Search Results (348)

Accurate, uncertainty-aware estimation of instantaneous wind turbine output is a prerequisite for integrating onshore assets into low-emission energy systems, where operational monitoring, energy-performance verification, and cooperative asset management depend on auditable digital representations of turbine behaviour. This study develops a Digital Shadow-based power-curve modelling framework on fourteen years of Supervisory Control and Data Acquisition records from an operational Vestas V52 onshore turbine (850 kW, Dundalk Institute of Technology, Ireland; 457,429 ten-minute records spanning 2006–2020) and benchmarks seven methods under identical preprocessing on a strict chronological hold-out (training 2006–2017; testing 2018–2020; n = 52,388). A parallel random 75/25 split is reported only as a within-distribution diagnostic; it quantifies an optimistic R² inflation of 0.003–0.027 depending on architecture. The Artificial Neural Network attains the best chronological performance (R² = 0.9924, BCa 95% confidence interval 0.9910–0.9931, RMSE = 19.79 kW); only the ANN and a one-dimensional Convolutional Neural Network with twenty-four-step wind-speed lags (R² = 0.9921) deliver clear positive skill against the IEC-style manufacturer power curve. Split-conformal calibration of a Quantile Regression Forest raises empirical 90% prediction-interval coverage from 0.534 to 0.904 at a width inflation from 30 to 51 kW. The framework qualifies as a Digital Shadow and is positioned, through a Horizon Europe Technology Readiness Level audit and an explicit mapping to ISO 50001:2018 Plan–Do–Check–Act energy management and Renewable Energy Community governance under Directive (EU) 2018/2001, as an auditable monitoring layer for cooperative onshore wind operations. The empirical evidence base is a single turbine; multi-turbine, multi-site replication is the natural follow-on validation. Full article

Autonomous driving systems (ADSs) are reliable only when heterogeneous sensors, estimation algorithms, and safety mechanisms are engineered as a single coherent safety-critical measurement system rather than as loosely coupled modules. Production stacks integrate cameras, LiDAR, automotive radar, and GNSS/IMU, yet deployment remains constrained by modality-specific failure modes, calibration and synchronization drift, and out-of-distribution (OOD) conditions that violate modeling assumptions. These limitations induce overconfidence and downstream decision errors whenever planning assumes certainty sharper than sensing can justify. This survey introduces a sensor-centric framework linking measurement physics, uncertainty propagation, fusion integrity, safety assurance, and risk-aware planning and control. We formalize what each modality physically measures; unify probabilistic, evidential, and conformal uncertainty representations; analyze filtering, factor-graph, BEV, transformer, and state-space fusion architectures with an emphasis on robustness and graceful degradation; and generalize aviation-style integrity concepts (RAIM/ARAIM) to multi-modal autonomy. The distinctive contribution is a single sensor-to-assurance throughline in which every uncertainty representation is tied to its measurement physics, every fusion architecture is evaluated against an explicit integrity-monitoring requirement generalized from RAIM/ARAIM, and every safety-standard clause is mapped to a concrete architectural mechanism. We map these mechanisms onto ISO 26262, ISO 21448 (SOTIF), ISO/PAS 8800, ANSI/UL 4600, and the UNECE framework, and connect perception uncertainty to decision-making through chance-constrained MPC and formal safety filters (RSS, CBF). Industry case studies and emerging V2X and generative-simulation approaches close the loop to deployable safety arguments. Full article

