ABSTRACT The interactions between scalar and vector properties is vital in oceanic phenomena and energy/material circulation processes. This study integrates scalar and vector fields in ocean visualization to clarify their interplay and proposes a standardized approach for designing transfer functions that simplify ocean feature extraction. An interactive collaborative transfer function operational mode was introduced to visualise the scalar and vector fields, effectively capturing the dynamic characteristics of oceanic phenomena under mutual influence. Using the high-resolution GLORYS12V1 marine dataset, we visualized thermohaline fields and currents. Results show that the collaborative visualisation method and standardized transfer function effectively extract morphological outlines of ocean fronts and mesoscale eddies. Furthermore, the real-time collaborative transfer function reveals high spatial and directional consistency between ocean fronts (extracted via a 0.05 °C/km temperature gradient threshold) and Kuroshio axes (identified using a 0.1 m/s flow velocity threshold), which highlights the barrier effect of ocean fronts on meridional heat exchange. Additionally, we revealed the dynamic entrainment and transport capability of energy and material in mesoscale eddies. The above results demonstrate that the proposed synergistic transfer function in this study can effectively uncover the key role of scalar-vector field interactions in the evolution of oceanic phenomena.

Get over here: black capuchin monkeys use long-range vocalizations to adjust the distance between individuals.

Sprengel's deformity is a rare congenital anomaly of the scapula, characterized by an elevated position, inferior tilting of the glenoid, and hypoplasia. Due to limited data on the impact of this congenital anomaly, the purpose of this study is to objectively characterize the initial clinical presentation and quantify both the range of motion and patient-reported function in children with Sprengel's deformity. Children with Sprengel's deformity were prospectively enrolled into the multicenter Congenital Upper Limb Differences (CoULD) Registry between 2014 and 2023. Shoulder range of motion and patient-reported outcomes (PROs) data were collected from the patient's most recent preoperative follow-up and compared with normative values. PROs included the Pediatric Outcomes Data Collection Instrument (PODCI) and PROMIS Upper Extremity, Pain Interference, Depression, Anxiety, and Peer Relations domains. Univariate analysis was performed to compare unilateral versus bilateral presentation, non-syndromic versus syndromic association, and Cavendish grades. In total, 59 patients (52.5% female) were included with a median age of 5.9 years. Most patients presented with unilateral involvement (96.6%) and without an associated syndrome (78.0%). Cavendish grade III was the most common (50.8%) presentation. Average shoulder abduction (113 degrees) and forward elevation (120 degrees) were significantly less than the normal range ( P <0.001). Children with Sprengel's deformity reported less anxiety and depression than the normative population ( P =0.017 and 0.028, respectively). Patients scored significantly lower on PODCI Upper Extremity Function, Sports, and Global Function modules than the normative population ( P <0.05). PODCI Transfer sub-scores significantly varied by Cavendish classification ( P =0.011). Neither bilateral presentation nor syndromic association significantly affected other PROs ( P >0.05). Children with Sprengel's deformity have decreased shoulder range of motion, specifically abduction and forward elevation. Regardless of bilateral or syndromic presentation, patients generally demonstrated significantly lower physical function and sports abilities, but reported less anxiety and depression than population norms. A higher Cavendish grade was associated with worse transfer and mobility function. Therapeutic level II.

To characterize the image quality and dose level of a cone-beam CT (CBCT) scanner dedicated to maxillo-facial intra-surgical navigation. Acquisition protocols for head imaging of average pediatric and adult patients were investigated. The detector response curve and the modulation transfer function (MTF) were assessed. The 3D image quality was evaluated using a commercial Catphan604 phantom in terms of accuracy of Hounsfield Unit (HU) estimates and slice uniformity. The MTF and the noise power spectrum (NPS) were assessed over the 3D reconstructed images. The weighted cone-beam dose index (CBDIw) was used for dosimetric benchmarking, and TLD chips placed in two anthropomorphic phantoms provided insight into the patient dose distribution. The detector exhibited a response curve with a double natural logarithmic behavior and spatial resolutions up to 6.3mm-1. The 3D spatial resolution ranged from 0.70mm-1 at the scanner isocenter, for the pediatric protocol, to 0.46mm-1 at 7cm from the isocenter for the adult protocol. Due to beam hardening and the scatter, discrepancies between expected and measured HU were observed, in particular for positive HU values (i.e. those for acrylic, bone, delrin and teflon inserts). The CBDIw and dose distribution within anthropomorphic phantoms provided a dosimetric benchmark for the scanner. This study characterized a CBCT scanner in maxillo-facial surgery navigation. The findings support the definition of quality assurance protocols, providing methodologies and reference values for image quality and dose, while also highlighting limitations in spatial resolution and accuracy relevant for quantitative evaluations in clinical practice.

