Miracle-dz/UniFAR-FTUs huggingface dataset:
Association of Cystatin C With Mortality, Cardiovascular Events, and Incident Heart Failure Among Persons With Coronary Heart Disease: Data From the Heart and Soul Study

Background— Serum creatinine and related estimating equations predict cardiovascular events and mortality among persons with coronary heart disease (CHD). Cystatin C is a novel and sensitive endogenous marker of kidney function. Whether cystatin C concentrations are associated with adverse events among ambulatory persons with CHD is unknown. Methods and Results— Nine hundred ninety ambulatory persons with CHD were categorized into quartiles of serum cystatin C at inception, with ≤0.91 mg/L constituting the lowest quartile (I) and ≥1.30 mg/L constituting the highest (IV). Cox proportional hazards models evaluated time to all-cause mortality, cardiovascular events (composite of CHD death, myocardial infarction, and stroke), and incident heart failure. After a median follow-up of 37 months, 132 participants (13%) died, 101 (10%) had cardiovascular events, and 57 (7%) had incident heart failure. Compared with participants in the lowest cystatin C quartile, those in the highest quartile were at increased risk of all-cause mortality (hazard ratio, 3.6; 95% CI, 1.8 to 7.0), cardiovascular events (hazard ratio, 2.0; 95% CI, 1.0 to 3.8), and incident heart failure (hazard ratio, 2.6; 95% CI, 1.0 to 6.9) in analyses adjusted for traditional cardiovascular risk factors. Cystatin C in the highest quartile predicted similar risk for these outcomes among participants with lower (≤60 mL/min per 1.73 m2) or higher estimated glomerular filtration rate and among participants with or without microalbuminuria. Conclusions— High cystatin C concentrations predict substantial increased risks of all-cause mortality, cardiovascular events, and incident heart failure among ambulatory persons with CHD. This risk is not completely captured by measures of kidney function routinely used in clinical practice.
Initialization-robust multipitch estimation based on latent harmonic allocation using overtone corpus

We present a new method for modeling the overtone structures of musical instruments that uses an overtone corpus generated using a MIDI synthesizer. Since multipitch estimation requires a joint estimation of F0's and their overtone structures, one of the most important problems is the overtone structure modeling. Latent harmonic allocation (LHA), a promising multipitch estimation method, is difficult to use for various applications because it requires appropriate prior distributions of the overtone structures, which cannot be determined from statistical evidence. Our method uses an overtone corpus to avoid the problem of setting prior distributions and instead restricts the lower and upper bounds of each overtone weight. The bounds are determined from reference signals generated by a MIDI synthesizer. Experimental results demonstrated that the overtone structures were stably and accurately estimated for a wide variety of initial settings.
The Impact of Land Fragmentation on Rice Production Cost and Input Use

This article estimated the impacts of land fragmentation on production costs and input demands using panel data of Japanese rice farms. Empirical results reveal that fragmentation increases production costs and offsets economies of size, and that these impacts are strong especially for large size farms. This result implies that as the farm gets larger, emphasis should be switched from increasing size to the settlement of fragmentation, in order to enhance efficiency. Moreover, it was demonstrated that fragmentation increases not only fuel inputs and labor hours for weeding and harvesting as generally accepted, but also managerial labor such as bookkeeping and meeting, and materials such as fertilizers and pesticides probably due to the substitution effects from labor. The range of fragmentation's impacts is spread beyond our scope. This result implies that the settlement of fragmentation will bring not only the reduction of production cost but also an environmental benefit by reducing fertilizers and pesticides.
The Model of Service Quality at Na Yai Arm Sub-District Administrative Organization, Na Yai Arm District, Chantaburi Province, Thailand

The objectives of this study were: 1) to analyze the model of service quality at Na Yai Arm Sub-district Administrative Organization, Na Yai Arm District, Chanthaburi Province using empirical data, and; 2) to study the effect on administration using the concept of good governance of service quality in the Na Yai Arm Sub-district Administrative Organization, Na Yai Arm District, Chanthaburi Province. The population consisted of 2,946 heads of households who were registered in Na Yai Arm Sub-District Administrative Organization. Using a stratified random sampling technique, 352 participants comprised the sample group , while participants from each village were randomly selected by simple random sampling. A questionnaire was used as the research instrument in this study. A Structural Equation Model Analysis was used for inspecting the concordance of the developed model with the empirical data and for studying the direct effect of administration following the concept of good governance on service quality at Na Yai Arm Sub-district Administration Organization, Na Yai Arm District, Chanthaburi Province. The findings were as follows: 1. The analysis result showed that the model of service quality fit with the empirical data 2. The result of the analysis also showed that good governance affected service quality at Na Yai Arm Sub-district Administrative Organization.
Leaf Volatile Compounds and Associated Gene Expression during Short-Term Nitrogen Deficient Treatments in Cucumis Seedlings

