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Three-dimensional effects of the wake on wind turbine sound propagation using parabolic equation
Get PDFThe influence of three-dimensional (3D) wind turbine wake effects on sound propagation is investigated. To study this, numerical simulations are conducted using a 3D parabolic equation model at low frequencies, with comparisons made to a two-dimensional (2D) approach that neglects transverse horizontal propagation. Three atmospheric stability conditions are investigated using analytical wind profiles that incorporate the wake effects. The wind turbine noise source is specified using an aeroacoustic extended source model. 3D effects due to the wake are shown to be significant, especially for the stable atmosphere. Indeed, horizontal refraction induces focusing that a 2D approach fails at predicting. As the wind turbine blades are rotating, the focal zones are moving accordingly, yielding large variations of the sound levels. Downstream the turbine, amplitude modulation can locally reach values as high as 16.5 dB over long distances. In addition, higher average SPL are predicted by 3D simulations compared to 2D ones, with deviations up to 4.5 dB. For neutral and unstable conditions differences in 2D and 3D sound propagation approaches are smaller, as velocity gradients in the wind turbine wake are smaller.</p
PSMA expression and PSMA PET/CT imaging in metastatic soft tissue sarcoma patients, results of a prospective study
Get PDFPurpose: Prostate-specific membrane antigen (PSMA) expression has been observed in a subset of soft tissue sarcomas, mainly in the neovascular endothelial cells. This feasibility study aimed to evaluate PSMA expression and PSMA PET/CT imaging in metastatic soft tissue sarcoma, providing important insights for potential future exploration of PSMA-targeted radioligand therapy. Methods: This prospective single-center study included adult patients with metastatic soft tissue sarcoma, with measurable disease (lesion diameter > 1 cm), available biopsy/resection material, ECOG/WHO performance status of 0–2 and either no prior systemic treatment, progressive disease during/after treatment, or stable disease/partial response with the last dose > 8 weeks prior. Immunohistochemical PSMA staining was performed on previously obtained biopsy or resection material. In case of high PSMA expression, a [18F]-JK-PSMA-7 PET/CT scan evaluated tracer uptake, with adequate uptake defined as SUVmax > 8. Results: Of 25 included patients, 11 (44%) had high PSMA expression: 4/11 leiomyosarcomas, 3/4 dedifferentiated liposarcomas, 2/5 undifferentiated pleomorphic sarcomas, 1/2 myxofibrosarcomas and 1/1 malignant peripheral nerve sheath tumour. Five of 11 patients agreed to a [18F]-JK-PSMA-7 PET/CT, of which 3 had lesions that showed adequate tracer uptake (SUVmax 10.7–16.7). However, uptake across all metastatic lesions was highly heterogeneous (median SUVmax = 3.8; range 0.5–16.7), indicating that these patients are unlikely to benefit sufficiently from PSMA-targeted therapy. The study was therefore terminated prematurely. Conclusion: PSMA expression and PSMA tracer uptake in metastatic soft tissue sarcoma were highly heterogeneous. A deeper understanding of PSMA biology and improved patient selection criteria are essential for future application of PSMA-targeted radioligand therapy in this disease. Trial registration: : clinicaltrials.gov, NCT05522257. Registered 31-08-2022.</p
External validation of a serum tumor marker algorithm for early prediction of no durable benefit to immunotherapy in metastastic non-small cell lung carcinoma:Tumor Biology
Get PDFBackground Immune checkpoint inhibitors (ICIs) provide a significant survival benefit in non-small cell lung cancer (NSCLC) patients; however, accurately predicting which patients will benefit remains a challenge. As previously shown, the STOP model, a machine learning model based on serum tumor markers, is capable of identifying non-responders after 6 weeks of ICIs.Objective This study aims to externally validate this model and to assess the predictive value in combination with radiological response assessment using RECIST criteria.Methods In a cohort of 242 metastatic NSCLC patients, CYFRA, CEA, and NSE were measured before start and after 6 weeks of ICI treatment. The ability of the STOP model to predict no durable benefit (NDB; progressive disease, death within 6 months or disease control of less than 6 months) was assessed using specificity and positive predictive value (PPV). Moreover, a combination of the STOP model with RECIST after 6?8 weeks of ICIs was investigated.Results The STOP model achieved a specificity of 96% (95% CI 95%?97%) and a PPV of predicting NDB of 88.1% (95% CI 85.9%?90.3%). Combining the STOP model with RECIST improved specificity and PPV to 100% and predicted NDB on average 11.6 weeks (IQR 1.8?18.0 weeks) prior to developing radiologically defined progression.Conclusions After 6 weeks of ICIs, the blood-based STOP model was capable of accurately predicting NDB in metastatic NSCLC patients, earlier than conventional radiological assessment. The combined serological and radiological response assessment creates an early opportunity to safely stop ICI treatment in patients who will not benefit, although the clinical utility of the assay is limited since the high specificity comes at the cost of a lower sensitivity
