esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Materials and Methods
### GC\(\times\)GC-Q-TOF MS Analysis  
All samples were analyzed by GC\(\times\)GC-TOFMS (comprehensive two-dimensional gas chromatography quadrupole time-of-flight mass spectrometry), which was equipped with an Agilent 8890 GC/7250 gas chromatography tandem quadrupole time-of-flight mass spectrometer (Agilent, Santa Clara, CA, USA), a headspace solid-phase microextraction automatic sampler (GERSTEL, Mulheim an der Ruhr, Germany), and a solid-state thermal modulator (J&X Technologies, Shanghai, China). Amounts of 5 mL of wine sample, 1 g of NaCl, and 10 \(\mu\)L of 4-methyl-2-pentanol (324.4 \(\mu\)g/L, internal standard) were placed in a 20 mL headspace vial, immediately sealed with a screw cap, and placed in an automatic sampler tray. The solid-phase microextraction needle fiber was made of divinylbenzene/carbon molecular sieve/polydimethylsiloxane (DVB/C-WR/PDMS; fiber thickness: 50/30 \(\mu\)m; Thermo Fisher Scientific, Carlsbad, CA, USA). SPME fibers were extracted at 45 \({}^{\circ}\)C at 250 rpm for 30 min and then quickly inserted into the syringe port at 250 \({}^{\circ}\)C for thermal desorption (3 min).  
GC\(\times\)GC consisted of a DB-WAX column (30 m \(\times\) 0.25 mm \(\times\) 0.25 \(\mu\)m, Agilent, Santa Clara, CA, USA) and a DB-17 MS column (1.85 m \(\times\) 0.180 mm \(\times\) 0.18 \(\mu\)m, Agilent, Santa Clara, CA, USA). The initial temperature of the column box was 50 \({}^{\circ}\)C, which was increased to 230 \({}^{\circ}\)C at a rate of 3 \({}^{\circ}\)C/min and maintained for 2 min. Splitless injection was carried out. The carrier gas was helium (99.999%), and the constant flow rate was 1 mL/min. The ion source temperature was maintained at 230 \({}^{\circ}\)C, and the EI ionization energy was 70 eV. The mass scan range was set to 45-500 m/z at full scan mode, the mass spectrometry sampling rate was 50 times/s, and the solvent delay was 2 min. For the heating and cooling stages, the solid-state modulator used the SV modulation column (C\({}_{6}\)-C\({}_{40}\)), the modulation period was 4 s, and the cold zone temperature was maintained at \(-\)50 \({}^{\circ}\)C.
## 3 Results and Discussion
### Isothermal Analysis  
#### 3.3.1 Freundlich Isotherm  
The obtained results were fit with the experimental data of the Freundlich isotherm model, which were confirmed by a high correlation coefficient of R\({}^{2}\) = 0.989 for the MWCNTs, indicating that this model is favorable for the adsorption process (Figure 11). A strong bond occurred between the IV2R dye and the adsorbents, as indicated by the value of 1/n, which is called the heterogeneity factor, describing the deviation from the linearity of sorption as follows: When 1/n is equivalent to 1, the adsorption is linear, and the ammonia particle concentration does not influence the division between the two stages. When 1/n is below 1, chemical adsorption occurs; however, when 1/n is more than 1, cooperative adsorption occurs, and this adsorption is more favorable physically and includes strong interactions among the particles of the adsorbate [6]. In this work, the value of factor \"1/n\" was less than 1; the data shows chemical sorption method on a surface with this isotherm equation being favorable.
## 3 Results and Discussion
### Assessment of the Experimental Results
#### 3.1.2 Second Data Collection Period  
The second data collection campaign was implemented during a whole week, as explained in Section 2.1.2.; however, Figures 7-9 show the hygthermal variables measured during a 24-h period starting at 7:00 h on Saturday 14 th September 2019, when the air renovations consisted of 100% unconditioned fresh air. Normal surgical activity was studied in detail in [21] and has not suffered relevant changes since then. These new collected data were recorded to validate the new simulation and calibrated model, both during occupied and unoccupied periods.  
The boundary conditions are different for each OR. These enclosure characteristics have important influences in the evolution of the indoor temperature and RH inside the room when using a floating thermal model equipped with a ventilation system. In these models, the indoor conditions are not controlled with a HVAC system. For this reason, although the ventilation airflows and the ACH are similar in the three ORs, the temperatures of each OR are different, especially during the night period. During such periods, the temperature of the intake air in OR1 is similar to the room temperature. However, in OR2 and OR3, the temperature of the intake air is slightly lower than the room temperatures because of the thermal gains from the boundary thermal zones. This behavior is also observed in the moisture model because when the intake air goes into the zone, this air is tempered and the RH is reduced.
