Search Results (15,933)

Several types of self-balancing vehicles have been successfully developed and commercialized in the past two decades, both as manned vehicles and as autonomous mobile robots. At the same time, due to their characteristic instability and underactuation, a large body of research has been devoted to their control. However, despite this practical and theoretical interest, the current publicly available literature does not cover their systematic design and development. In particular, overall processes that lead to a finished vehicle starting from a set of requirements and specifications have not been examined in the literature. Within this context, this paper contributes a comprehensive mechatronic, dynamics-based procedure for the design of this class of vehicles; to promote clarity of exposition, the procedure is systematically presented using Model-Based Systems Engineering tools and principles. In particular, the proposed design method is developed and formalized starting from an original description of the vehicle, which is treated as a complex system composed of several interconnected multi-domain components that exchange power and logical flows through suitable interfaces. A key focus of this work is the analysis of these exchanges, with the goal of defining a minimal set of quantities that should be necessarily considered to properly design the vehicle. As a salient result, the design process is organized in a logical sequence of steps, each having well-defined inputs and outputs. The procedure is also graphically outlined using standardized formalisms. The design method is shown to cover all the mechanical, electrical, actuation, measurement and control components of the system, and to allow the unified treatment of a large variety of different vehicle variants. The procedure is then applied to a specific case study, with the goal of developing the detailed design of a full-scale vehicle. The main strengths of the proposed approach are then widely highlighted and discussed. Full article

In industrial scenarios, the control of permanent magnet synchronous servo motors is mostly achieved with proportional–integral controllers, which require manual adjustment of control parameters. At the same time, the performance of the servo system is usually disturbed by internal characteristic changes, load changes, and external factors. Therefore, preset control parameters may not achieve the desired optimal performance. Many scholars use intelligent algorithms, such as neural networks, to adaptively tune control parameters. However, the offline pre-training of neural networks is often time- and resource-consuming. Due to the lack of a model pre-training process in the neural network online self-tuning process, randomly setting the initial network weight seriously affects the position tracking performance of the servo control system in the start-up phase. In this paper, the physical model and the traditional frequency domain-tuning method of the three-closed-loop permanent magnet synchronous servo system are analyzed. Combined with the neural network PI control parameter self-tuning method and physical symmetry, a physical information-driven optimization framework is proposed. To demonstrate its superiority, the neural network PI controller and the proposed optimization framework are used to control the single-axis sine wave trajectory. The results show that the optimization framework proposed can effectively improve the position tracking control performance of the servo control system in the start-up phase by setting the threshold of the servo control parameters, reduce the position tracking control error to 0.75 rads in the start-up phase, and reduce the position tracking drop caused by a sudden load by 25%. This method achieves the independent optimization adjustment of control parameters under position tracking control, providing a reference for the intelligent control of permanent magnet synchronous servo motors. Full article

The WHO considers the Epidermal Growth Factor Receptor (EGFR) one of the key biomarkers of glioblastoma (GB). EGFR can be identified and targeted using molecular recognition elements (MoREs), like aptamers and aptamer–drug conjugates (ApDCs). Understanding the kinetics of anti-EGFR ApDC interactions with EGFR as well as the kinetics of their internalization into the cells is a crucial step for the further development of anti-EGFR ApDCs. For the first time, a novel approach was implemented to study real-time kinetics by measuring the cellular index (CI) using impedance (xCELLigence). Doxorubicin (DOX) was used as an indicator drug. Because DOX intercalates into the DNA double helix, aptamer–DOX non-covalent complexes were obtained. For the anti-EGFR DNA aptamer GR20, an additional duplex was constructed by synthesizing the extra region (GR20h) and via hybridization with the complementary oligonucleotide (h’) to form a duplex (hh’), thus creating the aptamer construct with complementary oligonucleotide (ACCO) GR20hh’. The original HPLC method quantified the assembly efficiency of an ACCO. The ACCO GR20hh’ retained affinity for the recombinant extracellular domain of EGFR, as measured using Biolayer Interferometry (BLI). According to cytofluorimetry, the ACCO GR20hh’ interacts with cells of continuous culture from GB patient (CCGBP) surgical samples. The DOX–ACCO GR20hh’ complexes are more efficiently internalized by EGFR+ cells lines A-431 and CCGBP 107 than DOX alone. Full article

