Search Results (273)

Understanding landform evolution is essential for assessing how terrain responds to geomorphic drivers such as weathering, fluvial erosion, hillslope processes, and tectonic uplift. This is particularly important in applications such as constructed post-mining landform rehabilitation, where predicting long-term erosional stability is vital for sustainable closure planning. In addition to long-term average erosion rates, the spatial patterns of gullies, rills, and channels are critical for assessing landform stability. This review examines Digital Elevation Model (DEM)—driven, process-based Landform Evolution Models (LEMs), with a primary focus on SIBERIA, CAESAR-Lisflood, and SSSPAM, which are widely used to evaluate the erosional behaviour of constructed post-mining landforms, each with distinct characteristics. These models are systematically compared in terms of input requirements, process representations, parameterisation, and predictive capabilities. Recent advances in high-spatial resolution DEMs (e.g., LiDAR, SRTM), along with digital soil and rainfall databases and satellite-derived vegetation indices, have improved the parameterisation of erosion, hydrological, and sediment-transport processes of the LEMs. A brief comparative case study is presented to demonstrate how these LEMs simulate 1000-year erosional behaviour along a linear hillslope. This review synthesises the current capabilities and limitations of DEM-driven LEMs, providing guidance for researchers, land managers, and practitioners in selecting appropriate models to support sustainable post-mining landform management, as well as outlining potential future advancements. Full article

Conventional uses of building information modeling (BIM) in existing-building representation tend to prioritize geometric consistency and efficiency, but often at the expense of interpretive depth. This paper challenges BIM’s tendency to promote epistemic closure by proposing a method to foreground relational ambiguity, transforming view reconciliation from a default automated process into a generative act of critical inquiry. The method, implemented in Autodesk Revit, introduces a parametric reference frame within BIM sheets that foregrounds and manipulates reciprocal relationships between orthographic views (e.g., plans and sections) to promote interpretive ambiguity. Through a case study, the paper demonstrates how parameterized view relationships can resist oversimplification and encourage conflicting interpretations. By intentionally sacrificing efficiency for epistemic resilience, the method aims to expand BIM’s role beyond documentation, positioning it as a tool for architectural knowledge production. The paper concludes with implications for software development, pedagogy, and future research at the intersection of critical representation and computational tools. Full article

This article provides an in-depth overview of mine gas emission monitoring practices in the Ostrava-Karviná Coalfield (OKR), one of the most significant regions in Central Europe affected by post-mining methane leakage. The study presents field measurement techniques, including atmogeochemical surveys, systematic methane screening in soil air, and surface emission rate monitoring using accumulation chambers. Over the course of several long-term projects, more than 43 km² of land were surveyed, and risk classification maps were developed based on measured methane concentrations and surface release rates. These data support land-use planning, the design of degasification measures, and the verification of their effectiveness. Results confirm that methane emissions persist even decades after mine closures and vary depending on atmospheric pressure and local geological conditions. The OKR methodology was also compared to international practices in Poland, Canada, and China. The article concludes with future research directions focused on automation, integration of sensor networks, and predictive modeling of gas migration in post-mining environments. Full article

To address the challenges in unstructured orchard environments, including high geometric similarity between fruit trees (with the measured average Euclidean distance difference between point cloud descriptors of adjacent trees being less than 0.5 m), significant dynamic interference (e.g., interference from pedestrians or moving equipment can occur every 5 min), and uneven terrain, this paper proposes an improved mapping algorithm named OSC-LIO (Orchard Scan Context Lidar Inertial Odometry via Smoothing and Mapping). The algorithm designs a dynamic point filtering strategy based on Euclidean clustering and spatiotemporal consistency within a 5-frame sliding window to reduce the interference of dynamic objects in point cloud registration. By integrating local semantic features such as fruit tree trunk diameter and canopy height difference, a two-tier verification mechanism combining “global and local information” is constructed to enhance the distinctiveness and robustness of loop closure detection. Motion compensation is achieved by fusing data from an Inertial Measurement Unit (IMU) and a wheel odometer to correct point cloud distortion. A three-level hierarchical indexing structure—”path partitioning, time window, KD-Tree (K-Dimension Tree)”—is built to reduce the time required for loop closure retrieval and improve the system’s real-time performance. Experimental results show that the improved OSC-LIO system reduces the Absolute Trajectory Error (ATE) by approximately 23.5% compared to the original LIO-SAM (Tightly coupled Lidar Inertial Odometry via Smoothing and Mapping) in a simulated orchard environment, while enabling stable and reliable path planning and autonomous navigation. This study provides a high-precision, lightweight technical solution for autonomous navigation in orchard scenarios. Full article

