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Fiber composite materials exhibit exceptional specific stiffness and strength compared to traditional engineering materials. Nevertheless, automating the handling of limp flexible materials like fabrics remains a challenging process, often relying on multi-stage manual operations for hand layups. In this study, carbon fabric properties were initially characterized through standard experiments to develop and calibrate a finite element (FE) model. The FE model was subsequently validated against real-world pick-and-place tests involving soft robotic grippers. The validation results demonstrated a high correlation between the FE model and experiments, achieving an average accuracy of 97.2% for fabric projected area and 84.6% for fabric vertices' displacement. Additionally, the FE model was used to design, evaluate, and optimize alternative automation strategies. It was discovered that a convex surface improved fabric projection area and placement accuracy by 5.9% and 1.9%, respectively, compared to a concave surface with the same curvature radius. Larger concave surfaces contributed to increased projected area and placement accuracy as well. Longitudinal pick-and-place operations also enhanced the projection area and placement accuracy compared to transverse handling processes. Achieving successful fabric pick-and-place operations necessitates a comprehensive system's approach, considering the interaction between grippers, fabric, and mold surface. The FE model developed in this study will be further employed by the current research team in designing innovative compliant grippers tailored to complex mold surface geometries and specific fabric material requirements. The presented FE model offers valuable insights and paves the way for rapid, efficient, cost-effective, and secure implementation of automation solutions for handling limp flexible materials. [ABSTRACT FROM AUTHOR]

The main objective of this research is to establish a new formulation and mathematical model based on graph theory to create dynamic equations and provide clarity on the fundamental formulation. We have employed graph theory as a new approach to develop a new representation and formulate the vertical dynamics of a motorcycle with four degrees of freedom, including a suspension and tire model. We have outlined the principal procedural steps required to generate the mathematical and dynamic equations. This systematic approach ensures clarity and precision in our formulation process and representation. Subsequently, we implemented the dynamics equations to examine the dynamic behavior of both the sprung and unsprung masses' vertical displacements, while considering the varying conditions of the road profile. [ABSTRACT FROM AUTHOR]

Fault dynamometer cards are the basis of the diagnosis technique for sucker rod pumping systems. Predicting fault cards with a pumping condition model is an economical and effective method. The usual model is described by a mixed function of the pump displacement and pump load, and it is difficult to use in the prediction method based on the analytical solution of the sucker rod string wave equation. In this paper, a normal pumping condition model described by a function of polished rod velocity is proposed. For the analytical solution of the sucker rod wave equation, an iterative prediction algorithm with pumping condition models is proposed, its convergence is analyzed, and then it is validated by classical finite difference method simulated cards and measured surface dynamometer cards. The results show that the proposed algorithm is accurate. The algorithm has a maximum relative error of 0.10% for the classical method simulated card area and 1.45% for the measured card area. The research of this paper provides an effective scheme for the design, prediction, and fault diagnosis of a sucker rod pumping system with an analytical solution. [ABSTRACT FROM AUTHOR]

With the unique structure of multi-core compound droplets, they are increasingly used in various industrial production fields, material fabrication, biological sciences, medicine, and other numerous promising large-scale applications. This study focuses on using a front tracking method to study the dynamics of a multi-core compound droplet as it moves within a ratchet microchannel. The dynamics of the multi-core droplet is assessed by deformation (determined by elongation deformation indices, and surface indentation) and the transit time of the droplet within the microchannel. The presence of the ratchet region in the microchannel increases deformation and reduces the transit time of the compound droplets. Increasing the number of ratchets leads to faster droplet motion but has no significant effect on the deformation of the compound droplet. The results indicate that the parameters such as the capillary number, microchannel geometry (i.e., number of ratchets and neck radius), droplet size and structure significantly impact the compound droplet dynamics. The compound droplet radius equal to 0.3 times the microchannel radius results in the most significant elongation deformation. The number of core droplets has minimal effect on the deformation and transit time of the compound droplet. This study provides a profound insight into the dynamics of multi-core compound droplets in a ratchet microchannel and contributes a better understanding of their behavior and potential applications in various fields. [ABSTRACT FROM AUTHOR]

Digital PCR (dPCR) is a highly accurate technique for the quantification of target nucleic acid(s). It has shown great potential in clinical applications, like tumor liquid biopsy and validation of biomarkers. Accurate classification of partitions based on end-point fluorescence intensities is crucial to avoid biased estimators of the concentration of the target molecules. We have evaluated many clustering methods, from general-purpose methods to specific methods for dPCR and flowcytometry, on both simulated and real-life data. Clustering method performance was evaluated by simulating various scenarios. Based on our extensive comparison of clustering methods, we describe the limits of these methods, and formulate guidelines for choosing an appropriate method. In addition, we have developed a novel method for simulating realistic dPCR data. The method is based on a mixture distribution of a Poisson point process and a skew- |$t$| distribution, which enables the generation of irregularities of cluster shapes and randomness of partitions between clusters ('rain') as commonly observed in dPCR data. Users can fine-tune the model parameters and generate labeled datasets, using their own data as a template. Besides, the database of experimental dPCR data augmented with the labeled simulated data can serve as training and testing data for new clustering methods. The simulation method is available as an R Shiny app. [ABSTRACT FROM AUTHOR]

Background: The high prevalence and negative outcomes associated with skin cancer demand effective strategies to prepare nurse practitioner students to detect cancerous lesions and manage patient care. However, few studies have examined dermatologic simulations to prepare nurse practitioner students to detect and manage skin cancer. Purpose: An exploratory--descriptive qualitative approach was used to examine nurse practitioner students' experiences with simulations involving standardized patients wearing three-dimensional (3-D) prosthetic skin lesions, perceptions of ability to apply the simulations to clinical practice, and preferences for learning dermatologic care. Methodology: A convenience sample of 39 nurse practitioner students participated in simulations with standardized patients wearing 3-D skin lesions. Focus groups were conducted following simulation participation, and thematic analysis was performed by two researchers. Results: Four themes emerged: Simulation provides a safe place to practice, Dermatology should be an integral part of education, Realism makes a difference, and Improved confidence and preparation for practice. Conclusions: Simulations with standardized patients wearing 3-D skin lesion prosthetics provided students the opportunity to assess, diagnose, and manage the care of patients with cancerous skin lesions. Participants valued the realistic practice with dermatologic care and reported improved confidence and preparation for practice. Implications: Faculty can use simulations to provide experiential learning about the provider role in general and as it pertains to skin cancer care. Attention to realism is important to aid in building students' confidence and preparation for practice. [ABSTRACT FROM AUTHOR]

