esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results
### On the Occurrence of the Ionospheric Storm Effects
The ionization increases were apparent in all local time sectors, while they clearly dominated in the afternoon hours, and they were accompanied only partially by an increase in the F2 layer peak electron density height (hmF2) [47]. Although it is known that the afternoon ionization enhancements observed during storm conditions, when portrayed as a percentage change, are inversely related to solar flux, simply because of the monthly median control curves having smaller magnitudes (i.e., net solar cycle effect) [22], the identified differences were better attributed to different solar wind drivers: positive disturbances with strong afternoon components tend to be a critical feature of the ionospheric response to the impact of CIR/HSSs in the ionospheric middle latitudes that tend to dominate during the declining solar cycle phase and solar minimum conditions. Similar results have also been reported at several occasions for middle latitudes. As indicative cases, we note: [PERSON] et al. [39] reported mainly positive disturbances in terms of the peak electron density under the occurrence of CIR-generated storms that occurred in the low solar activity years 2008-2009, with no significant changes in hmF2 in several cases; [PERSON] et al. [48] found positive effects of geomagnetic storms in the peak electron density of the ionospheric F2 layer in the main storm days during CIR/HSSs-driven events; [PERSON] et al. [49] and [PERSON] et al. [50; 51] revealed the close relationship between the positive ionospheric storms and recurrent geomagnetic activity; [PERSON] and [PERSON] [52] concluded that positive ionospheric storm effects in terms of GPS-derived TEC were more prevalent over middle, low and equatorial latitude stations during  
Figure 3: The annual distributions of the DfoF2 estimates obtained over European locations for each year of the considered time period (i.e., 2008–2020) in a box plot format. The box has lines at the lower quartile, median (red line), and upper quartile values. Whiskers extend from each end of the box to the adjacent values in the data; in our case, to the most extreme values within 1.5 times of the interquartile range from the ends of the box. Outliers (e.g., data with values beyond the ends of the whiskers) are presented by red crosses. both CME- and CIR-driven storms, while negative ionospheric storm effects occurred only during CME-driven storms at the considered Southern and Northern Hemisphere middle latitudes.
###### Abstract  
In recent years, Fourier Transform Infrared (FTIR) micro-spectroscopy has shown promising potential in medical diagnostics at the cellular level. In fact, FTIR spectra can provide information related to DNA, protein, and lipid content and how such a content changes when a pathological state arises. Most of these information is included in the so-called fingerprint region (1000-1800 cm\({}^{-1}\)), consisting of several spectral peaks related to vibrational modes occurring inside cellular components. Unfortunately, the slides commonly used in cytology (as the glass microscopy slides and coverslips) are opaque to IR radiation in the fingerprint region, whereas they are transparent for wavenumber values larger than 2000 cm\({}^{-1}\), where few and broad spectral absorption bands, mainly due to lipids and proteins, are present. Nonetheless, here we show that FTIR spectra performed in the high wavenumber range 2750-3000 cm\({}^{-1}\) can be used to discriminate two different types of cells, one from a normal cell line (Human Keratinocyte, HUKE) and the other from a cancer one (SH-SYSY). The spectra are discriminated by means of their Principal Component Analysis, according to the PC1 component, and by means of ratiometric analysis, according to the ratio of the intensity of the peak at 2956 cm\({}^{-1}\) and that of the peak at 2924 cm\({}^{-1}\). The PC1 score values of the HUKE are statistically different from the PC1 score values of SH-SYSY, whereas the intensity ratio results larger for SH-SYSY than for HUKE cells. Such results occur for different substrates over which the cells have been grown, including the thick glass slides used for cytological analysis. This result is a further step toward the application of FTIR microspectroscopy in the cytological routine diagnosis.  
FTIR micro-spectroscopy; human cell lines; Principal Component Analysis 2020 10 8825 10.3390/app10248825
# Motion Simulation and Human-Computer Interaction System for Lunar Exploration
## 3 Simulation Results
### Multi-Channel Interactive System Experiment
#### 3.4.2 Voice Control-Touch-Button Three-Channel Interactions  
To test the effect of voice control, touch screens, and buttons on improving the work efficiency of the driver, we designed an experiment. The specific process is as follows:  
* Experiment 1: Starting the rover. The experimenter needed to complete the four operations of powering the console, turning on the attitude adjustment system, turning on the radar, and turning on the simulation system.
