esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Simulation and Discussion
### Discussion  
Exploitation and exploration abilities are two important indicators in evaluating optimization algorithms. The exploitation ability of an optimization algorithm means its power to provide a quasi-optimal solution. An algorithm that offers a better quasi-optimal solution than another algorithm has a higher exploitation ability. The unimodal objective functions F\({}_{1}\) to F\({}_{7}\), which have only one global optimal solution without local solutions, are applied to analyze the exploitation ability of optimization algorithms. The results presented in Tables 2-6 show that the proposed DM by modifying the optimization algorithms is able to increase the exploitation ability of the optimization algorithms and as a result more suitable quasi-optimal solutions are provided by the modified version. The exploration ability means the power of the optimization algorithm to scan the search space of an optimization problem. Given that the basis of optimization algorithms is random scanning of the search space, an algorithm that scans the search space more accurately is able move towards a quasi-optimal solution by escape from local optimal solutions. In the second and third category of objective functions F\({}_{8}\) to F\({}_{23}\), there are multiple local solutions besides the global optimum which are useful to analyze the local optima avoidance and an explorative ability of an algorithm. Tables 2-6 show that the modified version with the DM of optimization algorithms has a higher exploration ability than the original version. The convergence curves shown in Figures 3-7 visually show the effect of the proposed DM on the modifying the optimization algorithms. In these figures it is clear that the modified version moves with more convergence towards the quasi-optimal solution. The simulation results of optimization algorithms to solve the optimization problems show that the modified version of the optimization algorithms with the DM are much more competitive than the its original version. Therefore, the proposed method has the ability to be implemented on a variety of optimization algorithms in order to solve various optimization problems. The result of computational time analysis for both original and modified by DM versions is presented in Tables 7-9. In these tables, three different time criteria are presented, which are the average time per iteration (P.I. ), the average time per complete run (P.C.R. ), and overall time required for the original and modified algorithm to achieve similar objective function value (O.T.S.). Due to the addition of a correction phase based on proposed DM, P.I. and P.C.R. have been increased compared to the original version. Table 7 shows that except for four cases (TLBO: F\({}_{3}\), GWO: F\({}_{3}\), F\({}_{5}\), and F\({}_{7}\)), in all unimodal objective functions, the modified version provides the final solution of the original version in less time. Tables 8 and 9 show that the modified version of the studied algorithms for all F\({}_{8}\) to F\({}_{23}\) objective functions provides the final solution of the original version in less time.
## 2 Subject, Device, Data Collection and Experiments
### Experiments  
The experiments in this study are divided into two types. First of all, during the study period of this study, under the diagnosis of clinicians, the patient with lymphedema needed to undergo left foot fibrous tissue resection, right foot fibrous tissue resection and intra-abdominal lymph node transfer at different times. The research team took this opportunity to explore the changes in plantar pressure before and after the patient underwent surgery. During the experiment, the subject was invited to wear homemade insoles with no texture height and no arch. Under the guidance and supervision of the doctor, the subject performed three experiments of standing, walking and riding a bicycle before and after the operation (Figure 4).  
Figure 3: (**a**) An artificial arch support. (**b**) Arduino microcontroller. (**c**) Piezoresistive force sensors. (**d**) Textured granule.  
Figure 2: (**a**) The positions of the sole where the sensors are placed. (**b**) A pair of homemade pressure insoles and shoes.  
The second type of experiment included investigating the effects of using different textured height insoles and foot arches on the plantar pressure when the patient underwent surgery. This experiment was performed five months after the surgery. During the course of the experiment, similarly, under the guidance and supervision of the physician, the patient with lymphaden was invited to wear the three different heights of the foot pressure insole (Figure 3) designed with the arch to explore the impact on the patient's plantar pressure. Because the forefoot was the largest area of foot during the stance phase, we only placed textured granules under the forefoot (18 textured granules of the same height and size). The artificial arch support was placed on the medial midfoot. The patient was requested to step directly on the specially designed pressure insole without shoes on.
