Search Results (320)

T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive hematologic malignancy, typically presenting with systemic symptoms and mediastinal involvement. Leukemia cutis (LC) and renal infiltration are rare, especially at disease onset. A 27-year-old man presented with a solitary scalp lesion without systemic symptoms or hematologic abnormalities. Histopathology revealed a blastoid lymphoid infiltrate with a T-ALL immunophenotype. Two weeks later, laboratory tests showed leukocytosis, lymphocytosis, and renal dysfunction. Imaging revealed a large mediastinal mass, scalp soft tissue involvement, and bilateral renal infiltration. Bone marrow biopsy confirmed T-ALL with a mature phenotype. FISH identified TRAD:NKX2 rearrangement and CDKN2AB deletion. The patient received three cycles of pediatric-inspired chemotherapy, achieving complete molecular remission and resolution of extramedullary disease. He subsequently underwent allogeneic hematopoietic stem cell transplantation (HSCT) from an HLA-matched sibling. Post-transplant complications included febrile neutropenia and mucositis. On day +100, he remained in minimal residual disease (MRD)-negative remission. This case illustrates a rare presentation of T-ALL with isolated skin involvement and renal infiltration at diagnosis, highlighting the importance of early biopsy and immunophenotyping of atypical skin lesions. Intensive chemotherapy followed by HSCT represents a viable strategy for young adults with high-risk T-ALL and extramedullary disease. Full article

Vibrio is a genus of ubiquitous aquatic bacteria that includes numerous pathogenic species. Their remarkable genomic plasticity and rapid evolution make them of particular interest from both clinical and ecological perspectives. Successful infection by Vibrio species often relies on multiple virulence factors, including secreted enzymes. Here, we report the characterization of a novel environmental Vibrio strain isolated from a wild octopus that developed fulminant septicaemia accompanied by widespread soft tissue lysis. These severe symptoms prompted a detailed investigation into the bacterium’s identity and enzymatic profile, focused on proteases as potential virulence factors. Multi-locus sequence analysis placed the isolate within the Harveyi clade but revealed no perfect match to known strains, supporting its designation as a novel strain. Biochemical assays demonstrated strong proteolytic—including collagenolytic—activity, which makes this strain a promising source of enzymes for biotechnological applications. Full article

Traditional pneumatic soft grippers often suffer from a limited contact area and poor shape-matching performance, restricting their effectiveness in handling objects with complex or delicate surfaces. To address this problem, this study proposed an integrated soft gripper that combines pneumatic actuators with specially designed mechanical metamaterials, aiming to optimize deformation characteristics and enhance gripping surface conformity to target objects. The key contributions are as follows: (1) A novel integrated structure is designed, incorporating pneumatic actuators and mechanical metamaterials. (2) A highly efficient design framework based on deep learning is developed, incorporating forward and inverse neural networks to enable efficient performance prediction and inverse design. (3) The novel gripper is fabricated using stereolithography (SLA) and silicone casting, with experimental validation conducted via machine vision and multi-shape object tests. FEA simulations and experiments demonstrate significant improvements in shape matching: average deviations of gripping surfaces from targets are greatly reduced after optimization. This work validates that integrating mechanical metamaterials with data-driven design enhances the gripper’s adaptability, providing a feasible solution for high-performance soft gripping systems. Full article

Overall sitting comfort is related to both static pressure distribution and dynamic human–seat interaction during vibration. This study proposes a simplified finite-element model of the seated human body that could potentially be used to assess overall sitting comfort. The static pressures of the seated human body measured on a rigid seat with different footrest layouts, together with the overall and localised apparent masses of the human body measured in a previous study, were used for model validation. The proposed model contained homogeneous soft tissues of the buttocks and thighs and rigid bodies connected to represent the torso. The tissue geometry was adjusted to match the measured anthropometry. Viscoelastic material was assigned to the tissues, and the properties were identified by fitting the modelled pressures and apparent masses to the measurement results. The proposed model was capable of reproducing static pressures and dynamic forces over the seat for the three sitting postures. Full article

This article deals with the analysis and exploration of the concept of integrating human knowledge (HK) and artificial intelligence (AI) in the management process. The authors point out that the implementation of advanced AI technologies into already functioning and often complex systems, such as enterprise resource planning (ERP), presents significant technical challenges and requires a well-thought-out integration strategy. The complexity arises from the need to align new solutions with existing processes, resources, and data. Using the example of a fuel distribution system, the authors present the concept of integrating human knowledge (HK) and artificial intelligence (AI) in the management process. The article presents a comprehensive analysis of the smart upgrade of fuel delivery management (FDM) architecture by incorporating an AI app to solve complex problems, such as predicting demand or traffic flows, as well as correctly detecting near-miss events. Technological convergence enables the mutual pursuit of improving the management process by developing soft skills and expanding knowledge managers. The authors’ findings show that an important factor for successful convergence is horizontal and vertical matching of the human knowledge and artificial intelligence cooperation for archive max positive synergy. Some recommendations could be useful for tank truck operators as a starting point to predict demand patterns, smart route planning, etc., where an AI app could be very successful. Full article

