esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Materials and Methods
### GC-MS and GC-FID Analysis  
The GC-MS and GC-FID analysis were carried out for qualitative and quantitative purposes, respectively.  
GC-MS analyses were carried out on a GC-QP2010 system (Shimadzu, Kyoto, Japan). For the separation, an SLB-5 ms fused-silica capillary column (30 m \(\times\) 0.25 mm _i.d._\(\times\) 0.25 \(\upmu\)_d._) (29804-U) (Merck Life Science, Merck KGaA, Darmstadt, Germany) was applied. Helium was used as carrier gas at a constant linear velocity of 30.0 cm/s, which corresponded to an inlet pressure of 24.2 kPa. The temperature program was the following: 40 \({}^{\circ}\)C held for 1 min to 350 \({}^{\circ}\)C at 3 \({}^{\circ}\)C/min, held for 5 min. The interface and ion source temperatures were 250 and 200 \({}^{\circ}\)C, respectively. The acquisition was made in full scan mode in the mass range of 40-500 \(m\)/z, with a scanning rate interval of 0.2 s. Data handling was supported by GCMS solution ver. 4.30 software (Shimadzu, Kyoto, Japan). For the characterization, the following databases were used: W11N17 (Wiley11-NistI7, Wiley, Hoboken, NJ, USA, and FFNSC 4.0 (Shimadzu, Kyoto, Japan). The identification was performed applying two filters, namely spectral similarity match over 85% and linear retention index (LRI) match calculated using a C7-C40 saturated _n_-alkane homologue series with a filter window of \(\pm\)10 LRI units.  
GC-FID analyses were carried out on a GC2010 system (Shimadzu, Kyoto, Japan). Owen temperature program and injection parameters were the same as for MS applications. Helium was used as carrier gas, at a constant linear velocity of 30.0 cm/s, which corresponded to an inlet pressure of 97.4 kPa. The injector temperature was set at 260 \({}^{\circ}\)C. The FID temperature was set at 280 \({}^{\circ}\)C (sampling rate 200 ms), hydrogen and air flows were 40 and 400 mL/min, respectively. Data were collected by LabSolution software ver. 5.92 (Shimadzu, Kyoto, Japan). Quantitative results were determined as peak area percentage without any correction. Samples were analyzed in triplicates.
# Recent Progress in Fast Distributed Brillouin Optical Fiber Sensing
###### Abstract  
Brillouin-based optical fiber sensing has been regarded as a good distributed measurement tool for the modern large geometrical structure and the industrial facilities because it can demodulate the distributed environment information (e.g., temperature and strain) along the sensing fiber. Brillouin optical time domain analysis (BOTDA), which is an excellent and attractive scheme, has been widely developed thanks to its high performance in a signal-to-noise ratio, a spatial resolution, and sensing distance. However, the sampling rate of the classical BOTDA is severely limited by several factors (especially the serially frequency-sweeping process) so that it cannot be suitable for the quickly distributed measurement. In this work, we summarize some promising breakthroughs about the fast BOTDA, which can be named as an optical frequency comb technique, an optical frequency-agile technique, a slope-assisted technique, and an optical chirp chain technique.  
