esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Materials and Methods
### Data Analysis Methodology
#### 2.5.1 Convolutional Neural Network (CNN)  
A convolutional neural network (CNN) architecture was designed based on previously reported studies, with some modification [28, 48, 49]. The proposed and developed network is divided into three major blocks (Figure 3). This architecture, shown in Figure 3, shows the CNN backbone, which consists of the ResNet50 and FPN, the feature maps leading to the region proposal network, and the region of interest (RoI) alignment. Subsequently, from the RoI, there are the connected layers with classifications and the bounding box, finally producing the masks from the fully convoluted networks. Moreover, in order to achieve the aim of determining the pesticide residue coverage on the citrus leaves, a more specialized Mask-Region-Based CNN was integrated in this work [50].  
The mask R-CNN is widely known for its ability to effectively perform instance segmentation, which is particularly helpful in this project for the object detection process and the creation of a mask for each instance [51]. This capability aligns with the project aims of distinguishing multiple objects (e.g., leaves) appearing in a single image. Conversely, a recent model, YOLOv11 [52], was considered for the object detection, instance image segmentation, and image classification. This model builds on a previous version of YOLO [53] to achieve higher accuracy rates with the addition of enhanced instance image segmentation and advanced data augmentation. Nevertheless, mask R-CNN can provide higher performance than YOLOv11 in scenarios in which accurate instance segmentation is required. Since YOLOv11 is more applicable to driving, object tracking, and surveillance [52, 54], the mask R-CNN was selected as a more suitable alternative considering the project's objective, its higher accuracy, and the widely established applicability to image analysis and robotic vision [55, 56, 57].
# Photocatalytic Lithography
## 4 Applications of Direct and Remote Photocatalytic Lithography
### Patterning of Metal Surfaces and Sculpturing of Metal Nanoparticles  
The reactive oxygen species generated by both the direct and remote approach are active not only towards organic molecules but also towards inorganic species. For example, by means of photocatalysis, metal surfaces can be oxidized and metal salts can be reduced. Thus, photocatalytic lithography can be considered an efficient dry technique to generate metal patterns. A great advantage offered by photocatalytic lithography is the possibility to generate metallic elements, such as current-conducting paths, microelectrode assemblies, and other circuit elements, as well as catalytic surfaces for growing carbon nanotubes on large substrates without the need to use photoresists and vacuum evaporation. The feasibility of deposition of a variety of noble metals (including Ag, Pd, and Cu) onto the surface of semiconductor oxides during photocatalytic reactions promoted by UV irradiation allows the formation on the exposed areas of catalytically active metal sites, which, in turn, can mediate the subsequent electroless deposition of various metals from solutions containing metal ions and reducing agents. A high selectivity of electroless deposition on the surface photoactivated in such a manner ensures the fabrication of metal patterns with a resolution of a few micrometers [46]. The site-selective deposition of quantum dots onto nanocrystalline TiO\({}_{2}\) films has been reported by [PERSON] et al. [47]. Quantum dots of cadmium sulfide and selenide (CdS and CdSe) were attached to the oxide surface through bifunctional mercaptoalkanoic acid linkers, which were subsequently degraded by means of photocatalysis, leading to a patterned surface.  
Recently, [PERSON] et al. demonstrated that silver triangular nanoprisms [48] self-assembled on a titanium dioxide surface can be partially dissolved and reshaped by means of direct photocatalysis [49]. Upon UV light irradiation, the nanoprisms underwent a rapid (5 min) dissolution process, which led to particles reshaping into spheroids or discoids. The results obtained during experiments with hole scavengers, such as ethanol, gave evidence that this photocatalysis-induced shaping process may be mediated by photogenerated holes. Eventually, patterns which displayed a remarkably different Surface-Enhanced Raman Scattering (SERS) behavior were obtained, with promising applications for sensor development (Figure 7).
