esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Residual Stress
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**No.**} & \multicolumn{2}{c}{**Force Bur-**} & \multicolumn{2}{c}{**Feed Rate**} & \multirow{2}{*}{\(\sigma_{x}\)**, **MPa**} & \multirow{2}{*}{**Measurement Error, MPa**} & \multirow{2}{*}{\(\sigma_{y}\)**, **MPa**} & \multirow{2}{*}{**Measurement Error, MPa**} \\  & \multicolumn{2}{c}{**N**} & & & & & \\ \hline
1 & 40 & 500 & \(-86\) & \(\pm 4\) & \(-158\) & \(\pm 5\) \\
2 & 40 & 1000 & \(-102\) & \(\pm 4\) & \(-188\) & \(\pm 4\) \\
3 & 40 & 1500 & \(-126\) & \(\pm 6\) & \(-184\) & \(\pm 3\) \\
4 & 50 & 500 & \(-130\) & \(\pm 4\) & \(-219\) & \(\pm 3\) \\
5 & 50 & 1000 & \(-116\) & \(\pm 5\) & \(-215\) & \(\pm 6\) \\
6 & 50 & 1500 & \(-119\) & \(\pm 4\) & \(-221\) & \(\pm 5\) \\
7 & 60 & 500 & \(-113\) & \(\pm 3\) & \(-242\) & \(\pm 7\) \\
8 & 60 & 1000 & \(-101\) & \(\pm 4\) & \(-238\) & \(\pm 5\) \\
9 & 60 & 1500 & \(-89\) & \(\pm 6\) & \(-187\) & \(\pm 5\) \\ base & - & - & 2 & \(\pm 5\) & \(-6\) & \(\pm 5\) \\ \hline \hline \end{tabular}
\end{table} 
Table 4: The results of residual stresses according to PS/DC 3\({}^{2}\). Figure 3: Residual stress of the EN AW-2024-T3 butt welded joints after SDB. Table 5 presents the results of the significance analysis (ANOVA test--\(p\)-value) of the impact \(f\) and \(P\) on \(\sigma_{x}\) and \(\sigma_{y}\). The results show that \(P\) is statistically significant (\(p=0.047\)) for \(\sigma_{y}\). Based on the ANOVA analysis of variance, an adequate stress value regression model was developed at the significance level \(\alpha=0.05\) in the transverse direction \(\sigma_{x}\) (5) (Figure 5a):  
\[\sigma_{x}=487.778-0.128333f-0.0001666f^{2}-21.85P+0.0032 fP+0.1883P^{2} \tag{5}\]  
and in the longitudinal direction \(\sigma_{y}\) (6) (Figure 5b):  
\[\sigma_{y}=599.611-0.288167f-0.0000473f^{2}-25.1667P+0.00405 fP+0.18833P^{2} \tag{6}\]  
Table 6 presents the R\({}^{2}\) (coefficient of determination) value and significance analysis (\(p\)-value) for individual structural elements of regression models for \(\sigma_{x}\) and \(\sigma_{y}\). The R\({}^{2}\) value shows the high accuracy of the models. Moreover, the results indicate that not all structural elements of the model are statistically significant. However, attempts to omit them in the model resulted in a decrease in the quality of the model--a decrease in the value of R\({}^{2}\). \begin{table}
\begin{tabular}{c c c c c c c} \hline  & **R\({}^{2}\)** & **Intercept** & \(f\) & \(P\) & \(f\)P & \(P^{2}\) & \(f^{2}\) \\ \hline \(\sigma_{x}\) & 0.9254 & **0.0370 \({}^{*}\)** & **0.0088 \({}^{*}\)** & 0.2170 & **0.0087 \({}^{*}\)** & **0.0312 \({}^{*}\)** & 0.4582 \\ \(\sigma_{y}\) & 0.9381 & 0.0628 & **0.0445 \({}^{*}\)** & 0.0536 & **0.0378 \({}^{*}\)** & 0.1011 & 0.2376 \\ \hline \end{tabular} Legend: \({}^{*}\) statistically significant.  
\end{table} 
Table 6: R\({}^{2}\) value and \(p\)-value for individual structural elements of regression models. Figure 5: Plots of the regression functions of residual stresses (**a**) in the transverse direction \(\sigma_{x}\), (**b**) in the longitudinal direction \(\sigma_{y}\).
