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[Display omitted] • Preliminary screening of reagents and theoretical extraction property are calculated and discussed at molecular level by DFT. • Efficient aqueous hexafluorophosphate extraction via Alamine336 was firstly proved feasible and efficacious. • Affecting factors of extraction and stripping process were comprehensively investigated. • The extraction of hexafluorophosphate occurs mainly through electrostatic attraction and Van der Waals force. Effluent derived from spent lithium-ion batteries (LIBs) electrolyte or discarded ionic liquids (ILs) is a potentially resource of hexafluorophosphate (PF 6 −) which can be recovered through solvent extraction. In this study, an efficient extraction approach was proposed to recover the hexafluorophosphate from solutions. A basic investigation on the interactions between extractants and hexafluorophosphate was firstly carried out using density functional theory (DFT), which demonstrated the stability of the extracted complex structure. The effects of extractant (Alamine336) and modifier, common anions and metallic ions in waste-streams, initial pH, and temperature on the extraction efficiency were explored. The results showed that 96.16 % of hexafluorophosphate could be extracted and transferred into organic phase using Alamine336/modifier as extractant under optimal conditions (0.15 mol/L of Alamine336 and 0.25 mol/L of modifier). The organic phase exhibited an excellent extraction capability of >95 % under optimal condition. Moreover, it was found that the use of sodium hydroxide as stripping reagent presented a superb stripping and cycling properties. Thermodynamic analysis and spectral data indicated that PF 6 − was extracted into the organic phase in the form of R 3 NH⋅PF 6 , which is a spontaneous exothermic process. The novel extraction method provides a broad application perspective for the removal and recovery of valuable hexafluorophosphate from aqueous system. [ABSTRACT FROM AUTHOR]

Aerial swarm systems possess immense potential in various aspects, such as cooperative exploration, target tracking, and search and rescue. Efficient accurate self- and mutual state estimation are the critical preconditions for completing these swarm tasks, which remain challenging research topics. This article proposes Swarm-LIO2, a fully decentralized, plug-and-play, computationally efficient, and bandwidth-efficient light detection and ranging (LiDAR)-inertial odometry for aerial swarm systems. Swarm-LIO2 uses a decentralized plug-and-play network as the communication infrastructure. Only bandwidth-efficient and low-dimensional information is exchanged, including identity, ego state, mutual observation measurements, and global extrinsic transformations. To support the plug and play of new teammate participants, Swarm-LIO2 detects potential teammate autonomous aerial vehicles (AAVs) and initializes the temporal offset and global extrinsic transformation all automatically. To enhance the initialization efficiency, novel reflectivity-based AAV detection, trajectory matching, and factor graph optimization methods are proposed. For state estimation, Swarm-LIO2 fuses LiDAR, inertial measurement units, and mutual observation measurements within an efficient error state iterated Kalman filter (ESIKF) framework, with careful compensation of temporal delay and modeling of measurements to enhance the accuracy and consistency. Moreover, the proposed ESIKF framework leverages the global extrinsic for ego state estimation in the case of LiDAR degeneration or refines the global extrinsic along with the ego state estimation otherwise. To enhance the scalability, Swarm-LIO2 introduces a novel marginalization method in the ESIKF, which prevents the growth of computational time with swarm size. Extensive simulation and real-world experiments demonstrate the broad adaptability to large-scale aerial swarm systems and complicated scenarios, including GPS-denied scenes and degenerated scenes for cameras or LiDARs. The experimental results showcase the centimeter-level localization accuracy, which outperforms other state-of-the-art LiDAR-inertial odometry for a single-AAV system. Furthermore, diverse applications demonstrate the potential of Swarm-LIO2 to serve as a reliable infrastructure for various aerial swarm missions.

The ability of the mammalian kidney to repair or regenerate after acute kidney injury (AKI) is very limited. The maladaptive repair of AKI promotes progression to chronic kidney disease (CKD). Therefore, new strategies to promote the repair/regeneration of injured renal tubules after AKI are urgently needed. Hypoxia has been shown to induce heart regeneration in adult mice. However, it is unknown whether hypoxia can induce kidney regeneration after AKI. In this study, we used a prolyl hydroxylase domain inhibitor (PHDI), MK-8617, to mimic hypoxic conditions and found that MK-8617 significantly ameliorated ischemia reperfusion injury (IRI)-induced AKI. We also showed that MK-8617 dramatically facilitated renal tubule regeneration by promoting the proliferation of renal proximal tubular cells (RPTCs) after IRI-induced AKI. We then performed bulk mRNA sequencing and discovered that multiple nephrogenesis-related genes were significantly upregulated with MK-8617 pretreatment. We also showed that MK-8617 may alleviate proximal tubule injury by stabilizing the HIF-1α protein specifically in renal proximal tubular cells. Furthermore, we demonstrated that MK-8617 promotes the reprogramming of renal proximal tubular cells to Sox9+renal progenitor cells and the regeneration of renal proximal tubules. In summary, we report that the inhibition of prolyl hydroxylase improves renal proximal tubule regeneration after IRI-induced AKI by promoting the reprogramming of renal proximal tubular cells to Sox9+renal progenitor cells.

