SMURF: Spatial Multi-Representation Fusion for 3D Object Detection with 4D Imaging Radar

The 4D Millimeter wave (mmWave) radar is a promising technology for vehicle sensing due to its cost-effectiveness and operability in adverse weather conditions. However, the adoption of this technology has been hindered by sparsity and noise issues in radar point cloud data. This paper introduces spatial multi-representation fusion (SMURF), a novel approach to 3D object detection using a single 4D imaging radar. SMURF leverages multiple representations of radar detection points, including pillarization and density features of a multi-dimensional Gaussian mixture distribution through kernel density estimation (KDE). KDE effectively mitigates measurement inaccuracy caused by limited angular resolution and multi-path propagation of radar signals. Additionally, KDE helps alleviate point cloud sparsity by capturing density features. Experimental evaluations on View-of-Delft (VoD) and TJ4DRadSet datasets demonstrate the effectiveness and generalization ability of SMURF, outperforming recently proposed 4D imaging radar-based single-representation models. Moreover, while using 4D imaging radar only, SMURF still achieves comparable performance to the state-of-the-art 4D imaging radar and camera fusion-based method, with an increase of 1.22% in the mean average precision on bird's-eye view of TJ4DRadSet dataset and 1.32% in the 3D mean average precision on the entire annotated area of VoD dataset. Our proposed method demonstrates impressive inference time and addresses the challenges of real-time detection, with the inference time no more than 0.05 seconds for most scans on both datasets. This research highlights the benefits of 4D mmWave radar and is a strong benchmark for subsequent works regarding 3D object detection with 4D imaging radar

Techno-Economic Analysis of Photovoltaic Hydrogen Production Considering Technological Progress Uncertainty

The application of photovoltaic (PV) power to split water and produce hydrogen not only reduces carbon emissions in the process of hydrogen production but also helps decarbonize the transportation, chemical, and metallurgical industries through P2X technology. A techno-economic model must be established to predict the economics of integrated PV–hydrogen technology at key time points in the future based on the characteristics, variability, and uncertainties of this technology. In this study, we extracted the comprehensive technical factors (including PV tracking system coefficient, PV conversion efficiency, electrolyzer efficiency, and electrolyzer degradation coefficient) of an integrated PV–hydrogen system. Then, we constructed a PV hydrogen production techno-economic (PVH2) model. We used the levelized cost of hydrogen production (LCOH) method to estimate the cost of each major equipment item during the project lifetime. We combined the PVH2 and learning curve models to determine the cost trend of integrated PV–hydrogen technology. We developed a two-dimensional Monte Carlo approach to predict the variation interval of LCOH for PV–hydrogen projects in 2030 and 2050, which described the current technology variability with variable parameters and the uncertainty in the technology advancement with uncertain parameters. The results showed that the most critical factors influencing LCOH are PV conversion efficiency and the capital cost of the electrolyzer. The LCOH of PV to hydrogen in China will drop to CNY 18–32/kg by 2030 and CNY 8–18/kg by 2050. The combination of a learning curve model and a Monte Carlo method is an effective tool to describe the current variability in hydrogen production technologies and the uncertainty in technological progress

Transcriptome−Based Identification and Characterization of Genes Associated with Resistance to Beta−Cypermethrin in Rhopalosiphum padi (Hemiptera: Aphididae)

Beta−cypermethrin is one of the most widely used pyrethroid insecticides. However, its continuous and extensive use developed pests’ resistance to beta−cypermethrin. To identify candidate genes for potential resistance phenotypes and facilitate more targeted studies, we screened out a wide range of resistance−related genes by comparing multiple transcripts before and after the induction of multiple agents. In this study, transcriptomes were compared to elucidate the mechanisms and genetic basis of potential resistance between Rhopalosiphum padi (R. padi) sensitive (SS) and resistant (Beta−R) strains to beta−cypermethrin (resistance ratio: 4588.48). These two strains of aphids were treated with a spray solution of lethal beta−cypermethrin concentration (i.e., LC50). To obtain diverse transcripts, we obtained 17,985,440–25,478,353 clean data from different transcript groups, of which 17,183 genes were annotated. Subsequently, these transcripts were divided into multiple groups for comparison purposes to obtain more comprehensive genes related to resistance. There were 178 to 2856 differentially expressed genes (DEGs) in these transcript groups. The DEGs, including the enriched ones, were classified according to the GO and KEGG Pathway databases. Besides, some drug−resistant DEGs were related to cuticle proteins and detoxification metabolic processes. Among them, 17 genes related to cuticle protein were upregulated and 20 were downregulated, 11 genes related to P450 were upregulated and 25 were downregulated, 7 genes related to UGT were upregulated and 15 were downregulated, 2 genes related to ABC transporter were upregulated and 4 were downregulated, 2 genes related to trypsin were upregulated and 1 were downregulated. Finally, qRT−PCR by DEGs confirmed the observed trend in the RNA sequencing expression profile, and most of the results were consistent between qRT−PCR and RNA sequencing (RNA−seq). The results of this study are highly significant in understanding the resistance phenomenon in R. padi and other similar wheat aphids, establishing the valuable basis for further research in the complex mechanism of R. padi resistance to beta−cypermethrin

