esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Results and Discussion
### Spectral Fatigue Analysis

Table 9: Factors related to fatigue life for weld improvement techniques. In the linear analysis stage, which includes (i) operation and storm conditions, (ii) dynamic storm response, and (iii) seismic resistance level, unity checks on elements, tubular joints, and piles demonstrate compliance with regulatory requirements in cases (i) and (ii). However, under seismic loading, overstressing is observed in a beam, necessitating potential solutions such as increasing the web or flange thickness, adding a second or third web plate, or enhancing the yield strength. For the tubular sections, proposed reinforcement measures include increasing thickness, adding stiffeners, or injecting cement. Furthermore, hydrostatic collapse is observed across all three linear analyses. This phenomenon is attributed to the depth at which the element is submerged. To mitigate hydrostatic collapse, the commonly employed solutions in Mexico include the following:  
* For structures in the design phase: Increasing thickness, diameter, or yield strength, as well as reinforcing with internal plates or external ring-shaped stiffeners. * For already constructed but uninstalled structures: Reinforcement using external ring plates. * For installed offshore structures: The most frequently utilized method involves cement injection within the tubular section. These solutions are indicative rather than exhaustive, and a comprehensive analysis should be conducted to evaluate their cost-effectiveness and installation feasibility. In the nonlinear analysis, a high safety factor is observed for seismic loading compared to ultimate wave resistance. This finding confirms that wave loading governs the design of offshore platforms in Campeche Bay, indicating that seismic activity is not the most critical condition for the structural design of these platforms. In the predictive fatigue analysis, initial evaluations using the first S-N curve (without considering weld control in the most unfavorable scenario) indicate that all joints meet the minimum service life requirement, except for joint 370. Two additional analyses were conducted by modifying the S-N curves, following API [35] guidelines. The results confirm that joint 370 meets the minimum design life when a profiling control method known as \"burr grinding\" is applied. Based on these findings, the results can be deemed satisfactory, underscoring the necessity of performing six fundamental analyses to assess the structural behavior of offshore platforms throughout their operational lifespan and ensure their structural integrity. Finally, this study highlights the importance of installing offshore platforms in new exploration fields to enhance resource exploitation.
# Opportunities and Challenges for Error Control Schemes for Wireless Sensor Networks: A Review
## 3 Standard, Network and Channel Models  
In this section, we introduce the IEEE standard for WSN that is followed by network and channel models used for WSN in the literature.
# Data Knowledge Dual-Driven Rate of Penetration Prediction Method for Horizontal Wells
###### Abstract  
The prediction and optimization of the rate of penetration (ROP) for horizontal wells are more complicated than for vertical wells, but most of the current ROP prediction studies are for vertical wells, which cannot be adapted to the complex drilling characteristics of horizontal wells. To this end, this paper proposes a data knowledge dual-driven horizontal well ROP prediction method. Firstly, the drilling characteristics of horizontal wells are analyzed, showing that the horizontal wells ROP prediction model cannot be modeled using surface measurement data; secondly, based on the analysis of horizontal well drilling characteristics, a physical model-based horizontal well ROP modeling data pre-processing method is proposed by introducing the drag and torque model. Finally, a data knowledge dual-driven horizontal well ROP prediction method is proposed in conjunction with data-driven algorithms. The proposed horizontal well ROP prediction method is applied to the A1\(\sim\)A4 wells in the Sichuan area. Compared with the conventional data-driven ROP prediction method, the prediction accuracy of this method is improved by 30%. The proposed method can provide a basis for the intelligent optimization and management of ROP during the drilling of horizontal wells.  
