esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Comparative Verification
### Comparison with Engineering-Measured Data  
We consider a rectangular pipe jacking project for a rail transit entrance channel [26]. Regarding the outer edge of the pipe section cross-section, the height is 4.9 m, and the span is 6.9 m; regarding the excavation boundary, the height is 4.92 m and the span is 6.92 m. The buried depth at the top boundary is 5.04 m, the ground heaviness is 19.6 \(\mathrm{kN/m^{3}}\), the modulus of elasticity is 19.2 MPa, the Poisson's ratio is 0.2, and the rate of ground loss is 0.7%. For this project, the analytical solution of the complex function of this paper is used to calculate the surface subsidence caused by pipe jacking excavation using the midpoint and corner point of the bottom boundary of the excavation and the midpoint and corner point of the top boundary as the control points of the mapping function. The surface subsidence is compared with the engineering-measured data, as shown in Figure 8. It can be seen that the surface subsidence patterns, maximum values, and ranges are relatively close to each other, and the measured value of the maximum surface subsidence is 4.64 mm, while the analytical solution is 4.77 mm, and the relative error between the latter and the former is 2.8%, which is acceptable.  
Figure 8: Measured data and analytical solution of the surface subsidence of a rectangular pipe jacking project.  
Figure 7: Comparison of the analytical solution and the numerical solution for the stratum stress of the excavation boundary.
## 4 D-Leach
### Layer Configuration Phase  
D-LEACH configures layers of different sizes based on the relative distances of the sensor nodes. Figure 8. shows the layer structure of D-LEACH.  
Each sensor node transmits a message including the ID information to the BS. The BS calculates the relative distance of each sensor node based on the strength of the signal and stores the ID of the sensor node. The BS constructs layers of different sizes using the distance of the nearest sensor node and the distance of the farthest sensor node. The sensor nodes located close to the BS are included in the upper layer, and the sensor nodes located far away from the BS are included in the lower layer. The number of sensor nodes included in the layer decreases from the upper layer to the lower layer. The number of sensor nodes in layer \(i\) is expressed as \(N_{i}\) in Equation (5).  
\[Ni=N\times\frac{k-(i-1)}{\sum_{j=1}^{k}j} \tag{5}\]  
The number of sensor nodes in the network is \(N\), the total number of layers is \(k\), and the layer number is \(i\).
# Flexible Antennas: A Review
## 3 Fabrication Techniques for Flexible Antennas
### Inkjet Printing
Another work using photo paper to fabricate reconfigurable multiband antenna via two p-i-n diodes was reported [96]. A new silver nanoparticle-based conductive ink, having a built-in sintering mechanism, which is triggered during the drying of the printed pattern has been used to reduce the equipment cost and eliminate the complexity of post-treatment of the printed layer [97]. Meanwhile, chemically cured conductive ink (Ag nanoparticle) was used for fabricating a Z-shape antenna for operation in the ISM band (2.45 GHz) on a low-cost pre-treated PET substrate [98]. Printing resolution for inkjet-printed flexible antenna depends on the surface roughness of the substrate. For smooth substrates like Polyimide, PET, PEN, LCP, photo paper, etc., an excellent pattern resolution is achievable. For wearable, flexible substrates like E-textiles having the weaving of warp and weft yarns typically have an uneven surface. Hence, adequate resolution remains a challenge [99]. For fabricating wearable/flexible antenna, stitching, embroidery, and substrate integrated waveguide base (SIW) methods are mostly followed.
