La mecánica newtoniana en bachillerato. Diseño de problemas y evaluación de aprendizajes

Se presenta una investigación realizada en el campo de la Mecánica con alumnos de 1º Bachillerato trabajando con un modelo investigativo de resolución de problemas. Resolver las situaciones problemáticas diseñadas al efecto ha permitido comprobar la potencialidad del modelo para vencer la resistencia de las concepciones alternativas de los estudiantes en estos niveles educativos. Se presentan los resultados obtenidos en relación al cambio conceptual y al aprendizaje de los procedimientos científicos implicados. La incidencia positiva en las actitudes constata la importancia de utilizar este tipo de metodologías que proporcionan a los alumnos herramientas útiles y contribuyen a la adquisición de una competencia básica: “aprender a aprender”, un objetivo relevante en sí mismo y un poderoso medio para conseguir alcanzar los demás objetivos educativos

La mecánica newtoniana en bachillerato. Diseño de problemas y evaluación de aprendizajes

Se presenta una investigación realizada en el campo de la Mecánica con alumnos de 1º Bachillerato trabajando con un modelo investigativo de resolución de problemas. Resolver las situaciones problemáticas diseñadas al efecto ha permitido comprobar la potencialidad del modelo para vencer la resistencia de las concepciones alternativas de los estudiantes en estos niveles educativos. Se presentan los resultados obtenidos en relación al cambio conceptual y al aprendizaje de los procedimientos científicos implicados. La incidencia positiva en las actitudes constata la importancia de utilizar este tipo de metodologías que proporcionan a los alumnos herramientas útiles y contribuyen a la adquisición de una competencia básica: "aprender a aprender", un objetivo relevante en sí mismo y un poderoso medio para conseguir alcanzar los demás objetivos educativos

Clustering of Russian texts using χ² statistics

Проблема обнаружения скрытых структур текста связана с перспективной методикой установления авторства. В работе описан Корпус текстов русского языка, созданный для исследований текстов методами математической статистики. Описывается исследование, проведённое на базе Корпуса с применением статистики χ2. Кластеризация текстов, обнаруженная в результате исследования, может служить основанием для их атрибуции. Работа выполнена на кафедре полиграфии и веб-дизайна ИРИТ-РтФ УрФУ.The problem of detection of the hidden structures of the text is associated with a promising method of attribution. The paper describes a corpus of Russian language created for investigations of texts by the methods of mathematical statistics. The research conducted on the basis of the statistics χ2 is described. Clustering of texts discovered by the study can serve as a basis for their attribution. The work was coudveted at the department of printing art and web-design, Ural Federal University

Основные методики исследования структуры текста

Проблема обнаружения скрытых структур текста связана с перспективной методикой установления авторства. В работе обосновывается выбор методики для обнаружения и изучения таких структур в русскоязычных текстах. Рассмотрены основные методики, оперирующие в качестве единиц анализа смыслосодержащими элементами, лексическими или графическими формами и частотными характеристиками текста. Авторы предполагают существование скрытых структур, исходя из ранее полученных результатов. Предлагается использование частотного анализа как наиболее адекватного задаче обнаружения скрытых структур текста.The problem of finding the hidden structures of the test is associated with promising method of attribution. The paper substantiates the choice of methods for the detection and study of such structures in the Russian-language texts. The basic techniques that operate as units of analysis elements that carry meaning, lexical or graphical form, and frequency characteristics of the text. The authors suggest the existence of hidden structures, based on previous results. It is proposed to use frequency analysis as the most adequate to detect hidden structures of the text

Electrosprayed Minocycline-loaded PLGA Microparticles for the Treatment of Glioblastoma

Background: Around 12,340 patients in the US are diagnosed with glioblastoma multiforme (GBM) yearly, and despite the current treatment options, such as chemotherapy, radiotherapy, surgical resection, or a combination of them, the median survival is only about 15 months after initial diagnosis. Minocycline, a tetracycline antibiotic, has shown to inhibit U87 glioblastoma cell death and inhibit angiogenesis, or the creation of new blood vessels as is often needed by the tumor to grow. The utilization of biomaterials such as poly lactic-co-glycolic acid (PLGA) can better sustain the release and bioactivity of loaded drugs. The use of polyethylene glycol (PEG), a hydrophilic polymer, may improve the encapsulation of minocycline into the PLGA microparticles, given its hydrophilic nature. Electrospraying may be a promising method to fabricate drug loaded PLGA microparticles with high drug loading and loading efficiency. Therefore, the objective of this project was to develop electrosprayed minocycline-loaded PLGA microparticles for the treatment of GBM. Methods: Minocycline-loaded PLGA microparticles were fabricated through electrospraying utilizing an 18 cm needle-tip to glass plate distance, 0.9 ml/hr flowrate, and 14 kV voltage. The solution consisted of 1 ml of chloroform as the solvent and 70 mg of PLGA as the polymer with different minocycline amounts and with or without polyethylene glycol (PEG). The amount of drug loaded into the microparticles was determined by dissolving the microparticles in 1 mL of dimethylsulfoxide and then measuring the absorbance of minocycline at 350 nm. Release kinetics studies were performed by placing the microparticles in phosphate-buffered saline and reading minocycline absorbance of the supernatant at various timepoint. Scanning Electron Microscopy (SEM) was used to determine size and morphology of the minocycline-loaded PLGA microparticles. Results: The amount of drug loading and loading efficiency increased with the addition of PEG (3.23 ± 0.29 vs. 4.02 ± 0.34 and 49.40 ± 4.49 vs. 64.30 ± 5.47%, respectively) and the utilization of higher amount of drug (4.02 ± 0.34 vs. 9.93 ± 0.64 and 64.30 ± 5.47 vs. 70.76 ± 4.57%, respectively). The release kinetics study demonstrated that the different microparticles experienced a burst release within the first hour (67-80%). The microparticles were spherical in shape and ranged between 4-11 μm in size. The addition of PEG resulted in the aggregation of the microparticles, as observed in SEM imaging. Conclusions: This study demonstrated that electrosprayed minocycline-loaded PLGA microparticles can be successfully fabricated with high drug loading and loading efficiency and have a spherical shape within the micron size range. PEG was able to increase drug loading of the lipophilic drug by increasing the solubility of the drug in the polymer/chloroform solution. However, the utilization of PEG affected the collection of the particles and therefore, further optimization of the electrospraying parameters needs to be done to improve the collection of non-aggregated microparticles. In addition, given their burst release of minocycline, the microparticles may need to be further encapsulated in a scaffold or depot to prolong their release of drug

