Experimental Techniques Research Articles

Antibacterial Potential of West Kalimantan Local Bajakah (Spatholobus suberectus) Ethanol Extract Against Staphylococcus aureus ATCC 25923 and Methicillin Resistant Staphylococcus aureus

The primary factor contributing to bacterial resistance is the overutilization of antibiotics caused by Staphylococcus aureus ATCC25923. The prevalence of methicillin-resistant Staphylococcus aureus (MRSA) strains possess a significant challenge in both clinical and community environments. Consequently, there is a need to investigate alternative antibacterial sources derived from natural ingredients and local traditional medicines. One such potential source is bajakah Jie Xue Teng (Spatholobus suberectus). The available data on the active component composition and antibacterial efficacy of the ethanol extract derived from bajakah (S. suberectus) in the West Kalimantan region is currently insufficient. The objective of this study is to evaluate the phytochemical composition and antibacterial properties of the ethanol extract derived from bajakah (S. suberectus), a plant species indigenous to West Kalimantan. The antimicrobial activity of the extract will be tested against two bacterial strains, namely S. aureus and MRSA, using in vitro methods. This study employs experimental techniques and is comprised of two distinct phases. The first phase involves conducting a phytochemical test on the ethanol extract of bajakah stem, utilizing the Thin Layer Chromatography (TLC) method. The second phase involves evaluating the antibacterial properties of the ethanol extract of bajakah stem against S. aureus and MRSA, employing the paper disc diffusion method. The research findings indicate that the bajakah ethanol extract derived from S. suberectus, a plant indigenous of West Kalimantan, possesses alkaloids, flavonoids, saponins, and steroids. The optimal antibacterial efficacy is observed at a concentration of 1,000,000 ppm, resulting in an inhibition zone diameter of 9 mm against S. aureus and 10 mm against MRSA.

A method to partition boiling heat transfer mechanisms using synchronous through-substrate high-speed visual and infrared measurements

Heat transfer during boiling involves a variety of transport mechanisms. Available experimental techniques cannot yet fully delineate these mechanisms which has contributed to a long-standing, persistent challenge of constructing accurate mechanistic models for boiling. In this work, we develop a method to identify and distinguish between the individual heat transfer mechanisms that occur during boiling using synchronous, through-substrate, high-speed visual and infrared measurements. Local heat fluxes are deduced from temperature measurements and a synchronized set of binarized phase maps are obtained from processing high-speed visual measurements. Experimental pool boiling investigation of HFE-7100 fluid on an indium tin oxide surface revealed four distinct heat transfer signatures in the heat flux maps corresponding to liquid convection, contact line evaporation, vapor convection, and local microconvection due to rewetting during boiling. To classify these regions, pixel-wise binary and morphological operations are performed on the phase maps of the entire surface. In contrast with prior partitioning techniques which use standalone heat flux measurements, our synchronous high-resolution visualization enables the region classification around fine bubble footprints that otherwise would not be detected with heat flux maps alone. The heat fluxes and superheats are then partitioned into their underlying mechanisms using classified regions from the phase maps. Analysis of the nucleate boiling regime data shows that different mechanisms contribute in varying degrees to the overall heat transfer at different points along the boiling curve: for the surface-fluid combination studied, single-phase liquid heat transfer is the primary contributor at low heat fluxes while at high heat fluxes, contact line evaporation contributed the most. We further employ the experimental approach to partitioning dynamic processes resulting from step increases in heat input demonstrating its potential for investigating transient phenomena such as dryout. The experimental and post-processing method introduced in this study is the first to delineate partitioning between different heat transfer mechanism regions in the presence of multiple interacting bubbles over the entire surface throughout the boiling curve in both steady and transient operating conditions.

The "hidden noise" problem in MR image reconstruction.