# Portable Raman Spectrometer for In Situ Analysis of Asbestos and Fibrous Minerals
## 3 Results and Discussion  
### Mineralogical Description  
Valmalenco asbestos-bearing veins mainly consist of long-fiber chrysotile, occurring in sub-vertical cross-fiber and slip-fiber veins, with thickness from mm up to several cm [42]. XRPD analysis of mineralized veins confirmed the sole presence of serpentine (Supplementary Material S2.1). Under the microscope, veins of slip chrysotile occur in the form of bundles of fibrous and curvilinear fibers, typical of the chrysotile morphology (Figure 2a,b).  
In the former Balangero asbestos mine, where massive and fractured serpentinites occur, two generations of both short (Figure 2c,d) and long-chrysotile veins crop out in the northern part of the mine. An example of slip short-fiber chrysotile veins is displayed in Figure 2c. Balangeroite was strictly associated with longer fiber chrysotile veins (Figure 2e). XRPD analysis showed the presence of serpentine associated with magnetite (Supplementary Material S2.2 and S2.3). Minor amounts of stichtite (chromium and magnesium carbonate; Supplementary Material S2.2) and balangeroite (Supplementary Material S2.3) were detected. At SEM observation, chrysotile presents its peculiar morphology, characterized by bundles of fibrous, curvilinear thin fibers with frayed and splayed ends (Figure 2d). Balangeroite occurs in the form of a bundle of rigid acicular elongated particles (Figure 2e,f) due to its gageite-like structure [53].  
At the Tontouta mine, veins of chrysotile and fibrous antigorite, with thickness from less than 1 mm to several centimeters, were intimately associated with minor tremolite-actinolite amphiboles. XRPD analysis of mineralized serpentine (Supplementary Material S2.4) and tremolite (Supplementary Material S2.5) veins confirmed the identification of the main phases. Minor chlorite, talc, and other Mg-Al-rich phyllosilicate (e.g., saponite) were occasionally observed. Petrographic and SEM observations showed the intimate intergrowth of chrysotile and fibrous antigorite fibers to form curvilinear bundles (Figure 2g,h). Tremolite occurred in highly fractured veins, with an acicular to needle-like morphology (Figure 2i,l).
## 4 Open Issues and Challenges
### Relative Motion between the UAV and the Sensors  
Both UAVs and targets are moving in U-WSN applications, such as animals monitoring. The topology of the network changes as the node and the UAV move. At this point, one node is within the range of the UAV, while at another time, it may be outside the transmission range. Thus, mobility directly affects the connectivity of the network. It has a significant impact on the data transmission performance of the network.  
The duration that the mobile node is within the transmission range of the UAV has an essential impact on the performance of the network, which is defined as contact duration [7; 17; 18; 19]. However, it only considers the case of mobile nodes and the same mobile direction as the UAV, the static case and opposite mobile direction with the UAV are not considered. In the following, we will provide a complete definition.
# Identification, Control, and Characterization of Peristaltic Pumps in Hemodialysis Machines
## 3 Analysis of Results
### Characterization
**Caption:** Relationship between revolutions per minute (RPM) and volumetric flow rate (mL/min) based on experimental data. The polynomial model provides the best fit with an RMSE of 0.9193 mL/min. Figure 7: Experimental setup for system characterization and validation. **Caption:** The system consists of a peristaltic pump controlled by a LabVIEW interface, connected to hemodialysis blood circuit hoses, and a synthetic blood reservoir. Synthetic blood flows through a hemodialysis filter to simulate real treatment conditions. Volume and mass measurements are recorded using graduated cylinders and a Sartorius weight scale to validate flow accuracy and stability. The setup replicates clinical conditions by integrating all components required for precise flow control, enabling characterization and validation of the developed control system under realistic operational scenarios. _Note: Red dye was added only to visualize the synthetic blood_. Table 2 highlights the statistical parameters for each setpoint, including average flow rate, standard deviation, and RMSE. The data indicate that the control system effectively maintains target flow rates with minimal variability. For example, at a target of 100 mL/min, the standard deviation was only 0.45 mL/min, reflecting high system accuracy. However, at higher flow rates, such as 600 mL/min, the standard deviation increased to 0.60 mL/min, consistent with prior studies that show greater variability at higher RPMs [25; 30; 31]. Despite this, the controller maintained a maximum error of only 1.897 RPM across all setpoints. The RMSE, measuring deviations between observed and target values, was relatively low across the range. For instance, the RMSE at 200 mL/min was zero, highlighting excellent accuracy at this point. However, at higher flow rates, such as 700 mL/min and 730 mL/min, the RMSE increased, reflecting the greater challenges in maintaining consistency at elevated speeds. These findings are consistent with previous research indicating that fluid dynamics and tubing friction introduce variability at higher RPMs [29; 30; 31]. The P.I. controller demonstrated strong performance, achieving minimal steady-state error and excellent repeatability across all tests. This indicates its suitability for precise control applications, particularly those requiring consistent and accurate flow regulation. Finally, Figure 9 compares a linear estimation with the experimental data. The linear model showed deviations exceeding 15 mL/min in key points (e.g., 100, 400, 500, and 700 mL/min), confirming the need for a non-linear approach. The fitted polynomial function, with its small quadratic coefficient (1.3255 \(\times\) 10\({}^{-5}\)), closely approximates a linear relationship but provides better accuracy. These results affirm that a non-linear model is more appropriate for describing the relationship between flow and RPM in peristaltic pumps.
