Search Results (14,034)

Background: Glenoid radiolucenct lines (gRLL) and glenoid component subsidence (gSC) after anatomic total shoulder arthroplasty (aTSA) have traditionally been linked to implant loosening and functional decline. However, their impact on long-term clinical outcomes remains unclear. This study aimed to evaluate whether gRLL and gSC are associated with inferior clinical or functional results in patients without revision surgery. Methods: In this retrospective study, 52 aTSA cases (2008–2015) were analyzed with a minimum of five years of clinical and radiographic follow-up. Based on final imaging, patients were categorized according to the presence and extent of gRLL and gSC. Clinical outcomes included the Constant-Murley Score, DASH, VAS for pain, and range of motion (ROM). Radiographic parameters included the critical shoulder angle (CSA), acromiohumeral distance (AHD), lateral offset (LO), humeral head-stem index (HSI), and cranial humeral head decentration (DC). Group comparisons were conducted between: (1) ≤2 vs. 3 gRLL zones, (2) 0 vs. 1 zone, (3) 0 vs. 3 zones, (4) gSC vs. no gSC, and (5) DC vs. no DC. Results: Demographics and baseline characteristics were comparable across groups. Functional scores (Constant, DASH), pain (VAS), and ROM were largely similar. Patients with extensive gRLL showed reduced external rotation (p = 0.01), but the difference remained below the MCID. Similarly, gSC was associated with lower forward elevation (p = 0.04) and external rotation (p = 0.03), both below MCID thresholds. No significant differences were observed for DC. Conclusions: Neither extensive gRLL nor gSC significantly impaired long-term clinical or functional outcomes. As these radiographic changes can occur in the absence of symptoms, regular radiographic monitoring is essential, and revision decisions should be made individually in cases of progressive bone loss. Full article

Hybrid AC/DC microgrids have emerged as a promising solution for integrating diverse renewable energy sources, enhancing efficiency, and strengthening resilience in modern power systems. However, existing control schemes exhibit critical shortcomings that limit their practical effectiveness. Traditional linear controllers, designed around nominal operating points, often fail to maintain stability under large load and generation fluctuations. Optimization-based methods are highly sensitive to model inaccuracies and parameter uncertainties, reducing their reliability in dynamic environments. Intelligent approaches, such as fuzzy logic and ML-based controllers, provide adaptability but suffer from high computational demands, limited interpretability, and challenges in real-time deployment. These limitations highlight the need for robust control strategies that can guarantee reliable operation despite disturbances, uncertainties, and varying operating conditions. Numerical performance indices demonstrate that the reviewed robust control strategies outperform conventional linear, optimization-based, and intelligent controllers in terms of system stability, voltage and current regulation, and dynamic response. This paper provides a comprehensive review of recent robust control strategies for hybrid AC/DC microgrids, systematically categorizing classical model-based, intelligent, and adaptive approaches. Key research gaps are identified, including the lack of unified benchmarking, limited experimental validation, and challenges in integrating decentralized frameworks. Unlike prior surveys that broadly cover microgrid types, this work focuses exclusively on hybrid AC/DC systems, emphasizing hierarchical control architectures and outlining future directions for scalable and certifiable robust controllers. Also, comparative results demonstrate that state of the art robust controllers—including H∞-based, sliding mode, and hybrid intelligent controllers—can achieve performance improvements for metrics such as voltage overshoot, frequency settling time, and THD compared to conventional PID and droop controllers. By synthesizing recent advancements and identifying critical research gaps, this work lays the groundwork for developing robust control strategies capable of ensuring stability and adaptability in future hybrid AC/DC microgrids. Full article