horizontal well; rate of penetration; prediction; data driven +
Footnote †: journal: Applied sciences
# A Split Ring Resonator-Based Metamaterial for Microwave Impedance Matching with Biological Tissue
## 1 Introduction
Generally, the SRR metamaterials are optimized for sensing/imaging applications at different operating frequencies. The design is focused (i) to improve the impedance matching of the antenna loaded with human tissue, thus avoiding the impedance mismatch and the formation of stationary waves which are deleterious for an efficient operation of the microwave applicator; (ii) to obtain a better focusing of the electromagnetic power into human tissue. This feasibility investigation constitutes a preliminary proof of concept for the development of a compact and low-cost microwave applicator for dermatology. The heating investigation is neglected in this paper, while the matching properties of metamaterial are experimentally demonstrated by employing a pre-prototype applicator which consists of a suitable SIW cavity-backed patch antenna with the optimized metamaterial lens based on SRR array. The antenna cavity has been designed by considering SIW technology. Higher gain, efficiency and directivity have been obtained by putting a SRR metamaterial over a patch antenna applicator. The impact of this research lies in the novelty of the proposed device and in its practical potential due to the possibility to refine a set of different SRR geometries. These can be optimized by considering the kind of organ, age and gender of the patients, for the same source and applicator. The obtained results pave the way towards the construction of an external microwave applicator for skin cancer thermal treatment.
## 2 Materials and Methods
### Hyperparameter Tuning and Model Evaluation
#### 2.3.2 Implementation Details and Constraints  
To achieve the best-fitting hyperparameters for subsequent performance evaluations, two distinct tuning sessions were performed--one using 10-fold cross-validation (10\(\times\)-CV) and another using 5 \(\times\) 2 cross-validation (5 \(\times\) 2-CV)--so that each model ultimately has two sets of optimized hyperparameters. Throughout tuning, regularization played an important role wherever applicable (e.g., L1- and L2-penalties or their combinations). Regularization helps prevent overfitting by penalizing overly complex models, thereby improving generalization [13]. For instance, Logistic Regression, XGBoost, LightGBM, and CatBoost (among others) support L1 (lasso-type) and/or L2 (ridge-type) penalties; including these settings in the search space improved model resilience against noisy features.  
In designing the Bayesian optimization boundaries, certain parameter interactions were carefully constrained to reflect known model requirements. For instance, in Random Forest, the choice of'max_features' influences how many features are randomly selected at each split. Similarly, in CatBoost, enabling certain grow policies or adjusting the 'leaf_estimation_iterations' must remain consistent with the chosen learning rate. By defining conditional search spaces, Hyperopt effectively navigated these complexities, yielding model-specific hyperparameter sets that delivered both high predictive performance and improved computational efficiency.  
All hyperparameter tuning trials were conducted on identical hardware configurations and software versions, with uniform random seeds ensuring repeatability in all comparisons. Detailed hyperparameter ranges for each model (e.g., solver types, penalty mechanisms, search bounds for regularization coefficients) can be found in Table 2. This uniformity of the process across all models guarantees that the observed differences in performance can be attributed to model characteristics and not to inconsistent experimental conditions.  
In the Table 2 _'Hyperparameter Ranges'_ column, the notation specifies the nature of the search space for each parameter. Values enclosed in brackets ([]) indicate that the search space consists of the explicitly listed discrete values. When the notation includes log(range), the parameter values are sampled logarithmically across the specified range. If the range is defined as n1-n2, the search space includes all continuous values between n1 and n2, inclusive. For ranges denoted as n1-n2'K, the search space is limited to discrete steps of size K within the specified range from n1 to n2.
## 4 Discussion
### Limitations  
Our study has several notable limitations that warrant consideration. The primary limitation is the use of patient profiles from the MIMIC-III repository, which reflects specific patient demographics and healthcare contexts. Given that the data are predominantly from large urban areas, the generalizability of our findings to ICU patients in smaller healthcare facilities remains uncertain. To enhance the robustness of our conclusions, future studies should strive to include data from a variety of settings, including rural or small healthcare facilities. Additionally, the lack of high-quality care records for a significant proportion of patients poses a potential limitation, particularly when extrapolating the performance of this model to other critical care settings. While physician-recorded information during patient consultations is valuable for research on diseases and treatments, it also presents inherent challenges, such as common spelling errors and inaccuracies. Another significant limitation is the absence of external validation of our predictive model, which affects the overall reliability and trustworthiness of the proposed model. Future research efforts should prioritize the inclusion of robust external validation procedures to solidify the model's credibility. Furthermore, our study specifically focused on predicting mortality and readmission rates in patients with type 2 diabetes in intensive care units. Future research should broaden this scope to encompass various diseases or conditions, enabling a more comprehensive exploration of predictive models for different patient groups. Incorporating written summaries from physicians could enhance the reliability of predictions. Investigating different patient groups may reveal distinct patterns and factors that influence outcomes, providing a richer understanding of the complexities involved. This expanded scope could lead to the development of customized predictive models that adapt to the unique characteristics of specific medical conditions, thereby increasing the applicability and effectiveness of such models in clinical practice.
