esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Theory and Methodology
### Univariate Interpolation Schemes
#### 2.2.1 Univariate Lagrange Interpolation  
The level-\(i\) univariate Lagrange interpolation is defined as:  
\[\mathcal{I}_{i}\left[g\right]\left(y\right)=\sum_{j=1}^{m\left(i\right)}g \left(y_{i,j}\right)l_{i,j}\left(y\right), \tag{3}\]  
where \(l_{i,j}\) are univariate Lagrange polynomials, defined on the interpolation grid \(Z_{i}\) as:  
\[l_{i,j}\left(y\right)=\prod_{k=1,k\
eq j}^{m\left(i\right)}\frac{y-y_{i,k}}{y _{i,j}-y_{i,k}}.\]  
The accuracy of the interpolation depends crucially on the choice of nodes, e.g., Gauss-Legendre and Gauss-Hermite quadrature nodes are popular choices for RVs following uniform or normal distributions, respectively. In particular, the error between \(g\) and \(\mathcal{I}_{i}\left[g\right]\) is related to the best polynomial approximation error \(\epsilon_{\text{best}}\) through [6; 16]:  
\[\left\|g-\mathcal{I}_{i}\left[g\right]\right\|_{L^{\infty}\left(\mathbb{P}_{i} \right)}\leq\left(1+\mathbb{L}_{i}\right)\epsilon_{\text{best}},\]  
where \(\mathbb{P}_{i}\) denotes the space of Lagrange polynomials with degree up to \(m(i)-1\) and \(\mathbb{L}_{i}\) the Lebesgue constant:  
\[\mathbb{L}_{i}=\sup\frac{\left\|\mathcal{I}_{i}\left[g\right]\right\|_{L^{ \infty}\left(\mathbb{P}_{i}\right)}}{\left\|g\right\|_{L^{\infty}\left( \mathbb{P}_{i}\right)}}.\]  
Therefore, assuming that the interpolation error decreases for increasing interpolation levels, the interpolation nodes should be associated to a Lebesgue constant which grows at a slower rate.
# Damping of Beam Vibrations Using Tuned Particles Impact Damper
## 2 Idea of the Tuned Particles Impact Damper  
Popular granular vibrations attenuators are devices introducing additional damping to the system. Dynamic properties of such structures depend on many parameters, where the most important are: size, shape and volume of the container, filling ratio of granular media, grains features like density, shape and roughness. All previous studies related to the application of PIDs in dynamic systems assumed that changing of damping properties can be achieved by passive adjusting of previously mentioned parameters. Taking into consideration the advantages of semi-active methods of damping of vibrations over classical passive strategies the authors decided to improve the classical PIDs and introduce the Tuned Particles Impact Damper (TPID) enabling the user to adjust in the damping properties.  
The present paper focuses on the revealing the extraordinary features of the TPID device prototype, where rapid changes of the volume container allow for adjusting the damping characteristics of the system aimed in reducing the effects of temporary external excitations. The simplified idea of investigated TPID prototype and scheme of experimental setup is presented in Figure 1.  
The TPID can be treated as an additional device that can be mounted onto (eventually into) various mechanical systems to control their dynamical features, mainly to reduce their mechanical vibrations. The TPID prototype considered in this paper consists of the container (1) having a varying volume of the range (\(V_{min}=0.2\) [dm\({}^{3}\)]; \(V_{max}=0.79\) [dm\({}^{3}\)]). This volume can be controlled by the balloon (2) located inside the container. The balloon in its initial state is deflated and closely encapsulates the loose granular material (3) placed inside of it. In such a case the grains can be treated as a concentrated mass located in a selected place of the system. At the same time discs (4) connected with springs (5) limit the container volume to \(V_{min}\) value. The balloon is additionally equipped with a valve (6), the end of which protrudes from the container, enabling connection of the external pump. Changing the pressure inside the balloon expands it causing the movement of the disc and increasing the operating volume of the container. At this stage the granular material starts to vibrate which results in two main phenomenon: inelastic collisions between single grains and interaction with the casing. A further inflating of the balloon causes reaching the \(V_{max}\) volume of the device. The rapid changes of the TPID operating volume of the TPID device is a novel mechanism enabling adaptive-passive or in future semi-active damping of vibrations strategies. The additional advantages of the proposed TPID prototype are its uncomplicated design, high strength of its components and finally environmental friendliness.
