Searching for the two-dimensional (2D) topological insulators (TIs) with large bulk band gaps is the key to achieve room-temperature quantum spin Hall effect (QSHE). Using first-principles ...calculations, we demonstrated that the recently-proposed antimonene Zhang et al., Angew. Chem. Int. Ed. 54, 3112-3115 (2015) can be tuned to a 2D TI by reducing the buckling height of the lattice which can be realized under tensile strain. The strain-driven band inversion in the vicinity of the Fermi level is responsible for the quantum phase transition. The buckled configuration of antimonene enables it to endure large tensile strain up to 18% and the resulted bulk band gap can be as large as 270 meV. The tunable bulk band gap makes antimonene a promising candidate material for achieving quantum spin Hall effect (QSH) at high temperatures which meets the requirement of future electronic devices with low power consumption.
Quantum spin Hall (QSH) effect is promising for achieving dissipationless transport devices but presently is achieved only at extremely low temperature. Searching for the large-gap QSH insulators ...with strong spin–orbit coupling (SOC) is the key to increase the operating temperature. We demonstrate theoretically that this can be solved in the chloridized gallium bismuthide (GaBiCl2) monolayer, which has nontrivial gaps of 0.95 eV at the Γ point, and 0.65 eV for bulk, as well as gapless edge states in the nanoribbon structures. The nontrivial gaps due to the band inversion and SOC are robust against external strain. The realization of the GaBiCl2 monolayer will be beneficial for achieving QSH effect and related applications at high temperatures.
Using first-principle calculations, we show that germanene can attach on Ag(111) surface forming germanene/Ag superstructures
via
electrostatic interactions. In all the optimized superstructures, we ...found a kind of epitaxially grown germanene is similar to the isolated low-buckled germanene. The adsorption energy of germanene on Ag(111) surface is about −464 meV to −428 meV per Ge atom, close to that of silicene on Ag(111) surface. Germanene on Ag(111) is a continuous layer and the p-d hybridization between Ag and Ge is revealed. These indicate Ag(111) surface is a good substrate for stabilizing germanene. The band structures of germanene are submerged in electronic states of metallic Ag substrate. To preserve the excellent electronic structures of germanene, we also considered another substrate hexagonal boron nitride (h-BN). We show that germanene can stably attach on h-BN substrate
via
Van der Waals (vdW) interactions, forming germanene/BN Moiré superstructures. At equilibrium state, a small band gap of about 50 meV is opened up in the Dirac point of germanene, whose value is insensitive to the rotation angle and the sliding between the two lattices, but can be effectively tuned by changing the interlayer distance. In these superstructures, the high carrier mobility of germanene is well preserved. These imply that h-BN can act as an ideal substrate material for germanene to achieve specific applications in nanoscale electronic devices.
From view of first-principle calculations, germanene can attach on Ag(111) surface and h-BN, forming germanene/Ag and germanene/BN superstructures.
•Direct and indirect effects of sectors on net energy consumption are analysed.•Level effect is identified as the major driver for increasing energy consumption.•Manufacturing has the largest energy ...consumption reduction potential.•How to decrease net energy consumption has been offered to policy-makers.
This paper provides a comprehensive analysis of Australian net energy consumption between 2004–05 and 2014–15. Results from environmentally-extended input-output (EEIO) analysis show that the Transport sector has the largest direct effect on net energy consumption in industrial sectors, which decreased by about 35% for net energy consumption per million $AUD in the period. The Export sector has the largest direct net energy consumption while Households consumption results in the largest net energy consumption embodied in different categories of Final demand. The structural decomposition analysis (SDA) decomposes the change of net energy consumption into five drivers, in which net energy intensity mainly reduces Australian net energy consumption by about 8000 Petajoules, while the level effect of Final demand increases it by about 10,000 Petajoules. Analysis of forward and backward linkages highlights the Manufacturing sector as the key industrial sector with the largest energy consumption reduction potential via minor changes in its input and Final demand. This indicates that more attention should be given to the reduction of energy demand from the consumption patterns of Households consumption, the improvement of energy intensity, and the application of cleaner technologies in the Transport and Manufacturing sectors. The Australian Environmental-Economic Accounts is combined with Australian input-output tables to construct the EEIO tables for net energy consumption. The combination of economic and environmental data sets provides a depth of understanding their potential to inform environmental policy decisions. The novelty of the research is the combination of economic and energy data sets, the application of EEIO model, the implementation of the additive SDA method, and the use of forward and backward linkages for the Australian energy system.
