esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Solvents for CO\({}_{2}\) Capture
### Chemical Solvents  
In contrast to the physical solvents that rely solely on the solubility of CO\({}_{2}\) in the liquid phase, chemical solvents exploit the selective reaction between CO\({}_{2}\) and the solvent molecule, either in a separation column or in a membrane module, to further enhance the rate of separation. The flue gas is brought into contact with the solvent and the different reactions taking place in the liquid phase determine the efficiency of the chemical absorption of CO\({}_{2}\). Aqueous amine solvents for chemical absorption of CO\({}_{2}\) are considered to be a robust technology. A very large number of CO\({}_{2}\) capture solvents has already been developed and used routinely in both industrial and pilot scales, while research is still ongoing for the identification of new molecules with targeted optimal properties. Such molecules range from the more mature amines to the more recently developed phase change solvents (PCSs) and ionic liquids (ILs). In all cases, certain performance indicators need to be maximized for the consideration of each solvent according to the application. One of the most important indices is the CO\({}_{2}\) cyclic capacity, commonly referred to as the working capacity, which is the difference in the amount of CO\({}_{2}\) captured per mol of solvent before and after the reaction has taken place. Such a property is linked to thermodynamics in the form of the vapor-liquid equilibrium (VLE) as well as to the kinetics of the chemical system. Vapor pressure and viscosity play an important role for the assessment of chemical solvents as they indirectly affect the regeneration strategy and associated required energy. In addition, the solvent's resistance to thermal and oxidative degradation, in cases where oxygen is also present in the inlet stream, represents a measure of the process viability as it is directly associated with the need of replacement or the use of make-up streams in order to maintain steady state conditions.
# A TCP Acceleration Algorithm for Aerospace-Ground Service Networks
## 3 Transmission Acceleration Using BoostTCP  
This paper proposes the BoostTCP, which represents a learning-based TCP transmission acceleration method based on transmission history learning. By improving the judgment and handling of congestion, the BoostTCP can judge and recover packet loss more accurately and rapidly, thus accelerating TCP transmission and increasing TCP connection stability.
# The Quanta Image Sensor: Every Photon Counts
###### Abstract  
The Quanta Image Sensor (QIS) was conceived when contemplating shrinking pixel sizes and storage capacities, and the steady increase in digital processing power. In the single-bit QIS, the output of each field is a binary bit plane, where each bit represents the presence or absence of at least one photoelectron in a photodetector. A series of bit planes is generated through high-speed readout, and a kernel or \"cubicle\" of bits (x, y, t) is used to create a single output image pixel. The size of the cubicle can be adjusted post-acquisition to optimize image quality. The specialized sub-diffraction-limit photodetectors in the QIS are referred to as \"jots\" and a QIS may have a gigajot or more, read out at 1000 fps, for a data rate exceeding 1 Tb/s. Basically, we are trying to count photons as they arrive at the sensor. This paper reviews the QIS concept and its imaging characteristics. Recent progress towards realizing the QIS for commercial and scientific purposes is discussed. This includes implementation of a pump-gate jot device in a 65 nm CIS BSI process yielding read noise as low as 0.22 e-- r.m.s. and conversion gain as high as 420 uV/e--, power efficient readout electronics, currently as low as 0.4 pJ/b in the same process, creating high dynamic range images from jot data, and understanding the imaging characteristics of single-bit and multi-bit QIS devices. The QIS represents a possible major paradigm shift in image capture.  
