esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Discussion
### Pople Notation in the Strong Heteronuclear J-Coupling Regime  
In addition to distinct quantitative data, each compound also had a unique JCS signature in both \({}^{1}\)H and \({}^{19}\)F regions caused by strong heteronuclear \(J\)-coupling. Due to differences in the \(J\)-couplings for each molecule, each spectrum was a unique spectral fingerprint or signature. While it is tedious to describe every spectrum on the basis of the observed \(J\)-couplings, it is illustrative to describe several of the spectra and the spectral features associated with the phenomena that occur at LF [21; 25; 27; 32]. Each spin system can be described in a reduced form using Pople notation [60; 61]. In Pople notation, nuclei that are chemically inequivalent are denoted by a letter (A, M, X... etc.) and nuclei that are weakly coupled, such as heteronuclei at high field, are denoted by letters far from each other such as AX for an H-F spin system. Nuclei that are strongly coupled are denoted by adjacent letters, such as AB for two strongly coupled protons. Finally, nuclei that are chemically equivalent, but magnetically inequivalent, are given a prime notation (\({}^{\prime}\)). For example, monofluorobenzene at high field would be described in Pople notation as an AA'BB'CX system, where the protons in the 2,6 and 3,5 positions are chemically equivalent, but magnetically inequivalent. Here, all three sets of protons are strongly coupled to each other due to minute chemical shift differences. The spectrum of each NMR active nucleus then consists of several subspectra, which stem from both the strong and weak \(J\)-couplings for each chemically inequivalent environment. For example, consider the \({}^{1}\)H JCS of 1,4-difluorobenzene (Figures 1a and 3d). The spectrum consists of three unique subspectra at 2189 Hz, 2196 Hz, and 2202 Hz. The Pople notation for each system will change at LF since the A and X nuclei are strongly coupled. Therefore, monofluorobenzene at LF has a Pople notation of AA'BB'CD. Both the high field and LF Pople notations are given for each fluorobenzene molecule in Figure 8. At LF, monofluorobenzene and pentafluorobenzene have equivalent Pople notations, as does 1,4-difluorobenzene and 1,2,4,5-tetrafluorobenzene. Therefore, it is expected that these compounds will have similar subspectra, albeit with the subspectra centered at the opposite Larmor frequency. For example, the \({}^{1}\)H region of monofluorobenzene and the \({}^{19}\)F spectrum of pentafluorobenzene consists of two subspectra separated by \(\approx\)5 Hz (Figures 3 and 4). For 1,4-difluorobenzene, the \({}^{1}\)H region has three unique subspectra, while the \({}^{19}\)F region has five distinct subspectra. This is equivalent to the number of subspectra in the \({}^{19}\)F and \({}^{1}\)H regions of 1,2,4,5-tetrafluorobenzene, respectively (Figures 3 and 4). Of course, just as the heteronuclear and homonuclear \(J\)-couplings are different between the molecules with the same Pople notation, the absolute spacing and peak intensities of the subspectra are unique for each molecule.
# Epileptic Seizure Detection in Neonatal EEG Using a Multi-Band Graph Neural Network Model
## 3 Methods
### Graph Generation
#### 3.2.3 Graph Node Generation  
To complete the graph node representation of the EEG epochs, a set of features was extracted from each channel-wise time series. A total of 9 statistical features were combined as the node representation based on the following considerations. Firstly, the aim should be concentrated on characterizing the morphology of the time series since the raw EEG has been decomposed into narrowband signals. Secondly, it is necessary to exclude complex features so that the computation latency can be reduced for the real-time monitoring. Thirdly, the feature dimension should be restricted to mitigate the effect of the overfitting problem. Consequently, the node feature set includes the following features: the mean, the median, the standard deviation, the skewness, the kurtosis, the sum over the absolute value of consecutive changes, the complexity-invariant distance [28], the length of the longest consecutive subsequence above the mean, and the length of the longest consecutive subsequence below the mean.
