1.2 10 1.2 1 10 mods info:srw/schema/1/mods-v3.5 xml 1Keller, EileenEileenKeller1985autVerfasserInHoffmann, IsabellIsabellHoffmannautVerfasserInDeutsch-Französisches InstitutisbHerausgebendes OrgantextLudwigsburgdfi202606/03/2026monographicfre1 Online-Ressource (30 min)avec les éclairages d'Eileen Keller et d'Isabell HoffmannLe17716364321972069276https://www.dfi.de/fileadmin/dfi/audio/le-podkast/S6_E4__Crash-test_%C3%A0_Stuttgart.mp3S6,401-06-2601-06-261972069276rda info:srw/schema/1/mods-v3.5 xml 2ATaylor, Grahame N.Grahame N.TaylorautVerfasserIntext2026engRed Hook, NYCurran Associates, Inc.2026Seite 1626-2447196858249519720592622384239201-06-2601-06-261972059262rda info:srw/schema/1/mods-v3.5 xml 3Fernandes, Fernando B.Fernando B.FernandesautVerfasserInRezende, Fernando H. G.Fernando H. G.RezendeautVerfasserIntext2026engRed Hook, NYCurran Associates, Inc.2026816 Seiten1968577858197205781257561201-06-2601-06-261972057812rda info:srw/schema/1/mods-v3.5 xml 4Lima, V. N.V. N.LimaautVerfasserInGardner, D.D.GardnerautVerfasserInRandeberg, E.E.RandebergautVerfasserInTaheri, A.A.TaheriautVerfasserIntext2026engRed Hook, NYCurran Associates, Inc.2026816 Seiten1968577858197205767733835301-06-2601-06-261972057677rda info:srw/schema/1/mods-v3.5 xml 5Yazdani, SaeidSaeidYazdaniautVerfasserInTechnische Universität ChemnitzdggGrad-verleihende InstitutionUniversitätsverlag ChemnitzpblVerlagtextChemnitzUniversitätsverlag Chemnitz2026monographiceng1 Online-Ressource (xxvii, 193 Seiten)Illustrationen, DiagrammeTechnische Universität Chemnitz, Dissertation, 2025Saeid YazdaniChemnitzHalbleiterRegelungstechnikLeistungselektronikMesstechnik620621urn:nbn:de:bsz:ch1-qucosa2-10416121971907502https://doi.org/10.51382/978-3-96100-324-228-05-2628-05-261971907502rda info:srw/schema/1/mods-v3.5 xml 6an EU-wide political stress testHindriks, JeanJeanHindriksautVerfasserInCetin, SefaneSefaneCetinautVerfasserIntext2026engMany countries have implemented a variety of pension reforms in response to the challenges posed by an aging population. These reforms typically involve a trade-off between 'refinancing' (i.e., increasing contributions) and 'retrenchment' (i.e., reducing benefits). The primary question addressed in this study is whether policymakers in the European Union (EU) possess the necessary capacity to sustain legislated pension reforms, particularly given the growing political influence of the elderly. To examine this issue, we develop a bargaining model designed to optimally allocate the economic burden of aging between successive cohorts of workers and retirees, incorporating retirement incentives. In a scenario where bargaining power remains constant, the optimal allocation rule dictates a fixed-contribution system, effectively shifting the full burden of aging onto the elderly. However, when bargaining power is allowed to fluctuate in response to changes in the relative size of the retiree population (i.e., the dependency rate), the optimal allocation rule involves a compromise between increasing contributions and reducing benefits. In the empirical analysis, we compare these theoretical optimal allocation rules with projections of pension benefit rates and dependency ratios from the 2021 Economic Policy Committee. By calculating the implicit bargaining power required to align projected pension benefits with the optimal sharing rule for each year, we demonstrate a growing divergence between projected pension benefits and the optimal levels in many EU countries, as demographic shifts progress. Furthermore, our findings indicate that for most countries, projected pension benefits are increasingly falling below optimal levels when bargaining power adjusts in accordance with population aging.Jean Hindriks and Sefane Cetinagingbargainingpension reformstress testsustainabilityCambridgeCambridge Univ. Press2002Online-Ressource3485871121971792721https://www.cambridge.org/core/services/aop-cambridge-core/content/view/5D8997FC9F6B22DBCC1F8180794FD99A/S1474747225100103a.pdf/sustainability_of_pension_reforms_an_euwide_political_stress_test.pdfhttps://doi.org/10.1017/S14747472251001032514517127-05-2627-05-261971792721rda info:srw/schema/1/mods-v3.5 xml 