esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Discussion
### Latency and Event-Based Application Support  
Latency is one of the most critical performance parameters of a UAN, since it determines whether the UAN can support event-based applications. Figure 5 depicts the latency of a 100-byte payload data unit transmitted by sensor nodes to their next hop, for a representative module implementing an enabling technology of each type of UAN class. For the MNO UAN, the result is obtained from the empirical measurements mentioned in the previous subsection. For the rest of UANs, latency is calculated theoretically, assuming an error-free scenario, and including the acknowledgment delay for LR-WPAN and WLAN UANs. For the DTN UAN, a period between connectivity opportunities of 10 min has been assumed for comparison purposes. This period has been chosen as an optimistic value, considering a relatively frequent rate of connectivity opportunities, which may be found when public buses play the role of data mules. Note that the period between connectivity opportunities may be even in the order of a day, when garbage collection vehicles are used as data mules. Latency in DTN UANs is strongly dominated by the period between connectivity opportunities, whereas in the rest of UAN classes, connectivity is permanent.  
As shown in Figure 5, in LR-WPAN and WLAN UANs, the latency of data transmitted by sensor nodes is low (_i.e._, up to a few milliseconds per hop). SO UANs may lead to delays between hundreds of milliseconds up to tens of seconds, depending on the bit rate used. MNO UANs offer delays up to around ten seconds, which do not allow real-time transmissions, but are sufficient for event-based applications in Smart Cities. In DTN UANs, sensor nodes have to wait for minutes or hours until the next connection opportunity with a data mule for data communication. Therefore, DTN UANs constitute the only UAN class that does not support event-based applications.  
In the opposite direction, the sensor node duty cycle (or the connectivity opportunity rate in DTN UANs) determines the delay until data can be sent to the sensor node from the previous hop, which can typically be in the order of minutes, or even hours.
# Universal Voltage Conveyor and its Novel Dual-Output Fully-Cascadable VM APF Application
## 1 Introduction
Since the first UVC-based VM APF was published [11], four more dual-output VM APFs have been introduced into the literature [12; 13; 14]. Here it is worth noting that none of these UVC-based APFs simultaneously satisfy the desired features (i)-(v) listed above. Therefore, this letter aims to report a dual-output VM APF with high input and low output impedance characters employing only single UVC and all grounded passive components and with no complex passive matching constraints, which enables a reduction of the circuit complexity. The behavior of the proposed circuit has been experimentally measured using the readily available UVC-N1C 0520. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Reference** & **ABB** & **Grounded** & **Floating** & **Simul./** & \(f_{\mathbf{p}}\) & **Supply** \\  & **Type** & **R/C** & **R/C** & **Meas.** & **(Hz)** & **(V)** \\ \hline Figure 4b in [5] & FD-OPA \& CCII & 0/0 & 1/1 & Meas. & 29.6 k & \(\pm\)5 \\ Figure 1 in [6] & FD-OPA & 0/0 & 0/1 & Simul. & 92 k & \(\pm\)1.5 \\ Figure 2 in [7] & ICCII+ & 0/0 & 1/1 & Simul. & 1.59 M & \(\pm\)1.25 \\ Figure 2 in [8] & FDCCII & 0/1 & 1/0 & Simul. & 159.2 k & \(\pm\)3 \\ Figure 2 in [9] & DV-DXCCII \& 1 NMOS & 0/1 & 0/0 & Simul. & 27 M & \(\pm\)0.9 \\ Figure 3 in [10] & VDIBA & 0/0 & 0/1 & Both & S: 9.44 M; M: 1 M & \(\pm\)0.9; \(\pm\)5 \\ Figure 1 in [11] & UVC \& OTA & 0/0 & 0/1 & Simul. & 3 M & \(\pm\)2 \\ Figure 3 in [12] & UVC & 2/0 & 1.1 & Both & S: 3.5 M; M: 160.4 k & \(\pm\)2.5; \(\pm\)1.65 \\ Figure 2a in [13] & UVC & 2/0 & 0/1 & Simul. & 1.17 M & \(\pm\)2.5 \\ Figure 2b in [13] & UVC & 2/0 & 0/1 & Both & S: 1.17 M; M: 746.4 k & \(\pm\)2.5; \(\pm\)1.65 \\ Figure 2 in [14] & UVC & 0/1 & 2/0 & Simul. & 390 k & \(\pm\)2.5 \\ This work & UVC & 2/2 & 0/0 & Meas. & 277.8 k & \(\pm\)1.65 \\ \hline \hline \end{tabular} Note: S.: simulation result; M.: measurement result. CCII: second-generation current conveyor; DV-DXCCII: differential voltage dual-X second-generation current conveyor; FD-OPA: fully-differential operational amplifier; FDCCII: fully differential second-generation current conveyor; ICCII+: positive-type inverting second-generation current conveyor;OTA: operational transconductance amplifier; UVC: universal voltage conveyor; VDIBA: voltage differencing inverting buffered amplifier; NMOS: n-type metal-oxide-semiconductor.  
