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In this work, we introduce a collision model specifically tailored for the simulation of inextensible textiles. The model considers friction, contacts, and inextensibility constraints all at the same time without any decoupling. Self-collisions are modeled in a natural way that allows considering the thickness of cloth without introducing unwanted oscillations. The discretization of the equations of motion leads naturally to a sequence of quadratic problems with inequality and equality constraints. In order to solve these problems efficiently, we develop a novel active-set algorithm that takes into account past active constraints to accelerate the resolution of unresolved contacts. We put to a test the developed collision procedure with diverse scenarios involving static and dynamic friction, sharp objects, and complex-topology folding sequences. Finally, we perform an experimental validation of the collision model by comparing simulations with recordings of real textiles as given by a Motion Capture System. The results are very accurate, having errors around 1 cm for DIN A2 textiles (42 x 59.4 cm) even in difficult scenarios involving fast and strong hits with a rigid object. In this work, we present a novel collision model for inextensible textiles and validate it experimentally through a comparison with real textiles as recorded by a Motion Capture System. In the figure we can see four frames comparing the recorded hitting with a stick of a DIN A2 (42 x 59.4 cm) polyester sheet (left) with its inextensible simulation (right); its average error being 1.44 cm. The recordings are obtained by attaching 20 reflective markers of diameter 3 mm and weight of 0.013 g to the real textile and following their trajectory. On the bottom, we show a full plot of the mean absolute error of the position of each marker with respect to its simulation and with yellow lines we highlight the moments in which the object is in contact with the cloth. Notice that the biggest errors appear not during the hits but just after because of aerodynamic effects. The above simulations, with a 7 × 9 mesh, are two times faster than real-time. Our custom active-set solver is three times faster than a standard interior-point method using the same mesh resolution. • We develop a cloth collision model which results in a coupled resolution of friction, inextensibility, and contact forces. • Self-collisions are modeled in a way that allows considering cloth's thickness without introducing unwanted oscillations. • An active-set solver for the system's integration is developed, which can start from any non-necessarily feasible point. • An empirical validation is performed, with scenarios involving high-friction surfaces and strong hits with a stick. [ABSTRACT FROM AUTHOR]

This paper presents the demonstration of underwater thermoacoustic (TA) sound generation using three-dimensional graphene (3D-C). 3D-C is able to interface with water as the immediate acoustic medium, resulting in reduced attenuation across solid packaging encapsulation due to favorable acoustic impedance matching. This is shown using array configurations of 2*2 and 4*4 individual 3D-C elements prepared onto printed circuit boards and secured within a watertight cuboid Delrin container with deionized water. Comparisons of underwater acoustic performance between internal medium of water and air shows significant improvement in measured sound pressure level (SPL) with internal water medium, in contrast with internal air medium where SPL were below noise floor. This demonstration opens up new possibilities of 3D-C for underwater acoustic applications. Simulations are conducted using 3D finite element model generated with COMSOL Multiphysics and validated with experimental results. A revised formulation of transmission voltage response (TVR) specific to TA sound generation is proposed due to the difference in power scaling of TA sound generation and subsequently validated using simulation. [ABSTRACT FROM AUTHOR]

Background: Acute lung injury (ALI) is a serious illness that has few treatment options available. Tribuloside, a natural flavonoid extracted from the Tribulus Terrestris plant in China, is potent in addressing many health issues such as headaches, dizziness, itching, and vitiligo. Objective: This study intends to explore the mechanisms of action of Tribuloside in treating ALI through a combination of network pharmacology and experimental validation. Methods: We obtained the 2D structure and SMILES number of Tribuloside from the PubChem database. We used the SwissTargetPrediction database to identify pharmacological targets. We found 1215 targets linked to ALI by examining the GeneCards database. We used the String database and Cytoscape software to create the "drug or disease-target" network as well as the protein-protein interactions (PPI). Key targets were identified by evaluating associated biological processes and pathway enrichment. A Venny Diagram showed 49 intersection points between Tribuloside and ALI. Molecular docking with AutoDockTools found that Tribuloside had a high affinity for IL6, BCL2, TNF, STAT3, IL1B, and MAPK3, the top 6 targets in the PPI network by Degree values. To test Tribuloside's therapeutic efficacy in ALI, an acute lung damage model in mice was constructed using lipopolysaccharide. Tribuloside treatment reduced inflammatory cell infiltration, decreased fibrotic area, repaired damaged alveoli, and suppressed inflammatory factors IL-6, TNF-α, and IL-1β in the lungs through many pathways and targets. Conclusion: This study reveals that Tribuloside has the potential to treat ALI by targeting various pathways and targets, according to network pharmacology predictions and experimental confirmation. [ABSTRACT FROM AUTHOR]

This article methodically develops an improved self-regulating fuzzy-adaptive Sliding Mode Controller (SMC) that strengthens the disturbance compensation capacity of the nonlinear rotary pendulum systems while effectively attenuating the chattering content and curbing the control energy consumption. The article contributes to augmenting the SMC with online adaptation tools to achieve the said objectives. It employs the conventional Gao's power-rate reaching law as the baseline. The scaling gain and the power rate of the said reaching law are adaptively modulated via a pre-calibrated two-input state-error-driven fuzzy nonlinear function. Additionally, the sign function in the law is also replaced with an odd-symmetric nonlinear fuzzy function to address the hard limits imposed by the former. Finally, the membership functions of the fuzzy function are self-regulated using the Extended-Kalman-Filter to improve the compensator's adaptability in handling the system's rapidly changing control requirements under exogenous disturbances. The aforementioned propositions are verified by performing customized and reliable hardware-in-loop experiments on the Quanser single-link rotary pendulum platform. As compared to baseline SMC law, the proposed control procedure contributes a ∼45.2%, ∼48.5%, and ∼34.8% reduction in position-regulation errors, control energy consumption, and peak overshoots, respectively. The experimental assessment validates the proposed control system's enhanced robustness and chattering-suppression capability. [ABSTRACT FROM AUTHOR]

