esa-sceva/satcom-chunk-collection huggingface dataset:
# Damage Assessment of Shear Wall Structures in an Earthquake-Blast Disaster Chain
## 7 Conclusions  
This paper explored the effect of the earthquake-explosion disaster chain on a shear wall structure and presented a novel damage-assessment methodology. The maximum story drift ratio under an earthquake-explosion disaster chain compared to the maximum story drift ratio when the structural collapse is imminent serves as a new damage index to evaluate the damage levels of the shear wall structures. A 12-story shear wall structure was analyzed numerically to demonstrate the proposed assessment method. The main conclusions are:  
1. The deformation of the floor directly subjected to the explosion load is much greater than that of other floors. For the case in this paper, the deformation of the sixth story of the structure was much higher than the deformation of the first story.
2. The deformations caused by an explosion in the structural system's middle room are much more significant than if the explosion occurs in a corner room.
3. Under earthquake excitation, the damage state of the shear wall structure will be at level 1. After the explosion, the shear wall structure will become severely damaged, reaching level 2 or even level 3.
4. The damage induced by an earthquake-blast disaster chain can be more severe than when only a minor or strong earthquake has occurred. The significant local damage of the explosion to the shear wall structures, especially after being weakened by seismic activity, can lead to structural failure.  
[PERSON] conceived the idea of this research and revised the manuscript, [PERSON] made the calculations and wrote the manuscript, [PERSON] made the calculations, and [PERSON] acquired the funding and supervised this research. All authors have read and agreed to the published version of the manuscript.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Earthquake Record**} & \multicolumn{2}{c}{\(\boldsymbol{\xi_{DR}}\) and DSs} & & & \\ \cline{2-6}  & **Series-I** & **Series-II** & **Series-III** & **Series-IV** & **Series-V** \\ \hline \multirow{2}{*}{Hector Mine} & 0.024 & 0.159 & 0.167 & 0.163 & 0.181 \\  & DS1 & DS2 & DS2 & DS2 & DS1 \\ \multirow{2}{*}{San Fernando} & 0.009 & 0.152 & 0.263 & 0.161 & 0.248 \\  & DS1 & DS2 & DS3 & DS2 & DS3 \\ \multirow{2}{*}{Imperial Valley} & 0.031 & 0.160 & 0.164 & 0.163 & 0.182 \\  & DS1 & DS2 & DS2 & DS2 & DS1 \\ \hline \hline \end{tabular}
\end{table}
Table 13: Damage indexes and damage states of 15 simultaneous major earthquake–blast disaster chains.  
**Funding:** The authors sincerely appreciate the State Key Program of the National Natural Science Foundation of China (grant number 51738007), which supported this research.  
**Conflicts of Interest:** The authors declare no conflict of interest.
## 2 Principle  
### Optical Morse Signal Characterization  
Morse code is a classical encoding scheme in telecommunications composed of a unique sequence of short-long dots, dashes, and spaces to represent different letters of the alphabet, numbers, and procedural notations. It is usually transmitted by on-off radio, light, or tones [18].  
While using light as a transmitting medium, the dots and dashes are represented as high level (light on), and the spaces or pauses refer to low level (light off). In addition, the Morse code depends on accurate time intervals, which correspond to the pulse width in the signal waveform. The duration of a dot is regarded as a basic unit, and the dash duration is three times that. The spaces or time intervals between dot-dashes, between letters, and between words are 1, 3, and 5 units, respectively [19]. As illustrated in Figure 1, it is more like the Return-to-Zero OOK (RZ-OOK) scheme in optical wireless communications. Unlike RF, the optical Morse-encoded signal should be real and non-negative due to the intensity modulation/direct detection (IM/DD) mechanism [20].  
As mentioned above, the recognition is achieved based on the different time intervals and signal amplitude to distinguish different elements. However, the automatic recognition of manually sent Morse light signals in the real world is facing two obvious challenges. One is that the unstable typing pace can lead to variations in different elements durations, and the other is the amplitude fluctuation resulting from ambient light noise.  
