Miracle-dz/UniFAR-FTUs huggingface dataset:
CLINICAL RESEARCH Interventional Cardiology Value of Platelet Reactivity in Predicting Response to Treatment and Clinical Outcome in Patients Undergoing Primary Coronary Intervention Insights Into the STRATEGY Study

OBJECTIVES The purpose of this study was to evaluate the value of platelet reactivity (PR) in predicting the response to treatment and outcome in patients with ST-segment elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention assisted by glycoprotein (GP) IIb/IIIa inhibition. BACKGROUND There is limited prognostic information on the role of spontaneous or drug-modulated PR in STEMI patients. METHODS The PR was measured with Platelet Function Analyzer (PFA)-100 and light transmission aggregometry (LTA) using adenosine diphosphate as agonist in 70 consecutive STEMI patients at entry (PR-T0), 10 min after GP IIb/IIIa bolus (PR-T1), and discharge (PR-T2) and in 30 stable angina (SA) patients (PR-SA). Complete platelet inhibition (CPI) was based on closure time 300 s by PFA-100 and percentage inhibition of platelet aggregation 95% by LTA. Clinical, electrocardiographic, and angiographic responses to treatment during 1-year follow-up were collected. RESULTS According to both techniques, PR-T0 was higher than: 1) PR-T2 and PR-SA; 2) in those without CPI at T1; and 3) in patients with final Thrombolysis In Myocardial Infarction (TIMI) flow grade 3. The PR-T0 assessed with PFA-100 correlated with: 1) corrected TIMI frame count (r 0.6, p 0.001); 2) ST-segment resolution (r 45, p 0.001); and 3) creatine kinase-MB (r 0.47, p 0.001). At 1 year, patients with high PR-T0 showed an adjusted 5- to 11-fold increase in the risk of death, reinfarction, and target vessel revascularization (hazard ratio [HR] 11, 95% confidence interval [CI] 1.5 to 78 [p 0.02] in PFA-100; HR 5.2, 95% CI 1.1 to 23 [p 0.03] in LTA). CONCLUSIONS The PR at entry affects response to GP IIb/IIIa inhibition, mechanical treatment, and long-term outcome in STEMI patients undergoing primary intervention. (J Am Coll Cardiol 2006;48:2178 – 85) © 2006 by the American College of Cardiology Foundation
Steganalysis of Analysis-by-Synthesis Compressed Speech

In this paper a steganalysis method for analysis-by-synthesis (AbS) compressed speech is proposed. In the steganalysis method, the probability difference of 0 and 1 and five statistics, including sum of histogram local flatness, sum of histogram local extremum difference, sum of histogram local variance, sum of histogram characteristic function, are used as distinguishing features. SVM classifiers are employed to discriminate stego speech from cover speech. For the example of steganalysis to speech compressed by G.729 algorithm, experiment results show the proposed algorithm has good performance.
Bayesian computation: a statistical revolution

The 1990s saw a statistical revolution sparked predominantly by the phenomenal advances in computing technology from the early 1980s onwards. These advances enabled the development of powerful new computational tools, which reignited interest in a philosophy of statistics that had lain almost dormant since the turn of the century. In this paper we briefly review the historic and philosophical foundations of the two schools of statistical thought, before examining the implications of the reascendance of the Bayesian paradigm for both current and future statistical practice.
In Search for Intelligence : Automatically Estimating the Implicitness of Police Officers ’ Observation Messages , an Ongoing Action Research

This paper presents a method to identify observations containing information about potentially suspect situations (intelligence), made by police officers and registered in a digital notebook. The underlying assumption was that messages containing intelligence have a more implicit character than factual reports on car accidents and the like. To identify messages with a high level of implicit content, we applied a classification method using different kinds of features extracted from the text. Besides the representation of a document in word vectors, we also added additional syntactical and lexical features: number of adjectives, number of nouns, number of verbs and number of characters used in the message. One predefined field of the message, used for the time interval in which the observation took place, was also added. Moreover, domain knowledge, typical jargon used by police offers, was added to adjust the classifier such that the number of false negatives was minimized. The results show that the number of adjectives was of high value in the classifier and that adding domain knowledge to the classifier does help minimizing the number of observations falsely classified as having no implicit content.
Multilevel Hierarchical Kernel Spectral Clustering for Real-Life Large Scale Complex Networks