## 3 Case Study
### OSP in Seamless Condition
#### 3.3.2 Select the Number of Sensors  
Once the target number of modes is determined, the next step is to determine the number of sensors. The vibration response of measuring points near the top of the arch dam is relatively large, which is conducive to the identification of modal parameters, and sensors generally cannot be placed underwater [30]. To avoid excessive concentration of sensors and unnecessary information redundancy, 188 initial candidate measurement points are selected at equal intervals on the downstream surface of the arch dam, as shown in Figure 9. According to selected modal orders, the curve of MAC-MAX versus the number of sensors is plotted, as shown in Figure 10.  
Figure 8: Modal order shapes of seamless condition.  
Figure 7: Normalized MPF for the first 20 modal orders.  
When MAC-MAX is less than 0.25, it can be considered that modal shape vectors can be well distinguished. The preliminary principles for selecting the number of sensors in this paper are as follows: (1) MAC-MAX should be less than or equal to 0.25; (2) try to choose the stable phase of curve descent as much as possible; (3) considering the economic requirements, the number of sensors should not be too high, and this paper stipulates that the number of sensors should not be more than 40, which is consistent with the number of sensors in references [7; 31; 33]. According to Figure 10, as the number of sensors increases, the curve undergoes the most significant changes between 0 and 20 sensors. After placing 20 sensors, the MAC-MAX curve gradually stabilizes, ranging from 0.0758 to 0.1398, with a small variation. Further increasing the number of sensors contributes little to the reduction in MAC-MAX. Therefore, this section recommends selecting 20 sensors for placement.
# RDSP: Rapidly Deployable Wireless Ad Hoc System for Post-Disaster Management
## 5 Conclusions  
In this study, an RDSP was proposed that aims to reduce the average waiting times for transmitting the request messages containing rescue groups and victim's location information towards the control server. Additionally, unlike existing schemes, the RDSP does not rely on the periodic exchange of entire routing tables. However, the proposed RDSP scheme enables intermediate relays to dynamically select their IDs based on the information provided by their neighbor relays and then each intermediate relay selects the best forwarders towards the control server to minimize end-to-end delays. The results of real time experiments demonstrate that with the proposed RDSP scheme, a request message generated by the client device can reach the server device with a minimal delay in both light and heavily deployed paths compared to the existing UF system. In addition, the results confirmed that the RDSP outperforms the UF scheme under various relay densities in terms of the end-to-end delay, round-trip delay, massage delivery ratio, and network overhead.  
**Author Contributions:** conceptualization, hardware, software, writing, A.K. and A.M.; methodology, validation, Z.K. and F.U.; resources, conceptualization, funding acquisition, M.B. and L.N.; writing-original draft preparation, S.S.; resources, writing-review, and editing, L.D.N.; writing-review and editing, funding acquisition, S.M.R.I and K.-S.K. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This work was supported by National Research Foundation of Korea-Grant funded by the Korean Government (Ministry of Science and ICT) NRF 2020R1A2B5B0200247  
**Conflicts of Interest:** The authors declare no conflict of interest.
## 4 Conclusions  
High-purity crystals and freshwater were simultaneously recovered from wastewater from the anodizing industry by applying MD/MCr. The applied membrane showed stable flux under all of the thermal and hydrodynamic conditions that were investigated. In all of the cases, more than 80% of the freshwater from the wastewater was recovered, thus significantly reducing the volume of the wastewater to be disposed. The high-quality water that was produced can be used in the anodizing process to avoid the failure of the bath chemistry, which might force the disposal of expensive solution. At the same time, sodium sulfate crystals were recovered, which can find applications within the anodizing process or elsewhere, thus adding value to the process. It was observed that two polymorphs (in needle and prism shapes) of sodium sulfate were precipitated. The relative proportion and size of the recovered crystalline phases depends upon the applied operating conditions. Overall, the MD/MCr unit was able to convert approximately 90% of the wastewater into products (freshwater and salt crystals). The footprints and weight of the MCr unit that were required for the wastewater treatment significantly decrease with the temperature of the feed solution. Thus, MD/MCr is a promising innovative solution to approach zero liquid discharge in the anodizing industry, while at the same time recovering high-quality freshwater and salt crystals.  
Conceptualization, A.A. and C.A.Q.-J.; methodology, A.A. and J.H.J.; validation, J.H.J., H.C.J. and C.A.Q.-J.; Formal analysis, H.C.J. and C.A.Q.-J.; investigation, A.A. and J.H.J.; writing--original draft preparation, A.A. and J.H.J.; writing--review and editing, A.A., M.L.C. and C.A.Q.-J.; visualization, A.A. and C.A.Q.-J.; supervision, M.L.C. and C.A.Q.-J.; project administration, C.A.Q.-J.  
This research received no external funding.  
The Danish Anodizing Industry (DAI) is greatly acknowledge for providing the wastewater. The authors declare no conflict of interest.
