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Despite reservations over the status of esports as sports, the International Olympic Committee (IOC) has, for policy reasons, encouraged International Federations to pursue links with providers of 'virtual and simulated' sports, in part by the introduction of an event, the Olympic Virtual Series, first held in 2021. In providing an account of 'virtuality' and 'simulation', we query the theoretical basis of the Olympic Virtual Series. In particular, we query the IOC's use of the term 'virtual' in the description of two very different activities: what it calls 'physical virtual sports' (which we argue are simply Olympic-type sports – real sports! – and should just be called 'sports') and 'non-physical virtual sports' (which we argue are not sports at all, and should be recognized for what they are – computer games). [ABSTRACT FROM AUTHOR]

This essay analyzes the 2007 board game Pandemic in light of the COVID-19 global pandemic. The essay explores the connections between the reality of Pandemic and the play of COVID-19. To do this, it uses Ian Bogost's interpretation of systems (both real and imagined) to invite a dialectic of reality and game simulation. The interaction of such systems, in a game whose theme became real, highlights a major tenet of game studies—the borders between reality and games are thin, blurred, and mobile, if they exist at all. Games, in their simulation of the real, are mimetic, and, in turn, reality has become gamified. The essay examines the board game and highlights its mechanics, which include cooperation and mitigation of risk. It also explores how the game and reality blur their borders in this instance of play, inviting further study into the ramifications of simulated games and the fantasy of the real. [ABSTRACT FROM AUTHOR]

Soft matter with diverse functionalities that are easily designable has fascinated tremendous research interests in the past several decades. Nevertheless, the inherent confluence of time and length scale ubiquitous in soft matter immensely complicates the elucidation of the structure–property relationship and thereby severely impedes the function exploration of soft materials. Recently, the emergent machine learning (ML) techniques open new paradigms in property prediction and molecular design of functional materials, due to their extraordinarily distinguished performance in the aspect of trend identity and pattern extraction from data, and objective optimization by accelerating the guided search in high‐dimensional spaces. This review exclusively focuses on the current state‐of‐the‐art progress in the development of ML techniques applied in the realms of soft matter, ranging from coarse‐grained simulations to theoretical prediction on the structural formation and macroscopic properties, as well as the optimization and algorithm‐aided design in experiments. Finally, an outlook on the challenges and opportunities for this rapidly evolving field is discussed. [ABSTRACT FROM AUTHOR]

Here we propose a new class of probability distributions as an extended version of the exponential hyper-Poisson distribution and Weibull Poisson distribution. We investigate several important aspects of the distribution through deriving expressions for its probability density function (pdf), cumulative distribution function, survival function, failure rate function, pdf of the order statistics, r-th raw moments, etc. The method of maximum likelihood estimation procedures along with EM algorithm is discussed for estimating the parameters of the distribution and a test procedure is suggested for testing the significance of the additional parameters of the proposed model. The use of the proposed distribution is illustrated through real-life data sets. Further, a brief simulation study is carried out for evaluating the performance of the estimators obtained for the parameters of the distribution. [ABSTRACT FROM AUTHOR]

Aims Methods Results Conclusions The aims of this study were to develop a population pharmacokinetic (PK) model for risperidone ISM® and to investigate the relationships between active moiety exposure, as described by apparent clearance (CL40), and several covariates using all data from five clinical studies.A population PK model was developed using active moiety concentrations from a study in healthy volunteers and two studies in patients with schizophrenia. Data from a comparative bioavailability study in medically stable patients and a Phase III study in patients with acute exacerbation of schizophrenia were then incorporated, using empirical Bayesian feedback and model refinement in NONMEM. Finally, covariate analysis was performed on CL40.The final model adequately described the pharmacokinetics of 6288 active moiety concentrations in 17 healthy volunteers and 430 patients with schizophrenia. This one‐compartment disposition model had a complex absorption process, combining a small amount immediately entering the central active moiety compartment, two first‐order absorption processes and a combined zero‐order and first order process, with first‐order elimination from the central compartment. Significant covariates on CL40 were BMI and sex. Goodness‐of‐fit (GOF) plots and visual predictive checks (VPC) confirmed acceptable description of the data.The population PK model adequately described active moiety concentrations from five clinical studies after risperidone ISM® administration. Relationships between active moiety exposure and covariates were defined in order to facilitate simulations for future studies. The model showed that risperidone ISM® rapidly achieves therapeutic plasma levels within the first hours after the first injection that are maintained sustainedly throughout the whole dosing interval following once‐monthly gluteal injections of 100 mg and 75 mg. [ABSTRACT FROM AUTHOR]

Barium titanate (BaTiO3, BT)/poly (vinylidene fluoride, PVDF) composites containing 0%–50% of ceramic filler volume fraction were fabricated by spin‐coating method, and it was shown that the permittivity of BT/PVDF composites increased with the addition of ceramic filler. In order to enhance the interfacial bonding between the two phases, the surface modification treatment of BT ceramic particles was carried out using different mass fractions of γ‐Aminopropyl‐triethoxysilane (KH550). The results indicated that the dielectric properties of the modified composites were enhanced. The dielectric constant of the BT/PVDF composite with 10 vol.% ceramic filler treated with 1 wt.% KH550 is 20.3, which is twice as much as pure PVDF. A model of BT/PVDF dielectric composite was employed by using COMSOL Multiphysics to simulate and analyze the effects of filler particle size, volume fraction, and degree of dispersion on the properties of composite dielectric films from the perspective of microstructural. Calculated results show that the addition of ceramic particles triggers local electric field distortion, which affects the dielectric properties of the composites. Meanwhile, the degree of dispersion of the filler also affects the breakdown resistance of the composite material, when the filler is uniformly dispersed, the local electric field is reduced, which effectively enhances the breakdown resistance of the material. Finite element simulation analyzes the macroscopic dielectric properties from a microstructural point of view, which is beneficial for further understanding of ceramic‐polymer composites. Highlights: The dielectric properties of the polymer matrix were enhanced by doping BT.The KH550 can enhance the dispersion of BT particles in the PVDF.The surface‐modified BT improved the dielectric properties of the composite.COMSOL simulation confirmed the effectiveness of the interface modification. [ABSTRACT FROM AUTHOR]

Background Purpose Methods Results Conclusion Computer algorithms that simulate lower‐doses computed tomography (CT) images from clinical‐dose images are widely available. However, most operate in the projection domain and assume access to the reconstruction method. Access to commercial reconstruction methods may often not be available in medical research, making image‐domain noise simulation methods useful. However, the introduction of non‐linear reconstruction methods, such as iterative and deep learning‐based reconstruction, makes noise insertion in the image domain intractable, as it is not possible to determine the noise textures analytically.To develop a deep learning‐based image‐domain method to generate low‐dose CT images from clinical‐dose CT (CDCT) images for non‐linear reconstruction methods.We propose a fully image domain‐based method, utilizing a series of three convolutional neural networks (CNNs), which, respectively, denoise CDCT images, predict the standard deviation map of the low‐dose image, and generate the noise power spectra (NPS) of local patches throughout the low‐dose image. All three models have U‐net‐based architectures and are partly or fully three‐dimensional. As a use case for this study and with no loss of generality, we use paired low‐dose and clinical‐dose brain CT scans. A dataset of 326$\hskip.001pt 326$ paired scans was retrospectively obtained. All images were acquired with a wide‐area detector clinical system and reconstructed using its standard clinical iterative algorithm. Each pair was registered using rigid registration to correct for motion between acquisitions. The data was randomly partitioned into training (251$\hskip.001pt 251$ samples), validation (25$\hskip.001pt 25$ samples), and test (50$\hskip.001pt 50$ samples) sets. The performance of each of these three CNNs was validated separately. For the denoising CNN, the local standard deviation decrease, and bias were determined. For the standard deviation map CNN, the real and estimated standard deviations were compared locally. Finally, for the NPS CNN, the NPS of the synthetic and real low‐dose noise were compared inside and outside the skull. Two proof‐of‐concept denoising studies were performed to determine if the performance of a CNN‐ or a gradient‐based denoising filter on the synthetic low‐dose data versus real data differed.The denoising network had a median decrease in noise in the cerebrospinal fluid by a factor of 1.71$1.71$ and introduced a median bias of +0.7$ + 0.7$ HU. The network for standard deviation map estimation had a median error of +0.1$ + 0.1$ HU. The noise power spectrum estimation network was able to capture the anisotropic and shift‐variant nature of the noise structure by showing good agreement between the synthetic and real low‐dose noise and their corresponding power spectra. The two proof of concept denoising studies showed only minimal difference in standard deviation improvement ratio between the synthetic and real low‐dose CT images with the median difference between the two being 0.0 and +0.05 for the CNN‐ and gradient‐based filter, respectively.The proposed method demonstrated good performance in generating synthetic low‐dose brain CT scans without access to the projection data or to the reconstruction method. This method can generate multiple low‐dose image realizations from one clinical‐dose image, so it is useful for validation, optimization, and repeatability studies of image‐processing algorithms. [ABSTRACT FROM AUTHOR]

