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Background: Laparoscopic surgery is associated with a prolonged learning curve for emerging surgeons, and simulation-based training (SBT) has become increasingly prominent in this context due to stringent working time regulations and heightened concerns regarding patient safety. While SBT offers a safe and ethical learning environment, the accuracy of simulators in the context of evaluating surgical skills remains uncertain. This study aims to assess the precision of a laparoscopic simulator with regard to evaluating surgical performance and to identify the instructor's role in SBT. Materials and methods: This retrospective study focused on surgical residents in their 1st through 5th years at the Department of Surgery of Linkou Chang Gung Memorial Hospital. The residents participated in a specially designed SBT program using the LapSim laparoscopic simulator. Following the training session, each resident was required to perform a laparoscopic procedure and received individualized feedback from an instructor. Both simulator and instructor evaluated trainees' performance on the LapSim, focusing on identifying correlations between the simulator's metrics and traditional assessments. Results: Senior residents (n = 15), who employed more complex laparoscopic procedures, exhibited more significant improvements after receiving instructor feedback than did junior residents (n = 17). Notably, a stronger correlation between the simulator and instructor assessments was observed in the junior group (junior Global Operative Assessment of Laparoscopic Skills (GOALS) adjusted R2 = 0.285, p = 0.016), while no such correlations were observed among the senior group. Conclusion: A well-designed, step-by-step SBT can be a valuable tool in laparoscopic surgical training. LapSim simulator has demonstrated its potential in assessing surgical performances during the early stages of surgical training. However, instructors must provide intuitive feedback to ensure appropriate learning in later stages. [ABSTRACT FROM AUTHOR]

Background: Simulation-Based Learning (SBL) serves as a valuable pedagogical approach in nursing education, encompassing varying levels of fidelity. While previous reviews have highlighted the potential effectiveness of SBL in enhancing nursing students' competencies, a gap persists in the evidence-base addressing the long-term retention of these competencies. This systematic review aimed to evaluate the impact of SBL on nursing students' knowledge and skill acquisition and retention. Method: A comprehensive search of electronic databases, including CINAHL, PubMed, Embase, Scopus, and Eric, was conducted from 2017 to 2023 to identify relevant studies. The Joanna Briggs critical appraisal tools were used to assess the methodological quality of the included studies. A total of 33 studies (15 RCTs and 18 quasi-experimental) met the inclusion criteria and were included in the review. A descriptive narrative synthesis method was used to extract relevant data. Results: The cumulative sample size of participants across the included studies was 3,670. Most of the studies focused on the impact of SBL on life-saving skills like cardiopulmonary resuscitation (CPR) or other life-support skills. The remaining studies examined the impact of SBL on critical care skills or clinical decision-making skills. The analysis highlighted consistent and significant improvements in knowledge and skills. However, the evidence base had several limitations, including the heterogeneity of study designs, risk of bias, and lack of long-term follow-up. Conclusion: This systematic review supports the use of SBL as a potent teaching strategy within nursing education and highlights the importance of the ongoing evaluation and refinement of this approach. While current evidence indicates enhancing knowledge and skill acquisition, limited studies evaluated the retention beyond five months, constraining generalisable claims regarding durability. Further research is essential to build on the current evidence and address gaps in knowledge related to the retention, optimal design, implementation, and evaluation of SBL interventions in nursing education. [ABSTRACT FROM AUTHOR]

Background: Computer simulators of human metabolism are powerful tools to design and validate new diabetes treatments. However, these platforms are often limited in the diversity of behaviors and glycemic conditions they can reproduce. Replay methodologies leverage field-collected data to create ad hoc simulation environments representative of real-life conditions. After formal validations of our method in prior publications, we demonstrate its capacity to reproduce a recent clinical trial. Methods: Using the replay methodology, an ensemble of replay simulators was generated using data from a randomized crossover clinical trial comparing the hybrid closed loop (HCL) and fully closed loop (FCL) control modalities in automated insulin delivery (AID), creating 64 subject/modality pairs. Each virtual subject was exposed to the alternate AID modality to compare the simulated versus observed glycemic outcomes. Equivalence tests were performed for time in, below, and above range (TIR, TBR, and TAR) and high and low blood glucose indices (HBGI and LBGI) considering equivalence margins corresponding to clinical significance. Results: TIR, TAR, LBGI, and HBGI showed statistical and clinical equivalence between the original and the simulated data; TBR failed the equivalence test. For example, in the HCL mode, simulated TIR was 84.89% versus an observed 84.31% (P = 0.0170, confidence interval [CI] [−3.96, 2.79]), and for FCL mode, TIR was 76.58% versus 77.41% (P = 0.0222, CI [−2.54, 4.20]). Conclusion: Clinical trial data confirm the prior in silico validation of the UVA replay method in predicting the glycemic impact of modified insulin treatments. This in vivo demonstration justifies the application of the replay method to the personalization and adaptation of treatment strategies in people with type 1 diabetes. [ABSTRACT FROM AUTHOR]

Background: Several computational and mathematical models of protein synthesis have been explored to accomplish the quantitative analysis of protein synthesis components and polysome structure. The effect of gene sequence (coding and non-coding region) in protein synthesis, mutation in gene sequence, and functional model of ribosome needs to be explored to investigate the relationship among protein synthesis components further. Ribosomal computing is implemented by imitating the functional property of protein synthesis. Result: In the proposed work, a general framework of ribosomal computing is demonstrated by developing a computational model to present the relationship between biological details of protein synthesis and computing principles. Here, mathematical abstractions are chosen carefully without probing into intricate chemical details of the micro-operations of protein synthesis for ease of understanding. This model demonstrates the cause and effect of ribosome stalling during protein synthesis and the relationship between functional protein and gene sequence. Moreover, it also reveals the computing nature of ribosome molecules and other protein synthesis components. The effect of gene mutation on protein synthesis is also explored in this model. Conclusion: The computational model for ribosomal computing is implemented in this work. The proposed model demonstrates the relationship among gene sequences and protein synthesis components. This model also helps to implement a simulation environment (a simulator) for generating protein chains from gene sequences and can spot the problem during protein synthesis. Thus, this simulator can identify a disease that can happen due to a protein synthesis problem and suggest precautions for it. [ABSTRACT FROM AUTHOR]

In power plants, one of the important maneuvers is the switching of pumps, where incorrect execution can even cause the unit to shut down. Therefore, the objective of this paper is to create a virtual environment for training the critical maneuver of the pump switching operation. The method used as reference was the specific procedure for the actual execution of the pump switching maneuver. Then the procedure was interpreted in order to reproduce in the virtual environment the same behaviors as in the real environment. Subsequently, visits to the field, control room, and control room simulator were undertaken in order to obtain material and data for the assembly of the virtual environment. Finally, with all the information collected, a virtual environment was created. The result was the creation of a system and equipment of interest for switching pumps interactively in the virtual environment, with great fidelity to the real environment. Tests were done by nuclear power plant operators and instructors on this virtual environment. The test results of this group demonstrated that the virtual environment created is a good tool to significantly assist in this type of training, as it promotes the experience of imposed challenges, which are common to several other systems of a nuclear power plant. In this way, the choice of a system to be reproduced in a virtual environment that represents the challenge of training critical maneuvers that affect the reactor was fundamental. [ABSTRACT FROM AUTHOR]