This paper introduces an algorithm to tackle the boundary condition (BC) problem, which has long persisted in the numerical and computational treatment of smoothed particle hydrodynamics (SPH). Central to the BC problem is a need for an effective method to reconcile a numerical representation of particles with 2D or 3D geometry. We describe and evaluate an algorithmic solution—boundary SPH (BSPH)—drawn from a novel twist on the mesh-based boundary method, allowing SPH particles to interact (directly and implicitly) with either convex or concave 3D meshes. The method draws inspiration from existing works in graphics, particularly discrete signed distance fields, to determine whether particles are intersecting or submerged with mesh triangles. We evaluate the efficacy of BSPH through application to several simulation environments of varying mesh complexity, showing practical real-time implementation in Unity3D and its high-level shader language (HLSL), which we test in the parallelization of particle operations. To examine robustness, we portray slip and no-slip conditions in simulation, and we separately evaluate convex and concave meshes. To demonstrate empirical utility, we show pressure gradients as measured in simulated still water tank implementations of hydrodynamics. Our results identify that BSPH, despite producing irregular pressure values among particles close to the boundary manifolds of the meshes, successfully prevents particles from intersecting or submerging into the boundary manifold. Average FPS calculations for each simulation scenario show that the mesh boundary method can still be used effectively with simple simulation scenarios. We additionally point the reader to future works that could investigate the effect of simulation parameters and scene complexity on simulation performance, resolve abnormal pressure values along the mesh boundary, and test the method's robustness on a wider variety of simulation environments. [ABSTRACT FROM AUTHOR]

Immunization programs globally have played a pivotal role in reducing mortality rates. However, the effectiveness of these programs often falls short of the intended coverage targets, primarily due to challenges within the supply chain, storage facilities, and distribution processes. Notably, a substantial percentage of vaccine wastage has been observed in numerous countries, thereby imposing a significant financial burden on immunization initiatives, and presenting a formidable challenge to policymakers. This paper undertakes a comprehensive study of the financial dynamics inherent in an immunization program within the context of India. Employing a systems perspective, we scrutinize the intricate interactions among various cost factors. Through a five-year system dynamics simulation, we derive insights into the amplified financial constraints resulting from vaccine wastage and the inefficiencies associated with shared personnel. Furthermore, our analysis extends to evaluate the impact of an additional investment aimed at enhancing the quality of the cold chain infrastructure and health worker proficiency on the overall funds of the immunization program. This research contributes to a nuanced understanding of the financial intricacies of immunization programs, offering valuable insights for policymakers and stakeholders seeking to optimize program efficiency and resource allocation. [ABSTRACT FROM AUTHOR]

Charge carrier lifetime is a crucial material parameter in optoelectronic devices and knowing the dominant recombination channels points the way for improvements. The effective carrier lifetime τeff of surface‐passivated hyperdoped (hSi) and nonhyperdoped “black” (bSi) silicon by quasi‐steady‐state photoconductance decay (QSSPC) measurements and its evolution upon controlled wet‐chemical etching are studied. Sample preparation involves the irradiation of Si by numerous ultrashort laser pulses either in SF6 for hSi or ambient atmosphere for bSi. Findings suggest that the hSi is composed of a double layer: 1) an amorphous resolidified top layer with about 92% of the total incorporated sulfur that accounts for the sub‐bandgap absorptance and 2) a crystalline layer underneath in which sulfur concentration tails off toward the Si substrate. The effective lifetime is deconstructed by a 1D simulation to quantify the impact of the local lifetime of the defect‐rich top layer, τtop. It is found that by the QSSPC method, a maximum τtop for 1) can be estimated. For 2), τtop between 2 and 8 ns is estimated. The bSi sample shows a faster lifetime recovery upon etching which suggests that in hSi samples purely laser‐induced defects are not limiting the carrier lifetime compared to sulfur‐related defects. [ABSTRACT FROM AUTHOR]

In recent years, legged robots have been more and more widely used on non-structured terrain, and their foot structure has an important impact on the robot's motion performance and stability. The structural characteristics of the yak foot sole with a high outer edge and low middle, which has excellent soil fixation ability and is an excellent bionic prototype, can improve the friction between the foot and the ground. At the same time, the foot hooves can effectively alleviate the larger impact load when contacting with the ground, which is an excellent anti-slip buffer mechanism. The bionic foot end design was carried out based on the morphology of the yak sole; the bionic foot design was carried out based on the biological anatomy observation of yak foot skeletal muscles. The virtual models of the bionic foot end and the bionic foot were established and simulated using Solidworks 2022 and Abaqus 2023, and the anti-slip performance on different ground surfaces and the influence of each parameter of the bionic foot on the cushioning effect were investigated. The results show that (1) the curved shape of the yak sole has a good anti-slip performance on both soil ground and rocky ground, and the anti-slip performance is better on soil ground; (2) the curved shape of the yak sole has a larger maximum static friction than the traditional foot, and the anti-slip performance is stronger under the same pressure conditions; (3) the finger pillow–hoof ball structure of the bionic foot has the greatest influence on the buffering effect, and the buffering effect of the bionic foot is best when the tip of the bionic foot touches the ground first. [ABSTRACT FROM AUTHOR]

To solve the parameter tunning problem of PID controllers in master-slave control structure of electro-hydraulic servo system, this paper proposed a solution method based on multi-objective optimization algorithm combined with model simulation. This method modeled the problem as a multi-objective optimization problem whose target space included four dimensions, namely master-slave synchronization error, settling time, overshoot and integral squared error. And it established the simulation model of master-slave PID control structure to obtain the target value of the target space. Additionally, it improved the MOEAD algorithm by strengthenning the diversity of generated offspring through the selection of parents along with the offspring generate operators and readjusting the weight vector through the substitution strategy of invalid ones using external populations and binding mechanism between weight vectors and individuals. Finally, this method got the final Pareto non-dominated solution set and then selected the knee point individual as the optimal parameter of the controller in the solution set, which improves the control quality of the master-slave synchronization structure. [ABSTRACT FROM AUTHOR]

Literature regarding simulation for learning interprofessional collaborative practice (IPCP) indicates a need to include a range of health professions and to focus on students' development of team communication and conflict resolution skills in day-to-day healthcare delivery. This study evaluated the impact of interprofessional simulation for occupational therapy, physiotherapy, dietetics, and nursing students on interprofessional collaboration competencies, specifically collaborative communication and conflict resolution during day-to-day interactions, and their intention for IPCP during placement. A series of simulations featuring the potential for interprofessional conflict and involving explicit coaching on communication and conflict resolution were conducted. A single cohort pre-test post-test design included the Students' Perceptions of Interprofessional Clinical Education Revised (SPICE-R), the Interprofessional Collaborative Competencies Attainment Survey (ICCAS), and an open response survey question on future intended practice. A total of 237 students participated in the simulation experience. Overall scores and scores on all IPCP competencies in the ICASS (n = 193) and SPICE-R (n = 226) improved for all professions post-simulation. The mean score of the ICCAS increased for 98% of the respondents and similarly the mean score of the SPICE-R increased for 71% of the respondents. Open-ended responses indicated students' intentions to pursue self-leadership in IPCP. Students who participated in an interprofessional simulation reported perceived improvements in IPCP competencies and were encouraged to initiate IPCP when on placement in the practice setting. [ABSTRACT FROM AUTHOR]