The long-term stability of legacy pillars remains a critical challenge in mining engineering, as pillar collapse may threaten human safety, damage infrastructure, and complicate sustainable mine closure. Conventional empirical methods are often inadequate for addressing the complexity of heterogeneous rock masses and time-dependent deterioration. In this study, a dual-perspective framework is proposed by integrating finite difference method (FDM)-based numerical simulation with artificial intelligence (AI) techniques to improve the reliability of pillar safety assessment. FDM models are developed to analyze stress redistribution, deformation, and failure processes of pillars under varying depths, geometries, rock quality, and rock mechanics. In parallel, AI models are trained on datasets derived from numerical simulations to provide rapid predictions of pillar instability probability (P_f) with high computational efficiency. The complementary use of both approaches ensures cross-validation: FDM simulations provide mechanistic insights into pillar behavior, while AI models enhance predictive capability and account for uncertainties in geological conditions. The integrated framework demonstrates superior robustness and applicability compared to single-method approaches, offering a comprehensive tool for assessing legacy pillar safety. This research provides practical guidance for hazard mitigation, mine closure planning, and the development of monitoring strategies in sustainable mining engineering. Full article

Background/Objectives: Delayed sternal closure (DSC) is a useful management strategy for complex cardiac interventions. The aim of this study was to investigate the patients who had DSC in our clinic over a 12-year period and to evaluate the postoperative results. Methods: A total of 124 DSC patients from a total cardiac surgery practice during a 12-year period (n = 6532, 1.8%, between January 2014 and September 2025) were retrospectively analyzed. Preoperative and intraoperative patient characteristics, morbidities, and mortality rates were collected and compared with the group undergoing primary sternal closure (PSC), which were matched with the DSC group in terms of preoperative and intraoperative patient characteristics. Results: A total of 124 (1.8%) patients required DSC, and 33.1% of the patients were females. The indications were bleeding (n = 81, 65%) and hemodynamic instability (n = 43, 35%). Total bypass times, cross-clamp times, and CPB temperature were higher in patients with DSC. A higher rate of inotropic support, intra-aortic balloon pump, extracorporeal lung support, blood transfusion, and bleeding were found in the DSC group. There was no difference in terms of sternal infection rate (2.4%). Intensive care unit stay, hospital stay, and mortality rate were also significantly increased in patients with DSC. Mortality rate in the DSC group was 16.1%. Conclusions: Multiple sternum revisions due to bleeding and low cardiac output syndrome may lead to increased mortality in high-risk patients. Planned postponement of sternal closure in these high-risk cardiac surgery patients helps to reduce perioperative morbidity and mortality. Full article

The present study describes a digitally guided workflow for the Split Bone Block Technique (SBBT) using standardized cortical and particulate allogeneic grafts in combination with custom-designed, 3D-printed surgical guides. The aim was to illustrate the feasibility of a donor-site-free alternative to the conventional autologous approach, which remains technically demanding and associated with increased morbidity. A narrative literature review and a single clinical case report were conducted to contextualize the proposed workflow. Digital planning was performed by merging DICOM and STL datasets to design cutting boxes for standardized allogeneic laminae and a transporter guide for intraoperative positioning. The technique was applied in a patient with severe horizontal ridge atrophy. Primary wound closure and uneventful healing were achieved. Six-month CBCT evaluation demonstrated an increase in horizontal ridge width from 2 mm to 8 mm. Within the limitations of a single illustrative case, this report suggests that a fully guided allogeneic SBBT workflow is feasible and may facilitate controlled graft adaptation while avoiding autologous bone harvesting. Further controlled clinical studies are required to evaluate accuracy, reproducibility, and long-term outcomes. Full article

