esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Non-Ischemic Heart Diseases
### Sarcoidosis  
Some studies have investigated the potential role of LIE-CT in sarcoidosis, a systemic granulomatous disease of unknown etiology with cardiac involvement, encountered in only 2-5% of patients [45]. In these patients, the existence and extension of LGE have been documented to forecast unfavorable cardiac outcomes [46]. Typically, it exhibits a diverse range of patterns, commonly involving the mid-wall and/or epicardium while sparing the sub-endocardium at the base of the heart, particularly affecting the septum and lateral wall [47]. A study conducted by [PERSON] et al. aimed to assess the diagnostic value of LIE-CT for cardiac sarcoidosis in patients with and without implantable devices compared to LGE-CMR. A cohort of 24 patients underwent analysis, demonstrating high interobserver agreement in visually identifying segments with increased signal intensity on LIE-CT. This agreement was consistent regardless of the presence or absence of implantable devices. Additionally, comparisons between LIE-CT and LGE-CMR revealed good correlations in quantifying the extent of the hyper-enhanced myocardium, with correlation coefficients of 0.96 for the per-patient analysis and 0.83 for the per-segment analysis (both statistically significant, \(p<0.001\)). LIE-CT demonstrated sensitivity of 94% and specificity of 33% in diagnosing cardiac sarcoidosis [48]. However, despite these promising results, it is important to consider the limited sample size of the study. Additionally, in a case report by [PERSON], a patient with suspected cardiac sarcoidosis and an implanted cardioverter-defibrillator underwent a DECT examination to assess LIE, as CMR was contraindicated. DECT images were acquired immediately after contrast media injection and repeated after 10 min. First-pass images revealed myocardial thinning in the apical and basal septum, while LIE images showed hyper-enhancement in corresponding regions, as well as patchy, subepicardial areas in the apical and lateral walls, characteristic of cardiac sarcoidosis [49]. This case underscores the utility of CCT as a viable alternative in patients with metallic implants that are not magnetic resonance imaging-conditional.  
See Figure 1 as an example of LIE-CT in a patient with both ischemic and non-ischemic enhancement due to a stenotic right coronary artery and cardiac sarcoidosis.
## 4 Empirical Propagation Models
### Floating-Intercept Model (FI)  
The floating-intercept (FI) propagation model, also known as the alpha-beta (AB) model, does not have parameters based on physical fundamentals. It utilizes curve-fitting factors calculated by the minimum mean square error (MMSE) method. The model has been adopted by the 3 rd Generation Partnership Project (3 GPP) and the WINNER II association, which provide standard propagation models. The 3 GPP and WINNER II models are widely used in the industry as they cover various types of scenarios. However, they are only used for frequencies below 6 GHz and need to be enhanced for higher frequency bands [38].  
For this reason, the FI model has been extensively studied. It can be used to characterize millimeter-wave frequencies, where channels may be in line-of-sight or non-line-of-sight environments [38; 39]. The equation of the FI model is given in (4):  
\[PL_{FI(dB)}=\alpha+10\beta log_{10}\left(\frac{d}{d_{0}}\right)-X_{\sigma FI} \tag{4}\]  
In which \(\alpha\) is the floating intercept coefficient in dB, known as the offset, \(\beta\) is the slope of the line, \(\mathrm{d}\) is the distance between the antennas in meters, and \(X_{\sigma FI}\) is the slow fading variable, which describes large-scale signal fluctuations over the average path loss, with zero mean and standard deviation \(\sigma\). The values of \(\alpha\) and \(\beta\) are calculated by MMSE to minimize the value of \(X_{\sigma FI}\)[40]. A dataset obtained from measurements is necessary to compute the path loss values. The coefficients are then obtained from these values using established formulas [38] that minimize the standard deviation.  
The FI model can be further expanded into another model known as ABG (alpha-beta-gamma), which adds another fitting parameter for frequency. Like the FI model, it has no physical anchoring and provides a curve that best fits the dataset across multiple frequencies simultaneously.
# Daily Flood Monitoring Based on Spaceborne GNSS-R Data: A Case Study on Henan, China
## 3 Results
### Comparison with Remote Sensing Images  
It can be seen from Figure 2 that the flood was mainly concentrated in Xinxiang. By observing the amount of change in CYGNSS reflectivity before and after the flood (see Figure 17), it is possible to estimate the area that was most severely affected by the flood.  