Kernel spectral clustering corresponds to a weighted kernel principal component analysis problem in a constrained optimization framework. The primal formulation leads to an eigen-decomposition of a centered Laplacian matrix at the dual level. The dual formulation allows to build a model on a representative subgraph of the large scale network in the training phase and the model parameters are estimated in the validation stage. The KSC model has a powerful out-of-sample extension property which allows cluster affiliation for the unseen nodes of the big data network. In this paper we exploit the structure of the projections in the eigenspace during the validation stage to automatically determine a set of increasing distance thresholds. We use these distance thresholds in the test phase to obtain multiple levels of hierarchy for the large scale network. The hierarchical structure in the network is determined in a bottom-up fashion. We empirically showcase that real-world networks have multilevel hierarchical organization which cannot be detected efficiently by several state-of-the-art large scale hierarchical community detection techniques like the Louvain, OSLOM and Infomap methods. We show that a major advantage of our proposed approach is the ability to locate good quality clusters at both the finer and coarser levels of hierarchy using internal cluster quality metrics on 7 real-life networks.
Multi-Node Transfer Alignment Based on Mechanics Modeling for Airborne DPOS

This paper deals with the problem of multi-node transfer alignment estimation of airborne distributed position and orientation system (DPOS), and its aim is to achieve the motion parameters for all sub-nodes as high precision as possible by using the main system. The complicated aircraft deformation, especially the wing’s flexure, will seriously decrease the accuracy of transfer alignment. Usually, the deformation between the main node and each sub-node is idealized as an independent Markov process. In fact, these deformations are interrelated at a certain moment. To solve the mentioned problem, a multi-node transfer alignment method based on mechanics modeling is proposed in this paper. In this method, the elastic mechanics theory is used to build a unified kinematic equation of the wing to describe the flexible deformations of all sub-nodes, and then the transfer alignment is performed to obtain the motion parameters of each sub-node with inertial measurement units (IMU). Finally, the motion parameters of other sub-nodes without IMUs are obtained by the least squares fitting. The mathematical simulation and semi-physical simulation based on flight experiment show that the proposed method is not only effective but also provides us some new insights into the multi-node measurement of DPOS.
Graph cuts by using local texture features of wavelet coefficient for image segmentation

This paper proposes an approach to image segmentation using iterated graph cuts based on local texture features of wavelet coefficient. Using multiresolution analysis based on Haar wavelet, low-frequency range (smoothed image) is used for n-link and high-frequency range (local texture features) is used for t-link along with color histogram. The proposed method can segment the object region with noisy edges and colors similar to the background, but heavy texture change. Experimental results illustrate the validity of our method.
Mediating between modeled and observed behavior: The quest for the “right” process: Keynote

Operational processes leave trails in the information systems supporting them. Such event data are the starting point for process mining - an emerging scientific discipline relating modeled and observed behavior. Whereas an event log describes example behavior of the underlying process, a process model aims to describe an abstraction of the same process. Models may be descriptive or normative. Descriptive models aim to describe the underlying process and are used for discussion, performance analysis, obtaining insights, and prediction. Normative models describe the desired behavior and are used for workflow management, system configuration, auditing, compliance management, and conformance checking. Differences between modeled and observed behavior may point to undesirable deviations or inadequate models. In this paper, we discuss challenges related to finding the “right” process, i.e., the process model that describes the real underlying process or a process that behaves as desired.
Director Field Model of the Primary Visual Cortex for Contour Detection

