esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Problem Formulation and Objectives
### Objective Model on Resource Management  
In our proposed approach, MEC is leveraged to conduct assessments of resource management and orchestration for the priority of IIoT tasks. MEC provides resource capability and indicates stringent requirements. We aim to minimize energy consumption by leveraging MEC to provide accommodation for NFV to instantiate virtual machines (VM) and adjust and reconfigure the resource capacity of utilizations. In addition, VM minimizes resource utilization over the MEC server, ensuring the efficiency of VNF deployments and enhancing computation. Where \(R_{n}\) denotes resource requirements of task-\(n\), \(P_{v}\) denotes processing power required by VNF in the MEC server and \(U_{v}\) is the utilization of VNF-\(v\).  
\[\underset{[H_{n,m},S_{n}]}{\text{min}}\underset{[H_{n,m},S_{n}]}{\text{sum}} \underset{m\in M}{\sum}\left(\frac{\sum_{i\in I}\underset{m\in N}{\sum}S_{n}^{ i}\cdot R_{n}}{C_{mcc}}+\frac{\sum_{v\in V}P_{v}\cdot U_{v}}{C_{mcc}}\right) \tag{8}\]  
Subject to  
\[\sum_{i\in I}\underset{m\in N}{\sum}S_{n}^{i}\cdot R_{n}+\sum_{v\in V}P_{v} \cdot U_{v}<X_{mcc},\;\forall m\in M \tag{9}\]  
\[\sum_{i\in I}\underset{m\in N}{\sum}S_{n}^{i}\cdot D_{n}<B_{m},\;\forall m\in M \tag{10}\]  
\[\sum_{m\in M}S_{n}^{i}\cdot C_{mcc}^{n,m}<L_{max},\;\forall n\in N \tag{11}\]  
\[\sum_{v\in V}P_{v}\cdot U_{v}<C_{max},\;\forall m\in M \tag{12}\]  
\[E_{local}^{i}\cdot L_{n}^{i}+\sum_{m\in M}E_{off}^{n,m}S_{n}^{i}\leq E_{max}, \;\forall i\in I \tag{13}\]
# Comparative Impact Analysis of Cyclone Ana in the Mozambique Channel Using Satellite Data
###### Abstract  
There is still insufficient information available for a streamlined impact assessment of tropical cyclones on coastal habitats, particularly in the Mozambique Channel. Using Sentinel-1 and Sentinel-2 data, along with socio-ecological parameters including mangrove forest health and population density, we modeled the extent of flooding and its impact following the'severe tropical storm' Ana which occurred between the 20 January until 25 January over the Mozambique Channel. Focusing on regions hit by Ana, namely the Sofala and Zampezia regions and the Boeny and Melaky provinces in Mozambique and Madagascar, respectively, we adapted a model by the United Nations Platform for Space-Based Information for Disaster Management and Emergency Response (UNSPIDER) to effectively assess storm impacts at a resolution of up to 10 m. Our results showed that in Mozambique, more than 195,977 people have been potentially affected by Ana, while in Madagascar this number was down to 79,003. The central region of Zampezia accounted for the majority of flooding occurrences, although the Boeny province accounted for most of the flooding as a proportion of its total area. The Sofala region of Mozambique displayed the highest-affected population and highest-affected urban area, with 108,400 exposed people. However, it was found that only a small proportion of affected areas in all regions of interest (ROIs) were urban areas, accounting for 1.4% of the flooded areas on average. Low mangrove normalized-difference vegetation index (NDVI) changes between before the 2021-2022 cyclone season were found throughout all ROIs, despite the appearance of degraded mangrove patches in the proximity of barren areas at a fine scale (<20 m). Finally, it was found that healthy mangrove forest ecosystems in the Mozambique Channel were effective in protecting highly populated areas from cyclonic events for up to 40 km, on average.  
