Effect of Land Use and Climate Change on Runoff in the Dongjiang Basin of South China

Variability and availability of water resources under changing environment in a regional scale have been hot topics in recent years, due to the vulnerability of water resources associated with social and economic development. In this paper, four subbasins in the Dongjiang basin with a significant land use change were selected as case study. Runoffs of the four subbasins were simulated using the SCS monthly model to identify the quantitative impacts of land use and climate change. The results showed that (1), in the Dongjiang basin, temperature increased significantly, evaporation and sunlight decreased strongly, while precipitation showed a nonsignificant increase; (2) since the 1980s, land uses in the Dongjiang basin have experienced a significant change with a prominent increase in urban areas, a moderate increase in farmlands, and a great decrease in forest areas; (3) the SCS monthly model performed well in the four subbasins giving that the more significant land use change in each subbasin, the more runoff change correspondingly; (4) overall, runoff change was contributed half and half by climate change and human activities, respectively, in all the subbasins, in which about 20%~30% change was contributed by land use change

Numerical investigation of seismic behaviour of railway embankments in cold regions

U ovom radu provedene su iscrpne rasprave i analize primjenom numeričkih tehnika, a s ciljem da se posve ispita seizmičko ponašanje željezničkog nasipa Qinghai-Tibet. Točnije, provedena je analiza jednodimenzionalnog ekvivalentnog linearnog odziva tla u područjima permafrosta. Na temelju toga, seizmički odziv tipičnog željezničkog nasipa dalje se ispitao nelinearnim dinamičkim proračunom metodom konačnih elemenata. To je rezultiralo određivanjem nelinearnog ponašanja tla na području permafrosta (stalno smrznuto tlo), a raspravljalo se o dinamičkom ubrzanju, brzini i pomaku nasipa te se predvidjela približna kvantitativna ocjena. Rezultati upućuju na to da dinamički odziv nasipa ima izrazito nelinearna svojstva. Koeficijent vršnog ubrzanja tla na kruni nasipa veći je nego na prirodnoj površini tla, a označava povećanje od 73 % u odnosu na koeficijent na prirodnoj površini tla. Kada seizmički intenzitet postigne određenu vrijednost, područje plastičnosti postupno se pojavljivalo na nasipu, a postoji i kontinuirano proširenje područja plastičnosti koje je povezano s povećanjem vršnog ubrzanja ulaznog seizmičkog vala. Rezultati istraživanja mogu dati uvide i imati značajne implikacije za daljnje istraživanje hladnih područja.To investigate more fully seismic behaviour of the Qinghai-Tibet railway embankment, a comprehensive discussion and a781nalysis is conducted in this paper by applying a numerical technique. Specifically, the one dimensional equivalent linear ground response analysis was conducted in permafrost regions. On this basis, the seismic response of a typical railway embankment was further studied by applying the nonlinear dynamic finite element analysis method. As a result, nonlinear behaviour of permafrost sites was determined, and the dynamic acceleration, velocity and displacement of the embankment was discussed and the quantitative assessment was approximately estimated. The results indicate that the dynamic response of the embankment has distinct nonlinear characteristics. The peak ground acceleration coefficient at the embankment shoulder is larger than the natural ground surface, marking a 73% increase compared to the coefficient on the natural ground surface. When the seismic intensity reaches a certain value, a plastic zone gradually appears in the embankment, and a continuous extension of the plastic zone can be noted with an increase in peak acceleration of the input seismic wave. The findings of this research may provide an additional insight and have significant implications for further research of cold regions

A Tile-Based EGPU with a Fused Universal Processing Engine and Graphics Coprocessor Cluster

As various applied sensors have been integrated into embedded devices, the Embedded Graphics Processing Unit (EGPU) has assumed more processing tasks, which requires an EGPU with higher performance. A tile-based EGPU is proposed that can be used in both general-purpose computing and 3D graphics rendering. With fused, scalable, and hierarchical parallelism architecture, the EGPU has the ability to address nearly 100 million vertices or fragments and achieves 1 GFLOPS per second at a clock frequency of 200 MHz. A fused and scalable architecture, constituted by Universal Processing Engine (UPE) and Graphics Coprocessor Cluster (GCC), ensures that the EGPU can adapt to various graphic processing scenes and situations, achieving more efficient rendering. Moreover, hierarchical parallelism is implemented via the UPE. Additionally, tiling brings a significant reduction in both system memory bandwidth and power consumption. A 0.18 µm technology library is used for timing and power analysis. The area of the proposed EGPU is 6.5 mm ∗ 6.5 mm, and its power consumption is approximately 349.318 mW. Experimental results demonstrate that the proposed EGPU can be used in a System on Chip (SoC) configuration connected to sensors to accelerate its processing and create a proper balance between performance and cost

Heat shock proteins in stabilization of spontaneously restored sinus rhythm in permanent atrial fibrillation patients after mitral valve surgery

