esa-sceva/satcom-chunk-collection huggingface dataset:
## 10 Conclusions and Future Perspective
### Material Optimization  
There are critical issues such as low hydrophilic groups or the weak strength of styrene-containing groups that do not support membranes to work at a high efficiency. The research is focusing to incorporate more hydrophilic functional groups [-SO3H, -PO3H, acrylic acid groups, etc.] by using a crosslinking agent or without using a crosslinking agent, radical polymerization, chemical grafting technique, etc., which further enhance the absorption of water helpful in PEMFC and DMFC ion conduction property. As discussed in the section  
\begin{table}
\begin{tabular}{p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt}} \hline \hline
**Types of Materials** & **Types of Fuel Cell** & \begin{tabular}{c} **Ion Conductivity** \\ **(m5 cm\({}^{-1}\))** \\ \end{tabular} & \
\begin{tabular}{c} **Current Density** \\ **(mA cm\({}^{-2}\))** \\ \end{tabular} & **Power Density** & **Ref.** \\ \hline SBS-TMA & AEMFC & 100 & - & - & [120] \\ \hline h-SBS & AEMFC & 93 & - & - & [121] \\ \hline SEBS-PS & - & 190 & 2.09 & 1000 & [122] \\ \hline
\begin{tabular}{l} SPSEBS- \\ glutaraldehyde \\ \end{tabular} & DMFC & 10 & 200 & 68/56 & [123] \\ \hline SEBS-PEB & AEMFC & 81 & 320 & 320 & [124] \\ \hline Amine-SEBS & AEMFC & 20 & & & [125] \\ \hline PTP-SEBS & AEMFC & 102.02 & & & [126] \\ \hline PBB-SEBS & AEMFC & 146.25 & - & - & [127] \\ \hline SEBS-TPIP & AEMFC & 86.76 & 460 & 221 & [128] \\ \hline PPO-SEBS & AEMFC & - & - & 405 & [129] \\ \hline PSAN/H\({}_{3}\)PO\({}_{4}\) & PEMFC & 10 & - & & [130] \\ \hline \hline \end{tabular}
\end{table}
Table 3: SEBS-based membrane for application in fuel cells.  
on \"recent advances of styrene in fuel cell\", there is an advantage of high structure stability when functional groups attach with styrene without a crosslinking agent. In AEMFCs, styrene-based membrane functionalized with quaternary ammonium groups [-NR\({}^{4+}\)] makes it suitable to conduct hydroxide [-OH] conduction instead of protons. Another method of boosting the water contents and ion conductivity of styrene-based membranes is to introduce units such as fluorine and ionic liquids which remove membrane dryness and help in creating ionic channels. Moreover, its high thermal stability make membrane able to work at a high temperature.
# Ferrite-Loaded Spidron Fractal Loop VHF Antenna for UAV Applications
## 2 Antenna Design
The geometry of the ferrite represents an area of 240 \(\times\) 240 mm\({}^{2}\) discretized into 8 \(\times\) 8 grid cells. The size of a ferrite unit cell is 30 \(\times\) 30 \(\times\) 6.7 mm\({}^{3}\). The 8 \(\times\) 8 grid cells are divided into four quadrants, each consisting of 4 \(\times\) 4 grid cells. Initially, the first quadrant is formed, followed by the second, third, and fourth, which are formed by mirroring the first quadrant in the horizontal, vertical and diagonal directions, respectively, at the center of the 8 \(\times\) 8 grid cells. As a result, a symmetrical radiation pattern is obtained due to the symmetric shape of the ferrite. The 4 \(\times\) 4 grid cells of the first quadrant are optimized by a GA of the type used to achieve antenna performance goals in earlier works [19; 20]. We used MATLAB to implement the GA, and the 4 \(\times\) 4 grid cells are encoded into a 16-bit ternary string with the chromosomes '0', '1' and '2' corresponding to the number of stacked ferrite unit cells. Ternary GA optimization is conducted with MATLAB linked to CST through a CST Visual Basic script. In consideration of the payload weight limitations of UAVs, the total number of ferrite unit cells and the maximum number of chromosomes are set to 48 and 2, respectively. The optimized ternary-encoded result by the GA is given in Figure 4a and the configuration of the optimized ferrite and unit cell is described in Figure 4b. Through ternary genetic algorithm optimization, the ferrite is mainly formed below the conductor, where the distribution of the magnetic field is concentrated. Figure 4: Ferrite configuration: (**a**) Optimized 8\(\times\)8 grid cells; (**b**) Optimized ferrite configuration and unit cell. Figure 3: Simulated realized peak gains of the Spidron fractal loop antenna with and without cuboid ferrite. Figure 5 shows the simulated realized peak gains and the efficiency rates of the Spidron fractal loop antenna with the optimized and cuboid ferrite on the 10 m \(\times\) 10 m ground plane. The configuration of the cuboid ferrite is depicted in Figure 1b. The amount of the ferrite is decreased to 37.5% relative to the cuboid ferrite after the optimization process. The low frequency gain of the antenna with the optimized ferrite is slightly lower than that of the cuboid ferrite due to the reduced amount of ferrite. However, the gain improvement is similar to that in the results of the cuboid ferrite. In the high frequency band, the total efficiency of the antenna with the optimized ferrite is higher than that of cuboid ferrite due to the reduced magnetic loss of the ferrite. Therefore, the high frequency gain of the antenna with the optimized ferrite is improved considerably relative to that of the cuboid ferrite. The gain of the loop antenna with the optimized ferrite ranges from \(-\)28.9 to 2 dBi in the operating band.
