds to the lower overall % F of ABT-199 versus navitoclax despite similar systemic availability via the portal vein (similar % F in TDC animals). This is consistent with the higher long chain triglyceride solubility of navitoclax (9.2 mg/ml) versus ABT-199 (2.2 mg/ml). In fasted TDC animals, lymph transport of navitoclax and ABT-199 decreased by 1.8-fold and 10-fold, respectively.
Unsupervised authorship analysis of phishing webpages

Authorship analysis on phishing websites enables the investigation of phishing attacks, beyond basic analysis. In authorship analysis, salient features from documents are used to determine properties about the author, such as which of a set of candidate authors wrote a given document. In unsupervised authorship analysis, the aim is to group documents such that all documents by one author are grouped together. Applying this to cyber-attacks shows the size and scope of attacks from specific groups. This in turn allows investigators to focus their attention on specific attacking groups rather than trying to profile multiple independent attackers. In this paper, we analyse phishing websites using the current state of the art unsupervised authorship analysis method, called NUANCE. The results indicate that the application produces clusters which correlate strongly to authorship, evaluated using expert knowledge and external information as well as showing an improvement over a previous approach with known flaws.
Robust Object Detection in Images Components

In this thesis we develop a component based person detection system that is capable of detecting frontal, rear and near side views of people, and partially occluded persons in cluttered scenes. The framework that is described here for people is easily applied to other objects as well. The motivation for developing a component based approach is two fold: first, to enhance the performance of person detection systems on frontal and rear views of people and second, to develop a framework that directly addresses the problem of detecting people who are partially occluded or whose body parts blend in with the background. The data classification is handled by several support vector machines classifiers arranged in two layers. This architecture is known as Adaptive Combination of Classifiers (ACC). The system performs very well and is capable of detecting people even when all components of a person are not found. The performance of the system is significantly better than a full body person detector designed along similar lines. This implies that the improved performance is due to the components based approach and the ACC data classification structure. Thesis Supervisor: Tomaso Poggio Title: Uncas and Helen Whitaker Professor Department: Department of Brain and Cognitive Sciences
MRI Noise Reduction via Phase Correction and Wavelet-Domain Filtering

Post-acquisition processing of MRI images to remove noise can potentially improve their diagnostic value. Currently there are many suggested wavelet thresholding algorithms for denoising MRI data with most of them focused on magnitude-reconstructed images. An alternate approach is to correct phase errors in the image and then take the real value of each pixel as the grayscale intensity. We present a two-step technique, involving first performing phase correction and then wavelet filtering the real values to produce the final image. We compare the results of this two-step process to using just wavelet processing or just phase correction.
Taxonomy of fungi causing mucormycosis and entomophthoramycosis (zygomycosis) and nomenclature of the disease: molecular mycologic perspectives.

Molecular phylogenetic analysis confirmed the phylum Zygomycota to be polyphyletic, and the taxa conventionally classified in Zygomycota are now distributed among the new phylum Glomeromycota and 4 subphyla incertae sedis (uncertain placement). Because the nomenclature of the disease zygomycosis was based on the phylum Zygomycota (Zygomycetes) in which the etiologic agents had been classified, the new classification profoundly affects the name of the disease. Zygomycosis was originally described as a convenient and inclusive name for 2 clinicopathologically different diseases, mucormycosis caused by members of Mucorales and entomophthoramycosis caused by species in the order Entomophthorales of Zygomycota. Without revision of original definition, the name "zygomycosis," however, has more often been used as a synonym only for mucormycosis. This article reviews the progress and changes in taxonomy and nomenclature of Zygomycota and the disease zygomycosis. The article also reiterates the reasons why the classic names "mucormycosis" and "entomophthoramycosis" are more appropriate than "zygomycosis. "
A Comparisoii of Techniques for Scheduling Earth-Observing Satellites

Scheduling observations by coordinated fleets of Earth Observing Satellites . (EOS) involves large search spaces, complex constraints and poorly understood bottlenecks, conditions where e\*olutiona.ry and related algorithms are often effective. However, there are many such algorithms and the best one to use is not clear. Here we compare multiple variants of the ge-netic algorithm: stochastic hill climbing, simulated annealing. squeaky wheel opt.imization and iterated sampling on ten realistically-sized EOS scheduling problems. Schedules are represented by a permutation (non-temperal ordering) of the observation requests. A simple deterministic scheduler assigns times and resources to each observation request in the order indicated by the permutation, discarding tkiose that violate the constraints created by previously scheduled observations. Simulated annealing performs best. Random mutation outperform a more ‘intelligent’ mutator. Furthermore, the best niutator, by a small margin, was a novel approach we call ’temperature dependent ran-do= sm-ap’ that makes large changes in the early stages of evolution and smaller changes towards the end of search.
Applying niching genetic algorithms for multiple cluster discovery in spatial analysis

