Search Results (663)

The study of vibration characteristics and suppression methods in integrated electric drive systems of electric vehicles is of critical importance. To investigate these characteristics, both current harmonics within the motor and nonlinear factors within the drivetrain were considered. A 17-degree-of-freedom nonlinear torsional–planar dynamic model was developed, with electromagnetic torque and output speed as coupling terms. The model’s accuracy was experimentally validated, and the system’s dynamic responses were analyzed under different working conditions. To mitigate vibrations caused by torque ripple, a coordinated control strategy was proposed, combining a quasi-proportional multi-resonant (QPMR) controller and a full-frequency harmonic controller (FFHC). The results demonstrate that the proposed strategy effectively suppresses multi-order current harmonics in the driving motor, reduces torque ripple by 45.1%, and enhances transmission stability. In addition, the proposed electromechanical coupling model provides valuable guidance for the analysis of integrated electric drive systems. Full article

Optical solitons have emerged as a highly active research domain in nonlinear fiber optics, driving significant advancements and enabling a wide range of practical applications. This study investigates the dynamics of dark solitons in systems governed by the resonant nonlinear Schrödinger equation (RNLSE). For the RNLSE with third-order (3OD) and fourth-order (4OD) dispersions, the dark soliton solution of the equation in the (1+1)-dimensional case is derived using the F-expansion method, and the analytical study is extended to the (2+1)-dimensional case via the self-similar method. Subsequently, the nonlinear equation incorporating perturbation terms is further studied, with particular attention given to the dark soliton solutions in both one and two dimensions. The soliton dynamics are illustrated through graphical representations to elucidate their propagation characteristics. Finally, modulation instability analysis is conducted to evaluate the stability of the nonlinear system. These theoretical findings provide a solid foundation for experimental investigations of dark solitons within the systems governed by the RNLSE model. Full article

The influence of social media personalities has grown significantly, especially among youth audiences who spend substantial time on platforms like TikTok. The emergence and popularity of different types of social media influencers accelerated during the COVID-19 pandemic in many countries, including South Africa. In turn, this period also saw a surge in youth audiences following these influencers. This rapid growth of influencer followings among young people is largely driven by specific types of content that resonate with them, thus encouraging continued engagement. However, the benefits that these young followers gain from engaging with various influencers and the factors driving their preferences for specific influencers remain underexplored, particularly within the context of South African students within higher education. Therefore, this study explores the types of social media influencers most followed by university students at a South African University and investigates the key factors that drive their preferences. A structured online questionnaire was distributed, gathering both multiple-choice and open-ended responses from students. The data were analyzed using categorical frequency counts and thematic analysis. The data highlight how students actively turn to influencers as emotional anchors, role models, and sources of practical guidance. Their engagement reflects a deep need for connection, inspiration, and identity formation in a challenging academic and social environment. These patterns show that influencer content is not just entertainment but plays a critical developmental role. Understanding these motivations helps educators, policymakers, and brands to align better with youth values. The significance of these results lies in how influencer content is now coming in to fill the emotional, cultural, and educational gaps left by traditional systems among the young South African university students in this modern era. Full article

This study designed and validated a dual-component beat-frequency quartz-enhanced photoacoustic spectroscopy (BF-QEPAS) gas detection system utilizing time-division multiplexing (TDM). By applying TDM to drive distributed feedback lasers, the system achieved the simultaneous detection of acetylene and methane. Its key innovation lies in exploiting the transient response of the quartz tuning fork (QTF) to acquire gas concentrations while concurrently capturing the QTF resonant frequency and quality factor in real-time. Owing to the short beat period and rapid system response, this approach significantly reduces time-delay constraints in time-division measurements, eliminating the need for periodic calibration inherent in conventional methods and preventing detection interruptions. The experimental results demonstrate minimum detection limits of 5.69 ppm for methane and 0.60 ppm for acetylene. Both gases exhibited excellent linear responses over the concentration range of 200 ppm to 4000 ppm, with the R² value for methane being 0.996 and for acetylene being 0.997. The system presents a viable solution for the real-time, calibration-free monitoring of dissolved gases in transformer oil. Full article

In this research, a step-down converter with a lossless snubber is proposed, and its output is floating; therefore, it can be applied to LED driving applications. Such a structure is a modification of the conventional buck converter by adding a resonant capacitor, a resonant inductor, and two diodes to form this lossless snubber to reduce the switching loss during the switching period. Although the efficiency improvement in this circuit is not as good as the existing soft switching circuits, this circuit has the advantages of simple structure, easy control, and zero voltage switching (ZVS) cutoff. Full article

