Miracle-dz/UniFAR-FTUs huggingface dataset:
Myoelectric activity of the muscular layer of the abdominal aorta in pigs in vivo

The study was conducted on 5 pigs weighing 20–30 kg. Bipolar electrodes were surgically implanted into the muscular layer of the vascular smooth muscle cell of the abdominal aorta just below the renal arteries. Myoelectric activity characterized by the appearance of changes of membrane potential was found. Changes of potential could be divided according to the amplitude, duration and frequency into first-, second- and third-order waves. First-order waves appeared with a mean frequency of 128 ± 14/min. The mean wave amplitude was 0.150 ± 0.03 mV, and the mean duration was 0.43 ± 0.05 s. They were closely correlated with the electrocardiogram and blood pressure changes. Second-order waves appeared with a mean frequency of 15.9 ± 4.4/min. They were characterized by a mean duration of 2.69 ± 1.5 s. The mean amplitude of the discharge was 0.205 ± 0.157 mV for the second-order wave, they were correlated with the animal’s respiratory action. Third-order waves appeared with a mean frequency of 4.03 ± 1.07/ min. They were characterized by a mean duration of 11.81 ± 5.3 s. The mean amplitude of the discharge was 0.345 ± 0.232 mV for the third-order wave and they were associated with the autonomic control of the lumen of the blood vessel. For the first time the usefulness of the electromyography method in monitoring changes in the vascular smooth muscle cell of pig abdominal aorta was proved. Electromyography, membrane potential, VSMC, contractility The function of the abdominal aorta is to transport blood to the smaller arterial vessels under high pressure. It performs this function due to the adaptation of the anatomy and biophysical properties of the vessel wall. Generally, the wall of blood vessels is composed of an endothelial layer, a middle layer containing numerous smooth muscular coat cells with collagen and elastic fibres, and adventitia surrounding the vessel. The biophysical properties of blood vessels are determined by the mutual quantity ratio of these three elements together and the ratio of the vessel wall thickness to the internal radius. The wall of larger arteries is characterized by a low ratio of wall thickness to the internal radius (on average 1 : 6), (Harder et al. 1981). It is dominated by elastic fibres that provide it with considerable tensibility. The presence of smooth muscular tissue in the arteries provides control of the vessel lumen. Muscular coat contraction causes reduction in the crosssection of the vessel which results in increased vascular resistance and blood pressure. The control of the vessel lumen takes place through nerves by the autonomic nervous system and hormonally by the secretion of vasoconstrictor (Guyenet 2006; Grassi et al. 2008). The aim of this research was to study the bioelectric properties of the smooth muscular coat of the aorta in pigs and to interpret the obtained patterns, considering the fact that there is a strong correlation between bioelectric activity and contractility. This work is an
Structural and functional bases for individual differences in motor learning

People vary in their ability to learn new motor skills. We hypothesize that between‐subject variability in brain structure and function can explain differences in learning. We use brain functional and structural MRI methods to characterize such neural correlates of individual variations in motor learning. Healthy subjects applied isometric grip force of varying magnitudes with their right hands cued visually to generate smoothly‐varying pressures following a regular pattern. We tested whether individual variations in motor learning were associated with anatomically colocalized variations in magnitude of functional MRI (fMRI) signal or in MRI differences related to white and grey matter microstructure. We found that individual motor learning was correlated with greater functional activation in the prefrontal, premotor, and parietal cortices, as well as in the basal ganglia and cerebellum. Structural MRI correlates were found in the premotor cortex [for fractional anisotropy (FA)] and in the cerebellum [for both grey matter density and FA]. The cerebellar microstructural differences were anatomically colocalized with fMRI correlates of learning. This study thus suggests that variations across the population in the function and structure of specific brain regions for motor control explain some of the individual differences in skill learning. This strengthens the notion that brain structure determines some limits to cognitive function even in a healthy population. Along with evidence from pathology suggesting a role for these regions in spontaneous motor recovery, our results also highlight potential targets for therapeutic interventions designed to maximize plasticity for recovery of similar visuomotor skills after brain injury. Hum Brain Mapp, 2011. © 2010 Wiley‐Liss, Inc.
Journal of Quantitative Analysis in Sports Testing the Commitment Hypothesis in Contractual Settings : Evidence from Soccer