A complete workflow was presented for estimating the concentration of microorganisms in biological samples by automatically counting spots that represent viral plaque forming units (PFU) bacterial colony forming units (CFU), or spot forming units (SFU) in images, and modeling the counts. The workflow was designed for processing images from dilution series but can also be applied to stand-alone images. The accuracy of the methods was greatly improved by adding a newly developed bias correction method. When the spots in images are densely populated, the probability of spot overlapping increases, leading to systematic undercounting. In this paper, this undercount issue was addressed in an empirical way. The proposed empirical bias correction method utilized synthetic images with known spot sizes and counts as a training set, enabling the development of an effective bias correction function using a thin-plate spline model. Its application focused on the bias correction for the automated spot counting algorithm LoST proposed by Lin et al. Simulation results demonstrated that the empirical bias correction significantly improved spot counts, reducing bias for both fixed and random spot sizes and counts. [ABSTRACT FROM AUTHOR]

The transition to more environmentally friendly steel production methods has intensified research into hydrogen-based direct reduction (HyDR) of iron oxide pellets. The aim of this study is to systematically investigate the kinetics of the reduction process, the evolution of porosity and the resulting microstructural changes on the reduction behavior of high-quality pellets during HyDR of iron ore at different temperatures. A modified mathematical model is developed based on the shrinkage kernel model, taking into account both mass and heat transport in a hydrogen atmosphere. The effects of temperature, particle size and time on the reduction behavior of the pellets are investigated. The simulated results are validated and discussed by the results of a batch of iron oxide pellets consisting of ten almost spherical pellets subjected to the direct reduction process with pure hydrogen. The results show that the total energy input to the HyDR process is a complex balance of factors, including chemical reaction rates, diffusion dynamics and entropy generation. The increase in free volume and simultaneous decrease in pore diameter reflect the dynamic nature of the microstructure, which includes additional free volume and defects due to the volume discrepancies and associated stresses between the reactant and product phases. Furthermore, the data show that higher temperatures accelerate the reduction reactions, especially the transformation of wustite into metallic iron. This phase transition is characterized by a significant volume change that cannot be accommodated by elastic deformation alone, leading to the development of lattice defects such as cracks, creep pores and dislocations that serve as stress relief mechanisms. The trends for porosity change at 950 °C and 1000 °C observed in the experimental results are correct and in good agreement with the numerical and simulated results. [Display omitted] • Development of a model to evaluate HyDR kinetics and microstructural changes in iron oxide pellets. • Higher temperatures accelerate HyDR, which affects phase transitions and defect formation. • Temperature-induced porosity affects kinetics and gas diffusion despite tortuosity. • HyDR leads to stress defects and increased porosity in the microstructure. • The interaction of kinetics and entropy in the optimization of the HyDR process for steel was highlighted. [ABSTRACT FROM AUTHOR]

Background: It is a requirement that medical students are educated in emergencies and feel well prepared for practice as a doctor, yet national surveys show that many students feel underprepared. Virtual reality (VR), combined with 360-degree filming, provides an immersive, realistic, and interactive simulation experience. Unlike conventional in-person simulation, it is scalable with reduced workforce demands. We sought to compare students’ engagement and enjoyment of VR simulation to desktop computer-based simulation. Methods: We conducted a prospective, interventional, evaluation study. The study was carried out on final year medical students undertaking their Pre-Foundation Assistantship (n = 116) at Imperial College School of Medicine (ICSM) in London. We compared objective engagement, subjective engagement, and subjective enjoyment of VR simulation to desktop computer-based simulation using cardiac arrest and life-threatening asthma scenarios. Engagement was measured objectively using students’ physiological parameters, including heart rate and eye tracking, and facilitator observations using the validated ‘Behavioural Engagement Related to Instruction’ (BERI) protocol. Students’ subjective engagement and enjoyment levels were measured using a post-session survey. Results: Students’ maximum heart rates were significantly higher during VR simulation with a mean difference of 4.2 beats per minute (3.2 to 5.2, p < 0.001), and eye tracking showed they spent a significantly greater mean percentage of time of 6.4% (5.1 to 7.7, p < 0.001) focusing on the scenarios in VR compared to standard desktop. Qualitative data showed students enjoyed and felt engaged with the sessions, which provided a safe space for learning. Conclusions: Our study shows that students found VR simulations enjoyable and were more engaged compared to standard desktop simulation. This suggests that 360-degree VR simulation experiences provide students with immersive, realistic training, which is scalable, giving them the unique opportunity to manage emergencies and work within emergency teams, which would not typically occur during traditional training. [ABSTRACT FROM AUTHOR]

Dementia patients may have language barriers and decreased comprehension ability. Their family caregivers can feel frustrated when communicating with them. Poor communication hinders family caregivers from obtaining accurate health information about patients, and may also increase their emotional burden, affecting patient care quality. The present study developed a virtual reality‐based simulated communication training (VRSCT) system and applied it to a training course for family caregivers of dementia patients. It allowed family caregivers to simulate real‐world situations in a VR environment, experience the daily communication barriers and stress with dementia patients, and apply their acquired knowledge and skills to solve related problems. This study used a randomised control experimental design with mixed analysis methods. A total of 63 family caregivers were recruited and randomly divided into the experimental group (N = 32) learning with the VRSCT system to interact with virtual dementia patients and practice communication skills, and the control group (N = 31) using the traditional role‐playing method for practice. Quantitative data were analysed to determine participants' knowledge of dementia care, attitudes, communication confidence and skills. In addition, the qualitative method was used to analyse the participants' discussion records. The results showed that by using the VRSCT approach, participants significantly improved their knowledge of dementia care, attitudes, communication confidence and communication skills compared to the control group. In addition, participants reported that through the real‐time feedback of the VRSCT system, they could recognise their previous incorrect communication approach. As a result, they adjusted their communication strategies and increased their self‐confidence. Practitioner notes What is already known about this topic Situational simulation helps learners improve their communication skills in a safe environment. Virtual reality (VR) creates a realistic, highly interactive learning environment, allowing users to be deeply immersed in the learning experience. What this paper adds This study proposed a VR‐based simulated communication training (VRSCT) approach; moreover, seven dementia cases of different degrees of severity were designed in the VR system to enable family members to experience possible challenges of taking care of dementia patients they might encounter in their daily lives. Each case in the VRSCT system has its unique symptoms and communication barriers. The learner in the story plays a caregiver, experiencing and solving the problems and challenges posed by the system. The experimental results show that the proposed method improves learners' knowledge, attitudes, communication confidence, and communication skills related to dementia care. Implications for practice and/or policy Utilising VR training can amplify awareness and secure enhanced social support for dementia‐related challenges. Using VRSCT, as governments and institutions recognise the effectiveness of VR training, they will provide more resources and promote its widespread application. What is already known about this topic Situational simulation helps learners improve their communication skills in a safe environment. Virtual reality (VR) creates a realistic, highly interactive learning environment, allowing users to be deeply immersed in the learning experience. What this paper adds This study proposed a VR‐based simulated communication training (VRSCT) approach; moreover, seven dementia cases of different degrees of severity were designed in the VR system to enable family members to experience possible challenges of taking care of dementia patients they might encounter in their daily lives. Each case in the VRSCT system has its unique symptoms and communication barriers. The learner in the story plays a caregiver, experiencing and solving the problems and challenges posed by the system. The experimental results show that the proposed method improves learners' knowledge, attitudes, communication confidence, and communication skills related to dementia care. Implications for practice and/or policy Utilising VR training can amplify awareness and secure enhanced social support for dementia‐related challenges. Using VRSCT, as governments and institutions recognise the effectiveness of VR training, they will provide more resources and promote its widespread application. [ABSTRACT FROM AUTHOR]

