esa-sceva/satcom-chunk-collection huggingface dataset:
# A Novel RPL Algorithm Based on Chaotic Genetic Algorithm
## 3 RPL-Cga
### Selecting Preferred Parents  
Based on Section 3.6, in the candidate parents set, the one with the lowest value of Equation (19) will be chosen as the preferred parent (the next hop), except for in the following situations:  
1. According to Equation (19), if the value of current preferred parent is greater than the value of one candidate parent, but the difference between them is less than the preferred parent change threshold, then the current preferred parent will not be changed.
2. If the calculated value of Equation (19) is greater than 100 or less than 1, then the corresponding candidate parent must be removed from the candidate parent set.
3. If several candidate parents have the same minimum calculated values of Equation (19), then an additional metric named as NSA (Node State Attribute, NSA) will be considered to choose the next hop among these several candidate parents.
4. According to Equation (19), if the value of the current preferred parent is equal to the minimum value, and there are several candidate parents also with the minimum value, then the node still uses its current preferred parent.
5. If node \(c\) only has one candidate parent, then \(c\) should wait for some time to receive DIO messages broadcast by other nodes to determine whether there are other nodes that will become its candidate parents. After that, if \(c\) has two or more candidate parents, \(c\) selects a preferred parent through RPL-CGA algorithm. Otherwise, if c still has one candidate parent, it directly selects only one candidate parent as its preferred parent without executing the RPL-CGA algorithm.
# Genetic Variants in Patients with Premature Ovarian Insufficiency in a Mexican Cohort
## 3 Results
### Mutation Screening  
From the PCR-SSCP assays, I identified 13 genetic variants in six (_WT1_, _NR0B1_, _NR5A1_, _LHX9_, _ZNF275_, and _NRIP1_) of the eight candidate genes. Figure 2 illustrates the molecular identification of four genetic variants in the _WT1_ gene (exon 1b: three different SSCP patterns, exon 1e: two different SSCP patterns, exon 3: two different SSCP patterns, and exon 7: three different SSCP patterns); two genetic variants in the _NR0B1_ gene (exon 1b: two different SSCP patterns and 1c: three different SSCP patterns); two genetic variants in the _NR5A1_ gene (exon 4b: two different SSCP patterns and intron IV: three different SSCP patterns); three genetic variants in the _LHX9_ gene (intron II: two different SSCP patterns, intron III: three different SSCP patterns, and exon 4: two different SSCP patterns); one genetic variant in the _ZNF274_ gene (exon 3: two different SSCP patterns); and one variant in the _NRIP1_ gene (exon 1r: two different SSCP patterns); while no variations were detected in the _ZFP92_ and _INSL3_ genes.  
Figure 1: Representative banding patterns for the _WT1_ (NM_024426.6), _NR0B1_ (NM_000475.5), _NR5A1_ (NM_004959.5), _LHX9_ (NM_020204.3), _ZF92_ (NM_001136273.2), _ZNF275_ (NM_001080485.4), _INSL3_ (NM_001265587.2), and _NRIP1_ (NM_003489.4) genes. All exons were amplified by (\(\alpha\)-\({}^{32}\)P)-dCTP-PCR, and one representative exon is shown for each gene. The arrows indicate 500 bp, and 100 bp indicates the molecular weight marker (100–1500 bp). C1 and C2 are unrelated healthy subjects. P1–P11 are patients clinically classified with POI. The expected sizes for the amplified exons are shown on the right.  
Figure 2: Genetic variants identified using (\(\alpha\).\({}^{32}\)P)-dCTP-PCR-SSCP analysis of the _WT1_ (NM_024426.6), _NR0B1_ (NM_000475.5), _NRSA1_ (NM_004959.5), _LHX9_ (NM_020204.3), _ZNF275_ (NM_001080485.4), and _NRIP1_ (NM_003489.4) genes from patients with POI (P) and healthy subjects (C). Different SSCP patterns are marked by asterisks. Heterozygous and homozygous subjects are indicated by two and one asterisks, respectively.
