RDMNet: Reliable Dense Matching Based Point Cloud Registration for Autonomous Driving

Point cloud registration is an important task in robotics and autonomous driving to estimate the ego-motion of the vehicle. Recent advances following the coarse-to-fine manner show promising potential in point cloud registration. However, existing methods rely on good superpoint correspondences, which are hard to be obtained reliably and efficiently, thus resulting in less robust and accurate point cloud registration. In this paper, we propose a novel network, named RDMNet, to find dense point correspondences coarse-to-fine and improve final pose estimation based on such reliable correspondences. Our RDMNet uses a devised 3D-RoFormer mechanism to first extract distinctive superpoints and generates reliable superpoints matches between two point clouds. The proposed 3D-RoFormer fuses 3D position information into the transformer network, efficiently exploiting point clouds' contextual and geometric information to generate robust superpoint correspondences. RDMNet then propagates the sparse superpoints matches to dense point matches using the neighborhood information for accurate point cloud registration. We extensively evaluate our method on multiple datasets from different environments. The experimental results demonstrate that our method outperforms existing state-of-the-art approaches in all tested datasets with a strong generalization ability.Comment: 11 pages, 9 figure

LKCA: Large Kernel Convolutional Attention

We revisit the relationship between attention mechanisms and large kernel ConvNets in visual transformers and propose a new spatial attention named Large Kernel Convolutional Attention (LKCA). It simplifies the attention operation by replacing it with a single large kernel convolution. LKCA combines the advantages of convolutional neural networks and visual transformers, possessing a large receptive field, locality, and parameter sharing. We explained the superiority of LKCA from both convolution and attention perspectives, providing equivalent code implementations for each view. Experiments confirm that LKCA implemented from both the convolutional and attention perspectives exhibit equivalent performance. We extensively experimented with the LKCA variant of ViT in both classification and segmentation tasks. The experiments demonstrated that LKCA exhibits competitive performance in visual tasks. Our code will be made publicly available at https://github.com/CatworldLee/LKCA

Study on induction hardening performance of 34CrNi3MoA steel crankshaft

The evolution of the temperature field, microstructure field, and residual stress field of a 34CrNi3MoA steel marine diesel engine crankshaft during medium-frequency induction hardening was studied based on an electromagnetic-thermal-transformation-stress coupled numerical model, which considers the effect of internal stress induced by transformation induced plasticity on residual stress. Using the equal conversion rate method, the austenitizing region of the crankshaft was determined during the induction heating stage. In the quenching stage, the parameters of the phase transformation model are derived from the continuous heating expansion curve and the continuous cooling transformation curve, and the phase transformation kinetics equation is used to analyze the phase transformation process of the crankshaft. The results indicate that extending the heating time can enhance the uniformity of the surface temperature of the crankshaft and the thickness of the hardened layer. The simulation results are validated by measurements of hardened layer, hardness and residual stress, and the simulation results are in good agreement with the experimental results

Impacts of climate change, population growth, and power sector decarbonization on urban building energy use

Climate, technologies, and socio-economic changes will influence future building energy use in cities. However, current low-resolution regional and state-level analyses are insufficient to reliably assist city-level decision-making. Here we estimate mid-century hourly building energy consumption in 277 U.S. urban areas using a bottom-up approach. The projected future climate change results in heterogeneous changes in energy use intensity (EUI) among urban areas, particularly under higher warming scenarios, with on average 10.1–37.7% increases in the frequency of peak building electricity EUI but over 110% increases in some cities. For each 1 °C of warming, the mean city-scale space-conditioning EUI experiences an average increase/decrease of ~14%/ ~ 10% for space cooling/heating. Heterogeneous city-scale building source energy use changes are primarily driven by population and power sector changes, on average ranging from –9% to 40% with consistent south–north gradients under different scenarios. Across the scenarios considered here, the changes in city-scale building source energy use, when averaged over all urban areas, are as follows: –2.5% to –2.0% due to climate change, 7.3% to 52.2% due to population growth, and –17.1% to –8.9% due to power sector decarbonization. Our findings underscore the necessity of considering intercity heterogeneity when developing sustainable and resilient urban energy systems.<br/

