Search Results - "Innatism"

The Immune Response to Implanted Materials and Devices The Impact of the Immune System on the Success of an Implant /

Table of Contents: “…Host response to implanted materials and devices - overview -- Innate and acquired immunity: umoral and cellular components (Protein adsorption, cell recruitment, tissue response) -- Acute/Chronic inflammation, foreign body reaction - implications -- Macrophages: from immune response to tissue restoration -- Host response to cell-grafted biomaterials -- Host response to therapeutic nanoparticles -- Host response to synthetic versus natural biomaterials (The effects of the composition, structure on function, stability, and final outcome) -- Biomimicry at the cell-material interface to mitigate the immune reaction -- Bioactive materials design for immunomodulation - exploiting the patient's own body machinery to achieve functional tissue restoration -- Host response to materials for orthopaedic applications: current approaches and future perspectives -- Methods to activate cellular immunity or determine immune evasion.…”
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Effectors in plant-microbe interactions /

Table of Contents: “…Front Matter -- Section 1: Plant Immune Response Pathways. Innate Immunity: Pattern Recognition in Plants / Delphine Chinchilla, Thomas Boller -- Microbial Effectors and Their Role in Plant Defense Suppression / Dagmar Hann, Thomas Boller -- Section 2: Genome-Wide Analyses of Microbial Effectors and Effector Evolution. …”
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Deep Learning with TensorFlow and Keras - 3rd Edition : Build and Deploy Supervised, Unsupervised, Deep, and Reinforcement Learning Models. by Kapoor, Amita

Table of Contents: “…Context autoencoder -- Colorization -- Innate relationship prediction -- Relative position -- Solving jigsaw puzzles -- Rotation -- Hybrid self-prediction -- VQ-VAE -- Jukebox -- DALL-E -- VQ-GAN -- Contrastive learning -- Training objectives -- Contrastive loss -- Triplet loss -- N-pair loss -- Lifted structural loss -- NCE loss -- InfoNCE loss -- Soft nearest neighbors loss -- Instance transformation -- SimCLR -- Barlow Twins -- BYOL -- Feature clustering -- DeepCluster -- SwAV -- InterCLR -- Multiview coding -- AMDIM -- CMC -- Multimodal models -- CLIP -- CodeSearchNet -- Data2Vec -- Pretext tasks -- Summary -- References -- Chapter 11: Reinforcement Learning -- An introduction to RL -- RL lingo -- Deep reinforcement learning algorithms -- How does the agent choose its actions, especially when untrained? …”
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Death, the dead and popular culture / by Penfold-Mounce, Ruth, 1979-

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Rethinking Platinum Anticancer Drug Design: Towards Targeted and Immuno-chemotherapeutic Approaches by Wong, Daniel Yuan Qiang

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Getting It Right in Science and Medicine Can Science Progress through Errors? Fallacies and Facts / by Kricheldorf, Hans R.

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Advances in Artificial Systems for Medicine and Education

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