Nitrogen (N) is an important macronutrient for plant growth and development, but the regulatory mechanism of volatile compounds in response to N deficiency is not well understood, especially in cucumber, which consumes excessive N during growth. In this study, the major volatile compounds from cucumber leaves subjected to N deficiency were analyzed by GC-MS. A total of 24 volatile components were identified including 15 aldehydes, two ketones, two alkenes, and five other volatile compounds in 9930 leaves. Principal component analysis using volatile compounds from cucumber leaves provided good separation between N-sufficient and N-deficient treatments. The main volatiles in cucumber leaves were found to be C6 and C9 aldehydes, especially (E)-2-hexanal and (E,Z)-2,6-nonadienal. (E)-2-hexanal belonged to the C6 aldehyde and was the most abundant compound, whereas (E,Z)-2,6-nonadienal was the chief component of C9 aldehydes. During N-deficient treatment, short-chain volatile content was significantly improved at 5 day, other volatiles displayed significant reduction or no significantly changes in all sampling points. Improvement of short-chain volatiles was confirmed in the six other inbred lines at 5 day after N-deficient treatments. The expression analysis of 12 cucumber LOX genes and two HPL genes revealed that CsLOX19, CsLOX20, and CsLOX22 had common up-regulated expression patterns in response to N-deficient stress in most inbred lines; meanwhile, most sample points of CsHPL1 also had significant up-regulated expression patterns. This research focused on the relationship between volatiles in cucumber and different nitrogen environments to provide valuable insight into the effect of cultivation and management of the quality of cucumber and contributes to further research on volatile metabolism in cucumber.
A novel content-adaptive image compression system

This paper presents a novel content-adaptive image compression system. Utilizing a pattern-driven model, we explore the synergy between content-based analysis and compression. For a given image, disparate low-level visual patterns are automatically separated, modeled, and encoded using compact and “customized” features and parameters. The feasibility and efficiency of the proposed system were corroborated by quantitative experiments and comparisons. Since different patterns are separated and modeled explicitly during the compression, our method holds potentials for providing better support for compressed-domain analysis.
Predicting Phases in Business Cycles Under Concept Drift

For many tasks where data is collected over an extended period of time, its underlying distribution is likely to change. A typical example is information filtering, i.e. the adaptive classification of documents with respect to a particular user interest. Both the interest of the user and the document content change over time. Machine learning approaches handling this type of concept drift have been shown to outperform more static approaches ignoring it in experiments with different types of simulated concept drifts on real-word text data. In this paper, these approaches to learning drifting concepts are applied to the problem of classifying phases in business cycles. Their performance is compared to the more static approaches on real-world data for this classification task, in order to evaluate whether this domain also exhibits concept drifts and whether the concept drift approaches also allow performance gains in this domain. While previous studies were based on simulated concept drift scenarios, the experiments in this domain are not based on any simulated drift, but on the real concept drift inherent to this real-world data. Hence this paper provides significant support for the applicability of the proposed machine learning approaches to handling concept drift in real-
Association between Serum Fructosamine and Kidney Function in Nondiabetic Individuals without Chronic Kidney Disease

Background Serum fructosamine (SF) has been considered to be an indicator that estimates glycemic control in patients with diabetes mellitus (DM). There is increasing evidence that SF concentration and oxidative stress are significantly elevated in patients with chronic kidney disease (CKD). However, the data about SF and its association with kidney function are lacking in nondiabetic individuals without CKD. We included 1891 nondiabetic individuals who had not been diagnosed with CKD to determine the association between SF and kidney function. Material/Methods We conducted a retrospective analysis on the basis of the biochemistry database in nondiabetic individuals without CKD. Results When eligible participants were stratified in accordance with SF quartiles, from the bottom to the top quartile of SF, a significant decrease of estimated glomerular filtration rate (GFR) was observed in baseline data. SF concentration was negatively associated with estimated GFR (r=−0.066, P=0.004) in the Pearson correlation analysis. Estimated GFR was associated with SF levels independently of glucose (GLU), total cholesterol (TC), triglyceride (TG), and total protein (TP) in multivariable logistic regression analysis (OR=0.984; CI 95% 0.977–0.991; P<0.001). Conclusions We suggest that mild elevation of SF concentration is associated with estimated GFR in nondiabetic individuals without CKD. These findings indicate that SF may underlie CKD in nondiabetic individuals.
Memory in the small: an application to provide task-based organizational memory for a scientific community

