Miracle-dz/UniFAR-FTUs huggingface dataset:
Prevalence of Metabolic Syndrome in COPD Patients and Its Consequences

Background The prevalence of metabolic syndrome in COPD patients and its impact on patient related outcomes has been little studied. We evaluated the prevalence of metabolic syndrome and clinical and functional characteristics in patients with COPD and healthy subjects. Methods 228 COPD patients and 156 healthy subjects were included. Metabolic syndrome was defined using criteria of the IDF. In all patients spirometry, body composition, functional exercise performance, and mood and health status were assessed. Groups were stratified for BMI and gender. Results Metabolic syndrome was present in 57% of the COPD patients and 40% of the healthy subjects. After stratification for BMI, presence of metabolic syndrome in patients with a BMI ≥25 kg/m2 was higher than in healthy peers. Patients with metabolic syndrome and a BMI <25 kg/m2 had higher BMI, fat free mass index and bone mineral density, and a lower 6MWD than the BMI matched patients without metabolic syndrome. Spirometry, maximal ergometry, mood and health status, and blood gases were not different between those groups. In COPD patients with metabolic syndrome self-reported co-morbidities and medication use were higher than in those without. Conclusion Metabolic syndrome is more prevalent in overweight or obese COPD patients than in BMI matched healthy subjects. Metabolic syndrome did not additionally impact patients' functional outcomes, but did impact the prevalence of co-morbidities.
Eye Movements, Visual Search and Scene Memory, in an Immersive Virtual Environment

Visual memory has been demonstrated to play a role in both visual search and attentional prioritization in natural scenes. However, it has been studied predominantly in experimental paradigms using multiple two-dimensional images. Natural experience, however, entails prolonged immersion in a limited number of three-dimensional environments. The goal of the present experiment was to recreate circumstances comparable to natural visual experience in order to evaluate the role of scene memory in guiding eye movements in a natural environment. Subjects performed a continuous visual-search task within an immersive virtual-reality environment over three days. We found that, similar to two-dimensional contexts, viewers rapidly learn the location of objects in the environment over time, and use spatial memory to guide search. Incidental fixations did not provide obvious benefit to subsequent search, suggesting that semantic contextual cues may often be just as efficient, or that many incidentally fixated items are not held in memory in the absence of a specific task. On the third day of the experience in the environment, previous search items changed in color. These items were fixated upon with increased probability relative to control objects, suggesting that memory-guided prioritization (or Surprise) may be a robust mechanisms for attracting gaze to novel features of natural environments, in addition to task factors and simple spatial saliency.
Hierarchical taxonomy preparation for text categorization using consistent bipartite spectral graph copartitioning

Multiclass classification has been investigated for many years in the literature. Recently, the scales of real-world multiclass classification applications have become larger and larger. For example, there are hundreds of thousands of categories employed in the Open Directory Project (ODP) and the Yahoo! directory. In such cases, the scalability of classification methods turns out to be a major concern. To tackle this problem, hierarchical classification is proposed and widely adopted to get better trade-off between effectiveness and efficiency. Unfortunately, many data sets are not explicitly organized in hierarchical forms and, therefore, hierarchical classification cannot be used directly. In this paper, we propose a novel algorithm to automatically mine a hierarchical structure from the flat taxonomy of a data corpus as a preparation for the adoption of hierarchical classification. In particular, we first compute matrices to represent the relations among categories, documents, and terms. And, then, we cocluster the three substances at different scales through consistent bipartite spectral graph copartitioning, which is formulated as a generalized singular value decomposition problem. At last, a hierarchical taxonomy is constructed from the category clusters. Our experiments showed that the proposed algorithm could discover very reasonable taxonomy hierarchy and help improve the classification accuracy.
Modelling Credit Value Adjustment Using Defaultable Options Approach

