Miracle-dz/UniFAR-FTUs huggingface dataset:
Vascular Smooth Muscle and the Anisotropy of Dog Carotid Artery

Segments of dog carotid artery were held at in-situ length and studied in vitro after excitation of the muscle with norepinephrine and after poisoning of the muscle with potassium cyanide. In-situ length corresponded to a longitudinal strain of . 57±. 02 relative to the unstretched length. The longitudinal elastic modulus was about 4.1×106 dyn/cm2 at in-situ length and zero transmural pressure. This value was not altered by excitation of the vascular smooth muscle. The longitudinal stress due to traction decreased as the longitudinal stress due to transmural pressure increased, and it was suggested that this interaction underlies the relative constancy of vessel length in situ. The Poisson's ratio between the circumferential and longitudinal directions was about 0.3 and was found to decrease slightly with activation of the vascular muscle. The data for the longitudinal modulus and for Poisson's ratio were used to compute the circumferential elastic modulus. Activation of the muscle increased the circumferential elastic modulus when plotted as a function of circumferential strain. Comparison between the moduli in the two directions revealed that the arterial wall is not isotropic at physiological pressures because the circumferential elastic modulus is greater than the longitudinal modulus. Calculations indicated that assuming isotropy slightly underestimates the true circumferential modulus at small circumferential strains, and greatly overestimates the true circumferential modulus at large circumferential strains. Active smooth muscle has little direct effect on these estimations, but does alter the error by contracting the vessel to smaller strains.
Developments of the Research of the Formant Tracking Algorithm

The formant is the important part of the phonetic characters, and reliable formant tracking algorithm is the base to study the phonetics. Based on the development course of the phonetic formant tracking algorithm, the linear prediction coding (LPC) and the model matching method are introduced emphatically, and there own advantages and disadvantages are analyzed, and the model matching method based on the hidden dynamic model will be the development direction of the future formant tracking technology.
The Influence of High School Activity Portfolios on Risky Behaviors in Emerging Adulthood

Extracurricular participation in adolescence is often linked to the development of a prosocial identity and social relationships. Through these social psychological mechanisms, participation is thought to prevent risky behavior in adolescence and into emerging adulthood. This study examined the relationship between high school activity portfolios and risky behaviors (i.e. binge drinking, drug use, and law violation) among a college sample. Five activity portfolios were identified, including sports-focused, low involvement, highly engaged, and two combination portfolios. There were significant differences between portfolios on social psychological measures (e.g. prosocial beliefs and social responsibility), current extracurricular involvement, and risky behaviors. Regression models indicated that social psychological factors and current involvement partially mediated the association between portfolios and risky behaviors, but portfolio type retained direct effects. Portfolios associated with involvement across several activity domains were more protective for emerging adults, in part by shaping their beliefs, sense of social responsibility, and continuing involvement.
Daytime light exposure : optimizing effects on cognitive performance and subjective wellbeing

This study examined whether diurnal non-image forming (NIF) effects of illuminance on cognitive task performance depend on task difficulty and time of day. We employed a balanced crossover design with two 60-min sessions of 200 vs. 1000 lx at eye level. Digit-span task difficulty was manipulated within subjects (forward (FDST) vs. backward (BDST) digit-span task), n-back task difficulty was manipulated between subjects (n = 1, 2, or 3). Bright light exposure improved FDST performance during the final measurement block, especially in the afternoon. In contrast, BDST performance deteriorated slightly under bright light in the afternoon. Two-back performance was significantly worse under bright light in the afternoon, while no effect of illuminance was found on 3-back performance. Thus, the more difficult BDST was affected differently by light intensity as compared to the easier FDST. N-back accuracy, however, did not confirm this role of task difficulty. Future studies should investigate whether similar results hold for other types of tasks and how other variables (e.g., time of day, physiological arousal, or other task characteristics) may influence the direction and magnitude of NIF effects on performance. This chapter was published as: Huiberts, L. M. , Smolders, K. C. H. J., & De Kort, Y. A. W. (2015). Shining light on memory: Effects of bright light on working memory performance. Behavioural Brain Research, 294, 234-245. Chapter 2 Effects of bright light on working memory performance _____________________________________________________________________________
A Discussion on English Language Students’ Body Image: Beauty Standards and Fatness

In this qualitative study, we intend to discuss how adolescent students in a Brazilian public school classroom define their body image and personalize the themes beauty standards and fatness. Grounded on a critical approach to language teaching, these two social themes were problematized in eight lessons of Ensino Médio (secondary education). The discussion of the empirical material suggests that (1) body image is strongly connected to gendered relations, making life experiences of men and women different based on the bodies they have, and (2) beauty standard and fatness are strongly related to students’ lives since twelve out of nineteen students personalized the themes by telling oppressive stories they went through because of their bodies.
Stochastic-Based Robust Dynamic Resource Allocation in a Heterogeneous Computing System