Background Maternal colonization by the bacterium Group B streptococcus (GBS) increases risk of preterm birth, a condition that has an important impact on the health of children. However, research studies that quantify the effect of GBS colonization on preterm birth have reported variable estimates of the effect measure. Methods We performed a simulated cohort study of pregnant women to assess how timing of exposure (GBS colonization) assessment might influence results of studies that address this question. We used published data on longitudinal maternal GBS colonization and on the distribution of preterm births by gestational age to inform parameters used in the simulations. Results Assuming that the probability of preterm birth is higher during weeks when pregnant women are colonized by GBS, our results suggest that studies that assess exposure status early during pregnancy are more likely to estimate an association between GBS colonization and preterm birth that is closer to the null, compared with studies that assess exposure either at birth or during gestational weeks matched to preterm births. In sensitivity analyses assuming different colonization acquisition rates and diagnostic sensitivities, we observed similar results. Conclusions Accurate quantification of the effect of maternal GBS colonization on the risk of preterm birth is necessary to understand the full health burden linked to this bacterium. In this study, we investigated one possible explanation, related to the timing of exposure assessment, for the variable findings of previous observational studies. Our findings will inform future research on this question. [ABSTRACT FROM AUTHOR]

The key feature of a knowledge formation is that it finds a way to finance the production of knowledge. We are accustomed to thinking of universities as the standard knowledge formation of modern science, social science, and the humanities. But this was not true before the twentieth century and is decreasingly true in the twenty-first. The RAND Corporation, which evolved from its military origins, was a model alternative to this model. As Dayé shows, RAND produced ideas that would never have been developed in the university: two "prospection" techniques, Delphi and Political Gaming. It also created careers outside the university for brilliant misfits who savored intellectual delights and relevance that the university would have crushed. How they produced knowledge matters: it gives us some ideas about what is possible for future knowledge formations. [ABSTRACT FROM AUTHOR]

Background and Objectives: When a haematopoietic stem cell registry size is constrained by limits on recruiting, as in Canada, identifying the right person to recruit is a critical determinant of effectiveness. The aim of this study was to evaluate the impact of changes to donor recruitment effort, within ethnic groups, on the matching effectiveness of the Canadian registry as it evolves over time. Materials and Methods: Simulation methods are applied to create a cohort of donor recruits and patients over a 10‐year time horizon. New recruits are added to the registry each year, while some existing donors 'age‐out' upon reaching their 36th birthday. In a similar fashion, simulated patient lists are created. At the end of each simulated year, simulated patients are matched against the simulated registry. Results: There are increased matches in non‐White populations when diverse registrants are preferentially recruited, but there are larger decreases in the number of matches for Caucasian patients. Additionally, ethnic communities that have limited registrants in the Canadian registry in 2021 do not benefit from increased recruiting efforts as much as communities with a larger initial number of registrants. Conclusion: Preferentially recruiting from non‐Caucasian populations reduces the number of matches from Canadian sources because increases in non‐Caucasian populations will not fully counterbalance decreases to Caucasian patient matches. Nevertheless, more than 80% of all matches are for Caucasian patients, regardless of the donor recruiting effort within ethnic groups. [ABSTRACT FROM AUTHOR]

Epistasis is a ubiquitous phenomenon in genetics, and is considered to be one of main factors in current efforts to unveil missing heritability of complex diseases. Simulation data is crucial for evaluating epistasis detection tools in genome‐wide association studies (GWAS). Existing simulators normally suffer from two limitations: absence of support for high‐order epistasis models containing multiple single nucleotide polymorphisms (SNPs), and inability to generate simulation SNP data independently. In this study, we proposed a simulator SimHOEPI, which is capable of calculating penetrance tables of high‐order epistasis models depending on either prevalence or heritability, and uses a resampling strategy to generate simulation data independently. Highlights of SimHOEPI are the preservation of realistic minor allele frequencies in sampling data, the accurate calculation and embedding of high‐order epistasis models, and acceptable simulation time. A series of experiments were carried out to verify these properties from different aspects. Experimental results show that SimHOEPI can generate simulation SNP data independently with high‐order epistasis models, implying that it might be an alternative simulator for GWAS. [ABSTRACT FROM AUTHOR]

MicroRNA (miRNA), a type of non‐coding RNA, is known to suppress the expression of target genes and there is an increasing number of studies analyzing various miRNAs in cancer. In an integrated analysis of miRNA and gene expressions, it is often difficult to obtain a significant result with a small amount of data. In this study, we proposed a method that allows integrated analysis even with a small amount of miRNA and gene expression data, and examined its validity. The method is based on a group comparison between target genes having specific functions controlled by a specific miRNA and a background group of randomly selected genes. We conducted a simulation to verify the validity of the proposed method. The simulation results indicated that the method can detect significant differences in expression of target genes controlled by a miRNA showing significant expression change. We then applied the proposed method to real data derived from multiple myeloma cells. As a result, some functions were detected as significantly changed due to a significant change of miRNA. [ABSTRACT FROM AUTHOR]

In factor analysis of ordinal variables, category thresholds determine the values of a hypothetical latent response at which a transition to a higher response option occurs. In general, category thresholds are estimated as free parameters. In the Rasch measurement theory framework, the rating-scale model has been proposed that prescribes equal sets of distances between category thresholds for all items. As a factor analytic parallel, I propose a model with a constrained threshold structure (FACTS). The application of the model is illustrated with a real data example. A simulation study showed that the thresholds are estimated more accurately with the FACTS model than with the standard unconstrained model for different sample sizes, test lengths, and number of response categories. In addition, the likelihood ratio test generally showed good power in comparing the two models. Because the FACTS model performs well and provides a meaningful interpretation of category thresholds, it may be used routinely in factor analysis of categorical item responses. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate the production of high purity oxygen (90–95%) through experiments in a PSA/VSA unit and develop a mathematical model to describe the dynamic behavior of the process. Different operational parameters and the dead volume were investigated for their impact on process performance. The experiments used a laboratory-scale unit filled with beads of a commercial LiX zeolite to obtain breakthrough and PSA/VSA data for model validation. Equilibrium isotherms of pure oxygen and nitrogen were measured at 288, 298 and 313 K for the pressure range of 0 to 3 bar. Single and multicomponent breakthrough curves were obtained at 298 K. Synthetic air (grade 5.0 purity, excluding argon) with a composition of 20% (± 0.5%) O2 and 80% (± 0.5%) N2 was used in the PSA/VSA experiments. A novel approach was developed using the mathematical model designed to simulate PSA/VSA cycles to account for the dead volume effects commonly found in units of this type. The model was implemented and solved using gPROMS® software. The simulation data matched well with the experimental data, accurately representing histories of concentration, pressure, temperature, and purity variations during the process. The validated model revealed optimal operating conditions for a VSA unit: 7.5 s adsorption time, 1.5 bar adsorption pressure, 0.1 bar desorption pressure, and a flow rate of 1 SLPM, producing a purity of approximately 94% and a recovery of about 20%. Increasing the adsorption duration negatively affected the oxygen purity but positively influenced process recovery and productivity. Adding an equalization stage improved process recovery by 18.9% for PSA and 14.5% for VSA. Additionally, increased dead volume in the column had adverse effects on purity, productivity, and recovery for both PSA and VSA units. [ABSTRACT FROM AUTHOR]

