esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Antibacterial Activity Is Also Dependent on the Length of Fermentation
#### 3.4.5 Sensory Evaluation  
From the sensory evaluation, one can see the resulting spider diagrams for chlorine and whey treatments in Figures 5a and 5b, respectively. Therefore, from the spider diagrams, one can see that all the attributes were highly scored, with all above the midpoint 5, over the 10 days of cold storage.  
To compare the two treatments, overall acceptability was chosen to represent the sensory results, and in Figure 6 it can be seen that there are two major plateaus. The first showed top scores until day 5, and the second with scores around 6 from 7 to the 10 th day of cold storage, probably related to the scores obtained for off-odors and flavor. From these results, no differences can be seen for the two treatments, with whey or with chlorine.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Days** & \multicolumn{3}{c}{**Water**} & \multicolumn{3}{c}{**Chlorine Solution**} & \multicolumn{3}{c}{**Fermented Whey Solution**} \\ \cline{2-10}
**Storage** & **L*** & **a*** & **b*** & **L*** & **a*** & **b*** & **L*** & **a*** & **b*** \\ \hline
0 & \(72.0\pm 4.4\) & \(-20.9\pm 1.4\) & \(39.0\pm 1.1\) & \(97.6\pm 2.4\) & \(-19.8\pm 1.2\) & \(37.2\pm 0.9\) & \(72.1\pm 1.7\) & \(-21.3\pm 0.9\) & \(38.3\pm 1.7\) \\
1 & \(70.2\pm 3.3\) & \(-20.8\pm 2.4\) & \(33.1\pm 1.2\) & \(72.7\pm 3.2\) & \(-20.4\pm 0.9\) & \(36.7\pm 1.0\) & \(103.3\pm 2.8\) & \(-21.3\pm 0.6\) & \(40.9\pm 2.5\) \\
3 & \(71.6\pm 3.7\) & \(-17.3\pm 1.4\) & \(33.1\pm 1.9\) & \(69.2\pm 3.4\) & \(-20.7\pm 0.9\) & \(39.3\pm 2.5\) & \(107.1\pm 3.1\) & \(-20.9\pm 0.9\) & \(37.8\pm 2.2\) \\
5 & \(101.8\pm 2.3\) & \(3.8\pm 1.3\) & \(2.4\pm 1.8\) & \(100.5\pm 1.5\) & \(-19.2\pm 0.8\) & \(34.3\pm 1.3\) & \(61.5\pm 3.3\) & \(-19.5\pm 1.3\) & \(36.3\pm 2.3\) \\
7 & \(74.5\pm 2.9\) & \(-19.1\pm 1.4\) & \(36.1\pm 1.9\) & \(95.2\pm 1.9\) & \(-108.1\pm 0.1\) & \(17.8\pm 2.3\) & \(64.9\pm 2.2\) & \(-20.2\pm 0.8\) & \(37.4\pm 2.2\) \\
9 & \(94.2\pm 3.8\) & \(-19.4\pm 1.7\) & \(39.7\pm 2.7\) & \(98.5\pm 1.8\) & \(-20.1\pm 1.5\) & \(35.2\pm 2.7\) & \(95.0\pm 2.5\) & \(-19.6\pm 1.5\) & \(37.9\pm 2.3\) \\
10 & \(97.1\pm 4.0\) & \(-19.0\pm 1.6\) & \(36.5\pm 1.7\) & \(105.6\pm 3.3\) & \(-16.2\pm 1.6\) & \(35.8\pm 1.9\) & \(93.8\pm 3.3\) & \(-19.8\pm 1.6\) & \(39.9\pm 2.6\) \\ \hline \hline \end{tabular}
\end{table}
Table 4: Lightness (L*) color parameter of the lettuce after sanitizer treatments, over 10 days in cold storage. Results represent the average of at least three replicate experiments (n = 3) \(\pm\) SD.  
