esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Discussion
### Between-Group Analysis  
Examination of the significant differences of the HR among the groups in each measurement condition shows that the median HR in each measurement condition and also at rest without headphones, was on average about 10 bpm higher in young adults than in older adults (without PD). The median HR of the PD adults was an intermediate between these two groups, but was also below the HR of the younger adults (Figure 1). The significant difference between the older adults and the PD patients for the modulated noise, 117 bpm, is rather negligible on the basis of identical medians. Therefore, young adults tend to have a slightly higher HR than older people (groups EA and PD) and, thus, the differences found cannot be associated with listening to music or sounds.  
The finding that exciting music, such as heavy metal music, is associated with a higher HR than soothing music [13], cannot be confirmed in the context of this study for any of the groups. In addition, we could not demonstrate evidence for a coupling of the heart rate to the musical beats. However, [PERSON]'s statement [10] can be confirmed by our study, i.e., that when arousal is balanced by different music, there are no changes in the HR with the time differences of the music (90 vs. 120 bpm). Likewise, there was no integration of the HR with the musical beats, confirming the finding of [PERSON] and [PERSON] [31]. Contrary to the results of [PERSON] et al. [9], there was no evidence of increased heart rate with \"unpleasant stimuli\" (such as pink noise or continuous noise at 117, 139 or 174 bpm) or with \"silence\" versus \"pleasant stimuli\" (musical songs).  
The correlation between resting pulse rate, age and sex of 92,457 adults [32] showed that the resting pulse rate increases until about the age of 50 years and then decreases regardless of sex. Thus, the present differences observed in our study, between group TA and groups EA and PD, cannot be explained by the present age differences alone. However, EA did include an increased proportion of men. However, the difference in the number of sexes has not been shown to have any significant interaction effect.  
The potential reason for the decreasing heart rate with increasing age might be on the basis of a reduced left ventricular compliance due to an increase in the collagen content and the associated decrease in water content leading to fibrosis [20; 33]. Changes in the conduction system itself may also play a role [20; 33]. With decreasing pacemaker cells and increasing fatty infiltration a loss of specialized fibers results and, thus, an intrinsic decrease in sinus automatism. In addition, dynamic histochemical and immunohistochemical changes during the aging process appear to have an impact on the autonomic responses associated with the decrease in heart rate in the elderly [34; 35]. Furthermore, it should be taken into account that possible effects due to medication (e.g., L-dopa) in PD patients could have biased the results.
# Data Collection in Areas without Infrastructure Using LoRa Technology and a Quadrotor
###### Abstract  
The use of sensor networks in monitoring applications has increased; they are useful in security, environmental, and health applications, among others. These networks usually transmit data through short-range stations, which makes them attractive for incorporation into applications and devices for use in places without access to satellite or mobile signals, for example, forests, seas, and jungles. To this end, unmanned aerial vehicles (UAVs) have attractive characteristics for data collection and transmission in remote areas without infrastructure. Integrating systems based on wireless sensors and UAVs seems to be an economical and easy-to-use solution. However, the main difficulty is the amount of data sent, which affects the communication time and even the flight status of the UAV. Additionally, factors such as the UAV model and the hardware used for these tasks must be considered. Based on those difficulties mentioned, this paper proposes a system based on long-range (LoRa) technology. We present a low-cost wireless sensor network that is flexible, easy to deploy, and capable of collecting/sending data via LoRa transceivers. The readings obtained are packaged and sent to a UAV. The UAV performs predefined flights at a constant height of 30 m and with a direct line-of-sight (LoS) to the stations, during which it collects information from two data stations, concluding that it is possible to carry out a correct data transmission with a flight speed of 10 m/s and a transmission radius of 690 m for a group of three packages confirmed by 20 messages each. Thus, it is possible to collect data from routes of up to 8 km for each battery charge, considering the return of the UAV.
