Search Results (2,589)

In 2071, the Hydraulic community will commemorate the second centenary of the Baré de Saint-Venant equations, also known as the Shallow Water Equations (SWE). These equations are fundamental to the study of open-channel flow. As non-linear partial differential equations, their solutions were largely unattainable until the development of computers and numerical methods. Following 1960, various numerical schemes emerged, with Preissmann’s scheme becoming the most widely employed in many software applications. In the 1990s, some researchers identified a significant limitation in existing software and codes: the inability to simulate transcritical flow. At that time, Preissmann’s scheme was the dominant method employed in hydraulics tools, leading the research community to conclude that this scheme could not handle transcritical flow due to suspected instability. In response to this concern, several researchers suggested modifications to Preissmann’s scheme to enable the simulation of transcritical flow. This paper will demonstrate that these accusations against the Preissmann scheme are unfounded and that the proposed improvements are unnecessary. The observed instability is not due to the numerical method itself, but rather a mathematical instability inherent to the SWE, which can lead to ill-posed conditions if a specific derived condition is not met. In the context of a friction slope formula based on Manning or Chézy types, the condition for ill-posedness of the 1D shallow water equations simplifies to the Vedernikov number condition, which is necessary for roll waves to develop in uniform flow. This derived condition is also relevant for the formation of roll waves in unsteady flow when the 1D shallow water equations become ill-posed. Full article

The Korteweg–de Vries (KdV) equation is a nonlinear evolution equation that reflects a wide variety of dispersive wave occurrences with limited amplitude. It has also been used to describe a range of major physical phenomena, such as shallow water waves that interact weakly and nonlinearly, acoustic waves on a crystal lattice, lengthy internal waves in density-graded oceans, and ion acoustic waves in plasma. The KdV equation is one of the most well-known soliton models, and it provides a good platform for further research into other equations. The KdV equation has several forms. The aim of this study is to introduce and investigate a (2+1)-dimensional generalized fifth-order KdV equation with power law nonlinearity (gFKdVp). The research methodology employed is the Lie group analysis. Using the point symmetries of the gFKdVp equation, we transform this equation into several nonlinear ordinary differential equations (ODEs), which we solve by employing different strategies that include Kudryashov’s method, the $(G^{\prime }/G)$ expansion method, and the power series expansion method. To demonstrate the physical behavior of the equation, 3D, density, and 2D graphs of the obtained solutions are presented. Finally, utilizing the multiplier technique and Ibragimov’s method, we derive conserved vectors of the gFKdVp equation. These include the conservation of energy and momentum. Thus, the major conclusion of the study is that analytic solutions and conservation laws of the gFKdVp equation are determined. Full article

In this study, we focus on solving the nonlinear time-fractional Hirota–Satsuma coupled Korteweg–de Vries (KdV) and modified Korteweg–de Vries (MKdV) equations, using the Yang transform iterative method (YTIM). This method combines the Yang transform with a new iterative scheme to construct reliable and efficient solutions. Readers can understand the procedures clearly, since the implementation of Yang transform directly transforms fractional derivative sections into algebraic terms in the given problems. The new iterative scheme is applied to generate series solutions for the provided problems. The fractional derivatives are considered in the Caputo sense. To validate the proposed approach, two numerical examples are analysed and compared with exact solutions, as well as with the results obtained from the fractional reduced differential transform method (FRDTM) and the q-homotopy analysis transform method (q-HATM). The comparisons, presented through both tables and graphical illustrations, confirm the enhanced accuracy and reliability of the proposed method. Moreover, the effect of varying the fractional order is explored, demonstrating convergence of the solution as the order approaches an integer value. Importantly, the time-fractional Hirota–Satsuma coupled KdV and modified Korteweg–de Vries (MKdV) equations investigated in this work are not only of theoretical and computational interest but also possess significant implications for achieving global sustainability goals. Specifically, these equations contribute to the Sustainable Development Goal (SDG) “Life Below Water” by offering advanced modelling capabilities for understanding wave propagation and ocean dynamics, thus supporting marine ecosystem research and management. It is also relevant to SDG “Climate Action” as it aids in the simulation of environmental phenomena crucial to climate change analysis and mitigation. Additionally, the development and application of innovative mathematical modelling techniques align with “Industry, Innovation, and Infrastructure” promoting advanced computational tools for use in ocean engineering, environmental monitoring, and other infrastructure-related domains. Therefore, the proposed method not only advances mathematical and numerical analysis but also fosters interdisciplinary contributions toward sustainable development. Full article