Modular breast and tumor perfusion phantoms for validation of 4D dynamic contrast-enhanced dedicated breast CT
No full textBreast tumors are heterogeneous, complicating diagnosis and treatment. Four-dimensional dynamic contrast-enhanced dedicated breast CT (4D DCE-bCT) is a novel imaging technique designed to detect the full extent of tumor heterogeneity by imaging the wash-in and wash-out of iodinated contrast with high spatial and temporal resolution. This study aims to develop breast tumor perfusion phantoms to validate 4D DCE-bCT. Three tumor phantoms were 3D-printed with clear resin material. The first phantom includes eight internal channels of 0.8mm and 1mm diameter. The second has similar channels with 0.3mm leaky vessels into an outer shell. The third features gyroid structures with 1.3mm and 1.5mm pores. These phantoms were integrated into a breast perfusion model, consisting of a 3D-printed breast filled with olive oil to simulate fatty tissue. A flow setup with programmable syringe pumps generated contrast wash-in of up to 6mg I/mL over 100s and wash-out over 200s. Time-intensity curves were analyzed in four regions of interest, focusing on areas with varying channel and pore sizes and at the phantom entrance and exit. Dynamic images showed the expected wash-in and wash-out at the phantom entrance and exit. The channel phantom showed 2.5 times higher enhancement in larger channels. The leaking outer shell demonstrated contrast pooling with 30s delayed wash-out. The gyroid phantom showed no differences between the two sides. This study presents the development of 3D-printed breast tumor perfusion phantoms and points to the feasibility of using 4D DCE-bCT to image detailed perfusion patterns
Vapor density gradients near the sublimating interface of a carbon dioxide sphere
Get PDFInvestigating the sublimation characteristics of dry ice particles exposed to convective heating in an unsaturated gaseous medium holds significance for applications employing cooling through dry ice sprays. While the transport phenomena between dry ice and its surrounding gas medium are central to various applications, a comprehensive understanding of these processes during dry ice sublimation remains incomplete. As a model problem, this study experimentally and numerically examines the sublimation of an isolated dry ice sphere within a controlled gas flow environment. Schlieren imaging is utilized in experiments to visualize density gradients at the dry ice–vapor interface for different CO 2 concentrations in the surrounding gas. An additional set of experiments involving backlight imaging is conducted to observe dry ice morphology and track its boundary over time. Numerical simulations using COMSOL Multiphysics software are performed to simulate the shrinkage of the sublimating dry ice sphere, accounting for heat, mass, and momentum transport in the gas mixture surrounding the dry ice. The numerical predictions of the density gradient near the sublimating dry ice interface exhibit qualitative agreement with the variations in light intensity observed in Schlieren images, thus confirming the predictive capabilities of the numerical model in this context. Furthermore, the numerical prediction of the temporal variation in dry ice mass closely aligns with experimental observations up to a certain duration, until the onset of frost formation on the dry ice surface, causing distortion in its morphology as evident in the images obtained during the experiments.</p
Process Mining for Demographic Insights: A Subpopulation Analysis in Healthcare Pathways
Get PDFDemographic variations in healthcare pathways are key for delivering effective and equitable patient care. Examining pathway differences across age and gender groups can help uncover demographic-specific disparities in care delivery. In this paper, we demonstrate the use of the Process Mining Project Methodology in Health-care (PM2HC) for the subpopulation-based analysis of treatment pathways, using process mining techniques. We validate this methodology through a case study on frozen shoulder treatment using the MIMIC-IV data set. Key findings reveal distinct procedural sequences for male and female patients, as well as notable age-based variations in treatment choices and timelines. These insights underscore the influence of demographic factors on healthcare processes. Expert evaluations further highlight the practicality of the methodology and its potential to guide targeted interventions that address various patient needs, thus enhancing personalized care. This work contributes t o clinical research and practice by identifying inefficiencies and informing tailored interventions. Future efforts will extend the methodology to other medical conditions and integrate multi-institutional data for broader applicability. By advancing process mining in healthcare, this research provides insight into improving patient care and addressing demographic diversity
