Search Results (798)

Background: Sacral and pelvic insufficiency fractures (SIFs and PIFs) are increasingly recognized yet frequently underdiagnosed complications after adult spinal deformity (ASD) surgery, particularly in patients undergoing long-segment spinal fusion to the sacrum or pelvis. Methods: We present a representative case of sacral and pelvic insufficiency fractures following extensive spinal fusion, highlighting diagnostic and therapeutic challenges. In addition, a systematic review of the literature was performed according to PRISMA guidelines through PubMed, MEDLINE, and Scopus databases, including studies up to December 2024. Data regarding demographics, risk factors, diagnostic modalities, management strategies, and outcomes were extracted and narratively synthesized. Results: A total of 21 studies comprising 89 patients were included. The majority were elderly postmenopausal women with osteoporosis and additional risk factors such as chronic corticosteroid therapy or high body mass index. Diagnosis was frequently delayed due to low sensitivity of plain radiographs, whereas computed tomography was the most reliable modality. Management was surgical in 49 patients (55%)—most commonly extension of fixation to the pelvis or use of S2-alar-iliac screws—with favorable fracture healing reported in most cases. Conservative treatment, employed in 40 patients (45%), included bracing, restricted activity, and bone health optimization, also leading to healing in the majority of cases. Conclusions: Sacral and pelvic insufficiency fractures represent an underrecognized but clinically significant complication after ASD surgery. Early recognition through cross-sectional imaging (CT/MRI) is crucial, and both surgical and conservative approaches can be effective if tailored to patient and fracture characteristics. Full article

Background: The intracranial space has limited capacity; thus, volume changes in any component can raise intracranial pressure and cause mass effect. This mechanism underlies many neurological disorders. Artificial Intelligence, increasingly applied in medicine and diagnostic imaging, may support the evaluation of such conditions. This systematic review investigates AI-based models for cerebrospinal fluid segmentation and analysis on computed tomography. Methods: In December 2024, a systematic review was conducted across MEDLINE (PubMed), Scopus, Web of Science, Embase, and Cochrane Library. From 559 identified studies, 14 were included after independent review by two evaluators. Extracted data covered study characteristics, AI model design, dataset composition, and performance metrics for CSF segmentation. Quality assessment followed PRISMA 2020 and used JBI, AMSTAR 2, and CASP checklists. Results: The 14 studies demonstrated applications of AI in CSF segmentation and volumetric assessment, primarily for hydrocephalus diagnosis, mass effect evaluation, and stroke outcome prediction. Convolutional Neural Networks and Random Forests were the most frequent approaches. Reported segmentation accuracy was high, with Dice Similarity Coefficient values ranging from 0.75 to 0.95 and strong volumetric correlations (r up to 0.99) between AI-based and manual measurements. Conclusions: AI-assisted CSF segmentation from CT images shows promising accuracy and efficiency, with potential to enhance neurological diagnostics. Remaining challenges include dataset variability, inconsistent algorithm performance, and limited clinical validation. Future research should prioritize standardization of methods, larger and more diverse training datasets, and integration of AI tools into clinical workflows. Full article

Rock mass characterization is crucial for evaluating slope stability and recommending effective prevention mechanisms. This study presents a comparative analysis of three approaches for discontinuity analysis: (1) conventional field survey, (2) digital manual measurement on 3D models generated with UAV-based photogrammetry, and (3) semi-automatic analysis based on clustering algorithms (K-NN) for point cloud segmentation. All three methods were applied to the same slope, allowing their performance to be evaluated in terms of accuracy, efficiency, and replicability. The results showed that the semi-automatic method achieved the highest coverage (81%) and identified 586 discontinuities, with RMSE values of 2.58° for orientation, 0.087 m for spacing, and 2.05 m for persistence, using the conventional method as a reference. The digital manual method, with 19% coverage, yielded very low error (RMSE of 3.27° for orientation, 0.012 m for spacing, and 0.063 m for persistence), validating it as a complementary and reliable alternative. In contrast, the conventional method required the longest execution time (10 h) and achieved only 19% coverage, being the least replicable due to its dependence on expert judgment. Overall, the comparison highlights the advantages of digital methods, especially the semi-automatic approach, in improving efficiency, safety, and replicability, while providing robust information to recommend prevention strategies for rock slope stability. Full article

