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To investigate the state-of-the-art of virtual reality in special education, we reviewed the related research over the past ten years. Strategies and approaches of the study design have been characterized and categorized based on their research focuses. Both perspectives from the special educators and the students with special needs are addressed. This study reveals that immersive virtual reality is effective in special education, while challenges still remain in this area. We provide insights for future studies and also call for more collaboration among researchers, practitioners, and educators. 

Abstract The Madden-Julian oscillation (MJO) has profound impacts on weather and climate phenomena, and thus changes in its activity have important implications under human-induced global climate change. Here, the time at which the MJO change signal emerges from natural variability under anthropogenic warming is investigated. Using simulations of the Community Earth System Model version 2 large ensemble forced by the shared socioeconomic pathways SSP370 scenario, an increase in ensemble mean MJO precipitation amplitude and a smaller increase in MJO circulation amplitude occur by the end of the 21 st century, consistent with previous studies. Notably, the MJO precipitation amplitude change signal generally emerges more than a decade earlier than that of MJO wind amplitude. MJO amplitude changes also emerge earlier over the eastern Pacific than other parts of the tropics. Our findings provide valuable information on the potential changes of MJO variability with the aim of improving predictions of the MJO and its associated extreme events. 

We establish an explicit embedding of a quantum affine sl_n into a quantum affine sl_{n+1} . This embedding serves as a common generalization of two natural, but seemingly unrelated embeddings, one on the quantum affine Schur algebra level and the other on the non-quantum level. The embedding on the quantum affine Schur algebras is used extensively in the analysis of canonical bases of quantum affine sl_n and gl_n. The embedding on the non-quantum level is used crucially in a work of Riche and Williamson on the study of modular representation theory of general linear groups over a finite field. The same embedding is also used in a work of Maksimau on the categorical representations of affine general linear algebras. We further provide a more natural compatibility statement of the em- bedding on the idempotent version with that on the quantum affine Schur algebra level. A gl_n-variant of the embedding is also established. 

A soft, flexible pressure sensor is developed to measure hydrostatic pressure in the ocean environment, which can be potentially integrated with many platforms including diver equipment and marine animal tags for real-time pressure monitoring.

 

In this work, we investigate the diffusive optical tomography (DOT) problem in the case that limited boundary measurements are available. Motivated by the direct sampling method (DSM) proposed in Chow et al. (SIAM J Sci Comput 37(4):A1658–A1684, 2015), we develop a deep direct sampling method (DDSM) to recover the inhomogeneous inclusions buried in a homogeneous background. In this method, we design a convolutional neural network to approximate the index functional that mimics the underling mathematical structure. The benefits of the proposed DDSM include fast and easy implementation, capability of incorporating multiple measurements to attain high-quality reconstruction, and advanced robustness against the noise. Numerical experiments show that the reconstruction accuracy is improved without degrading the efficiency, demonstrating its potential for solving the real-world DOT problems.

 

Linked climate and crop simulation models are widely used to assess the impact of climate change on agriculture. However, it is unclear how ensemble configurations (model composition and size) influence crop yield projections and uncertainty. Here, we investigate the influences of ensemble configurations on crop yield projections and modeling uncertainty from Global Gridded Crop Models and Global Climate Models under future climate change. We performed a cluster analysis to identify distinct groups of ensemble members based on their projected outcomes, revealing unique patterns in crop yield projections and corresponding uncertainty levels, particularly for wheat and soybean. Furthermore, our findings suggest that approximately six Global Gridded Crop Models and 10 Global Climate Models are sufficient to capture modeling uncertainty, while a cluster-based selection of 3-4 Global Gridded Crop Models effectively represents the full ensemble. The contribution of individual Global Gridded Crop Models to overall uncertainty varies depending on region and crop type, emphasizing the importance of considering the impact of specific models when selecting models for local-scale applications. Our results emphasize the importance of model composition and ensemble size in identifying the primary sources of uncertainty in crop yield projections, offering valuable guidance for optimizing ensemble configurations in climate-crop modeling studies tailored to specific applications.

 

Solitary fibrous tumor (SFT) is a rare soft-tissue sarcoma. This nonhereditary cancer is the result of an environmental intrachromosomal gene fusion between NAB2 and STAT6 on chromosome 12, which fuses the activation domain of STAT6 with the repression domain of NAB2. Currently there is not an approved chemotherapy regimen for SFTs. The best response on available pharmaceuticals is a partial response or stable disease for several months. The purpose of this study is to investigate the potential of RNA-based therapies for the treatment of SFTs. Specifically, in vitro SFT cell models were engineered to harbor the characteristic NAB2–STAT6 fusion using the CRISPR/SpCas9 system. Cell migration as well as multiple cancer-related signaling pathways were increased in the engineered cells as compared to the fusion-absent parent cells. The SFT cell models were then used for evaluating the targeting efficacies of NAB2–STAT6 fusion-specific antisense oligonucleotides (ASOs) and CRISPR/CasRx systems. Our results showed that fusion specific ASO treatments caused a 58% reduction in expression of fusion transcripts and a 22% reduction in cell proliferation after 72 h in vitro. Similarly, the AAV2-mediated CRISPR/CasRx system led to a 59% reduction in fusion transcript expressions in vitro, and a 55% reduction in xenograft growth after 29 days ex vivo.