Traffic flow anomalies represent significant deviations from normal traffic behavior and disrupt the smooth operation of transportation systems. These may appear as unusually high or low traffic volumes compared to historical trends. Unexpectedly high volume can lead to congestion exceeding usual capacity, while unusually low volume might indicate incidents like road closures, or malfunctioning traffic signals. Identifying and understanding both types of anomalies is crucial for effective traffic management. This paper presents a clustering based approach for enhanced characterization of anamolies in traffic flows. Anomalies in traffic patterns are determined using three anomaly detection techniques: Elliptic Envelope, Isolation Forest, and Local Outlier Factor. These anomalies were newly detected in this work on the Montréal dataset after preprocessing, rather than directly reused from earlier studies. These methods were applied to a dataset that had been pre-processed using windowing techniques with different configuration settings to enhance the detection process. Then, to leverage the detected anomalies, we utilized clustering algorithms, specifically k-means and hierarchical clustering, to segment these anomalies. Each clustering algorithm was used to determine the optimal number of clusters. Subsequently, we characterized these clusters through detailed visualization and mapped them according to their unique characteristics. This approach not only identifies traffic anomalies effectively but also provides a comprehensive understanding of their spatial and temporal distributions, which is crucial for traffic management and urban planning. Full article

Increasing aridity and climate extremes are challenging the resilience of key Mediterranean species. Proxies that indicate plant water status, physiological condition and soil water availability are valuable tools for management planning. However, their reliability requires species-specific validation under dynamic environmental conditions. This study examined the relationship between predawn leaf water potential (Ψ_PD) and soil water potential (Ψ_S) in potted seedlings of two co-occurring Mediterranean evergreen oaks, Q. ilex and Q. suber, subjected to imposed soil drying under greenhouse conditions. We further quantified the occurrence and magnitude of predawn disequilibrium (PDD)—the mismatch between Ψ_PD and Ψ_S—and evaluated its association with soil water availability, plant water-status indicators, environmental factors, and physiological variables. In parallel, we assessed stomatal closure dynamics during the desiccation phase and characterised species-specific mortality patterns under progressive drought. Linear Mixed-Effects Models (LMMs), with pot identity included as a random factor, were fitted to assess the relationship between Ψ_PD and Ψ_S, as well as the occurrence of PDD and its potential drivers for each species. Stomatal conductance (g_s) responses to Ψ_S were evaluated using a paired t-test and an additional LMM. Finally, Generalised Linear Mixed-Effects Models (GLMMs) were used to analyse interspecific differences in mortality. We confirmed a tight relationship between Ψ_PD and Ψ_S, followed by a consistent PDD in both species, with magnitudes of 0.53 MPa for Q. ilex and 0.98 MPa for Q. suber, which increased significantly with drought severity. Our findings suggest that PDD under the studied conditions is primarily driven by soil water depletion and plant desiccation, as indicated by its negative correlation with water status parameters, as well as by its increase with progressive drought. Both oaks exhibited a water-saving strategy, with stomatal closure initiated around Ψ_S = −0.31 MPa (Q. ilex) and −0.42 MPa (Q. suber). Despite their physiological similarities, Q. suber showed higher mortality under imposed drought. These results encourage modelling the relationship between Ψ_PD and Ψ_S to accurately interpret plant and soil water needs in Mediterranean oaks, especially under soil water scarcity, and highlight species-specific responses critical for forest management and restoration under climate change. Full article