Objectives: The objective of this study was to compare occlusal and articular characteristics between young adults with and without a confirmed diagnosis of sleep bruxism, through a case-control study based on polysomnography. Methods: We conducted a case–control study with probabilistic sampling, including 20 participants with a polysomnography-confirmed diagnosis of sleep bruxism and 20 age- and sex-matched controls. A clinical oral examination was conducted to identify wear facets, joint sounds, and soft tissue indentations. Occlusal relationships were analyzed using mounted models on a semi-adjustable articulator, evaluating interferences during working, balancing, and protrusive movements, premature contacts, attrition, and dental inclinations. Results: Sleep bruxism showed a higher frequency of temporomandibular joint sounds (35% vs. 5%; p = 0.017; w = 0.375) and left-side balancing interferences (p = 0.04; d = 0.723). Multivariate analysis revealed a moderate correlation between bruxism and the combination of joint sound and occlusal inclination (COR = 0.39; 95% CI: 0.19–0.57; I² = 0.0%). Joint sound showed a weak association with REM-related bruxism (COR = 0.29; 95% CI: 0.05–0.51; I² = 21.7%) and a moderate association with non-REM bruxism (COR = 0.41). The correlation with occlusal inclination was stronger during REM sleep (COR = 0.41) than during non-REM sleep (COR = 0.35; I² = 0.0%), indicating consistent and clinically relevant associations. Conclusions: Occlusal and functional characteristics associated with sleep bruxism were identified, particularly joint sounds and dental inclinations, although no direct causal relationship was established. These findings suggest the presence of specific morphofunctional patterns that may play a role in the clinical expression of sleep bruxism. Full article

In the absence of standard procedures for testing 3D-printed soft polymers, an experimental protocol was proposed to assess the suitability of Flexible 80A Resin for a pediatric trachea anatomical 3D model for surgical simulation. Eighteen specimens printed via stereolithography are involved, including anatomical, cylindrical, and dog-bone shapes, to investigate the geometry effect on measured properties. Static tensile tests revealed that using standardized dog-bone specimens as a reference for the material’s Young’s modulus leads to a mean absolute percentage error (MAPE) up to 50% compared to anatomical specimens. Measurement uncertainty combined repeatability with input errors, and the ANOVA test confirmed the need for dedicated mechanical measurements when evaluating complex 3D-printed geometries. The study concludes the suitability of selected material: the average elastic modulus of anatomical specimens was 4.75 MPa, closely matching values reported for tracheal tissue in the literature, with a MAPE of only 2%. Dynamic mechanical tests showed trachea-like viscoelasticity: anatomical specimens were consistently stiffer and more dissipative than cylindrical ones. Creep tests confirmed the viscoelastic behavior simulating airway time scales. The anatomical specimens exhibit faster local relaxation, while cylindrical ones show slower long-term relaxation, both modeled by a two-element generalized Maxwell model (R² = 0.99 and 0.98). Full article

In optical one-dimensional grating-on-layer planar structures, an optical resonance occurs when the incident light wave becomes phase-matched to a leaky waveguide mode excited in the layer underneath the grating by an appropriate tuning of the grating periodicity. Changing the refractive indices of the grating’s constituents, and/or thickness, changes the resonance frequency. In the case of a two-dimensional grating atop such a smooth layer, a similar and also cavity-mode resonance can occur. This idea has straightforward usage in diverse optical sensor applications. In this study, a novel guided-mode resonance sensor design for detecting glucose and hemoglobin in minute concentrations at a wide range of incidence angles is presented. In this design, materials of the grating, such as a polymer and cesium-lead halide with a perovskite crystal structure, are examined, which will allow flexible, low-cost fabrication by soft-lithography/imprint-lithography methods. The sensitivity, figure of merit, and quality factor are reported for one- and two-dimensional grating structures. The simulations performed are based on rigorous coupled-wave analysis. Optical resonance quality factor of ∼$5·{10}^5$ is achieved at oblique incidence for a structure comprising a one-dimensional grating etched in a poly-vinylidene chloride layer atop a silicon nitride waveguide layer on a substrate. Record values of the above-noted characteristics are achieved with a synergetic interplay of the materials, structural dimensions, incidence angle, polarization, and grating geometry. Full article

