Search

Given the intrinsic low energy and high consumption characteristics of sensor nodes, it is imperative to explore strategies for achieving energy-efficient routing within wireless sensor networks (WSNs). A significant body of existing research on clustered routing algorithms for WSNs has concentrated on employing heuristic optimization algorithms to facilitate the selection of routing paths. However, once the number of sensor nodes or the deployment environment changes, the algorithm’s performance can fluctuate significantly, potentially requiring redesign and retuning. In this article, we propose the clustered routing algorithm based on forwarding mechanism optimization (CRFMO), which defines separate routing rules for intracluster and intercluster communication, providing suitable communication paths for nodes. The algorithm eschews the complex procedure of parameter tuning during the routing path selection process and contributes to expediting WSN deployment and balancing node load pressure, ultimately extending the network’s operational lifespan. Simulation outcomes reveal that, in comparison to LEACH-IACA and IMP-LEACH, the CRFMO algorithm markedly enhances energy distribution balance, equalizes the burden among nodes, sustains high network coverage over an extended period, which enhances the quality of network monitoring, and significantly extends the lifetime of the network.

This article proposes a novel design strategy to realize multifunctional reflective surface polarization converters based on the concept of linear-to-circular polarization decomposition. By decomposing the linearly polarized incident wave into a pair of orthogonal circularly polarized waves, namely, a right-handed circularly polarized (RHCP) wave and a left-handed circularly polarized (LHCP) wave, and controlling the phase states of the two circularly polarized components independently, various polarization conversion functions may be achieved. A reflective surface unit cell consisting of a square patch and a 90° hybrid coupler is proposed to facilitate the linear-to-circular polarization decomposition, allowing to adjust the phase states of the two circularly polarized components by adding different phase shifters at the end of the hybrid coupler. Three different functions including linear-to-dual-polarization conversion, simultaneous linear polarization rotation and beam steering, and radar cross section (RCS) reduction are realized based on the proposed reflective surface unit cell. The proposed design strategy is theoretically analyzed and demonstrated by three reflective surfaces corresponding to the three functions with both full-wave simulation and experiment.

This paper focuses on the trajectory planning problem in highly complex and irregular parking lot scenarios. We formulate this problem as an optimal control problem (OCP) according to the requirements of the task and propose a planner to solve it numerically. To ensure optimal planning results, the proposed planner consists of three procedures, which are responsible for generating the guiding route, constructing the collision-free tunnel, and optimizing the trajectory, respectively. Firstly, we use the generalized Voronoi graph (GVG) to build an equidistant roadmap and propose an improved adaptive A* algorithm (IAA*) to improve the time efficiency of the guiding route generation process. Secondly, we employ a coarse trajectory to guide a homotopic route and replace the intractably scaled collision-avoidance constraints with within-tunnel constraints, which are small-scale and independent of the environment’s complexity. Our tunnel construction method ensures the integrity of the free spaces, so that repeated construction is not necessary. Finally, in the process of trajectory optimization, we propose a lightweight OCP iterative solution framework to search for the optimal solution with high computational efficiency, in which the customized OCP with only box constraints is quickly solved in each iteration. Besides, the theoretical analysis, numerical simulations, and real-world experiments had been carried out to demonstrate the effectiveness and efficiency of the method.

The utilization of vanadium titano-magnetite concentrate (VTM) for pellet preparation poses challenges in terms of low consolidation strength and high energy consumption during the thermal process. The effect and function mechanism of high-pressure grinding roll (HPGR) pretreatment on the preparation of VTM pellets were investigated. The results indicate that HPGR pretreatment increased the strength of the pellets prepared by VTM and decreased the thermal processing temperature and time. The main reason can be attributed to the reduced particle size of VTM, accompanied by an increase in specific surface area, iron-bearing mineral liberation, and improved interfacial hydrophilicity and particle ballability. Moreover, HPGR pretreatment reduced the crystallite size of VTM and increased lattice microstrain and amorphousness, leading to a 13.21 kJ/mol improvement in the mechanical energy storage of titanomagnetite. The increased specific surface area was a crucial factor in strengthening the preparation of VTM pellets, which increased the contacting points participated in interface physicochemical reactions. The enhanced hydrophilicity and ballability were beneficial to improving the strength of green pellets, while the increased strength of roasted pellets was primarily attributed to the iron-containing mineral liberation and crystal mechanical activation, which promoted the oxidation of iron-bearing minerals and the microcrystalline diffusion and connection. Compared with the untreated VTM, the compressive strength of roasted pellets increased from 2168 N P−1(Newton per pellet) to 2813 N P−1when the roller pressure intensity was 12 MPa, and the proper roasting temperature could be reduced by more than 50 °C.

There are inevitably a large number of uncertainties in the actual engineering structures. How to measure the degree of influence of the uncertainty of input variables on structural response is an important issue in structural design. Global sensitivity analysis is an effective means of addressing this problem, in which, the non-probabilistic reliability sensitivity analysis method has received more attention because it is not restricted by the distribution type of random variables. However, the non-probabilistic importance analysis method requires optimization analysis to obtain the extreme values of the performance function, resulting in its application in practical engineering problems being somewhat limited. To address this problem, this paper firstly proposed an efficient optimization method based on the high-dimensional model decomposition and Taylor expansion series combined with the quadratic function; Secondly, the non-probabilistic reliability importance analysis method is improved based on the proposed optimization method; Finally, two numerical cases are utilized to illustrate the accuracy and efficiency of the proposed method, and an engineering example is used to illustrate the engineering practicality of the proposed method. It was found that regardless of the value of the safety threshold, it affects only the non-probability reliability indicators and has little effect on the magnitude of the non-probability reliability importance indicators and the order of importance of the parameters.