This paper designs and implements an empirical test to discern whether the parties to a contract are able to commit not to renegotiate their agreement. We study optimal contracts with and without commitment and derive an exclusion restriction that is useful to identify the relevant commitment scenario. The empirical analysis takes advantage of a data set on Spanish soccer player contracts. Our test rejects the commitment hypothesis. We argue that our conclusions should hold a fortiori in many other economic environments.
Monitoring fetal maturation—objectives, techniques and indices of autonomic function

Monitoring the fetal behavior does not only have implications for acute care but also for identifying developmental disturbances that burden the entire later life. The concept, of ‘fetal programming’, also known as ‘developmental origins of adult disease hypothesis’, e.g. applies for cardiovascular, metabolic, hyperkinetic, cognitive disorders. Since the autonomic nervous system is involved in all of those systems, cardiac autonomic control may provide relevant functional diagnostic and prognostic information. The fetal heart rate patterns (HRP) are one of the few functional signals in the prenatal period that relate to autonomic control and, therefore, is predestinated for its evaluation. The development of sensitive markers of fetal maturation and its disturbances requires the consideration of physiological fundamentals, recording technology and HRP parameters of autonomic control. Based on the ESGCO2016 special session on monitoring the fetal maturation we herein report the most recent results on: (i) functional fetal autonomic brain age score (fABAS), Recurrence Quantitative Analysis and Binary Symbolic Dynamics of complex HRP resolve specific maturation periods, (ii) magnetocardiography (MCG) based fABAS was validated for cardiotocography (CTG), (iii) 30 min recordings are sufficient for obtaining episodes of high variability, important for intrauterine growth restriction (IUGR) detection in handheld Doppler, (iv) novel parameters from PRSA to identify Intra IUGR fetuses, (v) evaluation of fetal electrocardiographic (ECG) recordings, (vi) correlation between maternal and fetal HRV is disturbed in pre-eclampsia. The reported novel developments significantly extend the possibilities for the established CTG methodology. Novel HRP indices improve the accuracy of assessment due to their more appropriate consideration of complex autonomic processes across the recording technologies (CTG, handheld Doppler, MCG, ECG). The ultimate objective is their dissemination into routine practice and studies of fetal developmental disturbances with implications for programming of adult diseases.
Oral contraceptive use in girls and alcohol consumption in boys are associated with increased blood pressure in late adolescence

Aims: Lifestyle behaviours established during adolescence may adversely affect blood pressure (BP) and contribute to gender differences in cardiovascular risk in adulthood. We aimed to assess the association of health behaviours with BP in adolescents, using data from the Western Australian Pregnancy (Raine) Study. Methods: Cross-sectional analysis on 1248 Raine Study adolescents aged 17 years, to examine associations between lifestyle factors and BP. Results: Boys had 8.97 mmHg higher systolic BP, as compared with girls. The 30% of girls using oral contraceptives (OC) had 3.27 and 1.74 mmHg higher systolic and diastolic BP, respectively, compared with non-users. Alcohol consumption in boys, increasing body mass index (BMI) and the sodium-potassium ratio were associated with systolic BP. We found a continuous relationship between BMI and systolic BP in both genders; however, the gradient of this relationship was significantly steeper in boys, compared with girls not taking OC. In boys, systolic BP was 5.7 mmHg greater in alcohol consumers who were in the upper quartile of BMI and the urinary sodium-potassium ratio compared with teetotallers in the lowest quartile. In girls, systolic BP was 5.5 mmHg higher in those taking OC, in the highest BMI and urinary sodium-potassium ratio quartile as compared to those not taking the OC pill and in the lowest quartile. Conclusion: In addition to gender-related differences in the effects of adiposity on BP, we found lifestyle-related health behaviours such as high salt intake for both sexes, consumption of alcohol in boys, and OC use in girls were important factors associated with BP measurements in late adolescence. This suggests that gender-specific behavioural modification in adolescence may prevent adult hypertension.
Mutational Analysis of the Poly(ADP-Ribosyl)ation Sites of the Transcription Factor CTCF Provides an Insight into the Mechanism of Its Regulation by Poly(ADP-Ribosyl)ation