## Data and Software
### Software  
LRSC algorithm was used in order to examine its classification performance for infrared spectral data and LIBS data, and it was compared to the performances of other classification algorithms such as PLSDA, SIMCA, ANN, RF, and SVM. The sparse solution was implemented using L1-Homotopy package [24]; SVM used libSVM 3.20 toolbox [25]; PLSDA and SIMCA were implemented with Classification_toolbox_4.2 [26]; ANN was implemented using MATLAB's RBF neural network; and RF was implemented with the RF_MexStandalone-v0.02 toolbox [27]. All code used in the experiment was written on MATLAB 2012a.
## 1 Introduction
[24] carried out an experimental model of the horizontal cyclic load on the pile group in sandy soils, investigating the effects on the pile body's horizontal displacement, bearing angle, and bending moment. [PERSON] et al. [25] proposed a pile group design method considering the cyclic effects based on the model experiment of the \(1\times 5\) pile group model under the action of a bidirectional cyclic load. Subsequently, [PERSON] et al. [26] conducted a series of model experiments to study the horizontal cyclic characteristics of the pile group in soft soil foundations. In recent years, [PERSON] et al. [27] further demonstrated that the pile group effect exacerbates the cyclic effects on piles under horizontal cyclic loads based on pile group model tests in clay soils. Moreover, [PERSON] et al. [28] conducted unidirectional cyclic loading tests on the pile group in soils with varying impurities, revealing the nonlinear effect of impurities on the loading-displacement relationship of pile groups. [PERSON] et al. [29] studied different types of clays and analyzed the load deflection and bending moment curves of the pile group. [PERSON] et al. [30] analyzed the effects of axial load and pile shape on the performance of the pile group under cyclic loading. Overall, the 1 g model test is widely used to investigate the load-bearing deformation characteristics and evolution law of pile groups under horizontal cyclic loads. At present, considerable efforts have been dedicated to investigating the bearing characteristics of pile group foundations under horizontal cyclic loading. In addition, some scholars have delved into the correlation between the cumulative deformation of the pile group foundation and the weakening of soil circulation around the pile, as well as the dynamic response of pore water pressure evolution and soil pressure variation near the pile under horizontal cyclic loading [31; 32]. Nevertheless, existing studies predominantly rely on numerical models, while experimental studies have primarily been limited to a few hundred repetitions, failing to truly capture the long-term behavior of pile group foundations under sustained loading. In this paper, the small-scale model test of the pile group foundation using the self-designed indoor model test cyclic loading system under horizontal cyclic loading was carried out, and the number of cycles was over \(5\times 10^{3}\) when studying the force deformation characteristics of the pile group foundation and the dynamic response of the soil around the pile in saturated clay under horizontal cyclic loading. The self-designed indoor cyclic loading system and the corresponding testing procedure are introduced first. Subsequently, the accumulative deformation of the bearing platform, the horizontal cyclic stiffness, and the bending moment of the pile shaft, as well as the dynamic response of saturated clay under horizontal cyclic loading on the cumulative deformation of the pile group, are fully examined. Finally, the application fields of the research results are pointed out.
# Analysis of 5G and LTE Signals for Opportunistic Navigation and Time Holdover
## 3 Results
### Differential Stability Measurement
#### 3.3.1 Evaluation of Multi-Radio Multi-SDR Observable Stability  
To isolate all the other parameters, two radios were set to observe the same cell simultaneously while connected to the same antenna and driven by the same local Rb oscillator, a configuration that is analogous to a 'zero-baseline' differential measurement in GNSS systems [30]. This configuration would ideally always produce a null output value, but some level of differential thermal noise and other parameters will also be present in real systems. Over multiple one-hour periods of observation, the peak-to-peak variation in the differential measurement was less than 0.02 m. Since this result was more than an order of magnitude smaller than the observations obtained from either individual cellular downlinks that were measured previously, it was considered safe to neglect this factor in subsequent analyses. The results of these tests are placed in Appendix A.
## 6 Conclusions  
The long-term durability of treated soil was investigated on an artificial island at Central Japan International Airport, where the pneumatic flow mixing method was first fully introduced. The results of five investigations conducted immediately after construction and 4, 10, 15, and 20 years after construction were summarised. The results obtained and conclusions are as follows:  
1. No reduction in the unconfined compressive strength or needle penetration gradient was observed in the interiors of treated soil samples, and there was no sign of deterioration.
