esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Effect of Phlorotannin Extracts on AMP-Activated Protein Kinase (AMPK) Expression  
Results showed that treatment of diabetic rats with phlorotannins extracts was activated AMPK expression in diabetic rats that treated with _S. linifolium_ extract (1.79 Rat 2) as compared to those control-diabetic (0.549), shown in Table 8. The energy-sensing enzyme AMPK signals to accelerate glucose uptake in the skeletal muscles, fatty acid oxidation in the adipose (and other) tissues, and decrease hepatic glucose synthesis when cellular energy levels are low. There is strong evidence that type 2 diabetes and metabolic syndrome affect both people and animals and that AMPK activation (either physiologically or pharmacologically) can enhance insulin sensitivity and metabolic health [76]. Obesity is one of the essential risk factors for type 2 diabetes; [PERSON] [77] found that a polyphenol extract from Ecklonia cava caused the activation of AMPK and inhibited adipogenesis. [PERSON] et al. [78] studied how Dieckol, a phlorotannin from the brown alga _Ecklonia cava_, inhibits adipogenesis and induces AMPK phosphorylation via AMP-activated protein kinase (AMPK). Both had a significant effect on lowering blood sugar levels. Swiss albino mice treated with _Spirulina platensis_, Lactobacillus, or a combination showed significant reductions in total cholesterol (TC) and triglycerides (TG) [79].  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Animal Groups** & **Total Antioxidant (mM/g Tissue)** & **MDA Level (nmol/g Tissue)** \\ \hline Control normal (CN) & 0.51 \({}^{\text{a}}\)\(\pm\) 0.165 & 5.02 \({}^{\text{c}}\)\(\pm\) 0.43 \\ CN + _S. linifolium_ & 0.59 \({}^{\text{a}}\)\(\pm\) 0.078 & 9.65 \({}^{\text{b}}\)\(\pm\) 2.54 \\ Control diabetic (CD) & 0.37 \({}^{\text{a}}\)\(\pm\) 0.076 & 13.26 \({}^{\text{a}}\)\(\pm\) 1.6 \\ CD + _S. linifolium_ & 0.76 \({}^{\text{a}}\)\(\pm\) 0.284 & 7.3 \({}^{\text{bc}}\)\(\pm\) 2.54 \\ \hline \hline \end{tabular} Different letters represent significant value.  
\end{table}
Table 7: Total antioxidant capacity and MDA levels in the differently treated rats.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**No** & **Sample** & **CT** & **IC.CT** & \(\boldsymbol{\Delta}\)**CT** & \(\boldsymbol{\Delta}\)**ACT** & \(\boldsymbol{\Delta}\)**CT** &
\begin{tabular}{c} **Relative** \\ **Expression** \\ \end{tabular} \\ \hline
1- & Control normal & 22.76 & 13.36 & 9.4 & 0 & 1 \\
2- & CN + _S. linifolium_ & 18.86 & 11.91 & 6.95 & \(-\)2.45 & 5.64 \\
3- & Control diabetic & 22.45 & 12.18 & 10.27 & 0.87 & 0.549 \\
4- & CD + _S. linifolium_ & 22.62 & 14.06 & 8.56 & \(-\)0.84 & 1.79 \\
5- & CD + _S. linifolium_ & 21.67 & 14.91 & 6.76 & \(-\)2.64 & 6.2 \\ \hline \hline \end{tabular}
\end{table}
Table 8: Real-time PCR data analysis for AMPK expression of phlorotannins extracted from _S. linifolium_ alga.
# Experimentation Environments for Data Center Routing Protocols: A Comprehensive Review
## 4 Experimentation Methodology
### Stop Criteria
#### 4.7.3 Sliding Window  
The sliding window concept here represents the idea of looping through a set of control packets with a fixed step size. Determining when a protocol has converged using sliding windows inherits some ideas from Algorithm 2.  
First, it is also protocol-dependent, as shown by the usage of the function _countRelevant_ in Algorithm 3. This function has the same considerations mentioned in Section 4.7.2 for the function _receivedControlPacket_, i.e., its behavior depends on the routing protocol being considered.  
Second, the same threshold concept is used. In this case, it is the average of the control packets (related with convergence) over all the control packets received. Consequently, we set the minimum number of convergence-related control packets required in each window sample to determine convergence by defining this threshold.  
Finally, with this approach, a node notifies the controller after its average number of control packets reaches the configured threshold.  
