esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Short-Term Effects of Biochar and Biofertilizer on Soil Characteristics
N\({}_{\text{inorg}}\) presented significant variations between cycles and treatments (Figure 3b), which is explained by the multiple transformations that N undergoes in soil. However, with the initial addition of biochar and all treatments, N\({}_{\text{inorg}}\) increased significantly relative to the initial content, although in CT and BBft, it continued to be at a very low level (<10 mg\(\cdot\)kg\({}^{-1}\)) while in BT20 and BT50 it reached medium values (10-20 mg\(\cdot\)kg\({}^{-1}\)). The N\({}_{\text{inorg}}\) increases observed in CT, BT20, and BT50 can be due to higher adsorption of inorganic forms of N (NH\({}_{4}\)\({}^{+}\) and NO\({}_{2}\)\({}^{-}\)), as opposed to BBft, where the increase in pH could favor ammonia emission. Figure 4 shows two important situations; on the one hand, comparing the treatments that received 100% phosphorus fertilization, we observed that the soil with biochar and biofertilizer (BBft) retained between 40-87% more P\({}_{\text{av}}\) than the chemically fertilized soil without biochar (CT). On the other, we found that by adding biochar, it is possible to reduce phosphorus fertilizer by 50-80% if we consider BT20 and BT50, with 80% and 50% less phosphorus fertilization, respectively; they retained 22-76% and 35-87%, respectively, more P\({}_{\text{av}}\) than CT. Although CT was the only treatment in which P\({}_{\text{av}}\) significantly (_p_ < 0.05) increased in the second cycle relative to the first one; its concentration was much lower than that of the biochar treatments. [PERSON] et al. [22] found that fine particles (\(\leq\)0.5 mm) of biochar significantly increased P\({}_{\text{av}}\) in soils, but when 1% of mixed size particles of biochar were added to the same soils, only in one of them, P\({}_{\text{av}}\) increased. In our study, a mixture of particles containing 33.5% of fines (<0.6 mm) from biochar significantly increased P\({}_{\text{av}}\) in soil. P retention in the soil is of utmost importance since approximately 85% of P added by chemical fertilization is lost, and reserves of this element are limited [14]. Additionally, biochar could be a P source because if pyrolysis temperature is not higher than 700\({}^{\circ}\)C, P from feedstock is retained in biochar [44]. Therefore, the recycling of nutrients through biochar and biofertilizers are helpful strategies to support agricultural sustainability and the circular economy.
# Ablation of Copper Metal Films by Femtosecond Laser Multipulse Irradiation
## 2 Theoretical Background  
### Two Temperature Model  
We have chosen a metal target (copper foil) of thickness \(d=3\)\(\upmu\)m and at initial temperature \(T_{0}=300\) K irradiated by ultrashort laser pulses of fluence \(F\) on the front surface (\(z=0\)).  
The laser pulse is Gaussian in time with a Full Width at Half Maximum (FWHM) \(t_{p}\) of 120 fs with a central wavelength of 800 nm. The evolution of electron-lattice temperature can be described by the TTM [11; 21]:  
\[C_{e}(T_{e})\frac{\partial T_{e}}{\partial t}=\frac{\partial}{\partial z}(k_{e} \frac{\partial T_{e}}{\partial z})-G(T_{e}-T_{l})+S(z,t) \tag{1}\]  
\[C_{l}\frac{\partial T_{l}}{\partial t}=G(T_{e}-T_{l}) \tag{2}\]  
\(C\) is the heat capacity; \(k\) is thermal conductivity, where \(e\) and \(l\) denote electron and lattice, respectively. \(G\) is the electron-phonon coupling factor. \(z\) is the direction perpendicular to the target surface (the model is considered in one dimension implying that the temperature is calculated just in the center of the focal volume), and \(t\) is the time.  
