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Smart antennas have received great attention for their potentials to enable communication and perception functions at the same time. However, realizing the function synthesis remains an open challenge, and most existing system solutions are limited to narrow operating bands and high complexity and cost. Here, we propose an externally perceivable leaky-wave antenna (LWA) based on spoof surface plasmon polaritons (SSPPs), which can realize adaptive real-time switching between the “radiating” and “non-radiating” states and beam tracking at different frequencies. With the assistance of computer vision, the smart SSPP-LWA is able to detect the external target user or jammer, and intelligently track the target by self-adjusting the operating frequency. The proposed scheme helps to reduce the power consumption through dynamically controlling the radiating state of the antenna, and improve spectrum utilization and avoid spectrum conflicts through intelligently deciding the radiating frequency. On the other hand, it is also helpful for the physical layer communication security through switching the antenna working state according to the presence of the target and target beam tracking in real time. In addition, the proposed smart antenna can be generalized to other metamaterial systems and could be a candidate for synaesthesia integration in future smart antenna systems.

Abstract Improving battery health and safety motivates the synergy of a powerful duo: physics and machine learning. Through seamless integration of these disciplines, the efficacy of mathematical battery models can be significantly enhanced. This paper delves into the challenges and potentials of managing battery health and safety, highlighting the transformative impact of integrating physics and machine learning to address those challenges. Based on our systematic review in this context, we outline several future directions and perspectives, offering a comprehensive exploration of efficient and reliable approaches. Our analysis emphasizes that the integration of physics and machine learning stands as a disruptive innovation in the development of emerging battery health and safety management technologies.

Summary: Programmable metasurfaces have garnered significant attention for their capacity to dynamically manipulate electromagnetic (EM) waves. In particular, the programmable metasurfaces offer to generate a wide range of EM beams when the appropriate digital coding patterns are designed. Traditionally, optimizing the coding patterns involves time-consuming nonlinear optimization algorithms due to the high computational complexity. In this study, we propose a physics-assisted deep learning (DL) model that can calculate the coding pattern in milliseconds, requiring only a simple depiction of the desired beam. An extended version of the macroscopic model for digital coding metasurface is introduced as the physics-driven component, which can compute the radiation pattern rapidly based on the provided coding pattern. The integration of the macroscopic model ensures to generate the physics-compliant coding designs. We validate the proposed method experimentally by measuring several coding patterns for both single-beam and dual-beam scenarios, which demonstrate good performance of beamforming.

Abstract The effects of IT and R.I.C.E. treatment on arm muscle performance in overhead athletes with elbow pain (EP) have been partially validated. However, there is a lack of research evidence regarding the efficacy of these two methods on arm muscle performance among swimmers with EP. The aim of this study was to investigate the trends and differences in the effects of IT and R.I.C.E. treatment on arm muscle performance among swimmers with EP. The main outcomes were the time effects and group effects of interventions on muscle voluntary contraction (MVC). Sixty elite freestyle swimmers from Tianjin, China, voluntarily participated in the study and completed a 10-week intervention program. Swimmers with EP in the IT group showed a positive trend in MVC, with an approximately 2% increase, whereas the MVC of subjects in the R.I.C.E. treatment group and control group decreased by approximately 4% and 5%, respectively. In comparison, the effects of the IT intervention on the MVC of the triceps and brachioradialis muscles in swimmers with EP were significant (p = 0.042