# A Study of MANET Routing Protocols in Heterogeneous Networks: A Review and Performance Comparison
## 4 Results and Discussion
### Throughput Performance
#### 4.2.4 Node Throughput for OLSR Routing Protocol  
Figure 16 shows the throughput performance of the laptop nodes for the OLSR routing protocol. The throughput stabilizes after the initial fluctuations, maintaining a steady rate around 800-1000 kbps across all the nodes. The OLSR protocol ensures consistent performance by leveraging its proactive nature, which helps sustain optimal throughput levels even in dynamic network conditions.  
Figure 14: DYMO’s throughput for mobile nodes.  
Figure 15: DYMO’s throughput for fixed nodes.  
The effect of the fixed nodes on the throughput performance of the OLSR routing protocol is shown in Figure 17. The throughput steadily increases as the simulation progresses, reflecting the proactive nature of the OLSR protocol, which maintains routing information consistently. The fixed nodes exhibit a stable upward trend in throughput, indicating efficient data transmission over time, with minimal fluctuations.  
The effect of the mobile nodes on the performance of the OLSR routing protocol is shown in Figure 18. Throughout the simulation, there is a steady increase in throughput for the mobile nodes, although there are some fluctuations because of dynamic changes in the network topology. OLSR's proactive nature helps to maintain relatively consistent throughput, despite the mobility of the nodes, reflecting its efficiency in routing updates and maintaining network stability.  
Figure 16: OLSR’s throughput for laptop nodes.  
Figure 17: OLSR’s throughput for fixed nodes.
## 1 Introduction
### Buildings at Risk of Overheating  
As shown in [6; 33; 34], users' behaviour is an important factor affecting the internal temperature in dwellings, comparable to or exceeding the influence of construction type and environmental conditions. However, because of their structure or location, some buildings may be more prone to overheating than others. Publications [19; 35] used the term \"vulnerable\" not only in the context of people but also of buildings, stressing the importance of coupling thermal mass and night ventilation and reducing solar and internal gains to keep the internal temperature at the comfort level. Factors contributing to overheating may be:  
* City centre location (urban heat island effect) [36];
* High level of insulation and airtightness of the building's fabric [4; 34; 35];
* Lightweight construction [37];
* Location of flats on the top floor under poorly insulated roofs of dark colour [32; 35; 38];
* Elevated glazing-to-wall ratio [19; 38];
* South to west orientation of the main glazing [19; 38];
* Absence of window shading [19; 38];
* Restrictions in window opening [23];
* Lack of cross-ventilation possibility and reduced levels of ventilation [19];
* Smaller floor areas, together with a bigger density of occupancy and unfavourable daytime occupancy patterns [4; 35].  
Up to date research showed that overheating is an issue arising from a very wide context, including external climate, building construction, and the behaviour of users. Moreover, except for some quantitative measures of overheating range and time, personal perception may differ depending on age, sex, or individual preferences. This is why studies within this area can still introduce some new and interesting observations despite many available publications.
