Miracle-dz/UniFAR-FTUs huggingface dataset:
Norges Teknisk-naturvitenskapelige Universitet Efficient Quadrature of Highly Oscillatory Integrals Using Derivatives Efficient Quadrature of Highly Oscillatory Integrals Using Derivatives

In this paper we explore quadrature methods for highly oscillatory integrals. Generalizing the method of stationary phase, we expand such integrals into asymptotic series in inverse powers of the frequency. The outcome are two families of methods , one based on a truncation of the asymptotic series and the other extending an approach implicit in the work of Filon. Both kinds of methods approximate the integral as a linear combination of function values and derivatives, with coefficients that may depend on frequency. We determine asymptotic properties of these methods, proving that, perhaps counterintuitively, their performance drastically improves as frequency grows. The paper is accompanied by numerical results that demonstrate the potential of this set of ideas.
Effect of the low- versus high-intensity exercise training on endoplasmic reticulum stress and GLP-1 in adolescents with type 2 diabetes mellitus

[Purpose] The primary objective of this study was to investigate the effect of low-intensity exercise training compare with high-intensity exercise training on endoplasmic reticulum stress and glucagon-like peptide-1 in adolescents with type 2 diabetes mellitus. [Subjects and Methods] The low-intensity exercise training group performed aerobic exercise training at an intensity of ≤ 45% of the heart rate reserve. The high-intensity interval exercise training group performed interval exercise training at an intensity of ≥ 80% of the heart rate reserve. The exercise-related energy consumption was determined for both groups on a per-week basis (1,200 kcal/week). [Results] Both groups showed improvement in the glucose-regulated protein 78 and dipeptidyl peptidase-4, but the size of the between-group effect was not statistically significant. The high-intensity interval exercise training group showed a significant reduction in percentage body fat. The C-peptide level increased after the 12-weeks programs and was significantly different, between the groups. Fasting glucose, insulin resistance in the fasting state according to homeostasis model assessment, and leptin decreased after the 12-weeks exercise program and were significantly different between the groups, and glucagon-like peptide-1 increased after the 12-week exercise programs and was significantly different between the groups. [Conclusion] In conclusion high-intensity interval exercise training, as defined in this study, may lead to improvements in body composition, glycemic control, endoplasmic reticulum stress, and the glucagon-like peptide-1 in adolescents with type 2 diabetes mellitus.
CHAOS, FRACTALS AND QUANTUM POINCARÉ RECURRENCES IN DIAMAGNETIC KEPLER PROBLEM

The statistics of quantum Poincare recurrences in Hilbert space for diamagnetic hydrogen atom in strong magnetic field has been investigated. It has been shown that quantities characterizing classical chaos are in good agreement with the ones that are used to describe quantum chaos. The equality of classical and quantum Poincare recurrences has been shown. It has been proved that one of the signs of the emergence of quantum chaos is the irreversible transition from a pure quantum mechanical state to a mixed one.
Neural Tuning to Numerosity Relates to Perceptual Tuning in 3–6-Year-Old Children

Neural representations of approximate numerical value, or numerosity, have been observed in the intraparietal sulcus (IPS) in monkeys and humans, including children. Using functional magnetic resonance imaging, we show that children as young as 3–4 years old exhibit neural tuning to cardinal numerosities in the IPS and that their neural responses are accounted for by a model of numerosity coding that has been used to explain neural responses in the adult IPS. We also found that the sensitivity of children's neural tuning to number in the right IPS was comparable to their numerical discrimination sensitivity observed behaviorally, outside of the scanner. Children's neural tuning curves in the right IPS were significantly sharper than in the left IPS, indicating that numerical representations are more precise and mature more rapidly in the right hemisphere than in the left. Further, we show that children's perceptual sensitivity to numerosity can be predicted by the development of their neural sensitivity to numerosity. This research provides novel evidence of developmental continuity in the neural code underlying numerical representation and demonstrates that children's neural sensitivity to numerosity is related to their cognitive development. SIGNIFICANCE STATEMENT Here we test for the existence of neural tuning to numerosity in the developing brain in the youngest sample of children tested with fMRI to date. Although previous research shows evidence of numerical distance effects in the intraparietal sulcus of the developing brain, those effects could be explained by patterns of neural activity that do not represent neural tuning to numerosity. These data provide the first robust evidence that from as early as 3–4 years of age there is developmental continuity in how the intraparietal sulcus represents the values of numerosities. Moreover, the study goes beyond previous research by examining the relation between neural tuning and perceptual tuning in children.
Cerebral blood flow changes in Parkinson?s disease associated with dementia.