# Prescriptive Maintenance: A Systematic Literature Review and Exploratory Meta-Synthesis
## 3 Results
### Content-Based Data Descriptive and Exploratory Analysis
Across the literature, data-driven condition monitoring often employs degradation metrics (e.g., wear, corrosion) and comparative metrics (e.g., anomaly detection, pattern changes) to estimate remaining useful life (RUL). In PsM research discourse, temperature remains the most frequently used condition monitoring parameter for assessing system health. This is followed by system-specific data (\"Others\" 43%), energy/power consumption (34%), pressure (30%), speed (18%), flow (18%), load (18%), and others. The preference for emission-based signals, such as vibration, heat, and acoustics, is likely due to their sensitivity and the maturity of the available sensing technologies. While data-driven approaches dominate the current landscape, there is an emerging body of work emphasising the integration of physics-based models and causal machine learning [54; 55]. This shift reflects a broader rationale for evolving from purely data-centric to process- and energy-driven causal decision-making frameworks in PsM. Such integration is expected to enhance decision reliability, reduce model opacity, and improve prescriptive accuracy by incorporating domain knowledge and causal inference mechanisms. A study [56] demonstrates the superiority of causal knowledge graphs over non-parametric ML models in failure classification.
## 4 Discussion
### Comparison with State-of-the-Art Methods
The undoubted advantage of this solution was the short computation time, but this resulted in lower values for the specificity parameter (95.30%, 93.23%, and 93.99%) compared to other methods, including the method proposed in this work. In the last two to three years, the features characterizing the RR intervals and the atrial activity part of the ECG signal have yielded promising results for detecting AF. [PERSON] [10] proposed a decision tree classifier that achieved the highest specificity (99.6%) in our comparison but displayed a lower sensitivity (97.9%). [PERSON] [8] proposed a hybrid approach that combined the non-linear entropy features of RR intervals and atrial activity, which proved to be superior to approaches that used only one field of analysis. [PERSON] [46] used a dual-domain attention cascade deep learning method (D2 AFNet) to extract and fuse features from segmented ECG signals. With a 10-fold cross-validation procedure, the sensitivity and specificity achieved were 98.39% and 98.57%, respectively, which are among the best values presented here. Based on the overview provided, it is evident that the method proposed in this work accurately detected atrial fibrillation with minimal error. When compared to other non-deep-learning methods outlined in Table 7, the proposed algorithm achieved similar or even better results.
# Reliable Visual Exploration System with Fault Tolerance Structure
## 5 Termination Condition: Completeness Evaluation
### Density-Based Evaluation  
The coarse evaluation is performed based on the spatial density of keyframes. With respect to the growth of the pose-graph, the number of edges and vertexes keeps increasing during exploration. Considering indoor applications, the vertexes in a limited space become denser and denser. Therefore, the exploration can be terminated if the vertexes are dense enough.  
Figure 6: Illustration of submap-based back-end, three submaps are shown in the figure (red, green and blue), and they are connected by constraints (arrows) between/within submaps, where the yellow points are the switchable factors for robustness loop-closure detection.  
Figure 7: Organization of proposed termination condition, where the input is a built graph (including vertexes and edges), both density-based evaluation and distribution-based evaluation are contained in a coarse-to-fine mechanism.  
Since the number of loop-closure edges is proportional to the overlap between keyframe observations, and the overlap also increases with the increase of vertex density. In other words, for a certain number of edges \(N_{edge}\), when the size of needed new keyframe \(k_{count}=0\) is small enough, and such a situation lasts for a certain duration \(D_{dense}\), the vertexes in a limited space can be thought to be dense enough. This density-based evaluation is illustrated in Algorithm 3.  