The heat density \(S\) can be expressed for a single pulse as [21]:  
\[S(z,t)=0.94\frac{1-R}{t_{p}(\delta+\delta_{b})(1-e^{-d/(\delta+\delta_{b})})} F.\exp[\frac{-z}{(\delta+\delta_{b})}-2.77(\frac{t}{t_{p}})^{2}] \tag{3}\]  
We generalize this expression for the case of a multipulse per burst as follows:  
\[S(z,t)=\sum_{i=1}^{N}0.94\frac{1-R}{t_{p}(\delta+\delta_{b})(1-e^{-d/(\delta+ \delta_{b})})}F.\exp[\frac{-z}{(\delta+\delta_{b})}-2.77(\frac{t-(i-1)t_{sep} }{t_{p}})^{2}] \tag{4}\]  
where \(N\) is the number of pulses per burst, \(t_{sep}\) is the separation time between pulses, \(\delta=1/\alpha\) is the absorption depth, \(\alpha\) is the absorption coefficient and \(R\) the reflectivity. \(\delta_{b}\) is the ballistic range, where \(\delta_{b}\) can be calculated as \(\delta_{b}=v_{e}t_{b}\), \(v_{e}\) being the electron velocity calculated by: \(v_{e}=\sqrt{\frac{2k_{B}T_{e}}{m^{2}}}\), where \(k_{B}\) is the Boltzmann constant, and \(m^{*}_{e}=1.41m_{e}\) is the effective mass of an electron [22], with \(m_{e}=9.1\times 10^{-31}\) kg. \(t_{b}=24.7\) fs is the Drude relaxation time given by the relationship \(t_{b}=\frac{m_{e}\sigma}{n_{e}e^{2}}\), where \(\sigma=5.88\times 10^{7}\)ohm\({}^{-1}\) is the electrical conductivity and \(n_{e}=8.45\times 10^{28}\) m\({}^{-3}\) is electrons' density [23]. The ballistic range value has an important impact in the simulations since it provides the ballistic transport of energy by the hot electrons. More details of its role can be found in [21]. Note that electrical conductivity also depends on the temperature, but we take it as constant to simplify the simulation and reduce the computation time.
## 3 Problem Explanation  
The underwater topology is randomly deployed where the source and sonobuoys are far apart from each other. Therefore, the energy consumption of nodes is deprecated. Forwarding nodes try to transmit the data, but early deprecation of nodes (that bear the total traffic of the source and intermediate nodes) creates empty regions. Furthermore, when the node starts data forwarding and does not know the exact location where empty regions exist [38]. Mostly, the data are not forwarded due to the presence of empty regions inside the route information. The proper angle towards the node does not consider while forwarding; as a result, the delay and low PDR come into exists. The empty gaps near the sink's neighboring nodes are needed to fix, as these sink neighboring nodes are responsible for covering these void holes successfully at both ends. However, the empty regions can also be covered by the adjustment of nodes depth level. The adjustment of the node's depth is based on angle and movement as described in Figure 1. The movement and alignment of nodes are discussed in the literature and in the baseline approach that is taken for comparison, i.e., angle-based approach where each node is aligned up to some angle and with layer-based hierarchy. Moreover, the overhead cache is increased when, for each iteration, the angle needs to be computed. Another problem is that by checking the continuous energy status of nodes, like sink neighboring nodes, is not possible as per some opportunistic routing protocols do this easily [39]. Additionally, most of the previous approach where these issues try to enhance the energy of sink neighboring nodes, is all in vain. The reason is that the energy of the overall network is decreased when a large amount of this material is considered to be dedicated to particular sink neighboring nodes in the underwater acoustic environment. Therefore, the energy sources our primary check for the proposed technique. This approach is also successful in sparse and dense water areas.  
For the problems mentioned above, therefore, we need an energy-efficient technique for like TANVEER with its three subsections like LBA-TANVEER, DPD-TANVEER, and BIN-TANVEER. The LBA is used to control the empty region's occurrence by using the location of the node and its energy status, while for reliable data delivery the DPD-TANVEER works out. To rescue the data of empty regions before and after the node's deprecation, the BIN-TANVEER is used. Furthermore, the detail of the proposed system model is presented in the next section.
