esa-sceva/satcom-chunk-collection huggingface dataset:
# High-Speed, High-Performance DQPSK Optical Links with Reduced Complexity VDEE Equalizers
## 4 Optical Layer Simulation
The complexities of balanced and two-input equalization are comparable and the performance of the balanced scheme surpasses the one offered by the two-input partially-joint single-ended configuration for every type of equalizer (SVDFE, VDFE) and for all sets of [\(M_{p}\)\(M_{b}\)]. However, the superiority of balanced equalization becomes more evident as the values of \(M_{f}\) and \(M_{b}\) increase. It should be highlighted that the balanced VDFE[9; 5] (i.e., B-VDFE[9; 5]) is able to alleviate up to 630 ps/nm of residual dispersion and, thus, almost doubles the dispersion tolerance of the optical system, compared to the case where the compensation is performed only with optical means, whereas the equivalent two-input partially-joint equalizer (2I-VDFE[9; 5]-IdQd) that carries the same complexity can reach dispersion tolerance values up to \(\sim\)500 ps/nm. The performances of four-input and three-input equalizers exceed, by far, those offered by the two-input partially-joint and balanced equalizers and are presented here only for completeness. Disregarding inputs from the equalization process proved to be exceptionally efficient when compared against the performance of four-input joint single-ended equalizers on one hand, and low complexity balanced receiver equalizers on the other. The first case exhibits high performance, high complexity, and questionable numerical accuracy. High complexity is dictated by the number of filters that are used. Furthermore numerical accuracy is compromised by the linear dependency of the optical inputs that leads to high condition numbers in the equalization process. The balanced case exhibits  
Figure 10: Estimated BER of optical links that utilize (**a**) SVDFE[5; 3]; (**b**) VDFE[5; 3]; (**c**) SVDFE[9; 5] and (**d**) VDFE[9; 5] for 2I-, 3I, and balanced equalization. low performance, but very low complexity and cost. In this paper, starting from the requirements for low-complexity, high-performance equalizers, the effect of reducing the number of single-ended ports in the equalization process is investigated with exceptional results. Due to the nature of DQPSK, when one of the destructive ports is not utilized in the equalization process, even low-complexity VDFE equalizers manage to compensate for residual dispersion. However, it has been proved that when it comes to ignoring more than one input at the same time (i.e., both destructive input ports) the performance of the balanced equivalent is superior, especially as the filter memory of the FF and FB part increase. When deployed in multi-span systems, three-input partially-joint SVDFE equalizers can stretch 40 Gb/s DQPSK transmission systems beyond 800 km with very good performance and 25% lower complexity than four input joint equalization counterparts.
## 5 Classification Experiments
### Semi-Supervised Strategy for Automatic Labelling
#### 5.3.2 Results for Nine-Class Taxonomy  
Table 8 shows the recall results of each of the iterations for each of the datasets. We calculated the metrics as described in Section 5.3.1.  
For the ConvBlock system, an improvement was observed up to iter4 for the UD part and up to iter 3 for the SDv&UD part. In the case of the ResNet, an improvement was observed up to iter3 for the UD part and up to iter2 for the SDv&UD part.  
The improvement rate is different for both system. For the ConvBlock system, the UD part improves 6.2 points and the SDv&UD improves 1.8 points. While, for the ResNet the UD part improves 4.1 and the SDv&UD part improves nearly 1 point. The SDv part only improves in the first iteration and then loses recall. The improvement in the UD part compensates the loss of accuracy of the SDv part on the SDv&UD result.  