This thesis calculates Credit Value Adjustment on defaultable options. The prices of defaultable European options are computed through analytical, quadrature approximation and Monte Carlo simulations under the assumption of a constant rate of default. Subsequently, we propose to inversely relate the company’s instantaneous rate of default to its underlying stock price, resulting in a non-constant rate of default. This allows for a new approach to estimate the default of company different from previous work where default is calculated through historical data. The rationale behind this idea relies on the fact that price of the stock plunges before the event of default. For a given set of option parameters, we show that it is possible to find an optimal intensity, which produces the same prices of European options under a simpler framework. However, this intensity fluctuates with changes in other parameters. Implementation details and analysis of the results are provided.
Segmented DP-SLAM

Simultaneous Localization and Mapping (SLAM) is one of the most difficult tasks in mobile robotics. While the construction of consistent and coherent local solutions is simple, the SLAM remains a critical problem as the distance travelled by the robot increases. To circumvent this limitation, many strategies divide the environment in small regions, and formulate the SLAM problem as a combination of multiple precise submaps. In this paper, we propose a new submap-based particle filter algorithm called Segmented DP-SLAM, that combines an optimized data structure to store the maps of the particles with a probabilistic map of segments, representing hypothesis of submaps topologies. We evaluate our method through experimental results obtained in simulated and real environments.
Competition in B 2 C e-Commerce : Analytical Issues and Empirical Evidence

This paper questions the widely held view that B2C e-commerce markets are characterized by a high intensity of competition, using a combination of theoretical arguments and empirical evidence. We discuss two hypotheses and survey empirical studies that test them. We argue that the goods sold in B2C e-commerce have to be interpreted as heterogeneous ‘composite goods’, that market transparency in B2C e-commerce is lower than widely assumed, and that high endogenous sunk costs limit the intensity of competition in B2C
The TAO Project: Intelligent wheelchairs for the handicapped

An R&D project to build a series of intelligent autonomous wheelchairs is discussed. A standardized autonomy management system that can be installed on commercially available well-engineered power chairs has been developed and tested. A behavior-based approach was used to establish sufficient on-board autonomy at minimal cost and material usage, while achieving high efficiency, maximum safety, Iransparency in appearance, and extendability. So far, the add-on system has been installed and tried on two power wheelchair models. Initial results are highly encouraging.
A software memory partition approach for eliminating bank-level interference in multicore systems

Main memory system is a shared resource in modern multicore machines, resulting in serious interference, which causes performance degradation in terms of throughput slowdown and unfairness. Numerous new memory scheduling algorithms have been proposed to address the interference problem. However, these algorithms usually employ complex scheduling logic and need hardware modification to memory controllers, as a result, industrial venders seem to have some hesitation in adopting them.
A Rapid Parallel Hierarchical Aggregation Algorithm on High Dimensional OLAP

On-Line Analytical Processing (OLAP) refers to the technologies that allow users to efficiently retrieve data from the data warehouse for decision support purposes. OLAP queries tend to be complex, often requiring computationally expensive operations such as multi-table joint and aggregation. In the high dimensional DW, we fully materialize the data cube impossibly. In this paper, we propose a novel aggregation algorithm, DHEPHA, to vertically partition a high dimensional dataset into a set of disjoint low dimensional datasets called shell Cube fragments. Using inverted hierarchical encoding indices and pre-aggregated results, OLAP queries are computed online by dynamically constructing cuboids from these Cube fragments. DHEPHA uses the small and their prefix, so it can rapidly retrieve the matching dimension member hierarchical encoding and evaluate the set of query ranges for each dimension, so that it can drastically reduce the multi-table joining effort and even could completely remove one or more join operations. As a result, the method we propose in this paper can greatly reduce the disk I/Os and highly improve the efficiency of OLAP queries.
Terahertz Laser Vibration-Rotation Tunneling Spectroscopy of the Water Tetramer

