FusionFormer: A Multi-sensory Fusion in Bird's-Eye-View and Temporal Consistent Transformer for 3D Objection

Multi-sensor modal fusion has demonstrated strong advantages in 3D object detection tasks. However, existing methods that fuse multi-modal features through a simple channel concatenation require transformation features into bird's eye view space and may lose the information on Z-axis thus leads to inferior performance. To this end, we propose FusionFormer, an end-to-end multi-modal fusion framework that leverages transformers to fuse multi-modal features and obtain fused BEV features. And based on the flexible adaptability of FusionFormer to the input modality representation, we propose a depth prediction branch that can be added to the framework to improve detection performance in camera-based detection tasks. In addition, we propose a plug-and-play temporal fusion module based on transformers that can fuse historical frame BEV features for more stable and reliable detection results. We evaluate our method on the nuScenes dataset and achieve 72.6% mAP and 75.1% NDS for 3D object detection tasks, outperforming state-of-the-art methods

Identification of Sare0718 As an Alanine-Activating Adenylation Domain in Marine Actinomycete Salinispora arenicola CNS-205

BACKGROUND: Amino acid adenylation domains (A domains) are critical enzymes that dictate the identity of the amino acid building blocks to be incorporated during nonribosomal peptide (NRP) biosynthesis. NRPs represent a large group of valuable natural products that are widely applied in medicine, agriculture, and biochemical research. Salinispora arenicola CNS-205 is a representative strain of the first discovered obligate marine actinomycete genus, whose genome harbors a large number of cryptic secondary metabolite gene clusters. METHODOLOGY/PRINCIPAL FINDINGS: In order to investigate cryptic NRP-related metabolites in S. arenicola CNS-205, we cloned and identified the putative gene sare0718 annotated "amino acid adenylation domain". Firstly, the general features and possible functions of sare0718 were predicted by bioinformatics analysis, which suggested that Sare0718 is a soluble protein with an AMP-binding domain contained in the sequence and its cognate substrate is L-Val. Then, a GST-tagged fusion protein was expressed and purified to further explore the exact adenylation activity of Sare0718 in vitro. By a newly mentioned nonradioactive malachite green colorimetric assay, we found that L-Ala but not L-Val is the actual activated amino acid substrate and the basic kinetic parameters of Sare0718 for it are K(m) = 0.1164±0.0159 (mM), V(max) = 3.1484±0.1278 (µM/min), k(cat) = 12.5936±0.5112 (min(-1)). CONCLUSIONS/SIGNIFICANCE: By revealing the biochemical role of sare0718 gene, we identified an alanine-activating adenylation domain in marine actinomycete Salinispora arenicola CNS-205, which would provide useful information for next isolation and function elucidation of the whole cryptic nonribosomal peptide synthetase (NRPS)-related gene cluster covering Sare0718. And meanwhile, this work also enriched the biochemical data of A domain substrate specificity in newly discovered marine actinomycete NRPS system, which bioinformatics prediction will largely depend on

Extreme Precipitation Changes in the Semiarid Region of Xinjiang, Northwest China

This study focuses on extreme precipitation changes in Xinjiang Province of Northwest China, which has experienced an increase in climate disasters in recent years. This paper investigates extreme precipitation events in Xinjiang, using 54 stations with daily precipitation records from the period 1961–2008. Different statistical tests and approaches were used to check the significance of trends of single and Xinjiang regionally aggregated precipitation series for intensity and in frequency. There were predominantly positive trends in annual maximum precipitation and a remarkable increment in the frequency of extreme precipitation over certain thresholds (from 10 to 40 mm). Although the series of frequencies exceeding thresholds had positive trends, only a minority were statistically significant. This lack of significance is because of the high variability of extreme precipitation in space and time. Thus, significant trends were evident when we assessed the extreme precipitation indicators of intensity and frequency at the regional level, both in intensity and frequency over thresholds, with a clearer signal in Xinjiang

Study on the Relationship between Topological Characteristics of Vegetation Ecospatial Network and Carbon Sequestration Capacity in the Yellow River Basin, China

