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Energy efficiency is essential in electric autonomous driving systems, particularly within the framework of smart grid (SG) and vehicle-to-grid (V2G) interactions. However, prior studies have rarely examined energy consumption during lane changes, especially with respect to different driving styles. This study addresses this gap by incorporating driving style variables and employing a quintic polynomial lane-change trajectory model, optimized through Sequential Quadratic Programming (SQP) and the Lagrange multiplier method, to assess energy consumption during lane changes. Additionally, a driving style recognition model categorizes driving behaviors as aggressive, normal, or conservative. The study considers factors such as lane-change duration, speed, and trajectory coefficients to analyze the impact of driving styles on energy usage. Results demonstrate that varying lane-change styles significantly affect energy consumption. These findings offer new perspectives for optimizing the energy efficiency of electric autonomous vehicles within SG environments, supporting the development of adaptive, energy-saving driving strategies and contributing to the advancement of smart grid-connected autonomous electric vehicle systems.

The spatial–temporal sampling errors arising from the differences in geographical locations and measurement times between co-located Global Navigation Satellite System (GNSS) radio occultation (RO) and radiosonde (RS) data represent systematic errors in the three-cornered hat (3CH) method. In this study, we propose a novel spatial–temporal sampling correction method to mitigate the sampling errors associated with both RO–RS and RS–model pairs. We analyze the 3CH processing chain with this new correction method in comparison to traditional approaches, utilizing Fengyun-3E (FY-3E) GNSS Occultation Sounder II (GNOS II) RO data, atmospheric models, and RS datasets from the Hailar and Xisha stations. Overall, the results demonstrate that the improved 3CH method performs better in terms of spatial–temporal sampling errors and the variances of atmospheric parameters, including refractivity, temperature, and specific humidity. Subsequently, we assess the error variances of the FY-3E GNOS II RO, RS and model atmospheric parameters in China, in particular the northern China and southern China regions, based on large ensemble datasets using the improved 3CH data processing chain. The results indicate that the FY-3E GNOS II BeiDou navigation satellite system (BDS) RO and Global Positioning System (GPS) RO show good consistency, with the average error variances of refractivity, temperature, and specific humidity being less than 1.12%2, 0.13%2, and 700%2, respectively. A comparison of the datasets from northern and southern China reveals that the error variances for refractivity are smaller in northern China, while temperature and specific humidity exhibit smaller error variances in southern China, which is attributable to the differing climatic conditions.

Two different Global Navigation Satellite System (GNSS) Reflectometry wind products are to be developed for the Global Navigation Satellite System Occultation Sounder II (GNOS-II) payload on the FengYun-3E (FY-3E) satellite: A global wind product optimized for global low-to-medium wind speeds and a cyclone wind product optimized for high wind speeds in the tropical and extratropical cyclones. This article presents a comprehensive assessment of the GNOS-II global wind product for both global positioning system (GPS) and Beidou (BDS) product at wind speeds below 25 m/s using its data of first six months. Three datasets, including the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis, HY-2B scatterometer and Soil Moisture Active Passive (SMAP) winds, are used for the assessment. The assessment of the Level 1 observables shows that the instrument's performance and calibration are generally stable. For the assessment of retrieved winds, the general performances of GPS and BDS products are similar. The overall wind speed root-mean-square error is 1.54 m/s for GPS-R and 1.44 m/s for BDS-R when compared with ECMWF, 1.48 m/s for GPS-R and 1.36 m/s for BDS-R when compared with HY-2B, and 2.08 m/s for GPS-R and 2.04 m/s for BDS-R when compared with SMAP. The overall wind speed biases for GPS-R and BDS-R are about zeros when compared with each dataset. The assessment is also made by the dependence on time, signal-to-noise ratio, observable, GNSS block, wind speed, incidence angle, and geography. Overall, the FY-3E GNOS-II global wind product is consistent over time and space with an accuracy meeting the requirement of operational use.

