234 research outputs found

    The Arts and Technology: How Educational Technology Can Bring Humanities Further Into Elementary and Primary School Systems

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    As the world becomes more inclined to implement technology in nearly every aspect of society, the United States Department of Education must find a way to incorporate new styles of modern and high-tech teaching without pushing out certain subjects from its curriculum. I believe technology can be used to bring the Humanities further into the classroom. In today’s society American education programs are desperately trying to make up for subpar primary school scores in mathematics and science. According to the government accredited international education forum (the Organization for Economic Co-operation and Development) the United States was found to be below the OECD average in science ranking 25th, reading 24th and mathematics 41st (Businessinsider.com). With these mediocre scores the United States has been forced to take drastic measure in bolstering its primary education systems. While an added emphasis in elementary math and science curriculum is an obvious route, it seems that the removal or distancing from the arts and other social forms of education has also become part of the solution. While science, technology, engineering and math are all extremely important, the United States Department of Education should be able to recommend modernized approaches that incorporate art history, history, literature, art, music, philosophy and language. In our ever-changing high-tech world, the Humanities are needed in our classrooms to supply equality and perspective. The Humanities widen our thought process, build global understanding, assist in the formation of critical thinking skills, train individuals to communicate and share, bolster moral accountability and cultural sensitivity, support scientific advancements through unique societal perspectives, guide humanity towards a more rational and inclusive way of thinking, and create a well-balanced 21st century scholar. In today’s modern society it is more than reasonable to explore options that involve the intertwining of technology and the arts in our elementary school systems. It must also be mentioned, the goal of this paper is to in now way lessen or devalue the role of the instructor, rather, the research provided is aimed at highlighting certain types of technologies that can potentially assist primary and elementary educators who aspire to further incorporate the Humanities and its core philosophies into their curriculum

    Channel estimation and symbol detection for block transmission using data-dependent superimposed training

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    We address the problem of frequency-selective channel estimation and symbol detection using superimposed training. The superimposed training consists of the sum of a known sequence and a data-dependent sequence that is unknown to the receiver. The data-dependent sequence cancels the effects of the unknown data on channel estimation. The performance of the proposed approach is shown to significantly outperform existing methods based on superimposed training (ST)

    EM Algorithms for Weighted-Data Clustering with Application to Audio-Visual Scene Analysis

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    Data clustering has received a lot of attention and numerous methods, algorithms and software packages are available. Among these techniques, parametric finite-mixture models play a central role due to their interesting mathematical properties and to the existence of maximum-likelihood estimators based on expectation-maximization (EM). In this paper we propose a new mixture model that associates a weight with each observed point. We introduce the weighted-data Gaussian mixture and we derive two EM algorithms. The first one considers a fixed weight for each observation. The second one treats each weight as a random variable following a gamma distribution. We propose a model selection method based on a minimum message length criterion, provide a weight initialization strategy, and validate the proposed algorithms by comparing them with several state of the art parametric and non-parametric clustering techniques. We also demonstrate the effectiveness and robustness of the proposed clustering technique in the presence of heterogeneous data, namely audio-visual scene analysis.Comment: 14 pages, 4 figures, 4 table

    The removal of thermally aged films of triacylglycerides by surfactant solutions

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    Thermal ageing of triacylglycerides (TAG) at high temperatures produces films which resist removal using aqueous surfactant solutions. We used a mass loss method to investigate the removal of thermally aged TAG films from hard surfaces using aqueous solutions of surfactants of different charge types. It was found that cationic surfactants are most effective at high pH, whereas anionics are most effective at low pH and a non-ionic surfactant is most effective at intermediate pH. We showed that the TAG film removal process occurs in several stages. In the first ‘‘lag phase’’ no TAG removal occurs; the surfactant first partitions into the thermally aged film. In the second stage, the TAG film containing surfactant was removed by solubilisation into micelles in the aqueous solution. The effects of pH and surfactant charge on the TAG removal process correlate with the effects of these variables on the extent of surfactant partitioning to the TAG film and on the maximum extent of TAG solubilisation within the micelles. Additionally, we showed how the TAG removal is enhanced by the addition of amphiphilic additives such as alcohols which act as co-surfactants. The study demonstrates that aqueous surfactant solutions provide a viable and more benign alternative to current methods for the removal of thermally aged TAG films