The craniofacial skeleton is a complex three-dimensional structure, and major reconstructive cases remain challenging. We describe a synergistic approach combining intra-operative navigation, three-dimensionally (3D) printed skull models, and mixed reality (MR) to improve predictability in surgical outcomes. A patient with previously repaired bilateral cleft lip and palate, significant midfacial retrusion, and a large maxillary alveolar gap underwent segmental Le Fort I osteotomy and advancement. Preoperative virtual planning was performed, and reference templates were uploaded onto MR glasses. Intra-operatively, the MR glasses projected the templates as holograms onto the patient’s skull, guiding osteotomy line marking and validating bony segment movement, which was confirmed with conventional navigation. The 3D-printed skull model facilitated dissection and removal of intervening bony spicules. Preoperative planning proceeded seamlessly across software platforms. Osteotomy lines marked with MR showed good concordance with conventional navigation, and final segment positioning was accurately validated. Postoperative outcomes were satisfactory, with re-established occlusion and closure of the maxillary alveolar gap. The combined use of conventional navigation, 3D-printed models, and MR is feasible and allows safe integration of MR into complex craniofacial reconstruction while further validation of the technology is ongoing. Full article

Background/Objectives: Gastroschisis is a congenital abdominal wall defect characterized by herniation of bowel loops without a covering membrane and typically located to the right of the umbilical cord. Although contemporary management is well established, its historical study development has not been comprehensively synthesized. This review examines the chronological evolution of focus of interest in gastroschisis and highlights how research priorities shifted across eras, shaping current anatomical understanding, diagnostic strategies, and surgical management. Methods: A structured literature search was performed in PubMed, Web of Science, and Scopus. Studies in English, Spanish, Turkish, and Arabic were included. Titles, abstracts, and full texts were screened independently. Eligible publications addressed historical descriptions, differentiation from omphalocele, advancements in imaging, surgical techniques, or experimental modeling. Results: Sixty-eight studies met the inclusion criteria. Early reports from the sixteenth to eighteenth centuries provided descriptive accounts without distinguishing gastroschisis from omphalocele. The nineteenth century introduced the term “gastroschisis,” and definitive clinical differentiation was achieved in the mid twentieth century. Surgical innovation progressed from primary closure in the 1940s to the development of preformed and spring-loaded silos, which improved physiologic tolerance and survival. Animal models clarified mechanisms of bowel injury, including the effects of amniotic exposure and delayed maturation of interstitial cells of Cajal. Advances in ultrasound and magnetic resonance imaging facilitated prenatal risk stratification and shifted research attention toward predicting complex gastroschisis and optimizing perinatal planning. Conclusions: The historical trajectory of studies about gastroschisis demonstrates a coherent pattern in which developments in anatomical definition, surgical innovation, and mechanistic research sequentially enabled modern prenatal diagnostic and prognostic strategies. Recognizing these temporal shifts provides important context for current practice and highlights opportunities to improve prenatal markers of bowel compromise and refine individualized postnatal care. Full article

Severe aortic stenosis represents a significant prognostic burden, particularly in symptomatic patients. The advent of transcatheter aortic valve replacement (TAVR) has revolutionized the treatment of patients previously considered ineligible for surgical aortic valve replacement (SAVR). TAVR provides a relatively safe intervention that leads to improvements in survival, symptoms, and functional status within months of implantation. A major complication following TAVR is the occurrence of paravalvular leaks (PVLs), which have been associated with increased mortality and higher rates of heart failure-related hospitalizations. PVLs refer to abnormal blood flow between the implanted valve and the aortic wall, which can compromise the functionality of the device. Careful pre-procedural planning enables the identification of patients at higher risk for PVL development. Although the incidence of PVLs has decreased with the introduction of newer-generation transcatheter valves, the condition remains clinically relevant. Due to the complex anatomy of the aortic valve apparatus and interference from the prosthetic frame, accurate evaluation of PVLs requires a multimodal diagnostic approach. Current evidence on PVL management is limited. In most cases, a conservative approach is adopted, while interventional strategies (such as pre- and post-dilatation, percutaneous PVL closure, and TAVR-in-TAVR) are reserved for selected patients. We performed a systematic literature review to summarize the incidence, predictors, diagnostic techniques, and management strategies of PVLs following TAVR. Full article