```
0:\(s\): window size; \(t\): threshold; whileaverage \(>t\)do \(x\leftarrow\)countRelevant(receiveControlPacket(\(s\))) \(average\gets x/s\) endwhile  notifyEnd()
```  
**Algorithm 3** Convergence with sliding window.
## 4 Performance Evaluation: Results  
This section presents simulation results, and is organized in five subsections. Section 4.1 presents results obtained when considering synthetic rewards generated using the _Hard_ configuration, while Section 4.2 presents results obtained in the _Easy_ configuration. Next, Section 4.3 presents results obtained using real data and linear conversion, while Section 4.4 analyzes the effect of the logarithmic conversion. Finally, Section 4.5 discusses and compares the results presented in the previous subsections.  
A general consideration can be done before analyzing the results: the two proposed algorithms, muUCB1 and MLI, cannot achieve any performance gain with respect to the other algorithms when \(T_{U}=T_{M}\). In this case, in fact, the _measure_ action lasts as long as the _use_ one, but obtains no gain, making it impossible for the proposed algorithms to obtain a smaller regret than the one achieved by algorithms that always select a _use_ action, and therefore get a gain for exploiting the resource, while also refining the estimation of mean value of reward for the selected arm.
# Data Augmentation Methods for Enhancing Robustness in Text Classification Tasks
## 4 Evaluation Experiments
### Experiment Results
#### 4.2.1 Performance Results  
The results of the AG-News dataset [20] in Figure 1 indicate that all data augmentation methods improve the accuracy and F1-score compared to the original model. Among these methods, _Antipode3_ produces the most significant improvement, with an increase of 1.87% in the accuracy and 1.91% in the F1-score.  
The results of the TREC dataset [21; 22] depicted in Figure 2 reveal that, compared to the original model, all data augmentation methods decrease both the accuracy and F1-score. The exception to this trend is _Antonym2_, which results in a slight increase in the accuracy (0.07%) but a decrease in the F1-score.  
As illustrated in Figure 3, the results of the SUBJ dataset [23] demonstrate that, with some exceptions, most data augmentation methods improve the accuracy and F1-score  
Figure 1: AG-News Performance Improvement Results.  
Figure 2: TREC Performance Improvement Results.  
compared to the original model. EDA [10] produces the most significant improvement of these methods, with an increase of 0.60% in both the accuracy and F1-score. _Antonym1_ also shows comparable results, with an increase of 0.40% in the accuracy and 0.39% in the F1-score.  
The results of the SMS-Spam dataset [24] depicted in Figure 4 indicate that all data augmentation methods improve the accuracy and F1-score compared to the original model. Among these methods, CheckList [7] produces the most significant improvement, with an increase of 0.53% in the accuracy and 1.22% in the F1-score. _Antipode2_ also demonstrates comparable results, with an increase of 0.47% in the accuracy and 1.05% in the F1-score.  
The most effective methods for improving the performance vary across datasets. While our proposed methods may only consistently outperform others on some datasets, the  
Figure 4: SMS-Spam Performance Improvement Results.  
Figure 3: SUBJ Performance Improvement Results.  
Antipode-based methods demonstrate a high level of versatility and efficacy, suggesting their utility in various contexts.
## 3 Energy Balance Results and Discussion
### Annual Energy Balance Results
If approximately 15% more solar panels were to be installed, either on facades, in public spaces, or nearby solar fields, the entire energy demand could be met with solar energy. The reason for the lower SHS and FCEV2G requirements in Murcia compared to Hamburg is the better match in time (daily and seasonal) between solar electricity production and building electricity consumption. In addition, Murcia also has a relatively higher solar electricity output and lower building demand compared to Hamburg. In the Mid Century scenario in Murcia, the same solar system produces 73% more electricity than in Hamburg. * _Relatively, 70% and 30% more seasonal hydrogen storage is needed in the Mid Century scenario_ for, respectively, Hamburg and Murcia. Even though absolute hydrogen and electricity production, energy consumption, and seasonal hydrogen storage decrease in the Mid Century scenario, the higher dependency on solar electricity production increases the seasonal effect. Hence, there is an increase in relative seasonal hydrogen storage compared to the annual hydrogen and electricity production in the Mid Century scenario. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Location** & \multicolumn{2}{c}{**Hamburg**} & \multicolumn{2}{c}{**Murcia**} \\ \hline
