Search Results (343)

Spectral features of photoionization of various levels of C III are reported. These include characteristics of Rydberg and Seaton resonances, low and high excited levels, lifetimes, and total and partial cross sections. Calculations are performed in the relativistic Breit–Pauli R-matrix method with close-coupling approximation, including damping effects on the resonance structure associated with the core-excited states produced by the electron excitation of C IV and photoionization of C III. For bound channel contribution, the close-coupling wavefunction expansion for photoionization includes ground and 14 excited states of the target ion CIV and 105 states configurations of C III. Extensive sets of atomic data for bound fine-structure levels, resulting in 762 dipole-allowed transitions, radiative probabilities, and photoionization cross sections out of J^π = 0^± − 4^± fine-structure levels are obtained. The ground-level photoionization cross section smoothly decreases with increasing energy, showing a very narrow, strong Rydberg resonance converging to the CIV 1s²2p threshold. The work shows that prominent Seaton resonances for 2sns states with n ≥ 5, caused by photoexcitation of the core electron below the 2p threshold, visibly contribute to photoabsorption from excited states of C III. The present results provide highly accurate parameters of various model applications in plasma spectroscopy. Full article

In this paper, a new mechanical vibration technology applied to continuous casting production is studied, which is used to break the dendrite at the solidification front, expand the equiaxed dendrite zone, and improve the center quality of the billet. The exciting force of this vibration technology is provided by a new type of vibration equipment (Vibration roll) independently developed and designed. Firstly, an investigation is conducted into the impacts of vibration acceleration, vibration frequency, and the contact area between the Vibration roll (VR) and the billet surface on the internal stress distribution within the billet shell, respectively. Secondly, the billet with and without vibration treatment was sampled and analyzed through industrial tests. The results show that the area ratio of equiaxed dendrites in transverse specimens treated with vibration technology was 11.96%, compared to 6.55% in untreated specimens. Similarly, for longitudinal samples, the linear ratio of equiaxed dendrites was observed to be 34.56% in treated samples and 22.95% in untreated samples. Compared to the specimens without mechanical vibration, the billet treated with mechanical vibration exhibits an increase in the area ratio and linear ratio of equiaxed dendrite ratio by 5.41% and 11.61%, respectively. Moreover, the probability of bridging at the end of solidification of the billet treated by vibration technology was significantly reduced, and the central porosity and shrinkage cavities of the billet were significantly improved. This study provides the first definitive evidence that the novel mechanical vibration technology can enhance the quality of the billet during the continuous casting process. Full article

Zn-doped carbon dots (Zn@C-210 calcination temperature at 210 °C and Zn@C-260 calcination temperature at 260 °C) were synthesized via an in situ calcination method using zinc citrate complexes as precursors, aiming to investigate the mechanisms of their distinctive fluorescence properties. A range of analytical methods were employed to characterize these nanomaterials. The mechanism study revealed that the coordination structure of Zn-O, formed through zinc doping, can induce a metal–ligand charge-transfer effect, which significantly increases the probability of radiative transitions between the excited and ground states, thereby enhancing the fluorescence intensity. The Zn@C-210 in a solid state and Zn@C-260 in water exhibited approximately 71.50% and 21.1% quantum yields, respectively. Both Zn@C-210 and Zn@C-260 exhibited excitation-independent luminescence, featuring a long fluorescence lifetime of 6.5 μs for Zn@C-210 and 6.2 μs for Zn@C-260. Impressively, zinc-doped CDs displayed exceptional biosafety, showing no acute toxicity even at 1000 mg/kg doses. Zn@C-210 has excellent fluorescence in a solid state, showing promise in anti-photobleaching applications; meanwhile, the dual functionality of Zn@C-260 makes it useful as a folate sensor and cellular imaging probe. These findings not only advance the fundamental understanding of metal-doped carbon dot photophysics but also provide practical guidelines for developing targeted biomedical nanomaterials through rational surface engineering and doping strategies. Full article

