Miracle-dz/UniFAR-FTUs huggingface dataset:
Cardiac peroxisome proliferator-activated receptor-alpha activation causes increased fatty acid oxidation, reducing efficiency and post-ischaemic functional loss.

AIMS Myocardial fatty acid (FA) oxidation is regulated acutely by the FA supply and chronically at the transcriptional level owing to FA activation of peroxisome proliferator-activated receptor-alpha (PPARalpha). However, in vivo administration of PPARalpha ligands has not been shown to increase cardiac FA oxidation. In this study we have examined the cardiac response to in vivo administration of tetradecylthioacetic acid (TTA, 0.5% w/w added to the diet for 8 days), a PPAR agonist with primarily PPARalpha activity. METHODS AND RESULTS Despite the fact that TTA treatment decreased plasma concentrations of lipids [FA and triacylglycerols (TG)], hearts from TTA-treated mice showed increased mRNA expression of PPARalpha target genes. Cardiac substrate utilization, ventricular function, cardiac efficiency, and susceptibility to ischaemia-reperfusion were examined in isolated perfused hearts. In accordance with the mRNA changes, myocardial FA oxidation was increased 2.5-fold with a concomitant reduction in glucose oxidation. This increase in FA oxidation was abolished in PPARalpha-null mice. Thus, it appears that the metabolic effects of TTA on the heart must be owing to a direct stimulatory effect on cardiac PPARalpha. Hearts from TTA-treated mice also showed a marked reduction in cardiac efficiency (because of a two-fold increase in unloaded myocardial oxygen consumption) and decreased recovery of ventricular contractile function following low-flow ischaemia. CONCLUSION This study for the first time observed that in vivo administration of a synthetic PPARalpha ligand elevated FA oxidation, an effect that was also associated with decreased cardiac efficiency and reduced post-ischaemic functional recovery.
Chapter 2 Origin of Prokaryotes and Eukaryotes

The fundamental desire to understand the origin of life is demonstrated by the fact that essentially all human cultures contain a story of how life began. From the tribes of ancient times to the mythologies of more modern cultures, there are countless stories of the origin of life. Some are based in pagan beliefs, while others are based on creation resulting from a holy deity. This collection of myths, legends, and tribal knowledge handed down over generations is the collective expression of how man has attempted to explain his world and his place in it. What is common to all these cultures is that their specific story of how life began is accepted without question. The role of the adults is simply to teach the story to the children. The distinguishing feature of the scientific approach to understanding the origin of life is that it begins by acknowledging the fact that we do not know how life began. Only by admitting that we do not have the answer, is it possible to put forth and test multiple hypotheses. The origin of life is one of the most challenging problems in biology. The best evidence is that prokaryotic life (microorganisms lacking a membrane-bound nucleus) first appeared on Earth about 3.8 billion years ago (Zimmer 2009). The abiogenesis theory of the origin of life begins with the experimentally supported concept that simple organic compounds, such as amino acids, organic acids, purines, pyrimidines, and simple sugars, could have been produced spontaneously in the earth’s primitive reducing atmosphere (Oró and Kamat 1961), containing CH4, H2, H2O, N2, and NH3 (Schaefer and Fegley 2010). Further, these molecules could have been concentrated into a ‘‘prebiotic organic soup’’ in evaporation ponds. Whatever the earliest events on the road to the first living cell were, it is clear that at some point the large biological molecules found in modern cells must have emerged. Considerable debate in origin-of-life studies has revolved also around which of the fundamental macromolecules came first—proteins, DNA, or RNA. To gain insight into this question it is useful to consider the functions performed by each of these polymers in existing organisms.
Filtering of functional near infrared spectroscopy signals by eigenvalue based methods