Carrot (Daucus carota L.) is an important root vegetable crop in the Apiaceae and is widely cultivated around the world. Expansins play crucial roles in the growth and development of plants. Here, a total of 35 carrot expansins were identified from carrot. Sequence alignment and phylogenetic analysis revealed that carrot expansins could be classified into four subfamilies, each with similar exon/intron structures and motif compositions, indicating that carrot expansins were relatively conserved during evolution. Chromosomal localization and gene duplication analysis indicated that DcEXP genes were unevenly distributed across carrot nine chromosomes and had evolved predominantly under purifying selection. Measurements of key agronomic characters of carrots at different developmental stages (30, 60, and 90 days after sowing) indicated significant positive correlations among root fresh weight, aboveground fresh weight, root–shoot ratio, root length, and root diameter. The period from 30 to 60 days after sowing was identified as the primary phase of taproot enlargement. Analysis of spatiotemporal expression patterns revealed that most DcEXP genes were specifically expressed in the taproots, and only one gene, DcEXP18, was specifically expressed in leaves. During the rapid growth period of carrot taproots (30 and 60 days after sowing), the genes DcEXP2, DcEXP3, DcEXP5, DcEXP8, DcEXP11, DcEXP13, DcEXP17, DcEXP19, DcEXP20, DcEXP22, DcEXP26, DcEXP28, and DcEXP33 exhibited high expression levels, suggesting that they played potential important roles in carrot taproot enlargement. These findings will advance our knowledge of the molecular mechanisms underlying expansin regulation of carrot growth and development. Full article

Modifying lubricants with hard material particles improves lubricant performance by allowing the particles to penetrate the contact area and separate the contacting surfaces. The use of solid particles as additives in fluid lubricants presents a promising avenue for providing effective lubrication under high loads in sheet metal forming. This article presents the results of friction tests using the bending under tension friction tribotester. Low-carbon DC01 steel sheets were used as the test material. The main goal of the study was to determine the effect of lubricant modification by adding MoS₂ and SiO₂ particles and the modification of 145Cr6 steel countersamples on the coefficient of friction (CoF), changes in friction-induced surface roughness and friction mechanisms. The surfaces of the countersamples were modified using electron beam melting and the ion implantation of lead (IPb). It was found that increasing the SiO₂ and MoS₂ content in DC01/145Cr6 and DC01/IPb contacts under base oil lubrication conditions resulted in a decrease in the CoF value. For the countersample subjected to electron beam melting, considering all friction conditions, the CoF decreased between 31.9% and 37.5%. Full article

Impurities in polypropylene random copolymer (PPR) raw materials can seriously affect the performance of the final product, and efficient and accurate impurity detection is crucial to ensure high production quality. In order to solve the problems of high small-target miss rates, weak anti-interference ability, and difficulty in balancing accuracy and speed in existing detection methods used in complex industrial scenarios, this paper proposes an enhanced machine vision detection algorithm based on YOLOv11. Firstly, the FasterLDConv module dynamically adjusts the position of sampling points through linear deformable convolution (LDConv), which improves the feature extraction ability of small-scale targets on complex backgrounds while maintaining lightweight features. The IR-EMA attention mechanism is a novel approach that combines an efficient reverse residual architecture with multi-scale attention. This combination enables the model to jointly capture feature channel dependencies and spatial relationships, thereby enhancing its sensitivity to weak impurity features. Again, a DC-DyHead deformable dynamic detection head is constructed, and deformable convolutions are embedded into the spatial perceptual attention of DyHead to enhance its feature modelling ability for anomalies and occluded impurities. We introduce an enhanced InnerMPDIoU loss function to optimise the bounding box regression strategy. This new method addresses issues related to traditional CIoU losses, including excessive penalties imposed on small targets and a lack of sufficient gradient guidance in situations where there is almost no overlap. The results indicate that the average precision (mAP@0.5) of the improved algorithm on the self-made PPR impurity dataset reached 88.6%, which is 2.3% higher than that of the original YOLOv11n, while precision (P) and recall (R) increased by 2.4% and 2.8%, respectively. This study provides a reliable technical solution for the quality inspection of PPR raw materials and serves as a reference for algorithm optimisation in the field of industrial small-target detection. Full article

