Accurate Capture Research Articles

RenderBench: The CPU Rendering Benchmark Suite Based on Microarchitecture-Independent Characteristics

This research addresses the issue of evaluating CPU rendering performance by introducing the innovative benchmark test suite construction method RenderBench. This method combines CPU microarchitecture features with rendering task characteristics to comprehensively assess CPU performance across various rendering tasks. Adhering to principles of representativeness and comprehensiveness, the constructed benchmark test suite encompasses diverse rendering tasks and scenarios, ensuring accurate capture of CPU performance features. Through data sampling and in-depth analysis, this study focuses on the role of microarchitecture-independent features in rendering programs, including instruction-level parallelism, instruction mix, branch prediction capability, register dependency distance, data flow stride, and memory reuse distance. The research findings reveal significant variations in rendering programs across these features. For instance, in terms of instruction-level parallelism, rendering programs demonstrate a high level of ILP (instruction-level parallelism), with an average value of 5.70 for ILP256, surpassing benchmarks such as Mibench and NAS Parallel Benchmark. Furthermore, in aspects such as instruction mix, branch prediction capability, register dependency distance, data flow stride, and memory reuse distance, rendering programs exhibit distinct characteristics. Through the application of the RenderBench method, a scalable and highly representative benchmark test suite was constructed, facilitating an in-depth exploration of CPU performance bottlenecks in rendering tasks. By delving into microarchitecture-independent features, this study provides profound insights into rendering program performance, offering valuable guidance for optimizing CPU rendering performance. The application of ensemble learning models, such as random forest, XGBoost, and ExtraTrees, reveals the significant influence of features like floating-point computation, memory access patterns, and register usage on CPU rendering program performance. These insights not only offer robust guidance for performance optimization but also underscore the importance of feature selection and algorithm choice. In summary, the results of feature importance ranking in this study provide beneficial directions and deep insights for the optimization and enhancement of CPU rendering program performance. These findings are poised to exert a positive impact on future research and development endeavors.

A three-dimensional fully threaded tree adaptive mesh phase-field lattice Boltzmann method for gas–liquid phase change problems

A fully threaded tree adaptive mesh lattice Boltzmann method based on the phase-field model with the conservative Allen–Cahn equation is presented for the simulation of multiphase flows and heat transfer, especially the gas–liquid phase change problems in three dimensions. The presented model incorporates the conservative Allen–Cahn equation for interface tracking and employs hydrodynamics and temperature evolution D3Q19 lattice Boltzmann equations to recover the corresponding Navier–Stokes equations and energy equations. The gas–liquid phase change at the phase interface can be reflected with introducing the mass production rate in the lattice Boltzmann evolution equations. With the fully threaded tree adaptive mesh implemented to capture the phase interface, the computational efficiency can obviously be raised while ensuring the accurate capture of gas–liquid interface. The present method is used to reproduce several classical benchmarks, namely, the droplet evaporation in superheated gas, the buoyancy-driven bubble rising in viscous liquid, the 3-dimensional Rayleigh Taylor instability problem, the nucleate boiling on a wall with constant temperature, and the film boiling on superheated bottom.

Novel experimental technique to evaluate soil thermal conductivity in a transient state

novel experimental technique to evaluate soil thermal conductivity in a transient state

The Phygital Evolution

This contribution examines the results of a research project on collaborations between the audiovisual industry and the textile and fashion sector in the city of Prato, experimenting with new relationships between the physical and digital dimensions. The main purpose of the project was the production of content for the textile manufacturing industry using innovative media production technologies such as 3D, animation, etc., transmitted through 5G network infrastructure. Specifically, the project focused on significant archives of the Prato textile district through a process of digitizing fabrics using productive reverse engineering techniques. This allowed for obtaining a digital representation of existing fabrics, preserving and enhancing the traditional textile heritage in a digital format. The use of advanced techniques enabled the accurate capture of fabric characteristics and properties, facilitating the creation of 3D models and their manipulation through media production technologies.

