esa-sceva/satcom-chunk-collection huggingface dataset:
# System Dynamics Modeling for Estimating the Locations of Road Icing Using GIS
## 2 Materials and Methods  
Research was conducted in six steps as shown in Figure 1. The first step is the selection of a scenario for model testing. The numerical results of the model were derived by selecting a scenario that shows freezing rain, which is the main cause of road icing [36]. The second step is the acquisition of spatial and meteorological data. Data that affect the generation of road icing were acquired from the Korea Meteorological Administration and topographic information-related platforms and were utilized [23]. Third, the types and values of parameters to be included in the model were designed. Fourth, modeling was performed to estimate road icing using the data and parameters selected by the scenario. It was designed to calculate road icing after calculating the road temperature and road moisture. The amount of road icing by location was then simulated by expressing the results of the modeling in GIS. Finally, it was analyzed whether road icing significantly occurred in actual areas vulnerable to traffic accidents [37].
# A Review of Ghost Imaging via Sparsity Constraints
## 3 Applications of GISC
### Fast Sampling Methods  
_(a) Prefabricated pseudo-thermal light source._ As depicted in Figure 1a, a reference CCD camera is placed in the reference path to record the intensity distributions simultaneously, and the sampling speed is constrained by the frames rate of the camera. Therefore, a prefabricated pseudo-thermal light source has been proposed to breakthrough this speed constraint. The key of the technique is to accurately address incident positions on a diffuser by a high-precision motor to produce repeatable pseudo-thermal speckle patterns. All reference intensity distributions are recorded in a low speed in advance, eliminating the camera recording in the imaging process [51; 52; 53].  
_(b) Structure 3D image reconstruction algorithms._ As described above, GISC technique exploits the sparsity of a natural target as a constraint, and it can reconstruct the target with a sampling rate far below the Nyquist limit. In a 3D image reconstruction, the orthogonal properties of the target at different distances can be also used for better reconstruction. Taking these into consideration, the number of measurement required to realize a successful 3D reconstruction can be greatly reduced, which is also constructive for fast imaging [19; 54].
## 3 Results and Discussion
### Scanning Electron Microscope (SEM) Observation and Energy Dispersive Spectrometer (EDS) Analysis  
The SEM photographs of the untreated GF-WTB and UP152-modified GF-WTB are shown in Figure 10. It can be seen from the figure that the surface of the original GF-WTB is smooth without any rough groove structure except for some resin curing agent residues scattered on it. After the modification of UP152, the surface of the fiber is covered with a rough graft layer of silane coupling agent and the fiber diameter also increases, indicating that the graft layer of the coupling agent UP152 has a certain thickness. Figure 11 shows the corresponding EDS element spectrum by spot scanning, and relative contents of elements are listed in Tables 4 and 5. Tables 4 and 5 show that after UP152 modification, the C element on the surface of GF-WTB increases significantly, Si and O contents decrease, and Ca element decreases significantly, indicating that the coupling  
According to the FTIR, SEM, and EDS analysis of the UP152-modified GF-WTB, the coupling agent grafted fiber surface becomes thicker and rougher and introduces a vinyl functional group, which improves the adhesion of the grafted GF-WTB to the SBS-modified asphalt.
# LBFT: An Asynchronous Committee-Based Blockchain Storage Strategy on Zero Trust Model
## 2 System and Problem Statement  
### System Model  
**Asynchronous Network.** We assume that any two nodes in the system are connected by asynchronous, fully meshed, authenticated point-to-point (P2P) channels. In this model, the adversary can arbitrarily delay the messages sent by the honest nodes, but they will be eventually delivered. This means two things: (1) all the messages sent from the honest nodes will not be dropped, and (2) they might be reordered by the adversary at will.  
**Threat Model.** In our system model, any node from the internet can join or leave the system without approval or authentication. There exists a round-adaptive Byzantine adversary, which can arbitrarily control the nodes at the beginning of each round to behave maliciously (e.g., forge and drop the messages), in order to impede the system to achieve consensus. In such a system with \(n=r\cdot f+1\) nodes, the adversary can corrupt up to \(f\) Byzantine nodes (where \(r\) is the fault factor satisfying that \(r\geq 3\)).  
