esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract  
This study investigates the synthesis and evaluation of ZnO/g-C\({}_{3}\)N\({}_{4}\) composites as efficient green catalysts for advanced oxidation processes (AOPs) targeting the treatment of contaminated water. The composites were synthesized using a ternary deep eutectic solvent and physically-chemically characterized in detail, confirming their structural integrity and successful synthesis. Photocatalytic, photo-Fenton- and electro-Fenton-like experiments were conducted using Rhodamine B as a model contaminant to evaluate the catalytic performance, reuse and stability of the synthesized material. The synthesized ZnO/g-C\({}_{3}\)N\({}_{4}\) composites demonstrated excellent photocatalytic activity under LED light (395 nm), achieving a pollutant removal of around 59% in 90 min. The combined effect of the designed catalyst and Fenton-like process, a photo-Fenton-like process, significantly improved this performance, achieving removal of close to 95% in 60 min due to the synergistic effects of the irradiation and H\({}_{2}\)O\({}_{2}\) activation. Finally, the catalytic action of synthesized ZnO/g-C\({}_{3}\)N\({}_{4}\) composites in the electro-Fenton-like process exhibited superior efficiency, achieving 90% removal within 45 min and kinetic constants four times higher than those of anodic oxidation alone. In addition, reuse studies confirmed the stability and catalytic activity of the composites for several cycles with high removal efficiencies, demonstrating their viability for long-term and scalable water treatment applications. These findings highlight the potential of ZnO/g-C\({}_{3}\)N\({}_{4}\) composites synthesized through DES as a sustainable and cost-effective alternative for water remediation technologies.  
ZnO/g-C\({}_{3}\)N\({}_{4}\) composites; deep eutectic solvent; photocatalytic; photo-Fenton like; electro-Fenton like +
Footnote †: journal: Applied sciences
# A Strategy-Driven Semantic Framework for Precision Decision Support in Targeted Medical Fields
## 5 The Emergency Strategy Case Study: Needs Analysis and Formalization
### Formalizing the Emergency Strategy
#### 5.3.3 The Refined Framework Algorithms  
We describe the additional algorithms developed in our framework to support the emergency strategy.  
Algorithm 1 builds the personalized subgraph from KG by adding the patient's personal information (the indicators). Algorithm 2 incorporates the patient's symptoms into the personalized sub-graph and uses inference to generate a ranked list of potential diseases. This list is then used as input for Algorithm 3, which identifies the most probable community and a relevant question, and for Algorithm 4 in [4; 5], which generates a set of hypotheses ranked by their urgency. Recall that each hypothesis is a pair consisting of a disease and a symptom indicating it.  
```
Input: knowledge graph \(KG=(D\bigcup S,E)\), PI, ES, R Output: personalized sub-graph PKG Algorithm: 0. Let PKG be KG. 1. For every \(s\in ES\): 1. For every \(r\in R\) that contains \(s\), that is \(r=\left\langle s,d,f_{s,d}\right\rangle\): 2. If \(f_{s,d}\) (PI)=true, add the edge \((s,d)\) to PKG. 2. Return PKG.
```  
**Algorithm 2** identify possible diseases  
```
Input: PKG, ES, C Output: possible diseases, sorted according to their risk Algorithm: 1. Let \(PD\ \longleftarrow\ \{\}\). 2. Let \(C^{\prime}\subseteq C\) be the set of communities having positive LinD. 3. Sort \(C^{\prime}\) in a non-decreasing order according to their Risk (primary) and then according to their LinD (secondary). 3.1. Let \(c\) be the community in the order: 3.1.1 Go over the diseases in \(c\).  First, go over the diseases \(d\) with risk?==true. Sort them according to their \(R^{d}\)(d) (in a decreasing order) and add them in that order into PD.  Then, add the rest of the diseases in \(c\), sorted (in a decreasing order) according to their \(R^{d}\)(d). 4. Return PD.