SMURF: Spatial Multi-Representation Fusion for 3D Object Detection with 4D Imaging Radar

The 4D millimeter-Wave (mmWave) radar is a promising technology for vehicle sensing due to its costeffectiveness and operability in adverse weather conditions. However, the adoption of this technology has been hindered by sparsity and noise issues in radar point cloud data. This paper introduces spatial multi-representation fusion (SMURF), a novel approach to 3D object detection using a single 4D imaging radar. SMURF leverages multiple representations of radar detection points, including pillarization and density features of a multidimensional Gaussian mixture distribution through kernel density estimation (KDE). KDE effectively mitigates measurement inaccuracy caused by limited angular resolution and multipath propagation of radar signals. Additionally, KDE helps alleviate point cloud sparsity by capturing density features. Experimental evaluations on View-of-Delft (VoD) and TJ4DRadSet datasets demonstrate the effectiveness and generalization ability of SMURF, outperforming recently proposed 4D imaging radarbased single-representation models. Moreover, while using 4D imaging radar only, SMURF still achieves comparable performance to the state-of-the-art 4D imaging radar and camera fusion-based method, with an increase of 1.22% in the mean average precision on bird’s-eye view of TJ4DRadSet dataset and 1.32% in the 3D mean average precision on the entire annotated area of VoD dataset. Our proposed method demonstrates impressive inference time and addresses the challenges of real-time detection, with the inference time no more than 0.05 seconds for most scans on both datasets. This research highlights the benefits of 4D mmWave radar and is a strong benchmark for subsequent works regarding 3D object detection with 4D imaging radar

Femtosecond Laser Polishing of Additively Manufactured Parts at Grazing Incidence

Surface polishing is usually a requisite for making additively manufactured (AM) parts ready for practical applications. Due to its advantages of being flexible and noncontact, laser polishing has attracted increasing research interest. Laser polishing primarily utilizes continuous-wave or long-pulse lasers to melt thin surface layers, which usually depends on the initial surface roughness of AM parts, and also less effective for materials and applications sensitive to heat. In this research, femtosecond (fs) laser polishing was established to post-process both the top surfaces and sidewalls of AM parts. The challenge to remove three levels of roughness (i.e., the initial surface roughness of the AM parts, the undulations newly introduced during fs laser polishing, and the micro-nanoscale surface features induced by fs laser irradiation) was identified and addressed. Mirror surfaces with Sa 20 µm, equivalent to > 99% improvement on the surface finish. Both parallel- and perpendicular-incidence were investigated for the polishing, with the former verified to be more effective in eliminating the initial roughness of the AM parts, due to the elongated focal intensity profile of a Gaussian beam irradiated on the AM part surfaces. The challenge of forming three-zone surfaces during the parallel-incidence was further addressed through a grazing-incidence polishing approach, and uniform smooth surfaces were realized. Fine-tuning the laser power enabled controlling the submicron surface features formed under fs laser irradiation (from continuous ripples to random and finer particles), which determined the final achievable surface roughness. This research has laid a foundation to make fs laser polishing an effective technique for processing various materials

Transcriptome-Based Identification and Characterization of Genes Associated with Resistance to Beta-Cypermethrin in <i>Rhopalosiphum padi</i> (Hemiptera: Aphididae)

Beta-cypermethrin is one of the most widely used pyrethroid insecticides. However, its continuous and extensive use developed pests’ resistance to beta-cypermethrin. To identify candidate genes for potential resistance phenotypes and facilitate more targeted studies, we screened out a wide range of resistance-related genes by comparing multiple transcripts before and after the induction of multiple agents. In this study, transcriptomes were compared to elucidate the mechanisms and genetic basis of potential resistance between Rhopalosiphum padi (R. padi) sensitive (SS) and resistant (Beta-R) strains to beta-cypermethrin (resistance ratio: 4588.48). These two strains of aphids were treated with a spray solution of lethal beta-cypermethrin concentration (i.e., LC50). To obtain diverse transcripts, we obtained 17,985,440–25,478,353 clean data from different transcript groups, of which 17,183 genes were annotated. Subsequently, these transcripts were divided into multiple groups for comparison purposes to obtain more comprehensive genes related to resistance. There were 178 to 2856 differentially expressed genes (DEGs) in these transcript groups. The DEGs, including the enriched ones, were classified according to the GO and KEGG Pathway databases. Besides, some drug-resistant DEGs were related to cuticle proteins and detoxification metabolic processes. Among them, 17 genes related to cuticle protein were upregulated and 20 were downregulated, 11 genes related to P450 were upregulated and 25 were downregulated, 7 genes related to UGT were upregulated and 15 were downregulated, 2 genes related to ABC transporter were upregulated and 4 were downregulated, 2 genes related to trypsin were upregulated and 1 were downregulated. Finally, qRT-PCR by DEGs confirmed the observed trend in the RNA sequencing expression profile, and most of the results were consistent between qRT-PCR and RNA sequencing (RNA-seq). The results of this study are highly significant in understanding the resistance phenomenon in R. padi and other similar wheat aphids, establishing the valuable basis for further research in the complex mechanism of R. padi resistance to beta-cypermethrin

