Miracle-dz/UniFAR-FTUs huggingface dataset:
Mapping the affinity landscape of Thrombin-binding aptamers on 2΄F-ANA/DNA chimeric G-Quadruplex microarrays

Abstract In situ fabricated nucleic acids microarrays are versatile and very high-throughput platforms for aptamer optimization and discovery, but the chemical space that can be probed against a given target has largely been confined to DNA, while RNA and non-natural nucleic acid microarrays are still an essentially uncharted territory. 2΄-Fluoroarabinonucleic acid (2΄F-ANA) is a prime candidate for such use in microarrays. Indeed, 2΄F-ANA chemistry is readily amenable to photolithographic microarray synthesis and its potential in high affinity aptamers has been recently discovered. We thus synthesized the first microarrays containing 2΄F-ANA and 2΄F-ANA/DNA chimeric sequences to fully map the binding affinity landscape of the TBA1 thrombin-binding G-quadruplex aptamer containing all 32 768 possible DNA-to-2΄F-ANA mutations. The resulting microarray was screened against thrombin to identify a series of promising 2΄F-ANA-modified aptamer candidates with Kds significantly lower than that of the unmodified control and which were found to adopt highly stable, antiparallel-folded G-quadruplex structures. The solution structure of the TBA1 aptamer modified with 2΄F-ANA at position T3 shows that fluorine substitution preorganizes the dinucleotide loop into the proper conformation for interaction with thrombin. Overall, our work strengthens the potential of 2΄F-ANA in aptamer research and further expands non-genomic applications of nucleic acids microarrays.
On the Verification of High-Order Constraint Compliance in IC Design

The increasing quality requirements on safety-critical electronic components and the rapid technological progress necessitate the compliance with all specified functional and non-functional design constraints. This paper introduces a novel verification method based on an unified data representation of constraints to enable multi-tool verification tasks. A constraint engineering system is presented which provides flexible, extensible, and multi-tool definitions of complex constraints and high-order verification tasks. Existing verification and simulation tools are combined so that the achieved complexity level of the high-order verification by far exceeds the level of the single tools. The shown examples target practical applications in analog system design and demonstrate the flexibility and the potential of this new verification approach.
Correlations between Income Inequality and Antimicrobial Resistance

Objectives The aim of this study is to investigate if correlations exist between income inequality and antimicrobial resistance. This study’s hypothesis is that income inequality at the national level is positively correlated with antimicrobial resistance within developed countries. Data collection and analysis Income inequality data were obtained from the Standardized World Income Inequality Database. Antimicrobial resistance data were obtained from the European antimicrobial Resistance Surveillance Network and outpatient antimicrobial consumption data, measured by Defined daily Doses per 1000 inhabitants per day, from the European Surveillance of antimicrobial Consumption group. Spearman’s correlation coefficient (r) defined strengths of correlations of: > 0.8 as strong, > 0.5 as moderate and > 0.2 as weak. Confidence intervals and p values were defined for all r values. Correlations were calculated for the time period 2003-10, for 15 European countries. Results Income inequality and antimicrobial resistance correlations which were moderate or strong, with 95% confidence intervals > 0, included the following. Enterococcus faecalis resistance to aminopenicillins, vancomycin and high level gentamicin was moderately associated with income inequality (r= ≥0.54 for all three antimicrobials). Escherichia coli resistance to aminoglycosides, aminopenicillins, third generation cephalosporins and fluoroquinolones was moderately-strongly associated with income inequality (r= ≥0.7 for all four antimicrobials). Klebsiella pneumoniae resistance to third generation cephalosporins, aminoglycosides and fluoroquinolones was moderately associated with income inequality (r= ≥0.5 for all three antimicrobials). Staphylococcus aureus methicillin resistance and income inequality were strongly associated (r=0.87). Conclusion As income inequality increases in European countries so do the rates of antimicrobial resistance for bacteria including E. faecalis, E. coli, K. pneumoniae and S. aureus. Further studies are needed to confirm these findings outside Europe and investigate the processes that could causally link income inequality and antimicrobial resistance.
A Deformation Theory of Self-Dual Einstein Spaces

