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Self-synchronizing voltage source inverter (SSVSI) can effectively improve grid frequency stability. However, the synchronous frequency resonance (SFR) inevitably exists in SSVSI. In this paper, a small-signal model considering power coupling is established to analyze the system characteristics. It is found that the control parameter adjustment and the virtual resistance method can suppress the SFR. However, the control parameter adjustment will change the dynamic and steady-state characteristics of the system, and the virtual resistance method will exacerbate the power coupling of the system. For this reason, based on the idea of eliminating the resonance peaks, this paper proposes an SFR suppression method based on band-stop filters. By connecting band-stop filters in series in the active power control loop (APCL) and the reactive power control loop (RPCL), the proposed method effectively suppresses the resonance peaks without changing the original control parameters of the system, and the control bandwidth is wider, which improves the power response speed of the system. In addition, the proposed method avoids exacerbating the power coupling of the system compared with the virtual resistance method. Finally, the simulation and experimental results verify the correctness of the theoretical analysis and the effectiveness of the control method.

Summary: Fat infiltration (FI) in the rotator cuff muscle is associated with poor clinical outcomes and failed repair of rotator cuff tears (RCTs) in patients. In this study, we aimed to investigate the function of ginsenoside Rb1 in inhibiting FI in muscles after RCT and its underlying molecular mechanism. After TT modeling, mice treated with Rb1 for 6 weeks showed lower FI in the SS muscle compared with mice in the control groups and those treated with other ginsenoside components. Mechanically, Rb1 binds to the NAD+ domain of SIRT1, activating its expression and enzyme activity. This activation stimulates the deacetylation of CPT1A at site K195, thereby promoting fatty acid β-oxidation in adipocyte cells and improving lipolysis. These findings suggest that Rb1 is a potential therapeutic component for improving the outcomes of patients with RCTs.

Summary: Within the population of humans with otherwise normal vision, there exists some proportion whose ability to perceive depth from binocular disparity is poor or absent. The prevalence of this “stereo-anomaly” has been reported to be as small as 2%, or as great as 30%. We set out to investigate this discrepancy. We used a digital tool to measure stereoacuity in tasks requiring either the detection of disparity or the discrimination of the direction of disparity. In a cohort of 228 participants, we found that 98% were able to consistently perform the detection task. Of these, only 69% consistently performed the discrimination task. The 31% of participants who had difficulty with the discrimination task could further be divided into 17% who were consistently unable to perform the task and 14% who showed limited ability. This suggests that identification of the direction of disparity requires further processing beyond merely detecting its presence.

Due to the fact that the impedance of grid interacts with that of direct-drive wind turbines under weak grid, the direct-drive wind power system (DDWPS) possesses the risk of power oscillation. Given that phase-locked loop (PLL) is the crucial factor that hinders DDWPS stability under weak grid, the following has been achieved: firstly, potential factors influencing PLL output phase angle stability by using linearized PLL model are found; secondly, for PLL output phase angle, a voltage feedforward compensation method based on the relationship between the PLL output phase angle and grid voltage is proposed, which effectively suppresses power oscillation in DDWPS under weak grid; thirdly, the sequence admittance model of DDWPS adopting the proposed voltage feed-forward compensation based PLL (VFC-PLL) is established. Comparative analysis of the stability with the DDWPS using traditional PLL (T-PLL) demonstrates that the proposed VFC-PLL significantly improves DDWPS stability. More importantly, this method does not require complex parameter design and measured grid impedance information, so under weak grid, it is easy to popularize and apply in DDWPS. Finally, the experiment testifies to the validity and feasibility of the proposed VFC-PLL.

Iconic memory and short-term memory are not only crucial for perception and cognition, but also of great importance to mental health. Here, we first showed that both types of memory could be improved by improving limiting processes in visual processing through perceptual learning. Normal adults were trained in a contrast detection task for ten days, with their higher-order aberrations (HOA) corrected in real-time. We found that the training improved not only their contrast sensitivity function (CSF), but also their iconic memory and baseline information maintenance for short-term memory, and the relationship between memory and CSF improvements could be well-predicted by an observer model. These results suggest that training the limiting component of a cognitive task with visual perceptual learning could improve visual cognition. They may also provide an empirical foundation for new therapies to treat people with poor sensory memory.

Swarm intelligence optimization algorithms have garnered considerable attention for solving real-world optimization problems owing to their ability to emulate collective behaviors such as the movement, interaction, and evolution observed in biological swarms. In this paper, we propose a novel bionic swarm intelligence optimization method called the sheep flock migrate optimization (SFMO) algorithm, which is inspired by the intermittent collective motion behavior exhibited by sheep. The SFMO algorithm comprises grazing operator, collective motion operator, and compensation strategy. The grazing operator is formulated based on mathematical models that capture the local foraging behavior of sheep within a confined range. This operator is inspired by the “two-phase motion of sheep”, as well as the widely recognized “green wave chasing” mechanism observed in herbivores. The grazing operator, which is responsible for the local search functionality, enhances the algorithm’s exploitation capability, thereby enhancing its ability to effectively exploit the search space. The collective motion operator builds upon the “two-phase motion mechanism” and incorporates the “leader–follower” mechanism observed during the movement of a sheep flock. By simulating the overall migration behavior of a sheep flock, this operator assumes the role of global search and aims to enhance the algorithm’s exploration ability. The compensation strategy temporarily expands the search range by leveraging the social learning mechanism observed in flock behavior, thereby improving the algorithm’s ability to escape from local optima. Distinguished from the existing swarm intelligence-based optimization methods, the SFMO algorithm alternately executes the grazing operator and collective motion operator, mirroring the intermittent collective motion mechanism exhibited by flocks. The compensation mechanism is adaptively triggered when the algorithm is likely to converge to a local optimal solution, ensuring a balance between the exploration and exploitation capabilities. SFMO introduces a novel and efficient optimizer in the field of population intelligence optimization by mitigating the probability of falling into local optima through extensive stochastic search-guided population migration and an expanded search mechanism during migration stagnation. The convergence proof and complexity analysis results of the SFMO algorithm provide theoretical support for its feasibility and effectiveness. To further validate the proposed method, we conduct numerical simulations using CEC-2017 benchmark functions and compare SFMO with representative optimization algorithms, namely, pigeon-inspired optimization (PIO), particle swarm optimization (PSO), and gray wolf optimizer (GWO), under equivalent conditions. The simulation results demonstrate that SFMO effectively solves function optimization problems and offers considerable advantages, particularly in the context of multimodal function optimization. Among the four algorithms, SFMO demonstrates superior search efficiency, stability, and accuracy. Moreover, it exhibits remarkable advantages in addressing high-dimensional optimization problems, showcasing the highest level of robustness compared with the other algorithms.

Adhesives have attracted a great deal of attention as an advanced modality in biomedical engineering because of their unique wound management behavior. However, it is a grand challenge for current adhesive systems to achieve robust adhesion due to their tenuous interfacial bonding strength. Moreover, the absence of dynamic adaptability in conventional chemical adhesives restricts neoblasts around the wound from migrating to the site, resulting in an inferior tissue-regeneration effect. Herein, an extracellular matrix-derived biocomposite adhesive with robust adhesion and a real-time skin healing effect is well-engineered. Liquid–liquid phase separation is well-harnessed to drive the assembly of the biocomposite adhesive, with the active involvement of supramolecular interactions between chimeric protein and natural DNA, leading to a robustly reinforced adhesion performance. The bioadhesive exhibits outstanding adhesion and sealing behaviors, with a sheared adhesion strength of approximately 18 MPa, outperforming its reported counterparts. Moreover, the engineered bioderived components endow this adhesive material with biocompatibility and exceptional biological functions including the promotion of cell proliferation and migration, such that the use of this material eventually yields real-time in situ skin regeneration. This work opens up novel avenues for functionalized bioadhesive engineering and biomedical translations.

