Synthetic Model Research Articles

Robust CO2 plume imaging by joint tomographic inversion using distributed pressure and temperature measurements

The scientific community has become increasingly interested in geological CO2 sequestration and CO2 enhanced oil recovery (EOR). The tracking of the CO2 propagation in both space and time during geologic sequestration is necessary to ensure the secure and effective handling of a site for CO2 injection. Our objective is to develop efficient and novel models and monitoring techniques for visualizing CO2 plumes using field measurements. As a first step, the streamline-based data integration approach is extended to include data from distributed temperature sensors (DTS). The DTS and pressure data are then jointly history matched using a hierarchical workflow combining evolutionary and streamline methods. As a final step, we will create maps that visualize CO2 propagation during the sequestration process based on saturation and streamline maps. We validate the extended streamline-based inversion method using a synthetic model. An application of the hierarchical workflow is then made to the CO2 geologic storage test site in Michigan, USA. Monitoring data includes bottom-hole pressure of the injection well, DTS data at the monitoring well, and distributed pressure measurements from several downhole sensors along the monitoring well. Based on the history matching results, the CO2 movement is largely limited to the zones intended for injection, which is in agreement with an independent warmback analysis of the temperature data. The novelty of this work is the extension of the streamline-based inversion algorithm for the DTS data, its field application to the Department of Energy regional carbon sequestration project, and potential extensions to other CO2-EOR and/or associated geological storage projects.

Joint inversion of induced polarization and hydraulic tomography data for hydraulic conductivity imaging

SUMMARY For accurate modelling of groundwater flow and transport processes within an aquifer, precise knowledge about hydraulic conductivity K and its small-scale heterogeneities is fundamental. Methods based on pumping tests, such as hydraulic tomography (HT), allow for retrieving reliable K-estimates, but are limited in their ability to image structural features with high resolution, since the data from time-consuming hydraulic tests are commonly sparse. In contrast, geophysical methods like induced polarization (IP) can potentially yield structural images of much higher resolution, but depend on empirical petrophysical laws that may introduce significant uncertainties to the K-estimation. Therefore, this paper presents a joint inversion procedure for both HT and IP data, which allows for combining the complementary abilities of both methods. Within this approach, a traveltime inversion is applied to the HT data, while the IP inversion is based on a full-decay time-domain forward response, as well as a reparametrization of the Cole–Cole model to invert for K directly. The joint inversion is tested on a synthetic model mimicking horizontally layered sediments, and the results are compared with the individual HT and IP inversions. It is shown that jointly inverting both data sets consistently improves the results by combining the complementary sensitivities of the two methods, and that the inversion is more robust against changes in the experimental setups. Furthermore, we illustrate how a joint inversion approach can correct biases within the petrophysical laws by including reliable K-information from hydraulic tests and still preserving the high-resolution structural information from IP. The different inversion results are compared based on the structural similarity index (SSIM), which underlines the robustness of the joint inversion compared to using the data individually. Hence, the combined application of HT and IP within field surveys and a subsequent joint inversion of both data sets may improve our understanding of hydraulically relevant subsurface structures, and thus the reliability of groundwater modelling results.

Protocells Featuring Membrane-Bound and Dynamic Membraneless Organelles.

Living cells, especially eukaryotic ones, use multicompartmentalization to regulate intra- and extracellular activities, featuring membrane-bound and membraneless organelles. These structures govern numerous biological and chemical processes spatially and temporally. Synthetic cell models, primarily utilizing lipidic and polymeric vesicles, have been developed to carry out cascade reactions within their compartments. However, these reconstructions often segregate membrane-bound and membraneless organelles, neglecting their collaborative role in cellular regulation. To address this, we propose a structural design incorporating microfluidic-produced liposomes housing synthetic membrane-bound organelles made from self-assembled poly(ethylene glycol)-block-poly(trimethylene carbonate) nanovesicles and synthetic membraneless organelles formed via temperature-sensitive elastin-like polypeptide phase separation. This architecture mirrors natural cellular organization, facilitating a detailed examination of the interactions for a comprehensive understanding of cellular dynamics.