Background: Abnormal expression of protein tyrosine kinase 6 (PTK6) has been proven to be involved in the development of gynecological tumors. However, its immune-related carcinogenic mechanism in other tumors remains unclear. Objective: The aim of this study was to identify PTK6 as a novel prognostic biomarker in pan-cancer, especially in lung adenocarcinoma (LUAD), which is correlated with immune infiltration, and to clarify its clinicopathological and prognostic significance. Methods: The prognostic value and immune relevance of PTK6 were investigated by using bio-informatics in this study. PTK6 expression was validated in vitro experiments (lung cancer cell lines PC9, NCI-H1975, and HCC827; human normal lung epithelial cells BEAS-2B). Western blot (WB) revealed the PTK6 protein expression in lung cancer cell lines. PTK6 expression was inhibited by Tilfrinib. Colony formation and the Cell Counting Kit-8 (CCK-8) assay were used to detect cell proliferation. The wound healing and trans-well were performed to analyze the cell migration capacity. Then flow cytometry was conducted to evaluate the cell apoptosis. Eventually, the relationship between PTK6 and immune checkpoints was examined. WB was used to estimate the PD-L1 expression at different Tilfrinib doses. Results: PTK6 was an independent predictive factor for LUAD and was substantially expressed in LUAD. Pathological stage was significantly correlated with increased PTK6 expression. In accordance with survival analysis, poor survival rate in LUAD was associated with a high expression level of PTK6. Functional enrichment of the cell cycle and TGF-β signaling pathway was demonstrated by KEGG and GSEA analysis. Moreover, PTK6 expression considerably associated with immune infiltration in LUAD, as determined by immune analysis. Thus, the result of vitro experiments indicated that cell proliferation and migration were inhibited by the elimination of PTK6. Additionally, PTK6 suppression induced cell apoptosis. Obviously, PD-L1 protein expression level up-regulated while PTK6 was suppressed. Conclusion: PTK6 has predictive value for LUAD prognosis, and could up regulated PD-L1. [ABSTRACT FROM AUTHOR]

Most standard controllers for high degrees of freedom (dof) robots are prone to consume large quantity of energy and computational time. Humanoid high dof robots are mostly controlled using model-based controllers due to their better accuracy relatively to other controllers. This paper presents a model-based feed-forward control strategy incorporating a Decoupled Natural Orthogonal Complement (DeNOC) methodology for a wheeled humanoid robot. For a 15 dof humanoid robot with a wheeled base, performance of the proposed feed-forward controller was compared with a traditional feed-forward controller. A steady state error, settling time and energy consumption during a task performance were compared to determine an efficiency of the proposed controller. A simulation study and an experimental validation were used to evaluate results of the performance analysis. [ABSTRACT FROM AUTHOR]

This scientific paper presents the development and validation process of a dynamic model in Simulink used for decision-making regarding the locomotion and driving type of autonomous omnidirectional mobile platforms. Unlike traditional approaches relying on differential equations, this study uses Simulink's block-based diagrams, offering a simpler and efficient development process. Importantly, the dynamic model accounts for friction forces, a critical factor for energy monitoring. The model's validation is conducted experimentally, ensuring its accuracy and reliability. This paper formulates mathematical models for both conventional and Mecanum wheel configurations, facilitating energy-efficient driving strategies. By decomposing resistive forces into inertial and frictional components using the Jacobian matrix, this study accurately simulates electrical current consumption during robot motion. Through fuzzy decision algorithms utilizing parameters such as energy consumption, travel time, precision, and desired maneuverability, this paper proposes a method for determining the optimal locomotion mode for mobile platforms with Mecanum wheels. Overall, this research brings a new contribution to the field of mobile robotics by providing a comprehensive framework for dynamic modeling and it offers the possibility to drive omnidirectional robots in an energy-efficient manner. [ABSTRACT FROM AUTHOR]

Steering torque constitutes the primary motorcycle control input for the lateral dynamics; consequently, estimating it is important. Conventionally, this is done with complete motorcycle models, requiring significant identification effort. The simplified models in the literature only describe the steering torque under specific cases. This work defined a steering assembly model with few parameters to estimate the steering torque analytically for stationary and transient manoeuvres. The model equations followed from existing motorcycle models through simplifying hypotheses; transfer functions describing the roll response and the Lane Change Roll Index (LCRI) were obtained from these equations. Measured steering torque signals from different datasets, including diverse motorcycle classes, were used as the reference for validation. A good agreement resulted between the estimated and measured torques, in the time and speed-acceleration domains and in terms of LCRI. When using the roll as the motorcycle response, manoeuvrability was highest at lower frequencies. The scooter was the most manoeuvrable; the sports and touring motorcycles were the least manoeuvrable at low and high frequencies, respectively. Concerning design parameters, the front-wheel spin inertia and front twist stiffness influenced manoeuvrability the most. The model allows recreating the steering torque signal for new and pre-existing datasets using commonly measured signals; the signal can describe the riding style and the effort required. Few parameters are required, facilitating its use and reducing the computational burden, allowing its use for steering assistance systems. [ABSTRACT FROM AUTHOR]

For solving the problem about heat dissipation of COB LED (Chip on Board Light Emitting Diode), a mathematical model is established based on two-dimensional heat conduction equation which can quickly calculate heat distribution on the surface of COB LED heat sink in this study. In order to facilitate the solution of the model, the finite difference method is used to solve the mathematical model and the alternate direction implicit scheme is chosen as its difference scheme. According to the boundary conditions and initial conditions in the model, the COB LED normal temperature lighting experiment is designed, and the simulation analysis is carried out hased on ANSYS finite element analysis software. The rationality of the mathematical model is verified by comparing the solution results, simulation results and experimental results. The results show that the relative error of the maximum temperature between the solution nsult and the experimental results is about 23.57%, and the temperature variation trend of the two is consistent. The maximum temperature relative error hetween the solution result and simulation results is about 34.84%, and the temperature distribution is close. The rationality and correctness of the mathematical model are proved. [ABSTRACT FROM AUTHOR]

The rehabilitation of existing buildings façades should be based on the improvement in comfort and the decrease of energy consumption. For this purpose, it is necessary to select a retrofitted solution capable of minimizing the heat losses across the building envelope. However, it is not only the retrofitted solution of the wall that influences the amount of heat transported across it, but also the moisture content in the wall under in-service conditions. An experimental prototype was developed to experimentally assess the impact of a wetting period on the energy performance of wall test specimens. The experiment simulated the exposure of the specimens to a rainy period with a continuous record of the heat fluxes across both surfaces of the specimens. Additionally, the validation of the WUFI hygrothermal simulation model, based on the experimental measurements performed, was carried out. Driving rain resulted in an increase of heat losses of around 10%. [ABSTRACT FROM AUTHOR]

The interfacial area between two phases plays a crucial role in the mass transfer rate of gas–liquid processes such as absorption. In this context, the droplet size distribution within the flow field of a droplet-based absorber significantly affects the surface area, thereby influencing the absorption efficiency. This study focuses on developing a computational fluid dynamics (CFD) model to predict the size and distribution of water droplets free-falling in a transparent square tube. This model serves as a digital twin of our experimental setup, enabling a comparative analysis of experimental and computational results. For the accurate measurement of droplet size and distribution, specialized experimental equipment was developed, and a high-speed camera along with Fiji software was used for the capturing and processing of droplet images. At the point of injection and at two different heights, the sizes and distributions of falling droplets were measured using this setup. The interaction between the liquid water droplets and the gas phase within the square tube was modeled using the Eulerian–Lagrangian (E-L) framework in the STAR-CCM+ software. The E-L multiphase CFD model yielded approximations with errors ranging from 11 to 27% for various average mean diameters, including d 10 , d 20 , d 30 , and d 32 , of the liquid droplets at two distinct heights (200 mm and 400 mm) for both nozzle plates. This comprehensive approach provides valuable insights into the dynamics of droplet-based absorption processes. [ABSTRACT FROM AUTHOR]