## 3 Methodology  
The study comprised five stages. First, the building to be studied was selected. The research target was a building in which the maximum number of solar panels could be installed on the building's facade. Additionally, to avoid shadow interference, there should be no other buildings around the building. Second, the solar-energy-harvesting-based facade system was modeled and simulated virtually using building information modeling (BIM). BIM integrates various data into the architectural design process and implements them from the architectural planning and design stage to construction and operation [37]. The modeling and simulation in this study were conducted using Autodesk Revit 2020 software [38], a representative BIM. Dynamo [39], a Revit 2020 software plug-in, was used to implement flexible elevation of the solar-energy-harvesting-based facade system. Third, for maximal solar energy generation, the optimal angle of the solar panel for each month was derived, and the solar panel movement according to the monthly angle was simulated. Fourth, Insight [40], a Revit 2020 software plug-in, was used to estimate the amount of energy generated monthly. Fifth, the amount of renewable energy generated in one year was calculated, and the overall appearance of the building with the attached kinetic facade system was evaluated (Figure 1).
## 3 Computation Model
### Data Partition and Communication  
When using MPI (Message Passing Interface) to accelerate the program in parallel, there are two ways to partition the mesh, namely, one-dimensional (1D) partitioning and 2D partitioning, as shown in Figure 3a,b. According to the literature [20], 2D partitioning is more advantageous than 1D partitioning. Therefore, this paper adopts the 2D partitioning method; at each peripheral boundary of each MPI process, a layer of data buffer is set to store the boundary data transmitted by the adjacent process. The computation area of the original size is \(NX\times NY\), and the size with the buffer is changed to \((NX+2)\times(NY+2)\) (\(NX\) and \(NY\) are the number of grids in the horizontal and vertical directions, respectively).
## 7 Conclusions and Future Work  
In this paper, a sensor platform called Sensor4 PRI has been presented to provide a system to cost-effectively monitor railway infrastructures using Wireless Sensor Networks. The technical features of the different platform components have been shown, together with the exhaustive experiments carried out in order to analyze and evaluate them.  
The sensor platform has been specifically designed be part of a slab track, to be inserted in it during its construction, so that it can be used in both installation and maintenance phases of these kinds of systems. Distance sensors and inclinometers are used in the installation phase helping operators to place the slabs in the right position. Accelerometers are in charge of collecting information on vibrations suffered by the infrastructure when a train travels over it, achieving the supervision and maintenance of the infrastructure's structural health. In addition, solar panels have been included to increase the life time of the battery that supplies energy to the board.  
As for future work, we are involved in the deployment of several Sensor4 PRI platforms along a section of railway infrastructure (we still need to get the corresponding permission from the authorities) and, using the data mule based communication mechanism described and simulated in  
\begin{table}
\begin{tabular}{c c} \hline
**Component** & **Price** \\ \hline Arduino Mega & 41.00 \(\upcels\) \\ Module Xbee-Pro 868 & 75.00 \(\upcels\) \\ Xbee explorer regulated & 8.50 \(\upcels\) \\ Antenna 0 dBi & 8.00 \(\upcels\) \\ Battery Litio 1000 mA/h-3.7 V & 9.10 \(\upcels\) \\ Shield solar cell & 11.50 \(\upcels\) \\ Solar Panel 1.5 W & 6.65 \(\upcels\) \\ Accelerometer ADXL345 & 21.00 \(\upcels\) \\ Inclinometer & 63.14 \(\upcels\) \\ Distance Sensor SRF05 & 16.00 \(\upcels\) \\ Open Log & 24.95 \(\upcels\) \\ SD card & 6.00 \(\upcels\) \\ Total & 290.84 \(\upcels\) \\ \hline \end{tabular}
\end{table}
Table 11: Selected components.  
Figure 13: Sensor4 PRI platform.  
our previous approach, we hope to achieve a real WSN-based monitoring system for railway infrastructure protection.  
This work was funded by the Spanish projects ITC-20131017 (\"Fastrack: Eco-Friendly and Sustainable slab TRACK for high-speed lines\"), TIC-1572 (\"MIsITca: Critical Infrastructures Monitoring based on Wireless Technologies\") and TIN2011-23795 (\"WiCMaS: Wireless based Critical Information Management Systems\").  