The FengYun-3E Global Navigation Satellite System (GNSS) occultation sounder II (FY-3E GNOS II) was launched on 5 July 2021. For the first time, based on the new GNOS II sensor, this mission realizes radio occultation (RO) and reflectometry observations using the navigation signals from the third-generation BeiDou System (BDS-3), and it is hence important to assess and analyze the BDS-3 remote sensing performances relative to other systems. Here, we assessed FY-3E GNOS II RO atmospheric retrievals by inter-comparing with corresponding data from the NCEP FNL global atmospheric analysis and FY-3D GNOS mission. The GNOS RO data quality and consistency of the different FY-3 meteorological satellites, i.e., FY-3D and FY-3E, as well as different GNSS systems (GPS, BDS-2, BDS-3) were analyzed. We find that the FY-3E GNOS II RO data exhibit better quality than FY-3D GNOS, particularly in the number, penetration height toward surface, and global coverage by BDS RO profiles, due to the integration of BDS-2 and BDS-3. Additionally, comparing with co-located NCEP FNL analysis profiles, the mean difference (and standard deviation) of the FY-3E GNOS II RO atmospheric refractivity profile retrievals is found to be smaller than 0.2% (and 1%), in the upper troposphere and lower stratosphere, from 5 to 30 km, and remains consistent at this accuracy and precision level with the FY-3D GNOS RO data. These features provide clear evidence for a high utility of the new GNOS II RO data for weather and climate research and applications.

Semantic segmentation is a critical task in computer vision that aims to assign each pixel in an image a corresponding label on the basis of its semantic content. This task is commonly referred to as dense labeling because it requires pixel-level classification of the image. The research area of semantic segmentation is vast and has achieved critical advances in recent years. Deep learning architectures in particular have shown remarkable performance in generating high-level, hierarchical, and semantic features from images. Among these architectures, convolutional neural networks have been widely used to address semantic segmentation problems. This work aims to review and analyze recent technological developments in image semantic segmentation. It provides an overview of traditional and deep-learning-based approaches and analyzes their structural characteristics, strengths, and limitations. Specifically, it focuses on technical developments in deep-learning-based 2D semantic segmentation methods proposed over the past decade and discusses current challenges in semantic segmentation. The future development direction of semantic segmentation and the potential research areas that need further exploration are also examined.

Fengyun-3C (FY-3C) is the first Chinese satellite that is capable of using the Radio Occultation (RO) technique to retrieve atmospheric profiles. This research evaluates the quality of FY-3C RO profiles including refractivity, temperature, and specific humidity by comparing with corresponding information from the European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Reanalysis (ERA-Interim) data over the period of 2015–2018. The evaluation is carried out by calculating and analyzing mean systematic differences between FY-3C and ERA-Interim profiles and corresponding standard deviations over a selected spatial and temporal domain. Results show that the FY-3C RO profiles are overall with good agreements with the ERA-Interim data. Global mean refractivity systematic differences are within ±0.2% from 5 to 30 km altitude range with relative standard deviations of less than 2%. Global temperature mean systematic differences vary within ±0.2 K from a 10- to 20-km altitude range with standard deviations of less than 2 K. Global mean specific humidity differences are found to be within ±0.2 g/kg from 2 to 20 km with standard deviations of less than 1 g/kg. FY-3C profiles show visible latitudinal and altitudinal variations, while the seasonal variations are minor. Sampling errors of refractivity and temperature are also found to be larger at higher latitudinal regions due to RO events being less sampled in the polar region.