The performance of modern image reconstruction methods is commonly judged using quantitative error metrics like root mean squared-error and the structural similarity index, which are calculated by comparing reconstructed images against fully sampled reference data. In practice, the reference data will contain noise and is not a true gold standard. In this work, we demonstrate that the "hidden noise" present in reference data can substantially confound standard approaches for ranking different image reconstruction results. Using both experimental and simulated k-space data and several different image reconstruction techniques, we examined whether there was correlation between performance metrics obtained with typical noisy reference data versus those obtained with higher-quality reference data. For conventional performance metrics, the reconstructions that matched best with the higher-quality reference data were substantially different from the reconstructions that matched best with typical noisy reference data. This leads to suboptimal reconstruction results if the performance with respect to noisy reference data is used to select which reconstruction methods/parameters to employ. These issues were reduced when employing alternative error metrics that better account for noise. Reference data containing hidden noise can substantially mislead the ranking of image reconstruction methods when using conventional error metrics, but this issue can be mitigated with alternative error metrics.

Effects of chlorine and nitro groups on the crystal structure of novel 4-quinolinone derivatives from sulfonamide chalcone

This study explores the impact of introducing chlorine and nitro groups into two novel quinolone derivatives, (E)-3-(4-nitrobenzylidene)-2-(3-nitrophenyl)-2,3-dihydro-1-(phenylsulfonyl)-quinolin-4(1H)-one (NPQ) and (E)-3-(4-chlorobenzylidene)-2-(3-nitrophenyl)-2,3-dihydro-1-(phenylsulfonyl)-quinolin-4(1H)-one (CPQ), using experimental techniques and density functional theory (DFT). The research focuses on crystalline packing, conformational changes, and intermolecular interactions. The investigation reveals that weak non-classical hydrogen interactions, hydrophobic, and CH···π interactions, predominantly stabilize the crystal structures. These interactions, quantified through a Hirshfeld surface analysis. Additionally, the Fukui function analysis indicates antioxidant potential in the crystals. NPQ and CPQ exhibit a small energy gap, implying low kinetic stability, high reactivity, and reduced resistance to charge transfer when compared. These findings provide valuable insights into the structural and electronic properties of these quinolone derivatives, aiding the design of novel compounds with desired characteristics and applications. The DFT analysis utiliazsed the M062-X functional and the 6–311++G(d,p) basis set in the Gaussian 09 package, and the result was visualized using the GaussView software.

Torsion Effects Beyond the δ Bond and the Role of π Metal-Ligand Interactions.

Previous studies on bimetallic paddlewheel compounds have established a direct correlation between metal-metal distance and ligand torsion angles, leading to the rule that higher torsion results in longer metal-metal bond distances. Here, the new discovery based on diarylformamidinateRu₂⁵⁺ paddlewheel compounds [Ru2Cl(DArF)4]that show an opposite behavior is reported: higher torsions lead to shorter metal-metal distances. This discovery challenges the assumption that internal rotation solely impacts the δ bond. By combining experimental and theoretical techniques, it is demostrated that this trend is associated with previously overlooked π metal-ligand interactions. These π metal-ligand interactions are a direct consequence of the paddlewheel structure and the conjugated nature of the bidentate ligands. This findings offer far-reaching insights into the influence of equatorial ligands and their π-conjugation characteristics on the electronic properties of paddlewheel complexes. That this effect is not exclusive of diruthenium compounds but also occurs in other bimetallic cores such as ditungsten or dirhodium is demonstrated, and with other ligands showing allyl type conjugation. These results provide a novel approach for fine-tuning the properties of these compounds with significant implications for materials design.

