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2022 ◽  
Vol 30 (6) ◽  
pp. 0-0

Empirical studies have shown that China's Air Pollution Prevention and Control Law (APPCL2000), as an environmental regulation, has significantly alleviated the air pollution problem and improved the TFP of air polluting enterprises. However, few scholars have studied the regional heterogeneity of this policy. To study this issue, this manuscript introduces the "Hu Line" from the perspective of regional resource endowment differences and divides China into a resource advantage area (A area) and a resource disadvantage area (B area). Subsequently, this manuscript uses the triple difference model and big data of Chinese industrial enterprises to verify. The results show that under environmental regulations, the TFP of air polluting enterprises in B area has increased more than in A area, and the rapid decline in the proportion of low-efficiency air polluting enterprises in B area is the main mechanism. It shows that environmental regulation is beneficial to narrow the gap of regional economic growth and realize economic catch-up in resource-disadvantaged areas.

2022 ◽  
Vol 2022 ◽  
pp. 1-11
Chunqiao Song ◽  
Xutong Wu

At present, image restoration has become a research hotspot in computer vision. The purpose of digital image restoration is to restore the lost information of the image or remove redundant objects without destroying the integrity and visual effects of the image. The operation of user interactive color migration is troublesome, resulting in low efficiency. And, when there are many kinds of colors, it is prone to errors. In response to these problems, this paper proposes automatic selection of sample color migration. Considering that the respective gray-scale histograms of the visual source image and the target image are approximately normal distributions, this paper takes the peak point as the mean value of the normal distribution to construct the objective function. We find all the required partitions according to the user’s needs and use the center points in these partitions as the initial clustering centers of the fuzzy C-means (FCM) algorithm to complete the automatic clustering of the two images. This paper selects representative pixels as sample blocks to realize automatic matching of sample blocks in the two images and complete the color migration of the entire image. We introduced the curvature into the energy functional of the p-harmonic model. According to whether there is noise in the image, a new wavelet domain image restoration model is proposed. According to the established model, the Euler–Lagrange equation is derived by the variational method, the corresponding diffusion equation is established, and the model is analyzed and numerically solved in detail to obtain the restored image. The results show that the combination of image sample texture synthesis and segmentation matching method used in this paper can effectively solve the problem of color unevenness. This not only saves the time for mural restoration but also improves the quality of murals, thereby achieving more realistic visual effects and connectivity.

2022 ◽  
Arjun Gupta ◽  
Sangeeta Agrawal

Globally, nearly a million plastic bottles are produced every minute (1). These non-biodegradable plastic products are composed of Polyethylene terephthalate (PET). In 2016, researchers discovered PETase, an enzyme from the bacteria Ideonella sakaiensis which breaks down PET and nonbiodegradable plastic. However, PETase has low efficiency at high temperatures. In this project, we optimized the rate of PET degradation by PETase by designing new mutant enzymes which could break down PET much faster than PETase, which is currently the gold standard. We used machine learning (ML) guided directed evolution to modify the PETase enzyme to have a higher optimal temperature (Topt), which would allow the enzyme to degrade PET more efficiently. First, we trained three machine learning models to predict Topt with high performance, including Logistic Regression, Linear Regression and Random Forest. We then used Random Forest to perform ML-guided directed evolution. Our algorithm generated hundreds of mutants of PETase and screened them using Random Forest to select mutants with the highest Topt, and then used the top mutants as the enzyme being mutated. After 1000 iterations, we produced a new mutant of PETase with Topt of 71.38℃. We also produced a new mutant enzyme after 29 iterations with Topt of 61.3℃. To ensure these mutant enzymes would remain stable, we predicted their melting temperatures using an external predictor and found the 29-iteration mutant had improved thermostability over PETase. Our research is significant because using our approach and algorithm, scientists can optimize additional enzymes for improved efficiency.

