esa-sceva/satcom-chunk-collection huggingface dataset:
# Free Vibration Analysis of Functionally Graded Sandwich Plates with a Homogeneous Core
## 4 Numerical Results
### Free Vibration Characteristics
The volume fraction index, \(n\), and the width-to-thickness ratio, \(b/h\), were set at 1.0 and 10, respectively. The aspect ratio, \(a/b\), was variable; changes to \(a\) were applied, while \(b\) was kept unchanged because the fundamental frequency was calibrated with respect to \(b\), as given in Equation (22). It was found that the calibrated fundamental frequency increased, reversely proportional to the aspect ratio, regardless of the type of core, because the plate became stiffer as the aspect ratio decreased. This effect of the aspect ratio on the calibrated fundamental frequency is well represented in Figure 10a,b. Meanwhile, both softcore and hardcore cases show variations to the thickness, \(H_{1}(=H_{2})\), which are similar to Figure 9a,b, respectively, regardless of the value of the aspect ratio. \begin{table}
\begin{tabular}{c c c c c c c} \hline \multirow{2}{*}{_a/lb_} & \multicolumn{6}{c}{\(H_{1}\)\(-\)\(H_{2}\)\(-\)\(H_{3}\)} \\ \cline{2-7}  & **1-1-1** & **2-2-1** & **3-3-1** & **4-4-1** & **8-8-1** & **16-16-1** \\ \hline \multirow{4}{*}{1} & \multirow{4}{*}{1.60105} & \multirow{4}{*}{1.54583} & \multirow{4}{*}{1.49576} & \multirow{4}{*}{1.45646} & \multirow{4}{*}{1.36884} & \multirow{4}{*}{1.30447} \\  & & & & & & \\ \cline{1-1} \cline{5-7}
0.8 & 2.01452 & & & & & \\ \cline{1-1} \cline{5-7}
0.6 & 2.87617 & 2.78392 & 2.70324 & 2.63834 & 2.49003 & 2.38025 \\
0.4 & 4.70632 & 4.59038 & 4.53748 & 4.50635 & 4.45577 & 4.30833 \\ \cline{1-1} \cline{5-7}  & & & Hardcore & & & \\ \cline{1-1} \cline{5-7}
1 & 1.38588 & 1.43531 & 1.45256 & 1.46875 & 1.49820 & 1.52534 \\
0.8 & 1.76225 & 1.81436 & 1.84618 & 1.86672 & 1.90385 & 1.92563 \\
0.6 & 2.56688 & 2.64136 & 2.68659 & 2.71576 & 2.76846 & 2.79936 \\
0.4 & 4.76499 & 4.89651 & 4.97526 & 5.02593 & 5.11735 & 5.17093 \\ \hline \end{tabular}
\end{table} 
Table 7: _The effect of aspect ratio_ on the calibrated fundamental frequencies, \(\overline{\omega}\), for simply supported FG sandwich plates with homogeneous cores (\(n=1,\ b/h=10\) ). Figure 9: Variation of the calibrated fundamental frequency, \(\overline{\omega}\). to the thickness, \(H_{1}(=H_{2})\), of layers 1 and 2 for: (**a**) softcore cases; (**b**) hardcore cases.
# A Lightweight Method for Detecting Sewer Defects Based on Improved YOLOv5
###### Abstract
If the office technicians cannot judge the videos in a timely manner, maintenance of serious defects may be delayed; thus, researching lightweight models that are suitable for small mobile devices is also of great significance. The single-stage object detection networks, which avoid the drawbacks of two-stage detection networks based on candidate boxes such as slower detection speed, are more suitable for applications that require rapid detection. Among them, YOLOv5 has previously added various improvement strategies to the YOLO series of networks, and can achieve a balance between higher detection accuracy and detection speed, making it the best choice for pipeline defect detection tasks. Therefore, this paper proposes a lightweight model for sewer defect detection, YOLOv5-GBC, by improving the YOLOv5 model. The specific improvements are as follows:  
1. By replacing the backbone network of YOLOv5 with a lightweight network called GhostNet, which is suitable for mobile platforms, the problem of calculating redundancy in traditional convolution methods is solved, greatly reducing the volume and computing power of the model. 2. A new feature fusion network is proposed, which improves the neck network based on the weighted feature fusion and same-scale feature residual connection in the Bidirectional Feature Pyramid Network (BiFPN) [15]. Shallow feature increase is introduced to provide the model with detailed information in images, enhancing the efficiency of feature fusion and the accuracy of detecting tiny defects. 3. By introducing a coordinate attention mechanism [16] to improve the bottleneck modules of the neck network, the model can be made lightweight while achieving higher sensitivity to critical features.