In Figure 17, from top to bottom, the red jagged lines represent the Wei River, Jialu River, Ying River, and Sha River. It can be seen from Figure 17 that the reflectivity of the flood discharge area (black box) affected by flood discharge of the Jialu River and the flood discharge area (purple box) affected by flood discharge of the Sha River and Ying River are more obvious, indicating that the disaster situation is serious. In Xinxiang (blue Box), the changes are more apparent. This is due to extreme weather moving northwards from Zhengzhou and dropping 26 cm (10 inches) of rain in Xinxiang within two hours. In addition, there are many rivers and reservoir networks in the area, so it is greatly affected by the flood.  
Figure 16: (**a,b**) are the amount of change in the soil moisture from 19 July to 24 July 2021 and before the flood (from 16 July to 18 July 2021).  
Figure 14: The amount of change in CYGNSS reflectivity from 19 July to 24 July 2021 and before (on 18 July 2021) the flood.  
Figure 15: (**a,b**) are the amount of change in the brightness temperature from 19 July to 24 July 2021 and before the flood (from 16 July to 18 July 2021).  
Thus, based on the estimates from the CYGNSS observations, the data on the areas severely affected by the flood are also consistent with the optical image in Figure 2.
# A Compact Rectifier Design Method Utilizing Harmonics
## 1 Introduction  
Microwave power transmission (MPT) transmits power from one point to another [1] or to multiple points [2] through free space. MPT technology has become one of the most promising power supply methods for electronic devices, such as mobile terminals [3], wireless sensor networks [4], and drones [5]. In a MPT system, the rectifier, converting the microwave power into the direct-current (DC) power, is a key component. The rectifying diode works in the nonlinear state of large-signal and produces the high-order harmonics. Generally, to lessen the influence of the harmonics and obtain high rectifying efficiency, there are two design methods. One is re-rectifying harmonic for recycling [6, 7], another is harmonic controlling by using class-F [8] and class-F\({}^{-1}\)[9].  
In recent years, [PERSON] al. proposed to use the 3 rd harmonic for antenna beam alignment of the MPT system [10, 11]. In [10], a hybrid coupler was suggested to transfer the input power for rectification and utilize the 3 rd harmonic to the isolation port for antenna beam alignment. In [11], a ring-shaped coupler directed the 3 rd harmonic to the input port and was radiated through a dual-frequency antenna. However, the couplers make the rectifiers complicated and necessitate having large sizes. The separate 2 nd harmonic utilization path was employed in [12], but this method also had a large size. The 2 nd harmonic is used as the pilot signal for the retrodirective system in [13]. Although the rectifier utilized the 2 nd harmonic without extra devices and complicated structure, the rectifying efficiency was only 42.5%.  
Based on a specially designed DC-pass filter, this paper presents a compact rectifier design method for utilizing harmonics while maintaining high rectifying efficiency. Table 1 summarizes the comparison between the proposed rectifier and the published literatures. The proposed rectifier design method can utilize the 2 nd and the 3 rd harmonics simultaneously without an extra coupler or a separate harmonic utilization path, and the rectifying efficiency is above 70%. The amplitudes of the utilized harmonics can be controlled conveniently by designing the DC-pass filter to meet the communication system demand.  
Furthermore, the rectifier design method of only utilizing the 2 nd or the 3 rd harmonic is also analyzed.
# Assessing Voided Reinforced Concrete by Numerical Modelling of Impact-Generated Rayleigh Waves
## 6 Conclusions  
This study demonstrated the feasibility of using a 2D finite element model to simulate impact-generated Rayleigh wave propagation in voided concrete. The model, calibrated and validated against experimental data, achieved strong agreement in waveform correlation (0.975 for plain concrete) and velocity (within 5% of theoretical values). While the correlation for reinforced concrete (0.567) was lower, it remains acceptable considering the model's simplifications and ease of application for quick investigation. More crucially, we  
Figure 12: Simulation screenshots: wave propagation (**top**), diffraction of R-wave (**bottom left**), travel path of R-wave (**bottom right**).  
