esa-sceva/satcom-chunk-collection huggingface dataset:
# An Experimental Study on the Reflection Characteristics of Laser Echo Light Waves
## 2 Basic Principles
### Atmospheric Turbulent Channel Model  
The atmospheric refractive index structure constant \(C_{n}^{2}\) is an important parameter reflecting the characteristics of atmospheric optical turbulence and quantitatively describes the intensity of optical turbulence. This paper uses the scintillation method to measure \(C_{n}^{2}\)[15], and its expression is  
\[C_{n}^{2}=4.48 CD_{t}^{7/3}L^{-3}\sigma_{x}^{2} \tag{2}\]  
where \(L\) is the link length, \(D_{r}\) and \(D_{t}\) are the transmitter aperture size and receiver aperture size, respectively, and \(\sigma_{x}^{2}\) is the logarithmic amplitude variance [16]  
\[\sigma_{x}^{2}=0.25 ln[1+\left(\frac{s}{\left\langle I\right\rangle}\right)^{ 2}] \tag{3}\]  
where \(\left\langle I\right\rangle\) is the mean light intensity, and \(s\) is the standard deviation of light intensity.  
The atmospheric refractive index structure constant \(C_{n}^{2}\) is the core parameter for evaluating the characteristics of atmospheric optical turbulence. Based on [PERSON] theory, turbulence is divided into three categories: \(C_{n}^{2}\geq 2.5\ \times 10^{-13}\ \text{m}^{-2/3}\) is strong turbulence; \(6.4\times 10^{-17}\ \text{m}^{-2/3}\leq C_{n}^{2}<2.5\ \times 10^{-13}\ \text{m}^{-2/3}\) is moderate turbulence; \(C_{n}^{2}<6.4\ \times 10^{-17}\ \text{m}^{-2/3}\) is weak turbulence. Its specific value is affected by a combination of factors such as weather conditions, geographical location, and surface characteristics.
# Unmanned Vehicles' Placement Optimisation for Internet of Things and Internet of Unmanned Vehicles
## 5 Towards Algorithm Development: Propagation Concepts, Path Loss and Communication Graph  
When designing a ground wireless network, one of the concerns that arise is the possibility of ensuring the communication link between a transmitter and a receiver at a certain distance and under certain conditions. A more complex scenario resides in the integration of unmanned aerial vehicles into a hybrid wireless network, as an efficient 3D (tri-dimensional) positioning of the UAV must be determined. To correctly plan the positioning of UAVs and USVs, when referring to the quality of the communication, one  
Figure 2: FSANET-WSN network example: \(n_{UV}=7\), \(n_{UAV}=5\), \(n_{USV}=2\), \(M=5\).  
must describe the parameters involved, the propagation environments and propagation channels and models.
## 2 Theoretical Background and Hypotheses Development
### Performance Expectancy (PE)  
Several studies conclude that PE significantly influences the intention to use a certain technology [37; 45; 46]. In particular, performance expectancy is defined as \"the degree to which an individual believes that using the system will help him or her to attain gains in job performance\" [43]. In the context of research, performance expectancy relates to the improvement of job performance. They were proposed as hypotheses:  
**Hypothesis 1 (H1):**: _Performance expectancy has a significant effect on behavioral intention to use IoT._  
**Hypothesis 2 (H2):**: _Gender is a factor that has a significant effect on performance expectancy of IoT._  
**Hypothesis 3 (H3):**: _Age is a factor that has a significant effect on performance expectancy of IoT._  
Figure 1: Research model.
# Hyperspectral Imaging for the Detection of Bitter Almonds in Sweet Almond Batches  
[PERSON]  
1 Department of Animal Production, University of Cordoba, Rabanales Campus, 14071 Cordoba, Spain; p82 [EMAIL_ADDRESS] (J.-A.E.); pa1 [EMAIL_ADDRESS] (A.G.-V.)2 Department of Bromatology and Food Technology, University of Cordoba, Campus of Rabanales, 14071 Cordoba, Spain; [EMAIL_ADDRESS] (M.-T.S.); g32 [EMAIL_ADDRESS] (M.V.-C.)2 Correspondence: g72 [EMAIL_ADDRESS] (I.-T.-R.); [EMAIL_ADDRESS] (D.P.-M.)  
