esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Materials and Methods
### Pulsed Electric Field Equipment  
NFC blood orange juice was subjected to PEF treatment by adopting the juiceCEPT+\({}^{\text{\textcircled}}\) equipment distributed by Opticept technologies AB (Lund, Sweden). The juiceCEPT+\({}^{\text{\textcircled}}\) is a pre-assembled, plug and play unit (Figure 9). The components are hygienically designed in compliance with EHEDG provisions. It consists of a PEF high-voltage generator and a cabinet with an optimized booster step (treatment chamber). The equipment continuously monitors and logs the product conductivity, pressures, temperatures, product flow, and power level. These sensors provide valuable information about the treatment process and allow for complete quality assurance and process safety. The treatment is only enabled when there is enough flow through the system, and the integrated control valve ensures the maximum flow rate is not exceeded. Any amount of product that has not been sufficiently treated is returned through a 3-way valve. The equipment generates near-squared pulses in both monopolar and bipolar modes with an infinitesimally short rise time. The pulse generator has a maximum voltage of 8 kV, which generates the required electric field during the treatment, and maximum power of 8.4 kW. The number of pulses and treatment time (\(\mu\)S) may be modulated to adapt the treatment to the product. The treatment intensity recorded in terms of energy density was varied during the treatments by either increasing the power or decreasing the flow rate, wherein the energy density ranged from 120 to 200 kJ/kg of the product. The process connection is made from stainless steel and is food-grade. The patented 3D-printed treatment chamber is made from Nylon 12/PA12 and its two parallel parallelepiped electrodes are made from titanium covered with a noble metal coating for quick replacement and long life. The juiceCEPT+\({}^{\text{\textcircled}}\) is operated via a Siemens-based PLC system based on digital start/stop signals or complete integration to end users' PLC systems. The juiceCEPT+\({}^{\text{\textcircled}}\) is CE certified, meaning it is qualified to work safely. All cables and protective devices are designed and sized to comply with the EU Safety Directive and the relevant Electrical and Current Directives. The EMC Directive is equally guaranteed and certified by a qualified external body, ensuring zero emissions both via air and cables.  
Figure 9: Scheme of the PEF equipment (Opticept Technologies AB, Lund, Sweden).
# Multi-Hazard WebGIS Platform for Coastal Regions
## 3 Showcasing the Results: Application to the Central West Portuguese Coast
### Cova-Gala Observatory
#### 3.2.2 Observatory Information
In summary, the service: (1) downloads the images from ESA sciencehub ([[https://scihub.copernicus.eu](https://scihub.copernicus.eu)]([https://scihub.copernicus.eu](https://scihub.copernicus.eu)) (accessed on 10 May 2021)), using the SentinelSat API ([[https://pypi.org/project/sentinelsat/](https://pypi.org/project/sentinelsat/)]([https://pypi.org/project/sentinelsat/](https://pypi.org/project/sentinelsat/)) (accessed on 10 May 2021)); (2) verifies if clouds do not cover the ROI (region of interest); (3) calculates the NDWI indexes for all available images for that particular ROI and period (i.e., usually the last week is considered); (4) afterwards, an automatic threshold is applied to determine the water-land interface; and finally (5) the water mask results are shown in the service portal. In order to ensure that the images correspond to the area of the selected observatory, the script uses a predefined bounding box of the observatory area. The images are downloaded every five days, which corresponds to the revisit time of the Sentinel mission over this coast, using RabbitMQ and Celery to schedule and run a periodic task. The downloaded and cropped images are then binarized to identify the land and water pixels. The resulting binary image is rasterized and stored in the project database. Based on the observatory chosen by the user, [PERSON] orchestrates the building of a JSON file with the latest rasters. The rasters are then loaded into the Leaflet map, which allows for selected the binarized image being visualized in the map. The satellite data interface allows switching between observatories and provides the possibility to return to the data hub. Forecast results from both SCHISM and XBeach models are available in the forecasts (_previsoes_) page of the interface. The user can select the variable and model to be visualized on the map, built using Leaflet. This selection triggers the choice of the hour of the day for the prediction to be visualized, over a 48 h period, provided by the OPENCoastS  
Figure 11: Sample land/water interface at the Cova-Gala observatory represented by dark (**land**) and blue (**water**) pixels. service. The layers are created by the OPENCoastS engine and are obtained through a direct, customizable URL (Figure 12). The URL is directly accessed through Javascript and imported into the map via the Leaflet library. The URL allows the customization of the layer, which can come from either of the two models in the modeling infrastructure: SCHISM and XBEACH.
