Miracle-dz/UniFAR-FTUs huggingface dataset:
Glucagon-Like Peptide 1 Reduces Endothelial Dysfunction, Inflammation, and Oxidative Stress Induced by Both Hyperglycemia and Hypoglycemia in Type 1 Diabetes

OBJECTIVE Hyperglycemia and hypoglycemia currently are considered risk factors for cardiovascular disease in type 1diabetes. Both acute hyperglycemia and hypoglycemia induce endothelial dysfunction and inflammation, raising the oxidative stress. Glucagon-like peptide 1 (GLP-1) has antioxidant properties, and evidence suggests that it protects endothelial function. RESEARCH DESIGN AND METHODS The effect of both acute hyperglycemia and acute hypoglycemia in type 1 diabetes, with or without the simultaneous infusion of GLP-1, on oxidative stress (plasma nitrotyrosine and plasma 8-iso prostaglandin F2alpha), inflammation (soluble intercellular adhesion molecule-1 and interleukin-6), and endothelial dysfunction has been evaluated. RESULTS Both hyperglycemia and hypoglycemia acutely induced oxidative stress, inflammation, and endothelial dysfunction. GLP-1 significantly counterbalanced these effects. CONCLUSIONS These results suggest a protective effect of GLP-1 during both hypoglycemia and hyperglycemia in type 1 diabetes.
Journal of Economic Behavior & Organization a Lifecycle Perspective of Stock Market Performance and Wellbeing ଝ

We estimate the effect of stock market fluctuations on subjective wellbeing and mental health using Australian survey data over the period 2001–2012, which includes the global financial crisis. A particular innovation of the paper is the use of three satisfaction measures – overall, financial, employment – and the use of a stylised lifecycle investment model. These features, coupled with a robust identification strategy based on comparing survey respondents interviewed in the same quarter and location, allow us to better understand individual reactions to stock market changes. We find that stock market increases lead to a significant but modest improvements in life satisfaction and mental health. This effect is driven by young and middle-aged males, and is stronger for those with direct exposure to the stock market. For young cohorts, the stock market index acts as a leading indicator of employment prospects, whilst for older cohorts it acts directly on financial satisfaction.
Music/Voice Separation Using the Similarity Matrix

Repetition is a fundamental element in generating and perceiving structure in music. Recent work has applied this principle to separate the musical background from the vocal foreground in a mixture, by simply extracting the underlying repeating structure. While existing methods are effective, they depend on an assumption of periodically repeating patterns. In this work, we generalize the repetitionbased source separation approach to handle cases where repetitions also happen intermittently or without a fixed period, thus allowing the processing of music pieces with fast-varying repeating structures and isolated repeating elements. Instead of looking for periodicities, the proposed method uses a similarity matrix to identify the repeating elements. It then calculates a repeating spectrogram model using the median and extracts the repeating patterns using a time-frequency masking. Evaluation on a data set of 14 full-track real-world pop songs showed that use of a similarity matrix can overall improve on the separation performance compared with a previous repetition-based source separation method, and a recent competitive music/voice separation method, while still being computationally efficient.
Influence of Students' Characteristics on E- textbook Experiences: The Moderating Effects of Technology Savvy and Gender

The adoption of electronic textbooks in universities by the majority of students has yet to materialize, requiring a better understanding of the differences among individual users to customize its design and support. The main focus of this study is to examine the role of technology savvy in terms of the experiences, skills and self-efficacy of students in using information technologies. It is hypothesized that technology savvy moderates the relationships among E-textbook Helpfulness, Student Involvement and Learning Outcome. Based on the data gathered through a survey, the results suggest that the e-textbook experiences of students vary significant across technology veterans and novices. In particular, the mediating relationship between E-textbook Helpfulness and Learning Outcome through Student Involvement is stronger for users with higher technology savvy. An additional comparison based on gender is performed to find out whether the gender stereotyping regarding technology preference holds true for the new generation of students impacting the relationship between technology savvy and e-textbook preferences. The results show that gender does not fully account for the differences in technology savvy, and its moderating effects on E-textbook experiences are quite different from those of technology savvy.
Carers’ experiences accessing information on supports and services: Learning the social care “dance”

