Miracle-dz/UniFAR-FTUs huggingface dataset:
Opening Our Eyes: How Activist Women in Ecuador Learn Critical Political and Self-Aware Consciousness

This dissertation seeks to answer two questions: “H ow are different aspects of consciousness learned and relearned by members of women’s organiz ations in Ecuador? ” and “How do women’s critical political and self-aware conscious ne ses impact their organizations and their ability to build relationships based on solidarity? ” Critical political consciousness is defined as awareness of hegemonic social structures and their relationship to intersectional embodied identities, accompanied by a desire for equality an d justice. Critical self-aware consciousness is understood as awareness of: one’s own public and su bjective identities; agency; how life experiences affect different aspects of the self; a nd the interconnectedness of individuals, communities, and the Pacha Mama (Kichwa for Mother Nature or Mother Universe). I combined participant observation, interview, focu s group, survey and photovoice methods to research local, regional, and national level organi z tions in Ecuador between 2010 and 2013. To examine how activists can better concientizar (rais e the consciousness of) their members, I draw on sociocultural learning theory to analyze how ide ntity, consciousness and epistemological ignorance are learned, unlearned and relearned. I interrogate how women learn to code their surroundings; attain language and other tools as th ey become part of communities of practice of girls, women, and organizations, oppressed or privi leged communities; and as they learn different types of consciousness. I examine how le arning is facilitated by individuals’ openness to new perspectives and pedagogies that teach the w hole person (including mind, body, emotions and spirit) in connection to her community. I find that consciousness is contradictory. People think and act from the social location corresponding to their intersectional embodied iden titi s, internalizing hegemonic social forces’
A Model Based Approach For Regression Testing Utilizing Distributed Architecture

The explosive growths in the usage of object oriented programming in the development of large applications have put extensive pressure in testing and maintenance of these systems. A graphical representation for these programs has the advantage of lending to efficient analysis compared to code based textual analysis. The Class Dependence Graph (ClDG) is insufficient to capture the features of real time safety critical object oriented program. We extend the basic ClDG to incorporate features like control flow and exception handling, timing, criticality, method sequences and sate information. The model that we have developed can easily be subjected to automated analysis for establishing points within a program that needs to be tested when the program is subjected to changes. General Terms ClDG, Regression Testing, Distributed Systems, Model-Based Regression Testing
The unusual microtubule polarity in teleost retinal pigment epithelial cells

In cells of the teleost retinal pigment epithelium (RPE), melanin granules disperse into the RPE cell's long apical projections in response to light onset, and aggregate toward the base of the RPE cell in response to dark onset. The RPE cells possess numerous microtubules, which in the apical projections are aligned longitudinally. Nocodazole studies have shown that pigment granule aggregation is microtubule- dependent (Troutt, L. L., and B. Burnside, 1988b Exp. Eye Res. In press.). To investigate further the mechanism of microtubule participation in RPE pigment granule aggregation, we have used the tubulin hook method to assess the polarity of microtubules in the apical projections of teleost RPE cells. We report here that virtually all microtubules in the RPE apical projections are uniformly oriented with plus ends toward the cell body and minus ends toward the projection tips. This orientation is opposite that found for microtubules of dermal melanophores, neurons, and most other cell types.
Self-whitening algorithms for adaptive equalization and deconvolution

In equalization and deconvolution tasks, the correlated nature of the input signal slows the convergence speeds of stochastic gradient adaptive filters. Prewhitening techniques have been proposed to improve the convergence performance, but the additional coefficient memory and updates for the prewhitening filter can be prohibitive in some applications. We present two simple algorithms that employ the equalizer as a prewhitening filter within the gradient updates. These self-whitening algorithms provide quasi-Newton convergence locally about the optimum coefficient solution for deconvolution and equalization tasks. Multichannel extensions of the techniques are also described.
Modeling data dissemination in online social networks: a geographical perspective on bounding network traffic load