The white rhinoceros (Ceratotherium simum) offers a unique model for investigating the genomic consequences of extreme demographic bottlenecks. However, the fragmented southern white rhinoceros genome assembly has limited chromosome-scale structural and evolutionary comparisons with the functionally extinct northern subspecies. Here, we report a chromosome-scale genome assembly for the southern white rhinoceros by integrating Oxford Nanopore Technology long-read sequencing, Illumina short-read polishing and high-throughput chromosome conformation capture (Hi-C) scaffolding. The final assembly spans 2.48 Gb and achieves a contig N50 of 42.06 Mb, representing a 452-fold improvement in contiguity over the previous assembly. In total, 2.46 Gb of sequence was anchored to 40 autosomes plus the X and Y chromosomes. Genome annotation identified 1.13 Gb of repetitive elements (45.7% of the assembly), 22,593 protein-coding genes, and 100.68 Mb of segmental duplications. Inspection of the major histocompatibility complex class II gene region further supported the local assembly and annotation reliability, revealing conserved gene composition and order between the southern and northern white rhinoceroses. Whole-genome comparison with the northern white rhinoceros assembly indicated extensive chromosome-scale synteny, along with localized structural variants between the two subspecies, including 111 inversions spanning 33.48 Mb and 497 translocations spanning 36.48 Mb. Furthermore, coalescent demographic reconstruction indicated asynchronous Pleistocene population dynamics for southern and northern white rhinoceroses, reflecting divergent responses to historical climate oscillations. Both subspecies also exhibit lower recent effective population sizes than estimated Pleistocene ancestral levels, underscoring persistent conservation concern. This assembly provides a useful resource for evaluating the genomic consequences of historical bottlenecks, informing future genomic-rescue plans, and strengthening the comparative framework for rhinoceros conservation and evolutionary genomics. Full article

Finite element models of the mitral valve can be useful tools for physicians as a predictive tool for surgical planning, teaching, or observation. In order to seamlessly implement these tools in a clinical setting, the process for the creation of the models needs to take into account the diagnostic procedures and tools available to physicians. In this study, a rapid patient-specific model for clinical applications is developed, creating a parametric geometry from measurements routinely taken during the diagnostic process and maintaining a low computational cost through simplifications in material and boundary conditions. The healthy valve model is then validated against ultrasound images from peak diastole to peak systole, finding a good conformity despite simplifications. These results can serve as a stepping stone towards the development of a clinical digital twin of the mitral valve that combines engineering knowledge and medical process. Full article

Reliable prediction of post-initiation run-out distance of rainfall-induced landslides is essential for hazard assessment, evacuation planning, and disaster-risk mitigation. However, most existing data-driven approaches formulate run-out prediction as a deterministic regression problem and therefore provide limited information on predictive uncertainty, rare long-runout events, and explainable decision support. To address these limitations, this study proposes CQR-EVT-XAI, a trustworthy AI framework that integrates Quantile LightGBM, Conformalized Quantile Regression (CQR), Extreme Value Theory (EVT), and Explainable Artificial Intelligence (XAI) for uncertainty-aware and explainable landslide run-out risk prediction. Based on 10,158 rainfall-induced landslide samples, physics-informed features are constructed from elevation difference H, source area A, source volume V, and mean slope angle $\theta$. The proposed framework generates calibrated prediction intervals, threshold-based exceedance probabilities, upper-tail risk indicators, and interpretable risk levels. The CQR-LightGBM median model achieves high point-prediction accuracy, with $R^2$ = 0.939, RMSE = 18.03 m, and MAE = 6.55 m. Conformal calibration improves the empirical coverage of the nominal 90% and 95% prediction intervals from 0.813 to 0.903 and from 0.876 to 0.953, respectively. Tail-risk analysis shows that the upper prediction bound ${\widehat{L}}_{95}$ effectively identifies extreme long-runout events, achieving recall values of 0.974 and 0.900 for L > 300 m and L > 500 m, respectively. SHAP analysis reveals that elevation difference H, source volume V, and energy-related derived features dominate both median run-out prediction and upper-tail risk behavior, while slope-related variables mainly influence predictive uncertainty and exceedance-risk levels. These results demonstrate that the proposed CQR-EVT-XAI framework provides a practical workflow for calibrated uncertainty quantification, tail-risk identification, and explainable decision support in rainfall-induced landslide run-out risk assessment. Full article

