The Canadian fur trade in the industrial age / / Arthur J. Ray

• Record Nr.: UNINA9910796934703321
• Autore: Ray Arthur J.
• Pubbl/distr/stampa: Toronto, Ontario ; ; Buffalo, New York ; ; London, England : , : University of Toronto Press, , 1990; ©1990
• ISBN: 1-4426-5913-0; 0-8020-2699-0; 1-4426-5740-5
• Descrizione fisica: 1 online resource (283 p.)
• Collana: Heritage
• Disciplina: 971.201
• Soggetti: Fur trade - Canada - History; Indians of North America - Canada - Economic conditions; History; Electronic books.; Northern Canada; Canada
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Does the fur trade have a future? -- Laying the groundwork for government involvement, 1870-1885 -- The fur trade in transition -- The turning point : the impact of the First World War on the northern fur trade -- The international marketing of Canadian furs, 1920-1945 -- The struggle for dominance in the Canadian north during the 1920s -- Attempts to revitalize the Hudson's Bay Company's Fur Trade Department, 1920-1945 -- The native people, the Hudson's Bay Company, and the state in the industrial fur trade, 1920-1945 -- The decline of the old order.
• Sommario/riassunto: Throughout much of the nineteenth century the Hudson's Bay Company had a virtual monopoly on the core area of the fur trade in Canada. Its products were the object of intense competition among merchants on two continents - in Leipzig, New York, London, Winnipeg, St Louis, and Montreal. But in 1870 things began to change, and by the end of the ; Second World War the company's share had dropped to about a quarter of the trade. Arthur Ray explores the decades of transition, the economic and technological changes that shaped them, and their impact on the Canadian north and its people. Among the developments that affected the fur trade during this period were innovations in transportation and communication; increased government involvement in business, conservation, and native economic welfare; and the effects of two severe depressions (1873-95 and 1929-38) and two world wars. The Hudson's Bay Company, confronting the first of these changes as early as 1871, embarked on a diversification program that was intended to capitalize on new economic opportunities in land development, retailing, and resource ventures. Meanwhile it continued to participate in its traditional sphere of operations. But the company's directors had difficulty keeping pace with the rapid changes that were taking place in the fur trade, and the company began to lose ground. Ray's study is the first to make extensive use of the Hudson's Bay Company archives dealing with the period between 1870 and 1945. These and other documents reveal a great deal about the decline of the company, and thus about a key element in the history of the modern Canadian fur trade.

Research in Computational Molecular Biology : 28th Annual International Conference, RECOMB 2024, Cambridge, MA, USA, April 29–May 2, 2024, Proceedings / / edited by Jian Ma

