esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Data  
### PSAC Data  
The main purpose of HJ-2 series satellites is for monitoring and early warning of environmental pollution and disasters, which is operated by China Centre for Resources Satellite Data and Application (CCRSDA. Available online: [[http://www.cresda.com](http://www.cresda.com)]([http://www.cresda.com](http://www.cresda.com)) (accessed on 18 January 2022)). HJ-2A and HJ-2B are the first two of the HJ-2 series, and both satellites are polar orbiting satellites with an orbital altitude of 645 km. PSAC onboard HJ-2 satellite is mainly used for atmospheric monitoring. It has a spatial resolution of about 6 km and an imaging width of more than 800 km. PSAC has nine spectral channels with polarization detection capability, including two NIR channels (865 and 910 nm) dedicated to CWV retrieval. The spectral response functions (SRF) of two bands of PSAC used for CWV retrieval are shown in Figure 1, and more characteristics of them can be found in Table 1. Since CCRSDA only provides us with PSAC data from March 2021 to August 2021 during the in-orbit testing period, the time period chosen for this study was these 6 months.  
Figure 1: The SRFs of two bands of PSAC used for CWV retrieval. The first line in the legend (blue line) represents the water vapor absorption transmittance (WVAT) of the atmosphere when the view zenith angle (VZA) and solar zenith angle (SZA) are equal to 0 and CWV is equal to 1 cm. The second line (yellow line) represents the WVAT when VZA and SZA are equal to 0 and CWV is equal to 3 cm. The next two are SRFs of the two bands of PSAC used for CWV retrieval.
# Intraoperative Imaging of Cortical Blood Flow by Camera-Based Photoplethysmography at Green Light
## 2 Methods and Clinical Cases
### Clinical Cases  
The study was carried out with five patients with different diagnoses who underwent open surgery on the brain. Four of them had tumor pathologies, and one had diagnosis of arterial atherosclerotic occlusion. In all trials, the cbPPG system revealed spatial distribution of blood-pulsation parameters over more than 98% of the open brain cortex. However, here, we report in detail the results of the two most representative trials. The first patient had a tumor formation of the right lateral ventricle, complicated by occlusive hydrocephalus syndrome. He underwent surgery for tumor resection with open transcortical access. His ependimoma of the right ventricle was treated with typical right-sidefrontal craniotomy. After dura mater dissection, slight brain protrusion was observed. The transfrontal approach to the anterior horn of the right ventricle was used. After tumor resection, the brain surface was returned to its original position. The second patient had extracranial atherosclerotic occlusion with the left internal carotid artery. He underwent an anastomosis operation between the left temporal artery and the M4 segment of the left mid-cerebral artery. In both cases, intraoperative and early postoperative complications were not observed.
# A Survey on Wireless Body Area Networks for eHealthcare Systems in Residential Environments
## 4 Future Prospects
### Advantages of Smartphone-Based Healthcare Applications  
A collection of different types of low-cost sensors (e.g., accelerometer, gyroscope, camera, magnetometer, pedometer, goniometer, actometer, biometric and pressure) embedded in smartphones have enabled these multifunctional devices to be applied in many aspects of future healthcare systems. In addition, combination of some of these sensors such as biometric sensors with big data has provided a potential for smartphones to hugely impact the future of healthcare systems. For instance, people may habitually check their smartphones 100 times a day. This statistic information can be used to enable smartphone devices to frequently obtain the user's facial scan. In this way, vital signs such as heart rate or blood pressure can be measured [104]. If this technique is used over a large population and such biometric data is collected in the cloud, contagious disease outbreaks can be discovered more quickly [104].  
With the prevalent use of smartphones and the appearance of fourth generation of mobile telecommunications technology (4G) that provides higher speed mobile broadband internet access services along with the ubiquity of Wi-Fi technology, healthcare informatics (an interdisciplinary field combining healthcare, computer science and information science) is now able to overcome time and location limitations. This is enormously important specifically in cases that an immediate response is extremely critical or when a patient's condition is not stable and dynamically changing.  
In contrast to intrusive wearable devices that impose a burden on user's daily activities, smartphones are non-intrusive, non-obstructive and not required to follow a cumbersome usage protocol. This results in reducing the possible usability complications.  
Smartphones do not require supplementary hardware and many health-related mobile apps are accessible and free which lead to a more cost-effective solution compared to traditional wearable devices. Smartphones also have potential to manage chronic diseases such as Alzheimer's, Hypertension and Diabetes. This can be done by frequent monitoring of patients through mobile apps or message reminders regarding the drug dosage information.
