Real Model Research Articles

INFORMATION AND REALITY (PROBLEMS OF SEMANTICS AND PRAGMATICS)

The relevance of the topic of the article is due to the need for philosophical research into the nature of information as a factor that significantly affects the development of modern society. Understanding the nature of information is important for the study of processes, mechanisms, and technologies in any sphere of social life.The study is based on a semiotic approach, the relationship between information and reality is considered based on the semantic and pragmatic aspects of this problem. The concept of semantic information by Luciano Floridi and the views on the nature of information by Yuval Noah Harari are analyzed. The semantic aspect is understood not only in terms of the “truthfulness” of data, but also in terms of the perception and interpretation of this data by the consumer of information. Information appears as a model of reality, and at the same time information models reality, creating a second, illusory reality. A person exists in a situation of “two realities” (ontological and semiotic). This situation of “two realities” creates numerous philosophical and semiotic problems.Information not only reflects and constructs reality but is also used as a means of influencing consciousness, as a means of control. The modern information society is built on technologies of manipulation of consciousness. This is associated with the peculiarities of the functioning of information in society. In modern culture, information increasingly replaces reality, simulates reality. These are fakes and disinformation, rumors and conspiracy theories, as well as literature and art that exist as an imitation of reality. The media record events less and less often, and more and more often direct them. This is what describes the state of post-truth, when information flows themselves determine what is true and what is not. Information loses touch with reality, information and reality do not intersect or intersect rarely. People are increasingly immersed in this artificial reality, being in the information, virtual world.

Interrelation of Religion and Culture: An Analysis of Honoring Asyhur Al-Hurum Culture on Cliford Greetz's Anthropological Theory

Religion and culture are two interconnected entities. However, there are some groups who claimed that Islam is against local culture and traditions. That arguments are significant to be reviewed and studied comprehensively. This research aims to review the interrelation between Islamic teachings and the culture of honoring asyhur al-hurum from the perspective of Clifford Geertz's anthropological theory. With a library research approach and qualitative method, this research results that the teachings in Islam appreciate and are accommodative of local traditions. Many pre-Islamic traditions have been adopted and then integrated into Islam, one of them is the culture of honoring asyhur al-hurum (Rajab, Dhulqa'dah, Dhulhijjah, and Muharram). There are several verses of the Qur'an that contain an appreciative attitude towards this culture, including QS al-Baqarah verses 194, 197, and 217; QS al-Maidah verses 2 and 97; QS al-Taubah verse 36. Some of the verses mentioned provide an understanding that Islam is a religion that strengthens respect for the culture of the glory of the haram months (asyhur al-hurum). The verse reflects the tahmil process as a form of dialectic between the Qur'an and culture. Based on the analysis using Clifford Geertz's theory of models for reality and models of reality, the teachings in Islam instruct Muslims to glorify the haram months by increasing worship, both ritual worship and social worship related to cultural practices that apply in a multicultural society. The interrelation between religious teachings about the haram months and local culture contributes to the formation of collective identity, both in religious and social contexts.

Solid-State NMR Validation of OPLS4: Structure of PC-Lipid Bilayers and Its Modulation by Dehydration.

Atomistic molecular dynamics (MD) simulations are a much-used tool for investigating the structure and dynamics of biomembranes with atomic resolution. The validity of the representations obtained is determined by the accuracy and realism of the MD model (force field). Here, we evaluated the proprietary OPLS4 force field of Schrödinger, Inc. against atomic-resolution experimental data, and compared its performance to CHARMM36, one of the best-performing openly available force fields. As a benchmark, we used high-resolution nuclear magnetic resonance (NMR) order parameters for C-H bonds─directly and reliably calculable from MD simulations─measured in phosphatidylcholine (PC) lipid bilayers under varying hydration conditions. Comparisons were made with two dehydration data sets: for saturated (1,2-dimyristoylphosphatidylcholine, DMPC) lipid bilayers from the literature and for unsaturated (1-palmitoyl-2-oleoylphosphatidylcholine, POPC) lipid bilayers measured here. Our findings indicate that OPLS4 reproduces the structure and dehydration response of PC-lipid bilayers fairly well, even slightly outperforming CHARMM36. Both models' main inaccuracies appear in (1) the order parameter magnitudes in the glycerol backbone and unsaturated carbon segments and (2) the qualitatively differing structural response of the PC headgroup to dehydration compared to experiments. In summary, this work underscores the importance of independent validation for (proprietary) force fields and highlights the striking similarities and nuanced differences between OPLS4 and CHARMM36 in describing biomembranes.

