esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Experiment Results and Discussion
### Energy Dissipation
#### 3.2.2 Comparative Analysis Based on Different Influencing Factors
Influence of initial damage on the strengthening effect  
A comparison of RP-1 with RP-3 (Table 4) showed that initial damage reduced the peak load \(F_{p}\), initial stiffness \(K_{0}\), and ductility coefficient \(\mu\) of the strengthened specimens by 0.5%, 4.6%, and 32.3%, respectively. We inferred that the initial damage led to a slight weakening of the bearing capacity and initial stiffness of the pier column. Moreover, the damage accumulation between the initial damaged area and its filled concrete interface during the loading process inevitably weakened the ductility performance of the pier column. In addition, the secant stiffness \(K_{i}\), energy dissipation per cycle \(E_{hi}\), equivalent viscous damping \(\xi_{api}\), and stiffness degradation rate of the two specimens were highly similar during the entire loading stage (Figures 14 and 16). Hence, the stiffness, bearing capacity, and energy dissipation capacity of the strengthened specimen with initial damage could be restored to a near-undamaged state. Influence of length-diameter ratio on the strengthening effect  
A comparison of RP-1, RP-4, and RP-5 (Table 4) showed that the peak load \(F_{p}\), initial stiffness \(K_{0}\), and ductility coefficient \(\mu\) decreased as the length-diameter ratio of the strengthened specimen increased from 4 to 6 to 8, with total decreases of 53.8%, 70.7%, and 28.9%, respectively. Similarly, the secant stiffness \(K_{i}\), energy dissipation per cycle \(E_{hi}\), and equivalent viscous damping \(\xi_{api}\) significantly decreased with increased length-diameter ratios of the strengthened specimen during the entire loading stage (Figures 14 and 16). The larger the length-diameter ratio, the longer the effective length of the column and the greater the bending moment effect caused by the horizontal earthquake action, resulting in an apparent decrease in the bearing capacity, stiffness, ductility, and energy dissipation capacity of the strengthened pier columns.
## 2 Non-Symmetric Cross-Section  
In its most general form, the Vlasov theory [7; 8] applies to any thin-walled, non-symmetric, open cross-section (see Figure 1a,b). The theory is limited to small deformation linear elasticity in which infinitesimal strain is compatible with the first derivative of displacement. Forces applied are in static equilibrium with internal stress distributions, and the boundary conditions are matched to each thin-walled structure. Here, a cantilever beam with different thin-walled channel sections is examined. Stress analyses are presented for three symmetrical sections of standard US dimensions and one non-symmetrical channel with unequal flange lengths. Transverse forces \(F_{x}\) and \(F_{y}\) are applied at the centroid of the free-end section.
# Coordinated Multi-UAV Reconnaissance Scheme for Multiple Targets
## 5 Simulation Experiment
### Dynamic Task Planning Simulation  
The traditional dynamic assignment model gives more priority to the constraints than to the optimization objective, and the evaluation of new reconnaissance sequences temporarily disregards the objective of maximizing the gain. The traditional dynamic allocation mechanism for updating the reconnaissance sequence prioritizes the insertion of new reconnaissance targets after the closest task area, considering the goal of distance minimization to some extent. In contrast, the dynamic allocation mechanism proposed in this paper achieves an improvement by inserting the new reconnaissance target between the two nearest task areas and minimizing the cost of additional distance traveled.  
In the simulation experiments, the multi-UAV task assignment results, which are shown in Table 3, are selected as the initial assignment plan. A random moment is generated when dynamic task planning is required, and two contingency cases of decreasing the number of UAVs and increasing the number of task areas are triggered, respectively, followed by dynamic task assignment to satisfy the dynamicity requirement. The processing results of the two assignment models for each case are as follows.