Chinese construction industry is gradually transforming to industrialization, which promotes the development of prefabricated buildings. As an efficient lateral force resisting system, prefabricated steel-plate concrete composite shear wall structure has become a research hotspot in the field of architecture at home and abroad. Based on the mechanical characteristics of the shear wall, this paper proposes a end steel plate connection prefabricated composite shear wall structure. Through numerical simulation and analysis of the prefabricated composite shear wall with different connection areas and the cast-in-place composite shear wall, which verified the feasibility and reliability of end steel plate connection. Based on the above verification, the influence of different parameters on the seismic performance of the prefabricated composite shear wall with end steel plate connection has been further studied, and the theoretical calculation of bearing capacity is carried out. The results show that the length of the connector should be controlled within a reasonable range. The tie bars in the node connection area can improve the strength and ductility of the prefabricated composite shear wall. The aspect ratio and axial pressure ratio have obvious influence on the seismic performance of the wall, which should be reasonably selected in design.

Abstract Metal–organic frameworks (MOFs) are promising candidates for room‐temperature hydrogen storage materials after modification, thanks to their ability to chemisorb hydrogen. However, the hydrogen adsorption strength of these modified MOFs remains insufficient to meet the capacity and safety requirements of hydrogen storage systems. To address this challenge, a highly defective framework material known as de‐MgMOF is prepared by gently annealing Mg‐MOF‐74. This material retains some of the crystal properties of the original Mg‐MOF‐74 and exhibits exceptional hydrogen storage capacity at above‐ambient temperatures. The MgO5 knots around linker vacancies in de‐MgMOF can adsorb a significant amount of dissociated and nondissociated hydrogen, with adsorption enthalpies ranging from −22.7 to −43.6 kJ mol−1, indicating a strong chemisorption interaction. By leveraging a spillover catalyst of Pt, the material achieves a reversible hydrogen storage capacity of 2.55 wt.% at 160 °C and 81 bar. Additionally, this material offers rapid hydrogen uptake/release, stable cycling, and convenient storage capabilities. A comprehensive techno‐economic analysis demonstrates that this material outperforms many other hydrogen storage materials at the system level for on‐board applications.

Layered two-dimensional ferromagnetic materials have emerged as a promising platform for spintronic applications, owing to their extraordinary physical properties. Remarkably, the representative two-dimensional ferromagnet Fe3GeTe2 has been extensively investigated due to its high Curie temperature and strong perpendicular magnetic anisotropy, which are beneficial for high-density storage at room temperature. However, there are few reports on its stability in the air and the surface oxidation products, which may prohibit its future application. Here, we report the natural oxidation process of Fe3GeTe2 films grown by molecular beam epitaxy evolved in the atmosphere, which was studied by x-ray photoelectron spectroscopy measurements and transmission electron microscopy. Our research shows that the surface of the Fe3GeTe2 film is oxidized quickly when exposed to air and shows two obviously evolving stages in the whole oxidation process. In the first stage, metallic Ge atoms are almost completely oxidized to form Ge–O bonds in GeO2, while partial metallic Fe and Te atoms are oxidized into Fe2O3 and TeO2, respectively. The second stage of oxidation is dominated by changes in the valence state of the Fe element, where Fe2O3 is reduced to FeCO3 through the participation of carbon adsorbed on the surface with the final oxidation product of FeCO3 · GeO2 · TeO2. Our findings provide insight into the subsequent growth and protection of Fe3GeTe2 thin films, which is of great significance for in-depth study and further application of spintronic devices in two-dimensional limits.

The discharge and flashover phenomenon of post insulators in rainy weather has not been given sufficient consideration; however, with the construction of ultra-high voltage power grids, the performance of the external insulation and the ability to withstand special climate conditions need to be guaranteed. Therefore, it is meaningful to conduct studies on the discharge characteristics of contaminated post insulators under rainfall conditions. Moreover, the conventional perception tends to confuse the flashover of polluted insulators in the rain with the pollution flashover that occurs in the fog; however, in fact, the discharge of contaminated insulators that occurs during rainfall has characteristics that can be distinguished from the pollution flashover. In this study, firstly, the current status of research on the external insulation characteristics of post insulators was analyzed through an examination of the available literature. Secondly, the concept of a ‘pollution rain flashover’ of insulators was established and clarified, to distinguish it from the traditional meaning of ‘pollution flashover’ or ‘contamination flashover’. Thirdly, research results on the pollution rain flashover of post insulators used in power stations in recent years were summarized, which included the characteristics and mechanism of the discharge, parameters and factors influencing the flashover voltage, and their influence laws. Particularly, the gap discharge between insulator sheds triggered by raindrops, which is the most significant feature of the pollution rain flashover, and the profile optimization of sheds, which is an effective way to improve the performance, were emphasized in this work. Fourthly, the prevention methods were studied, which mainly include the application of rainproof sheds and the shed optimization for pollution rain flashover of post insulators. Finally, a brief prospect is given for future research.

Aims: Rotator cuff muscle atrophy and fatty infiltration affect the clinical outcomes of rotator cuff tear patients. However, there is no effective treatment for fatty infiltration at this time. High-intensity interval training (HIIT) helps to activate beige adipose tissue. The goal of this study was to test the role of HIIT in improving muscle quality in a rotator cuff tear model via the β3 adrenergic receptor (β3AR). Methods: Three-month-old C57BL/6 J mice underwent a unilateral rotator cuff injury procedure. Mice were forced to run on a treadmill with the HIIT programme during the first to sixth weeks or seventh to 12th weeks after tendon tear surgery. To study the role of β3AR, SR59230A, a selective β3AR antagonist, was administered to mice ten minutes before each exercise through intraperitoneal injection. Supraspinatus muscle, interscapular brown fat, and inguinal subcutaneous white fat were harvested at the end of the 12th week after tendon tear and analyzed biomechanically, histologically, and biochemically. Results: Histological analysis of supraspinatus muscle showed that HIIT improved muscle atrophy, fatty infiltration, and contractile force compared to the no exercise group. In the HIIT groups, supraspinatus muscle, interscapular brown fat, and inguinal subcutaneous white fat showed increased expression of tyrosine hydroxylase and uncoupling protein 1, and upregulated the β3AR thermogenesis pathway. However, the effect of HIIT was not present in mice injected with SR59230A, suggesting that HIIT affected muscles via β3AR. Conclusion: HIIT improved supraspinatus muscle quality and function after rotator cuff tears by activating systemic sympathetic nerve fibre near adipocytes and β3AR. Cite this article: Bone Joint Res 2023;12(8):455–466.

The additive mass method (AMM) is applied to test the compaction density of soil–rock mixtures (S–RMs) due to its high efficiency, nondestructiveness and accuracy. However, there is no systematic research on influence factor of AMM. In this study, AMM test parameters were systematically calibrated first, and a calculation model for the compaction density of S–RM was established in the test area. After that, the AMM was applied in the on-site detection of the compaction density of an earth–rockfill dam. After calibration test, the main geophone frequency was 40 Hz, the drop distance and offset distance were 20 and 70 cm, respectively, and set the ∆m of five levels as 38, 88, 138, 213, and 288 kg. The detection error of K–K/ρ model had a better precision than the ω−2−ω−2/ρ model through on-site testing and verification. A new calculation model with lower accuracy based on vibration stiffness–vibration stiffness/density K−K/ρ) model was proposed according to the test error distribution. It was found that the test error of the K−K/ρ model was reduced to 0.9%. The results demonstrated that the AMM could accurately detect the compaction density of S–RM after the test parameters were reasonably determined.

