esa-sceva/satcom-chunk-collection huggingface dataset:
# Sea Level Estimation Based on GNSS Dual-Frequency Carrier Phase Linear Combinations and SNR
## 1 Introduction
[28] used both L1 and L2 SNR data at a tide gauge site with GNSS to estimate a leveling tie between the two instruments and hence, estimate the ellipsoidal height of the tide gauge datum. [PERSON] et al. [29] were the first to use BDS (Beidou Navigation Satellite System)-Reflectometry to estimate sea level change based on SNR and triple-frequency phase and code combinations. [PERSON] et al. proposed a new method to retrieve sea level information from GNSS SNR data that relies upon inverse modelling of the detrended SNR, and the method was found to give an RMS error of 1.8 cm in the year of 2016 [30]. However, SNR is not always available in the raw GPS data files because it was thought to be of little or no use to most users of GPS [20]. Although L5 has been included in GPS, it is rarely included in the distributed data, such as in the public observation data of Plate Boundary Observation (PBO), and in the stations of the IGS (International GNSS Service) GPS network. Conversely, the combination of the two L-band carriers, L1 and L2, is always available and can be used to study multipath effects. In this paper, the GPS observations from PBO station SC02 are used to test our algorithms. Data from this GPS station have been used by several previous researchers. Sea level changes were successfully derived for the first time from SC02 GPS data by [PERSON] et al. [31]. [PERSON] et al. [32] used a standard analysis method to derive the sea level variances based on one-year of GPS L1 data at this station. [PERSON] et al. [33] used SC02 GPS station data to assess the quality of ten years of GPS-derived water levels. [PERSON] et al. used the GPS SNR data to derive the sea level at this station to verify their azimuth selection method. In order to verify the possibility of sea level retrieval using the L4 method, we also adopted this station as our test site [34].The aim of this paper is to present a method for retrieving sea level change data based on geometry-free linear combinations of dual-frequency carrier phase observations. At the same time, the SNR data from dual-frequency signals are also analyzed for extensive comparisons. The reminder of this paper is organized as follows: In Section 2, the methods of ground-based GNSS-R altimetry retrieval using the GNSS multipath effect are described in detail. In Section 3, an overall introduction to the experimental data and data processing strategies is provided, and the results of a data comparison with a nearby TG are analyzed. Finally, Sections 4 and 5 provide a discussion and conclusion of the study, respectively.
# Address Space Layout Randomization Next Generation
## 7 ASLR-NG: Address Space Layout Randomization Next Generation
### Profile Modes  
The ASLR-NG design provides two possibilities for allocating each object: isolated or in a specific-zone. From a security point of view, the more isolated objects, the better, but there are multiple side effects that should be carefully considered and balanced, as described in Section 6. In order to simplify the configuration of ASLR-NG, we provide four different working modes or profiles. Each mode randomizes each object using the isolated or the specific-zone method. The four modes are summarized in Table 3, and a representative example of each one is sketched in Figure 16. Next is the design rationale for each mode:  
**Mode 1--Concentrated:**: all objects are allocated in a single specific-zone, which results in a compact layout. The number of entropy bits is not degraded but only the correlation entropy between them. In other words, the cost (if brute force were used) to obtain the address of an object is not reduced by using this mode. The goal is to reduce the footprint of the page table.
**Mode 2--Conservative:**: this mode is equivalent to that used in Linux and PaX. The main stack, the executable and the heap are independently randomized, while the rest (libraries and mmaps) are allocated in the mmap specific-zone. Since the objects are randomized using the full allocation range, ordering is not preserved; for example, the stack may be below the executable.
**Mode 3--Extended:**: this is an extension of the conservative mode, with additional randomization forms: (1) specific-zones for sensitive objects (thread stacks, heap, huge pages, read-write-exec and only executable objects); (2) sub-page randomization of the heap and thread stacks and (3) per-fork randomization. This can be considered a very secure configuration mode  
Figure 16: ASLR-NG: Profile mode examples.  
which addresses most of the weaknesses and sets a reasonable balance between security and performance. Therefore, this should be the default mode on most systems.
**Mode 4--Paranoid:**: every object is independently randomized, and no specific-zones are used. As a result, there is no correlation between any objects, which could even prevent future sophisticated attacks. It is intended to be used on processes that are highly exposed, for example networking servers, but should be carefully used when applied globally to all system processes because of additional memory overheads.