A hydrophobic composite coating was obtained on the carbon steel surface through electrochemical deposition of a copper coating in a sulfate solution and chemical vapor deposition of a carbon fiber film. It alleviated the serious corrosion problem of carbon steel on the evaporator of hot film coupled seawater desalination system in harsh marine environment. The morphologies and compositions of the coatings were analyzed, revealing the influence of electrodeposition time on their performance. The micro-nano copper structure formed by electrodeposition significantly improved the deposition effect of carbon layer. Additionally, experiments with seawater solution contact angle tests indicated that electrodeposition transformed the surface properties from hydrophilic to hydrophobic, effectively inhibiting the diffusion of corrosive medium into the interior of the substrate. Through polarization curves, electrochemical impedance spectroscopy, and other analyses, it was demonstrated that the hydrophobic coating significantly improves the corrosion resistance of carbon steel substrates in seawater environments, surpassing the performance of traditional duplex steel.

This paper presents FAST-LIVO2, a fast and direct LiDAR-inertial-visual odometry framework designed for accurate and robust state estimation in SLAM tasks, enabling real-time robotic applications. FAST-LIVO2 integrates IMU, LiDAR, and image data through an efficient error-state iterated Kalman filter (ESIKF). To address the dimensional mismatch between LiDAR and image measurements, we adopt a sequential update strategy. Efficiency is further enhanced using direct methods for LiDAR and visual data fusion: the LiDAR module registers raw points without extracting features, while the visual module minimizes photometric errors without relying on feature extraction. Both LiDAR and visual measurements are fused into a unified voxel map. The LiDAR module constructs the geometric structure, while the visual module links image patches to LiDAR points, enabling precise image alignment. Plane priors from LiDAR points improve alignment accuracy and are refined dynamically during the process. Additionally, an on-demand raycast operation and real-time image exposure estimation enhance robustness. Extensive experiments on benchmark and custom datasets demonstrate that FAST-LIVO2 outperforms state-of-the-art systems in accuracy, robustness, and efficiency. Key modules are validated, and we showcase three applications: UAV navigation highlighting real-time capabilities, airborne mapping demonstrating high accuracy, and 3D model rendering (mesh-based and NeRF-based) showcasing suitability for dense mapping. Code and datasets are open-sourced on GitHub to benefit the robotics community.

Herein, the de novosynthesis of atropisomeric benzofurans through the Cu/spirocyclic-pyrrolidine-oxazoline (SPDO) complex catalyze asymmetric formal [3 + 2] cycloaddition between quinones and ynamides is explored, producing a range of structurally diverse axially chiral benzofurans in satisfactory yields with good to excellent enantioselectivities. Furthermore, density functional theory calculations were applied to explain the possible reaction mechanism.

This work proposed a LiDAR-inertial-visual fusion framework termed R$^{3}$3LIVE++ to achieve robust and accurate state estimation while simultaneously reconstructing the radiance map on the fly. R$^{3}$3LIVE++ consists of a LiDAR-inertial odometry (LIO) and a visual-inertial odometry (VIO), both running in real-time. The LIO subsystem utilizes the measurements from a LiDAR for reconstructing the geometric structure, while the VIO subsystem simultaneously recovers the radiance information of the geometric structure from the input images. R$^{3}$3LIVE++ is developed based on R$^{3}$3LIVE and further improves the accuracy in localization and mapping by accounting for the camera photometric calibration and the online estimation of camera exposure time. We conduct more extensive experiments on public and self-collected datasets to compare our proposed system against other state-of-the-art SLAM systems. Quantitative and qualitative results show that R$^{3}$3LIVE++ has significant improvements over others in both accuracy and robustness. Moreover, to demonstrate the extendability of R$^{3}$3LIVE++, we developed several applications based on our reconstructed maps, such as high dynamic range (HDR) imaging, virtual environment exploration, and 3D video gaming.

AbstractIn this paper, we show that if His a Dedekind complete normed Riesz space with the local Egoroff property, then His lattice isomorphic to an ideal of an AM-space if and only if for any order bounded norm null sequence in H. Based on this, several characterizations of discrete Banach lattices with order continuous norms are provided. As an application, we find the special regulator for every relative uniform convergent sequence in discrete Banach lattices with order continuous norms.

