LEADER 05327nam 2200649Ia 450 001 9910133647803321 005 20221223164020.0 010 $a1-283-40791-4 010 $a9786613407917 010 $a1-4443-9219-0 010 $a1-4443-9221-2 035 $a(CKB)3400000000000368 035 $a(EBL)661828 035 $a(OCoLC)705353461 035 $a(SSID)ssj0000482378 035 $a(PQKBManifestationID)11291763 035 $a(PQKBTitleCode)TC0000482378 035 $a(PQKBWorkID)10526702 035 $a(PQKB)10918276 035 $a(MiAaPQ)EBC661828 035 $a(EXLCZ)993400000000000368 100 $a20100714d2011 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aSparidae$b[electronic resource] $ebiology and aquaculture of gilthead sea bream and other species /$fedited by Michalis A. Pavlidis, Constantinos C. Mylonas 210 $aChichester, West Sussex, UK ;$aAmes, Iowa $cWiley-Blackwell$d2011 215 $a1 online resource (422 p.) 300 $aDescription based upon print version of record. 311 $a1-4051-9772-2 320 $aIncludes bibliographical references and index. 327 $aSparidae; Contents; Preface; List of Contributors; Chapter 1 Current status of Sparidae aquaculture; 1.1 Introduction; 1.2 World Sparidae production; 1.3 Aquaculture status of Atlantic-Mediterranean species; 1.3.1 Current status of gilthead sea bream (S. aurata) production; 1.3.1.1 Main species characteristics; 1.3.1.2 Production cycle; 1.3.1.3 Gilthead sea bream current production; 1.3.1.4 Sector characteristics; 1.3.1.5 Production economics; 1.3.1.6 Markets; 1.3.2 Current status of common pandora (P. erythrinus) production; 1.3.2.1 Main species characteristics; 1.3.2.2 Production cycle 327 $a1.3.2.3 Common pandora current production1.3.3 Current status of blackspot sea bream (P. bogaraveo) aquaculture production; 1.3.3.1 Main species characteristics; 1.3.3.2 Production cycle; 1.3.3.3 Blackspot sea bream current production; 1.3.4 Current status of white sea bream (D. sargus) production; 1.3.4.1 Main species characteristics; 1.3.4.2 Production cycle; 1.3.4.3 White sea bream current production; 1.3.5 Current status of sharpsnout sea bream (Diplodus puntazzo) production; 1.3.5.1 Main species characteristics; 1.3.5.2 Production cycle; 1.3.5.3 Sharpsnout sea bream current production 327 $a1.3.6 Current status of common dentex (D. dentex) production1.3.6.1 Main species characteristics; 1.3.6.2 Production cycle; 1.3.6.3 Common dentex current production; 1.3.7 Current status of red porgy (Pagrus pagrus) production; 1.3.7.1 Main species characteristics; 1.3.7.2 Production cycle; 1.3.7.3 Red porgy current production; 1.3.8 A comparative economic analysis on the ongrowing of blackspot sea bream, common dentex, redbanded sea bream, red porgy and sharpsnout sea bream; 1.4 Aquaculture status of Indo-Pacific species; 1.4.1 Current status of the red sea bream (P. major) production 327 $a1.4.1.1 Main species characteristics1.4.1.2 Production cycle; 1.4.1.3 Red sea bream current production; 1.4.1.4 Red sea bream aquaculture in Japan; 1.4.1.5 Red sea bream restocking programmes; 1.4.2 Current status of blackhead sea bream (A. schlegeli) production; 1.4.2.1 Main species characteristics; 1.4.2.2 Production cycle; 1.4.2.3 Blackhead sea bream current production; 1.4.2.4 Blackhead sea bream restocking programmes; 1.4.3 Current status of sobaity sea bream (S. hasta) production; 1.4.3.1 Main species characteristics; 1.4.3.2 Production cycle 327 $a1.4.3.3 Sobaity sea bream current production1.4.4 Current status of goldlined sea bream (Rhabdosargus sarba) production; 1.4.4.1 Main species characteristics; 1.4.4.2 Production cycle; 1.4.4.3 Goldlined sea bream current production; References; Chapter 2 Phylogeny, evolution and taxonomy of sparids with some notes on their ecology and biology; 2.1 The position of the Sparidae in the fish tree of life; 2.2 Fossil record; 2.3 The monophyly of the Sparidae; 2.4 Intrafamiliar relationships; 2.5 Larval taxonomy and systematics; 2.6 Biogeography; 2.7 Biology; 2.7.1 Habitat choice 327 $a2.7.2 Reproduction 330 $aThe Sparidae, commonly known as breams and porgies, is a family of fishes of the order Perciformes, and includes about 115 species of mainly marine coastal fish of high economic value, exploited and farmed for human consumption, as well as for recreational purposes. This landmark publication brings together a huge wealth of information on the biology and culture of gilthead sea bream and other Sparidae species. Commencing with an overview of the current status of aquaculture of Sparidae, the book continues with comprehensive coverage of the family's phylogeny, evolution and taxonomy, stress 606 $aSparus aurata 606 $aSparidae 606 $aFish culture 615 0$aSparus aurata. 