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Rice (Oryza sativa L.) stands as the most significantly influential food crop in the developing world, with its total production and yield stability affected by environmental stress. Drought stress impacts about 45% of the world’s rice area, affecting plants at molecular, biochemical, physiological, and phenotypic levels. The conventional breeding method, predominantly employing single pedigree selection, has been widely utilized in breeding numerous drought-tolerant rice varieties since the Green Revolution. With rapid progress in plant molecular biology, hundreds of drought-tolerant QTLs/genes have been identified and tested in rice crops under both indoor and field conditions. Several genes have been introgressed into elite germplasm to develop commercially accepted drought-tolerant varieties, resulting in the development of several drought-tolerant rice varieties through marker-assisted selection and genetically engineered approaches. This review provides up-to-date information on proof-of-concept genes and breeding methods in the molecular breeding era, offering guidance for rice breeders to develop drought-tolerant rice varieties.

Osteoarthritis (OA) is a degenerative disease with a high prevalence in the elderly population, but our understanding of its mechanisms remains incomplete. Analysis of serum exosomal small RNA sequencing data from clinical patients and gene expression data from OA patient serum and cartilage obtained from the GEO database revealed a common dysregulated miRNA, miR-199b-5p. In vitro cell experiments demonstrated that miR-199b-5p inhibits chondrocyte vitality and promotes extracellular matrix degradation. Conversely, inhibition of miR-199b-5p under inflammatory conditions exhibited protective effects against damage. Local viral injection of miR-199b-5p into mice induced a decrease in pain threshold and OA-like changes. In an OA model, inhibition of miR-199b-5p alleviated the pathological progression of OA. Furthermore, bioinformatics analysis and experimental validation identified Gcnt2 and Fzd6 as potential target genes of MiR-199b-5p. Thus, these results indicated that MiR-199b-5p/Gcnt2 and Fzd6 axis might be a novel therapeutic target for the treatment of OA.

Quantification of behavior is critical in diverse applications from neuroscience, veterinary medicine to animal conservation. A common key step for behavioral analysis is first extracting relevant keypoints on animals, known as pose estimation. However, reliable inference of poses currently requires domain knowledge and manual labeling effort to build supervised models. We present SuperAnimal, a method to develop unified foundation models that can be used on over 45 species, without additional manual labels. These models show excellent performance across six pose estimation benchmarks. We demonstrate how to fine-tune the models (if needed) on differently labeled data and provide tooling for unsupervised video adaptation to boost performance and decrease jitter across frames. If fine-tuned, SuperAnimal models are 10–100× more data efficient than prior transfer-learning-based approaches. We illustrate the utility of our models in behavioral classification and kinematic analysis. Collectively, we present a data-efficient solution for animal pose estimation. Quantifying animal behavior is crucial in various fields such as neuroscience and ecology, yet we lack data-efficient methods to perform behavioral quantification. Here, the authors provide new unified models across 45+ species without manual labeling, thus enhancing analysis in behavioral studies. [ABSTRACT FROM AUTHOR]

Ultrasonic detection is currently used in the industry of medium-density fiberboard to detect blister defects. Due to the small detection area of a single sensor, multiple sensors need to be used, which results in high costs. Starting from elastic thin plate vibration theory, this paper builds a vibration dynamic model to detect blisters. The size and depth of the blister area can be established by determining the natural frequency of the thin plate vibration in the blister area. In this model, if the elastic modulus and density are known, the natural frequency of the thin plate vibration at the blister place is directly proportional to the blister depth and inversely proportional to the square of the blister radius. The size and depth of the blister can be determined by measuring the first third-order natural frequency of this area of research. A total of 25 specimens with blister sizes and depths were simulated, and the natural frequencies of the specimens were measured. Subsequently, the detection model was verified by comparing its experimental data with theoretical values. The theoretical value was highly consistent with the measured data. The measured values of the first, second, and third-order natural frequencies were slightly smaller than the theoretical calculated values, with average relative deviations of −1.6%, −1.34%, and −1.03%, respectively. As the order progressed, the deviation exhibited a downward trend, and the third-order natural frequency displayed the smallest deviation and highest accuracy. The proposed vibration dynamic model can detect larger blister areas by measuring the natural frequency, which can overcome the shortcomings of small ultrasonic detection areas in current actual industries. Thus, the practical online blister detection device is expected to be further developed. [ABSTRACT FROM AUTHOR]