Figure 5: Sensory scores of the lettuce treated with chlorine solution (**a**) and Fermented whey (**b**) over 10 days in cold storage. Results represent the average of at least three replicate experiments (n = 3) \(\pm\) SD.
# Scenario-Based Techno-Economic Analysis of Steam Methane Reforming Process for Hydrogen Production
## 3 Results and Discussion
### Sensitivity Analysis  
We perform a sensitivity analysis of Sc 6 to investigate the influence of main parameters on the H\({}_{2}\) production process, including CO\({}_{2}\) capture, by varying key economic and process parameters by \(\pm\)20% from the base conditions, as shown in Figure 4. Among the parameters, the feedstock cost is the most significant cost driver; a \(\pm\)20% variation of it leads to a \(\pm\)8.3% variation in the H\({}_{2}\) production cost. The second most important cost driver is the CO\({}_{2}\) capture cost; a \(\pm\)20% variation of it leads to a \(\pm\)6.1% change in the H\({}_{2}\) production cost. The third factor is the IRR, leading to a \(\pm\)3.9% change in the H\({}_{2}\) production cost with a \(\pm\)20% change. The next important cost drivers are the GHSV of the reformer, GHSV of the WGS reactor, and deionized water price, sequentially. Therefore, the economics of the SMR process can be further improved with the lower feedstock price, CO\({}_{2}\) capture cost, and IRR.  
Figure 5 shows a viability envelope for Sc 6, which is used to investigate the effect of TCI and IRR on the H\({}_{2}\) production cost according to the CO\({}_{2}\) selling price. The general H\({}_{2}\) production cost using SMR is between $1.70/kg-H\({}_{2}\) and $2.09/kg-H\({}_{2}\), as reported in the literature [45], and shown in Figure 5. Figure 5a shows the change in H\({}_{2}\) production cost when the TCI in the base case is multiplied by a given multiplier (0.8 or 1.2), and the curves in Figure 5b represent the change in H\({}_{2}\) production cost for a 12.5% IRR and 15.0% IRR [46].  
Figure 3: H\({}_{2}\) production cost comparison in six scenarios.  
When there is no change in TCI and IRR values, Sc 6 is economically viable if the CO2 selling price is between $60/t and $92/t and economically attractive if the CO2 selling price is larger than $92/t because the H2 production cost is lower than the general production cost range.  
When the TCI is decreased by 0.8 times and the CO2 selling price is higher than $72/t, then the H2 production cost is lower than the lowest H2 production cost of $1.70/kg-H2, and the proposed process becomes economically favorable. When the TCI increases by 1.2 times, Sc 6 becomes economically attractive if the CO2 selling for higher than $114/t.  
Even if the IRR increases by 12.5% or 15.0%, the H2 production cost remains within the general H2 production cost range if CO2 selling for lower than $105/t or $118/t, respectively. In addition, it enters the cost preference area if CO2 selling for higher than $105/t or $118/t for a 12.5% or 15.0% IRR, respectively.  
Figure 4: Sensitivity analysis of key economic parameters in Sc 6 using single-point tornado chart.  
Figure 5: Viability envelope according to changes in (**a**) total capital investment (TCI) and (**b**) internal rate of return (IRR) in Sc 6. The reference range is between $1.7/kg-H2 and $2.09/kg-H2.
## 3 Mathematical Formulation
### Array Far-Field Calculation
#### 3.3.2. Directivity and Axial Ratio  
As last, directivity and axial ratio of the 3D array are considered as the main FoMs to evaluate FoV enhancement. Directivity \(\underline{D}(\theta,\varphi)=\left\{D_{LHCP},D_{RHCP}\right\}\) is computed as [36]  
\[\underline{D}(\theta,\varphi)=\frac{4\pi}{2\eta}\cdot\frac{\left|\underline{AF} (\theta,\varphi)\right|^{2}}{P_{rad}}, \tag{13}\]  
where \(\eta\approx 377\)\(\Omega\) is the free space wave impedance and \(P_{rad}\) is the array radiated power which can be computed by using the full-wave calculation for the single element \(P_{rad}^{elem}\) multiplied for the number of active antennas \(N_{on}\) as  
\[P_{rad}=P_{rad}^{elem}\cdot N_{on}, \tag{14}\]  
which is valid only when amplitude tapering is not considered.  