All authors contributed to the conception of the proposal and defined the methodology. [PERSON] and [PERSON]\(\,\)nete designed and performed the experiments. All authors analysed the results and contributed to write and revise the article.  
The authors declare no conflict of interest.
# Advances in the Synthesis and Physiological Metabolic Regulation of Nicotinamide Mononucleotide
## 3 Biosynthesis of NMN
### Metabolic Engineering for NMN Synthesis
#### 3.2.1 Metabolic Engineering of the NAMPT Pathway  
PRPP, the essential co-substrate for NMN biosynthesis, can be produced through the pentose phosphate pathway, utilizing 5-phosphoribosyl-1-phosphate as an intermediate. Consequently, the multienzyme cascade catalysis method offers a highly efficient and straightforward approach to NMN production [53]. [PERSON] et al. [29] applied NAMPT orthologs from diverse sources for NMN synthesis in _E. coli_ through fermentation. To enhance the supply of PRPP, they co-expressed ribose phosphate pyrophosphokinase (Prs) from _Bacillus amyloidaqueous_, resulting in a remarkable fermentation yield of 15.42 mg/L. [PERSON] et al. [54] constructed three different metabolic pathways for NMN synthesis in _E. coli_, and the results showed that the overexpression of nicotinamide phosphoribosyltransferase (NadV) from _Ralstonia solanacearum_ increased NMN yield 130 times compared with the starting strain, reaching 1.5 mmol/L.  
Through metabolic engineering, the metabolic flux was enhanced to improve the yield of NMN from cost-effective substrates such as glucose, xylose, and ribose [11; 53; 55]. In addition, previous studies reported that native enzymes of _E. coli_ can partially convert the product NMN into nicotinamide and other by-products. Therefore, the knockout of genes related to these pathways in host bacteria can block the conversion of the product and improve substrate utilization. [PERSON] et al. [56] increased the expression of the endogenous _ygcS_ gene in _E. coli_ to enhance carbohydrate uptake simultaneously knocking out genes encoding NMN aminohydrolase (_pncC_) and NMN adenylyltransferase (_nadR_). As a result, the highest yield of NMN was achieved, reaching 496.2 mg/L. The inhibitory effect of high substrate loading on the catalytic performance of the enzyme can be overcome by introducing an NMN transporter [57; 51]. [PERSON] et al. [30] overexpressed the coding genes of seven enzymes in the pentose phosphate pathway (PPP) in _E. coli_ (pgi, zwf, pgl, gnd, rpiA, rpiB, and prs) and identified two functional transporters (NiaP and PnuC). By enhancing the PRPP biosynthesis pathway and improving the transport, the efficient synthesis of NMN from extracellular glucose and nicotinamide was achieved, whereby a high NMN yield of 6.79 g/L was obtained in 8 h, with a substrate conversion rate of 86%. Building on this foundation, [PERSON] et al. [12] employed a comprehensive metabolic engineering strategy, including the elimination of NMN degradation pathways, the selection of an optimal NAMPT enzyme, the introduction of nicotinamide transporters, the optimization of gene expression, and the optimization of culture conditions. Finally, 16.2 g/L NMN was obtained in a 5 L bioreactor.
# Modeling and Control of a DC Motor Coupled to a Non-Rigid Joint
## 2 Proposed Models
### Non-Rigid Joint Model  
For the non-rigid joint construction, a passive system was designed and developed. Applying 4 springs, attached to a circular support part as further represented in Figure 6, a rotational force is applied in the support's centre of rotation, is passed to the next link through the springs, providing elasticity and cushioning to the rotational movement. To connect all the parts, as can be noticeable by the mentioned figure, bearings are applied to decrease the rotational friction, as well as to allow a tighter connection between all the parts.  
The mathematical/physical representation of the system, with its respective constants, velocities and torques present in Figure 1.  
