Linking chromatin acylation mark-defined proteome and genome in living cells.

A generalizable strategy with programmable site specificity for in situ profiling of histone modifications on unperturbed chromatin remains highly desirable but challenging. We herein developed a single-site-resolved multi-omics (SiTomics) strategy for systematic mapping of dynamic modifications and subsequent profiling of chromatinized proteome and genome defined by specific chromatin acylations in living cells. By leveraging the genetic code expansion strategy, our SiTomics toolkit revealed distinct crotonylation (e.g., H3K56cr) and ß-hydroxybutyrylation (e.g., H3K56bhb) upon short chain fatty acids stimulation and established linkages for chromatin acylation mark-defined proteome, genome, and functions. This led to the identification of GLYR1 as a distinct interacting protein in modulating H3K56cr's gene body localization as well as the discovery of an elevated super-enhancer repertoire underlying bhb-mediated chromatin modulations. SiTomics offers a platform technology for elucidating the "metabolites-modification-regulation" axis, which is widely applicable for multi-omics profiling and functional dissection of modifications beyond acylations and proteins beyond histones.

Increased transcriptional elongation and RNA stability of GPCR ligand binding genes unveiled via RNA polymerase II degradation.

RNA polymerase II drives mRNA gene expression, yet our understanding of Pol II degradation is limited. Using auxin-inducible degron, we degraded Pol II's RPB1 subunit, resulting in global repression. Surprisingly, certain genes exhibited increased RNA levels post-degradation. These genes are associated with GPCR ligand binding and are characterized by being less paused and comprising polycomb-bound short genes. RPB1 degradation globally increased KDM6B binding, which was insufficient to explain specific gene activation. In contrast, RPB2 degradation repressed nearly all genes, accompanied by decreased H3K9me3 and SUV39H1 occupancy. We observed a specific increase in serine 2 phosphorylated Pol II and RNA stability for RPB1 degradation-upregulated genes. Additionally, α-amanitin or UV treatment resulted in RPB1 degradation and global gene repression, unveiling subsets of upregulated genes. Our findings highlight the activated transcription elongation and increased RNA stability of signaling genes as potential mechanisms for mammalian cells to counter RPB1 degradation during stress.

Predictive Path-Tracking Control of an Autonomous Electric Vehicle with Various Multi-Actuation Topologies.

This paper presents the development of path-tracking control strategies for an over-actuated autonomous electric vehicle. The vehicle platform is equipped with four-wheel steering (4WS) as well as torque vectoring (TV) capabilities, which enable the control of vehicle dynamics to be enhanced. A nonlinear model predictive controller is proposed taking into account the nonlinearities in vehicle dynamics at the limits of handling as well as the crucial actuator constraints. Controllers with different actuation formulations are presented and compared to study the path-tracking performance of the vehicle with different levels of actuation. The controllers are implemented in a high-fidelity simulation environment considering scenarios of vehicle handling limits. According to the simulation results, the vehicle achieves the best overall path-tracking performance with combined 4WS and TV, which illustrates that the over-actuation topology can enhance the path-tracking performance during conditions under the limits of handling. In addition, the performance of the over-actuation controller is further assessed with different sampling times as well as prediction horizons in order to investigate the effect of such parameters on the control performance, and its capability for real-time execution. In the end, the over-actuation control strategy is implemented on a target machine for real-time validation. The control formulation proposed in this paper is proven to be compatible with different levels of actuation, and it is also demonstrated in this work that it is possible to include the particular over-actuation formulation and specific nonlinear vehicle dynamics in real-time operation, with the sampling time and prediction time providing a compromise between path-tracking performance and computational time.

Electrical stimulation alters DNA methylation and promotes neurite outgrowth.

Electrical stimulation (ES) influences neural regeneration and functionality. We here investigate whether ES regulates DNA demethylation, a critical epigenetic event known to influence nerve regeneration. Retinal ganglion cells (RGCs) have long served as a standard model for central nervous system neurons, whose growth and disease development are reportedly affected by DNA methylation. The current study focuses on the ability of ES to rescue RGCs and preserve vision by modulating DNA demethylation. To evaluate DNA demethylation pattern during development, RGCs from mice at different stages of development, were analyzed using qPCR for ten-eleven translocation (TETs) and immunostained for 5 hydroxymethylcytosine (5hmc) and 5 methylcytosine (5mc). To understand the effect of ES on neurite outgrowth and DNA demethylation, cells were subjected to ES at 75 µAmp biphasic ramp for 20 min and cultured for 5 days. ES increased TETs mediated neurite outgrowth, DNA demethylation, TET1 and growth associated protein 43 levels significantly. Immunostaining of PC12 cells following ES for histone 3 lysine 9 trimethylation showed cells attained an antiheterochromatin configuration. Cultured mouse and human retinal explants stained with ß-III tubulin exhibited increased neurite growth following ES. Finally, mice subjected to optic nerve crush injury followed by ES exhibited improved RGCs function and phenotype as validated using electroretinogram and immunohistochemistry. Our results point to a possible therapeutic regulation of DNA demethylation by ES in neurons.

