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Advances in New Technology for Targeted Modification of Plant Genomes [[electronic resource] /] / edited by Feng Zhang, Holger Puchta, James G. Thomson
| Advances in New Technology for Targeted Modification of Plant Genomes [[electronic resource] /] / edited by Feng Zhang, Holger Puchta, James G. Thomson |
| Edizione | [1st ed. 2015.] |
| Pubbl/distr/stampa | New York, NY : , : Springer New York : , : Imprint : Springer, , 2015 |
| Descrizione fisica | 1 online resource (171 p.) |
| Disciplina |
570
571.32 581.35 631.52 660.6 |
| Soggetto topico |
Plant breeding
Plant genetics Plant anatomy Plant development Plant Breeding/Biotechnology Plant Genetics and Genomics Plant Anatomy/Development |
| ISBN | 1-4939-2556-3 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Double-strand break repair and its application to genome engineering in plants -- Engineering meganuclease for precise plant genome modification -- High efficient genome modification by designed Zinc Finger Nuclease -- Engineered TAL effector proteins: versatile reagents for manipulating plant genomes -- Oligo-mediated targeted gene editing -- Gene targeting in crop species with effective selection systems -- Recombinase Technology for Precise Genome Engineering -- PBRM1: Developing CRISPR technology in major crop plants. |
| Record Nr. | UNINA-9910298280903321 |
| New York, NY : , : Springer New York : , : Imprint : Springer, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Genome Editing in Neurosciences [[electronic resource] /] / edited by Rudolf Jaenisch, Feng Zhang, Fred Gage
| Genome Editing in Neurosciences [[electronic resource] /] / edited by Rudolf Jaenisch, Feng Zhang, Fred Gage |
| Autore | Feng Zhang |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Springer Nature, 2017 |
| Descrizione fisica | 1 online resource (XI, 123 p. 16 illus. in color.) |
| Disciplina |
611.01816
599.935 |
| Collana | Research and Perspectives in Neurosciences |
| Soggetto topico |
Human genetics
Neurosciences Biomedical engineering Human Genetics Biomedical Engineering/Biotechnology |
| Soggetto non controllato |
CRISPR
muscular dystrophy Parkinson's disease DNA Rett syndrome double-strand breaks Huntington's disease genetic engineering |
| ISBN | 3-319-60192-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- In vitro modeling of complex neurological diseases -- Aquatic model organisms in neurosciences : the genome editing revolution -- Genome-wide genetic screening in the mammalian CNS -- CRISPR/Cas9-mediated Knockin and Knockout in Zebrafish -- Dissecting the role of synaptic proteins with CRISPR -- Recurrently Breaking Genes in Neural Progenitors: Potential Roles of DNA Breaks in Neuronal Function, Degeneration and Cancer -- Neuroscience research using non-human primate models and genome editing -- Multiscale genome engineering: Genome-wide screens and targeted approaches -- Using Genome Engineering to Understand Huntington’s Disease -- Therapeutic gene editing in muscles and muscle stem cells. |
| Record Nr. | UNINA-9910231247003321 |
Feng Zhang
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| Springer Nature, 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Machine Learning and Medical Engineering for Cardiovascular Health and Intravascular Imaging and Computer Assisted Stenting [[electronic resource] ] : First International Workshop, MLMECH 2019, and 8th Joint International Workshop, CVII-STENT 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings / / edited by Hongen Liao, Simone Balocco, Guijin Wang, Feng Zhang, Yongpan Liu, Zijian Ding, Luc Duong, Renzo Phellan, Guillaume Zahnd, Katharina Breininger, Shadi Albarqouni, Stefano Moriconi, Su-Lin Lee, Stefanie Demirci