In this article, a 2-bit reconfigurable reflective metasurface (RRM) with multifunction for both far-field pattern and polarization performance is proposed. To facilitate the independent design of two orthogonal polarizations as well as the diode integration at the bottom, the radiation and phase shifting parts are designed separately. The top patch is designed to receive and reradiate electromagnetic (EM) waves, which converts the wave states between free-space waves and guided waves. The bottom phase shifting structure is designed to switch four phase states with a 90° interval for the reflected guided wave. An $8\times8$ RRM is designed and fabricated using the proposed 2-bit element. Driven by a field programmable gate array (FPGA), the RRM achieves real-time control for different functions of beam deflection, radar cross Section (RCS) reduction, and polarization conversion. The measured results show that the steered beam from −30° to +30° can be obtained around 3.83 GHz with different coding matrices, and more than 10 dB RCS reduction from 3.70 to 3.84 GHz can be achieved by properly distributing phase responses randomly; moreover, a linear polarization (LP) to left-handed circular polarization (LHCP) conversion in the range 3.82–3.85 GHz and right-handed circular polarization (RHCP) conversion in the range 3.68–3.82 GHz are realized by switching all the p-i-n diodes ON and OFF.

This article presents a high-sensitivity magnetic tactile sensor comprising a dipole magnetic film and a ${z}$ -axis Hall sensor. The tactile sensor primarily focuses on pressure response along the ${z}$ -axis, minimizing interference from magnetic fields in other axes and thereby simplifying signal processing complexity. To enhance the overall performance of the tactile sensor, a qualitative analysis and structural optimization are conducted on both the magnetic film and the Hall sensor. The magnetic film is optimized by comparing different thicknesses and magnetic powder mass fractions, and the Hall sensor undergoes structural optimization through a comparative analysis of different length-to-width ( ${L}/{W}{)}$ ratios. By embedding the Hall sensor into the printed circuit board (PCB), we can ensure a snug fit with the ultrathin flat magnetic film, resulting in an advantageous packaging effect. Employing these approaches, we substantially improve sensitivity, measuring at 5.92 Gs/N, surpassing the sensitivity level (about 0.17 Gs/N) reported in previous works by one order of magnitude. Finally, the device performs comprehensive characterizations, revealing excellent properties, including low hysteresis (6.82%), the rapid response time (< 2 ms), remarkable stability (0.09%), and high repeatability (0.48%). This research will actively promote the development of tactile sensors, which offer substantial applications in robotics, health monitoring, and electronic skin devices.

Wireless sensor network (WSN) is usually deployed in unattended monitoring environments, with limited energy and large-scale characteristics. Therefore, the performance of WSN is susceptible to the influence of external environment and its own energy. The existing routing protocols try to optimize energy efficiency and routing reliability from the perspective of the network itself. However, they do not take into account the environmental impact from the outside, which makes them unable to properly respond to harsh environment. Therefore, a new environment fusion routing protocol (EFRP) is proposed. Cluster heads (CHs) are selected in a probabilistic manner according to the ratio of the energy of each node and environmental factors. Nodes with excellent environment have a higher probability of being selected as CHs. Besides, the EFRP optimal path is determined according to the comprehensive potential field superimposed by the distance field, residual energy field, and environmental field. The best path can be weighed among delay, energy saving, and routing invulnerability. Therefore, the balance of network energy is realized, and the invulnerability of the network in harsh environment is improved. The experimental results show that EFRP can significantly improve the data transmission and invulnerability of the network in harsh environments.

This article presents a complementary metal-oxide semiconductor (CMOS)-microelectromechanical system (MEMS) monolithic integrated thermal flow sensor system, which consists of a MEMS sensor with dual pairs of thermistors, a precise constant temperature difference (CTD) control circuit, and a low-noise readout circuit with a current feedback instrument amplifier (CFIA). The MEMS sensor is fabricated using an in-house developed post-CMOS process, while its sensing structure is thinned to 2.52 $\mu \text{m}$ for power reduction. Meanwhile, the distance between the microheater and thermistors is optimized with a linear range of larger than ±4 m/s by the Peclet number (Pe) < 1 criterion. The designed CTD control circuit can offer a driving current of 1.88 mA with an output swing of up to 2.82 V, which enables the microheater to operate in 50-K CTD mode with a deviation of less than 0.01 K. Additionally, the designed CFIA has a noise floor of 12.4 nV/rtHz with a 1/f corner of less than 400 mHz. The performance of the system-on-chip (SoC) sensor is evaluated with N2 gas flow. The SoC sensor has a high sensitivity of 156 mV/(m/s) with a detectable flow range of up to ±11 m/s, while its system power is less than 5 mW. The SoC sensor also has state-of-the-art linearity in a range of ±6 m/s and a detection limit down to 86 $\mu \text{m}$ /s. Moreover, the tested results of this SoC sensor are in good agreement with the theoretical models, confirming the feasibility of the proposed design strategy.

We propose a novel transient partial differential equation (PDE) model for the development of highly sensitive microthermal expansion-based angular motion ( $\mu $ TEAM) sensors based on the study of time-dependent response. With the efficient prediction of thermal time constant ( $\tau ^{\ast} $ ) based on the PDE model, which is >2200 times faster than 3-D CFD simulation (32.67 s versus >20 h) and was validated by the experimental results, the parametric analysis has been conducted for design optimization. The $\mu $ TEAM sensors with three pairs of temperature detectors (TDs) were adopted for the systematic study of the PWM frequency ( ${f} _{\text {PWM}}$ ) effect on the sensor performance to identify the optimal ${f} _{\text {PWM}}$ ( ${f} _{\text {o}}$ ), which can optimize the sensitivity by >11%. Based on the time-dependent analysis of our PDE model, ${f} _{\text {o}}$ was verified to be dominated by the thermal response of the sensor. A generalized “Phase Diagram” regarding the normalized sensitivity ( $S^{\ast} $ ) was presented, for the first time, as a function of ${f} _{\text {PWM}}$ and the normalized heater-to-detector distance ( ${D} _{x}/{L} _{x}$ ). Accordingly, an optimal region, where $S^{\ast} \ge0.95$ , was identified to successfully develop an SF 6-based $\mu $ TEAM sensor with a high sensitivity of 1.5631 mV/°/s, which was >3.5 times as large as that of the N2-based sensor (0.4203 mV/°/s). In particular, the SF6-based sensor reveals an excellent normalized sensitivity of 0.0487 mV/°/s/mW compared to the reported thermal angular motion sensors (AMSs); thus, the comprehensive study based on the PDE model enables the significant improvement of sensor sensitivity and would be useful for system-level integration in the future.