**Scenario** & **Near Future** & **Mid Century** & **Near Future** & **Mid Century** \\ \hline
**FCEV2G** & & & & \\ Fleet average FCEV2G hours at 10 kW & 880 & 440 & 670 & 330 \\ (hours/year) & & & & \\ Annual electricity production (MWh) & 20,794 & 10,388 & 12,247 & 6112 \\ Max. power (MW) & 7.60 & 3.91 & 7.72 & 2.75 \\ Date max. power (dd-mm) & 3 January & 4 January & 12 June & 3 September \\ Max. FCEV2 Gs (\#) / Max fleet percentage (\%) & 760/32.1 & 391/16.5 & 772/41.8 & 275/14.9 \\
**FCEV Driving** & & & & \\ Average driving time passenger car & 310 & 310 & 280 & 280 \\ (hours/year) & & & & \\
**Solar electrolyzer** & & & & \\ Capacity factor (\%) & 4.1 & 8.6 & 7.8 & 15.5 \\ Annual electricity consumption (MWh) & 2680 & 12,428 & 5658 & 7648 \\ Max. absorbed power (MW) & 7.43 & 16.47 & 8.26 & 19.05 \\ Date max. power (dd-mm) & 27 July & 27 July & 23 February & 23 February \\
**SHS** & & & & \\ Max. H\({}_{2}\) storage (\(\times\)1000 kg H\({}_{2}\)) & 191 & 163 & 122 & 92 \\ Max. H\({}_{2}\) storage relative to typical SHS 3733 & & 5.1 & 4.4 & 3.2 & 2.5 \\  & & & & \\ No. similar smart city areas served by one & 20 & 23 & 30 & 40 \\  & & & & \\  & & & & \\  & & & & \\  & & & & \\  & & & & \\ \end{tabular}
\end{table} 
Table 3: Key energy balance parameters for FCEVs through vehicle-to-grid (FCEV2G), solar electrolyzer, and SHS usage for Hamburg and Murcia in the Near Future and Mid Century scenarios. Figure 4: Annual energy balance for Hamburg for the Near Future scenario (left) and Mid Century scenario (right). Figure 5: Annual energy balance for Murcia for the Near Future scenario (left) and the Mid Century scenario (right).
## 4 Results and Discussion  
### Deformation Characteristics of the Expansive Soil Slope Model with No Prefabricated Crack  
The slope model of expansive soil was created with no prefabricated crack, as shown in Figure 4a. Figure 5 gives the horizontal strain contours of the slope model under different loadings, which were obtained using VIC-2d software. The horizontal strain was set to zeroby default, with five strain-monitoring points from a to e (Figure 5a). During the whole loading and irrigation infiltration process, the slope soil was in a state of elastic-plastic and small deformation. Thus, the slope model did not show excessive deformation or sliding failure and no obvious surface tensile cracks appeared. With the increase in overburden loading, the horizontal strain increased gradually. Stress gradually spread from the top to the foot of the slope. There was a trend of compressive strain at the foot of the slope, and a trend of tensile strain in the middle of the slope surface. When the vertical loading increased to 16 MPa, the foot of the slope was still under pressure, the compressive stress zone appeared below the shoulder, and the tensile stress zone appeared in the lower middle of the slope (Figure 5d). Hence, the surface sliding zone began to appear. Compared with the same vertical pressure condition of 1.6 MPa, when the top of the slope was subjected to vertical loading and irrigation at the same time, the horizontal strain of the slope was obviously larger than that of the slope without infiltration (Figure 6a). With the increase in the overburden, the amount of infiltration increased gradually, and the horizontal strain of the slope continued to increase. A compressive stress zone was formed at the back of the slope, which mainly bore the overburden pressure. The surface tensile stress zone was more obvious (Figure 6b). With the increase in overburden stress and continuous infiltration, the compressive stress at point a and b on the surface of the slope decreased significantly, while that at point c at the foot of the slope increased significantly (Figure 7). Based on the strain development law and strain statistics, the concentrated area of tension strain could be easily identified (Figures 5d and 6b). A sliding surface was gradually formed (Figure 6b). Therefore, for an expansive soil slope without prefabricated cracks, there was no fixed sliding surface under loading conditions. When the slope was subjected to excessive overburden pressure, the potential sliding surface was gradually formed (Figure 5d). More importantly, it can be seen that water infiltration had a great influence on the stability of the slope surface and made the sliding surface more shallow (Figure 6b).  
Figure 5: Strain contours of the slope model with no crack under different loadings. (**a**) No loading; (**b**) under 1.6 MPa; (**c**) under 3.2 MPa; (**d**) under 16 MPa.