Background: Microsurgical clipping is a delicate neurosurgical procedure used to treat complex Unruptured Intracranial Aneurysms (UIAs) whose outcome is dependent on surgeon's experience. Simulations are emerging as excellent complements to standard training, but their adoption is limited by the realism they provide. The aim of this study was to develop and validate a microsurgical clipping simulator platform. Methods: Physical and holographic simulators of UIA clipping have been developed. The physical phantom consisted of a 3D printed hard skull and five (n = 5) rapidly interchangeable, perfused and fluorescence compatible 3D printed aneurysm silicone phantoms. The holographic clipping simulation included a real-time finite-element-model of the aneurysm sac, allowing interaction with a virtual clip and its occlusion. Validity, usability, usefulness and applications of the simulators have been assessed through clinical scores for aneurysm occlusion and a questionnaire study involving 14 neurosurgical residents (R) and specialists (S) for both the physical (p) and holographic (h) simulators by scores going from 1 (very poor) to 5 (excellent). Results: The physical simulator allowed to replicate successfully and accurately the patient-specific anatomy. UIA phantoms were manufactured with an average dimensional deviation from design of 0.096 mm and a dome thickness of 0.41 ± 0.11 mm. The holographic simulation executed at 25–50 fps allowing to gain unique insights on the anatomy and testing of the application of several clips without manufacturing costs. Aneurysm closure in the physical model evaluated by fluorescence simulation and post-operative CT revealed Raymond 1 (full) occlusion respectively in 68.89% and 73.33% of the cases. For both the simulators content validity, construct validity, usability and usefulness have been observed, with the highest scores observed in clip selection usefulness Rp=4.78, Sp=5.00 and Rh=4.00, Sh=5.00 for the printed and holographic simulators. Conclusions: Both the physical and the holographic simulators were validated and resulted usable and useful in selecting valid clips and discarding unsuitable ones. Thus, they represent ideal platforms for realistic patient-specific simulation-based training of neurosurgical residents and hold the potential for further applications in preoperative planning. [ABSTRACT FROM AUTHOR]

Recent advancements in vehicle technology have stimulated innovation across the automotive sector, from Advanced Driver Assistance Systems (ADAS) to autonomous driving and motorsport applications. Modern vehicles, equipped with sensors for perception, localization, navigation, and actuators for autonomous driving, generate vast amounts of data used for training and evaluating autonomous systems. Real-world testing is essential for validation but is complex, expensive, and time-intensive, requiring multiple vehicles and reference systems. To address these challenges, computer graphics-based simulators offer a compelling solution by providing high-fidelity 3D environments to simulate vehicles and road users. These simulators are crucial for developing, validating, and testing ADAS, autonomous driving systems, and cooperative driving systems, and enhancing vehicle performance and driver training in motorsport. This paper reviews computer graphics-based simulators tailored for automotive applications. It begins with an overview of their applications and analyzes their key features. Additionally, this paper compares five open-source (CARLA, AirSim, LGSVL, AWSIM, and DeepDrive) and ten commercial simulators. Our findings indicate that open-source simulators are best for the research community, offering realistic 3D environments, multiple sensor support, APIs, co-simulation, and community support. Conversely, commercial simulators, while less extensible, provide a broader set of features and solutions. [ABSTRACT FROM AUTHOR]

Introduction: Shooting simulations provide an excellent opportunity to train use-of-force decisions in controlled environments. Recently, military and law enforcement organizations have expressed a growing desire to integrate physiological measurement into simulations for training and feedback purposes. Although participants can easily wear physiological monitors in these scenarios, direct implementation into training may not be simple. Theoretical problems exist in the ultra-short heart rate variability windows associated with use-offorce training, and practical problems emerge as existing scenario libraries at training organizations were not designed for physiological monitoring. Methods: The current study explored the challenges and possibilities associated with direct implementation of physiological monitoring into an existing library of firearms training scenarios. Participants completed scenarios in a shooting simulator using existing military training scenarios while wearing a device to monitor their heart rate. Results: The results revealed lower heart rate variability (approximately 6%) occurred in scenarios where participants did not have to fire weapons, indicating that don't-shoot scenarios may actually impose more cognitive stress on shooters. Additional evidence further demonstrated how both behavioral and physiological factors could be used concomitantly to predict unintentionally firing on non-hostile actors. However, behavioral measures were more predictive (e.g., χ = .221) than physiological measures (e.g., χ = -.132) when the latter metrics were limited to specific scenarios. Qualitative results suggest that simply applying physiological monitoring to existing shooting simulations may not yield optimal results because it would be difficult to directly integrate physiological measurement in a meaningful way without re-designing some elements of the simulations, the training procedure, or both. Discussion: Future use-of-force shooting simulations should consider designing novel scenarios around the physiological measurement rather than directly implementing physiological assessments into existing libraries of scenarios. [ABSTRACT FROM AUTHOR]

Objective: To determine the reliability of the Carousel simulator in medical education for obstetric examinations. Cervical dilation examination training in pregnant women exposes patients to additional uncomfortable and health‐risk procedures, a gold standard, and does not objectively evaluate the medical student's competence. Method: We studied the reliability of training internship medical students in obstetrics. Participating students were assigned to take the examination of digital assessment of the cervical dilation on the simulator. Classes performed 12 consecutive randomly blind predetermined cervical dilation examinations using the Carousel simulator. The exact answer and the answer with certainty within ±1 cm were registered and analyzed. Incorrect or outlier answers were considered with a cutoff of ≥2 cm from the dilation. A dispersion graph for each centimeter of dilation simulation was constructed. Results: Sixty‐six medical obstetricians took part, performing 396 examinations. Thus, we observed 49 outliers (12.37%) in simulated assessments. According to the analysis, we did not observe outliers from dilation 1 to 4 cm; dilation 7 to 9 cm had a higher index of outlier measurements. We did not consider any dilation simulation dispersion graphic as a null correlation. A strong correlation was seen in the dilation 1 to 6 cm and the dilation 10 cm. The dilations 7, 8, and 9 cm showed a weak correlation. Conclusion: The Carousel simulator model is a reliable method for student learning. The simulator is an essential study tool capable of reducing the embarrassment and possible harm caused by the excessive and repetitive number of in vivo digital vaginal examinations. Novel studies are proposed to improve the simulator device and method, mainly to estimate the adequate repetitions and training needed before in vivo practice. Synopsis: We demonstrated the reliability of a novel simulator device used for digital vaginal examination of cervical dilation during labor for medical education. [ABSTRACT FROM AUTHOR]

Assessing the efficacy of algorithms plays a pivotal role in advancing various fields, both in theory and practice. Unlike the predictive models, due to the intricate relationship between decisions and the underlying data‐generating processes, the evaluation of decision algorithms cannot directly rely on real data. Hence, a simulator becomes indispensable for appraising decision algorithm effectiveness. In this paper, we aim to leverage assortment decisions, a widely used application in revenue management, to illustrate the utilization of a machine learning‐based simulation. The process can be summarised as: we utilize the modified Transformer‐based choice model, acting as a simulator, to generate a synthetic dataset that mimics consumer purchasing behavior. After training the MNL, DeepFM, and DeepFM‐a models, all of which can swiftly provide assortment decisions in real‐time, we utilize the simulator to evaluate the revenue generated by each assortment prescribed by different choice models. This approach mitigates the challenge of validating decision models that alter real‐world observed data. To show the benefit of such a simulation approach, we have conducted various numerical studies. These studies aim to examine the impact of outside option attractiveness, data size, the number of features, and cardinality. Admittedly, due to the close alignment between the simulator and complex consumer purchase choice datasets, some numerical observations may be challenging to explain. Nevertheless, by employing the simulator, we are able to contrast the differences between the MNL and DeepFM/DeepFM‐a models, shedding light on their respective model misspecifications. [ABSTRACT FROM AUTHOR]