# Research on Bidirectional Reservation Method for Anti-Permeation Geomembrane Slack
## 2 Geomembrane Slack Methods
### Two-Way Reservation Method
#### 2.2.2 Two-Way Reservation Method  
The bidirectional reservation method is considered based on the existing unidirectional geomembrane reservation methods. Among these techniques, because the wave-shaped slack reservation method makes the geomembrane form many folds under the action of overburden pressure, which threatens the safety of the geomembrane [22], it is excluded from the design of this bidirectional reservation strategy. The unidirectional groove-shaped and Z-shaped techniques are extended to become bidirectional, and the combination of the two is considered. Thus, we propose the cross-groove-shaped, cross-Z-shaped, and combined groove- and Z-shaped techniques as three bidirectional reservation methods.  
1. Cross-groove-shaped laying method. As shown in Figure 2a, the unidirectional recess is modified based on the recess-type slack preparation method by changing the unidirectional recess into a cross-groove-shaped bidirectional recess. In this case, the size of the recess must be determined according to the corresponding specifications [17; 18; 19]. When the geomembrane is subjected to tensile stress due to environmental changes, the geomembrane in the cross-shaped recess is lifted so that the geomembrane is not tight, even when subjected to tensile stress. Theoretically, when the geomembrane is subjected to tensile stress in any direction, the geomembrane hidden in the cross-shaped grooves will be pulled up. So, the cross-shaped groove can basically address tensile stresses in any direction of the geomembrane.
2. Cross-Z-shaped laying method. Based on the unidirectional Z-shaped technique, the geomembrane is folded in a direction perpendicular to the original Z shape to obtain a bidirectional Z shape, as shown in Figure 2b. The Z-shaped slackening reservation method is shown in Figure 2b.
3. Combined Z- and groove-shaped laying method. By combining the unidirectional Z shape and unidirectional groove shape, a new bidirectional geomembrane slack reservation method can be obtained. As shown in Figure 2c, the unidirectional Z-folded geomembrane is laid on a foundation with a unidirectional groove. In this case, the zigzag folded strip is geometrically perpendicular to the recess.
# Semantic Segmentation of Aerial Imagery Using U-Net with Self-Attention and Separable Convolutions
## 3 Proposed Method
### Proposed Model
#### 3.4.2 Infusing Contextual Awareness with Self-Attention  
Recognizing the need for nuanced contextual awareness in satellite image segmentation, self-attention mechanisms are seamlessly woven into the fabric of the model. The introduction of attention layers, specifically tailored to focus on salient features, enables the model to discern intricate patterns and long-range dependencies. This strategic fusion of contextual understanding and computational efficiency sets the proposed model apart in the realm of satellite imagery analysis.  
Explaining the Components of the Model Architecture:
## 2 Understanding the Jargon: Equipment and Data Products
### Understanding ALS Data Products
Figure 8: Spatial and intensity information obtained with ALS and the fusion of both for a sparsely vegetated area. (**a**) Shaded relief map of DSM; (**b**) LiDAR Intensity image; (**c**) 3D model from DSM overlaid with intensity image. Figure 9: Spatial and intensity information obtained with ALS in a heavily vegetated area from the top of canopy and ground surface. (**a**) Shaded relief map from DSM; (**b**) shaded relief map from DEM; (**c**) intensity image produced from first returns only; (**d**) intensity image produced from ground returns only. Until very recently most ALS systems were single wavelength, however commercial systems that incorporate multiple wavelengths are starting to appear on the market and in the near future active multispectral images derived from ALS intensity will open new research possibilities to archaeologists working in sparsely vegetated areas. These active images will have some advantages over traditional passive imagery including no dependence on solar illumination for their collection, the reduction of shadowing, and the production of quasi-perfect orthophotos [36].