# Advanced Sensor Integration and AI Architectures for Next-Generation Traffic Navigation
## 1 Introduction
### Paper Contributions  
The literature review analysis shows gaps concerning integrating all parameters, such as travel distance, traffic delays, estimated travel time, road safety, and road sensitivity, in selecting the best path to maximize traffic in urban areas.  
The main contributions of the paper are mentioned below:  
* Introduces Traffic Optimization Algorithm (TOA) that computes the Global Route Quality Indicator (_GRQlk_), integrating multiple parameters such as travel distance, traffic delays, estimated travel time, road safety, and road sensitivity for optimal route evaluation;
* The system employs ESP32-based sensors, including the MPU 6050 gyroscopes and accelerometers, for real-time detection of road anomalies such as potholes;* Azure's Safety Content is employed for real-time hazard detection, enabling classification and reporting of traffic-related incidents, such as accidents and violent events, to improve route selection dynamically;
* Demonstrates the effectiveness of IoT devices for collecting accurate, real-time traffic and road condition data with validated thresholds (e.g., 0.8 rad/s for pothole detection);
* The system allows a holistic assessment of route quality, balancing efficiency, safety, and road conditions by combining diverse metrics into the _GRQIK_;
* The study thoroughly evaluates the system, including _GRQIK_ performance across extreme scenarios, precision and recall of Azure's Content Safety Application Programming Interface (API), and practical examples of TOA application in real-world routing.  
These contributions collectively advance the field of intelligent traffic management by offering an adaptive solution for improving urban mobility.  
The paper is organized into five sections. Section 2 presents the methodology, outlining the system architecture, including IoT integration, the TOA, and _GRQIK_ calculation. The results are presented in Section 3 and focus on the evaluation of _GRQIK_, pothole detection accuracy, and Azure's Content Safety API. The discussion from Section 4 explores the implications, limitations, and recommendations for future research. Finally, Section 5 describes the conclusions, summarizes the findings, and emphasizes the study's contributions to intelligent traffic management.
## 4 Development and Validation of CFD/RBD Coupled Solvers
### CFD/RBD Co-Simulation Procedure
By the transformation relation mentioned in the section on a coordinate system, the \(x_{cm,I},y_{cm,I},z_{cm,I}\) and \(\varphi_{I},\theta_{I},\psi_{I}\) is transformed into \(x_{cm,C},y_{cm,C},z_{cm,C}\) and \(\varphi_{C},\theta_{C},\psi_{C}\), which are the centroid position and attitude angle of aircraft in the reference frame of the fluid computing domain. The last step is to update the computing dynamic mesh. The coordinates of the node on fuselage dynamic mesh are updated first. The coordinates of a fluid node of fuselage dynamic mesh in the body frame \(x_{f,B},y_{f,B},z_{f,B}\) are angular transformed by the angle of \(\varphi_{C},\theta_{C},\psi_{C}\) acquired in the last step and translated by \(x_{cm,C},y_{cm,C},z_{cm,C}\), by which the coordinates of the fluid node of fuselage dynamic mesh in the CFD frame \(x_{f,C},y_{f,C},z_{f,C}\) are obtained. The next is to complete the dynamic mesh update of the elevator, which can be divided into two cases. When there is no elevator deflection command in \(t\) time step, that is, when the elevator is in a neutral position, the coordinates of a fluid node of the elevator dynamic mesh \(x_{e,B},y_{e,B},z_{e,B}\) under the body frame can be transformed directly to \(x_{e,C},y_{e,C},z_{e,C}\) according to the angle and displacement calculated by RBD. Additionally, if there is a deflection of the elevator, the transformation of the coordinates of the elevator relative to the body frame should be achieved first, by which the coordinates of the deflected elevator in the body frame could be obtained:  
\[ \begin{array}{l}x_{e,local}=x_{e,B}-x_{o,local}\\ y_{e,local}=y_{e,B}\\ z_{e,local}=z_{e,B}-z_{o,local}\\ x_{e,B}^{\prime}=\cos(\Delta\phi_{e})*x_{e,local}-\sin(\Delta\delta_{e})*y_{e, local}+x_{o,local}\\ y_{e,B}=y_{e,B}\\ z_{e,B}=\sin(\Delta\delta_{e})*x_{e,local}+\cos(\Delta\delta_{e})*y_{e,local}+y_{ o,local}\end{array}  \tag{24}\]  
where \(x_{e,local},y_{e,local},z_{e,local}\) are the coordinates of the elevator in the local reference frame, \(x_{o,local},y_{o,local},z_{o,local}\) are the coordinates of the origin of the local reference frame relative to  
Figure 8: Program procedure of the CFD/RBD co-simulation. the body frame, \(x_{e,B},y_{e,B},z_{e,B}\) is the coordinate of undeflected elevator dynamic mesh in the body frame and \(x^{\prime}_{e,B},y^{\prime}_{e,B},z^{\prime}_{e,B}\) is the coordinate of deflected elevator dynamic mesh in the body frame, \(\Delta\delta_{e}\) is the elevator deflection angle by command. Finally, just like the operation in the first case, the coordinates of the deflected elevator dynamic mesh in the body frame were transformed into the mesh of the elevator in the fluid computational frame.