Background and Clinical Significance: Herein, we describe the clinical case of a 17-year-old patient with psychotic disorder secondary to cerebral venous thrombosis due to primary thrombophilia, which was related to protein S deficiency and a heterozygous MTHFR gene mutation with the p.Ala222Val variant. Case presentation: A 17-year-old female, with no history of previous illnesses, was admitted to the emergency service department due to a psychotic break. Psychiatric evaluation detected disorganized thought, euphoria, ideas that were fleeting and loosely associated, psychomotor excitement, and deviant judgment. On the fifth day, an inflammatory process in the parotid gland was detected, pointing out a probable viral meningoencephalitis, prompting antiviral and antimicrobial treatment. One week after antiviral and steroidal anti-inflammatory treatments, the symptoms’ improvement was minimal, which led to further neurological workup. MRI venography revealed a filling defect in the transverse sinus, consistent with cerebral venous thrombosis. Consequently, anticoagulation treatment with enoxaparin was initiated. The patient’s behavior improved, revealing that the encephalopathic symptoms were secondary to thrombosis of the venous sinus. Hematological studies indicated the cause of the venous sinus thrombosis was a primary thrombophilia caused by a heterozygous MTHFR mutation variant p.Ala222Val and a 35% decrease in plasmatic protein S. Conclusions: This case highlights the possible relationship between psychiatric and thrombotic disorders, suggesting that both the MTHFR mutation and protein S deficiency could lead to psychotic disorders. Early detection of thrombotic risk factors in early-onset psychiatric disorders is essential for the comprehensive management of patients. Full article

Studies of subradiance in a chain N two-level atoms in the single excitation regime focused mainly on the complex spectrum of the effective Hamiltonian, identifying subradiant eigenvalues. This can be achieved by finding the eigenvalues N of the Hamiltonian or by evaluating the expectation value of the Hamiltonian on a generalized Dicke state, depending on a continuous variable k. This has the advantage that the sum above N can be calculated exactly, such that N becomes a simple parameter of the system and no longer the size of the Hilbert space. However, the question remains how subradiance emerges from atoms initially excited or driven by a laser. Here we study the dynamics of the system, solving the coupled-dipole equations for N atoms and evaluating the probability to be in a generalized Dicke state at a given time. Once the subradiant regions have been identified, it is simple to see if subradiance is being generated. We discuss different initial excitation conditions that lead to subradiance and the case of atoms excited by switching on and off a weak laser. This may be relevant for future experiments aimed at detecting subradiance in ordered systems. Full article

Aimed at dealing with the problems of high reliability solution cost and low solution accuracy under random excitation, especially Gaussian white noise excitation, this paper proposes a probability density evolution and reliability analysis method for nonlinear gear transmission systems under Gaussian white noise excitation based on the path integration method. This method constructs an efficient probability density evolution framework by combining the path integration method, the Chapman–Kolmogorov equation, and the Laplace asymptotic expansion method. Based on Rice’s theory and combined with the adaptive Gauss–Legendre integration method, the transient and cumulative reliability of the system are path integration method calculated. The research results show that in the periodic response state, Gaussian white noise leads to the diffusion of probability density and peak attenuation, and the system reliability presents a two-stage attenuation characteristic. In the chaotic response state, the intrinsic dynamic instability of the system dominates the evolution of the probability density, and the reliability decreases more sharply. Verified by Monte Carlo simulation, the method proposed in this paper significantly outperforms the traditional methods in both computational efficiency and accuracy. The research reveals the coupling effect of Gaussian white noise random excitation and nonlinear dynamics, clarifies the differences in failure mechanisms of gear systems in periodic and chaotic states, and provides a theoretical basis for the dynamic reliability design and life prediction of nonlinear gear transmission systems. Full article

