esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Results and Discussion
### Comparison with the State-of-the-Art Approaches  
In addition to the empirical evaluation to emphasize the practicality of the proposed system, a comparative evaluation with the state-of-the-art approaches was conducted to determine the academic value of this study. In order to formulate new-product portfolios, the conventional case-based reasoning mechanism was further revamped with a consideration of the customer preferences, in which the transfer learning for natural language processing was embedded to analyze customer comments available in the retail e-commerce platforms. Compared with existing work [14; 19], the differences in terms of objectives, methodologies, and novel elements for the NPD decisions were summarized, as shown in Table 7. In the research methodology, the transfer learning for opinion mining was incorporated into the cycle of case-based reasoning so as to achieve the customer-centric NPD management, in which the continuous improvements and customer-centric thinking were orchestrated.  
It was found that the concept of customer-centric thinking was included in NPPM through this study, while the transfer learning for BERT was designed and developed for the case-retrieval process. Unlike the theoretical development of the previous studies, this study provides a real-life case study in the printer manufacturing business to show the entire mechanism and process to effectively illustrate the value of the intelligent project portfolio management over a CBR cycle with opinion-mining capabilities. Regarding the technical  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**No.**} & \multicolumn{2}{c}{**Average of the Scales**} & \multicolumn{2}{c}{\(p\)**-Value**} \\ \cline{2-4}  & **Before** & **After** & **of the Mann–Whitney U Test** \\ \hline
1 & 3.111 & 3.667 & 0.105 \\
2 & 3.111 & 3.889 & 0.021 * \\
3 & 2.556 & 3.556 & 0.068 \\
4 & 3.111 & 4.000 & 0.048 * \\
5 & 3.556 & 4.222 & 0.076 \\ \hline \hline \end{tabular}  
* Remark: The \(p\)-value with asterisk (*) denotes that the median differences of the measurement items are statistically significant at 95% confidence interval, and thus the median of the scale after the system implementation is significantly higher than the scale before the system implementation.  
\end{table}
Table 6: Mann–Whitney U test for the statistical measurement.  
\begin{table}
\begin{tabular}{l l} \hline \hline
**No.** & **Measurement Items** \\ \hline
1 & The current NPPM approach is good with respect to ease of implementation \\
2 & The current NPPM approach is good with respect to ease of use. \\
3 & The current NPPM approach is effectively compatible with other enterprise \\  & systems for the NPD process. \\
4 & The security level of the current NPPM approach is satisfactory. \\
5 & My overall performance for the current NPPM approach is positive. \\ \hline \hline \end{tabular}
\end{table}
Table 5: Measurement items of the empirical investigation.  
aspects, the proposed work was developed not only for cost and profit optimization, but also for customer requirements and feedback on relevant products available in the market.
# From the Martian Surface to Its Low Orbit in a Reusable Single-Stage Vehicle--[PERSON]
## 3 Results
### Energy Requirements  
The general power requirement for the different processes associated with the manufacturing and storing of the propellant is summarised in Table 2. This is the constant required power in the case of one launch over a 130 days period. The power required is computed based on the energy required to produce each of the propellant constituents, as well as the energy required to transform the raw mined materials to the products used to create the propellant constituents. In addition, the efficiencies of the different transformations has been taken into account. Finally, the Sabatier reaction releases energy, which thus has a negative contribution to the propellant manufacturing power budget. For the process of water electrolysis, which is the most power consuming process, it is assumed to occur with 286 kJ/mol and a 75% efficiency, which can be assumed for steam reforming electrolysis [45].  
There is thus a need for a total of 1.02 MW of power constantly for one launch in 130 days. Moreover, considering electrolysis, oxygen liquefying and carbon dioxide capture to be electrical processes, 972 kW of this power needs to be electrical, while 50 kW is thermal.  
The 1 MW electrical power requirement makes one consider a scaled-back nuclear power plant to provide the required energy. While small scale projects exist as nuclear reactors on the Martian surface [46], mission concepts with a megawatt-rated nuclear power plant were suggested a long time ago--both by the Soviet Union [47] and NASA [48]. Such a reactor would require 1.1 kg of Uranium-235. This could be either imported from Earth or found on Mars, where, although no hard-proven data exists, mathematical models predict an abundance of Uranium resources, as it is predicted that the formation of found radioactive potassium traces are from Uranium [49]. Therefore, while additional studies are needed on the feasibility of uranium mining on Mars, a nuclear reactor of such scale is a realistic and highly probable concept for the Martian base, as it is easier to construct and operate than thousands of square meters of solar arrays. In the case that 10 launches would occur every 260 days, this nuclear reactor would have to be significantly scaled up in order to produce enough power.
