esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction  
Microwave radiometry is today routinely used to remotely measure geophysical parameters. Microwave radiometers are highly sensitive instruments, but measurements may be corrupted by the presence of Radio-Frequency Interference (RFI). Sources of RFI include spurious signals and harmonics from lower frequency bands, spread-spectrum signals overlapping the \"protected\" band of operation, or out-of-band emissions not properly rejected by pre-detection filters.  
The presence of RFI in the pre-detected voltage signal modifies the value of the measured power leading to an erroneous retrieval of the measured geophysical parameters [1; 2; 3]. In recent years, techniques to detect the presence of RFI in radiometric measurements have been developed. They include time- and/or frequency domain analyses [4], or statistical analysis of the received signal [5; 6].  
In addition, the so-called Spectral Kurtosis algorithm has been studied in [7] with good results, taking advantage of the effectiveness of the combination of different RFI detection algorithms.  
Combining the time and frequency domains analysis jointly, the spectrogram stands as a powerful tool which has been previously used in RFI detection in radio-astronomy [8,9]. The spectrogram consists of an intensity plot (usually on a decibel scale) of the Short-Time Fourier Transform (STFT) magnitude [10]. The STFT consists of a set of Fourier Transforms (FT) of consecutive windowed data segments from a longer data set. Windows usually overlap in time, thus data segments may have redundant information, as sketched in Figure 1. The STFT provides time-localized spectral information of the frequency components of a signal varying over time, whereas the standard FT provides the frequency information averaged over the entire signal time interval [10]. As a spectrogram is a two-dimensional intensity plot, it can be analyzed as an image, thus having all the image processing tools at our hand.  
In this work, a simple thresholding algorithm to detect and eliminate interference patterns in radiometric signal spectrograms is developed first, and simulation results are presented. The simulated RFI signals are generically from the sinusoidal and chirp families. By adjusting the signals' parameters, the bandwidth and temporal duration, many different types of signals can be obtained. A two-dimensional (2D) Wiener filter is then applied to the spectrogram in order to try to improve the cancellation of RFI components in the radiometric signal. A brief description of the spectrogram calculation is given in Section 2. Section 3 describes the image processing algorithm proposed in this work, which is called \"Smoothing Algorithm\". In Section 4 the Wiener filtering process is described and compared to the \"Smoothing Algorithm\" proposed. Section 5 shows the results obtained with the application of both algorithms to a thermal noise signal contaminated with a set of RFI chirp signals. Finally, Section 6 summarizes the conclusions of this work.  
Figure 1: Process of obtaining a Spectrogram from a sampled signal of thermal noise.
## 3 Results
### Image Fusion Results  
The Landsat remote sensing image sequence and the HJ-1 B remote sensing image sequence are fused according to the method discussed in Section 2.2.3. Figure 4 shows the original images of Landsat and HJ-1 B image sequences and the fused image in a certain area of the study area.  
Table 2 lists the statistical characteristics of the images in the orange squared region before and after the fusion. Combined with visual effects and statistical results, it can be concluded that the fused remote sensing images are more similar to the Landsat.
###### Abstract  
Six concrete beam-column frame sub-assemblages reinforced with basalt fiber-reinforced polymer (BFRP) bars in the frame beams were designed to investigate the collapse resistance after a middle column removal. Effect of parameters, including span to depth ratio of frame beams, prestressing, as well as material types of stirrups in the beams, on the collapse resistance of the sub-assemblages, was investigated. Experimental results showed that the initial stiffness of the frame beams was apparently lower due to low elastic modulus of BFRP bars. The collapse resistance of the sub-assemblages presented wave-like increasing tendency with the vertical displacement of the failed middle column, and it mainly attributed to the cracking or crushing of concrete and rupture of BFRP bars in the frame beams. Top longitudinal BFRP bars at the beam ends near to the side column (BESCs) and bottom longitudinal BFRP bars at the beam ends near to the middle column (BEMCs) kept tensile during the loading process, which played an important role in resisting structural collapse. Adjacent structural members such as frame beams and columns could provide horizontal reaction forces to constrain the free deformation of the residual sub-assemblages after the middle column failed, and it was beneficial to mitigate the structural collapse risk. The vertical deformation of the frame beams was nearly linear and proportional to the vertical displacement of the failed middle column. Finally, the dynamic increase factor (DIF) of collapse load was discussed using energy conservation method, and a calculation method of DIF for prestressed concrete frame structures was developed. It was suggested that the DIF values for the non-prestressed frame structures reinforced with BFRP bars in the beams should be taken as 2.0, while those for the prestressed sub-assemblages can be taken between 1.44 and 2.0.  