The ATP-binding cassette (ABC) transporter family is one of the largest eukaryotic protein families. Its members play roles in numerous metabolic processes in plants by releasing energy for substrate ...transport across membranes through hydrolysis of ATP. Maize belongs to the monocotyledonous plant family, Gramineae, and is one of the most important food crops in the world. We constructed a phylogenetic tree with individual ABC genes from maize, rice, sorghum,
, and poplar. This revealed eight families, each containing ABC genes from both monocotyledonous and dicotyledonous plants, indicating that the amplification events of ABC gene families predate the divergence of plant monocotyledons. To further understand the functions of ABC genes in maize growth and development, we analyzed the expression patterns of maize ABC family genes in eight tissues and organs based on the transcriptome database on the Genevestigator website. We identified 133 ABC genes expressed in most of the eight tissues and organs examined, especially during root and leaf development. Furthermore, transcriptome analysis of
genes showed that exposure to metallic lead induced differential expression of many maize ABC genes, mainly including
,
,
,
,
,
,
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,
,
,
,
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and
genes, etc. These results indicated that
genes play an important role in the response to heavy metal stress. The comprehensive analysis of this study provides a foundation for further studies into the roles of ABC genes in maize.
With the widespread application of GNSS, the delicate handling of biases among different systems and different frequencies is of critical importance, wherein the inter-frequency clock biases (IFCBs) ...and observable-specific signal biases (OSBs) should be carefully corrected. Usually, a serial approach is used to calculate these products. To accelerate the computation speed and reduce the time delay, a multicore parallel estimation strategy for IFCBs, code, and phase OSBs by utilizing task parallel library (TPL) is proposed, the parallel computations, including precise point positioning (PPP), IFCBs, and OSBs estimation, being carried out on the basis of data parallelisms and task-based asynchronous programming. Three weeks of observables from the multi-GNSS experiment campaign (MGEX) network is utilized. The result shows that the IFCB errors of GPS Block IIF and GLONASS M+ satellites are nonnegligible, in which the GLONASS M+ satellite R21 shows the largest IFCB of more than 0.60 m, while those of other systems and frequencies are marginal, and the code OSBs present excellent stability with a standard deviation (STD) of 0.10 ns for GPS and approximately 0.20 ns for other satellite systems. Besides, the phase OSBs of all systems show the stability of better than 0.10 ns, wherein the Galileo satellites show the best performance of 0.01 ns. Compared with the single-core serial computing method, the acceleration rates for IFCBs and OSBs estimation are 3.10, 5.53, 9.66, and 17.04 times higher using four, eight, sixteen, and thirty-two physical cores, respectively, through multi-core parallelized execution.
With the modernization of GLONASS, four M+ and two K satellites are able to broadcast code-division multiple-access signals at a G3 frequency. The evaluation of the G3 frequency is necessary, among ...which the satellite-induced code pseudorange variation is one of the most important indicators. Using the code-minus-carrier (CMC) combination, it was found that the magnitude of the code pseudorange variations at the G3 frequency is about 1 m, which is primarily caused by the fact that G3 is transmitted from a different antenna, the same as G1 and G2. However, different from BDS-2 medium Earth orbit and inclined geo-synchronous orbit satellites, the code pseudorange variations at the GLONASS G3 frequency have a very weak relationship with the elevation angle, while a strong correlation exists with the time series, by using wavelet transformation and correlation analysis. Validation is carried out using a single-site model and a continuous multi-site model over 24 h, and the correction performance of these two models is comparable. The systematic deviation of the CMC and Melbourne–Wübbena combinations are significantly corrected, so only random errors remain. With a more concentrated distribution of the pseudorange residuals of single point positioning, the standard deviation of the pseudorange residuals is reduced.