Figure 9 shows the evolution of the recall results for the different categories during the different iterations for both architectures. We present the results for the SDv&UD dataset. In both cases it can be seen that the good performing classes tend to improve with the through the iteration whereas the worse performing class \"Impact\" degrades. The classes with intermediate recalls vary in an unpredictable way.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & \multicolumn{3}{c}{**ConvBlock**} & \multicolumn{3}{c}{**ResNet**} \\ \hline
**Iterations** & **UD (m \(\pm\)\(\sigma\))** & **SDv (m \(\pm\)\(\sigma\))** & **SDv\&UD (m \(\pm\)\(\sigma\))** & **SDv (m \(\pm\)\(\sigma\))** & **SDv\&UD (m \(\pm\)\(\sigma\))** \\ \hline iter0 & \(56.5\pm 4.2\
## 8 Conclusions  
This study has presented the findings on the development of ANN models to predict transition and ultimate zones of FRP-confined concrete based on readily available parameters. Sensitivity analysis and model validation were used to verify the influence of the input parameters on the proposed models. It was shown that the accuracy of the ANN models for predicting ultimate condition was higher compared to that of the best performing existing models developed by different approaches. In addition, the ANN models proposed in this study offered a higher or similar accuracy compared to existing ANN models to predict the ultimate condition while a larger number of datasets was used in this study. Moreover, the developed ANN models used to predict the transition zone had significantly higher accuracy compared to best performing existing models. These observations indicate that the proposed ANN models captured the impact of the lateral confinement by FRP on the ultimate and transition zones of the confined concretes with a more robust performance compared to the existing models.  
Conceptualization, A.F.P. and A.G.; methodology, A.F.P. and A.G.; software, A.F.P.; validation, A.F.P. and A.G.; formal analysis, A.F.P. and A.G.; writing--original draft preparation, A.F.P.; writing--review and editing, A.G. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The data presented in this study are available on request from the corresponding author.  
The authors declare no conflict of interest.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Model** & **Test Data** & **AAE (\%)** & **M (\%)** & **SD (\%)** & **RMSE (\%)** \\ \hline [PERSON] et al. [4] & 228 & 14.7 & 98 & 18.6 & 0.08 \\ [PERSON] at al. [6] & 228 & 15 & 101 & 18.8 & 0.08 \\ [PERSON] [7] & 228 & 15.6 & 103 & 19.3 & 0.08 \\ [PERSON] et al. [8] & 228 & 22.7 & 118 & 22.4 & 0.1 \\ \hline Proposed model & 228 & 8.8 & 100.2 & 10.9 & 0.05 \\ \hline \hline \end{tabular}
\end{table}
Table 15: Prediction statistics of the best performing \(\varepsilon_{\text{cl}}\) models.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Model** & **Test Data** & **AAE (\%)** & **M (\%)** & **SD (\%)** & **RMSE (MPa)** \\ \hline [PERSON] et al. [4] & 256 & 8.5 & 98.0 & 9.8 & 8.5 \\ [PERSON] at al. [6] & 256 & 8.5 & 97.5 & 11.6 & 10.2 \\ [PERSON] and [PERSON] [10] & 256 & 8.8 & 95.1 & 10.1 & 9.0 \\ [PERSON] et al. [8] & 256 & 9.2 & 96.7 & 12.8 & 11.5 \\ [PERSON] [7] & 256 & 9.8 & 103 & 13.1 & 10.5 \\ \hline Proposed model & 256 & 3.1 & 100.3 & 5.3 & 2.4 \\ \hline \hline \end{tabular}
\end{table}
Table 14: Prediction statistics of the best performing \(\varepsilon_{\text{cl}}\) models.