To date, it remains challenging to precisely and efficiently construct structurally intriguing polycarbocycles with densely packed stereocenters in organic synthesis. Niduterpenoid B, a naturally occurring ERα inhibitor, exemplifies this complexity with its intricate polycyclic network comprising 5 cyclopentane and 1 cyclopropane rings, featuring 13 contiguous stereocenters, including 4 all-carbon quaternary centers. In this work, we describe the first total synthesis of niduterpenoid B using a structural reorganization strategy. Key features include the following: (1) an efficient methoxy-controlled cascade reaction that precisely forges a highly functionalized tetraquinane (A–D rings) bearing sterically hindered contiguous quaternary stereocenters; (2) a rhodium-catalyzed [1 + 2] cycloaddition that facilitates the construction of a strained 3/5 bicycle (E–F rings) angularly fused with ring D.

Dermatomyositis, an idiopathic inflammatory myopathy, is characterized by distinctive skin manifestations, proximal muscle weakness, and multiple organ involvement and can be accompanied by malignancies. To provide a reference for dermatologists and clinicians in other relevant fields of clinical practice, experts from the Dermatology Branch of the China International Exchange and Promotion Association for Medical and Health Care and the National Clinical Research Center for Dermatologic and Immunologic Diseases developed this consensus on the diagnosis and treatment of adult dermatomyositis using Chinese and international literature and expert advice.

A new rhombohedral phase (termed R′) in a solution−aging-treated titanium alloy (Ti−4.5Al−6.5Mo−2Cr− 2Nb−1V−1Sn−1Zr, wt.%) was identified. Its accurate Bravais lattice parameters were determined by a novel unit cell reconstruction method based on conventional selected-area electron diffraction (SAED) technique. The orientation relationship between R′phase and BCC phase was revealed. The results show that the R′phase is found to have 48 crystallographically equivalent variants, resulting in rather complicated SAED patterns with high-order reflections. A series of in-situ SAED patterns were taken along both low- and high-index zone axes, and all weak and strong reflections arising from the 48 variants were properly explained and directly assigned with self-consistent Miller indices, confirming the presence of the rhombohedral phase. Additionally, some criteria were also proposed for evaluating the indexed results, which together with the Bravais lattice reconstruction method shed light on the microstructure characterization of even unknown phases in other alloys.

Solar photocatalytic H2production from lignocellulosic biomass has attracted great interest, but it suffers from low photocatalytic efficiency owing to the absence of highly efficient photocatalysts. Herein, we designed and constructed ultrathin MoS2-modified porous TiO2microspheres (MT) with abundant interface Ti–S bonds as photocatalysts for photocatalytic H2generation from lignocellulosic biomass. Owing to the accelerated charge transfer related to Ti–S bonds, as well as the abundant active sites for both H2and ●OH generation, respectively, related to the high exposed edge of MoS2and the large specific surface area of TiO2, MT photocatalysts demonstrate good performance in the photocatalytic conversion of α-cellulose and lignocellulosic biomass to H2. The highest H2generation rate of 849 μmol·g–1·h–1and apparent quantum yield of 4.45% at 380 nm was achieved in α-cellulose aqueous solution for the optimized MT photocatalyst. More importantly, lignocellulosic biomass of corncob, rice hull, bamboo, polar wood chip, and wheat straw were successfully converted to H2over MT photocatalysts with H2generation rate of 10, 19, 36, 29, and 8 μmol·g–1·h–1, respectively. This work provides a guiding design approach to develop highly active photocatalysts via interface engineering for solar H2production from lignocellulosic biomass.

The sodium smelting of vanadium–titanium magnetite can achieve the comprehensive utilization of Fe, V, and Ti. However, the generation of alkaline slag during this process may cause damage to refractory materials. The wettability and corrosion behavior of alkaline slag on three types of refractory (MgO–C, SiC, and high alumina refractory) substrates were investigated at temperatures up to 1200 °C. The effects of duration on the wettability of molten slag on SiC substrates were also investigated. Results showed that the high alumina refractory exhibited better wettability with the molten slag than the others, and thus, it is easier to be corroded. The results of scanning electron microscopy coupled with energy dispersive spectroscopy showed that MgO–C and high alumina refractory substrates were severely eroded. There was a visible and regular interfacial reaction layer between the slag and SiC refractory substrate, which was produced by the redox reaction between the metal oxides in the slag and the SiC refractory substrate. With the increase in holding time, the interface layer expands and silico-ferrite phases are generated at the interface. The redox reaction between Fe2O3and SiC substrate is the main reason for the corrosion. By comparing the differences in wettability and corrosion behavior between the alkaline slag from sodium smelting of vanadium–titanium magnetite and MgO–C, SiC and high alumina refractories, it is concluded that SiC refractory has good corrosion resistance to the slag. Iron oxides in the slag accelerate the oxidation rate of SiC refractory.