# Hybrid Chirp Signal Design for Improved Long-Range (LoRa) Communications
## 4 Proposed Modulation Scheme  
In previous studies, it was shown that the chirp signal design based on joint up and down chirps always exhibits better performance compared to the chirp signal composed of either only up- or down-chirps. For example, in the context of indoor positioning, the scheme based on joint up- and down-chirps provides better location accuracy than the one based on only either up- or down-chirp schemes. Motivated by this, we propose a LoRa modulation scheme using both up- and down-chirps in contrast to the conventional either up- or down-chirp approach. In our proposed scheme, we represent the first half of the \(2^{\mathcal{S}}\) bit combinations with up-chirp based signals, while the rest of the combinations are represented by down-chirp based signals. With the proposed scheme, the instantaneous frequency of \(k^{th}\in\{0,2^{\mathcal{S}}-1\}\) symbol is given by  
\[f_{x_{k}}(t)=\begin{cases}f_{l}+\frac{kB}{2^{\mathcal{S}-1}}+\frac{B}{T}t& \text{if $t\leq\tau_{k_{u}}$ and $k<2^{\mathcal{S}-1}$}\\ f_{l}+\frac{kB}{2^{\mathcal{S}-1}}-B+\frac{B}{T}t&\text{if $t>\tau_{k_{u}}$ and $k<2^{ \mathcal{S}-1}$}\\ f_{h}-\frac{kB}{2^{\mathcal{S}-1}}-\frac{B}{T}t&\text{if $t\leq\tau_{k_{d}}$ and $k\geq 2^{ \mathcal{S}-1}$}\\ f_{h}-\frac{kB}{2^{\mathcal{S}-1}}+B-\frac{B}{T}t&\text{if $t>\tau_{k_{d}}$ and $k\geq 2^{ \mathcal{S}-1}$},\end{cases} \tag{7}\]  
where \(\kappa=mod(k,2^{\mathcal{S}-1})\), \(\tau_{k_{u}}=T-\frac{kT}{2^{\mathcal{S}-1}}\), and \(\tau_{k_{d}}=T-\frac{kT}{2^{\mathcal{S}-1}}\). With the above specifications, a simple example of the proposed LoRa modulation (for \(\mathcal{S}=2\)) scheme is shown in Figure 2.
## 5 Conclusions  
Taking Yunnan as an example, this study investigated the prevention and control of flash floods in mountainous cities. In the research, we utilized the data from investigations and evaluations of flash flood disasters. The adopted method can rapidly iterate the results of the prevention and control zoning, along with updating the results. Before the flood season arrives each year, the flood control department could focus on investigating and rechecking the number of people affected by flash floods in high-risk and medium-risk river basins, update the results of the prevention and control zoning in a timely manner, and clarify the key points of flood control work. For example, under the current data conditions, the results show that 8% of the land area in Yunnan is a key flash flood prevention and control zone, and 29% is a medium flash flood prevention and control zone. These areas are predominately distributed in the central and northeastern regions of Yunnan, and the main cities involved are Dehong, Kunming, Yuxi, and Zhaotong. The combined area of key and medium prevention and control zoning for flash floods in these four cities exceeded 50% of the urban administrative area. Key flood control and hydrological monitoring should be carried out in these cities during the flood season, such as checking and removing water obstructions in river channels in advance, and ensuring that rainfall monitoring equipment can operate normally. For villages with flood control levels lower than the five-year recurrence period, the flood control level of villages along rivers should be enhanced as a priority. If necessary, residents can be organized to evacuate in advance based on the forecast of precipitation.  
In December 2023, the Ministry of Water Resources of the People's Republic of China promulgated technical requirements for a supplementary survey and evaluation of flash flood disasters, which indicates that the results of flash flood disaster investigations and evaluations are constantly updated and improved. The research method adopted in this study can be used to constantly update the prevention and control zoning for flash floods according to the results of flash flood disaster investigation and evaluation while also providing a reference for flash flood disaster prevention and control in mountain cities in the context of accelerating urbanization.  