```
0: Given threshold of the number of edge, represented as \(N_{edge}\); Given threshold of the number of keyframe, represented as \(N_{keyframe}\); Built graph of explored environment, represented as \(M_{graph}\); Threshold of dense constraints duration, represented as \(D_{dense}\)
1: Counter of new edge \(e_{count}=0\)
2: Counter of new keyframe \(k_{count}=0\)
3: Counter of dense constraints building \(d_{count}=0\)
4:while\(e_{count}<N_{edge}\)do
5: For new keyframe \(f_{new}\), build edges for it whose number is \(e_{new}\)
6:\(e_{count}+=e_{new}\)
7:\(f_{new}+=1\)
8:endwhile
9:if\(f_{new}<N_{keyframe}\)then
10:\(d_{count}+=1\)
11:else
12: Judgement of density-based evaluation \(j_{density}\)=false
13:endif
14:if\(d_{count}>D_{dense}\)then
15: Judgement of density-based evaluation \(j_{density}\)=true
16:else
17: Judgement of density-based evaluation \(j_{density}\)=false
18:endif
19:return\(j_{density}\)
```  
**Algorithm 3** Density-based completeness evaluation
# Reliability of a New Portable Dynamometer for Assessing Hip and Lower Limb Strength
###### Abstract  
The purpose of this study was to evaluate intra- and inter-session reliability of the new, portable, and externally fixated dynamometer called MuscleBoard(r) for assessing the strength of hip and lower limb muscles. Hip abduction, addiction, flexion, extension, internal and external rotation, knee extension, ankle plantarflexion, and Nordic hamster exercise strength were measured in three sessions (three sets of three repetitions for each test) on 24 healthy and recreationally active participants. Average and maximal value of normalized peak torque (Nm/kg) from three repetitions in each set and agonist:antagonist ratios (%) were statistically analyzed; the coefficient of variation and intra-class correlation coefficient (ICC2\({}_{\text{LJ}}\)) were calculated to assess absolute and relative reliability, respectively. Overall, the results display high to excellent intra- and inter-session reliability with low to acceptable within-individual variation for average and maximal peak torques in all bilateral strength tests, while the reliability of unilateral strength tests was moderate to good. Our findings indicate that using the MuscleBoard(r) dynamometer can be a reliable device for assessing and monitoring bilateral and certain unilateral hip and lower limb muscle strength, while some unilateral strength tests require some refinement and more extensive familiarization.  
Keywords:hip strength; force; torque; agonist:antagonist ratio; Nordic hamstering exercise +
Footnote †: journal: Applied
## 4 Conclusions  
The dissolution of praseodymium oxide in 5 YSZ at 1450-1550 \({}^{\circ}\)C is kinetically limited and occurs via the formation of pyrochlore-type Pr2 Zr2O7 intermediate. High-temperature treatments result in the stabilization of Pr3+ in fluorite or pyrochlore structures. The fraction of Pr4+ at 600-1000 \({}^{\circ}\)C in air is \(\leq\)2%. The praseodymium content has the main impact on the properties of [(ZrO2)0.95(Y2O3)0.051]1-x[PrOy]\({}_{x}\) ceramics prepared by the direct firing of compacted 5 YSZ + PrOy mixtures. Increasing praseodymia additions results in a larger fraction of the pyrochlore-type phase and larger porosity, which limit the total electrical conductivity to 2.0-4.6 S/m at 900 \({}^{\circ}\)C and 0.28-0.68 S/m at 700 \({}^{\circ}\)C in air. Increasing the time and temperature of firing promotes the phase and microstructural homogenization of the ceramics, but with a comparatively low effect on density and conductivity. 5 YSZ with praseodymia additions remains a predominantly oxygen ionic conductor. The \(p\)-type electronic contribution to the total electrical conductivity increases with Pr content, but does not exceed 2% for \(x\) = 0.15 at 700-900 \({}^{\circ}\)C. The average thermal expansion coefficients of the prepared ceramics are in the range of 10.4-10.7 ppm/K slightly decreasing with praseodymium additions. Exposure to reducing atmospheres seems to facilitate the low-temperature phase re-equilibration.  
Conceptualization and methodology, J.R.F. and A.Y.; investigation, A.N., A.B., A.Z. and A.Y.; data analysis, A.N., J.R.F. and A.Y.; writing--original draft preparation, J.R.F., A.N. and A.Y.; writing--review and editing, A.N., J.R.F., A.B., A.Z. and A.Y.; supervision, project administration and funding acquisition, J.R.F. and A.Y. All authors have read and agreed to the published version of the manuscript.  
PhD scholarship of A.N. is funded by the FCT (grant SFRH/BD/116853/2016). This work was supported by the projects HEALING (POCI-01-0145-FEDER-032036) and CARBOSTEAM (POCI-01-0145-FEDER-032295) funded by FEDER through COMPETE2020--Programa Operacion-al Competitividade Internacionalizacao (POCI) and by national funds through FCT/MCTES, and by the project CICECO--Aveiro Institute of Materials (UIDB/50011/2020 and UIDP/50011/2020), financed by national funds through the FCT/MCTES and when appropriate co-financed by FEDER under the PT2020 Partnership Agreement. A.Z. gratefully acknowledges financial support from the Ministry of Science and Higher Education of the Republic of Poland for Statutory Grant CPE/098/STAT-MN-AZ/20 in the Institute of Power Engineering.  