7Schmidt, ChristianChristianSchmidtautVerfasserInYüksel, CanCanYükselautVerfasserInIwa, RomanRomanIwaautVerfasserInCorban, EricEricCorbanautVerfasserInStaudacher, EmonaEmonaStaudacherautVerfasserInDistelmaier, MartinaMartinaDistelmaierautVerfasserInObeidi, YoussraYoussraObeidiautVerfasserInMesropyan, NarineNarineMesropyanautVerfasserInXie, KunpengKunpengXieautVerfasserInLemessa, JonathanJonathanLemessaautVerfasserInHaag, FlorianFlorianHaagautVerfasserInKuhl, ChristianeChristianeKuhlautVerfasserInBruners, PhilippPhilippBrunersautVerfasserInBarajas Ordonez, FelixFelixBarajas OrdonezautVerfasserIntext2026July 2026engIllustrationenBackground - Accurate arterial-phase timing in contrast-enhanced CT (CECT) is critical for evaluating hepatocellular carcinoma (HCC). Standard-delay methods may fail to capture peak arterial enhancement due to interindividual hemodynamic variability, potentially reducing lesion conspicuity. This study evaluated whether individualized, dynamically tailored arterial-phase CT (t-CT) based on test-bolus peak in the lesion or, if not feasible, within the portal vein, improves quantitative enhancement and lesion conspicuity compared with standard-delay CT (s-CT). - Materials and methods - This intraindividual study included 39 patients with 60 HCC lesions who underwent both t-CT and s-CT. Maximum and mean lesion attenuation (HUmax, HUmean), relative lesion-to-liver attenuation (relative HUmax, relative HUmean), and image noise were measured. Four readers rated lesion conspicuity on a five-point Likert scale; inter-reader agreement was assessed using weighted κ, Krippendorff’s α, and intraclass correlation coefficient (ICC). - Results - All quantitative parameters differed significantly between protocols. HUmax was greater in t-CT than on s-CT (151.0 [130.0-199.8] HU vs 113.5 [97.0-150.0]; p < 0.001), as well as HUmean (124.5 [104.5-144.8] HU vs 90.5 [79.8-112.8]; p < 0.001), relative HUmax (1.9 [1.7-2.3] vs 1.8 [1.5-2.2]; p = 0.009) and relative HUmean (1.6 [1.4-1.9] vs 1.4 [1.3-1.7]; p < 0.001). Image noise was lower on t-CT than on s-CT (8.4 [6.7-9.7] vs 11.1 [9.6-12.9]; p < 0.001). Median lesion conspicuity was higher on t-CT (4.0 vs 3.0; p < 0.001). - Conclusion - Individualized lesion-oriented test bolus arterial-phase timing in CECT demonstrated higher lesion attenuation, greater lesion-to-liver contrast, lower image noise, and higher visibility compared with standard arterial-phase timing in HCC.Christian Schmidt, Can Yüksel, Roman Iwa, Eric Corban, Emona Staudacher, Martina Distelmaier, Youssra Obeidi, Narine Mesropyan, Kunpeng Xie, Jonathan Lemessa, Florian Haag, Christiane Kuhl, Philipp Bruners, Felix Barajas OrdonezOnline verfügbar: 15. April 2026, Artikelversion: 19. April 2026Gesehen am 26.05.2026Hepatocellular carcinomaImage qualityTomographyX-Ray computedAmsterdam [u.a.]Elsevier Science1990Online-Ressource32044483X1971551368https://doi.org/10.1016/j.ejrad.2026.112875https://www.sciencedirect.com/science/article/pii/S0720048X260022382001826-05-2626-05-261971551368rda info:srw/schema/1/mods-v3.5 xml 8Compile Better Code with Swift Testing and TDDLodi, GioGioLodiautVerfasserIntextBerkeley, CAApress2026Berkeley, CAImprint: Apress2nd ed. 2026.monographiceng1 Online-Ressource(XIX, 296 p. 37 illus.)Chapter 1: Why Test-Driven Development? -- Chapter 2: Swift Testing Introduction -- Chapter 3: Getting Started with Test-Driven Development -- Chapter 4: Test-Driven Development in the Real World Chapter -- 5: Changing Tests with Fixtures -- Chapter 6: Testing Static SwiftUI Views -- Chapter 7: Testing Dynamic SwiftUI Views -- Chapter 8: Testing Code Based on Indirect Inputs -- Chapter 9: Testing JSON Decoding -- Chapter 10: Testing Network Code -- Chapter 11: Injecting Dependencies with @EnvironmentObject -- Chapter 12: Testing Side Effects -- Chapter 13: Testing Conditional View Presentation -- Chapter 14: Fixing Bugs and Changing Existing Code with TDD Chapter -- 15: Keeping Tests Isolated with Fakes and Clear with Dummies -- Chapter 16: Conclusion.Leverage Swift to practice effective and efficient Test-Driven Development (TDD). Software testing and TDD are evergreen programming concepts—yet Swift developers haven’t widely adopted them. What’s needed is a clear roadmap to learn and adopt TDD in the Swift world. Apple has invested heavily in the Swift Testing library and Xcode’s testing infrastructure, making testing a first-class priority in their ecosystem. The tools are there. This book will show you how to wield them. TDD has much