Miracle-dz/UniFAR-FTUs huggingface dataset:
Endotoxin-Induced Mortality Is Related to Increased Oxidative Stress and End-Organ Dysfunction, Not Refractory Hypotension, in Heme Oxygenase-1–Deficient Mice

BackgroundHeme oxygenase (HO)-1 is an enzyme that degrades heme to generate CO (a vasodilatory gas), iron, and the potent antioxidant bilirubin. A disease process characterized by decreases in vascular tone and increases in oxidative stress is endotoxic shock. Moreover, HO-1 is markedly induced in multiple organs after the administration of endotoxin (lipopolysaccharide [LPS]) to mice. Methods and ResultsTo determine the role of HO-1 in endotoxemia, we administered LPS to mice that were wild-type (+/+), heterozygous (±), or homozygous null (−/−) for targeted disruption of HO-1. LPS produced a similar induction of HO-1 mRNA and protein in HO-1+/+ and HO-1+/− mice, whereas HO-1−/− mice showed no HO-1 expression. Four hours after LPS, systolic blood pressure (SBP) decreased in all the groups. However, SBP was significantly higher in HO-1−/− mice (121±5 mm Hg) after 24 hours, compared with HO-1+/+ (96±7 mm Hg) and HO-1+/− (89±13 mm Hg) mice. A sustained increase in endothelin-1 contributed to this SBP response. Even though SBP was higher, mortality was increased in HO-1−/− mice, and they exhibited hepatic and renal dysfunction that was not present in HO-1+/+ and HO-1+/− mice. The end-organ damage and death in HO-1−/− mice was related to increased oxidative stress. ConclusionsThese data suggest that the increased mortality during endotoxemia in HO-1−/− mice is related to increased oxidative stress and end-organ (renal and hepatic) damage, not to refractory hypotension.
Visualization of Object‐Centered Vulnerability to Possible Flood Hazards

As flood events tend to happen more frequently, there is a growing demand for understanding the vulnerability of infrastructure to flood‐related hazards. Such demand exists both for flood management personnel and the general public. Modern software tools are capable of generating uncertainty‐aware flood predictions. However, the information addressing individual objects is incomplete, scattered, and hard to extract. In this paper, we address vulnerability to flood‐related hazards focusing on a specific building. Our approach is based on the automatic extraction of relevant information from a large collection of pre‐simulated flooding events, called a scenario pool. From this pool, we generate uncertainty‐aware visualizations conveying the vulnerability of the building of interest to different kinds of flooding events. On the one hand, we display the adverse effects of the disaster on a detailed level, ranging from damage inflicted on the building facades or cellars to the accessibility of the important infrastructure in the vicinity. On the other hand, we provide visual indications of the events to which the building of interest is vulnerable in particular. Our visual encodings are displayed in the context of urban 3D renderings to establish an intuitive relation between geospatial and abstract information. We combine all the visualizations in a lightweight interface that enables the user to study the impacts and vulnerabilities of interest and explore the scenarios of choice. We evaluate our solution with experts involved in flood management and public communication.
2 Sequential Parameter Optimization 2 . 1 SPOT in a Nutshell

Sequential parameter optimization (SPO) is a heuristic that combines classical and modern statistical techniques to improve the performance of search algorithms. It includes a broad variety of meta models, e.g., linear models, random forest, and Gaussian process models (Kriging). The selection of an adequate meta model can have significant impact on SPO’s performance. A comparison of different meta models is of great importance. A recent study indicated that random forest based meta models might be a good choice. This rather surprising result will be analyzed in this paper. Moreover, Optimal Computing Budget Allocation (OCBA), which is an enhanced method for handling the computational budget spent for selecting new design points, is presented. The OCBA approach can intelligently determine the most efficient replication numbers. We propose the integration of OCBA into SPO. In this study, SPO is directly used as an optimization method on different noisy mathematical test functions. This is differs from the standard way of using SPO for tuning algorithm parameters in the context of complex real-world applications. Using SPO this way allows for a comparison to other optimization algorithms. Our results reveal that the incorporation of OCBA and the selection of Gaussian process models are highly beneficial. Moreover, SPO outperformed three different alternative optimization algorithms on a set of five noisy mathematical test functions.
Double the trouble: handling noise and reverberation in far-field automatic speech recognition

Far-field microphone speech signals cause high error rates for automatic speech recognition systems, due to room reverberation and lower signal-to-noise ratios. We have observed large increases in speech recognition word error rates when using a far-field (3-6 feet) microphone in a conference room, in comparison with recordings from close-talking microphones. In an earlier paper, we showed improvements in far-field speech recognition performance using a longterm log spectral subtraction method to combat reverberation. This method is based on a principle similar to cepstral mean subtraction but uses a much longer analysis window (e.g., 1 s) in order to deal with reverberation. Here we show that a combination of short-term noise filtering and longterm log spectral subtraction can further reduce recognition word error rates.
Discoursing Mathematically: Using Discourse Analysis to Develop a Sociocritical Perspective of Mathematics Education