From directivity, axial ratio is computed as [34]  
\[AR(\theta,\varphi)=-\frac{1+XPD}{1-XPD}, \tag{15}\]  
where \(XPD\) is the linear cross-polarization discrimination defined as  
\[XPD=\sqrt{D_{LHCP}/D_{RHCP}}. \tag{16}\]  
Moreover, due to the 3D arrangement of the array elements, not all the radiators are contributing to the overall radiation or they contribute in a limited way (e.g., the tilted element contributes less in the array radiation due to the gain roll-off of the stand-alone element). Therefore, directivity loss \(\Gamma\) is considered as further parameter and it is defined as  
\[\Gamma=\frac{\max\left\{D_{reference}\right\}_{\theta_{s}}}{\max\left\{D_{x} \right\}_{\theta_{s}}}, \tag{17}\]  
where \(D_{reference}\) is the directivity computed for the reference array and the maximum value is taken among all the steering angles \(\theta_{s}\). Instead, \(D_{x}\) is the directivity for the specific geometry under test.  
Figure 7: Rotation of the antennas for compensating the asymmetry of the non-ideal element pattern in a linear array.
## 4 Analysis of the Test Results
### Relative Displacement between the Track System Layers
#### 4.2.1 Vertical Relative Displacement between Layers
For the symmetrical position of the middle section of the test beam, the vertical relative displacement values between the track slab and the CA mortar layer near the shear slot are greater than those of the other side; that is, the relative displacement values of sections 0 L and \(\frac{1}{4}\) L are greater than those of sections L and \(\frac{3}{4}\) L.  
Under the cyclic action of the temperature in a single day, the relative displacement occurs between the track system and the beam body and between the structural layers of the track system. Due to the constraint of the shear slots on the track system, the space deformation and relative displacement of the base plate are limited. The deformation of the track system at the beam end near the shear slots is mostly realized by the track slab through the CA mortar layer, so the vertical relative displacement between the track slab and the CA mortar layer at section 0 L is far greater than that at section L.  
In summary, the above three groups of vertical relative displacement curves show that the structural layers of the track system cooperate with each other in terms of deformation, and the relative displacement value changes with the change in the ambient temperature, with a slight lag in the change trend. In the period from 17:00 to 23:00, the change rate of vertical relative displacement is low. Under the common constraints of two adjacent span beams, the longitudinal track system, shear slots and the slab itself, the deformation and relative displacement of the track system at section 0 L of the test beam are mostly realized by the CA mortar layer and track slab, and the vertical relative displacement between the base plates is essentially zero; the rail system at section L is less affected by the shear slots than other sections. The relative displacement of the track system at sections 0 L and L are smaller than those at the midspan. Figure 10: The displacement between the track slab and CA mortar layer.
# Data-Driven Network Latency Processing for Auxiliary Services in Virtual Power Plant
## 4 Data-Driven Network Latency Processing
### Statistical Data Analysis  
In order to eliminate the nonideal factors of the network latency data collected by the real system, we first cleaned the data. We removed the negative points in the data and sliced out the continuous collection interval.  
