esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 System Design  
### Overall Design of the Platform  
A management framework for operation and maintenance based on the cross-regional operations of combine harvesters is put forward in the form of the platform depicted in Figure 2. The developed system had four layers of architecture, namely, the support layer, the data layer, the functional layer, and the user layer. The support layer was mainly responsible for the collection of sensing data acquired from combine harvester, data transmission from the vehicle terminal of the combine harvester, and server storage and loading of the software, all of which are used to establish, store and combine data related to remote operation and maintenance, the operational information of key components, and data on the status of the combine harvester. By means of the support layers, the application logic for harvester repair services can be quickly created, assembled, deployed and managed. The data layer comprises a database for service resource operation and maintenance constituted on the basis of service branch data, maintenance personnel data, data related to spare parts centers and spare parts quantities, maintenance service vehicle data, and expert maintenance history data, all associated and structured as SQL database service resources. The permission settings of the O&M platform, the business logic relationships of each module, and the workflow of maintenance and management activities were also written using the SQL database. The functional layer mainly uses the intelligent optimization algorithm according to the maintenance service scenario and the fault maintenance task order to quickly complete maintenance work in consideration of factors such as maintenance path, cost, and time. The service interface converts the basic data in order to realize business functions, including real-time records of operation and maintenance management activities, visual analysis and early warning displays of faults in combine harvesters, traceable queries, statistical analysis, etc. In the user layer, the platform functions are integrated and classified for users, and finally integrated for three major users: platform management personnel, maintenance personnel, and agricultural machinery drivers.  
Figure 1: Schemes follow the same formatting.
# Performance Analysis of Quantum Key Distribution Technology for Power Business
###### Abstract  
Considering the complexity of power grid environments and the diversity of power communication transmission losses, this study proposes a quantum key distribution (QKD) network structure suitable for power business scenarios. Through simulating the power communication transmission environment, performance indicators of quantum channels and data interaction channels in power QKD systems are tested and evaluated from six aspects, such as distance loss, galloping loss, splice loss, data traffic, encryption algorithm and system stability. In the actual environment, this study combines the production business to build a QKD network suitable for power scenarios, and conducts performance analyses. The experimental results show that power QKD technologies can meet the operation index requirements of power businesses, as well as provide a reference for large-scale applications of the technology.  
a Article  
Performance Analysis of Quantum Key Distribution Technology for Power Business  
[PERSON] 1,2, [PERSON] 1, [PERSON] 3,* 4, [PERSON] 3, [PERSON] 1, [PERSON] 4,* and [PERSON] 3
# A Systematic Review of the Effects of Nutrient Intake in Handball Players on Exercise Performance
## 4 Discussion
### Carbohydrates  
Handball, like the vast majority of team sports, intersperses repeated bouts of brief, high-intensity exercise with lower-intensity actions on a consistent basis [78, 84]. Even between playing positions, there is wide variability in the number and frequency of such actions during the course of a single match [78]. In these scenarios, a decrease in muscle glycogen stores and altered muscle excitability and calcium kinetics is associated with increased central and peripheral fatigue in the form of reduced work rates, impaired skill and concentration, and increased perception of exertion [85]. The ACSM sets daily recommendations of 6-10 g CHO/kg body weight for moderate- to high-intensity exertions of 1-3 h duration [10]. [PERSON] et al. [15], in a 2011 review of nutritional strategies for team sports, established more modest daily recommendations of around 5-7 g CHO/kg/day during the competitive phase, with these amounts being increased during periods of higher energy demand such as major competition days or periods or high-intensity double sessions [37, 44]. Only athletes in three studies met the recommendations discussed above [37, 40, 34]. A well-controlled study by [PERSON] et al. [37] even showed how female track handball players modified their CHO intake according to the daily training load (6.5 to 7.5 g/kg/day on days with the highest training load). Intakes of around 7.9 g/kg/day were observed by [PERSON] et al. [40] in male beach handball athletes, although 80% of the athletes were not supervised by dieticians-nutritionists.  
However, most of the studies included in this review show inadequate CHO intakes with respect to the aforementioned recommendations, with amounts ranging from 3.25 to 4.7 g/kg/day in males and 3.1 to 4.2 g/kg/day in females [18, 25, 28, 29, 30, 33, 35, 38, 39, 41]. These data on low CHO intake, together with low energy intake, are consistent with those observed in other team sports disciplines and female populations [86, 87], although there is currently no clear consensus on the need to establish gender-specific CHO and PRO guidelines [88].  