In response to the low efficiency of collaborative processing of sewing machine cases at the part level in network collaborative manufacturing, this paper proposes a sewing machine cases manufacturing service composition optimization method based on an improved multi-objective artificial hummingbird algorithm. The structure and production process of sewing machine cases are analyzed; a framework for service composition optimization in the sewing machine cases manufacturing service platform is established; the required manufacturing resource service composition is determined; and a dual-objective service composition optimization mathematical model that considers Quality of Service (QoS) indicators and flexibility indicators is constructed. Opposition-based learning strategies, roulette wheel selection strategies, and improved differential evolution strategies are embedded in the multi-objective artificial hummingbird algorithm, and the improved artificial hummingbird algorithm (ORAHA_DE) is used to solve the sewing machine cases manufacturing service composition optimization model. The experimental results show the effectiveness and superiority of this composition optimization method in solving the sewing machine cases manufacturing composition optimization problem while avoiding entrapment in a local optimum during the solution process, thereby achieving the composition optimization of sewing machine cases collaborative manufacturing services. Full article

The intelligent upgrade of heating systems faces the challenge of accurately identifying high-dimensional pipe-network resistance coefficients; difficulties in accomplishing this can lead to hydraulic imbalance and redundant energy consumption. To address the limitations of traditional Differential Evolution (DE) algorithms under high-dimensional operating conditions, this paper proposes an Improved Differential Evolution Algorithm (SDEIA) incorporating chaotic mapping, adaptive mutation and crossover strategies, and an immune mechanism. Furthermore, a multi-constrained identification model is constructed based on Kirchhoff’s laws. Validation with actual engineering data demonstrates that the proposed method achieves a lower average relative error in resistance coefficients and exhibits a more concentrated error distribution. SDEIA provides a high-precision tool for multi-heat-source networking and dynamic regulation in heating systems, facilitating low-carbon and intelligent upgrades. Full article

Differential equations need boundary conditions (BCs) for their solution. It is widely acknowledged that differential equations and BCs are representative of independent physical processes, and no correlations between them are required. Two recent studies by Hilhorst, Chung et al. argue instead that, in the specific case of diffusion equations (DEs) in bounded systems, BCs are uniquely constrained by the form of transport coefficients. In this paper, we revisit how DEs emerge as fluid limits out of a picture of stochastic transport. We point out their limits of validity and argue that, in most physical systems, BCs and DEs are actually uncorrelated by virtue of the failure of diffusive approximation near the system’s boundaries. When, instead, the diffusive approximation holds everywhere, we show that the correct chain of reasoning goes in the direction opposite to that conjectured by Hilhorst and Chung: it is the choice of the BCs that determines the form of the DE in the surroundings of the boundary. Full article

The increasing complexity and scale of electronic health records (EHRs) demand advanced tools for efficient data retrieval, summarization, and comparative analysis in clinical practice. MERA (Medical Electronic Records Assistant) is a Retrieval-Augmented Generation (RAG)-based AI system that addresses these needs by integrating domain-specific retrieval with large language models (LLMs) to deliver robust question answering, similarity search, and report summarization functionalities. MERA is designed to overcome key limitations of conventional LLMs in healthcare, such as hallucinations, outdated knowledge, and limited explainability. To ensure both privacy compliance and model robustness, we constructed a large synthetic dataset using state-of-the-art LLMs, including Mistral v0.3, Qwen 2.5, and Llama 3, and further validated MERA on de-identified real-world EHRs from the MIMIC-IV-Note dataset. Comprehensive evaluation demonstrates MERA’s high accuracy in medical question answering (correctness: 0.91; relevance: 0.98; groundedness: 0.89; retrieval relevance: 0.92), strong summarization performance (ROUGE-1 F1-score: 0.70; Jaccard similarity: 0.73), and effective similarity search (METEOR: 0.7–1.0 across diagnoses), with consistent results on real EHRs. The similarity search module empowers clinicians to efficiently identify and compare analogous patient cases, supporting differential diagnosis and personalized treatment planning. By generating concise, contextually relevant, and explainable insights, MERA reduces clinician workload and enhances decision-making. To our knowledge, this is the first system to integrate clinical question answering, summarization, and similarity search within a unified RAG-based framework. Full article