Due to the fact that the range of the collected network latency was very large, we adopted three times the median absolute deviation to screen the normal network latency data until the outlier was less than 1% of the number of statistical samples. We define median absolute deviation as  
\[\text{MAD}=c\times median(|x_{i}-median(X)|), \tag{2}\]  
where  
\[c=\frac{-1}{\sqrt{2}\times\text{erfcinv}(\frac{3}{2})}, \tag{3}\]  
\(median()\) means to take the median. \(\text{erfcinv}(\cdot)\) is the inverse error function. Therefore, the normal latency satisfied that  
\[\left|\frac{x_{i}-median(X)}{MAD}\right|<3. \tag{4}\]  
It shows the distribution of the network delay under normal conditions in Figure 5. It is easy to find that the median uplink and downlink latencies of the network are about 17 and 41 ms, respectively. The uplink and downlink latency ranges are 14-21 ms and 35-55 ms, respectively. This value refers to the intrinsic latency of the network, which is a key indicator to indicate DERs to participate in a certain auxiliary service. For simplicity, we represent the continuous network experiment data after processing as  
\[Y=\{y_{1},y_{2},\ldots,y_{N}\}. \tag{5}\]  
At the same time, due to the fluctuation of the network latency, the network delay needs to be closely monitored and accurately predicted in order to better allow the VPP to interact with the electric power system.  
Figure 4: Original network latency.
# Geometrical Parametric Study on Steel Beams Exposed to Solar Radiation
###### Abstract  
A finite element thermal analysis was conducted in this study with the aim of evaluating the influence of the geometrical parameters of steel sections on their thermal response under solar radiation. Four W12 and W24 standard steel beams were investigated under the solar irradiation conditions of a sunny summer day. The finite element analysis was carried out using COMSOL Multiphysics considering the Sun's movement from sunrise to sunset, reflected radiation from the ground, surface convection of air and long wave radiation as the main boundary thermal loads. The temperature-time variation at different locations in the sections, vertical temperature distributions, temperature gradient distributions and thermal stress distributions were investigated. The results showed that the daily maximum temperatures, temperature variation, temperature and temperature gradient distributions and thermal stresses are influenced by the geometry of the steel section. The flange width and flange thickness were found to be the controlling parameters during the noon hours, while these parameters in addition to web depth control the shading effect during the afternoon. On the other hand, web thickness affects the temperature of webs at sunrise and sunset times. Geometrical ratios like \(W_{\text{f}}/H\), \(W_{\text{f}}/t_{\text{f}}^{2}\) and \(2W_{\text{f}}/Ht_{\text{f}}\) were the most influential parameters on temperatures, temperature gradients and thermal stresses of steel beams subjected to solar radiation. The investigated section with the maximum \(W_{\text{f}}/t_{\text{f}}^{2}\) value of 0.96 (\(W12\times 58\)) recorded the highest top-surface noon temperature, while section W24 \(\times\) 84 with the lowest \(W_{\text{f}}/t_{\text{f}}^{2}\) value of 0.60 exhibited the lowest temperature.  
solar radiation; air temperature; steel beam; temperature gradient; thermal stress +
Footnote †: journal: Applied Sciences
as acid mine drainage (AMD) [2], marginal ores [3] and tailings [4; 5; 6], urban mines [7], and waste electric and electronic equipment (WEEEs) [8; 9].  
The treatment of solid wastes and ores may involve (after dismantling and/or grinding) gravimetric and magnetic separations. Roasting [10] and leaching [11] constitute the processes most frequently applied to these solid wastes via the pyro- and hydro-branches of extractive metallurgy, respectively [12]. The leaching steps may include acidic [13], alkaline [14], or bioleaching solutions [6; 15]. Simple precipitation techniques are poorly selective for the treatment of leachates [16; 17], and it is generally necessary to couple selective precipitation steps [13; 18; 19] with complementary separation processes, such as solvent extraction [20; 21; 22] or sorption processes [23; 24]. Sorption processes are usually preferred to solvent extraction for the treatment of low-concentration effluents. A wide range of materials have been reported for cerium or REE sorption, including biosorbents [25; 26; 27; 28; 29; 30], carbon-based supports [24; 31; 32], inorganic sorbents [33; 34], and chelating and ionic-exchange resins [35; 36; 37; 38; 39; 40; 41].  
