Precision Instruments Research Articles

Scientific production on robotic metabolic and bariatric surgery: a comprehensive bibliometric analysis on its current world status.

Robotic metabolic and bariatric surgery (RMBS) has emerged as an innovative approach in the treatment of severe obesity by combining the ergonomic precision of robotic technology and instrumentation with the established benefits of weight loss surgery. This study employs a bibliometric approach to identify local research trends and worldwide patterns in RMBS. The research methodology used "robotic" and "metabolic" or "bariatric surgery" to search Web of Science. Articles that were published prior to December 31st, 2023, were included. The analyses were developed using the Rayyan and Bibliometric, in R Studio. 265 articles from 51 different journals were included. Scientific production of RMBS experienced a significant annual growth rate of 21.96% from 2003 to 2023, resulting in an average of 12.6 papers published per year. A high correlation (R2 = 0.94) was found between the year and number of articles. The mean number of citations per document was 13.25. Approximately 90% of the journals were classified as zone 3, according to the Bradford categorization. International collaboration was identified in 10.57% of cases, with the University of California and the University of Illinois being the most common organizations. The countries with the highest number of corresponding authors, in descending order, were the United States of America, China, and Switzerland. Scientific production in RMBS has experienced sustained growth since the first original publications in 2003. While it has not yet reached the volume, impact, and international collaboration seen in studies related to non-robotic metabolic and bariatric surgery, RBMS holds potential that remains to be explored.

Glutathione Modulates Hydrogen Sulfide Release and the Ocular Hypotensive Action of Diallyl Polysulfide Compounds.

Hydrogen sulfide (H2S) is an endogenous transmitter with the potential to regulate aqueous humor dynamics and protect retinal neurons from degeneration. The aim of the present study was two-fold: (a) to evaluate the release of H2S from two polysulfides, diallyl disulfide (DADS), and diallyl trisulfide (DATS); and (b) to investigate their ocular hypotensive actions in normotensive male and female rabbits in the presence and absence of GSH. H2S was quantified hourly for up to 6 h using a H2S-Biosensor (World Precision Instruments, Sarasota, Fl). Intraocular pressure (IOP) was assessed in normotensive New Zealand Albino rabbits using a pneumotonometer (model 30 classic; Reichert Ophthalmic Instruments, Depew, NY, USA). In the presence of GSH, there was an increase in the in vitro release of H2S produced by DADS and DATS. Both DADS and DATS also caused a dose-dependent reduction in IOP in male and female rabbits, in both treated and untreated eyes. For instance, in male animals, the presence of GSH (3% and 5%) significantly (p < 0.05, n = 5) enhanced the ocular hypotensive action of DADS (2%) and DATS (2%) from 14.02 ± 2.89% to 18.67 ± 5.6% and from 16.22 ± 3.48 to 23.62 ± 5.79%, respectively. GSH enhanced both H2S release and ocular hypotensive action of the polysulfides in a manner that was dependent on the number of sulfur atoms present in each polysulfide. Furthermore, female animals were less sensitive to the IOP-lowering action of the polysulfides, when compared to their male counterparts.

Improving quality control procedures for the measurement of total daily energy expenditure using the two-point doubly labeled water method.

The precision of the doubly labeled water (DLW) method is determined by the precision and accuracy of the isotopic measurements. Quality control (QC) procedures to mitigate sample variability require additional measurements if sample duplicates differ more than a factor of instrument precision. We explored the effect of widening QC ranges on total daily energy expenditure (TDEE) determined using the two-point sampling method. We screened DLW data from 121 individuals for instances where samples were analyzed more than twice using our existing QC criteria (±2.0 per mil [δ] for 2H and ±0.5 δ for 18O). We then applied wider QC ranges for accepting duplicate measures and recalculated TDEE. Widening the 2H QC range to ±10.0 δ in samples collected on the first day (most enriched) and to ±5.0 δ in samples collected on the final day (less enriched) produced almost identical mean TDEE compared to the originally calculated TDEE (2684 ± 508 vs. 2687 ± 512 kcal/day, p= 0.40). There was a strong correlation with the originally calculated TDEE (r2=0.97, p< 0.001). Expanding the 2H QC range to ±10.0 δ for samples collected on the first day and ±5.0 δ for samples collected on the final day provides similar mean TDEE results. These findings may help DLW labs optimize QC criteria and reduce analytical costs.