* Experiment 2: The experimenter turned on the radar and adjusted the suspension during driving.
* Control method: a. Button control; b. A combination of buttons, voice, and touch. Each experimenter used two control methods to conduct experiments. We recorded the duration of the experiment and the evaluation of operating comfort. The experimental data is shown in Tables 3-6:  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Number** & **1** & **2** & **3** & **4** & **5** & **6** & **7** & **8** \\ \hline Vision & 37.2 & 32.6 & 40.5 & 39.2 & 33.6 & 31.3 & 42.3 & 35.5 \\ Vision and force perception & 39.2 & 34.1 & 44.1 & 37.8 & 35.6 & 36.1 & 42.9 & 34.8 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Driving hours of visual and force interaction experiment.  
Figure 22: Comparison of experimenters’ driving routes.  
From the above data, it can be seen that the three-channel combination of buttons, touch, and voice control could shorten the operation time, and experimenters generally believed that the multi-channel combination was more comfortable and convenient.
## 3 Results and Discussion
### SLN/CnEO Biocompatibility  
One of the primary objectives of cancer therapy is to kill tumor cells by preventing, or at least minimizing, detrimental side effects on healthy organs.  
The SLN/CnEO hemotoxicity was tested as a first step in identifying the potential negative effects of the formulation (Figure 5A,B). The interaction with erythrocytes becomes an important factor when assessing the safety of nanoparticles, particularly if intravenous delivery is thought of as an SLN potential route [41]. According to the ISO/TR 7406 standard, biomaterials that result in a hemolytic ratio of less than 5% can be deemed safe for biomedical uses [42]. Here, erythrocytes were exposed to very high concentrations (100-400 \(\mu\)L/L) of free or encapsulated CnEO and long exposure periods (up to 48 h) to identify the safety of the formulations. A dose-dependent hemotoxicity of free CnEO was observed, which was significant at the highest tested concentration (400 \(\mu\)L/L) (Figure 5A,B). On the other hand, hemolytic ratios of less than 3.5% were found at any condition analyzed in SLN/CnEO. Probably, SLN may be protecting erythrocytes from direct CnEO exposure, where the main VOCs could be destabilizing their membranes, leading to hemolysis.  
Figure 4: CnEO EE and cumulative release. (**A**) CnEO EE (%). (**B**) CnEO release from SLN/CnEO at pH 7.4 and 5.0. Values are expressed as the mean \(\pm\) SD (n = 3).  
In addition, the cytotoxicity of SLN/CnEO on WI-38 normal lung fibroblasts was examined. Figure 5C shows that SLN/CnEO was non-toxic for WI-38 cells (viability \(>\) 70%) at 50 and 100 \(\mu\)L/L CnEO, which inhibited about 40 and 65% A549 cell viability, respectively (Figure 3B). This specific activity dependent on the cell type (normal or tumoral) may be associated with the selective activity of monoterepenes against cancer cells previously described [26; 43], although further studies are required to shed light on this issue.  
Altogether, these findings suggest that SLN/CnEO is a biocompatible and safe system able to improve the anticancer activity of CnEO.
# Personalized Video Summarization: A Comprehensive Survey of Methods and Datasets
## 5 Types of Methodology
### Keyshot Selection  
A video shot is a segment of video that is captured in continuous time through a camera. The keyframes are selected after the video has been split into shots. Another challenge arises when one shot is selected by the keyframes [49]. Identifying and defining crucial factors in this method is a hurdle and is used to choose the appropriate keyshots. Subsequently, methods for keyshot selection are introduced.  
* _Activity-based shot selection:_ The activity-based summaries focus particularly on specific activities of a video, which are analyzed and considered criteria for detecting keyshots of the video. In [20; 66], the selection of the keyshot is based on activity.
