esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results  
The mean age of the participants was 24 years old, ranging between 19 and 38 years. A total of 77.1% of the sample presented normal BMI, while 22.9% of the sample was overweight. The average PA level of the participants ranged between moderate and high. Only 11.4% presented a low PA level, 48.6% presented a moderate PA level, and 40% presented a high PA level. The average MV was 271 mL, ranging between 22.51 and 1112.12 mL. The implants of 220 mL, 315 mL, and 365 mL represented an average of 0.71 \(\pm\) 0.07%, 1.01 \(\pm\) 0.11%, and 1.18 \(\pm\) 0.12% of the participant's total body weight, respectively. This study included only three left-handed women. In terms of resting and dynamic scapular positions, most participants presented type IV (symmetrical scapulohumeral), followed by type II (prominent medial border) scapular positions. Descriptive statistics for sample characterization are presented in Table 3.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Variable** & **Mean** & **SD** & **Min** & **Max** \\ \hline Age (years) & 24.03 & 4.08 & 19 & 38 \\ MV (mL) & 270.46 & 259.18 & 22.51 & 1112.12 \\ BMI (kg/m\({}^{2}\)) & 22.78 & 2.29 & 18.66 & 27.65 \\ \hline \multicolumn{5}{c}{N} & \multicolumn{3}{c}{\%} \\ \hline Normal Weight (18.5-24.9 kg/m\({}^{2}\)) & 27 & & 77.1 & \\ Overweight (25.0-29.9 kg/m\({}^{2}\)) & 8 & & 22.9 & \\ \hline \multicolumn{5}{c}{Mean} & SD & Min & Max \\ \hline IPAQ Total Score (MET/week) & 3048.37 & 3180.86 & 0 & 14,154 \\ \hline \multicolumn{5}{c}{N} & \multicolumn{3}{c}{\%} \\ \hline Low PA (<600 MET-min/week) & 4 & & 11.4 & \\ Moderate PA (600–3000 MET-min/week) & 17 & & 48.6 & \\ High PA (>3000 MET-min/week) & 14 & & 40.0 & \\ \hline \multicolumn{5}{c}{Mean} & SD & Min & Max \\ \hline Body\%implant220 (\%) & 0.71 & 0.07 & 0.57 & 0.87 \\ Body\%implant315 (\%) & 1.01 & 0.11 & 0.82 & 1.24 \\ Body\%implant365 (\%) & 1.18 & 0.12 & 0.94 & 1.44 \\ \hline \multicolumn{5}{c}{N} & \multicolumn{3}{c}{\%} \\ \hline Right-handed & 32 & & 91.4 & \\ Left-handed & 3 & & 8.6 & \\ Type I Scapular Dyskenisis & 2 & & 5.7 & \\ Type II Scapular Dyskenisis & 12 & & 34.3 & \\ Type III Scapular Dyskenisis & 1 & & 2.9 & \\ Type IV Scapular Dyskenisis & 20 & & 57.1 & \\ \hline \hline \end{tabular}
\end{table}
Table 3: Mean, standard deviation (SD), minimum (Min) and maximum (Max) of age, MV, BMI, IPAQ, and each Body%implant. Number (N) and percentage (%) for each categorical variable as BMI, IPAQ, dominant arm, and scapular classification.
# Visual Navigation Systems for Maritime Smart Ships: A Survey
## 2 Smart Ships and Navigation Technology
### Smart Ships
#### 2.1.2 Progress and Development of Smart Ships
With a deeper understanding of ship dynamics and the marine environment, collision avoidance technology has evolved from relying on manual judgment and operations to advanced systems that can automatically detect potential collision risks and take avoidance measures. The development of these technologies has significantly improved the safety of ships in complex sea conditions. With the development of single perception technologies, smart ships are beginning to explore multi-sensor integrated perception technologies. Such fusion technologies are able to integrate data from different sensors to provide a more comprehensive and accurate perception of the environment. The combined application of technologies such as AIS, radar, infrared and vision systems can provide more comprehensive environmental sensing capabilities. This integrated perception not only improves the accuracy of the perception, but also enhances the robustness of a system, which maintains an effective perception capability even when some sensors fail. Through the gradual development and mutual integration of these technological fields, smart ships are moving towards a higher level of automation and intelligence and the innovation and development of the maritime transportation industry continues to be promoted.