Maintenance Treatment for Metastatic Pancreatic Cancer: Balancing Therapeutic Intensity with Tolerable Toxicity.

Metastatic pancreatic ductal adenocarcinoma is typically treated with multi-agent chemotherapy until disease progression or intolerable cumulative toxicity. For patients whose disease shows ongoing control or response beyond a certain timeframe (≥3-4 months), options include pausing chemotherapy with close monitoring or de-escalating to maintenance therapy with the goal of prolonging progression-free and overall survival while preserving quality of life. There is currently no universally accepted standard of care and a relative dearth of randomized clinical trials in the maintenance setting. Conceptually, such therapy can entail continuing the least toxic components of a first-line regimen and/or introducing novel agent(s) such as the poly(ADP-ribose) polymerase inhibitor olaparib, which is presently the only approved drug for maintenance treatment and is limited to a genetically defined subset of patients. In addition to identifying new therapeutic candidates and combinations in the maintenance setting, including targeted agents and immunotherapies, future research should focus on better understanding this unique biologic niche and how treatment in the maintenance setting may be distinct from resistant/refractory disease; identifying molecular predictors for more effective pairing of specific treatments with patients most likely to benefit; and establishing patient-reported outcomes in clinical trials to ensure accurate capture of quality of life metrics.

Heterogeneous temporal representation for diabetic blood glucose prediction.

Background and aims: Blood glucose prediction (BGP) has increasingly been adopted for personalized monitoring of blood glucose levels in diabetic patients, providing valuable support for physicians in diagnosis and treatment planning. Despite the remarkable success achieved, applying BGP in multi-patient scenarios remains problematic, largely due to the inherent heterogeneity and uncertain nature of continuous glucose monitoring (CGM) data obtained from diverse patient profiles. Methodology: This study proposes the first graph-based Heterogeneous Temporal Representation (HETER) network for multi-patient Blood Glucose Prediction (BGP). Specifically, HETER employs a flexible subsequence repetition method (SSR) to align the heterogeneous input samples, in contrast to the traditional padding or truncation methods. Then, the relationships between multiple samples are constructed as a graph and learned by HETER to capture global temporal characteristics. Moreover, to address the limitations of conventional graph neural networks in capturing local temporal dependencies and providing linear representations, HETER incorporates both a temporally-enhanced mechanism and a linear residual fusion into its architecture. Results: Comprehensive experiments were conducted to validate the proposed method using real-world data from 112 patients in two hospitals, comparing it with five well-known baseline methods. The experimental results verify the robustness and accuracy of the proposed HETER, which achieves the maximal improvement of 31.42%, 27.18%, and 34.85% in terms of MAE, MAPE, and RMSE, respectively, over the second-best comparable method. Discussions: HETER integrates global and local temporal information from multi-patient samples to alleviate the impact of heterogeneity and uncertainty. This method can also be extended to other clinical tasks, thereby facilitating efficient and accurate capture of crucial pattern information in structured medical data.

Facile preparation of Ru nanoassemblies for electrochemical immunoassay of carcinoembryonic antigen in clinical serum

Abnormal expression of carcinoembryonic antigen (CEA) can be used for early diagnosis of various cancers (e.g. colorectal cancer, cervical carcinomas, and breast cancer). In this work, using l-cysteine-ferrocene-ruthenium nanocomposites (L-Cys-Fc-Ru) to immobilize secondary antibody (Ab2) and Au nanoparticles (NPs) as the substrate to ensure accurate capture of primary antibody (Ab1), a signal-on sandwich-like biosensor was constructed in the presence of CEA. Specifically, Ru nanoassemblies (NAs) were first prepared by a facile one-step solvothermal approach as signal amplifiers for the electrical signal of Fc. Based on specific immune recognition, as the increase of CEA concentration, the content of L-Cys-Fc-Ru-Ab2 captured on the electrode surface also increased, thus the signal of Fc gradually increased. Therefore, the quantitative detection of CEA can be realized according to the peak current of Fc. After a series of experiments, it was found that the biosensor has a wide detection range from 1.0 pg mL−1 to 100.0 ng mL−1 and a low detection limit down to 0.5 pg mL−1, as well as good selectivity, repeatability and stability. Furthermore, satisfactory results were also obtained for the determination of CEA in serums, which were comparable to commercial electrochemiluminescence (ECL) method. The developed biosensor shows great potential in clinical applications.