Understanding and controlling thermal rectification is pivotal for designing phononic devices that guide heat flow in a preferential direction. This study investigates one-dimensional atomic chains with binary mass asymmetry and nonlinear interatomic potentials, focusing on how energy propagates under thermal and wave excitation. Two potential models—the β-FPU and Morse potentials—were employed to examine the role of nonlinearity and bond softness in energy transport. Simulations reveal strong directional energy transport governed by the interplay of mass distribution, nonlinearity, and excitation type. In FPU chains, pronounced rectification occurs: under “cold-heavy” conditions, energy in the left segment increases from ~1% to over 63%, while reverse (“hot-heavy”) cases show less than 4% net transfer. For wave-driven excitation, the rectification coefficient reaches ~0.58 at 100:1. In contrast, Morse-based systems exhibit weaker rectification (∆E < 1%) and structural instabilities at high asymmetry due to bond breaking. A comprehensive summary and heatmap visualization highlight how system parameters govern rectification efficiency. These findings provide mechanistic insights into nonreciprocal energy transport in nonlinear lattices and offer design principles for nanoscale thermal management strategies based on controlled asymmetry and potential engineering. Full article

Future lunar exploration will depend on a clearer understanding of regolith behavior, as underscored by adhesion issues observed during Apollo. The Lunaris Payload, a compact instrument developed in Poland, targets in situ assessment of lunar regolith adhesion to engineering materials using a resource-constrained optical approach. Here we introduce and validate six lightweight 2D-to-3D geometric models for estimating particle volume from planar images, benchmarked against the high-resolution micro-computed tomography (micro-CT) ground truth. The tested methods include spherical, cylindrical, fixed-aspect-ratio ellipsoid, adaptive ellipsoid, and Feret-based models and an empirically scaled voxel proxy. Using micro-CT scans of adhered simulant particles, we evaluate accuracy across >8000 particles segmented from 2D projections. Ellipsoid-based models consistently outperform the alternatives, with absolute percentage errors of 30–35%, while fixed-aspect-ratio variants offer strong accuracy–complexity trade-offs suitable for mass- and power-limited payloads. To our knowledge, this is the first comprehensive benchmarking of six 2D-to-3D volume models against micro-CT for bulk-adhered lunar regolith analogs. The results provide a validated, efficient framework for in situ dust characterization and reliable particle mass estimation, advancing Lunaris’ capability to quantify regolith adhesion and supporting broader goals in dust mitigation, ISRU, or habitat construction. Full article

The estimation of the area susceptible to rock failure and the prediction of its movement process are pivotal for hazard mitigation, yet they are also challenging. In this study, we proposed a novel integrated method combining field investigation, remote sensing, and three-dimensional discrete element method (DEM) simulation to achieve our goal. The field investigation and remote sensing analysis are used for the purpose of ascertaining the deformation phenomenon and the structure of the rock slope, identifying the potential failure position and area of the slope. Subsequently, a three-dimensional DEM simulation is employed to quantitatively assess the potential rock failure-affected area and movement process, based on the above potential failure information. The simulation results demonstrate that potential rock failure persists for approximately 30 s, and its movement process can be categorized into two distinct stages: acceleration and deceleration. The initial acceleration stage is characterized by a duration of 10 s, culminating in a peak average velocity of 13 m/s. The subsequent deceleration stage extends for a duration of 20 s. Notably, the maximum attainable velocity for the segment of rock mass under consideration is estimated to be 50 m/s. Furthermore, the model demonstrates the variation in fracture energy, friction energy, and kinetic energy over time. The potential affected area is 140,000 m², and approximately 8000 m² of residential construction will be destroyed if a rock failure occurs. It is imperative to implement measures aimed at the prevention of rock failure in order to mitigate the risk of such an occurrence. Full article