To address the challenges of selecting task schemes and ensuring secure channels duringdata collection and transmission by unmanned aerial vehicles, the study divides the secure transmission model into physical domain and social domain based on graph theory to ensure the security of unmanned aerial vehicles during task execution. Secondly, the multi to one matching problem was optimized through matching theory, achieving maximum benefits between drones and ground to ground (D2D) users. This study designed a stable matching scheme for drone task allocation based on bipartite graphs and a popular matching strategy for drone security spectrum resource allocation based on bipartite graphs. By adapting the design of a series of coherent actions of drones from information collection to information transmission, the efficiency and security of drone information transmission can be improved. The experimental results show that the average revenue of the designed algorithm for unmanned aerial vehicles is between 21 and 40, while the average revenue range for a single task is between 173 and 210. Compared with other algorithms in terms of security performance for drones and D2D users, the algorithm designed in the study shows strong advantages. Specifically, in terms of drone safety performance, the design algorithm’s performance improves as the spectrum sharing limit increases. The advantage becomes more obvious when the sharing limit value reaches 1; From the perspective of D2D users, the average worst-case safety rate of the design algorithm increases with the increase of flight cycle and average power. Compared tofixed-trajectory drones, the overall performance gain of the research and design algorithm reaches about 18.2%, and compared with fixed power drones, the overall performance gain reaches about 15.5%. In summary, the research has made significant progress in task allocation and channel security spectrum resource allocation. The design algorithm achieves the optimal effect between computational complexity and performance, and overall maximizes the benefits between drones and D2D users.

Abstract Applications of lithium–sulfur (Li–S) batteries are still limited by the sluggish conversion kinetics from polysulfide to Li2S. Although various single‐atom catalysts are available for improving the conversion kinetics, the sulfur redox kinetics for Li–S batteries is still not ultrafast. Herein, in this work, a catalyst with dual‐single‐atom Pt‐Co embedded in N‐doped carbon nanotubes (Pt&Co@NCNT) was proposed by the atomic layer deposition method to suppress the shuttle effect and synergistically improve the interconversion kinetics from polysulfides to Li2S. The X‐ray absorption near edge curves indicated the reversible conversion of Li2Sx on the S/Pt&Co@NCNT electrode. Meanwhile, density functional theory demonstrated that the Pt&Co@NCNT promoted the free energy of the phase transition of sulfur species and reduced the oxidative decomposition energy of Li2S. As a result, the batteries assembled with S/Pt&Co@NCNT electrodes exhibited a high capacity retention of 80% at 100 cycles at a current density of 1.3 mA cm−2 (S loading: 2.5 mg cm−2). More importantly, an excellent rate performance was achieved with a high capacity of 822.1 mAh g−1 at a high current density of 12.7 mA cm−2. This work opens a new direction to boost the sulfur redox kinetics for ultrafast Li–S batteries.

Summary: Claudin-5 (CLDN5) is an endothelial tight junction protein essential for blood-brain barrier (BBB) formation. Abnormal CLDN5 expression is common in brain disease, and knockdown of Cldn5 at the BBB has been proposed to facilitate drug delivery to the brain. To study the consequences of CLDN5 loss in the mature brain, we induced mosaic endothelial-specific Cldn5 gene ablation in adult mice (Cldn5iECKO). These mice displayed increased BBB permeability to tracers up to 10 kDa in size from 6 days post induction (dpi) and ensuing lethality from 10 dpi. Single-cell RNA sequencing at 11 dpi revealed profound transcriptomic differences in brain endothelial cells regardless of their Cldn5 status in mosaic mice, suggesting major non-cell-autonomous responses. Reactive microglia and astrocytes suggested rapid cellular responses to BBB leakage. Our study demonstrates a critical role for CLDN5 in the adult BBB and provides molecular insight into the consequences and risks associated with CLDN5 inhibition.

Abstract All-solid-state lithium-sulfur batteries offer a compelling opportunity for next-generation energy storage, due to their high theoretical energy density, low cost, and improved safety. However, their widespread adoption is hindered by an inadequate understanding of their discharge products. Using X-ray absorption spectroscopy and time-of-flight secondary ion mass spectrometry, we reveal that the discharge product of all-solid-state lithium-sulfur batteries is not solely composed of Li2S, but rather consists of a mixture of Li2S and Li2S2. Employing this insight, we propose an integrated strategy that: (1) manipulates the lower cutoff potential to promote a Li2S2-dominant discharge product and (2) incorporates a trace amount of solid-state catalyst (LiI) into the S composite electrode. This approach leads to all-solid-state cells with a Li-In alloy negative electrode that deliver a reversible capacity of 979.6 mAh g−1 for 1500 cycles at 2.0 A g−1 at 25 °C. Our findings provide crucial insights into the discharge products of all-solid-state lithium-sulfur batteries and may offer a feasible approach to enhance their overall performance.

