esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Problem Analysis and Theory
### Principles of PIRNN Method
#### 2.4.2 PIRNN Full Waveform Inversion  
The velocity model \(\mathbf{v}\) is embedded as the trainable parameter within the PIRNN network architecture. The loss function is constructed based on the discrepancy between the observed and simulated data, utilizing the Mean Square Error (MSE) as the measurement metric:  
\[J_{\text{MSE}}(\mathbf{v})=\frac{1}{N_{\text{s}}T}\sum_{s=1}^{N_{\text{s}}} \sum_{t=1}^{T}||\mathbf{d}_{\text{cal}}(\mathbf{x}_{r},\mathbf{x}_{s},t, \mathbf{v})-\mathbf{d}_{\text{obs}}(\mathbf{x}_{r},\mathbf{x}_{s},t)||^{2}, \tag{10}\]  
where N\({}_{\text{s}}\) and \(T\) represent the total number of time steps and \(\mathbf{d}_{\text{cal}}\) and \(\mathbf{d}_{\text{obs}}\) denote the simulated and observed data at the corresponding source locations and time steps, respectively. Within the PIRNN framework, the temporal dependencies between wavefield variables are transformed into chain relationships that were automatically recorded during the forward propagation process. The back-propagation algorithm computes the gradients of the loss function with respect to the model parameters. Because the velocity parameter \(\mathbf{v}\) is embedded within the network, gradient information can be obtained through automatic  
Figure 4: PIRNN-based forward modeling process.  
differentiation mechanisms, and parameter updates can be performed using optimization algorithms, as shown in Equation (11):  
\[v^{k+1}=v^{k}-\gamma\frac{\partial J(v)}{\partial v}, \tag{11}\]  
where \(\gamma\) is the learning rate. [PERSON] [14] and [PERSON] et al. [34] validated a PIRNN-based FWI method and demonstrated promising results. However, although this method reduces the dependency of FWI on the initial models, it can nonetheless lead to local minima when utilizing velocity models that lack prior knowledge and low-frequency information, resulting in inaccurate results. Therefore, this study introduces a first-arrival constrained physics-embedded recurrent neural network FWI method to ensure an FWI that is insensitive to initial velocity models.
## 2 Materials and Methods
### Data Augmentation  
The OHTS exhibited a significant class imbalance (healthy versus POAG patients), with only 337 patients diagnosed with POAG (approximately 20.6%) by the end of the study. A deep learning model normally needs around a 50:50 ratio between classes to better learn to differentiate them. To address this, we oversampled the minority class (i.e., cases where patients develop POAG) in the training and validation sets. To ensure diversity in the training and validation sets, we applied data augmentation techniques, including horizontal and vertical translations (up to 20% of the image dimensions), rotations (up to 20 degrees), and random adjustments to brightnesses, contrast, hue, and saturation. This ensured that the model would not memorize the resampled images but rather develop a general understanding of how POAG appears on fundus photos. Each augmented image retained the same label as the original image.
