esa-sceva/satcom-chunk-collection huggingface dataset:
# Frequency Selective Surfaces: A Review
## 4 Types of FSSs
### FSSs Based on Applications
#### 4.3.2 Active FSSs (AFSS)
A stopband 3D FSS with a periodic array of vertical graphene micro-ribbons has been proposed by [PERSON] et al., as shown in Figure 20, in which substrates (GaAs) are kept parallel to the direction of incident EM wave, such that it can easily penetrate into the structure at non-resonating frequencies and generate a small insertion loss [159]. It is noticed the incident EM wave concentrates in the graphene micro-ribbons and decays during its propagation along the structure at the plasmonic resonant frequency. The frequency response can be adjusted, while a superior selectivity in THz resonance frequency and BW may be preserved by varying the applied electrostatic bias on graphene. As an emerging class of MSs, tunable 3D FSSs present an arbitrarily pseudo-elliptical functionality by implementing microstrip line resonators, through the excitation of an appropriate number of propagation modes and control their coupling with the air. A useful evaluation of categories of AFSS is presented in Table 9, for FBW, the presence/absence of sensitivity to polarization, and most importantly, tuning range (TR) of tunable AFSS. The tuning range shows how much the resonant frequency shifts by a change of capacitance (tuning by using  
Figure 19: (**a**) Fabricated two-dimensional (2D) array AFSS structure. (**b**) Effect on resonance frequency under different reverse bias voltages measured by parallel plate waveguide. Figure 20: 3D FSS structure with one cell of graphene micro-ribbons and cross-section of the whole structure (in xy plane). different approaches). For example, if the capacitance is varied from \(\rm C_{a}\) to \(\rm C_{b}\), then, the resonance frequency is shifted from \(\rm f_{a}\) to \(\rm f_{b}\) and TR can be evaluated by (12) [175]. \[\rm TR=2\times\left|\frac{\rm f_{b}-\rm f_{a}}{\rm f_{b}+\rm f_{a}}\right| \tag{12}\]  
From comparison in Table 9, it can be deduced that tunable AFSSs loaded with varactor diodes provide a reasonable tuning range and FBW [175; 176; 164; 172; 177]; although in some cases the FBW is not necessarily found with a satisfactory percentage. Likewise, switchable AFSS loaded with PIN diode also perform convincingly with good FBW [156; 157]. However, polarization insensitivity is an issue with some applications, which, in most cases, is not achievable due to unsymmetrical design. It is worthy to mention that active FSS have many linked issues. Higher fabrication cost and complexity in manufacturing are of serious concern. A huge biasing system is usually required that effects the performance of the system with sensitivity to polarization and reduced selectivity. If an increased number of active elements are employed, power management becomes another severe dilemma.
# Characterization of Chromatic Dispersion and
## 4 Measuring Technique and Results
Finally, we compared the values obtained in this work for the refractive indices and for the coefficients of chromatic dispersion with those reported by other authors from measurements of PMMA fiber preforms [17] (see Figure 8). For this purpose, 50 m samples of both manufacturers were analyzed in an extended range of wavelengths, up to the near infrared region, where some of the data are available. It is clear that the results obtained in this work match satisfactorily with those reported from PMMA fiber preforms. Moreover, our calculated refractive indices also coincide with the values obtained from PMMA bulk material that can be found in the literature [18; 25]. These similarities  
Figure 6: Refractive indices obtained for POFs made by Toray (**a**) and by Mitsubishi (**b**). Three different lengths of fiber have been employed for each manufacturer: 25 m (green lines), 50 m (blue lines), and 75 m (red lines). Figure 7: Normalized Raman spectrum measured for the cores (**a**) and for the claddings (**b**) of two different brands of fiber: Toray (blue lines) and Mitsubishi (red lines). With both manufacturers, the core is made of PMMA and the cladding is made of a fluorinated polymer. between our results and those reported from other measurement methods seem to corroborate the validity of our measurement technique and of our results. We would also like to emphasize that our measurement technique allows us to directly obtain the refractive indices and the coefficients of dispersion from the POF, without having to use the preform or the bulk material, which is the main novelty of our work.
## 3 System Design
### Application Server
#### 3.2.2 Data Rendering Module  
The data rendering module is responsible for data rendering and subsetting. NetCDF is not convenient for rendering on web browsers and is transformed into image files by this module. Some of the visualization-ready images, such as original simulation data and pre-calculated statistics data, are stored permanently in the data repository. The others such as the results of data analysis are stored temporarily. The data rendering module also provides subsetting functions to process client requests for visualizing data of sub regions.