# Quasi-Isotropic Hybrid Dielectric Resonator Antenna--Bow-Tie Patch with Harmonic Suppression
## 1 Introduction
However, since the harmonic suppression function is implemented for an antenna with a unidirectional or omnidirectional pattern, research on an antenna with a quasi-isotropic pattern and a harmonic suppression function is required. In this paper, a quasi-isotropic hybrid DRA and bow-tie patch with harmonic suppression is proposed. DRA and bow-tie patch antennas were used to implement the quasi-isotropic pattern. The seventh-order Chebyshev low-pass filter was designed in the feed line of the proposed antenna to remove harmonics. This paper is organized as follows: Section 2 first explains the principle of implementing the quasi-isotropic pattern, the configuration of the proposed antenna, and the antenna design parameters. Second, the filter design method and changes in filter characteristics for the filter order are described. Finally, when the filter and the antenna are integrated, a study was conducted on how much the filter affects the realization of a quasi-isotropic pattern. CST of a microwave studio was utilized to design the proposed antenna and analyze the radiation pattern and distribution of the electric field. Section 3 shows the comparison between the measured and simulated results after the proposed antenna is fabricated. The conclusion is presented in Section 4. Design of Proposed Quasi-Isotropic Hybrid Dielectric Resonator Antenna-Bow-Tie Patch with Harmonics Suppression
## 2 Materials and Methods
### Methodology
#### 2.2.2 Phase 2: Data Retrieval  
Python Version 3.0 [63] is used to extract the data from IMERG. The satellite files downloaded contain a huge matrix of data for the globe. To extract the data of this study area we want, the boundary coordinate of the country or this study area has to be calculated based on the coverage that the satellite captured and its spatial resolution. As the spatial resolution of IMERG is 0.1 degree and has a spatial coverage of [\(-\)180, 180] for longitude and [\(-\)90, 90] for latitude, the IMERG grid calculation for an area can be derived as follows:  
\[Longitude:(X)Grid=(X+179.95)/0.1 \tag{1}\]  
\[Latitude:(Y)Grid=(Y+89.95)/0.1 \tag{2}\]  
Initially, the whole Peninsular Malaysia boundaries are marked as rectangle size and defined with the longitude of 99.35 (\(X1\)) to 104.95 (\(X2\)) and the latitude of 1.05 (\(Y1\)) to 7.05 (\(Y2\)). With Equations (1) and (2), the IMERG grids are derived in matrix format as \"\(X1\) grid\": \"\(X2\) grid\"; \"\(Y1\) grid\": \"\(Y2\) grid\". Later, a Python program that makes use of h5 py library was prepared to extract all IMERG grids that match the matrix for the whole of Peninsular Malaysia from the HDF5 data files. Due to the huge amount of data to be extracted, an EXE program was compiled from Python and a batch job was created to run continuously on the server. Hourly rain gauge observation records were obtained (in CSV format) from ground gauging stations from the DID.
## 3 Signal Model  
This section first introduces the downlink physical channels of 5G NR, emphasizing the signal components that can be used in opportunity navigation. Subsequently, the OFDM modulation with CP is elaborated. The power spectral density (PSD) of the NR reference signal is derived, serving as the foundation for tracking performance analysis.
## 3 Simulation Results  
The effectiveness of KLQVI-CFAR is demonstrated through experimental validation, where its detection performance is evaluated using a Monte-Carlo experiment. The amplitudes of the background clutter signals \(I\) and \(Q\) follow a Rayleigh distribution, the power of the signal passing through the square law detector follows an exponential distribution, and the CUT under \(H_{0}\) has a probability density function:  
\[f(x|H_{0})=\frac{1}{\mu}\exp\left(-\frac{x}{\mu}\right) \tag{11}\]  
where \(H_{0}\) indicates \(X_{0}<S\), and \(\mu\) is the scale parameter.  
The CUT and the interferences in the reference cells follow the Swerling II model, and the CUT or interferences under \(H_{1}\) has a probability density function:  
\[f(x|H_{1})=\frac{1}{\mu(1+SNR)}\exp\left(-\frac{x}{\mu(1+SNR)}\right) \tag{12}\]  
where \(H_{1}\) indicates \(X_{0}>S\).  
The scale parameter is set as \(\mu=1\), the number of reference cells is set as \(N=32\), and the thresholds are set as \(K_{VI}=4.76\) and \(K_{MR}=1.806\) according to Ref. [12].  
Choose CA-CFAR [24], OS-CFAR [10], KLQ-CFAR [11], VIHCEMOS-CFAR [15], and IBQ-CFAR [25] as comparative methods for performance analysis. Unless stated otherwise, the SNR is varied from 0 dB to 35 dB in steps of 1 dB, for each CFAR detector, set \(P_{FA}=10^{-6}\), and \(10^{4}\) Monte-Carlo experiments are performed to evaluate performance.