• Record Nr.: UNINA9910861086203321
• Autore: Ma Jian
• Pubbl/distr/stampa: Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
• ISBN: 9781071639894; 1071639897
• Edizione: [1st ed. 2024.]
• Descrizione fisica: 1 online resource (508 pages)
• Collana: Lecture Notes in Computer Science, , 1611-3349 ; ; 14758
• Disciplina: 4
• Soggetti: Computer science; Computer Science
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di contenuto: -- Enhancing gene set analysis in embedding spaces a novel best match approach. -- Prompt based Learning on Large Protein Language Models Improves Signal Peptide Prediction. -- Decoil Reconstructing extrachromosomal DNA structural heterogeneity from longread sequencing data. -- Privacy Preserving Epigenetic PaceMaker Stronger Privacy and Improved Efficiency. -- Mapping Cell Fate Transition in Space and Time. -- Approximate IsoRank for Scalable Global Alignment of Biological Networks. -- Sequential Optimal Experimental Design of Perturbation Screens Guided by Multimodal Priors. -- Efficient Analysis of Annotation Colocalization Accounting for Genomic Contexts. -- Secure federated Boolean count queries using fully homomorphic cryptography. -- FragXsiteDTI Revealing Responsible Segments in Drug Target Interaction with Transformer Driven Interpretation. -- An integer programming framework for identifying stable components in asynchronous Boolean networks. -- ImputeCC enhances integrative Hi C based metagenomic binning through constrained random walk based imputation. -- Graph based genome inference from Hi C data. -- Meta colored de Bruijn graphs. -- Color Coding for the Fragment Based Docking Design and Equilibrium Statistics of Protein Binding ssRNAs. -- Automated design of efficient search schemes for lossless approximate pattern matching. -- CELL E ; A Text To Image Transformer for Protein Localization Prediction. -- A Scalable Optimization Algorithm for Solving the Beltway and Turnpike Problems with Uncertain Measurements. -- Overcoming Observation Bias for Cancer Progression Modeling. -- Inferring Metabolic States from Single Cell Transcriptomic Data via Geometric Deep Learning. -- Computing robust optimal factories in metabolic reaction networks. -- Undesignable RNA Structure Identification via Rival Structure Generation and Structure Decomposition. -- Structure and Function Aware Substitution Matrices via Learnable Graph Matching. -- Secure Discovery of Genetic Relatives across Large Scale and Distributed Genomic Datasets. -- GFETM Genome Foundation based Embedded Topic Model for scATAC seq Modeling. -- SEM sized based expectation maximization for characterizing nucleosome positions and subtypes. -- Centrifuger lossless compression of microbial genomes for efficient and accurate metagenomic sequence classification. -- BONOBO Bayesian Optimized sample specific Networks Obtained By Omics data. -- regLM Designing realistic regulatory DNA with autoregressive language models. -- DexDesign A new OSPREY based algorithm for designing de novo D peptide inhibitors. -- Memory bound and taxonomy aware kmer selection for ultra large reference libraries. -- SpaCeNet Spatial Cellular Networks from omics data. -- Discovering and overcoming the bias in neoantigen identification by unified machine learning models. -- MaSk LMM A Matrix Sketching Framework for Linear Mixed Models in Association Studies. -- Community structure and temporal dynamics of viral epistatic networks allow for early detection of emerging variants with altered phenotypes. -- Maximum Likelihood Inference of Time scaled Cell Lineage Trees with Mixed type Missing Data. -- TRIBAL Tree Inference of B cell Clonal Lineages. -- Mapping the topography of spatial gene expression with interpretable deep learning. -- GraSSRep Graph Based Self Supervised Learning for Repeat Detection in Metagenomic Assembly. -- PRS Net Interpretable polygenic risk scores via geometric learning. -- Haplotype aware sequence alignment to pangenome graphs. -- Disease Risk Predictions with Differentiable Mendelian Randomization. -- DIISCO A Bayesian framework for inferring dynamic intercellular interactions from time series single cell data. -- Protein domain embeddings for fast and accurate similarity search. -- Processing bias correction with DEBIAS M improves cross study generalization of microbiome based prediction models. -- VICTree a Variational Inference method for Clonal Tree reconstruction. -- DeST OT Alignment of Spatiotemporal Transcriptomics Data. -- Determining Optimal Placement of Copy Number Aberration Impacted Single Nucleotide Variants in a Tumor Progression History. -- Accurate Assembly of Circular RNAs with TERRACE. -- Semi Supervised Learning While Controlling the FDR With an Application to Tandem Mass Spectrometry Analysis. -- CoRAL accurately resolves extrachromosomal DNA genome structures with long read sequencing. -- A Scalable Adaptive Quadratic Kernel Method for Interpretable Epistasis Analysis in Complex Traits. -- Optimal Tree Metric Matching Enables Phylogenomic Branch Length Estimation. -- Inferring allele specific copy number aberrations and tumor phylogeography from spatially resolved transcriptomics. -- Contrastive Fitness Learning Reprogramming Protein Language Models for Low N Learning of Protein Fitness Landscape. -- Scalable summary statistics based heritability estimation method with individual genotype level accuracy. -- scMulan a multitask generative pre trained language model for single cell analysis.
• Sommario/riassunto: This book constitutes the proceedings of the 28th Annual International ; Conference on Research in Computational Molecular Biology, RECOMB 2024, held in Cambridge, MA, USA, during April 29–May 2, 2024. The 57 full papers included in this book were carefully reviewed and selected from 352 submissions. They were organized in topical sections as follows: theoretical and foundational algorithm contributions and more applied directions that engage with new technologies and intriguing biological questions.