Designing payload and spaceflight operations for plants from extreme terrestrial environments

Terrestrial plants from the very limits of life are likely to harbor genes that confer an advantage in human space exploration. These plants are seemingly capable of performing mission critical functions in spaceflight and on extraterrestrial farms while informing directed gene manipulation in target plant species. However, their adaptations to physiologically extreme habitats may hinder the efficacy of routine laboratory techniques for model plants. We here present the development of Antarctic moss Ceratodon purpureus payload and flight operations for the ANT1 Radiation Tolerance Experiment with Moss in Orbit on the Space Station (ARTEMOSS) experiment to the International Space Station (ISS) given limited physical space and crew time. We demonstrate that the hydrophobic surface of Antarctic moss impedes chemical tissue fixation and precludes the use of RNAlater coupled with payload hardware deployed in standard plant spaceflight experiments. We show that deep-freezing the moss tissue on Petri plates provides adequate tissue fixation and allows the extraction of high-quality RNA suitable for gene expression profiling. We replaced hardware with stacks of Petri plates housing Antarctic moss and chemical fixation with deep-freezing in a cryogenic GLACIER freezer. Our design can be translated to other plant species to expand current experimentation techniques with plants from extreme terrestrial environments in order to advance human space exploration.

Investigating the Protein-Based Therapeutic Relationship between Honey Protein SHP-60 and Bevacizumab on Angiogenesis: Exploring the Synergistic Effect through In Vitro and In Silico Analysis.

Honey is a natural product produced by honeybees, which has been used not only as food but also as a medicine by humans for thousands of years. In this study, 60 kDa protein was purified from Pakistani Sidr honey named as SHP-60 (Sidr Honey Protein-60), and its antioxidant potential and the effect of Bevacizumab with purified protein on in vitro angiogenesis using human umbilical vein endothelial cells (HUVEC) were investigated. We further validated the molecular protein-protein (SHP-60 with Bevacizumab) interactions through in silico analysis. It showed very promising antioxidant activity by reducing 2,2-diphenyl-1-picrylhydrazyl free radicals with a maximum of 83% inhibition at 50 μM and an IC50 of 26.45 μM statistically significant (**p < 0.01). Angiogenesis is considered a hallmark of cancer, and without it, the tumor cannot grow or metastasize. Bevacizumab, SHP-60, and both in combination were used to treat HUVEC, and the MTT assay was used to assess cell viability. To demonstrate in vitro angiogenesis, HUVEC was grown on Geltrex, and the formation of endotubes was examined using a tube formation assay. HUVEC viability was dose-dependently decreased by Bevacizumab, SHP-60, and both together. Bevacizumab and SHP-60 both inhibited angiogenesis in vitro, and their combination displayed levels of inhibition even higher than those of Bevacizumab alone. We investigated the protein-protein molecular docking interactions and molecular dynamics simulation analysis of MRJP3 (major royal jelly protein 3) similar to SHP-60 in molecular weight with both the heavy chain (HC) and light chain (LC) of Bevacizumab. We found significant interactions between the LC and MRJP3, indicating that ASN468, GLN470, and ASN473 of MRJP3 interact with SER156, SER159, and GLU161 of LC of Bevacizumab. The integration of experimental data and computational techniques is believed to improve the reliability of the findings and aid in future drug design.

Extracellular Microvesicles Modified with Arginine-Rich Peptides for Active Macropinocytosis Induction and Delivery of Therapeutic Molecules.

Extracellular vesicles (EVs), including exosomes and microvesicles (MVs), transfer bioactive molecules from donor to recipient cells in various pathophysiological settings, thereby mediating intercellular communication. Despite their significant roles in extracellular signaling, the cellular uptake mechanisms of different EV subpopulations remain unknown. In particular, plasma membrane-derived MVs are larger vesicles (100 nm to 1 μm in diameter) and may serve as efficient molecular delivery systems due to their large capacity; however, because of size limitations, receptor-mediated endocytosis is considered an inefficient means for cellular MV uptake. This study demonstrated that macropinocytosis (lamellipodia formation and plasma membrane ruffling, causing the engulfment of large fluid volumes outside cells) can enhance cellular MV uptake. We developed experimental techniques to induce macropinocytosis-mediated MV uptake by modifying MV membranes with arginine-rich cell-penetrating peptides for the intracellular delivery of therapeutic molecules.

Perspective on Integrative Simulations of Bioenergetic Domains.