This research investigates the problem of robust dynamic resource allocation for heterogeneous distributed computing systems operating under imposed constraints. Often, such systems are expected to function in an environment where uncertainty in system parameters is common. In such an environment, the amount of processing required to complete an application may fluctuate substantially. Determining a resource allocation that accounts for this uncertainty---in a way that can provide a probability that a given level of service is achieved---is an important area of research. We define a mathematical model of stochastic robustness appropriate for a dynamic environment that can be used during resource allocation to aid heuristic decision making. In addition, we design a novel technique for maximizing stochastic robustness in this environment. Our performance results for this technique are compared with several well known resource allocation techniques in a simulated environment that models a heterogeneous distributed computing system.
Differences in Chemical, Physical and Microbiological Characteristics of Italian Burrata Cheeses Made in Artisanal and Industrial Plants of Apulia Region

The burrata cheese is a traditional product from Southern Italy, consisting of an envelope of pasta filata (stretched curd) filled with cream and pasta filata strips (usually leftovers from mozzarella production). Physical [water activity (aw), pH], chemical (moisture, NaCl content) and microbiological [total viable count (TVC), Listeria monocytogenes, Salmonella spp. , Yersinia enterocolitica, Bacillus cereus, Escherichia coli, Enterobacteriaceae, coagulase-positive staphylococci] characteristics of burrata cheeses manufactured in artisanal and industrial plants were evaluated. The artisanal burrata showed lower aw values in the filling and the final product. The same was recorded in the filling for the moisture, probably due to differences between the types of cream used in the artisanal and the industrial cheesemaking. The pH value of the filling differed between the two groups but no difference was recorded in the final product. Microbiological differences were also recorded, with higher values for TVC and E. coli in artisanal than industrial burrata. All samples were negative for the other microbial determinations, with the exception of coagulase-positive staphylococci and Y. enterocolitica, which were detected in artisanal burrata. Differences in cheesemaking process were probably responsible for the strong variability of the physical and chemical data between the two cheeses; furthermore, differences in the hygienic features were also recorded. Even though artisanal products showed lower aw and pH values and higher NaCl concentration, the higher E. coli loads highlighted the need for a more accurate compliance with hygienic procedures along the artisanal cheesemaking process.
Emotional Intelligence Level of Year One and Two Medical Students of University Malaysia Sarawak: Association With Demographic Data

Emotional intelligence is the ability to monitor one’s own and other’s emotions, to discriminate among them, and to guide one’s thinking and actions. It is very important to assess as it helps to reason out our emotional responses. The objective of this study is to assess the emotional intelligence level of Year one and two medical students of UNIMAS. Majority has strength in all the domains except managing emotions domain where 51.5% need attention. No respondent fall into the development priority competency. There were no significant difference among all the domains between two groups but Year 1 students need more attention in managing emotions domain compared to Year 2 students. There was no significant association between demographic characteristics – age, residency, qualification and ethnicity – but there was a significant association (p value of 0.038) in male with empathy domain. Further study should be done on groups spanning from Year 1 to Year 5 as they have a greater difference in age as well as exposure to clinical practice which may have a significant impact on their emotional intelligence.
Extended dynamic fuzzy logic system for a class of MIMO nonlinear systems and its application to robotic manipulators

SUMMARY This paper presents an indirect adaptive fuzzy control scheme for a class of unknown multi-input multi-output (MIMO) nonlinear systems with external disturbances. Within this scheme, the dynamic fuzzy logic system (DFLS) is employed to identify the unknown nonlinear MIMO systems. The control law and parameter adaptation laws of DFLS are derived based on the Lyapunov synthesis approach. The control law is robustified in H∞ sense to attenuate external disturbance, model uncertainties, and fuzzy approximation errors. It is shown that under appropriate assumptions it guarantees the boundness of all signals in the closed-loop system and the asymptotic convergence to zero of tracking errors. An extensive simulation on the tracking control of a two-link rigid robotic manipulator verifies the effectiveness of the proposed algorithms.
Regression test selection technique for multi-programming language