Static recrystallization (SRX) behaviors and corresponding recrystallization mechanisms of 7Mo super-austenitic stainless steel were studied under different deformation conditions. The order of influence of deformation parameters on static recrystallization behaviors, from high to low, is followed by temperature, first-stage strain and strain rate. Meanwhile, the effect of holding time on static recrystallization behaviors is significantly controlled by temperature. In addition, with the increase in temperature from 1000 to 1200 °C, the static recrystallization mechanism evolves from discontinuous static recrystallization and continuous static recrystallization (cSRX) to metadynamic recrystallization and cSRX, and finally to cSRX. The cSRX exists at all temperatures. This is because high stacking fault energy (56 mJ m−2) promotes the movement of dislocations, making the deformation mechanism of this steel is dominated by planar slip of dislocation. Large undissolved sigma precipitates promote static recrystallization through particle-stimulated nucleation. However, small strain-induced precipitates at grain boundaries hinder the nucleation of conventional SRX and the growth of recrystallized grains, while the hindering effect decreases with the increase in temperature.

Diffuse large B-cell lymphoma (DLBCL) is an aggressive malignancy and the most common form of non-Hodgkin lymphoma (NHL) that occurs worldwide. To discover risk factors and pathogenesis of DLBCL, we performed the largest GWAS of DLBCL to date in samples of East Asian ancestry, consisting of 2,888 patients with DLBCL and 12,458 controls. The meta-analysis identified three novel loci, rs2233434 on 6p21.1 (OR = 1.26, P= 1.17 × 10−8), rs11066015 on 12q24.12 (OR = 1.24, P= 6.57 × 10−9) and rs6032662 on 20q13.12 (OR = 1.24, P= 5.22 × 10−12). Fine mapping analysis revealed that the extensive association within the MHC region was driven by two novel HLA alleles, HLA-A*02 and HLA-DQB1*03. Functional annotation, eQTL and colocalization analyses of the susceptibility loci implicated NFKBIE/TCTE1, ALDH2/BRAPand CD40as candidate disease genes. The pleiotropic effect analysis of the DLBCL loci revealed shared genetic susceptibility between DLBCL and several autoimmune diseases. Our study also suggested genetic heterogeneity between Asian and European populations by identifying ancestry-specific genetic associations. Overall, this study has implicated novel disease genes and molecular mechanism for DLBCL.

Two-terminal monolithic perovskite/silicon tandem solar cells demonstrate huge advantages in power conversion efficiency compared with their respective single-junction counterparts1,2. However, suppressing interfacial recombination at the wide-bandgap perovskite/electron transport layer interface, without compromising its superior charge transport performance, remains a substantial challenge for perovskite/silicon tandem cells3,4. By exploiting the nanoscale discretely distributed lithium fluoride ultrathin layer followed by an additional deposition of diammonium diiodide molecule, we have devised a bilayer-intertwined passivation strategy that combines efficient electron extraction with further suppression of non-radiative recombination. We constructed perovskite/silicon tandem devices on a double-textured Czochralski-based silicon heterojunction cell, which featured a mildly textured front surface and a heavily textured rear surface, leading to simultaneously enhanced photocurrent and uncompromised rear passivation. The resulting perovskite/silicon tandem achieved an independently certified stabilized power conversion efficiency of 33.89%, accompanied by an impressive fill factor of 83.0% and an open-circuit voltage of nearly 1.97 V. To the best of our knowledge, this represents the first reported certified efficiency of a two-junction tandem solar cell exceeding the single-junction Shockley–Queisser limit of 33.7%.

The correlation between the microstructure, properties, and strain partitioning behavior in a medium-carbon carbide-free bainitic steel was investigated through a combination of experiments and representative volume element simulations. The results reveal that as the austempering temperature increases from low to intermediate, the optimal balance of properties shifts from strength–toughness to plasticity–toughness. The formation of fine bainitic ferrite plates and bainite sheaves under low austempering temperature (270 °C) enhances both strength and toughness. Conversely, the wide size and shape distribution of the retained austenite (RA) obtained through austempering at intermediate temperature (350 °C) contribute to increased work-hardening capacity, resulting in enhanced plasticity. The volume fraction of the ductile film-like RA plays a crucial role in enhancing impact toughness under relatively higher austempering temperatures. In the simulations of tensile deformation, the concentration of equivalent plastic strain predominantly manifests in the bainitic ferrite neighboring the martensite, whereas the equivalent plastic strain evenly spreads between the thin film-like retained austenite and bainitic ferrite. It is predicted that the cracks will occur at the interface between martensite and bainitic ferrite where the strain is concentrated, and eventually propagate along the strain failure zone.