Bioenergetic processes in cells, such as photosynthesis or respiration, integrate many time and length scales, which makes the simulation of energy conversion with a mere single level of theory impossible. Just like the myriad of experimental techniques required to examine each level of organization, an array of overlapping computational techniques is necessary to model energy conversion. Here, a perspective is presented on recent efforts for modeling bioenergetic phenomena with a focus on molecular dynamics simulations and its variants as a primary method. An overview of the various classical, quantum mechanical, enhanced sampling, coarse-grained, Brownian dynamics, and Monte Carlo methods is presented. Example applications discussed include multiscale simulations of membrane-wide electron transport, rate kinetics of ATP turnover from electrochemical gradients, and finally, integrative modeling of the chromatophore, a photosynthetic pseudo-organelle.

Mechanical activation and silver supplementation as determinants of the antibacterial activity of titanium dioxide nanoparticles

Metals and metal oxides have subpar antibacterial activities compared to those of small-molecule antibiotics, yet there are hopes that with proper compositional and structural adjustments this gap might be bridged. In this study, titanium dioxide (TiO2) nanoparticles were mechanically activated and combined with particulate silver through simple reduction process elicited by UV irradiation and assisted with the ultrasound. The resulting powders in various combinations (Ag vs. no Ag, activated vs. non-activated) were characterized using a range of experimental techniques and assessed for their antibacterial activities. The preparation procedure presented in this work prevails over the disadvantages of many chemical routes, most critically by avoiding the use of toxic substances. The mechanical activation did not reduce the particle size or crystallinity of TiO2 nor did it consistently alter the bandgap, yet it enabled the doubling of the amount of silver incorporable into the material. Further, while both mechanical activation and the addition of silver in the amount not exceeding 0.5 wt% produced barely detectable structural changes in the material, they both augmented its antibacterial activity. The precursor TiO2 powder produced no inhibition zone against any of the four bacterial species tested, while the mechanical activation of TiO2 led to the formation of distinct inhibition zones against each of the four bacterial species tested. The addition of silver to activated TiO2 further widened the inhibition zones and it also imparted the antibacterial activity to non-activated TiO2. The boost in the antibacterial activity achieved by the short mechanical activation was of a similar magnitude as the boost obtained after the addition of silver. The antibacterial activity was not different for different species when no silver was added to the system. However, with the addition of silver, species selectivity was obtained, as the composites were more effective against the two Gram-negative species (Escherichia coli and Klebsiella pneumoniae) than against the two Gram-positive ones (Staphylococcus aureus and Bacillus subtilis). The antibacterial activity increased with the addition of silver in the broth assay, but it was mediocre compared to that detected in the agar assay, attesting to the poor dispersability of the powders and their best performance when the bacterial cells migrate to the composite surface than vice versa. The findings of this study give hope that with appropriate microstructural or compositional alterations, the antibacterial activity of metal oxide powders and inorganic materials in general can be made comparable to that of small-molecule antibiotics.

Biomolecular phase separation through theoretical and computational microscope

AbstractBiomolecular phase separation is a vital mechanism for orchestrating biomolecules within living cells. This crucial role has spurred an intense pursuit to comprehend the molecular underpinnings governing and regulating these processes. Computational methodologies offer a unique perspective, augmenting experimental techniques by providing detailed information that cannot be obtained otherwise. In this review, we briefly overview the theoretical and computational approaches to investigate biomolecular phase separation. As a short primer, we explain the factors driving and affecting phase separation of biomolecules, and then we delve into analytical and simulation methods used to study phase separation. We explain how analytical methods like the Flory–Huggins theory, random phase approximation, and graph‐based methods have been used to study phase behaviors of various proteins. We also discuss principles and applications of all‐atom simulations, coarse‐grained simulations, and field‐theoretical approaches. Additionally, we explore the recent advances in machine learning approach to predict phase separation of biomolecules.

Quercetin alleviates chronic unpredictable mild stress-induced depression-like behavior by inhibiting NMDAR1 with α2δ-1 in rats.