## 2 AUV Modeling and Problem Statements
### Problem Statement  
The AUV is required to start from an origin and track a time parameterized path to arrive at the destination. In the specified origin-destination region where the AUV operates, the ocean current information, i.e., \(V_{\rm c}\) and \(\beta_{\rm c}\), usually can be either predicted by regional ocean models or roughly measured by the sensors carried with the AUV [10]. However, these predictions or measurements are not precise and are mostly stochastically uncertain. Therefore, we assume that the ocean current could in principle be obtained by predictions, but with small prediction biased errors \(\epsilon_{b}\) and uncertainties following a normal distribution as, i.e., \(\mathbf{b}\sim N(\bar{\mathbf{b}}+\mathbf{e}_{b},\Sigma_{b})\) where \(\bar{\mathbf{b}}=[\bar{V}_{\rm c},\bar{\beta}_{\rm c}]\), and \(\bar{V}_{\rm c}\), \(\bar{\beta}_{\rm c}\) are the predicted mean current speed and angle in the inertial coordinate system, respectively; \(\Sigma_{b}=diag([\sigma_{V}^{2},\sigma_{\beta}^{2}])\) is the corresponding covariance that reflect the prediction accuracy where \(diag\) means diagonal matrices; \(\mathbf{e}_{b}=[\epsilon_{v},\epsilon_{\beta}]\) with \(\epsilon_{v}\) and \(\epsilon_{\beta}\) are the corresponding prediction biased errors, respectively. Note that the biased errors are unknown in the design process, and are modeled only for simulation purposes. In the simulations, we will explore how the ocean current biased errors influence the AUV motions as well as the robustness to small magnitude biased errors due to the feedback from acoustic localization. Furthermore, \(V_{\rm c}\) and \(\beta_{\rm c}\) are assumed to be independent and identically distributed random variables.  
For the controller design, full states need to be known precisely for feedback in general. However, the sensors such as GPS that are used for the state measurement of ground or airborne vehicles are not applicable in the underwater environment. Therefore, in the next section, we first propose a distance dependent localization method to \"measure\" the AUV position.
## 3 Results and Discussion
### Adsorption Isotherms  
To get specific information on isotherm parameters associated with MB, the collected adsorption data were analyzed using Langmuir and Freundlich isotherm models [36; 37]. [PERSON] and Freundlich isotherm models are presented by Equations (1) and (2), where \(k_{L}\) represents [PERSON] constant (L mg\({}^{-1}\)), \(q_{e}\) denotes the equilibrium adsorption capacity (mg g\({}^{-1}\)), \(q_{\text{max}}\) is the Langmuir monolayer adsorption capacity (mg g\({}^{-1}\)), \(K_{f}\) is Freundlich constant (L mg\({}^{-1}\)), 1/n is the empirical parameter in terms of adsorption capacity and intensity. Figure 4c,d illustrates the equilibrium isotherms for MB adsorption by using MPC as an adsorbent. The data of the equilibrium adsorption calculated from [PERSON] and Freundlich isotherm models are shown in Table 1. As can be seen from Figure 4c,d and Table 1, the experimental data is not well correlated with the [PERSON] model, whereas the data matches well with [PERSON] model. This finding suggests that MB adsorption on the adsorbent surface is homogeneous. Moreover, the equilibrium parameter \(R_{\text{L}}\), which can be estimated by Equation (3), is a useful parameter to determine the feasibility of adsorption [38]. The \(R_{\text{L}}\) values were calculated to be 0.00674-0.00822 for MB adsorption on MPC, suggesting that the adsorption of MB over MPC was a favorable process [39].  
\[\frac{C_{e}}{q_{e}}=\frac{C_{e}}{q_{\text{max}}}+\frac{1}{q_{\text{max}}k_{L}} \tag{1}\]  
\[\log q_{e}=\log K_{f}+\frac{1}{n}\log C_{e} \tag{2}\]  
\[R_{L}=\frac{1}{1+k_{L}C_{0}} \tag{3}\]  
Figure 4: (**a**) Adsorption compacity vs. initial solution pH for MB removal on MPC and the corresponding Zeta potential; (**b**) Comparison of the adsorption capacities of MB on various adsorbents; (**c**) Freundlich and (**d**) Langmuir adsorption isotherms of MB with MPC.