The data are contained within the article and/or available from the corresponding author upon reasonable request.  
The authors declare no conflict of interest.
# Ceramic Matrix Composites for Aero Engine Applications--A Review
## 5 Non-Oxide CMCs  
Non-oxide CMCs are technical ceramics displaying covalent bonds, which mainly include conductive carbides and non-conductive nitrides [83]. The composition of non-oxide CMCs allows for high toughness, although their constituents are very brittle. This is achieved through the design of the fiber/matrix interface, which is capable of deflecting cracks formed when a large amount of load occurs in the brittle matrix, avoiding an early failure of the fibrous reinforcement, such as the O-CMCs. In more detail, a thin layer of a compliant material with low shear strength is added to the fiber surface, creating an interphase that reacts as a mechanical fuse [84,85].  
Non-oxide CMC combinations provide different material properties and require different manufacturing procedures, which determine their usage for a variety of applications in different industrial sectors. The literature highlights that non-oxide CMC is the most commonly used CMC for high-temperature applications [86]. They can be separated into composite material categories, which include carbon, silicon, titanium, and tungsten carbide particles. Their mechanical and thermal properties allow them to be used as cutting tools, super-hard abrasives, rocket nozzles, electrodes for metal melts, as well as heating elements.  
The most used structural non-oxide materials are silicon carbides, known as sialons, which are nitride-based ceramics with a wide range of oxide content. They are mainly processed in high-temperature environments with inert gases to reduce oxidation [87, 88, 89]. Non-oxide CMCs composition includes different matrices which can be used as base material and different fillers and reinforcements, as shown in Figure 5. The four main material matrices include carbon, silicon carbide, titanium carbide, and tungsten carbide.
# A Dynamic-Routing Algorithm Based on a Virtual Quantum Key Distribution Network
## 2 Technical Foundation
### Design of QKP
#### 2.3.3 Remaining Key Volume  
The number of remaining keys in a QKP can be used to evaluate the number of quantum keys available in the network, thus helping to select a better quantum communication path [38; 39]. To maximize the saving of quantum keys and enable it to support as many users as possible, improve communication efficiency. Therefore, we defined the following equation to calculate the number of keys remaining in QKP.  
Assume that \(K_{0}\) denotes the initial amount of keys in the QKP, \(R_{ij}\) represents the rate of quantum key generation, and \(Q_{ij}\) indicates the rate of quantum key consumption. Introducing a mathematical calculus model to describe the change in the number of keys provides a more accurate and comprehensive analysis to predict the trend in the number of keys. Where \(\int_{t_{0}}^{t}\mathrm{R_{ij}}-\mathrm{Q_{ij}}\) denotes the cumulative number of keys consumed in the interval from the time \(t_{0}\) to \(t\), the amount of keys \(K_{\mathrm{ij}}^{t}\) in the remaining essential pool is indicated as follows:  
\[K_{\mathrm{ij}}^{t}=K_{0}+\int_{t_{0}}^{t}R_{ij}-Q_{ij} \tag{5}\]  
In QKD, by setting the critical value of the remaining quantum key in the QKP, the system's security and operational efficiency can be improved while preventing unauthorized access and attacks. Assuming that the critical value of the remaining key volume is \(K_{\mathrm{min}}\), this can be expressed using the following equation:  
\[K_{\mathrm{min}}=\frac{R_{ij}\times T}{Q_{ij}} \tag{6}\]  
where \(T\) denotes the time interval between quantum key generation and consumption, the meaning of the formula is that the critical value of the remaining key amount is equal to the ratio of the quantum key generation rate to the consumption rate multiplied by the time interval. \(K_{\mathrm{min}}\) can be used to determine whether the quantum key needs to be regenerated, and when the remaining essential amount \(K_{\mathrm{ij}}^{t}\) is lower than the critical value \(K_{\mathrm{min}}\), we can trigger the regeneration process of the quantum key to ensure that there are enough remaining keys available before the critical distribution completes.