Many forms of organizational memory must exist embedded within the organizational processes and tasks. This paper argues that "memory-in-the small", memory utilized in the performance of an organizational task, can serve as an effective performance support mechanism. By basing organizational memory upon organizational tasks (and basing task support upon organizational memory), organizational memory systems can provide additional and necessary support services for organizations and communities. As an example of memory-in-the-small, this paper describes a software application called the ASSIST, that combines organizational memory with task performance for a scientific community. The ASSIST utilizes and stores the collective memory of astrophysicists about data analysis and is used world-wide by astrophysicists. The paper also considers the theoretical and architectural issues involved when combining organizational memory with task performance. <<ETX>>
Designing a system for cooperative work on the World-Wide Web: experiences with the BSCW system

The Basic Support for Cooperative Work (BSCW) project at GMD is developing tools that provide support for cross-platform information sharing for groups of users over the World Wide Web. The basis for these tools is the BSCW shared workspace system, a centralised shared information system integrated with an unmodified Web server and accessible from standard Web browsers. We discuss the experiences with the public release of version 1 of the system and the subsequent re-design for the current version (version 2), following feedback from the users. We describe particular problems, and demonstrate our solutions, arising from the choice of the Web as a platform for collaboration tools, and extend this to suggest that some of our experiences may be more generally applicable to the design of effective collaboration-support systems.
Using mobile crawlers to search the Web efficiently

Due to the enormous growth of the World Wide Web, search engines have become indispensable tools for Web navigation. In order to provide powerful search facilities, search engines maintain comprehensive indices for documents and their contents on the Web by continuously downloading Web pages for processing. In this paper, we demonstrate an alternative, more efficient approach to the “download-first process-later” strategy of existing search engines by using mobile crawlers. The major advantage of the mobile approach is that the analysis portion of the crawling process is done locally where the data resides rather than remotely inside the Web search engine. This can significantly reduce network load which, in turn, can improve the performance of the crawling process. In this report, we provide a detailed description of our architecture supporting mobile Web crawling and report on its novel features as well as the rational behind some of the important design decisions that were driving our development. In order to demonstrate the viability of our approach and to validate our mobile crawling architecture, we have implemented a prototype that uses the UF intranet as its testbed. Based on this experimental prototype, we conducted a detailed evaluation of the benefits of mobile Web crawling.
High levels of HB-EGF and interleukin-18 are associated with a high risk of in-stent restenosis

Objective: To explore the clinical significance of heparin-binding epidermal growth factor-like growth factor (HB-EGF), interleukin-18 (IL-18), and interleukin-10 (IL-10) in restenosis after percutaneous coronary intervention (PCI). Methods: A total of 198 patients with acute coronary syndrome underwent coronary drug-eluting stent implantation and were divided into the restenosis group and non-restenosis group on the basis of second coronary angiography. Biological parameters and HB-EGF, IL-18, and IL-10 levels were measured. Patients in the restenosis group were further divided into 3 subgroups according to Gensini score: group A (Gensini score of <20), group B (Gensini score of >20 but <40), and group C (Gensini score of >40). Results: Compared with the non-restenosis group, HB-EGF and IL-18 levels were significantly higher but serum IL-10 levels were significantly lower in the restenosis group. Furthermore, HB-EGF levels increased with the Gensini score among the 3 subgroups. Spearman’s correlation analysis showed that HB-EGF levels were associated with IL-18 levels and the number of diseased vessels. Multivariate logistic regression analysis showed that diabetes, HB-EGF, and IL-18 were risk factors for restenosis [odds ratio with 95% confidence interval: 3.902 (1.188-4.415), 2.185 (1.103-4.014), and 2.079 (1.208-4.027), respectively]. Conclusion: The present study has demonstrated that HB-EGF may be used to evaluate the severity of restenosis and coronary artery lesion and that inflammatory responses may be involved in the process of restenosis.
Surface Soil Water Content Estimation from Thermal Remote Sensing based on the Temporal Variation of Land Surface Temperature

Soil water content (SWC) is a crucial variable in the thermal infrared research and is the major control for land surface hydrological processes at the watershed scale. Estimating the surface SWC from remotely sensed data using the triangle method proposed by Price has been demonstrated in previous studies. In this study, a new soil moisture index (Temperature Rising Rate Vegetation Dryness IndexTRRVDI) is proposed based on a triangle constructed using the mid-morning land surface temperature (LST) rising rate and the vegetation index to estimate the regional SWC. The temperature at the dry edge of the triangle is determined by the surface energy balance principle. The temperature at the wet edge is assumed to be equal to the air temperature. The mid-morning land surface temperature rising rate is calculated using Meteosat Second GenerationSpinning Enhanced Visible and Infrared Imager (MSG-SEVIRI) LST products over 4 cloud-free days (day of year: 206, 211, 212, 242) in 2007. The developed TRRVDI is validated by in situ measurements from 19 meteorological stations in Spain. The results indicate that the coefficient of determination (R-2) between the TRRVDI derived using the theoretical limiting edges and the in situ SWC measurements is greater than that derived using the observed limiting edges. The R-2 values are 0.46 and 0.32; respectively (p < 0.05). Additionally, the TRRVDI is much better than the soil moisture index that was developed using one-time LST and fractional vegetation cover (FVC) with the theoretically determined limiting edges.
Geometric approach to sampling and communication

