esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Conclusions  
In conclusion, we have analyzed, by micromagnetic simulations based on the GPU-accelerated software MuMax3, the effect of DMI on the characteristics of the spin waves spectrum of magnetic nanoelements magnetized in-plane, 1.5 nm thick: isolated stripes of width 100 nm and elliptical dots with lateral dimensions of 100 \(\times\) 50, 200 \(\times\) 100 and \(300\times 150\) nm\({}^{2}\). The eigenmodes spectrum of the above-mentioned nanostructures is appreciably modified by the DMI-induced non-reciprocity in spin-waves propagation: the frequencies of the eigenmodes are red-shifted and their spatial profiles appreciably altered due to the lack of stationary character in the direction orthogonal to the magnetization direction. As a consequence, even for values of \(D\) between 1 and 2 mJ/m\({}^{2}\), easily achievable in real samples, one finds important modifications in the frequency position and in the cross-section of the different modes of the spectra. For instance, the (0,1) antisymmetric mode of elliptical dot would remain invisible without DMI, while it would be the most intense for \(D\) as large as 2 mJ/m\({}^{2}\). Moreover, we found that if one further increases the value of \(D\) above 3 mJ/m\({}^{2}\), the low frequency antisymmetric mode becomes soft, reflecting the transition of the ground state from uniform state to a chiral one with opposite chirality at the borders. We are confident that the results of this theoretical study will stimulate the realization of ferromagnetic resonance or Brillouin light scattering experiments on real samples, which are still lacking in the literature, aimed at verifying our theoretical predictions and achieving a quantitative comprehension of the effect of DMI on the dynamical properties of nanostructured samples, paving the way to their exploitation in spintronic devices.  
The video animations of the eigenmodes for the stripes and the dots are available online at this link: [[https://doi.org/10.5281/zenodo.4540983](https://doi.org/10.5281/zenodo.4540983)]([https://doi.org/10.5281/zenodo.4540983](https://doi.org/10.5281/zenodo.4540983)) (accessed on 15 February 2021).  
Conceptualization, methodology and investigation, writing--review and editing, visualization, R.S., M.A., S.T., and G.C.; software, data curation, R.S. and M.A.; supervision and project administration, funding acquisition, G.C. and S.T. All authors have read and agreed to the published version of the manuscript.  
This project 17 Fun08 TOPS has received funding from the EMPIR programme co-financed by the Participating States and from the European Union's Horizon 2020 research and innovation programme.  
Not applicable.  
The data presented in this study are openly available in Zenodo at [[https://doi.org/10.5281/zenodo.4629664](https://doi.org/10.5281/zenodo.4629664)]([https://doi.org/10.5281/zenodo.4629664](https://doi.org/10.5281/zenodo.4629664)) (accessed on 15 February 2021).  
The authors declare no conflict of interest.
## 3 Results and Analysis  
### Descriptive Statistics of Soil Nutrients  
Upon evaluating the soil nutrient indices from the sample points, we eliminated any outliers and proceeded with a descriptive statistical analysis. We also tested for normal distribution. The specifics can be found in Table 2. In our study area, the mean values for various metrics were as follows: soil pH--6.68; organic matter--25.04 g/kg; total nitrogen--1.51 g/kg; alkali-hydrolyzable nitrogen--129.88 mg/kg; available phosphorus--28.96 mg/kg; rapid-acting potassium--141.94 mg/kg; slow-acting potassium--238.33 mg/kg. Utilizing the grading metrics from China's Second Soil Census [26], our analysis indicated the soil's pH as neutral. In terms of nutrient content, the organic matter, total nitrogen, available phosphorus, and rapid-acting potassium were found to be at a medium level. Meanwhile, the slow-acting potassium appeared at a low level. Furthermore, referencing the variation coefficient standards from related studies [27], we categorized variation strength. Specifically, weak variation: coefficient of variation < 10%; moderate variation: coefficient of variation between 10% and 90%; strong variation: coefficient of variation > 90%. Our findings revealed that the soil's pH exhibited weak variation, with its coefficient of variation at 13.6%. Conversely, all other soil nutrient metrics displayed moderate variation. Notably, the alkali-hydrolyzable nitrogen showed the least variation, having a variation coefficient of 19.45%. Lastly, tests for normal distribution of the soil nutrient metrics indicated the following: pH, organic matter, total nitrogen, and alkali-hydrolyzable nitrogen align with a normal distribution. Meanwhile, metrics such as available phosphorus, rapid-acting potassium, and slow-acting potassium aligned with normal distribution only after undergoing logarithmic transformation.
