Computing a Compact Spline Representation of the Medial Axis Transform of a 2D Shape

We present a full pipeline for computing the medial axis transform of an arbitrary 2D shape. The instability of the medial axis transform is overcome by a pruning algorithm guided by a user-defined Hausdorff distance threshold. The stable medial axis transform is then approximated by spline curves in 3D to produce a smooth and compact representation. These spline curves are computed by minimizing the approximation error between the input shape and the shape represented by the medial axis transform. Our results on various 2D shapes suggest that our method is practical and effective, and yields faithful and compact representations of medial axis transforms of 2D shapes.Comment: GMP14 (Geometric Modeling and Processing

Genomic prediction of drought tolerance during seedling stage in maize using low-cost molecular markers

Drought tolerance in maize is a complex and polygenic trait, especially in the seedling stage. In plant breeding, complex genetic traits can be improved by genomic selection (GS), which has become a practical and effective breeding tool. In the present study, a natural maize population named Northeast China core population (NCCP) consisting of 379 inbred lines were genotyped with diversity arrays technology (DArT) and genotyping-by-sequencing (GBS) platforms. Target traits of seedling emergence rate (ER), seedling plant height (SPH), and grain yield (GY) were evaluated under two natural drought stress environments in northeast China. Adequate genetic variations were observed for all the target traits, but they were divergent across environments. Similarly, the heritability of the target trait also varied across years and environments, the heritabilities in 2019 (0.88, 0.82, 0.85 for ER, SPH, GY) were higher than those in 2020 (0.65, 0.53, 0.33) and cross-2-years (0.32, 0.26, 0.33). In total, three marker datasets, 11,865 SilicoDArT markers obtained from the DArT-seq platform, 7837 SNPs obtained from the DArT-seq platform, and 91,003 SNPs obtained from the GBS platform, were used for GS analysis after quality control. The results of phylogenetic trees showed that broad genetic diversity existed in the NCCP population. Genomic prediction results showed that the average prediction accuracies estimated using the DArT SNP dataset under the two-fold cross-validation scheme were 0.27, 0.19, and 0.33, for ER, SPH, and GY, respectively. The result of SilicoDArT is close to the SNPs from DArT-seq, those were 0.26, 0.22, and 0.33. For the trait with lower heritability, the prediction accuracy can be improved using the dataset filtered by linkage disequilibrium. For the same trait, the prediction accuracies estimated with two DArT marker datasets were consistently higher than that estimated with the GBS SNP dataset under the same genotyping cost. The prediction accuracy was improved by controlling population structure and marker quality, even though the marker density was reduced. The prediction accuracies were improved by more than 30% using the significant-associated SNPs. Due to the complexity of drought tolerance under the natural stress environments, multiple years of data need to be accumulated to improve prediction accuracy by reducing genotype-by-environment interaction. Modeling genotype-by-environment interaction into genomic prediction needs to be further developed for improving drought tolerance in maize. The results obtained from the present study provides valuable pathway for improving drought tolerance in maize using GS

Compact representation of medial axis transform

Shape representation is a fundamental topic in geometric modeling, which is ubiquitous in computer graphics. Compared with the explicit and implicit shape representations, the medial representation possesses many advantages. It provides a comprehensive understanding of the shapes, since it gives direct access to both the boundaries and the interiors of the shapes. Although there are many medial axis computation algorithms which are able to filter noises in the medial axis, introduced by the perturbations on the boundary, and generate stable medial axis transforms of the input shapes, the medial axis transforms are usually represented in a redundant way with numerous primitives, which brings down the flexibility of the medial axis transform and hinders the popularity of the medial axis transform in geometric applications. In this thesis, we propose compact representations of the medial axis transforms for 2D and 3D shapes. The first part of this thesis proposes a full pipeline for computing the medial axis transform of an arbitrary 2D shape. The instability of the medial axis transform is overcome by a pruning algorithm guided by a user-defined Hausdorff distance threshold. The stable medial axis transform is then approximated by spline curves in the 3D space to produce a smooth and compact representation. These spline curves are computed by minimizing the approximation error between the input shape and the shape represented by the medial axis transform. The second part of this thesis discusses improvements on the existing medial axis computation algorithms, and represent the medial axis transform of a 3D shape in a compact way. The CVT remeshing framework is applied on an initial medial axis transform to promote the mesh quality of the medial axis. The simplified medial axis transform is then optimized by minimizing the approximation error of the shape reconstructed from the medial axis transform to the original 3D shape. Our results on various 2D and 3D shapes suggest that our method is practical and effective, and yields faithful and compact representations of medial axis transforms of 2D and 3D shapes.published_or_final_versionComputer ScienceDoctoralDoctor of Philosoph

Changes in sucrose metabolism in maize varieties with different cadmium sensitivities under cadmium stress.

