Synthesizing Physically Plausible Human Motions in 3D Scenes

Synthesizing physically plausible human motions in 3D scenes is a challenging problem. Kinematics-based methods cannot avoid inherent artifacts (e.g., penetration and foot skating) due to the lack of physical constraints. Meanwhile, existing physics-based methods cannot generalize to multi-object scenarios since the policy trained with reinforcement learning has limited modeling capacity. In this work, we present a framework that enables physically simulated characters to perform long-term interaction tasks in diverse, cluttered, and unseen scenes. The key idea is to decompose human-scene interactions into two fundamental processes, Interacting and Navigating, which motivates us to construct two reusable Controller, i.e., InterCon and NavCon. Specifically, InterCon contains two complementary policies that enable characters to enter and leave the interacting state (e.g., sitting on a chair and getting up). To generate interaction with objects at different places, we further design NavCon, a trajectory following policy, to keep characters' locomotion in the free space of 3D scenes. Benefiting from the divide and conquer strategy, we can train the policies in simple environments and generalize to complex multi-object scenes. Experimental results demonstrate that our framework can synthesize physically plausible long-term human motions in complex 3D scenes. Code will be publicly released at https://github.com/liangpan99/InterScene

Demethyleneberberine alleviated the inflammatory response by targeting MD-2 to inhibit the TLR4 signaling

IntroductionThe colitis induced by trinitrobenzenesulfonic acid (TNBS) is a chronic and systemic inflammatory disease that leads to intestinal barrier dysfunction and autoimmunedisorders. However, the existing treatments of colitis are associated with poor outcomes, and the current strategies remain deep and long-time remission and the prevention of complications. Recently, demethyleneberberine (DMB) has been reported to be a potential candidate for the treatment of inflammatory response that relied on multiple pharmacological activities, including anti-oxidation and antiinflammation. However, the target and potential mechanism of DMB in inflammatory response have not been fully elucidated.MethodsThis study employed a TNBS-induced colitis model and acute sepsis mice to screen and identify the potential targets and molecular mechanisms of DMB in vitro and in vivo. The purity and structure of DMB were quantitatively analyzed by high-performance liquid chromatography (HPLC), mass spectrometry (MS), Hydrogen nuclear magnetic resonance spectroscopy (1H-NMR), and infrared spectroscopy (IR), respectively. The rats were induced by a rubber hose inserted approximately 8 cm through their anus to be injected with TNBS. Acute sepsis was induced by injection with LPS via the tail vein for 60 h. These animals with inflammation were orally administrated with DMB, berberine (BBR), or curcumin (Curc), respectively. The eukaryotic and prokaryotic expression system of myeloid differentiation protein-2 (MD-2) and its mutants were used to evaluate the target of DMB in inflammatory response.ReslutsDMB had two free phenolic hydroxyl groups, and the purity exceeded 99% in HPLC. DMB alleviated colitis and suppressed the activation of TLR4 signaling in TNBS-induced colitis rats and LPS-induced RAW264.7 cells. DMB significantly blocked TLR4 signaling in both an MyD88-dependent and an MyD88-independent manner by embedding into the hydrophobic pocket of the MD-2 protein with non-covalent bonding to phenylalanine at position 76 in a pi–pi T-shaped interaction. DMB rescued mice from sepsis shock induced by LPS through targeting the TLR4–MD-2 complex.ConclusionTaken together, DMB is a promising inhibitor of the MD-2 protein to suppress the hyperactivated TLR4 signaling in inflammatory response

Cellular immunotherapy as maintenance therapy prolongs the survival of the patients with small cell lung cancer in extensive stage

