Search Results (13,279)

Unmanned Aerial Vehicles (UAVs) are increasingly integral to construction site management, supporting monitoring, inspection, and data collection tasks. Effective UAV path planning is essential for maximizing operational efficiency, particularly in complex and dynamic construction environments. While previous BIM-based approaches have explored representation models such as space graphs, grid patterns, and voxel models, each has limitations. Space graphs, though common, rely on predefined spatial spaces, making them less suitable for projects still under construction. Voxel-based methods, considered well-suited for 3D indoor navigation, suffer from three key challenges: (1) a disconnect between the BIM and voxel models, limiting data integration; (2) the computational cost and time required for voxelization, hindering real-time application; and (3) inadequate support for 4D BIM integration during active construction phases. This research introduces a novel framework that bridges the BIM–voxel gap via an enriched voxel map, eliminates the need for repeated voxelization, and incorporates 4D BIM and additional model data such as defined workspaces and safety buffers around fragile components. The framework’s effectiveness is demonstrated through path planning simulations on BIM models from two real-world construction projects under varying scenarios. Results indicate that the enriched voxel map successfully creates a connection between BIM model and voxel model, while covering every timestamp of the project and element attributes during path planning without requiring additional voxel map creation. Full article

Collagen is a family of large, fibrous biomacromolecules common in animals, distinguished by unique molecular, structural, and functional properties. Despite the relatively low complexity of their sequences and the repetitive conformation of the triple helix, which is the defining feature of this family, unraveling sequence–stability and structure–function relationships in this group of proteins remains a challenging task. Considering the importance of the structural aspects in collagen chain recognition and selection, we reviewed our current knowledge of the heterotrimeric structures of non-collagenous (NC) regions that lack the triple helix sequence motif, Gly-X-Y, and are crucial for the correct folding of the functional states of these proteins. This study was conducted by simultaneously surveying the current literature, mining the structural database, and making predictions of the three-dimensional structure of these domains using highly reliable approaches based on machine learning techniques, such as AlphaFold. The combination of experimental structural data and predictive analyses offers some interesting clues about the structural features of heterotrimers formed by collagen NC regions. Structural studies carried out in the last decade show that for fibrillar collagens (types I, V, XI, and mixed V/XI), key factors include the formation of specific disulfide bridges and electrostatic interaction patterns. In the subgroup of collagens whose heterotrimers create supramolecular networks (types IV and VIII), available structural information provides a solid ground for the definition of the basis of the molecular and supramolecular organization. Very recent AlphaFold predictions and structural analyses of type VI collagen offer strong evidence of the specific domains in the NC region of the protein that are involved in chain selection and their staggering. Insightful crystallographic studies have also revealed some fundamental elements of the chain selection process in type IX collagen. Collectively, the data reported here indicate that, although some aspects (particularly the quantification of the relative contribution of the NC and triple helix regions to correct collagen folding) are yet to be fully understood, the available structural information provides a solid foundation for future studies aimed at precisely defining sequence–structure–function relationships in collagens. Full article

Rolling Element Bearing (REB) failures represent a critical challenge in rotating machinery maintenance, accounting for approximately 45% of industrial breakdowns. Considering the variable operating conditions of speeds and loads, vibration fault signatures are generally masked by noises. Consequently, traditional diagnostic methods relying on time and frequency analysis or conventional machine learning often fail to capture the nonlinear interactions and phase coupling characteristics essential for accurate fault detection, particularly in noisy industrial environments. In this study, we propose a framework that synergistically combines (1) Empirical Mode Decomposition (EMD) for adaptive handling of non-stationary vibration signals, (2) bispectrum analysis to extract phase-coupled features while inherently suppressing Gaussian noise, and (3) Time-Series Transformer with attention mechanisms to automatically weight discriminative feature interactions. Experimental results based on five different benchmarks show that the proposed BSEMD-Transformer framework is a powerful tool for REB diagnosis, reaching a classification accuracy of at least 98.2% for all tests regardless of the used dataset. The proposed approach is judged to be consistent, robust, and accurate even under variable conditions of speed and loads. Full article