Reinforcement learning is a crucial area of machine learning, with a wide range of applications. To conduct experiments in this research field, it is necessary to define the algorithms and parameters to be applied. However, this task can be complex because of the variety of possible configurations. In this sense, the adoption of AutoRL systems can automate the selection of these configurations, simplifying the experimental process. In this context, this work aims to propose a simulation environment for combinatorial optimization problems using AutoRL. The AutoRL-Sim includes several experimentation modules that cover studies on the symmetric traveling salesman problem, the asymmetric traveling salesman problem, and the sequential ordering problem. Furthermore, parameter optimization is performed using response surface models. The AutoRL-Sim simulator allows users to conduct experiments in a more practical way, without the need to worry about implementation. Additionally, they have the ability to analyze post-experiment data or save them for future analysis. [ABSTRACT FROM AUTHOR]

Traditional road testing of autonomous vehicles faces significant limitations, including long testing cycles, high costs, and substantial risks. Consequently, autonomous driving simulators and dataset-based testing methods have gained attention for their efficiency, low cost, and reduced risk. Simulators can efficiently test extreme scenarios and provide quick feedback, while datasets offer valuable real-world driving data for algorithm training and optimization. However, existing research often provides brief and limited overviews of simulators and datasets. Additionally, while the role of virtual autonomous driving competitions in advancing autonomous driving technology is recognized, comprehensive surveys on these competitions are scarce. This survey paper addresses these gaps by presenting an in-depth analysis of 22 mainstream autonomous driving simulators, focusing on their accessibility, physics engines, and rendering engines. It also compiles 35 open-source datasets, detailing key features in scenes and data-collecting sensors. Furthermore, the paper surveys 10 notable virtual competitions, highlighting essential information on the involved simulators, datasets, and tested scenarios involved. Additionally, this review analyzes the challenges in developing autonomous driving simulators, datasets, and virtual competitions. The aim is to provide researchers with a comprehensive perspective, aiding in the selection of suitable tools and resources to advance autonomous driving technology and its commercial implementation. [ABSTRACT FROM AUTHOR]

In many industries, there is a continuous high demand for skilled welders. Practical training in welding is cost- and time-intensive. To reduce this problem, VR welding simulators have been developed in recent years. They vary in terms of portability, hardware and software components, and functionalities. In this paper, a VR simulator to support practical training in MIG/MAG welding, as a highly portable and affordable solution, is presented. Its only hardware components are an off-the-shelf mobile VR set, a welding torch, and welding coupons that are manufactured using the FDM 3D printing method. The software part is accessed and used via an Internet browser. An important feature of the simulator is also the possibility to differ immersion in the working environment while carrying out virtual welding, which makes the solution also usable for users prone to cybersickness. The VR welding simulator was refined based on feedback obtained during pilot tests. The test participants found it a useful aid for welders' training, which justifies further work on its development and integration into the teaching of welding in educational and training units. [ABSTRACT FROM AUTHOR]

Anticipatory brain activity makes it possible to predict the occurrence of expected situations. However, events such as traffic accidents are statistically unpredictable and can generate catastrophic consequences. This study investigates the brain activity and effective connectivity associated with anticipating and processing such unexpected, unavoidable accidents. We asked 161 participants to ride a motorcycle simulator while recording their electroencephalographic activity. Of these, 90 participants experienced at least one accident while driving. We conducted both within‐subjects and between‐subjects comparisons. During the pre‐accident period, the right inferior parietal lobe (IPL), left anterior cingulate cortex (ACC), and right insula showed higher activity in the accident condition. In the post‐accident period, the bilateral orbitofrontal cortex, right IPL, bilateral ACC, and middle and superior frontal gyrus also showed increased activity in the accident condition. We observed greater effective connectivity within the nodes of the limbic network (LN) and between the nodes of the attentional networks in the pre‐accident period. In the post‐accident period, we also observed greater effective connectivity between networks, from the ventral attention network (VAN) to the somatomotor network and from nodes in the visual network, VAN, and default mode network to nodes in the frontoparietal network, LN, and attentional networks. This suggests that activating salience‐related processes and emotional processing allows the anticipation of accidents. Once an accident has occurred, integration and valuation of the new information takes place, and control processes are initiated to adapt behavior to the new demands of the environment. [ABSTRACT FROM AUTHOR]

OBJECTIVE: To assess attempts to proficiency of experienced veterinary surgeons for 2 surgical tasks when using a robotic simulator (Mimic dV-Trainer; Surgical Sciences) and determine factors associated with the successful performance of these tasks. METHODS: Veterinary surgeons with rigid, minimally invasive surgery experience performed 2 tasks ("pick and place" and "knot the ring 1") using the simulator until they attained proficiency. Individual performance variables were recorded. The number of attempts to proficiency was recorded. Performance variables were also assessed for effect on proficiency by the Kendall tau correlation and hierarchical multiple linear regression. The study period was from July 25, 2022, through December 14, 2022. RESULTS:Tled required a median of 8.5 attempts (95% CI, 7 to 12; range, 6 to 22) to reach proficiency for the basic task versus 27 attempts (95% CI, 21 to 38; range, 10 to 63) for the advanced task. Surgeons took a median of 6 minutes (range, 3 to 11 minutes) to complete training for the basic task and 12 minutes (range, 4 to 46 minutes) for the advanced task. The number of attempts to reach proficiency correlated strongly with economy of motion (tau = 0.72), instrument collisions (tau = 0.72), and time to completion (tau = 0.96). [ABSTRACT FROM AUTHOR]

Offloading computation-intensive tasks of an application from a mobile device to a remote computation resource can improve the runtime of the application as well as improve the lifetime of the mobile device's battery. However, computation offloading is a complex endeavour: remote computation resources in the cloud and in the fog have different computation capabilities and costs, and the network bandwidth and latency between different resources need to be taken into account. In addition, the mobile device would ideally like to offload multiple applications simultaneously, further adding to the complexity of assigning different tasks of each application to available computation resources. In this paper, we introduce an open-source versatile computation offloading simulator (OVCOSim), capable of simulating and optimizing offloading multiple applications to different cloud and fog resources and visualizing the outcome for users. We demonstrate how OVCOSim can be used to optimize assignment of tasks to computation resources to accommodate different user objectives, runtime, battery life, cost, or a combination of these objectives, using a variety of assignment algorithms. We also provide several examples to demonstrate how OVCOSim can be used, as well as validate its functionality. [ABSTRACT FROM AUTHOR]

Purpose: Minimally invasive surgery for gastrointestinal cancers is rapidly advancing; therefore, surgical education must be changed. This study aimed to examine the feasibility of early initiation of robotic surgery education for surgical residents. Methods: The ability of staff physicians and residents to handle robotic surgical instruments was assessed using the da Vinci® skills simulator (DVSS). The short-term outcomes of 32 patients with colon cancer who underwent robot-assisted colectomy (RAC) by staff physicians and residents, supervised by a dual console system, between August 2022 and March 2024 were compared. Results: The performances of four basic exercises were assessed after implementation of the DVSS. Residents required less time to complete these exercises and achieved a higher overall score than staff physicians. There were no significant differences in the short-term outcomes, operative time, blood loss, incidence of postoperative complications, and length of the postoperative hospital stay of the two surgeon groups. Conclusion: Based on the evaluation involving the DVSS and RAC results, it appears feasible to begin robotic surgery training at an early stage of surgical education using a dual console system. [ABSTRACT FROM AUTHOR]