Achieving carbon neutrality is a necessary effort to rid humanity of a catastrophic climate and is a goal for China in the future. Ecological space plays an important role in the realization of carbon neutrality, but the relationship between the structure of vegetation ecological space and vegetation carbon sequestration capacity has been the focus of research. In this study, we extracted the base data from MODIS products and other remote sensing products, and then combined them with the MCR model to construct a vegetation ecospatial network in the Yellow River Basin in 2018. Afterward, we calculated the topological indicators of ecological nodes in the network and analyzed the relationship between the carbon sequestration capacity (net biome productivity) of ecological nodes and these topological indicators in combination with the Biome-BGC model. The results showed that there was a negative linear correlation between the betweenness centrality of forest nodes and their carbon sequestration capacity in the Yellow River Basin (p < 0.05, R2 = 0.59). On the other hand, there was a positive linear correlation between the clustering coefficient of grassland nodes and their carbon sequestration capacity (p < 0.01, R2 = 0.49). In addition, we briefly evaluated the vegetation ecospatial network in the Yellow River BASIN and suggested its optimization direction under the background of carbon neutrality in the future. Increasing the carbon sequestration capacity of vegetation through the construction of national ecological projects is one of the ways to achieve carbon neutrality, and this study provides a reference for the planning of future national ecological projects in the Yellow River Basin. Furthermore, this is also a case study of the application of remote sensing in vegetation carbon budgeting

Influence of electrode types on the electrohydrodynamic instability patterning process:a comparative study

<p> This article studies the effect that different types of patterned electrodes have on the electrohydrodynamic instability patterning (EHDIP) process for the faithful replication of micro-and nanostructures. Two types of patterned electrodes are studied. One is fully conductive, i.e. both pattern and substrate are conductive. The other type has conductive microstructures fabricated on a dielectric substrate. By employing the COMSOL (TM) Multiphysics software package, a rigorous numerical simulation of the EHDIP process has been carried out for both types of electrodes. The simulation results show that both electrodes can realize a faithful replication of the micro-and nanostructures once the variable, Delta E/Delta x, reaches the critical value. Moreover, it is demonstrated that a fully conductive template is preferred if a small polymer film thickness is employed; a partially conductive electrode is preferred for larger film thickness. These results provide guidelines for the better control of the EHDIP process in order to realize the perfect pattern replication of structures for a variety of applications in MEMS or micro/nanofluidics.</p

Study on the Relationship between Topological Characteristics of Vegetation Ecospatial Network and Carbon Sequestration Capacity in the Yellow River Basin, China

Achieving carbon neutrality is a necessary effort to rid humanity of a catastrophic climate and is a goal for China in the future. Ecological space plays an important role in the realization of carbon neutrality, but the relationship between the structure of vegetation ecological space and vegetation carbon sequestration capacity has been the focus of research. In this study, we extracted the base data from MODIS products and other remote sensing products, and then combined them with the MCR model to construct a vegetation ecospatial network in the Yellow River Basin in 2018. Afterward, we calculated the topological indicators of ecological nodes in the network and analyzed the relationship between the carbon sequestration capacity (net biome productivity) of ecological nodes and these topological indicators in combination with the Biome-BGC model. The results showed that there was a negative linear correlation between the betweenness centrality of forest nodes and their carbon sequestration capacity in the Yellow River Basin (p R2 = 0.59). On the other hand, there was a positive linear correlation between the clustering coefficient of grassland nodes and their carbon sequestration capacity (p R2 = 0.49). In addition, we briefly evaluated the vegetation ecospatial network in the Yellow River BASIN and suggested its optimization direction under the background of carbon neutrality in the future. Increasing the carbon sequestration capacity of vegetation through the construction of national ecological projects is one of the ways to achieve carbon neutrality, and this study provides a reference for the planning of future national ecological projects in the Yellow River Basin. Furthermore, this is also a case study of the application of remote sensing in vegetation carbon budgeting

Energy variation curve of CSTB at peak stress point under uniaxial loading.

Energy variation curve of CSTB at peak stress point under uniaxial loading.</p

Toughness curves of fiber reinforced CSTB.

(a) 3 mm length, (b) 6 mm length, and (c) 12 mm length.</p

Failure characteristics of CSTB with different sulfur contents.

(a) 6% sulfur content, (b) 12% sulfur content, (c) 18% sulfur content, and (d) 25% sulfur content.</p

Chemical composition of cement and tailings (mass fraction) %.

Chemical composition of cement and tailings (mass fraction) %.</p