# Transmitters and Receivers for High Capacity Indoor Optical Wireless Communication
## 3 Receiver for Optical Wireless Communication
### Quad Photodiode Array
#### 3.3.3 Results  
Figure 9a shows BER curves in relation to the received power. The BER curves at 1 Gbps overlap for both incidence angles of 0\({}^{\circ}\) and 16\({}^{\circ}\). Therefore, the photodiode array has the same response in the tested range of incidence angles. Figure 9b shows the BER relationship with the optical received power for data rates between 10 Gbps and 23 Gbps. The eye diagrams for 16 Gbps and 20 Gbps are shown in Figure 10. Error-free transmission was achieved at 16 Gbps. The transmission of 20 Gbps could still be done with hard decision FEC, and 23 Gbps with soft decision FEC.  
Figure 8: **Left**: Photograph of the quad photodiode array (in the center). **Right**: Diagram of the experimental setup used for characterization of the quad photodiode array.  
Figure 10: Eye diagrams of the received signal at \(-8\) dBm received power at 0\({}^{\circ}\) incidence angle for **left**: 16 Gbps and **right**: 20 Gbps.  
Figure 9: Experimental results of the BER measurement. Left: (**a**) 1 Gbps transmission at an incidence angle of 0\({}^{\circ}\) and 16\({}^{\circ}\). Right: (**b**) Varying bit rates at 0\({}^{\circ}\) incidence angle.
# From 5G to 6G--Challenges, Technologies, and Applications
## 3 Sixth-Generation Network's Aspects
### Network Requirements
#### 3.2.2 Technologies
Edge-native AI introduces distributed learning at edge nodes, which has been demonstrated to be capable of offering faster and more reliable decision-making than traditional centralized learning [91; 92]. However, two implied challenges, the cooperation among network elements and the time cost of training, prevent the deployment of distributed intelligence and must be well addressed. Edge-native AI promotes human-centric networks by encouraging the participation of edge nodes in data sharing, data processing, and even network management. However, by considering the potential selfishness of edge nodes, they may not be willing to perform these tasks, as they may need to consume extra resources, experience possible service quality degradation, and/or face inconvenience,by changing the living habits and behaviors of their users; this also has to be addressed through the introduction of incentives with the aid of well-designed mechanisms to encourage all edge devices' participation. Security and user privacy comprise another important aspect. The focus is on designing efficient, secure, and robust data integrity and privacy protection mechanisms and developing edge-based threat intelligence frameworks. Integrating federated learning and blockchain technologies is a promising solution. However, the tradeoff between protection effectiveness and network resource (both communication and computation) efficiency must be well discussed. All the mentioned technologies are expected to be implemented and ready for commercial use by the year 2030 [28]. This will give enough time to develop efficient proactive network management systems in parallel. A brief comparison between 5G and 6G regarding their specifications is displayed in Figure 6.
## 3 The Proposed EATS-MOBFS Method for the 2L-VRPSC
### Framework of the Solution Mechanism
#### 3.1.1 Initial Solution Construction  
In this study, an insertion-based mechanism is utilized to construct the feasible initial solution. Algorithm 3 provides the pseudocode for the initialization process. Specifically, the customers are first sorted in descending order based on the total area of their items, and \(K\) empty routes are generated (Algorithm 3 line 1). Afterward, each customer \(i\) is sequentially assigned to the route that has the smallest unoccupied loading surface that does not violate the loading constraints (i.e., can accommodate the items of customer \(i\)) (Algorithm 3 line 4-5). If a feasible route is found, the customer is inserted into the position of this route with the minimum incremental cost. Otherwise, if customer \(i\) cannot be inserted into any of the \(K\) routes, the position of customer \(i\) and a randomly selected customer will be exchanged, and the former procedure is restarted under the new customer sequence (Algorithm 3 line 7).
# Design of Micro-Phasor Measurement System to Identify Phasor of Distribution Transformers
## 4 Interface Design of the Portable Device
### The framework of the Micro-Phase Identification System  
Measurement data at the reference side are stored in the server via the mobile communication network that installed in the substation. When the on-site measurements are completed, the APP allows staff to connect to the server, thereby enables data comparison. Figure 8 illustrates the flow chart of the APP used at on-site measurement.  
Figure 7: Designed interface of application: (**a**) Transformers information; (**b**) Phasor identification results.  
On the interface of the APP, users can search for the distribution transformer to be measured or update which distribution transformer is imported from the DMMS database. However, the property of distribution transformers are excessively large in quantity, a SQLite database is added to this APP to accelerate the searching process. After a transformer is selected as a measurement target, an APP interface on the portable device is used to connect with the micro-phasor measurement system to measure the target distribution transformer. Figure 9 depicts the framework of this APP.  
