esa-sceva/satcom-chunk-collection huggingface dataset:
# The Application of Mesenchymal Stem Cells on Wound Repair and Regeneration
## 10 In Vitro Models  
The convenient use of different models (in vitro/in vivo) is relevant for wound-healing studies, better understanding of the mechanism present in the cascade and to discover improved ways of enhancing healing, thereby preventing abnormal scars [33,68]. For instance, in vitro models allow a different approach since it is possible to make a direct quantitative examination, in specific cell types, of a certain effect without taking into consideration other factors. Despite the valuable information provided by the in vitro models they do not completely correlate with the in vivo reaction/effect [68].  
There are different in vitro models of tissue repair that can help us to understand cell signaling in response to cell injury or stress. For example, in optimal conditions,  
Figure 4: Bioscaffolds are 3D printed with biocompatible materials which generate 3D patterns. This process allows to incorporate the cells which have grown under specific conditions in culture. Afterwards, the scaffold goes to the bioreactor so that it can be implanted. Based on [30]. (Adapted and modified from Servier Medical Art. Servier is licensed under a Creative Commons Attribution 3.0 Unported License).  
keratinocytes derived from a skin biopsy can be expanded in vitro to generate cultured epithelial autografts in three to four weeks [22].  
The in vivo models are needed since the in vitro ones do not represent the mechanisms and interactions present in the skin itself, like cells metabolism, signaling mechanisms, and the effect of the extracellular matrix concerning structure [68].  
Regarding wound healing, most assays use two-dimensional (2D) cell cultures or cells in monolayer, due to the availability of the materials needed. However, it has become more common to perform these assays in 3D models, capturing better the complexity of the human skin and cell to cell interactions in the process of skin healing [33].  
In 2D cell culture, the wound healing assay consists in damaging the confluent monolayer (wounding) to create a cell-free space in which cells can proliferate in order to repair the damage. There are several methods, the most common being the scratch assay which is mechanical. Other methods used are thermal (excessive heat), optical (laser) or electrical wounding (pulses of high voltage) [33]. The main advantage of the scratch assay is its simple protocol in which a sharp object is used to destroy the monolayer. Afterwards, cell migration is recorded and analyzed. On the other hand, the disadvantages are the possible irregularity of the scratches and extracellular matrix coatings destruction [33]. Another mechanical method is stamping (destroying the cells by crushing them) which has the advantage of not destroying the extracellular matrix when compared to the previous one [33].  
The 3D wound-healing model is not yet standardized, but it consists in different models of skin substitutes and the data analysis is mainly histological [33].
## 3 Joint System Implementation
### Joint System Implementation  
Figure 5 presents the proposed joint waveform method based on the FBMC chirp signal, where the communication information is first modulated to different symbols along with the intercepted radar signal after grouping and coding. A digital modulator is used to map a series of bits of data to complex symbols in light of the OQAM modulation scheme. Before transmittal to the RF front-end, its average value is removed and the power is normalized so that all emitted pulses have the same power. After the wireless transmission and jamming scenario, it reaches the receiver side. At the receiving end, the received signal is first symbol-segmented, and the signal is zeroed. The symbol sequence is converted to a bit sequence by synchronization, phase compensation, and then by a digital demodulator.  
Figure 4: Symbol design of joint signal.  
Finally, after the channel decoding block that performs error correction while extracting uncoded bits are the protection remover and the parallel-to-serial (P/S) blocks. The jamming and communication signals are demodulated and separated orthogonally and can then be used for subsequent radar jamming and to assist the communication signal in achieving channel estimation, thus reconstructing different parallel branches of the original stream; finally, the collaborator's communication system recovers the original communication information.  
The target reflected radar signal superimposed with jamming is the main component of the received waveform; therefore, it has to undergo standard radar processing. When radar carries out echo signal processing, it typically uses a constant false alarm rate (CFAR) detection algorithm to set the target detection threshold and compare it with the echo power to determine whether there is a real target. Specifically, CFAR can estimate clutter signal power in space by the noise, jamming, or ground clutter in several reference units around the target echo signal, and it can filter the noise signal and detect the target signal by setting the threshold after the clutter signal power change [35; 36; 37]. In addition, extended definitions for traditional CFAR, such as multi-static primary surveillance radar (MSPSR) and passive surveillance system (PSS) technologies, have been widely used in recent years and become the basis of surveillance [38].  