The self-dual Einstein equations on a compact Riemannian 4-manifold can be expressed as a quadratic condition on the curvature of an $SU(2)$ (spin) connection which is a covariant generalization of the self-dual Yang-Mills equations. Local properties of the moduli space of self-dual Einstein connections are described in the context of an elliptic complex which arises in the linearization of the quadratic equations on the $SU(2)$ curvature. In particular, it is shown that the moduli space is discrete when the cosmological constant is positive; when the cosmological constant is negative the moduli space can be a manifold the dimension of which is controlled by the Atiyah-Singer index theorem.
Prolonged Attenuation of Amygdala-Kindled Seizure Measures in Rats by Convection-Enhanced Delivery of the N-Type Calcium Channel Antagonists ω-Conotoxin GVIA and ω-Conotoxin MVIIA

Convection-enhanced delivery (CED) permits the homogeneous distribution of therapeutic agents throughout localized regions of the brain parenchyma without causing tissue damage as occurs with bolus injection. Here, we examined whether CED infusion of the N-type calcium channel antagonists ω-conotoxin GVIA (ω-CTX-G) and ω-conotoxin MVIIA (ω-CTX-M) can attenuate kindling measures in fully amygdala-kindled rats. Rats were implanted with a combination infusion cannula-stimulating electrode assembly into the right basolateral amygdala. Fully kindled animals received infusions of vehicle, ω-CTX-G (0.005, 0.05, and 0.5 nmol), ω-CTX-M (0.05, 0.15, and 0.5 nmol), proteolytically inactivated ω-CTX-M (0.5 nmol), or carbamazepine (500 nmol) into the stimulation site. CED of ω-CTX-G and ω-CTX-M over a 20-min period resulted in a dose-dependent increase in the afterdischarge threshold and a decrease in the afterdischarge duration and behavioral seizure score and duration during a period of 20 min to 1 week after the infusion, indicating an inhibitory effect on the triggering and expression of kindled seizures. The protective effects of ω-conotoxins reached a maximum at 48 h postinfusion, and then they gradually resolved over the next 5 days. In contrast, carbamazepine was active at 20 min but not at 24 h after the infusion, whereas CED of vehicle or inactivated ω-CTX-M had no effect. Except for transient tremor in some rats receiving the highest toxin doses, no adverse effects were observed. These results indicate that local CED of high-molecular-weight presynaptic N-type calcium channel blockers can produce long-lasting inhibition of brain excitability and that they may provide prolonged seizure protection in focal seizure disorders.
PERFECT HYPERMOMENTUM FLUID: VARIATIONAL THEORY AND EQUATIONS OF MOTION

The variational theory of the perfect hypermomentum fluid is developed. The new type of the generalized Frenkel condition is considered. The Lagrangian density of such fluid is stated, and the equations of motion of the fluid and the Weyssenhoff-type evolution equation of the hypermomentum tensor are derived. The expressions of the matter currents of the fluid (the canonical energy–momentum three-form, the metric stress–energy four-form and the hypermomentum three-form) are obtained. The Euler-type hydrodynamic equation of motion of the perfect hypermomentum fluid is derived. It is proved that the motion of the perfect fluid without hypermomentum in a metric-affine space coincides with the motion of this fluid in a Riemann space.
Enabling Folksonomies for Knowledge Extraction: A Semantic Grounding Approach

Folksonomies emerge as the result of the free tagging activity of a large number of users over a variety of resources. They can be considered as valuable sources from which it is possible to obtain emerging vocabularies that can be leveraged in knowledge extraction tasks. However, when it comes to understanding the meaning of tags in folksonomies, several problems mainly related to the appearance of synonymous and ambiguous tags arise, specifically in the context of multilinguality. The authors aim to turn folksonomies into knowledge structures where tag meanings are identified, and relations between them are asserted. For such purpose, they use DBpedia as a general knowledge base from which they leverage its multilingual capabilities.
Second order refinements for the classical capacity of quantum channels with separable input states

