esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Conclusions  
The performance of the oxygen carrier is the key to the tar conversion during the chemical looping gasification of biomass. The in-situ conversion of toluene as a biomass tar compound using catalytic oxygen carrier of Ni-decorated LaFeO\({}_{3}\) were investigated. The performance of LaM (M = Fe, Ni, Mn, Co, and Cu) with different transition metals was initially evaluated. LaFe (partial oxidation) and LaNi (catalytic pyrolysis) exhibited better reactivity on promoting syngas production than other oxygen carriers. Therefore, Ni-substituted ferrite LaFe\({}_{1.X}\)Ni\({}_{x}\) (x = 0, 0.2, 0.4, 0.6, 0.8 and 1) was further developed to enhance the toluene conversion. The substitution of Ni (x > 0.4) significantly strengthened the H\({}_{2}\) formation, too much Ni substitution would cause either over-oxidation or serious coke formation. Steam addition promoted the toluene steam reforming and carbon gasification, enhancing C\({}_{1}\) and H\({}_{2}\) yield, and Ni addition can further enhance the reactivity stability of oxygen carrier. With S/C increasing from 0.8 to 2.0, the C\({}_{1}\) and H\({}_{2}\) yield increasing from 74% to 97% and from 198 to 270%, respectively. The elevated temperature (800-900 \({}^{\circ}\)C) also exhibited a positive effect on C1 yield would further increasing C1 yield. A 10-cycle stable operation of chemical looping toluene conversion indicates that the LaFe\({}_{0.6}\)Ni\({}_{0.4}\) has strong reactivity stability for toluene conversion at S/C=1.6 at 900 \({}^{\circ}\)C.  
Not applicable.  
Data Availability StatementData is contained within the article.  
The authors declare no conflict of interest.  
Figure 14: Yield of C\({}_{1}\), H\({}_{2}\), and coke (\(\times\)30) during chemical looping toluene conversion using LaFe\({}_{0.6}\)Ni\({}_{0.4}\) with S/C = 1.6 at 900 \({}^{\circ}\)C.
# Computational Modeling of U-Shaped Seismic Dampers for Structural Damage Mitigation
## 5 Future Research  
### Optimizing Seismic Response and Lifetime of U-Shaped Dampers  
The detailed numerical models that characterize local stress, strain, and energy dissipation patterns provide a solid foundation for optimizing the design of high-performance U-shaped dampers for seismic applications. Various optimization approaches could be explored, such as maximizing the energy dissipation capacity, bidirectional capability, optimizing material selection, and achieving a more homogeneous strain distribution to enhance fatigue life. Furthermore, the integration of the design of experiment methodologies could reduce the number of numerical models required during the optimization process. Additionally, the reliable mesh discretization established by this numerical model enables the application of more sophisticated models that consider micromechanical damage, fracture prediction, and fatigue behavior, ultimately leading to accurate lifetime predictions for U-shaped dampers and, consequently, safer designs to improve structural resilience during seismic events.
## 3 Results and Discussions
### Droplets Size Evolution
#### 3.2.2 Droplets Shelf-Life during Storage  
To determine the droplets shelf-life during the storage, an accelerated aging test was carried at elevated temperatures. The test is intended to increase the rate of chemical degradation or physical change of the products in a relatively short time. According to [PERSON], 1995 [15], the resistance emulsion-based products against phase separation before and after the test are equivalent to the stability for 2 years under normal conditions. The shelf-life of the droplets during the storage is presented in Figure 5.  
After 5 days of storage (Figure 5a, solid line), the exothermic peak still has the same shape as the fresh one before storage (Figure 5a, dotted line), where the mean freezing temperature is still around T* = \(-35.5\)\({}^{\circ}\)C. T* moves to the higher temperature \(-34.8\)\({}^{\circ}\)C (Figure 5a, dashed line) after 10 days then shifts to \(-33.8\)\({}^{\circ}\)C (Figure 5a, dotted line) after 14 days. The droplets beginning to coalesce during the test is indicated by increasing T* to the higher temperature. Even though the exothermic signal is the same as the fresh one, the droplets merge continuously but they did not break at all.  
Figure 5: Observation droplet shelf-life during storage by (**a**) DSC test; (**b**) laser diffraction granulometry; and (**c**) optical microscopy.  
