esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Key Design Requirements and System Components
### Layer 6: Consortium Blockchain  
The proposed model employs blockchain technology to ensure secure and transparent transactions within the federated wireless communication network. This approach facilitates reliable management of key operations, including subscriber authentication, service requests, and provisioning. Blockchain transactions between NW providers establish decentralized agreements to coordinate network coverage, share resources, and determine billing criteria for subscriber usage. NW brokers and providers take on the role of blockchain miners, validating transactions and managing the distributed ledger, which promotes transparency and accountability and ensures data integrity within the federated network.  
The consortium blockchain structure in this framework inherently provides a layer of validation by involving trusted miners as stewards who verify smart contracts before deployment, ensuring alignment with business logic and system requirements. Additionally, methodologies such as formal verification [21] can mathematically prove contract correctness, while model-checking systematically evaluates all possible states to detect inconsistencies. Static analysis tools like Slither aid in early vulnerability detection [22], and symbolic execution [23] explores multiple execution paths to uncover potential flaws.  
These approaches collectively contribute to the safety and reliability of smart contracts and autonomous agents. While ensuring the functional correctness of smart contracts and autonomous agents is crucial, a comprehensive exploration of this topic falls outside the primary scope of this paper.
# Communication Architecture for Grid Integration of Cyber Physical Wind Energy Systems
## 3 CPWES Modeling and Assumption
### Traffic Model for an Offshore Substation Based on IEC 61850
The traffic configuration and data flow for the CB-IED and MU-IED considered in our model are given in Table 5. IEDs and relays were connected through a 100 Mbps ethernet-based architecture. At the station level, there were the following: a station PC, a protection and control server, ethernet switches, and communication links. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Zone** & **CB IED** & **MU IED** & **P\&C IED** \\ \hline Wind Turbine & \(1\) & \(1\) & \(1\) \\ Collector Feeder & \(1\) & \(1\) & \(1\) \\ Collector Bus & \(1\) & \(1\) & \(1\) \\ Substation Transformer & \(2\) & \(1\) & \(1\) \\ \hline \hline \end{tabular}
\end{table} 
Table 4: IEDs configuration in the wind farm substation. IED: intelligent electronic device. Figure 5: Schematic diagram of the cyber physical model for the wind farm substation. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Zone** & **Measurement** & **From** & **To** \\ \hline CB IED & Breaker Status & CB IED & Station Server \\ MU IED & Sampled 3-phase V, I message & MU IED & Station Server \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Traffic configuration for IEDs.
## 3 Experiments
### 5G Delay Experiments  
Apart from the energy optimization, latency is another crucial factor for IoT systems within real-time monitoring scenarios. This subsection analyses the end-to-end communication delays within the 5G network under different data sizes and link conditions. All the tests were performed using different payloads and bandwidth constraints, which can impact transmission latency. This is critical information for determining the responsiveness and reliability of a 5G-based IoT system.
# Brown Coconut Husks as Media Within an Anaerobic Filter for Improving On-Site Wastewater Treatment
## 2 Materials and Methods  
### Anaerobic Filter Setup  
A laboratory-scale reactor was set up in the same way as previous studies [20] (Figure 1). The reactor had a diameter of 290 mm and height of 360 mm. Perforated plates were placed 60 mm from the bottom of the reactor and 60 mm from the top of the reactor to contain the pieces of coconut husk and prevent blockage of the outlet. The anaerobic filter tank was connected to two effluent collection containers (20 L and 50 L). Another 75 L container was used as a feed tank. The synthetic wastewater was based on [PERSON] et al. [21], and it was diluted to reduce the concentration to approximately 300 mgCOD/L to mimic effluent from a septic tank [22]. The components of the synthetic wastewater are shown in Table 1.  
