Search Results (9,906)

This paper establishes a graph-theoretic framework for idealization semigroups arising from Bruck–Reilly extensions. Building on a recent study by Wazzan and Ozalan, we introduce five graph families—${\Gamma }_E$, ${\Gamma }_0$, ${\Gamma }_{\mathrm{Cay}}$, ${\Gamma }_{\mathcal{K}}$, and $\Gamma \left(G_k\right)$—each encoding a distinct algebraic facet of $S{B}_i(\bowtie )B$. We prove explicit correspondences linking combinatorial invariants to algebraic structure: diameter captures generating efficiency and semilattice height; girth signals short relations; chromatic number bounds idempotent cardinalities and $\mathcal{D}$-class counts; clique number measures maximal commuting subsets; and Laplacian spectra encode ideal size and Schützenberger groups. Our central result demonstrates that Green’s relations are combinatorially recoverable from graph pairs. For commutative $S{B}_i(\bowtie )B$, $({\Gamma }_E,{\Gamma }_{\mathcal{K}})$ uniquely determines $\mathcal{J}$-order, $\mathcal{D}$-classes, and $\mathcal{H}$-classes via neighborhood inclusions, bipartite components, and automorphism orbits, yielding the first algorithmic reconstruction of ideal-theoretic structure from graph data. The framework is implemented in SageMath as a reproducible open-source toolkit validated on concrete examples. This work synthesizes algebraic graph theory, semigroup theory, and computational mathematics into a unified algebraic-combinatorial dictionary, providing both new analytical tools and a methodological template for studying algebraic constructions via graph invariants. Full article

The objective of this research is to determine whether levels of road accessibility in urban, peri-urban, and sub-urban localities within the municipalities of Mexicali and San Felipe, in Baja California, Mexico, can be associated with processes of territorial expansion, population growth, and changes in urban marginalization levels. This is assessed through a methodology that combines ex-ante and ex-post analysis, the use of the Urban Marginalization Index (UMI) at the AGEB scale, and a hierarchical accessibility classification (Levels A, B, and C), thereby contributing a replicable tool for analyzing socio-spatial impacts derived from road infrastructure. To this end, modernization, maintenance, and reconstruction works, as well as the construction of an interchange carried out between 2006 and 2017 along Federal Highway No. 5—specifically the Mexicali–San Felipe section—were examined in relation to the accessibility they provide to ten nearby localities. UMI values were estimated for 134 AGEB using data from 2000, 2010, and 2020, which enabled the assessment of changes in quality of life before, during, and after the execution of these works. The results show significant population growth in six localities, accompanied by territorial expansion processes. Localities with direct connection to the study corridor tended to exhibit middle to low marginalization levels, while those with indirect accessibility or direct access through another federal highway section tended toward middle to high levels, with some shifting to middle to low. It is concluded that road accessibility constitutes a relevant factor in the progressive improvement in socioeconomic conditions and quality of life in urban, peri-urban, and sub-urban areas. Full article

Sui–Tang Luoyang represents a classic achievement in Chinese capital planning, yet research remains dominated by archaeological and historical–geographical approaches, lacking a unifying theoretical framework. This research addresses this gap by applying the Historic Urban Landscape (HUL) approach to systematically interpret the city’s integration of built form and natural landscape. This research developed a three-dimensional analytical scheme comprising spatial structure, visual axis, and borrowed scenery and implemented it using historical documents, archaeological data, GIS, and cross-validation methods. The results reconstruct the city’s triple spatial structure (Palace City, Imperial City, Outer City) and identify a near-north–south central axis that connects the palace with the Longmen Yique and Mount Mang, forming a dominant view corridor and ritual sequence. Further analysis examines how multi-layered borrowed scenery embodies and articulates the traditional “Harmony of Nature and Humanity” philosophy. This research supports the plausibility of the applicability of HUL to sites with scarce surface remains and provides a transferable framework for the holistic conservation, view-corridor management, and digital reconstruction of historic cities. Full article