## 3 Materials and Methods
### Preparation of Rac-Ofloxacin MMIPs  
Magnetic Fe\({}_{3}\)O\({}_{4}\) nanoparticles were synthesized by a coprecipitation method according to the reported procedure [30; 31] with a minor modification. Briefly, FeCl\({}_{3}\cdot\)6H\({}_{2}\)O (2.4 g) and FeCl\({}_{2}\cdot\)4H\({}_{2}\)O (0.9 g) were dissolved in deionized water (80 mL), and this solution was purged with nitrogen for 30 min to displace oxygen. The mixture was stirred and heated to 75 \({}^{\circ}\)C, and then NH\({}_{3}\cdot\)H\({}_{2}\)O was added dropwise to adjust the pH to 9-10. After 10 min, 10 mL of OA was added into the mixture, which was reacted for a further 1 h, and then allowed to cool to room temperature. Finally, the obtained OA-Fe\({}_{3}\)O\({}_{4}\) nanoparticles were washed with water and ethanol several times to remove excess NH\({}_{3}\cdot\)H\({}_{2}\)O and OA.  
The MMIPs were synthesized by suspension polymerization according to the literature procedure [32; 33; 34; 35] with a minor modification. PVA (2.0 g) was dissolved in 200 mL of deionized  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Analytes**} & **OFL Added** & \multirow{2}{*}{**Recovery (\%)**} & \multicolumn{2}{c}{**Precision (RSD\%)**} \\ \cline{3-5}  & **(\(\upmu\)g\({}^{-1}\))** & & **Intra-Day** & **Inter-Day** \\ \hline \multirow{2}{*}{\(S\)-(\(-\))-OFL} & 0.25 & 79.3 & 3.5 & 6.0 \\  & 1.25 & 83.7 & 2.9 & 3.4 \\  & 2.5 & 84.1 & 3.9 & 4.2 \\ \hline \multirow{2}{*}{\(R\)-(+)-OFL} & 0.25 & 79.2 & 3.6 & 5.6 \\  & 1.25 & 83.9 & 3.2 & 3.5 \\  & 2.5 & 84.4 & 4.0 & 4.6 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Recoveries and RSDs of OFL on MMIPs for spiked fish samples (\(n=6\)).  
water, followed by the addition of 4.3 mL of MMA, 0.5 mL of DVB, and 6.8 mL of GMA. Then, 1 g of OA-Fe\({}_{3}\)O\({}_{4}\) was added to the above system under ultrasonication (KQ-250B ultrasonic cleaner, Kunshan Ultrasonic Instrument Co., Ltd., Jiangsu, China). Finally, 1.0 g of BPO in 20 mL of ethanol was added dropwise under vigorous stirring; nitrogen was bubbled into the reaction mixture throughout the procedure. The mixture was reacted at 80 \({}^{\circ}\)C for 2 h, and the product was isolated under a magnetic field and washed with water and ethanol. Exactly 2 g of obtained particles was dispersed into 50 mL of methanol containing 1.0 mmol of _rac_-OFL, and 10 mL of EDA was added dropwise under stirring. The reaction was then maintained at 80 \({}^{\circ}\)C for 8 h. Upon completion of the reaction, the nanoparticles were isolated with an external magnetic field and washed with water and methanol. Subsequently, the obtained particles were ultrasonically cleaned with 10% (\(v/v\)) acetic acid in methanol for 30 min until template molecules were no longer observed by HPLC. Finally, the MMIPs were dried for 32 h in a freeze dryer at \(-40\)\({}^{\circ}\)C. In parallel, MNIPs were prepared using the same procedure without _rac_-OFL.