| Machine Learning and Medical Engineering for Cardiovascular Health and Intravascular Imaging and Computer Assisted Stenting [[electronic resource] ] : First International Workshop, MLMECH 2019, and 8th Joint International Workshop, CVII-STENT 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings / / edited by Hongen Liao, Simone Balocco, Guijin Wang, Feng Zhang, Yongpan Liu, Zijian Ding, Luc Duong, Renzo Phellan, Guillaume Zahnd, Katharina Breininger, Shadi Albarqouni, Stefano Moriconi, Su-Lin Lee, Stefanie Demirci |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XVII, 212 p. 83 illus., 68 illus. in color.) |
| Disciplina | 610.285 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Artificial intelligence Image Processing and Computer Vision Artificial Intelligence |
| ISBN | 3-030-33327-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Proceedings of the Machine Learning and Medical Engineering for Cardiovascular Health, MLMECH 2019 -- Arrhythmia Classification with Attention-Based ResBiLSTM-Net -- A Multi-Label Learning Method to detect Arrhythmia Based on -- An Ensemble Neural Network for Multi-label Classification of Electrocardiogram -- Automatic Diagnosis with 12-lead ECG Signals -- Diagnosing Cardiac Abnormalities from 12-Lead Electrocardiograms Using Enhanced Deep Convolutional Neural Networks -- Transfer Learning for Electrocardiogram Classification under Small Dataset -- Multi-label classification of abnormalities in 12-lead ECG using 1D CNN and LSTM -- An Approach to Predict Multiple Cardiac Diseases -- A 12-lead ECG Arrhythmia Classification Method Based on 1D Densely Connected CNN -- Automatic Multi-label Classification in 12-lead ECGs Using Neural Networks and Characteristic Points -- Automatic Detection of ECG Abnormalities by using an Ensemble of Deep Residual Networks with Attention -- Deep Learning to Improve Heart Disease Risk Prediction -- LabelECG: A Web-based Tool for Distributed Electrocardiogram Annotation -- Particle Swarm Optimization for Great Enhancement in Semi-Supervised Retinal Vessel Segmentation with Generative Adversarial Networks -- Attention-Guided Decoder in Dilated Residual Network for Accurate Aortic Valve Segmentation in 3D CT Scans -- ARVBNet: Real-time Detection of Anatomical Structures in Fetal Ultrasound Cardiac Four-chamber Planes -- Proceedings of the Computing and Visualization for Intravascular Imaging and Computer Assisted Stenting, CVII-STENT 2019 -- The Effect of Labeling Duration and Temporal Resolution on Arterial Transit Time Estimation Accuracy in 4D ASL MRA Datasets - a Flow Phantom Study -- Towards Quantifying Neurovascular Resilience -- Random 2.5D U-net for Fully 3D Segmentation -- Abdominal aortic aneurysm segmentation using convolutional neural networks trained with images generated with a synthetic shape model -- Tracking of intracavitary instrument markers in coronary angiography images -- Healthy Vessel Wall Detection Using U-Net in Optical Coherence Tomography -- Advanced Multi-objective Design Analysis to Identify Ideal Stent Design -- Simultaneous Intracranial Artery Tracing and Segmentation from Magnetic Resonance Angiography by Joint Optimization from Multiplanar Reformation. |
| Record Nr. | UNISA-996466194903316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Machine Learning and Medical Engineering for Cardiovascular Health and Intravascular Imaging and Computer Assisted Stenting [[electronic resource] ] : First International Workshop, MLMECH 2019, and 8th Joint International Workshop, CVII-STENT 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings / / edited by Hongen Liao, Simone Balocco, Guijin Wang, Feng Zhang, Yongpan Liu, Zijian Ding, Luc Duong, Renzo Phellan, Guillaume Zahnd, Katharina Breininger, Shadi Albarqouni, Stefano Moriconi, Su-Lin Lee, Stefanie Demirci