**Zero-Trust Model.** We assume our system model is a practical application of the concept _Zero Trust_, removing the definitions of trusted networks (usually the internal networks) and untrusted networks (external networks) [35]. As a result, all the network traffic is considered threat traffic, even if the channels and devices are authenticated. Hence, the packets need to be verified that they are indeed inspected, authorized, and secured before access because the information in the packets cannot manifest the veracity of the asserted identities. To ensure system security in such a model, the following requirements are necessary [8]:  
* Ensure that all the resources are accessed securely, no matter where they originate from or who create them;* Adopt a least privilege strategy to reduce the likelihood for people to behave maliciously, and enforce access control strictly to protect access to restricted resources;
* Inspect and log all the network traffic, flipping the mantra _trust but verify_ into _verify and never trust_.
# Effects of _Cordycepps militaris_ Extracts on Macrophage as Immune Conductors
###### Abstract  
Although _Cordycepps militaris_ is documented several medicinal functions, there is not enough for demonstration of leukocyte differentiation. Cordycepin and adenosine were 11.75 ug and 1.25 ug in the extract, respectively. Unlike the levels of TNF-\(\alpha\) and IL-1\(\beta\) in macrophages that were approximately 4 time and 48 times higher than the control under lipopolysaccharidesaccharides (LPS), macrophages under the extract (1 ug/mL) showed 13- and 10-fold lower TNF-\(\alpha\) and IL-1\(\beta\) levels than the LPS-treated cells. This was corroborated by flow cytometry, where their levels were 20 times and 14 times lower, respectively. Under the extract, the LPS-treated macrophages enhanced M2 polarization and attenuated M1 polarization. In addition, the extract also dose-dependently activated macrophage phagocytosis. Under the extract conditioned medium, dendritic cells (DCs) were strongly differentiated toward CD11b\({}^{+}\) and Xcr1\({}^{+}\) cells because their densities were 13.6 times and 6.26 times higher than those in the LPS conditioned medium, respectively. Differentiation of Treg and natural killer T-like (NKTL) cells also were increased about 1.67 times and 6.73 times than those in the LPS conditioned medium, respectively. These results suggest that the _C. militaris_ extract has strong effects on the modulation of macrophages and dendritic cells and T cells under inflammatory stress.  
Cordycepps militaris; cordycepin; inflammation; dendritic cell; macrophage; T cell +
Footnote †: journal:  
slow blood clotting, and interaction with other drugs [14]. Although there are no clear causes for the side effects, _Cordyceps_ has many bioactive compounds, including polysaccharides, terpenes, phenolic compounds, and proteins [13]. The suggested dose of _Cordyceps_ is two and three times with 1050 mg extract or 0.14% adenosine [14].  
Macrophages, which are derived from monocytes, play an important role in phagocytosis in disease lesions and act as anti-inflammatory and pro-inflammatory cells depending on their polarization [15]. They are also involved in the modulation of innate and acquired immunities [15]. During inflammatory reactions, they also play a defensive role by producing nitric oxide (NO) and cytokines [16]. Lipopolysaccharides (LPS) are major endotoxins that are derived from gram-negative bacterial cell walls [17]. Macrophages exposed to LPS produce inflammatory cytokines, including interleukin (IL)-18, IL-6, and tumor necrosis factor (TNF), and they polarize to M1 macrophages [18; 19]. Although reported researches have shown the anti-inflammatory effects of _C. militaris_ extracts [20], there is no clear evidence of whether these extracts could act on macrophages to conducting the immune response.  
The goal of this study was to quantify the 3\({}^{\prime}\)-deoxyadenosine levels in _C. militaris_ and to evaluate the biological functions of _C. militaris_ extracts in the immunological conducting of LPS-treated macrophages.