Well integrity is paramount for the safe, environmentally responsible, and economically viable operation of wells throughout their lifecycle, encompassing conventional oil and gas production, unconventional resource extraction (e.g., shale gas and tight oil), and geological storage applications (CO₂, H₂, and natural gas). This review presents a comprehensive synthesis of well integrity challenges, failure mechanisms, monitoring technologies, and management strategies across these operational domains. Key integrity threats—including cement sheath degradation (chemical attack, debonding, cracking, microannuli), casing failures (corrosion, collapse, burst, buckling, fatigue, wear, and connection damage), sustained casing pressure (SCP), and wellhead leaks—are examined in detail. Unique challenges posed by hydraulic fracturing in unconventional wells and emerging risks in CO₂ and hydrogen storage, such as corrosion, carbonation, embrittlement, hydrogen-induced cracking (HIC), and microbial degradation, are also highlighted. The review further explores the evolution of integrity standards (NORSOK, API, ISO), the implementation of Well Integrity Management Systems (WIMS), and the integration of advanced monitoring technologies such as fiber optics, logging tools, and real-time pressure sensing. Particular emphasis is placed on the role of digital technologies—including artificial intelligence, machine learning, and digital twin systems—in enabling predictive maintenance, early failure detection, and lifecycle risk management. The novelty of this review lies in its integrated, cross-domain perspective and its emphasis on digital twin applications for continuous, adaptive well integrity surveillance. It identifies critical knowledge gaps in modeling, materials qualification, and data integration—especially in the context of long-term CO₂ and H₂ storage—and advocates for a proactive, digitally enabled approach to lifecycle well integrity. Full article

UAV delivery and ground transfer scheduling in emergency scenarios represent critical technological systems for enhancing disaster response capabilities and safeguarding lives and property. This study systematically reviews recent advances across eight core research domains: UAV emergency delivery systems, ground–air integrated transportation coordination, emergency logistics optimization, UAV path planning and scheduling algorithms, collaborative optimization between ground vehicles and UAVs, emergency response decision support systems, low-altitude economy and urban air traffic management, and intelligent transportation system integration. Research findings indicate that UAV delivery technologies in emergency contexts have evolved from single-aircraft applications to intelligent multi-modal collaborative systems, demonstrating significant advantages in medical supply distribution, disaster relief, and search-and-rescue operations. Current technological development exhibits four major trends: hybrid optimization algorithms, multi-UAV cooperation, artificial intelligence enhancement, and real-time adaptation capabilities. However, critical challenges persist, including regulatory framework integration, adverse weather adaptability, cybersecurity protection, human–machine interface design, cost–benefit assessment, and standardization deficiencies. Future research should prioritize distributed decision architectures, robustness optimization, cross-domain collaboration mechanisms, emerging technology integration, and practical application validation. This comprehensive review provides systematic theoretical foundations and practical guidance for emergency management agencies in formulating technology development strategies, enterprises in investment planning, and research institutions in determining research priorities. Full article

Despite its wide acceptance, one of the most critical limitations of Terahertz wave technology is its high sensitivity to moisture. This limitation can, in turn, be exploited for use in moisture detection applications. This work presents a quantitative, non-invasive characterization of moisture content in standard gypsum drywall using Terahertz Time-Domain Spectroscopy (THz-TDS). With an increase in the moisture content of the drywall sample, experimental results indicated an increase in the dielectric properties such as the refractive index, permittivity, absorption coefficient, extinction coefficient, and dissipation factor. The demonstrated sensitivity to moisture establishes THz-TDS as a powerful tool for structural monitoring, hidden defect detection, and electromagnetic modeling of real-world building environments. Beyond material diagnostics, these findings have broader implications for THz indoor propagation studies, especially for emerging sub-THz and low THz communication technologies in 5G/6G and THz imaging of objects hidden behind the wall. Full article

