esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Conclusions  
The article describes the research results regarding the formation of a sliding layer during tribological contact between expanded graphite and stainless steel. The tests were carried out under static contact for 30 s and dynamic contact for 15 and 30 min under dry conditions and during the cooperation of the samples with moist rings. The loads of 10, 20, and 30 N and speeds of 25 and 50 mm/s were used. Changes in surface geometry caused by material transfer were determined based on measurements of the Ra surface roughness parameters of stainless steel samples after a friction cycle. It was established that:  
1. The presence of moisture in the stainless steel-expanded graphite friction node affects the formation of a sliding layer. The resulting layer reduces the surface roughness of the cooperating materials and prevents their accelerated wear. A reduction of the Ra surface roughness parameter of the stainless steel sample was observed for approx. 80% of cases when working with a graphite counter-sample soaked in water, and for approx. 35% of cases when dry working.
2. The transfer of graphite material to the surface of the stainless steel sample was observed during static contact of these materials. However, no significant reduction of the Ra surface roughness parameter of the stainless steel sample was observed.
3. After 5 min of work with the water-soaked graphite counter-sample, depending on the friction conditions, a reduction of the Ra surface roughness parameter of the stainless steel sample was achieved in the range of 11-18% compared to the initial value. In turn, for dry worked samples, the Ra parameter decreased slightly--by approximately 4%.  
After 30 min of operation, stainless steel samples working with wet expanded graphite were characterized only by a reduction of the Ra surface roughness parameter in the range of 3-25% compared to the initial value. However, the Ra parameter decreased in the range of 5-13% in the case of dry worked samples.
* Pilot studies have shown that operating conditions, i.e., time, load, speed, and humidity, influence the formation of a sliding layer in the tribological contact between stainless steel and expanded graphite. This confirms the validity of conducting further research in this area.  
Conceptualization, A.R.; Methodology, A.R. and G.K.; Software, A.R.; Validation, A.R., K.P. and G.K.; Formal analysis, A.R., K.L. and G.K.; Investigation, A.R., K.P. and G.K.; Resources, A.R.; Data curation, A.R. and K.L.; Writing--original draft, A.R. and K.P.; Writing--review & editing, A.R. and K.L.; Visualization, A.R. and K.P.; Supervision, A.R. and K.L.; Project administration, A.R. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.  
The authors declare no conflict of interest.
# Applications of Water Jet Cutting Technology in Agricultural Engineering: A Review
## 3 Applications of Water Jet Cutting Technology on Different Agricultural Materials
### Meats
#### 3.3.3 Reducing Meat Loss  
Meat loss (or kerf width) is the central problem encountered in water jet cutting, closely related to economic benefits [60]. [PERSON] et al. [55] found that large nozzles caused excessive meat loss, especially at higher water pressures and slower traverse speeds. [PERSON] [65] conducted pure water jet cutting experiments on cod and salmon fillets. The results showed that super-chilling applied before cutting had a better cutting effect. Due to the kerf width increasing with transverse speed and nozzle diameter, the transverse speed range should be set for disparate parts of the fish fillet (i.e., tail, waist, and abdomen), and a smaller nozzle aperture could obtain a better cutting performance. [PERSON] [60] et al. found that a salt abrasive water jet could make the surface of meats with bone smooth and the kerf width measured by a variable thickness feeler gauge was less than 1 mm, making less meat loss (Figure 4, 400 MPa jet pressure, 5 mm/s traverse speed, 16.2 kg/h salt mass flow rate for salt water jet). Moreover, as the cutting depth deepens, the kerf width gradually decreases.  
Figure 4: Contrast tests of cutting pork included bone with pure water jet and saltwater jet ([60], adapted from “Cutting meat with bone using an ultrahigh pressure abrasive waterjet” with permission from Elsevier, 2022).  
Hence, meat cutting operations can be completed by water jet cutting under the optimal cutting parameters and suitable jet media. Pre-cooling meat is convenient for pure water jet cutting. Adding abrasives or liquids can improve the cutting ability and cut larger sections of meat, bone, or meat with bone. Furthermore, meat can be cut at room temperature using AWJ, which will reduce the cost of pre-cooling but increase the cost of abrasives. As for reducing meat loss, it is necessary to add abrasives or pre-cooling based on optimizing the cutting parameters (i.e., a low transverse speed and a small nozzle diameter). Moreover, water jet cutting devices with a wide applicability and strong functionality need to be designed to reduce the overall costs.