## 1 Introduction
Since there is a time delay, the methods will have difficulty eliminating the synchronization error completely. Through investigation, we found that the synchronization error is caused by the characteristic difference in the dynamic response of the dual-motor system, and, because the fractional-order deferential operator can accurately describe the control frequency-domain characteristics required by the controlled object, there are several control methods based on fractional-order control theory [23; 24; 25]. In literature [26], the authors developed a feedforward control method for PMLSM based on the fractional-order control theory. Through the accurate description of the system's control frequency-domain characteristics, the fractional-order feedforward control method improved the PMLSM tracking accuracy effectively for a single-motor system. However, for a dual-motor system, besides the tracking accuracy of each motor, the synchronization accuracy of the two motors is the key issue and needs to be further studied. Therefore, considering the advantage of the fractional-order control theory, this paper proposes an adaptive fractional-order anti-saturation synchronous control method to improve the synchronization accuracy of the dual-motor system. Through compensation, we unified the frequency-domain characteristics of the motors in a dual-motor system to ensure they have the same dynamic response characteristics. With the design of the frequency-domain characteristics' unification module (FDC-UM), the dynamic response characteristics of the two motors were adjusted to be consistent. Then, the adaptive fractional-order anti-saturation module (AFOAM) was designed to avoid the saturation effect of the control voltage. By calculating the theoretical peak voltage, the parameters of the AFOAM were determined by the relationship between the parameter selection and the FDC adjustment of the fractional-order lead-lag controller (FOLLC). Through the AFOAM, the dual-motor system can prevent the control voltage from reaching the voltage limitation and thus guarantee the suppression of the FDC-UM for the synchronization error. Therefore, the proposed adaptive fractional-order anti-saturation synchronous method can actively suppress the generation of the synchronization error and avoid the saturation effect, ensuring a dual-motor system with high-precision synchronous motion performance. The remainder of this paper is organized as follows. Section 2 introduces the kinetic model of the dual-motor system and the proposed adaptive fractional-order anti-saturation synchronous control method in detail. In Section 3, based on the established relationship between the FDC and the dynamic response characteristics of the motor systems, the FDC-UM and the AFOAM are designed and finalized with the required parameters. In Section 4, the experimental setup is described, and experimental work is performed to verify the effectiveness and superiority of the proposed method. Section 5 presents the discussion, and Section 6 presents the conclusions.
# Ensuring Agricultural Sustainability through Remote Sensing in the Era of Agriculture 5.0
## 3 Artificial Intelligence and RS
The other challenge is a lack of datasets for deep learning-assisted applications. Another commonly associated product of RS technology in relation to AI is the decision support systems (DSS). Therefore, it would be important to highlight the potential and roles of DSS in agricultural RS.
## 5 Discussion
### Subsurface Conductivity Structure and Associated Interpretations
#### 5.3.2 The Importance of Conductive Major Normal Fault H  
Another interesting feature is the major normal fault **H** (Figure 1) which is close to MT station 028 (Figure 9). The hanging wall of this fault has been qualified as hydrogeological barrier separating the rift to a conductive northeastern zone and relative resistive southwestern [6]. The latter study is in agreement with the 2D conductivity model developed in this work (Figure 9), where the extent of C2 layer is more pronounced in the northeastern zone. Additionally, the synclinal form of C3, C4 and R2 at the center close to the vertical projection of **H** fault at great depth (Figure 9) may suggest a possible direct link of a sub-vertical dipping and sub-vertical dyke in an approximate north-south striking direction, as inferred by dimensionality analysis at long periods (Figures 3-5). The author argued that the **H** fault is the main active fault in Asal rift, and it is likely connected to a deep hydrothermal system which change the hydrostatic and lithostatic pressure when the state of the underlying overpressure magma reservoir changes at the deeper level. This may be evidenced by the high conductance of conductive layers (C2, C3, C4 in Figure 9) observed at the center of rift close to the vertical projection of **H** fault. And the TE and TE-TM models (Figure 9 and Appendix A) display high conductive medium between 2 and 5 km depth for the same zone. Similar patterns where a high conductance of conductive layer was associated with a reservoir hosting the source of deformation and where upward release triggers micro-earthquakes were found for a hydrothermal system in Japan [63]. In the hydrothermal system of Unzen graben of Japan, vertical conductive zone having a width of 2 km and an extend down to below 4 km was also interpreted as interconnected fractures network generated by the main active normal fault in which magmatic volatiles are supplied from a deeper pressure source causing surface deformation [69]. The resistivity structure estimated by new 2D inversion method allowed to resolve narrow conductors zones beneath three main faults in the central Japan [70]. The later authors interpreted the narrow conductive zones under faults as localized ductile shear zones with highly connected fluid which are responsible for the strain accumulation along the active faults. Additionally, in a rift zone, steep crustal-scale faults inferred from MT data analysis were interpreted as preferred path that connect between the deep dominantly magmatic fluid and upper crustal meteoric regime [42].