The brown coconut husks used in this work were sourced from a coconut farm in the Kingdom of Tonga (_Cocos nucifera_, cultivar Tongan Tall). The coconut husk pieces were one-third to one-quarter of an entire husk. Moisture content measurements were performed, and the brown husks had an average moisture content of 19.8%. The coconut husks were placed in cow manure for 15 minutes to inoculate the reactor with anaerobic  
\begin{table}
\begin{tabular}{l c} \hline
**Component** & **Amount Added to 50 L of Water (g)** \\ \hline Glucose & 8.15 \\ Yeast extract & 0.68 \\ Dried milk & 2.72 \\ Urea & 0.68 \\ NH\({}_{4}\)Cl & 1.36 \\ Na\({}_{2}\)HPO\({}_{4}\)\(\cdot\)2H\({}_{2}\)O & 2.26 \\ KHCO\({}_{3}\) & 1.13 \\ NaHCO\({}_{3}\) & 2.94 \\ MgSO\({}_{4}\)\(\cdot\)7H\({}_{2}\)O & 1.13 \\ FeSO\({}_{4}\)\(\cdot\)H\({}_{2}\)O & 0.05 \\ CaCl\(\cdot\)6H\({}_{2}\)O & 0.01 \\ Bentonite & 1.01 \\ \hline \end{tabular}
\end{table}
Table 1: Composition of the synthetic wastewater.  
Figure 1: Experimental setup for the laboratory-scale anaerobic filter.  
bacteria. These husks were then used to fill the anaerobic filter (Figure 1). The total weight of brown coconut husks added to the reactor was 1.371 kg.  
In order to mimic wastewater produced from a typical household, the feed pump was run twice daily for one hour (8-9 am and 4-5 pm). This was to simulate the production of wastewater in the morning and evening. The HRT was set at 12 h. The water volume of the anaerobic filter tank was 11 L excluding the coconut husks; therefore, the amount of water pumped each time the pump was run was approximately 11 L, with a total amount of approximately 22 L each day. Initially, the reactor was started on diluted synthetic wastewater to allow the biofilm to become established without overloading. For the first 10 days, the reactor was run using 25% concentration; then, this was increased to 50% until day 25 when the feed was then used at full strength.
# Vibration Energy Harvesting from Raindrops Impacts: Experimental Tests and Interpretative Models
## 5 Interpretative Mathematical Model
### Force Model for the Wet Spoon
#### 5.2.2 Approximation of the Crown Motion  
The implementation in Equation (18) of an analytical formulation of the actual crown motion is practically impossible. It is a very complicated motion, described by nonlinear dynamic equations involving several interaction phenomena, e.g., water-water, water-air, and water-solid (the spoon) interactions. The goal of the present paper is to find an approximation of the crown motion that is able to represent the main crown movements responsible for harvester excitation, i.e., the maximum elongation and the collapse. To this end, the crown is modeled through a mass-spring-damper system, of which the free response to initial conditions (i.e., the drop impact, which means \(y_{e}(0)=0\) and \(\dot{y}_{e}(0)\
eq 0\)) can represent the crown evolution. The mass of the system has been set to be equal to the displaced water mass in Equation (24), i.e.,:  
\[m=\rho_{w}A_{e}y_{e_{max}}\bigg{(}1+\frac{A_{e}}{A_{i}}\bigg{)} \tag{27}\]  
The other system parameters--i.e., the stiffness \(k\), the viscous damping coefficient \(c\), and the initial crown velocity \(\dot{y}_{e0}=\dot{y}_{e}(0)\)--are determined by imposing three conditions on the free-vibration response of this equivalent system, so that it can match the known information about the crown evolution. Let \(t_{1}\) and \(t_{2}\) indicate the instants at which the crown reaches its maximum height and at which it collapses, respectively; the imposed conditions are two for the crown stabilization phase (\(y_{e}(t_{1})=y_{e_{max}}\) and \(\dot{y}_{e}(t_{1})=0\)) and one for the crown collapse phase (\(y_{e}(t_{2})=0\)). The time instants \(t_{1}\) and \(t_{2}\), similarly to \(y_{e_{max}}\)can be inferred from the experimental data if available or using the models available in the literature (e.g., [29]) for the determination of \(t_{1}\), and [19] for the determination of \(t_{2}\).  