# Applications of Mueller Matrix Polarimetry to Biological and Agricultural Diagnostics: A Review
## 4 Applications of MMP to Biology and Agriculture
### Microbiological Research  
MMP is relevant for the detection of viruses and microorganisms. For example, MMP was used to analyze blood for the presence of the dengue virus [19]. It was found that blood samples with dengue fever virus have a higher depolarization factor than normal samples, which, hypothetically, could allow the detection of this virus in the early stages of infection. Changes in the growth of rod-shaped bacteria were studied using polarimetric scatterometry [62]. The block-diagonal elements of MM are sensitive to the size and shape of microbiological entities, as shown in the example of microalgae in [113]. Quantitative parameters for distinguishing between different bacterial colonies can be acquired from MM images using the MM polar decomposition method, frequency distribution histograms and the central moment analysis method [31]. Water-polarized reflectance was investigated to retrieve the properties of oceanic constituents (suspended organic matter and phytoplankton), primarily their concentration and biomass [119].  
Figure 8: Main directions for the application of MMP in agriculture.
# Survivable Deployments of Optical Sensor Networks against Multiple Failures and Disasters: A Survey
## 3 Sensing Connectivity and K-Node (Edge) Sensing Connectivity
### K-Node (Edge) Sensing Connectivity
#### 3.3.2 Maximum Number of Independent End-to-Sensing Light Path Calculations  
_K_-node (edge) sensing connectivity means that at least \(k\) independent paths exist and can be used by each collector to access the sensing data. An OSN is called _k_-node (edge) sensing-connected when it satisfies _k_-node (edge) sensing connectivity requirements. Therefore, we can achieve _k_-node (edge) sensing-connected OSNs by searching for independent \(k\). To determine if the current sensor deployment satisfies the _k_-node (edge) sensing connectivity requirement or not, we need to search the maximum number of independent end-to-sensing light paths between users and the sensors set from current sensor deployment. If the maximum number of independent end-to-sensing light paths between the collector and the sensors set from current sensor deployment is greater than or equal to \(k\), we believe that the candidate sensor set satisfies the _k_-node (edge) sensing-connected requirement. The algorithm that searches the maximum number of independent end-to-sensing light paths between the node and node set can be proved to be Non-deterministic Polynomial Complete (NP-Complete). The ILP model and heuristic methods, such as ant colony, genetic algorithm, and simulated annealing algorithm, can be used to obtain the maximum number of independent end-to-sensing light paths. Figure 8 presents the schematic diagram of the maximum number of independent end-to-sensing light path calculations. In Figure 8a-c, the number of available sensors is one, two, and three, respectively. For example, in Figure 8c, the maximum number of independent end-to-sensing light paths between user_1 and sensors E, F, and G is three. These three light paths are P\({}_{1}\): 1\(\rightarrow\)E, P\({}_{2}\): 1\(\rightarrow\)2\(\rightarrow\)F, and P\({}_{3}\): 1\(\rightarrow\)6\(\rightarrow\)G.  
Figure 8: Independent end-to-sensing light path calculations: (**a**) independent end-to-sensing light paths with one available sensor; (**b**) independent end-to-sensing light paths with two available sensors; (**c**) independent end-to-sensing light paths with three available sensors.
# Saturation, Allowed Transitions and Quantum Interference in Laser Cooling of Solids
## 2 Theory  
In prior experimental research, the forbidden transitions of trivalent rare-earth ions such as Yb\({}^{3+}\) were employed to demonstrate ASF cooling in insulating crystals and glasses. While many proposals have been advanced to diversify the possible approaches for cooling and to extend the results to a wider class of materials [10; 11; 12; 13; 14; 15; 16], no alternatives to net cooling by anti-Stokes fluorescence have emerged. This failure has impeded the application of laser cooling to the refrigeration of semiconductor circuitry for sensors in space, although an ASF cryocooler for this type of application has been reported [4]. Better speed and efficiency of cooling would be highly advantageous for practical applications. In the following subsections, theoretical advances are described that address the need for the improved performance of optical refrigeration based on anti-Stokes fluorescence cooling through optical saturation and the use of electric-dipole-allowed transitions. The experimental realizations of these proposals are presented in Section 3.