A FLEXIBLE WORKFLOW FOR MULTIMODAL 3D IMAGING OF VAULTED PAINTED CEILINGS IN HIGH DETAIL

Abstract. 3D imaging is an increasingly common tool for the investigation of cultural heritage. Painted ceilings offer particular challenges as the art historical requirements necessitate highly detailed and accurate capture of colour textures with sub-millimetre resolution, even of large areas of 100s of square metres, situated in a wide variety of building environments. Geometrical information is also required to represent fully the three-dimensional nature of these sculpted and vaulted ceilings, again at the resolution necessary for both documentation and use by cultural heritage professionals including conservators, restorers, building researchers, architects and art historians. This paper describes a multi-modal campaign of 3D digitisation of three very different sites undertaken as part of the Franco-German Plafond 3D project. We introduce a flexible and adaptable methodology that allows the detailed imaging of large interiors and ceiling paintings in a short period of time and with varying levels of access.

The role of strength distributions for premature creep failure

Premature and unexpected creep damage is a significant concern in high-temperature engineering. Identifying outliers in creep rupture data is essential for assessing the risk of premature creep failure. This study proposes a new method to evaluate premature creep failure using log-logistic distribution fit of prediction errors and outlier positions. Fitting results for seven different alloys were obtained from extrapolation procedures using soft-constrained machine learning algorithms (SCMLAs) and constrained time-temperature parameters (TTPs) based on prior research. A comprehensive statistical analysis was conducted for all materials. The log-logistic distribution was validated as a suitable method for fitting prediction error distributions. Regression plots demonstrate effective residual balance and accurate outlier capture. The best fitting methods were identified based on the width of the distributions. Outlier positions were used to evaluate the probability of premature creep failure quantitatively. For example, a 0.5% probability of observing creep rupture strengths that are approximately 50% lower than the standardized creep stress was found for TP316H, T321H, and high Cr steels SUH616B. These findings offer valuable insights for estimating premature creep failure in materials.

Defining challenging areas of the preparation finish line by using an open-source 3D modeling computer program: A tip to simplify margin identification by the dental laboratory technician

