CONA: A novel CONtext-Aware instruction paradigm for communication using large language model

We introduce CONA, a novel context-aware instruction paradigm for effective knowledge dissemination using generative pre-trained transformer (GPT) models. CONA is a flexible framework designed to leverage the capabilities of Large Language Models (LLMs) and incorporate DIKW (Data, Information, Knowledge, Wisdom) hierarchy to automatically instruct and optimise presentation content, anticipate potential audience inquiries, and provide context-aware answers that adaptive to the knowledge level of the audience group. The unique aspect of the CONA paradigm lies in its combination of an independent advisory mechanism and a recursive feedback loop rooted on the DIKW hierarchy. This synergy significantly enhances context-aware contents, ensuring they are accessible and easily comprehended by the audience. This paradigm is an early pioneer to explore new methods for knowledge dissemination and communication in the LLM era, offering effective support for everyday knowledge sharing scenarios. We conduct experiments on a range of audience roles, along with materials from various disciplines using GPT4. Both quantitative and qualitative results demonstrated that the proposed CONA paradigm achieved remarkable performance compared to the outputs guided by conventional prompt engineering

Reliability Evaluation and Prediction Method with Small Samples

How to accurately evaluate and predict the degradation state of the components with small samples is a critical and practical problem. To address the problems of unknown degradation state of components, difficulty in obtaining relevant environmental data and small sample size in the field of reliability prediction, a reliability evaluation and prediction method based on Cox model and 1D CNN-BiLSTM model is proposed in this paper. Taking the historical fault data of six components of a typical load-haul-dump (LHD) machine as an example, a reliability evaluation method based on Cox model with small sample size is applied by comparing the reliability evaluation models such as logistic regression (LR) model, support vector machine (SVM) model and back propagation neural network (BPNN) model in a comprehensive manner. On this basis, a reliability prediction method based on one-dimensional convolutional neural network-bi-directional long and short-term memory network (1D CNN-BiLSTM) is applied with the objective of minimizing the prediction error. The applicability as well as the effectiveness of the proposed model is verified by comparing typical time series prediction models such as the autoregressive integrated moving average (ARIMA) model and multiple linear regression (MLR). The experimental results show that the proposed model is valuable for the development of reliability plans and for the implementation of reliability maintenance activities

Structural basis of DNA binding by the WhiB-like transcription factor WhiB3 in Mycobacterium tuberculosis

Mycobacterium tuberculosis (Mtb) WhiB3 is an iron–sulfur cluster-containing transcription factor belonging to a subclass of the WhiB-Like (Wbl) family that is widely distributed in the phylum Actinobacteria. WhiB3 plays a crucial role in the survival and pathogenesis of Mtb. It binds to the conserved region 4 of the principal sigma factor (σA4) in the RNA polymerase holoenzyme to regulate gene expression like other known Wbl proteins in Mtb. However, the structural basis of how WhiB3 coordinates with σA4 to bind DNA and regulate transcription is unclear. Here we determined crystal structures of the WhiB3:σA4 complex without and with DNA at 1.5 Å and 2.45 Å, respectively, to elucidate how WhiB3 interacts with DNA to regulate gene expression. These structures reveal that the WhiB3:σA4 complex shares a molecular interface similar to other structurally characterized Wbl proteins and also possesses a subclass-specific Arg-rich DNA-binding motif. We demonstrate that this newly defined Arg-rich motif is required for WhiB3 binding to DNA in vitro and transcriptional regulation in Mycobacterium smegmatis. Together, our study provides empirical evidence of how WhiB3 regulates gene expression in Mtb by partnering with σA4 and engaging with DNA via the subclass-specific structural motif, distinct from the modes of DNA interaction by WhiB1 and WhiB7