2022 ◽  
Vol 14 (2) ◽  
pp. 795
Shaojun Ma ◽  
Lei Li ◽  
Huimin Ke ◽  
Yilin Zheng

The Beijing–Tianjin–Hebei urban agglomeration (BTH) is striving to realize the transformation process from a low-efficiency to a high-quality development mode; however, it still has problems regarding reducing energy consumption and ecological environment pressure. Based on panel data from 2013 to 2017, this paper proposes an evaluation index system based on BTH’s “environmental protection–industrial structure–urbanization” system. In the course of applying the coupling degree model (CDM) and the coupling coordination degree model (CCDM) with exploratory spatial data analysis (ESDA) methods, this paper discusses the spatiotemporal process, development level, and spatial agglomeration characteristics of the environmental protection–industrial structure–urbanization system in each city of the BTH area. The findings reveal that the coupling degree of the BTH system is gradually increasing, and that the development level of the BTH subsystem is unbalanced: the coupling coordination level of BTH shows a positive evolution process; however, it is in a stage of low-level collaborative development, and there are obvious differences in the level of BTH coupling coordination in space, revealing the convergence of low–high and high–low types. This paper concludes by putting forward the strategy of optimizing the regional spatial pattern of urban agglomeration and implementing integrated development in order to achieve the desired coupling and coordination effects.

2022 ◽  
Vol 2022 ◽  
pp. 1-14
Liming Li ◽  
Shubin Zheng ◽  
Chenxi Wang ◽  
Shuguang Zhao ◽  
Xiaodong Chai ◽  

This work presents a new method for sleeper crack identification based on cascade convolutional neural network (CNN) to address the problem of low efficiency and poor accuracy in the traditional detection method of sleeper crack identification. The proposed algorithm mainly includes improved You Only Look Once version 3 (YOLOv3) and the crack recognition network, where the crack recognition network includes two modules, the crack encoder-decoder network (CEDNet) and the crack residual refinement network (CRRNet). The improved YOLOv3 network is used to identify and locate cracks on sleepers and segment them after the sleeper on the ballast bed is extracted by using the gray projection method. The sleeper is inputted into CEDNet for crack feature extraction to predict the coarse crack saliency map. The prediction graph is inputted into CRRNet to improve its edge information and local region to achieve optimization. The accuracy of the crack identification model is improved by using a mixed loss function of binary cross-entropy (BCE), structural similarity index measure (SSIM), and intersection over union (IOU). Results show that this method can accurately detect the sleeper crack image. During object detection, the proposed method is compared with YOLOv3 in terms of directly locating sleeper cracks. It has an accuracy of 96.3%, a recall rate of 91.2%, a mean average precision (mAP) of 91.5%, and frames per second (FPS) of 76.6/s. In the crack extraction part, the F-weighted is 0.831, mean absolute error (MAE) is 0.0157, and area under the curve (AUC) is 0.9453. The proposed method has better recognition, higher efficiency, and robustness compared with the other network models.

2022 ◽  
Vol 2022 ◽  
pp. 1-10
Wanxia Zhang ◽  
Bo Liu ◽  
Sang-Bing Tsai

Digital reading promotion service is a service way for libraries to provide readers with a series of digital resources, enjoy the service functions, and share the experience of using them in various digital reading platforms, which is to meet the reading interests and reading needs of more readers, and is also the focus of the current library work. In the era of new media, the characteristics of digital reading are subtly changing the readers’ needs for reading environment, reading content, and reading style. Libraries should keep pace with the development of the times and provide readers with diversified, intelligent, and targeted digital reading platforms. The digital reading platform should continuously improve the digital reading service functions, broaden the service scope and dissemination channels, and finally realize the diversification, interest, and intelligence of digital reading service. This paper takes the digital reading platform of libraries in the region as the research theme and carries out research work on libraries. The province is divided into three regions according to the geographical map: southeastern region, central region, and northwestern region. The digital reading platforms of 14 prefecture-level public libraries and 58 libraries of higher education institutions in each region were accessed. Firstly, we check the construction of digital resources within the library websites, secondly, we count the opening of digital reading platform functions, and finally, we check the opening of digital reading platforms. Through the research, it is found that there are problems of unbalanced distribution of digital reading resources in regional libraries; unattractive design of readers’ interface and inadequate reading service functions; lack of continuous training of readers’ guidance; insufficient publicity and promotion; low efficiency of staff in responding to consultation; and low degree of platform openness and weak awareness of sharing. Finally, the problems found in the research are summarized, and the solution measures for the regional digital reading platform are proposed. Libraries in the digital era should give priority to systems that can manage all library resources comprehensively and effectively, adapt to more flexible library workflows, and enable libraries to provide better services to users.