# Remedial Modelling of Steel Bridges through Application of Analytical Hierarchy Process (AHP)
## 4 Remedial Treatments
### Crack Repair  
Fatigue cracks that originate from sources of stress concentration, geometric variations, or from localised corrosive deterioration are often encountered by bridge inspectors and engineers. If these cracks are not repaired in a timely manner, a severe reduction in load carrying capacity may be experienced [18].  
Crack-stop holes are extensively used for emergency repair, whilst, a more permanent solution is sought after and engaged [19]. This involves a hole of specific diameter drilled at the tip of the formed crack, thus, relieving the stress concentration. The crack-stop hole may then be sealed with epoxy resins, or protective coatings to prevent the ingress of moisture. The installation of a tensioned bolt, or cold expansion around the perimeter of the hole, may also be exercised for improved strength characteristics. It must be mentioned, that the above methods will not guarantee further crack propagation, thus continual monitoring of the structure is a necessity.  
Alternatively, epoxy based resins can be used to prevent the ingress of air and moisture in minor fatigue cracks. For more significant cracking found in compression members, field welding is generally undertaken, while, for tension members the perceived safety risk of welding often leads authorities to alternate methods, such as member replacement.  
In addition, shot peening and Ultrasonic Impact Treatment is an effective technique used to extend the fatigue life, improve reliability, and reduce subsequent maintenance costs for steel structures [19; 20]. These properties are achieved by propelling small hard particles at high velocities onto metallic surfaces, thus inducing compressive stresses on the surface [10].
## 4 Case Study and Results
### Comparative Analysis
#### 4.3.3 Mass-to-Energy Linearity  
In all scenarios, the energy consumption grows linearly with payload mass. Figure 8 illustrates this behavior for Line 2. The strong correlation validates the physical consistency of the model and supports using linear approximations for battery sizing or feasibility estimation.  
The slope of each line can be interpreted as a specific energy cost per kilogram, which is valuable for operational planning and comparative fleet analysis.
## 4 Architecture
### Decentralized IoT Solution with Prevalent Processing at the Edge
The flow includes opening camera sensors, synchronizing the scene, updating objects, and sharing real-time audio and gesture data. of the users within the physical environment. Subsequently, the headsets connect with the cloud server via _connectToServer()_, a crucial step that allows users to access the same virtual scene and collaborate in real-time. Once the connection is established, the server proceeds with the initial synchronization of the scene for both users, sending the current state of the virtual environment via _syncScene()_, ensuring that User A and User B see a consistent and up-to-date representation of the shared scene. User A interacts with a virtual object during the session by moving it within the scene. Their headset captures this action via _sendInputData(action)_, then communicates the update to the cloud server. The server processes the input received and, through _broadcastUpdates(action)_, propagates the changes to all connected users, including User B, who receives the update and sees the modified scene thanks to updateScene(). At the same time, an audio communication dimension develops between the users. User A sends audio data (such as words or sounds) that, passing through the server via _sendAudio(audioData)_ and _distributeAudio(audioData)_, reach User B, allowing them to listen to [PERSON] A in real time. When User B moves within the environment, their actions are transmitted to the server, which, in turn, updates [PERSON] on the new position of User B in the virtual scene, ensuring that the changes are visible to all participants. It is worth noting that at the same time as the user's movement tracking initialization process, a series of routines are started that involve all the sensors, including the camera, which is essential for the success of an augmented reality application. Finally, it is worth noting that a routine that is constantly called is _UpdateScene()_, which calls the camera update for each frame. The last architecture moves processing almost entirely to the network edge, dramatically reducing latency and making the system more independent of cloud disruptions. The decentralized model is also well suited for use in areas with limited connectivity.
# Scenario-Based Configuration Refinement for High-Load Cellular Networks: An Operator View
## 4 Emergency Scenario
### Summary  
According to the above analysis and the traffic loads characteristics of emergency, we summarize the refinement polices for cells in terms of time slot ratios of downlink to uplink, frequency band, and signaling packet load. In large-scale events and concerts, the time slot ratio of downlink to uplink is suggested to be configured as 2:2 because the uplink traffic load dominates the whole traffic load, which can improve the bearing capacity of uplink and user experience. Furthermore, key parameters related to user access are suggested to adjust to decrease signaling packet loads and to improve the bearing capacity in large-scale events and concerts.