Finally, for match or competition days, intakes of 1-4 g/kg of easily digestible CHO 2-4 h prior to the event may be recommended [15, 84, 89]; half-time intakes of small amounts of easily absorbable CHO of 30-60 g/h or even mouth rinses may be sufficient to replenish glycogen stores and maintain blood glucose levels during the second half [89, 90]; and intakes of 1.2 g CHO/kg including CHO-dense foods and beverages for 2 h post-match are recommended to take advantage of enhanced glycogen repletion rates, especially when the recovery period between matches is short [15, 36, 84, 91].
## 2 Proposed Approach
### Input Features
#### 2.1.4 Intensity Vector  
Since the spectral features described above are used for SED, additional features are required for DOAE. Acoustic IVs extracted from the FOA format are used for DOAE because they convey the information about the acoustic energy direction of the sound wave [11]. In the FOA format, omnidirectional and three-directional components are indicated in the order of the first to fourth channels, respectively. An acoustic IV consists of the real parts of the values computed by multiplying the conjugate value of the first channel signal and the value of the remaining channel signals in the STFT domain expressed as [12]  
\[\mathbf{I}(f,t)=\Re\left\{\mathbf{W}^{*}(f,t)\cdot\begin{bmatrix}\mathbf{X}(f, t)\\ \mathbf{Y}(f,t)\\ \mathbf{Z}(f,t)\end{bmatrix}\right\}, \tag{5}\]  
where \(\mathbf{W}(f,t)\), \(\mathbf{X}(f,t)\), \(\mathbf{Y}(f,t)\), and \(\mathbf{Z}(f,t)\) are spectral values of the first to fourth channel signals at frequency bin \(f\) and frame \(t\) in the STFT domain, respectively. \(\Re\{\cdot\}\) and * indicate the real part and the conjugate of a complex-valued matrix, respectively. The resulting three-dimensional vector is normalized by  
\[\mathbf{\bar{I}}(f,t)=\frac{\mathbf{I}(f,t)}{\|\mathbf{I}(f,t)\|_{2}}, \tag{6}\]  
where \(\|\|_{2}\) represents the l2-norm.  
Since the generalized cross-correlation with phase transform (GCC-PHAT) extracted from the microphone array is the most basic feature in the time difference of arrival (TDOA) problem, many participants used it a lot in previous challenges. However, this feature is noisy when multiple sound sources overlap or a moving source occurs. Since the TNSSE 2021 dataset contains the events moving at an angular speed of 40 degrees per second in addition to overlapped sound sources, DOAE may not be reliable using the GCC-PHAT. To effectively solve SELD in the multi-source scenario with interference, only the IV without the GCC-PHAT is used for DOAE in this paper.
## 5 Conclusions  
While the advanced technologies in GNSS, including ongoing modernization with new signals, have been introduced into positioning applications, there are no guidelines and specifications for GNSS-derived heights from real-time solutions. Two phases of GNSS RT solutions were intensively analyzed in this study to investigate the possibility of applying network RT solutions for  
Figure 12: Ellipsoidal height errors plotted for all intervals.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Duration** & 5 s & 30 s & 60 s & 180 s & 300 s & 600 s \\ \hline
**Mean (cm)** & 0.27 & 0.23 & 0.28 & 0.25 & 0.18 & 0.09 \\ \hline
**Std. Dev. (cm)** & 1.19 & 1.15 & 1.13 & 1.01 & 0.94 & 0.87 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Statistics of the multiple-epoch solutions by duration.  
GNSS-derived heights. The RT solutions with four different types of antennas were collected for short baselines in Florida. The performance is generally comparable, but the RT solutions can be biased by up to 9 mm by the surrounding environment. The accuracy of RT solutions is generally dependent on the baseline lengths. However, there seems to be no clear relationship between the baseline lengths and the mRTN solutions in case of GPSBMs, and the built-in antenna is worse than others even for a favorable surrounding environment. For the RTN solution, there is no explicit bias for a baseline up to 30 km (both mRTN and sRTN), and the precision indicator by the receiver is generally overly optimistic, as already pointed out by [2]. The duration of occupations for RTN solutions of up to 600 s shows no obvious difference in the mean values, but the variance of the solutions is inversely proportional to the duration time due to the smoothing effect.  