A Multiscale Mathematical Model for Fetal Gas Transport and Regulatory Systems During Second Half of Pregnancy.

Fetal asphyxia, a condition resulting from the combined effects of hypoxia and hypercapnia, leads to approximately 900,000 annual deaths worldwide. One cause is umbilical cord compression during labor-induced uterine contractions, disrupting the transport of metabolites to and from the placenta, and resulting in asphyxia. Current fetal well-being assessment relies on monitoring fetal heart rate and uterine contractions as indicators of oxygen delivery to the brain. To enhance our understanding of this complex relationship, this study aims to develop a modular mathematical model including fetal blood gas dynamics, the autonomic nervous system, and cerebral blood flow regulation. The novelty of this study lies in the capability of the model to simulate fetal growth. These submodels are part of a larger multiscale mathematical model describing fetal circulation in the second half of pregnancy. The blood gas model realistically replicates partial oxygen and carbon dioxide pressures in umbilical arteries and veins during healthy fetal development reported in the literature. An in silico experiment is conducted to simulate umbilical cord occlusion and is compared with lamb experiments to verify the realism of the regulation models during fetal growth. Our findings suggest that premature infants are more susceptible to umbilical cord occlusion, exhibiting elevated cerebral perfusion pressure and flow. This modular mathematical model may serve as a valuable tool for testing hypotheses related to the fetal regulatory system.

Homeodynamic feedback inhibition control in whole-brain simulations.

Simulations of large-scale brain dynamics are often impacted by overexcitation resulting from heavy-tailed structural network distributions, leading to biologically implausible simulation results. We implement a homeodynamic plasticity mechanism, known from other modeling work, in the widely used Jansen-Rit neural mass model for The Virtual Brain (TVB) simulation framework. We aim at heterogeneously adjusting the inhibitory coupling weights to reach desired dynamic regimes in each brain region. We show that, by using this dynamic approach, we can control the target activity level to obtain biologically plausible brain simulations, including post-synaptic potentials and blood-oxygen-level-dependent functional magnetic resonance imaging (fMRI) activity. We demonstrate that the derived dynamic Feedback Inhibitory Control (dFIC) can be used to enable increased variability of model dynamics. We derive the conditions under which the simulated brain activity converges to a predefined target level analytically and via simulations. We highlight the benefits of dFIC in the context of fitting the TVB model to static and dynamic measures of fMRI empirical data, accounting for global synchronization across the whole brain. The proposed novel method helps computational neuroscientists, especially TVB users, to easily "tune" brain models to desired dynamical regimes depending on the specific requirements of each study. The presented method is a steppingstone towards increased biological realism in brain network models and a valuable tool to better understand their underlying behavior.

HYBRID APPROACH TO LEARNING BASED ON EMOTIONAL EXPERIENCE AND THE DEVELOPMENT OF INNOVATIVE METATHINKING IN POST-WAR UKRAINE

