esa-sceva/satcom-chunk-collection huggingface dataset:
# NC-OFDM Satellite Communication Based on Compressed Spectrum Sensing
## 5 Simulation of NC-OFDM Satellite Communication System  
### BER Performance of NC-OFDM Satellite Communication System  
In order to avoid interference from the subcarrier side band to the adjacent frequencies of authorized users, a frequency domain filter is applied before emission on each subcarrier signal. The spectrum of the IF signal composed of 57 data subcarriers is shown in Figure 7.  
\begin{table}
\begin{tabular}{c p{142.3 pt}} \hline \hline
**Algorithm** & **Parameters** \\ \hline GA & Evolutionary algebra: 200, population size: 300, \\  & crossover probability: 0.3, mutation probability: 0.05 \\ \hline PSO & Number of iterations: 200, population size: 60, particle speed: 2, \\  & weight factor \(c_{1}\): 0.5, weight factor \(c_{2}\): 1.5 \\ \hline HGAPSO & Evolutionary algebra: 200, population size: 100, particle velocity: 2, weight factor \(c_{1}\): 0.5, weight factor \(c_{2}\): 1.5, crossover probability: 0.3, mutation probability: 0.05 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Parameters of different algorithms.  
Figure 6: Comparison of the throughput by different algorithms.  
The channel coding adopts convolutional code 2,1,6, and the modulationtype is BPSK. The transmission and reception of all data subcarriers are simulated and the BER performance is obtained as shown in Figure 8.  
The BER threshold of satellite communication is usually \(10^{-3}\)-\(10^{-4}\). As shown in Table 4, 11 subcarriers do not meet the requirements. The reason is that their frequencies are at the up and down boundary of the entire data subcarrier frequency domain, which cannot offset the interference of subcarriers efficiently as OFDM. It can be seen that 57 effective data subcarriers realize a data transmission rate of 228 Mbps, which proves that the NC-OFDM system can make efficient use of the spectrum holes in satellite communication.
## 2 Materials and Methods
### Single-Gateway Model  
Many researchers have utilized the single communication model to design a user authentication for WSN. The model, as shown in Figure 3, includes user, gateway, and sensor nodes. In the model, the user can access the desired sensor node after registering himself/herself into the GWN. However, the model user can only access the sensor nodes that are deployed within the local network. Furthermore, a user cannot access any sensor nodes that are deployed in the different agriculture fields, especially in large-scale environments. The user first sends an authentication message to the gateway; the gateway then sends the message to the deployed sensor. Later, the sensor node sends back the message to the gateway, and it forwards the message to the user whether the user was granted access or not.
## 4 Basic Concepts about Applied Cryptography Mechanisms
### ElGamal Algorithm  
ElGamal cryptography, known for being one of the earliest and well-known public key encryption methods, gained popularity in the 1980s due to its effectiveness and lack of patent restrictions [24]. It relies on the use of random integers during key generation, making it a relatively secure approach. The ElGamal algorithm is recognized for its simplicity and efficiency in various cryptographic operations, providing protection against threats in computer networks, including e-apps, online websites, and cryptanalyst attacks [24; 25]. As an asymmetric cryptography method, the ElGamal algorithm involves both public and private keys in the encryption and decryption processes. Its security is based on the complexity of discrete logarithms. The key ElGamal algorithm is created using the following: \(p=\) primes and \(y=gx\ mod\ p\) stands for random numbers and \(g<p\). Conditions: \(x=\) random numbers, \(x<p\). The following is how the text is encrypted: \(a=gk\ mod\ p\), where \(k\) denotes a random number decrypting text involves the following: \(m=b*a(p-1-x)\ mod\ p\)[25]. The ElGamal cryptosystem is a very effective application of the Diffie-Hellman algorithm; the cipher text for a particular message \(m\) is not repeated due to randomness in the enciphering process. The distinguishing characteristic of the ElGamal algorithm's encryption and decryption is the use of the residual obtained when a large number is divided by a prime number. Since there are countless ways to divide the number, it becomes exceedingly challenging to identify the original unique combination of factors that produced that specific residual [26]. The key size utilized by ElGamal's approach will eventually be utilized to calculate the positive prime number \(p\) and the integer \(q\), which is the primitive root of \(p\). For instance, a low parameter will be used to increase accuracy and make calculations simpler such as a key length of 1024-bit.