# Experimental Study on the Soil-Structure Responses Induced by Tunnelling in Limited Space
## 3 Model and Test Descriptions
### Test Schemes and Monitoring Equipment  
The detailed layout of the experimental devices in the model test is depicted in Figure 8. To obtain a better understanding of the influence induced by tunnelling in limited space, a model test for the excavation of the same tunnel at a \"greenfield\" site [41] was also conducted.  
The variation of the earth pressure during the tunnel construction was also a main research object in this study. Hence, prior to the beginning of the test, a series of micro earth pressure cells were put both inside and outside the confined space. The detailed locations of the micro earth pressure cells are illustrated in Figure 9.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Type** & \begin{tabular}{c} **Outer** \\ **Diameter (m)** \\ \end{tabular} & \begin{tabular}{c} **Inner** \\ **Diameter (m)** \\ \end{tabular} & \begin{tabular}{c} **Thickness of** \\ **the Lining (m)** \\ \end{tabular} & \begin{tabular}{c} **\(E\)** \\ **(MPa)** \\ \end{tabular} & \
\begin{tabular}{c} **Poisson** \\ **Ratio** \\ \end{tabular} & **Material** \\ \hline prototype tunnel & 6.6 & 6.0 & 0.3 & 3.45e4 & 0.2 & concrete \\ \hline model tunnel & 0.22 & 0.2 & 0.01 & 953.67 & 0.2 &
\begin{tabular}{c} modified organic \\ plastics \\ \end{tabular} \\ \hline similarity ratio & 30 & 30 & 30 & 36.2 & 1 & / \\ \hline \hline \end{tabular}
\end{table}
Table 3: The parameters of linings of prototype tunnel and model tunnel.  
Figure 7: The drainage controlling system: (**a**) the water bag outside the tunnel; (**b**) drainage-controlling device.  
The deformation of the tunnel during the excavation process was measured with an automatic tunnel convergence measuring device. The inner force of the model tunnel was measured with a high precision strain gauge. The measuring sections were selected at the rings 15, 30 and 45. Each measuring section was equipped with 8 strain gauges and the angle between the adjacent stain gauges was 45\({}^{\circ}\). The locations of the strain gauges and the measuring sections of the inner force of the model tunnel are presented in Figure 10.  
Figure 8: Layout of the model test: (**a**) tunnelling in limited space; (**b**) tunnelling at greenfield site.  
Figure 9: Layout of the micro earth pressure cells.  
The ground settlements were measured with a high-accuracy displacement meter (the accuracy of the displacement meter was 0.01 mm). As the soil movement in the limited space was hard to monitor with traditional measuring instruments, this study adopted a non-contact measurement method with a digital image analyzing system (DIAS) [42; 43]. The DIAS included a high-definition camera and an image-based recognition system. The photos of soil movement were taken during the whole process of the experiment. These photos were compared with the original state which was captured before the model test.