Purpose of the study is to synthesize generalized metaheuristic and metacognitive models, the use of which in project culture contributes to the formation of innovative creative-critical metathinking of an individual. Methodology. The methodology for studying creative activity and training of a designer is based on the post-neoclassical paradigm of scientific knowledge, subject-object integrity of the system of relations and dialectically developing relationships in a hybrid innovative learning environment. The methodology also includes new methods of interdisciplinary research and modeling of reality, integrating physical and social ontology. It is shown that the development of a structural-functional approach to the perception of physical and digital reality takes into account the peculiarities of an individual's brain activity. Results. The main results obtained are a triad of generalized author's metamodels, namely: 1. A heuristic metamodel of post-neoclassical perception of physical reality by a designer, in which the independence of cognition cycles, as well as the complementarity of paradigms (synergetic, triadic and semiotic) combines physical and social ontology, which creates new opportunities for the formation of a designer's creative metathinking in the process of experience. activity. 2. A heuristic metamodel of post-neoclassical perception and reflection of physical and virtual reality by a conceptual designer, in which the dependence of cycles of cognition, as well as the complementarity of heuristic metamodels, is achieved through universal triangles (fractal, Pascal, Sierpinski), the structures of which contribute to innovative activity of the conceptual designer. 3. Cognitive meta-model for the formation of meta-thinking of a designer-conceptualist, which is based on the spatio-temporal balance of explicit and hidden relationships, the cognitive visualization of which contributes to the search for harmony in the process of experience-oriented learning and creative activity through semiotic tools. Scientific novelty is determined by the complementarity of the structures of the author's metamodels of physical and digital reality, the synergy of which contributes to the optimization of experience-oriented models of teaching and self-learning. The interrelation of the structures of metamodels and their complementarity is the basis of successful activities in a hybrid learning environment (real physical and virtual mathematical), which facilitates the transfer of emotional and intellectual content between objects and subjects of the digital world. Practical significance of complementarity and interconnection of new metamodels of metathinking allows us to develop: universal criteria for determining the quality of design objects using GenAI; a method for identifying triads of interconnected opposites in information sources of various natures, the visualization of which simplifies interdisciplinary interaction between designers; create a personal e-assistant, e-consultant, e-expert using GenAI. In post-war Ukraine, interdisciplinary exchange of ideas, methods and successful experiences is extremely relevant within the framework of a hybrid approach to understanding the harmony of physical and digital reality, which promotes successful creative activity based on the perception of the harmony of nature to achieve the unattainable. Further development of experiential learning through the formation of metathinking is necessary to improve mental health and adapt to inevitable social transformations.

The Rochester Model for Spinal CSF Leak Repair Simulation and Scoring.

Iatrogenic spinal durotomies occur at a rate of 1% to 17%. Surgical simulation for durotomy repair is needed to provide affordable, accessible, and validated practice. This study sought to design and validate a simple 3-dimensional printed model for spinal cerebrospinal fluid (CSF) leak repair and to introduce the Rochester original objective structured assessment of technical skills (OSATS) CSF leak (ROCL) repair criteria for assessment. A spinal model was designed to mimic a lumbar laminectomy with the L3-5 lamina removed and 3-dimensional printed using Vero polymers. The model was paired with a porcine collagen "dura" that was pressurized using IV saline and overlayed with gel-molded fascial, muscle, and skin layers with an opening. Participants were provided a training model with a 1.5-cm midline durotomy, surgical microinstrument set, microscope, and 6-0 prolene suture. The 25-point ROCL repair criteria were adapted from the original OSATS principles to assess proficiency in surgical repair by 2 blinded neurosurgeons not participating in the trials. Postsimulation survey data regarding model realism were collected. Six residents and 4 attendings participated. Median operative time in minutes was 13 minutes among residents and 7 minutes among attendings. Moreover, the ROCL score was a median of 19/25 for attendings and 15/25 for residents. The suture angle was statistically more consistent among senior residents and attendings compared with junior residents. Participants agreed that the model was realistic (median 4/5), useful for improving the operative technique (median 5/5), and would increase comfort in spinal CSF leak repair procedures (median 5/5). Each reusable model had a cost of $19.99 if printed with polylactic acid and each replacement dura cost <3¢. This study presents an affordable, realistic, and educational spinal CSF leak repair model and introduces ROCL for assessment.

Investigating a Toolchain from Trajectory Recording to Resimulation

The growing variety of transportation options and increasing traffic congestion pose new challenges for road safety. As a result, there is an intensified focus on developing automated driving features and assistance systems aimed at minimizing accidents caused by human errors. The creation of these systems requires a substantial amount of testing kilometers, with estimates suggesting that around 2.1 billion kilometers would be necessary to ensure that each situation pertinent to the driving function is encountered at least once with a probability of 50%. This paper advances the microscopic simulation of traffic scenarios beyond linear patterns, utilizing the open-source environment openPASS. It addresses the research question of whether existing microscopic simulations are able to realistically represent non-linear traffic scenarios. A comprehensive toolchain integrates simulation with video recordings and laser scans. The study compares recorded traffic flow data with simulations at a T-junction, assessing the realism of vehicle models and trajectory representation. Three scenarios are analyzed, considering vehicles and pedestrians. The 3D geometry of the scene was captured with a laser scanner, enabling the mapping of recorded video data onto a geo-referenced environment. Object trajectories were extracted using an ’Regions with Convolutional Neural Networks features’ object detector. While openPASS simulated vehicle and pedestrian behaviors effectively, limitations in trajectory variability and reaction times were observed. These findings highlight the need for more realistic behavior models. This research emphasizes the necessity for improvements to accommodate complex driving behaviors and pedestrian dynamics.