This study addresses the issues related to the inaccurate assessment of transient voltage stability margins and the limited participation of resources involved in regulation during high-voltage direct current (HVDC) receiving-end grid faults under high-penetration new energy integration. This paper proposes a method for transient voltage emergency control at the HVDC receiving-end grid, utilizing a multi-resource approach based on transient voltage similarity partitioning with a multiple-two-element notation criterion. First, the transient voltage stability margin and the new energy transient off-grid margin index, based on the multiple-two-element notation criterion, are introduced. Second, a grid partitioning scheme is employed, which clusters nodes based on the similarity of their transient voltage features, and the impact of multiple resources on the transient voltage stability of the HVDC receiving-end system is analyzed using trajectory sensitivity. On this basis, a multi-resource optimization model for transient voltage emergencies is established with the aim of minimizing the control cost, considering the transient voltage stability, off-grid new energy, and other safety evaluation constraints, in order to coordinate multiple resources participating in transient voltage control until the stability requirements are met. Finally, the validity of the proposed control scheme is verified using the improved frequency stability benchmark test system (Chinese Society for Electrical Engineering—Frequency Stability, CSEE-FS). The research results demonstrate that the scheme proposed in this study can be utilized to accurately assess the transient voltage stability and off-grid potential of renewable energy units following failure at the HVDC receiving-end system. Additionally, it can reasonably partition the grid based on transient operating conditions while fully exploiting the potential of multiple resources within the faulted partition to control transient voltage emergencies in the grid. Full article

Stress granules (SGs) are dynamic membrane-less structures assembled in response to stress. The formation of stress granules in plants is poorly understood, especially the mechanism of mRNA recruitment. The problem of the specificity of mRNA interaction with stress granule proteins is unexplored. Oligouridylate binding protein 1B (UBP1B) is considered as the core element of plant SGs. In this study, we expressed the AtUBP1b protein from Arabidopsis thaliana in E. coli cells. Mass spectroscopic analysis showed that the AtUBP1b protein expressed in E. coli cells is phosphorylated at serine, threonine, and tyrosine residues. We also performed a de novo phosphorylation reaction in wheat germ extracts with the addition of radioactively labeled phosphorus and showed AtUBP1b phosphorylation in plant extracts. We hypothesized that phosphorylation or dephosphorylation of AtUBP1b in plant cells is a signal for protein binding to RNA. The purified protein was tested for its ability to bind to mRNA in vitro. In gel-shifting assays we demonstrated that AtUBP1b protein binds specifically to 5′-untranslated regions (5′UTR) of mRNA. When AtUBP1b was added to a cell-free wheat germ translation system, it exerted different effects on protein synthesis. We showed that AtUBP1b had a significant inhibitory effect on the expression of mRNAs containing 5′UTRs that were shown to bind to the protein in the gel-shifting reaction. Full article

The rim-driven device (RDD) integrates the motor and the impeller, which can achieve shaftless, modular, and integrated operation of the turbomachinery system and has broad application prospects. To reduce the axial length and radial thickness of the RDD, a motor with a thin-yoke wide-tooth fractional slot concentrated winding stator and a coreless Halbach permanent magnet array rotor is designed. Theoretical and finite element simulation analyses of its air gap magnetic field characteristics were carried out. The results show that, for the thin-yoke wide-tooth fractional slot concentrated winding permanent magnet motor, the harmonic magnetic field generated by the magnetic poles should mainly consider the magnetic field components produced by the interaction between the harmonic magnetomotive force of the magnetic poles and the constant air gap specific magnetic permeability, as well as the magnetic field components generated by the interaction between the fundamental magnetomotive force of the magnetic poles and the fundamental and second-order harmonic air gap specific magnetic permeability. The harmonic magnetic field generated by the current should mainly consider the magnetic field components produced by the interaction between the harmonic magnetomotive force with a small number of pole pairs (NOPP) and large amplitude generated by the current and the constant air gap specific magnetic permeability. Compared with radial magnetic flux density, tangential magnetic flux density has the same NOPP and frequency components, with a phase difference of 90°. The fundamental amplitude difference between them is larger, while the harmonic amplitude difference between them is smaller. Full article

