esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 An Anti-Jamming Algorithm Based on Dyna-Q
The anti-jamming algorithm based on Dyna-Q communication can be summarized as Algorithm 1:  
```
Initialize\(Q(s,a)=0,\ \textbf{model}(s,a)=0,\ \forall s\in\textbf{S},\forall a\in\textbf{A},\ \text{set the parameters }\alpha,\ \gamma\). For\(t=1,2,\dots T\)do (1) In the current environment state \(s_{t}\), the transmitter performs the last decision action \(a_{t}\), or the initial action to select the next communication node; (2) After taking the action \(a_{t}\), the payoff \(r\) and the state \(s_{t+1}\) at the next moment can be obtained. (3) According to Equation (7), the Q function is updated. (4) The latest quad \((s_{t},a_{t},s_{t+1},r)\) is used to update \(\textbf{model}(s,a)\). (5) \(n\) cycles are performed: 1 Random quads \((s_{t},a_{t},s_{t+1},r)\) are selected from \(\textbf{model}(s,a)\); 2 The Q function is updated according to Equation (7). (6) The receiver gets the transmitter action \(a_{t+1}\) at the next moment according to the following criteria and sends it back to the transmitter: \(a_{t}\ =\ \left\{ \begin{array}{ll}\underset{a\in A}{\arg\max}Q(s_{t},a)& \text{Probability of }1-\varepsilon\\ \forall a\in\mathcal{A}&\text{Probability of }\varepsilon\end{array} \right.\) endfor
```  
**Algorithm 1**Anti-jamming algorithm for wireless communication network
# Predicting Shot Accuracy in Badminton Using Quiet Eye Metrics and Neural Networks
## 2 Related Work
### The Quiet Eye in Sports Performance  
In recent years, the role of Quiet Eye (QE) in sports has evolved from descriptive analyses to predictive applications. Studies in sports like basketball, golf, and archery have shown how QE duration positively correlates with motor skill success. For instance, [PERSON] et al. [3] demonstrated that longer QE durations are associated with improved accuracy in precision sports like basketball, where targeting is crucial. Similarly, research in tennis has shown that expert players, particularly in high-pressure situations, benefit from extended QE periods, allowing them to better anticipate and react to their opponent's moves [3].  
[PERSON] et al. [4] demonstrated that QE training can significantly improve performance under pressure in golf, with increased QE duration and total fixation time correlating with better outcomes. Their study showed that after QE training, golfers displayed longer quiet eye movement time and total fixation time, leading to higher hit ratios and better putting performance under pressure conditions.  
Research in racket sports like badminton remains comparatively limited, although existing studies suggest that QE has the potential to influence shot accuracy in fast-paced environments. [PERSON] et al. [5] observed that QE durations tend to decrease under physical fatigue, even in high-paced environments like table tennis, but are sustained during successful shots. This suggests that QE could be an important factor for maintaining performance under physical stress, which is common in sports like badminton.  
[PERSON] et al. [6] suggest that in sports where fast responses and pinpoint accuracy are needed, visual attention, which is a key aspect of QE, is crucial. While their work primarily focuses on eye-tracking technology, its implications are highly relevant to sports like badminton, where swift decision-making is essential.  
[PERSON] & [PERSON] [7] explored differences in QE between expert and novice players, demonstrating that expert athletes exhibit significantly longer QE durations, which correspond to higher accuracy rates in basketball. This research supports the potential for QEto serve as a key component in developing training interventions for badminton players, particularly by helping novices stabilize their cognitive and visual focus.  
[PERSON] et al. [4] demonstrated that QE training enhances accuracy and performance under pressure in precision sports, showing increased QE duration and total fixation time during successful performance. Their findings in golf contribute to the growing evidence that QE training can benefit athletes across various precision-based sports.
# Nano-/Microcapsules, Liposomes, and Micelles in
## 2 Spherical Nanoparticles  
The prevalent spherical nanostructures used as carriers for bioactive compounds are nanocapsules, micelles, inverted micelles, and liposomes (Figure 1).  