Mathematical Modeling of the Co‐Infection Dynamics of Dengue and Malaria Using Delay Differential Equations

AbstractThis study presents a comprehensive mathematical model to analyze the dynamics of co‐infection between dengue and malaria using delay differential equations. The model investigates the transmission dynamics of both diseases, focusing on the stability of equilibrium points and the basic reproductive ratio, which measures the number of secondary infections caused by a single infected individual. A time‐delay component is incorporated to account for the incubation periods, enhancing the model's realism. The study performs a detailed sensitivity analysis and global stability assessments, providing insights into the control and management of diseases. Numerical simulations are conducted to illustrate the effect of various transmission parameters on disease spread. This research highlights the importance of mathematical modeling in understanding co‐infection dynamics and provides critical insights for public health interventions, particularly in regions where both diseases are endemic. The results emphasize the role of controlling transmission rates and the use of vector management strategies in mitigating disease outbreaks.

Neurocircle microsurgery model: Description of simulation-based training and exoscope.

Microsurgery is crucial in neurosurgery, requiring precise skills for interventions on delicate structures. Effective training is essential for developing these skills. In Peru and Latin America, however, there is a notable shortage of specialized training centers and high costs associated with foreign simulators, hindering the development of neurosurgical skills. To address this issue, the NeuroZone3D Research Center has initiated a project to create a national dataset on Peruvian craniometry and develop locally adapted training models. The "NeuroCircle Microsurgery Model" was created through a multi-phase process. Phase 1 involved designing a simulation platform using a 3D printer. Phase 2 focused on creating a realistic biomodel with polyurethane and advanced modeling techniques. In Phase 3, the biomodel was assembled and integrated into the platform. Phase 4 included using a wooden module, a cost-effective exoscope simulation, and surgical instruments to provide a realistic training environment. The "NeuroCircle Microsurgery Model" provided a stable and effective training environment. Feedback from training sessions with neurosurgery residents and medical students indicated significant improvements in microsurgical skills. Participants valued the model's realism and its role in enhancing their surgical proficiency. The "NeuroCircle Microsurgery Model" is a significant advancement in microsurgery training for Peru and Latin America. Its development provides a valuable, locally adaptable tool for improving surgical skills and addresses the critical training gaps in the region.

Fast and customizable image formation model for optical coherence tomography.

Optical coherence tomography (OCT) is a technique that performs high-resolution, three-dimensional, imaging of semi-transparent scattering biological tissues. Models of OCT image formation are needed for applications such as aiding image interpretation and validating OCT signal processing techniques. Existing image formation models generally trade off between model realism and computation time. In particular, the most realistic models tend to be highly computationally demanding, which becomes a limiting factor when simulating C-scan generation. Here we present an OCT image formation model based on the first-order Born approximation that is significantly faster than existing models, whilst maintaining a high degree of realism. This model is made more powerful because it is amenable to simulation of phase sensitive OCT, thus making it applicable to scenarios where sample displacement is of interest, such as optical coherence elastography (OCE) or Doppler OCT. The low computational cost of the model also makes it suitable for creating large OCT data sets needed for training deep learning OCT signal processing models. We present details of our novel image formation model and demonstrate its accuracy and computational efficiency.

Development and Validation of a Low-Cost, High-Fidelity Simulation Model for Robotic Internal Mammary Artery Harvest Using the da Vinci Xi Robot.

