Coping with multiple institutional logics:temporal process of institutional work during the emergence of the one foundation in China

An increasing body of research has applied an institutional perspective to understand actors’ responses to conflicting institutional logics and the creation process of new organizational forms. Although China provides a natural, real-time laboratory to study this topic, few empirical research have been done. Moreover, we find it is insufficient to apply current frameworks, which have been mainly driven by studies conducted in Western contexts, to study actors’ responses to institutional multiplicity in China, especially in its emerging non-profit sector. This paper fills research gaps by providing an in-depth case analysis of the creation and legitimation process of One Foundation − the first independent charity fundraising foundation established by civic individuals in China. Our study shows that the coexisting and competing relationship among state, civil society, social mission, and market logics provides impetus for organizational change and innovation. This paper theorizes a temporal model by showing that actors seek provisional solutions in different organizational stages and gradually develop capabilities to progress institutional work from individual to organizational and to societal level to achieve their goals. By showing how a charity foundation plays a role as a changing agent, this paper also sheds lights on the condition and process that drive innovation in China’s non-profit sector

Identification and characterization of a novel thermostable pyrethroid-hydrolyzing enzyme isolated through metagenomic approach

<p>Abstract</p> <p>Background</p> <p>Pyrethroid pesticides are broad-spectrum pest control agents in agricultural production. Both agricultural and residential usage is continuing to grow, leading to the development of insecticide resistance in the pest and toxic effects on a number of nontarget organisms. Thus, it is necessary to hunt suitable enzymes including hydrolases for degrading pesticide residues, which is an efficient "green" solution to biodegrade polluting chemicals. Although many pyrethroid esterases have consistently been purified and characterized from various resources including metagenomes and organisms, the thermostable pyrethroid esterases have not been reported up to the present.</p> <p>Results</p> <p>In this study, we identified a novel pyrethroid-hydrolyzing enzyme Sys410 belonging to familyV esterases/lipases with activity-based functional screening from Turban Basin metagenomic library. Sys410 contained 280 amino acids with a predicted molecular mass (Mr) of 30.8 kDa and was overexpressed in <it>Escherichia coli </it>BL21 (DE3) in soluble form. The optimum pH and temperature of the recombinant Sys410 were 6.5 and 55°C, respectively. The enzyme was stable in the pH range of 4.5-8.5 and at temperatures below 50°C. The activity of Sys410 decreased a little when stored at 4°C for 10 weeks, and the residual activity reached 94.1%. Even after incubation at 25°C for 10 weeks, it kept 68.3% of its activity. The recombinant Sys410 could hydrolyze a wide range of ρ-nitrophenyl esters, but its best substrate is ρ-nitrophenyl acetate with the highest activity (772.9 U/mg). The enzyme efficiently degraded cyhalothrin, cypermethrin, sumicidin, and deltamethrin under assay conditions of 37°C for 15 min, with exceeding 95% hydrolysis rate.</p> <p>Conclusion</p> <p>This is the first report to construct metagenomic libraries from Turban Basin to obtain the thermostable pyrethroid-hydrolyzing enzyme. The recombinant Sys410 with broad substrate specificities and high activity was the most thermostable one of the pyrethroid-hydrolyzing esterases studied before, which made it an ideal candidate for the detoxification of pyrethroids.</p

Banks’ maturity mismatch, financial stability, and macroeconomic dynamics

The average maturity of total bank assets has been rising sharply following the 4-trillion-yuan stimulus package proposed by the Chinese government in 2009. This paper investigates the macroeconomic implications of maturity mismatch problem using the Chinese data over the period 2007Q1–2019Q4. We extend the New-Keynesian DSGE framework from several dimensions: (i) financial frictions between banks and households; (ii) multi-period loan contracts; (iii) dynamic differential reserve requirement as a macroprudential regulation tool. After estimating the model with Chinese data, the simulation results indicate that the sluggish adjustment of financing cost caused by maturity mismatch will attenuate the real sector fluctuation, however, the feedback effects will amplify the responses of the banking sector. Meanwhile, a severe maturity mismatch will dampen the effect of the required reserve rate as a tool to keep financial stability when confronted with productivity shock

Deraining and Desnowing Algorithm on Adaptive Tolerance and Dual-tree Complex Wavelet Fusion

Severe weather conditions such as rain and snow often reduce the visual perception quality of the video image system, the traditional methods of deraining and desnowing usually rarely consider adaptive parameters. In order to enhance the effect of video deraining and desnowing, this paper proposes a video deraining and desnowing algorithm based on adaptive tolerance and dual-tree complex wavelet. This algorithm can be widely used in security surveillance, military defense, biological monitoring, remote sensing and other fields. First, this paper introduces the main work of the adaptive tolerance method for the video of dynamic scenes. Second, the algorithm of dual-tree complex wavelet fusion is analyzed and introduced. Using principal component analysis fusion rules to process low-frequency sub-bands, the fusion rule of local energy matching is used to process the high-frequency sub-bands. Finally, this paper used various rain and snow videos to verify the validity and superiority of image reconstruction. Experimental results show that the algorithm has achieved good results in improving the image clarity and restoring the image details obscured by raindrops and snows

Transforming the Interactive Segmentation for Medical Imaging

The goal of this paper is to interactively refine the automatic segmentation on challenging structures that fall behind human performance, either due to the scarcity of available annotations or the difficulty nature of the problem itself, for example, on segmenting cancer or small organs. Specifically, we propose a novel Transformer-based architecture for Interactive Segmentation (TIS), that treats the refinement task as a procedure for grouping pixels with similar features to those clicks given by the end users. Our proposed architecture is composed of Transformer Decoder variants, which naturally fulfills feature comparison with the attention mechanisms. In contrast to existing approaches, our proposed TIS is not limited to binary segmentations, and allows the user to edit masks for arbitrary number of categories. To validate the proposed approach, we conduct extensive experiments on three challenging datasets and demonstrate superior performance over the existing state-of-the-art methods. The project page is: https://wtliu7.github.io/tis/.Comment: Accepted to MICCAI 202

Can the Query-based Object Detector Be Designed with Fewer Stages?