Introduction Drying is one of the oldest methods of food preservation. To increase the efficiency of heat and mass transfer while maintaining product quality, the study of the drying process is crucial scientifically and meticulously. It is possible to conduct experimental tests, trial and error, in the drying process. However, this approach consumes time and cost, with a significant amount of energy resources. By harnessing available software and leveraging technological advancement to develop a general model for drying food under varying initial conditions, the drying process can be significantly optimized. Materials and Methods This study was conducted with the aim of simulating heat and mass transfer during Refractance window drying for aloe vera gel. Comsol Multiphysics version 5.6 is a three-dimensional model used to solve heat and mass transfer equations. For this purpose, the differential equations of heat and mass transfer were solved simultaneously and interdependently. The above model considered various initial conditions: water temperature of 60, 70, 80, and 90°C, and aloe vera gel thickness of 5 and 10 mm. The initial humidity and temperature of the aloe vera is uniform. The initial temperature is 4° and the initial humidity of the fresh aloe vera sample is 110 gwater/gdry matter. Heat is supplied only by hot water from the bottom surface of the product. Results and Discussion The drying time was needed to reduce the moisture content of aloe vera gel from 110 to 0.1 gwater/gdry matter during Refractance window drying. Aloe vera gel with a thickness of 5 mm dried in 120, 100, 70, and 50 minutes at water temperatures of 60, 70, 80, and 90°, respectively. For a 10 mm thick layer of aloe vera gel, the drying time was 240, 190, 150, and 120 minutes, for water temperatures of 60 to 90°, respectively. These results demonstrate the importance of both the water temperature and thickness on the drying time. Furthermore, the drying rate of aloe vera gel increased as the water temperature increased from 60 to 90°, the drying rates were 0.915, 1.099, 1.57, and 2.198 gwater/min for 5 mm thickness and 0.457, 0.578, 0.732, and 0.915 gwater/min for 10 mm thick layer of aloe vera gel, respectively. Conclusion Based on the simulation results, the optimal model is with a water temperature of 90° and an aloe vera gel thickness of 5 mm. Overall, the modeling results are consistent with the results of experimental data. [ABSTRACT FROM AUTHOR]

Economic sanctions have the potential to affect environmental factors through various channels, including income reduction and constraints on accessing finance and environmentally friendly technologies. This study aims to simulate the energy and environmental consequences resulting from international sanctions in Iran. To achieve this, we develop a System Dynamics model integrating a spectrum of variables spanning economic, social, and environmental dimensions, for the period from 2008 to 2028. Our simulation outcomes indicate that by 2028, sanctions are anticipated to precipitate a notable upsurge in CO2 emissions, ranging from 12.5% to 30% compared to the baseline scenario. The magnitude of this escalation hinges on a variety of factors, including energy intensity and scenarios related to economic growth. According to our findings, prolonging international sanctions could be a major barrier to improving energy intensity and lowering CO2 emissions. Given the potential environmental consequences of sanctions, international communities, particularly sanctioning countries, should consider the environmental impacts of sanctions in their policy-making decisions in order to reduce emissions damage. [ABSTRACT FROM AUTHOR]

Moving the laser focus to the vicinity of the gas-liquid interface is the key point for many new enhanced and new methods to improve the quality of spectral signals in water Laser induced breakdown spectroscopy (LIBS) detection. Understanding the generation and evolution characteristics of the plasma induced by pulsed laser near the gas–liquid interface is of great significance for the establishment of evolution models and improvement of these new LIBS methods. In this paper, a set of slow horizontal flow auxiliary system is established to provide an ideal flat gas–liquid two-phase interface experimental condition. Experimental research on vertical incidence flat system was conducted using techniques such as time-resolved imaging, plasma characterization diagnosis, and spectral analysis. And the detection capabilities of the system were also tested. The characteristics and mechanisms of LIBS near the gas-liquid two-phase interface were investigated with the laser incident on the sample along the vertical direction. Simulation of the laser beam focusing process and observation of laser beam spot images show that the shift of plasma generation position relative to the focal point results from the refraction of the laser beam entering the solution from the air and the 'interface effect' of propagation on the vertical direction. Moreover, the plasma forms only the optical power density surpasses the breakdown threshold. In this work, plasma with smaller size, rounder shape, stronger radiation, higher temperature, and higher density can be produced when the focus position is in the liquid column 0.3 mm away from the upper interface. Simultaneously, for example, the Mg ion line at 285.213 nm, the obtained spectral intensity to signal-to-background ratio reaches the maximum value, and a better spectral signal can be obtained, which is 2–4 times of other positions, and the detection limits of the elements Na, Mg, and Ca also reach the lowest level, with 1.6–2.4 times of the detection limit of other focusing positions for Mg and 1.4–1.7 times for Ca, respectively. [ABSTRACT FROM AUTHOR]

This paper constructs a data-driven demand purchasing confidence rule-based model based on the theory of evidential reasoning to address the problem of purchasing decision bias in which the decision maker anchors the prior demand. First, we apply a synthetic algorithm to reason about the confidence structure distribution of the purchasing decision and then iteratively optimize the purchasing quantity according to the confidence structure distribution to minimize the cost loss function. Finally, we choose the average cost loss and service level value as the evaluation indexes to explore the purchasing confidence rule model. The simulation shows that compared with the expected purchasing decision based on the stochastic cumulative distribution function, the decision based on the confidence structure distribution can reduce the purchasing decision bias, manifested in the lower mean cost loss and a higher mean value of service level. Sensitivity analyses of the number of rules, product shelf life, and critical values show that the purchasing confidence rule base is highly adaptable. [ABSTRACT FROM AUTHOR]

Simulation methods are currently widely used, from simulations of various experiments to the calculation of certain integrals to the solution of differential equations. We can also use them in the economy and business operations. A specific industry, such as air transport, currently applies simulations to decision-making processes only to a small extent. The aim of the article is to point out the applicability of Monte Carlo simulation in the area of risk assessment of projects and investment activities, which is an important factor in achieving business sustainability. Through stochastic and deterministic modelling, simulations were performed using the Crystal Ball software tool. The simulation criterion is Net Present Value (NPV), modelled in different variants of variables in the form of own and foreign sources of financing. Simulation research in the field of financial decision-making is practically unknown and not applied to aviation companies. The process of planning investments and simulating their development in order to ensure sustainability for the future should become an integral part of all companies in aviation. [ABSTRACT FROM AUTHOR]

The presented article deals with the issue of inventory management optimization through modelling and simulation in the software Tecnomatix Plant Simulation. Based on an in-depth analysis of the supply chain with an emphasis on inventory management, a simulation model was developed. It was optimized using the inventory theory methodology in combination with a discrete-event simulation approach. Dynamic simulation made it possible to perform experiments and optimize the existing state. The solution to the problem is elaborated on a case study to achieve the efficiency of the supply process of a specific operation of a clothing retail chain, which is struggling with the problems of excessive and inaccurate supply. [ABSTRACT FROM AUTHOR]