Polysaccharides are a promising biomaterial for developing nutrient delivery systems due to their high stability, hydrophilicity, biodegradability, non-toxicity, and biocompatibility, coupled with their versatile chemical functions. Particle size, shape, and potential have a crucial impact on nutrient uptake by spherical nanoparticles, which are obtained primarily through hydrophobic interactions, hydrogen bonds, and electrostatic interactions [47]. The shape and size of a nanoparticle have an impact on the biological processes of living organisms. The size determines the potential for intracellular transport such as phagocytosis, endocytosis, and transportation through blood vessels, which, in turn, influences permeation through cell membranes, tissues, and organs. According to scientific reports, it is advised that the nanoparticle size should not be too small. It is established that renal excretion ranges from 6 to 8 nm. Additionally, particles smaller than 6 nm may be coated with serum proteins in the bloodstream, resulting in a larger hydrodynamic diameter, which can hinder renal excretion. Nanoparticles larger than 100 nm are likewise captured by macrophages in the lung, spleen, or liver [48]. Moreover, nanoparticles' high surface area-to-volume ratio has an impact on the quick release potential of the core substance or drug.  
Recent scientific research indicates that spherical polysaccharide nanoparticles possess the potential to be utilised as functional biomaterials in the food industry, particularly for the encapsulation of hydrophobic natural phytochemicals (such as zein-Mesona quinensis) [47; 49]. The capsule core wall includes polysaccharides that act as a surface decorator. This can potentially improve cellular uptake and increase the anticancer effectiveness of nanomaterials [50]. The polysaccharide used affects the potential of the particles, which further influences their applicability and usage. For instance, chitosan, currently the most widely used polysaccharide, is capable of electrostatic interaction with negatively charged mucosal surfaces, resulting in favourable mucoadhesive properties. Furthermore, the presence of a positively charged NH\({}_{3}\)+ group in chitosan allows for interaction with negatively charged proteoglycans on the cell surface, leading to improved absorption of the nanoparticle core in the gut by promoting the opening up of connections between epithelial cells [51; 52]. Depending on the utilisation and characteristics of the polysaccharide, it can be determined how the active ingredient of the nanocapsule's core will impact the consumer within the product. For example, dextran possesses multiple hydroxylated groups, making it easily conjugated to proteins [51].
# Exploring Pre-Trained Models for Skin Cancer Classification
## 3 Materials and Methods
### Considered Pre-Trained Models
#### 3.3.2 VGG19  
VGG19 is a deep CNN with 19 layers, characterized by its uniform architecture, where small 3 \(\times\) 3 convolutional filters are stacked sequentially. The model employs max pooling layers for downsampling, enabling it to capture complex patterns in medical images. While VGG19 is computationally intensive due to its depth, its structured architecture makes it effective for fine-grained image classification tasks, such as distinguishing different types of skin lesions.
# Microplastics' Detection in Honey: Development of Protocols in a Simulation
###### Abstract  
Honey, renowned for its nutritional and therapeutic properties, has recently come under scrutiny due to its contamination by microplastics, in multiple ways. Bees' exposure to plastic pollution impacts the whole hive's ecosystem, and plastic tends to accumulate in hive products. Plastic packaging as polyethylene terephthalate (PET) is used to store honey in small flexible packages, which also increases the risk of microplastic migration. This study aims to establish three practical detection methods for PET microplastics and nanoplastics in honey, using readily available laboratory equipment without the need for chemical digestion or costly pretreatment protocols, in a laboratory-based simulation. The first method utilizes Raman micro-spectroscopy, offering high-resolution identification of PET microplastics on cellulose acetate filters with Raman mapping, eliminating the need for organic solvents or dyes. The second method employs optical microscopic observation under fluorescence with the aid of 4-dimethylaminoa-4'-nitrosolhene dye and ultraviolet radiation to enhance microplastic visibility, making it suitable for laboratories with standard optical microscopes. To isolate MPs from the solid honey particles, a density separator has been introduced using pentane. Lastly, the third method employs the use of electrospray ionization mass spectrometry for the detection of nanoplastics (<200 nm) in honey samples, through the examination of the different extraction phases of density separation. All the aforementioned methods contribute to efficient microplastic detection in honey, ensuring its quality and safe consumption.  
polyethylene terephthalate (PET); nanoplastics (NPs); Raman spectroscopy; density separation; pentane; 4-dimethylaminoa-4'-nitrosolhene (DANS); fluorescence; electrospray ionization mass spectrometry (ESI-MS)
## 5 Treatment
### Adjuvant Treatments
#### 5.3.3 APCs  
APCs have emerged as a notable advancement in the management of MRONJ, offering promising results in mitigating the onset of MRONJ and fostering rapid epithelialization [8; 9]. These concentrates, enriched with growth factors, are instrumental in modulating inflammation and expediting the immune response, crucial factors in the healing process for patients undergoing BP treatment.  