With the accumulation of the ionospheric radio occultation (IRO) data observed by Global Navigation Satellite System (GNSS) occultation sounder (GNOS) onboard FengYun-3C (FY3C) satellite, it is possible to use GNOS IRO data for ionospheric climatology research. Therefore, this work aims to validate the feasibility of FY3C/GNOS IRO products in climatology research by comparison with that of Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC), laying the foundation for its application in climatology study. Since previous verification works of FY3C/GNOS were done by comparison with ionosondes, this work matched NmF2/hmF2 of FY3C/GNOS and COSMIC into data pairs to verify the profile-level accuracy of FY3C/GNOS IRO data. The statistical results show that the overall correlation coefficients of both NmF2 and hmF2 are above 0.9, the overall bias and std of NmF2 differences between FY3C/GNOS and COSMIC are −2.19% and 17.48%, respectively, and the bias and std of hmF2 differences are −3.29 and 18.01 km, respectively, indicating a high profile-level precision consistency between FY3C/GNOS and COSMIC. In ionospheric climatology comparison, we divided NmF2/hmF2 of FY3C/GNOS into four seasons, then presented the season median NmF2/hmF2 in 5° × 10° grids and compared them with that of COSMIC. The results show that the ionospheric climatological characteristics of FY3C/GNOS and COSMIC are highly matched, both showing the typical climatological features such as equatorial ionosphere anomaly (EIA), winter anomaly, semiannual anomaly, Weddell Sea anomaly (WSA) and so on, though minor discrepancies do exist like the differences in magnitude of longitude peak structures and WSA, which verifies the reliability of FY3C/GNOS IRO products in ionospheric climatology research.

The Chinese radio occultation sounder GNOS (Global Navigation Occultation Sounder) is on the FY-3C satellite, which was launched on September 23, 2013. Currently, GNOS data is transmitted via the Global Telecommunications System (GTS) providing 450–500 profiles per day for numerical weather prediction applications. This paper describes the processing for the GNOS profiles with large biases, related to L2 signal degradation. A new extrapolation procedure in bending angle space corrects the L2 bending angles, using a thin ionosphere model, and the fitting relationship between L1 and L2. We apply the approach to improve the L2 extrapolation of GNOS. The new method can effectively eliminate about 90% of the large departures. In addition to the procedure for the L2 degradation, this paper also describes our quality control (QC) for FY-3C/GNOS. A noise estimate for the new L2 extrapolation can be used as a QC parameter to evaluate the performance of the extrapolation. Mean phase delays of L1 and L2 in the tangent height interval of 60 to 80km are analysed and applied in the QC as well. A statistical comparison between GNOS and ECMWF (European Centre for Medium-Range Weather Forecasts) forecast data demonstrates that GNOS performs almost as well as GRAS, especially in the core region from around 10 to 35km. The GNOS data with the new L2 extrapolation is suitable for assimilation into numerical weather prediction systems. [ABSTRACT FROM AUTHOR]

The Global Navigation Satellite System (GNSS) occultation sounder (GNOS) is one of the new generation payloads onboard the Chinese FengYun 3 (FY-3) series of operational meteorological satellites for sounding the Earth's neutral atmosphere and ionosphere. FY-3C GNOS, onboard the FY-3 satellite C launched in September 2013, was designed for acquiring setting and rising radio occultation (RO) data by using GNSS signals from both the Chinese BeiDou System (BDS) and the U.S. Global Positioning System (GPS). So far, the GNOS measurements and atmospheric and ionospheric data products have been validated and evaluated and then been used for atmosphere and ionosphere related scientific applications. This paper reviews the FY-3C GNOS instrument, RO data processing, data quality evaluation, and research applications. The reviewed data validation and application results demonstrate that the FY-3C GNOS mission can provide accurate and precise atmospheric and ionospheric GNSS (i.e., GPS and BDS) RO profiles for numerical weather prediction (NWP), global climate monitoring (GCM) and space weather research (SWR). The performance of the FY-3C GNOS product quality evaluation and scientific applications establishes confidence that the GNOS data from the series of FY-3 satellites will provide important contributions to SWP, GCM and SWR scientific communities. [ABSTRACT FROM AUTHOR]