Langevin ultrasonic transducers, also known as Tonpilz transducers, are widely used in high-power ultrasonic applications, including underwater sonar arrays, ultrasonic cleaning, and sonication devices. Traditionally designed for narrowband operation centered on a fundamental longitudinal resonance mode, their performance has been limited by structural constraints that tie resonance frequency to overall transducer length and mass. However, technical demands in biomedical, industrial, and underwater technologies have driven the development of broadband Langevin transducers capable of operating over wider frequency ranges. Lower frequencies are desirable for deep penetration and cavitation effects, while higher frequencies offer improved resolution and directivity. Recent design innovations have focused on modifications to the three key components of the transducer: the head mass, piezoelectric drive stack, and tail mass. Techniques such as integrating flexural or edge-resonance modes, adopting piezocomposite stacks, and tailoring structural geometry have shown promising improvements in bandwidth and transmitting efficiency. This review examines broadband Langevin transducer designs over the past three decades, offering detailed insights into design strategies for future development of high-power broadband ultrasonic transducers. Full article

Colorectal carcinoma remains one of the primary contributors to cancer deaths; however, it is also considered a preventable type of cancer, because the prognosis of the disease is directly dependent on its timely detection. Developing accurate risk prediction models for colorectal cancer is crucial for identifying individuals at both low and high risk, as risk stratification determines the need for additional interventions, which carry their own risks. The development of new non-invasive diagnostic methods based on biomaterial analysis, alongside standard diagnostic techniques such as colonoscopy with biopsy, computed tomography scanning, and magnetic resonance imaging, can address multiple objectives: improving screening accuracy, providing a comprehensive assessment of minimal residual disease, identifying patients at a high risk of colorectal cancer, and evaluating the effectiveness of ongoing treatments. The lack of sensitive diagnostic methods drives contemporary research toward the discovery of new tools for detecting tumor cells, particularly through the examination of biological materials, including blood, exhaled air, and tumor tissue itself. In this article, we analyze current studies regarding biomarkers in colorectal cancer and prognostic significance. Full article

Musculoskeletal (MSK) disorders remain a major global cause of disability, with diagnostic complexity arising from their heterogeneous presentation and multifactorial pathophysiology. Recent advances across imaging modalities, molecular biomarkers, artificial intelligence applications, and point-of-care technologies are fundamentally reshaping musculoskeletal diagnostics. This review offers a novel synthesis by unifying recent innovations across multiple diagnostic imaging modalities, such as CT, MRI, and ultrasound, with emerging biochemical, genetic, and digital technologies. While existing reviews typically focus on advances within a single modality or for specific MSK conditions, this paper integrates a broad spectrum of developments to highlight how use of multimodal diagnostic strategies in combination can improve disease detection, stratification, and clinical decision-making in real-world settings. Technological developments in imaging, including photon-counting detector computed tomography, quantitative magnetic resonance imaging, and four-dimensional computed tomography, have enhanced the ability to visualize structural and dynamic musculoskeletal abnormalities with greater precision. Molecular imaging and biochemical markers such as CTX-II (C-terminal cross-linked telopeptides of type II collagen) and PINP (procollagen type I N-propeptide) provide early, objective indicators of tissue degeneration and bone turnover, while genetic and epigenetic profiling can elucidate individual patterns of susceptibility. Point-of-care ultrasound and portable diagnostic devices have expanded real-time imaging and functional assessment capabilities across diverse clinical settings. Artificial intelligence and machine learning algorithms now automate image interpretation, predict clinical outcomes, and enhance clinical decision support, complementing conventional clinical evaluations. Wearable sensors and mobile health technologies extend continuous monitoring beyond traditional healthcare environments, generating real-world data critical for dynamic disease management. However, standardization of diagnostic protocols, rigorous validation of novel methodologies, and thoughtful integration of multimodal data remain essential for translating technological advances into improved patient outcomes. Despite these advances, several key limitations constrain widespread clinical adoption. Imaging modalities lack standardized acquisition protocols and reference values, making cross-site comparison and clinical interpretation difficult. AI-driven diagnostic tools often suffer from limited external validation and transparency (“black-box” models), impacting clinicians’ trust and hindering regulatory approval. Molecular markers like CTX-II and PINP, though promising, show variability due to diurnal fluctuations and comorbid conditions, complicating their use in routine monitoring. Integration of multimodal data, especially across imaging, omics, and wearable devices, remains technically and logistically complex, requiring robust data infrastructure and informatics expertise not yet widely available in MSK clinical practice. Furthermore, reimbursement models have not caught up with many of these innovations, limiting access in resource-constrained healthcare settings. As these fields converge, musculoskeletal diagnostics methods are poised to evolve into a more precise, personalized, and patient-centered discipline, driving meaningful improvements in musculoskeletal health worldwide. Full article