Emergence of two-fold non-Hermitian spectral topology through synthetic spin engineering

The union of topology and non-Hermiticity has led to the unveiling of many intriguing phenomena. We introduce a synthetic spin-engineered model belonging to symmetry class AI, which is a rare occurrence, and demonstrate the emergence of a multi-fold spectral topology. As an example of our proposal, we engineer non-Hermiticity in the paradigmatic Su–Schrieffer–Heeger (SSH) model by introducing a generalized synthetic spin, leading to an emergent two-fold spectral topology that governs the decoupled behaviour of the corresponding non-Hermitian skin effect. As a consequence of the spin choice, our model exhibits a rich phase diagram consisting of distinct topological phases, which we characterize by introducing the notion of paired winding numbers, which, in turn, predict the direction of skin localization under open boundaries. We demonstrate that the choice of spin parameters enables control over the directionality of the skin effect, allowing for it to be unilateral or bilateral. Furthermore, we discover non-dispersive flat bands emerging within the inherent SSH model framework, arising from the spin-engineering approach. We also introduce a simplified toy model to capture the underlying physics of the emergent flat bands and direction-selective skin effect. As an illustration of experimental feasibility, we present a topoelectric circuit that faithfully emulates the underlying spin-engineered Hamiltonian, providing a viable platform for realizing our predicted effects. Our findings pave way for the exploration of unconventional spectral topology through spin-designed models.

Boron Abundances in Early B Dwarfs of the Galactic Open Cluster NGC 3293* * Based on observations made with the NASA/ESA Hubble Space Telescope, obtained at the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-26555. These observations are associated with proposal GO-14673.

New boron abundances or upper limits have been determined for eight early B stars in the young Galactic open cluster NGC 3293, using UV spectra obtained by the Hubble Space Telescope Cosmic Origins Spectrograph. With previous observations, there are now 18 early B stars in this cluster with boron measurements. Six of the newly observed stars have projected rotational velocities greater than 200 km s−1, allowing new constraints on rotationally driven mixing in main-sequence stars. When comparing to synthetic model populations, we find that the majority of our sample stars agree well with the predicted trends of stronger boron depletion for larger rotation and for larger mass or luminosity. Based on those, a smaller than the canonical rotational mixing efficiency (f c ≈ 0.0165 versus the more standard value of 0.033) appears to be favored. In addition, the five mostly slowly rotating stars, when considered as a group, tend to show more boron depletion than expected from rotational mixing, and we speculate that most or all of these originate from binary mergers.

Relative contribution of the nail and plate to a nail-plate construct for comminuted distal femoral fractures.

The purpose of this study was to assess the biomechanical contributions of the nail and the plate individually to a complete nail-plate construct in the setting of comminuted distal femur fractures. For this biomechanical study, comminuted extra-articular distal femur fractures were created in 24 synthetic osteoporotic femur models. These were then split into three groups: the nail-only group, the plate-only group, and the nail-plate group. After fixation, each specimen underwent sequential axial and torsional loading, and axial and torsional stiffness were calculated and compared. The addition of a nail to a plate-only construct increased axial stiffness by 19.7% and torsional stiffness by 59.4%. The plate-only group and nail-plate group both demonstrated significantly greater axial and torsional stiffness than the nail-only group at all levels of axial and torsional load. (p < 0.001) At 1000 and 2000 N of cyclic loading, the nail-plate group demonstrated significantly greater axial stiffness than the plate-only group (p ≤ 0.018). The nail-plate group demonstrated greater torsional stiffness than the plate-only groups at all levels of torsional loading (p < 0.001). In osteoporotic comminuted distal femur fracture models, most of the axial stiffness in a nail-plate construct comes from the plate. While the combination of the two constructs is not fully additive, the plate contributes the majority of the axial and torsional stiffness in a nail-plate construct. The supplementation of the plate with a nail primarily helps to increase resistance to rotational forces. Level of Evidence: III.