With the rapid growth of user service demands, space–air–ground integrated networks (SAGINs) face challenges such as limited resources, complex connectivity, diverse service requirements, and no-fly zone (NFZ) constraints. To address these issues, this paper proposes a joint optimization approach under NFZ constraints, maximizing system utility by simultaneously optimizing user association, unmanned aerial vehicle (UAV) trajectory, and slice resource allocation. Due to the problem’s non-convexity, it is decomposed into three subproblems: user association, UAV trajectory optimization, and slice resource allocation. To solve them efficiently, we design the iterative SAC-MS algorithm, which combines matching game theory for user association, sequential convex approximation (SCA) for UAV trajectory, and soft actor–critic (SAC) reinforcement learning for slice resource allocation. Simulation results show that SAC-MS outperforms TD3-MS, DDPG-MS, DQN-MS, and hard slicing, improving system utility by 10.53%, 13.17%, 31.25%, and 45.38%, respectively. Full article

Wearable systems are increasingly adopted for health monitoring and wellness promotion. Among the most relevant biosignals, the electrocardiogram (ECG) plays a key role; however, in wearable settings (e.g., during physical activity), it is often corrupted by electromyogram (EMG) interference. This study presents a novel adaptive algorithm, template masking (TM), which integrates the stationary wavelet transform (SWT) with template matching for denoising the ECG from EMG. The method identifies the optimal wavelet and decomposition level to maximise detail sparsity. To mitigate EMG interference, after alignment in the SWT domain with a template, the detail coefficients are multiplied by a binary mask and smoothed. TM was compared with soft and hard thresholding on (1) simulations combining clinical ECGs (MIT-BIH database) and synthetic EMGs with different signal-to-noise ratios (SNRs), and (2) experimental signals including ECGs acquired with dry electrodes corrupted by EMGs (SimEMG database, also varying SNRs), as a potential wearable scenario. In both cases, TM yielded significantly lower reconstruction errors at SNRs below 5 dB ($p<0.01$) and significantly outperformed thresholding in the sensitivity of R-peaks estimation ($p<0.001$). These results demonstrate the potential of TM, highlighting the value of adaptive denoising algorithms. Full article

Digital dentistry is undergoing rapid evolution, with three-dimensional imaging technologies increasingly integrated into routine clinical workflows. Originally developed for accurate dental arch reconstruction, modern intraoral scanners have demonstrated expanding versatility in capturing intraoral mucosal as well as perioral cutaneous structures. Concurrently, photogrammetry has emerged as a powerful method for full-face digital reconstruction, particularly valuable in orthodontic and prosthodontic treatment planning. These advances offer promising applications in forensic sciences, where high-resolution, three-dimensional documentation of anatomical details such as palatal rugae, lip prints, and bite marks can provide objective and enduring records for legal and investigative purposes. This study explores the forensic potential of two digital acquisition techniques by presenting two cadaveric cases of animal bite injuries. In the first case, an intraoral scanner (Dexis 3600) was used in an unconventional extraoral application to directly scan skin lesions. In the second case, photogrammetry was employed using a digital single-lens reflex (DSLR) camera and Agisoft Metashape, with standardized lighting and metric scale references to generate accurate 3D models. Both methods produced analyzable digital reconstructions suitable for forensic archiving. The intraoral scanner yielded dimensionally accurate models, with strong agreement with manual measurements, though limited by difficulties in capturing complex surface morphology. Photogrammetry, meanwhile, allowed for broader contextual reconstruction with high texture fidelity, albeit requiring more extensive processing and scale calibration. A notable advantage common to both techniques is the avoidance of physical contact and impression materials, which can compress and distort soft tissues, an especially relevant concern when documenting transient evidence like bite marks. These results suggest that both technologies, despite their different origins and operational workflows, can contribute meaningfully to forensic documentation of bite-related injuries. While constrained by the exploratory nature and small sample size of this study, the findings support the viability of digitized, non-destructive evidence preservation. Future perspectives may include the integration of artificial intelligence to assist with morphological matching and the establishment of digital forensic databases for pattern comparison and expert review. Full article

This study presents the development and validation of an automated oyster classification system designed to classify oysters by size and place them into trays for freezing. Addressing limitations in conventional manual processing, the proposed system integrates a vision-based recognition algorithm and a delta robot (parallel robot) equipped with a soft gripper. The vision system identifies oyster size and optimal grasp points using image moment calculations, enhancing the accuracy of classification for irregularly shaped oysters. Experimental tests demonstrated classification and grasping success rates of 99%. A process simulation based on real industrial conditions revealed that seven units of the automated system are required to match the daily output of 7 tons achieved by 60 workers. When compared with a theoretical 100% success rate, the system showed a marginal production loss of 715 oysters and 15 trays. These results confirm the potential of the proposed system to improve consistency, reduce labor dependency, and increase productivity in oyster processing. Future work will focus on gripper design optimization and parameter tuning to further improve system stability and efficiency. Full article