Heavy-duty hydraulic manipulators exhibit high robustness and an impressive power-to-weight ratio, enabling their application to execute complex and demanding tasks. Evaluating velocity performance is crucial for successful task performance, as it informs trajectory planning, configuration selection, and design optimization. However, assessing the velocity performance of hydraulic manipulators is challenging due to flow coupling between joints, asymmetric actuators, and implicit constraints introduced by complex higher order dynamics. In this article, a flow manipulability polytope is proposed for evaluating hydraulic manipulators. Flow constraints are analyzed and established as linear constraint inequalities in a quasi-steady state. The implicit constraints are avoided by simplifying the dynamic model, and the impact of gravity load variations on the constraints is considered. The proposed method is employed to identify the optimal position in the workspace of the hydraulic manipulator. The optimal position, compared with that obtained by the manipulability ellipsoid, demonstrates superior velocity performance. The average flow is reduced by 11.25%, the pressure fluctuation is reduced by 19.75%, and the maximum joint error is reduced by 35.23%.

Exposure to widely used inert fibrous nanomaterials (for example, glass fibres or carbon nanotubes) may result in asbestos-like lung pathologies, becoming an important environmental and health concern. However, the origin of the pathogenesis of such fibres has not yet been clearly established. Here we report an electrochemical nanosensor that is used to monitor and quantitatively characterize the flux and dynamics of reactive species release during the frustrated phagocytosis of glass nanofibres by single macrophages. We show the existence of an intense prolonged release of reactive oxygen and nitrogen species by single macrophages near their phagocytic cups. This continued massive leakage of reactive oxygen and nitrogen species damages peripheral cells and eventually translates into chronic inflammation and lung injury, as seen during in vitro co-culture and in vivo experiments.

In the challenging applications of hydraulic robots, control performance in the full workspace is required for successful task completion. The model-based controller of the hydraulic manipulator is an effective means to improve control performance. However, most of the existing identification methods rely on least squares or weighted least squares, which may lead to the physically infeasible parameters. Although the physical feasibility of inertial parameters can be solved by the linear matrix inequality, physical feasibility and prior knowledge constraints of hydraulic parameters, such as bulk modulus and valve port coefficients, have not been considered in the identification process. Parameters that do not satisfy constraints will affect system stability in the model-based controller. In this article, an identification framework is proposed, which integrates inertial, friction, and hydraulic parameters physical feasibility. Compared with the nonidentified parameters, the ratio of tracking error to maximum velocity with the proposed method is reduced by 50%–56%. Compared with the least squares identification, the control stability in the full workspace is guaranteed. The proposed method is applicable to serial hydraulic manipulators with arbitrary degrees of freedom and is supported by experimental analysis of a hydraulic manipulator.

IntroductionThere are many migrant workers in China’s first-tier cities, but little is known about road safety. This paper systematically analysed road traffic injuries and risk factors among migrant workers in Guangzhou, China.MethodsRoad traffic crash data from 2017 to 2021 were obtained from the Guangzhou Public Security Traffic Management Integrated System. We plotted the crash network of road users in road traffic crashes and used logistic regression to analyse the risk factors for migrant workers of motorcycle and four-wheeled vehicle crashes. Moreover, the roles of migrant workers and control individuals as perpetrators in road traffic crashes were also analysed.ResultsBetween 2017 and 2021, 76% of road traffic injuries were migrant workers in Guangzhou. Migrant workers who were motorcyclist drivers most commonly experienced road traffic injuries. Crashes between motorcyclists and car occupants were the most common. The illegal behaviours of migrant worker motorcyclists were closely related to casualties, with driving without a licence only and driving without a licence and drunk driving accounting for the greatest number. Migrant workers were responsible for many injuries of other road users. Motorcycle drivers have a higher proportion of drunk driving.DiscussionMigrant workers play an important role in road traffic safety. They were both the leading source of road traffic injuries and the main perpetrators of road traffic crashes. Measures such as strict requirements for migrant workers to drive motorcycles with licences, prohibit drunk driving, greater publicity of road safety regulations, and combining compulsory education with punishment for illegal behaviours.