Sucrose metabolism contributes to the growth and development of plants and helps plants cope with abiotic stresses, including stress from Cd. Many of these processes are not well-defined, including the mechanism underlying the response of sucrose metabolism to Cd stress. In this study, we investigated how sucrose metabolism in maize varieties with low (FY9) and high (SY33) sensitivities to Cd changed in response to different levels of Cd (0 (control), 5, 10, and 20 mg L-1 Cd). The results showed that photosynthesis was impaired, and the biomass decreased, in both varieties of maize at different Cd concentrations. Cd inhibited the activities of sucrose phosphate synthase (SPS) and sucrose synthase (SS) (sucrose synthesis), and stimulated the activities of acid invertase (AI) and SS (sucrose hydrolysis). The total soluble sugar contents were higher in the Cd-treated seedlings than in the control. Also, Cd concentrations in the shoots were higher in SY33 than in FY9, and in the roots were lower in SY33 than in FY9. The decreases in the photosynthetic rate, synthesis of photosynthetic products, enzyme activity in sucrose synthesis direction, and increases in activity in hydrolysis direction were more obvious in SY33 (the sensitive variety) than in FY9 (the tolerant variety), and more photosynthetic products were converted into soluble sugar in SY33 than in FY9 as the Cd stress increased. The transcript levels of the sugar transporter genes also differed between the two varieties at different concentrations of Cd. These results suggest that sucrose metabolism may be a secondary response to Cd additions, and that the Cd-sensitive variety used more carbohydrates to defend against Cd stress rather than to support growth than the Cd-tolerant variety

Research on Early Warning Mechanism and Model of Liver Cancer Rehabilitation Based on CS-SVM

Since the 20th century, cancer has become one of the main diseases threatening human health. Liver cancer is a malignant tumor with extremely high clinical morbidity and fatality rate and easy recurrence after surgery. Research on the postoperative recurrence time and recurrence location of patients with liver cancer has a crucial influence on the postoperative intervention of patients. Evaluation of the clinical manifestations of patients after liver cancer surgery is conducted according to medical knowledge or national standards to determine the main factors affecting liver cancer rehabilitation. In order to better study the mechanism of liver cancer recurrence, this paper uses CS-SVM to predict the recurrence time of liver cancer patients, so as to timely intervene the patients. There are five evaluation indicators which are basic indicators, immune indicators, microenvironment indicators, psychological indicators, and nutritional indicators, respectively. This paper collects the clinical evaluation data of postoperative follow-up visits for patients with liver cancer in a hospital, improves the parameter selection process of the support vector machine by using the search ability of the cuckoo algorithm, and establishes an algorithm-optimized prediction model of support vector machine for the prognosis of liver cancer to predict the location and approximate time of recurrence. According to the clinical evaluation data of patients with liver cancer after surgery, logistics regression, BP neural network, and other related methods are used to predict the prognosis of liver cancer patients after surgery. The prediction effects of several methods are compared, and the superiority of the model is discussed. At the end of this article, we conducted an empirical analysis on the clinical evaluation data of patients with liver cancer after surgery. For the collected samples of 776 liver cancer recurrences after surgery, the established liver cancer prognosis outcome prediction model was used to predict the recurrence time and recurrence location, respectively. The mean square error of recurrence time prediction is 9.2101, which is much smaller than the prediction mean square error of BP neural network of 177.9451; the prediction accuracy of recurrence location is 95.7%, which is much higher than the 63.14% of logistic regression. The empirical analysis results show that the improved support vector machine model based on cuckoo established in this paper can effectively predict the time and location of cancer recurrence

Modelling the potential distribution and shifts of three varieties of Stipa tianschanica in the eastern Eurasian Steppe under multiple climate change scenarios