We aim to build the simplest possible model capable of detecting long, noisy contours in a cluttered visual scene. For this, we model the neural dynamics in the primate primary visual cortex in terms of a continuous director field that describes the average rate and the average orientational preference of active neurons at a particular point in the cortex. We then use a linear-nonlinear dynamical model with long range connectivity patterns to enforce long-range statistical context present in the analyzed images. The resulting model has substantially fewer degrees of freedom than traditional models, and yet it can distinguish large contiguous objects from the background clutter by suppressing the clutter and by filling-in occluded elements of object contours. This results in high-precision, high-recall detection of large objects in cluttered scenes. Parenthetically, our model has a direct correspondence with the Landau - de Gennes theory of nematic liquid crystal in two dimensions.
Analysis of boost dc-dc converters with integrated coupled inductors

An analytical model of a fully-integrated boost dc-dc converter with coupled on-chip spiral inductors is proposed. The model, which takes the inductor parasitic elements into consideration, shows that the efficiency of the conventional boost converter is very similar to the efficiency of the coupled-inductor boost converter. However, the coupled-inductor converter has a lower input-current ripple, which is critical to meet EMI requirements. The simulations for a 65-nm CMOS process show an input-current ripple reduction of 24.5%. The simulation results also demonstrate the accuracy of the proposed model and shows a maximum error within 2%.
The Effects of an Orientation Seminar on Non-Traditional Female Students Initiating College Studies.

This study focused on the adjustments nontraditional female students who return to college must make in order to complete their studies. The study examined the influence of a 3-hour orientation program for such students to see of the seminar would increase the coping skills and decrease the anxiety levels of nontraditional female students, most of whom had been away from academic settings for some time. Eleven female nontraditional students were asked to participate in the orientation class. Control groups were 22 participants with no orientation seminar and 25 students who had been enrolled in a 10-week orientation seminar offered the prior year. Participants completed a measure of state-trait anxiety and a coping resources inventory. Participants in the three groups did not show significant differences in coping skills, and state anxiety levels did not differ significantly. Results do suggest that the anxiety-reducing skills taught in the two seminars did help participants deal better with long term stress than those who received no orientation. Five appendixes contain forms used in the study and supplemental information. (Contains 9 tables and 91 references.) (SLD) Reproductions supplied by EDRS are the best that can be made from the original document.
Prediction of p38 map kinase inhibitory activity of 3, 4-dihydropyrido [3, 2-d] pyrimidone derivatives using an expert system based on principal component analysis and least square support vector machine

A quantitative structure–activity relationship (QSAR) study is suggested for the prediction of biological activity (pIC50) of 3, 4-dihydropyrido [3,2-d] pyrimidone derivatives as p38 inhibitors. Modeling of the biological activities of compounds of interest as a function of molecular structures was established by means of principal component analysis (PCA) and least square support vector machine (LS-SVM) methods. The results showed that the pIC50 values calculated by LS-SVM are in good agreement with the experimental data, and the performance of the LS-SVM regression model is superior to the PCA-based model. The developed LS-SVM model was applied for the prediction of the biological activities of pyrimidone derivatives, which were not in the modeling procedure. The resulted model showed high prediction ability with root mean square error of prediction of 0.460 for LS-SVM. The study provided a novel and effective approach for predicting biological activities of 3, 4-dihydropyrido [3,2-d] pyrimidone derivatives as p38 inhibitors and disclosed that LS-SVM can be used as a powerful chemometrics tool for QSAR studies.
antiSMASH: rapid identification, annotation and analysis of secondary metabolite biosynthesis gene clusters in bacterial and fungal genome sequences