AbstractBackgroundSmall cell lung cancer (SCLC) is the most devastating type of human lung cancer. Patients usually present with disseminated disease to many organs (extensive stage). This study was to investigate the efficacy and safety of cellular immunotherapy (CIT) with autologous natural killer (NK), γδT, and cytokine-induced killer (CIK) cells as maintenance therapy for extensive-stage SCLC (ES-SCLC) patients.MethodsA pilot prospective cohort study was conducted with ES-SCLC patients who had responded to initial chemotherapy. Patients received either CIT as maintenance therapy (CIT group), or no treatment (control group). Progression-free survival (PFS), overall survival (OS), and adverse effects were compared.ResultsForty-nine patients were recruited in this study, with 19 patients in the CIT group and 30 patients in the control group. The patient characteristics of the 2 groups were comparable except for age, as patients in the CIT group were older than those in the control group (P < 0.05). PFS in the CIT group was superior to the control group (5 vs. 3.1 months, P = 0.020; HR, 0.489, 95% CI, 0.264–0.909, P = 0.024). OS of the CIT group was also longer than that of the control group (13.3 vs. 8.2 months, P = 0.044; HR, 0.528, 95% CI, 0.280–0.996, P = 0.048, respectively). No significant adverse reactions occurred in patients undergoing CIT.ConclusionsCIT maintenance therapy in ES-SCLC prolonged survival with only minimal side effects. Integrating CIT into the current treatment may be a novel strategy for ES-SCLC patients, although further multi-center randomized trials are needed

Reconstructed covalent organic frameworks

Covalent organic frameworks (COFs) are distinguished from other organic polymers by their crystallinity1–3, but it remains challenging to obtain robust, highly crystalline COFs because the framework-forming reactions are poorly reversible4,5. More reversible chemistry can improve crystallinity6–9, but this typically yields COFs with poor physicochemical stability and limited application scope5. Here we report a general and scalable protocol to prepare robust, highly crystalline imine COFs, based on an unexpected framework reconstruction. In contrast to standard approaches in which monomers are initially randomly aligned, our method involves the pre-organization of monomers using a reversible and removable covalent tether, followed by confined polymerization. This reconstruction route produces reconstructed COFs with greatly enhanced crystallinity and much higher porosity by means of a simple vacuum-free synthetic procedure. The increased crystallinity in the reconstructed COFs improves charge carrier transport, leading to sacrificial photocatalytic hydrogen evolution rates of up to 27.98 mmol h−1 g−1. This nanoconfinement-assisted reconstruction strategy is a step towards programming function in organic materials through atomistic structural control

GIS-based advanced spatial analysis of total organic carbon and potentially toxic elements in European agricultural and Irish soils