In this paper, we model the data dissemination in online social networks (OSNs) and study the scaling laws of traffic load. We propose a three-layered system model to formulate data dissemination sessions for social applications in OSNs. The layered model consists of the physical network layer, social relationship layer, and application session layer. By analyzing mutual relevances among these three layers, we investigate the geographical distribution feature of dissemination sessions in OSNs. Based on this, we derive the traffic load of OSNs under a realistic assumption that every source sustains a data generating rate of constant order. To the best of our knowledge, this is the first work to address the issue of traffic load scaling for OSNs by modeling the social data dissemination from a layered perspective.
Expected Allele Coverage and the Role of Mutation in Genetic Algorithms

It is part of the traditional lore of genetic algorithms that low mutation rates lead to efficient search of the solution space, while high mutation rates result in diffusion of search effort and premature xtinction of favorable schemata in the population. We argue that the optimal mutation rate depends strongly on the choice of encoding, and that problems requiring nonbinary encodings may benefit from utation rates much higher than those generally used with binary encodings. We introduce the notion of the expected allele coverage of a population, and discuss its role in guiding the choice of mutation rate and population size.
The role of alcohol price in young adult drinking cultures in Scotland

Minimum Unit Pricing (MUP) is one of the Scottish Government's key policy options to reduce alcohol consumption and related harm. Although strongly evidenced for efficacy in reducing headline population level consumption, efficacy in changing the role of alcohol in Scottish culture is unknown. Questions remain as to how MUP will play across population subgroups with different sensitivities to price. In this paper we explore the views of the young adult population and situate the influence of price paid for alcohol alongside broader cultural drivers of consumption. Qualitative data from two studies investigating the role of alcohol in the transition to adulthood from 130 participants (aged 16–30) are analysed to situate the influence of price paid in shaping drinking styles and practices. Findings highlight how considerations of price paid for alcohol compete with non-financial considerations associated with choosing to drink excessively, moderately or not at all. Two broad categories of response to potential price increases were anticipated by drinkers which indicate that young adults are not a homogenous group in relation to price sensitivity. These differences highlight the potential for variation in subgroup responses to a pricing policy conceived to be effective at a population level.
Pfam: clans, web tools and services

Pfam is a database of protein families that currently contains 7973 entries (release 18.0). A recent development in Pfam has enabled the grouping of related families into clans. Pfam clans are described in detail, together with the new associated web pages. Improvements to the range of Pfam web tools and the first set of Pfam web services that allow programmatic access to the database and associated tools are also presented. Pfam is available on the web in the UK (), the USA (), France () and Sweden ().
Rho-GTPase and Atherosclerosis: Pleiotropic Effects of Statins

3‐Hydroxy‐methylglutaryl‐coenzyme A (HMG‐CoA) reductase inhibitors or statins are a class of medications with potent effects on reducing serum cholesterol level, and currently have been widely used in the primary and secondary prevention of atherosclerotic cardiovascular diseases (ASCVD).
What makes a convincing argument? Empirical analysis and detecting attributes of convincingness in Web argumentation

This article tackles a new challenging task in computational argumentation. Given a pair of two arguments to a certain controversial topic, we aim to directly assess qualitative properties of the arguments in order to explain why one argument is more convincing than the other one. We approach this task in a fully empirical manner by annotating 26k explanations written in natural language. These explanations describe convincingness of arguments in the given argument pair, such as their strengths or flaws. We create a new crowd-sourced corpus containing 9,111 argument pairs, multi-labeled with 17 classes, which was cleaned and curated by employing several strict quality measures. We propose two tasks on this data set, namely (1) predicting the full label distribution and (2) classifying types of flaws in less convincing arguments. Our experiments with feature-rich SVM learners and Bidirectional LSTM neural networks with convolution and attention mechanism reveal that such a novel fine-grained analysis of Web argument convincingness is a very challenging task. We release the new UKPConvArg2 corpus and software under permissive licenses to the research community.
Effects and Mechanisms of Fruit and Vegetable Juices on Cardiovascular Diseases

