esa-sceva/satcom-chunk-collection huggingface dataset:
# Centralized MPPT Control Architecture for Photovoltaic Systems Using LoRa Technology
###### Abstract  
Maximum power point tracking (MPPT) algorithms are necessary to optimize the power generation in solar photovoltaic (PV) power plants. Typically, MPPT control systems depend on the wired connections among sensors, processing nodes, and DC-DC power converters. However, Low-Power Wide-Area Networks (LPWANs) allow for centralizing the execution of MPPT algorithms wirelessly, achieving more flexibility and reducing costs. In particular, LoRa/LoRaWAN is a low-cost/low-consumption technology with an excellent immunity to interference, which is able to operate over tens of kilometers. This article presents a centralized MPPT control architecture for PV systems based on the LoRa/LoRaWAN technology. This technology provides long-range/low-cost wireless connectivity with PV plants located far away. The presented approach allows for executing in parallel, on a central computing node, different MPPT algorithms for distinct PV subsystems. A proof-of-concept prototype was implemented to experimentally validate the architecture. It involved a rooftop PV system and a DC-DC converter connected to a computer, which executes the MPPT algorithms, by means of a point-to-point LoRa network. For validation purpose, two MPPT control techniques were implemented: Perturb and Observe (P&O) and Sliding Mode Control (SMC). However, the presented approach allows for the implementation of more sophisticated MPPT algorithms for optimizing energy production. The obtained results prove the validity of the concept and suggest that the proposed low-cost approach can be extrapolated to be used with LoRaWAN networks.  
photovoltaic systems; centralized control; MPPT; LoRa Article
# High-Speed Visible Light Communications: Enabling Technologies and State of the Art
## 2 Potentials of VLC System
### Safe  
The health hazards of radio frequency have attracted increasing attention. Under long-term exposure to strong electromagnetic radiation, the function of the human body may suffer from a certain degree of hurt. Therefore, wireless communications generally need to limit their own transmitting power, which can greatly affect system performance. VLC uses LEDs emitting white light for lighting, which is the same as natural light, and almost harmless to the human body. Such advantages make VLC communication a popular alternative when health considerations are taken into account.
## 4 Results and Discussion
### Height Estimation of Single Objects
#### 4.4.3 Buildings
If for Pleiades data a 2D minimum building size of 7.5 m length by 6 m width is needed in order to get \(p>50\%\), for WorldView-3 data only 4 m \(\times\) 2.5 m is needed. The mean value for the residual heights corresponding to reconstructed buildings with \(p>50\%\) (of 2.02 m for Pleiades with 0.7 m GSD) is comparable with the residuals of 1.94 m obtained by [18] when using a DSM from a GeoEye stereo pair (0.5 m GSD). Figure 9: Interval-based percentage and standard deviation for height estimation of buildings depending on (**a**) lengths; (**b**) widths.
# Partial Discharge Wideband Full-Band High-Gain Resonant Cavity UHF Sensor Research
## 2 Principle of Antenna  
### The Basic Principle of Monopole Patch Antenna  
A monopole patch antenna is a very common antenna, which usually consists of a radiating patch on a thin dielectric substrate and a relatively grounded metal floor for receiving electromagnetic signals propagating in space and feeding through coaxial probes, microstrip, or coplanar waveguides, with the advantages of a low profile, small size, and simple fabrication [14].  
The planar monopole patch antenna can be approximated with an equal height cylindrical structure [15], as shown in Figure 1, where the orange area in Figure 1b is the metal radiating electrode and the yellow is the metal floor. When the cylindrical structure is cut and expanded along its height, the rectangle obtained from this cylindrical structure is the estimated rectangular radial patch:  
\[2\pi RL=ab \tag{1}\]  
where \(R\) is the base radius of the equivalent cylinder, \(L\) is the height of the equivalent cylinder, \(a\) is the width of the radiating patch of the monopole antenna, and b is the length of the radiating patch.  
Figure 1: Monopole patch antenna schematic: (**a**) Cylindrical Structure; (**b**) Antenna prototype.  