Keywords:Progressive collapse; basalt fiber reinforced polymer (BFRP); dynamic increase factor (DIF); prestressed concrete +
Footnote †: journal: Applied Soft. 2019, 9, 4436; doi:10.3390/appr9204436
## 2 Related Work
Additionally, while numerous studies have explored the advantages of IBC over traditional radio frequency (RF) communication, very few have proposed robust methodologies for integrating biometric identification into IBC frameworks. This gap in the research highlights the need for a systematic approach to utilize IBC for reliable user identification within WBANs.
## 3 Results and Discussion
### Effect of Tungsten Addition on Laves Phase Precipitation
Figure 6: Representative SEM-BSE micrographs of thermomechanically induced Laves phase evolution of model alloys (**a**) Fe17 Cr2.6W and (**b**) Fe17 Cr3.6W created by deformation at 800 \({}^{\circ}\)C, deformation grade of 0.5, and isothermal tempering after the deformation at 800 \({}^{\circ}\)C for 60 s.  
Figure 7: Results of the quantitative particle analysis: (**a**) particle size equivalent circle diameter (ECD), (**b**) phase fraction, and (**c**) ultimate tensile strength and yield strength of model alloys Fe17 Cr2.6W and Fe17 Cr3.6W. Due to the higher diffusivity of niobium atoms in the ferritic matrix as compared to tungsten, an early precipitation of the unstable niobium-rich LT Laves phase was observed. Generally, this is attributed to better thermodynamic conditions for nucleation and further growth [23]. However, during ongoing heat treatment, a diffusion flux is created and the LT Laves phase starts to decompose. This continued process of tungsten enrichment during isothermal annealing has been already observed and reported in [23; 24; 25]. The higher availability of the tungsten atoms with a slow diffusivity in the ferritic matrix reduces the diffusion distance for the atoms to reach the precipitates. Laves phase precipitation during thermomechanical treatment occurs in this class of steels immediately. Therefore, a noticeable tungsten enrichment of the Laves phase precipitates was expected. A comparison of the chemical composition of the precipitated particles is shown in Figure 8 based on the SEM-EDX analysis. Regarding the EDX-tested area and the size of the analyzed fine particles, the estimated chemical composition does not correspond to the exact composition of the Laves phase precipitates, because the surrounding ferritic matrix influences the results. However, the analysis is sufficient for the investigation of the trend in the developing chemical composition of the precipitates. Additionally, the simulated chemical composition of the unstable LT and stable HT Laves phases are given. The tungsten enrichment of the precipitated Laves phase particles in the high tungsten alloy at the expense of niobium and iron content can be observed. A tungsten content of 11.9 wt. % in Fe17 Cr2.6W and 18.8 wt. % in Fe17 Cr3.6W, respectively, has been reached. In comparison to the simulated chemical composition, the stable content of tungsten corresponds to 44.5 wt. %. Consequently, a stable state of the HT Laves phase has not been achieved by thermomechanical treatment, and therefore, further tungsten enrichment of the precipitates can be expected during application at operating temperature, as reported in [24].
## 2 Background and Related Work
### VANET Design Issues and Challenges  
[PERSON] et al. [20] discussed various issues in VANET applications, including hidden and exposed node problems, stability, scalability, reliability, and security. High mobility and rapid network topology changes in vehicular networks can impact system operations. Scalability, as well as hidden and exposed node problems, also affect the system performance. [PERSON], [PERSON] et al. [21] studied VANET performance under various traffic loads. [PERSON] [22] investigated the potential of VANET for safety applications and focused on security and privacy issues. Researchers have explored various aspects of VANET, including traffic, infrastructure requirements, and security measures. [PERSON] et al. [23] developed an accident prevention technique using real-time warnings to drivers. Overall, VANETs offer promising safety applications but their security and infrastructure considerations require attention. The challenges pertaining to the security and applications of VANET have been the subject of recent studies [24; 25].