| Machine Learning and Medical Engineering for Cardiovascular Health and Intravascular Imaging and Computer Assisted Stenting [[electronic resource] ] : First International Workshop, MLMECH 2019, and 8th Joint International Workshop, CVII-STENT 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings / / edited by Hongen Liao, Simone Balocco, Guijin Wang, Feng Zhang, Yongpan Liu, Zijian Ding, Luc Duong, Renzo Phellan, Guillaume Zahnd, Katharina Breininger, Shadi Albarqouni, Stefano Moriconi, Su-Lin Lee, Stefanie Demirci |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XVII, 212 p. 83 illus., 68 illus. in color.) |
| Disciplina | 610.285 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Artificial intelligence Image Processing and Computer Vision Artificial Intelligence |
| ISBN | 3-030-33327-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Proceedings of the Machine Learning and Medical Engineering for Cardiovascular Health, MLMECH 2019 -- Arrhythmia Classification with Attention-Based ResBiLSTM-Net -- A Multi-Label Learning Method to detect Arrhythmia Based on -- An Ensemble Neural Network for Multi-label Classification of Electrocardiogram -- Automatic Diagnosis with 12-lead ECG Signals -- Diagnosing Cardiac Abnormalities from 12-Lead Electrocardiograms Using Enhanced Deep Convolutional Neural Networks -- Transfer Learning for Electrocardiogram Classification under Small Dataset -- Multi-label classification of abnormalities in 12-lead ECG using 1D CNN and LSTM -- An Approach to Predict Multiple Cardiac Diseases -- A 12-lead ECG Arrhythmia Classification Method Based on 1D Densely Connected CNN -- Automatic Multi-label Classification in 12-lead ECGs Using Neural Networks and Characteristic Points -- Automatic Detection of ECG Abnormalities by using an Ensemble of Deep Residual Networks with Attention -- Deep Learning to Improve Heart Disease Risk Prediction -- LabelECG: A Web-based Tool for Distributed Electrocardiogram Annotation -- Particle Swarm Optimization for Great Enhancement in Semi-Supervised Retinal Vessel Segmentation with Generative Adversarial Networks -- Attention-Guided Decoder in Dilated Residual Network for Accurate Aortic Valve Segmentation in 3D CT Scans -- ARVBNet: Real-time Detection of Anatomical Structures in Fetal Ultrasound Cardiac Four-chamber Planes -- Proceedings of the Computing and Visualization for Intravascular Imaging and Computer Assisted Stenting, CVII-STENT 2019 -- The Effect of Labeling Duration and Temporal Resolution on Arterial Transit Time Estimation Accuracy in 4D ASL MRA Datasets - a Flow Phantom Study -- Towards Quantifying Neurovascular Resilience -- Random 2.5D U-net for Fully 3D Segmentation -- Abdominal aortic aneurysm segmentation using convolutional neural networks trained with images generated with a synthetic shape model -- Tracking of intracavitary instrument markers in coronary angiography images -- Healthy Vessel Wall Detection Using U-Net in Optical Coherence Tomography -- Advanced Multi-objective Design Analysis to Identify Ideal Stent Design -- Simultaneous Intracranial Artery Tracing and Segmentation from Magnetic Resonance Angiography by Joint Optimization from Multiplanar Reformation. |
| Record Nr. | UNINA-9910349274303321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Network and Parallel Computing [[electronic resource] ] : 15th IFIP WG 10.3 International Conference, NPC 2018, Muroran, Japan, November 29 – December 1, 2018, Proceedings / / edited by Feng Zhang, Jidong Zhai, Marc Snir, Hai Jin, Hironori Kasahara, Mateo Valero
| Network and Parallel Computing [[electronic resource] ] : 15th IFIP WG 10.3 International Conference, NPC 2018, Muroran, Japan, November 29 – December 1, 2018, Proceedings / / edited by Feng Zhang, Jidong Zhai, Marc Snir, Hai Jin, Hironori Kasahara, Mateo Valero |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource (XII, 192 p. 115 illus., 73 illus. in color.) |
| Disciplina | 004.35 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Computer engineering