These results are in accordance with the droplet size calculation that is summarized in Table 4. The emulsions resist destabilization during storage. A similar volume means droplet size distribution is obtained for the emulsions in 0 days and 5 days, D43 = 10 \(\mu\)m. The droplets size, D43 at the 10 days is 11 \(\mu\)m and then it increases to 14 \(\mu\)m at the end of the test. Figure 5c shows the population is the mono-disperse distribution for all samples of the test. It means that the emulsion produces long term stability. In general, temperature affects emulsion stability significantly. Temperature changes the properties of interfacial films and surfactant solubility in oil and water phases. Temperature increases the frequency of drop collisions. It also reduces the interfacial viscosity, which results in faster film drainage rate and faster droplets coalescence [26].
## 4 Conclusions  
A comparative study between equivalent-circuit and behavioral modeling approaches for reproducing transistor scattering parameter measurements was presented. The comparison was accomplished by using \(S\)-parameters measured up to 65 GHz on a 0.25 \(\times\) 1500-\(\upmu\)m\({}^{2}\) GaN HEMT on a silicon carbide substrate. The tested device was heated up to 200 \({}^{\circ}\)C and biased at \(V_{DS}\) = 30 V and \(V_{GS}\) = \(-\)3.1 V. Three different modeling strategies were analyzed: an equivalent-circuit model, artificial neural networks, and gate recurrent units. It was found that each modeling strategy possesses its own inherent strengths and weaknesses, and the best choice depends on the actual use of the model. To be sure that the selected model is the best choice, it is necessary to carefully examine the model performance in terms of prediction accuracy, generalization ability, computational efficiency, representation compactness, and model usefulness. The developed analysis showed that the equivalent circuit is a compact representation based on using sixteen parameters, which allowed for achieving a good prediction accuracy and may be very useful as physically meaningful feedback for improving device fabrication and as a starting point for building both large-signal and noise models. On the contrary, behavioral-based techniques have the great advantage of allowing achieving straightforward better prediction accuracy without needing to determine an equivalent-circuit representation. In addition, ANNs allow for ob  
\begin{table}
\begin{tabular}{c c c c} \hline \(T_{a}\) (\({}^{\circ}\)C) & \(g_{m}\) (mS) & \(C_{gg}\) (pF) & \(f_{T}\) (GHz) \\ \hline
35 & 347.9 & 2.560 & 21.63 \\ \hline
90 & 293.6 & 2.372 & 19.70 \\ \hline
145 & 249.7 & 2.222 & 17.89 \\ \hline
200 & 215.4 & 2.130 & 16.09 \\ \hline \end{tabular}
\end{table}
Table 4: Values of \(g_{m}\), \(C_{gg}\), and \(f_{T}\) as a function of \(T_{a}\) for a GaN HEMT at \(V_{DS}\) = 30 V and \(V_{GS}\) = \(-\)3.1 V.  
taining a very good prediction accuracy even for data different from those used in training, thereby demonstrating the model generalization ability of the behavioral-based approach.  
Investigation, G.C., M.L., G.G., Z.M., J.C. and G.B.; Methodology, G.C., A.R. and N.D.; Supervision A.R., E.F. and N.D; Writing--original draft, G.C., M.L., G.G., Z.M. and G.B.; Writing--review and editing, J.C., A.R., E.F. and N.D. All authors have read and agreed to the published version of the manuscript.  
This research was funded in part by the Italian Ministry of University and Research (MUR) through the PRIN 2017 Project under Grant 2017 FL8C9N, by the GaN4 AP (GaN for Advanced Power Applications) project (CUP: B82C21001520008), and by the Ministry of Science, Technological Development and Innovations of the Republic of Serbia.  
Not applicable.  
The authors declare no conflict of interest.
# Improvement of [PERSON]'s Stripe Noise Suppression Method for Side-Scan Sonar Images
## 2 Methods
### Improved Algorithm for Stripe Noise Suppression in Side-Scan Sonar Images
#### 2.2.2 Improvement of Optimal Match Block Search  
Firstly, in the Criminisi algorithm, the search for the optimal matching block employs a global search, meaning that it searches the entire image for the best match. However, for stripe noise suppression in side-scan sonar images, such an exhaustive search is unnecessary. The process primarily aims to restore the background and textures of the side-scan sonar image, where the best matching block inevitably exists near the region to be restored. Therefore, in this method, the global search is replaced with a local search, significantly enhancing the restoration efficiency.  