have identified the 5 kHz velocity index as a sensitive parameter for evaluating effects of void density on R-wave propagation, demonstrating a strong linear correlation. This insight signifies the potential of realising a simple in situ non-invasive measurement methodology for quantification and characterisation of concrete honeycomb. The suggested numerical modelling framework is relatively simple and easily applied, and does not require significant computation resources or highly specialised modelling skills. This framework could be adopted for rapid inspection for defects in reinforced concrete. Future work will focus on refining the model to improve the accuracy and effectiveness of damage detection in reinforced concrete and composite materials, aiming to achieve 3D simulations of materials with complex material configurations that are not fully isotropic. The data analysis scheme to be developed would also benefit from the incorporation of suitable machine learning algorithms for analysing the complex features of elastic waves. Machine learning could also assist with automating R-wave component extraction and wave property quantification and thus identifying the correlations of these properties with damage/defect characteristics.  
Conceptualisation, H.K.C. and F.W.L.; methodology, Y.Y.; software, Y.Y.; validation, H.K.C. and F.W.L.; formal analysis, Y.Y.; investigation, Y.Y.; resources, H.K.C.; data curation, Y.Y.; writing--original draft preparation, Y.Y.; writing--review and editing, H.K.C. and F.W.L.; visualisation, F.W.L.; supervision, H.K.C.; project administration, H.K.C.; funding acquisition, H.K.C. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
Dataset available on request from the authors. The raw data supporting the conclusions of this article will be made available by the authors on request.  
The authors declare no conflicts of interest.  
The following abbreviations are used in this manuscript:  
\begin{tabular}{l l}
2D & Two-dimensional \\ NDT & Non-destructive test \\ R-wave & Rayleigh wave \\ RC & Reinforced concrete \\ \end{tabular}
## 1 Introduction
### Effects on the Dermatologic System  
During short-duration space travel, skin conditions such as contact dermatitis, skin sensitivity, biosensor electrolyte paste reactions, and thinning skin are common [235; 44]. However, these conditions are generally mild and unlikely to significantly impact astronaut safety or prevent completion of space missions [44].  
The greatest dermatologic concern for long-duration space travelers is the theoretical increased risk of developing skin cancer due to space radiation exposure. This hypothesis is supported by one study which found the rate of basal cell carcinoma, melanoma, and squamous cell carcinoma of the skin to be higher among astronauts compared to a matched cohort [236]. While the three-fold increase in prevalence was significant, there were a number of confounders (e.g., the duration of prolonged UV exposure on Earth for training or recreation, prior use of sunscreen protection, genetic predisposition, and variations in immune system function) that must also be taken into account. A potential management strategy for dealing with various skin cancers during space travel involves telediagnostic and telesurgical procedures. Further research is needed to improve the telediagnosis and management of dermatological conditions (e.g., adjustment for a lag in communication time) during spaceflight.
## 5 Implementation and Evaluation
### Complexity Analysis for the Water Cycle Detection Approach  
In this work, the accuracy performance metric was utilized to analyse the WC detection approach using the WSN-SD Dataset in different classification categories. The aims were to find the highest number of True Positives (_TP_) and True Negatives (_TN_) and the lowest number of False Negatives (_FN_) and False Positives (_FP_). The number of _TN_ indicates that valid traffic is recognized, while _TP_ is the likelihood of irregular traffic being recognized. The number of _FN_ illustrates the likelihood of attack flows being identified as normal flows, while _FP_ represents the likelihood of normal flows identified as attack flows. The False Positive Rate (FPR) indicates the wrongly defined attack ratio and the inverse False Negative Rate (FNR) represents the cumulative sum of incorrect forecasts. Accuracy is the percentage of accurate model prediction for all types of predictions produced. The following Equation represents the accuracy performance metric used in this analysis:  
\[Accuracy=\frac{TP+TN}{TP+TN+FP+FN} \tag{22}\]  
\begin{table}
\begin{tabular}{c c} \hline \hline
**WSN-DS Feature** & **Sequence** \\ \hline Time & 1 \\ Is\_CH & 2 \\ Who-CH & 3 \\ Distance to CH & 4 \\ ADV\_S & 5 \\ ADV\_R & 6 \\ Join\_S & 7 \\ Join\_R & 8 \\ SCH\_S & 9 \\ SCH\_R & 10 \\ Rank & 11 \\ Data\_S & 12 \\ Data\_R & 13 \\ Data\_sent\_to\_AP & 14 \\ Dist\_CH\_to\_AP & 15 \\ Send\_code & 16 \\ Expanded\_energy & 17 \\ Label & 18 \\ \hline \hline \end{tabular}
\end{table}
Table 3: WSN-DS Features Sequence.