Substantial amounts of fresh agricultural food products are lost after harvest, during handling, storage, processing, and transport. Drying is a method by which food is kept from spoilage after harvest. In the current study, a simple mathematical modelling is developed for leaf drying to reduce the physical experimentation. The governing differential equation is converted into an algebraic equation using the finite difference implicit technique. A finite difference equation is developed for each node to determine the water content, and all of the nodal equations are solved simultaneously. Experimental investigation was carried out using leaves of tropical amaranth in a fabricated large-scale heat pump dryer (HPD). Drying rate curves are plotted for moisture concentration of leaves at different depths and total moisture removed at any time step. The model is validated with experimental findings. The simulated results are consistent with the experimental data. A reasonable correlation coefficient (R2) of 0.96 is obtained for moisture concentration of leaf at different intervals when comparing experimental and anticipated data (derived from a numerical solution). The moisture concentration calculated using the numerical method assuming the convective mass transfer boundary condition matches the moisture content calculated using the analytical solution assuming the moisture content at the boundary is constant at all times. The coefficient of performance (COP) of a heat pump is found to be 1.75 after a thermodynamic study of the heat pump cycle in the experiment. A psychometric study is also performed, and the dehumidification efficiency of 22.9% is obtained and compared to the literature. The average specific moisture extraction rate (SMER) for experimental data is 0.038542 kg/kWh, whilst it is 0.051275 kg/kWh for simulated data. The new numerical modelling developed in this study can be used to simulate the experimental data that can be obtained from a HPD for drying different kinds of leaves without conducting physical experimentation. The model's accuracy is verified by an uncertainty analysis. [ABSTRACT FROM AUTHOR]

At present, direct carbon fuel cells constitute an emerging energy technology that electrochemically converts solid carbon to electricity with high efficiency. The recent trend of DCFCs fueled with biochar from biomass carbonization as green fuel has reinforced the environmental benefits of DCFCs as a clean and sustainable technology. However, there remain new challenges related to some complex unknown kinetic parameters, X = (α a , α c , σ g , i 0 , a , i 0 , c , i l O 2 , i l CO 2 , c , i l CO 2 , a , i l CO ) , of the electrochemical conversion of biochar in DCFCs and there is a need for intelligent techniques for prediction and optimization, refering to the available experimental data. The differential evolution (DE) algorithm, which ranked as one of the top performers in optimization competitions with competitive accuracy and convergence speed, was used here for providing the optimized values of these parameters by minimizing the root mean squared errors (RMSE). The proposed technique was then applied to DCFCs fueled by activated pure carbon (APC) using CO2 and CO/CO2 electrochemical models with RMSE around 10−2 and 10−3, respectively. Then, the CO/CO2 model was applied to a DCFC fueled with almond shell biochar (ASB), which displayed a slight increase in RMSE (of the order of 10−2) due to the complex porous structure of ASB and the content of additional chemical elements that affect the electrochemistry of the DCFC and are not considered in the model. [ABSTRACT FROM AUTHOR]

Treating kidney diseases from the perspective of spleen is an important clinical method in traditional Chinese medicine (TCM) for anti-renal fibrosis (RF). Si-jun-zi decoction (SJZD), a classic formula for qi-invigorating and spleen-invigorating, has been reported to alleviate RF. This study aims to investigate the potential mechanism by which SJZD attenuates RF. The results demonstrated notable improvements in renal function levels, inflammation and fibrosis indices in UUO-mice following SJZD intervention. The main active ingredients identified were Quercetin, Kaempferol, Naringenin and 7-Methoxy-2-methyl isoflavone. Furthermore, STAT3, MAPK3, MYC were confirmed as key targets. Additionally, GO enrichment analysis demonstrated that SJZD delayed RF primarily by regulating oxidative stress and other biological mechanisms. KEGG enrichment analysis revealed the involvement of pathways such as Lipid and atherosclerosis signaling pathway, MAPK signaling pathway and other pathways in the reno-protective effects of SJZD. The molecular docking results revealed that the active ingredients of SJZD were well-bound and stable to the core targets. The experiments results revealed that Quercetin, Kaempferol, and Naringenin not only improved the morphology of TGF-β-induced HK-2 cells but also reversed the expression of α-SMA, COL1A1 and MAPK, thereby delaying the progression of RF. The anti-RF effects of SJZD were exerted through multi-components, multi-targets and multi-pathways.

The Organic Rankine Cycle (ORC) plays a pivotal role in the domain of renewable energy, adeptly harnessing thermal energy from sources such as solar and geothermal to generate electrical power. Central to this system is the scroll expander, whose operational efficacy directly influences the ORC's overall efficiency. This study initiates with a detailed numerical analysis of the impact of various operational parameters on both the steady and transient output performance of the scroll expander. Following this, a sophisticated performance prediction model is developed employing the response surface methodology. The model boasts high coefficients of determination, R2,values of 0.9967 and 0.9916, respectively, underscoring its superior predictive accuracy. Further, this model delves into the complex interactions among operational parameters and their consequent effects on the expander's performance. Validation of this predictive model is achieved through rigorous testing on an experimental platform designed for the ORC low-temperature waste heat power generation system. The discrepancies between predicted and actual performance measurements fall within a commendable margin of 15 %, affirming the model's robustness in forecasting scroll expander performance. The culmination of this research furnishes a novel and efficacious optimization strategy, establishing a robust theoretical foundation and offering fresh insights for the enhancement and prediction of scroll expander performance. This not only underscores the innovation of the approach but also its practical applicability in advancing the efficiency of renewable energy systems.

Insulin resistance (IR) is the main cause of type 2 diabetes mellitus (T2DM). The specific targets and underlying mechanisms responsible for the ameliorative effects of the stilbenoid compounds found in fenugreek seeds for ameliorating IR require further study. Here, we were predicted by using the network pharmacology prediction, molecular docking and molecular dynamics simulation approach the targets in common and the potential mechanismsof three stilbenoid compounds (rhaponticin, desoxyrhaponticin, and rhapontigenin) in relation to T2DM and IR. The results showed that the compounds may improve IR through the phosphatidylinositol 3-kinase/protein kinase B (PI3K/AKT) signaling pathway. Molecular docking studies revealed that they exhibit high binding affinity with the structural domains of peroxisome proliferator-activated receptor gamma (PPARG), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), PI3K, and AKT. These results suggest that PPARG and GAPDH may be the potential targets for these three compounds in the treatment of T2DM.Subsequently, experiments using the zebrafish T2DM model showed that the stilbenoid compounds had varying degrees of efficacy in improving IR through the PI3K/AKT/mTOR signaling pathway, and rhaponticin had the most promising effects. The findings implicate a potential mechanism of action for the three stilbenoid compounds in enhancing insulin resistance (IR) through modulation of the PI3K/AKT/mTOR pathway.