Given the proposed non-rigid joint, its model will become as follow:  
\[\tau_{K}=K\cdot(\theta_{m}-\theta_{j}) \tag{9}\]  
\[\tau_{B}=B\cdot(\dot{\theta}_{m}-\dot{\theta}_{j}) \tag{10}\]  
\[J\cdot\ddot{\theta}=\sum\tau=\tau_{K}+\tau_{B} \tag{11}\]  
\[\frac{d\omega}{dt}=\frac{1}{J}(-K\theta-B\dot{\omega}) \tag{12}\]  
\[J\cdot\frac{d^{2}\theta(t)}{dt}+B\cdot\frac{d\theta(t)}{dt}+K\cdot\theta(t)=0 \tag{13}\]  
\[J\cdot(s^{2}\theta(s)-s\theta(t=0)-\frac{d\theta}{dt}(t=0))+B\cdot(s\theta(s) -\theta(t=0))+K\cdot\theta(s)=0 \tag{14}\]  
Figure 1: Motor Joint Representation.  
Considering that the initial conditions can be not null, the following variables take values:  
\[\theta(t=0)=\theta_{0} \tag{15}\]  
\[\frac{d\theta(t=0)}{dt}=\omega(t=0)=0 \tag{16}\]  
\[Js^{2}\theta(s)-Js\theta_{0}+Bs\theta(s)-B\theta_{0}+K\theta(s)=0 \tag{17}\]  
\[\theta(s)=\frac{\theta_{0}\cdot(Js+B)}{Js^{2}+Bs+K} \tag{18}\]  
\[\theta(s)=\theta_{0}\cdot\frac{(s+\frac{B}{f})}{s^{2}+(\frac{B}{f})s+(\frac{ K}{f})} \tag{19}\]  
Similar to what was described in the above subsection, for modeling the non-rigid joint, as well as for estimating the parameters associated with it, some hardware tests will also be performed, in order to obtain parameters \(J\), \(K\) and \(B\), consisting of:  
* In this test, the link attached to the non-rigid joint is pulled manually for a certain set of increasing angles. For those angles the torque is measured. Then, the link is rotated in the same way to the negative side and the same procedure is applied;
* Through this test, the link attached to the non-rigid joint is pulled manually and, after reaching a determined angle, is released and left to stabilize until it reaches the rest angle. The angular speed, the torque and the angle are sampled with a period of 10 ms;
## 7 Finite Element (FE) Modelling
### Validation of the FE Model  
Experimental results obtained from upright with 1800 mm height for both thicknesses were used to evaluate the validity and accuracy of the numerical model. Figures 21 and 22 show the comparisons between the numerical and test results in terms of load-displacement curves for uprights with 1.6 mm and 2.5 mm thickness, respectively. As indicated in these figures, the developed FE model predicts well the overall load-displacement curve of the specimens. The slight differences between the numerical and the experimental results can be attributed to this point that the load in the actual test could not precisely be applied at the centroid of the section which can cause a different eccentricity compared to numerical inputs.  
Figure 21: Comparison of the finite element (FE) model against the experimental data for 1.6 mm thick uprights.  
Figure 20: (**a**) Full frame meshing, (**b**) meshing around the polygon perforations, and (**c**) meshing around the circular perforations.  
Figure 23 also illustrates the final deformation of uprights for both numerical model and experimental test. Similar to the experimental deformations, the figure shows that the FE method is able to capture the overall behavior of the upright frames.  
Comparing FE and experimental results in terms of the load-displacement curve and deformation contours shows that the FE model is capable of estimating the overall behavior of the upright frame. Therefore, the numerical modelling is reliable enough to undertake a further study for investigating the effects of different reinforcement spacing on the buckling behavior of uprights.