# Unified Friction Formulation from Laminar to Fully Rough Turbulent Flow
## 3 Switching Functions, Friction Factors, New Formulation, and Comparative Analysis
### Friction Factors
#### 3.2.1 Laminar Flow \((a)\)  
Due to the overriding effect of viscosity forces in laminar flow, even rough inner pipe surface appears to be hydraulically smooth for Reynolds numbers lower than about 3000. Consequently, the roughness of walls, unless significant, does not affect the flow resistance. Under these conditions of flow, the friction coefficient \(\lambda\) is always a function of the Reynolds number \(Re\) alone, as seen in Equation (10):  
\[(a)\,\sim\lambda=\frac{64}{Re} \tag{10}\]
# Optimizing CNT Loading in Antimicrobial Composites for Urinary Tract Application
## 3 Results and Discussion
### AntibioticMins Assays
coli_ CECT 434 GFP biofilms developed on the different surfaces (Figure 6) clearly show an effect of the BM treatment on biofilm architecture, while corroborating the cell quantification results obtained for 3 wt% CNT-O/PDMS composites. In fact, while PDMS surfaces were completely covered by dense biofilm, the presence of empty spaces on biofilm structure tends to increase with increasing BM regimes. Figure 5: Percentage of _E. coli_ CECT 434 GFP (**a**) culturable and (**b**) total cells after 24 h of biofilm formation on PDMS (control), 3 wt% CNT-O/PDMS and 3 wt% CNT/PDMS composite surfaces containing 1, 2, 3 and 4 h ball-milled CNTs. The means \(\pm\) SE for three independent experiments are illustrated. Significant differences were considered for _p_-values < 0.05 (**_p_ < 0.001). Although all the tested surfaces presented significant reductions in the three parameters analysed--biovolume, biofilm thickness and surface coverage--the 4 h ball-milled CNT/PDMS surface yielded the best results. In fact, when compared with 3 wt% CNT-O/PDMS, 4 h ball-milled CNTs composites reduced the amount of biofilm per surface area, biofilm thickness and surface coverage by 31, 47 and 27%, respectively. Although 4 h ball-milled CNT decreases the dispersion degree of CNTs into PDMS matrix compared to 3 h ball-milled CNT, the toxicity imposed by the presence of exposed CNTs on the surface of these particular composites, as demonstrated by SEM analysis (Figure 3e), may have increased their antimicrobial effect. In fact, by being more exposed, the piercing effect of CNTs on the membrane of bacterial cells [46; 47] can be potentiated. Probably, by inducing a more open structure on the 3 wt% 4 h ball-milled CNT/PDMS composites, biofilms could be more susceptible to antimicrobial treatment [48], something that will be explored in future work. Overall, these results suggest that CNTs dispersed into the PDMS matrix preserved their activity and increased microbial growth inhibition. Moreover, the use of polymers in the fabrication of CNT composites allows the conservation of structural and mechanical properties of the final composite in biological environments [49; 50], limiting the release of CNTs and, consequently, their human toxicity. Figure 6: (**a**) Representative _E. coli_ CECT 434 GFP biofilm structures on PDMS, 3 wt% CNT-O/PDMS, 3 wt% CNT-BM 3 h/PDMS and 3 wt% CNT-BM 4 h/PDMS. These images were obtained from confocal \(z\)-stacks using IMARIS software and present an aerial view of the biofilms (shadow projection on the right). The white scale bar corresponds to 50 \(\upmu\)m. (**b–d**) Quantitative biofilm parameters obtained from the \(z\)-stacks: (**b**) biovolume, (**c**) thickness, and (**d**) surface coverage. The means \(\pm\) SD for three independent experiments are illustrated. Significant differences were considered for \(p\)-values \(<\) 0.05 (* \(p\) < 0.01).
