esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Adsorption Studies
#### 3.2.4 Effect of Sorbent Amount  
The amount of biosorbent directly influences the number of active sites available on its surface for interaction with metal ions. The adsorption of copper ions by the four selected  
Figure 7: Influence of the temperature on the amount of adsorbed Cu(II) ions onto M, LA, L, and MO.  
materials was investigated at five different biosorbent quantities, ranging from 0.1 to 0.6 g (Figure 8), using a solution with an initial concentration of 200 mg L\({}^{-1}\) at an optimal pH of 4. The results showed that in the range of 0.2 to 0.6 g, the percentage of adsorption remained nearly constant. This observation aligns with the findings of [PERSON] et al. [39], who reported that such a trend arises due to the agglomeration of sorbent particles, leading to a reduction in accessible active sites. Based on these results, an optimum biosorbent amount of 0.2 g was selected, corresponding to a biosorbent concentration of 10 mg L\({}^{-1}\).
# An Empirical Evaluation of Nuclei Segmentation from H&E Images in a Real Application Scenario
## 4 Experimental Evaluation
### Experimental Set-Up
Considering \(n_{G}\) and \(n_{S}\), the number of cells in the ground truth and the segmented images, respectively, the ODI is defined as  
\[ODI=\frac{1}{2}\left[\sum_{i=1}^{n_{G}}\gamma_{i}\text{Dice}(G_{i},S_{i})+ \sum_{j=1}^{n_{G}}\sigma_{j}\text{Dice}(G_{j},S_{j})\right], \tag{5}\]  
where  
\[\gamma_{i}=|G_{i}|/\sum_{p=1}^{n_{G}}|G_{p}|,\quad\sigma_{j}=|S_{j}|/\sum_{q= 1}^{n_{S}}|S_{q}| \tag{6}\]  
Equation (5) present two summation terms that are weighted by the relative area of the cell, the first summation term reflects how well each ground truth cell overlaps its segmented cell, and the second summation term reflects how well each segmented cell overlaps its ground truth cell. The ODI value ranges over the interval \([0,1]\), where the value of 1 means perfect segmentation. The OHD measures the boundary-based segmentation accuracy between the segmented cells and the ground truth cells. Differently from the other metrics that compute a score or a similarity value, OHD computes a distance value; the lower the OHD value, the better the segmentation accuracy, thus OHD = 0 meansperfect segmentation. The usual definition of a Hausdorff distance between ground truth object \(G\) and segmented object \(S\) is  
\[\mathrm{H}(G,S)=\max\{\sup_{x\in G}\inf_{y\in S}d(x,y),\sup_{y\in S}\inf_{x\in G}d( x,y)\} \tag{7}\]  
where \(d(x,y)\) denotes the Euclidean distance. Similarly to ODI, the OHD takes into account also the information of individual cells, and is defined as:  
\[OHD=\frac{1}{2}\left[\sum_{i=1}^{n_{G}}\gamma_{i}\mathrm{H}(G_{i},S_{i})+\sum _{j=1}^{n_{S}}\sigma_{j}\mathrm{H}(G_{j},S_{j})\right], \tag{8}\]  
Finally, to simulate a real application scenario, we performed several cross-dataset experiments using training images taken from one source dataset and testing the resulting model on images taken from a different (target) dataset. As a baseline to evaluate the performance gap between a laboratory scenario and real application scenario, for each model, we also include the same-dataset results, obtained using training and testing samples from the same dataset.
## 3 System Architecture
### Strategy of Each Player
#### 3.3.1 Private/Local Telecom Operator  
The Private/Local Telecom Operator mainly provides two services: an end-user application service and a business-to-business service. Regarding the former service, there are generally multiple application service types from a third-party perspective. The service provider purchases the application itself from a third party; advertising is done in the application, as is billing [64; 65]. Most application providers use Freemium and subscription models [66; 67]. If these models are applied to an MEC-oriented platform, the Private/Local Operator has two types of service options. First, it can collect the cost of using the application itself from the end user based on the resources running at the MEC. Second, it can license the application.  