Reconfigurable battery systems (RBSs) provide a promising alternative to traditional battery systems due to their flexible and dynamically changeable topological structures that can be adapted to different battery charging and discharging strategies. A critical system parameter known as the maximum allowable current (MAC) is pivotal to RBS operation. This parameter is instrumental in maintaining the current of each individual battery within a safe range and serves as a guiding indicator for the system’s reconfiguration, ensuring its safety and reliability. This paper proposes a method for calculating the MAC of an arbitrary RBS using a greedy algorithm in conjunction with a directed graph model of the RBS. Using the shortest path of the battery, the greedy algorithm transforms the exhaustion of the switch states in the brute-force algorithm or variable search without utilizing structures in the heuristic algorithms in the combination of the shortest paths. The directed graph model, based on an equivalent circuit, provides a specific method for calculating the MAC of a given structure. The proposed method is validated using 2 previously published RBS structures and an additional one with a more complex structure. The results are the same as those from the brute-force algorithm, but the proposed method substantially improves the computational efficiency, being theoretically Ns2Ns − Nblog10Nb times faster than the brute-force algorithm for an RBS with Nb batteries and Ns switches. Another advantage of the proposed method is its ability to calculate the MAC of RBSs with arbitrary structures and variable batteries, even in scenarios with random isolated batteries.

The rapid development and application of AMRs is important for Industry 4.0 and smart logistics. For large-scale dynamic flat warehouses, vision-based road recognition amidst complex obstacles is paramount for improving navigation efficiency and flexibility, while avoiding frequent manual settings. However, current mainstream road recognition methods face significant challenges of unsatisfactory accuracy and efficiency, as well as the lack of a large-scale high-quality dataset. To address this, this paper introduces IndoorPathNet, a transfer-learning-based Bird’s Eye View (BEV) indoor path segmentation network that furnishes directional guidance to AMRs through real-time segmented indoor pathway maps. IndoorPathNet employs a lightweight U-shaped architecture integrated with spatial self-attention mechanisms to augment the speed and accuracy of indoor pathway segmentation. Moreover, it surmounts the challenge of training posed by the scarcity of publicly available semantic datasets for warehouses through the strategic employment of transfer learning. Comparative experiments conducted between IndoorPathNet and four other lightweight models on the Urban Aerial Vehicle Image Dataset (UAVID) yielded a maximum Intersection Over Union (IOU) of 82.2%. On the Warehouse Indoor Path Dataset, the maximum IOU attained was 98.4% while achieving a processing speed of 9.81 frames per second (FPS) with a 1024 × 1024 input on a single 3060 GPU.

In this paper, we propose a geometric channel model for air-to-air (A2A) unmanned aerial vehicle (UAV) communication scenarios. The model is established by incorporating line-of-sight, specular reflection, and diffuse scattering components, and it can capture the impacts of UAV vibrations induced by the propeller’s rotation. Based on UAV heights and ground scatterer density, a closed-form expression is derived to jointly capture the zenith and azimuth angular distributions of diffuse rays. The power of diffuse rays is modeled according to the grazing angle of the rays and the electrical properties and roughness of the ground materials. Key statistics, including the temporal autocorrelation function, spatial cross-correlation function, Doppler power spectrum density, and coherence time are derived, providing an in-depth understanding of the time-variant characteristics of the channel. The results indicate that the presented model is capable of capturing certain A2A channel characteristics, which align with the corresponding theoretical analysis. The findings suggest that the scattering effect of the A2A channel is significantly influenced by the altitude of the UAV. Additionally, it is shown that UAV vibrations can introduce extra Doppler frequencies, notably decreasing the temporal correlation and coherence time of the channel. This effect is more prominent when the system operates at high-frequency bands. The effectiveness of the presented model is confirmed through a comparison of its statistics with those of an existing model and with available measurement data.

Combined SINS/GPS navigation systems have been widely used. However, when the traditional combined SINS/GPS navigation system travels between tall buildings, in the shade of trees, or through tunnels, the GPS encounters frequent signal blocking, which leads to the interruption of GPS signals, and as a result, the combined SINS/GPS-based navigation method degenerates into a pure inertial guidance system, which will lead to the accumulation of navigation errors. In this paper, an adaptive Kalman filtering algorithm based on polynomial fitting and a Taylor expansion is proposed. Through the navigation information output from the inertial guidance system, the polynomial interpolation method is used to construct the velocity equation and position equation of the carrier, and then the Taylor expansion is used to construct the virtual measurement at the moment of the GPS signal interruption, which can make up for the impact of the lack of measurement information on the combined SINS/GPS navigation system when the GPS signal is interrupted. The results of computer simulation experiments and road measurement tests based on the loosely combined SINS/GPS navigation system show that when the carrier faces a GPS signal interruption situation, compared with a combined SINS/GPS navigation algorithm that does not take any rescue measures, our proposed combined SINS/GPS navigation algorithm possesses a higher accuracy in the attitude angle estimation, a higher accuracy in the velocity estimation, and a higher accuracy in the positional localization, and the system possesses higher stability.

The phase evolution, magnetic properties and microstructure of rod-shaped permanent magnets prepared by annealing the amorphous precursor Fe70−xNd7B21Zr2Nbx (x = 0–3.0) were systematically studied. X-ray diffraction analysis, magnetometer, microstructure and δM-plots studies show that the good magnetic properties of the magnet are attributed to the uniform microstructure composed of exchange-coupled α-Fe and Nd2Fe14B phases. Nb addition to Fe67.5Nd7B21Zr2Nb2.5 alloy led to an increase in the volume fraction of the soft magnetic phase, reinforced exchange coupling and improved magnetic properties. The magnetic properties of the optimized annealed Fe67.5Nd7B21Zr2Nb2.5 rod are: coercivity (Hci) = 513.92 kA/m, remanence (Br) = 0.58 T, squareness (Hk/Hci) = 0.24 and magnetic energy product ((BH)max) = 37.59 kJ/m3.

Abstract The non-linear and non-stationary vibration data generated by rotating machines can be used to analyze various fault conditions for predicting the remaining useful life(RUL). It offers great help to make prognostic and health management(PHM) develop. However, the complexity of the mechanical working environment makes the vibration data collected easily affected, so it is hard to form an appropriate health index(HI) to predict the RUL. In this paper, a PSR-former model is proposed including a Phase space reconstruction(PSR) layer and a Transformer layer. The PSR layer is utilized as an embedding to deepen the understanding of vibration data after feature fusion. In the Transformer layer, an attention mechanism is adopted to give different assignments, and a layer-hopping connection is used to accelerate the convergence and make the structure more stable. The effectiveness of the proposed method is validated through the Intelligent Maintenance Systems (IMS) bearing dataset. Through analysis, the prediction accuracy is judged by the parameter RMSE which is 1.0311. Some state-of-art methods such as LSTM, GRU, and CNN were also analyzed on the same dataset to compare. The result indicates that the proposed method can effectively establish a precise model for RUL predictions.

