esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Sensory Tests
#### 3.4.2 Consumer Acceptance and Purchase Intention Test Scores
\begin{table}
\begin{tabular}{c c c c c c} \hline \multicolumn{2}{c}{**Gender**} & \multicolumn{3}{c}{**Age**} \\ \hline
**Male** & **Female** & **18–24** & **25–34** & **34–44** & **45–59** \\ \hline
26\% & 74\% & 39\% & 47\% & 8\% & 6\% \\ \hline \multicolumn{2}{c}{**Level of education**} & \multicolumn{3}{c}{**Level of education**} \\ \hline
**Basic education** & **Complete high school** & \begin{tabular}{c} **Incomplete** \\ **graduation** \\ \end{tabular} & \
\begin{tabular}{c} **Complete** \\ **graduation** \\ \end{tabular} &
\begin{tabular}{c} **Master’s or** \\ **Doctoral degree** \\ \end{tabular} \\ \hline
6\% & 10\% & 31\% & 7\% & 46\% \\ \hline \multicolumn{2}{c}{**Family income (MW: minimum wages)**} & & \\ \hline
**1 MW** & 2-3 MW & 4-5 MW & \textgreater{}5 MW \\ \hline \multicolumn{2}{c}{\(1\%\)} & 25\% & 25\% & 46\% \\ \hline \multicolumn{2}{c}{**Frequency of tea/herbal tea consumption**} & \multicolumn{3}{c}{**Portionsize**} \\ \hline
**Daily** & **Twiedaily** & **Weekly** & **50 mL** & \
\begin{tabular}{c} **Regular cup** \\ **(150 mL)** \\ \end{tabular} &
\begin{tabular}{c} **Largecup** \\ **(240 mL)** \\ \end{tabular} \\ \hline
30\% & 16\% & 54\% & 12\% & 33\% & 55\% \\ \hline \multicolumn{2}{c}{**Types of teas commonly consumed**} & & \\ \hline
**Black tea** & **Green tea** & **White tea** & **Toasted mate** & **Chamomile** & **Lemonbalm** & **Fruity** &
\begin{tabular}{c} **Other teas** \\ \end{tabular} \\ \hline
35\% & 27\% & 6\% & 57\% & 65\% & 50\% & 44\% & 28\% \\ \hline \multicolumn{2}{c}{**Bulk orsache7**} & \multicolumn{3}{c}{**Brands**} & & \\ \hline
**Only** & **Only bulk teas** & **Sachetand bulk teas** & **Only traditional** & **Only** & **Traditional** \\ \hline
48\% & 7\% & 45\% & 82\% & 6\% & 12\% \\ \hline \multicolumn{2}{c}{**Dinking temperature**} & \multicolumn{3}{c}{**Consumption of ready-to-drink**} & \multicolumn{3}{c}{**Habit of**} \\ \multicolumn{2}{c}{**infusions ***} & & & **sweeteening tea** \\ \hline
**Only hot** & **Only cold** & **Hot and cold** & **Yes** & **No** & **Yes*** & **No** \\ \hline
51\% & 4\% & 45\% & 53\% & 47\% & 45\% & 55\% \\ \hline \end{tabular}  
* Other infusions such as hibscus, mint, bilberry, and horsetail. ** Consuming only bulk teas purchased in natural food stores or even from their gardens. *** Traditionally served cold and sweetened. *** Among those who sweetened, 77\% reported using sugar and 23\% sweeteners.  
\end{table} 
Table 4: Assessor’characteristics. These findings suggest that post-graduate women aged 25-34 years with family monthly incomes higher than 5 MW are potential consumers of cascara coffee tea. This consumer tends to appreciate exotic and expensive gourmet products [67]. On the other hand, young consumers aged 18-24 years, with lower income and education, are not good candidates.
## 3 Results and Discussion
### Evolution of Mechanical Properties
#### 3.3.3 Elastic Modulus  
The evolution of the elastic modulus of the inner shaft lining concrete on Day 1, Day 3, and Day 7 after pouring is depicted in Figure 10. The elastic modulus of the shaft lining concrete significantly increases in the first three days and increases slightly in the later ages. In the last four days, the increase of elastic modulus of concrete in three analyzed thicknesses is less than 0.58%, which means that the elastic modulus of concrete in the lining has increased to a relatively stable state in the first three days. The tensile strength of the lining at the same age increased significantly with the thickness, but the increase rate exhibited no apparent relation to the thickness. Under the three analyzed thicknesses, the elastic modulus of the shaft lining concrete with three different thicknesses ranged between \(3.17\times 10^{4}\) MPa and \(3.56\times 10^{4}\) MPa within the first 7 d. Finally, the evolution equation of elastic modulus with age within the first 7 d after pouring is fitted based on experimental data, as shown in Table 6.