In the latter case, the MEC environment must have platform correlation in order to run applications running in the cloud. Correlation allows MEC/Cloud Orchestrators to deploy applications according to conditions by providing support for interfaces such as representational state transfer (REST) for higher levels. For that purpose, the MEC/Cloud  
Figure 4: Network Architecture of Private/Local Telecom Operator.  
Figure 5: Relationship chart for each player.  
Orchestrator may wish for a consultant to have Cloud Owner build a correlated platform, requiring a business alliance scheme.
## 3 Experimental Setup Testing and Analysis Results
### Concrete Object Crack Detection  
Since the purpose of this study is to develop a system to detect the defects in a damaged concrete object in a timely manner and be able to use this system in real damaged structures such as buildings and bridges, our lab asked the concrete industry to produce regular and defective concrete objects. A total of one regular and two cracked objects were used for characteristic analysis (Table 1).
## 3 Results  
Thermal sensation scores (Figure 2A,B) significantly decreased from baseline level (0 min) throughout the cooling protocol in both sexes (\(p<0.001\)). These scores reached their lowest point after 40 min of cooling in males and females before significantly increasing (\(p<0.001\)) when recordings were taken 5 min post-exercise completion in both males and females. Male participants reported no difference in thermal sensation between all garment conditions. However, female participants felt significantly colder in the control garment compared to the thermal garment at 20 (1.0 \(\pm\) 0.5, \(p=0.006\)), 30 (1.0 \(\pm\) 0.5, \(p=0.001\)) and 40 min (0.5 \(\pm\) 0.5, \(p=0.009\)) during cooling and at 5 min post-testing (1.0 \(\pm\) 1.0, \(p<0.018\)) and in compression garment at 20 (1.0 \(\pm\) 0.5, \(p=0.002\)) and 40 min (0.5 \(\pm\) 0.5, \(p=0.013\)) time periods.  
When CMJ height was analysed, cooling was found to be independent of the sex of the participant but significantly associated with the type of garment worn (\(p<0.001\)). The compression garment reduced the loss of CMJ height due to cooling by 3% (95% confidence interval of the mean difference = 2.9% to 4.5%) compared to the control garment. Also, the thermal garment reduced CMJ height loss compared to the control garment by 4% (95% confidence interval of the mean difference = 1.6% to 4.8%; Table 1).  
Figure 2: Time course of assessed thermal sensation in males (**A**) and females (**B**) for different parts of the cooling protocol. \(\epsilon\) Denotes higher perceived sensation with compression garments than with control garments (\(p<0.05\)). \(\Psi\) Denotes higher perceived sensation with thermal garments than with control garments (\(p<0.05\)).  
Cooling was not associated with the maximum knee frontal plane angle during landing. Male participants displayed less knee valgus with cooling (right 0.6 \(\pm\) 4.32\({}^{\circ}\) knee varus; left 2.5 \(\pm\) 5.2\({}^{\circ}\) knee varus) while females displayed more (right 1.0 \(\pm\) 4.46\({}^{\circ}\) knee valgus; left 0.3 \(\pm\) 5.11\({}^{\circ}\) knee valgus). The change in maximum knee frontal plane angle with cooling was not significantly associated with the garment worn or the sex of the participant.
## 3 Results and Discussion
### Polyphenolic Profile  
A chromatogram of a _S. fruticosa_ extract, monitored at 350 nm, is given in Figure 8. The chromatograms corresponding to extracts obtained with either of the cyclodext tested did not display any significant difference (data not shown). In total, nine polyphenols could be reliably detected by carrying out LC/MS/MS, but for peak #1, no tentative structure could be proposed (Table 9). Peaks #2-9 were tentatively identified based on the information provided by previous studies [29; 30].  