The original algorithm uses the Sum of Squared Differences (SSD) criterion between the target block to be restored and the sample blocks. However, this criterion has poor adaptability to side-scan sonar images with complex textures and noise, as it cannot choose the best block when the computed differences are equal. To address this, a feature similarity-based matching criterion is introduced. The experimental results, as shown in Figure 3, (a) depict a side-scan sonar image with stripe noise, while (b) shows the image denoised using the feature similarity-based criterion. As can be seen in the figure, the texture of the denoised image is not consistent with the intact part in the original noisy image, and there is only a certain similarity in color. The results indicate that this criterion fails to effectively remove stripe noise. Therefore, in this paper, an improvement is proposed based on the SSD criterion, where calculations are confined to the known regions, and, in cases of equal differences, a Manhattan distance metric is introduced to further select the optimal block. The experimental results demonstrate that the proposed enhancement achieves superior restoration outcomes.
## 2 Materials and Methods
### Selection of Potential Bacterial Strains as Protective Cultures
#### 2.1.1 Antimicrobial Activity of the CFS by Agar Well Diffusion Assay  
Nine micro-organisms, both pathogenic and spoiling, including different bacteria and yeasts, were selected as indicator micro-organisms (Table S3). In the case of pathogenic micro-organisms, the decision was taken based on the information collected in Rapid Alert System Feed and Food on the main pathogens responsible for food alerts in Europe in 2023 [4]. Spoilage micro-organisms were chosen among the most common micro-organisms in fresh and minimally processed foods, according to CNTA experience.  
The antimicrobial activity of the potential CFSs against the indicator strains was determined by using the modified agar well diffusion assay [26]. Briefly, TSA-YE agar (0.8\(\%\)) was autoclaved, poured 20 mL onto each petri dish (VWR) of 90 mm, and solidified. When the plates were ready, a concentration of 10\({}^{6}\) CFU/mL of the indicator micro-organism was evenly added and spread with a sterile Digralsky loop to form lawn growth cells. Then, wells of 7.2 mm in diameter were made in the plates using a sterile borer, and the wells were filled with 100 \(\upmu\)L of the testing CFS (Table S1). The plates were kept for 2 h at room temperature on the bench to aid the diffusion. Finally, they were incubated in aerobic or anaerobic conditions at different temperatures for 24 or 48 h depending on the micro-organism tested. After that time, the inhibition halo was measured. Considering the criteria outlined by [PERSON] et al. [27] and [PERSON] et al. [28], the antimicrobial activity of the CFSs was classified based on the inhibition halo showed by indicator micro-organisms when exposed to each CFS. Including the diameter of the well (7.20 mm), it was deemed negative when the resulting halo was less than 9.20 mm above the diameter of the well, while a halo ranging from 9.20 to 15.0 mm was considered medium activity. If the inhibition halo ranged from 15.00 mm to 25.00 mm, it was categorized as high antimicrobial activity. A halo of more than 25.0 mm was considered as strong antimicrobial activity.
## 1 Introduction
The perturbation of particles in PSO depends on the summation of vector position and velocity in which if a large perturbation is selected, it increases the perturbation but may cause the particles to overlook the optimum point. If a small perturbation is chosen, it may increase the number of iterations where a longer time is taken to reach the MPP [40]. Lately, the interest in metaheuristics optimization has caught the attention of many researchers [41]. The biological behavior of animals or birds can be simulated to search the optimum solution of a given problem. Metaheuristics optimization algorithms are implemented in MPPT such as Ant Colony Optimization, Artificial Bee Colony [2], Cuckoo search [40], and the Fireflies Algorithm [42]. The performance of these algorithms in MPPT application shows good results in terms of tracking speed, steady-state oscillation, and stability. Levy flight has been applied in various fields, especially in biology and engineering [43]. The study done by authors [44; 45] reveals that the technique of using Levy flight in PSO by replacing the Levy distribution in PSO shows a great advantage in terms of the time response compared to the conventional PSO technique. In their studies, this technique is compared with a set of problems with different benchmark functions. The research reveals that Levy-based PSO outperforms the conventional PSO with a fast response time due to the characteristics of the Levy flight distribution with fat-tailed characteristics [43]. This significantly inspired the authors to apply this technique in MPP. This paper presents a modified LFO algorithm that incorporates some modifications to the conventional Levy flight search. The proposed method is inspired by PSO behavior in the search of MPPT, and the formula of Levy flight with modification of the \(\beta\) parameter to the global best particles is included. This has significantly improved the performance of the conventional Levy flight with the global search capability in the algorithm. The response time and efficiency of MPPT in tracking local and global optimums are significantly improved. Section 2 explains the PV configuration, modeling, and converter system. Section 3 presents the overview of Levy flight optimization. Section 4 describes MPPT with the modified Levy Flight Optimization. Sections 5 and 6 present the results and discussion from the simulation and experiment, respectively. Lastly, the conclusion is given in Section 7.