Influence of thermo-diffusive effects and pressure on laminar premixed hydrogen flame transfer functions

This study presents an improved mathematical model that incorporates negative interaction mechanisms to predict the dynamics of cell signaling pathways. By employing stochastic differential equations and the Euler-Maruyama method, we simulate the responses of proteins within the mitogen-activated protein kinase and oxytocin signaling pathways over time. Conventional signaling models that consider only positive interactions often lead to unrealistic signal over-amplification, the absence of oscillatory dynamics, and an inability to reproduce compensatory responses following targeted inhibition. To address these limitations, our model explicitly incorporates inhibitory interactions through a sign-changing characteristic function and bounds protein activity using a hyperbolic-tangent transfer function, ensuring biologically plausible saturation behavior. Our findings indicate that the inhibition of upstream proteins such as MEK1/2 leads to a rapid decrease in ERK1/2 activation while causing a compensatory increase in other proteins such as SOS, RAS, and RAF. Furthermore, we explore the synergistic effects of combination therapies, demonstrating that targeting multiple signaling pathways can enhance therapeutic efficacy. Through the application of the Bliss Independence Index, we assess the effectiveness of these therapeutic combinations. Additionally, we investigate the effects of abnormal activation increases caused by gain-of-function mutations on downstream proteins and the resulting changes in balance induced by negative interactions. Overall, our enhanced mathematical model serves as a valuable tool for simulating signaling dynamics with inhibitory crosstalk and for generating mechanistic hypotheses relevant to targeted and combination therapies.

The effects of heat exposure on dynamic cerebral autoregulation (dCA), the capacity of the cerebrovasculature to buffer rapid changes in arterial pressure, and its directional sensitivity, defined as the asymmetric cerebrovascular response to increases versus decreases in mean arterial pressure (MAP), remain incompletely understood. This uncertainty is largely attributable to concomitant heat-induced reductions in arterial carbon dioxide. We hypothesized that moderate isocapnic hyperthermia would impair dCA, particularly at higher frequencies of MAP oscillations, while preserving directional sensitivity across thermal conditions. Twenty healthy young participants (9 females, age: 24 ± 5 yrs) completed oscillatory lower body negative pressure trials at 0.05 and 0.10 Hz under normothermic and hyperthermic (core temperature +1.0°C) conditions. End-tidal carbon dioxide partial pressure (PETCO2) was clamped at baseline using a computer-controlled gas delivery system. Middle cerebral artery mean blood velocity (MCAvmean), MAP, PETCO2, heart rate, and core temperature were continuously recorded. dCA was assessed using transfer function analysis (TFA), and directional sensitivity was quantified using time-adjusted absolute (∆MCAvmeanT/∆MAPT) and relative (RelMCAvmeanT/RelMAPT) metrics. Moderate isocapnic hyperthermia increased TFA coherence at both frequencies and selectively impaired dCA at 0.10 Hz, as evidenced by increased TFA gain and normalized gain. Directional sensitivity was present at 0.05 Hz, indicated by higher ∆MCAvmeanT/∆MAPT and RelMCAvmeanT/RelMAPT during MAP decreases compared with increases, but was absent at 0.10 Hz. These findings demonstrate that isocapnic hyperthermia impairs dCA at higher frequency while preserving directional sensitivity at lower frequency, suggesting that distinct physiological mechanisms govern these components of cerebrovascular regulation beyond the influence of carbon dioxide.