Traditional genetic algorithms with elitist selection are unable to locate more than one solution in a multimodal fitness landscape in a single run. This genetic drift is illustrated in Mapex, a smart spatial analysis technique, employing a genetic algorithm for spatial cluster discovery. However, for detecting multiple clusters Mapex provides a non-ideal approach. In this paper, we use a fitness sharing niching technique along with circle overlap detection to enhance Mapex. The results show the suitability of such an approach to locate solutions in a multimodal domain.
Wavelet Domain Radiofrequency Pulse Design Applied to Magnetic Resonance Imaging

A new method for designing radiofrequency (RF) pulses with numerical optimization in the wavelet domain is presented. Numerical optimization may yield solutions that might otherwise have not been discovered with analytic techniques alone. Further, processing in the wavelet domain reduces the number of unknowns through compression properties inherent in wavelet transforms, providing a more tractable optimization problem. This algorithm is demonstrated with simultaneous multi-slice (SMS) spin echo refocusing pulses because reduced peak RF power is necessary for SMS diffusion imaging with high acceleration factors. An iterative, nonlinear, constrained numerical minimization algorithm was developed to generate an optimized RF pulse waveform. Wavelet domain coefficients were modulated while iteratively running a Bloch equation simulator to generate the intermediate slice profile of the net magnetization. The algorithm minimizes the L2-norm of the slice profile with additional terms to penalize rejection band ripple and maximize the net transverse magnetization across each slice. Simulations and human brain imaging were used to demonstrate a new RF pulse design that yields an optimized slice profile and reduced peak energy deposition when applied to a multiband single-shot echo planar diffusion acquisition. This method may be used to optimize factors such as magnitude and phase spectral profiles and peak RF pulse power for multiband simultaneous multi-slice (SMS) acquisitions. Wavelet-based RF pulse optimization provides a useful design method to achieve a pulse waveform with beneficial amplitude reduction while preserving appropriate magnetization response for magnetic resonance imaging.
A map approach for ℓq-norm regularized sparse parameter estimation using the EM algorithm

In this paper, Bayesian parameter estimation through the consideration of the Maximum A Posteriori (MAP) criterion is revisited under the prism of the Expectation-Maximization (EM) algorithm. By incorporating a sparsity-promoting penalty term in the cost function of the estimation problem through the use of an appropriate prior distribution, we show how the EM algorithm can be used to efficiently solve the corresponding optimization problem. To this end, we rely on variance-mean Gaussian mixtures (VMGM) to describe the prior distribution, while we incorporate many nice features of these mixtures to our estimation problem. The corresponding MAP estimation problem is completely expressed in terms of the EM algorithm, which allows for handling nonlinearities and hidden variables that cannot be easily handled with traditional methods. For comparison purposes, we also develop a Coordinate Descent algorithm for the ℓq-norm penalized problem and present the performance results via simulations.
Tunable Control Strategy for Wave Energy Converters With Limited Power Takeoff Rating

In wave energy converters (WECs), the maximum power extraction would be achievable at the expense of a very high rating of the electric and power electronics equipment. The goal of this paper is to show how a convenient tradeoff between high-power extraction and viable electrical device rating can be achieved by a proper choice of the WEC control strategy. Referring to a direct coupled point absorber in heave operating in regular waves, it will be analytically shown how most common control techniques impact on both the power performance and the power takeoff (PTO) rating. Thus, a tool that can assist in the preliminary PTO sizing by taking into account the main constraints imposed by the application is obtained. Following, an adaptive control strategy including a reactive component is proposed, whose goal is to improve the overall system performance when the WEC is already operative in the sea. Its effectiveness in increasing the average power extraction while respecting the PTO peak power constraint is proved by computer simulations in both regular and irregular waves, and specific analyses also including the PTO force/torque limitation are finally developed.
An examination of changes in spoken productions within constraint-induced aphasia therapy