# Lightweight Design of Multi-Objective Topology for a Large-Aperture Space Mirror
## 3 Application Examples of the Topology Optimization Method  
### Initial Design of the Primary Mirror  
For this study, we considered a large aperture primary mirror with a center hole from a Cassegrain space telescope. The material of the mirror is SiC with the mechanical properties shown in Table 2. \(E_{0}\) is [PERSON]'s modulus; \(\mu\) is [PERSON]'s ratio; and \(\rho\) is density. The mirror is mounted by three BFs, as indicated in Figure 1.  
\begin{table}
\begin{tabular}{c c c c c} \hline \(\gamma\), \(\eta\), \(\mu\) & \(\alpha\) & \(D_{1}\) & \(D_{2}\) & \(P\) \\ \hline
0.33 & 0.3 & 25 nm & 160 nm & 0.2 kPa \\ \hline \end{tabular}
\end{table}
Table 1: Design parameters in topology optimization.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Outside Diameter** & **Inside Diameter** & **Outer Edge Thickness** & \multicolumn{3}{c}{**SiC**} \\ \cline{3-5}  & & & \(E_{0}\) & \(\mu\) & \(\rho\) \\ \hline
610 mm & 86 mm & 70 mm & 280 GPa & 0.17 & 2800 kg/m\({}^{3}\) \\ \hline \end{tabular}
\end{table}
Table 2: Parameters and material properties of the primary mirror.  
The finite element model is established in the commercial software HyperMesh. To improve the computational efficiency of topology optimization and ensure the rotation characteristics, a 1/3 finite element method (FEM) model with cyclic symmetry condition is proposed. Considering the manufacturability, the material is removed along the height direction of the mirror to obtain an open back configuration. This is achieved by setting the draw direction in optimization-topology panel in OptiStruct. The vector from an anchor node on the mirror surface to its projection node on the back surface determines the direction of the draft, and elements are also established in every row along the draft direction. The best distribution of the material is described through calculating the relative density of the elements. Figure 2 shows the 2/3 FEM model of the primary mirror. The FEM model of the primary mirror is divided into design area and non-design area. The non-design area distinguished in red color includes front mirror surface, outer edge, and inner edge, wherein the initial thickness of the front mirror surface is 4 mm, the outer edge and inner edge thickness are 5 mm. The remaining part of the mirror distinguished in green color is design area. The nodes of the fixed area are constrained during the optimization process. There are 116,520 elements and 129,912 nodes.
# In Vivo Evaluation of Decellularized Human Tooth Scaffold for Dental Tissue Regeneration
###### Abstract
Various growth factors regulate transplanted or endogenously homed cells, and play a critical role in cell proliferation, odontoblastic differentiation, extracellular matrix synthesis, contingogenesis, and chemotaxis [27; 28; 29; 30; 31]. The periodontitis is a supportive complex of gingiva, PDL, cementum, and alveolar bone, which provides attachment to the bone and acts as a barrier from the oral micropathogen. Secondarily, PDLs are directly associated with tooth vitality [32]. However, dental infection and trauma may bring significant adverse effects to the pulp and PDL, ultimately causing poor regeneration capability of the PDL. Several studies attempted periodontal ligament regeneration by utilizing PDLSCs and scaffolds including cell sheets [33; 34]. Pulp regeneration is important in restoring tooth vitality and maintaining the development of immature permanent teeth. Innovative regenerative endodontic procedures (REP) can overcome the limitations of conventional root canal treatments [35; 36]. However, REPs form dental pulp-like tissue, but in situ transplantation of human dental pulp stem cells (DPSC) has been shown to successfully regenerate vascularized pulp tissue [37; 38]. The direct transplantation of stem cells produces higher capillary density in newly formed tissues than the cell homing-based method [39]. The hypothesis for the current study was that decellularized human tooth scaffolds would retain their extracellular matrix integrity, support recellularization, and promote differentiation in stem cells. In our previous studies, we confirmed the effective fabrication method of decellularized human tooth scaffolds and the properties of decellularized human dental scaffolds. In addition, after recellularization of PDLSC and pulp on decellularized human dental scaffolds, their properties were confirmed in vitro [23; 24]. The current study, as a follow-up study, evaluated that decellularized human tooth scaffolds promote in vivo differentiation of DPSCs and PDLSCs.