# Lightweight Robust Image Classifier Using Non-Overlapping Image Compression Filters
## 3 Materials and Methods
### Overlapping and Non-Overlapping Processes  
The data transmission methods of the two different image filters are shown in Figure 3b,d. In the overlapping image filter, one pixel \(x\) in the input image is calculated using three pixels \(l_{2},l_{3},\) and \(l_{4}\) in the filter layer if the size of the receptive field is \(1\times 3\). In other words, pixel \(x\) can affect the three pixels in the filter layer. But in the non-overlapping image filter, pixel \(x\) only affects one pixel \(l^{{}^{\prime}}_{1}\) in the filter layer. If adversarial noise is carefully added to pixel \(x\), the adversarial noise is likely to be transmitted to the filter layer in the overlapping image filter, but it is ignored in the non-overlapping image filter.  
In the overlapping filtering operation, the size of the input image is the same as that of the output image. However, the non-overlapping filter method can lead to a reduction in the size of the output image. However, whether processed by \"overlapping\" or \"non-overlapping\" filters, the labels of the images always maintain their original labels. The size of the receptive field is \(2\times 2\).  
Figure 4 presents a comparison of the valid and adversarial sample sets of the overlapping and non-overlapping filters on the MNIST dataset. In undisturbed images, both filters can extract the shape of the original image. However, in adversarial images, the situation is different. The image processed by the overlapping filter not only retains the shape of the adversarial image but also amplifies the adversarial noise. In contrast, images processed by the non-overlapping filter effectively eliminate most of the adversarial noise. We have chosen to use the non-overlapping image filter for our research.
## 3 Multi-Hop IoT Systems for Patient Monitoring
### Multi-Hop Communication Networks for Patient Monitoring  
Multi-hop communication networks offer transformative possibilities for enhancing patient monitoring systems within the medical sector. By employing a multi-hop approach, health-monitoring devices can seamlessly communicate across extended distances, presenting a paradigm shift in how healthcare data are collected and transmitted [33].  
In the medical sector, where patient monitoring is often distributed across various locations, multi-hop communications plays a pivotal role in overcoming geographic constraints [34]. This approach facilitates the creation of interconnected networks, enabling health monitoring devices to communicate through a series of intermediate nodes. As a result, even in geographically dispersed environments, healthcare providers can obtain real-time data from patient monitoring devices, fostering a comprehensive and continuous health surveillance system.  
Moreover, the reliability and redundancy inherent in multi-hop architectures significantly contribute to improved patient care. In scenarios where a direct communications link may face disruptions or interference, the multi-hop network dynamically reroutes data through alternative paths, ensuring uninterrupted transmission. This redundancy is crucial  
Figure 6: Remote monitoring via IoT healthcare systems.  
for critical health data, where timely and continuous monitoring is imperative for effective decision making.  
The scalability of multi-hop communications is particularly advantageous for the medical sector. As healthcare facilities expand or integrate new monitoring devices, the multi-hop architecture accommodates these additions seamlessly, without requiring a direct connection to a central hub [35]. This scalability aligns with the evolving nature of healthcare demands, allowing flexible and efficient system growth.  
The application of multi-hop communications in patient monitoring holds immense potential for revolutionizing healthcare. It addresses geographic challenges, enhances reliability, and offers scalability, ultimately contributing to the creation of robust and responsive health monitoring systems in the medical sector [36].
## 4 Results and Discussion
### Simulation Results Analysis  
In this section, the simulation results of the three-stage SST are shown. The source voltage, source current, load voltage, load current, and DC-link voltage after completion of SST simulation are shown in Figure 10. The behavior of the input remains the same, even if the load side transient is disturbed. Thus, SST provides excellent isolation through the DAB converter and maintains the same phase angle at the input stage.  
Figure 10: _Cont._  
Figure 9: Output stage (**a**) Bode plot, (**b**) Nyquist plot, (**c**) Nichols plot, (**d**) Root locus, (**e**) Pole–zero plot, (**f**) Eigen plot.
