Search Results (1,103)

Atmospheric turbulence significantly degrades the performance of High Energy Laser (HEL) systems by distorting the laser wavefront as it propagates through the atmosphere. Conventional correction techniques rely on Adaptive Optics (AO), which preserve beam quality at the object. However, AO systems require wavefront sensors, such as Shack–Hartmann, and a reference beam, increasing system complexity and cost. This work presents a Deep Learning (DL)-based wavefront sensing approach that operates directly on scene imagery, thereby eliminating the need for dedicated wavefront sensors and a reference beam. A DL model was trained to predict wavefront distortions, represented by Zernike coefficients, from aberrated imagery of the Reaper Unmanned Aerial Vehicle (UAV). Reaper imagery utilized in training was aberrated at different levels of turbulence, $D/r_0$, with $D=30$ cm being the aperture diameter of a telescope capturing the object scene and $r_0=3, 5, 7$ cm the Fried parameter that defines weak turbulence for higher values and strong turbulence for lower values. The proposed model, trained across all these turbulence levels, outperformed models trained on a single level by providing superior accuracy and offering practical advantages for deployment. The model also demonstrated strong generalization capabilities for two practical scenarios: (a) Reaper imagery with turbulence levels beyond the training range, and (b) Mongoose UAV imagery not included in the training set. The model predicts turbulence accurately in both cases. The results confirm that if the model is trained for a UAV model for a certain turbulence level, it provides accurate predictions for turbulence levels outside its training range and for other UAV aberrated images. Full article

Academic conferences have been pivotal in scholarly communications, facilitating the exchange of ideas and fostering collaborations among attendees by using advanced sensing, networking, and control technologies. Traditionally held in physical venues, the landscape of academic conferences has been revolutionised by the advent of virtual and hybrid formats as supported by the Internet of Things, Artificial Intelligence, and virtual reality tools. Despite the burgeoning literature on smart conferences, there exists a gap in comprehensive reviews that consolidate the various advancements and methodologies in this domain. This article aims to fill this gap by providing a thorough review of the latest developments in smart conference technologies and practices. It offers a multidimensional analysis, including predictive analytics, smart content delivery, networking improvements, and data-driven assessments. Fundamentally, we frame conference activities as a complex process involving multi-stage planning, real-time dynamic execution, and post-event analysis and refinement. This review specifically highlights how smart technologies are transforming this end-to-end process. Additionally, the concept of parallel intelligence is introduced, exploring its potential to transform future conferences. The significance of this article lies in its holistic perspective, offering valuable insights for enhancing conference planning, attendee engagement, and overall conference experiences. Full article

To address the limitations of conventional wavefront sensorless adaptive optics (AO) systems regarding iteration efficiency and convergence speed, this study conducts an experimental validation of a model-based wavefront sensorless AO approach. A physical experimental platform was established, which consisted of a light source, a Shack–Hartmann wavefront sensor, a deformable mirror (DM), and an imaging detector. Wavefront aberrations under different turbulence levels were employed as correction objects to evaluate the performance of the model-based wavefront sensorless AO system. For comparative analysis, experimental results obtained by using the classical stochastic parallel gradient descent (SPGD) control algorithm are also presented. Under identical software and hardware conditions, the experimental results show that as the turbulence level increases, the SPGD-based wavefront sensorless AO system requires a larger number of iterations and exhibits a slower convergence. In contrast, the model-based wavefront sensorless AO system demonstrates improved applicability and robustness in correcting large aberrations under strong turbulence levels, maintaining an almost constant convergence speed and achieving better correction performance. These findings offer theoretical insights and technical support for the real-time correction potential of large wavefront aberrations. Full article

Circulating tumor DNA (ctDNA) analysis offers a non-invasive approach to molecular profiling. While RAS mutations are well-established predictive biomarkers in metastatic colorectal cancer (mCRC), the prognostic value of their variant allele frequency (VAF) remains unclear. We retrospectively analyzed individual patient data with mCRC who underwent ctDNA testing using the FoundationOne^® Liquid CDx assay. The primary objective was to determine the optimal RAS VAF cutoff for overall survival (OS) prognostication. Between November 2020 and July 2024, 282 patients were enrolled. Among 265 eligible patients, 134 (50.6%) were ctRAS mutant, 25 (9.4%) ctBRAF^V600E mutant, and 106 (40.0%) were ctRAS/BRAF wild-type. A RAS VAF threshold of 5% yielded the highest prognostic discrimination for OS (HR = 2.41; 95% CI 1.65–3.55; p < 0.0001; C-index = 0.601). ctRAS-high mutant tumors (VAF ≥ 5%) were associated with synchronous metastatic disease, multiple metastatic sites, higher blood tumor mutational burden, and elevated tumor fraction. ctRAS-low mutant tumors (VAF < 5%) were more frequently metachronous, presented with a single metastatic site, and showed liver involvement. High RAS VAF in ctDNA is a strong and independent prognostic marker for OS in mCRC. Quantitative ctDNA profiling may enhance risk stratification and guide personalized management strategies. Full article