Aiming at the poor transient convergence and real-time performance of the horizontal vibration state variables of the high-speed elevator car system, and the low control accuracy and stability, this paper proposes an adaptive control strategy to ensure the transient response of the elevator car system. First, a prescribed preset transient performance function is introduced into the controller design to control the variation range of the state variables and ensure the steady transient performance of the elevator car; Second, representing the information of observation error/control error through algebraic operations, designing an adaptive law based on e-correction, estimating unknown parameters in the elevator car system, and achieving online parameter updates; Then, using neural networks to learn and compensate for unknown dynamics in the elevator car system, and solving the online estimation problem of neural network weights through adaptive laws, so that the tracking error and weight estimation error converge to a tight set near zero; Finally, using MATLAB/SIMULINK to compare and analyze the four control algorithms of passive control, PID control, adaptive control based on gradient descent method and transient response adaptive control proposed in this paper under two different rail excitations: Random excitation and pulse excitation. The simulation results show that the adaptive control strategy proposed in this paper effectively suppresses the horizontal vibration of the elevator car, makes the state variables have faster convergence speed and smaller convergence error, and ensures the stable and transient performance of the elevator car system. [ABSTRACT FROM AUTHOR]

Safety is essential for sustainable aviation fuels (SAFs). However, evaluating SAFs' impacts on aero-engine safety is challenging because it involves multiple space scales and the strongly coupled relationships of aero-engine components. Aiming at addressing this problem, a model-based approach is proposed to establish the relationship between the fuel-level physical properties and engine-level safety parameters. Firstly, a unified modeling criterion is proposed to consider the interrelations of aero-engine components. Under this criterion, aero-engine secondary air system (SAS) components are included in SAF safety assessment, since they have non-neglectable influences on aero-engine safety. Secondly, this paper proposes a surrogate-based iteration strategy to embed the combustor's high-dimensional computational fluid dynamics (CFD) model into the aero-engine flow network model. Then, the proposed model-based safety assessment approach is applied to a Fischer–Tropsch hydro-processed synthesized paraffinic kerosine (F-T SPK) safety assessment case. The effects of fuel flow and blending ratio are considered. The results indicate the necessity to evaluate SAFs' safety at the aero-engine level and consider the influences of SAS components. The proposed model-based approach may provide a preliminary screening before SAFs' certification tests. This convenience may be beneficial for reducing the cost and accelerating SAFs' application. [ABSTRACT FROM AUTHOR]

This paper conducts the analytical investigation on the buckling of cylindrical shells with axially variable elastic modulus subjected to axial compressive load for the first time. First, it proves that the axially distributed elastic modulus can be expressed as the combination of constant and variable component. Then, governing differential equations for buckling analysis are derived and exactly solved by the combined perturbation method and Fourier analysis. Accordingly, the closed analytical solutions for the cylinder with arbitrarily variable elastic modulus are obtained, which reveal the explicit relations among buckling load, shell sizes and elastic modulus functions. Based on the presented analytical formulas, four types of elastic modulus variations for shell material which are uniform, periodic, linear and combined are studied in detail, and the results are also well verified. The derived analytical solutions in this paper can serve as benchmarks for buckling analyses of thin-walled cylinders with elastic modulus variations resulted from design, material manufacturing process, material imperfections and so on. [ABSTRACT FROM AUTHOR]