Many studies have indicated that consumption of vegetables and fruits are positively related to lower incidence of several chronic noncommunicable diseases. Although composition of fruit and vegetable juices is different from that of the edible portion of fruits and vegetables, they contain polyphenols and vitamins from fruits and vegetables. Drinking vegetable and fruit juices is very popular in many countries, and also an efficient way to improve consumption of fruits and vegetables. The studies showed that fruit and vegetable juices affect cardiovascular risk factors, such as lowering blood pressure and improving blood lipid profiles. The main mechanisms of action included antioxidant effects, improvement of the aspects of the cardiovascular system, inhibition of platelet aggregation, anti-inflammatory effects, and prevention of hyperhomocysteinemia. Drinking juices might be a potential way to improve cardiovascular health, especially mixtures of juices because they contain a variety of polyphenols, vitamins, and minerals from different fruits and vegetables. This review summarizes recent studies on the effects of fruit and vegetable juices on indicators of cardiovascular disease, and special attention is paid to the mechanisms of action.
Improved gender/age recognition system using arousal-selection and feature-selection schemes

This work proposes the arousal-selection and feature-selection schemes to improve speaker's gender and age identification performance. Our previous results showed that gender and age recognition rates would increase as affective stimulation degrees were lower and higher, respectively. Considering a practical scenario, the speaker's mood does not alter frequently, so speech frames are partitioned into two groups with low and high arousal levels. Here, two Gaussian Mixture Model (GMM) probability density functions are employed to characterize the distributions of the degrees of speech stimuli in terms of tone and energy variations. Such approach can appropriately classify speech frames and easily adapt to different speakers. As well as speech frames are fairly filtered and partitioned, the feature-selection scheme is effectively used to determine adequate low-level features. To do fair comparison, the experiment database adopts Lwazi corpus from South Africa. The proposed system using the arousal-selection and feature-selection schemes exhibits that accuracy rates of gender and age estimations reach 98.9% and 71.6% with 1.7% and 10.8% increases, respectively, as compared to the ones without using arousal-selection and feature-selection schemes. Therefore, the recognition system proposed herein successfully enhances accuracy rates of age and gender estimations for various human-machine interaction and multimedia applications.
Mosquito: Another One Bites the Data Upload STream

Mosquito is a lightweight and adaptive physical design framework for Hadoop. Mosquito connects to existing data pipelines in Hadoop MapReduce and/or HDFS, observes the data, and creates better physical designs, i.e. indexes, as a byproduct. Our approach is minimally invasive, yet it allows users and developers to easily improve the runtime of Hadoop. We present three important use cases: first, how to create indexes as a byproduct of data uploads into HDFS; second, how to create indexes as a byproduct of map tasks; and third, how to execute map tasks as a byproduct of HDFS data uploads. These use cases may even be combined.
Aid is Out There: Looking for Help from Tweets during a Large Scale Disaster

The 2011 Great East Japan Earthquake caused a wide range of problems, and as countermeasures, many aid activities were carried out. Many of these problems and aid activities were reported via Twitter. However, most problem reports and corresponding aid messages were not successfully exchanged between victims and local governments or humanitarian organizations, overwhelmed by the vast amount of information. As a result, victims could not receive necessary aid and humanitarian organizations wasted resources on redundant efforts. In this paper, we propose a method for discovering matches between problem reports and aid messages. Our system contributes to problem-solving in a large scale disaster situation by facilitating communication between victims and humanitarian organizations.
Tackling Data Sparseness in Recommendation using Social Media based Topic Hierarchy Modeling

Recommendation systems play an important role in E-Commerce. However, their potential usefulness in real world applications is greatly limited by the availability of historical rating records from the customers. This paper presents a novel method to tackle the problem of data sparseness in user ratings with rich and timely domain information from social media. We first extract multiple side information for products from their relevant social media contents. Next, we convert the information into weighted topic-item ratings and inject them into an extended latent factor based recommendation model in an optimized approach. Our evaluation on two real world datasets demonstrates the superiority of our method over state-of-the-art methods.
Speaker adaptation for HMM-based speech synthesis system using MLLR