# Joint Pricing, Server Orchestration and Network Slice Deployment in Mobile Edge Computing Networks
## 6 Performance Evaluation
### Convergence Performance
In DBDQ-WOM, the penalty for illegal actions is set to \(-5\), \(-10\) and \(-14\) when \(N\) is equal to \(1\), \(2\) and \(3\). We note that as \(M\) increases, the convergence of DD3 QN becomes slower and less stable. When \(N=2\) and \(N=3\), the output of the RAL's D3 QN will be up to \(10^{7}\) and \(10^{10}\), which is beyond the capability of our computer. As for DMDDQ, even as the network scale increases, the efficiency of the algorithm does not decrease significantly, and it can converge between the 150 th and 250 th epoch. Taking \(M=5\) as an example, the convergence of DMDDQ is improved by 28.3% compared with DD3 QN; the reason is that DMDDQ introduces the branching network, which reduces the complexity of the network's outputs, and is more suitable for problems with large-scale action spaces. Meanwhile, the convergence of DMDDQ is improved by 21.9% compared with DBDQ-WOM. The reason is that DMDDQ introduces an illegal action modification method to avoid the agents from incurring a large number of illegal action penalties, which would hinder the exploration of the agents and the estimation of the value functions. The convergence performance of DBDQ-WOM is worse than that of DMDDQ. Reference [46] has pointed out that if we only penalize illegal actions, the agent may explore too many illegal actions during early exploration, requiring excessive time to find rule-compliant actions when the space of illegal actions is large. Taking Figure 6(b) as an example, DBDQ-WOM takes about 50 epochs to reach the same starting point as that of DMDDQ, because DBDQ-WOM explores lots of illegal actions in the first 50 epochs. In Figure 8, the illegal action space increases as \(N\) increases, and the gap between DBDQ-WOM and DMDDQ grows larger. It is worth noting that although DBDQ-WOM uses a branching architecture, its performance is not superior to that of DD3 QN. This is because each action advantage branch in BDQ is independent, which leads to a disadvantage for each branch in evaluating joint actions. In contrast, D3 QN evaluates the state-action values of all joint actions with a fully connected hidden layer. After incorporating the illegal action modification, DMDDQ performs better than DD3 QN, which proves that the proposed DMDDQ is more applicable to our problem.
## 3 Theoretical Derivations
### Analysis of Primary Support Bearing Capacity  
#### 4.3.1 The Influence of the Bolts' Length  
The spacing between the bolts is set at 1.6 m, and the lining thickness is set at 0.3 m. The results of analyzing the tunnel wall displacement and bearing capacity under different bolt lengths using the method proposed in this article are shown in Table 7.  
According to the analytical results, as the length of the bolts increases, the displacement \(u_{2}\) of the tunnel wall after applying the bolts gradually decreases. It can be seen that the longer the bolts, the more they can constrain the loosening of the surrounding rock. The parameters of the shotcrete and steel frame have not changed, but the surrounding rock \(u_{4}\) of the tunnel wall after support also shows a gradual decreasing trend. It can be seen that the change in the bolt lengths can improve the constraint displacement ability of the entire primary support system, reflecting the concept of the synergistic effect of the bolts and shotcrete support system.
## 3 Concept and Architecture of DigiHoriRobot  
The DigiHHoriRobot architecture is designed to support intelligent and sustainable horticulture in hydroponic greenhouse environments through a fully integrated digital twin framework. The system establishes a synchronized loop between physical components, comprising biological, robotic, and infrastructural elements, and their digital counterparts, modeled using artificial intelligence, semantic representations, and simulation techniques. An IoT-enabled communication infrastructure ensures real-time data exchange, facilitating continuous alignment between virtual models and physical processes. The architecture adheres to the foundational structure of a digital twin: (i) a physical system, (ii) its virtual representation, and (iii) a bidirectional data interface that enables convergence and interaction between the two domains [8; 23]. To enable the practical deployment of the proposed architecture, DigiHHoriRobot is structured into three interdependent components: (1) the Physical Layer, comprising all real-world entities and sensing devices; (2) the virtual layer, encompassing AI-driven models and synchronization infrastructure; and (3) the implementation framework, which governs task execution and learning across multiple operational phases. Figure 1 illustrates the core structure of DigiHHoriRobot, organized into three primary layers: the Physical Layer (bottom), the Virtual Layer (top), and the Implementation Framework (center). The Physical Layer encompasses biological systems, sensors, and robotic components operating in the greenhouse. Data collected from this layer is transmitted upward through the Communication and IoT Service layers using protocols such as ROS 2 and MQTT. The Virtual Layer contains dynamic models of crops, environment, and robot behavior, supported by AI-based reasoning and semantic representations. Bidirectional arrows indicate the synchronization flow: sensor data is ingested and used for simulation, while planned actions and task policies are sent back to the physical actuators. The central Implementation Framework governs decision-making, workflow orchestration, and task execution across phases. This modular structure ensures scalability, interoperability, and continuous adaptation between real-world conditions and digital reasoning. These components are described in more detail in the following subsections.
