The socket shield technique (SST) preserves peri-implant tissues during immediate implant placement in teeth with intact roots, yet its biomechanical behavior in the presence of vertical root fractures (VRFs) remains unquantified. This study evaluated the mechanical feasibility of a modified multi-shield SST (MS-SST) designed for single-fracture-line scenarios in maxillary central incisors. Three-dimensional finite element models representing conventional immediate implantation (CII), classic SST (C-SST), and MS-SST were subjected to 45° oblique occlusal loading from 10 to 100 N in 10 N increments. Bone and tooth structures were modeled as heterogeneous isotropic materials based on computed tomography gray values, whereas the periodontal ligament (PDL) was simulated using a nonlinear first-order Ogden hyperelastic constitutive law. Biomechanical metrics included von Mises stresses on the implant and abutment, displacements of the shield and PDL, hydrostatic pressure in the PDL and peri-implant bone, and strain energy density (SED) of the peri-implant bone. Comparative response patterns remained consistent across all loading magnitudes. At the representative peak load of 100 N, CII produced the most unfavorable peri-implant bone response, with the highest hydrostatic pressure (compressive: 26.94 MPa; tensile: 37.67 MPa) and SED (0.0447 MPa). C-SST yielded the lowest peri-implant SED (0.0302 MPa) and implant-abutment stresses. MS-SST exhibited intermediate SED (0.0347 MPa) and stress magnitudes, while reducing adverse peri-implant bone mechanical indicators relative to CII. Although MS-SST generated higher tensile hydrostatic pressure within the PDL than C-SST (0.0304 vs. 0.0166 MPa), shield displacement remained comparably low (0.0101 vs. 0.0104 mm). Within the assumptions of this finite element model, MS-SST appears mechanically feasible as a compromise design for vertically fractured maxillary central incisors when preservation of an intact buccal shield is not possible. Buccal shield segmentation did not markedly compromise shield stability and reduced adverse peri-implant biomechanical environment relative to CII. Further experimental and clinical validation remains necessary.
This study investigated the biomechanical effects of multidirectional maxillary repositioning combined with mandibular advancement and rotation on temporomandibular joint (TMJ) components using patient-specific finite element analysis. Patient-specific three-dimensional models, reconstructed from the preoperative computed tomography (CT) data of six distinct patients presenting with varying dentofacial deformities, were used to generate the six virtual orthognathic surgery configurations, including isolated mandibular advancement, bimaxillary repositioning, vertical maxillary movements, and asymmetric rotational components.
Under identical loading and boundary conditions, stress distributions in the condyle, articular disc, and glenoid fossa were evaluated. The results showed that isolated mandibular advancement produced higher and more asymmetric stress concentrations, whereas bimaxillary configurations resulted in lower and more homogeneous stress distribution. Vertical maxillary repositioning and rotational asymmetry increased unilateral and unbalanced joint loading. These findings suggest that bimaxillary surgical approaches may provide a more favorable biomechanical environment for the TMJ, while large mandibular advancements and rotational components should be planned cautiously because of their potential to increase postoperative joint loading.
.
BACKGROUND:The great saphenous vein (SV) is widely used for coronary artery bypass grafting (CABG), but vein graft failure remains associated with endothelial injury and intimal hyperplasia. Sophisticated ex vivo platforms can reproduce complex coronary hemodynamics, yet their construction, operating cost, space requirements, and culture throughput may limit routine laboratory use. 
Methods: We developed a simple and economical in vitro vessel culture system (VVCS) comprising a custom Petri dish, a closed tubing circuit, a peristaltic pump, a pressurized medium bag, and pressure monitoring. Human SV segments from three CABG patients were cultured for 14 days under steady-direction perfusion and pulsatile pressure of 80/120 mmHg at a pump setting of 60-80 RPM. Histology, CD31 immunostaining, and EVG staining were used to assess early remodeling. 
