esa-sceva/satcom-chunk-collection huggingface dataset:
# Enhancing Telexistence Control Through Assistive Manipulation and Haptic Feedback
## 6 Results and Analysis
### Qualitative Results and Analysis  
In the semi-structured interviews, participants were asked to share their feedback regarding their preferences for the four conditions of the system. The results reveal that 70% of participants found the condition featuring haptic feedback and assistance to be the most user-friendly, as illustrated in Figure 16. These findings are consistent with the rankings of conditions, as 60% of participants preferred the haptic and assistance condition as the most favorable. In contrast, the condition of no haptics and no assistance was ranked the least favorable.  
In our study, we evaluated users' perceptions of the telexistence system by asking them to identify their preferred features and rate the usefulness of various system components. Results indicate that a significant proportion of participants (approximately one-third) found haptic feedback to be the most enjoyable aspect of the system, with an average rating of 6.1 out of 7 for its usefulness. Additionally, around 30% of participants reported that the ability to move the robotic hand and have it mimic their hand was their preferred feature. Another 20% of participants found the ability to move the robotic arm itself to be the most enjoyable aspect of the system. The remaining participants (approximately 20%) reported that the ability to move the stereo camera by moving their heads was their preferred feature, with an average rating of 5.9 out of 7 for its usefulness.  
\begin{table}
\begin{tabular}{l c c c c c c} \hline \hline
**Mode** & **N** & **Mean** & **SD** & **SE** & **Coefficient of Variation** \\ \hline NN & 12 & 23.193 & 6.664 & 1.924 & 0.287 \\ NA & 12 & 22.056 & 5.531 & 1.597 & 0.251 \\ HN & 12 & 21.361 & 4.140 & 1.195 & 0.194 \\ HA & 12 & 18.944 & 5.035 & 1.453 & 0.266 \\ \hline \hline \end{tabular}
\end{table}
Table 11: The descriptive statistics for time across the different modes.  
Figure 16: The easiest condition results.  
\begin{table}
\begin{tabular}{l c c c c c c c} \hline \hline  & & \multicolumn{3}{c}{**95\% CI for Mean Difference**} & & & \\
**Comparison** & **Estimate** & **Lower** & **Upper** & **SE** & **df** & **t** & **_p_ \\ \hline NA-NN & \(-1.137\) & \(-4.444\) & \(2.169\) & \(1.625\) & \(33\) & \(-0.700\) & \(0.489\) \\ HN-NN & \(-1.832\) & \(-5.139\) & \(1.474\) & \(1.625\) & \(33\) & \(-1.128\) & \(0.268\) \\ HA-NN & \(-4.249\) & \(-7.556\) & \(-0.943\) & \(1.625\) & \(33\) & \(-2.615\) & \(0.013\) \\ \hline \hline \end{tabular}
\end{table}
Table 12: Simple contrast for the time.
## 5 Evaluation by Early Users  
It is worth mentioning that all the presented services have been evaluated by an initial set of early users that were employed to use and evaluate them. Specifically, 28 university students of the ECE School of NTUA were requested to use the Course Recommender service to help them select courses, while 3 professors were requested to use the Curriculum Designer service to receive recommendations concerning updates for their courses. Finally, all 31 users were requested to use the MCDSS service to prioritize their alternatives. For all three services, the majority of users found them at least useful, according to the questionnaires that they were requested to fill in after using the services.  
In particular, the vast majority of Course Recommender evaluators stated that the recommended skills are in high demand by the labor market, and the proposed courses teach the recommended skills. Moreover, the vast majority of the evaluators stated that the recommended skills and courses are at least satisfactory to them. Last but not least, they stated that it is very likely to use Course Recommender in the future for course selection. These results are illustrated in more detail also in Figure 15:  
Regarding Curriculum Designer, all three evaluators stated that the proposed skills are highly demanded by the labor market, and that they are relevant to the courses in which they are proposed to be introduced. Finally, all professors stated that it is very likely to use Curriculum Designer for updating their courses in the future. The evaluation results for Curriculum Designer are illustrated in Figure 16:  
Figure 14: Curriculum Designer analytics page, emphasizing the JavaScript skill.  
