esa-sceva/satcom-chunk-collection huggingface dataset:
# A Comprehensive Survey on Knowledge-Defined Networking
## 8 Discussion
### Challenges
#### 8.2.3 Privacy  
Privacy concerns can appear as the KDN paradigm involves the collection of data for network optimization by knowledge generation, which may include sensitive information of users such as user identities, confidential information of users and devices, sensitive sensor data such as private audio, video, or images, etc. There is a risk of the dissemination of such sensitive data to third parties, which can ruin the reputation of users. Thus, in KDN, private data should be handled in an ethical and secure manner. This paves the way for additional requirements for data protection measures such as encryption, access control, and monitoring to make sure that only authorized entities handle data and sensitive data are not disclosed to external parties. Furthermore, machine learning models should be trained to give fair and ethical results. If the knowledge generated by them produces a discriminatory decision, it can affect the whole organization. Thus, machine learning models should be trained with unbiased and non-discriminatory data to produce ethical results without discriminating against individuals. For example, if a machine learning model is trained in a discriminative manner to classify traffic coming from a certain group of users as lower priority, then that group of users' traffic will most likely be given low priority under any network scenario. The ethical way to train a model is without such discrimination, considering the dynamics of the network with the intention of improving network performance. Therefore, in order to mitigate privacy risk in KDN, organizations should implement robust data protection measures and ensure that knowledge generation models are trained without bias or discrimination.
# Three-Dimensional Modeling of the Xichang Crust in Sichuan, China by Machine Learning
## 2 Data and Methods
### Data
#### 2.1.2 Earthquake Catalogue  
In 2012, The Institute of Geophysics of China Earthquake Administration deployed a high-density and broadband mobile seismic array in Luding-Mianning-Xichang along the Anninghe fault zone to monitor the deep seismic activity behavior. It evaluated the detection ability of the array for microearthquakes at different depths [2] and seismic activity parameters [42]. This campaign provides reliable data sources and parameter support for our quantitative approach. We have selected 9338 earthquakes monitored in this area from 2013 to 2019 as samples to conduct precise relocation. The magnitude (ML) range is \(-2.0\) to \(6.9\). Combined with the characteristics of tectonic faults and lithology distribution, it is suggested that (Figure 1), except for the granite body in the Shimian area cut by the Daliangshan fault, the other faults are distributed along the boundary of the magmatic body or the Xichang basin, obviously constrained by the geometric framework of the basement. Earthqu in this region are mainly distributed in clusters along intrusive gramitic rocks and deep fault zones, especially in areas with complex fracture structures, such as the Shimian area. Along this profile, the seismic clusters also have good stratification characteristics. Most earthquakes are concentrated in the 5-20 km depth range, while the clusters in the depth range of 20-35 km are also found at fault intersections.
## 1 Introduction
The wavelet-scalogram CNN structure presented in this work was initially introduced in a preliminary conference paper for the identification of sharp waves in a small experimental dataset of HI EEG of preterm fetal sheep post HI-insult [28]. It has also been tested for the identification of HI gamma spike transients [27]. Furthermore, we demonstrated that a higher number of automatically quantified sharp waves after the first 2 h of HI insult in preterm fetal sheep models is significantly correlated with more subcortical damage [13]. This correlation prompted our interest in investigating this wave-type in preterm human EEG [11]. This article presents, for the first time, the exceptional capabilities of convolutional neural network (CNN)-based pattern classifiers in accurately identifying HI sharp wave biomarkers in a large dataset of 256 Hz sampled EEG from human preterm infants at birth. The work indicates how spectrally-rich wavelet scalograms (WS) of clinical EEG can serve as inputs to a deep 2D-CNN pattern classifier for sharp wave identification. The WS-CNN pattern classifier underwent training using an exclusive data bank of clinical recordings, comprising 6812 EEG sharp waves sampled at 256 Hz clinical sampling rate, from eight preterm infants during their first 6-7 h of life (n = 8, total of 48 h recording), manually identified by an expert. The performance of the WS-CNN pattern classifier was also assessed against a wavelet-Fourier CNN (WF-CNN), a conventional 1D-CNN, and a wavelet-Fuzzy approach introduced previously in [13,14]. The article outlines how the WS-CNN pattern classifier robustly identifies HI sharp waves from EEG background and artifacts, irrespective of potential morphological changes induced by treatments/drugs. We determined a high cross-validated accuracy of 99.34 \(\pm\) 0.51%, showcasing exceptional performance without the need for manual intervention.