* _Object-based shot selection:_ The summaries that are object based place special emphasis on distinct objects within a video, which are examined and used as benchmarks for the summarization process. Based on the selected object, the keyshots of the video are detected. In the following studies [12; 19; 60; 62; 66; 67; 69; 70], the keyshot selection technique is based on object detection.
* _Event-based shot selection:_ Video keyshots are identified based on a particular event that the user finds interesting. For the personalized summaries in [31; 62], the selection of keyshots are based on events.
* _Area-based shot selection:_ Area-based summaries focus particularly on specific regions within a video, which are scrutinized and employed as reference points for the summarization procedure. Depending on the chosen region, the video keyshots are identified. For the personalized summaries presented in [62; 66], the selection of keyshots is based on the area.
# Resource Management and Secure Data Exchange for Mobile Sensors Using Ethereum Blockchain
## 3 Problem Description
* _Security and Privacy Concerns_: Blockchain's immutability and transparency can raise security and privacy issues, particularly in sensor networks dealing with sensitive data [52; 53; 55]. Ensuring data privacy and confidentiality while maintaining blockchain integrity is crucial. To address these challenges, our research proposes several innovative solutions:
* _Communication Modes_: We introduce two distinct modes of communication--node-to-node (N2N) and node-to-structure (N2S)--to enhance data exchange capabilities and improve scalability. This approach provides more alternatives for data transmission, even under peak traffic conditions, thereby addressing scalability issues. * _Unique Network Model_: A novel network model is proposed that optimizes performance by considering multiple attributes of network and signal quality, such as transmittance power, channel gain, and noise. This model aims to reduce latency and energy consumption while addressing scalability challenges. * _Simplified Consensus Mechanism_: The proposed scheme includes a simplified finite field and robust key generation approach to enhance security without compromising performance. This covers a novel validation scheme and an innovative trust computation method. These innovations collectively address the limitations of existing blockchain-based approaches by improving scalability, reducing energy consumption, optimizing storage and bandwidth usage, minimizing latency, and managing transaction costs effectively. The proposed scheme aims to provide a scalable, efficient, and secure model that bridges the gap between blockchain technologies and mobile sensor networks, thereby enhancing IoT applications.
## 4 Numerical Analysis
### Intra-Domain Handover for VANET in PMIP6 with Multicasting  
The intra-domain handover for VANET in PMIP6 for the proposed architecture is represented by Equation (12).  
\[TC_{Intra-PMIP6}^{VANET}=T_{Intra-Authentication}^{VANET}+BUC_{Intra-PMIP6}^{VANET}+ PDC_{Intra-PMIP6}^{VANET} \tag{12}\]The authentication cost, \(T_{Intra-Authentication}^{VANET}\), will have the component \(T_{Intra-Network-Entities}^{VANET}\), which is the same as \(T_{Network-Entities}^{VANET}\) in Equation (3). During intra-domain handoff, if the TTP of the local PMIPv6 domain has information about the vehicle, then it is authenticated; otherwise, the authentication request from the TTP present in the local PMIPv6 domain is multicasted to neighboring TTPs, and the TTP that has the authentication information will unicast the authentication response back to the requested TTP. The cost of authentication for vehicles includes the minimum cost required to multicast to neighboring TTPs. Thus, the authentication cost for vehicle, \(T_{Intra-Mobile-Entities}^{VANET}\) is expressed as in Equation (13).  
\[\begin{array}{ll}T_{Intra-Mobile-Entities}^{VANET}=&N_{Vch}\times\big{(}T_{ Setup}+Max(S_{TTP}\times 2T_{MAG-TTP},S_{TTP}\\ &\times T_{TTP-LMA})\big{)}+(S_{TTP}\\ &\times Min(2T_{TTP1-TTP2},2T_{TTP1-TTP3},\ldots\ldots 2T_{TTP1-TTPn}))\end{array} \tag{13}\]  
The binding update cost for intra-domain handoff, \(BUC_{Intra-PMIPv6}^{VANET}\), for VANET in PMIPv6 is same as \(BUC_{PMIPv6}^{VANET}\) in Equation (7), and the packet delivery cost for intra - domain handoff, \(PDC_{Intra-PMIPv6}^{VANET}\), is also same as \(PDC_{PMIPv6}^{VANET}\) in Equation (10). Therefore, referring to Equations (3), (7), (10) and (13), they give rise to Equation (14) as the total cost, \(TC_{Intra-PMIPv6}^{VANET}\), for intra-domain handover for the proposed model [23].  
