SK-Net: Deep Learning on Point Cloud via End-to-end Discovery of Spatial Keypoints

Since the PointNet was proposed, deep learning on point cloud has been the concentration of intense 3D research. However, existing point-based methods usually are not adequate to extract the local features and the spatial pattern of a point cloud for further shape understanding. This paper presents an end-to-end framework, SK-Net, to jointly optimize the inference of spatial keypoint with the learning of feature representation of a point cloud for a specific point cloud task. One key process of SK-Net is the generation of spatial keypoints (Skeypoints). It is jointly conducted by two proposed regulating losses and a task objective function without knowledge of Skeypoint location annotations and proposals. Specifically, our Skeypoints are not sensitive to the location consistency but are acutely aware of shape. Another key process of SK-Net is the extraction of the local structure of Skeypoints (detail feature) and the local spatial pattern of normalized Skeypoints (pattern feature). This process generates a comprehensive representation, pattern-detail (PD) feature, which comprises the local detail information of a point cloud and reveals its spatial pattern through the part district reconstruction on normalized Skeypoints. Consequently, our network is prompted to effectively understand the correlation between different regions of a point cloud and integrate contextual information of the point cloud. In point cloud tasks, such as classification and segmentation, our proposed method performs better than or comparable with the state-of-the-art approaches. We also present an ablation study to demonstrate the advantages of SK-Net

The quality difference in five oolong tea accessions under different planting management patterns in south Fujian of China

IntroductionOolong tea, celebrated for its significance in Chinese tea culture, was the subject of investigation in this study.MethodsFive varieties of Minnan oolong tea were sampled, each cultivated under two distinct management approaches: conventional management and natural growth methods. The study aimed to discern variations in sensory attributes, encompassing appearance and liquor color, alongside the analysis of chemical composition.Results and discussionThe results indicated that oolong tea cultivated through conventional manual management generally exhibited qualities in terms of shape and foliage appearance, in contrast to those grown naturally. However, naturally grown oolong tea tended to exhibit more favorable aroma and taste profiles compared to conventionally managed counterparts. Furthermore, the content of water extract, amino acids, polyphenols, caffeine, and other pivotal chemical constituents were typically higher in naturally grown tea varieties compared to conventionally managed ones. Conversely, catechin content was found to be more abundant in traditionally managed bushes than in those grown naturally. These findings emphasize the significance of implementing appropriate natural growth management practices to enhance the quality of Minnan oolong tea and maintain ecological sustainability

Stable and antisintering tungsten carbides with controllable active phase for selective cleavage of aryl ether C-O bonds

Transition-metal carbides are important materials in heterogeneous catalysis. It remains challenging yet attractive in nanoscience to construct the active phase of carbide catalysts in a controllable manner and keep a sintering-resistant property in redox reactions, especially hydroprocessing. In this work, an integrated strategy was presented to synthesize stable and well-defined tungsten carbide nanoparticles (NPs) by assembling the metal precursor onto carbon nanotubes (CNTs), wrapping a thin polymeric layer, and following a controlled carburization. The polymer served as a soft carbon source to modulate the metal/carbon ratio in the carbides and introduced amorphous carbons around the carbides to prevent the NPs from sintering. The as-built p-WxC/CNT displayed high stability in the hydrogenolysis of aryl ether C–O bond in guaiacol for more than 150 h. Its activity was more than two and six times higher than those prepared via typical temperature-programmed reduction with gaseous carbon (WxC/CNT-TPR) and carbothermal reduction with intrinsic carbon support (WxC/CNT-CTR), respectively. Our p-WxC/CNT catalyst also achieved high efficiency for selective cleavage of the aryl ether C–O bonds in lignin-derived aromatic ethers, including anisole, dimethoxylphenol, and diphenyl ether, with a robust lifespan

Rail Optimization of Noncircular Curve of Crane Turning Based on Quasiquartic Bezier Curve with Three Shape Parameters