The commercial resins applied to the recovery of rare earth elements may bear a wide variety of functional groups, such as sulfonic (Amberlite 200C H, or Lewatit Monolplus SP112, Lewatit MDS 200H) or sulfonate (Amberlite 200C H), picolylamine (Dowex M 4195, Dowex XUS43605) [36; 41; 42; 43], sulfonic/phosphonic (Purolite 9597) [44],iminodiacetic (Amberlite IRC748, Purolite S930, or Lewatit Monolplus TP208, Lewatit TP207), aminophosphonic (Amberlite IRC747, Purolite S940, Purolite S950) [41; 45], or diphosphonic/sulfonic/carboxylic groups (Diphonix) [46]. By comparison with these commercially available resins, numerous investigations have focused on the grafting of supports with similar functional groups, such as aminophosphonic onto activated carbon [47], an algal/PEI support decorated with sulfonic groups [48] or phosphonate moieties [49], phosphonate onto metal organic framework [50], and diethylenetriamine incorporated onto magnetic chitosan microparticles [51]. [PERSON] et al. [52] compared a series of aminated PS-DVB beads grafted with a wide series of functional groups (phosphonoacetic acid, phosphoomethylglycine, or diethylenetriaminepentaacetic acid di-anhydride) for the sorption of Nd(III), Gd(III), and Ho(III).
## 2 Results and Discussion
### In Silico Simulated Gastrointestinal (GI) Digestion of Bioactive Peptides
\(<\) 500 g/mol; POLAR, Polarity: 20 A2 \(<\) TPSA \(<\) 130 A2; INSOLU, Insolubility: 0 \(<\) Log S (ESOL) \(<\) 6; INSATU, Instauration: 0.25 \(<\) Fraction Csp3 \(<\) 1; FLEX, Flexibility: 0 \(<\) Number of rotatable bonds \(<\) 9. The colored zone is the suitable physicochemical space for oral bioavailability. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Active** & \multicolumn{3}{c}{**Physicochemical Properties**} & \multicolumn{3}{c}{**Lipophilicity**} & \multicolumn{3}{c}{**Drug Likelihoods**} & \multicolumn{1}{c}{**Pharmacokinetics**} \\ \cline{2-9}
**Fragment** & **ROTB** & **HBA** & **HBD** & **ESOL** & **TPSA (Å2)** & **C LogP** & **Bioavailability** & **Lipinski** & **GIA** \\ \hline Captopril & 4 & 3 & 1 & \(-\)1.14 & & 96.41 & 0.62 & 0.56 & Yes (0) & High \\  & 6 & 4 & 3 & 0.66 & & 78.43 & 0.04 & 0.55 & Yes (0) & High \\  & 8 & 6 & 4 & Highly soluble & & 0.83 & & \\  & 8 & 6 & 4 & Highly soluble & & 129.72 & \(-\)0.69 & 0.56 & Yes (0) & High \\  & 3 & 4 & 2 & Highly soluble & & 83.63 & \(-\)1.17 & 0.55 & Yes (0) & High \\  & 6 & 4 & 3 & 0.39 & & 92.42 & 0.05 & 0.55 & Yes (0) & High \\  & 9 & 5 & 6 & Highly soluble & & 1.94 & 140.33 & \(-\)1.59 & 0.55 & Yes (1) & Low \\ \hline \hline \end{tabular}
\end{table} 
Table 10: In silico absorption, distribution, metabolism, excretion (ADME), and physicochemical properties of bioactive peptides. The pink area in the radar represents the favorable range for oral bioavailability which is based on the optimal values for each property. For example, lipophilicity which is indicated by the partition coefficient range between n-octanol and water (log Po/w), should range from \(-\)0.7 to +5.0. The molecular weight should be within the size of 150-500 Da and optimal range of TPSA should fall into 20-130 A\({}^{2}\). In addition, solubility which is denoted using the descriptor decimal logarithm of the molar solubility in water should not be higher than 6, whereas the fraction of carbons in the sp\({}^{3}\) hybridization should not exceed 0.25. The optimum flexibility is accountable for having less than 9 rotatable bonds. However, the crucial determinants related to oral bioavailability of the molecule are flexibility and polarity [42; 46]. In our study, except PR, all other dipeptides fall into the optimal range of each parameter (Figure 1). These findings suggest that identified bioactive dipeptides, excluding PR, have excellent conditions for oral bioavailability and better absorption ability in the GI tract. Thus, SwissADME classifiers predictions demonstrate that peptides derived from sea cucumber hydrolyses may possess drug-like properties, similar to standard inhibitory drugs (captopril) and have the potential to be used in  
Figure 1: Bioavailability radar of sea cucumber-derived bioactive peptide and ACE inhibitory drug (captopril) based on physicochemical indices ideal for oral bioavailability. the pharmaceutical industry. However, further experimental validation is needed for confirmation of the predicted properties.