Ever-increasing demands to improve fuel burn efficiency of aero gas turbines lead to rises in fuel system pressures and temperatures, posing challenges for the structural integrity of the pump housing and creating internal deflections that can adversely affect volumetric efficiency. Non-invasive strain and vibration measurements could allow transient effects to be quantified and considered during the design process, leading to more robust fuel pumps. Fuel pumps used on a high bypass turbofan engine were instrumented with optical fibre Bragg grating (FBG) sensors, strain gauges and thermocouples. A hydraulic hand pump was used to facilitate measurements under static conditions, while dynamic measurements were performed on a dedicated fuel pump test rig. The experimental data were compared with the outputs from a finite element (FE) model and, in general, good agreement was observed. Where differences were observed, it was concluded that they arose from the sensitivity of the model to the selection of nodes that best matched the sensor location. Strain and vibration measurements were performed over the frequency range of 0 to 2.5 kHz and demonstrated the ability of surface-mounted FBGs to characterise vibrations originating within the internal sub-components of the pump, offering potential for condition monitoring. Full article

Ultra-high performance concrete (UHPC) and ultra-high toughness cementitious composite (UHTCC) offer superior mechanical properties compared to normal concrete, with UHPC excelling in compressive strength and UHTCC in tensile ductility and crack resistance. This study focuses on UHPC/UHTCC-encased steel tubular (UEST) columns, establishing finite element (FE) models to simulate the axial behavior of UEST columns, conducting parametric studies on stud number, encasement thickness, steel yield strength, and width-to-thickness ratio, and developing a theoretical model considering thin-walled steel buckling to calculate the axial resistance of UEST columns. The proposed theoretical model predicts axial resistance with an average error of 3.4%, providing a reliable design method for engineering applications. Full article

Motors are among the most energy-consuming devices worldwide. With growing interest in eco-friendly solutions, minimum efficiency regulations for industrial motors are being enforced. In response to continuously rising minimum efficiency requirements, research on improving the efficiency of motors is actively underway. In the case of induction motors, which are the most widely used industrial electric motors, rotor ohmic loss occurs due to their operating characteristics. In contrast, line-start synchronous reluctance motors (LS-SynRMs) have a significant advantage in efficiency because once they reach synchronous speed, no eddy currents are generated by the fundamental current waveform. This leads to a sharp decrease in rotor ohmic losses, greatly enhancing efficiency. In this paper, a rotor design is carried out to improve the efficiency of LS-SynRMs. To support the rotor design, the torque characteristics of LS-SynRMs were analyzed under both asynchronous and synchronous state operations, and improvement directions for enhancing efficiency were identified. For rotor type selection, two bar-type rotors with linear flux barriers and two boomerang-type rotors with curved flux barriers were designed. The electromagnetic characteristics of these designs were compared using finite element analysis. Among them, the boomerang-type rotor that exhibited the best electromagnetic performance was selected as the final rotor type. Its final geometry was derived through detailed design, considering the mechanical safety of the rotor. Finally, experimental validation was conducted to verify the effectiveness of the proposed rotor design. Full article

This study investigates the determinants of service demand in the packaging and printing industry, identifying 19 key factors through expert evaluation. These factors were analyzed using the Importance–Satisfaction (I–S) Model to pinpoint areas requiring enhancement, with four elements classified within the improvement zone. Considering resource constraints, improvement priorities were established through a modified Risk Priority Number (RPN) framework derived from Failure Modes and Effects Analysis (FMEA), expressed as RPN = I × F × E. The highest-priority areas for improvement included product pricing, flexibility in meeting customer requirements, suppliers’ emergency response capabilities, and proactive communication regarding raw material price fluctuations. The findings indicate that consumers balance price against sustainability value, highlighting the necessity of setting prices that align with perceived value to sustain trust and meet expectations. Strengthening firms’ emergency response mechanisms and developing an online standard operating procedure (SOP) notification system for raw material price changes can enhance communication efficiency, increase transparency in pricing, and ultimately improve organizational competitiveness. Full article

