Nonuniform Microwave Photonic Delay-Line Filter For Optical Sensor Network Interrogation

We propose a new design of nonuniform spaced microwave photonic delay-line filter based generic optical fiber sensors interrogation platform. Both the amplitude and phase response of the microwave filter are used to demodulate optical sensors. Therefore, a large sensor network with different types of optical sensors can be interrogated simultaneously. The concept of this new microwave photonics enabled interrogation approach is presented and verified by simulations where four different types of optical sensors are simultaneously interrogated via inverse Fourier transform of filter frequency response

Multi-node Acceleration for Large-scale GCNs

Limited by the memory capacity and compute power, singe-node graph convolutional neural network (GCN) accelerators cannot complete the execution of GCNs within a reasonable amount of time, due to the explosive size of graphs nowadays. Thus, large-scale GCNs call for a multi-node acceleration system (MultiAccSys) like TPU-Pod for large-scale neural networks. In this work, we aim to scale up single-node GCN accelerators to accelerate GCNs on large-scale graphs. We first identify the communication pattern and challenges of multi-node acceleration for GCNs on large-scale graphs. We observe that (1) coarse-grained communication patterns exist in the execution of GCNs in MultiAccSys, which introduces massive amount of redundant network transmissions and off-chip memory accesses; (2) overall, the acceleration of GCNs in MultiAccSys is bandwidth-bound and latency-tolerant. Guided by these two observations, we then propose MultiGCN, the first MultiAccSys for large-scale GCNs that trades network latency for network bandwidth. Specifically, by leveraging the network latency tolerance, we first propose a topology-aware multicast mechanism with a one put per multicast message-passing model to reduce transmissions and alleviate network bandwidth requirements. Second, we introduce a scatter-based round execution mechanism which cooperates with the multicast mechanism and reduces redundant off-chip memory accesses. Compared to the baseline MultiAccSys, MultiGCN achieves 4~12x speedup using only 28%~68% energy, while reducing 32% transmissions and 73% off-chip memory accesses on average. It not only achieves 2.5~8x speedup over the state-of-the-art multi-GPU solution, but also scales to large-scale graphs as opposed to single-node GCN accelerators.Comment: To appear in T

HiHGNN: Accelerating HGNNs through Parallelism and Data Reusability Exploitation

Heterogeneous graph neural networks (HGNNs) have emerged as powerful algorithms for processing heterogeneous graphs (HetGs), widely used in many critical fields. To capture both structural and semantic information in HetGs, HGNNs first aggregate the neighboring feature vectors for each vertex in each semantic graph and then fuse the aggregated results across all semantic graphs for each vertex. Unfortunately, existing graph neural network accelerators are ill-suited to accelerate HGNNs. This is because they fail to efficiently tackle the specific execution patterns and exploit the high-degree parallelism as well as data reusability inside and across the processing of semantic graphs in HGNNs. In this work, we first quantitatively characterize a set of representative HGNN models on GPU to disclose the execution bound of each stage, inter-semantic-graph parallelism, and inter-semantic-graph data reusability in HGNNs. Guided by our findings, we propose a high-performance HGNN accelerator, HiHGNN, to alleviate the execution bound and exploit the newfound parallelism and data reusability in HGNNs. Specifically, we first propose a bound-aware stage-fusion methodology that tailors to HGNN acceleration, to fuse and pipeline the execution stages being aware of their execution bounds. Second, we design an independency-aware parallel execution design to exploit the inter-semantic-graph parallelism. Finally, we present a similarity-aware execution scheduling to exploit the inter-semantic-graph data reusability. Compared to the state-of-the-art software framework running on NVIDIA GPU T4 and GPU A100, HiHGNN respectively achieves an average 41.5$\times$ and 8.6$\times$ speedup as well as 106$\times$ and 73$\times$ energy efficiency with quarter the memory bandwidth of GPU A100

Impacts of Urban Green Space on Land Surface Temperature from Urban Block Perspectives

Urban green space (UGS) can be regarded as an effective approach to mitigate urban heat island (UHI) effects. Many studies have investigated the impacts of composition and configuration of UGS on land surface temperature (LST), while little attention has been paid to the impacts among different urban blocks. Thus, taking 1835 urban blocks in Beijing as samples, including low-rise point (LRP), low-rise street (LRS), low-rise block (LRB), mid-rise point (MRP), mid-rise street (MRS), mid-rise block (MRB), high-rise point (HRP), high-rise street (HRS) and high-rise block (HRB), this study investigated the impacts of UGS on LST among different urban blocks. The results showed that UGS serves as cold islands among different urban blocks. Percentage of landscape (PLAND) of UGS in all types of urban blocks, edge density (ED) of UGS in MRS, area-weighted fractal dimension index (FRAC_AM) of UGS in HRS and HRB show significantly negative impacts on LST, while aggregation index (AI) of UGS in LRP shows significantly positive impacts. The findings suggest that both composition and configuration of UGS can affect LST among different urban blocks and rational allocation of UGS would be effective for mitigating UHI effects

Identifying Human-Induced Spatial Differences of Soil Erosion Change in a Hilly Red Soil Region of Southern China

Soil erosion (SE) processes are closely related to natural conditions and human activities, posing a threat to environment and society. Identifying the human impact on regional SE changes is increasingly essential for pertinent SE management. Jiangxi province is studied here as a representative area of hilly-red-soil regions within southern China. The main objectives of this study were to investigate the changing trend of SE within Jiangxi and identify human impacts on regional SE change from the perspective of spatial differences, through a new approach based on a gravity-center model. Our results showed that SE status presented an overall amelioration from 1990 to 2015, while the average soil erosion modulus (SEM) declined from 864 to 281 Mg/(km2·a). Compared to the situation under human and natural impacts, human-induced spatial differences of SE change demonstrated that the western and northwest regions showed stronger negative effects; the southern region shifted towards negative effects; the northeast region presented a much weaker negative effect. Our results indicated that 4 cities with strong negative effects need more attention in further SE management suited to their local conditions and development, and also suggested that the approach based on a gravity-center has potential for identifying the human impact on regional SE change from the perspective of spatial patterns