Objectives: This study aimed to evaluate the influence of tumor geometry on dose distribution and delivery accuracy, and to assess the impact of the Automatic Lower Dose Objective (ALDO) function on dosimetric performance. Methods: Computed tomography images of a Rando anthropomorphic phantom were used to simulate intracranial multiple metastases. Two contour groups were generated on the same CT dataset, consisting of two spherical targets with diameters of 1 cm and 2 cm, respectively. For each group, target pairs were created with edge-to-edge separation distances ranging from 1 to 6 cm. Automated single-isocenter stereotactic radiosurgery plans were generated using the HyperArc workflow, both with and without the ALDO function. Dosimetric performance was evaluated using the RTOG conformity index, Paddick conformity index, gradient index, and homogeneity index. Patient-specific quality assurance was performed using electronic portal imaging device-based verification and radiochromic film dosimetry. Gamma analysis with multiple criteria was applied to assess the impact of target size and geometric separation on delivery accuracy. Results: The use of ALDO improved dose conformity and gradient performance but resulted in increased dose heterogeneity and higher hot spots. In non-ALDO configurations, the agreement between EPID portal dosimetry and film measurements varied according to target size, gamma criteria, and spatial position. For the 2 cm targets, EPID portal dosimetry generally demonstrated higher gamma passing rates than film measurements, whereas the 1 cm targets showed mixed results depending on measurement position and gamma criteria. These differences likely reflect the distinct detector characteristics and spatial sensitivities of the two QA methodologies. Larger discrepancies were observed under stricter gamma criteria and at off-axis positions, indicating potential influences of target geometry and high-dose gradient regions within the simplified phantom configurations evaluated in this study. Conclusions: Within the simplified two-target phantom configurations evaluated in this study, tumor geometric distribution significantly affects both dosimetric characteristics and QA outcomes in HyperArc SRS. Film measurements provide greater sensitivity, whereas EPID-PD alone may be insufficient for evaluating small-target high-gradient regions under strict gamma criteria. Full article

Cybersecurity testing laboratories must produce auditable conformity evidence while operating with rapidly changing toolchains, conditional requirements, and qualitative PASS/FAIL/INCONCLUSIVE outcomes. ISO/IEC 17025:2017 is widely used to demonstrate laboratory competence, yet its operationalisation in cybersecurity testing remains under-specified for software- and tool-driven security assessments. This paper separates an architectural contribution from an empirical contribution. The architectural contribution is a digitalized quality-management framework and automation-ready compliance architecture that translate ISO/IEC 17025 clauses into cybersecurity-specific artefacts, decision rules, controlled toolchains, evidence bundles, and review workflows. The empirical contribution is an exploratory single-laboratory case study based on unpublished, anonymised, and confidentiality-constrained laboratory artefacts: an ETSI TS 103 701 workbook with 68 provision-level test groups, including 41 claimed/applicable rows for ambiguity analysis; an IEC 62443 corrective-action plan; and ISO/IEC 17025 governance records. Within this case, structured decision rules and evidence traceability reduced the Conformity Statement Ambiguity Index from 0.976 to 0.049 and converted 37 previously INCONCLUSIVE provisions into PASS determinations. These results are reported as descriptive within-case evidence only; they do not establish predictive validity or cross-laboratory generalisability. The study contributes a clause-to-artefact crosswalk, a concrete evidence-traceability architecture, and candidate cyber-maintenance indicators for future multi-laboratory validation. Full article

To address the control coupling challenges arising from task heterogeneity of unmanned surface vehicle (USV) formation, a distributed hybrid deep reinforcement learning (HDRL) framework is proposed. The framework decomposes the formation task into two subtasks: leader path planning using the single-agent deep reinforcement learning (SADRL) algorithm and follower formation tracking using the multi-agent deep reinforcement learning (MADRL) algorithm. By embedding the physical constraints of the real Otter USV into the training loop, the policy network outputs are mapped to propeller revolutions that conform to its dynamic characteristics. To optimize control performance, a dynamic gating mechanism triggered by formation position error is developed to mitigate multi-objective interference through temporal task scheduling. Concurrently, a mirror mapping mechanism leveraging the physical symmetry of the formation is designed to achieve policy sharing and data augmentation. Furthermore, the desired velocity calculated based on rigid-body kinematics is used to achieve kinematic-compensated formation tracking. The simulation results indicate that, compared to the SADRL algorithm, the planning success rate of HDRL is improved by 44.59%. Furthermore, compared to the MADRL algorithm, the integrated tracking performance is enhanced by 21.79–39.64%. Full article