China is striving to reach a peak in its carbon dioxide emissions by 2030 and achieve carbon neutrality by 2060. The accurate accounting of carbon emissions is important for achieving these dual carbon goals. An extensive literature review and field measurements were conducted to investigate the specific impact of population density on carbon emissions in large integrated healthcare organizations. This research uses VOSviewer to visualize the literature analysis. We determined that the flow of people is a key factor affecting carbon emissions during the operational phase of large-scale comprehensive medical institutions. Through field measurements, the relationship between the density of pedestrian flow and indoor environment measurements was derived, and the incremental equipment operating loads caused by changes in the indoor environment were analyzed. Using the carbon emission factor method advocated by the IPCC, a carbon emission accounting model based on different flow intervals was constructed, and the energy consumption of different equipment was fully considered according to its proportion. The validation results showed that the error between the calculated value and the actual values of the model was 3.07% (less than 5%), which has good validity. The model calculates the direct and indirect carbon emissions in the operational phase based on the population flow perspective, which can provide a reference for the energy-saving design and green operation of large-scale comprehensive medical institutions. The research will continue to focus on the population flow, and the accounting model will be further optimized through machine learning algorithms. [ABSTRACT FROM AUTHOR]

For the problem of the rotor position estimation and control accuracy of permanent magnet synchronous motor (PMSM), this paper proposes a PMSM sensorless based on radial basis function (RBF) neural network optimized Automatic disturbance rejection control (RBF-ADRC) and strong tracking filter (STF) improved square root generalized fifth-order cubature Kalman filter (SGHCKF-STF). The Automatic disturbance rejection control (ADRC) has strong robustness, but there are many parameters and difficult to adjust. Now we use RBF neural network to adjust the parameters in ADRC online so as to improve the robustness and anti-disturbance ability. In order to improve the estimation accuracy of rotor position and speed, the orthogonal triangle (QR) decomposition and STF are introduced on the basis of the generalized fifth-order cubature Kalman filter (GHCKF) to design the SGHCKF-STF algorithm that not only ensure the non-positive nature of the covariance matrix but also improve the ability to cope with sudden changes in state during the filtering process. Experimental results show that the combination of RBF-ADRC and SGHCKF-STF improve the sensorless control effect of the PMSM to some extent. [ABSTRACT FROM AUTHOR]

To effectively suppress the longitudinal vibration of the car under the conditions of high-speed operation and emergency braking, and improve the ride comfort of the car system, this paper proposes an adaptive fuzzy inverse optimal output feedback control strategy. Firstly, the dynamic model of the high-speed elevator system is established and the nonlinear dynamic model is approximated by the fuzzy logic system, and the auxiliary system model is established. Fuzzy state observer is designed to estimate the unmeasurable state. Furthermore, an adaptive inverse optimal output feedback controller based on fuzzy observer is designed by using adaptive backstepping technology and inverse optimal control principle. The stability analysis shows that the proposed adaptive fuzzy inverse optimal output feedback control strategy not only ensures the stability of the car attitude of high-speed elevator but also realizes the inverse optimization of the target cost function. Finally, the acceleration time–frequency response analysis of the two typical stages of high-speed elevator uniform running and emergency braking is carried out, and the numerical results are compared with the linear quadratic controller optimized by stepping quantum genetic algorithm (GA-LQR) and controller based on the state-dependent Ricatti equation (SDRE). The analysis verifies the effectiveness of the controller. [ABSTRACT FROM AUTHOR]

This document is a correction notice for an article titled "Neural Network Adaptive Damping Control Strategy for High Speed Elevator Car System with Transient Performance" published in the International Journal of Structural Stability and Dynamics. The correction addresses errors in equations (1) and (6) of the original article. The authors provide the corrected versions of the equations. The article focuses on a control strategy for elevator car systems and utilizes neural network adaptive damping. The authors are affiliated with the School of Mechanical and Electrical Engineering at Shandong Jianzhu University in China. [Extracted from the article]