## 7 Conclusions  
The objective of this analysis was to investigate the impact of specific seismic record characteristics on the nonlinear response of buildings and to define the characteristics with the most significant influence on structural damage in order to be able to select proper earthquake records for reliable time history analysis. The analysis was carried out using a previously calibrated nonlinear model based on the experimental ICONS model, representing \"existing buildings\" designed without earthquake regulations approximately 40 years ago. The analysis involved the process of selecting seismic records based on magnitude (M) and epicentral distance (R), which are the results of disaggregation, as well as peak ground acceleration (PGA). For each of the observed areas, 30 seismic records were chosen.  
The comparison of the maximum interstory drifts, a critical damage demand parameter of building structures under earthquake loads, and individual seismic characteristics determined that there is a substantial correlation with specific seismic record characteristics. Peak ground velocity (PGV), specific energy density (SED), and Housner Intensity (HI) were the seismic characteristics that proved to be the most influential on the damage to the structures and, therefore, these characteristics are the most reliable for assessing structural damage. The correlation between the IDR and various groups of ground motion metrics are as follows:  
* Traditional metrics, PGV and PGD, show a high-to-significant correlation with the IDR, making them crucial for structural damage assessment.
* Energy-based and spectrum-based metrics (SED, Ia, ASI, and HI) provide strong predictive capabilities for the IDR, highlighting the importance of energy effects.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline  
* Duration-based and fundamental metrics (UD, SD, M, and R) contribute moderately, especially in assessing long-duration shaking impacts.  
Combining multiple ground motion parameters could provide the most reliable assessment of potential structural damage. Therefore, the traditional metric of PGV should be used as the main one, instead of PGA, and then energy- and spectrum-based metrics can be used as additional ones for comprehensive seismic performance evaluation and finally selecting suitable earthquake records for time history analyses.  
Conceptualization, T.K.S. and A.B.; methodology, T.K.S.; software, T.K.S., U.B. and U.R.; validation, T.K.S. and A.B.; formal analysis, T.K.S. and A.B.; investigation, U.B. and U.R.; resources, U.B. and U.R.; data curation, T.K.S. and A.B.; writing--original draft preparation, T.K.S. and A.B.; writing--review and editing, T.K.S., A.B., U.B. and U.R.; visualization, T.K.S., A.B., U.B. and U.R.; supervision, T.K.S. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.  
The authors declare no conflicts of interest.
## 3 Results and Discussion  
### Model Validation  
Due to the scarcity of experimental data of two HDR dampers, the model validation will be carried out using single HDR damper results of Cu and Han [11]. In this case, the system will be considered without a second HDR damper (\(K_{2}=0\), \(l_{2}=0\), \(\lambda_{2}=0\)) whereas the other input parameters of the remained HDR damper is same to the work of [11]. Particularly, the bending stiffness of stay cable is considered in the present model compared to [11]. The non-dimensional spring factor is redefined by \(K^{*}=K_{1}.l_{1}\)/S with a loss factor equal to 0.4 and the tension force, \(S=2900\) kN. The nonlinear equations 7-8 are solved using the algorithm shown in Figure 2 to obtain the damping ratio of HDR damper utilizing spring factor (\(K^{*}\)) and installation position (\(l_{1}\)/\(L\)) values varying from 0.5 to 1.5 and from 0 to 0.5, respectively [11]. Figure 3 presents the damping ratio computed by present model and [11] for different damper locations. In general, the damping ratio calculated by the present model shows high agreement with findings of Cu and Han [11]. The validation metrics of present model and [11] are shown in Table 1. The predicted value of the present model and [11] exhibits a high correlation. The correlation coefficient (\(C_{\text{C}}\)) is approximate 0.999 for three different cases. In addition, the mean absolute gross error (\(E_{\text{MAGE}}\)) and root mean square error (\(E_{\text{RMSE}}\)) are very small, less than 1% for all cases (Table 1). The results obtained with the current model agree very well with [11] in terms of damping ratio value as well as the trend in the results for three different cases. In short, present model can be successfully utilized for approximate estimation of damping ratio for stay cable.