The Randles impedance model is a widely used 2R-1C equivalent circuit for characterizing chemical/biological processes and sensors. Parameter identification of the impedance model usually needs sweep-frequency (SF) measurements and an iterative least squares estimation algorithm using impedance spectroscopy data. To reduce execution time and computational burden, this article provides a novel analytical method to identify the model parameters in sweep-phase (SP) measurements and noniterative matrix operation-based least squares estimation using sinusoidal complete response data (combination with time-domain transient response and frequency-domain steady-state response). First, theoretical analysis for parameter identification of the Randles model is presented. Then, computer simulations on MATLAB software is conducted to identify the model parameters by changing: 1) the number of sweep phases (2–40); 2) the level of measurement noise (14–80 dB); and 3) the measurement frequency (5–500 kHz), with the maximum identified errors less than 6%. Moreover, SP experiment measurements based on a customized impedance device is compared with traditional SF measurements conducted by a commercial impedance analyzer on parameter identification of: 1) emulated Randles circuits and 2) an electrode–electrolyte interface. The mean difference of the identified model parameters between the two methods is less than 2% in emulated circuits, and 6% in the electrode–electrolyte interface, while the mean execution time of the SP method in the estimation process is 2.9 ms, which is 34 times less than the SF method. In sum, the article validates the feasibility of the first SP approach on parameter identification of the Randles impedance model, which shows good identification accuracy and shorter execution time relative to the traditional SF analysis method.

Objective: Colorectal cancer (CRC), a prevalent malignancy worldwide, has prompted extensive research into anticancer drugs. Traditional Chinese medicinal materials offer promising avenues for cancer management due to their diverse pharmacological activities. This study investigated the effects of Notopterygium incisum, a traditional Chinese medicine named Qianghuo (QH), on CRC cells and the underlying mechanism. Methods: The sulforhodamine B assay and colony formation assay were employed to assess the effect of QH extract on the proliferation of CRC cell lines HCT116 and Caco-2. Propidium iodide (PI) staining was utilized to detect cell cycle progression, and PE Annexin V staining to detect apoptosis. Western blotting was conducted to examine the levels of apoptotic proteins, including B-cell lymphoma 2-interacting mediator of cell death (BIM), B-cell lymphoma 2 (Bcl-2), Bcl-2-associated X protein (BAX) and cleaved caspase-3, as well as BIM stability after treatment with the protein synthesis inhibitor cycloheximide. The expression of BAX was suppressed using lentivirus-mediated shRNA to validate the involvement of the BIM/BAX axis in QH-induced apoptosis. The in vivoeffects of QH extract on tumor growth were observed using a xenograft model. Lastly, APCMin+mice were used to study the effects of QH extract on primary intestinal tumors. Results: QH extract exhibited significant in vitroanti-CRC activities evidenced by the inhibition of cell proliferation, perturbation of cell cycle progression, and induction of apoptosis. Mechanistically, QH extract significantly increased the stability of BIM proteins, which undergo rapid degradation under unstressed conditions. Knockdown of BAX, the downstream effector of BIM, significantly rescued QH-induced apoptosis. Furthermore, the in vitroeffect of QH extract was recapitulated in vivo. QH extract significantly inhibited the tumor growth of HCT116 xenografts in nude mice and decreased the number of intestinal polyps in the APCMin+mice. Conclusion: QH extract promotes the apoptosis of CRC cells by preventing the degradation of BIM.

Occupancy mapping is a fundamental component of robotic systems to reason about the unknown and known regions of the environment. This article presents an efficient occupancy mapping framework for high-resolution light detection and ranging (LiDAR) sensors, termed D-Map. The framework introduces three main novelties to address the computational efficiency challenges of occupancy mapping. First, we use a depth image to determine the occupancy state of regions instead of the traditional ray-casting method. Second, we introduce an efficient on-tree update strategy on a tree-based map structure. These two techniques avoid redundant visits to small cells, significantly reducing the number of cells to be updated. Third, we remove known cells from the map at each update by leveraging the low false alarm rate of LiDAR sensors. This approach not only enhances our framework's update efficiency by reducing map size but also endows it with an interesting decremental property, which we have named D-Map. To support our design, we provide theoretical analyzes of the accuracy of the depth image projection and time complexity of occupancy updates. Furthermore, we conduct extensive benchmark experiments on various LiDAR sensors in both public and private datasets. Our framework demonstrates superior efficiency in comparison with other state-of-the-art methods while maintaining comparable mapping accuracy and high memory efficiency. We demonstrate two real-world applications of D-Map for real-time occupancy mapping on a handheld device and an aerial platform carrying a high-resolution LiDAR.