## 3 Results and Discussion
For the PCDL, TPU synthesized using 1,4-BDO or 1,3-BDO as the chain exender had a similar shear-thinning curve. Looking at the morphological analysis conducted using AFM, we can explain this property by referring to the influence of structure. Regardless of the type of butanediol used to synthesize the PCDL, the aggregation of the soft and hard chain zones would be more even and compatible than in the other groups. The higher level of microphase compatibility would result in a satisfactory level of melt viscosity obtained from the flow behavior. Next, to confirm the viscoelasticity, a vibration scan experiment was performed at 200 \({}^{\circ}\)C. The data are compiled and displayed in Figure 8. A vibration rheology experiment allows rapid observation of the presence of an intersection point between G\({}^{\prime}\) and G\({}^{\prime\prime}\). The loss modulus (G\({}^{\prime\prime}\)) of all the TPUs was higher than their storage modulus (G\({}^{\prime\prime}\)); this indicates all the TPU fused masses are viscous and can be used as hot melt adhesive. A difference between G\({}^{\prime}\) and G\({}^{\prime\prime}\) could also be detected; the difference between G\({}^{\prime}\) and G\({}^{\prime\prime}\) was larger in two groups, namely PBA and PTMG. TPU polymerized using 1,3-BDO has a more loosely organized internal structure; thus, the maintenance of a crystal structure is more difficult. Relatively, for TPUs polymerized using PCDL, differences between TPUs synthesized using different types of butanediol are minor. They have a similar internal structure, and their microphase compatibility is relatively better. Thus, they could be candidate materials for hot melt adhesives [9]. Figure 6: AFM scanned images: (**a**) PCDL-1,3-BDO, (**b**) PCDL-1,4-BDO.
## 2 Minkowski Fractal Reflectarray Design and Its Sensitivity Analysis
Hence, for the optimal design scenario, the size of the elements N must be determined based on space availability, with high distribution efficiency and a higher block ratio. The minimum and maximum ranges of these design parameters, used for design considerations, are detailed in Figure 3:0 This will provide valuable insight into selecting an appropriate range of parameters when designing a reflectarray. For the proposed fractal reflectarray, the gain can be observed in the range from 18.5 dBi to a maximum of 37.5 dBi with a variation in N from 5 to 41. Similarly, the FDe/Ade and BR can be taken from the range of 0.5 to 0.9, and the beam scan angle can be taken from a 0-degree to 60-degree maximum. Within these ranges, consideration of parameters can have an adverse effect, possibly resulting in lower gain and higher side lobe levels.
## 2 STATCOM Configuration and Operation
### STATCOM Configuration with Seven Level VSC  
The proposed configuration of a binary-weighted transformer integrated seven level VSC consists of self-commutating switching devices: GTOs or IGBTs, DC capacitance, AC reactance, interface transformer units and their controls. Figure 1a shows a STATCOM configuration with binary-weighted transformer-based seven level VSC. It has only one DC-Link capacitance and two three-phase modules, and each module consists of 3 H-bridges. The voltage source converters output is connected to transformers in 1:1 and 1:2 turn ratios.  