Background and objectives: Previous dynamic collimator system (DCS) developments included: (1) hardware construction and commissioning, (2) an accurate dose calculation algorithm, (3) a quality assurance approach, and (4) development of optimization tools for treatment planning. Clinical DCS implementation necessitates efficient treatment plan delivery and fully integrated tools. In this work, a novel algorithm for minimizing treatment time was developed with the goal of reducing the DCS time increase, relative to conventional pencil beam scanning, to one minute or less per beam. In this extensive end-to-end evaluation, treatment plans generated with a modified U.S. Food and Drug Administration (FDA)-cleared treatment planning system were delivered on an Ion Beam Applications (IBA) Proteus Plus proton therapy system, with and without a DCS, to evaluate delivery times and dosimetric accuracy for a relatively large patient dataset, providing evidence of the clinical potential of the approach. Methods: Ten previously treated brain patients were replanned, consisting of both deep-seated central and superficial targets, the latter of which required an external 4 cm polyethylene range shifter. DCS treatments were optimized using a maximum conformity planning technique exploiting per-spot collimator capabilities. An optimization algorithm was incorporated to minimize treatment delivery time by determining the optimal sequencing of spot positions and collimator settings. Plan quality was quantified using conformity and dose-volume histogram (DVH)-based metrics while delivery accuracy was validated through measurements using both patient-specific quality assurance (PSQA) and log file analysis at the Miami Cancer Institute (MCI). Results: The DCS reduced the dose gradient index on average by 26.4% (17.7–37.1%) and the mean dose to the adjacent healthy tissue (within 10 mm of the target) by 19.3% (16.3–26.2%). The average reduction to the mean and maximum dose to the involved optic nerves was 50% (25.7–80.7%) and 18.7%, respectively, and the mean and D_2cc dose to the involved brainstem was reduced by 63.9% (31.5–96.4%) and 60.4% (10.8–99.8%), respectively. PSQA pass rates among DCS-collimated and baseline uncollimated treatments were 99.7% and 99.2%, respectively. DCS treatment fields were delivered within an average of 49 s (32–61 s) from their uncollimated intensity modulated proton therapy (IMPT) counterparts. Average spot position errors were −0.05 ± 0.2 mm and 0.04 ± 0.2 mm for the x- and y-position, respectively. The maximum error in magnitude for collimator positioning was 0.2 mm or less. Conclusions: DCS collimated IMPT treatments can provide significant dosimetric improvements over uncollimated treatments. These highly collimated treatments can be delivered with sufficient accuracy for clinical use while incurring an additional time penalty of around one minute or less per field compared to uncollimated treatments. Full article

This study investigates peri-urban land management in Uttar Pradesh through a comparative analysis of Varanasi, Kanpur, and Prayagraj, focusing on the gap between planned frameworks and actual urban growth. As rapidly expanding Tier-II cities, they represent critical sites where formal planning intersects with complex peri-urban transformations. The study employs a mixed-method approach, combining GIS-based master plan conformance analysis using Effective Boundary Control (EBC) with semi-structured expert interviews. This integration enables both spatial measurement of urban expansion and interpretive understanding of underlying governance and institutional dynamics. The results reveal significant divergence between planned and observed development, particularly in peripheral areas, with clear variation across cities. Kanpur exhibits the highest level of non-conformance (EBC: 2.23), indicating weak boundary control and pronounced peri-urban sprawl. Varanasi also demonstrates substantial deviation (EBC: 2.06), reflecting persistent gaps between planning intent and implementation. In contrast, Prayagraj shows relatively stronger conformance (EBC: 1.04), though underlying challenges remain. These differences are shaped by local conditions, including land acquisition conflicts, fragmented governance structures, infrastructure deficits, and limited financial mechanisms. Importantly, the findings underscore that even where spatial conformity appears stronger, it does not necessarily translate into effective planning outcomes. The study concludes that peri-urban growth is not simply unplanned but is shaped by negotiated and context-specific processes. It highlights the need for adaptive, implementation-focused planning, stronger institutional capacity, and integrated financial strategies. By bridging spatial and qualitative analysis, the research provides a more comprehensive framework for understanding and managing peri-urban development in rapidly urbanizing regions. Full article

