High-performance real-world optical computing trained by in situ model-free optimization

Optical computing systems can provide high-speed and low-energy data processing but face deficiencies in computationally demanding training and simulation-to-reality gap. We propose a model-free solution for lightweight in situ optimization of optical computing systems based on the score gradient estimation algorithm. This approach treats the system as a black box and back-propagates loss directly to the optical weights' probabilistic distributions, hence circumventing the need for computation-heavy and biased system simulation. We demonstrate a superior classification accuracy on the MNIST and FMNIST datasets through experiments on a single-layer diffractive optical computing system. Furthermore, we show its potential for image-free and high-speed cell analysis. The inherent simplicity of our proposed method, combined with its low demand for computational resources, expedites the transition of optical computing from laboratory demonstrations to real-world applications

HC3 Plus: A Semantic-Invariant Human ChatGPT Comparison Corpus

ChatGPT has gained significant interest due to its impressive performance, but people are increasingly concerned about its potential risks, particularly around the detection of AI-generated content (AIGC), which is often difficult for untrained humans to identify. Current datasets utilized for detecting ChatGPT-generated text primarily center around question-answering, yet they tend to disregard tasks that possess semantic-invariant properties, such as summarization, translation, and paraphrasing. Our primary studies demonstrate that detecting model-generated text on semantic-invariant tasks is more difficult. To fill this gap, we introduce a more extensive and comprehensive dataset that considers more types of tasks than previous work, including semantic-invariant tasks. In addition, the model after a large number of task instruction fine-tuning shows a strong powerful performance. Owing to its previous success, we further instruct fine-tuning Tk-instruct and built a more powerful detection system. Experimental results show that our proposed detector outperforms the previous state-of-the-art RoBERTa-based detector

Identification and comprehensive analyses of the CBL and CIPK gene families in wheat (Triticum aestivum L.)

The interaction analysis of wheat TaCBL and TaCIPK proteins were performed by Y2H method. (PDF 191 kb

Culture-related grief beliefs of Chinese Shidu parents: Development and psychometric properties of a new scale

Background: In China, parents whose only-child dies and who have no living or adopted child are called Shidu parents. Negative thinking is assumed to contribute to the development of emotional problems in bereavement. Because grief cognitions are likely influenced by the concepts of Chinese traditional culture (e.g., family continuation), Shidu parents may hold specific culture-related grief beliefs about themselves or the world, which, in turn, could impede their recovery. Objective: This study developed a questionnaire assessing the culture-related grief beliefs of Shidu parents and examined its psychometric properties. Methods: This newly developed questionnaire was administered to the combined sample of 313 Shidu parents. Exploratory (n = 164) and confirmatory factor analysis (n = 149) were conducted. Psychometric properties of the questionnaire were evaluated. Results: Exploratory factor analysis revealed three distinct factors (filial piety belief, destiny belief and perceived stigma), generating a nine-item culture-related grief beliefs of Shidu parents questionnaire (CBSQ). Confirmatory factor analysis verified the three-factor structure (chi(2)(24) = 39.103, p = 0.027, chi(2)/df = 1.630, CFI = .980, TLI = .970, RMSEA = .065, SRMR = .052). Internal consistency and temporal stability were adequate. Convergent, discriminant and concurrent validity were supported. Conclusions: This study highlights the importance of extending the concept of grief cognitions to include culture-specific beliefs, and provides a first measurement tool to assess culture-related grief beliefs after only-child loss, which can be used in future research with Shidu parents.National Social Science Fund of China [16ZDA233]Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Retinoic acid-inducible gene-I like receptor pathway in cancer: modification and treatment

Retinoic acid-inducible gene-I (RIG-I) like receptor (RLR) pathway is one of the most significant pathways supervising aberrant RNA in cells. In predominant conditions, the RLR pathway initiates anti-infection function via activating inflammatory effects, while recently it is discovered to be involved in cancer development as well, acting as a virus-mimicry responder. On one hand, the product IFNs induces tumor elimination. On the other hand, the NF-κB pathway is activated which may lead to tumor progression. Emerging evidence demonstrates that a wide range of modifications are involved in regulating RLR pathways in cancer, which either boost tumor suppression effect or prompt tumor development. This review summarized current epigenetic modulations including DNA methylation, histone modification, and ncRNA interference, as well as post-transcriptional modification like m6A and A-to-I editing of the upstream ligand dsRNA in cancer cells. The post-translational modulations like phosphorylation and ubiquitylation of the pathway’s key components were also discussed. Ultimately, we provided an overview of the current therapeutic strategies targeting the RLR pathway in cancers

Proteolytic processing of SERK3/BAK1 regulates plant immunity, development and cell death

Plants have evolved many receptor-like kinases (RLKs) to sense extrinsic and intrinsic cues. The signaling pathways mediated by multiple leucine-rich repeat (LRR) RLK (LRR-RLK) receptors require ligand-induced receptor-coreceptor heterodimerization and transphosphorylation with BAK1/SERK family LRR-RLKs. Here we reveal an additional layer of regulation of BAK1 via a Ca2+-dependent proteolytic cleavage process that is conserved in Arabidopsis thaliana, Nicotiana benthamiana and Saccharomyces cerevisiae . The proteolytic cleavage of BAK1 is intrinsically regulated in response to developmental cues and immune stimulation. The surface-exposed aspartic acid (D287) residue of BAK1 is critical for its proteolytic cleavage and plays an essential role in BAK1-regulated plant immunity, growth hormone brassinosteroid-mediated responses and cell death containment. BAK1D287A mutation impairs BAK1 phosphorylation on its substrate BIK1, and its plasma membrane (PM) localization. Intriguingly, it aggravates BAK1 overexpression-triggered cell death independent of BIK1, suggesting that maintaining homeostasis of BAK1 through a proteolytic process is crucial to control plant growth and immunity. Our data reveal that in addition to layered transphosphorylation in the receptor complexes, the proteolytic cleavage is an important regulatory process for the proper functions of the shared co-receptor BAK1 in diverse cellular signaling pathways

On the use of deep learning for phase recovery

Phase recovery (PR) refers to calculating the phase of the light field from its intensity measurements. As exemplified from quantitative phase imaging and coherent diffraction imaging to adaptive optics, PR is essential for reconstructing the refractive index distribution or topography of an object and correcting the aberration of an imaging system. In recent years, deep learning (DL), often implemented through deep neural networks, has provided unprecedented support for computational imaging, leading to more efficient solutions for various PR problems. In this review, we first briefly introduce conventional methods for PR. Then, we review how DL provides support for PR from the following three stages, namely, pre-processing, in-processing, and post-processing. We also review how DL is used in phase image processing. Finally, we summarize the work in DL for PR and outlook on how to better use DL to improve the reliability and efficiency in PR. Furthermore, we present a live-updating resource (https://github.com/kqwang/phase-recovery) for readers to learn more about PR.Comment: 82 pages, 32 figure