We study the non-asymptotic fundamental limits for transmitting classical information over memoryless quantum channels, i.e. we investigate the amount of information that can be transmitted when the channel is used a finite number of times and a finite average decoding error is permissible. We show that, if we restrict the encoder to use ensembles of separable states, the non-asymptotic fundamental limit admits a Gaussian approximation that illustrates the speed at which the rate of optimal codes converges to the Holevo capacity as the number of channel uses tends to infinity. To do so, several important properties of quantum information quantities, such as the capacity-achieving output state, the divergence radius, and the channel dispersion, are generalized from their classical counterparts. Further, we exploit a close relation between classical-quantum channel coding and quantum binary hypothesis testing and rely on recent progress in the non-asymptotic characterization of quantum hypothesis testing and its Gaussian approximation.
Untimed-C based SoC Architecture Design Space Exploration for 3G and Beyond Wireless Systems

In this paper, we propose an un-timed C/C++ level verification methodology that integrates key technologies for truly high-level VLSI modelling to keep pace with the explosive complexity of SoC designs in the 3G and beyond wireless communications. A Catapult C/C++ based architecture scheduler transfers the major workload to the algorithmic C/C++ fixed-point design. Case study is given to explore the VLSI design space extensively for various types of computational intensive algorithms in MIMO-CDMA systems, such as a MIMO equalizer to avoid the Direct-Matrix-Inverse. Extensive time/area tradeoff study is enabled with different architecture and resource constraints in a short design cycle. Architecture efficiency and productivity are improved significantly, enabling truly rapid prototyping for the 3G and beyond wireless systems.
TGF-β Negatively Regulates CXCL1 Chemokine Expression in Mammary Fibroblasts through Enhancement of Smad2/3 and Suppression of HGF/c-Met Signaling Mechanisms

Fibroblasts are major cellular components of the breast cancer stroma, and influence the growth, survival and invasion of epithelial cells. Compared to normal tissue fibroblasts, carcinoma associated fibroblasts (CAFs) show increased expression of numerous soluble factors including growth factors and cytokines. However, the mechanisms regulating expression of these factors remain poorly understood. Recent studies have shown that breast CAFs overexpress the chemokine CXCL1, a key regulator of tumor invasion and chemo-resistance. Increased expression of CXCL1 in CAFs correlated with poor patient prognosis, and was associated with decreased expression of TGF-β signaling components. The goal of these studies was to understand the role of TGF-β in regulating CXCL1 expression in CAFs, using cell culture and biochemical approaches. We found that TGF-β treatment decreased CXCL1 expression in CAFs, through Smad2/3 dependent mechanisms. Chromatin immunoprecipitation and site-directed mutagenesis assays revealed two new binding sites in the CXCL1 promoter important for Smad2/3 modulation of CXCL1 expression. Smad2/3 proteins also negatively regulated expression of Hepatocyte Growth Factor (HGF), which was found to positively regulate CXCL1 expression in CAFs through c-Met receptor dependent mechanisms. HGF/c-Met signaling in CAFs was required for activity of NF-κB, a transcriptional activator of CXCL1 expression. These studies indicate that TGF-β negatively regulates CXCL1 expression in CAFs through Smad2/3 binding to the promoter, and through suppression of HGF/c-Met autocrine signaling. These studies reveal novel insight into how TGF-β and HGF, key tumor promoting factors modulate CXCL1 chemokine expression in CAFs.
Image-assisted modeling from sketches

In this paper, we propose a method for creating freeform surfaces from sketch-annotated images. Beginning from an image, the user sketches object boundaries, features, and holes. Sketching is made easier by a magnetic pen that follows strong edges in the image. To create a surface from the sketch, a planar mesh is constructed such that its geometry aligns with the boundary and interior features. We then inflate to 3D using a discrete distance transform filtered through a cross-sectional mapping function. Finally, the input image is applied as a texture to the surface. The benefits of our framework are demonstrated with examples in modeling both freeform and manufactured objects.
PREDATOR EFFECTS ON AN ASSEMBLAGE OF CONSUMERS THROUGH INDUCED CHANGES IN CONSUMER FORAGING BEHAVIOR

This investigation examines how a predator-induced reduction in activity of a prey species (a “nonlethal” predator effect) affects the growth rate of the prey and, indirectly, the growth rate of competitors of the prey. We further determine how the magnitudes of these effects depend on density of the prey species. We develop a foraging model that predicts a predator will reduce the growth of a focal prey species at low prey density but have little effect at high prey density. The model also predicts that presence of the predator will indirectly facilitate growth of a competitor of the focal species, and that this effect will be negligible at low, and maximal at high, focal species density. Thus it is precisely where the effect of the predator on the growth of the focal species is minimum that the indirect effect on the competitor is maximum. We tested these predictions using a system of three species/size classes of anuran larvae and a larval odonate predator (Anax longipes) in cattle watering tanks. By c.
Feeling the Future Again: Retroactive Avoidance of Negative Stimuli