Genome-Wide Association Study for Milk Protein Composition Traits in a Chinese Holstein Population Using a Single-Step Approach

Genome-wide association studies (GWASs) have been widely used to determine the genetic architecture of quantitative traits in dairy cattle. In this study, with the aim of identifying candidate genes that affect milk protein composition traits, we conducted a GWAS for nine such traits (αs1-casein, αs2-casein, β-casein, κ-casein, α-lactalbumin, β-lactoglobulin, casein index, protein percentage, and protein yield) in 614 Chinese Holstein cows using a single-step strategy. We used the Illumina BovineSNP50 Bead chip and imputed genotypes from high-density single-nucleotide polymorphisms (SNPs) ranging from 50 to 777 K, and subsequent to genotype imputation and quality control, we screened a total of 586,304 informative high-quality SNPs. Phenotypic observations for six major milk proteins (αs1-casein, αs2-casein, β-casein, κ-casein, α-lactalbumin, and β-lactoglobulin) were evaluated as weight proportions of the total protein fraction (wt/wt%) using a commercial enzyme-linked immunosorbent assay kit. Informative windows comprising five adjacent SNPs explaining no &lt; 0.5% of the genomic variance per window were selected for gene annotation and gene network and pathway analyses. Gene network analysis performed using the STRING Genomics 10.0 database revealed a co-expression network comprising 46 interactions among 62 of the most plausible candidate genes. A total of 178 genomic windows and 194 SNPs on 24 bovine autosomes were significantly associated with milk protein composition or protein percentage. Regions affecting milk protein composition traits were mainly observed on chromosomes BTA 1, 6, 11, 13, 14, and 18. Of these, several windows were close to or within the CSN1S1, CSN1S2, CSN2, CSN3, LAP3, DGAT1, RPL8, and HSF1 genes, which have well-known effects on milk protein composition traits of dairy cattle. Taken together with previously reported quantitative trait loci and the biological functions of the identified genes, we propose 19 novel candidate genes affecting milk protein composition traits: ARL6, SST, EHHADH, PCDHB4, PCDHB6, PCDHB7, PCDHB16, SLC36A2, GALNT14, FPGS, LARP4B, IDI1, COG4, FUK, WDR62, CLIP3, SLC25A21, IL5RA, and ACADSB. Our findings provide important insights into milk protein synthesis and indicate potential targets for improving milk quality

Preoperative computed tomography-based tumoral radiomic features prediction for overall survival in resectable non-small cell lung cancer

ObjectivesThe purpose of this study was to evaluate whether preoperative radiomics features could meliorate risk stratification for the overall survival (OS) of non-small cell lung cancer (NSCLC) patients.MethodsAfter rigorous screening, the 208 NSCLC patients without any pre-operative adjuvant therapy were eventually enrolled. We segmented the 3D volume of interest (VOI) based on malignant lesion of computed tomography (CT) imaging and extracted 1542 radiomics features. Interclass correlation coefficients (ICC) and LASSO Cox regression analysis were utilized to perform feature selection and radiomics model building. In the model evaluation phase, we carried out stratified analysis, receiver operating characteristic (ROC) curve, concordance index (C-index), and decision curve analysis (DCA). In addition, integrating the clinicopathological trait and radiomics score, we developed a nomogram to predict the OS at 1 year, 2 years, and 3 years, respectively.ResultsSix radiomics features, including gradient_glcm_InverseVariance, logarithm_firstorder_Median, logarithm_firstorder_RobustMeanAbsoluteDeviation, square_gldm_LargeDependenceEmphasis, wavelet_HLL_firstorder_Kurtosis, and wavelet_LLL_firstorder_Maximum, were selected to construct the radiomics signature, whose areas under the curve (AUCs) for 3-year prediction reached 0.857 in the training set (n=146) and 0.871 in the testing set (n=62). The results of multivariate analysis revealed that the radiomics score, radiological sign, and N stage were independent prognostic factors in NSCLC. Moreover, compared with clinical factors and the separate radiomics model, the established nomogram exhibited a better performance in predicting 3-year OS.ConclusionsOur radiomics model may provide a promising non-invasive approach for preoperative risk stratification and personalized postoperative surveillance for resectable NSCLC patients