# Improved Least Squares Phase Unwrapping Method Based on Chebyshev Filter
## 2 Methods
### The Improved Least Squares Phase Unwrapping Method
Secondly, the filtered phase gradient is used for phase unwrapping:  
\[\phi_{i,j}^{k}=DCT^{-1}\Bigg{\{}\frac{DCT\Big{\{}\rho_{i,j}^{k}\Big{\}}}{2 \Big{(}\cos\Big{(}\tau\frac{i}{M}\Big{)}+cos\Big{(}\tau\frac{j}{N}\Big{)}-2 \Big{)}}\Bigg{\}}, \tag{11}\]  
where  
\[\rho_{i,j}^{k}=H\Big{(}\Delta_{i,j}^{x}\Big{)}-H\Big{(}\Delta_{i-1,j}^{x} \Big{)}+H\Big{(}\Delta_{i,j}^{y}\Big{)}-H\Big{(}\Delta_{i,j-1}^{y}\Big{)}. \tag{12}\]  
By Equation (8), if there is the incomplete unwrapped phase, there must inevitably exist \(\phi_{i,j}^{k+1}\):  
\[\phi_{i,j}^{k+1}=DCT^{-1}\Bigg{\{}\frac{DCT\Big{\{}\rho_{i,j}^{k+1}\Big{\}}}{2 \Big{(}\cos\Big{(}\tau\frac{i}{M}\Big{)}+cos\Big{(}\tau\frac{j}{N}\Big{)}-2 \Big{)}}\Bigg{\}}, \tag{13}\]  
\[\rho_{i,j}^{k+1}=H\Big{(}\Delta\delta_{i,j}^{x}\Big{)}-H\Big{(}\Delta\delta_{ i-1,j}^{x}\Big{)}+H\Big{(}\Delta\delta_{i,j}^{y}\Big{)}-H\Big{(}\Delta\delta_{i,j-1}^{y} \Big{)}, \tag{14}\]  
where \(\Delta\delta_{i,j}^{x}\) represents the error phase gradient. Then, if  
\[Avg\Big{|}\phi_{i,j}^{k+1}-\phi_{i,j}^{k}\Big{|}>e\text{ or }N>Nit, \tag{15}\]  
the wrapped phase can be regarded as fully unwrapping, where _Avg_ represents the mean-finding operation, and \(|\cdots|\) represents the absolute value operation. \(e\) is a very small number, and this paper sets it to \(10^{-3}\); in this case, it can be considered as completely unwrapping. Nit represents the maximum number of iterations, and this paper sets it to \(300\), preventing the unwrapping process from not converging. Finally, the unwrapped phase can be obtained as follows:  
\[\phi_{i,j}=\sum_{k=1}^{N}\phi_{i,j}^{k}. \tag{16}\]  
The proposed method is represented by the block diagram in Figure 1, which consists of the following main steps:  
1. Calculated phase gradient;
2. The parameters of the Chebyshev filter are determined according to the phase gradient;
3. The Chebyshev filter is used for phase gradient filtering;
4. Iteratively recover the entire wrapped phase.
## 5 Conclusions  
Due to the existence of the traditional adaptive interpolation de-fitting error, the solution to the satellite visibility problem results in a cycle calculation error. In this paper, we introduced an adaptive interpolation algorithm based on vertex protection that makes the vertices of the multi-hump function the endpoints of the adaptive interpolation subinterval to the greatest extent possible in order to avoid the period calculation error in the satellite visibility problem, making the adaptive interpolation algorithm applicable to a wider range of satellite visibility problems. The first solution for quickly determining the satellite-to-Moon visibility problem was given, and experiments were conducted using data from three BDS orbiting satellites to analyze its efficiency and accuracy. The experiments showed that  
Figure 8: Graphs of Earth occultation start and end times.  
Figure 7: Graphs of C01, C06, and C11 satellite rise and set times.  
the method reduces the computation time by approximately 98% compared to the brute force method, and the computational accuracy and efficiency of the algorithm proposed in this paper are better than those of the traditional adaptive interpolation method, with a reduction in computation time of up to 30%.  
Conceptualization, X.L. and F.C.; methodology, X.L.; validation, X.L. and P.S.; investigation, X.L. and D.L.; writing--original draft preparation, X.L.; writing--review and editing, X.L. and F.C.; visualization, P.S. and D.L.; supervision, F.C.; project administration, F.C. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the Project for Guangxi Science and Technology Base and Talents (Grant No. GK AD22035957), the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. DA28040300), the Informatization Plan of the Chinese Academy of Sciences (Grant No. CAS-WX2021 SF-03044), and the West Light Foundation of the Chinese Academy of Sciences (XAB2018B20).  