fiber optics sensors; nonlinear optics, fibers; scattering; stimulated Brillouin +
Footnote †: journal: Applied Sciences  
1
# Phenolic and Volatile Composition of a Dry Spearmint (_Mentha spicata_ L.) Extract
## Results and Discussion
### Characterisation of Volatile Composition
This can be attributed to the fact that the chemical composition of mint leaves, as the composition of essential oil, can be dependent on different agronomical factors as plant maturity, variety, growth region, climatic conditions, and genetics [3]. In contrast, other typical spearmint volatile fraction components, such as menthone, carvone, eugenol, piperitone, and isopiperitone, were detected. These volatiles have been already reported in peppermint and spearmint essential oils as being responsible for the typical mint notes [45; 46]. Carvone and piperitone are two oxygenated terpenoids generated during the biosynthesis of terpen, which starts from geranyl pyrophosphate, and they are derived from d-limonene. In particular, carvone, with its characteristic aromatic note of mint and liquorice, has different applications, such as repellent, medical, and flavour preparation [5]. However, the carvone level recorded in the spearmint extract is 200-fold lower than that previously reported in an aqueous extract of peppermint (~0.2 vs. 40 \(\upmu\)g/100 mg extract), another member of the Lamiaceae family [47]. This low carvone level, in agreement with [PERSON] et al. [11], may cause lesser mint notes in this line relative to native spearmint lines, which could support its palatability in food and beverage applications. Among ketones, the most abundant were menthone (2.18 \(\pm\) 0.72 \(\upmu\)g/100 mg) and \(\beta\)-damascenone (0.66 \(\pm\) 0.17 \(\upmu\)g/100 mg), which were consistent with results found by [PERSON] et al. [46] and [PERSON] et al. [37] for spearmint and peppermint. The spearmint volatile fraction was also rich in alcohols. In addition to the _p_-cymen-8-ol (1.96 \(\pm\) 0.74 \(\upmu\)g/100 mg) as identified in _Mentha_ essential oils [4], detectable amounts of 2-acetyl-4-methylphenol, thymol, carvacrol, and _p_-menthen-1-ol were also observed. In addition to ketones, terpenoids, and alcohols, several compounds belonging to different chemical classes represented the remaining 18%-19% of the volatile fraction of the dried spearmint powder. Among these minor volatile compounds, dihydroudelman II (two signals: 2.27 \(\pm\) 0.66 and 0.69 \(\pm\) 0.09 \(\upmu\)g/100 mg) was identified. Dihydroedulan II is a benzopyran compound that has already been detected in the essential oil of _Ocimum basilicum_ (basil), another member of the Lamiaceae family [48] but not previously reported in _Mentha spicata_. In accordance with data from [PERSON] [46] in peppermint, detectable amounts of _R_-(+)-menthofuran (0.16 \(\pm\) 0.05 \(\upmu\)g/100 mg) were observed. Slight quantities of aldehydes, in particular furfurral (0.52 \(\pm\) 0.12 \(\upmu\)g/100 mg) and 5-methyl furfural (0.18 \(\pm\) 0.03 \(\upmu\)g/100 mg), were also detected. Similarly, [PERSON] et al. [37] identified these compounds in distilled extracts from some medicinal plants, such as _Angelica tenuissimae_, pine needles from _Pinus sylvestris_, and leaves of sweet flags (_Acorus gramineus_).
## 3 Demand-Side Resources in Active Distribution Systems
### Protocols in Active Distribution Systems  
The electrical industry employs open protocols, which were created in the 1990s, to manage SCADA systems over great distances. It was created to provide extra services via Ethernet TCP/IP (Transport Control Protocol)/ (Internet Protocol) networks and Master/Slave serial communication (RS232, RS485) networks. It is built on four layers:  
Figure 3: Data rate, coverage distance, and power consumption for various protocols [53].  
application, pseudo transport, data link, and physical layer. The system consists of a master terminal unit (MTU), a remote terminal unit (RTU), and IED (Intelligent Electronic Devices) [54]. There are two main categories of communication technologies for the active distribution network: wired and wireless. In terms of dependability, security, and bandwidth, wired technologies are frequently seen as being preferable to wireless ones. In contrast to wireless communication solutions, wired solutions do not rely on batteries and do not have any interference problems. However, wireless communication systems allow for flexible deployments with little cabling and inexpensive installation costs, enabling connectivity to be offered over vast areas or in places where there is no existing communication infrastructure [1]. Due to this, depending on the intended applications and functionality, each of these communication technologies has benefits and drawbacks that must be taken into account. Smart grid communication is based on the IEC61850 standard [55], which provides specifications for the design and operation of those intelligent grids [56]. Before we critically evaluate the IEC61850 standard, we look at other standards necessary for communications in ADNs.
# Routing Strategies for Isochronal-Evolution Random Matching Network
### Related Works on Models for Real-World Networks  
Researchers have tried to build mathematical models for various types of real-world networks [11]. In [12], a model of face-to-face interaction networks was developed. In [13], a method was used to generate static networks with edge dynamics. In [14], an activity-driven model of time-varying networks was proposed. In [15], a more statistics-oriented model of communication in social networks was put forward. In [16], a model where both nodes and links are activated by temporal effects was proposed. In [17], a temporal network of the Chinese venture capital market was studied. However, these network models are not suitable for the modeling of a network that evolves isochronally and has a collection of edges that are pairwise disjoint at any time; the reasons for this are as follows.  
