Search Results (24,525)

Soft soil sites can amplify the peak acceleration by a factor of 1.5 to 3.5 and exhibit the filtering effect on seismic waves. This effect results in the attenuation of high frequencies, amplification of low frequencies, and extension of the predominant period of ground motion. Consequently, soft soil sites have a more pronounced impact on isolation buildings constructed on them. The seismic isolation structure design typically involves assuming rigid foundation for calculations. However, the soil properties can significantly impact the dynamic response of the structure, affecting factors such as input ground motion, changes in vibration characteristics, radiation energy dissipation, and material damping energy dissipation. Therefore, neglecting these influences and relying solely on the rigid foundation assumption for calculations can lead to significant errors in the final seismic response analysis of the structure. Currently, there are numerous LNG storage tanks, museums, and other isolation buildings constructed on soft soil sites. Therefore, research on seismic isolation measures for soft soil sites holds significant practical importance. In light of this, this paper, firstly, provides a systematic summary of seismic isolation strategies and engineering applications for soft soil sites. Secondly, it further discusses advancements in research on the dynamic interactions of soil–isolated structures, covering analytical methods, numerical investigations, and experimental studies on soft soil sites. Lastly, the paper concludes with insights on current research progress and prospects for further studies. Full article

In this paper, a dual-wavelength narrow-linewidth fiber laser based on parity-time (PT) symmetry theory is proposed and experimentally demonstrated. The PT-symmetric filter system consists of two optical couplers (OCs), four polarization controllers (PCs), a polarization beam splitter (PBS), and cascaded fiber Bragg gratings (FBGs), enabling stable switchable dual-wavelength output and single longitudinal-mode (SLM) operation. The realization of single-frequency oscillation requires precise tuning of the PCs to match gain, loss, and coupling coefficients to ensure that the PT-broken phase occurs. During single-wavelength operation at 1548.71 nm (λ₁) over a 60-min period, power and wavelength fluctuations were observed to be 0.94 dB and 0.01 nm, respectively, while for the other wavelength at 1550.91 nm (λ₂), fluctuations were measured at 0.76 dB and 0.01 nm. The linewidths of each wavelength were 1.01 kHz and 0.89 kHz, with a relative intensity noise (RIN) lower than −117 dB/Hz. Under dual-wavelength operation, the maximum wavelength fluctuations for λ₁ and λ₂ were 0.03 nm and 0.01 nm, respectively, with maximum power fluctuations of 3.23 dB and 2.38 dB. The SLM laser source is suitable for applications in long-distance fiber-optic sensing and coherent LiDAR detection. Full article

To address the issue of reduced positioning accuracy caused by satellite signal interruptions when trains pass through long tunnels, a novel train positioning method based on an innovative adaptive unscented Kalman filter (UKF) under kinematic constraints is proposed. This method aims to improve the accuracy of the location of trains during operation. By considering the dynamic characteristics of the train, a dynamic kinematic-constrained inertial navigation system (INS)/odometer (ODO) combination positioning system is established. This system utilizes kinematic constraints to correct the accumulated errors of the INS. Additionally, the algorithm incorporates real-time estimation of the measurement noise covariance using innovation sequences. The updated adaptive estimation algorithm is applied within the UKF framework for nonlinear filtering, forming the innovative adaptive UKF algorithm. At each time step, the difference between the ODO sensor data and the INS output is used as the measurement input for the innovative adaptive UKF algorithm, enabling global estimation. This process ultimately yields the actual positioning result for the train. Simulation results demonstrate that the innovative adaptive UKF train positioning method, incorporating kinematic constraints, effectively mitigates the impact of satellite signal interruptions. Compared with the traditional INS/ODO positioning method, the innovative adaptive UKF method reduces position errors by 34.35% and speed errors by 36.33%. Overall, this method enhances navigation accuracy, minimizes train positioning errors, and meets the requirements of modern train positioning systems. Full article

In order to ensure the safety of navigation in a bridge area, and based on the theory of the safety potential field, a method of ship safety assessment and early warning in an inland river bridge area is proposed. Firstly, the risk elements associated with ship collisions in a bridge area are classified. Secondly, these risks are quantified using the potential energy field, the boundary potential field and the behavioural field, and then the ship state under the influence of wind flow, predicted by the Kalman filter, is quantified using the kinetic energy field. Then, the above four potential energy fields are merged to obtain a superposition field, and the magnitude of the instantaneous risk in the bridge area is obtained based on its magnitude. Finally, the change of field strength values under different moments is used for early warning. The results of the simulation of a ship passing through the piers of the Baijusi Bridge show that the model can effectively quantify the risk of a ship–bridge collision in the inland bridge area and provide real-time warning of the risk of a ship–bridge collision in the bridge area, which is of great significance for improving the safety of the inland bridge area. Full article