Not applicable.  
All data are available from the Multi-GNSS Experiment (MGEX).  
The authors are grateful to the Multi-GNSS Experiment (MGEX) stations and analysis centers for providing GNSS precise orbit sets. The authors gratefully acknowledge GFZ, WHU, IAC, SHAO, and CNES/CLS for providing precise products.  
The authors declare no conflict of interest.
## 5 Obstacles and Challenges in Evolving V2X Communication
### Architecture Obstacles and Challenges
#### 5.6.4 Mode 3 Communication  
The C-V2X standards offer a specific, non-GNSS-signal-based way of operation, which promises to enhance channel utilization in a congested channel environment. However, this communication mode introduces a single point of failure, which is not acceptable in the case of safety-critical applications. A good question is who the operator of the orchestrator is, since it needs to be clarified who is allowed to provide such a service (just as its business model) [59].
## 1 Introduction
At the compiling time, the binary code of BBs is calculated by a hash function to obtain an integrity digest, and the possible execution order of BBs is mapped into a control flow graph (CFG) and a bitmap. Each BB in the CFG is assigned a unique label. At runtime, the hardware-monitoring module (HMM), which is the core part of the overall architecture, will monitor whether the digest and the Hamming distance (HD) between labels are changed. For indirect jump instructions, HMM will check whether the jump operation is legal by detecting the value of the point on the bitmap corresponding to the target address of the instruction. The summary of our contributions is as follows:  
* We propose a hardware-based data integrity (DI) and control flow integrity (CFI) security-monitoring architecture. The architecture extracts the digest representing the DI information, and the label and bitmap representing the CFI information when the program is offline, and implements the integrity check of a variety of parameters through the hardware-monitoring module when the program is running, ensuring that malicious attacks on the data and control flow will be detected. * The proposed CFI protection mechanism that takes into account indirect jumps can effectively resist attacks against the control flow of embedded systems, such as CRAs, with lower resource overhead. For direct-jump-type instructions, the mechanism connects the BBs containing these instructions into CFG, and assigns a label to each BB according to the specific HD. For indirect-jump-type instructions, this mechanism maps the legal target address into a bitmap, which reduces the required storage space and speeds up the search. * We implemented the proposed architecture in hardware and evaluated the security capabilities, hardware implementation overhead, and performance overhead of the architecture based on the selected benchmarks. Experimental results show that the architecture can effectively resist tampering attacks on the data and control flow of embedded systems, and the performance overhead is about 6%. The rest of this paper is organized as follows. Section 2 introduces the related work on the DI protection methods and CFI protection methods of embedded systems based on hardware monitoring. Section 3 introduces the preliminary knowledge about our proposed architecture, including BB extraction, CRAs, and the threat model. In Section 4, the proposed method is analyzed in detail, including the overall structure, data integrity protection mechanism, control flow integrity protection mechanism, and the HMM. Section 5 evaluates the security capability, resource overhead, and performance overhead of the HIIMA. Section 6 concludes the work completed in this paper and the results achieved.