In contemporary industrial machinery, bearings are a vital component, so the ability to diagnose bearing faults is extremely important. Current methodologies face challenges in feature extraction and perform suboptimally in environments with high noise levels. This paper proposes an enhanced, multimodal, feature-fusion-bearing fault diagnosis model. Integrating a 1DCNN-dual MLP framework with an enhanced two-way cross-attention mechanism enables in-depth feature fusion. Firstly, the raw fault time-series data undergo fast Fourier transform (FFT). Then, the original time-series data are input into a multi-layer perceptron (MLP) and a one-dimensional convolutional neural network (1DCNN) model. The frequency-domain data are then entered into the other multi-layer perceptron (MLP) model to extract deep features in both the time and frequency domains. These features are then fed into a serial bidirectional cross-attention mechanism for feature fusion. At the same time, a GCOS learning rate scheduler has been developed to automatically adjust the learning rate. Following fifteen independent experiments on the Case Western Reserve University bearing dataset, the fusion model achieved an average accuracy rate of 99.83%. Even in a high-noise environment (0 dB), the model achieved an accuracy rate of 90.66%, indicating its ability to perform well under such conditions. Its accuracy remains at 86.73%, even under 0 dB noise and variable operating conditions, fully demonstrating its exceptional robustness. Full article

Detecting physical fatigue can help prevent overexertion. While typically defined at the muscle level, systemic fatigue remains less clear. Heart rate variability (HRV) reflects autonomic adaptability to physical stressors and may provide insight into fatigue-related responses. This study investigated the impact of physical fatigue on HRV and its correlation with endurance performance. Twenty participants (9 F, 11 M; 23.4 ± 5.0 y) walked on the treadmill at 1.25 m/s with progressively increased incline. HRV metrics were derived from baseline standing (STAND), pre-fatigued (PRE) and post-fatigued walking (POST). Time-domain HRV measures (lnTRI and lnTINN) were significantly reduced at POST compared to PRE or STAND (p < 0.05). Non-linear measures (DFA-α1, lnApEn, and lnSampEn) decreased at POST, while lnPoincaré SD2/SD1 increased. Normalized frequency-domain measures showed no condition effects. Baseline non-linear measures (lnApEn, lnSampEn, lnPoincaré SD2/SD1), normalized frequency measures and Total Power were significantly correlated with total fatiguing duration. Significant reductions in HRV and irregularity were observed post-fatigue. Greater baseline variability, irregularity, and high-frequency band power, reflecting parasympathetic activity, were associated with better endurance performance. Time-domain and non-linear measures were more sensitive to fatigue, whereas frequency-domain measures remain useful for identifying associations with endurance. The findings highlight HRV features that could enhance wearable sensing for fatigue and performance. Full article

In this work, a controller hardware-in-the-loop (CHIL) simulation of a grid-connected three-phase inverter equipped with an LCL filter is implemented using a real-time digital simulator (RTDS) as the plant and a digital signal processor (DSP) as the control hardware. This work identifies and discusses the critical aspects of the CHIL implementation process, emphasizing the relevance of the control delays that arise from sampling, computation, and pulse width modulation (PWM), which also adversely affect system stability, accuracy, and performance. Time and frequency domains are used to validate the modeling of the system, either to represent large-signal or small-signal models. This work shows multiple representations of the system under study: the fundamental frequency model, the switched model, and the switched model controlled by the DSP, are used to validate the nonlinear model, whereas the impedance-based modeling is followed to validate the linear representation. The results demonstrate a strong correlation among the models, confirming that the delay effects are accurately captured in the different simulation approaches. This comparison provides valuable insights into configuration practices that improve the fidelity of CHIL-based validation and supports impedance-based stability analysis in power electronic systems. The findings are particularly relevant for wideband modeling and real-time studies in electromagnetic transient analysis. Full article