The printing company's process performance depends on the possibility of providing requested products and managing the existing constraints of fixed machine layouts and high setup times between different products. Process inefficiencies caused by these factors reflect on throughput, production times, and resource utilization. The changes that improve one part of the production system usually affect other parts, needing additional optimization, and it is very useful to test the feasibility of proposed solutions with simulation before implementation. This paper presents a new algorithm for continuous improvement of enterprises performance, combining the lean approach with cellular manufacturing, and simulation. The performance is observed in a way that a certain setup influences the system in its entirety, rather than on a specific part of that system. The results are presented through models developed within the production optimization phase, representing various ways in which the continuous improvement algorithm can unfold. Each of them comes with its advantages and disadvantages, all intending to create more efficient production processes that generate less production waste. [ABSTRACT FROM AUTHOR]

Use of ultrasonography has been suggested as an accurate adjunct to clinical evaluation of fetal position and station during labor. There are no available reports concerning its actual use in delivery wards. The aim of this survey was to evaluate the current practice regarding the use of ultrasonography during labor. A questionnaire was sent to members of the Italian Society of Ultrasound in Obstetrics and Gynecology employed in delivery wards. The qFeuestionnaire was made up of 22 questions evaluating participant characteristics and the current use of ultrasound in labor in their hospital of employment. The answers were grouped according to participant characteristics. A total of 200 participants replied. Ultrasound was considered useful before an operative vaginal delivery by 59.6 % of respondents, while 51.8 and 52.5 % considered it useful in the management of prolonged first and second stages of labor, respectively. The major indication for ultrasound use during labor was the assessment of fetal occiput position. The major difficulties in its application were the perceived lack of training and the complexity of the ultrasound equipment use. Participants that reported fewer difficulties were those employed in hospitals with a higher number of deliveries or having delivery units with more years of experience using ultrasound in labor, or those who had attended specific training courses. The results indicate that, despite the reported evidence of a higher accuracy of ultrasound compared to clinical evaluation in assessing fetal position and station, its use is still limited, even amongst maternal-fetal medicine practitioners specialized in ultrasonography. [ABSTRACT FROM AUTHOR]

Background: Simulation methodology in teacher education offers a wide range of practice opportunities in a controlled environment. However, even though not much has been written about the benefits of simulation in teacher training, even less has been said about the difficulties perceived by the participants in doing simulation. Method: In this study we conducted an exploratory longitudinal study which includes 205 postgraduate participants scattered around the globe who took part in a computer mediated simulation in the years 2019 to 2022 as an assessment tool in a master's degree for teacher education. Aside from the positive impact on learning, which has already been disseminated (autor1), some recurring difficulties have been identified and presented in this study. A mixed analysis is performed based on the triangulation between qualitative and quantitative approaches. The qualitative data were analysed using a qualitative content analysis method through an open question about participants' perceptions post-treatment, video recordings and individual final reports. The quantitative data was gathered through a Likert-type questionnaire and analysed using statistical methods. Findings: Findings indicate that (1) simulation entails several concerns about task overload and time consumption along with lack of understanding of what the simulation phases involve (learning focus vs performance focus); and (2) simulation can cause uneasiness and anxiety related to the use of technological devices and teamwork. Contributions: Thus, these results have several implications for research, theory and practice when it comes to applying simulation as a pedagogical strategy. [ABSTRACT FROM AUTHOR]

Dissociative identity disorder (DID) is characterised by, among others, subjectively reported inter-identity amnesia, reflecting compromised information transfer between dissociative identity states. Studies have found conflicting results regarding memory transfer between dissociative identity states. Here, we investigated inter-identity amnesia in individuals with DID using self-relevant, subject specific stimuli, and behavioural and neural measures. Data of 46 matched participants were included; 14 individuals with DID in a trauma-avoidant state, 16 trauma-avoiding DID simulators, and 16 healthy controls. Reaction times and neural activation patterns related to three types of subject specific words were acquired and statistically analysed, namely non-self-relevant trauma-related words (NSt), self-relevant trauma-related words from a trauma-avoidant identity state (St), and trauma-related words from a trauma-related identity state (XSt). We found no differences in reaction times between XSt and St words and faster reaction times for XSt over NSt. Reaction times of the diagnosed DID group were the longest. Increased brain activation to XSt words was found in the frontal and parietal regions, while decreased brain activity was found in the anterior cingulate cortex in the diagnosed DID group. The current study reproduces and amalgamates previous behavioural reports as well as brain activation patterns. Our finding of increased cognitive control over self-relevant trauma-related knowledge processing has important clinical implications and calls for the redefinition of "inter-identity amnesia" to "inter-identity avoidance". [ABSTRACT FROM AUTHOR]

The major objective when applying non-destructive testing (NDT) in civil engineering is the detection of defects such as honeycombs. Defects can impair the service life of structures and could lead in the worst case to fatal failures. All structures such as bridges, tunnels, locks etc. are unique objects with variation in geometry, dimensions, materials, environmental condition, load scenarios etc. Thus, the interpretation of NDT data is challenging and the validation of the NDT method, the training of inspectors and the reliability analysis of NDT rely on mock-ups with known defect situations mimicking the type of defect as realistic as possible. The considered defect sizes inside the mock-ups should cover the transition zone between detectable and non-detectable to properly evaluate the capability of the inspection system. However, knowledge about the limits of an inspection system is mostly non-existent. To overcome this limitation, this study applies realistic numerical simulations for ultrasonic testing in reinforced concrete performed with the elastodynamic finite integration technique (EFIT) to identify this transition zone. First, the study shows the development and the validation of a numerical representation of concrete considering the implementation of a qualitatively realistic noise level. Additionally, the accurate representation of the sources during ultrasonic testing is confirmed by an investigation of the radiation characteristic for dry point contact ultrasonic transducers. The simulation outcome enabled the design of a mock-up, which explores the detection limits for honeycombs during ultrasonic testing under different boundary conditions. A case study demonstrates the applicability of the design scheme based on numerical simulation. In the real specimen designed with the assistance of numerical simulations, 68 % of the implemented defects are detectable, proving the effectiveness of the design methodology. [ABSTRACT FROM AUTHOR]

• A mathematical model for the lyophilization process is capable of addressing the heterogeneity of thermal characteristics of different vial suppliers, according to the design space concept. • The critical parameters for the primary drying stage, as predicted by the model, were experimentally tested using sucrose and sodium chloride solutions rendering lyophilized products of homogenous quality independently of the suppliers and the position of the vials on the lyophilizer shelf. Primary drying is the most critical stage of the freeze-drying process. This work aimed to establish a design space for this process by means of mathematical modeling of the primary drying stage, capable of addressing the thermal characteristics of distinct vial suppliers. Modeling of primary drying was implemented on Microsoft Excel using steady-state heat and mass transfer equations at two extreme conditions as assessed by risk analysis, to predict product temperature and primary-drying time. The heat transfer coefficients (K v) of four different vial suppliers were experimentally determined, both, at the center and edge of the freeze-dryer's shelf. Statistically significant differences (ANOVA p <0.05) were observed between suppliers throughout the assessed pressure range. Overall, the average K ve /K vc (edge/center) ratio was higher than 1.6 for all suppliers due to the radiation effect. A design space for the drying process was established using mathematical modeling taking into account the K v of the worst-case supplier, in the shelf edge. A primary drying cycle was carried out at a shelf temperature of -25 °C and a chamber pressure of 45 mTorr for 8 % sucrose and at -10 °C and 75 mTorr for 5 % NaCl. Freeze-dried products with good cosmetic appearance were obtained for the four vial suppliers both, in the shelf center and edge. The results show that it is possible to predict and establish the critical parameters for the primary drying stage, under a design space concept, considering the differences in the K v of vial suppliers without adverse consequences on the quality of the finished freeze-dried product. [ABSTRACT FROM AUTHOR]