Monolithic approaches involving nanostructure engineering has been explored previously for white light emission. A dual wavelength, 5000 K to 20,000 K color tunable, multifacet QW LED was demonstrated by [PERSON] et al. in 2008 [PERSON] et al. (2008). [PERSON] et al. have reported color tunability and CRI values more than 90 for \"dot in a wire\" core shell LEDs on silicon [PERSON] et al. (2008). Nevertheless, this approach requires a complex growth and fabrication process with precise control over wire diameter and dot size, which is not ideal for mass production. In addition, luminous efficacy of these devices is still far from phosphor covered LEDs [PERSON] et al. (2008). [PERSON] et al. demonstrated dual wavelength MQW LED with 46% indium (In) content for red emission peak at 2.12 eV thus achieving emission color from red to yellow to white with CRI of 85.6 [PERSON] et al. (2008). However, large lattice mismatch between higher In incorporated InGaN red QW on GaN substrate results in issues related to charge separation and increased defect density [PERSON] et al. (2008). A simpler fabrication approach of vertically stacked QWs emitting at two distinct wavelengths has been reported. Active region of such devices can consist of either: (i) longer wavelength emitting passive QWs pumped by active blue QW [PERSON] et al. (2008); or (ii) all electrically pumped active QWs [PERSON] et al. (2008); Li et al. (2008); Li et al. (2008). The first approach is similar to phosphor covered LEDs and the spectrum is controlled by number of passive QWs in active region. In addition, since the passive QWs are designed to operate on the green gap spectral range they being less efficient than phosphor for that range and their sensitivity to active QW emission wavelength is a disadvantage Li et al. (2008). The best CRI for such devices reported is 41 Li et al. (2008). White light emission from all electrically pumped QWs with CCT\(\sim\)6000 K has been reported previously Li et al. (2008).  
In this paper, we demonstrate phosphor free, color tunable monolithic white LED. The device is designed for dichromatic emission at 450 nm and 550 nm. The emission wavelengths are such chosen so that the line joining the corresponding x-y coordinates on CIE 1931 chromaticity diagram passes through the white region. The x-y tristimulus coordinates of standard D65 illuminant is demonstrated with these devices at current densities of 6.21 A/cm\({}^{2}\). It is also shown that CRI of over 60 can be demonstrated with these devices and CCT of emission in such LEDs can be easily tuned by modulation of pumping current.
# Design and Analysis on Decoupling Techniques for MIMO Wireless Systems in 5G Applications
## 4 The Methods of Decoupling
### External Decoupling
#### 4.1.5 Metamaterials Technique  
Metamaterials are a kind of artificial structure to achieve mutual coupling reduction by affecting EM wave transmission. In metamaterial structures design, the negative permeability or permittivity can be constructed depending on requirements, which was described fully by [PERSON] et al. [52]. Thus, the propagation of EM waves can be altered in these structures with negative refractive indexes, which is opposite to the dielectric in nature. The electromagnetic band gap (EBG), split-ring resonator (SRR) and CSRR are commonly used types of metamaterials.  
The EBG and SRR can be equated to a resonator circuit, in which the microstrip lines are represented for inductance and the thin gap between them acts as capacitance. A four EBG array was inserted between two antenna elements as in Figure 5a [53]. Multiple stop bands were exhibited by the EBG array. The performance that EBG effectively suppresses the undesired surface waves excited in the E-plane was shown in Figure 5b and E-plane coupling was suppressed (>18 dB). A ten CSRR array was etched from the ground plane between two elements [54]. Additionally, the improvement of isolation about 41.26 dB can be observed by introducing CSRR.  
A metamaterial based on SRR was introduced and acceptable isolation can be attained [55, 56, 57]. The surface current distribution showed that the SRR structures placed on the bottom of each antenna element tended to increase the current density and the current boundaries were established [55]. Thus, the coupling effect was controlled with isolation better than 20 dB. A near-field resonator (NFR) consisting of five split rings was proposed [56]. It was observed from E-field distributions with decoupled arrays, the NFRs were attached above each patch element and acted as coupling-mode transformation. The two neighboring elements with NFRs performed orthogonal modes. Therefore, the isolation was further improved to more than 20 dB. In [57], an additional SRR structure was  
Figure 4: MIMO antenna with grounding branches: (a) geometry of proposed MIMO; and (b) the current distributions with DGS (Results from [48]).  
Figure 5: MIMO antenna with EBG: (a) geometry of proposed MIMO; and (b) current distributions (Results from [53]).  
placed on the top layer. The third resonance frequency at 5.1 GHz was compared without SRR and isolation better than 14 dB.