The parameters of the simplified crown model are found by solving the following system of non-linear equations:  
\[f(\mathbf{x})=\mathbf{0} \tag{28}\] \[\textbf{x}=\left\{k\quad c\quad\dot{y}_{\omega 0}\right\}^{\mathrm{T}}\] (29) \[f(\mathbf{x})=\left\{\begin{array}{l}\frac{\dot{y}_{ \omega 0}}{\omega_{d}}\sin(\omega_{d}t_{1})e^{-\xi\omega_{d}t_{1}}-y_{\omega_{ max}}\\ \left(-\frac{\xi}{\sqrt{1-\xi^{2}}}\sin(\omega_{d}t_{1})+\cos(\omega_{d}t_{1}) \right)\dot{y}_{\omega 0}e^{-\xi\omega_{d}t_{1}}\\ \frac{\dot{y}_{\omega 0}}{\omega_{d}}\sin(\omega_{d}t_{2})e^{-\xi\omega_{d}t_{2}} \end{array}\right.\] (30) \[with:\quad\omega_{n}=\sqrt{\frac{k}{m_{c}}};\,\xi=\frac{c}{2 \sqrt{km_{c}}};\,\omega_{d}=\omega_{n}\sqrt{1-\xi^{2}}. \tag{31}\]  
The solution of Equations (28) makes it possible to compute the force \(R(t)\) in Equation (18) that the harvester exerts on the water and hence the force that acts on the harvester, that is, \(F(t)=-R(t)\). Figure 13 schematically summarizes the simplified model adopted for describing the crown motion, as well as the imposed conditions, and the resulting motion.
## 4 Absolute Dose Measurement
### Active Detectors  
One of the most accurate dosimetry devices is the Faraday cup [33; 38]. It allows for an absolute determination of the number of protons reaching its charge collector. Therefore, Faraday cups are widely used to accurately measure low beam currents in different accelerator facilities [39; 40], as well as the reference dose of clinical proton beams [38]. The Faraday cup has been shown to give linear response while varying beam current also for ultra-high dose rates [33]. The Faraday cup is a destructive detector and can, thus, be used only as a beam stopper (Figure 2). Therefore, it can only be employed in transmission mode.  
While thinking about high dose rates, a natural concept is to apply solutions widely used in high energy physics. One of the easily applicable detectors would be calorimeters. A calorimeter measures the energy deposited by particles contained in a particle shower initiated by the incident particle in the material of the calorimeter. Compact graphite calorimeters have already been developed for dosimetry of clinical proton beams [41; 42]. As in the case of the Faraday cup, this kind of dosimeter cannot be applied in front of the patient (Figure 2).  
Semiconductor-based dosimeters, such as a silicon diode or diamond, represent another class of active detectors. Standard silicon diodes will suffer from readout saturation when exposed to ultra-high dose rates. Some efforts have been made to overcome that problem, including the development of new p-type silicon strip detectors (SSD) [43]. They have found application in dosimetry of X-ray microbeams and have been tested at ultra-high dose rates [44; 45; 46]. Diamond detectors represent an attractive choice for dosimetry. Diamond has numerous advantages, among which are a good tissue equivalency (its atomic  
Figure 2: Destructive and non-destructive detectors for dosimetry. The former may be used on either side of the patient, while the latter can serve beam stopper only in the case of transmission irradiation.  
number is very close to the effective atomic number of the tissue), a high resistance to radiation damage, high sensitivity and stability of response, and a good time resolution [47]. Diamond detectors can be produced in small sizes (compared to standard dosimeters, such as cylindrical or plane-parallel ionization chambers), so they can be easily placed in different experimental setups and anatomical structures of irradiated phantoms, as well as be deployed for in vivo dosimetry [48]. Diamond detectors have already been used in dosimetry of proton pencil beams [49]. They have also been employed in FLASH experiments, and no significant dose-rate dependency has been found for dose rates up to 40 Gy/s [9].
## 2 Method and Data
### Main Data for GLOPEM-CEVSA Model Input and Validations
#### 2.2.1 Meteorological Data  
The meteorological data needed for GLOPEM-CEVSA included the interpolated air temperature, precipitation, wind speed, air relative humidity, and radiance data. In this study, the air relative humidity was calculated with the dew temperature and air temperature according to [PERSON] [52]. The air temperature, dew temperature and wind speed were the Global Surface summary Of Day Data (GSOD) produced by the National Climatic Data Center (NCDC). The eight-day mean was calculated with the daily observations of the station from 1980-2008 and then interpolated to an eight-day grid with 8-km spatial resolution. The ANUSPLIN package (version 4.2), that is based on thin plate smoothing splines of multi-variates, was applied for interpolation in this study because of its good performance compared to other interpolation methods [53].  
