Robust Method Research Articles

An improved robust identification method for position independent geometric errors of the swing axis of the gear grinding machine

An improved robust identification method for position independent geometric errors of the swing axis of the gear grinding machine

Live Single-Cell Transcriptional Dynamics in Plant Cells.

Transcriptional reprogramming plays a key role in a variety of biological processes. Recent advances in RNA imaging techniques have allowed to visualize, in vivo, transcription-related mechanisms in different organisms. The MS2 system constitutes a robust method that has been used for over two decades to image multiple steps of a transcript's life cycle from "birth to death" with high spatiotemporal resolution in the animal field. It is based on the high affinity binding of the MS2 bacteriophage coat protein to its RNA hairpin ligands. Despite its broad applicability, a limited number of studies have implemented the system in plants, but without exploiting its full potential. Here, we describe the transposition of the MS2 technique to Arabidopsis. Combined with microfluidics, it allows to visualize the transcriptional repression of a phosphate starvation induced gene (SPX1) upon phosphate refeeding in vivo. The system provided access to the transcriptional response kinetics of individual cells, gene expression heterogeneity, and revealed bursting phenomena in plantae. The described methods provide new insights for multiple applications.

Abstract B057: Base-error model (BEM) for improved detection of ctDNA in lymph samples of HPV-negative head and neck cancer patients

Abstract Introduction: Previously we demonstrated that ctDNA present in lymphatic exudate collected via surgical drains (“lymph”) outperformed plasma for detecting minimal residual disease (MRD) in head and neck squamous cell carcinoma (HNSCC) patients through a targeted sequencing (TS) approach. However, artifacts introduced during library preparation and sequencing remain challenges to sensitive low allelic fraction mutation detection. To enhance the performance of the TS approach, we characterized the background noise in lymph samples and developed a base-error model (BEM) that reduces sequencing artifacts and maximizes ctDNA signal. Methods: Lymph and blood were collected from 44 HPV-negative HNSCC patients postoperatively at 24 hours along with resected tumor. Cell-free DNA was extracted from lymph and sequenced using a custom TS panel with unique molecular identifiers (UMI). Somatic mutations were identified by tumor and blood exome sequencing (200x). Five patients had <2 mutations in tumor and were excluded. Two patients were censored due to lack of clinical data, yielding 17 patients with disease recurrence (REC) and 20 with no evidence of disease (NED) with >1 year of follow-up. Tumor-specific variants were force-called in lymph using a custom pipeline. A BEM of each tumor variant was built using a series of high-quality lymph reference samples to quantify the background noise. BEM was fit by Weibull distribution if more than 5 non-zero non-reference alleles were observed at a tumor variant position across the reference samples. Otherwise, Gaussian distribution was used to fit BEM. Force-called variants were considered artifacts if the variant allele fraction (VAF) was not greater than BEM cutoff controlled by false discovery rate. Patients were considered MRD positive if the mean VAF was greater than the estimated limit of detection. The Kaplan-Meier (KM) estimator with log-rank test and Cox proportional-hazards model were used for survival analyses. Results: Background noise was observed in reference lymph samples across all 12 nucleotide substitution classes. Out of 299 single nucleotide variants (SNVs), 94 were determined as artifacts by BEM. Among the artifacts, 77 were C/G to A/T mutations, indicating that the majority of recurrent background artifact in TS is likely the result of oxidative damage. The artifacts had VAFs ranging from 0.004% to 0.12% with median of 0.02%. Incorporation of BEM in lymph TS showed significantly improved specificity (sensitivity (SN) = 71%, specificity (SP) = 65%; p = 0.027, Hazard ratio (HR) = 3.07) compared to the same cohort without BEM (SN = 76%, SP = 30%, p = 0.60, HR = 1.34). Conclusions: BEM is a sensitive and robust method to improve ctDNA detection accuracy in TS. We demonstrated its utility in improving recurrence prediction in a HNSCC cohort. Given its advantages, we envision that BEM will prove useful as a general strategy for deep sequencing applications requiring precise digital quantification of low frequency alleles in TS. Citation Format: Zhuosheng Gu, Maciej Pacula, Seka Lazare, Noah Earland, Marra S. Francis, Adam Harmon, Megan Long, Aadel A. Chaudhuri, Jose P. Zevallos, Wendy Winckler. Base-error model (BEM) for improved detection of ctDNA in lymph samples of HPV-negative head and neck cancer patients [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr B057.