###### Abstract  
The measured vibrational responses of the pumping station pipeline in the irrigation site were chosen to confirm the chaotic characteristics of the pumping station pipeline vibration and to determine the vibrational excitation that makes it chaotic. First, the chaotic properties of the pipeline vibration responses were investigated using a saturation correlation dimension and the maximum Lyapunov exponent. The vibration excitation with chaotic features was obtained using an improved variational mode decomposition (IVMD) method to examine the multi-time-scale chaotic characteristics of the pipeline vibration responses. The results show that the vibrational responses of each measuring point of the pipeline under different operating conditions have clear chaotic characteristics, where the chaotic characteristics of the axial points and bifurcated pipe points are relatively strong. The vibration of the operating conditions and measurement points affected by the unit's operation and flow state change is further complicated. The intrinsic mode function (IMF) produces a low-dimensional chaotic attractor after the IVMD disrupts the vibration response. Still, the vibration excitation of the remaining components on behalf of the units does not have chaotic properties, implying that water pulsation excitation makes the pumping station pipeline vibrations chaotic. The vibration excitation caused by the unit's operation covers the chaotic characteristics of the pipeline vibration and increases its uncertainty. The outcomes of this study provide a theoretical basis for further exploration of the vibration characteristics of pumping station pipelines, and a new method of chaos analysis is proposed.  
pumping station pipeline; chaotic characteristic; IVMD; vibration response; correlation dimension; Lyapunov exponent +
Footnote †: journal: Applied Sciences
# Prediction of RF-EMF Exposure by Outdoor Drive Test Measurements
## 5 Discussion  
The results show a good prediction in the outdoor urban environment using publicly accessible information. Indeed, considering the complexity of the ANN model and performance of prediction, the hybrid model with \(N=3\) is the best model for the reconstruction of RF-EMF exposure in terms of total Eq900.  
However, the wireless traffic is time-varying [26, 27], depending on the usage of voice and data. According to [26], the ratio of maximum to mean E-field at a given location and for a long duration is mainly below two. However, the time variation during the daytime is limited. As a consequence, the influence of the traffic on the drive test measurements along routes of 65 Km is limited compared to the influence of spatial location affected by the path loss. While in this paper we focus on the spatial reconstruction, we will dedicate future works to taking into account the temporal variation of the traffic.  
Due to the limitation of devices for the current measurements, frequency selective drive test measurements with high resolution are not possible. To assess the RF-EMF exposure level in the frequency band of interest and improve the measurement design in the future, higher data acquisition resolution will be considered.  
Since in the present paper we are interested in total Eq900, the impacts from channel fading are reduced in the computation of total Eq900. Therefore, large-scale fading domi  
Figure 8: Scattering plot obtained from hybrid ANN with \(N=3\).  
Figure 7: Ground truth (**left**) and prediction (**right**) of total Eq900 E-field prediction for \(N=3\) (and model b).  
nates the total Eq900, which indicates using distances to neighboring BSs as the input of the ANN models is reasonable. Moreover, the ANN model should consider more input parameters related to the surrounding environment, such as the building density, the average building heights, etc. Extensive measurement campaigns should be carried out in order to collect more data from various environments. Consequently, the model should be updated and tested on a small part of the route. All these aspects will be considered in future works.