α-Synuclein (α-Syn) is an intrinsically disordered protein whose aggregation in the brain has been significantly implicated in Parkinson’s disease (PD). Beyond the brain, oligomers of α-Synuclein are also found in cerebrospinal fluid (CSF) and blood, where the analysis of these aggregates may provide diagnostic routes and enable a better understanding of disease mechanisms. However, detecting α-Syn in CSF and blood is challenging due to its heterogeneous protein size and shape, and low abundance in clinical samples. Nanopore technology offers a promising route for the detection of single proteins in solution; however, the method often lacks the necessary selectivity in complex biofluids, where multiple background biomolecules are present. We address these limitations by developing a strategy that combines nanopore-based sensing with molecular carriers that can specifically capture α-Syn oligomers with sizes of less than 20 nm. We demonstrate that α-Synuclein oligomers can be detected directly in clinical samples, with minimal sample processing, by their ion current characteristics and successfully utilize this technology to differentiate cohorts of PD patients from healthy controls. The measurements indicate that detecting α-Syn oligomers present in CSF may potentially provide valuable insights into the progression and monitoring of Parkinson’s disease.

In this article, pseudorandom noise (PN) sequence time-modulated reflective metasurfaces are proposed to provide a low-cost, low-complexity, simple solution for target recognition. By covering the target to be recognized with a time-modulated metasurface modulated by a PN time sequence, the metasurface scatters the interrogating harmonic wave into a binary PN-modulated wave. As a result, the radar detector with the foreknowledge of the modulating PN sequence may recognize the target by applying the properties of strong autocorrelation and weak cross correlation of PN sequences and performing cross correlation between the modulating PN sequence and the picked-up signal after downshifting its frequency without actually decoding and reading the scattered information. A 1-bit reconfigurable metasurface unit cell operating at 2.4 GHz is proposed and full-wave simulated to achieve out-of-phase reflective responses by controlling the ON and OFF states of the p-i-n diode for PN time modulation. The target recognition is demonstrated by experiment in two different scenarios where only one metasurface and multiple metasurfaces are present for recognition. The experimental results show that by providing an appropriate threshold in the cross-correlation detecting results, the proposed method can recognize the targets well in both scenarios.

Early control of elevated blood pressure is the most promising treatment for acute intracerebral haemorrhage. We aimed to establish whether implementing a goal-directed care bundle incorporating protocols for early intensive blood pressure lowering and management algorithms for hyperglycaemia, pyrexia, and abnormal anticoagulation, implemented in a hospital setting, could improve outcomes for patients with acute spontaneous intracerebral haemorrhage.

Currently, the prediction of cyanobacterial blooms in rivers and lakes is mainly based on data obtained from on-site water quality monitoring, which cannot analyze the overall water area. Remote sensing images can reflect spatiotemporal and spatial information of the overall water area. However, the existing methods cannot effectively predict the spatial and temporal distribution of overall water bloom by pixel-level prediction of remote sensing images, and the raw remote sensing images often have many problems that cannot be directly used for modeling. Therefore, the method of remote sensing image time series pre-processing is firstly proposed in this paper. Secondly, attentional convolution long short-term memory network embedding to 3D U-Net’s Pix2Pix (ACL3DPix2Pix) is proposed in this paper to achieve pixel-level prediction of remote sensing images. The model generator is a convolutional long short-term memory network (ConvLSTM) embedded into the 3D U-Net network. The attention mechanism is added to the ConvLSTM, the residual structure is added to the 3D U-Net network, and then the loss function of the overall model is updated to achieve pixel-level prediction of remote sensing images. On this basis, the spatial and temporal distribution prediction of cyanobacterial blooms based on remote sensing image analysis is realized by adjusting the existing eutrophication grading criteria of cyanobacterial bloom water bodies. Finally, the experimental results show that the method is effective in predicting cyanobacterial blooms.

ABSTRACTBackgroundSleep plays a critical role in maintaining human health. This study aimed to explore the association between sleep status and thyroid nodules.MethodsA total of 2414 individuals aged 18 or older with euthyroidism were enrolled in this community-based survey. Sleep status was self-reported. Thyroid ultrasonography was performed to measure nodules. Multiple logistic analyses were applied to adjust for confounding factors.ResultsThe percentages of thyroid nodules among individuals who slept <5 hours, 5–8 hours, and >8 hours per night were 57.79% (115/199), 44.19% (833/1885) and 42.73% (141/330), respectively (p = 0.001). Individuals who slept <5 hours per night had a significantly higher percentage of thyroid nodules than those who slept 5–8 hours per night (57.79% vs. 44.19%, p = 0.001) or >8 hours per night (57.79% vs. 42.73%, P < 0.001). However, no similar result was shown between individuals who slept >8 hours and 5–8 hours per night (42.73% vs. 44.19%, p = 0.621). Multiple logistic analysis showed that a sleep duration of <5 hours per night was significantly associated with thyroid nodules (odds ratio (OR) 1.643, 95% confidence interval (CI) 1.084–2.490, p = 0.019) when compared to a sleep duration of >8 hours per night. However, a sleep duration of <5 hours per night was not associated with thyroid nodules compared to a sleep duration of 5–8 hours (OR 1.294, 95% CI 0.918–1.824, p = 0.141). Similarly, no significant differences were seen among sleep duration per day, time of falling asleep, habit of daytime napping or thyroid nodules in multiple logistic analyses (all p > 0.05).ConclusionsShort nighttime sleep duration was associated with thyroid nodules in our community-based population. Screening for thyroid nodules among these individuals is recommended.

