Technology in elt to improve learners’ communicative competence

The topic of technology has become very popular in ELT, especially with the transition to online education in the COVID pandemic times. There are a multitude of benefits of using technology for students (and teachers). However, teachers often believe that they are not tech-savvy and avoid using technology. This article will prepare educators to implement various tools to raise their self-confidence in terms of technology use. The article includes the latest research on the topic of technology in teaching languages, and offers practical applications and authentic tasks to raise teachers’ tech awareness and readiness. Enhancing teachers’ technological skills can help design curriculum and lesson plans more efficiently. By doing so, teachers can keep students engaged and motivated through digitally generated activities. The article will offer ideas for a fun schema activating task, a theoretical discussion, and practical applications of the suggested digital tools. The key takeaway from this article is that tea

Laser-free method for creation of two-mode squeezed state and beam-splitter transformation with trapped ions

We propose a laser-free method for creation of a phonon two-mode squeezed state and a beam-splitter transformation, using time-varying electric fields and non-linear couplings between the normal modes in a linear ion crystal. Such non-linear Coulomb-mediated interactions between the collective vibrational modes arise under specific trap-frequency conditions in an ion trap. We study the quantum metrological capability for parameter estimation of the two quantum states and show that a Heisenberg limit of precision can be achieved when the initial state with $n$ phonons evolves under the action of the beam-splitter transformation. Furthermore, we show that the phonon non-linearity and the spin-dependent force can be used for creation of a three-qubit Fredkin gate.Comment: 7 pages, 6 figure

The world's largest oil and gas hydrocarbon deposits: ROSA database and GIS project development

This article proposes the use of Big Data principles to support the future extraction of hydrocarbon resources. It starts out by assessing the possible energy-system transformations in order to shed some light on the future need for hydrocarbon resource extraction and corresponding drilling needs. The core contribution of this work is the development of a new database and the corresponding GIS (geographic information system) visualization project as basis for an analytical study of worldwide hydrocarbon occurrences and development of extraction methods. The historical period for the analytical study is from 1900 to 2000. A number of tasks had to be implemented to develop the database and include information about data collection, processing, and development of geospatial data on hydrocarbon deposits. Collecting relevant information made it possible to compile a list of hydrocarbon fields, which have served as the basis for the attribute database tables and its further filling. To develop an attribute table, the authors took into account that all accumulated data features on hydrocarbon deposits and divided them into two types: static and dynamic. Static data included the deposit parameters that do not change over time. On the other hand, dynamic data are constantly changing. Creation of a web service with advanced functionality based on the Esri Geoportal Server software platform included search by parameter presets, viewing and filtering of selected data layers using online mapping application, sorting of metadata, corresponding bibliographic information for each field and keywords accordingly. The collected and processed information by ROSA database and GIS visualization project includes more than 100 hydrocarbon fields across different countries

Chemical Composition and Energy Nutritional Value of the Meat of Guinea Fowls (Numidameleagris), Fattened to different Ages

The aim of the study was to investigate the chemical composition and energy content of the meat of young Guinea-fowls, with different duration of the fattening period, raised in a free-range, semi-intensive production system. The authors establish the following data: dry matter content- from 27.08 to 28.82% in breast muscle and from 23.83 to 26.56% in thigh muscle; crude protein in dry matter –from 86.19to 93.54% in breastand from 82.02 to 87.84% in thigh muscle; crude fat in dry matter - from 5.64 to 7.58% in breast and from 9.02 to 11.05% in thigh muscles. The average energy content in 100 g dry matter varies from 23.7 (breast muscle, 16 weeks of age) to 25.07 kJ (thigh muscle, 24 weeks of age)

Rare KIT (CD117) expression in multiple myeloma abrogates the usefulness of imatinib mesylate treatment

Background: Imatinib mesylate blocks the tyrosine kinase activity of KIT (CD117) and is an effective treatment for gastrointestinal stromal tumors. In multiple myeloma, KIT expression has been detected by flow cytometry in about 33% of specimens, but no previous immunohistochemical assessment has yet been made of the expression pattern of KIT. Materials and methods: We performed immunohistochemical analyses of 100 patients, including 72 with multiple myeloma (MM), 8 with lymphoplasmacytic lymphoma (LPL), 10 with monoclonal gammopathy of undetermined significance (MGUS) and 10 with reactive plasmocytosis. One KIT-positive MM was sequenced using polymerase chain reaction analysis. Results: In MM, only 2 cases (2.8%) were KIT positive. The great majority of the cases (97, 2%) did not express the KIT receptor tyrosine kinase. No mutation of the c-kit gene was detected. Conclusions: KIT expression is a rare event in MM and not detectable in MGUS and LPL. Therefore, treatment with imatinib is unlikely to be effective in these patient

STUDY OF FREE AMINO ACIDS IN WHITE RAT KIDNEYS FOLLOWING TREATMENT WITH MERCURY BICHLORIDE AND PROTEIN HYDROLYSATE "HYDROPROT"

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Eigenvector alignment : assessing functional network changes in amnestic mild cognitive impairment and Alzheimer's disease

Eigenvector alignment, introduced herein to investigate human brain functional networks, is adapted from methods developed to detect influential nodes and communities in networked systems. It is used to identify differences in the brain networks of subjects with Alzheimer’s disease (AD), amnestic Mild Cognitive Impairment (aMCI) and healthy controls (HC). Well-established methods exist for analysing connectivity networks composed of brain regions, including the widespread use of centrality metrics such as eigenvector centrality. However, these metrics provide only limited information on the relationship between regions, with this understanding often sought by comparing the strength of pairwise functional connectivity. Our holistic approach, eigenvector alignment, considers the impact of all functional connectivity changes before assessing the strength of the functional relationship, i.e. alignment, between any two regions. This is achieved by comparing the placement of regions in a Euclidean space defined by the network's dominant eigenvectors. Eigenvector alignment recognises the strength of bilateral connectivity in cortical areas of healthy control subjects, but also reveals degradation of this commissural system in those with AD. Surprisingly little structural change is detected for key regions in the Default Mode Network, despite significant declines in the functional connectivity of these regions. In contrast, regions in the auditory cortex display significant alignment changes that begin in aMCI and are the most prominent structural changes for those with AD. Alignment differences between aMCI and AD subjects are detected, including notable changes to the hippocampal regions. These findings suggest eigenvector alignment can play a complementary role, alongside established network analytic approaches, to capture how the brain's functional networks develop and adapt when challenged by disease processes such as AD

OA031-02. Regulatory T cells inhibit CD8 T cell proliferation in HIV-1 infection through CD39/adenosine pathway

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