Detection and characterization of hidden defects, impurities, and damages in homogeneous materials like aluminum die casting materials, as well as composite materials like Fiber–Metal Laminates (FML), is still a challenge. This work discusses methods and challenges in data-driven modeling of automated damage and defect detectors using measured X-ray single- and multi-projection images. Three main issues are identified: Data and feature variance, data feature labeling (for supervised machine learning), and the missing ground truth. It will be shown that simulation of synthetic measuring data can deliver a ground truth dataset and accurate labeling for data-driven modeling, but it cannot be used directly to predict defects in manufacturing processes. Noise has a significant impact on the feature detection and will be discussed. Data-driven feature detectors are implemented with semantic pixel Convolutional Neural Networks. Experimental data are measured with different devices: A low-quality and low-cost (Low-Q) X-ray radiography, a typical industrial mid-quality X-ray radiography and Computed Tomography (CT) system, and a state-of-the-art high-quality μ-CT device. The goals of this work are the training of robust and generalized data-driven ML feature detectors with synthetic data only and the transition from CT to single-projection radiography imaging and analysis. Although, as the title implies, the primary task is pore characterization in aluminum high-pressure die-cast materials, but the methods and results are not limited to this use case. [ABSTRACT FROM AUTHOR]

Due to connectivity and automation trends, the medical device industry is experiencing increased demand for safety and security mechanisms. Anomaly detection has proven to be a valuable approach for ensuring safety and security in other industries, such as automotive or IT. Medical devices must operate across a wide range of values due to variations in patient anthropometric data, making anomaly detection based on a simple threshold for signal deviations impractical. For example, surgical robots directly contacting the patient's tissue require precise sensor data. However, since the deformation of the patient's body during interaction or movement is highly dependent on body mass, it is impossible to define a single threshold for implausible sensor data that applies to all patients. This also involves statistical methods, such as Z-score, that consider standard deviation. Even pure machine learning algorithms cannot be expected to provide the required accuracy simply due to the lack of available training data. This paper proposes using hybrid filters by combining dynamic system models based on expert knowledge and data-based models for anomaly detection in an operating room scenario. This approach can improve detection performance and explainability while reducing the computing resources needed on embedded devices, enabling a distributed approach to anomaly detection. [ABSTRACT FROM AUTHOR]

Biomolecular 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. [ABSTRACT FROM AUTHOR]

Despite being among the most common medical procedures, needle insertions suffer from a high error rate. Impedance measurements using electrode‐equipped needles offer promise for improved tissue targeting and reduced errors. Impedance visualization usually requires an extensive pre‐measured impedance dataset for tissue differentiation and knowledge of the electric fields contributing to the resulting impedances. This work presents two finite element simulation approaches for both problems. The first approach describes the generation of a multitude of impedances with Monte Carlo simulations for both, homogeneous and inhomogeneous tissue to circumvent the need to rely on previously measured data. These datasets could be used for tissue discrimination. The second method describes the simulation of the spatial sensitivity distribution of an electrode layout. Two singularity analysis methods were employed to determine the bulk of the sensitivity within a finite volume, which in turn enables consistent 3D visualization. The modeled electrode layout consists of 12 electrodes radially placed around a hypodermic needle. Electrical excitation was simulated using two neighboring electrodes for current carriage and voltage pickup, which resulted in 12 distinct bipolar excitation states. Both, the impedance simulations and the respective singularity analysis methods were compared with each other. The results show that the statistical spread of impedances is highly dependent on the tissue type and its inhomogeneities. The bounded bulk of sensitivities of both methods are of similar extent and symmetry. Future models should incorporate more detailed tissue properties such as anisotropy or changing material properties due to tissue deformation to gain more accurate predictions. [ABSTRACT FROM AUTHOR]

Objectives: This study developed multivariate law enforcement officer (LEO) body models for digital simulation of LEO accommodation in police cruiser cabs. Background: Anthropometrically accurate digital LEO body models, representing the United States LEOs, for computerized LEO cruiser interface simulations are lacking. Methods: Twenty body dimensions (with and without gear combined) of 756 male and 218 female LEOs were collected through a stratified national survey using a data collection trailer that traveled across the US. A multivariate Principal Component Analysis (PCA) approach was used to develop digital LEO body models. Results: Fifteen men and 15 women representing unique body size and shape composition of the LEO population were identified. A combined set of 24 male and female models (removal of 6 redundant models for which female and male models overlapped) is suggested. Conclusions: A set of 24 digital LEO body models in 3-dimensional form, along with their anthropometric measurements, were developed to facilitate LEO cruiser cab design. Application: Digital modeling software developers can use the models and their anthropometric data to build digital avatars for simulated evaluation of LEO cruiser cab configuration, console communication-equipment fitting, and cruiser ingress/egress access arrangement. LEO vehicle and equipment designers also can use eight key body dimensions (i.e., stature, buttock-popliteal length, eye height sitting, knee height sitting, shoulder-grip length, popliteal height, sitting height, and body weight) of the body models to recruit 24 human subjects to physically evaluate their vehicle prototypes for improved vehicle and equipment design. [ABSTRACT FROM AUTHOR]

Background: Genome‐wide association studies (GWAS) is a useful tool for the detection of disease or quantitative trait‐related genetic variations in the veterinary field. For a binary trait, a case/control experiment is designed in GWAS. However, there is limited information on the optimal case/control and sample size in GWAS. Objectives: In this study, it was aimed to detect the effects of case/control ratio and sample size for GWAS using computer simulation under certain assumptions. Method: Using the PLINK software, we simulated three different disease scenarios. In scenario 1, we simulated 10 different case/control ratios with increasing ratio of cases to controls. In scenario 2, we did versa of scenario 1 with the increasing ratio of controls to cases. In scenarios 1 and 2, sample size gradually was increased with the change case/control ratios. In scenario 3, the total sample size was fixed to 2000 to see real effects of case/control ratio on the number of disease‐related single nucleotide polymorphisms (SNPs). Results: The results showed that the number of disease‐related SNPs were the highest when the case/control ratio is close to 1:1 in scenarios 1 and 2 and did not change with an increase in sample size. Similarly, the number of disease‐related SNPs was the highest in case/control ratios 1:1 in scenario 3. However, unbalanced case/control ratio caused the detection of lower number of disease‐related SNPs in scenario 3. The estimated average power of SNPs was highest when case/control ratio is 1:1 in all scenarios. Conclusions: All findings led to the conclusion that an increase in sample size may enhance the statistical power of GWAS when the number of cases is small. In addition, case/control ratio 1:1 may be the optimal ratio for GWAS. These findings may be valuable not only for veterinary field but also for human clinical experiments. [ABSTRACT FROM AUTHOR]

