Miracle-dz/UniFAR-FTUs huggingface dataset:
Differential effects of arginine methylation on diastolic dysfunction and disease progression in patients with chronic systolic heart failure.

AIMS To investigate the association of arginine methylation with myocardial function and prognosis in chronic systolic heart failure patients. METHODS AND RESULTS Asymmetric dimethylarginine (ADMA) and symmetric dimethylarginine (SDMA), as well as N-mono-methylarginine (MMA) and methyl-lysine, were simultaneously measured by tandem mass spectrometry in 132 patients with chronic systolic heart failure with echocardiographic evaluation and follow-up. Increasing ADMA and SDMA levels were associated with elevated natriuretic peptide levels (both P < 0.001), and increasing SDMA levels were associated with worsening renal function (P < 0.001). Higher plasma levels of methylated arginine metabolites (but not methyl-lysine) were associated with the presence of left ventricular (LV) diastolic dysfunction (E/septal E', Spearman's r = 0.31-0.36, P < 0.001). Patients taking beta-blockers had lower ADMA levels than those not taking beta-blockers [0.42 (0.33, 0.50) vs. 0.51 (0.40, 0.58), P < 0.001]. Only increasing ADMA levels were associated with advanced right ventricular (RV) systolic dysfunction. Elevated ADMA levels remained a consistent independent predictor of adverse clinical events (hazard ratio = 1.64, 95% CI: 1.20-2.22, P = 0.002). CONCLUSION In chronic systolic heart failure, accumulation of methylated arginine metabolites is associated with the presence of LV diastolic dysfunction. Among the methylated derivatives of arginine, ADMA provides the strongest independent prediction of disease progression and adverse long-term outcomes.
Dissimilarity representation on functional spectral data for classification

In chemometrics, spectral data are typically represented by vectors of features in spite of the fact that they are usually plotted as functions of e.g. wavelengths and concentrations. In the representation, this functional information is thereby not reflected. Consequently, some characteristics of the data that can be essential for discrimination between samples of different classes or any other analysis are ignored. Examples are the continuity between measured points and the shape of curves. In the Functional Data Analysis (FDA) approach, the functional characteristics of spectra are taken into account by approximating the data by real valued functions, e.g. splines. Another solution is the Dissimilarity Representation (DR), in which classifiers are trained in a space built by dissimilarities with training examples or prototypes of each class. Functional information may be incorporated in the definition of the dissimilarity measure. In this paper we compare the feature‐based representation of chemical spectral data with three other representations: FDA, DR defined on raw data and DR defined on FDA descriptions. We analyze the classification results of these four representations for five data sets of different types, by using different classifiers. We demonstrate the importance of reflecting the functional characteristics of chemical spectral data in their representation, and we show when the presented approaches are more suitable. Copyright © 2011 John Wiley & Sons, Ltd.
A Symbol-Based Approach to Gait Analysis From Acceleration Signals: Identification and Detection of Gait Events and a New Measure of Gait Symmetry

Gait analysis can convey important information about one's physical and cognitive condition. Wearable inertial sensor systems can be used to continuously and unobtrusively assess gait during everyday activities in uncontrolled environments. An important step in the development of such systems is the processing and analysis of the sensor data. This paper presents a symbol-based method used to detect the phases of gait and convey important dynamic information from accelerometer signals. The addition of expert knowledge substitutes the need for supervised learning techniques, rendering the system easy to interpret and easy to improve incrementally. The proposed method is compared to an approach based on peak detection. A new symbol-based symmetry index is created and compared to a traditional temporal symmetry index and a symmetry measure based on cross correlation. The symbol-based symmetry index exemplifies how the proposed method can extract more information from the acceleration signal than previous approaches.
ArchDB: Towards Parallelized Recovery in Massive Archived Databases

Monitoring online transactions or tracking users' behavior will generate large-scale archived streaming data in scientific experiments, inner-network audit logs and so on. These archived systems may scale up to petabytes (1015 Bytes). Storing and analyzing the structural data in such scale calls forth at least three challenging issues: data reliability, data storing and analyzing performance, and tradeoff between high reliability and high performance. Based on analyzing the characteristics of the archived streaming data, we propose a novel high reliable log-free database architecture, ArchDB. In order to meet the three challenges, this paper designs optimized data placement policy, data block size and data archiving occasion, pipelining and parallelizing archiving procedure. The experimental results show ArchDB can double the insertion performance and speed up the recovery process by a factor of the parallel recovery degree.
Diversity of Soil Fauna and Ecosystem Function