# Burnup Credit Evaluation for BWR Spent Fuel from Full Core Calculations
## 3 Models Description  
### Fuel Assembly Design  
BWR fuel assembly design has evolved noticeably from the first reactor generations. For example, the lattice size has been increased from \(7\times 7\) to \(10\times 10\), with a gradual decrease in the rod diameter [24]. The goal of BWR fuel assembly optimisation is to use fuel as efficiently as possible during reactor operation. Over the last few decades, BWR fuel vendors have iteratively enhanced FA design to improve fuel performance. Despite some differences between FA constructions, the main features, such as non-uniform axial and radial fuel enrichment, rods containing burnable poison, water rods and part-length rods, have always been present in the various designs. For this study, GE14 \(10\times 10\) fuel assembly described in [25] was chosen for the BUC analysis. The fuel is uniformly enriched by 4.5 wt% of U-235 and the FA contains 15 gadolinium-poisoned rods with 7 wt.% of Gd\({}_{2}\)O\({}_{3}\). The study [16] showed that the impact of averaging radial enrichment in comparison to the non-uniform one, which is typical for the modern BWR fuel, only has a minor effect on the k\({}_{\text{eff}}\) and final isotopic composition in the BWR fuel assembly. Thus, the usage of the uniformly enriched fuel rods in this study will not significantly affect the results of the BUC analysis. The FA design includes 14 part-length rods which divide the FA into two axial regions. At the bottom region, all fuel rod positions are filled with fuel, forming the so-called \"dominant\" lattice (DOM) [25]. The upper part has empty rod spaces, providing additional moderation. This region is called a \"vanished\" lattice (VAN) [25]. The fuel assembly was modelled with naturally enriched (NE) uranium blankets (0.71 wt% of U-235) on top and bottom. The FA design is presented in Figure 1. Table 1 represents the main parameters of the BWR GE14 assembly.  
The described fuel assembly design is preferable for the study because it is based on a real, currently operated fuel assembly configuration and contains all main features of the modern BWR GE14 assembly [25] but has a lower degree of complexity in the modelling and simulations.  
Figure 1: Boiling water reactor (BWR) GE-14 \(10\times 10\) fuel assembly design as used for the study.
_Appl. Sci._**2015**, \(5\), 136-144; doi:10.3390/app5020136  
_Applied sciences_  
**ISSN 2076-3417**  
www.mdpi.com/journal/applsci  
Autocorrelation and Frequency-Resolved Optical Gating Measurements Based on the Third Harmonic Generation in a Gaseous Medium  
**[PERSON] 1,\({}^{\dagger}\), [PERSON] 2,\({}^{\dagger}\), [PERSON] 1,\({}^{\dagger}\) and [PERSON] 1,3,\({}^{\star}\)**  
1 Department of Applied Chemistry, Graduate School of Engineering, Kyushu University,  
744, Motooka, Nishi-ku, Fukuoka 819-0395, Japan; E-Mails: [EMAIL_ADDRESS] (Y.T.); [EMAIL_ADDRESS] (Y.K.)  
2 Laboratory of Chemistry, Graduate School of Design, Kyushu University, 4-9-1, Shiobaru, Minami-ku, Fukuoka 815-8540, Japan; E-Mail: [EMAIL_ADDRESS]  
3 Division of Optoelectronics and Photonics, Center for Future Chemistry, Kyushu University, 744, Motooka, Nishi-ku, Fukuoka 819-0395, Japan  
\({}^{\dagger}\) These authors contributed equally to this work.  
\({}^{\star}\) Author to whom correspondence should be addressed; E-Mail: [EMAIL_ADDRESS]; Tel.: +81-92-802-2883; Fax: +81-92-802-2888.  
Academic Editor: [PERSON]  
_Received: 7 April 2015 / Accepted: 3 June 2015 / Published: 9 June 2015_  
**Abstract:** A gas was utilized in producing the third harmonic emission as a nonlinear optical medium for autocorrelation and frequency-resolved optical gating measurements to evaluate the pulse width and chirp of a Ti:sapphire laser. Due to a wide frequency domain available for a gas, this approach has potential for use in measuring the pulse width in the optical (ultraviolet/visible) region beyond one octave and thus for measuring an optical pulse width less than 1 fs.  