Query-based object detectors have made significant advancements since the publication of DETR. However, most existing methods still rely on multi-stage encoders and decoders, or a combination of both. Despite achieving high accuracy, the multi-stage paradigm (typically consisting of 6 stages) suffers from issues such as heavy computational burden, prompting us to reconsider its necessity. In this paper, we explore multiple techniques to enhance query-based detectors and, based on these findings, propose a novel model called GOLO (Global Once and Local Once), which follows a two-stage decoding paradigm. Compared to other mainstream query-based models with multi-stage decoders, our model employs fewer decoder stages while still achieving considerable performance. Experimental results on the COCO dataset demonstrate the effectiveness of our approach

Coping with multiple institutional logics:temporal process of institutional work during the emergence of the one foundation in China

ABSTRACTAn increasing body of research has applied an institutional perspective to understand actors’ responses to conflicting institutional logics and the creation process of new organizational forms. Although China provides a natural, real-time laboratory to study this topic, scant empirical research has been done. Moreover, we find it is insufficient to apply current frameworks, which have been mainly driven by studies conducted in Western contexts, to study actors’ responses to institutional multiplicity in China, especially in its emerging non-profit sector. This article fills research gaps by providing an in-depth case analysis of the creation and legitimation process of the One Foundation – the first independent charity foundation established by civic individuals in China. Our study shows that the coexisting and competing relationship among state, civil society, social mission, and market logics provides impetus for organizational change and innovation. This article theorizes a temporal model by showing that actors seek provisional solutions in different organizational stages and gradually develop capabilities to progress institutional work from individual to organizational and to societal level to achieve their goals. By showing how a charity foundation plays a role as a change agent, this article also sheds light on the condition and process that drive innovation in China's non-profit sector.</jats:p

LORS: Low-rank Residual Structure for Parameter-Efficient Network Stacking

Deep learning models, particularly those based on transformers, often employ numerous stacked structures, which possess identical architectures and perform similar functions. While effective, this stacking paradigm leads to a substantial increase in the number of parameters, posing challenges for practical applications. In today's landscape of increasingly large models, stacking depth can even reach dozens, further exacerbating this issue. To mitigate this problem, we introduce LORS (LOw-rank Residual Structure). LORS allows stacked modules to share the majority of parameters, requiring a much smaller number of unique ones per module to match or even surpass the performance of using entirely distinct ones, thereby significantly reducing parameter usage. We validate our method by applying it to the stacked decoders of a query-based object detector, and conduct extensive experiments on the widely used MS COCO dataset. Experimental results demonstrate the effectiveness of our method, as even with a 70\% reduction in the parameters of the decoder, our method still enables the model to achieve comparable orComment: 9 pages, 5 figures, 11 tables, CVPR2024 accepte

Low expression of acyl-CoA thioesterase 13 is associated with poor prognosis in ovarian serous cystadenocarcinoma

Objective: Acyl-CoA thioesterase 13 (ACOT13) encodes a member of the thioesterase superfamily. It has not been reported in ovarian cancer. This research aimed at evaluating the expression and prognostic value of ACOT13 in ovarian serous cystadenocarcinoma (OSC).Methods: We extracted and analyzed TCGA, GEPIA, THPA, GTEx, miRWalk, and GDSC databases to investigate the potential carcinogenic mechanism of ACOT13 in OSC, including the correlation of ACOT13 with prognosis, immune checkpoint, tumor mutational burden (TMB), and 50% inhibition concentration (IC50) score. The incidence of endpoint events was compared with Kaplan-Meier survival analysis. Independent prognostic factors for OSC were evaluated with univariate and multivariate Cox regression analyses, and a nomogram was established.Results: The expression of ACOT13 was increased in OSC and correlated with tumor stage, with higher expression in stages I and II than in stages III and IV. Besides, it was observed that low expression of ACOT13 is correlated with poor overall survival (OS), progression-free survival (PFS), and disease-specific survival (DSS) in patients with OSC. There was a positive correlation between ACOT13 expression and immune checkpoint sialic acid-binding Ig-like lectin (SIGLEC) 15 and TMB. Patients with low ACOT13 expression had higher cisplatin IC50 scores.Conclusion: ACOT13 is an independent prognostic factor and a promising clinical target for OSC. In the future, the carcinogenic mechanism and clinical application value of ACOT13 in ovarian cancer need to be further studied

Improved QR Decomposition-Based SIC Detection Algorithm for MIMO System

Abstract: Multiple-Input Multiple-Output (MIMO) systems can increase wireless communication system capacity enormously. Maximum Likelihood (ML) detection algorithm is the optimum detection algorithm which computational complexity growing exponentially with the number of transmit-antennas, which makes it difficult to use it in practice system. Ordered Successive Interference Cancellation (SIC) algorithm with lower computing complexity will suffer from error propagation when an incorrect symbol is selected in the early layers. An MIMO signal detection algorithm based on Improved Sorted-QR decomposition (ISQR) is presented in this study. According to the rule of SNR, ISQR can obtain the optimum detection order with less calculation. Based on ISQR an improved detection algorithm is proposed which providing 2 adjustable parameters. Trade-off between performance and complexity can be selected properly by setting the 2 parameters at different values. Simulation experiments are given under the multiple scattering wireless communication environments and the simulation experiment results show the validity of proposed algorithm