Soybean hundred seed weight (HSW) is a complex quantitative trait affected by multiple genes and environmental factors. To date, a large number of quantitative trait nucleotides (QTNs) have been reported, but less information on QTN-by-environment interactions (QEIs) and QTN-QTN interaction (QQIs) for soybean HSW is available. Mapping without QEIs and QQIs result in missing some important QTNs that are significantly related to HSW. Therefore, the present study conducted genome-wide association analysis to map main QTNs, QEIs and QQIs for HSW in a panel with 573 diverse soybean lines tested in three independent environments (E1, E2 and E3) with Mean- and best linear unbiased value (BLUP)- phenotype. In all, 147 main effect QTNs, 11 QEIs, and 24 pairs of QQIs were detected in the Mean-phenotype, and 138 main effect QTNs, 13 QEIs, and 27 pairs of QQIs in the BLUP-phenotype. The total phenotypic variation explained by the main effect QTNs, QEIs, and QQIs were 35.31–39.71, 8.52–8.89 and 34.77–35.09%, respectively, indicating an important role of non-additive effects on HSW. Out of these, 33 QTNs were considered as stable with 23 colocalized with previously known loci, while 10 were novel QTNs. In addition, 10 pairs stable QQIs were simultaneously detected in the two phenotypes. Based on homolog search in Arabidopsis thaliana and in silico transcriptome data, seven genes (Glyma13g42310, Glyma13g42320, Glyma08g19580, Glyma13g44020, Glyma13g43800, Glyma17g16620 and Glyma07g08950) from some main-QTNs and two genes (Glyma06g19000 and Glyma17g09110) of QQIs were identified as potential candidate genes, however their functional role warrant further screening and functional validation. Our results shed light on the involvement of QEIs and QQIs in regulating HSW in soybean, and these together with candidate genes identified would be valuable genomic resources in developing soybean cultivars with desirable seed weight.

Because the conventional Temperature Drift Error (TDE) estimation model for Capacitive MEMS Gyros (CMGs) has inadequate Temperature Correlated Quantities (TCQs) and inaccurate parameter identification to improve their bias stability, its novel model based on thermal stress deformation analysis is presented. Firstly, the TDE of the CMG is traced precisely by analyzing its structural deformation under thermal stress, and more key decisive TCQs are explored, including ambient temperature variation ∆T and its square ∆T2, as well its square root ∆T1/2; then, a novel TDE estimation model is established. Secondly, a Radial Basis Function Neural Network (RBFNN) is applied to identify its parameter accurately, which eliminates local optimums of the conventional model based on a Back-Propagation Neural Network (BPNN) to improve bias stability. By analyzing heat conduction between CMGs and the thermal chamber with heat flux analysis, proper temperature control intervals and reasonable temperature control periods are obtained to form a TDE precise test method to avoid time-consuming and expensive experiments. The novel model is implemented with an adequate TCQ and RBFNN, and the Mean Square Deviation (MSD) is introduced to evaluate its performance. Finally, the conventional model and novel model are compared with bias stability. Compared with the conventional model, the novel one improves CMG’s bias stability by 15% evenly. It estimates TDE more precisely to decouple Si-based materials’ temperature dependence effectively, and CMG’s environmental adaptability is enhanced to widen its application under complex conditions.

Abstract Background The trihelix family of transcription factors plays essential roles in the growth, development, and abiotic stress response of plants. Although several studies have been performed on the trihelix gene family in several dicots and monocots, this gene family is yet to be studied in Chenopodium quinoa (quinoa). Results In this study, 47 C. quinoa trihelix (CqTH) genes were in the quinoa genome. Phylogenetic analysis of the CqTH and trihelix genes from Arabidopsis thaliana and Beta vulgaris revealed that the genes were clustered into five subfamilies: SIP1, GTγ, GT1, GT2, and SH4. Additionally, synteny analysis revealed that the CqTH genes were located on 17 chromosomes, with the exception of chromosomes 8 and 11, and 23 pairs of segmental duplication genes were detected. Furthermore, expression patterns of 10 CqTH genes in different plant tissues and at different developmental stages under abiotic stress and phytohormone treatment were examined. Among the 10 genes, CqTH02, CqTH25, CqTH18, CqTH19, CqTH25, CqTH31, and CqTH36, were highly expressed in unripe achenes 21 d after flowering and in mature achenes compared with other plant tissues. Notably, the 10 CqTH genes were upregulated in UV-treated leaves, whereas CqTH36 was consistently upregulated in the leaves under all abiotic stress conditions. Conclusions The findings of this study suggest that gene duplication could be a major driver of trihelix gene evolution in quinoa. These findings could serve as a basis for future studies on the roles of CqTH transcription factors and present potential genetic markers for breeding stress-resistant and high-yielding quinoa varieties.

Micro-channel vaporizer has the advantages of high heat exchange efficiency, high pressure resistance and compact structure, and has broad application prospect as an LNG vaporizer. Presently, most of the LNG micro-channel vaporizers are designed by the segmentation method, which requires massive calculation by the programming computation, and it is not conductive for its promotion and application in engineering. Therefore, a four-segmented design method was proposed for the LNG micro-channel vaporizer. The vaporizer is divided into 4 segments based on the temperature of working fluids under different phases. Then, the heat transfer amount, heat transfer area and pressure drop of each segment can be obtained through the heat balance calculation and structural design calculation, and thereby the total heat transfer area can be calculated. The calculation results have an error of 13.4% compared with that given in the reference. The numerical simulation for the flow and heat transfer characteristics of the designed micro-channel unit shows that the simulated values of the channel temperature and the pressure drop are well consistent with the calculated values of the four-segmented method, and thereby, the reliability of the four-segmented design method for the LNG micro-channel vaporizer is verified.Generally, the method has the characteristics of reasonable segmentation, less calculation, and intuitive and reliable results, which provides an effective way for the design and optimization of LNG micro-channel vaporizer.

Abstract Background Percutaneous vertebroplasty (PVP) has been widely used to treat vertebral pathological fractures in recent decades, and the modified PVP instrument is very suitable for percutaneous biopsy of diseases promoting vertebral bone destruction. The purpose of this study was to evaluate the relevance of the clinical application of the modified PVP instrument in computed tomography-guided (CT-guided) biopsies of the vertebral body. Methods Retrospective analysis of clinical data obtained by percutaneous biopsy using a modified PVP outer shell of a bone filler device (OSBF) from 161 patients presenting vertebral body destruction was conducted. The rate of correctly performed biopsy diagnosis was evaluated from three aspects: imaging performance, histological type, and vertebral segment. Results The results of 149 biopsy cases were consistent with the final clinical diagnosis. From those cases, 92 were diagnosed as vertebral body metastasis, 45 cases presented primary spinal tumors and tumor-like changes, 7 cases presented vertebral body infections, and 5 cases displayed normal bones or fractures. From the remaining 12 patients, whose biopsy results were inconsistent with the final clinical diagnosis, 4 presented vertebral metastases, 4 displayed primary vertebral tumors, and 4 presented vertebral infections. The diagnostic rate of the modified PVP OSBF biopsy was 92.5%. The rate of correct biopsy diagnosis for vertebral metastases was 95.8%. The rate of correct diagnosis of primary vertebral tumors and tumor-like biopsy was 91.8%, and the rate of correct diagnosis for vertebral infectious diseases was 63.6%. Conclusion The modified PVP OSBF allows obtaining more lesion tissue, in multiple directions and multiple angles, during the biopsy of vertebral bones presenting destructive lesions. The technique displays appropriate safety and high diagnostic accuracy and presents a desirable reference value for the preoperative diagnosis of diseases that yield vertebral bone destruction, especially for vertebral tumor lesions.