\end{table} 
Table 1: Comparative study of existing dual-output voltage-mode (VM) all-pass filters (APFs).
# Flavour Compensation Role of Yeast Strains in Reduced-Salt Dry Sausages: Taste and Odour Profiles
## 3 Results and Discussion
### Volatile Compound Analysis
In the present study, the content of acetic acid significantly increased after 12 days of fermentation (\(p<0.05\)) and the content of acetic acid was significantly higher in the CR treatment on day 12 (\(p<0.05\)), indicating that the lower salt content could promote the production of acetic acid. Among the inoculated sausages, the contents of all acids in the DH treatment were significantly higher than that in the CT and CR treatments (\(p<0.05\)). Increases in heptanoic acid and nonanoic acid were found in the PK treatment, and an increase in heptanoic acid was found in the TD treatment (\(p<0.05\)). Nevertheless, despite being ester precursors, acids are generally non-essential aroma contributors due to their high odour thresholds. Esters are crucial contributors to the unique odour profile of dry sausages and generally originate from the non-enzymatic esterification of alcohols and acids, as well as enzymatic catalysis by microorganisms [60]. Most of the esters identified in the present study were ethyl esters, which impart fruity aromans and mask unpleasant odours [48]. These compounds included ethyl acetate, ethyl lactate, ethyl butyrate, ethyl hexanoate, ethyl heptanoate, ethyl caprylate, and ethyl caprate. After 12 days of fermentation, the total ester contents increased in all treatments and each treatment exhibited a unique ester profile. Among the inoculated sausages, the DH treatment showed the highest total ester content at 340.44 \(\mu\)g/kg, followed by the PK and TD treatments, reaching 194.93 and 192.77 \(\mu\)g/kg, respectively, suggesting that yeast inoculation can promote the production of esters that could positively affect the dry sausage aroma. The same phenomenon has been reported in different meat products, such as fermented sausages [56], dry-cured ham [61], and cured pork [46]. However, these effects depend largely on the genus and species of the inoculated yeasts. A total of 15 terpen and six other compounds were detected, most of which were not related to chemical or biological processes, but may be related to the spices added during sausage preparation. As a result of the fermentation process, the contents of some compounds [sabinene, \(\gamma\)-terpinene, (1S)-(1)-\(\beta\)-pinene and 3-carene] from spices increased to various degrees.
## 3 Numerical Simulation Calculation Method and Experimental Validation
### Boundary Conditions  
According to the calculation model and meshing in Section 3.1, ANSYS FluENT 19.2 software was used for the steady-state numerical calculations. The numerical simulation of the diagonal flow fan uses a steady-state (Steady) method based on a Pressure-Based solver, which uses sequential solving to set the variables--setting the dynamic lobe fluid domain as the rotational domain, the outlet cross section in the outlet fluid domain as the flow monitoring surface, and the inlet and outlet boundary conditions as the pressure-inlet and pressure-outlet. The turbulence modeling uses the Realizable k-\(\varepsilon\) eddy viscosity model, which is highly accurate in calculating rotational uniform shear flows, boundary layer flows and separation flows. The SIMPLE algorithm was used to calculate the flow field, and the transport equations were discretized by the finite volume method. The second-order accurate discretisation is chosen for individual terms and the second-order upwind is selected for the convection terms. The root means square (RMS) value of the residuals of the control equation is less than \(10^{-5}\) to guarantee the accuracy of the numerical calculation.  
Figure 6 shows the grid number's influence on the numerical simulation results of the diagonal flow fan. This fan's total pressure and flow rate stop changing after the grid number exceeds 3 million. The calculation grid number is finally determined to be 3 million after considering the calculation accuracy and time.