## 3 Results and Discussion
### Linear Fitting
In Table 2, the \(R^{2}\) value for all four temperatures is 0.987-0.991, which is higher than the data obtained for the Freundlich isotherm's linear fitting. Consequently, the \(g\) values for all four temperatures are close to 1 in the R-P equation, implying a Langmuir-type mechanism. Similar to the R-P isotherm, the Sips and Toth isotherm models combine the Langmuir and Freundlich models. However, each model has distinctive characteristic features. Typically, the Sips model predicts heterogeneous surface adsorption and circumvents the limitation observed at a high adsorbate concentration in the Freundlich model. Thus, the model predicts heterogeneous surface adsorption at low adsorbate concentrations, while it assumes monolayer adsorption at higher concentrations. The model's parameters are also subject to pH, temperature, and concentration. In comparison, the Toth isotherm model is suitable for identifying heterogeneous adsorption systems in an adsorbate's low- and high-concentration boundary conditions. Additionally, it considers the adsorbent surface's heterogeneity, and the exponent \(n\) characterizes the heterogeneity of the adsorption system. If \(n\) is between 0 and 1, the model follows the Langmuir equation; however, in the heterogeneous adsorption system, \(n\) deviates from unity (1). The data obtained from the Sips and Toth models based on linear fitting at all four temperatures are presented in Table 3. The empirical data tend to have an identical coefficient for every testing temperature, indicating the Toth model's superiority over the Sips model [6]. Table 3 shows that the \(R^{2}\) values of the two models are the same  
Figure 3: Sorption equilibrium data and linear-fitted isotherm models of MB with AG at (**a**) 303, (**b**) 313, (**c**) 323, and (**d**) 333 K.  
for a particular temperature. Except for 333 K, the values of \(n\) for the AG are slightly higher than 1 in all of the studied temperatures for MB adsorption, suggesting the systems' heterogeneity and providing support for the Freundlich model. Similar to the Sips model, the Toth isotherm equation also implies the involvement of heterogeneous adsorption for the consecutively lower temperatures of 303-323 K as \(n\leq 1\). Meanwhile, the monolayer adsorption capacity predicted with the Sips and Toth models follows similar trends to the Langmuir equation. Thus, the comparison of the values of \(R^{2}\) and the other parameters of all six linearized Langmuir equations with those of the Freundlich, R-P, Sips, and Toth isotherms shows different outcomes. Figure 3a-d shows the linear regression of the predicted isotherms against the experimental equilibrium data at 305, 313, 323, and 333 K, respectively. From Figure 3, it is evident that the linearized isotherms do not fit well with the experimental equilibrium data. This results from the data transformations that violate least-squares normality assumptions and indirectly change the error structure and the error variance [66].
## 1 Introduction
However, most of the previous studies focused on MOFs in powder form, which limited the application of MOFs due to their challenges such as dust contamination, poor water stability, and low recycling rate. In this study, a CuBTC@PET composite fiber membrane was prepared based on the aqueous phase synthesis of CuBTC, and the in situ growth of CuBTC on a PET fiber substrate was achieved by a simple and low-cost layer-by-layer growth method, which effectively solved the above problem. Polyethylene terephthalate (PET) fibers are widely used in the modern textile field because of their durability, high tensile strength, and low price [35; 36]. PET molecular chains have open ester groups on both sides of the molecular chain, which can provide binding sites for the subsequent in situ growth of CuBTC without any treatment, which greatly reduces the cost and difficulty of preparing CuBTC composite fibers. In this paper, the excellent flexibility and nanoscale size of electrostatically spun fibers are combined with the high porosity, specific surface area, surface charge, and metal ion carrying capacity of CuBTC. Compared with the traditional electrostatically spun fibers, the great advantages of CuBTC@PET composite fibers in the adsorption of PM and bacterial inhibition make it an ideal material with high efficiency of filtration and bacterial inhibition performance. They provide an effective solution for the preparation of high-performance air filtration and bacteriostatic membranes.
