esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Materials and Methods
### Experimental Design and Optimization through Response Surface Methodology  
For mathematical modelling of the process, an empirical approach [29; 30; 31] employing response surface methodology (RSM) was adopted [32; 33; 34]. RSM reportedly reduces systematic errors with an estimation of investigational error and also reduces the number of experiments [30], requires lesser computer simulations, is more accessible and more efficient than the other methods based on limited components or computational complexity [31].  
RSM based on the central composite design (CCD) was used to examine the efficacy of the NF membrane and EC processes. CCD helped in arriving at the operational conditions highlighting the highest removal efficiency scenarios. In the NF membrane process, the solution pH, pressure, concentration, and temperature were the key factors widely reported to contribute to the removal of metal ions [35; 36; 37; 38] and thus design expert software was used for the experimental design with a varying range of these factors (Table 1).  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Code**} & \multirow{2}{*}{**Factors**} & \multicolumn{6}{c}{**Coded Level of N.E**} \\ \cline{3-7}  & & \(-\alpha\) & \(-1\) & \(0\) & \(+1\) & \(+\alpha\) \\ \hline X\({}_{1}\) & pH & 2.0 & 4.5 & 7.0 & 9.5 & 12.0 \\ \hline X\({}_{2}\) & Pressure (bar) & 2.5 & 10 & 17.5 & 25 & 32.5 \\ \hline X\({}_{3}\) & Concentration (ppm) & 2.5 & 10 & 17.5 & 25 & 32.5 \\ \hline X\({}_{4}\) & Temperature (\({}^{\circ}\)C) & 5 & 15 & 25 & 35 & 45 \\ \hline \multirow{3}{*}{Code} & \multirow{3}{*}{Factors} & \multicolumn{6}{c}{Coded level of E.C.} \\ \cline{3-7}  & & \(-\alpha\) & \(-1\) & 0 & \(+1\) & \(+\alpha\) \\ \hline X\({}_{1}\) & pH & 3.0 & 4.5 & 6.0 & 7.5 & 9.0 \\ \hline X\({}_{2}\) & Time (min) & 20 & 40 & 60 & 80 & 100 \\ \hline X\({}_{3}\) & Concentration(ppm) & 2.5 & 10 & 17.5 & 25 & 32.5 \\ \hline X\({}_{4}\) & Current (Å) & 0.5 & 1.0 & 1.5 & 2.0 & 2.5 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Factor and range for design experiments of NF membrane and EC.  
In the EC process, solution pH, time, concentration, and current were the key factors [25] widely reported to contribute to the removal of metal ions [39; 40; 41; 42] and thus design expert software was used for experimental design with a varying range of these factors (Table 1). The initial and final conductivity values were 2.78 and 2.35 mS/cm for the final optimum condition. The complete design matrix of the NF membrane and EC processes obtained after the application of CCD is presented in Supplementary Table S1 and Supplementary Table S2 respectively, which suggest thirty sets of runs and six centrally coded level runs for each treatment process.
## 3 Hydrological Applications
### Indirect estimation of Hydrological parameters
#### 3.2.2 Fractional Vegetation Cover  
To understand the change in the vegetation cover for images of different scenes and dates, the scaled NDVI (\(NDVI_{s}\)) has been used by many researchers ([PERSON], 1987; [PERSON] and [PERSON], 1992; and [PERSON] and [PERSON], 2000).  
\[NDVI_{S}=\frac{NDVI-NDVI_{low}}{NDVI_{high}-NDVI_{low}} \tag{1}\]  
where NDVI\({}_{\rm low}\) and NDVI\({}_{\rm high}\) are values for bare soil and dense vegetation respectively.  
[PERSON] and [PERSON] (1997) found the relationship between fractional vegetation cover (FVC) and scaled NDVI to be  
\[FVC\approx(NDVI_{S})^{2} \tag{2}\]  
Where FVC ranges between 0 and 1.  
From the 1986 TM and 2000 ETM\({}^{+}\) Landsat images, PVC was estimated for Econlockhatchee River sub-basin (Econ sub-basin), Florida and compared to understand the change sin the vegetation cover over the 16 years (Figure 6) ([PERSON] et al. 2003a, 2003b).  
Figure 5: Land cover mapping: (a) Scattergram of NDVI vs surface temperature (b) Land cover classes of Heart River sub-basin, Missouri River basin.