Purpose To describe an atypical nodular episcleritis mimicking a solitary giant episcleral mass, which is not attributed to any systemic diseases and identified only after immunohistochemical examination.Case report A sixty-year-old Chinese woman with systemic hypertension presented with 6-month history of giant, solitary and redness epibulbar mass arising from the superior aspect of her left eye. The lesion gradually enlarged, even with 6-month history of irregular topical steroid eye drops treatment. Imaging studies and laboratory test revealed a 10 mm × 8 mm episcleral mass absence of any infection indicator and autoimmune antibody changes. The mass was completely removed before its extension through the deep scleral, histopathologic examination revealed a nodular episcleritis composed of various chronic inflammatory cells infiltration. Topical steroid eye drops treatment combined with oral steroidal anti-inflammatory drugs was then administrated regularly for 1 month, and no recurrence occurred after 1-year follow-up.Conclusion Nodular anterior episcleritis is characterized by underlying chronic inflammation of the anterior episclera and can be presented as asymptomatic episcleral mass. Besides a thorough investigation systemically, tissue biopsy is required for definite diagnosis.

The spotted lanternfly (SLF), Lycorma delicatulaWhite, is native to Asia where it is not a pest. However, it has caused serious damage and economic loss after invading South Korea and the USA. Nowadays it is regarded as a worldwide invasive pest that threatens many crops and trees, especially grapes. In this review we have summarized the biology and ecology of this pest covering its taxonomy and morphology, current and potential distribution and the drivers of its spread, and its biology, behavior and host plants. We also reviewed the economic losses due to this pest invasion and management strategies including quarantine and biocontrol. This information will assist government and landowners to develop effective management strategies and mitigate the loss of agricultural production.

We propose a novel design of a near-field transmitting focused metasurface, which transforms a linearly polarized planar incident wave into a near-field focused beam with multiple foci and multiple nulls in this article. A generalized method of obtaining the metasurface field distribution on its aperture for specified near-field foci and nulls is first introduced. Then, a three-layer metasurface particle structure with close to full range reconfigurable amplitude and phase transmitting response for realizing the required field distribution is studied. By adjusting the arc length and the rotating angle of the middle-layer metasurface particle structure, a transmitting response with arbitrary amplitude and phase is achieved. Finally, a focused metasurface with two near-field foci and two near-field nulls is designed based on the proposed theory and metasurface particle structure. The designed metasurface is full-wave simulated, fabricated, and measured in the experiment. The experimental results agree well with the full-wave simulating results, showing that both the foci and nulls are well presented at the specified positions and the measured power of the near-field nulls is more than 26 dB below the power of the foci.

Autoencoder (AE) has been widely used in the field of hyperspectral anomaly detection. It is assumed that the background can be reconstructed well, but the anomalies cannot. Hence, the pixels with larger reconstruction errors are considered anomalies. However, owing to the strong nonlinear representation ability of AE, it is difficult to distinguish between background and anomalies. To address this problem, we propose a residual self-attention-based AE (RSAAE) for hyperspectral anomaly detection. RSAAE consists of dense residual self-attention (RSA) modules, an encoder, and a decoder. First, a novel RSA module is designed, which can effectively extract the main features and weaken the ability of subsequent networks to reconstruct anomalies, as well as preserve the original features to avoid the deterioration of network performance after the use of dense self-attention modules. Furthermore, inspired by manifold learning, we assume that the background is low-rank in the original space, and has the same property in the latent space after dimensionality reduction. We proposed a low-rank loss function to constrain the latent space, thereby suppressing anomaly reconstruction. Experiments on four real hyperspectral image (HSI) datasets showed that the proposed RSAAE method can produce more accurate detection results than eight popular methods.

A new framework of scattering analysis of metasurfaces composed of an assemble of resonant scatterers, with a multistage analysis procedure, is presented. The metasurface analysis using this framework utilizes a dispersive surface susceptibility model (SSM) and a finite-difference time-domain (FDTD) method, replacing the traditional brute force simulation with the physics-based SSM. The SSM extraction for characterizing scatterers is provided, which then is used to replace detailed practical scatterers in numerical simulation. The SSM with the frequency-dependent features’ behavior is described by multiple-Lorentz pole pairs, and the coefficients of the Lorentz model are obtained by using a rational fitting method. An easy-to-implement FDTD algorithm combined with the Lorentz-described SSM is proposed and presented. The efficiency of the proposed framework is proven by comparing it with conventional FDTD. The validity of the proposed framework is verified using commercial EM simulation software. The use of this analysis procedure is demonstrated by two example scatterers. Through the examples, we discuss the requirement of the meshing lattice size, sensitivity of the algorithm to the incident angle, and influence of the edge effects on the bistatic radar cross section (RCS) computation.

This paper introduces a learning-based Nonlinear Model Predictive Control (NMPC) method that combines NMPC with a Reinforcement Learning (RL) algorithm to achieve automatic parameter tuning of the NMPC optimizer, resulting in better control performance. In this study, two learning-based models were designed based on the tabular Q-learning algorithm but with different definitions of state and action spaces. To test the effectiveness of the proposed model, we conducted two kinds of experiments in which the models were applied to optimize the lane-keeping performance of an autonomous driving system. The case study results from simulations showed that the agent could match a proper parameter matrix for the NMPC within one minute. In real-world experiments, we extended the proposed control scheme to practical driving tasks using a 1:8 scale Audi model car in a specific experimental field. The model exhibited acceptable robustness in the face of relatively large deviations from the sensors and other real-time interference. These results demonstrate that the proposed learning-based NMPC method is a promising direction for solving real-time control problems.

Rhenium disulfide (ReS2) with distinct physicochemical properties has shown promising potential in disease theranostics, such as drug delivery, computed tomography (CT), radiotherapy, and photothermal therapy (PTT). However, the synthesis and post-modification of ReS2agents for different application scenarios are time- and energy-consuming, which seriously hinders the clinical translation of ReS2. Herein, we proposed three facile excipient strategies for different theranostic applications of ReS2just through the flexible use of commercial ReS2powder. Three excipients, including sodium alginate (ALG), xanthan gum (XG), and ultraviolet-cured resin (UCR), were used to prepare different dosage forms of commercial ReS2powder, like hydrogel, suspension, and capsule, respectively. These dosage forms of ReS2with distinct characteristics showed great potential for second near-infrared window PTT against tumours, gastric spectral CT imaging, and functional evaluation of the digestive tract in vivo. In addition, these ReS2formulations exhibited good biocompatibility both in vitroand in vivo, showing a promising prospect for clinical transformation. More importantly, the facile excipient strategies for commercial agents pave a bridge to the development and wide bioapplication of many other theranostic biomaterials.