impact analysis; tropical cyclone; Mozambique; mangrove; satellite data +
Footnote †: journal: Applied Sciences
_Applied_  
_sciences_  
_Article_  
**The Use of a Two-Dimensional Electrical Resistivity Tomography (2D-ERT) as a Technique for Cadmium Determination in Cacao Crop Soils**  
**[PERSON] 1,*\({}^{\copyright}\) and [PERSON] 2**  
1 Laboratory of Soil Microbiology and Calorimetry, Corporacion Colombiana de Investigacion Agropecuaria -AGROSAVIA, Centro de Investigacion Tibaitata\(-\)Km 14, Via Mosquera-Bogota, Mosquera CO-0571, Colombia  
2 Laboratory of Physics, University of Narino, Pasto CO-0572, Colombia;[EMAIL_ADDRESS]  
*Correspondence: [EMAIL_ADDRESS]; Tel.: +57-(1)-4227300 (ext. 1413)  
Received: 9 May 2020; Accepted: 11 June 2020; Published: 17 June 2020  
**Featured Application: This study provides new insights into the methodologies to pursue cadmium detection in cacao soils during field tests. This is critical as a first step to produce cocoa that conforms to the European Union and _Codex Alimentarius_ regulations, regarding permissible Cd content in products derived from cocoa beans. Thus, the use of the 2D-ERT technique represents a diagnostic methodology to recognize the distribution of cadmium in the soil of cacao growing farms, including both topsoil and subsoil boundaries.**  
**Abstract:** Cadmium (Cd) is a non-essential heavy metal naturally occurring in the earth's crust or due to anthropogenic activity. The presence of this metal in cacao farm soils represents a significant issue as levels are now regulated in products derived from cacao beans (_Theobroma cacao_ L.). Several strategies have been proposed to measure cadmium levels; however, little is known regarding in situ non-destructive and time efficient techniques to analyze Cd contents in both cacao toposils and subsoils, particularly nearby the root system. Therefore, this research aims to integrate the physical property of soil resistivity to Cd content in cacao soils. Cd hot spots are estimated from resistivity measurements using a two-dimensional electrical resistivity tomography (2D-ERT) technique and correlated to Cd determination using inductively coupled plasma optical emission spectrometry (ICP-OES). To assess the dynamics of soil Cd content the correlation is discussed with other physical chemical parameters of soils (pH, organic matter, Ca, Fe, and P). The study was performed in 27 cacao farms in Colombia. A farm in Santander district proved to have the highest level of Cd using the correlated techniques (2.76 mg\(\cdot\)kg\({}^{-1}\) Cd and 1815 Ohm\(\cdot\)m) followed by farms in Boyaca and Arauca districts (2.6 and 0.66 mg\(\cdot\)kg\({}^{-1}\) Cd, related to 1616 and 743 Ohm\(\cdot\)m, respectively). A high correlation between 2D-ERT and Cd determination (R\({}^{2}\) = 0.87) was found. The discussion regarding the soil parameters analyzed suggests that the 2D-ERT technique could be used as a preliminary approach to explore Cd distribution in cacao soils.  
**Keywords:** cadmium; cacao; two-dimensional electrical resistivity tomography (2D-ERT); ICP-OES; phosphorus (P); soil organic matter (SOM)
## 3 Matrix-Based Establishment of Mathematical Model
### Matrix-Based Description of Topological Relationships between Components
#### 3.1.2 Interference Matrix  
The interference matrix is a tool to express the layout interference and degrees of freedom during assembly in a matrix format. [PERSON] et al. [37] proposed a method to generate a homologous moving wedge with the interference matrix. Firstly, they defined the problem: let \(P=\{p_{1},p_{2},p_{3},\ldots,p_{n}\}\) denote the set of parts of an assembly \(A\). Then they defined a set of valid assembly directions for each pair of \((p_{i},p_{j})\) as a moving wedge [38] of \(p_{i}\) to \(p_{j}\), denoted by \(MW(p_{i},p_{j})=\{d_{+x},d_{-x},d_{+y},d_{-y},d_{+z},d_{-z}\}\), where:  
\[d_{*}=\left\{\begin{array}{ll}1,\text{ if }p_{i}\text{ can be assembled together in direction }*\\ 0,\text{ otherwise}\end{array}\right. \tag{3}\]  
When assembling prefabricated wall components, the interference along the directions of \(+z\) and \(-z\) can be ignored. A hidden premise of \(MW(p_{i},p_{j})\) is that component \(j\) is assembled before component \(i\), and component \(j\) is connected to component \(i\). If component \(i\) and component \(j\) have no connection relationships, the elements in \(MW(p_{i},p_{j})\) are all zero. From a computer-friendly perspective, dividing the moving wedge into four interference matrices corresponding to four directions is better. Table 2 and Figure 2, respectively, list the moving wedge and interference matrices of the example in Figure 1.  
Figure 1: An example of linking graph and adjacency matrix. (**a**) The BIM model of three walls; (**b**) The plan view of three walls; (**c**) The linking graph of three walls; (**d**) The adjacency matrix of three walls.  
Based on the classified discussion of the relative position between two components, such as the coordinate, length, and extension direction of walls, the interference matrix is easy to obtain.