# Cost-Benefit Assessment of 5G Rollout: Insights from Brazil
## 3 5G International Practices
### India  
The study by [13] focuses on the implementation of 5G through the neutral host network (NHN) model in rural India, using network slicing to enhance connectivity. Given India's geographical diversity, which includes mountains, plains, and deserts, providing reliable Internet in rural regions, where about 70% of the population resides, presents significant challenges. The goal is to address the digital divide by offering an economically sustainable solution for 5G deployment in areas where connectivity is limited.  
The study evaluates different deployment scenarios using simulations and cost modeling to estimate capital expenditures and operational expenditures. CAPEX includes the costs of establishing the infrastructure, such as base stations, fiber optics, and backup systems, while OPEX covers recurring costs, such as maintenance, site rentals, and spectrum fees. By optimizing these costs, the NHN model allows different service providers to share the same physical infrastructure, significantly reducing the investment required for 5G deployment in rural areas.  
Network slicing, a key component of this model, segments the 5G infrastructure into virtual slices, each serving different tenants or applications. This segmentation ensures that each slice operates independently, offering customized bandwidth, latency, and security configurations to meet specific customer needs. For example, a rural healthcare service may require low-latency, high-reliability connectivity, while agricultural monitoring might prioritize broader coverage with lower bandwidth.  
The NHN model also relies on a neutral infrastructure provider (InP), which manages the network without offering services directly. The InP ensures that multiple service providers can operate using the same network infrastructure, maximizing efficiency and versatility. This model can reduce CAPEX and OPEX while maintaining high service quality, making the implementation of 5G more viable in rural areas.  
In terms of economic feasibility, the study highlights that regions with lower population densities, such as Dhanushkodi, require more aggressive pricing strategies to be sustainable. However, areas with higher population densities, such as Bandholi and Muddunoor, demonstrate stronger economic viability due to higher demand and easier access to revenue streams.
## 2 Materials and Methods
### Evaluation Metrics and Methodology  
To evaluate each symbolic expression after it was obtained with the GPSC algorithm is to calculate the output values with symbolic expression by providing the inputs of train or test dataset. Then these output values go as inputs into the Sigmoid decision function and the calculated output is compared with real dataset output value to calculate precision, recall, F1-score, and of course Area under curve (AUC) value.
## 3 Pulsed Ion Beams (Protons and Carbon Ions): Laser-Driven Source Features  
Proton and heavy ion therapy are important and efficient sources of therapeutic irradiation on account of the capability for dose localization. Figure 1 illustrates the well-known relative dose of therapeutic irradiation beams as a function of depth in tissue.  
It can be seen that commonly used X-ray beams feature a maximum dose at a shallow tissue depth but continue to deposit energy throughout the X-ray range. On the other hand, the maximum deposition of proton energy is near the end of its range (resulting in the well-known Bragg Peak phenomenon) which can coincide with tumor depth with an appropriate energy choice. Healthy tissue located upstream and downstream of the tumor is less affected by the irradiation. This localization defines the strength and effectiveness of the applied irradiation procedure. Furthermore, carbon ions are biologically more effective and feature improved dose localization over protons such that healthy tissue is better spared. For example, Figure 1 shows that, for a tumor located about 32 cm into the body, the dosage would be maximized using 200 MeV protons while the dosage to healthy tissue would be significantly reduced compared to that from an X-ray beam.
