esa-sceva/satcom-chunk-collection huggingface dataset:
# Perspectives of Hydrogen Generation in Cavitation-Jet Hydrodynamic Reactor
## 4 Conclusions  
A significant outcome of using both cavitation-jet liquid treatment and the chemical method of aluminum surface activation is the recognition of synergy, which refers to the superiority of the obtained result compared to the anticipated results of using both procedures independently [59; 60].  
It is anticipated that a synergistic effect will result from combining cavitation-jet treatment with e-beam irradiation, improving water decomposition into hydrogen and other by-products. This effect is particularly notable when dissolved gases (such as CO\({}_{2}\) and H\({}_{2}\)S) or liquid radioactive waste are present, which will be the focus of upcoming research. In the latter case, radionuclides can play a role as a catalyst for water radiolysis under the cavitation-jet processing of liquid radioactive waste, which may solve the global problem of reducing their volume.  
Consequently, cavitation-jet processing holds significant promise for atmospheric greenhouse gas purification and hydrogen generation, owing to its ability to produce high concentrations of oxidizing agents like OH\({}^{\bullet}\) and H\({}_{2}\)O\({}_{2}\) in water solutions. It also creates localized areas of high temperature and pressure, which could make it a convenient and user-friendly option. Hydrodynamic cavitation could emerge as an economically viable and highly efficient alternative to current methods.  
It can be assumed that the non-equilibrium plasma produced during liquid cavitation-jet processing causes a self-oscillating process in which oxidation and reduction occur simultaneously with in a short period of time. Consequently, it is not enough to focus only on the production of active particles with oxidizing properties such as hydroxyl radical (HO\({}^{\bullet}\)) and hydrogen peroxide (H\({}_{2}\)O\({}_{2}\)). The production of reducing particles such as hydrogen radical (H\({}^{\bullet}\)) and carbon monoxide (CO) should also be considered.  
This work provides a contribution to the study of the mechanism of hydrogen generation by cavitation-jet treatment of water and aqueous solutions, in which conditions are created for double cavitation in hydrodynamic tubes of different cross-sections.  
Conceptualization, G.K.M.; Methodology, Z.I.B.; Software, I.V.D.; Investigation, I.V.D. and Y.R.N.; Data curation, A.R.; Writing--original draft, G.K.M.; Supervision, G.K.M. All authors have read and agreed to the published version of the manuscript.  
Funding:** The work was performed under financial support of the State Institution \"Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan\" within the framework of the Scientific-Technical Program BR18574073.  
**Data Availability Statement:** The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.  
The authors declare no conflict of interest.
# Research on Lifespan Prediction Methods Using Ultrasonic Microimaging for Electronic Packaging
## 2 Materials and Methods  
Acoustic microimaging technology utilizes high-frequency ultrasonic waves to detect defects within materials. When defects such as cracks occur at solder joints, they cause a mismatch in acoustic impedance within the material, altering the reflection and refraction characteristics of the ultrasonic waves [18]. These changes are visually represented in C-scan images and displayed in grayscale intensity, clearly revealing the internal structural changes of the solder joints. By analyzing the intensity variations in C-scan images of solder joints across different testing cycles, one can effectively assess the health state of the solder joints [19; 20]. Based on the aforementioned analysis, a method for predicting the lifespan of electronic packaging using acoustic microimaging is proposed, as illustrated in Figure 1.  
The proposed method comprises the following steps.  
1. Experimental Data Acquisition: Four test boards were designed and manufactured, each equipped with 14 flip-chip packages mounted on a flame retardant type 4 substrate (FR-4). The boards underwent accelerated thermal cycling lifespan experiments until the chips detached. During the experiments, ultrasonic images of the flip chip were periodically acquired using the C-scan mode of an acoustic microscope, recording changes in their internal structure. To ensure the reliability and robustness of this study, a large-scale experimental dataset was collected. A total of 4 test boards were designed and fabricated, each equipped with 14 flip-chip packages, resulting in 56 flip chips for the experiments. Each test board contained 109 solder joints, and all samples underwent accelerated thermal cycling aging tests. During the experiment, data were collected every 4 thermal cycles, resulting in over 490 sampling points. The thermal cycling experiments lasted for a total of 2126 h over one year, producing more than 2 TB of experimental data. This dataset includes 3750 ultrasonic C-scan images of flip chips and over 400,000 solder joint images, providing a robust foundation for data analysis and model development.