The authors present an intelligent metasurface system that uses a target detection algorithm combined with a depth camera, to automatically detect the position of moving targets and achieve real-time wireless communications. The system can operate for multiple targets in limited ambient light, outdoor and other realistic environments.

The current attribute reduction algorithms for information systems are difficult to handle imbalanced data with default values. Therefore, to address the shortcomings of traditional attribute reduction algorithms (ARAs) in incomplete information systems, a new algorithm is proposed by introducing intuitive fuzzy pairs (IFP). In addition, a composite minority oversampling technique TampC and Central Limit SMOTE (TampC-CL-SMOTE) is proposed to improve the pre-data sampling method of the algorithm, and its effectiveness is verified by experiments. The experimental results show that the average classification accuracy of the improved attribute reduction algorithm on the naive Bayes classifier is 82.13%, and the average classification accuracy on the support vector machine classifier is 86.48%. In the comparison of operational efficiency, the average running time of the improved attribute reduction algorithm is 5.92 seconds, and the overall consumption of running time is lower than that of the comparison algorithm. Meanwhile, the average accuracy, recall, and F-measure of the algorithm are 76.14%, 78.35%, and 77.19%, respectively. In addition, the G-means of TampC-CL-SMOTE are 2.9% and 5.3% higher than the comparison algorithm, respectively. Overall, the improved attribute reduction algorithm has high efficiency in handling imbalanced data, while the optimization of TampC-CL-SMOTE has effectiveness in practical applications and has advantages in handling high and low imbalanced data in incomplete information environments.

Layered oxide cathode active materials suffer from interfacial structural instability when coupled with sulfide solid-state electrolytes. Here, the authors propose a gradient coating with a lithium oxythiophosphate layer that can stabilize the cathode|solid-state electrolyte interface.

Abstract Arrester is an important lightning protection device in the electrical field. The parameters of arrester such as creepage distance, umbrella distance and diameter are important for product quality, but they are difficult to measure because the shape of arrester is irregular. However, the three-dimensional (3D) reconstruction technique is efficient in measuring arrester parameters. The uniform distributed structure of umbrella skirt on the arrester surface restrict the registration of point cloud. In this paper, a scale-invariant points features histogram (SIPFH) descriptor is proposed; the descriptor combines the characteristics of Scale-invariant Feature Transform (SIFT) and fast point feature histogram (FPFH). Moreover, the improved Levenberg-Marquardt (LM) algorithm is presented, the maximum distance of corresponding points in the iterative process is adjusted to realize the local optimization. The point cloud registration method consists of two parts: primary registration method based on SIPFH, and secondary registration method based on improved LM algorithm. Point clouds of different arresters are collected to establish datasets, some of which have interference. Experimental results indicate that the root mean square error of the method is less than 0.02 m; the average running time is 2.7 s, which is $$41.4\%$$ 41.4 % of the conventional method based on FPFH.

This paper investigates the impact of increasing maximum wind speed of tropical cyclones on the return periods of water levels in the sea area of the Yangtze River Delta. To conduct this study, a series of numerical experiments are performed using historical tropical cyclones that impacted the Yangtze River Delta from 1949 to 2019. The aim is to analyze the effects of global climate change on extreme water levels and the corresponding return periods. To obtain the historical water levels in the sea areas of the Yangtze River Delta, a storm surge model is driven by the selected tropical cyclones. The simulated astronomical tidal levels during the same period are also used. The extreme water levels of different return periods are then calculated. The maximum wind speeds of the selected tropical cyclones are increased by 11% according to the expected amount of increase under global climate change. The extreme water levels of different return periods under this scenario are calculated with the same procedure. The results of the study show that the impact of increasing maximum wind speed of tropical cyclones on the increases of extreme water levels and the decrease of return periods is more significant in the inner area of the estuaries than in the outer areas. Moreover, the responses of the extreme water levels and the corresponding return periods in the Yangtze River Estuary and the Hangzhou Bay show different characteristics. The results of this study provide significant reference value for the management of future coastal disaster prevention and mitigation in the Yangtze River Delta. Furthermore, the methodology used in this study can be applied in other estuaries to investigate the potential impacts of changes in climate and hydrology factors on extreme water levels and the corresponding return periods.