Assume the time intervals of dots, dashes, and spaces in unstable Morse light signals are distributed in a nearly normal fashion [21]. Let us denote \(D_{1}\) and \(D_{2}\) as the dot and dash durations samples, respectively; then, the probability density function (PDF) is expressed as  
\[f(D)=\frac{1}{\sqrt{2\pi}}\exp(-\frac{(D-\mu)^{2}}{2\sigma^{2}}), \tag{1}\]  
where \(D_{1}\sim N\left(\mu,\,\sigma^{2}\right)\), \(D_{2}\sim N\left(3\mu,\,\sigma^{2}\right)\), \(\mu\) denotes the means, and \(\sigma\) is the scale parameter. By controlling proper \(\mu\) and \(\sigma^{2}\), it is able to generate manually sent-like Morse light signals based on the Morse encoding rules as the data source to verify the designed algorithm later. A histogram of the distribution of different element durations is shown in Figure 2, and it can be clearly seen that the duration ratio changes. Generally, the durations of different elements in the two figures nearly follow a ratio of 1:3 and 1:3:5:7, respectively. In addition, additive white Gaussian noise (AWGN) is considered to be added to the raw Morse data. Figure 3 plots the signal waveform in the time domain with/without noise. It is observed that the noise will cause amplitude fluctuation, but not affect the duration of different elements. In addition, these duration and amplitude variations can lead to errors for recognition.  
Figure 1: Waveform of optical Morse signal interpreting “SOS.”
# Digital Twin in the Maritime Domain: A Review and Emerging Trends
## 4 Present Digital Twin Manipulations in Marine Industry
### Training and Testing Support  
DT can be incorporated into the training of seafarers in Full Mission Simulators, Part Task Simulators or computer-based training systems. Part Task Simulators often use Hardware In the Loop (HIL) based solutions with real plants operating in parallel with a virtual platform [80]. These platforms can ensure the safety of the personnel (trainers/traines) along with the engagement of critical operations without endangering expensive real-life platforms. DNV-GL is using HIL testing, integration, and optimization of new control systems with a DT-based simulation platform and later goes for actual production with complete runnable executable solutions [55]. Designers and equipment manufacturers will provide and share model parts with the shipbuilder where the complete outfit will be tested, leading to fewer errors and modifications during construction. In their \"Nerves of Steel\" venture, all hydrodynamic data were also simulated in varying sea conditions, leading to an efficient and safe hull design.  
A DT model can be developed to address a specific problem, or it can be harnessed as an open data source ready to be manipulated by human, operational and environmental dimensions of a vessel or any other marine platform. It is a critical asset in enabling future technological advances in data-driven operations. Even producing a surrogate model is also possible using the original DT model, which can mimic the operation with less computational load, achieving the intended efficiency [81].  
Increasing user engagement is another advantage of a DT-based marine system. During the product design, the DT model can be tested to virtually test the interaction between the operator and the physical model [65]. From that, data can be accumulated and processed to reflect the user habits, and the same can be incorporated to improve the physical model with naive innovations. DT acts as a hub for technologies such as Big Data Analytics, IoT, machine learning, simulation, modelling, etc., providing a gateway to achieve much more complex analytical power to the operators and developers with the sensing data of the actual physical model contrasted with simulation data and Machine Learning algorithms.
# A Novel Security Architecture for WSN-Based Applications in Smart Grid
###### Abstract  
The Smart Grid (SG) aims to cope with the problems of the traditional grid, using renewable power generators. Similarly, SG benefits from the deployment of wireless sensor networks (WSNs) to enhance its aspects by monitoring the physical behavior of the power generators. However, new threats and attacks may arise due to the open nature and large scale of SG where WSNs are deployed. In this paper, we propose a new security architecture for WSNs in SG based on public key infrastructure (PKI). The key idea of the proposed architecture is to distribute the role of the certification authority (CA) among a set of sensor nodes to ensure the availability and scalability of the CA services. To elect this set of sensor nodes, we propose a novel lightweight clustering algorithm for WSNs that relies on the trust metrics of the nodes and their energy levels. The proposed architecture provides many security services such as authentication and confidentiality and mitigates many types of attacks such as Sybil and eavesdropping. Extensive simulations have been conducted using network simulator OMNET++ and Castalia framework to investigate the performance of the clustering algorithm. The results show that almost 100% of the sensors are members of clusters, and even in the presence of malicious nodes, the number of cluster heads remains static which reflects the robustness of the proposed architecture.  