The real part of the input impedance of the monopole patch antenna is slightly less than 1/4 wavelength monopole length while considering the gap \(g\) between the metal floor and the radiation patch, the lowest working frequency \(f_{L}\) of the antenna is obtained as follows:  
\[f_{L}=\frac{c}{\lambda}=\frac{72}{L+R+g} \tag{2}\]  
where \(c\) is the speed of light and \(\lambda\) is the wavelength corresponding to the lowest operating frequency. After considering the effect of the dielectric substrate on the resonant frequency of the antenna, Equation (2) is corrected, that is  
\[f_{L}=\frac{c}{\lambda}=\frac{72}{(L+R+g)\sqrt{\epsilon_{\mathit{eff}}}} \tag{3}\]  
where \(\epsilon_{\mathit{eff}}\) is the equivalent dielectric constant. It can be estimated as  
\[\epsilon_{\mathit{eff}}=\frac{\epsilon_{r}+1}{2} \tag{4}\]  
where \(\epsilon_{r}\) is the relative permittivity of the substrate.  
The above theory can be used to estimate the starting size of the monopole patch antenna. Subsequently, the design can be optimized on this basis to achieve the desired performance.
# Pasteurization of Foods with Ultrasound: The Present and the Future
## 3 Microbial Inactivation
In several countries, there are specific limits on AFM\({}_{1}\); in the United States, the Maximum Residue Level (MRL) for AFM\({}_{1}\) is 0.5 ug/L [58]. Few promising studies have been conducted with parasites and ultrasound [70; 71]. Although the studies are focused more on wastewater and effluents, the effect of ultrasound on the oocyst viability can be easily transferred to those food products in which the presence of parasites became a safety problem, such as herbs, salads, and fresh produce. The Centers for Disease Control and Prevention [72] list _Cyclospora_ as the main parasite of concern in recent foodborne outbreaks. Hence, the importance of ultrasound research for parasite inactivation in food safety. [PERSON] et al. [70] studied the effect of ultrasound (20 kHz, 53.1, 70.8, and 88.5 W/cm\({}^{2}\)) on the oocyst viability of _Cryptosporidium parvum_, a protozoan parasite of concern in water. Their findings listed the reduction of oocyst viability from 98.57% to only 4.16% in distilled water after 10 min of treatment. Finally, an area of concern in ultrasound is related to sublethally injured cells and how some microorganisms can recover from storage as viable cells. Microorganisms can use homeostasis mechanisms (i.e., metabolic and chemical reactions) to repair injuries and recover from stress. This is a critical point that could lead to a food safety risk. Several studies show that hurdle technology and sonication can reduce the number of sublethally injured cells [25; 28; 73]. Sublethal injured cells have been observed in several novel technologies such as pulsed electric fields [74; 75], ohmic heating [76], radio frequency [77], high-pressure carbon dioxide [78], high pressure, and cold plasma [73], among others.
# Tuning the Cell and Biological Tissue Environment through Magneto-Active Materials
## 4 Fundamentals of Smart Polymeric Materials: Focus on Magneto-Active Elastomers and Hydrogels
### Magnetorheological Elastomers (MREs)
#### 4.2.1 Fabrication of Magnetorheological Elastomers  
**The synthesis of MREs** includes the conventional methods for elastomers fabrication, as well as novel methods, such as 3D printing. In this section, we will focus on the conventional methods. In them, the mixture of magnetic particles and the matrix material is crosslinked, cured or vulcanised in a mould. Therefore, magnetizable particles stay locked within the polymeric network after the mixture is completely crosslinked. The mould defines the dimensions, such as the thickness and width of an MRE to be developed [121]. A new step arises in the fabrication of MREs as the disposition of the magnetic particles inside the matrix can be defined in the curing process. In the presence of a magnetic field during the curing process, the magnetic particles are oriented and aligned in the direction of the magnetic field, and the resulting MRE has an oriented, anisotropic structure consisting of chains of particles. MREs cured without the magnetic field results in a well-dispersed distribution of particles with no particular orientation and, therefore, the result is an isotropic structure. Apart from the presence of a magnetic field during the process of curing, the distribution of magnetic particles in MREs is influenced by many factors,such as the interaction forces between particles (in the case of hard-magnetic particles), sample size, volume fraction of particles and temperature. However, while understanding the influence of these factors during MRE fabrication is important, it is extremely difficult for experimental and computational methods.