## 5 Establish the Short-Term Load Forecasting Model
### The Main Factors Influencing Load Forecasting  
The proportion of the meteorological sensitive load in the total load is increasing, and meteorological factors have become the primary factors affecting short-term load forecasting. The main meteorological factors that affect the load are temperature, humidity, rainfall, wind speed, and others [44; 45]. Temperature is the primary meteorological factor that affects the load [46].  
The cumulative effect of meteorological factors cannot be ignored either. Because human senses have an adaptation process to meteorological changes, the predicted days will be affected by the accumulation of temperature or humidity in previous days. It shows that the change in daily load is delayed by meteorological changes, and we call it the accumulation effect of meteorological factors. The cumulative effect is mainly affected by the meteorological factors three days before the predicteddate, in which the cumulative effect of temperature and relative humidity is most prominent [47; 48]. Combined with the other load factors selected in this paper, the influence of temperature and relative humidity on short-term load forecasting is considered in this paper. Due to the different degrees of cumulative effect caused by temperature and relative humidity, temperature and relative humidity were addressed by referring to the _THI_ used by the USA PJM market [1].  
\[THI=Temp_{F}-(0.55-0.55 Hmd)\times(Temp_{F}-58), \tag{17}\]  
where \(Temp_{F}\) represents temperature, with the units as degrees Fahrenheit, and \(Hmd\) is relative humidity. Due to the difference between the meteorological factors of the previous day and the meteorological factors of the two days before the forecast, the \(THI\) of the first two days were weighted. The \(THI_{1}\) of the previous day and the \(THI_{2}\) of the previous two days of the forecast are, respectively,  
\[THI_{1}=\frac{4}{5}\times THI, \tag{18}\]  
\[THI_{2}=\frac{1}{5}\times THI, \tag{19}\]  
where the _THI_ is calculated by Equation (17).  
Industrial load accounts for the main part of regional load, and the decrease of industrial load caused by the factory's holiday is the main factor of the change of holiday load [49; 50; 51]. Therefore, this paper considers the impact of holidays on load forecasting.
# Perpetual American Cancellable Standard Options in Models with Last Passage Times
## 2 Preliminaries
### The Structure of Optimal Exercise Times  
Let us now determine the structure of the optimal stopping times at which the holders should exercise the contracts. We first note that, it follows from the structure of the first integrands in (20) and (21) that it is not optimal to exercise the perpetual American cancellable put option when \(H_{1}(X_{t})\geq 0\), while it is not optimal to exercise the corresponding call option when \(H_{2}(X_{t})\geq 0\), for any \(t\geq 0\), respectively. In this respect, if we assume that \(\delta^{\prime}\equiv 2r-\delta-\sigma^{2}\leq 0\) holds, that obviously implies that \(\alpha\equiv 2(r-\delta)/\sigma^{2}-1\ <\ 0\) holds, then we see from the expression in (20) that the equality \(\tau^{*}\ =\ 0\) should hold for the optimal stopping time, so that one should exercise the perpetual American cancellable put option instantly. In this view, for simplicity of presentation, we further assume that \(\delta^{\prime}\ >\ 0\) holds, as well as note that the fact that \(\alpha\equiv 2(r-\delta)/\sigma^{2}-1\ >\ 0\) holds obviously implies that \(\delta^{\prime}\equiv 2r-\delta-\sigma^{2}\ >\ 0\) holds. In this case, the inequality \((\delta^{\prime}x-rL)(h/x)^{\alpha}\geq 0\) is satisfied if and only if \(x\geq\overline{a}\) holds with \(\overline{a}\ =\ rL/\delta^{\prime}\). Furthermore, the inequality \((rK-\delta^{\prime}x)(g/x)^{\alpha}\geq 0\) is satisfied if and only if \(x\leq\underline{b}\) holds with \(\underline{b}\ =\ rK/\delta^{\prime}\).  