Finally, the MCDSS service was found to be useful for course selection by most of the students. The same goes for professors. Specifically, 16 out of 28 students and 2 out of 3 professors found the MCDSS service useful for updating a course, while 10 students and 1 professor were uncertain about its usefulness, and 2 students found it useless. Finally, regarding the likeliness of using the MCDSS service in the future, almost half of the users were positive. However, there were a considerable number of users (1 out of 3) who were not sure if they would use it. This can partly be explained by the fact that MCDSS methods require users to be somewhat familiar with them so that they can be effectively used. Finally, there were 3 users who do not intend to use the service in the near future. The evaluation results for the MCDSS service are illustrated in Figure 17:  
Figure 16: Curriculum Designer evaluation by professors.  
Figure 15: Course Recommender evaluation by university students.
## 4 Stepwise Process Enclosed in Proposed Research
### First Stage: Design of Optimal Routing Protocol
#### 4.2.2 Formation of a Grid  
The entire region considered for the experiment was partitioned into a square-shaped grid of equal size. The size of a single grid is calculated based on the communication range of the node. The mathematical formula used for calculating the size of a single grid is given by Equation (1):  
\[\mathrm{a}=\frac{\mathrm{R}}{\sqrt{2}} \tag{1}\]  
Equation (1), a denotes the size of the grid and R signifies the communication range of the node. Each grid is indicated with a different grid identifier number, and this number for each node is known using a GPS tracking system. In addition to the grid identifier number, each node has a different identification number.
# The Current Development of Structural Health Monitoring for Bridges: A Review
## 4 Early Warning Systems
The proposed tool from this study is expected to be used as a future platform for bridge displacement assessment and warning. [PERSON] et al. [118] used an improved InSAR method to analyze satellite observation scenes before the collapse of Tadcaster Bridge in the UK, demonstrating that the method can serve as an effective warning system for monitoring bridges at risk of erosion. [PERSON] et al. [119] proposed a measurement system for the vibration characteristics of suspension bridges based on low-frequency cantilever-based fiber Bragg grating accelerometers (CFAs) and verified the accuracy of the system on a suspension bridge in Malaysia. Additionally, the system can trigger early damage warnings when detecting changes in vibration characteristics. Among the US bridges with BHM systems installed [6], multiple types of sensors were installed on the Sunshine Skyway Bridge, and data other than the vibration of the cable-stayed bridge were used to predict the bridge's motion as caused by temperature and wind direction changes, while determining the threshold for triggering alerts. After discovering cracks on the Carroll Lee Cropper Bridge in the US, micro-crack gauges were installed in the direction of the cracks. The researchers determined the threshold for crack expansion and developed a warning system to alert when the crack exceeds the threshold. Different warning systems set warning thresholds based on different parameters, such as wind-induced vibration, beam deflection and displacement, cable tension, etc. The significance of the warning system is that when the monitoring data reaches or exceeds the threshold value, the regulator can be alerted very soon after the occurrence of an anomaly, so that subsequent inspections can be carried out. In addition, the temperature effect of the structure should always be taken into account, as it may cause unnecessary warning. Table 2 summarizes all the literature reviewed in this section, listing the specific bridges examined in each study and the methods applied in the early warning system.