Abstract B074: Intrinsic subtypes in Ethiopian breast cancer patients: Implications for better care

Abstract Objective: The recent development of multi-gene assays for gene expression profiling has contributed significantly to the understanding of the clinically and biologically heterogeneous breast cancer (BC) disease. PAM50 is one of these assays used to stratify BC patients and individualize treatment. The present study was conducted to characterize PAM50-based intrinsic subtypes among Ethiopian BC patients. Patients and methods: Formalin-fixed paraffin- embedded tissues were collected from 334 BC patients who attended five different Ethiopian health facilities. All samples were assessed using the PAM50 algorithm for intrinsic subtyping. Results: The tumor samples were classified into PAM50 intrinsic subtypes as follows: 104 samples (31.1%) were luminal A, 91 samples (27.2%) were luminal B, 62 samples (18.6%) were HER2-enriched and 77 samples (23.1%) were basal-like. The intrinsic subtypes were found to be associated with clinical and histopathological parameters such as steroid hormone receptor status, HER2 status, Ki-67 proliferation index and tumor differentiation, but not with age, tumor size or histological type. An immunohistochemistry-based classification of tumors (IHC groups) was found to correlate with intrinsic subtypes. Conclusion: The distribution of the intrinsic subtypes confirms previous immunohistochemistry-based studies from Ethiopia showing potentially endocrine-sensitive tumors in more than half of the patients. Health workers in primary or secondary-level health care facilities can be trained to offer endocrine therapy to improve breast cancer care. Additionally, the findings indicate that PAM50-based classification offers a robust method for the molecular classification of tumors in the Ethiopian context. Citation Format: Zelalem Desalegn Woldesonbet, Meron Yohannes, Martin Porsch, Kathrin Stückrath, Endale Anberber, Pablo Santos, Marcus Bauer, Adamu Addissie, Yonas Bekuretsion, Mathewos Assefa, Yasin Worku, Lesley Taylor, Tamrat Abebe, Eva J Kantelhardt, Martina Vetter. Intrinsic subtypes in Ethiopian breast cancer patients: Implications for better care [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr B074.

PunctaFinder: an algorithm for automated spot detection in fluorescence microscopy images.

Fluorescence microscopy has revolutionised biological research by enabling the visualisation of subcellular structures at high resolution. With the increasing complexity and volume of microscopy data, there is a growing need for automated image analysis to ensure efficient and consistent interpretation. In this study, we introduce PunctaFinder, a novel Python-based algorithm designed to detect puncta, small bright spots, in raw fluorescence microscopy images without image denoising or signal enhancement steps. Furthermore, unlike other available spot detectors, PunctaFinder not only detects puncta, but also defines the cytoplasmic region, making it a valuable tool to quantify target molecule localisation in cellular contexts. PunctaFinder is a widely applicable punctum detector and size estimator, as evidenced by its successful detection of Atg9-positive vesicles, lipid droplets, aggregates of a destabilised luciferase mutant, and the nuclear pore complex. Notably, PunctaFinder excels in detecting puncta in images with a relatively low resolution and signal-to-noise ratio, demonstrating its capability to identify dim puncta and puncta of dynamic target molecules. PunctaFinder reliably detects puncta in fluorescence microscopy images where automated analysis was not possible before, providing researchers with an efficient and robust method for punctum quantification in fluorescence microscopy images.

Optimized Scintillation Imaging in low dose rate and bright room light conditions.