Cities across England will see a growing number of informal carers as the population ages, many of whom do not begin this role equipped with the knowledge they need to access social care services and supports. One of the more significant changes brought by passage of the Care Act of 2014 is local governments’ increased responsibility to improve the provision of information and advice on social care to informal carers, long recognized as a policy priority. To better understand where improvements can be made on a local level in order to achieve the goals laid out in the Care Act, this study considers carers’ experiences accessing information and advice on social care services and supports in a city with a population of over 250,000 in the south of England. This was done through the collection of semi-structure qualitative interviews with 11 carers to people aged 65 and older from April 2015 to July 2015. Thematic analysis of interviews revealed a tension between carers’ varying levels of knowledge and experience with the social care system and information services’ one-size-fits-all approach to providing information. Findings suggest local governments should focus on creating information services that more actively reach out to carers, provide greater guidance to those carers who need it, and work to flexibly meet informal carers information needs, acknowledging that some carers will be less familiar than others with aspects of the social care system.
Vehicle localization using road markings

Reliable lane-level localization is a requirement for many driver-assistance methods as well as for autonomous driving. Localization using cameras is desirable due to ubiquity and cheapness of sensors but is hard to achieve reliably. We propose a method towards reliable visual localization using traffic signs painted on the road such as arrows, pedestrian crossings, and speed limits. These road markings are relatively easily detected since they are designed to be highly conspicuous. Our method automatically recognizes road markings and uses features detected within them to compute the location of the vehicle. This provides an absolute global localization if the road markings have been surveyed before hand, and relative positioning information otherwise. We demonstrate using experiments and with groundtruth data that our method provides accurate lane-level visual localization under various lighting conditions and using various types of road markings.
On-demand Injection of Lexical Knowledge for Recognising Textual Entailment

We approach the recognition of textual entailment using logical semantic representations and a theorem prover. In this setup, lexical divergences that preserve semantic entailment between the source and target texts need to be explicitly stated. However, recognising subsentential semantic relations is not trivial. We address this problem by monitoring the proof of the theorem and detecting unprovable sub-goals that share predicate arguments with logical premises. If a linguistic relation exists, then an appropriate axiom is constructed on-demand and the theorem proving continues. Experiments show that this approach is effective and precise, producing a system that outperforms other logic-based systems and is competitive with state-of-the-art statistical methods.
Approximate pattern matching using the Burrows-Wheeler transform

Summary form only given. The approximate pattern matching on the text transformed by the Burrows-Wheeler transform (BWT) was considered. This is an important first step towards developing a compressed pattern matching algorithm for the BWT based compression system. Algorithms are proposed to solve the K-mismatch problem. Tests were performed on different pattern lengths using 133 selected files from the Canterbury, Calgary, and TREC corpus. The results on the K-mismatch pattern matching show that the running time and storage are superior to the fast suffix tree approach. Thus, once the index arrays are created, for repeated pattern search operations and for long patterns, the proposed algorithms perform significantly better than the agrep and ngrep. Using DFA verification, the search time is almost constant. The amortized cost is lower for multiple patterns search operations.
A multi-label classification approach for the detection of broken bars and mixed eccentricity faults using the start-up transient

In this article a data driven approach for the classification of simultaneously occurring faults in an induction motor is presented. The problem is treated as a multi-label classification problem with each label corresponding to one specific fault, using the power-set approach. The faulty conditions examined, include the existence of a broken bar fault and the presence of mixed eccentricity with various degrees of static and dynamic eccentricity. For the feature extraction stage, the time-frequency representation, resulting from the application of the short time Fourier transform of the start-up current is exploited. The proposed approach is validated using simulation data with promising results.
Monocular Human Motion Tracking with Non-Connected Body Part Dependency

2D articulated human pose tracking in monocular image sequences remains an extremely challenging task due to background cluttering, variation in body appearance, occlusion and imaging conditions. Most of the current approaches only deal with simple appearance and adjacent or connected body part dependencies, especially the tree-structured priors assumed over body part connections. Such prior excludes the dependencies between non-connected body parts which could actually contribute to tracking accuracies. Building on the successful pictorial structures model, we propose a novel framework for human pose tracking including more dependencies of non-connected body parts. In order to implement inference efficiently for the proposed model, we introduce a factor graph to factorize all the unary term and all dependencies that are modelled in the pairwise term of the proposed model. In this paper, we also observe that the posterior marginals of each part from the tree structure model satisfy a Gaussian distribution. Based on this property, the sampling procedure becomes straight-forward and the search space can be shrunk effectively. We incorporate a simple motion constraint to capture the temporal continuity of body parts between frames, since the positions/orientations of body parts usually change smoothly between consecutive frames. In addition, we introduce a full body detector as the first step of our framework to reduce the search space for pose tracking. We also exploit the temporal continuity of body parts between frames by incorporating constraints on the location distance and the orientation difference for each body part between two successive frames. We evaluate our framework on two challenging image sequences and conduct a series of experiments to compare the performance with the approaches based on the tree-based model. The results illustrate that the proposed framework improves the performance significantly.
Identifying gene-Specific Variations in Biomedical Text