## 3 Results and Discussion
### Introduction of HMDS for QD Improvement
The degree of dispersion can be checked from the atomic force microscope (AFM) results in Figure A1 in the Appendix A. It can be seen that the roughness of QD coated using HMDS is excellent. Oxygen'element is always present in the air, making it difficult to distinguish using the EDX component mapping method. The Si and O elements on the CdSe/ZnS QD surface were additionally investigated by the XPS measurement technique as shown in Figure 1d. The intensities of both O 1s and Si 2p are higher when the CdSe/ZnS QDs were coated with HMDS, indicating the formation of the SiO bonds on the CdSe/ZnS QD surface. The strong intensity in XPS means that the number of bonds of the element corresponding to the energy is large. When the QD was blended with HMDS, the intensity of O increased, indicating that the number of bonds of oxygen increased and it became oxidation. Furthermore, for the samples treated with HMDS, the peak position of the O 1s signal shifted toward the direction of higher binding energy. This observation also suggests that the samples treated with HMDS move to a higher oxidation state due to the formation of SiO(CH\({}_{3}\))\({}_{3}\) on the CdSe/ZnS QD surface. In [24], it is said that the oxygen bound to the organic component increases the binding energy range from 530.9 to 533.8 eV. When HMDS was not coated on QD, O 1s was 531.7 eV, and when HMDS was coated, O 1s showed a peak of 533.3 eV. It was found that the binding energy was increased by 533.3 eV as carbon, the organic component, was combined with O. It can be predicted from the increased binding energy that Si-O-(CH\({}_{3}\))\({}_{3}\) is formed. As described above, despite the fact that the Oxide layer was not visible at the QD edge from the TEM results, the Si component was confirmed in EDX, and the presence of oxygen was predicted by the strong intensity and the increased binding energy of O 1s in XPS. From these results, rather than a uniform oxide layer, it is considered that a thin oxide of the extent to passivation of defects of QDs in various places is formed. Further analysis of the passivated material on the surface of the CdSe/ZnS QD is necessary for future analysis.
## 3 Promotion of Double-Duplex Invasion by Modified PNAs
### Ruthenium-Complex PNA Conjugate (Ru-PNA)  
PNA conjugated with ruthenium (Ru) complex (Ru-PNA) has been reported as a modified PNA that exhibits high invasion efficiency under physiological conditions [74]. Ru-polypyrid complexes are known to have high DNA affinity due to hydrophobic and electrostatic interactions with DNA. Therefore, the DNA binding ability of PNA has been improved by conjugation with Ru complexes, and an increase in invasion efficiency has been achieved. Similar to NLS-PNAs, this method only requires the introduction of the DNA-binding molecule into the PNA, and the preparation of modified PNA is effortless. The introduction of the Ru complexes into PNA is easily achieved via amide condensation between the carboxyl group derivatives of the Ru complex and amino acids having an amino group on the side chain. The synthesis of Ru-PNAs is accomplished by standard solid-phase peptide synthesis, and the Ru complex was introduced to the PNA via an amino group on the side chain of the N-terminal \({}_{L}\)-2,3-diaminopropionic acid (Dap; Figure 8a).  
Ru-PNA exhibited high invasion efficiency even at low PNA concentrations and 100 mM NaCl (Figure 8b), where with unmodified pcPNA, it is difficult to form an invasion complex. Furthermore, even under physiological conditions, the invasion efficiency was nearly 90% using six equivalents of Ru-PNA. Ru-PNA also showed high sequence-discrimination ability, and no invasion proceeded with mismatched DNA that differs by only one base pair. This increase in invasion efficiency is attributed to the high DNA-binding ability of Ru-PNA, which was confirmed by melting temperature (\(T_{\text{m}}\)) measurements. It is suggested by the \(T_{\text{m}}\) measurements that the Ru-complex interacts with DNA outside the target sequence of the PNA. Interestingly, it has also been reported that the invasion efficiency of Ru-PNAs varies greatly depending on the introduction manner of the Ru complex. In addition to PNA conjugated with Ru complexes on the side chain of Dap, the introduction of Ru complexes on the side chain of Lys and the amino group of the PNA main chain were also investigated. However, no increase in invasion efficiency was observed with those Ru-PNAs, suggesting that the Ru complexes could not interact appropriately with DNA. These results indicate that the introduction mode and spatial arrangement of the Ru complexes are very important for the appropriate interaction of the Ru complexes with DNA and the improvement of invasion efficiency.  