Evapotranspiration affects uncertain changes in volumetric soil moisture content (θ) of earth surface, which is considerably controlled by temporal variability of weather parameters like rainfall and ambient temperature. Accurate measurement of temporal variation and spatial distribution of θ in a particular land is very challenging. Numerical modelling with any suitable computer code might be useful in such cases. Thus, Hydrus 2D modelling of θ variation in the soil at Odisha University of Agriculture and Technology (OUAT) in Bhubaneswar is undertaken as main objective of present study to investigate soil moisture dynamics in top surface layer. For the study, the θ in OUAT land was measured daily by 5 TM water content sensor for the duration of two years spanning from January 2021 to December 2022. Meteorological data for these 2 years are collected from a nearby weather station at OUAT and used for calculating evapotranspiration (ET) based on five different well known ET models. Soil hydraulic parameters of OUAT land were also evaluated by laboratory investigation. The evapotranspiration so calculated along with precipitation and materials properties were then assigned as the inputs in Hydrus 2D simulations. The simulated results are found to be in good agreement with field observations. It is proven by Pearson's coefficient of determination (R2) and Nash-Sutcliffe efficiency (NSE) which are found to be 0.83 and 0.84 respectively. The soil moisture simulation was the most accurate only when measured soil parameters along with atmospheric boundary involving Penman-Monteith (PM) ET model were considered as model inputs. [ABSTRACT FROM AUTHOR]

Carbon dioxide concentration in enclosed spaces is an air quality indicator that affects occupants' well-being. To maintain healthy carbon dioxide levels indoors, enclosed space settings must be adjusted to maximize air quality while minimizing energy consumption. Studying the effect of these settings on carbon dioxide concentration levels is not feasible through physical experimentation and data collection. This problem can be solved by using validated simulation models, generating indoor settings scenarios, simulating those scenarios, and studying results. In previous work, we presented a formal Cellular Discrete Event System Specifications simulation model for studying carbon dioxide dispersion in rooms with various settings. However, designers may need to predict the results of altering large combinations of settings on air quality. Generating and simulating multiple scenarios with different combinations of space settings to test their effect on indoor air quality is time-consuming. In this research, we solve the two problems of the lack of ground truth data and the inefficiency of producing and studying simulation results for many combinations of settings by proposing a novel framework. The framework utilizes a Cellular Discrete Event System Specifications model, simulates different scenarios of enclosed spaces with various settings, and collects simulation results to form a data set to train a deep neural network. Without needing to generate all possible scenarios, the trained deep neural network is used to predict unknown settings of the closed space when other settings are altered. The framework facilitates configuring enclosed spaces to enhance air quality. We illustrate the framework uses through a case study. [ABSTRACT FROM AUTHOR]

In the present research, we consider a biological model of serum hepatitis disease. We carry out a detailed analysis of the mentioned model along with a class with asymptomatic carriers to explore its theoretical and numerical aspects. We initiate the study by using the piecewise fractal–fractional derivative (FFD) by which the crossover effects within the model are examined. We split the time interval into subintervals. In one subinterval, FFD with a power law kernel is taken, while in the second one, FFD with an exponential decay kernel of the proposed model is considered. This model is then studied for its disease-free equilibrium point, existence, and Hyers–Ulam (H-U) stability results. For numerical results of the model and a visual presentation, we apply the Lagrange interpolation method and an extended Adams–Bashforth–Moulton (ABM) method, respectively. [ABSTRACT FROM AUTHOR]

The global scientific community is intensively promoting energy-plus buildings. Following the leading world trends, this paper presents a new energy-plus building concept—elevational earth-sheltered buildings with three different types of horizontal overhang photovoltaic-integrated panels: wooden support columns covered with clay tiles, steel pipes as support columns covered with sheet steel, and concrete support columns with concrete coverage. In this instance, the specific multi-numerical case study building model for the city of Kragujevac (located in central Serbia with favorable climatic conditions) was performed over 7 months (from 1 October to 30 April), taking into account the soil temperature, the effects of solar shading, the performance of the heating system—a ground source heat pump—and the characteristics of the artificial and automatic lighting control system. The simulation results show that the optimal depth of a horizontal overhang (energy-plus status) depends on the occupant's habits, in addition to meteorological conditions. The presented methodology can be used for any other location, both in Europe and the world. [ABSTRACT FROM AUTHOR]

Wildland fires cause economic and ecological damage with devastating consequences, including loss of life. To reduce these risks, numerous fire detection and recognition systems using deep learning techniques have been developed. However, the limited availability of annotated datasets has decelerated the development of reliable deep learning techniques for detecting and monitoring fires. For such, a novel dataset, namely, SWIFT, is presented in this paper for detecting and recognizing wildland smoke and fires. SWIFT includes a large number of synthetic images and videos of smoke and wildfire with their corresponding annotations, as well as environmental data, including temperature, humidity, wind direction, and speed. It represents various wildland fire scenarios collected from multiple viewpoints, covering forest interior views, views near active fires, ground views, and aerial views. In addition, three deep learning models, namely, BoucaNet, DC-Fire, and CT-Fire, are adopted to recognize forest fires and address their related challenges. These models are trained using the SWIFT dataset and tested using real fire images. BoucaNet performed well in recognizing wildland fires and overcoming challenging limitations, including the complexity of the background, the variation in smoke and wildfire features, and the detection of small wildland fire areas. This shows the potential of sim-to-real deep learning in wildland fires. [ABSTRACT FROM AUTHOR]

This paper describes the creation of a fast, deterministic, 3D fractal cloud renderer for the AFIT Sensor and Scene Emulation Tool (ASSET). The renderer generates 3D clouds by ray marching through a volume and sampling the level-set of a fractal function. The fractal function is distorted by a displacement map, which is generated using horizontal wind data from a Global Forecast System (GFS) weather file. The vertical windspeed and relative humidity are used to mask the creation of clouds to match realistic large-scale weather patterns over the Earth. Small-scale detail is provided by the fractal functions which are tuned to match natural cloud shapes. This model is intended to run quickly, and it can run in about 700 ms per cloud type. This model generates clouds that appear to match large-scale satellite imagery, and it reproduces natural small-scale shapes. This should enable future versions of ASSET to generate scenarios where the same scene is consistently viewed from both GEO and LEO satellites from multiple perspectives. [ABSTRACT FROM AUTHOR]

Introduction: Extended periods of bed rest and mechanical ventilation (MV) have devastating effects on the body. Background: Early mobility (EM) for patients in respiratory failure is safe and feasible, and an interprofessional team is recommended. Using simulation to train EM skills improves student confidence. The purpose of this study was to enable health care student collaboration as an interprofessional team in providing safe management and monitoring during an EM simulation for a patient requiring MV. Methods: Nursing (n = 33), respiratory (n = 7), occupational (n = 24), and physical therapist students (n = 55) participated in an EM interprofessional education (IPE) simulation experience. A mixed-methods analytic approach was used with pre/post quantitative analysis of the Student Perceptions of Interprofessional Clinical Education--Revised, Version 2 instrument and qualitative analysis of students' guided reflection papers. Results: Pre/post surveys completion rate was 39.5% (n = 47). The Student Perceptions of Interprofessional Clinical Education--Revised, Version 2 instrument indicated a significant improvement (P = .037) in students' perceptions of interprofessional collaborative practice. Qualitative data showed a positive response to the EM simulation IPE. Themes reflected all 4 Interprofessional Education Collaborative competencies. Discussion: This study demonstrated improved perception of interprofessional collaborative practice and better understanding of the Interprofessional Education Collaborative competencies. Conclusion: Students collaborated in the simulation-based IPE to provide EM for a patient requiring MV and reported perceived benefits of the experience. [ABSTRACT FROM AUTHOR]