## 2 Materials and Methods
### Datasets
#### 2.1.2 MCD12Q1  
MCD12Q1 is a global land use data product produced by NASA with a temporal resolution of 1a and a spatial resolution of 500 m. The MCD12Q1 dataset's feature of global coverage makes it possible to provide data on land cover worldwide. Secondly, the dataset's high spatial resolution enables it to deliver information on land cover and coverage that is more precise. Additionally, the MCD12Q1 dataset features yearly updates that give researchers access to the most recent land cover and coverage data. The dataset is free and publicly accessible.  
MODIS land use data include a variety of classification systems [28; 34]. This study adopts the International Geosphere-Biosphere Programme (IGBP) global vegetation classification scheme for land cover types, which divides the Earth's surface into 17 land use types. Further processing of these data was conducted in MATLAB to merge these land use types into eight categories: forest, shrub, grassland, cropland, built-up area, bare soil, wetland, and water body. This study analyzed the seasonality and annual variation characteristics of the UHI in Zhengzhou.  
To obtain the surface temperature image of Zhengzhou City, the quantitative relationship between the brightness value of the pixels of the image and the surface temperature was used, and conversion of the pixel brightness value \(B_{LST}\) into the surface temperature (\({}^{\circ}\)C) value was obtained using the Equation (1):  
\[T_{LST}=0.02B_{LST}-273.15 \tag{1}\]  
This study used three heat island indicators--ground surface temperature, heat island intensity, and local heat island intensity--to examine the heat island of a populated metropolis in four different ways: current status, day and night change, seasonal change, and year change. According to meteorology, there are four distinct seasons: spring (March-May), summer (June-August), autumn (September-November), and winter (December-February).
# Transactive Energy to Thwart Load Altering Attacks on Power Distribution Systems
## 2 Power Balancing in Power Grids
### Correcting Power Imbalances by Means of Reserve Power  
In purchasing energy from wholesale market, an energy utility should forecast the power consumption of its power distribution system 5 min in advance of the operating time of the power grid. However, load forecasting methods [35] utilized by energy utilities are not perfect and come with limited accuracies. Accordingly, the real time power consumption of the distribution system may fluctuate and deviate from the power consumption scheduled in the wholesale market. The resulting imbalance between power generation and power consumption are compensated for by the reaction of generators that provide reserve power to the power grid. In correcting power imbalances, a mechanism known as automatic generation control comes into operation in these generators. The automatic generation control mechanism is discussed in the next section.
# Arsenic Removal from Water by Adsorption onto Iron Oxide/Nano-Porous Carbon Magnetic Composite
## 3 Results and Discussion
### Effect of Contact Time  
Effect of contact time on the adsorption of As (III) by the composite is presented in Figure 4. Adsorption percentage was increased linearly from 5 min to 60 min, and thereafter it remained almost constant, indicating the attainment of adsorption equilibrium. The adsorption rate was faster at initial stages that might be caused by a large number of available sites on the composite surface for As adsorption. The sorption rapidly occurs and is normally controlled by the diffusion process from the bulk to the surface. With the progress of time, the active sites are being saturated with more As (III) ions. It gives a decrease in the adsorption rate until the adsorption equilibrium is reached. Therefore, 60 min was chosen as the equilibrium time for As adsorption. Similar findings were observed by [PERSON] et al. for As removal from aqueous solutions by adsorption onto iron oxide/AC magnetic composite [17].
## 5 Conclusions  
This paper reported on a new low-cost circularly polarized RDRA for 5G NR Sub-6 GHz band applications. A new conformal metal strip was utilized for excitation of the higher-order orthogonal mode pair to generate CP response. A circular polarization over a bandwidth of \(\sim\)10% was achieved along with a wide impedance matching bandwidth of \(\sim\)17%. The axial ratio bandwidth was in conjunction with impedance matching bandwidth. A left-hand CP response was achieved with stable radiation patterns throughout the circular polarization bandwidth. A useful gain of \(\sim\)6.2 dBic was attained by the antenna. The use of a simple and low-cost feeding mechanism, i.e., a unique conformal strip, to generate a circularly polarized wave by excitation of higher-order orthogonal modes, is the significant feature of this research, as compared to reports in the literature. A good agreement was observed in simulation and experimental results.  