photon counting; image sensor; quanta image sensor; QIS; low read noise; low power
# Sensor Fusion of GNSS and IMU Data for Robust Localization via Smoothed Error State Kalman Filter
## 2 GNSS and IMU Integrated Filter Design
### Error State Kalman filter  
For the formulation of the error state filter, the system states are defined as the true, nominal, and error state values. The true state is expressed as a combination of the nominal and error states. The approach is to treat the nominal state as a dominant signal, which is highly nonlinear, and the error state as a small signal, which is linearly effective and suitable for linear Gaussian filtering. The nominal state vector of \([\mathbf{p},\mathbf{v},\mathbf{q},\mathbf{a}_{b},\mathbf{\omega}_{b}]^{T}\) is used in this study, where the additional dimension appears due to the quaternion representation used for rotation, the quaternion method is widely used in attitude update because it only requires the calculation of matrix differential equations, which is relatively small in computation and can avoid the singular value problem of Euler angles. In this paper, the quaternion method is used to solve the attitude of the carrier. The operators \(\mathbf{q}\) and \(\mathbf{R}\) represent, respectively, the quaternion corresponding to the axial angular vector \(\mathbf{\theta}\) and its rotation matrix. In addition, the error state vector is \([\delta\mathbf{p},\delta\mathbf{v},\delta\mathbf{q},\delta\mathbf{a}_{b},\delta\mathbf{\omega}_{b} ]^{T}\). The relevant symbol definitions of true, nominal, and error state are listed and compared in Table 1.
# LoRaWAN Physical Layer-Based Attacks and Countermeasures, A Review
## 2 LoRaWAN
### LoRaWAN Packet Structure  
Figure 4 delivers an overview of the messages involved in LoRaWAN [6]. Each LoRaWAN payload is contained in a physical-layer LoRa packet, which includes a preamble, a physical-layer header and a CRC code. These fields are necessary for LoRa-receiver synchronization, LoRa-receiver demodulation parameters (e.g., coding rate setting) and CRC-error correction. The LoRaWAN payload itself (PHY payload) conveys the MAC message, which, in turn, holds the MAC-payload, join-request, rejoin-request or join-accept parts. The MAC payload contains the frame header, frame port and the frame payload. The first two fields are utilized to, firstly, communicate the MAC commands and, secondly, to carry further important information including the device address and the frame parameters. For the latter, the frame control field specifies, e.g., whether or not the adaptive data rate and/or packet acknowledgement shall be enabled. Further, the frame-counter field contains a counter value, which is utilized to keep track of the number of packets exchanged between an end device and a gateway. The frame-options field is an optional data field carrying the MAC commands. Finally, the frame-payload field carries LoRaWAN application data.  
Figure 3: (a) I\(-\)branch of the LoRa signal. (b) Spectrogram of the LoRa signal.
## 4 Impact of Aerosols on Thunderstorm Processes and Lightning Activity  
Social production activities and daily life are heavily concentrated in urban areas [69]. As urban construction operations proceed, significant amounts of energy are consumed, leading to the emission of air pollutants and anthropogenic heat into the atmosphere. This alters the composition and structure of the near-surface atmosphere [21], ultimately shaping the local climate of the city [70; 71]. The primary air pollutants emitted by vehicles and industrial activities in urban areas include sulfur dioxide (SO\({}_{2}\)), particulate matter (PM), and other air pollutants [72].  
Scholars have conducted comprehensive research on the influence of aerosols on lightning activity, exploring the intricate relationship between these atmospheric components and their role in modulating lightning occurrence [11; 32; 43; 73; 74; 75; 76; 77; 78; 79; 80]. [PERSON] and [PERSON] [43] utilized lightning detection data to analyze the lightning activities in various Spanish cities and found that higher concentrations of SO\({}_{2}\) correlate with an increase in CG flashes. [PERSON] et al. [75] discovered by analyzing air pollutant data that aerosols can extend the duration of thunderstorms and increase lightning frequency. [PERSON] and [PERSON] [76] observed an increase in lightning activity in the southern Indian city of Bangalore and attributed this trend to increasing aerosol concentrations. [PERSON] et al. [63] concluded that a higher concentration of SO\({}_{2}\) contributes to the enhancement of CG lightning flashes, and the contribution of the PM\({}_{10}\) concentration did not appear in this study to be as significant as SO\({}_{2}\) in the enhancement of CG lightning flashes. [PERSON] and [PERSON] [77] found that aerosols can impact the microphysical processes of thunderstorms, promoting the electrification process within thunderstorm clouds, ultimately leading to an increase in  
Figure 5: CG flash density of a total thunderstorm (**a**), super thunderstorm (**b**), strong thunderstorm (**c**), and weak thunderstorm (**d**), in Beijing. The color code at the bottom represents the CG flash density (unit: flashes km\({}^{-2}\) a\({}^{-1}\)) [39].  