# A Review of Early Injection Strategy in Premixed Combustion Engines
## 3 Injection Timing
### Two-Stage Early Injection
#### 3.2.2 Second Injection Timing
The retarded second injection caused the combustion to continue after TDC. As a result, the unburned fuel was increased by the lower in-cylinder temperature and pressure during the expansion stroke. CO emission also increased as the second injection was retarded because of the decreased cylinder temperature. However, retarding the second injection prolonged the time to form a leaner mixture, and it burned under low-temperature conditions during the expansion stroke, resulting in a drop of NOx emissions. [PERSON] et al. [87] investigated the effects of second injection timing on combustion and emissions of an HCCI-DI engine. Results showed that retarding the second injection timing increased the cooling  
Figure 9: Flame characteristics as a function of second injection timing change [79]. (**a–d**): different second injection timing, the images of flame change with crank angle. effect and inhomogeneity of the mixture, which decreased peak cylinder mean temperature values (Tmax). NOx emissions decreased, while CO emissions increased due to incomplete combustion. [PERSON] et al. [88] studied the effects of main injection timing on controlling the combustion phasing of a homogeneous charge compression ignition engine using a new dual-injection strategy. The main injection timing (MIT) was investigated from 26\({}^{\circ}\) to 8\({}^{\circ}\) BTDC. Results showed that BTE for HCCI combustion was consistently lower as the MIT was retarded. BSFC was the opposite. As the MIT was retarded, NOx emissions decreased because peak cylinder pressure got lower. As the injection timing was retarded, ignition delay of the main fuel was further reduced, resulting in increased smoke formation. Because the retarded main injection put off the combustion phasing and subsequently increased ignition delay, the pilot fuel was mixed better, leading to rapidly increasing HC emissions. Table 5 shows a summary of the variation of the performance and emissions of the PCCI engine after retarding the second injection timing. In general, retarding the second injection timing will reduce NOx emissions, but increase soot, HC, and CO emissions. Engine performance deteriorates with retarding of second injection timing due to the shifting of diffusive combustion to later than TDC.
## 2 Materials and Methods
### Purification of Recombinant Maize Z-ISO  
Maize Z-ISO fused to maltose-binding protein (MBP) was purified following a protocol adapted from those described by [PERSON] et al [5,35,36]. The sequence of the codon-optimized construct that was cloned into pET21a(+), yielding plasmid pH545, is provided in Table S3. Twelve 500 mL cultures of _E. coli_ BL21(DE3) harboring pH545 were grown in 2 xYT medium (10 g L\({}^{-1}\) yeast extract, 16 g L\({}^{-1}\) tryptone, and 5 g L\({}^{-1}\) NaCl) containing100 \(\mu\)g mL\({}^{-1}\) ampicillin at 37 \({}^{\circ}\)C with shaking (200 rpm) to an optical density at 600 nm of 0.6, at which point 1 mM isopropyl \(\beta\)-d-1-thiogalactopyranoside was added to each culture and the temperature was lowered to 28 \({}^{\circ}\)C for overnight (~18 h) incubation. Cells were collected by centrifugation at 8671\(\times\)\(g\) for 10 min at 4 \({}^{\circ}\)C and resuspended in 50 mM Tris-HCl pH 7.6, 300 mM NaCl, 5% (\(w/v\)) glycerol, 0.5 mM dithiothreitol (buffer A) supplemented with a Roche protease inhibitor tablet, and a small spatula each of DNase I and lysozyme. The cell suspension was cooled on ice and lysed by two passes through a chilled French press at 18,000 psi with 5 min of chilling on ice between cycles. Lysed cells were centrifuged at 7025\(\times\)\(g\) for 20 min at 4 \({}^{\circ}\)C to remove cell debris and unbroken cells, and the supernatant was centrifuged again at 48,400\(\times\)\(g\) for 30 min at 4 \({}^{\circ}\)C to pellet _E. coli_ membranes. The pellet (membrane fraction) was resuspended in 80 mL buffer A and n-dodecyl-\(\beta\)-D-maltoside (\(\beta\)-DDM; Anatrace) was added to a final concentration of 1.5% (\(w/v\)) before a 1-h period of incubation in the dark at 4 \({}^{\circ}\)C with gentle agitation. The solubilized membrane solution was centrifuged at 48,400\(\times\)\(g\) for 30 min at 4 \({}^{\circ}\)C and the supernatant was retained, diluted 2x in buffer A, and incubated with 3 mL of pre-washed amylose resin (New England Biolabs (UK) Ltd.) overnight at 4 \({}^{\circ}\)C with gentle agitation. The next day, the resin was collected by filtration through a 0.22 \(\mu\)m spin column, washed with 20 resin volumes of buffer A containing 0.04% (\(w/v\)) \(\beta\)-DDM, and bound protein was eluted in the same buffer supplemented with 10 mM maltose. Eluted protein was directly analyzed by absorbance spectroscopy in a UV-Vis cuvette (Sarstedt Inc.) using a Cary 60 UV-Vis spectrophotometer (Agilent Technologies). For redox difference spectra, the protein was oxidized by incubation with a few grains of potassium ferricanide and then reduced by addition of a small quantity of sodium dithionite. Spectra were measured following 1 min of incubation with each reagent.  