This paper proposes a novel method for locating single-phase grounding faults in generator stator windings with high resistance, which are typically challenging to locate due to weak fault characteristics. The method utilizes an active voltage injection technique combined with traveling wave reflection analysis, singular value decomposition (SVD) denoising, and discrete wavelet transform (DWT). A DC voltage signal is then injected into the stator winding, and the voltage and current signals at both terminals are collected. These signals undergo denoising using SVD, followed by DWT, to identify the arrival time of the traveling waves. Fault location is determined based on the reflection and refraction of these waves within the winding. Simulation results demonstrate that this method achieves high accuracy in fault location, even with fault resistances up to 5000 Ω. The method offers a reliable and effective solution for locating high-resistance faults in generator stator windings without requiring winding parameters, demonstrating strong potential for practical applications. Full article

In this paper, silver oxide (AgO) and copper oxide (CuO) coatings are placed on a single sputtering target with the direct-current magnetron sputtering (DCMS) and high-power impulse magnetron sputtering (HIPIMS) methods. All the tested coatings are obtained in a reactive process using a metallic target made by the Kurt Lesker company. The investigated coatings are deposited at room temperature on substrates made of pure iron (ARMCO) and polypropylene (PP) without substrate polarization. The deposition time for all the coatings is the same. The results of SEM and TEM investigations clearly show that using the HIPIMS method for the deposition of AgO and CuO coatings reduces their thickness and increases their structure density. Coatings produced with the HIPIMS method are characterized by a higher hardness and Young’s modulus. The value of hardness for AgO and CuO coatings deposited by the HIPIMS method is around 50% higher for AgO coatings and around 24% higher for CuO coatings compared to the coatings obtained by the DC method. This is also true of Young’s modulus values, which are around 30% higher for AgO coatings and 15% higher for CuO coatings produced by the HIPIMS method compared to those of coatings obtained with the DC method. AgO and CuO coatings deposited with both the methods (HIPIMS and DCMS) showed 100% reduction in the viability of two reference laboratory bacteria strains—Escherichia coli (Gram−) and Staphylococcus aureus (Gram+)—on both types of substrates. Additionally, these coatings are characterized by their hydrophobic properties, which means that they can create a protective barrier, making it difficult for bacteria to stick to the surface, limiting their development and preventing the phenomenon of biofouling. The HIPIMS technology allows for the deposition of coatings with better mechanical properties than those produced with the DCMS method, which means that they are more resistant to brittle fractures and wear and have very good antimicrobial properties. Full article

Dynamic compression (DC) bioreactors are widely used to mimic joint loading and study how human mesenchymal stem cells (hMSCs) respond to mechanical cues. However, it remains unclear whether DC alone is sufficient to induce chondrogenesis or how such cues interact during construct maturation. In this study, hMSCs were encapsulated in fibrin hydrogels at different cell densities and subjected to DC without, during, or after TGF-β3-mediated chondrogenic induction. DC alone modestly increased SOX9 expression but failed to upregulate key cartilage matrix genes such as ACAN and COL2A1, indicating that mechanical stimulation alone is insufficient to initiate chondrogenesis. When mechanical stimulation was coupled with TGF-β3, a more mature chondrogenic phenotype was observed for high cell seeding densities (HD). To simulate a post-implantation scenario, we applied DC following growth factor withdrawal and observed marked downregulation of SOX9, ACAN, and COL2A1 in low-density (LD) constructs. This reduction was not observed in HD constructs, which maintained a more stable chondrogenic phenotype under loading. These findings show that construct maturation critically influences mechanoresponsiveness and suggest that immature grafts may not tolerate mechanical stimulation. DC bioreactors may therefore serve not only to support cartilage engineering but also to predict in vivo graft performance. Full article

This study focuses on the characterization of MoN thin films deposited by the direct current magnetron sputtering (dcMS), mid-frequency magnetron sputtering (mfMS), and inductively coupled plasma magnetron sputtering (ICPMS) methods. Two mixed metallic phases, namely, α-Mo and γ-Mo₂N, were detected from the film obtained using the dcMS, whereas only single γ-Mo₂N phase was detected from the films obtained using the mfMS and ICPMS. Furthermore, the residual stress of the deposited thin films was strongly dependent on the sputtering process. As the mfMS and ICPMS deposition process were introduced, the film morphology changed from a porous columnar to a dense structure with finer grains than film deposited using dcMS. The surface roughness and crystal grain size of coated films were investigated by atomic force microscopy and X-ray diffraction analysis methods. Furthermore, the variation in hardness and electrical resistivity of the MoN thin films deposited by three plasma-enhanced magnetron sputtering was explained on the basis of microstructure and residual stress of the thin films. Full article