This work simulated a modified three-dimensional single-track finite element model and a temperature discrimination mechanism in order to investigate the variation of temperature field in stainless steel and the effect of technological parameters on the coating. Through theoretical calculation, the distinction between the thermal characteristics of CoCrCuFeNi powders and CoCrCuFeNi alloys was made to improve the precision of simulation findings. In addition, to more precisely represent the heat transfer, an asymmetric Gaussian was used to distributed heat source and exponentially change the laser energy to account for the attenuation of laser power along the z-axis. The absorption rate of the laser beam at different temperatures of the material was also considered. The data was curve-fitted to examine the impact of laser power and scanning speed on the cladding layer morphologies. The laser power was found to be proportional to the width and depth of the clad layer, whereas the laser scanning speed was found to be inversely related to the width and depth of the clad layer. The simulation results were basically matched to the experiment. [ABSTRACT FROM AUTHOR]

This study proposes an alternative risk assessment approach for evaluating extreme air pollution events through vine copula modeling. Three characteristics of unhealthy air pollution events (i.e., severity, intensity, and duration) in Klang, Malaysia, are examined. The vine copula is fitted using sequential maximum likelihood estimation and joint maximum likelihood estimation, with a subsequent comparison based on criteria such as log-likelihood, Akaike's information criterion, and Bayesian's information criterion. Model fitting and comparison studies demonstrate that the most well-fitted vine copula model, achieved through joint maximum likelihood estimation, comprises the Joe, Rotated Tawn type 2 (180 degrees), and Rotated BB8 (90 degrees) copulas. The positive Kendall's τ correlation coefficient (0.26) for the obtained vine copula indicates that higher values of one characteristic are likely to be associated with higher values of the other characteristics, and vice versa. Furthermore, with the upper tail dependence coefficient (0.31) surpassing the lower tail dependence coefficient (0.18), indicating stronger dependence in the upper tail of their distribution, this underscores the significance of conducting risk assessments for extreme air pollution events characterized by extreme levels of severity, intensity, and duration. A vine copula-based simulation study is conducted to delve deeper into the risk assessment, revealing that extreme air pollution events are not linked to the highest values of joint and conditional probabilities. These findings suggest that extreme values in those distinct characteristics do not consistently occur simultaneously. The return period measures also indicate that extreme air pollution events have long waiting periods. Despite the current status of extreme air pollution events in Klang being controllable, achieving effective control necessitates ongoing efforts, encompassing regulatory actions, industrial controls, robust public transportation programs, and a dedicated transition to cleaner energy sources. This task is crucial for ensuring continuous clean air quality, sustaining our environment, and avoiding negative impacts on the economy and public well-being. [ABSTRACT FROM AUTHOR]

Archaeologists all over the world face problems regarding complexity and disorganization. Whether surveying, excavating, or doing laboratory analysis, the nature of the evidence of prehistoric societies is fragmented and incomplete. On a global and very general basis, the older the site, the greater the fragmentation, the more the missing data, and the greater the disorganization that the archaeologist must navigate to understand the past. Of course, there are notable exceptions. Most archaeologists consider the topic from the specificity of a particular time, a particular place, and a particular society. In this paper, it is considered in its most non-particular and general format. In order to do so, the paper creates an artificial archaeological region that is surveyed and excavated to a greater and lesser extent and analyzed with a variety of statistical and graphic evaluations. It concludes that when all other things are equal, increasing fragmentation causes far more disorganization and increases complexity than does missing data. Thus, fragmentation is a far more important problem for archaeological interpretation than relatively small amounts of missing data. [ABSTRACT FROM AUTHOR]

Background: Simulation models enable learners to have repeated practise at their own time, to master the psycho-motor and sensory acuity aspects of surgery and build their confidence in the procedure. The study aims to develop and evaluate the feasibility of a low-cost drilling model to train surgeons in the drilling task. The model targets three aspects of drilling – (1) Reduce plunge depth, (2) Ability to differentiate between bone and medullary canal and (3) Increase accuracy drilling in various angles. Methods: This cross-sectional study was conducted after obtaining ethics approval. We invited Consultants in the field of Orthopaedic or Hand Surgery to form the 'expert' group, and the 'novice' group consisted of participants who had no prior experience in bone drilling. We developed a drilling simulator model made from a polyvinyl chloride (PVC) pipe filled with liquid silicone. This model cost less than US$5. An electric Bosch drill (model GBM 10 RE) with a 1.4 mm K-wire 10 cm in length (6.5 cm outside the drill) was used for drilling. The main outcomes of the study were time taken for drilling, plunge depth, ability to penetrate the far cortex and accuracy. Results: Thirty-one participants were recruited into the study, of which 15 were experts and 16 were novices. The experts performed significantly better for plunge depth (t = −3.65, p = 0.0003) and accuracy (t = −2.07, p = 0.04). The experts required 20% less time to complete the drilling tasks, but it was not statistically significant (t = −0.79, p = 0.43). Conclusions: The low-cost drilling model could be useful in training Residents in the drilling task. It will allow Residents to practise independently at their own time and assess their own performance. [ABSTRACT FROM AUTHOR]

The injection of a polymer chain into a small circular cavity under tangential self-propelled force is studied by using Langevin dynamics simulation. Results indicate that the injection dynamics of the active polymer shows strong correlation with the polymer conformation inside the cavity depending on the polymer rigidity (kb). The injection time τ varies nonmonotonously with increasing kb, and reaches its minimum at kb*. When kb is small (kb ≪ kb*), the polymer is nearly random coil in the cavity, and spends a long time at the final stage of the injection process due to the large repulsion between monomers inside the cavity. When kb is moderate (kb ∼ kb*), the part of polymer inside the cavity forms spiral configuration under the tangential active force, and the whole polymer moves synchronously with a constant velocity during the injection process, leading to a small injection time. When kb is large (kb ≫ kb*), the polymer is nearly straight at the initial stage of the injection process, and takes a long time to bend itself, leading to a large injection time. [ABSTRACT FROM AUTHOR]

This study examines the supply chain network design (SCND) problem with multiple suppliers, warehouses and retailers in the presence of random disruptions using a two-stage approach. The first stage addresses the SCND problem without disruption, employing a genetic algorithm-based heuristic. This approach is integrated with the induced backorder for inventory coordination. In the second stage, simulation is used to evaluate several reactive strategies whilst introducing disruptions in the network and to adjust the inventory control parameters obtained in the first stage as part of a proactive strategy. The numerical results show that neglecting the risk of disruptions may lead to network designs with low fill rates and the proposed approach is able to make the supply chain network more resilient in the presence of disruptions. Based on the simulation results, a localized-reactive strategy is able to suppress the spread of disruptions to other supply channels. [ABSTRACT FROM AUTHOR]

This simulation study assessed the ability of Speech-Output Technologies (SOTs) to keep in-time during conversational repair. Fifty-eight Other Initiated Repair (OIR) initiators were collected from transcripts of repair interaction sequences collected from past research. A range of selection latencies were then used to calculate simulated utterance composition delays for the OIR initiators using two popular SOT software apps, with and without the use of word prediction. To determine whether OIR utterances could be produced within a socially sensitive temporal gap, composition delay was compared to a conservative temporal limit obtained for oral communicators (Kendrick, 2015). Even at the fastest 0.5 s selection latency level, utterance-level composition delays for both SOTs were substantially greater than the OIR limit set for this study. Next, AAC production rate data spanning a variety of technologies, access methods, tasks and user profiles was obtained from the literature. Communication performance for these groups was then evaluated against the identified temporal OIR limit. None of the user groups were found to be capable of producing full OIR utterances within the temporal limits of oral-speech conversation, with most unable to type even a single selection within these bounds. Because of the frequency and importance of repair in conversation, these results have important implications for designing devices to enable their users to successfully engage in such important conversational activities. [ABSTRACT FROM AUTHOR]