## 3 Results
In the southeast part of the study area (mainly covered by cropland), the smallest soil moisture occurred in the late winter and spring period (February, March, and April); because winter wheat was in the growing period, the water consumption increased, which made the soil moisture significantly reduced. The largest soil moisture appeared in the precipitation period (July, August, and September). In addition, regarding the change characteristics of the northeastern part and southwestern part, soil moisture in summer was higher than that in winter. \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline  & \begin{tabular}{c} **Downscaling Model** \\ **Using _TVDI_ as** \\ **Downscaling Factor** \\ \end{tabular} & \begin{tabular}{c} **Downscaling Model** \\ **Based on Original** \\ **SMI Method**. \\ \end{tabular} & \
\begin{tabular}{c} **Level 3 SMAP Soil** \\ **Moisture Product in** \\ **9-km Resolution** \\ \end{tabular} & & & & & \\ \hline \multirow{4}{*}{
\begin{tabular}{c} A1 \\ **A2** \\ **(m\({}^{3}\cdot\)m\({}^{-3}\))** \\ \end{tabular} } & AE & RMSE & AE & RMSE & AE & RMSE & **Vegetation** & & \\  & **(\%)** & **(m\({}^{3}\cdot\)m\({}^{-3}\))** & **(\%)** & **(m\({}^{3}\cdot\)m\({}^{-3}\))** & **(\%)** & **(\%)** & **Water** & **Roughens** & **LST** \\ \hline A1 & 0.0112 & 6.28\% & 0.0138 & 7.73\% & 0.0260 & 17.77\% & 0.1320 & 0.1366 & 29.9737 \\ A2 & 0.0218 & 8.74\% & 0.0223 & 8.96\% & 0.0640 & 25.38\% & 0.3281 & 0.1563 & 33.0361 \\ B1 & 0.0156 & 8.96\% & 0.0190 & 10.94\% & 0.0555 & 21.00\% & 0.6930 & 0.1552 & 27.0131 \\ B2 & 0.0081 & 4.67\% & 0.0119 & 6.82\% & 0.0341 & 18.10\% & 0.1844 & 0.1066 & 15.3997 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Comparison of SMAP soil moisture and downscaled result within each sampling area. (AE: absolute error, _NDVI_: Normalized Difference Vegetation Index, RMSE: root mean square error, LST: land surface temperature, RMSE (%) = 100% \(\times\) AE/Observations).
# Wheeler Method for Evaluation of Antennas Submerged in Lossy Media
###### Abstract  
A Wheeler method for the evaluation of the radiation efficiency of submerged antennas within lossy media is presented and demonstrated for the first time in the literature. Extensive investigations have been devised by empirical and simulation methods. Normal-mode helical antenna (NMHA) was first designed and fabricated to exemplify a real-life application at the UHF band (0.3 to 3 GHz). The antenna under test (AUT) was evaluated within an artificial lossy material using a series of Wheeler caps featuring different radii to study the validity of this method. The error between the experimental and simulation radiation efficiency is below 3% near the theoretical radian length. The presented measurement method of radiation efficiency without any essential measurement facilities or accessories could be a promising candidate for fast and accurate evaluation for any wire-type antenna submerged within lossy media.  
radiation efficiency evaluation; radiation resistance measurement; Wheeler method; lossy media; submerged antennas +
Footnote †: journal: Applied  
18 February 2021  
1
# Damping of Beam Vibrations Using Tuned Particles Impact Damper
## 1 Introduction
The gap (free volume of the system) can be manually changed by the threaded lid. The research takes into account experiments, simulations and focuses on comparing three types of dampers: Particle Dampers, Tuned Particles Dampers and Tuned Mass Dampers. Determining the effectiveness of attenuation ability depending on the various excitation frequency and grains mass is also discussed. In the previous paper of the authors [40], the initial TPID concept was discussed. Preliminary study is presented and discussed. In contrast to Reference [40], in this paper, the authors present a significantly greater number of experimental results conducted for free and kinematically excited vibrations. Based on the recent results it possible to determine the effectiveness of the TPID damper to attenuate vibrations depending on the application of various grains material, variable mass of particles and container volume and the excitation frequency. The main novelty of this paper is the presentation of several different TPID intermediate states during a dynamic strategy of changing the container volume. A mathematical model based on a nonlinear-exponential control function has been proposed. A verification of the real system response and numerical simulations is additionally provided. The authors of this paper state, that Tuned Particle Impact Dampers can be competitive to other more sophisticated and expensive control schemes for industrial wind turbines such as proportional integral derivative regulators. The overview of PID literature presented in the Introduction section includes mainly passive damping strategies. The dynamics of attenuated by loose materials structures can be basically controlled by grains volume ratio, mass of the granular material or the coefficient of restitution. Although it was shown that PIDs are competitive to other damping techniques, up to this point granular dampers could not be used as a part of semi-active damping strategies. In this paper the authors propose an innovative Tuned Particles Impact Damping device. Its novelty consists of the possibility to rapidly change the volume of the compartment where the grains are encapsulated. This solution enables the implementation of a completely new adaptive-passive strategy of semi-active vibration damping. The paper is divided into several sections. In the next one the idea of the Tuned Particles Impact Damper is presented. In the third and fourth Sections the original test stand and experimental results are discussed respectively. The paper is completed with a Conclusion Section where the summary and the perspective research are revealed.