# Range-Doppler Based CFAR Ship Detection with Automatic Training Data Selection
## 4 Clutter Statistics and Detection
### Chi Square \(\left(\chi^{2}\right)\) Distribution  
The \(\chi^{2}\) distribution is one of the models used when the K-distribution fit fails because the estimated shape parameter gives negative values. The \(\chi^{2}\) distribution function with \(2L\) degrees of freedom is represented as [45]  
\[f(I,\sigma,L)=\frac{I^{L-1}}{2^{L}\sigma^{2L}\Gamma(L)}\exp\left(\frac{-I}{2 \sigma^{2}}\right)I\geq 0, \tag{22}\]  
The number of unknowns in this case is 2: number of looks \(L\) and the standard deviation \(\sigma\). The PFA as a function of the threshold \(\eta\) can be written as  
\[P_{\text{fa}}\left(\eta\right)=\frac{1}{\Gamma(L)}\,I\!\left(L,\frac{\eta}{2 \sigma^{2}}\right), \tag{23}\]  
where \(\Gamma(\cdot)\) is the gamma function. For a single look, the threshold becomes \(\eta=-2\sigma^{2}\ln(P_{\text{fa}})\). The parameters in this case are estimated using the NLLSQ method as explained in Section 4.1.2.
## 6 Conclusions and Future Works  
In this paper, DNN-based indoor localization schemes are presented. We use LDA for preprocessing the RSS data sources, and then BSSIDs having the five strongest RSS values were appended with filtered RSS values for training and testing. The proposed system is evaluated with respect to classification- and regression-based indoor localization. Our proposed method is also compared with KNN and SVM-Poly in different scenarios to evaluate its localization accuracy. The proposed system has 99.15% localization accuracy with respect to the classification scheme. For regression-based localization, 100% of the estimation accuracy has an error less than 0.98 m in the proposed approach. Additionally, our method was performed with lower error mean and variance, which implies the error distributions in each set of testing points are low and slow. The computational time complexities are also improved in the proposed method, compared to other algorithms, in each scenario. Thus, the integration of MLP and LDA gives state-of-the-art performance on indoor localization in hierarchical and multi-buildings environments. For indoor localization, LDA jointly working with kernel methods is proposed as a future work, since the datasets transformed into a projection function may not be always linear. The application of a DNN for indoor-outdoor localization using an unmanned aerial vehicle in urban areas is also a potential future work.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Algorithm**} & \multicolumn{3}{c}{**Testing Times of MLP in Different Scenarios (s)**} \\ \cline{2-4}  & **Scenario 1** & **Scenario 2** & **Scenario 3** \\ \hline MLP & 1.16 & 0.39 & 0.24 \\ \hline \hline \end{tabular}
\end{table}
Table 5: Regression-based computational complexity.  
regarding the work. [PERSON] performed the experiment, and wrote the program with A.B.A. S.-[PERSON] collected related references and gave comments. Finally, all mentioned authors read and approved the final version of the manuscript.  
This research was funded by Ministry of Science and Technology (MoST) in Taiwan (Grant No: 107-2634-F-009-006).  
This research is partially supported by Ministry of science and Technology, Taiwan government 2018.  
The authors declare no conflict of interest.
## 1 Introduction  
Hyperbolic topologies have sparked the imaginations of science fiction prosaists for almost a century [1]. In turn, the topology of isofrequency k-surfaces in photonic materials now fascinates the members of the optics community. The known topologies include bounded k-surfaces, such as spheres or ellipsoids, and unbounded k-surfaces--single- and double-leaf hyperboloids [2; 3; 4], and recently discovered bihyperboloids [5]. As can be seen from this list of k-surface topologies, the main difference between them and therefore the key to their classification is the propagation or absence of high-k modes in the corresponding materials (Figure 1). The high-k modes, which are the short-wavelength solutions of macroscopic Maxwell's equations in hyperbolic metamaterials, are of primary interest in photonics, and have already found applications for optical imaging in nanoscopic resolution using hyperlenses, emission control due to diverging optical density of high-k states, and emission-directivity control [6].  
With the development of nanofabrication, a variety of bianisotropic and chiral metamaterials have been realized, which includes a combination of split-ring resonators, helixes, gammadions, and other metallic shapes in unit cells [6]. In this letter we theoretically predict novel isofrequency topology phases, tri- and tetrahyperbolic materials, and obtain an equation that describes the k-space directions in which the high-k modes exist in terms of the 36 material parameters of an arbitrary bianisotropic material. Furthermore, we employ a theorem from [PERSON] (1873) [7] to show that our prediction of the tri- and tetrahyperbolic topological phases completes the classification of bianisotropic materials, meaning that an optical material belongs to one of the following classes--tetra-, tri-, bi-, mono-, or nonhyperbolic. The novel tetra- and trihyperbolic phases which we predict here are induced via the introduction of chirality. Chirality-induced modification of topology in the energy-momentum space was previously studied for monohyperbolic materials [8]. Here we discuss the topology of isofrequency surfaces in k-space.  