2. Ultrasonic Image Data Processing and Feature Extraction: The collected ultrasonic C-scan images were processed to ensure the consistency, stability, and accuracy of the image data. The mean intensity within the solder joint images was extracted as a key feature indicative of defects, which correlates with the solder joint's fatigue stress and number of cycles, providing a basis for subsequent analysis.
3. Failure Modeling and Lifespan Prediction: Based on the features of the solder joint images, a failure curve correlating the image features with the number of cycles was constructed. A cumulative failure probability model for individual solder joints was established using the Anderson-Darling test. This model was validated across multiple samples, demonstrating its accuracy and robustness in predicting the lifespan of solder joints. The model allows for the classification of solder joint health states, enabling lifespan prediction.
## 3 Methodology
### Sentiment Lexicon-Enhanced Dynamic Modulation Layer  
The principle of lexicon-based sentiment analysis (SA) is to associate terms with predefined sentiment scores to determine the overall sentiment tendency of a text [40]. Previous studies have proven that the lexicon-based methods account for approximately 52% of the techniques used in the field of requirements elicitation from app reviews [5]. Inspired by this approach, we introduce a sentiment lexicon-enhanced dynamic modulation layer into the BERT model. The sentiment lexicon is embedded as additional semantic clues to improve the model's ability to perceive and understand the sentiment features of terms in context. This layer incorporates \"word-sentiment polarity pairs\" into the neural network using a custom activation function.
## 5 Multi-Path Routing Protocol  
Once the sensor nodes are deployed in the area of interest using the approach in Section 4, the network will be \(k-connected\) from the topology point of view. The routing protocols are used to find a specific path from the source to the destination according to specific routing algorithms. When the nodes or links fail on this path for whatever reason, the routing protocols need to detect failures first and then findalternative paths to the destination. As a consequence, the routing protocols play an important role in resilient WSNs.  
The work in [111] classifies the routing protocols in wireless _ad hoc_ and mesh networks into different categories: proactive, reactive, geographical, multi-path, hierarchical, flow-oriented, Wireless Mesh Network (WMN) and multicast, power aware, _etc_. Of course, some of them share common properties. However, surveying routing protocols in WSNs is out of the scope of this paper; the reader is referred to [111] for more details. Multi-path routing and energy-aware protocols, such as [112], Robust and Energy Efficient multipath Routing (REER) [113], Energy Efficient Multipath Routing protocol for WSNs (referred as RELAX) [114], Low-Interference Energy-efficient Multipath ROuting (LIEMRO) [115], Energy Efficient Fault Tolerant Multipath (EEFTM) [116] and Probing Environment and Adaptive Sleeping (PEAS) [95], are suitable for resilient WSNs.  
The challenges here are how to design low overhead and low complexity routing algorithms, taking into account heterogeneous or homogenous network models, stationary or mobile networks, using 2D or 3D models, knowing the locations of nodes (e.g., by GPS) or not, localized (distributed) or centralized (globalized) algorithms, _etc_.