# Real-Time Filtering Non-Intentional Bid Request on Demand-Side Platform
## 2 Online Advertising and Real-Time Bidding
### Online Advertising and Real-Time Bidding  
Online advertising refers to any form of promotional brands or services on various online platforms, such as social media, websites, search engines, etc. The main objective of online advertising is to increase sales and brand awareness without being restricted by time and space. On the other hand, RTB is a part of online advertising that automates buying and selling of online advertising impressions. RTB is beneficial to both publishers and advertisers. For advertiser side, RTB allows advertisers to buy more efficiently and displays more relevant advertisements to users. For publisher side, RTB allows publishers to increase their budget and filling rates by opening a real-time auction. The process of RTB happens in a very short time (less than one second) with the process as described in Figure 1. The definitions of some important terminologies in online advertising and RTB are presented below:  
* Advertiser: buys advertising space on the internet to promote their products and services;
* Publisher: owns the online platforms with digital space to sell and show the advertisements;
* Demand Side Platform (DSP): purchases ad impressions on publisher advertising inventory in an automated manner;
* Supply Side Platform (SSP): sells advertising in an automated manner;
* Ad Exchange: trades the advertising transaction procedure between SSP and DSP;
* Ad network: connects multiple platforms by matching advertisers to websites looking to host advertisements;
* Agency: helps advertisers display advertisements in the most suitable place and optimize the budget;
* Impression: the number of times advertisements have appeared on any device screen within the publisher's network;
* Click: a click event is created when users have clicked on an advertisement to reach online information about the advertiser's products and services;
* Click Through Rate (CTR): the ratio of clicks to impressions;* Conversion: a conversion event is generated when a user clicks on an advertisement and keeps on performing some activities on the site such as download, sign up, purchase of a product, etc.
## 5 Conclusions  
Studies addressing the degradability of polymers in marine environments are very recent and focus mainly on a short-term scale, whereas long-term biodegradation dynamics and the effects on the marine biota are still missing. Furthermore, standard analytical methods to trace and quantify the biodegradation pathways are scarce and need improvements, considering that most studies are at the laboratory scale and not representative of different environmental conditions and habitats. Hence, the lack of knowledge about long-term degradation and the occurrence of residual biopolymers in the marine environment can generate speculations about their sustainability and contribution to marine plastic pollution.  
This study revealed that two types of Mater-Bi(r) materials seem to be composed of polyester and starch, and that, once in the marine environment, the starch fraction is subjected to fast degradation (hydrolysis) estimated at about 124-180 days.  
The combination of the IRMS technique with FTIR has been revealed as a promising and time/money-saving tool to more efficiently address the biodegradation of polymers in the marine environment and infer their degradation times and kinetics.  
Conceptualization: D.B. and F.R.; methodology: F.R., S.N., C.G., M.F., N.C. and A.D.L.; data validation: D.B. and L.B.; formal analysis: F.R., S.N., C.G., M.F., N.C. and V.C.; statistical analyses: N.C.; data curation: all authors; writing--original draft preparation: F.R. and D.B.; writing--review and editing: all authors. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
Data Availability StatementData can be made available upon request to the corresponding author.  
The authors thank the Nautical Club of Chioggia for making the space available for the environmental exposure experiment.  
The authors declare no conflict of interest.
## 4 Onsite Blasting Experiments
### Blasting Design  
The detonation network used in the onsite experiments is shown in Figure 15. Three onsite experiments were conducted. The blasting parameters for the first experiment were as follows: the blast hole spacing was 3 m, the row spacing was 2 m, and the detonation  
Figure 14: Simulation and analysis process of rock blasting fragmentation.  
mode employed a 17 ms micro differential and equal interval delay, implemented using a digital electronic detonator. The charging structure used was an uncoupled charging structure, as depicted in Figure 16. The explosive used was a 90 mm emulsion explosive, with a blast hole diameter of 115 mm, an explosive length of 12.5 m, and a stemming length of 2.5 m. The detailed blasting parameters are provided in Table 4. It should be noted that, to prevent excessive or distant fly rocks caused by variations in the resistance line during actual construction, the layout of the blast holes near the slope and the design of the charge structure were adjusted based on the specific site conditions.  
