Instructional design of foreign language blended courses

The article deals with different models of virtual environment integration in the educational process, including those in the National Research Tomsk Polytechnic University. The paper focuses on the motivational reflective model of electronic course design for foreign language teaching purposes. The authors describe the specifics of the five stages / structural elements of the model, evaluate evidence from experimental research, and offer a time-plan for foreign language five-stages-courses in blended learning

A novel three-colour fluorescence in situ hybridization approach for the detection of t(7;12)(q36;p13) in acute myeloid leukaemia reveals new cryptic three way translocation t(7;12;16)

© 2013 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).The t(7;12)(q36;p13) translocation is a recurrent chromosome abnormality that involves the ETV6 gene on chromosome 12 and has been identified in 20–30% of infant patients with acute myeloid leukaemia (AML). The detection of t(7;12) rearrangements relies on the use of fluorescence in situ hybridization (FISH) because this translocation is hardly visible by chromosome banding methods. Furthermore, a fusion transcript HLXB9-ETV6 is found in approximately 50% of t(7;12) cases, making the reverse transcription PCR approach not an ideal screening method. Considering the report of few cases of variant translocations harbouring a cryptic t(7;12) rearrangement, we believe that the actual incidence of this abnormality is higher than reported to date. The clinical outcome of t(7;12) patients is believed to be poor, therefore an early and accurate diagnosis is important in the clinical management and treatment. In this study, we have designed and tested a novel three-colour FISH approach that enabled us not only to confirm the presence of the t(7;12) in a number of patients studied previously, but also to identify a cryptic t(7;12) as part of a complex rearrangement. This new approach has proven to be an efficient and reliable method to be used in the diagnostic setting

Mid-summer snow-free albedo across the Arctic tundra was mostly stable or increased over the past two decades

Arctic vegetation changes, such as increasing shrub-cover, are expected to accelerate climate warming through increased absorption of incoming radiation and corresponding decrease in summer shortwave albedo. Here we analyze mid-summer shortwave land-surface albedo and its change across the pan-Arctic region based on MODIS satellite observations over the past two decades (2000-2021). In contrast to expectations, we show that terrestrial mid-summer shortwave albedo has not significantly changed in 82% of the pan-Arctic region, while 14% show an increase and 4% a decrease. The total median significant change was 0.014 cumulative over the past 22 years. By analyzing the visible and near-/shortwave-infrared range separately, we demonstrate that the slight increase arises from an albedo increase in the near-/shortwave infrared domain while being partly compensated by a decrease in visible albedo. A similar response was found across different tundra vegetation types. We argue that this increase in reflectance is typical with increasing biomass as a result of increased multiple reflection in the canopy. However, CMIP6 global climate model albedo predictions showed the opposite sign and different spatial patterns of snow-free summer albedo change compared to satellite-derived results. We suggest that a more sophisticated vegetation parametrization might reduce this discrepancy, and provide albedo estimates per vegetation type

Digitalization in construction: transformation of procedural approaches and project optimization in order to increase the profitability of the industry

The article is an in-depth analysis of the impact of digital technologies on the construction industry. In the course of the study, the authors delve into the process of transformation of traditional methods of work, emphasizing the key changes provided by digital approaches. The focus is on design optimization and its role in improving the efficiency of construction processes. The paper also discusses in detail the digitalization strategies aimed at achieving specific goals, in particular, to increase the profitability of the industry. The authors give practical examples of successful implementation of digital innovations in construction, discussing their impact on the final results of projects. The review provides readers with a deep understanding of how digital technologies are shaping the future of the construction industry and how their integration can lead to a significant improvement in the profitability of the industry. The article also examines the main problems faced by the construction industry and how digital technologies can offer innovative solutions to solve them. It identifies not only technical changes related to the introduction of digital processes, but also changes in organizational culture and project management. Special attention is paid to the issues of safety, standardization and sustainability in the context of digitalization of construction. The consequences of digital transformations on existing business models are analyzed and assumptions are made about the future development of the industry in the conditions of universal digitalization. Thus, the article provides a study of the digital revolution in construction, providing readers with an in-depth analysis of not only technological changes, but also the broad impact of digitalization on all aspects of the construction industry

Genomic and phenotypic analysis of Vavilov's historic landraces reveals the impact of environment and genomic islands of agronomic traits.

The Vavilov Institute of Plant Genetic Resources (VIR), in St. Petersburg, Russia, houses a unique genebank, with historical collections of landraces. When they were collected, the geographical distribution and genetic diversity of most crops closely reflected their historical patterns of cultivation established over the preceding millennia. We employed a combination of genomics, computational biology and phenotyping to characterize VIR's 147 chickpea accessions from Turkey and Ethiopia, representing chickpea's center of origin and a major location of secondary diversity. Genotyping by sequencing identified 14,059 segregating polymorphisms and genome-wide association studies revealed 28 GWAS hits in potential candidate genes likely to affect traits of agricultural importance. The proportion of polymorphisms shared among accessions is a strong predictor of phenotypic resemblance, and of environmental similarity between historical sampling sites. We found that 20 out of 28 polymorphisms, associated with multiple traits, including days to maturity, plant phenology, and yield-related traits such as pod number, localized to chromosome 4. We hypothesize that selection and introgression via inadvertent hybridization between more and less advanced morphotypes might have resulted in agricultural improvement genes being aggregated to genomic 'agro islands', and in genotype-to-phenotype relationships resembling widespread pleiotropy