## 3 Analysis Models by CRM
### ANSYS Modeling  
To study the dynamic properties of the deployed reflector structure in orbit, the FEMs are established here. The typical materials widely used in aerospace engineering are listed in Table 1 with their mechanical parameters. The central hub, supporting bars, and petals use a kind of polymer composite material. The satellite interface and cables in cable replacement modeling method are made of aluminum alloy, while the joint pins are made of titanium alloy. Based on ANSYS modeling in Figure 3, the details of element information for each component are listed in Table 2. The element mesh of model is made as shown in Figure 3, considering the computing efficiency and accuracy. The shell element mesh size is reduced at the connection with other components to develop the local accuracy.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Material** & **Elastic Modulus (GPa)** & **Poisson’s Ratio** & **Density (kg/mm3)** \\ \hline Aluminum alloy & 70 & 0.33 & \(2.7\times 10^{-6}\) \\ Polymer composite material & 120 & 0.3 & \(1.7\times 10^{-6}\) \\ Titanium alloy & 108 & 0.34 & \(4.5\times 10^{-6}\) \\ \hline \hline \end{tabular}
\end{table}
Table 1: Material parameters.  
Figure 2: Schematic diagram of model details.  
The drag spring is connected with two adjacent petals through linkage butts at the end of each petal shown Figure 2a. Each linkage butt modeled as listed in Table 2 is fixed on the edge of the petal. The drag spring is established as a linear spring fixed on the end of two adjacent linkage butt with a pair of pre-tensioned forces T = 3.5 N. The FEM with drag springs is shown in Figure 4.
# Green Extraction of Valuable Compounds from Rubber Seed Trees: A Path to Sustainability
## 8 Challenges and Future Directions
### Sustainability and Industrial Scaling in Green Extraction for Rubber Seeds  
The intersection of sustainability and the potential for large-scale industrial application marks a critical juncture in the development of green extraction techniques for obtaining bioactive compounds from rubber seeds. Sustainability is the linchpin of these methods, emphasizing their commitment to environmental responsibility. By utilizing eco-friendly solvents and optimizing extraction parameters to minimize resource consumption, these green methods align perfectly with the global push for sustainable practices. The resulting reduction in environmental impact and the limited generation of hazardous waste make these approaches highly attractive to industries seeking eco-conscious alternatives.  
Transitioning from small-scale laboratory experimentation to full-fledged industrial implementation represents a significant leap, necessitating a keen focus on industrial scalability. The challenge lies in seamlessly translating the efficiency and effectiveness observed in controlled environments to larger operational scales. Engineers and researchers are meticulously fine-tuning processes, establishing methodologies for quality control, and developing strategies to ensure equipment compatibility and efficiency. Successfully bridging the gap between scientific experimentation and industrial reality holds the promise of harnessing the benefits of green extraction for widespread commercial applications.  
Within these challenges lie opportunities. While green extraction methods may require initial investments in specialized equipment, these costs are often offset by long-term advantages such as reduced resource consumption, minimized waste generation, and enhanced product quality. Moreover, the sustainability principles underpinning these methods resonate with environmentally conscious consumers, providing a distinctive marketing advantage. Additionally, the potential contribution to a circular economy, where waste from one process becomes a valuable resource for another, adds further value to the fusion of sustainability and industrial scalability.  
