Miracle-dz/UniFAR-FTUs huggingface dataset:
The effect of an acute elevation of NEFA concentrations on glucagon-stimulated hepatic glucose output.

To determine the effect of nonesterified fatty acids (NEFA) on glucagon action, glucagon was infused intraportally (1.65 ng.min(-1). kg(-1)) for 3 h into 18-h-fasted, pancreatic-clamped conscious dogs in the presence [NEFA + glucagon (GGN)] or absence (GGN) of peripheral Intralipid plus heparin infusion. Additionally, hyperglycemic (HG), hyperglycemic-hyperlipidemic (NEFA + HG), and glycerol plus glucagon (GLYC + GGN) controls were studied. Arterial plasma glucagon concentrations rose equally in GGN, NEFA + GGN, and GLYC + GGN but remained basal in hyperglycemic controls. Peripheral infusions of Intralipid and heparin increased arterial plasma NEFA concentrations equally in NEFA + GGN and NEFA + HG and did not change in other protocols. After 15 min, glucagon infusion resulted in a rapid, brief increase in net hepatic glycogenolysis (NHGLY, mg.min(-1). kg(-1)) of approximately 6.0 in GGN and GLYC + GGN but only increased by 3.8 +/- 1.3 in NEFA + GGN. Thus increases in NHGLY, and consequently net hepatic glucose output (NHGO), were blunted by 40%, with no difference between the groups in the last 2.5 h of the study. NHGO and NHGLY did not significantly change in HG and NEFA + HG. Net hepatic gluconeogenic flux did not change in GGN, GLYC + GGN, or HG. However, Intralipid and heparin infusion resulted in similar increases in net hepatic gluconeogenic flux in NEFA + GGN and NEFA + HG. Thus elevated NEFA limit the initial increase in glucagon-stimulated HGO by blunting glycogenolysis, without having any effect on the gluconeogenic or glycogenolytic contributions or NHGO thereafter.
The impact of brief reflective responses on student performance

One-minute papers allow students to process what they learned during class and improve student performance. However, this activity can become monotonous and takes significantly longer than the name implies. The research described here tests the effectiveness of a briefer, more flexible version of this technique to increase the perceived relevance of the material and, in turn, performance. Students were randomly assigned to either self-generate a reflective response or answer a content-specific question generated by the instructor at the end of class. Students positively evaluated the brief reflective response activity. Moreover, answering the self-generated reflective responses was associated with greater perceived relevancy of course material to students’ daily lives compared to answering the content-specific questions. Perceived relevancy, in turn, was associated with higher examination grades. Thus, brief reflective responses are a useful tool to increase meaningful connections to course material which enhances examination performance.
Integration of an Inverse Optimal Neural Controller with Reinforced-SLAM for Path Panning and Mapping in Dynamic Environments

This work presents an artificial intelligence approach to solve the problem of finding a path and creating a map in unknown environments using Reinforcement Learning (RL) and Simultaneous Localization and Mapping (SLAM) for a differential mobile robot along with an optimal control system. We propose the integration of these approaches (two of the most widely used ones) for the implementation of robot navigation systems with an efficient method of control composed by a neural identifier and an inverse optimal control in order to obtain a robust and autonomous system of navigation in unknown and dynamic environments.
mutant thioredoxinEscherichia colia [ 2 Fe2 S ] iron – sulfur cluster in an The crystal structure of TrxA ( CACA ) : Insights into the formation of