Functional Near Infrared Spectroscopy is used in neuroimaging studies to observe the oxyhemoglobin (HBO2) and deoxyhemoglobin (HB) changes. Blood oxygen level dependency (BOLD) signal that is collected by using this system shows response in related region in brain against an applied stimulus. Therefore in these signals, signal to noise ratio (SNR) is quite important to decide the behavior of brain in related region In this study, fNIRS data was filtered by using eigenvalue based methods such as Principal Component Analysis (PCA) and Truncated Singular Value Decomposition (tSVD). Using SNR and Autoregressive (AR) power spectrum performance results were compared.
Dynamical solution of the on-line minority game

We solve the dynamics of the on-line minority game, with general types of decision noise, using generating functional techniques a la De Dominicis and the temporal regularization procedure of Bedeaux et al. The result is a macroscopic dynamical theory in the form of closed equations for correlation- and response functions defined via an effective continuous-time single-trader process, which are exact in both the ergodic and in the non-ergodic regime of the minority game. Our solution also explains why, although one cannot formally truncate the Kramers-Moyal expansion of the process after the Fokker-Planck term, upon doing so one still finds the correct solution, that the previously proposed diffusion matrices for the Fokker-Planck term are incomplete, and how previously proposed approximations of the market volatility can be traced back to ergodicity assumptions.
Two Essays in Empirical Asset Pricing

This thesis includes two research papers in the area of empirical asset pricing. In the first research paper titled “Option implied moments and risk aversion”, under reasonable assumptions, I provide empirical evidence that index options implied higher moments can predict the index returns and Sharpe ratio. Specifically, I present a method to recover option implied subjective moments of the S&P500 index under the assumption of no arbitrage and logarithmic utility. This result adds further evidence to the extensive finance literature that claims that market returns are predictable. In the second research paper titled “Expected returns: systematic risk or firm characteristics” I provide empirical evidence that expected returns can be viewed as determined by the exposure of firm returns to systematic factors that are based on firm characteristics, and not directly to the cross–sectional differences in the firm characteristics. This result addresses an ongoing debate within the empirical asset pricing literature as to whether the cross–section of expected returns is “explained” by the loadings to systematic factors or by differences in firm characteristics. The evidence I provide supports the loading to systematic factors story, consistent with the consumption asset pricing model.
Closed-Form Expressions for Irradiance from Non-Uniform Lambertian Luminaires Part II : Polynomially-Varying Brightness ∗

We present new analytical techniques for computing illumination from non-uniform luminaires. The methods are based on new closed-form expressions derived by generalizing the concepts of irradiance tensor and angular moment to rational forms and an arbitrary number of directions, known as rational irradiance tensors and rational angular moments, respectively. The techniques apply to any emission, reflection or transmission distribution expressed as a polynomial over a polygonal surface, and provide a powerful mathematical tool to handle more complex BRDF’s. We derive closed-form expressions for irradiance due to polygonal luminaires with polynomially varying brightness, which satisfy a recurrence relation that subsumes Lambert’s formula for uniform luminaires. Our formulas extend the class of available closed-form expressions for computing direct radiative transfer from planar surfaces to points, and can find many potential applications in simulating non-Lambertian illumination and scattering phenomena.
Multiplexing/Beamforming Switching for Coded MIMO in Spatially Correlated Channels Based on Closed-Form BER Approximations

This paper considers low-complexity coded multiple-input-multiple-output transmission in Rayleigh channels with correlation between antennas at both the transmitter and receiver. We consider statistical beamforming (SB) and spatial multiplexing (SM) with a zero-forcing receiver. We calculate the link-level capacity of both schemes with bit-interleaved coded modulation and derive accurate closed-form approximations to the bit error rate. We then show how the resulting expressions can be used in an adaptive algorithm to select the best combination of code rate, modulation format, and transmission scheme (SB or SM) in order to maximize throughput. Unlike other mode-switching schemes that require empirical lookup tables, this approach applies to any correlation scenario. Numerical studies are used to demonstrate the performance as a function of signal-to-noise ratio and correlation parameters.
ACCOUNTABILITY AND FINANCIAL CONTROL AS ‘PATRIOTIC’ STRATEGIES: ACCOMPTANTS AND THE PUBLIC ACCOUNTS COMMITTEE IN LATE 17TH AND EARLY 18TH - CENTURY IRELAND