Phosphorus (P) is an essential element for plant growth, yet it is only available to plants in the form of orthophosphate. In most soils, P occurs predominantly in insoluble forms, such as calcium phosphates in alkaline soils and aluminum/iron phosphates in acidic soils, limiting plant uptake. Fertilization is commonly used to overcome this limitation; however, large fractions of applied P rapidly become unavailable. Phosphorus-solubilizing bacteria (PSB) are a sustainable alternative to enhance P availability. This study evaluated the P-solubilization capacity of bacterial strains belonging to different genera isolated from different host plants, soil types, and climates (mainland Portugal, Cape Verde, and Angola). Following initial screening, the most efficient strains were tested under greenhouse conditions in soils with pH 7 and 8. Strains exhibited diverse solubilization capacities, with highly efficient PSB (phosphate solubilization index ≥ 2) accounting for 5% of the total isolates, predominantly originating from the Namib Desert (Angola) and Southern Portugal, and mainly belonging to the genera Pseudomonas, Flavobacterium, Enterobacter, Chryseobacterium and Pantoea. At pH 7, most PSB promoted maize growth, with strain C11 increasing plant P content around 2-fold compared to the control. At pH 8, fewer strains were effective, but strains F and C11 enhanced shoot weight and M shoot length by 28%, 27%, and 10%, respectively. These findings highlight the potential of selected PSB strains as next-generation bioinoculants for sustainable agriculture. However, strain selection must consider geography, crop type, and management practices to ensure consistent efficacy, thereby supporting the broader application of PSB as a precision tool for improving food security. Full article

By using Geographic Information Systems, satellite imagery from remote sensing techniques provides quantitative and qualitative data about Earth’s natural and human elements. However, the direct use of raw imagery may prevent the accurate identification of the spectral and temporal characteristics of the target objects. To obtain meaningful results from these data, the object and surface features in the image must be classified correctly. In this context, this study develops a new deep learning approach that includes hyperparameter optimization that considers uncertainty factors when classifying satellite imagery. In the proposed approach, a hybrid architecture called CNN-Pythagorean Fuzzy Deep Neural Network (PFDNN) is developed by combining the ability of convolutional neural networks (CNN) to reveal expressive features with the ability of Pythagorean fuzzy set (PFS) theory to predict uncertainty. In addition, to further improve the model’s success, the hyperparameters are automatically optimized using Optuna. In the experiments conducted on the EuroSAT RGB dataset, the CNN+PFDNN+Optuna model achieved 0.9696 ± 0.0037 accuracy and a macro-AUC value of 0.9983, outperforming other methods such as DNN, FDNN, PFDNN and VGG16+PFDNN. Including the Pythagorean fuzzy layer in the system provided about 13.05% higher accuracy than conventional fuzzy systems. These results show that integrating the Pythagorean fuzzy set approach into deep learning models contributes to more effective management of uncertainties in remote sensing data and that hyperparameter optimization significantly impacts model performance. Full article