## 3 Iterative Scheduling Algorithm for Throughput Optimization
### Communication Bandwidth Allocation Subtask Optimization  
The third sub-optimization block pertains to the allocation of bandwidth, which encompasses a decision variable dimension of significant magnitude.  
\[\begin{array}{ll}\mathit{Objective}&=\sum R_{i}\\ &=\sum B_{i}*log_{2}(1+SINR).\end{array} \tag{20}\]  
To ensure optimal communication efficiency for all users, it is imperative to guarantee that the allocated bandwidth does not fall below the minimal threshold required for the successful transmission of communication data, resulting in constraint on \(R_{i}\). An equal constraint is also given in this sub-block, as the sum of allocated bandwidths needs to be no more than \(B\), but with no waste.  
\[\begin{array}{ll}\max_{B_{i}}&\sum_{n}^{N}\sum_{i}^{K}R_{i,n}\\ &s.t.&\left\{\begin{array}{l}R_{min}\leq R_{i}\\ \sum_{i}^{K}B_{i}=B.\end{array}\right.\end{array} \tag{21}\]  
Decision variable \(B_{i}\) refers to bandwidth resource allocated to user \(i\) at a certain time slot. After these three sub-optimization tasks iterate and eventually converge, a multi-stage planning scheme can be proposed as follows, with sets of decision variables including U, B, and P, regarding UAV location, bandwidth allocation, and power control strategy, respectively. After all, our designed multi-subtask algorithm is established, with three sub-block problem consisting the total optimization function.  
\[\begin{array}{ll}\max_{UBP}&\sum_{n}^{N}\sum_{i}^{K}R_{i,n}\\ &s.t.&\left\{\begin{array}{l}0\leq P_{u}\leq P_{max}\\ \sum_{i}^{C}E_{i,n}+E_{n}^{F}\leq E_{max}\\ \sum B_{i,n}\leq B_{i}\\ v_{n}\leq v_{max}\\ R_{min}\leq R_{i}\end{array}\right.\end{array} \tag{22}\]
# Recent Trends in AI-Based Intelligent Sensing
## 2 AI Methods for Intelligent Sensing
### Lessons Learned  
In this section, several approaches based on AI are reviewed that can analyze the complex characteristics of sensor data for various applications. Most of the ML and DL-based algorithms work with numerous types of sensory data that come from different sources. However, algorithms of supervised learning for classification (i.e., SVM, DT, and RF) are mainly recommended when data have complex feature space (for example, hyperspectral sensor data). In particular, for data fusion from multiple devices, EL is more favorable because the fused data can be fed to an ensemble classifier for better results. For cases where the dataset size is small, K-NNs perform well as compared to other algorithms. The task is more challenging when the sensor data are unlabelled, and hence, the desired results can be obtained using unsupervised learning algorithms. Classification based on semi-supervised algorithms requires a limited set of annotated sensor data and performs well with time-series data. Another category is reinforcement learning that works well with the high-dimensional stream of input data. Its integration with deep learning is applied in new areas of research such as drone navigation. Furthermore, DL-based algorithms are also discussed and several conclusions are drawn. The variations of CNN are preferred when input sensor data is more than 1-D and are highly recommended due to their simultaneous feature extraction and classification capabilities. Most of the recent architectures such as RNN and LSTM perform well with sequential sensing data (i.e., sequence of words, images, etc.), but more favorably, LSTM is used due to its long-term dependencies among input data. For generating synthesized data that is different from actual sensor data, GAN is considered and has been proven to be successful in handling data privacy.  