The contemporary carbon balance over the Tibetan Plateau is highly uncertain with a ten-fold difference between various estimates. In a warming world, the potential exists for a large carbon release from its permafrost which could compromise China’s 2060 carbon-neutral goal. Here, we used a satellite- and inventory-based approach, ecosystem models, and atmospheric inversions to estimate that the carbon sink was 33.12–37.84 TgC yr−1during 2000–2015. The carbon sink induced by climate change and increasing CO2levels largely overcompensated for a livestock grazing-induced carbon source of 0.38 TgC yr−1. By 2060, the carbon sink is projected to increase by 38.3–74.5% under moderate to high emissions scenarios, with the enhanced vegetation carbon uptake outweighing the warming-induced permafrost carbon release. The restoration of degraded grassland could sequestrate an additional 9.06 TgC yr−1, leading to a total carbon sink of 57.78–70.52 TgC yr−1. We conclude that the Tibetan Plateau’s ecosystems absorbed two-and-a-half times the amount of its cumulative fossil CO2emissions during 2000–2015 and that their carbon sinks will almost double in strength in the future, helping to achieve China’s pledge to become carbon neutral by 2060.

In order to improve the torque density of traditional permanent magnet rim propulsion machine, a flux modulated fault-tolerant permanent magnet rim driven machine (FMFTPM-RDM) with combined stator is proposed, designed, and optimized in this paper. The combined stator originates from the open-slot stator and split-teeth stator. The key is adopting the combined stator with non-uniformly distributed flux modulation poles (FMPs) to yield multi-working harmonics and contribute to torque improvement. The expressions of back EMF and self-inductance of the proposed machine are derived by analytical method, and their effectiveness is proved by finite element analysis (FEA). Besides, leading geometric sizes influences on performances of the proposed machine are conducted. For obtaining the optimal geometric sizes quickly and accurately, response surface method (RSM) coupled with multi-objective genetic algorithm (MOGA) is adopted to optimize this machine. Afterward, comparative analysis of the proposed machine with traditional one is performed by FEA. It is concluded that the proposed FMFTPM-RDM has better performances such as higher torque density, lower torque ripple, and stronger fault-tolerant capability. Finally, a prototype is manufactured and the test results verify the proposed combined stator design.

Simulating the microstructure and mechanical properties of natural tissues to achieve rapid tissue regeneration and protect cells under strain during body movement is a giant challenge in locomotive tissue engineering. Here, we built a hierarchical helical scaffold with high stretchability, which not only structurally resembles natural tissues but also matches their non-affine deformation mechanical properties. The cells on this scaffold can maintain high viability under cyclic strains, because the non-planar motion of coil structures mitigates the local maximum strain during stretching. Moreover, the in vivoexperiments demonstrated that the scaffold affords a stable structural and mechanical microenvironment for cell growth and tissue morphogenesis. This helical scaffold breaks the inherent mindset of fixation repairing and makes it possible for reconstruction of the defective tissue even in moderate motion. The study proposes a new thinking about construction of stretchable scaffolds with superior mechanical properties for repairing locomotive tissue injuries.

Rheumatoid arthritis (RA) is marked by joint damage and inflammation, with B cells playing a key role by generating autoantibodies. This study shows that G protein-coupled receptor 40 (GPR40) deficiency in B cells leads to increased activation, proliferation, antibody production, germinal center formation, and class switch recombination. GPR40 regulates Plcγ2 phosphorylation and intracellular calcium flux downstream of the B cell receptor by binding to the Gαq protein. In GPR40-deficient mice, susceptibility to collagen-induced arthritis was higher. GPR40 agonists showed potential as therapeutic agents, and their reduced expression in patients with RA correlated with disease onset, suggesting GPR40 as a potential therapeutic target and diagnostic marker.

Manganese (Mn) intake has been found to be linked with risk of type 2 diabetes. However, the role of Mn in the development of gestational diabetes mellitus (GDM) remains to be investigated. This prospective study included pregnant women from the Tongji Maternal and Child Health Cohort. A total of 2327 participants with plasma specimens before 20 weeks were included. Among the pregnant women, 9.7% (225/2327) were diagnosed with GDM. After adjustment, pregnant women with the third and highest quartile of plasma Mn levels had 1.31-fold (RR, 2.31 [1.48, 3.61]) and 2.35-fold (RR, 3.35 [2.17, 5.17]) increased risk of GDM compared with those with the lowest quartile. A 1 standard deviation increment of ln-transformed plasma Mn levels (0.53 μg/L) was related to elevated risks of GDM with RRs of 1.28 [1.17, 1.40]. The positive associations between Mn and GDM remained consistent in all the subgroups. The weighted quantile sum index was significantly related to GDM (RR, 1.60 [1.37, 1.86]). The contribution of Mn (58.69%) to the metal mixture index was the highest related to GDM. Higher plasma Mn levels were found to be linked with elevated fasting and 2 h post-load blood glucose. This study revealed relationships of higher plasma Mn levels in early pregnancy and increased risk of GDM, suggesting that though essential, excess Mn in the body might be a potential important risk factor for GDM.

Flexible and stretchable humidity sensors for wearable purposes have become increasingly important in health care and physiological signal monitoring. However, to the authors’ knowledge, there is no report on flexible and stretchable paper-based humidity sensors that are low-cost, easily fabricated, and environmentally friendly. In this work, for the first time, we propose a stretchable, textile-compatible paper-based origami humidity sensor (POHS). The POHS can achieve good stretchability by integrating origami folding structures with a paper substrate, in which an airlaid paper acts as both a sensing material and a sensor substrate. This sensor has high sensitivity, good response, and recovery properties with excellent stability during deformation. This sensor has proved to be capable of dynamically monitoring the breathing rate after 300 folding and unfolding cycles. The flexible and stretchable nature of our POHS ensures that it is compatible for textile attachment and its utility for wearable applications, including respiration rate monitoring and diaper wetting detection. The facile fabrication process and convenient disposal method of the POHS proposed in this study provide feasible solutions for the development of low-cost wearable humidity sensors.