Due to the presence of jamming signals in the reference units, the noise power estimated by CFAR is high, resulting in the detection threshold of CFAR being higher than the real target signal power, which achieves the coverage effect of the target. At the same time, due to the rise in the detection threshold of CFAR, the jamming signal is also lower than the detection threshold, so the opponent's radar cannot detect the jamming signal.
## 2 Related Works
The number of nodes participating in forwarding is determined by the flooding angle. DFR can prevent flooding effectively to the whole network. However, it has an impractical assumption that all nodes know their geographic location. In [18], [PERSON] et al. proposed LB-AGR, which defines an integrated forwarding factor for each candidate node based on available energy, density, location, and level-difference between neighbor nodes, and is used to determine the best next-hop among multiple qualified candidates. The adaptive mobile of courier nodes in threshold-optimized DBR protocol (AMCTD) was proposed in [19]. AMCTD uses adaptive depth threshold, which solves different depth thresholds in networks with different density nodes. The energy-consumption of the upper nodes is decreased by the courier nodes' movement. However, the movement of courier nodes makes AMCTD unsuitable for data-sensitive applications during the instability phase. So [PERSON] et al. proposed i-AMCTD in [20]. i-AMCTD precedes AMCTD by introducing both hard and soft thresholds. In addition to sending a hello packet, it sends threshold data. However, sending a threshold consumes a lot of energy. In [21], the authors proposed a routing protocol based on the transmission time. The neighbor with the least transmission time to the sender has the highest priority. Although the route leads to less delay, the link quality and energy-consumption are not considered.
## 4 Results and Discussion
### 33-Bus Test System
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Method**} & **DG** & **DG** & **Penetration** & **PF\({}_{\text{DG}}\)** & **Total Power** & **PlR (\%)** \\  & **Number** & **Location** & **Level (\%)** & **(Lagging)** & **Losses (kW)** & **PlR (\%)** \\ \hline Proposed & DG1 & 13 & 20.125 & 0.91 & 11.7 & 94.455 \\ method & DG2 & 24 & 27.088 & 0.90 & & \\  & DG3 & 30 & 33.012 & 0.71 & & \\ \hline Hybrid & DG1 & 13 & 19.980 & 0.90 & 11.7 & 94.455 \\  & DG2 & 24 & 27.144 & 0.89 & & \\  & DG3 & 30 & 32.934 & 0.71 & & \\ \hline \hline \multirow{2}{*}{PSO} & DG1 & 13 & 19.751 & 0.91 & 11.8 & 94.408 \\  & DG2 & 24 & 27.189 & 0.90 & & \\ \cline{1-1}  & DG3 & 30 & 32.751 & 0.71 & & \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Comparison between methods for adding three DGs using 33-bus test system. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Method**} & **DG Location** & **Penetration** & **PF\({}_{\text{DG}}\)** & **Total Power** & **PlR (\%)** \\  & **Level (\%)** & **(Lagging)** & **Losses (kW)** & **PlR (\%)** \\ \hline Proposed method & 6 & 70.444 & 0.8255 & 67.75 & 67.89 \\ Hybrid & 6 & 69.301 & 0.82 & 67.90 & 67.82 \\ PSO & 6 & 69.461 & 0.82 & 67.90 & 67.82 \\ IA & 6 & 71.109 & 0.82 & 67.90 & 67.82 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Comparison between methods for adding single DG using 33-bus test system. Figure 17 shows the voltage profile for 69-bus test system before and after the DG interconnection, it is observed that voltage profile improves in all cases when the DG is connected to the system, moreover the voltage profile variations satisfy the voltage constraint which is defined in the international standards.