lightning activity. [PERSON] et al. [11] postulated that air pollutants can delay the initial discharge from thunderstorm clouds, prolonging the duration of lightning and, ultimately, increasing its frequency. Conversely, some scholars have suggested that aerosols can inhibit lightning activity. [PERSON] et al. [79] and [PERSON] et al. [5] propose that air pollutants in the boundary layer can increase the concentration of cloud condensation nuclei and inhibit the average droplet size, thereby influencing the electrification and lightning activity within the cloud (as illustrated in Figure 6). Therefore, while numerous significant advancements have been made in the study of the impact of air pollutants on lightning activity, there is no consensus on the role of aerosols in this regard.
# Can Livestock Farming Benefit from Industry 4.0 Technology? Evidence from Recent Study
## 4 Results
### Dairy Farming  
Milk is among the key food products consumed by humans in many countries around the world. Population growth, together with an increase in income, results in the increased consumption of milk products. Similar to meat, the consumption of milk reflects national wealth. Milk is among the essential products of the agricultural market, and it is the key agricultural product for the European Union [69].  
The EU produced 160.1 million tons of raw milk in 2020 [70]. With 33.2 million tons of raw milk, Germany is the biggest cow milk producer within the EU and net exporter of milk and dairy products. Milk production is the most important branch of Germany's agriculture [71]. The milk production sector is based on approx. 55,800 farms and 3.89 million dairy cows (April 2021). The number of farms with dairy cows has dropped down by 40% since 2010, but the number of cows only dropped by less than 10% at the same time [72].  
In the characterization of the economic situation of dairy farms in European countries, Germany fell into cluster 5 together with France, Italy, and Belgium. The characteristic feature of this cluster was a quite high level of the assets-to-land ratio compared to other groups. This can be explained by the medium area of agricultural land accompanied by the widespread use of production machinery and a high value of fixed assets [69]. However, this classification was based on averages per country, and Germany shows an average herd size of 70 cows, a big variety by region. Average farm sizes range from 43 dairy cows in Bavaria to 246 in Mecklenburg-West Pomerania, including some farms with more than one thousand dairy cows. Farm size is used as an indicator for several characteristics, like labor input, land use, or technology level.  
Owners of small farms in southern Germany often obtain part of their income from non-agricultural activity. Most of the milk production is located in regions with a high grassland percentage. Overall, 31% of German dairy cows have pasture access in the summertime and 88% live in loose housing systems [72].  
Based on the European Council regulation (EC) No. 820/97, Germany has established a system for the identification and registration of bovine animals: Hi-Tier (commonly called HIT) [73]. This system was expanded gradually with additional components such as the application of pharmaceuticals and animal health management and documentation.
## 3 Theoretical Analysis
### Throughput  
For a performance comparison of the block orthogonal codes with other modulation schemes and encodings, we will now analyze the respective throughputs. Reducing PER by channel coding can enhance the throughput of WuR. Lower PER of WuR can receive more successful wake-up packets. This means that WuR has a higher throughput. Therefore, the wake-up time can be shorter. In other words, the WuR can receive more information in a certain time. The PER of WuR is caused by false wake-ups and missed wake-ups.  
To clarify the false wake-ups or missed wake-ups, we define true positive, false positive, true negative and false negative for WuR. Positive means the WuR receives the wake-up signal. Negative means the WuR does not receive the wake-up signal. True positive means that the transmitter sends a wake-up signal and the WuR receives a wake-up signal. False positive means that the transmitter does not send a wake-up signal and the WuR receives any other wake-up signal, also called a false alarm or false wake-ups. True negative means that the transmitter does not send a wake-up signal and the WuR does not receive a wake-up signal. False negative means that the transmitter sends a wake-up signal and the WuR does not receive any wake-up signal, also called a miss detection or missed wake-ups. The false wake-ups and missed wake-ups lead to the PER of WuR. They are discussed in cases 1a and 1b of previous work, respectively [24].  
