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Japanese and Chinese Immigrant Activists

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ISBN: 9780813540405 Year: Language: English
Publisher: Rutgers University Press Grant: Knowledge Unlatched - 101111
Added to DOAB on : 2018-01-25 11:01:48
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Japanese and Chinese immigrants in the United States have traditionally been characterized as hard workers who are hesitant to involve themselves in labor disputes or radical activism. How then does one explain the labor and Communist organizations in the Asian immigrant communities that existed from coast to coast between 1919 and 1933? Their organizers and members have been, until now, largely absent from the history of the American Communist movement. Here, Josephine Fowler brings us the first in-depth account of Japanese and Chinese immigrant radicalism inside the United States and across the Pacific.

Organizing Matters

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Book Series: ILERA Publication series ISBN: 9781839104022 9781839104039 Year: Pages: 264 DOI: 10.4337/9781839104039 Language: English
Publisher: Edward Elgar Publishing
Subject: Political Science --- Economics --- Law
Added to DOAB on : 2020-06-15 17:10:44
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Organizing Matters demonstrates the interplay between two distinct logics of labour’s collective action: on the one hand, workers coming together, usually at their place of work, entrusting the union to represent their interests and, on the other hand, social bargaining in which the trade union constructs labour’s interests from the top down. The book investigates the tensions and potential complementarities between the two logics through the combination of a strong theoretical framework and an extensive qualitative case study of trade union organizing and recruitment in four countries – Austria, Germany, Israel and the Netherlands. These countries still utilize social-wide bargaining but find it necessary to draw and develop strategies transposed from Anglo-American countries in response to continuously declining membership.

Stadt als Schule

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ISBN: 9783966270144 9783966270120 Year: Pages: 68 DOI: 10.33968/9783966270144-00 Language: German
Publisher: HTWK Leipzig - OA-Hochschulverlag
Subject: Architecture
Added to DOAB on : 2019-10-21 11:21:20
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When a fire department called "Ostwache" in the eastern part of Leipzig closed down, it left their old building behind vacant. Soon after a neighbourhood initiative sought to use the space to establish a community center for the surrounding neighbourhood. At the same time, the municipal government was planning a new school on the same lot. This thesis presents a solution for this conflict. By bringing together architectural, urban planning and pedagogical perspectives, while aiming for synergies. Following the model of Freinet pedagogy, a community school was planned with a new building at the site of the old fire station and the community center is to be located in the existing building of the old Ostwache. Through a common courtyard, shared work and sports facilities and a shared lunch, the school opens up to the city and its neighborhood to the school. This is how city works as school and a school works as city.

Energy Storage and Management for Electric Vehicles

Authors: --- ---
ISBN: 9783039218622 9783039218639 Year: Pages: 238 DOI: 10.3390/books978-3-03921-863-9 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: General and Civil Engineering --- Technology (General)
Added to DOAB on : 2020-01-30 16:39:46
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This Special Edition of Energies on “Energy Storage and Management for Electric Vehicles” draws together a collection of research papers that critically evaluates key areas of innovation and novelty when designing and managing the high-voltage battery system within an electrified powertrain. The addressed topics include design optimisation, mathematical modelling, control engineering, thermal management, and component sizing.

Keywords

zinc–nickel single-flow battery --- equivalent circuit model --- self-discharge --- dynamic flow rate optimization --- genetic algorithm --- hybrid power system --- electric vehicle --- rule-based optimal strategy --- dynamic programming approach --- thermal modelling --- thermal behaviour --- lithium titanate oxide batteries --- optimal control --- supercapacitors --- batteries --- fuel cell --- hybrid vehicle --- battery degradation --- battery energy storage system --- charging scheme --- efficiency --- electric vehicle --- linear programming --- lithium ion battery --- operating expenses --- residential battery storage --- vehicle-to-building --- supercapacitor models --- parameter estimation --- ECE15 --- HPPC --- Simulink --- Simscape --- Matlab --- Identification --- regenerative energy --- timetable optimization --- energy storage system --- ?-constraint method --- improved artificial bee colony --- lithium-ion battery --- equivalent circuit model --- recursive least square --- adaptive forgetting factor --- parameter identification --- energy storage ageing and degradation --- life cycle assessment --- second-life energy storage applications --- Li-Sulfur batteries --- lithium-ion battery --- cell sorting --- multi-parameters sorting --- principal component analysis --- self-organizing maps clustering --- battery charging --- cycle-life --- state-of-health (SOH) --- battery cycle-life extension --- nonlinear battery model --- state of charge estimation --- lithium-ion battery --- Lipschitz nonlinear system --- Luenberger observer