Computer networks Operating systems (Computers) Logic design Image processing—Digital techniques Computer vision Artificial intelligence Data protection Computer Engineering and Networks Operating Systems Logic Design Computer Imaging, Vision, Pattern Recognition and Graphics Artificial Intelligence Data and Information Security |
| ISBN | 3-030-05677-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | CNLoc: Channel State Information Assisted Indoor WLAN Localization Using Nomadic Access Points -- ALOR: Adaptive Layout Optimization of Raft Groups for Heterogeneous Distributed Key-Value Stores -- STrieGD: A Sampling Trie Indexed Compression Algorithm for Large-Scale Gene Data -- On Retargeting the AI Programming Framework to New Hardwares -- An Efficient Method For Determining Full Point-to-point Latency Of Arbitrary Indirect HPC Networks -- KT-Store: A Key-Order and Write-Order Hybrid Key-Value Store with High Write and Range-query Performance -- GRAM: A GPU-based Property Graph Traversal and Query for HPC Rich Metadata Management -- GPU-Accelerated Clique Tree Propagation for Pouch Latent Tree Models -- HPC-SFI: System-level Fault Injection for High Performance Computing Systems -- Data Fine-pruning: A Simple Way to Accelerate Neural Network Training -- Balancing the QOS and Security in Dijkstra Algorithm by SDN Technology -- Labeled Network Stack: A Co-Designed Stack for Low Tail-Latency and High Concurrency in Datacenter Services -- A Deep Learning Approach for Network Anomaly Detection based on AMF-LSTM -- FSObserver: A Performance Measurement and Monitoring Tool for Distributed Storage Systems -- vGrouper: Optimizing the Performance of Parallel Jobs in Xen by Increasing Synchronous Execution of Virtual Machines -- Systolic Array Based Accelerator and Algorithm Mapping for Deep Learning Algorithms -- A Fine-grained Performance Bottleneck Analysis Method for HDFS -- Mimir+ : An Optimized Framework of MapReduce on Heterogeneous High-Performance Computing System -- DLIR: An Intermediate Representation for Deep Learning Processors -- GPU Memory Management Solution Supporting Incomplete Pages -- Leveraging Subgraph Extraction for Performance Portable Programming Frameworks on DL Accelerators -- An Intelligent Parking Scheduling Algorithm based on Traffic and Driver Behavior Predictions. . |
| Record Nr. | UNISA-996466459603316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Network and Parallel Computing [[electronic resource] ] : 15th IFIP WG 10.3 International Conference, NPC 2018, Muroran, Japan, November 29 – December 1, 2018, Proceedings / / edited by Feng Zhang, Jidong Zhai, Marc Snir, Hai Jin, Hironori Kasahara, Mateo Valero
| Network and Parallel Computing [[electronic resource] ] : 15th IFIP WG 10.3 International Conference, NPC 2018, Muroran, Japan, November 29 – December 1, 2018, Proceedings / / edited by Feng Zhang, Jidong Zhai, Marc Snir, Hai Jin, Hironori Kasahara, Mateo Valero |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource (XII, 192 p. 115 illus., 73 illus. in color.) |
| Disciplina | 004.35 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Computer engineering
Computer networks Operating systems (Computers) Logic design Image processing—Digital techniques Computer vision Artificial intelligence Data protection Computer Engineering and Networks Operating Systems Logic Design Computer Imaging, Vision, Pattern Recognition and Graphics Artificial Intelligence Data and Information Security |