ABSTRACTDysregulation of macroautophagy/autophagy contributes to the delay of wound healing in diabetic skin. N6-methyladenosine (m6A) RNA modification is known to play a critical role in regulating autophagy. In this study, it was found that SQSTM1/p62 (sequestosome 1), an autophagy receptor, was significantly downregulated in two human keratinocyte cells lines with short-term high-glucose treatment, as well as in the epidermis of diabetic patients and a db/db mouse model with long-term hyperglycemia. Knockdown of SQSTM1led to the impairment of autophagic flux, which was consistent with the results of high-glucose treatment in keratinocytes. Moreover, the m6A reader protein YTHDC1 (YTH domain containing 1), which interacted with SQSTM1mRNA, was downregulated in keratinocytes under both the acute and chronic effects of hyperglycemia. Knockdown of YTHDC1affected biological functions of keratinocytes, which included increased apoptosis rates and impaired wound-healing capacity. In addition, knockdown of endogenous YTHDC1resulted in a blockade of autophagic flux in keratinocytes, while overexpression of YTHDC1rescued the blockade of autophagic flux induced by high glucose. In vivo, knockdown of endogenous Ythdc1or Sqstm1inhibited autophagy in the epidermis and delayed wound healing. Interestingly, we found that a decrease of YTHDC1 drove SQSTM1mRNA degradation in the nucleus. Furthermore, the results revealed that YTHDC1 interacted and cooperated with ELAVL1/HuR (ELAV like RNA binding protein 1) in modulating the expression of SQSTM1. Collectively, this study uncovered a previously unrecognized function for YTHDC1 in modulating autophagy via regulating the stability of SQSTM1nuclear mRNA in diabetic keratinocytes.Abbreviations:ACTB: actin beta; AGEs: glycation end products; AL: autolysosome; AP: autophagosome; ATG: autophagy related; AKT: AKT serine/threonine kinase; ANOVA: analysis of variance; BECN1: beclin 1; Co-IP: co-immunoprecipitation; DEGs: differentially expressed genes; DM: diabetes mellitus; ELAVL1: ELAV like RNA binding protein 1; FTO: FTO alpha-ketoglutarate dependent dioxygenase; G: glucose; HaCaT: human keratinocyte; GO: Gene Ontology; GSEA: Gene Set Enrichment Analysis; HE: hematoxylin-eosin; IHC: immunohistochemical; IRS: immunoreactive score; KEAP1: kelch like ECH associated protein 1; KEGG: Kyoto Encyclopedia of Genes and Genomes; m6A: N6-methyladenosine; M: mannitol; MANOVA: multivariate analysis of variance; MAP1LC3: microtubule associated protein 1 light chain 3; MAP1LC3B: microtubule associated protein 1 light chain 3 beta; MeRIP: methylated RNA immunoprecipitation; METTL3: methyltransferase 3, N6-adenosine-methytransferase complex catalytic subunit; MTOR: mechanistic target of rapamycin kinase; MTORC1: mechanistic target of rapamycin complex 1; NBR1: NBR1 autophagy cargo receptor; NFE2L2: nuclear factor, erythroid 2 like 2; NG: normal glucose; NHEK: normal human epithelial keratinocyte; OE: overexpressing; p-: phospho-; PI: propidium iodide; PPIN: Protein-Protein Interaction Network; RBPs: RNA binding proteins; RIP: RNA immunoprecipitation; RNA-seq: RNA-sequence; RNU6–1: RNA, U6 small nuclear 1; ROS: reactive oxygen species; siRNAs: small interfering RNAs; SQSTM1: sequestosome 1; SRSF: serine and arginine rich splicing factor; T2DM: type 2 diabetes mellitus; TEM: transmission electron microscopy; TUBB: tubulin beta class I; WT: wild-type; YTHDC1: YTH domain containing 1.

Image captioning is a challenging task that aims to generate a natural description for an image. The word prediction is dependent on local linguistic contexts and fine-grained visual information and is also guided by previous linguistic tokens. However, current captioning works do not fully utilize local visual and linguistic information, generating coarse or incorrect descriptions. Also, captioning decoders have less recently focused on convolutional neural network (CNN), which has the advantage in extracting features. To solve these problems, we propose a local representation-enhanced recurrent convolutional network (Lore-RCN). Specifically, we propose a visual convolutional network to obtain enhanced local linguistic context, which incorporates selected local visual information and models short-term neighboring. Furthermore, we propose a linguistic convolutional network to obtain enhanced linguistic representation, which models long- and short-term correlations explicitly to leverage guiding information from previous linguistic tokens. Experiments conducted on COCO and Flickr30k datasets have verified the superiority of our proposed recurrent CNN-based model.

Traditional open head and neck surgery often leaves permanent scars, significantly affecting appearance. The emergence of surgical robots has introduced a new era for minimally invasive surgery. However, the complex anatomy of the head and neck region, particularly the oral and maxillofacial areas, combined with the high costs associated with established systems such as the da Vinci, has limited the widespread adoption of surgical robots in this field. Recently, surgical robotic platform in China has developed rapidly, exemplified by the promise shown by the KangDuo Surgical Robot (KD-SR). Although the KD-SR has achieved some results comparable to the da Vinci surgical robot in urology and colorectal surgery, its performance in complex head and neck regions remains untested. This study evaluated the feasibility, effectiveness, and safety of the newly developed KD-SR-01, comparing it with standard endoscopic systems in head and neck procedures on porcine models. We performed parotidectomy, submandibular gland resection, and neck dissection, collected baseline characteristics, perioperative data, and specifically assessed cognitive workload using the NASA-TLX. None of the robotic procedures were converted to endoscopic or open surgery. The results showed no significant difference in operation time between the two groups (P= 0.126), better intraoperative bleeding control (P= 0.001), and a significant reduction in cognitive workload (P< 0.001) in the robotic group. In conclusion, the KD-SR-01 is feasible, effective, and safe for head and neck surgery. Further investigation through well-designed clinical trials with long-term follow-up is necessary to establish the full potential of this emerging robotic platform.

