528 research outputs found

    Re-balancing the excellence frameworks with individualistic logic

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    The analysis and assessment of business excellence are often associated with the discussion on the design and justification of the excellence measures and their dimensions. This paper re-visits the critical issues in assessing business excellence, and aims to explore the conceptual development on re-balancing the performance dimensions in view of a framework. Based on the synthesising of published literatures and case studies it reveals that all the published excellence frameworks are based on the commonality logic ; and it suggests re-balancing them with the individualistic logic . This concept has then been operationalised by constructing a new excellence framework named world-class diamond model. Based on the surveyed data and by using structural equation modelling the re-balanced diamond model is tested and analysed in order to secure its theoretical validity. With the re-balanced framework, it stresses the critical importance of the individualistic logic in achieving business excellence. It also argues that the managerial implication of the individualistic logic lies in the firm-specific and situation-sensitive practices of business excellence. The original contribution of the research is a conceptually re-balanced perspective of business excellence, suggesting a shift from commonality logic towards individualistic logic

    Structural and biochemical insights into small RNA 3' end trimming by Arabidopsis SDN1.

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    A family of DEDDh 3'→5' exonucleases known as Small RNA Degrading Nucleases (SDNs) initiates the turnover of ARGONAUTE1 (AGO1)-bound microRNAs in Arabidopsis by trimming their 3' ends. Here, we report the crystal structure of Arabidopsis SDN1 (residues 2-300) in complex with a 9 nucleotide single-stranded RNA substrate, revealing that the DEDDh domain forms rigid interactions with the N-terminal domain and binds 4 nucleotides from the 3' end of the RNA via its catalytic pocket. Structural and biochemical results suggest that the SDN1 C-terminal domain adopts an RNA Recognition Motif (RRM) fold and is critical for substrate binding and enzymatic processivity of SDN1. In addition, SDN1 interacts with the AGO1 PAZ domain in an RNA-independent manner in vitro, enabling it to act on AGO1-bound microRNAs. These extensive structural and biochemical studies may shed light on a common 3' end trimming mechanism for 3'→5' exonucleases in the metabolism of small non-coding RNAs

    C3: Zero-shot Text-to-SQL with ChatGPT

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    This paper proposes a ChatGPT-based zero-shot Text-to-SQL method, dubbed C3, which achieves 82.3\% in terms of execution accuracy on the holdout test set of Spider and becomes the state-of-the-art zero-shot Text-to-SQL method on the Spider Challenge. C3 consists of three key components: Clear Prompting (CP), Calibration with Hints (CH), and Consistent Output (CO), which are corresponding to the model input, model bias and model output respectively. It provides a systematic treatment for zero-shot Text-to-SQL. Extensive experiments have been conducted to verify the effectiveness and efficiency of our proposed method

    Computational prediction of novel non-coding RNAs in Arabidopsis thaliana

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    BackgroundNon-coding RNA (ncRNA) genes do not encode proteins but produce functional RNA molecules that play crucial roles in many key biological processes. Recent genome-wide transcriptional profiling studies using tiling arrays in organisms such as human and Arabidopsis have revealed a great number of transcripts, a large portion of which have little or no capability to encode proteins. This unexpected finding suggests that the currently known repertoire of ncRNAs may only represent a small fraction of ncRNAs of the organisms. Thus, efficient and effective prediction of ncRNAs has become an important task in bioinformatics in recent years. Among the available computational methods, the comparative genomic approach seems to be the most powerful to detect ncRNAs. The recent completion of the sequencing of several major plant genomes has made the approach possible for plants.ResultsWe have developed a pipeline to predict novel ncRNAs in the Arabidopsis (Arabidopsis thaliana) genome. It starts by comparing the expressed intergenic regions of Arabidopsis as provided in two whole-genome high-density oligo-probe arrays from the literature with the intergenic nucleotide sequences of all completely sequenced plant genomes including rice (Oryza sativa), poplar (Populus trichocarpa), grape (Vitis vinifera), and papaya (Carica papaya). By using multiple sequence alignment, a popular ncRNA prediction program (RNAz), wet-bench experimental validation, protein-coding potential analysis, and stringent screening against various ncRNA databases, the pipeline resulted in 16 families of novel ncRNAs (with a total of 21 ncRNAs).ConclusionIn this paper, we undertake a genome-wide search for novel ncRNAs in the genome of Arabidopsis by a comparative genomics approach. The identified novel ncRNAs are evolutionarily conserved between Arabidopsis and other recently sequenced plants, and may conduct interesting novel biological functions

