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  • 2020-2024  (45)
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  • 1
    Keywords: Environment. ; Soil science. ; Physical geography. ; Geographic information systems. ; Environmental Sciences. ; Soil Science. ; Physical Geography. ; Geographical Information System.
    Description / Table of Contents: Chapter 1. Introduction and Background on Rainfall Erosivity Processes and Soil Erosion -- Chapter 2. Natural Conditions of Central Asia -- Chapter 3. Data sources on Rainfall and RUSLE model -- Chapter 4. Projected Rainfall Erosivity and Soil Erosion in Central Asia -- Chapter 5. Spatio-temporal variations and Projected Rainfall Erosivity and Erosivity Density in Kazakhstan -- Chapter 6. Conclusions and Recommendations.
    Abstract: This book analyses climate change influences on rainfall erosivity and soil erosion across Central Asia, provides an overview (past and projections) on the Central Asian countries where projected changes in rainfall erosivity and erosivity density are the greatest, and discusses the potential impacts on the environment across the region. This analysis is accomplished primarily using the RUSLE model with past and future climate projections, spatiotemporal variations of rainfall erosivity and soil erosion based on WorldClim, and Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models (for Central Asia and separately Kazakhstan). The relationship between precipitation characteristics and erosion has been well established, but spatial and temporal projections of future rainfall erosivity in a changing climate in Central Asia have not been published significantly. Therefore, assessing rainfall erosivity and its consequences can assist specialists and researchers in achieving the best practices for soil conservation. The result of this type of research is all-encompassing, and may reflect normal variations in other parts of the world (for example, the arid and semi-arid regions) and is inherently limited to the Central Asian region.
    Type of Medium: Online Resource
    Pages: XVIII, 84 p. 36 illus., 35 illus. in color. , online resource.
    Edition: 1st ed. 2021.
    ISBN: 9783030635091
    Series Statement: SpringerBriefs in Environmental Science,
    DDC: 333.7
    Language: English
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  • 2
    Publication Date: 2023-12-21
    Description: In this dissertation, concepts of the electronic architecture of automotive Integrated Safety System are developed as a cooperative approach of engineering process, dependable hardware architecture and software platform. The development process covers distributed rapid prototyping with virtual front-loading and correct-by-construction. Concepts of fault tolerant hardware architecture and dependability software services are discussed with design guidelines.
    Keywords: T1-995 ; dependable software platform ; Agreement ; dependability software services ; E/E-Architecture ; Integrated Safety System ; SW-Watchdog ; fault-tolerant hardware ; bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues
    Language: English
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  • 3
    Publication Date: 2024-04-05
    Description: Tensor network is a fundamental mathematical tool with a huge range of applications in physics, such as condensed matter physics, statistic physics, high energy physics, and quantum information sciences. This open access book aims to explain the tensor network contraction approaches in a systematic way, from the basic definitions to the important applications. This book is also useful to those who apply tensor networks in areas beyond physics, such as machine learning and the big-data analysis. Tensor network originates from the numerical renormalization group approach proposed by K. G. Wilson in 1975. Through a rapid development in the last two decades, tensor network has become a powerful numerical tool that can efficiently simulate a wide range of scientific problems, with particular success in quantum many-body physics. Varieties of tensor network algorithms have been proposed for different problems. However, the connections among different algorithms are not well discussed or reviewed. To fill this gap, this book explains the fundamental concepts and basic ideas that connect and/or unify different strategies of the tensor network contraction algorithms. In addition, some of the recent progresses in dealing with tensor decomposition techniques and quantum simulations are also represented in this book to help the readers to better understand tensor network. This open access book is intended for graduated students, but can also be used as a professional book for researchers in the related fields. To understand most of the contents in the book, only basic knowledge of quantum mechanics and linear algebra is required. In order to fully understand some advanced parts, the reader will need to be familiar with notion of condensed matter physics and quantum information, that however are not necessary to understand the main parts of the book. This book is a good source for non-specialists on quantum physics to understand tensor network algorithms and the related mathematics.