## 1 Introduction
The temporal decoherence of echo induced by turbulence could add an extra random phase, which deteriorates the phase stability of the echo and results in imperfect performance at the receiver. Therefore, the size and variation speed of the phase fluctuation are the main factors to corrupt the desired signal, which leads to high-resolution ISAL imaging losing its unique advantage. To analyze the temporal decoherence of the echo induced by turbulence, the atmospheric coherent time is defined [18] to describe the variation speed of the phase fluctuation of the echo. The atmospheric coherent time can be improved by increasing the wavelength and adjusting the transmitting and receiving parameters properly. Then, we investigate its influence on ISAL images. According to heterodyne detection and the ISAL image principle, we demonstrate that the relationship between the pulse duration time and atmospheric coherent time determines the ISAL imaging quality. It is shown that our proposal can effectively mitigate the adverse effect of atmospheric turbulence on ISAL and can improve image quality. This paper is organized as follows. In Section 2, the main methods used in this paper are briefly introduced, including the infinitely long phase screen method, heterodyne detection process, and range-Doppler (R-D) algorithm. In Section 3, we investigate the influence of atmospheric turbulence with the R-D algorithm on ISAL imaging and evaluate the correction effect of our proposed relative size to compensate for the turbulence-induced phase error for ISAL images. In Section 4, we discuss the ISAL imaging results and conclude the paper.
# IoT-Chain and Monitoring-Chain Using Multilevel Blockchain for IoT Security
## 1 Introduction
### Motivation  
Blockchain technology is used to solve the problem of centralized structures [11]. Blockchain is a distributed system that shares information with all non-central participants and distributes data to all network nodes using a peer-to-peer (P2P) network. The problem of data forgery and falsification of existing centralized servers can be solved by allowing nodes in all networks to store the same data. In addition, by securing the reliability of data through an inter-node consensus algorithm, the security problem of IoT devices can be solved with the blockchain function.  
However, due to the limitations of blockchain technology, there is a limit to operation in IoT devices, and high-performance external cloud and edge computing technologies are used. This guarantees the immutability of the stored data, but it goes through multiple gateways and nodes during the storage process and cannot guarantee the reliability of the data. **Therefore, the blockchain-based IoT data management method cannot achieve decentralization and cannot solve the limitations of the existing centralized structure.**
## Materials and Methods  
### Study Sites  
The monitoring of rainfall parameters and splash erosion measurements was located at two sites in Austria and one in the Czech Republic (Figure 1). The Austrian sites, Petzenkirchen (48\({}^{\circ}\)9\({}^{\prime}\)17\({}^{\prime\prime}\) N, 15\({}^{\circ}\)14\({}^{\prime}\)46\({}^{\prime\prime}\) E) and Mistelbach (48\({}^{\circ}\)34\({}^{\prime}\)59\({}^{\prime\prime}\) N, 16\({}^{\circ}\)35\({}^{\prime}\)15\({}^{\prime\prime}\) E), are situated in the region of Lower Austria, where most of the country agricultural activity takes place. The Czech site was located in Prague (50\({}^{\circ}\)6\({}^{\prime}\)17\({}^{\prime\prime}\) N, 14\({}^{\circ}\)23\({}^{\prime}\)15\({}^{\prime\prime}\) E). The long-term, average annual precipitation for the three sites is 902, 537 and 459 mm for Petzenkirchen, Mistelbach, and Prague, respectively [45; 46; 47]. According to data measured by [PERSON] and [PERSON] [48] in Lower Austria, most of the erosive storms occurred during the summer period. [PERSON] et al. [49] also confirmed the highest rainfall erosivity during summer in the Central European region. Therefore, the selected monitoring period was during late spring and summer from 2017 to 2019.  
Figure 1: Location map of the study sites in Austria (Petzenkirchen and Mistelbach) and the Czech Republic (Prague), marked with solid dots, and locations of the soil sampling sites (Zwerbach, Mistelbach and Bilkovice), marked with solid triangles.