# A New Internet of Things Hybrid VLC/RF System for m-Health in an Underground Mining Industry
## 5 Results and Discussion
operates at a center frequency of 868 MHz, with a path loss exponent of 2.2. The RF transmitter has a transmitted power of 10 dBm and an antenna gain of 2.5 dBi. On the other hand, the RF receiver has a minimum power received (sensitivity) of \(-100\) dBm and an antenna gain of 2.5 dBi. These parameters are essential to understand the performance and characteristics of RF uplink communication in the proposed system. The power received for the RF uplink, as shown in Figure 9. This curve shows a gradual decrease in power received as the distance between the RF transmitter and the RF receiver increases. This behavior is in line with the expected path loss characteristics in wireless communication systems, where the received power diminishes as the distance between the transmitter and receiver increases. The causes of this gradual decrease in received power can be attributed to factors such as free-space loss, antenna gains, and the path loss exponent. Free-space loss, which is influenced by the distance between the transmitter and receiver, results in a reduction of signal strength as the distance increases. Furthermore, antenna gains of transmitting and receiving antennas play a role in the received power, as they affect the effective radiated power and the ability to capture the transmitted signal. The path loss exponent, which accounts for the environment's impact on signal propagation, also contributes to the observed power-distance relationship. Finally, environmental factors such as obstacles, reflections, and absorption of the RF signal in the mining environment can also influence the received power. These factors can cause signal attenuation and contribute to a gradual decrease in received power as the distance increases. Figure 9: Received power for RF uplink.
# Maximizing Efficiency in Energy Trading Operations through IoT-Integrated Digital Twins
## 3 Proposed Architecture
### Evaluation
#### 3.4.2 Round Trip Time Analysis  
The analysis of round-trip time (RTT) in energy trading tasks examines the reaction time of the tasks inside the energy trading architecture that is based on IoT orchestration. The assessment parameter is utilized to evaluate the capabilities of jobs performed within a digital twin-based IoT task orchestration system. The formula for RTT calculation is shown below:  
\[\text{RTT}=t_{\text{acknowledge}}-t_{\text{send}} \tag{11}\]  
where \(t_{\text{acknowledge}}\) is the time when the acknowledgment or completion notification is received, and \(t_{\text{send}}\) is the time when the task was initially sent.
# Information Propagation and Bionic Evolution Control of the _Sebar_ Model in a Swarm System
## 3 Equilibrium Points and Basic Reproduction Number
### Basic Reproduction Number
\begin{array}{l}J_{1}=J(X_{1})\\ =\left[\begin{array}{cccc}0&-\langle k\rangle p_{2}&-\langle k\rangle p_{3 }&-\langle k\rangle p_{1}&p_{7}\\ 0&\langle k\rangle p_{2}-p_{4}-p_{5}&\langle k\rangle p_{3}&\langle k\rangle p _{1}&0\\ 0&p_{5}&-p_{8}&0&0\\ 0&p_{4}&0&-p_{6}&0\\ 0&0&p_{8}&p_{6}&-p_{7}\end{array}\right]\end{array}  \tag{15}\]  
The characteristic polynomial of Formula (15) can be expressed as:  
\[|\lambda E-J_{1}|=b_{0}\lambda^{5}+b_{1}\lambda^{4}+b_{2}\lambda^{3}+b_{3} \lambda^{2}+b_{4}\lambda+b_{5} \tag{16}\]  
By solving the characteristic polynomial, we obtain  