To develop a robust method for non-contact surface dosimetry during Total Body Irradiation (TBI) that uses an optimally paired choice of scintillator material with camera photocathode and can work insensitively to the normal ambient room lighting conditions (~500 Lux). 
Approach: This goal was approached by assessing the emission contrast of scintillator signal to background room ratio (SBR) detected by the camera, in the challening conditions of low dose rate TBI with high room lights. A total of 9 fast-response scintillators, 3 wavelength shifters, and 2 camera photocathodes were systematically tested to determine the optimal combination. The effects of room lights on the scintillator signal and the background signal were assessed to avoid signal saturation while retaining accurate dose measurement. A bandpass wavelength filter was then applied to reduce the effects on room lights and scintillator signal.
Main Results: One scintillator (EJ262) combined with a blue-green sensitive photocathode camera and a 500nm band pass filter produced the greatest available scintillator SBR of 95 with maximal room lights on. The caveat is that this design rejects all patient Cherenkov light, which can be useful for visualizing the patient treatment. Another option which retained the Cherenkov signal but produced less available scintillator signal was found with another scintillator (EJ-260) and a red photocathode camera with SBR of 35, but a narrow bandpass filter is required to make it work in ambient room lights, which addition will also remove most of the Cherenkov signal. 
Significance: Non-contact scintillator imaging can be used for surface dosimetry in TBI with appropriate pairing of scintillator emission spectrum and camera photocathode sensitivity or optical filtering range.&#xD.

Chromatographic analysis of ponatinib and its impurities: method development, validation, and identification of new degradation product

BackgroundPonatinib, a third-generation tyrosine kinase inhibitor, is employed in the management of adult chronic myeloid leukemia. Nevertheless, the presence of process impurities and degradation impurities linked to ponatinib may potentially influence its effectiveness and safety. Therefore, the objective of this research was to establish a robust liquid chromatography method and systematically validate it for the detection of substances related to ponatinib.MethodsThe separation of ponatinib and its impurities was conducted using an Agilent 5HC-C18 chromatographic column (4.6 mm × 250 mm, 5 μm). The mobile phase A comprised a mixture of water and acetonitrile in a 9:1 ratio, with an aqueous solution of pH 2.4 containing 2 mM potassium dihydrogen phosphate and 0.4% triethylamine. Mobile phase B, consisting of acetonitrile, was eluted in a gradient fashion. The flow rate was set at 1.0 mL/min, detection wavelength at 250 nm, column temperature at 40°C, and injection volume at 10 μL.ResultsThe method demonstrated high specificity, sensitivity, solution stability, linearity, precision, accuracy, and robustness. Additionally, this research unveiled a novel compound, imp-B, generated via the oxidative degradation of ponatinib. The molecular structure of the newly discovered product was elucidated through the utilization of nuclear magnetic resonance (NMR) and high-resolution mass spectrometry (HRMS).ConclusionIn conclusion, the chromatographic method developed in this study has the potential to be utilized for the detection of ponatinib and its impurities, thereby offering significant insights for quality assessment in ponatinib research.

High-Throughput Measurement of Single-Fission Yeast Cell Volume Using Fluorescence Exclusion.

Cell volume is a critical parameter for the biology of living species and has an impact on virtually all cellular functions. In Schizosaccharomyces pombe, the regulation of cell size has been the focus of intense investigation, and mechanisms that couple size control with cell cycle progression have been identified. In fission yeast, cell length at division is generally used as a proxy for determining cell size. However, it only allows for an inaccurate evaluation of this critical parameter and neglects potential changes in cell morphology and diameter, which can strongly impact cell volume. Until recently, one of the major obstacles for studying the complexity of cell size regulation in fission yeast has been the lack of a robust method for high-throughput, direct measurement of single-cell volume. Here, we provide a comprehensive protocol for S. pombe cell volume determination based on the Fluorescence eXclusion method and microfluidics technologies. This approach makes it possible to reliably describe cell volume and its distribution in populations of fission yeast cells.

Advancing Parameter Estimation in Differential Equations: A Hybrid Approach Integrating Levenberg–Marquardt and Luus–Jaakola Algorithms

This study presents an integrated approach that combines the Levenberg–Marquardt (LM) and Luus–Jaakola (LJ) algorithms to enhance parameter estimation for various applications. The LM algorithm, known for its precision in solving non-linear least squares problems, is effectively paired with the LJ algorithm, a robust stochastic optimization method, to improve accuracy and computational efficiency. This hybrid LM-LJ methodology is demonstrated through several case studies, including the optimization of MESH equations in distillation processes, modeling controlled diffusion in biopolymer films, and analyzing heat and mass transfer during the drying of cylindrical quince slices. By overcoming the convergence issues typical of gradient-based methods and performing global searches without initial parameter bounds, this approach effectively handles complex models and closely aligns simulation results with experimental data. These capabilities highlight the versatility of this approach in engineering and environmental modeling, significantly enhancing parameter estimation in systems governed by differential equations.