2. Some degradation was observed on the top and bottom exposed surfaces of the treated soil, similar to that of soil after other treatments. In addition to needle penetration and chemical tests, elemental mapping using an EPMA was performed to determine the degree of degradation. The depth of degradation 20 years after construction was approximately 18-25 mm.
3. Although the amount of cement added in the pneumatic flow mixing method was relatively small, the degradation depth was within the range of the degradation depth over time investigated in previous studies and was not significant.
4. The artificial island at Central Japan International Airport has a 2 m thick soil cover on top of the improved soil, and a reduction in strength of this magnitude would not affect the stability of the ground as a whole. In other words, it was confirmed to be durable at least during the first 20 years of construction.
5. Based on the results to date, it is unlikely that the degree or extent of strength reductions of the treated soil will change abruptly; however, from the perspective of the long-term maintenance of the airport facilities, it is important to continuously investigate the long-term behaviour of the improved ground. Airport facilities demand high performance from the ground, and if there is an accelerated deterioration trend, measures need to be taken.
6. There are only a few examples and reports on the long-term strength and durability of treated soils in the field; therefore, this study provides valuable data. The test results are particularly important for understanding the durability of the pneumatic flow mixing method. This method contributes to sustainability in terms of the effective use of dredged soil and less cement addition, and it would be more sustainable if it has long-term durability.  
Investigation, I.S. and A.O.; project administration, H.T.; validation, Y.M.; writing--original draft preparation, H.T. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Figure 17: Relationship between duration of exposure and depth of degradation (Addendum to [13]).
## 3 Results  
Table 2 shows the outcome of the MANOVA test, which suggests that CAD/CAM material type, surface treatment, and interaction between them significantly influenced the surface roughness (\(p\) < 0.001). Table 3 presents the mean Ra of the surface-treated CAD/CAM ceramics. The highest and lowest Ra were presented by the control VE (0.63 \(\pm\) 0.23 \(\upmu\)m) and the glazed LU specimens (0.04 \(\pm\) 0.01 \(\upmu\)m), respectively. Irrespective of the CAD/CAM material type, the glazed specimens demonstrated the lowest Ra (0.05\(\pm\) 0.01 \(\upmu\)m), while the control specimens had the highest Ra (0.46 \(\pm\) 0.13 \(\upmu\)m). Figure 3 presents the overall mean Ra of the CAD/CAM ceramics irrespective of the surface treatment. Among the CAD/CAM material, LU (0.16 \(\pm\) 0.04 \(\upmu\)m) and CS (0.17 \(\pm\) 0.06 \(\upmu\)m) had the smoothest surface, and the Ra values of these materials were within the threshold limit (0.2 \(\upmu\)m). The Ra of CU and VE were 0.27 \(\pm\) 0.04 \(\upmu\)m and 0.31 \(\pm\) 0.09 \(\upmu\)m, respectively, and these values were above the threshold limit. The [PERSON]'s post hoc test to identify the pairwise significance showed significant differences in Ra among the surface-treated groups within a material (\(p\) < 0.001), except between the MP-treated and control specimens of CS material (\(p\) = 0.188) (Table 4). The SEM micrographs of the control and polished specimens are presented in Figure 4. The micrographs confirm the findings of the Ra values. The glazed OG specimens had the smoothest texture, although some small voids were present on the surface. The specimens in the control group had deep grooves, but with MP, the grooves became shallow. The VE and CS specimens polished with MP demonstrated more surface grooves and flaws than LU and CS. The surface texture of CAD/CAM ceramics polished with MP+PP showed a smooth surface compared to the OG specimens. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Source** & \
\begin{tabular}{c} **Sum of** \\ **Squares** \\ \end{tabular} & **df** &
\begin{tabular}{c} **Mean** \\ **Square** \\ \end{tabular} & **F** & **Sig \({}^{*}\)** \\ \hline CAD/CAM materials & 0.759 & 3 & 0.253 & 31.589 & 0.000 \\ Surface treatment & 5.061 & 3 & 1.687 & 210.516 & 0.000 \\ CAD/CAM materials \(\times\) Surface treatment & 0.397 & 9 & 0.044 & 5.499 & 0.000 \\ \hline \hline \end{tabular} \({}^{*}\) Statistically significant (\(p\) < 0.05).  