This article explores how the concepts of discourse and its methodological extension discourse analysis can help mathematics educators re-conceptualize their practices using a sociocultural view of learning. It provides conceptual and methodological tools as well as activities that can be helpful in mathematics methods courses and professional development sessions aimed at developing a more situated and social view of mathematical discourse and its relationship to student learning, particularly how mathematical discourse relates to Language Minority Students (LMS). In this article, I discuss the main features of discourse as a framework for mathematics educators and how participants in a cross-site research center collectively engaged and developed a more robust understanding of the significance of discourse and discourse analysis for understanding mathematics as a sociocultural practice. This article describes learning activities whose instructional goal is to develop a sociocritical understanding of language and mathematics. The activities presented here can be adopted as a model for engaging mathematics teacher educators and mathematics teachers to deepen their understanding of the inextricable link between language and mathematics, and of mathematics as a cultural and political activity.
Variations phonologiques en production et perception de la parole : le phénomène de l'assimilation

The present PhD thesis provides an in-depth study of a phonological variation frequently encountered in French, namely voice assimilation. The goal of the first series of experiments was to study the production of assimilated words and to provide an acoustico-phonetic description of word-final assimilated obstruents. Acoustic measurements showed that voice assimilation is often a graded, rather than a categorical phonetic process. Moreover, degrees of assimilation varied as a function of underlying voicing. Cross-modal priming results showed that the role of phonological right context varies as a function of the degree of assimilation. Perceptual processing of completely assimilated segments was facilitated in the presence of the right context, whereas the presence of "acoustic traces" sufficed to access partially assimilated segments. The hypothesis of the presence of acoustic traces in assimilated words was confirmed in the third series of experiments using semantic priming.
Motion parallax in stereo 3D

Binocular disparity is the main depth cue that makes stereoscopic images appear 3D. However, in many scenarios, the range of depth that can be reproduced by this cue is greatly limited and typically fixed due to constraints imposed by displays. For example, due to the low angular resolution of current automultiscopic screens, they can only reproduce a shallow depth range. In this work, we study the motion parallax cue, which is a relatively strong depth cue, and can be freely reproduced even on a 2D screen without any limits. We exploit the fact that in many practical scenarios, motion parallax provides sufficiently strong depth information that the presence of binocular depth cues can be reduced through aggressive disparity compression. To assess the strength of the effect we conduct psycho-visual experiments that measure the influence of motion parallax on depth perception and relate it to the depth resulting from binocular disparity. Based on the measurements, we propose a joint disparity-parallax computational model that predicts apparent depth resulting from both cues. We demonstrate how this model can be applied in the context of stereo and multiscopic image processing, and propose new disparity manipulation techniques, which first quantify depth obtained from motion parallax, and then adjust binocular disparity information accordingly. This allows us to manipulate the disparity signal according to the strength of motion parallax to improve the overall depth reproduction. This technique is validated in additional experiments.
Synthesis of loop-free programs

We consider the problem of synthesizing loop-free programs that implement a desired functionality using components from a given library. Specifications of the desired functionality and the library components are provided as logical relations between their respective input and output variables. The library components can be used at most once, and hence the library is required to contain a reasonable overapproximation of the multiset of the components required. We solve the above component-based synthesis problem using a constraint-based approach that involves first generating a synthesis constraint, and then solving the constraint. The synthesis constraint is a first-order ∃∀ logic formula whose size is quadratic in the number of components. We present a novel algorithm for solving such constraints. Our algorithm is based on counterexample guided iterative synthesis paradigm and uses off-the-shelf SMT solvers. We present experimental results that show that our tool Brahma can efficiently synthesize highly nontrivial 10-20 line loop-free bitvector programs. These programs represent a state space of approximately 2010 programs, and are beyond the reach of the other tools based on sketching and superoptimization.
Predicting Impacts of Climate Change on Fasciola hepatica Risk