The decades immediately following the Glorious Revolution in 1688 witnessed a variety of political, social and structural responses to this cataclysmic event. In Ireland, religious conflict and economic under-development, as well as the devastation of war from 1689 to 1691, combined to ensure that the Anglo-Irish body politic found it difficult to capture the fruits of success from an English polity that had gradually accreted to itself much of the political power and economic wealth of the country. By 1704, however, the Anglo-Irish had managed to appropriate to themselves some of the economic and constitutional benefits of the Revolution by exploiting various parliamentary practices and structures. One of their strategies centered around developing and leveraging the role of the Public Accounts Committee as a means of imposing accountability on the executive and its officials. To achieve this the members were required to understand, contest and reconfigure official accounting information.
An Investigation into the Mathematical Nature of Electrophysiological Signals with Applications

In this work we have proposed a rigorous mathematical definition for the one dimensional time domain electrophysiological signals and established its relationship with two of the three Dirichlet's conditions. We have argues that any such signal can be represented as the trajectory of a particle moving in a force field with one degree of freedom. At point on the trajectory, that is, on the signal, the kinetic energy dissipated by the particle embeds semantic information into the trajectory or the signal in terms of giving its shape. We have shown that the rate of kinetic energy dissipation operator or the power operator P is of importance in shape analysis of the signal by considering its sign changes. Operating the P-operator on digital signals we have mathematically proved that its sign change can induce 13 different shapes to a three successive point configuration. In other words, semantic information at each point in a digital signal can be embedded by a syllable of 13 different letters. We have shown some preliminary applications.
Michael Poole, The Origins of Economic Democracy: Profit Sharing and Employee-Shareholding Schemes and Michael Poole and Glenville Jenkins, The Impact of Economic Democracy: Profit Sharing and Employee Shareholding Schemes

Note : les règles d'écriture des références bibliographiques peuvent varier selon les différents domaines du savoir. Ce document est protégé par la loi sur le droit d'auteur. L'utilisation des services d'Érudit (y compris la reproduction) est assujettie à sa politique d'utilisation que vous pouvez consulter à l'URI
Global Prevalence of Chronic Kidney Disease – A Systematic Review and Meta-Analysis

Chronic kidney disease (CKD) is a global health burden with a high economic cost to health systems and is an independent risk factor for cardiovascular disease (CVD). All stages of CKD are associated with increased risks of cardiovascular morbidity, premature mortality, and/or decreased quality of life. CKD is usually asymptomatic until later stages and accurate prevalence data are lacking. Thus we sought to determine the prevalence of CKD globally, by stage, geographical location, gender and age. A systematic review and meta-analysis of observational studies estimating CKD prevalence in general populations was conducted through literature searches in 8 databases. We assessed pooled data using a random effects model. Of 5,842 potential articles, 100 studies of diverse quality were included, comprising 6,908,440 patients. Global mean(95%CI) CKD prevalence of 5 stages 13·4%(11·7–15·1%), and stages 3–5 was 10·6%(9·2–12·2%). Weighting by study quality did not affect prevalence estimates. CKD prevalence by stage was Stage-1 (eGFR>90+ACR>30): 3·5% (2·8–4·2%); Stage-2 (eGFR 60–89+ACR>30): 3·9% (2·7–5·3%); Stage-3 (eGFR 30–59): 7·6% (6·4–8·9%); Stage-4 = (eGFR 29–15): 0·4% (0·3–0·5%); and Stage-5 (eGFR<15): 0·1% (0·1–0·1%). CKD has a high global prevalence with a consistent estimated global CKD prevalence of between 11 to 13% with the majority stage 3. Future research should evaluate intervention strategies deliverable at scale to delay the progression of CKD and improve CVD outcomes.
Dimension reduction based on categorical fuzzy correlation degree for document categorization