Results: No contamination was observed during 14 days of culture. Histology demonstrated lumen dilation, medial fiber rearrangement, and focal structural injury. Endothelial coverage decreased in all three samples (Wilcoxon P = 0.25). Mean intimal thickness increased by 1.63-2.35 μm; the donor-level Wilcoxon test yielded P = 0.25, while a repeated-measures linear mixed-effects analysis estimated a mean increase of 2.07 μm (95% CI, 1.75-2.40 μm; P = 5.49 x 10^-5). 
Conclusion: The VVCS combines a compact architecture, low medium demand, efficient parallel culture, and sustained pulsatile-pressure conditioning. It provides an accessible model for investigating SV early pressure-associated remodeling after CABG and establishes a foundation for subsequent studies.
Objective assessment of physical activity in children and adolescents supports school health surveillance and the evaluation of behavioral interventions, but wearable recognition models are typically developed on adults, public benchmarks, or sample-level data splits that do not test performance on new users. Baseline models also encode the inertial stream alone and carry no description of the individual, leaving developmental differences in body size and movement execution uncorrected. This study developed the Anthropometry-Aware Temporal Attention DeepConvLSTM (AATA-DeepConvLSTM) model for single-label 22-class activity recognition from a chest-worn school-badge inertial measurement unit (IMU). It combines convolutional-recurrent encoding of eight inertial channels (triaxial acceleration and angular velocity at 100 Hz plus their magnitudes), temporal attention pooling, and representation-level fusion of age, sex, height, body weight, and body mass index as subject-level context. After quality control, 4,666 activity records from 128 participants aged 5-18 years were analyzed under subject-independent five-fold cross-validation, with record-level macro-averaged F1 (Macro-F1) as the primary metric. AATA-DeepConvLSTM reached a record-level accuracy of 0.9377 and a Macro-F1 of 0.9291, against 0.9092 and 0.8992 for the strongest baseline, DeepConvLSTM. In ablation, temporal attention alone raised Macro-F1 from 0.8992 to 0.9112 and real anthropometric context raised it to 0.9291, whereas shuffling the anthropometric values across participants returned it to 0.9117; height alone recovered 0.9264. Static postures remained the weakest classes. These results support anthropometry-aware wearable-signal modeling as a feasible engineering approach for pediatric activity assessment, while naturalistic validation and stable calibration protocols remain necessary before routine school-based deployment.
Accurate measurement of tooth displacement is essential for orthodontic treatment planning and outcome evaluation. In routine practice, however, commonly used methods such as manual caliper measurement are constrained by limited resolution, marked operator dependence, and low efficiency when repeated measurements are required. This study proposes a fully automated image-based measurement framework in which orthodontic brackets are detected as anatomical reference markers using a YOLOv11-based detection model. The detected brackets are then automatically sorted, classified into maxillary and mandibular groups, and used for scale-normalized distance calculation, enabling high-precision displacement measurement. The method can support real-time longitudinal monitoring during orthodontic treatment and retrospective quantitative analysis of archived clinical images. Evaluation on an intraoral clinical dataset from six orthodontic patients showed that the model achieved an average mAP@0.5 of 95.4% and a precision of 97.9% in patient-level cross-validation, with an average processing time of 40 ms per image. The system measurement resolution reached 0.01 mm. In 140 clinical gauge-block validation measurements, the mean absolute error was 0.028 mm, and all errors were within 0.05 mm. These results indicate that the proposed system provides a rapid, accurate, and repeatable solution for clinical assessment of orthodontic tooth displacement.
This study investigates a fig-based phantom material for benchtop evaluation of endovascular devices intended for treatment of chronic post-thrombotic venous obstruction, a common sequela of deep vein thrombosis (DVT). The proposed phantom is designed to reproduce selected functional mechanical characteristics relevant to device interaction with fibrotic, organized post-thrombotic lesions, is fabricated using controlled aging durations and temperatures to tune its mechanical properties. Phantom formulations were evaluated by combining clinician haptic feedback (device-mediated resistance and force transmission) assessment with uniaxial compression testing. Haptic feedback evaluation was performed by experienced interventional clinicians using a 1-10 similarity scale to assess correspondence with clinical recanalization procedures. Compression testing demonstrated formulation-dependent differences in mechanical behavior, while clinician evaluations indicated comparable levels of perceived procedural realism across the tested formulations. Exploratory correlation analyses revealed positive associations between compressive resistance and clinician similarity scores, although these relationships did not reach statistical significance. The fig-based phantoms exhibited a reproducible nonlinear compression response with strain-dependent stiffening, resembling the mechanical behavior of organized post-thrombotic tissue. Together, these results support the feasibility of using fig-based materials as controlled and reproducible surrogate lesions for functional benchtop testing. Such a platform could complement higher-fidelity biological models by enabling accessible and standardized early-stage evaluation of endovascular devices for chronic venous recanalization.