The Role of Quantified Parameters on River Plume Structure: Numerical Simulation

A three-dimensional numerical model was established with OpenFOAM-5.x to investigate plume characteristics under windless and rainless weather conditions. The large eddy simulation was applied, combined with a modified solver for solving governing equations with the Boussinesq approximation in a single rotating frame. The relationship between plume characteristics (e.g., gradient Richardson number and maximum plume width) and quantified parameters (e.g., rotation period, shelf slope, and reduced gravity) was analyzed progressively. The results show the model can reproduce the change in plume types and instability found in the laboratory experiments. With the increase in the rotation period, river plumes change from a surface-advected type to a bottom-attached type. The outline of the plume bulge accurately delineates the external region where the gradient Richardson number is less than 0.25, as well as the region near the wall. When the shelf slope approaches 0, the offshore movement becomes stronger while the alongshore coastal current comes into being with a delay associated with the slope and the rotation period. Compared with the extremely gentle slope case and the steep slope case, the maximum width in the gentle slope case changes significantly at about 1.5 rotation periods. Greater reduced gravity does promote offshore propagation, especially near the surface

Study on the Factors Affecting the Performance of a Pressure Filtration–Flocculation–Solidification Combined Method for Mud Slurry Treatment

A pressure filtration–flocculation–solidification combined treatment possesses great potential for the reutilization of the waste mud slurry generated from diverse construction projects as filling material due to its versatility and high efficiency. However, very limited existing studies have focused on the factors affecting pressure filtration’s efficiency. In this paper, a calculation model for compression filtration is established based on laboratory pressure filtration model tests and one-dimensional large-strain consolidation theory. The influence of various parameters on pressure filtration’s efficiency is analyzed, and favorable values for these parameters are recommended. The results show that an increased initial mud cake thickness significantly increases the dewatering time and reduces the treatment’s efficiency. A lower dewatering time and higher efficiency can be achieved by increasing the filtration pressure, but the efficiency improvements become limited after reaching the critical pressure threshold. For the mud slurry used in this study, the optimal values for the initial mud slurry bag thickness, filtration pressure, and dewatering time are 240 mm, 1.0 MPa, and 30 min, respectively, yielding a final mud cake water content of 58.7% after filtration

Assessment of GF3 Full-Polarimetric SAR Data for Dryland Crop Classification with Different Polarimetric Decomposition Methods

Crop classification is one of the most important agricultural applications of remote sensing. Many studies have investigated crop classification using SAR data, while few studies have focused on the classification of dryland crops by the new Gaofen-3 (GF3) SAR data. In this paper, taking Hengshui city as the study area, the performance of the Freeman–Durden, Sato4, Singh4 and multi-component decomposition methods for dryland crop type classification applications are evaluated, and the potential of full-polarimetric GF3 data in dryland crop type classification are also investigated. The results show that the multi-component decomposition method produces the most accurate overall classifications (88.37%). Compared with the typical polarization decomposition techniques, the accuracy of the classification results using the new decomposition method is improved. In addition, the Freeman method generally yields the third-most accurate results, and the Sato4 (87.40%) and Singh4 (87.34%) methods yield secondary results. The overall classification accuracy of the GF3 data is very positive. These results demonstrate the great promising potential of GF3 SAR data for dryland crop monitoring applications

Mechanisms of improved aortic stiffness by arotinolol in spontaneously hypertensive rats.

OBJECTIVES: This study investigates the effects on aortic stiffness and vasodilation by arotinolol and the underlying mechanisms in spontaneously hypertensive rats (SHR). METHODS: The vasodilations of rat aortas, renal and mesenteric arteries were evaluated by isometric force recording. Nitric oxide (NO) was measured in human aortic endothelial cells (HAECs) by fluorescent probes. Sixteen-week old SHRs were treated with metoprolol (200 mg·kg-1·d⁻¹), arotinolol (30 mg·kg-1·d⁻¹) for 8 weeks. Central arterial pressure (CAP) and pulse wave velocity (PWV) were evaluated via catheter pressure transducers. Collagen was assessed by immunohistochemistry and biochemistry assay, while endothelial nitric oxide synthase (eNOS) and eNOS phosphorylation (p-eNOS) of HAECs or aortas were analyzed by western blotting. RESULTS: Arotinolol relaxed vascular rings and the relaxations were attenuated by Nω-nitro-L-arginine methyl ester (L-NAME, NO synthase inhibitor) and the absence of endothelium. Furthermore, arotinolol-induced relaxations were attenuated by 4-aminopyridine (4-AP, Kv channels blocker). Arotinolol produced more nitric oxide compared to metoprolol and increased the expression of p-eNOS in HAECs. These results indicated that arotinolol-induced vasodilation involves endothelium-derived NO and Kv channels. The treatement with arotinolol in 8 weeks, but not metoprolol, markedly decreased CAP and PWV. Biochemistry assay and immunohistochemistry showed that aortic collagen depositions in the arotinolol groups were reduced compared with SHRs with metoprolol. Moreover, eNOS phosphorylation was significantly increased in aortinolol-treated SHR compared with SHRs with metoprolol. CONCLUSIONS: Arotinolol improves arterial stiffness in SHR, which involved in increasing NO and decreasing collagen contents in large arteries