| ISBN | 3-030-05677-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | CNLoc: Channel State Information Assisted Indoor WLAN Localization Using Nomadic Access Points -- ALOR: Adaptive Layout Optimization of Raft Groups for Heterogeneous Distributed Key-Value Stores -- STrieGD: A Sampling Trie Indexed Compression Algorithm for Large-Scale Gene Data -- On Retargeting the AI Programming Framework to New Hardwares -- An Efficient Method For Determining Full Point-to-point Latency Of Arbitrary Indirect HPC Networks -- KT-Store: A Key-Order and Write-Order Hybrid Key-Value Store with High Write and Range-query Performance -- GRAM: A GPU-based Property Graph Traversal and Query for HPC Rich Metadata Management -- GPU-Accelerated Clique Tree Propagation for Pouch Latent Tree Models -- HPC-SFI: System-level Fault Injection for High Performance Computing Systems -- Data Fine-pruning: A Simple Way to Accelerate Neural Network Training -- Balancing the QOS and Security in Dijkstra Algorithm by SDN Technology -- Labeled Network Stack: A Co-Designed Stack for Low Tail-Latency and High Concurrency in Datacenter Services -- A Deep Learning Approach for Network Anomaly Detection based on AMF-LSTM -- FSObserver: A Performance Measurement and Monitoring Tool for Distributed Storage Systems -- vGrouper: Optimizing the Performance of Parallel Jobs in Xen by Increasing Synchronous Execution of Virtual Machines -- Systolic Array Based Accelerator and Algorithm Mapping for Deep Learning Algorithms -- A Fine-grained Performance Bottleneck Analysis Method for HDFS -- Mimir+ : An Optimized Framework of MapReduce on Heterogeneous High-Performance Computing System -- DLIR: An Intermediate Representation for Deep Learning Processors -- GPU Memory Management Solution Supporting Incomplete Pages -- Leveraging Subgraph Extraction for Performance Portable Programming Frameworks on DL Accelerators -- An Intelligent Parking Scheduling Algorithm based on Traffic and Driver Behavior Predictions. . |
| Record Nr. | UNINA-9910349385603321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Pluralism and world order : theoretical perspectives and policy challenges / / edited by Feng Zhang
| Pluralism and world order : theoretical perspectives and policy challenges / / edited by Feng Zhang |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Singapore : , : Palgrave Macmillan, , [2023] |
| Descrizione fisica | 1 online resource (251 pages) |
| Disciplina | 574 |
| Collana | IPPA distinguished lecture publication |
| Soggetto topico |
Great powers
International relations |
| ISBN |
9789811998720
9789811998713 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1: Introduction -- Part I: Theoretical Perspective -- Chapter 2: The Rise and Fall of Political Orders -- Chapter 3: Deep Pluralism as the Emerging Structure of Global Society -- Part II: The Great Powers -- Chapter 4: China, the United States, and the Future Global Order: One World, Two Contending Pluralist Visions -- Chapter 5: World Power Structure over the Short and Long Run -- Chapter 6: Pluralism and the US-China Development Partnership -- Chapter 7: India’s Frustrated Search for a Multipolar Order -- Part III: Multilateralism and Regionalism -- Chapter 8: The United Nations and New Multilateralism -- Chapter 9: East Asian Multilateralism: A Glass Half Full -- Chapter 10: ASEAN’s Strategic Response to the United States-China Competition -- Chapter 11: Regionalism and the Future of Latin America and the Caribbean -- Part IV: Future Prospects -- Chapter 12: Contours of a Future World Order. |
| Record Nr. | UNINA-9910678261703321 |
| Singapore : , : Palgrave Macmillan, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Understanding of Atmospheric Systems with Efficient Numerical Methods for Observation and Prediction / / edited by Lei-Ming Ma, Feng Zhang, and Chang-Jiang Zhang
| Understanding of Atmospheric Systems with Efficient Numerical Methods for Observation and Prediction / / edited by Lei-Ming Ma, Feng Zhang, and Chang-Jiang Zhang |
| Pubbl/distr/stampa | London, England : , : IntechOpen, , 2019 |
| Descrizione fisica | 1 online resource (168 pages) |
| Disciplina | 550 |
| Soggetto topico | Earth sciences - Study and teaching |
| ISBN |
1-83880-634-2
1-83880-112-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910326249403321 |
| London, England : , : IntechOpen, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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