We show that in all high-k modes, both electric and magnetic fields are polarized longitudinally. In this sense, these modes are similar [9] to the bulk plasmon polaritons, bulk magnon polaritons, or longitudinal optical phonon polaritons, except that the high-k modes are short-wavelength. Therefore, we shall refer to these modes as high-k polaritons (HKPs). For these HKPs, we explicitly express the ratio between the longitudinal electric and magnetic field, i.e., longitudinal impedance \(Z_{l}\), in term of the 36 bianisotropic material parameters. To accomplish this, we introduce the index of refraction operator \(\hat{N}\). We obtain the direction-dependent refraction indices explicitly in arbitrary bianisotropic material.
# Algorithms Utilized for Creep Analysis in Torque Transducers for Wind Turbines
## 2 Creep Study  
### Parameters Influencing Torque Transducer Creep  
Various parameters, including temperature, applied load, calibration frequency, and environmental factors, influence the creep behavior of torque transducers [17; 18; 19; 20].  
* Temperature: Temperature variations significantly impact the performance and accuracy of torque transducers. High temperatures can lead to thermal expansion, causing materials to deform and introducing measurement errors. On the other hand, low temperatures can affect the viscosity of lubricants used within the transducers, resulting in changes in frictional forces and subsequently affecting their creep behavior.
* Applied Load: The magnitude and duration of the applied load directly influence the creep characteristics of torque transducers. High loads can cause deformation within the transducer's sensing elements and alter their elastic properties, leading to an increased likelihood of creep. Moreover, long durations of sustained load can induce plastic deformation in the transducer, resulting in permanent changes in its calibration and accuracy.
* Calibration Frequency: Regular calibration is essential for maintaining the accuracy of torque transducers. The frequency at which these instruments are calibrated affects their creep behavior. Infrequent calibrations may lead to drift or systematic errors over time, impacting the reliability of torque measurements. Therefore, regular and timely calibration routines are necessary to ensure the optimal performance of torque transducers in wind energy applications.
* Environmental Factors: Environmental conditions, such as humidity and dust exposure, can influence the creep behavior of torque transducers. Moisture absorption may affect the transducer materials' mechanical properties, leading to changes in creep rates. Additionally, dust or contaminants can accumulate on transducer surfaces, altering their friction characteristics and introducing measurement errors. Therefore, protection measures to mitigate these environmental factors are essential for maintaining accurate torque measurements.  
Understanding the key parameters influencing torque transducer creep is essential for ensuring accurate and reliable measurements in wind energy applications.
# New Satellite Selection Approach for GPS/BDS/GLONASS Kinematic Precise Point Positioning
## 4 Test and Analysis
### Positioning Accuracy of the NSS Model
#### 4.2.2 The Measured Data
The above results mean that the computational load could be significantly reduced in undifferenced and uncombined GPS/BDS/GLONASS kinematic PPP with the use of the proposed NSS model. Additionally, the positioning accuracy of the NSS model PPP solution is still within the requirement and similar to the optimal DOP algorithm solution. This study can provide a reference for the application of satellite selection algorithms in real-time kinematic PPP in low-cost GNSS receivers.
# Numerical Simulation on Dynamic Behavior of Slab-Column Connections Subjected to Blast Loads
## 4 Analysis Results
### Critical Section in Slab  
In slab-column connections, a section that is 1/2 of the effective depth, d, from the outer surface of the column is regarded as a critical section [45]. Sufficient safety must be ensured for critical sections to prevent the collapse of the entire structure due to large damage of the joints [44,64]. Figure 8 shows failure shapes of slabs for specimens subjected to 12 kg of TNT. For specimens EC and CC, spalling due to the blast load occurred over the critical section, but specimens IC and IC-D showed a more positive structural behavior in which spalling did not spread to the critical section. Table 4 shows the deformation and support rotation at the critical section for all specimens. The deformations in the critical section of the specimens IC-D4 and IC-D12 were 0.040 mm and 3.284 mm, which were the least deformations among the specimens subjected to the same blast load. Figures 9 and 10 show the deflections in the critical section. In Figure 9, the specimens, except for specimen  
Figure 6: Slab deflection of specimens with TNT 4 kg.  