\[\left\{ \begin{array}{l}b_{0}=1\\ b_{1}=(p_{4}+p_{5}-\langle k\rangle p_{2})+(p_{6}+p_{7}+p_{8})\\ b_{2}=(p_{4}+p_{5}+p_{6}-\langle k\rangle p_{2})(p_{7}+p_{8})+\\ \qquad(p_{4}p_{6}+p_{5}p_{6}-\langle k\rangle(p_{1}p_{4}+p_{2}p_{6}+p_{3}p_{5} ))\\ b_{3}=p_{7}(p_{4}p_{6}+p_{5}p_{6}-\langle k\rangle(p_{1}p_{4}+p_{2}p_{6}+p_{3} p_{5}))+\\ \qquad p_{7}(p_{4}p_{8}+p_{5}p_{8}-\langle k\rangle p_{2}p_{8})+\\ \qquad(p_{4}p_{6}p_{8}+p_{5}p_{6}p_{8}-\langle k\rangle(p_{1}p_{4}p_{8}+p_{2} p_{6}p_{8}+p_{3}p_{5}p_{6}))\\ b_{4}=p_{7}(p_{4}p_{6}p_{8}+p_{5}p_{6}p_{8}-\langle k\rangle(p_{1}p_{4}p_{8}+p_{ 2}p_{6}p_{8}+p_{3}p_{5}p_{6}))\\ b_{5}=0\end{array} \right. \tag{17}\]  
When \(R_{0}<1\), it can be deduced that  
\[\left\{ \begin{array}{l}p_{4}+p_{5}>\langle k\rangle p_{2}\\ p_{4}p_{6}+p_{5}p_{6}>\langle k\rangle(p_{1}p_{4}+p_{2}p_{6}+p_{3}p_{5})\\ p_{4}p_{6}p_{8}+p_{5}p_{6}p_{8}>\langle k\rangle(p_{1}p_{4}p_{8}+p_{2}p_{6}p_{8 }+p_{3}p_{5}p_{6})\end{array} \right. \tag{18}\]  
Combined with Formula (17), and (18), we obtain  
\[b_{1}>0,b_{2}>0,b_{3}>0,b_{4}>0 \tag{19}\]  
According to the Routh-Hurwitz stability criterion, it can be concluded that  
\[\Delta_{1}=b_{1}>0 \tag{20}\]  
\[\Delta_{2}= \begin{vmatrix}b_{1}&b_{0}\\ b_{3}&b_{2}\end{vmatrix} =b_{1}b_{2}-b_{3}b_{0}>0 \tag{21}\]\[\Delta_{3}=\left| \begin{array}{ccc}b_{1}&b_{0}&0\\ b_{3}&b_{2}&b_{1}\\ b_{5}&b_{4}&b_{3}\end{array} \right|=b_{0}b_{1}b_{5}+b_{1}b_{2}b_{3}-b_{1}^{2}b_{4 }-b_{0}b_{3}^{2}>0 \tag{22}\]  
When \(R_{0}<1\), the equilibrium point \(X_{1}\) is locally asymptotically stable; when \(R_{0}>1\), the Jacobian matrix has positive eigenvalues. Therefore, the equilibrium point \(X_{1}\) is non-locally asymptotically stable. \(\square\)
# Virtual Pseudonym-Changing and Dynamic Grouping Policy for Privacy Preservation in VANETs
## 6 Experimental Evaluation Setup
### Evaluation Metrics
#### 6.2.1 Anonymity Set Size  
The Anonymity Set Size (ASS) is used to measure vehicle location privacy in the vehicular communication network. The ASS means the set of indistinguishable vehicles, including the subject or target vehicle [29]. The purpose of ASS is to anonymize the vehicles in the group of vehicles of similar status. The achieved level of vehicle privacy depends on the anonymization process. The higher the anonymization of vehicles, the higher the privacy protection will be. Our proposed scheme DGVP, combines similar status vehicles in a group and changes pseudonyms simultaneously. The cooperation of vehicles for pseudonym-changing is considered a Poisson process with vehicle arrival rate \(\lambda\), and \(X\) is the random variable that specifies the number of vehicles in a group at a specific time \(T\). The probability of vehicles is computed as given in Equation (54) [46].  
\[P(X=x)=\frac{(\lambda T)^{x}}{x!}e^{-(\lambda T)}. \tag{54}\]  
\(\lambda T\) the expected number of vehicles that update pseudonyms simultaneously. The expected number of vehicles in a group at time \(T\) is specified as:  
\[E(X=x)=\sum_{x=1}^{\infty}x\frac{(\lambda T)^{x}}{x!}e^{-(\lambda T)}=\lambda T. \tag{55}\]  
The anonymity set of the expected number of vehicles can be calculated as follows:  
\[|ASS|=\sum_{i,j=1}^{n}Veh_{i}Pseudo_{j}=\sum_{i=1}^{n}E(X_{i}=x)=\sum_{j=1}^{n }\lambda_{j}T. \tag{56}\]  
where \(Veh_{i}Pseudo_{j}\) is the number of vehicles that change pseudonyms simultaneously in the group for anonymization of pseudo-identities.