We assume the system bandwidth as the noise bandwidth \(B_{s}\), that the wake-up packet length is \(L_{surp}\) bits, that the transmitter sends \(L_{packet}\) wake-up packets and that the packet reception rate (PRR) of the WuR is given by:  
\[\text{PRR}_{surr}=1-p_{ep} \tag{12}\]  
where \(\text{PRR}_{surr}\) is the WuR's PRR and \(p_{ep}\) is the WuR's packet error probability with varying modulation types and encodings. The throughput \(S_{surr}\) is given by:  
\[S_{surr}=\frac{\text{PRR}_{surr}B_{s}}{L_{packet}L_{surp}} \tag{13}\]
# Interest Flooding Attacks in Named Data Networking and Mitigations: Recent Advances and Challenges
###### Abstract  
Named Data Networking (NDN) represents a promising Information-Centric Networking architecture that addresses limitations of traditional host-centric Internet protocols by emphasizing content names rather than host addresses for communication. While NDN offers advantages in content distribution, mobility support, and built-in security features, its stateful forwarding plane introduces significant vulnerabilities, particularly Interest Flooding Attacks (IFAs). These IFA attacks exploit the Pending Interest Table (PIT) by injecting malicious interest packets for non-existent or unsatisfiable content, leading to resource exhaustion and denial-of-service attacks against legitimate users. This survey examines research advances in IFA detection and mitigation from 2013 to 2024, analyzing seven relevant published detection and mitigation strategies to provide current insights into this evolving security challenge. We establish a taxonomy of attack variants, including Fake Interest, Unsatisfiable Interest, Interest Loop, and Collusive models, while examining their operational characteristics and network performance impacts. Our analysis categorizes defense mechanisms into five primary approaches: rate-limiting strategies, PIT management techniques, machine learning and artificial intelligence methods, reputation-based systems, and blockchain-enabled solutions. These approaches are evaluated for their effectiveness, computational requirements, and deployment feasibility. The survey extends to domain-specific implementations in resource-constrained environments, examining adaptations for Internet of Things deployments, wireless sensor networks, and high-mobility vehicular scenarios. Five critical research directions are proposed: adaptive defense mechanisms against sophisticated attackers, privacy-preserving detection techniques, real-time optimization for edge computing environments, standardized evaluation frameworks, and hybrid approaches combining multiple mitigation strategies.  
Named Data Networking (NDN); Interest Flooding Attacks (IFA); Information-Centric Networking (ICN); Network Security; Denial of Service (DoS) Attacks; Content-Centric Security
## 4 Discussion
In this case, the purification steps could be skipped to avoid the yield and the algal raw material losses, as well as to minimize the process costing. The high purity of the molecule is essential for structural determination in order to investigate its biological properties and bring to light new elicitors with particular features. Using the aqueous extraction of polysaccharides is a simple and green optimization method. Additionally, it can decrease the yield loss of polysaccharides and ensure that there are no changes to its physical and chemical characteristics. For industry, this extraction process seemed to be adequate, since it fulfills all the criteria needed, such as being time-saving and cost-effective. Several studies have demonstrated the elicitor potential of aqueous extract from marine seaweed. A crude extract prepared from _Ulva armoricaan_, essentially enriched in ulvans, has enhanced resistance against three powdery mildew pathogens on the common bean, grapevine, and cucumber [72]. Extracts of the brown alga _Ascophyllum nodosum_ are the most commonly explored in agricultural commercial production, and are used to improve plant tolerances to abiotic and biotic stresses, to promote plant growth, and to ameliorate the root and microorganism interactions [73].
# A Multi-Objective Evaluation Method for Smart Highway Operation and Management
## 3 Establishment of the Smart Highway Evaluation Framework
### Definition of Evaluation Indicators  
The evaluation of \"Facility structure\" encompasses the assessment of roads, the main structures of bridges and tunnels, and ancillary facilities. It primarily relies on current regulations and findings from industry research, serving to integrate with the established highway evaluation system. Specifically, it pertains to the \"Technical Specifications of Maintenance for Highways\" (JTG H10-2009) [48], \"Standards for Technical Condition Evaluation of Highway Bridges\" (JTG/T H21-2011) [49], and \"Highway Performance Assessment Standards\" (JTG 5210-2018) [50]. The specific indicators of facility structure are listed in Table 1.  