615 0$aSparidae. 615 0$aFish culture. 676 $a639.3 676 $a639.3/772 701 $aPavlidis$b Michalis$0884186 701 $aMylonas$b Constantinos$0884187 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910133647803321 996 $aSparidae$91974458 997 $aUNINA LEADER 09000nam 22006135 450 001 9910746289403321 005 20251113191227.0 010 $a9783031363948 010 $a3031363949 024 7 $a10.1007/978-3-031-36394-8 035 $a(MiAaPQ)EBC30746892 035 $a(Au-PeEL)EBL30746892 035 $a(CKB)28267869200041 035 $a(DE-He213)978-3-031-36394-8 035 $a(EXLCZ)9928267869200041 100 $a20230918d2023 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aUncertainty, Constraints, and Decision Making /$fedited by Martine Ceberio, Vladik Kreinovich 205 $a1st ed. 2023. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2023. 215 $a1 online resource (437 pages) 225 1 $aStudies in Systems, Decision and Control,$x2198-4190 ;$v484 311 08$aPrint version: Ceberio, Martine Uncertainty, Constraints, and Decision Making Cham : Springer International Publishing AG,c2023 9783031363931 327 $aPreface -- directory Preface -- 1. Applications to Biology and Medicine -- Hunting Habits of Predatory Birds: Theoretical Explanation of an Empirical Formula -- Why Rectified Power (RePU) Activation Functions Are Efficient in Deep Learning: A Theoretical Explanation -- Aquatic Ecotoxicology: Theoretical Explanation of Empirical Formulas -- How Hot Is Too Hot -- How Order and Disorder Affect People's Behavior: An Explanation -- Shape of an Egg: Towards a Natural Simple Universal Formula -- A General Commonsense Explanation of Several Medical Results -- Why Immunodepressive Drugs Often Make People Happier -- Systems Approach Explains Why Low Heart Rate Variability Is Correlated with Depression (and Suicidal Thoughts) -- 2. Applications to Economics and Politics -- How to Make Inflation Optimal and Fair -- Why Seneca Effect? -- Why Rarity Score Is a Good Evaluation of a Non-Fungible Token -- Resource Allocation for Multi-Tasking Optimization: Explanation of an Empirical Formula -- Everyone Is Above Average: Is It Possible? Is It Good? -- How Probable is a Revolution? A Natural ReLU-Like Formula that Fits the Historical Data -- Why Should Exactly 1/4 Be Returned to the Original Owner: An Economic Explanation of an Ancient Recommendation -- Why Would Anyone Invest in a High-Risk Low-Profit Enterprise? -- Which Interval-Valued Alternatives Are Possibly Optimal If We Use Hurwicz Criterion -- How to Solve the Apportionment Paradox -- In the Absence of Information, the Only Reasonable Negotiation Scheme Is Offering a Certain Percentage of the Original Request: A Proof -- 3. Applications to Education -- How to Make Quantum Ideas Less Counter-Intuitive: A Simple Analysis of Measurement Uncertainty Can Help -- Physical Meaning Often Leads to Natural Derivations in Elementary Mathematics: On the Examples of Solving Quadratic and Cubic Equations -- Towards Better Ways to Compute the Overall Grade for a Class -- Why Some Theoretically Possible Representations of Natural Numbers Were Historically Used andSome Were Not: An Algorithm-Based Explanation -- 4. Applications to Engineering -- Dielectric Barrier Discharge (DBD) Thrusters -- Aerospace Engines of the Future: Invariance-Based Analysis -- Need for Optimal Distributed Measurement of Cumulative Quantities Explains the Ubiquity of Absolute and Relative Error Components -- Over-Measurement Paradox: Suspension of Thermonuclear Research Center and Need to Update Standards -- How to Get the Most Accurate Measurement-Based Estimates -- How to Estimate The Present Serviceability Rating of a Road Segment: Explanation of an Empirical Formula -- 5. Applications to Linguistics -- Word Representation: Theoretical Explanation of an Empirical Fact -- Why Menzerath's Law? -- 6. Applications to Machine Learning -- One More Physics-Based Explanation for Rectified Linear Neurons -- Why Deep Neural Networks: Yet Another Explanation -- 7. Applications to Mathematics -- Really Good Theorems Are Those That End Their Life as Definitions: Why -- 8. Applications to Physics -- How to Describe Hypothetic Truly Rare Events (with Probability 0) -- Spiral Arms Around a Star: Geometric Explanation -- Why Physical Power Laws Usually Have Rational Exponents -- Freedom of Will, Non-Uniqueness