ABSTRACTCircular RNAs (circRNAs) have been extensively studied in various diseases, including sepsis-induced acute kidney injury (AKI). This research intended to elucidate the mechanism of circular RNA HIPK3 (circHIPK3) in sepsis-engendered AKI. Human tubule epithelial cells (HK2) were stimulated with lipopolysaccharide (LPS) to establish a septic AKI cell model. The gene expression levels were evaluated by RT-qPCR. Cell viability, apoptosis, and cell cycle distribution were assessed through CCK-8 and flow cytometry assays. The potential interactions between genes were verified by luciferase reporter and RIP assays. The results displayed that circHIPK3 expression was enhanced in septic AKI patients and LPS-triggered HK2 cells. Moreover, circHIPK3 interference expedited HK2 cell viability and attenuated apoptosis, inflammatory and oxidative damages following LPS stimulation. Furthermore, circHIPK3 functioned as a molecular sponge for miR-338, and forkhead box A1 (FOXA1) was negatively regulated by miR-338. CircHIPK3 aggravated cell injury in LPS-treated HK2 via targeting miR-338, and FOXA1 addition overturned the suppressing impacts of miR-338-3p augmentation on LPS-activated HK2 cell damage. Finally, we demonstrated that circHIPK3 modulated LPS-induced cell damage via the miR-338/FOXA1 axis. In sum, our results elaborated that circHIPK3 knockdown attenuated LPS-triggered HK2 cell injury by regulating FOXA1 expression via interacting with miR-338, suggesting that circHIPK3 might be a potential biomarker and therapeutic target for sepsis-induced AKI patients.

D-xylose is an abundant sugar found in plant biomass and can be used as a renewable feedstock for the microbial production of diverse biofuels and bioproducts. However, D-xylose metabolism is slow in many industrial microorganisms, at least as compared to glucose metabolism. Not surprisingly, a number of approaches have been developed for improving D-xylose metabolism in diverse microorganisms. In this work, we applied a previously developed evolution strategy based on media-in-oil emulsions for improving the growth yield of Escherichia coliNCM3722 on D-xylose. After 30 rounds of evolutions, we isolated multiple mutants with increased growth yield on D-xylose. In addition, we also observed similar increases in the growth rate. Three mutants were selected for whole-genome sequencing. Two mutants had an amber stop mutation in adenylate cyclase, which truncates nearly 60% of the enzyme. However, the ability of this mutant to grow on xylose indicated that truncated enzyme, lacking the C-terminal regulatory domain, is still active. The other mutant had a point mutation in the cyclic AMP receptor protein (CRP), near the high affinity binding site for cyclic AMP. Both mutations, when introduced into wild type E. coli, were able to increase the growth yields at levels similar to the isolated mutants. In addition to D-xylose, these mutant strains and their genetic mimics also exhibited higher growth rates and yields on glucose, lactose, and L-arabinose. These results suggest that the improved growth rates and yields are due to changes in the production and sensing of intracellular cyclic AMP concentrations and also suggest native concentrations are suboptimal with respect to the growth rate and yield under the growth conditions tested. Collectively, these results may prove useful for engineering strains of E. colifor high-density fermentations or protein production.

ObjectivePancreatic ductal adenocarcinoma (PDAC) shows a remarkable predilection for liver metastasis. Pro-oncogenic secretome delivery and trafficking via exosomes are crucial for pre-metastatic microenvironment formation and metastasis. This study aimed to explore the underlying mechanisms of how PDAC-derived exosomes (Pex) modulate the liver microenvironment and promote metastasis.DesignC57BL/6 mice were ‘educated’ by tail vein Pex injection. The intrasplenic injection liver metastasis and PDAC orthotopic transplantation models were used to evaluate liver metastasis. Stable cell lines CD44v6 (CD44 variant isoform 6) or C1QBP (complement C1q binding protein) knockdown or overexpression was established using lentivirus transfection or gateway systems. A total of 142 patients with PDAC in Huashan Hospital were retrospectively enrolled. Prognosis and liver metastasis were predicted using Kaplan-Meier survival curves and logistic regression models.ResultsPex tail vein injection induced the deposition of liver fibrotic extracellular matrix, which promoted PDAC liver metastasis. Specifically, the exosomal CD44v6/C1QBP complex was delivered to the plasma membrane of hepatic satellite cells (HSCs), leading to phosphorylation of insulin-like growth factor 1 signalling molecules, which resulted in HSC activation and liver fibrosis. Expression of Pex CD44v6 and C1QBP in PDAC patients with liver metastasis was significantly higher than in PDAC patients without liver metastasis, and simultaneous high expression of exosomal CD44v6 and C1QBP correlated with a worse prognosis and a higher risk of postoperative PDAC liver metastasis.ConclusionThe Pex-derived CD44v6/C1QBP complex is essential for the formation of a fibrotic liver microenvironment and PDAC liver metastasis. Highly expressed exosomal CD44v6 and C1QBP are promising biomarkers for predicting prognosis and liver metastasis in patients with PDAC.