Figure 7: Slab deflection of specimens with TNT 12 kg.  
According to the criteria, the limit of support rotation to effectively resist the moment is two degrees [41; 43]. However, according to the analysis results, it was found that this evaluation criterion alone was insufficient to adequately represent the blast-resistant performance of the member. This is because the support rotation in the critical section of all specimens was below the criteria limit of two degrees, but in reality, most specimens showed that the slab was destroyed. Therefore, in order to more accurately and reasonably evaluate blast-resistant performance, it is necessary to consider various evaluation factors in addition to support rotation.
###### Abstract  
Energy efficiency and spectrum efficiency are the most important issues for future mobile systems. Heterogeneous networks (HetNets) with coordinated multiple points (CoMP) are wildly approved as a promising solution to meet increasing demands of mobile data traffic and to reduce energy consumptions. However, hyper-dense deployments and complex coordination mechanisms introduce several challenges in radio resource management (RRM) of mobile communication systems. To address this issue, we present an RRM approach for CoMP-based HetNets, which aims to maximize weighted energy efficiency while guaranteeing the data rate of each transmission. The proposed RRM approach is based on a cross-entropy (CE) optimization method that is an effective and low-complexity heuristic algorithm. Furthermore, we also give the implementations of the proposed RRM approach in centralized and decentralized mode, respectively. At last, extensive simulations are conducted to validate the effectiveness of the proposed schemes.  
cross-entropy (CE) method; heterogeneous network (HetNet); coordinated multipoint (CoMP); energy efficiency (EE) +
Footnote †: journal: Information
## 2 Materials and Methods
### Evaluation of Antioxidant Activity  
To determine the antioxidant potency of _C. axillaris_ ethyl acetate, acetone, methanolic, and aqueous extracts, a widely accepted and simple 1,1-diphenyl-2-picrylhydrazyl (DPPH) free radical scavenging technique was selected. The experimental procedure for this study was adopted from a previously published research article [46] with slight modifications. A DPPH solution with a concentration of 0.1 mM was prepared using ethanol as the diluent. Similarly, stock solutions of standard ascorbic acid (10 ug/mL) and plant extract (1 mg/mL) were prepared using the same diluent. Subsequently, four different concentrations of diluted ascorbic acid solutions (10 ug/mL, 5 ug/mL, 2.5 ug/mL, and 1 ug/mL) and six different concentrations of plant extract solutions (250 ug/mL, 125 ug/mL, 62.50 ug/mL, 31.25 ug/mL, 15.625 ug/mL, and 7.812 ug/mL) were prepared using a serial dilution technique. For the free radical scavenging reaction, 5 mL of DPPH solution was transferred into a glass test tube, followed by the addition of 5 mL of the plant extract solution into the same tube. This reaction was performed separately for each diluted plant extract and standard sample in individual tubes. After thorough mixing, the resulting mixture solutions were incubated for approximately 30 min, ensuring protection from light. The degree of DPPH free radical scavenging by various concentrations of plant extract samples was assessed by measuring the absorbance of plant extract-DPPH solutions using a UV spectrophotometer at 517 nm. Ethanol served as the blank control, while the ascorbic acid solution acted as the positive control. Each measurement was conducted three times. The percentage of free radicals inhibited by each plant extract sample was calculated using the following equation:  
\[\text{Percentage radical scavenged}=[(\text{A}_{0}-\text{A}_{5})/\text{A}_{0}] \times 100\%\]  
The equation used for calculating the percentage of free radicals inhibited is based on the absorbance values, where A\({}_{0}\) represents the absorbance of the blank control and A\({}_{5}\) represents the absorbance exhibited by the DPPH-plant mixture. Additionally, the IC\({}_{50}\) value, which represents the concentration of the sample in \(\upmu\)g/mL required to inhibit 50% of DPPH free radicals, was determined through logarithmic regression analysis by interpolating the data obtained for different concentrations of the plant extract [46].