Kidney diseases are a group of conditions related to the functioning of kidneys, which are in turn unable to properly filter waste and excessive fluids from the blood, resulting in the presence of dangerous levels of electrolytes, fluids, and waste substances in the human body, possibly leading to significant health effects. At the same time, the toxins amassing in the organism can lead to significant changes in breath composition, resulting in halitosis with peculiar features like the popular ammonia breath. Starting from this evidence, scientists have started to work on systems that can detect the presence of kidney diseases using a minimally invasive approach, minimizing the burden to the individuals, albeit providing clinicians with useful information about the disease’s presence or its main related features. The electronic nose (e-nose) is one of such tools, and its applications in this specific domain represent the core of the present review, performed on articles published in the last 20 years on humans to stay updated with the latest technological advancements, and conducted under the PRISMA guidelines. This review focuses not only on the chemical and physical principles of detection of such compounds (mainly ammonia), but also on the most popular data processing approaches adopted by the research community (mainly those relying on Machine Learning), to draw exhaustive conclusions about the state of the art and to figure out possible cues for future developments in the field. Full article

Understanding the density of possible prices in one-minute intervals provides traders, investors, and financial institutions with the data necessary for making informed decisions, managing risk, optimizing trading strategies, and enhancing the overall efficiency of the cryptocurrency market. While high accuracy is critical for researchers and investors, market nonlinearity and hidden dependencies pose challenges. In this study, the filtered historical simulation is used to generate pathways for the next hour on the one-minute step for Bitcoin and Ethereum quotes. The innovations in the simulation are standardized historical returns resampled with the method of block bootstrapping, which helps to capture any hidden dependencies in the residuals of a conditional parameterization in the mean and variance. Ordinary bootstrapping requires the feed innovations to be free of any dependencies. To deal with complex data structures and dependencies found in ultra-high-frequency data, this study employs block bootstrap to resample contiguous segments, thereby preserving the sequential dependencies and sectoral clustering within the market. These techniques enhance decision-making and risk measures in investment strategies despite the complexities inherent in financial data. This offers a new dimension in measuring the market risk of cryptocurrency prices and can help market participants price these assets, as well as improve the timing of their entry and exit trades. Full article

In this paper, one-to-one correspondences and equivalences between ideals, primals, filters and grills are introduced. It is shown that the local functions and the topological spaces induced by them are the same. From this point of view, the topological properties of one topology can be derived from the topological properties that are valid in the corresponding topology. Full article

Background/Objectives: Coated drug pellets enjoy widespread use in hard gelatine capsules. In heterogeneous pellets, the drug substance is layered onto core pellets. Coatings are often applied to generate a retarded release or an enteric coating. Methods: In the present study, the thickness of a polymer coating layer on drug pellets was correlated to the drug release kinetics. Results: The question should be answered whether it is possible to stop the coating process when a layer thickness referring to an intended drug release is achieved. Inert pellets were first coated with sodium benzoate and second with different amounts of water insoluble polyacrylate in a fluidized bed apparatus equipped with a Wurster inlet. The whole process was controlled in-line and at-line with process analytical technology by the measurement of the particle size and the layer thickness. The in-vitro sodium benzoate release was investigated, and the data were linearized by different standard models and compared with the polyacrylate layer thickness. With increasing polyacrylate layer thickness the release rate diminishes. The superposition of several processes influencing the release results in release profiles corresponding approximately to first order kinetics. The coating layer thickness corresponds to a determined drug release profile. Conclusions: The manufacturing of coated drug pellets with intended drug release is possible by coating process control and layer thickness measurement. Preliminary investigations are necessary for different formulations. Full article

The technology of military equipment entity extraction, a crucial component in constructing military knowledge bases, holds significant research value and theoretical importance for guiding the development and improvement of equipment support forces. In the military domain, equipment entities exhibit a phenomenon of nesting, where one entity is contained within another, and abbreviations or codes are frequently used to represent these entities. To address this complexity, this paper proposes a method named CoTNER for extracting entities. Initially, a large-scale language model is used to perform data augmentation with chain-of-thought on the original dataset, providing additional semantic and contextual information. Subsequently, the augmented dataset is fine-tuned on a small-scale language model to adapt it to the task of military equipment entity extraction and to enhance its ability to learn complex rules specific to the domain of military equipment. Additionally, a high-quality data filtering strategy based on instruction-following difficulty scoring is proposed to address the catastrophic forgetting issue that may occur during the fine-tuning of large language models. The experimental results demonstrate that the proposed military equipment entity extraction method outperforms mainstream traditional deep learning methods, validating the effectiveness of CoTNER. Full article