The daily precipitation datasets were derived from the Asian Precipitation Highly-Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE's Water Resources) project [54]. We used the dataset in the Monsoon Asia area from 1980-2007 and as precipitation showed spatial discontinuity, we re-projected and resampled from 0.25 \({}^{\circ}\) to 8-km using the nearest neighbour algorithm. The Surface Radiation Budget (SRB) Release 3.0 daily data for 1984-2007 were obtained from the NASA Langley Research Center Atmospheric Sciences Data Center NASA/GEWEX SRB Project. The SRB dataset is a daily global product with 1 \({}^{\circ}\times 1\)\({}^{\circ}\)resolution and it was resampled to 8-km spatial resolution with the bilinear algorithm as radiation data showed good spatial continuity. Then, the photosynthetically active radiation and net radiation were calculated with the all-sky surface downward and upward shortwave flux.
# Feedback-Forward Neural Networks for Failure Mechanics Problems
## 4 Neural Network (NN) Based Elasticity for Fracture Problems
### Numerical Examples
#### 4.3.1 Single-Edge-Notched Tension Test  
The first benchmark test considers a square plate (\(L=1\) mm) with a horizontal notch placed at the middle height, as plotted in Figure 10 (left). The specimen is discretized using FEM with linear triangles.  
A mesh refinement in the expected fracture zone is applied. Furthermore, Figure 10 shows the contour plot of the crack phase-field \(d\) for different loading states up to final rupture.  
Next, Figure 11 illustrates a comparison between FEM and the Neural Network formulation by calculating the stress-strain relationship using both methods. The predicted stress thoroughly follows the FE solution, which verifies the general  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**No.** & **Name** & **Parameter** & **Value** & **Unit** \\ \hline
1. & [PERSON]’s modulus & \(E\) & 21 & kN/mm\({}^{2}\) \\
2. & [PERSON]’s ratio & \(\
u\) & 0.3 & \(-\) \\
3. & Critical fracture energy & \(\psi_{c}\) & \(1.35\times 10^{-3}\) & kN/mm\({}^{2}\) \\
4. & Fracture length scale & \(l\) & 0.004 & mm \\
5. & Fracture viscosity & \(\eta\) & \(1\times 10^{-6}\) & N\(\cdot\)s/mm\({}^{2}\) \\
6. & Post critical parameter & \(\zeta\) & 1.0 & \(-\) \\ \hline \hline \end{tabular}
\end{table}
Table 4: Material parameters used in the numerical examples.  
Figure 10: Single-edge notched test (SENT). Geometry and contour plots of the fracture phase-field \(d\) for different loading states up to final failure using FEM with 3-noded linear triangular elements.
# Mechanical Performance of Polymer Materials for Low-Temperature Applications
## 2 Materials and Methods
### Experimental Apparatus  
A uniaxial tensile test was conducted on the three types of polymer specimens to experimentally investigate general behavior and mechanical properties according to temperature and strain rate. Figure 2a shows the photograph of the custom-built cryogenic-chamber-equipped universal testing machine. The specially built cryogenic chamber, with temperature automatically programmed by controlling the amount of liquid nitrogen, was used to maintain the cryogenic condition throughout the test. The temperature was measured by the three different thermocouples present in the chamber. When liquid nitrogen was injected to lower the temperature to the cryogenic temperature, the automatic temperature control system prevented the further injection of liquid nitrogen once the temperature reached the desired value. In addition, when the temperature started to increase, the control system lowered the temperature through reinjection such that it was maintained at the desired value. Special care was taken to maintain the thermal equilibrium condition by performing precooling for 30 min prior to the tensile test. In addition, a specially designed assistant jig was adopted to fasten the testing specimen. To acquire reliable experimental data, a cryogenic extensometer (3542-05M-100-LT, Epsilon Tech. Corp) was embedded on the polymer specimen. Figure 2b shows the shape and dimensions of the polymer testing specimen fabricated in accordance with ASTM D638-1.