Automated detection of volatile organic compounds in the atmosphere can be achieved by applying pattern recognition analysis to passive infrared (IR) multispectral remote sensing data. However, obtaining analyte-active training data through field experiments is time-consuming and expensive. To address this issue, methodology has been developed for simulating radiance profiles acquired using a multispectral IR line-scanner mounted in a downward-looking position on a fixed-wing aircraft. The simulation strategy used Planck's radiation law and a radiometric model along with the laboratory spectrum of the target compound to compute the upwelling IR background radiance with the presence of the analyte within the instrumental field-of-view. By combining the simulated analyte-active radiances and field-collected analyte-inactive radiances, a synthetic training dataset was constructed. A backpropagation neural network was employed to build classifiers with the synthetic training dataset. Employing methanol as the target compound, the performance of the classifiers was evaluated with field-collected data from airborne surveys at two test fields. [ABSTRACT FROM AUTHOR]

This paper extends a 1D dynamic physics-based model of the scrape-off layer (SOL) plasma, DIV1D, to include the core SOL and possibly a second target. The extended model is benchmarked on 1D mapped SOLPS-ITER simulations to find input settings for DIV1D that allow it to describe SOL plasmas from upstream to target—calibrating it on a scenario and device basis. The benchmark shows a quantitative match between DIV1D and 1D mapped SOLPS-ITER profiles for the heat flux, electron temperature, and electron density within roughly 50% on: (1) the Tokamak Configuration Variable (TCV) for a gas puff scan; (2) a single SOLPS-ITER simulation of the Upgraded Mega Ampere Spherical Tokamak; and (3) the Upgraded Axially Symmetric Divertor EXperiment in Garching Tokamak (AUG) for a simultaneous scan in heating power and gas puff. Once calibrated, DIV1D self-consistently describes dependencies of the SOL solution on core fluxes and external neutral gas densities for a density scan on TCV whereas a varying SOL width is used in DIV1D for AUG to match a simultaneous change in power and density. The ability to calibrate DIV1D on a scenario and device basis is enabled by accounting for cross field transport with an effective flux expansion factor and by allowing neutrals to be exchanged between SOL and adjacent domains. [ABSTRACT FROM AUTHOR]

Background: Using low titer group O whole blood (LTOWB) is increasingly popular for resuscitating trauma patients. LTOWB is often RhD‐positive, which might cause D‐alloimmunization and hemolytic disease of the fetus and newborn (HDFN) if transfused to RhD‐negative females of childbearing potential (FCP). This simulation determined the number of life years gained by the FCP and her future children if she was resuscitated with LTOWB compared with conventional component therapy (CCT). Methods: The model simulated 500,000 injured FCPs of each age between 0 and 49 years with LTOWB mortality relative reductions (MRRs) compared with components between 0.1% and 25%. For each surviving FCP, number of life years gained was calculated using her age at injury and average life expectancy for American women. The number of expected future pregnancies for FCPs that did not survive was also based on her age at injury; each future child was assigned the maximum lifespan unless they suffered perinatal mortality or serious neurological events from HDFN. Results: The LTOWB group with an MRR 25% compared with CCT had the largest total life years gained. The point of equivalence for RhD‐positive LTOWB compared to CCT, where life years lost due to severe HDFN was equivalent to life years gained due to FCP survival/future childbearing, occurred at an MRR of approximately 0.1%. Conclusion: In this model, RhD‐positive LTOWB resulted in substantial gains in maternal and child life years compared with CCT. A >0.1% relative mortality reduction from LTOWB offset the life years lost to HDFN mortality and severe neurological events. [ABSTRACT FROM AUTHOR]

This research paper focuses on the challenges associated with learning classifiers from large-scale, highly imbalanced datasets prevalent in many real-world applications. Traditional algorithms learning often need better performance and high computational efficiency when dealing with imbalanced data. Factors such as class imbalance, noise, and class overlap make it demanding to learn effective classifiers. In this study, we propose a novel self-paced ensemble framework for classifying imbalanced data. The framework employs under-sampling to self-harmonize data hardness and build a robust ensemble. Extensive experimental testing demonstrates promising results in handling overlapping classes and skewed distributions while maintaining computational efficiency. The self-paced ensemble method addresses the challenges of high imbalance ratios, class overlap, and noise presence in large-scale imbalanced classification problems. By incorporating the knowledge of these challenges into our learning framework, we establish the concept of classification hardness distribution, and the self-paced ensemble is a revolutionary learning paradigm for massive imbalance categorization, capable of improving the performance of existing learning algorithms on imbalanced data and providing better results for future applications. [ABSTRACT FROM AUTHOR]

The transplantation of seedlings represents a pivotal stage in plug tray seedling cultivation. Conventional end effectors used in transplanters are primarily tailored for seedlings with well-established root systems and tightly bound substrates. However, when the substrate lacks sufficient root wrapping and remains loose, independent seedling removal devices utilising blowing or suction methods are often employed. This results in structural complexity and increased costs for the transplanter. To address the challenge of grasping loose substrate, this study advocates for a novel approach utilising a diagonal oblique-insertion type end effector. Through repose angle trials, discrete element simulation parameters were calibrated. Subsequently, leveraging these calibrated simulation parameters, the end effector was optimisation through orthogonal experiments. Findings reveal that the relative error between simulated and actual repose angles is minimised under specific conditions, with the shear modulus at 8.2 × 106 Pa, the particle-particle rolling friction coefficient at 0.234, the particle-steel static friction coefficient at 0.36, and the JKR surface energy at 0.347 J m−2. Employing these simulation parameters for end effector optimisation, it was determined that the average substrate integrity rate reaches 79.26% with an end effector featuring 5 tines, a gripper positioned 2.5 mm from the edge of the hole, and a gripper ascent speed of 0.056 m s−1. The average relative error between actual grasping experimental and simulation results was observed at 10.21%, indicating the suitability of these discrete element parameters for optimising simulations of end effectors for transplanters. Furthermore, the end effector devised in this study demonstrated efficacy in transplanting loose substrates. • A diagonal oblique-insertion type end effector was designed. • Calibration of discrete element parameters for substrate using repose angle test. • Optimisation of end effector using discrete element simulation. [ABSTRACT FROM AUTHOR]

In order to reduce time and costs, while maintaining a high level of product quality, effective implementation of systems engineering processes may be beneficial for small and medium-sized enterprises. However, applying a prescriptive generic system engineering standard in the enterprise, without any consideration of the company's organisation, background and context, is inappropriate. Moreover, due to severe resource limitations, the difficulties in following and complying with a standard are even more obvious in SMEs. In this context, this paper explores a framework to help SMEs evaluate the maturity of processes, promote a progressive deployment and standardisation of their engineering processes to manage manufacturing projects, based on the experience and practices underway in SMEs and with reference to international systems engineering standards. Our proposal is to stand by companies to help them evolve their engineering processes by progressively aligning them with systems engineering standards without disrupting the overall organisation and practices of the company. [ABSTRACT FROM AUTHOR]

