Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Acute b-blocker Withholding on Ventilatory Efficiency in Patients With Advanced Chronic Heart Failure

Background: This is the first study to examine the effect of acute (24-hour) b-blocker withholding on ventilatory efficiency in patients with advanced chronic heart failure (CHF) during maximal incremental treadmill cardiopulmonary exercise test. Methods and Results: Seventeen CHF patients were studied either 3 hours after administration of b-blocker (BBON) or 27 hours after the last b-blocker ingestion (BBOFF). The ventilatory efficiency was measured via the slope of the linear relationship between ventilation (VE) and carbon dioxide production (VCO2) (ie, V 0 E/V CO2 slope). Measurements were also made at rest, anaerobic threshold (AT), maximal end-tidal pressure for carbon dioxide (PETCO2max), respiratory compensation point (RC), and peak exercise. Compared with BBON, the V 0 E/V CO2 slope was significantly increased during BBOFF (30.8 6 7.4 vs. 29.1 6 5.4, P 5 .04). At peak exercise, oxygen uptake (V O2, 16.0 6 2.7 vs. 15.6 6 2.8 mL$kg$min) and VCO2 (1458 6 459 vs. 1414 6 429 mL/min) were not different between the 2 conditions, whereas VE was higher during BBOFF (49.5 6 10.7 vs. 46.1 6 9.6 L/min, P 5 .04). No differences were noted at AT and RC in VO2, V CO2, V 0 E, V 0 E/V O2, and V 0 E/V CO2 ratios during the 2 conditions. At PETCO2max, used to noninvasively estimate the CO2 set point, V 0 E was higher (33.9 6 7.6 vs. 31.7 6 7.3 L/min, P 5 .002) and PETCO2 was lower (37.4 6 4.8 vs. 38.5 6 4.0 mm Hg, P 5 .03), whereas VCO2 was unchanged (1079 6 340 vs. 1050 6 322 mL/min) during BBOFF. Conclusion: Acute b-blocker withholding resulted in decreased ventilatory efficiency mostly from an increase of VCO2-independent regulation of V 0 E and less likely from a change in ventilation/perfusion mismatching. (J Cardiac Fail 2010;16:548e555)
Black-Box Classification Techniques for Demographic Sequences: from Customised SVM to RNN

Nowadays there is a large amount of demographic data which should be analysed and interpreted. From accumulated demographic data, more useful information can be extracted by applying modern methods of data mining. The aim of this study is to compare the methods of classification of demographic data by customising the SVM kernels using various similarity measures. Since demographers are interested in sequences without discontinuity, formulas for such sequences similarity measures were derived. Then they were used as kernels in the SVM method, which is the novelty of this study. Recurrent neural network algorithms, such as Simple RNN, GRU and LSTM, are also compared. The best classification result with SVM method is obtained using a special kernel function in SVM by transforming sequences into features, but recurrent neural network outperforms SVM.
Governmental Context Determines Institutional Value: Independently Certified Performance and Failure in the Spanish Newspaper Industry

Many societies demand that independent professionals (e.g. auditors) certify the performance of firms. The value placed on such certification (i.e. the public perception of reliability/unreliability that may impact on an organization's success/failure) is not uniform, however, but contingent upon changing political contexts. This study presents and analyses data on the entire population of newspapers in Spain from 1966 to 1993, a time of peaceful transition from military dictatorship to capitalist democracy. Our results highlight the contingent nature of institutional life, demonstrating how changes in political contexts are associated with varying understandings of institutions. In particular, our findings support the prediction that, under a dictatorship, independently certified performance is not instrumental in organizational success or failure whereas, in a modern democracy, the certification process has a positive effect on the survival chances of firms.
A Perspective On Segment Reporting Choices And Segment Reconciliations