Figure 1b shows that H-bridge switching pattern output waveforms are obtained in every level of a voltage source converter, and transformer 2 output voltage is twice the transformer 1 output voltage. The Equation (1) is a novel firing angle '\(\alpha\)' generated for a multilevel voltage source converter (MLVSC). The firing angle is generated for seven Level VSC in the below-given procedure. The quarter sinusoidal waveform is equally divided into three levels of points and develops a staircase waveform. The firing angle is considered in advance of 0.5 to maintain the perfect levels of VSC with low THD values. The phase angle '\(\alpha\)' is responsible for the reactive power control. The optimized firing pulses are chosen for the minimum THD value. The optimized firing pulses '\(\alpha_{1}\)', '\(\alpha_{2}\)', and '\(\alpha_{3}\)' are estimated using Equation (1).  
\[\alpha_{\mathrm{i}}=\sin^{-1}\left(\frac{\mathrm{i}-0.5}{3}\right),\;\mathrm{ i}=1,2,3. \tag{1}\]  
where i = level of VSC and 3 is the maximum levels of VSC.  
\[\alpha_{\mathrm{1}}=9.59^{\lx@math@degree},\alpha_{\mathrm{2}}=30^{ \lx@math@degree},\alpha_{\mathrm{3}}=56.44^{\lx@math@degree}\]  
Figure 1c shows the harmonic spectrum of seven level VSC voltage output waveforms. The THD is 12.02% (a lower value than conventional VSC configurations).  
Figure 1: _Cont._Figure 1: (**a**) STATCOM co2 figuration with seven level VSC. (**b**) seven level voltage source converter voltage output waveforms. (**c**) Harmonic spectrum of seven level voltage source converter voltage output waveforms.
###### Abstract  
Information communication technology (ICT)-based mine safety management systems are being introduced at numerous mining sites to track the location of equipment and workers in real time and monitor environmental changes. This paper presents the results of a case study in which the big data created by an ICT-based mine safety management system are used for simulating truck haulage operations. An underground limestone mine located in Danyang, South Korea was studied, and the data generated over three months, from October 1 to December 31, 2018, were analyzed. Truck tag packet data recognized by relays were extracted and analyzed to calculate the averages and standard deviations of the truck travel times of each mine segment. A discrete event simulation program that simulates truck haulage operations in the study area was developed. Haulage times, the number of haulage operations, production output, and truck delay times were predicted, and results were compared with the actual operation results that were obtained on January 2 and 9, 2019. The difference between the predicted and actual results for the total amount of loaded ore was 30 tons for January 2 and 0 tons for January 9. The mean absolute error between the predicted and observed truck travel times was 0.13 min for January 2 and 0.14 min for January 9. The truck travel times that were measured differently according to the data aggregation period were set as temporal factors, and truck haulage simulations were performed. The results showed that more reliable simulation results were obtained as data accumulation time increased.  
url  
**Keywords: underground mine; mine safety management; big data; truck travel time; truck haulage simulation**
## 3 Results  
### Test Platform and Parameter Settings  
In this study, the experimental data included 600 pictures of airborne disease spores, of which 70% were used for training and 30% were used for testing. The low-order color moments contained abundant color distribution information. The HSV color space model was converted from the RGB color space model, which can be used for color expression in machine vision. The V component of the HSV color model is independent of color [25]. In this study, we used the color moment algorithm to extract the mean, variance, and skewness of the H and S color components, giving a total of 6 color features. The surface properties of the scene correspond to the image or image area described by the texture feature [26]. The gray level co-occurrence matrix was used to extract 16 texture features. The LBP algorithm was used to extract 59 texture features. The size range of _P. cubensis_ spores was 21.1-39.8 \(\upmu\)m. The size range of _P. xanthii_ spores was 30.2.1-39.5 \(\upmu\)m. The size range of _B. cinerea_ spores was 11.4-26.7 \(\upmu\)m. Therefore, in this study, the circularity, slenderness ratio, and 7 Hu invariant moment features of the spores were extracted as their shape features. The classification experiment was performed in the MATLAB R2016b environment. The computer system configuration used was as follows: Win10 (64-bit) (Microsoft Corporation, Washington, DC USA), running 16 GB memory(SAMSUNG, Gyeonggi Province, South Korea), with an Intel(R) Core (TM)i5-9400F CPU processor @ 2.90 GHz(Intel Corporation, Santa Clara, CA, USA). When the LR model was used to classify the spores of the three diseases, the instability caused by the possible bias of the sample number was considered and the adopted classification method was one-vs.