The Airy beam has intrigued long-held research interests and developed various striking applications attributed to the unprecedented diffraction-free, self-bending and self-healing properties. Metasurfaces with superior design freedom and small structure size open a fire-new avenue for generating efficient and broadband Airy beam. Nevertheless, most existing Airy beam generators can only respond to one polarization state of electromagnetic waves and produce the single Airy beam, which immensely limit the serviceability and utilization of the Airy beam generators. Herein, an inspiring strategy of multichannel Airy beam generator based on the multichannel amplitude and phase controlled metasurface is proposed to independently generate the Airy beams for linear polarized waves in 20–24 GHz and orthogonal circular polarized waves in 12–14 GHz and 15–17 GHz. Notably, an appealing paradigm of multichannel beam focusing can be realized by the integrated multichannel Airy beam generator, which possesses strong ability to circumvent the obstacle owing to the self-healing feature of the Airy beam. A proof-of-concept prototype is constructed to verify the feasibility of our methodology, and multitudinous simulations and experiments are in excellent accordance with our theoretical predictions. This novel design of multichannel Airy beam generator will have tremendous application potential in sensing, communication and other multifunctional metadevices.

Aerosol particle size has a crucial impact on the environment and public health. Current satellite-based regression models focus on the total amount of particles and are limited by surface observations. This study proposes an algorithm to derive the long-term normalized volume size distribution (VSD) of aerosol particles, which is independent of ground measurements. The size distribution and aerosol optical depth of Multi-angle Imaging SpectroRadiometer (MISR) components are employed. We find the estimated MISR VSD is consistent with Aerosol Robotic Network (AERONET) observations, with R = 0.56, 0.54, 0.59, and 0.68 for daily, monthly, seasonal, and annual levels. The stratified validations of radius, stations, and years further confirm the stable performance of derived VSD (R = 0.28 to 0.73). The application of the random forest model demonstrates the potential improvements of predicted VSD by 10-fold cross-validation R = 0.86 at the monthly level. We apply MISR VSD to quantify the normalized volume of fractional aerosol particles at a resolution of 0.2° × 0.2° during 2004 to 2016 in China. We also calculate the proportion of small and medium particles to indicate the contribution of anthropogenic aerosols. The highest ratios are concentrated in the northeastern regions especially during winter while relatively lower in the Taklamakan Desert of western China. The case study demonstrates that the application of MISR data can yield valuable and resolved size distributions of aerosol particles.

IRE1 helps mitigate endoplasmic-reticulum stress by cleaving specific mRNAs at a conserved sequence endomotif via regulated IRE1-dependent decay (RIDD). Here the authors discover a more promiscuous IRE1 activity dubbed RIDD lacking endomotif (RIDDLE).

Holography has been continuously spurring tremendous interest of researchers attributed to its unparalleled capability of photographically reconstructing the desired images. Based on the metasurfaces with multiple degrees of freedom, multiplexing meta-holograms are experiencing the research upsurge because of enormous application potential. However, existing multiplexing meta-holograms cannot tailor the amplitude information, and possess limited imaging channels and high channel crosstalk, which hinder the improvement of information capacity and imaging quality of multiplexing meta-holograms. Herein, an innovative multiplexing meta-hologram based on the helicity-assisted meta-atoms is proposed, which can perfectly reconstruct four independent images by altering the working frequency, polarization state and propagation direction of incident waves, and theoretically realize the holography in sixteen different channels by easily rotating, mirroring, and arranging the structures of meta-atoms. Numerous simulations and experiments collectively corroborate the feasibility of our methodology, and the quantitative analyses verify the high fidelity of the reconstructed images, which results from the low crosstalk between the amplitude modulation and phase modulation in different imaging channels. This inspiring strategy of multiplexing meta-hologram with large channel capacity and high imaging quality will have promising application prospects in information display, storage and encryption, and provide an alternative path for the design of multifunctional microwave devices.