###### Abstract  
Fast and reliable information is crucial for first responders to draw correct conclusions at crime scenes. An ambient pressure laser desorption (APLD) mass spectrometer is introduced for this scenario, which enables detecting substances on surfaces without sample pretreatment. It is especially useful for substances with low vapor pressure and thermolabile ones. The APLD allows for the separation of desorption and ionization into two steps and, therefore, both can be optimized separately. Within this work, an improved version of the developed system is shown that achieves limits of detection (LOD) down to 500 pg while remaining fast and flexible. Furthermore, realistic scenarios are applied to prove the usability of this system in real-world issues. For this purpose, post-blast residues of a bomb from the Second World War were analyzed, and the presence of PETN was proven without sample pretreatment. In addition, the analyzable substance range could be expanded by various drugs and drug precursors. Thus, the presented instrumentation can be utilized for an increased number of forensically important compound classes without changing the setup. Drug precursors revealed a LOD ranging from 6 to 100 ng. Drugs such as cocaine hydrochloride, heroin, (3,4-methylenedioxy-methamphetamine) hydrochloride (MDMA) hydrochloride, and others exhibit a LOD between 10 to 200 ng.  
APLD; drugs; explosives; post blast residue detection; mass spectrometry; chemical ionization; on-line measurement; forensic chemistry; mapping 2018 8933390/app8060933
## 2 Data and Methods
### Analysis Methodology  
The comparison methodology includes four parts. First, the basic relationship between the NDVI of six datasets (NDVIg, NDVI3g, STAR, VIP, SPOT, Terra) were intercompared over the common time-period from 2001 to 2008. Three types of linear regressions were performed between each pair of datasets: (1) a general regression using all 10-day periods from 2001 to 2008 for nine select point locations (see Section 3.2) corresponding to various biomes; (2) the temporal regression between each pair of datasets for each pixel (not water or snow/ice) to determine how the relationship between datasets varies in space for NDVI; and (3) the spatial regression over all pixels (not water or snow/ice) of the 10-day time period for one dataset against the same 10-day period for another dataset for each dataset pair to create time-series of annual averages of the 10-day spatial correlation and regression slopes. For all regressions, an orthogonal regression was performed [34] that assumes the error variance of the dependent and independent variables are equal whereas the traditional least squares regression assumes that the independent variable has no error associated with it [57]. Furthermore, the mean and range (maximum-minimum) of the annual maximum NDVI (\(N_{p,max}\)) from the 6 datasets spanning 2001 to 2008 were compared for each IGBP vegetation class.  
Second, the trends of the four long-term datasets (NDVIg, NDVI3g, STAR, VIP) were intercompared to understand how vegetation abundance and phenology are changing and if changes are consistent across products. First, the long-term significant linear trends at the 95% level (\(p<\) 0.05) were calculated for \(N_{p,max}\) for each dataset for each pixel. Next, the phenology of NDVI was calculated for each year and dataset for start, end and duration of greening season. Furthermore, significant trends in these metrics were computed at the pixel and land cover class level. In addition to the 95% statistical significance, the results are also filtered to include only those pixels whose dominant greening period occurs at nearly the same time each year. Most of the pixels excluded from the analysis were from arid and semi-arid areas in the Southwest US, southern Texas and northern Mexico as well as broadleaf evergreen areas in the tropical forests of southeastern Mexico.  
Third, the green vegetation fraction (GVF) methodology from [PERSON] _et al._[41] (to be discussed in detail in Section 3.3) will be introduced as a method to homogenize the datasets, and the same analysis used to intercompare the six NDVI datasets was also completed for the transformed GVF datasets.  
Finally, the phenology of GVF was calculated in the same way as the phenology of NDVI and the change in phenological trends between NDVI and GVF were analyzed for each long-term dataset.
