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  • 1
    Online Resource
    Online Resource
    Washington, D.C., : The World Bank,
    UID:
    almafu_9958246511802883
    Format: 1 online resource (31 pages)
    Series Statement: Policy research working papers.
    Content: This paper analyzes the dynamic effects of rate-of-return regulation on firms'emissions compliance behavior when the price of emissions permits is uncertain. The paper shows that uncertainty regarding the price of permits would motivate a regulated firm to adopt a more self-sufficient strategy and would reduce the cost-effectiveness of emission allowance trading. When allowance transactions are treated as capital investments, uncertainty could reverse the classic Averch-Johnson effect, so that a regulated firm would purchase fewer permits in the ex ante period than its unregulated counterpart. These results are driven by the asymmetric impact of a price change on the expected marginal value of allowances under rate-of-return regulation. A wider variation in the permit price and a decline in the regulated rate of return would amplify the asymmetry. These results have implications for the efficiency of the proposed global carbon trading system.
    Language: English
    URL: Volltext  (Deutschlandweit zugänglich)
    URL: Volltext  (kostenfrei)
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  • 2
    UID:
    almafu_BV046747526
    Format: 1 Online-Ressource (XXIV, 701 p. 321 illus., 198 illus. in color).
    Edition: 1st ed. 2020
    ISBN: 978-3-030-48513-9
    Series Statement: Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 322
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-48512-2
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-48514-6
    Language: English
    Keywords: Cloud Computing ; Intelligentes Stromnetz ; Kryptologie ; Electronic Commerce
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: Volltext  (URL des Erstveröffentlichers)
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  • 3
    Online Resource
    Online Resource
    London, United Kingdom : IntechOpen
    UID:
    b3kat_BV049498091
    Format: 1 Online-Ressource , Illustrationen, Diagramme
    ISBN: 9781837683956 , 9781837683949
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-1-83768-393-2
    Language: English
    URL: Volltext  (kostenfrei)
    URL: Volltext  (kostenfrei)
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  • 4
    Online Resource
    Online Resource
    New York, NY :Springer US :
    UID:
    almahu_9949251207702882
    Format: 1 online resource (XI, 226 p. 19 illus., 16 illus. in color.)
    Edition: 1st ed. 2020.
    ISBN: 1-0716-0904-1
    Series Statement: Methods in Molecular Biology, 2204
    Content: This book serves to introduce the technologies and applications of precision medicine. Beginning with a section on emerging experimental and bioinformatics technologies, the collection continues with chapters covering cancer studies, cardiovascular diseases, COPD and systemic lupus erythematosus, as well as the latest engineering and surgical developments in precision medicine. As a volume in the highly successful Methods in Molecular Biology series, this book presents key information from experts in the field. Authoritative and cutting-edge, Precision Medicine covers perspectives of precision medicine from basic research to clinical surgeries, from cancer to cardiovascular disease, from sequencing technology to big data analysis in the hope of broadening the horizons for researchers, engineers, and clinicians and accelerating the interdisciplinary precision medicine research and applications.
    Note: T Cell Receptor Repertoire Sequencing -- Nanopore Sequencing and Its Clinical Applications -- The Clinical Significance of Microsatellite Instability in Precision Treatment -- Applications of Network Analysis in Biomedicine -- Diagnosis and Treatment of Breast Cancer in the Precision Medicine Era -- Application and Analysis of Biomedical Imaging Technology in Early Diagnosis of Breast Cancer -- Recent Advances in DNA Repair Pathway and Its Application in Personalized Care of Metastatic Castration-Resistant Prostate Cancer (mCRPC) -- Methylation in Lung Cancer: A Brief Review -- Epstein–Barr Virus DNA in Nasopharyngeal Carcinoma: A Brief Review -- A Review on Cancer of Unknown Primary Origin: The Role of Molecular Biomarkers in the Identification Unknown Primary Origin -- DNA Methylation in Atrial Fibrillation and Its Potential Role in Precision Medicine -- PCSK9 Inhibition and Atherosclerosis: Current Therapeutic Option and Prospection -- Precise Drug Sequential Therapy Can Improve the Cardioversion Rate of Atrial Fibrillation with Valvular Disease after Radiofrequency Ablation -- Precision Medicine and Dilated Cardiomyopathy -- Research Progress in Pathogenesis of Total Anomalous Pulmonary Venous Connection -- Airway Inflammation Biomarker for Precise Management of Neutrophil-Predominant COPD -- Genome Variation and Precision Medicine in Systemic Lupus Erythematosus -- Precision Medicine in Tissue Engineering on Bone -- Progress of Clinical Application for Ex Vivo Lung Perfusion (EVLP) in Lung Transplantation.
    Additional Edition: ISBN 1-0716-0903-3
    Language: English
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  • 5
    Online Resource
    Online Resource
    New York, NY :Springer New York :
    UID:
    almahu_9949251598502882
    Format: 1 online resource (XII, 417 p. 48 illus., 38 illus. in color.)
    Edition: 1st ed. 2018.
    ISBN: 1-4939-7717-2
    Series Statement: Methods in Molecular Biology, 1754
    Content: This volume introduces the reader to the latest experimental and bioinformatics methods for DNA sequencing, RNA sequencing, cell-free tumour DNA sequencing, single cell sequencing, single-cell proteomics and metabolomics. Chapters detail advanced analysis methods, such as Genome-Wide Association Studies (GWAS), machine learning, reconstruction and analysis of gene regulatory networks and differential coexpression network analysis, and gave a practical guide for how to choose and use the right algorithm or software to handle specific high throughput data or multi-omics data. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Computational Systems Biology: Methods and Protocols aims to ensure successful results in the further study of this vital field. .