Abstract Background Microsurgical clipping is a delicate neurosurgical procedure used to treat complex Unruptured Intracranial Aneurysms (UIAs) whose outcome is dependent on surgeon’s experience. Simulations are emerging as excellent complements to standard training, but their adoption is limited by the realism they provide. The aim of this study was to develop and validate a microsurgical clipping simulator platform. Methods Physical and holographic simulators of UIA clipping have been developed. The physical phantom consisted of a 3D printed hard skull and five (n = 5) rapidly interchangeable, perfused and fluorescence compatible 3D printed aneurysm silicone phantoms. The holographic clipping simulation included a real-time finite-element-model of the aneurysm sac, allowing interaction with a virtual clip and its occlusion. Validity, usability, usefulness and applications of the simulators have been assessed through clinical scores for aneurysm occlusion and a questionnaire study involving 14 neurosurgical residents (R) and specialists (S) for both the physical (p) and holographic (h) simulators by scores going from 1 (very poor) to 5 (excellent). Results The physical simulator allowed to replicate successfully and accurately the patient-specific anatomy. UIA phantoms were manufactured with an average dimensional deviation from design of 0.096 mm and a dome thickness of 0.41 ± 0.11 mm. The holographic simulation executed at 25–50 fps allowing to gain unique insights on the anatomy and testing of the application of several clips without manufacturing costs. Aneurysm closure in the physical model evaluated by fluorescence simulation and post-operative CT revealed Raymond 1 (full) occlusion respectively in 68.89% and 73.33% of the cases. For both the simulators content validity, construct validity, usability and usefulness have been observed, with the highest scores observed in clip selection usefulness Rp=4.78, Sp=5.00 and Rh=4.00, Sh=5.00 for the printed and holographic simulators. Conclusions Both the physical and the holographic simulators were validated and resulted usable and useful in selecting valid clips and discarding unsuitable ones. Thus, they represent ideal platforms for realistic patient-specific simulation-based training of neurosurgical residents and hold the potential for further applications in preoperative planning.

Reinforcement learning is a crucial area of machine learning, with a wide range of applications. To conduct experiments in this research field, it is necessary to define the algorithms and parameters to be applied. However, this task can be complex because of the variety of possible configurations. In this sense, the adoption of AutoRL systems can automate the selection of these configurations, simplifying the experimental process. In this context, this work aims to propose a simulation environment for combinatorial optimization problems using AutoRL. The AutoRL-Sim includes several experimentation modules that cover studies on the symmetric traveling salesman problem, the asymmetric traveling salesman problem, and the sequential ordering problem. Furthermore, parameter optimization is performed using response surface models. The AutoRL-Sim simulator allows users to conduct experiments in a more practical way, without the need to worry about implementation. Additionally, they have the ability to analyze post-experiment data or save them for future analysis.

Aims: Patient dissatisfaction is not uncommon following primary total knee arthroplasty. One proposed method to alleviate this is by improving knee kinematics. Therefore, we aimed to answer the following research question: are there significant differences in knee kinematics based on the design of the tibial insert (cruciate-retaining (CR), ultra-congruent (UC), or medial congruent (MC))? Methods: Overall, 15 cadaveric knee joints were examined with a CR implant with three different tibial inserts (CR, UC, and MC) using an established knee joint simulator. The effects on coronal alignment, medial and lateral femoral roll back, femorotibial rotation, bony rotations (femur, tibia, and patella), and patellofemoral length ratios were determined. Results: No statistically significant differences were found regarding coronal alignment (p = 0.087 to p = 0.832). The medial congruent insert demonstrated restricted femoral roll back (mean medial 37.57 mm; lateral 36.34 mm), while the CR insert demonstrated the greatest roll back (medial 42.21 mm; lateral 37.88 mm; p < 0.001, respectively). Femorotibial rotation was greatest with the CR insert with 2.45° (SD 4.75°), then the UC insert with 1.31° (SD 4.15°; p < 0.001), and lowest with the medial congruent insert with 0.8° (SD 4.24°; p < 0.001). The most pronounced patella shift, but lowest patellar rotation, was noted with the CR insert. Conclusion: The MC insert demonstrated the highest level of constraint of these inserts. Femoral roll back, femorotibial rotation, and single bony rotations were lowest with the MC insert. The patella showed less shifting with the MC insert, but there was significantly increased rotation. While the medial congruent insert was found to have highest constraint, it remains uncertain if this implant recreates native knee kinematics or if this will result in improved patient satisfaction. Cite this article: Bone Jt Open 2024;5(7):592–600.

Abstract Introduction Non-ophthalmologists often lack sufficient operational training to use a direct ophthalmoscope proficiently, resulting in a global deficit of basic ophthalmological skills among general practitioners. This deficiency hampers the timely diagnosis, referral, and intervention of patients. Consequently, the optimization of teaching tools and methods to enhance teaching efficiency is imperative. This study explores the effectiveness of the Eyesi Direct Ophthalmoscope Simulator (Eyesi) as an innovative tool for fundus examination training. Methods Medical undergraduates were randomly assigned to Group A or B (n = 168). All participants completed a pre-training questionnaire. Group A received Eyesi training, while Group B underwent traditional direct ophthalmoscope (TDO) training. Subsequently, participants answered questionnaires relevant to their respective training methods. Both groups exchanged training tools and completed a summary questionnaire. Results After training, 54.17% of participants believed that images presented by the Eyesi were consistent with the real fundus. Group A scored significantly higher than Group B in fundus structure recognition and self-confidence in examination. The degree of mastery over fundus theory score increased from 6.10 ± 0.13 to 7.74 ± 0.16 (P

The article describes the experience of applying the methodology of Model-Based Systems Engineering (MBSE) in the organization of ground tests of the on-board equipment complex of unmanned aerial vehicles at Kronshtadt JSC. This methodology was successfully used in the development of various complex control systems such as embedded control systems, digital signal processing, computer vision, radar and communications. The analysis of the on-board equipment testing process using an existing ground test bench was performed, and a method for automating its operation has been proposed. The calculation of economic efficiency was performed.

Introduction. Teaching the skill of renal cavity puncture remains a pressing issue for both resident trainees and practicing physicians. Because patient-based training is ethically questionable and can be unsafe in terms of complications, training models have been created to practice skills.Objective. To compare two non-biological simulators for renal cavity puncture under ultrasound guidance: “UROSON”, GEOTAR, Russia and the kidney phantom “SafeToAct”, Estonia.Materials & methods. The study involved 40 young doctors with no experience in kidney puncture. Group 1 (20 people) practised on the UROSON simulator (GEOTAR, Russia). Group 2 (20 people) trained on a kidney phantom (SafeToAct, Estonia). Both simulators were evaluated by doctors before and after practice, as well as in the long-term period for 3 and 6 months. The assessment was carried out using a Likert scale.Results. The UROSON was rated higher (p < 0.05) according to the results of the comparison of the parameters (colour and consistency, visualisation of the cavity and calyx on ultrasound). Renal cavity visualisation of the UROSON simulator was rated as "good" throughout the study. Visualisation deteriorated by 6.9% after six months of use. Meanwhile, the SafeToAct kidney phantom showed a 64% deterioration in visualisation after one month of use. The SafeToAct kidney phantom was not evaluated later point because it became unusable. Both simulators had "tracks" after punctures. The UROSON had 30% and the SafeToAct kidney phantom 100% (p < 0.0001).Conclusion. The UROSON simulator can be used for training, master classes and accreditation of specialists. This simulator can be used for a long time.