## 2 Second Messengers in Cyanobacteria
### Calcium, Ca\({}^{2+}\)
#### 2.1.1 Calcium Controls Motility  
Calcium is involved in behavioral responses in prokaryotes, including directional motility in cyanobacteria [1, 23, 24, 25]. The first reported study to investigate the effects of Ca\({}^{2+}\) as a second messenger  
Figure 2: External signals controlling free intracellular Ca\({}^{2+}\) levels and phenotypes or processes that are controlled by Ca\({}^{2+}\) in cyanobacteria. Levels of free intracellular Ca\({}^{2+}\) are regulated externally by influx(es) of extracellular Ca\({}^{2+}\) through ion channels or internally by release of Ca\({}^{2+}\) from Ca\({}^{2+}\)-binding proteins. Green arrow from free [Ca\({}^{2+}\)] indicates increased Ca\({}^{2+}\) levels from external sources leads to noted phenotypes, whereas the red arrow indicates that increased Ca\({}^{2+}\) levels from internal sources leads to the noted phenotypes. Blue arrow indicates that referenced studies did not demonstrate whether the noted phenotypes are under external or internal control. +, indicates process promoted by increased cellular Ca\({}^{2+}\) levels; –, indicates process inhibited by increased intracellular Ca\({}^{2+}\) levels.  
in cyanobacteria showed that gliding was attributed to an increase in cellular Ca\({}^{2+}\) concentration [26]. A study of hormogonia, which are motile filaments of cells, confirmed that Ca\({}^{2+}\) was critical to promote the differentiation of hormogonia and sustain motility [27]. In _Synechocystis sp_. PCC 6803 (hereafter _Synechocystis_), depletion of free Ca\({}^{2+}\) resulted in diminished photoorientation and gliding speed [28]. Based on Ca\({}^{2+}\) chelation and calcium ionophore studies, the authors concluded that phototactic orientation was likely caused by the uptake of extracellular Ca\({}^{2+}\), whereas gliding motility was dependent on internal Ca\({}^{2+}\) mobilization or release from Ca\({}^{2+}\)-binding proteins [28]. Using genetic and biochemical approaches, proteins containing Ca\({}^{2+}\)-binding domains were discovered [29; 30; 31]. A key step to understand gliding motility in cyanobacteria was to isolate surface fibrils. Fibrils in some cyanobacteria are composed of a single type of protein called oscillin, which contains multiple Ca\({}^{2+}\)-binding motifs [29]. _Phormidium uncinatum_ filaments that did not accumulate oscillin were not able to glide [29]. Similar cell surface-associated glycoproteins function in this manner in other cyanobacteria [29]. Motility in _Synechococcus_ sp. WH8102 depended on the protein SwmA, a homolog of oscillin that contains Ca\({}^{2+}\)-binding motifs. A mutant lacking _swmA_ could still rotate but no longer exhibited swimming motility [30]. Calcium was also shown to promote swimming in _Synechococcus_ strain WH8113 [31].
## 2 System Composition and Working Principle  
The plant protection drone variable spray system designed by the research team is presented in Figure 1. It comprises a prescription graphic translation subsystem and a variable spraying subsystem. At first, the prescription value of the medication is interpreted by the prescription graphic translation subsystem from the prescription map of the work area. Subsequently, the prescription value is transmitted to the variable spray system. At last, the closed-loop PID control algorithm is utilized to adjust the duty cycle according to the prescription value received. By assigning a value to the single-chip timer counter, a square wave signal with an adjustable duty cycle is generated to adjust the rotation speed of the micro-diaphragm pump. Therefore, the way of variable spraying is realized. In the spray system pipeline, the flow information in the spray pipeline is fed back to the STM32 controller by the Hall flow sensor. Meanwhile, the instantaneous flow rate, real-time position, flight parameters and prescription values are displayed through the liquid crystal display (LCD).