During the past decades, several theories have been proposed that relate quantum mechanics to information processing in the human mind. These theories predict that the arrow of time has no direction during unconscious processing states. Across 7 experiments, we tested whether masked negative stimuli presented in the future lead to an unconscious avoidance reaction in the presence. Response registration took place about 500 milliseconds before stimulus onset. In the majority of the studies, the predicted retroactive influence was found. On average, participants were able to unconsciously avoid negative future outcomes (mean ES = 0.07; Combined Bayes factor = 293). These results are in line with similar precognitive avoidance effects recently reported by Daryl Bem in 2011 (Experiment 2). The reported findings are discussed with regard to the proposed quantum model of the mind. We also highlight the limitations of our research.
An improved Content Based Image Retrieval using three region colour and straight line signatures of the image

In this work, we have performed Content Based Image Retrieval using combined colour histograms for three regions (top, bottom and middle) of the image. This will indirectly include the space information within it along with the colour information. Besides this, retrieval of images from the image database according to the user query image are done using straight line signatures of the images. The average precision is used as a metric to evaluate the performance of the system. Experiments were successfully implemented on 1000 images of Semantics Sensitive Integrated Matching for Picture Libraries using MAT Lab. The performance of our method is compared with four other previous methods such as Integrated Region Matching, Fuzzy Integrated Region Matching , CBIR using colour salient points and shape features and Interactive CBIR using Ripplet Transform and Fuzzy Relevance Feedback Mechanism which used the same data set and evaluation method. According to the arrived results, the performance of the proposed combined three region colour and straight line signatures based CBIR systems were significantly better than other compared methods.
KDRuleEx: A Novel Approach for Enhancing User Comprehensibility Using Rule Extraction

Knowledge representation opaque model like ANN has advantage of accuracy and limitation of interpretability. Transparent models like decision tree, decision table and rules represent knowledge in more understandable form and can easily be integrated with other learning system. Converting an opaque model like ANN to transparent model is called rule extraction. Lot of work has been done in the field of rule extraction like "SVM to Rules", "ANN to Decision Tree", "ANN to Rules" etc. We did not find any direct approach of converting ANN to decision table in our literature survey. In this paper, we proposed a novel pedagogical rule extraction technique to generate a decision table using training example set and a trained artificial neural network on it. The proposed algorithm can be used with both discrete as well as continuous input. The proposed algorithm has advantage in terms of computational performance and memory management.
Applying fuzzy neural network in human resource selection system

It is widely believed that the role of managers is becoming a key determinant for enterprises' competitiveness in today's knowledge economy era. Owing to fast development of information technologies (ITs), corporations are employed to enhance the capability of human resource management, which is called human resource information system (HRIS). Recently, due to promising results of artificial neural networks (ANNs) and fuzzy theory in engineering, they have also become candidates for HRIS. The artificial intelligence (AT) field can play a role in this, especially, in assuring that the fuzzy neural network has the characteristics and functions of training, learning, and simulation to make an optimal and accurate judgment according to the human thinking model. The main purposes of the study are to discuss the appointment of managers in enterprises through fuzzy neural network, to construct a new model for evaluation of managerial talent, and accordingly to develop a decision support system in human resource selection. Therefore, the research methods of reviewing literature, in-depth interview, questionnaire survey, and fuzzy neural network are used in the study. The fuzzy neural network is used to train the concrete database, based on 191 questionnaires from experts, for getting the best network model in different training conditions. In order to let decision-makers adjust weighted values and obtain decisive results of each phase's scores, we adopted the simple additive weighting (SAW) and fuzzy analytic hierarchy process (FAHP) methods in the study. Finally, the human resource selection system of Java user interface has been constructed by FNN in the study.
Acute Myocardial Infarction Inhibits the Neurogenic Tachycardic and Vasopressor Response in Rats via Presynaptic Cannabinoid Type 1 Receptor

