The safety and efficacy of hypothermia combining mechanical thrombectomy or thrombolysis in the treatment of ischemic stroke: A systematic meta-analysis

Background: Stroke is a major global public health problem, affecting 13.7 million people worldwide. Previous studies have found a neuroprotective effect of hypothermia therapy and the efficacy and safety of combined hypothermia and mechanical thrombectomy or thrombolysis in the treatment of ischemic stroke have also attracted attention. Objective: In the present research, the authors conducted a meta-analysis to comprehensively assess the safety and efficacy of hypothermia combining mechanical thrombectomy or thrombolysis in the treatment of ischemic stroke. Methods: Articles published from January 2001 to May 2022 were searched from Google Scholar, Baidu Scholar and PubMed to evaluate the clinical significance of hypothermia treatment in ischemic stroke. Complications, short-term mortality, and the modified Rankin Scale (mRS) in the full text was extracted. Results: 89 publications were selected and 9 among them were included in this study with sample size of 643. All selected studies are in accordance with the inclusion criteria. Forest plot of clinical characteristics was as follows: complications (RR = 1.132, 95% CI 0.942‒1.361, p = 0.186, I2 = 37.2%), mortality within 3 months (RR = 1.076, 95% CI 0.694‒1.669, p = 0.744, I2 = 0.00%), mRS ≤ 1 at 3 months (RR = 1.138, 95% CI 0.829‒1.563, p = 0.423, I2 = 26.0%), mRS ≤ 2 at 3 months (RR = 1.672, 95% CI 1.236‒2.263, p = 0.001, I2=49.6%) and mRS ≤ 3 at 3 months (RR = 1.518, 95% CI 1.128‒2.043, p = 0.006, I2 = 0.00%). The funnel plot suggested that there was no significant publication bias in the meta-analysis on complications, mortality within 3 months, mRS ≤ 1 at 3 months and mRS ≤ 2 at 3 months. Conclusion: In summary, the results showed that hypothermia treatment was correlated with mRS ≤ 2 at 3 months, but not linked with complications and mortality within 3 months

Modeling Government Credit Information Systems Diffusion in China: A System Dynamics Approach

This paper examines the usage and diffusion of Government Credit Information Systems (GCIS) in district-level governments in shanghai. The diffusion of GCIS was studied from a process-oriented perspective. A System Dynamics (SD) model is developed to simulate the relationships of technological, organizational and environmental, and institutional factors on GCIS diffusion under different management policies. A holistic view on the feedback loops, the consequently nonlinear behavior pattern of GCIS usage, and its diffusion in Shanghai government agencies is examined. Our research model and results suggest that workload faced by GCIS users and the tolerable maximum workload have a high impact on GCIS usage, task volume brought by GCIS, work pressure and the perception of technological factors. Different combination of work intensity and the tolerable maximum work intensity significantly influence the system usage. The contribution of our study lies in revealing that the diffusion of GCIS requires a systematic consideration of the business development plan, the GCIS user\u27s workload and the organization\u27s business environment. Flexible managerial incentive strategy will enhance user\u27s work efficiency, thus lead to effective diffusion of GCIS in organizations. The theoretical and practical implications of this study are discussed

Isolation of a nitrate-reducing bacteria strain from oil field brine and the inhibition of sulfate-reducing bacteria

A nitrate-reducing bacteria (NRB) strain with vigorous growth, strong nitrate reduction ability, strain B9 2-1, was isolated from Suizhong36-1 oilfield, its routine identification and analysis of 16S rRNA and also the competitive inhibition experiments with the enrichment of sulfate-reducing bacteria (SRB) were carried out. The results showed that only the dosing of nitrate, nitrite as electron acceptors, the activation of nitrate-reducing bacteria, as well as the inhibition of sulfide production resulted from a limited capacity, while addition of NRB isolated from the produced fluid, growth and sulfide production activity of sulfate reducing bacteria produced a significant inhibition and antibacterial effects of nitrite, which was better than nitrate. At the same time, the small amount of molybdate dosing showed better results, which will be of significance when applied to shipping and state-defending industries.Key words: Nitrate-reducing bacteria, sulfate-reducing bacteria, restriction fragment length polymorphism, nitrates, nitrite, oil field, competitive inhibition

Effects of different rhizosphere ventilation treatment on water and nutrients absorption of maize

The objective of this study was to explore the effects of different rhizosphere ventilation treatment on water and nutrients absorption of maize. The pot experiment was conducted using three methods: no ventilation, two day ventilation and four day ventilation, under conditions of the different levels of irrigation methods. As such, the influence of rhizosphere ventilation treatment on the physiological, water and nutrient absorption of maize was studied. Results showed that, with the increase inventilation frequency, plant height, leaf area and the content of chlorophyll in maize increased to a certain degree. Root activity of once in every four days ventilation was the biggest (8.237 mg/ (g·h)), followed by that of once in every two days ventilation (6.171 mg/ (g·h)), and that of no ventilation was the least (4.940 mg/ (g·h)). Consequently, it increased by 66.7 and 29.9%, respectively. The chlorophyll content experimental results showed that, rhizosphere ventilation treatment does not affect transpiration of potted maize and has no significant difference on the irrigation water utilization rate.Key words: Potted maize, rhizosphere ventilation, water, nutrients absorption, agricultural water-saving