1. These models do not consider cases where the edges of the aforementioned network are pairwise disjoint at any time.
2. The lifetime of each edge of the aforementioned network may not be continuous and follow a certain probability distribution, which does not meet the conditions of these models.
3. The time scale of the aforementioned network is different from those of these models, because the aforementioned network pays more attention to the value of all slots than to the duration of a slot.  
Therefore, we studied how to abstract away a network model from the aforementioned network and investigate it. To the best of the authors' knowledge, this is the first time that a new complex network model has been proposed to represent NSNs. It is also the first time that a study has focused on the fact that the edges of an MCN are pairwise disjoint at any time.
# _meta.shrinkage_: An R Package for Meta-Analyses for Simultaneously Estimating Individual Means
## 2 Background  
### Meta-Analysis  
This subsection reviews the basic concepts for meta-analysis.  
To clarify the concepts, we introduce some notations and assumptions for a meta-analysis. Define \(G\) as the number of studies, where \(G\) stands for groups in the meta-analysis. For each \(i=1,2,\ldots,G\), let \(Y_{i}\) be an estimator for a target estimand \(\mu_{i}\) that is unknown. Let \(y_{i}\) be a realized value of the random variable \(Y_{i}\). We assume that the error is normally distributed so that \(Y_{i}\sim N\left(\mu_{i},\sigma_{i}^{2}\right)\), where \(\sigma_{i}^{2}>0\) is a known variance for the error distribution. Thus, \(\mu_{i}\) is the mean of \(Y_{i}\). The observed data are \(\{y_{i}:\ i=1,2,\ldots,G\}\) in this meta-analysis. We will not consider a setting where the variance is unknown [21; 22], as this setting does not follow the framework of meta-analyses based on \"summary data\". Without a loss of generality, we assume that \(\mu_{i}=0\) corresponds to the null value.  
Traditionally, the objective of meta-analyses is to estimate the common mean, denoted as \(\mu\). It is defined by the fixed effect model assumption of \(\mu\equiv\mu_{1}=\ldots=\mu_{G}\) or the random-effects model assumption of \(\mu_{i}\sim N(\mu,\tau^{2})\) for \(i=1,2,\ldots,G\), where \(\tau^{2}\) is the between-study variance. In this article, we assume neither, since the aforementioned models do not always fit the data at hand. For instance, if the studies have _ordered means_ (e.g., \(\mu_{1}\leq\ldots\leq\mu_{G}\)), the model is neither fixed nor random [20]. Indeed, many real meta-analyses have some covariates to systematically explain the reason for increasing means \(\mu_{1}\leq\ldots\leq\mu_{G}\) or decreasing means \(\mu_{1}\geq\ldots\geq\mu_{G}\) (see Section 5). In such circumstances, there is no general way to define the common mean \(\mu\). Below, we discuss what meta-analyses can do in the absence of the common mean.
## 4 Simulation Results
### Comparison of the Network Lifetime  
As a visual evaluation standard reflecting the performance of clustering routing protocols, the network lifetime refers to the live nodes in the network with the iteration rounds. The steady lifetime refers to the number of rounds until the first node death. In a steady lifetime, the nodes in the network are full of energy and can perform large-scale data communication. This lifetime is the most vigorous moment of the WSN's vitality. As shown in Figure 15, the steady lifetimes of the LEACH, DEEC, and GSEN are 1061, 1135, and 1163 rounds, respectively, and the steady lifetime of the EECRP-HQSND is 1331, which further exceeds LEACH, DEEC, and GSEN by 25.45%, 17.27%, and 14.45%, respectively. In addition, through a reasonable ICRM, the EECRP-HQSND-ICRM extends the steady lifetime by 33 rounds compared to the EECRP-HQSND. With the iteration rounds, there are few nodes in LEACH and DEEC around the 1300 th round. At this time, there is no node death in EECRP-HQSND or EECRP-HQSND-ICRM. After around the 1356 th round, the number of nodes in EECRP-HQSND is almost 0, but EECRP-HQSND-ICRM still maintains 91. So, we find that ICRM can reduce the network energy consumption well. In addition, in terms of the downward trend of the curves of the live nodes, it is obvious that compared with LEACH, DEEC, and GSEN, after the death of the first node, the slopes of EECRP-HQSND and EECRP-HQSND-ICRM change the fastest, and the slopes can almost reach negative infinity. Thus we find that compared with the traditional CH selection mechanisms, CH selection through partition based on the uniformity of the CH distribution in this paper can balance the network energy consumption well.