Background: Myogenous temporomandibular disorders (TMDs) typically present with pain but without obvious restriction of mandibular motion, making subtle dysfunctions difficult to detect clinically. In this study, we evaluated mandibular kinematics in myogenous TMDs using an electronic axiography system (Cadiax Diagnostic). The specific objective of this study was to evaluate whether patients with myogenous temporomandibular disorders exhibit qualitative abnormalities in mandibular movements that are not detectable using conventional clinical examination. Methods: Twenty-six patients with myogenous TMD (muscle pain without intra-articular disorders, diagnosed per DC/TMD) and 26 matched controls were examined. Clinical assessment (DC/TMD Axis I) measured mandibular range of motion and deviations. Instrumental recordings of maximal opening, protrusion, and laterotrusion were obtained with Cadiax 4. Quantitative (excursion ranges) and qualitative (movement symmetry and sagittal deviations) parameters were analyzed. Condylar position changes between the reference position and maximum intercuspation were evaluated (Condyle Position Measurement, CPM). Exact χ² or Fisher tests were applied with effect sizes (φ) and 95% confidence intervals (CI). Results: Maximal opening, lateral excursions, and protrusion ranges were statistically similar between groups (mean opening: 47.96 ± 6.5 mm in TMDs vs. 49.46 ± 5.4 mm in controls, p = 0.40; 95% CI of difference −1.8 to 4.8 mm). However, qualitative deviations were more frequent in TMD. Of note, 12/26 (46.2%) patients vs. 6/26 (23.1%) controls showed a ΔY deflection during protrusion (χ² = 3.06, p = 0.08; φ ≈ 0.24; difference = 23.1%, 95% CI −2.0–48.2%). Identical proportions (46.2% vs. 23.1%) showed a ΔY deflection upon opening (χ² = 3.06, p = 0.08). Inferior condylar shifts (distractions) on closing into intercuspation occurred only in the mTMD group: 5/26 (19.2%) left condyles vs. 0% (p ≈ 0.05; 95% CI diff 4.1–34.4%) and 2/26 (7.7%) right vs. 0% (p ≈ 0.49; 95% CI −2.5–17.9%). Condylar compressions (superior shifts) were similar between groups. In summary, roughly half of TMD patients exhibited lateral jaw deflections (ΔY) and exclusive condylar “distraction” on closure; upon comparison, these conditions were rare in controls. Conclusions: Despite normal mandibular range of motion, patients with myogenous TMDs exhibited qualitative abnormalities in jaw kinematics, including movement deflections, condylar asymmetries, and centric–intercuspal discrepancies. Axiographic analysis with Cadiax enabled detection of subtle functional changes not identifiable in routine examinations, underscoring its diagnostic value in early dysfunction and potential therapeutic planning. The detection of kinematic abnormalities could influence early diagnosis or treatment planning for myogenous TMDs. Full article