Attribution is a Russian-language texts using the law of large numbers

Работа посвящена статистическому исследованию русскоязычных текстов. Исследуется связь между длиной текста и среднеквадратичным отклонением величины χ2 для распределения сочетаний гласных букв. Установлена справедливость закона больших чисел для этой величины. Работа выполнена на кафедре полиграфии и веб-дизайна ИРИТ-РтФ УрФУ.The work is devoted to the statistical study of Russian texts. Examines the relationship between text length and standard deviation of the χ2 values for the distribution of combinations of vowels. Established the validity of the law of large numbers for this value. The work was performed at the Department of printing and web design IRIT-RTF UrFU

Machine attribution of Russian-language texts: a review of methods

The paper considers the problem of attribution and classification of Russian language texts. There are characteristics of different approaches. Authors explain choice of approaches and propose parameters for classificationВ статье рассматривается проблема атрибуции и классификации русскоязычных текстов. Приводятся характеристики различных подходов и обосновывается выбор. В рамках каждого подхода предлагается параметр для классификаци

Tools of case linguistics

В статье рассмотрено несколько корпусов русского языка. Описаны цели, с которыми такие корпуса создавались, как они устроены и то, какие результаты у них есть на сегодняшний день.In article some cases of Russian are considered. The purposes with which such cases were created are described as they are arranged also what results they have today

Application of the random walk model for description Russian-language texts

В статье рассматривается проблема анализа и атрибуции текста с помощью модели случайных блужданий. В качестве элемента атрибуции предлагается коэффициент пропорциональности в законе Эйнштейна, условно названный коэффициентом диффузии. В ходе работы было сделано предположение, что коэффициент диффузии связан с формой коммуникации между автором и читателем.The paper considers the problem of analysis is and attribution of text using the random walk model. One of elements is coefficient of proportionality in Einstein law, which is named conventionally diffusion coefficient. We suppose that diffusion coefficient is associated with form of communication between author and reader

Usefulness of data from magnetic resonance imaging to improve prediction of dementia: population based cohort study

© BMJ Publishing Group Ltd 2015. OBJECTIVE: To determine whether the addition of data derived from magnetic resonance imaging (MRI) of the brain to a model incorporating conventional risk variables improves prediction of dementia over 10 years of follow-up. DESIGN: Population based cohort study of individuals aged ≥65. SETTING: The Dijon magnetic resonance imaging study cohort from the Three-City Study, France. PARTICIPANTS: 1721 people without dementia who underwent an MRI scan at baseline and with known dementia status over 10 years' follow-up. MAIN OUTCOME MEASURE: Incident dementia (all cause and Alzheimer's disease). RESULTS: During 10 years of follow-up, there were 119 confirmed cases of dementia, 84 of which were Alzheimer's disease. The conventional risk model incorporated age, sex, education, cognition, physical function, lifestyle (smoking, alcohol use), health (cardiovascular disease, diabetes, systolic blood pressure), and the apolipoprotein genotype (C statistic for discrimination performance was 0.77, 95% confidence interval 0.71 to 0.82). No significant differences were observed in the discrimination performance of the conventional risk model compared with models incorporating data from MRI including white matter lesion volume (C statistic 0.77, 95% confidence interval 0.72 to 0.82; P=0.48 for difference of C statistics), brain volume (0.77, 0.72 to 0.82; P=0.60), hippocampal volume (0.79, 0.74 to 0.84; P=0.07), or all three variables combined (0.79, 0.75 to 0.84; P=0.05). Inclusion of hippocampal volume or all three MRI variables combined in the conventional model did, however, lead to significant improvement in reclassification measured by using the integrated discrimination improvement index (P=0.03 and P=0.04) and showed increased net benefit in decision curve analysis. Similar results were observed when the outcome was restricted to Alzheimer's disease. CONCLUSIONS: Data from MRI do not significantly improve discrimination performance in prediction of all cause dementia beyond a model incorporating demographic, cognitive, health, lifestyle, physical function, and genetic data. There were, however, statistical improvements in reclassification, prognostic separation, and some evidence of clinical utility