Search Results (1,062)

Vascularised composite allotransplantation (VCA) has an evolving role in the reconstruction of complex functional and aesthetic deficits non-amenable to autologous or implant-based reconstructive modalities. International applications of VCA span upper extremity, face, abdominal wall, uterus, and penile transplantation, with more than 300 procedures performed worldwide. Among these, abdominal wall transplantation has uniquely contributed to the development of the sentinel skin flap (SSF) concept, in which solid organ transplant patients undergo simultaneous transplantation of a solid organ and a donor-derived vascularised skin flap, with the skin component of the SSF being trialled internationally as a means of monitoring for rejection within the solid organ allograft. Despite growing clinical success, VCA continues to face substantial barriers to wider adoption. Acute rejection remains highly prevalent, affecting up to 89% of recipients, with significant morbidity linked to intensive systemic immunosuppression. Challenges are further amplified by the unique immunological heterogeneity of composite grafts, ethical concerns surrounding identity-linked tissues, and the lack of standardised outcomes reporting across VCA subtypes. Advances in machine perfusion technologies and emerging cellular and biomaterial-based immunomodulation strategies show promise in reducing immunosuppression burden and improving graft longevity. This review outlines the current state of VCA, including clinical applications, outcomes, and mechanistic insights from pre-clinical studies, while highlighting key ethical considerations and evolving regulatory frameworks. Future progress will depend on standardised reporting systems, improved donor–recipient matching, better understanding of ischemia–reperfusion injury, and the development of next-generation immunosuppressive/immuno-modulatory therapies. Collectively, these innovations position VCA as a rapidly advancing field with significant potential to redefine reconstructive and transplant surgery. Full article

This paper analyses the role of landscape as a fundamental dimension of post-earthquake recovery in the inland areas of Central Italy, arguing that reconstruction must be understood not only as the repair of damaged buildings but as a broader territorial process affecting identity, spatial organization, and long-term settlement trajectories. In this sense, post-earthquake recovery is also interpreted as a strategic opportunity to reinforce coast–inland relationships, acknowledging the structural interdependence between inland Apennine areas and coastal urban systems. Drawing on insights from applied research conducted in the L’Aquila 2009 crater and on the conceptual framework developed within the PRIN TRIALS project, the paper discusses how seismic events accelerate pre-existing territorial dynamics and produce enduring transformations, particularly in the proximity landscapes surrounding historic centres. Rather than presenting empirical findings, the contribution offers a theoretical and operational framework aimed at integrating landscape considerations into reconstruction processes. It outlines key concepts such as landscape quality, transformative resilience, and permanent temporariness; reviews critical normative aspects linked to emergency procedures; and proposes a set of landscape-oriented guidelines and criteria for the contextual integration of reconstruction projects. These include landscape quality objectives, multiscalar readings of identity values, and operational tools such as visual-impact assessment, Project Reference Context analysis, and principles for managing transformations in peri-urban and historic environments. Overall, the paper argues that adopting a landscape-based perspective can strengthen territorial cohesion, support the sustainable redevelopment of historic centres and their surroundings, and embed post-earthquake reconstruction within broader coast–inland territorial strategies aimed at long-term resilience and balanced regional development in Apennine communities. Full article

Background/Objectives: Bilateral Achilles tendon ruptures are exceptionally rare, accounting for <1% of Achilles injuries; chronic presentations are frequently linked to diagnostic delay in the acute phase. The aim of this paper is to describe a modified, single-stage bilateral reconstruction of neglected Achilles tendon ruptures using Flexor Digitorum Longus (FDL) transfer and turndown flaps. This study evaluates 12-month functional and radiological outcomes while comparing this surgical strategy with current literature. Methods: A 58-year-old man with rheumatoid arthritis on long-term corticosteroids presented 4 months after asynchronous bilateral Achilles ruptures with progressive weakness and gait limitation. Clinical examination and MRI confirmed chronic discontinuity with retracted stumps and interstump gaps of ~6.5–7.0 cm. Intervention: After pre-operative tapering of corticosteroids, a single-stage bilateral reconstruction was performed. Surgical intervention involved simultaneous bilateral reconstruction using flexor digitorum longus (FDL) transfer for one tendon and a combination of FDL and flexor hallucis longus (FHL) transfers for the other, with bilateral turndown flap augmentation. Decisions regarding tendon transfers were based on intraoperative findings, with the FDL selected for its larger caliber when the FHL was deemed insufficient. Results: Recovery was uneventful. At 6 months, the patient resumed full-time work and could perform repeated tiptoe rises. The AOFAS ankle-hindfoot score improved from 46 pre-operatively to 85. At 12 months, MRI demonstrated bilateral tendon continuity without re-rupture, with hypertrophy at the reconstructed stumps. Conclusions: In chronic, large-gap bilateral Achilles ruptures with systemic risk factors, single-stage reconstruction using FDL (with or without FHL) plus turndown augmentation is feasible and yields favorable functional recovery. Careful tensioning, secure calcaneal fixation, steroid optimization, and structured rehabilitation appear pivotal to outcomes. This case supports the applicability of this strategy in complex bilateral presentations. Full article