[PERSON]  
2 Department of Bromatology and Food Technology, University of Cordoba, Campus of Rabanales, 14071 Cordoba, Spain; [EMAIL_ADDRESS] (M.-T.S.); g32 [EMAIL_ADDRESS] (M.V.-C.)2 Correspondence: g72 [EMAIL_ADDRESS] (I.-T.-R.); [EMAIL_ADDRESS] (D.P.-M.)  
[PERSON]  
2 Department of Bromatology and Food Technology, University of Cordoba, Campus of Rabanales, 14071 Cordoba, Spain; [EMAIL_ADDRESS] (M.-T.S.); g32 [EMAIL_ADDRESS] (M.V.-C.)2 Correspondence: g72 [EMAIL_ADDRESS] (I.-T.-R.); [EMAIL_ADDRESS] (D.P.-M.)  
A common fraud in the sweet almond industry is the presence of bitter almonds in commercial batches. The presence of bitter almonds not only causes unpleasant flavours but also problems in the commercialisation and toxicity for consumers. Hyperspectral Imaging (HSI) has been proved to be suitable for the rapid and non-destructive quality evaluation in foods as it integrates the spectral and spatial dimensions. Thus, we aimed to study the feasibility of using an HSI system to identify single bitter almond kernels in commercial sweet almond batches. For this purpose, sweet and bitter almond batches, as well as different mixtures, were analysed in bulk using an HSI system which works in the spectral range 946.6-1648.0 nm. Qualitative models were developed using Partial Least Squares-Discriminant Analysis (PLS-DA) to differentiate between sweet and bitter almonds, obtaining a classification success of over the 99%. Furthermore, data reduction, as a function of the most relevant wavelengths (VIP scores), was applied to evaluate its performance. Then, the pixel-by-pixel validation of the mixtures was carried out, identifying correctly between 61-85% of the adulterations, depending on the group of mixtures and the cultivar analysed. The results confirm that HSI, without VIP scores data reduction, can be considered a promising approach for classifying the bitterness of almonds analysed in bulk, enabling identifying individual bitter almonds inside sweet almond batches. However, a more complex mathematical analysis is necessary before its implementation in the processing lines.  
hyperspectral imaging; adulteration detection; shelled almonds; bitter almond identification
# Experimental Study on a Granular Material-Filled Lining in a High Ground-Stress Soft-Rock Tunnel
## 2 Principle of a Lining with Compressible Granular Filling Material  
### Technical Stage of the Lining Support with Compressible Granular Filling Material  
The specific method of granular material-filled lining support technology is to place a buffer layer of filling material (ceramsite, soil, sand) with good mobility and compressibility at the reserved deformation layer between the tunnel's surrounding rock and the secondary lining [31, 37], and to place a pressure relief valve with a threshold in the lining structure. The buffer layer can provide deformation space for the adjacent rock when the surrounding rock is deformed by taking advantage of the mobility, compressibility, and discharge performance of the granular material. It can also absorb part of the surrounding rock stress due to its strength, so that the stress of the secondary tunnel lining support structure is more uniform and better able to protect the overall tunnel support structure. After tunnel excavation, the granular material filling layer is installed directly between the tunnel's surrounding rock and secondary lining. Following this, in the area with significant stress, deep anchors are implanted for local reinforcement and support. This method can negate the need for part of the initial lining anchor bolt support and reduce the free time of the tunnel's excavated surface to effectively restrain the displacement of the free surface and the development of the plastic zone towards the depth of the surrounding rock.  
The granular material-filled lining support process is divided into three stages, as shown in Figure 1.  
Filling lining initial installation stage: The reserved deformation layer of the tunnel is filled with the compressible granular filling material, automatic pressure relief valves are installed on both sides of the arch feet and on the top of the arch, and the pressure relief threshold P3, which can be adjusted, is set. At this stage, the supporting structure's stress distribution is not uniform, and its stress is less than P1, as shown in Figure 1a.  
Homogenization and pressurization stage below the relief-pressure threshold: With the development of the deformation of the surrounding rock, granular materials flow, compress, and break. The force pattern of the lining structure is changed from a point type to a surface type. At this point, the force on the support structure increases to P2, as shown in Figure 1b.  