Three different RT solutions of GPSBMs with various baseline lengths were investigated in order to analyze the characteristics of each method. The single-epoch network RTK (sRTN) solution is comparable to the multiple-epoch solutions, which should be investigated further in the future. Possible degradation of quality during transition between different duration times as well as changing the reference station should also be investigated. Since the individually-calibrated antenna phase center variation can deviate up to 1 cm in the up component [21], it may be necessary to consider calibrating the individual antenna for better positioning accuracy of height.  
This research was supported by the National Geodetic Survey (NGS) grant GRT00033679/60042989. The authors would also like to express their gratitude to NGS and Gustin, Cothern, and Tucker, Inc. for providing RTK/RTN test data collected in Florida and South Carolina.
## 5 Discussion
### Interpretation of Earthquake-Induced Anomalies
#### 5.3.2 Trace Element Signatures of Earthquake Anomalies
Simultaneously, Cr and V concentrations rose as the pH approached the zero-point charge of Fe/Mn oxides (pH 6-7), promoting the desorption of CrO4\({}^{2-}\) and VO4\({}^{3-}\). Mild acidity also reduced Sb(OH)\({}_{3}\) adsorption, enhancing Sb mobility. Oxygen penetration facilitated pyrite (FeS\({}_{2}\)) oxidation, generating SO4\({}^{2-}\) and H\({}^{+}\), and mobilizing MoO4\({}^{2-}\) and Sb(OH)\({}_{6}\)\({}^{-}\). Elevated SO4\({}^{2-}\) concentrations suppressed molybdate re-adsorption, sustaining Mo enrichment. By day 34 post-Wushi \(M_{5}7.1\) earthquake, concentration of all trace elements except Be returned to baseline. The persistent Be enrichment suggests incomplete sealing of shallow fracture closure. The contrasting post-seismic behaviors of trace elements--namely, the depletion of Li, B, and Rb, and the enrichment of Be and Sr--can be attributed to differences in their geochemical mobility, mineral-hosting environments, and response to fracture evolution. Highly mobile elements such as Li\({}^{+}\) and B(OH)\({}_{3}\) are more susceptible to dilution following deep fluid shutoff, while Be\({}^{2+}\) and Sr\({}^{2+}\) are likely sourced from mechanically activated shallow fractures and readily released through acid-driven mineral dissolution [17]. In addition, element-specific adsorption and desorption dynamics under shifting pH and redox conditions further contribute to these variations. These results highlight the importance of disequilibrium fluid-rock interactions and fracture-controlled fluid transport in shaping hydrochemical responses to seismic events. Trace element anomalies, exhibiting a \"concentration-time coupling\" pattern, delineate the full rupture cycle from pre-slip to post-earthquake adjustment. Integrating trace element and major ion anomalies offers a critical geochemical perspective on deep-shallow fault interactions, aiding in earthquake preparation and foreshock identification.