Abstract Background Liquid–liquid phase separation (LLPS) within the nucleus is directly linked to driving gene expression through transcriptional complexes. Histone lysine methyltransferase 2D (KMT2D) is widely present in many cancers. It is known to epigenetically stimulate the expression of genes associated with tumorigenesis and metastasis. Our analyses show that KMT2D possesses two distinct low-complexity domains (LCDs) capable of driving the assembly of membrane-less condensates. The dependence of the mechanisms underlying monomethylation of H3K4 on the LLPS microenvironment derived from KMT2D LCDs is unclear in tumor. Methods KMT2D LCD-depletion cells were used to investigate tumor cell proliferation, apoptosis, and migration. We identified some core proteins, including WDR5, RBBP5, and ASH2L, which are involved in the KMT2D-associated catalytic complex in KMT2D LCD-deficient cells to further elucidate the mechanism that decreases monomethylation of H3K4. We also evaluated the viability of KMT2D LCD-deficient cells in vivo. Finally, using 1,6-hexanediol (HD), an inhibitor of LLPS, we determined cell activities associated with KMT2D function in wild-type PANC-1 cells. Results Without the LLPS microenvironment in KMT2D LCD-deficient cells or wild-type PANC-1 cells treated with HD, the WDR5 protein was significantly less stable and the protein–protein interactions between the components of the KMT2D–enzyme complex were attenuated, impairing the formation of the complex. Moreover, with the decrease in H3K4me1 level at enhancers, transcription factors such as LIFR and KLF4 were markedly downregulated, effectively inhibiting tumor progression. In xenograft tumor models, PANC-1 cells lacking the KMT2D LCDs showed effectively suppressed tumor growth compared to normal cells. Conclusions Our data indicate that the two low-complexity domains of the KMT2D protein could form a stable LLPS microenvironment, promoting the KMT2D catalysis of H3K4 monomethylation through stabilization of the WDR5 protein and KMT2D–enzyme complex. Therefore, finding ways to regulate the LLPS microenvironment will be benefitial for new cancer treatment strategies.

Synthesizing single-atom catalysts through a general method presents a great challenge. Here the authors report that Fe, Co and Ni single-atom catalysts can be obtained using pre-located isolated Pt atoms as the catalyst and identify the role of Pt single atoms in the synthesis process.

Based on Nickel isotope analysis of meteorites and terrestrial rocks, the authors suggest that the Bulk Silicate Earth has a sub-chondritic Nickel isotope composition. This signature is thought to result from the impact and accretion of a Mercury-like impactor which originated from the innermost Solar System.

With the continuous development and popularity of blockchain technology, anonymity of cryptocurrency has attracted wide attention. Zcash is an altcoin of Bitcoin aiming to protect blockchain anonymity. Its anonymity is highly guaranteed by zero-knowledge proofs. However, it is still practicable to decrease Zcash's anonymity. In this paper, we provide a refined empirical analysis of Zcash anonymity. We improve current address clustering methods and increase the clustering rate by 9%. We also analyze the whole process of distributing mining reward and identify 87.5% addresses and 25.7% transactions. Besides, we simplify Zcash transaction network and then pick out nodes (edges) which play important roles in network connectivity. We show that these nodes are mostly mining pools. In particular, users participating in shieldedpool are mostly founders, miners and mining pools, although shieldedpool itself is designed for protecting anonymity of users with high privacy requirements. Our results, to an extent, are opposite to the original intention of Zcash.