Impact-Resistant Adhesive Based on the Shear-Stiffening Effect via Dynamic B-O Linkages.

The occurrence of adhesive failure under impact poses significant risks, including property damage, structural collapse, and even loss of life. Herein, we have developed a series of impact-resistant adhesives by incorporating dynamic B-O linkages into linear polymeric chains. These adhesives not only possess broad-area adhesion and superior adhesive strength compared to 3 M commercial products but also exhibit a shear-stiffening effect. The shear-stiffening effect provided by the B-O linkages endows the adhesives with remarkable impact resistance, achieving a force attenuation efficiency of 84.3-86.3%. Additionally, when they are bonded to target materials, the resulting sandwich structures retain their excellent impact resistance. Therefore, this class of impact-resistant adhesives with a shear-stiffening effect shows significant potential for applications in protecting precision instruments and buildings.

Study of the Micro-Vibration Response and Related Vibration Isolation of Complex Traffic Load-Induced Experimental Buildings

In view of the high-sensitivity vibration effect of precision instrument laboratory buildings under the influence of surrounding traffic loads, field micro-vibration tests under various working conditions were carried out based on actual projects. Combined with numerical simulation, measured data served as input loads to simulate the vibration effect of various traffic loads on the floor of a building structure, and the structural vibration laws under the comprehensive action of various loads were analyzed. The vibration isolation effect of the isolation ditch on the oblique orthogonal load was investigated according to the corresponding safety index. The results show that the main frequency components of the site vibration frequency caused by various traffic loads are approximately 25 Hz and that the root-mean-square speed value is stable below VC-E, which meets the design requirements. Under the comprehensive action of multiple loads, the site structure will produce a vibration amplification effect, which is obvious when all types of loads are distributed symmetrically and the curve distribution is controlled by load factors with large amplitudes. The isolation effect of a small isolation ditch is best when it is located close to the source and the building. The depth of the isolation ditch must be greater than the maximum depth of the source to achieve better results, and the width has little influence. The effect of a small isolation trench on vertical vibration is poor, and the oblique orthogonal triaxial load has a counteracting effect on the vertical component. Thus, additional structural vibration isolation measures are needed. The research results provide a reference for engineering vibration isolation, damping measures, and structural design.

Solar internetwork magnetic fields: Statistical comparison between observations and MHD simulations

Although the magnetic fields in the quiet Sun account for the majority of the magnetic energy in the solar photosphere, inferring their exact spatial distribution, origin, and evolution poses an important challenge because the signals lie at the limit of today's instrumental precision. This severely hinders and biases our interpretations, which are mostly made through nonlinear model-fitting approaches. Our goal is to directly compare simulated and observed polarization signals in the Fe I $ angstrom $ and $ angstrom $ spectral lines in the very quiet Sun, the so-called solar internetwork (IN). This way, we aim to constrain the mechanism responsible for the generation of the quiet Sun magnetism while avoiding the biases that plague other diagnostic methods. We used three different three-dimensional radiative magneto-hydrodynamic simulations representing different scenarios of magnetic field generation in the internetwork: small-scale dynamo, decay of active regions, and horizontal flux emergence. We synthesized Stokes profiles at different viewing angles and degraded them according to the instrumental specifications of the spectro-polarimeter (SP) on board the Hinode satellite. Finally, we statistically compared the simulated spectra to the Hinode/SOT/SP observations at the appropriate viewing angles. Of the three simulations, the small-scale dynamo best reproduced the statistical properties of the observed polarization signals. This is especially prominent for the disk center viewing geometry, where the agreement is excellent. Moving toward more inclined lines of sight, the agreement worsens slightly. The agreement between the small-scale dynamo simulation and observations at the disk center suggests that small-scale dynamo action plays an important role in the generation of quiet Sun magnetism. However, the magnetic field around 50 km above the continuum layer in this simulation does not reproduce observations as well as at the very base of the photosphere.

LC-MS/MS and GC-MS/MS Cross-Checking Analysis Method for 426 Pesticide Residues in Agricultural Products: A Method Validation and Measurement of Uncertainty.