ABSTRACT Poly(ADP-ribosyl)ation of the conserved multifunctional transcription factor CTCF was previously identified as important to maintain CTCF insulator and chromatin barrier functions. However, the molecular mechanism of this regulation and also the necessity of this modification for other CTCF functions remain unknown. In this study, we identified potential sites of poly(ADP-ribosyl)ation within the N-terminal domain of CTCF and generated a mutant deficient in poly(ADP-ribosyl)ation. Using this CTCF mutant, we demonstrated the requirement of poly(ADP-ribosyl)ation for optimal CTCF function in transcriptional activation of the p19ARF promoter and inhibition of cell proliferation. By using a newly generated isogenic insulator reporter cell line, the CTCF insulator function at the mouse Igf2-H19 imprinting control region (ICR) was found to be compromised by the CTCF mutation. The association and simultaneous presence of PARP-1 and CTCF at the ICR, confirmed by single and serial chromatin immunoprecipitation assays, were found to be independent of CTCF poly(ADP-ribosyl)ation. These results suggest a model of CTCF regulation by poly(ADP-ribosyl)ation whereby CTCF and PARP-1 form functional complexes at sites along the DNA, producing a dynamic reversible modification of CTCF. By using bioinformatics tools, numerous sites of CTCF and PARP-1 colocalization were demonstrated, suggesting that such regulation of CTCF may take place at the genome level.
Structure of the fungal β‐glucan‐binding immune receptor dectin‐1: Implications for function

The murine molecule dectin‐1 (known as the β‐glucan receptor in humans) is an immune cell surface receptor implicated in the immunological defense against fungal pathogens. Sequence analysis has indicated that the dectin‐1 extracellular domain is a C‐type lectin‐like domain, and functional studies have established that it binds fungal β‐glucans. We report several dectin‐1 crystal structures, including a high‐resolution structure and a 2.8 Å resolution structure in which a short soaked natural β‐glucan is trapped in the crystal lattice. In vitro characterization of dectin‐1 in the presence of its natural ligand indicates higher‐order complex formation between dectin‐1 and β‐glucans. These combined structural and biophysical data considerably extend the current knowledge of dectin‐1 structure and function, and suggest potential mechanisms of defense against fungal pathogens.
Learning Salient Features for Real-Time Face Verification

We propose a novel person veriication system for real-time face identiication. The main features of the system include accurate registration of face images using a robust form of correlation, a framework for global registration of a face database using a minimum spanning tree algorithm and a method for selecting a subset of features optimal for discrimination between clients and impostors. We present results obtained through experiments on a large database with 295 subjects and show that the method is performing well in comparison with two standard methods based on elastic graph matching.
A strong direct product theorem in terms of the smooth rectangle bound

A strong direct product theorem states that, in order to solve k instances of a problem, if we provide less than k times the resource required to compute one instance, then the probability of overall success is exponentially small in k. In this paper, we consider the model of two-way public-coin communication complexity and show a strong direct product theorem for all relations in terms of the smooth rectangle bound, introduced by Jain and Klauck as a generic lower bound method in this model. Our result therefore uniformly implies a strong direct product theorem for all relations for which an (asymptotically) optimal lower bound can be provided using the smooth rectangle bound, for example Inner Product, Greater-Than, Set-Disjointness, Gap-Hamming Distance etc. Our result also implies near optimal direct product results for several important functions and relations used to show exponential separations between classical and quantum communication complexity, for which near optimal lower bounds are provided using the rectangle bound, for example by Raz [1999], Gavinsky [2008] and Klartag and Regev [2011]. In fact we are not aware of any relation for which it is known that the smooth rectangle bound does not provide an optimal lower bound. This lower bound subsumes many of the other lower bound methods, for example the rectangle bound (a.k.a the corruption bound), the smooth discrepancy bound (a.k.a the \gamma_2 bound) which in turn subsumes the discrepancy bound, the subdistribution bound and the conditional min-entropy bound. We show our result using information theoretic arguments. A key tool we use is a sampling protocol due to Braverman [2012], in fact a modification of it used by Kerenidis, Laplante, Lerays, Roland and Xiao [2012].
Prosperous Digital Image Watermarking Approach by using DCT-DWT

In this paper, Everyday tons of data is embedded on digital media or distributed over the internet. The data so Distributed can easily be replicated without error, putting the rights of their owners at risk. Even when encrypted for distribution, data can easily be decrypted and copied. One way to discourage illegal duplication is to insert information known as watermark, into potentially valuable data in such a way that it is impossible to separate the watermark from the data. These challenges motivated researchers to carry out intense research in the field of watermarking. A watermark is a form, image or text that is impressed onto paper, which provides evidence of its Authenticity. Digital watermarking is an extension of the same concept. There are two types of watermarks visible watermark and invisible watermark. In this project we have concentrated on implementing watermark in image. The main consideration for any watermarking scheme is its robustness to various attacks
A DTW and Fourier Descriptor based approach for Indian Sign Language recognition