###### Abstract
The drought over that period can be also captured by satellite observed solar-induced chlorophyll fluorescence (SIF) [16]. Anomalous carbon uptake over Australia around 2011 was also discovered with satellite observations and model simulations [17]. Extreme drought events in North America during 2011 and 2012 were also selected as a case, for checking the capability of using SIF to characterize vegetation response to climate change [18]. The strong 2015/2016 El Nino [19; 20; 21] may have increased carbon flux releases by 0.9 \(\pm\) 0.29, 0.8 \(\pm\) 0.22, and 0.8 \(\pm\) 0.28 GTC over the tropical continents including South America, Africa and Asia [22]. These studies show how carbon fluxes anomalies associated with extreme climate events can impact atmospheric CO\({}_{2}\) concentrations. There is also great potential in identifying anomalous changes in the land carbon sink without prior knowledge of extreme weather events [23; 24; 25]. Variations in atmospheric CO\({}_{2}\) can be used for anomalous carbon source and sink change analysis. The column-averaged CO\({}_{2}\) dry air mole fraction (XCO\({}_{2}\)) derived from the Greenhouse gases Observing SATellite (GOSAT) proved valuable for confirming the effect of extreme climate events (such as El Nino) on the CO\({}_{2}\) concentration [26]. However, the gaps in time and space limit the satellite retrieved XCO\({}_{2}\) from probing the time and space of carbon sources and sinks anomalies. In this study, we use XCO\({}_{2}\) time series from satellite observations with global mapping [27; 28] for extreme high XCO\({}_{2}\) detection. In contrast to earlier studies, which concentrated on surface environment variables (such as fraction of absorbed photosynthetically active radiation (fPAR), GPP, surface temperature and so on) [29; 30; 31], we focus on using atmospheric CO\({}_{2}\) concentration for extreme event detection. CO\({}_{2}\) anomalies integrate influences from many biosphere-atmospheric interaction, including carbon uptake/release from soil ecological activity, vegetation activity, biomass burning, etc. In addition, XCO\({}_{2}\) anomalies can be connected across time and space as a result of atmospheric transport. We aim to develop an approach for detecting spatiotemporal continuum high XCO\({}_{2}\) anomalies using satellite XCO\({}_{2}\) observations, which are related to terrestrial biosphere anomalies of CO\({}_{2}\) uptake and release. The detected high XCO\({}_{2}\) can be attributed to carbon source/sink changes caused by extreme weather events. The dataset used in this study and its preprocess is described in Section 2. The method of extreme events detection can be found in Section 3. Corresponding results of the extreme detection are revealed in Section 4. Discussion of the detected spatial pattern over specific duration and correlation between XCO\({}_{2}\) and local CO\({}_{2}\) flux is in Section 5, and conclusions are presented in Section 6.
By incorporating different topologies together, LWAS designs one topology-fused search space that can cover many human-designed architectures and develops a resource-aware differentiable search algorithm to select light-weight architectures from the search space. * The DSP algorithm. With the proposed differentiable pruning criterion, DSP can build a stronger correlation between the pruning criterion and the model performance. An additional attention-similarity loss function is specially developed for MHA modules to get better pruning performance. * Extensive experiments demonstrate the effectiveness of LWMD in compressing E2E ASR models. More ablation and exploration explain the contributions of the LWAS framework and the DSP algorithm. The rest of this paper is organized as follows. Section 2 briefly introduces previous works related to this work. Section 3 describes our proposed LWMD platform. Section 4 provides the experiment results and analysis. Section 5 gives the conclusion.
# Output Power Smoothing Control for a Wind Farm Based on the Allocation of Wind Turbines
## 3 Power Smoothing Control Strategy
### Control Strategy for the CWTs  
The reference power given control method was adopted for the CWTs and its control diagram is shown in Figure 6. When the control target of the CWTs was the MPPT control, the reference power will be set to the maximum power according to Equation (5). When the target is changed to smooth output power, the reference power will be obtained according to the block diagram shown in Figure 4. The given power and the actual power were compared and the difference was adjusted by the PI module to obtain the \(q\)-axis current. The reference \(d\)-axis current was set to zero to simplify the control. Similar to the control of P WTs, the SVPWM method was applied in the CWTs control, as shown in Figure 7.