A systematic review scrutinizing 19 studies, including controlled interventions, observational studies, and cohorts, delves into the efficacy of APCs, alongside laser therapy, in the prevention and treatment of MRONJ [8]. The review accentuates the therapeutic potential of APCs in enhancing the healing of hard and soft tissues, thereby reducing the recurrence rates of MRONJ. Although initial, non-invasive treatments typically involve antibiotics and antiseptics, surgical intervention, such as the removal of necrotic bone, is sometimes indispensable. The review corroborates those surgical approaches, particularly when combined with APCs like \"platelet-rich plasma\" and \"leucocyte- and platelet-rich fibrin\", that yield superior clinical outcomes and comprehensive soft tissue healing, underscoring the synergistic effect of combining surgical debridement with APCs for improved bone tissue maintenance and overall healing [8].  
Complementing this, another review rigorously evaluates the application of APCs and MSCs as adjunct therapies for MRONJ, analyzing data from 29 articles encompassing 306 patients [9]. This review acknowledges the role of APCs in advancing tissue healing by introducing growth factors that facilitate cell chemotaxis, proliferation, differentiation, angiogenesis, and the formation of a new extracellular matrix. However, it also recognizes the necessity for more extensive research to substantiate these preliminary findings and develop standardized clinical protocols for the effective application of APCs and MSCs in MRONJ management [9].  
In summary, both reviews highlight the potential of APCs in enhancing the recovery process for patients with MRONJ, suggesting a beneficial role in both prevention and treatment strategies. Nonetheless, they also underscore the need for further empirical studies to solidify the scientific evidence supporting the use of APCs and MSCs and to establish robust, standardized treatment protocols in clinical practice.
###### Abstract  
The present study analyzes the potential propagation trajectories and fate of floating microplastic particles released on the Kara Sea shelf. The transport of microplastics is described using a Lagrangian model based on daily 2016-2020 data obtained from numerical modeling of Arctic Ocean dynamics. A particle biofouling model is used to simulate the submergence of floating microplastic particles in the water column. The model includes a parameterization of the processes of biofilm accumulation (via collision with algae in surrounding water, algae growth) and degradation (via respiration, mortality). The behavior of microplastic particles of different sizes (0.5 and 0.01 mm) during the sinking process and subsequent rising due to biofilm degradation is examined. The simulation results reveal that particles of 0.01 mm in size display a tendency to sink immediately during the process of biofouling. However, when the biofilm degraded, the particles exhibited a rising velocity, comparable to the current vertical velocity, and the particles remained submerged in the water for long periods. In contrast, the 0.5 mm particles remained at the surface for a longer period before sinking, accumulating biofilm. Subsequently, their behavior was oscillatory in response to changes in the biofilm, rising rapidly when the biofilm decayed and sinking rapidly again as a result of biomass accumulation. In winter, the 0.5 mm particles were mostly frozen into the ice. The phenomenon of biofouling, whereby microplastic particles of various sizes sink at different depths, results in considerable variation in the subsequent pathways of these particles in the Arctic Ocean.  
plastic pollution; ocean microplastic transport; biofouling parameterization; numerical modeling; Arctic Ocean 2024 14 10229
# Effect of Shot Peening on the Evolution of Scale on T91 Steel Exposed to Steam
## 5 Conclusions  
In this work, the effects of shot peening on preventing the oxidation scale formed on T91 upon steam exposure were investigated. We reach the following conclusions:  
1. Grain refinement occurs on the top surface of the 10-min shot peened specimen, for which the grain size is \(\sim\)3 \(\upmu\)m, compared to the original grain size of \(\sim\)10 \(\upmu\)m.