The Global Navigation Satellite System (GNSS) Occultation Sounder (GNOS) is one of the new generation payloads onboard the Chinese FengYun 3 (FY-3) series of operational meteorological satellites for sounding the Earth's neutral atmosphere and ionosphere. GNOS was designed for acquiring setting and rising radio occultation (RO) data by using GNSS signals from both the Chinese BeiDou System (BDS) and the U.S. Global Positioning System (GPS). An ultra-stable oscillator with 1-sec stability (Allan deviation) at the level of 10-12 was installed on FY-3C GNOS, thus both zero-difference and single-difference excess phase processing methods should be feasible for FY-3C GNOS observations. In this study we focus on evaluating zero-difference processing of BDS RO data vs. single-difference processing, in order to investigate the zero-difference feasibility for this new instrument, which after its launch in September 2013 started to use BDS signals from 5 geostationary orbit (GEO) satellites, 5 inclined geosynchronous orbit (IGSO) satellites and 4 medium earth orbit (MEO) satellites. We used a 3-month set of GNOS BDS RO data (October to December 2013) for the evaluation and compared atmospheric bending angle and refractivity profiles, derived from single- and zero-difference excess phase data, against co-located profiles from ECMWF (European Centre for Medium-Range Weather Forecasts) analyses. We also compared against co-located refractivity profiles from radiosondes. The statistical evaluation against these reference data shows that the results from single- and zero-difference processing are consistent in both bias and standard deviation, clearly demonstrating the feasibility of zero-differencing for GNOS BDS RO observations. The average bias (and standard deviation) of the bending angle and refractivity profiles were found to be as small as about 0.05 %--0.2 % (and 0.7 %--1.6 %) over the upper troposphere and lower stratosphere, including for the GEO, IGSO, and MEO subsets. Zero-differencing was found to perform slightly better, as may be expected from its lower vulnerability to noise. The validation results establish that GNOS can provide, on top of GPS RO profiles, accurate and precise BDS RO profiles both from single- and zero-difference processing. The GNOS observations by the series of FY-3 satellites will thus provide important contributions to numerical weather prediction and global climate change analysis. [ABSTRACT FROM AUTHOR]

Bursaphelenchus xylophilus causes pine wilt disease in Pinus trees whereas B. mucronatus has no or little virulence to the trees. Interspecific crossing experiments conducted so far suggest reproductive interference between the two nematode species. Theory predicts that one of the two competing species populations quickly displaces the other through reproductive interference in a frequency-dependent manner. Thus, it is anticipated that B. mucronatus suppresses the virulence of B. xylophilus against pine trees when B. mucronatus heavily outnumber B. xylophilus. To determine the suppressive effects of B. mucronatus, the two nematode species were inoculated simultaneously on 30 3-year-old Pinus thunbergii seedlings at three combinations of different numbers, and B. xylophilus alone was inoculated on 30 other seedlings at the corresponding numbers in early August. Seedlings were observed at intervals of 4 or 6 weeks and two stem sections were sampled from each seedling to determine the density and species composition of nematode populations after death or in December. Inoculation of B. mucronatus significantly retarded the speed of foliage discolouration from 0.170 ± 0.024 week-1 to 0.061 ± 0.017 week-1 and significantly prolonged the survival time of seedlings. Bursaphelenchus mucronatus significantly reduced the nematode density from 1799.7 ± 305.0 to 521.0 ± 148.4 (g dried seedling stem)-1. Analysis of rDNA genotype showed 1846 B xylophilus, no B. mucronatus and one hybrid. [ABSTRACT FROM AUTHOR]