Background: Carinal resections remain a challenging and demanding surgical technique for both the patient and medical professionals. The most common indications are adenoid cystic carcinoma and bronchogenic carcinoma. There have been no randomized controlled trials because of the low incidence of pathologic processes suited to carinal resections and the difficulties associated with designing such studies. Methods: The known data are limited to a few single-institutional, retrospective studies over the last several decades. In this review article, we focus on the available data regarding surgical techniques and the types of ventilation that can help in the construction of the anastomosis—the most crucial part of the operation. Important issues regarding carinal resections are discussed in detail. Results: The available literature is reviewed in detail regarding indications, surgical techniques and approaches, types of ventilation, the rates of morbidity and mortality, and 5-year survival. The authors present their experience with two patients, where they utilized ECMO and crossfield ventilation. The role of minimally invasive surgery in carinal resections is also discussed. Conclusions: Carinal resections are complex surgical procedures, but acceptable mortality and morbidity rates can be achieved in carefully selected patients. Excellent cooperation between the surgeon and anesthesiologist is essential in the construction of the anastomosis. Various types of airway management, especially ECMO, help to reduce complication rates and facilitate secure airway reconstruction. Full article

Achieving breakthroughs in key core technologies is an inherent requirement for attaining a high level of scientific and technological self-reliance. The construction of a unified market (market integration construction) reshapes the rules of the innovation system and drives enterprises to tackle key core technologies. Based on the theory of complex adaptive systems, this paper uses the data of China’s A-share listed companies from 2008 to 2023 and the statistical yearbook to study the impact of market integration construction on the key core technological innovation of enterprises and its mechanism. The empirical research results show that: (1) Market integration construction reconstructs the rules governing resource flow, competitive incentives, and collaborative networks, guiding enterprises to achieve the emergence of key core technologies through nonlinear interactions. (2) Market integration construction exerts distinct effects on key core technological innovation by enhancing industrial investment and financial investment. (3) Agile responsiveness positively moderates the relationship between market integration construction and key core technological innovation. (4) The positive impact of market integration construction on key core technological innovation is more pronounced in non-state-owned, follower, and large enterprises. This study provides a theoretical basis and practical insights for advancing market integration construction and tackling key core technologies. Full article

Dynamic phase transition of natural gas hydrates confined within complex pore–throat structures is a key factor impacting the safe and efficient development of hydrate-bearing deposits. In this work, hydrate-bearing samples with varying saturation were first reconstructed with the proposed ice-seeding method using actual marine soil in hydrate-bearing sediments from the South China Sea. Dynamic evolution characteristics of hydrate formation in evolving porous media under different temperature and pressure conditions were analyzed in detail. Combined with high-resolution CT scanning, image processing, pore network extraction, and statistical analysis, the typical microscopic pore–throat structures of hydrate-bearing sediments were revealed, and the presence of nanopores was identified. Furthermore, highly controllable heterogeneous pore–throat structures were constructed for microfluidic chips by integrating stochastic modeling, equivalent modeling, and machine learning approaches. On this basis, a novel microfluidic testing method was developed for investigating the dynamic formation, dissociation, and phase transition characteristics of natural gas hydrates in complex pore structures by controlling the temperature. This study provides reliable data support and theoretical guidance for the productivity prediction of marine hydrate-bearing deposits. Full article

Flood change detection from remote sensing data can be used to identify post-disaster flooded areas, providing decision support for emergency rescue and post-disaster reconstruction. Although the combination of SAR and optical images effectively addresses obscuration by clouds and rain, the inherent difference in their imaging mechanisms poses a challenge to improving the accuracy of flood area change detection. Furthermore, existing flood inundation change detection methods based on heterogeneous remote sensing imagery struggle to distinguish small ground objects within the background from the actual inundated regions. Therefore, a pseudo-Siamese hybrid dilation spiral feature network (PSiam-HDSFNet) is proposed in this paper. Firstly, the feature extraction pipeline progressively processes optical and SAR images through five-layer Enhanced Deep Residual Blocks and five-layer Residual Dense Blocks, respectively. A Hybrid Dilated Pyramid (HDP) module based on a sawtooth wave-like dilated coefficient is designed to enhance multi-scale semantics of deep features in order to selectively reinforce semantic features in flood areas and weaken the noise semantics from small ground objects. Then, a Spiral Feature Pyramid (SFP) module is designed to make the deep features of SAR and optical images more consistent in spatial structure and numerical distribution patterns, so that the features of flood areas become more prominent while the noise semantics from small ground objects are further suppressed. After that, the Galerkin-type attention with linear complexity is introduced to the decoder, rapidly reconstructing the abstract semantic information of floods into interpretable flood features. Finally, the Align OPT-SAR (AlignOS) method is designed to align SAR and optical image features, enabling subsequent flood area detection. Seven metrics are adopted in the comparison between PSiam-HDSFNet and the other 14 methods. The results indicate that PSiam-HDSFNet improves change detection accuracy by extracting and processing depth features of these two images without image domain translation, and its F1 scores are improved by 7.704%, 7.664%, 4.353%, and 1.111% in the four flood coverage categories detection tasks compared to the suboptimum. Full article