## 2 Materials and Methods  
### The Study Site  
The carbon flux monitoring tower for this study was situated within the Alligator River National Wildlife Refuge (ARNWR) in Dare County, North Carolina, USA (35\({}^{\circ}\)45\({}^{\prime}\)16.44\({}^{\prime\prime}\) N, 75\({}^{\circ}\)54\({}^{\prime}\)13.64\({}^{\prime\prime}\) W) (Figure 1). The site experiences persistent inundation resulting from impeded groundwater drainage into the adjacent ocean, a condition exacerbated by rising sea levels. Tree-rooted 'hummocks' generally remain above the water table, while the lower, unvegetated 'hollows' are inundated for approximately 70% of the year. Groundwater table (GWT) data from this study from 2009 to 2012 indicate episodic flooding; however, from 2013 to 2019, GWT levels were predominantly above the soil surface, indicating sustained inundation. Consistent with findings from previous studies [14, 15, 16], sea level rise (Figure 2b) has led to the retreat of the lower wetland boundary, increasing flooding in coastal wetlands. This phenomenon has adversely impacted vegetation survival at our study location, similar to observations reported in other wetland ecosystems [2; 3; 17; 18].  
As documented in previous studies [19; 20; 21], dominant tree species include American holly (_Ilex opaca_ [PERSON]), tupelo (_Nyssa sylvatica_ [PERSON]), sweetgum (_Liquidambar styaciiflua_  
Figure 1: Study site at the Alligator River National Wildlife Refuge, Dare County, North Carolina, USA, showing the location of the flux tower and surrounding plots. Top photo: flux tower structure; middle: site conditions in 2009; bottom: canopy structure in 2019.  
Figure 2: Temporal variation in **(a)** relative groundwater table (GWT) depth, **(b)** relative sea level, **(c)** cumulative tree mortality rates, and **(d)** leaf area index (LAI) from 2009 to 2019. The tau value for GWT, relative sea level, total mortality rates, and LAI were taken from Kendall trend analysis. All data were collected within the flux footprint of US-NC4 tower at Alligator River National Wildlife Refuge in North Carolina, USA.  
L.), loblolly pine (_Pinus taeda_ L.), and red maple (_Acer rubrum_ L.). The canopy averages approximately 23 m in height, with an estimated density of 2320 trees per hectare. Soils at the site are classified as Pungo series Haplosaprists, featuring an organic layer between 0.3 and 1.0 m thick. Elevation at the site is less than 1 m above sea level. The regional average annual precipitation over 1981-2019 was 1168 \(\pm\) 204 mm, and the mean annual temperature from 2005-2019 was 15.8 \(\pm\) 1.8 \({}^{\circ}\)C [19; 20; 21].
## 2 Study Area and Data Preparation
### Study Area
It is desirable to adopt the satellite precipitation products at fine spatiotemporal resolutions such as IMERG and 3B42V7 as supplementary precipitation data sources for effective runoff simulations. This requires validation of the IMERG and 3B42V7 precipitation estimates and assessment of the feasibility of these two precipitation products in rainfall-runoff modeling. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Weather/Streamflow Stations** & **Hkamti** & **Homalin** & **Mawlaik** & **Kalewa** & **Monywa** \\ \hline Elevation (m) & 387 & 121 & 119 & 126 & 78 \\ Drainage area (km\({}^{2}\)) & 27,420 & 43,124 & 69,339 & 72,848 & 110,350 \\ Mean annual precipitation (mm) & 3745.5 & 2184.0 & 1716.5 & 1646.4 & 750.4 \\ Mean annual runoff depth (mm) & 2631.0 & 2319.5 & 1800.3 & 1794.8 & 1260.5 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Basic information of main weather/streamflow stations in the Chindwin River basin. Figure 2: Mean monthly: (**a**) Air temperature; (**b**) precipitation; and (**c**) runoff at main weather and streamflow stations in the Chindwin River basin.
# Application of Thermoelectric Generators for Low-Temperature-Gradient Energy Harvesting
## 2 Basic Principles of Thermoelectric Generators
### The Seebeck Effect  
Seebeck generators or thermoelectric generators (TEGs) are semiconductor devices designed to convert heat flow or a temperature gradient directly into DC electrical energy through the Seebeck effect. The Seebeck effect, which is due to the motion of charge carriers within semiconductors, produces an electromotive force (emf) across two points of a conductive material when there is a temperature gradient between these points.  