Computational statistics is a critical skill for professionals in fields such as data science, statistics, and related disciplines. One essential aspect of computational statistics is the ability to simulate random variables from specified probability distributions. Commonly employed techniques for sampling random variables include the inverse transform method, acceptance–rejection method, and Box–Muller transformation, all of which rely on sampling from the uniform (0 , 1) distribution. A significant concept in statistics is the finite mixture model, characterized by a convex combination of multiple probability density functions. In this paper, we introduce a modified version of the composition method, a standard approach for sampling finite mixture models. Our modification offers the advantage of relying on sampling from the uniform (0 , 1) distribution, aligning with prevalent methods in computational statistics. This alignment simplifies teaching computational statistics courses, as well as having other benefits. We offer several examples to illustrate the approach. [ABSTRACT FROM AUTHOR]

The burden of human schistosomiasis, a known but neglected tropical disease in Sub-Saharan Africa, has been worrisome in recent years. It is becoming increasingly difficult to tackle schistosomiasis with praziquantel, a drug known to be effective against all Schistosoma species, due to reports of reduced efficacy and resistance. Therefore, this study seeks to investigate the antischistosomal potential of phytochemicals from Azadirachta indica against proteins that have been implicated as druggable targets for the treatment of schistosomiasis using computational techniques. In this study, sixty-three (63) previously isolated and characterized phytochemicals from A. indica were identified from the literature and retrieved from the PubChem database. In silico screening was conducted to assess the inhibitory potential of these phytochemicals against three receptors (Schistosoma mansoni Thioredoxin glutathione reductase, dihydroorotate dehydrogenase, and Arginase) that may serve as therapeutic targets for schistosomiasis treatment. Molecular docking, ADMET prediction, ligand interaction, MMGBSA, and molecular dynamics simulation of the hit compounds were conducted using the Schrodinger molecular drug discovery suite. The results show that Andrographolide possesses a satisfactory pharmacokinetic profile, does not violate the Lipinski rule of five, binds with favourable affinity with the receptors, and interacts with key amino acids at the active site. Importantly, its interaction with dihydroorotate dehydrogenase, an enzyme responsible for the catalysis of the de novo pyrimidine nucleotide biosynthetic pathway rate-limiting step, shows a glide score and MMGBSA of −10.19 and −45.75 Kcal/mol, respectively. In addition, the MD simulation shows its stability at the active site of the receptor. Overall, this study revealed that Andrographolide from Azadirachta indica could serve as a potential lead compound for the development of an anti-schistosomal drug. [ABSTRACT FROM AUTHOR]

The sprawling growth of urban settlements is a dominant spatial process in many cities of developing countries. This development's most severe apparent effect is the loss of ecological infrastructure. In this way, consequently, the ecosystem services that have been provided for human settlements for thousands of years will be lost. Urban ecological infrastructure is also very effective in climate change and energy consumption. This research aims to spatially analyze the sprawling growth of Miandoab City with an emphasis on ecological infrastructures. In this regard, first, land cover maps have been prepared. Then the future land cover is simulated and predicted by the CA-MARKOV chain method. Also, the metrics of the number of patches, the patch size, and the patch cohesion of spots have been calculated for all land cover types in the landscape. In addition, the urban expansion intensity in different directions and changes in the density of built land cover have been estimated. According to the findings, Miandoab City has experienced a very sprawling growth until 2023, during which the structural integrity of green infrastructure and bare lands has been severely destroyed in favor of built land cover. The direction of physical-spatial development of the city has been towards the eastern suburbs. Most of the bare lands and intensive growth potential are in these areas. Solutions with three strategies (protective, defensive, and opportunistic) have been presented for balancing physical-spatial development and increasing urban and extra-urban ecological infrastructure integrity. [ABSTRACT FROM AUTHOR]

In this paper, we develop and analyze a mathematical model for spreading malaria, including treatment with transmission‐blocking drugs (TBDs). The paper's main aim is to demonstrate the impact the chosen model for demographic growth has on the disease's transmission and the effect of its treatment with TBDs. We calculate the model's control reproduction number and equilibria and perform a global stability analysis of the disease‐free equilibrium point. The mathematical analysis reveals that, depending on the model's demography, the model can exhibit forward, backward, and even some unconventional types of bifurcation, where disease elimination can occur for both small and large values of the reproduction number. We also conduct a numerical analysis to explore the short‐time behavior of the model. A key finding is that for one type of demographic growth, the population experienced a significantly higher disease burden than the others, and when exposed to high levels of treatment with TBDs, only this population succeeded in effectively eliminating the disease within a reasonable timeframe. [ABSTRACT FROM AUTHOR]

Spatial models enable understanding potential redistribution of marine resources associated with ecosystem drivers and climate change. Stock assessment platforms can incorporate spatial processes, but have not been widely implemented or simulation tested. To address this research gap, an international simulation experiment was organized. The study design was blinded to replicate uncertainty similar to a real‐world stock assessment process, and a data‐conditioned, high‐resolution operating model (OM) was used to emulate the spatial dynamics and data for Indian Ocean yellowfin tuna (Thunnus albacares). Six analyst groups developed both single‐region and spatial stock assessment models using an assessment platform of their choice, and then applied each model to the simulated data. Results indicated that across all spatial structures and platforms, assessments were able to adequately recreate the population trends from the OM. Additionally, spatial models were able to estimate regional population trends that generally reflected the true dynamics from the OM, particularly for the regions with higher biomass and fishing pressure. However, a consistent population biomass scaling pattern emerged, where spatial models estimated higher population scale than single‐region models within a given assessment platform. Balancing parsimony and complexity trade‐offs were difficult, but adequate complexity in spatial parametrizations (e.g., allowing time‐ and age‐variation in movement and appropriate tag mixing periods) was critical to model performance. We recommend expanded use of high‐resolution OMs and blinded studies, given their ability to portray realistic performance of assessment models. Moreover, increased support for international simulation experiments is warranted to facilitate dissemination of methodology across organizations. [ABSTRACT FROM AUTHOR]

To increase vehicle dynamics modelling accuracy in simulation environments, in this work, we propose a model, where the mutual influence of the vehicle dynamics and tyre wear is taken into account. In this context, simulation-oriented models aim at representing the main features of the vehicle dynamics, while keeping the complexity low, making them suitable for control-oriented analyses and design. The wear model quantifies tyre wear as a tyre mass loss depending on the tyre-road interaction, derived from the vehicle dynamics and kinematics; then, the outcome of this model is consequently used to update the tyre friction characteristics, by modifying the main parameters of the Pacejka's magic formula. We also discuss the steps required to use the model in two-wheeled vehicles, where the roll dynamics plays an important role in the tyre wear. The main features of the developed model are discussed on a motorcycle, as a simulation case-study. [ABSTRACT FROM AUTHOR]