In essence, the harmonious integration of sustainability and industrial scalability is pivotal in unlocking the transformative potential of green extraction methods for rubber seeds. As these methods evolve, addressing challenges, refining processes, and fostering collaborations, they possess the capability to usher in a new era of environmentally conscious and economically viable approaches to extracting valuable bioactive compounds from rubber seed sources.
## 2 Data and Method
### Sources of Uncertainty and Datasets
#### 2.2.3 Uncertainties Obtained by Comparisons with Rain-Gauge Network
[20], assuming the various uncertainty sources to be independent, the error budget can be defined according to sampling, algorithmic and calibration error terms. In addition, as described by [PERSON] et al. [40], L3 satellite-based precipitation products can be affected by other errors that are linked, for instance, to the characteristics of the rain (i.e., intensity and occurrence), the climate and the environmental conditions, such as the seasonality, topography surface type, etc. Such performance distributions were summarized by [PERSON] et al. [11] for the Tropical Rainfall Measuring Mission (TRMM) Era. [PERSON] et al. [15] highlighted the importance of the density of gauges and its qualities as a reference for satellite-based precipitation assessments, as it is crucial for the success of categorical and continuous verification. In Brazil, the L3 satellite-based precipitation uncertainties, especially in terms of relative bias, were demonstrated to be as  
Figure 3: The relative difference distribution between satellite (GSMaP NRT) and ground-based data (\(y\)-axis, in %) as a function of the daily precipitation (\(x\)-axis, in mm day\({}^{-1}\)) over Brazil (land only) for December-January-February-March of three consecutive years (May 2014, June 2015 and July 2016). Panel shows the density scatterplot (colored scale) superimposed by the log-binned IQR distributions (in black) of the relative error vs. the daily accumulated precipitation (log-scale distributed). Outliers are represented by blue dots. sociated with distinct conditions, such as the surface type, precipitation regime, topography, gauge density, etc. [41; 42; 43; 44].
## 2 Comprehensive Comparison of Four Pole-Slot Ratio Schemes
### Comparison of Electromagnetic Performance of Four Kinds of Pole-Slot Motors
It can be seen from this figure that the efficiencies of the four motors were not much different, and the efficiencies of the 70P84S motor and the 80P90S motor were the highest, reaching more than 96%. However, the power factor of the 70P168S motor was much lower than those of the other three motors, only 0.915. In addition, because the end of the distributed winding was longer, the copper loss of the 70P168S motor was the largest, reaching 857 W. Due to the rich harmonic content, the eddy current loss of the permanent magnet of the 70P84S motor and the 80P90S motor was the largest, both exceeding 100 W. The iron loss of 80P180S motor was the largest, reaching 723 W.  
Figure 4: The no-load magnetic cloud diagram and magnetic line diagram of four pole–slot ratio motors. (**a**) 70P84S. (**b**) 70P168S. (**c**) 80P90S. (**d**) 80P180S. Figure 5: The output torque and maximum torque curves of four pole-slot ratio motors. (**a**) Output torque curves. (**b**) Maximum torque curves. The electromagnetic performance of the four pole-slot ratio motors is summarized in Table 2. When the size of the stator and rotor, the current density, the amount of permanent magnet and the no-load back EMF were equal or similar, the efficiencies of the four motors were basically the same. The power factor of the 70P168S motor was low, but it met the performance requirements of the motor. In addition, the torque ripple of the 70P168S motor was only 1.4%, and the maximum output torque ratio reached 4.48 times. These two performances were excellent.
# Heterologous Production of Flavour and Aroma Compounds in _Saccharomyces cerevisiae_
## 3 Heterologous Compounds Derived from Intermediates of the Mevalonate Pathway  
### Isoprenoids  
Isoprenoids (also known as terpen or terpenoids) are a large group of diverse organic compounds that encompass thousands of different chemical forms and which are mainly observed as the products of plants. Despite their chemical diversity, all isoprenoids are biosynthesized from the basic unit isoprene (C\({}_{5}\)H\({}_{8}\)), with different subclasses of compounds classified according to the number of isoprene units (hemiterpenes, monoterpenes, sesquiterpenes, and diterpenes with 1, 2, 3, and 4 isoprene units, respectively). Many of the compounds belonging to the terpene group are toxic and/or display unpleasant, irritant odours and are used by host plants to deter predatorial foraging and pathogen invasion [30]. However, a small selection of specific isoprenoinds have found application in variety of industries, including food and beverage as attractive flavouring additives.