## 2 Materials and Methods  
ZnO, B\({}_{2}\)O\({}_{3}\) and SLS are the main source of raw material for this preparation. The SLS glass waste was crushed to produce glass powder and ground into 45 \(\upmu\)m powder. Then, the SLS glass powder was mixed with ZnO and B\({}_{2}\)O\({}_{3}\) powder by following the composition mixture of 55 ZnO-5B\({}_{2}\)O\({}_{3}\)-40 SLS in weight percent. A mixed sample of 30 g was poured into a high purity alumina crucible (controltherm Sdn. Bdh., Malaysia) with dimensions 45 mm top diameter \(\times\) 50 mm height, and then heated through the melting process at 1350 \({}^{\circ}\)C for 3 h. The melted sample was then poured immediately into a container filled with water in order to produce glass frits. The glass frits sample obtained after the fast quenching process is highly transparent with no bubbles. The crushing, grinding and sieving processes were repeated on the glass frits to form a fine glass sample powder with a particle size of less than 45 \(\upmu\)m for the pelleting process. The powder was mixed with polyvinyl alcohol (PVA) as a binder and pressed into a specific shape using a hydraulic press machine to form 13 mm diameter glass pellets. The solid pellets were then subjected to the heat-treatment process at 600, 700, 800 and 900 \({}^{\circ}\)C for 2 h with a 10 \({}^{\circ}\)C/min constant heating rate. Then, the sample was characterized by using densimeter and vernier caliper measurements, and X-ray diffraction (XRD) (PW 3040/60 model, Philips, San Jose, CA, USA), Fourier transform infrared reflection (FTIR) (Spectrum 100 model, Perkin Elmer; Waltham, Massachusetts,USA), ultraviolet-visible (UV-Vis) (UV-3600 model, Shimadzu, Kyoto, JAPAN) and photoluminescence (PL) (LS 55 model; Perkin Elmer; Waltham, Massachusetts, USA) spectroscopic techniques.  
In the electronic densimeter, the conventional Archimedes' principle was applied to measure the density of the pallet sample. In this measurement, 50 mL of plain distilled water was utilized as the buoyancy liquid. In addition, the XRD measurement (PANalytical X'pert PRO, PW3040 model) in the range of 20\({}^{\circ}\) to 80\({}^{\circ}\) of 20 was used to confirm the amorphous phase of the precursor glass and identify the crystal growth in the glass-ceramic sample. The FTIR absorption spectra of glass and glass-ceramic sample were measured in the range 400-1400 cm\({}^{-1}\) using a Perkin Elmer Spectrum, 100 series model spectrometer, equipped with universal attenuated total reflectance (ATR). The UV-3600 UV-Vis-NIR spectrophotometer was exploited to identify the optical absorption and reflectance. These data were used to estimate the optical band gap of the sample in the wavelength range 400-800 nm using Kubelka-Munk (K-M) theory. Lastly, the photoluminescence excitation and emission spectra of the glass and glass-ceramic sample were measured using a Perkin Elmer, LS 55 model fluorescence spectrometer in the range of 450 to 600 nm.
# A Quantum-Resistant FHE Framework for Privacy-Preserving Image Processing in the Cloud
## 2 Threat Model and Security Guarantees
### Adversary Model  
We consider a realistic client-server model with two distinct adversaries, whose capabilities are standard in the cloud security literature [17]:  
1. The Network Adversary (\(\mathbf{\mathcal{A}}_{\textit{net}}\)): This is an active attacker who has full control over the communication channel between the client and the cloud server. \(\mathcal{A}_{\textit{net}}\) can read, inject, modify, and delete any packets. We assume that this adversary is computationally bounded but may have access to a large-scale quantum computer, enabling them to run algorithms like [PERSON]'s algorithm [2].
2. The Cloud Server Adversary (\(\mathbf{\mathcal{A}}_{\textit{cloud}}\)): This adversary represents an untrusted cloud provider. We model it as an honest-but-curious (or semi-honest) adversary. The server is \"honest\" in that it correctly follows the prescribed computational protocols. However, it is also \"curious,\" meaning that it will attempt to deduce as much information as possible about the client's data from all information that it observes, including ciphertexts, access patterns, and memory states [18; 19].