Rubinstein–Taybi Syndrome type 1 (RSTS1) is an uncommon autosomal dominant genetic disorder associated with neurodevelopmental impairments and multiple congenital anomalies, with an incidence of 1:100,000–125,000 live births. The syndrome, caused by de novo mutations in the CREBBP gene, is characterized by phenotypic variability, including intellectual disability, facial dysmorphisms, and systemic abnormalities. The current case report describes a 15-year-old Brazilian female diagnosed with RSTS1 through whole-exome sequencing, which identified a de novo heterozygous missense mutation in the CREBBP gene (NM_004380.3; c.4393G > C; p.Gly1465Arg), classified as pathogenic. The patient’s clinical presentation included facial dysmorphisms, skeletal abnormalities, neurodevelopmental delay, psychiatric conditions, and other systemic manifestations. A comprehensive genetic counseling process facilitated the differential diagnosis and management strategies, emphasizing the importance of early and precise diagnosis for improving clinical outcomes. This report contributes to the growing knowledge of the genotype–phenotype correlations in RSTS1, aiding in the understanding and management of this uncommon condition. Full article

Background/Objectives: Alterations in DNA damage repair mechanisms can impair the therapeutic effectiveness of cisplatin. MicroRNAs (miRNAs), key regulators of DNA damage repair processes, have been proposed as promising biomarkers for predicting the response to platinum-based chemotherapy (CT) in non-small cell lung cancer (NSCLC). In this study, by using a bioinformatics approach, we identified six miRNAs, which were differentially expressed (DE) between NSCLC patients characterized as responders and non-responders to platinum-based CT. We further validated the differential expression of the selected miRNAs on tumor and matched normal tissues from patients with resected NSCLC. Methods: Two miRNA microarray expression datasets were retrieved from the Gene Expression Omnibus (GEO) repository, comprising a total of 69 NSCLC patients (N = 69) treated with CT and annotated data from their response to treatment. Differential expression analysis was performed using the Linear Models for Microarray Analysis (Limma) package in R to identify DE miRNAs between responders (N = 33) and non-responders (N = 36). Quantitative real-time PCR (qRT-PCR) was used to assess miRNA expression levels in clinical tissue samples (N = 20). Results: Analysis with the Limma package revealed 112 DE miRNAs between responders and non-responders. A random-effects meta-analysis further identified 24 miRNAs that were consistently up- or downregulated in at least two studies. Survival analysis using the Kaplan–Meier plotter (KM plotter) indicated that 22 of these miRNAs showed significant associations with prognosis in NSCLC. Functional and pathway enrichment analysis revealed that several of the identified miRNAs were linked to key pathways implicated in DNA damage repair, including the p53, Hippo, PI3K and TGF-β signaling pathways. We finally distinguished a six-miRNA signature consisting of miR-26a, miR-29c, miR-34a, miR-30e-5p, miR-30e-3p and miR-497, which were downregulated in non-responders and are involved in at least three DNA damage repair pathways. Comparative expression analysis on tumor and matched normal tissues from surgically treated NSCLC patients confirmed their differential expression in clinical samples. Conclusions: In summary, we identified a signature of six miRNAs that are suppressed in NSCLC and may serve as a predictor of cisplatin response in NSCLC. Full article

This study presents a next-generation clinical decision-support architecture for Clinical Decision Support Systems (CDSS) focused on emergency triage. By integrating Large Language Models (LLMs), Federated Learning (FL), and low-latency streaming analytics within a modular, privacy-preserving framework, the system addresses key deployment challenges in high-stakes clinical settings. Unlike traditional models, the architecture processes both structured (vitals, labs) and unstructured (clinical notes) data to enable context-aware reasoning with clinically acceptable latency at the point of care. It leverages big data infrastructure for large-scale EHR management and incorporates digital twin concepts for live patient monitoring. Federated training allows institutions to collaboratively improve models without sharing raw data, ensuring compliance with GDPR/HIPAA, and FAIR principles. Privacy is further protected through differential privacy, secure aggregation, and inference isolation. We evaluate the system through two studies: (1) a benchmark of 750+ USMLE-style questions validating the medical reasoning of fine-tuned LLMs; and (2) a real-world case study (n = 132, 75.8% first-pass agreement) using de-identified MIMIC-III data to assess triage accuracy and responsiveness. The system demonstrated clinically acceptable latency and promising alignment with expert judgment on reviewed cases. The infectious disease triage case demonstrates low-latency recognition of sepsis-like presentations in the ED. This work offers a scalable, audit-compliant, and clinician-validated blueprint for CDSS, enabling low-latency triage and extensibility across specialties. Full article