Regression testing is a maintenance activity applied to modified software to provide confidence that the changed parts are correct and that the unchanged parts have not been adversely affected by the modifications. Regression test selection techniques reduce the cost of regression testing, by selecting a subset of an existing test suite to use in retesting modified programs. This paper presents the first general regression-test-selection technique, which based on code and allows selecting test cases for any programs written in any programming language. Then it handles incomplete program. We also describe RTSDiff, a regression-test-selection system that implements the proposed technique. The results of the empirical studied that performed in four programming languages java, C#, C++ and Visual basic show that the efficiency and effective in reducing the size of test suit.
MathBrush: An Experimental Pen-Based Math System

It is widely believed that mathematics will be one of the major applications for Tablet PCs and other pen-based devices. In this paper we discuss many of the issues that make doing mathematics on such pen-based devices a hard task. We give a preliminary description of an experimental system, currently named MathBrush, for working with mathematics using penbased devices. The system allows a user to enter mathematical expressions with a pen and to then do mathematical computation using a computer algebra system. The system provides a simple and easy way for users to verify the correctness of their handwritten expressions and, if needed, to correct any errors in recognition. Choosing mathematical operations is done making use of context menus, both with input and output expressions.
Critical Echo State Networks that Anticipate Input using Adaptive Transfer Functions

The paper investigates a new type of truly critical echo state networks where individual transfer functions for every neuron can be modified to anticipate the expected next input. Deviations from expected input are only forgotten very slowly in power law fashion. The paper outlines the theory, numerically analyzes a one neuron model network and finally discusses technical and also biological implications of this type of approach.
Pixel saliency metric based pixel-level medical image fusion

This paper proposes a novel medical image fusion algorithm based on pixel salience metric in gradient domain. We first obtain the gradient image of every input image and measure their salience map, and then use saliency to weight gradient pixel to acquire a target gradient field. Applying dynamic range compression (DRC) algorithm to reduce halo effect. Finally, exploiting successive over-relaxation method to solve a Poisson equation for minimizing the energy function. Experimental result shows that the proposed method is the best in the concept of saliency compared to the existing pixel-level image fusion methods.
The Standard S Control Chart with Run Rules

The application of standard control chart with two run rules in control of process variability is discussed in this paper. The control limits and average run length(ARL) are computed by the method of Markov chain. The results show that the standard control chart with run rules has smaller ARL than the standard control chart for all kinds of magnitudes of shifts. In the end, an example accompanied by simulation is used to illustrate that the chart with run rules is more sensitive to shifts in the process variability.
Vocal Emotion Recognition with Log-Gabor Filters

Vocal emotion recognition aims to identify the emotional states of speakers by analyzing their speech signal. This paper builds on the work of Ezzat, Bouvrie and Poggio by performing a spectro-temporal analysis of affective vocalizations by decomposing the associated spectrogram with 2D Gabor filters. Based on the previous studies of the emotion expression in voices and the turn out display in spectrogram, we assumed that each vocal emotion has a unique spectro-temporal signature in terms of orientated energy bands which can be detected by properly tuned Gabor filters. We compared the emotion-recognition performances of tuned log-Gabor filters with standard acoustic features. The experimental results show that applying pairs of log-Gabor filters to extract features from the spectrogram yields a performance that matches the performance of an approach based on traditional acoustic features. Their combined emotion recognition performance outperforms state-of-the-art vocal emotion recognition algorithms. This leads us to conclude that tuned log-Gabor filters support the automatic recognition of emotions from speech and may be beneficial to other speech-related tasks.
A Modern Method for Constructing the S-Box of Advanced Encryption Standard

The substitution table (S-Box) of Advanced Encryption Standard (AES) and its properties are key elements in cryptanalysis ciphering. We aim here to propose a straightforward method for the non-linear transformation of AES S-Box construction. The method reduces the steps needed to compute the multiplicative inverse, and computes the matrices multiplication used in this transformation, without a need to use the characteristic matrix, and the result is a modern method constructing the S-Box.
Monitoring radiofrequency ablation with ultrasound Nakagami imaging.