-one. Some characteristic parameters of the spores of the three diseases intersected (such as the shape parameters). A logistics classifier was adopted and the Sigmoid function was used for the quantization function. In order to avoid overfitting, the LR algorithm chooses L\({}_{2}\) as the regular term. When the three disease spores were classified by the KNN model, 70% of the training sets were reclassified considering the number of samples, and the K value of the KNN algorithm was estimated by 10-fold cross-validation. The number of nearest neighbors of the KNN algorithm was set to 4. Euclidean distance was adopted for the distance function. When the RF model was used to classify the spores of the three diseases, in order to achieve the aim of drawing an equal number of samples, the sampling method used was \"put back\" sampling. The number of trees was set to 100. The minimum sample required to split the internal nodes was set to 2. The minimum number of samples on the leaf node of the RF algorithm was set to 1. The SVM algorithm uses a Gaussian kernel function and the classification method used was one-vs.-one.
# A Novel Scheme for MIMO-SAR Systems Using Rotational Orbital Angular Momentum
## 4 Results
### MISO Mode  
To further verify the effectiveness of our scheme, an experiment on the MISO mode was conducted. As shown in Figure 8, most of the configurations were the same as those in the SISO mode, except for the transmitting end. The signal from the signal generator was divided into two signals by the power divider. One connected to Tx1 transmitted the rotational vortex EM waves of mode +1, and the other one connected to Tx2 transmitted vortex EM waves of mode \(-1\). The horn antenna in the middle was still used to receive the superimposed signals from the target. The center frequency of the transmitting CW signal was 14.5 GHz.  
The spectrums of the received signals are shown in Figure 9. The red line denotes the spectrum when the rotation speed is 5 r/s in an anti-clockwise direction. Marker1, which denotes the echo of stationary mode \(-1\), was located at 14.5 GHz (0 Hz in Figure 9), while Marker2 was shifted \(-5\) Hz from Marker1, which denoted the echo of rotational mode \(+1\). When the rotation direction was changed to a clockwise direction, a +5 Hz frequency shift was obtained between Marker1 and Marker3, as shown in Figure 9 (the blue line). In contrast, the different frequency shifts among the two cases indicated that the rotational Doppler shift was determined by not only the rotation speed, but also the rotation direction, which was consistent with the theory. Consequently, the echoes of different OAM modes could be easily separated by the bandpass filter in the frequency domain.  
Figure 8: (a) Schematic configuration of the MISO mode; (b) experimental scenario of the MISO mode.
# The Recent Development of the Surgical Treatment for Hepatocellular Carcinoma
## 7 Liver Transplantation for HCC  
Liver transplantation for HCC can cure underlying cirrhosis, the origin of multicentric carcinogenesis, while removing the tumor by total hepatectomy. The Milan criteria, defined by the size and number of the tumor, is the most commonly used and accepted indication criteria for patients with HCC [86]. Subsequently, various expanded criteria based on tumor size and number have been reported with comparable long-term outcomes compared to the Milan criteria [87; 88; 89; 90]. In addition, a combination of alfa-fetoprotein (AFP) or des-gamma-carboxy prothrombin (DCP) values as factors other than tumor size and number has been reported to improve the prognostic value of transplantation compared to the Milan criteria [91; 92; 93]. Recently, new expanded criteria, the so-called \"5-5-500 rule\", was proposed by the Japanese Liver Transplantation Society based on a retrospective data analysis of the Japanese nationwide survey [94]. In the study of 965 living donor liver transplants for HCC, patients with nodule size \(\leq\)5 cm in diameter, nodule number \(\leq\)5, and AFP value \(\leq\)500 ng/mL without extrapicate disease or vascular invasion showed a 95% confidence interval of a five-year recurrence rate of 7.3% with an increase in number of eligible liver transplant candidates by 19% compared to the Milan criteria. In 2020, the \"5-5-500 rule\" was accepted as inclusion criteria for liver transplantation by the Japanese Social Insurance Coverage. There have been several reports on downstaging, and relatively good results have been obtained in terms of overall survival. Still, the recurrence rate is somewhat higher than that of cases within the Milan criteria. Therefore, the search for biomarkers, such as AFP and FDG-PET values after pretreatment, that can accurately assess the indication for liver transplantation after downstaging has been actively underway [95; 96; 97; 98; 99; 90].