Bacterial and fungal secondary metabolism is a rich source of novel bioactive compounds with potential pharmaceutical applications as antibiotics, anti-tumor drugs or cholesterol-lowering drugs. To find new drug candidates, microbiologists are increasingly relying on sequencing genomes of a wide variety of microbes. However, rapidly and reliably pinpointing all the potential gene clusters for secondary metabolites in dozens of newly sequenced genomes has been extremely challenging, due to their biochemical heterogeneity, the presence of unknown enzymes and the dispersed nature of the necessary specialized bioinformatics tools and resources. Here, we present antiSMASH (antibiotics & Secondary Metabolite Analysis Shell), the first comprehensive pipeline capable of identifying biosynthetic loci covering the whole range of known secondary metabolite compound classes (polyketides, non-ribosomal peptides, terpenes, aminoglycosides, aminocoumarins, indolocarbazoles, lantibiotics, bacteriocins, nucleosides, beta-lactams, butyrolactones, siderophores, melanins and others). It aligns the identified regions at the gene cluster level to their nearest relatives from a database containing all other known gene clusters, and integrates or cross-links all previously available secondary-metabolite specific gene analysis methods in one interactive view. antiSMASH is available at http://antismash.secondarymetabolites. org.
Da0324, an inhibitor of nuclear factor-κB activation, demonstrates selective antitumor activity on human gastric cancer cells

Background The transcription factor nuclear factor-κB (NF-κB) is constitutively activated in a variety of human cancers, including gastric cancer. NF-κB inhibitors that selectively kill cancer cells are urgently needed for cancer treatment. Curcumin is a potent inhibitor of NF-κB activation. Unfortunately, the therapeutic potential of curcumin is limited by its relatively low potency and poor cellular bioavailability. In this study, we presented a novel NF-κB inhibitor named Da0324, a synthetic asymmetric mono-carbonyl analog of curcumin. The purpose of this study is to research the expression of NF-κB in gastric cancer and the antitumor activity and mechanism of Da0324 on human gastric cancer cells. Methods The expressions between gastric cancer tissues/cells and normal gastric tissues/cells of NF-κB were evaluated by Western blot. The inhibition viability of compounds on human gastric cancer cell lines SGC-7901, BGC-823, MGC-803, and normal gastric mucosa epithelial cell line GES-1 was assessed with the 3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyltetrazolium bromide assay. Absorption spectrum method and high-performance liquid chromatography method detected the stability of the compound in vitro. The compound-induced changes of inducible NF-κB activation in the SGC-7901 and BGC-823 cells were examined by Western blot analysis and immunofluorescence methods. The antitumor activity of compound was performed by clonogenic assay, matrigel invasion assay, flow cytometric analysis, Western blot analysis, and Hoechst 33258 staining assay. Results High levels of p65 were found in gastric cancer tissues and cells. Da0324 displayed higher growth inhibition against several types of gastric cancer cell lines and showed relatively low toxicity to GES-1. Moreover, Da0324 was more stable than curcumin in vitro. Western blot analysis and immunofluorescence methods showed that Da0324 blocked NF-κB activation. In addition, Da0324 significantly inhibited tumor proliferation and invasion, arrested the cell cycle, and induced apoptosis in vitro. Conclusion The asymmetric mono-carbonyl analog of curcumin Da0324 exhibited significantly improved antigastric cancer activity. Da0324 may be a promising NF-κB inhibitor for the selective targeting of cancer cells. However, further studies are needed in animals to validate these findings for the therapeutic use of Da0324.
Everything SAXS: small-angle scattering pattern collection and correction

For obtaining reliable nanostructural details of large amounts of sample—and if it is applicable—small-angle scattering (SAS) is a prime technique to use. It promises to obtain bulk-scale, statistically sound information on the morphological details of the nanostructure, and has thus led to many a researcher investing their time in it over the last eight decades of development. Due to pressure from scientists requesting more details on increasingly complex nanostructures, as well as the ever improving instrumentation leaving less margin for ambiguity, small-angle scattering methodologies have been evolving at a high pace over the past few decades. As the quality of any results can only be as good as the data that go into these methodologies, the improvements in data collection and all imaginable data correction steps are reviewed here. This work is intended to provide a comprehensive overview of all data corrections, to aid the small-angle scatterer to decide which are relevant for their measurement and how these corrections are performed. Clear mathematical descriptions of the corrections are provided where feasible. Furthermore, as no quality data exist without a decent estimate of their precision, the error estimation and propagation through all these steps are provided alongside the corrections. With these data corrections, the collected small-angle scattering pattern can be made of the highest standard, allowing for authoritative nanostructural characterization through its analysis. A brief background of small-angle scattering, the instrumentation developments over the years, and pitfalls that may be encountered upon data interpretation are provided as well.
EXPANDING UNDERSTANDING OF PUBLIC POLICY AS A COMPLEX AND PLURI-DISCIPLINARY SYSTEM: ILLUSTRATING POSSIBILITIES OF EPISTEMIC PLURALISM