    Bio-Inspired Autonomous Learning Algorithm With Application to Mobile Robot Obstacle Avoidance

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    Spiking Neural Networks (SNNs) are often considered the third generation of Artificial Neural Networks (ANNs), owing to their high information processing capability and the accurate simulation of biological neural network behaviors. Though the research for SNNs has been quite active in recent years, there are still some challenges to applying SNNs to various potential applications, especially for robot control. In this study, a biologically inspired autonomous learning algorithm based on reward modulated spike-timing-dependent plasticity is proposed, where a novel rewarding generation mechanism is used to generate the reward signals for both learning and decision-making processes. The proposed learning algorithm is evaluated by a mobile robot obstacle avoidance task and experimental results show that the mobile robot with the proposed algorithm exhibits a good learning ability. The robot can successfully avoid obstacles in the environment after some learning trials. This provides an alternative method to design and apply the bio-inspired robot with autonomous learning capability in the typical robotic task scenario

    Effect of magnetic Fe3O4 nanoparticles with 2-methoxyestradiol on the cell-cycle progression and apoptosis of myelodysplastic syndrome cells

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    This study aims to evaluate the potential benefit of combination therapy of 2-methoxyestradiol (2ME) and magnetic nanoparticles of Fe3O4 (MNPs-Fe3O4) on myelodysplastic syndrome (MDS) SKM-1 cells and its underlying mechanisms. The effect of the unique properties of tetraheptylammonium-capped MNPs-Fe3O4 with 2ME on cytotoxicity was tested by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay. Cell-cycle distribution and apoptosis were assessed by flow cytometry. The expression of cell-cycle marker protein was measured by Western blotting. Growth inhibition rate of SKM-1 cells treated with the 2ME-loaded MNPs-Fe3O4 was enhanced when compared with 2ME alone. 2ME led to an increase of caspase-3 expression, followed by apoptosis, which was significantly increased when combined with an MNPs-Fe3O4 carrier. Moreover, the copolymer of 2ME with MNPs- Fe3O4 blocked a nearly two-fold increase in SKM-1 cells located in G2/M phase than in 2ME alone, which may be associated with an accompanying increase of p21 as well as a decrease in cyclin B1 and cdc2 expression, but there was no obvious difference between the MNPs-Fe3O4 and control group. These findings suggest that the unique properties of MNPs-Fe3O4 as a carrier for 2ME, a new anticancer agent currently in clinical trials, may be a logical strategy to enhance the therapeutic activity of MDS

    Comparisons of different approaches and incisions of thyroid surgery and selection strategy

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    To date, the traditional open thyroid surgery via a low collar incision remains the standard approach for patients undergoing thyroidectomy. However, this conventional approach will inevitably leave patients a neck scar and even cause a variety of complications such as paresthesia, hypesthesia, and other uncomfortable sensations. With the progress in surgical techniques, especially in endoscopic surgery, and the increasing desire for cosmetic and functional outcomes, various new approaches for thyroidectomy have been developed to avoid or decrease side effects. Some of these alternative approaches have obvious advantages compared with traditional surgery and have already been widely used in the treatment of thyroid disease, but each has its limitations. This review aims to evaluate and compare the different approaches to thyroidectomy to help surgeons make the proper treatment strategy for different individuals
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