# Performance Analysis and Testing of Spiral Quantitative Fertiliser Distributors in Orchards
## 3 Results and Analysis
### Verification Test  
The verification test was performed in a soil-box laboratory at Tarim University on 20 November 2022 as shown in Figure 7. The temperature and relative humidity on the test day were 3 \({}^{\circ}\)C and 24%, respectively. The applied fertilizer was the same batch as the previous tests. A verification test of the optimized spiral quantitative fertilizer distributor for orchards in South Xinjiang was conducted according to the regulated test method described in an earlier study [28]. The fertilizer distributor was fixed behind the traction table through a three-point suspension, and the operation steps were consistent with the previous test. The traction table was started, and three repeated tests were performed when the advancing speed, the opening degree of the fertilizer outlet and the rotation speed of the conveyor were 2.7 km/h, 42% and 66 RPM, respectively. The \(CV\) of uniformity was used to select the mean result.  
Figure 6: The impact of various interaction factors on response values. (**a**) spiral rotation speed and opening degree of fertilizer outlet; (**b**) opening degree of fertilizer outlet and advancing speed.  
Figure 7: Validation test chart.  
The \(CV\) of uniformity of the optimized spiral quantitative fertilizer distributor for orchards was 6.521%. Moreover, it was 7.9% in the prototype test, showing minimal error. The \(CV\) of uniformity conformed to the regulations in NYT1003-2006, Technical Specification for Mechanical Quality Evaluation [29]; the \(CV\) of uniformity \(\leq\) 40% for the fertilizer distributors. This result conforms to the fertilizing requirements of orchards with a wide row space and narrow plant space in South Xinjiang.
## 2 Materials and Methods  
### Description of the XMed-Dry Network and the Multiplatform Observations  
#### 2.1.1 Dry Deposition Measurements  
Aerosol dry deposition was collected at three locations for this study: on the flat roof of the Engineering department building (Ecotekne campus) at Lecce (18.6\({}^{\circ}\) E, 40.2\({}^{\circ}\) N, 40 m above sea level/15 m above street level), on top of a measurement container in a pine forest at Athens (23.5\({}^{\circ}\) E, 37.6\({}^{\circ}\) N, 290 m above sea level/10 m above ground level), and on flat roof of a building at the edge of a housing area at San Lawrenz, Gozo (14.1\({}^{\circ}\) E, 36.0\({}^{\circ}\) N, 130 m above sea level/10 m above street level). A novel dry deposition collector with an active rain protection was used. The geometry of its sampling head follows the 'flat-plate' design as described by [PERSON] et al. [31]. The function of the spacers in the given design was replaced by an external mounting frame, thus reducing the disturbance of the flow field between the plates. For additional rain protection, the outer part of the top plate is moved down around the lower plate in case of a positive signal from the rain detector sensor. The sampling substrate is positioned approximately 2 m above the roof. Samples were exposed to the atmosphere for 48 to 72 h, approximately. Particles were collected on a pure carbon adhesive (SpectroTabs, Plano GmbH, Wetzlar, Germany) mounted to a standard electron microscopy aluminum stub and stored in dry boxes at room temperature.  