Escherichia coli thioredoxin is a small monomeric protein that reduces disulfide bonds in cytoplasmic proteins. Two cysteine residues present in a conserved CGPC motif are essential for this activity. Recently, we identified mutations of this motif that changed thioredoxin into a homodimer bridged by a [2Fe-2S] iron–sulfur cluster. When exported to the periplasm, these thioredoxin mutants could restore disulfide bond formation in strains lacking the entire periplasmic oxidative pathway. Essential for the assembly of the iron–sulfur was an additional cysteine that replaced the proline at position three of the CGPC motif. We solved the crystalline structure at 2.3 Å for one of these variants, TrxA(CACA). The mutant protein crystallized as a dimer in which the iron–sulfur cluster is replaced by two intermolecular disulfide bonds. The catalytic site, which forms the dimer interface, crystallized in two different conformations. In one of them, the replacement of the CGPC motif by CACA has a dramatic effect on the structure and causes the unraveling of an extended a-helix. In both conformations, the second cysteine residue of the CACA motif is surface-exposed, which contrasts with wildtype thioredoxin where the second cysteine of the CXXC motif is buried. This exposure of a pair of vicinal cysteine residues apparently allows thioredoxin to acquire an iron–sulfur cofactor at its active site, and thus a new activity and mechanism of action.
First Complete Genome Sequence of a Subdivision 6 Acidobacterium Strain

ABSTRACT Although ubiquitous and abundant in soils, acidobacteria have mostly escaped isolation and remain poorly investigated. Only a few cultured representatives and just eight genomes of subdivisions 1, 3, and 4 are available to date. Here, we determined the complete genome sequence of strain HEG_-6_39, the first genome of Acidobacterium subdivision 6.
Fuzzy-rough approaches for mammographic risk analysis

The accuracy of methods for the assessment of mammographic risk analysis is heavily related to breast tissue characteristics. Previous work has demonstrated considerable success in developing an automatic breast tissue classification methodology which overcomes this difficulty. This paper proposes a unified approach for the application of a number of rough and fuzzy-rough set methods to the analysis of mammographic data. Indeed this is the first time that fuzzy-rough approaches have been applied to this particular problem domain. In the unified approach detailed here feature selection methods are employed for dimensionality reduction developed using rough sets and fuzzy-rough sets. A number of classifiers are then used to examine the data reduced by the feature selection approaches and assess the positive impact of these methods on classification accuracy. Additionally, this paper also employs a new fuzzy-rough classifier based on the nearest neighbour classification algorithm. The novel use of such an approach demonstrates its efficiency in improving classification accuracy for mammographic data, as well as considerably removing redundant, irrelevant, and noisy features. This is supported with experimental application to two well-known datasets. The overall result of employing the proposed unified approach is that feature selection can identify only those features which require extraction. This can have the positive effect of increasing the risk assessment accuracy rate whilst additionally reducing the time required for expert scrutiny, which in-turn means the risk analysis process is potentially quicker and involves less screening.
Development of Vertical Power-Assisted Crane System Considering Absolute Stability

In this paper, a vertical power-assisted crane system is proposed. The purpose of this research is to develop a crane system which reduces the operator's burden by power-assisted functions and facilitates the intuitive operation of a heavy object by direct manual manipulation. First, the structure of this system is described, and an analytical optimal controller is designed to stabilize the system under the model uncertainty and to optimize response. Second, "the limit-cycle problem" when an object contacts the ground is pointed out, and the condition for the attenuation of the limit-cycle is discussed. Finally, the usefulness of the proposed controller is demonstrated by an actual power-assisted crane system
Some Environmental Factors Affecting the Morphology of Streptococcus mutans 10449

This Thesis is brought to you for free and open access by the Theses and Dissertations at Loyola eCommons. It has been accepted for inclusion in Master's Theses by an authorized administrator of Loyola eCommons. For more information, please contact ecommons@luc.edu. Dedication To all the good people in my life. Acknowledgements I would like to thank Dr. Dale Birdsell for his guidance, his faith in my abilities and his friendship. To Dr. Tadayo Hashimoto goes my deepest gratitude and thanks for his help and guidance during the completion of this thesis. My thanks and appreciation to Dr. H. J. Blumenthal and Dr. R. J. Doyle for the time and effort they spend in critical evaluation of my work. Finally, my thanks to Mrs. T. Hashimoto for her generosity and skill in preparing the figures used in this thesis and to Christine Kallal for typing the manuscript.
How Can Dolphins Recognize Fish According to Their Echoes? A Statistical Analysis of Fish Echoes