Osteonecrosis of the femoral head (ONFH) often presents with nonspecific early symptoms, which may lead to missed or delayed diagnosis. Gait abnormality is an important functional manifestation of ONFH, and wearable inertial measurement unit (IMU)-based gait analysis may provide a portable and non-invasive approach for auxiliary assessment. In this study, we developed a wearable IMU-based gait-cycle signal processing and modeling framework for preliminary auxiliary identification of ONFH. Raw multichannel gait signals were segmented into gait cycles, followed by cycle-level quality control and temporal normalization to obtain fixed-length multichannel gait-cycle samples. A Multi-Scale Gated Attention Network (MSGA-Net) was further proposed to capture multi-scale temporal dynamics within gait cycles while controlling model complexity. The framework was evaluated at the subject level using leave-one-subject-out cross-validation and compared with advanced time-series models and conventional machine-learning baselines based on handcrafted gait features. Complementary feature-based and hierarchical occlusion analyses were conducted to examine model interpretability. MSGA-Net achieved a subject-level accuracy of 0.941, sensitivity of 0.810, specificity of 0.996, and AUC of 0.982 at the default threshold. The interpretability analyses suggested that the predictions relied on multiple gait characteristics rather than a single feature. A post hoc threshold-dependent analysis showed a trade-off between sensitivity and specificity in the present dataset. These findings suggest that wearable IMU-derived gait-cycle dynamics may contain discriminative information for distinguishing ONFH patients from healthy controls. The proposed framework provides preliminary feasibility evidence for IMU-based auxiliary identification of ONFH and warrants validation in larger independent cohorts before practical clinical use.
Accurate breast cancer subtyping guides treatment selection, yet
histopathology captures morphology without molecular state, while genomic
profiling captures molecular signatures without spatial context. Existing
fusion methods rely on concatenation, or on attention applied only after each
modality is encoded independently. This work identifies a scale-dependent
asymmetry in the direction of cross-modal conditioning: the direction that
performs best under limited samples is not the one that holds at scale, and
the reversal is traced to the capacity of the modulation pathway rather than
to the fusion principle. The comparison is carried out within a
hypernetwork-guided framework in which an auxiliary network maps one
modality to conditioning parameters that modulate the other's feature
representation, shaping features at the parametric level rather than the
decision stage; modulation is patient-specific rather than patch-specific.
Both directions are instantiated --- gene-to-image (HyperG2I) and
image-to-gene (HyperI2G) --- and trained under a label-aware MixUp strategy
that interpolates within-class samples across both modalities, preserving the
hard binary labels clinical decisions require. The framework is evaluated on
two paired TCGA-BRCA cohorts --- one limited-sample, one independently
assembled at scale --- under a single protocol spanning two whole-slide
representations, multiple visual backbones, and both conditioning directions.
On the limited-sample cohort, gene-to-image conditioning at its optimal
augmentation setting exceeds early fusion and both unimodal baselines, giving
the highest recall on the aggressive Basal/HER2 class of any configuration
evaluated, and an ablation favours intra-class over inter-class mixing. At
scale this ordering does not hold: image-to-gene conditioning sustains its
performance whereas gene-to-image does not, recovering only partially under
the full tissue bag and isolating the capacity of the modulation pathway as
the binding constraint. Direction and capacity of cross-modal conditioning,
rather than fusion depth alone, therefore govern how such frameworks scale.