The issue of climatic change and its strong influence on species distributions is currently of great interest in the field of biogeography. In this study, three varieties of Stipa tianschanica (S. tianschanica var. tianschanica, S. tianschanica var. gobica and S. tianschanica var. klemenzii), which are high-quality forage for local rangeland, were selected from the desert steppe of the Mongolian Plateau and Central Asia. Based on high-resolution environmental data for past, current and future climate scenarios, we modelled the suitable habitat in 6 periods for S. tianschanica var. tianschanica, S. tianschanica var. gobica and S. tianschanica var. klemenzii using MaxEnt and GIS technology; evaluated the importance of environmental factors in shaping their distribution; and identified distribution shifts under different climate change scenarios. Our results showed that temperature seasonality (bio04) and precipitation in October and November (pre10, pre11) were the most critical factors shaping the distribution of S. tianschanica var. tianschanica, while precipitation in June, August and December (pre06, pre08 and pre12) were the most critical for shaping the distributions of S. tianschanica var. gobica and S. tianschanica var. klemenzii. The suitable future habitat for the three species tended to increase under the RCP2.6 scenario and to decrease to varying degrees in the desert steppe in the RCP8.5 scenario in 2070 as global warming intensified. Overall, the size of the core distribution area and direction of the core distributional shifts are different for each species over the 6 periods. Our prediction showed that although these three varieties belong to the same species, their survival strategy and adaptability are different when faced with the same climate change scenarios. The projected spatial and temporal patterns of the distribution range shifts for S. tianschanica var. tianschanica, S. tianschanica var. gobica and S. tianschanica var. klemenzii will be useful references in developing desert steppe management and conservation strategies for these three ecologically important varieties. Keywords: Species distribution models (SDMs), Maximum entropy (MaxEnt), Stipa tianschanica var. tianschanica, Stipa tianschanica var. gobica, Stipa tianschanica var. klemenzii, Bioclimatic variables, Core size and shif

High-Fat Diet Induces Dysbiosis of Gastric Microbiota Prior to Gut Microbiota in Association With Metabolic Disorders in Mice

Accumulating evidence suggests that high-fat diet (HFD) induced metabolic disorders are associated with dysbiosis of gut microbiota. However, no study has explored the effect of HFD on the gastric microbiota. This study established the HFD animal model to determine the impact of HFD on the gastric microbiota and its relationship with the alterations of gut microbiota. A total of 40 male C57BL/6 mice were randomly allocated to receive a standard chow diet (CD) or HFD for 12 weeks (12CD group and 12HFD group) and 24 weeks (24CD group and 24HFD group) (n = 10 mice per group). Body weight and length were measured and Lee’s index was calculated at different time points. The insulin sensitivity and serum levels of metabolic parameters including blood glucose, insulin and lipid were also evaluated. The gastric mucosa and fecal microbiota of mice were characterized by 16S rRNA gene sequencing. The body weight was much heavier and the Lee’s index was higher in 24HFD group than 12HFD. The insulin resistance and serum level of lipid were increased in 24HFD group compared to 12HFD, indicating the aggravation of metabolic disorders as HFD went on. 16S rRNA gene sequencing showed dysbiosis of gastric microbiota with decreased community diversity while no significant alteration in gut microbiota after 12 weeks of HFD. The phyla Firmicutes and Proteobacteria tended to increase whereas Bacteroidetes and Verrucomicrobia decrease in the gastric microbiota of 12HFD mice compared to 12CD. Moreover, a remarkable reduction of bacteria especially Akkermansia muciniphila, which has beneficial effects on host metabolism, was observed firstly in the stomach of 12HFD group and then in the gut of 24HFD group, indicating the earlier alterations of microbiota in stomach than gut after HFD. We also found structural segregation of microbiota in the stomach as well as gut between 12HFD and 24HFD group, which is accompanied by the aggregation of metabolic disorders. These data suggest that HFD affects not only gut microbiota but also gastric microbiota and the disruption of microbial ecosystem in the digestive tract may play a part in the development and progression of metabolic diseases although molecular mechanism requires further investigation

Genome-Wide Investigation and Characterization of SWEET Gene Family with Focus on Their Evolution and Expression during Hormone and Abiotic Stress Response in Maize