# Bio-Sourced and Biodegradable Membranes
## 4 Green Membrane Technology Applications
### Peraporation  
As one of the emerging technologies, Pervaporation has experienced rapid development in recent decades. This technology involves the membrane separation and liquid-to-vapor phase transition through the pressure difference between the feed and permeate sides (as the driving force) and works based on the difference between the diffusion/sorption of the components in the mixtures [207,208]. In order to create the pressure difference, a vacuum pump is employed at the permeate side, resulting in the vaporization and transport of the components with a higher affinity. Pervaporation is an easily performed, which is an environmentally friendly and energy-efficient process used to separate an organic compound from a dilute liquid mixture or an organic mixture with a close boiling point and dehydration of azeotropic- aqueous organic mixtures [208, 209, 210, 211]. Biodegradable membranes have been increasingly used in pervaporation systems to improve the sustainability of the process. However, the efficiency and performance of this process are highly dependent upon the membrane's selectivity and its ability to separate the particular components from liquid mixtures [207,209]. Membranes with polar characteristics and aromatic groups such as CS, PVA, agarose, alginate, and fluorinated polymers are favorable for organic dehydration due to their hydrophilic property and high water selectivity [211]. Conversely, hydrophobic membranes like poly-dimethyl siloxane [211] polyurethane urea [212] are more suitable to remove non-polar components (mostly organic matters) from dilute solutions. PLA, PHA, CS-based, PVA-based, and mixed matrix membranes are the most common biodegradable membranes for boiling azeotrope mixtures like methanol-methyl tert-butyl ether or methanol-toluene [213, 214, 215, 216]. Table 2 summarizes the use of biodegradable membranes in various pervaporation processes.
# Rainfall Erosivity Main Features and Their Associated Synoptic Conditions in North-Eastern Romania
## 2 Materials and Methods
### Methods  
#### 2.3.1 Fournier Index (FI) and Modified Fournier Index (MFI)  
Generally, there is a strong link between the annual rainfall distribution and the amount of eroded soil. Many researchers [9; 12; 39; 40; 41] have shown that the Fournier Index and the Modified Fournier Index are indispensable in studying rainfall erosivity.  
To calculate the first index (Table 1), we used the average monthly amount of precipitation for the rainiest month of the year (p\({}_{\text{max}}\)) and the annual amount of precipitation (P): F = p\({}_{\text{max}}\)\({}^{2}\)/P.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Erosion Class** & **Fournier Index** & **Soil Loss (t/ha/year)** \\ \hline Very Low & 0–20 & 0–5 \\ Low & 20–40 & 5–12 \\ Moderate & 40–60 & 12–50 \\ Severe & 60–80 & 50–100 \\ Very severe & 80–100 & 100–200 \\ Extremely severe & \textgreater{}100 & \textgreater{}200 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Erosion classes based on Fournier Index values [42].  
While the Fournier Index takes into account precipitations amounts from the rainiest month of the year, [PERSON] [43] proposed a modification to this index (Table 2) so that precipitations of other months are considered. Its formula uses the average monthly amount of precipitation (_Pi_) and the annual precipitation amount (_P_): \(MFI=\sum_{i=1}^{12}Pi^{2}/P\).
# A Self-Scrutinized Backoff Mechanism for IEEE 802.11 ax in 5G Unlicensed Networks
###### Abstract  
The IEEE 802.11 ax high-efficiency wireless local area network (HEW) is promising as a foundation for evolving the fifth-generation (5G) radio access network on unlicensed bands (5G-U). 5G-U is a continued effort toward rich ubiquitous communication infrastructures, promising faster and reliable services for the end user. HEW is likely to provide four times higher network efficiency even in highly dense network deployments. However, the current wireless local area network (WLAN) itself faces huge challenge of efficient radio access due to its contention-based nature. WLAN uses a carrier sense multiple access with collision avoidance (CSMA/CA) procedure in medium access control (MAC) protocols, which is based on a binary exponential backoff (BEB) mechanism. Blind increase and decrease of the contention window in BEB limits the performance of WLAN to a limited number of contenders, thus affecting end-user quality of experience. In this paper, we identify future use cases of HEW proposed for 5G-U networks. We use a self-scrutinized channel observation-based scaled backoff (COSB) mechanism to handle the high-density contention challenges. Furthermore, a recursive discrete-time Markov chain model (R-DTMC) is formulated to analyze the performance efficiency of the proposed solution. The analytical and simulation results show that the proposed mechanism can improve user experience in 5G-U networks.  