Arc fault detection in photovoltaic systems is crucial, since it may cause incidents like fires and explosions. So far, most existing methods rely on an arc’s local features and do not characterize arc faults globally, which may lead to detection failure in noisy environments. In this paper, a fundamentally different method is proposed that relies on an arc’s global features instead of local ones. The core idea of the method is that the physical mechanisms of the arc fault signals and the normal signals are so different that they are thought to be generated by two independent sources. Based on this insight, independent component analysis (ICA) is introduced to decompose the photovoltaic system’s DC currents. By using ICA, the DC current signals with an arc fault can be decomposed into two independent signals, while the normal signals without an arc fault cannot be decomposed into two such independent signals. This indicates that arc faults can be detected by using the concept of “independence”. Then, the dynamic time warping algorithm was used to determine the independence level of the ICA outputs so as to realize end-to-end arc fault detection. Experimental results showed that our method has better performance than traditional methods in terms of detection accuracy and robustness against environmental disturbances. Full article

In coastal hot and humid regions, the steel pin of AC porcelain insulators often suffers from severe electrochemical corrosion due to surface contamination and moisture, leading to insulator string breakage. Contrary to the common belief that AC corrosion is negligible, this study reveals the significant role of the DC component in leakage currents and the synergy of this DC component with localized high current densities in accelerating corrosion, based on field investigations and experiments. Using a simulation model based on the Suwarno equivalent circuit, it is shown that non-linear contamination causes highly non-sinusoidal leakage currents, with total harmonic distortion up to 40% and a DC component of approximately 22%. To mitigate this, a conductive silicone rubber coating is proposed to block moisture and distribute leakage current evenly, keeping surface current density below the critical threshold of 100 A/m². Simulations indicate that a 2 mm thick coating with conductivity around 10⁻⁴ S/m effectively reduces current density to a safe level. Accelerated corrosion tests confirm that this conductive coating significantly suppresses pitting corrosion caused by high current densities, outperforming traditional insulating coatings. This study presents a practical and effective approach for protecting AC insulators in harsh environments, contributing to improved transmission line reliability in high-temperature and high-humidity regions. Full article

The increasing use of UAVs has reshaped urban logistics, enabling sustainable alternatives to traditional deliveries. To address critical issues inherent in the system, the proposed study presents the design and evaluation of an innovative unmanned aerial vehicle (UAV) prototype that integrates advanced electronic components and artificial intelligence (AI), with the aim of reducing environmental impact and enabling autonomous navigation in complex urban environments. The UAV platform incorporates brushless DC motors, high-density LiPo batteries and perovskite solar cells to improve energy efficiency and increase flight range. The Deep Q-Network (DQN) allocates energy and selects reference points in the presence of wind and payload disturbances, while an integrated sensor system monitors motor vibration/temperature and charge status to prevent failures. In urban canyon and field scenarios (wind from 0 to 8 m/s; payload from 0.35 to 0.55 kg), the system reduces energy consumption by up to 18%, increases area coverage by 12% for the same charge, and maintains structural safety factors > 1.5 under gust loading. The approach combines sustainable materials, efficient propulsion, and real-time AI-based navigation for energy-conscious flight planning. A hybrid methodology, combining experimental design principles with finite-element-based structural modelling and AI-enhanced monitoring, has been applied to ensure structural health awareness. The study implements proven edge-AI sensor fusion architectures, balancing portability and telemonitoring with an integrated low-power design. The results confirm a reduction in energy consumption and CO₂ emissions compared to traditional delivery vehicles, confirming that the proposed system represents a scalable and intelligent solution for last-mile delivery, contributing to climate resilience and urban sustainability. The findings position the proposed UAV as a scalable reference model for integrating AI-driven navigation and renewable energy systems in sustainable logistics. Full article