## 3 Results and Discussion
### Feature Extraction and Selection
#### 3.2.5 Relation Steady-State Response Average Value  
Relation steady-state response average value (RSAV): The response curve of the gas sensor had a relatively stable interval; thus, the average value of this interval could be used to characterize the stable characteristic. The calculation formula was expressed as follows:  
\[RSAV=\frac{\sum\
olimits_{i=t_{0}}^{T}x_{i}}{T-t_{0}} \tag{7}\]In the formula, \(x_{i}\) is the response value of the sensor to the ith second of a sample; \(t_{0}\) is the corresponding time when the stability is to be reached; and \(T\) is the acquisition time of a sample by the sensor.
## 5 Conclusions  
Computational geometry using the convex hull algorithm was used to determine the maximum volume formed by the AE source location hits inside 18 concrete beams with varying water-cement ratios and reinforcements. The volume of the convex hull showed a good relation to the damage encountered in the four-point bending test for each type of beam. The specimens with a high water-cement ratio had higher convex hull volume formation compared to those with a lower water-cement ratio due to the ductility, where the movement of AE source location hits spreads out wider.  
The changes in the convex hull volume from 20% load to 40% load was more than five times for all beams. In addition, the changes in convex hull volume from 20% load to 60% load was more than 13 times from CHV of 20% load for all beams. Lastly, the changes in convex hull volume from 60% to failure for all beams exhibited no significant difference. This showed that the convex hull volume correlated well with the damage until 60% of the ultimate load was reached.  
Figure 16: Average CHV according to L1, L2, L3, and L4.  
Figure 17: Ratio of CHV L2/L1, L3/L1, and L4/L3.  
**Acknowledgments:** The research work was funded under the JSPS-Rompaku Scholarship. The open access publication fee was funded by the main author of the paper.  
**Author Contributions:** [PERSON], [PERSON] and [PERSON] conceived and designed the experiments; [PERSON] performed the experiments, analyzed the data, and wrote the paper.  
**Conflicts of Interest:** The authors declare no conflict of interest.  
**Acronym/Symbol**  
**Description**  
AE Acoustic Emission  
AESL Acoustic Emission Source Location  
CHV Convex Hull Volume  
Design A Two longitudinal top bars and two longitudinal bottom bars  
Design B Two longitudinal bottom bars  
Design C One longitudinal bottom bar  
DIC Digital Image Correlation  
FPZ Fracture Process Zone  
ITZ Interfacial Transition Zone  
L1 Cyclic load from 0 to 20% of ultimate load  
L2 Cyclic load from 0 to 40% of ultimate load  
L3 Cyclic load from 0 to 60% of ultimate load  
L4 Load from 60 to 100% of ultimate load  
NDT Non-Destructive Test  
RC Reinforced Concrete  
WC40 Water-Cement Ratio of 0.40  
WC40 Water-Cement Ratio of 0.60
## 4 Discussion
### Study Limitations  
One of the main limitations of the meta-analysis was the short-term follow-up. A long follow-up period of 6 or 12 months would have facilitated a more accurate assessment of the effects of HA treatment over time and to compare its efficacy with SRP alone. Furthermore, there was considerable heterogeneity (I\({}^{2}\) > 90%) across the studies, which impacted the reliability of the results. Such heterogeneity could result from differences in how periodontal cases are defined, as well as in the diverse stages and grades of periodontal disease. This review did not include formal sensitivity analyses to explore sources of heterogeneity, which is a limitation. It is recommended that future systematic reviews, with more homogeneous data and greater availability of study-level variables, include such analyses. A further limitation concerns the BOP parameter, for which a comprehensive analysis could not be performed owing to the few studies that used a HA concentration < 0.3%. Consequently, the meta-analysis included only studies with a HA concentration > 0.8% per cent and precluded the assessment of efficacy in relation to the percentage used and limiting itself to an absolute analysis of the treatment effect.  
An important limitation of our meta-analysis is the variability in the classification of periodontal disease among the included studies. Different classification criteria (e.g., mild, moderate, and severe periodontitis) were used, which may have affected the aggregated results. Despite the review and inclusion of studies published by different sources, no funnel plots or Egger tests were conducted to assess publication bias. This might represent a limitation in our meta-analysis, as a publication bias might have influenced the results. Future analyses should include these tests to explore more critically the possibility of publication bias and its influence on the overall results.