Flood Forecasting Using Machine Learning Methods

Authors: --- ---
ISBN: 9783038975489 Year: Pages: 376 DOI: 10.3390/books978-3-03897-549-6 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering --- Environmental Engineering
Added to DOAB on : 2019-03-08 11:42:05
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This book is a printed edition of the Special Issue Flood Forecasting Using Machine Learning Methods that was published in Water

Keywords

data scarce basins --- runoff series --- data forward prediction --- ensemble empirical mode decomposition (EEMD) --- stopping criteria --- method of tracking energy differences (MTED) --- deep learning --- convolutional neural networks --- superpixel --- urban water bodies --- high-resolution remote-sensing images --- monthly streamflow forecasting --- artificial neural network --- ensemble technique --- phase space reconstruction --- empirical wavelet transform --- hybrid neural network --- flood forecasting --- self-organizing map --- bat algorithm --- particle swarm optimization --- flood routing --- Muskingum model --- machine learning methods --- St. Venant equations --- rating curve method --- nonlinear Muskingum model --- hydrograph predictions --- flood routing --- Muskingum model --- hydrologic models --- improved bat algorithm --- Wilson flood --- Karahan flood --- flood susceptibility modeling --- ANFIS --- cultural algorithm --- bees algorithm --- invasive weed optimization --- Haraz watershed --- ANN-based models --- flood inundation map --- self-organizing map (SOM) --- recurrent nonlinear autoregressive with exogenous inputs (RNARX) --- ensemble technique --- artificial neural networks --- uncertainty --- streamflow predictions --- sensitivity --- flood forecasting --- extreme learning machine (ELM) --- backtracking search optimization algorithm (BSA) --- the upper Yangtze River --- deep learning --- LSTM network --- water level forecast --- the Three Gorges Dam --- Dongting Lake --- Muskingum model --- wolf pack algorithm --- parameters --- optimization --- flood routing --- flash-flood --- precipitation-runoff --- forecasting --- lag analysis --- random forest --- machine learning --- flood prediction --- flood forecasting --- hydrologic model --- rainfall–runoff, hybrid & --- ensemble machine learning --- artificial neural network --- support vector machine --- natural hazards & --- disasters --- adaptive neuro-fuzzy inference system (ANFIS) --- decision tree --- survey --- classification and regression trees (CART), data science --- big data --- artificial intelligence --- soft computing --- extreme event management --- time series prediction --- LSTM --- rainfall-runoff --- flood events --- flood forecasting --- data assimilation --- particle filter algorithm --- micro-model --- Lower Yellow River --- ANN --- hydrometeorology --- flood forecasting --- real-time --- postprocessing --- machine learning --- early flood warning systems --- hydroinformatics --- database --- flood forecast --- Google Maps

Molecular Computing and Bioinformatics

Authors: --- ---
ISBN: 9783039211951 9783039211968 Year: Pages: 390 DOI: 10.3390/books978-3-03921-196-8 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- Biotechnology
Added to DOAB on : 2019-08-28 11:21:27
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This text will provide the most recent knowledge and advances in the area of molecular computing and bioinformatics. Molecular computing and bioinformatics have a close relationship, paying attention to the same object but working towards different orientations. The articles will range from topics such as DNA computing and membrane computing to specific biomedical applications, including drug R&D and disease analysis.

Keywords

prostate cancer --- Mycoplasma hominis --- endoplasmic reticulum --- systems biology --- protein targeting --- biomedical text mining --- big data --- Tianhe-2 --- parallel computing --- load balancing --- bacterial computing --- bacteria and plasmid system --- Turing universality --- recursively enumerable function --- miRNA biogenesis --- structural patterns --- DCL1 --- protein–protein interaction (PPI) --- clustering --- protein complex --- penalized matrix decomposition --- avian influenza virus --- interspecies transmission --- amino acid mutation --- machine learning --- Bayesian causal model --- causal direction learning --- K2 --- brain storm optimization --- line graph --- Cartesian product graph --- join graph --- atom-bond connectivity index --- geometric arithmetic index --- P-glycoprotein --- efflux ratio --- in silico --- machine learning --- hierarchical support vector regression --- absorption --- distribution --- metabolism --- excretion --- toxicity --- image encryption --- chaotic map --- DNA coding --- Hamming distance --- Stenotrophomonas maltophilia --- iron acquisition systems --- iron-depleted --- RAST server --- NanoString Technologies --- siderophores --- gene fusion data --- gene susceptibility prioritization --- evaluating driver partner --- gene networks --- drug-target interaction prediction --- machine learning --- drug discovery --- microRNA --- environmental factor --- structure information --- similarity network --- bioinformatics --- identification of Chinese herbal medicines --- biochip technology --- DNA barcoding technology --- DNA strand displacement --- cascade --- 8-bit adder/subtractor --- domain label --- Alzheimer’s disease --- gene coding protein --- sequence information --- support vector machine --- classification --- adverse drug reaction prediction --- heterogeneous information network embedding --- stacking denoising auto-encoder --- meta-path-based proximity --- Panax ginseng --- oligopeptide transporter --- flowering plant --- phylogeny --- transcription factor --- multiple interaction networks --- function prediction --- multinetwork integration --- low-dimensional representation --- dihydrouridine --- nucleotide physicochemical property --- pseudo dinucleotide composition --- RNA secondary structure --- ensemble classifier --- diabetes mellitus --- hypoxia-inducible factor-1? --- angiogenesis --- bone formation --- osteogenesis --- protein transduction domain --- membrane computing --- edge detection --- enzymatic numerical P system --- resolution free --- molecular computing --- molecular learning --- DNA computing --- self-organizing systems --- pattern classification --- machine learning --- laccase --- Brassica napus --- lignification --- stress --- molecular computing --- bioinformatics --- machine learning --- protein --- DNA --- RNA --- drug --- bio-inspired