A 12.8GS/s Sub-Sampling ADC Front-End With 38GHz Input Bandwidth and >39dB SNDR for 1 to 32GHz in 22nm FDSOI
No full textThe demand for higher data rates combined with the crowded wireless spectrum results in a trend towards millimeter-wave frequencies. RF-sampling architectures offer advantages in terms of flexibility, simplicity and robustness. However, presenting the ADC directly with tens of GHz at the input poses significant challenges especially to the front-end, leading to a demand for high-bandwidth-and fidelity implementations. This work targets RF-sampling of X-band to Ka-band frequencies while maximizing signal purity and a Nyquist bandwidth of 6.4GHz to allow flexibility and multi-channel reception, but minimizing system complexity and data-rate overhead. The focus is on the lower Ka-band around 27 to 31GHz used for high-throughput Earth-to-Satellite communication applications
Widespread neuronal chaos induced by slow oscillating currents
No full textThis paper investigates the origin and onset of chaos in a mathematical model of an individual neuron, arising from the intricate interaction between 3D fast and 2D slow dynamics governing its intrinsic currents. Central to the chaotic dynamics are multiple homoclinic connections and bifurcations of saddle equilibria and periodic orbits. This neural model reveals a rich array of codimension-2 bifurcations, including Shilnikov-Hopf, Belyakov, Bautin, and Bogdanov-Takens points, which play a pivotal role in organizing the complex bifurcation structure of the parameter space. We explore various routes to chaos occurring at the intersections of quiescent, tonic spiking, and bursting activity regimes within this space and provide a thorough bifurcation analysis. Despite the high dimensionality of the model, its fast-slow dynamics allow a reduction to a one-dimensional return map, accurately capturing and explaining the complex dynamics of the neural model. Our approach integrates parameter continuation analysis, newly developed symbolic techniques, and Lyapunov exponents, collectively unveiling the intricate dynamical and bifurcation structures present in the system.</p
Frozen Cheerios effect:Particle-particle interaction induced by an advancing solidification front
Get PDFParticles at liquid interfaces have the tendency to cluster due to capillary forces competing with gravitational buoyancy (i.e., normal to the distorted free surface). This is known as the Cheerios effect. Here we experimentally and theoretically study the interaction between two submerged particles near an advancing water-ice interface during the freezing process. Particles that are thermally more conductive than water are observed to attract each other and form clusters once frozen. We call this feature the frozen Cheerios effect, where interactions are driven by alterations to the direction of the experienced repelling force (i.e., normal to the distorted isotherm). On the other hand, particles less conductive than water separate, highlighting the importance of thermal conduction during freezing. Based on existing models for single particle trapping in ice, we develop an understanding of multiple particle interaction. We find that the overall efficacy of the particle-particle interaction critically depends on the solidification front velocity. Our theory explains why the thermal conductivity mismatch between the particles and water dictates the attractive or repulsive nature of the particle-particle interaction.</p
A solution method for active suppression of reflections in anechoic chambers
No full textA solution method to improve an anechoic chamber at low frequencies with the use of active noise control is presented. The approach uses the Kirchhoff-Helmholtz integral to compute the reflected sound field resulting from the primary sources together with an algorithm to compute the filter coefficients of a controller driving secondary sources on the walls of the enclosure using reference signals as inputs, which are measured on a contour enclosing the primary sources. A causal frequency domain method with conjugate gradient iterations is derived to determine the controller. The method is sufficiently efficient to allow computation of a causal time-domain controller with hundreds of secondary sources and hundreds of reference sensors in two- (2D) or three-dimensional configurations using a fully coupled multiple-input multiple-output system. The paper shows the results of a simulation with 200 secondary sources, 200 reference sensors, and 225 performance sensors based on a 2D finite element simulation. The method is verified in real-time in an experiment with the objective to suppress the reflections from the walls in a smaller 2D setup. Measurements with verification microphones show that the reverberation time is effectively reduced in the real-time experiment.</p