Accurate spinal tuberculosis (TB) diagnosis is of utmost importance for adequately treating and managing the disease. Given the need for additional diagnostic tools, this study aimed to investigate the utility of host serum miRNA biomarkers for diagnosing and distinguishing spinal tuberculosis (STB) from pulmonary tuberculosis (PTB) and other spinal diseases of different origins (SDD). For a case-controlled investigation, a total of 423 subjects were voluntarily recruited, with 157 cases of STB, 83 cases of SDD, 30 cases of active PTB, and 153 cases of healthy controls (CONT) in 4 clinical centers. To discover the STB-specific miRNA biosignature, a high-throughput miRNA profiling study was performed in the pilot study with 12 cases of STB and 8 cases of CONT using the Exiqon miRNA PCR array platform. A bioinformatics study identified that the 3-plasma miRNA combination (hsa-miR-506-3p, hsa-miR-543, hsa-miR-195-5p) might serve as a candidate biomarker for STB. The subsequent training study developed the diagnostic model using multivariate logistic regression in training data sets, including CONT(n=100) and STB (n=100). Youden’s J index determined the optimal classification threshold. Receiver Operating Characteristic (ROC) curve analysis showed that 3-plasma miRNA biomarker signatures have an area under the curve (AUC) = 0.87, sensitivity = 80.5%, and specificity = 80.0%. To explore the possible potential to distinguish spinal TB from PDB and other SDD, the diagnostic model with the same classification threshold was applied to the analysis of the independent validation data set, including CONT(n=45), STB(n=45), brucellosis spondylitis (BS, n=30), PTB (n=30), spinal tumor (ST, n=30) and pyogenic spondylitis (PS, n=23). The results showed diagnostic model based on three miRNA signatures could discriminate the STB from other SDD groups with sensitivity=80%, specificity=96%, Positive Predictive Value (PPV)=84%, Negative Predictive Value (NPV)=94%, the total accuracy rate of 92%. These results indicate that this 3-plasma miRNA biomarker signature could effectively discriminate the STB from other spinal destructive diseases and pulmonary tuberculosis. The present study shows that the diagnostic model based on 3-plasma miRNA biomarker signature (hsa-miR-506-3p, hsa-miR-543, hsa-miR-195-5p) may be used for medical guidance to discriminate the STB from other spinal destructive disease and pulmonary tuberculosis.

Abstract The pandemic of COVID-19 caused by SARS-CoV-2 has raised a new challenges to the scientific and industrious fields after over 1-year spread across different countries. The ultimate approach to end the pandemic is the timely application of vaccines to achieve herd immunity. Here, a novel SARS-CoV-2 receptor-binding domain (RBD) homodimer was developed as a SARS-CoV-2 vaccine candidate. Formulated with aluminum adjuvant, RBD dimer elicited strong immune response in both rodents and non-human primates, and protected mice from SARS-CoV-2 challenge with significantly reducing viral load and alleviating pathological injury in the lung. In the non-human primates, the vaccine could prevent majority of the animals from SARS-CoV-2 infection in the respiratory tract and reduce lung damage. In addition, antibodies elicited by this vaccine candidate showed cross-neutralization activities to SARS-CoV-2 variants. Furthermore, with our expression system, we provided a high-yield RBD homodimer vaccine without additional biosafety or special transport device supports. Thus, it may serve as a safe, effective, and low-cost SARS-CoV-2 vaccine candidate.

In this study, nine soils at different depths in a decommissioned uranium tailing pond in Jiangxi Province are selected as the research objects to study their mineralogical properties and reveal the leaching law of radioactive element uranium under natural rainfall conditions. The research results are as follows: 1) The distribution characteristics of uranium are affected by the mineral composition, microscopic morphology and physical and chemical properties of uranium tailings. 2) In static leaching experiments, acidic solutions, small particles, and high solid-to-liquid ratios all promote the release of uranium. 3) In the dynamic leaching experiment, the lower the pH of simulated rainfall, the more uranium is released. According to Fick theory, the migration mechanism of uranium is mainly surface dissolution, and the release of uranium is related to the content of migratory uranium.

Methylation has a close relationship with immune reactions, metastasis, and cancer cell growth. Additionally, RNA methylation-related proteins have emerged as potential cancer therapeutic targets. The connection between the tumor microenvironment (TME) and methylation-related genes (MRGs) remains unclear. We explored the expression patterns of the MRGs in the genome and transcriptional fields of 796 prostate cancer (PCa) samples using two separate data sets. We identified a relationship between patient clinicopathological characteristics, prognosis, TME cell infiltrating qualities, and different MRG changes, as well as the identification of two distinct molecular groupings. Then, we formed an MRGs model to predict overall survival (OS), and we tested the accuracy of the model in patients with PCa. In addition, we developed a very accurate nomogram to improve the MRG model’s clinical applicability. The low-risk group had fewer tumor mutational burden (TMB), greater tumor immune dysfunction and exclusion (TIDE) ratings, fewer mutant genes, and better OS prospects. We discuss how MGRs may affect the prognosis, clinically important traits, TME, and immunotherapy responsiveness in PCa. In order to get a better understanding of MRGs in PCa, we could further explore the prognosis and create more effective immunotherapy regimens to open new avenues.

The high noise and low energy characteristics of the raw signals collected by sensors make the signal features weak and difficult to train. The purpose of this paper is to enhance the fault features of abnormal signals using the hierarchical feature enhancement method (HFE) which contains three layers. In the first layer, the signals are decomposed into multiple modals estimated by a variational optimization problem. The modals we choose are used to reconstruct the signals to form a complex matrix used to extract features in the second layer. In the third layer, the feature signals are converted into two-dimensional space and then are input into the convolutional neural network (CNN) for fault diagnosis after HFE since CNN helps to mine deeper features and compute in parallel on a large scale. The experimental results effectively verify the performance of the HFE for enhancing the weak fault features and preventing noise interference. The signals analyzed by HFE used as input greatly improve the diagnosis ability of CNN. In addition, the ablation and comparison experiments are conducted which still show superiority.

Stroke is a leading cause of death and long-term disability worldwide. Tissue plasminogen activator (tPA) is an effective treatment for ischemic stroke. However, only a small part of patients could benefit from it. Therefore, finding a new treatment is necessary. Bone marrow mesenchymal stromal cells (BMSCs) provide a novel strategy for stroke patients. Now, many patients take stem cells to treat stroke. However, the researches of the precise inflammatory mechanism of cell replacement treatment are still rare. In this review, we summarize the immune response of BMSCs treated to stroke and may provide a new perspective for stem cell therapy.

Mangroves are high-productive ecosystems and globally protected. Establishing nature reserves aimed at counteracting the negative effects of anthropogenic activities is one of the most pivotal approaches to conserve mangrove ecosystems. Evaluation of the conservation effectiveness for mangrove nature reserves is thus indispensable for making knowledge-based conservation policies and funding-decisions by government and managers. In this study, using composited Landsat images by the Google Earth Engine cloud platform and object-oriented deep learning classification method, the land cover maps of national mangrove nature reserves (NMNRs) in China were obtained from 1987 to 2019. The systematic evaluation of conservation effectiveness for each NMNR was conducted by landscape metrics and an entropy weight model. Combined with the dynamics in mangrove distribution, human interference intensity, and natural environment change, the driving force factors affecting the conservation effectiveness for NMNRs were investigated. The results show that the total mangrove area in all NMNRs increased 968.6 ha during the study period, a 21.8 % rate of increase. Except for one NMNR with a slight decline, the conservation of remaining NMNRs was considered effective with increase varied from 14.8 % to 87.5 % in the level of protective efficacy. The conservation effectiveness of NMNRs was affected by both anthropogenic and natural factors, while the improvement to the conservation effectiveness was largely attributed to the implementation of protection policies, such as reforestation engineering. Further direct or indirect challenges in mangrove conservation effectiveness, e.g., pollution, natural disasters, and exotic species invasion, still require close attention. This study provides an effective and efficient approach to quantify the conservation effectiveness of mangrove nature reserves, which would facilitate mangrove conservation and management in the future.