Accurate and robust place recognition is essential for robot navigation, yet achieving full pose invariance and high performance across diverse scenes remains challenging. In this work, we propose a novel global and local combined descriptor named binary triangle combined (BTC) descriptor. We first extract the keypoints of a point cloud by projecting the points to planes extracted therein. Any three keypoints form a unique triangle, with the lengths of its sides constituting a triangle descriptor that captures the global appearance of the point cloud. Thanks to the distinct shape of a triangle given three side lengths, the similarity between two triangles and their vertices (i.e., keypoints) correspondence can be naturally determined from the side lengths of the triangle descriptors. The matched triangle pairs evaluate the appearance similarity between two point clouds, while the vertices’ correspondence enables accurate estimation of their relative pose; both are crucial for the place recognition task. To enhance the accuracy of triangle matching, BTC introduces a binary descriptor, which describes the point distribution neighboring each keypoint. The local geometry information encoded by the binary descriptor augments descriptiveness and discriminativeness to the triangle descriptor. Collectively, the two descriptors achieve both global and local descriptions of the environment with high accuracy, efficiency, and robustness. We extensively compare the proposed BTC descriptor against state-of-the-art methods (e.g., Scan Context, LCD-Net) on a wide range of datasets collected using different types of LiDAR sensors (spinning LiDARs and nonrepetitive scanning LiDARs) in various environments (urban, campus, forest, park, and mountain). The quantitative results demonstrate that BTC exhibits greater adaptability and significant improvement in precision compared to its counterparts, especially in challenging cases with large viewpoint variations (e.g., reverse direction, large translation, and/or rotation).

Juvenile hormone III (JH III) is a crucial hormone synthesized exclusively as R-stereoisomer in most insects. Herein, we established a mature Tris-HCl culture system for essential biochemical reactions and applied stable instrumental detection methods to analyze JH III, methyl farnesoate (MF) and juvenile hormone acid (JHA) using UPLC-MS/MS. Our results revealed that the R-JH III terminal synthesis pathway in Apis melliferafollows the “esterify then epoxidize” sequence, with precise methyl-(2E,6E)-farnesoate titer regulation and its spatial cis–transisomerism, achieving selective R-JH III synthesis. Furthermore, we observed that the preferred generation of S/R-JH III chiral enantiomers varied depending on the spatial cis–transisomerism of different MFs. Our results suggest that S-JH III could theoretically exist in insects, offering a novel perspective for understanding the synthesis mechanism of diverse complex juvenile hormones in different insect species.

A catalytic enantioselective polycyclization of tertiary enamides with terminal silyl enol ethers has been developed by virtue of Cu(OTf)2catalysis with a novel spiropyrroline-derived oxazole (SPDO) ligand. This tandem reaction offers an effective approach to assemble bicyclic and tricyclic N-heterocycles bearing both aza- and oxa-quaternary stereogenic centers, which are primal subunits in a range of natural alkaloids. Strategic application of this methodology and a late-stage radical cyclization as key steps have been showcased in the concise total synthesis of (−)-cephalocyclidin A.

Graphical Abstract

Error-state extended Kalman filter (ESEKF) is one of the extensively used filtering techniques in robot systems. There are many works that cast ESEKF on manifolds to improve consistency. However, most of these works are designed case by case, which makes it difficult to extend to new manifolds. In this article, we propose a generic method to formulate the iterated error-state extended Kalman filter (IESEKF) on manifolds, which aims to facilitate the deployment of IESEKF for on-manifold systems (e.g., lidar-inertial and visual-inertial systems). First, a canonical on-manifold representation of the robot system is proposed, based on which, an on-manifold IESEKF framework is formulated and solved by linearization at each estimation point. The proposed framework has two main advantages, one is that an equivalent error-state system is derived from linearization, which is minimally parameterized without any singularities in practice. And the other is that in each step of IESEKF, the manifold constraints are decoupled from the system behaviors, ultimately leading to a generic and symbolic IESEKF framework that naturally evolving on manifolds. Based on the separation of manifold constraints from the system behaviors, the on-manifold IESEKF is implemented as a toolkit in C++ packages, with which the user needs only to provide the system-specific descriptions, and then call the respective filter steps (e.g., predict, update) without dealing with any manifold constraints. The existing implementation supports full iterated Kalman filtering for versatile systems on manifold $\mathcal {M} = \mathbb {R}^{m}\!\times SO(3)\!\times \!\cdots \!\times \!SO(3)\!\times \!SE_{N}(3)\!\times \!\cdots \!\times \!SE_{N}(3)\!\times \mathbb {S}^{2} \times \cdots \times \mathbb {S}^{2}$ or any of its submanifolds, and is extendable to other types of manifold when necessary. The proposed symbolic IESEKF and the developed toolkit are verified by implementing two filter-based tightly coupled lidar-inertial navigation systems. Results show that, while greatly facilitating the EKF deployment, the developed toolkit leads to estimation performances and computation efficiency comparable to hand-engineered counterparts. Finally, the toolkit is open-sourced at https://github.com/hku-mars/IKFoM. The aimed application is the real-time state estimation of dynamic systems (e.g., robots) whose states are evolving on manifolds.