2. After 100-600 h steam exposure at 650 \({}^{\circ}\)C, oxide scales formed on T91 specimens were identified as: an uppermost Fe\({}_{2}\)O\({}_{3}\) layer, an Fe\({}_{3}\)O\({}_{4}\) layer below, and an FeCr\({}_{2}\)O\({}_{4}\) spinel layer. The total scale thickness of the SP and untreated specimens as measured at various steam exposure durations follows parabolic oxidation kinetics. Untreated specimens exhibit much larger scale thickness and faster scale growth rate than SP-treated specimens, indicating that shot peening improves oxidation resistance.
3. After steam exposure for 800-1000 h at 650 \({}^{\circ}\)C, numerous voids and micro-cracks form between the Fe\({}_{2}\)O\({}_{3}\) and Fe\({}_{3}\)O\({}_{4}\) layers in the untreated specimens, resulting in partial exfoliation of the uppermost Fe\({}_{2}\)O\({}_{3}\) layer. In contrast, the SP-treated specimens retain dense and compact oxidation scale with few voids or micro-cracks.
4. A Cr-depleted zone forms at the oxide-metal interface in the SP-treated specimen after 100 h steam exposure, in which decomposition of M\({}_{23}\)C\({}_{6}\) precipitate is observed.  
Conceptualization, Y.H. and L.X.; methodology, L.X. and Y.H.; validation, Y.H., Y.K. and K.S.; formal analysis, L.X.; investigation, L.X.; resources, Y.K. and Y.H.; data curation, L.X.; writing--original draft preparation, L.X.; writing--review and editing, K.S.; visualization, L.X.; supervision, K.S.; project administration, Y.K. and Y.H.; funding acquisition, Y.K. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the Korea Institute of Energy Technology Evaluation and Planning (KETEP) and the Ministry of Trade, Industry, and Energy (MOTIE) of the Republic of Korea (no. 20161110100090). This work was partially supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (no. 2018R1A5A6075959).  
Not applicable.  
The authors declare no conflict of interest.  
Figure 8: Cross-sectional SEM images of oxidation scale of SP-treated specimen after 600 h steam exposure.
# Improving Adversarial Robustness of CNNs via Maximum Margin
## 4 Experiments
### Robustness of AT-SVM Model  
In Table 1, we compare the performance of the standard AT, GAIRAT, and AT-SVM. We compare these methods to the best checkpoint model (suggested by [PERSON] et al. [19]). Besides the accuracy of clean data, we evaluate models' adversarial robustness by FGSM attack, momentum iterative method (MIM) attack [44], and PGD attack. All these attacks are generated with 20 iterations and \(\epsilon=8/255\). In addition, we follow the suggestion of evaluating transfer attacks by [PERSON] et al. [14] to inspect whether the models trained by AT-SVM will cause the issue of obfuscated gradient and give a false sense of model robustness. We test the black-box PGD attack (PGD-b), in which we generate adversarial examples of CIFAR-10 from SAT models and evaluate their attack performance on the target mode. Moreover, we also use the ray searching attack (RayS) [45] to test the robustness of the models under hard-label or gradient-independent attack. For RayS, we set the maximum number of queries to 10,000. All experimental data are obtained in our implementation.  
Compared with SAT, our AT-SVM improve adversarial robustness without degradation of clean accuracy, which alleviates the trade-off problem between accuracy and robustness. GAIRAT also achieves this effect, but we found that its robustness under black-box attacks is lower than under white-box attacks, which means there is an obfuscated gradient. Instead, our approach avoids this. In Table 1, the \"Robustness\" is the lowest accuracy under all attacks in the experiment to approximate the adversarial robustness.  
In Figure 3, we show some sample images from the CIFAR-10 dataset, with their corresponding adversarial examples. We find that the robust models trained by AT-SVM have strong interpretability. It can be found that a normal model can be attacked by adversarial perturbation not perceptible to humans, while the adversarial image of the AT-SVM model has obvious features of the misclassified class. This shows that images around the decision boundary of the robust model have features of both classes.  
\begin{table}
\begin{tabular}{l c c c c c c c} \hline \hline
**Methods** & **Clean** & **FGSM** & **MIM** & **PGD** & **PGD-b** & **RayS** & **Robustness** \\ \hline Natural & 90.09 & 0 & 0 & 0 & 0 & 13.01 & 0 \\ SAT & 82.64 & 57.15 & 55.15 & 52.23 & 52.23 & 62.05 & 52.23 \\ GAIRAT & 78.84 & 62.62 & 62.30 & 60.47 & 54.19 & 54.17 & 54.17 \\ AT-SVM & 83.51 & 59.35 & 58.54 & 56.38 & 59.76 & 62.40 & 56.38 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Test accuracy of ResNet-18 on CIFAR-10 dataset.