Land cover classification (LCC) is of paramount importance for assessing environmental changes in remote sensing images (RSIs) as it involves assigning categorical labels to ground objects. The ...growing availability of multi-source RSIs presents an opportunity for intelligent LCC through semantic segmentation, offering a comprehensive understanding of ground objects. Nonetheless, the heterogeneous appearances of terrains and objects contribute to significant intra-class variance and inter-class similarity at various scales, adding complexity to this task. In response, we introduce SLMFNet, an innovative encoder-decoder segmentation network that adeptly addresses this challenge. To mitigate the sparse and imbalanced distribution of RSIs, we incorporate selective attention modules (SAMs) aimed at enhancing the distinguishability of learned representations by integrating contextual affinities within spatial and channel domains through a compact number of matrix operations. Precisely, the selective position attention module (SPAM) employs spatial pyramid pooling (SPP) to resample feature anchors and compute contextual affinities. In tandem, the selective channel attention module (SCAM) concentrates on capturing channel-wise affinity. Initially, feature maps are aggregated into fewer channels, followed by the generation of pairwise channel attention maps between the aggregated channels and all channels. To harness fine-grained details across multiple scales, we introduce a multi-level feature fusion decoder with data-dependent upsampling (MLFD) to meticulously recover and merge feature maps at diverse scales using a trainable projection matrix. Empirical results on the ISPRS Potsdam and DeepGlobe datasets underscore the superior performance of SLMFNet compared to various state-of-the-art methods. Ablation studies affirm the efficacy and precision of SAMs in the proposed model.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
For positioning tasks of mobile robots in indoor environments, the emerging positioning technique based on visual inertial odometry (VIO) is heavily influenced by light and suffers from cumulative ...errors, which cannot meet the requirements of long-term navigation and positioning. In contrast, positioning techniques that rely on indoor signal sources such as 5G and geomagnetism can provide drift-free global positioning results, but their overall positioning accuracy is low. In order to obtain higher precision and more reliable positioning, this paper proposes a fused 5G/geomagnetism/VIO indoor localization method. Firstly, the error back propagation neural network (BPNN) model is used to fuse 5G and geomagnetic signals to obtain more reliable global positioning results; secondly, the conversion relationship from VIO local positioning results to the global coordinate system is established through the least squares principle; and finally, a fused 5G/geomagnetism/VIO localization system based on the error state extended Kalman filter (ES-EKF) is constructed. The experimental results show that the 5G/geomagnetism fusion localization method overcomes the problem of low accuracy of single sensor localization and can provide more accurate global localization results. Additionally, after fusing the local and global positioning results, the average positioning error of the mobile robot in the two scenarios is 0.61 m and 0.72 m. Compared with the VINS-mono algorithm, our approach improves the average positioning accuracy in indoor environments by 69.0% and 67.2%, respectively.
To provide continuous and reliable real-time precise positioning services in challenging environments and poor internet conditions, the real-time precise corrections of the BeiDou global navigation ...satellite system (BDS-3) PPP-B2b signal are utilized to correct the satellite orbit errors and clock offsets. In addition to this, using the complementary characteristics of the inertial navigation system (INS) and the global navigation satellite system (GNSS), a PPP-B2b/INS tight integration model is established. With observation data collected in an urban environment, the results show that PPP-B2b/INS tight integration can ensure a decimeter-level positioning accuracy; the positioning accuracies of the E, N, and U components are 0.292, 0.115, and 0.155 m, respectively, which can provide a continuous and secure position during short interruptions in the GNSS. However, there is still a gap of about 1 dm compared with the three-dimensional (3D) positioning accuracy obtained from Deutsche GeoForschungsZentrum (GFZ) real-time products, and a gap of about 2 dm compared with the GFZ post-precise products. Using a tactical inertial measurement unit (IMU), the velocimetry accuracies of the tightly integrated PPP-B2b/INS in the E, N, and U components are all about 0.3 cm/s, and the attitude accuracy of yaw is about 0.1 deg, while the pitch and roll show a superior performance of less than 0.01 deg. The accuracies of the velocity and attitude mainly depend on the performance of the IMU in the tight integration mode, and there is no significant difference between using real-time products and post products. The performance of the microelectromechanical system (MEMS) IMU and tactical IMU is also compared, and the positioning, velocimetry, and attitude determinations with the MEMS IMU are significantly worsened.
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