Synovial sarcoma (SySa) is a malignant soft tissue tumor that is characterized by an SS18::SSX fusion protein, which integrates into BAF chromatin remodeling complexes and alters global gene transcription. Despite its uniform genetic driver, SySa displays striking histomorphological and phenotypic heterogeneity, including spindle cell, glandular and poorly differentiated patterns. Prognosis is variable, with around 50% of patients developing metastases. Limited response to chemotherapy highlights the need for a better understanding of the underlying molecular mechanisms to guide alternative therapeutic strategies. Given the pivotal function of BAF complexes in SySa and their recently described impact on cellular differentiation processes, this study aims to investigate the role of SS18::SSX and specific BAF subunits in SySa differentiation. Nanostring analysis revealed that silencing of SS18::SSX and the GBAF subunit BRD9 modulates the cellular differentiation pathways. SS18::SSX and BRD9 were found to regulate epithelial–mesenchymal-transition (EMT)-associated factors of Snail and Slug on different levels, with SS18::SSX repressing E-Cadherin expression. Published single-cell RNA sequencing data were analyzed to validate our finding that BRD9 contributes to SySa EMT regulation. Our study provides novel insights into the multilayered regulation of key EMT players by SS18::SSX and BRD9 in SySa, thereby defining tumor phenotype and (potentially) prognosis. Full article

The macrolide antibiotic telithromycin was developed to avoid common antibiotic resistances, yet it has been recently withdrawn from the European market due to severe side effects. Both side effects and the effectiveness of a drug can be related to the strength of its interaction with human serum albumin (HSA). However, as of yet, interactions between telithromycin and HSA have not been thoroughly studied. In this work, we evaluate the interaction strength and structural details of telithromycin and HSA via diffusion ordered spectroscopy (DOSY) and transferred NOE measurements. The binding strengths are compared with those of related macrolides. Our results show that the interaction strength increases with the decreasing polarity of the side chains in the antibiotic. Among the tested macrolide antibiotics, telithromycin interacted the strongest with HSA. Structure calculations based on transferred NOEs, using DFT calculations, show that telithromycin adopts a specific conformation upon binding, which shields the polar moieties attached to the aglycon and enables more hydrophobic interactions with HSA. Full article

Leishmania (L.) infantum infections in dogs can cause severe recurrent disease. The aim of this study was to investigate different parameters for early detection of disease relapses in L. infantum-infected dogs in Germany. Fifty-two dogs naturally infected with L. infantum were enrolled. During the one-year study period, all dogs remained outside of endemic areas and attended study appointments every three months, including physical examination, blood pressure measurement, complete blood count with differential, serum biochemistry with symmetrical dimethylarginine and C-reactive protein, complete urinalysis including urine protein-to-creatinine ratio, L. infantum PCR, and antibody ELISA. Disease relapse was defined as deterioration of clinical or laboratory parameters in dogs that had achieved complete or partial remission before. Univariable and multivariable Bayesian logistic regression were used to identify predictors of disease relapse. Lymphadenopathy (p < 0.01; OR = 6.93), seborrhea/hypotrichosis (p = 0.02; OR = 8.02), and proteinuria (p < 0.01; OR = 9.14) were significantly associated with upcoming disease relapses (n = 10; 9/52 dogs), while associations between higher antibody levels and upcoming disease relapses trended towards significance (p = 0.06; OR = 1.03). Different parameters are important for an early diagnosis of disease relapse in canine leishmaniosis and should thus be regularly assessed and interpreted accordingly in the monitoring of L. infantum-infected dogs. Full article

Peripheral artery disease (PAD) leads to reduced blood flow, primarily affecting the vessels of lower extremities. Symptoms include pain, cramping and reduced functional capacity, and patients are also at increased risk of cardiovascular complications and mortality. Postoperative medical management in PAD patients includes the use of antiplatelet and antithrombotic medications, which help to prevent postoperative graft and stent thrombosis and associated adverse effects. Despite extensive research, there is little consensus on the best strategy or medication regimen for patients with PAD or on monitoring strategies for the antithrombotic therapies. Thromboelastography, with the adjunct of platelet function assessment, is well established for providing real-time assessment of coagulation and platelet function in patients undergoing cardiovascular surgery or cardiovascular procedures. TEG^® PlateletMapping^® assays can assess hypercoagulable changes in pre- and post-intervention in cardiovascular patients, including in patients with PAD and help physicians guide antithrombotic treatments after revascularization. The use of thromboelastography with platelet function analysis provides an opportunity to tailor antithrombotic therapy and personalize care in patients with PAD, which could be integral to improving limb salvage and preventing adverse events in these patients. Full article