Semiconductors are particularly appropriate for thermoelectric applications because the concentration of charge carriers can be changed by doping the material. In an n-type doped semiconductor, the charge carriers are mostly free electrons, while in a p-type doped semiconductor, the charge carriers are free holes, i.e., missing electrons in the valence band. The thermocouple (consisting of a p-type and an n-type semiconductor connected in series by a metal strip) is the basic building block of a TEG. Due to the temperature gradient, the charge carriers of the hot side have higher kinetic energy, so they diffuse from the hot to the cold side of the semiconductor. Eventually, the cold end of the TEG becomes positively (p-type semiconductor) or negatively (n-type semiconductor) charged, and the hot end negatively (p-type semiconductor) or positively (n-type semiconductor) charged [23]. Charges build-up at the cold end, creating an electromotive force (\(\Delta V\) or Seebeck voltage) [24] between the n-type and p-type hot ends of the semiconductors that is directly proportional to the temperature difference \(\Delta T=T_{hot}-T_{cold}\) between the hot and cold ends of the semiconductors, as shown in Figure 1. To boost the voltage and current generated, commercial TEGs include many pairs of n-type and p-type couples [21] connected in series and/or parallel to generate the desired electrical voltage and current. The couples are typically placed between two parallel ceramic plates, which provide a flat surface, structural rigidity, and an insulating layer to prevent short circuits.  
TEGs offer several advantages, including reliability and quiet operation, since they are solid-state devices with no moving parts, are compact, do not emit greenhouse gases, can be mounted in any orientation, are scalable from \(\mu\)W to kW, and directly convert heat into electrical energy.
## 3 Results and Analysis  
### Slump  
Figure 5 shows the slump of the cement mortar made by replacing sand with TPSW and that the slump of the control group (0%) was 81.3% lower than that of the 15% TPSW group when the W/C was 0.4. When the W/C increased from 0.4 to 0.5, the slump of the control group was 55% lower than that of the 15% experimental group. When the W/C increased from 0.5 to 0.6, the slump of the control group was 31% lower than that of the 15% experimental group. When the W/C increased, the slump tended to increase because the increase in the water content reduced the cohesion of the paste and increased the slump, and the overall workability and fluidity of the cement mortar increased. Overall, the slump decreased as the amount of TPSW added increased. When the W/C increased, the overall slump increased as the water content increased, so the W/C had a greater impact on the slump than the substitution amount did.  
As shown in Figure 5, the slump decreased significantly as the proportion of the TPSW materials replacing sand increased. When the water-cement ratio was 0.4, the slumps decreased by 25%, 68.8%, and 81.3% for the substitution amounts of 5%, 10%, and 15%, respectively. For a water-cement ratio of 0.5, the slumps decreased by 13.9%, 36.1%, and 55.6%, respectively. At a water-cement ratio of 0.6, the slumps decreased by 4.4%, 13.3%, and 31.1% for the same substitution levels. These findings are consistent with other studies [38], and the reduction in slump could be attributed to the flaky shape of the TPSW material, which did not perform as well as the coarse aggregate. While increasing the substitution amount reduced the slump, the research results indicate that the water-cement ratio had a greater impact on the slump than the substitution amount.
# Design, Experiment, and Improvement of a Quasi-Zero-Stiffness Vibration Isolation System
## 1 Introduction
During the finite element modeling analysis, it was found that the axial magnetization magnetic ring's stiffness-displacement characteristics could be used for positive stiffness spring optimization. The following improvements were made: choosing the appropriate parameters of the ring height to improve the negative stiffness spring and designing a suitable nonlinear spring that is parallel with the linear spring acting as a positive stiffness system. Finally, the improved QZS system had a better performance regarding transmissibility than the non-improved QZS system in theory. The paper is organized as follows. In Section 2, the theoretical modeling of the QZS vibration isolation system is set up and the force-displacement characteristics of the two coupled magnet springs are developed. Then, the influence of the parameters of the coupled magnetic rings on stiffness is investigated. In Section 3, the dynamic response of the proposed QZS isolation system is analyzed. In Section 4, an experimental prototype is developed and experiments are conducted to verify the effectiveness of the QZS system. In Section 5, two methods for the improvement of the QZS system are discussed and the performance of the improved QZS system is analyzed and compared to a conventional system. Finally, some conclusions are given in Section 6.