# Toward Sustainable Development: Exploring the Value and Benefits of Digital Twins
## 2 Background
The realms of IoT and DTs overlap when it comes to describing, discovering, and accessing resources [47]. This is conceptualized on five layers, starting from physical space, communication network, virtual space, data analysis and virtualization, and ending with the application layer [48]. In the case of the first layer, the naming of objects is typically associated with the word \"smart\" when IoT comes into action; hence, numerous studies have already discussed smart buildings [49], smart enterprises [50], smart factories [51, 52], smart farming [53], smart grid [54], smart health [55], and smart transportation [56], to name a few. In recent years, significant advancements in mobile and wireless technologies have enabled many applications beyond traditional voice and video calls on mobile phones [57]. Digital Twin solutions are no exception to this trend. One of the main assumptions underlying the design of Digital Twins is reliability [58], which implies that twins are synchronized in real-time with their physical counterparts by receiving actual data with low latency. Data from physical entities are collected through Data Acquisition Systems (DAC) deployment [59] equipped with sensors, measurement devices, and computers [60]. The concept of a Digital Twin is not merely a passing trend from a business perspective. Even industries such as aviation and wind turbine manufacturing, which traditionally have little to do with digitization, have embraced the latest technological advancements and adapted their existing systems and procedures to incorporate Digital Twins. Recently, the term Digital Twin is often used to refer to the latest wave of computer modeling and simulation, which aim to develop digital representations of real-world objects, systems, or processes. Ultimately, the application of Digital Twins is expected to lead to significant time and cost savings [61].
# Static Evaluation of a Midimew Connected Torus Network for Next Generation Supercomputers
## 4 Comparative Static Network Performance Evaluation
### Wire Complexity  
Wire complexity refers to the total number of wires required to implement the network topology. It depended on the node degree, since it identified the wires exiting a node. Although wire complexity was not an actual cost of the network configuration due to physical routers and the length and wire types used, it provided a reliable indicator of resource demand. The greater the number of wires that were needed, the more cost was required for physical resources. However, costs could be justified according to their contributions to low latency and high fault tolerance, and even lower the costs of the overall network, that is, they could elicit a better performance in terms of the connectivity between nodes and hierarchal levels. The MTN had better performance on this parameter, as compared to the TFBN, due to having lower wire complexity for physical links, improving its scalability and affordability. Finally, Figure 8, below, is used to show the wire complexity of various networks in comparison with MTN when the network size increases.  
Figure 7: Bisection width of various networks when increasing the network size.  
This evaluation indicated the most important parameters for the implementation of a practical supercomputer. The best adaptation of the parallel processing environment would require some compromises in terms of robustness versus costs. For example, given the high probability of faults when scaling is regularly conducted, the reasonable costs of the flexible MTN makes it a better choice than the TFBN, which could become quite expensive under these circumstances. However, a TTN could provide simpler and less costly scaling, as compared to an MTN. In contrast, MTNs have better inter-node communication with respect to average message transfer latency due to the lower average distance. According to the above comparison, MTNs have better fault tolerance, enhanced cost-efficient scaling, improved inter-node communication, and fewer physical wires, as compared to other HINs with similar features.
# Experimental Investigation of Mechanical Properties of Clay-Cement Slurry Containing Graphene Oxide
## 3 Results
### Anti-Permeability Performance of Grouting Reinforcement
#### 3.2.1 Range Analysis of Permeability Coefficient Test  
To evaluate the effects of OPC content (Factor A), GO content (Factor B), and gradation (Factor C) on the permeability coefficient of the slurry-stone body, range analysis was  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Number** & **OPC/\%** & **GO/\%** & **Gradation** \\ \hline I & 30.0 & 10 & 19.6 \\ II & 68.2 & 10 & 19.6 \\ III & 33.9 & 10 & 19.6 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Gravel grouting test specimen ratio.  
performed on nine sets of experimental results. The range analysis results are listed in Table 6.  
In the table above, \(Q_{i}\) represents the experimental index for the range analysis level; \(R\) is the range of variation in the experimental index. The larger \(R\) is, the greater the impact of the factor on the experimental index. The magnitude of \(R\) can also be used to determine the importance of the factors.  