Six interprofessional (IP) poverty simulations were conducted at a mid-sized university from 2017 through 2019. Fifteen participants from five majors were interviewed to explore experiences, emotions, thoughts, attitudes, and applications to practice after the simulations. Themes related to poverty included empathy, thinking differently about poverty, demonstrating humility/respect, knowing/teaching resources, and profession-specific applications to practice. Interprofessional-related themes included the importance of the IP team, communication, and roles and responsibilities. The study found reflection with classroom and clinical content integration was critical to the participants' learning and transformation process. [ABSTRACT FROM AUTHOR]

• MRI may reduce induction of labor rates for macrosomia in a hypothetical cohort. • Repeating Boulvain's trial using MRI would result in similar rates of shoulder dystocia. • There is possible clinical utility of MRI in the management of macrosomia. To simulate the outcomes of Boulvain's trial by using magnetic resonance imaging (MRI) for estimated fetal weight (EFW) as a second-line confirmatory imaging. Data derived from the Boulvain's trial and the study PREMACRO (PREdict MACROsomia) were used to simulate a 1000-patient trial. Boulvain's trial compared induction of labor (IOL) to expectant management in suspected macrosomia, whereas PREMACRO study compared the performance of ultrasound-EFW (US-EFW) and MRI-EFW in the prediction of birthweight. The primary outcome was the incidence of significant shoulder dystocia (SD). Cesarean delivery (CD), hyperbilirubinemia (HB), and IOL at < 39 weeks of gestation (WG) were selected as secondary outcomes. A subgroup analysis of the Boulvain's trial was performed to estimate the incidence of the primary and secondary outcomes in the true positive and false positive groups for the two study arms. Sensitivity, specificity, positive and negative predictive values (PPV, NPV) for the prediction of macrosomia by MRI-EFW at 36 WG were calculated, and a decision tree was constructed for each outcome. The PPV of US-EFW for the prediction of macrosomia in the PREMACRO trial was 56.3 %. MRI-EFW was superior to US-EFW as a predictive tool resulting in lower rates of induction for false-positive cases. Repeating Boulvain's trial using MRI-EFW as a second-line test would result in similar rates of SD (relative risk [RR]:0.36), CD (RR:0.84), and neonatal HB (RR:2.6), as in the original trial. Increasing the sensitivity and specificity of MRI-EFW resulted in a similar relative risk for SD as in Boulvain's trial, but with reduced rates of IOL < 39 WG, and improved the RR of CD in favor of IOL. We found an inverse relationship between IOL rate and incidence of SD for both US-EFW and MRI-EFW, although overall rates of IOL, CD, and neonatal HB would be lower with MRI-derived estimates of fetal weight. The superior accuracy of MRI-EFW over US-EFW for the diagnosis of macrosomia could result in lower rates of IOL without compromising the relative advantages of the intervention but fails to demonstrate a significant benefit to justify a replication of the original trial using MRI-EFW as a second-line test. [ABSTRACT FROM AUTHOR]

This article focuses on unjust credibility deficits in cases of testimony about emotional reactions towards acts of oppression. It argues that the injustice in these cases is not rooted in the hearer's identity prejudices against the speaker, but the hearer's problematic way of dealing with his simulation of being in the speaker's situation. The simulation is in itself not morally problematic. However, I focus on a case where the hearer either recklessly or negligently fails to consider knowledge about the differences in people's emotional reactions and comes to believe that his simulated reaction is the only possible reaction, thus believing that the speaker does not report her emotions truthfully.In this case, the 'epistemic poison' results from the recklessness or negligence not necessarily from identity prejudice against the speaker. This credibility deficit is unjust, yet its persistent and systematic nature stems from the fact that a hearer who is not from the same marginalized or oppressed group as the speaker will simulate different emotional reactions to those reported by the speaker. Hence, the unjust credibility deficit can be connected to other forms of social injustices suffered by the speaker. [ABSTRACT FROM AUTHOR]

Is it impossible to imaginatively simulate what it's like to be someone with a different gender experience – to understand them empathically? Or is it simply difficult, a challenge requiring effort and dedication? I first distinguish three different sorts of obstacle to empathic understanding that are sometimes discussed: Missing Ingredient problems, Awkward Combination Problems, and Inappropriate Background Problems. I then argue that, although all three should be taken seriously, there is no clear reason to think that any of them are both genuinely intractable and also significant impediments to the kind of empathic understanding we might want. To that extent, the challenge to interpersonal understanding here may be more a matter of skill and work than a hard boundary. [ABSTRACT FROM AUTHOR]

When we learn about a severe moral transgression that has been committed, we are often not only horrified but also puzzled. We are inclined to raise questions such as 'Why did they do this?' or exclaim: 'I cannot understand why anyone would do such a thing!'. This suggests that there is something difficult to understand about severe moral wrongs. In this paper, I offer an explanation of the phenomenon that severe moral transgressions are often difficult to understand. I begin by arguing that the relevant sense in which we try but often fail to understand morally bad action is that we try but fail to empathize with the agent at the time of the action. Then, I introduce a distinction between two broad kinds of morally bad action. Finally, I show that each of these kinds of morally bad action gives rise to obstacles to empathizing with the agent at the time of the action. Based on this explanation, I consider whether we should try to overcome this limitation to our understanding. [ABSTRACT FROM AUTHOR]

As the adoption of digital twins increases steadily, it is necessary to determine how to operate them most effectively and efficiently. In this article, the digital twin synchronization problem is introduced and defined formally. Frequent synchronizations would increase cost and data traffic congestion, whereas infrequent synchronizations would increase the bias of the predictions and yield wrong decisions. This work defines the synchronization problem variants in different contexts. To discuss the problem and its solution, the problem of determining when to synchronize an unreliable production system with its digital twin to minimize the average synchronization and bias costs is formulated and analyzed analytically. The state-independent, state-dependent, and full-information solutions have been determined by using a stochastic model of the system. Solving the synchronization problem using simulation is discussed, and an approximate policy is proposed. Our results show that the performance of the state-dependent policy is close to the optimal solution that can be obtained with full information and significantly better than the performance of the state-independent policy. Furthermore, the approximate periodic state-dependent policy yields near-optimal results. To operate digital twins more effectively, the digital twin synchronization problem must be considered and solved to determine the optimal synchronization policy. [ABSTRACT FROM AUTHOR]

Introduction: Simulation training is an important component of medical education. In former studies, diagnostic simulation training for direct and indirect funduscopy was already proven to be an effective training method. In this prospective controlled trial, we investigated the effect of simulator-based fundus biomicroscopy training. Methods: After completing a 1-week ophthalmology clerkship, medical students at Saarland University Medical Center (n = 30) were block-randomized into two groups: The traditional group received supervised training examining the fundus of classmates using a slit lamp; the simulator group was trained using the Slit Lamp Simulator. All participants had to pass an Objective Structured Clinical Examination (OSCE); two masked ophthalmological faculty trainers graded the students' skills when examining patient's fundus using a slit lamp. A subjective assessment form and post-assessment surveys were obtained. Data were described using median (interquartile range [IQR]). Results: Twenty-five students (n = 14 in the simulator group, n = 11 in the traditional group) (n = 11) were eligible for statistical analysis. Interrater reliability was verified as significant for the overall score as well as for all subtasks (≤ 0.002) except subtask 1 (p = 0.12). The overall performance of medical students in the fundus biomicroscopy OSCE was statistically ranked significantly higher in the simulator group (27.0 [5.25]/28.0 [3.0] vs. 20.0 [7.5]/16.0 [10.0]) by both observers with an interrater reliability of IRR < 0.001 and a significance level of p = 0.003 for observer 1 and p < 0.001 for observer 2. For all subtasks, the scores given to students trained using the simulator were consistently higher than those given to students trained traditionally. The students' post-assessment forms confirmed these results. Students could learn the practical backgrounds of fundus biomicroscopy (p = 0.04), the identification (p < 0.001), and localization (p < 0.001) of pathologies significantly better with the simulator. Conclusions: Traditional supervised methods are well complemented by simulation training. Our data indicate that the simulator helps with first patient contacts and enhances students' capacity to examine the fundus biomicroscopically. [ABSTRACT FROM AUTHOR]