4D Printing of Butterfly Scale-Inspired Structures for Wide-Angle Directional Liquid Transport.

Unidirectional liquid transport has been extensively explored for water/fog harvesting, electrochemical sensing, and desalination. However, current research mainly focuses on linear liquid transport (transport angle α = 0°), which exhibits hindered lateral liquid spreading and low unidirectional transport efficiency. Inspired by the wide-angle (0° < α < 180°) liquid transport on butterfly wings, this work successfully achieves linear (α = 0°), wide-angle, and even ultra-wide-angle (α = 180°) liquid transport by four-dimensional (4D) printing of butterfly scale-inspired re-entrant structures. These asymmetric re-entrant structures can achieve unidirectional liquid transport, and their layout can control the Laplace pressure in the forward (structure-tilting) and lateral directions to adjust the transport angle. Specifically, high transport efficiency and programmable forward/lateral transport paths are simultaneously achieved by the ultra-wide-angle transport, where liquid fills the lateral path before being transported forward. Moreover, the ultra-wide-angle transport is also validated in 3D space, which provides an innovative platform for advanced biochemical microreaction, large-area evaporation, and self-propelled oil-water separation.

A simple polarimetric measurement based on a computational algorithm.

A simple and compact polarimeter comprising two electrically controlled liquid-crystal variable retarders (LCVRs) and a linear polarizer is demonstrated, which is enabled by analyzing the intensity variation of the modulated output light based on a computational algorithm. A proof-of-concept prototype is presented, which is mounted onto a power meter or a CMOS camera for the intensity data collection. The polarimetric measurement for the spatial variant polarization states of light is also verified, indicating the possibility of achieving a resolution-lossless polarimeter. Thus, our proposed method shows a cost-effective way to realize a compact polarimeter in polarization optics.

Experimental Demonstration of Laser Guiding and Wakefield Acceleration in a Curved Plasma Channel.

Curved plasma channels have been proposed to guide intense lasers for various applications, such as x-ray laser emission, compact synchrotron radiation, and multistage laser wakefield acceleration [e.g. J. Luo et al., Phys. Rev. Lett. 120, 154801 (2018)PRLTAO0031-900710.1103/PhysRevLett.120.154801]. Here, a carefully designed experiment shows evidences of intense laser guidance and wakefield acceleration in a centimeter-scale curved plasma channel. Both experiments and simulations indicate that when the channel curvature radius is gradually increased and the laser incidence offset is optimized, the transverse oscillation of the laser beam can be mitigated, and the stably guided laser pulse excites wakefields and accelerates electrons along the curved plasma channel to a maximum energy of 0.7 GeV. Our results also show that such a channel exhibits good potential for seamless multistage laser wakefield acceleration.

Sensor Fusion and Advanced Controller for Connected and Automated Vehicles.

Nowadays, intelligent vehicles are equipped with a number of advanced sensors, such as radar and cameras [...].

A Study on Dynamic Motion Planning for Autonomous Vehicles Based on Nonlinear Vehicle Model.

Autonomous driving technology, especially motion planning and the trajectory tracking method, is the foundation of an intelligent interconnected vehicle, which needs to be improved urgently. Currently, research on path planning methods has improved, but few of the current studies consider the vehicle's nonlinear characteristics in the reference model, due to the heavy computational effort. At present, most of the algorithms are designed by a linear vehicle model in order to achieve the real-time performance at the cost of lost accuracy. To achieve a better performance, the dynamics and kinematics characteristics of the vehicle must be simulated, and real-time computing ensured at the same time. In this article, a Takagi-Sugeno fuzzy-model-based closed-loop rapidly exploring random tree algorithm with on-line re-planning process is applied to build the motion planner, which effectively improves the vehicle performance of dynamic obstacle avoidance, and plans the local obstacle avoidance path in line with the dynamic characteristics of the vehicle. A nonlinear vehicle model is integrated into the motion planner design directly. For fast local path planning mission, the Takagi-Sugeno fuzzy modelling method is applied to the modeling process in the planner design, so that the vehicle state can be directly utilized into the path planner to create a feasible path in real-time. The performance of the planner was evaluated by numerical simulation. The results demonstrate that the proposed motion planner can effectively generate a reference trajectory that guarantees driving efficiency with a lower re-planning rate.