# Are Green Buildings an Indicator of Sustainable Development?
## 3 Results and Discussion
### GDP and GHG Emissions  
The relationship between the average GDP per capita in the EU (dependent variable) and GHG emissions per capita (independent variable) is studied through simple linear regression with data taken from Eurostat Database.  
The ten points in Figure 4 (blue dots) represent the years between 2010 and 2019. The trendline is linear with an equation of y = \(-\)0.2685x + 15.997, a \(p\)-value = 0.0099 and an R\({}^{2}\) = 0.5852. However, if we do not consider 2014 (highlighted with a red triangle in Figure 5 and characterised by extreme climate conditions with significantly fewer heating degree days compared to other years), the chart assumes a more linear equation y = \(-\)0.2996x + 16.862 with more accurate \(p\)-value = 0.0027 and R\({}^{2}\) = 0.7446.  
Figure 4: Relationship between GDP per capita and GHG emissions per capita in the EU (2010–2019).  
According to the assumptions stated in the Methodology, \(p\)-value and R\({}^{2}\) are consistent, and the equation that correlates the two variables is accurate with a strong significance.  
As illustrated by the EKC curve, in a developed area such as the EU, a higher income per capita is related to fewer GHG emissions per capita due to the best technologies already in place. This confirms the outcomes of another study [7] but differs from the ones from the second study [8] that assessed data in a mutating economic period within the EU (1995-2010) with the simultaneous presence of the left and right side of the EKC curve.
## 2 Materials and Methods
### Determination of Free Phenolic Compounds with HPLC-ESI-QqQ-Ms  
The separation of free phenolic compounds was carried out in accordance with [PERSON] et al. [27], with some modifications. The liquid chromatography apparatus used was the 1290 Infinity Series, equipped with a binary pump delivery system (mod. G4220B), a thermostatted column compartment (mod. G1316C), and an autosampler (mod. G4226A). The HPLC system was coupled with a 6420 triple quadrupole mass spectrometer (mod. G6420A). Both the HPLC system and mass spectrometer were from Agilent Technologies (Santa Clara, CA, USA). A Poroshell 120 SB-C18 (3.0 \(\times\) 100 mm, 2.7 \(\upmu\)m) column from Agilent Technologies (Santa Clara, CA, USA) was used for compound separation; the column temperature was maintained at 35 \({}^{\circ}\)C during analyses. A gradient elution was programmed using, as mobile phase A, acidified water (1% acetic acid) and, as mobile phase B, acetonitrile. The following multistep linear gradient was applied: 0 min, 5% B; 12.5 min, 30% B; 17.5 min, 60% B; and 22 min, 5% B. The initial conditions were maintained for 5 min. The flow rate was set to 0.6 mL/min throughout the gradient. The injection volume in the HPLC system was 2.5 \(\upmu\)L.  
After an optimization procedure, the following MS conditions were adopted throughout the analyses: type of analysis: multiple reaction monitoring (MRM); type of source: atmospheric pressure ionization-electrospray source (API-ES); polarity: negative; drying gas (nitrogen) temperature: 350 \({}^{\circ}\)C; gas flow: 13 L/min; nebulizer pressure: 50 psi; capillary voltage: +3500 V; cell accelerator voltage: 3 V; collision energy: 20 eV; and fragmentor: 85. Other parameters such as the parent ion, fragment ions, and quantification transition are specified in Table 1. \begin{table}
\begin{tabular}{c c c c} \hline
**Compounds** & **[M \(-\) H]–** & **Fragment Ions** & **Quantification** \\  & **(_m/z_)** & **Transition** \\ \hline _Phenelic acids_ & & & \\ \hline Caffe acid-O-hexoside 1 & 341 & 179-135 & 341\(\rightarrow\)179 \\ Caffe acid-O-hexoside 2 & 341 & 179-135 & 341\(\rightarrow\)179 \\ Caffe acid-O-hexoside 3 & 341 & 179 & 341\(\rightarrow\)179 \\ Neochlorogenic acid & 353 & 191-179-135 & 353\(\rightarrow\)191 \\ Coumaric acid-O-hexoside & 325 & 163-119 & 325\(\rightarrow\)163 \\ Cryptochlorogenic acid & 353 & 191-173-135 & 353\(\rightarrow\)191 \\ \hline \end{tabular}
\end{table} 
Table 1: Negative ion fragmentation data for the phenolic compounds determined in different samples of raw materials and uncooked and cooked pasta.