# Data Hiding of Multicompressed Images Based on Shamir Threshold Sharing
## 1 Introduction
The embedding capacity of this method is 1 bit per pixel (bpp), and although the visual quality of the stego images is slightly lower, this method can fully restore the original image after secret message extraction. This method is a kind of secret sharing data hiding in the extreme case. Although the security of the secret message is improved, the authorized receiver cannot recover the secret message without the complete two shadow images. In 2013, [PERSON] et al. proposed a magic matrix-based two-image RDH method [21]. Each group of two original pixels can be used to embed a three-bit secret message. During the embedding process, the maximum modification level of the covered pixels is four. Although the embedding capacity of this method reaches 1.55 bpp, the visual quality of the two stego images is not good. In 2015, [PERSON] et al. proposed a reversible data hiding method based on EMD [22]. In the process of secret embedding, the traditional EMD method is used to modify the pixels in the first secret digital by no more than one gray level to realize the embedding of secret data. Although the pixels in the second stego image are adaptively modified by referring to the first stego image, there is no confusion in the image restoration process. At the receiving end, the secret data can be easily extracted, and the original cover image can be correctly recovered from the two stego images. The method maintains acceptable visual quality for two cryptic images, while keeping the embedding rate of 1.16 bpp. In 2018, [PERSON] et al. proposed secret sharing data hiding based on the Turtle shell (TS) matrix [23], which splits the secret message into two parts. The secret message is hidden in the cover image through the TS matrix. Compared with the EMD method, the visual quality of the covert image of this method is greatly improved, but the visual quality of the two shadow images is different, which easily attracts the attackers' attention. In 2022, [PERSON] et al. proposed a reversible data hiding method based on the combination of pixel pair orientations in double stego images [24]. The pixel pairs of the two hidden images are divided into the main embedded pixel pair and the auxiliary embedded pixel pair. There are 25 combinations of dual stego-pixel pairs in a 3\(\times\)3 block and the original pixel value can be uniquely determined in extracting phase. The embedding capacity of this scheme is about 1.14 bpp, and the two generated shadow images also have advanced visual quality of 49.92 dB. In 2021, [PERSON] et al. made full use of the characteristics of the EMD matrix. One secret bit and a base-5 digit can be concealed in a cover pixel to generate a pixel pair that is assigned to two stego images. Unlike previous methods, the authors hid a secret bit and a base-5 secret number in a pixel instead of a pixel pair [25]. As a result, the embedding rate reached 1.56 bpp, but the Peak Signal to Noise Ratio (PSNR) of the two covert images was lower than most related algorithms.
# Semantic Image Segmentation Using Scant Pixel Annotations
## 4 Evaluation of the SSPA Approach
### Experimental Setup  
Training for the U-Net models was implemented using Keras with a Tensorflow backend as the deep learning framework on an Ubuntu workstation with 12-Core Intel iO-9920x and 128 GB RAM. We randomly selected 20% of the dataset as the validation set and the remaining as the training set during each fold. We used a learning rate of 0.1 and compiled the models using Adam optimizer [51] for 25 epochs, using the binary cross-entropy loss function. An early-stop mechanism was used to prevent over-fitting.
# A Location-Aware Waypoint-Based Routing Protocol for Airborne DTNs in Search and Rescue Scenarios
## 4 Protocol Design
### Contact Movement Path Checking
#### 4.3.2 Message Deletion  
**Variant 1.** Once forwarded, \(m\) is normally deleted from \(c\)'s buffer. In this way, there is only one message in the entire network, similar to the First Encounter protocol.  
**Variant 2.** The deletion of \(m\) from the buffer is avoided in order to increase the chance to find a better FN but at the cost of increasing the message replication.