The influence of genetic variations on diseases or cellular processes is the main focus of many investigations, and results of biomedical studies are often only accessible through scientific publications. Automatic extraction of this information requires recognition of the gene names and the accompanying allelic variant information. In a previous work, the OSIRIS system for the detection of allelic variation in text based on a query expansion approach was communicated. Challenges associated with this system are the relatively low recall for variation mentions and gene name recognition. To tackle this challenge, we integrate the ProMiner system developed for the recognition and normalization of gene and protein names with a conditional random field (CRF)-based recognition of variation terms in biomedical text. Following the newly developed normalization of variation entities, we can link textual entities to Single Nucleotide Polymorphism database (dbSNP) entries. The performance of this novel approach is evaluated, and improved results in comparison to state-of-the-art systems are reported.
Progressive design: staged evolution of scenarios in the design of a collaborative science learning environment

Scenario-based esign techniques are increasingly popular in KC1 design Although many techniques exist, we see a growing demand for more structured and systematic methods of scenario generation and development. This paper describes a case study in which a collaborative science learning environment was designed using an evolutionary scenario-based design approach. The case study has attempted to make consistent use of scenarios and claims as design representations, to integrate the desigu aE both the system and the activities that incorporate if and to evolve design in an organized and principled manner. We have termed this approach progressive cbesign.
The Big Five, Learning Goals, Exam Preparedness, and Preference for Flipped Classroom Teaching: Evidence from a Large Psychology Undergraduate Cohort

Previous research has found that the flipped classroom (i.e., learning prior to the lecture, and using the lecture time for consolidating knowledge) increases students’ deep learning, and has an association with improved grades. However, not all students benefit equally from flipping the classroom, and there may be important individual differences that influence preference for different teaching styles. In the present study, undergraduate Psychology students (n = 200) answered questions about exam preparedness, learning goals, preference for the traditional or flipped classroom, and the Big Five of personality. We found that preference for the flipped classroom had a significant, positive association with agreeableness and the mastery goal. Preference for the traditional lecture was predicted by beliefs about exam preparedness. The results are discussed with a reference to the Big Five paradigm in the context of learning and teaching.
Systems to Support Decision Making

Both advisory systems and expert systems provide expertise to support decision making in a myriad of domains. Expert systems are used to solve problems in well defined, narrowly focused problem domains, whereas advisory systems are designed to support decision making in more unstructured situations which have no single correct answer. This paper provides an overview of advisory systems, which includes the organizational needs that they address, similarities and differences between expert and advisory systems, and the supportive role advisory systems play in unstructured decision making.
Three Paradigms for Selective Attention in Vision

Three Paradigms for Selective Attention in Vision Serap Yiğit Elliott Chair of the Supervisor Committee Professor John C. Palmer Psychology The first study investigated the underlying mechanisms of selective attention and the extent of which an irrelevant stimulus is processed as well as the nature of this processing. A spatial filtering paradigm was used to quantify the effects of an irrelevant stimulus in a selective attention task (Chapter 1). The results have shown that if the task requires observers to constrain their attention to a small spatial area, a blocking mechanism is used for selection. In blocking, unattended stimuli are blocked from further processing. If the task requires observers to distribute their attention to a large spatial area, an attenuation mechanism is used for selection. In attenuation, the unattended stimuli are reduced in strength, but at high intensities (e.g., high contrast), they can still have access to further processing. In the second study, the same paradigm was used with the combination of many-to-one response mapping of the flanker paradigm to unravel the nature of the effects of irrelevant stimuli on the judgment of a relevant stimulus (Chapter 2). The results have shown that the effects of irrelevant stimuli are consistent with a failure of selection, which is an example of blocking mechanism.
Integrated RNA-Seq and sRNA-Seq Analysis Identifies Chilling and Freezing Responsive Key Molecular Players and Pathways in Tea Plant (Camellia sinensis)