The main interface of the server displays information regarding measurement time, voltage, angle, and frequency. Because of the excessively large data quantity, this server also employs a built-in database that saves the measurement results obtained from the master station. When the mobile device sends a request to the server, it will search for data from the database automatically and reply to the  
Figure 8: Flow chart of the APP used at the on-site measurement.  
Figure 9: The framework of the APP.  
mobile device for phasor comparison. This server also provides interface when inputting the time and voltage angle measured on-site that show phasor comparison result. The framework of the phase comparison is illustrated in Figure 10.
## 4 Discussion
### Unmanned Area Applications  
In field experiments that are carried out in plateau inland waters, many lakes and rivers are in unmanned areas and, therefore, cannot be measured with spectrometers such as Trios. Instead, we can use micro-spectrometers to measure the spectra of unmanned water bodies. The calibrated micro-spectrometer is carried on unmanned boats for the measurements. We designed the route according to the GPS of the unmanned boat and in accordance with the experiment time to ensure that the three probes of the micro-spectrometer met the solar zenith angle of 40\({}^{\circ}\) and the solar azimuth angle of 135\({}^{\circ}\), or met the 45\({}^{\circ}\) water measurement angle requirements. When the unmanned boat arrives at the predetermined point, the unmanned boat will stop and sway according to the water waves; thus, we arrived at the point moving slowly in order to obtain the measurement of the point walking water  
Figure 6: Micro-spectrometer measurements of clear water and turbid water R_rs_ and bias, and in situ photos of (**a**) spectrum of Qinghai Lake, (**b**) spectrum of Golmud city River.  
body spectrum. Here, the water spectra of the Qarhan Salt Lake (DBX,NHBX) and the Hoh Xil Salt Lake (KKXL) were measured, as shown in Figure 7. From the in situ photos, it can be seen that DBX3 is the most turbid, with the highest water reflectance at 590 nm at 0.055 sr\({}^{-1}\), and at 500-700 nm exceeding 0.03 sr\({}^{-1}\), resulting in a heavy greyish-brown color. DBX8 is also more turbid, with the highest water reflectance at 600 nm at 0.039 sr\({}^{-1}\), and 550-720 nm. The reflectance of DBX6 reached the highest value at 600 nm at 0.02 sr\({}^{-1}\), and had a grey-green color; the reflectance of KKXL1 and KKXL2 reached the highest value at 580 nm, and the reflectance was more stable at 400-580 nm, and thus, the color of the water body was blue.
## 2 System Model
### The Proposed Flip-Filtered OFDM
#### 2.2.2 Receiver  
The Flip-F-OFDM receiver is exemplified in Figure 5. In this receiver, we assume a white Gaussian noise with a plane channel and idealistic equalization, resulting in the received signal \(y(t)\). Subsequently, the photodetector changes the acquired signal into an electrical signal. Next, the received signal undergoes analog-to-digital conversion, and the cyclic prefix allied with each F-OFDM subframe is eliminated. To acquire the bipolar signal, \(y_{2N}(n)\), the produced signal, \(y_{4N}(n)\), is reconstructed according to the following expression:  
\[y_{2N}(n)=^{+}y_{4N}(n)-^{-}y_{4N}(2N+n) \tag{14}\]  
Figure 4: Unipolar (flipped) Filtered\(-\)OFDM signal.  
Figure 3: (**A**) Real signal, (**B**) imaginary signal, and (**C**) juxtaposed signal.  
Consequently, the noncomplex signal, \(y_{2N}(n)\), is reconstructed to the complex signal, as expressed below:  
\[\begin{cases}y_{\mathbb{R}}(n)=y_{2N}(n),&\implies\quad n=0,1,\ldots,N-1\\ y_{\mathbb{S}}(n)=y_{2N}(N+n),&\implies\quad n=0,1,\ldots,N-1\end{cases} \tag{15}\]  
where \(y_{\mathbb{R}}(n)\) and \(y_{\mathbb{S}}(n)\) represent two portions of the complex signal, \(y(n)\), correspondingly. Afterward, the generated complex signal is passed through the subband filter to the demodulator, following the standard procedure of complex F-OFDM systems. The retrieved frequency signals \(Y(\kappa)\) are then expressed as follows:  
\[Y(\kappa)=\sum_{n=0}^{N-1}y_{n}exp^{-\frac{2\pi i\kappa}{N}} \tag{16}\]  
\[Y(\kappa)=\sum_{n=0}^{N-1}[y_{\mathbb{R}}(\kappa)+jy_{\mathbb{S}}(\kappa)]exp^ {-\frac{2\pi i\kappa}{N}}=Y_{\mathbb{R}}(\kappa)+jY_{\mathbb{S}}(\kappa) \tag{17}\]  
Here, \(y_{\mathbb{R}}(\kappa)\) and \(y_{\mathbb{S}}(\kappa)\) signify the values of the two parts of the received frequency symbols.