Relationships that exist between the classical, Shannon-type, and geometric-based approaches to sampling are investigated. Some aspects of coding and communication through a Gaussian channel are considered. In particular, a constructive method to determine the quantizing dimension in Zador's theorem is provided. A geometric version of Shannon's Second Theorem is introduced. Applications to Pulse Code Modulation and Vector Quantization of Images are addressed.
A novel Split Bregman algorithm for MRI denoising task in an e-Health system

An interesting challenge in e-Health is to develop tools and software in order to benefit the healthcare services. Our applicative context is Magnetic Resonance Imaging (MRI). The main purpose of this paper is to propose a regularization framework for solving an inverse reconstruction problem in MRI. We focus on the Split Bregman method, which is a well known efficient tool for solving a wide variety of optimization problems e.g. total variation minimization problems arising from image denoising. The proposed denoising approach, based on the TV/ROF model, involves a second-order derivative penalty term and, accordingly, introduces some modifications to the Split Bregman scheme. Our iterative regularization strategy has interesting features in highlighting the image contrasts and in the noise removal. Numerical experiments prove the goodness of the proposed approach.
Urinary Proteomics Pilot Study for Biomarker Discovery and Diagnosis in Heart Failure with Reduced Ejection Fraction

Background Biomarker discovery and new insights into the pathophysiology of heart failure with reduced ejection fraction (HFrEF) may emerge from recent advances in high-throughput urinary proteomics. This could lead to improved diagnosis, risk stratification and management of HFrEF. Methods and Results Urine samples were analyzed by on-line capillary electrophoresis coupled to electrospray ionization micro time-of-flight mass spectrometry (CE-MS) to generate individual urinary proteome profiles. In an initial biomarker discovery cohort, analysis of urinary proteome profiles from 33 HFrEF patients and 29 age- and sex-matched individuals without HFrEF resulted in identification of 103 peptides that were significantly differentially excreted in HFrEF. These 103 peptides were used to establish the support vector machine-based HFrEF classifier HFrEF103. In a subsequent validation cohort, HFrEF103 very accurately (area under the curve, AUC = 0.972) discriminated between HFrEF patients (N = 94, sensitivity = 93.6%) and control individuals with and without impaired renal function and hypertension (N = 552, specificity = 92.9%). Interestingly, HFrEF103 showed low sensitivity (12.6%) in individuals with diastolic left ventricular dysfunction (N = 176). The HFrEF-related peptide biomarkers mainly included fragments of fibrillar type I and III collagen but also, e.g., of fibrinogen beta and alpha-1-antitrypsin. Conclusion CE-MS based urine proteome analysis served as a sensitive tool to determine a vast array of HFrEF-related urinary peptide biomarkers which might help improving our understanding and diagnosis of heart failure.
The major allergen content of allergenic preparations reflects their biological activity

The content of major allergens in biologically standardized allergenic preparations of birch, mite (Der p), cat, Alternaria (Alt a) and ragweed (Amb e) was determined. It was found fairly constant between species, i.e. varied within a factor of 2, with the exception of Alt a 1 in Alternaria alternata extract. This variation is allowed by authorities between different batches prepared from the same species of allergen. The method for biological standardization (BS) prescribed in the Nordic Guidelines has, for common inhalant allergens, been shown to give reproducible results between regions of Europe. However, it is difficult to define patients suitable for BS of most food allergens as well as less common inhalant allergens. Therefore we propose that, in the future, BS is replaced by determination of well‐established major allergens and that 1 ng of major allergen is given the value of 1 Biological Unit.
Structural analysis of protein dynamics by MD simulations and NMR spin‐relaxation

Molecular dynamics (MD) simulations and nuclear magnetic resonance spin‐relaxation measurements provide detailed insights into ps‐ns structural dynamics of proteins. An analysis of discrepancies between the two methods is presented for the B3 immunoglobulin‐binding domain of streptococcal protein G. MD simulations using three MD force fields (OPLS‐AA, AMBER ff99SB, and AMBER ff03) overestimate the flexibility of backbone NH vectors at the borders of secondary structure and in loops when compared with experimentally determined backbone amide generalized order parameters (Hall and Fushman, J Am Chem Soc 2006; 12:7855–7870 ). Comparison with a previous study of residual dipolar coupling constants (Bouvignies et al., Proc Natl Acad Sci USA 2005;102:13885–13890 ) indicates that slower timescale motions do not account for the discrepancies. Structural analysis reveals that relative imbalance between the description of hydrogen bonding and other terms of modern force fields may be responsible for disagreement. Proteins 2008. © 2007 Wiley‐Liss, Inc.