Echo-based object classification is a fundamental task of animals that use a biosonar system. Dolphins and porpoises should be able to rely on echoes to discriminate a predator from a prey or to select a desired prey from an undesired object. Many studies have shown that dolphins and porpoises can discriminate between objects according to their echoes. All of these studies however, used unnatural objects that can be easily characterized in human terminologies (e.g., metallic spheres, disks, cylinders). In this work, we collected real fish echoes from many angles of acquisition using a sonar system that mimics the emission properties of dolphins and porpoises. We then tested two alternative statistical approaches in classifying these echoes. Our results suggest that fish species can be classified according to echoes returning from porpoise- and dolphin-like signals. These results suggest how dolphins and porpoises can classify fish based on their echoes and provide some insight as to which features might enable the classification.
A system for automatic broadcast news summarisation, geolocation and translation

An increasing amount of news content is produced in audiovideo form every day. To effectively analyse and monitoring this multilingual data stream, we require methods to extract and present audio content in accessible ways. In this paper, we describe an end-to-end system for processing and browsing audio news data. This fully automated system brings together our recent research on audio scene analysis, speech recognition, summarisation, named entity detection, geolocation, and machine translation. The graphical interface allows users to visualise the distribution of news content by entity names and story location. Browsing of news events is facilitated through extractive summaries and the ability to view transcripts in multiple languages.
High resolution 21 cm mapping of the Ursa Major Galactic cirrus: Power spectra of the high-latitude HI gas

We present a power spectrum analysis of interferometric 21 cm observations of the Ursa Major high-latitude cirrus, obtained with the Dominion Radio Astrophysical Observatory (DRAO) of Penticton (Canada). These high-resolution data reveal the intricate structure of the diffuse Galactic H, at angular scales from 1 arcmin to 3 degrees. A filtering method based on a wavelet decomposition was used to enhance the signal-to-noise ratio of the data. The power spectra of the integrated emission and of the centroid velocity fields were used to deduce the three-dimensional (3D) spectral index of the density and velocity fields of the H cirrus. The spectral index is similar for the 3D density and velocity fields with a value of −3.6 ± 0.2. Using the Leiden/Dwingeloo observations, this analysis was extended to the whole North Celestial Loop (which includes the Ursa Major cirrus), showing that the scaling laws prevail from 0.1 to 25 pc. The centroid velocity and integrated emission fields show moderate correlation, with a maximum cross-correlation value of 0.44.
CS 221 Othello Report Demosthenes

This report is intended to inform the reader about our experiences and strategies in programming an artificially intelligent Othello client. More specifically, we will describe what went right, what went wrong, and what we would do if we were to do it again. There is a brief discussion on various searching, training, and evaluation techniques, accompanied by analysis on what we found to work the best. The last section provides some thoughts on future work and extension.
Composite Kernels for Fusing Colour Information in Face Verification Systems

In this work, a novel method of fusing colour information in feature level is proposed considering a face verification system. For this purpose, composite kernels which have been already used in Support Vector Machine classifier is applied within the framework of the Generalised Discriminant Analysis (GDA) algorithm. The performance of the resulting system is evaluated using the XM2VTS face database and its associated experimental protocols. Our experiments show that by combining colour information using the proposed approach the good classification performance demonstrated by the kernel based methods can be further improved.
Visual Information Fidelity in evaluating Retinex enhancement algorithms

Developing image enhancement algorithms require that there exists a proper evaluation scheme to compare different algorithms. Most objective algorithms fail because they are not designed for the subjective nature of the enhancement problem. This necessitates an evaluation scheme that would correlate with scores provided by a group of human observers. In this paper, we consider the quality assessment of images which are visually improved using various versions of Retinex algorithm. The objective of this paper is twofold. To check the suitability of available current distortion based quality assessment methods to evaluate nonlinear image enhancement algorithms and to check if consistently better objective scores are obtained for better Retinex algorithms. To this end, we find correlation between mean opinion score obtained from subjective evaluation and objective quality score for each of the methods under consideration.
In-person vs. eHealth Mindfulness-based Intervention for Adolescents with Chronic Illnesses: A Pilot Randomized Trial