Dementia is one of the main non-motor symptoms of Parkinson's disease (PD) and it is diagnosed in about 30% of cases. Its aetiology remains unclear and contributing factors are controversial. Dementia may be more common in old patients with severe motor symptoms and mild cognitive impairment. Clinico-pathological studies show the association between dementia in PD and the age-related group of dementias, such as AD and VaD. A valuable aid in the assessment of dementia in PD is cerebral blood flow (CBF) brain SPECT scanning. It shows three different patterns of rCBF reduction, including frontal lobe hypoperfusion, Alzheimer-like type of hypoperfusion and multiple, vascular defects. The heterogeneity of rCBF reduction may reflect the multifactorial pathophysiology of dementia in PD. It may result from concomitant AD pathology, cerebrovascular disease, destruction of nigro-striato-frontal projection or may be a distinct disease of different aetiology.
Thrombin and other potential mechanisms underlying restenosis.

P ercutaneous transluminal coronary angioplasty (PTCA) has become important in the management of coronary artery disease; however, proliferative restenosis in 25-35% of the patients undergoing PTCA limits its usefulness. The pathogenesis of the postangioplasty restenosis lesion has not been defined. Morphologically, the lesion largely comprises smooth muscle cells (SMCs) and develops in the first 3 to 6 months after balloon angioplasty. Little is known about the time course of cell proliferation in the human lesion, including where cell proliferation begins or why proliferation stops in some people but continues in others. Some degree of smooth muscle proliferation is a likely part of the healing process after injury; however, it is unclear why some individuals develop clinically significant lesions. Morphological observations, assembled from human vessels after balloon catheterization, have been primarily descriptive with few insights into the causes or the time course of the development of the postangioplasty restenosis lesion. However, one common finding of these studies has been the presence of intimal or medial tears with concomitant thrombus formation on the injured surface.1-4
Fast capsule image segmentation based on linear region growing

In computer vision based on-line capsule inspection, as defects contrasting with capsule are different in each part, it is needed to perform detection respectively in each of them. Yet owning to differential light penetration, the gray scale in the same region is inhomogeneous. Though various methods targeted at inhomogeneous region segmentation have been proposed in the literature, most of them are too complicated and time consuming to satisfy processing speed of on-line inspection. By analyzing the traditional image segmentation methods, a region growing technique based on linear scanning aiming at this issue is adopted. Unlike traditional region growing, it needs not to conduct complicated operation to specify initial seeds. The known input image structure is fundamental to its validity. Thus it is especially applicable to those applications which image structures have been already known, such as industrial on-line detection. It provides a fast extraction of the region-of-interest (ROI), saving precious time for following treatments. Its efficiency and robustness have been proved both in experiments and field applications.
NT-proBNP can be used to detect right ventricular systolic dysfunction in pulmonary hypertension

