Thermokarst lakes and ponds (hereafter referred to as thaw lakes) play an important role in the permafrost regions by regulating hydrology, ecology, and biogeochemistry. However, detailed ...quantitative information on thaw lake extent and distribution remains poorly resolved across the entire permafrost regions on the Qinghai‐Tibet Plateau (QTP). Here, we applied the random forest (RF) model and manual visual vectorization methods to extract thaw lake boundaries on the QTP based on Sentinel‐2 images. Accuracy assessment was comprehensively demonstrated regarding the inherent spatial resolution of imagery and RF model performance. The results showed that the accumulated uncertainty of the total thaw lake area was ±5.75 km2, and the mean accuracy (91.9%) from field‐measured boundaries of 132 thaw lakes supported the accuracy of this inventory. A total of ∼161,300 thaw lakes with sizes ranging from 500 m2 to 3 km2 were detected, with a total area of ∼2,825.45 ± 5.75 km2. Most thaw lakes were detected in the continuous permafrost type (94.1%) and within the elevations of 4,500–5,000 m (68.4%). The small thaw lakes (<10,000 m2) predominated the total lake number (78.9%) but contributed to a small portion of the total lake area (12.7%). Spatial distributions of thaw lakes in terms of different climatic and environmental conditions were also comprehensively explored, including temperature, precipitation, ground thermal stability, active layer thickness, vegetation, soil properties, and underground ice content. This inventory is expected to be incorporated into Earth system models for a more comprehensive projection of the large‐scale biogeochemical feedback of thermokarst landforms on the QTP under continued global warming.
Plain Language Summary
Thaw lakes develop when warming soil melts ground ice, causing the surface to collapse and form pools of water. Such lakes can greatly influence local water resources and ecosystems, but also are important sources of greenhouse gas released into the atmosphere. Using Sentinel‐2 images, we provided robust information of thaw lake numbers, areas, and spatial distributions across the entire QTP permafrost regions by applying the random forest model and manual visual vectorization methods. The accuracy of the data set has been demonstrated in regard to the image spatial resolution, model performance, and field‐measured results. Within sizes ranging from 500 m2 to 3 km2, we extracted ∼161,300 thaw lakes with a total area of ∼2,825.45 ± 5.75 km2. We found that most thaw lakes were located in the continuous permafrost regions and within the elevations of 4,500–5,000 m. Most thaw lake sizes were smaller than 10,000 m2 but they only contributed to a little percentage of the total lake area. We also comprehensively explored the spatial distributions of thaw lakes in different climatic and environmental areas. This inventory would be useful for future Earth system models to predict the large‐scale biogeochemical feedback of thaw lakes on the Qinghai‐Tibet Plateau in the future.
Key Points
Using Sentinel‐2 images, we established an inventory data set of thaw lakes on the QTP via random forest model and manual postprocessing methods
Approximately 161,300 thaw lakes with sizes ranging from 500 m2 to 3 km2 were extracted, with a total area of ∼2,825.45 ± 5.75 km2
Distributions of thaw lakes were highly uneven in regard to different geospatial, climatic and environmental status
As the Internet of Things (IoT) industry grows, the risk of network protocol security threats has also increased. One protocol that has come under scrutiny for its security vulnerabilities is MQTT ...(Message Queuing Telemetry Transport), which is widely used. To address this issue, an automated execution program called fuzz has been developed to verify the security ofMQTTbrokers. This program is provided with various random and unexpected input data and monitored for different responses, such as acknowledgments, crashes, failures, or memory leaks. To generate a significant number of realistic MQTT protocols, we have proposed a Generative Adversarial Networks (GAN)-based protocol fuzzer called SGANFuzz. Our experimental results showthat SGANFuzz has successfully detected 6 vulnerabilities among 7MQTTimplementations, including 3 CVE bugs. Compared to the state-of-the-art fuzzing tools, SGANFuzz has proven to be the most efficient fuzzing tool in terms of vulnerability detection and has expanded the feedback coverage by receiving more unique network responses from MQTT brokers.
Classical simulation of quantum computation is vital for verifying quantum devices and assessing quantum algorithms. We present a new quantum circuit simulator developed on the Sunway TaihuLight ...supercomputer. Compared with other simulators, the present one is distinguished in two aspects. First, our simulator is more versatile. The simulator consists of three mutually independent parts to compute the full, partial and single amplitudes of a quantum state with different methods. It has the function of emulating the effect of noise and support more kinds of quantum operations. Second, our simulator is of high efficiency. The simulator is designed in a two-level parallel structure to be implemented efficiently on the distributed many-core Sunway TaihuLight supercomputer. Random quantum circuits can be simulated with 40, 75 and 200 qubits on the full, partial and single amplitude, respectively. As illustrative applications of the simulator, we present a quantum fast Poisson solver and an algorithm for quantum arithmetic of evaluating transcendental functions. Our simulator is expected to have broader applications in developing quantum algorithms in various fields.