```  
\begin{table}
\begin{tabular}{p{142.3 pt} p{284.5 pt}} \hline
**Term** & **Definition** \\ \hline \(R^{s}\)(\(s\),\(c\)) & \(R^{c}\)(\(s\),\(c\)) \(-\)\(\left(\sum_{c\
eq c^{\prime}\in PD}R^{c}(s,c^{\prime})\right)\) \\  & Defined by the number of edges from symptom s to community \(c\) minus the number of edges from s to some other community \(c^{\prime}\) \\  & The outcome indicates how this symptom characterizes \(c\) \\ \hline \(Cs\) & Community symptom \\  & Defines a symptom indicating a high number of diseases in the community \(c\) and a low number out of \(c\); hence, given a community \(c\), it is the symptom s with the highest \(R^{s}\)(\(s\),\(c\)) \\ \hline \(SCM\) & symptom community matrix (\(SCM\)) represents the associations between groups of diseases and the various symptoms (see [4] for a formal definition) \\ \hline \end{tabular}
\end{table}
Table 1: _Cont._
## 8 Conclusions  
This article shows the robust control of a team of quadrotors for the transportation of a deformable linear object (DLO) following a mission path that featured sharp changes in direction, the influence of sudden strong disturbances and the ability to cope with height-changing spiral paths. The proposed system has a main contribution to the state-of-the-art methods: the hybrid modeling of the DLO sections. Hybrid modeling allows the system to cope with sudden changes in DLO section shapes. Future studies will address the realization of physical experiments to validate the simulation results in a controlled environment by providing the optical tracking of the drones and the shape of the DLO sections. Moreover, research on the design of a type-3 fuzzy logic could permitted the improvement of our control strategy to unknown and dynamic conditions. This type of fuzzy logic has already shown good performance and precision in control problems of renewable energies [70; 71]. Another line of future research is the complete modeling of the DLO during the entire flight, including take off and landing when the DLO suffers strong nonlinear effects.  
Conceptualization, J.E. and M.G.; methodology, J.M.L.-G. and M.G.; software, J.E. and G.G.; validation, J.E. and J.M.L.-G.; writing--original draft preparation, J.E.; writing--review and editing, All; funding acquisition, M.G. All authors have read and agreed to the published version of the manuscript.  
This work has been partially supported by spanish MICIN project PID2020-116346 GB-100, and project KK-2021/00070 of the Elkartek 2021 funding program of the Basque Government. This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 777720.  
Figure 18: Euclidean distance along time between drones in Experiment 3.
# Unlocking Wellness: Probiotics as Key Drivers in Functional Food Innovation and Health Promotion
## 4 Application of Probiotics in Functional Foods
### Meat Products  
In developing new functional meat products, the primary application strategy for probiotics is their integration into fermented sausage production. The developed probiotic meat products are not only nutrient-rich and conducive to intestinal digestion and absorption but also possess a unique fermentation flavor and the distinct advantages of probiotics, allowing for extended storage. [PERSON] [119] used a compound starter of _L. acidophilus_ and _Staphylococcus xylosus_ in a 1:1 volume ratio, inoculating it into sausage at a concentration of \(10^{7}\) CFU/mL. The fermented sausage produced using this method has an excellent taste, is neither greasy nor sweet, has moderate saltiness, a slight wine aroma, and a bright red color. [PERSON] et al. [120] used _L. plantarum_, _P. pentosaceus_, and _Staphylococcus_ as fermentation agents to inoculate Sichuan sausage, effectively overcoming the issues of long fermentation times and susceptibility to contamination by other bacteria in traditional Sichuan sausage. The prepared sausage has an appropriate balance of sour and spicy flavors, successfully retaining the unique flavor characteristics of traditional Sichuan sausage. [PERSON] et al. [121] successfully inoculated sausage with three types of bacteria isolated from infant feces, substantially inhibiting the growth of harmful microbes and significantly increasing product safety. [PERSON] et al. [122] added the screened strains SJRP66 and SJRP169 of _L. casei_ to low-fat fermented sausage. The research indicates that the addition of probiotics affects the oxidation process of oil and the color value of the final product, demonstrating significant potential for application in low-fat fermented sausage. In the production of fermented sausage, its matrix structure effectively protects the survival and continuity of probiotics. However, this requires probiotics to have excellent tolerance to withstand adverse conditions such as high salinity and low pH during processing. [PERSON] et al. [123] selected _Debaryomyces Hansenii_ yeast as an aroma agent and inoculated it into a low-salt, low-fat sausage. This technology effectively increases the aromatic components in sausages, making their flavor similar to that of traditional sausages.
# Generating Low-Earth Orbit Satellite Attitude Maneuver Profiles Using Deep Neural Networks
## 2 Background
### LEO Satellite Attitude Guidance Profile Constraints  
The maximum allowable values for the angular acceleration and angular rate should be used to maximize the attitude maneuver performance of an LEO satellite. The maximum torque and momentum of the actuators primarily limit the maximum angular acceleration and angular rate of an LEO satellite [7; 10; 19]. There may be additional constraints on the angular rate to ensure the performance of the GPS receivers and star trackers.  