To determine the optimal low-keV level using deep learning image reconstruction (DLIR) that maximizes lesion detectability, and to assess the potential for iodinated contrast media (ICM) reduction based on detectability improvements across varying patient body habitus. An abdominal phantom was scanned using a standard thoraco-abdomino-pelvic dual-energy computed tomography (DECT) protocol during the portal venous phase, with three rings inserted simulating different body habitus. Virtual monoenergetic images (VMI) were reconstructed from 40 to 70 keV in 10 keV increments using adaptive statistical iterative reconstruction-V (ASIR-V) 50% and high-strength DLIR (DLIR-H). Contrast enhancement was quantified, spatial resolution was evaluated with the task-based transfer function, and noise characteristics were analyzed using the noise power spectrum. Low-contrast lesion detectability (5-10 mm) was assessed using an anthropomorphic model observer. Compared to ASIR-V, DLIR-H provided equivalent contrast, reduced image noise, and improved spatial resolution. All lesion sizes with DLIR-H were technically detectable under all conditions. The reconstruction at 40 keV demonstrated the highest detectability of hypovascular lesions under all conditions. However, a decrease in detectability was observed in the large phantom relative to the small and medium phantoms, resulting in a reduced theoretical potential for iodine dose reduction. The theoretical potential for iodine dose reduction using 40 keV with DLIR-H is at least 31.3% based on the phantom-based model. Under phantom conditions, 40 keV with DLIR-H shows superior detectability of hypovascular lesions under all conditions, suggesting the theoretical possibility of reducing iodine load by up to 31.3%, based on modeled detectability performance. Based on a phantom-derived model, the combination of 40-keV VMI reconstruction with DLIR-H suggests the potential for more than 30% ICM reduction in oncologic body CT, a finding that warrants confirmation in clinical studies. Based on a phantom-derived model 40 keV VMI with DLIR-H achieved the highest detectability of hypovascular liver lesions. This approach enabled a 31.3% ICM volume reduction. Larger body habitus limits ICM volume reduction optimization margins.

Image quality assessment in digital breast tomosynthesis equipment in the cities of Belo Horizonte and Aracaju.

Auditory localization depends on the integration of binaural and spectral cues, yet their relative contributions to localization judgments remain difficult to quantify within a unified computational framework. This study introduces a Bayesian model of static auditory localization with an explicit cue-weighting (ECW) mechanism that estimates cue-specific weighting parameters by fitting behavioral responses. By embedding ECW into the likelihood function, the model provides a probabilistic framework for characterizing how weighted acoustic cues, spatial priors, and motor noise jointly shape localization responses. The estimated weighting patterns were broadly consistent with classic psychoacoustic findings, showing stronger weighting of binaural cues together with selective high-frequency weighting of spectral cues. The model further accounted for major behavioral trends across broadband stimulation and several challenging acoustic conditions, including non-individualized head-related transfer functions and reduced spectral resolution via vocoders. Together, these results indicate that the proposed ECW model extends Bayesian models of auditory localization by making the relative contributions of established binaural and spectral cues behaviorally estimable while providing competitive predictive performance.

To develop a new tool (IQ-PAT) for noise power spectrum (NPS) and task-based transfer function (TTF) evaluation on patient images and validate this tool on an image quality phantom. IQ-PAT was developed to compute automatically NPS and TTF in the thoracic aorta. First aorta mask and mesh were generated by a segmentation tool. Regions of interest (ROIs) were drawn on 100 slices in order to compute NPS. For TTF assessment, the barycenter of the aorta on 100 consecutive slices was calculated and used to extract and align radial profiles for Edge Spread Function (ESF) computation. Profiles affected by anatomical variability or pathology were automatically excluded. TTF was then derived by differentiating the ESF and applying the Fourier Transform. Validation was done on a Mercury v4.0 phantom (26 and 31cm section, 14.5mGy, 120 kVp, gated aortic protocol). Images were reconstructed with iDose4 (level 4-6), 1mm slices, and kernels A-C. IQ-PAT was compared to ImQuest and applied to 20 patients. Phantom data showed that NPS and TTF values from IQ-PAT closely matched those from ImQuest. For each combination of reconstruction kernel and phantom diameter, noise magnitude, average spatial frequency (fav) and TTF at 50% (f50) values were not significantly different between IQ-PAT and ImQuest (all p>0.05). In patients, IQ-PAT exhibited trends consistent with phantom results across reconstruction settings. IQ-PAT provided reliable and consistent assessments of NPS and TTF on phantom images, with comparable results to ImQuest. Early application to patient data demonstrated the method's feasibility in clinical conditions.

The purpose of this study was to assess the performance of iterative reconstruction (IR) and deep-learning image reconstruction (DLR) algorithms developed by four CT vendors in terms of image quality. Acquisitions were performed on an image quality phantom at three dose levels (1.8, 6 and 11 mGy) using four CT systems (further referred to as G-CT, P-CT, U-CT, and C-CT). For each CT, raw data were reconstructed using the commonly used soft tissue kernel and level for IR and DLR algorithms. Noise power spectrum and task-based transfer function were computed to assess noise magnitude, noise texture (fav) and spatial resolution, respectively. Detectability indexes (d') were computed to model the detection of two abdominal lesions. Compared to IR, noise magnitude reduction with DLR was similar for all dose levels for G-CT (-21.1 ± 1.5 [standard deviation (SD)] %) and P-CT (-48.4 ± 0.1 [SD] %) but more pronounced at 1.8 mGy and decreased as the dose level increased for U-CT and C-CT. Noise texture was greater with DLR than IR at all dose levels for all CT systems, except for U-CT, which gave similar fav values. For both inserts, spatial resolution was better with DLR than with IR for all CT systems, except for the low-contrast insert with C-CT at 1.8 and 6 mGy and P-CT at 1.8 mGy. For both simulated lesions and all dose levels, d' values were greater with DLR than with IR by 77.5 ± 8.7 (SD) % for C-CT, 33.7 ± 5.6 (SD) % for G-CT, 112.7 ± 4.7 (SD) % for P-CT and from 158.3 % to 546.6 % on average for U-CT. Compared to IR, DLR algorithms reduce the image noise and improve detectability whilst providing similar or better noise texture and spatial resolution.