A surface-based duct (SBD) is an abnormal atmospheric structure with a low probability of occurrence buta strong ability to trap electromagnetic waves. However, the existing research is based on the ...assumption that the range direction of the surface duct is homogeneous, which will lead to low productivity and large errors when applied in a real-marine environment. To alleviate these issues, we propose a framework for the inversion of inhomogeneous SBD M-profile based on a full-coupled convolutional Transformer (FCCT) deep learning network. We first designed a one-dimensional residual dilated causal convolution autoencoder to extract the feature representations from a high-dimension range direction inhomogeneous M-profile. Second, to improve efficiency and precision, we proposed a full-coupled convolutional Transformer (FCCT) that incorporated dilated causal convolutional layers to gain exponentially receptive field growth of the M-profile and help Transformer-like models improve the receptive field of each range direction inhomogeneous SBD M-profile information. We tested our proposed method performance on two sets of simulated sea clutter power data where the inversion of the simulated data reached 96.99% and 97.69%, which outperformed the existing baseline methods.
Background:
Carbon monoxide (CO) is gaining increased attention in air pollution-induced arrhythmias. The severe cardiotoxic consequences of CO urgently require effective pharmacotherapy to treat it. ...However, existing evidence demonstrates that CO can induce arrhythmias by directly affecting multiple ion channels, which is a pathway distinct from heart ischemia and has received less concern in clinical treatment.
Objective:
To evaluate the efficacy of some common clinical antiarrhythmic drugs for CO-induced arrhythmias, and to propose a potential pharmacotherapy for CO-induced arrhythmias through the virtual pathological cell and tissue models.
Methods:
Two pathological models describing CO effects on healthy and failing hearts were constructed as control baseline models. After this, we first assessed the efficacy of some common antiarrhythmic drugs like ranolazine, amiodarone, nifedipine, etc., by incorporating their ion channel-level effects into the cell model. Cellular biomarkers like action potential duration and tissue-level biomarkers such as the QT interval from pseudo-ECGs were obtained to assess the drug efficacy. In addition, we also evaluated multiple specific
I
Kr
activators in a similar way to multi-channel blocking drugs, as the
I
Kr
activator showed great potency in dealing with CO-induced pathological changes.
Results:
Simulation results showed that the tested seven antiarrhythmic drugs failed to rescue the heart from CO-induced arrhythmias in terms of the action potential and the ECG manifestation. Some of them even worsened the condition of arrhythmogenesis. In contrast,
I
Kr
activators like HW-0168 effectively alleviated the proarrhythmic effects of CO.
Conclusion:
Current antiarrhythmic drugs including the ranolazine suggested in previous studies did not achieve therapeutic effects for the cardiotoxicity of CO, and we showed that the specific
I
Kr
activator is a promising pharmacotherapy for the treatment of CO-induced arrhythmias.
Abstract
Black-box quantum state preparation is a fundamental building block for many higher-level quantum algorithms. The basic task of black-box state preparation is to transduce the data encoded ...as computational basis of quantum state into the amplitude. In the present work, we address the problem of transducing the reciprocal of the data, not the data itself into the amplitude, which is called the inverse-coefficient problem. This algorithm can be used directly as a subroutine in the matrix inversion algorithms. Furthermore, we extend this approach to address the more general nonlinear-coefficient problem in black-box state preparation. Our algorithm is based on the technique of inequality test. It can greatly relieve the need to do quantum arithmetic and the error is only resulted from the truncated error of binary string. The present algorithms enrich the algorithm library of black-box quantum state preparation and will be useful ingredients of quantum algorithm to implement non-linear quantum state transformations.
Objective
The aim of the study was to evaluate non-invasive brain stimulation (NIBS) including transcranial magnetic stimulation (TMS) and transcranial electrical stimulation (tES) on neurological ...symptoms in patients with multiple sclerosis (PwMS).
Method
We searched PubMed, Embase, Cochrane Library, Web of Science and Ovid MEDLINE until February 2022. And we evaluated the included studies for methodological quality by the Cochrane bias risk assessment tool and assessed the studies' certainty of evidence using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) framework. We performed network meta analysis (NMA) by using Stata 15 and ranked the results of the NMA by using the surface under the cumulative ranking curve (SUCRA) ranking chart.