DDEL-18. OPTIMIZED METHOD TO QUANTIFY TTFIELDS-INDUCED PERMEABILIZATION OF CELL MEMBRANES

Abstract Tumor Treating Fields (TTFields) therapy is FDA-approved for glioblastoma. Using plate-based readouts of FITC-dextran fluorescent probes in U87 human glioblastoma cells, we previously reported increased uptake of FITC-dextrans (4-20kDa) post-TTFields exposure. However, this approach is unable to distinguish FITC-dextran uptake in live-vs-dead cells post-TTFields exposure. We demonstrate flow cytometry (FC) as a more robust and economical method to quantify the amount of FITC-dextrans entering the cells. We first identified the optimal [FITC-dextran] for the FC-based approach (titration 0-6.5mg/mL). Cells were then seeded onto coverslips and exposed to 200kHz TTFields, 1-3V/cm peak-to-peak (inovitro systemTM, Novocure), or no-TTFields (control), for 24-72h. Cells were harvested and stained for 1h using 4kDa or 20kDa FITC-dextrans. Cells were washed and analyzed by FC for mean±SD fluorescence intensity, and compared by unpaired t-test. Dead cells were excluded using propidium iodide staining. In the control vs. TTFields group, 4kDa FITC-dextrans had significantly increased uptake at 24h (4.9±0.3 vs. 8.0±1.7, p=0.01), 48h (6.5±0.2 vs. 8.3±1.0, p=0.01), and 72h (5.7±0.3 vs. 8.8±1.0, p=0.001). Likewise, in the TTFields group, the 20kDa FITC-dextrans had significantly increased uptake at 24h (5.6±0.3 vs. 7.5±0.9, p=0.006), 48h (4.8±0.3 vs. 6.6±0.8, p=0.006), and 72h (5.3±0.2 vs. 11.3±2.6, p=0.004). In the TTFields group, the 20kDa FITC-dextrans had significantly increased uptake between the 24h and 72h timepoints (p=0.03). The FC-based method utilized 0.36mg of FITC-dextrans/sample, much less compared to the 1-3mg recommended for plate-based methods. Another advantage of the FC-based method was exclusion of the dead cell population after TTFields exposure. We validated a FC-based-method that is economical and can reproducibly quantify the membrane permeabilization induced by TTFields. Compared to control conditions, TTFields increase membrane permeabilization of cells that remain alive after TTFields exposure, in a time-dependent manner for the 20kDa probe.

A General Approach for Metal Nanoparticle Encapsulation Within Porous Oxides.

Encapsulation of metal nanoparticles within oxide materials has been shown as an effective strategy to improve activity, selectivity, and stability in several catalytic applications. Several approaches have been proposed to encapsulate nanoparticles, such as forming core-shell structures, growing ordered structures (zeolites or metal-organic frameworks) on nanoparticles, or directly depositing support materials on nanoparticles. Here, a general nanocasting method is demonstrated that can produce diverse encapsulated metal@oxide structures with different compositions (Pt, Pd, Rh) and multiple types of oxides (Al2O3, Al2O3-CeO2, ZrO2, ZnZrOx, In2O3, Mn2O3, TiO2) while controlling the size and dispersion of nanoparticles and the porous structure of the oxide. Metal@polymer structures are first prepared, and then the oxide precursor is infiltrated into such structures and the resulting material is calcined to form the metal@oxide structures. Most Pt@oxides catalysts show similar catalytic activity, demonstrating the availability of surface Pt sites in the encapsulated structures. However, the Pt@Mn2O3 sample showed much higher CO oxidation activity, while also being stable under aging conditions. This work demonstrated a robust nanocasting method to synthesize metal@oxide structures, which can be utilized in catalysis to finely tune metal-oxide interfaces.