The sugar will eventually be exported transporters (SWEET) family is an important group of transport carriers for carbon partitioning in plants and has important functions in growth, development, and abiotic stress tolerance. Although the SWEET family is an important sugar transporter, little is known of the functions of the SWEET family in maize (Zea mays), especially in response to abiotic stresses. To further explore the response pattern of maize SWEET to abiotic stress, a bioinformatics-based approach was used to predict and identify the maize SWEET gene (ZmSWEET) family. Twenty-four ZmSWEET genes were identified using the MaizeGDB database. Phylogenetic analysis resolved these twenty-four genes into four clades. One tandem and five segmental duplication events were identified, which played a major role in ZmSWEET family expansion. Synteny analysis provided insight into the evolutionary characteristics of the ZmSWEET genes with those of three graminaceous crop species. A heatmap showed that most ZmSWEET genes responded to at least one type of abiotic stress. By an abscisic acid signaling pathway, among which five genes were significantly induced under NaCl treatment, eight were obviously up-regulated under PEG treatment and five were up-regulated under Cd stress, revealing their potential functions in response to abiotic stress. These findings will help to explain the evolutionary links of the ZmSWEET family and contribute to future studies on the functional characteristics of ZmSWEET genes, and then improve abiotic stress tolerance in maize through molecular breeding

Role of 5-Hydroxytryptamine and Intestinal Flora on Depressive-Like Behavior Induced by Lead Exposure in Rats

Objective. To investigate the effects of 5-hydroxytryptamine (5-HT) and intestinal flora on depression-like behavior induced by lead exposure in rats. Methods. 30 healthy SPF adult male SD rats were randomly divided into control group and lead exposure group. The depression-like behavior of rats was detected. The blood, striatum, and intestinal tissue were collected. The lead content was detected by ICP-MS. The mRNA expressions of ChgA, TPH1, 5-HT, and 5-HT3R were tested by qRT-PCR. The content of 5HT was checked by HPLC-ECD. The content of 5-HT3R was detected by ELISA. The protein expressions of 5-HT, 5-HT3R, ChgA, and TPH were gauged by immunohistochemistry. Fecal samples were collected, and the composition of intestinal flora in experimental rats was analyzed by 16 s RNA metagene sequencing. Results. Lead exposure can greatly cause depression. The content of 5-HT in blood and striatum in the lead exposure group decreased, and the expression levels of 5-HT, 5-HT3 R, ChgA, and TPH in the intestine decreased distinctly. Compared with the control group, the distribution of a-polymorphism related indexes Simpson, Chao1, Shannon, and ACE in rats with depressive-like behavior after lead exposure was significantly increased; in the lead exposure group, there were 61 different operational taxonomic units (OUTs) in intestinal flora at the family level. Based on linear discriminant analysis, it was found that the key bacteria were Lactobacillaceae and Bifidobacteriaceae, and their abundance decreased evidently in the lead exposure group. Conclusion. Lead exposure improves depressive-like behavior by affecting intestinal flora and regulating neurotransmitter 5-HT through the intestinal-brain axis

Diversity-productivity relationships vary in response to increasing land-use intensity

Background and aims: Theoretical and experimental evidence, predominantly from temperate grasslands, demonstrates strong support for a positive relationship between biodiversity and ecosystem functioning. This relationship is likely to be affected by land use drivers that remove vegetation, and/or disturb the soil surface. Our study aimed to examine the links between land use intensity and plant richness, and potential effects on productivity and function. Methods: We examined the impact of mowing, grazing, and mowing plus grazing, on the relationship between plant diversity, and two measures of function; aboveground biomass and soil carbon. Our focus was on Eurasian grasslands, which support a high diversity of plant species, millions of people and their livelihoods, and where livestock grazing and mowing are predominant land uses. We used structural equation modelling to examine the effects of these land use drivers at 371 sites across 100,000 km2 of northern China. Results: Mown sites supported a greater number of plant species than sites that were either grazed, or grazed and mown. Increasing plant richness was associated with greater aboveground biomass and soil carbon when sites were either mown or grazed, but these relationships disappeared when the two land use drivers were combined. Relationships among plant diversity and two measures of function were maintained when we accounted for the spatial differences between sites. Conclusion: Our results demonstrate that additional land use pressure imposed when mowing and grazing are applied together can decouple the positive associations between plant richness and functions. An understanding of these potential effects is important if we are to adopt strategies, such as destocking or reduced mowing, to maintain diverse grassland ecosystems, and their services and functions