Background/Objectives: Screw loosening and vertebral fractures remain common after vertebral body tethering (VBT). Because tightening torque sets screw preload, its biomechanical effect warrants explicit modeling. In this paper, a Finite Element (FE) model, supported by ex vivo porcine vertebral tests, was developed and validated that incorporates torque-induced pre-tension to quantify vertebral stress, aiming toward customizable VBT planning. Methods: An FE model with pre-tension and axial extraction failure was parameterized using ex vivo tests on five porcine vertebrae. A laterally inserted surgical screw in each specimen was tightened to $5.9\pm 0.80$ Nm. Axial extraction produced failure loads of $2.1\pm 0.31$ kN. This is also considered in the FE model to validate the failure scenario. Results: Torque alone generated peak von Mises stresses of $16.1\pm 0.86$ MPa (cortical bone 1) and $2.1\pm 0.13$ MPa (trabecular), lower than prior reports. With added axial load, peaks rose to $141.1\pm 0.70$ MPa and $19.7\pm 0.23$ MPa, exceeding typical ranges. However, predicted failure agreed with experiments, showing $0.58$ mm displacement and a conical displacement distribution around the washer. Conclusions: Modeling torque-induced pre-tension is essential to reproduce realistic stress states and anchor failure in VBT. The framework enables patient-specific assessment (bone geometry/density) to recommend safe tightening torques, potentially reducing screw loosening and early fractures. Full article

Background: A cataract is a clouding of the normally clear lens that obscures the passage of light, effectively reducing clarity and sharpness of vision. Although this disease can affect both children and adults, the most common type is the age-related cataract (ARC). The literature describes many potential agents associated with cataract development. However, this study focuses on modifiable factors, especially nutritional ones and those that may induce oxidative stress. The objective of the present study was to assess serum selenium (Se), copper (Cu), and zinc (Zn) concentrations, as well as the copper/zinc molar ratio (Cu/Zn molar ratio), total antioxidant status (TAS), total oxidant status (TOS), and oxidative stress index (OSI), of patients with ARC in relation to their dietary habits. Methods: A total of 68 patients with ARC and 64 healthy volunteers, with ages ranging from 48 to 92 years, were included in this study. The experimental material collected from the participants consisted of blood samples, which were tested for Se, Cu, and Zn concentrations using atomic absorption spectrometry (AAS). Oxidative stress (OS) parameters, such as TAS and TOS, were estimated spectrophotometrically. In addition, a food frequency questionnaire (FFQ) was used to collect information on the dietary habits of ARC patients. Results: Statistical analysis of the data revealed that the concentrations of Se, Cu, and Zn in serum were significantly lower in ARC patients compared to the controls. In the ARC group, some elements of dietary behavior had a significant effect on the levels of the examined elements and OS parameters. Conclusions: Thus, eventual alterations to one’s diet appear to be worth considering in the context of maintaining homeostasis and adequate mineral levels in ARC patients. Full article

Background: Fibromyalgia (FM) is a chronic musculoskeletal disorder characterized by widespread body pain and various symptoms. Its etiology remains unclear to date. It has been associated with various pathogenic mechanisms, primarily inflammation. Immature granulocytes (IGs) have been proposed as a potential biomarker, playing a role in both inflammatory responses and prognosis in numerous diseases. No other study has investigated the count of immature granulocytes (IG#) and percentage of immature granulocytes (IG%) in FM patients. The aim of this study is to investigate the IG# and IG% in FM patients and to evaluate the relationship between these parameters and disease parameters. Methods: This retrospective observational study included 95 patients diagnosed with FM and 63 healthy control subjects matched for body mass index and gender. Biochemical, hematological parameters, erythrocyte sedimentation rate (ESR), C-reactive protein (CRP) and other inflammatory markers were recorded for both groups. Fibromyalgia Survey Diagnostic Criteria and Severity Scale (FSDC) and Fibromyalgia Impact Questionnaire (FIQ) scores were recorded for FM patients. Results: In FM patients, the IG% and IG# were significantly higher than in the healthy control group (p < 0.001, p: 0.006, respectively). There was no significant difference between the CRP and ESR values of the two groups. The platelet large cell count (PLCC) was significantly lower in the FM group (p < 0.032). Conclusions: IG levels can be used as a systemic early, sensitive, and low-cost marker in patients with FM. Based on our current knowledge, and considering the heterogeneous nature of FM, IG levels may serve as a meaningful tool in identifying subgroup elements reflecting an inflammatory phenotype. However, these findings require further validation through larger sample size, prospective studies, and advanced analyses including cytokine levels. Full article