    Keywords: Physics ; Physics ; Quantum physics ; Quantum optics ; Statistical physics ; Machine learning ; Elementary particles (Physics) ; Quantum field theory ; thema EDItEUR::P Mathematics and Science::PH Physics::PHJ Optical physics ; thema EDItEUR::P Mathematics and Science::PH Physics::PHQ Quantum physics (quantum mechanics and quantum field theory) ; thema EDItEUR::P Mathematics and Science::PH Physics::PHS Statistical physics ; thema EDItEUR::P Mathematics and Science::PH Physics::PHU Mathematical physics ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning ; thema EDItEUR::P Mathematics and Science::PH Physics::PHJ Optical physics ; thema EDItEUR::P Mathematics and Science::PH Physics::PHQ Quantum physics (quantum mechanics and quantum field theory) ; thema EDItEUR::P Mathematics and Science::PH Physics::PHS Statistical physics ; thema EDItEUR::P Mathematics and Science::PH Physics::PHU Mathematical physics ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning
    Language: English
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  • 4
    Publication Date: 2024-04-20
    Description: In order to study the relationship between the Large Igneous Province volcanism with OAE 1d. We used the mercury geochemical analyses, including element content, isotope values, and other related element and organic matter content data to study the mid-Cretaceous, especially Albian-Cenomanian, sediments in southern Tibet, which was located at the northern margin of the Indian plate at ~100 Ma. We herein provided all these geochemical data and some analytical methods.
    Keywords: EXPO; Exposure; mecury geochemistry; OAE 1d; Tibet; Tingri; volcanism
    Type: Dataset
    Format: application/zip, 72 kBytes
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  • 5
    Publication Date: 2024-06-18
    Description: This dataset comprises new data and previously published data on marine lipid biomarkers (brassicasterol, dinosterol, C37 alkenones, and the sum of them [∑PB]) in surface suspended particles at 334 stations from seven cruises between 2010 and 2015, and in surface sediments at 258 stations from eight cruises between 2006 and 2012 in the eastern China marginal seas (ECMS). Of all marine lipid biomarker data, 107 surface suspended particle samples were newly measured, with 227 surface suspended particle samples and 258 sediment samples previously published. We also provide the following oceanographic data, most of which were collected from published results (as described in the publication): sea surface temperature (SST, n = 273, from five cruises in summer of 2010–2015), salinity (n = 273, from five cruises in summer of 2010–2015), nutrient concentrations (dissolved inorganic nitrogen [DIN], dissolved inorganic phosphorus [DIP] and silicate [Si]) (n = 133, from three cruises in summer of 2011 and 2015) and Chl a (chlorophyll a, n = 229, from five cruises in summer of 2010–2014) in the surface water, as well as terrestrial biomarker [∑(C27 + C29 + C31) n-alkanes] contents (n = 226), TOC (total organic carbon content, n = 200), δ13CTOC (stable carbon isotope values for TOC, n=269), and sedimentation rate (n = 220) in surface sediments. Some data were measured using in situ CTD instrument in this study: sea surface temperature and salinity in the East China Sea in June 2010 and July 2013 (n = 54), and Chl a in the Changjiang River Estuary in August 2015 (n = 33). The contents of ∑(C27 + C29 + C31) n-alkanes in the southern Yellow Sea in April 2012 (n = 32) were also newly measured. The surface suspended particle samples were obtained by filtering on Whatman GF/F filters, and the surface sediments were collected by multiple corers or stainless-steel grab samplers. Marine and terrestrial lipid biomarkers were analyzed by gas chromatograph (Agilent 6890N) according to the method in Zhao et al. 2006 (doi: 10.1016/j.orggeochem.2005.08.022) and Wu et al. 2016 (doi: 10.1002/2015JG003167). The study resulting from this analysis has been published in Frontiers in Marine Science (doi:10.3389/fmars.2022.824181).