Smart Grid (SG); wireless sensor networks (WSNs); public key infrastructure (PKI); clustering: certification authority (CA) 20225633-649.
# Advances and Challenges of Corrosion and Topology Detection of Grounding Grid
## 3 Grounding Network Topology Detection Method
### Magnetic Field Excitation Method  
The magnetic field excitation method excites the grounded flat steel through the coil to generate the eddy current field (the secondary field), and the topology of the grounding network is obtained by detecting the eddy current field. The transient electromagnetic method [46] measures the net secondary field, and it has high detection accuracy. The topography of the grounding grid can be visually obtained using the apparent resistivity imaging technology, and the image is intuitive, but it has a large amount of calculation. In addition, the topology of the grounding grid can be obtained by analyzing the amplitude characteristic of the magnetic field which generated by the sinusoidal current. The method is simple in measurement and small in calculation, but the background field is included in the measurement result of the method, so the detection accuracy is relatively low.
# Scheduling Sparse LEO Satellite Transmissions for Remote Water Level Monitoring
## 2 Materials and Methods
### Efficient Packet Data Bundling  
Note that there are a few important functions in Figure 5, such as the data bundling, as the transmission duration directly causes energy consumption. Table 3 shows the format of data. Each datum includes a timestamp, expressed in minutes since 1 January 1970. Due to the nature of the GNSS-IR, we omit seconds, which allows the re-purposing of 4 bits for 16 status codes. For completeness, using 28 bits allows timekeeping for 510 years. This format allows the whole datum to fit in 16 bytes, which divides evenly into 192 bytes per packet, such that each packet will be maximally utilized with 12 data points per packet.  
\begin{table}
\begin{tabular}{l l} \hline \hline
**Background Noise RSSI (dBm)** & **Quality (for Transmission)** \\ \hline \(-90\) and higher & Bad (unlikely to work) \\ \(-93\) and lower & Marginal \\ \(-97\) and lower & OK \\ \(-100\) and lower & Good \\ \(-105\) and lower & Great \\ \hline \hline \end{tabular}
\end{table}
Table 2: Background noise intensity required for likelihood of transmission.  
\begin{table}
\begin{tabular}{l l l} \hline \hline
**Name** & **Type** & **Bits** \\ \hline Water level & Floating-point & 32 bits (4 bytes) \\ Error & Floating-point & 32 bits (4 bytes) \\ Roughness & Floating-point & 32 bits (4 bytes) \\ Minutes since 1 January 1970 & Positive integer & 28 bits (<4 bytes) \\ Status & Positive integer & 4 bits (<1 byte) \\ \hline Total & & 128 bits (16 bytes) \\ \hline \hline \end{tabular}
\end{table}
Table 3: Format for each datum within the software.  
Second implicit function within the high-level processes shown in Figure 5 is that of good satellite pass selection, while the algorithm for actually predicting satellite passes--at least from the user perspective--is made fairly simple with the help of an open-source SGP4 satellite pass prediction Arduino library, quantifying what satellite passes are \"good\" depends much on environmental conditions, setup details, and empirical observations, as described next.
## 2 Materials and Methods  
### Dual Quaternion Rule  
Quaternions are fourth-order hypercomplex numbers often used to describe changes in four-dimensional hyperplanes and vectors in graphics. Quaternions are generally represented in the form \(a+bi+cj+dk\), where \(a,b,c\), and d are real numbers, and \(i,j\), and \(k\) are basic quaternions. Quaternions can be composed of a scalar part and a vector part. \(q\) is a quaternion represented as \(q=(r,v)\), where r is a scalar defined in the real number field, and \(v\) is a three-dimensional vector. \(q^{*}\) is the conjugate of \(q\), represented by \(q^{*}=(r,-v)\). \(q_{1}\) and \(q_{2}\) are two quaternions. The result and outer product of those are shown in Equations (1) and (2). The product of two quaternions is called the Grassmann product and is denoted by the symbol \(\otimes\).  