\[\begin{array}{ll}TC_{Intra-PMIPv6}^{VANET}=&N_{MAG}\times(S_{TTP}\times 2T_{ MAG-TTP})+S_{TTP}\times 2T_{LMA-TTP}+N_{Vch}\\ &\times\big{(}T_{Setup}+Max(S_{TTP}\times 2T_{MAG-TTP},S_{TTP}\times T_{ TTP-LMA})\big{)}\\ &+(S_{TTP}\times Min(2T_{TTP1-TTP2},2T_{TTP1-TTP3},\ldots\ldots 2T_{TTP1-TTPn}))\\ &+S_{Control}\times 2T_{MAG-LMA}+S_{Data}\\ &\times(\mu\times T_{CN-MAG}+\tau\times 2T_{LMA-MAG}+\mu\times T_{ MAG-Vch})+\beta\\ &\times\text{log}(N_{MAG}\times N_{Vch/MAG})\end{array} \tag{14}\]
## 5 Results and Discussion
### Analysis of the Thermal Performance of the Storage Tank during Discharge with a c-h Ratio of 0.38  
#### 5.1.1 Time-Dependent Temperature Profile  
Figure 8 shows the axial temperature distribution inside the storage tank at dimensionless times 0.001, 0.4, and 0.6 for conditions E1, E2, and E3 as listed in Table 1.  
The axial temperature distribution for each condition exhibits two inflection points: at the first inflection point, the temperature begins to rise and the gradient increases; at the second inflection point, the temperature gradient starts to decrease, eventually rising at a slower rate until it reaches a stable temperature.  
During the discharge process, the thermocline migrates upward along with the entire flow field. As shown in Figure 8, when the flow rate is 0.1 m/s, the temperature distributions inside the three types of storage tanks show minor differences due to the relatively low flow rate. However, the final hot water temperature obtained in Type c is higher than that in Type b and Type a, while the thermocline temperature in Type b is higher than that in Type a. This indicates that at this flow rate, the porous structure still demonstrates superior energy storage performance. Due to the low flow rate, the discharge time is extended, and thermal conduction in the axial direction causes the energy of the upper hot water to transfer downward, resulting in the final hot water temperature in each tank being significantly lower than the inlet hot water temperature.  
When the flow rates are 0.2 m/s and 0.3 m/s, the lower degree of mixing as cold water passes through the porous obstacles results in a higher thermocline temperature in Type c, allowing for higher-temperature water to be obtained. The thermocline temperatures in both Type b and Type c are higher than in Type a, and the low water temperatures in Type a and Type b are higher than in Type c. The range of the temperature gradient region expands as the discharge process progresses, and the greater the flow rate, the more significant the differences in the temperature gradient regions among the three types of storage tanks. At a flow rate of 0.3 m/s, the differences in energy storage among the three tanks are most pronounced. At a dimensionless time of 0.6, the proportion of high-temperature hot water in Type c is 5% higher than in Type b and 10% higher than in Type a.
# Research on the Lossless Data Compression System of the Argo Buoy Based on BiLSTM-MHSA-MLP
## 2 Probabilistic Prediction Models  
### Bidirectional Long Short-Term Memory Network Model  
A long short-term memory (LSTM) network controls the flow of information by introducing memory units and gating mechanisms, thereby solving the gradient vanishing and exploding problems in traditional RNNs and improving the ability to capture the long-term dependencies of sequences. The forget gate determines how much of the memory cell state of the previous time step needs to be retained and how much needs to be forgotten. The input gate determines how much of the input information of the current time step needs to be added to the memory cell state. The update of the memory cell state is based on the output of the forget gate and the input gate to update the memory cell state of the current time step. The output gate determines which part of the current memory cell state will be output, and it combines the hidden state to form the output of the current time step. The unidirectional LSTM processes input sequentially in time order and in a forward direction, and the output of each time step depends only on the current time step and the previous time step. It may not be able to fully capture the sequence symmetry and utilize contextual information, so BiLSTM is introduced. BiLSTM is an extension of LSTM. By processing the input sequence in both directions, it can better understand and capture the symmetrical information and dependencies in the sequence. This paper uses a single-layer bidirectional long short-term memory network unit to perform sequence modeling and feature extraction on the output of the embedding layer. BiLSTM consists of two LSTM layers, one processing the forward sequence and the other processing the backward sequence. The BiLSTM network architecture is shown in Figure 1.  
