Bio-recycling of plastic waste is a promising solution to plastic pollution. As one of the most abundant plastic wastes, polyethylene terephthalate (PET) can be degraded by carboxylic ester ...hydrolases (EC 3.1.1). Nevertheless, the biological PET hydrolysis efficiency is always limited by the low activity and poor thermostability of the enzymes. Herein, to address the above barriers, we rationally mutated the relevant sites of
Thermobifida cellulosilytica
cutinase 1 (ThcCut1) involved in substrate binding. The wider substrate-binding pockets after mutation could facilitate the accessibility of the enzyme to the substrate. Divalent metal-binding sites were further predicted and substituted with disulfide bonds, with the aim of effectively improving the thermostability of the mutant ThcCut1. Coupled with sequence alignment and structural dynamics analysis, the ThcCut1-D205C/E254C/Q93G variant with a melting temperature exceeding the glass transition temperature of recycled PET was constructed. After comprehensively screening the active and thermally stable mutation sites, the resulting ThcCut1-G63A/F210I/D205C/E254C/Q93G (ThcCut1-AICCG) variant exhibited high enzymatic activity at a high temperature (70 °C). As result, 96.2% of the post-consumer PET bottle particles (without energy-intensive melt-quenching pretreatment) can be successfully degraded after 96 h of hydrolysis using ThcCut1-AICCG, which was 87.5 times higher than that using the wild-type ThcCut1. This novel strategy for amino acid site analysis will facilitate the modification of homologous cutinases to improve the catalytic performance, and provide a reliable technical method for constructing a PET hydrolase modification platform.
The enhanced enzymatic activity and thermal stability of cutinase 1 from
Thermobifida cellulosilytica
by enzyme engineering were utilized to achieve efficient degradation of post-consumer polyethylene terephthalate (PET) bottle particles.
Precipitation predictions during the flood season are critical and imperative on continents, especially in monsoon-impacted areas. However, majority of current dynamical models failed to predict the ...flood-season rainfall very well, although their simulations are high correct. In this study, based on the EOF decomposition of multi-factors field, we used a similar-error correction method to improve model prediction effect, which we call dynamic–statistic combined prediction method. Chinese Global atmosphere-ocean Coupled Model/Climate System Model was combined with dynamic–statistic combined prediction method as a case and the real-time prediction during 2009-2019 were implemented. The spatial anomaly correlation coefficient between predicted and observed values was used to assess the effectiveness of the improvement. The results show that the average anomaly correlation coefficient scores of dynamic–statistic combined prediction method (0.16) is 0.12 higher than that of Chinese Global atmosphere-ocean Coupled Model/Climate System Model (0.04), implying that dynamic–statistic combined prediction method has a broad application prospects in precipitation prediction. We suggest that dynamic–statistic combined prediction method should be promoted to other models for testing.
Emerging, flexible, textile-based supercapacitors have attracted considerable research interest in energy storage devices. However, very few flexible supercapacitors with good mechanical stability ...have been successfully developed based on traditional current collectors, especially for brittle transition metal oxides/hydroxides electrode material. This work reports a rational design of a nickel-deposited fiber fabric current collector, which displays excellent conductivity with sheet resistances of 0.355 Ω cm−2 before and 0.537 Ω cm−2 after 100,000 bending cycles. Further, a series of transition metal oxides/hydroxides were fabricated on the Ni-fabric current collector via an electrodeposition approach. The prepared Co(OH)2, NiO, and NiCo2O4 electrodes showed specific capacitances of 880.1, 589.1, and 725.7 F g−1 at 1 A g−1, respectively. In addition, when the electrodes with activated carbon (AC) were assembled into all-solid-state asymmetric supercapacitors, the as-prepared Co(OH)2//AC, NiO//AC, and NiCo2O4//AC devices delivered specific capacitances of 170.3, 265.6, and 219.8 mF cm−2, respectively, with energy densities of 1.24, 1.63, and 1.35 mWh cm−3 at 1 mA cm−2. The capacitances of these devices retained high values of 92.8%, 94.4%, and 95.1% even after 1000 cycles of bending and folding by the automatic test machine. These results indicate that metal oxide compound electrodes based on a Ni-fabric current collector provide a universal strategy for high-performance and ultra-flexible supercapacitors.
•A flexible nickel fabric current collector was fabricated by electroless deposition.•A universal strategy to deposit various materials on the nickel current collector.•The devices deliver excellent mechanical and electrochemical performance.