The geometric precision of ballastless tracks critically determines the performance and safety of high-speed railways. Traditional manual fine adjustment methods remain labor-intensive, iterative, and sensitive to human expertise, making it difficult to achieve sub-millimeter accuracy and global consistency. To address these challenges, this paper proposes a virtual-model–enabled pre-adjustment framework for high-speed ballastless track construction. The framework integrates a dual-frame SLAM-based and multi-sensor measurement system based on RC-SLAM principles and a local attitude compensation model, enabling accurate 3D mapping and reconstruction of long-track segments under extended-range and GNSS-denied conditions typical of linear infrastructure scenarios. A constraint-based global optimization algorithm is further developed to transform empirical fine adjustment into a computable geometric control problem, generating executable adjustment configurations with engineering feasibility. Field validation on a 1 km railway section demonstrates that the proposed method achieves sub-millimeter measurement accuracy, improves adjustment efficiency by over eight times compared with manual operations, and reduces material waste by $2800–$7000 per kilometer. This paper demonstrates a previously unexplored execution-level workflow for long-rail fine adjustment, establishing a closed-loop paradigm from measurement to predictive optimization and paving the way for SLAM-driven, simulation-based, and multi-sensor–integrated precision control in next-generation railway construction. Full article

Three-dimensional (3D) reconstruction of ultrasound (US) images represents a novel advancement that has been extensively explored over the past three decades. This technique enables endoscopists to perform more detailed and enhanced visualizations of anatomical structures, which is not feasible using traditional ultrasound methods. The reconstructed images also facilitate navigation during endoscopy-guided procedures, such as fine-needle aspiration. Furthermore, augmented reality (AR) algorithms can overlay the reconstructed images with real-time anatomical images, thereby enhancing clinician performance during these procedures. Current evidence suggests that 3D ultrasound reconstruction has already been widely implemented in various clinical imaging studies. However, its application for generating procedural guidance and augmented reality overlays remains in the early research stages and has not yet achieved widespread adoption. Existing pre-clinical evidence suggests that 3D reconstruction has significant potential to enhance clinician performance in various ultrasound-guided procedures. Full article

This paper presents a controller-hardware-in-the-loop simulation (C-HILS) framework for validating models, evaluating control performance, and assessing the thermal lifetime of a tens-of-kilowatt inverter. The real inverter and the C-HILS platform were operated in parallel, and accuracy was quantified using phase-current root mean square error, voltage spectral analysis, and total harmonic distortion (THD). Across a wide range of SVPWM and DPWM cases, deviations remained within 2–5%, confirming close agreement between experiment and simulation. Using the validated C-HILS system, sampling frequency and output power were swept while comparing current tracking, THD, average switching frequency, semiconductor losses, and efficiency. SVPWM achieved lower THD, whereas DPWM reduced average switching frequency and switching losses, improving efficiency. C-HILS waveforms were then applied to a Foster thermal network to reconstruct the junction–temperature trajectory; $T_{\mathrm{j}}\left(t\right)$, and $\mathsf{\Delta }{T}_{\mathrm{j}}$ and $T_{\mathrm{j},\mathrm{m}\mathrm{i}\mathrm{n}}$ were mapped to lifetime using the Bayerer model. For a representative cyclic mission, $\mathsf{\Delta }{T}_{\mathrm{j}}$ decreased from approximately $25.6 °\mathrm{C}$ with SVPWM to about $17.5 °\mathrm{C}$ with DPWM, increasing the estimated lifetime from approximately 1.36 years to 9.14 years. These results demonstrate that the proposed C-HILS framework provides a unified pre-prototype tool for model verification, control strategy comparison, and quantitative thermal reliability assessment of shipboard propulsion inverters. Full article