Humans with hearing disabilities are highly dependent on non-verbal forms of communication involving hand gestures. A gesture recognition system capable of transforming gestures to other forms of communication can bring about a significant improvement in the quality of life of such human beings. A novel approach making use of Fourier Descriptors for shape extraction followed by Dynamic Time Warping for sequence matching in order to recognize gestures representing English alphabets present in the Indian Sign Language (ISL) has been proposed in this paper. A feature vector constituting the top 220 coefficients of the Fourier Descriptor is calculated for all images present in the training and test dataset. The test sequences are matched with the training sequences using Dynamic time Warping algorithm in order to calculate the similarity between the test image and all the images of the training dataset. The results are stored in the increasing order of the cost between the two sequences which is a measure of similarity between the two sequences. K-nearest neighbor algorithm is then applied to a cost vector containing 15 gestures having the minimum cost with the test image to recognize the most dominant gesture. A data set constituting of 338 images is used for training the algorithm for classifying 26 different characters. The algorithm was found to have an accuracy of 96.15 % when tested on a dataset of 78 images.
Across-Document Neighborhood Expansion: UMass at TAC KBP 2012 Entity Linking

Last year’s competition demonstrated that the NER context contains important information that should not be ignored in entity linking. State-of-the-art approaches anchor on unambiguous entities, look for overlap in categories, or approximate a joint model of candidate assignments, after Wikipedia candidates have been selected. Current candidate approaches, such as anchor text maps, are effective but may lead to very large candidate sets to be examined. UMass has two objectives for our TAC submission. First, we use cross-document context information to perform entity neighborhood expansion and estimate the importance of entity context using corpus-wide information. Second, we use probabilistic information retrieval that incorporates the neighborhood information to generate a ranked candidate set in a single step. The result is a small candidate set that even for less than 50 candidates contains the true answer in 95% of the cases, allowing for computationally intensive inference in the next phase. It turns out that our best performing run simply predicts the top candidate of the unsupervised candidate ranking, outperforming more than half of the contestants.
Program induction: building a wall

Evolutionary programming of many systems has been demonstrated in the literature. In This work we use these techniques to program a virtual robot to build a wall out of blocks that impede progress in one direction across a grid of squares. Specifically, two methods for automatic program induction are compared on this task. Virtual blocks are presented one at a time in a fixed location on the grid. The robot must move the currently presented block to enable presentation of the next block as well as using the blocks to build the wall. An evolutionary algorithm operating on strings of actions for the task is used for baseline performance measurement. Evolutionary algorithms operating on GP-Automata and ISAc lists are then applied to the wall building task. In addition to broadening the palette of virtual robotics task, this permits us to compare these two representations for program induction. We study two versions of the wall building problem. The first, in which there are impenetrable walls at the boundary of the virtual world, is much easier than the second method that takes place on a virtual table-top where blocks and the robot may fall off. In addition to the usual randomized initialization, a technique for initializing evolutionary runs with already evolved solutions is presented for the string baseline and both program induction representations.
Optimizing 3D NoC design for energy efficiency: A machine learning approach

Three-dimensional (3D) Network-on-Chip (NoC) is an emerging technology that has the potential to achieve high performance with low power consumption for multicore chips. However, to fully realize their potential, we need to consider novel 3D NoC architectures. In this paper, inspired by the inherent advantages of small-world (SW) 2D NoCs, we explore the design space of SW network-based 3D NoC architectures. We leverage machine learning to intelligently explore the design space to optimize the placement of both planar and vertical communication links for energy efficiency. We demonstrate that the optimized 3D SW NoC designs perform significantly better than their 3D MESH counterparts. On an average, the 3D SW NoC shows 35% energy-delay-product (EDP) improvement over 3D MESH for the nine PARSEC and SPLASH2 benchmarks considered in this work. The highest performance improvement of 43% was achieved for RADIX. Interestingly, even after reducing the number of vertical links by 50%, the optimized 3D SW NoC performs 25% better than the fully connected 3D MESH, which is a strong indication of the effectiveness of our optimization methodology.
Preference Estimation for SNS Fan Pages Based on Statistical Information

It is important to identify the preferred features of sentences in different contexts. In particular, many people are increasingly using communication tools such as SNS and it is becoming easier to obtain user data. In this study, we estimate the preference for sentences in Facebook. More specifically, we try to improve the estimation of the importance of words in actual sentences. We conducted evaluation experiments, which showed that 1) inverse document frequency (IDF) is effective for both English and Japanese, 2) the estimated and actual preference levels were correlated.