Result
Twenty seven clinical trials were finally included (
N
= 596, 66.4% women). For the immediate effects, rTMS over M1 yielded the most optimal scheme for fatigue reduction among all the interventions compared to the sham stimulation groups MD = −0.85, 95% CI (−1.57, −0.14) (SUCRA = 82.6%). iTBS over M1 yielded the most signifcant reduced pain level than the sham groups did MD = −1.26, 95% CI (−2.40, −0.11) (SUCRA = 98.4%). tDCS over F3 was the best protocol of NIBS to improve quality of life (QOL) MD = 1.41, 95% CI = (0.45,2.36) (SUCRA = 76.7%), and iTBS over M1 may significantly reduce spasticity compared to sham stimulation MD = −1.20, 95% CI = (−1.99, −0.41) (SUCRA = 90.3%). Furthermore, rTMS, tRNS, and tDCS on certain areas may improve PwMS accuracy, response time, manual dexterity, pain relief and QOL, but does not show statistically significant differences. The evidence assessed using GRADE is very low.
Conclusion
Based on the NMA and SUCRA ranking, we can conclude that symptoms including fatigue, pain, spasticity, and QOL can be improved by following NIBS protocol after treatment. Nonetheless, most of the included studies lack a good methodology, and more high-quality randomized clinical trials are needed.
NiO nanoparticles with average particle size of 25 nm were successfully prepared by anodic arc plasma method. The composition, morphology, crystal microstructure, specific surface area, infrared ...spectra, and particle size distribution of product were analyzed by using X-ray diffraction (XRD), transmission electron microscopy (TEM) and the corresponding selected area electron diffraction (SAED), Fourier transform infrared (FTIR) spectrum, and Brunauer-Emmett-Teller (BET) N2 adsorption. The experiment results show that the NiO nanoparticles are bcc structure with spherical shape and well dispersed, the particle size distribution ranging from 15 to 45 nm with the average particle size is about 25 nm, and the specific surface area is 33 m2/g. The infrared absorption band of NiO nanoparticles shows blue shifts compared with that of bulk NiO.
Modified Benney-Luke equation (mBL equation) is a three-dimensional temporal-spatial equation with complex structures, that is a high-dimensional partial differential equation (PDE), it is also a new ...equation of the physical ocean field, and its solution is important for studying the internal wave-wave interaction of inclined seafloor. For conventional PDE solvers such as the pseudo-spectral method, it is difficult to solve mBL equation with both accuracy and speed. Physics-informed neural network (PINN) incorporates physical prior knowledge in deep neural networks, which can solve PDE with relative accuracy and speed. However, PINN is only suitable for solving low-dimensional PDE with simple structures, and not suitable for solving high-dimensional PDE with complex structures. This is mainly because high-dimensional PDEs usually have complex structures and high-order derivatives and are likely to be high-dimensional non-convex functions, and the high-dimensional non-convex optimization problem is an NP-hard problem, resulting in the PINN easily falling into inaccurate local optimal solutions when solving high-dimensional PDEs. Therefore, we improve the PINN for the characteristics of mBL equation and propose “DF-ParPINN: parallel PINN based on velocity potential field division and single time slice focus” to solve mBL equation with large amounts of data. DF-ParPINN consists of three modules: temporal-spatial division module of overall velocity potential field, data rational selection module of multiple time slices, and parallel computation module of high-velocity fields and low-velocity fields. The experimental results show that the solution time of DF-ParPINN is no more than 0.5s, and its accuracy is much higher than that of PINN, PIRNN, cPINN, and DeepONet. Moreover, the relative error of DF-ParPINN after deep training 1000000 epochs can be reduced to less than 0.1. The validity of DF-ParPINN proves that the improved PINN also can solve high dimensional PDE with complex structures and large amounts of data quickly and accurately, which is of great significance to the deep learning of the physical ocean field.
Monochamus alternatus is an important insect pest in pine forests of southern China and the dispersing vector of the pine wood nematode, Bursaphelenchus xylophilus, which leads to pine wilt disease ...(PWD). Microbiome of M. alternatus may contribute to survival of larvae in the host pine trees. In order to investigate the intestinal bacterial structure of M. alternatus during the larvae and pupae stages in host trees, and infer the function of symbiotic bacteria, we used 16S rRNA gene Illumina sequencing to obtain and compare the bacterial community composition in the foregut, midgut, and hindgut of larvae, pupal intestines, larval galleries, and pupal chambers of M. alternatus. The diversity of the bacterial community in larval intestines and pupal intestines were similar, as well as was significantly greater in larval galleries and pupal chambers. Although there were differences in bacterial compositions in different samples, similar components were also found. Proteobacteria and Firmicutes were the two most dominant phyla in all samples, and genera Enterobacter, Raoultella, Serratia, Lactococcus, and Pseudomonas were dominant in both the intestinal samples and plant tissue samples. Enterobacter was the most abundant genus in larval intestines, and Serratia was dominant in pupal intestine. The functions of these dominant and specific bacteria were also predicted through metagenomic analyses. These bacteria may help M. alternatus degrade cellulose and pinene. The specific role of symbiotic bacteria in the infection cycle of PWD also warrants further study in the future.
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