Depression is a serious mental disorder and the most prevalent cause of disability and suicide worldwide. Chronic unpredictable mild stress (CUMS) can lead to a significant acceleration of depression development. Quercetin (Que) is a flavonoid compound with a wide range of pharmacological effects. Recent studies have shown that quercetin can improve CUMS-induced depression-like behavior, but the mechanism of its improvement is still unclear. α2δ-1 is a regulatory subunit of voltage-gated calcium channel, which can interact with N-methyl-D-aspartate receptor (NMDAR) to form a complex. In this study, we found that Que could inhibit the increase of α2δ-1 and NMDAR expression in rat hypothalamus induced by CUMS. In pain, chronic hypertension and other studies have shown that α2δ-1 interacts with the NMDAR to form a complex, which subsequently affects the expression level of NMDAR. Consequently, the present study aimed to investigate the antidepressant effect of Que invivo and invitro and to explore its mechanism of action in terms of the interaction between α2δ-1 and NMDAR. Rats were randomly exposed to two stressors every day for 4 weeks to establish a CUMS rat model, then sucrose preference test (SPT), forced swimming test (FST), tail suspension test (TST), and open field test (OFT) were performed to detect the behavior of CUMS rats, so as to evaluate whether the CUMS rat model was successfully established and the improvement effect of Que on CUMS-induced depression-like behavior in rats. Experimental techniques such as serum enzyme-linked immunosorbent assay (ELISA), immunofluorescence, Western blot, and co-immunoprecipitation, as well as invitro experiments, were used to investigate the mechanisms by which Que exerts its antidepressant effects. Behavioral and ELISA test results showed that Que could produce a reduction in the excitability of the hypothalamic-pituitary-adrenal (HPA) axis in CUMS rats and lead to significant improvements in their depressive behavior. Western blot, immunofluorescence, and co-immunoprecipitation experiments showed that Que produced a decrease in NMDAR1 and α2δ-1 expression levels and interfered with α2δ-1 and NMDAR1 binding. In addition, the neural regulation mechanism of Que on antidepressant effect in PC12 cells knocked out α2δ-1 gene was further verified. Cellular experiments demonstrated that Que led to a reversal of up-regulation of NMDAR1 and α2δ-1 expression levels in corticosterone-injured PC12 cells, while Que had no effects on NMDAR1 expression in PC12 cells with the α2δ-1 gene knockout. Que has a good antidepressant effect and can significantly improve the depression-like behavior caused by CUMS. It exerts antidepressant effects by inhibiting the expression level of α2δ-1, interfering with the interaction between α2δ-1 and NMDAR, and then reducing the excitability of the HPA axis.

PFDN6 contributes to colorectal cancer progression via transcriptional regulation

ObjectiveColorectal cancer (CRC) is a common cancer worldwide. Although there are several treatments for cancer, the therapeutic effect on CRC remains unsatisfactory, and it is imperative to identify new therapeutic...

Atom-light interactions using optical nanofibres—a perspective

Complete control of light-matter interactions at a single quantum level is critical for quantum science applications such as precision measurement and information processing. Nanophotonic devices, developed with recent advancements in nanofabrication techniques, can be used to tailor the interactions between single photons and atoms. One example of such a nanophotonic device is the optical nanofibre, which provides an excellent platform due to the strongly confined transverse light fields, long interaction length, low loss, and diverse optical modes. This facilitates a strong interaction between atoms and guided light, revealing chiral atom-light processes and the prospect of waveguide quantum electrodynamics. This paper highlights recent advances, experimental techniques, and future perspectives of the optical nanofibre-atom hybrid quantum platform.

Characterizing Natural Frequencies of the Hybrid III and NOCSAE Headforms.