This study presents a novel methodology for the fabrication of aluminum matrix composites (AMCs) reinforced with a hybrid of MAX phase (Ti₃AlC₂) and MXene (Ti₃C₂T_x) particles via vacuum hot-pressing sintering, aiming to enhance the mechanical properties and tribological performance of aluminum matrix composites. The hybrid-reinforced aluminum matrix composites were fabricated with Ti₃AlC₂/Ti₃C₂T_x reinforcements at a 1:1 mass ratio, incorporating reinforcement contents of 5 wt.%, 15 wt.%, and 25 wt.%, respectively. The optimized vacuum hot press sintering process was as follows: firstly, a cold press pressure of 20 MPa was applied to the composite powder, and then hot press sintering was carried out by means of segmental pressurization with a sintering pressure of 20 MPa, a temperature of 500 °C, and a heat preservation of 1 h before cooling in the furnace. It was found by micro-morphological characterization and mechanical property testing that with the increase of Ti₃AlC₂/Ti₃C₂T_x reinforcement content (5 wt.%→15 wt.%), the micro-hardness of the composites (31.9→76.1 HV_0.2), compressive strength (41.7→151.9 MPa), and tribological properties (friction coefficient 0.68→0.50) were significantly improved; however, when the content of reinforcement exceeded 15 wt.%, the deterioration of properties triggered by the increase in pore defects and particle agglomeration leads instead to a decrease in compressive strength (by 12.3%), apparent modulus of elasticity (specimen’s compressive specific stiffness, by 9.8%) and frictional stability (coefficient of friction recovered to 0.62). The 15 wt.% hybrid reinforcement composites demonstrated optimal strength-toughness synergies, exhibiting a 361.6% increase in yield strength and a 597.1% increase in apparent modulus of elasticity compared to pure aluminum. Furthermore, the friction coefficient exhibited a 26.47% reduction in comparison to pure aluminum, thereby substantiating enhanced tribological performance. The observed enhancements are attributed to the synergistic effects of the MAX and MXene phases, where MXene improves interfacial wettability and densification, while MAX particles enhance overall strength through diffusion reinforcement. Full article

Outdoor substations present complex conditions such as uneven terrain, strong illumination variations, and frequent occlusions, which pose significant challenges for autonomous robotic inspection. To address these issues, we develop an embedded inspection robot that integrates attention-enhanced semantic segmentation with GPS-assisted navigation for reliable operation. A lightweight DeepLabV3+ model is improved with ECA-SimAM and CBAM attention modules and further extended with a GPS-guided attention component that incorporates coarse location priors to refine feature focus and improve boundary recognition under challenging lighting and occlusion. The segmentation outputs are used to generate real-time road masks and navigation lines via center-of-mass and least-squares fitting, while RTK-GPS provides global positioning and triggers waypoint-based behaviors such as turning and stopping. Experimental results show that the proposed method achieves 85.26% mean IoU and 89.45% mean pixel accuracy, outperforming U-Net, PSPNet, HRNet, and standard DeepLabV3+. Deployed on an embedded platform and validated in real substations, the system demonstrates both robustness and scalability for practical infrastructure inspection tasks. Full article

Cell towers play a key role in providing telecommunications infrastructure, especially in remote mountainous regions. This paper presents an approach to the efficient design of 42-metre-high cell towers intended to install high-power equipment in remote mountainous regions of the Carpathians (750 m above sea level). The region requires rapid deployment of many standardized towers adapted to geographical features. The main design challenges were the limited space available for the base, the impact of extreme weather conditions, and the need for a fast project implementation due to the critical importance of ensuring stable communication. Special methodological attention is given to how the transition between pyramidal and prismatic segments in cell tower shafts influences overall structural performance. The effect of this geometric boundary on structural efficiency and material usage has not been addressed in previous studies. A dedicated investigation shows that positioning the transition at a height of 33 m yields the best compromise between stiffness and weight, minimizing a generalized penalty function that accounts for both the horizontal displacement of the tower top and its total mass. Modal analysis confirms that the chosen configuration maintains a natural frequency of 1.68 Hz, ensuring a safe margin from resonance. For the final analysis of the behavior of towers with elements of different cross-sectional shapes, finite element modeling was used for a detailed numerical study of their structural and performance characteristics. This allowed us to assess the impact of geometric constraints of structures and take into account the most unfavorable combinations of static and dynamic loads. The study yields a concise rule of thumb for towers with compact foundations, namely that the pyramidal-to-prismatic transition should be placed at roughly 78–80% of the total tower height. Full article

