What Shapes the Integration Trajectory of Refugee Students? A Comparative Policy Analysis in Two German States

Enabling the successful integration of refugee students into the German schooling system poses a crucial challenge for the coming years. Drawing from the human rights frame- work of the Inter-agency Network for Education in Emergencies standards, we applied a rights-based approach to policy analysis on educational provisions for refugee students from 2012 to 2018. According to international and European law, Germany is obliged to grant similar access to education for nationals as well as refugee children and youth. In reality, the realization of educational rights varies from state to state. This will be highlighted and discussed in this article, using the example of two very different German states, Hamburg and Saxony. The sudden rise of numbers of refugees led only slowly to an increase in educational policy density and intensity on federal state and national levels in 2016 and 2017. We find that the differences in compulsory schooling, models of integration into schooling, and the asylum and settlement policies in both states shape the educational participation of refugee children and youths. Both states implemented parallel integration models that might bear risks of stigmatization and limit educational possibilities. However, transition and language support concepts in both contexts contain integrative phases offer- ing language supports in the regular classrooms. Asylum policies and state-specific settlement policies have profound implications for the rights and access to education. Further, vocational education and training programs play a crucial role, especially in Saxony, to tackle demographic challenges.

Layered assemblers for scalable parallel integration

Many complex natural and artificial systems are composed of large numbers of elementary building blocks, such as organisms made of many biological cells or processors made of many electronic transistors. This modular substrate is essential to the evolution of biological and technological complexity, but has been difficult to replicate for mechanical systems. This study seeks to answer if layered assembly can engender exponential gains in the speed and efficacy of block or cell-based manufacturing processes. A key challenge is how to deterministically assemble large numbers of small building blocks in a scalable manner. Here, we describe two new layered assembly principles that allow assembly faster than linear time, integrating n modules in O( n 2/3 ) and O( n 1/3 ) time: one process uses a novel opto-capillary effect to selectively deposit entire layers of building blocks at a time, and a second process jets building block rows in rapid succession. We demonstrate the fabrication of multi-component structures out of up to 20 000 millimetre scale spherical building blocks in 3 h. While these building blocks and structures are still simple, we suggest that scalable layered assembly approaches, combined with a growing repertoire of standardized passive and active building blocks could help bridge the meso-scale assembly gap, and open the door to the fabrication of increasingly complex, adaptive and recyclable systems.

Inflammatory Pain Study in Animal Models

Pain is an easily recognized sensation that is experienced by humans and animals alike. However, the process behind the production of the pain experience is a complex pathway that requires parallel integration of both the emotional and sensory experiences together with noxious perceptual information registered by multiple layers of our brain structure with the purpose of defending our body from harm’s way. Here, the complete protocol that is being adapted for inflammatory pain study in animals induced by different phlogogenic agents and different assessment methods were elaborated along with the underlying mechanism of actions. This provides a concise idea and improves our scientists’ understanding of inflammatory pain management in future research.

Integrating Proteomes for Lung Tissue and Lavage Reveals Pathways that Link Responses in Allergen-Challenged Mice

To capture interplay between biological pathways we analyzed the proteome from matched lung tissue and bronchoalveolar lavage fluid (BALF) of individual allergen-naïve and house dust mite (HDM)-challenged BALB/c mice, a model of allergic asthma. Unbiased label-free LC-MS/MS analysis quantified 2,675 proteins from tissue and BALF of allergen-naïve and HDM-exposed mice. In comparing the four datasets we found significantly greater diversity in proteins between lung tissue and BALF than in the changes induced by HDM challenge. The biological pathways enriched after allergen exposure were compartment-dependent. Lung tissue featured innate immune responses and oxidative stress, while BALF most strongly revealed changes in metabolism. We combined lung tissue and BALF proteomes, which principally highlighted oxidation reduction (redox) pathways, a finding influenced chiefly by the lung tissue dataset. Integrating lung and BALF proteomes also uncovered new proteins and biological pathways that may mediate lung tissue and BALF interactions after allergen challenge, for example, B Cell Receptor signaling. We demonstrate that enhanced insight is fostered when different biological compartments from the lung are investigated in parallel. Integration of proteomes from lung tissue and BALF compartments reveals new information about protein networks in the response to environmental challenge and interaction between intracellular and extracellular process.

Unsteady State Lightweight Iris Certification Based on Multi-Algorithm Parallel Integration

Aimed at the one-to-one certification problem of unsteady state iris at different shooting times, a multi-algorithm parallel integration general model structure is proposed in this paper. The iris in the lightweight constrained state affected by defocusing, deflection, and illumination is taken as the research object, the existing algorithms are combined into the model structure effectively, and a one-to-one certification algorithm for lightweight constrained state unsteady iris was designed based on multi-algorithm integration and maximum trusted decision. In this algorithm, a sufficient number of iris internal feature points from the unstable state texture were extracted as effective iris information through the image processing layer composed of various filtering processing algorithms, thereby eliminating defocused interference. In the feature recognition layer, iris deflection interference was excluded by the improved methods of Gabor and Hamming and Haar and BP for the stable features extracted by the image processing layer, and two certification results were obtained by means of parallel recognition. The correct number of certifications for an algorithm under a certain lighting condition were counted. The method with the most correct number was set as the maximum trusted method under this lighting condition, and the results of the maximum trusted method were taken as the final decision, thereby eliminating the effect of illumination. Experiments using the JLU and CASIA iris libraries under the prerequisites in this paper show that the correct recognition rate of the algorithm can reach a high level of 98% or more, indicating that the algorithm can effectively improve the accuracy of the one-to-one certification of lightweight constrained state unsteady iris. Compared with the latest architecture algorithms, such as CNN and deep learning, the proposed algorithm is more suitable for the prerequisites presented in this paper, which has good environmental inclusiveness and can better improve existing traditional algorithms’ effectiveness through the design of a parallel integration model structure.