A magnetic-controlled flexible continuum robot (MFCR) is a kind of continuum robot with small-size and flexibility that deforms under controlled magnetic fields, which makes MFCRs easy to fit in special sizes and designs and provides them with the ability to feasibly arrive at the desired area through certain blood vessel bifurcation. The magnetic drive method is suitable for the miniaturization of soft continuum robots but shows limitations in realizing high flexibility. To achieve miniaturization and high flexibility, in this work, the deformation schemes of a magnetic-controlled flexible continuum robot (MFCR) are proposed, simulated, and experimentally validated. The proposed MFCR includes a soft steering part made of a silicone elastomer with uniformly dispersed NdFeB powder which has a specific magnetization direction. With the actuation of different magnetic fields, the proposed MFCR shows three different deformation modes (C-shape, J-shape, and S-shape) and high flexibility. By using the potential energy model combined with magnetic and elastic potential energy, the quasi-static deformation model of MFCR is built. Through various simulations and experiments, we analyzed and predicted different deformation modes. The results from the experiments demonstrate the accuracy of the deformation model. The results indicate that the MFCR has good control precision and deformation performance with potential applications in robot-assisted minimally invasive surgery.

Biomedical glues often face a challenge in providing strong adhesion and providing remodelling capabilities. Here the authors report on the development of a biocompatible and biodegradable protein-based coacervate adhesive and demonstrate application in haemostasis and wound healing using pig models.

The potent cytotoxic property of Vγ2Vδ2 T cells makes them attractive for adoptive T cell transfer therapy. The transfusing of the expanded Vγ2Vδ2 T cells into cancer patients shows well-tolerated, but the clinical response rates are required to be improved, implying that there is still an unmet efficacy with low toxicity for this novel anti-tumor therapy. In this study, we test the anti-tumor efficacy of a Y-body-based bispecific antibody (bsAb) Vγ2 x PD-L1 that preferentially redirects Vγ2Vδ2 T cells to combat PD-L1 positive tumor cells. With nanomolar affinity levels to Vγ2Vδ2 T cells and PD-L1+ tumor cells, Vγ2 x PD-L1 bridges a Vγ2Vδ2 T cell with a SKOV3 tumor cell to form a cell-to-cell conjugation. In a PD-L1-dependent manner, the bsAb elicits effective activation (CD25+CD69+), IFNγ releasing, degranulation (CD107a+), and cytokine production (IFNγ+ and TNFα+) of expanded Vγ2Vδ2 T cells. The activations of the Vγ2Vδ2 T cells eliminate PD-L1-expressing human cancer cell lines, including H1975, SKOV3, A375, H1299, and H2228 cells, but not PD-L1 negative cells including HEK-293 (293) cells and healthy PBMCs. Finally, we show that combining Vγ2 x PD-L1 with adoptively transferring Vγ2Vδ2 T cells inhibits the growth of existing tumor xenografts and increases the number of Vγ2Vδ2 T cells into the tumor bed. Vγ2 x PD-L1 represents a promising reagent for increasing the efficacy of adoptively transferred Vγ2Vδ2 T cells in the treatment of PD-L1 positive malignant tumors.

Abstract Background To compare the diseased verses the non-diseased intervertebral surgery used in the treatment of thoracolumbar and lumbar spinal tuberculosis and to explore the best choice of fusion of fixation range. Methods Two hundred twenty-one patients with thoracolumbar and lumbar tuberculosis were categorized into two groups. One hundred eighteen patients underwent the diseased intervertebral surgery (lesion vertebral pedicle fixation, Group A) and 103 patients underwent the non-diseased intervertebral surgery (1 or 2 vertebral fixation above and below the affected vertebra, group B). Spinal tuberculosis diagnosis was confirmed in both groups of patients before lesion removal, bone graft fusion, and internal fixation. Clinical data and efficacy of the two surgical methods were then evaluated. Results The mean follow-up duration for both procedures was 65 months (50–68 months range). There were no significant differences in laboratory examinations, VAS scores, and the Cobb angle correction rate and the angle loss. However, significant differences existed in the operation time, blood loss, serosanguineous drainage volume, and blood transfusion requirement between the two groups. The diseased intervertebral surgery group performed significantly better than the non-diseased intervertebral surgery group in all of these areas. In both cases, the bone graft fused completely with the normal bone by the last follow-up, occuring at 50–86 months post surgery. Conclusion The diseased intervertebral surgery is a safe and feasible option for the treatment of thoracolumbar and lumbar tuberculosis. It effectively restores the physiological curvature of the spine and reduces the degeneration of adjacent vertebral bodies in the spinal column.

ObjectivesDue to the aging and illegal operation of crane equipment during hoisting operations on offshore platforms, dropped object accidents are the most prevalent type of accident, of which the dropping of slender rod-like objects such as drill collars and casings is the most common. Due to the small contact area and high velocity, the failure of the partial-plate structure is often caused, which requires attention.MethodsThis paper studies the specific deformation mechanism of a deck under the impact of dropped slender rods at different impact angles while considering the influence of the impact angle on damage to the deck. A new deformation model is proposed for decks subject to impact loads at different impact angles. Based on this new deformation model, a prediction method which considers the influence of the impact angle is obtained on the basis of the plastic mechanics theory.ResultsThe results show that a small impact angle will cause great structural damage and deformation, as well as high structural energy absorption. According to the structural response, the impact angle can be divided into four angle intervals. The energy absorption curves obtained from the analytical method and simulation are similar in value and change trend.Conclusions When a rod-like structure hits a deck at a certain angle, the shape of the plastic deformation area of the deck changes with the depth of the collision. The analytical results of the deformation characteristics of the deck at each stage can provide valuable references for the preliminary structural design and assessment of the crashworthiness of the deck structures of offshore platforms.

Wildfires directly threaten the safety of life and property. Predicting wildfires with a model driven by wildfire danger factors can significantly reduce losses. Weather conditions continuously influence the drying rate of fuel as well as the occurrence probability and danger degree of wildfires. Previous studies have paid little attention to the continuous effects of weather and fuel on wildfires. This study improved the accuracy and effect of wildfire danger assessment using the time series features of weather and fuel. First, the time series features of weather and fuel factors within the 16 days before the fire were analyzed. Then, four feature groups were selected—feature group without time series values, feature group with time series values, feature group with Tsfresh transformation of time series values, and feature group with gradient and cumulative transformation of time series values—and three models were trained, respectively: random forest, balanced random forest, and extreme gradient boosting. The results showed that the f1-score of all feature groups with time series values (0.93) increased by 0.15, on average, compared with those without time series values (0.78) for the three models. The feature group with gradient and cumulative features had a more stable prediction accuracy and a more accurate wildfire danger map. The results suggest that using the appropriate time series features of weather and fuel can help improve the precision and effect of the wildfire danger assessment model.