Massive MIMO systems can substantially enhance spectral efficiency, but such gains rely on the availability of accurate channel state information (CSI). However, the increase in the number of antennas leads to a significant growth in feedback overhead, while conventional deep-learning-based CSI feedback methods also impose a substantial computational burden on the user equipment (UE). To address these challenges, this paper proposes LLM4FB, a one-sided CSI feedback framework that leverages a pre-trained large language model (LLM). In this framework, the UE performs only low-complexity linear projections to compress CSI. In contrast, the BS leverages a pre-trained LLM to accurately reconstruct and predict CSI. By utilizing the powerful modeling capabilities of the pre-trained LLM, only a small portion of the parameters needs to be fine-tuned to improve CSI recovery accuracy with low training cost. Furthermore, a multiobjective loss function is designed to simultaneously optimize normalized mean square error (NMSE) and spectral efficiency (SE). Simulation results show that LLM4FB outperforms existing methods across various compression ratios and mobility levels, achieving high-precision CSI feedback with minimal computational capability from terminal devices. Therefore, LLM4FB presents a highly promising solution for next-generation wireless sensor networks and industrial IoT applications, where terminal devices are often strictly constrained by energy and hardware resources. Full article

To address the limitation of 2D methods in inferring absolute scrap dimensions from images, we propose Scrap-SAM-CLIP (SSC), a vision-language model integrating the segment anything model (SAM) and contrastive language-image pre-training in Chinese (CN-CLIP). The model enables identification of canonical scrap shapes, establishing a foundational framework for subsequent 3D reconstruction and dimensional extraction within the 3D recognition pipeline. Individual modules of SSC are fine-tuned on the self-constructed scrap dataset. For segmentation, the combined box-and-point prompt yields optimal performance among various prompting strategies. MobileSAM and SAM-HQ-Tiny serve as effective lightweight alternatives for edge deployment. Fine-tuning the SAM decoder significantly enhances robustness under noisy prompts, improving accuracy by at least 5.55% with a five-positive-points prompt and up to 15.00% with a five-positive-points-and-five-negative-points prompt. In classification, SSC achieves 95.3% accuracy, outperforming Swin Transformer V2_base by 2.9%, with t-SNE visualizations confirming superior feature learning capability. The performance advantages of SSC stem from its modular assembly strategy, enabling component-specific optimization through subtask decoupling and enhancing system interpretability. This work refines the scrap 3D identification pipeline and demonstrates the efficacy of adapted foundation models in industrial vision systems. Full article

Determining long-term changes in global ice and water storage from satellite gravimetry remains challenging due to the limited temporal coverage of high-resolution missions. Here, we combine Satellite Laser Ranging (SLR) and Gravity Recovery and Climate Experiment (GRACE) data to reconstruct large-scale, non-linear mass variations from 1995 to 2024, extending gravity-based observations into the pre-GRACE era while preserving spatial detail through backward extrapolation. The combined model reveals widespread and statistically significant accelerations in global water and ice mass changes and enables the identification of key turning points in their temporal evolution. Results indicate that in Svalbard, a non-linear transition in ice mass balance occurred in late 2004, followed by a pronounced acceleration of mass loss due to climate warming. Glaciers in the Gulf of Alaska exhibit persistent mass loss with a marked intensification after 2012, while in the Antarctic Peninsula, ice mass loss substantially slowed and a potential trend reversal emerged around 2021. The reconstructed mass anomalies show strong consistency with independent satellite altimetry and climate indicators, including a clear response to the 1997/1998 El Niño event prior to the GRACE mission. These findings demonstrate that integrating SLR with GRACE enables robust detection of non-linear, climate-driven mass redistribution on a global scale and provides a physically consistent extension of satellite gravimetry records beyond the GRACE era. Full article

The inherent semantic symmetry and cross-modal alignment between textual prompts and generated images have fueled the success of text-to-image (T2I) generation. However, this strong correlation also introduces security vulnerabilities, specifically prompt stealing attacks, where valuable prompts are reverse-engineered from images. In this paper, we address the challenge of information asymmetry in black-box attack scenarios and propose PromptTrace, a fine-grained prompt stealing framework via Contrastive Language-Image Pre-training (CLIP)-guidedbeam search. Unlike existing methods that rely on single-stage generation, PromptTrace structurally decomposes prompt reconstruction into subject generation, modifier extraction, and iterative search optimization to effectively restore the visual–textual correspondence. By leveraging a CLIP-guided beam search strategy, our method progressively optimizes candidate prompts based on image–text similarity feedback, ensuring the stolen prompt achieves high fidelity in both semantic intent and stylistic representation. Extensive evaluations across multiple datasets and T2I models demonstrate that PromptTrace outperforms existing methods, highlighting the feasibility of exploiting cross-modal symmetry for attacks and underscoring the urgent need for defense mechanisms in the T2I ecosystem. Full article