Right ventricular systolic dysfunction (RVSD) at baseline (pre-treatment) predicts early death in patients with pulmonary hypertension (PH). However, RVSD can only be detected reliably by prohibitively invasive or expensive techniques. N-terminal B-type natriuretic peptide concentration ([NT-proBNP]) correlates with RV function in PH; however, an [NT-proBNP] threshold that indicates RVSD in individual patients has not previously been determined. Twenty-five patients with PH (pulmonary arterial hypertension (n = 19) or chronic thromboembolic PH (n = 6)) underwent cardiovascular magnetic resonance (CMR) imaging and NT-proBNP measurement at baseline. [NT-proBNP] was correlated against RV dimensions and ejection fraction (RVEF) measured directly by CMR imaging. The ability of NT-proBNP to detect RVSD (defined as a CMR-derived RVEF >2 sds below control values) was tested and predictors of [NT-proBNP] identified. [NT-proBNP] correlated negatively with RVEF. RVSD was present in nine out of 25 patients. An [NT-proBNP] threshold of 1,685 pg·mL−1 was sensitive (100%) and specific (94%) in detecting RVSD. RVEF and RV mass index independently predicted [NT-proBNP]. In pulmonary hypertension, a baseline N-terminal B-type natriuretic peptide concentration of >1,685 ng·L−1 suggests right ventricular systolic dysfunction, and thus an increased risk of early death. N-terminal B-type natriuretic peptide could prove useful as an objective, noninvasive means of identifying patients with pulmonary hypertension who have right ventricular systolic dysfunction at presentation.
Region of Interest Extraction in Infrared Images Using One-Bit Transform

This paper presents a novel approach for region of interest (ROI) extraction in infrared images based on the one-bit transform. Potential interest regions in the infrared image are obtained by a target mask that is obtained using the one-bit transform in a local way. The histograms of the original image and the masked image are compared and the histogram region that remains unchanged is used to obtain an automated threshold value that is then utilized to detect the ROI in the infrared image. The proposed approach can be used as an effective pre-process for target detection and tracking algorithms in infrared images.
OPTICAL SURFACE RECONSTRUCTION OF LASER STRUCTURED MICRO-OBJECTS

Decoding performance of threshold-decodable forward-error-correcting codes is improved through the use of three methods. These methods employ measurements of received-digit reliability, and extended examination of syndrome digits. The first disclosed method allows correction of most partially-masked channel errors. These errors are not corrected in the prior art. The second and third disclosed methods correct almost all channel correctable with prior art, but furthermore disable action by the decoder in most cases where prior art would erroneously alter an information digit that had been received correctly.
Amygdala volume associated with alcohol abuse relapse and craving.

OBJECTIVE Amygdala volume has been associated with drug craving in cocaine addicts, and amygdala volume reduction is observed in some alcohol-dependent subjects. This study sought an association in alcohol-dependent subjects between volumes of reward-related brain regions, alcohol craving, and the risk of relapse. METHOD Besides alcohol craving, the authors assessed amygdala, hippocampus, and ventral striatum volumes in 51 alcohol-dependent subjects and 52 age- and education-matched healthy comparison subjects after detoxification. After imaging and clinical assessment, patients were followed for 6 months and alcohol intake was recorded. RESULTS Alcohol-dependent subjects showed reduced amygdala, hippocampus, and ventral striatum volumes and reported stronger craving in relation to healthy comparison subjects. However, only amygdala volume and craving differentiated between subsequent relapsers and abstainers. A significant decrease of amygdala volume in alcohol-dependent subjects was associated with increased alcohol craving before imaging and an increased alcohol intake during the 6-month follow-up period. CONCLUSIONS These findings suggest a relationship between amygdala volume reduction, alcohol craving, and prospective relapse into alcohol consumption.
A Subspace Approach to Texture Modelling by Using Gaussian Mixtures

Assuming local and shift-invariant texture properties we describe the statistical dependencies between pixels by a joint probability density of gray-levels within a suitably chosen observation window. We estimate the unknown multivariate density in the form of a Gaussian mixture of product components from data obtained by shifting the observation window. Obviously, the size of the window should be large to capture the low-frequency properties of textures but, on the other hand, the increasing dimension of the estimated mixture may become prohibitive. By considering a subspace approach based on a structural mixture model we can increase the size of the observation window while keeping the computational complexity in reasonable bounds
3D Face Recognition using iso-Geodesic Surfaces