## 3 Metabolomics Applied to Marine Organisms in Cancer Studies
### Metabolite Changes in Treated Cancer Cell Lines  
As mentioned above, a few studies report analyses of metabolite changes after treatment of cancer cells with extracts/molecules isolated from sponges or algae. An interesting method to study cytotoxic activity is to provide a metabolic profiling of the treated cells to understand at which level the compound is interacting. This was the aim of the research conducted by [PERSON] et al. (2019). The studied sponge was _Geodia cydonium_ and it was tested on three breast cancer cell lines, MCF7, MDA-MB-231 and MDA-MB-468. An organic extract of this sponge had a cytotoxic effect with IC\({}_{50}\) of 37, 44 and 70 ug/mL, respectively, on three cancer cell lines analysed, whereas it was inactive on normal breast cells (MCF-10A). After the treatment, the metabolomic profile was studied through \({}^{1}\)H-NMR spectra. Interestingly, the active fraction was able to interfere with the glycolysis, lipid and amino acid metabolism of the tumor cells, enabling them to support their bioenergetic and macromolecular synthesis. In particular, the proton resonances related to the metabolites identified in three breast cancer cells were studied. The spectral region from 0.5 to 3 ppm showed the presence of signals from alanine, arginine, aspartate, glutamate, glutamine, isoleucine, lactate, leucine, lipids, lysine, proline, threonine and valine. The spectral region from 3 to 5.5 ppm was mainly composed of signals corresponding to choline, -glucose, -glucose, glycine, glycero-phosphcholine and phosphocholine. The 5.5-8.5 ppm region contained the resonances of histidine, phenylalanine and tyrosine. They also showed an increasing level of lactate after treatment in all three cell lines, and a decrease of \(\alpha\)-glucose, \(\beta\)-glucose, choline, glycerophosphocholine, glutamine, glutamate and lipids. Other metabolites were also reduced: proline in MCF-7 cells, threonine in MDA-MB231 and asparagine and lysine in MDA-MB468 cells, whereas glycine was reduced in both MDA-MB231 and MDA-MB468 cells. A decrease of pro-inflammatory cytokines (VEGF, CXCL10 and IL-8) levels was detected, as well, along with an increase of anti-inflammatory cytokines levels (IL-4 and IL-10). Finally, the chemical entities present in this fraction were analyzed by liquid chromatography high-resolution mass spectrometry combined with molecular networking. An additional interesting approach to the brown macroalga _F. vesiculosus_ was performed by [PERSON] et al. (2013), who investigated seasonal variations in the metabolome of this inhabitant of the Baltic Sea and its potential relation to the bioactivity profile. The authors developed an optimised protocol in order to extract algal biomass monthly for a full year, employing UHPLC-MS for untargeted metabolome analysis. Simultaneously,
## 6 Properties of the Matching Algorithm  
In this section, the properties of the three-dimensional and the two-dimensional matching algorithm, including convergence, stability, optimality, and complexity, are analyzed in detail.  
The analyses of the convergence, stability and optimality of the three-dimensional matching algorithm are given as follows:  
**Theorem 1**.: _The matching process would end with finite iterations._  
**Theorem 2**.: _The proposed Algorithm 2 can converge to a two-sided stable matching \(\tilde{\mathcal{X}}\) in finite iterations._  
**Theorem 3**.: _The solution of three-dimensional matching \(\tilde{\mathcal{X}}\) is weak Pareto optimal for D2D TRs on combinations of RSs and RBs._  
The proof of Theorems 1-3 can be found in Appendices B-D, respectively.  
The analysis of the optimality of two-dimensional matching algorithm is given as follows:  
**Theorem 4**.: _For any set of prices when the matching process ends, the result of the matching process has the maximum total utility of all of the possible assignments of RBs to D2D TRs._  
The proof of Theorem 4 can be found in Appendix E. The proofs of the convergence and stability of two-dimensional matching are similar to Theorems 1 and 2, respectively, which can also be referred to Appendices B and C. Next, we discuss the complexity of the proposed algorithm.  
For the three-dimensional matching algorithm, because each D2D TR would firstly calculate the achieved EE for each RC unit, in the process of preference establishment, the computational complexity for any TR \(i\in M\) to obtain the preferences is \(\mathcal{O}(RC)\). The preference list can be derived by sorting the preference values for each TR, and the computational complexity is \(\mathcal{O}(RC\log(RC))\). In Algorithm 2, the complexity of each price raising process, in which TRs that remain single propose their most preferred RC units, is \(\tilde{M}^{loop}\). \(\tilde{M}^{loop}\) is the required number of iterations by the price rising process to resolve the conflict, i.e., during \(\tilde{M}^{loop}\) iterations, the conflicting elements assignment are finished when \(\Omega\
eq\emptyset\). We have \(\tilde{M}^{loop}=1\) when \(\Omega=\emptyset\). Then, the computational complexity of the matching process is \(\mathcal{O}(M\tilde{M}^{loop})(M\geq C)\) or \(\mathcal{O}(C\tilde{M}^{loop})(C\geq M)\).  
For the two-dimensional matching algorithm, since each D2D TR would calculate the interference for each RB and for any TR \(i\in M\), the computational complexity to obtain the preference is \(\mathcal{O}(C)\). The complexity of each price rising process, in which TRs that remain single propose their most preferred RBs, is \(\tilde{M}^{loop}\). \(\tilde{M}^{loop}\) is the required number of iterations by the price rising process to resolve the conflict. Then, the computational complexity of the matching process is \(\mathcal{O}(M\tilde{M}^{loop})(M\geq C)\) or \(\mathcal{O}(C\tilde{M}^{loop})(C\geq M)\).