Particles were analyzed by automated scanning electron microscopy (FEI Quanta 400F ESEM, FEI, Eindhoven, The Netherlands) with attached X-ray fluorescence analysis (Oxford X-Max 120, Oxford Instruments, Abingdon, UK) under vacuum condition. Image acquisition was done at 100-150 nm/pixel resolution, and particle size was estimated from their projected cross-sectional area. Particle mass and aerodynamic diameter were estimated from their size assuming preferential flat orientation and a density based on the approximate composition from chemistry (for details refer to [PERSON] et al. [31]). X-Ray fluorescence analysis time was chosen to allow for a minimum of 40,000 X-ray counts per particle. Quantification was carried out by the corresponding control software (Oxford Aztec 4.0). Prior to automated analysis, samples were visually inspected to avoid analysis of damaged samples surface areas. A total of 1500 to 5000 particles per sample were analyzed. More details of the data acquisition, quantification and processing have been previously reported [27].  
Particles were classified according to their chemical composition [32]. This detailed classification was then summarized into dust, sea-salt and other particles groups. The dust particle group mainly consists of silicate and carbonate particles, but includes also iron and titanium oxides as well as other minerals, which only contribute negligibly to the total mass. The statistical uncertainty dominating the overall random error was estimated by a bootstrap approach and is reported in terms of the limits of the central 95% confidence interval.
# Wireless Communication Technologies for Smart Grid Distribution Networks +
## 2 Available Wireless Technologies for Smart Grid Communications
It is suitable for home energy management and advanced metering infrastructures. Its disadvantages include coverage, the need for encryption techniques due to the information passing through every access point, and loop problems causing a reduction in bandwidth. A summary of the features, strengths, and challenges of each of the communication technologies is presented in Tables 1 and 2, including whether they incorporate deployment in a wireless mesh technology [5].
# The Effects of Compression on the Detection of Atrial Fibrillation in ECG Signals
## 1 Introduction
Since wavelet coefficients allow for effective compaction of energy in the signal, this property can be exploited by the SPIHT scheme. For example, in [25], SPIHT was used to compress ECG signals and it was shown that good performance in fundamental ECG parameter extraction (such as QRS detection and HRV parameter estimation) was possible at high levels of compression, with sensitivity and specificity remaining above 90% for compression ratios above 50. The system proposed in [30] used SPIHT-based decomposition, augmented with a rate-distortion curve to control the bit rate. The performance criterion was distortion of the signal, rather than performance in a diagnostic application. The main contribution of this paper is to analyze the effects of compression on automated atrial fibrillation detection, where the primary performance criterion is diagnostic performance. In particular, the paper aims to demonstrate that a high level of diagnostic information is retained in the compressed signal even at high levels of signal compression that introduce significant distortion in the signal, and this diagnostic information can be used for automated AF detection with a high degree of accuracy. Signals are first compressed using SPIHT, the signal is then reconstructed, and QRS detection and entropy measures are used to automatically detect AF in the reconstructed signals. Classification results are presented in terms of sensitivity and specificity. Standard measures of signal distortion (percent RMS distortion) are also employed to demonstrate that AF can be detected with high reliability even with very large amounts of signal morphology distortion. The results demonstrate that SPIHT can achieve high accuracy for AF detection, at high compression levels of the ECG signal. The remainder of the paper is structured as follows. Section 2 outlines the database used for evaluation, the compression algorithm employed, the AF detection method, and the performance metrics used for evaluation. Section 3 presents results, while Section 4 contains a discussion of the results, and conclusions.