The state-of-health (SoH) of the reaction wheel (RW) is a key indicator of the satellite’s ability to function properly and complete its mission successfully. Quick and accurate prediction of the RW’s SoH is an important guarantee of autonomous satellite mission execution and health management. In view of the pseudoperiodicity and strong noise characteristics of satellite on-orbit telemetry data, this paper aims to design a prediction framework meeting the satellite state on-orbit prediction requirements, which mainly includes data reconstruction, similar data screening, self-revised prediction and the fuzzy expression of results. First, a new method for RW health characterization is proposed for actual telemetry data from satellites, and a completely new set of historical samples is constructed. Second, a fusion deviation measure is proposed by selecting samples from the historical sample set that are similar to the sample to be predicted. Third, a Fourier Broad Learning System (FBLS) is proposed to improve the depiction accuracy of a standard Broad Learning System (BLS) in learning satellite telemetry data with less computational and time resources. Finally, a fuzzy expression is proposed to obtain the prediction results. The proposed method is validated with real satellite on-orbit telemetry data. The case study results show that the SoH of the RW can be predicted quickly and accurately, which demonstrates the promising performance of our method.

Background Infrapatellar fat pad (IPFP) is regarded as an essential knee tissue involved in osteoarthritis (OA) for its potential structural-related or metabolism-related function. This cross-sectional study aims to identify which part is more related to OA. Methods Patients with knee OA ( n = 53) and healthy controls ( n = 54) were prospectively recruited. Based on high-resolution magnetic resonance imaging with a slice thickness of only 0.35 mm, IPFP structural-related parameters (volume and maximal area), metabolism-related parameter (signal), degeneration indicators, and patellar maltracking indicators (patellar translation, patellofemoral angle, and Insall-Salvati ratio) were measured. IPFP volume (maximal area, and signal) was compared between healthy controls and OA patients. The level of significance for all comparisons was set as .05. Results OA patients had higher IPFP signal (672.9 ± 136.9 vs 567.3 ± 63.6, p = .009), but no significant difference in IPFP volume or maximal area compared with healthy controls. In healthy controls, IPFP signal was positively associated with age ( β = 1.481; 95% CI: 0.286–2.676; p = .018); IPFP maximal area was positively related to Insall-Salvati ratio ( β = 0.001; 95% CI: 0.0003–0.0017; p = .039), but not associated with patellar translation and patellofemoral angle. In OA patients, IPFP signal was positively associated with cartilage loss ( β = 0.005; 95% CI: 0.003–0.007; p = .013); no correlation between knee pain and IPFP volume or maximal area was observed. Conclusions The metabolism-related function of IPFP, which can be reflected by the IPFP signal, might play a more critical role in OA progression than its structural function.

Disturbance of bone homeostasis caused by Mycobacterium tuberculosis (Mtb) is a key clinical manifestation in spinal tuberculosis (TB). However, the complete mechanism of this process has not been established, and an effective treatment target does not exist. Increasing evidence shows that abnormal osteoclastogenesis triggered by an imbalance of the receptor activator of NF-κB ligand (RANKL)/osteoprotegerin (OPG) axis may play a key role in the disturbance of bone homeostasis. Previous studies reported that RANKL is strongly activated in patients with spinal TB; however, the OPG levels in these patients were not investigated in previous studies. In this study, we investigated the OPG levels in patients with spinal TB and the dysregulation of osteoblasts caused by Mtb infection. Inhibition of the Mce4a gene of Mtb by an antisense locked nucleic acid (LNA) gapmer (Mce4a-ASO) was also investigated. Analysis of the serum OPG levels in clinical samples showed that the OPG levels were significantly decreased in patients with spinal TB compared to those in the group of non-TB patients. The internalization of Mtb in osteoblasts, the known major source of OPG, was investigated using the green fluorescent protein (GFP)-labeled Mycobacterium strain H37Ra (H37RaGFP). The cell-associated fluorescence measurements showed that Mtb can efficiently enter osteoblast cells. In addition, Mtb infection caused a dose-dependent increase of the CD40 mRNA expression and cytokine (interleukin 6, IL-6) secretion in osteoblast cells. Ligation of CD40 by soluble CD154 reversed the increased secretion of IL-6. This means that the induced CD40 is functional. Considering that the interaction between CD154-expressing T lymphocytes and bone-forming osteoblast cells plays a pivotal role in bone homeostasis, the CD40 molecule might be a strong candidate for mediating the target for treatment of bone destruction in spinal TB. Additionally, we also found that Mce4a-ASO could dose-dependently inhibit the Mce4a gene of Mtb and reverse the decreased secretion of IL-6 and the impaired secretion of OPG caused by Mtb infection of osteoblast cells. Taken together, the current finding provides breakthrough ideas for the development of therapeutic agents for spinal TB.

It is difficult to detect the inner layer of the bimetallic tube and to describe its full-cross-section deformation, which negatively affects its verification and utility. To tackle this issue, a novel theory is proposed for fitting the full-cross-section deformation characterization of Cu/Al bimetallic tubes under Rotary-Draw-Bending. The cross-section profiles on the bending outside are fitted by the physics-driven B-spline curves. The geometric characteristics and the bending principles are set as the physics information and drive the design of the control vertices of the fitting B-curves. The interlaminar shape inheritance of the bimetallic tube is implemented by the same position angle of the corresponding control vertices. The cross-section profiles on the bending inside are fitted by the regular curves considering the elongation percentage. The comparison between the theoretical profiles and the experimental profiles shows remarkable agreement. The average circumferential errors of the theoretical profiles are within 1.82%, far smaller than the errors of the traditional ovalization profiles. Additionally, the representative parameters of full-cross-section deformation are differently affected by the wall-thickness. The wall-thinning of the outer layer and inner layer usually shows an opposite tendency when the wall-thickness varies.

Abstract Background Seed weight is a complex yield-related trait with a lot of quantitative trait loci (QTL) reported through linkage mapping studies. Integration of QTL from linkage mapping into breeding program is challenging due to numerous limitations, therefore, Genome-wide association study (GWAS) provides more precise location of QTL due to higher resolution and diverse genetic diversity in un-related individuals. Results The present study utilized 573 breeding lines population with 61,166 single nucleotide polymorphisms (SNPs) to identify quantitative trait nucleotides (QTNs) and candidate genes for seed weight in Chinese summer-sowing soybean. GWAS was conducted with two single-locus models (SLMs) and six multi-locus models (MLMs). Thirty-nine SNPs were detected by the two SLMs while 209 SNPs were detected by the six MLMs. In all, two hundred and thirty-one QTNs were found to be associated with seed weight in YHSBLP with various effects. Out of these, seventy SNPs were concurrently detected by both SLMs and MLMs on 8 chromosomes. Ninety-four QTNs co-localized with previously reported QTL/QTN by linkage/association mapping studies. A total of 36 candidate genes were predicted. Out of these candidate genes, four hub genes (Glyma06g44510, Glyma08g06420, Glyma12g33280 and Glyma19g28070) were identified by the integration of co-expression network. Among them, three were relatively expressed higher in the high HSW genotypes at R5 stage compared with low HSW genotypes except Glyma12g33280. Our results show that using more models especially MLMs are effective to find important QTNs, and the identified HSW QTNs/genes could be utilized in molecular breeding work for soybean seed weight and yield. Conclusion Application of two single-locus plus six multi-locus models of GWAS identified 231 QTNs. Four hub genes (Glyma06g44510 , Glyma08g06420 , Glyma12g33280 & Glyma19g28070) detected via integration of co-expression network among the predicted candidate genes.