# POL-MUX System for Noncoherent Optical Networks
## 3 POL-MUX on a Real Optical Network
This practical measurement confirmed that polarization changes in the real optical network are slow and thus dynamic polarization controllers could keep the polarization angle of the transmitted signal. It is necessary to note that for both workplaces, the temperature was kept at a constant temperature by air conditioning, so the change in polarization was caused only by ambient conditions around the optical link between both workplaces. The measurement result is very important because although the system did not possess a dynamic polarization controller, there were no dynamic (fast) polarization changes. This means that if we employed a dynamic polarization controller, it should react to gradual temperature changes.
# Microalgal Proteins and Bioactives for Food, Feed, and Other Applications
## 1 Introduction
### Microalgae for Food and Functional Food Applications
#### 1.1.3 Carbohydrates  
Carbohydrates make up approximately 20% of microalgae biomass and usually accumulate in the form of starch or other polysaccharides, including \(\beta\)-glucans, sulfated polysaccharides and exopolysaccharides [8]. Nowadays, fermentable polysaccharides including starch, which is the main storage polysaccharide in microalgae, or cellulose, which is the main polysaccharide constituent in the microalgae cell wall, are widely explored for use in bioethanol and biofuels production [8]. Microalgae species known for their high carbohydrate contents and evaluated as feasible for biofuel production include the species _Porphyridium cruentum_, which has a carbohydrate content of between 40-57%, and _Spirogyna_ sp., which has a carbohydrate content of 33-64% [76]. _Chlorella_ sp. have carbohydrate contents of 50% of the dry mass of the alga [77]. Moreover, some polysaccharides and oligosaccharides from _Arthrospira_ sp., _Nostoc_ sp. and _Chlorella_ sp. were looked at previously for their prebiotic effects [8]. The types of polysaccharide found within the biomass of selected microalgae and their potential applications are summarized in Table 5.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Species** & **Omega-3 [\% of FA]** & **Omega-3 [\% of DW]** & **References** \\ \hline _Isochrysis galbana_ & EPA 25 & EPA 5.3 & [67] \\ _Nammochloropsis culdata_ & EPA 20 & EPA 8.3 & [68] \\ _Pavlova lutheri_ & EPA 12 & EPA 2.3 & [69] \\ _Phaeodactylum tricornutum_ & EPA 20 & EPA 7.7 & [70] \\ _Cryptheocardiium cohiii_ & DHA 44 & DHA 5.8 & [71] \\ _Schizochytrium_ sp. & DHA 43 & DHA 11 & [72] \\ \hline
**Species** & **Omega-6 [\% of FA]** & **Omega-6 [\% of DW]** & **References** \\ \hline _Arthrospira platensis_ & GLA 20–23 & - & [73] \\ _Porphyridium purpureum_ & ARA 24 & AEA 0.8 & [74] \\ \hline \hline \end{tabular} Arachidic acid (ARA); gamma-linolenic acid (GLA); anandamide (AEA).  
\end{table}
Table 4: Content of PUFAs found in common microalgaespecies.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Species** & **Carbohydrate** & **Application** & **References** \\ \hline _Arthrospira platensis_ & Sulfated polysaccharides— & Antibacterial and & [78] \\ \multicolumn{4}{c}{exopolysaccharides/glycogen} & antioxidant activity & \\ \hline _Arthrospira platensis_ & & & \\ _Dualiella salina_ & Polysaccharides & Plant bio-stimulants & [79] \\ _Porphyridium_ sp. & & & \\ \hline _Arthrospira platensis_ & Extracellular polysaccharides— & Prebiotic/stimulate & \\ \multicolumn{4}{c}{exopolysaccharides/glycogen} & growth of _Lactobacilli_ & [80] \\ \hline \hline \end{tabular}
\end{table}
Table 5: Reported prebiotic potential of microalgae derived polysaccharides and oligosaccharides.