Figure 8: (**a**) Structure of Ru-PNA utilizing \({}^{L}\)-2,3-diaminopropionic acid for introducing the Ru-complex. (**b**) Ru-PNAS stabilize double-duplex invasion.
# Multi-Disciplinary Optimization of UV-C Filter for Air Disinfection
## 2 Filter Modeling and Simulation
### UV Ray Tracing Simulation  
The combination of CFD particle tracking and UV ray tracing simulations is used to evaluate how the changes in geometry parameters affect the device's performance and if the UV-C radiation intensity inside the device is sufficient to achieve a proper disinfection.  
From the CFD analysis, as described in the previous paragraph, the trajectory of the particles through the device can be tracked. Figure 7a illustrates a sample of particle flow trajectories, colored by their velocity magnitude (m/s), for the baseline filter geometry. The residence time of each particle slightly changes between 0.37s and 0.41s.  
Figure 7: (a) Particle flow path sample. (b) Particle spatial distribution in 3 sections [m]. (c) Radiation intensity distributions in 3 sections [W/m\({}^{2}\)]. Adapted from paper cited in [19].  
For each design proposed in the optimization, the radiation intensity is evaluated by TracePro 2023 software in 14 different sections of the filter, equally spaced along the main \(z\)-axis. Figure 7b shows the X-Y position of each trajectory (colored by their ID number) for the baseline filter geometry in three key sections of the device (placed, respectively, at coordinates z1 = \(-\)6 cm, z2 = \(-\)1 cm, and z3 = 0 cm), while Figure 7c shows the UV radiation intensity [W/m\({}^{2}\)] for the same three sections. For each of the 14 sections, a 100 \(\times\) 100 matrix is defined, whose elements describe the UV intensity distribution on the (\(X\), \(Y\)) plane.  
By combining the radiation intensity with the particle trajectory, it is possible to compute the UV dose of radiation absorbed for each particle, as described by Equation (1). The trajectory of the particle is divided into \(N\) different timesteps, and at each timestep \(i\) the particle is associated with the closest section according to its axial position. The radiation absorbed in this timestep (\(gi(x)\) in Equation (4)) is retrieved from the radiation intensity matrix corresponding to this section, at the (\(X\), \(Y\)) position of the particle.  
The total dose of radiation absorbed by the particle (Equation (4)) is finally obtained by summing the absorbed radiations in each timestep, multiplied by the delta time (\(\Delta T\)) between two consecutive timesteps:  
\[UV_{i}=\sum_{i}^{N}g_{i}\left(\frac{\rightarrow}{x}\right)\Delta T \tag{4}\]
# Aquasafe: A Remote Sensing, Web-Based Platform for the Support of Precision Fish Farming
## 2 Materials and Methods
### Data
#### 2.2.2 In-Situ  
_In-situ_ data are being used for both validation and calibration of our models and include field measurements of physicochemical parameters such as DO and SST from the selected fish farms. Specifically, comparison of these measurements with the satellite data offers means of validation since it allows the evaluation of the system's performance. Moreover, archiving the _in-situ_ recordings provides time series, which are essential for calibrating and improving the models at a later stage. Additionally, specifications about fish and cages for each farm are being manually input from the users and can be edited at any time. This serves a dual function. On the one hand, the performance of the fish model can be evaluated while the obtained data can be used in future parametrization and improvement. On the other hand, it allows a real-time adjustment of the model to correct for potential deviations. This is achieved by resetting the initialization of the simulations based on the most recent input provided by the user.
# Modeling of Fuzzy Systems Based on the Competitive Neural Network
## 2 Theoretical Framework
### Discussion  
For this research, the methodologies of Competitive Neural Networks and Fuzzy Inference Systems were selected due to the great results they have produced in research carried out by scientists around the world, specifically, in research focused on data clustering and classification problems. On the one hand, unsupervised approaches have limitations under complex datasets; therefore, to solve this problem, we propose the use of fuzzy logic to generate a robust model. Furthermore, one of the limitations of fuzzy logic is how to obtain the parameters (type of inference system, type of input and output MF, the parameters of the MF, how the MFs are granulated, and generate the fuzzy rules). In this sense, the CNN helps to obtain the MF parameters from the data, how these are granulated, and generate fuzzy rules based on the input data.  