When generating the attitude profiles for target pointings and maneuvering between target pointings, there may be an increase in the throughput of the flight software, which can lead to difficulties in performing complex missions. Furthermore, this approach may not be applicable to satellites in orbit. Therefore, we considered a ground-based technique for generating a reference attitude maneuver profile for operational applications. The reference attitude maneuver profile, which is generated on the ground and uploaded to the satellite, should minimize the increase in throughput when restored onboard. In particular, the contact time with LEO satellites is limited [23]. As a result, the upload time for mission execution, scheduled command sets for the next satellite contact, and playback execution for receiving satellite data during the time in which the satellite is inaccessible are also limited. Therefore, it is important to also minimize the data size uploaded. Accordingly, we developed an optimization approach to provide LEO satellites with reference data for attitude maneuvers between target pointings using the acceleration profiles for each axis, as shown in Figure 2. In other words, the size of the data sent to the satellite was reduced by using the time information (\(t_{1}\)_to_\(t_{8}\)), and the maximum and minimum values of the acceleration profile for each axis (a and b) are shown in Figure 2. Then, onboard the satellite, the acceleration was integrated to create a reference profile for the satellite's angular rate and attitude to maneuver the satellite.  
Figure 2: Attitude upload profile between target pointings of LEO satellites.
## 3 Results and Discussion
### Plume Height Analysis
#### 3.4.2 Dynamic Tests Influence MMRTG/Mast  
The influence of the thermal emission plume was analyzed for a scenario with a non-active resistor at 289 K (16 \({}^{\circ}\)C) and for an active resistor at 301 K (28 \({}^{\circ}\)C). Flow rates of 0.3, 0.7, and 1.4 mL/s, corresponding to wind speeds approximately equivalent to 1 m/s, were examined (Table 1). A representative case from these experiments is illustrated in Figures 5 and 6. It is important to note that the booms on the mast were positioned approximately 100 mm above the ground, and the total surface area of the complete model was 0.027 m\({}^{2}\). It can be observed from the data (Table 4 and Figures 5 and 6) that the plume height increases with an increasing flow rate and temperature. Furthermore, this increase is more pronounced in the non-active resistance scenario at 289 K (16 \({}^{\circ}\)C).  
Regarding the comparison between the active and non-active resistor cases, a slight increase in plume height is observed for the same flow rates. This can be attributed to the fact that the increased temperature of the ink flow enhances its buoyancy relative to the water in the towing tank.  
Thus, it can be preliminarily determined that since the height of the plume is equal to or greater than the height of the MEDA station for flow rates exceeding 0.75 mL/s (wind speeds of \(\sim\)1 m/s), regardless of the model temperature, the influence on the station is possible and a factor to be considered.  
\begin{table}
\begin{tabular}{c c c} \hline
**Air Velocity [m/s]** & **Downstreams Coordinate x [m] 1** & **Plume Height [m]** \\ \hline
0.3 & 2 & 7.4 \\
0.5 & 2 & 4.5 \\
1.0 & 2 & 2.2 \\
2.0 & 2 & 1.1 \\ \hline \end{tabular} 1  
\end{table}
Table 6: Thermal plume height (mathematical calculations—real scenario).  
Figure 8: Zenithal view exit angle flow rate 0.7 [mL/s]—dynamic mast/MMRTG active resistor. Upper images (from 1 to 4) show the ink emission flow evolution; lower image details (green lines) the measurement of the exit angle.  
Figure 7: Zenithal view exit angle flow rate 0.7 [mL/s]—dynamic mast/MMRTG-non-active resistor. Upper images (from 1 to 4) show the ink emission flow evolution; lower image details (green lines) the measurement of the exit angle.