Background and Clinical Significance: Focal hemorrhagic severity associated with posterior convexity pial brain arteriovenous malformation (AVM) cases can be exacerbated by hemodynamic stress focusing on focal areas of architectural weakness and by superficial venous outflow being restricted by non-redundant superficial venous drainage. This clinical case report exemplifies how bedside neurologic localization and angioarchitectural characteristics can inform the selection of microsurgical approaches for the treatment of ruptured AVMs that are directed at reducing hemorrhage recurrence risk through corridors based on rupture location. Case Presentation: An otherwise healthy young adult male (modified Rankin scale [mRS] pre-morbid = 0) initially presented with a thunderclap headache, emesis, photophobia, decreased level of consciousness (admitted Glasgow Coma Score [GCS] = 11; E3V3M5), and subsequent deficits including left-sided pyramidal weakness, visual field loss, and visuo-spatial neglect. A non-contrast computed tomogram (CT) confirmed an intraparenchymal hemorrhage (ICH) located within the right hemisphere’s posterior lobe. Angiographic evaluation of this AVM with catheter injection and three-dimensional reconstruction revealed a compact right occipital posterior convexity pial AVM (nidus 8 × 3 mm) supplied by distal cortical branches of the right middle cerebral artery (MCA); all blood draining from the nidus was directed to a single cortical vein which then drained into the superior sagittal sinus; there were two additional intranidal saccular aneurysms (approximately 3 × 2 mm and 3 × 3 mm). Because of the acute worsening secondary to ICH and because all venous drainage was superficial-only, a single-stage approach was selected given the urgency: decompressive evacuation of the hematoma via a corridor to the site of the AVM, followed by microsurgical removal of the AVM. The removal of the AVM was accomplished in a feeder-first, vein-last sequence, and en-passage arteries and parasagittal bridging veins were preserved throughout the procedure. Additionally, the two intranidal aneurysms identified as potential weak points during progressive devascularization of the AVM were specifically treated during the removal procedure. Following the successful removal of the AVM, the patient experienced a rapid recovery and returned to a nearly premorbid state of functioning, excepting a persistent small area of quadrantanopia. Conclusions: Rupture of posterior convexity AVMs may result in increased hemorrhagic severity due to localized architectural weaknesses in addition to the overall size of the AVM nidus. By correlating neurological findings, the topography of the hemorrhage, and angioarchitectural features early after rupture, emergency decisions regarding management can be better informed. The application of a hematoma-corridor, feeder-first/vein-last microsurgical approach for the treatment of such AVMs can achieve definitive curative results while minimizing damage to posterior cortical regions. Full article

Based on GRACE RL06 data, this study reconstructs a monthly Terrestrial Water Storage Anomaly (TWSA) series in Shandong Province (2003–2024) using Singular Spectrum Analysis (SSA) and derives Groundwater Storage Anomaly (GWSA) via the water balance equation. The spatiotemporal evolution characteristics of GWSA were systematically examined, and the relative contributions of climatic factors and human activities to groundwater storage changes were quantitatively assessed, with the aim of contributing to the development, utilization, and protection of groundwater in Shandong Province. The results indicate that temporally, GWSA in Shandong Province exhibited a statistically significant decreasing trend at a rate of −8.45 mm/a (p < 0.01). The maximum GWSA value of 17.15 mm was recorded in 2006, while the Mann–Kendall abrupt change-point analysis identified 2013 as a significant transition point. Following this abrupt change, GWSA demonstrated a persistent decline, reaching the minimum annual average of −225.78 mm in 2020. Although moderate recovery was observed after 2020, GWSA values remained substantially lower than those in the pre-abrupt change period. Seasonal analysis revealed a distinct “higher in autumn and lower in spring” pattern, with the most pronounced fluctuations occurring in summer and the most stable conditions in winter. Spatially, approximately 99.1% of the study area showed significant decreasing trends, displaying a clear east–west gradient with more severe depletion in inland regions compared to relatively stable coastal areas. Crucially, human activities emerged as the dominant driving factor, with an average contribution rate of 86.11% during 2003–2024. The areal proportion where human activities served as the decisive factor (contribution rate > 80%) increased dramatically to 99.58%. Furthermore, the impact of human activities demonstrated bidirectional characteristics, transitioning from negative influences during the depletion phase to positive contributions promoting groundwater recovery in recent years. At present, the GWSA in Shandong Province is expected to continue declining in the future, with an overall downward trend. Countermeasures must be implemented promptly. Full article