We further search for the optimal stopping times in the problems of (20) and (21) with the structure:  
\[\tau^{*}\ =\ \inf\{t\geq 0\,|\,X_{t}\leq a^{*}\}\quad\text{and}\quad\zeta^{*}\ =\ \inf\{t\geq 0\,|\,X_{t}\geq b^{*}\} \tag{22}\]  
where the constant boundaries \(0\ <\ a^{*}\ <\ L\ <\ h\) and \(b^{*}\ >\ K\ >\ g\ >\ 0\) are to be determined, when \(\alpha\ <\ 0\) or \(\alpha\ >\ 0\), respectively (see Figures 1 and 2 below for computer drawings of the value functions and the optimal exercise boundaries).
# Periodical Vehicle Inspections with Smart Technology
## 2 Materials and Methods
### App Design  
The inspector can perform the actions described in Figure 2 in the application. First of all, the inspector must log into the application Figure 3. Once successfully logged in, the inspector will see the main activity screen of the app, as displayed in Figure 4, which begins with the inspector's name displayed at the top. Beneath the name is the so-called waiting list, which includes a list of assigned inspections. The assigned inspections are identified by the car's registration number, make, and model. When a specific inspection is selected by the inspector, the inspection details are displayed as shown in Figure 4. At this time, the inspector may perform the following actions:  
* Take photos of the VIN, odometer and vehicle;
* Read data from the OBD II diagnostic port of the vehicle;
* Perform a brake test of the vehicle.  
Data from all three actions are continuously uploaded to the national PTI server. Therefore, the developed application needs a continuous internet connection to function properly. The network architecture of the application can be seen in Figure 5. The application operates in this architecture as a client and communicates with the server through a REST API, from which it retrieves the necessary data about inspections and sends measurements and photos. The communication between the server is encrypted and possible only after authentication and authorization of the user account on the client side (Figure 3). There are two ways to connect a mobile application to the server: using a local Wi-Fi network or mobile data. The second option is advantageous, especially for inspections of agricultural vehicles that are performed outdoors or at the owner's location.  
During the process of taking photos and testing brakes, information about the mobile phone's location is also obtained. The choice of navigation system (GPS, GALILEO, etc.) depends on the capabilities of the phone used, but precise location is required. Therefore, localization based on the GSM network is considered insufficient.
## 1 Introduction
experimentally studied the wake development of a stationary cylinder and the VIV of a pivoted cylinder with elliptical trajectories at a fixed _Re_ = 3027. Their experiments showed that the wake topology of a 2 DOF VIV with different amplitudes significantly deviated from the shedding map of an one-degree-of-freedom (1 DOF) forced VIV originated from [PERSON] and [PERSON] [7; 8]. [PERSON] and [PERSON] adopted two-dimensional (2D) direct numerical simulations (DNSs) to study the hydrodynamic forces acting on a circular cylinder at _Re_ = 500 [9]. They found that the lift exhibited a variation when the wake vortex changed. However, the state of the wake mode was not reported in their research. [PERSON] and [PERSON] et al. performed a three-dimensional (3D) DNS of a forced oscillating cylinder at _Re_ = 10,000 [10]. Their simulation effectively predicted the lift and drag coefficients through a comparison with the experimental results, but the wake structure was also not illustrated in their study. Although the 2D simulation has some limitations, it has been extensively employed in high Reynolds number VIV studies [10]. [PERSON] et al. studied the effect of a modulated excitation frequency on a forced oscillating cylinder at _Re_ = 500 to 8000 by using an extensive 2D LES and qualitatively validated their conclusion through a comparison with the experimental data [11]. To accurately simulated the VIV phenomenon, numerical simulation commonly was restricted to low Reynolds numbers. This was caused by the fact that a large number of computational resources and additional modeling works needed to be invested to reasonably describe the flow regime beyond the laminar flow [12; 13; 14]. Significant improvements have been made to address the difficulties in numerical simulations of the VIV phenomenon. Currently LESs are increasingly applied to calculate the separation flows at subcritical, critical, and supercritical Reynolds numbers. [5; 15; 16] The LES method can accurately solve the large-eddy structures, because the transient large-scale turbulent motions are explicitly calculated. However, the LES method is usually not computationally feasible, since it is sensitive to the grid resolution requirement near the wall when the global flow dynamics is significantly impacted by the attached boundary layers. Additionally, LES often requires more computing resources [17]. To reduce the computational cost, hybrid turbulence modeling methods have been extensively developed, such as a very LES (VLES) method. The VLES method has also been used in an unsteady flow to handle the transient dynamics of a separated flow [18]. In this paper, a high-efficiency VLES method is used to simulate the VIV phenomenon of the oscillating cylinder at a subcritical Reynolds number \(Re\) = 4000 combined with the dynamic grid technique.