## 3 Proposed Real-Time 3D Mapping-Aided (3 DMA) GNSS-Positioning System
### Offline Stage Skymasks Generation  
A skymask is a skyplot with building boundaries for a single location. It is an array with a total of 360 entries that represents the azimuth angle from \(0^{\circ}\) to \(359^{\circ}\). Each entry stores the highest elevation angle of the building blockage in degrees in the corresponding entry (each azimuth angle). Skymasks are generated in an offline stage. The intentional coverage area for the 3 DMA GNSS was first selected, and then the 3D city models were downloaded. The models were imported into the Rhino 7 3D-modelling software [45], and then converted to the Unreal engine-supported format for automated skymask generation [46]. The selected area was separated into 4 m catchment areas for each potential location to capture a 360\({}^{\circ}\) equirectangular image of the building outline. The skymask generation process was then performed by setting up a virtual camera in the Unreal engine to capture the panorama image at each potential location outside the building and above the terrain. The camera height was set manually based on the covered area, which was 15 m in this study, to best accommodate the elevation variation across the testing area. The elevation of the potential location can be set based on the digital terrain model for mass generation. Saved panorama images were then classified into obstacles and sky. At the cutting edge between obstacles and the sky, pixels were converted to angular position (azimuth and elevation angle) at the skymask. Lastly, each skymask corresponded to one position in the state plane coordinate system, which was converted to WGS84 for real-time 3 DMA GNSS positioning. The extracted skymask at each available location was then saved to a specified format for the microcomputer to use during real-time positioning [30].
# The Role of Smart Meters in Enabling Real-Time Energy Services for Households: The Italian Case
## 6 Communications Technologies for Real-Time Home Services  
Depending on the specific application, different requirements in terms of data volume, data rate, transmission/propagation delay, and reliability of data transfer can be identified for the SM communications channel. In this section, we review the main existing wireline and wireless technologies for SM communications (see Table 3 for the taxonomy), with a particular emphasis on those that enable real-time metering services. A more detailed survey can be found, for example, in [41].
## 3 Discussion
\begin{table}
\begin{tabular}{c c} \hline \hline
**Quantity** & **Value** \\ \hline Current concentration range (NO\({}_{2}\)) & 100–1000 \(\upmu\)mol/mol \\ \hline Optimal precision & 0.825 \(\upmu\)mol/mol at \\ \(\Delta\)t = 86 s \\ \hline GUM compliant total relative uncertainty & 5.1\% (\(k\) = 1) \\ \hline Relative repeatability at 1000 \(\upmu\)mol/mol and at & 0.1\% and 0.5\% \\
100 \(\upmu\)mol levels & 0.06 * sec to 0.5 s \\ \hline Time resolution & \\ (max = single scan to 10 scan average) & \\ \hline \hline \end{tabular}  
* \(\cdot\)abequisition time of 3.5 ms as extra time is needed to save the data.  
\end{table} 
Table 2: Summary of NO\({}_{2}\) OGS instrument capabilities. Figure 5: Simulation: NO\({}_{2}\) in exhaust gas matrix. emission measurement systems (PEMS) of less than 2% for NO\({}_{2}\). Regarding the line strength, we estimate that we can achieve an uncertainty better than 1.7% or 0.2% in future line strength measurements, similarly to in our previous works [51; 52], which would lead to a corresponding improvement in the NO\({}_{2}\) amount fraction uncertainty. One of the critical points in achieving an OGS is ensuring direct traceability to the SI. The traceability of the NO\({}_{2}\) amount fraction results in this work was addressed via the traceability of the input quantities on the right-hand side of Eqn.1, such as quantities \(p_{\text{total}}\), \(T\), \(L\) (SI-traceable to respective PTB standards). As presented, the validated line strength \(S_{T}\) value was taken from the HITRAN database [45] and SI-traceability was not reported. Therefore, in addition to a reduced uncertainty in the line strength value, new SI-traceable NO\({}_{2}\) line strength measurements are planned in separate experiments similar to [51; 52]. This work shows that an OGS for NO\({}_{2}\) amount fraction measurements is feasible. An OGS (providing _direct_ NO\({}_{2}\) amount fraction results traceable to the SI) for NO\({}_{2}\) can complement the current standard reference method (based on CLD), where NO\({}_{2}\) is \"only\" _indirectly_ measured (note: the concept of indirect measurement is not the issue here, but rather the conversion efficiency of NO\({}_{2}\) to NO and maintaining a minimum residence time). By providing amount fraction results that are directly traceable to the SI, an OGS can also complement (use in the place of) calibrate reference gases both in the laboratory and in the field. An OGS will add the advantage of simultaneous in situ measurement and side-by-side field NO\({}_{2}\) calibrations of other analyzers.
