Thoughts and Targeted Initiatives for the Nurturing of Youth Football Reserve Talents in China

In order to strengthen the foundation for the cultivation of Chinese youth football reserve talents, a systematic review of the current ideas on the development of Chinese youth football reserve talents is conducted, and based on this, a targeted response is derived from it. The study concludes that the cultivation of Chinese youth football reserve talents should be based on the country and the world in a hierarchical and directional manner, with emphasis on the integration of the excellent Chinese traditional culture at the primary school level and the absorption of outstanding foreign achievements and experience at the secondary school level, and the promotion of three types of policy tools, namely the supply side, the demand side and the environment side, to form a protective synergy for the cultivation of youth football reserve talents, so as to build an effective and long-term development strategy that will benefit the present and the future. The aim is to speed up the construction of a reserve pool of Chinese youth football talents, improve the international competitiveness and influence of Chinese football, and contribute to the early realisation of the Chinese football dream

Learning Explicit Contact for Implicit Reconstruction of Hand-held Objects from Monocular Images

Reconstructing hand-held objects from monocular RGB images is an appealing yet challenging task. In this task, contacts between hands and objects provide important cues for recovering the 3D geometry of the hand-held objects. Though recent works have employed implicit functions to achieve impressive progress, they ignore formulating contacts in their frameworks, which results in producing less realistic object meshes. In this work, we explore how to model contacts in an explicit way to benefit the implicit reconstruction of hand-held objects. Our method consists of two components: explicit contact prediction and implicit shape reconstruction. In the first part, we propose a new subtask of directly estimating 3D hand-object contacts from a single image. The part-level and vertex-level graph-based transformers are cascaded and jointly learned in a coarse-to-fine manner for more accurate contact probabilities. In the second part, we introduce a novel method to diffuse estimated contact states from the hand mesh surface to nearby 3D space and leverage diffused contact probabilities to construct the implicit neural representation for the manipulated object. Benefiting from estimating the interaction patterns between the hand and the object, our method can reconstruct more realistic object meshes, especially for object parts that are in contact with hands. Extensive experiments on challenging benchmarks show that the proposed method outperforms the current state of the arts by a great margin.Comment: 17 pages, 8 figure

Visual-Kinematics Graph Learning for Procedure-agnostic Instrument Tip Segmentation in Robotic Surgeries

Accurate segmentation of surgical instrument tip is an important task for enabling downstream applications in robotic surgery, such as surgical skill assessment, tool-tissue interaction and deformation modeling, as well as surgical autonomy. However, this task is very challenging due to the small sizes of surgical instrument tips, and significant variance of surgical scenes across different procedures. Although much effort has been made on visual-based methods, existing segmentation models still suffer from low robustness thus not usable in practice. Fortunately, kinematics data from the robotic system can provide reliable prior for instrument location, which is consistent regardless of different surgery types. To make use of such multi-modal information, we propose a novel visual-kinematics graph learning framework to accurately segment the instrument tip given various surgical procedures. Specifically, a graph learning framework is proposed to encode relational features of instrument parts from both image and kinematics. Next, a cross-modal contrastive loss is designed to incorporate robust geometric prior from kinematics to image for tip segmentation. We have conducted experiments on a private paired visual-kinematics dataset including multiple procedures, i.e., prostatectomy, total mesorectal excision, fundoplication and distal gastrectomy on cadaver, and distal gastrectomy on porcine. The leave-one-procedure-out cross validation demonstrated that our proposed multi-modal segmentation method significantly outperformed current image-based state-of-the-art approaches, exceeding averagely 11.2% on Dice.Comment: Accepted to IROS 202

ClickINC: In-network Computing as a Service in Heterogeneous Programmable Data-center Networks

In-Network Computing (INC) has found many applications for performance boosts or cost reduction. However, given heterogeneous devices, diverse applications, and multi-path network typologies, it is cumbersome and error-prone for application developers to effectively utilize the available network resources and gain predictable benefits without impeding normal network functions. Previous work is oriented to network operators more than application developers. We develop ClickINC to streamline the INC programming and deployment using a unified and automated workflow. ClickINC provides INC developers a modular programming abstractions, without concerning to the states of the devices and the network topology. We describe the ClickINC framework, model, language, workflow, and corresponding algorithms. Experiments on both an emulator and a prototype system demonstrate its feasibility and benefits

Metabolism and transcriptome profiling provides insight into the genes and transcription factors involved in monoterpene biosynthesis of borneol chemotype of Cinnamomum camphora induced by mechanical damage