# Integrated DVB-X2 Receiver Architecture with Common Acceleration Engine
## 3 DVB-X2 Receiver Architecture
### Interface between the H/W Engine and the Frame Processor  
A large amount of data is exchanged between the H/W engine and the frame processor. Therefore, if the data is not effectively exchanged, the frame processor may have difficulty in processing the DVB-T2, DVB-C2, or DVB-S2 frame. To solve this problem, an interrupt method is used. The DVB-T2/C2 demodulator generates an interrupt each time an OFDM symbol is received. It provides an index each time an OFDM symbol is stored in order to prevent loss of an OFDM symbol. The DVB-S2 demodulator is difficult to share the first-in first-out (FIFO) memory used in the DVB-T2/C2 demodulator because of the clock using a different frequency. Thus, it directly interfaces with the LDPC decoder through a separate FIFO memory. If multiple sources generate interruptions, it can degrade the performance of the frame processor. Therefore, data transfer between the LDPC decoder and the frame processor is based solely on the interrupt generated by the DVB-T2/C2 demodulator.  
Figure 8 shows the procedure of data transfer between the frame processor and the H/W engine to perform decoding of the T2 frame. The operation of the frame processor is as follows. If the H/W engine triggers the interrupt, the frame processor moves the data stored in the memory of the H/W engine into the internal memory of the frame processor. Then, the frame processor performs the possible functions with the data collected up to then and waits for the interrupt again. The functions of the frame processor include functions to collect many OFDM symbol data. For example, in order to perform the time de-interleaving function, a number of T2 frames need to be received depending on the operation mode. Thus, each time the interrupt is generated, it performs only storing data needed to perform the time de-interleaving function and performs other functions. When the interrupt is generated again and all of the data is collected, the frame processor performs the time de-interleaving function and other functions.  
Figure 8: Example of data transfer between the frame processor and H/W engine.
## 2 Nanoparticle-Modified Electrodes

Table 2: _Cont._producibility are often encountered. To address these issues, various strategies have been developed to modify the surfaces of electrodes using different redox-active molecules, perm-selective polymers, and electrode activation methods. These modifications result in improved electrode activity and sensitivity towards the target material, faster electron transfer between the analyte and electrode, increased electrocatalytic activity with a larger surface area, faster diffusion at the electrode surface, less interference, and reduced fouling [79; 80]. In addition to their electrocatalytic properties, these nanoparticle-modified electrodes have the advantages of low cost, high sensitivity, and convenient operability, making them very promising to overcome potential interferences from analogs with similar chemical structures and to improve the stability and selectivity of these sensors. Recently, two-dimensional nanomaterials have received great attention in the field of electrochemical applications because of their outstanding physicochemical properties [81]. Therefore, vanadium carbide entrapped on graphitic carbon nitride nanosheets (VC/g-CN NSs) was used as a highly efficient electrocatalyst for the determination of furazolidone (FZD) in biological samples. The electrochemical performance of the VC/g-CN NSs-modified glassy carbon electrode (GCE) for FZD detection was studied using cyclic voltammetry and amperometric methods. Thus, the proposed electrode offered active sites with a large electron-transfer rate and a rapid mass transport ability to enhance the electrochemical activity toward FZD detection. Under the optimization conditions, the VC/g-CN NSs modified electrode showed a wide detection range (0.004-141 \(\upmu\)M), a very low detection limit (0.5 nM), and excellent selectivity and reproducibility.
## 2 Materials and Methods
### qPCR Preparation  
Total RNA was extracted from bovine cartilage explants following PEMF exposure for 7 days, with parallel untreated controls. Cartilage was homogenized using TRIzol reagent (Cat. No. 15596018; Thermo Fisher Scientific, Waltham, MA, USA) and chloroform was added to extract total RNA followed by vigorous agitation [48]. RNA precipitation was performed using Qiagen miRNeasy columns (Cat. No. 74106; QIAGEN, Hilden, Germany). cDNA was synthesized from RNA using the iScript cDNA Synthesis Kit (Product No. 1708891; Bio-Rad, Hercules, CA, USA) and diluted to 1 ng/\(\upmu\)L concentration for PCR. Gene specific master mixes were prepared using the designed primers, and iTaq Universal SYBR Green Supermix (Product No. 1725122; Bio-Rad, Hercules, CA, USA). RT-qPCR was run on a QuantStudio(tm 6 Flex Real-Time PCR System (Applied Biosystems, Waltham, MA, USA) [47]. The following primers (Integrated DNA Technologies) were evaluated: aggrecan (ACAN) and collagen types I-V, X-XI alpha 1 chain (COL1, COL2, COL3, COL4, COL5, COL10, COL11) (Table 1). GAPDH was used as the housekeeping gene, and all samples were normalized to day 0 controls using the 2\({}^{-\Delta\Delta\text{CI}}\) method.