A vibration−rotation-tunneling (VRT) spectrum of (H2O)4 has been recorded near 2.04 THz (67.9 cm-1). The band origin of this ΔK = 0 symmetric rotor spectrum is shifted by 0.1 cm-1 to the blue of that of a (D2O)4 band reported previously [Science, 1996, 271, 59]. Similar to that spectrum, each transition in the (H2O)4 spectrum exhibits a regular doublet splitting. The (D2O)4 and (H2O)4 doublet spacings, 5.6 and 2260 MHz, respectively, are constant as a function of rotation, indicative of degenerate tunneling splittings. They have been rationalized in terms of a concerted flipping motion of the H atoms that do not participate in hydrogen bonding in the S4 equlibrium structure, analogous to ammonia inversion. Both bands have been assigned to the lowest Ag→ Bg intermolecular vibration in the molecular symmetry group C4h(M). Additional K = 2 splittings, which increase nonlinearly with increasing J, were found in both D2O and H2O tetramer spectra. Evidence for the bifurcation tunneling motion observed in the wa.
Microbial Ecology of Thailand Tsunami and Non-Tsunami Affected Terrestrials

The effects of tsunamis on microbial ecologies have been ill-defined, especially in Phang Nga province, Thailand. This ecosystem was catastrophically impacted by the 2004 Indian Ocean tsunami as well as the 600 year-old tsunami in Phra Thong island, Phang Nga province. No study has been conducted to elucidate their effects on microbial ecology. This study represents the first to elucidate their effects on microbial ecology. We utilized metagenomics with 16S and 18S rDNA-barcoded pyrosequencing to obtain prokaryotic and eukaryotic profiles for this terrestrial site, tsunami affected (S1), as well as a parallel unaffected terrestrial site, non-tsunami affected (S2). S1 demonstrated unique microbial community patterns than S2. The dendrogram constructed using the prokaryotic profiles supported the unique S1 microbial communities. S1 contained more proportions of archaea and bacteria domains, specifically species belonging to Bacteroidetes became more frequent, in replacing of the other typical floras like Proteobacteria, Acidobacteria and Basidiomycota. Pathogenic microbes, including Acinetobacter haemolyticus, Flavobacterium spp. and Photobacterium spp. , were also found frequently in S1. Furthermore, different metabolic potentials highlighted this microbial community change could impact the functional ecology of the site. Moreover, the habitat prediction based on percent of species indicators for marine, brackish, freshwater and terrestrial niches pointed the S1 to largely comprise marine habitat indicating-species.
Mechanism Profiling of Hepatotoxicity Caused by Oxidative Stress Using Antioxidant Response Element Reporter Gene Assay Models and Big Data

Background: Hepatotoxicity accounts for a substantial number of drugs being withdrawn from the market. Using traditional animal models to detect hepatotoxicity is expensive and time-consuming. Alternative in vitro methods, in particular cell-based high-throughput screening (HTS) studies, have provided the research community with a large amount of data from toxicity assays. Among the various assays used to screen potential toxicants is the antioxidant response element beta lactamase reporter gene assay (ARE-bla), which identifies chemicals that have the potential to induce oxidative stress and was used to test > 10,000 compounds from the Tox21 program. Objective: The ARE-bla computational model and HTS data from a big data source (PubChem) were used to profile environmental and pharmaceutical compounds with hepatotoxicity data. Methods: Quantitative structure–activity relationship (QSAR) models were developed based on ARE-bla data. The models predicted the potential oxidative stress response for known liver toxicants when no ARE-bla data were available. Liver toxicants were used as probe compounds to search PubChem Bioassay and generate a response profile, which contained thousands of bioassays (> 10 million data points). By ranking the in vitro–in vivo correlations (IVIVCs), the most relevant bioassay(s) related to hepatotoxicity were identified. Results: The liver toxicants profile contained the ARE-bla and relevant PubChem assays. Potential toxicophores for well-known toxicants were created by identifying chemical features that existed only in compounds with high IVIVCs. Conclusion: Profiling chemical IVIVCs created an opportunity to fully explore the source-to-outcome continuum of modern experimental toxicology using cheminformatics approaches and big data sources. Citation: Kim MT, Huang R, Sedykh A, Wang W, Xia M, Zhu H. 2016. Mechanism profiling of hepatotoxicity caused by oxidative stress using antioxidant response element reporter gene assay models and big data. Environ Health Perspect 124:634–641; http://dx.doi. org/10.1289/ehp.1509763
Sex differences in carotenoid status and immune performance in zebra finches