Soils are natural resources of utmost. importance for a number of ecosystem and biosphere processes such as plant production, cycling of organic matter and nutrients, storage of C and water, and release of nitrous oxides, CO2 and methane. Soil degradation, through various processes, is a matter of great concern, since their integrity is absolutely critical to increasing food production (FAO, 1995), and regulating atmospheric fluxes of greenhouse gases (Jenkinson, 199 1 ; Wallace, 1994).
A Comparison of Univariate Time Series Methods for Forecasting Intraday Arrivals at a Call Center

Predictions of call center arrivals are a key input to staff scheduling models. It is, therefore, surprising that simplistic forecasting methods dominate practice, and that the research literature on forecasting arrivals is so small. In this paper, we evaluate univariate time series methods for forecasting intraday arrivals for lead times from one half-hour ahead to two weeks ahead. We analyze five series of intraday arrivals for call centers operated by a retail bank in the United Kingdom. A notable feature of these series is the presence of both an intraweek and an intraday seasonal cycle. The methods considered include seasonal autoregressive integrated moving average (ARIMA) modeling; periodic autoregressive modeling; an extension of Holt-Winters exponential smoothing for the case of two seasonal cycles; robust exponential smoothing based on exponentially weighted least absolute deviations regression; and dynamic harmonic regression, which is a form of unobserved component state-space modeling. Our results indicate strong potential for the use of seasonal ARIMA modeling and the extension of Holt-Winters for predicting up to about two to three days ahead and that, for longer lead times, a simplistic historical average is difficult to beat. We find a similar ranking of methods for call center data from an Israeli bank.
Evolving forest fire burn severity classification algorithms for multispectral imagery

Between May 6 and May 18, 2000, the Cerro Grande/Los Alamos wildfire burned approximately 43,000 acres (17,500 ha) and 235 residences in the town of Los Alamos, NM. Initial estimates of forest damage included 17,000 acres (6,900 ha) of 70-100% tree mortality. Restoration efforts following the fire were complicated by the large scale of the fire, and by the presence of extensive natural and man-made hazards. These conditions forced a reliance on remote sensing techniques for mapping and classifying the burn region. During and after the fire, remote-sensing data was acquired from a variety of aircraft-based and satellite-based sensors, including Landsat 7. We now report on the application of a machine learning technique, implemented in a software package called GENIE, to the classification of forest fire burn severity using Landsat 7 ETM+ multispectral imagery. The details of this automatic classification are compared to the manually produced burn classification, which was derived from field observations and manual interpretation of high-resolution aerial color/infrared photography.
A Comparison of Aspects of Social Skills Development to Build Friendships as Portrayed in Thai and American Award Winning Children’s Books

friendship roles as portrayed in books for preschoolers. The criterion for selecting materials used in this study was threefold. Firstly, the 120 books were children’s literature award winners published in the United States or Thailand from 1996-2016. The awards considered for this study included the Caldecott, Coretta Scott King, the Notable Children’s Book Awards (US.), the Wankeaw, Nanmee, Nai-In Book Awards (Thai), the Office of Basic Education Commission (OBEC) Award, and other highly recommended books for preschool children. Secondly, the books were developmentally and culturally appropriate when adults were interactively reading with preschool and kindergarten children (ages 3-6). Lastly, content of the books portrayed children’s friendship roles, and/or animal characteristics demonstrating friendships. To gather data, the Children’s Book Evaluation Form (updated August, 2016) was used to evaluate the content of each book in these areas: language, genre, setting, plot, theme, writing style, illustrations, behaviors, and feelings as depicted. The form also recorded bibliographical details, book details, types of friendships, story elements, and recommendations. The children’s literature evaluations were coded and analyzed using the Statistical Package for the Social Sciences 22.0 (SPSS). Findings revealed that certain positive behaviors and pro-social skills were necessary to build and maintain friendships, for example, helping, sharing, spending time together, face to face communication , and the acceptance of others, etc. In the development of friendships, the results indicated that certain psychological states, like happiness, satisfaction, empathy, sympathy, closeness, and affection were strengthene
EXPLAINING PERFORMAN CE OF HIGH GROWTH NEW FIRMS IN FINLAND