Point mutants in the maize _Z-ISO_ gene were generated with the Quikchange II Site-Directed Mutagenesis Kit (Agilent Technologies) using pAH545 as template and the primer pairs detailed in Table S2. The variant proteins were purified in the same way as WT maize Z-ISO.
## 3 Results
### Oxidation Behaviour  
Figure 2 plots the mass gain data obtained at 1000 \({}^{\circ}\)C and overall appearance of the specimens after the tests. The single-phase B2-ordered HfCo alloy showed a continuous mass gain, achieving 74.2 mg/cm\({}^{2}\) after 100 h (Figure 2a). The mass gain of the dual-phase bcc+B2 (HfCo)\({}_{90}\)(NbMo)\({}_{10}\) alloy with \(f_{\rm bcc}\) = 13% was close to that of the HfCo alloy until 15 h, followed by a nearly constant value of \(\sim\)30 mg/cm\({}^{2}\). Some variations in mass gain at this stage could be an indication of the oxide scale spallation. In the dual-phase bcc+B2 (HfCo)\({}_{75}\)(NbMo)\({}_{25}\) alloy with \(f_{\rm bcc}\) = 28%, the spallation commenced already after 1 h, judging from the mass gain vs. time dependence. Only these three alloys survived  
after 100 h, and only the HfCo alloy retained a pristine form (Figure 2b). The specimen of the (HfCo)\({}_{90}\)(NbMo)\({}_{10}\) alloy was partially spalled off, yet it saved its geometry and some regions with an intact oxide scale. The (HfCo)\({}_{75}\)(NbMo)\({}_{25}\) alloy experienced a more serious oxidation resulting in loss of integrity along the edge surfaces and some bending of the oxidized remnants (Figure 2b).  
The other three alloys, namely, dual-phase bcc+B2 (HfCo)\({}_{40}\)(NbMo)\({}_{60}\) (\(f_{bcc}=51\%\)) and (HfCo)\({}_{25}\)(NbMo)\({}_{75}\) (\(f_{bcc}=76\%\)) and single-phase bcc NbMo, demonstrated either rapid mass gain or mass loss (Figure 2a). Visual inspection revealed complete disintegration of the specimens of the (HfCo)\({}_{40}\)(NbMo)\({}_{60}\) and (HfCo)\({}_{25}\)(NbMo)\({}_{75}\) alloys after 5 h, while the NbMo alloy oxidized already after 1 h (Figure 2b).  
For the HfCo and (HfCo)\({}_{90}\)(NbMo)\({}_{10}\) alloys, we evaluated the oxidation kinetics according to a well-known equation [46]:  
\[\Delta\mathrm{m}=\mathrm{k}\mathrm{r}^{n}, \tag{1}\]  
where \(\Delta\mathrm{m}\)--the mass gain per unit surface area (mg/cm\({}^{2}\)); k--the oxidation rate constant (mg/cm\({}^{2}\) h); t--time (h); and n--the time exponent. The entire curve of the HfCo alloy can be fitted using n = 0.58 and k = 5.23 mg/cm\({}^{2}\) h\({}^{0.58}\), indicating near-parabolic oxidation kinetics. In a part of the curve (0-15 h) prior to the spallation, the (HfCo)\({}_{90}\)(NbMo)\({}_{10}\) alloy also displayed a near-parabolic regime with n = 0.46 and k = 7.75 mg/cm\({}^{2}\) h\({}^{0.46}\).