## 4 Results
### MI System Architectures
#### 4.2.1 AR for Data Presentation  
Data presentation using AR is one of the applications of AR in MI systems. When an interaction device recognizes an identifier by looking at an IoT device (Figure 4a) or another entity (Figure 4b), the MI system sends the data collected from the IoT device to the interaction device. Data that are sent by the IoT device are presented by two-dimensional (2D) or three-dimensional (3D) graphical AR content [35; 36] and are used for signaling a sound cue [37; 38]. The data displayed on an interaction device is changed when an agent manipulates either an IoT device (Figure 4a) or another entity (Figure 4b).  
As an example of the pattern that is illustrated in Figure 4a, [PERSON] et al. [35] proposed a mobile AR application that can identify a coffee maker using an AR marker that is attached to it. The IoT device acquires the status of the coffee maker and sends data to the mobile AR application. When the agent manipulates the coffee maker, the state of the coffee maker in the mobile AR application is updated.  
[PERSON] et al. [39] developed a mobile educational AR application that is an example of Figure 4b. The application requests the agent to estimate the temperature and CO\({}_{2}\) level of the location, where an IoT device is installed. When the application is started, a 3D character is placed on an AR marker or a plane that is recognized by the smartphone based on clusters of feature points in the real-world. The 3D character indicates the temperature and CO\({}_{2}\) levels by changing its clothes. The agent is asked to guess the current temperature and CO\({}_{2}\) level. The closer the guessed value is to the actual value that is sent by the IoT device, the more points are awarded.  
Figure 4: Four identified patterns of multimodal interaction system architecture from 23 reviewed studies. Each identified pattern is categorized by two bases: (1) whether an agent is able to control the IoT device through AR (**c,d**) or not (**a,b**) and (2) whether an IoT device (**a,c**) or another entity (**b,d**) is used as an identifier for AR.
## 2 Materials and Methods
### Determinations of Total Vitamin C (TAA), AA, and DHAA Content  
For the determination of L-ascorbic acid (AA), samples of the tested juices were diluted with 2% oxalic acid in a ratio of 1:10 \(v/v\) and filtered through a 0.45 \(\upmu\)m PTFE syringe filter to a chromatographic vial. For the determination of total vitamin C (TAA), samples of the tested juices were diluted in a 1:1 \(v/v\) ratio with a DL-dithiothreitol (DTT) solution and filtered through a 0.45 \(\upmu\)m PTFE syringe filter to a chromatographic vial. Total vitamin C, L-ascorbic acid (AA), and L-dehydroascorbic acid (DHAA) were determined using high-pressure liquid chromatography coupled with a UV-VIS detector (Prominence HPLC system, Shimadzu, Japan) according to a previously published method [29]. The stationary phase was an Onyx Monolithic C18 column (100 \(\times\) 4.6 mm, 5 \(\upmu\)m, Phenomenex, Torrance, CA, USA). The mobile phase was a 0.1% \(m\)-phosphoric acid. The analysis was performed in an isocratic system at a flow rate of 1 mL/min. The chromatograms were recorded at a \(\lambda\) = 254 nm. The equation obtained from the calibration curve of AA in the range of 0.5-40 mg/100 mL was y = 480867x + 193017 (r = 0.999). The DHAA content in the samples was calculated as the difference between the total vitamin C and AA contents. All results were expressed in mg/100 mL of juice.
# Upscaling Gross Primary Production from Leaf to Canopy for Potato Crop (_Solanum tuberosum_ L.)
###### Abstract  
Estimating gross primary production (GPP) is important to understand the land-atmosphere CO\({}_{2}\) exchange for major agroecosystems. Eddy covariance (EC) measurements provide accurate and reliable information about GPP, but flux measurements are often not available. Upscaling strategies gain importance as an alternative to the limitations of the use of the EC. Although the potato provides an important agroecosystem for worldwide carbon balance, there are currently no studies on potato GPP upscaling processes. This study reports two GPP scaling-up approaches from the detailed leaf-level characterization of gas exchange of potatoes. Multilayer and big leaf approaches were applied for extrapolating chamber and biometric measurements from leaf to canopy. Measurements of leaf area index and photosynthesis were performed from planting to the end of the canopy life cycle using an LP-80 ceptometer and an IRGA Li-Cor 6800, respectively. The results were compared to concurrent measurements of surface-atmosphere GPP from the EC measurements. Big-leaf models were able to simulate the general trend of GPP during the growth cycle, but they overestimated the GPP during the maximum LAI phase. Multilayer models correctly reproduced the behavior of potato GPP and closely predicted both: the daily magnitude and half-hourly variation in GPP when compared to EC measurements. Upscaling is a reliable alternative, but a good treatment of LAI and the photosynthetic light-response curves are decisive factors to achieve better GPP estimates. The results improved the knowledge of the biophysical control in the carbon fluxes of the potato crop.  