In order to solve the problems of rail gnawing and jamming during turning of rail crane, a noncircular curve scheme of the crane based on Bezier curve is proposed. In the scheme, the quasiquartic Bezier curve with three shape parameters is chosen as the turning curve of the inner rail. According to the single-wheel and multiwheel situation of the crane, the tracks of the front and rear points on the outer side are calculated through the geometric relationship of the traveling mechanism of the crane cart. Taking the minimum deviation of the front and back points as the objective function of optimization, the optimal parameters of Bezier curve are searched by the multistart point heuristic global optimization algorithm, and the outer rail trajectory is fitted by Hermite interpolation. The calculation results show that the maximum deviation of the front and rear points on the outside of the crane during the turning process decreases significantly when the quartic Bezier curve is used as the turning track compared with the traditional circular turning track. When the quasiquartic Bezier curve with three shape parameters is used as the inner rail, the deviation can be further reduced by adjusting the three parameters. In addition, it is also analyzed the specific influence of turning parameters on the deviation. Finally, ADAMS is used to carry out dynamic simulation experiment and demonstrate the calculation

The Final Model Building for the Supersymmetric Pati-Salam Models from Intersecting D6-Branes

All the possible three-family ${\cal N}=1$ supersymmetric Pati-Salam models constructed with intersecting D6-branes from Type IIA orientifolds on $T^6/(\mathbb{Z}_2\times \mathbb{Z}_2)$ are recently presented in arXiv: 2112.09632. Taking models with largest wrapping number $5$ and approximate gauge coupling unification at GUT scale as examples, we show string scale gauge coupling unification can be realized through two-loop renormalization group equation running by introducing seven pairs of vector-like particles from ${\cal N}=2$ sector. The number of these introduced vector-like particles are fully determined by the brane intersection numbers while there are two D6-brane parallel to each other along one two-torus. We expect this will solve the gauge coupling unification problem in the generic intersecting brane worlds by introducing vector-like particles that naturally included in the ${\cal N}=2$ sector.Comment: 3 figure

A Novel Intelligent Leakage Monitoring-Warning System for Sustainable Rural Drinking Water Supply

Leakage occurs in rural water supply pipelines very often and its locating is quite demanding even for specialists, which could result in a poor operation efficiency of rural water supply projects and thus a low rural water supply guarantee rate. In view of this problem, the detection of leakage, as well as its prediction, is of great significance for the operation, maintenance, and administration of rural water supply projects. The traditional monitoring-warning systems for urban water distribution networks cannot be applied to rural water distribution networks, due to various limitations. Meanwhile, as with the traditional models, most new approaches based on machine learning such as the artificial neural network (ANN), probabilistic neural network (PNN), and statistical learning theory (SLT) do not fit rural water distribution networks much better, being unable to converge and force high-accuracy results with small sample sizes, which is a crucial demand to meet when dealing with rural water supply pipelines. Extreme gradient boosting (XGBoost), a model that specializes in small sample sizes and has a high generalization ability, was applied to a rural water supply project in Ningxia, China. In this study, a monitoring-warning system featuring both leakage locating and quantity estimation was established based on XGBoost. The accuracy and F1-score of the leakage locating model were 95% and 93%, respectively, while those of the leakage quantity model reached 96% and 97%, respectively. Furthermore, the pressure of monitoring stations could be obtained through the feature importance analysis enabled by XGBoost, which is essential for leakage warning. These results indicate that this system based on XGBoost could be a promising solution to the leakage issue in rural water supply projects, as a great inspiration for future developments in intelligent monitoring-warning systems, thus providing reliable approaches for the sustainable development of rural drinking water supply projects

Supercritical Water-induced Lignin Decomposition Reactions: A Structural and Quantitative Study

The use of supercritical water for the decomposition of lignin and evaluation of its influence on lignin decomposition and conversion to various products was the thrust of the current study. Poplar alkali lignin (AL), corncob-to-xylitol residue lignin (XRL), and cornstalk-to-ethanol residue lignin (ERL) were the lignin species studied because they constitute the main residual lignins available in the biomass refinery industry. The lignins were characterized by elementary analysis, Fourier transform infrared spectrometry (FT-IR), phosphorus nuclear magnetic resonance (31P-NMR), and X-ray diffraction (XRD), and their hydrothermal depolymerization products were analyzed by gas chromatography-mass spectrometer (GC–MS). The results showed that the residual lignin is a potential source for valuable aromatics. The XRL had the best total phenolics yield, 140 mg/g, while AL had the lowest, 90 mg/g. The maximum yields of phenol (28.94 mg/g) and 4-ethylphenol (36.21 mg/g) were obtained from XRL depolymerization at 375 °C for 30 min, and the optimal yields of guaiacol (14.34 mg/g) and 2,6-dimethoxyphenol (15.67 mg/g) were achieved by AL at 375 °C for 30 min. The information here provides some insights toward developing selective biorefinery methods for lignin-to-organic products conversion processes

