Cross-Domain Polarity Models to Evaluate User eXperience in E-learning

[EN] Virtual learning environments are growing in importance as fast as e-learning is becoming highly demanded by universities and students all over the world. This paper investigates how to automatically evaluate User eXperience in this domain using sentiment analysis techniques. For this purpose, a corpus with the opinions given by a total of 583 users (107 English speakers and 476 Spanish speakers) about three learning management systems in different courses has been built. All the collected opinions were manually labeled with polarity information (positive, negative or neutral) by three human annotators, both at the whole opinion and sentence levels. We have applied our state-of-the-art sentiment analysis models, trained with a corpus of a different semantic domain (a Twitter corpus), to study the use of cross-domain models for this task. Cross-domain models based on deep neural networks (convolutional neural networks, transformer encoders and attentional BLSTM models) have been tested. In order to contrast our results, three commercial systems for the same task (MeaningCloud, Microsoft Text Analytics and Google Cloud) were also tested. The obtained results are very promising and they give an insight to keep going the research of applying sentiment analysis tools on User eXperience evaluation. This is a pioneering idea to provide a better and accurate understanding on human needs in the interaction with virtual learning environments and a step towards the development of automatic tools that capture the feed-back of user perception for designing virtual learning environments centered in user's emotions, beliefs, preferences, perceptions, responses, behaviors and accomplishments that occur before, during and after the interaction.Partially supported by the Spanish MINECO and FEDER founds under Project TIN2017-85854-C4-2-R. Work of J.A. Gonzalez is financed under Grant PAID-01-17Sanchis-Font, R.; Castro-Bleda, MJ.; González-Barba, JÁ.; Pla Santamaría, F.; Hurtado Oliver, LF. (2021). Cross-Domain Polarity Models to Evaluate User eXperience in E-learning. 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Circuit Quantum Electrodynamics: Coherent Coupling of a Single Photon to a Cooper Pair Box

Under appropriate conditions, superconducting electronic circuits behave quantum mechanically, with properties that can be designed and controlled at will. We have realized an experiment in which a superconducting two-level system, playing the role of an artificial atom, is strongly coupled to a single photon stored in an on-chip cavity. We show that the atom-photon coupling in this circuit can be made strong enough for coherent effects to dominate over dissipation, even in a solid state environment. This new regime of matter light interaction in a circuit can be exploited for quantum information processing and quantum communication. It may also lead to new approaches for single photon generation and detection.Comment: 8 pages, 4 figures, accepted for publication in Nature, embargo does apply, version with high resolution figures available at: http://www.eng.yale.edu/rslab/Andreas/content/science/PubsPapers.htm

A Genetic Screen for Dihydropyridine (DHP)-Resistant Worms Reveals New Residues Required for DHP-Blockage of Mammalian Calcium Channels

Dihydropyridines (DHPs) are L-type calcium channel (Cav1) blockers prescribed to treat several diseases including hypertension. Cav1 channels normally exist in three states: a resting closed state, an open state that is triggered by membrane depolarization, followed by a non-conducting inactivated state that is triggered by the influx of calcium ions, and a rapid change in voltage. DHP binding is thought to alter the conformation of the channel, possibly by engaging a mechanism similar to voltage dependent inactivation, and locking a calcium ion in the pore, thereby blocking channel conductance. As a Cav1 channel crystal structure is lacking, the current model of DHP action has largely been achieved by investigating the role of candidate Cav1 residues in mediating DHP-sensitivity. To better understand DHP-block and identify additional Cav1 residues important for DHP-sensitivity, we screened 440,000 randomly mutated Caenorhabditis elegans genomes for worms resistant to DHP-induced growth defects. We identified 30 missense mutations in the worm Cav1 pore-forming (α1) subunit, including eleven in conserved residues known to be necessary for DHP-binding. The remaining polymorphisms are in eight conserved residues not previously associated with DHP-sensitivity. Intriguingly, all of the worm mutants that we analyzed phenotypically exhibited increased channel activity. We also created orthologous mutations in the rat α1C subunit and examined the DHP-block of current through the mutant channels in culture. Six of the seven mutant channels examined either decreased the DHP-sensitivity of the channel and/or exhibited significant residual current at DHP concentrations sufficient to block wild-type channels. Our results further support the idea that DHP-block is intimately associated with voltage dependent inactivation and underscores the utility of C. elegans as a screening tool to identify residues important for DHP interaction with mammalian Cav1 channels

A Score of the Ability of a Three-Dimensional Protein Model to Retrieve Its Own Sequence as a Quantitative Measure of Its Quality and Appropriateness

