Miracle-dz/UniFAR-FTUs huggingface dataset:
Real and integer Wedderburn rank reduction formulas for matrix decompositions

The Wedderburn rank reduction formula is a powerful method for developing matrix factorizations and many fundamental numerical linear algebra processes. We present a new interpretation of the Wedderburn rank reduction formula and its associated biconjugation process and see a more extensive result of the formula. In doing this, we propose a new formulation based on the null space transformations on rows and columns of A simultaneously, and show several matrix factorizations that can be derived from the Wedderburn rank reduction formula. We also present a generalization of the biconjugation process and compute banded and Hessenberg factorizations. Using the new formulation, we compute the WZ and ZW factorizations of a nonsingular matrix as well as the and the factorizations of a symmetric positive definite matrix. Then, we develop the integer Wedderburn rank reduction formula and its integer biconjugation process and present a class of algorithms for computing all integer matrix factorizations such as the integer LU factorization and the Smith normal form of an arbitrary integer matrix.
Improving event prediction by representing script participants

Automatically learning script knowledge has proved difﬁcult, with previous work not or just barely beating a most-frequent baseline. Script knowledge is a type of world knowledge which can however be useful for various task in NLP and psycholinguistic modelling. We here propose a model that includes participant information (i.e., knowledge about which participants are relevant for a script) and show, on the Dinners from Hell corpus as well as the InScript corpus, that this knowledge helps us to signiﬁcantly improve prediction performance on the narrative cloze task.
Relationship between Functional Status Prior to Onset of Critical Illness and Mortality: A Prospective Multicentre Cohort Study

This prospective study aimed to assess the association between prior functional status and hospital mortality for patients admitted to four intensive care units in Spain between 2006 and 2012. Prior functional status was classified into three groups, using a modification of the Glasgow Outcome Scale (GOS), including group 1 with no limitations on activities of daily living; group 2 with some limitations but self-sufficient; and group 3 who were dependent on others for their activities of daily living. Of the 1,757 patients considered (mean Simplified Acute Physiology Score [SAPS] predicted mortality 14.8% and hospital mortality 13.7%), group 1 had the lowest observed hospital mortality (8.3%) compared to the SAPS 3 predicted mortality (11.6%). The observed mortality for group 2 (20.6%) and group 3 (27.4%) were both higher than predicted (19.2% and 21.2% respectively; odds ratio [OR] 1.97, 95% confidence interval [CI] 1.38–2.82 for group 2 and OR 2.90, 95% CI 1.78–4.72 for group 3 compared to group 1). Combining prior functional status and Sequential Organ Failure Assessment (SOFA) score with SAPS 3 further improved the ability of the SAPS 3 scores in predicting hospital mortality (area under the receiver operating characteristic curve 0.85 [95% CI 0.82–0.88] versus 0.84 [95% CI 0.81–0.87] respectively). In summary, patients with limited functional status prior to ICU admission had a higher risk of observed hospital mortality than predicted. Assessing prior functional status using a relatively simple questionnaire, such as a modified GOS, has the potential to improve the accuracy of existing prognostic models.
Reshaping our model of the world over time

An accurate estimate of the 3D-structure in the environment is key to robotic applications such as autonomous inspection, obstacle avoidance and manipulation. Recent years have seen substantial algorithmic advances towards creating highly accurate models of small objects as well as large scale architectural structures. Most commonly a rich set of images covering a static scene are used to jointly estimate the pose of the cameras and the observed 3D-structure. For many practical application however the assumption of static scenes and sufficient coverage by images does not hold. In fact for industrial inspection the change in the scene is of most interest and the limited resources on mobile platforms don't allow for extensive data captures. In this paper we investigate the potential of combining multiple independent captures of a place to selectively reconstruct a scene over time. We propose an incremental reconstruction algorithm which identifies and fuses novel data into a joint model of the scene. Being able to identify changing parts of the scene is particularly interesting for mobile applications where bandwidth, storage and processing power are limited. Through detailed experiments, we show the potential of our approach to use multiple mobile devices to reconstruct and update a model of the static part of the environment over time.
Adenosine A2A receptor activation and macrophage‐mediated experimental glomerulonephritis