ABSTRACT Background: Researchers are continuing to investigate the impact of constraint-induced aphasia therapy (CIAT) programs on the spoken language capabilities of people with aphasia at the utterance and discourse level. Currently, there is a lack of consensus on how spoken productions should be measured and there are no investigations that explore the spoken language that people with aphasia use during a CIAT program. Therefore, clinicians and researchers cannot truly know if they are utilizing the most revealing outcome measures to illuminate treatment induced gains in spoken production. Aims: The purpose of this investigation was to examine the within treatment learning of people with aphasia in a CIAT program, by exploring the sensitivity of measures of content, length, syntax, and efficiency at the utterance level and reveal linguistic gains. Methods & Procedures: A repeated measures design was employed to examine 200 utterance samples from eight participants with various types and severity of chronic aphasia between early and late treatment sessions. The measures of correct information units (CIUs), counted words, T-Units, CIUs per utterance, mazes, and mean length of utterance were compared. Outcomes & Results: Nonparametric analyses revealed significant positive gains for the participants in the number of produced CIUs (p = 0.035), counted words (p = 0.012), T-Units, (p = 0.025), and CIUs per utterance (p = 0.012). A significant decrease in the amount of mazes (p = 0.028) was also found. No significant increase was detected in the participants’ mean length of utterance (p = 0.161). Conclusions: The participants displayed advances in the content, syntax, and efficiency of their spoken utterances during the course of a 10-day CIAT program. Specifically, the measures of CIUs, counted words, mazes, and CIUs per utterance emerged as being the most sensitive to capture the within treatment changes made by the participants. The utility of these measures should be further explored to establish treatment baselines, demonstrate within treatment learning, and show posttreatment gains.
Gait generation and transition for a five-link biped robot by Central Pattern Generator

In recent decades, the locomotion control has been a main research field in robotics. In locomotion control problems, understanding the relationship between neuroscience and robotics is very important. In this work, a bio-inspired method for the gait generation and transition of a biped robot is implemented. This method uses a Central Pattern Generator (CPG), which is a neural network responsible for generating rhythmic output signals without sensory information. Humans and animals have the ability to produce various gaits by CPG according to the environmental conditions. The 4-cell CPG model proposed by Golubitsky et al, and symmetry in this model are used for walk and run gaits generation. In this work, Transitions from walk to skip and from run to skip are achieved by changing coupling weights of walk and run. The Morris-Lecar oscillator is used as the oscillator of each cell. The numerical simulations of periodic signals corresponding to the five-link bipedal walk and run gaits and transitions from walk to skip and run to skip are shown in the 4-cell CPG model. The periodic signals resulting of this model can be used as joint angles of hip and knee joints of a five-link biped robot. The results obtained in this work show the feasibility of using CPG-based methods to generate five-link biped locomotion and transitions between different gaits.
MUI-suppression with reduced T-equalizer for UTRA FDD downlink

Wideband CDMA systems with orthogonal spreading codes suffer severely due to the loss of orthogonality by multipath propagation. This yields multiple user interference (MUI), which gravely reduces the performance of classical systems with RAKE-receivers. We attempt to restore orthogonality by using a modified T-equalizer. Classical T-equalizers are composed as FIR filters with equidistant delays and appropriate coefficients. Their main disadvantage is the high computational effort due to the large number of coefficients. The question arises whether we need to calculate all equally spaced coefficients, or if some of the coefficients can be neglected. Basically, we use only a subset of coefficients and set all others to zero. The main advantages are the reduced computational effort in calculating the filter and the decreased computational costs in using it. We show the feasibility with some simulation results for block fading channels. In practice, a T-equalizer is not very often used for time variant channels, due to its high computational costs. Instead, an adaptive algorithm is taken and modified accordingly. We take a least mean squares (LMS) algorithm for MUI-suppression in a time variant environment. In order to show the feasibility of this approach, some simulation results for channels with low Doppler frequency are presented and compared with the classical RAKE-receiver and a full version of the LMS/Griffith by M.J. Heikkila (see Proc. IEEE Int. Symp. on Personal, Indoor and Mobile Radio Commun., PIMRC, 2001).
The fibroproliferative response in acute respiratory distress syndrome: mechanisms and clinical significance

Acute respiratory distress syndrome (ARDS) continues to be a major healthcare problem, affecting >190 000 people in the USA annually, with a mortality of 27–45%, depending on the severity of the illness and comorbidities. Despite advances in clinical care, particularly lung protective strategies of mechanical ventilation, most survivors experience impaired health-related quality of life for years after the acute illness. While most patients survive the acute illness, a subset of ARDS survivors develops a fibroproliferative response characterised by fibroblast accumulation and deposition of collagen and other extracellular matrix components in the lung. Historically, the development of severe fibroproliferative lung disease has been associated with a poor prognosis with high mortality and/or prolonged ventilator dependence. More recent studies also support a relationship between the magnitude of the fibroproliferative response and long-term health-related quality of life. The factors that determine which patients develop fibroproliferative ARDS and the cellular mechanisms responsible for this pathological response are not well understood. This article reviews our current understanding of the contribution of pulmonary dysfunction to mortality and to quality of life in survivors of ARDS, the mechanisms driving pathological fibroproliferation and potential therapeutic approaches to prevent or attenuate fibroproliferative lung disease. Despite protective ventilation, a subset of ARDS survivors develop lung fibrosis contributing to poor quality of life http://ow.ly/q8xCo