# Robust U-Nets for Fetal R-Peak Identification in Electrocardiography
###### Abstract  
Accurate fetal R-peak detection from low-SNR fetal electrocardiogram (FECG) signals remains a critical challenge as current NI-FECG methods struggle to extract high SNR FECG signals and conventional algorithms fail when signal quality deteriorates. We proposed a U-Net-based method that enables robust R-peak detection directly from low-SNR FECG signals (0-12 dB), bypassing the need for high-SNR inputs that are clinically difficult to acquire. The method was evaluated on both real (A&D FECG) and synthetic (FECGSYN) databases, comparing against ten state-of-the-art detectors. The proposed method significantly reduces false predictions compared to commonly used detection algorithms, achieving a PPV of 99.81%, an SEN of 100.00%, and an F1-score of 99.91% on the A&D FECG database and a PPV of 99.96%, an SEN of 99.93%, and an F1-score of 99.94% on the FECGSYN database. Further investigation of robustness in low-SNR conditions (0 dB, 5 dB, and 10 dB) achieved 87.38% F1-score at 0 dB SNR on real signals, surpassing the best-performing algorithm implemented in Neurokit by 13.58%. In addition, the algorithm showed \(\leq\)2.65% performance variation across tolerance windows (50 reduced to 20 ms), further underscoring its detection accuracy. Overall, this work reduces the reliance on high-SNR FECG signals by reliably extracting R-peaks from suboptimal signals, providing implications for the reliability of fetal heart rate variability analysis in real-world noisy environments.  
U-Net; R-peak detection; QRS detection; fetal electrocardiogram (FECG) 2025
# Fine-Grained Detection of Pavement Distress Based on Integrated Data Using Digital Twin
## 3 Methodology
### Fine-Grained Pavement Distress Detection Based on Deep-Object Detection Networks
#### 3.2.1 Image Annotation  
The training dataset is not made up by captured images. The original images need to experience a series of labeling operations to turn them into corresponding format data for training. For each image, the objects of interest in the image are manually labeled, such as alligator cracks (AC), cross cracks (CC), longitudinal cracks (LC), potholes (P), and transverse cracks (TC) in the pavement images. The XML files correspond to the target information of the objects of interest in the annotation image, including the target size and type, generally represented with rectangular box boundary coordinates and the label name, respectively. In this paper, the labeling tool (Labelimg) is used to label five different types of pavement distresses into PASCAL VOC format, and each image corresponds to an XML file, which is then converted into a TXT file for model training, and the annotation results are recorded in the txt file. The annotation process is shown in Figure 6.  
Figure 6: Images annotation process.(**a**) Annotation by Labelimg. (**b**) Convert the XML file to a TXT file. (**c**) Training results visualization.
# Precision Farming in Hilly Areas: The Use of Network RTK in GNSS Technology
## 2 Materials and Methods
The latter reported the path and the deviation from the trajectory to be followed in a monitor/video. The third mode involved the implementation of a total automation processes. The tractor followed specific paths, defined on a map, through the automatic pilot. The operator was limited to monitoring the correct operation of devices and operating machines. This compares the traditional operating modes with precision agriculture, in terms of products used, execution times, and job safety. The reduction of environmental emissions into the atmosphere and the inadequacies in the implementation of agronomic practices were also assessed. Regarding the latest research goal, a fleet management device was not immediately visible from the cabin (as it is an alarm device in case of theft). The system has many configuration options and functions, as well as serving as an aid to the management and maintenance of the vehicle itself. It is also possible to define a \"limit zone\" in the system: if the vehicle exits or enters this area, at uninterrupted time intervals, even when the engine is off, the device sends SMS or e-mail alerts. For areas with poor Internet coverage, a device called an RTK-Bridge has been tested (Figure 3). The device was placed in an area where there was a low Internet coverage. It has been connected to the permanent station network, sending its approximate position. It downloaded the differential corrections and then redistributed all the media operating through a low power radio. The width of the radio coverage depends on the territorial profile and the presence of obstacles. Like all radio devices, it is better to place the device at the highest point of the working area. In addition, for increasing operator safety, a device has been tested to send alarms via SMS and to switch on an led in the cabin, when one or more previously set inclination values of the vehicle have been reached. Two limit corners were set (a first angle of 15\({}^{\circ}\) and a second one of 45\({}^{\circ}\)). This latter angle greatly exceeded the safety limits for crawler tractors, and thus represented an alarm for probable overturning of the vehicle.