Background and Aims: Simulation-based medical education is effective for developing and improving critical care-related clinical skills training and reducing patient safety threats. The present study aimed to describe the technological approach of building and evaluating a prototype of a Lung Box (LB) mechanical ventilation simulator. Materials and Methods: In this practical study with an analytical approach, the device's body, constructed from 5 mm plexiglass sheets, occupies a respiratory circuit, an airflow obstruction system, a pressure gauge manometer, a spring-loaded manual system to apply limits on the bag inflation range, a tidal volume measurement system, a respiratory trigger simulator system, and a four-layer accordion-style plastic bag assembly that can be inflated and deflated with air. Additionally, there is a user manual storage box along with it. Results: The design and drawing of the device's map were performed with AutoCAD software, and the parts were assembled after laser cutting. The device was connected to the ICU ventilator, and the respiratory mode of continuous forced ventilation was selected. Prior to ventilation, the tidal volumes were selected to be 0.60, 0.55, 0.50, 0.45, and 0.40 ml, and respiratory rates were set as 18, 15, 12, and 9 bpm. The simulation of the respiratory trigger was performed with different values ​​of flow sensitivity (0.05-15 lit/min). There was no statistically significant difference (P>0.05) in terms of the reproducibility of the values ​​of the selected variables for the test Lung (TL) with those chosen for LB. Conclusion: In this technical study, a prototype educational mechanical ventilation simulator was developed and functionally tested using the concepts of fluid dynamics and respiratory physiology. Compared with conventional TL, this device is accurate and efficient enough.

Abstract Leptospirosis is a global disease that impacts people worldwide, particularly in humid and tropical regions, and is associated with significant socio-economic deficiencies. Its symptoms are often confused with other syndromes, which can compromise clinical diagnosis and the failure to carry out specific laboratory tests. In this respect, this paper presents a study of three algorithms (Decision Tree, Random Forest and Adaboost) for predicting the outcome (cure or death) of individuals with leptospirosis. Using the records contained in the government National System of Aggressions and Notification (SINAN, in portuguese) from 2007 to 2017, for the state of Pará, Brazil, where the temporal attributes of health care, symptoms (headache, vomiting, jaundice, calf pain) and clinical evolution (renal failure and respiratory changes) were used. In the performance evaluation of the selected models, it was observed that the Random Forest exhibited an accuracy of 90.81% for the training dataset, considering the attributes of experiment 8, and the Decision Tree presented an accuracy of 74.29 for the validation database. So, this result considers the best attributes pointed out by experiment 10: time first symptoms medical attention, time first symptoms ELISA sample collection, medical attention hospital admission time, headache, calf pain, vomiting, jaundice, renal insufficiency, and respiratory alterations. The contribution of this article is the confirmation that artificial intelligence, using the Decision Tree model algorithm, depicting the best choice as the final model to be used in future data for the prediction of human leptospirosis cases, helping in the diagnosis and course of the disease, aiming to avoid the evolution to death.

Each year maritime accidents occur at sea causing human casualties. Training facilities serve to reduce the risk of human error by allowing maritime teams to train safety procedures in cooperative real-size immersive simulators. However, they are expensive and only few maritime professionals have access to such simulators. Virtual Reality (VR) can provide a digital all-immersive learning environment at a reduced cost allowing for increased access. However, a key ingredient of what makes all-immersive physical simulators effective is that they allow for multiple participants to engage in cooperative social interaction. Social interaction which allows trainees to develop skills and competencies in navigating situational awareness essential for safety training. Social interaction requires social fidelity. Moving from physical simulators into digital simulators based upon VR technology thus challenges us as HCI researchers to figure out how to design social fidelity into immersive training simulators. We explore social fidelity theoretically and technically by combining core conceptual work from CSCW research to the design experimentation of social fidelity for maritime safety training. We argue that designing for social fidelity in VR simulators requires designers to contextualize the VR experience in location, artifacts, and actors structured through dependencies in work allowing trainees to perform situational awareness, coordination, and communication which are all features of social fidelity. Further, we identify the risk of breaking the social fidelity immersion related to the intent and social state of the participants entering the simulation. Finally, we suggest that future designs of social fidelity should consider not only trainees in the design, but also the social relations created by the instructors’ guidance as part of the social fidelity immersion. [ABSTRACT FROM AUTHOR]

Introduction: Non-ophthalmologists often lack sufficient operational training to use a direct ophthalmoscope proficiently, resulting in a global deficit of basic ophthalmological skills among general practitioners. This deficiency hampers the timely diagnosis, referral, and intervention of patients. Consequently, the optimization of teaching tools and methods to enhance teaching efficiency is imperative. This study explores the effectiveness of the Eyesi Direct Ophthalmoscope Simulator (Eyesi) as an innovative tool for fundus examination training. Methods: Medical undergraduates were randomly assigned to Group A or B (n = 168). All participants completed a pre-training questionnaire. Group A received Eyesi training, while Group B underwent traditional direct ophthalmoscope (TDO) training. Subsequently, participants answered questionnaires relevant to their respective training methods. Both groups exchanged training tools and completed a summary questionnaire. Results: After training, 54.17% of participants believed that images presented by the Eyesi were consistent with the real fundus. Group A scored significantly higher than Group B in fundus structure recognition and self-confidence in examination. The degree of mastery over fundus theory score increased from 6.10 ± 0.13 to 7.74 ± 0.16 (P < 0.001) in Group A, but Group B did not demonstrate a significant difference. We also compared undergraduates' tendencies for different learning purposes, 75.59% of participants preferred the Eyesi to TDO as a training tool, and 88.41% of participants were receptive to introducing the Eyesi in training. Conclusion: According to subjective participant feedback, Eyesi outperformed TDO in fundus observation, operational practice, and theoretical learning. It effectively equips undergraduates with fundus examination skills, potentially promoting the use of direct ophthalmoscopes in primary medical institutions. [ABSTRACT FROM AUTHOR]

Background: Drivers with dementia are at a higher risk of motor vehicle accidents. The characteristics of driving behaviour of patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD) have not been fully elucidated. We investigated driving ability and its relationship with cognitive function and magnetic resonance imaging (MRI) morphometry indicators. Methods: The driving abilities of 19 patients with AD and 11 with amnestic MCI (aMCI) were evaluated using a driving simulator. The association between each driving ability parameter and the Mini‐Mental State Examination (MMSE) score or voxel‐based specific regional analysis system for AD (VSRAD) was assessed. Results: Patients with AD made a significantly higher number of operational errors than those with aMCI in attention allocation in the complex task test (P = 0.0008). The number of operational errors in attention allocation in the complex task test significantly and negatively correlated with MMSE scores in all participants (r = −0.4354, P = 0.0162). The decision time in the selective reaction test significantly and positively correlated with the severity and extent of medial temporal structural atrophy (r = 0.4807, P = 0.0372; r = 0.4862, P = 0.0348; respectively). Conclusion: An increase in the operational errors for attention allocation in the complex task test could be a potential indicator of progression from aMCI to AD. Atrophy of the medial temporal structures could be a potential predictor of impaired judgement in driving performance in aMCI and AD. A driving simulator could be useful for evaluating the driving abilities of individuals with aMCI and AD. [ABSTRACT FROM AUTHOR]