DGNMDA: Dual Heterogeneous Graph Neural Network Encoder for miRNA-Disease Association Prediction

In recent years, numerous studies have highlighted the pivotal importance of miRNAs in personalized healthcare, showcasing broad application prospects. miRNAs hold significant potential in disease diagnosis, prognosis assessment, and therapeutic target discovery, making them an integral part of precision medicine. They are expected to enable precise disease subtyping and risk prediction, thereby advancing the development of precision medicine. GNNs, a class of deep learning architectures tailored for graph data analysis, have greatly facilitated the advancement of miRNA-disease association prediction algorithms. However, current methods often fall short in leveraging network node information, particularly in utilizing global information while neglecting the importance of local information. Effectively harnessing both local and global information remains a pressing challenge. To tackle this challenge, we propose an innovative model named DGNMDA. Initially, we constructed various miRNA and disease similarity networks based on authoritative databases. Subsequently, we creatively design a dual heterogeneous graph neural network encoder capable of efficiently learning feature information between adjacent nodes and similarity information across the entire graph. Additionally, we develop a specialized fine-grained multi-layer feature interaction gating mechanism to integrate outputs from the neural network encoders to identify novel associations connecting miRNAs with diseases. We evaluate our model using 5-fold cross-validation and real-world disease case studies, based on the HMDD V3.2 dataset. Our method demonstrates superior performance compared to existing approaches in various tasks, confirming the effectiveness and potential of DGNMDA as a robust method for predicting miRNA-disease associations.

FastSLAM-MO-PSO: A Robust Method for Simultaneous Localization and Mapping in Mobile Robots Navigating Unknown Environments

In the realm of mobile robotics, the capability to navigate and map uncharted territories is paramount, and Simultaneous Localization and Mapping (SLAM) stands as a cornerstone technology enabling this capability. While traditional SLAM methods like Extended Kalman Filter (EKF) and FastSLAM have made strides, they often struggle with the complexities of non-linear dynamics and non-Gaussian noise, particularly in dynamic settings. Moreover, these methods can be computationally intensive, limiting their applicability in real-world scenarios. This paper introduces an innovative enhancement to the FastSLAM framework by integrating Multi-Objective Particle Swarm Optimization (MO-PSO), aiming to bolster the robustness and accuracy of SLAM in mobile robots. We outline the theoretical underpinnings of FastSLAM and underscore its significance in robotic autonomy for mapping and exploration. Our approach innovates by crafting a specialized fitness function within the MO-PSO paradigm, which is instrumental in optimizing the particle distribution and addressing the challenges inherent in traditional particle filtering methods. This strategic fusion of MO-PSO with FastSLAM not only circumvents the pitfalls of particle degeneration, but also enhances the overall robustness and precision of the SLAM process across a spectrum of operational environments. Our empirical evaluation involves testing the proposed method on three distinct simulation benchmarks, comparing its performance against four other algorithms. The results indicate that our MO-PSO-enhanced FastSLAM method outperforms the traditional particle filtering approach by significantly reducing particle degeneration and ensuring more reliable and precise SLAM performance in challenging environments. This research demonstrates that the integration of MO-PSO with FastSLAM is a promising direction for improving SLAM in mobile robots, providing a robust solution for accurate mapping and localization even in complex and unknown settings.

Improved extraction efficiency of radioactive copper produced via accelerator neutrons method through phosphate buffer-enhanced column pre-treatment

We report a straightforward and robust method for isolating medical copper radioisotopes 64Cu and 67Cu, generated by an accelerator neutrons technique from natZn(n, x). This study reveals the key role of a phosphate buffer pre-treatment of the cation exchange column in the separation process. Incorporating the phosphate buffer into the column pre-treatment markedly enhances the retention of copper isotopes within the column throughout the separation procedure. This approach yields a remarkably high-purity radioactive copper sample with a high extraction efficiency of 94.4 (1.5) % of the initially produced copper, all within a relatively short experimental timeframe of approximately 5 h for 100 g of starting material. This single-step separation scheme is reproducible across a range of starting material target sizes, from small (10 g) to large (100 g). The copper radioisotopes obtained are suitable for use in pre-clinical studies. Thus, this approach offers a more effective means for routine preparation of copper radioisotopes.