\[(r_{1},\mathbf{v}_{1})+(r_{2},\mathbf{v_{2}})=(r_{1}+r_{2},\mathbf{v}_{1}+\mathbf{v_{2}}) \tag{1}\]  
\[(r_{1},\mathbf{v}_{1})(r_{2},\mathbf{v_{2}})=(r_{1}r_{2}-\mathbf{v}_{1}\cdot\mathbf{v_{2}},r_{1} \mathbf{v_{2}}+r_{2}\mathbf{v}_{1}+\mathbf{v}_{1}\times\mathbf{v_{2}}) \tag{2}\]  
The dual numbers are a system of hypercomplex numbers, which are expressions of the form \(c+d\varepsilon\), where \(c\) and \(d\) are real numbers, and \(\varepsilon\) is a symbol taken to satisfy. When \(c\) and \(d\) are replaced by quaternions using real numbers, the dual numbers are called dual quaternions. A dual quaternion can be represented in the form of \(\hat{\mathbf{q}}\), which can be written as \(\hat{\mathbf{q}}=\mathbf{q}_{r}+\varepsilon\mathbf{q}_{d}\). Among them, \(\mathbf{q}_{r}\) and \(\mathbf{q}_{d}\) are two quaternions, respectively, referred to as the imaginary and real parts of dual quaternions. \(\hat{\mathbf{q}}^{*}\) represents the dual quaternion conjugate, as shown in Equation (3).  
\[\hat{\mathbf{q}}^{*}=\mathbf{q}_{r}^{*}+\varepsilon\mathbf{q}_{d}^{*} \tag{3}\]
## 4 The WBANs Communication Stack
### Medium Access Control Layer
#### 4.2.3 Existing State-of-the-Art on the MAC Protocols
Average packet loss rate (PLR), delay and throughput were evaluated through simulations. The performance achieved with the different data rates available at the 2.45 GHz band was analyzed and a comparison with a network based on IEEE 802.15.4 standard was carried out. The results point out the impact of different channel models on the network performance, underlying the importance of the choice of the proper model for every specific scenario. Then, the comparison between the two standards showed that, for very small payloads, 802.15.4 performs better than 802.15.6 in terms of PLR, while for longer payloads 802.15.6 achieves lower PLRs. As for the delay, the values obtained for 802.15.4 are in general lower than the ones obtained for 802.15.6. Therefore, depending on the application requirements, 802.15.4 could be more suitable in some cases than 802.15.6. Anyway, in this first evaluation, for a fair comparison between the two standards, they considered only the CSMA/CA access method and they set the same user priority for all the nodes. The possibility to choose also the slotted Aloha and to set different priorities for the various applications makes IEEE 802.15.6 standard more complex, but at the same time more flexible to meet the diverse requirements of WBANs, and its performance has to be further investigated.
# Anthropometric Profiles in Table Tennis Players: Analysis of Sex, Age, and Ranking
## 1 Introduction  
Physical demands and technical skills in racket sports such as table tennis are dependent on the anthropometric and body type characteristics [1, 2]. An optimal body composition for a given racket sport discipline is essential to develop a successful sportive career [3, 4, 5]. Furthermore, anthropometric and body composition attributes play an important role in the identification of talent in racket sports [6, 7] and particularly in table tennis [8, 9]. Since body composition is modifiable by practice, a number of studies have sought to describe skeletal and morphological changes as a result of training in differentsports disciplines and stages of maturation [10; 11; 12]. However, information about how body type differs throughout formative stages in table tennis and its influence on performance is very limited.  
Table tennis has recently evolved towards a highly demanding sport increasing match-play intensity and the speed of actions [13; 14]. As a result, there is an increasing interest in examining to what extent modern table tennis has altered young and senior players' skills, morphology, and conditioning [5; 15; 16; 17; 18; 19]. Nonetheless, researchers have failed to yield conclusive results due to insufficient sample size, heterogeneity of players' level, lack of women's data, and the absence of performance outcomes to make comparisons [20]. Thus, a comprehensive knowledge of anthropometric and biotype profiles in modern table tennis players is lacking. Specifically, data about young players between 10 and 17 years old are alarmingly scarce [15].  