Amid the accelerating processes of modernization and commercialization, traditional rural public spaces are increasingly losing their cultural value and social functions. This study investigates the transformative role of art intervention in enhancing the quality and cultural significance of rural public spaces, with a focus on Machang Village in Tengchong, China. The study first develops a conceptual model to explore the causal relationships and pathways between these influencing factors. Drawing on this framework, the research then uses Structural Equation Modeling (SEM) to empirically test a multi-dimensional resident satisfaction model that incorporates spatial aesthetics, functional suitability, historical-cultural identity, and emotional cognition. Through field surveys and data collected from 224 residents, the study reveals that cultural emotions and functional completeness are the most influential factors in driving overall satisfaction. Artistic innovation and aesthetics contribute moderately, indicating that visual creativity alone is insufficient without deeper cultural integration and functional coherence. The findings suggest a dual-pathway satisfaction mechanism, where both symbolic emotional resonance and practical usability shape residents’ perceptions of public space quality. The study offers theoretical and practical insights into optimizing rural public space design, advocating for art-led, community-engaged, and culturally embedded approaches to rural revitalization. Full article

Breast cancer (BC) is a highly heterogeneous disease with distinct molecular subtypes, each exhibiting unique metabolic adaptations that drive tumor progression and therapy resistance. Metabolomics has emerged as a powerful tool for understanding cancer metabolism and identifying clinically relevant biomarkers guiding personalized therapeutic strategies. Advances in analytical techniques such as mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy have enabled the identification of metabolic alterations associated with BC initiation, progression, and treatment response (dysregulated glycolysis, lipid metabolism, amino acid utilization, and redox homeostasis). This review aims to provide a comprehensive overview of the role of metabolomics in BC research, focusing on its applications in identifying metabolic biomarkers for early diagnosis, prognosis, and treatment response. It underscores how metabolomic profiling can unravel the metabolic adaptations of different BC subtypes, offering insights into tumor biology and mechanisms of therapy resistance. Ultimately, it highlights the promise of metabolomics in driving biomarker-guided diagnostics and the development of metabolically informed, personalized therapeutic strategies in the era of precision medicine. Full article

Under China’s dual-carbon strategy, the construction sector still lacks a systematic quantitative view of what drives its shift to a circular economy. This study couples the Decision-Making Trial and Evaluation Laboratory (DEMATEL) with Total Adversarial Interpretive Structural Modeling (TAISM) to build a weighted, multi-layer model of the policy–market–organization–technology chain. DEMATEL measures causal strengths, and TAISM arranges the variables into five levels without subjective thresholds, revealing a five-stage activation pathway. Fiscal incentives and regulations start the cascade; market demand amplifies their effect into a “resonant resilience” mechanism that improves cost performance. Robustness tests show 87% hierarchy stability and causal variation within ±0.6%. Sensitivity checks indicate that policy support must supply at least 30% of total network weight, because market capital alone cannot meet circular-construction costs. A three-tier intervention—policy incentives, financial amplification, and digital decomposition via green finance, BIM, and material passports—is therefore recommended. Full article

Processing errors can result in an asymmetric stiffness distribution within a microelectromechanical system (MEMS) disk resonator gyroscope (DRG) and thereby cause a mode mismatch and reduce the mechanical sensitivity and closed-loop scale factor stability. This paper proposes an automatic mode-matching method that utilizes mode reversal to obtain the true resonant frequency of the operating state of a gyroscope for high-precision matching. This method constructs a gyroscope control system that contains a drive closed loop, sense force-to-rebalance (FTR) closed loop, and quadrature error correction closed loop. After the gyroscope was powered on and started up, the x- and y-axes were quickly switched to obtain the resonant frequencies of the two axes through a phase-locked loop (PLL), and the x-axis tuning voltage was automatically adjusted to match the two-axis frequency. The experimental results show that the method takes only 5 s to execute, the frequency matching accuracy reaches 0.01 Hz, the matching state can be maintained in the temperature range of −20 to 60 °C, and the fluctuation of the frequency split does not exceed 0.005 Hz. Full article