# Off-Resonance Control and All-Optical Switching: Expanded Dimensions in Nonlinear Optics
## 3 Laser-Modified Absorption
If the fixed frequency lies anywhere in the wings of an absorption band as depicted by Figure 3a,b, from a different (preferably higher) frequency region than the range of the linear absorption measurements, then the associated near-resonance enhancement of the quasi-hyperpolarizability tensor may contribute many further orders of magnitude enhancement to the significance of laser-modified effects. It is interesting that excitation of a molecule to a metastable state, i.e., one that is one-photon forbidden by orbital symmetry properties, may become possible by input of the off-resonant beam,  
Figure 3: Positions of potential resonance levels for laser-modified single-photon processes of absorption (**a**,**b**) and fluorescence (**c**,**d**). For simplicity, the off-resonant beam is not shown. In each instance, the vertical black arrow shows the overall transition, and green dotted arrows together denote a sequence for one of the interaction permutations approaching one or more resonances; a purple dotted line indicates a one-photon resonance level and a purple dashed line indicates a two-photon resonance; grey dotted lines indicate an energetically forbidden resonance: (**a**) single-photon absorption of optical frequency \(\omega\), with off-resonant frequency \(\omega^{\prime}>\omega\); (**b**) as in (**a**), with \(\omega^{\prime}<\omega\); (**c**) single-photon emission at frequency \(\omega\), with off-resonant frequency \(\omega^{\prime}>\omega\); (**d**) as in (**c**), with \(\omega^{\prime}<\omega\). since the resulting three-photon mechanism for access to a conventionally symmetry-unfavorable state could then become allowed [55]. This enables a population of a 'dark' state--a transition that would otherwise be improbable. For such an effect to occur would, however, demand the levels of intensity routinely associated with three-photon absorption measurements. In another connection with multiphoton absorption, it is also noteworthy that an off-resonant beam can alter the rate of two-photon absorption through a fourth-order perturbation effect [52].
## 3 Modeling and Data Sources
### Models  
#### 3.1.1 Stepwise Regression Model  
The Stepwise Regression Model (SRM) is an efficient statistical method predominantly used for selecting the most influential predictive variables from a large pool of potential predictors, while concurrently eliminating those with minimal predictive impact. This approach, through an automated variable selection process, significantly streamlines the construction of linear regression models, making it particularly apt for handling complex and high-dimensional datasets [24]. Beyond its widespread application in forest fire prediction, the practicality and methodological rigor of the SRM have been corroborated in various research domains. For instance, studies by [PERSON] and colleagues, conducted in the context of travel impedance analysis, have explored the adaptability and effectiveness of the SRM across diverse research fields. Such interdisciplinary references not only validate our choice of this method but also enhance our understanding of the application value of the SRM in environmental science and statistical research [25].  
The stepwise regression model is shown in Equation (1):  
\[Y=\beta_{0}+\beta_{1}X_{1}+\beta_{2}X_{2}+\beta_{3}X_{3}+\beta_{4}X_{4}+\varepsilon \tag{1}\]  
\(Y\) is the dependent variable,  
\(\beta_{0}\) is the intercept, the expected value of \(Y\) when all explanatory variables are zero,  
Figure 2: Research framework.  
\(\beta_{1}\), \(\beta_{2}\), \(\beta_{3}\)... are the coefficients of the explanatory variables, indicating the expected change in \(Y\) per unit change in the variable.  
\(\varepsilon\) is the error term, representing random variation not explained by the model.  
Factor Selection: Climatic factors play a pivotal role in the causation of forest fires. Elevated temperatures dry out forest vegetation, increasing flammability and thereby the risk of fires. Increased rainfall inhibits the occurrence and spread of fires. Prolonged rainfall deficiency leads to low water content in vegetation and soil, raising the likelihood of fires. Higher wind speeds facilitate the spread of flames, accelerating fire propagation. Variability in wind direction and strong winds exacerbate the difficulty and risk of fire control. Under low humidity conditions, vegetation and surface materials are more combustible, raising the fire hazard. Diurnal variations in humidity significantly affect fire occurrences, with higher nighttime humidity reducing fire risk and vice versa. Temperature, rainfall, wind speed, and humidity significantly influence the incidence and spread of forest fires through various mechanisms [26]. Understanding these effects is crucial for forest fire prevention and the formulation of effective forest management and emergency response strategies.