Sex differences in immunity are common throughout the animal kingdom, with males typically showing reduced immune capacity compared with females due to the immunosuppressive action of androgens like testosterone. However, in animals (e.g. birds, fishes) in which immunostimulatory carotenoid pigments are used to develop colourful traits, males tend to circulate higher concentrations of these immunomodulators to become more colourful than females. In these instances, it is uncertain how differences in carotenoid status might affect sex-specific patterns of immune function. We tested the relationship between carotenoid status and two measures of immunocompetence in male and female zebra finches (Taeniopygia guttata). Non-breeding males circulated a higher concentration of carotenoids through blood than females. Females mounted a significantly higher cell-mediated immune response (to phytohaemagglutinin) than males, but males mounted a significantly higher humoral response (to sheep red blood cells) than females. When supplemented with dietary carotenoids, males showed significant improvements in both cell-mediated and humoral immune performance, while females only showed elevated humoral responsiveness. These results generally support the immunostimulatory role of carotenoids in colourful male and female birds, and indicate that males may gain certain offsetting, carotenoid-facilitated immunological benefits relative to females. It appears that shunting carotenoids to the humoral arm of the immune system – perhaps a more costly yet more effective means of fighting off pathogens – may take priority over elevating cell-mediated immunity in both sexes.
A Preliminary Attempt to Apply Detection and Estimation Theory to Intrusion Detection

Research into the automated detection of computer security violations is hardly in its infancy, yet little comparison has beenmade with the established field of detection and estimation theory, the results of which have been found applicable to a wide range of problems in other disciplines. This paper attempts such a comparison, studying the problem of intrusion detection by the use of the introductory models of detection and estimation theory. Examples are given from current intrusion detection situations, and it is concluded that there are sufficient similarities between the fields to merit further study.
Identification of the transfer function for dual-rate system based on IPSO

This paper proposes that the dual-rate system is transformed from a lifted state-space model to the difference equation of transfer function. An improved particle swarm optimization (IPSO) algorithm is presented to estimate the transfer function's parameters. Comparing the simulation results with a recursive least squares (RLS) the algorithms of IPSO estimates parameters in different signal to noise ratio (SNR). Simulation results show that identification of IPSO has better stability and robust than one of RLS.
Genetic Association Between CDKN1B rs2066827 Polymorphism and Susceptibility to Cancer

AbstractMuch attention has been directed to the association between cancer risk and rs2066827 polymorphism of the CDKN1B gene. However, the results are indefinitive and inconclusive. This study was devised to evaluate the hypothesis that rs2066827 polymorphism is associated with the risk of cancer.Computer-based databases (EMBASE, PubMed, and CNKI) were used to seek all case–control studies evaluating rs2066827 polymorphism and susceptibility to cancer. The genetic risk was assessed by calculating pooled odds ratio (OR) with its corresponding 95% confidence interval (CI). Fixed-effects pooled ORs were calculated by the Mantel–Haenszel method (Ph > 0.05), and random-effects pooled ORs were estimated by the DerSimonian–Laird method (Ph < 0.05). Data on rs2066827 polymorphism and cancer risk were available for 9038 cancer cases and 11,596 controls participating in 17 studies. Carriage of a TG genotype was associated with a minor but significant decrease in the risk of cancer (pooled OR 0.92, 95% CI: 0.86–0.99; model, TG vs. TT). We observed a moderately decreased risk of ovarian cancer based on 1829 cases and 2868 controls (pooled OR 0.85, 95% CI: 0.74–0.97; model, TG vs. TT). A slightly deceased risk of cancer was also indicated in Caucasians consisting of 6707 cases and 8279 controls (pooled OR 0.91, 95% CI: 0.85–0.98; model, TG vs. TT). These data suggest that carriage of a TG genotype at rs2066827 polymorphism may be associated with decreased susceptibility to cancer, ovarian cancer in particular.
Open Source as a Signalling Device - An Economic Analysis