# Enhanced High-Definition Video Transmission for Unmanned Driving in Mining Environments
## 4 Experiments and Discussion  
### Experimental Setup  
In a coal mine in northwestern China, the full deployment of 5G networking equipment and the underground coverage of 5G signals has been achieved, setting the stage for validating high-definition video transmission for remote-controlled unmanned driving. This experiment takes place in a 2 km long transport tunnel, with a width of about 5 m and a height of approximately 4 m. The deployment of the 5G base station and antenna is illustrated in Figure 8. The RF transmission power is limited to 6 watts due to safety regulations in underground coal mines, resulting in a reduced coverage radius for the base station compared to surface scenarios. Consequently, the 5G base stations are deployed at intervals ranging between 350 and 400 m.  
Figure 8: The deployment of the 5G base station and antenna: (**a**) 5G base station; (**b**) antenna.  
Figure 7: Schematic diagram of dynamic frame chasing.  
The 5G super uplink band operates with a sub-carrier interval of 30 kHz and provides a time domain resource granularity of 0.5 ms, allowing for control of the air interface's end-to-end latency within 7 ms. Taking into account the decoding process, which typically takes around 5 ms, the end-to-end latency can be controlled to achieve a theoretical value of 12 ms. The incorporation of 2.1 GHz resources with a lower frequency enables an expanded coverage area, resulting in improved transmission rates in edge coverage areas when compared to the 3.5 GHz band. This approach also helps in reducing the cost of network construction [39].  
The peak rate test employs data encapsulation using the File Transfer Protocol (FTP). In the high-definition video transmission test [40,41], 7-channel 4K high-definition cameras are connected to the 5G terminal in the mine for data aggregation. Dual-band super uplink technology is utilized to establish a connection with the mine 5G system. The video stream is decoded at the edge of the platform and then transmitted in real-time to the remote monitoring subsystem.
## 4 Vibration Characteristics during Various Building Construction Stages
### Soil Vibrations  
The vertical acceleration levels of the soil at distances of 8.3 m, 17.3 m, and 26.3 m from track #2 under various construction stages are depicted in Figure 13. The vibration responses induced by train operations in both the pile construction and free field exhibit similar trends. However, the vibrations in the free field significantly surpass those observed in the pile construction, particularly at the measurement points located far from the vibration source. This phenomenon can be attributed to the dominance of Rayleigh waves in far-field vibrations, with a substantial dissipation of energy from body waves, indicating that the structure effectively suppresses soil vibrations. Furthermore, this phenomenon can also be partially ascribed to the implementation of the pile foundation, which introduces an additional mechanism for the dissipation of energy.  
Within a distance of 26.3 m from the source, both the pile construction and free field exhibit a dominant frequency response of 50 Hz for soil vibration. The platform construction and building construction also demonstrate consistent near-field behavior with a peak frequency of 63 Hz, attributed to the emergence of novel characteristic frequencies within the soil-structure system. As the measurement point moves to the far field at 17.3 m, the peak frequency decreases to 50 Hz. This phenomenon can be attributed to the dissipation of body wave energy as the distance from the source increases, leading to the dominance of Rayleigh waves and consequent attenuation of high-frequency components. The order of soil vibration amplitudes is as follows: free field, pile construction, building construction, and platform construction. The impact of soil vibration is directly proportional to the mass and stiffness of a building. Buildings with higher masses and greater stiffness will induce stronger reactions when vibrating in a non-free field, resulting in amplified soil vibration compared to platform construction.  
Figure 13: Comparison of soil vibrations at different distances from the track. (**a**) 8.3 m; (**b**) 17.3 m; (**c**) 26.3 m.
# RSS-Based Localization and Mobility Evaluation Using a Single NB-IoT Cell+
## 6 Results  
During the large-scale RSS-based localization experiments, we discovered a mobility issue in the NB-IoT protocol. In this section, we first show the results of the localization algorithms in terms of location estimation error. Consequently, the mobility of NB-IoT is evaluated in terms of sector reliability and cell reselection time.