A variety of factors differed between rural and urban areas may further influence iodine status and thyroid structure. Hence, this study compared iodine nutrition, the prevalence of thyroid goiter, and nodules between rural and urban residents in Guangzhou, a southern coastal city of China.A total of 1211 rural residents and 1305 urban residents were enrolled in this cross-sectional study. A questionnaire regarding personal characteristics was administered. Urinary iodine concentration (UIC) was examined. Ultrasonography of the thyroid was performed to evaluate thyroid goiter and nodules. Multiple logistic analysis was used to identify the potential associated factors.The median UIC was significantly lower in rural residents than in urban residents (120.80 μg/L vs 136.00 μg/L, P< 0.001). Although the coverage rate of iodized salt was much higher in rural residents than in urban residents (99.59% vs 97.29%, P< 0.001), the percentages of seafood intake (8.60% vs 29.29%, P< 0.001), iodine-containing drug consumption (0.33% vs 1.24%, P= 0.011), and iodine contrast medium injection (0.58% vs 1.87%, P= 0.004) were lower in rural residents than in urban residents. Both the prevalence of thyroid goiters and nodules was significantly higher in rural residents than in urban residents (goiter: 8.06% vs 1.20%, P< 0.001; nodules: 61.89% vs 55.04%, P= 0.023). Living in rural areas was associated with thyroid goiter (OR 5.114, 95% CI 2.893–9.040, P< 0.001).There were differences in iodine nutrition and the prevalence of thyroid goiter and nodules in rural and urban residents in Guangzhou. Differentiated and specialized monitoring is recommended in our area.

This study introduces a new quasi-flapping wing driving mechanism based on a half-rotating mechanism which is capable of pure rotational flapping rather than the more traditional oscillatory flapping method. Lift models for half-rotating wing (HRW) aircraft in hovering flight are proposed based on the kinematics of a HRW prototype and the flow characteristics near the surface of its wing. Alongside further analytical expressions for lift based on kinematic extractions, computational models and a novel lift validation mechanism are used to reinforce the aerodynamic characteristics of the HRW in hovering flight. The aerodynamics of the HRW are experimentally assessed for different wing layouts and wing materials. Results indicate that the flow field generated by the motion of the wing arranged symmetrically on both sides of the body interfere with each other, causing the average lift coefficient of the paired-wing HRW to be less than that of the single-wing HRW. The average lift coefficient of the flexible wing is larger than that of the rigid wing. In addition, the average lift of the flexible wing increases with increasing flexural compliance within a particular range. Lift forces in different flight conditions are calculated using derived formulas alongside representative computational models, through which the derivation of lift variation for the HRW in hovering flight is validated. The theoretical lift curves show reasonable agreement with numerical simulation results in terms of the time course over one stroke cycle. The mechanisms of the HRW for generation and shedding of vortices in hovering flight are further revealed in computed flow field characteristics results. The velocity vectors of the flow field between the HRW and the symmetrically rotating wing indicate that the HRW with asymmetric rotation can generate lift force effectively. The velocity difference between the wing and the fluid is the key factor influencing the structure of generated vortices. In detailed three-dimensional (3D) vortex flows, our computational fluid dynamics study shows that a horseshoe-shaped vortex is first generated in the early downstroke. The horseshoe-shaped vortex subsequently grows into a doughnut-shaped vortex ring, with a jet stream appearing in its core which forms the downwash. The doughnut-shaped vortex ring eventually elongates into a long arc-shaped wake vortex ring. A large increasing lift force is generated during the upstroke, most likely due to the stable distal attached vortices; and in accordance with this, downwash becomes evident in the vortex ring during the downstroke.

Sensitivity analysis plays an important role in quantifying the impact of input uncertainty on model response uncertainty. Through sensitivity analysis, we can grasp the crucial parameters and gain a deeper understanding of the model behavior. In this paper, an effective analytical solution for solving the variance-based global sensitivity index is proposed. Firstly, the original performance function is approximated as the sum of a series of univariate functions using the conventional dimensional reduction method (C-DRM). Then, the Taylor series expansion is used to expand the univariate function as unary linear function and unary quadratic functions. Finally, the analytical solutions of the variance-based global sensitivity index based on unary linear function and unary quadratic functions are derived respectively. The computational cost of the proposed method is completely concentrated on the calculation of the partial derivative information of the performance function with respect to each variable. As long as the partial derivative information is obtained, the variance-based global sensitivity index can be obtained directly by the proposed method without any additional computational cost. For simple explicit performance functions, the derivative information can be directly derived analytically. For complex explicit or implicit performance functions, the derivative information can be estimated by some simple numerical difference methods. Five examples are studied to investigate the accuracy and efficiency of the proposed method.

The management of oral and maxillofacial tissue defects caused by tumors, trauma, and congenital or acquired deformities has been a major challenge for surgeons over the last few decades. Autologous tissue transplantation, the gold standard of tissue reconstruction, is a valid method for repairing the oral and maxillofacial functions and aesthetics. However, several limitations hinder its clinical applications including complications of donor sites, limited tissue volume, and uncertain long-term outcomes. Adipose-derived mesenchymal stem cells (ADMSCs) widely exist in adipose tissue and can be easily obtained through liposuction. Like the bone marrow-derived mesenchymal stem cells (BMSCs), ADMSCs also have the multi-pluripotent potencies to differentiate into osteoblasts, chondrocytes, neurons, and myocytes. Therefore, the multilineage capacity of ADMSCs makes them valuable for cell-based medical therapies. In recent years, researchers have developed many candidates of ADMSCs-based biomaterial scaffolds to cater for the needs of oral and maxillofacial tissue engineering due to their superior performance. This review presents the advances and applications of ADMSCs-based biomaterial scaffolds, and explores their tissue engineering prospects in oral and maxillofacial reconstructions.

The input variable of engineering structure inevitable has certain uncertainty. How to quantify the influence of those uncertainties on the uncertainty of structural response is an important issue in structural design. Non-probabilistic reliability importance analysis is one of the methods to quantify this influence when variable data information is insufficient. Although the method has great advantages for variables with insufficient data information, there is no efficient calculation method at present, and the excessive computational cost seriously hinders its application in actual engineering structures. In this paper, the multiplicative dimensional reduction method, Taylor series expansion and unary quadratic function are combined to put forward an efficient algorithm to estimate two non-probabilistic reliability importance indices. With the proposed method, all the calculation processes used to solve the extreme value of function are replaced by an approximate analytical solution. Since the proposed method is an approximate analytical solution, the calculation efficiency is extremely high. Three examples are investigated to verify the accuracy and efficiency of the proposed method.