Automatic pressure-relief stage of the lining: When the pressure in the granular material-filled lining reaches the pressure relief threshold P3 and the filling materials release through the automatic pressure relief valves, the pressure of the supporting structure is maintained at P3 without further increase. The lining structure is evenly forced, as shown in Figure 1c.
Obviously, compared to the conical observations, the hemispherical observations of the up-welling radiation have the advantage of sampling a wider area [10] and hence provide a footprint that is more similar to that of the EC measurements. However, for bi-hemispherical measurements with a cosine-corrected foreoptic, the radiation transfer path turns out to be different from that for conical observations. The radiation transfer path length (RTPL) increases with the view zenith angle in the form of a secant function. For conical observations made with a bare fiber, as the FOV is very small (perhaps 25\({}^{\circ}\)), the equivalent radiation transfer path length (ERTPL) is approximately equal to the height of the sensor above the surface. However, for hemispherical measurements, the FOV is 180\({}^{\circ}\) and so the ERTPL will be much larger than the height of the sensor. For ground-based SIF retrieval, the most commonly used bands are the telluric oxygen absorption bands, which are very sensitive to the atmospheric radiation transfer. The absorption depth of the oxygen absorption bands is mainly related to the RTPL. Accordingto the study by [PERSON] et al. [27], a bias of 10 m in the sensor's height will lead to a bias of about 0.1 mW/m\({}^{2}\)/nm/sr in the retrieved SIF at the O\({}_{2}\)-A band, which is not negligible for SIF retrieval. Therefore, accurate atmospheric correction (in other words, accurate estimation of the ERTPL) is of vital importance for tower-based observations of SIF, even if the height of the sensor above the canopy is only some tens of meters. Consequently, the ERTPL of bi-hemispherical measurements must be analyzed. However, according to our knowledge, no such analysis has been reported until now. Therefore, the modeling of the footprint and ERTPL of bi-hemispherical spectral measurements is important in the context of tower-based measurements of SIF. The aims of this paper are: (1) to analyze the footprints of tower-based hemispherical spectral observations, and also the match between these footprints and those of tower-based flux observations; (2) to determine the ERTPL of hemispherical spectral observations and; (3) to evaluate the derived ERTPL using simulations and to test the validity of the atmospheric correction by using the derived ERTPL for tower-based SIF retrieval.
# Underwater Wireless Sensor Network Performance Analysis Using Diverse Routing Protocols
### Zone Routing Protocol (ZRP)  
The zone routing protocol (ZRP) [10] is a reactive protocol for zone communication and proactive discovery inside a node's immediate neighborhood. These two aspects of the protocol will be described further below. This combination technique combines the greatest characteristics of reactive and proactive methods into a single, easy-to-implement strategy. It is logical to suppose that in a MANET, the majority of interactions occur between nodes that are physically close to one another. The zero trust protocol (ZRP) is not a stand-alone protocol but rather a framework that helps other protocols run smoothly. This decoupling of a node's local surroundings from the network's global design enables the employment of a diverse collection of approaches, each of which has its own set of advantages when used appropriately. This is possible because a node's neighborhood is independent of the network's global topology. These smaller, more manageable communities are referred to as \"zones,\" and each node may reside within numerous overlapping zones of varying sizes. Instead of utilizing geographical coordinates, a radius of length is utilized to calculate a zone's \"size,\" signifying the number of hops from the zone's perimeter. This distance is used to compute the so-called \"size\" of a zone. The zone routing protocol divides the system into overlapping, varying-sized zones. A ZRP is not a single component but rather a set of parts that, when combined, provide a sophisticated routing system. This will only be feasible if every component is used. Each component runs autonomously and may apply a wide range of technologies to achieve optimal performance in the specialized areas in which it specializes. The ZRP can be disassembled into its constituent parts, which are the IARP, IERP, and BRP.