# Hybrid Clustering Algorithm Based on Improved Density Peak Clustering
## 4 Experiments
### Evaluation Metrics  
To effectively gauge and compare the outcomes, we employed several established evaluation metrics to assess the performance of the clustering methodology. These metrics include accuracy (ACC), the Rand index (RI), and the adjusted Rand index (ARI). Accuracy serves as an indicator for measuring the correspondence between the clustering results generated by algorithms and the ground truth clusters. The formulation of this metric is as follows:  
\[ACC(Y,C)=\sum_{i=1}^{n}\delta(y_{i},c_{i})/n \tag{9}\]  
where \(n\) denotes the number of samples, \(y_{i}\) and \(c_{i}\) are the true label and the predicted label of a sample \(x_{i}\), and the \(\delta\) function represents whether \(y_{i}\) and \(c_{i}\) are the same. If they are the same, it is 1, and if they are not the same, it is 0. The adjusted Rand index (ARI) is a metric used to assess clustering results by assuming a generalized hypergeometric distribution as the randomness model. This measure is defined as follows:  
\[ARI(Y,C)=\frac{\sum_{i,j}(\frac{n_{ij}}{2})-\sum_{i}(\frac{n_{i}}{2})\sum_{j}( \frac{n_{j}}{2})/(\frac{n}{2})}{1/2[\sum_{i}(\frac{n_{i}}{2})+\sum_{j}(\frac{n_ {j}}{2})]-\sum_{i}(\frac{n_{i}}{2})\sum_{j}(\frac{n_{j}}{2})/(\frac{n}{2})} \tag{10}\]  
Among these equations, \(Y\) represents the clustering result, and \(C\) represents the true clustering labels. \(n_{ij}\) denotes the number of samples that are in both clusters \(c_{i}\) and \(y_{j}\), while \(n_{i}\) and \(n_{j}\) represent the total number of samples in clusters \(c_{i}\) and \(y_{j}\), respectively. It is important to note that ARI is an adjusted version of RI and is used as an external standard for comparing clustering results. The RI value falls within the range \([0,1]\), whereas the ARI value falls within the range \([-1,1]\).  
\[RandIndex(Y,C)=\frac{(a+b)}{(\frac{n}{2})} \tag{11}\]  
In the formula, \(n\) represents the total number of samples, \(Y\) and \(C\) denote two distinct clustering sets, \(a\) signifies the logarithm of samples belonging to the same cluster in \(Y\) and \(C\), and \(b\) represents the logarithm of samples belonging to different groups (non-similar groups) in \(Y\) and \(C\). It is important to note that the Rand index (RI) falls within the range of 0 to 1. When two sets of clustering results are identical, RI assumes a value of 1, and when the two sets of clustering results are entirely dissimilar, it equals 0.
## 6 Conclusions and Future Work  
VANET enables a next-generation communication network that provides vehicle-to-vehicle communication as well as communication between the vehicle and fixed infrastructure. One of the most important responsibilities of VANET is to provide seamless mobility to vehicles. Host-based mobility management protocols and network-based mobility management protocols for ubiquitous services are two categories of IP-based mobility protocols. According to researchers, host-based management protocols are less effective and efficient than network-based management protocols.  
The PMIPv6 protocol, which is utilized as a localized mobility management protocol for VANET deployment, is the IP mobility management solution that is more compatible and interoperable. However, PMIPv6 does not support inter-domain handover at all; it is primarily intended for quick intra-domain handover. This article proposed an intra-domain and inter-domain handoff for VANET in PMIPv6 with a multicasting approach and analyzed the total cost of inter-domain and intra-domain handover. Various existing mobility management protocols have shortcomings; for example, MIPv6 supports both intra- and inter-domain handoff but suffers from high handover latency, and it does not support Layer 4 handover. Meanwhile, the PMIPv6 protocol minimizes the problem of high latency but does not support inter-domain handoff. In our proposed architecture, we  
Figure 11: Effect of varying unit transmission cost (wireless link) on intra-domain handoff.  
Figure 10: Effect of varying unit transmission cost (wired link) on inter-domain handoff.  
have incorporated an authentication procedure to ensure secure handoff communication, and we have used the concept of multicasting authentication information to various trusted servers responsible for authentication, which permits inter-domain handover for VANET in PMIPv6. A cost comparison between the multicasting approach and the case with no multicasting was performed for parameters such as a different number of MAGs, setup costs required in setting up the initial connection, and unit transmission costs for wired and wireless links. Although the proposed approach is more secure than the ones currently in use, the authentication process may include a slight communication overhead, but it is very negligible. In the future, the formation of multicast groups and/or the placement of network components such as the LMA and MAG in the domain could further lower the signaling cost overhead.  
Conceptualization, A.K.G. and G.A.; methodology, A.K.G.; software, G.A.; validation, A.K.T.; formal analysis, A.K.T.; investigation, M.S.; resources, M.S.; data curation, A.K.G.; writing--review and editing, A.K.G.; visualization, A.K.G.; supervision, G.A.; project administration, M.S.; funding acquisition, M.S. All authors have read and agreed to the published version of the manuscript.  
This work was supported by Dongseo University, via the \"Dongseo Cluster Project\" Research Fund of 2023 (DSU-20230006).  
Not applicable.  
The authors declare no conflict of interest.