Intraoral data acquisition and computer-aided design and computer-aided manufacturing (CAD-CAM) systems have simplified and expedited the fabrication of dental prostheses. 1 Van Noort R. The future of dental devices is digital. Dent Mater. 2012; 28: 3-12 Crossref PubMed Scopus (801) Google Scholar ,2 Giuliodori G. Rappelli G. Aquilanti L. Intraoral scans of full dental arches: an in vitro measurement study of the accuracy of different intraoral scanners. Int J Environ Res Public Health. 2023; 20: 4776 Crossref Scopus (0) Google Scholar Contemporary dental CAD-CAM provides the freedom to design and fabricate diverse dental devices, including custom impression trays, surgical templates, and removable and fixed dental prostheses. 1 Van Noort R. The future of dental devices is digital. Dent Mater. 2012; 28: 3-12 Crossref PubMed Scopus (801) Google Scholar ,3 Revilla-León M. Özcan M. Additive manufacturing technologies used for processing polymers: current status and potential application in prosthetic dentistry. J Prosthodont. 2019; 28: 146-158 Crossref PubMed Scopus (217) Google Scholar ,4 Turkyilmaz I. Wilkins G.N. Varvara G. Tooth preparation, digital design and milling process considerations for CAD/CAM crowns: understanding the transition from analog to digital workflow. J Dent Sci. 2021; 16: 1312-1314 Crossref Scopus (8) Google Scholar These dental appliances are created from a digital file that recreates the surface geometry of the target object, typically a standard tessellation language (STL) file. 5 Grant G.T. Campbell S.D. Masri R.M. Andersen M.R. The American college of prosthodontist digital dentistry glossary development task force. Glossary of digital terms. J Prosthodont. 2016; 25: S2-S9 Crossref PubMed Scopus (27) Google Scholar A prerequisite for accurate manufacture is the exact capture and identification of the fine details in the target intraoral structures. An accurate capture can be challenging when the preparation finish line is subgingival, when abundant bleeding or salivation occurs, or when operator scanning skills and speed are still developing. 6 Mangano F. Gandolfi A. Luongo G. Logozzo S. Intraoral scanners in dentistry: a review of the current literature. BMC Oral Health. 2017; 17: 149 Crossref PubMed Scopus (308) Google Scholar Additionally, the location of fine details can be challenging for the dental laboratory technician to visualize when the CAD file is outsourced for the manufacture of the definitive restoration, since STL files lack attributes such as color and texture. 5 Grant G.T. Campbell S.D. Masri R.M. Andersen M.R. The American college of prosthodontist digital dentistry glossary development task force. Glossary of digital terms. J Prosthodont. 2016; 25: S2-S9 Crossref PubMed Scopus (27) Google Scholar These features help differentiate the tooth from its surrounding tissues when finish lines are subgingival or when displacement is limited. The present article presents a straightforward workflow that defines challenging areas of the preparation finish line by using an open-source 3D modeling computer program. This procedure can be used to communicate the finish line observed to the dental laboratory technician when STL files are used to design the definitive restoration and stops the technician guessing the finish line, since the hard-to-see areas are defined by the clinician. Additionally, this approach has advantages over the margin tracing and sculpting tools available in most 3-dimensional (3D) CAD computer programs since it allows selecting the critical areas around the finish line considering the mesh geometry of the 3D file. Visualizing the 3D mesh permits a more precise selection, which can minimize distortion as even the smallest changes in the mesh surface can be observed if transformation or sculpting procedures are used.

A mass-preserving level set method for simulating 2D/3D fluid flows with deformed interface

This research paper focuses on the development of a novel interface-capturing solver for predicting two-phase flow in 2D/3D Cartesian meshes within the framework of Eulerian approaches. The primary objective is to ensure mass conservation and accurate capture of interface topology. To achieve this, a mass-preserving level set advection equation formulated as a scalar sign-distance function is proposed. The key innovation of the Eulerian solver lies in the incorporation of a scalar speed function for robust reconstruction of the classical level set equation. The effectiveness and reliability of the proposed flow solver in solving incompressible two-phase viscous flow equations are demonstrated through several benchmark problems.

Online monitoring instantaneous 2D temperature distributions in a furnace using acoustic tomography based on frequency division multiplexing

The online and accurate capture of dynamic changes in furnace temperature distribution is crucial for production efficiency improvement and international environmental policy compliance in power plants. To achieve this, a measurement system with a reliable online reconstruction capability and high temporal resolution is necessary. This paper presents a novel technique that can improve the temporal resolution of the currently existing acoustic tomography (AT) system using frequency division multiplexing (FDM). This method allows for concurrent transmissions of acoustic signals in several different frequency bands instead of a sequential manner, which leads to more efficient channel utilization and allows all acoustic signals to be acquired at the same time, so that a better temporal uniformity of multipath acoustic signals can be realized. Theoretical analysis and experiments have been conducted to verify the effectiveness of this technique. The results prove that the proposed method can significantly improve the temporal resolution of the AT system while maintaining the accuracy and robustness of the reconstruction.