# Image Quality Improvement and Memory-Saving in a Permanent-Magnet-Array-Based MRI System
## 2 Theory
### Characteristics of a Non-Linear SEM Supplied by a PMA
the radial lines in the \(\theta-\)direction, compared to the k-space\({}_{11}\), they are even more unevenly distributed, which is because the angles of the gradient deviate more from the rotation angles of the magnet array, as shown in the same sub-figure at Row 2, Column 2 in Figure 3. In the case when a non-linear SEM is used for encoding, no global k-space can represent the encoding. Investigation on the Approaches to Improve Image Quality by Increasing the Density of the Signal Space  
In order to improve the image quality, a dense signal space, i.e., a dense global k-space or dense local k-spaces, are desired. For a PMA-based system, this can be obtained by increasing the number of rotation angles (\(N_{\theta}\)) and/or by increasing the number of sampling points (\(N_{l}\)). In this section, these two approaches are investigated and evaluated in terms of their impacts on acquisition time, image quality improvement, image reconstruction time, and memory consumption. In terms of the effect on the signal acquisition time by taking the two approaches, in this study, the number of sampling points is increased when the total readout time is fixed. Therefore, increasing the number of sampling point does not increase the acquisition time. On the other hand, although for each radial line (i.e., each rotation angle), the maximum distance of the signal point to the origin remains the same, more sampling points can locate in the blue dashed box, especially for those cases when the gradient is high. For the second approach by increasing the number of rotation angles, it increases the density of the signal points effectively, however, the acquisition time increases proportionally with the number of the rotation angles.
## 3 Modeling Approaches
### Kernel Logistic Regression  
KLR is a powerful and flexible discriminative method, which possesses the ability to provide the confidence of class prediction [56]. A conventional logistic regression model was constructed in high-dimensional feature space and proposed by a Mercer kernel [57]. Given the labelled training data:  
\[D=\{(x_{i},y_{i})\},i=1,x_{i}\in X\in R^{d},y_{i}\in[0,1], \tag{2}\]  
where \(x_{i}\) is the landslide conditioning factor, and \(K:X\times X\to R\) evaluates the inner product between the images of input vectors in the feature space.  
The kernel function used in this study is the isotropic radial basis function (RBF):  
\[K(x,x^{\prime})=e^{\{\xi\|x-x^{\prime}\|^{2}\}} \tag{3}\]  
Then, a conventional logistic regression model was constructed in the feature space as follows:  
\[\log it\{h(x)\}=\omega\cdot\varphi(x)+c,\,\log it(p)=\log\frac{p}{1-p}, \tag{4}\]  
where (\(\omega\),\(c\)) are the optimal model parameters.
# Research on Satellite Network Traffic Prediction Based on Improved GRU Neural Network
## 5 Results Simulation and Analysis  
### Description of the Data Set  
This simulation experiment uses OPNET and STK simulation software to simulate the information transmission network. From the Iridium constellation, we selected six satellites and two ground stations to simulate the integrated information network of heaven and earth. First, the data packets are routed through the satellite network to find the best path, then transmitted to the relay node, and finally arrive at the ground station. The _INT_ node is the input end of the ground base station communication traffic in the analog network topology, and the node transmits the ground communication traffic
## 3 Results
### Pre-Treatment of SA-MIPs with SA-Derivative Reduce the Binding to Cells  
The SA-derivatives ME0970 or ME1057 were pre-incubated at either 20 \(\upmu\)M or 200 \(\upmu\)M, respectively, with 0.1 mg/mL SA-MIPs and were then added to the T47D cells. The binding of the pre-treated cells was compared with the binding to the same cell line of 0.1 mg/mL of SA-MIPs alone, and was shown to be reduced by 7% (20 \(\upmu\)M) and 66% (200 \(\upmu\)M), respectively, for ME0970, and by 0.5% (20 \(\upmu\)M) and 64% (200 \(\upmu\)M), respectively, for ME1057 (Figure 6). The reduction in binding of the pre-treated cells was concentration-dependent, as shown with both SA-derivatives.  
Figure 5: Fluorescence confocal microscopy SA-MIPs—scale bar 20 \(\upmu\)m. Four different breast cancer cell lines were stained with SA-MIPs using nitrobenzoxadiazole (NBD) in green, rhodamine-phalloidin (actin filaments) in red, and DAPI (nuclei) in blue, and analyzed with fluorescence confocal microscopy.  
Figure 6: SA-MIPs were pre-incubated with different concentrations of the SA-derivatives and analyzed with flow cytometry. The reduction of binding compared to SA-MIP binding alone is shown. (**A**) The SA-derivative ME1057 was added at 20 \(\upmu\)M and 200 \(\upmu\)M. (**B**) ME0970 was added at 20 \(\upmu\)M and 200 \(\upmu\)M.