1,721,307 research outputs found
The LU-LC conjecture is false
The LU-LC conjecture is an important open problem concerning the structure of entanglement of states described in the stabilizer formalism. It states that two local unitary equivalent stabilizer states are also local Clifford equivalent. If this conjecture were true, the local equivalence of stabilizer states would be extremely easy to characterize. Unfortunately, however, based on the recent progress made by Gross and Van den Nest, we find that the conjecture is false. © Rinton Press
Streamflow of the Betwa River under the Combined Effect of LU-LC and Climate Change
We estimate the combined effect of climate and landuse-landcover (LU-LC) change on the streamflow of the Betwa River; a semi-arid catchment in Central India. We have used the observed and future bias-corrected climatic datasets from 1980–2100. To assess the LU-LC change in the catchment, we have processed and classified the Landsat satellite images from 1990–2020. We have used Artificial Neural Network (ANN) based Cellular Automata (CA) model to simulate the future LU-LC. Further, we coupled the observed and projected LU-LC and climatic variables in the SWAT (Soil and water assessment tool) model to simulate the streamflow of the Betwa River. In doing so, we have setup this model for the observed (1980–2000 and 2001–2020) and projected (2023–2060 and 2061–2100) time periods by using the LU-LC of the years 1990, 2018, and 2040, 2070, respectively. We observed that the combined effect of climate and LU-LC change resulted in the reduction in the mean monsoon stream flow of the Betwa River by 16% during 2001–2020 as compared to 1982–2000. In all four CMIP6 climatic scenarios (SSP126, SSP245, SSP370, and SSP585), the mean monsoon stream flow is expected to decrease by 39–47% and 31–47% during 2023–2060 and 2061–2100, respectively as compared to the observed time period 1982–2020. Furthermore, average monsoon rainfall in the catchment will decrease by 30–35% during 2023–2060 and 23–30% during 2061–2100 with respect to 1982–2020
Investigation and Prediction of the Land Use/Land Cover (LU/LC) and Land Surface Temperature (LST) Changes for Mashhad City in Iran during 1990–2030
Studies on how cities are affected by urban heat islands (UHI) are critical nowadays for a better understanding of the connected effects and for providing helpful insights for sustainable city development planning. In this study, Landsat-5 Thematic Mapper (TM), Landsat-7 Enhanced Thematic Mapper+ (ETM+), and Landsat-8 Operational Land Imager (OLI) images were used to assess the dynamics of the spatiotemporal pattern of land use/land cover (LU/LC) and land surface temperature (LST) in the metropolitan city of Mashhad, Iran in the period between 1990 and 2019. The Markov chain model (MCM) was used to predict LU/LC and LST for 2030. In the analyzed LU/LC maps, three LU/LC classes were distinguished, including built-up land (BUL), vegetated land (VL), and bare land (BL) using the maximum likelihood (ML) classification method. The collected data showed different variations in the geographical pattern of Mashhad LST during the research period that impacted the LST in this metropolis. The study evaluated the variations in LU/LC classes and evaluated their impact on the LST. The value of the LST was positively correlated with the occurrence of the built-up land (BUL), and with the bare land areas, while it was negatively correlated with the occurrence of the VL areas. The analysis of changes observed over three decades with 10-year intervals and the prediction of the LU/LC and LST for 2030 constitute an important contribution to the delineation of the dynamics of long LU/LC and LST records. These innovative results may have an important impact on policymaking fostering environmental sustainability, such as the control and management of urban expansion of Mashhad in connection with UHI
Investigation and Prediction of the Land Use/Land Cover (LU/LC) and Land Surface Temperature (LST) Changes for Mashhad City in Iran during 1990–2030
Studies on how cities are affected by urban heat islands (UHI) are critical nowadays for a better understanding of the connected effects and for providing helpful insights for sustainable city development planning. In this study, Landsat-5 Thematic Mapper (TM), Landsat-7 Enhanced Thematic Mapper+ (ETM+), and Landsat-8 Operational Land Imager (OLI) images were used to assess the dynamics of the spatiotemporal pattern of land use/land cover (LU/LC) and land surface temperature (LST) in the metropolitan city of Mashhad, Iran in the period between 1990 and 2019. The Markov chain model (MCM) was used to predict LU/LC and LST for 2030. In the analyzed LU/LC maps, three LU/LC classes were distinguished, including built-up land (BUL), vegetated land (VL), and bare land (BL) using the maximum likelihood (ML) classification method. The collected data showed different variations in the geographical pattern of Mashhad LST during the research period that impacted the LST in this metropolis. The study evaluated the variations in LU/LC classes and evaluated their impact on the LST. The value of the LST was positively correlated with the occurrence of the built-up land (BUL), and with the bare land areas, while it was negatively correlated with the occurrence of the VL areas. The analysis of changes observed over three decades with 10-year intervals and the prediction of the LU/LC and LST for 2030 constitute an important contribution to the delineation of the dynamics of long LU/LC and LST records. These innovative results may have an important impact on policymaking fostering environmental sustainability, such as the control and management of urban expansion of Mashhad in connection with UHI.Shanghai Municipal Science and Technology CommissionFCT (Fundação para a Ciência e a Tecnologia
Going Beyond Counting First Authors in Author Co-citation Analysis
The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Techniques and Challenges of the Machine Learning Method for Land Use/Land Cover (LU/LC) Classification in Remote Sensing Using the Google Earth Engine
In order to accurately observe the globe, land use and land cover are crucial. Due to the proliferation of several global modifications associated with the existence of the planet, land use/land cover (LU/LC) classification is now regarded as a topic of highest significance in the natural environment and an important field to be researched by researchers. Google Earth provides satellite image dataset which contains high-resolution images; these images are used to analyze the land area. In order to address the dearth of review articles throughout the land use/land cover classification phase, we proposed a full evaluation, which might help researchers continue their work. Therefore, the purpose of this study is to investigate the methodical steps involved in classifying land use and land cover utilizing the Google Earth platform. The most widely used techniques researchers employ to achieve LU/LC classification using Google Earth Engine are examined in this work. The classification of land use and land cover for a specific region using time series was covered in this study, along with the many types of land use and land cover classes and the approach employed by Google Earth. The limits of the GEE tool and difficulties encountered during the process of classifying land use and cover have also been covered in this survey document. The importance of this review rests in inspiring future scholars to tackle the LU/LC analysis problem successfully, and this study offers researchers a road map for assessing land use/land cover classification
Appropriate Similarity Measures for Author Cocitation Analysis
We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
A futuristic survey of the effects of LU/LC change on stream flow by CA–Markov model: a case of the Nekarood watershed, Iran
Land use (LU) or land cover (LC) is a critical factor dictating the amount of available water in runoff and groundwater. LU/LC Land use (LU) or land cover (LC) is a critical factor which can determine amount of available water in runoff and groundwater. In this study future effect of LU/LC change on stream flow in Nekarood watershed is investigated by Soil Water Assessment Tool (SWAT). Land use maps (1986–2016) based on Landsat TM and ETM+ satellite imagery are used. Furthermore, land use projection is performed by CA-Markov for the future period of 2016–2030. According to the results, agriculture and residential land use are increased by 40%, 28%, 38% and 31% respectively, and forest area is reduced by 12% and 6% during 1986–2001 and 2001–2016, respectively. Moreover, land use projection results showed that from 2016 to 2030 forest area will decrease by 6%, residential areas and agricultural will increase by 34% and 19%, respectively
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