## 1 Introduction  
The Jordan Valley, a region stretching from the Sea of Galilee to the Dead Sea, is known for its status as the lowest point on Earth, at an elevation of over 400 m below sea level. This region, also known as the Ghor, has a rich history of cultivation spanning thousands of years. However, in recent times, the area has faced challenges due to low rainfall and an increase in soil salinity. Soil salinity escalation is a significant global issue, affecting various regions in semi-arid areas such as the Jordan Valley [1]. Salinity exerts profound effects on cellular processes, leading to a range of morphological, physiological, and molecular alterations in plants [2; 3]. The primary impact of salinity on plant growth and development arises from the imposition of osmotic stress, which directly affects water availability. Thisstress induces the cellular build-up of toxic ions, such as sodium (Na+) and chloride (Cl-), disrupts nutrient balance, and causes oxidative stress injury [4,5].  
Numerous plant species have shown remarkable adaptations to thrive in these challenging habitats [6]. Plants commonly establish symbiotic relationships with endophytic bacteria, which facilitate their growth under stress conditions through various mechanisms. These bacteria enhance nutrient absorption by stimulating the uptake of nutrients, producing siderophores to capture iron, solubilizing phosphorus, and engaging in nitrogen fixation [7,8]. Additionally, they have the ability to generate specific bioactive secondary metabolites like phytohormones [9]. Furthermore, endophytic bacteria play a crucial role in maintaining plant health by combating pathogens such as fungi and bacteria [10].  
_Pseudomonas_ bacteria are classified within the phylum Pseudomonas and belong to the family Pseudomonas. This genus includes several motile, Gram-negative, rod-shaped species. Some of them are considered pathogenic, such as _P. aeruginosa_[11], an opportunistic human pathogen, and _P. syringae_, a plant pathogen [12], while other species have been identified as plant growth-promoting endophytes such as _P. fluorescens_[13], _P. migulae_[14], and _P. graminis_[15]. In a previous study, several bacterial endophytes colonizing durum wheat (_Tritcium turgidum_ ssp. _durum_) roots were isolated from saline fields in the Ghor region [16,17]. Here, we report the isolation and characterization of a new halotolerant endophyte, _P. jordanii_ strain G34, associated with the roots of durum wheat plants in the saline environment of the Ghor Sweimeh region. _Pseudomonas jordanii_ strain G34 significantly promotes durum wheat growth under severe salinity stress conditions. The draft genome of _P. jordanii_ strain G34 has been sequenced, and detailed descriptions of its genome sequence and plant growth-promoting effects are provided. In conclusion, _P. jordanii_ strain G34 is a new bacterial species with potential as a biofertilizer to enhance durum wheat growth in saline soils.
# Multiobjective Optimization Design for a MR Damper Based on EBFNN and MOPSO
## 2 Magnetorheological Damper  
### Configuration of MR Damper  
The MR damper discussed in this paper is based on a novel MR damper with a bended magnetic circuit and folded flow gap, which was briefly introduced in the previous study [31]. Figure 1 shows the configuration of the double-ended MR damper, which consists of the piston assembly, piston rod, cylinder, end covers, end shield, and other accessories. The exciting coil is wound inside the piston assembly, and the folded annular flow gap is formed by the magnetic rings, magnetic sleeves, and nonmagnetic sleeve around the coil. In addition, the bended magnetic circuit is produced by tactfully placing the nonmagnetic sleeve, thus leading to the magnetic flux passing through the outer flow gap multiple times. Therefore, when the coil is electrified, a magnetic field acting on the MR fluid is generated in more areas of the flow gap to obtain a higher controllable damping force. The damping force can be controlled by adjusting the current of the exciting coil. The piston assembly diagram of the MR damper is shown in Figure 2. In addition, Table 1 lists the main structural dimensions of the proposed MR damper.  
Figure 1: Schematic diagram of MR damper with bended magnetic circuit and folded flow gap. 1: Piston rod; 2: end cover; 3: cylinder; 4: piston cover; 5: small magnetic ring; 6: big magnetic ring; 7: magnetic sleeve; 8: nonmagnetic ring; 9: exciting coil; 10: magnetic semicircle; 11: nonmagnetic disk; 12: magnetic core; 13: end shield.