Conceptualization, Z.Z. and Q.L.; methodology, C.L.; software, Z.Z.; validation, Q.L.; formal analysis, Z.Z.; investigation, Q.L.; resources, Y.C.; data curation, Y.C.; writing--original draft preparation, Z.Z.; writing--review and editing, Z.Z. and Q.L.; supervision, C.L.; project administration, Y.C. All authors have read and agreed to the published version of the manuscript.  
This research was supported by the National Key R&D Program of China (2023 YFC3006705).  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.  
**Conflicts of Interest:** The authors declare no conflicts of interest.
## 5 Conclusions  
In conclusion, this study has demonstrated the effectiveness of using a medium spatial resolution satellite constellation to monitor vegetation dynamics in U.K. woodlands. The results produced from the DMC imagery used in this research concur with those found in other similar studies using medium spatial resolution imagery. The potential advantage of using a constellation of satellites is in the frequency of observation that is possible. Constellations allow daily and even sub-daily observation of a study area [65], which, in temperate regions, would increase the potential to get cloud-free imagery. Frequent observations are vital for measuring phenological events. Here, nine cloud-free DMC images were identified for the study period, compared with only three images from Landsat. As discussed earlier, the nine DMC images represented a subset of the potential images, at least one a day, which might have been available if the DMC satellites had been tasked to continuously collect imagery of the U.K. This research has also shown that the spectral bands available from the DMC instruments have the potential to produce spectral indices that may be used to estimate LAI. Further work is required to look at how the temporal variations in LAI estimated from DMC relate to phenological events, and a greater frequency of images over the growing season would allow that.  
DMC International Imaging Ltd. (DMCii) and the Nigerian National Space Research and Development Agency (NASRDA) are acknowledged for providing the DMC data; [PERSON] (DMCii) kindly assisted in identifying suitable imagery and provided technical assistance. Risley Moss Local Nature Reserve is acknowledged for allowing access to the field site and providing logistical support for the field measurements.  
[PERSON] conducted the fieldwork and image processing as part of his PhD research under the supervision of [PERSON] and [PERSON]. For the initial draft of the paper [PERSON] prepared the introduction and methods sections, [PERSON] designed the results and discussion sections and [PERSON] produced the Figures. [PERSON] was responsible for responding to the comments of the referees and co-ordinating the revisions to the paper.
# Measurement of Bridge Vibration by UAVs Combined with CNN and KLT Optical-Flow Method
## 4 Experimental Results and Analysis
### Comparisons for DIC and KLT Method  
The displacement results of the bridge model measured by fixed camera are showed in Figure 11, which demonstrates that the displacement time-history curves obtained by the DIC and KLT optical-flow method have very similar characteristics of free-vibration attenuation, and the maximum amplitude is about 5.7 mm. The ideal displacement curve \(x^{\prime}(t)\) can be obtained by smoothing the displacement time-history curve \(x(t)\) through locally weighted regression (LOWESS [38]). The difference between \(x(t)\) and \(x^{\prime}(t)\) is the error curve, and the average of the error curve reflects the smoothness of the displacement time-history curve measured by the DIC or KLT optical-flow method, which is defined as SDTH in this paper. The SDTHs of the DIC and KLT optical-flow method are 0.048 and 0.031, respectively. In addition, the displacement time-history curve obtained by DIC has obvious burrs, which illustrates its low measurement accuracy. In contrast, the displacement diagram obtained by the KLT optical-flow method is smoother, indicating that DIC is not as accurate as the KLT optical-flow method.  
Figure 10: Process of displacement correction by CNN.  
As shown in Figure 12, it is the displacements of the static point on the model measured by the fixed camera and obtained by the DIC and KLT optical-flow method. Theoretically, the curve should be a straight line with displacement of 0, so that the standard deviation (STD) of the curve can reflect the accuracy of the two methods. The STDs of the DIC and KLT optical-flow method are 0.075 and 0.061, respectively, which indicate that the KLT optical-flow method is more accurate than DIC.  
Figure 11: Measurement results of vibration model with fixed camera: (**a**) results of DIC; (**b**) results of KLT optical-flow method.  
Figure 12: Displacements of the static point obtained by the DIC and KLT optical-flow method.  