PURPOSE Radiofrequency ablation (RFA) is a widely used alternative modality in the treatment of liver tumors. Ultrasound B-mode imaging is an important tool to guide the insertion of the RFA electrode into the tissue. However, it is difficult to visualize the ablation zone because RFA induces the shadow effect in a B-scan. Based on the randomness of ultrasonic backscattering, this study proposes ultrasound Nakagami imaging, which is a well-established method for backscattered statistics analysis, as an approach to complement the conventional B-scan for evaluating the ablation region. METHODS Porcine liver samples (n = 6) were ablated using a RFA system and monitored by employing an ultrasound scanner equipped with a 7.5 MHz linear array transducer. During the stages of ablation (0-12 min) and postablation (12-24 min), the raw backscattered data were acquired at a sampling rate of 30 MHz for B-mode, Nakagami imaging, and polynomial approximation of Nakagami imaging. The contrast-to-noise ratio (CNR) was also calculated to compare the image contrasts of the B-mode and Nakagami images. RESULTS The results demonstrated that the Nakagami image has the ability to visualize changes in the backscattered statistics in the ablation zone, including the shadow region during RFA. The average Nakagami parameter increased from 0.2 to 0.6 in the ablation stage, and then decreased to approximately 0.3 at the end of the postablation stage. Moreover, the CNR of the Nakagami image was threefold that of the B-mode image, showing that the Nakagami image has a better image contrast for monitoring RFA. Specifically, the use of the polynomial approximation equips the Nakagami image with an enhanced ability to estimate the range of the ablation region. CONCLUSIONS This study demonstrated that ultrasound Nakagami imaging based on the analysis of backscattered statistics has the ability to visualize the RFA-induced ablation zone, even if the shadow effect exists in the B-scan.
A pr 2 00 2 GRADIENT FORMULA FOR LINEARLY SELF-INTERACTING BRANES

The computation of long range linear self-interaction forces in string and higher dimensional brane models requires the evaluation of the gradients of regularised values of divergent self-interaction potentials. It is shown that the appropriately regularised gradient in directions orthogonal to the brane surface will always be obtainable simply by multiplying the regularised potential components by just half the trace of the second fundamental tensor, except in the hypermembrane case for which the method fails. Whatever the dimension of the background this result is valid provided the codimension is two (the hyperstring case) or more, so it can be used for investigating brane-world scenarios with more than one extra space dimension.
Path Shortening Schema for Minimum Delay Spanning Tree on Overlay Multicast

Overlay networks are expected to play a significant role in interactive group applications in the Internet. In these applications, since the applications require broadcast communication, application layer multicast under the overlay networks involving all active participants is a reasonable solution. Therefore, considering that the applications are generally delay sensitive, minimizing delay on an overlay multicast tree becomes important issue. In this paper, we propose a novel schema that allows us to minimize delay in overlay multicast tree. Our schema consist two-phase procedure: join procedure and refinement procedure. The join procedure performs which node on multicast tree to select and to connect it when a new node joins multicast tree. The refinement procedure corrects imbalance of multicast tree, and restructures it
Codeease: harnessing method clone structures for reuse

Searching for code examples on the internet is commonly and frequently performed by software developers but wastes a lot of their time and reduces their productivity. To aid developers with this problem, a system is needed that can allow them to get appropriate code recommendations for reuse within the IDE. In this paper, we present our prototype tool CodeEase, developed as an Eclipse plugin, which generates method recommendations against the code of the developer. The recommendations are based on clone detection and an analysis of Method Clone Structures (MCS) – a type of structural clones- from a large repository of code.
A PropBank for Portuguese: the CINTIL-PropBank

With the CINTIL-International Corpus of Portuguese, an ongoing corpus annotated with fully flegded grammatical representation, sentences get not only a high level of lexical, morphological and syntactic annotation but also a semantic analysis that prepares the data to a manual specification step and thus opens the way for a number of tools and resources for which there is a great research focus at the present. This paper reports on the construction of a propbank that builds on CINTIL-DeepGramBank, with nearly 10 thousand sentences, on the basis of a deep linguistic grammar and on the process and the linguistic criteria guiding that construction, which makes possible to obtain a complete PropBank with both syntactic and semantic levels of linguistic annotation. Taking into account this and the promising scores presented in this study for inter-annotator agreement, CINTIL-PropBank presents itself as a great resource to train a semantic role labeller, one of our goals with this project.
Elucidating Activity-related Physico-chemical Features in Antimicrobial Peptides

The rise of drug-resistant bacteria has brought attention to antimicrobial peptides (AMPs) as targets for novel antibacterial drug research. Many machine learning methods aim to improve recognition of AMPs. Sequence-derived features are often employed in the context of supervised learning through Support Vector Machines (SVMs). This can be useful for expediently screening databases for AMP-like peptides. However, AMPs are characterized by great sequence diversity. Moreover, biological studies focusing on AMP modification and de novo design stand to benefit from computational methods capable of exposing underlying features important for activity at the amino-acid level position. We take the first steps in this direction by considering an extensive list of amino-acid physico-chemical features. We gradually narrow this list down to relevant features in the context of SVM classification. We focus on a specific AMP class, cathelicidins, due to the abundance of documented sequences, to improve their recognition over carefully-designed decoy sequences. Analysis of the features important for the classification reveals interesting physico-chemical properties to preserve when modifying or designing novel AMPs in the wet laboratory.