# Hydrogen Production in Methane Decomposition Reactor Using Solar Thermal Energy
## 4 Development of Methane Decomposition Reactor  
### Direct Heating Reactor  
The initial reactor was a direct heating-type reactor, which used a quartz window, as shown in Figure 5. It also had a similar structure as the reactor used in the experiment where water splitting was previously performed using a catalyst coated with CeO\({}_{2}\)[28]. To ensure that the inside of the reactor was uniformly heated, and the residence time was ensured, the conical silicon carbide (SIC) structure was placed inside the reactor to monitor the distribution of heat quantity based on the focal length. To measure the internal temperature, three thermocouples were mounted through the structure at uniform intervals along the axis of the reactor. The quartz was located between the reactor front flanges, and the part in contact with the flange used graphite sealing with high temperature durability  
Figure 4: Schematic diagram of the experimental facility.  
to maintain airtightness. To reduce the thermal damage of the quartz window caused by high temperatures, a water flow path was created inside the flange to cool it. Methane was injected into four inlet ports installed inside the reactor between the quartz and the catalyst, and passed through the high temperature SIC catalyst. On completion of the reaction, the end product was discharged through the outlet.  
To determine the performance of the reactor, a preliminary experiment was performed after installing the reactor in the solar furnace, as shown in Figure 6. In the process of increasing the temperature, nitrogen was supplied, and 5 L/min of methane was supplied when the temperature of the structure reached 1000 \({}^{\circ}\)C. The decomposition of methane produced hydrogen and carbon, and some of the carbon in the product was deposited on quartz. As a result, the transmittance of the quartz decreased, and the concentrated light was locally absorbed, causing an increase in the temperature of the quartz, which subsequently resulted in a crack, as shown in Figure 7.  
Figure 5: Direct heating reactor model.  
Figure 6: Direct heating reactor with quartz window.  
One of the causes of this phenomenon is that the position of the methane injector, which is adjacent to the quartz, causes the carbon to become easily attached to the quartz. Accordingly, the inside of the reactor was modified to further increase the distance between the catalyst and the inlet port; however, the problem persisted. This was because some of the carbon produced did not exit smoothly through the outlet, and was accumulated inside the reactor, obstructing the flow from the inlet to the outlet. Another problem was that, as the gas supply flow increased, a gas leak occurred in the flange of the reactor, and it was difficult to prevent the leak owing to the weak stiffness of the quartz window.
## Materials and Methods
### Primer Design and mRNA Quantification by Real-time qRT-PCR  
Several virulence genes of _Pectobacterium_ have been identified and well characterized. The most recognized are genes related to plant cell wall-degrading enzymes (PCWDEs), quorum-sensing and the type III secretion system. Accordingly, we examined the expression levels of _pel_ and _peh_ (representative PCWDE genes), _expl_ and _expR_ (QS system genes), _hrpL_ (representative of T3 SS) and _araF_ (a representative membrane-transporter gene). The primer specificity for the aforementioned gene has already been validated previously by [PERSON] et al. [28], the same primers were used in this study. Similarly, the expression levels of defense-related genes (lipoxygenase _lox2_, pathogenesis-related gene _PR-1_, phenylalanine ammonia lyase _pal_ and aspartate aminotransferase _ast_) in calls illy and cabbage were evaluated. Primers for these genes in calls illy were designed using Primer 3.0 ([[http://bioinfo.ut.ee/primer3-0.4.0/](http://bioinfo.ut.ee/primer3-0.4.0/)]([http://bioinfo.ut.ee/primer3-0.4.0/](http://bioinfo.ut.ee/primer3-0.4.0/))) software as explained [28] and detailed in Table 1. Gene sequences of calls illy is not available in the database, therefore cDNA sequences of defense related genes were sequenced by our lab and deposited at figshare.com (DOI 10.6084/m9.figshare.12326495). Sequences of the same genes for cabbage were obtained from the Joint Genome Institute (JGI) database ([https://phytozome.jgi.doe.gov/pz/portal.html](https://phytozome.jgi.doe.gov/pz/portal.html)) and primers were designed as explained above and detailed in Table 1. The specificity and quality of the primers were tested using serial dilution of cDNA mix from all treatments and data were translated into standard curve. Specifically, all primers were tested for their specificity (single product amplification, observed as single melting curve), efficiency (90-105% observed) and correlation coefficient R\({}^{2}\) (>0.98 observed). Primers, that passed quality check, were used for qRT-PCR reactions using the Step One Plus Real-Time PCR system (Applied Biosystems Inc. Foster City, CA, USA), with reaction details mentioned as in [PERSON] et al. (2018). Finally, data were analyzed by the comparative C\({}_{t}\) (\(\Delta\Delta\)C\({}_{t}\)) method, relative to control (bacteria cultured in sterile water), with expression normalized to the expression of the reference gene _recA_ for bacteria, actin for calls lily, and tubulin for cabbage. The reference genes were selected based on their expression consistency under all conditions.