## 3 Transient Analysis of PES System Using Fourier Integral Transform
### Case of Active-Inductive Load with Back-Emf  
The connection of the electrical circuit is shown in Figure 11, and the principal time waveforms of the input and output (load) voltages in Figure 7b, where the input voltage \(u_{in}(t)\) is harmonic cosine function, and S1 and S2 are electronic switches.  
Figure 10: Amplitude spectra of steady-state (**a**) and transient component (**b**) under \(R\)-\(L\) load in transient phenomenon at switch-on the system.  
The Fourier coefficients of that series are calculated by Euler relations.  
If \(\beta=\pi-\alpha\) using Appendix C  
\[a_{1}=\tfrac{8}{T}\int\limits_{\alpha}^{\tfrac{T}{\alpha}}\cos\omega t.\cos \omega t\ \mathrm{d}t=\tfrac{2}{\pi}\int\limits_{\alpha}^{\pi}\cos^{2}\omega t\ \mathrm{d}\omega t \tag{26a}\] \[=1-\tfrac{2\alpha}{\pi}-\tfrac{\sin 2\alpha}{\pi}.\]  
or  
\[=\tfrac{2}{\pi}\int\limits_{\alpha}^{\pi/2}(1+\cos 2\omega t)\ \mathrm{d} \omega t=\tfrac{2}{\pi}[\omega t]_{\alpha}^{\pi/2}+\tfrac{1}{\pi}[\sin 2 \omega t]_{\alpha}^{\pi/2} \tag{26b}\] \[=\tfrac{2}{\pi}(\tfrac{\pi}{2}-\alpha)+\tfrac{1}{\pi}(\sin\pi-\sin 2 \alpha)=1-\tfrac{2\alpha}{\pi}-\tfrac{\sin 2\alpha}{\pi}.\]  
The same result we obtain using Equation (18c) for \(\beta=\pi-\alpha\)  
\[a_{1}=U_{m}\frac{1}{\pi}\bigg{[}(\pi-\alpha-\alpha)-\frac{\sin 2(\pi-\alpha)- \sin 2\alpha}{2}\bigg{]}=U_{m}\bigg{(}1-\frac{2\alpha}{\pi}-\frac{\sin 2 \alpha}{2\pi}\bigg{)}. \tag{26c}\]  
Similarly, for the sine coefficient of fundamental harmonic  
\[b_{1}=\tfrac{2}{\pi}\int\limits_{\alpha}^{\pi}\cos\omega t.\sin \omega t\ \mathrm{d}\omega t=\tfrac{1}{\pi}\int\limits_{\alpha}^{\pi}\sin 2\omega t\ \mathrm{d}\omega t \tag{26d}\] \[=\tfrac{1}{\pi}\int\limits_{\alpha}^{\pi}\sin 2\omega t\ \mathrm{d} \omega t=\tfrac{1}{\pi}(\int\limits_{\alpha}^{\pi}+\int\limits_{\tfrac{\pi}{ 2}}^{\pi-\alpha})\sin 2\omega t\ \mathrm{d}\omega t\] \[=\tfrac{1}{2\pi}[\cos 2\alpha-(-1)+(-1)-\cos 2\alpha]=0.\]  
Checking, \(\alpha=0\), \(A1=1\)  
\[u(t,\alpha)=U_{m}\sum\limits_{v=1}^{\infty}{(-1)}^{\frac{v-1}{2}}\frac{A_{v}}{ v}\cos\omega t. \tag{27}\]  
Fundamental harmonic max value  
\[I_{1m}=\frac{2}{\pi}\int\limits_{\alpha}^{\pi-\alpha}\frac{U_{m}}{\omega L}( \cos\omega t+\cos\alpha)\mathrm{cos}\omega t.\mathrm{d}\omega t=\frac{V_{m}}{ \omega L}\frac{2}{\pi}\bigg{(}\frac{1}{2}\mathrm{sin}2\alpha+\pi-\alpha\bigg{)}. \tag{27a}\]  
The parameters of the system are given in Table 2.  