## 3 Design of Multi-Objective Fuzzy Continuous Damping Controller  
CDC suspension can guarantee the comfort of passengers under good level road conditions. The damping forces in the suspension can be changed through the control function of CDC suspension. This step can reduce the vehicle roll degree and change the vertical load distribution of the vehicle so as to aid the ESP. The vertical force on the suspension of each wheel can be expressed by the following equations, and the suspension model is shown in Figure 4.  
\[F_{v11}=K_{s1l}\Big{(}Z_{u1l}-Z_{s}+L_{1}\sin\theta+\frac{B_{1}}{2}\sin\varphi \Big{)}+C_{s1l}\big{(}Z_{u1l}^{\cdot}-w+L_{1}q\cos\theta+\frac{B_{1}}{2}p\cos \varphi\Big{)} \tag{19}\]  
\[F_{v12}=K_{s12}\Big{(}Z_{u12}-Z_{s}-L_{2}\sin\theta+\frac{B_{2}}{2}\sin\varphi \Big{)}+C_{s2l}\big{(}Z_{u12}-w-L_{2}q\cos\theta+\frac{B_{2}}{2}p\cos\varphi \Big{)} \tag{20}\]  
\[F_{v11}=K_{s1l}\Big{(}Z_{u1l}-Z_{s}+L_{1}\sin\theta-\frac{B_{1}}{2}\sin\varphi \Big{)}+C_{s1l}\big{(}Z_{u1l}^{\cdot}-w+L_{1}q\cos\theta-\frac{B_{1}}{2}p\cos \varphi\Big{)} \tag{21}\]  
\[F_{v22}=K_{s2}\Big{(}Z_{u2l}-Z_{s}-L_{2}\sin\theta-\frac{B_{2}}{2}\sin\varphi \Big{)}+C_{s2}\big{(}Z_{u2l}^{\cdot}-w-L_{2}q\cos\theta-\frac{B_{2}}{2}p\cos \varphi\Big{)} \tag{22}\]  
where \(F_{vij}\) is the vertical force of each wheel; \(p\), \(q\) are the roll angle rate and pitch angle rate of the vehicle, respectively; \(w\) is the vertical speed of the vehicle; \(\varphi\), \(\theta\) are the roll angle and pitch angle of the vehicle; \(K_{sij}\), \(K_{uij}\) are the stiffness coefficients of spring and wheel of each wheel, respectively; \(C_{sij}\), \(C_{uij}\) are the damping coefficients of the shock absorber and wheel, respectively; \(Z_{uij}\) is the unsprung mass  
Figure 3: Electronic stability program (ESP) controller model. According to the monorail model with two degrees of freedom, the ideal values of yaw rate and mass sideslip angle of the ESP control system are generated, and the difference is calculated with the actual measured yaw rate and the center of the mass sideslip angle. PID control is carried out to output the difference of the left and right wheel moments.  
displacement of each wheel; \(B_{j}\) is the wheel distance of each axle; subscript \(i\) (\(l\) or \(r\)) indicates the left or right side.  
The DYC moment can be written as:  
\[M_{zd-ESP}=(F_{b11}-F_{br1})B_{1}+(F_{b12}-F_{br2})B_{2} \tag{23}\]  
where \(F_{bij}\) is the braking force of each wheel (direction back is positive).  
The braking force is constrained by the adhesion of the ground:  
\[F_{bij}=\sqrt{\left(\mu F_{vij}\right)^{2}-F_{yij}}^{2} \tag{24}\]  
where \(F_{yij}\) is the lateral force of each wheel.  
The previous equations indicate that CDC can change the adhesion by changing the vertical force of the ground, thereby increasing the threshold range of the braking force.
# Research on Fractional-Order Control of Anchor Drilling Machine Optimized by Intelligent Algorithms
## 3 A Fractional-Order FOPID Controller Based on Intelligent Optimization Algorithms  
The automated bolting rig provides the hardware foundation for automated support operations, but the complex conditions of unmanned scenarios require enhanced control precision. To address this, we propose an optimized electro-hydraulic control strategy. Conventional proportional-integral-derivative (PID) control is insufficient for precisely aligning the manipulator-held drill rod with the power head, especially under non-linear load disturbances. Therefore, we introduce a collaborative control strategy combining fractional-order PID (FOPID) with algorithm-based optimization. By incorporating fractional differentiation (\(\uplambda\)) and integration (\(\upmu\)), this approach creates a more adaptable and precise control model.