Abstract This study examines the effects of the factors involved in the start-up situation and the first seven years’ development on the subsequent high growth of firms. On the basis of former literature and models of entrepreneurial behaviour three models of new firm performance will be tested with logistic regression method. First, new venture performance, measured by high growth of the firm, will be e x-plained by entrepreneurial characteristics (entrepreneur’s perso nality, strategic control orientation and skills of entrepreneur). The second model explains rel ative growth by using entrepreneurial team and interaction between the firm and environment as explanatory variables. The third model combines these two models. Doubling of turnover will be used as the criterion of high growth. The longitudinal study follows up 200 SMEs from Finnish metal products manufacturing and business service firms established in 1990 up to the year 1997. The sample consists of 138 firms from the branch of manufacturing of metal products and 62 business service firms. At the seven-year-follow-up 86 firms which survived answered, 55 firms had closed down and 59 firms refused to participate the follow-up study. The study concentrates on the 86 firms which su rvived. About 52 % ( 45 firms) of these firms where iden-tified as growing firms in relation to the whole sample of the study. The first two models that were tested both classified correctly a little bit less than 70 % of ob-servations. In the first model the age of the entrepreneur was the only statistica lly significant variable. In the second model the explanation was slightly higher but altogether five var iables - differentiation of the main product, motives for establishing firm ( 2 variables), style of management (2 variables) - were discovered to be statistically significant. The third model class ified correctly over 76 % of obse r-vations, the age of entrepreneur, motives for establis hing, main product and style of management being the statistically significant variables, as could be expected on the basis of the results of the former models. The analysis suggests that personality and skills of the entrepreneur or environmental factors do not themselves explain the growth performance of new ventures. However, the entrepreneurial skills and previous experience could influence both its ability to obtain resources (Eisenhardt & Schoonhoven, 1990), and the decision to which industry the firm will enter (Chrisman et al., 1999). Environmental factors combined with the personality, especially with the experience factor (age), cla s-
Modeling College and Career Readiness for Adolescents With and Without Disabilities: A Bifactor Approach

Nonacademic skills related to college and career readiness (CCR) have become more prevalent in the literature as proposed conceptual models and frameworks, yet little empirical research exists in their support. We employed latent variable modeling to empirically test a previously proposed six-domain framework of CCR for adolescents with and without disabilities. Results support four specific factors of CCR: Academic Engagement, Critical Learning Processes, Mind-Set, and Transition Knowledge. Using a bifactor model, we confirmed one general factor (CCR) and one specific factor (Transition Knowledge), established measurement invariance on the basis of disability, and found latent mean differences between these groups; students without disabilities had greater overall CCR and transition knowledge. Findings support the use of a CCR measurement model with two potential factor scores in future research and practice and may inform efforts to measure CCR nonacademic skills.
Fast finger tracking system for in-air typing interface

We developed a system which performs 3D motion tracking of human's hand and fingers from images of a single high-frame-rate camera and that recognizes his/her typing motion in the air. Our template-matching-based method using hand textures reduces background effect and enables markerless tracking. In addition, use of a high-frame-rate camera enables recognition of rapid typing motion which is difficult to track using standard cameras. In order to realize real-time recognition, we developed hardware which parallelizes and accelerates image processing. As a result, we achieved real-time recognition of typing motion with the throughput of 138 fps (frames per second) and the latency of 29 ms.
Categorisation of Distortion Profiles in Relation to Audio Quality

Since digital audio is encoded as discrete samples of the audio waveform, much can be said about a recording by the statistical properties of these samples. In this paper, a dataset of CD audio samples is analysed; the probability mass function of each audio clip informs a feature set which describes attributes of the musical recording related to loudness, dynamics and distortion. This allows musical recordings to be classiﬁed according to their “distortion character”, a concept which describes the nature of amplitude distortion in mastered audio. A subjective test was designed in which such recordings were rated according to the perception of their audio quality. It is shown that participants can discern between three different distortion characters; ratings of audio quality were signiﬁcantly different (F(1; 2) = 5:72; p < 0:001; eta^2 = 0:008) as were the words used to describe the attributes on which quality was assessed (�Chi^2(8; N = 547) = 33:28; p < 0:001). This expands upon previous work showing links between the effects of dynamic range compression and audio quality in musical recordings, by highlighting perceptual differences.
The O++ database programming language: implementation and experience

Ode, a database system and environment based on the object paradigm, is discussed. Ode is defined, queried and manipulated using the database programming language O++, which is based on C++. The O++ compiler translates O++ programs into C++ programs that contain calls to the Ode object manager. The implementation of O++, the Ode object manager, and the translation of the database facilities in O++ are described. The problems encountered in the implementation and their resolutions are reviewed. <<ETX>>
Comparative Study of Nest Architecture and Colony Structure of the Fungus-Growing Ants, Mycocepurus goeldii and M. smithii