Figure 4: Overall framework of the evaluation system. \begin{table}
\begin{tabular}{l l l} \hline \hline
**Guideline Level B** & \multicolumn{2}{c}{**Indicator Level C**} \\ \hline \multirow{6}{*}{Subgrade (B11)} & Roadbed settlement (B111) & Number and location of roadbed settlements (C1) \\ \cline{2-3}  & Shoulder damage (B112) & Shoulder damage area (C2) \\ \cline{2-3}  & Slope collapse (B113) & Number and location of slope collapse (C3) \\ \cline{2-3}  & Damage to roadbed structures (B114) & Number and location of damaged retaining walls (C4) \\ \cline{2-3}  & \multicolumn{2}{c}{Displacement/settlement values of retaining walls (C5)} \\ \cline{2-3}  & \multicolumn{2}{c}{Curb stone lacking (B115)} & Length of curb stone lacking (C6) \\ \cline{2-3}  & \multicolumn{2}{c}{Washout gully due to water damage (B116)} & Number and location of washout gullies due to water damage (C7) \\ \cline{2-3}  & Poor drainage (B117) & Number of blocked drainage locations (C8) \\ \hline \multirow{6}{*}{Pavement (B12)} & Pavement damage (B121) & Pavement surface condition index (PCI) (C9) \\ \cline{2-3}  & Pavement riding quality (B122) &
\begin{tabular}{l} Pavement Riding Quality Index (RQI) (C10) \\ \cline{2-3}  & Unevenness of riding quality (C11) \\ \cline{2-3}  & \multicolumn{2}{c}{Pavement Rutting Depth Index (RDI) (C12)} \\ \cline{2-3}  & \multicolumn{2}{c}{Unevenness of rut depth (C13)} \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Specific indicators of facility structure.
# A Study of Model Iterations of Fitts' Law and Its Application to Human-Computer Interactions
## 6 Prospects  
Fitts' law has applications in a variety of industries, including sports and medicine, while being traditionally linked to domains such as HCI. During treatments and diagnostic testing, patients in medical practices frequently come across graphical representations. Fitts' law is useful for measuring and evaluating patient performance in comprehending and utilizing these kinds of visual features objectively [106]. The law's usefulness also extends to research involving patients who have neurological abnormalities and arm tremors, as it makes it easier to create linear regression models that assess treatment outcomes. This modeling technique has the potential to help healthcare providers evaluate patient progress and improve treatment plans, and this potential is growing as it continues to develop. The usefulness of this assessment technique may eventually spread to smaller healthcare settings thanks to improved model refinement, enabling physicians in a greater variety of medical scenarios and streamlining the treatment of patient diseases [96; 107].  
Fitts' law has produced insightful results when used in conjunction with training in sports such as handball, fencing, golf, and soccer [38; 108; 109; 110]. A recurring theme appears in all of these different sports: applying Fitts' law to tasks involving left hand and foot movements can improve the creation of more successful execution plans. This shows that Fitts' law may be applied to sports training as a useful tool, providing a mathematical framework to estimate the amount of time required to move from a starting place to a desired position. By intentionally adjusting the target's width and distance characteristics, athletes can improve their speed and accuracy when performing motions that are specific to their sport. Athletes can improve their performance by refining their movements and creating specialized methods to advance their skill level by using this mathematical approach.  
Given Fitts' law's adaptability outside of the conventional interface design domain, there is an increasing expectation that it will be applied in other domains. [PERSON] law has a significant impact on fields other than interaction design, such as athletic training and ergonomics in healthcare. Fitts' law can provide insightful analysis and useful applications that can boost output, optimize training regimens, and enhance user experiences by expanding its application to diverse fields such as healthcare and sports development.  
Conceptualization, methodology, writing--review and editing, H.X.; writing--original draft preparation, Y.S., Z.D. and Y.H.; writing, J.L., M.L. and Y.L.; writing--review and editing, Y.Z. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The authors declare no conflicts of interest.