A method was developed to analyze residual pesticides in various vegetables using liquid chromatography-tandem mass spectrometry (LC-MS/MS) and gas chromatography-tandem mass spectrometry (GC-MS/MS). A method can analyze over 200 individual compounds, selectively separate peaks within 30 min, and meet various criteria such as those by the Codex Alimentarius Commission (CODEX). Most compounds showed recovery rates between 70 and 120%, and a relative standard deviation was within 20%. Measurement uncertainty, considering various influencing factors such as instrument precision, method sensitivity, experimental conditions, sample handling, and analytical procedures, was meticulously calculated. The expanded uncertainties of cross-checking 33 available pesticides ranged from 10.1 to 26.2 μg/kg at a confidence level of approximately 95%. Risk assessment of detected pesticides in agricultural products indicated a safety range of 0.00003-2.87240%. The developed method effectively analyzes diverse compounds simultaneously, contributing to agricultural product safety.

Drifted Uncertainty Evaluation of a Compact Machine Tool Spindle Error Measurement System

The accurate measurement of spindle errors, especially quasi-static errors, is one of the key issues for the analysis and compensation of machine tool thermal errors in machining accuracy. To quantitatively analyze the influence of the measurement system’s own drift on the measurement results, a drifted uncertainty evaluation method of the precision instrument considering the time drift coefficient is proposed. This study also produced a high-precision compact spindle error measurement device (with a displacement measurement error of less than ±1.33 μm and an angular measurement error of less than ±1.42 arcsecs) as the research object to verify the proposed drift uncertainty evaluation method. A method for evaluating the drift uncertainty of the measurement system is proposed to quantitatively evaluate the system error and drift uncertainty of the measurement device. Experiments show that the drift uncertainty evaluation method proposed in this paper is more suitable for evaluating the uncertainty changes in measurement instruments during long-term measurements compared to traditional methods.

Research on magnetic fluid precise localized lubrication thrust cylindrical roller bearing with low-friction micro-vibration and high load-bearing capacity

Abstract As the magnetic field that is difficult to be distributed in the existing magnetic fluid thrust cylindrical roller bearing structure, it is more difficult for the magnetic fluid to be evenly distributed inside the bearing raceway with the axial localized lubrication, which seriously affects the engineering application of the magnetic fluid bearing. To solve the magnetic field control problem that the magnetic fluid is uneasy to be accurately localized and adsorbed, a new type of magnetic fluid thrust cylindrical roller bearing is designed in this study, which shows good characteristics of low-friction, micro-vibration and high load-bearing capacity. The seat-ring is set as an annular raceway that can be used for magnetic fluid storage and matching with the roller lubrication system, and an annular permanent magnet is designed as an external magnetic field source to be placed below the annular raceway to adsorb the magnetic fluid on the friction surface. The structure design of the axial magnetic fluid localized lubrication bearing is reasonable, which is especially suitable for precision instruments with strict operating-conditions and precision-lubrication.

Application of ferromagnetic materials for technological processes thermal regime stabilization (Review)

The research focuses on the technological and auxiliary equipment used in various industries that require maintaining a specific narrow temperature range. The study aims to critically analyze the potential use of structural elements made of ferromagnetic materials with a second-kind phase transition temperature (Curie temperature or Curie point) in high-performance, knowledge-intensive industries, particularly the chemical industry. These materials correspond to the required temperature of the processed or transported liquid or loose medium. The technological processes using the magnetothermal effect and the corresponding designs of equipment are considered: heat exchange, heat and mass exchange, mechanical and hydromechanical, equipment for processing thermoplastics, as well as other devices used in various branches of industry, in particular chemical, food and microbiological, in thermal energy, metallurgy, agriculture, medicine and construction. It is shown that the specified method of ensuring the required thermal regime is suitable for use primarily in large-tonnage continuous production. As the conducted studies have shown, the proposed approach to stabilizing the heat flow of various technological and auxiliary equipment is effective and quite promising. The indisputable advantage of the corresponding method is to ensure a certain temperature of the working parts of the equipment with high accuracy, however, this method is quite difficult to implement on the existing equipment, which is mostly made of magnetic materials (steel, cast iron). Therefore, to implement the proposed method in practice, it is necessary to develop new equipment designs or to subject existing samples to deep modernization. At the same time, there may be difficulties associated with the search for existing or the creation of new ferromagnetic materials with the required thermomagnetic properties for the manufacture of appropriate structural elements of technological and auxiliary equipment. However, in certain cases, the proposed method of maintaining the specified temperature of the processed media may become the most appropriate (primarily in fine chemical technology, biotechnology, pharmaceuticals, precision instrument manufacturing, microelectronics, and medicine).