Polyaniline-based 3D network structure promotes entrapment and detection of drug-resistant bacteria

Sensitive and accurate capture, enrichment, and identification of drug-resistant bacteria on human skin are important for early-stage diagnosis and treatment of patients. Herein, we constructed a three-dimensional hierarchically structured polyaniline nanoweb (3D HPN) to capture, enrich, and detect drug-resistant bacteria on-site by rubbing infected skins. These unique hierarchical nanostructures enhance bacteria capture efficiency and help severely deform the surface of the bacteria entrapped on them. Therefore, 3D HPN significantly contributes to the effective and reliable recovery of drug-resistant bacteria from the infected skin and the prevention of potential secondary infection. The recovered bacteria were successfully identified by subsequent real-time polymerase chain reaction (PCR) analysis after the lysis process. The molecular analysis results based on a real-time PCR exhibit excellent sensitivity to detecting target bacteria of concentrations ranging from 102 to 107 CFU/mL without any fluorescent signal interruption. To confirm the field applicability of 3D HPN, it was tested with a drug-resistant model consisting of micropig skin similar to human skin and Klebsiella pneumoniae carbapenemase-producing carbapenem-resistant Enterobacteriaceae (KPC-CRE). The results show that the detection sensitivity of this assay is 102 CFU/mL. Therefore, 3D HPN can be extended to on-site pathogen detection systems, along with rapid molecular diagnostics through a simple method, to recover KPC-CRE from the skin.Graphical

Stepwise application of ECG and electrogram based criteria to ensure left bundle branch pacing

Abstract Funding Acknowledgements Type of funding sources: Public Institution(s). Main funding source(s): MPL received the Catalan Society of Cardiology Research Grant in 2019 and 2020 (Catalonia, Spain); the Josep Font Grant (2019-2022) from Hospital Clínic Barcelona (Catalonia, Spain). Background Left bundle branch pacing (LBBP) has emerged as an alternative to biventricular pacing. However, lack of a systematic stepwise application of the left bundle branch (LBB) capture criteria complicates implantation. Objective To define a stepwise application of LBBP capture criteria that will simplify implantation and ensure LBB capture. Methods A cohort of 24 patients from the LEVEL-AT trial who received LBBP and had electrocardiographic imaging (ECGI) at 45 days post-implant were included. The usefulness of ECG and electrogram based criteria to predict accurate LBB capture were analyzed. A two-step approach was developed to ensure LBB capture. The gold standard used to confirm LBB capture was the change in ventricular activation pattern and shortening in left ventricular activation time, assessed by ECGI. Results Twenty-two (91.6%) patients showed LBBP capture on ECGI. All patients fulfilled pre-screwing requisites: lead in septal position in left-oblique projection and W paced morphology in V1. In the first step, presence of either right bundle branch conduction delay pattern (qR or rSR in V1) or left bundle branch capture Plus (QRS ≤120ms) resulted in 95% sensitivity and 100% specificity to predict LBB capture, with an accuracy of 95.8%. In the second step, the presence of selective capture (100% specificity, only 41% sensitivity) or a spike-R<80ms (100% specificity, sensitivity 46%) ensured 100% accuracy to predict LBBP capture. Conclusions Stepwise application of ECG and electrogram criteria ensured an accurate assessment of left conduction system capture.

Flexible, high-resolution cortical arrays with large coverage capture microscale high-frequency oscillations in patients with epilepsy.