BACKGROUND:Breast ultrasound segmentation is sensitive to external-domain shift caused by scanner, acquisition, annotation and appearance variation. Shadowing, gain and contrast variation are particularly relevant given that ultrasound is not an optical imaging modality, yet many segmentation reports still rely mainly on randomly split or source-overlapping validation. METHODS:We reformulated the study as a strict external validation analysis. Six model configurations-U-Net, CMU-Net, RTCMUNet, PMix, CGate and PMix+CGate-were evaluated under three source-composition protocols: all-source joint training, leave-BUS-UCLM-out training and leave-BUS-BRA-out training. BUS (n = 163) and BUSI-WHU (n = 927) were held out from training and validation under all protocols and used as fixed strict external out-of-distribution cohorts. The primary endpoint was image-level intersection over union (IoU), with paired image-level bootstrap (10,000 resamples) used to estimate 95% confidence intervals. A targeted source-inclusion sensitivity analysis additionally compared two training-pool compositions for RTCMUNet and PMix+CGate that differed only in whether a small set of previously excluded malignant-red lesion images from one source was added. RESULTS:PMix+CGate under all-source joint training achieved the highest average strict external out-of-distribution IoU across the two held-out cohorts (equal-domain mean 72.19). Against RTCMUNet trained without BUS-UCLM, the cross-protocol delta was +1.32 percentage points; the 95% CI [-0.33, 2.98] crossed zero and did not support a cross-protocol advantage. In the source-inclusion sensitivity analysis, RTCMUNet and PMix+CGate responded in opposite directions to the same compositional change, producing a model-by-composition interaction in IoU (-4.31 percentage points, 95% CI [-6.66, -2.15]) whose image-sampling interval excluded zero. CONCLUSION:PMix+CGate achieved the highest average strict external out-of-distribution IoU under all-source joint training, but its cross-protocol advantage over RTCMUNet was not supported by an interval that crossed zero. The source-inclusion analysis further indicates model- and cohort-dependent sensitivity to training-pool composition, rather than a universal benefit from adding data or a universally preferred configuration.
BACKGROUND AND OBJECTIVE:Compared with lateral locking plate (LLP) fixation, dual‑plate (DP) fixation has not demonstrated superior clinical outcomes in the treatment of distal femur fractures (DFFs). We propose that this discrepancy arises from unclear indications. 
Methods: Finite element analysis was conducted to compare the biomechanical performance of LLP-only versus DP fixation in AO/ASIF type C2 fractures with varying metaphyseal defect sizes (0, 5, 10, 15, 20, 25, and 30 mm). Fourteen models were established and subjected to axial (700 N) and torsional (14 Nm) loading. 
Results: As the metaphyseal defect size increased (0-30 mm), all measured parameters under axial compression and torsional loading exhibited consistent trends. Overall, changes were more pronounced in the LLP-only group. Under axial loading, increasing defect size led to a 95.2% reduction in axial stiffness, a 58.2-fold increase in axial displacement, and 7.7 times rise in the maximum equivalent stress of the LLP-only fixation. 
Conclusions: This study demonstrates that larger metaphyseal defects result in decreased fixation stiffness, increased fracture-site displacement, and elevated plate stress, including in the medial plate of DP constructs. These changes are consistently less pronounced with DP fixation compared to LLP -only constructs. Biomechanically, a transitional range exists between the two methods, with a mechanical suitability threshold near a metaphyseal defect size of 15 mm.
To support the analysis of compact hollow-fiber dialyzers operated under low-flow conditions relevant to wearable artificial kidney development, a mechanistic model of multisolute transport was developed. Unlike conventional homogeneous-membrane descriptions, the dialysis membrane was represented as a three-layer asymmetric porous structure. Within a continuum framework, pore-scale hindered diffusion, ultrafiltration-driven convection, and transmembrane hydraulics were coupled to describe diffusion-convection transport under low-flow conditions. Comparisons with manufacturer-stylein vitroclearance data from commercial low-flow dialyzers showed that the model captured the main clearance trends of representative solutes under selected operating conditions. Apparent resistance decomposition further suggested that, under the baseline condition and the present resistance definition, the apparent blood-side boundary-layer fraction increased with solute size, whereas the apparent intramembrane fraction decreased. Parametric analyses were further conducted to examine the effects of selected operating and geometric factors in this model. The proposed framework may support preliminary numerical screening and mechanistic interpretation of compact dialysis-module concepts under wearable artificial kidney-relevant low-flow conditions.