# Review of Advanced Medical Telerobots
## 2 Medical Telerobotic Topologies
### Multilateral Teleoperation
#### 2.3.2 Single-Leader/Multi-Follower (SL/MF)  
Another topology of the multilateral teleoperation system is Single-leader/Multi-follower (SL/MF) structure. In this type, more than one follower is in the loop to improve dexterity, manipulability, performance, and functionality of the system. This topology is usually used when one leader is sufficient for commanding the task, while one follower cannot overcome the complexity and geometry of the task [4]. Examples of applications for this topology are micro-tweezing [227], handling heavy and bulky objects [225], cooperative manipulation [225, 226], motion coordination of multiple robotic agents (swarm robotics) [228], assembly line tasks such as for bolt-nut pairs [225]. The main challenges are the synchrony between multiple follower robots operating in a shared environment while ensuring a secure grasp under the command of the leader robot [226]. A control algorithm that has been used to ensure the security of the grasp is a passivity-based control framework for cooperative robotic systems at the follower side [226, 227], using which the dynamics of the follower robots are divided into two subsystems; shaping system and locking system. The shaping system gets controlled by disturbance cancellation to make sure the grasp is secured, while the locking system is controlled based on the operator's commands with higher dynamics. This control approach was applied to the bio-operation micro-tweezing task. There are other control strategies designed for enhancing the performance of SL/MF topology such as task-oriented controller [225] that requires knowledge of the task before the operation, and wave-variable controller [229], which is used to synchronize follower consoles in the presence of time-varying communication delays while guaranteeing stability.
# Fine Recognition of MEO SAR Ship Targets Based on a Multi-Level Focusing-Classification Strategy
## 2 Signal Modeling and Characteristic Analysis of MEO SAR Ships
### MEO SAR Image Defocusing Caused by Ship Rotation
Based on the defocusing characteristics of MEO SAR ships, a multi-level focusing-classification strategy is proposed to realize accurate recognition of MEO SAR ship targets.
# Quantum Key Distribution in the Presence of the Intercept-Resend with Faked States Attack
## 6 Conclusions  
The Intercept Resend with Faked (blinding) States (\(IRFS\)) attack is detected by the _nack state_ protocol using the gain of single and double detection events. The protocol uses the same optical hardware of the \(BB84\) protocol, and it can be implemented in most \(QKD\) systems as a software module application.  
Although double detection events represent a small fraction of the total detection events, they are useful to detect the \(IRFS\) attack. In addition, the smaller \(QBER\) can be useful in future implementations to distill secret bits at longer distances.  
**Author Contributions:** All authors contributed equally to this work. [PERSON] conceived the _nack state_ protocol. [PERSON] analyzed, discussed and improved the protocol. [PERSON] analyzed the protocol and contributed with discussion to the work presented in this paper. All authors discussed the results and implications and commented on the manuscript at all stages. All authors have read and approved the final manuscript.  
**Conflicts of Interest:** The authors declare no conflict of interest.
# Antioxidant Activity and Polyphenolic Content of North Macedonian Wines
## 3 Results and Discussion
### Statistical Evaluation of Results  
Pearson's coefficients (Table 3) show a very strong relationship between TPC and results with DPPH (r = 0.987, n = 34), FRAP (r = 0.970, n = 34) and CUPRAC (r = 0.957, n = 34) assays, indicating that the antioxidant activity of all varieties is related to the presence of phenolic compounds. Results for TFC also show a strong correlation with DPPH, (r = 0.990, n = 34), FRAP (r = 0.979, n = 34) and CUPRAC (r = 0.972, n = 34) assays. Apart from the relative amount of the flavonoids, attention has to be given to other factors affecting the antioxidant activity of flavonoids, primarily to the structure of the flavonoids, number of OH groups, saturation degree of carbon-carbon bonds and substitution of the OH groups with methyl and glycoside moieties [33].  
Results for TTC (LA and VA assays) show good correlation with the DPPH, FRAP and CUPRAC assays (Table 3), but this relationship is weaker compared to the relationships of TPC and TFC with the antioxidant assays. The degree of polymerisation of the tannins may play a key role in their ability to behave as antioxidants, knowing that the higher degree of polymerisation is associated with the higher antioxidant activity of tannins [33]. On the other hand, the correlation coefficient between TAC, and DPPH, FRAP and CUPRAC, recorded lower values (r = 0.730, n = 16), (r = 0.754, n = 16) and (r = 0.698, n = 16), respectively. However these results are justified, taking into account that anthocyanins are less effective as antioxidants since the O-glucose substitution on the C3 position of the C ring diminishes their antioxidant potency [33].  