High salinity causes severe damage to plant growth and significantly reduces crop yields. The CCX family proteins can facilitate the transport of multiple ions to prevent toxicity. CCX proteins play an important role in regulating plant salt tolerance, but no detailed studies on CCX proteins in apples have been reported. Here, the CCX family gene MdCCX1 was cloned from apple (Malus domestica). It is constitutively expressed in various apple tissues and is significantly induced by salt stress. As a plasma membrane-localized protein, MdCCX1-overexpression could complement the Na+-sensitive phenotype of yeast mutants and reduce the Na+ content in yeast cells under NaCl treatment, suggesting that MdCCX1 could be a plasma membrane-localized Na+ transporter. To identify the function of MdCCX1 in salt response, we transformed this gene into Arabidopsis, apple calli, and apple plants. Overexpression of MdCCX1 significantly improved the salt tolerance of these transgenic materials. The significantly reduced Na+ content under NaCl treatment indicated that MdCCX1 overexpression could enhance plant salt tolerance by inhibiting the excessive accumulation of Na+. Besides, MdCCX1 overexpression could also enhance plant salt tolerance by promoting ROS scavenging. These findings provide new insight and rich resources for future studies of CCX proteins in plant species.

Animals, from insects to humans, exhibit obvious diurnal rhythmicity of feeding behavior. Serving as a genetic animal model, Drosophila has been reported to display feeding rhythms; however, related investigations are limited due to the lack of suitable and practical methods. Here, we present a video recording-based analytical method, namely, Drosophila Feeding Rhythm Analysis Method (dFRAME). Using our newly developed computer program, FlyFeeding, we extracted the movement track of individual flies and characterized their food-approaching behavior. To distinguish feeding and no-feeding events, we utilized high-magnification video recording to optimize our method by setting cut-off thresholds to eliminate the interference of no-feeding events. Furthermore, we verified that this method is applicable to both female and male flies and for all periods of the day. Using this method, we analyzed long-term feeding status of wild-type and period mutant flies. The results recaptured previously reported feeding rhythms and revealed detailed profiles of feeding patterns in these flies under either light/dark cycles or constant dark environments. Together, our dFRAME method enables a long-term, stable, reliable, and subtle analysis of feeding behavior in Drosophila. High-throughput studies in this powerful genetic animal model will gain great insights into the molecular and neural mechanisms of feeding rhythms.

Previous results reported that SiCp (Silicon Carbide particles) particle doping proved to be effective in enhancing the wear performance of WE43 magnesium alloy. In this work, finite element simulation was employed to investigate the effect of SiCp particle shape on the mechanical behaviors of SiCp/WE43 magnesium matrix composites. SiCp particles underwent larger load internally and a smaller plastic deformation under tensile loading, leading to the enhanced strength and stiffness of the composites. Polygonal SiCp particles provided a better enhancement in strength for the composites than round SiCp particles, but the enhancement in stiffness was opposite. Meanwhile, the damage is likely to initiate at the interface between the matrix and particle, at the location of the highest stress concentration. This phenomenon was more prominent in polygonal particle-reinforced composites. These current findings provide a comprehensive understanding of the effect of SiCp particle shape on the mechanical behaviors of magnesium matrix composites.

Motivated by the significant natural circulation capability of lead–bismuth eutectic (LBE)–cooled systems, the RELAP5 MOD3.2 code was modified for the analysis of LBE-cooled reactors and non-nuclear systems. The thermo-physical properties of LBE have been incorporated into the code without affecting the code’s original performance; new heat transfer correlations for liquid metal have been implemented. For the purpose of validating the modified code, experimental results of two different LBE natural circulation test loops were compared with the code simulation results. The first one was a natural circulation setup process test at a power of 22.5 kW performed at the Natural Circulation Experimental (NACIE) facility. The simulated inlet and outlet LBE temperatures across the heat source and mass flow rate of LBE agreed well with the test data. The second one was natural circulation conditions under five different power levels conducted at the Natural Circulation Capability Loop (NCCL) facility. The LBE temperature difference and mass flow rate under different power levels predicted by the code were consistent with the experimental data. Generally speaking, the modified code gives acceptable results, and the code could be applied for further LBE systems thermal-hydraulic analysis.