In immune‐induced inflammation, leukocytes are key mediators of tissue damage. Since A2A adenosine receptors (A2ARs) are endogenous suppressors of inflammation, we examined cellular and molecular mechanisms of kidney damage to determine if selective activation of A2AR would suppress inflammation in a rat model of glomerulonephritis. Activation of A2AR reduced the degree of kidney injury in both the acute inflammatory phase and the progressive phase of glomerulonephritis. This protection against acute and chronic inflammation was associated with suppression of the glomerular expression of the MDC/CCL22 chemokine and down‐regulation of MIP‐1α/CCL3, RANTES/CCL5, MIP‐1β/CCL4, and MCP‐1/CCL2 chemokines. The expression of anti‐inflammatory cytokines, interluekin (IL)‐4 and IL‐10, also increased. The mechanism for these anti‐inflammatory responses to the A2AR agonist was suppression of macrophages function. A2AR expression was increased in macrophages, macrophage‐derived chemokines were reduced in response to the A2AR agonist, and chemokines not expressed in macrophages did not respond to A2AR activation. Thus, activation of the A2AR on macrophages inhibits immune‐associated inflammation. In glomerulonephritis, A2AR activation modulates inflammation and tissue damage even in the progressive phase of glomerulonephritis. Accordingly, pharmacological activation of A2AR could be developed into a novel treatment for glomerulonephritis and other macro‐phage‐related inflammatory diseases. —Garcia, G. E. , Truong, L. D. , Li, P., Zhang, P., Du, J., Chen, J. F. , Feng, L. Adenosine A2A receptor activation and macrophage‐mediated experimental glomerulonephritis. FASEB J. 22, 445–454 (2008)
Increased Cortical Thickness in Sports Experts: A Comparison of Diving Players with the Controls

Sports experts represent a population of people who have acquired expertise in sports training and competition. Recently, the number of studies on sports experts has increased; however, neuroanatomical changes following extensive training are not fully understood. In this study, we used cortical thickness measurement to investigate the brain anatomical characteristics of professional divers with extensive training experience. A comparison of the brain anatomical characteristics of the non-athlete group with those of the athlete group revealed three regions with significantly increased cortical thickness in the athlete group. These regions included the left superior temporal sulcus, the right orbitofrontal cortex and the right parahippocampal gyrus. Moreover, a significant positive correlation between the mean cortical thickness of the right parahippocampal gyrus and the training experience was detected, which might indicate the effect of extensive training on diving players' brain structure.
FPGA acceleration of quasi-Monte Carlo in finance

Today, quasi-Monte Carlo (QMC) methods are widely used in finance to price derivative securities. The QMC approach is popular because for many types of derivatives it yields an estimate of the price, to a given accuracy, faster than other competitive approaches, like Monte Carlo (MC) methods. The calculation of the large number of underlying asset pathways consumes a significant portion of the overall run-time and energy of modern QMC derivative pricing simulations. Therefore, we present an FPGA-based accelerator for the calculation of asset pathways suitable for use in the QMC pricing of several types of derivative securities. Although this implementation uses constructs (recursive algorithms and double-precision floating point) not normally associated with successful FPGA computing, we demonstrate performance in excess of 50times that of a 3 GHz multi-core processor.
O modelo de “letramentos acadêmicos”: teoria e aplicações

Embora o termo “letramentos acadêmicos” tenha sido originalmente desenvolvido visando ao estudo de letramentos em nível superior, o conceito também se aplica ao período da pré-escola ao ensino médio. Uma perspectiva dos letramentos acadêmicos concebe leitura e escrita como práticas sociais que variam segundo contexto, cultura e gênero (Barton; Hamilton, 1998; Street, 1984, 1985). As práticas de letramento de disciplinas acadêmicas podem ser entendidas como práticas sociais variadas associadas a diferentes comunidades. Além disso, uma perspectiva dos letramentos acadêmicos também leva em consideração letramentos não diretamente relacionados a temas e disciplinas, mas a discursos institucionais mais amplos e a gêneros. Do ponto de vista do estudante, um traço dominante das práticas de letramento acadêmico é a exigência de mudança de estilo de escrita e gênero segundo contexto. O objetivo é dispor de modo conjunto de práticas de letramento apropriadas a cada cenário e lidar com sentidos sociais e identidades que cada prática evoca.
Open Access Research Article Transcriptional Regulation of Gene Expression Clusters in Motor Neurons following Spinal Cord Injury