Tea [Camellia sinensis (L) O. Kuntze, Theaceae] is one of the most popular non-alcoholic beverages worldwide. Cold stress is one of the most severe abiotic stresses that limit tea plants’ growth, survival and geographical distribution. However, the genetic regulatory network and signaling pathways involved in cold stress responses in tea plants remain unearthed. Using RNA-Seq, DGE and sRNA-Seq technologies, we performed an integrative analysis of miRNA and mRNA expression profiling and their regulatory network of tea plants under chilling (4℃) and freezing (-5℃) stress. Differentially expressed (DE) miRNA and mRNA profiles were obtained based on fold change analysis, miRNAs and target mRNAs were found to show both coherent and incoherent relationships in the regulatory network. Furthermore, we compared several key pathways (e.g., ‘Photosynthesis’), GO terms (e.g., ‘response to karrikin’) and transcriptional factors (TFs, e.g., DREB1b/CBF1) which were identified as involved in the early chilling and/or freezing response of tea plants. Intriguingly, we found that karrikins, a new group of plant growth regulators, and β-primeverosidase (BPR), a key enzyme functionally relevant with the formation of tea aroma might play an important role in both early chilling and freezing response of tea plants. Quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR) analysis further confirmed the results from RNA-Seq and sRNA-Seq analysis. This is the first study to simultaneously profile the expression patterns of both miRNAs and mRNAs on a genome-wide scale to elucidate the molecular mechanisms of early responses of tea plants to cold stress. In addition to gaining a deeper insight into the cold resistant characteristics of tea plants, we provide a good case study to analyse mRNA/miRNA expression and profiling of non-model plant species using next-generation sequencing technology.
Gravity-driven Poiseuille Flow in Dilute Gases. Elastic and Inelastic Collisions

An overview of the hydrodynamic profiles derived by kinetic theory tools (Boltzmann equation and kinetic models) for the gravity-driven Poiseuille flow with particles colliding either elastically (planar and cylindrical geometries) or inelastically (planar geometry) is presented. The results obtained through second order in the gravity acceleration show that the Navier-Stokes predictions are qualitatively incorrect over distances of the order of the mean free path, especially in the case of the temperature profile
Computational Auditory Scene Analysis and Automatic Speech Recognition

The human auditory system is, in a way, an engineering marvel. It is able to do wonderful things that powerful modern machines find extremely difficult. For instance, our auditory system is able to follow the lyrics of a song when the input is a mixture of speech and musical accompaniments. Another example is a party situation. Usually there are multiple groups of people talking, with laughter, ambient music and other sound sources running in the background. The input our auditory system receives through the ears is a mixture of all these. In spite of such a complex input, we are able to selectively listen to an individual speaker, attend to the music in the background, and so on. In fact this ability of ‘segregation’ is so instinctive that we take it for granted without wondering about the complexity of the problem our auditory system solves. Colin Cherry, in the 1950s, coined the term ‘cocktail party problem’ while trying to describe how our auditory system functions in such an environment [12]. He did a series of experiments to study the factors that help humans perform this complex task [11]. A number of theories have been proposed since then to explain the observations made in those experiments [11,12,70]. Helmhotz had, in the mid-nineteenth century, reflected upon the complexity of this signal by using the example of a ball room setting [22]. He remarked that even though the signal is “complicated beyond conception,” our ears are able to “distinguish all the separate constituent parts of this confused whole. ” So how does our auditory system solve the so-called cocktail party problem? Bregman tried to give a systematic account in his seminal 1990 book Auditory Scene Analysis [8]. He calls
Neural Mechanisms of Task Failure During Sustained Submaximal Contractions

3 Dedication . 6 Acknowledgments . 7 List of Figures . 9 List of Abbreviations . 12 Chapter 1: Introduction . 13 Background and Significance . 13 Innovation . 17 Assumptions and Limitations . 18 Chapter 2: Review of the Literature . 20 Fatigue . 20 Neurophysiologic methods to measure fatigue . 42 Chapter 3: Cortical and Spinal Mechanisms of Task Failure of Sustained Submaximal Fatiguing Contractions with Different Load Compliances . 70 Abstract . 70 Introduction . 72 Methods . 82 Results . 100 Discussion . 110 Conclusion . 127 Chapter 4: Anodal Transcranial Direct Current Stimulation Enhances Time to Task Failure of a Sustained Submaximal Contraction . 129 Abstract . 129 Introduction . 131 Methods . 135 Results . 145 Discussion . 149 Conclusion . 162 Chapter 5: Conclusions and Future Directions . 165 Conclusions . 165 Future Directions . 172 Summary . 177 References . 179 Figures . 208
GO: : TermFinder--open source software for accessing Gene Ontology information and finding significantly enriched Gene Ontology terms associated with a list of genes

SUMMARY GO::TermFinder comprises a set of object-oriented Perl modules for accessing Gene Ontology (GO) information and evaluating and visualizing the collective annotation of a list of genes to GO terms. It can be used to draw conclusions from microarray and other biological data, calculating the statistical significance of each annotation. GO::TermFinder can be used on any system on which Perl can be run, either as a command line application, in single or batch mode, or as a web-based CGI script. AVAILABILITY The full source code and documentation for GO::TermFinder are freely available from http://search.cpan. org/dist/GO-TermFinder/.