In 2014, segment reporting gained third place in SEC comment letters. This article reviews the history of segment reporting including segment reporting choices and segment reconciliations, the current concerns as the level of detail in segment disclosures varies widely across organizations, the value relevance of segment reconciliations and its market consequences, and the importance of segment reporting to management. The following are highlights of the manuscript: The third-most-common area discussed in SEC comment letters: segment reporting. The application of SFAS131: the whole may not equal the sum of its parts. The level of detail in segment disclosures varies widely across organizations. Segment reconciliation adds value to consolidated earnings. Segment reconciliation can have significant market consequences. Additional guidance on segment reporting may be beneficial and necessary in the future.
Comparison of Credit Scoring Models on Probability of Default Estimation for Us Banks

This paper is devoted to the estimation of the probability of default (PD) as a crucial parameter in risk management, requests for loans, rating estimation, pricing of credit derivatives and many others key financial fields. Particularly, in this paper we will estimate the PD of US banks by means of the statistical models, generally known as credit scoring models. First, in theoretical part, we will briefly introduce the two main categories of credit scoring models, which will be afterwards used in application part - linear discriminant analysis and regression models (logit and probit), including testing the statistical significance of estimated parameters. In the main part of the paper we will work with the sample of almost three hundred US commercial banks which will be separated into two groups (non-default and default) on the basis of historical information. Subsequently, we will stepwise apply the mentioned above scoring models on this sample to derive several models for estimation of PD. Further we will apply these models to the control sample to determine the most appropriate model.
Analyzing architectural space: identifying salient regions by computing 3D isovists

: Spatio-cognitive properties – including the capacity to evoke a sense of place or support wayfinding – are amongst the most important considerations in the design of large urban and architectural spaces. Both wayfinding and spatial identity rely on the capacity of a space to be noticeably distinct; a property that is called saliency. However, there are relatively few experimental techniques to identify locations that are rich in such visual properties and those that do exist were typically developed in the 1980s using only two-dimensional viewshed geometry. In contrast, this paper describes the use of 3D isovists to develop a salient region estimation technique for architectural and urban environments. The underlying method of saliency estimation is based on principal component analysis that is used to compare geometric properties of the areas surrounding a vantage point. Statistical summaries of the 3D isovists are compared in the principal component space to differentiate the monotonous regions from the ones that are more visually distinct. The experimental results reported in this paper are developed using a model of the Villa Savoye to demonstrate that 3D isovists can be used to determine the extent to which an environment supports a capacity for wayfinding. The paper makes two major contributions to architectural computational analysis; first, it demonstrates a consistent, stable 3D isovist method and second, it proposes a quantitative technique for detecting regions with strong visual characteristics.
Importance of the Clr 2 protein in heterochromatin formation in the fission yeast Schizosaccharomyces pombe

Epigenetics is an area of biology that studies heritable changes in gene expression without any change in the DNA sequence. The most studied epigenetic mechanisms are DNA methylation, RNA interference and histone modifications. There are over 130 different modifications that can be attached to histones, and the most commonly studied are methylation, acetylation, phosphorylation, sumoylation and ubiquitination. The modifications, spread out through the genome, form the histone code, which recruits transcription factors and modifies the accessibility of the DNA, which results in either active or silenced transcription. The silenced form of chromatin is known as heterochromatin and is usually found in regions of the chromosome that need to be highly regulated. To study epigenetics, the model organism Schizosaccharomyces pombe is used widely used. S. pombe is a single cell, rod shaped, fission yeast. The simplicity of S. pombe and its similarities to higher eukaryotes makes it a good model organism for studying epigenetics. We find that, when mutating evolutionary conserved amino acids in the Clr2 protein, which is involved in heterochromatin formation in S. pombe, there is a change in silencing in different heterochromatic regions. When constructs of Clr2 with the BAH domain deleted are overexpressed, there is an increase in silencing in the central core centromere of chromosome II of S. pombe. We choose to go to the Moon in this decade and do the other things, not because they are easy, but because they are hard -John F. Kennedy, September 12, 1962
User Acceptance and Usage of E-learning Technologies: A Theoretical Review

