Psychological and Pedagogical Aspects of the Development of Integrative Readiness of Future Specialists for Professional Activity

The need to develop an integrative readiness of future specialists is a relevant scientific problem. The reasons for this could be based on the fact that that the specialists-to-be were expected to be involved in the fierce competition for vacancies and areas of activity, have modern information and communication tools, i.e. have an integrative readiness for professional activity. Institutions do not, however, have a single integration (interdisciplinary) framework for training, do not provide a comprehensive educational information, technical tools, strategies and technologies of education, reasoned psychological and pedagogical conditions. According to the author, the integrative readiness of future specialists for professional activity is a system-personality formation that reflects the unity of theoretical and managerial training and practical ability of students to comprehensively apply regulatory, socio-economic, psychological and pedagogical methods and technologies for solving different problems. This readiness reflects the unity of the motivational inclination of future specialists to professional activity and knowledge of practical technologies for solving a wide range of professional problems in personal and business interactions. The research methodology is based on the concept of key competence, which provides systematization, classification of significant problems, development of a matrix of significant problems, and determination of overall strategy, management technology of professional training development process. Students and teachers can use research materials can be used by in educational and practical activities; developers of content, organizational forms and methods of professional training to improve the practical component of curricula and standards of their development

Методика применения теории экстремальных значений для анализа данных

Проблематика. Для розв’язання задач моделювання і прогнозування на основі великих масивів (у тому числі вироджених) даних в умовах наявності невизначеності необхідно розробляти інтегровані інформаційні системи підтримки прийняття рішень (СППР). Пропонується методика застосування теорії екстремальних значень для побудови статистичних моделей та СППР на їх основі. Мета дослідження. Мета роботи полягає у застосуванні теорії екстремальних значень для аналізу й оцінювання параметрів моделей на основі випадкових вибірок даних. Необхідно розробити ефективну методику аналізу псевдовипадкових значень та оцінювання невідомих параметрів статистичних моделей; навести приклади аналізу за допомогою теорії екстремальних значень і створеного програмного інструментарію. Методика реалізації. Для розв’язання поставлених задач використано такі методи: процедури генерування псевдовипадкових послідовностей, ймовірнісні розподіли теорії екстремальних значень і методи оцінювання невідомих параметрів моделей. Запропоновано багатокрокову методику обробки екстремальних значень і розроблено СППР для аналізу та моделювання випадкових послідовностей. Результати дослідження. За допомогою створеної СППР і згенерованих статистичних даних, а також запропонованої методики побудовано процедуру аналізу екстремальних значень. Процедура призначена для подальшого застосування при оцінюванні прогнозних моделей процесів різної природи. Виконано порівняльний аналіз характеристик параметрів GEV-розподілів. Висновки. За допомогою розробленого інструментарію показано, що запропонований підхід до обробки екстремальних значень є зручним для аналізу вироджених масивів даних. Це підтверджується максимальним наближенням емпіричної кривої до теоретичної функції щільності розподілу. Порівняння результатів оцінювання параметрів моделей показало, що уточнення параметрів форми і масштабованості сприяє прискоренню збіжності оцінок.Background. To solve the problems of modeling and forecasting on the basis of large datasets (including singular ones) in conditions of uncertainty it is necessary to develop integrated information decision support systems (DSS). A methodology is proposed for application of extreme value theory for statistical models development and DSS on their basis. Objective. The goal of the study is in application of the extreme value theory for analysis and estimation of model parameters on the basis of random samples. It is necessary to develop an effective methodology for analysis of pseudorandom sequences and estimation of unknown model parameters; to present examples of analysis using extreme value theory and software developed. Methods. To solve the problems stated the following approaches were used: pseudorandom sequences generating procedures; probabilistic distributions of the extreme value theory, and methods for estimating unknown model parameters. A multistep methodology is proposed for extreme values processing and DSS is developed for analysis and modeling of pseudorandom sequences. Results. Using the DSS developed and generated statistical data as well as proposed methodology the procedure was developed for extreme values analysis. The procedure is to be used for estimating of forecasting models for the process of various origin. A comparative analysis of parameter characteristics for GEV-distributions was performed. Conclusions. Using the instrumentation developed it was shown that the proposed methodology for processing extreme values is convenient for analysis of singular datasets. This is substantiated with the high quality approximation of theoretical probability density by empirical curve. A comparison of model parameters estimation results showed that the estimates converge faster when parameters of form and scale are defined more exactly.Проблематика. Для решения задач моделирования и прогнозирования на основе больших массивов (в том числе вырожденных) данных в условиях наличия неопределенностей необходимо разрабатывать интегрированные информационные системы поддержки принятия решений (СППР). Предлагается методика применения теории экстремальных значений для построения статистических моделей и СППР на их основе. Цель исследования. Цель работы состоит в применении теории экстремальных значений для анализа и оценивания параметров моделей на основе случайных выборок данных. Необходимо разработать эффективную методику анализа псевдослучайных значений и оценивания неизвестных параметров моделей; привести примеры анализа с помощью теории экстремальных значений и программного инструментария. Методика реализации. Для решения поставленных задач использованы такие процедуры и методы: процедуры генерирования псевдослучайных последовательностей, вероятностные распределения теории экстремальных значений и методы оценивания неизвестных параметров моделей. Предложена многошаговая методика обработки экстремальных значений, и разработана СППР для анализа и моделирования случайных последовательностей. Результаты исследования. С помощью созданной СППР и сгенерированных статистических данных, а также предложенной методики построена процедура анализа экстремальных значений. Процедура предназначена для дальнейшего использования при оценивании прогнозных моделей процессов различной природы. Выполнен сравнительный анализ характеристик параметров GEV-распределений. Выводы. С помощью разработанного программного инструментария показано, что предложенный подход к обработке экстремальных значений представляет собой удобный инструмент анализа вырожденных массивов данных. Это подтверждается максимальным приближением эмпирической кривой к теоретической функции плотности распределения. Сравнение результатов оценивания параметров показало, что уточнение параметров формы и масштаба способствует ускорению сходимости оценок