# Discrete Element Analysis of Indirect Tensile Fatigue Test of Asphal Mixture
###### Abstract  
In order to investigate the damage to microstructure and some other micromechanical responses during a fatigue test on asphalt mixture, Particle Flow Code (PFC) was used to reconstruct a two-dimensional discrete element model of asphalt mixture, based on computed tomography (CT) images and image-processing techniques. The indirect tensile fatigue test of asphalt mixture was simulated with this image-based microstructural model, and verified in the laboratory. It was found that there were four stages during the fatigue failure: no crack, crack initiation, crack developing, and interconnected crack. Cracks mainly developed between the aggregate and asphalt mortar, near the loading axis. The corresponding stages of failure, the developing trend and the distribution characteristics of the cracks matched well with those in the laboratory test. Furthermore, the trends of both the time-load curve and time-displacement curve from the simulation test were also consistent with those from the experimental test. In short, the distribution characteristics of cracks and internal forces of asphalt mixture show that it is feasible to simulate the fatigue performance of the asphalt mixture by a discrete element method (DEM).  
discrete element; asphalt mixture; digital image; fatigue; crack +
Footnote †: journal: Applied Sciences
###### Abstract  
Knee alignment after total knee arthroplasty (TKA) is essential for implant survival. Several studies on accelerometer-based navigation systems have given controversial results, with or without improvement in knee alignment. The aim was to evaluate the accuracy of an accelerometer-based navigation system for tibial resection during total knee arthroplasty. Twenty TKAs performed with an accelerometer-based navigation system were included in this prospective-comparative study. They were matched (on age, body mass index, and preoperative mechanical axis of the lower limb) in a 2:1 ratio with TKA performed with a conventional technique. The objective of this study was to determine the accuracy of the Perseus System for making the tibial cut on TKA. The primary endpoint was the tibial mechanical angle (TMA) measured on radiographic images at two months postoperatively. Secondary endpoints were the tibial slope and the mechanical axis of the lower limb (HKA angle, Hip-Knee-Ankle). The mean TMA in the accelerometer group was 87.6 \(\pm\) 2.1\({}^{\circ}\) versus 89.1 \(\pm\) 1.6\({}^{\circ}\) in the control group (\(p<\) 0.01). The tibial slope in the accelerometer group was 90.0 \(\pm\) 1.9\({}^{\circ}\) versus 89.9 \(\pm\) 1.3\({}^{\circ}\) in the control group (not significant). The mean HKA was 177.7 \(\pm\) 1.8\({}^{\circ}\) in the accelerometer group and 177.5 \(\pm\) 2.2\({}^{\circ}\) in the control group (not significant). This accelerometer-based navigation system during TKA did not improve the accuracy of the tibial cut compared to the conventional technique, but it restored the tibial slope.  
Keywords:knee arthroplasty; navigation system; accelerometer-based navigation; component alignment; radiological evaluation of total knee arthroplasty +
Footnote †: journal: Applied Sciences
## 4 System Model  
A vehicular network with N number of nodes is considered for modeling our propagation channel. d is the transmission range in meters. Figure 3 depicts the simulation model in which node i is communicating with node j. Consider a scenario in which node i is approaching node j which is decelerating. Node j will send a warning message to node i. We have simulated the scenario and have compared our results with simulated BER in the Rayleigh channel. Our BER computational approach with node i and node j is described in the next subsections. The simulations were performed in Matlab, as Matlab is user-friendly, and developing computational code and plotting graphs is easy in Matlab.  
The pathloss (PL) in db can be computed using expression [14]  
\[PL=10.\alpha.log_{10}(d)+\frac{15.d}{1000}+\beta \tag{1}\]  
where \(\alpha\) represents path loss exponent; \(\beta\) corresponds to a parameter for different numbers of blockers. The middle term in Equation (1) represents atmospheric attenuation for 60 GHz. The simulation parameters are shown in Table 2.  
The received SNR \(\gamma\) can be computed using expression (2).  
\[\gamma=P_{t}+G_{tx}+G_{rx}-NP-PL-N_{t} \tag{2}\]  
where \(P_{t}\) corresponds to transmit power, \(G_{tx}\) represents transmitter array gain, \(G_{rx}\) represents receiver array gain, \(N_{t}\) represents the number of transmitters, \(R_{c}\) corresponds to code rate, \(NF\) represents noise figure and NP corresponds to noise power which is computed using the expression below.  
\[NP=-174+NF\]  
Simulation parameters of SNR are depicted in Table 3.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**n** & \(\beta\) & \(\alpha\) \\ \hline
0 & 70 & 1.77 \\
1 & 78.6 & 1.71 \\
2 & 115 & 0.635 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Pathloss simulation parameters.  
Figure 3: Simulation model.  
These simulation parameters were used to compute the SNR of our model. In Sections 4.1 and 4.2, the SNR is used in our closed-form expression derivation.