## 3 Research Method  
### Heat Balance Model  
The heat balance model of the waste heat recovery system is established according to the law of thermodynamics. For the system used in this paper, the following parameters are mostly concerned in the data reconciliation calculation process. The total carbon dioxide mass flow in S-CO\({}_{2}\) cycle expresses as follows:  
\[\dot{m}_{\text{CO}_{2}0}=\dot{m}_{\text{CO}_{2}1}+\dot{m}_{\text{CO}_{2}2} \tag{1}\]  
where \(\dot{m}_{\text{CO}_{2}1}\) and \(\dot{m}_{\text{CO}_{2}2}\) are the mass flow of CO\({}_{2}\) into ST1 and ST2 branches respectively. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Component** & **Parameter** & **Value** & **Unit** \\ \hline Air compressor & \begin{tabular}{c} Pressure ratio \\ Inlet pressure \\ Inlet temperature \\ Mass flow of air \\ \end{tabular} & \begin{tabular}{c} 15.0 \\ 101.0 \\ 25.0 \\ 91.22 \\ \end{tabular} & \begin{tabular}{c} \(-\) \\ kPa \\ kPa \\ \end{tabular} \\ \hline Air preheater & \begin{tabular}{c} Outlet exhaust pressure \\ Outlet exhaust temperature \\ \end{tabular} & \begin{tabular}{c} 109.6 \\ 527.6 \\ \end{tabular} & \begin{tabular}{c} kPa \\ \({}^{\circ}\)C \\ \end{tabular} \\ \hline Heat exchanger & \begin{tabular}{c} Terminal temperature difference \\ Terminal temperature difference \\ \end{tabular} & \begin{tabular}{c} 10 \\ 10 \\ 10 \\ 10 \\ 10 \\ 10 \\ 10 \\ \end{tabular} & \begin{tabular}{c} \({}^{\circ}\)C \\ \({}^{\circ}\)C \\ \end{tabular} \\ \hline S-CO\({}_{2}\) compressor & \
\begin{tabular}{c} Inlet pressure \\ Outlet pressure \\ \end{tabular} &
\begin{tabular}{c} 8000 \\ 20,000 \\ 20,000 \\ \end{tabular} & kPa \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Different equipment characteristic parameters of waste heat recovery system. The net output work of the coupled system expresses as follows:  
\[W_{net}=W_{GT}+W_{ST1}+W_{ST2}-W_{AC}-W_{SC} \tag{2}\]  
where \(W_{GT}\) is the output power of the gas turbine, \(W_{ST1}\) and \(W_{ST2}\) are the output power of the S-CO\({}_{2}\) turbines 1 and 2, respectively, and \(W_{AC}\) and \(W_{SC}\) are the consumption power of the air compressor and the S-CO\({}_{2}\) compressor, respectively. The heat balance equation models of the components in the system are shown in Table 2, where \(h_{i}(i=1,2,3,\ldots)\) is the enthalpy value of stream \(i\), \(h_{i,s}(i=1,2,3,\ldots)\) is the ideal enthalpy value after an isentropic process, \(m_{i}(i=1,2,3,\ldots)\) is the mass flow of stream \(i\), \(Q\) is the heat exchange amount of a heat exchanger, and \(\eta\) is the isentropic efficiency of the equipment.
## 5 Analysis of Simulation Results
### Impact of Temperature on Bending Moment of Retaining Piles  
According to Figure 21, the maximum bending moment (_BM_) of the retaining pile occurred on the excavation face after the excavation of the foundation pit was completed. After the temperature rose by 15 \({}^{\circ}\)C, due to the constraints of the crown beam and the waist beam, the absolute value of bending moment at the corresponding part of the retaining pile increased relatively. The bending moment of the retaining pile body below the excavation face changed most owing to the constraints of the soil on both sides. The increment in the bending moment of piles 1, 2, and 3 on the excavation face was 2.63,  
Figure 20: Comparison between the measured and simulated values: (**a**) The horizontal displacement of pile 3; (**b**) the stress on waist beam 1.  
\(-0.74\), and \(-0.83\) KN\(\cdot\)m, respectively. It can be seen that the temperature rise increased the maximum positive bending moment of pile 1, but reduced the maximum positive bending moments of piles 2 and 3. The bending moment of pile 1 was obviously more affected by the temperature than that of piles 2 and 3. Under the temperature effect, the maximum bending moment reached 11.34 KN\(\cdot\)m. The bending moment of the retaining pile can be expressed by:  
\[M_{max}=\sigma\times W_{x}=310\times 10^{6}\times 334\times 10^{-6}\approx 104 \text{ KN}\cdot\text{m} \tag{4}\]  
where \(\sigma\) represents the allowable stress, and \(W_{x}\) is the bending cross-sectional coefficient.  
This equation confirms that the bending moment of the retaining pile is within a reasonable range.