: The quest for higher education has prompted learning institutions to adopt e-learning technologies around the world. To support learning, institutions have shifted from the traditional methods of content delivery and started to use of information technology tools and applications such as learning management systems. E-learning technologies are tools and facilities that enable instructors and learners to interact remotely. Instructors and learners acceptance affects their usage and this critical for successful implementation of e-learning technologies. The objective this paper is to review theoretical literature on learners and instructors acceptance and use of e-learning technologies using Technology Acceptance Model (TAM) and Unified Theory of Acceptance and Usage of Technology (UTAUT), to establish the factors that influence user acceptance and usage of information communications technology and to provide further insight of the issues encompassing acceptance of e-learning technologies by learners and lecturers. This study reveals that despite TAM being a much referred model for predicting technology acceptance factors and usage, the theory in not powerful enough. The paper also established that most of researchers’ referred to UTAUT in their articles considering their end goal was to back a contention instead of utilizing the theory. Others that reported the utilization of UTAUT really employed
A Projection-Based Interface to Involve Semi-Immersed Users in Substitutional Realities

Virtual Reality (VR) allows users to experience Immersive Virtual Environments (IVEs) in a multi-sensory fashion and is about to make its way into many different fields. Becoming an everyday technology, VR has the potential to transform entertainment at home, professional work in the office, and also the way users engage in everyday sports activities. The concept of Substitutional Reality (SR) maps a virtual onto a real environment and enables users to physically interact with IVEs, which allows for an increased feeling of presence. While most previous work focused on providing the VR user with a realistic and highly immersive VR experience, bystanders in the real environment are often not involved. In this paper, we introduce a projection-based system to involve bystanders in the virtual experience, by projecting the virtual environment onto the registered, physical counterpart. Using controllers, the system allows bystanders to interact with the IVE and to perceive the virtual environment in a semi-immersive way. We further present a case study where we applied the system in a substitutional reality climbing scenario and discuss potential application areas.
Improvement in Apriori Algorithm with New Parameters

Data Mining or Knowledge Discovery in Databsaes is an advanced approach which refers to the extraction of previously unknown and useful information from large databases. Association Rule Mining is an important technique of data mining. This technique emphasis on finding interesting relationships. For understanding these relationships, a technique called Market Basket Analysis has been introduced in Data Mining. This helps in understanding the customer behaviour more easily so that frequent patterns can be generated. Apriori algorithm is used in association rule mining for generating frequent patterns. But it generates patterns only on the basis of presence and absence of items, resulting into lack of efficient results. So new parameters have been included in this paper which will be helpful in giving maximum profit to the business organizations. This paper shows that how addition of new parameters improve the efficiency of Apriori algorithm by comparing the results of improved algorithm with the results of traditional Apriori algorithm.
Learning on a Budget Using Distributional RL

Agents acting in real-world scenarios often have constraints such as finite budgets or daily job performance targets. While repeated (episodic) tasks can be solved with existing RL algorithms, methods need to be extended if the repetition depends on performance. Recent work has introduced a distributional perspective on reinforcement learning, providing a model of episodic returns. Inspired by these results we contribute the new budget- and risk-aware distributional reinforcement learning (BRAD-RL) algorithm that bootstraps from the C51 distributional output and then uses value iteration to estimate the value of starting an episode with a certain amount of budget. With this strategy we can make budget-wise action selection within each episode and maximize the return across episodes. Experiments in a grid-world domain highlight the benefits of our algorithm, maximizing discounted future returns when low cumulative performance may terminate repetition.
Vision Based Tracker for Dart Catching Robot

This paper describes how high-speed computer vision can be used in a motion control application. The specific application investigated is a dart catching robot. Computer vision is used to detect a flying dart and a filtering algorithm predicts its future trajectory. This will give data to a robot controller allowing it to catch the dart. The performance of the implemented components indicates that the dart catching application can be made to work well. Conclusions are also made about what features of the system are critical for performance.
Autocorrelations of stellar light and mass in the low-redshift Universe