The Role of Antioxidant Enzymes in the Ovaries

Proper physiological function of the ovaries is very important for the entire female reproductive system and overall health. Reactive oxygen species (ROS) are generated as by-products during ovarian physiological metabolism, and antioxidants are indicated as factors that can maintain the balance between ROS production and clearance. A disturbance in this balance can induce pathological consequences in oocyte maturation, ovulation, fertilization, implantation, and embryo development, which can ultimately influence pregnancy outcomes. However, our understanding of the molecular and cellular mechanisms underlying these physiological and pathological processes is lacking. This article presents up-to-date findings regarding the effects of antioxidants on the ovaries. An abundance of evidence has confirmed the various significant roles of these antioxidants in the ovaries. Some animal models are discussed in this review to demonstrate the harmful consequences that result from mutation or depletion of antioxidant genes or genes related to antioxidant synthesis. Disruption of antioxidant systems may lead to pathological consequences in women. Antioxidant supplementation is indicated as a possible strategy for treating reproductive disease and infertility by controlling oxidative stress (OS). To confirm this, further investigations are required and more antioxidant therapy in humans has to been performed

Automatic Chinese Postal Address Block Location Using Proximity Descriptors and Cooperative Profit Random Forests

Locating the destination address block is key to automated sorting of mails. Due to the characteristics of Chinese envelopes used in mainland China, we here exploit proximity cues in order to describe the investigated regions on envelopes. We propose two proximity descriptors encoding spatial distributions of the connected components obtained from the binary envelope images. To locate the destination address block, these descriptors are used together with cooperative profit random forests (CPRFs). Experimental results show that the proposed proximity descriptors are superior to two component descriptors, which only exploit the shape characteristics of the individual components, and the CPRF classifier produces higher recall values than seven state-of-the-art classifiers. These promising results are due to the fact that the proposed descriptors encode the proximity characteristics of the binary envelope images, and the CPRF classifier uses an effective tree node split approach

Molecular Link between Leaf Coloration and Gene Expression of Flavonoid and Carotenoid Biosynthesis in Camellia sinensis Cultivar ‘Huangjinya’

‘Huangjinya’ is an excellent albino tea germplasm cultivated in China because of its bright color and high amino acid content. It is light sensitive, with yellow leaves under intense light while green leaves under weak light. As well, the flavonoid and carotenoid levels increased after moderate shading treatment. However, the mechanism underlying this interesting phenomenon remains unclear. In this study, the transcriptome of ‘Huangjinya’ plants exposed to sunlight and shade were analyzed by high-throughput sequencing followed by de novo assembly. Shading ‘Huangjinya’ made its leaf color turn green. De novo assembly showed that the transcriptome of ‘Huangjinya’ leaves comprises of 127,253 unigenes, with an average length of 914 nt. Among the 81,128 functionally annotated unigenes, 207 differentially expressed genes were identified, including 110 up-regulated and 97 down-regulated genes under moderate shading compared to full light. Gene ontology (GO) indicated that the differentially expressed genes are mainly involved in protein and ion binding and oxidoreductase activity. Antioxidation-related pathways, including flavonoid and carotenoid biosynthesis, were highly enriched in these functions. Shading inhibited the expression of flavonoid biosynthesis-associated genes and induced carotenoid biosynthesis-related genes. This would suggest that decreased flavonoid biosynthetic gene expression coincides with increased flavonoids (e.g., catechin) content upon moderate shading, while carotenoid levels and biosynthetic gene expression are positively correlated in ‘Huangjinya.’ In conclusion, the leaf color changes in ‘Huangjinya’ are largely determined by the combined effects of flavonoid and carotenoid biosynthesis

Identification of Dynamic Active Sites Among Cu Species Derived from MOFs@CuPc for Electrocatalytic Nitrate Reduction Reaction to Ammonia

Highlights Cu species with tunable loading supported on N-doped TiO2/C were successfully fabricated utilizing MOFs@CuPc precursors via the pre-anchor and post-pyrolysis strategy. Cu species with tunable loading supported on N-doped TiO2/C were successfully fabricated utilizing MOFs@CuPc precursors via the pre-anchor and post-pyrolysis strategy. Restructured CuN4&Cu4 performed the highest NH3 yield (88.2 mmol h−1 gcata −1) and FE (~94.3%) at − 0.75 V due to optimal adsorption of NO3 − and rapid conversion of the key intermediates