Coal mining is known to have negative impacts on the environment, necessitating land rehabilitation after mining activities. Amongst the problems associated with coal mining is the accumulation of acid mine drainage characterized by large amounts of heavy metals and high acidity. The impact of these environmental problems on the ecosystem around mining areas underscores a need to devise strategies that will ensure sustainable restoration of the ecosystem integrity to ensure environmental protection. Of these, treatment of acid mine drainage using calcium sulfate dihydrate, which is subsequently used for irrigation during phytoremediation, holds great promise for restoration of open-cast mines. However, although grasses are used for rehabilitation of coal mined areas, the impacts of treated mine water on the germination, seedling emergence, and plant growth of grasses are not well known. The aim of the study was to evaluate the germination and early seedling growth responses of different forage grasses to treated mine water. Seven forage grass species were selected, with four species represented by two varieties while others were represented by one variety, totaling 11 forage grasses. For each plant entry, 100 seeds were placed in J.R. Petri’s dishes lined with Whatman No. 2 filter paper and watered with distilled and mine water to assess germination. For the seedling establishment experiment, only five species were studied, in which twenty seeds per species were sown in pots containing mine soil and irrigated using distilled and treated mine water. The final germination percentage (FGP), germination rate index (GRI), corrected germination rate index (CGRI), and T₅₀ were determined for the germination trail and total biomass was assessed for the seedling growth trail. The highest FGP for all grasses was attained under controlled conditions, using distilled water, ranging from 38–94%. All grasses germinated when watered using treated mine water and had a FGP ranging from 20–91%. Relative to distilled water, GRI and CGRI were highest only for L. multiflorum cv AgriBoost when seeds were watered using the treated mine water. All grasses watered with treated mine water produced high biomass for the first two weeks, after which biomass production started to decline. Two grasses, Eragrostis curvula cv Ermelo and Lolium multiflorum cv Archie, showed tolerance to treated mine water irrespective of its high electrical conductivity (557 mS∙m⁻¹). Therefore, these grasses could be used in the rehabilitation of coal-mined areas irrigated with treated mine water. Full article

Nitrogen (N) deposition rates have notably increased around the world, especially in high-altitude regions like the Qinghai–Tibetan Plateau (QTP). We conducted a six-year comprehensive experiment to simulate nitrogen deposition in an alpine grassland area near Qinghai Lake. Four levels of nitrogen depositions, i.e., 0 (CK), 8 kg N ha⁻¹year⁻¹ (N1), 40 kg N ha⁻¹year⁻¹ (N2), and 72 kg N ha⁻¹year⁻¹ (N3), with three replicates for each N treatment, were tested annually in early May and early July, with the meticulous collection of plant and soil samples during the peak growth period from 15 July to 15 August. We used the null model to evaluate the impact of environmental filtration and interspecific competition on the dynamics of the plant community was assessed based on the level of discrete species affinities within the plant community by constructing a phylogenetic tree. The results showed that the environmental filter was the predominant driver for the change of community’s genealogical fabric. The N2 and N3 treatments increased the influence of soil factors on the change of plant community structure. Climatic factors played a crucial role on the change of plant community in the CK grassland area, while soil factors were dominant in the N1- and N3-treated grasslands. Full article

Outdoor ozone (O₃) is elevated on hot, sunny days when residential air conditioning is used most. We evaluated the impact of direct evaporative coolers (ECs) and vapor-compression air conditioners (ACs) on indoor O₃ concentrations in homes (N = 31) in Utah County, Utah, United States of America. Indoor and outdoor O₃ concentrations were measured for 24 h at each home using nitrite-impregnated glass-fiber filters. AC homes (n = 16) provided a protective envelope from outdoor O₃ pollution. Only one AC home had O₃ levels above the limit of detection (LOD). Conversely, EC homes (n = 15) provided minimal protection from outdoor O₃. Only one EC home had O₃ levels below the LOD. The average indoor O₃ concentration in EC homes was 23 ppb (95% CI 20, 25). The indoor-to-outdoor (I/O) ratio for O₃ in EC homes was 0.65 (95% CI 0.58, 0.72), while the upper bound for the I/O ratio for AC homes was 0.13 (p < 0.001). Indoor exposure to O₃ for residents in EC homes is approximately five times greater than for residents of AC homes. Although ECs offer energy and cost-saving advantages, public health awareness campaigns in O₃-prone areas are needed, as well as research into O₃ pollution controls for direct ECs such as activated carbon filtration. Full article