Field-Evolved Sulfoxaflor Resistance of Three Wheat Aphid Species in China

Sulfoxaflor belongs to a new class of insecticides which are effective against many sap-feeding pests. Sitobion miscanthi, Rhopalosiphum padi, and Metopolophium dirhodum are the predominant pests coexisting on wheat plants. It is unknown whether these aphid species have developed resistance to sulfoxaflor. Here, the susceptibilities of three wheat aphid species from different regions of China to sulfoxaflor were evaluated. The results showed that two S. miscanthi, one R. padi, and two M. dirhodum field populations were highly resistant to sulfoxaflor. Additionally, 13 S. miscanthi, 9 R. padi, and 4 M. dirhodum field populations were moderately resistant to sulfoxaflor. Analysis of differences in toxicity showed that the susceptibility levels of R. padi in 9 of 20 regions, M.&nbsp;dirhodum in 5 of 9 regions, and M. dirhodum in 3 of 9 regions to sulfoxaflor were greater than those of S. miscanthi, S. miscanthi, and R. padi in the same regions, respectively. Thus, each wheat aphid species has field populations that are highly sulfoxaflor resistant. The R. padi and M. dirhodum populations were more susceptible to sulfoxaflor than those of S. miscanthi. These findings provide new insights into insecticide resistance development and rational sulfoxaflor use

Fitness Cost of the Field-Evolved Resistance to Sulfoxaflor and Multi-Insecticide Resistance of the Wheat Aphid <i>Sitobion miscanthi</i> (Takahashi)

Sulfoxaflor belongs to a new class of insecticides that is effective against many sap-feeding pests. In this study on Sitobion miscanthi (Takahashi) (i.e., the predominant wheat pest), a highly sulfoxaflor-resistant (SulR) population was obtained from a field. Its resistance to the other seven insecticides and its biological fitness were analyzed using a leaf-dip method and a two-sex life table approach, respectively. Compared with the relatively susceptible (SS) population, the SulR population was highly resistant to sulfoxaflor, with a relative insecticide resistance ratio (RR) of 199.8 and was moderately resistant to beta-cypermethrin (RR = 14.5) and bifenthrin (RR = 42.1) but exhibited low resistance to chlorpyrifos (RR = 5.7). Additionally, the SulR population had a relative fitness of 0.73, with a significantly prolonged developmental period as well as a lower survival rate and poorer reproductive performance than the SS population. In conclusion, our results suggest that S. miscanthi populations that are highly resistant to sulfoxaflor exist in the field. The possibility that insects may develop multi-resistance between sulfoxaflor and pyrethroids is a concern. Furthermore, the high sulfoxaflor resistance of S. miscanthi was accompanied by a considerable fitness cost. The study data may be useful for improving the rational use of insecticides and for exploring novel insecticide resistance mechanisms

Femtosecond-laser sharp shaping of millimeter-scale geometries with vertical sidewalls

As femtosecond (fs) laser machining advances from micro/nanoscale to macroscale, approaches capable of machining macroscale geometries that sustain micro/nanoscale precisions are in great demand. In this research, an fs laser sharp shaping approach was developed to address two key challenges in macroscale machining (i.e. defects on edges and tapered sidewalls). The evolution of edge sharpness (edge transition width) and sidewall tapers were systematically investigated through which the dilemma of simultaneously achieving sharp edges and vertical sidewalls were addressed. Through decreasing the angle of incidence (AOI) from 0 • to −5 • , the edge transition width could be reduced to below 10 µm but at the cost of increased sidewall tapers. Furthermore, by analyzing lateral and vertical ablation behaviors, a parameter-compensation strategy was developed by gradually decreasing the scanning diameters along depth and using optimal laser powers to produce non-tapered sidewalls. The fs laser ablation behaviors were precisely controlled and coordinated to optimize the parameter compensations in general manufacturing applications. The AOI control together with the parameter compensation provides a versatile solution to simultaneously achieve vertical sidewalls as well as sharp edges of entrances and exits for geometries of different shapes and dimensions. Both mm-scale diameters and depths were realized with dimensional precisions below 10 µm and surface roughness below 1 µm. This research establishes a novel strategy to finely control the fs laser machining process, enabling the fs laser applications in macroscale machining with micro/nanoscale precisions