of Cauchy Problem, Fractal Processes, Renormalization, Phase Transitions, and Stealth Aircraft -- How Can the Opposite to a True Theory Be Also True? A Similar Talmudic Discussion Helps Make This Famous Bohr's Statement Logically Consistent -- How to Detect (and Analyze) Independent Subsystems of a Black-Box (or Grey-Box) System -- 9. Applications to Psychology and Decision Making -- Why Decision Paralysis -- Why Time Seems to Pass Slowly for Unpleasant Experiences and Quickly for Pleasant Experiences: An Explanation Based on Decision Theory -- How to Deal with Conflict of Interest Situations When Selecting the Best Submission -- Why Aspirational Goals: Geometric Explanation -- Why Hate: Analysis Based on Decision Theory -- Why Self-Esteem Helps to Solve Problems: An Algorithmic Explanation -- Why Five Stages of Solar Activity, Why Five Stages of Grief, Why Seven Plus Minus Two: A General Geometric Explanation -- 10. Applications to Software Engineering -- Anomaly Detection in Crowdsourcing: Why Midpoints in Interval-Valued Approach -- Unexpected Economic Consequence of Cloud Computing: A Boost to Algorithmic Creativity -- Unreachable Statements Are Inevitable In Software Testing: Theoretical Explanation -- 11. General Computational Techniques -- Why Constraint Interval Arithmetic Techniques Work Well: A Theorem Explains Empirical Success" -- "How to Describe Relative Approximation Error? A New Justification for Gustafson's Logarithmic Expression" -- Search Under Uncertainty Should be Randomized: A Lesson From the 2021 Nobel Prize in Medicine" -- Why Convex Combination Is an Effective Crossover Operation in Continuous Optimization: A Theoretical Explanation" -- "Why Optimization Is Faster than Solving Systems of Equations: A Qualitative Explanation" -- Estimating Skewness and Higher Central Moments of an Interval-Valued -- Fuzzy Set" -- How to Detect the Fundamental Frequency: Approach Motivated by Soft -- Computing and Computational Complexity" -- What If There Are Too Many Outliers?" -- What Is a Natural Probability Distribution on the Class of All Continuous Functions: Maximum Entropy Approach Leads to Wiener Measure" -- An Argument in Favor of Piecewise-Constant Membership Functions" -- "Data Processing under Fuzzy Uncertainty: Towards More Accurate Algorithms" -- "Epistemic vs. Aleatory: Case of Interval Uncertainty" -- "Standard Interval Computation Algorithm Is Not Inclusion-Monotonic: Examples" -- "Monotonic Bit-Invariant Permutation-Invariant Metrics on the Set of All Infinite Binary Sequences" -- Computing the Range of a Function-of-Few-Linear-Combinations Under Linear Constraints: A Feasible Algorithm" -- "How to Select a Representative Sample for a Family of Functions?. 330 $aIn the first approximation, decision making is nothing else but an optimization problem: We want to select the best alternative. This description, however, is not fully accurate: it implicitly assumes that we know the exact consequences of each decision, and that, once we have selected a decision, no constraints prevent us from implementing it. In reality, we usually know the consequences with some uncertainty, and there are also numerous constraints that needs to be taken into account. The presence of uncertainty and constraints makes decision making challenging. To resolve these challenges, we need to go beyond simple optimization, we also need to get a good understanding of how the corresponding systems and objects operate, a good understanding of why we observe what we observe ? this will help us better predict what will be the consequences of different decisions. All these problems ? in relation to different application areas ? are the main focus of this book. 410 0$aStudies in Systems, Decision and Control,$x2198-4190 ;$v484 606 $aAutomatic control 606 $aDynamics 606 $aNonlinear theories 606 $aEngineering mathematics 606 $aControl and Systems Theory 606 $aApplied Dynamical Systems 606 $aEngineering Mathematics 615 0$aAutomatic control. 615 0$aDynamics. 615 0$aNonlinear theories. 615 0$aEngineering mathematics. 615 14$aControl and Systems Theory. 615 24$aApplied Dynamical Systems. 615 24$aEngineering Mathematics. 676 $a658.403 700 $aCeberio$b Martine$01429749 701 $aKreinovich$b Vladik$0117742 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910746289403321 996 $aUncertainty, Constraints, and Decision Making$93568991 997 $aUNINA