With the increasing availability of data in environmental geochemistry, one of the biggest challenges is to extract useful knowledge and interpretable information from large and diverse data sources. The unprecedented volume and complexity of datasets make it difficult to rely on traditional tools for data analysis, which requires the applications and development of GIS-based spatial techniques. In this thesis, four advanced spatial analysis and machine learning (ML) techniques: (1) hot spot analysis (Get-is Ord Gi*); (2) Geographically weighted regression (GWR); (3) K-means clustering analysis; and (4) Geographically Weighted Pearson Correlation Coefficient (GWPCC) were deployed to investigate the spatial patterns and to extract hidden information in large-scale datasets. The total organic carbon (TOC) and potentially toxic elements (PTEs) were studied based on datasets of GEochemical Mapping of Agricultural Soil (GEMAS) of EuroGeoSurveys and Tellus of Geological Survey of Ireland. On the one hand, the TOC contents are receiving increasing attention in agricultural soils as an important indicator of soil nutrient, not only due to their close relationship with soil fertility, but also with carbon dioxide (CO2) in the atmosphere. On the other hand, the advanced spatial techniques played important roles to evaluate concentrations and spatial variation of PTEs affected by multiple influencing factors from natural and anthropogenic sources. These studies provide demonstrations of applications of these advanced analytical techniques as possible solutions to the challenges of data analytics in the big data era. (1) The hot spot analysis was performed on a total of 2,108 agricultural soil samples based on GEMAS data and revealed an overall negative correlation between TOC and pH, which was in line with the general relationship between these two variables. However, a ‘special’ feature of co-existence of comparatively low TOC and pH values was also identified in north-central Europe. It has been found that these ‘special’ patterns are strongly related to the high concentration of quartz (SiO2) in the coarse-textured glacial sediments in north-central Europe. (2) The GWR further explored the spatially varying relationships between TOC and pH based on the GEMAS data, with more than 50% original negative relationship changed to positive at the continental level. The significant positive correlations clustered in central-eastern Europe, while negative correlations were observed mainly in northern Europe. Mixed relationships occurred in southern Europe. Such results further highlighted the influences of the extensive occurrence of quartz-rich soils and climate factors on the ‘special’ positive correlations. In addition, anthropogenic inputs also interfered the relationships in the mixed southern European areas. (3) The integration of hot spot analysis and K-means clustering analysis was applied to investigate the spatial patterns for 15 PTEs and associations with their controlling factors based on the Tellus data under the complicated geological background of Northern Ireland (NI). The spatial clustering patterns for the 15 PTEs from hot spot analysis and hidden patterns of 6,862 soil samples from K-means clustering were consistent with each other, highlighting the dominant control of peat and basalt in the topsoil of Northern Ireland. (4) The GWPCC found that the relationships between lead (Pb) and aluminium (Al) are spatially varying, with both positive and negative correlations in the topsoil of northern half of Ireland based. The ‘special’ negative correlations were observed in more than 35% of the whole study area, mainly clustered in the north-eastern and western Ireland. The positive correlations were observed in the midlands. Mixed relationships of both negative and positive correlations occurred in the eastern coastal areas. The majority of negative correlation patterns showed clear association with blanket peat, which can be attribute to long-distance transportation of Pb from atmospheric deposition. The main scientific contributions to the advancements in environmental geochemical studies of this research include the following: (1) identified a ‘special’ feature of positive relationship of low TOC contents and low pH values in the north-central Europe; (2) introduced the topic of ‘spatially varying relationships between TOC and pH’ which provide added value and clarification to the understanding of the controversy of their complicated relationship in the literature; (3) provided latest understanding and classification of 15 PTEs in the topsoil of NI to enhance the current knowledge of their controlling factors under the complicated geological background; (4) proved and observed the spatially varying relationships between Pb and Al which are associated with atmospheric deposition and anthropogenic activities. Overall, these novel findings indicated that the spatial techniques have strong efficiency in processing large-scale datasets, providing demonstration and evidence for the application of GIS-based advanced spatial analysis on identification of the hidden spatial patterns for TOC and PTEs in the topsoil and to associate them with related influencing factors. These analytical results enhanced the current knowledge for soil management and risk assessment, and can be applied in environmental studies elsewhere

Exploration of spatially varying relationships between Pb and Al in urban soils of London at the regional scale using geographically weighted regression (GWR)

In this study, geographically weighted regression (GWR) was applied to reveal the spatially varying relationships between Pb and Al in urban soils of London based on 6467 samples collected by British Geological Survey. Results showed that the relationships between Pb and Al were spatially varying in urban soils of London, with different relationships in different areas. The strong negative relationships between Pb and Al were found in the northeast and north areas and weak relationships were located in central areas, implying the links with the impact of anthropogenic activities on Pb concentration, while road traffic, industry activities and construction in centre of London may be linked to the weakened or changed direction of the relationship. However, positive relationships between Pb and Al were found in large parklands and greenspaces in the southeast and southwest as well as a small area in central London, due to less influences from human activities where the natural geochemical signatures were preserved. This study suggests that GWR is an effective tool to reveal spatially varying relationships in environmental variables, providing improved understanding of the complicated relationships in environmental parameters from the spatial aspect, which could be hardly achieved using conventional statistical analysis

Dynamic equivalent-based reliability evaluation of distribution systems with DGs

This study proposes a novel dynamic reliability network-equivalent approach (RNEA) for distribution generations (DGs) enhanced distribution system. This method includes a bottom-up process and a top-down process, which are developed based on equivalent principle, and the synthesis of both processes yields the reliability performance of any node in the system. In addition, a novel switch zone concept is defined and introduced into the bottom-up equivalent process as to save the computation cost. Besides, a hybrid restoration model is proposed to account for the practical restoration process in power grids, and solved using particle swarm optimisation. The most significant of the proposed approach over other equivalent methods such as section technique, RNEA, and zone-branch method is that it provides a more generalised element-by-element equivalent approach that can greatly simplify the network for reliability assessment irrespective of the network topology. The proposed methodology has been successfully tested on a real 362-node urban distribution system in China, with and without DGs considered