Use of GIS tools, enhanced by FFT filtering methods, to detect blurred craters in Synthetic Digital Elevation Models, to improve their location and morphological characterisation

Filtered Geomorphic Reference Models (FGRMs), extracted from High-Pass Filters based on the Fast Fourier Transform (HPF-FFT), provide a semi-automated and objective detection of a wide range of geoforms and geomorphic situations (flat areas, slopes, depressions, or valley bottoms). The method is sensitive enough to reveal numerous inflection points that enable the identification of subtle changes in relief polarity, resulting in accurate representations of real land depressions. The effectiveness of this method has been demonstrated in lunar landscapes, utilizing altimetry extracted from high-precision Planetary Digital Elevation Models (PDEMs) to construct crater inventories with well-defined FGRMs. However, when analysing lunar environments with closely-spaced geomorphic features, the FGRMs display blurring and generalization effects, reducing their capability to identify all existing crater depressions. This limitation controls the ability of FGRMs, to generate reliable crater inventories. This study examines such effects in three experiments. Using Synthetic Digital Relief Models (SDRMs) constructed by means of a MATLAB script two experiments are performed. In Experiment_1 different scenarios of proximity between aligned craters are analysed. The marks, or footprints, formed by craters of identical size and shape (i.e., circular bowl-shaped depressions with central peaks) are considered, resulting in simplified PDEMs. Various scenarios of crater centre separation (proximity) and the presence of internal features within craters are also analysed. Experiment_2 validates the method with different proximities, locations and crater sizes. Experiment_3 validates the approach in a sampled area of LRO lunar PDEM corresponding to Zelinskiy crater (Mare Ingenii area). To address these blurring effects, a hybrid methodology is employed, generating FGRMs extracted from HPF-FFT, in conjunction with other GIS and remote sensing tools, such as singular point zoning, aspect-slope zoning, and edge-limits zoning. As a result, the correspondence between the FGRMs and the synthetic forms is examined, aiding the comprehension of the graphical response provided by filtering in these cratered areas. The methodology demonstrates that FGRMs derived from HPF-FFT are sensitive to capturing connections between shapes as soon as the crater features start to merge, while blurring becomes evident when the craters are located at a proximity of <20 model units. Additionally, the results highlight the method's utility in accurately locating crater footprints and morphologically characterizing inner crater features, even when crater centres are closely spaced. This approach effectively mitigates blurring effects and enables the precise localization of crater marks and their internal features. The validations carried out in complex relief and high precise DEMs provide a use in real situation.

The effect of oxidative degradation of Dopa-melanin on its basic physicochemical properties and photoreactivity.

Melanin, particularly eumelanin, is commonly viewed as an efficient antioxidant and photoprotective pigment. Nonetheless, the ability of melanin to photogenerate reactive oxygen species and sensitize the formation of cyclobutane pyrimidine dimers may contribute to melanin-dependent phototoxicity. The phototoxic potential of melanin depends on a variety of factors, including molecular composition, redox state, and degree of aggregation. Using complementary spectroscopic and analytical methods we analyzed the physicochemical properties of Dopa-melanin, a synthetic model of eumelanin, subjected to oxidative degradation induced by aerobic photolysis or exposure to 0.1 M hydrogen peroxide. Both modes of oxidative degradation were accompanied by dose-dependent bleaching of melanin and irreversible modifications of its paramagnetic, ion- and electron-exchange and antioxidant properties. Bleached melanin exhibited enhanced efficiency to photogenerate singlet oxygen in both UVA and short-wavelength visible light. Although chemical changes of melanin subunits, including a relative increase of DHICA content and disruption of melanin polymer induced by oxidative degradation were considered, these two mechanisms may not be sufficient for a satisfactory explanation of the elevated photosensitizing ability of the bleached eumelanin. This study points out possible adverse changes in the photoprotective and antioxidant properties of eumelanin that could occur in pigmented tissues after exposure to high doses of intense solar radiation.