Where X is the output of the input data after the embedding layer, and its dimensions are (batch_size, timesteps, emb_size). Y is the output of the BiLSTM layer, with dimensions of (batch_size, timesteps, lstm_size \(\times\) 2). Y contains rich contextual information about the input data.
## 3 Experimental Setup  
At the transmitter side, the optical sources were provided by single mode laser diodes (LDs, EP2000-DM-B at 2 \(\upmu\)m wavelengths by Eblana Photonics at Dublin, Ireland/NBD1550-00158 at C-band by Netopto at Shenzhen, China/TSL-550 at O-band by Santec Corporation at Aichi-ken, Japan). The working temperature and the current of the LD were maintained as constants by employing a Laser Diode Controller (LDC, Newport LDC-3744C by Newport Corporation at Montana, America). Because of the starting power threshold of the optical amplifiers and the large loss in MZMs, the optical carrier outputted from the LD was amplified by a commercial optical amplifier (TDFA, CTFA-PB-SM-33-BW3 at 2 \(\upmu\)m wavelengths by Keopsys at Lannion, France/EDFA, LTRAN LOA3000 at C-band by Luster at Beijing, China/SOA, AEON006 at O-band by Aeon Laser at Florida, America) before entering the MZMs. The optical amplifier was protected by the isolator (OP-112110333 at 2 \(\upmu\)m wavelengths by Idealphotonics at Shenzhen, China/HOPECOM 150128001 at C-band by Hopecom Optic Communications at Shanghai, China/HOPECOM 160706004 at O-band by Hopecom Optic Communications at Shanghai, China) from the reflection power. The best modulation efficiency of the polarization-sensitive MZMs was achieved by adopting a polarization controller (PC) to adjust the polarization state. The RF modulation signals (sinusoidal type) were applied by a signal generator (1465F-V by Ceyear at Qingdao, China) to drive the Mach-Zehnder Modulators (MX2000-LN-10 at 2 \(\upmu\)m wavelengths by iXBlue Photonics at Besancon, France/FTM7938 EZ at C-band by Fujitsu Optical Components Limited at Kanagawa-ken, Japan/MX1300-LN at O-band by iXBlue Photonics at Besancon, France), and the phase noise was as low as--120 dBc/Hz at 100 kHz offset (3 GHz \(\leq f\leq\) 20 GHz). At the receiving end, the photo-to-electric power conversion was achieved by employing an indium-rich InGaAs diode (ET-5000F by Electro-Optics Technology at Michigan, America) with the cut-off wavelength covering 1.31 \(\upmu\)m to 2 \(\upmu\)wavelengths. Optical spectrums of the optical signals after the MZMs and electric spectrums of the microwave carriers generated were observed by applying an optical spectrum analyzer (OSA, AQ6375 by Yokogawa Electric Corporation at Tokyo, Japan) and electric spectrum analyzer (ESA, N9030A by Keysight Technologies at California, America). In the experiment, the C-band single mode fibers were used to connect the optical devices that were also able to work at the 2 \(\upmu\)m/1.31 \(\upmu\)m wavelengths, and the experimental setups at the 2 \(\upmu\)m/1.55 \(\upmu\)m/1.31 \(\upmu\)m wavelengths were similar. Figure 1 shows the experimental setup for microwave carrier generation at the 2 \(\upmu\)m/1.55 \(\upmu\)m/1.31 \(\upmu\)m wavelengths using the DSB-CS modulation method.