Background: Spinal cord injury leads to neurological dysfunctions affecting the motor, sensory as well as the autonomic systems. Increased excitability of motor neurons has been implicated in injury-induced spasticity, where the reappearance of self-sustained plateau potentials in the absence of modulatory inputs from the brain correlates with the development of spasticity. Results: Here we examine the dynamic transcriptional response of motor neurons to spinal cord injury as it evolves over time to unravel common gene expression patterns and their underlying regulatory mechanisms. For this we use a rat-tail-model with complete spinal cord transection causing injury-induced spasticity, where gene expression profiles are obtained from labeled motor neurons extracted with laser microdissection 0, 2, 7, 21 and 60 days post injury. Consensus clustering identifies 12 gene clusters with distinct time expression profiles. Analysis of these gene clusters identifies early immunological/inflammatory and late developmental responses as well as a regulation of genes relating to neuron excitability that support the development of motor neuron hyper-excitability and the reappearance of plateau potentials in the late phase of the injury response. Transcription factor motif analysis identifies differentially expressed transcription factors involved in the regulation of each gene cluster, shaping the expression of the identified biological processes and their associated genes underlying the changes in motor neuron excitability. Conclusions: This analysis provides important clues to the underlying mechanisms of transcriptional regulation responsible for the increased excitability observed in motor neurons in the late chronic phase of spinal cord injury suggesting alternative targets for treatment of spinal cord injury. Several transcription factors were identified as potential regulators of gene clusters containing elements related to motor neuron hyper-excitability, the manipulation of which potentially could be used to alter the transcriptional response to prevent the motor neurons from entering a state of hyper-excitability. Background The mammalian central nervous system has limited capability for regeneration. Spinal cord injury therefore leads to neurological dysfunctions affecting the motor, sensory as well as the autonomic systems [1]. In the immediate phase following spinal cord injury the excitability of the motor networks caudal to the injury becomes depressed. This initial state of motor depression is often followed by a maladaptive increase in network excitability resulting in
Classification of the Spoken Hindi Partially Reduplicated Words using Artificial Neural Network

The most ordinary way of information exchange is Speech. It provides an efficient way of man-machine communication using speech interfacing. Speech interfacing involves two process, speech synthesis and speech recognition. Speech recognition allows a computer to identify the words that a person speaks to a microphone or telephone. The two main mechanism, used in speech recognition, are signal processing mechanism at front-end and pattern matching mechanism at back-end. In this paper, a setup for recognition of Spoken Hindi Partially Reduplicated Words (SHPRW), that uses Mel frequency cepstral coefficients at front-end and artificial neural networks at back-end has been developed to perform the experiment. General Terms Automatic Speech Recognition, Endpoint Detection, Feature Extraction, Pattern Recognition, Classification, Recognition Rate.
Controlled release of growth factors based on biodegradation of gelatin hydrogel