Objective: Based on network pharmacology and experimental validation, this study aimed to screen the potential targets of Liuwei Dihuang decoction (LW) against mild cognitive impairment (MCI). Methods: Based on network pharmacology, this study preliminarily explored the targets and molecular mechanisms of LW in the treatment of MCI. The results showed that the mechanism of action of LW against MCI may be related to the cAMP pathway. Then, an aging cell and animal model was established to further verify its molecular mechanism. Results: A total of 23 active ingredients were identified in LW. In addition, through network pharmacological analysis, we found 22 anti-MCI active ingredients in LW, of which alisol B had the most significant effect, and predicted the potential mechanism pathway by which LW may improve MCI through the cAMP signaling pathway. Further in vivo and in vitro experiments confirmed that LW can alleviate cognitive dysfunction in aging mice and reduce D-galactose-induced senescent cells, which may be through activation of the cAMP/PKA/CREB signaling pathway. Conclusion: This study found that the traditional Chinese medicine formula LW may play a role in improving MCI by regulating the cAMP/PKA/CREB signaling pathway, which provides a reference for further clinical research on the anti-MCI effect of LW and its molecular mechanism.

Abstract Background Rheumatoid arthritis (RA) is a prevalent autoimmune disease marked by chronic synovitis as well as cartilage and bone destruction. Halofuginone hydrobromide (HF), a bioactive compound derived from the Chinese herbal plant Dichroa febrifuga Lour., has demonstrated substantial anti-arthritic effects in RA. Nevertheless, the molecular mechanisms responsible for the anti-RA effects of HF remain unclear. Methods This study employed a combination of network pharmacology, molecular docking, and experimental validation to investigate potential targets of HF in RA. Results Network pharmacology analyses identified 109 differentially expressed genes (DEGs) resulting from HF treatment in RA. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses unveiled a robust association between these DEGs and the IL-17 signaling pathway. Subsequently, a protein-protein interaction (PPI) network analysis revealed 10 core DEGs, that is, EGFR, MMP9, TLR4, ESR1, MMP2, PPARG, MAPK1, JAK2, STAT1, and MAPK8. Among them, MMP9 displayed the greatest binding energy for HF. In an in vitro assay, HF significantly inhibited the activity of inflammatory macrophages, and regulated the IL-17 signaling pathway by decreasing the levels of IL-17 C, p-NF-κB, and MMP9. Conclusion In summary, these findings suggest that HF has the potential to inhibit the activation of inflammatory macrophages through its regulation of the IL-17 signaling pathway, underscoring its potential in the suppression of immune-mediated inflammation in RA.

To accelerate the practicality of electromagnetic railguns, it is necessary to use a combination of three-dimensional numerical simulation and experiments to study the mechanism of bore damage. In this paper, a three-dimensional numerical model of the augmented railgun with four parallel unconventional rails is introduced to simulate the internal ballistic process and realize the multi-physics field coupling calculation of the rail gun, and a test experiment of a medium-caliber electromagnetic launcher powered by pulse formation network (PFN) is carried out. Various test methods such as spectrometer, fiber grating and high-speed camera are used to test several parameters such as muzzle initial velocity, transient magnetic field strength and stress-strain of rail. Combining the simulation results and experimental data, the damage condition of the contact surface is analyzed.

Abstract Structural resolution of protein interactions enables mechanistic and functional studies as well as interpretation of disease variants. However, structural data is still missing for most protein interactions because we lack computational and experimental tools at scale. This is particularly true for interactions mediated by short linear motifs occurring in disordered regions of proteins. We find that AlphaFold-Multimer predicts with high sensitivity but limited specificity structures of domain-motif interactions when using small protein fragments as input. Sensitivity decreased substantially when using long protein fragments or full length proteins. We delineated a protein fragmentation strategy particularly suited for the prediction of domain-motif interfaces and applied it to interactions between human proteins associated with neurodevelopmental disorders. This enabled the prediction of highly confident and likely disease-related novel interfaces, which we further experimentally corroborated for FBXO23-STX1B, STX1B-VAMP2, ESRRG-PSMC5, PEX3-PEX19, PEX3-PEX16, and SNRPB-GIGYF1 providing novel molecular insights for diverse biological processes. Our work highlights exciting perspectives, but also reveals clear limitations and the need for future developments to maximize the power of Alphafold-Multimer for interface predictions.

Abstract Bushen Tiaoxue Granules (BTG) is an empirical Chinese herbal formula that has been used for the treatment of subfertility. The protective effect of BTG on controlled ovarian hyperstimulation (COH)-induced impaired endometrial receptivity has been reported in our previous study. This study aims to explore the mechanisms of BTG on ameliorating abnormal morphology of endometrium based on network pharmacology. Active compounds of BTG were identified via the traditional Chinese medicine systems pharmacology and UPLC-MS technology. The SwissTargetPrediction platform and HERB database were used to screen out the putative targets of BTG. Potential targets of endometrial dysfunction caused by COH were obtained from three GEO databases. Through the STRING database, the protein–protein interaction was carried out according to the cross-common targets of diseases and drugs. GO terms and KEGG pathways enrichment analyses were conducted via the Metascape database. AutoDock Vina was used for docking validation of the affinity between active compounds and potential targets. Finally, in vivo experiments were used to verify the potential mechanisms derived from network pharmacology study. A total of 141 effective ingredients were obtained from TCMSP and nine of which were verified in UPLC-MS. Six genes were selected through the intersection of 534 disease related genes and 165 drug potential targets. Enrichment analyses showed that BTG might reverse endometrial dysfunction by regulating adherens junction and arachidonic acid metabolism. Hematoxylin–eosin staining revealed that BTG ameliorated the loose and edematous status of endometrial epithelium caused by COH. The protein expression of FOXO1A, β-Catenin and COX-2 was decreased in the COH group, and was up-regulated by BTG. BTG significantly alleviates the edema of endometrial epithelium caused by COH. The mechanisms may be related to adheren junctions and activation of arachidonic acid metabolism. The potential active compounds quercetin, taxifolin, kaempferol, eriodictyol, and isorhamnetin identified from the BTG exhibit marginal cytotoxicity. Both high and low concentrations of kaempferol, eriodictyol, and taxifolin are capable of effectively ameliorating impaired hESC cellular activity.