The displacement signals in Figure 11 are processed into PSD curves. The peak of the PSD curve corresponds to the natural first frequency of the model, as shown in Figure 13. It can be seen from the figure that the natural frequencies extracted by the two methods are 3.281 Hz and 3.282 Hz, respectively, and the relative error is 0.03%. It shows that the KLT optical-flow method is feasible to replace DIC to extract the natural frequency of the structure under fixed camera.
## 2 Materials and Methods
### Gapped Microstrips
A microstrip line for analysis purposes was designed, and the S11 parameters and impedance values were extracted. Figure 1c shows the microstrip model used for this analysis, with the close-up area showing the gap size s and the distance d. The size of the gap was changed from 0.5 to 5 mm in intervals of 0.5 mm, while the distance from the gap to the source point was maintained at 2 mm. We extracted the reflection coefficients and impedance values, as shown in Figure 2a,b, respectively. From the reflection coefficient S11 parameters, it can be seen that the gap length influences the resonance frequency. It is expected from Equations (2)-(4) that the series capacitance decreases as the gap size increases, and the resonance frequency is then shifted toward higher frequencies. A second consideration for our application in MRI is that the 1B1 field should be uniform along the y-z plane, which is important for producing uniform images. For this purpose, we used the microstrip model in Figure 1c to move the position of the gap d along the strip line. The position d of the gap was changed at two different r  
Figure 2: The effects of the microstrip line to different gap size, (**a**) the S11 parameters and (**b**) the impedance. The effects of moving the gap along the microstrip, (**c**) the S11 parameters and (**d**) the 1B1 field profile along the microstrip. the position was moved from 0 to 10 mm in 10 steps and for the second, the position was moved from 20 to 86.7 mm in another four steps. For this analysis, we extracted the S11 parameters and the \(\mid\)B\({}_{1}\mid\) field profile at the center of the line along the y-z axis. Figure 2c shows the S11 parameters of the microstrip line when the gap is moved at different positions along the line. In this case, the resonance frequencies shifted to higher frequencies when the gap was moved to the end of the line. This can be used for further tuning the microstrip to the desired frequency. However, the field uniformity is affected by the discontinuity of the gap, as show in Figure 2d, which plots the \(\mid\)B\({}_{1}\mid\) field profiles at the center of the conducting line and along the z-y plane. We only included selected plots of the distance in order to provide a better visualization. As shown in Figure 2d, the field is distorted as the gap is moved further into the line. Based on this analysis, we chose to use a gap size of 0.5 mm, with the gap as close to the source as possible.
# Information-Centric Network-Based Vehicular Communications: Overview and Research Opportunities
## 5 ICN-Based VANET Research Opportunities
### ICN-Based VANET Routing  
ICN considers in-network caching- an approach that encompasses replicas of the accessed contents in the process of data routing [9]. An in-network node in ICN can satisfy subscribers' content requests by looking for those particular sources where the contents are cached. Once content is delivered to the requested subscriber, a path between the content publisher and subscriber, and a specific interface from which the request was received, are recorded for the execution of future requests [42]. This path is recorded by looking at the network condition. The contents in ICN are accessed through names rather than IP addresses, which help in combining requests for a specific content and enable its provision to the corresponding subscribers through multicast forwarding mechanisms.  
However, this forwarding in the VANET environment raises more challenges due to instant mobility of caching sensors (vehicles). Thus, the research community is encouraged to design forwarding mechanisms by considering mobility and caching modules for the swift transmission of content objects.
# FL-SDUAN: A Fuzzy Logic-Based Routing Scheme for Software-Defined Underwater Acoustic Networks
## 5 Experimental Results and Analysis
### The Packet Delivery Rate  
The packet delivery rate is a fundamental merit of a routing protocol. The PDR of LEACH, EEHC, [PERSON]'s algorithm, FPO-MST, and FCO-MST in different rounds is shown in Figure 9. The PDR of all five algorithms tended to decrease as the number of rounds increases. When runtime increased, some nodes died. Therefore, the network connectivity became worse. FPO-MST and FCO-MST use triangular fuzzy logic to estimate the optimal path weights between CHs. Consequently, they had a higher PDR. Due to re-clustering, FCO-MST had the highest PDR before round 43. After this period, the dead nodes increased dramatically. As a result, many new CHs were selected and the size of the spanning tree increased. As a result, FPO-MST had the highest PDR.  