BACKGROUND: Despite the remarkable progress of bioinformatics, how the primary structure of a protein leads to a three-dimensional fold, and in turn determines its function remains an elusive question. Alignments of sequences with known function can be used to identify proteins with the same or similar function with high success. However, identification of function-related and structure-related amino acid positions is only possible after a detailed study of every protein. Folding pattern diversity seems to be much narrower than sequence diversity, and the amino acid sequences of natural proteins have evolved under a selective pressure comprising structural and functional requirements acting in parallel. PRINCIPAL FINDINGS: The approach described in this work begins by generating a large number of amino acid sequences using ROSETTA [Dantas G et al. (2003) J Mol Biol 332:449-460], a program with notable robustness in the assignment of amino acids to a known three-dimensional structure. The resulting sequence-sets showed no conservation of amino acids at active sites, or protein-protein interfaces. Hidden Markov models built from the resulting sequence sets were used to search sequence databases. Surprisingly, the models retrieved from the database sequences belonged to proteins with the same or a very similar function. Given an appropriate cutoff, the rate of false positives was zero. According to our results, this protocol, here referred to as Rd.HMM, detects fine structural details on the folding patterns, that seem to be tightly linked to the fitness of a structural framework for a specific biological function. CONCLUSION: Because the sequence of the native protein used to create the Rd.HMM model was always amongst the top hits, the procedure is a reliable tool to score, very accurately, the quality and appropriateness of computer-modeled 3D-structures, without the need for spectroscopy data. However, Rd.HMM is very sensitive to the conformational features of the models' backbone

Baseline factors predictive of serious suicidality at follow-up: findings focussing on age and gender from a community-based study

The electronic version of this article is the complete one and can be found online at: http://www.biomedcentral.com/1471-244X/10/41Background: Although often providing more reliable and informative findings relative to other study designs, longitudinal investigations of prevalence and predictors of suicidal behaviour remain uncommon. This paper compares 12-month prevalence rates for suicidal ideation and suicide attempt at baseline and follow-up; identifies new cases and remissions; and assesses the capacity of baseline data to predict serious suicidality at follow-up, focusing on age and gender differences. Methods: 6,666 participants aged 20-29, 40-49 and 60-69 years were drawn from the first (1999-2001) and second (2003-2006) waves of a general population survey. Analyses involved multivariate logistic regression. Results: At follow-up, prevalence of suicidal ideation and suicide attempt had decreased (8.2%-6.1%, and 0.8%-0.5%, respectively). However, over one quarter of those reporting serious suicidality at baseline still experienced it four years later. Females aged 20-29 never married or diagnosed with a physical illness at follow-up were at greater risk of serious suicidality (OR = 4.17, 95% CI = 3.11-5.23; OR = 3.18, 95% CI = 2.09-4.26, respectively). Males aged 40-49 not in the labour force had increased odds of serious suicidality (OR = 4.08, 95% CI = 1.6-6.48) compared to their equivalently-aged and employed counterparts. Depressed/anxious females aged 60-69 were nearly 30% more likely to be seriously suicidal. Conclusions: There are age and gender differentials in the risk factors for suicidality. Life-circumstances contribute substantially to the onset of serious suicidality, in addition to symptoms of depression and anxiety. These findings are particularly pertinent to the development of effective population-based suicide prevention strategies.A Kate Fairweather-Schmidt, Kaarin J Anstey, Agus Salim and Bryan Rodger

Clinical characteristics and outcomes of patients with acute myelogenous leukemia admitted to intensive care: a case-control study