## 2 Study Area, Data and Methodology  
### Study Area  
This research focused on the southern part of Guangzhou as the study area, including Panyu District and Nansha District, with a geographic range of 113\({}^{\circ}\)14\({}^{\prime}\) E-113\({}^{\circ}\)45\({}^{\prime}\) E, 22\({}^{\circ}\)32\({}^{\prime}\) N-23\({}^{\circ}\)05\({}^{\prime}\) N and an area of 1340 km\({}^{2}\). As shown in Figure 1, located in the Western Pearl River Estuary, the study area is the geometric center, and the traffic junction of the Guangdong-Hong Kong-Macao Greater Bay Area (GHM GBA) city cluster is adjacent to Hong Kong and Macao and crosses the sea from Southeast Asia. The study area is located in the subtropical monsoon climate zone with a mild climate and an average annual rainfall amount up to 1600 mm. The topography is mainly delta plain, and a few low hills are distributed in the central and southern regions. Superior climatic conditions and the unique location of the estuary, the dense channel of the Pearl River, the geographical characteristics of the river-sea interface, the rich wetlands and other ecological factors cause the study area to have excellent natural endowments and extremely rich ecological resources. The ecosystem of the study area plays an important role in maintaining the ecological balance of the Pearl River Estuary and safeguarding the sound ecological network in GHM. Nansha Wetland Park, Huangshanlu Forest Park, 18 Luohan Mountain Forest Park, Changlong Tourist Resort and Lianhua Mountain are all famous ecological tourism areas in the study area.
## 2 Operation Principle  
### EOT Structure  
The components of an electro-optical telescope (EOT) can be typically divided into functional subsystems that contribute to understanding the errors that affect pointing [26; 27]. The electro-mechanical gimbal, consisting of a base, bearings, motors, actuators, etc., provides physical support and allows the motion of the axes. This paper concentrates on the alt-azimuth telescope [28], whose gimbal arrangement is depicted in Figure 1, including the azimuth axis, elevation axis, and line of sight. The servo control system generates and coordinates the motion, while the optical system collects and transmits information about the targets.
# Optimizing CNN-LSTM for the Localization of False Data Injection Attacks in Power Systems
## 5 Discussion  
Accurately locating the position of false data injection attacks is of great significance for maintaining the stability and security of power systems. By quickly and accurately identifying attack behaviors, effective measures can be taken in a timely manner, thereby reducing potential losses. The method proposed in this paper performs excellently in terms of localization accuracy and response speed, demonstrating outstanding adaptability and robustness. Especially in the simulation experiments on the IEEE 14- and 118-bus test systems, the model achieved F1-scores of 99.71% and 99.10% for localization, respectively, demonstrating superior localization performance compared to existing methods. In the actual deployment process, considerations of computational resources and system compatibility are critical factors. It is essential to continue optimizing the model structure to reduce resource dependencies while maintaining high levels of detection performance.
## 3 Theoretical Framework of Compressed Sensing
### Measurement Matrix  
Given a \(K\)-sparse signal \(x\) with a length of \(N\), and a measurement matrix \(\mathbf{\Phi}\in\mathbb{R}^{M\times N}(M<<N)\), we then calculated the measured value. If \(x\) is sparse, then the measured value could be calculated by \(\mathbf{y}=\mathbf{\Phi}\mathbf{x},y_{j}=\left<x,\phi_{j}\right>\); if \(x\) is non-sparse, then we first performed sparse representation \(\mathbf{x}=\mathbf{\
abla}\mathbf{s}\) and then calculated the measured value, \(\mathbf{y}=\mathbf{\Phi}\mathbf{x}=\mathbf{\Phi}\mathbf{\
abla}\mathbf{s}=\mathbf{\Theta}\mathbf{s}\). Each row of \(\Phi\) can be regarded as a sensor. Part of the information can be picked up by multiplying the signal by \(\mathbf{\Phi}\).  
Figure 2: Compression sensing code block diagram.  
To achieve the reconstruction of signal, [PERSON] and [PERSON] proposed and proved that the sensing matrix \(\mathbf{\Theta}\) should satisfy the restricted isometry property [PERSON] and [PERSON] (1999). For any \(K\)-sparse signal \(v\) and a constant \(\delta_{K}\in(0,1)\), if  
\[(1-\delta_{K})\|v\|_{2}^{2}\leq\|\mathbf{\Theta}v\|_{2}^{2}\leq(1+\delta_{K})\|v\|_ {2}^{2} \tag{2}\]  
is satisfied, then the matrix satisfies the restricted isometry property. [PERSON] et al. proved that if \(\mathbf{\Phi}\) is a Gaussian random matrix, then the sensing matrix \(\mathbf{\Theta}\) can most likely satisfy the restricted isometry property [PERSON] and [PERSON] (1999). Therefore, we can select a Gaussian measurement matrix, with a size of \(M\times N\), to construct \(\mathbf{\Phi}\), in which each value satisfies the independent normal distribution of \(N(0,1/N)\). Some other measurement matrices that can make the sensing matrix satisfy the restricted isometry property include the consistent spherical/ball matrix, the two-value/binary random matrix, the local Fourier matrix, the local Hadamard matrix and the Toeplitz matrix [PERSON] and [PERSON] (1999).