Revealing Genetic Diversity and Population Structure of Endangered Altay White-Headed Cattle Population Using 100 k SNP Markers

Understanding the genetic basis of native cattle populations that have adapted to the local environment is of great significance for formulating appropriate strategies and programs for genetic improvement and protection. Therefore, it is necessary to understand the genetic diversity and population structure of Altay white-headed cattle so as to meet the current production needs under various environments, carry out continuous genetic improvement, and promote rapid adaptation to changing environments and breeding objectives. A total of 46 individual samples of endangered Xinjiang Altay white-headed cattle were collected in this study, including nine bulls and 37 cows. To collect genotype data, 100 k SNP markers were used, and then studies of genetic diversity, genetic structure, inbreeding degree, and family analysis were carried out. A total of 101,220 SNP loci were detected, and the genotype detection rate for individuals was ≥90%. There were 85,993 SNP loci that passed quality control, of which 93.5% were polymorphic. The average effective allele number was 0.036, the Polymorphism Information Content was 0.304 and the minimum allele frequency was 0.309, the average observed heterozygosity was 0.413, and the average expected heterozygosity was 0.403. The average genetic distance of Idengtical By State (IBS) was 0.3090, there were 461 ROH (genome-length homozygous fragments), 76.1% of which were between 1 and 5 MB in length, and the average inbreeding coefficient was 0.016. The 46 Altay white-headed cattle were divided into their families, and the individual numbers of each family were obviously different. To sum up, the Altay white-headed cattle conservation population had low heterozygosity, a high inbreeding degree, few families, and large differences in the number of individuals in each family, which can easily cause a loss of genetic diversity. In the follow-up seed conservation process, seed selection and matching should be carried out according to the divided families to ensure the long-term protection of Altay white-headed cattle genetic resources

A novel approach for characterizing variations in serum peptides in rheumatic heart disease

Background & objectives: Acute rheumatic fever and rheumatic heart disease (RHD) are important public health problems in developing countries. In this study, peptidomic analyses on RHD patients and healthy individuals were performed to characterize variations in serum peptide levels using label-free quantitation approaches. Methods: Blood samples were obtained from 160 healthy controls and 160 RHD patients. Of the 448 identified peptides, 272 were analyzed by two label-free mass spectrometry methods, the spectral count and spectral index. Results: There were 38 proteins and 95 peptides with significant (adjusted P<0.001) differences in the abundance of peptides between healthy controls and RHD patients, including multiple peptides derived from histone H2B, villin-like protein, complement C4-B and motile sperm domain containing protein-2. The levels of 10 peptides were upregulated, and 85 peptides were downregulated in patients compared to controls. In addition, in patients, the levels of four proteins were upregulated and 34 were downregulated compared to controls. Interpretation & conclusions: This study shows that detection of significant changes in serum peptides reflects the difference between RHD patients and healthy controls. This label-free method may be helpful for clinicians to treat RHD patients during the perioperative period

Analysis of the Genetic Relationship and Inbreeding Coefficient of the Hetian Qing Donkey through a Simplified Genome Sequencing Technology

The Hetian Qing donkey is an excellent local donkey breed in Xinjiang. It is of great significance to accelerate breeding and the speed of breeding and rejuvenation, as well as to understand the genetic basis of the strategies and population. This study collected a total of 4 male donkeys and 28 female donkeys. It then obtained genotype data through Simplified Genomic Sequencing (GBS) technology for data analysis. The results detected a total of 55,399 SNP loci, and the genotype detection rate of individuals was ≥90%. A total of 45,557 SNP loci were identified through quality control, of which 95.5% were polymorphic. The average minimum allele frequency was 0.250. The average observed heterozygosity was 0.347. The average expected heterozygosity was 0.340. The average IBS (state homologous) genetic distance was 0.268. ROH: 49 (homozygous fragments), with 73.47% of the length between 1 and 5 Mb. The average per-strip ROH length was 1.75 Mb. The mean inbreeding coefficient was 0.003. The 32 Hetian green donkeys could be divided into six families. The number of individuals in each family is significant. To sum up, the Hetian Qing donkey population has low heterozygosity, few families, and large differences in the number of individuals in each family, which can easily cause a loss of genetic diversity. In the subsequent process of seed protection, seed selection should be conducted according to the divided pedigree to ensure the long-term protection of the genetic resources of Hetian green donkeys