This paper explores some frame bundles and physical implications of Killing vector fields on the two-sphere ${\mathbb{S}}^2$, culminating in a novel application to Maxwell’s equations in free space. Initially, we investigate the Killing vector fields on ${\mathbb{S}}^2$ (represented by the unit sphere of ${\mathbb{R}}^3$), which generate the isometries of the sphere under the rotation group $SO\left(3\right)$. These fields, realized as functions $K_v:{\mathbb{S}}^2\to {\mathbb{R}}^3$, defined by $K_v\left(q\right)=v\times q$ for a fixed $v\in {\mathbb{R}}^3$ and any$q\in {\mathbb{S}}^2$, generate a three-dimensional Lie algebra isomorphic to $\mathfrak{so}\left(3\right)$. We establish an isomorphism $K:{\mathbb{R}}^3\to \mathcal{K}\left({\mathbb{S}}^2\right)$, mapping vectors $v=au$ (with $u\in {\mathbb{S}}^2$) to scaled Killing vector fields $a{K}_u$, and analyze its relationship with $SO\left(3\right)$ through the exponential map. Subsequently, at a fixed point $e\in {\mathbb{S}}^2$, we construct a smooth orthonormal right-handed tangent frame $f_e:{\mathbb{S}}^2\setminus \{e,-e\}\to T{\left({\mathbb{S}}^2\right)}^2$, defined as $f_e\left(u\right)=({\widehat{K}}_e\left(u\right),u\times {\widehat{K}}_e\left(u\right))$, where ${\widehat{K}}_e$ is the unit vector field of the Killing field $K_e$. We verify its smoothness, orthonormality, and right-handedness. We further prove that any smooth orthonormal right-handed frame on ${\mathbb{S}}^2\setminus \{e,-e\}$ is either $f_e$ or a rotation thereof by a smooth map $\rho :{\mathbb{S}}^2\setminus \{e,-e\}\to SO\left(3\right)$, reflecting the triviality of the frame bundle over the parallelizable domain. The paper then pivots to an innovative application, constructing solutions to Maxwell’s equations in free space by combining spherical symmetries with quantum mechanical de Broglie waves in tempered distribution wave space. The deeper scientific significance lies in bringing together differential geometry (via $SO\left(3\right)$ symmetries), quantum mechanics (de Broglie waves in Schwartz distribution theory), and electromagnetism (Maxwell’s solutions in Schwartz tempered complex fields on Minkowski space-time), in order to offer a unifying perspective on Maxwell’s electromagnetism and Schrödinger’s picture in relativistic quantum mechanics. Full article

Background: The Nursing Work Environment (NWE) plays a critical role in determining the quality of care, staff well-being, and organizational performance, particularly in oncology settings. Despite increasing attention, a comprehensive synthesis of organizational factors shaping oncology NWEs has been lacking. This scoping review aimed to describe the key features of oncology NWEs and to explore the outcomes associated with these characteristics. Methods: A scoping review was conducted following the Joanna Briggs Institute guidelines. Peer-reviewed studies published in English or Italian were included without time restrictions. Literature searches were performed in MEDLINE via PubMed, CINAHL, and Scopus between January and April 2025. Results: Twenty studies met the inclusion criteria. Key organizational characteristics of oncology NWEs were grouped into the following four domains: leadership and organizational support; workload and resource availability; ethical climate and collegial relationships; and physical and structural conditions of care settings. Across the studies, a positive NWE was frequently reported to be associated with improved nurse-related outcomes and, to a lesser extent, with patient-related outcomes. However, these associations should be interpreted with caution due to the heterogeneity of contexts and the predominance of cross-sectional designs. Conclusions: The NWE is a strategic element in delivering effective, safe, and sustainable oncology care. Practical actions for nurse managers and healthcare leaders include implementing leadership training programs, ensuring adequate staffing and resource allocation, fostering open communication, and promoting interdisciplinary collaboration. These measures are essential to protect staff well-being and guarantee high-quality, patient-centered care. Full article

Accessible, dependable cognitive assessment is integral to patient care of people with multiple sclerosis (PwMS). Traditional neuropsychological tests are well validated in the multiple sclerosis (MS) population, but not without limitations, such as the time and financial cost associated with traditional in person administration. Recent endeavors have sought to refine assessment, with particular attention to psychometric properties, accessibility, efficiency, and other practical considerations. One approach has been to streamline neuropsychological batteries to brief measures of essential domains, such as the Brief International Cognitive Assessment for MS (BICAMS). Another approach is the use of computerized neuropsychological assessment devices (CNADs). A systematic review of CNADs in PwMS was published in 2019. However, research has continued to expand in the years since. Here, we present an updated review of the BICAMS and further development of CNADs in MS. Tests with strong psychometric foundations are highlighted. Full article