    Keywords: Alkenones; Biomarkers; marginal seas; sterol; Surface sediments; surface water
    Type: Dataset
    Format: application/zip, 4 datasets
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  • 6
    Publication Date: 2024-06-18
    Keywords: 24-Methylcholesta-5,22E-dien-3beta-ol; 4alpha,23,24-Trimethyl-5alpha-cholest-22E-en-3beta-ol; Alkenone, C37; Alkenones; Biomarkers; Chlorophyll a; Continuous flow analyzer; DATE/TIME; Depth, bottom/max; Depth, top/min; DEPTH, water; Eastern China Marginal Seas; ECMS_water_201006; ECMS_water_201106; ECMS_water_201107; ECMS_water_201307; ECMS_water_201408; ECMS_water_201508; ELEVATION; Event label; In situ CTD instrument; LATITUDE; LONGITUDE; marginal seas; Nitrogen, inorganic, dissolved; Phosphorus, inorganic, dissolved; Reference/source; Sea surface salinity; Sea surface temperature; see description in data abstract; Silicate; Station label; sterol; Sum Brassicasterol, Dinosterol and C37 alkenones; Surface sediments; surface water; Water sample; WS
    Type: Dataset
    Format: text/tab-separated-values, 3968 data points
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  • 7
    Publication Date: 2024-06-18
    Keywords: 24-Methylcholesta-5,22E-dien-3beta-ol; 4alpha,23,24-Trimethyl-5alpha-cholest-22E-en-3beta-ol; Alkenone, C37; Alkenones; Biomarkers; Box corer/grab; Carbon, organic, total; DATE/TIME; Depth, bottom/max; DEPTH, sediment/rock; Depth, top/min; Eastern China Marginal Seas; ECMS_sediment_200604_08; ECMS_sediment_200808; ECMS_sediment_200812; ECMS_sediment_201006; ECMS_sediment_201106_1; ECMS_sediment_201106_2; ECMS_sediment_201108; ECMS_sediment_201204; ELEVATION; Event label; LATITUDE; LONGITUDE; marginal seas; n-Alkane C27+C29+C31; Reference/source; see description in data abstract; Station label; sterol; Sum Brassicasterol, Dinosterol and C37 alkenones; Surface sediments; surface water
    Type: Dataset
    Format: text/tab-separated-values, 2526 data points
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  • 8
    Publication Date: 2024-06-18
    Keywords: Alkenones; Biomarkers; DATE/TIME; Eastern China Marginal Seas; ECMS_sediment_d13C_200808; ECMS_sediment_d13C_200812; ECMS_sediment_d13C_201106; ECMS_sediment_d13C_201110; ECMS_sediment_d13C_201205; Elementar IsoPrime 100 isotope ratio mass spectrometer; Event label; LATITUDE; LONGITUDE; marginal seas; Reference/source; Station label; sterol; Surface sediments; surface water; Thermo Delta V mass spectrometer; Thermo Delta V mass spectrometer and Elementar IsoPrime 100 isotope ratio mass spectrometer; δ13C, total organic carbon
    Type: Dataset
    Format: text/tab-separated-values, 807 data points
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  • 9
    Publication Date: 2024-06-18
    Keywords: 210Pb and 137Cs; Alkenones; Biomarkers; Date of determination; Eastern China Marginal Seas; ECMS_sedimentation_rate; LATITUDE; LONGITUDE; marginal seas; MULT; Multiple investigations; Reference/source; Sedimentation rate per year; Station label; sterol; Surface sediments; surface water
    Type: Dataset
    Format: text/tab-separated-values, 832 data points
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  • 10
    Publication Date: 2024-01-08
    Description: Four halophilic archaeal strains, YPL8 T , SLN56 T , LT61 T and KZCA68 T , were isolated from a salt mine, saline soil and a salt lake located in different regions of China. Sequence similarities of 16S rRNA and rpoB′ genes among strains YPL8 T , SLN56 T , LT61 T and the current members of Natrinema were 94.1–98.2 % and 89.3–95.1 %, respectively, while these values among strain KZCA68 T and the current members of Haloterrigena were 97.2–97.4 % and 91.7–91.9 %, respectively. The average nucleotide identity, in silico DNA–DNA hybridization and average amino acid identity values among these four strains and their closely related species were all lower than the threshold values for species boundary. All four strains were unable to hydrolyse casein, gelatin, or Tween 80. Strain YPL8 T contained phosphatidic acid (PA), phosphatidylglycerol (PG), phosphatidylglycerol phosphate methyl ester (PGP-Me), sulfated mannosyl glucosyl diether (S-DGD-1), disulfated mannosyl glucosyl diether (S 2 -DGD) and sulfated mannosyl glucosyl diether-phosphatidic acid (S-DGD-PA). Strain SLN56 T contained PA, PG, phosphatidylglycerol sulphate (PGS), PGP-Me, S-DGD-1, S 2 -DGD and S-DGD-PA. Strain LT61 T contained PA, PG, PGS, PGP-Me, S-DGD-1 and S 2 -DGD. The phospholipids of strain KZCA68 T were PA, PG and PGP-Me. These results showed that strains YPL8 T (=CGMCC 1.13883 T =JCM 31181 T ), SLN56 T (=CGMCC 1.14945 T =JCM 30832 T ) and LT61 T (=CGMCC 1.14942 T =JCM 30668 T ) represent novel species of the genus Natrinema , for which the names, Natrinema halophilum sp. nov., Natrinema salinisoli sp. nov. and Natrinema amylolyticum sp. nov. are proposed. Strain KZCA68 T (=CGMCC 1.17211 T =JCM 34158 T ) represents a novel species of Haloterrigena , for which the name Haloterrigena alkaliphila sp. nov. is proposed.
    Type: Article , PeerReviewed
    Format: text
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