New Generation Federated Learning.

With the development of the Internet of things (IoT), federated learning (FL) has received increasing attention as a distributed machine learning (ML) framework that does not require data exchange. However, current FL frameworks follow an idealized setup in which the task size is fixed and the storage space is unlimited, which is impossible in the real world. In fact, new classes of these participating clients always emerge over time, and some samples are overwritten or discarded due to storage limitations. We urgently need a new framework to adapt to the dynamic task sequences and strict storage constraints in the real world. Continuous learning or incremental learning is the ultimate goal of deep learning, and we introduce incremental learning into FL to describe a new federated learning framework. New generation federated learning (NGFL) is probably the most desirable framework for FL, in which, in addition to the basic task of training the server, each client needs to learn its private tasks, which arrive continuously independent of communication with the server. We give a rigorous mathematical representation of this framework, detail several major challenges faced under this framework, and address the main challenges of combining incremental learning with federated learning (aggregation of heterogeneous output layers and the task transformation mutual knowledge problem), and show the lower and upper baselines of the framework.

A Three-Dimensional Integrated Non-Linear Coordinate Control Framework for Combined Yaw- and Roll-Stability Control during Tyre Blow-Out.

A tyre blow-out can greatly affect vehicle stability and cause serious accidents. In the literature, however, studies on comprehensive three-dimensional vehicle dynamics modelling and stability control strategies in the event of a sudden tyre blow-out are seriously lacking. In this study, a comprehensive 14 degrees-of-freedom (DOF) vehicle dynamics model is first proposed to describe the vehicle yaw-plane and roll-plane dynamics performance after a tyre blow-out. Then, based on the proposed 14 DOF dynamics model, an integrated control framework for a combined yaw plane and roll-plane stability control is presented. This integrated control framework consists of a vehicle state predictor, an upper-level control mode supervisor and a lower-level 14 DOF model predictive controller (MPC). The state predictor is designed to predict the vehicle's future states, and the upper-level control mode supervisor can use these future states to determine a suitable control mode. After that, based on the selected control mode, the lower-level MPC can control the individual driving actuator to achieve the combined yaw plane and roll plane control. Finally, a series of simulation tests are conducted to verify the effectiveness of the proposed control strategy.

A comparative study of clinical effect of total knee arthroplasty in the treatment of primary osteoarthritis and osteoarthritis of Kashin-Beck disease.

OBJECTIVE: To evaluate the clinical efficacy of total knee arthroplasty (TKA) in the treatment of primary osteoarthritis (OA) and osteoarthritis of Kashin-Beck disease (KBD). METHODS: This study enrolled 77 KBD patients (77 knees, KBD-TKA) and 75 OA patients (75 knees, OA-TKA) who underwent TKA from September 2008 to June 2018. Clinical assessments for each patient were performed pre-operatively and last follow-up. The efficacy measures included the visual analogue scale (VAS) pain score, range of motion (ROM), Hospital for Special Surgery (HSS) score, and short form 36 Health Survey (SF-36) as well as related influencing factors between the two groups. RESULTS: All patients were followed up; the follow-up time of KBD-TKA was 14-132 months, with an average of 72.68 ± 37.55 months; OA-TKA was 15-120 months, with an average of 49.2 ± 28.91 months. There was no difference in pre-operative VAS score (7.29 vs. 7.24) and SF-36 (PCS) score (4.87 vs. 5.49) between KBD-TKA and OA-TKA (P > 0.05), while compared with OA, KBD-TKA had significantly worse pre-operative ROM (75.48° vs. 82.87°), HSS score (36.40 vs. 41.84), and SF-36 (MCS) score (26.28 vs. 28.73) (P < 0.05). At the final follow-up, there was no significant difference in VAS score (1.13 vs. 1.16), ROM (105.79 vs. 105.79), and HSS score (92.06 vs. 92.25) between KBD-TKA and OA-TKA (P > 0.05), while compared with OA, KBD-TKA had significantly worse SF-36 (PCS) score (36.90 vs. 42.00) and SF-36 (MCS) score (55.16 vs. 59.70) (P < 0.05). In a multivariate regression, controlling for multiple potential confounders, diagnosis of KBD was associated with poor quality of life after surgery, whereas pre-operative pain was specifically associated with post-operative pain. However, preoperative gender, age, BMI, and the angles of knee prosthesis (before and after surgery) were not associated with post-operative outcome. CONCLUSION: Patients with KBD undergoing primary TKA have excellent outcomes, comparable with OA at the final follow-up, in spite of worse pre-operative ROM, HSS score, and SF-36(MCS) score. However, KBD patients are worse than OA in terms of general health. Pre-operative age, gender, BMI, and the angles of knee prosthesis were not the factors influencing the clinical efficacy of TKA. The diagnosis of KBD was an independent risk factor for poor quality of life after TKA. Pre-operative pain was a clinically important predictor of outcome.