High dimensionality of the feature space is a common problem in document categorization. Most of the features obtained through conventional feature selection algorithms such as IG are relevant and redundant. In this paper, a two-step feature selection method is proposed. At the first step redundancy analysis among original features based on categorical fuzzy correlation degree is applied to filter the redundant features with the similar categorical term frequency distribution. In the second step, conventional IG feature selection algorithm is adopted to select the final feature set for document categorization. Experiments dealing with the well-known Reuters-21578 and 20news-18828 corpuses show that the proposed method can eliminate redundant features with high fuzzy correlation degree between each other and obtain a compressed feature space where the dimension of feature space is dramatically reduced. The document categorization results on two corpuses show that the conventional IG feature selection algorithm can achieve a better document categorization performance on the compressed feature space and demonstrate the effectiveness of the proposed method.
Draft Genome Sequence of the Polychlorinated Biphenyl-Degrading Bacterium Cupriavidus basilensis KF708 (NBRC 110671) Isolated from Biphenyl-Contaminated Soil

ABSTRACT We report the draft genome sequence of Cupriavidus basilensis KF708 (NBRC 110671), which utilizes biphenyl as a sole carbon source and degrades polychlorinated biphenyls (PCBs). The KF708 strain possesses genes for biphenyl catabolism and other genes involved in various aromatic compounds.
Biased Yes/No Questions : The Role of VERUM

Some information-seeking yes/no (yn)-questions convey an epistemic bias of the speaker. Examples are questions with the particle really (e.g., Did he really bring a present? ), negative questions with preposed negation (e.g., Doesn't John drink? ), and in some contexts even regular questions (e.g., Is it raining? ). The goal of this paper is to compare two main approaches to biased yn-questions - the VERUM approach and the Decision Theory approach - and to argue that, while certain formal notions from Decision Theory are important, the operator VERUM is needed to derive the full range of data. Furthermore, the paper explores the behavior of VERUM and really as expressive items.
Subjective assessment of super-resolution

Results of a subjective assessment of superresolution (SR) technology for 4K TV sets are reported. 4K TV sets are currently available in the market, and some are equipped with SR functionality. Recently, SR technology that uses nonlinear signal processing (NLSP) and can work in real time has been proposed. The proposed method can enhance images without enlargement. The subjective assessment was performed by comparing 4K videos with and without NLSP on 4K TV sets. The assessment method was a combination of Scheffe's paired comparison and ITU-R BT.500. Assessment data were statistically analyzed, and the results proved that NLSP is superior in resolution.
A model for cancer-suppressive inflammation

In oncology, inflammation is generally regarded as a cancer-promoting process only. Here, we argue that this view may represent a misleading oversimplification. We present evidence from our own work and from the literature documenting cancer-suppressive aspects of inflammation. We propose that specific types of inflammation, in particular inflammation driven by tumor-specific Th1 cells, may repress rather than promote cancer. Th1 cells collaborate with tumor-infiltrating M1 macrophages to efficiently recognize and eliminate malignant cells. In a Th1 environment, pro-inflammatory cytokines such as interleukin (IL)-1α, IL-1β, IL-6 and tumor-necrosis factor α (TNFα) enhance anti-cancer immunity. Inducing Th1-type inflammation may significantly improve immunotherapeutic strategies against cancer.
School Competition and Efficiency with Publicly Funded Catholic Schools

We study competition between two publicly funded school systems in Ontario, Canada: one that is open to all students, and one that is restricted to children of Catholic backgrounds. A simple model of competition between the competing systems predicts greater effort by school managers in areas with more Catholic families who are willing to switch systems. Consistent with this insight, we find significant effects of competitive pressure on test score gains between third and sixth grade. Our estimates imply that extending competition to all students would raise average test scores in sixth grade by 6 percent to 8 percent of a standard deviation. (JEL I21, I22, H75, Z12)
Bifurcations and parametric representations of traveling wave solutions for the Green-Naghdi equations