A fully synthetic three-dimensional human cerebrovascular model based on histological characteristics to investigate the hemodynamic fingerprint of the layer BOLD fMRI signal formation.

Recent advances in functional magnetic resonance imaging (fMRI) at ultra-high field (≥7 tesla), novel hardware, and data analysis methods have enabled detailed research on neurovascular function, such as cortical layer-specific activity, in both human and nonhuman species. A widely used fMRI technique relies on the blood oxygen level-dependent (BOLD) signal. BOLD fMRI offers insights into brain function by measuring local changes in cerebral blood volume, cerebral blood flow, and oxygen metabolism induced by increased neuronal activity. Despite its potential, interpreting BOLD fMRI data is challenging as it is only an indirect measurement of neuronal activity. Computational modeling can help interpret BOLD data by simulating the BOLD signal formation. Current developments have focused on realistic 3D vascular models based on rodent data to understand the spatial and temporal BOLD characteristics. While such rodent-based vascular models highlight the impact of the angioarchitecture on the BOLD signal amplitude, anatomical differences between the rodent and human vasculature necessitate the development of human-specific models. Therefore, a computational framework integrating human cortical vasculature, hemodynamic changes, and biophysical properties is essential. Here, we present a novel computational approach: a three-dimensional VAscular MOdel based on Statistics (3D VAMOS), enabling the investigation of the hemodynamic fingerprint of the BOLD signal within a model encompassing a fully synthetic human 3D cortical vasculature and hemodynamics. Our algorithm generates microvascular and macrovascular architectures based on morphological and topological features from the literature on human cortical vasculature. By simulating specific oxygen saturation states and biophysical interactions, our framework characterizes the intravascular and extravascular signal contributions across cortical depth and voxel-wise levels for gradient-echo and spin-echo readouts. Thereby, the 3D VAMOS computational framework demonstrates that using human characteristics significantly affects the BOLD fingerprint, making it an essential step in understanding the fundamental underpinnings of layer-specific fMRI experiments.

AdvNF: Reducing mode collapse in conditional normalising flows using adversarial learning

Deep generative models complement Markov-chain-Monte-Carlo methods for efficiently sampling from high-dimensional distributions. Among these methods, explicit generators, such as Normalising Flows (NFs), in combination with the Metropolis Hastings algorithm have been extensively applied to get unbiased samples from target distributions. We systematically study central problems in conditional NFs, such as high variance, mode collapse and data efficiency. We propose adversarial training for NFs to ameliorate these problems. Experiments are conducted with low-dimensional synthetic datasets and XY spin models in two spatial dimensions.

Copper sulfide mineral performs non-enzymatic anaerobic ammonium oxidation through a hydrazine intermediate.

Anaerobic ammonium oxidation (anammox)-the biological process that activates ammonium with nitrite-is responsible for a significant fraction of N2 production in marine environments. Despite decades of biochemical research, however, no synthetic models capable of anammox have been identified. Here we report that a copper sulfide mineral replicates the entire biological anammox pathway catalysed by three metalloenzymes. We identified a copper-nitrosonium {CuNO}10 complex, formed by nitrite reduction, as the oxidant for ammonium oxidation that leads to heterolytic N-N bond formation from nitrite and ammonium. Similar to the biological process, N2 production was mediated by the highly reactive intermediate hydrazine, one of the most potent reductants in nature. We also found another pathway involving N-N bond heterocoupling for the formation of hybrid N2O, a potent greenhouse gas with a unique isotope composition. Our study represents a rare example of non-enzymatic anammox reaction that interconnects six redox states in the abiotic nitrogen cycle.