A few attempts were made to examine the parameters that affect the performance of intelligent sensing. Internal and external factors such as the collection of real-time environmental data from multiple sensors, the nature of datasets, the accuracy of the training datasets, optimization parameters, etc., may hinder the overall performance of intelligent sensing. Thus, to create an efficient and robust smart system, it is vital to identify anomalies in data and take appropriate measures to remove them.
## 4 Discussion
### Challenges  
The study demonstrating the utilization of hyperspectral reflectance for non-destructive kiwifruit sweetness testing holds great promise for the future. However, this investigation exclusively focused on Cuixiang kiwifruit, characterized by a smooth, scarless surface and oval shape, for the purpose of controlling variables. It remains to be explored whether similar results can be achieved with other kiwifruit varieties or those with minor imperfections. Therefore, future research should involve a broader selection of kiwifruit varieties, encompassing diverse appearances, to ensure model stability, broaden the scope of measurement, and enhance model accuracy.
###### Abstract  
Previous studies using probiotics have shown strain-dependent effects on body mass index (BMI), body mass, or fat mass (FM). The aim of this study was to evaluate how the addition of yogurt containing _Lactobacillus acidophilus_ LA-5 and _Bifidobacterium animalis_ subsp. _lactis_ BB-12 strains to a diet plan affects selected anthropometric parameters in obese people on an energy-restricted diet. Fifty-four subjects aged 20-49 (34.52 \(\pm\) 9.58) years were included in this study. The recruited subjects were assigned to two subgroups: consuming probioticic yogurt along with a hypocaloric diet (GP) (n-27) or the same diet but without an intentional introduction of yogurt (GRD) (n-27) for 12 weeks. Both GP and GRD decreased body weight, BMI, fat mass and visceral fat by 5.59 kg and 4.71 kg, 1.89 and 1.61 kg/m\({}^{2}\), 4.80 kg and 4.07 kg, and 0.68 and 0.65 L, respectively, although the obtained differences were not significant. Analysis of GP and GRD results separately at the beginning and end of the intervention showed that fat loss was substantial in both groups (\(p<0.05\)). Consumption of yogurt containing LA-5 and BB-12 does not significantly improve anthropometric parameters in obese patients.  
probiotics; obesity; probioticic yogurt; energy-restricted diet; body composition 2020 10 5830; doi:10.3390/app10175830
# A Comprehensive Review of In-Body Biomedical Antennas: Design, Challenges and Applications
## 2 Design Specifications
### Miniaturization
#### 2.2.2 Path Lengthening of Current Flow  
By modifying the physical properties of an in-body antenna, it is possible to attain a prolonged path of effective current flow. This shifts the resonant frequency to a lower band, resulting in significant size reduction of the antenna [2; 17]. Numerous design techniques are considered for this purpose, such as meandered [33], spiral [33], hook slotted [3], waffle type [30] and radiator staking methods [27]. This technique can suffer from higher ohmic loss, resulting in lower radiation efficiency [32].