# A Multi-Hop Clustering Mechanism for Scalable IoT Networks
## 2 Related Works
In the spectrum-based mechanisms, the sensors are partitioned into fan-shaped sectors centered at the BS and each sector is then divided into multiple cells according to the distance from BS [26; 27; 28; 29]. A cell corresponds to a cluster and a CH is selected for each cell. Due to the characteristic of a sector, the size of a cell which is farther away from the BS is larger than that of the ones nearer to the BS. As a consequence, the farther the cell is from the BS, there exist more sensors in the cell. Since the data transmission requires the higher energy consumption as the distance from the BS becomes farther, the spectrum-based mechanisms try to make cells have even longevity regardless of their distance from the BS by having the farther cells contain more sensors, i.e., more candidates of CH. Since theenergy consumption for data transmission is not a prime concern in the clustering of IoT networks that have continuous supply of power, spectrum-based clustering mechanisms are not the optimal solutions for IoT network clustering purposes.
# Encapsulated Probiotics: Potential Techniques and Coating Materials for Non-Dairy Food Applications
## 4 Biomaterials Utilized for Probiotics Encapsulation
### Caseins  
Caseins are a promising encapsulating material for probiotics owing to their structural and physicochemical properties. Caseins have excellent gelation properties and can form gels under mild conditions through different techniques, including extrusion, emulsification, spray-drying, and acid- and enzyme-induced gelation. As one of the protein components in milk, casein accounts for almost 80% of milk's total protein content. Moderate viscosities of caseins have contributed to easy dispersion of the probiotics, producing gel beads with high density and better protection for the encapsulated probiotics. The strong amphiphilic character allows caseins to encapsulate both hydrophilic and hydrophobic probiotics. Caseins can also produce gel beads of varying sizes (ranging from 1 to 1000 \(\upmu\)m). In probiotic encapsulation, sodium caseinate is most used, owing to its excellent emulsifying properties and high resistance to thermal denaturation [41, 88, 89].
## 2 Preliminaries  
### Access Structure  
**Definition 1** ([9]).: _Consider a set \(S\) containing \(n\) attributes, where each attribute is denoted by \(s_{i}\) for \(1\leq i\leq n\), a set \(\mathbb{A}\in 2^{\{s_{1},\ldots,s_{n}\}}\setminus\{\emptyset\}\) is an access structure on \(S\), for \(\forall B,C\in\mathbb{A}\) : if \(B\in\mathbb{A}\) and \(B\subseteq C\), then \(C\in\mathbb{A}\), and \(\mathbb{A}\) is called monotonic. If a set is in \(\mathbb{A}\), then it is called an authorized set, otherwise it is called a non-authorized set._
## 3 Results
### Comparison with Pretrained State-of-the-Art  
The selection of the VGG19 network as the baseline for integrating the feature-fusion block and the attention module was based on the recent literature [17; 29] and the experi  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Network** & **Accuracy** & **Sensitivity** & **Specificity** & **F-1 Score** \\ \hline Baseline VGG16 & 0.6770 & 0.7606 & 0.6117 & 0.6736 \\ Baseline VGG19 & 0.6955 & 0.7700 & 0.6374 & 0.6891 \\ FF-VGG19 [10] & 0.7119 & 0.7840 & 0.6557 & 0.7046 \\ Attention VGG19 & 0.7469 & 0.8498 & 0.6667 & 0.7464 \\ Attention FF-VGG19 & 0.7881 & 0.8732 & 0.7216 & 0.7832 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Performance metrics of VGG approaches with reference to ICA findings.  
Figure 3: Training and validation accuracy and loss of AFF-VGG19 when trained with the ICA findings as reference.  
ments provided in Table 3. Several baseline state-of-the-art pretrained models were trained using the ICA findings to determine the best-performing one.  
VGG16, VGG19, Xception, and EfficientNetB6 provided the top four accuracies. The minor differences in the accuracy of the four best models were not investigated for statistical significance. Instead, the most uniform network was chosen (VGG).
## 4 Conclusions  
Building upon the exceptional properties of nanomaterials, this study innovatively proposes a synergistic reinforcement strategy involving the encapsulation of Al2O3 by nano-TiO2. Through the precise design of a core-shell structure consisting of 65 wt% nano-TiO2 encapsulating 30 wt% micron-sized Al2O3, the mechanical properties of the coating, such as hardness and toughness, are further enhanced via dispersion strengthening and fine-grain strengthening mechanisms. Leveraging the high chemical stability of nano-TiO2 and the high strength of Al2O3, this approach achieves a complementary optimization of material performance.  
