Miracle-dz/UniFAR-FTUs huggingface dataset:
Climatic warming, glacier recession and runoff from Alpine basins after the Little Ice Age maximum

Abstract Records of discharge of rivers draining Alpine basins with between 0 and ~70% ice cover, in the upper Aare and Rhône catchments, Switzerland, for the period 1894–2006 have been examined together with climatic data for 1866–2006, with a view to assessing the effects on runoff from glacierized basins of climatic warming coupled with glacier recession following the Little Ice Age maximum. Annual runoff from ice-free basins reflects precipitation variations, rising from minima between 1880 and 1910 to maxima between the late 1960s and early 1980s. The more highly glacierized the basin, the more runoff mimicked mean May–September air temperature during two periods of warming. Runoff increased gradually from the 1900s, rapidly in the 1940s, before decreasing to the late 1970s. Rising runoff levels during the second warming period failed to exceed those attained during the first, despite higher summer temperatures. Although temperatures continued to rise, discharge from glacierized basins declined after reaching maxima in the late 1980s to early 1990s. In the first warming period, rising specific melt rates augmented by increasing precipitation opposed the impact of declining glacier area on runoff. Although melt continued to increase in the second period, enhanced melting (even in the exceptionally warm summer of 2003) appears to have been insufficient to offset reducing glacier surface area exposed to melt, low or reducing levels of precipitation, and increasing evaporation. Thus runoff from glacierized basins peaked in the late 1940s to early 1950s.
Factors Influencing the Implementation and Use of a Portal for Knowledge Management in Higher Education

This study investigates the factors affecting the implementation and use of a portal to assist knowledge management objectives in higher education. The study explored factors influencing knowledge distribution by deriving a conceptual framework consisting of four (4) dimensions: knowledge volume, knowledge quality, knowledge dissemination, and information system management. This study found that there are many factors influencing the selection and structure of information and knowledge. The importance of information quality was also addressed and the study found that while it is imperative for a portal to focus on quality information, accountability for quality assurance of information rests with organizational policy imperatives. The study explored knowledge dissemination techniques available via portals and identified that personalisation of knowledge is a high priority. The characteristic of a portal to integrate many systems into one central repository and provide users with their personal view of many systems was acknowledged as a productive means to distribute information within a higher education institution.
Novel Gravity Probe B Frame-Dragging Effect

The Gravity Probe B (GP-B) satellite experiment will measure the precession of on-board gyroscopes to extraordinary accuracy. Such precessions are predicted by General Relativity (GR), and one component of this precession is the `frame-dragging' or Lense-Thirring effect, which is caused by the rotation of the earth. A new theory of gravity, which passes the same extant tests of GR, predicts, however, a second and much larger `frame-dragging' precession. The magnitude and signature of this larger effect is given for comparison with the GP-B data.
Semi-Supervised and Latent-Variable Models of Natural Language Semantics

This thesis focuses on robust analysis of natural language semantics. A primary bottleneck for semantic processing of text lies in the scarcity of high-quality and large amounts of annotated data that provide complete information about the semantic structure of natural language expressions. In this dissertation, we study statistical models tailored to solve problems in computational semantics, with a focus on modeling structure that is not visible in annotated text data. We first investigate supervised methods for modeling two kinds of semantic phenomena in language. First, we focus on the problem of paraphrase identification, which attempts to recognize whether two sentences convey the same meaning. Second, we concentrate on shallow semantic parsing, adopting the theory of frame semantics (Fillmore, 1982). Frame semantics offers deep linguistic analysis that exploits the use of lexical semantic properties and relationships among semantic frames and roles. Unfortunately, the datasets used to train our paraphrase and frame-semantic parsing models are too small to lead to robust performance. Therefore, a common trait in our methods is the hypothesis of hidden structure in the data. To this end, we employ conditional loglinear models over structures, that are firstly capable of incorporating a wide variety of features gathered from the data as well as various lexica, and secondly use latent variables to model missing information in annotated data. Our approaches towards solving these two problems achieve state-of-the-art accuracy on standard corpora. For the frame-semantic parsing problem, we present fast inference techniques for jointly modeling the semantic roles of a given predicate. We experiment with linear program formulations, and use a commercial solver as well as an exact dual decomposition technique that breaks the role labeling problem into several overlapping components. Continuing with the theme of hypothesizing hidden structure in data for modeling natural language semantics, we present methods to leverage large volumes of unlabeled data to improve upon the shallow semantic parsing task. We work within the framework of graph-based semi-supervised learning, a powerful method that associates similar natural language types, and helps propagate supervised annotations to unlabeled data. We use this framework to improve frame-semantic parsing performance on unknown predicates that are absent in annotated data. We also present a family of novel
Transferring knowledge from a RNN to a DNN