Hyperspectral imaging in the long-wave infrared (LWIR) range enables identification of chemical compositions and material properties, but reconstructing 3D models from gimballed pushbroom sensors remains challenging because their unique acquisition geometry is incompatible with conventional photogrammetric software designed for frame cameras. This study presents a workflow for creating explorable 3D models from multi-angle LWIR hyperspectral imagery by co-registering hyperspectral line-scan data with simultaneously acquired RGB frame camera imagery using deep learning-based image matching. The co-registered images are processed in commercial photogrammetric software (Agisoft Metashape), and a texture-to-image mapping algorithm preserves correspondences between 3D model coordinates and original hyperspectral pixels across multiple viewing angles. Quantitative evaluation against reference data demonstrates that co-registration reduces geometric error approaching the accuracy of models built from high-resolution RGB imagery. The resulting models enable the retrieval of 8–50 spectral signatures per surface point, captured from different viewing geometries. This approach facilitates interactive exploration of angular variations in thermal infrared spectra, supporting material identification for non-Lambertian surfaces where single-angle observations may be insufficient for reliable classification. Full article

Manufacturing condition monitoring in low-frequency sensing environments presents significant challenges for traditional anomaly detection methods, which depend on dense temporal observations or instantaneous thresholding. In these contexts, transient fluctuations often overshadow individual measurements, resulting in unstable and unreliable alarm responses. This paper addresses these challenges by framing anomaly monitoring as an alarm-centric decision problem specifically designed for low-frequency manufacturing sensor data. The proposed framework assesses deviations relative to stable idle-state reference values using absolute relative error (ARE), which provides a normalized and dimensionless representation of proportional degradation across diverse sensor features. Alarm decisions are then based on the persistence of threshold exceedances over consecutive idle-state observations, rather than relying on single-sample anomalies. By distinctly separating deviation modeling from alarm decision-making, the framework facilitates stable and interpretable alarm generation without depending on waveform reconstruction or parametric distribution assumptions. Validation of the framework is conducted using real industrial monitoring data under controlled fault-simulation conditions. The results indicate that persistence-based decision logic significantly enhances alarm reliability for both absolute and squared deviation baselines, while the ARE-based deviation yields superior discrimination for sustained proportional degradation. By combining ARE-based deviation modeling with persistence-based alarm decision logic, the proposed ARE-based persistence strategy achieves the highest reliability in alarm behavior among all methods compared, demonstrating its efficacy for low-frequency manufacturing monitoring. Full article

The onshore southern Lake Albert Rift Basin in Uganda represents a geologically complex and hydrocarbon-prone segment of the western branch of the East African Rift System. This study integrates seismic, well and geochemical data, and 2D Basin and Petroleum Systems modeling to reconstruct the petroleum system of the basin. Results highlight spatial variations in source rock maturity and indicate a predominantly oil-prone character. Migration modeling reveals hydrocarbon expulsion and vertical migration into both the overlying Middle—late Miocene Kakara and underlying early Miocene Kisegi sandstone reservoirs, facilitated by fault-controlled pathways. The late Miocene—early Pliocene Oluka Formation proves to be an effective regional seal, supported by its low modeled porosity, while overpressure zones enhance migration and accumulation efficiency. Present-day thermal maturity profiles and porosity–depth relationships indicate favorable conditions for hydrocarbon generation, migration, and preservation. These findings redefine our understanding of petroleum system dynamics in the Albert Rift and underscore the exploration potential of underexplored structural and stratigraphic traps in the southern sector of this rift and analogous rift settings. Full article