## 3 Results and Discussions
### Ultimate Analysis  
Figure 6 demonstrates the change in H/C and O/C molar ratios with respect to the torrefraction residence time. The relative increase in the carbon and the decrease in hydrogen and oxygen content also suggests the change in chemical composition, which leads to the decrease in H/C and O/C ratios. This increases the hydrophobic nature, which enhances the storage and transportation capability of the biomass. In addition, the decrease in H/C and O/C ratios is advantageous as less smoke and water vapor is formed, reducing the energy loss during combustion and gasification processes. Therefore, this alteration in the chemical composition of biomass can upgrade its quality as an energy source as more oxygen is lost in the form of volatiles than carbon.  
The increase in the calorific value coordinates with the increase in the carbon content and the decrease in the oxygen and hydrogen content with the increase in the torrefraction temperature and residence time. The reduction in oxygen and hydrogen content is due to the loss of oxygen0 and hydrogen-rich volatile components during the pyrolysis phase of torrefraction. In contrast, the nitrogen establishes no correlations with the torrefraction temperature. The decrease in H/C and H/C ratios can also lead to increase in the degree of torrefraction [48]. Lower O/C ratios observed at temperature above 200 \({}^{\circ}\)C can be due to the release of oxygen-rich compounds, such as CO\({}_{2}\) and H\({}_{2}\)O, while the decrease in H/C can be associated with the formation of CH\({}_{4}\) during torrefraction [49]. This can be correlated with the gas analysis from Figure 7 where CH\({}_{4}\) is produced after 250 \({}^{\circ}\)C, and CO and CO\({}_{2}\) after 200 \({}^{\circ}\)C.  
Figure 5: (**a**) Volatile fraction (%); (**b**) fixed carbon (%); and (**c**) ash (%) as a function of the torrefraction residence time.
## 5 Cryptosystems Choice
### Cryptosystem for Vendor'S Key-Pair  
In the described digital cash paradigm, the vendor is in possession of a key-pair whose public key has been denoted as \(PK_{V}\). This key-pair is used for the generation of the \(\{Y,\text{Sign}_{PK_{V}}(Y)\}\) digest-signature tuple. This tuple is generated differently depending on whether the generated e-coin is valued or not. More precisely,  
* If the e-coin is valued, the customer computes \(Y\) and requires the vendor to compute a blind signature on it (Section 4.3, step 5).  
If the e-coin is no-valued, the tuple is simulated by the customer. The vendor does not take part in this process (Section 4.4, step 1).  
Hence, the signature scheme chosen for such \(\{Y,\text{Sign}_{PK_{V}}(Y)\}\) tuples has to enable both:  
The computation of _blind_ signatures.  
The generation of _simulated_ digest-signature tuples.  
Next, we discuss two feasible options.
# Radiometric Method for Determining Canopy Stomatal Conductance in Controlled Environments
## 4 Discussion
### The Control of Transpiration by CO\({}_{2}\) Concentration  
The radiometric method developed in this study was used to determine the response curve of G\({}_{\rm S}\) to CO\({}_{2}\) concentration in wheat (Figure 11, Table 3). As CO\({}_{2}\) concentration increased, the measured decrease in E\({}_{\rm can}\) was lower than the measured decrease in G\({}_{\rm S}\) because feedback between E\({}_{\rm can}\) and D\({}_{\rm S}\) operating at the canopy scale effectively reduces the sensitivity of E\({}_{\rm can}\) to changes in G\({}_{\rm S}\). Thus, a smaller change in E\({}_{\rm can}\) was observed as CO\({}_{2}\) increased, and the reduction in E\({}_{\rm can}\) is largely explained by changes in \(\Omega\), which are determined by the relative magnitudes of g\({}_{\rm A}\) and G\({}_{\rm S}\).  
In this study, an increase of 1.77 X CO\({}_{2}\) (that is, an increase from 390 to 690 \(\upmu\)mol mol\({}^{-1}\); Table 3) caused a \(-\)23% drop in E\({}_{\rm can}\) and a +15% increase in photosynthesis. These changes are comparable to the results of [PERSON] and [PERSON] [50], who used a combined climate-vegetation model to predict a similar \(-\)25% drop in ET and a +19.4% increase in GPP for a doubling ambient CO\({}_{2}\) (2 X CO\({}_{2}\)). In a four-year SoyFACE study, [PERSON] et al. [51] found a 9-16% reduction in canopy ET and reported that meta-analyses across FACE experiments indicate a 17-22% drop in leaf level stomatal conductance when daytime CO\({}_{2}\) was raised by 175 umol mol\({}^{-1}\) from 375 to 550 umol mol\({}^{-1}\). In this study, the two regression equations in Figure 11 (E\({}_{\rm can}\) and G\({}_{\rm S}\) as a function of CO\({}_{2}\) concentration) predict a 13% decrease in E\({}_{\rm can}\) and a 22% decrease in canopy G\({}_{\rm S}\) for an increase of 175 umol mol\({}^{-1}\) of CO\({}_{2}\). These comparisons suggest that the responses of G\({}_{\rm S}\) and E\({}_{\rm can}\) to CO\({}_{2}\) reported in this study are similar to responses in canopy G\({}_{\rm S}\) and ET observed in CO\({}_{2}\)-enriched plant canopies in field settings.