Small-scale robots offer significant potential in minimally invasive medical procedures. Due to the nature of soft biological tissues, however, robots are exposed to complex environments with various challenges in locomotion, which is essential to overcome for useful medical tasks. A single mini-robot often provides insufficient force on slippery biological surfaces to carry medical instruments, such as a fluid catheter or an electrical wire. Here, for the first time, a team of millirobots (TrainBot) is reported to generate around two times higher actuating force than a TrainBot unit by forming a convoy to collaboratively carry long and heavy cargos. The feet of each unit are optimized to increase the propulsive force around three times so that it can effectively crawl on slippery biological surfaces. A human-scale permanent magnetic set-up is developed to wirelessly actuate and control the TrainBot to transport heavy and lengthy loads through narrow biological lumens, such as the intestine and the bile duct. The first electrocauterization performed by the TrainBot is demonstrated to relieve a biliary obstruction and open a tunnel for fluid drainage and drug delivery. The developed technology sheds light on the collaborative strategy of small-scale robots for future minimally invasive surgical procedures., (© 2024 The Author(s). Advanced Science published by Wiley‐VCH GmbH.)

Background: Pulmonary sarcomatoid carcinoma (PSC) is a rare, highly malignant type of non-small cell lung cancer (NSCLC) with a poor prognosis. Targeted drugs for MET exon 14 ( MET ex14) skipping mutation can have considerable clinical benefits. This study aimed to predict MET ex14 skipping mutation in PSC patients by whole-tumour texture analysis combined with clinical and conventional contrast-enhanced computed tomography (CECT) features., Methods: This retrospective study included 56 patients with PSC diagnosed by pathology. All patients underwent CECT before surgery or other treatment, and both targeted DNA- and RNA-based next-generation sequencing (NGS) were used to detect MET ex14 skipping mutation status. The patients were divided into two groups: MET ex14 skipping mutation and nonmutation groups. Overall, 1,316 texture features of the whole tumour were extracted. We also collected 12 clinical and 20 conventional CECT features. After dimensionality reduction and selection, predictive models were established by multivariate logistic regression analysis. Models were evaluated using the area under the curve (AUC), and the clinical utility of the model was assessed by decision curve analysis., Results: MET ex14 skipping mutation was detected in 17.9% of PSCs. Mutations were found more frequently in those (I) who had smaller long- or short-axis diameters (P=0.02, P=0.01); (II) who had lower T stages (I, II) (P=0.02); and (III) with pseudocapsular or annular enhancement (P=0.03). The combined model based on the conventional and texture models yielded the best performance in predicting MET ex14 skipping mutation with the highest AUC (0.89). The conventional and texture models also had good performance (AUC =0.83 conventional; =0.88 texture)., Conclusions: Whole-tumour texture analysis combined with clinical and conventional CECT features may serve as a noninvasive tool to predict the MET ex14 skipping mutation status in PSC., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-24-56/coif). Y.W. is an employee of GE Healthcare. The other authors have no conflicts of interest to declare., (2024 Translational Lung Cancer Research. All rights reserved.)

Background: The incidence of gallbladder diseases is as high as 20%, but whether gallbladder diseases contribute to hepatic disorders remains unknown., Methods: Here, we established an animal model of gallbladder dysfunction and assessed the role of a diseased gallbladder in cholestasis-induced hepatic fibrosis (CIHF)., Results: Mice with smooth muscle-specific deletion of Mypt1, the gene encoding the main regulatory subunit of myosin light chain phosphatase (myosin phosphatase target subunit 1 [MYPT1]), had apparent dysfunction of gallbladder motility. This dysfunction was evidenced by abnormal contractile responses, namely, inhibited cholecystokinin 8-mediated contraction and nitric oxide-resistant relaxation. As a consequence, the gallbladder displayed impaired bile filling and biliary tract dilation comparable to the alterations in CIHF. Interestingly, the mutant animals also displayed CIHF features, including necrotic loci by the age of 1 month and subsequently exhibited progressive fibrosis and hyperplastic/dilated bile ducts. This pathological progression was similar to the phenotypes of the animal model with bile duct ligation and patients with CIHF. The characteristic biomarker of CIHF, serum alkaline phosphatase activity, was also elevated in the mice. Moreover, we observed that the myosin phosphatase target subunit 1 protein level was able to be regulated by several reagents, including lipopolysaccharide, exemplifying the risk factors for gallbladder dysfunction and hence CIHF., Conclusions: We propose that gallbladder dysfunction caused by myosin phosphatase target subunit 1 ablation is sufficient to induce CIHF in mice, resulting in impairment of the bile transport system., (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Association for the Study of Liver Diseases.)

