esa-sceva/satcom-chunk-collection huggingface dataset:
# A Novel Feeder Link Handover Strategy for Backhaul in LEO Satellite Networks
## 5 Simulation and Analysis
### Simulation Results and Analysis
Thus, the backhaul capacity performance is extremely low. Therefore, the weight of the service time factor should be set close to 0. Figure 7: The performance comparison with different handover control factors. Finally, the backhaul capacity versus time slots is presented in Figure 9. The number of satellites is set to \(N=800\) and the number of GSs is set to \(M=15\). The weights of the utility function are set as \(w_{1}=0.64\), \(w_{2}=0.16\), and \(w_{3}=0.2\). Obviously, MBCHS outperforms both benchmarks at all times. Compared with MGCS, which also aims at maximizing network capacity, the proposed strategy improves the backhaul capacity performance by 25%. The average backhaul capacity of the proposed algorithm is almost 200 Gbps, while the average backhaul capacity of MGCS is almost 159 Gbps. Note that the curve of MSTS varies greatly with time. The reason is that the handover occurs only when the satellite is out of sight and the feeder link connections are relatively stable for a long duration. As the satellite moves periodically at a circular orbit, the backhaul capacity would change as the propagation distance of the feeder link changes to small and then to large. Figure 8: The performance comparison with different weights of service time.
## 4 Results and Discussion
### Sensor Robot Design as Access Point
#### 4.1.1 Recognizing Unit: For Sensing Vehicles  
The recognition unit (the detector, labeled as 210 in Figure 7a) uses an ultrasonic sensor to measure the distance to the vehicle approaching the sensor robot device. The detector uses an ultrasonic to a RADAR (or LIDAR) sensor, which uses frequency bands in the range of 20 kHz to 79 GHz to measure the distance from an object. Besides the ultrasonic sensor, the detector includes a sensor equipped with a position-sensitive detector sensor, a charge-coupled device image sensor, and an infrared (IR) sensor to identify the presence and distance of the vehicle.  
The recognition unit periodically measures the distance between the robot device and the vehicle. When the measured distance between vehicles is close to 0-200 m, the vehicle is considered to be approaching the robot device. The recognition unit then generates access information when an  
Figure 6: Process diagram: Sensor robot communicate via network infrastructure - API - mobile app.  
Figure 7: The architecture of the sensor robot system: **(a)** controlling module with the sensor assembly; **(b)** implemented projection.  
approaching vehicle is detected. Here, the \"access information\" refers to information about the detection of the approach of a vehicle to the robot device and includes at least one piece of unique identification information of the robot.
## 2 Bridge Properties and Modelling
Although this modelling procedure (i.e., using the lumped plasticity model) has been widely used in research and practice for design and evaluation of bridges and is recommended in many seismic codes and guidelines (e.g., [8; 18]), to further validate the modeling assumptions the numerical results were compared to some experimental data. The data from the RC column tests [19] (data was available in the Pacific Earthquake Engineering Research Center (PEER) structural database [20]; verification details are available in [12]), as well as the data from a large-scale (i.e., 1:2.5) pseudo-dynamic test [21] were considered to validate the predictions from the numerical models. The bridge data labelled as B213C in the experimental study were used for the verifications. A comparison of the results from numerical modelling with experimental results (see Figure 3) indicates that the recommendations made by [PERSON] et al. [7] (i.e., the use of the lumped plasticity model with the Takeda hysteresis rule) for modelling bridge structures provided sufficient accuracy in predicting the maximum displacement demands [12]. Therefore, these modelling assumptions were adopted for the seismic analysis and evaluation of the bridges in this research. More details concerning the modelling of the bridges and the verification of computer models are available in [1; 12; 22; 23; 24]. Figure 2: Structural modelling of the bridges: (**a**) Schematic presentation of the structural modelling of the bridge in the Ruaumoko program (adapted from [12]); (**b**) modified Takeda hysteresis loop (adapted from [17]). The modal properties of the bridges including the fundamental transverse mode, T\({}_{\text{T}}\), second transverse mode, T\({}_{\text{T}2}\), fundamental longitudinal period, T\({}_{\text{L}}\), geometric mean period, T\({}_{\text{G}}\), (defined as T\({}_{\text{G}}\) = (T\({}_{\text{L}}\cdot\)T\({}_{\text{T}}\))\({}^{0.5}\)) and the effective modal mass ratios are presented in Table 1. The periods are computed using the effective stiffness of the columns.