## 1 Introduction
Recently, we developed a theoretical model for treating the propagation of light beams under this situation, based on the eHF method [33]. The average intensity and coherence properties of the Gaussian-Schell-model beam under such anisotropic turbulence circumstances are investigated in detail and some results are demonstrated in the experiment [34]. Partially coherent beams with spatially varying coherence, named nonuniformly correlated (NUC) beams, were first introduced by [PERSON] and [PERSON] [35]. Different from Schell-model sources, whose coherence distributions are uniform over the whole field, The NUC beams have a locally varying degree of coherence. Owing to its unique coherence properties, the NUC beams exhibit two peculiar propagation features, i.e., \"self-focusing\" and the shift of intensity maxima, during free-space propagation. The evolution of the average intensity and the scintillation index of the NUC beams, propagating through isotropic turbulence, were investigated in [36; 37]. These results show that the NUC beams not only possess a lower on-axis scintillation index but also a higher on-axis intensity compared to Gaussian-Schell model beams. This property may be useful in free-space communication. The study of the NUC beams was also extended to the vectorial case and to the behaviors of the polarization and the intensity in case of isotropic atmospheric/oceanic turbulence [38; 39; 40; 41]. [PERSON] and co-works successfully generated scalar or vector NUC beams involving in the experiment one or two spatial light modulators (SLM) [42]. We found that the theoretical model for the NUC beams introduced by [PERSON] et al. is different from the one used in [36; 37; 38; 39; 40; 41; 42]. The NUC beams in [35] are assumed to have a rectangular symmetry whereas in [36; 37; 38; 39; 40; 41; 42], the NUC beams are assumed to have a circular symmetry. Recently, [PERSON] et al. reported the generation of partially coherent beams from a high-power tapered superluminescent diode with amplified spontaneous emission [43]. This method may open a new way to generate the NUC beams. To our knowledge,no results for the propagation characteristics of the NUC beams including rectangular or circular symmetric in anisotropic turbulence have been reported yet. In this paper, our aim is to study the propagation features of NUC beams with rectangular symmetry through anisotropic turbulence along the horizontal path near the ground. The effects of the anisotropy factor on the evolution of the average intensity and the shift of the intensity maxima are studied in detail. In addition, the power-in-bucket of the NUC beam at the receiver plane is also presented.
# Long-Term and Seasonal Changes in Sources of Urban Atmospheric Particulates in the Western Pacific
## 3 Results and Discussion
### Individual City Trends
The [P\({}_{\rm H}\)]/[P\({}_{\rm c}\)] ratio (0.52) was close to the values of the Japanese cities with the exception of Kitakyushu (Table 3), suggesting that the main contributor to P\({}_{\rm c}\) was vehicles. Based on their profiles of [P\({}_{\rm c}\)], [P\({}_{\rm H}\)] and [P\({}_{\rm I}\)], the 10 cities were separated into three classes. Class 1: commercial cities whose major contributor to P\({}_{\rm c}\) was vehicles and which showed lower [P\({}_{\rm c}\)] levels with larger [P\({}_{\rm H}\)]/[P\({}_{\rm c}\)] ratios. Sapporo, Kanazawa, Tokyo, Sagamihara (Japan), Shanghai (China), and Busan (Korea) were contained in this class. Class 2: cities whose main source of P\({}_{\rm c}\) was coal heating which emits large amounts of P\({}_{\rm I}\). This results in the much higher winter [P\({}_{\rm c}\)] with larger [P\({}_{\rm I}\)]/[P\({}_{\rm c}\)] ratios. Beijing, Shenyang (China), and Vladivostok (Russia) were contained in this class. Class 3: steel manufacturing city which showed lower [P\({}_{\rm c}\)] with larger [P\({}_{\rm I}\)]/[P\({}_{\rm c}\)] ratio. The low [P\({}_{\rm c}\)] appeared to be due to elimination of P\({}_{\rm I}\) from coke oven plants. Only Kitakyushu was contained in this class. Thus, different long-term and seasonal changes in contributions of vehicles and coal combustion to urban atmospheric suspended particulate matter (TSP) in each city, that were unknown in our previous studies [10; 11; 12], have been elucidated.
## 4 Discussion
### The Impact of Soil and Air Temperature  
Temperature is usually mentioned as one of the main factors that have an impact on GHG fluxes. The seasonality of CO2 fluxes from both silver birch and black alder stems discussed in the previous section could be explained by the annual changes in soil and air temperature and the subsequent decrease/increase in tree physiological activity, as positive correlations between CO2 fluxes and soil and air temperature have been found [33; 56; 57]. Respiration and diffusion rates, sap flow and other physiological processes in trees are assumed to increase exponentially with an increase in air temperature [58; 59; 22]. In a study carried out in Finland, positive correlations were found between net GHG fluxes of stems and indicators of physiological activity--gross primary productivity (GPP), photosynthetically active radiation (PAR) and evapotranspiration [33].  