Application of Bioinformatics in Cancers

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ISBN: 9783039217885 9783039217892 Year: Pages: 418 DOI: 10.3390/books978-3-03921-789-2 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- Biotechnology
Added to DOAB on : 2019-12-09 11:49:16
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This collection of 25 research papers comprised of 22 original articles and 3 reviews is brought together from international leaders in bioinformatics and biostatistics. The collection highlights recent computational advances that improve the ability to analyze highly complex data sets to identify factors critical to cancer biology. Novel deep learning algorithms represent an emerging and highly valuable approach for collecting, characterizing and predicting clinical outcomes data. The collection highlights several of these approaches that are likely to become the foundation of research and clinical practice in the future. In fact, many of these technologies reveal new insights about basic cancer mechanisms by integrating data sets and structures that were previously immiscible.

Keywords

comorbidity score --- mortality --- locoregionally advanced --- HNSCC --- curative surgery --- traditional Chinese medicine --- health strengthening herb --- cancer treatment --- network pharmacology --- network target --- high-throughput analysis --- brain metastases --- colorectal cancer --- KRAS mutation --- PD-L1 --- tumor infiltrating lymphocytes --- drug resistance --- gefitinib --- erlotinib --- biostatistics --- bioinformatics --- Bufadienolide-like chemicals --- molecular mechanism --- anti-cancer --- bioinformatics --- cancer --- brain --- pathophysiology --- imaging --- machine learning --- extreme learning --- deep learning --- neurological disorders --- pancreatic cancer --- TCGA --- curation --- DNA --- RNA --- protein --- single-biomarkers --- multiple-biomarkers --- cancer-related pathways --- colorectal cancer --- DNA sequence profile --- Monte Carlo --- mixture of normal distributions --- somatic mutation --- tumor --- mutable motif --- activation induced deaminase --- AID/APOBEC --- transcriptional signatures --- copy number variation --- copy number aberration --- TCGA mining --- cancer CRISPR --- firehose --- gene signature extraction --- gene loss biomarkers --- gene inactivation biomarkers --- biomarker discovery --- chemotherapy --- microarray --- ovarian cancer --- predictive model --- machine learning --- overall survival --- observed survival interval --- skin cutaneous melanoma --- The Cancer Genome Atlas --- omics --- breast cancer prognosis --- artificial intelligence --- machine learning --- decision support systems --- cancer prognosis --- independent prognostic power --- omics profiles --- histopathological imaging features --- cancer --- intratumor heterogeneity --- genomic instability --- epigenetics --- mitochondrial metabolism --- miRNAs --- cancer biomarkers --- breast cancer detection --- machine learning --- feature selection --- classification --- denoising autoencoders --- breast cancer --- feature extraction and interpretation --- concatenated deep feature --- cancer modeling --- interaction --- histopathological imaging --- clinical/environmental factors --- oral cancer --- miRNA --- bioinformatics --- datasets --- biomarkers --- TCGA --- GEO DataSets --- hormone sensitive cancers --- breast cancer --- StAR --- estrogen --- steroidogenic enzymes --- hTERT --- telomerase --- telomeres --- alternative splicing --- network analysis --- hierarchical clustering analysis --- differential gene expression analysis --- cancer biomarker --- diseases genes --- variable selection --- false discovery rate --- knockoffs --- bioinformatics --- copy number variation --- cell-free DNA --- methylation --- mutation --- next generation sequencing --- self-organizing map --- head and neck cancer --- treatment de-escalation --- HP --- molecular subtypes --- tumor microenvironment --- Bioinformatics tool --- R package --- machine learning --- meta-analysis --- biomarker signature --- gene expression analysis --- survival analysis --- functional analysis --- bioinformatics --- machine learning --- artificial intelligence --- Network Analysis --- single-cell sequencing --- circulating tumor DNA (ctDNA) --- Neoantigen Prediction --- precision medicine --- Computational Immunology

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