130 research outputs found
Modiff: Action-Conditioned 3D Motion Generation with Denoising Diffusion Probabilistic Models
Diffusion-based generative models have recently emerged as powerful solutions
for high-quality synthesis in multiple domains. Leveraging the bidirectional
Markov chains, diffusion probabilistic models generate samples by inferring the
reversed Markov chain based on the learned distribution mapping at the forward
diffusion process. In this work, we propose Modiff, a conditional paradigm that
benefits from the denoising diffusion probabilistic model (DDPM) to tackle the
problem of realistic and diverse action-conditioned 3D skeleton-based motion
generation. We are a pioneering attempt that uses DDPM to synthesize a variable
number of motion sequences conditioned on a categorical action. We evaluate our
approach on the large-scale NTU RGB+D dataset and show improvements over
state-of-the-art motion generation methods
Comparison of cold resistance physiological and biochemical features of four Herba Rhodiola seedlings under low temperature
AbstractTo discuss the cold resistance performance of different Herba Rhodiolae and successfully transplant Herba Rhodiolae to the Gansu plateau area for nursing, domestication and planting, this paper systematically studies six physiological and biochemical features of Rhodiola kirilowii, Rhodiola algida, Rhodiola crenulata and Herba Rhodiolae that are closely associated with cold resistance features and concludes with the cold resistance capability of Rhodiola kirilowii. In the selected six main indexes of the Herba Rhodiolae, the POD, SOD and CAT activity and MDA and Pro content in the leaf are the main physiological and biochemical indexes to indicate the cold resistance performance of four Herba Rhodiolae seedlings and can be regarded as the preliminary indexes to assess the winter performance of Herba Rhodiolae. The research work will provide the theoretical basis for the wild variants of Herba Rhodiolae and GAPJ base construction
Arbuscular mycorrhizal fungal interactions bridge the support of root-associated microbiota for slope multifunctionality in an erosion-prone ecosystem
The role of diverse soil microbiota in restoring erosion-induced degraded lands is well recognized. Yet, the facilitative interactions among symbiotic arbuscular mycorrhizal (AM) fungi, rhizobia, and heterotrophic bacteria, which underpin multiple functions in eroded ecosystems, remain unclear. Here, we utilized quantitative microbiota profiling and ecological network analyses to explore the interplay between the diversity and biotic associations of root-associated microbiota and multifunctionality across an eroded slope of a Robinia pseudoacacia plantation on the Loess Plateau. We found explicit variations in slope multifunctionality across different slope positions, associated with shifts in limiting resources, including soil phosphorus (P) and moisture. To cope with P limitation, AM fungi were recruited by R. pseudoacacia, assuming pivotal roles as keystones and connectors within cross-kingdom networks. Furthermore, AM fungi facilitated the assembly and composition of bacterial and rhizobial communities, collectively driving slope multifunctionality. The symbiotic association among R. pseudoacacia, AM fungi, and rhizobia promoted slope multifunctionality through enhanced decomposition of recalcitrant compounds, improved P mineralization potential, and optimized microbial metabolism. Overall, our findings highlight the crucial role of AM fungal-centered microbiota associated with R. pseudoacacia in functional delivery within eroded landscapes, providing valuable insights for the sustainable restoration of degraded ecosystems in erosion-prone regions
Children neuropsychological and behavioral scale-revision 2016 in the early detection of autism spectrum disorder
BackgroundThe Children Neuropsychological and Behavioral Scale-Revision 2016 (CNBS-R2016) is a widely used developmental assessment tool for children aged 0–6 years in China. The communication warning behavior subscale of CNBS-R2016 is used to assess the symptoms of autism spectrum disorder (ASD), and its value of >30 points indicates ASD based on CNBS-R2016. However, we observed that children with relatively lower values were also diagnosed with ASD later on in clinical practice. Thus, this study aimed to identify the suitable cutoff value for ASD screening recommended by the communication warning behavior of CNBS-R2016.Materials and methodsA total of 90 typically developing (TD) children and 316 children with developmental disorders such as ASD, developmental language disorder (DLD), and global developmental delay (GDD; 130 in the ASD group, 100 in the DLD group, and 86 in the GDD group) were enrolled in this study. All subjects were evaluated based on the CNBS-R2016. The newly recommended cutoff value of communication warning behavior for screening ASD was analyzed with receiver operating curves.ResultsChildren in the ASD group presented with lower developmental levels than TD, DLD, and GDD groups in overall developmental quotient assessed by CNBS-R2016. We compared the consistency between the scores of communication warning behavior subscale and Autism Behavior Checklist (ABC), Childhood Autism Rating Scale (CARS), Autism Diagnostic Observation Schedule, second edition (ADOS-2), and clinical diagnosis for the classification of ASD at a value of 30 based on the previously and newly recommended cutoff value of 12 by the CNBS-R2016. The Kappa values between the communication warning behavior and ABC, CARS, ADOS-2, and clinical diagnosis were 0.494, 0.476, 0.137, and 0.529, respectively, with an agreement rate of 76.90%, 76.26%, 52.03%, and 82.27%, respectively, when the cutoff point was 30. The corresponding Kappa values were 0.891, 0.816, 0.613, and 0.844, respectively, and the corresponding agreement rate was 94.62%, 90.82%, 90.54%, and 93.10%, respectively, when the cutoff point was 12.ConclusionThe communication warning behavior subscale of CNBS-R2016 is important for screening ASD. When the communication warning behavior score is 12 points or greater, considerable attention and further comprehensive diagnostic evaluation for ASD are required to achieve the early detection and diagnosis of ASD in children