This paper describes a voice characteristics conversion technique for an HMM-based text-to-speech synthesis system. The system uses phoneme HMMs as the speech synthesis units, and voice characteristics conversion is achieved by changing HMM parameters appropriately. To transform the voice characteristics of synthetic speech to the target speaker, we apply an MLLR (Maximum Likelihood Linear Regression) technique, one of the speaker adaptation techniques, to the system. From the results of objective and subjective tests, it is shown that the characteristics of synthetic speech is close to target speaker’s voice, and the speech generated from the adapted model set using 5 sentences has almost the same DMOS score as that from the speaker dependent model set.
Comparison of an Interior Mounted Permanent Magnet Synchronous Generator with a Synchronous Reluctance Generator for a Wind Application

— This article presents a performance comparison of an interior mounted permanent magnet synchronous generator (IPMSG) with a synchronous reluctance generator (SynRG) with the same size for a wind application. It is found that using the same geometrical dimensions, a SynRG can convert 74 % of the power that an IPMSG can convert, while it has 80% of the IPMSG weight. Moreover it is found that the efficieny for the IMPSG is 99% at rated power compared to 98.7% for the SynRG.
Determination of radial quantum dot position in trumpet nanowires from far field measurements

A quantum dot embedded in a trumpet nanowire has been shown to be a good candidate for realising an efficient on-demand single-photon source [1, 2]. At the lateral quantum dot position the diameter of the nanowire only supports two guided modes — the HE11 and TE01 modes. These modes are excited by the quantum dot after recombination of an electron-hole pair. The slow expansion of the nanowire diameter secures an adiabatic propagation of the modes through the taper meaning that the occupation of the HE11 and TE01 modes will remain the same at the top of the trumpet nanowire (see Fig. 1 right). It is for now not possible to control the radial position of the quantum dot in the nanowires and thus it is important to experimentally determine this after fabrication.
Aldosterone Antagonism Ameliorates Proteinuria and Nephrosclerosis Independent of Glomerular Dynamics in L-NAME/SHR Model

Background: The renin-angiotensin-aldosterone system participates importantly in the progression of hypertensive renal disease. Angiotensin-converting enzyme inhibitors or angiotensin II receptor antagonists have been demonstrated to afford renoprotection in L-NAME-exacerbated nephrosclerosis in SHR rats. This study was designed to examine the effects of the aldosterone antagonist eplerenone on systemic and renal hemodynamics, glomerular dynamics, renal function and histopathology in L-NAME/SHR, and determine whether aldosterone antagonism would enhance the effectiveness of ACE inhibition. Methods: Six groups of 20-week-old SHR were studied using renal micropuncture and histopathological techniques after 3 weeks of treatment: SHR control (tapwater, n = 10); SHR + eplerenone (101 ± 8.3 mg/kg/day, n = 10); SHR + L-NAME (5.0 ± 0.12 mg/kg/day, n = 9); SHR + L-NAME + eplerenone (n = 8); SHR + L-NAME + lisinopril (3 mg/kg/day, n = 9), and SHR + L-NAME + eplerenone + lisinopril (n = 9). Results:L-NAME-treated SHR developed massive proteinuria, severe hypertensive nephrosclerosis, and tubulointerstitial damage. Eplerenone significantly reduced proteinuria (127.4 ± 26.5 vs. 51.9 ± 16.7 mg/24 h, p < 0.01), improved glomerular and arteriolar injuries (65 ± 9 vs. 29 ± 9 score/100 glomeruli, p < 0.01; 116 ± 18 vs. 41 ± 13 score/100 arterioles, p < 0.01, respectively), and decreased tubulointerstitial damage index (1.43 ± 0.07 vs. 0.39 ± 0.07, p < 0.01) without altering mean arterial pressure or glomerular dynamics. Combined therapy of eplerenone with lisinopril produced no further benefits than lisinopril alone. Conclusion: The aldosterone antagonist eplerenone significantly ameliorated proteinuria and nephrosclerosis in the L-NAME/SHR model, independent of hemodynamic effects.
Irs4p and Tax4p: Two Redundant EH Domain Proteins Involved in Autophagy