To evaluate the image quality and clinical utility of high-resolution computed tomography (CT) images reconstructed using post-processing with a 1024 × 1024 matrix. Four CT image types were reconstructed: type A (512 × 512 matrix, 1-mm slice thickness), type B (1024 × 1024 matrix, 1-mm slice thickness), type C (1024 × 1024 matrix, 0.5-mm slice thickness), and type D (retargeted zoomed images; 512 × 512 matrix, 1-mm slice thickness). Type D images served as the reference standard with a field of view (FOV) half that of the other image types. Phantom image quality was objectively assessed using the task transfer function (TTF), noise power spectrum (NPS), and attenuation profile analysis. In the clinical study, two radiologists independently evaluated image quality in 93 patients, including abnormal lung findings, normal structures, and subjective image noise. In the phantom study, post-processing 1024 × 1024 matrix reconstruction derived from the same sinogram as conventional 512 × 512 reconstruction improved spatial resolution while maintaining comparable noise characteristics at the same slice thickness. Clinically, image quality of normal structures and abnormal lesions was significantly higher in the order of type C > type B > type A (p < 0.0001). Subjective image noise followed the same order. Image quality and noise levels of type B images were comparable to those of type D images. Post-processing 1024 × 1024 matrix reconstruction improves spatial resolution and provides clinically useful high-resolution CT images comparable to retargeted zoomed reconstruction without the limitation of a reduced FOV.

This study investigates the behavior of single-anchored steel sheet pile walls used as temporary retaining systems in medium-depth excavations ranging from 5 to 6 meters in depth. A series of parametric analyses were performed using PLAXIS 2D under static conditions to evaluate the effects of excavation depth, soil internal friction angle, unit weight, and vertical anchor position on wall performance. Consequently, the optimum vertical distance of the anchor from the ground surface was determined to be between 0.25 and 0.3H in terms of displacement. The results of the numerical simulations provided the basis for developing a predictive model for maximum horizontal wall displacement. To obtain accurate, generalized predictions, a hybrid Artificial Neural Network (ANN) model optimized using the Harris Hawks Optimization (HHO) algorithm was developed. In this approach, HHO was used to optimize the ANN hyperparameters, including transfer functions and the number of hidden-layer neurons. The findings highlight the potential of combining finite element analysis with hybrid soft-computing approaches to enhance the design and performance evaluation of anchored retaining systems in temporary excavations.

Elucidating the quaternary structures of protein complexes under physiological conditions remains a central challenge for structural biology. Here, we introduce an integrative analytical pipeline that combines size exclusion chromatography (SEC), Taylor dispersion analysis (TDA), native mass spectrometry (nMS), and artificial intelligence to resolve macromolecular architectures under near-native solution conditions. The workflow begins with the SEC-based separation of heterogeneous mixtures, followed by online TDA in a PEEK capillary to probe hydrodynamic behavior via laminar-flow-induced dispersion. By deconvolving pre- and postdispersion chromatograms, a system transfer function is derived and subjected to Gaussian fitting to yield precise measurements of hydrodynamic radii. These experimentally derived radii are subsequently applied as biophysical constraints in an AlphaFold 3-based structural selection process. We validated this method using a six-protein model mixture, demonstrating its ability to simultaneously determine the hydrodynamic radii of individual components within complex mixtures. The methodology was further applied to three protein complexes (FCGRT-B2M, streptavidin, and concanavalin A), allowing for the precise measurement of their oligomeric hydrodynamic radii and the determination of their quaternary structures. By bridging high-resolution analytical chemistry with AI-driven structural prediction, this strategy offers a robust experimentally grounded framework for characterizing macromolecular assemblies.