# Path Difference Optimization of 5G Millimeter Wave Communication Networks in Malaysia
## 2 Related Work  
The primary focus of this study revolves around rain attenuation, path loss within urban and highway scenarios, link margin, and the optimization of path differences. Within the existing literature, numerous articles have delved into topics such as path loss models, received signal strength, and the evaluation of rain attenuation across different frequencies. These references are compiled and presented in Table 1.  
\begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline
**Author \& Ref. No.** & **Frequency** & **Objectives** & **Key Findings** \\ \hline \multirow{8}{*}{[PERSON]. [PERSON], et al., [13]} & & ITU models are used to measure the rain rate and rain attenuation in Malaysia throughout the year and estimated the error percentage. & At 0.01\% of time the rain rate was 120 mm/h and the rain attenuation was 34 dB at 1.3 km are observed. \\  & 24 GHz & & \\  &  
These references reveal that rain attenuation is primarily influenced by several factors, including rainfall rate, path difference, operating frequency, and polarization. Additionally, a variety of prediction models, such as empirical, statistical, fade slope, physical, and optimization models, play a role in understanding and quantifying this phenomenon. The rainfall rate and rain attenuation directly impact the signal characteristics.  
In this study, we examine the influence of rainfall and rain attenuation on signal propagation characteristics, specifically, path loss, path loss error statistics, and link margin, within urban and highway scenarios. The impact of rain attenuation in tropical regions significantly affects signal propagation. Consequently, our investigation includes an assessment of rain attenuation and the estimation and optimization of path loss and path difference, respectively, in both urban and highway scenarios.
## 7 Discussion and Further Work
### Event Communication  
While most applications (things) log events, they do not have mechanisms to communicate them to remote destinations. For this purposes, various protocols can be utilized that can read from the event log file or hook onto the event framework output stream and communicate them remotely in a timely manner. Some of these are logging specific, for instance SYSLOG [45] and SNMP, while general protocols, like HTTP, REST architecture [28] or MQTT [46], can also be utilized. However, the question to investigate here is: which of these will be more reliable and efficient to be used as communication agents in low-end devices as sensors in IoT? As already mentioned, these events contain critical information that should be protected during communication. Therefore, the event communication protocol needs to ensure that channel is well protected. Furthermore, to ensure energy efficiency and fast delivery factors, like the protocol's packet size, request-response time and other QoS attributes needs to be evaluated before it is adopted. For instance, just to reflect on this issue, [PERSON] in an experiment [47] shows that MQTT saves about 30% of battery as compared to HTTPS when 1024 messages each of one byte are sent over a period of 1 h. In the same experiment, he also shows that MQTT can send about 94-times more messages than HTTPS over a 3 G network and 72-times more messages over a WiFi connection. An experiment like this implies that one must consider the communication protocol in an environment like IoT where resource-limited devices are the primary driving force.  
In EDAS, we assume that the security analysts who design the threat correlation contexts have a keen understanding of the different types of events generated by a multitude of things in the monitored scope. It seems to be a complex task; however, most mature products (things) are provided with well-documented reference material of which they can take advantage.
# Analyzing Zone-Based Registration Using a Three Zone System: A Semi-Markov Process Approach
## 4 Numerical Results
### Effect of Implicit Registration by Outgoing Calls  
As explained in Section 3, when a call is made from the UE in the current zone, the network updates the location through the call processing messages without location registration messages, which is called an implicit registration (IR) by an outgoing call. In this case, the paging cost can be reduced in 2Z or 3Z systems since the network can infer the UE's current zone.  
Let us examine the IR effect by outgoing calls in a 3Z system numerically. Figure 12 compares the performance results for a 3Z system without IR, a 3Z system with IR and a 1Z system for some CMRs, while assuming T\({}_{m}\) follows an exponential distribution with a mean of 1. In this case, it is also assumed that the outgoing call rate is equal to the incoming call rate (\(\lambda_{i}=\lambda_{o}\)). In the figure, we can see that the 3Z system with IR is much superior to a 3Z system without IR. Note that when IR is not  
Figure 11: Total cost for various gamma distributions (\(\theta\) = 0.3).  
Figure 10: Total cost for various \(\theta\)s.  
considered, the 3Z system is inferior to the 1Z system but when IR is considered, the 3Z is superior to the 1Z system. In conclusion, the IR effect by outgoing calls should be considered for the 3Z system to achieve a minimal total cost.