The vibrational characteristics of the Hybrid III and NOCSAE headforms are not well understood. It is hypothesized that they may perform differently in certain loading environments due to their structural differences; their frequency responses may differ depending on the impact characteristics. Short-duration impacts excite a wider range of headform frequencies than longer-duration (padded) impacts. While headforms generally perform similarly during padded head impacts where resonant frequencies are avoided, excitation of resonant frequencies during short-duration impacts can result in differences in kinematic measurements between headforms for the matched impacts. This study aimed to identify the natural frequencies of each headform through experimental modal analysis techniques. An impulse hammer was used to excite various locations on both the Hybrid III and NOCSAE headforms. The resulting frequency response functions were analyzed to determine the first natural frequencies. The average first natural frequency of the NOCSAE headform was 812Hz. The Hybrid III headform did not exhibit any natural frequencies below 1000Hz. Comparisons of our results with previous studies of the human head suggest that the NOCSAE headform's vibrational response aligns more closely with that of the human head, as it exhibits lower natural frequencies. This insight is particularly relevant for assessing head injury risk in short-duration impact scenarios, where resonant frequencies can influence the injury outcome.

Optimization of chemistry and process parameters for control of intermetallic formation in Mg sludges

Intermetallic formation in sludge during magnesium (Mg) melting, holding and high pressure die casting practices is a very important issue. But, very often it is overlooked by academia, original equipment manufacturers (OEM), metal ingot producers and even die casters. The aim of this study was to minimize the intermetallic formation in Mg sludge via the optimization of the chemistry and process parameters. The Al8Mn5 intermetallic particles were identified by the microstructure analysis based on the Al and Mn ratio. The design of experiment (DOE) technique, Taguchi method, was employed to minimize the intermetallic formation in the sludge of Mg alloys with various chemical compositions of Al, Mn, Fe, and different process parameters, holding temperature and holding time. The sludge yield (SY) and intermetallic size (IS) was selected as two responses. The optimum combination of the levels in terms of minimizing the intermetallic formation were 9 wt.% Al, 0.15 wt.%Mn, 0.001 wt.% (10 ppm) Fe, 690 °C for the holding temperature and holding at 30 mins for the holding time, respectively. The best combination for smallest intermetallic size were 9 wt.% Al, 0.15 wt.%Mn, 0.001 wt.% (10 ppm) Fe, 630 °C for the holding temperature and holding at 60 mins for the holding time, respectively. Three groups of sludge factors, Chemical Sludge (CSF), Physical Sludge (PSF) and Comprehensive Sludge Factors (and CPSF) were established for prediction of sludge yields and intermetallic sizes in Al-containing Mg alloys. The CPSF with five independent variables including both chemical elements and process parameters gave high accuracy in prediction, as the prediction of the PSF with only the two processing parameters of the melt holding temperature and time showed a relatively large deviation from the experimental data. The Chemical Sludge Factor was primarily designed for small ingot producers and die casters with a limited melting and holding capacity, of which process parameters could be fixed easily. The Physical Sludge Factor could be used for mass production with a single type of Mg alloy, in which the chemistry fluctuation might be negligible. In large Mg casting suppliers with multiple melting and holding furnaces and a number of Mg alloys in production, the Comprehensive Sludge Factor should be implemented to diminish the sludge formation.

Evaluation of student failure in higher education by an innovative strategy of fuzzy system combined optimization algorithms and AI

This research suggests two novel metaheuristic algorithms to enhance student performance: Harris Hawk's Optimizer (HHO) and the Earthworm Optimization Algorithm (EWA). In this sense, a series of adaptive neuro-fuzzy inference system (ANFIS) proposed models were trained using these methods. The selection of the best-fit model depends on finding an excellent connection between inputs and output(s) layers in training and testing datasets (e.g., a combination of expert knowledge, experimentation, and validation techniques). The study's primary result is a division of the participants into two performance-based groups (failed and non-failed). The experimental data used to build the models measured fourteen process variables: relocation, gender, age at enrollment, debtor, nationality, educational special needs, current tuition fees, scholarship holder, unemployment, inflation, GDP, application order, day/evening attendance, and admission grade. During the model evaluation, a scoring system was created in addition to using mean absolute error (MAE), mean squared error (MSE), and area under the curve (AUC) to assess the efficacy of the utilized approaches. Further research revealed that the HHO-ANFIS is superior to the EWA-ANFIS. With AUC = 0.8004 and 0.7886, MSE of 0.62689 and 0.65598, and MAE of 0.64105 and 0.65746, the failure of the pupils was assessed with the most significant degree of accuracy. The MSE, MAE, and AUC precision indicators showed that the EWA-ANFIS is less accurate, having MSE amounts of 0.71543 and 0.71776, MAE amounts of 0.70819 and 0.71518, and AUC amounts of 0.7565 and 0.758. It was found that the optimization algorithms have a high ability to increase the accuracy and performance of the conventional ANFIS model in predicting students' performance, which can cause changes in the management of the educational system and improve the quality of academic programs.