The final data release of the Sloan Digital Sky Survey (SDSS) provides reliable photometry and spectroscopy for about half a million galaxies with median redshift 0.09. Here, we use these data to estimate projected autocorrelation functions w(p)(r(p)) for the light of galaxies in the five SDSS photometric bands. Comparison with the analogous stellar mass autocorrelation, estimated in a previous paper, shows that stellar luminosity is less strongly clustered than stellar mass in all bands and on all scales. Over the full non-linear range 10 h-1 kpc < r(p) < 10 h-1 Mpc our autocorrelation estimates are extremely well represented by power laws. The parameters of the corresponding spatial functions xi(r) = (r/r(0))gamma vary systematically from r(0) = 4.5 h-1 Mpc and gamma = -1.74 for the bluest band (the u band) to r(0) = 5.8 h-1 Mpc and gamma = -1.83 for the reddest one (the z band). These may be compared with r(0) = 6.1 h-1 Mpc and gamma = -1.84 for the stellar mass. Ratios of w(p)(r(p)) between two given wavebands are proportional to the mean colour of correlated stars at projected distance r(p) from a randomly chosen star. The ratio of the stellar mass to luminosity autocorrelations measures an analogous mean stellar mass-to-light ratio (M(*)/L). All colours get redder and all mass-to-light ratios get larger with decreasing r(p), with the amplitude of the effects decreasing strongly to redder passbands. Even for the u band the effects are quite modest, with maximum shifts of about 0.1 in u - g and about 25 per cent in M(*)/L(u). These trends provide a precise characterization of the well-known dependence of stellar populations on environment.
Effects of Exogenous Lipid Peroxides on Mortality and Tissue Alterations in Japanese Pearl Oysters Pinctada fucata martensii

Abstract The effects of exogenous lipid peroxides, suspected to be a cellular injury factor that causes mass mortalities of cultured Japanese pearl oysters Pinctada fucata martensii, were investigated in vivo and in vitro. Cumulative mortalities of experimental oysters exposed to oxidized oils in suspension (fish feed oil) or emulsion (methyl linoleate) were approximately 40% after 8 or 9 weeks, whereas mortalities were 0.0% (suspension) and 5.6% (emulsion) in control oysters exposed to unoxidized oils. Pathological changes observed in experimental oysters were characterized by blebbing and necrosis of cells in various organs that had spread from the digestive organ and were identical to those observed in diseased oysters from natural mass mortalities. The thiobarbituric acid values of experimental oysters were consistently and significantly higher than those of control oysters. An in vitro exposure examination also demonstrated that oxidized oil caused conspicuous blebbing and necrosis in the epithelial .
Comparison of Three Algorithms for Filtering Airborne Lidar Data

This paper compares three methods for removing non-ground measurements from airborne laser scanning data. These methods, including the elevation threshold with expanding window (ETEW), maximum local slope (MLS), and progressive morphological (PM) filters, analyze data points based on variations of local slope, and elevation. Low and high-relief data sets with various densities of trees, houses, and sand dunes were selected to test the filtering methods. The results show that all three methods can effectively remove most nonground points in both low-relief urban and high-relief forested areas. The PM filter generated the best result in coastal barrier island areas, whereas the other algorithms tended to remove the tops of steep sand dunes. Each method experienced various omission or commission errors, depending on the filtering parameters. Topographic slope is the most sensitive parameter for the three filtering methods.
Effects of antioxidants on copper induced lipid oxidation during salting of cod (Gadus morhua L.)

This is the final draft post refereeing version of the article. © Wiley, reprinted with permission. Published version available at http://dx.doi. org/10.1111/j.1745-4522.2004. tb00264.x The article is part of Kristin Lauritzsen's doctoral thesis, which is available in Munin at http://hdl.handle. net/10037/1819
New NADPH / 9-AA module for the DUAL-PAM-100 : Description , operation and examples of application

