-
1 month ago | 
nature.com | Chang Liu |Yawei Lv |Pan Xu |Chao Ma |Xingqiang Liu |Fang Wang | +5 more
AbstractBarrier detectors such as nBn and pBp architectures (formed by a n- or p-type contact layer, a barrier layer and a n- or p-type absorber) aim to block one carrier type while allowing the other to pass, but require complex hetero-integration and precise band engineering. Here, we propose an ultra-thin polar barrier strategy using a 0.75 nm water-intercalated WSe2/H2O/PdSe2 heterostructure.
-
Nov 23, 2024 | 
mdpi.com | Xu Dong |Fang Wang |Meichen Fu |Xinming Dong
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
-
Nov 9, 2024 | 
mdpi.com | Ting Chen |Boyi Deng |Fang Wang |Longlin Yu
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
-
Oct 16, 2024 | 
mdpi.com | Fang Wang |Carlos A. Barrero
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
-
Aug 21, 2024 | 
onlinelibrary.wiley.com | Fang Wang |Ling Zhang |Zhiwen Chen |Xiankun Sun
Data Availability Statement The data that support the findings of this study are available from the corresponding author upon reasonable request.
-
Jul 22, 2024 | 
onlinelibrary.wiley.com | Fang Wang |qiang li |Hong Zhou Chen
REFERENCES , & (2019). Automation and new tasks: How technology displaces and reinstates labor. Journal of Economic Perspectives, 33(2), 3–30. https://doi.org/10.1257/jep.33.2.3 , , & (2019). Exploring the impact of artificial intelligence: Prediction versus judgment. Information Economics and Policy, 47, 1–6. https://doi.org/10.1016/j.infoecopol.2019.05.001 , , & (2003). Are selling, general, and administrative costs “sticky”? Journal of Accounting Research, 41(1), 47–63.
-
Jul 8, 2024 | 
pubs.rsc.org | Kaiyi Zhang |Fang Wang |Lei Zheng |Junqing Wei
“Cage-Confinement” Controlled Dimensionality Conversion of Bi2O2Se Crystals towards High-Performance Phototransistors
2D Bi2O2Se is an intriguing building block for next-generation optoelectrevices due to its ultrahigh electron mobility and ultrabroadband photodetecting capability.
-
Jun 28, 2024 | 
biorxiv.org | Xiao Zhu |Chenchen Qin |Fang Wang |Fan Yang
AbstractThe central dogma serves as a fundamental framework for understanding the flow and expression of genetic information within living organisms, facilitating the connection of diverse biological sequences across molecule types. In this study, we present CD-GPT (Central Dogma Generative Pretrained Transformer), a generative biological foundation model comprising 1 billion parameters, aiming to capture the intricate system-wide molecular interactions in biological systems.
-
Jun 27, 2024 | 
onlinelibrary.wiley.com | Qin Jiang |Fang Wang |Gang Zhou
Corresponding Author Gang Zhou State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Wuhan University, Wuhan, China Department of Oral Medicine, School and Hospital of Stomatology, Wuhan University, Wuhan, China Correspondence Gang Zhou, Department of Oral Medicine, School and Hospital of Stomatology, Wuhan University, Luoyu Road 237, Wuhan,...
-
Jun 3, 2024 | 
nature.com | Xiangsheng Huang |Fang Wang |Yilong Liao |Wenjing Zhang |Li Zhang |Zhenrong Xu | +1 more
The early screening of depression is highly beneficial for patients to obtain better diagnosis and treatment. While the effectiveness of utilizing voice data for depression detection has been demonstrated, the issue of insufficient dataset size remains unresolved. Therefore, we propose an artificial intelligence method to effectively identify depression. The wav2vec 2.0 voice-based pre-training model was used as a feature extractor to automatically extract high-quality voice features from raw audio. Additionally, a small fine-tuning network was used as a classification model to output depression classification results. Subsequently, the proposed model was fine-tuned on the DAIC-WOZ dataset and achieved excellent classification results. Notably, the model demonstrated outstanding performance in binary classification, attaining an accuracy of 0.9649 and an RMSE of 0.1875 on the test set. Similarly, impressive results were obtained in multi-classification, with an accuracy of 0.9481 and an RMSE of 0.3810. The wav2vec 2.0 model was first used for depression recognition and showed strong generalization ability. The method is simple, practical, and applicable, which can assist doctors in the early screening of depression.