    Rational Design of Superhydrophilic/Superoleophobic Surfaces for Oil-Water Separation via Thiol-Acrylate Photopolymerization

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    We report a simple, rapid, and scalable strategy to fabricate surfaces exhibiting in-air superoleophobic/superhydrophilic wetting via sequential spray deposition and photopolymerization of nanoparticle-laden thiol–acrylate resins comprising both hydrophilic and oleophobic chemical constituents. The combination of spray deposition with nanoparticles provides hierarchical surface morphologies with both micro- and nanoscale roughness. Mapping the wetting behavior as a function of resin composition using high- and low-surface-tension liquid probes enabled facile identification of coatings that exhibit a range of wetting behavior, including superhydrophilic/superoleophilic, superhydrophobic/superoleophobic, and in-air superhydrophilic/superoleophobic wetting. In-air superhydrophilic/superoleophobic wetting was realized by a dynamic rearrangement of the interface to expose a greater fraction of hydrophilic moieties in response to contact with water. We show that these in-air superoleophobic/superhydrophilic coatings deposited onto porous supports enable separation of model oil–water emulsions with separation efficiencies up to 99.9% with 699 L·m–2 h–1 permeate flux when the superhydrophilic/superoleophobic coatings are paired with 0.45 μm nylon membrane supports

    Tailoring block copolymer nanoporous thin films with acetic acid as a small guest molecule

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    Block copolymers offer the fabrication of mesoporous thin films with distinct nanoscale structural features. In this contribution, we present the use of acetic acid (CH3COOH) as a low‐molecular‐weight guest molecule to tune the supramolecular assembly of poly[styrene‐block‐(4‐vinylpyridine)] (PS‐b‐P4VP), offering a versatile and straightforward method to obtain tailored nanostructured films with controlled topography and pore size. Spin‐coating toluene solutions of PS‐b‐P4VP, with a variable amount of CH3COOH, leads to micellar thin films, where the micelles contain the carboxylic acid as a guest molecule. The size can be conveniently modified in these films (from 48 to 75 nm) by varying the amount of organic acid in the starting solutions. Subsequent surface reconstruction of micellar films using ethanol leads to ring‐shaped copolymer nanoporous films with modulated diameter. Controlling the micelle reconstruction process, cylindrical porous films are also obtained. Interestingly, changing the type of aliphatic carboxylic acid leads to a modification of the observed film morphology from micelles to out‐of‐plane P4VP cylinders (or lamellae) in a PS matrix

    Recognition memory deficits in mild cognitive impairment

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    There is no agreement on the pattern of recognition memory deficits characteristic of patients diagnosed with mild cognitive impairment (Mel). Whereas lower performance in recollection is the hallmark of Mel, there is a strong controversy about possible deficits in familiarity estimates when using recognition memory tasks. The aim of this research is to shed Iight on the pattern of responding in recollection and familiarity in MCl. Five groups of participants were tested. The main participant samples were those formed by two Mel groups differing in age and an Alzheimer's disease group (AD), which were compared with two control groups, Whereas one of the control groups served to assess the performance of the MeI and AD people, the other one, composed of young healthy participants, served the purpose of evaluating the adequacy of the experimental tasks used in the evaluation of the different components of recognition memory. We used an associative recognition task as a direct index of recollection and a choice task on a pair of stimuli, one of which was perceptually similar to those studied in the associative recognition phase, as an index of familiarity. Our results indicate that recollection decreases with age and neurological status, and familiarity remains stable in the elderly control sample but it is deficient in Me!. This research shows that a unique encoding situation generated deficits in recollective and familiarity mechanisms in mild cognitive impaired individuals, providing evidence for the existence of deficits in both retrieval processes in recognition memory in a MeI stage