## 3 Structure of the Adaptive Controller
### PID Gain Scheduler
#### 3.1.2 Gain Scheduler for the Frame of the Roll Axis  
The tilting degree around the roll axis of the loading device is mainly caused by the slope of one jaw of the stair, and it is smaller than the tilt of the pitch axis. The frame of the roll axis is the inner frame of the gimbal structure. The \(X\) set to gather the optimized gain of the frame of the roll axis is Equation (21).  
Figure 4: Gain-scheduling three-dimensional functions for the frame of the pitch axis of the loading device: (**a**) P gain scheduler; (**b**) 1 gain scheduler; (**c**) D gain scheduler.  
\[0\;\mathrm{kg}:\;X_{3}=98.039,\;X_{2}=\left[-29.5:\frac{29.5}{20}:29.5\right] \tag{21}\] \[1\;\mathrm{kg}:\;X_{3}=66.445,\;X_{2}=\left[-29.5:\frac{29.5}{20}:29.5\right]\] \[2\;\mathrm{kg}:\;X_{3}=50.251,\;X_{2}=\left[-22:\frac{29.5}{20}:22\right]\] \[3\;\mathrm{kg}:\;X_{3}=33.784,\;X_{2}=\left[-15:\frac{15}{20}:1 5\right]\] \[4\;\mathrm{kg}:\;X_{3}=25.445,\;X_{2}=\left[-11:\frac{11}{20}:1 1\right]\] \[5\;\mathrm{kg}:\;X_{3}=20.367,\;X_{2}=\left[-9:\frac{9}{20}:9\right]\]  
In the results of the simulation to obtain the optimized gain set, the \(P_{\mathrm{gain}}\) converges in the initial setting value in several simulations. In the case of the frame of the roll axis, the adjustment of \(P_{\mathrm{gain}}\) is an insignificant effect because the allowed error is limited by the outer frame of the gimbal being small. The gain scheduler of the frame of the roll axis adapts the I and D gain by the gain-scheduling functions and uses a fixed \(P_{\mathrm{gain}}\). Figure 5 and Equations (23) and (24) are the PID gain-scheduling function for the frame of the roll axis. The normalization of interpolating the gains is shown in Equation (22).  
\[x=\frac{X_{2}}{12.46},\;\;\;y=\frac{X_{3}-49.06}{26.88} \tag{22}\]  
\[I_{\mathrm{gain}}=0.02152 - 0.0001089\;x-0.01084\;y+0.003878\;x^{2}+0.0001591\;x\;y+0.004848\;y^ {2}-0.000337\;x^{2}\;y \tag{23}\] \[- 0.001033\;y^{3}-0.0005136\;x^{4}-0.0002505\;x^{3}\;y-0.001298\;x^ {2}\;y^{2}+0.0001455\;x\;y^{3}\] \[+ 0.002524\;y^{4}+0.000275\;x^{4}\;y+0.0001112\;x^{3}\;y^{2}+0.0003 705\;x^{2}\;y^{3}-0.0001177\;x\;y^{4}\] \[- 0.001327\;y^{5}\] \[D_{\mathrm{gain}}=0.1975 + 0.0001443\;x-0.09851\;y+-0.002835\;x^{2}-0.002265\;x\;y+0.07358 \;y^{2}+0.0004731\;x^{3}\] (24) \[+ 0.01318\;x^{2}\;y-0.002979\;x\;y^{2}-0.02471\;y^{3}-0.0005513\;x^ {4}-0.0001227\;x^{3}\;y\] \[- 0.005469\;x^{2}\;y^{2}+0.002157\;x\;y^{3}\]
# How 5G Wireless (and Concomitant Technologies) Will Revolutionize Healthcare?
## 2 Challenges Posed by the Current Healthcare System
### Resource Constraints  
Despite the great success in creating an impressive outlook of the healthcare system, the overall healthcare services are still insufficient. Patients have to travel from distant places to visit their doctors. Travelling barriers cause rescheduling or missing of appointments and delay in medications. There are 57 countries with a critical shortage of healthcare workers; for instance, Africa has 2.3 health workers per 1000 population as compared to the Americas, which have 24.8 health workers per 1000 population [12]. Similarly, in Pakistan, there is one doctor for 1038 inhabitants [7]. The problem is now becoming more acute, and the world will have an anticipated shortage of 12.9 million healthcare workers by 2035 [13]. Therefore, we need some serious developments in healthcare to increase the productivity of health professionals by using telemedicine and e-Heath-like services.