Fasciola hepatica (liver fluke) is a physically and economically devastating parasitic trematode whose rise in recent years has been attributed to climate change. Climate has an impact on the free-living stages of the parasite and its intermediate host Lymnaea truncatula, with the interactions between rainfall and temperature having the greatest influence on transmission efficacy. There have been a number of short term climate driven forecasts developed to predict the following season's infection risk, with the Ollerenshaw index being the most widely used. Through the synthesis of a modified Ollerenshaw index with the UKCP09 fine scale climate projection data we have developed long term seasonal risk forecasts up to 2070 at a 25 km square resolution. Additionally UKCIP gridded datasets at 5 km square resolution from 1970-2006 were used to highlight the climate-driven increase to date. The maps show unprecedented levels of future fasciolosis risk in parts of the UK, with risk of serious epidemics in Wales by 2050. The seasonal risk maps demonstrate the possible change in the timing of disease outbreaks due to increased risk from overwintering larvae. Despite an overall long term increase in all regions of the UK, spatio-temporal variation in risk levels is expected. Infection risk will reduce in some areas and fluctuate greatly in others with a predicted decrease in summer infection for parts of the UK due to restricted water availability. This forecast is the first approximation of the potential impacts of climate change on fasciolosis risk in the UK. It can be used as a basis for indicating where active disease surveillance should be targeted and where the development of improved mitigation or adaptation measures is likely to bring the greatest benefits.
BvgAS is sufficient for activation of the Bordetella pertussis ptx locus in Escherichia coli

BvgA and BvgS, which regulate virulence gene expression in Bordetella pertussis, are members of the two-component signal transduction family. The effects of growth conditions on the ability of BvgAS to activate transcription of fhaB (encoding filamentous hemagglutinin) and ptxA (encoding the S1 subunit of pertussis toxin) were assessed in Escherichia coli by using chromosomal fhaB-lacZYA and ptxA-lacZYA fusions. Although it had previously been reported that a ptxA-lacZYA transcriptional fusion was not activated by bvgAS in E. coli (J. F. Miller, C. R. Roy, and S. Falkow, J. Bacteriol. 171:6345-6348, 1989), we now present evidence that ptxA is activated by bvgAS in E. coli in a manner that is highly dependent on the growth conditions. Higher levels of beta-galactosidase were produced by ptxA-lacZYA in the presence of bvgAS during growth in Stainer-Scholte medium or M9 minimal salts medium with glucose than in Luria-Bertani medium. In contrast, the level of fhaB-lacZYA expression was high during growth in all media. Addition of modulating stimuli which inhibit BvgAS function eliminated expression of ptxA-lacZYA. Levels of beta-galactosidase expressed from the ptx-lacZYA fusion correlated with growth rate and with the final optical density at 600 nm, suggesting that the lower growth rate in M9-glucose and Stainer-Scholte media was responsible for greater accumulation of beta-galactosidase than was seen in Luria-Bertani medium. Overproduction of BvgA was not sufficient for activation of ptxA expression but was sufficient for fhaB expression. However, overproduction of a constitutive BvgA allele (bvgA-Cl) or overproduction of BvgA in the presence of BvgS was able to activate ptxA. Our results demonstrate Bvg-dependent activation of a ptxA-lacZYA fusion in E. coli and indicate that bvg is the only Bordetella locus required for ptxA activation in this heterologous system.
Improving the Testability of Object-oriented Software during Testing and Debugging Processes

Testability is the probability whether tests will detect a fault, given that a fault in the program exists. How efficiently the faults will be uncovered depends upon the testability of the software. Various researchers have proposed qualitative and quantitative techniques to improve and measure the testability of software. In literature, a plethora of reliability growth models have been used to assess and measure the quantitative quality assessment of software during testing and operational phase. The knowledge about failure distribution and their complexity can improve the testability of software. Testing effort allocation can be made easy by knowing the failure distribution and complexity of faults, and this will ease the process of revealing faults from the software. As a result, the testability of the software will be improved. The parameters of the model along with the proportion of faults of different complexity to be removed from the software have been presented in the paper . We have used failure data of two object oriented software developed under open source environment namely MySQL for python and Squirrel SQL Client for estimation purpose
Software clustering based on information loss minimization

The majority of the algorithms in the software clusteringliterature utilize structural information in order to decomposelarge software systems. Other approaches, such as usingfile names or ownership information, have also demonstratedmerit. However, there is no intuitive way to combine informationobtained from these two different types of techniques.In this paper, we present an approach that combines structuraland non-structural information in an integrated fashion.LIMBO is a scalable hierarchical clustering algorithm basedon the minimization of information loss when clustering asoftware system.We apply LIMBO to two large software systems in a numberof experiments. The results indicate that this approachproduces valid and useful clusterings of large software systems.LIMBO can also be used to evaluate the usefulnessof various types of non-structural information to the softwareclustering process.
Measuring and Predicting Pupils’ Progress in Special Education