Eosin Y sensitized BiPO4 nanorods for bi-functionally enhanced visible-light-driven photocatalysis.

In this work, we report a novel photocatalyst of Eosin Y dye sensitized BiPO4 nanorods via a low-temperature and impregnation adsorption method. It shows enhanced visible-light-driven photocatalytic activity for degrading methylene blue (MB) and 2,4-DCP compared to that of pristine BiPO4 nanorods. The mass ratio of Eosin Y/BiPO4 is varied from 5 wt% to 30 wt% and the optimum value is 15 wt%, showing 46.7 and 10.5 fold greater apparent reaction rates than pristine BiPO4. Moreover, all of the reduced MB was transformed into CO2 and H2O during the photocatalysis, showing the good mineralization ability (almost 100%) of the composite. Furthermore, the photocatalytic mechanism of the composite is also investigated here by the zeta potential, scavenger experiments, Electron Paramagnetic Resonance (EPR), Photoluminescence Spectroscopy (PL), and a series of electrochemical analyses. The results show that (i) e- is the main reactive species and (ii) Eosin Y coated and adsorbed on BiPO4, thus widening the response range to the visible light region and accelerating the charge separation/transfer, resulting in bi-functionally promoted activity.

Isolated elliptically polarized attosecond soft X-ray with high-brilliance using polarization gating of harmonics from relativistic plasmas at oblique incidence.

The production of intense isolated attosecond pulse is a major goal in ultrafast research. Recent advances in high harmonic generation from relativistic plasma mirrors under oblique incidence interactions gave rise to photon-rich attosecond pulses with circular or elliptical polarization. However, to achieve an isolated elliptical attosecond pulse via polarization gating using currently available long driving pulses remains a challenge, because polarization gating of high harmonics from relativistic plasmas is assumed only possible at normal or near-normal incidence. Here we numerically demonstrate a scheme around this problem. We show that via control of plasma dynamics by managing laser polarization, it is possible to gate an intense single attosecond pulse with high ellipticity extending to the soft X-ray regime at oblique incidence. This approach thus paves the way towards a powerful tool enabling high-time-resolution probe of dynamics of chiral systems and magnetic materials with current laser technology.

Constructed wetland using corncob charcoal substrate: pollutants removal and intensification.

To investigate the feasibility of using corncob charcoal substrate in constructed wetlands, four laboratory-scale vertical flow constructed wetlands (VFCWs) were built. Effluent pollutant (chemical oxygen demand (COD), NH4+-N, total phosphorus (TP)) concentrations during the experiment were determined to reveal pollutant removal mechanisms and efficiencies at different stages. In the stable stage, a VFCW using clay ceramisite substrate under aeration attained higher COD (95.1%), and NH4+-N (95.1%) removal efficiencies than a VFCW using corncob charcoal substrate (91.5% COD, 91.3% NH4+-N) under aeration, but lower TP removal efficiency (clay ceramisite 32.0% and corncob charcoal 40.0%). The VFCW with raw corncob substrate showed stronger COD emissions (maximum concentration 3,108 mg/L) than the corncob charcoal substrate (COD was lower than influent). The VFCW using corncob charcoal substrate performed much better than the VFCW using clay ceramisite substrate under aeration when the C/N ratio was low (C/N = 1.5, TN removal efficiency 36.89%, 4.1% respectively). These results suggest that corncob charcoal is a potential substrate in VFCWs under aeration with a unique self -supplying carbon source property in the denitrification process.

Sperm freezing damage: the role of regulated cell death.

Substantial progress in research on sperm cryopreservation has occurred since the twentieth century, especially focusing on improving sperm freezing procedures and optimizing semen extenders. However, the cellular biological mechanisms of sperm freezing damage are still unclear, which greatly restricts the promotion and development of sperm cryopreservation. An essential component of sperm freezing damage is the occurrence of cell death. Considering the existence of multiple types of cell death pathways, this review discusses connections between characteristics of regulated cell death (e.g., apoptosis and ferroptosis), and accidental cell death (e.g., intracellular ice crystals) with sperm freezing damage and explores possible future research directions in this field.

Servo torque fault diagnosis implementation for heavy-legged robots using insufficient information.