# Two Designs of Automatic Embedded System Energy Consumption Measuring Platforms Using GPIO
## 3 Methodology and Data Acquisition
### Timestamp and Data Synchronization  
For the hardware design and code optimization, it is necessary to understand the energy consumption corresponding to the code, which requires the power consumption data to be synchronized with the execution status of the code segments. However, the code is executed on the embedded system and the power consumption data are measured and collected outside the embedded system; therefore, there is no common time baseline between them. GPOS like Windows or Linux do not guarantee real time. Therefore, we decided to use the intermediate device to handle the timestamp and the power consumption data. Figure 2 shows how the timestamps and power consumption data are synchronized.  
Figure 1: Time sequence demonstrating how the intermediate device logs timestamps via GPIO.  
The upper half represents the embedded system being measured, wherein the code is run and the GPIO level changes are produced. The lower half represents the intermediate device, which collects the power consumption data continuously and uses interrupt service routing (ISR) to respond to GPIO level changes and to record timestamps. In this way, the power consumption data and the timestamp share a common time baseline. Because the intermediate device runs an RTOS, the accuracy of the timestamps is also guaranteed.
# Secure Aviation Control through a Streamlined ADS-B Perception System
## 4 Methodology
### Feature Selection  
The dataset consists of 18 features; they characterize what a typical ADS-B message contains and give more details and understanding of its structure. Table 5 introduces the features and briefly defines what the values represent. We omitted two features in this section (icao24 and callsign); the reason was that these attributes are strings that correlate to the aircraft type, and such information has no impact on detecting or classifying an injected message. Moreover, it could aid with decreasing the margin of error caused by encoding those strings into numerical values before testing.
## 4 ROLQ-TEE Scheme
### Threat Model  
We construct the ROLQ-TEE scheme based on the following assumptions regarding its threat model. We assume that attackers are computationally bounded and unable to break standard cryptographic assumptions, meaning they cannot compromise the hardware security of the TEE. This ensures that the TEE protects the predefined code and data contained within it. In addition, \(\mathcal{DO}\), \(\mathcal{RU}\), and TEE are trusted, and \(\mathcal{CSP}\) without TEE is honest and curious. This implies that the cloud service provider honestly executes all algorithm instructions. Meanwhile, the \(\mathcal{CSP}\) may exhibit curiosity about the sensitive information contained in the stored encrypted data and might attempt to learn additional sensitive information through RNN queries. To prevent the leakage of sensitive information, the \(\mathcal{DO}\) store only ciphertexts of their location data on the \(\mathcal{CSP}\), while the \(\mathcal{DU}\) submit encrypted forms of their RNN queries (i.e., query tokens) to the \(\mathcal{CSP}\). Additionally, the \(\mathcal{CSP}\) may exhibit curiosity about the query results of the \(\mathcal{DU}\), making it essential to assume the absence of collusion between the \(\mathcal{DO}\) and the \(\mathcal{CSP}\). In summary, our ROLQ-TEE scheme is considered to be secure, meaning that the following security requirements should be met simultaneously.  
Figure 3: System architecture.  
Data privacy: Data privacy means that the outsourced location data, query tokens, customer lists, and query results cannot be broken by the adversary.
* Revocation security: The data users whose access has been revoked are unable to initiate new optimal location queries and are also prevented from decrypting any ciphertext data associated with subsequent queries.
* Data anonymity: The data users cannot utilize the obtained information to infer the locations stored in the database of the data owner, other than the intersection location data.
## 3 Proposed Approach
### Network Layer Attacks and Countermeasures
* By utilizing machine learning, normal traffic patterns can be studied and understood, enabling the system to automatically detect and alert administrators when abnormal traffic occurs. This approach helps to prevent social engineering attacks or insider threats that exploit network vulnerabilities, providing a more proactive and intelligent defense against potential security breaches. By applying these security measures, the network layer can be significantly strengthened to resist cyberattacks, protecting critical infrastructure from potential disruptions.