In regular primary education, LVS tests are used to measure and predict pupils’ progress in math ability (θ). In special education, due to measurement error and a distribution of scores that is different from regular education, both measuring and predicting progress is difficult. A solution to the problem in measurement is investigated in the field of computerized adaptive testing (CAT). Using a simulation study, two CAT item selection mechanisms have been tested, for three different ability levels. Results suggest that using CAT mechanisms, accurately estimating a pupil’s ability is possible, as long as the items are suitable for the ability levels. Overall, allthough the selection mechanisms are different, both mechanisms show equal performance in accuracy of measurment. For the problem of predicting progress, a distribution for special education is calculated and tested. The results suggest that, due to regression to the mean, the special education distribution does not predict accurately for pupils with θ values far from the population mean. Using Growth Mixture Modeling (GMM) multiple distributions have been defined to solve this problem. Using multiple distributions for pupils with different ability levels, the problem of regression to the mean is less severe.
ALLONE: A new adaptive failure detector model for Low-power Lossy Networks

We consider the problem of failure detection in networks with energy and communication constraints. Most of current implementations of unreliable failure detectors (FD) use mechanisms to notify process failures in fully connected networks with reliable communication links. This assumption is not applicable to lossy networks. Furthermore, such implementations do not consider resource limitations in terms of energy, storage and bandwidth. This paper presents a new failure detection model for Low-power Lossy Networks (LLN). Our approach defines an adaptive timer-based paradigm. Besides, we introduce two techniques based on the proposed general model. We evaluate all contributions using implementation on Omnet++/Mixim framework. Simulation results demonstrate that our FD enhances detection performances for LLN compared to traditional FD.
Doxycycline Induces Expression of P Glycoprotein in MCF-7 Breast Carcinoma Cells

ABSTRACT P-glycoprotein (P-gp) overexpression by tumor cells imparts resistance to multiple antineoplastic chemotherapeutic agents (multiple drug resistance). Treatment of tumor cells with chemotherapeutic agents such as anthracyclines, epipodophyllotoxins, and Vinca alkaloids results in induction of P-gp expression. This study was performed to determine if clinically relevant antimicrobial drugs (i.e., drugs that are used to treat bacterial infections in cancer patients) other than antineoplastic agents can induce expression of P-gp in MCF-7 breast carcinoma cells. Expression of P-gp and MDR1 mRNA was determined in samples from MCF-7 cells that were treated in culture with doxorubicin (positive control) and the antimicrobial drugs doxycycline, piperacillin, and cefoperazone. The functional status of P-gp was assessed using laser cytometry to determine intracellular doxorubicin concentrations. The MTT (3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyltetrazolium bromide) assay was used to determine if the cytotoxicity of experimental drugs was related to their ability to induce P-gp expression. MCF-7 cells treated with doxycycline (MCF-7/doxy) were stimulated to overexpress P-gp, whereas cells treated with piperacillin and cefoperazone did not overexpress P-gp. MCF-7/doxy cells were compared to a positive-control subline, MCF-7/Adr, previously selected for doxorubicin resistance, and to MCF-7 cells treated with doxorubicin (MCF-7/doxo). All three sublines overexpressed P-gp and MDR1 mRNA and accumulated less intracellular doxorubicin than did control MCF-7 cells. P-gp expression was induced only by experimental drugs that were cytotoxic (doxorubicin and doxycycline). Doxycycline, a drug that has been used for treatment of bacterial infections in cancer patients, can induce functional P-gp expression in cancer cells, resulting in multidrug resistance.
Long-Term Effects of Maternal Citrulline Supplementation on Renal Transcriptome Prevention of Nitric Oxide Depletion-Related Programmed Hypertension: The Impact of Gene-Nutrient Interactions

Maternal malnutrition can elicit gene expression leading to fetal programming. l-citrulline (CIT) can be converted to l-arginine to generate nitric oxide (NO). We examined whether maternal CIT supplementation can prevent NG-nitro-l-arginine-methyl ester (l-NAME, NO synthase inhibitor)-induced programmed hypertension and examined their effects on the renal transcriptome in male offspring using next generation RNA sequencing (RNA-Seq) technology. Pregnant Sprague-Dawley rats received l-NAME administration at 60mg/kg/day subcutaneously via osmotic minipump during pregnancy alone or with additional 0.25% l-citrulline solution in drinking water during the whole period of pregnancy and lactation. Male offspring were assigned to three groups: control, l-NAME, and l-NAME + CIT. l-NAME exposure induced hypertension in the 12-week-old offspring, which CIT therapy prevented. Identified differentially expressed genes in l-NAME and CIT-treated offspring kidneys, including Guca2b, Hmox1, Hba2, Hba-a2, Dusp1, and Serpine1 are related to regulation of blood pressure (BP) and oxidative stress. In conclusion, our data suggests that the beneficial effects of CIT supplementation are attributed to alterations in expression levels of genes related to BP control and oxidative stress. Our results suggest that early nutritional intervention by CIT has long-term impact on the renal transcriptome to prevent NO depletion-related programmed hypertension. However, our RNA-Seq results might be a secondary phenomenon. The implications of epigenetic regulation at an early stage of programming deserve further clarification.