<p>Abstract</p> <p>Background</p> <p>There is limited epidemiologic data on patients with acute myelogenous (myeloid) leukemia (AML) requiring life-sustaining therapies in the intensive care unit (ICU). Our objectives were to describe the clinical characteristics and outcomes in critically ill AML patients.</p> <p>Methods</p> <p>This was a retrospective case-control study. Cases were defined as adult patients with a primary diagnosis of AML admitted to ICU at the University of Alberta Hospital between January 1^st2002 and June 30^th2008. Each case was matched by age, sex, and illness severity (ICU only) to two control groups: hospitalized AML controls, and non-AML ICU controls. Data were extracted on demographics, course of hospitalization, and clinical outcomes.</p> <p>Results</p> <p>In total, 45 AML patients with available data were admitted to ICU. Mean (SD) age was 54.8 (13.1) years and 28.9% were female. Primary diagnoses were sepsis (32.6%) and respiratory failure (37.3%). Mean (SD) APACHE II score was 30.3 (10.3), SOFA score 12.6 (4.0) with 62.2% receiving mechanical ventilation, 55.6% vasoactive therapy, and 26.7% renal replacement therapy. Crude in-hospital, 90-day and 1-year mortality was 44.4%, 51.1% and 71.1%, respectively. AML cases had significantly higher adjusted-hazards of death (HR 2.23; 95% CI, 1.38-3.60, p = 0.001) compared to both non-AML ICU controls (HR 1.69; 95% CI, 1.11-2.58, p = 0.02) and hospitalized AML controls (OR 1.0, reference variable). Factors associated with ICU mortality by univariate analysis included older age, AML subtype, higher baseline SOFA score, no change or an increase in early SOFA score, shock, vasoactive therapy and mechanical ventilation. Active chemotherapy in ICU was associated with lower mortality.</p> <p>Conclusions</p> <p>AML patients may represent a minority of all critically ill admissions; however, are not uncommonly supported in ICU. These AML patients are characterized by high illness severity, multi-organ dysfunction, and high treatment intensity and have a higher risk of death when compared with matched hospitalized AML or non-AML ICU controls. The absence of early improvement in organ failure may be a useful predictor for mortality for AML patients admitted to ICU.</p

Gender differences and determinants of health related quality of life in coronary patients: a follow-up study

<p>Abstract</p> <p>Background</p> <p>The role of gender differences in Health Related Quality Life (HRQL) in coronary patients is controversial, so understanding the specific determinants of HRQL in men and women might be of clinical importance. The aim of this study was to know the gender differences in the evolution of HRQL at 3 and 6 months after a coronary event, and to identify the key clinical, demographic and psychological characteristics of each gender associated with these changes.</p> <p>Methods</p> <p>A follow-up study was carried out, and 175 patients (112 men and 63 women) with acute myocardial infarction (AMI) or unstable angina were studied. The SF-36v1 health questionnaire was used to assess HRQL, and the GHQ-28 (General Health Questionnaire) to measure mental health during follow-up. To study the variables related to changes in HRQL, generalized estimating equation (GEE) models were performed.</p> <p>Results</p> <p>Follow-up data were available for 55 men and 25 women at 3 months, and for 35 men and 12 women at 6 months. Observations included: a) Revascularization was performed later in women. b) The frequency of rehospitalization between months 3 and 6 of follow-up was higher in women c) Women had lower baseline scores in the SF-36. d) Men had progressed favourably in most of the physical dimensions of the SF-36 at 6 months, while at the same time women's scores had only improved for Physical Component Summary, Role Physical and Social Functioning; e) the variables determining the decrease in HRQL in men were: worse mental health and angina frequency; and in women: worse mental health, history of the disease, revascularization, and angina frequency.</p> <p>Conclusions</p> <p>There are differences in the evolution of HRQL, between men and women after a coronary attack. Mental health is the determinant most frequently associated with HRQL in both genders. However, other clinical determinants of HRQL differed with gender, emphasizing the importance of individualizing the intervention and the content of rehabilitation programs. Likewise, the recognition and treatment of mental disorders in these patients could be crucial.</p

13C labeling experiments at metabolic nonstationary conditions: An exploratory study

<p>Abstract</p> <p>Background</p> <p>Stimulus Response Experiments to unravel the regulatory properties of metabolic networks are becoming more and more popular. However, their ability to determine enzyme kinetic parameters has proven to be limited with the presently available data. In metabolic flux analysis, the use of ¹³C labeled substrates together with isotopomer modeling solved the problem of underdetermined networks and increased the accuracy of flux estimations significantly.</p> <p>Results</p> <p>In this contribution, the idea of increasing the information content of the dynamic experiment by adding ¹³C labeling is analyzed. For this purpose a small example network is studied by simulation and statistical methods. Different scenarios regarding available measurements are analyzed and compared to a non-labeled reference experiment. Sensitivity analysis revealed a specific influence of the kinetic parameters on the labeling measurements. Statistical methods based on parameter sensitivities and different measurement models are applied to assess the information gain of the labeled stimulus response experiment.</p> <p>Conclusion</p> <p>It was found that the use of a (specifically) labeled substrate will significantly increase the parameter estimation accuracy. An overall information gain of about a factor of six is observed for the example network. The information gain is achieved from the specific influence of the kinetic parameters towards the labeling measurements. This also leads to a significant decrease in correlation of the kinetic parameters compared to an experiment without ¹³C-labeled substrate.</p