Unit distributions, exhibiting inherent symmetrical properties, have been extensively studied across various fields. A significant challenge in these studies, particularly evident in parameter estimations, is the existence and uniqueness of estimators. Often, it is challenging to demonstrate the existence of a unique estimator. The major issue with maximum likelihood and other estimator-finding methods that use iterative methods is that they need an initial value to reach the solution. This dependency on initial values can lead to local extremes that fail to represent the global extremities, highlighting a lack of symmetry in solution robustness. This study applies a very simple, and unique, estimation method for unit Weibull and unit Burr XII distributions that both attain the global maximum value. Therefore, we can conclude that the findings from the obtained propositions demonstrate that both the maximum likelihood and graphical methods are symmetrically similar. In addition, three real-world data applications are made to show that the method works efficiently. [ABSTRACT FROM AUTHOR]

Recognizing and attempting management of patients with urgent or emergent conditions is one of the Association of American Medical Colleges Core Entrustable Professional Activities (#10) and a skill desired of new interns. However, given the acuity of these patient conditions, medical students often struggle to gain experience in these situations. Virtual reality could help fill this void while lowering costs and resources compared with high-fidelity simulation. We converted a high-fidelity chest pain simulation case to virtual reality format utilizing short video clips filmed with a 360-degree camera and superimposed menus of options at decision points. This virtual reality simulation was offered to fourth-year medical students during their transition to residency course in the spring of 2023. Students were offered a post-survey on the simulation. There were 47 fourth-year students that completed the virtual reality simulation; 41 completed the post-survey (response rate 87.2%). Over 90% of the students agreed or strongly agreed with the following statements: the virtual reality simulation was a valuable part of the transition to residency course, the virtual reality case was similar to what they will face as an intern, and they would like to have more virtual reality simulations earlier in the fourth year; 85.4% agreed or strongly agreed that the virtual reality simulation helped prepare them for the first few days of intern year. We demonstrated that virtual reality is an acceptable, cost-effective, and feasible modality to teach medical students how to recognize and attempt management of urgent clinical situations (Core Entrustable Professional Activity 10). [ABSTRACT FROM AUTHOR]

Inter-turn faults (ITFs) are one of the most common types of faults that affect the operation of induction motors. This paper presents an ABC frame-based model to simulate the induction motor with ITFs. The proposed model is capable of representing the induction motor in both health and faulty conditions considering the introduced unbalance by ITFs in the machine circuit. The performance of the proposed model is thoroughly investigated using a detailed simulation in MATLAB/Simulink environment. Different fault cases with a variety of motor loading conditions are considered and compared with the experimental results obtained from a specially wounded 3-phase induction motor. The simulation current response of the proposed model shows good correlation with the experimentally obtained response under the same conditions. Also, a comparison between the proposed ABC model and a DQ-model is established demonstrating ABC model superior performance in simulating ITFs in induction motor. [ABSTRACT FROM AUTHOR]

BACKGROUND: Delivering difficult news to families is an essential but challenging skill. Pediatric trainees report limited confidence in this skill and perform poorly in simulation. We implemented the American Academy of Pediatrics (AAP) Resilience Curriculum and evaluated performance and self-efficacy in delivering difficult news. METHODS: The AAP Resilience Curriculum, using the SPIKES (Set-up, Perception, Invitation, Knowledge, Empathy, and Summary) framework, was taught to pediatric fellows. Fellows’ performance during simulations with standardized patients before and after curriculum implementation was scored with a SPIKES checklist. Preand post-test surveys assessed self-efficacy in delivering difficult news. RESULTS: Fellows (n=19) significantly improved their performance in delivering difficult news, increasing the median SPIKES checklist scores from 78% to 90% completion (P<0.001). Pediatric fellows (n=35) reported improved confidence from 3.4/5 to 3.9 (P=0.01). CONCLUSIONS: Pediatric fellows demonstrated significant improvement in their ability to deliver difficult news during a simulated patient encounter and reported increased self-efficacy in delivering difficult news. [ABSTRACT FROM AUTHOR]

Gas migration behaviour in saturated, compacted bentonite, especially under rigid-boundary conditions, is controversial. Gas breakthrough phenomena, observed under higher pressure gradient conditions in laboratory experiments, are described in literatures by adopting visco-capillary or dilatancy-controlled flow concept. Since, under rigid-boundary conditions, volumetric expansion is restricted and/or water dissipation is not detected, these concepts cannot be implemented satisfactorily. Instead, a diffusion and solubility-controlled (DSC) flow concept was previously found to be adequate for describing the behaviours at lower temperatures (20 °C). The DSC concept describes gas breakthrough as a function of gas solubility. Breakthrough occurs when concentration of dissolved gas reaches or surpasses the solubility limit in the entire specimen. In this work, the DSC flow concept is applied to validate gas migration and breakthrough experiments conducted at higher temperatures, e.g. 40 and 60 °C. Good agreements are observed between the experimental and predicted results, suggesting that the DSC flow concept can be applied to describe gas migration behaviour satisfactorily in rigidly confined saturated bentonites (under constant volume conditions) for various temperature regimes. Results also show that helium dissolution and diffusion processes in saturated bentonite are sensitive to test temperature and pressure conditions. The processes become more stable with increasing gas injection pressure and ambient temperature. [ABSTRACT FROM AUTHOR]

The economic efficiency of conventional breeding strategies for forest trees based on biparental crosses is compared with that of alternative strategies based on pedigree reconstruction using molecular markers. Analyses of economic efficiency is based on comparisons of breeding scenarios corresponding to the same total investment. The first step is the description and cost evaluation of each basic operation, from crossing to genetic selection and clonal archive establishment. Breeding scenarios are then compared by stochastic sampling with a parametric genetic model (POPSIM), the comparison criteria in this case being genetic gain in the seed orchard for a given level of genetic diversity. Additionally, the economic gain resulting from the use of improved material is estimated for different levels of breeding investment. Our analysis shows that genotyping costs account for a much smaller proportion of total investment than phenotyping costs. We also show that, in comparisons of breeding scenarios corresponding to the same total investment, the three main breeding strategies (biparental crosses, polymix crosses, and open pollination) achieve similar genetic gains provided that sufficiently large numbers of parents are considered. These results open up promising perspectives for the wider integration of molecular markers into forest tree breeding strategies. [ABSTRACT FROM AUTHOR]

In this study, 67 historical mosques from the 15th and 16th centuries selected from different regions of Turkey were analyzed in terms of evacuation time, exit width per person, average evacuation speed and occupant load. It was aimed to determine the general tendencies of mosques, which are one of the building types with the highest occupant load, in the context of evacuation. Measuring the evacuation efficiency of mosques in cases such as terrorist attacks and fires is an important issue for Turkey, which has more than 89 thousand mosques. In this study which mosques with an occupant load from 113 people to 4799 people were examined, it was detected that the evacuation times of the mosques ranged from 51 seconds to 8 minutes and 19 seconds. It was also observed that the mosques with an occupant load of less than 1000 people and more than 1000 people differ in terms of evacuation outputs. [ABSTRACT FROM AUTHOR]