The onsite experiment images are shown in Figure 17. Figure 17a depicts the site before blasting, while Figure 17b shows the site after blasting. Under the influence of explosives, the rocks are fractured into fragments of varying sizes. As shown in Figure 17b,  
\begin{table}
\begin{tabular}{c c} \hline
**Blasting Parameter** & **Content** \\ \hline Bench height & 13.5 m \\ Blast hole layout & Rectangle \\ Drilling diameter & 115 mm \\ Drilling angle & 90\({}^{\circ}\) \\ Drilling depth & 15 m \\ Blast hole spacing & 3 m \\ Array pitch & 2 m \\ Front resistance line & 2.0 m \\ Explosive type & 2\# emulsion explosive \\ The main blasting charge structure & Continuous charging \\ Stemming length & 2.5 m \\ Explosive length & 12.5 m \\ Delayed initiation mode & Digital electronic detonator 17 ms delayed initiation \\ \hline \end{tabular}
\end{table}
Table 4: Detailed blasting parameters.  
Figure 16: Charge structure.  
Figure 15: Onsite rock blasting network experiment.  
some large rocks remain partially unbroken in the onsite experiment. The presence of these large rocks, which require secondary breaking, impacts subsequent excavation efficiency. Therefore, it is crucial to develop a method for predicting the rock blasting fragmentation results in advance, providing guidance and reference for onsite parameter design.
# Study About the Performance of Ascon in Arduino Devices
## 3 Ascon as Authenticated Encryption
### MonkeyDuplex Construction  
The security of MonkeyDuplex construction requires the associated data to be unique. In other words, Duplex constructions only ensure the confidentiality of the ciphertext if, for the same key and different messages, the associated data are unique (for more information see [13]). The main features of this scheme are the following:  
* It is an object that, upon creation, is loaded with a message authentication code (MAC), a key, and a nonce. Once initialized, duplex calls can be performed by providing an input string and requesting an output string. Its main characteristic is that the output string depends on all the previous input strings, the key, and the nonce.
* The initialization of the \(b\)-bit state of the construction is performed by concatenating the key and the nonce, among others, subject to \(n\) initial rounds. This is where permutation comes in. If the permutation is good enough in terms of security, the state values of MonkeyDuplex objects with different nonce values can be considered to be independent. In this case, state recovery by an attacker with access to multiple objects gains no advantage over state recovery from a single object.  
* The duplexing calls are quantitatively the same as in the Duplex construction. It is possible to reduce the number of rounds of the permutation, without compromising the scheme's robustness, provided that an initialization protocol is established. As such, differential attacks will be unfeasible, i.e., an attacker would have no knowledge of the difference between the different objects in the MonkeyDuplex construction.
* The difficulty of recovering a state is directly proportional to the number \(n\) of rounds of the permutation, and inversely proportional to the size of \(r\). The efficiency is determined by the parameter \(r/n\). Indeed, a larger value of \(r\) allows one to process a larger amount of data per iteration, while a smaller value of \(n\) reduces the number of permutation operations required per data block, speeding up the computation. Consequently, the ratio \(r/n\) represents the number of useful bits processed per round of permutation applied. The greater \(r/n\), the more efficient the scheme, since the amount of data processed per computational unit is maximized.