The exploitation of liquids and gases from certain depths can cause land subsidence, which poses a threat to the safety of surface pipelines and buildings. Accurate subsidence prediction is an important part of environmental impact assessment involving oil and gas reservoir development. Currently, the analytical method research on land subsidence due to oil and gas reservoir development only focuses on regular reservoir shapes and uniform pressure drop, the numerical research has the problem of low calculation accuracy in far-field large grid. There exists limited guiding significance for actual reservoir development. In this study, we extended the classical Geertsma's method by considering the mechanical effects due to uneven pore pressure drop and changes in fluid density in the reservoir. Accordingly, we established a complete description of the equivalent body force and equivalent surface force. Further, we obtained the solution based on Mindlin's basic solution and the convolution method. The proposed method exhibited better generality than others, and can ensure the same solution accuracy in the far and near fields. We conducted case studies to demonstrate that this method can be used to directly evaluate actual oil reservoirs of any shape and pressure distribution. It can also be used to accurately analyze the maximum subsidence position. The calculation results showed that the decrease of reservoir pressure will cause land subsidence, and the decrease in fluid density leads to a certain uplift effect on the formation, resulting in forming subsidence, micro-uplift and stable areas on the land. Moreover, the position of the maximum subsidence point changes with the change in pressure distribution. The proposed method demonstrated guiding significance for actual reservoir development. [ABSTRACT FROM AUTHOR]

Context.—: A prolonged activated partial thromboplastin time (APTT), a vital screening test for coagulation, can be due to deficiencies in coagulation factors and the existence of factor inhibitors or antiphospholipid antibodies. APTT mixing studies are being optimized to help find the cause., Objective.—: To optimize APTT mixing studies, we evaluated existing standards and explored when and how to combine 1:1 and 4:1 mixing., Design.—: Patients with a prolonged APTT but otherwise normal prothrombin time and thrombin time were enrolled in our hospital from January 1, 2018, to December 31, 2019. All samples were subjected to 1:1 mixing studies, while 134 were subjected to 4:1., Results.—: A total of 251 samples were involved, including 116 with factor deficiencies, 75 with FVIII inhibitors, and 60 with antiphospholipid antibodies. A Rosner index less than 11% or an extended incubation time of more than 3 seconds was better than other existing standards in differentiating factor deficiencies from inhibitors and in differentiating time-dependent inhibitors from time-independent inhibitors, but the approach presented here improves upon those. For the best diagnostic accuracy, samples with a Rosner index between 5.0% and 9.1% need a 4:1 mixing study, while others need 1:1. A combination of Rosner index and percent-extended incubation time-P seemed to offer objective and effective criteria for interpreting the results., Conclusions.—: APTT mixing studies had overall good sensitivity and specificity in differentiating factor deficiencies from inhibitors, or time-dependent from time-independent inhibitors. The combination of 1:1 and 4:1 mixing studies can improve the diagnostic ability compared with 1:1 alone., (© 2022 College of American Pathologists.)

In order to identify the contribution to health risk derived from various emission sources, this study investigated monsoon variations in PM 2.5 mass and concentrations of the associated trace elements in a region with complex pollution sources in central Taiwan. This study applied the Chemical Mass Balance model to analyze the source contribution of PM 2.5 . The source apportionment to obtain the risk contribution of different sources were conducted for different monsoon periods according to the monsoon patterns. In this way, the contributions of individual sources and chemicals to health risk under different monsoon types can be understood to support development of effective control strategies. Among the top contributors of PM 2.5 during the north-east monsoon were Secondary Aerosol 28.93% >Coal Boiler 19.82% >Crustal Dust 15.99%; in south-west monsoon were Coal Boiler 37.29% >Traffic Emission 21.19% >Secondary Aerosol 17.84%. The total risk of cancer was above the acceptable risk (3.07 × 10 -6 ), while the non-carcinogenic risk was within the acceptable range (0.262). The variation in the concentration and composition of PM 2.5 was related to the change of monsoon type. During the north-east monsoon, the air mass had a long transmission distance and the PM 2.5 concentration was relatively high. During the south-west monsoon, the air mass had a short transmission distance and the composition was mainly influenced by nearby emission sources, which resulted in higher risk due to chemical characteristics. To provide sound air quality management, attention should be paid to the composition of PM 2.5 in addition to its concentration., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)