###### Abstract
The partly saturated sample showed significant positive feedback between pore pressure diffusion and damage growth, while the fully saturated sample demonstrated quite ductile fracture behavior and a low level of AE activity. More recently, laboratory creep experiments on carbonate-bearing fault gouge suggested that the coupling between fluid pressure and rate-and-state friction parameters controls fault stability [27; 28]. Previous laboratory experiments have systematically investigated the mechanism of injection-induced earthquakes; however, many issues are still not fully understood and must be addressed. For instance, the leading cause of strong induced earthquakes is the reactivation of pre-existing faults [12; 19], but the existing research primarily concentrates on how fluid injection affects the deformation and fracture of rocks. Again, because no apparent differences have been found between natural origin events and induced earthquakes concerning earthquake seismological aspects [12; 29], the mechanism of induced earthquakes is explained mainly by the knowledge of tectonic earthquakes. For example, the velocity weakening of fault was applied to explain focal depths [30]. Since injection-induced earthquakes mainly occur in shallow sedimentary faults that are usually characterized by velocity-strengthening properties, it is a question of whether the velocity weakening of a fault may also be applied to induced earthquakes at shallow sedimentary faults [15]. Considering this gap, this paper performed frictional experiments with pressurized water injection on granite, sandstone, and limestone faults using a triaxial friction apparatus and measured their velocity dependence. Moreover, it highlights the impacts of fluid injection on the faulting slip, and the results can shed light on the mechanism and influencing factors of injection-induced earthquakes.
## 4 Performance of Waste-Plastic-Modified Bitumen Binder and Mixture
### Characteristics of Plastic-Modified Bitumen Binder
#### 4.1.1 Mechanical and Rheological Enhancements
Response surface optimization research determined that optimal low-temperature rheological performance was achieved with 3% LDPE and 2.02% crumb rubber. This formulation reduced creep stiffness and enhanced the m-value in BBR testing, signifying a balance between flexibility and rigidity [40].
## 3 GLRT-Based Fusion Rule  
In this section, we discuss a GLRT-based fusion rule by assuming that the quantizers are known. The quantized data are transmitted to the FC over a distortion channel modeled as binary symmetric channels (BSCs) to form a global decision. The design of the quantizers will be discussed in Section 4.
# Adaptive TCP Transmission Adjustment for UAV Network Infrastructure
## 2 Related Work
However, reduced packet loss can be achieved with lowered throughput, but it cannot be easily recognized in evaluating normalized throughput. Therefore, this evaluation cannot suggest that throughput is improved. [PERSON] et al. [21] showed a simulation-based analysis of the robustness of high-speed TCP-CUBIC connections when random packet losses increase in a network with large bandwidth-delay product and different TCP connections. They showed strong point of TCP-CUBIC compared with other TCP algorithm under high packet loss environment.
# An Efficient Adaptive Data-Link-Layer Architecture for LoRa Networks
## 4 Data Link Layer Design
### ADL Mechanism  
The adaptive data link (ADL) mechanism is performed by both sides of each link between an end node and the packet forwarder and uses the MAC protocol described in the previous section for communication. The ADL mechanism adjusts the SF and the TxP dynamically for each end node according to the link quality conditions observed by the packet forwarder since the last ACK, namely the number of data packets lost and the stored SNR from the received packets. The feedback from the packet forwarder to the end node is inserted in the ACK packet, which is transmitted only after \(Np\) data packets are sent by the end nodes in order to reduce the protocol overhead (ToA and energy consumption) and to give time to collect a sufficient number of link quality observations. The value of \(Np\) is configurable by the network administrator.  
As observed in Figure 8, where \(T\) is the end node's data transmission interval, based on the link quality observations, the packet forwarder sends the new calculated values for the spreading factor (SF) and transmission power in the ACK packet, which allows adapting these parameters in order to reduce the energy consumption of the end nodes without compromising data reception. A timeout mechanism was also implemented at the end nodes, which increases these parameters to the maximum in case the ACK is missed, aiming to restore the link between the end node and the packet forwarder.  