In modern vehicles, Autonomous Driving Systems (ADSs) are designed to operate partially or fully without human intervention. The ADS pipeline comprises multiple layers, including sensors, perception, localization, mapping, path planning, and control. The Robot Operating System (ROS) is a widely adopted framework that supports the modular development and integration of these layers. Among them, the path-planning and control layers remain particularly challenging due to several limitations. Classical path planners often struggle with non-smooth trajectories and high computational demands. Meta-heuristic optimization algorithms have demonstrated strong theoretical potential in path planning; however, they are rarely implemented in real-time ROS-based systems due to integration challenges. Similarly, traditional PID controllers require manual tuning and are unable to adapt to system disturbances. This paper proposes a ROS-based ADS architecture composed of eight integrated nodes, designed to address these limitations. The path-planning node leverages a meta-heuristic optimization framework with a cost function that evaluates path feasibility using occupancy grids from the Hector SLAM and obstacle clusters detected through the DBSCAN algorithm. A dynamic goal-allocation strategy is introduced based on the LiDAR range and spatial boundaries to enhance planning flexibility. In the control layer, a modified Pure Pursuit algorithm is employed to translate target positions into velocity commands based on the drift angle. Additionally, an adaptive PID controller is tuned in real time using the Differential Evolution (DE) algorithm, ensuring robust speed regulation in the presence of external disturbances. The proposed system is practically validated on a four-wheel differential drive robot across six scenarios. Experimental results demonstrate that the proposed planner significantly outperforms state-of-the-art methods, ranking first in the Friedman test with a significance level less than 0.05, confirming the effectiveness of the proposed architecture. Full article

Soil-transmitted helminths (STHs) and Herpes Simplex Virus type 2 (HSV-2) are highly prevalent infections with overlapping distribution, particularly in resource-poor regions. STH/HSV-2 co-infections may impact female reproductive health. However, many aspects of STH/HSV-2 co-infections, including the role of microRNAs (miRNAs) in regulating female genital tract (FGT) immunity and their potential contribution to pathologies such as chronic inflammation, impaired mucosal defense, and reproductive tract cancers remain unclear. In this study we investigated the miRNA expression profiles in murine FGT tissues following single or co-infection with Nippostrongylus brasiliensis (Nb) and HSV-2 and explored predicted miRNA-mRNA targets and pathways. An analysis of miRNA sequencing data was conducted to determine differentially expressed (DE) miRNAs between infected FGT tissues and uninfected controls. Ingenuity Pathway Analysis was conducted to predict the immune-related target genes of the DE miRNAs and reveal enriched canonical pathways, top diseases, and biological functions. Selected representative DE miRNAs were validated using RT-qPCR. Our results showed a total of eight DE miRNAs (mmu-miR-218-5p, mmu-miR-449a-5p, mmu-miR-497a-3p, mmu-miR-144-3p, mmu-miR-33-5p, mmu-miR-451a, mmu-miR-194-5p, and mmu-miR-192-5p) in the comparison of Nb-infected versus uninfected controls; nine DE miRNAs (mmu-miR-451a, mmu-miR-449a-5p, mmu-miR-144-3p, mmu-miR-376a-3p, mmu-miR-192-5p, mmu-miR-218-5p, mmu-miR-205-3p, mmu-miR-103-3p, and mmu-miR-200b-3p) in the comparison of HSV-2-infected versus uninfected controls; and one DE miRNA (mmu-miR-199a-5p) in the comparison of Nb/HSV-2 co-infected versus uninfected controls (p-value < 0.05, |logFC| ≥ 1). Core expression analysis showed that, among other canonical pathways, the DE miRNAs and their predicted mRNA targets were involved in neutrophil degranulation, interleukin-4 and interleukin-13 signaling, natural killer cell signaling, interferon alpha/beta signaling, and ISGylation. Additionally, cancer was predicted as one of the significantly enriched diseases, particularly in the co-infected group. This is the first study to provide insights into the FGT miRNA profiles following Nb and HSV-2 single and co-infection, as well as the predicted genes and pathways they regulate, which may influence host immunity and pathology. This study highlights the role of miRNAs in regulating FGT immunity and pathology in the context of STH/HSV-2 co-infection. Full article