more to offer than catching bugs. With this book, you’ll learn a philosophy for building software. TDD helps you solve problems incrementally, writing only as much code as necessary. By decomposing big problems into small steps, you can move along at a fast pace, always making visible progress. Embark on the Test-Driven Development journey by building a real iOS application and picking up new techniques in each chapter. The book’s concepts will emerge as you figure out ways to use tests to drive the solutions to the problems of each chapter. You’ll be introduced to all the staples and advanced concepts of the craft, understand the trade-offs each technique offers, and review an iterative process of software development. In this fully revised edition, all code is updated to use Apple’s new Swift Testing framework, with networking rewritten using structured concurrency and UI refreshed to match the latest SwiftUI APIs and iOS 26 design, making it the ideal resource for developers embracing the latest computing and development tools. Test-Driven Development in Swift gives you the blueprint for a highly efficient way to make amazing apps. You will: • Write tests that are easy to maintain • Manage and scale an ever-growing test suite • Build a testing vocabulary that transfers beyond Swift • See how Swift’s type system enhances the TDD flow of dynamic languages • Discover how compiler errors can provide the same helpful guidance as failing tests.by Gio LodiPDF/UA-1. Table of contents navigation. Single logical reading order. Short alternative textual descriptions. Use of color is not sole means of conveying information. Use of high contrast between text and background color. Next / Previous structural navigation. All non-decorative content supports reading without sightAccessibility summary: This PDF has been created in accordance with the PDF/UA-1 standard to enhance accessibility, including screen reader support, described non-text content (images, graphs), bookmarks for easy navigation, keyboard-friendly links and forms and searchable, selectable text. We recognize the importance of accessibility, and we welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us at accessibilitysupportspringernature.com. Please note that a more accessible version of this eBook is available as ePub.. No reading system accessibility options actively disabled. Publisher contact for further accessibility information: accessibilitysupportspringernature.com005.268127852018https://doi.org/10.1007/979-8-8688-2637-52055Springer ebook Computing2055Springer ebook Computing2059eBook Springer2064eBook Springer2149eBook Springer26-05-2626-05-261971546038rda info:srw/schema/1/mods-v3.5 xml 9Chaisemartin, ClémentClémentChaisemartinautVerfasserInD'Haultfœuille, XavierXavierD'HaultfœuilleautVerfasserIntext[Paris]SciencesPo, Department of Economics2026monographiceng1 Online-Ressource (circa 44 Seiten)IllustrationenAssume that an estimator is asymptotically normal for a target parameter under some conditions. Suppose also that one can test these conditions, and one conducts inference for the target only if the pre-test is not rejected. Does such pre-testing undermine inference? We show that if the tested conditions and mild regularity restrictions hold, conditional inference is still valid, albeit typically conservative. Validity holds regardless of the asymptotic dependence between the estimator and the pre-test. If the tested conditions do not hold, we exhibit conditions under which confidence intervals have larger conditional than unconditional coverage.Clément de Chaisemartin and Xavier d'Haultfoeuilleno. 2026, 0618903958891971457272https://sciencespo.hal.science/hal-05598141v1/file/2026_de_chaisemartin_and_d_haultfoeuille_is_infernce_conditional_on_not_rejecting_a_pre_test_less_reliable_than_unconditional_inference.pdfhttps://sciencespo.hal.science/hal-05598141v122-05-2627-05-261971457272rda info:srw/schema/1/mods-v3.5 xml 10Amodel-based simulation, robust control design, and deep-learning identificationAlhanouti, MuhammedMuhammedAlhanoutiautVerfasserIntextKarlsruhe2026[2026?]monographiceng1 Online-Ressource (xlv, 226 Seiten)IllustrationenKarlsruher Institut für Technologie (KIT), Dissertation, 2026von M.Sc. Muhammed AlhanoutiKarlsruhe1971381675https://doi.org/10.5445/IR/1000193044manoeuvres21-05-2621-05-261971381675rda