Background: The main clinical manifestations of patients with Pierre Robin sequence (PRS) include micrognathia, the glossoptosis and dyspnoea. The difficulty of tracheal intubation (TI) in such patients is increased. Objective: The purpose of the study was to evaluate the reliability and efficacy of the PRS simulator. Methods: A PRS simulator was developed by using 3-dimensional (3D) printing technology under computer-aided design. A total of 12 anaesthesiologists each trained 5 times for TI on the PRS Training Simulator-1 and recorded the simulation time. After the training, they were randomly divided into three groups with a total of 12 nontrained anaesthesiologists, and the simulation was completed on PRS Simulator-2, 3 and 4. The simulation time was recorded, and the performance was evaluated by three chief anaesthesiologists. Then, all 24 anaesthesiologists completed the questionnaire. Results: A PRS simulator developed by 3D printing was used to simulate the important aspects of TI. The average number of years worked was 6.3 ± 3.1 years, and 66.7% were female. The time for the 12 anaesthesiologists to complete the training gradually decreased (p < 0.01). Compared with the trained anaesthesiologists, the simulation time of TI in the nontrained anaesthesiologists was much longer (all p < 0.01). In addition, the simulation performance of the trained anaesthesiologists was relatively better (all p < 0.01). Conclusion: The reliability and efficacy of the PRS simulator is herein preliminarily validated, and it has potential to become a teaching and training tool for anaesthesiologists. [ABSTRACT FROM AUTHOR]

The present investigation aims to develop the green methodology based on phytoextracts to enrich coal quality in thermal power stations. High ash content in domestic coals is one of the serious problems in thermal power generation in India. This results in high specific coal consumption, transportation losses, environmental issues, increase in operational problems in generating stations, etc. Coal beneficiation technologies are based on physical and chemical methods. The chemical methods of reducing ash content are costly, hazardous, and difficult to handle in large scale. In this context, "biomethods" based on treating the coal with "bio-extracts" of the plants to increase the quality of coal are interesting. The bio-extract of Citrus limon plant is identified to effectively decrease the content of metal oxides (ash) in 212-μ fine coal powder on digestion under "condensate distillation (100 °C)" for optimum period of 1.0 h in the pH range 4–6. The method is applied to the coals of various sources used in Dr Narla Tata Rao Thermal Power Station (Dr NTTPS), Vijayawada, India. The percentage of ash content in the coal is decreased to the designed levels of the boilers of Dr NTTPS, and thereby, optimum combinations of fixed carbon with volatile matter are achieved for ideal combustion. The coals before and after treatment are characterized by XRD and IR analysis in addition to proximate and ultimate analysis. A prototype simulator is designed with the optimum conditions established at the laboratory scale. To apply the finding for the entire power station, modifications are suggested in the crusher house of thermal power station. The developed method is effective in reducing the cost of power generation from Rs 2.38 to Rs 1.91 per unit of power. This results in savings of many crores of rupees per year. [ABSTRACT FROM AUTHOR]

Unlike other marketing strategies, sporting goods marketing strategies are affected by the fragility and randomness of marketing data, resulting in more restrictive factors. To improve the economic benefits of sporting goods enterprises, the design of sporting goods marketing strategy simulation system based on multi-agent technology was proposed. Based on the LMZ10503 circuit, ADP2164 circuit, and ADP1755 circuit, the rectifier is the power supply. The hardware design of the system is completed by combining the design of the marketing strategy acquisition card module and the sporting goods marketing strategy simulator module. In the software design of the system, according to the evaluation results of the logic degree of the sports marketing strategy simulation node, the logic degree of the marketing strategy simulation node is optimized. The multi-agent technology is used to implement the multi-agent modeling of the marketing strategy, and the simulation of the sports marketing strategy is realized by generating the marketing strategy simulation signal. The test results show that the sports equipment market marketing strategy simulation system based on multi-agent technology has successfully simulated the marketing strategy of sports equipment and achieved exciting results. Through the application of this system, sales volume and profit margin have increased to 900,000 units and 90% respectively. These results validate the potential of the system in optimizing marketing strategies and improving economic benefits, and provide strong reference and guidance for the sports equipment industry. Further promotion and application of this system is expected to help enterprises develop more accurate and scientific marketing strategies, achieve higher sales volume and profit margins, and thus promote the sustainable development and competitive advantage of the enterprise. [ABSTRACT FROM AUTHOR]

Copyright of China Petroleum Machinery is the property of China Petroleum Machinery Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Leptospirosis is a global disease that impacts people worldwide, particularly in humid and tropical regions, and is associated with significant socio-economic deficiencies. Its symptoms are often confused with other syndromes, which can compromise clinical diagnosis and the failure to carry out specific laboratory tests. In this respect, this paper presents a study of three algorithms (Decision Tree, Random Forest and Adaboost) for predicting the outcome (cure or death) of individuals with leptospirosis. Using the records contained in the government National System of Aggressions and Notification (SINAN, in portuguese) from 2007 to 2017, for the state of Pará, Brazil, where the temporal attributes of health care, symptoms (headache, vomiting, jaundice, calf pain) and clinical evolution (renal failure and respiratory changes) were used. In the performance evaluation of the selected models, it was observed that the Random Forest exhibited an accuracy of 90.81% for the training dataset, considering the attributes of experiment 8, and the Decision Tree presented an accuracy of 74.29 for the validation database. So, this result considers the best attributes pointed out by experiment 10: time first symptoms medical attention, time first symptoms ELISA sample collection, medical attention hospital admission time, headache, calf pain, vomiting, jaundice, renal insufficiency, and respiratory alterations. The contribution of this article is the confirmation that artificial intelligence, using the Decision Tree model algorithm, depicting the best choice as the final model to be used in future data for the prediction of human leptospirosis cases, helping in the diagnosis and course of the disease, aiming to avoid the evolution to death. [ABSTRACT FROM AUTHOR]

Striving to increase the speed of rail vehicles and thus improve the comfort of traveling passengers at the same time, undertakes activities in the sphere of ensuring an appropriate level of safety of rail, passenger, and freight transport. One of the elements of activities in this area is the training of train drivers. Until recently, this training consisted of a theoretical and practical part on the vehicle, alongside an experienced train driver. Considering the increasing level of automation of railway traffic control systems and locomotive equipment, as well as training costs and requirements related to the introduction of TSI, it is becoming an increasingly common requirement to conduct practical training on railway vehicle traffic simulators, while the conditions in the simulator cabin and the trainee's feelings should correspond to the actual driving conditions. A locomotive driving simulator is a system consisting of a cabin of a suitable type of locomotive or EMU, mapped in 1:1 scale, coupled with a motion excitation system and computer programs connected together forming the software of the cab visualization and dynamics system. The basic program simulating the dynamics and kinematics of the cabin's motion is a program containing a motion dynamics model that generates signals forcing the movement of the exciters on which the cabin's platform is mounted. The correct operation of the simulation model depends on the created mathematical model, which can be built in several ways. This article presents the issue of building a mathematical model describing the dynamics of the rail vehicle motion, which can then be used in the simulation model of the simulator cabin motion. Two ways of proceeding in the process of approaching the construction of a mathematical model of rail vehicle motion dynamics will be presented, with the possibility of later use in creating a simulation model of the motion of the locomotive simulator cabin. One of the possible routes was used in the past in the construction of the EP09 locomotive simulator. [ABSTRACT FROM AUTHOR]