Background: This study investigated sex differences in foot arch structure and function, and their impact on postural control and energy flow during dynamic tasks. Findings aim to inform sex-specific training, movement assessment, and injury prevention strategies. Methods: A total of 108 participants (53 males and 55 females) underwent foot arch morphological assessments and performed a sit-to-stand (STS). Motion data were collected using an infrared motion capture system, three-dimensional force plates, and wireless surface electromyography. A rigid body model was constructed in Visual3D, and joint forces, segmental angular and linear velocities, center of pressure (COP), and center of mass (COM) were calculated using MATLAB. Segmental net energy was integrated to determine energy flow across different phases of the STS. Results: Arch stiffness was significantly higher in males. In terms of postural control, males exhibited significantly lower mediolateral COP frequency and anteroposterior COM peak velocity during the pre-seat-off phase, and lower COM displacement, peak velocity, and sample entropy during the post-seat-off phase compared to females. Conversely, males showed higher anteroposterior COM velocity before seat-off, and greater anteroposterior and vertical momentum after seat-off (p < 0.05). Regarding energy flow, males exhibited higher thigh muscle power, segmental net power during both phases, and greater shank joint power before seat-off. In contrast, females showed higher thigh joint power before seat-off and greater shank joint power after seat-off (p < 0.05). Conclusions: Significant sex differences in foot arch function influence postural control and energy transfer during STS. Compared to males, females rely on more frequent postural adjustments to compensate for lower arch stiffness, which may increase mechanical loading on the knee and ankle and elevate injury risk. Full article

Background/Objectives: Sarcopenia, characterized by progressive loss of skeletal muscle mass and strength, significantly impacts physical function and quality of life in older adults. Traditional measurement methods like Dual-energy X-ray absorptiometry (DEXA) are often inaccessible in primary care. This study aimed to develop and validate an AI-driven auto-segmentation model for muscle mass assessment using long X-rays as a more accessible alternative to DEXA. Methods: This was a retrospective validation study using data from the Real Hip Cohort at Inha University Hospital in South Korea. 351 lower extremity X-ray images from 157 patients were collected and analyzed. AI-based semantic segmentation models, including U-Net, V-Net, and U-Net++, were trained and validated on this dataset to automatically segment muscle regions. Model performance was assessed using Intersection over Union (IoU) and Dice Similarity Coefficient (DC) metrics. The correlation between AI-derived muscle measurements and the DEXA-derived skeletal muscle index was evaluated using Pearson correlation analysis and Bland–Altman analysis. Results: The study analyzed data from 157 patients (mean age 77.1 years). The U-Net++ architecture achieved the best segmentation performance with an IoU of 0.93 and DC of 0.95. Pearson correlation demonstrated a moderate to strong positive correlation between the AI model’s muscle estimates and DEXA results (r = 0.72, *** p < 0.0001). Regression analysis showed a coefficient of 0.74, indicating good agreement with reference measurements. Conclusions: This study successfully developed and validated an AI-driven auto-segmentation model for estimating muscle mass from long X-rays. The model provides an accessible alternative to DEXA, with potential to improve sarcopenia diagnosis and management in community and primary care settings. Future work will refine the model and explore its application to additional muscle groups. Full article

Background: Sarcopenia is characterized by a loss of muscle mass and strength, resulting in functional limitations and an increased risk of falls, injuries and fractures. The aim of this study was to obtain detailed information on skeletal muscle changes in patients with multiple myeloma (MM) during treatment. Methods: A total of 51 patients diagnosed with MM who had undergone whole-body low-dose computed tomography acquisition prior to induction therapy (T1) and post autologous stem cell transplantation (T2) were examined retrospectively. Total volume (TV), muscle volume (MV) and intramuscular adipose tissue volume (IMAT) of the autochthonous back muscles, the iliopsoas muscle and the gluteal muscles were evaluated on the basis of the resulting masks of the BOA tool with the fully automated combination of TotalSegmentator and a body composition analysis. An in-house trained artificial intelligence network was used to obtain a fully automated three-dimensional segmentation assessment. Results: Patients’ median age was 58 years (IQR 52–66), 38 were male and follow-up CT-scans were performed after a mean of 11.8 months (SD ± 3). Changes in MV and IMAT correlated significantly with Body-Mass-Index (BMI) (r = 0.7, p < 0.0001). Patients (n = 28) with a decrease in BMI (mean −2.2 kg/m²) during therapy lost MV (T1: 3419 cm³, IQR 3176–4000 cm³ vs. T2: 3226 cm³, IQR 3014–3662 cm³, p < 0.0001) whereas patients (n = 20) with an increased BMI (mean +1.4 kg/m²) showed an increase in IMAT (T1: 122 cm³, IQR 96.8–202.8 cm³ vs. T2: 145.5 cm³, IQR 115–248 cm³, p = 0.0002). Loss of MV varied between different muscle groups and was most prominent in the iliopsoas muscle (−9.8%) > gluteus maximus (−9.1%) > gluteus medius (−5.8%) > autochthonous back muscles (−4.3%) > gluteus minimus (−1.5%). Increase in IMAT in patients who gained weight was similar between muscle groups. Conclusions: The artificial intelligence-based three-dimensional segmentation process is a reliable and time-saving method to acquire in-depth information on sarcopenia in MM patients. Loss of MV and increase in IMAT were reliably detectable and associated with changes in BMI. Loss of MV was highest in muscles with more type 2 muscle fibers (fast-twitch, high energy) whereas muscles with predominantly type 1 fibers (slow-twitch, postural control) were less affected. This study provides valuable insight into muscle changes of MM patients during treatment, which might aid in tailoring exercise interventions more precisely to patients’ needs. Full article