The method to estimate joint motion quickly and accurately from surface electromyogram (sEMG) has been explored by many researchers. However, the effect of different grabbing loads is ignored by most of them, which limits its clinical and daily applicability. In order to eliminate this effect in the course of motion estimation, an Adaboost-AF method based on Adaboost regression was proposed to identify the load information and estimate motion intention. This method is composed of three parts: the sEMG preprocessing part, the load identification part, and the motion intention estimation part. The average value of sEMG feature signal, which is obtained during sEMG preprocessing part, was used to identify the load information. Five features, root mean square (rms), waveform length, difference absolute standard deviation value, the integral signal of sEMG (IEMG), and low-pass filtered signal of sEMG (LPFEMG) similar to sEMG envelope were explored whether the average value of features signal can be used to identify the load under different speeds. After the load was identified, the Adaboost regression framework with the decision tree as the weak learner was applied to be the motion intention estimation part. Experimental results showed that the average rms difference between an actual angle and estimated angle by using the Adaboost-AF method was 0.1193 ± 0.0148, and the average execution time for a section of data with 17.58 s was 0.3932 ± 0.0610s. (Scikit-learn packet was adopted, and the version number was V0.21. The running software was Spyder, Python3.6.) This paper shows that the method based on the average value of sEMG feature signals can eliminate the influence of different loads without adding new sensors; IEMG and LPFEMG from the biceps brachii muscle show the optimal loads identification performance; the proposed Adaboost-AF method takes the influence of different loads into account and ensures the rapid and accurate estimation performance of motion intention.

Carbon fiber reinforced plastic (CFRP) is the main material of aircraft skin. Preparing superhydrophobic anti-icing/deicing surface on the CFRP is of great importance for aircraft flight safety. In this work, a variety of multi-scale micro-nano structures were imprinted on CFRP by femtosecond laser processing, and a transition from hydrophilic to superhydrophobic CFRP was realized. After being optimized by different geometries and laser conditions, the water contact angle, which is tested at 24.3 °C and 34% humidity, increased from 88 ± 2° (pristine) to 149 ± 3° (100 μm groove) and 153 ± 3° (80 μm grid). A further anti-icing test at −10 °C (measured on the cooling platform) and 28% humidity showed that the freezing time was increased from 78 ± 10 s (pristine) to 282 ± 25 s (80 μm grid). Most importantly, the tensile tests showed that the femtosecond laser processing method did not deteriorate the mechanical properties of CFRP. This work provides great significance for aircraft passive deicing technology.

The unfolded protein response (UPR) maintains protein folding homeostasis in the endoplasmic reticulum (ER). In metazoan cells, the Ire1 branch of the UPR initiates two functional outputs—non-conventional mRNA splicing and selective mRNA decay (RIDD). By contrast, Ire1 orthologs from Saccharomyces cerevisiae and Schizosaccharomyces pombe are specialized for only splicing or RIDD, respectively. Previously, we showed that the functional specialization lies in Ire1’s RNase activity, which is either stringently splice-site specific or promiscuous (Li et al., 2018). Here, we developed an assay that reports on Ire1’s RNase promiscuity. We found that conversion of two amino acids within the RNase domain of S. cerevisiae Ire1 to their S. pombe counterparts rendered it promiscuous. Using biochemical assays and computational modeling, we show that the mutations rewired a pair of salt bridges at Ire1 RNase domain’s dimer interface, changing its protomer alignment. Thus, Ire1 protomer alignment affects its substrates specificity.

The development of probes for the testing of the carcinogenic pollutant 2,4,6-trinitrophenol (TNP) is of great importance for environmental protection and human health. In this paper, a new rapid and sensitive fluorescence detection method based on carbon dots (CDs) was designed for the detection of TNP. The CDs were synthesized by simple pyrolysis using citric acid as raw material and characterized by various advanced techniques. The addition of TNP caused a significant turn off in the fluorescence of the CDs. The fluorescence quench intensity and TNP concentration exhibited a good linear correlation in the range of 0–80 μM with a minimum detection limit of 0.48 μM and a related coefficient of 0.994. The analytical method was applied to the determination of trace TNP in river water and tap water with recoveries in the range of 98%–110% and relative standard deviations less than 5%. Importantly, carbon dots functionalized papers (CDFPs) were prepared using the synthesized CDs and successfully applied to the determination of TNP in aqueous solutions, demonstrating the promising application of the method.