To assess the efficiency of the CDs tested for polyphenol extraction, the two major constituents were considered, luteolin 7-O-glucuronide and rosmarinic acid, in order to minimize variations attributed to extraction. As can be seen in Table 10, extraction with m-\(\beta\)-CD afforded 7.7% higher luteolin 7-O-glucuronide yield compared with \(\beta\)-CD and 34.4% compared with HP-\(\beta\)-CD. On the other hand, \(\beta\)-CD was 10.1% more effective compared with m-\(\beta\)-CD and 13.3% compared with HP-\(\beta\)-CD in  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**CD** & \multicolumn{4}{c}{**Parameter Estimates**} \\ \hline  & \(\mathbf{k_{0}}\) (\(\times\)10\({}^{-6}\)) & **a (\(\times\)10\({}^{-5}\))** & **b** & **R\({}^{2}\)** & **_p_** \\ \hline \(\beta\)-CD & 3.409 & 0.4500 & 0.0305 & 0.97 & 0.0320 \\ HP-\(\beta\)-CD & 2.242 & 0.0068 & 0.0816 & 1.00 & 0.0022 \\ m-\(\beta\)-CD & 2.103 & 0.1727 & 0.0238 & 0.96 & 0.0351 \\ \hline \hline \end{tabular}
\end{table}
Table 8: Fitting parameter values determined by correlating second-order extraction rates (\(k\)) with \(T\).  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**No** & **R (min)** & **UV/Vis (Omax)** & **[M - H]\({}^{-}\) (m/z)** & **Other Ions (m/z)** & **Tentative Identity** \\ \hline
1 & 19.58 & 270, 340 & 593 & - & Unknown \\
2 & 22.28 & 280, 344 & 477 & 301 & 6-Hydroxy luteolin 7-O-glucoside \\
3 & 24.38 & 256, 352 & 461 & 285 & Luteolin 7-O-glucuronide \\
4 & 25.25 & 258, 348 & 593 & 285 & Luteolin 7-O-trutinoside \\
5 & 25.82 & 270, 352 & 491 & 299 & 6-Methylucolin 7-O-glucoside (nepitrin) \\
6 & 26.62 & 246, 316 & 359 & 161 & Rosmamic acid \\
7 & 27.50 & 264, 346 & 445 & 269 & Apigenin 7-O-glucuronide \\
8 & 29.55 & 270, 352 & 475 & 299 & 6-Methylucolutin derivative \\
9 & 30.12 & 274, 332 & 461 & 299, 283 & 6-Methylucolutin derivative \\ \hline \hline \end{tabular}
\end{table}
Table 9: Spectral information pertaining to polyphenols detected in _S. fruticosa_ extracts, obtained with either CD tested.  
Figure 7: Non-linear regression between second-order extraction rates (\(k\)) and \(T\).  
extracting rosmarinic acid. This outcome suggested that the structural differences in CDs may account for selectivity towards different polyphenols. In all cases, it was observed that HP-\(\beta\)-CD was the least effective of the three CDs tested, and future studies pertaining to cyclodextrin-aided extraction of polyphenols such as flavonoid glycosides and rosmarinic acid, should consider m-\(\beta\)-CD as the most efficacious extraction booster.
# Progress in Topological Mechanics
## 2 Mechanical Topological Edge Sates
### Analogue Spin Hall Insulators  
QSHE was firstly proposed in electronic systems based on spin-orbital coupling effects [4,6]. Although the bosons do not have half-integer spin as electrons, the QSHE is also demonstrated in photonics [35, 36, 37, 81] and acoustics [47, 48, 51, 82] by constructing pseudo spins. In addition, the QSHE has been verified in elastic materials theoretically and experimentally [58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68]. We note that there are three main methods used to construct mechanical structures via QSHE, which include designing coupled pendula mimicking spin-orbital coupling effects [58, 59], using the elastic plates with distinct polarizations and coupled deformation mechanisms to produce accidental fourfold degeneracy [60, 61], and a zone-folding method with honeycomb lattices [62, 63, 64, 65, 66, 67, 68].  