We compared the PDR with a different number of nodes, as shown in Figure 10. The PDR tended to increase with increasing DNs. EEHC is a cluster-based routing algorithm that combines the depth of the DNs and the residual energy. Therefore, the PDR was  
\begin{table}
\begin{tabular}{c c c c} \hline
**Parameter** & **Value** & **Parameter** & **Value** \\ \hline Control channel model & Rayleigh Fading [40] & Data channel model & Rice Fading [41] \\ Noise type & Complex Gaussian & Underwater signal rate & 2000 bps \\ Carrier frequency & 10 kHz & Size of data Packet & 6400 bits \\ Size of control package & 200 bits & Power of clustering & 200 mW \\ Threshold of delay & 0.01 & Power of data communication & 300 mW \\ Threshold of PDR & 0.005 & Power of control & 500 mW \\  & & communication & \\ Threshold of reselecting CH & 0.35 & Power of the receiving & 100 mW \\ Duration of the sequence & 5 ms & Power of sleep & 50 mW \\ \hline \end{tabular}
\end{table}
Table 4: Experimental parameters.  
Figure 9: PDRs vs. rounds.  
relatively high. [PERSON]'s algorithm also uses a clustering architecture with a small square structure, so the PDR was relatively low. On the contrary, LEACH had the lowest PDR. Since the number of single-node clusters may increase after running for a while, the routing efficiency decreased sharply. When the number of DNs increased to 140, the PDR of FCO-MST was higher than that of FPO-MST. Thus, FCO-MST is more suitable for large-scale hydroacoustic networks.
# Blockchain-Based Distributed Patient-Centric Image Management System
## 5 Evaluation
### PCIM System Analysis
#### 5.3.3 Transaction Efficiency  
We performed the efficiency analysis of the PCAC-SC based on transaction storing time and gas consumption. The multi-bar graph in Figure 11 reports the deployment and execution time of PCAC-SC in Ethereum testnet using five different patients' Ethereum address. It is noted that storing _create_contract()_ events takes more time than deploying the SC and storing the events of _requesting_access()_, _approve_IRs()_, _remove_IRs()_, and  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Function** & **Gas Used** & **Actual Cost(ether)** & **USD** \\ \hline _create\_contract()_ & 67,394 & 0.000134788 & 0.025 \\ _requesting\_access()_ & 246,908 & 0.000493816 & 0.093 \\ _approve\_IRs()_ & 170,412 & 0.000340824 & 0.064 \\ _trace\_authorization()_ & 34,266 & 0.000068532 & 0.013 \\ _remove\_IRs()_ & 59,358 & 0.000118716 & 0.022 \\ \hline \hline \end{tabular}
\end{table}
Table 1: PCAC-SC Cost Analysis (gasprice = 2 Gwei, 1 ether = 187 USD).  
Figure 10: Showing the Average Time Taken to Upload and Download the Medical Images of Various Sizes by the Proposed and Conventional PACS Storage in Seconds (s). The Bar Graph Represents the Download Time and the Line Graph Represents the Upload Time of the Two Systems. The Dashed Lines Represent the Numerical Data Labels of the Line Graph.  
trace_authorization()_ functions. Our results show that most transactions were validated and written into a block within 4.98-16.97 s. The access granting process took in significantly less time than the rest of the functions. Figure 12 shows the gas used for storing a number of transaction events in the blockchain and its block size. It has been noted that maximum gas (66.94%) was consumed by the fourth transaction since the block size is high (20,629 bytes). The minimum gas (8.85%) was consumed by the seventeenth transaction, while the block size is low (3485 bytes). We observed that gas consumption increases and decreases based on the block size. Furthermore, the analysis shows that gas consumption decreases as the number of transactions increases. Gas consumption percentages in our experiment were varying but reasonably stable. Thus, the above analysis shows that the proposed scheme outperforms in terms of average time and gas consumption to store the events in the blockchain.