The paper innovatively studies the impact of dual randomness of structural parameters and seismic excitation on the seismic reliability of highway pile–slab structures using the probability density evolution method. A nonlinear stochastic dynamic model was established through the platform, integrating, for the first time, the randomness of concrete material properties and seismic motion variability. The main findings include the following: Under deterministic seismic input, the displacement angle fluctuation range caused by structural parameter randomness is ±3%, and reliability decreases from 100% to 65.26%. For seismic excitation randomness, compared to structural parameter randomness, reliability at the 3.3% threshold decreases by 7.99%, reaching 92.01%. Dual randomness amplifies the variability of structural response, reducing reliability to 86.38% and 62%, with a maximum difference of 20.5% compared to single-factor scenarios. Compared to the Monte Carlo method, probability density evolution shows significant advantages in computational accuracy and efficiency for large-scale systems, revealing enhanced discreteness and irregularity under combined randomness. This study emphasizes the necessity of addressing dual randomness in seismic design, advancing probabilistic seismic assessment methods for complex engineering systems, thereby aiding the design phase in enhancing facility safety and providing scientific basis for improved design specifications. Full article

This study investigates the seismic performance of the V3.0 220 kV standard-designed substation of the Southern Power Grid, located in a high-intensity seismic zone, with a focus on the application of seismic isolation technology. Seismic isolation and structural analysis were conducted and shaking table tests were performed on both isolated and non-isolated structural models. A total of 40 tests were carried out using three levels of ground motion intensity (i.e., 140 gal, 400 gal, and 800 gal) and in three directions (unidirectional, bidirectional, and triaxial). The dynamic characteristics, seismic response, and isolation effectiveness were evaluated. Results indicate that the test models exhibit strong agreement with theoretical and numerical predictions, with an average frequency deviation of 10.98%. The fundamental period of the isolated structure was extended by a factor of 2.33 compared to the non-isolated configuration. As the peak ground acceleration increased, structural frequency decreased, and the period increased. The isolated structure showed a lower first-period growth rate (4.82%) than the non-isolated structure (15.38%). Even under 800 gal excitations, the isolated structure remained within the elastic range. Seismic isolation significantly reduced structural response, with a control effectiveness exceeding 50%, enabling a one-degree reduction in seismic design intensity. A vulnerability analysis based on 200 simulated earthquake cases revealed that the isolated structure exhibited lower failure probabilities across four performance states. At 600 gal PGA, the failure probability in the LS3 state was reduced by 27.8%. These findings confirm the effectiveness and reliability of seismic isolation design for substations in high seismic intensity regions. Full article

Stochastic vibration control of uncertain structures under random loading is an important problem and its minimax optimal control strategy remains to be developed. In this paper, a stochastic optimal control strategy for uncertain structural systems under random excitations is proposed, based on the minimax stochastic dynamical programming principle and the Bayes optimal estimation method with the combination of stochastic dynamics and Bayes inference. The general description of the stochastic optimal control problem is presented including optimal parameter estimation and optimal state control. For the estimation, the posterior probability density conditional on observation states is expressed using the likelihood function conditional on system parameters according to Bayes’ theorem. The likelihood is replaced by the geometrically averaged likelihood, and the posterior is converted into its logarithmic expression to avoid numerical singularity. The expressions of state statistics are derived based on stochastic dynamics. The statistics are further transformed into those conditional on observation states based on optimal state estimation. Then, the obtained posterior will be more reliable and accurate, and the optimal estimation will greatly reduce uncertain parameter domains. For the control, the minimax strategy is designed by minimizing the performance index for the worst-parameter system, which is obtained by maximizing the performance index based on game theory. The dynamical programming equation for the uncertain system is derived according to the minimax stochastic dynamical programming principle. The worst parameters are determined by the maximization of the equation, and the optimal control is determined by the minimization of the resulting equation. The minimax optimal control by combining the Bayes optimal estimation and minimax stochastic dynamical programming will be more effective and robust. Finally, numerical results for a five-story frame structure under random excitations show the control effectiveness of the proposed strategy. Full article