ix Expanding Understanding and Illustrating Possibilities . 1 Rationale . 3 Definition of Terms . 7 Research Overview . 12 Plan of the Dissertation . 17 Conceptual/Textual Underpinnings . 19 About Philosophical Investigations . 19 Nodes of Understanding . 22 Study Categories . 26 What is Epistemic Pluralism and why does it Matter? 33 Applications to Electronic Governmentality . 35 Methodology – An Interpretivist Approach . 37 Gadamer and the Hermeneutic Circle . 37 Research Design: A Modified Hermeneutic Circle . 39 Analytic Strategy . 44 Validity . 49 Justification . 49 Limitations of Approach . 50 Analytical Results: The Narrative of the Conscious . 51 Analytical Results of Stage 1 . 52 Analytical Results of Stage 2 . 67 Analytical Results of Stage 3 . 69 Analytical Results of Stage 4 . 80
Asynchronous gossip

We study the complexity of gossip in an asynchronous, message-passing fault-prone distributed system. We show that an adaptive adversary can significantly hamper the spreading of a rumor, while an oblivious adversary cannot. The algorithmic techniques proposed in this article can be used for improving the message complexity of distributed algorithms that rely on an all-to-all message exchange paradigm and are designed for an asynchronous environment. As an example, we show how to improve the message complexity of asynchronous randomized consensus.
Monocyte-Derived Dendritic Cells Exhibit Increased Levels of Lysosomal Proteolysis as Compared to Other Human Dendritic Cell Populations

Background Fine control of lysosomal degradation for limited processing of internalized antigens is a hallmark of professional antigen presenting cells. Previous work in mice has shown that dendritic cells (DCs) contain lysosomes with remarkably low protease content. Combined with the ability to modulate lysosomal pH during phagocytosis and maturation, murine DCs enhance their production of class II MHC-peptide complexes for presentation to T cells. Methodology/Principal Findings In this study we extend these findings to human DCs and distinguish between different subsets of DCs based on their ability to preserve internalized antigen. Whereas DCs derived in vitro from CD34+ hematopoietic progenitor cells or isolated from peripheral blood of healthy donors are protease poor, DCs derived in vitro from monocytes (MDDCs) are more similar to macrophages (MΦs) in protease content. Unlike other DCs, MDDCs also fail to reduce their intralysosomal pH in response to maturation stimuli. Indeed, functional characterization of lysosomal proteolysis indicates that MDDCs are comparable to MΦs in the rapid degradation of antigen while other human DC subtypes are attenuated in this capacity. Conclusions/Significance Human DCs are comparable to murine DCs in exhibiting a markedly reduced level of lysosomal proteolysis. However, as an important exception to this, human MDDCs stand apart from all other DCs by a heightened capacity for proteolysis that resembles that of MΦs. Thus, caution should be exercised when using human MDDCs as a model for DC function and cell biology.
Heterogeneous Three-Dimensional Electronics by Use of Printed Semiconductor Nanomaterials

We developed a simple approach to combine broad classes of dissimilar materials into heterogeneously integrated electronic systems with two- or three-dimensional layouts. The process begins with the synthesis of different semiconductor nanomaterials, such as single-walled carbon nanotubes and single-crystal micro- and nanoscale wires and ribbons of gallium nitride, silicon, and gallium arsenide on separate substrates. Repeated application of an additive, transfer printing process that uses soft stamps with these substrates as donors, followed by device and interconnect formation, yields high-performance heterogeneously integrated electronics that incorporate any combination of semiconductor nanomaterials on rigid or flexible device substrates. This versatile methodology can produce a wide range of unusual electronic systems that would be impossible to achieve with other techniques.