Using videos as tools for reflection has a strong grounding in the research literature. Traditionally, these videos provide representations of K-12 students interacting with one another and their teacher during small or whole group instruction and come from teachers' own or their peers' classrooms. More recently, online simulated classrooms have been used as practice spaces to support teachers in learning how to engage in core teaching practices, such as facilitating discussions. The purpose of this study was to explore the potential usefulness of video records generated from online simulations as a tool for self-reflection. To do so, we examined the nature of in-service elementary teachers' self-reflections from video records of them facilitating argumentation-focused discussions with five student avatars in an online simulated classroom. Findings suggest that most teachers' reflections on their discussion practice tended to be positive in nature. In addition, findings suggest that most in-service teachers used multiple pieces of evidence to justify their overall quality assessment of their discussion on five key dimensions of argumentation-focused discussions. The types of evidence they used were aligned with how a scoring rubric defined these dimensions but varied in nature across the participants. Finally, findings show that study participants tend to draw upon both what they and students say and do during these discussions as evidence to support their overall assertions about how well they attended to specific discussion dimensions. Implications for using videos from online teaching simulations as tools for reflection are discussed. [ABSTRACT FROM AUTHOR]

Surveillance of human subjects is how data-intensive companies obtain much of their data, yet surveillance increasingly meets with social and regulatory resistance. Data-intensive companies are thus seeking other ways to meet their data needs. This article explores one of these: the creation of synthetic data, or data produced artificially as an alternative to real-world data. I show that capital is already heavily invested in synthetic data. I argue that its appeal goes beyond circumventing surveillance to accord with a structural tendency within capitalism toward the autonomization of the circuit of capital. By severing data from human subjectivity, synthetic data contributes to the automation of the production of automation technologies like machine learning. A shift from surveillance to synthesis, I argue, has epistemological, ontological, and political economic consequences for a society increasingly structured around data-intensive capital. [ABSTRACT FROM AUTHOR]

To explore the effects of waste heat (50–170°C) from steel plant flue gas on the column photobioreactor algal liquid temperature for microalgal production, a flue gas‐microalgal liquid heat transfer model was developed that simulated the microalgal growth environment for flue‐gas carbon dioxide (CO2) fixation. The simulation results showed that the influence of high‐temperature flue gas weakened with the increasing microalgal liquid temperature due to enhanced evaporation and heat dissipation. Increasing the flue gas temperature and aeration rate resulted in a higher microalgal liquid temperature up to a maximum increase of 4.16°C at an ambient temperature of 25°C, an aeration rate of 2 L/min, and a flue gas temperature of 170°C. In an experiment on the effect of incubation temperature on the growth rate of microalgae, at an optimal temperature of 35°C, the Chlorella sp. PY‐ZU1 growth rate exhibited a remarkable increase of 104.7% compared to that at 42.5°C. Therefore, modulating the flue gas conditions can significantly increase the microalgal growth rate for CO2 fixation, making it a promising approach to increase biomass production for efficient carbon utilization. [ABSTRACT FROM AUTHOR]

This comprehensive research addresses the significant challenge of building‐related energy consumption in Morocco. Our innovative approach involves integrating phase change materials (PCMs) into hollow bricks, strategically addressing the diverse climate zones prevalent in the country. The primary focus is on enhancing energy efficiency within structures. Leveraging detailed simulations and employing the enthalpy‐porosity approach, our study models the impact of PCMs on internal temperatures. Optimal outcomes are achieved by partially filling brick holes with PCMs in specific configurations, demonstrating the materials' ability to adapt to varying conditions. A noteworthy finding is the 2–3‐h phase shift observed in cold zones, indicating the potential for PCMs to effectively regulate temperatures. Equally significant is their capability to maintain a constant internal temperature of 26°C in hot zones, even amidst extreme external conditions reaching up to 47°C. This resilience underscores the novel and tailored thermal regulation potential of PCMs. Beyond the technical insights, our research highlights the paramount importance of considering regional climates in PCM applications' implementation. This awareness is crucial for optimizing energy performance in buildings and ensuring sustainability. In essence, this study contributes valuable knowledge and practical implications for the strategic deployment of PCMs to enhance building energy efficiency, emphasizing the need for context‐specific solutions in diverse environmental conditions. [ABSTRACT FROM AUTHOR]

Friction stir welding (FSW) produces inhomogeneous mechanical and metallurgical properties in the weld, which further require post-weld processing to control the heterogeneity. In the present study, the heterogeneity in the weld is reduced through counter-variable rotation friction stir welding (CVRFSW). The material flow and temperature distribution significantly affect the inhomogeneity of the FSWed properties which has been studied by developing a three-dimensional Lagrangian method-based viscoplastic model. The material flow, strain rate, and temperature distribution in conventional FSW (CFSW) and CVRFSW are studied quantitatively. The study revealed that CVRFSW improved joint strength and reduced the inhomogeneity of temperature, strain, and hardness. At a 10% lower shoulder speed than a pin, the weld strength improved by 16%. The simulation predicted that the temperature difference between the advancing side (AS) and the retreating side (RS) was 36 °C in CFSW, which was reduced to 8 °C in CVRFSW. Material deformation in CVRFSW occurred at a strain rate more than twice that of CFSW, and the asymmetry of strain rate between AS and RS reduced to one-fifth. Microstructures and their orientations of the welds were studied in detail. These findings contribute to the understanding of CVRFSW processes for enhanced weld quality and mechanical performance for industrial applications. [ABSTRACT FROM AUTHOR]

A comprehensive approach to creating a control system for the shape of the radio-reflecting surface of a large-size space reflector is considered. Large-aperture space antennas are used for satellite communications and space exploration. The design of these structures is one of the most promising areas. Ensuring the specified characteristics of the reflector is directly related to maintaining the specified shape of the radio-reflective netting. Developing a control system for the shape of the active antenna surface is an urgent task. Optimizing this process makes it possible to accomplish the mission during the operational period effectively. The paper evaluates the effects of perturbations on a large-scale structure operating in outer space. A method for adjusting the geometry of the frontal network is proposed. This allows for improved communication between spacecraft and ground stations, which is very important for the safety of space flights. The conductive parts of the reflector are considered to transmit energy and control signals to the actuators. The application results of various control algorithms of the executive device making it possible to correct the netting considering the minimization of energy costs and oscillations of the structure are shown. According to the simulation results, the optimal algorithm of the target criteria hierarchy showed greater stability in terms of convergence in the presence of measurement noise and disturbances, which allows it to be applied in real time. This algorithm is supposed to be used in the future when creating a prototype of the system for controlling the shape of the radio-reflective surface of a large-size space reflector using its current-conducting structural parts. • The design of a system for setting up and maintaining a radio-reflective network fabric has been developed. • Algorithms are developed to minimize energy when setting up a radio-reflective mesh. • The optimal algorithm of the control allows solving the problem in real time. • The method for transmitting energy and control signals through the use of conductive structural parts of the reflector is proposed. [ABSTRACT FROM AUTHOR]