## 5 Performance Evaluation  
### Simulation Environments and Parameters  
In the simulation, to provide more insight into the proposed routing protocol and clustering, we compared the performance of the HPA-SR protocol with AODV routing protocol. The simulation environments and parameters are presented in Table 4. In particular, we deployed 30, 50, and 100 nodes moving over an area of size 1000 \(\times\) 1000 m\({}^{2}\) in urban scenario. In this case, mobile nodes move according to the group mobility. The nodes are divided into groups, and several groups will move in the same direction. The groups will build their movements based on the group leader's movement [45]. The initial position of nodes is randomly distributed along the street and moves with different speeds (20 km/h, 40 km/h, 60 km/h, and 80 km/h) [46]. The MAC layer is modeled using the IEEE 802.11 standard, and using the received signal strength indicator (RSSI) threshold is \(-80\) dBm for communication range to more practically. One of the reasons for considering the use of RSSI is that the value of fluctuations in RSSI obtained has taken into account its effect on changes in channel conditions including multi-path fading [47]. All the simulation experiments are carried out on the NS3 simulator.
## 4 BPSK FDA System Design  
### Linear Array Length Selection  
The number of elements of the FDA with linearly progressive frequency offsets is inversely related to the mainbeam width (see Figures 5 and 6 in [6] for a comparison), which relates to the coherency window of the baseband waveform in our single channel receiver. Thus, we model the down conversion process by bringing Equations (2) and (3) to baseband as follows:  
\[\begin{split} F_{bb}(t;R,\theta)&=\bigg{[}\sum_{n= 0}^{N-1}e^{2\pi f_{n}(t-R_{n}/c)}\bigg{]}\cdot e^{-2\pi f_{0}t}\\ &=\sum_{n=0}^{N-1}e^{2\pi n\Delta f(t-R_{n}/c)}\cdot e^{-2\pi f_{ 0}R_{n}/c}\end{split} \tag{4}\]  
and  
\[\begin{split} F_{bb,B}(t;R,\theta)&=B(t)\bigg{[} \sum_{n=0}^{N-1}e^{2\pi f_{n}(t-R_{n}/c)}\bigg{]}\cdot e^{-2\pi f_{0}t}\\ &=B(t)\sum_{n=0}^{N-1}e^{2\pi n\Delta f(t-R_{n}/c)}\cdot e^{-2 \pi f_{0}R_{n}/c}.\end{split} \tag{5}\]  
We then plot the real component of Equation (4) with \(N=2\) and \(N=4\) elements, where \(f_{0}=720\) MHz and \(\Delta f=10\) kHz in Figure 2 at a nominal point in the far-field \((R,\theta)=(10\) m,\(0^{\circ})\).  
By comparing the waveforms in Figure 2, we notice that the baseband waveform from the \(N=2\) element FDA has a much wider mainbeam temporal window within which data can be modulated, as well as a simpler baseband behavior, and the \(N=4\) element FDA produces a narrower beam with a tighter coherency window. This highlights a design  
Figure 1: Schematic of a uniform linear FDA.  
trade-off between the mainbeam coherency window and mainbeam width with increasing linear FDA size.  
Due to host PC limitations, we set our BPSK chip rate to \(T_{c}=1\) us, yielding 10 samples per chip for the receiver with a receive sample rate of \(f_{s}=10\) MHz. Thus, we select the \(N=2\) array length for the longer coherency window, which allows for more bits per transmission pulse.
## 2 System Design  
### System Architecture  
This study proposes an impact-echo detection system that automatically oscillates and rapidly processes data. In terms of the system's architecture, the hardware comprises an automatic oscillation impact device our lab designed for this study, and adjustable automatic oscillator circuits, while the software features an echo signal acquisition and structural anomaly analysis. The overall system framework is presented in Figure 1.  
Figure 1: The overall system architecture.
###### Abstract
The primary objective of this paper is to explore how the thickness of the composite laminate can affect the propagation properties of embedded UGWs. By comparing the results obtained using surface-mounted PZT transducers from the author's previous work, the researchers aim to assess the impact of thickness on the reliability of damage localization. The study starts by employing active sensing techniques to analyze the guided wave propagation through composite panels with thicknesses of 2 mm, 4 mm, and 9 mm. This analysis considers how temperature variations impact the propagation behavior of UGWs within the composite panels. Finally, the paper focuses on damage detection and localization. The study aims to enhance our understanding of how thickness influences these factors, ultimately contributing to the advancement of structural health monitoring techniques for composite structures.