This paper applies methods of multiple resolution map comparison to quantify characteristics for 13 applications of 9 different popular peer-reviewed land change models. Each modeling application simulates change of land categories in raster maps from an initial time to a subsequent time. For each modeling application, the statistical methods compare: (1) a reference map of the initial time, (2) ence map of the subsequent time, and (3) a prediction map of the subsequent time. The three possible two-map comparisons for each application characterize: (1) the dynamics of the landscape, (2) the behavior of the model, and (3) the accuracy of the prediction. The three-map comparison for each application specifies the amount of the prediction's accuracy that is attributable to land persistence versus land change. Results show that the amount of error is larger than the amount of correctly predicted change for 12 of the 13 applications at the resolution of the raw data. The applications are summarized and compared using two statistics: the null resolution and the figure of merit. According to the figure of merit, the more accurate applications are the 123Comparing the input, output, and validation maps for several models of land change 13 ones where the amount of observed net change in the reference maps is larger. This paper facilitates communication among land change modelers, because it illustrates the range of results for a variety of models using scientifically rigorous, generally applicable, and intellectually accessible statistical techniques. JEL Classification

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The fourth industrial revolution (Industry 4.0) with the breakthrough of internet and artificial intelligence has had a strong impact, changing all aspects of global socio-economic life. Digital transformation in the spread of Industry 4.0 is no longer a choice but has become an inevitable development trend for businesses to truly stand up to the times. Digital transformation is the transformation of business activities, processes, products, and models to fully leverage the opportunities of digital technologies, characterised by development, growth, innovation, and disruption. In particular, "digital disruption" is the situation when new technology competes with the traditional business way that we now often refer to under the concepts of cloud computing, big data, and internet of things (IoT). This competition will help businesses utilise digitised data and processes to create a new model that is more efficient and convenient. Digital technologies in oil and gas companies can have a significant business impact as it contributes to increasing hydrocarbon recovery, ensuring safety across the business ecosystem, and improving operational reliability. This paper addresses the oil and gas industry’s trends in digital transformation and the initiatives at Bien Dong POC.

Abstract. In this study, total 41 Vietnamese rice landraces were evaluated for their salt tolerance in the laboratory and field conditions. Amongst them, 15 landraces have shown moderate to high salinity tolerance in both screening conditions. The three landraces Chanh trui, Cuom dang 2 and Nep cuc have revealed the highest salt tolerance which were similar to the Pokkali. However, with time and levels of salt treatments, salt injury symptoms were clearly observed in all landraces with different symptoms. All plants growth parameters were remarkably reduced in all landraces under increasing salt-treated concentrations. By use of molecular marker RM217 linked with salinity tolerance QTL located on the chromosome 4, 11 landraces have been found to carry the allen involving in salt tolerance. This study has provided useful information on salinity tolerance of rice landraces for breeding programs to deal with the climate change in this country.