Radiological Modalities for the Assessment of Fetal Growth Restriction: A Comprehensive Review

Fetal growth restriction is a significant contributor to fetal morbidity and mortality. In addition, there are heightened maternal risks associated with surgical operations and their accompanying dangers. Monitoring fetal development is a crucial objective of prenatal care and effective methods for early diagnosis of Fetal growth restriction, allowing prompt management and timely intervention to improve the outcomes. Screening for Fetal growth restriction can be achieved via many modalities; it can be medical, biochemical, or radiological. Some recommended combining more than one for better outcomes. Currently, there is inconsistency about the best method of Fetal growth restriction screening. In this review, a comprehensive evaluation of the current radiological methods used for Fetal growth restriction, including serial growth scan, Doppler velocimetry, and biophysical profile is offered. Limitations, and potential enhancements area were specifically analyzing the effectiveness. Moreover, recently developed experimental radiological techniques were presented and how to integrate them into practice to enhance follow-up performance and results.

Analysis of Fluid Pressure Drop through a Globe Valve using Computational Fluid Dynamics and Statistical Techniques

Fluid mechanics plays a crucial role in everyday life, enabling the selection of accessories, materials, and various components essential for a system through which fluid flows. Pressure drop stands out as one of the most relevant factors in the design of fluid flow systems. However, analytical and experimental physical methods can increase these analyses' costs and time. Hence, in this study, statistical tools are employed to carry out specific experiments supported by numerical fluid simulation, aiming to comprehend the pressure drop behavior in a fluid as it passes through a globe valve. This valve, in turn, possesses distinct operating and manufacturing characteristics. The methods employed encompass a complete factorial system of response surface as support to construct the experimental design path through computational fluid dynamics. Among the key findings, it is demonstrated that, for systems with relatively low flow rates, the valve opening percentage does not exhibit a significant relationship with fluid pressure drop. Conversely, significant effects are observed for systems with relatively high flow rates regarding the valve opening percentage and pressure drop, reaching values of up to 73% pressure drop in this study. It can be inferred that the integration of statistical experimental design techniques and computational fluid dynamics constitutes a valuable resource for studying the pressure drop of a fluid passing through a system.

Model-free robust motion control for biological optical microscopy using time-delay estimation with an adaptive RBFNN compensator

The field of large numerical aperture microscopy has witnessed significant advancements in spatial and temporal resolution, as well as improvements in optical microscope imaging quality. However, these advancements have concurrently raised the demand for enhanced precision, extended range, and increased load-bearing capacity in objective motion carrier (OMC). To address this challenge, this study introduces an innovative OMC that employs a ball screw mechanism as its primary driving component. Furthermore, a robust nonlinear motion control strategy has been developed, which integrates fast nonsingular terminal sliding mode, experimental estimation techniques, and adaptive radial basis neural network, to mitigate the impact of nonlinear friction within the ball screw mechanism on motion precision. The stability of the closed-loop control system has been rigorously demonstrated through Lyapunov theory. Compared with other enhanced sliding mode control strategies, the maximum error and root mean square error of this controller are improved by 33% and 34% respectively. The implementation of the novel OMC has enabled the establishment of a high-resolution bio-optical microscope, which has proven its effectiveness in the microscopic imaging of retinal organoids.