# Accuracy of Assessing Weight Status in Adults by Structured Observation
## 3 Results
### Associations between Measured and Estimated Weight and Height  
Figure 1 shows the distributions of measured weight and height, according to the respective categories of estimation (n = 254 observations). A strong positive rank correlation  
\begin{table}
\begin{tabular}{l c c c c} \hline \hline  & **Total** & **Women** & **Men** & **\(p\)-Value** \\  & **(n = 127)** & **(n = 70)** & **(n = 57)** & **\(p\)-Value** \\ \hline Age (years), mean \(\pm\) SD & 50.3 \(\pm\) 16.3 & 47.9 \(\pm\) 1.7 & 53.4 \(\pm\) 2.5 & 0.058 \\ Age categories, n (\%) & & & & \\
18–34 & 24 (18.9) & 15 (21.4) & 9 (15.8) & \\
35–54 & 53 (41.7) & 33 (47.1) & 20 (35.1) & 0.127 \\ \(\geq\)55 & 50 (39.4) & 22 (31.4) & 28 (49.1) & \\ \hline Height (cm), mean \(\pm\) SD & 164.9 \(\pm\) 9.6 & 159.7 \(\pm\) 0.8 & 171.5 \(\pm\) 1.1 & \textless{}0.001 \({}^{\text{a}}\) \\ Height categories, n (\%) & & & & \\ \(\leq\)154 & 14 (11.0) & 13 (18.6) & 1 (1.8) & \\
155–164 & 52 (40.9) & 42 (60.0) & 10 (17.5) & \textless{}0.001 \({}^{\text{b}}\) \\ \(\geq\)165 & 61 (48.0) & 15 (21.4) & 46 (80.7) & \\ \hline Weight (kg), mean \(\pm\) SD & 73.1 \(\pm\) 12.9 & 68.3 \(\pm\) 1.4 & 79.1 \(\pm\) 1.6 & \textless{}0.001 \({}^{\text{a}}\) \\ Weight categories, n (\%) & & & & \\ \(\leq\) 54 & 11 (8.7) & 10 (14.3) & 1 (1.8) & \\
55–74 & 63 (49.6) & 41 (58.6) & 22 (38.6) & \textless{}0.001 \({}^{\text{b}}\) \\ \(\geq\)75 & 53 (41.7) & 19 (27.1) & 34 (59.6) & \\ \hline BMI (kg/m\({}^{2}\)), mean \(\pm\) SD & 26.9 \(\pm\) 4.1 & 26.8 \(\pm\) 0.5 & 26.9 \(\pm\) 0.5 & 0.900 \\ BMI categories, n (\%) & & & & \\ \(<\)18.5 & 5 (3.9) & 4 (5.7) & 1 (1.8) & \\
18.5–24.9 & 32 (25.2) & 21 (30.0) & 11 (19.3) & \\
25.0–29.9 & 61 (48.0) & 24 (34.3) & 37 (64.9) & 0.006 \({}^{\text{b}}\) \\ \(\geq\)30 & 29 (22.8) & 21 (30.0) & 8 (14.0) & \\ \hline \hline \end{tabular} BMI, Body mass index; SD, standard deviation. \({}^{\text{a}}\) Statistically significant differences according to the \(t\)-test for independent samples with a significance level of 0.05. \({}^{\text{b}}\) Statistically significant differences according to the Chi-square test with a significance level of 0.05.  
\end{table}
Table 1: Age and anthropometric measures of the participants (n = 127).  
was observed between the anthropometric measures and the corresponding estimations, both for weight (\(\rho\) = 0.74, \(p\) < 0.001) and height (\(\rho\) = 0.78, \(p\) < 0.001).
## 1 Introduction  
Melanoma incidence rapidly increased over the last decades [1], and malignant melanoma is the most lethal form of skin cancer today [2]. Complicating its clinical treatment, the heterogeneity of malignant melanoma challenges the design of effective anti-tumor therapies [3]. Gold standard approaches in treatment and palliation include surgery, radiation therapy, chemotherapy, electrochemotherapy, adoptive cell transfer strategies, and immunotherapy [4; 5; 6; 7]. The outstanding success of immunotherapies awarded with the Nobel Prize for Medicine and Physiology 2018 has provided compelling clinical evidence that the immune system plays a critical role in tumor defense [8]. Research interest in oncology is therefore not only focused on whether tumor cells are eliminated by a given substance or therapy, but also whether they can be recognized by immune cells [9]. Moreover, plasma treatment itself can also exert effects on immune cells [10; 11; 12].  