# Progress in Transparent Nano-Ceramics and Their Potential Applications
## 2 Transparent Nano-Ceramics for Solid-State LASERs
### Summary  
Since it took [PERSON] and [PERSON] [12] 31 years to use lasers for Nd:YAG transparent nano-ceramics in 1995, this was not a rapid development. Over the next seven years, advances in powder synthesis and ceramic sintering allowed the 1 kW output power threshold to be broken in 2002 [13], followed by another seven years until the 100 kW mark was crossed in 2009 [33; 34].  
In terms of powder-preparation methods, the most mature technologies are the solid-state reaction method and liquid-phase coprecipitation process. The solid-state reaction method has a simple process, but the commercial raw material powder used has low sintering activity, which is not conducive to the densification of transparent ceramics. In terms of doped YAG transparent ceramics' sintering, vacuum sintering is currently the most commonly used sintering technology for fabricating them. Although vacuum sintering helps to eliminate pores and improve the density, it is nevertheless unable to entirely eradicate residual pores inside the ceramics, resulting in most sintered samples having a transmittance of less than 80%. In addition, according to the needs of solid-state lasers, rare earth ion-doped YAG transparent ceramics can be used to make laser materials with excellent performance, which are widely used in the field of solid-state lasers.  
It can be seen from the above experiments that after doping with Nd\({}^{3+}\), the transmittance increases to 81.8%; the output power of Ho-doped sesquioxide ceramics is nearly an order of magnitude higher than that of other ceramics; Er-doped YAG transparent ceramics have very low levels of quantum defects, and their peak power can also reach 11.3 kW; Tm-doped ceramics can ensure an efficient step-down version of energy transfer; and Yb doping can adjust the environment and the temperature inside the pumping laser medium. In general, the transmittance and output power of ceramics doped with YAG were greatly improved, and the temperature could be controlled at the same time, which makes them a good candidate for ultrafast lasers with a high power density and high power output.  
However, most of the current research on Nd:YAG transparent ceramics is based on experimental results [36; 37], and there is a lack of relevant theoretical simulation data. For example, there is still a lack of research on the relationship between structural defects (such as grain boundaries) and the photothermal damage of ceramics, as well as on the types and concentration distributions of doped rare earth ions. In addition, it is also necessary to study the occupancy mechanism and distribution of dopant ions of different types  
Figure 4: Schematic diagram of YAG transparent nano-ceramics’ application in laser diode pumping system.  
and concentrations inside the ceramic, as well as the influence of the surrounding crystal field. These breakthroughs in the mechanism of action need to be solved through effective theoretical models.
## 7 Algorithm Process  
Overall, the process of proposed adaptive algorithm is summarized as following.  
1. Initialization * Initialize the PNCM Q, the measurement noise covariance matrix R, the initial state \(x_{0}\). * Initialize the parameters used in VB algorithm. * Initialize the neural network parameters state \(\W_{0}\), which contains the linkweight and threshold value. * Initialize the prediction error \(e_{0}\), whose all compents are equals to 0.
2. Perform the algorithm For \(k=1,2,3,\cdots\) do // for each time instant * Predict state \(\x_{k}^{-}\) and its covariance matrix \(\P_{k}^{-}\) via Equations (5) and (6).  
Figure 6: The neural network structure.  
* If \(k>60\)
* Calculate the prediction error \(\mathbf{e}_{k}\) via Equations (38) and (39).
* Update the neural network parameters vector \(\mathbf{W}_{k}\) via Equations (A25)-(A29).
* Perform the state updating via Equations (7)-(11) based on Extended Kalman filter.