Anisotropy in Stratified and Equivalent Media: Kinematic and Amplitude Analysis

We implemented an elastic-anisotropic seismic modeling algorithm via synthetic models to evaluate different geological scenarios, where intercalations of sandstones and shales, carbonates and shales and halite and high-speed salt were simulated. These lithologies were selected based on their abundance in the sedimentary record and the importance they have in the composition of petroleum systems. We analyzed the results relative to kinematic and dynamic aspects to broaden the understanding of how these elements act in the presence of anisotropy. Additionally, the elastic and anisotropic parameters of intercalations composed by the referred lithologies were analytically estimated, thus obtaining the characteristics of several equivalent media. The results confirm previous postulations that the intercalation of layers with different properties can generate extrinsic anisotropy, contributing to the perspective of different wavelength(λ)/thickness ratios favorable to such effects. The results indicate that λ/thickness ratios greater than 6 are propitious for extrinsic anisotropy generation and the use of equivalent media as substitutes for stratified layers are ratified for thicknesses lower than 10 meters. Also, it was observed that in most cases, intrinsic anisotropy has a main role over extrinsic anisotropy.

Joint inversion of direct waves, primaries, and multiples for vertical cable seismic data

By anchoring vertical cable in seawater and receiving the data excited by the towing cable seismic source, the reflection data from subsurface structures with a high signal-to-noise ratio, wide frequency band, and wide azimuth angle can be obtained, thereby achieving high-quality imaging of the target area. However, due to drifting receivers driven by ocean currents and the nonuniform coverage caused by the vertical orientation of the receivers, the traditional imaging method cannot be directly used in the vertical cable seismic data. Furthermore, crosstalk between the primaries and multiples commonly contaminates the final imaging. A new inversion method, based on the Bayesian inference and the assumption that all errors are Gaussian distributed, is presented to address these problems. The direct waves are used to invert the source/receiver locations. The primary and multiple wavefields are accurately reconstructed based on the reconstructed direct wavefield, and the corresponding reflectivity updates are obtained. The model-domain Hessian matrices consisting of different data are approximated by their diagonal elements to mitigate the nonuniform coverage issue, and the related covariance matrices and data-domain Hessian matrices are defined and approximated, respectively, to alleviate the calculation problem. In addition, the zero-lag correlated wavefields in the gradient are consistent with the actual wavefield propagation process, e.g., a primary wave is generated when the direct wavefield encounters reflectivity, avoiding the crosstalk. Numerical examples for synthetic models and field data illustrate that our method can accurately recover the source/receiver locations and provide high-resolution balanced-amplitude imaging results without evident crosstalk.

Training in Endoscopic Endonasal Neurosurgical Procedures: A Systematic Review of Available Models

Abstract Background Proficiency in endoscopic endonasal neurosurgery (EEN) requires a unique skill set and is associated with a steep learning curve. Endoscopic simulation models present an opportunity for trainees to enhance their surgical skills and anatomical knowledge in a risk-free environment. To date, four main categories of training modalities have been recorded: cadaveric, synthetic, animal, and virtual reality (VR) models. Objective To analyze the features, advantages, and disadvantages of each EEN training model, describe the stages of simulation training, and propose future directions and an algorithm for EEN training. Methods A comprehensive search was performed including studies published before August 2023. Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines were followed in the search and selection of studies included. Terms for searching title and abstract were (“simulation”) AND (“endoscopic endonasal”) AND (“neurosurgery”). Articles were screened for duplicates. Results We identified 176 references, and 43 studies met the inclusion criteria. Twelve articles described cadaveric models, with 7 of them studying internal carotid artery injury management and 3 of them cerebrospinal leak management; 14 articles illustrated synthetic models, 1 article described animal models, and 16 articles outlined VR simulations. Conclusion Cadaveric models provide realistic hands-on surgical training with acceptable cost and remain the gold standard method for training. Synthetic models are most effective for preoperative surgical planning and animal models are best suited for testing of hemostatic techniques. VR simulations may become the primary training tool for novices to acquire basic anatomical knowledge as their role in advanced surgical planning is evolving.