In 2015, [PERSON] et al. numerically demonstrated elastic-wave analogs of the QSHE with a dual-scale phononic slab [60]. Inspired by this work, [PERSON] et al. experimentally investigated the topologically protected helical edge modes via elastic plates, e.g., the sample in Ref. [60] in 2018 [61]. The patterned plate (PP) which resemblesthe twisted Kagome lattice geometrically [83] and the unit cell, are shown in Figure 2a. The perspective and cross-sectional view of the unit cells are shown in Figure 2b. By introducing circular through holes (THs) in the PP, the accidental fourfold degeneracy of two Dirac cones emerges at the K point. Furthermore, replacing THs with blind holes (BHs), the through-the-thickness symmetry is broken, which resembles spin orbital coupling and lifts the degeneracy at K point, as shown in Figure 2c The manufacturing pattern plate used for the experiment is divided into two parts by a Z-shaped interface with BHs drilled on the opposite (top or bottom) surfaces. As expected, the topologically protected Z-shaped interface supports helical edge modes.  
In 2018, [PERSON] et al. numerically [62] and experimentally [63] demonstrated the pseudospin Hall effect via a zone-folding technique, respectively [81]. The actual system, with bolts mounted on the thin plate and arranged in hexagonal lattices, is shown in Figure 2d. The advent of double Dirac cones at \(\Gamma\) and the energy band reversal are controlled by modulating the circumferential radius R of the bolts. The emergence of the low-frequency edge states at the domain wall created between two topologically distinct lattice patterns are controlled by the local resonance of bolts as shown in Figure 2e, and the experimental setup is shown in Figure 2f. In the same year, [PERSON] et al. designed an on-chip topological elastic material that can generate high-frequency waves [64]. These on-chip devices could produce steady-state transmission and might have potential applications in on-chip acoustic devices.
## 4 Optical Communications and Computing  
Nonlinear waveguides can play a key role in optical communication applications, in particular in the 2 \(\upmu\)m wavelength band, where interest in mitigating the 'capacitycrunch' is growing. In this context, [PERSON] and co-authors [8] fabricated and characterized silicon-rich nitride (SRN) ridge waveguides with different widths and rib heights. The structures showed a loss of \(\sim\)2 dB/cm, and the SRN nonlinear refractive index was shown to be \(\sim\)1.13 \(\times\) 10\({}^{-18}\) m\({}^{2}\)/W around the wavelength 1950 nm. By optimizing parameters to improve nonlinear performances for the 2 \(\upmu\)m band, a maximal nonlinear figure of merit (i.e., the ratio of nonlinearity to loss) of 0.0804 W\({}^{-1}\) or a super-broad FWM bandwidth of 518 nm were found. These results pave the way for high-performance on-chip nonlinear waveguides for use in optical communications in the 2 \(\upmu\)m wavelength band.  
Finally, the review proposed by [PERSON] and co-authors [9] underlined how the recent development of nanofabrication technologies for the generation, processing and detection of optical signals have paved the way in the field of new analog optical computing. Particular attention was given to metamaterials or metasurfaces, which offer unprecedented opportunities to arbitrarily manipulate light waves at the subwavelength scale, leading to an acceleration of the progress of wave-based spatial analog computing. Furthermore, the authors discussed challenges and future opportunities in high-efficiency signal processing by exploiting quantum behaviors.  
This research received no external funding.  
This issue would not be possible without the valuable contributions of all the authors and peer reviewers. We would like to take this opportunity to record our sincere gratefulness to the editorial team of _Applied Sciences_.  
The authors declare no conflict of interest.
## 1 Introduction
The frequency parameters and corresponding mode shapes can be obtained by solving the eigenvalue problem numerically. A convergence study and extensive comparisons with previous results were conducted to verify the accuracy and efficiency of the present method. The mode shapes of an orthotropic plate having different degrees of rotational restraints along the opposite edges were also illustrated.