Deep Neural Network (DNN) acoustic models have yielded many state-of-the-art results in Automatic Speech Recognition (ASR) tasks. More recently, Recurrent Neural Network (RNN) models have been shown to outperform DNNs counterparts. However, state-of-the-art DNN and RNN models tend to be impractical to deploy on embedded systems with limited computational capacity. Traditionally, the approach for embedded platforms is to either train a small DNN directly, or to train a small DNN that learns the output distribution of a large DNN. In this paper, we utilize a state-of-the-art RNN to transfer knowledge to small DNN. We use the RNN model to generate soft alignments and minimize the Kullback-Leibler divergence against the small DNN. The small DNN trained on the soft RNN alignments achieved a 3.93 WER on the Wall Street Journal (WSJ) eval92 task compared to a baseline 4.54 WER or more than 13% relative improvement.
The Sudden Devotion Emotion: Kama Muta and the Cultural Practices Whose Function Is to Evoke It

When communal sharing relationships (CSRs) suddenly intensify, people experience an emotion that English speakers may label, depending on context, “moved,” “touched,” “heart-warming,” “nostalgia,” “patriotism,” or “rapture” (although sometimes people use each of these terms for other emotions). We call the emotion kama muta (Sanskrit, “moved by love”). Kama muta evokes adaptive motives to devote and commit to the CSRs that are fundamental to social life. It occurs in diverse contexts and appears to be pervasive across cultures and throughout history, while people experience it with reference to its cultural and contextual meanings. Cultures have evolved diverse practices, institutions, roles, narratives, arts, and artifacts whose core function is to evoke kama muta. Kama muta mediates much of human sociality.
A Pore Residue of the KCNQ3 Potassium M-Channel Subunit Controls Surface Expression

KCNQ2 (Kv7.2) and KCNQ3 (Kv7.3) are the principal subunits underlying the potassium M-current, which exerts a strong control on neuronal excitability. KCNQ3 subunits coassemble with KCNQ2 to form functional heteromeric channels that are specifically transported to the axonal initial segment and nodes of Ranvier. In contrast, there is no evidence for functional homomeric KCNQ3 channels in neurons, and it appears that these are inefficiently trafficked to the plasma membrane. Among eukaryotic potassium channels, the KCNQ3 subunit is unusual because it has an alanine in place of a threonine at the pore inner vestibule, three residues upstream of the GYG signature sequence of the selectivity filter. This residue is critical for the potentiation of the current after heteromerization, but the mechanism is unknown. We report that the presence of this uncommon residue at position 315 has a strong impact on the stability of the homotetramers and on channel trafficking. Wild-type KCNQ3 expressed alone is retained within the endoplasmic reticulum, and this mechanism is overcome by the substitution of threonine for Ala315. KCNQ3 subunits require assembly with KCNQ2 to exit this compartment, whereas KCNQ3-A315T is no longer dependent on KCNQ2 to form channels that are efficiently trafficked to the plasma membrane. The presence of this alanine, therefore, plays an important role in regulating the subunit composition of functional M-channels expressed at the surface of neurons.
Epidemiology and predictors of short-term mortality in symptomatic venous thromboembolism.

BACKGROUND The epidemiology of symptomatic venous thromboembolism (VTE) in Taiwan has not been well investigated. The aim of this study was to report on the epidemiology and short-term prognosis of symptomatic VTE. METHODS AND RESULTS This nationwide population-based cohort study used the Taiwanese National Health Insurance claims databases to identify adults older than 18 years of age with symptomatic VTE diagnosed in 2002. We investigated the clinical features of VTE and determined independent risk factors of 1-month mortality. A total of 2,774 patients were identified with a mean age of 62.8 years and the female-to-male ratio was 1.15:1. The crude incidence of symptomatic VTE was 16.5 per 100,000 persons, which steadily increased with age, ranging from 4 per 100,000 in patients <40 years old to 108 per 100,000 in patients ≥ 80 years. We observed no seasonal and meteorological variations in the incidence of VTE. The overall 1-month mortality rate was 8.8%, with 7.1% in deep venous thrombosis and 12.9% in pulmonary embolism. Multivariate analysis demonstrated that pulmonary embolism, cancer, neurologic disease with extremity paresis or paralysis, older age, longer hospital stay, and major abdominal and thoracic surgery in the 3 months preceding VTE were independent predictors of 1-month death. CONCLUSIONS Although the incidence of VTE was lower in Taiwanese populations than in Western ones, short-term mortality rates were high in specific populations. These findings suggest optimal treatment is needed in higher-risk patients.
Interventions to improve the labour market situation of adults with physical and/or sensory disabilities in low- and middle-income countries