Current testicular prostheses are predominantly manufactured from silicone elastomers and often fail to reproduce the biomechanical and viscoelastic characteristics of native testicular tissue. This study aimed to develop and mechanically characterize a poly(vinyl alcohol) (PVA) hydrogel-based testicular prosthesis with tissue-mimicking properties. PVA hydrogels with concentrations of 5%, 10%, and 15% (w/v) were fabricated using a freeze-thaw crosslinking process and evaluated through comprehensive mechanical testing, including uniaxial compression, tensile testing, stress relaxation, creep, dynamic mechanical analysis (DMA), and cyclic compression fatigue testing. A prototype hydrogel testicular prosthesis was subsequently fabricated and its mechanical performance compared with native testicular tissue and a commercially available silicone implant. Mechanical behavior was strongly dependent on polymer concentration. Increasing PVA concentration resulted in significant increases in compressive modulus, tensile strength, toughness, storage modulus, and fatigue resistance. The 10% PVA hydrogel demonstrated the closest overall agreement with native tissue, exhibiting a compressive modulus of 78 ± 10 kPa compared with 64 ± 12 kPa for native tissue, while maintaining comparable tensile strength, recovery ratio, and energy dissipation characteristics. Viscoelastic characterization revealed tissue-like stress relaxation and creep responses, whereas cyclic compression testing demonstrated stable mechanical performance over 1000 loading cycles. In contrast, the silicone implant exhibited lower compliance, reduced energy dissipation capacity, and inferior overall biomechanical similarity to native tissue. These findings demonstrate that freeze-thaw PVA hydrogels provide a promising platform for biomimetic testicular prostheses. By tailoring polymer concentration, hydrogel implants can achieve mechanical and viscoelastic properties that more closely replicate native tissue than conventional silicone devices. The proposed hydrogel-based approach may improve implant realism and patient outcomes, providing a foundation for future long-term durability studies and in vivo evaluation.
Most mandibular finite element models are deterministic and overlook the influence of biological and modeling variability. This study proposes an automated, uncertainty-aware computational workflow for a patient-specific mandibular FE model using Latin Hypercube Sampling and sparse Polynomial chaos expansion. We investigated 24 input parameters related to masticatory muscle loading, material properties, and geometric discretization over 2400 simulations. Global and regional sensitivity analyses were performed using both Spearman rank correlations and variance-based Sobol indices to identify the primary drivers of von Mises stress. Within this modeling framework, muscle force magnitudes and articular disc stiffness are the dominant sources of stress variability, whereas high-resolution bone property classification had a negligible influence within the explored ranges. Statistical convergence analysis demonstrated that contact-sensitive condylar regions require significantly larger sample sizes (N> 2000) for stable sensitivity estimates compared to global metrics. This methodological benchmark identifies critical modeling parameters and provides a scalable pipeline for future patient-specific biomechanical studies and cohort-level simulations.
Existing evaluations of IMU-based joint angle estimation mainly rely on global accuracy metrics, which may obscure local error exposure during complex functional movements. This study analyzed data from 16 healthy male participants in the Hip-ROM-Y dataset. Using leave-one-subject-out outputs from a unified left hip joint predictor, we characterized left hip angle estimation errors by movement category, normalized movement phase, and high-error segment. The relationship between error distribution and post hoc disturbance features was further examined. The results showed that, under the current model and data conditions, complex movements (CMs) generally produced higher errors than basic movements. However, the increase in error was not uniformly distributed, but was mainly concentrated in local mid-phase periods of several CMs and was accompanied by greater deviations in the relative relationship between the pelvis and thigh segment. These findings suggest that evaluations of hip angle estimation under similar wearable configurations should pay attention to local error distributions during CMs and to the stability of the pelvis-thigh segment relationship.