Fault diagnosis of hydro-turbine runner based on improved masking signal method incorporate RLMD

Sediment erosion and foreign object impacts can cause irreversible damage to hydro-turbine runner. It is proposed to use the Improved Masked Signal method combined with the Robust Local Mean Decomposition method (IMS-RLMD) to denoise the acoustic vibrational signals collected from the hydro-turbine runner under normal operating condition, sediment-landed water flow condition, and foreign object impact condition. The IMS method reduces modal aliasing, which is easily occurred in the RLMD decomposition method, and achieves excellent signal denoised by efficiently screening the components. To validate the effectiveness of IMS-RLMD method, we use the Support Vector Machine optimized by the Grey Wolf algorithm (GWO-SVM) to identify the acoustic vibrational signals denoised by different methods. The accuracy of signal set processed by the IMS-RLMD method is 96.67 %, and the accuracy of original signal set and the signal set processed by the EMD, LMD, RLMD and VMD methods are 66.67 %, 75 %, 78.3 %, 86.67 % and 90 %. This result shows that the IMS-RLMD method is not only more suitable for denoising hydro-turbine acoustic vibrational signals, but also retains more effective features in the signals. Meanwhile, the LSTM and CNN models are set as the control group, and the identification results show that the identification method, GWO-SVM, and the denoising method, IMS-RLMD, are the best adapted solutions. Furthermore, it is found that the frequency spectrum of the acoustic vibrational signals changes significantly when foreign objects are washed into the runner or when sediment-landed water flow through the runner. This study provides an effective reference for the daily condition monitoring method of hydropower units and a valuable addition to the condition monitoring and fault diagnosis system of hydro-turbine.

Enhancing carbamazepine degradation in electrochemical systems: The interplay of sulfur vacancies and absorbed peroxydisulfate in molybdenite electrodes

Achieving high reaction efficiency with low energy input is crucial for electrochemical water remediation processes, yet remains a significant challenge. This study reported a practicable method, utilizing natural molybdenite as particle electrodes in an electro-activated peroxydisulfate (PDS) process (3D system) to develop a cost-efficient electrocatalytic oxidation system. Molybdenite’s unique ability to generate sulfur vacancies during electrocatalysis significantly enhances system efficiency. The 3D system enhanced the rate constant of carbamazepine (CBZ) abatement sixfold compared to the system without molybdenite. Additionally, a substantial decrease in electrical energy per order (EE/O) from 7.13 kWh/m3 to 0.326 kWh/m3 indicates a near 22-fold increase in energy efficiency. Characterizations involving electron microscopies, electrochemical experiments and density functional theory calculations confirm that hydroxyl radicals (•OH) and adsorbed PDS(PDS*) are the main active species. Molybdenite’s surface with plenty of edge-S, released S vacancy during electrocatalytic oxidation, providing adsorption and activation sites for PDS and H2O. This led to more active sites and facilitating the generation of PDS*, lowering the energy barrier for •OH formation and boosting the oxidation performance of the 3D system. The results underscore the constructed 3D system is a robust and energy-efficient method for practical water treatment.

Novel Gene Biomarkers Specific to Human Mesenchymal Stem Cells Isolated from Bone Marrow

In this paper, we present a comparative analysis of the transcriptomic profile of three different human cell types: hematopoietic stem cells (HSCs), bone marrow-derived mesenchymal stem cells (MSCs) and fibroblasts (FIBs). The work aims to identify unique genes that are differentially expressed as specific markers of bone marrow-derived MSCs, and to achieve this undertakes a detailed analysis of three independent datasets that include quantification of the global gene expression profiles of three primary cell types: HSCs, MSCs and FIBs. A robust bioinformatics method, called GlobalTest, is used to assess the specific association between one or more genes expressed in a sample and the outcome variable, that is, the ‘cell type’ provided as a single univariate response. This outcome variable is predicted for each sample tested, based on the expression profile of the specific genes that are used as input to the test. The precision of the tests is calculated along with the statistical sensitivity and specificity for each gene in each dataset, yielding four genes that mark MSCs with high accuracy. Among these, the best performer is the protein-coding gene Transgelin (TAGLN, Gene ID: 6876) (with a Positive Predictive Value > 0.96 and FDR < 0.001), which identifies MSCs better than any of the currently used standard markers: ENG (CD105), THY1 (CD90) or NT5E (CD73). The results are validated by RT-qPCR, providing novel gene biomarkers specific for human MSCs.