    Note: DNA Sequencing Data Analysis -- Transcriptome Sequencing: RNA-seq -- Capture Hybridization of Long-range DNA Fragments for High-throughput Sequencing -- The Introduction and Clinical Application of Cell-free Tumour DNA -- Bioinformatics Analysis for Cell-free Tumor DNA Sequencing Data -- An Overview of Genome-Wide Association Studies -- Integrative Analysis of Omics Big Data -- The Reconstruction and Analysis of Gene Regulatory Networks -- Differential Coexpression Network Analysis for Gene Expression Data -- iSeq: Web-based RNA-seq Data Analysis and Visualization -- Revisit of Machine Learning Supported Biological and Biomedical Studies -- Identifying Interactions Between Long Non-coding RNAs and Diseases Based on Computational Methods -- Survey Of Computational Approaches For Prediction of DNA-binding Residues on Protein Surfaces -- Computational Prediction of Protein O-GlcNAc Modification -- Machine Learning Based Modeling of Drug Toxicity -- Metabolomics: A High-throughput Platform for Metabolite Profile Exploration -- Single-Cell Protein Assays--A Review -- Data Analysis in Single-cell Transcriptome Sequencing -- Applications of Single-cell Sequencing For Multi-omics -- Progress on Diagnosis of Tuberculous Meningitis -- Insights of Acute Lymphoblastic Leukemia with Development of Genomic Investigation.
    Additional Edition: ISBN 1-4939-7716-4
    Language: English
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  • 6
    UID:
    almafu_9960408015902883
    Format: 1 electronic resource (234 p.)
    Content: This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact
    Note: English
    Additional Edition: ISBN 2-88966-274-8
    Language: English
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  • 7
    UID:
    gbv_1869167899
    Format: 1 Online-Ressource (308 p.)
    ISBN: 9783036582283 , 9783036582290
    Content: The aim of this reprint focuses on the latest protocol research, software/hardware development and implementation, and system architecture design in addressing emerging security and privacy issues for modern wireless communication networks. Relevant topics include, but are not limited to, the following: deep-learning-based security and privacy design; covert communications; information-theoretical foundations for advanced security and privacy techniques; lightweight cryptography for power-constrained networks; physical layer key generation; prototypes and testbeds for security and privacy solutions; encryption and decryption algorithm for low-latency constrained networks; security protocols for modern wireless communication networks; network intrusion detection; physical layer design with security consideration; anonymity in data transmission; vulnerabilities in security and privacy in modern wireless communication networks; challenges of security and privacy in node–edge–cloud computation; security and privacy design for low-power wide-area IoT networks; security and privacy design for vehicle networks; security and privacy design for underwater communications networks
    Note: English
    Language: Undetermined
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  • 8
    UID:
    gbv_1794542086
    Format: 1 Online-Ressource (393 p.)
    ISBN: 9782889635542
    Content: Precision medicine is being developed as a preventative, diagnostic and treatment tool to combat complex human diseases in a personalized manner. By utilizing high-throughput technologies, dynamic ‘omics data including genetics, epi-genetics and even meta-genomics has produced temporal-spatial big biological datasets which can be associated with individual genotypes underlying pathogen progressive phenotypes. It is therefore necessary to investigate how to integrate these multi-scale ‘omics datasets to distinguish the novel individual-specific disease causes from conventional cohort-common disease causes. Currently, machine learning plays an important role in biological and biomedical research, especially in the analysis of big ‘omics data. However, in contrast to traditional big social data, ‘omics datasets are currently always “small-sample-high-dimension”, which causes overwhelming application problems and also introduces new challenges: (1) Big ‘omics datasets can be extremely unbalanced, due to the difficulty of obtaining enough positive samples of such rare mutations or rare diseases; (2) A large number of machine learning models are “black box,” which is enough to apply in social applications. However, in biological or biomedical fields, knowledge of the molecular mechanisms underlying any disease or biological study is necessary to deepen our understanding; (3) The genotype-phenotype association is a “white clue” captured in conventional big data studies. But identification of “causality” rather than association would be more helpful for physicians or biologists, as this can be used to determine an experimental target as the subject of future research. Therefore, to simultaneously improve the phenotype discrimination and genotype interpretability for complex diseases, it is necessary: To design and implement new machine learning technologies to integrate prior-knowledge with new ‘omics datasets to provide transferable learning methods by combining multiple sources of data; To develop new network-based theories and methods to balance the trade-off between accuracy and interpretability of machine learning in biomedical and biological domains; To enhance the causality inference on “small-sample high dimension” data to capture the personalized causal relationship
    Note: English
    Language: English
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  • 9
    UID:
    gbv_179458188X
    Format: 1 Online-Ressource (234 p.)
    ISBN: 9782889662746
    Content: This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact
    Note: English
    Language: English
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  • 10
    UID:
    gbv_272851558
    Format: XI, 170 S , 25 cm
    ISBN: 0313243662
    Series Statement: Bibliographies and indexes in Afro-American and African studies 2
    Language: English
    Subjects: General works
    RVK:
    Keywords: USA ; Schwarze ; Bibliographie ; Bibliografie
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