This study addresses the issues of sparse observations from buoys in the tropical Indian Ocean and systematic biases in reanalysis products by proposing a daily-mean wind speed reconstruction framework that integrates multi-source meteorological fields. This study also considers the impact of different source domains on model pre-training, with the goal of providing reliable data support for wind energy assessment. The model was pre-trained using data from the Americas and tropical Pacific buoys as the source domain and then fine-tuned on Indian Ocean buoys as the target domain. Using annual leave-one-out cross-validation, we evaluated the model’s performance against uncorrected ERA5 and CCMP data while comparing three deep reconstruction models. The results demonstrate that deep models significantly reduce reanalysis bias: the RMSE decreases from approximately 1.00 m/s to 0.88 m/s, while R² improves by approximately 8.9% and 7.1% compared to ERA5/CCMP, respectively. The Branch CNN–Transformer outperforms standalone LSTM or CNN models in overall accuracy and interpretability, with transfer learning yielding directional gains for specific wind conditions in complex topography and monsoon zones. The 20-year wind energy data reconstructed using this model indicates wind energy densities 60–150 W/m² higher than in the reanalysis data in open high-wind zones such as the southern Arabian Sea and the Somali coast. This study not only provides a pathway for constructing high-precision wind speed databases for tropical Indian Ocean wind resource assessment but also offers precise quantitative support for delineating priority development zones for offshore wind farms and mitigating near-shore engineering risks. Full article

Japanese modern irrigation management is considered a successful model of water governance worldwide. However, debates continue over whether this success is due to natural water abundance or to water management practices. This study evaluates pre-modern water scarcity risk for six irrigation schemes, developed during that period in the Kinu River Basin (1603–1868); a period without large reservoirs, canal systems, or modern regulatory technologies. As the methodology, pre-modern river flows were reconstructed by removing the effects of four modern dams from the present-day river discharge, adjusting the conveyance efficiency, changes in paddy field area, rainfall input, and return flows. Water demand was assessed using Japanese irrigation standards of 5 mm/d (minimum water demand corresponding to evapotranspiration) and 20 mm/d (easy management), and risk was evaluated under both the prior appropriation and Equal Water Distribution rules. Results show that modern flow in the dry season is approximately 25 m³/s, whereas reconstructed natural flow during drought years declines to 10–18 m³/s, and about 15 m³/s after rainfall adjustment. Under the 20 mm/d demand scenario, scarcity occurred in four schemes (2 of 17 years in the third scheme and 7 of 17 years for the sixth scheme), while no scarcity occurred under the minimum-demand scenario (5 mm/d), even during low-flow conditions. This indicates that the available water in these schemes was at a level where drought damage could occur under extensive irrigation management, but could be avoided by intensive irrigation management to supply the minimum necessary water to all paddy fields. Full article

This study proposes an automated system using deep learning-based object detection to identify implant systems, leveraging recent progress in self-supervised learning, specifically masked image modeling (MIM). We advocate for self-pre-training, emphasizing that its advantages when acquiring suitable pre-training data is challenging. The proposed Masked Deep Embedding (MDE) pre-training method, extending the masked autoencoder (MAE) transformer, significantly enhances dental implant detection performance compared to baselines. Specifically, the proposed method achieves a best detection performance of AP = 96.1, outperforming supervised ViT and MAE baselines by up to +2.9 AP. In addition, we address the absence of a comprehensive dataset for implant design, enhancing an existing dataset under dental expert supervision. This augmentation includes annotations for implant design, such as coronal, middle, and apical parts, resulting in a unique Implant Design Dataset (IDD). The contributions encompass employing self-supervised learning for limited dental radiograph data, replacing MAE’s patch reconstruction with patch embeddings, achieving substantial performance improvement in implant detection, and expanding possibilities through the labeling of implant design. This study paves the way for AI-driven solutions in implant dentistry, providing valuable tools for dentists and patients facing implant-related challenges. Full article