\end{table} 
Table 2: MANOVA outcome of the surface roughness. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Surface Treatment** & **LU** & **VE** & **CS** & **CU** & **Total** \\ \hline Control & 0.34 \(\pm\) 0.11 & 0.63 \(\pm\) 0.23 & 0.34 \(\pm\) 0.12 & 0.54 \(\pm\) 0.05 & 0.46 \(\pm\) 0.13 \\ MP & 0.20 \(\pm\) 0.05 & 0.39 \(\pm\) 0.11 & 0.22 \(\pm\) 0.13 & 0.34 \(\pm\) 0.05 & 0.29 \(\pm
# Median Absolute Deviation for BGP Anomaly Detection
## 3 Results
### Comparative Analysis with Deep Learning Techniques  
Following the performance evaluation of our method (which we will refer to as MAD for simplicity) across various anomaly events, it is essential to compare these results with existing anomaly approaches. We will compare our model's results against deep learning models, including the most recent methodology mentioned in our Section 1.1, the MAD-MulW model [8], while it may seem that comparing our statistical approach with more advanced machine learning and deep learning techniques is not entirely fair, we must highlight that our research intention is not to compete directly with these methods. Rather, our objective is to demonstrate how integrating our technique with these models can enhance the overall accuracy of anomaly detection. This approach aims to leverage the strengths of both methodologies to achieve superior results.  
This comparison is particularly pertinent as the MAD-MulW framework evaluates its performance against more deep learning models and for the exact anomaly events that we are evaluating (Table 5). Given this context, we extend our comparison to include three of these deep learning models, including RNN [30] which is a well-known deep learning model, and MTAD [31] and DAGMM [32] which, coupled with MAD-MulW, are some of the latest deep learning models toward anomaly detection. This extended comparison is aimed at showcasing the performance of our statistical approach in terms of accuracy and precision.  
The comparative analysis against deep learning models provides important insights. Our method outperforms the RNN, MTAD, and DAGMM models in both accuracy and precision for all the indirect anomaly events, which highlights the effectiveness of MAD in detecting anomalies more accurately than these deep learning models.  
In the specific scenarios of the Moscow Blackout and TMnet Misconfiguration, the MTAD and DAGMM models demonstrated slightly higher accuracy, exceeding MAD's results by a narrow margin of 1-2%, making it not substantially significant. On the other hand, MAD showcased superior precision scores for these anomaly events, affirming its reliability and effectiveness in identifying true positives with fewer false alarms.  
Finally, for the MAD-MulW comparison, MAD demonstrates a strong and competitive performance, especially considering the Slammer and Nimda Worm events, where it achieved a perfect precision score of 100% and 97%, respectively.
# Atmospheric and Fog Effects on Ultra-Wide Band Radar Operating at Extremely High Frequencies
## 5 Distance Measurement Accuracy and Resolution
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Frequency (GHz)** & \(\frac{\overline{\Delta d}}{d}\) & \(\frac{\Delta d_{\text{min}}-\Delta d_{\text{min}}}{\text{fid}}\) \\ \hline
23 & 0.03715\% & - \\
35 & 0.03725\% & - \\
60 & 0.03630\% & 173\% \\
77 & 0.03735\% & - \\
94 & 0.037329\% & - \\
120 & 0.03715\% & - \\
183 & 0.03325\% & 700\% \\
220 & 0.03785\% & - \\
325 & 0.03425\% & 833\% \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Distance accuracy \(\overline{\Delta d}/d\) and resolution degradation \((\Delta d_{\text{max}}-\Delta d_{\text{min}})/\delta d\) when the target is at a distance of \(d~{}=~{}1\) km. Figure 4: The range error in atmospheric foggy conditions. (**a**) 60 GHz; (**b**) 94 GHz; (**c**) 325 GHz.