In situ groundwater remediation technique is a commonly adopted method for the treatment of contaminated groundwater and the porous media associated with it. Engineered Injection and Extraction (EIE) has evolved as an improved methodology for in situ remediation, where sequential injection and extraction of clean water around the treatment area enhances the spreading of treatment reagents by inducing additional flow fields. Conventional EIE studies were based on flow fields in two dimensions. There are only limited experimental and theoretical studies exploring the potential of inducing a three-dimensional flow field using EIE. The present study experimentally and numerically evaluates the effect of a three-dimensional flow field induced by partially screened wells. EIE experiments were conducted on a laboratory-scale aquifer model with laterite soil as the porous medium. Tracer transport in porous medium was studied by measuring the concentration at various observation points and enhanced dilution was observed when EIE was employed with partially screened wells. Experimental observations were also used to calibrate and validate the numerical model developed using Visual MODFLOW Flex. Enhancement in spreading was quantified in terms of concentration mass attenuation and maximum mass attenuation was observed when EIE was employed with partially screened wells. HIGHLIGHTS Experimental investigation of engineered injection extraction (EIE) in three-dimension is carried out in this study using a laboratory-scale aquifer model.; Study experimentally proved the improvement in spreading when EIE is employed with partially screened wells over EIE with fully screened wells.; Calibrated and validated numerical model created using Visual MODFLOW Flex using experimental observations.;

A tracking stability control problem for the vertical electric stabilization system of moving tank based on adaptive robust servo control is addressed. This paper mainly focuses on two types of possibly fast time-varying but bounded uncertainty within the vertical electric stabilization system: model parameter uncertainty and uncertain nonlinearity. First, the vertical electric stabilization system is constructed as an uncertain nonlinear dynamic system that can reflect the practical mechanics transfer process of the system. Second, the dynamical equation in the form of state space is established by designing the angular tracking error. Third, the comprehensive parameter of system uncertainty is designed to estimate the most conservative effects of uncertainty. Finally, an adaptive robust servo control which can effectively handle the combined effects of complex nonlinearity and uncertainty is proposed. The feasibility of the proposed control strategy under the practical physical condition is validated through the tests on the experimental platform. This paper pioneers the introduction of the internal nonlinearity and uncertainty of the vertical electric stabilization system into the settlement of the tracking stability control problem, and validates the advanced servo control strategy through experiment for the first time.

In this study, the effectiveness of encrypted control systems in detecting attacks is experimentally demonstrated using a networked control system testbed that allows for man-in-the-middle (MITM) attacks. The developed testbed is a networked position control system for an industrial-use linear stage. Generally, an attacker can reroute and modify packet data via a wireless router, harnessing the address-resolution-protocol-spoofing technique, which allows for the execution of MITM attacks, such as falsification and replay attacks. The deployed MITM-attack-detection method is grounded on a threshold-based method that monitors control inputs. The demonstration examines falsification- and replay-attack scenarios across unencrypted, static-key, and key-updatable encrypted control systems. The results confirm that encrypted control systems are both effective and apt in detecting attacks in real time. Furthermore, the potential for developing alternative attack-detection schemes based on variations in processing times is discussed.

Tengfei Chen,1,* Sihan Li,1,* Dongyin Lian,1 Qin Hu,2 Hongping Hou,1 Delian Niu,1 Han Li,1 Ling Song,1 Yunhang Gao,1 Ying Chen,1 Xiaoru Hu,3 Jianrong Li,1 Zuguang Ye,1 Bo Peng,1 Guangping Zhang1 1Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, People’s Republic of China; 2College of Life Sciences and Bio-Engineering, Beijing University of Technology, Beijing, People’s Republic of China; 3National Institute for Food and Drug Control, Beijing, People’s Republic of China*These authors contributed equally to this workCorrespondence: Bo Peng; Guangping Zhang, Tel +8610 64056575, Email bpeng@icmm.ac.cn; gpzhang@icmm.ac.cnPurpose: This study aimed to investigate the main pharmacological action and underlying mechanisms of Jin Gu Lian Capsule (JGL) against rheumatoid arthritis (RA) based on network pharmacology and experimental verification.Methods: Network pharmacology approaches were performed to explore the core active compounds of JGL, key therapeutic targets, and signaling pathways. Molecular docking was used to predict the binding affinity of compounds with targets. In vivo experiments were undertaken to validate the findings from network analysis.Results: A total of 52 targets were identified as candidate JGL targets for RA. Sixteen ingredients were identified as the core active compounds, including, quercetin, myricetin, salidroside, etc. Interleukin-1 beta (IL1B), transcription factor AP-1 (JUN), growth-regulated alpha protein (CXCL1), C-X-C motif chemokine (CXCL)3, CXCL2, signal transducer and activator of transcription 1 (STAT1), prostaglandin G/H synthase 2 (PTGS2), matrix metalloproteinase (MMP)1, inhibitor of nuclear factor kappa-B kinase subunit beta (IKBKB) and transcription factor p65 (RELA) were obtained as the key therapeutic targets. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis showed that the efficacy of JGL was functionally involved in regulating immune-mediated inflammation, in which IL-17/NF-κB signaling was recommended as one of the main pathways. Molecular docking suggested that the core active compounds bound strongly to their respective targets. Experimentally, JGL treatment mitigated inflammation, showed analgesic activity, and ameliorated collagen-induced arthritis. Enzyme-linked immunosorbent assay showed that JGL effectively reduced the serum levels of cytokines, chemokines, and MMPs. Immunohistochemistry staining showed that JGL markedly reduced the expression of the targets in IL-17/NF-κB pathway including IL-17A, IL-17RA, NF-κB p65, C-X-C motif ligand 2, MMP1 and MMP13.Conclusion: This investigation provided evidence that JGL may alleviate RA symptoms by partially inhibiting the immune-mediated inflammation via IL-17/NF-κB pathway. Keywords: rheumatoid arthritis, Jin Gu Lian capsules, network pharmacology, experimental validation, immune-mediated inflammation

Wave energy has the potential to provide a sustainable solution for global energy demands, particularly in coastal regions. This study explores the use of reinforcement learning (RL), specifically the Q-learning algorithm, to optimise the energy extraction capabilities of a wave energy converter (WEC) using a single-body point absorber with resistive control. Experimental validation demonstrated that Q-learning effectively optimises the power take-off (PTO) damping coefficient, leading to an energy output that closely aligns with theoretical predictions. The stability observed after approximately 40 episodes highlights the capability of Q-learning for real-time optimisation, even under irregular wave conditions. The results also showed an improvement in efficiency of 12% for the theoretical case and 11.3% for the experimental case from the initial to the optimised state, underscoring the effectiveness of the RL strategy. The simplicity of the resistive control strategy makes it a viable solution for practical engineering applications, reducing the complexity and cost of deployment. This study provides a significant step towards bridging the gap between the theoretical modelling and experimental implementation of RL-based WEC systems, contributing to the advancement of sustainable ocean energy technologies.

Hyperthermia induces slight temperature increase of 4–8 °C inside the tumor, making it more responsive to radiation and drugs, thereby improving the outcome of the oncological treatment. To verify the level of heat in the tumor and to avoid damage of the healthy tissue, methods for non-invasive temperature monitoring are needed. Temperature estimation by means of microwave imaging is of great interest among the scientific community. In this paper, we present the results of experiments based on ultra-wideband (UWB) M-sequence technology. Our temperature estimation approach uses temperature dependency of tissue dielectric properties and relation of UWB images to the reflection coefficient on the boundary between tissue types. The realistic measurement setup for neck cancer hyperthermia considers three antenna arrangements. Data are processed with Delay and Sum beamforming and Truncated Singular Value Decomposition. Two types of experiments are presented in this paper. In the first experiment, relative permittivity of subsequently replaced tumor mimicking material is estimated, and in the second experiment, real temperature change in the tumor imitate is monitored. The results showed that the presented approach allows for qualitative as well as quantitative permittivity and temperature estimation. The frequency range for temperature estimation, preferable antenna configurations, and limitations of the method are indicated.