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals &lt;1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Online Deformation Measurement of Laser Repair Substrate Based on Orthogonal Sampling Moiré

As an important branch of metal additive manufacturing, laser repair has broad application potential in the aerospace, automobile and ship building industries. In the process of laser repair, metal powder is introduced into the laser action area and heated to a molten state to form a molten pool, which moves on the component surface according to the preset scanning path. Additionally, the temperature of the repaired component changes dynamically with the movement of the molten pool, leading to the time-evolution of stress and deformation. Therefore, online deformation measurement for the repair process is essential for understanding the evolution mechanism of stress and deformation in laser repair. However, extreme environments such as ultra-high temperature, strong laser radiation and metal powder splashing exist during the laser repair, which bring great challenges for dynamic optical measurement. In this paper, an online deformation measurement system based on orthogonal sampling moiré for laser repair environment is developed, which is applied to measure the deformation field of the metal substrate during laser repair. In the measurement, laser repair is performed on a cantilever beam substrate and orthogonal grating is prepared on the side surface of the cantilever beam. The real-time grating images are recorded by an optical imaging system, in which a group of filter components are used to obtain optical images with high signal-to-noise ratio. Finally, the deformation field of the substrate during laser repair is calculated with the orthogonal sampling moiré method. The results show that the scanning path in the repair process has a significant influence on the distribution of residual deformation, which offers reference for optimizing parameters of laser repair

The efficacy and safety of Xuefu Zhuyu Decoction Combined Mifepristone in the treatment of Uterine leiomyoma：A protocol systematic review and meta-analysis

Abstract Background Uterine leiomyoma (UL) is a common severe gynecological issue. In China, Xuefu Zhuyu Decoction (XFZYD), combined with Mifepristone, is widely used in the treatment of UL. However, their combined effectiveness and safety for this purpose have not yet been explored. Objective This systematic review aims to evaluate the effectiveness and safety of XFZYD combined with Mifepristone as a method of treatment for UL. Methods We searched the following 7 databases: 3 English medical databases (PubMed, EMBASE, Cochrane Library), and 4 Chinese medical databases (Chinese Biomedical Literature Database (CBM), Chinese National Knowledge Infrastructure (CNKI), Chinese Scientific Journal Database (VIP), and the Wanfang database). The primary outcome was the effect of XFZYD combined with Mifepristone on the effective rate, uterine leiomyoma volume (ULV), and uterine volume (UV) of uterine leiomyoma. Bias risk was assessed using the Cochrane risk of bias tool. The software RevMan5 was used to evaluate the quality of the included studies and process the data. Results: This study will evaluate the efficacy and safety of XFZYD combined with Mifepristone in the treatment of uterine fibroids by evaluating the effective rate, Uterine Leiomyoma volume, and uterine volume, the incidence of estradiol, luteinizing hormone, and other indicators. Conclusion: This study will provide reliable evidence-based evidence for Xuefu Zhuyu Decoction Combined with Mifepristone in the treatment of uterine fibroids

A Novel Procedure to Measure Membrane Penetration of Coarse Granular Materials

The membrane penetration effect will significantly influence the measurement of specimen volume deformation in the triaxial test. This paper presents a novel procedure for measuring and correcting the membrane penetration of rubber by using a newly developed multiscale triaxial apparatus. A series of triaxial tests on coarse granular materials was conducted with different specimen diameters, and it is found that the proportion of volume change due to membrane penetration decreases linearly with increasing specimen diameter. To reduce the margin of error induced by membrane penetration in the triaxial test, it is recommended to use specimens of larger size. Such a method can facilitate the correction and estimation of the membrane penetration effect of coarse granular materials