## 4 Analytical Analysis of the Transverse Cracks in BFRP-CRCP
### Analytical Results  
Table 3 presents the input parameters of the concrete and the BFRP for obtaining the analytical predictions. All the geometric parameters of the concrete and BFRP--i.e., the thickness of the concrete, the BFRP diameter, the reinforcement ratio of BFRP, and the spacing of BFRP--were the same as those specified in the aforementioned CRCP test section with BFRP bars. The concrete material properties were from the results of the lab tests. The coefficient of the bond stiffness of the BFRP and the concrete was calculated through pull-out test results of the concrete and BFRP bars, while the friction coefficient between the concrete and the base layer and the linear expansion coefficient of the BFRP reinforcement were estimated based on a previous study [18]. \(\Delta T\) was the temperature drop from the temperature during concrete casting to the coldest temperature in the year 2014 in the test section area.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Parameters** & **Concrete** & **BFRP** \\ \hline Elastic Modulus (GPa) & 30 & 40 \\ Tensile Strength (MPa) & 3.20 & 750 \\ Compressive Strength (MPa) & 40 & - \\ Concrete Shrinkage & 0.0002 & - \\ Coefficient of Linear Expansion (\(10^{-6}\)/\({}^{\circ}\)C) & 10 & 9 \\ Thickness of CRCP (cm) & 26 & - \\ Reinforcement content (\%) & & 0.50 \\ \(\Delta T\) (\({}^{\circ}\)C) & 30 & - \\ Coefficient of Friction (MPa/m) & 40 & - \\ Coefficient of Bond Stiffness (GPa/m) & - & 30 \\ BFRP Diameter (mm) & - & 12 \\ BFRP Spacing (cm) & - & 8 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Input parameters for the BFRP-CRCP test section for the analytical model.  
Based on the inputs in Table 3, the analytical predictions for the crack spacing and crack width in CRCP with BFRP bars were calculated to be 4.47 m and 1.78 mm, respectively, as described in Figure 6. The greater crack spacing and width for the BFRP is mainly due to the lower elastic modulus of BFRP, which is 40 GPa as compared to the steel (210 GPa). In order to achieve a lower crack spacing and crack width in CRCP with BFRP reinforcement, one possible way is to increase the reinforcement ratio of the BFRP bar.
# A Critical Review of SCWG in the Context of Available Gasification Technologies for Plastic Waste
## 2 Gasification Process
### The Role of Gasifying Agent  
Depending on the gasifying agent different processes can be distinguished [44]: Air gasification [60], oxygen gasification [61], steam gasification [62], carbon dioxide gasification [63], supercritical water gasification [64], etc. Generally, oxygen gasification, steam gasification, carbon dioxide gasification, and supercritical water gasification result in higher heating values (HHVs) of syngas than air gasification, but the latter technique is the most studied and used experimentally, as it has some advantages: Air is an inexpensive gasifying agent, the structure of the reactor is simple, and the reaction process is easy [44]. A further advantage in the use of air as a gasifying agent is linked to a lower tar content in the gaseous product compared to steam gasification. Moreover, in gasification with air (or oxygen) there are no external energy requirements, while in the other kind of gasification external heating is required because the overall gasification reaction is generally endothermic. The use of air leads to a syngas with a low heating value due to dilution with N\({}_{2}\)[43; 65]. Air gasification of plastic waste is commonly performed in fluidized bed reactors [20]. In regards to other gasifying agents, the addition of steam has been reported as a strategy to manipulate the H\({}_{2}\)/CO ratio from dry reforming of simulated mixed waste plastics [66]. The syngas obtained from steam gasification, being rich in H\({}_{2}\), can be used for chemical synthesis applications [67] and may allow matching the specific H\({}_{2}\)/CO ratio requested by the end-use process [68; 69]. The disadvantage in the use of this gasifying agent is related to the need to supply heat from the outside. An alternative to air or steam is pure oxygen. This gasifying agent allows obtaining a hydrogen-rich syngas, but its use is too complex and expensive for small- and medium-scale plants. Gasification with supercritical water (SCWG) is currently receiving considerable interest. This promising technique will be explored in detail in the next chapter.