Background: Rheumatoid arthritis (RA) is a prevalent autoimmune disease marked by chronic synovitis as well as cartilage and bone destruction. Halofuginone hydrobromide (HF), a bioactive compound derived from the Chinese herbal plant Dichroa febrifuga Lour., has demonstrated substantial anti-arthritic effects in RA. Nevertheless, the molecular mechanisms responsible for the anti-RA effects of HF remain unclear. Methods: This study employed a combination of network pharmacology, molecular docking, and experimental validation to investigate potential targets of HF in RA. Results: Network pharmacology analyses identified 109 differentially expressed genes (DEGs) resulting from HF treatment in RA. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses unveiled a robust association between these DEGs and the IL-17 signaling pathway. Subsequently, a protein-protein interaction (PPI) network analysis revealed 10 core DEGs, that is, EGFR, MMP9, TLR4, ESR1, MMP2, PPARG, MAPK1, JAK2, STAT1, and MAPK8. Among them, MMP9 displayed the greatest binding energy for HF. In an in vitro assay, HF significantly inhibited the activity of inflammatory macrophages, and regulated the IL-17 signaling pathway by decreasing the levels of IL-17 C, p-NF-κB, and MMP9. Conclusion: In summary, these findings suggest that HF has the potential to inhibit the activation of inflammatory macrophages through its regulation of the IL-17 signaling pathway, underscoring its potential in the suppression of immune-mediated inflammation in RA. [ABSTRACT FROM AUTHOR]

This study presents an integration of the level set-based two-material topology optimization method and the additive manufacturing technique for the design and fabrication of continuous carbon fiber (CCF)-reinforced composite structures. Firstly, optimal configurations of the resin material and fiber reinforcement are obtained to maximize the structural stiffness under desired volume constraints using the two-material topological optimization. After that, the level set-based cutting mesh method and triangulation scheme are employed to interpret these topological designs into stereolithography (STL) models with clear structural boundaries for the manufacturing. A customized pre-processing strategy is used to accurately determine the fiber placement regions from the optimal designs. Topological results are then fabricated using the CCF-based 3D printing method with prepreg carbon fibers. Subsequently, the performance of printed CCF-reinforced composite structures is investigated, using different resin materials: polylactic acid (PLA) and polyamide 12 with 10% carbon fiber (PA12_10CF). Experimental results indicate a significant increase in stiffness and strength of composite structures with fiber reinforcements for all resin materials, with an increase of 315% for PLA and 234% for PA12_10CF. Additionally, the CCF-reinforced composite structures made of PA12_10CF exhibit superior stiffness compared to those made of PLA with a double increment. The microstructural characteristics of damaged regions are examined using scanning electron microscope (SEM) images, which provide valuable insights into the behavior of resin and fiber materials. [ABSTRACT FROM AUTHOR]

Hydroxyapatite and β-tricalcium phosphate have been clinically applied as artificial bone materials due to their high biocompatibility. The development of artificial bones requires the verification of safety and efficacy through animal experiments; however, from the viewpoint of animal welfare, it is necessary to reduce the number of animal experiments. In this study, we utilized machine learning to construct a model that estimates the bone-forming ability of bioceramics from material fabrication conditions, material properties, and in vivo experimental conditions. We succeeded in constructing two models: 'Model 1′, which predicts material properties from their fabrication conditions, and 'Model 2′, which predicts the bone-formation rate from material properties and in vivo experimental conditions. The inclusion of full width at half maximum (FWHM) in the feature of Model 2 showed an improvement in accuracy. Furthermore, the results of the feature importance showed that the FWHMs were the most important. By an inverse analysis of the two models, we proposed candidates for material fabrication conditions to achieve target values of the bone-formation rate. Under the proposed conditions, the material properties of the fabricated material were consistent with the estimated material properties. Furthermore, a comparison between bone-formation rates after 12 weeks of implantation in the porcine tibia and the estimated bone-formation rate. This result showed that the actual bone-formation rates existed within the error range of the estimated bone-formation rates, indicating that machine learning consistently predicts the results of animal experiments using material fabrication conditions. We believe that these findings will lead to the establishment of alternative animal experiments to replace animal experiments in the development of artificial bones. [ABSTRACT FROM AUTHOR]

Chaiqin Qingning Capsule (CQQNC), a traditional Chinese patent medicine, can effectively shorten the duration of fever and significantly improve fever symptoms. However, the mechanism of its antipyretic effect needs to be further elucidated. Therefore, we aimed to investigate the molecular mechanism of CQQNC in the treatment of fever. We used the network pharmacology method to analyze the mechanism of action of CQQNC in the treatment of fever and validated our study primarily by molecular docking. Finally, the predictive results were verified by IL‐1β‐induced bEnd.3 cells. The results showed that quercetin, kaempferol, cubebin, chenodeoxycholic acid, isorhamnetin, bilirubin, cholic acid, and baicalin were the major components of CQQNC against fever. A total of 381 common targets have been crossed by CQQNC for the treatment of fever. Furthermore, we found that CQQNC targets several deregulated genes in fever such as AKT1, COX2, AVP, cAMP, IL6, IL1B, TNF, mPGES1, and PI3K, biological functions such as endopeptidase, cytokine receptor binding, and phosphatase activity, and signaling pathways such as the PI3K‐Akt pathway and the AGE‐RAGE signaling pathway in diabetic complications. The docking study revealed that the core components of CQQNC both had high affinity for hub targets, especially the targets of COX‐2, cAMP, mPGES1, and PI3K proteins. To further investigate the mechanism of CQQNC, an Elisa assay and Western blot detection were performed as part of an in vitro study. Elisa's result showed that CQQNC can significantly decrease the expression levels of cPLA2, sPLA2, PGE2, cAMP, and 15‐PGDH after stimulating IL‐1β to bEnd.3 cells in a dose‐dependent manner (p <.01, p <.001, p <.0001). In addition, detection of the PGE2/ COX /cMAP pathway via immunoblotting showed that CQQNC can significantly downregulate the protein expression of COX‐1, COX‐2, EP3, cAMP, and mPGES1 in bEnd.3 (p <.0001, p <.001, p <.01). In conclusion, our study confirmed that the antipyretic mechanism of CQQNC affects the synthesis and secretion processes of PGE2 via the PGE2/ COX/cAMP pathway, providing insight into the antipyretic mechanism of CQQNC in clinical application. [ABSTRACT FROM AUTHOR]