2022 ◽  
Vol 12 (1) ◽  
Muhammad Ramzan ◽  
Nazia Shahmir ◽  
Hassan Ali S. Ghazwani ◽  
Kottakkaran Sooppy Nisar ◽  
Faizah M. Alharbi ◽  

AbstractSolar thermal systems have low efficiency due to the working fluid's weak thermophysical characteristics. Thermo-physical characteristics of base fluid depend on particle concentration, diameter, and shapes. To assess a nanofluid's thermal performance in a solar collector, it is important to first understand the thermophysical changes that occur when nanoparticles are introduced to the base fluid. The aim of this study is, therefore, to analyze the hydrodynamic and heat characteristics of two different water-based hybrid nanofluids (used as a solar energy absorber) with varied particle shapes in a porous medium. As the heat transfer surface is exposed to the surrounding environment, the convective boundary condition is employed. Additionally, the flow of nanoliquid between two plates (in parallel) is observed influenced by velocity slip, non-uniform heat source-sink, linear thermal radiation. To make two targeted hybrid nanofluids, graphene is added as a cylindrical particle to water to make a nanofluid, and then silver is added as a platelet particle to the graphene/water nanofluid. For the second hybrid nanofluid, CuO spherical shape particles are introduced to the graphene/water nanofluid. The entropy of the system is also assessed. The Tiwari-Das nanofluid model is used. The translated mathematical formulations are then solved numerically. The physical and graphical behavior of significant parameters is studied.

Catalysts ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. 70
Barouch Giechaskiel ◽  
Anastasios Melas ◽  
Victor Valverde ◽  
Marcos Otura ◽  
Giorgio Martini

The emission limit of non-volatile particles (i.e., particles that do not evaporate at 350 °C) with size >23 nm, in combination with the real driving emissions (RDE) regulation in 2017, resulted in the introduction of gasoline particulate filters (GPFs) in all light-duty vehicles with gasoline direct injection engines in Europe. Even though there are studies that have examined the particulate emissions at or beyond the current RDE boundary conditions, there is a lack of studies combining most or all worst cases (i.e., conditions that increase the emissions). In this study, we challenged a fresh (i.e., no accumulation of soot or ash) “advanced” prototype GPF at different temperatures (down to −9 °C), aggressive drive cycles and hard accelerations (beyond the RDE limits), high payload (up to 90%), use of all auxiliaries (air conditioning, heating of the seats and the rear window), and cold starts independently or simultaneously. Under hot engine conditions, the increase of the particulate emissions due to higher payload and lower ambient temperature was 30–90%. The cold start at low ambient temperature, however, had an effect on the emissions of up to a factor of 20 for particles >23 nm or 300 when considering particles <23 nm. We proposed that the reason for these high emissions was the incomplete combustion and the low efficiency of the three-way oxidation catalyst. This resulted in a high concentration of species that were in the gaseous phase at the high temperature of the close-coupled GPF and thus could not be filtered by the GPF. As the exhaust gas cooled down, these precursor species formed particles that could not be evaporated at 350 °C (the temperature of the particle number system). These results highlight the importance of the proper calibration of the engine out emissions at all conditions, even when a GPF is installed.

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