## 2 Materials and Methods
### Turbulent Flow Sub-Model Sensitivity Study
This means that in three-dimensional space, this model requires seven additional transport equations, which account for the streamline curvature, swirl, rotation and rapid changes in strain rate. Due to the nature of the model and the amount of additional equations, this model can be considered computationally expensive, in comparison with k-\(\varepsilon\) modelling. The buoyancy is included in the model as a force (Gij). This model assumes that the value of turbulent Prandtl number is 0.85 [18]. Another popular approach to turbulence modelling in fire safety is so called Large Eddy Simulation (LES) [44]. In this model large eddies of the flow are resolved directly, while small eddies are modelled. The assumption is that small eddies are less dependent on the geometry, tend to be more isotropic--thus may be simulated in a more universal way. The large eddies are usually problem dependent, and since they cannot be modelled universally, they are resolved directly. The boundary between large and small eddies is referred to as the Smagorinsky filter, and typically is the size of the discrete element. Since it is not possible to directly model eddies smaller than the size of the mesh, the solution is more dependent on the grid quality. More to that, in order to properly resolve the flow field the Courant-Friedrichs-Lewy criterion should be satisfied (CFL \(<\) 1), which leads to significant requirements towards the time-scale resolution of the simulation. For a successful use of LES model, it can be assumed that not less than 80% of the energy is resolved [45]. The filter size is applied to the governing equations (especially the N-S equations), while rest of the flow is resolved with a sub-grid model. In the case of this study, LES model was used only for comparison, and as such will not be discussed in details, which may be found in [27; 44]. For the purpose of the choice of the turbulence sub-model, a sensitivity analysis consisting of 8 simulations was performed. Two mixtures were chosen for this study (No. 1 and 2, Table 1). The following turbulent flow submodels were used: (a) standard k-\(\varepsilon\), (b) Realizable k-\(\varepsilon\), (c) Reynolds stress model (RSM) and (d) LES. The sensitivity study focused on the oxygen concentration at the probe, for which the retention time was reached the soonest. For both of the tested mixtures, no major differences were found with the use of different turbulent flow submodels, Figures 5 and 6. The minor discrepancy was found for the RSM model in scenario No. 1, in which oscillatory behaviour was observed. However, the predicted retention time with this model was close to one measured in the experiment. As no major influence of the turbulent flow sub model was found, the most economical sub-model (Realizable k-\(\varepsilon\)) was chosen for the remainder of this study.
## 4 Research Results
### Comparison of Results of Measuring Method UPV and Radiography  
To validate the values measured by ultrasound, a radiographic method was chosen, which is not usable for in situ measurements, but it is a standard method for verifying the discontinuities of materials.  
Figure 12a shows radiography result of the tested Slab A2-2. The final radiogram clearly shows the structure of the wire distribution in the slab. The steel fibers in the slab are distributed homogeneously, areas with locally higher or lower concentration are negligible. Figure 12b shows isovels distribution the SFRC tested slab. It indicates no significant discontinuity in the slab.  
Figure 11: Boxplots of the ultrasonic wave transmission for Slab V3 and all rain levels (r0, r1 and r7).  
Figure 12: The comparison of results of ultrasonic testing method measuring and radiography for Slab A2-2: (**a**) the Slab A2-2, the steel fibers are distributed homogeneously, areas with locally higher or lower concentration are negligible; (**b**) isovels distribution the SFRC tested Slab A2-2. It indicates no significant discontinuity in the slab.  
Figure 13a shows radiography result of the tested Slab A2-3. The final radiogram clearly shows the structure of the wire distribution in the slab. The steel fibers in the slab are distributed homogeneously, areas with locally higher or lower concentration are negligible. The predominant unidirectional orientation of the steel fibers occurs only in the lower part of the slab, as a marginal effect during concreting. Figure 12b shows isovels distribution of the SFRC tested slab. It indicates no significant discontinuity in the slab. The longer transit time of the ultrasonic waves is concentrated in the lower part of the plate, which supports the conclusion from the radiography.  
The final evaluation of fibers scattering homogeneity in testing slabs. Based on the analysis of acquired radiographs and on the basis of measured values using the ultrasonic method, it can be stated that the structure of steel fibers distribution in concrete is very homogeneous in Slabs A2-2 and A2-3, only with slight deviations of locally increased or decreased concentration.