## 5 Evolution of Opportunistic Routing in Asynchronous WSN
### Evolution of Asynchronous Duty-Cycled MAC Protocols
#### 5.1.4 BoX-MAC  
Two types of protocols were proposed in BoX-MAC: Box-MAC-1 and BoX-MAC-2 [31]. Rather than transmitting a wakeup preamble, as B-MAC does, BoX-MAC-1 continuously transmits the data packet directly. This continuously packetized wakeup transmission allows the BoX-MAC-1 receiver nodes to save energy by only staying awake for packets destined for them. This is a solution to the BMAC overhearing problem. BoX-MAC-1 is more efficient for use in high-volatility networks with little traffic.  
On the other hand, the decoupling between packet size and receipt check duration allows BoX-MAC-2 to replace X-MAC's dummy wakeup packets with the final deliverable packet. As a result, no handshaking is required in BoXMAC-2 to obtain the intended payload, and throughput can be nearly doubled compared to that of X-MAC. While both radios are awake, subsequent packets are delivered to the recipient at maximum throughput. In other words, multiple packets can be communicated bi-directionally after a single receive check detection. BoX-MAC-2 is more efficient in low-volatility networks with lots of traffic.  
Using BoX-MAC-1 (Figure 8 (left)), node A continuously sends a data packet until a receiver wakes up and receives the data packet. Other nodes will avoid the packet if it is not meant to be transmitted to them, after the first packet they receive, and will go to sleep. On the other hand, in BoX-MAC-2 (Figure 8 (right)), node A has a packet to send. After waking up, it sends a data packet instead of a preamble with a pause within it. Each pause node waits for an ACK from the receiver. After data is received by receiver B, it will send an ACK.  
However, two primary factors affect the performance of BoX-MAC protocols in a network: volatility and traffic. Sender-initiated low-power listening (LPL) protocols such as BoX-MAC are efficient in clean environments, but suffer from high power consumption due to false wakeups in noisy environments. In both of the Box-MAC protocols, the issue of the hidden node problem was not addressed.  
Figure 7: Packet transmission in X-MAC [30].
## 2 Composite Pulse Generation
\(h(n)\) and \(h(n-1)\) are the orthogonal pulses generated with opposite phase and the addition of such complementary pulses, for instance \(MHP_{0}=h(n)\), and \(MHP_{0}=h(n-1)\), will cancel out each other. Hence it is vital that only one is chosen from the pair of generated complementary orthogonal pulses.For the proposed UWB system, \(MHP_{0}=h(n)\), \(MHP_{1}=h(n)\), \(MHP_{2}=h(n-1)\), and \(MHP_{3}=h(n)\) have been selected for their performance in providing better correlation results. Here, \(MHP_{0}=h(n)\) and \(MHP_{2}=h(n-1)\) are out of phase with \(MHP_{2}=h(n)\) and \  
The correlation values between the selected orthogonal pulses and all possible combinations of 2, 3, and 4 orthogonal pulses are shown in Tables 4 and 5. The correlation coefficient values show how closely the two signals under consideration resemble each other. Hence, it can be interpreted as a conviction factor for the given MHP to be present in the composite pulse under inspection. For instance, for 57% confidence it can occur that \(MHP_{0}\) is present in the composite pulse of \(MHP_{0,1}\) (Table 4: second row, second column). From Tables 4 and 5, the maximum correlation value for the false positive is 16.22% (Table 4: third row, fourth column) for the correlation between \(MHP_{1}\) and the combinations of \(MHP_{0,3}\  
Figure 2: Composite pulse (**a**) without noise (**b**) with signal-to-noise ratio (SNR) 10 dB (**c**) with SNR 20 dB. Thus, the selected threshold level of 21% satisfies both the low and high ends of the SNR values. With these results, it can be concluded that higher order orthogonal pulses can be generated using the modified Hermite pulse set generator. These orthogonal pulses can be added in time and then be transmitted as a composite pulse. It have been also shown that the composition of the composite pulse can be accurately determined with the threshold value of 21%, even at the lower end SNR of 10 dB.