Inefficient drying of alfalfa round bales causes significant nutrient loss (up to 50%) and quality degradation due primarily to uneven drying in existing processing methods. To address this challenge requiring dedicated equipment and optimized processes, this study developed a specialized hot-air drying test bench (CGT-1). A coupled heat and mass transfer model was established, and 3D dynamic simulations of temperature, humidity, and wind speed distributions within bales were performed using COMSOL multiphysics to evaluate drying inhomogeneity. Single-factor experiments and multi-factor response surface methodology (RSM) based on Box–Behnken design were employed to investigate the effects of hot air temperature (50–65 °C), wind speed (2–5 m/s), and air duct opening diameter (400–600 mm) on moisture content, drying rate, and energy consumption. Results demonstrated that larger duct diameters (600 mm) and higher wind speeds (5 m/s) significantly enhanced field uniformity. RSM optimization identified optimal parameters: temperature at 65 °C, wind speed of 5 m/s, and duct diameter of 600 mm, achieving a drying time of 119.2 min and a drying rate of 0.62 kg/(kg·min). Validation experiments confirmed the model’s accuracy. These findings provide a solid theoretical foundation and technical support for designing and optimizing alfalfa round-bale drying equipment. Future work should explore segmented drying strategies to enhance energy efficiency. Full article

A rigorous framework for determining actual and minimum boil-up ratios in binary distillation combining analytical mass and energy balances with an extended Ponchon–Savarit graphical approach was implemented. First, global balances across the enriching and stripping sections yield a closed-form expression of the boil-up ratio (V_B) based on enthalpy differences. Second, the V_B was directly determined from an enthalpy–composition diagram by measuring the enthalpy segments between the saturated liquid, vapor, and heat-duty points. Applying this method to high-stage columns confirms that the two methods converge on identical V_B values. Based on these findings, a unified graphical methodology was developed to determine the minimum boil-up ratio (V_Bmin). V_Bmin can be determined on the same diagram by locating the intersections of the extremal tie lines in both the enriching and exhausting sections, analogous to the reflux-pinch points. This procedure was systematically validated across the five canonical feed thermal states. The implemented method is a graphical approach based on the Ponchon–Savarit technique, developed for binary systems. Full article

Extensive green roofs (EGRs) are recognized as a promising passive cooling strategy due to their low areal mass, yet their thermal performance is strongly influenced by water availability. While prior studies have focused primarily on continuous irrigation or small-scale modules, the response of EGRs to temporary irrigation outages remains underexplored. This study presents a full-scale experimental investigation on an industrial roof segment in Dubnica nad Váhom, Slovakia, conducted during summer 2024. The thermal behavior of an EGR was compared to a conventional reflective flat roof (RR) and a roof with a hydroaccumulative layer covered with photovoltaic panels (PV). The experiment analyzed an unplanned irrigation interruption and the subsequent recovery, selecting representative three-day intervals from each phase. During non-irrigated periods under peak solar radiation, evapotranspiration (ET) was minimal, resulting in increased heat flux into the interior. After irrigation resumed, ET accounted for nearly 70% of net solar radiation, reducing interior heat flux to 32% of the non-irrigated value. Heat gain reductions between irrigated and non-irrigated days were 1% for RR, 38% for PV, and 68% for EGR, correlating with energy consumed for ET. These results highlight that active irrigation substantially enhances the cooling performance of EGRs, demonstrating their potential as an effective adaptation measure for buildings under extreme summer conditions. Full article