## 3 System Model and Problem Formulation
### Network Model
As the paper focuses on video retrieval, this paper considers only the downlink EPFD. The scenario particularly involves interference signals from a LEO satellite captured at a GEO ground station. For each GEO ground station \(j\), the EPFD value must adhere to the following constraint. These ground stations, which are equipped for both transmitting to and receiving from GEO satellites, are denoted by \(j\in\mathcal{J}_{geo}\). \[EPFD_{j}\leq EPFD_{thr},\quad\forall j\in\mathcal{J}_{geo} \tag{2}\]  
User terminals connect to network nodes via wireless links, enabling communication between users and the network, with all communication routed through access points. In this paper, the wireless access points are referred to as edge base stations \(j\), where users access the resource network by connecting through these base stations to acquire the desired video files. For the wireless network system, define the binary control variable \(x_{mj}\in\{0,1\}\), indicating the connection status between user \(m\) and base station \(j\). If \(x_{mj}=1\), user \(m\) has chosen base station \(j\) as their wireless access point; if not, then \(x_{mj}=0\). In contemporary mobile networks, a user typically connects to a single wireless access point. Thus, the following constraint enforces the user's selection of an access base station:  
\[\sum_{j\in\mathcal{J}}x_{mj}=1,\quad\forall m\in\mathcal{M} \tag{3}\]  
Each user is limited to a single connection to an access point; therefore, any video stream data intended for user \(m\) must initially be delivered to the access base station \(j\) linked to user \(m\). From there, it is relayed by base station \(j\) directly to user \(m\). Consequently, the wireless link between the user and the access base station is tasked with conveying the user's entire video data stream. This situation gives rise to specific traffic limitations for the wireless links:  
\[\sum_{\mathbf{p}_{mn}^{k}\in\mathcal{P}_{m}}a_{mj}r_{mn}^{k}=x_{mj}\sum_{g=1}^{ C}z_{gm}v_{g},\quad\forall m\in\mathcal{M},j\in\mathcal{J} \tag{4}\]  
where \(a_{mj}\) signifies whether the data stream utilizes the path from base station \(j\) to user \(m\). If this path is utilized, then \(a_{mj}=1\); otherwise, \(a_{mj}=0\). This connectivity constraint secures the full route for the video data stream from the service node to the user, ensuring that user \(m\)'s video data stream is sent to the access base station before being delivered to the user itself.
# Low-Cost Goethite Nanorods for As (III) and Se (VI) Removal from Water
## 3 Results and Discussion
### Adsorption Experiments of As(III) and Se(VI)  
The analysis of FTIR (Figure 2b) displayed functionalized surfaces while XRD results (Figure 2a) expressed the channel-like structure. In contrast, the analysis of PZC revealed exothermic surfaces and low adsorbent-adsorbate attraction forces suggesting weak and slow adsorption, which is a common phenomenon for goethite [33; 34; 35]. However, the nano-sized rods could provide a large surface area in contact with adsorbate ions. This evidence is fundamental for strong binding ligand uptake and substitutions with As(III) and Se(VI) ions. Furthermore, adsorption isotherms were implemented to eventually explain the nature of adsorbent-adsorbate physiochemical interactions. Of note, the base lines of heavy metal intensity were selected for As and Se, as per the WHO standards of drinking water at 10 and 40 ug/L, respectively. What's more, the removal efficiency (Removal (%)) was employed to present the adsorption data of goethite adsorbent according to Equation (3).  
\[Removal\ (\%)=\ \frac{(C_{o}-C_{e})}{C_{o}}\times 100\% \tag{3}\]  
where \(C_{o}\) and \(C_{e}\) (ug/L or ppb) are the initial and equilibrium concentration of As(III) or Se(VI) in aqueous solution, respectively.