# Implications of GNSS-Inferred Tropopause Altitude Associated with Terrestrial Gamma-ray Flashes
## 4 Discussions and Conclusions
As the continental area of South China extends to lower latitudes than the contiguous United States, the coordinated ground-based multi-instrument measurements in South China can readily obtain more desired observations to investigate the detailed connection between TGFs and parent lightning [51; 52]. The Chinese Gravitational-wave high-energy Electromagnetic Counterpart All-sky Monitor (GECAM) satellite launched in December 2020 will provide more opportunities to decipher the particular physical mechanism for the production of gamma-rays [53]. Conceptualization, T.X. and G.L. ; methodology, T.X. ; software, T.X. and Q.Y. ; validation, T.X., J.Y. and H.Z. ; formal analysis, T.X. ; investigation, T.X. ; resources, H.Z. and F.L. ; data curation, H.Z., S.X., Q.Y. and F.L. ; writing--original draft preparation, T.X. ; writing--review and editing, G.L., H.Z. and J.Y. ; visualization, T.X. and Y.W. ; supervision, G.L. ; project administration, T.X. and G.L. ; funding acquisition, T.X. and G.L. All authors have read and agreed to the published version of the manuscript. This work was supported by the National Key R&D Program of China (2017 YFC1501501), National Natural Science Foundation of China (42075071, 41622501, and U1938115), and the Chinese Meridian Project. The TGF data are available from the online archives as follows: RHESSI ([[https://hesperia.gsfc.nasa.gov/hessidata/](https://hesperia.gsfc.nasa.gov/hessidata/)]([https://hesperia.gsfc.nasa.gov/hessidata/](https://hesperia.gsfc.nasa.gov/hessidata/)) (accessed on 10 May 2021)), FERMI ([[https://heasarc.gsfc.nasa.gov/FTP/fermi/data/gbm/daily/](https://heasarc.gsfc.nasa.gov/FTP/fermi/data/gbm/daily/)]([https://heasarc.gsfc.nasa.gov/FTP/fermi/data/gbm/daily/](https://heasarc.gsfc.nasa.gov/FTP/fermi/data/gbm/daily/)) (accessed on 10 May 2021)), and Insight-HXMT (www.hxmt.org (accessed on 10 May 2021)); the GNSS-RO data are obtained at the CDAAC ([[https://cdaac-www.cosmic.ucare.edu/](https://cdaac-www.cosmic.ucare.edu/)]([https://cdaac-www.cosmic.ucare.edu/](https://cdaac-www.cosmic.ucare.edu/)) (accessed on 10 May 2021)), the merged IR data are from NCEP/CPC ([[https://doi.org/10.5067/T4](https://doi.org/10.5067/T4) HZ9N27 EKU]([https://doi.org/10.5067/T4](https://doi.org/10.5067/T4) HZ9N27 EKU) (accessed on 10 May 2021)), and the radiosonde sounding is from IGRA ([[https://www.ncdc.noaa.gov/data-access/weather-balloon/integrated-global-radiosondec-archive](https://www.ncdc.noaa.gov/data-access/weather-balloon/integrated-global-radiosondec-archive)]([https://www.ncdc.noaa.gov/data-access/weather-balloon/integrated-global-radiosondec-archive](https://www.ncdc.noaa.gov/data-access/weather-balloon/integrated-global-radiosondec-archive)) (accessed on 10 May 2021)). The _Insight_-HXMT mission is a project funded by China National Space Administration (CNSA) and Chinese Academy of Sciences (CAS). The authors declare no conflict of interest.
## 2 Sensitivity-Based VPP Control Algorithm
### Grouping of VPP Resources  
The purpose of resource grouping is to minimize the VPP control capacity by grouping renewable energy resources that are electrically close to each other. Grouping is performed based on the calculation of electrical sensitivities, and only resources with sensitivity values exceeding a predefined threshold are considered for grouping, as determined from the sensitivity matrix. An example of the DER grouping is shown in Figure 3.  
Table 1 presents an example of DER sensitivities for different monitoring buses. In this case, the sensitivity threshold is set to 0.01, meaning that only resources with sensitivity values equal to or greater than 0.01 are selected for grouping. If a resource exhibits sensitivity values above 0.01 for multiple monitoring buses, the resource is assigned to the group corresponding to the monitoring bus with the higher sensitivity value. For example, DER-2 has sensitivity values exceeding the threshold for both Monitoring Bus 1 and Monitoring Bus 2. However, since DER-2 shows a higher sensitivity value for Monitoring Bus 1, it is included in the group associated with Monitoring Bus 1. The final resource grouping results are shown in Table 2.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Resource** & **Monitoring Bus 1** & **Monitoring Bus 2** \\ \hline DER-1 & 0.008 & 0.04 \\ DER-2 & 0.02 & 0.01 \\ DER-3 & 0.04 & 0.05 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Sensitivity magnitude by monitoring bus.  