## 3 Experimental Results, Analysis and Discussion
### Detection of Failing Joint
When joints are failing in structure-B, spectrum modes are shifted to lower frequencies than those corresponding to structure-B with normally fastened joints. This observation illustrates the variable behavior in dynamics of structures with respect to those of single continuous bodies, and the relevant comment at the beginning of Section 2.3. Note that the same remark on the confidence intervals (at 95% confidence level) of the spectra presented in Figure 4 may be formulated for tests carried out with structure-B. There are quite small differences of up to \(\pm\)1.3 dB for magnitudes generally peaking between \(-\)75 and \(-\)85 dB. Thus, one may reasonably use the power spectrum curves presented in Figure 4 for estimating damping factor values by means of the second order approximation. Hence, detecting a structure with failing joints is a task which is possible to perform by carrying out several tests at NJ-A or NJ-B configurations for delimiting frequency ranges of specific main modes, and looking for shifted mode frequencies during the structure's inspection. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Test Case—Run \#**} & \multicolumn{3}{c}{**Mode—I**} & \multicolumn{3}{c}{**Mode—II**} \\ \cline{2-6}  & \(\xi\) & \(\omega n\) **(Hz)** & \(\omega n\)/\(\xi\) & \(\xi\) & \(\omega n\) **(Hz)** & \(\omega n\)/\(\xi\) \\ \hline NJ-B \#1 & 6.754 \(\times\)\(10^{-5}\) & 1211 & n/a & 2.936 \(\times\)\(10^{-6}\) & 1584 & n/a \\ NJ-B \#2 & 1.443 \(\times\)\(10^{-4}\) & 1205 & n/a & 2.741 \(\times\)\(10^{-5}\) & 1577 & n/a \\ NJ-B \#3 & 2.249 \(\times\)\(10^{-4}\) & 1201 & n/a & 1.764 \(\times\)\(10^{-5}\) & 1569 & n/a \\ F1-B \#1 & 1.898 \(\times\)\(10^{-5}\) & 1197.5 & 63,092,729.18 & 3.017 \(\times\)\(10^{-5}\) & 1566.5 & 51,922,439.51 \\ F1-B \#2 & 3.510 \(\times\)\(10^{-6}\) & 1195.1 & 340,484,330.48 & \(9\times\)\(10^{-6}\) & 1563 & 173,666,666.67 \\ F1-B \#3 & 1.263 \(\times\)\(10^{-4}\) & 1195 & 9,461,599.37 & 1.217 \(\times\)\(10^{-5}\) & 1561.5 & 128,307,313.06 \\ F2-B \#1 & 1.920 \(\times\)\(10^{-4}\) & 1193 & 6,213,541.67 & 6.636 \(\times\)\(10^{-5}\) & 1558 & 23,477,998.79 \\ F2-B \#2 & 1.782 \(\times\)\(10^{-4}\) & 1191 & 6,683,501.68 & 6.54 \(\times\)\(10^{-5}\) & 1558 & 23,822,629.97 \\ F3-B \#3 & 1.822 \(\times\)\(10^{-4}\) & 1191 & 6,536,772.78 & 3.418 \(\times\)\(10^{-5}\) & 1558 & 45,582,211.82 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Testing scenarios (at 80 Hz–600 mVpp) for detecting and identifying failing joints in structure-B. Figure 4: Spectra of output signals from test runs with structure-B (see Section 2.2) with the exciter driven: (**a**) By triangular waveform at 80 Hz-600 mVpp and (**b**) By triangular waveform at 80 Hz-800 mVpp. Insets present spectra of NJ-B (in blue) versus FJ1-B (in red) or FJ2-B (in green) showing clear frequency shifts for the two largest modes due to failing joints. Dashed lines indicate confidence intervals at 95% level.
## 3 Results and Discussions
### CD and Luminescence Spectra Analysis  
Circular dichroism (CD) spectroscopy is a powerful tool for characterizing the secondary structural changes in proteins, including enzymes. In this study, CD analysis was employed to examine the secondary structure composition of the WT enzyme and its mutants. The results revealed that the WT enzyme contained 29.95% \(\alpha\)-helix, 19.06% \(\beta\)-sheet, and 43.92% random coil (Figure 7a). In contrast, \(Mut2\) exhibited a slightly higher proportion of \(\alpha\)-helix (31.4%) and \(\beta\)-sheet (19.96%), with 48.64% random coil. These findings indicate that the introduction of artificial disulfide bonds in the mutants led to an increase in the content of \(\alpha\)-helix and \(\beta\)-sheet compared to the WT enzyme. This structural change suggests enhanced stability due to the additional disulfide cross-linking, which may contribute to the improved thermostability of the mutants. Similar observations have been reported in studies on 1,4-\(\alpha\)-glucan branching enzyme (GBE), where the introduction of disulfide bonds also resulted in increased secondary structural content and stability [29].  
Figure 6: Hydrogen bonds and non-bond interactions of WT and \(Mut2\). (**a**) Hydrogen bonds between WT and substrate. (**b**) Hydrogen bonds between \(Mut2\) and substrate. (**c**) Non-bond interactions between WT and substrate. (**d**) Non-bond interactions between \(Mut2\) and substrate. Red: hydrogen bonds. Orange: \(\pi\)-sulfur interactions. Green: conventional interactions. Pink: \(\pi\)-alkyl interactions.  
Numerous studies have confirmed that mutations in certain amino acids within luciferase can affect the luminescence spectrum, leading to \"red shift\" and \"violet shift\" phenomena. To investigate the impact of mutations, we used a spectrophotometer to scan the WT luciferase and determine if the mutations affected the luminescence spectrum. The luminescence spectra of _Mut2_ luciferase are shown in Figure 7b. The bioluminescence spectra of WT and _Mut2_ were very similar, with a maximum peak at a wavelength of 350 nm. This indicates that the artificial disulfide bonds had no effect on the emission spectrum of luciferase.