During the fabrication process, a low-temperature sintering technique at 400 \({}^{\circ}\)C was employed to deposit the nanoceramic coating on Q235 steel substrates using a slurry method. This process significantly diverges from traditional high-temperature approaches, dramatically reducing energy consumption and process complexity while effectively preventing microstructural degradation of the substrate caused by high temperatures. During coating formation, an interfacial metallurgical bonding process establishes a submicron-scale reinforcement network. This unique microstructure not only endows the coating with excellent wear resistance but also enhances its overall mechanical performance through synergistic interactions between the reinforcing phase and the matrix.  
In-depth analysis of the bonding mechanism reveals that the interface between the nanocomposite coating and the metal substrate is primarily formed through mechanical interlocking, resulting in a robust physical bond. This bonding method ensures high interfacial strength while imparting a certain degree of deformation compatibility, enabling the coating to maintain stable performance under complex working conditions. With broad application prospects in marine engineering, automotive manufacturing, and aerospace industries, this research provides solid theoretical and technical guidance for the process optimization and engineering application of metal-based ceramic coatings, holding significant importance for driving technological advancements in related industries.  
Conceptualization, S.M.; Data curation, J.C.; Formal analysis, G.C.; Funding acquisition, J.L.; Investigation, K.D.; Methodology, J.C. and S.M.; Project administration, J.L.; Resources, K.D.; Supervision, J.L.; Validation, G.C.; Writing--original draft, Y.L.; Writing--review and editing, Y.Z. and Y.L. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The data presented in this study are available on request from the corresponding author. The data are not publicly available due to privacy.  
Author [PERSON] was employed by the company CITIC Heavy Industries (Beijing) New Energy Material Technology Company. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
## 6 Results
### Acid Resistance Test  
A lot of cement's reaction elements have alkalinity specially C-H (which has a pH of more than 12). Thus, concrete made from Portland cement is highly susceptible to acid. There are various types of strong acid, some of them are sulfuric acid (H\({}_{2}\)SO\({}_{4}\)), acetic acid, hydrochloric acid, and nitric acid. Many of these acids are present in wastewater from industries. Because of the very low value of pH, Sulfuric acid (H\({}_{2}\)SO\({}_{4}\)) is the most damaging and hostile acid, that when reacts with C-H, makes (CaSO\({}_{4}\)) calcium sulfate which is a type of salt, which results in fast concrete degradation. In the present research, samples were placed in a 5% solution of sulfuric acid (H\({}_{2}\)SO\({}_{4}\)) and loss of mass as the degree of  
Figure 6: (**a**) Relative Analysis of Flexure Strength, (**b**) Correlation between Compressive and Flexure strength.  
degradation for each concrete sample for 28, 56, 90, and 120 days. The outcome of this test is displayed in Figure 7. The test outcome exhibits that concrete samples utilizing recycled concrete aggregate degrade very quickly as compared to samples having no recycled concrete aggregate. Recycled concrete aggregate has more quantity of C-H (exist in old mortar) and has high porosity as compared to natural concrete aggregate. Therefore, one of the potential approaches to enhance recycled aggregate concrete susceptibility against acid is by decreasing its amount in concrete. The utilization of silica fume is useful to susceptibility against acid at all ages of concrete. Silica fume addition decreases the calcium oxide quantity of binder, which prompts the low making of C-H as in comparison to samples having no silica fume. Besides, free C-H is consumed in pozzolanic reaction with silica fume aluminosilicate particles which produces chemical resistant and denser C-S-H [54]. Silica fume also enhances concrete ability against penetration of harmful elements, which causes decelerating the development of degradation of concrete samples. Enhancement in concrete susceptibility against acid has been revealed by [55] when supplementary materials with low calcium such as bentonite and RHA [32] are utilized as a cement substitute.  
Nylon fiber reinforced concrete samples exhibit that they are less susceptible to acid, i.e., NFRC improves concrete capacity against acid attack as compared to plain concrete samples. Nylon fibers produce microchannels [56] that can assist in quicker penetration of acid to the microstructure, but on the positive side, fibers can assist in sustaining binder matrix integrity. Under acid exposure, the utilization of fibers is best known to decrease the degradation of mass and strength because [26] fiber's assist in governing the expansion when gypsum and ettringite are formed. The utilization of silica fume into nylon fiber reinforced concrete samples also helps concrete with less vulnerability against acid. It can be decided that concrete utilizing recycled concrete aggregate, its resistance against acid can be improved by using nylon fibers, silica fume, or both.