FG-Depth: Flow-Guided Unsupervised Monocular Depth Estimation

The great potential of unsupervised monocular depth estimation has been demonstrated by many works due to low annotation cost and impressive accuracy comparable to supervised methods. To further improve the performance, recent works mainly focus on designing more complex network structures and exploiting extra supervised information, e.g., semantic segmentation. These methods optimize the models by exploiting the reconstructed relationship between the target and reference images in varying degrees. However, previous methods prove that this image reconstruction optimization is prone to get trapped in local minima. In this paper, our core idea is to guide the optimization with prior knowledge from pretrained Flow-Net. And we show that the bottleneck of unsupervised monocular depth estimation can be broken with our simple but effective framework named FG-Depth. In particular, we propose (i) a flow distillation loss to replace the typical photometric loss that limits the capacity of the model and (ii) a prior flow based mask to remove invalid pixels that bring the noise in training loss. Extensive experiments demonstrate the effectiveness of each component, and our approach achieves state-of-the-art results on both KITTI and NYU-Depth-v2 datasets.Comment: Accepted by ICRA202

Distributed joint optimization of traffic engineering and server selection

Internet service providers (ISP) apply traffic engineering (TE) in the underlay network to avoid congestion. On the other hand, content providers (CP) use different server selection (SS) strategies in the overlay network to reduce delay. It has been shown that a joint optimization of TE and SS is beneficial to the performance from both ISP's and CP's perspectives. One challenging issue in such a network is to design a distributed protocol which achieves optimality while revealing as little information as possible between ISP and CP. To address this problem, we propose a distributed protocol termed PETS, in which each router of ISP makes independent traffic engineering decision and each server of CP makes independent server selection decision. We prove that PETS can achieve optimality for the joint optimization of TE and SS. We also show that PETS can significantly reduce message passing and enables ISP to hide important underlay network information (e.g., topology) from CP. Furthermore, PETS can be easily extended to handle the case of multiple CPs in the network

Ada-DQA: Adaptive Diverse Quality-aware Feature Acquisition for Video Quality Assessment

Video quality assessment (VQA) has attracted growing attention in recent years. While the great expense of annotating large-scale VQA datasets has become the main obstacle for current deep-learning methods. To surmount the constraint of insufficient training data, in this paper, we first consider the complete range of video distribution diversity (\ie content, distortion, motion) and employ diverse pretrained models (\eg architecture, pretext task, pre-training dataset) to benefit quality representation. An Adaptive Diverse Quality-aware feature Acquisition (Ada-DQA) framework is proposed to capture desired quality-related features generated by these frozen pretrained models. By leveraging the Quality-aware Acquisition Module (QAM), the framework is able to extract more essential and relevant features to represent quality. Finally, the learned quality representation is utilized as supplementary supervisory information, along with the supervision of the labeled quality score, to guide the training of a relatively lightweight VQA model in a knowledge distillation manner, which largely reduces the computational cost during inference. Experimental results on three mainstream no-reference VQA benchmarks clearly show the superior performance of Ada-DQA in comparison with current state-of-the-art approaches without using extra training data of VQA.Comment: 10 pages, 5 figures, to appear in ACM MM 202

Synthesis, Optimization, Property, Characterization, and Application of Dialdehyde Cross-Linking Guar Gum

Dialdehyde cross-linking guar gum (DCLGG), as a novel material, was synthesized using phosphorus oxychloride as a cross-linking reagent, sodium periodate as an oxidant, and ethanol as a solvent through keeping the original particle form of guar gum. The process parameters such as the reaction temperature, reaction time, pH, amount of sodium periodate, and amount of ethanol were optimized by the response surface methodology in order to obtain the regression model of the oxidization. The covalent binding of L-asparagine onto the surfaces of DCLGG was further investigated. The results showed that the best technological conditions for preparing DCLGG were as follows: reaction temperature = 40°C, reaction time = 3.0 h, pH = 4.0, and amount of ethanol = 74.5%. The swelling power of DCLGG was intermediate between cross-linking guar gum and dialdehyde guar gum. The cross-linking and dialdehyde oxidization reduced the viscosity of GG. The cross-liking reduced the melting enthalpy of GG. However, the oxidization increased melting enthalpy of ACLGG. The thermal stability of GG was increased by cross-linking or oxidization. The variation of the onset decomposition temperature and end decomposition temperature of GG was not consistent with thermal stability of GG. L-asparagine could be chemically bound well by DCLGG through forming Schiff base under the weak acidity. The maximum adsorption capacity of L-asparagine on DCLGG with aldehyde content of 56.2% reached 21.9 mg/g