**Keywords:** autocorrelation; frequency-resolved optical gating; third harmonic generation; pulse width measurement; ultrafast measurement
# GenConViT: Deepfake Video Detection Using Generative Convolutional Vision Transformer
###### Abstract  
Deepfakes have raised significant concerns due to their potential to spread false information and compromise the integrity of digital media. Current deepfake detection models often struggle to generalize across a diverse range of deepfake generation techniques and video content. In this work, we propose a Generative Convolutional Vision Transformer (GenConViT) for deepfake video detection. Our model combines ConvNeXt and Swin Transformer models for feature extraction, and it utilizes an Autoencoder and Variational Autoencoder to learn from latent data distributions. By learning from the visual artifacts and latent data distribution, GenConViT achieves an improved performance in detecting a wide range of deepfake videos. The model is trained and evaluated on DFDC, FF++, TM, DeepfakeTIMIT, and Celeb-DF (v2) datasets. The proposed GenConViT model demonstrates strong performance in deepfake video detection, achieving high accuracy across the tested datasets. While our model shows promising results in deepfake video detection by leveraging visual and latent features, we demonstrate that further work is needed to improve its generalizability when encountering out-of-distribution data. Our model provides an effective solution for identifying a wide range of fake videos while preserving the integrity of media.  
deep learning; deepfakes; deepfake detection; vision transformer; generative models +
Footnote †: journal: Applied sciences
## 5 Discussion
### Effect of Bol Length and Density  
The normalized displacements with different bolt lengths and densities are plotted in Figure 13a, and the normalized bolt length \(l_{bn}=l_{b}/(r_{p}^{ub}-R)\)[27] was taken as the abscissa, where \(r_{p}^{ub}\) is the plastic radius in the unbolted case. Note that if \(0\leq l_{bn}\leq 1\), the bolts were entirely embedded in the plastic region; when \(l_{bn}>1.0\), the bolts penetrated the elastic region. Figure 13a shows that the normalized displacement decreased with the increasing normalized bolt length until \(l_{bn}=1.3\), whereas the longer bolts could barely take more effective reinforcement. This phenomenon can be explained as follows: once the bolt section within the elastic region provided effective anchorage, the reinforcement effectiveness could not be further improved by increasing the bolt length. Therefore, the far end of the bolts should penetrate the elastic region to fully mobilize their effectiveness, while it was not necessary to over-extend the bolts beyond the range of the plastic region [25]. Furthermore, increasing the bolt density can result in better effectiveness (as shown by the red dashed line in Figure 13b).  
Figure 13b,c plots the tension force and shear stress with different bolt lengths and densities. The figures show that the tension force and shear stress both increased with increasing bolt length and decreasing bolt density, while a large length or small density could cause the tension failure of the bolt and decoupling at the bolt-rock interface. Therefore, a reasonable length and density should be considered in passive bolt designs.
# Investigation on Unsteady Flow Characteristics of a SCO\({}_{2}\) Centrifugal Compressor
###### Abstract  
Supercritical carbon dioxide (SCO\({}_{2}\)) is a vital working fluid in the application of power units and its high density helps to achieve a compact mechanical structure. Centrifugal compressors are of vital use in various kinds of equipment. In this paper, a SCO\({}_{2}\) centrifugal compressor of large input power and mass flow rate is designed and numerically investigated. A thorough numerical analysis of the unsteady flow field in the centrifugal compressor is performed in ANSYS-CFX. The computation adopts hexahedral mesh, finite volume method, and the RNG \(k\)-\(\epsilon\) two-equation turbulence model. Streamlines, temperature, pressure, and Mach number distributions at different time steps in one revolution period are covered to present the unsteady effect of turbomachinery. Meanwhile, the force on a single rotor blade is monitored to investigate the frequency components of exciting force, thus providing the foundation for vibration analysis. Moreover, the torque, output power, pressure ratio, and isentropic efficiency in the steady and the unsteady time-averaged condition are calculated and compared with the design condition to measure the validity of the design. In summary, the unsteady computation result reveals that the unsteady flow characteristics are prominent in the designed compressor and the design of impeller and diffuser meet the requirement.  
Keywords:SCO\({}_{2}\); centrifugal compressor; unsteady flow; exciting force +
Footnote †: journal: Applied Sciences