## 3 Effect of Linear Damping on System Stability
### The Number of Iteration Cycles Changes  
The analysis results in Section 3.1 are obtained on the premise that the number of iteration cycles is fixed; that is, the long-term properties of the motion characteristics of system (2) are not considered. However, the long-term nature and behavior of a motor system are important components of system stability. It is meaningless to discuss the stability of the system without considering the time scale. In this section, we will analyze the number of iterative cycles, that is, the relationship between the motion time and the motion stability of system (2), in combination with the conclusion of the motion stability of system (2) above.  
When the number of iteration cycles is 300 and \(r\) takes values of 0.006, 0.007, and 0.009, respectively, the attraction domains are shown in Figure 6a-c. When the number of iteration cycles is 1000 and \(r\) is equal to 0.003 and 0.004, respectively, the attraction domains are shown in Figure 6d,e.  
Figure 5: When \(r\) is different, the attraction domains of system (2) in the space \(x\in(-0.5,\,0.5)\), \(y\in(-0.5,\,0.5)\): (**a–d**) exhibit unstable motion states; while (**e-h**) demonstrate relatively stable motion states.  
The number of iteration cycles has a direct relationship with the motion stability of system (2), as shown in Figure 6; the more iteration cycles, the closer system (2) is to a stable state; conversely, the fewer the number of iteration cycles, the worse the stability of system (2).  
According to Figure 5, as system (2) approaches a stable state, the rate of evolution in its attraction region slows down; whereas according to [PERSON] stability correlation theory, under certain parameter conditions, the smaller the Lyapunov exponents of system (2), the more stable it becomes. By referring to the \(M\)-Lyapunov exponents diagram and Poincare cross-section, we can determine the number of iteration cycles required for system (2) to reach a steady state given these parameter conditions.  
Figure 5 has already shown that when \(M\geq 500\) and \(r\geq 0.006\), system (2) is in a stable state. Now, let us take \(r=0.001\) as an example to determine the number of iteration cycles \(M\) required for system (2) to become stable, as shown in Figure 7.  
Based on the analysis in this chapter, we conclude that when fixing \(p=0.006\), a low linear damping coefficient will result in the system taking longer to reach stability, while a high linear damping coefficient allows the system to enter the steady state relatively faster.  
Figure 6: The attraction domains of system (2) in the space \(x\in(-0.5,0.5)\), \(y\in(-0.5,0.5)\): (**a–c**) when \(M=300\), the system that was stable at \(M=500\) becomes unstable; (**d,e**) when \(M=1000\), the system that was unstable at \(M=500\) becomes stable.
# Multibeam Wideband Transmit Beamforming Using 2D Sparse FIR Trapezoidal Filters  
[PERSON]  
1 Department of Electronic and Telecommunication Engineering, University of Moratuwa, Moratuwa 10400, Sri Lanka; [EMAIL_ADDRESS] (N.D.); [EMAIL_ADDRESS] (C.U.S.E.)  
[PERSON]  
1 Department of Electronic and Telecommunication Engineering, University of Moratuwa, Moratuwa 10400, Sri Lanka; [EMAIL_ADDRESS] (N.D.); [EMAIL_ADDRESS] (C.U.S.E.)  
[PERSON]  
3 School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, QLD 4072, Australia; [EMAIL_ADDRESS]  
[PERSON]  
2 Department of Electrical and Computer Engineering, Florida International University, Miami, FL 33199, USA 2  
reflectors in the environment. However, non-LOS channels are at times intentionally created by 6G systems using technologies such as large intelligent surfaces (LISs) and reconfigurable intelligent surfaces (RISs) [20; 21; 22; 23]. Non-LOS channels may consist of multiple ray-like paths that bridge an access point to mobile units. Typically, the number of such dominant non-LOS paths takes small integer values (usually fewer than five) in number for many practical situations. Therefore, non-LOS channels require energy from the transmit power amplifiers to be spatially directed to multiple directions using \(M\) beams pointed at said directions, such that the best received signal-to-noise ratio (SNR) can be realized while imposing the lowest possible harmful interference to unintended receivers. A steerable multibeam multiuser transmit beamformer with capabilities for both channel equalization, adaptive interference control via spatial nulling, and rapid beam reconfiguration at low complexity is therein a rather crucial part of 5G/6G array processing systems.