Recent studies have examine the benefits of strength training in elite and high-level table tennis players [16; 21]. Specifically, eight-week ballistic and power training increased upper and lower muscles strength, endurance, and agility but were not effective in changing body composition [16]. However, the fact that body composition was unaltered is not necessarily a negative result, given that these players possibly already had an optimal biotype to perform highly in table tennis. Thus, further data on body composition and somatotype in men and women table tennis players from a range of ages are required to assist coaches and researchers in interpreting their results. Likewise, information about the existing (or not) relationship between body composition and performance ranking position will help in making better decisions accordingly.  
In order to fill this gap in the literature, the aim of this study was to determine the differences in anthropometric attributes of table tennis players according to sex, age, and ranking. Based on previous studies, we hypothesized that high-level table tennis players would showed a similar somatotype, being predominantly mesomorphic in men [17; 19; 22] and endomorphic in women [17; 22]. Likewise, although the relationship between ranking position and body composition has not been fully examined, earlier studies suggested that body constitution might not be a crucial factor in achieving top results in table tennis [19].
## 3 Results and Discussion  
### Synthesis and Structural Characterization  
PPM-based copolymers containing \(n\)-octyloxy side chains were obtained by mixing the comonomers benzyl chloride and 4-octyloxybenzyl chloride at two ratios, 5.3% mol/mol and 11.2% mol/mol, respectively, and polymerization was subsequently carried out under the conditions reported in the Materials and Methods section. For both ratios the number-average molar masses of the resulting copolymers (M\({}_{\rm n}\)) amounted to about 2500 g mol\({}^{-1}\) and the weight-average molar masses (M\({}_{\rm w}\)) to about 5400 g mol\({}^{-1}\), resulting in polydispersity indices (PDI= M\({}_{\rm w}\)/M\({}_{\rm n}\)) of about 2.2-2.3 (Table 1). Notably, the fluorescence observed for PPM itself also emerged in the copolymers (Figure 2).  
The presence of octyloxy groups in the copolymers was assessed with \({}^{1}\)H NMR spectroscopy. With regard to the reported values of PPM [18; 19], \({}^{1}\)H NMR spectra of the copolymers showed the aromatic resonances (H\({}_{\rm Ar}\)) in the typical region of 6.8-7.2 ppm. The position of the bridging methylene signals (H\({}_{\rm m}\)) at 3.9 ppm differed from that of the corresponding signals of the CH\({}_{2}\)Cl group of the comonomers at 4.5 ppm (Figure 3). Notably, the presence of the signals corresponding to the alkoxy chains (H\({}_{\rm AIK}\)) in the region of 0.5-1.5 ppm confirms the inclusion of octyloxy side chains into the polymers. Furthermore, the ratio between integrated peak areas of alkyl signals (H\({}_{\rm AIK}\)) and those of the methylene bridges (H\({}_{\rm m}\)) were used to calculate the effective molar composition of the copolymers. The obtained values  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Sample** & **Mn (g mol\({}^{-1}\))** & **Mw (g mol\({}^{-1}\))** & **PDI (Mw/Mn)** \\ \hline
6.1\% octyloxy units & 2438 & 5402 & 2.21 \\
13.4\% octyloxy units & 2382 & 5496 & 2.3 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Molar masses of copolymers prepared from benzyl chloride and 4-octylbenzyl chloride (6.1% mol/mol and 13.4% mol/mol).  
Figure 2: Photographs taken under UV-light illumination of PPM and its derivatives solutions in chloroform (\(\approx\)0.5% m/m, 2 cm diameter of the vials): PPM (left), copolymer containing 13.4% (center) and 6.1% (right).  
showed somewhat higher molar ratios of constitutional repeat units of the octyloxy groups (13.4% and 6.1%) than the comonomer ratio employed for the reaction (11.2% and 5.3% respectively). Obviously, polymers with a higher fraction of unsubstituted phenylene methylene units were removed during sample workup with somewhat higher preference.