Figure 3: Grouping example.
## 6 Challenges and Future Directions
In terms of improving RISs' performance and capabilities, research efforts can focus on addressing RIS technology's current challenges. One approach is to develop new materials and fabrication techniques that enable high-performance and low-cost RISs. For example, using advanced nanomaterials such as graphene and carbon nanotubes can improve RIS properties, such as higher efficiency, larger bandwidth, and better controllability [82]. Additionally, developing new simulation and optimization tools can help optimize the design and operation of RISs for specific applications [74]. Another way to improve RISs is to investigate new concepts and architectures beyond the current RIS designs. For example, multi-functional RISs that can perform multiple functions such as sensing, imaging, and communication can significantly enhance the versatility and value of RISs [83]. In addition, incorporating artificial intelligence and machine learning techniques can enable RISs to adapt to changing environments and optimize their performance in real time [56]. On the other hand, exploring new applications and domains for RISs can lead to exciting and innovative uses of this technology. For example, RISs can be used in the emerging field of terahertz communications to enable high-speed and high-capacity wireless communication at terahertz frequencies [84; 85]. RISs can also be used in space applications such as satellite communication and sensing, where the high radiation environment and harsh operating conditions require robust and reliable technologies [86; 87]. Furthermore, RISs can be used in emerging smart cities and infrastructure areas. They can enhance the performance and efficiency of various systems such as transportation, energy, and communication [88]. RISs can also be used in the field of medicine and healthcare, where they can improve the accuracy and resolution of medical imaging and sensing systems [89; 90].
# EEMIP: Energy-Efficient Communication Using Timing Channels and Prioritization in ZigBee
## 4 Results and Discussion
### Evaluation of Scenario C
The data were measured at the coordinator devices (i.e., successfully received messages and lost messages). The measured data are provided in Table 10 and the comparison itself is given in Table 11. The \(S_{all}\) row refers to the processed and sent bytes in the simulated communications. The \(R_{all}\) row represents the amount of bytes successfully received and processed by the receiving device (i.e., without lost messages). The last row (\(R_{data}\)) represents the amount of successfully received bytes of data, i.e., without control overhead. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**End Device** & \multicolumn{2}{c}{**Nonbeacon ZigBee**} & \multicolumn{2}{c}{**EEMIP**} & \multicolumn{2}{c}{**EEMIP vs. Nonbeacon ZigBee**} \\
**ID** & **Bytes** & **Packets** & **Bytes** & **Packets** & **Bytes** & **Packets** \\ \hline  
*Average** & & & & & \(-\)40.20\% & +21.99\% \\ \hline \hline \end{tabular}
\end{table} 
Table 9: Comparison of the two simulation modes for a more realistic scenario. The result from this experiment is that the EEMIP method successfully transmits a higher amount of useful data by 20% on average during the same simulation time. The result is achieved by eliminating retransmissions of high-priority data, which are more frequent. This increases the communication efficiency, since the parameter of energy per successfully delivered data byte is increased. Another experiment using the same setup was targeted towards corner cases, in which either all the devices selected the low priority or all the devices selected the high priority for their data. Two congestion situations were simulated. The results of comparisons of EEMIP and nonbeacon ZigBee simulation results are provided in Table 12. The Low priority columns represent the cases in which only the low priority was used, and the High priority columns represent the cases in which only the high priority was used. Other data are represented analogously to Table 11.  
From the results, we can see that, although the higher priority data messages could not be preferred over the lower priority messages, the EEMIP method transmitted a higher amount of useful data by 12% in average. In both modes, approximately the same amount of messages were lost. However, in ZigBee, the lost data had to be retransmitted in a separated message, while in EEMIP, the next data message was used (reducing overhead). In most cases, the overhead of nonbeacon ZigBee retransmissions was higher than control overhead of EEMIP. In most cases, the EMIP mode sends less bytes and also less bytes are successfully received; however, the amount of successfully transmitted useful data were always higher in case of EEMIP (even though insignificantly in case of low priority and 2% packet loss).