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Ergebnis der Suche nach: "security"
im Bestand: Gesamter Bestand

16021 - 16030 von 16070
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Artikel 16021 Women's security: Critical perspectives on assessment techniques and preventive responses
Enthalten in Security journal Bd. 22, 24.6.2009, Nr. 3, date:7.2009: 175-177
Online Ressource
Artikel 16022 Women, Trade Liberalization and Food Security
Enthalten in Development Bd. 43, 19.1.2004, Nr. 2, date:6.2000: 88-90
Online Ressource
Artikel 16023 Work-related eye injuries among Social Security-insured workers in Brazil: magnitude and temporal trend, 2003–2019
Enthalten in Discover public health Bd. 22, 8.5.2025, Nr. 1, date:12.2025: 1-8
Online Ressource
Artikel 16024 Workers compensation-reported injuries among security and law enforcement personnel in the private versus public sectors
Enthalten in Injury Epidemiology Bd. 5, 2.7.2018, Nr. 1, date:12.2018: 1-9
Online Ressource
Artikel 16025 Working for Food Security and Sustainable Livelihoods: Voices from the Grassroots
Enthalten in Development Bd. 43, 19.1.2004, Nr. 4, date:12.2000: 85-93
Online Ressource
Artikel 16026 Workplace and security stressors and mental health among migrant workers on the Thailand–Myanmar border
Enthalten in Social psychiatry and psychiatric epidemiology Bd. 51, 12.12.2015, Nr. 5, date:5.2016: 713-723
Online Ressource
Artikel 16027 Workshop on Security in Business Processes
Enthalten in Enterprise modelling and information systems architectures Bd. 8, 22.3.2014, Nr. 1, date:1.2013: 75-79
Online Ressource
Artikel 16028 Would dependency on fossil fuels affect food security and sustainable production in aquaculture? Cultural energy use and energy use efficiency for earthen pond European seabass (Dicentrarchus labrax L., 1758) production
Enthalten in Aquaculture international Bd. 31, 24.8.2023, Nr. 5, date:10.2023: 3023-3053
Online Ressource
Artikel 16029 WTO and a permanent solution for food security: striving for a hunger-free world
Enthalten in Food security Bd. 16, 25.1.2024, Nr. 2, date:4.2024: 321-337
Online Ressource
Artikel 16030 X-CBNet: An Explainable Effective Deep Learning Framework Based on Spectrograms for Predicting Valvular Disorder using PCG Signals
Enthalten in Journal of transformative technologies and sustainable development Bd. 9, 27.11.2025, Nr. 1, date:12.2025: 1-15
Online Ressource


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