Background: Accurate differentiation of Parkinson’s disease (PD) from healthy aging is crucial for timely intervention and effective management. Postural sway abnormalities are prominent motor features of PD. Quantitative stabilometry and machine learning (ML) offer a promising avenue for developing objective markers to support the diagnostic process. This study aimed to develop and validate high-performance ML models to classify individuals with PD and age-matched healthy older adults (HOAs) using a comprehensive set of stabilometric parameters. Methods: Thirty-seven HOAs (mean age 70 ± 6.8 years) and 26 individuals with idiopathic PD (Hoehn and Yahr stages 2–3, on medication; mean age 66 years ± 2.9 years), all aged 60–80 years, participated. Stabilometric data were collected using a force platform during quiet stance under eyes-open (EO) and eyes-closed (EC) conditions, from which 34 parameters reflecting the time- and frequency-domain characteristics of center-of-pressure (COP) sway were extracted. After data preprocessing, including mean imputation for missing values and feature scaling, three ML classifiers (Random Forest, Gradient Boosting, and Support Vector Machine) were hyperparameter-tuned using GridSearchCV with three-fold cross-validation. An ensemble voting classifier (soft voting) was constructed from these tuned models. Model performance was rigorously evaluated using 15 iterations of stratified train–test splits (70% train and 30% test) and an additional bootstrap procedure of 1000 iterations to derive reliable 95% confidence intervals (CIs). Results: Our optimized ensemble voting classifier achieved excellent discriminative power, distinguishing PD from HOAs with a mean accuracy of 0.91 (95% CI: 0.81–1.00) and a mean Area Under the ROC Curve (AUC ROC) of 0.97 (95% CI: 0.92–1.00). Importantly, feature analysis revealed that anteroposterior sway velocity with eyes open (V-AP) and total sway path with eyes closed (TOD_EC, calculated using COP displacement vectors from its mean position) are the most robust and non-invasive biomarkers for differentiating the groups. Conclusions: An ensemble ML approach leveraging stabilometric features provides a highly accurate, non-invasive method to distinguish PD from healthy aging and may augment clinical assessment and monitoring. Full article

Adaptive optics transscleral flood illumination (AO-TFI) enables in vivo imaging of the retinal pigment epithelium (RPE) at near-cellular resolution. In this study, we evaluated its potential as a phenotyping tool in age-related macular degeneration (AMD) by analyzing disease-associated structural patterns and their correlation with optical coherence tomography (OCT) features. We examined AO-TFI images from 120 eyes diagnosed with either early-to-advanced dry AMD (including geographic atrophy, GA) or neovascular AMD (nvAMD). Images were graded by a masked reader, and patterns were matched to corresponding OCT findings. Four consistent morphologic patterns were identified: atrophy, pre-atrophy, soft drusen, and reticular pseudodrusen. Morphometric quantification of hyporeflective regions showed progressive changes in perimeter, diameter, and area from reticular pseudodrusen to soft drusen and pre-atrophy, returning to lower values in atrophy. Distinct nvAMD-specific signatures were not identified. AO-TFI offers a practical, high-resolution complement to OCT, AO-SLO, and AO-OCT for phenotypic characterization of AMD in clinical settings. Full article

Hybrid electric vehicles (HEVs) have gained significant attention for their superior energy efficiency and are becoming a predominant mode of urban transportation. The DC/DC converter plays a critical role in HEV energy management systems, especially in matching the voltage levels between the battery and DC bus. This paper proposes a novel high-gain DC/DC converter with a wide input voltage range based on coupled inductors. The innovation lies in the integration of a resonant cavity and the simultaneous realization of zero-voltage switching (ZVS) and zero-current switching (ZCS), effectively reducing both voltage/current stresses on the power switches and switching losses. Compared with conventional topologies, the proposed design achieves higher voltage gain without extreme duty cycles, improved conversion efficiency, and enhanced reliability. Detailed operating principles are analyzed, and design conditions for voltage stress reduction, gain extension, and soft switching are derived. The simulation model has been conducted in a PSIM environment, and a 300 W experimental prototype, implemented using a dsPIC33FJ64GS606 digital controller, has been established and demonstrates 93% peak efficiency at a 10 times voltage gain. The performance and practical feasibility of the proposed topology have been evaluated by both simulation and experiments. Full article