###### Abstract  
The design optimization of structures can be conducted in either the time domain or the frequency domain. The frequency domain approach is advantageous compared to its time domain counterpart, especially if the degree of freedom is large, the objectives and/or constraints are formulated in the frequency domain, or the structure is subject to random loading. In this paper, an attempt is undertaken to obtain feasible optimal solutions by implementing the Nevanlinna-Pick (NP) interpolation theory across multi-objective structural optimization problems in the frequency domain. The NP equations introduce a trade-off that originates from the interpolation theory for complex variables. According to the NP theory, a complex function cannot have an independent amplitude from its derivative at a certain frequency. Consequently, the frequency response of a physical system cannot be shaped arbitrarily at discrete frequencies. Our objectives within this paper include calculating the weight, natural frequency, fatigue life, frequency domain response, and its derivative. To illustrate our claims, sample parameter and topology optimization problems were formulated and solved, both with and without the NP constraints. It was found that the inclusion of NP constraints induced a considerable improvement in the optimal solutions, while also causing the convergence to the optimal solution to become smoother.  
structural optimization; optimization in the frequency domain; multi-objective optimization; parameter optimization; topology optimization; frequency domain fatigue life
## 2 Study Area and Materials
### Materials  
The SAR data utilized in this paper were sourced from the ESA Sentinel-1A/B satellites' images, which satellites carry C-band synthetic aperture radar. The two satellites can continuously provide SAR satellite image data for the entire world with a time interval of 6-12 days, provided that external conditions are not affected. The satellite images used in this paper are from 33 paths, with 103 views taken between 20 September 2015, and 28 December 2019, please see Table S1 for the specific data of each image acquisition. The main parameters of the SAR images are listed in Table 1. The Guobu slope is generally laid out in the northwest direction (NW285\({}^{\circ}\)) with an average slope of 43\({}^{\circ}\)[32]. This situation means the radar pulse beam of the ascending image reaches the top of the slope first, resulting in echo signals from different areas being projected into the same SAR image cell and creating a superimposed mask. Therefore, the descending orbit data are the only option for InSAR monitoring of the Guobu slope. The external digital elevation model (DEM) utilizes the 30 m resolution SRTM3 data released by NASA, which provides accurate elevation information for the study area and improves the reliability of the deformation effect. The experiment uses precision orbit determination (POD) precise orbit ephemerides data provided by the European Space Agency for orbit refinement, effectively avoiding the systematic errors caused by incorrect orbit information.  
During subsequent analysis and argumentation, precipitation and reservoir water level data were employed. The precipitation data were sourced from the meteorological station with identification number 52868, located at 36.2\({}^{\circ}\) N and 101.37\({}^{\circ}\) E, while the reservoir water level data were obtained from the Laxiwa Hydroelectric Station.
## 3 Case Study
### Image Data
#### 3.2.2 MODIS MCD43A4  
The second type of the images used in this study is daily MODIS MCD43A4 (Version 6). There are several collections of daily MODIS images that could be used to match the acquisition dates of the Sentinel-2 images time-series: MOD09 GA from Terra, MYD09 GA from Aqua, and MCD43A4. MOD09 GA and MYD09 GA were daily MODIS images, and MCD43A4 was daily but was with combined images from Terra and Aqua satellites with nadir bidirectional reflectance distribution function (BRDF) adjusted reflectance. Pixels of MCD43A4 were temporally weighted from the data of 16 days period for the 9 th day of the period. As both Sentinel-2 satellites and MODIS had almost the same local overpass time, most likely if a Sentinel-2 image has cloud coverage issues, the daily  
Figure 5: Cloud-free pixel distribution.  
MODIS MOD09 GA/MYD09 GA image acquired at the same day may also have the same problem. On the other hand, MCD43A4 came from 16 days images and cloudy pixels were not used for the data production. Furthermore, the view angle effects of MCD43A4 were removed according to bi-directional reflectance distribution function and they were alike from the nadir view angle, resulting in a stable and consistent NBAR (nadir BRDF adjusted reflectance) product [29]. Considering that the main purpose of this study was to reconstruct cloud-free Sentinel-2 image time-series, MCD43A4 images were more appropriate. Thus, MCD43A4 images at the same acquisition dates of the Sentinel-2 image time-series were used for image fusion exercise in this study. All the observation images were surface reflectance and downloaded from the USGS Earth Resources Observation and Science (EROS) Center [30].