Disability is a development issue, with widespread poverty, inequality and violation of human rights. Recent estimates suggest that more than one billion people are living with some form of disability. Persons with disabilities are over-represented among the world’s poor, and significant labour market disadvantage helps maintain the link between poverty and disability in many country contexts. The costs of disability are particularly acute in low- and middle-income countries (those with gross national income per capita of less than $12,616), where up to 80% of people with disabilities of working age can be unemployed, around twice that for their counterparts in high-income countries. When people with disabilities do work, they generally do so for longer hours and lower incomes, have fewer chances of promotion, are more likely to work in the informal labour market, and are at greater risk of becoming unemployed for longer periods. The barriers faced by people with disabilities globally in accessing and sustaining paid work is a profound social challenge. There is now growing recognition of employment as a key factor in the process of empowerment and inclusion into society, and the role of interventions to improve labour market outcomes for disabled people is receiving increased international attention. It is therefore both vital and timely to increase understanding of the impacts of available programmes, in order to ensure that they are effective in delivering positive outcomes for people with disabilities and provide value for money. Although several reviews have attempted to summarise the existing research in this area, there are a number of substantive and methodological limitations to these reviews. Thus, there is a need to systematically examine the evidence base to provide an overview of the types of interventions being used to improve employment outcomes, to identify those that are effective and ineffective, and to identify areas in which more research needs to be conducted.
Selective wheat germ agglutinin (WGA) uptake in the hippocampus from the locus coeruleus of dopamine-β-hydroxylase-WGA transgenic mice

We generated transgenic mice in which a trans-synaptic tracer, wheat germ agglutinin (WGA), was specifically expressed in the locus coeruleus (LC) neurons under the control of the dopamine-β-hydroxylase (DBH) gene promoter. WGA protein was produced in more than 95% of the tyrosine hydroxylase (TH)-positive LC neurons sampled. Transynaptic transfer of WGA was most evident in CA3 neurons of the hippocampus, but appeared absent in CA1 neurons. Faint but significant WGA immunoreactivity was observed surrounding the nuclei of dentate granule cells. Putative hilar mossy cells, identified by the presence of calretinin in the ventral hippocampus, appeared uniformly positive for transynaptically transferred WGA protein. GAD67-positive interneurons in the hilar and CA3 regions tended to be WGA-positive, although a subset of them did not show WGA co-localization. The same mixed WGA uptake profile was apparent when examining co-localization with parvalbumin. The selective uptake of WGA by dentate granule cells, mossy cells, and CA3 pyramidal neurons is consistent with evidence for a large proportion of conventional synapses adjacent to LC axonal varicosities in these regions. The lack of WGA uptake in the CA1 region and its relatively sparse innervation by DBH-positive fibers suggest that a majority of the TH-positive classical synapses revealed by electron microscopy in that region may be producing dopamine. The overall pattern of WGA uptake in these transgenic mice implies a selective role for the granule cell-mossy cell-CA3 network in processing novelty or the salient environmental contingency changes signaled by LC activity.
Simultaneous Mechanical Loading and Confocal Reflection Microscopy for Three-Dimensional Microbiomechanical Analysis of Biomaterials and Tissue Constructs

At present, mechanisms by which specific structural and mechanical properties of the three-dimensional extracellular matrix microenvironment influence cell behavior are not known. Lack of such knowledge precludes formulation of engineered scaffolds or tissue constructs that would deliver specific growth-inductive signals required for improved tissue restoration. This article describes a new mechanical loading–imaging technique that allows investigations of structural–mechanical properties of biomaterials as well as the structural–mechanical basis of cell–scaffold interactions at a microscopic level and in three dimensions. The technique is based upon the integration of a modified, miniature mechanical loading instrument with a confocal microscope. Confocal microscopy is conducted in a reflection and/or fluorescence mode for selective visualization of load-induced changes to the scaffold and any resident cells, while maintaining each specimen in a “live,” fully hydrated state. This innovative technique offers several advantages over current biomechanics methodologies, including simultaneous visualization of scaffold and/or cell microstructure in three dimensions during mechanical loading; quantification of macroscopic mechanical parameters including true stress and strain; and the ability to perform multiple analyses on the same specimen. This technique was used to determine the structural–mechanical properties of three very different biological materials: a reconstituted collagen matrix, a tissue-derived biomaterial, and a tissue construct representing cells and matrix.
"It's all part of the job": Everyday silencing in the life of a secondary school teacher