Clinical gait analysis is essential for understanding motor and cognitive contributions to mobility impairment. Continued methodological advancement in gait analysis is needed to detect important and subtle changes in walking behaviour that will inform this understanding. This study evaluated the reliability of a finite state machine (FSM) algorithm for stride segmentation during preferred and dual-task walking (DTW) and examined changes to temporal and accelerometry kinematic outcomes between tasks. Participants diagnosed with Alzheimer's disease or mild cognitive impairment completed a gait assessment as part of the Ontario Neurodegenerative Disease Research Initiative foundational study. Ankle-worn accelerometers and a GAITRite walkway captured data during preferred walking and three DTW conditions (counting backwards by ones, animal naming, counting backwards by sevens). Acceleration data were processed using the FSM algorithm to extract temporal and accelerometry kinematic outcomes defined by the FSM intra-stride segments. Stride time demonstrated excellent reliability (ICC ⩾ 0.97). Gait speed was significantly associated with gait variability during animal naming and counting backwards by sevens (p< 0.05), but not during counting backwards by ones. The FSM approach showed changes to intra-stride phases and accelerometry derived kinematics not seen with conventional stride-based approaches. There was a reduction in flat-foot phase and an increase in push-off phase across all dual-task conditions compared with PREF (p< 0.05), where conventional stance-phase segmentation did not show consistent differences. Kinematic outcomes were also significantly lower during DTW conditions when compared to preferred walking trials (p< 0.05) for the mid-swing peak amplitude and the slope of the accelerometer push-off. Findings demonstrate differences in performance between preferred and DTW conditions, the influence of gait speed on gait variability, and unique accelerometry-derived kinematics. The FSM segmentation method advances gait assessment by providing precise stride characteristics using low-cost, clinically accessible tools.
Compared with conventional needle-based injections, needle-free injections offer several advantages, including ease of operation and elimination of accidental needlestick injury. To investigate the influence of piston structure on the performance of a needle-free injection system, this study combined experiments with fluid-structure interaction numerical simulations to systematically examine the effects of groove length (L), groove height (H), and the spacing (L0) between the two grooves on jet performance and piston stress. The results showed that during the initial stage of needle-free injection, both the stagnation pressure and jet velocity exhibited pronounced oscillatory behavior, and the driving structure played a significant role in modulating this oscillation pattern. For the single-groove piston, as the groove volume increased fromL= 0 mm,H= 0 mm toL= 3 mm,H= 0.13 mm, the peak stagnation pressure increased by 22.3%, whereas the maximum von Mises stress in the piston rose from 0.53 MPa to 7.21 MPa. Based on the optimal single-groove configuration, the groove was further divided into a dual-groove structure with identical groove length and height. The results indicated that, as the dual-groove spacingL0increased from 0 to 1.5 mm, the maximum von Mises stress first rose sharply to a peak, then decreased to approximately 3 MPa atL0= 0.25 mm, and remained nearly stable forL0> 0.25 mm. Meanwhile, the peak stagnation pressure gradually decreased with increasing groove spacing. Considering the combined variation in peak stagnation pressure and structural stress,L0= 0.25 mm was identified as the optimal groove spacing. Compared with the optimal single-groove structure, the corresponding dual-groove configuration resulted in a reduction of less than 1% in peak stagnation pressure, while reducing the maximum von Mises stress by 58.4%.
Accurate restoration of the centre of rotation (CoR) is crucial for the long-term success of a total hip replacement (THR); however, cup positioning remains one of the major challenges of this procedure. The aim of this study was to critically review the existing literature documenting CoR planning in THR. Specifically: 1. The rationale behind component placement; 2. The benefits and limitations of the current techniques used; and 3. Future directions and their application to clinical practice. Traditional two-dimensional (2D) templating, although widely used, has limited accuracy due to magnification errors and variability in patient positioning. Three-dimensional computed tomography (3D-CT) preoperative planning allows for a more precise estimation of CoR. Integration with robotic systems enables intraoperative execution of the plan but comes with high costs and a steep learning curve. Patient-specific instrumentation (PSI) provides a cost-effective alternative. Meanwhile, surgeon experience and intraoperative judgement remain crucial, particularly in patients with abnormal anatomy or deformities. Restoration of CoR within approximately 5 mm of the planned medial and superior position has been associated with improved biomechanical performance and implant longevity. While 2D templating can achieve this in most routine cases, 3D planning, robotic-assisted surgery, and PSI allow for more accurate placement. This is particularly useful in complex cases, such as revisions or developmental dysplasia of the hip, where the risk of clinically significant deviations remains high and more targeted surgical strategies are needed.