Background/Objectives: Rickets is a pediatric disorder caused by impaired mineralization of the growth plate, primarily due to deficiencies in vitamin D, calcium, or phosphate. Lower limb deformities are among the most clinically relevant skeletal manifestations, significantly affecting quality of life. This review aims to summarize and compare lower limb deformities associated with different etiologies of rickets, specifically hypophosphatemic (HPR) and calcipenic (CR) forms. Methods: A systematic PubMed search was performed according to PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidelines. Of 2056 screened records, 126 studies including 21,568 patients met the inclusion criteria. Data on study characteristics, deformity types, and diagnostic methods were extracted and analyzed descriptively, with subgroup comparison between HPR and CR. Results: Among 2924 patients with reported with deformities (1537 CR, 1387 HPR), genu varum and genu valgum predominated, while windswept deformities were less frequent. Sagittal and torsional deformities, particularly femoral and tibial maltorsion or procurvatum, were mainly described in HPR but rarely reported in CR. Only a minority of studies met predefined quality standards regarding radiological assessment and deformity definition. Conclusions: Lower limb deformities are prevalent in both HPR and CR but differ significantly in type and documentation quality. While coronal plane deformities are common across both types, axial and sagittal deformities appear under-reported in rickets, particularly in CR. The results highlight the need for standardized diagnostic criteria and improved reporting in order to enhance comparability and clinical management of rickets-related deformities. Full article

Functional coatings on optical fibers enable selective detection of environmental and chemical parameters, but their use is typically limited to point or quasi-distributed sensing due to localized deposition techniques. In this work, we demonstrate a possible transition towards full-length functional coatings on optical fibers using a draw tower process, enabling their potential use in distributed sensor technology. An optical fiber with Pt:WO₃ nanocomposite polymer functional coating is employed as a proof of concept. The results demonstrate the successful application of this functional coating along hundreds of meters of fibers using a draw tower. When integrated into a distributed sensing configuration, the Pt:WO₃ fiber exhibited a clear change in response with varying hydrogen concentrations from 1% to 4% H₂, with a temperature increase of 2.5 °C at 4 vol.% indicating a promising performance for distributed hydrogen leak detection. This approach opens new opportunities for applying other functional coatings over extended fiber lengths using draw towers, which could be exploited for novel distributed sensing applications. Full article

Endometriosis, a disease affecting about one out of ten women, is characterized by the growth of endometrial-like tissue outside the uterine cavity. There is significant disease heterogeneity, but the pathophysiological mechanisms underlying differences in clinical presentation are poorly understood. Here, we investigated endometrial stromal cells (ESCs) from different types of endometrial lesions (endometrioma, superficial, and deep endometrial lesions), which revealed distinct differences in proliferation, migration, and contractility among different lesion types and when compared to ESC from normal (eutopic) endometrium. In particular, ESCs from endometriotic lesions showed reduced proliferation but increased migratory capacity, an effect most pronounced in endometrioma ESCs but also evident in ESCs from superficial and deep lesions. ESCs from superficial and deep lesions—but not those from endometrioma—showed increased contractility, a feature involved in tissue scarring and pain perception. Transcriptomics and proteomics revealed changes in genes and proteins involved in cell division, proliferation, extracellular matrix organization, and migration in endometriosis vs. healthy ESCs. Overall, our results demonstrate that stromal cells from different endometriotic lesions show distinct in vitro phenotypes that might explain differences in clinical presentation. Further, these cells represent an excellent in vitro model for studying patho-mechanisms involved in endometriosis heterogeneity. Full article