The reliability of sensors and servos is paramount in diagnosing the Heavy-Legged Robot (HLR). Servo faults stemming from mechanical wear, environmental disturbances, or electrical issues pose significant challenges to traditional diagnostic methods, which rely heavily on delicate sensors. This study introduces a framework that solely relies on joint position and permanent magnet synchronous motor (PMSM) information to mitigate dependency on fragile sensors for servo-fault diagnosis. An essential contribution involves refining a model that directly connects PMSM currents to HLR motion. Moreover, to address scenarios where actual servo outputs and HLR cylinder velocities are unavailable, an improved sliding mode observer (ISMO) is proposed. Additionally, a Fourier expansion model characterizes the relationship between operation time and fault-free disturbance in the HLR. Subsequently, the dual-line particle filter (DPF) algorithm is employed to predict fault-free disturbance. The outputs of DPF serve as a feedforward to the ISMO, enabling the real-time servo torque fault diagnosis. The accuracy and validity of this technical framework are verified through various simulations in MATLAB/SIMSCAPE and real-world experiments.

On-Demand Optimization of Colorimetric Gas Sensors Using a Knowledge-Aware Algorithm-Driven Robotic Experimental Platform.

Synthesizing the best material globally is challenging; it needs to know what and how much the best ingredient composition should be for satisfying multiple figures of merit simultaneously. Traditional one-variable-at-a-time methods are inefficient; the design-build-test-learn (DBTL) method could achieve the optimal composition from only a handful of ingredients. A vast design space needs to be explored to discover the possible global optimal composition for on-demand materials synthesis. This research developed a hypothesis-guided DBTL (H-DBTL) method combined with robots to expand the dimensions of the search space, thereby achieving a better global optimal performance. First, this study engineered the search space with knowledge-aware chemical descriptors and customized multiobjective functions to fulfill on-demand research objectives. To verify this concept, this novel method was used to optimize colorimetric ammonia sensors across a vast design space of as high as 19 variables, achieving two remarkable optimization goals within 1 week: first, a sensing array was developed for ammonia quantification of a wide dynamic range, from 0.5 to 500 ppm; second, a new state-of-the-art detection limit of 50 ppb was reached. This work demonstrates that the H-DBTL approach, combined with a robot, develops a novel paradigm for the on-demand optimization of functional materials.

Improving the accuracy of bone mineral density using a multisource CBCT.

Multisource cone beam computed tomography CBCT (ms-CBCT) has been shown to overcome some of the inherent limitations of a conventional CBCT. The purpose of this study was to evaluate the accuracy of ms-CBCT for measuring the bone mineral density (BMD) of mandible and maxilla compared to the conventional CBCT. The values measured from a multi-detector CT (MDCT) were used as substitutes for the ground truth. An anthropomorphic adult skull and tissue equivalent head phantom and a homemade calibration phantom containing inserts with varying densities of calcium hydroxyapatite were imaged using the ms-CBCT, the ms-CBCT operating in the conventional single source CBCT mode, and two clinical CBCT scanners at similar imaging doses; and a clinical MDCT. The images of the anthropomorphic head phantom were reconstructed and registered, and the cortical and cancellous bones of the mandible and the maxilla were segmented. The measured CT Hounsfield Unit (HU) and Greyscale Value (GV) at multiple region-of-interests were converted to the BMD using scanner-specific calibration functions. The results from the various CBCT scanners were compared to that from the MDCT. Statistical analysis showed a significant improvement in the agreement between the ms-CBCT and MDCT compared to that between the CBCT and MDCT.

Low-cost dual-energy CBCT by spectral filtration of a dual focal spot X-ray source.

Dual-energy cone beam computed tomography (DE-CBCT) has been shown to provide more information and improve performance compared to a conventional single energy spectrum CBCT. Here we report a low-cost DE-CBCT by spectral filtration of a carbon nanotube x-ray source array. The x-ray photons from two focal spots were filtered respectively by a low and a high energy filter. Projection images were collected by alternatively activating the two beams while the source array and detector rotated around the object, and were processed by a one-step materials decomposition and reconstruction method. The performance of the DE-CBCT scanner was evaluated by imaging a water-equivalent plastic phantom with inserts containing known densities of calcium or iodine and an anthropomorphic head phantom with dental implants. A mean energy separation of 15.5 keV was achieved at acceptable dose rates and imaging time. Accurate materials quantification was obtained by materials decomposition. Metal artifacts were reduced in the virtual monoenergetic images synthesized at high energies. The results demonstrated the feasibility of high quality DE-CBCT imaging by spectral filtration without using either an energy sensitive detector or rapid high voltage switching.