Background: Testicular irradiation presents technical challenges due to the temperature-dependent cremasteric reflex causing positional variability, yet detailed immobilization protocols addressing this issue and cone-beam computed tomography (CBCT)-based setup data remain lacking. This formative and preliminary single-patient descriptive technical report describes a temperature-controlled immobilization technique and reports preliminary setup observations from its clinical application. Methods: A 74-year-old male with primary testicular diffuse large B-cell lymphoma (DLBCL) received prophylactic contralateral testicular irradiation. The immobilization protocol combined a custom thermoplastic device with infrared warming to maintain the scrotal surface temperature at 36–36.5 °C, intended to facilitate a relaxed scrotal position prior to and during each fraction under temperature-controlled conditions. Treatment was delivered using a three-field three-dimensional conformal radiotherapy (3D-CRT) technique (30.6 Gy in 17 fractions), and seven CBCT scans were used to document interfraction setup measurements. Results: The treatment was completed as planned with adequate target coverage (clinical target volume [CTV] D97% = 100%) and minimal organ-at-risk (OAR) doses. Setup measurements showed a CTV root-mean-square displacement (RMS) of 3.8 mm and a mean Dice similarity coefficient (DSC) of 0.85, while the testis alone showed an RMS of 5.2 mm and a mean DSC of 0.73. Conclusions: The temperature-controlled immobilization technique was feasibly implemented, and the setup measurements observed during its application showed a CTV RMS of 3.8 mm and a mean DSC of 0.85. These findings may provide a practical reference for institutions encountering this rare clinical scenario. Full article

Background/Objectives: Traditional radiotherapy treatments assume that patient anatomy remains unchanged over the course of treatment. Image guidance is used to reproduce the patient setup as closely as possible, and planning margins are used to account for setup errors. With the development of MR-guided Adaptive Radiotherapy (MRgART), daily plan adaptations are now feasible, allowing clinicians to edit the plan according to daily anatomical fluctuations. However, MRgART is currently restricted to step-and-shoot IMRT delivery, which can have reduced dose conformality compared to VMAT. In this study, we compare the accumulated dose over all fractions in prostate SBRT treatments for non-adaptive and adaptive external beam workflows. Methods: The simulation and daily images of twenty previously treated MRgART prostate SBRT patients were anonymized. On each simulation image, whole prostate VMAT and MRgART SBRT plans were generated. To simulate non-adaptive treatment dose, the daily images were rigidly registered to the planning images, and the doses were recalculated on the daily images. The MRgART plans were adapted to the daily anatomy and reoptimized. All fractional doses were accumulated, using deformable image registration, and compared to their respective planned doses. Results: All MRgART dose accumulations were within clinical tolerance. Four VMAT dose accumulations had a dose constraint that fell outside of clinical tolerance. The VMAT dose accumulations had statistically lower doses to the target compared to their planned doses. Conclusions: While high-quality plans can be delivered in a non-adaptive VMAT workflow despite interfractional motion, this study suggests that MRgART produces cumulative dose distributions that more closely resemble the initial treatment plan. Full article

Background: Achieving facial harmony in patients with micrognathia requires precise chin augmentation. While conventional ready-made implants often fail to conform to unique mandibular surfaces, expensive patient-specific options like PEEK or Titanium lack intraoperative adjustability. We introduce an innovative, cost-effective workflow utilizing 3D-printed templates to fabricate customized Polymethyl Methacrylate (PMMA) implants, emphasizing their clinical feasibility and intraoperative versatility. Methods: We retrospectively analyzed 20 patients with mild-to-moderate micrognathia (<6 mm advancement) who underwent genioplasty between March 2021 and June 2022. Patient-specific templates were produced via Fused Deposition Modeling (FDM) using low-shrinkage Acrylonitrile Butadiene Styrene (ABS) filament. During surgery, final PMMA implants were molded using these sterilized templates. Accuracy was evaluated by comparing mental advancement across preoperative, virtual simulation, and 6-month postoperative stages using Vectra 3D scanning. Results: Quantitative analysis revealed high fidelity between virtual planning and clinical outcomes. The mean discrepancy in horizontal advancement was only 1.02 mm (Planned: 5.04 mm vs. Actual: 4.02 mm). Statistical analysis showed a strong positive correlation (r = 0.928, p = 0.001). Subjective patient satisfaction was high, with 90% reporting “exceptional” or “very improved” results on the Global Aesthetic Improvement Scale (GAIS). Two cases of transient numbness resolved spontaneously within two months. Conclusions: This workflow combines FDM-based template fabrication with intraoperative PMMA molding, enabling real-time adjustment of implant geometry. The results demonstrate a high level of agreement between virtual planning and postoperative outcomes, supporting the clinical reliability of this approach. It may serve as a practical alternative to conventional CAD/CAM methods, particularly in cases requiring both precision and intraoperative flexibility. Full article