We created and validated a low-cost simulation model for robotic internal mammary artery (IMA) takedown. The simulation model utilized a calf fetus thorax cavity stented open internally and secured to a table. The simulation model was validated at a 2-day robotic cardiac surgery workshop. Each participant harvested one IMA using the da Vinci Xi robot (Intuitive Surgical, Sunnyvale, CA, USA). We compared participant self-reported confidence at robotic IMA harvest before and after using the simulator. Our novel thorax-securing strategy resulted in a stable structure and allowed access to both IMAs from the same 3 ports. The cost to set up the first simulation model was $176 and $133 for every subsequent model. Fifty participants used the simulation model: 42 cardiothoracic surgery attendings and 8 fellows or residents. The feedback form response rate was 78% (n = 39). On the Likert scale, participants rated realism of the calf model to simulate robotic IMA harvesting (0 = not realistic, 10 = highly realistic) with a median of 8 out of 10 (interquartile range [IQR] 7 to 9). Participant confidence (0 = not at all confident, 10 = very confident) in robotic IMA harvesting before and after using the simulator increased (P = 0.001) from a median of 5 (IQR 1 to 7) to 9 (IQR 7 to 10). This robotic IMA harvest simulation model is affordable, realistic, and improved participant confidence in robotic IMA harvest. It may provide a valuable training tool for surgeons learning robotic coronary bypass surgery and allows for training frequency necessary to pass basic learning curves.

3D Digital Modeling Technology for Thermal Power Plant Boilers Based on Digital Twins

With the rapid advancement of Digital Twins (DTs) technologies, they have emerged as viable solutions for enhancing the control and optimization of thermal power combustion processes. This paper presents a pioneering approach that leverages DTs to revolutionize the combustion process control system within thermal power generating units. Focused on bridging the physical and digital realms, our research establishes DTs of the combustion process control system (CPCS), situated within the Networked Control System Laboratory (NCSLab). We propose a novel five-dimensional (5D) DTs model encompassing the physical, data, service, connection, and virtual models, thereby facilitating a comprehensive fusion of physical and digital information. By analyzing the demands and technical intricacies of the combustion process control system, we design and implement a virtual 3D model, enriching the visualization and analytical capabilities of the DT environment. Furthermore, through controlled experiments on the combustion process and rigorous comparison with offline simulations, we validate the efficacy and feasibility of our approach. Importantly, our research opens avenues for future exploration, particularly in harnessing industrial real-time data to drive the virtual 3D model. Through the integration of Artificial Intelligence (AI) techniques such as Deep Learning, we elevate the capabilities of our DT framework. This enhanced predictive analytics, dynamic optimization, human–machine interaction, and virtual model realism. This research contributes to the advancement of DT technology in the context of thermal power plants and holds promise for driving innovation and efficiency across diverse industrial sectors.

Rearticulating Realism: Chains of Reference and Epistemic Success in the Sciences

In recent decades, the long-standing debate about the scientific status of the social sciences and their explanatory nature has been rearticulated through perspectivist, interpretivist, and mechanistic approaches. Whereas mechanistic approaches advocate for realism in sociological models, perspectivist and interpretivist perspectives challenge this by emphasizing the multiple interpretations and meaningful nature of social reality, as opposed to the natural sciences. Currently, the metatheoretical discussion centers on competing views regarding the relationship between theories and the objects they address. In contrast to this focus on theories, I propose a rearticulation of Hacking’s interventionist argument. I argue that all sciences share a common epistemic activity—the construction of chains of reference—which points to shared notions of success. This paves the way for realism through a practice-based argument that does not originate from ontological disputes, suggesting that our best theories are those literally embedded in scientific practice.

Toward widespread use of virtual trials in medical imaging innovation and regulatory science.

The rapid advancement in the field of medical imaging presents a challenge in keeping up to date with the necessary objective evaluations and optimizations for safe and effective use in clinical settings. These evaluations are traditionally done using clinical imaging trials, which while effective, pose several limitations including high costs, ethical considerations for repetitive experiments, time constraints, and lack of ground truth. To tackle these issues, virtual trials (aka in silico trials) have emerged as a promising alternative, using computational models of human subjects and imaging devices, and observer models/analysis to carry out experiments. To facilitate the widespread use of virtual trials within the medical imaging research community, a major need is to establish a common consensus framework that all can use. Based on the ongoing efforts of an AAPM Task Group (TG387), this article provides a comprehensive overview of the requirements for establishing virtual imaging trial frameworks, paving the way toward their widespread use within the medical imaging research community. These requirements include credibility, reproducibility, and accessibility. Credibility assessment involves verification, validation, uncertainty quantification, and sensitivity analysis, ensuring the accuracy and realism of computational models. A proper credibility assessment requires a clear context of use and the questions that the study is intended to objectively answer. For reproducibility and accessibility, this article highlights the need for detailed documentation, user-friendly software packages, and standard input/output formats. Challenges in data and software sharing, including proprietary data and inconsistent file formats, are discussed. Recommended solutions to enhance accessibility include containerized environments and data-sharing hubs, along with following standards such as CDISC (Clinical Data Interchange Standards Consortium). By addressing challenges associated with credibility, reproducibility, and accessibility, virtual imaging trials can be positioned as a powerful and inclusive resource, advancing medical imaging innovation and regulatory science.