Background/Objectives: Cardiovascular disease is the leading cause of mortality in patients with metabolic dysfunction-associated steatotic liver disease (MASLD), which includes simple steatosis (metabolic dysfunction-associated steatotic liver, MASL), metabolic dysfunction-associated steatohepatitis (MASH), and fibrosis. This study aimed to evaluate the association between left ventricular (LV) systolic function, measured by global longitudinal strain (GLS), and liver inflammation and fibrosis in obese patients with MASLD undergoing preoperative evaluation for bariatric surgery. Methods: Intraoperative liver biopsies classified patients into four groups: non-MASLD; MASL; MASH; and MASH with fibrosis. Preoperative transthoracic echocardiography (TTE) was performed, and LV GLS was assessed using automated strain analysis. Results: Ninety-two patients were included: 13 non-MASLD, 34 MASL, 21 MASH, and 24 MASH with fibrosis. Although most patients had normal LV GLS, values were significantly lower in the MASH with fibrosis group compared to the MASL and non-MASLD groups (p = 0.011). In multivariate analysis adjusted for HDL cholesterol and LV mass, LV GLS was associated with inflammation and fibrosis (OR 0.784; 95% CI 0.637–0.965; p = 0.022). Conclusions: LV GLS was significantly lower in patients with MASH and MASH with fibrosis and was associated with hepatic inflammation and fibrosis in obese individuals undergoing bariatric surgery. Full article

The present study investigates the magnetohydrodynamic (MHD) flow characteristics of a blood-based ternary nanofluid (Au/Cu/Al₂O₃-blood) in stenosed arteries, with a focus on symmetry-inspired modeling rooted in the axial symmetry of arterial geometry and the symmetric distribution of external physical fields (magnetic field, thermal radiation). The findings offer significant insights into the realm of hyperthermia therapy and targeted drug delivery within the domain of biomedical engineering. A mathematical model is established under a cylindrical coordinate system (consistent with arterial axial symmetry), integrating key physical effects (thermal radiation, chemical reactions, viscous dissipation, body acceleration) and fractional-order dynamics via Caputo derivatives—while ensuring the symmetry of governing equations in time and space. The numerical solutions for velocity and temperature profiles are obtained using the Laplace transform and Concentrated Matrix-Exponential (CME) method, a technique that preserves symmetric properties during the solution process. The results of the study indicate the following: The Hartmann number, which is increased, has been shown to reduce axial velocity due to the Lorentz force, thereby maintaining radial symmetry. Furthermore, thermal radiation has been demonstrated to raise fluid temperature, a critical factor in heat-based therapies, with the temperature field evolving symmetrically. In addition, it has been observed that ternary nanoparticles outperform single and binary systems in heat and mass transfer via symmetric dispersion. This work contributes to the existing body of knowledge by integrating symmetry principles into the study of fractional dynamics, electromagnetic fields, and body acceleration modeling. It establishes a comprehensive biomedical flow framework. It is imperative that future research explore pulsatile flow under symmetric boundaries and validate the model through experimental means. Full article

Natural convection enhanced by magnetic fields and nanofluids has broad applications in thermal management systems. This study investigates magnetohydrodynamic (MHD) natural convection in a wavy trapezoidal cavity containing centrally located heated square obstacles, filled with various nanofluids Cu–H₂O, Fe₃O₄–H₂O, and Al₂O₃–H₂O. A uniform magnetic field is applied horizontally, and the effects of key parameters such as Rayleigh number, Ra (10³–10⁶), Hartmann number, Ha (0–50), and nanoparticle volume fraction, φ (0.00, 0.02, 0.04) are analyzed. The numerical simulations are performed using the finite element method, incorporating a wavy upper boundary and slanted sidewalls to model realistic enclosures. Results show that an increasing Rayleigh number enhances heat transfer, while a stronger magnetic field reduces convective flow. Among the nanofluids, Cu–H₂O demonstrates the highest Nusselt number and ecological coefficient of performance (ECOP), whereas Fe₃O₄–H₂O exhibits superior performance under stronger magnetic fields due to its magnetic nature. Entropy generation, S_T decreases with increasing Ra and φ, indicating reduced thermodynamic irreversibility. These results provide insights into designing energy-efficient enclosures using nanofluids under magnetic control. Full article

Battery system engineers face the challenge of balancing competing requirements regarding performance, maintainability, sustainability, safety, and cost—especially in the automotive industry. Intelligent battery systems potentially offer a solution with fewer trade-offs. They feature a battery management system with advanced sensing and data analysis capabilities that facilitate improved battery monitoring and operation. Reconfigurable energy storage units enable sophisticated operating strategies, including complete cell state control, full energy content utilization, and a measured response to faults. This article presents the design, development, and operation of a full-scale intelligent battery system prototype comprising 324 automotive lithium-ion cells with a nominal voltage of 400 $\mathrm{V}$. The system exhibits a modular single cell architecture and an advanced centralized battery management system. We detail the system architecture, hardware and software component design, and system integration. Initial tests demonstrate the battery’s operability, extended functionality, and enhanced safety. Our analysis shows that the additional losses introduced by reconfigurability are more than offset by the benefits of full energy utilization—even for new cells, with increasing advantage as aging progresses. The results underscore the potential of intelligent battery systems and motivate further research and development toward economic assessment and industrial adoption. Full article