# A Review of Thermal Error Modeling Methods for Machine Tools
###### Abstract  
Thermal error caused by thermal deformation is one of the most significant factors influencing the accuracy of the machine tool. Compensation is a practical and efficient method to reduce the thermal error. Among all the thermal error compensation processes, thermal error modeling is the premise and basis because the effectiveness of the compensation is directly determined by the accuracy and robustness of modeling. In this paper, an overview of the thermal error modeling methods that have been researched and applied in the past ten years is presented. First, the modeling principle and compensation methods of machine tools are introduced. Then, the methods are classified and summarized in detail. Finally, the future research trend of thermal error modeling is forecasted.  
precision  
the key heat source temperature of the machine tool on the thermal error through analysis, statistics, and induction. By studying the functional relationship between the thermal error and the key heat source temperature, the thermal error model is obtained. Based on this model, the thermal error is predicted and then compensated [13]. Compared with the error avoidance method, it is a more convenient and cost-efficient way to reduce the thermal error by compensation [14; 15]. The thermal error compensation principle diagram of a CNC machine tool spindle is shown in Figure 1. By inserting the compensation signal generated from the thermal error model into the feedback loop of the servo system, the error compensation is achieved.  
In this paper, the existing thermal error modeling methods for machine tools that have been researched and applied in the past ten years are introduced, classified, and summarized. The classified modeling methods are cited in the article according to the time of publication. The advantages and disadvantages of these modeling methods are compared in Section 3, and the future research trend is forecasted in Section 4.
# A Coalition Formation Game Approach for Efficient Cooperative Multi-UAV Deployment
## 4 Simulation Results and Discussion  
In this section, we carry out simulations to verify the convergence and effectiveness of our proposed approach. Given the simulation parameters in [25], we set \(E_{0}=50\) nJ/bit, \(\varepsilon_{s}=10\) (nJ/bit/m\({}^{2}\)), \(\varepsilon_{l}=10\) (nJ/bit/m\({}^{4}\)). The mission area is uniformly divided into \(50\times 50\) cells (each cell's width is 10 m). We consider a UAV network consisting of one central control UAV \(\big{(}g^{ccn}=(15,15,40)(\times 10\) m\big{)}\) and a certain number of UAVs for data collecting and transmission, whose flying altitudes are all set to 30 (\(\times 10\) m). All UAVs' detection ranges are set to be 50m. The amount of data traffic per unit coverage reward is denoted as 1000 MB.
## 2 Materials and Methods
### Study Population  
Three different datasets were utilized in this study. The first two datasets correspond to the EVasCu [15] and VascuNET [16] studies, which are cross-sectional studies that were conducted in Cuenca, Spain, to evaluate vascular health in apparently healthy populations. While both studies shared a common goal, they were carried out in different periods and  
Figure 1: General outline of the stages within the methodology. Abbreviations: LR = Linear Regression, PR = Polynomial Regression, BR = Boosted Regression (Gradient Boosting), SVR = Support Vector Regression, NN = Neural Network, MSE = Mean Squared Error, RMSE = Root Mean Squared Error, R**2 = \(R^{2}\) = Coefficient of Determination.  
with distinct participant cohorts. Thus, the EVasCu study was conducted between October and December 2022, while VascuNET was carried out between March and November 2024. Additionally, the recruitment strategies and geographic distribution of participants varied between studies, further contributing to sample diversity. Both studies followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement guidelines for reporting observational studies [17].  
The third dataset corresponds to the ExIC-FEp Study [18], which includes both healthy control subjects and patients diagnosed with heart failure with preserved ejection fraction. The recruitment of these patients was carried out in the Cuenca I, II, and III primary health centers, as well as in the cardiology and internal medicine departments of the Hospital Virgen de la Luz, part of the Castilla-La Mancha Health Service (SESCAM), between 2023 and 2024.  
It is worth noting that all datasets were collected directly by the research team through clinical fieldwork conducted in real healthcare settings, and the research protocol of this study was approved by the Clinical Research Ethics Committee of the Cuenca Health Area (EVasCu (REG: 2022/PI2022), VascuNET (REG: 2023/PI1823), and ExIC-FEp (REG: 2022/PI2122)). Written informed consent to participate was obtained from all subjects included in the study. All procedures performed in this study were in accordance with the Declaration of Helsinki and its later amendments or comparable ethical standards for experiments involving humans [19].  
Table 1 provides a summary of the key demographic characteristics of the datasets used in this study, including the total number of participants, sex distribution, and age statistics (mean and standard deviation). Additionally, \(t\)-tests were conducted to evaluate differences in gender distributions across datasets.