## 4 WSN Clustering  
Because of the high energy consumption, sensor nodes fail prematurely. Direct communication between sensor nodes and the base station (or communication between sensor nodes and multiple hops to the base station) is not feasible to solve this problem because it would consume more energy as shown in Figure 4 below. Due to WSN's limitations, long-distance transmission is not possible. The most significant disadvantage of direct communication is the significant energy consumption. Problems also occur when duplicate data is sent from sensor nodes that are close to each other, with minor differences, resulting in the furthest nodes dying quickly. To address these issues, two-tier transmission is used, in which clusters of nodes are interconnected using a hierarchical method. The leader node, also known as the cluster head, coordinates data collection and forwarding to the BS.  
A two-level hierarchy is frequently formed, with the top level for cluster leaders and the bottom level for nodes. At regular intervals, some lower-level nodes send data to their respective CHs. When the cluster head obtains the aggregated data, it sends it to BS. For a long time, the CH node used more energy than others, especially when transmitting data over long distances [69]. Furthermore, after a certain number of rounds, the chosen CH may have depleted all of its energy, forcing it to withdraw. Because it is necessary to dynamically balance the energy consumption of the sensor nodes, the function of CH must be switched regularly [55; 56]. Figure 5 depicts intra-cluster communication within a cluster and inter-cluster communication between clusters.  
Cluster-based and grid-based hierarchical methods are the most commonly used [70]. Several distribution mechanisms for energy-efficient routing such as adaptive periodic threshold sensitive, low energy adaptive mechanisms have been proposed [71]. A comprehensive review reveals that energy consumption is the most important topic in WSN, but it is largely ignored by researchers and practitioners. Literature also proposed the adoption of computing, sensing, and data transmission mechanisms to the Base Station (BS) with the help of gateways to reduce energy consumption. Figure 6 illustrated the energy efficiency of cluster-based protocols in wireless sensor networks according to analyzing and results of the algorithms shows panel protocol is the highest one with energy efficiency. As such most of the developed protocols take in this aspect with advanced WSN and its applications  
Figure 4: Direct/1-tier communication in WSN.  
Figure 5: Indirect/multi-level communication in WSN.  
for many areas; as a result, there is a persistent need to conducting an overview on such heterogeneous algorithms and clustering based.
###### Abstract  
In this paper, the transmission mechanism of the spike information embedded in the low frequency fluctuation (LFF) dynamic in a cascaded laser system is numerically demonstrated. In the cascaded laser system, the LFF waveform is first generated by a drive laser with optical feedback and is then injected into a response laser. The range of crucial system parameters that can make the response laser generate the LFF dynamic is studied, and the effect of parameter mismatch on the transmission of LFF dynamics is explored through a method of symbolic time-series analysis and the index, such as the spike rate and the cross-correlation coefficient. The results show that the mismatch of the pump current has a more significant influence on the transmission of LFF waveforms than that of the internal physical parameter of the laser, such as the linewidth enhancement factor. Moreover, increasing the injection strength can enhance the robustness of LFF transmission. As spikes of the LFF dynamic generated by lasers with optical feedback is similar to the spike of neurons, the results of this paper can help understanding the information transporting and processing inside the photonic neurons.  
s +
Footnote †: journal: _Photonics_  
_2022_, 9, 483.  
external periodic signal on the output of the optical feedback laser has been studied [24; 25]. According to [26], the study of photonic neurons will evolve to the transmission of spikes in a photonic neural system composed of multiple photonic neurons. However, there are few studies on the transmission of various spike information embedded in LFF dynamics. Therefore, in this paper, the transmission of the LFF waveform in a cascaded laser system consisting of a laser with optical feedback and another laser is studied, and the effects of various system parameters on the output of the system are analyzed and discussed.  
The reminder of this paper is organized as follows. In Section 2, the system structure, theory model, and tools for describing the system output characteristics are introduced. In Section 3, the effect of various system parameters on the transmission of LFF dynamics is studied and analyzed. The discussion of the results and conclusions are provided in Section 4.