Background The borneol chemotype of Cinnamomum camphora (BCC), a monoterpene-rich woody plant species, is the sole source prescribed by the Chinese Pharmacopoeia for the production of natural D-borneol, a major monoterpene in BCC used for millennia as a topical analgesic in China. Nevertheless, the possible gene-regulatory roles of transcription factors (TFs) in BCC’s monoterpenoid biosynthesis remained unknown. Here, a joint analysis of the transcriptome and terpenoid metabolome of BCC induced by mechanical damage (MD) was used to comprehensively explore the interaction between TFs and terpene synthase (TPS) unigenes that might participate in monoterpene biosynthesis in BCC. Results Gas chromatography–mass spectrometry analysis detected 14 monoterpenes and seven sesquiterpenes. All but two monoterpenes underwent a significantly increased accumulation after the MD treatment. RNA sequencing data revealed that 10 TPS, 82 MYB, 70 AP2/ERF, 38 BHLH, 31 WRKY, and 29 bZIP unigenes responded to the MD treatment. A correlation analysis revealed that three monoterpene synthase genes (CcTPS1, CcTPS3, CcTPS4) highly correlated with multiple monoterpenes, namely D-borneol, camphor, and bornyl acetate, which could be responsible for monoterpenoid biosynthesis in BCC. Furthermore, five WRKY, 15 MYB, 10 ERF/AP2, five bZIP, and two BHLH genes had strong, positive correlations with CcTPS1 or CcTPS4, judging by their high coefficient values (R2 > 0.8). The bioinformatics results were verified by quantitative real-time PCR. Conclusion This study provides insight into the genes involved in the biosynthesis and regulation of monoterpene in BCC and thus provides a pool of candidate genes for future mechanistic analyses of how monoterpenes accumulate in BCC

A feature optimization study based on a diabetes risk questionnaire

IntroductionThe prevalence of diabetes, a common chronic disease, has shown a gradual increase, posing substantial burdens on both society and individuals. In order to enhance the effectiveness of diabetes risk prediction questionnaires, optimize the selection of characteristic variables, and raise awareness of diabetes risk among residents, this study utilizes survey data obtained from the risk factor monitoring system of the Centers for Disease Control and Prevention in the United States.MethodsFollowing univariate analysis and meticulous screening, a more refined dataset was constructed. This dataset underwent preprocessing steps, including data distribution standardization, the application of the Synthetic Minority Oversampling Technique (SMOTE) in combination with the Round function for equilibration, and data standardization. Subsequently, machine learning (ML) techniques were employed, utilizing enumerated feature variables to evaluate the strength of the correlation among diabetes risk factors.ResultsThe research findings effectively delineated the ranking of characteristic variables that significantly influence the risk of diabetes. Obesity emerges as the most impactful factor, overshadowing other risk factors. Additionally, psychological factors, advanced age, high cholesterol, high blood pressure, alcohol abuse, coronary heart disease or myocardial infarction, mobility difficulties, and low family income exhibit correlations with diabetes risk to varying degrees.DiscussionThe experimental data in this study illustrate that, while maintaining comparable accuracy, optimization of questionnaire variables and the number of questions can significantly enhance efficiency for subsequent follow-up and precise diabetes prevention. Moreover, the research methods employed in this study offer valuable insights into studying the risk correlation of other diseases, while the research results contribute to heightened societal awareness of populations at elevated risk of diabetes

The evolving early Cambrian Ocean of the Nanhua Basin, South China

The early Cambrian was an important period of environmental change and biological evolution, however, redox states and chemical features of the coeval ocean are still matters of debate. The Nanhua Basin in South China was connected to an open sea during this period, sedimentary successions deposited in the basin are thus ideal for paleoclimatic and paleoecologic reconstruction. In the present study, early Cambrian phosphorites from the Meishucun and Gezhongwu sections in SW China, and black shales from the Zhajin section in SE China, were investigated to decipher the circulation patterns of both the shallow and deep oceans. The phosphorite successions are divided into lower and upper units by a series of ~536 Ma tuff layers. In the Meishucun section (nearshore), rocks from the lower unit have abundant cyanobacterial-like microfossils, radial francolite aggregates and kerogen-like REE patterns, suggesting the early Cambrian phosphogenesis was intimately linked to proliferation of primary producers. Rocks from the upper unit of the Meishucun section have distinctly higher Zn, Cd and Pb concentrations than those in the lower unit, but are similar to those of the offshore phosphorites in the Gezhongwu section. Negative δ13Ccar excursions present in the upper phosphorite unit indicates extensive upwelling aftermath the ~536 Ma volcanisms was attributed to the chemical changes of the shallow ocean. Black shales in the Zhajin section deposited in the deep basin and have extremely high V concentrations and low δ98Mo values. An Fe-oxide shuttle may have developed in the depositional site to accumulate light Mo isotope. Substantial V enrichment in early Cambrian black shales elsewhere in the world indicates the presence of large marine vanadium reservoirs within the well- oxygenated ocean. Negative correlation between V concentrations and δ98Mo values reflects a significant burial of Fe-oxide during the early Cambrian which may have resulted in the termination of the ferruginous ocean existed since the early Archean. Authigenic anatases in organic-rich Zhajin black shales, indicates that Ti was migrated by hydrocarbon-rich liquids in organic rich shales during diagenesis. Methane generated from black shales may have consumed sulfates in the deep ocean during the Middle Cambrian, and caused global warming and mass extinction. Low δ34S values of carbonate-associated sulfates (CAS) but high δ34S values of disseminated pyrites from carbonaceous carbonates in the Zhajin area suggest sulfur stratification of the Nanhua Basin, in which the surface water had low δ34S but high SO42- and the bottom water had high δ34S but low SO42-. In general, during the early Cambrian, the shallow ocean was of high bio-productivity and was chemically modified by ocean upwelling after ~ 536 Ma. Proliferation of primary producers and intensified ocean circulation contributed to progressively oxygenation of the deep ocean. Post-depositional diagenesis of early Cambrian black shales released abundant methane to the ocean during the middle Cambrian, leading to oceanic S-stratification and global warming.published_or_final_versionEarth SciencesDoctoralDoctor of Philosoph