PASS4SWAT: Orchestration of containerized SWAT for facilitating computational reproducibility of model calibration and uncertainty analysis

When performing modeling routines with iterative simulations, a research gap exists in developing the parallelizing frameworks that are adaptable to the increasing complexities of the hydrologic models. This study addresses this gap by proposing a parallel simulation stack for SWAT (PASS4SWAT) that leverages the power of cloud-native infrastructure. Cloud-native applications are designed to be scalable, agile, and resilient, making them ideal for computationally intensive tasks such as hydrologic modeling. To achieve this goal, PASS4SWAT was created by integrating a message broker, a container runtime and orchestration tool, and certain components from SWAT-CUP. We evaluated PASS4SWAT using the Jinjiang watershed model and a synthetic model with high input/output demands to demonstrate its effectiveness. The results show that PASS4SWAT can consistently replicate the results obtained with SWAT-CUP and significantly reduce the runtime, achieving 91.5% and 93.2% reductions in single-node and multinode Kubernetes clusters, respectively. Therefore, in this paper, we conclude that PASS4SWAT can effectively address the high computational demands of the SWAT model by scaling out parallel tasks on a cluster, and can adapt flexibly to diverse environments, including single-node clusters, multinode clusters, and potential cloud platforms.

Thermodynamics of Proton-Coupled Electron Transfer at Tricopper μ-Oxo/Hydroxo/Aqua Complexes.

Multicopper oxidases (MCOs) utilize a tricopper active site to reduce dioxygen to water through 4H+ 4e- proton-coupled electron transfer (PCET). Understanding the thermodynamics of PCET at a tricopper cluster is essential for elucidating how MCOs harness the oxidative power of O2 while mitigating oxidative damage. In this study, we determined the O-H bond dissociation free energies (BDFEs) and pKa values of a series of tricopper hydroxo and tricopper aqua complexes as synthetic models of the tricopper site in MCOs. Tricopper intermediates on the path of alternating electron and proton transfer (ET-PT-ET-PT-ET) have modest BDFE(O-H) values in the range of 53.0-57.1 kcal/mol. In contrast, those not on the path of ET-PT-ET-PT-ET display much higher (78.1 kcal/mol) or lower (44.7 kcal/mol) BDFE(O-H) values. Additionally, the pKa of bridging OH and OH2 motifs increase by 8-16 pKa units per oxidation state. The same oxidation state changes have a lesser impact on the pKa of N-H motif in the secondary coordination sphere, with an increase of ca. 5 pKa units per oxidation state. The steeper pKa increase of the tricopper center promotes proton transfer from the secondary coordination sphere. Overall, our study shed light on the PCET pathway least prone to decomposition, elucidating why tricopper centers are an optimal choice for promoting efficient oxygen reduction reaction.

Validation of a synthetic simulation model of endoscopic rectus sheath plication.

Literature reviews outline minimally invasive approaches for abdominal diastasis in patients without skin excess. However, few surgeons are trained in endoscopic rectus sheath plication, and no simulated training programs exist for this method. This study aimed to develop and validate a synthetic simulation model for the training of skills in this approach under the Messick validity framework. A cross-sectional study was carried out to assess the participants' previous level of laparoscopic/endoscopic skills by a questionnaire. Participants performed an endoscopic plication on the model and their performance was evaluated by one blinded observer using the global rating scale OSATS and a procedure specific checklist (PSC) scale. A 5-level Likert survey was applied to 5 experts and 4 plastic surgeons to assess Face and Content validity. Fifteen non-experts and 5 experts in abdominal wall endoscopic surgery were recruited. A median OSATS score [25 (range 24-25) vs 14 (range 5-22); p < 0.05 of maximum 25 points] and a median PSC score [11 (range 10-11) vs 8 (range 3-10); p < 0.05 of maximum 11 points] was significantly higher for experts compared with nonexperts. All experts agreed or strongly agreed that the model simulates a real scenario of endoscopic plication of the rectus sheath. Our simulation model met all validation criteria outlined in the Messick framework, demonstrating its ability to differentiate between experts and non-experts based on their baseline endoscopic surgical skills. This model stands as a valuable tool for evaluating skills in endoscopic rectus sheath plication.

Quantifying dysmorphologies of the neurocranium using artificial neural networks.