Enormous computation and long data processing time of the online tolerance inspection procedure has been a bottleneck in reducing the production cycle time of automatic assembly line. To reduce time consumption while maintaining accuracy, a fast assembly tolerance inspection method is proposed in this paper using scale-reduced models. First, the general part surface, input by a laser-scanned dense point cloud, is segmented through feature-based clustering. Shape variation estimation are designed to determine reduction ratios between clusters adaptively. Then, assembly simulation method is further advanced to utilize coarse point models with imbalanced density. Finally, numerical experiments are designed to estimate both static and dynamic assembly tolerances as results of tolerance inspection. A case study on a motion component of a rail material transporter shows that the proposed method could reduce 81% of the data processing time compared to traditional practice. The precision loss has minor influence on the inspection results because spatial positioning error is no more than 6% of tolerance interval and 18% of scanning resolution. Moreover, the proposed method has a comprehensive advantage of time and accuracy than two conventional point cloud simplification techniques based on iterative and clustering methods.

Due to oversaturated traffic condition, few models are capable of describing the complexity and control strategies are difficult to design. This article proposes an arterial coordination control for unsaturated and oversaturated traffic condition via discretization analysis model. The Robertson discrete formula is introduced to describe the discrete relationship between the upstream and downstream flow. The downstream vehicle arrival rate satisfies the cyclical relationship when the turning traffic flow is low. On this basis, the traffic parameters of the upstream and downstream can be calculated by the `look-up table' method instead of the `recursion' method in using the periodic array to save the intermediate variables in the model. As a result, the computation time significantly decreases. For unsaturated situation, delays are accumulated in each time period and reduced through adjusting offsets. For oversaturated traffic condition caused by lane occupancy accidents, green time is optimized by genetic algorithm after the road capacity decline is estimated. Simulation experimental results verify the effectiveness of the control strategies and the practicability of the proposed model.

Abstract Background At present, bicortical pedicle screws (BPSs) are not used clinically because they carry the potential risk of damaging the prevertebral great vessels (PGVs). The authors observed the anatomical relationship between the PGVs and simulated BPSs at different transverse screw angles (TSAs), exploring the insertion method of the BPS. Methods Computed tomography angiography (CTA) images from 65 adults were collected. A total of 4–5 TSAs of the BPSs were simulated on the left and right sides of L1-L5 (L1-L3: 0°, 5°, 10°, 15°; L4-L5: 0°, 5°, 10°, 15°, 20°). There were three types of distances from the anterior vertebral cortex (AVC) to the PGVs (DAVC-PGV); DAVC-PGV

Abstract Background In practical production, dairy cows are frequently exposed to bacterial endotoxin (lipopolysaccharide, LPS) when they are subjected to high-concentrate diets, poor hygienic environments, as well as mastitis and metritis. Histone acetylation is an important epigenetic control of DNA transcription and a higher histone acetylation is associated with facilitated transcription. LPS might reduce histone acetylation in the mammary epithelial cells, resulting in lower transcription and mRNA expression of lactation-related genes. This study was conducted to investigate the effect of LPS on histone acetylation in bovine mammary epithelial cells and the efficacy of sodium butyrate (SB) in suppressing the endotoxin-induced adverse effect. Firstly, the bovine mammary epithelial cell line MAC-T cells were treated for 48 h with LPS at different doses of 0, 1, 10, 100, and 1000 endotoxin units (EU)/mL (1 EU = 0.1 ng), and the acetylation levels of histones H3 and H4 as well as the histone deacetylase (HDAC) activity were measured. Secondly, the MAC-T cells were treated for 48 h as follows: control, LPS (100 EU/mL), and LPS (100 EU/mL) plus SB (10 mmol/L), and the acetylation levels of histones H3 and H4 as well as milk gene mRNA expressions were determined. Results The results showed that HDAC activity increased linearly with increasing LPS doses (P 0.05). Sodium butyrate, an inhibitor of HDAC, effectively suppressed the endotoxin-induced decline of histone H3 acetylation (P

Abstract Background Senescent cells exert a significant influence over their surrounding cellular environment. Senescent chondrocytes (SnChos) were found to be accumulated in degenerated cartilage present in joints affected by osteoarthritis. The influence of SnChos on exogenously transplanted stem cells has yet to be reported. Methods In this study, we evaluated the interactions between SnChos and bone marrow mesenchymal stem cells (BMSCs) when co-cultured as well as in the intra-articular senescent microenvironment (IASM). The effect of IASM on cartilage regeneration was also assessed. Results It was found that a small fraction of SnChos induced BMSC cellular senescence and apoptosis. SnChos also inhibited proliferation, facilitated stemness, and suppressed chondrogenic differentiation of BMSCs. BMSCs induced the apoptosis of SnChos, reduced the proportion of SnChos, stimulated SnChos proliferation, and revealed a bidirectional effect on SnChos inflammaging. IASM significantly suppressed the survival, proliferation, and appropriate differentiation of grafted BMSCs in vivo, all of which impaired cartilage regeneration. Anti-senescence agent ABT-263 was able to partly rescue the cells from the negative effects of SnChos. Conclusions The SnChos and BMSCs interacted with each other at cellular senescence, apoptosis, proliferation, differentiation, and cell functions. This interaction impaired the cartilage repair of MSCs. Anti-senescence agent provided a possible solution for this impairment.

The joint planning of spare parts and maintenance workers in a multiple echelon inventory system with lateral and cross-echelon transshipment can reduce the total cost of the system. However, partial pooling is not extensively considered in the joint optimization problem of maintenance resources. In this paper, the objective is to determine the optimal inventory of spare parts and the number of maintenance workers to minimize the total cost of the system considering partial pooling. First, a greedy heuristic is used to obtain the initial inventory. Then, the cat swarm optimization algorithm is formulated to produce nearly optimal results, which can solve larger instances with a faster computation time. Furthermore, a maintenance system with 4 local warehouses, 3 central warehouses and 1 plant serving 5 machine groups is analyzed, in which each machine consists of 5 key components that can breakdown independently. The results verify the effectiveness of the proposed optimization approach. Finally, the total cost for different resource provision scenarios, failure rates and system parameters are discussed.

Traditional decision trees for fault diagnosis often use an ID3 construction algorithm. For promoting the accuracy and efficiency of decision trees, considering the cluster validity and fault rates, this paper proposes two improved trees, CV-DTs and FR-DTs. This paper mainly has two highlights. The first highlight is to propose a CV-DT which is constructed by an improved ID3 algorithm considering the cluster validity index. A new cluster validity index which can compare the cluster validities of different attributes is proposed to modify the information gain. This method selects the splitting attributes with higher classification credibility and increases the diagnostic accuracy. The second highlight is to propose an FR-DT which is constructed by an improved ID3 algorithm considering the fault rates. This algorithm not only considers the partitioning ability of each attribute, but also considers the isolation priority of faults with higher fault rates. This method decreases the average diagnostic steps and promotes the diagnostic efficiency. Through a simulation case and a real board case, these decision trees are proved to be effective diagnostic tools which have higher accuracies or efficiencies in analog circuit.

Space solar cell components always suffered from the complex and hostile space environment. The reliability of space solar cell components is important to ensure the mission success of space satellites. However, the current research mostly focuses on solar cells' degradation mechanisms. There is less research based on the performance parameters of space solar cell component's degradation to analyze its reliability. Therefore, a reliability analysis method based on the method of modeling the performance degradation of space solar cell components is proposed. By combining general stress-strength interference model and Gamma process, the reliability model of space solar cell components is established. The accelerated degradation test based on the equivalent particle dose is performed to simulate the radiation influence and verify the proposed method. Compared with the displacement damage dose method, the proposed method can further develop the reliability analysis based on performance degradation analysis. Moreover, the cover glass and interconnection are also taken into account together to form a completed component analysis. Through analyzing the cover glass and interconnection experiment results, the cover glass can affect the component reliability; whereas, the interconnection has little influence at the particle radiation condition. Based on the proposed method, the reliability is easier to calculate with the degradation of output power.