# Hyperbolic Asynchronous Method of a Radio Navigation Technique
###### Abstract  
Humans have always wanted to determine positions in an unknown environment. At the beginning, methods were simple. They were based on the observation of characteristic points--in the case of shipping, additional observations of the coastline. Then came navigation based on astronomical methods (astronavigation). At the beginning of the XX-th century, a new way of determining the current location was developed. It used radio wave signals. First came radio beacons, then ground-based systems. Currently, satellite systems are being used. At present, the most popular one is the Global Positioning System (GPS). This system is fully controlled by the Department of Defense, and only the U.S. forces and their closest allies have been guaranteed the accuracy offered by the system. Armies of other countries can only use the civilian version. This situation has engendered the need for an independent radiolocation system. This article describes the construction and operation of such a technology demonstrator that was developed at Gdansk University of Technology. The main advantage of the system is the ability to manage it without the chain organization of the reference stations, which currently work with each other asynchronously. This article demonstrates the functionality of such a system. It also presents results and analysis of its effectiveness.  
radio navigation technique; mobile navigation; hyperbolic method; TDOA localization; asynchronous algorithm; spread spectrum technique; self-organized system; ground-based applications; theoretical investigations; measurement testbed; measurement verifications +
Footnote †: journal: Applied Sciences
## 4 Conclusions  
By analyzing the distribution characteristics of blade stress, axial thrust, and wind turbine power output under periodic dynamic yaw conditions, the following conclusions were drawn:  
(1) During dynamic yaw, the distribution of blade stress on the windward side is consistent with that on the leeward side. The distribution trend of blade stress shows an increase, followed by a decrease, from the inside out along the span direction, and the stress values near the blade root exhibit significant fluctuations. When the azimuth angle of the blade is 0\({}^{\circ}\), the maximum stress value is located at the maximum chord length of the blade.  
(2) Within the range of a 10\({}^{\circ}\) to 30\({}^{\circ}\) yaw variation period, the stress value during positive yaw is greater than that during negative yaw. With the increase in the tip speed ratio, the stress values of dynamic windward yaw gradually exceed those of leeward yaw, and the highest stress value occurs in the range of \(-5^{\circ}\) to 15\({}^{\circ}\). The stress value of the blade is presented as a cosine distribution during yaw fluctuations, and the maximum stress value can increase by 2.22%, while the minimum stress value can decrease by 13.85%.  
(3) The three-blade axial thrust is presented as a cosine distribution with yaw fluctuations. The axial thrust exhibits varying degrees of fluctuation with dynamic yaw, with a maximum increase of 1.75% and a minimum decrease of 19.97%.  
(4) The output power of the wind turbine decreases with the increase in the yaw angle, and exhibits a cosine variation with yaw fluctuations, with a maximum reduction of 25.58%.  
The results of this study can support the effective and sustainable use of wind energy in the circular economy by serving as a theoretical foundation for structural design of wind turbines and yaw control systems that take dynamic yaw operation into account. In future research, the impact of aeroelastic coupling on blade stress will be considered, as well as the optimization design of blades based on existing research results.  
Methodology, L.Z.; Validation, Y.B.; Writing--original draft, Y.Z.; Writing--review & editing, [PERSON] and J.W.; Supervision, J.W. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Inner Mongolia Agricultural University high-level/Excellent Doctor talent introduction research project, grant number NDYB2021-29; the Scientific Research Projection of Higher Schools of Inner Mongolia, grant number NJZY23115; the Inner Mongolia Autonomous Region Natural Science Fund, grant number 2023 QN05039; the Inner Mongolia Autonomous Region Natural Science Fund, grant number 2019 MS05022; the National Nature Science Foundation of China, grant number 52066013; and the National Nature Science Foundation of China, grant number 52066014.  
Not applicable.  
Figure 17: Time–domain diagram of maximum stress variation with yaw angle.