To model the FIS, we selected the Mamdani and Sugeno systems; these have yielded good results in classification problems as we have previously mentioned. The choice of Triangular, Gaussian, and Trapezoidal MFs is based on the experts in the area according to previous works [24; 33], where the FIS is modeled with the aforementioned MFs and after several tests, we can obtain the best accuracy results. Finally, it is important to mention that these three types of membership functions are designed with mathematical and metric functions according to their form. The detailed explanation and the obtained results will be presented in Section 3.
# Hybrid Methodology Using Sentinel-1/Sentinel-2 for Soil Moisture Estimation
## 2 Materials and Methods  
### Database  
#### 2.1.1 ISMN Soil Moisture Data  
The training and validation of the proposed methods are conducted based on data from the International Soil Moisture Network (ISMN) [37]. The data are available in conjunction with additional datasets of Koppen-Geiger climate classes, ESA's CCI land cover, and soil characteristics. The upper soil layer (0-10 cm) moisture measurements are harmonized as fractional volumetric soil moisture (m\({}^{3}\)/m\({}^{3}\)) and converted into Coordinated Universal Time (UTC). After data quality verification, some ISMN networks suffer from a lack of measurements. Therefore, we considered 21 networks among a total of 71 spatially distributed as shown in Figure 1. The data of each station should cover a period of two years with at least 20 dates between the start and the end date of acquisitions--1 January 2015 and 19 August 2021, respectively. Consequently, in the same network, we retain only stations with valid dataset as detailed in Table 1.  
Figure 1: The global distribution of the International Soil Moisture Network (ISMN).  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Network** & **Country** & \begin{tabular}{c} **Number of** \\ **Selected Stations** \\ \end{tabular} & \
\begin{tabular}{c} **SM** \\ **Sensors** \\ \end{tabular} & **References** \\ \hline \multirow{4}{*}{AMMA-CATCH} & \multirow{2}{*}{Benin, Niger} & \multirow{4}{*}{7} & \multirow{4}{*}{CS616} & [PERSON] et al. [38]; [PERSON] et al. [39]; [PERSON] et al. [40]; [PERSON] et al. [41]; [PERSON] et al. [42]; [PERSON] et al. [43]. \\ \cline{1-1} \cline{2-5}  & BIEBRZA-S-1 & Poland & 8 & GS-3 & [PERSON] et al. 2016 [44] \\ \hline \multirow{2}{*}{COSMOS} & \multirow{2}{*}{USA} & \multirow{2}{*}{2} & \multirow{2}{*}{Cosmic-ray-Probe} & [PERSON] et al. [45]; [PERSON] et al. [46] \\ \hline \multirow{2}{*}{HOBE} & \multirow{2}{*}{Denmark} & \multirow{2}{*}{3} & \multirow{2}{*}{Decagon-5 TE} & [PERSON] et al. [47]; [PERSON] et al. [48] \\ \hline \multirow{2}{*}{
\begin{tabular}{c} FLUXNET- \\ AMERIFLUX \\ \end{tabular} } & \multirow{2}{*}{USA} & \multirow{2}{*}{4} & CS655, & \multirow{2}{*}{} \\  & & ThetaProbe-ML23 & & \\ \hline \multirow{2}{*}{FR-Aqui} & \multirow{2}{*}{France} & \multirow{2}{*}{3} & \multirow{2}{*}{ThetaProbe ML2X} & [PERSON] et al. [49]; [PERSON] et al. [50] \\ \hline \multirow{2}{*}{GROW} & \multirow{2}{*}{UK} & \multirow{2}{*}{20} & \multirow{2}{*}{Flower-Power} & [PERSON] et al. [51]; [PERSON] et al. [52]; [PERSON] et al. [53] \\ \hline \multirow{2}{*}{HOAL} & \multirow{2}{*}{Austria} & \multirow{2}{*}{32} & SPADE-Time-Domain- & [PERSON] et al. [54]; [PERSON], [PERSON], et al. [55] \\ \cline{1-1} \cline{2-5}  & & & CS655, & \multirow{2}{*}{[PERSON] et al. [56]} \\ \cline{1-1} \cline{2-5}  & & ThetaProbe-ML2X & & \\ \hline \hline \end{tabular}
\end{table}
Table 1: Overview of the considered ISMN networks.