# Ultra-Low-Power Wide Range Backscatter Communication Using Cellular Generated Carrier +
## 2 Background
### Low Power Wide Area Network (LPWAN)
#### 2.1.5 Ingenu  
Ingenu from the On-Ramp Wireless company [12], who developed and owned the random phase multiple access (RPMA) technique [17], is another emerging LPWAN technology. Different from the most of LPWANs using sub-GHz, Ingenu works at 2.4 GHz band. The robust physical layer design of Ingenu enables long-range radio link under challenging RF environments.
## 2 State of the Art
### Energy Control Models and Optimization Models
The different contributions of this article related to energy control and optimization models are as follows:  
* Define an energy model for each AIV using an optimal control problem. * Create a database for the optimal speed of an AIV between two nodes by solving the optimal control problem. * Propose an offline/online algorithm for energy consumption that calculates the speed profile and energy consumed for each AIV mission. * Present three strategies for speed profiles based on two parameters: waiting baggage and traffic circulation. * Develop a fuzzy logic model to select the appropriate strategy for each AIV during its mission.
## 3 Results and Discussion
### Characterization of the Materials
#### 3.1.5 Sem  
The surface morphology and microstructure of the XDA-1G resin were examined using FESEM-EDS, as shown in Figure 6a-f. At lower magnification (Figure 6a,b), the XDA-1G resin particles exhibit a uniformly spherical morphology with relatively consistent size distribution, indicating a well-defined polymerization process and structural integrity. This particle geometry is advantageous for practical application in packed beds or batch systems, ensuring good dispersion and minimal channeling.  
Figure 6: SEM and EDS characterization of the XDA-1G resin. (**a–d**) Scanning electron microscopy (SEM) images of the XDA-1G resin at various magnifications, revealing smooth, spherical morphology and uniform particle distribution; energy-dispersive X-ray spectroscopy (EDS) data tables are shown as insets in (**c,d**), confirming elemental composition. (**e,f**) SEM-EDS elemental mapping images of carbon and oxygen, demonstrating a uniform elemental distribution across the resin surface.  
Higher magnification images (Figure 6c,d) reveal that the XDA-1G resin surfaces are smooth but exhibit microtextural heterogeneity, potentially related to underlying microprosity or structural flexibility in the polymer matrix. Although macropores are not directly observed, the surface features suggest the presence of fine-scale roughness and submicron porosity. These observations are in agreement with nitrogen adsorption-desorption measurements, which confirmed a high BET surface area (1439 m\({}^{2}\cdot\)g\({}^{-1}\)) and a hierarchical pore structure, including both micropores and mesopores, as essential contributors to adsorption performance.  
Elemental composition and spatial distribution were analyzed through EDS, as presented in the insets of Figure 6c,d, and the corresponding elemental maps are shown in Figure 6e,f. The EDS spectrum and the corresponding atomic percentage table confirm that the resin is primarily composed of carbon (C: \(>\)90%) and oxygen (O: \(>\)5%), which are uniformly distributed over the XDA-1G resin surface. The high carbon content is consistent with the styrene-divinylbenzene (S-DVB) polymer backbone, while the oxygen content suggests the presence of oxygenated functional groups, likely introduced during post-synthetic processing or functionalization steps. Minor signals of silicon and chlorine were also detected, likely originating from processing additives or backbone modification.  
Overall, the SEM and EDS analyses provide critical morphological and compositional insights that align with the manufacturer's specifications and support the resin's suitability for adsorption applications. The spherical particle morphology, porous surface structure, and elemental composition contribute to the high surface area, accessible adsorption sites, and chemical affinity required for effective removal of organic contaminants like m-cresol.