## 3 Results and Discussion
### Physicochemical Properties of the Samples
#### 3.2.4 SEM Analysis  
Figure 6 shows the SEM images of virgin ZSM-5 and Co\({}_{4}\)Fe\({}_{1}\)-ZSM-5. As can be seen from Figure 6a,b, the surface of ZSM-5 showed smoothness. Differently, there were some tiny particles emerging on the surface of ZSM-5 for Co\({}_{4}\)Fe\({}_{1}\)-ZSM-5, suggesting the successful introduction of active species. Meanwhile, there were no significant variations detected in the structure of the modified samples, suggesting that morphology is not the main reason for the variations in the Hg\({}^{0}\) removal efficiency of the serial adsorbents.  
EDX was used to characterize the distributions of Fe and Co species over ZSM-5. As shown in Figure 7b, Co\({}_{3}\)O\({}_{4}\) with bright contrast was dispersed over the entire surface of ZSM-5. The corresponding elemental maps of ferric also imply that Fe\({}_{2}\)O\({}_{3}\) was well distributed throughout the ZSM-5. EDX analysis (Figure 7d) displays that the Fe/Co mass ratio of Co\({}_{4}\)Fe\({}_{1}\)-ZSM-5 was 3.9, which matched the ICP result well (Table S2).  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Samples** & **Surface Area/(m\({}^{2}\)/g)** & \begin{tabular}{c} **Micropore Surface** \\ **Area/(m\({}^{2}\)/g)** \\ \end{tabular} & \
\begin{tabular}{c} **External Surface** \\ **Area/(m\({}^{2}\)/g)** \\ \end{tabular} &
\begin{tabular}{c} **Total Pore** \\ **Volume/(cm\({}^{3}\)/g)** \\ \end{tabular} \\ \hline ZSM-5 & 356 & 289 & 67 & 0.18 \\ \hline Co-ZSM-5 & 336 & 260 & 76 & 0.16 \\ \hline Fe-ZSM-5 & 343 & 269 & 74 & 0.19 \\ \hline Co\({}_{4}\)Fe\({}_{1}\)-ZSM-5 & 351 & 264 & 87 & 0.18 \\ \hline \hline \end{tabular}
\end{table}
Table 1: N\({}_{2}\) adsorption results of a series samples.  
Figure 5: (a) N\({}_{2}\) adsorption–desorption isotherms and (b) pore distributions of a series samples.
## 3 Chemical Modification of Hyaluronan
### Oxidation of Hyaluronan
HA (unknown Mw) was modified by amidation mediated by EDC/HOBT with (\(\pm\))-3-amino-1,2-propanediol followed by oxidation with NaIO\({}_{4}\). The hydrogels exhibited a short gelation time (3 s). This time was controlled by the concentration of HA in the formulation. Strong shear-thinning and self-healing properties were observed due to the dynamic covalent bonding of the Schiff base bond. The hydrogel degraded in the mice's peritoneum after a week of implantation and showed excellent biocompatibility and adhesive properties. The hydrogels decreased bleeding to as low as fibrin glue without using thrombin and fibrinogen in a mouse liver bleeding model in both single- and double-barreled syringe administrations [128]. However, the use of gelatin could produce immune reactions. [PERSON] and colleagues prepared a hydrogel composed of methacylated gelatin (Gel-MA) and oxidized LMW-HA (HA-di-CHO). For the preparation, native HA (1.0-2.0 \(\times\) 10\({}^{4}\) g/mol) was oxidized by means of NaIO\({}_{4}\). The prepared hydrogels were used as delivery systems of the antibiotic gentamicin sulfate (GS) and lysozyme (LZM). The amino moieties of GS were reacted with dialdehydes presented on HA by the formation of Schiff base bonds to impart antibacterial properties. A composite hydrogel prepared by methacylated gelatin and oxidized HA was prepared by photo-crosslinking mediated by LAP. The synergy between GS/LZM imparts higher antibacterial properties against _S. aureus_ and _E. coli_. The hydrogel triggered the adhesion of platelets and gave a fast-hemostatic effect, with a hemolysis rate lower than 1%. These observed properties made the material as promising for wound healing [131]. Though, the mechanical properties of this material were not reported. Some other groups have tested the anti-inflammatory efficacy of polysaccharides such as salecan (Sal) [132]. In this idea, [PERSON] et al. prepared a self-healing injectable hydrogel via thermal treatment and dynamic Schiff base reaction using oxidized HA and hydrazide-modified selecan (Sal-ADH). The antimicrobial drug poly (hexamethylene) biguanide (PHMB) was encapsulated in the hydrogel. The oxidation of MMW-HA (2.0-4.0 \(\times\) 10\({}^{5}\) g/mol) was performed by NaIO\({}_{4}\). This polysaccharide was condensed with chemically modified high molecular weight Sal (2.0 \(\times\) 10\({}^{6}\) g/mol). In the case of HA, its Mw decreased to 9.1 \(\times\) 10\({}^{4}\) g/mol and dispersity (D) of 1.315. The hydrogel was non-cytotoxic and was hemocompatible. PHMB imparted antimicrobial properties against _E. coli_ and _S. aureus_. Wound contraction was determined in mice after 14 days with extended collagen formation at the wound site [133].