The air transportation system is composed of multiple elements and belongs to a complex socio-technical system. It is difficult to assess the risk of an aircraft fault because it could constantly change during operation and is influenced by numerous factors. Although traditional methods such as Failure Mode, Effects, and Criticality Analysis (FMECA) and Fault Tree Analysis (FTA) can reflect the degree of fault risk to a certain extent, they cannot accurately quantify and evaluate the fault risk under the multiple influences of human factors, random faults, and external environment. In order to solve these problems, this article proposes a fault risk assessment method for aircraft control systems based on a fault risk composite assessment framework using the Improved Risk Priority Number (IRPN) as the basis for the fault risk assessment. Firstly, a Bayesian network (BN) and Gated Recurrent Unit (GRU) are introduced into the traditional evaluation framework, and a hybrid prediction model combining static and dynamic failure probability is constructed. Subsequently, this paper uses the functional resonance analysis method (FRAM) by introducing a risk damping coefficient to analyze the propagation and evolution of fault risks and accurately evaluate the coupling effects between different functional modules in the system. Finally, taking the fault of a jammed flap/slat drive mechanism as an example, the risk of the fault is evaluated by calculating the IRPN. The calculation results show that the comprehensive failure probability of the aircraft control system in this case is 3.503 × 10⁻⁴. Taking into account the severity, the detection, and the risk damping coefficient, the calculation result of IRPN is 158.00. According to the classification standard of the risk level, the failure risk level of the aircraft belongs to a controlled risk, and emergency measures need to be taken, which is consistent with the actual disposal decision in this case. Therefore, the evaluation framework proposed in this article not only supports a quantitative assessment of system safety and provides a new method for fault risk assessments in aviation safety management but also provides a theoretical basis and practical guidance for optimizing fault response strategies. Full article

In the digital age, mobile games have become a new frontier for cultural identity and virtual consumption among Chinese Generation Z youth. With the development of the internet, users have gradually adapted to the coexistence of virtual and real identities, enriching the “small society” within games. However, virtual consumption and its underlying driving mechanisms have not received sufficient attention. Through interviews with 20 young people of Chinese Generation Z, this study argues that virtual consumption is not only about material consumption but also serves as a link between emotions and identity. In China’s increasingly atomised society, the idea of the “mimetic homeland” has become an essential interactive domain for Generation Z in the digital age. It offers individuals a dynamic space to engage with their cultural identity and sustain emotional resonance amid fragmented social conditions. In the “mimetic homeland”, game content, broadcaster charm, symbolic consumption, and player creation intertwine, allowing mobile games to create a diverse cultural identity mechanism. This mechanism rekindles players’ recognition of cultural identity and provides them with spiritual support. In mobile games, players continuously produce and consume cultural identity, using digital means to shape and spread spiritual consciousness symbols, ultimately achieving cultural identity commodification. Full article

In a susceptible individual, persistent, low-level injury to the airway epithelium initiates an exaggerated wound repair response, ultimately leading to idiopathic pulmonary fibrosis (IPF). The mechanisms driving this fibroproliferative response are not fully understood. Here, we review recent spatially resolved transcriptomics and proteomics studies that provide insight into two distinct matricellular microenvironments important in this pathological fibroproliferation. First, in response to alveolar epithelial injury, alveolar differentiation intermediate (ADI) basal cells arising from Secretoglobin (Scgb1a1) progenitors re-populate the injured alveolus remodeling the extracellular matrix (ECM). ADI cells exhibit an interconnected cellular stress response involving the unfolded protein response (UPR), epithelial–mesenchymal transition (EMT) and senescence pathways. These pathways reprogram cellular metabolism to support fibrillogenic ECM remodeling. In turn, the remodeled ECM tonically stimulates EMT in the ADI population, perpetuating the transitional cell state. Second, fibroblastic foci (FF) are a distinct microenvironment composed of activated aberrant “basaloid” cells supporting transition of adjacent mesenchyme into hyaluronan synthase (HAS^hi)-expressing fibroblasts and myofibroblasts. Once formed, FF are the major matrix-producing factories that invade and disrupt the alveolar airspace, forming a mature scar. In both microenvironments, the composition and characteristics of the ECM drive persistence of atypical epithelium sustaining matrix production. New approaches to monitor cellular trans-differentiation and matrix characteristics using positron emission tomography (PET)–magnetic resonance imaging (MRI) and optical imaging are described, which hold the potential to monitor the effects of therapeutic interventions to modify the ECM. Greater understanding of the bidirectional interrelationships between matrix and cellular phenotypes will identify new therapeutics and diagnostics to affect the outcomes of this lethal disease. Full article