Long gamma-ray bursts and core-collapse supernovae have different environments

When massive stars exhaust their fuel they collapse and often produce the extraordinarily bright explosions known as core-collapse supernovae. On occasion, this stellar collapse also powers an even more brilliant relativistic explosion known as a long-duration gamma-ray burst. One would then expect that long gamma-ray bursts and core-collapse supernovae should be found in similar galactic environments. Here we show that this expectation is wrong. We find that the long gamma-ray bursts are far more concentrated on the very brightest regions of their host galaxies than are the core-collapse supernovae. Furthermore, the host galaxies of the long gamma-ray bursts are significantly fainter and more irregular than the hosts of the core-collapse supernovae. Together these results suggest that long-duration gamma-ray bursts are associated with the most massive stars and may be restricted to galaxies of limited chemical evolution. Our results directly imply that long gamma-ray bursts are relatively rare in galaxies such as our own Milky Way.Comment: 27 pages, 4 figures, submitted to Nature on 22 August 2005, revised 9 February 2006, online publication 10 May 2006. Supplementary material referred to in the text can be found at http://www.stsci.edu/~fruchter/GRB/locations/supplement.pdf . This new version contains minor changes to match the final published versio

Prediction of breast self-examination in a sample of Iranian women: an application of the Health Belief Model

<p>Abstract</p> <p>Background</p> <p>Iranian women, many of whom live in small cities, have limited access to mammography and clinical breast examinations. Thus, breast self examination (BSE) becomes an important and necessary approach to detecting this disease in its early stages in order to limit its resultant morbidity and mortality. This study examined constructs arising from the Health Belief Model as predictors of breast self examination behavior in a sample of women living in Bandar Abbas, Iran.</p> <p>Methods</p> <p>This study was conducted in eight health centers located in Bandar Abbas, Iran. The sample consisted of 240 eligible women who were selected from referrals to the centers. The inclusion criteria were as follows: aged 30 years and over; and able to read and write Farsi. Women with breast cancer, who were pregnant, or breast feeding, were excluded from the study. Data were collected by using a self administered questionnaire which included demographic characteristics and Champion's Health Belief Model Scale. This instrument measures the concepts of disease susceptibility (3 items), seriousness (6 items), benefits (4 items), barriers (8 items) and self-efficacy (10 items).</p> <p>Results</p> <p>The subjects' mean age was 37.2 (SD = 6.1) years. Just under a third of the subjects (31.7%) had performed BSE in the past and 7.1% of them performed it at least monthly. Perceived benefits and perceived self-efficacy of the women who performed BSE were significantly higher compared with women who did not practice BSE (p < 0.03). Furthermore, perceived barriers were lower among those who had performed BSE (p < 0.001). Logistic regression analysis indicated that women who perceived fewer barriers (OR: 0.70, 95% CI: 0.63-0.77, p < 0.001) and had higher self-efficacy (OR: 1.08, 95% CI: 1.02-1.13, p = 0.003) were more likely to perform BSE (R²= 0.52).</p> <p>Conclusion</p> <p>Findings from this study indicated that perceived barriers and perceived self-efficacy could be predictors of BSE behavior among the sample of women. Therefore, BSE training programs that emphasize self-efficacy and address perceived barriers are recommended.</p

PTK (protein tyrosine kinase)-6 and HER2 and 4, but not HER1 and 3 predict long-term survival in breast carcinomas