Structural resolution of protein interactions enables mechanistic and functional studies as well as interpretation of disease variants. However, structural data is still missing for most protein interactions because we lack computational and experimental tools at scale. This is particularly true for interactions mediated by short linear motifs occurring in disordered regions of proteins. We find that AlphaFold-Multimer predicts with high sensitivity but limited specificity structures of domain-motif interactions when using small protein fragments as input. Sensitivity decreased substantially when using long protein fragments or full length proteins. We delineated a protein fragmentation strategy particularly suited for the prediction of domain-motif interfaces and applied it to interactions between human proteins associated with neurodevelopmental disorders. This enabled the prediction of highly confident and likely disease-related novel interfaces, which we further experimentally corroborated for FBXO23-STX1B, STX1B-VAMP2, ESRRG-PSMC5, PEX3-PEX19, PEX3-PEX16, and SNRPB-GIGYF1 providing novel molecular insights for diverse biological processes. Our work highlights exciting perspectives, but also reveals clear limitations and the need for future developments to maximize the power of Alphafold-Multimer for interface predictions. Synopsis: Based on thorough benchmarking of AlphaFold-Multimer a strategy for structure prediction was developed and applied to 62 protein interactions linked to neurological disease. Six novel protein interfaces were further experimentally corroborated. AlphaFold-Multimer (AF) largely fails to predict structures of interacting proteins involving short linear motifs when using full length sequences. A prediction strategy was developed based on protein fragmentation, which boosts AF sensitivity at costs of specificity. Application of this strategy to 62 protein interactions linked to neurological disease resulted in 18 correct or likely correct structural models. Six novel protein interfaces were further supported by experiments. Based on thorough benchmarking of AlphaFold-Multimer a strategy for structure prediction was developed and applied to 62 protein interactions linked to neurological disease. Six novel protein interfaces were further experimentally corroborated. [ABSTRACT FROM AUTHOR]

Far-field blast loading has been studied extensively for decades. Close-in, confined, and semi-confined detonations less so, partly because it is difficult to obtain good experimental data. The increase in computational power in recent years has made it possible to conduct studies of this kind numerically, but the results of such simulations ultimately depend on experimental validation and verification. This work thus aims at using reliable experiments to validate and verify numerical models developed to represent blast loading in general. Test rigs consisting of massive steel cylinders with pressure sensors were used to measure the pressure profiles of semi-confined detonations with different charge sizes. The experimental data set was then used to assess numerical models appropriate for simulating blast loading. In general, the numerical results were in excellent agreement with the experimental data, in both qualitative and quantitative terms. These results may in turn be used to analyse structures exposed to internal blast loads, which constitutes the next phase of this research project. [ABSTRACT FROM AUTHOR]

Bushen Tiaoxue Granules (BTG) is an empirical Chinese herbal formula that has been used for the treatment of subfertility. The protective effect of BTG on controlled ovarian hyperstimulation (COH)-induced impaired endometrial receptivity has been reported in our previous study. This study aims to explore the mechanisms of BTG on ameliorating abnormal morphology of endometrium based on network pharmacology. Active compounds of BTG were identified via the traditional Chinese medicine systems pharmacology and UPLC-MS technology. The SwissTargetPrediction platform and HERB database were used to screen out the putative targets of BTG. Potential targets of endometrial dysfunction caused by COH were obtained from three GEO databases. Through the STRING database, the protein–protein interaction was carried out according to the cross-common targets of diseases and drugs. GO terms and KEGG pathways enrichment analyses were conducted via the Metascape database. AutoDock Vina was used for docking validation of the affinity between active compounds and potential targets. Finally, in vivo experiments were used to verify the potential mechanisms derived from network pharmacology study. A total of 141 effective ingredients were obtained from TCMSP and nine of which were verified in UPLC-MS. Six genes were selected through the intersection of 534 disease related genes and 165 drug potential targets. Enrichment analyses showed that BTG might reverse endometrial dysfunction by regulating adherens junction and arachidonic acid metabolism. Hematoxylin–eosin staining revealed that BTG ameliorated the loose and edematous status of endometrial epithelium caused by COH. The protein expression of FOXO1A, β-Catenin and COX-2 was decreased in the COH group, and was up-regulated by BTG. BTG significantly alleviates the edema of endometrial epithelium caused by COH. The mechanisms may be related to adheren junctions and activation of arachidonic acid metabolism. The potential active compounds quercetin, taxifolin, kaempferol, eriodictyol, and isorhamnetin identified from the BTG exhibit marginal cytotoxicity. Both high and low concentrations of kaempferol, eriodictyol, and taxifolin are capable of effectively ameliorating impaired hESC cellular activity. [ABSTRACT FROM AUTHOR]

The cold-start of proton exchange membrane fuel cell (PEMFC) has been one of the leading technical challenges for fuel cell vehicle commercialization. During the cold start process, a new control-oriented modelling methodology of a water-cooled PEMFC stack system was present. The voltage and temperature change throughout the stack may be forecast using the model technique. Then the model was validated in a 5 Kw, 20 cells, water-cooled stack at room and subzero temperatures. The result shows that the model accuracy can capture the stationary and transient states of the fuel cell stack well. For the cold start of PEMFCs in automotive applications, the suggested model may be utilized to investigate real-time state estimates and model-based control approaches. • A model is developed by the control volume and thermal resistance network method. • The cold start experiment is conducted to verify the time and space distribution. • The proposed model can be used to study the real-time cold start control strategy. [ABSTRACT FROM AUTHOR]

This work uses an experimentally validated mathematical model to maximize alkaline membrane fuel cell (AMFC) stacks net power output. Temperature distribution, efficiency, polarization, and power output curves are obtained. Fundamental optimization opportunities exist for the internal and external structure, which led to a two-way optimized AMFC stack for maximized net power. After system optimization, a parametric analysis was carried out for electrolyte KOH mass fraction, stoichiometric ratios and total fuel cell stack size (volume). KOH content was shown to lead to a third optimum, i.e., 40 wt %. The three-way optimized AMFC stack (ξ s = 1.37 × 10 − 3 , y = 40 wt% KOH) opt was shown to be independent of the stoichiometric ratio and stack size variation, but (ξ y / ξ x = ξ z / ξ x) o p t was affected by total stack volume (or size). In fact, it was found that the three-way maximized dimensionless AMFC stack net power output rises as the stack volume rises in a path that is well correlated by W ˜ n e t , m m m × 10 − 3 = 36.266 V ˜ T 0.74 , which is similar to the allometric law of nature that correlates basal metabolic rate (BMR, W) and body mass (m b , kg) for living beings, i.e., B M R ∼ m b 0.74 , that could be understood as an indication that inanimate and animate systems follow the same evolution laws. • Alkaline membrane fuel cell (AMFC) stacks were 3-way optimized numerically. • The AMFC model utilized in this work was experimentally validated previously. • A parametric analysis was carried out to investigate maxima robustness. • General mathematical correlations were obtained for AMFC stack optimal design. • The results suggest that inanimate and animate systems evolve similarly. [ABSTRACT FROM AUTHOR]