## 6 Numerical Results
### Metrics of Interest  
If a reward function is necessary for comparing policies, performance metrics are more important for providers. We considered characteristics from the provider's perspective rather than the user's perspective, such as the average number of requests in the buffer and the average waiting time. These characteristics include the probability (\(\beta\)) of resource reallocation if a signal arrives and the coefficient (\(\gamma\)) of resource utilization. These coefficients have the same meaning as the weights in the reward function (the second and third terms, respectively).  
\[\beta=\sum_{\mathbf{s}=(m,n_{1},n_{2})\in\mathcal{B}}\pi(m,n_{1},n_{2}),\]  
where \(\mathcal{B}=\Big{\{}\mathbf{s}\in\mathcal{S}:\;\;n_{1}>m,\;\;n_{2}<N-m\;\; \vee\;\;n_{2}>N-m,\;\;n_{1}<m\Big{\}}\),  
\[\gamma=\frac{\gamma_{1}+\gamma_{2}}{2},\] \[\gamma_{1}=\sum_{\mathbf{s}\in\mathcal{S}:\;\;n_{1}\geq m}\pi(m,n _{1},n_{2})+\sum_{\mathbf{s}\in\mathcal{S}:\;\;n_{1}<m}\frac{n_{1}}{m}\cdot\pi( m,n_{1},n_{2}),\] \[\gamma_{1}=\sum_{\mathbf{s}\in\mathcal{S}:\;\;n_{2}\geq N-m}\pi( m,n_{1},n_{2})+\sum_{\mathbf{s}\in\mathcal{S}:\;\;n_{2}<N-m}\frac{n_{2}}{N-m} \cdot\pi(m,n_{1},n_{2}).\]  
Figure 10 illustrates the graphs for the coefficient (\(\beta\)) of resource reallocation for a fixed set of reward function weights \(\mathbf{w}=(1,1,1)\). Since the baseline algorithm prioritizes maximum resource utilization over the resulting reallocation, its coefficient is lower than that of the optimal policy, which considers all principles equally. As the arrival rate of requests increases, there are fewer vacancies in the buffer and fewer resources available for data transfer. However, it is not possible to increase the total size of both slices; only the size of the \(k\)-slice can be changed by \"moving the boundary\". Therefore, in this scenario, the resulting resource reallocation decreases due to fewer states where \"moving the boundary\" is necessary.  
Figure 11 displays the graphs for the resource utilization coefficient (\(\gamma\)) for a fixed set of reward function weights \(\mathbf{w}=(1,1,1)\). As the baseline algorithm aims for maximum resource utilization, its coefficient is close to one. However, the optimal policy considers multiple principles simultaneously, resulting in a coefficient of approximately half the size. With an increase in the arrival rate of requests, a larger slice size is needed, causing the coefficient to increase.  
Figure 10: Probability that if a signal arrives, this results in resource reallocation. (**A**) Baseline algorithm. (**B**) Optimal policy.  
Figure 12 illustrates the relationship between the coefficients in question and the rate of signals (\(\delta\)) from the controller in the context of the baseline algorithm. The graphical data indicate that an increase in signal reception frequency correlates with a reduced necessity for adjusting the boundary between slices. Concurrently, although there is a reduction in the characteristic of resource utilization, its magnitude remains appreciably high.