To develop a carrier for the controlled release of biologically-active growth factors, biodegradable hydrogels were prepared through glutaraldehyde cross-linking of gelatin with isoelectric points (IEP) of 5.0 and 9.0, i.e. 'acidic' and 'basic' gelatins, respectively. Radioiodinated growth factors were used to investigate their sorption and desorption from the hydrogel of both types of gelatin. Basic fibroblast growth factor (bFGF) and transforming growth factor-β1 (TGF-β1) were well sorbed with time to the acidic gelatin hydrogel, while less sorption was observed for the basic gelatin hydrogel. This could be explained in terms of the electrostatic interaction between the growth factors and the acidic gelatin. However, bone morphogenetic protein-2 (BMP-2) and vascular endothelial growth factor (VEGF), though their IEPs are higher than 7.0, were sorbed to the acidic gelatin hydrogel to a smaller extent than the two other growth factors. Under in vitro non-degradation conditions, approximately 20% of the incorporated bFGF and TGF-β1 was desorbed from the hydrogels within the initial 40 min, followed by no further substantial desorption, whereas large initial desorption was observed for BMP-2 and VEGF. When implanted in the back subcutis of mice, gelatin hydrogels were degraded over time. Each growth factor was retained in vivo being incorporated in the acidic gelatin hydrogel: the smaller the in vitro desorption amount from the hydrogel, the longer the in vivo retention time. The in vivo profile of bFGF and TGF-β1 retention was in good accordance with that of the hydrogel. These findings indicate that the growth factor immobilized to the acidic gelatin hydrogel through ionic interaction was released in vivo as a result of hydrogel degradation.
Power management verification experiences in Wireless SoCs

We look into the validation a power managed ARM Cortex A-8 core used in SoCs targeted for mobile segment. Low Power design techniques used on the chip include clock gating, voltage scaling, and power gating. We focus on the verification challenges faced in designing the processor core including RTL modeling of power switches, isolation, and level-shifting cells, simulation of voltage ramps, generation of appropriate control signals to put the device into various power states, and ensuring correct operation of chip in these states as well as during the transitions between these states.
Trade‐off between frequency and precision during stepping movements: Kinematic and BOLD brain activation patterns

The central nervous system has the ability to adapt our locomotor pattern to produce a wide range of gait modalities and velocities. In reacting to external pacing stimuli, deviations from an individual preferred cadence provoke a concurrent decrease in accuracy that suggests the existence of a trade‐off between frequency and precision; a compromise that could result from the specialization within the control centers of locomotion to ensure a stable transition and optimal adaptation to changing environment. Here, we explore the neural correlates of such adaptive mechanisms by visually guiding a group of healthy subjects to follow three comfortable stepping frequencies while simultaneously recording their BOLD responses and lower limb kinematics with the use of a custom‐built treadmill device. In following the visual stimuli, subjects adopt a common pattern of symmetric and anti‐phase movements across pace conditions. However, when increasing the stimulus frequency, an improvement in motor performance (precision and stability) was found, which suggests a change in the control mode from reactive to predictive schemes. Brain activity patterns showed similar BOLD responses across pace conditions though significant differences were observed in parietal and cerebellar regions. Neural correlates of stepping precision were found in the insula, cerebellum, dorsolateral pons and inferior olivary nucleus, whereas neural correlates of stepping stability were found in a distributed network, suggesting a transition in the control strategy across the stimulated range of frequencies: from unstable/reactive at lower paces (i.e., stepping stability managed by subcortical regions) to stable/predictive at higher paces (i.e., stability managed by cortical regions). Hum Brain Mapp 37:1722–1737, 2016. © 2016 Wiley Periodicals, Inc.
Improving urban road extraction in high-resolution images exploiting directional filtering, perceptual grouping, and simple topological concepts

In this letter, the problem of detecting urban road networks from high-resolution optical/synthetic aperture radar (SAR) images is addressed. To this end, this letter exploits a priori knowledge about road direction distribution in urban areas. In particular, this letter presents an adaptive filtering procedure able to capture the predominant directions of these roads and enhance the extraction results. After road element extraction, to both discard redundant segments and avoid gaps, a special perceptual grouping algorithm is devised, exploiting colinearity as well as proximity concepts. Finally, the road network topology is considered, checking for road intersections and regularizing the overall patterns using these focal points. The proposed procedure was tested on a pair of very high resolution images, one from an optical sensor and one from a SAR sensor. The experiments show an increase in both the completeness and the quality indexes for the extracted road network
Multi-view hard c-means with automated weighting of views and variables