Autonomous driving is an area that has been growing in recent years. However, cars are unprepared to cooperate with others nearby, wasting resources and computational power. Thus, cooperative autonomous driving reveals its importance in the future. In this work-in-progress paper, we define, implement and test an architecture for a simulation environment where cooperative autonomous driving protocols can be tested. Additionally, a Manoeuvre Negotiation Protocol is implemented. This protocol will make an existing autonomous driving (AD) stack more resilient in real driving scenarios, improving its robustness and safety. [ABSTRACT FROM AUTHOR]

Ice management is essential for maintaining the safety of offshore operations in Arctic regions. We present the combined results of three experiments conducted in a full-mission bridge simulator specially designed for ice management. From a quantitative analysis of the results, we infer the effect of three variables on performance: (1) experience, (2) training, and (3) Decision Support System (DSS). The results confirm that experience and training improve performance for untrained and inexperienced simulator participants. The DSS also improves performance, but with a smaller effect. Qualitative observations using vessel position heat-map diagrams and exit interviews suggested that novice participants using the DSS adopted expert strategies but carried out their tasks more slowly and with less precision. This has important consequences for the design of a future DSS used in training simulators or onboard ships. Potential improvements to the DSS design might include real-time feedback to the user, a redesign of the human-machine interface (HMI), and increasing user input and customization with a human factors focus. [ABSTRACT FROM AUTHOR]

Background: Hemorrhage is the leading cause of preventable death after trauma. In high‐income countries first responders are trained in hemorrhage control techniques but this is not the case for developing countries like Guatemala. We present a low‐cost training model for tourniquet application using a combination of virtual and physical components. Methods: The training program includes a mobile application with didactic materials, videos and a gamified virtual reality environment for learning. Additionally, a physical training model of a bleeding lower extremity is developed allowing learners to practice tourniquet application using inexpensive and accessible materials. Validation of the simulator occurred through content and construct validation. Content validation involved subjective assessments by novices and experts, construct validation compared pre‐training novices with experts. Training validation compared pre and post training novices for improvement. Results: Our findings indicate that users found the simulator useful, realistic, and satisfactory. We found significant differences in tourniquet application skills between pre‐training novices and experts. When comparing pre‐ and post‐training novices, we found a significantly lower bleeding control time between the groups. Conclusion: This study suggests that this training approach can enhance access to life‐saving skills for prehospital personnel. The inclusion of self‐assessment components enables self‐regulated learning and reduces the need for continuous instructor presence. Future improvements involve refining the tourniquet model, validating it with first‐responder end users, and expanding the training program to include other skills. [ABSTRACT FROM AUTHOR]

Background & Aims: Endoscopy simulators are primarily designed to provide training in interventions performed during procedures. Peri-interventional tasks such as checking patient data, filling out forms for team time-out, patient monitoring, and performing sedation are often not covered. This study assesses the face, content, and construct validity of the ViGaTu (Virtual Gastro Tutor) immersive virtual reality (VR) simulator in teaching these skills. Methods: 71 nurses and physicians were invited to take part in VR training. The participants experienced an immersive VR simulation of an endoscopy procedure, including setting up the endoscopic devices, checking sign-in and team time-out forms, placing monitoring devices, and performing sedation. The actions performed by the participants and their timing were continuously recorded. Face and content validity, as well as the System Usability Scale (SUS), were then assessed. Results: 43 physicians and 28 nurses from 43 centers took a mean of 27.8 min (standard deviation ± 14.42 min) to complete the simulation. Seventy-five percent of the items for assessing face validity were rated as realistic, and 60% of items assessing content validity and usefulness of the simulation for different learning goals were rated as useful by the participants (four out of five on a Likert scale). The SUS score was 70, demonstrating a high degree of usability. With regard to construct validity, experienced endoscopy staff were significantly faster in setting up the endoscope tower and instruments than beginners. Conclusions: This multicenter study presents a new type of interdisciplinary endoscopy training system featuring peri-interventional tasks and sedation in an immersive VR environment. [ABSTRACT FROM AUTHOR]

In this article, the development of a software system—a simulator for testing software systems using a binary protocol—is proposed. The purpose of the development is to achieve full testing of a wide class of software systems. They are directly related to the management of hardware systems, with which communication is based on a binary protocol. The developed simulator allows different types of messages to be simulated during real communication. In this way, it is possible to check how a given program system would react to correct and incorrect messages in the communication stage. This article presents a GUI system developed in the standard C++ programming language and the Qt platform, which makes it platform-independent. The system provides the ability to select preset commands via an external file or enter/correct commands in real-time. The commands may be different depending on the integration scope of the binary protocol. The connection between the developed simulator and the tested system is through RS 232 interface. Configuring settings and testing binary protocols through the developed application becomes fast and intuitive. [ABSTRACT FROM AUTHOR]

Identifying users’ experience when using products is one of the major challenges for design. Analyzing users’ psychophysiological reactions to an experience using biofeedback can produce more reliable results than using subjective evaluations, such as structured interviews and questionnaires. Two case studies were conducted to identify emotions users actually felt and to check whether there is some correspondence with what they reported after using two computational systems. The first system investigated users’ emotions during training on a vehicle driving simulator, and the second analyzed the emotions experienced during a car racing game, both in a virtual reality environment. User’s opinions about their emotional state were obtained using self-report techniques (using the Geneva Emotions Wheel—GEW and Positive and Negative Affective Schedule—PANAS questionnaires) and applying EEG (brain activity with Frontal Alpha Asymmetry Index—FAAI) and infrared thermography (facial thermograms). The training experiment presented the greater concordance between the psychophysiological and the self-report responses. Results evidenced the importance of undertaking multimodal studies in design research to determine users’ emotional experiences in a virtual reality context. [ABSTRACT FROM AUTHOR]

Most accidents and serious incidents of commercial air transport helicopters occur during standard flight phases, whereby a main cause is pilots' situational awareness. Enabling pilots to better assess their situational awareness can make an important contribution in reducing the risk of fatal accidents. One approach is to examine a pilot's gaze behavior with the help of eye tracking. This paper reports the results of a case study with eye tracking measurements during real flight and simulator studies of a standard mission profile. The general gaze behavior is characterized by a dominant, external view, and the airspeed and altitude indicator as the most important flight instruments. A real-world applicability of gaze data obtained in the simulator could be shown. [ABSTRACT FROM AUTHOR]

A slotted patch antenna operating at 118 GHz is proposed to address challenges in the terahertz (THz) frequency band for wireless communication systems. The antenna design, utilizing a Rogers RO3003 substrate, which has a dielectric constant of er = 3 and tan δ = 0.001, strategically incorporates slots to enhance key performance parameters. Copper is employed for the ground and radiating patch, and a microstrip feeding method powers the antenna. High frequency structure simulator (HFSS) software is used for design and simulation, revealing resonance at 0.118 THz with a reflection coefficient of -42.41 dB and an impedance bandwidth of 4.42 GHz (115.84-120.26 GHz). At the operating frequency, the antenna exhibits a gain of 7.36 dB, maximum directivity of 7.38 dB, the voltage standing wave ratio (VSWR) of 1.01, and 99.75% radiation efficiency, all within a compact size of 1.5×1.3×0.1 mm³. The suggested antenna outperforms recent counterparts, making it suitable for applications like security screening and wireless communication systems (5G). Future efforts will target bandwidth expansion, gain enhancement, and further size reduction to enhance overall performance. [ABSTRACT FROM AUTHOR]