5G network; 5G unlicensed; IEEE 802.11 ax; channel contention +
Footnote †: journal: _Sustainability_  
_Article_  
A Self-Scrutinized Backoff Mechanism for IEEE 802.11 ax in 5G Unlicensed Networks
# Metabolite Analysis of Hangzhou Gongmei White Tea of Different Varieties  
[PERSON]  
1 Tea Research Institute, Hangzhou Academy of Agricultural Science, Hangzhou 310024, China; [EMAIL_ADDRESS] (C.A.); [EMAIL_ADDRESS] (X.N.); [EMAIL_ADDRESS] (J.Y.); [EMAIL_ADDRESS] (Z.C.)  
[PERSON]  
1 Tea Research Institute, Hangzhou Academy of Agricultural Science, Hangzhou 310024, China; aocun123@163.  
variety and origin on quality is particularly prominent. A comparison of Yunnan white tea and Fujian white tea reveals that the former is characterised by plump buds, a darker colour, and a less sweet and refreshing taste [9]. In addition, white tea produced from oolong tea varieties has been found to possess a floral aroma [23,24]. The variation in quality is primarily attributable to the differential composition of metabolites, both volatile and non-volatile, and their respective concentrations. Volatile metabolites are responsible for the aroma quality, while non-volatile metabolites determine the flavour quality. The main aroma compounds of white tea have been identified as oct-1-en-3-ol, linalool, geraniol, phenethyl alcohol, \(\beta\)-ionnone, \(\alpha\)-ionone, hexanal, \(\gamma\)-nonalactone, nonanal, phenylacetaldehyde, (\(E\),\(Z\))-nona-2,6-dienal, 2-amylfuran, safranal, and others [25]. Linalool and its oxides, geraniol, phenylacetaldehyde, and jasmone, were found to be positively correlated with floral aroma [20], while linalool and phenylacetaldehyde were also identified as the key aroma components for the fruity and sweet aroma of Jinggu white tea [26]. In addition, dihydro-5-pentyl-2(3H)-uranone, (\(E\))-6,10-dimethyl undeca-5,9-dien-2-one, and 2-pentylfuran were identified as the key aroma components of milk-flavoured white tea [27]. Furthermore, free amino acids and peptides have been identified as key contributors to umami and sweet tea flavours [6,19]. Sucrose, galactitol, and fructose were identified as the predominant sugar compounds in white tea, contributing to its sweet flavour [2]. In addition to ester-type catechins, flavonoid glycosides such as quercetin glycoside, kaempfer glycoside, and myricetin glycoside also had a bitter taste and enhanced the bitterness of caffeine [28,29].  
The comprehensive utilisation of tea resources is an important direction for the development of the tea industry. The popularity of white tea has led to the development of Hangzhou white tea, which is produced using fresh leaves in the late spring, summer, and autumn months. In order to standardise and promote the development of the Hangzhou white tea industry, the \"Hangzhou White Tea\" group standard of the Hangzhou Tea Science Society was published [30]. Currently, there is little research on Hangzhou white tea. The quality features and characteristic metabolites of HGW, one of the main products of Hangzhou white tea, are not yet fully understood [31]. This study was the first to combine sensory evaluation and metabolomics analysis of HGW from the key varieties cultivated in Hangzhou. The study provides a theoretical foundation for enhancing the quality and optimising the processing of Hangzhou white tea.
## 3 Results and Discussion
### Field Boundary  
The area of a boundary should represent the specific field size and location, as documented in the field catalogue (2.90 ha). It was calculated by the developed software with \(A_{boundary}=2.94\) ha, which results in an overestimation of 1.4%. Figure 15 shows a satellite view of the boundary (indicated in green) for the examined field. It fits the actual field location. Several error sources influenced the determination of the boundary. The erroneous D-GNSS positioning had an effect, especially at the field edges. A further influence negatively affecting the determination of the boundary was that the applied shrinking of the MATLAB function \"boundary\" could not deliver the closest fit possible. Furthermore, what is assumed to cause error is the deviation from the plow rotation scheme or a variation in working width, especially at the beginning and the end of a field part. Another possible error source is the rolling of the tractor while driving on a slope along the field edges. All these errors could not be monitored and corrected. Considering these errors, the deviation of 1.4% from the actual field size is a strong indication of the efficiency of the developed algorithm.