# An Overview of Lidar Imaging Systems for Autonomous Vehicles
## 3 Sources and Detectors for Lidar Imaging Systems in Autonomous Vehicles  
Lidar systems illuminate a scene and use the backscattered signal that returns to a receiver for range-sensing and imaging. Thus, the basic system must include a source or transmitter, a sensitive photodetector or receiver, the data processing electronics, and a strategy to obtain the information from all the target, essential for the creation of the 3D maps and/or proximity data images. We have just discussed the main imaging strategies, and the data processing electronics used are usually specialized regarding their firmware or code, but there is not really a choice of technology specific for lidar for these components in general. Data processing and device operation are usually managed by variable combinations of field programmable gate arrays (FPGAs), digital signal processors (DSPs), microcontrollers or even computers depending on the system architecture. Efforts oriented to dedicated  
\begin{table}
\begin{tabular}{p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt}} \hline \hline  & **Mechanical** & **MEMS** & **OPAs** & **Flash** & **AMCWs** \\  & **Scanners** & **Scanners** & & & \\ \hline Working principle & Galvos, rotating mirrors or prisms & MEMS micromirror & Phased array of antennas & Pulsed flood illumination & Pixelated phase meters \\ \hline Main advantage & 360 deg FOV in horizontal & Compact and lightweight & Full Solid State & Fast frame rate & Commercial \\ \hline Main disadvantage & Moving elements, bulky & Laser power management, linearity & Lab-only for long-range & Limited range/Blindable & Only indoor range/Blindable \\ \hline \hline \end{tabular}
\end{table}
Table 2: Summary of imaging strategies.  
chipsets for lidar are emerging and have reached the commercial level [86], although they still need of dedicated sources and detectors.  
Thus, we believe the inclusion of a dedicated section to briefly review the particularities of sources and detectors used in lidar imaging systems is required to complete this paper. Due to the strong requirements on frame rate, spatial resolution and SNR imposed to lidar imaging systems, light sources and photodetectors become key state-of-the-art components of the unit, subject to strong development efforts, and which have different trade-offs and performance limits which affect the overall performance of the lidar setup.
# Understanding Consumer Acceptance for Blockchain-Based Digital Payment Systems in Bhutan
## 6 Discussion
### Theoretical Contributions  
This paper provides a significant contribution as it is one of the first works to explore consumer acceptance of blockchain-based digital payments in Bhutan, addressing a crucial gap in academic research. Previous research [35; 78] has examined blockchain adoption, but this study uniquely applies the UTAUT model in a developing economy with unique socio-cultural and infrastructural conditions. The research expands current technology acceptance frameworks by providing empirical evidence from Bhutan's developing digital landscape. The most significant finding of this study reveals that performance expectancy acts as the primary factor in motivating consumer acceptance in Bhutan. These research findings are consistent with previous studies by [35; 80; 82] where performance expectancy stands out as a vital factor in adopting blockchain technology and digital financial services. Contrary to [PERSON] et al.'s [79] findings regarding performance expectancy's negative effect on cryptocurrency adoption, this study shows that performance expectancy is a key factor for Bhutanese consumers in blockchain-based payment systems.  
Effort expectancy and facilitating conditions serve as essential drivers for acceptance by highlighting the importance of usability aspects together with digital literacy and technological infrastructure. These findings align with [PERSON] et al. [78] and [PERSON] et al. [35], supporting the view that ease of use and robust infrastructure are essential elements for successful adoption. However, [PERSON] et al. [84] refute that effort expectancy, together with performance expectancy, does not significantly drive blockchain adoption while demonstrating that these factors' effects may vary based on the context. Bhutanese consumers' acceptance of blockchain-based digital payments is significantly influenced by social factors, which include cultural norms as well as peer recommendations and institutional trust. The study by [PERSON] [80] and [PERSON] et al. [82] recognized social influence as a major factor in driving blockchain and neobank adoption, which is supported by the findings of this paper.
## 3 System Model
### Time Division Duplexing and Multiplexing  
As was stated previously, due to the utilized TDM scheme, not all the links can be activated simultaneously. We assumed that, at each time instant, each network antenna sector can be in one of the following states:  
1. Transmitting to a network node (transmit backhaul);
2. Receiving from a network node (receive backhaul);
3. Transmitting to associated UEs (transmit access);
4. Receiving from associated UEs (receive access).  
Furthermore, in order to limit self-interference, we assumed that, at each time instant, all sectors of the same node can either all transmit or receive. For example, at a time  
Figure 4: Queuing network representation of an IAB-node.  
in a node \(n\), Sector 1 can be _receiving backhaul_ and Sectors 2 and 3 _receiving access_, while at a time \(t=t_{2}\), all sectors can be _transmitting access_.  