Public participation in planning, though a foundational democratic principle, faces persistent implementation challenges across diverse planning systems. This paper examines participatory planning practice in Ireland and Serbia—two countries representing distinct planning traditions (discretionary and conformance-based, respectively) yet confronting shared structural pressures. Through comparative analysis of four local land use planning instruments (the Development Plan and Local Area Plan in Ireland; the Municipal Spatial Plan and General Regulation Plan in Serbia), the study investigates how institutional design and legislative frameworks shape the depth and quality of participatory practice. Methodologically, the research triangulates statutory regulations, public hearing documentation, and non-statutory participation records across two planning scales (county/municipal and local/sub-municipal). A four-dimensional analytical framework—informing, consultation, collaboration, and monitoring—guides the systematic comparison of participatory mechanisms across the selected cases. Findings reveal that, while both systems remain predominantly at the informing and consultation levels, critical differences emerge in how participation is structured and documented in institutional practice. Ireland’s discretionary system enables multi-channel information dissemination, feedback-oriented consultation, and non-statutory collaborative experimentation beyond legal minimums. Serbia’s conformance-based system confines participation largely to statutory procedures, with objection-based consultation and limited collaborative mechanisms, though distinctive features, such as the public hearing session, provide direct opportunities for deliberation absent in the Irish context. The study contributes to European comparative planning scholarship by demonstrating that participatory depth is shaped less by the formal existence of legal provisions than by the interplay between institutional design, procedural arrangements, transparency, and responsiveness. Full article

Objectives: Hidradenitis suppurativa (HS) is a chronic, inflammatory skin disease that significantly impairs patients’ quality of life, especially in its moderate to severe forms. Traditional treatments, including antibiotics, hormonal therapies, and surgery, often fail to provide long-term relief in such cases. This study aims to explore the role of radiotherapy, particularly with the use of 3D printing technology to create personalized boluses and applicators, as an adjunctive treatment for refractory HS. A systematic review of published studies was conducted to assess the efficacy of radiotherapy in managing HS, with a specific focus on studies using 3D printing technology to create customized boluses and applicators. Methods: Publications from databases such as PubMed, Scopus, and Google Scholar were analyzed for studies detailing radiotherapy techniques, dosing regimens, and the use of 3D-printed devices in HS treatment. The studies selected included those employing both external beam radiotherapy and brachytherapy, with particular emphasis on patient outcomes and adverse effects. Results: The reviewed studies highlighted a growing body of evidence supporting the use of radiotherapy for HS, especially in severe or treatment-resistant cases. The use of 3D-printed boluses and applicators in radiotherapy demonstrated significant improvements in treatment precision and patient comfort. Personalized treatment plans allowed for more accurate dose distribution, minimized air gaps, and reduced exposure of healthy tissue. No major long-term toxicity was reported across the majority of studies. Conclusions: Radiotherapy, particularly when combined with 3D printing technology, presents a promising treatment option for patients with severe or refractory HS. Customizable boluses and applicators enhance the precision of radiotherapy by conforming to irregular skin surfaces, thereby improving dose conformity and reducing side effects. Despite the positive results, further research is needed to assess the long-term safety and clinical feasibility of this approach. The integration of 3D printing in radiotherapy could significantly improve treatment outcomes, offering a more personalized and effective therapeutic option for HS patients. Full article