Background: Almaty, located in a mountain–valley basin, frequently experiences stagnant conditions that trap pollutants and cause sharp diurnal contrasts in air quality. Current forecasting systems either offer detailed physical realism at high computational cost or yield statistically accurate but physically inconsistent results. Urban air quality in mountain–valley cities is strongly shaped by thermal inversions and weak nocturnal ventilation that trap pollutants close to the surface. We present a hybrid physics–machine-learning framework that combines a Navier–Stokes surface-layer model with data-driven post-processing to produce short-term forecasts of wind, temperature, and particulate matter while preserving physical consistency. The approach captures diurnal ventilation patterns and the well-known negative linkage between near-surface wind and particulate loadings during wintertime inversions. Compared with purely statistical baselines, the hybrid system improves short-range forecast skill and maintains interpretability through physically grounded diagnostics. Beyond Almaty, the workflow is transferable to other mountain–valley environments and is directly actionable for early warning, traffic and heating-related emission management, and health-risk communication. By uniting physically meaningful fields with lightweight Machine Learning correction, the method offers a practical bridge between computational fluid dynamics and operational decision support for cities facing recurrent stagnation episodes. Aim: Develop and verify a method for the diagnostics and short-term forecasting of surface circulation and particle concentrations in Almaty (2024), ensuring physical consistency of fields, increased forecast accuracy on 6–24 h horizons, and interpretability of risk factors. Compared to purely statistical baselines (R² ≈ 0.55 for PM forecasts), our hybrid framework achieved a 16% gain in explained variance and reduced RMSE by 25%. This improvement was most evident during winter inversion episodes. Methods: This study introduces a hybrid modeling framework that integrates the Navier–Stokes equations with machine-learning algorithms to diagnose and forecast surface air circulation and particulate matter concentrations. The approach ensures both physical consistency and improved predictive accuracy for short-term horizons (6–24 h). The Navier–Stokes equations in the Boussinesq approximation, the energy equation, and K-closure particulate matter transport were used. The numerical solution is based on the projection method (convection—TVD/QUICK, pressure—Poisson equation). The ML module is gradient boosting and decision trees for meteorological parameters, lags, and diagnostic quantities. The 2024 data are cleaned, normalized, and visualized. Results: The hybrid model reproduces the diurnal cycle of ventilation and concentrations, especially during winter inversions. For 6 h: wind RMSE ≈ 1.2 m/s (R² ≈ 0.71), temperature RMSE ≈ 1.8 °C (R² ≈ 0.78), and particles RMSE ≈ 0.012 mg/m³ (R² ≈ 0.64). Errors are higher for 24 h. A negative relationship between wind and concentration was established: +1 m/s reduces the median by 10–15% during winter nights. Conclusions: The approach can be generalized to other mountain–valley cities beyond Almaty. Combining the physical model and ML correction improves short-term predictive ability and maintains physical consistency. The method is applicable for air quality risk assessment and decision support; further clarification of emissions and consideration of urban canyon geometry are required. The results support early-warning systems, health risk communication, and urban planning. Full article

Background: Myxofibrosarcomas are notoriously highly infiltrative soft-tissue sarcomas, making negative surgical margins difficult to obtain. Recently, vacuum-assisted closure (VAC) is used to delay wound closure until a negative margin has been achieved; however, this can delay care and increase costs. Our institution has historically performed single-stage resections with intraoperative frozen margin analysis and reconstruction in these patients. The purpose of this study is to report the outcomes of this technique. Methods: We reviewed 112 patients (62 males, mean age 70 ± 14 years) with superficial myxofibrosarcoma. Eighty-eight patients received preoperative radiation. All patients underwent surgical resection with intraoperative frozen margin analysis, and the planned reconstruction was performed in a single anesthetic. Results: The 10-year local recurrence-free survival was 90%; positive intraoperative frozen section (HR 7.44, p = 0.004) and final permanent margins (HR 8.53, p = 0.007) were associated with local recurrence. Intraoperative margins were negative in 103 (92%) of patients, 1 of which was positive on final permanent section. There were nine cases of microscopically positive margins, of which seven underwent immediate re-excision to a negative margin. The accuracy of frozen margin assessment for myxofibrosarcoma was between 92.92 and 98.23%. All patients underwent reconstruction at the time of resection, with 19% needing an additional procedure, most commonly due to a wound complication (12%). Conclusions: Multidisciplinary single-stage excision with intraoperative frozen margin assessment and soft-tissue reconstruction yields low rates of local recurrence in patients with superficial myxofibrosarcoma. Full article