carbon flux; gross primary productivity; upscaling; eddy covariance method [PERSON], [PERSON], [PERSON], A.M., Geez-Vinasco, G.A., Marin, F.R. Upscaling Gross Primary Production from Leaf to Canopy for Potato Crop (_Solanum tuberosum_ L.)
## 3 Results and Discussions
### Antioxidant SOD, CAT, and Lipid Peroxide (MDA)  
The administration of tap water and water mixed with HMs resulted in an obvious reduction in some antioxidant levels in the liver tissue, such as catalase (CAT) and glutathione (GSH), compared with the distilled water control group (Table 9). In addition, the stimulated lipid peroxidation was assessed by a significant elevation in the lipid peroxidation by-products of malondialdehydedehyde (MDA) and NO. [PERSON] et al. (2018) stated that NO is an essential chemical compound that plays a significant role in many inflammation stages. The increase in NO production results in the onset and development of many unhealthy conditions like cancer, type one diabetes, psoriasis, sepsis, colitis, arthritis, and multiple sclerosis. Germinated wheat and barley reduced the MDA and NO levels in the liver tissues and stimulated the antioxidant activity compared with the water mixed with HMs group. Barley grass possesses antioxidant properties ([PERSON] et al., 2016). It is abundant in antioxidants (like saponarin, polyphenols, superoxide dismutase (SOD), luttonarin, chlorophyll, Se vitamins (pro-vitamin A, C, and E), and flavonoids) that overturn lipid peroxidation ([PERSON] et al., 2016). [PERSON] et al. (2017) showed that barley grass juice has an influential antioxidant activity. Barley sprouts juice hindered the increase of malondialdehydedehyde concentration and the reduction of catalase activities ([PERSON] et al., 2016). [PERSON] et al. (2018) reported an elevation in the hepatic concentrations of antioxidant enzymes owing to the barley free phenolic extract. In addition, it has been stated ([PERSON] et al., 2016) that barley sprout extraction has a protective influence on liver cells under oxidative stress through triggering Nrf2 and rising glutathione synthesis, particularly against liver injury caused by alcohol. It has also been shown that phenolic components and vitamins produced through the sprouting of wheatgrass have powerful antioxidant and anti-inflammatory activities ([PERSON] et al., 2016). It is clear that the flavonoid-rich wheatgrass diet improved the plasma antioxidant potentials and raised the GSH and CAT levels in rats subjected to toxic HMs. The activity of antioxidants in wheatgrass was noticed at different protection levels, from radical scavenging and suppressing the free radicals that induce membrane damage ([PERSON] et al., 2016). [PERSON] et al. (2017) stated that wheatgrass decreased MDA and NO levels and consequently increased the activity of the antioxidant enzymes (CAT and GSH), and improved the haematological markers in rats subjected to toxic HMs. This showed that a diet rich in phenolic contents could prevent oxidative stress by enhancing antioxidant enzyme concentrations and opposing liver damage.
## 5 Results and Discussion
### Results for the 33-Node AC MG Operating in Islanded Mode
#### 5.2.1 Statistical Analysis of the Objective Function \(FO_{1}\) (Operating Costs)
In contrast, PSO required 525.5258 s, i.e., it was the slowest among all the evaluated methods. The average processing time for all approaches was 326.4040 s, placing PGA significantly below the threshold. These results confirm PGA's strong computational efficiency, which is particularly relevant in isolated scenarios where timely decision-making is critical for MG stability and cost-effectiveness.