Background: The acquisition of skills in penile prosthesis surgery has many limitations mainly due to the absence of simulators and models for training. Three-dimensional (3D) printed models can be utilized for surgical simulations, as they provide an opportunity to practice before entering the operating room and provide better understanding of the surgical approach. Aim: This study aimed to evaluate and validate a 3D model of human male genitalia for penile prosthesis surgery. Methods: This study included 3 evaluation and validation stages. The first stage involved verification of the 3D prototype model for anatomic landmarks compared with a cadaveric pelvis. The second stage involved validation of the improved model for anatomic accuracy and teaching purposes with the Rochester evaluation score. The third stage comprised validation of the suitability of the 3D prototype model as a surgical simulator and for skill acquisition. The third stage was performed at 3 centers using a modified version of a pre-existing, validated questionnaire and correlated with the Rochester evaluation score. Outcome: We sought to determine the suitability of 3D model for training in penile prosthesis surgery in comparison with the available cadaveric model. Results: The evaluation revealed a high Pearson correlation coefficient (0.86) between questions of the Rochester evaluation score and modified validated questionnaire. The 3D model scored 4.33 ± 0.57 (on a Likert scale from 1 to 5) regarding replication of the relevant human anatomy for the penile prosthesis surgery procedure. The 3D model scored 4.33 ± 0.57 (on a Likert scale from 1 to 5) regarding its ability to improve technical skills, teach and practice the procedure, and assess a surgeon's ability. Furthermore, the experts stated that compared with the cadaver, the 3D model presented greater ethical suitability, reduced costs, and easier accessibility. Clinical implications: A validated 3D model is a suitable alternative for penile prosthesis surgery training. Strengths and limitations: This is the first validated 3D hydrogel model for penile prosthesis surgery teaching and training that experts consider suitable for skill acquisition. Because specific validated guidelines and questionnaires for the validation and verifications of 3D simulators for penile surgery are not available, a modified questionnaire was used. Conclusion: The current 3D model for penile prosthesis surgery shows promising results regarding anatomic properties and suitability to train surgeons to perform penile implant surgery. The possibility of having an ethical, easy-to-use model with lower costs and limited consequences for the environment is encouraging for further development of the models. [ABSTRACT FROM AUTHOR]

Zolpidem is a widely prescribed hypnotic Z-drug used to treat short-term insomnia. However, a growing number of individuals intentionally overdose on these drugs. This study aimed to develop a predictive tool for physicians to assess patients with zolpidem overdose. A population pharmacokinetic (PK) model was established using digitized data obtained from twenty-three healthy volunteers after a single oral administration of zolpidem. Based on the final PK model, a web application was developed using open-source R packages such as rxode2, nonmem2rx, and shiny. The final model was a one-compartment model with first-order absorption and elimination with PK parameters, including clearance (CL, 16.9 L/h), absorption rate constant (Ka, 5.41 h−1), volume of distribution (Vd, 61.7 L), and lag time (ALAG, 0.394 h). Using the established population PK model in the current study, we developed a web application that enables users to simulate plasma zolpidem concentrations and visualize their profiles. This user-friendly web application may provide essential clinical information to physicians, ultimately helping in the management of patients with zolpidem intoxication. [ABSTRACT FROM AUTHOR]

Background and Aims: Simulation-based medical education is effective for developing and improving critical care-related clinical skills training and reducing patient safety threats. The present study aimed to describe the technological approach of building and evaluating a prototype of a Lung Box (LB) mechanical ventilation simulator. Materials and Methods: In this practical study with an analytical approach, the device's body, constructed from 5 mm plexiglass sheets, occupies a respiratory circuit, an airflow obstruction system, a pressure gauge manometer, a spring-loaded manual system to apply limits on the bag inflation range, a tidal volume measurement system, a respiratory trigger simulator system, and a four-layer accordion-style plastic bag assembly that can be inflated and deflated with air. Additionally, there is a user manual storage box along with it. Results: The design and drawing of the device's map were performed with AutoCAD software, and the parts were assembled after laser cutting. The device was connected to the ICU ventilator, and the respiratory mode of continuous forced ventilation was selected. Prior to ventilation, the tidal volumes were selected to be 0.60, 0.55, 0.50, 0.45, and 0.40 ml, and respiratory rates were set as 18, 15, 12, and 9 bpm. The simulation of the respiratory trigger was performed with different values ​​of flow sensitivity (0.05-15 lit/min). There was no statistically significant difference (P>0.05) in terms of the reproducibility of the values ​​of the selected variables for the test Lung (TL) with those chosen for LB. Conclusion: In this technical study, a prototype educational mechanical ventilation simulator was developed and functionally tested using the concepts of fluid dynamics and respiratory physiology. Compared with conventional TL, this device is accurate and efficient enough. [ABSTRACT FROM AUTHOR]

Copyright of Automatisierungstechnik is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

IntroductionShooting simulations provide an excellent opportunity to train use-of-force decisions in controlled environments. Recently, military and law enforcement organizations have expressed a growing desire to integrate physiological measurement into simulations for training and feedback purposes. Although participants can easily wear physiological monitors in these scenarios, direct implementation into training may not be simple. Theoretical problems exist in the ultra-short heart rate variability windows associated with use-of-force training, and practical problems emerge as existing scenario libraries at training organizations were not designed for physiological monitoring.MethodsThe current study explored the challenges and possibilities associated with direct implementation of physiological monitoring into an existing library of firearms training scenarios. Participants completed scenarios in a shooting simulator using existing military training scenarios while wearing a device to monitor their heart rate.ResultsThe results revealed lower heart rate variability (approximately 6%) occurred in scenarios where participants did not have to fire weapons, indicating that don't-shoot scenarios may actually impose more cognitive stress on shooters. Additional evidence further demonstrated how both behavioral and physiological factors could be used concomitantly to predict unintentionally firing on non-hostile actors. However, behavioral measures were more predictive (e.g., β = .221) than physiological measures (e.g., β = −.132) when the latter metrics were limited to specific scenarios. Qualitative results suggest that simply applying physiological monitoring to existing shooting simulations may not yield optimal results because it would be difficult to directly integrate physiological measurement in a meaningful way without re-designing some elements of the simulations, the training procedure, or both.DiscussionFuture use-of-force shooting simulations should consider designing novel scenarios around the physiological measurement rather than directly implementing physiological assessments into existing libraries of scenarios.

In the rapidly evolving field of medical education, the integration of innovative technologies has become paramount to enhance the training and proficiency of future surgeons. Among these advancements, the application of 3D printing technology stands out as a useful tool in surgical training. The advantages of the 3D printing model include customization, re-usability and low-cost. The average cost of the 3D printing simulators was between $100–1000. However, there were extremely high potential labor cost during the 3D printing that hadn’t been calculated into. Additionally, in the current stage, the 3D printing simulator still have specific limitations. The most mentioned limitation was poor haptic feedback of the simulators, which was very important during the surgical training, since it is the key element for junior doctors to master practical procedures. Also, some simulators didn’t possess the integrated and elaborate structure as the human tissue, hence not the whole surgical procedures can be practiced by the trainees, and further improvement should be made. Although there are shortages, many studies have proved that 3D printing simulator can effectively reduce learning curves and is useful to enhance the trainees’ surgical skills.