## 5 Authenticity, Processing and Adulteration for Apitherapy Use
These antibiotics and drugs are used to treat the honeybee colony for various diseases or pest control [244]. Recently, [PERSON] et al. (2020) [245] have investigated the antifungal residues present in Romanian honey samples by using high-resolution mass spectrometry, where the most present was enilconazole, followed by metalaxyl, penconazole and propiconazole among others. Another major source of contamination in honey are pesticides that are governed by regulation (EC) No. 396/2005 [246] in which values have been established for maximum residue levels (between 10 to 50 mg/kg in honey). The use of these products on the environment can affect both the bees and their products, and consequently can become a threat for consumer's health [244]. For instance, [PERSON] et al. (2019) [247] found the presence of amitraz, coumaphos, thymol and thiazolprid in conventional and organic honey samples from Slovenia, while for the studies carried on in Israel [248], the same residues were found in higher concentration. In the same study [248], an analysis was conducted on the trace element residues, underlining the presence of Cr, which had the highest mean concentration (65.1 ug/kg), followed by Zn (54.1 ug/kg) and Mn (43.4 ug/kg). For both studies, the quantified levels of residues were in accordance with the European regulation. As for adulteration in honey, it should be noted that the common methods used for this purpose include artificial and over feeding of bees with sucrose, artificial addition of high fructose corn syrup (HFCS) and rice syrup, and mislabelling of botanical, entomological, and geographical origin [27; 220]. In light of the current research, [PERSON] et al. (2021) [249] detected the adulteration of Acacia honey with high fructose corn syrup (HFCS) by determining the \(\alpha\)-Dicarbonyl compound (3,4-DDPS). Using ion-mobility mass spectrometry coupled with UHPLC-MS/MS, the authors indicated that the 3, 4-DDPS can be used to identify the adulteration of Acacia honey with a concentration of 20% HFCS. The results were in accordance with the studies performed by [PERSON] et al. (2019) [123]. The use of these methods has the advantage to increase the apparent value of honey and decrease its production cost [120], providing the producers with economic gains [250]. However, the disadvantages cannot be ignored, namely the negative impact on the bioactive and curative properties of honey along with the toxic effects that can be observed in human health [248]. Hence, determining the quality parameters of honey and therefore its expected therapeutic properties requires performing qualified laboratory analyses that can suggest whether a honey variety can meet the required quality conditions for human consumption and apitherapy use. In addition, correct labelling can be viewed as a quality guarantee for consumers and as a sign of origin, authenticity and prestige for producers [250].
# A Long-Distance WiFi Network as a Tool to Promote Social Inclusion in Southern Vercarruz, Mexico
## 3 Methodology
### Diagnosis of the Municipality of Mecayapan
#### 3.1.1 Location and Geographical Characteristics  
Mecayapan is a town with a high percentage of the Nahua indigenous population, whose language is Nahuatl, nestled on the slopes of Cerro Santa Marta within the physical and geographical environment in the southeast of the state of Veracruz. It is located between the coordinates of the Sierra Santa Marta and San Martin and those of Los Tuxtlas at 18\({}^{\circ}\)12\({}^{\prime}\)49\({}^{\prime\prime}\) N and 04\({}^{\circ}\)17\({}^{\prime}\)40\({}^{\prime\prime}\) E in Mexico, located 340 m above sea level. This municipality has an area of 315.4 km\({}^{2}\), which represents 0.43% of the state's total, and 70% is used in agriculture and livestock, 20% in homes, 3% for commerce, and 7% for offices and public spaces. To the north, it borders the Gulf of Mexico, to the south it borders Chinameca and Soteapan, to the east it borders Pajapan and the Gulf of Mexico, and to the west it borders Catemaco, Soteapan, and Tatahuicapan. It has 15 communities: Huazuntalan, Cerro de la Palma, Ikhuapan, Agrarian Plan, Los Arrecifes, La Perla del Golfo, Vicente Guerrero, El Salado, El Paraiso, La Nueva Esperanza, San Andres Chamilpa, Encino Amarillo, El Rubi, El Naranjo, and Arroyo Texizapan. The closest cities to the municipal seat are Acayucan, Jaltipan, Chinameca, Oteapan, Cosoleacaque, Minattilan, and the City of Puerto de Coatzacoalco. A map is shown in Figure 2.  