Development and Validation of a High-Performance Thin-Layer Chromatography Method for the Qualitative Analysis and Quantification of Hispidulin in Hydroethanol Extract of S. barbata D. Don

Background: Hispidulin, a flavonoid renowned for its diverse pharmacological activities, is abundant in S. barbata D. Don. Given its prevalence, it is essential to establish a dependable analytical method for quantifying hispidulin in this plant. Methods: This study introduces a sensitive and reliable high-performance thin-layer chromatographic (HPTLC) method for both qualitative and quantitative analysis of hispidulin in S. barbata D. Don. Pre-coated TLC aluminum plates were utilized, and after testing various mobile phase combinations, the most effective separation was achieved with Toluene-ethyl acetate-formic acid (5:4:1, v/v/v). The method underwent extensive validation for linearity, specification, instrument precision, precision, limits of LOD and LOQ, accuracy, and robustness. Results: The developed method demonstrated excellent linearity over a specified concentration range, with a determination coefficient (r2) of 0.988. A well-defined spot at Rf 0.7, corresponding to hispidulin, was observed. The concentration of hispidulin in the hydroethanolic extract of S. barbata D. Don was quantified as 13.02 μg/mg of extract. Conclusion: In conclusion, the HPTLC method presented in this study offers a simple, accurate, and robust tool for quantitatively analyzing hispidulin in the hydroethanol extract of S. barbata D. Don. This method is suitable for routine quality control and standardization of herbal formulations containing S. barbata D. Don, thereby contributing to the advancement of research in natural product- based pharmaceuticals.

Vision-based reinforcement learning control of soft robot manipulators

Purpose This study aims to tackle control challenges in soft robots by proposing a visually-guided reinforcement learning approach. Precise tip trajectory tracking is achieved for a soft arm manipulator. Design/methodology/approach A closed-loop control strategy uses deep learning-powered perception and model-free reinforcement learning. Visual feedback detects the arm’s tip while efficient policy search is conducted via interactive sample collection. Findings Physical experiments demonstrate a soft arm successfully transporting objects by learning coordinated actuation policies guided by visual observations, without analytical models. Research limitations/implications Constraints potentially include simulator gaps and dynamical variations. Future work will focus on enhancing adaptation capabilities. Practical implications By eliminating assumptions on precise analytical models or instrumentation requirements, the proposed data-driven framework offers a practical solution for real-world control challenges in soft systems. Originality/value This research provides an effective methodology integrating robust machine perception and learning for intelligent autonomous control of soft robots with complex morphologies.

Prognostic Significance and Immune Landscape of an Efferocytosis-Related Gene Signature in Bladder Cancer.

Bladder cancer poses a significant global health challenge, underscoring the imperative for precise prognostic instruments to advance patient care. Against the backdrop of efferocytosis's increasingly recognized role in cancer, this research endeavors to develop and authenticate a prognostic signature intricately linked to efferocytosis in bladder cancer. LASSO-COX regression analysis crafted an efferocytosis-related genes risk prognostic model, followed by the construction of a column chart. External validation sets confirmed the predictive accuracy of both the model and chart. Clinical, tumor microenvironment, drug sensitivity, and immunotherapy analyses were employed to comprehensively assess efferocytosis-related scores. The expression of TGFB3 key genes was validated via RT-PCR and western blotting. Further validation included Transwell, Wound healing, Colony formation, and EDU assays. We formulated and validated an efferocytosis-related genes risk model in bladder cancer, comprising 13 core genes. The risk model demonstrated autonomous prognostic significance in both univariate and multivariate Cox analyses. Following the multivariate analysis, we devised a nomogram. Moreover, by utilizing individual risk scores derived from this risk model, we successfully stratified patients into two discernible risk cohorts, unveiling noteworthy variances in immune infiltration profiles and responsiveness to immunotherapy. Notably, the model's key gene TGFB3 was validated through comprehensive experimental investigations, including Transwell assays for migration and invasion and Wound healing assays for motility on the T24 and BIU cell lines. This study has furnished innovative perspectives on an efferocytosis-related prognostic signature, elucidating the prognosis and immune milieu intricacies in patients with bladder cancer.