Background/Objectives: The Mitrofanoff appendicovesicostomy (MAV) is the gold standard for creating a continent catheterizable channel in children unable to perform clean intermittent catheterization (CIC) through the native urethra. Minimally invasive surgery has progressively replaced open techniques in pediatric urology, offering improved recovery and favorable cosmetic outcomes, and robotic-assisted Mitrofanoff has gained popularity in recent years. However, the high costs and limited availability of robotic systems create disparities in access to pediatric urologic reconstruction, particularly in low- and middle-income countries. In this context, the laparoscopic Mitrofanoff (MAV-L) and the laparoscopic-assisted Mitrofanoff (MAV-LA) represent practical, cost-effective alternatives, valuable in institutions without robotic platforms or in resource-limited settings. Recent evidence demonstrates that advanced laparoscopic approaches remain feasible even for complex urological procedures, supporting their continued relevance in the robotic era. Methods: We conducted a retrospective case series including seven male children (aged 9–12 years) who underwent MAV between 2018 and 2023. Peri-operative data included demographics, operative time, length of hospitalization, and complications. Functional and aesthetic outcomes were assessed during long-term follow-up. Statistical analysis accounted for the small sample size by using non-parametric tests where appropriate. Results: Three patients (43%) underwent MAV-L and four (57%) MAV-LA. Mean operative time appeared longer in MAV-L (273.3 ± 20.5 min) than in MAV-LA (203.8 ± 24.3 min; exploratory p = 0.019). Hospital stay was 9 ± 0.8 days vs. 7.5 ± 0.5 days (p = 0.026). During follow-up (43.3 ± 10.9 vs. 26.3 ± 5.4 months; p = 0.034), two complications occurred, both in the MAV-L group (stomal stenosis and channel leakage). All patients reported excellent continence, ease of catheterization, and high cosmetic satisfaction. Conclusions: Both laparoscopic and laparoscopic-assisted Mitrofanoff techniques are safe, feasible, and effective in children. Favorable cosmetic satisfaction was reported in the fully laparoscopic subgroup, based on subjective assessment. Importantly, these laparoscopic techniques are sustainable alternatives to robotic surgery, offering accessibility and high-quality reconstructive care even in centers with limited financial and technological resources. Full article

Aortic arch diseases represent one of the most complex domains in cardiovascular surgery due to the need for cerebral protection, anatomical precision, and durable reconstruction. Their management requires highly individualized strategies that balance cerebral protection, systemic organ perfusion, anatomical complexity, and long-term durability. Over recent decades, antegrade cerebral perfusion has significantly reduced neurological morbidity. In parallel, vascular prostheses have progressed from conventional Dacron grafts to hybrid stent graft systems simplifying arch reconstruction and expanded treatment options in high-risk cohorts. Total endovascular arch repair using branched or fenestrated devices has emerged for selected high-risk patients; however, current data remain limited, with early stroke rates of approximately 5–8% and restricted long-term durability evidence. From both clinical and economic perspectives, open and hybrid approaches remain central to durable arch management. Full article