Proteins carrying EPS15 homology (EH) domains are present from yeast to mammals. The characterized members of this protein family are all involved in intracellular trafficking, typically endocytosis and endocytic recycling. We focused on two members of this family in Saccharomyces cerevisiae Irs4p and Tax4p, whose functions are less well characterized. We show that the deletion of IRS4 altered the function of a neighboring gene, VPS51, involved in endocytic recycling. The irs4Δtax4Δ cells complemented for the loss of Vps51p (irs4Δtax4Δ*) display no defects in endocytosis and endosomal recycling, clearly differentiating these two EH proteins from the other protein family members. Because Irs4p is phosphorylated when autophagy is induced, we studied the potential role of these two proteins in this latter process. We observed a loss of viability upon starvation in irs4Δtax4Δ* cells because of a delay in bulk autophagy. Irs4p and Tax4p are also required for pexophagy but not for the cytoplasm‐to‐vacuole pathway. In growing cells, Irs4p and Tax4p colocalized to few cytoplasmic puncta distinct from endosomes and Golgi compartments. In conditions inducing autophagy, Irs4p and Tax4p partially localized to the pre‐autophagosomal structure (PAS) and are required to efficiently recruit to the PAS Atg17p, a factor modulating the autophagic response. We propose that Irs4p and Tax4p are two redundant modulators of the autophagic processes acting upstream from Atg17p, possibly in the signaling events leading to the activation of the autophagic machinery in response to starvation.
Relationship Between Observed Parental Optimism and Adolescent Optimism with Parental Involvement as a Mediating Variable: Two Wave Panel Study

Relationship Between Observed Parental Optimism and Adolescent Optimism with Parental Involvement as a Mediating Variable: Two Wave Panel Study Allison Ellsworth School of Family Life Master of Science Using coded data from parent-child interaction tasks and questionnaires, this longitudinal study examined the relationship between observed mother and father optimism and self-reported and observed optimism of their adolescent child one year later with mother and father involvement as mediators. Results from structural equation modeling indicated that while there was not a direct association between maternal optimism and child optimism, that father involvement mediated that relationship, and that father involvement further mediated the relationship between father involvement and child optimism.
Scaling up from Dialogue to Multilogue: Some Principles and Benchmarks

The paper considers how to scale up dialogue protocols to multilogue, settings with multiple conversationalists. We extract two benchmarks to evaluate scaled up protocols based on the long distance resolution possibilities of non-sentential utterances in dialogue and multilogue in the British National Corpus. In light of these benchmarks, we then consider three possible transformations to dialogue protocols, formulated within an issue-based approach to dialogue management. We show that one such transformation yields protocols for querying and assertion that fulfill these benchmarks.
Large scale data mining approach for gene-specific standardization of microarray gene expression data

MOTIVATION The identification of the change of gene expression in multifactorial diseases, such as breast cancer is a major goal of DNA microarray experiments. Here we present a new data mining strategy to better analyze the marginal difference in gene expression between microarray samples. The idea is based on the notion that the consideration of gene's behavior in a wide variety of experiments can improve the statistical reliability on identifying genes with moderate changes between samples. RESULTS The availability of a large collection of array samples sharing the same platform in public databases, such as NCBI GEO, enabled us to re-standardize the expression intensity of a gene using its mean and variation in the wide variety of experimental conditions. This approach was evaluated via the re-identification of breast cancer-specific gene expression. It successfully prioritized several genes associated with breast tumor, for which the expression difference between normal and breast cancer cells was marginal and thus would have been difficult to recognize using conventional analysis methods. Maximizing the utility of microarray data in the public database, it provides a valuable tool particularly for the identification of previously unrecognized disease-related genes. AVAILABILITY A user friendly web-interface (http://compbio.sookmyung.ac.kr/~lage/) was constructed to provide the present large-scale approach for the analysis of GEO microarray data (GS-LAGE server).