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Titlebook: Wie ?konomisches Wissen wirksam wird; Von der Performativi Jan Sparsam Book 2019 Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer

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樓主: Truman
21#
發(fā)表于 2025-3-25 05:13:40 | 只看該作者
22#
發(fā)表于 2025-3-25 08:41:03 | 只看該作者
23#
發(fā)表于 2025-3-25 13:36:56 | 只看該作者
Comparing Life Historiesher key limiting variable. A more useful approach for understanding life history diversity is to combine optimality theory with comparative data on fertility and mortality schedules, which are likely to vary with habitat. Differences in body size are important in so far as they influence those sched
24#
發(fā)表于 2025-3-25 17:56:28 | 只看該作者
Methods for Assessing the In Vivo Role of PTEN in Glucose Homeostasisso via its role in other cell processes required to maintain metabolic homeostasis. We describe the generation of tissue-specific PTEN knockout mice and models of both type 1 and type 2 diabetes, which we have found useful for the study of diabetes pathogenesis. We also outline common methods suitab
25#
發(fā)表于 2025-3-25 23:59:48 | 只看該作者
A Steady-State Genetic Algorithm for the Dominating Tree Problemin wireless sensor networks. This problem consists in finding a tree, say ., with minimum total edge weight on an undirected, weighted and connected graph such that each vertex of the graph is either in . or adjacent to a vertex in .. In this paper, a steady-state genetic algorithm (SSGA) is propose
26#
發(fā)表于 2025-3-26 04:11:58 | 只看該作者
27#
發(fā)表于 2025-3-26 05:32:19 | 只看該作者
Efficient Numerical Implementation Strategies via Sparse Representations and Compressive Sampling,l bases, whereas the sparsity of the expansions is exploited, as well, for decreasing the overall computational cost. The chapter concludes with various examples with distinct features for assessing the performance of the WPI technique.
28#
發(fā)表于 2025-3-26 09:36:31 | 只看該作者
Self-Adaptive Frequency Scaling Architecture for Intrusion Detection System,rediction of the network traffic. It calculates optimal frequency scaling operation sequence via an internal sandbox model, so as to achieve energy saving purposes. Experiments show that our method can save 60?% power consumption generally.
29#
發(fā)表于 2025-3-26 14:48:14 | 只看該作者
Cross-Layer Feature Attention Module for Multi-scale Object Detection,ith the fused features. Experiments show the proposed module improves the detection rate by 2% against the baseline architecture, and outperforms recent state-of-the-art methods on the Pascal VOC benchmark.
30#
發(fā)表于 2025-3-26 17:58:01 | 只看該作者
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