Adaptive PF-CZM for multiphysics fracture analysis in functionally graded materials

Functionally graded materials (FGM) hold significant relevance in engineering due to their tailored material property gradation, designed for specific engineering applications. The challenge in fracture analysis of FGM stems from the spatial variation of material properties, which complicates the prediction of crack topology. Local and global refinement strategies are impractical for fracture analysis in FGM due to the unpredictable nature of crack topology, which renders local refinement infeasible. Additionally, global refinement is not advisable as it leads to a significant increase in degrees of freedom, adversely affecting computational efficiency.The novelty of this research lies in the incorporation of spatial variation in both the length scale and material properties, enhancing the realism of FGM domain modeling. To preserve the required length scale, it is necessary to adopt a minimum mesh size, which consequently results in a substantial increase in the degrees of freedom and, thereby, escalates the computational cost. To address these challenges, the study employs an adaptive mesh refinement (AMR) algorithm integrated with a phase-field cohesive zone model (PF-CZM), providing a robust solution for accurate fracture analysis in FGM. Based on the ideas stemming from the need for efficient and realistic modeling, the AMR-PF-CZM framework refines the mesh efficiently in regions of crack growth based on crack-driving energy and phase field variable, thereby eliminating the need for pre-refinement. The findings demonstrate a 76%–85% increase in computational efficiency and accuracy of the AMR-PF-CZM approach compared to the non-adaptive PF-CZM. Furthermore, the developed algorithm’s applicability to dynamic fracture and multi-physics problems, specifically addressing mechanical and thermal fracture in FGM, underscores the importance of this approach in capturing complex fracture phenomena.

Improving Resident Comfort With Peripartum Cesarean Hysterectomy Through the Use of Low-Fidelity Simulation Models.

Introduction Cesarean hysterectomy is a relatively rarely performed, complex, life-saving procedure considered during post-partum hemorrhage and other obstetric complications. This multi-site study aimed at validating a low-cost, low-fidelity cesarean hysterectomy model to support resident proficiency and increase their confidence in performing this critical procedure. Materials and methods We developed a low-fidelity, anatomically representative model for cesarean hysterectomy simulation purposes. Obstetrics and Gynecology residents at two residency programs were offered a simulation experience using the model, with a performance assessment via two validated assessment tools. The clinical case involved a 38 y/o woman with a delivery complicated by postpartum hemorrhage who failed conservative therapy and required a peripartum hysterectomy. Participants included 26 residents, postgraduate year (PGY)1 through PGY4, at two midwestern university-based obstetrics and gynecology residency programs. Results The median resident scores on the Task Specific Checklist (TSC) and Global Rating Scale (GRS) correlated with increasing PGY levels. The combined TSC+GRS score was a median of 40 out of 49 total for the PGY4 class, while the PGY1 class had a median combined TSC+GRS score of 12 of 49. The PGY2 and -3 classes had TSC+GRS scores of 14 and 28, respectively. The simulation model was well-received with a median 4/5 rating for improving comfort level with cesarean hysterectomy and a median 4/5 rating for model realism. Conclusion This study validated a cost-effective, easily reproducible model that highlights the vital anatomy relevant to a cesarean hysterectomy. The model and simulation offer a way to introduce cesarean hysterectomies to residents while in training, particularly at sites that may not perform a substantial number of these procedures.