Design and integration of a novel bioreactor for articular cartilage tissue manufacturing with real-time feedback of chondrogenic gene expression

Kinematic interaction (KI) effects arising from foundation embedment alter the motion transmitted from the free field to the foundation level and can therefore influence the seismic demands imposed on structures. Although several analytical formulations and guideline-based procedures exist to represent these effects, their accuracy when used directly to modify design and response spectra has not been thoroughly validated against real ground-motion data. This study provides a systematic evaluation of two widely used KI approaches; (i) the analytical transfer functions of Elsabee and Morray (1977) and (ii) the spectral-modification procedure of FEMA-440 (2005). Using a large suite of recorded motions, free-field and foundation input motions are computed through frequency-domain modification, and corresponding acceleration response spectra are obtained to form computed spectral ratios. These computed ratios serve as a benchmark for assessing the predictive performance of the simplified KI procedures across a range of embedment-to-stiffness conditions. The results show that analytical KI factors substantially underestimate short-period spectral ordinates, whereas FEMA-440 captures overall trends more effectively but loses accuracy for larger embedment depths. The study defines practical ranges in which simplified KI procedures remain reliable and identifies conditions that require more refined soil-structure interaction modelling. The findings provide engineers with clearer guidance for incorporating KI effects in seismic analysis and design.

Among the diverse forms of cyber-attacks, false data injection (FDI) attacks are prone to occur and have become prominent threats. The present paper is concerned with the design of data-driven controllers of unknown cyber physical systems (CPSs) subjected to FDI attacks, using input-state data but no model knowledge. A core aspect of this issue revolves around the modelling of unknown FDI attacked system in the context of data-driven control. To solve the problem, we formulate an FDI attacks as a convex optimisation problem using the H 2 -norm, a FDI attacks channel model, and stability constraints. First, based on the input-state data sequences, the optimal feedback control law is designed to minimise the H 2 -norm of the closed-loop system's transfer function. The attacker's capability is modelled as a bounded constraint on attack power. The Schur complement lemma and a regularisation term provide sufficient conditions for the Schur stability of the FDI attacked system. The effectiveness of the proposed approach can be proved through a numerical example.

As an indispensable part of modern diagnosis and image-guided therapy, medical X-ray imaging requires detector materials that combine low-dose operation, high spatial resolution, fast response, energy-resolved capability, long-term stability, and scalable integration. Metal halide perovskites are promising candidates for high-performance and low-cost X-ray absorbers, because their strong X-ray attenuation, tunable composition, defect tolerance, favorable charge transport, and low-temperature processability enable both direct- and indirect-conversion detector designs. However, clinical translation cannot be assessed only by sensitivity or detection limit. Practical medical detectors must also satisfy requirements in modulation transfer function, noise power spectrum, detective quantum efficiency, lag/ghosting, dynamic range, pixel uniformity, readout compatibility, radiation durability, and safety. These requirements define a key gap between laboratory demonstrations and practical clinical applications. This review examines perovskite-based X-ray detectors from a materials-to-medical-images perspective. Conventional detector materials are first considered as reference platforms for defining clinical imaging requirements. Recent progress in perovskite-based X-ray detectors is then discussed with emphasis on their relevance to clinical imaging. Finally, the key barriers to clinical implementation are analyzed. By linking material properties, detector architectures, imaging metrics, and modality-specific requirements, this review outlines a translation roadmap for perovskite-based X-ray detectors toward future low-dose, high-resolution, and energy-resolved clinical imaging.

Abstract The genus Lobostemon (Boraginaceae) comprises 28 shrubby species endemic to the Cape Floristic Region of South Africa. We investigated mature wood structure in 11 species and examined correlations between wood traits, plant stature, and climate to clarify the adaptive roles of living fibre-tracheids, vessel dimorphism, and related features. Vestured intervessel pits proved characteristic of Lobostemon . Contrary to the view that fibre-tracheids with living protoplasts are juvenile (Frankiewicz et al., 2024), we found that the ground tissue of mature wood is largely composed of these elements. Their bordered pits may facilitate the release of stored water into the transpiration stream, thereby enhancing hydraulic capacitance. Grouping of wider vessels increased with aridity and continentality, suggesting a role in sustaining water transport during seasonal drought by forming subsidiary pathways around embolized vessels. By contrast, the percentage of solitary narrow vessels positively associated with milder hot seasons, suggesting their function in capillary water storage and lateral transfer between vessels and fibre-tracheids, also supporting hydraulic capacitance. Increased plant stature in drier habitats likely reflects the need for greater stem storage capacity, consistent with an avoidance strategy that allows Lobostemon species to withstand seasonal drought.