According to Table 6, the order of factors affecting the permeability coefficient of the grout-strengthened stone body is OPC content > GO content > gradation. Each factor has a certain influence on the permeability coefficient of the grouted stone body. Among these factors, the OPC (ordinary Portland cement) content has the most pronounced effect on the permeability coefficient of the grout-strengthened body. Following that, the GO (graphene oxide) content has a significant impact, while the gradation of materials has the weakest influence on the permeability coefficient of the grout-strengthened body. The research results show that when each factor changes, the permeability coefficient of the grout-strengthened body decreases with the increase in OPC content and GO content. Among all the influencing factors, the permeability coefficient of the grout-strengthened body fluctuates greatly under the influence of OPC content, followed by GO content, and is least affected by formation conditions.
## 2 Results and Discussion
### Candidate Genes Involved in the Biosynthesis of Triterpenoid Saponins
#### 2.2.3 P450s  
Following the formation of amyrin, functional groups, such as hydroxyl and carboxyl, are introduced at different positions of the backbone, and this reaction is catalysed by the P450s (EC 1.14.x.x). This step contributes to increasing structural diversity [27, 28]. As in the hypothesis described in Figure 1, CYP450s of C19-oxidase and C28-oxidase are essential for modifying \(\alpha\)-amyrin during the formation of pomolic acid, which is an important intermediate compound. Dehydration of pomolic acid yields a second double bond, in addition to the first bond at C12-C13. This reaction might be catalysed spontaneously or by a dehydrase(s). Through either method, the dehydration of pomolic acid gives rise to radialic acid, 19-dehydrousolic acid and 19(29)-dehydrousolic acid, which are precursors of skeletons A, B and C, respectively. Moreover, isomerisation of these three precursors might take place spontaneously or mediated by isomerase. Further, C23-oxidase and C24-oxidase are necessary to form skeleton D. In brief, it is expected that these oxidisations are catalysed by P450s. The P450s is one of the largest and most diverse gene families in plants [29, 30]. To date, only a few P450s have been identified as involved in triterpen biosynthesis. CYP93E1 from _G. max_ was the first one characterised, and catalyses the C24-hydroxylation of \(\beta\)-amyrin [31]. CYP93E3 in liquorice exhibits a similar catalytic activity as CYP93E1 [32]; and CYP716A12 in _M. truncatula_ and CYP716 AL1 in _C. roseus_ were characterised as multifunctional enzymes with \(\beta\)-amyrin 28-oxidase,  
Figure 6: PCR products of amplified CL3079.contig1 (A) and CL481.contig1 (B).  
\(\alpha\)-amyrin 28-oxidase and lupeol 28-oxidase activities [27,33]. In the transcriptomic data, 269 unigenes were annotated to be P450s. BLASTp analysis using the above-mentioned characterised genes as queries against the transcriptome narrowed down the potential unigene number. Ten unigenes (CL1221.Contig1 to 3, CL3010.Contig1 to 4, unigene10591, unigene23155 and unigene25510) were highly homologous to CYP716A12 and CYP716 AL1, with peptide sequence identities of more than 55%, which implies that they may belong to the same subfamily, according to the assignment of P450s to families and subfamilies developed by [PERSON] [34]. In addition, CL410.Contig1 exhibited 49.22% and 51.07% sequence identity to CYP93E1 and CYP93E3, respectively, which was coincident with the KEGG annotation. These P450s are shown in Table S5.
# Secure D2D Group Authentication Employing Smartphone Sensor Behavior Analysis
## 7 Performance Analysis
### Communication Cost  
In this section, the required communication rounds for the D2D authentication in SN side is analyzed, where totally \(t\) UEs are assumed to be authenticated. In our design, for each UE, only 3 rounds are required for the entire authentication process, where the offline registration phase is not included. Hence, the total communication rounds involving \(t\) UEs is \(n+2\) in our design, where the authenticating request and the final group key distribution message are through one broadcast operation. Accordingly, the comparison result on communication cost is given in Table 5, demonstrating that less communication rounds are conducted in our scheme comparing with the state-of-the-arts.
## 3 Accuracy Verification of the Analytical Solution  
### Selection of Feature Parameters  
For the calculation model of FSPR in Figure 3, since the freezing tubes are periodically arranged, take an A-type freezing tube and a B-type freezing tube adjacent to the x-axis as research objects. Taking the origin of coordinates as the center of the circle, select the fan-shaped area as shown in Figure 6 for calculation.  