The concept of immunogenic cancer cell death (ICD) proposes stimulation of an immune response against apoptotic tumor cells in a living host [13]. Apoptotic tumor cells, exposing plasma membrane-localized or intracellular molecules (damage associated molecular patterns, DAMPs), recruit myeloid cells [14]. Internalizing apoptotic cells, myeloid cells are capable to cross-present processed antigens on MHC class I molecules to tumor specific T cells [15]. This process results in a pro-inflammatory immune response [16], inducing tumor specific CD8\({}^{+}\) T cells potentially able to target melanoma cells [17]. Physical therapies in oncology have been shown to be potent ICD inducers, such as ionizing radiation, electrochemotherapy, and photodynamic therapy [18]. Another medical technology, cold physical plasma, was recently suggested for anti-melanoma therapy and danger signaling [19; 20; 21].  
For medical purposes, cold physical plasma is a partially ionized gas operated at atmospheric pressure and body temperature [22]. It reacts with ambient air and generates RONS species leading to decreased melanoma cell activity and growth in vitro [23; 24; 25] and in vivo [26; 27; 28]. High species concentrations can be used to exploit apoptotic redox signaling pathways in tumor cells [29], and first cancer patients have benefited from plasma therapy [30]. Plasma treatment can act in concert with other drugs [31; 32; 33], and plasma-generated reactive species induce pro-immunogenic molecules on tumor cells, such as ecto-calreticulin (CRT) [34; 35; 36]. Although the release of this and other DAMP signals after plasma treatment in melanoma cells has been shown, evidence of immune cell activation in response to plasma-treated melanoma is scarce. We here performed co-cultures of plasma-treated murine melanoma cells with murine splenocytes consisting of myeloid as well as lymphoid cells. Plasma treatment decreased melanoma activity and increased release of danger signals. The cytokine profile as well as cellular activation markers and signaling pathways were investigated in immune cells to track a hypothesized perception of plasma-killed tumor cells by lymphocytes or phagocytes.
## 3 Presentation of Developed Interface
### The End-User Mobile Phone Interface
#### 3.2.1 The End-User Mobile Phone Interface for DR Events  
Together with the creation of a DR event, all the contracted end users receive notifications which include the relevant information about the planned event, as shown in Figure 13. The system also checks any update through the internet connection. By clicking the received message, a list of the contracted appliances owned by the end user is shown on the screen, as seen in Figure 14. In this case, the end-user has three options: to decline to participate in the event, to allow all the available appliances to be controlled by the system operator during the DR event or to choose some of them only. It should be noted that the screen can be easily upgraded with further information consisting of total power, participant ratio and potential monetary and carbon emission savings, etc.  
Figure 12: The system operator interface screen for the list of present and previous events.  
Figure 13: The notifications on the end-user interface.  
In order to minimize the waste of time that is likely to be faced during response processes, an automatic reply option is also available for certain types of appliances and/or time periods based on end-user preferences, as shown in Figure 15. This menu enables end-users to automatically accept or decline DR events within the predefined time periods without receiving any notification.