Graphite is a revolutionary material, and the development of synthetic graphite could potentially solve the shortage of natural graphite in the future. In this paper, the formation of core-shell-structured synthetic graphite prepared from an anthracite-FeO mixture was systematically investigated by a two-step method. First, heat treatment was performed on a layer of almandine (3FeO·Al 2 O 3 ·3SiO 2 ) particles to obtain a large quantity of uniform-sized glass-phase spheroids. Second, the deashed anthracite was graphitized on the surface of the obtained spheroids to prepare core-shell-structured graphite. Furthermore, the obtained graphite products were systematically characterized by XRD, Raman spectroscopy, SEM-EDS, and TEM. Finally, a model was proposed to illustrate the formation mechanism of the core-shell structure during graphitization of the anthracite-almandine mixture. Under lower temperatures, almandine started to melt into spheroids. Under higher temperatures, the volatile components in the anthracite turned into the gas phase, and the carbon matrix started to bend on the surface of the core material and deposit layer by layer, thus forming the core-shell-structured graphite. The findings could provide theoretical guidance for the synthetic graphite industry and have meaningful implications for the coal chemistry field., Competing Interests: The authors declare no competing financial interest., (© 2024 The Authors. Published by American Chemical Society.)

The architecture of apple trees plays a pivotal role in shaping their growth and fruit-bearing potential, forming the foundation for precision apple management. Traditionally, 2D imaging technologies were employed to delineate the architectural traits of apple trees, but their accuracy was hampered by occlusion and perspective ambiguities. This study aimed to surmount these constraints by devising a 3D geometry-based processing pipeline for apple tree structure segmentation and architectural trait characterization, utilizing point clouds collected by a terrestrial laser scanner (TLS). The pipeline consisted of four modules: (a) data preprocessing module, (b) tree instance segmentation module, (c) tree structure segmentation module, and (d) architectural trait extraction module. The developed pipeline was used to analyze 84 trees of two representative apple cultivars, characterizing architectural traits such as tree height, trunk diameter, branch count, branch diameter, and branch angle. Experimental results indicated that the established pipeline attained an R 2 of 0.92 and 0.83, and a mean absolute error (MAE) of 6.1 cm and 4.71 mm for tree height and trunk diameter at the tree level, respectively. Additionally, at the branch level, it achieved an R 2 of 0.77 and 0.69, and a MAE of 6.86 mm and 7.48° for branch diameter and angle, respectively. The accurate measurement of these architectural traits can enable precision management in high-density apple orchards and bolster phenotyping endeavors in breeding programs. Moreover, bottlenecks of 3D tree characterization in general were comprehensively analyzed to reveal future development., Competing Interests: Competing interests: The authors declare that they have no competing interests., (Copyright © 2024 Tian Qiu et al.)

Background: Pneumonic-type lung adenocarcinoma (P-ADC) is a rare and challenging subtype of primary lung cancer that can be difficult to distinguish from pneumonia based on radiological images. Furthermore, no drugs are currently available that specifically target KRAS G12V., Case Presentation: Here we report a case of P-ADC with typical and informative imaging features throughout the course of the disease, including patchy shadows, high-density lesions with aerated bronchus, diffuse ground-glass opacities, and nodular shadows from computed tomography (CT) scan. The KRAS G12V mutation was detected using Next-generation sequencing (NGS). An individualized Afatinib-based therapeutic schedule was prescribed and achieved sustained response after multiple lines of treatment had failed., Conclusion: Our case highlights the typical and dynamic changes in imaging features of P-ADC and provides an indicative treatment strategy for KRAS G12V-mutated lung adenocarcinoma., (© 2024. The Author(s).)