Simultaneous determination of sensor poses and scene geometry is a fundamental problem for robot vision that is often achieved by Bundle Adjustment (BA). This article presents an efficient and consistent bundle adjustment method for light detection and ranging (lidar) sensors. The method employs edge and plane features to represent the scene geometry, and directly minimizes the natural Euclidean distance from each raw point to the respective geometry feature. A nice property of this formulation is that the geometry features can be analytically solved, drastically reducing the dimension of the numerical optimization. To represent and solve the resultant optimization problem more efficiently, this paper then adopts and formalizes the concept of point cluster, which encodes all raw points associated to the same feature by a compact set of parameters, the point cluster coordinates. We derive the closed-form derivatives, up to the second order, of the BA optimization based on the point cluster coordinates and show their theoretical properties such as the null spaces and sparsity. Based on these theoretical results, this paper develops an efficient second-order BA solver. Besides estimating the lidar poses, the solver also exploits the second order information to estimate the pose uncertainty caused by measurement noises, leading to consistent estimates of lidar poses. Moreover, thanks to the use of point cluster, the developed solver fundamentally avoids the enumeration of each raw point in all steps of the optimization: cost evaluation, derivatives evaluation and uncertainty evaluation. The implementation of our method is open sourced to benefit the robotics community.

In this article, we propose a novel light detection and ranging (LiDAR)(-inertial) odometry and mapping framework to achieve the goal of simultaneous localization and meshing in real time. This proposed framework termed immediately meshing (ImMesh) comprises four tightly-coupled modules: receiver, localization, meshing, and broadcaster. The localization module first utilizes the preprocessed sensor data from the receiver, estimates the sensor pose online by registering LiDAR scans to maps, and dynamically grows the map. Then, our meshing module takes the registered LiDAR scan for incrementally reconstructing the triangle mesh on the fly. Finally, the real-time odometry, map, and mesh are published via our broadcaster. The primary contribution of this work is the meshing module, which represents a scene by an efficient voxel structure, performs fast finding of voxels observed by new scans, and incrementally reconstructs triangle facets in each voxel. This voxel-wise meshing operation is delicately designed for the purpose of efficiency; it first performs a dimension reduction by projecting 3-D points to a 2-D local plane contained in the voxel, and then executes the meshing operation with pull, commit, and push steps for incremental reconstruction of triangle facets. To the best of authors' knowledge, this is the first work in the literature that can reconstruct online the triangle mesh of large-scale scenes, just relying on a standard CPU without GPU acceleration.

The conversion of lignocellulosic biomass to chemical fuel can achieve the sustainable use of lignocellulosic biomass, but it was limited by the lack of an effective conversion strategy. Here, we reported a unique approach of photothermal catalysis by using MoS2-reduced graphene oxide (MoS2/RGO) as the catalyst to convert lignocellulosic biomass into H2fuel in alkaline solution. The RGO acting as a support for the growth of MoS2results in the high exposed Mo edges, which act as efficient Lewis acidic sites for the oxygenolysis of lignocellulosic biomass dissolved in alkaline solution. The broad light absorption capacity and abundant Lewis acidic sites make MoS2/RGO to be efficient catalysts for photothermal catalytic H2production from lignocellulosic biomass, and the H2generation rate with respect to catalyst under 300 W Xe lamp irradiation in cellulose, rice straw, wheat straw, polar wood chip, bamboo, rice hull, and corncob aqueous solution achieve 223, 168, 230, 564, 390, 234, and 55 μmol·h–1·g–1, respectively. It is believed that this photothermal catalysis is a simple and “green” approach for the lignocellulosic biomass-to-H2conversion, which would have great potential as a promising approach for solar energy-driven H2production from lignocellulosic biomass.

A nickel hydride-catalyzed regio- and enantioselective hydroalkylation reaction was developed to give access to a library of chiral β- or γ-branched aromatic N-heterocycles. This intriguing asymmetric transformation features excellent selectivities, step- and atom-economies, and generating two kinds of chiral products through one synthetic strategy. Furthermore, the possible reaction mechanism was extensively investigated using numerous control experiments and density functional theory calculations.

An asymmetric conjugate addition of aldehydes with o-azaxylylene intermediates (indol-2-ones) from 3-bromooxindoles has been developed. The use of a novel spiro-pyrrolidine (SPD)-derived bifunctional N-sulfonylated amide catalyst is essential for a highly diastereo- and enantioselective transformation to provide a wide array of enantioenriched C3 quaternary oxindoles with structurally diverse β-aldehyde appendages. Further application of this synthetic methodology enables the construction of the tricyclic cores of akuammiline-type alkaloids.