Bacteriological water quality monitoring is of utmost importance for safeguarding public health against waterborne diseases. Traditional methods such as membrane filtration (MF), multiple tube fermentation (MTF), and enzyme-based assays are effective in detecting fecal contamination indicators, but their time-consuming nature and reliance on specialized equipment and personnel pose significant limitations. This paper introduces a novel, portable, and cost-effective UV-LED/RGB water quality sensor that overcomes these challenges. The system is composed of a multi-well self-loading microfluidic device for sample-preparation-free analysis, RGB sensors for data acquisition, UV-LEDs for excitation, and a portable incubation system. Commercially available defined substrate technology, most probable number (MPN) analysis, and machine learning (ML) are combined for the real-time monitoring of bacteria colony-forming units (CFU) in a water sample. Fluorescence signals from individual wells are captured by the RGB sensors and analyzed using Multilayer Perceptron Neural Network (MLPNN) and Support Vector Machine (SVM) algorithms, which can quickly determine if individual wells will be positive or negative by the end of a 24 h period. The novel combination of ML and MPN analysis was shown to predict in 30 min the bacterial concentration of a water sample with a minimum prediction accuracy of 84%. Full article

The complex and variable operating conditions of sucker-rod pumping wells pose a significant challenge for the timely and accurate identification of oil well operating conditions. Effective deep learning based on measured multi-source data obtained from the sucker-rod pumping well production site offers a promising solution to the challenge. However, existing deep learning-based operating condition recognition methods are constrained by several factors: the limitations of traditional operating condition recognition methods based on single-source and multi-source data, the need for large amounts of labeled data for training, and the high robustness requirement for recognizing complex and variable data. Therefore, we propose a semi-supervised class-incremental sucker-rod pumping well operating condition recognition method based on measured multi-source data distillation. Firstly, we select measured ground dynamometer cards and measured electrical power cards as information sources, and construct the graph neural network teacher models for data sources, and dynamically fuse the prediction probability of each teacher model through the Squeeze-and-Excitation attention mechanism. Then, we introduce a multi-source data distillation loss. It uses Kullback-Leibler (KL) divergence to measure the difference between the output logic of the teacher and student models. This helps reduce the forgetting of old operating condition category knowledge during class-incremental learning. Finally, we employ a multi-source semi-supervised graph classification method based on enhanced label propagation, which improves the label propagation method through a logistic regression classifier. This method can deeply explore the potential relationship between labeled and unlabeled samples, so as to further enhance the classification performance. Extensive experimental results show that the proposed method achieves superior recognition performance and enhanced engineering practicality in real-world class-incremental oil extraction production scenarios with complex and variable operating conditions. Full article

Prediction of the intensity of earthquake-induced motions at the ground surface attracts extensive attention from the geoscience community due to the significant threat it poses to humans and the built environment. Several factors are involved, including earthquake magnitude, epicentral distance, and local soil conditions. The local site effects, such as resonance amplification, topographic focusing, and basin-edge interactions, can significantly influence the amplitude–frequency content and duration of the incoming seismic waves. They are commonly predicted using site effect proxies or applying more sophisticated analytical and numerical models with advanced constitutive stress–strain relationships. The seismic excitation in numerical simulations consists of a set of input ground motions compatible with the seismo-tectonic settings at the studied location and the probability of exceedance of a specific level of ground shaking over a given period. These motions are applied at the base of the considered soil profiles, and their vertical propagation is simulated using linear and nonlinear approaches in time or frequency domains. This paper provides a comprehensive literature review of the major input parameters for site response analyses, evaluates the efficiency of site response proxies, and discusses the significance of accurate modeling approaches for predicting bedrock motion amplification. The important dynamic soil parameters include shear-wave velocity, shear modulus reduction, and damping ratio curves, along with the selection and scaling of earthquake ground motions, the evaluation of site effects through site response proxies, and experimental and numerical analysis, all of which are described in this article. Full article