Conceptualization, U.I., A.R. and J.I.; methodology, U.I. and J.I.; software, U.I., I.B. and F.M.; validation, M.A.K., I.B. and F.M.; formal analysis, M.A.K., I.B. and F.M.; investigation, M.A. and M.I.S.; resources, M.A., M.I.S. and F.M.; data curation, A.R. and J.I.; writing--original draft preparation, U.I. and J.I.; writing--review and editing, M.I., A.G. and G.N.; visualization M.I., A.G. and G.N.; supervision, M.I., A.G. and U.I.; project administration, M.I., M.A. and G.N.; funding acquisition, M.I., A.G., M.A.K. and A.R. All authors have read and agreed to the published version of the manuscript.  
The APC of the journal was supported by the Faculty of Electrical and Computer Engineering, Cracow University of Technology and by the Ministry of Science and Higher Education, Republic of Poland (grant No. E-1/2022).  
Not applicable.  
All data has been included in the study.  
The authors acknowledge the support from the Deanship of Scientific Research, Najran University, Kingdom of Saudi Arabia.  
The authors declare no conflict of interest.
# Preliminary Study on the Damping Effect of a Lateral Damping Buffer under a Debris Flow Load
## 3 Experiment Validation
### Equivalent Damping Ratio  
According to the test, the equivalent damping ratios are calculated based on its definition [32] (shown in Table 1). The equivalent damping ratio of the uncontrolled structure is about 4.0%, while the equivalent damping ratio of the structure with lateral damping buffer is 5.2%-7.5%, with improvement being 30.0%-87.5%. The lateral damping buffer has control effectiveness on account of the subsequent structural vibration.  
\begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline
**Loading Grades** & **1** & **2** & **3** & **4** & **5** & **6** & **7** & **8** & **9** & **10** \\ \hline Uncontrolled & 4.0 & 4.0 & 4.0 & 4.0 & 4.0 & 4.0 & 4.0 & 4.0 & 4.0 & 4.0 \\ With isolators & 5.2 & 6.2 & 6.1 & 6.2 & 5.4 & 6.1 & 6.7 & 7.5 & 7.0 & 6.3 \\ Improvement & 30.0 & 55.0 & 52.5 & 55.0 & 35.0 & 52.5 & 67.5 & 87.5 & 75.0 & 57.5 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Equivalent damping ratio (%).  
Figure 6: The frequency domain response: (**a**) Grade 4; (**b**) Grade 6.
# Spatiotemporal Variation of Land Surface Temperature Retrieved from FY-3D MERSI-II Data in Pakistan
## 2 The Study Region and the Data
### The FY-3D MERSI-II Data  
FY-3D MERSI-II satellite data have very high potential usages for various research fields. Climate change, water vapor estimation, numerical weather forecast, space weather prediction, and ecosystem monitoring are just a few of the many applications for the FY-3D MERSI-II satellite data [25]. The above-mentioned applications would benefit from a method that accurately and quickly retrieves LST from the MERSI-II data (i.e., the TFSW algorithm) [7]. Table 1 and Figure 2 compare the required bands of MERSI-II with the corresponding ones of MODIS for LST estimation. MERSI-II is similar to MODIS in certain ways, particularly in terms of wavelength frequency and band parameters. MERSI-II is a modified version of the first-generation same track type satellite sensors in terms of data  
Figure 1: Geographical location of the study region. (**a**) Land cover types in Pakistan during 2019, derived from the MODIS MCD12Q1 Version 6 data product. (**b**) Five homogeneous and contiguous regions were developed, which are similar to the climatic regions developed by [13]. (**c**) Digital Elevation Model based on the ASTER 30 m Digital Elevation Model.  
quality, band number, resolution, and other factors, in order to increase the detection range for various application areas. According to the TFSW algorithm characteristics, Bands 24 and 25 of MERSI-II are selected for LST estimation. The spectral response function of the MODIS (Band 31/32) and MERSI-II (Band 24/25) TIR bands are shown in Figure 2. From Table 1 and Figure 2, it can be clearly observed that the TIR band range of MERSI-II and MODIS is similar, and that the central wavelength is also similar to some extent. It is also verified that the MODIS data can be used for validation purposes. This study uses FY-3D MERSI-II Level-1B radiance data downloaded from the Fengyun Satellite Data Archiving Portal ([[http://satellite.nsmc.org.cn](http://satellite.nsmc.org.cn)]([http://satellite.nsmc.org.cn](http://satellite.nsmc.org.cn))) (accessed on 20 April 2022).