Figure 2: Geographical location of Mecayapan [48].  
The weather in Mecayapan is warm sub-humid regular, the most humid of the climatic subtypes. The average annual temperature is 23 \({}^{\circ}\)C and ranges between 18 and 26 \({}^{\circ}\)C. There is abundant rain in summer and early autumn, with less intensity in winter. The range of rainfall is 1900-4100 mm. The soil is the luvisol type, which is characterized by accumulating clay in the subsoil with a dark hue, and it is not very susceptible to erosion.  
The analysis of geographical and weather characteristics allows identifying important limitations concerning the access of telecommunications in the area, given the geographical location of the municipality of Mecayapan, in addition to the fact that telecommunications and ISP companies do not bet on investing in them, especially due to almost zero internet penetration. On the other hand, the satellite connection program that the Mexican government has is of a deficient character.
# 6G Use Cases and Scenarios: A Comparison Analysis Between ITU and Other Initiatives
## 10 Vertical Market Sectors
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Vertical Market Sectors (from APTIC** & **Vertical Market Sectors (Our Work)** & **Note** \\ \hline Aerospace and Defense & Factories of the Future (FFE) & \\ Agriculture and Forestry & Agriculture (AGR) & \\ Chemicals & Agriculture (AGR) & - \\ Computers and Technology & - & These are enabling technologies \\ Construction and Real Estate & Smart City (SC) & - \\ Education and Training & Education (EDU) & - \\ Energy and Utilities & Energy (EN) & - \\ Entertainment and Media & Entertainment (ENT) & - \\ Financial Services & e-Commerce (EC) & - \\ Food and Beverage & Factories of the future (FFE) & - \\ Healthcare and Pharmaceuticals & eHealth (personal monitor) (EH1); & - \\ Hospitality and Tourism & Smart City (SC) & - \\ Information Services & - & These are enabling technologies \\ Manufacturing & Factories of the Future (FFE) & - \\ Mass Media & Entertainment (ENT) & - \\ Professional Services & e-Commerce (EC) & - \\ Retail and Consumer Services & e-Commerce (EC) & - \\ Technology & - & These are enabling technologies \\ Telecommunications & - & These are enabling technologies \\ Transportation and Logistics & Transportation (TRA); Logistics (LOG) & - \\ Waste Management and Environmental & Environment (ENV) & - \\ Services & Smart City (SC) & - \\ - & Automotive & We separated it from the manufacturing \\ - & eGov (EGO) & Not included in the APTIC Consulting \\ - & Cultural Heritage (CH) & Not included in the APTIC Consulting \\ - & Emergency & Not included in the APTIC Consulting \\ \hline \hline \end{tabular}
\end{table} 
Table 9: The mapping of vertical market sectors provided by APTIC Consulting and by the present paper. within the environment (ENV) sector. Finally, professional services can be cast within e-commerce (EC), since (i) this sector is not directly addressed by the main stakeholder and (ii) the involvement of people is requested through digital interaction. Instead, we consider computers and technology, information services, technology, and telecommunications as enabling technologies supporting one or more vertical market sectors. In Table 8, we have introduced new vertical market sectors not included in the APTIC's list, such as e-gov (EGO), cultural heritage (CH), and emergency (EME). These have an important role within the actual 5G/BY5G and future 6G systems.