Canonical discriminant analysis (CDA) was applied for the results of TPC, DPPH and CUPRAC assays in order to establish any similarities or differences between the 6 wine varieties studied.  
\begin{table}
\begin{tabular}{c c c c} \hline  & **DPPH** & **FRAP** & **CUPRAC** \\ \cline{2-4}  & & **(mmol TE/L)** & \\ \hline
**TPC (mg GAE/L) * & 0.987 * & 0.970 * & 0.957 * \\
**TFC (mg CE/L) * & 0.990 * & 0.979 * & 0.972 * \\
**TAC (mg TA/L) ** & 0.730** & 0.754 ** & 0.698 ** \\
**LA (g TT/L) ** & 0.859 ** & 0.906 ** & 0.877 ** \\
**VA (g CE/L) ** & 0.880 ** & 0.927 ** & 0.925 ** \\ \hline \end{tabular}  
* Analysis applied to all wines (red and white; n = 34); ** Analysis applied to red wines only (n = 16).  
\end{table}
Table 3: [PERSON]’s correlation analysis between results of TPC, TFC, TAC, LA, VA, DPPH, FRAP and CUPRAC assays for all wine varieties.  
Results (Figure 1) show that white wines are clearly classified in one group without any differences between them. Results for red wines show that Vranec and Kratoshija are clearly separated from Stanushina.
# Evaluation of IEEE802.15.4g for Environmental Observations
## 4 Analysis
### Urban Canyon Scenario
#### 4.3.2 RX at 779 m
The reason is also interference, since a burst of short packets can be more affected by a single transmission of different technology/network using a lower data rated communication than a long packet burst. We see this more notably in OFDM2-100 at 406 m and OFDM1-400 at 512 m.  
Nodes located at further distance presenting higher PDR values than nodes located closer to the TX node. We are in a scenario where the radio signals interact with trees, people, cars, buses, shops, buildings and big metal infrastructure and for some RX locations, these objects are in the way between the TX and RX nodes. These objects can cause the shadowing effect of the node, affecting the quality of the link between TX and RX and thus, drastically reducing the PDR for that link.
# Applying Reinforcement Learning to Protect Deep Neural Networks from Soft Errors
## 4 Case Study
### Evaluating Resiliency by Injecting Faults  
Considering the energy efficiency and occupation of bit storage for large-scale neural networks, more and more hardware platforms intend to utilize 8-bit fixed points (INT-8) instead of 32-bit floating points to convert and store the parameters of the DNNs [66]. However, a side effect by using the INT-8 is that the DNNs require more precision and reliability to maintain the performance [67]. To meet these requirements, we test and validate our design by converting the weights of the DNNs to INT-8 and storing them in the proposed simulated model mentioned in Section 3.1. Given the significance and severity of soft errors [4, 5], including bit-flips and stuck-at-0/1 errors, we inject bit-flips--recognized as the most critical faults affecting DNN performance--into the weights of the simulated model according to Equation (1). The model is configured with an entry size of 256 bits, with each size storing four 64-bit words. With different parameters, we collect the metrics to evaluate the performance and robustness of the DNNs by using Equation (2). Specifically, we present the layer-wise resiliency evaluated under \(r_{b}=10\%\), and \(r_{c}^{i}\) follows the normal distribution with \(\sum_{i=1}^{N_{c}}r_{c}^{i}=1\) in Figure 5. The number of \(N_{c}\) depends on the number of weights within the target DNN model, and they are automatically sequentially allocated with an entry size of 256 bits. Figure 4(a) illustrates that Layer 1 and 2 could dramatically affect the performance when soft errors occur. Additionally, Layer 3 shows a better resiliency compared to the others.  
Based on the resiliency of this MLP, we generalize that the amount of protected bits is correlated to the layer index. For example, the neurons in the intermediate layers could require less protected bits than those in other layers. However, such a correlation is more complex when the layers become deeper in ResNet-18. Layer 1 of the ResNet-18 shows a similar pattern as the MLP. Meanwhile, Layers 7, 8, and 9, allocated in the middle of the network, are more sensitive to soft errors. Such a phenomenon shows that the various DNN architectures could differ regarding the performance of a unified protection scheme (e.g., conventional ECC scheme), indicating the demand of a tailored scheme reg  
Figure 5: Layer-wise resiliency of DNN by injecting faults with 500 iterations.