One step from oxides to sustainable bulk alloys

Metallurgical production traditionally involves three steps: extracting metals from ores, mixing them into alloys by liquid processing and thermomechanical processing to achieve the desired microstructures1,2. This sequential approach, practised since the Bronze Age, reaches its limit today because of the urgent demand for a sustainable economy2–5: almost 10% of all greenhouse gas emissions are because of the use of fossil reductants and high-temperature metallurgical processing. Here we present a H2-based redox synthesis and compaction approach that reforms traditional alloy-making by merging metal extraction, alloying and thermomechanical processing into one single solid-state operation. We propose a thermodynamically informed guideline and a general kinetic conception to dissolve the classical boundaries between extractive and physical metallurgy, unlocking tremendous sustainable bulk alloy design opportunities. We exemplify this approach for the case of Fe–Ni invar bulk alloys6,7, one of the most appealing ferrous materials but the dirtiest to produce: invar shows uniquely low thermal expansion6,8,9, enabling key applications spanning from precision instruments to cryogenic components10–13. Yet, it is notoriously eco-unfriendly, with Ni causing more than 10 times higher CO2 emission than Fe per kilogram production2,14, qualifying this alloy class as a perfect demonstrator case. Our sustainable method turns oxides directly into green alloys in bulk forms, with application-worthy properties, all obtained at temperatures far below the bulk melting point, while maintaining a zero CO2 footprint.

The health, climate, and equity benefits of freight truck electrification in the United States

Abstract Long-haul freight shipment in the United States relies on diesel trucks and constitutes ∼3% of U.S. greenhouse gas emissions and a significant share of local air pollution. Here, we compare the climate and air pollution-related health damages from electric versus diesel long-haul truck fleets. We use truck commodity flows to estimate tailpipe emissions from diesel trucks and regional grid emissions intensities to estimate charging emissions from electric trucks under various grid scenarios. We use a reduced complexity air quality model combined with valuation of air pollution-related premature deaths (using two hazard ratios (HRs)) and quantify the distributional health impacts in different scenarios. We find that annual health and climate costs of the current diesel fleet are $195–$249/capita compared to $174–$205/capita for a new diesel fleet, and $156–$177/capita for an electric fleet, depending on the HR. We find that freight electrification could avoid $6.2–8.5 billion in health and climate damages annually when compared to a fleet of new diesel vehicles (with even higher benefits when compared to the current diesel fleet). However, the Midwest and parts of the Gulf Coast would experience an increase in health damages due to vehicles charging using electricity from coal power plants. If old coal power plants (operating in 1980 or earlier) are replaced with zero-emission generation, electrification of all U.S. freight would result in $32.3–39.2 billion in avoided damages annually and health benefits throughout the U.S. Electrifying transport of consumer manufacturing goods (including electronics, transport equipment, and precision instruments) and food, beverage, and tobacco products would provide the largest absolute health and climate benefits, whereas mixed freight and manufacturing goods would result in the largest benefits per tonne-km. We find small variations in health damages across race and income. These results will help policymakers prioritize electrification and charging investment strategies for the freight transportation sub-sector.