The HER receptors are of therapeutic and prognostic significance in breast cancer, and their function is modulated by cytoplasmic tyrosine kinases like PTK6 (brk). We performed a retrospective study on archival breast cancer samples from patients with long follow-up and compared the protein expression between individual HERs and between HERs and the PTK6. Univariate and multivariate analyses were used to study the prognostic value of parameters. Metastases-free survival of patients for longer than 240 months was inversely associated (P⩽0.05) with nodal status, tumour size, and oestrogen receptor status, but was also directly associated with high protein expression levels of HER4 and PTK6 in Kaplan–Meier analysis. In multivariate analysis for metastases-free survival of >240 months, the stepwise selected parameters were tumour size (relative risk 3.1), PTK6 expression (0.4), and number of positive lymph nodes (1.2). Furthermore, we demonstrated a timedependence of the prognostic value attributed to the parameters. The HER receptors (HER2,4), but not PTK6, were independent prognostic markers for metastases-free survival at 60 months, whereas at 240 months PTK6 is the strongest prognostic marker. We demonstrate that PTK6 is a prognostic marker of metastases-free survival in breast cancer, and is independent of the classical morphological and molecular markers of lymph node involvement, tumour size, and HER2 status

A prospective compound screening contest identified broader inhibitors for Sirtuin 1

Potential inhibitors of a target biomolecule, NAD-dependent deacetylase Sirtuin 1, were identified by a contest-based approach, in which participants were asked to propose a prioritized list of 400 compounds from a designated compound library containing 2.5 million compounds using in silico methods and scoring. Our aim was to identify target enzyme inhibitors and to benchmark computer-aided drug discovery methods under the same experimental conditions. Collecting compound lists derived from various methods is advantageous for aggregating compounds with structurally diversified properties compared with the use of a single method. The inhibitory action on Sirtuin 1 of approximately half of the proposed compounds was experimentally accessed. Ultimately, seven structurally diverse compounds were identified

Enhanced electric conductivity at ferroelectric vortex cores in BiFeO3

In many large ensembles, the property of the system as a whole cannot be understood from studying the individual entities alone ¿ these ensembles can be made up by neurons in the brain, transport users in traffic networks or data packages in the Internet. The past decade has seen important progress in our fundamental understanding of what such seemingly disparate 'complex systems' have in common; some of these advances are surveyed here

Origins Space Telescope: Baseline mission concept

The Origins Space Telescope will trace the history of our origins from the time dust and heavy elements permanently altered the cosmic landscape to present-day life. How did galaxies evolve from the earliest galactic systems to those found in the Universe today? How do habitable planets form? How common are life-bearing worlds? To answer these alluring questions, Origins will operate at mid-and far-infrared (IR) wavelengths and offer powerful spectroscopic instruments and sensitivity three orders of magnitude better than that of the Herschel Space Observatory, the largest telescope flown in space to date. We describe the baseline concept for Origins recommended to the 2020 US Decadal Survey in Astronomy and Astrophysics. The baseline design includes a 5.9-m diameter telescope cryocooled to 4.5 K and equipped with three scientific instruments. A mid-infrared instrument (Mid-Infrared Spectrometer and Camera Transit spectrometer) will measure the spectra of transiting exoplanets in the 2.8 to 20 μm wavelength range and offer unprecedented spectrophotometric precision, enabling definitive exoplanet biosignature detections. The far-IR imager polarimeter will be able to survey thousands of square degrees with broadband imaging at 50 and 250 μm. The Origins Survey Spectrometer will cover wavelengths from 25 to 588 μm, making wide-area and deep spectroscopic surveys with spectral resolving power R ∼ 300, and pointed observations at R ∼ 40,000 and 300,000 with selectable instrument modes. Origins was designed to minimize complexity. The architecture is similar to that of the Spitzer Space Telescope and requires very few deployments after launch, while the cryothermal system design leverages James Webb Space Telescope technology and experience. A combination of current-state-of-the-art cryocoolers and next-generation detector technology will enable Origins\u27 natural background-limited sensitivity

Prothymosin alpha: a ubiquitous polypeptide with potential use in cancer diagnosis and therapy

The thymus is a central lymphoid organ with crucial role in generating T cells and maintaining homeostasis of the immune system. More than 30 peptides, initially referred to as “thymic hormones,” are produced by this gland. Although the majority of them have not been proven to be thymus-speciWc, thymic peptides comprise an eVective group of regulators, mediating important immune functions. Thymosin fraction Wve (TFV) was the Wrst thymic extract shown to stimulate lymphocyte proliferation and diVerentiation. Subsequent fractionation of TFV led to the isolation and characterization of a series of immunoactive peptides/polypeptides, members of the thymosin family. Extensive research on prothymosin (proT) and thymosin 1 (T1) showed that they are of clinical signiWcance and potential medical use. They may serve as molecular markers for cancer prognosis and/or as therapeutic agents for treating immunodeWciencies, autoimmune diseases and malignancies. Although the molecular mechanisms underlying their eVect are yet not fully elucidated proT and T1 could be considered as candidates for cancer immunotherapy. In this review, we will focus in principle on the eventual clinical utility of proT, both as a tumor biomarker and in triggering anticancer immune responses. Considering the experience acquired via the use of T1 to treat cancer patients, we will also discuss potential approaches for the future introduction of proT into the clinical setting