In this paper, we present a novel approach to 3D face matching that shows high effectiveness in distinguishing facial differences between distinct individuals from differences induced by non-neutral expressions within the same individual. The approach takes into account geometrical information of the 3D face and encodes the relevant information into a compact representation in the form of a graph. Nodes of the graph represent equal width iso-geodesic facial stripes. Arcs between pairs of nodes are labeled with descriptors, referred to as 3D Weighted Walkthroughs (3DWWs), that capture the mutual relative spatial displacement between all the pairs of points of the corresponding stripes. Face partitioning into iso-geodesic stripes and 3DWWs together provide an approximate representation of local morphology of faces that exhibits smooth variations for changes induced by facial expressions. The graph-based representation permits very efficient matching for face recognition and is also suited to be employed for face identification in very large datasets with the support of appropriate index structures. The method obtained the best ranking at the SHREC 2008 contest for 3D face recognition. We present an extensive comparative evaluation of performance with the FRGC v2.0 dataset and the SHREC08 dataset.
Exploring factors related to craving and relapse in alcohol-dependent outpatients

markdownabstractDespite years of research and improvements in treatment and prevention, relapse in alcohol dependence remains a problem. Even though many patients become abstinent or controlled drinkers after treatment, relapse rates remain high. Therefore, the goal of this thesis was to explore determinants of relapse, focusing on those determinants that are present in the moments leading up to a relapse, so-called proximal determinants. Using the dynamic model of relapse (Witkiewitz and Marlatt, 2004), proximal determinants of relapse were examined in this thesis. Especially the role of craving, negative affect, alcohol-related stimuli and implicit processes were subject of investigation. Additionally, since craving is often seen as important to relapse even though a firm empirical foundation is lacking, extra attention was given to craving and its determinants. Overall, negative affect, including stress, was an important predictor of both relapse and craving. More specifically, negative affect is an important determinant of relapse but is accompanied by other determinants when a patient relapses. However, predicting relapse based on a prior measurement of attentional bias or avoidance tendencies during treatment does not seem warranted even though these biases seem to be present in abstinent alcohol-dependent outpatients. When looking at determinants of craving, stress and anxiety are predictive of craving, and drinking to cope with negative affect seems to serve as a vulnerability for experiencing craving. Additionally, craving is accompanied by higher levels of stress and negative affect in those patients who had relapsed. However, patients infrequently experience craving and the intensity of episodes varies both between and within patients. Finally, the mere experience of craving was not a determinant for relapse.
Welschinger invariant and enumeration of real rational curves

Welschinger’s invariant bounds from below the number of real rational curves through a given generic collection of real points in the real projective plane. We estimate this invariant using Mikhalkin’s approach which deals with a corresponding count of tropical curves. In particular, our estimate implies that, for any positive integer d, there exists a real rational curve of degree d through any collection of 3d − 1 real points in the projective plane, and, moreover, asymptotically in the logarithmic scale at least one third of the complex plane rational curves through a generic point collection are real. We also obtain similar results for curves on other toric Del Pezzo surfaces.
Mind reading machines: automated inference of cognitive mental states from video

Mind reading encompasses our ability to attribute mental states to others, and is essential for operating in a complex social environment. The goal in building mind reading machines is to enable computer technologies to understand and react to people's emotions and mental states. This paper describes a system, for the automated inference of cognitive mental states from observed facial expressions and head gestures in video. The system is based on a multilevel dynamic Bayesian network classifier which models cognitive mental states as a number of interacting facial and head displays. Experimental results yield an average recognition rate of 87.4% for 6 mental states groups: agreement, concentrating, disagreement, interested, thinking and unsure. Real time performance, unobtrusiveness and lack of preprocessing make our system particularly suitable for user-independent human computer interaction
Generation of the Optimal Bit-Width Topology of the Fast Hybrid Adder in a Parallel Multiplier