Mindfulness-Based Interventions (MBIs) can improve mental health and well-being in adolescents with chronic illnesses. However, there are many barriers such as reduced mobility and distance which compromise accessibility to MBIs. The aim of this study was to determine the effectiveness of the Mindful Awareness and Resilience Skills for Adolescents (MARS-A) program in youth with chronic illnesses delivered in person or via eHealth. In this mixed method randomized controlled trial, participants received weekly 90- minute long MARS-A sessions for 8 weeks, either in person or via a secure eHealth audiovisual platform allowing group interactions in real time. Data was collected at baseline, immediately after and two months post-MBI through saliva analyses, electronic participant logs and validated questionnaires assessing mindfulness skills and mental health outcomes. Seven participants per group completed the intervention (total n=14, completion rate 77.8%). Paired t-test analyses revealed a significant reduction in depression/anxiety scores immediately post-intervention (p=0.048, Cohen’s d=0.934) and a significant reduction in pre-post mindfulness cortisol levels at week 8 (p=0.022, Cohen’s d=0.534) in the eHealth group. Frequency and duration of weekly individual home practice (eHealth: 6.5 times; 28.8 minutes; in-person: 6.0 times; 30.6 minutes) were similar in both groups and maintained at follow-up. This is the first study comparing in-person and eHealth delivery of an 8-week MBI for adolescents with chronic illnesses. Although the study was limited by the small size of the sample, our results suggest that eHealth delivery of MBIs may represent a promising avenue for increasing availability in this population.
The p 38 MAPK , CaMK and calcineurin-mediated signaling pathways transcriptionally regulate myogenin expression

1. Department of Biochemistry, Hong Kong University of science & Technology, Clear Water Bay, Kowloon, Hong Kong, Peoples Republic of China. 2. School and Department of medicine, University of California, San Diego, La Jolla, CA 92095, USA. 3. Department of Oncology, University of Western Ontario, London, Ontario, Canada N6A, 4L6. 4. Molecular Oncology Group, Department of Medicine, McGill University Health Center, Montreal, Quebec, Canada H3A, 1A1.
QR Factorization for the CELL Processor – LAPACK Working Note 201

The QR factorization is one of the most important operations in dense linear algebra, offering a numerically stable method for solving linear systems of equations including overdetermined and underdetermined systems. Classic implementation of the QR factorization suffers from performance limitations due to the use of matrix-vector type operations in the phase of panel factorization. These limitations can be remedied by using the idea of updating of QR factorization, rendering an algorithm, which is much more scalable and much more suitable for implementation on a multi-core processor. It is demonstrated how the potential of the CELL processor can be utilized to the fullest by employing the new algorithmic approach and successfully exploiting the capabilities of the CELL processor in terms of Instruction Level Parallelism and Thread-Level Parallelism.
MS-LESION SEGMENTATION IN MRI WITH RANDOM FORESTS

Multiple sclerosis (MS) is a common autoimmune disorder, whose diagnosis and study often relies on the extraction of biomarkers from magnetic resonance imaging (MRI) scans. Manual segmentation of MS lesions suffers from large intraand inter-rater differences, whereas automatic methods promise reproducibility and enhanced consistency, especially for tracking the disease progress over time. To test this claim, the ISBI 2015 Longitudinal MS Lesion Segmentation Challenge provides a platform to compare existing methods in a fair and consistent manner to each other and the manual approach. In this article, we present our challenge contribution, which is based on random forests and local context intensity features to segment MS lesions in multi-spectral MRI images.
The GridPACK#8482; toolkit for developing power grid simulations on high performance computing platforms