## 3 Experiment and Results Discussion
### Effect of the Influence of Environmental Factors on UV-Vis Spectroscopy
#### 3.1.2 Effect of the Influence of Temperature on UV-Vis Spectroscopy
Figure 8: The influence of \(NO_{3}^{-}\) on the UV-Vis spectra of real water samples. (**a**) The influence of \(NO_{3}^{-}\) on the spectra of real water samples. (**b**) The change in absorbance at different wavelengths with the \(NO_{3}^{-}\) of real water samples. The analysis of real water samples, as shown in Figure 8a, reveals that nitrate (\(NO_{3}^{-}\)) exhibits a distinct absorption peak at around 280 nm, which overlaps with one of the absorption peaks of the COD standard solution. There is minimal absorption at the first absorption peak of the COD at 236.09 nm. The absorbance at 280 nm increases by approximately 0.17 as the \(NO_{3}^{-}\) concentration increases from 1 to 19 mg/L. Furthermore, the absorbance generally increases with the rise in \(NO_{3}^{-}\) concentration (except for 236.09 nm), displaying a strong linear relationship, as shown in Figure 8b. However, the linearity of the absorbance at different wavelengths is inconsistent. Thus, \(NO_{3}^{-}\) significantly influences the UV-Vis spectroscopy, requiring the use of compensation methods to reduce this influence in COD detection based on UV-Vis spectroscopy. From the analysis above, it is evident that conductivity has a significant and complex influence on the UV-Vis spectroscopy of real water samples, with considerable variations across different wavelengths. This complexity makes it challenging to accurately model the relationship between absorbance and conductivity through a simple curve or model. Consequently, the detection of COD based on UV-Vis spectroscopy can result in substantial errors when there are large fluctuations in the sample's conductivity. In the case of common surface waters, such as domestic sewage, rivers, and lakes, conductivity can vary widely with seasonal and environmental changes. Therefore, to enhance the accuracy of COD detection using UV-Vis spectroscopy, it is essential to compensate for the influence of conductivity.
## 3 System Architecture, Software Services and Deployment  
The main entities of the fog computing-based smart water metering system presented in this paper are: (i) the smart meters deployed throughout the water distribution network that provide continuous monitoring of the water consumption and pressure; (ii) the smart water valves installed near the water meters that offer the ability to control the flow of water remotely; (iii) the edge computing infrastructure that interconnects wireless networks of smart devices with the core network, bundled with a fully customized edge processing and analytics framework for collecting and analysing the data produced; (iv) the cloud services that facilitate identity management, telemetry, asynchronous notifications and historic data storage, as well as the dedicated interfaces that will be utilized by both users and external services for getting access to the platform logs and data (e.g., for billing, etc.).
## 4 Experiments
### Quantitative Results  
**LIP.** We compare the performance of our network with other state-of-the-art methods on the LIP dataset. As shown in Table 1, the proposed method yields the result of 54.5% in terms of mIoU. Compared with the CE2P method, our method exceeds by 1.1%, 2.89% and 0.29% in terms of mIoU, Mean Acc. and Pixel Acc., respectively. In order to verify the detailed effectiveness of our structure, we further present the per-class IoU in Table 2. While comparing with the current state-of-the-art method CE2P, the DFE module significantly improves the performance of the small classes such as the scarf, glove and hat, which demonstrates its ability to capture low-level features. Our proposed approach achieves a large gain especially for some confusing categories such as upper-clothes, coats, dresses and skirts. From the viewpoint of the IoU of the dress and skirt, our method yields obviously an improvement approximately 5% and 6% better than CE2P. These improvements imply that the GTM module generates more global information via self-attention. Moreover, edge detection in our network utilizes edge features to assist human parsing. The left and right arms have a similar appearance; edge detection can identify them clearly. These superior performance experimental results further show that our method is capable of enforcing feature information globally and locally.  