## 3 Establishment and Verification of the Engine Model  
### Establishment of the Engine Model  
This research was based on the operating conditions of an engine with direct fuel injection and supercritical injection and combustion technology. We assumed that the mixture of gasoline and diesel would burn in the cylinder of the gasoline engine. The parameters of in-cylinder air cannot easily exceed the critical value of fuel at fuel injection time and cannot make fuel enter the supercritical state because the in-cylinder pressure is too low at the top dead center. Therefore, the diesel engine model and boundary condition used in [31] was utilized to simulate the operation of the engine under supercritical conditions by jetting a supercritical state mixture of gasoline and diesel into the cylinder in supercritical state [32]. The main structural parameters of the engine used are shown in Table 1.  
An engine model needs to be meshed in a numerical simulation. What we used in this simulation is unstructured grid. An unstructured grid easily adopts the boundary region and the calculation of stress concentration on the fluid surface. According to the symmetry of the selected engine, one-eighth of the entire combustion chamber was used as the calculation area. Figure 1 shows the shape of the combustion chamber at TDC and the grid used for calculation.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parameters** & **Values** \\ \hline Cylinder diameter \(\times\) cylinder stroke, mm & \(115\times 115\) \\ Compression ratio & 16:1 \\ Connecting rod length, mm & 210 \\ Displacement, L & 1.2 \\ Combustion chamber shape & \(\omega\) \\ Rotating speed, r-min\({}^{-1}\) & 1800 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Engine structural parameters  
Figure 1: Engine combustion chamber shape and grid diagram.  
Owing to the transient characteristics of parameters during engine operation, the relaxation time of turbulence and time-averaged movement are short, which reduces the influence of the initial conditions on the results. Therefore, the time-averaged parameters were selected as the initial condition in the numerical simulation.  
Grid size affects the accuracy of the calculation. As shown in Figure 2, in accordance with the geometrical structure of the model, the maximum grid size was set to 1, 2, and 4 mm, and a grid independent test was implemented. The maximum grid size was then determined to be 2 mm.
## 2 Theoretical background  
### Uses and Gratifications Theory  
The Uses and Gratifications (U&G) Theory, which originated in [30], aimed to detect the motivational needs of the audience of a radio quiz programme. Thereafter, it has been widely used in research. Recent studies [31; 32; 33; 34] legitimate the U&G approach as one of the most relevant communication theories for explaining the use of media based on the virtual environment.  
The U&G approach originally focused on identifying why people choose one communication medium over another [35; 36; 37; 38; 39; 40]. The theory has been used to explore a wide range of topics relating to recent ICT, such as virtual worlds [41; 42; 43], online social networking [44], web-based information services [45] and Internet news browsing [46]. However, there are few investigations in the field of augmented reality mobile games that apply the U&G theory [47].  
U&G principles establish that people usually have a wide range of needs that can be gratified when they consume media [48; 49]. For that reason, U&G Theory tries to explain the social and psychological reasons why people are motivated to use media to fulfil their needs [50; 51; 52]. In fact, U&G has the potential to examine personal motivations and persistent use of an augmented reality mobile game, specifically Pokemon Go.  
Prior research usually classifies gratifications into three categories [43; 53; 54]: (1) hedonic, (2) utilitarian, and (3) social. This last one is linked with the attainment of status. Among these three groups, perhaps the hedonic variables have received most attention in studies that try to analyse the  
Figure 1: Pokémon Go interfaces.  
motivations of those using ICT for leisure and voluntary activities. In this sense, the U&G approach can be applied to online games as they are a relevant part of the Internet and the media [53; 55].