## 3 Workflow Description
### User Input Through FreeCAD and Graphical Interface
The user can then exit the FreeCAD interface and provide the additional inputs required by T-WorkFlow through a dedicated  
Figure 5: Surfaces to be selected in sequence using the FreeCAD graphical interface are highlighted in green and red. graphical interface, developed with Python's tkinter library to facilitate the interaction with the software. The following inputs are requested:  
1. select the desired flow model between: (i) laminar; (ii) \(k\)-\(\epsilon\)[22]; (iii) \(k\)-\(\omega\)[23]; (iv) \(k\)-\(\omega\) SST [24];
2. select the.stl files for the radiator's inlet, outlet, and walls, needed to set up the fluid domain and define the boundary conditions;
3. specify the measurement unit used for the generation of the.stl files;
4. specify how often, in terms of iterations of the CFD solver, the user wants to visualize the flow distribution within the radiant ducts;
5. specify the volumetric flow rate to be imposed at the radiator inlet;
6. specify the turbulence intensity (_Tu_%) to be imposed at the radiator inlet;
7. indicate whether the inlet and outlet surfaces should be extruded along their normal direction (flow extension) to regularize the flow entering the radiator;
8. specify the number of processors to be used for parallel grid generation and parallel CFD computation (partitions). Note that the number of processes used in the two tasks may be different. Some of the information obtained through the graphical interface is used to generate the dictionary files in the system folder and to create the files in the 0 folder for imposing the desired boundary conditions, as detailed in Section 3.5. Figure 6 visually summarizes the operations performed by T-WorkFlow, with particular attention to the user's input phase. The software requires minimal inputs, streamlining the process while maintaining flexibility to test the models under any desired conditions. T-WorkFlow has been developed for technical office personnel, who should have no difficulty providing the small amount of required information. During the input phase, the most common error users may encounter is the incorrect selection of the surfaces highlighted in Figure 5 via the FreeCAD interface. If this happens, when the InputExtraction.FCMacro file is executed, an error message will appear on the FreeCAD GUI. The user will then need to reselect the three required surfaces. The needed geometrical data will only be saved in the InputLocation folder once the InputExtraction.FCMacro is executed successfully.
## 3 Results
### Color, Titntable Acidity and pH
The increase in BPP content led to a significant (\(p<0.05\)) rise in total color difference (\(\Delta\)E) between the supplemented and control samples. Previously, it was found that if the value of the color difference (\(\Delta\)E) is up to 5, then it means that any observer notices two different colors [55; 56]; this situation occurred for all the formulations of corn-based extruded snacks enriched with BPP. For visualization, Figure 1 presents the appearance of corn-based extruded snacks formulated in this study. \begin{table}
\begin{tabular}{l c c c c} \hline  & **CES 0** & **CES 2** & **CES 4** & **CES 6** \\ \hline L* & 69.40 \(\pm\) 1.19 a & 60.57 \(\pm\) 1.69 b & 40.48 \(\pm\) 1.34 c & 32.02 \(\pm\) 3.65 d \\ a* & 3.71 \(\pm\) 0.22 d & 9.40 \(\pm\) 0.63 c & 10.45 \(\pm\) 0.55 b & 13.13 \(\pm\) 0.45 a \\ b* & 21.37 \(\pm\) 0.47 a & 13.75 \(\pm\) 0.74 b & 8.15 \(\pm\) 0.23 c & 6.44 \(\pm\) 0.44 d \\ C* & 21.69 \(\pm\) 0.49 a & 16.66 \(\pm\) 0.87 b & 13.25 \(\pm\) 0.54 d & 14.63 \(\pm\) 0.37 c \\ h* & 80.19 \(\pm\) 0.42 a & 55.69 \(\pm\) 1.47 b & 37.98 \(\pm\) 1.18 c & 26.16 \(\pm\) 2.02 d \\ \(\Delta\)E & - & 13.09 \(\pm\) 1.62 c & 32.52 \(\pm\) 1.60 b & 41.37 \(\pm\) 2.50 a \\ Titralable acidity (g & 0.14 \(\pm\) 0.01 d & 0.21 \(\pm\) 0.02 c & 0.25 \(\pm\) 0.02 b & 0.28 \(\pm\) 0.02 a \\ ctric acid/100 g & 5.62 \(\pm\) 0.03 a & 4.95 \(\pm\) 0.02 b & 4.50 \(\pm\) 0.08 c & 4.23 \(\pm\) 0.06 d \\ \hline \end{tabular} Different letters in the same row indicate significant differences between corn-based extruded snack formulations (\(p<0.05\)); CES 0—control corn-based extruded snacks; CES 2—corn-based extruded snacks with 2% BPP addition; CES 4—corn-based extruded snacks with 4% BPP addition; CES 6—corn-based extruded snacks with 6% BPP addition.  