Effective surgical treatment of drug-resistant epilepsy depends on accurate localization of the epileptogenic zone (EZ). High-frequency oscillations (HFOs) are potential biomarkers of the EZ. Previous research has shown that HFOs often occur within submillimeter areas of brain tissue and that the coarse spatial sampling of clinical intracranial electrode arrays may limit the accurate capture of HFO activity. In this study, we sought to characterize microscale HFO activity captured on thin, flexible microelectrocorticographic (μECoG) arrays, which provide high spatial resolution over large cortical surface areas. We used novel liquid crystal polymer thin-film μECoG arrays (.76-1.72-mm intercontact spacing) to capture HFOs in eight intraoperative recordings from seven patients with epilepsy. We identified ripple (80-250 Hz) and fast ripple (250-600 Hz) HFOs using a common energy thresholding detection algorithm along with two stages of artifact rejection. We visualized microscale subregions of HFO activity using spatial maps of HFO rate, signal-to-noise ratio, and mean peak frequency. We quantified the spatial extent of HFO events by measuring covariance between detected HFOs and surrounding activity. We also compared HFO detection rates on microcontacts to simulated macrocontacts by spatially averaging data. We found visually delineable subregions of elevated HFO activity within each μECoG recording. Forty-seven percent of HFOs occurred on single 200-μm-diameter recording contacts, with minimal high-frequency activity on surrounding contacts. Other HFO events occurred across multiple contacts simultaneously, with covarying activity most often limited to a .95-mm radius. Through spatial averaging, we estimated that macrocontacts with 2-3-mm diameter would only capture 44% of the HFOs detected in our μECoG recordings. These results demonstrate that thin-film microcontact surface arrays with both highresolution and large coverage accurately capture microscale HFO activity and may improve the utility of HFOs to localize the EZ for treatment of drug-resistant epilepsy.

DHGECON: A multi-round conversational recommendation method based on dynamic heterogeneous encoding

Multi-round conversational recommendation (MCR), fulfilling a real–time recommendation task for users through interactively asking attributes and recommending items, can be regarded as a multi-step Markov decision-making process. Thus, in MCR, the key point is how to appropriately guide and characterize the dynamic interactive process in the conversation and to mine the dynamic relationship among the user, items and attributes to determine such policies as when to ask (attributes) and recommend (items), what (attributes) to ask and what (items) to recommend. Recent works mainly use statistical information involved in the conversation process to characterize the conversation without comprehensively considering the dynamic relationship among the user, items and attributes and may consequently have a negative impact on accurate capture of the user’s real-time preferences. To address this issue, we propose a multi-round conversational recommendation method based on dynamic heterogeneous encoding called DHGECON. Firstly, a dynamic heterogeneous graph with three types of node (users, items, and attributes) is constructed to characterize the proceeding conversation. Secondly, a heterogeneous graph-based encoder which adaptively updates the attention weight of nodes is designed to mine and represent the dynamic high-order semantic relationship among the user, items and attributes. Finally, the encoded information is fed into the decision-making module to get the action (i.e., recommending items or asking attributes) for guiding the next round conversation. Experimental results show that, compared with the state-of-the-art existing methods, the proposed method has a significant improvement in terms of major evaluation metrics over four real-world datasets.

Baits-trap chip for accurate and ultrasensitive capture of living circulating tumor cells.

Accurate analysis of living circulating tumor cells (CTCs) plays a crucial role in cancer diagnosis and prognosis evaluation. However, it is still challenging to develop a facile method for accurate, sensitive, and broad-spectrum isolation of living CTCs. Herein, inspired by the filopodia-extending behavior and clustered surface-biomarker of living CTCs, we present a unique baits-trap chip to achieve accurate and ultrasensitive capture of living CTCs from peripheral blood. The baits-trap chip is designed with the integration of nanocage (NCage) structure and branched aptamers. The NCage structure could "trap" the extended filopodia of living CTCs and resist the adhesion of filopodia-inhibited apoptotic cells, thus realizing the accurate capture (∼95% accuracy) of living CTCs independent of complex instruments. Using an in-situ rolling circle amplification (RCA) method, branched aptamers were easily modified onto the NCage structure, and served as "baits" to enhance the multi-interactions between CTC biomarker and chips, leading to ultrasensitive (99%) and reversible cell capture performance. The baits-trap chip successfully detects living CTCs in broad-spectrum cancer patients and achieves high diagnostic sensitivity (100%) and specificity (86%) of early prostate cancer. Therefore, our baits-trap chip provides a facile, accurate, and ultrasensitive strategy for living CTC isolation in clinical. STATEMENT OF SIGNIFICANCE: A unique baits-trap chip integrated with precise nanocage structure and branched aptamers was developed for the accurate and ultrasensitive capture of living CTCs. Compared with the current CTC isolation methods that are unable to distinguish CTC viability, the nanocage structure could not only "trap" the extended-filopodia of living CTCs, but also resist the adhesion of filopodia-inhibited apoptotic cells, thus realizing the accurate capture of living CTCs. Additionally, benefiting from the "baits-trap" synergistic effects generated by aptamer modification and nanocage structure, our chip achieved ultrasensitive, reversible capture of living CTCs. Moreover, this work provided a facile strategy for living CTC isolation from the blood of patients with early-stage and advanced cancer, exhibiting high consistency with the pathological diagnosis.