Beam-hardening and material cross-contamination remain significant challenges in quantitative computed tomography of multi-component samples acquired using polychromatic x-ray sources. In this work, a polychromatic quantitative absorption tomography (QAT) technique is extended to reconstruct component-specific density distribution maps in a two-component sample. The technique decomposes projection sinograms acquired under two distinct incident x-ray spectra into component-specific column density sinograms using a spectral forward model. Residual cross-contamination artifacts are addressed using a quantitative correction procedure based on spatial reference masks obtained by segmenting conventional linear attenuation reconstructions. Contaminated regions are identified from these masks and reinterpreted in the sinogram domain using the same polychromatic forward model prior to back-projection. Experimental validation was performed on an intertwined Al-Cu wire sample. The proposed correction improves material separation, reduces streak artifacts, and brings reconstructed densities within one standard deviation of independently measured average densities of the components. Together, the extended QAT technique and quantitative correction procedure provide a physically consistent methodology for improved quantitative densitometry in multi-component samples, with extensibility to samples containingcomponents.
Surface irregularities can substantially modify local hemodynamics within coronary arteries. This study experimentally investigated the influence of controlled grooved surface geometries on pulsatile flow characteristics using idealized coronary-type stenosis models. Four transparent models were fabricated, consisting of a smooth control and three grooved surfaces with increasing groove amplitudes. Time-resolved particle image velocimetry was employed to quantify phase-averaged velocity fields, recirculation structures, and turbulent kinetic energy (TKE). The results showed that groove-induced surface irregularities enhanced jet deflection, near-wall recirculation, and in-plane cross-stream motion compared with the smooth stenosis model. As groove amplitude increased, downstream jet deflection became more pronounced, indicating a redistribution of velocity fluctuations in the post-stenotic region. In contrast, the smooth stenosis sustained a longer and more coherent jet structure. Increased groove amplitude also reduced the downstream extent and magnitude of measured planar TKE. These findings demonstrate that even small-scale surface features can significantly alter post-stenotic flow structures and the spatial development of turbulence under coronary-relevant pulsatile flow conditions.
Quantitative gait analysis is an important tool in clinical assessment and biomechanical research. Vision-based motion capture systems used in dedicated gait laboratories are considered the reference standard, providing highly accurate kinematic measurements, but they require specialized infrastructure and controlled environments. As a result, wearable inertial sensor systems have become a practical alternative for clinical and everyday gait assessment. This study presents a comparative evaluation of a smartphone-based gait analysis method and a clinically established wearable inertial system. Gait recordings representing healthy, mildly asymmetric, and impaired walking patterns were analysed using both approaches. The comparison focused on clinically relevant parameters, including cadence, swing-phase duration symmetry, and vertical acceleration symmetry. The smartphone-based method employs median-based statistics and robust outlier rejection to enhance reliability under non-ideal measurement conditions. For healthy and mildly asymmetric gait, both systems produced comparable parameter estimates. In gait patterns with pronounced imbalance, the smartphone-based method detected larger deviations, indicating enhanced sensitivity to asymmetry and pathological alterations, highlighting the benefits of robust statistical modelling when gait data deviate from Gaussian distributions. These findings demonstrate a strong level of agreement between the proposed smartphone-based method and a clinically established wearable inertial system while supporting the practical applicability and robustness of the approach for quantitative gait assessment. The method provides gait parameters comparable to those obtained with a wearable reference system while maintaining stable performance across different walking conditions. Its low instrumentation requirements and applicability outside laboratory settings make it suitable for rehabilitation follow-up, fall risk assessment, and repeated gait evaluation over time.