## 3 Results and Discussion
### PXRD Analysis
The Vat sample, while poor in quartz, contains olivines (fayalite) and wustite which indicate that this slag originated most probably from smithing operations. The differences of the PXRD evidenced mineral content, in accordance with the PXRF and ICP-MS determined elemental compositions suggest that the iron-workers operant at the three different archaeological sites probably used different technologies. The majority of the finds seems to be a primary smithing slag [26]. The amount of the quartz present (acting as flux) is indicative that, at the site, bloom refining probably took place. Silica sand rich soils were added to the smithing hearth, possibly associated with other fluxes, in order to reduce the melting point of the slag, making it easier to squeeze out [6]. Removal of the slag became easier, also increasing the smithing hearthtemperature; the presence of more considerable quantities of cristobalite in the Brancovenesti slags suggests processing (slag formation) temperatures from 900 \({}^{\circ}\)C to 1200 \({}^{\circ}\)C [27]. The iron oxides are indicators of the redox conditions at the time of the slag solidification. The appreciable amount of goethite, a typical weathering mineral formed by wustite oxidation during burial, indicates mildly reducing conditions. Presumably initially wustite was the most frequent oxide phase, with minor amounts of magnetite (partially transformed into haematite) [28; 29]. Figure 2: X-ray diffractograms of selected samples. Samples 4137, 4264 are from the Calugäreni (_vicus_) site; 9487, 9445, and 9454 from Bräncovenesti, the _retentura_; sample Vat is from Vätava, _East of the tower_ location. The mineral components notation: Q—quartz; G—goethite; A—analcine; M—magnetic; C—cristobalite; H—hedenbergite; Cl—clinoclase; D—dolomite, W—wüstite.
## 2 Connectivity in Colombia
### Territorial Dynamics in Ovejas and Chalan Municipalities, Sucre, Colombia  
Colombian Caribbean territory known as Montes de Maria is historically recognized for its organizational capacity. This is corroborated by Commerce Chamber data that registers in the subregion 261 organizations classified as associations, cooperatives, corporations, and foundations [17].  
Ovejas and Chalan municipalities are part of the 15 municipalities that make up Montes de Maria subregion [18], territories, where in 2020, a backhaul telecommunications network was installed in the townships of La Pena, La Ceiba, the village of Almagra, and the municipal seat of Chalan. The objective of this network was to strengthen the organization's capacities from different actions, one of them the digital divide reduction [19]. In Ovejas and Chalan municipalities, the Internet connection is below department and country average. In 2019, broadband penetration in Ovejas and Chalan was 2.67% and 0.14%, respectively, while in the Sucre department, broadband penetration was 5.94% and 48.8% for Colombia [20; 21].  
On the other hand, demographic and population dynamics associated with post-conflict and the peace agreements implementation processes cause permanent civilian population displacements, generally not premeditated, from and to townships within the Montes de Maria. This floating population modifies the coexistence and work relationships and, therefore, continuously transforms the social and economic dynamics of the communities, making it difficult to create and continue social programs oriented toward inclusion and territorial integration [22; 23]. Thus, it is necessary to propose non-traditional or alternative sources of population data complementary to main sources (population census, surveys, and vital statistics) that ideally deliver reliable results in short periods of time and that allow instant and indirect measurement of population data from rural and hard-to-reach areas [24].  
According to Unified Victims Registry (RUV--Registro Unico de Victimas) [25], in the 1990s and 2000s, these territories were greatly affected by the armed conflict, which left between 82% and 85% of the population as armed conflict victims. According to the National Administrative Department of Statistics (DANE--Departamento Administrativo Nacional de estadisticas) 2020 projections, Ovejas will have a population of 20,806 inhabitants (urban 12,067 and rural 8739). For its part, Chalan will have a population of 4431 inhabitants (2792 live in the municipal seat and 1639 in rural areas) [26].  
Ovejas and Chalan territories are part of Colombian 170 municipalities where Development Plans with a Territorial Approach are implemented, whose conception promotes the closing of rural-urban gaps [27]. By 2028, Montes de Maria projects to be an innovative territory leader in agroecological production, with community tourism development and an educated, organized, and empowered population that fosters peasant participation and autonomy [5].