# Comparative Study on Physicochemical and Nutritional Qualities of Kiwifruit Varieties
## 3 Results  
### Pectin and Moisture  
In the case depicted in Figure 1A, the pectin contents of kiwifruits ranged from 0.20 to 0.50 g/100 g, with an average of 0.34 g/100 g. Among the kiwifruits with different fruit flesh colors, the green-fleshed kiwifruits showed the highest content of pectin compared with the red-fleshed and yellow-fleshed kiwifruits, and this case is depicted in Figure S1A. On the other hand, 'Donghong' showed the lowest content of pectin, followed by 'Cuiyu' and was 'Hort16A'--these three varieties belonged to _A. chinensis_. Except for _A. chinensis_ var. _delicious_ vs. _A. eriantha_, the content of pectin in each different species was significantly different. It was reported that the pectin content of green-fleshed 'Qinmei' kiwifruit, which was from _A. chinensis_ var. _delicious_, ranged from 0.09 g/100 g to 0.37 g/100 g [19]. In this study, the pectin contents of five green-fleshed kiwifruit samples from _A. chinensis_ var. _delicious_ and _A. eriantha_ were higher than those in a previous study. The green-fleshed kiwifruits with a high pectin content in _A. chinensis_ var. _delicious_ and _A. eriantha_ are a natural source of pectin, which could be used in the preparation of jellies and jams.  
The content of moisture plays critical roles in the shelf life and processing characteristics of the fruit. The results demonstrate that there were significant differences in the moisture content of the various samples, which spanned from 81.49% to 85.96%, and 'Jinmei' showed the highest content of moisture. Based on the flesh color, no significant difference was identified in the moisture contents of the three flesh color groups. Coincidentally, the content of moisture in different species showed no significance, and this case is depicted in Figure S1. It was reported that the moisture content of _A. chinensis_ and _A. chinensis_ var. _delicious_ was 83.22% and 83.07%, respectively [20], which was similar to the results of this study. In addition, studies showed that the moisture content in dragon fruit [21], apple [22] and citrus [23] were 82.40-84.80%, 81.66-3.40% and 75.40-80.32%, respectively. Therefore,it can be deduced that the kiwifruits had a high moisture content and are a good supplier of moisture for humans.
# Chinese Lip-Reading Research Based on ShuffleNet and CBAM
## 2 Lip-Reading Model Architecture
### ShuffleNet
#### 2.1.1 Group Convolution  
Group convolution was firstly used in AlexNet for distributing the network over two GPUs, which proved its effectiveness in ResNeXt [23]. Conventional convolution adopts channel-dense connection, which performs a convolution operation on each channel of input features.  
For conventional convolution, the width and height of the kernel are K and the C represents the number of input channels; if the number of the kernel is N, the number of the output channel is also N. The number of parameters is calculated as follows:  
\[\text{P(CC)}=\text{K}\times\text{K}\times\text{C}\times\text{N}\text{ (parameters)}\]  
(CC: Conventional Convolution)  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Model**} & \multicolumn{4}{c}{**mmAP (\%)**} & \multicolumn{4}{c}{**GPU Speed**} \\  & & & & & **(Images/s)** & \\ \hline FLOPs & 40M & 140M & 300M & 500M & 40M & 140M & 300M & 500M \\ Xception & 21.9 & 29.0 & 31.3 & 32.9 & 178 & 131 & 101 & 83 \\ ShuffleNet v1 & 20.9 & 27.0 & 29.9 & 32.9 & 152 & 85 & 76 & 60 \\ MobileNet v2 & 20.7 & 24.4 & 30.0 & 30.6 & 146 & 111 & 94 & 72 \\ ShuffleNet v2 & 23.7 & 29.6 & 32.2 & 34.2 & 183 & 138 & 105 & 83 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Measurement of accuracy and GPU speed of four different lightweight models with the same level of FLOPs on COCO object detection. (FLOPs: float-point operations).  
For group convolution, the channels of the input features are divided into G groups, such that the number of the kernel is C/G; the results from G groups are concatenated into larger feature outputs of the N channel. The number of parameters is calculated as follows:  
\[\text{P(GC)}=\text{K}\times\text{K}\times\text{C/G}\times\text{N}\text{ (parameters)}\]  
(GC: Group Convolution)  
From the above formulas, we can tell that the number of parameters in group convolution is much smaller than that of conventional convolution.  
The conventional convolution and group convolution are illustrated in Figure 2.