## Materials and Methods
### Characterizations  
The surface area and porosity of AC-RFA and MWCNTs samples were examined via the adsorption/desorption isotherms of nitrogen at \(-\)196 \({}^{\circ}\)C by a Micromertics ASAP2420\({}^{\text{\text{\textdegree}}}\) surface area and porosity analyzer. In advance of each analysis, the specimens were degassed in-situ for 24 h at 150 \({}^{\circ}\)C under high vacuum (1 \(\times\) 10\({}^{-4}\) Pa). The pore properties of samples were determined from the adsorbed volume of N\({}_{2}\) at \(-\)196 \({}^{\circ}\)C and the relative pressure (\(P/P_{0}\)) of 0.99 (99% of the saturation pressure).  
The FT-Raman spectra were collected by a Bruker FT-Raman spectrometer of type RFS 100/S that is attached to a Bruker-IFS 66/S spectrometer. The morphology of MWCNT/AC-RFA mixed specimens was observed using an FEI Nova(tm) nanoscanning electron microscope 450 (Nova NanoSEM). A transmission electron microscope (TEM) of Talos L120C and of FEI Tecnai G2 F20 FE-TEM, available at Qatar Environment and Energy Research Institute (QEERI), were utilized to investigate the samples. Thermogravimetric analyses (PerkinElmer Pyris 6 TGA) were proceeded under nitrogen gas flow with a ramp 10 \({}^{\circ}\)C/min from ambient temperature to 800 \({}^{\circ}\)C (see Figure S1 in Supplementary Materials).  
Adsorption/desorption isotherm measurements of CO\({}_{2}\) and CH\({}_{4}\) gases were carried out by a Rubotherm-Hygra magnetic suspension microbalance with a microgram resolution [22]. Prior to the adsorption measurement process on each sample, a buoyancy measurement using helium gas was conducted at 40 \({}^{\circ}\)C to assess the skeleton mass and  
Figure 2: The carbonization and activation processes of RF aerogel sample.  
volume, and hence the skeleton density, of each sample [22]. Furthermore, before conducting every adsorption isotherm, the samples were degassed in-situ at 120 \({}^{\circ}\)C for 24 h (see Figure S2 in Supplementary Materials). The adsorption calculations proceed afterwards as reported elsewhere [22; 24].  
The elemental analysis of MWCNT/AC-RFA mixed samples were carried out using a CHNS/O analyzer (2400, Series II, Perkin Elmer). X-ray diffraction (XRD) measurements were also conducted by utilizing a Miniflex II Benchtop XRD analyzer, manufactured by Rigaku Corporation Japan. The 20 scan data were collected over the range of 5\({}^{\circ}\) to 90\({}^{\circ}\). X-ray photoelectron spectroscopy (XPS) was achieved utilizing a Thermo Scientific K-alpha photoelectron spectrometer using monochromatic Al\({}_{\text{k,ex}}\) radiation.
## 4 Carols Airborne Data Analysis
### Methods for Qualification of CAROLS Data
#### 4.1.2 CAROLS Calibration Data  
During any given flight, periodic calibrations effectively decrease the influence of gain fluctuations, and improve the radiometer's sensitivity. Internal calibration consists in switching the receiver input between an internal load and a noise diode with the power turned alternately off and on. During campaigns, it is very important to monitor the drift of each instrument. The measured gain and receiver noise temperature are interpolated between successive calibration phases, in order to estimate the receiver's behavior during the antenna measurement, and to apply suitable corrections to the recorded values.  
In order to retrieve absolute values of natural emissions, absolute calibration of the measured brightness temperatures is needed. The absolute calibration of the radiometers is generally made by measuring the antenna temperatures while flying over fresh water lakes. In our case, this type of measurement was not possible because of the persistent presence of strong RFI around identified lakes in France. For this reason, absolute calibrations were carried out over the ocean. For the two antennas, the measurements were compared to calculated temperatures using the TRAP software. For these comparisons, measurements recorded under conditions of only limited variations in roll and pitch, and also SSS, were used.