Vegetation type is an important predictor of the arctic summer land surface energy budget

Despite the importance of high-latitude surface energy budgets (SEBs) for land-climate interactions in the rapidly changing Arctic, uncertainties in their prediction persist. Here, we harmonize SEB observations across a network of vegetated and glaciated sites at circumpolar scale (1994–2021). Our variance-partitioning analysis identifies vegetation type as an important predictor for SEB-components during Arctic summer (June-August), compared to other SEB-drivers including climate, latitude and permafrost characteristics. Differences among vegetation types can be of similar magnitude as between vegetation and glacier surfaces and are especially high for summer sensible and latent heat fluxes. The timing of SEB-flux summer-regimes (when daily mean values exceed 0 Wm−2) relative to snow-free and -onset dates varies substantially depending on vegetation type, implying vegetation controls on snow-cover and SEB-flux seasonality. Our results indicate complex shifts in surface energy fluxes with land-cover transitions and a lengthening summer season, and highlight the potential for improving future Earth system models via a refined representation of Arctic vegetation types

Russian Arctic Vegetation Archive—A new database of plant community composition and environmental conditions

Motivation: The goal of the Russian Arctic Vegetation Archive (AVA-RU) is to unite and harmonize data of plot-based plant species and their abundance, vegetation structure and environmental variables from the Russian Arctic. This database can be used to assess the status of the Russian Arctic vegetation and as a baseline to document biodiversity changes in the future. The archive can be used for scientific studies as well as to inform nature protection and restoration efforts. Main types of variables contained: The archive contains 2873 open-access geobotanical plots. The data include the full species. Most plots include information on the horizontal (cover per species and morphological group) and vertical (average height per morphological group) structure of vegetation, site and soil descriptions and data quality estimations. In addition to the open-access data, the AVA-RU website contains 1912 restricted-access plots. Spatial location and grain: The plots of 1–100 m2 size were sampled in Arctic Russia and Scandinavia. Plots in Russia covered areas from the West to the East, including the European Russian Arctic (Kola Peninsula, Nenets Autonomous district), Western Siberia (Northern Urals, Yamal, Taza and Gydan peninsulas), Central Siberia (Taymyr peninsula, Bolshevik island), Eastern Siberia (Indigirka basin) and the Far East (Wrangel island). About 72% of the samples are georeferenced. Time period and grain: The data were collected once at each location between 1927 and 2022. Major taxa and level of measurement: Plots include observations of >1770 vascular plant and cryptogam species and subspecies. Software format: CSV files (1 file with species list and abundance, 1 file with environmental variables and vegetation structure) are stored at the AVA-RU website (https://avarus.space/), and are continuously updated with new datasets. The open-access data are available on Dryad and all the datasets have a backup on the server of the University of Zurich. The data processing R script is available on Dryad

Vegetation type is an important predictor of the arctic summer land surface energy budget

Despite the importance of high-latitude surface energy budgets (SEBs) for land-climate interactions in the rapidly changing Arctic, uncertainties in their prediction persist. Here, we harmonize SEB observations across a network of vegetated and glaciated sites at circumpolar scale (1994-2021). Our variance-partitioning analysis identifies vegetation type as an important predictor for SEB-components during Arctic summer (June-August), compared to other SEB-drivers including climate, latitude and permafrost characteristics. Differences among vegetation types can be of similar magnitude as between vegetation and glacier surfaces and are especially high for summer sensible and latent heat fluxes. The timing of SEB-flux summer-regimes (when daily mean values exceed 0 Wm(-2)) relative to snow-free and -onset dates varies substantially depending on vegetation type, implying vegetation controls on snow-cover and SEB-flux seasonality. Our results indicate complex shifts in surface energy fluxes with land-cover transitions and a lengthening summer season, and highlight the potential for improving future Earth system models via a refined representation of Arctic vegetation types.An international team of researchers finds high potential for improving climate projections by a more comprehensive treatment of largely ignored Arctic vegetation types, underscoring the importance of Arctic energy exchange measuring stations.Peer reviewe

Vegetation type is an important predictor of the arctic summer land surface energy budget

Despite the importance of high-latitude surface energy budgets (SEBs) for land-climate interactions in the rapidly changing Arctic, uncertainties in their prediction persist. Here, we harmonize SEB observations across a network of vegetated and glaciated sites at circumpolar scale (1994–2021). Our variance-partitioning analysis identifies vegetation type as an important predictor for SEB-components during Arctic summer (June-August), compared to other SEB-drivers including climate, latitude and permafrost characteristics. Differences among vegetation types can be of similar magnitude as between vegetation and glacier surfaces and are especially high for summer sensible and latent heat fluxes. The timing of SEB-flux summer-regimes (when daily mean values exceed 0 Wm−2) relative to snow-free and -onset dates varies substantially depending on vegetation type, implying vegetation controls on snow-cover and SEB-flux seasonality. Our results indicate complex shifts in surface energy fluxes with land-cover transitions and a lengthening summer season, and highlight the potential for improving future Earth system models via a refined representation of Arctic vegetation types