Select the x-axis direction (main section, \(\theta\) = 0), between two pipes (Section 1, \(\theta\) = \(-\beta/2\)), and the sector boundary (Section 2, \(\theta\) = \(\pi\)/n \(-\)\(\beta/2\)) as the three characteristic sections for temperature calculation, \(\xi_{1}\) and \(\xi_{2}\) are the inner and outer frozen curtain thicknesses, respectively.  
Based on previous freezing engineering experience, six groups of freezing parameters are selected for calculation. The value range of freezing tube circle radius \(R_{2}\) is 2.5-10.0 m; value range of jacking pipe diameter \(D\) is 0.8-2.0 m; value range of the frozen pipe radius \(R_{0}\) is 0.06-0.16 m; value range of \(\xi_{1}\)/\(\xi_{2}\) is 1-1.2; temperature of the freezing tube wall \(T_{f}\) is \(-\)30 \({}^{\circ}\)C; value range of the frozen soil boundary temperature is \(T_{0}\) \(-\)1.5-0 \({}^{\circ}\)C; frozen tube parameters, such as \(n\) and \(\beta\) are shown in Table 1:
# 3D Printed High Gain Complementary Dipole/Slot Antenna Array
## 4 Conclusions  
A 3D printed planar high gain 16 \(\times\) 16 antenna array using the complementary dipole concept has been demonstrated in this paper. Both measured and simulated results agree well. Fabrication of an array using 3D printing, spraying and electroplating is presented. The advantage of a 3D printed array is the low cost and light weight in comparison to a metallic version. The 3D printed array weights only 0.35 kg. The basic radiating unit is constructed by the standard rectangular slot element and the two top-mounted metallic cuboids. A parallel waveguide feeding network with equal amplitude and equal phase characteristics was utilized due to its wideband feature. Combining the wideband complementary dipole radiating unit and the wideband feeding network, the 3D printed array has 14.8% impedance bandwidth for reflection coefficient \(\leq\)\(-\)15 dB in a 28 GHz band. Around a 32 dB gain for the operating band with broadside radiation was achieved. Together, these results suggest that the proposed array is suitable for 5G wireless communication applications.  
K.K.S. is responsible for the antenna design, fabrication, measurement and manuscript preparation. K.M.L. is responsible for the antenna design and manuscript preparation. C.H.C. is responsible for the 3D antenna fabrication technique and manuscript preparation. K.F.C. is responsible for the 3D antenna fabrication and manuscript preparation.  
This research received no external funding.  
The authors declare no conflict of interest.  
Figure 4: Measured and simulated performances of the 16 \(\times\) 16 complementary dipole antenna array: **(a)** reflection coefficients; **(b)** gains; **(c)** radiation patterns on phi = 0\({}^{\circ}\) at 25.74 GHz; **(d)** radiation patterns on phi = 90\({}^{\circ}\) at 25.74 GHz; **(e)** radiation patterns on phi = 0\({}^{\circ}\) at 27.80 GHz; **(f)** radiation patterns on phi = 90\({}^{\circ}\) at 27.80 GHz; **(g)** radiation patterns on phi = 0\({}^{\circ}\) at 29.85 GHz; **(h)** radiation patterns on phi = 90\({}^{\circ}\) at 29.85 GHz.
# Design and Development of an Embedded Controller for a Hydraulic Walking Robot WLBOT
## 5 Experiment
### Joint Angle Tracking  
The robot is tested by performing an offline joint trajectory tracking task, in which we compare the general PID controller and the compound PID controller with velocity feedforward compensation as Figure 12 depicts. The PID gains and the velocity compensation gain are shown in Table 3. With the control of a single PID controller, the maximum tracking errors of the knee and hip angles are 0.092 rad and 0.122 rad in a gait cycle. However, when using the compound PID controller, the maximum tracking errors decrease to 0.056 rad and 0.035 rad, reduced by 39.13% and 71.31% respectively, which has obvious improvement. Furthermore, the comparison of mean and standard deviation (SD) of tracking errors