This study aims to classify and differentiate mucinous and serous cystic neoplasms of the pancreas using a multi-source feature classification model based on deep learning for preoperative auxiliary ...diagnosis. Deep learning features and radiomics features were extracted from segmented images using deep learning and radiomics technology, respectively. Clinical features were also evaluated and quantified. LASSO (least absolute shrinkage and selection operator) and cross-validation methods were applied to screen the features, and two multi-source feature models were constructed: the radiomics combined with deep learning (RAD_DL) model and the clinical feature combined with RAD_DL (Clinical_RAD_DL) model. Traditional radiomics (RAD) and deep learning (DL) models were used as controls. SVM (support vector machine), ADAboost (adaptive boosting), Random Forest, and Logistic were selected for classification. The Clinical_RAD_DL feature model shows the best classification performance, with the accuracy of 0.923 1, rec
An Agent-as-a-Service (AaaS)-based geospatial service aggregation is proposed to build a more efficient, robust and intelligent geospatial service system in the Cloud for flood emergency response. It ...involves an AaaS infrastructure, encompassing the mechanisms and algorithms for geospatial Web Processing Service (WPS) generation, geoprocessing and aggregation. The method has the following advantages: 1) it allows separately hosted services and data to work together, avoiding transfers of large volumes of spatial data over the network; 2) it enriches geospatial service resources in the distributed environment by utilizing the agent cloning, migration and service regeneration capabilities of the AaaS, solving issues associated with lack of geospatial services to a certain extent; 3) it enables the migration of services to target nodes to finish a task, strengthening decentralization and enhancing the robustness of geospatial service aggregation; and 4) it helps domain experts and authorities solve interdisciplinary emergency issues using various Agent-generated geospatial services.
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•Agent-as-a-Service (AaaS)-based geospatial service aggregation on the Cloud is proposed.•It allows separately-hosted services and data to work together, which avoids transferring large volume of spatial data.•It enriches geospatial service resources in the distributed environment and solves the issue of lack of geospatial services.•It strengthens decentralization and enhances robustness of the geospatial service aggregation.•It provides experts assistance in solving the interdisciplinary emergency issues with agent-generated geospatial services.
Three groups of SBR reactors A, B and C with different aeration time were set up to culture the activated sludge which has already bulked. The results showed that the settling performance of ...activated sludge in reactor A changed a little, but reactors B and C had been significantly improved. High-throughput sequencing results showed that the aeration time had a significant inhibitory effect on the growth of Thothrix, and the longer the aeration time was, the more obvious the inhibition was. When the aeration time is more than 6h, the SBR mode can effectively inhibit filamentous sludge bulking, and the longer the aeration time, the better the effect.
Metal additive manufacturing is a disruptive technology that is revolutionizing the manufacturing industry. Despite its unrivaled capability for directly fabricating metal parts with complex ...geometries, the wide realization of the technology is currently limited by microstructural defects and anomalies, which could significantly degrade the structural integrity and service performance of the product. Accurate detection, characterization, and prediction of these defects and anomalies have an important and immediate impact in manufacturing fully-dense and defect-free builds. As such, this review seeks to elucidate common defects/anomalies and their formation mechanisms in powder bed fusion additive manufacturing processes. They could arise from raw materials, processing conditions, and post-processing. While defects/anomalies in laser welding have been studied extensively, their formation and evolution remain unclear. Additionally, the existence of powder in powder bed fusion techniques may generate new types of defects, e.g., porosity transferring from powder to builds. Practical strategies to mitigate defects are also addressed through fundamental understanding of their formation. Such explorations enable the validation and calibration of models and ease the process qualification without costly trial-and-error experimentation.
In current-fed closed-loop single/three-phase DC-AC converters, precise current sampling is required for better waveform quality and smaller steady-state error. However, interferences caused by ...switching noise pose challenges to acquiring precise averaging current value. This article presents some considerations regarding precise current sampling for high-frequency single- and three-phase DC-AC converters. Current spikes caused by spurious sampling points within narrow pulses' ranges are analyzed in detail. The dynamic sampling method in every switching cycle is proposed to avoid the high-frequency oscillation caused by switching transitions. The proposed method is validated in the platform of three-phase/level SiC-based T-type converter.
Since the Open Geospatial Consortium (OGC) proposed the geospatial Web Processing Service (WPS), standard OGC Web Service (OWS)-based geospatial processing has become the major type of distributed ...geospatial application. However, improving the performance and sustainability of the distributed geospatial applications has become the dominant challenge for OWSs. This paper presents the construction of an elastic parallel OGC WPS service on a cloud-based cluster and the designs of a high-performance, cloud-based WPS service architecture, the scalability scheme of the cloud, and the algorithm of the elastic parallel geoprocessing. Experiments of the remote sensing data processing service demonstrate that our proposed method can provide a higher-performance WPS service that uses less computing resources. Our proposed method can also help institutions reduce hardware costs, raise the rate of hardware usage, and conserve energy, which is important in building green and sustainable geospatial services or applications.
Big Traffic data 1 is cross-border multi-source data for multiple industries, but traffic roads have brought significant economic and social benefits, the number of traffic accidents and casualties ...is on the rise. Among them, traffic accidents are related to many factors, such as weather and population density. The data set used in this article is open source in Barcelona. The Random Forest algorithm is used to screen essential risk factors, establish a traffic risk prediction model, and compare traffic risks before and after COVID-19. It is concluded that the outbreak of the new crown virus -19-19 has a great impact on people's travel and transportation. Finally, the R square of the model established by Random Forest is 0.9. The K-means clustering algorithm is used to determine the location of the accident handling centre. Moreover, the scope of each accident risk management centre can cover more than 85 percent of traffic accident sites from 2016 to 2020.
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