# TARCS: A Topology Change Aware-Based Routing Protocol Choosing Scheme of FANETs
###### Abstract  
The rapid change of topology is one of the most important factors affecting the performance of the routing protocols of flying ad hoc networks (FANETs). A routing scheme suitable for highly dynamic mobile ad hoc networks is proposed for the rapid change of topology in complex scenarios. In the scheme moving nodes sense changes of the surrounding network topology periodically, and the current mobile scenario is confirmed according to the perceived result. Furthermore, a suitable routing protocol is selected for maintaining network performances at a high level. The concerned performance metrics are packet delivery ratio, network throughput, average end-to-end delay and average jitter. The experiments combine the random waypoint model, the reference point group mobility model and the pursue model to a chain scenario, and simulate the large changes of the network topology. Results show that an appropriate routing scheme can adapt to rapid changes in network topology and effectively improve network performance.  
f  
flying ad hoc network (FANET); mobile ad hoc network (MANET); highly dynamic; periodical; topology change awareness; routing protocol
## 3 Result
### Summary of the Results  
This section provides an integrated summary of the ANN model's performance in detecting starch adulteration in milk. While Table 1 presents specific metrics, here we expand on the broader implications and reliability of the model.  
Figure 7: ROC curve.  
Key Findings:
* The ANN model achieved perfect scores across all performance metrics (100% accuracy, precision, sensitivity, and F1-score), indicating its exceptional capability in identifying adulterated samples without false positives.
* The feature importance analysis, as depicted in Figure 6, reveals that wavelengths at 940 nm and 410 nm are most critical in influencing the model's predictions. This insight can guide future enhancements in sensor technology and data collection methods.
* The ROC curve, illustrated in Figure 7, with an AUC of 0.99, confirms the model's high discriminative power between adulterated and non-adulterated samples, providing strong evidence of its practical applicability in real-world settings. Implications for Future Research:
* The high accuracy and reliability of the ANN model suggest its potential for implementation in automated milk testing equipment.
* Future studies could explore the integration of this model with inline spectral analysis systems in dairy production lines to provide real-time quality assurance.
* Additional research is needed to evaluate the model's effectiveness across different milk types and under varying storage conditions, which could affect the spectral properties of milk.  
This summary not only underscores the technical achievements but also highlights the practical applications and future directions for research based on the current study's outcomes.
## 3 Results and Discussion
### Fracture Morphology  
For the sake of understanding the failure behavior and characteristics of Sn50 Pb49 Sb1/Cu solder joints after \(\gamma\)-ray irradiation, fracture morphology was observed using SEM and EDS. The SEM images of the fracture morphology of joints at various irradiation times was carried out after pull tests, as shown in Figure 8. The SEM fractography of the joints with three different irradiation times exhibited fracture surfaces with typical ductile dimples, which shows evidence of a great quantity of plastic deformation along the loading direction. It also demonstrates that the fracture type of Sn50 Pb49 Sb1/Cu solder joints is incapable of being changed by \(\gamma\)-ray irradiation, which is still a ductile fracture. Furthermore, as can be seen from Table 1, the chemical composition of dimples in the  
Figure 6: Schematic diagram of micro-defect generation in the Pb-based solid solution: (**a**) the formation of point defects induced by \(\gamma\)-ray; (**b**) the migration of lattice vacancy; (**c**) the formation of micro-defects.  
Figure 7: The pull force of the Sn50 Pb49 Sb1/Cu solder joint at various irradiation times.  
solder joints before/after irradiation was mainly Sn and Pb. Hence, it could be inferred that the tensile fractures all occurred within the solder bulk, which is very different to other reliability tests. However, as can be seen from Figure 8b,c, the depth and size of the dimples of the Sn50 Pb49 Sb1/Cu solder joint after 960 h irradiation decreased in comparison with the as-soldered joint, which could be explained by irradiation embrittlement. Numerous displaced atoms and lattice vacancies were generated by \(\gamma\) photons through the Compton effect, and the supersaturation of point defects improved the resistance of the dislocation glide, making solder joints difficult to deform [17; 18]. With the accumulation of the irradiation dose, the dimples of the broken joints were slightly less obvious than as-soldered joints, which indicates that the ductility of the Sn50 Pb49 Sb1/Cu solder joint decreased during the irradiation process.