Thermal oxidative aging failure of high-temperature vulcanized silicone rubber (HTV) in high-voltage insulators is the core hidden danger of power grid security. In this study, terahertz time domain spectroscopy (THz-TDS) and attenuated total reflection infrared spectroscopy (ATR-FTIR) were combined to reveal the quantitative structure–activity relationship between dielectric response and chemical group evolution of HTV during accelerated aging at 200 °C for 80 days. In this study, HTV flat samples were made in the laboratory, and the dielectric spectrum of HTV in the range of 0.1 THz to 0.4 THz was extracted by a terahertz time–domain spectrum platform. ATR-FTIR was used to analyze the functional group change trend of HTV during aging, and the three-stage evolution of the dielectric real part (0.16 THz), the dynamics of the carbonyl group, the monotonic rise of the dielectric imaginary part (0.17 THz), and the linear response of silicon-oxygen bond breaking were obtained by combining the double Debye relaxation theory. Finally, three aging stages of HTV were characterized by dielectric loss angle data. The model can warn about the critical point of early oxidation and main chain fracture and identify the risk of insulation failure in advance compared with traditional methods. This study provides a multi-scale physical basis for nondestructive life assessment in a silicon rubber insulator. Full article

Solid solutions of the metallocenes ferrocene (Cp₂Fe), nickelocene (Cp₂Ni), and cobaltocene (Cp₂Co) have been prepared by manually grinding the components together, or by co-crystallizing them from solution. In the solid solutions Cp₂Fe/Cp₂Ni and Cp₂Co/Cp₂Ni, the cyclopentadienyl (Cp) protons relax via dipolar electron–proton interactions, which represent the dominant relaxation mechanism. The ¹H T₁ relaxation times of the molecules Cp₂Ni and Cp₂Co, dissolved in CDCl₃, and in the solid solutions, show that the relaxation takes place intramolecularly. The relaxation of the protons is propagated exclusively via the unpaired electrons of the metal centers to which their Cp rings are coordinated, due to the large intermolecular distances that are greater than 3.91 Å. In contrast, the intramolecular distances between the electrons of the metal atoms and the protons of their coordinated Cp rings are merely 2.70 Å. Using these intramolecular distances and the ¹H T₁ relaxation times, the electron relaxation times T_1e have been determined as 17 × 10⁻¹³ s in CDCl₃ solutions and 45 × 10⁻¹³ s in the solid state for Cp₂Ni. The corresponding T_1e times for Cp₂Co are calculated as ca. 5 × 10⁻¹³ s and 20 × 10⁻¹³ s. Grinding Cp₂Fe and Cp₂Ni together leads to two different ¹H T₁ relaxation times for the protons of Cp₂Fe. The longer T₁ relaxation time indicates domains that consist mostly of Cp₂Fe molecules. The short T₁ times show a close contact of Cp₂Fe and Cp₂Ni molecules. An analysis of the short ¹H T₁ times reveals the presence of at least two to three short distances of 3.91 Å between Cp₂Fe and Cp₂Ni molecules. These results support the hypothesis that dry grinding of the metallocenes Cp₂Fe and Cp₂Ni in ratios that were changed in 10% increments from 90%/10% to 30%/70% leads to domains that mostly consist of Cp₂Fe molecules, and additionally to domains that contain a mixture of the components on the molecular level. Full article

Focusing on the discovery of new $\delta$ Scuti and $\gamma$ Doradus stars, we analyzed the Transiting Exoplanet Survey Satellite (TESS) light curves for 193,940 A-F stars selected from four legacy catalogs—the Henry Draper Catalogue (HD), the Smithsonian Astrophysical Observatory (SAO) Star Catalog, the Positions and Proper Motions Catalog (PPM), and the Bonner Durchmusterung (BD, including its extensions). Through visual inspection of light curve morphologies and periodograms, combined with evaluation of stellar parameters, we identified over 51,850 previously unreported variable stars. These include 15,380 $\delta$ Scuti, 18,560 $\gamma$ Doradus, 28 RR Lyrae stars, 260 heartbeat candidates, and 2645 eclipsing binaries, along with thousands of other variable types. Notably, over 4145 variables exhibit hybrid $\delta$ Scuti-$\gamma$ Doradus pulsations, and more than 380 eclipsing binaries feature pulsating primary components. This study reveals a substantial population of bright, previously undetected variables, providing a valuable resource for ensemble asteroseismology, binary evolution studies, and Galactic structure research. Our results also highlight the surprising richness in variability still hidden within well-known stellar catalogs and the continued importance of high-precision, time-domain surveys such as TESS. Full article