    Exploring Recollection and Familiarity Impairments in Parkinson´s disease

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    There is conflicting evidence on whether patients diagnosed with Parkinson's disease (PD) have cognitive deficits associated with episodic memory and particularly with recognition memory. The aim of the present study was to explore whether PD patients exhibit deficits in recollection and familiarity, the two processes involved in recognition. A sample of young healthy participants (22) was tested to verify that the experimental tasks were useful estimators of recognition processes. Two further samples ¿ one of elderly controls (16) and one of PD patients (20) ¿ were the main focus of this research. All participants were exposed to an associative recognition task aimed at estimating recollection followed by a two-alternative forced-choice (2AFC) test designed to estimate familiarity. The analyses showed a deficit in associative recognition in PD patients and no difference between elderly controls and PD patients in the 2AFC test. By contrast, young healthy participants were better than elderly controls and PD patients in both components of recognition. Further analyses of results of the 2AFC test indicated that the measure chosen to estimate conceptual familiarity was adequate

    Riesgo de mortalidad total y cardiovascular según la clasificación propuesta por las guías KDIGO en pacientes con diabetes tipo 2

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    Antecedentes y objetivo: El objetivo del estudio fue comprobar la validez de la clasificación de riesgo KDIGO 2012 para predecir mortalidad total (MT) y cardiovascular (MCV) en diabetes mellitus tipo 2 (DM2). Materiales y métodos: Estudio de cohortes prospectivo incluyendo pacientes con DM2. Los puntos finales clínicos fueron MT y MCV. La principal variable predictora fue la clasificación KDIGO, una variable que recoge 4 niveles de riesgo en dependencia de una combinación de la tasa de filtración glomerular y la excreción de albúmina urinaria. La evaluación del poder predictivo se realizó con el índice de mejora de discriminación integrada (IDI). Resultados: Se incluyeron 453 pacientes (39, 3% varones, edad 64, 9 [DE 9, 3] años y evolución de DM2 de 10, 4 [DE 7, 5] años). Durante una mediana de 13 años de seguimiento, hubo incremento significativo de la tasa/1000 pacientes-año de MT (26, 5 vs. 45, 1 vs. 79, 2 vs. 109, 8; p< 0, 001) y de MCV (8, 1 vs. 17, 4 vs. 24, 7 vs. 57, 5; p< 0, 001) en las sucesivas categorías de riesgo KDIGO. En análisis multivariante también hubo incremento de riesgo de MT (HR[riesgo moderado] = 1, 29; HR[riesgo alto] = 1, 83; HR[riesgo muy alto] = 2, 15; p = 0, 016) y MCV (HR[riesgo moderado] = 1, 73; HR[riesgo alto] = 2, 27; HR[riesgo muy alto] = 4, 22; p = 0, 007) en las sucesivas categorías. La clasificación KDIGO mejoró la predicción de MT (IDI = 0, 00888; p = 0, 047) y MCV (IDI = 0, 01813; p = 0, 035). Conclusiones: La clasificación de riesgo según guías KDIGO 2012 puede estratificar eficazmente el riesgo de MT y MCV en pacientes con DM2. Background and aims: Our aim was to assess the usefulness of KDIGO 2012 risk classification to predict total and cardiovascular mortality in type 2 diabetes mellitus (DM2). Material and methods: Prospective cohort study that included DM2 patients. Clinical end-points were total and cardiovascular mortality. The main predictive variable was KDIGO risk classification, which is a combination of urinary albumin excretion and glomerular filtration rate. The predictive value was evaluated by the integrated discrimination improvement (IDI) index. Results: 453 patients (39.3% males, aged 64.9 [SD 9.3] and with a mean diabetes duration of 10.4 [SD 7.5] years) were included. During a median follow-up of 13 years, mortality rates per 1000 patients/year (26.5 vs. 45.1 vs. 79, 2 vs. 109, 8; p< 0, 001) and cardiovascular mortality (8.1 vs. 17.4 vs. 24.7 vs. 57.5; p< 0, 001) were progressively increased in successive KDIGO categories. In the multivariate analysis, there was also a progressive increase of mortality risk (HR[moderate risk] = 1.29; HR[high risk]) = 1.83; HR[very high risk] = 2.15; p =.016) and cardiovascular mortality risk (HR[moderate risk] = 1.73; HR[high risk] = 2.27; HR[very high risk] = 4.22; p =.007) in the successive categories. KDIGO classification was able to improve the mortality risk prediction (IDI = 0.00888; p =.047) and cardiovascular mortality risk prediction (IDI = 0.01813; p =.035). Conclusions: KDIGO risk classification can effectively stratify total and cardiovascular mortality risk in DM2 patients
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