###### Abstract
Bacterial species involved in the biodegradation of plastic contaminants frequently inhabit landfalls and plastic waste disposal sites [22]. Examples are Pseudomonas alcaligenes, _Bacillus cereus_[23], _Alcanvirorax_ sp. [24], _Bacillus licheniformis_, and Sb2 as _Achromobacter xylos oxidans_[25]. _Flavobacteriumeae_, _Rlabolobacteraceae_, and _Vibrioaceae_ are primary plastic degraders [26]. Furthermore, it has recently been reported that a consortium of three yeast species (_Sterigmatomyces halophilus, Meyerozyma guilliermondii_, and _Meyerozyma caribica_) showed a substantial ability for degradation of LDPE [27]. The extent of plastic degradation via microorganisms varies from species to species. It has been reported that _Bacillus cereus_ and _Brebibacillus bordelensis_ exhibited degradation activity at 35.72% and 20.28%, respectively [28]. Furthermore, _Bacillus_ sp., isolated from soil samples collected in Jayawijaya Mountain, Papua, Indonesia, was capable of degrading synthetic polyethylene terephthalate plastic films up to 4.77 b/b for four weeks. [22]. Microorganisms secrete enzymes that start plastic degradation, including multicopper oxidase, manganese peroxidase, lactose, alkane hydroxylase, alkane monooxygenase, and the ligninolytic enzyme [29]. Microorganisms can depolymerize these polymers by secreting enzymes called intracellular and extracellular depolymerases. These exoenzymes depolymerize polymers into monomers, which can then enter cell walls and be used as energy sources [30; 31]. However, pretreatment of the polymer, which facilitates the oxidation to produce a carbonyl group C=O, can reduce the time required to biodegradable LDPE and can help facilitate the first step in polymer biodegradation [32]. There have been no intensive studies conducted in the Kingdom of Saudi Arabia's Eastern Province to describe and characterize the microorganisms capable of removing plastic contaminants from the environment. It has been reported that pyrene- and phenanthrene-degrading bacteria (_Pseudomonas aeruginosa, P. citronellosis, Ochrobarrum intermedium, and Cupriavidus taiwanensis_) were isolated from the Eastern Province, Saudi Arabia [33]. Furthermore, in the Al-Ahsa region, there are several industrial, medical, and domestic areas with plastic contamination, reflecting the potential risk to human health and existing organisms. Therefore, there is a desperate need to restore the environment to its original, healthy state. That is why we intend to look into the issue of plastic degradation and the bacterial species involved in the mechanism. This study aimed to isolate and identify bacterial species that have the potential to degrade low-density polyethylene (LDPE) from soil samples collected from a plastic dumping ground. The extent of degradation was analyzed, and morphological changes in the plastic powder were determined using weight loss and FTIR. The molecular identification of the isolated bacterial strains using 16S RNA gene analysis was also determined.
# Laser Observations of GALILEO Satellites at the CBK PAN Astroegodynamic Observatory in Borowiec
## 2 Laser Sensor at CBK PAN Borowiec (BORL)
Figure 2 displays the quantity of objects monitored by the BORL station from 1992 to 2023. It is evident from the figure that for nearly 20 years, the number of objects detected by the BORL station did not surpass 21. A significant rise in the number of tracked objects occurred in 2015. Subsequently, two separate laser modules were introduced at the BORL station (Figure 1), enabling the initiation of data collection not only from satellites on the ILRS list but also from numerous debris objects. In addition, between 2011 and 2022, many new satellites were added to the ILRS tracking list, with over 80 being mainly GNSS satellites (62 objects in total) that are still being tracked by laser stations. This increase in satellites also led to a significant rise in the number of objects monitored by the BORL station.
# State of the Art and Trends Review of _Smart Metering_ in Electricity Grids
## 5 Challenges to be Addressed in the Near Future
A review of the critical parameters used and assumptions made in national rollouts will help to refine technology choices. In the United States, _Smart Metering_ is still a developing industry. The FERC highlights the lack of integration of _HAN_s with _Smart Metering_ systems, as well as existing uncertainty over the development and evolution of standards and their effect on networking technology, especially regarding _HAN_ integration [17]. Utilities are also concerned about obsolescence, which may be addressed by adopting the most adequate technology for every particular case. Another subject under discussion, barely seen in Europe, refers to the impact of _Smart Metering_ deployment on residential customers and its translation into real bill savings [10]. This issue can be addressed by allowing access to metering data in real time to end-consumers and by offering peak-time rebates. Additionally, most _Smart Metering_ projects in the U.S. have had to deal with a lack of confidence among customers regarding magnetic radiation emissions, remote supply disconnections, and privacy issues [61]. This work has been partially supported by the Spanish Ministry of Economy and Competitiveness (project TEC2015-67868-C3-1-R), the University of the Basque Country (UPV/EHU) within the program for the specialization of the postdoctoral researcher staff, and _Microgrids with Renewable DistributedGeneration_ (MIGEDIR) (project 713 RT0468), funded by _the Science and Technology for Development Iberoamerican Program_ (CYTED). The authors declare no conflict of interest.