## 1 Introduction  
Many experimental and numerical studies have been conducted to study the effect of thermal loads on temperatures and thermal gradients for concrete and composite girder bridges. However, limited research has been conducted to investigate the thermal behavior of steel members, especially during the construction period. The inaccurate determination of the temperature distributions of steel members during construction can potentially cause constructional and structural deficiencies, resulting in thermal stresses and other safety hazards. Moreover, the Canadian highway bridge design code (CHBDC) [1] has implemented a single thermal gradient differential profile for all of Canada without considering each region's varying geographical conditions and geometry parameters. This could lead to different solar radiation intensities, drastically altering the girder section's temperature gradients and distributions. In this study, finite element thermal analysis was carried out using the validated thermal model to investigate the maximum effective temperatures and vertical thermal gradients. The abovementioned thermal behaviors were evaluated for one summer month using parametric studies for different Canadian climate regions and standard steel girders. Comparisons and observations of the FE thermal behaviors were conducted to propose the appropriate maximum effective temperatures, thermal gradient profiles and maximum thermal gradient variations based on the environmental and geometry parameters. Using regression analysis, formulas were proposed to predict the maximum effective temperature and maximum thermal gradient variation. Finally, the proposed maximum effective temperatures and maximum thermal gradient pattern and variations were compared with the corresponding values and pattern recommended by the CHBDC [1]. The results of the finite element thermal analysis in this study are valuable for designers to understand the influences of climate regions and geometrical parameters on the thermal responses of steel bridge girders. Furthermore, the findings can be used to develop realistic thermal gradient variation profiles for steel bridge girders in the Canadian highway bridge design code (CHBDC), ensuring the safety and reliability of steel bridges in different climate regions of Canada.
## 3 Results
### Endogenous Hormones and N Metabolism-Related Enzyme Concentrations in Maize Root  
At the V12 stage of maize, IAA and ZR concentrations in maize root were significantly increased by 42.32% and 50.11%, respectively, in the U+FA treatment compared with the U treatment (Figure 1A). Meanwhile, there is a significant effect on NR, NiR, GS, GSR, GOGAT, and GLDH in U+FA treatment at the V12 stage. The concentrations of NR, NiR, GS, GOGAT, and GLDH in the maize root of the U+FA treatment were significantly higher by 74.17%, 16.61%, 45.60%, 43.07%, and 69.02%, respectively, compared with the U treatment (Figure 1B-D). The GSR concentration in the U+FA treatment was higher, though not significantly, than in the U treatment (Figure 1C). In summary, the concentrations of endogenous hormone and the N metabolism-related enzymes in the maize root of urea in combination with FA solution treatment were boosted compared to the U treatment.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Treatment** & \begin{tabular}{c} **Aboveground Dry** \\ **Biomass (g pot\({}^{-1}\))** \\ \end{tabular} & \begin{tabular}{c} **100-Grain** \\ **Weight (g)** \\ \end{tabular} & \begin{tabular}{c} **Grains per** \\ **Row** \\ \end{tabular} & \begin{tabular}{c} **Rows per** \\ **Ear** \\ \end{tabular} & \begin{tabular}{c} **Grain Yield** \\ **(g pot\({}^{-1}\))** \\ \end{tabular} & \
\begin{tabular}{c} **Yield** \\ **Increase (\%)** \\ \end{tabular} &
\begin{tabular}{c} **NUE** \\ **(\%)** \\ \end{tabular} \\ \hline
2017 & & & & & & & \\ CK & 83.3 c & 25.4 b & 13.0 a & 12.0 c & 36.1 c & \(-\)78.92 & - \\ U & 289.9 b & 29.5 ab & 14.5 a & 32.8 b & 171.3 b & - & 36.96 \\ U+FA & 306.7 a & 30.4 a & 14.5 a & 39.0 a & 185.5 a & 8.31 & 54.05 \\
2018 & & & & & & & \\ CK & 162.1 c & 21.0 b & 12.0 b & 25.0 b & 85.2 c & \(-\)56.14 & - \\ U & 328.9 b & 28.8 a & 14.0 ab & 36.7 a & 194.2 b & - & 24.70 \\ U+FA & 381.0 a & 30.7 a & 15.3 a & 40.3 a & 227.0 a & 16.90 & 49.01 \\ \hline \hline \end{tabular}  
* Treatments: no nitrogen fertilizer (CK); application of urea (U); combined application of urea and fulvic acid (U+FA). Values within a same column followed by different letters are significantly different between treatments for a same year according to least significant difference test (\(p<0.05\)).  
\end{table}
Table 2: Maize aboveground dry biomass, yield and yield components, and nitrogen use efficiency (NUE) in different fertilization treatments.