## 4 Results
### Influence of joints in Rock Strata on the Stability of Interbedded Anti-Dip Rock Slopes
#### 4.1.2 Slope Stability without the Presence of Joints  
To reveal the effect of the joints on the stability of the anti-dip interbedded rock slope, one simulated model without joints was established to compare the differences in slope failure between them (Figure 2b). Compared with the rock slope with joints in Section 4.1.1, the main differences between the anti-dip interbedded rock slope with and without joints lie in the micro-crack distribution near the pre-existing joints and the velocity of the slope instability.  
From Figure 7, the cracks initially occurred at the slope toe of the step and subsequently propagated, expanded, and coalesced upwards towards the top of the slope. The number of cracks was smaller than the rock slope with joints. The cracks almost developed parallel to the slope surface, resulting in a sliding surface. The comparison of the failure modes showed that the pre-existing joints did not significantly affect the cracking patterns of the interbedded anti-dip rock slopes, and the cracks developed at similar positions but at a later time. In other words, the existence of joints induced the generation of cracks on the sliding surface, increased the crack density, and accelerated the process of slope failure.  
The stress distributions observed from the contact force chain evolution in the two kinds of rock slopes (i.e., with and without pre-existing joints) were also similar (Figures 5 and 8). However, it is worth noting that the number of contacts in the rock slope without joints was slightly higher than that in the slope with joints, which indicated that large strength and high stability occurred in the rock slope without pre-existing joints.  
Figure 7: Crack progression for a slope without joints. (**a**) Time step = 100, (**b**) Time step = 200, (**c**) time step = 1000, (**d**) Time step = 5000, (**e**) Time step = 10,000, (**f**) Time step = 30,000.  
Figure 9 shows a comparison of horizontal stresses at identical locations of the measuring circles. Measuring circles A-D and E-H are from the slope with and without joints, respectively. The horizontal stress from the slope without joints was slightly higher at the beginning of the slide, and the stress difference between the two kinds of slopes was overall small. The stresses all gradually decreased to zero as the landslide progressed. There were two reasons for the similar changes in stress: (1) The influence range of the initial joints was limited in this large slope model, and the location of the measuring circles was different from the location of the initial joints. Therefore, pre-existing joints have a small effect on the rock mass in the location of the measuring circles. (2) The measuring circles were near the sliding surface, and numerous cracks were distributed on the sliding surface. When the cracks coalesced, the stresses were nearly zero.
## 3 Results and Discussion
This would explain the friction increase at higher levels of water content. Other researchers have also shown some evidence that in the case of glycerol lubrication, water has been produced inside the high pressure contact thus contributing to the low friction [52]. Whether a similar reaction is taking place for the IL studied in this work has not been investigated. While for both glycerol and the IL studied in this work, the hygroscopic properties and the water content may help to reduce friction, it also makes the lubricants more challenging to use since the water content will influence both film forming capacity and friction properties. \begin{table}
\begin{tabular}{c c c c c c} \hline
**P [GPa]** & **U\({}_{e}\) [m/s]** & **H\({}_{c}\) Paraffin [nm]** & **H\({}_{c}\) IL [nm]** & **H\({}_{min}\) Paraffin [nm]** & **H\({}_{min}\) IL [nm]** \\ \hline
1.95 & 1 & 242 & 271 & 136 & 158 \\
1.95 & 3.14 & 520 & 584 & 297 & 344 \\
1.25 & 1 & 264 & 297 & 150 & 174 \\
1.25 & 3.14 & 568 & 638 & 327 & 379 \\ \hline \end{tabular}
\end{table} 
Table 6: Hamrock & Dowson central and minimum film thickness for friction tests. Figure 8: Friction measurements for Paraffin and [Choline] [Proline] at 40 \({}^{\circ}\)C and 1.95 GPa. [Choline] [Proline] had a water content of slightly below 15 wt %.