An investigation of anthropogenic influences on hydrologic connectivity using model stress tests

Abstract. Human influences threaten environmental flows directly or indirectly through groundwater abstraction. In alluvial geological settings, these may affect the contributions from groundwater-sustaining streamflow during dry summer months. The Dreisam River valley in southwest Germany represents a typical case where recurrent hydrological drought events between 2015 and 2022 have led to interruptions of longitudinal connectivity in the stream network. When and where vertical connectivity changes and where the streambed dries out have therefore become important questions. To help answer them, zero water level (ZWL) occurrences were previously measured at 20 locations in the river network during the drought of 2020, but they revealed high variability. This study therefore aimed to develop a methodology that allows the connectivity to be assessed along the entire stream network, i.e. by employing a numerical groundwater model to obtain the spatial distribution of the exchange flow between groundwater and surface water along the river. A reference model simulation for the period 2010–2022 assumed near-natural conditions. Stress test scenario model runs then imposed either an altered recharge regime or a set of introduced groundwater abstraction wells or both. To gain confidence in the model, ZWL patterns are compared to observations of dry riverbed locations in 2020, and the model generally reproduces the observed relative drying. Modelled exchange flows of the stress tests were then compared against the reference simulation. A set of specific metrics combining longitudinal and vertical connectivity is introduced for this task. The results of the stress test model runs show stronger changes of vertical connectivity in response to groundwater (GW) abstraction than to the imposed recharge stress. Reaches are identified where the effects of the stresses are particularly strong. Nevertheless, these results have to be interpreted within the limits of model realism and uncertainty. For more model realism, a number of improvements will be needed such as a higher-resolution parametrization of the riverbed's hydraulic conductivities and better coupling to contributions from hillslopes; for a quantification of the uncertainties, a systematic sensitivity analysis would be required. The study introduces a framework for modelling stress tests and metrics for surface water–groundwater interaction that can be transferred to other cases. It also suggests that even if not all influences can be modelled, the approach may help inform a resilient management of water resources under multiple stresses.

Innovating Flexor Tendon Repair Training with a Three-dimensional Printed Model.

Flexor tendon repair is a technically demanding procedure, with functional outcome directly proportional to skillful execution. A repair must be strong to manage early mobilization and precise to allow for gliding through the tendon sheath. As a result, junior residents face a steep learning curve that may be mitigated by exposure to surgical simulators. To facilitate flexor tendon repair training, a surgical training device and accompanying instructional video were developed. Simulation workshops were held for junior orthopedic and plastic surgery residents (n = 11). To objectively assess validity of the curriculum, study participants performed cadaveric flexor tendon repairs before and after the workshop. Anonymous recordings of these repairs were graded by two certified hand surgeons. Additionally, a tensometer was used to measure strength of repair. Model realism, educational utility, and overall usefulness rated high: 4.6 ± 0.52 95% confidence interval (CI) for realism, 4.9 ± 0.42 95% CI for device, 4.7 ± 0.96 95% CI for video, and 4.9 ± 0.66 95% CI overall. Subjective confidence increased after the training session (73% ranked "moderately" or "extremely"). Likewise, scores given by the surgeons grading the repairs improved for overall quality and time of repair (pre: 2.77 ± 0.61, post: 4.22 ± 0.56, P= 0.0002). Strength of repair did not change (P = 0.87). The proposed three-dimensional surgical simulator for flexor tendon repair is realistic and useful, with improved surgical technique and improved confidence demonstrated after use. This design can be three-dimensionally printed en masse and provide value to hand surgery training curriculum.

Advances and challenges in ecological connectivity science.

Maintaining and restoring ecological connectivity will be key in helping to prevent and reverse the loss of biodiversity. Fortunately, a growing body of research conducted over the last few decades has advanced our understanding of connectivity science, which will help inform evidence-based connectivity conservation actions. Increases in data availability and computing capacity have helped to dramatically increase our ability to model functional connectivity using more sophisticated models. Keeping track of these advances can be difficult, even for connectivity scientists and practitioners. In this article, we highlight some key advances from the past decade and outline many of the remaining challenges. We describe the efforts to increase the biological realism of connectivity models by, for example, isolating movement behaviors, population parameters, directional movements, and the effects of climate change. We also discuss considerations of when to model connectivity for focal or multiple species. Finally, we reflect on how to account for uncertainty and increase the transparency and reproducibility of connectivity research and discuss situations where decisions may require forgoing sophistication for more simple approaches.