**Fashion Clothing Dataset.** Table 3 reports the results and comparisons with three recent approaches on the Fashion Clothing dataset. Our method outperforms the DeepLab by 19.05% and 17.01%, in terms of average recall and average precision scores, respectively. Compared with the Attention method, our method significantly improves the pixel accuracy, foreground accuracy, average accuracy, average recall and average F-1 score and achieves 92%, 66.16%, 54.4%, 56.01% and 55.19%, respectively. This performance suggests the superiority of our parsing method with the assistance of detailed feature and edge factors, which can introduce contextual cues into the human parsing task.  
**ATR.** The evaluation results for the test set of the ATR dataset are given in Table 4. The proposed method has a significant performance improvement in most of the metrics. It is 3.23% and 0.45% higher than Co-CNN in terms of average recall and average precision. It confirms the effectiveness of the Transformer self-attention mechanism for human parsing and illustrates that the GTM module has a strong capability to incorporate global and local information.
## 5 Application and Discussion  
By comparing the proposed YOLOv10-vit network and YOLOv10-vit-cls network with several baseline versions on the corrosion detection dataset and corrosion level classification dataset, it was found that both models perform well. Therefore, the cascading architecture idea presented in this paper, utilizing YOLOv10-vit and YOLOv10-vit-cls networks, has been implemented and further validated by collecting real-world corrosion images of hydraulic metal structures.  
The real-world detection results are shown in Figure 10. Through the cascading architecture, successful detection of both corrosion localization and level classification was achieved. The four corrosion levels, A, B, C, and D are represented by blue, green, yellow, and red colors, respectively, with the corresponding corrosion level names annotated inside the detection boxes.  
For corrosion localization in complex scenes, there are still some missed detections and repeated detections. For example, in Figure 10a, the screw corrosion on the right side is not detected by the YOLOv10-vit network. Additionally, in the middle part of Figure 10a, the Level A corrosion patch is repeatedly detected multiple times by the YOLOv10-vit network.  
For some small but severely corroded areas, there are cases where other corrosion levels are misclassified as Level A. For example, the screw corrosion in Figure 10a is clearly not Level A. The blue box in Figure 10c also represents a misclassification; the overall corrosion condition should be Level C. Similarly, in Figure 10e, the corrosion level in the far-right detection box is also misclassified.  
For Figure 10b,d,f,g, the corrosion detection and corrosion level determination results are generally ideal.
# L2-CalSat: A Calibration Satellite for Ultra-Sensitive CMB Polarization Space Missions
## 4 L2-CalSat Description
### Requirements  
Focusing on small aperture CMB missions, the following general requirements have been established, based on formation flight of existing missions, previous experience, and thermal considerations (see Section 4.4):  
1. L2-CalSat shall be around L2 using a Lissajous orbit and maintain that orbit during 3 years.
2. L2-CalSat shall maintain a minimum-security distance of 4620 m from the main satellite and a distance of about 6600 m \(\pm\) 66 m during, at least, 6 h for each calibration session.
3. The maximum time to move away L2-CalSat from the main satellite FoV shall be less than 20 h.  
On the other hand, in order to achieve the required polar angle and beam characterization accuracy (see Sections 3.1 and 3.3), the following technological requirements related to the AOCS, Electrical Power System (EPS), payload, propulsion and structure, have also been considered:  
1. The sensors shall locate the direction of the main satellite with an error lower than 10 arcmin and shall know L2-CalSat orientation with an error lower than 1 arcmin.
2. L2-CalSat shall point to the telescope with an error less than 3 arcmin.
3. EPS shall fulfil every power subsystem requirement and provide enough energy to the payload to allow, at least, 2 calibrations per year. It has been considered a maximum power consumption of 50 W during calibration.
4. During calibration, the sensors shall be able to calculate the distance between both satellites with an accuracy of 3.3 m.
5. The propulsion system shall be able to provide enough thrust to fulfil the calibration requirements while providing a displacement error of less than 3.3 m.
6. L2-CalSat dimensions shall fit in a 6U CubeSat.
7. L2-CalSat must have minimum impact on the main CMB satellite.