In state-of-the-art Digital Signal Processing (DSP) and Graphics applications, multiplication is an important and computationally intensive operation, consuming a significant amount of delay. The final carry propagate hybrid adder inside a multiplier plays an important role in determining the performance of the multiplication block. This paper presents an algorithmic approach to generate the optimal bit-width configuration of each of the sub-adders present inside the hybrid adder. Our technique is useful in selecting the best configuration (out of a large number of possible configurations) of the hybrid adder, thereby improving the overall performance of the chip. Our experiments involve different combinations of designs, technology libraries and timing constraints, and the results show that our algorithm successfully predicts the best hybrid-adder topology with a very low runtime.
DUSC: Dimensionality Unbiased Subspace Clustering

To gain insight into today's large data resources, data mining provides automatic aggregation techniques. Clustering aims at grouping data such that objects within groups are similar while objects in different groups are dissimilar. In scenarios with many attributes or with noise, clusters are often hidden in subspaces of the data and do not show up in the full dimensional space. For these applications, subspace clustering methods aim at detecting clusters in any sub- space. Existing subspace clustering approaches fall prey to an effect we call dimensionality bias. As dimensionality of subspaces varies, approaches which do not take this effect into account fail to separate clusters from noise. We give a formal definition of dimensionality bias and analyze consequences for subspace clustering. A dimensionality unbiased subspace clustering (DUSC) definition based on statistical foundations is proposed. In thorough experiments on synthetic and real world data, we show that our approach outperforms existing subspace clustering algorithms.
Functional characterization of SR and SR‐related genes in Caenorhabditis elegans

The SR proteins constitute a family of nuclear phosphoproteins, which are required for constitutive splicing and also influence alternative splicing regulation. Initially, it was suggested that SR proteins were functionally redundant in constitutive splicing. However, differences have been observed in alternative splicing regulation, suggesting unique functions for individual SR proteins. Homology searches of the Caenorhabditis elegans genome identified seven genes encoding putative orthologues of the human factors SF2/ASF, SRp20, SC35, SRp40, SRp75 and p54, and also several SR‐related genes. To address the issue of functional redundancy, we used dsRNA interference (RNAi) to inhibit specific SR protein function during C.elegans development. RNAi with CeSF2/ASF caused late embryonic lethality, suggesting that this gene has an essential function during C.elegans development. RNAi with other SR genes resulted in no obvious phenotype, which is indicative of gene redundancy. Simultaneous interference of two or more SR proteins in certain combinations caused lethality or other developmental defects. RNAi with CeSRPK, an SR protein kinase, resulted in early embryonic lethality, suggesting an essential role for SR protein phosphorylation during development.
Molecular couplings and energy exchange between DNA and water mapped by femtosecond infrared spectroscopy of backbone vibrations

Molecular couplings between DNA and water together with the accompanying processes of energy exchange are mapped via the ultrafast response of DNA backbone vibrations after OH stretch excitation of the water shell. Native salmon testes DNA is studied in femtosecond pump-probe experiments under conditions of full hydration and at a reduced hydration level with two water layers around the double helix. Independent of their local hydration patterns, all backbone vibrations in the frequency range from 940 to 1120 cm–1 display a quasi-instantaneous reshaping of the spectral envelopes of their fundamental absorption bands upon excitation of the water shell. The subsequent reshaping kinetics encompass a one-picosecond component, reflecting the formation of a hot ground state of the water shell, and a slower contribution on a time scale of tens of picoseconds. Such results are benchmarked by measurements with resonant excitation of the backbone modes, resulting in distinctly different absorption changes. We assign the fast changes of DNA absorption after OH stretch excitation to structural changes in the water shell which couple to DNA through the local electric fields. The second slower process is attributed to a flow of excess energy from the water shell into DNA, establishing a common heated ground state in the molecular ensemble. This interpretation is supported by theoretical calculations of the electric fields exerted by the water shell at different temperatures.