Environmentally vulnerable or sensitive groups exhibiting varying concerns towards air pollution can drive government response to improve air quality
Air pollution seriously threatens human health, and its consequences are particularly prevalent among environmentally vulnerable or sensitive groups. However, whether the concerns among these groups are different and how they affect air pollution governance remain unclear. Here, we extract 3.8 million haze-related posts from China’s Sina Weibo and analyse the concerns raised by these groups by constructing an air pollution notability index. The results show that protection is the key theme for women aged 20-35 years, while elderly individuals are easily influenced by haze-related product ads yet lack awareness of scientific-based protection. Concerns shared by young individuals are more effective in pressuring the government in cities that experience higher levels of pollution. Concerns shared by women are more effective in cities that experience lower levels of pollution. This study evidences the influence of the public concerns conveyed via social media on air pollution governance in China
Boosting with an aerosolized Ad5-nCoV elicited robust immune responses in inactivated COVID-19 vaccines recipients
IntroductionThe SARS-CoV-2 Omicron variant has become the dominant SARS-CoV-2 variant and exhibits immune escape to current COVID-19 vaccines, the further boosting strategies are required.MethodsWe have conducted a non-randomized, open-label and parallel-controlled phase 4 trial to evaluate the magnitude and longevity of immune responses to booster vaccination with intramuscular adenovirus vectored vaccine (Ad5-nCoV), aerosolized Ad5-nCoV, a recombinant protein subunit vaccine (ZF2001) or homologous inactivated vaccine (CoronaVac) in those who received two doses of inactivated COVID-19 vaccines. ResultsThe aerosolized Ad5-nCoV induced the most robust and long-lasting neutralizing activity against Omicron variant and IFNg T-cell response among all the boosters, with a distinct mucosal immune response. SARS-CoV-2-specific mucosal IgA response was substantially generated in subjects boosted with the aerosolized Ad5-nCoV at day 14 post-vaccination. At month 6, participants boosted with the aerosolized Ad5-nCoV had remarkably higher median titer and seroconversion of the Omicron BA.4/5-specific neutralizing antibody than those who received other boosters. DiscussionOur findings suggest that aerosolized Ad5-nCoV may provide an efficient alternative in response to the spread of the Omicron BA.4/5 variant.Clinical trial registrationhttps://www.chictr.org.cn/showproj.html?proj=152729, identifier ChiCTR2200057278
The human lncRNA LINC-PINT inhibits tumor cell invasion through a highly conserved sequence element
Automatic Registration of Multi-Projector Based on Coded Structured Light
Multi-projector display systems are widely used in virtual reality, flight simulators, and other entertainment systems. Geometric distortion and color inconsistency are two key problems to be solved. In this paper a geometric correction principle is theoretically demonstrated and a consistency principle of geometric correction is first proposed. A new method of automatic registration of a multi-projector on a curved screen is put forward. Two pairs of binocular-cameras are used to reconstruct the curved screen. To capture feature points of the curved screen precisely, a group of red-blue coded structured light images is designed to be projected onto the screen. Geometric homography between each projector and the curved screen is calculated to gain a pre-warp template. Work which can gain a seamless display is illustrated by a six-projector system on the curved screen
Formal verification of Simulink/Stateflow diagrams: a deductive approach
This book presents a state-of-the-art technique for formal verification of continuous-time Simulink/Stateflow diagrams, featuring an expressive hybrid system modelling language, a powerful specification logic and deduction-based verification approach, and some impressive, realistic case studies. Readers will learn the HCSP/HHL-based deductive method and the use of corresponding tools for formal verification of Simulink/Stateflow diagrams. They will also gain some basic ideas about fundamental elements of formal methods such as formal syntax and semantics, and especially the common techniques applied in formal modelling and verification of hybrid systems. By investigating the successful case studies, readers will realize how to apply the pure theory and techniques to real applications, and hopefully will be inspired to start to use the proposed approach, or even develop their own formal methods in their future work
Learning to Have a Civil Aircraft Take Off under Crosswind Conditions by Reinforcement Learning with Multimodal Data and Preprocessing Data
Autopilot technology in the field of aviation has developed over many years. However, it is difficult for an autopilot system to autonomously operate a civil aircraft under bad weather conditions. In this paper, we present a reinforcement learning (RL) algorithm using multimodal data and preprocessing data to have a civil aircraft take off autonomously under crosswind conditions. The multimodal data include the common flight status and visual information. The preprocessing is a new design that maps some flight data by nonlinear functions based on the general flight dynamics before these data are fed into the RL model. Extensive experiments under different crosswind conditions with a professional flight simulator demonstrate that the proposed method can effectively control a civil aircraft to take off under various crosswind conditions and achieve better performance than trials without visual information or preprocessing data
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