The use of natural ventilation and natural lighting through the building envelope is preferred in all buildings. On the other hand, natural air and daylight are taken into the spaces with the vertical voids created in the green building. However, it is a risk for fire safety design that vertical interior voids and ventilation openings in the spaces adjacent to the voids create uninterrupted vertical and horizontal areas. These voids can cause the spread of smoke and flames in a fire event. To prevent the spread of smoke and flames through vertical interior voids in a fire event, in this study a performance-based design was developed for smoke and flame evacuation through vertical interior voids. Pyrosim simulation program was used to monitor smoke level, temperature change, and indoor air velocity. Pyrosim is a program that uses computational fluid dynamics, allows simulation, and includes FDS (Fire Dynamics Simulator) software. Temperature, smoke, and flame level analyses were made with scenarios created by changing the width and height of the vertical interior void in the prototype building, which was designed using the physical model studies in the literature. It was determined that the evacuation speed of smoke and flames increased, and the temperature and smoke level in the rooms decreased because of reducing the width of the inner void and increasing the height of the void. [ABSTRACT FROM AUTHOR]

Introduction and objectives: Ninety percent of maternal deaths are attributed to postpartum hemorrhage, with 50% being preventable. Annually, University of Mississippi Medical Center staff have more than 20,000 obstetrical encounters and deliver thousands of infants, with ∼75% being high-risk. The mother/baby unit, 3 Wiser, experienced two postpartum hemorrhages in August 2022. Post-event debriefings revealed opportunities for improvement. This project aimed to promote evidence-based practices regarding the prevention and management of postpartum hemorrhage in 3 Wiser. Methods: The project was guided by the JBI Model of Evidence-Based Healthcare and used the JBI Practical Application of Clinical Evidence System together with the Getting Research into Practice audit and feedback strategy. Four evidence-based practices were selected as audit criteria. After baseline audits were conducted, strategies to improve compliance with evidence-based practices were implemented. Finally, a follow-up audit was conducted, and the results of both audits were compared. Results: The baseline audits revealed 84% average compliance with the four evidence-based practices. Strategies to improve compliance included a simulation for nursing staff with a review of postpartum hemorrhage policies and skills. The post-implementation audit revealed 98% average compliance with the four evidence-based practices, a 14% increase from the baseline audit. Conclusions: This evidence implementation project utilized a clinical audit process, which led to improvements in practice related to the prevention and management of postpartum hemorrhage in the inpatient postpartum unit. [ABSTRACT FROM AUTHOR]

This paper aims to simulate total factor productivity, following the original proposal made by Cobb and Douglas (1928). Estimates with annual frequency are computed for the United States during two periods, i.e. 1899-1992 and 1933-2019. In the case of Mexico, estimates are computed for the 1993-2015 period. An income distribution in favor of capital in recent decades is found both for the United States and México. Capital share has grown in the United States from 25% in 1899-1922 to 89% in 1993-2019, while for Mexico it has been 82% for 1993-2015. Functional income distribution requires close monitoring. [ABSTRACT FROM AUTHOR]

Klark is a novel online medical education tool () where students take histories from virtual patients with common presentations from multiple specialities. We investigated whether Klark could enhance student confidence and competence in history-taking, and whether students find Klark helpful. A single cohort of first-year clinical medical students had access to Klark for three weeks. At both ends of the trial, participants were asked to complete feedback forms and participate in two mock Objective Structured Clinical Examination (OSCE) history stations. Outcome measures included self-reported confidence and competence in history-taking, performance in OSCE stations, and qualitative user experience data. Seventy participants successfully completed a case on Klark (mean 18.7), of which 63 (90% user retention) completed ≥ 2 cases. Self-reported competence (p < 0.001) and confidence (p < 0.001) improved. Participants found Klark to be helpful, impactful, and would recommend it to other students. OSCE scores improved for medical (57% vs. 69%, p < 0.001) and surgical (58% vs. 70%, p < 0.001) histories. Klark improved competence and confidence in history-taking. Students found it helpful and chose to continue using the platform. By developing confidence and competence at their own pace in the Klark simulated environment, students can then maximise benefit from in-person clinical opportunities. [ABSTRACT FROM AUTHOR]

Blockage, which arises from accumulated materials like sand, stones, sediment, uncontrolled growth of tree roots within pipes, and the inadvertent partial closure of in-line valves, poses a pervasive challenge in the operational sphere of water distribution networks (WDNs). This results in significant head loss in the pipes, leading to disruptions in the water supply. Identifying such blockages conventionally requires specialized human resources and is often encumbered by cost and time challenges. This paper introduces a method for precisely determining the location and magnitude of blockages within WDNs. This methodology is firmly grounded in a calibration-optimization framework, harnessing a specially crafted hybrid optimization algorithm known as PSOHS, which combines the strengths of particle swarm optimization (PSO) and harmony search (HS) algorithms. Detailed comparisons are drawn between simulated pressure data (derived from the hydraulic network model) and corresponding field data at multiple points to minimize disparities, thereby facilitating the precise identification of potential blockages in a WDN. The proposed method undergoes rigorous evaluation across two benchmark networks (modified Poulakis and Hanoi) under diverse scenarios as well as on an actual WDN. Results from over 60,000 simulated blockage scenarios underscore the method's remarkable proficiency, achieving blockage localization accuracy of 99.9% and magnitude estimation with a maximum absolute error (MAE) of less than 3%. Particularly noteworthy is the superior performance of the PSOHS algorithm as proposed, surpassing the PSO algorithm by enhancing blockage localization accuracy by a minimum of 10.5% and reducing MAE by 3%. Further, adopting the proposed algorithm over the HS algorithm yields improvements of 27.5% and 3.5%, respectively. Applying the proposed method in an actual network effectively pinpointed its blockage. Consequently, this algorithm presents a valuable tool for WDN operators, augmenting their capacity for effective network management. [ABSTRACT FROM AUTHOR]

This paper aims to propose an improved constitutive model based on the classical Chaboche mixed hardening model to describe the cyclic elastoplastic behavior of 6082-T6 aluminum alloy. First, 16 specimens from 6082-T6 aluminum alloy were tested under monotonic and cyclic loads. The variation law of the backstress, yield surface size, elastic modulus, and peak stress with equivalent plastic strain was obtained and analyzed. The results show that the kinematic hardening before and after the load reversal had a significant difference. Meanwhile, the elastic modulus and yield surface radius experienced a rapid decay at the early stage of equivalent plastic strain growth and then tended to flatten out. Based on these phenomena, a modified constitutive model based on the classical Chaboche mixed hardening model was proposed. The evolutions of isotropic hardening/softening, backstress, and elastic modulus were introduced. Then, the model was introduced to the ABAQUS software by the user subroutine to define a material's mechanical behavior (UMAT) subroutine and corresponding parameters were provided. Finally, the proposed constitutive model was proven to capture the cyclic elastoplastic properties of 6082-T6 aluminum alloy well and had a significant improvement on the classical Chaboche mixed hardening model. Among them, the constitutive model can accurately describe the initial yield surface of 6082-T6, with an accuracy improvement of 26.6% compared to the Chaboche mixed hardening model, and an accuracy improvement of 7.44% in describing changes in elastic modulus. [ABSTRACT FROM AUTHOR]