# Watermelon Rind and Flesh Volatile Profiles and Cultivar Difference
## 3 Results  
### Watermelon Rind and Flesh Total and Grouped Volatiles  
As shown in Figure 1 for the total volatiles identified in the rinds and flesh of four watermelon cultivars, the total volatile abundance (peak area) in the rinds was only 28-58% of the volatile abundance recorded in the corresponding flesh samples. Captivation had the highest volatile abundance in its rind and flesh, while Fascination had the lowest amount for both.  
Volatiles were classified into nine groups based on their chemical structure, namely, aldehydes, alcohols, ketones, terpenes/terpenoids, esters, lactones, acids, sulfides, and others (mainly, furans and aromatics), as shown in Figure 1. The major volatile groups were aldehydes and alcohols based on numbers and quantity (peak abundance) in both rind and flesh, while ketones were the third most abundant in flesh. A greater number of volatiles were identified in the flesh than rind; the flesh also had greater total volatile intensity (cumulative peak area). The remaining volatile groups (terpenes/terpenoids, esters, lactones, acids, and sulfides) were minimal for all eight samples.  
Watermelon find primarily consisted of aldehydes (31.4-65.1% of identifications) and alcohols (31.1-64.7% of identifications), summing to 94-96% of total peak areas as shown in Figure 1. The remaining 3.8-6.1% of volatiles were represented by ketones, terpenes/terpenoids, esters, lactones, acids, sulfurs, furans, and aromatics. Within four rind samples, it presented additional differences in total peak area and presence of volatiles in specific cultivars. Captivation had the greatest abundance (peak area) of volatiles, followed by Excursion, Exclamation, and Fascination. Fascination only had about half the amount compared to the other three cultivars. Interestingly, aldehydes were more abundant in the rinds of Captivation, Exclamation, and Fascination (65.1%, 59.8%, and 60.9%, respectively) compared to the rind of Excursion (31.4%), in which alcohols were most abundant (64.7%). Captivation, Exclamation, and Fascination, however, only contained 31.1%, 34.4%, and 33.0% alcohols, respectively.  
Similarly, aldehyde and alcohols were dominant in watermelon flesh, and were present in similar abundances (peak area) across all cultivars (52.2-57.1% aldehydes and 30.2-33.3% alcohols), as shown in Figure 1. The total amount of aldehydes and alcohols was 85.4-7.4%, while summed aldehydes, alcohols, and ketones accounted for 95.1-95.8% of the total volatiles. Terpenes/terpenoids, esters, lactones, acids, sulfur-containing compounds, and others represented the remaining 4.2-4.9% of the total volatiles. Each cultivar had a unique volatile profile. Captivation had the greatest total amount of volatiles, followed by Excursion, Exclamation, and Fascination.  
Figure 1: Group of volatiles (sum of peak areas, millivolts (mV)) in the rinds and fleshes of four watermelon cultivars of Captivation, Exclamation, Excursion, and Fascination using SPME-GC-MS analysis.
# Optimization Dubins Path of Multiple UAVs for Post-Earthquake Rapid-Assessment
## 2 Problem Modeling
### Heterogeneous UAVs
One of the specifics of the Dubins car model is that the minimal turning radius \(\rho\) influences the length of the shortest path between two spatial configurations. The main purpose of modeling UAV with the Dubins car model in this paper is to qualitatively analyze whether the turning radius and the heading angle have an impact on the UAV path planning. The kinematic model of a Dubins car with a constant velocity \(v\) and a control input \(u\in[-1,1]\) can be described as  
\[\dot{q}=\left[ \begin{array}{c}\dot{x}\\ \dot{y}\\ \dot{\theta}\end{array} \right]=v\left[ \begin{array}{c}\cos\theta\\ \sin\theta\\ \frac{u}{\rho}\end{array} \right] \tag{1}\]