This paper describes the GridPACK#8482; framework, which is designed to help power grid engineers develop modeling software capable of running on high performance computers. The framework contains modules for setting up distributed power grid networks, assigning buses and branches with arbitrary behaviors to the network, creating distributed matrices and vectors, using parallel linear and non-linear solvers to solve algebraic equations, and mapping functionality to create matrices and vectors based on properties of the network. In addition, the framework contains additional functionality to support IO and to manage errors. The goal of GridPACK#8482; is to provide developers with a comprehensive set of modules that can substantially reduce the complexity of writing software for parallel computers while still providing efficient and scalable software solutions.
Developing business advantages from the technological possibilities of enterprise information systems

Organizations are increasingly implementing Enterprise Information Systems (EIS), and Enterprise Resource Planning (ERP) systems in particular. Despite the notable studies on the advantages of an EIS, many organizations are not satisfied with the benefits or advantages gained. At the same time, it is assumed that such systems with increasing innovations and technological enhancements would generate abundant business advantages, if organizations exploited these opportunities. The investigation in this work drew on the sociomateriality perspective, using imbrication notion, and focused on a telecomm case study to examine how organizations can exploit the technological possibilities of an EIS to create business benefits. The study findings suggest that business benefits can be achieved when the EIS as a technical system is interwoven with the organizational work in which both dynamically change in practice (not from the technical features of the system), when the system provides interesting and beneficial technological possibilities that attract organizations, and when the firm has the organizational capabilities to translate these possibilities into real business benefits.
3D localization technique for broad band impulsive noise source

This paper presents a three-dimensional (3D) localization system for locating partial discharge (PD) on high-voltage apparatuses. An antenna array consisted of four sensors is employed to record the electromagnetic waves (EM) emitted from PD. The localization algorithm is based on the time difference of arrival (TDOA) of the signals. The TDOAs can be determined using the cross-correlation method, peak detection method, Akaike Information Criterion (AIC) method, Energy Criterion (EC) method, Gabor Centroid method, and/or threshold detection method. These system use two kind of antenna configurations. The first configuration is squared array with distance between antennas are 2 meter, and the second configuration is squared array with distance between antennas are 4 meter. In experimental setup, the implemented configuration is the first configuration, due to limitation of the experiment area. The effectiveness of the location method is tested through a computer simulation and the results are presented. From simulation result, the second configuration gives 11.12% better accuracy than the first configuration.
Simvastatin Ameliorates Matrix Stiffness-Mediated Endothelial Monolayer Disruption

Arterial stiffening accompanies both aging and atherosclerosis, and age-related stiffening of the arterial intima increases RhoA activity and cell contractility contributing to increased endothelium permeability. Notably, statins are 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase inhibitors whose pleiotropic effects include disrupting small GTPase activity; therefore, we hypothesized the statin simvastatin could be used to attenuate RhoA activity and inhibit the deleterious effects of increased age-related matrix stiffness on endothelial barrier function. Using polyacrylamide gels with stiffnesses of 2.5, 5, and 10 kPa to mimic the physiological stiffness of young and aged arteries, endothelial cells were grown to confluence and treated with simvastatin. Our data indicate that RhoA and phosphorylated myosin light chain activity increase with matrix stiffness but are attenuated when treated with the statin. Increases in cell contractility, cell-cell junction size, and indirect measurements of intercellular tension that increase with matrix stiffness, and are correlated with matrix stiffness-dependent increases in monolayer permeability, also decrease with statin treatment. Furthermore, we report that simvastatin increases activated Rac1 levels that contribute to endothelial barrier enhancing cytoskeletal reorganization. Simvastatin, which is prescribed clinically due to its ability to lower cholesterol, alters the endothelial cell response to increased matrix stiffness to restore endothelial monolayer barrier function, and therefore, presents a possible therapeutic intervention to prevent atherogenesis initiated by age-related arterial stiffening.