Since the SF is the parameter that has more impact on the ToA (and energy consumption), the algorithm starts decreasing the SF. If SF = 7 is achieved and the link quality remains satisfactory, the TxP is also decreased. If the link quality deteriorates for any reason, the values of these parameters are increased again to restore the reliability of the  
Figure 8: Activity diagram for the ADL mechanism.  
link. The Bw also has an effect on the ToA and range and, consequently, on the energy consumption and measured link quality, but less than the SF, so its adjustment was not included in the current version of the ADL mechanism.
# Low-Carbon Operation Strategy of Park-Level Integrated Energy System with Firefly Algorithm
## 1 Introduction
With the deepening application of emerging technologies such as cloud computing, big data, the Internet of Things, and blockchain in the energy industry, the large-scale deployment and coordinated control of renewable energy, energy storage, and distributed applications of flexible loads have become key research priorities in the planning, construction, and operational management of regional energy systems. In a park-level low-carbon integrated energy system, multiple components such as generation, grid, load, and storage are involved [13]. Its operation involves various factors, including technical, economic, energy conservation, environmental protection, and energy efficiency. It is necessary to establish a comprehensive energy system cooperative optimization control model based on the analysis and research of the characteristics of each component, i.e., generation, grid, load, and storage. This model aims to meet the optimization operational requirements in real-world scenarios [14]. The regional integrated energy system faces challenges in balancing the technical, environmental, reliability, and electrical quality objectives, with inherent correlations and contradictions among them [15]. Effectively coordinating these diverse goals remains a pivotal challenge in the field, aiming to optimize the system to the greatest extent across objectives. Current research predominantly focuses on singular aspects of low-carbon integrated energy systems in industrial parks, lacking comprehensive analyses of the entire system operation. This article constructs a low-carbon integrated energy system composed of distributed renewable energy and clean energy and establishes mathematical models for the source, grid, load, and storage components of the low-carbon integrated energy system in the industrial park. The study analyzes operational strategies for the park-level integrated energy system under various scenarios, aiming to design an economically, low-carbon, and efficient mode of operation for the integrated energy system to meet the objectives of diverse stakeholders.
## Materials and Methods
### Performance Indicators  
Three performance indicators (Table 3) were studied at different spatiotemporal resolutions. These indicators are selected based on the data available directly from the WaPOR portal:  
* Adequacy--The sufficiency of water use to meet the crop water requirement (CWR) or potential evapotranspiration;
* Equity--The fairness of irrigation water distribution;
* CWP--The unit of physical crop production or yield per unit water consumed.  
The indicators are applied to the scheme based on available data relating to crop information. The crop coefficient is only known for two schemes, and therefore, that indicator is only applied in those two schemes. In plots where the pixel size is less than the plot size, only pixels fully contained within the plot are considered. In plots where the pixel size is greater than the plot size, the data is extracted as point data to a point in the middle of the plot.  
Adequacy was assessed using the relative evapotranspiration (relative ET) indicator, which is estimated through the ratio of seasonal ETIa to the seasonal CWR [2,42] and is assessed on an annual basis. The CWR was taken at the seasonal relative ET multiplied by the average seasonal crop coefficient (Kc). Due to data limitations in the WaPOR database, there is insufficient information on crop growth cycle to consider Kc at a higher temporal resolution. The single Kc method, rather than the dual crop coefficient method, was used, as the purpose of this manuscript is not to test the actual adequacy but the ability of datasets with different resolutions to capture the variation. This indicator was assessed in the Metehara and the Wonji, where the schemes are heavily dominated by one major crop type at two levels, between irrigation plots and between irrigation schemes. The average annual sugarcane Kc for a sugarcane ratoon crop was taken as approximately 0.95 [41].  
Equity is a measure of irrigation uniformity [43,44]. It is assessed through estimating the coefficient of variation (CV) of ETIa at two levels--between irrigation plots and between irrigation schemes. The ETIa is assessed at annual and dekadal scale.  