Major depressive disorder (MDD) is a prevalent and disabling condition. Transcranial direct current stimulation (tDCS) may improve symptoms by modulating neuroplastic and inflammatory mechanisms. This randomized, double-blind, placebo-controlled trial will recruit adult outpatients with MDD showing residual symptoms despite at least four weeks of stable SSRI treatment. Participants will be randomized to active or sham add-on tDCS while continuing their antidepressant regimen. The intervention will consist of 15 sessions over 3 weeks, targeting the left dorsolateral prefrontal cortex (anode F3, cathode F4) at 2 mA for 30 min per session. The primary outcome is the reduction of depressive symptoms measured by the Hamilton Depression Rating Scale-17 (HDRS), with remission defined as HDRS-17 ≤ 7. Secondary outcomes include cognitive performance (attention, executive functioning, memory), serum biomarkers (BDNF, VEGF, NGF, NRG1, angiogenin, IGF1, IL-6, TNF-α), cortical excitability assessed by transcranial magnetic stimulation (motor threshold, silent period, intracortical inhibition/facilitation), and cerebral hemodynamics by transcranial Doppler sonography (blood flow velocity, pulsatility, resistivity). Assessments will occur at baseline, post-treatment, and 3- and 6-month follow-ups. This trial aims to evaluate the efficacy of adjunctive tDCS in MDD with residual symptoms and its biological correlates, bridging clinical improvement with electrophysiological and neurovascular mechanisms. Full article

This study presents a comparative analysis of efficiency and harmonic generation in Triple Active Bridge (TAB) converters under two operating configurations: Case I, with one input source and two loads, and Case II, with two input sources and one load. Two modulation strategies, Single-Phase Shift (SPS) and Dual-Phase Shift (DPS), are evaluated through frequency-domain modeling and simulations performed in MATLAB/Simulink. The analysis is complemented by experimental validation on a laboratory prototype. The results show that DPS reduces harmonic amplitudes, decreases conduction losses, and improves output waveform quality, leading to higher efficiency compared to SPS. Harmonic current spectra and total harmonic distortion (THD) are analyzed to quantify the impact of each modulation method. The findings highlight that DPS is more suitable for applications requiring stable power transfer and improved efficiency, such as renewable energy systems, electric vehicles, and multi-source DC microgrids. Full article

Background/Objectives: While oral nutritional supplements (ONSs) are known to support general growth in undernourished children, their specific effects on body composition and bone health remain underexplored. This manuscript evaluates the impact of ONS combined with dietary counselling (DC) on these outcomes in Indian children aged 3 to 6.9 years at nutritional risk, within the framework of a larger randomized controlled trial assessing multiple growth parameters. Methods: This prospective, randomized controlled trial was conducted among Indian children, both male and female participants with picky eating habits and at risk of undernutrition, aged 3 to 6.9 years (height-for-age and weight-for-height below the 25th percentile per WHO Growth Standards and Growth Reference). Participants were randomized in a 1:1 ratio to receive either ONS + DC or DC alone for 6 months. Body composition, bone mineral density (BMD), and bone mineral content (BMC) were measured using dual-energy X-ray absorptiometry (DXA) at baseline and after 6 months. Group differences were analyzed to evaluate intervention effects. Results: A total of 223 children were enrolled and randomized. At 6 months, the test group showed significantly greater improvements in BMD (0.023 g/cm²) compared to the control (0.017 g/cm²; p = 0.004), and a greater gain in BMC (36.60 g vs. 28.48 g; p =0.0007). Lean mass increased significantly more in the test group (926.33 g) versus the control (801.48 g; p = 0.0401). Fat mass showed a numerical reduction in the test group (−171.42 g) compared with the control group (−114.60 g), although this difference was not statistically significant. Conclusions: These findings highlight the potential of targeted nutritional interventions to favorably improve body composition and bone health during critical growth periods in undernourished children, offering a promising approach to address early-life nutritional deficits with lasting health benefits. Full article