In order to activate access links and transmit packets from the access buffers, it suffices that the corresponding sector goes into states _transmit access_ or _receive access_. Thus, e.g., as soon as a sector \((n,i)\) enters state _receive access_, all the content of the sector's inbound access buffer reaches node \(n\), and furthermore, any packet joining this buffer while the sector is in the _receive access_ state goes straight to node \(n\).  
To activate a backhaul link, however, coordinated actions of two connected sectors are required: one has to _transmit backhaul_ and the other to _receive backhaul_. Going back to Figure 3, the backhaul link between Nodes 1 and 2 is activated for downlink transmission (from Node 1 to Node 2) whenever Sector \((1,3)\) is _transmitting backhaul_ and Sector \((2,1)\) is _receiving backhaul_. During this time, all packets from the backhaul buffer in Sector \((1,3)\) instantaneously move to Node 2. Similarly, the backhaul link between Nodes 2 and 3 is activated uplink if Sector \((3,2)\) is _transmitting backhaul_ and Sector \((2,2)\) is _receiving backhaul_. If in a given topology, a sector is not used for backhaul, its feasible states are _transmit access_ and _receive access_, since being in states _transmit backhaul_ and _receive backhaul_ would not result in any link activation.
## 4 Illustrative Example of Proposed Method
### Determination of the Optimal Wavelet Basis  
The main challenge in using wavelet transform is selecting the optimal wavelet basis, as different wavelet bases applied to the same signal may produce different results. Traditionally, the wavelet basis functions are usually subjectivity selected by multiple attempts and comparisons, an approach which lacks a quantitative evaluation index. Based on the proposed method in Section 2.4, different wavelet families are applied to decompose the concrete strain data in different months at ten layers, and SI values are calculated and shown in Table 3. The results show that the order of SI value of the wavelet basis is stable among different months, indicating that the quality of the wavelet basis is  
Figure 5: Display of data noise level based on the 38 criterion (signal before noise removal). determined by the characteristics of the signal. Specifically, for concrete strain data, the performance of dbN, symN and coifN wavelet families is obviously better than that of biorNr.Nd and rbioNr.Nd wavelet families. By summing the rankings of all wavelet bases in four months, sym12 is determined as the best wavelet basis and bior3.1 is the worst wavelet basis for concrete strain signals. Figure 6 shows their results when the decomposition layer is 10. The amplitude of the detail coefficient of each layer of the best wavelet basis is low. It can be seen from the approximate coefficient A10 that the better wavelet basis can better retain the characteristics of the original signal and separate the noise. In Figure 6, it is also clearly shown that sym12 is better than bior3.1 at almost every decomposition level, so the results are that the reconstructed signal after denoising by sym12 is closer to the original signal. This shows that the proposed SI index is effective for selecting the optimal wavelet basis.
# Application of a Hybrid Model in Landslide Susceptibility Evaluation of the Western Tibet Plateau
## 2 Materials and Methods  
### Study Area  
The study area is located in the Zada basin, the west of the Tibetan Plateau; it belongs to the North Himalayan Tethys sedimentary zone. It lies in the junction zone of Himalayan land mass and Brahmaputra River. Between 78\({}^{\circ}\)15\({}^{\prime}\)-79\({}^{\circ}\)00\({}^{\prime}\) E and 32\({}^{\circ}\)20\({}^{\prime}\)-32\({}^{\circ}\)40\({}^{\prime}\) N, the total area covers 2600 km\({}^{2}\) (Figure 1). It lies in a typical alpine canyon landform, an elevation ranging from 3869 to 6357 m, with most peaks more than 5000 m above sea level. It belongs to the typical alpine canyon landform and it is mainly composed of hilly landforms and deep canyon forming bytectonic faults. The only river is Pali river, which flows through the urban area from NW to SE with elevation between 3000 and 3800 m. This area has cold and dry climatic conditions. The mean annual temperature is between 0 and 3 \({}^{\circ}\)C with an annual precipitation of 200 mm. The maximum summer temperatures reach above 21 \({}^{\circ}\)C, whereas winter temperatures can be lower than \(-41\)\({}^{\circ}\)C. The rock strata in the study area are mainly in the Holocene Series, Pleistocene Series, Selong Group and Cailiqun Group, and the rock types are mainly soil, gray and purple gray mesobioclastic micrite, carbonate rock (limestone, oolitic limestone, biological limestone) mainly composed of sand-shale assemblages. The rock structure is mainly block structure. Due to the special geographical  
Figure 1: Location of study area and landslide inventory.  
and geological conditions of the region, it is of great importance to carry out disaster risk assessments, and it is also a good area for conducting high-altitude research.