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J.R. Gilbert Account Book
Account book kept by J.R. Gilbert of the Gilead section of Hebron, Connecticut. Gilbert was a farmer and recorded sales of hay, potatoes, apples, beef, and other farm products.
Manchester
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Never Too Late
For her first book, Nicole J R Gilbert imagines the relationship between mother and daughter. The effect it takes them to overcome their own challenges from WW2 to the 80's, setting between Charleston in Cornwall and Crowborough in East Sussex. Never Too Late, dramatizes the story as the two protagonists attempt to come to terms with childhood and adulthood. Louise, the mother has to deal with her affection between two brothers, the secret she keeps and her sense of guilt for one of them. Mandy, the daughter has to deal with a broken marriage, death, and new relationship. Never Too Late retraced how mother and daughter relate to each other in difficult times. Filled throughout with all its weaknesses of life, this story forms this enjoyable reading family saga.
Comprehensive Biomaterials II
Comprehensive Biomaterials II, Second Edition, Seven Volume Set brings together the myriad facets of biomaterials into one expertly-written series of edited volumes. Articles address the current status of nearly all biomaterials in the field, their strengths and weaknesses, their future prospects, appropriate analytical methods and testing, device applications and performance, emerging candidate materials as competitors and disruptive technologies, research and development, regulatory management, commercial aspects, and applications, including medical applications. Detailed coverage is given to both new and emerging areas and the latest research in more traditional areas of the field. Partic...
Graph Algorithms in the Language of Linear Algebra
The current exponential growth in graph data has forced a shift to parallel computing for executing graph algorithms. Implementing parallel graph algorithms and achieving good parallel performance have proven difficult. This book addresses these challenges by exploiting the well-known duality between a canonical representation of graphs as abstract collections of vertices and edges and a sparse adjacency matrix representation. This linear algebraic approach is widely accessible to scientists and engineers who may not be formally trained in computer science. The authors show how to leverage existing parallel matrix computation techniques and the large amount of software infrastructure that exists for these computations to implement efficient and scalable parallel graph algorithms. The benefits of this approach are reduced algorithmic complexity, ease of implementation, and improved performance.