CWP is defined here as the ratio of beneficial biomass to ETIa. The CWP can vary based not just on management and irrigation practices [45,46,47] but on climate [48,49], crop cultivar [50], and other environmental factors [51,52,53]; therefore, it is assessed at only one level--between irrigation plots. The beneficial biomass is taken as the AGBP. The CWP is assessed at a seasonal or annual scale.
## 2 Principle of Ultrasonic Waves and FEM Simulation  
### Measurement of Rayleigh Waves  
Rayleigh waves are generated when ultrasonic waves reach the Rayleigh angle (the incident angle at which incident ultrasonic waves propagate by converting all of the ultrasonic energy into surface waves along the surface) at the liquid-solid interface as shown in Figure 1, and their energy is concentrated and propagated on a solid surface [1,5]. This study used Rayleigh waves with a high resolution to analyze the types of surface defects on piston rods. The energy of the Rayleigh waves was propagated on the solid surfaces in the direction of the angle of incidence through mode conversion.  
Figure 1 shows how the waves are reflected by the law of reflection when ultrasonic waves reach the Rayleigh angle, how the reflection path is shifted by Schoch displacement, and how a null field is formed due to the offset interference of Rayleigh waves and geometrically reflected waves [10; 11]. When two different media come into contact with each other, ultrasonic behaviors, such as refraction, transmission, reflection, and diffraction, occur depending on the angle of incidence, and this is called the mode conversion of ultrasonic waves. The Rayleigh wave used in this study is classified as an ultrasonic wave, and it was generated through the mode conversion of ultrasonic waves. Here, the Rayleigh wave is leaked as a longitudinal wave with directionality through mode conversion in the incident direction.  
The Rayleigh wave speed of the sample is obtained using Equation (1) below [1; 13].  
\[C_{R}=\frac{C_{i}}{sin\theta_{i}}. \tag{1}\]  
Here, \(C_{R}\). denotes the Rayleigh wave speed of the piston rod, \(C_{i}\) is the ultrasonic speed in the water, and \(\theta_{i}\) is the Rayleigh angle. The Rayleigh angle was 29.1\({}^{\circ}\), and the speed of the surface waves obtained using Equation (1) was 3040 m/s.  
In order to perform the FEM simulation program, COMSOL Multiphysics 4.3 b was utilized; therefore, an acoustic-solid structure model was adopted to implement the ultrasonic mode conversion generated at the interface between the water and the solid surface. The propagation behavior of the Rayleigh wave was analyzed under the time domain. In the water area, except for the interface with the steel, the infinite plane was assumed by setting the plane wave radiation as the boundary condition. The behavior of the Rayleigh wave could be confirmed by simulating the ultrasonic signal as in Equation (2). Moreover, the center frequency was 10 MHz, the mesh size of the water was 0.02 mm, and the mesh size of the steel was 0.01 mm.
# Infectious Diseases Associated with Exposure to Pollutants in a Local Population from Mexico
## 3 Results
### Binary Logistic Regression  
The results of the binary logistic regression are presented in Table 3. The binary logistic regression model was statistically significant (\(p\) = 0.001; [PERSON] and [PERSON] R\({}^{2}\) = 35.5%, [PERSON] R\({}^{2}\) = 48.5%). A significant association was found between the development of infections, indicating strong explanatory power through risk conditions.  
The development of infectious diseases was significantly associated with geographical zone (\(p\) = 0.001), occupation (\(p\) = 0.045), tobacco consumption (\(p\) = 0.017), alcohol consumption (\(p\) = 0.017), and chronic degenerative diseases (\(p\) = 0.022). However, sex (\(p\) = 0.394) and age (\(p\) = 0.051) were predictive variables that were not significantly related to the development of infectious diseases in the population of the municipality of Acatzingo, Puebla, Mexico (Table 3). Interestingly, tobacco or alcohol consumption habits did not influence the presence of infectious diseases (OR = 0.222, 95% CI = 0.079-0.624, \(p\) = 0.004).  