A robust numerical method for the generation and propagation of periodic finite-amplitude internal waves in natural waters using high-accuracy simulations

Abstract. The design and implementation of boundary conditions for the robust generation and simulation of periodic finite-amplitude internal waves is examined in a quasi two-layer continuous stratification using a spectral-element-method-based incompressible flow solver. The commonly used Eulerian approach develops spurious, and potentially catastrophic small-scale numerical features near the wave-generating boundary in a non-linear stratification when the parameter A/(δc) is sufficiently larger than unity; A and δ are measures of the maximum wave-induced vertical velocity and pycnocline thickness, respectively, and c is the linear wave propagation speed. To this end, an Euler–Lagrange approach is developed and implemented to generate robust high-amplitude periodic deep-water internal waves. Central to this approach is to take into account the wave-induced (isopycnal) displacement of the pycnocline in both the vertical and (effectively) upstream directions. With amplitudes not restricted by the limits of linear theory, the Euler–Lagrange-generated waves maintain their structural integrity as they propagate away from the source. The advantages of the high-accuracy numerical method, whose minimal numerical dissipation cannot damp the above near-source spurious numerical features of the purely Eulerian case, can still be preserved and leveraged further along the wave propagation path through the robust reproduction of the non-linear adjustments of the waveform. The near- and far-source robustness of the optimized Euler–Lagrange approach is demonstrated for finite-amplitude waves in a sharp quasi two-layer continuous stratification representative of seasonally stratified lakes. The findings of this study provide an enabling framework for two-dimensional simulations of internal swash zones driven by well-developed non-linear internal waves and, ultimately, the accompanying turbulence-resolving three-dimensional simulations.

A customizable and low-cost 3D-printed transwell device coupled with 3D cell culture for permeability assay

The permeability-based assay is commonly used to assess intestinal barrier function, and it relies on using a transwell insert as an essential compartment. The device consists of a semipermeable membrane that is attached at the bottom of the insert and splits the system into the apical and basolateral compartments. However, commercial inserts are standardized with different pore sizes based on the application and offer only a flat plane of two-dimensional cell culture. Herein, we present a simple, low-cost 3D-printed transwell device and a robust method to functionalize the inserts for paper-based 3D cell culture. This 3D-printed device was fabricated from a polylactic acid (PLA) filament, and a paper membrane used to support HT-29 cells for intestinal permeability assessment. A device showed good biocompatibility when culturing HT-29 cells for 48 and 72 h with 97 % and 98 % cell viability, respectively. Together with fluorescence images, cells were attached directly to the microfiber networks of a Matrigel-functionalized paper, indicating that the functionalized paper is biocompatible and bioactive. Furthermore, in a more appropriate culture microenvironment, SEM analyses revealed cellular features differentiating into mucus-secreting cells, evidenced by the formation of microvilli on the cell surface, which was further confirmed by immunofluorescence staining of villin-1. To demonstrate the usability of the 3D-printed transwell device, intestinal permeability was assessed using both chemical and biological stimulation treatments. The permeability results employing FITC-dextran validated the association between a different level of relative fluorescence intensity unit (RFU) and the orange color of live cells by CellTrackerTM. As a result, this 3D-printed transwell device provides a straightforward and cost-effective method for manufacturing a device for customization in many laboratory settings, making it a feasible alternative to marketed transwell devices that do not allow for customization.

Binocular camera-based visual localization with optimized keypoint selection and multi-epipolar constraints

In recent years, visual localization has gained significant attention as a key technology for indoor navigation due to its outstanding accuracy and low deployment costs. However, it still encounters two primary challenges: the requirement for multiple database images to match the query image and the potential degradation of localization precision resulting from the keypoints clustering and mismatches. In this research, a novel visual localization framework based on a binocular camera is proposed to estimate the absolute positions of the query camera. The framework integrates three core methods: the multi-epipolar constraints-based localization (MELoc) method, the Optimal keypoint selection (OKS) method, and a robust measurement method. MELoc constructs multiple geometric constraints to enable absolute position estimation with only a single database image, while OKS and the robust measurement method further enhance localization accuracy by refining the precision of these geometric constraints. Experimental results demonstrate that the proposed system consistently outperforms existing visual localization systems across various scene scales, database sampling intervals, and lighting conditions