The NADPH/9-AA module has become available as a new accessory for the DUAL-PAM-100. Fluorescence is excited at 365 nm using a UV-A Power LED. A photomultiplier sensor is employed for detection of blue-green emission (420 to 580 nm). The new module was optimized for measuring light-induced changes of NADPH fluorescence in suspensions of isolated chloroplasts, algae and cyanobacteria. It also may serve for highly sensitive measurements of various fluorescent probes, like 9-amino-acridine (9-AA), 9-amino-6-chloro-2-methoxyacridine (ACMA), acridine orange and acridine yellow, which in the past have been used for non-invasive monitoring of bioenergetic processes in isolated chloroplasts and whole cells. Technical features of the new emitter-detector module are outlined and some hints for optimal use of the new device and of the Dual-PAM software are given. Examples of application are focused on the phenomenology and interpretation of light induced NADPH fluorescence changes in suspensions of isolated spinach chloroplasts, Chlorella vulgaris and cyanobacteria (Synechococcus PCC 7942 and Synechocystis PCC 6803). Also simultaneous measurements of chlorophyll (Chl) and NADPH fluorescence are presented, revealing parallel and anti-parallel kinetic phases. Under favorable conditions, Saturation Pulses can serve for estimating the extent of NADP reduction in the steady state.
Changes in bacterial activity and community composition caused by exposure to a simulated oil spill in microcosm and mesocosm experiments.

We studied the effects of the Prestige oil spill on Ria de Vigo bacterial abundance, pro- duction and community structure by using mesocosms (ca. 3500 l) filled with water from the center of the Ria, to which we added a realistic concentration of polycyclic aromatic hydrocarbons (PAHs; ini- tial concentrations of approximately 20 to 30 µg l -1 chrysene equivalents) at each of the 4 periods of the seasonal cycle: spring bloom, summer stratification, autumn upwelling and winter. We followed the changes in bacterial activity by leucine and thymidine incorporation, and the changes in bacter- ial assemblage structure by 16S rDNA DGGE. In addition, simultaneously with the winter mesocosm experiment, we ran microcosms with fuel additions equivalent to 0.5, 1, 2 and 4 × the treatment imposed on the mesocosms in the seasonal experiments. Bacterial community structure was also ana- lyzed by CARD-FISH. We detected significant effects of the PAHs on bacterial community structure (increased number of bands) and production only in the summer experiment. In the microcosm experiments, we found similar effects to those in the mesocosms at PAH concentrations of ca. 20 to 40 µg l -1 , and clear detrimental effects on phytoplankton at concentrations of ca. 80 µg l -1 , with large development of Gammaproteobacteria. Our results indicate that an oil spill of the Prestige's magni- tude will have effects on the microbial resident community only at certain times of the year, while at higher PAH concentrations the effects might be more evident. For most of the year, the resident Ria de Vigo microbial communities appear to be accustomed to PAH concentrations such as those used in these experiments.
Joint transfer component analysis and metric learning for person re‐identification

A novel and efficient metric learning strategy for person re-identification is proposed. Person re-identification is formulated as a multi-domain learning problem. The assumption that the feature distributions from different camera views are the same is overthrown in this Letter. ID-based transfer component analysis (IDB-TCA) is proposed to learn a shared subspace, in which the differences in the feature distribution between source domain and target domain are significantly reduced. Experimental evaluation on the CUHK01 dataset demonstrates that metric learning with IDB-TCA embedded outperforms state-of-art metric methods for person re-identification.
Melanoma-Induced Endothelial Cell Growth Involves Phospholipase A2 and COX2 Upregulation

Angiogenesis, the process of formation of new vessels, is fundamental in many biological processes including development, reproduction and wound repair. In tumor biology, key biochemical questions remain to be answered, in particular the molecular and cellular mechanisms responsible for establishing melanoma new vessels. The search of role for already identified soluble factors in experimental cell models encompassing brain endothelial cells, murine melanoma cell lines and pericytes could expand our molecular understanding of cerebral melanoma proliferation. The purpose of this chapter is to summarize existing knowledge of biochemical mechanisms of melanoma adhesion and angiogenesis, as well as new experimental data on the enzymatic and signaling cross-talk between tumor and microvascular cells.