By using the bifurcation theory of dynamical systems to study the dynamical behavior of the Green--Naghdi equations, the existence of solitary wave solutions along with smooth periodic traveling wave solutions is obtained. Under different regions of parametric spaces, various sufficient conditions to guarantee the existence of the above solutions are given. Some exact and explicit parametric representations of traveling wave solutions are constructed.
Noise Stability and Correlation with Half Spaces

Benjamini, Kalai and Schramm showed that a monotone function $f : \{-1,1\}^n \to \{-1,1\}$ is noise stable if and only if it is correlated with a half-space (a set of the form $\{x: \langle x, a\rangle \le b\}$). We study noise stability in terms of correlation with half-spaces for general (not necessarily monotone) functions. We show that a function $f: \{-1, 1\}^n \to \{-1, 1\}$ is noise stable if and only if it becomes correlated with a half-space when we modify $f$ by randomly restricting a constant fraction of its coordinates. Looking at random restrictions is necessary: we construct noise stable functions whose correlation with any half-space is $o(1)$. The examples further satisfy that different restrictions are correlated with different half-spaces: for any fixed half-space, the probability that a random restriction is correlated with it goes to zero. We also provide quantitative versions of the above statements, and versions that apply for the Gaussian measure on $\mathbb{R}^n$ instead of the discrete cube. Our work is motivated by questions in learning theory and a recent question of Khot and Moshkovitz.
Do protein crystals nucleate within dense liquid clusters?

The evolution of protein-rich clusters and nucleating crystals were characterized by dynamic light scattering (DLS), confocal depolarized dynamic light scattering (cDDLS) and depolarized oblique illumination dark-field microscopy. Newly nucleated crystals within protein-rich clusters were detected directly. These observations indicate that the protein-rich clusters are locations for crystal nucleation.
Complex spliceosomal organization ancestral to extant eukaryotes.

In higher eukaryotes, introns are spliced out of protein-coding mRNAs by the spliceosome, a massive complex comprising five non-coding RNAs (ncRNAs) and about 200 proteins. By comparing the differences between spliceosomal proteins from many basal eukaryotic lineages, it is possible to infer properties of the splicing system in the last common ancestor of extant eukaryotes, the eukaryotic ancestor. We begin with the hypothesis that, similar to intron length (that appears to have increased in multicellular eukaryotes), the spliceosome has increased in complexity throughout eukaryotic evolution. However, examination of the distribution of spliceosomal components indicates that not only was a spliceosome present in the eukaryotic ancestor but it also contained most of the key components found in today's eukaryotes. All the small nuclear ribonucleoproteins (snRNPs) protein components are likely to have been present, as well as many splicing-related proteins. Both major and trans-splicing are likely to have been present, and the spliceosome had already formed links with other cellular processes such as transcription and capping. However, there is no evidence as yet to suggest that minor (U12-dependent) splicing was present in the eukaryotic ancestor. Although the last common ancestor of extant eukaryotes appears to show much of the molecular complexity seen today, we do not, from this work, infer anything of the properties of the earlier "first eukaryote. "
Unified model for software engineering data

Software process data is available in several tools such as version control systems, issue trackers and test and build systems to name a few. Using the data gathered in these software engineering tools would be ideal for collecting different kinds of software processes and product metrics as the data is already automatically gathered by the tools. However, the tools present and store the data in various formats. The data collection methods and interfaces also vary between the tools. This closes the software engineering data into silos and makes it hard to build reusable analysis and visualizations for the data. In this position paper we present a unified model for software engineering data and a framework for data collection, conversion and storing that utilizes our model. The aim of the model is to define a common format for software engineering data which is not dependent on specific software engineering tools or the software engineering process and thus can be used as a basis for building reusable visualization and analysis components. To demonstrate that we can build reusable visualization plugins on top of the framework, we created a timeline visualization plugin. The visualization plugin is used to visualize two data sets from industrial software projects that have different contexts and semantics.