# A Multisensor Approach to Satellite Monitoring of Trends in Lake Area, Water Level, and Volume
## 1 Introduction
### Background: Remote Sensing of Lake Hydrology
The upcoming Surface Water and Ocean Topography (SWOT) satellite mission, scheduled for launch in 2021, will provide lake area and water level measurements from its Ka and Ku band radars, providing further support for remote sensing of changes in lake volume [36; 37]. This objective has also been accomplished by combining remotely sensed images of lake area with water level estimates from a pre-existing digital elevation model (DEM) [38; 39]. Other remote sensing methods for monitoring dynamics of water storage in lakes, wetlands, and other aquatic systems include the use of interferometric radar (InSAR) or satellite gravimetry. InSAR can be used to estimate water levels by analysis of double-bounce returns from the stems of inundated vegetation [40; 41], due to the high interferometric coherence from these features, in contrast to the low coherence from open water. Alternatively, changes in water storage can be inferred from InSAR measurements of the displacement (uplift or subsidence) of the terrain surrounding large lakes [42]. Satellite gravimetry, using systems such as the Gravity Recovery and Climate Experiment (GRACE) or Gravity field and steady-state Ocean Circulation Explorer (GOCE), has been widely used to infer regional- to continental-scale changes in hydrology, due to the impact of changes in the mass of water in groundwater [43; 44] and surfacewater systems [45; 46] on the regional gravitational field. Recently, GRACE gravity data have been successfully shown to be capable of providing estimates of hydrologic change in finer-scale systems, such as individual lakes, via a modeling approach to downscale the regional GRACE signal, with results that match those from radar altimetry [47]. The study area for this work (the Toshka or Tushka Lakes in southern Egypt) has been the setting for several prior investigations using satellite remote sensing to monitor changes in lake hydrology. The methods and results of those prior studies will be discussed in Section 1.2 below. Following that,in Section 1.3, the dual objectives of this work are presented: First, to demonstrate and evaluate a set of methodological improvements that enable the construction of a fully-automated system for monitoring changes in surface area, water level, and volume in lakes; and second, to use this system to document the history of the Toshka Lakes at a higher temporal resolution and more rigorously and completely than previous studies.
## 4 Experimental Results and Discussions
### More Discussion on Computation Time  
Generally speaking, intelligent heuristic algorithms are more time consuming than other algorithms. On the other hand, computation time of heuristic algorithms normally depend on some measure of problem size, such as the number of cities in TSP problem. As you can see from Figure 9, CPU time consumed by BBO algorithm is increasing linearly and this conclusion is equally applicable to OBBO and ROBBO algorithms.  
Eight sets of computation time and sizes of TSP problem are carried out by least square method. The fitting results of all tested algorithms are given in Table 5. Herein relative error in the third row is the mean of differences between fitted value and experiment result and it can be defined as following  
\[Relative\ error=\sum_{i=1}^{num}\frac{CT_{fi}^{i}-CT_{exp}^{i}}{CT_{exp}^{i}} \tag{6}\]  
where \(CT_{exp}^{i}\) and \(CT_{fi}^{i}\) are the experiment result and fitted value for the \(i\)th benchmark problem, and \(num\) is the number of benchmark problems.  
It can be seen from Table 5 that the relative fitting errors of BBO, OBBO and ROBBO algorithms are maintained at moderate rate around 0.2% to 0.3%.  
At the same time, it is unfortunate that the computation time of our proposed algorithm is a bit different from the three mentioned above. As can be seen from Figure 9, its computation time is  
\begin{table}
\begin{tabular}{c c c} \hline
**Algorithm** & **Fitting line** & **Relative error (\%)** \\ \hline BBO & \(0.26351x+2.6561\) & \(0.26629\) \\ OBBO & \(0.20365x+2.2008\) & \(0.21228\) \\ ROBBO & \(0.20297x+2.1265\) & \(0.21109\) \\ COOBBO & \(1.04751x-49.2515\) & \(15.4708\) \\ \hline \end{tabular}
\end{table}
Table 5: Fitting results of BBO, OBBO, ROBBO and COOBBO algorithms.  
Figure 9: Comparison of computation time of BBO, OBBO, ROBBO and COOBBO algorithms.  
increased with expedition from 26s for 52 cities to 298s for 318 cities. If we fitted the experiment results by the same method, its relative error is around 15%, which is close to 60 times more than other algorithms. Therefore, we are not sure that the linear fitting is still effective to COOBBO algorithm, and then we surmise that it may be increased exponentially with the increase of the size of the TSP problem. Of course, the inference should be proved or falsified by more experiments in the future. Typically, the main reason for so much time of the COOBBO algorithm is the calculation of Euclidean distance between cities in the produce of forming opposite path.