Alveolar capillary dysplasia with misalignment of pulmonary veins (ACDMPV) is a rare, often fatal congenital disorder characterized by severe neonatal respiratory distress and associated with complex multisystem malformations. In approximately 90% of cases, the condition is linked to deletions or mutations affecting the FOXF1 gene or its upstream enhancer region on chromosome 16q24.1. This review analyzes reported prenatal cases with 16q24.1 deletion involving FOXF1, aiming to identify recurrent sonographic features and elucidate the underlying genomic and epigenetic mechanisms. We reviewed prenatal cases reported in the literature involving deletions of the 16q24.1 region, including the FOXF1 gene. Here, we expand the case series by reporting a fetus with increased nuchal translucency measuring 8 mm and a de novo 16q24.1 deletion. We identified nine prenatal cases with a 16q24.1 deletion, all involving the FOXF1 gene or its enhancer region. The main ultrasound findings included increased nuchal translucency and cystic hygroma during the first trimester, and cardiac, renal, and intestinal malformations from 20 weeks of gestation onward. Prenatal diagnosis of ACDMPV based solely on ultrasound findings is challenging. In most reported cases, the pregnancy was carried to term, with the diagnosis being confirmed by post-mortem histopathological examination. In the only case in which the pregnancy was terminated at 14 weeks’ gestation, histological examination of the fetal lungs, despite them being in the early stages of development, revealed misaligned pulmonary veins in close proximity to the pulmonary arteries and bronchioles. Evidence highlights the significance of non-coding regulatory regions in the regulation of FOXF1 expression. Differential methylation patterns, and possible contributions of parental imprinting, highlight the complexity of FOXF1 regulation. Early detection through array comparative genomic hybridization (array CGH) or next-generation sequencing to identify point mutations in the FOXF1 gene, combined with increased awareness of ultrasound markers suggestive of the condition, could improve the accuracy of prenatal diagnosis and genetic counseling. Further research into the epigenetic regulation of FOXF1 is crucial for refining recurrence risk estimates and improving genetic counseling practices. Full article

Asthma, the most common chronic respiratory condition in children, involves airway inflammation, hyper-responsiveness, and frequent exacerbation that worsen the airflow and inflammation. Exosomes, extracellular vesicles carrying microRNAs (miRNAs), play a key role in cell communication alongside other types of communication and are promising markers of asthma severity. This study compares exosomal miRNA and long non-coding RNA (lncRNA) profiles in boys with asthma, focusing on differences between those with normal lung functions and those with severe airflow obstruction. This study enrolled 20 boys aged 9–18 years with asthma, split into two groups based on their lung function. Ten had normal lung function (NLF; FEV1/FVC > 0.84, FEF75% > 69% predicted), while ten had severe airflow obstruction (SAO; FEV1/FVC < 0.70, FEF75 < 50% predicted). Saliva and blood samples were collected. Exosomes were isolated, quantified, and analyzed via small RNA sequencing to identify differentially expressed (DE) miRNA and lncRNA profiles. Bioinformatic tools were then used to explore potential miRNA biomarkers linked to asthma severity. SAO subjects were more likely to exhibit allergen sensitization, higher IgE levels, and more eosinophils. We identified 27 DE miRNAs in plasma and 40 DE miRNAs in saliva. Additionally, five key miRNAs were identified in both saliva and plasma which underline important pathways such as neurotrophins, T-cell receptor, and B-cell receptor signaling. We further outlined key features and functions of miRNAs and long non-coding RNAS (lncRNAs) and their interactions in children with asthma. This study identified DE miRNAs and lncRNAs in children with SAO when compared to those with NLF. Exosomal miRNAs show strong potential as non-invasive biomarkers for personalized asthma diagnosis, treatment, and monitoring. These RNA markers may also aid in tracking disease progression and response to therapy, thereby supporting the need for future studies aimed at applications in precision medicine. Full article

Colorectal cancer (CRC) is a major global health concern, with tumor progression closely influenced by inflammatory mechanisms and cytokine signaling. This study investigates the serum expression levels of interleukins IL-8, IL-17A, and IL-33 in patients with colon cancer, analyzing their association with tumor grade and depth of invasion. The cohort included 42 patients stratified by tumor differentiation (G1–G3) and various invasion types. ELISA assays revealed that IL-8 levels were highest in well-differentiated tumors and in cases of submucosal and serosal invasion, suggesting a key role in early stage inflammation and angiogenesis. IL-17A and IL-33 levels declined progressively with tumor dedifferentiation and increased invasion depth, indicating immune suppression in advanced stages. Multiple regression analyses highlighted a nonlinear, significant relationship between IL-8 and IL-17A, whereas IL-33 showed no direct correlation with other interleukins. A combined model incorporating IL-8, IL-17A, IL-33, and tumor grade accounted for over 70% of IL-17A variability, underscoring their interactive role in CRC biology. These findings support the potential utility of interleukins as biomarkers and therapeutic targets for stratified CRC management. Full article