02948nam 2200661Ia 450 991045109820332120200520144314.01-281-36797-497866113679781-4039-7721-6(CKB)1000000000342947(SSID)ssj0000518337(PQKBManifestationID)12179551(PQKBTitleCode)TC0000518337(PQKBWorkID)10493105(PQKB)10095459(SSID)ssj0000171928(PQKBManifestationID)11167265(PQKBTitleCode)TC0000171928(PQKBWorkID)10133488(PQKB)10602121(DE-He213)978-1-4039-7721-2(MiAaPQ)EBC308236(Au-PeEL)EBL308236(CaPaEBR)ebr10135633(CaONFJC)MIL136797(OCoLC)123538070(EXLCZ)99100000000034294720050509d2006 uy 0engurcn|||||||||txtccrThe history and politics of voting technology[electronic resource] in quest of integrity and public confidence /by Roy G. Saltman1st ed. 2006.New York Palgrave Macmillan20061 online resource (256 p.)Bibliographic Level Mode of Issuance: Monograph0-230-60598-2 1-4039-6392-4 Includes bibliographical references and index.1. The 2000 presidential election in Florida : the family secret is exposed -- 2. From the revolution to the Civil War : consent of the governed and the election clause -- 3. The late nineteenth centaury : struggling with corruption and fraud -- 4. The late nineteenth and early twentieth centuries : mechanization and political reforms -- 5. The middle and late twentieth centaury : movements for equality, enfranchisement, and voting facilitation -- 6. The middle and late twentieth century : election administration and computing technology -- 7. The great awakening after Florida, through July 2005.Saltman traces the evolution of voting technology in the USA, from voice to digital, highlighting how the antiquated systems in use today are a legacy of the industrial revolution of the Nineteenth-century and the early computer revolution of the 1950's and analyses the current day situation.VotingUnited StatesHistoryVotingTechnological innovationsUnited StatesHistoryElectronic books.VotingHistory.VotingTechnological innovationsHistory.324.6/5/0973Saltman Roy G939492MiAaPQMiAaPQMiAaPQBOOK9910451098203321The history and politics of voting technology2117919UNINA05528nam 2200709 450 991081418790332120230803204225.01-119-01521-91-119-00522-11-119-01533-2(CKB)3710000000218284(EBL)1765112(SSID)ssj0001411781(PQKBManifestationID)11753489(PQKBTitleCode)TC0001411781(PQKBWorkID)11401602(PQKB)10081305(MiAaPQ)EBC4040537(OCoLC)887507393(MiAaPQ)EBC1765112(Au-PeEL)EBL1765112(CaPaEBR)ebr10907565(CaONFJC)MIL637336(EXLCZ)99371000000021828420140822h20142014 uy 0engur|n|---|||||txtccrLogical modeling of biological systems /edited by Luis Fariñas del Cerro, Katsumi InoueLondon, [England] ;Hoboken, New Jersey :ISTE :Wiley,2014.©20141 online resource (429 p.)Bioengineering and Health Science SeriesDescription based upon print version of record.1-84821-680-7 Includes bibliographical references at the end of each chapters and index.Cover; Title Page; Copyright; Contents; Foreword; Chapter 1. Symbolic Representation and Inference of Regulatory Network Structures; 1.1. Introduction: logical modeling and abductive inference in systems biology; 1.2. Logical modeling of regulatory networks; 1.2.1. Background; 1.2.2. Logical model of signed-directed networks; 1.2.2.1. Prior knowledge; 1.2.2.2. Rule-based underlying model; 1.2.2.3. Integrity constraints; 1.2.2.4. Inferring signed-directed networks and explanatory reasoning; 1.3. Evaluation of the ARNI approach; 1.3.1. ARNI predictive power1.3.1.1. Prediction under biological and experimental noise1.3.1.2. Prediction under incomplete data; 1.3.2. ARNI expressive power; 1.3.2.1. Network motif representations; 1.3.2.2. Representing complex interactions; 1.4. ARNI assisted scientific methodology; 1.4.1. Testing biological hypotheses; 1.4.1.1. Testing cross-talk between signaling pathways; 1.4.2. Informative experiments for networks discrimination; 1.5. Related work and comparison with non-symbolic approaches; 1.5.1. Limitations and future work; 1.6. Conclusions; 1.7. BibliographyChapter 2. Reasoning on the Response of Logical Signaling Networks with ASP2.1. Introduction; 2.2. Answer set programming at a glance; 2.3. Learn and control logical networks with ASP; 2.3.1. Preliminaries; 2.3.2. Reasoning on the response of logical networks; 2.3.3. Learning models of immediate-early response; 2.3.4. Minimal intervention strategies; 2.3.5. Software toolbox: caspo; 2.4. Conclusion; 2.5. Acknowledgments; 2.6. Bibliography; Chapter 3. A Logical Model for Molecular Interaction Maps; 3.1. Introduction; 3.2. Biological background; 3.3. Logical model3.3.1. Activation and inhibition3.3.1.1. Activation and inhibition capacities; 3.3.1.2. Relations between the activation and inhibition causes and effects; 3.3.1.3. Relations between causal relations; 3.3.2. Model extension; 3.3.2.1. Phosphorylation; 3.3.2.2. Autophosphorylation; 3.3.2.3. Binding; 3.3.3. Causality relations redefinition; 3.3.3.1. Activation axioms; 3.3.3.2. Phosphorylation axioms; 3.3.3.3. Autophosphorylation axioms; 3.3.3.4. Binding axioms; 3.3.3.5. Inhibition axioms; 3.4. Quantifier elimination for restricted formulas; 3.4.1. Domain formulas; 3.4.2. Restricted formulas3.4.3. Completion formulas3.4.4. Domain of domain formulas; 3.4.5. Quantifier elimination procedure; 3.5. Reasoning about interactions in metabolic interaction maps; 3.6. Conclusion and future work; 3.7. Acknowledgments; 3.8. Bibliography; Chapter 4. Analyzing Large Network Dynamics with Process Hitting; 4.1. Introduction/state of the art; 4.1.1. The modeling challenge; 4.1.2. Historical context: Boolean and discrete models; 4.1.3. Analysis issues; 4.1.4. The process hitting framework; 4.1.5. Outline; 4.2. Discrete modeling with the process hitting; 4.2.1. Motivation4.2.2. The process hitting framework Systems Biology is the systematic study of the interactions between the components of a biological system and studies how these interactions give rise to the function and behavior of the living system. Through this, a life process is to be understood as a whole system rather than the collection of the parts considered separately. Systems Biology is therefore more than just an emerging field: it represents a new way of thinking about biology with a dramatic impact on the way that research is performed. The logical approach provides an intuitive method to provide explanations based on an expresBioengineering and health science series.BiologyMethodologyBiologyPhilosophyEvolution (Biology)BiologyMethodology.BiologyPhilosophy.Evolution (Biology)570.28Fariñas del Cerro LuisInoue KatsumiMiAaPQMiAaPQMiAaPQBOOK9910814187903321Logical modeling of biological systems3987207UNINA00691nac# 22002053i 450 VAN0009346420240806100656.53620130419f |0itac50 baIT|||| |||||b||||||||||Chorasensi e modi del costruireBeneventoHevelius.001VAN000319982001 ˆLa ‰dimensione dell'immaginazioneClaudio Bozzaotra210 BeneventoHevelius2000215 134 p., [8] c. di tav.ill.21 cm1BeneventoVANL000034Hevelius <editore>VANV108011650ITSOL20240906RICAVAN00093464Chora1777055UNICAMPANIA