In the scenario of power system monitoring, detecting the operating status of circuit breakers is often inaccurate due to variable object scales and background interference. This paper introduces DLCH-YOLO, an object detection algorithm aimed at identifying the operating status of circuit breakers. Firstly, we propose a novel C2f_DLKA module based on Deformable Large Kernel Attention. This module adapts to objects of varying scales within a large receptive field, thereby more effectively extracting multi-scale features. Secondly, we propose a Semantic Screening Feature Pyramid Network designed to fuse multi-scale features. By filtering low-level semantic information, it effectively suppresses background interference to enhance localization accuracy. Finally, the feature extraction network incorporates Generalized-Sparse Convolution, which combines depth-wise separable convolution and channel mixing operations, reducing computational load. The DLCH-YOLO algorithm achieved a 91.8% mAP on our self-built power equipment dataset, representing a 4.7% improvement over the baseline network Yolov8. With its superior detection accuracy and real-time performance, DLCH-YOLO outperforms mainstream detection algorithms. This algorithm provides an efficient and viable solution for circuit breaker status detection. Full article

Linear relationships, expressing the electrochemical properties of molecules as functions of structure, give insight into the associated electrochemical process and are a tool for prediction. Many biological activities rely on water-based dissociation, making electrochemical properties a bridge between structure and activity. Motivated by a previous study, a replica is made here on a different dataset in order to validate/invalidate the previously reported results. There are several methods for obtaining structure-based descriptors. Some of the methods have been devised to account for molecular topology, some to account for molecular geometry, and others to account for both. Two methods are involved here to derive structure-based descriptors and further obtain structure–property relationships (FMPI and ChPE). In order to express structure descriptors, both FMPI and ChPE express first the topology of the molecule, using the heavy atoms identity matrix and the heavy atoms adjacency matrix, both square symmetric matrices in the belief that symmetry is one major factor of molecular stability. A set of 2,6-dimethyl-1,4-dihydropyridine derivatives with oxidation peak potentials and coulometrically determined number of electrons experimental data is subjected to the search for structure–activity relationships. Even if the 2,6-dimethyl-1,4-dihydropyridine is a symmetric compound (of C_s point group), their derivatives are generally not symmetric (9 out of 24 are asymmetric). The dataset is subjected to descriptive and inferential statistics in order to filter out the most relevant structure–activity relationship. The geometry is built using three levels of theory (one from molecular mechanics and two others from density functionals, of which one accounts for the interaction with water as solvent). One challenge of picking one out of two reported measured values is dealt with by calculating the likelihood associated with the two choices. Relevant structure–activity models are extracted and discussed. The use of in vivo (in water, SM8 model) models in geometry optimization (from MMFF94 and B3LYP and to M06 + Water SM8) results in a precision gain, but this is, in most of the cases, not statistically significant, and this can be considered a negative result. Full article

To improve the machining accuracy of free-form surface parts, a coarse-to-fine free-form surface machining error decomposition and compensation method is proposed in this paper. First, the machining error was coarsely decomposed using variational mode decomposition (VMD), and the correlation coefficients between the intrinsic mode function (IMF) and the machining error were obtained to filter out the IMF components that were larger than the thresholding value of the correlation coefficients, which was the coarse systematic error. Second, the coarse systematic errors were finely decomposed using empirical mode decomposition (EMD), which still filters out the IMF components that are larger than the thresholding value of the set correlation coefficient based on the correlation coefficient. Then, the wavelet thresholding method was utilized to finely decompose all the IMF components whose correlation coefficients in the first two decomposition processes were smaller than the threshold value of the correlation coefficient set. The decomposed residual systematic errors were reconstructed with the IMF components screened in the EMD fine decomposition, which gave the fine systematic error. Finally, the machining surface was reconstructed according to the fine systematic error, and its corresponding toolpath was generated to compensate for the machining error without moving the part. The simulation and analysis results of the design show that the method has a more ideal processing error decomposition ability and can decompose the systematic error contained in the processing error in a more complete way. The results of actual machining experiments show that, after using the method proposed in this paper to compensate for the machining error, the maximum absolute machining error decreased from 0.0580 mm to 0.0159 mm, which was a 72.5% reduction, and the average absolute machining error decreased from 0.0472 mm to 0.0059 mm, which was an 87.5% reduction. It was shown that the method was effective and feasible for free-form surface part machining error compensation. Full article