###### Abstract  
Introduction: An altered dental occlusion can also affect balance stability or mobility. Thus, the aim of this study was to examine whether wearing a mandibular splint, which retains the occlusion close to the centric occlusion, can increase or decrease balance stability and the range of motion (ROM) of the cervical spine as opposed to the habitual occlusion, and if there is a difference between men and women. Material and methods: In this study, 41 male (\(34.7\pm 11.4\) years) and 50 female subjects (\(29.3\pm 12.7\) years) participated. Cervical spine ROM was recorded using the Zebris CMS 70P system. For balance stability, a pressure measuring platform integrated into the treadmill system (FDM-T) of the company Zebris\({}^{\text{\textregistered}}\) Medical GmbH was used. Here, the area of the ellipse and the length of the Center of Pressure (CoP) was recorded whilst in the bipedal and unipedal stance. Results: The sex comparison showed significant differences for the area of the ellipse of the right leg and ROM extension in the habitual occlusion: females showed a better balance stability and a larger ROM extension. When wearing the splint, only the CoP of the left leg was significant with a better balance stability in female subjects. Within the male subjects, the ellipse area in the bipedal and unipedal (left/right) stance showed mostly significant reductions, while the rotation left and right as well as the lateral flexion (left/right) improved when wearing the splint. Female subjects, when wearing the splint, showed a significant decrease of the ellipse area and the CoP length when standing on either leg. Flexion, rotation to the right and lateral flexion to the left/right, all increased significantly. Conclusion: Wearing a splint that keeps the jaw close to the centric relation improved balance stability and increased the ROM of the cervical spine for both male and female subjects. Women may have marginally different basic balance stability strategies than men, with regard to bipedal and unipedal standing. Nevertheless, there are scarcely any differences between the two sexes in the adaptation when wearing a splint. Changing the jaw relation in healthy adults can possibly support the release of movement potentials that simplify the performance of everyday activities or sports movements.  
splint; postural balance; cervical vertebrae; range of motion; sex characteristics
# Opportunities and Challenges of Smartglass-Assisted Interactive Telementoring
## 4 Five Scenarios for Smartglass-Assisted Interactive Telementoring
### SAIT for Foreigner Navigation  
* _Mentors and Mentees of Different Levels._ This scenario involves foreign travelers as mentees who do not have much information on where and how to find their destination as illustrated in Figure 10. It will be helpful if local experts can accompany them to guide their navigation. For this purpose, local residents can play the role of mentors to help the mentees in their travel.
* _Sharing of First-person and Eye-level View via Smartglass._ The mentees' eye-level view captured by their HMDs is shared with mentors. Since the mentors are familiar with the local site, they can give useful information such as where to find good restaurants or which public transportation to use.
* _Extended Use Cases with Bi-directional Interaction._ In this scenario, voice-based UIs are used to communicate between mentors and mentees in real-time. Furthermore, telestration UIs can be used to draw attention to specific areas to explore and navigate. For example, the mentor can highlight and recommend popular landmarks to visit.  
Figure 9: An illustration of SAIT for hardware engineer scenario.
## 3 Graph Theory and Sensor Networks  
In this section, we explore the connection between graph theory and sensor networks. The main idea is to model a sensor network using a Delaunay graph, an approach that has been employed in previous studies [19; 20; 21].  
Consider a group of sensors distributed across a planar field. Each sensor is represented as a vertex (or node) in the graph. These nodes serve as points for data collection and transmission, mirroring the physical location and function of the sensors within the network. The topology of the graph encapsulates the spatial distribution of sensors and their interconnections, providing an intuitive and visually meaningful representation of the network's structure.  
The edges of the graph represent the connections between the sensors in the network, encapsulating how these sensors communicate to exchange information. Specifically, the spatial arrangement of the sensors is used to construct the graph associated with the sensor network. Following this methodology, the Delaunay graph corresponding to the sensor network is formed by linking nodes that are sufficiently close to each other. Each sensor thus corresponds to a vertex in the Delaunay graph, and the physical proximity between sensors is depicted as edges within the graph. This approach ensures efficient connectivity, reflecting the geometric relationships between sensors in the network. We show an example of this association in Figure 3.  
Figure 1: Example of the Voronoi diagram.  
Figure 2: Example of Delaunay graph.  
In this paper, we deal with several graph tools such as vertex coloring and Eulerian and Hamiltonian paths. These tools and their connection with Delaunay graph have been studied previously in [22; 23; 24; 25; 26; 27].  
Now, in the next subsections, we propose several possible applications of these graph-theoretical tools to enhance the design and functionality of sensor networks. At the end of each of these subsections, we give an example concerning the Delaunay graph from Figure 3.