This study proposes a spatial multiplexing wireless communication method based on coding metasurfaces, achieving efficient electromagnetic wave manipulation through optimized coding matrices to enable independent information transmission in different directions. By employing the weighting theorem, we optimize the reflection characteristics of the metasurface, suppressing sidelobe gain and enhancing the gain difference between the main and sidelobes. This improves beam directionality and reduces energy leakage in non-target directions. In the experiment, we constructed a dual-channel direct digital transmission system, where an FPGA dynamically modulates the coding metasurface to generate specific reflected beams based on input data, enabling independent transmission of a 6.1 GHz carrier signal in two asymmetric directions. Experimental results show that, with Chebyshev-weighted optimized coding sequences, the gain difference between the main lobe and the strongest sidelobe increased by 4.99 dB, 1.5 dB, and 7.33 dB at three positive angles (+18°, +28°, and +45°), and by 4.94 dB, 4.03 dB, and 4.22 dB at three negative angles (−15°, −35°, and −40°), respectively. Furthermore, a wireless communication system was constructed based on the metasurface, enabling simultaneous transmission of digital information at two asymmetric angles, −15° and +18°. The proposed spatial multiplexing strategy can be further extended to multi-channel wireless transmission. This study verifies the feasibility of using metasurfaces to manipulate communication signals, providing a foundational reference for future expansion and applications in complex channel environments.

The millions of scientific papers published every year have made it well beyond any human’s ability to read and curate. As a result, valuable data and potentially ground-breaking insights remain buried deep in the mountain of publications. Unfortunately, while modern Information Extraction techniques show great promise, they are rarely developed for scientific text and often perform poorly in scientific scenarios. We present a Relation Extraction model that automates identification of relationships between entity pairs. We incorporate dependency parse information, relation-term attention, and specialized word embeddings in our model. Application to a benchmark dataset results in an F1 score of 0.755, outperforming the 0.682 by a more traditional model.

Despite significant progress in natural language processing, machine learning models require substantial expertannotated training data to perform well in tasks such as named entity recognition (NER) and entity relations extraction. Furthermore, NER is often more complicated when working with scientific text. For example, in polymer science, chemical structure may be encoded using nonstandard naming conventions, the same concept can be expressed using many different terms (synonymy), and authors may refer to polymers with ad-hoc labels. These challenges, which are not unique to polymer science, make it difficult to generate training data, as specialized skills are needed to label text correctly. We have previously designed polyNER, a semi-automated system for efficient identification of scientific entities in text. PolyNER applies word embedding models to generate entity-rich corpora for productive expert labeling, and then uses the resulting labeled data to bootstrap a context-based classifier. PolyNER facilitates a labeling process that is otherwise tedious and expensive. Here, we use active learning to efficiently obtain more annotations from experts and improve performance. Our approach requires just five hours of expert time to achieve discrimination capacity comparable to that of a state-of-the-art chemical NER toolkit.

Along with the advent and popularity of cloud computing, Internet of Things, and bring your own device, the trust requirement for terminal devices has increased significantly. An untrusted terminal, a terminal that runs in an untrustworthy execution environment, may cause serious security issues for enterprise networks. With the release of Software Guard Extension, Intel has provided a promising way to construct trusted terminals and services. Utilizing this technology, we propose a security-enhanced attestation for remote terminals, which can achieve shielded execution for measurements and attestation programs. Furthermore, we present a policy-based measurement mechanism where sensitive data, including secret keys and policy details are concealed using the enclave-specific keys. We implement our attestation prototype on real platform with Intel Skylake processor. Evaluation results show that our attestation system can provide much stronger security guarantees, yet incurs small performance overhead.