The present study was carried out to examine whether acute experimental myocardial infarction affects the sympathetic transmission to vessels and the heart of pithed rats via a presynaptic mechanism and, if so, to check whether inhibitory presynaptic cannabinoid (CB) receptors and endocannabinoids are involved in this response. In pithed and vagotomized rats, electrical stimulation (0.75 Hz; 1 ms; 50 V; 5 or 15 pulses for increases in heart rate or blood pressure, respectively) of the preganglionic sympathetic nerve fibers or intravenous injection of isoprenaline (0.1 nmol/kg) or noradrenaline (1 nmol/kg) increased heart rate and blood pressure by approximately 50 beats/min and 40 mm Hg, respectively. Ligation of the left coronary artery reduced the electrically (as opposed to the chemically) induced tachycardic and pressor responses by approximately 30 to 40%. The inhibitory effect of myocardial infarction was prevented by the CB1 receptor antagonist rimonabant but not by the CB2 receptor antagonist N-[(1S)-endo-1,3,3-trimethyl-bicyclo[2.2. 1]heptan-2-yl]-5-(4-chloro-3-methylphenyl)-1-(4-methylbenzyl)-pyra-zole-3-carboxamide (SR144528) and the transient receptor potential vanilloid 1 receptor antagonist capsazepine. The inhibitory effect of myocardial infarction was slightly enhanced by the inhibitors of anandamide and 2-arachidonyl glycerol degradation, 3′-(aminocarbonyl)[1,1′-biphenyl]-3-yl)-cyclohexylcarbamate (URB597) and 4-nitrophenyl-4-(dibenzo[d][1,3]dioxol-5-yl(hydroxy)methyl)piperidine-1-carboxylate (JZL184), respectively. Rimonabant increased myocardial infarction-induced mortality. Our results demonstrate that during the early phase of myocardial infarction the activation of presynaptic CB1 receptors by endogenously formed cannabinoids contributes to the inhibition of the neurogenic tachycardic and vasopressor responses. Thus, the CB1 receptor-mediated inhibition of excessive noradrenaline release from the sympathetic nerve fibers innervating the heart and vessels might play a protective role in myocardial ischemia.
Positron Emission Tomography Norepinephrine Reuptake and Postsynaptic ß-Adrenergic Receptor Density With Ventricular Cardiomyopathy : Quantitative Assessment of Presynaptic Abnormalities of Cardiac Sympathetic Innervation in Arrhythmogenic

Hartmut Lerch, Adriaan A. Lammertsma, Flemming Hermansen, Otmar Schober, Thomas Wichter, Michael Schäfers, Christopher G. Rhodes, Martin Borggrefe, Positron Emission Tomography Norepinephrine Reuptake and Postsynaptic ß-Adrenergic Receptor Density With Ventricular Cardiomyopathy : Quantitative Assessment of Presynaptic Abnormalities of Cardiac Sympathetic Innervation in Arrhythmogenic Right ISSN: 1524-4539 Copyright © 2000 American Heart Association. All rights reserved. Print ISSN: 0009-7322. Online 72514 Circulation is published by the American Heart Association. 7272 Greenville Avenue, Dallas, TX 2000, 101:1552-1558 Circulation http://circ.ahajournals. org/content/101/13/1552 located on the World Wide Web at: The online version of this article, along with updated information and services, is
Monetary Policy and the Distribution of Income: Evidence for the United States and the United Kingdom

The shift in the emphasis of macroeconomic policy during the late 1970s and early 1980s toward combating inflation rather than maintaining full employment and the associated tight monetary policies fostered by the majority of the advanced industrialized countries, caused interest rates to increase to unprecedented heights. Income distribution and unemployment are among the economic variables that may have been mostly affected by the new, restrictive menu of macroeconomic policy. Yet, little attention has been paid to the potentially profound effects of monetary policy and high interest rates on the functional distribution of income. 1 In this paper we set out to illuminate the issues surrounding the effects of monetary policy on changes in the income shares of industrial capital, financial capital, and labor in the nonfinancial corporate sector, in the United States and the United Kingdom? The second section develops a post-Keynesian-Kaleckian perspective of income distribution and a mechanism to show the way in which monetary policy might affect the distribution of income between the three aforementioned income groups.