The results of several previous studies on GHG fluxes from stems of deciduous trees have shown a significant and positive correlation between temperature and the amount of CO2 released into the atmosphere [18; 59; 60]. As air temperature increases, the amount of CO2 released in summer is significantly higher than in winter, spring or autumn [59]. In a study conducted in a riparian grey alder forest in Estonia, a moderate negative correlation was found between soil temperature and the CH4 flux from the surface of tree stems; however, no significant correlations were found at the ecosystem level [16]. Results regarding N2O emissions vary. In some studies, seasonal changes can be observed, driven by light intensity and temperature [25; 33; 61]. However, there are also studies in which such seasonal patterns of N2O fluxes were negligible [12].
# A Security and Privacy Scoring System for Contact Tracing Apps
## 1 Introduction
### Dangers of Privacy Loss  
Names, phone numbers, and other pieces of information are direct identifiers that reveal a user's identity. However, they are not the only information that can do so. Indirect identifiers are information which, when combined, identify a user. The combination of zip code, date of birth, and gender is unique for 87% of the U.S. populace [8], while GPS data can reveal personal information, such as habits [9] and home addresses [10], from studyingmovement patterns. Specific to contact tracing, data about which users are regularly meeting could be used to create a social web of users.  
One way to assess privacy loss from revealed information is to assess the size of the anonymity set, or the entropy [11, 12]. A simplified conceptualization starts with everyone having a set amount of anonymity and information learned about an individual, which lowers their anonymity based on how many people also have this attribute. Using the probability that the information is true about a random individual, one can calculate how much anonymity has been lost. Though this style of measurement can be useful, it also has shortcomings. Not all information has known and exact probabilities of uniqueness. For example, if an app does not delete metadata, then it is difficult to assess how much privacy has been lost because the exact data and their uniqueness are unknown.
# Biological and Technical Challenges Related to Cultured Meat Production
## 3 Challenges Related to Cultured Meat Production
### Biotechnological Challenges  
#### 3.1.1 Choice of Animal for Cell Harvesting  
The first challenge facing in cultured meat production is the choice of animal from which to perform the cell biopsy. The choice should not be random, but must take into account multiple variables, including age, sex, and rearing conditions, as they affect the presence or absence of satellite cells (adult skeletal muscle stem cells).  
As the animal ages, the concentration of satellite cells within the muscle decreases. The fastest decrease in the number of satellite cells occurs most during the first few months post  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Biotechnological Challenges** & **Technical Challenges** \\ \hline Choice of animal for cell harvesting & \\ Choice of site of collection & \\ Methods for cell harvesting & Scaffold fabrication \\ FBS: ethical challenges & Alternatives to scaffold fabrication \\ High cell proliferation and genetic instability & Biofabrication and 3D bioprinting \\ Nutritional and functional properties of cultured meat & Bioreactors \\ FBS alternatives & Industrial process scale-up \\ Food control system for cultured meat & \\ \hline \hline \end{tabular}
\end{table}
Table 1: The main biotechnological and technical challenges for cultured meat production.  
birth. In addition, because satellite cells in younger animals have undergone fewer mitotic cell divisions, they might retain their differentiation capacity for a longer proliferative period [14; 31].  
The sex of the animals is another factor involved in the proliferation of muscle stem cells.  
Sex hormones such as estrogen and testosterone are able to influence cell growth. Compared with female animals, male animals are characterized by a higher content and activity of satellite cells, thanks to the positive influence of testosterone [16]. This beneficial action is also underlined by [PERSON] et al., who demonstrated that casted animals presented a lower concentration of activity of satellite cells than non-castrated ones, a trend reversed with the administration of testosterone propionate [32].  
Animal rearing conditions also play an important role in the composition of muscle fibers. [PERSON] et al. showed that extensively reared animals had a higher number of type I muscle fibers but also a reduction in type II muscle fibers compared to intensively reared animals. This difference, according to the authors, is due to the different diets to which the animals are subjected; more precisely, to the amount of roughage consumed, which is higher in animals reared under extensive conditions [33].