Optimization of Tool Wear and Cutting Parameters in SCCO2-MQL Ultrasonic Vibration Milling of SiCp/Al Composites

Silicon carbide particle-reinforced aluminum matrix (SiCp/Al) composites are significant lightweight metal matrix composites extensively utilized in precision instruments and aerospace sectors. Nevertheless, the inclusion of rigid SiC particles exacerbates tool wear in mechanical machining, resulting in a decline in the quality of surface finishes. This work undertakes a comprehensive investigation into the problem of tool wear in SiCp/Al composite materials throughout the machining process. Initially, a comprehensive investigation was conducted to analyze the effects of cutting velocity vc, feed per tooth fz, milling depth ap, and milling width ae on tool wear during high-speed milling under SCCO2-MQL (Supercritical Carbon Dioxide Minimum Quantity Lubrication) ultrasonic vibration conditions. The results show that under the condition of SCCO2-MQL ultrasonic vibration, proper control of milling parameters can significantly reduce tool wear, extend tool service life, improve machining quality, and effectively reduce blade breakage and spalling damage to the tool, reduce abrasive wear and adhesive wear, and thus significantly improve the durability of the tool. Furthermore, a prediction model for tool wear was developed by employing the orthogonal test method and multiple linear regression. The model’s relevance and accuracy were confirmed using F-tests and t-tests. The results show that the model can effectively predict tool wear, among which cutting velocity vc and feed rate fz are the key parameters affecting the prediction accuracy. Finally, a genetic algorithm was used to optimize the milling parameters, and the optimal parameter combination (vc = 60.00 m/min, fz = 0.08 mm/z, ap = 0.20 mm) was determined, and the optimized milling parameters were tested. Empirical findings suggest that the careful selection of milling parameters can significantly mitigate tool wear, extend the lifespan of the tool, and enhance the quality of the surface. This work serves as a significant point of reference for the processing of SiCp/Al composite materials.

A comprehensive study on the microstructure evolution and mechanical property characterization of selective laser melted 18Ni300 stainless steel during heat treatment processes

The influence of different heat treatment processes on the microstructure and mechanical properties of 18Ni300 stainless steel manufactured by selective laser melting has been investigated in the present study. The microstructures, nanoprecipitates, and mechanical properties of the differently heat-treated samples were analyzed using various precision instruments. Compared with a non-treated 18Ni300 stainless steel sample, the results showed that the microstructure was mainly composed of fine lath-like martensite, with a large number of nano-precipitates dispersed both within the martensite and in the boundaries. In addition, there was a preserved amount of austenite between the lath-like martensite and the spherical nanoprecipitate in the SAT sample. The interactions between the martensite matrix and the nanoprecipitates and dislocations were assumed to be the main reason for the high strength of 18Ni300 stainless steel. These precipitates included rod-shaped or needle-shaped, Ni3Ti, Ni3Mo, and Ni3(Ti, Mo) nano-precipitates, as well as spherical Ti–Al nano-oxidized precipitates and massive Ni-rich precipitates. The shear and by-pass mechanisms between the strengthened nano-precipitate and the dislocations were found to depend on the size of the nanoprecipitate. The influence of the nanoprecipitation on the indentation hardness became more evident after heat treatment, but the effect on the indentation modulus was not that obvious. The AT- and SAT-treatments significantly improve the strength, hardness, and modulus of samples but were found to reduce the toughness and plasticity. After the AT- and SAT-treatments, the protrusions became smaller, and the small isometric protrusion of a shear lip became significantly smaller than for the as-built material.