Background/Objectives: Ventricular pre-excitation (VP) increases the risk of sudden cardiac death among children. While transcatheter ablation could potentially be therapeutic, it is not without risk, especially in smaller children. Accessory pathways (APs) may spontaneously lose anterograde conduction properties over time, making invasive treatment unnecessary. We aim to investigate the probability of spontaneous loss of VP during childhood, as well as the potential factors that may be associated with VP resolution. Methods: We conducted a retrospective study of patients with VP diagnosed before 12 years of age and referred to two Northern Italian tertiary care hospitals between 1993 and 2021. Patients with complex congenital heart disease were excluded. Our primary objective was to determine the likelihood of spontaneous resolution of VP. Results: Overall, 153 patients were included, with a median age at first diagnosis of 4.9 years (25th–75th percentile: 75 days–8.4 years) and a median follow-up of 4.9 years (25th–75th percentile: 1.8–8 years). Through left truncated Kaplan–Meier analysis, we estimated that anterograde conduction would persist in 53% and 33.8% of patients at the age of 1 and 16 years, respectively. Our findings revealed that the absence of symptoms and intermittent VP were associated with a higher likelihood of VP resolution. It is noteworthy that no major arrhythmic events were reported. Conclusions: Our study strongly supports the implementation of a conservative strategy in younger children with VP. Our findings indicate that a significant proportion of pediatric patients may experience spontaneous resolution of VP in the early years of their lives, making any invasive treatment unnecessary. Full article

With the increasing global emphasis on sustainable energy, wave energy has gained recognition as a significant renewable marine resource, drawing substantial research attention. However, the efficient conversion of low-frequency, random, and low-energy wave motion into electrical power remains a considerable challenge. In this study, an advanced hybrid generator design is introduced which enhances wave energy harvesting by optimizing wave–body coupling characteristics and incorporating both a triboelectric nanogenerator (TENG) and an electromagnetic generator (EMG) within the shell. The optimized asymmetric trapezoidal shell (ATS) improves output frequency and energy harvesting efficiency in marine environments. Experimental findings under simulated water wave excitation indicate that the accelerations in the x, y, and z directions for the ATS are 1.9 m·s⁻², 0.5 m·s⁻², and 1.4 m·s⁻², respectively, representing 1.2, 5.5, and 2.3 times those observed in the cubic shell. Under real ocean conditions, a single TENG unit embedded in the ATS achieves a maximum transferred charge of 1.54 μC, a short-circuit current of 103 μA, and an open-circuit voltage of 363 V, surpassing the cubic shell by factors of 1.21, 1.24, and 2.13, respectively. These performance metrics closely align with those obtained under six-degree-of-freedom platform oscillation (0.4 Hz, swing angle range of ±6°), exceeding the results observed in laboratory-simulated waves. Notably, the most probable output frequency of the ATS along the x-axis reaches 0.94 Hz in ocean trials, which is 1.94 times the significant wave frequency of ambient sea waves. The integrated hybrid generator efficiently captures low-quality wave energy to power water quality sensors in marine environments. This study highlights the potential of combining synergistic geometric shell design and generator integration to achieve high-performance wave energy harvesting through improved wave–body coupling. Full article

Using chaos theory, maximum entropies are calculated for 108 time series, each consisting of 28,463 hourly data of urban meteorology and pollutants. The series were measured with standardized and certified instruments (EPA) in six locations at different heights and in three periods (2010/2013, 2017/2020, and 2019/2022) in a basin geomorphology. Each urban meteorology series corresponds to relative humidity (RH), temperature (T), and wind speed magnitude (WS), and each pollutant series corresponds to 10 µm particulate matter (PM₁₀), 2.5 µm particulate matter (PM_2.5), and carbon monoxide (CO). These pollutants are in the top three places of presence in the studied geomorphology and in incidence in population diseases. From the calculated entropies, a quotient is constructed between the entropies of each of the first two urban meteorology variables (RH and T) and the sum of maximum entropies of the time series of anthropogenic pollutants, demonstrating the gradual decay in time of the quotient that is dominated by the maximum entropies of the pollutants. The latter leads to a more excited and warm boundary layer, due to thermal transfers, which makes it more unpredictable, increasing its capacity to contain water. It is verified that the diffusion is anomalous with alpha < 1 and that the contamination has a high probability, using a heavy-tailed probability function, of causing extreme events by influencing urban meteorology. Full article