Multi-View Clustering models can be viewed as a way to extract information from different data representations to improve the clustering accuracy. In multi-view clustering, some views are irrelevant and among the relevant ones, some may be more or less relevant than others. This is why the most part of existing algorithms assign a weight to each view aiming to compute its relevance in the clustering process. However very few algorithms computes also the relevance weight of variables inside each view aiming to achieve automated feature selection. This paper proposes a muti-view hard c-means clustering algorithm with automated computation of weights for both views and variables in such a way that the relevant views as well as the relevant variables in each view are selected for clustering. Compared to previous similar works, an advantage of the proposed method is that, apart the need to know previously the number of clusters, there are no additional parameters to tune. Experiments with benchmark data sets corroborate the usefulness of the proposed method.
Genetic Characterization of a Vancomycin-Resistant Staphylococcus aureus Isolate from the Respiratory Tract of a Patient in a University Hospital in Northeastern Iran

ABSTRACT Emergence of vancomycin-intermediate Staphylococcus aureus (VISA) and vancomycin-resistant S. aureus (VRSA) strains has led to global concerns about treatments for staphylococcal infections. These strains are currently rare even though there is an upward trend in their reported incidence. Therefore, appropriate screening and epidemiological evaluation of VRSA strains can affect future global health care policies. Isolates of Staphylococcus aureus were obtained from various clinical samples and were then evaluated with agar screening, disk diffusion, and MIC methods to determine resistance to vancomycin and methicillin. After confirmation of the isolated VRSA strain, genetic analysis was performed by evaluating mecA and vanA gene presence, SCCmec, agr, and spa types, and toxin profiles. Multilocus sequence typing (MLST) and plasmid analysis were also performed. The VRSA strain was resistant to oxacillin (MIC of 128 μg/ml) and vancomycin (MIC of 512 μg/ml). Disk diffusion antimicrobial susceptibility tests showed resistance to oxacillin, vancomycin, levofloxacin, ciprofloxacin, trimethoprim-sulfamethoxazole, clindamycin, rifampin, and tetracycline. The isolate was susceptible to minocycline and gentamicin. PCRs were positive for the mecA and vanA genes. Other genetic characteristics include SCCmec type III, agr I, spa type t037, and sequence type (ST) 1283. The plasmid profile shows five plasmids with a size of ∼1.7 kb to >10 kb. The isolated VRSA strain was obtained from a critically ill hospitalized patient. Genetic analysis of this strain suggested that the strain was a methicillin-resistant S. aureus (MRSA) clone endemic in Asia that underwent some genetic changes, such as mutation in the gmk gene and acquisition of the vanA gene.
Interleukin (IL)‐1 in rat parturition: IL‐1 receptors 1 and 2 and accessory proteins abundance in pregnant rat uterus at term – regulation by progesterone

The role of interleukin‐1 (IL‐1), a pro‐inflammatory cytokine, in parturition is typically noted by changes in its concentrations. Studying the expression of its receptor family, IL‐1 receptor (IL‐1R) 1, IL‐1R2, IL‐1R accessory protein (IL‐1RAcP), and its predominantly brain isoform, IL‐1RAcPb, during late gestation in the uterus in the Long‐Evans rat is another. We assessed changes in their mRNA and protein relative abundance in the uterus and compared IL‐1RAcP and IL‐1RAcPb mRNA abundance in uterus, cervix, ovaries, placenta, and whole blood of Long‐Evans rats during late gestation or in RU486 and progesterone‐treated dams using quantitative real‐time PCR and western immunoblotting. IL‐1R1, IL‐1RAcP, and IL‐1RAcPb mRNA abundance significantly increased in the uterus at delivery whereas IL‐1R2 mRNA abundance significantly decreased. IL‐1R1 protein increased at term and IL‐1R2 protein decreased at term compared to nonpregnant uteri. IL1‐RAcPb mRNA abundance was less than IL‐1RAcP, but in the lower uterine segment it was the highest of all tissues examined. RU486 stimulated preterm delivery and an increase in IL‐1R1 mRNA abundance whereas progesterone administration extended pregnancy and suppressed the increase in IL‐1R1. These data suggest that changes in uterine sensitivity to IL‐1 occur during late gestation and suggest another level of regulation for the control of delivery. The roles for IL‐1RAcP and IL‐1RAcPb need to be determined, but may relate to different intracellular signaling pathways.