\begin{table}
\begin{tabular}{c c c c c c} \hline
**Um** & \(f_{1}\) **R** & **L** & **Z** & \(\tau_{rise}\) & \(\varphi_{1}\) \\
**[V]** & **[Hz]** & **[W]** & **[mH]** & **[W]** & **[ms]** & **[deg]** \\ \hline
325 & 50 & 18.4 & 43.93 & 23 & 10 \(\tau_{1}\) & 90 \\ \hline \end{tabular}
\end{table}
Table 2: Parameters of the system \(\alpha=36^{\circ}\), i.e., \(\pi/5\).  
Figure 11: Schematic connection of an inductive load with back-emf.
# Dynamic Behavior Analysis of I-Shaped RC Beams under Combined Blast and Impact Loads
## 4 Numerical Results of I-Shaped RC Beams under Combined Loads  
In order to more accurately evaluate the failure behavior of I-shaped RC beams used in highway bridges under combined blast and impact loads, some parameters of the numerical model of the I-shaped RC beams were adjusted according to the design documents. The section of the model was the same as that of the experimental beam subjected to contact explosion, the span of the beam was changed to 2000 mm, the spacing of the transverse reinforcement was 100 mm, and the grid size of the structure was 10 mm. The explicit dynamic analysis software LS-DYNA was used to establish a numerical model and calculate. The detailed dimensions of the structure are shown in Figure 5. When the blast load was applied to the structure, the detonation point was 400 mm above the mid-span, and the explosive was TNT (Trinitrotoluene). Different weights of explosives can change the proportional distance Z of the explosion. When the impact load was applied  
\begin{table}
\begin{tabular}{l l l} \hline \hline
**Model** & **Parameter** & **Value** \\ \hline \multirow{4}{*}{Concrete} & Mass density (kg/m\({}^{3}\)) & 2440 \\  & Compressive strength (MPa) & 42 \\  & Rate effects & Turn on \\ \hline \multirow{4}{*}{Rebar (longitudinal and transverse)} & Young’s modulus (GPa) & 210 \\  & Failure strain & 0.14 \\ \cline{1-1}  & Poisson’s ratio & 0.3 \\ \cline{1-1}  & Strain rate parameter C & 40 \\ \cline{1-1}  & Strain rate parameter P & 5.0 \\ \hline Transverse rebar & Yield stress (MPa) & 295 \\ \hline Longitudinal rebar & Yield stress (MPa) & 418 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Material properties used for I-shaped RC beams under impact loads.  
Figure 4: Damage behavior and numerical analysis results of the RC beam under the impact load.  
to the structure, the drop weight was applied at the mid-span with a mass of 400 kg. The different initial velocities of the drop weight can reflect the height when the drop weight falls. The material model, contacts, and algorithms were the same as when the structure was subjected to a single load application. By setting the start and end time of the load., it can be realized that when the subsequent load starts to be applied to the structure, the previous load ends.