Open source projects produce goods or standards that do not allow for the appropriation of private returns by those who contribute to these projects. In this paper we analyze why programmers will nevertheless invest their time and effort to code open source software. We argue that the particular way in which open source projects are managed and especially how contributions are attributed to individual agents, allows the best programmers to create a signal that more mediocre programmers cannot achieve. Through setting themselves apart they can turn this signal into monetary rewards that correspond to their superior capabilities. With this incentive they will forgo the immediate rewards they could earn in software companies producing proprietary software by restricting the access to the source code of their product. Whenever institutional arrangements are in place that enable the acquisition of such a signal and the subsequent substitution into monetary rewards, the contribution to open source projects and the resulting public good is a feasible outcome that can be explained by standard economic theory. JEL Classification: D82, L14, L86, O31
Reliability evaluation of grid substations in Bangladesh power system

Determination of the reliability of a substation is important as it helps locate weak points that may be contributing to overall power system unreliability. This paper evaluates reliability of 230 kV grid substations in Bangladesh subject to protection failures. The problem belongs to the dynamic reliability evaluation field. Event tree analysis is used as the main method. Fault tree analysis is used to get the input of the event tree. Reliability of five grid substations are calculated. Ishurdi grid substation is found to have a mean time to failure of only six months, which will affect seriously the design and safety of the proposed nuclear power station at Rooppur sited closely nearby.
A stochastic flash A-to-D converter with dynamic element matching technique

This paper discusses and compares the effects of dynamic element matching (DEM) methods applied to the stochastic flash A-to-D converter (SFADC) to improve its linearity and noise behavior. Simulation results have shown that the application of DEM greatly improves linearity and SNDR behavior, and a simple random barrel-shift type of DEM is enough for 6-bit resolution case.
A process distribution approach for multisensor data fusion systems based on geographical dataspace partitioning

In this work, we present a new approach to distributed sensor data fusion (SDF) systems in multitarget tracking, called TSDF (Tessellated SDF), centered around a geographical partitioning (tessellation) of the data. A functional decomposition divides SDF into components that can be assigned to processing units, parallelizing the processing. The tessellation implicitly defines the set of tracks potentially yielding correlations with the sensor plots (observations) in a tile. Some tracks may occur as correlation candidates for multiple tiles. Conflicts caused by correlations of such tracks with plots in different tiles, are resolved by combining all involved tracks and plots into independent data association problems. The benefit of the TSDF approach to a clustering-based process distribution is independence of the problem space, which yields better scalability and manageability characteristics. The TSDF approach allows scaling in more than one way. It allows SDF for single sensor, multiple sensors on a single platform, and even for multiple sensors on multiple platforms. It also provides the flexibility to scale the processing to the size of the problem. This enables a better control of the throughput, to meet various timing constraints.
Waveform design principles for automotive radar systems

This paper presents a high performance 77 GHz FMCW radar sensor for automotive applications. Powerful automotive radar systems are currently under development for various applications. Radar sensor based comfort systems like Adaptive Cruise Control (ACC) are already available on the market. The main objective from a radar sensor point of view is to detect all targets inside the observation area and estimate target range and relative velocity simultaneously with a high update rate. FMCW radar sensors have the advantages of very high range resolution but a serious task occurs in multiple target situations to suppress so-called ghost targets. In classical FMCW waveforms this has been solved in using multiple chirp signals with different slope. But in this case a long measurement time (approximately 50 ms) is needed which is a contradiction to a high update rate. Therefore, in this paper a new waveform design is presented which has all advantages of FMCW radars but needs an extremely low measurement time (10 ms) in a radar sensor with 3 different antenna beams.