Craniosynostosis, a congenital condition characterized by the premature fusion of cranial sutures, necessitates objective methods for evaluating cranial morphology to enhance patient treatment. Current subjective assessments often lead to inconsistent outcomes. This study introduces a novel, quantitative approach to classify craniosynostosis and measure its severity. An artificial neural network was trained to classify normocephalic, trigonocephalic, and scaphocephalic head shapes based on a publicly available dataset of synthetic 3D head models. Each 3D model was converted into a low-dimensional shape representation based on the distribution of normal vectors, which served as the input for the neural network, ensuring complete patient anonymity and invariance to geometric size and orientation. Explainable AI methods were utilized to highlight significant features when making predictions. Additionally, the Feature Prominence (FP) score was introduced, a novel metric that captures the prominence of distinct shape characteristics associated with a given class. Its relationship with clinical severity scores was examined using the Spearman Rank Correlation Coefficient. The final model achieved excellent test accuracy in classifying the different cranial shapes from their low-dimensional representation. Attention maps indicated that the network's attention was predominantly directed toward the parietal and temporal regions, as well as toward the region signifying vertex depression in scaphocephaly. In trigonocephaly, features around the temples were most pronounced. The FP score showed a strong positive monotonic relationship with clinical severity scores in both scaphocephalic (ρ = 0.83, p < 0.001) and trigonocephalic (ρ = 0.64, p < 0.001) models. Visual assessments further confirmed that as FP values rose, phenotypic severity became increasingly evident. This study presents an innovative and accessible AI-based method for quantifying cranial shape that mitigates the need for adjustments due to age-specific size variations or differences in the spatial orientation of the 3D images, while ensuring complete patient privacy. The proposed FP score strongly correlates with clinical severity scores and has the potential to aid in clinical decision-making and facilitate multi-center collaborations. Future work will focus on validating the model with larger patient datasets and exploring the potential of the FP score for broader applications. The publicly available source code facilitates easy implementation, aiming to advance craniofacial care and research.

Social distancing and COVID-19 under violence: Evidence from Colombia

Did violence increase social distancing and decrease COVID-19 cases? We investigated the effects of massacres on social distancing and subsequent impacts on COVID-19 cases in Colombia. Using an augmented synthetic control method model, we find that massacres reduced human mobility toward parks by six percentage points compared to unaffected areas. However, we did not find significant changes in workplace mobility. Moreover, alterations in social interactions caused by the violence had minimal effects on the spread of COVID-19. Following the occurrence of the first massacre, there was a decrease in 35 new cases per 100,000 inhabitants in the subsequent four months, with no evidence of changes in COVID-19 deaths. By leveraging an exogenous shock unrelated to the fear of the disease or its previous levels, we demonstrate the effect of social distancing and offer insights into social dynamics and public health.

Conversion of T2-Weighted Magnetic Resonance Images of Cervical Spine Trauma to Short T1 Inversion Recovery (STIR) Images by Generative Adversarial Network.

The short T1 inversion recovery (STIR) sequence is advantageous for visualizing ligamentous injuries, but the STIR sequence may be missing in some cases. The purpose of this study was to generate synthetic STIR images from MRI T2-weighted images (T2WI) of patients with cervical spine trauma using a generative adversarial network (GAN). Methods: A total of 969 pairs of T2WI and STIR images were extracted from 79 patients with cervical spine trauma. The synthetic model was trained 100 times, and the performance of the model was evaluated with five-fold cross-validation. Results: As for quantitative validation, the structural similarity score was 0.519±0.1 and the peak signal-to-noise ratio score was 19.37±1.9 dB. As for qualitative validation, the incorporation of synthetic STIR images generated by a GAN alongside T2WI substantially enhances sensitivity in the detection of interspinous ligament injuries, outperforming assessments reliant solely on T2WI. The GAN model can generate synthetic STIRs from T2 images of cervical spine trauma using image-to-image conversion techniques. The use of a combination of synthetic STIR images generated by a GAN and T2WI improves sensitivity in detecting interspinous ligament injuries compared to assessments that use only T2WI.