# Research on Polarization Coding Cooperative Communication Scheme for FSO System
## 3 Construction Principle of System Polarization Code in Cooperative Communication
The implementation steps of the coding cooperation scheme based on system polarization code are as follows:  
1. At the source node, a system polarization code sequence up to the link \(S-R\) channel capacity is constructed. The code rate \(R<I(W_{SR})\) of the system polarization code is the mutual information of the channel. Assume \(0<\beta<\frac{1}{2}\) and \(\delta_{N}\triangleq\frac{1}{N}2^{-N^{\beta}}\). The frozen bit set of system polarization code is defined as: \[F_{SR}\triangleq\Big{\{}i\in\{0,1,\ldots,N-1\}:Z\Big{(}W_{SR}^{(i)}\Big{)} \geq\delta_{N}\Big{\}}\] (12) \[Z\Big{(}W_{SR}^{(i)}\Big{)}\] is the average Butterworth parameter of the channel. For a binary discrete memoryless channel, the average Butterworth parameter of the channel is: \[Z(W)=\frac{1}{2}\sum_{y\in Y}\sqrt{W(y|0)W(y|1)}\] (13) where \(y\) is the received signal of the channel and \(Y\) is the set of received signals. \(F_{SR}^{\zeta}\) is defined as the complement of \(F_{SR}\). The constructed system polarization code sequence only encodes information symbols \(M_{F_{SR}^{\zeta}}\). For the direct link \(S-D\), the construction  
Figure 2: Coding and decoding flow chart of cascaded CRC polar code. method of the system polarization code is the same as that of the link \(S-R\), and the frozen bit set of the link \(S-D\) is: \[F_{SD}\triangleq\left\{i\in\left\{0,1,\ldots,N-1\right\}:Z\left(W_{SD}^{(i)} \right)\geq\delta_{N}\right\}\] (14) (2) Firstly, the relay node decodes the information from the source node, and then extracts the set of information bits as the index \(F_{SD}\cap F_{SR}^{C}\), and then encodes these information bits with system polarization code up to the link \(R-D\) channel capacity, and finally sends them to the destination node. (3) The information decoded by the destination node includes some information sent by the source node to the relay node, that is, \(F_{SD}\cap F_{SR}^{C}\), the corresponding set of information bits. According to proposition 1 in reference [15], the frozen bit set \(F_{SR}\subseteq F_{SD}\) of the link \(S-R\). Therefore, the set \(F_{SR}^{C}\) of information bits of the link \(S-R\) can be used and recovered by \(F_{SD}\cap F_{SR}^{C}\) and \(F_{SR}\). Finally, the destination node combines the information bit set \(F_{SR}^{C}\) of the link \(S-R\) with the information bit set \(F_{SD}^{C}\) of the direct transmission link and decodes the combined information to recover the original information.
## 1 Introduction  
Carbon emission is among the factors that cause global warming; a major source of carbon emission is the burning of fossil fuels. In an effort to cut down carbon emissions, various alternative energy sources have been identified. Thermoelectric generators (TEGs) are among the promising alternatives for sustainable energy sources that can convert heat directly into electricity. This technology, if successful, will serve as a major source of energy on both the moon (space missions) and the earth (terrestrial applications). The thermoelectric effect often comprises the Seebeck effect, the Peltier effect, and the Thomson effect [1].  
Thermoelectric generators generally have a low conversion efficiency. This conversion efficiency depends on the transport properties of the thermoelectric (TE) material and is limited by electrical resistance and thermal contact resistance. Another factor that limits the conversion efficiency of TEG devices is Carnot efficiency [2]. Generally, for a TE material to be considered good enough for thermoelectric applications, its dimensionless figure of merit should be \(ZT=\alpha^{2}\sigma T/\kappa>1\). That is to say, the TE material should have a high power factor (\(\alpha^{2}\sigma\)) and a low thermal conductivity. TEG devices could be widely used if the conversion efficiency was increased. This can be achieved through increasing the figure of merits of the TE materials. The application of state-of-the-art technology in the design and optimization results in the minimization of thermal and electrical contact resistance losses. A reduction in these losses will give rise to an increase in the figure of merits. To date, various TE materials, such as skutterudite [3; 4; 5; 6], clathrate [7; 8; 9], half heusler [10; 11; 12], metal oxides [13; 14], perovskite [15; 16], and chalcogenide [17; 18], have been studied. Different material approaches have proven promising in increasing the \(ZT\) of materials; such approaches include Phonon Glass Electron Crystals (PGECs) [19], Phonon Liquid Electron Crystals (PLECs) [20], and the use of band resonant states to enhance the density of states [2], etc.  
Skutterudites, being cheap, abundant, relatively safe, having good thermal and mechanical stability and a high \(ZT>1\) at mid-range temperatures, is one of the TE materials that is increasingly attracting researchers' attention [21; 22]. Here, the modelling and optimization of skutterudite TE materials segmented with chalcogenides was done. The conversion efficiency values of the simulation were compared to the calculated efficiency values.