A spontaneously restored sinus rhythm in permanent atrial fibrillation patients has been often observed after mitral valve (MV) surgery, but persisting duration in sinus rhythm varies from patient to patient. Heat shock proteins (Hsps) may be involved in pathogenesis of atrial fibrillation. We hypothesized that stabilization of restored sinus rhythm is associated with expression of Hsps in the atria. To test this hypothesis, clinical data, biopsies of right atrial appendage, and blood samples were collected from 135 atrial fibrillation patients who spontaneously restored sinus rhythm after conventional isolated MV replacement. Comparison was made between patients who had recurrence of atrial fibrillation within 7 days (AF) vs. patients with persisted sinus rhythm for more than 7 days (SR). Results showed that SR patients had higher activity of heat shock transcription factor 1 (HSF1) as well as upregulated expressions of heat shock cognate 70, Hsp70, and Hsp27 in the tissues. The activation of HSF1–Hsps pathway was associated with less-aggressive pathogenesis as reflected by lower rates of myolysis, apoptosis, interstitial fibrosis, and inflammation in SR patients. However, Hsp60 was lower in both tissue and plasma in SR patients, and was positively correlated with apoptosis, interstitial fibrosis, and inflammation. These findings suggest that the Hsps play important roles in stabilization of restored sinus rhythm after MV surgery by inhibiting AF-related atrial remodeling and arrhythmogenic substrates in atrial fibrillation patients. Low circulating Hsp60 levels preoperatively might predict a stable spontaneously restored sinus rhythm postoperatively

Accurate Fish Detection under Marine Background Noise Based on the Retinex Enhancement Algorithm and CNN

Underwater detection equipment with fish detection technology has broad application prospects in marine fishery resources exploration and conservation. In this paper, we establish a multi-scale retinex enhancement algorithm and a multi-scale feature-based fish detection model to improve underwater detection accuracy and ensure real-time performance. During image preprocessing, the enhancement algorithm combines the bionic structure of the fish retina and classical retinex theory to filter out underwater environmental noise. The detection model focuses on improving the detection performance on small-size targets using a deep learning method based on a convolutional neural network. We compare our method to current mainstream detection models (Faster R-CNN, RetinaNet, YOLO, SSDetc.), and the proposed model achieves better performance, with a mean Average Precision (mAP) of 78.31% and a mean Miss Rate (mMR) of 54.11% in the open fish image data set. The test results for the data from the field experiment prove the feasibility and stability of our model

Novel Online Optimized Control for Underwater Pipe-Cleaning Robots

Due to the particularity of the jacket structure of offshore platforms and the complexity of the marine environment, there have been few effective localization and autonomous control methods for underwater robots that are designed for cleaning tasks. To improve this situation, a fusion bat algorithm (BA) online optimized fuzzy control method using vision localization was developed based on the constraints of the underwater operational environment. Vision localization was achieved based on images from a catadioptric panoramic imaging system. The features of the pipe edge and the boundary of the area covered by biofouling were obtained by image processing and feature extraction. The feature point chosen as the “highest” point of the boundary was calculated by projection transformation to generate the reference path. The specialized fuzzy controller was designed to drive the robot to track the reference path, and an improved bat algorithm with dynamic inertia weight and differential evolution method was developed to optimize the scale factors of the fuzzy controller online. The control method was simulated and further implemented on an underwater pipe-cleaning robot (UPCR), and the results indicate its rationality and validity

Organic Compounds as Corrosion Inhibitors for Carbon Steel in HCl Solution: A Comprehensive Review

Most studies on the corrosion inhibition performance of organic molecules and (nano)materials were conducted within “carbon steel/1.0 M HCl” solution system using similar experimental and theoretical methods. As such, the numerous research findings in this system are sufficient to conduct comparative studies to select the best-suited inhibitor type that generally refers to a type of inhibitor with low concentration/high inhibition efficiency, nontoxic properties, and a simple and cost-economic synthesis process. Before data collection, to help readers have a clear understanding of some crucial elements for the evaluation of corrosion inhibition performance, we introduced the mainstay of corrosion inhibitors studies involved, including the corrosion and inhibition mechanism of carbon steel/HCl solution systems, evaluation methods of corrosion inhibition efficiency, adsorption isotherm models, adsorption thermodynamic parameters QC calculations, MD/MC simulations, and the main characterization techniques used. In the classification and statistical analysis section, organic compounds or (nano)materials as corrosion inhibitors were classified into six types according to their molecular structural characteristics, molecular size, and compound source, including drug molecules, ionic liquids, surfactants, plant extracts, polymers, and polymeric nanoparticles. We outlined the important conclusions obtained from recent literature and listed the evaluation methods, characterization techniques, and contrastable experimental data of these types of inhibitors when used for carbon steel corrosion in 1.0 M HCl solution. Finally, statistical analysis was only performed based on these data from carbon steel/1.0 M HCl solution system, from which some conclusions can contribute to reducing the workload of the acquisition of useful information and provide some reference directions for the development of new corrosion inhibitors

Accurate Fish Detection under Marine Background Noise Based on the Retinex Enhancement Algorithm and CNN

Underwater detection equipment with fish detection technology has broad application prospects in marine fishery resources exploration and conservation. In this paper, we establish a multi-scale retinex enhancement algorithm and a multi-scale feature-based fish detection model to improve underwater detection accuracy and ensure real-time performance. During image preprocessing, the enhancement algorithm combines the bionic structure of the fish retina and classical retinex theory to filter out underwater environmental noise. The detection model focuses on improving the detection performance on small-size targets using a deep learning method based on a convolutional neural network. We compare our method to current mainstream detection models (Faster R-CNN, RetinaNet, YOLO, SSDetc.), and the proposed model achieves better performance, with a mean Average Precision (mAP) of 78.31% and a mean Miss Rate (mMR) of 54.11% in the open fish image data set. The test results for the data from the field experiment prove the feasibility and stability of our model