# Multi-Focus Microscopy Image Fusion Based on Swin Transformer Architecture
## 4 Experiments
### Experiment Results for Various Color Spaces  
In order to assess the effectiveness of our proposed model based on the Swin Transformer backbone, we explored various color spaces (RGB, YCrCb, HSV, LAB) for multi-focus microscope image fusion. We evaluated the performance of the fusion model for the two selected microscope images from the EDoF Fraunhofer dataset, as discussed in Section 4.2. In this section, we conducted qualitative and quantitative evaluations of the U-Swin fusion model with the channel mix fusion rule. The proposed model shown in previous sections fused the microscope images in RGB color spaces, treating the three channels of the multi-focus microscope images as the model inputs. Figure 6 and Table 3 demonstrate that our proposed model with the channel mix fusion rule could achieve satisfactory performance in various color spaces. The outcome suggests that the proposed model (U-Swin fusion model) achieves state-of-the-art (SOTA) results for the RGB color space and is applicable to other color spaces as well.  
Figure 5: The comparison example of multi-focus fused images from EDoF Fraunhofer dataset.  
\begin{table}
\begin{tabular}{c c c c} \hline  & **MSE** & **PSNR** & **SSIM** \\ \hline RGB & **2.74 \(\pm\) 0.63** & **43.85 \(\pm\) 0.93** & **0.9839 \(\pm\) 0.0020** \\ YCrCb & 4.39 \(\pm\) 0.66 & 41.75 \(\pm\) 0.63 & 0.9526 \(\pm\) 0.0025 \\ HSV & 6.40 \(\pm\) 1.27 & 40.16 \(\pm\) 0.86 & 0.9623 \(\pm\) 0.0052 \\ LAB & 4.96 \(\pm\) 0.78 & 41.23 \(\pm\) 0.67 & 0.9628 \(\pm\) 0.0021 \\ \hline \end{tabular}
\end{table}
Table 3: Quantitative evaluation results for the U-Swin fusion model with channel mix fusion rule for various color spaces. The values highlighted in bold font represent the best results in their respective evaluation metric columns.
# A New Propagation Channel Synthesizer for UAVs in the Presence of Tree Canopies
## 6 Discussion  
The presented UAV channel synthesizer applicable in the presence of tree canopies relies on generating two types of scattered fields--coherent and incoherent. Their corresponding models have been presented in Section 2. It should be noted that the validity of the PO/MST model for the coherent scattered field is limited by the fact that the path through a canopy should be below one or two skin depths, as noted in [7]. This approximately restricts the model to frequencies from L to X band [7] which are generally applicable for UAV communications.  
It has also been demonstrated that a number of simplifications were made to generate the resulting time series within reasonable computation times. Mainly, the complex propagation constant within tree canopies was the same for all forward scatter directions. Similarly, as the worst case scenario, the incoherent scattered field calculations supposed the equivalent scattering cross section per unit volume to be independent of the scattering direction. Further, the coherent scattered fields were calculated only for the selected trees which were the closest to the forward scatter direction. Other simplifications then include neglecting ground reflections, presence of tree trunks, and blockage by main branches in the canopies. We have also restricted the analysis to the vertical polarization configuration, although the polarization information is present within the synthesizer.  
It was demonstrated that the channel synthesizer matches the results that can be expected for an artificial scenario and, moreover, a very good match was identified for the case of the experimental data obtained for a typical UAV link in the presence of an alley of trees.  
Due to the multiplicative nature of the synthesizer's output, the generated time series can directly be converted into the resulting attenuation behind tree canopies and added, in the dB scale, to attenuation obtained for other propagation effects, e.g., diffraction by terrain features. In this way, the SNR graphs for a particular link can readily be obtained. It should be noted that the CIR characteristics generated by the synthesizer can also be used to simulate BER in the physical layer of UAV links.
## 2 Methodology  
The snow mass detection capability of sensors (and sensor constellations by construct) is limited by the sensors' viewing extent, the distribution of snow in space and time, and the sensors' efficacy to specific snow conditions (e.g., ability to retrieve deep snow, wet snow, snow overlap by vegetation). This section introduces the methods to analyze these three factors, including the methodology used to simulate the sensor viewing extent, different scenarios for simulations, application of a dynamic snow mask, and metrics for use in evaluating observation efficacy.