## 3 A proposed Cyberattack Prevention Framework and Hypothesis Development
### Organization Frequent Training  
For a business to conduct its everyday operations, periodic training will teach employees the best practices and values for preventing cyberattacks in an extended cybersecurity environment [74]. According to [PERSON] and [PERSON] (2021) [75], the majority of security awareness training initiatives concentrate on the most-recent network breaches and ongoing threats. Employees who receive cybersecurity training can better defend themselves and the company against online threats and attacks. An organization's frequent training improves service performance and efficiency to maintain long-term viability and stop threats and cyberattacks [73; 74; 75]. Organizations regularly train employees on email phishing scams used by hackers, hacktivists, and cybercriminals by letting them know how susceptible they are to a virus, spam, ransomware, and hacking. If workers don't have the slightest concept of how to identify a security risk and how they can be expected to avoid it, report it, or eliminate it, then organizations must teach them about cybersecurity. Organizational regular training will help employees recognize and eliminate cyberthreats and protect their most important assets [73]. Employees can therefore identify security breaches and prevent them by recognizing the threat level as spam, phishing, and malware, which are common occurrences in the workplace. Additionally, employees require online cybersecurity training to defend both themselves and the company from cyberattacks. Perhaps the most effective way to protect against cyberattacks and all forms of data breaches is to educate financial institution staff about how to prevent cyberattacks and keep them informed about recent hacks [73]. Employee mindfulness is essential for a financial business in this way. Therefore,  
**H6:**_Organization frequent training has a positive, significant relationship with cyberattack prevention._
# Estimating Destination of Bus Trips Considering Trip Type Characteristics
## 2 Literature Review
### Methodology for Estimating Destination Based on Combination of Approaches  
If a single estimation methodology, such as a trip-chain-based or AI/probability model-based alighting stop estimation methodology, is applied, there is the limitation that there are trips that are impossible to estimate using a single methodology. It is not possible to estimate alighting stops using trip-chain-based method for trips not linked to other trips. Application of the pattern-based method is not possible without historical trip data. To overcome this limitation, studies have been conducted by applying several alighting stop estimation methods. For example, a study applied the trip-chain-based estimation methodology first and then applied a boarding time similarity-based alighting stop estimation method [19]; a study applied different alighting stop estimation methods by classifying the trip type based on the number of trips per day, the last trip of the day, the transfers in the trip, etc. [26]; a study derived a higher success rate of the alighting stop estimation by applying the trip-chain-based alighting stop estimation methodology in the first stage and the machine learning-based methodology in the second stage [25].
## 2 Evolution of NMR Methodologies
### Solution-State NMR for Polysaccharides  
Solution-state NMR techniques have proven to be important in polysaccharide research due to their ability to provide detailed information about the molecular composition, structure, and dynamics in the solution environment. These methods allow researchers to examine complex polysaccharides without requiring crystallization, making them a great choice for studying natural heterogeneous systems. Researchers can identify glycosidic bonds, branching patterns, and correlations between atoms by employing advanced 2D NMR experiments, including COSY, HSQC, TOCSY, and NOESY [16; 17; 18].  
Recently, solution-state NMR has been applied in many fields, including the characterization of microbial extracellular polysaccharides. It is also helpful for identifying bioactive polysaccharides in metabolomics. Moreover, it can be used to evaluate polysaccharide interactions in traditional drugs and food matrices [19; 20; 21]. These advances show that the latest NMR is very important in bringing together basic research and practical uses in polysaccharide science.
# Direct Measurement of Heat Produced during Drilling for Implant Site Preparation
###### Abstract  
The aim of this study was to directly measure the temperature of the drill during implant site preparation. The measured temperature was compared to that previously reported inside the bone. The temperature change of the drill was measured using a thermocouple inserted inside the stainless steel drill using an 18-gauge needle and mercury-containing slip ring. Three thermocouples were inserted into the bone with different depths of 10 mm, 5 mm and 1 mm. The thermocouple was 0.5 mm away from the periphery of the drilled hole with a diameter of 3.4 mm. The drill rotating speed varied from 500 rpm to 2000 rpm. Each drilling procedure was performed 10 times, and the average was calculated. The temperature of the drill increased rapidly, and the thermocouples in the bone reached a maximum temperature after the drill temperature started to decrease. The maximum inner temperature of the bone was the highest at a depth of 10 mm. The patterns of the temperature change were similar at different rotating speeds. The actual maximum temperature at the drill and bone interface was significantly higher than the temperature measured inside the bone in previous reports.  
d  
dental implant; site preparation; drilling heat