Accurate Capture and Identification of Exosomes: Nanoarchitecture of the MXene Heterostructure/Engineered Lipid Layer.

Recently, exosome detection has become an important breakthrough in clinical diagnosis. However, the effective capture and accurate identification of cancer exosomes in a complex biomatrix are still a tough task. Especially, the large size and non-conductivity of exosomes are not conducive to highly sensitive electrochemical or electrochemiluminescence (ECL) detection. Therefore, we have developed a Ti3C2Tx-Bi2S3-x heterostructure/engineered lipid layer-based nanoarchitecture to overcome the limitations. The engineered lipid layer not only specifically captured and efficiently fused CD63 positive exosomes but also showed excellent antifouling property in the biological matrix. Moreover, the MUC1 aptamer-modified Ti3C2Tx-Bi2S3-x heterostructure further identified and covered the gastric cancer exosomes that have been trapped in the engineered lipid layer. In the self-luminous Faraday cage-type sensing system, the Ti3C2Tx-Bi2S3-x heterostructure with sulfur vacancies extended the outer Helmholtz plane and amplified the ECL signal. Therefore, this sensor can be used to detect tumor exosomes in ascites of cancer patients without additional purification. It provides a new pathway to detect exosomes and other large-sized vesicles with high sensitivity.

Modeling of particle-laden flows with n-sided polygonal smoothed finite element method and discrete phase model

In this work, an n-sided polygonal smoothed finite element method (nSFEM) using mean value shape function for concave polygonal element coupled with the discrete phase model (DPM) is developed to solve particle-laden flows. The fluid phase is solved using nSFEM stabilized by the well-developed characteristic-based split (CBS) algorithm. The concave polygonal element is successfully constructed via the intrinsic characteristic of mean value shape function and a new smoothing domain (SD) construction with more physical meaning; thus, addressing the severely distorted local mesh, as well as retaining good geometric adaptability. In the meantime, the modeling of the coupling between the fluid and the particle is achieved by reusing the mean value interpolation to obtain the fluid drag force acting on the particle. The accurate capture of fluid velocities at particle positions within arbitrary polygonal elements via mean value interpolation ensures fluid drag with high-fidelity. Several classical numerical examples, including particle-laden flow around a circular cylinder, are presented to demonstrate the high accuracy and good robustness, and the capability of the proposed method for predicting particle motion in the analysis of complex particle-laden flows.

Effect of camera distance and angle on color of diverse skin tone-based standards in smartphone photos.

Accurate and reproducible color capture is vital in medical photography. Camera distance and angle are particularly important as they are highly variable in a clinical setting. To account for variability in illumination, camera technology, and geometric effects, color standards are often used for color correction. To explore how geometry affects color, we quantified the change in CIELAB color value of a color standard for diverse skin tones at varying smartphone camera distances and angles. Whereas both chromaticity (a* and b*) and lightness (L*) were affected by angle, distance only affected L* (standard error of measurement, SEM > 1 CIELAB unit). Flash usage did not generally reduce distance and angle associated variability. Compared to compressed (JPG) format, raw (DNG) images had decreased median variability across different distances and angles. These findings suggest that in medical photography, inconsistent camera distance and angle can increase variability in photographed skin appearance over time.