# Circular Orbit Flip Trajectories Generated by E-Sail
## 1 Introduction
This particular feature of COFTs had not been discovered during previous studies of heliocentric trajectories with H-reversal points. In this sense, the utility of the results of this work can be considered more general than the simple application to a mission case involving an orbit flip maneuver. The paper is organized as a follows. Section 2 describes the mission scenario and illustrates the mathematical model used to obtain the COFT as a function of the propulsive performance of the E-sail. The core of the paper is Section 3, which highlights the characteristics of the COFTs obtained through the optimization process. In particular, Section 3 illustrates two possible shapes of the optimal trajectory. Finally, Section 4 critically analyzes the obtained results and proposes possible extensions of this work.
## 3 Design and Analysis of the Birdcage RF coil
### Magnetic Field Homogeneity  
Homogeneity of the magnetic field at the desired dominant resonance frequency (63.8 MHz for 1.5 T and 127.7 MHz for 3 T) everywhere inside the designed birdcage coils using the proposed analytical solution can be observed via 3D electromagnetic simulation. The simulation models of the birdcage RF coils were created in according with the dimensional information provided in Section 3.1 using 3D electromagnetic simulation software ANSYS HFSS [26]. The magnetic field distribution inside the coil under no load conditions (assuming air inside the coil) as determined in the transverse plans at different positions for each coil configuration is shown in Figure 10 below.  
Figure 10: Magnetic field distribution at dominant resonance frequency in transverse planes at various positions for all configurations of 1.5 T and 3 T birdcage RF coils.  
Figure 9: Reflection coefficient S11 for the different configurations of the birdcage RF coil without and with impedance matching circuit: (**a**) 1.5 T low pass, (**b**) 1.5 T high pass, (**c**) 1.5 T band pass, (**d**) 3 T low pass, (**e**) 3 T high pass, (**f**) 3 T band pass.  
It can be observed in Figure 10 above that each coil configuration causes quite homogeneous magnetic field distribution at the dominant resonance frequency while the bandpass configuration produces rather strong magnetic field than others for both 1.5 T and 3 T cases.
## 3 Materials and Methods  
### Concrete Beams  
Normal strength concrete (with CEM I 52.5 N) was prepared and mixed with the material composition given in Table 1. River sand with a particles diameter up to 4 mm was selected, whereas large (8-16 mm) coarse and rounded smaller (2-8 mm) aggregates were utilized. First, the dry raw materials were mixed for 3 min, and mixing continued for 1 more minute when water was added. Next, the mixed material was cast in layers into a wooden mold placed on a vibration table. Constant vibration for 5 min ensured a good compaction of the concrete material. The wooden mold had dimensions of 850 \(\times\) 100 \(\times\) 100 mm\({}^{3}\). The beam geometry was selected in order to compare the research outcome to previous test results [6; 8; 19] and since it ensured pure flexural cracks formation under four-point bending. After casting, the molds were covered by a plastic film to avoid excessive drying and stored in ambient conditions for 48 h. Then, the concrete was demolded and stored underwater at 20 \({}^{\circ}\)C until the age of 28 days.  
The healing system was pre-positioned into the wooden mold and its position was adjusted during concrete pouring with a 10-12 mm concrete cover (Figure 1e). Attention was given to ensure the concrete flowed below the network, filling the air gaps that might have developed underneath the network. Low vibration enhanced the concrete flow and good adhesion with the network. All inlet/outlet connection tubes were covered by duct tape to avoid the concrete entering the healing network. After curing, the concrete was taken out of the water and air pressure applied to remove water entrapped in the healing networks.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Polyurethane (PU) Healing Agent** & \multicolumn{2}{c}{**Concrete**} \\ \hline
**Polymerization Trigger** & **Moisture** & **Component** & **Weight (kg/m\({}^{3}\))** \\ \hline Curing time (20 \({}^{\circ}\)C) & 1-5 min & CEM I 52.5 N & 300 \\ Density (20 \({}^{\circ}\)C) & 1.12 g/cm\({}^{3}\) & Sand 0/4 & 670 \\ Viscosity (20 \({}^{\circ}\)C) & 4200 mPa-s & Aggregate 2/8 & 490 \\ Shelf life & 6 months & Aggregate 8/16 & 790 \\ Cost & 14 EUR/lt & Water & 150 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Healing agent properties and concrete composition.  
Figure 1: Reservoir-vascular network details: (**a**) pair of ceramic tubes mounted on 3D printed reservoirs; (**b**) 3D printed PLA tubes mounted on 3D printed reservoirs; (**c**) 3D printed PLA tubes mounted on flexible inlet/outlet tubes; (**d**) detail view of the 3D printed reservoir; (**e**) the networks embedded into the concrete mold during casting.