The study on 4D culture system of squamous cell carcinoma of tongue

Traditional cell culture methods often fail to accurately replicate the intricate microenvironments crucial for studying specific cell growth patterns. In our study, we developed a 4D cell culture model-a precision instrument comprising an electromagnet, a force transducer, and a cantilever bracket. The experimental setup involves placing a Petri dish above the electromagnet, where gel beads encapsulating magnetic nanoparticles and tongue cancer cells are positioned. In this model, a magnetic force is generated on the magnetic nanoparticles in the culture medium to drive the gel to move and deform when the magnet is energized, thereby exerting an external force on the cells. This setup can mimic the microenvironment of tongue squamous cell carcinoma CAL-27 cells under mechanical stress induced by tongue movements. Electron microscopy and rheological analysis were performed on the hydrogels to confirm the porosity of alginate and its favorable viscoelastic properties. Additionally, Calcein-AM/PI staining was conducted to verify the biosafety of the hydrogel culture system. It mimics the microenvironment where tongue squamous cell carcinoma CAL-27 cells are stimulated by mechanical stress during tongue movement. Electron microscopy and rheological analysis experiments were conducted on hydrogels to assess the porosity of alginate and its viscoelastic properties. Calcein-AM/PI staining was performed to evaluate the biosafety of the hydrogel culture system. We confirmed that the proliferation of CAL-27 tongue squamous cells significantly increased with increased matrix stiffness after 5 d as assessed by MTT. After 15 d of incubation, the tumor spheroid diameter of the 1%-4D group was larger than that of the hydrogel-only culture. The Transwell assay demonstrated that mechanical stress stimulation and increased matrix stiffness could enhance cell aggressiveness. Flow cytometry experiments revealed a decrease in the number of cells in the resting or growth phase (G0/G1 phase), coupled with an increase in the proportion of cells in the preparation-for-division phase (G2/M phase). RT-PCR confirmed decreased expression levels of P53 and integrinβ3 RNA in the 1%-4D group after 21 d of 4D culture, alongside significant increases in the expression levels of Kindlin-2 and integrinαv. Immunofluorescence assays confirmed that 4D culture enhances tissue oxygenation and diminishes nuclear aggregation of HIF-1α. This device mimics the microenvironment of tongue cancer cells under mechanical force and increased matrix hardness during tongue movement, faithfully reproducing cell growthin vivo, and offering a solid foundation for further research on the pathogenic matrix of tongue cancer and drug treatments.

A Hybrid VGG 19 and Capsule Network Based Deep Learning Model for Lung Cancer Diagnosis using CT S can Images

Objectives: Lung cancer is one of the most prevalent causes of carcinoma-related fatalities globally; precise and effective diagnostic instruments are desperately needed. Researchers and physicians continue to encounter difficulties when aiming to employ deep learning models in healthcare environments for recognizing lung cancer and to achieve higher sensitivity and accuracy on large data sets, despite several advancements in this field. Our study builds upon an extensive review of existing lung cancer detection methods, highlighting their strengths and weaknesses. The performance of this model deteriorates when there are variances in Lung CT image features such as rotation, tiling, and other aberrant image orientations. This study aims to address the issues associated with variations in lung CT images. Methods: A hybrid deep learning model that blends the potency of CNNs with the cutting-edge design of capsule networks is proposed. Inspired by recent advancements, our model integrates the VGG19 and Capsule Network architectures to address orientation-related challenges often encountered in traditional CNN-based approaches. The creation, training, and assessment of this hybrid model for lung nodule identification and categorization are our main research goals. Findings: We anticipate that our research has yielded several valuable outcomes, including improved nodule classification accuracy of 99.20%, reduced false positive rates, and minimized training times. Novelty: This research employing a hybrid deep learning model that combines the capabilities of the VGG-19 and capsule network could lead to more widespread utilization in cancer diagnosis by enhancing early lung cancer detection and developing the field of medical image analysis. The shortcomings of convolutional neural networks are addressed with Capsule Network. Leveraging the knowledge and insights gained from lung cancer detection, our research also investigates the potential applicability of our methodology to identify other types of medical image classification such as breast and ovarian cancer. Keywords: Computed Tomography, Lung cancer, Deep Learning, CNN, VGG19, Capsule Network

Active Composite Control of Disturbance Compensation for Vibration Isolation System with Uncertainty

The pointing and positioning accuracy of precision instruments in aerospace are often disturbed by low-frequency vibrations. An active/passive vibration isolation system is a feasible solution to suppress low-frequency vibrations. However, the vibration isolation performance of the active control strategy is seriously affected by the uncertainty of the system and the difficulty to meet the higher requirements of new-generation equipment. This paper proposes an active composite control (ACC) strategy for vibration isolation systems with uncertainty. The proposed ACC integrates feedforward control based on known systems and feedback control based on the Kalman filter for systems with uncertainty. Further, the derivation and stability analyses of the proposed ACC algorithm are provided, and the influence of system uncertainty on vibration isolation performance based on the proposed ACC is analyzed. Experimental verification is conducted and the experimental results confirm that the proposed ACC can effectively realize the low-frequency and wide-band vibration isolation for the system with uncertainty. Starting from 30 Hz, the vibration isolation performance of the proposed ACC with uncertainty is significantly improved than that of the ACC completely based on a deterministic system model.