A rolling element signal has a long transmission path in the acquisition process. The fault feature of the rolling element signal is more difficult to be extracted. Therefore, a novel weak fault feature extraction method using optimized variational mode decomposition with kurtosis mean (KMVMD) and maximum correlated kurtosis deconvolution based on power spectrum entropy and grid search (PGMCKD), namely KMVMD-PGMCKD, is proposed. In the proposed KMVMD-PGMCKD method, a VMD with kurtosis mean (KMVMD) is proposed. Then an adaptive parameter selection method based on power spectrum entropy and grid search for MCKD, namely PGMCKD, is proposed to determine the deconvolution period T and filter order L. The complementary advantages of the KMVMD and PGMCKD are integrated to construct a novel weak fault feature extraction model (KMVMD-PGMCKD). Finally, the power spectrum is employed to deal with the obtained signal by KMVMD-PGMCKD to effectively implement feature extraction. Bearing rolling element signals of Case Western Reserve University and actual rolling element data are selected to prove the validity of the KMVMD-PGMCKD. The experiment results show that the KMVMD-PGMCKD can effectively extract the fault features of bearing rolling elements and accurately diagnose weak faults under variable working conditions.

The synchronization error of the left and right steering-wheel-angles and the disturbances rejection of the synchronization controller are of great significance for the active rear axle independent steering (ARIS) system under complex driving conditions and uncertain disturbances. In order to reduce synchronization error, a novel hierarchical synchronization control strategy based on virtual synchronization control and linear active disturbance rejection control (LADRC) is proposed. The upper controller adopts the virtual synchronization controller based on the dynamic model of the virtual rear axle steering mechanism to reduce the synchronization error between the rear wheel steering angles of the ARIS system; the lower controller is designed based on an LADRC algorithm to realize an accurate tracking control of the steering angle for each wheels. Experiments based on a prototype vehicle are conducted to prove that the proposed hierarchical synchronization control strategy for the ARIS system can improve the control accuracy significantly and has the properties of better disturbances rejection and stronger robustness.

The endoplasmic reticulum (ER) protein folding capacity is balanced with the protein folding burden to prevent accumulation of un- or misfolded proteins. The ER membrane-resident kinase/RNase Ire1 maintains ER protein homeostasis through two fundamentally distinct processes. First, Ire1 can initiate a transcriptional response through a non-conventional mRNA splicing reaction to increase the ER folding capacity. Second, Ire1 can decrease the ER folding burden through selective mRNA decay. In Saccharomyces cerevisiae and Schizosaccharomyces pombe, the two Ire1 functions have been evolutionarily separated. Here, we show that the respective Ire1 orthologs have become specialized for their functional outputs by divergence of their RNase specificities. In addition, RNA structural features separate the splicing substrates from the decay substrates. Using these insights, we engineered an S. pombe Ire1 cleavage substrate into a splicing substrate, which confers S. pombe with both Ire1 functional outputs.

As an attractive alternative to the traditional plug-in charged electric vehicles (EVs), wireless-charged EVs have recently been in the spotlight. Opportunistically charged utilizing the wireless-charging infrastructure installed under the road at bus stops, an electric bus can have a smaller and lighter battery pack. In this paper, an improved opportunistic wireless-charging system (OWCS) for electric bus is introduced, which includes the opportunistic stationary wireless-charging system (OSWCS) and opportunistic hybrid wireless-charging system (OHWCS) consisting of stationary wireless-charging and dynamic wireless-charging. A general battery reduction model is established for the opportunistic wireless-charged electric bus (OWCEB). Two different battery-reduction models are built separately for OWCEB on account of the characteristics of OSWCS and OHWCS. Additionally, the cost saving models including the production cost saving, the operation cost saving and total cost saving are established. Then, the mathematical models are demonstrated with a numerical example intuitively. Furthermore, we analyze several parameters that influence the effectiveness of battery reduction due to the application of an opportunistic wireless-charging system on an electric bus. Finally, some points worth discussing in this work are performed.