\begin{table}
\begin{tabular}{l c c c c c c c} \hline \hline \multirow{2}{*}{**Predictor Variable**} & \multirow{2}{*}{**1 B**} & \multirow{2}{*}{**2 Odds Ratio [Exp B]**} & \multicolumn{2}{c}{**95\% CI**} & \multirow{2}{*}{\(p\)**-Value**} \\ \cline{5-6}  & & & & **Lower** & & \\ \hline Zones & & & & & & 0.001 * \\ Zone 1 & \(-\)3.265 & 0.038 & 0.016 & 0.090 & 0.001 * \\ Zone 2 & 0.155 & 1.167 & 0.600 & 2.271 & 0.648 \\ Zone 3 & 0.606 & 1.833 & 0.904 & 3.714 & 0.093 \\ Zone 4 & 0 & 1 & & & & \\ \hline Sex & & & & & & \\ Women & \(-\)0.270 & 0.763 & 0.410 & 1.421 & 0.394 \\ Men & 0 & 1 & & & & \\ \hline Age & & & & & 0.051 \\
30–59 years & 1.551 & 4.717 & 1.358 & 16.384 & 0.015 * \\
30–60 years & 1.408 & 4.090 & 0.886 & 18.878 & 0.071 \\
0–29 years & 0 & 1 & & & & \\ \hline Occupation & & & & & 0.045 * \\ Minors & 2.226 & 9.264 & 0.481 & 178.509 & 0.140 \\ Student & 1.285 & 3.615 & 0.353 & 36.990 & 0.279 \\ Farmer & \(-\)0.317 & 0.729 & 0.094 & 5.674 & 0.762 \\ Housewife & 0.911 & 2.486 & 0.302 & 20.466 & 0.397 \\ Businessman & 2.100 & 8.169 & 0.677 & 98.517 & 0.098 \\ Retired & 0 & 1 & & & & \\ \hline Smoker & & & & & 0.017 * \\
1–5 cigarettes/week & \(-\)1.505 & 0.222 & 0.079 & 0.624 & 0.004 * \\ More than 6 cigarettes/week & \(-\)0.709 & 0.492 & 0.022 & 11.003 & 0.655 \\ No smoking & 0 & 1 & & & \\ \hline \hline \end{tabular}
\end{table}
Table 3: Sociodemographic characteristics favorable for the development of infections in Acatzingo, Puebla, Mexico.
# A MAC Protocol to Support Monitoring of Underwater Spaces +
## 1 Introduction
Considering that in sensor networks, the data volume is usually low, and assuming average ocean parameters, the speed of sound in the water is close to 1.5 km/s; the carrier frequency is between 20 kHz and 70 kHz for distances larger than 1 km. The operating range to maintain sustainable communications at a reasonable baud rate, and with low corrupted data rates, is limited to 2 km point-to-point. The variance in the transmission times introduces uncertainty; therefore, the round trip time for a message is usually pessimistically evaluated, degrading the performance of the system [3]. Usually, underwater modems are built around a piezoelectric device, and the physical layer modulation scheme is based on frequency-shift keying with frequency-hopping (FH-FSK) [5]. There is a transversal component in these sensor networks that can be used to help address most of these challenges. This component is the medium access control (MAC) protocol used by the UWASN. Considering the needs and the challenges to implement underwater acoustic sensor networks and the limitations that the current approaches for implementing a MAC protocol for this type of network, this paper proposes an extended medium access control protocol based on time division multiple access (TDMA), but specifically for UWASN. The paper presents Underwater Self-organizing TDMA (UWSO-TDMA), a new hierarchical synchronization procedure that is performed following a top-down approach. The frame length and slot allocation process is made in a distributed way. Within each hop, only one node acts as a synchronization node and works as a sink of a particular sub-frame. Once the slot selection procedure is finished, the frame is reversed, so in just one frame, the messages in the leafs of the tree may reach the root or sink. The proposed approach prevents the hidden station problems. To the best of the authors knowledge, similar proposals have not been previously reported in the literature. The rest of the paper is organized in the following way. In Section 2, a short review of previous work is presented. In Section 3, the proposed MAC protocol is presented. In Section 4, a theoretical application example is presented, and in Section 5, a real application scenario is described. In Section 6, the evaluation process of this proposal is presented and discussed. Finally, in Section 7, we present the conclusions and future work.