Background/Objectives: Autism spectrum disorder (ASD) is biologically heterogeneous, and immune-linked variation may be associated with differences in tryptophan–kynurenine pathway (KP) metabolism. Here, we report a targeted urinary profile of KP metabolites, NAD (nicotinamide adenine dinucleotide), and neopterin in a Bulgarian pediatric ASD cohort to describe within-cohort patterns and associations. Methods: Second-morning, acid-stabilized spot urine was collected from 73 children with ASD in Bulgaria (3–13 years; 57 males; 16 females). No contemporaneous neurotypical control group was enrolled; therefore, laboratory-provided reference limits are reported only as contextual benchmarks and are not interpreted as ASD-specific abnormalities. Tryptophan (TRP), kynurenine (KYN), kynurenic acid (KYNA), 3-hydroxykynurenine (3-HK), quinolinic acid (QUIN), NAD, and neopterin were quantified and derived indices were computed (KYN/TRP × 1000; QUIN/KYNA). Non-parametric statistics, Benjamini–Hochberg false discovery rate (FDR) correction, and Spearman correlation analyses were applied. Results: Neopterin was strongly associated with QUIN and KYN in creatinine-normalized data (QUIN: ρ = 0.59, q36 = 2.64 × 10⁻⁷; KYN: ρ = 0.54, q36 = 3.69 × 10⁻⁶); these associations persisted when reconstructed as absolute concentrations (e.g., QUIN_abs: ρ = 0.68, q36 = 2.69 × 10⁻¹⁰) and after partial Spearman correlation controlling for spot creatinine (partial ρ = 0.46, q = 2.52 × 10⁻⁴). One NAD value was <LOQ and was imputed as ½LOQ; sensitivity analyses did not materially change inference. Conclusions: In this ASD-only cross-sectional dataset, urinary neopterin levels co-varied with urinary KYN and QUIN and with KP indices. Clinical interpretation and causal inference require controlled and longitudinal studies with richer covariate capture. Full article

Background and Clinical Significance: Traumatic brain injuries (TBI), most frequently caused by falls, represent a major source of morbidity and mortality and pose significant challenges in forensic investigations, especially when events are unwitnessed or testimonies conflict. Despite advances in imaging and autopsy, reconstructing the mechanism of head trauma often remains impossible. The objective of this study is to assess how biomechanical modeling can support forensic practitioners by narrowing the range of plausible scenarios and strengthening evidence-based interpretation in complex medico-legal contexts, without seeking to establish legal causality or certainty. Case Presentation: This case report investigates forensic biomechanics as a decision-support tool using a combined multibody and finite element (FE) modeling approach. An initial set of twenty-five scenarios, derived from witness statements and investigative data, was reconstructed to simulate potential fall- and assault-related mechanisms. Multibody simulations with the human facet model were first performed to estimate head impact velocities and orientations. These parameters were then applied to an FE head model to evaluate tissue response. Conclusions: Skull fracture patterns and intracerebral von Mises stress distributions were analyzed and systematically compared with clinical, radiological, and autopsy findings. Although simulated stress magnitudes were generally lower than injury thresholds reported in the literature, several scenarios reproduced fracture propagation and intracerebral stress patterns consistent with the documented lesions, including corpus callosum involvement. This multidisciplinary approach highlights the growing role of biomechanics in forensic investigations and forensic anthropology. Full article

Objectives: To assess the diagnostic accuracy of a deep learning (DL)-based algorithm for non-invasive computation of fractional flow reserve (FFR-CT) from coronary computed tomography angiography (CCTA) and to evaluate the model’s ability to automatically assign cardiovascular risk categories according to the Coronary Artery Disease–Reporting and Data System (CAD-RADS). Materials and Methods: Sixty patients with suspected coronary artery disease who underwent both CCTA and invasive coronary angiography (ICA) were retrospectively included in this multicenter study. Curved multiplanar reconstructions derived from CCTA were analyzed by the deep learning-based model to estimate FFR-CT values and to automatically assign CAD-RADS risk categories. The diagnostic performance of the software for the identification of hemodynamically significant coronary stenoses was evaluated using ICA as the reference standard. Receiver operating characteristic (ROC) curve analysis was performed to determine the area under the curve (AUC), sensitivity, and specificity on both a per-patient and per-vessel basis. Finally, agreement between CAD-RADS risk categories assigned by the DL algorithm and those determined by an expert radiologist was assessed. Results: FFR-CT demonstrated high diagnostic accuracy, with AUC of 0.935, sensitivity of 93.2%, specificity of 93.7%, and excellent agreement with reference standard (k = 0.836) on a per-patient level. Per-vessel diagnostic performance was consistently high across all major coronary arteries, with the left anterior descending artery (LAD) showing the highest accuracy (AUC = 0.932). Automated CAD-RADS classifications generated by the software showed good agreement with those assigned by human (k = 0.765). Conclusions: The DL-based model demonstrated high diagnostic accuracy and represents a promising noninvasive approach for ischemia assessment and cardiovascular risk stratification. Full article