* Estimate the PNCM based on VB algorithm via Equations (A1)-(A14), Equations (A18) and (A19), and Equations (A22) and (36). end For
# Porcine Parvovirus 7: Evolutionary Dynamics and Identification of Epitopes toward Vaccine Design
## 4 Discussion
Based on molecular docking, peptides with potential to SLA and high immunogenicity scores may prove highly immunogenic. Importantly, two conserved overlapped peptides (KRRSRMFAP and RRSRMFAPT) with high immunogenicity scores (1.2953 and 0.9148) should be experimentally tested for the PPV7 vaccine in future studies. Many parvoviruses, including porcine parvovirus (PPV), human parvovirus B19 (B19V) and human bocavirus 1 (HBoV1), cause infections of their hosts. Among them, B19V is an important human pathogen responsible for a variety of diseases and causes various pathological symptoms, including nonimmune hydrops fetalis and fetal death in pregnant women [43]. Vaccination is the most effective strategy against B19V pathogenesis and infection. Currently, there are two generations of B19V based virus like particles (VLPs) vaccines. The first generation of B19 VLPs consists of two viral structural proteins (VP1 and VP2) produced in the baculovirus expression system, and this induces neutralizing antibodies [44]. These vaccines, produced in insect cells, induced side effects, e.g., reactive symptoms in the host; therefore, baculovirus-based vaccines were abandoned during clinical trials. The second generation of B19 VLPs vaccines, composed of only VP2 protein, are expressed in _Saccharomyces cerevisiae_[44]. Until now, research for vaccines against B19V has been a huge challenge, due to the unavailability of viral antigens, a good cell line model and a virus-infected animal model. Moreover, there is almost no viremia in most B19V-infected patients when symptoms start to appear. Neutralizing antibodies against B19V are insufficient, emphasizing the importance of developing a vaccine that induces innate and cellular immunity against B19V. The research work of the B19V vaccine provides a further design reference for the PPV7 vaccine. Based on accumulated evidence, this newly emerging PPV7 has epidemic potential in the global swine population. There is limited information about its epidemiology, transmission, pathogenesis and molecular biology, or indeed, how PPV7 emerges in swine. Regardless, its presence in aborted pig fetuses and its co-infection with PCV2 imply that PPV7 threatens swine herd health security. Notably, the substitution rate of PPV7 was higher than PPV1-4, which may enable PPV7 to adapt to various environmental conditions and cause a substantial threat to the swine herd. Thus, a vaccine against PPV7 is needed to control this emerging virus infection. Inactivated vaccines against PPV1 have been used for 30 years because they hindered or reduced virus transmission. Low homology between PPV7 Cap and PPV1 suggested the PPV1 vaccine strains were not closely matched with PPV7 strains. Novel vaccine formulations containing PPV1 and the newly circulating strains PPV7 may overcome some potential weaknesses of current vaccines, perhaps increasing vaccine efficacy.
## 3 System Model
### Network Model  
As shown in Figure 1, this paper considers a rural area that is not covered by terrestrial networks. There is an LEO satellite with an MEC server in space that can cover this area. The computing capability of the MEC server deployed at the LEO satellite is weaker than that of the MEC server deployed at the BS. \(N\) UEs are randomly distributed in this area, and the set is expressed as \(\mathcal{N}\). These UEs are very small aperture terminals (VAST), which are equipped with directional antennas, so UEs can communicate with the LEO satellite directly. Each UE requests an indivisible task with two attributes, e.g., UE \(i\) requests task \(i\)\((c_{i},a_{i})\), \(c_{i}\) is the computing intensity, i.e., the computing resources required to compute 1 bit of task \(i\) (cycles per bit), and \(a_{i}\) is the data size of task \(i\) (bits). UEs can offload tasks to the LEO satellite, utilizing its MEC server to compute tasks. There is a BS deployed with an MEC server in an adjacent area, and the BS connects to a near gateway by wired connection. In addition to computing tasks by itself, the LEO satellite can migrate some tasks to the BS and make use of its MEC server to compute tasks. Different UEs have different computing capabilities. MEC servers have more computing resources than UEs, but their computing resources are limited. UE \(i\) has three strategies to complete its own task. UE \(i\) computes task \(i\) locally, i.e., local computing. UE \(i\) offloads task \(i\) to the LEO satellite, task \(i\) is computed by the LEO satellite's MEC server, i.e., LEO satellite edge computing. UE \(i\) offloads task \(i\) to the LEO satellite, and the LEO satellite migrates task \(i\) to the BS, task \(i\) is computed by the BS's MEC server, i.e., LEO satellite-assisted terrestrial edge computing.