## 5 Results
### Hjorth Features  
The results of the Hjorth method indicate 11,418 total features. Subject No. 1 showed good performance across classifiers, with LinearSVM reaching 83.11% accuracy, and CART and GSVM lagging behind. Subject No. 2 performed moderately well with LinearSVM, reaching 68.88%, but GSVM, CART, and SVM with a polynomial kernel showed a lower mark, around 50% or less for each. Subject No. 3 had strong scores, particularly LinearSVM (88.14%), although GSVM performed poorly (52.96%). For Subject No. 7 with LinearSVM, 90.02% was reached. Subject No. 6 showed the lowest overall performance, with LinearSVM at 48.81%, and other classifiers performed poorly, the same as the latter. Subject No. 9 performs well when using LinearSVM, reaching 84.76%; however, GSVM performed worse (53.18%).  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Classifier** & **LinearSVM** & **CART** & **GSVM** & **SVM (Kernel = “Poly”)** \\ \hline Subject No. 1 & 82.03 & 63.79 & 83.15 & 74.35 \\ Subject No. 2 & 68.51 & 44.07 & 66.66 & 59.25 \\ Subject No. 3 & 88.88 & 74.44 & 80.74 & 72.59 \\ Subject No. 4 & 64.07 & 34.73 & 55.65 & 44.97 \\ Subject No. 5 & 80.54 & 57.27 & 71.37 & 57.27 \\ Subject No. 6 & 46.51 & 33.78 & 43.76 & 35.60 \\ Subject No. 7 & 89.66 & 83.44 & 83.40 & 68.25 \\ Subject No. 8 & 89.36 & 62.48 & 84.44 & 79.90 \\ Subject No. 9 & 85.21 & 76.74 & 85.18 & 78.48 \\ \hline Avg. Success Rate & 77.20 & 58.97 & 72.71 & 63.41 \\ \hline \hline \end{tabular}
\end{table}
Table 4: The results of higher-order spectra features.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Classifier** & **LinearSVM** & **CART** & **GSVM** & **SVM (Kernel = “Poly”)** \\ \hline Subject No. 1 & 83.48 & 65.60 & 83.13 & 80.18 \\ Subject No. 2 & 68.51 & 45.55 & 63.70 & 60.37 \\ Subject No. 3 & 89.62 & 72.96 & 85.55 & 84.81 \\ Subject No. 4 & 62.17 & 35.89 & 64.42 & 60.61 \\ Subject No. 5 & 77.48 & 59.57 & 73.28 & 73.30 \\ Subject No. 6 & 50.16 & 31.93 & 47.89 & 41.97 \\ Subject No. 7 & 90.03 & 81.21 & 88.56 & 80.45 \\ Subject No. 8 & 88.59 & 60.64 & 85.92 & 84.05 \\ Subject No. 9 & 85.16 & 77.18 & 84.77 & 77.20 \\ \hline \hline Avg. Success Rate & 77.25 & 58.95 & 75.25 & 71.44 \\ \hline \hline \end{tabular}
\end{table}
Table 3: The results of wavelet analysis features.  
The lowest average success classifier score was SVM with a polynomial kernel (52.26%). GSVM and CART were slightly better (55.90% and 59.00%, respectively), yet LinearSVM still dominated and had the highest score (77.19%). The results of applying Hjorth methods for feature extraction are presented in Table 5.
# Video Super Resolution Using a Selective Edge Aggregation Network
## 3 Method
### Feature Extraction  
To extract target frame feature \(I_{t}\), \(LR_{t}\) is passed through a convolution layer. Then, \(LR_{t}\),\(F_{t-k}\),\(E_{t-k}\), and \(LR_{t-k}\) are concatenated with nine channel-sized features. To provide our model with multi-scale information, the concatenated map is passed through a convolution layer that yields \(M_{t-k}\). So \(M_{t-k}\) that has spatio-temporal and structure information can fill in the insufficient feature of \(I_{t}\).