• A segmented beam model with a moving interface is proposed to describe some specific engineering phenomena. • The WKB-recursive method is put forward to obtain the dynamic response efficiently. • The reliability of this simulation procedure is verified by the experiment of a clamped-free pipe. This research aims to seek a suitable way for analyzing the time-varying characteristics of some engineering phenomena such as the fuel consumption of flying rockets, the movement process of control rods used to regulate the reaction rate in nuclear reactors, etc. To address this problem, a simulated procedure containing modeling and response solving is proposed. A common variable cross-section pipeline with time-varying mass is designed as a practical time-varying system. A simplified segmented beam model with a moving interface is proposed to simulate the pipe's time-varying behavior. Then the Wentzel-Kramers-Brillouin (WKB)-recursive method is proposed to solve this time-varying problem. A two-segmented beam example is used to verify its computability. The computational efficiency is greatly improved in comparison with the conventional numerical integration methods. To validate this proposed procedure, numerical simulation is carried out and an experiment is specially designed and implemented. In the experiment, many cases of different rates of mass variation and excitation forces are carried out. Overall, the numerical dynamic responses match well with the experimental ones, which indicates that the proposed procedure is suitable for analyzing the system's time-varying characteristics. [ABSTRACT FROM AUTHOR]

Objective To investigate the underlying mechanism of plastrum testudinis (PT ) in the treatment of osteoporotic fracture ( OF) using network pharmacology and experimental validation . Methods The components of PT and their corresponding targets were obtained with the help of BATMAN database, and relevant targets of OF were obtained by searching Genecards and OMIM databases. Intersection targets were input into the STRING database to obtain protein-protein interaction ( PPI) information. The constructions of PPI network and PT-compound-target-OF network were done with Cytoscape 3. 7. 2, and GO function enrichment and KEGG pathway enrichment analyses were finished with Cytoscape3. 7. 2 and R. Additionally, to verify the reliability of the network pharmacology findings, we also conducted in vivo experiments to verify the effect of PT on improving OF and in vitro experiments, which investigated the phenotypes of human peripheral blood monocytes ( HPBMs) under the intervention of PT. Results Six active compounds and 342 targets of PT were obtained, including 34 targets correlated with OF. There were 802 results gained through GO function enrichment analysis ( P < 0. 05), and 67 results through KEGG pathway enrichment analysis, including 22 relevant signaling pathways ( P < 0.05 ), which were mainly involved in TNF, MARK, estrogen, NF-KB, and other signaling pathways. Notably, our in vivo experiments proved that PT could effectively treat the bone defects in OF model rats. The in vitro experiments showed that PT could inhibit RANKL-induced osteoclast differentiation in HPBMs. Conclusion By regulating inflammatory response, hormone metabolism, and cell cycle, PT may treat OF through numerous compounds, targets and pathways. The inhibition of osteoclast differentiation may play an important role in the mechanism of PT against OF. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Southeast University / Dongnan Daxue Xuebao is the property of Journal of Southeast University Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study validates EKF-SLAM for indoor autonomous vehicles by experimentally integrating the MPU6050 sensor and encoder data using an extended Kalman filter. Real-world tests show significant improvements, achieving high accuracy with just 1% and 3% errors in the X and Y axes. RPLiDAR A1M8 is utilized for mapping, producing accurate maps visualized through RViz-ROS. The research demonstrates the novelty and practical utility of EKF-SLAM in real-world scenarios, showcasing unprecedented effectiveness and precision. [ABSTRACT FROM AUTHOR]

Purpose: Brake squeal as a dynamic instability phenomenon is a major comfort problem observed in automotive disc brake systems. Thus, it is aimed to investigate the effects of certain operational parameters on squeal initiation. Methods: The problem is investigated both experimentally and mathematically from the perspective of system stability. Experimentally, a mass-sliding belt experiment is designed and built, with a focus on three key operational parameters. Experiments are conducted at a wide range of these operational parameters. Furthermore, the contact stiffness at the mass and sliding belt contact interface is evaluated via modal tests. Mathematically, a nonlinear mathematical model of the experiment is developed. The model is then linearized through certain assumptions, and the stability of the system is assessed through the linearized mathematical model via complex eigenvalue solution. Results: Data measured from the experiments are processed in time and frequency domains. Time domain results reveal local dynamic amplifications in time histories of certain operational parameters, which lead to the emergence of super-harmonics in frequency domain. Furthermore, Stribeck type friction characteristic is observed at the mass and sliding belt contact interface. The critical values of dynamic friction coefficient and motor angular speed are obtained for the validation of predictions with experimental data. Conclusion: A good correlation between the model predictions and experiments is achieved, thus the stability analysis based on linearized model is validated with the experimental data. An extensive understanding about the effects of key operational parameters on system stability is obtained. [ABSTRACT FROM AUTHOR]

Copyright of Acta Scientiarum Naturalium Universitatis Sunyatseni / Zhongshan Daxue Xuebao is the property of Sun-Yat-Sen University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Avances en Ciencias e Ingenierías (ACI) is the property of USFQ Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper addresses the issues caused by traditional tractors during seeding operations, such as soil compaction, decreased soil fertility, use of unclean fuel leading to environmental pollution, and the disruption of sustainable development. In response, the study designs a compact and lightweight electric four-wheel-drive chassis for a seeding robot suitable for strip planting of soybeans and corn. Using RecurDyn(V9R2) software and MATLAB/Simulink(2020a) modules, the paper conducts simulation and analysis of the straight-line driving process of the electric four-wheel-drive chassis on hilly terrain in field conditions. The simulation results demonstrate that when the suspension stiffness is 14.4 kN/m and the damping is 900 N·s/m, the chassis achieves optimal vibration reduction and straight-line driving performance. Experimental results based on the simulation findings indicate a high consistency between the simulation and actual models, confirming that optimizing the suspension damping parameters effectively improves chassis smoothness and enhances operational quality. [ABSTRACT FROM AUTHOR]

The on-ground validation of control systems designed for manipulators working in orbit is very difficult due to the necessity of simulating the microgravity environment on Earth. In this paper, we present the possibilities of utilising the KUKA KUBE test-bed with industrial robots to experimentally verify space systems using hardware-in-the-loop tests. The fixed-base KUKA industrial robot is operated in gravitational environment, while the space system model plant is solved in real time parallel to on-ground experiment. The test-bed measurements are the input of the model plant, and the output of the model is treated as an input for the industrial robot actuation. In the performed experiment, the control system based on the Dynamic Jacobian is validated. The desired point that is reached by the manipulator's end-effector is constant in the simulated environment and moving with respect to the test-bed frame. The position of the space manipulator's end-effector is calculated by evaluating dynamics of the satellite in real-time model. The results show that the control system applied to the KUKA robot works correctly. The measurements from the torque sensors mounted in KUKA robot's joints are in accordance with the simulation results. This fact enhances the possibilities of gravity compensation, thus simulating microgravity environment on the test-bed. [ABSTRACT FROM AUTHOR]