Abstract Nest architecture and demography of the non leaf-cutting fungus-growing ant species Mycocepurus goeldii and M. smithii (Attini: Formicidae) were studied in an agroforest habitat near Manaus, Brazil during the excavation of 13 nests. Both species built their nests in two different ways. The first type possessed a “tree-like” architecture, in which a vertical tunnel led downwards and lateral tunnels branched off at 90° angles from the main tunnel, with a chamber at the end of each side branch. Alternatively, other nests displayed a “necklace-like” architecture, where the main tunnel also led down vertically, but entered each chamber from the top and exited it at the bottom, resulting in an architecture where chambers appeared like pearls on a necklace. The nest systems of M. goeldii and M. smithii consisted of 1–21 or 1–15 chambers, respectively. Of 199 excavated chambers, 57 % contained fungus-gardens. Chambers not containing fungus gardens were filled with organic matter from decaying fungus gardens or earthworm feces. Only M. smithii workers deposited loose soil in abandoned chambers during the construction of new nest chambers. Workers of M. smithii constructed significantly smaller chambers than those of M. goeldii. In both species, fungus garden-containing chambers were larger than non-garden chambers and were homogenously distributed in the soil between 17 cm and 105 cm depth. Neither fungus gardens nor abandoned chambers were encountered more frequently in deeper or shallower soil strata indicating that ants of both species did not abandon shallower versus deeper chambers, or move the colony to deeper soil layers with increasing colony age. Fungus gardens were suspended from the ceiling of the subterranean chambers and originated as small mycelial tufts. Through continual addition of organic debris, the tufts first grew vertically to strands before they expanded laterally until most of the chamber volume was filled with fungus garden curtains. New garden chambers were found at depths ranging from 17 to 83 cm, suggesting that new garden chambers were not constructed in deeper soil strata with increasing colony age. The size of M. goeldii and M. smithii colonies was dependent on their age. Worker counts varied between a few individuals in recently founded colonies and 1352 workers in an adult M. goeldii colony. The ratio of worker number per fungus garden chamber was higher in M. goeldii colonies than M. smithii colonies; the M. goeldii colonies were more populous. Both species were oligogynous with a maximum of four and three queens observed in a single chamber of M. goeldii and M. smithii, respectively. The reproductive status of each queen was unknown. In both species the ratio of brood to workers was approximately 2:3. Larvae and pupae were unequally distributed throughout the nest, but were only located in chambers containing a garden. Their location in the chamber was dependent upon the developmental state of the fungus garden.
Neuroscience Meets Cryptography: Designing Crypto Primitives Secure Against Rubber Hose Attacks

Cryptographic systems often rely on the secrecy of cryptographic keys given to users. Many schemes, however, cannot resist coercion attacks where the user is forcibly asked by an attacker to reveal the key. These attacks, known as rubber hose cryptanalysis, are often the easiest way to defeat cryptography. We present a defense against coercion attacks using the concept of implicit learning from cognitive psychology. Implicit learning refers to learning of patterns without any conscious knowledge of the learned pattern. We use a carefully crafted computer game to plant a secret password in the participant's brain without the participant having any conscious knowledge of the trained password. While the planted secret can be used for authentication, the participant cannot be coerced into revealing it since he or she has no conscious knowledge of it. We performed a number of user studies using Amazon's Mechanical Turk to verify that participants can successfully re-authenticate over time and that they are unable to reconstruct or even recognize short fragments of the planted secret.
Global Dynamics and Stability Limits for Planetary Systems around HD 12661, HD 38529, HD 37124, and HD 160691

In order to distinguish between regular and chaotic planetary orbits, we apply a new technique, called the mean exponential growth factor of nearby orbits (MEGNO), in a wide neighborhood of orbital parameters determined using standard two-body Keplerian fits for the HD 12661, HD 38529, HD 37124, and HD 160691 planetary systems. We show that the currently announced orbital parameters place these systems in very different situations from the point of view of dynamical stability. While HD 38529 and HD 37124 are located within large stability zones in the phase space around their determined orbits, the preliminary orbits in HD 160691 are highly unstable. The orbital parameters of the HD 12661 planets are located in a border region between stable and unstable dynamical regimes, so while its currently determined orbital parameters produce stable regular orbits, a minor change within the margin of error of just one parameter may result in a chaotic dynamical system.
EEG Asymmetry and ERN: Behavioral Outcomes in Preschoolers

Research has documented reciprocal influences between approach-related and inhibition-related neural activity in adults. However, associations between neural systems of approach and inhibition have not been tested in children. It is thus unclear whether these links are present early in life and whether associations between neural systems of approach and inhibition have long-term behavioral consequences. To address these gaps in the literature, we used electroencephalography (EEG) to examine associations between approach-related neural activity (i.e., hemispheric asymmetry) and inhibition-related neural activity (i.e., error-related negativity [ERN]) in preschool-aged children. Furthermore, we explored whether interactions between asymmetry and ERN predicted social inhibition, a precursor to anxiety problems, or symptoms of Attention Deficit Hyperactivity Disorder (ADHD) six months later. Similar to research on adults, greater left asymmetry (i.e., greater approach-related neural activity) was correlated with reduced ERN amplitude (i.e., weaker inhibition-related neural activity). The interactive effect of asymmetry and ERN amplitude did not predict ADHD symptoms, but did predict social inhibition. When ERN was greater, less left asymmetry was associated with higher levels of social inhibition. Results were most prominent at parietal EEG sites. Implications for understanding the development of the overlap in neural systems of approach and inhibition are discussed.