This article examines the issue of racial silencing in mainstream education by analysing four autoethnographic vignettes based on the authors’ teaching experiences. The methodology draws attention to the underlying racial assumptions that underpin the everyday of teachers’ working lives, thus demonstrating how silencing serves to perpetuate the interests of Päkehä culture. We argue that mainstream pedagogical approaches to culture and ethnicity also contribute to the phenomenon of silencing, and assert that racialised students will continue to be disenfranchised in mainstream schools unless researchers, teachers and administrators are prepared to “see” how issues of race inform the daytoday experiences of a teacher’s working life.
A Comprehensive Evaluation of a Novel Approach to Probabilistic Information Extraction from Large Unstructured Datasets

In this paper, we discuss the evaluation of the probabilistic extraction as introduced in [1], by considering three different datasets introduced in [1] - [3]. the results show the potential of the approach, as well as its reliability and efficiency when analyzing datasets with different properties and structures. This is part of ongoing research aiming to provide a tool to extract, assess and visualize intelligence extracted from large unstructured datasets.
Interaction Between Modules in Learning Systems for Vision Applications

Complex vision tasks such as event detection in a surveillance video can be divided into subtasks such as human detection, tracking, and trajectory analysis. The video can be thought of as being composed of various features. These features can be roughly arranged in a hierarchy from low level features to high-level features. Low-level features include edges and blobs, and high-level features include objects and events. Loosely, the low-level feature extraction is based on signal/image processing techniques, while the high-level feature extraction is based on machine learning techniques. Traditionally, vision systems extract features in a feedforward manner on the hierarchy; that is, certain modules extract low-level features and other modules make use of these low-level features to extract high-level features. Along with others in the research community we have worked on this design approach. We briefly present our work on object recognition and multiperson tracking systems designed with this approach and highlight its advantages and shortcomings. However, our focus is on system design methods that allow tight feedback between the layers of the feature hierarchy, as well as among the high-level modules themselves. We present previous research on systems with feedback and discuss the strengths and limitations of these approaches. This analysis allows us to develop a new framework for designing complex vision systems that allows tight feedback in a hierarchy of features and modules that extract these features using a graphical representation. This new framework is based on factor graphs. It relaxes some of the constraints of the traditional factor graphs and replaces its function nodes by modified versions of some of the modules that have been developed for specific vision tasks. These modules can be easily formulated by slightly modifying modules developed for specific tasks in other vision systems, if we can match the input and output variables to variables in our graphical structure. It also draws inspiration from product of experts and Free Energy view of the EM algorithm. We present experimental results and discuss the path for future development.
Inhibition of NADPH oxidase improves impaired reactivity of pial arterioles during chronic exposure to nicotine.

Our goals were to determine whether chronic exposure to nicotine alters nitric oxide synthase (NOS)-dependent reactivity of cerebral (pial) arterioles and to identify a potential role for NADPH oxidase in impaired NOS-dependent responses during chronic exposure to nicotine. We measured in vivo diameter of pial arterioles to NOS-dependent (acetylcholine and ADP) and -independent (nitroglycerin) agonists in saline-treated rats and rats chronically treated with nicotine (2 mg.kg(-1). day(-1) for 2 wk via an osmotic minipump). We found that NOS-dependent, but not -independent, vasodilatation was impaired in nicotine-treated compared with saline-treated rats. In addition, the production of superoxide anion (lucigenin chemiluminescence) was increased in rats treated with nicotine compared with saline-treated rats. Furthermore, using Western blot analysis, we found that chronic exposure to nicotine increased p47phox protein in the parietal cortex. Finally, we found that apocynin (40 mg.kg(-1). day(-1)) in the drinking water to inhibit NADPH oxidase alleviated impaired NOS-dependent cerebral vasodilatation in nicotine treated rats but did not alter NOS-dependent responses in saline treated rats and did not alter NOS-independent reactivity in saline- or nicotine-treated rats. These findings suggest that chronic exposure to nicotine impairs NOS-dependent dilatation of pial arterioles by a mechanism that appears to be related to the formation of superoxide anion via activation of NADPH oxidase.
A Coverage-Based Approach to Recommendation Diversity On Similarity Graph

We consider the problem of generating diverse, personalized recommendations such that a small set of recommended items covers a broad range of the user's interests. We represent items in a similarity graph, and we formulate the relevance/diversity trade-off as finding a small set of unrated items that best covers a subset of items positively rated by the user. In contrast to previous approaches, our method does not rely on an explicit trade-off between a relevance objective and a diversity objective, as the estimations of relevance and diversity are implicit in the coverage criterion. We show on several benchmark datasets that our approach compares favorably to the state-of-the-art diversification methods according to various relevance and diversity measures.