# DeepGOMIMO: Deep Learning-Aided Generalized Optical MIMO with CSI-Free Detection
## 5 Conclusions  
In this paper, we have for the first time proposed a novel DeepGOMIMO framework for GOMIMO systems, where a DNN-based detector is specially designed to realize CSI-free detection of the received MIMO signals. The proposed CSI-free DNN detector contains a preprocessing module and a feedforward DNN module, which are used to address the adverse effects of MIMO transmission and to perform joint detection of spatial and constellation information, respectively. It is shown by our simulation results that, in a typical indoor 4 \(\times\) 4 MIMO-OWC system adopting both GOSM and GOSMP with unipolar nonzero 4-PAM modulation, the CSI-free DNN detector achieves comparable BER performance as the optimal joint ML detector, which greatly outperforms the ZF-ML detector. Moreover, the CSI-free DNN detector, the ZF-DNN detector and the ZF-ML detector require nearly the same computation time to perform detection, which is significantly shorter than that required by the joint ML detector. In addition, compared with the ZF-DNN detector, the CSI-free DNN detector can achieve an improved achievable data rate and reduced communication time delay because it does not require instantaneous channel estimation to obtain accurate CSI for ZF equalization. In conclusion, our proposed DeepGOMIMO can be a potential candidate for the implementation of practical high-speed and low-complexity OWC systems.  
Figure 8: Computation time comparison of the proposed CSI-free DNN detector and three benchmark detectors for (**a**) GOSM and (**b**) GOSMP at the center of the receiving plane.  
**Author Contributions:** Formal analysis, C.C., Z.Z. and M.L.; funding acquisition, C.C.; investigation, X.Z. and S.F.; methodology, S.F.; project administration, C.C.; resources, Z.Z.; software, S.F.; supervision, C.C. and M.L.; validation, X.Z.; writing--original draft, X.Z.; writing--review & editing, C.C., S.F., Z.Z. and M.L. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research was funded by the National Natural Science Foundation of China (62271091 and 61901065) and the Natural Science Foundation of Chongqing (cstc2021 jcyj-msxmX0480).  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** Not applicable.  
**Acknowledgments:** The authors would like to thank the anonymous reviewers for their valuable comments and suggestions.  
**Conflicts of Interest:** The authors declare no conflict of interest.
# In Situ Interaction of Enterocin A/P with _Staphylococcus aureus_ SA5 in Goat Milk Lump Cheese
## 2 Materials and Methods
### Standard Microbial Analysis  
Before the experiment, raw goat milk was analyzed for staphylococci using the Baird-Parker agar (BP, ISO 6888-1) with supplement and yolk tellurite (Oxoid, Ltd., Basingstoke, UK) as well as on the plate count agar (pH 7.0 Biomark Laboratories, Pune, India). Bacteria counted were under detection limit. Before the cheese experiment, in vitro inhibitory activity of Ent A/P was checked using the diffusion agar spot test [13; 14] against the SA5 strain and activity was expressed in AU/mL (1600 AU/mL). The principal indicator strain _E. avium_ EA5 (our strain) was the positive control (inhibitory activity 12,800 AU/mL). However, Ent A/P also inhibited a different staphylococcal species from Slovak local ewe milk lump cheeses with inhibitory activity up to 12,800 AU/mL [11]. Then the cheese samples (10 g) were homogenized in 90 mL of sterile peptone water (Merck, Germany)and treated in a Stomacher-Masticator PK400, IUL (Spain). Decimal dilutions (in Ringer solution, pH 7.0) were prepared according to the standard microbiological method (ISO, International Organization for Standardization). Appropriate dilutions were spread on the BP agar (Oxoid) and cultivated at 30 \({}^{\circ}\)C for 48 h. Two independent replicates were performed (each cheese was checked in duplicate) and the experiment was reproduced once. Bacterial counts were expressed as the average amount of colony forming units per gram of cheese (cfu/g \(\pm\) SD). The SA5 strain was also confirmed using PCR with the following primers: Sau1-F, 5\({}^{\prime}\)-TCT TCA GAA GAT GCG GAA TA-3\({}^{\prime}\) and Sau2-R, 5-TAA GTC AAA CGT TAA CAT ACG-3\({}^{\prime}\) with 30 cycles at 58 \({}^{\circ}\)C, 30 cycles at 72 \({}^{\circ}\)C, finally 5 min at 72 \({}^{\circ}\)C according to [PERSON] et al. [15]. The positive control was strain ATCC25923. PCR product was visualized using 1.5% (_v/w_) agarose gel (420 bp).