# Traffic Noise Reduction Strategy in a Large City and an Analysis of Its Effect
## 2 Materials and Methods
### Position and Height of Noise Barriers  
The location of noise barriers was determined based on two rules: (1) The noise barriers should be close to the noise source or the point of the receiver [36]; (2) the installation of noise barriers should not affect the daily life of the public. Hence, in the present study, the location of noise barriers was arranged close to the road boundary line, as shown in Figure 5a. The situation without noise barriers is shown in Figure 5b for comparison.  
According to the preliminary simulation results, the traffic noise could be reduced by 3-5 dBA when the defined height of the noise barriers was less than 6 m. When the height of the noise barriers was larger than 6 m, the reduction of traffic noise was predicted to be more than 5 dBA. Since the noise over-limit values in Panyu District fall in different ranges, as shown in Figures 1 and 2, specific heights of the noise barriers are proposed to meet the noise reduction requirements over different ranges. According to the \"Standard  
Figure 4: A noise map of a small area of Guangzhou University. (**a**) Daytime without a noise barrier; (**b**) daytime with an L-shaped noise barrier; (**c**) nighttime without a noise barrier; (**d**) nighttime with an L-shaped noise barrier. Note that only a noise map with an L-shaped noise barrier is shown for brevity.  
Figure 5: Comparison of three-dimensional noise maps of the small area near Guangzhou University in the University Town. (**a**) With noise barriers; (**b**) without noise barriers.  
requirement of acoustic design and measurement for noise barrier\" (HJ/T90-2004) [37], the height of noise barriers on both sides of roads should be less than 6 m. Hence, in the present study, the proposed height of the noise barriers was set to 6 m when the noise over-limit value of the specific areas was greater than 5 dBA. However, in the areas where the noise over-limit values were less than 5 dBA, the heights of the noise barriers were selected according to a computation by the software. Finally, the simulation model was rebuilt with noise barriers installed along both sides of the main roads and then recomputed. In the new simulation model, the total length of noise barriers applied in Panyu District was calculated to be 169.3 km.
# GNSS-Based Monitoring Methods for Mining Headframes
Particularly, the specialized monitoring of sheave settlement and inclination represents a research gap in the existing literature, as no prior studies have applied GNSS technology to this specific application. This advancement highlights the novelty and practical significance of the study in enhancing safety monitoring for mining infrastructure. With the continuous development of GNSS technology and its gradual penetration into the field of deformation monitoring, the application of GNSS technology to achieve the whole lifecycle safety monitoring of mining shafts will become one of the key technologies for ensuring the safe operation of mining areas. This study focuses on the Liuzhuang Mine West District in Fuyang City, Anhui Province, serving as a representative example of a deep-mine environment. The headframe of Liuzhuang Mine is influenced by the interplay of complex geological conditions and mechanical loading. Historically, there has been a lack of long-term dynamic monitoring data for this site. Through 66 days of continuous observation, this research has, for the first time, developed a spatiotemporal database documenting headframe deformation in the region, thus providing a benchmark case for risk assessment in analogous settings. The study encompasses data cleaning, three-dimensional spatiotemporal deformation analysis and visualization, risk prediction, and assessment. It investigates early warning methodologies for headframe monitoring within this mining area. This research contributes to safety inspections of the headframe and offers theoretical and methodological insights for designing construction and reinforcement strategies, as well as for the optimal layout and planning of GNSS monitoring stations. The structure of this paper is organized as follows: Section 1 introduces the importance of monitoring deformation in mining headframes, discusses the limitations inherent in traditional techniques, and highlights the potential of GNSS technology, while also outlining the research objectives. Section 2 provides a detailed description of the GNSS monitoring scheme, including the station layout and equipment installation, as well as the capabilities of the self-developed Beidou Intelligent Monitoring and Rapid Warning Platform (BIMRWP). Section 3 elaborates on the data cleaning methodologies employed, such as cubic spline interpolation and generalized extreme studentized deviate (GESD) outlier detection, and the spatiotemporal analysis of three-dimensional deformation. Section 4 conducts a quantitative evaluation of the primary deformation factors and safety thresholds through correlation analysis and risk assessment. Finally, Section 5 summarizes the research findings and suggests future directions for enhancing the integration of multi-source sensor data.