\end{table} 
Table 2: Effect of BPP addition on color parameters, pH, and titralable acidity of corn-based extruded snacks. The enrichment with BPP significantly influenced (\(p<0.05\)) the pH and titratable acidity values of corn-based extruded snacks (Table 2). Titratable acidity significantly increased (\(p<0.05\)) while pH level significantly decreased (\(p<0.05\)) in supplemented corn-based extruded snacks as the level of BPP addition increased due to the high acidity of BPP (5.60 \(\pm\) 0.24 g citric acid/100 g). A similar tendency has been reported previously after the enrichment of extruded snacks with dried fruits and fruit pomaces [14; 17]. This is expected to have a positive effect on the quality and shelf life of supplemented snacks by protecting the color and flavor and by inhibiting oxidation and bacterial growth [7]. It is well known that anthocyanins are more stable in acidic conditions. [PERSON] et al. [4] reported a lower degradation rate of the anthocyanins as well as a delay of the oxidation rate in puffed corn samples supplemented with barberry (_Berberis vulgaris_) fruit powder compared with the control.
## 8 Conclusions  
The aspects of bidirectional and resonant \(DC\)-\(DC\) converters and multilevel inverters have been reviewed in this work to highlight the need to produce a combination of converters for grid-connected and energy storage applications. Each converter has been elaborated in various aspects, such as classifications, advantages, disadvantages, and their abilities to enhance energy conversion in modern energy systems. Based on this review, a soft-switching approach should be employed instead of hard switching to reduce and eliminate switching losses. \(RPC\) is a promising solution for \(EMI\) that occurs in \(PWM\) converters; it can increase efficiency and minimize the number of components. Bidirectional \(DC\)-\(DC\) converters with galvanic isolation are more suitable for hybrid energy systems. In this study, comparisons have been made between different types of bidirectional converters and between multilevel and conventional inverters; the reviewed converters have also been compared in terms of their abilities to improve energy storage and grid connection integration. Lastly, the challenges in developing an efficient and combined multilevel resonant converter that can work under high voltage integration with soft-switching and bidirectional approaches have been elaborated. This article reviewed the significant contributions in the areas of bidirectional, multilevel, and resonant power converters with the intent of providing insight on the prospects in this study area. Therefore, producing and developing integrated bidirectional resonant multilevel converters are expected to meet the requirements of several industrial applications, such as electric vehicle charging, vehicle-to-grid (\(V2G\)), and medium-voltage (\(MV\)) drives, due to their merits of reducing cost and size and their abilities to operate with high switching frequencies and less harmonic distortions.  
Conceptualization, S.A., M.S. and H.S.D.; methodology, A.B. and D.I.; writing--original draft preparation, S.A., M.S. and A.B.; investigation, D.I., M.S., M.A.N. and M.K.; resources, M.K. and A.B.; writing--review and editing, M.S., M.A.N. and S.A.; visualization, M.K. and H.S.D.; supervision, M.S. and D.I.; funding acquisition, M.K., M.S. and S.A. All authors have read and agreed to the published version of the manuscript.  
This work was supported by Universiti Sains Malaysia.  
Not applicable.  
The authors would like to express their gratitude to Universiti Sains Malaysia and the Research Creativity and Management Office (RCMO) for supporting and funding this research under short-term grant No. 304/PELECT/6315330.  
The authors declare no conflict of interest.
## 3 Results and Discussion
### Ascorbate Content  
The ascorbate (AsA) level was also measured [Figure 5B]. The AsA content was predominantly higher and statistically significant in cruciferous and celery vegetables from the organic production system than in vegetables from conventional cultivation. The AsA content depends on plant variety, ripeness, growing conditions, and harvest time. These factors could lead to significant variations in results, both between studies and within studies [95]. In our research, ascorbate content also depended on species and cultivation systems [Table 3]. Ascorbic acid is one of the least durable vitamins and is very sensitive to storage and processing processes [96]. A relationship was found between the soil's nitrogen [N] content and the AsA level. The accumulation of ascorbic acid increases whenever the nitrogen available in the ground is low [97]. [PERSON] et al. [98] point to the critical role of N-level optimisation to maximise vitamin C content and provide a better understanding of the maturity stage-dependent N regulation on vitamin C anabolism. Generally, high nitrate provision also triggers the ascorbate-glutathione cycle gene expression [99]. The organic production system's research results regarding celery and parsley confirm the above relationship [Figures 1A and 5B]. Importantly, in most of the tested vegetable species (except carrot, celery, and rocket), the AsA level was significantly higher in vegetables from the organic production system. Additionally, the highest level of ascorbate [82.39 nmoles \(\times\) g\({}^{-1}\) FW] was recorded for organically grown parsley [Figure 5B].