# User Experience Factors for People with Autism Spectrum Disorder
## 3 Related Work  
In a previous study [2], we analyzed the impact that technology has on people with ASD. One of the research questions answered in this research was \"Which user experience and accessibility elements/methods are considered when analyzing the impact of technology on people with autism spectrum disorder?\". We found a lack of empirical evidence and details from studies evaluating user experience and/or usability in systems designed for people with ASD.  
After the systematic literature review carried out previously [2] and a review of the literature at present, we found studies that have evaluated the user experience and/or usability in systems designed for people with ASD. Some studies [9; 10; 11] mention havingcarried out focus groups, and other studies [9; 12; 13] propose the use of eye tracking. In ref. [10; 11; 14; 15; 16; 17], the authors distribute questionnaires to users after having interacted with the systems, and in the same way, studies such as [18; 19; 20] evaluate the usability of systems through the use of the \"System Usability Scale\" (SUS) [21] or SUS-ASD [22].  
[PERSON] et al. [23] evaluated the usability of their software system based on [PERSON]'s methodology [24], which facilitates usability tests for serious games. Furthermore, studies [25; 26; 27] claim to have evaluated the usability of their systems designed for people with ASD based on an analysis of observations, through the collection of comments, and/or with the help of experts in the domain of people with ASD. On the other hand, studies such as [PERSON] et al. [28] propose evaluating the usability of systems for people with ASD through adaptations of the Nielsen heuristics [29]. Furthermore, studies such as [15; 30; 31; 32; 33] claim to have developed systems for people with ASD with a focus on accessibility given by the use of touch screens.  
These studies do not present empirical evidence or details that formalize the process of evaluating the user experience with systems designed for people with ASD. Additionally, no studies formally specify the attributes/factors/aspects of UX for systems designed for people with ASD, which we believe would provide a basis for formalizing the evaluation process. However, studies do identify the creation and/or use of design guidelines that characterize people with ASD as a means to develop systems for said people in different contexts, which can be a starting point for creating UX factors tailored to people with ASD. Below are studies that define design guidelines based on the characteristics of people with ASD.
## 4 Conclusions  
The computational model managed to reproduce the compression test of concrete cylinders, with a good approach to the values of the experimental development in terms of gradation, compressive stress, and modulus of elasticity.  
All assigned mesh sizes were close to each other and converged to the experimental value with some variations, depending on the assigned size. These differences appeared in different magnitudes in relation to the search event, such as compressive stress and elastic modulus.  
Both at the level of compression and the modulus of elasticity, the mesh that offered the most functional result in terms of time and results was the 3.0 mm mesh. The results in mesh No. 2.5 only varied in the second decimal with respect to that of 3.0 mm, which was inefficient in terms of time. The review carried out with the Tukey estimator showed the 3.0 mm mesh to be the best performance result.  
In terms of variation, the modulus of elasticity was more sensitive to variation in mesh size than compressive stress when using finite element analysis. The difference in results for the compressive stress was of the order of 3%, while for the modulus of elasticity, it was 4-6%. The error of the mean in the modulus of elasticity grew three times more than the resistance to compression, which established this parameter as more sensitive than the compressive strength.  
Future research. Concrete modeling in its individual phases, in this case, coarse aggregate and mortar, allows us to give way to new possibilities by recreating different geometric shapes. For this, it is necessary to start modeling from known or referenced meshes.  
Conceptualization, L.F.P. and L.C.S.H.; Methodology, A.J.B. and V.M.-P.; Software, L.F.P.; Validation, G.M.-A.; Formal analysis, L.F.P. and A.R.O.; Investigation, G.M.-A. and A.R.O.; Resources, A.J.B. and V.M.-P.; Data curation, V.M.-P.; Writing - original draft, A.J.B. and L.C.S.H.; Writing - review & editing, L.C.S.H.; Visualization, L.C.S.H.; Project administration, A.J.B.; Funding acquisition, G.M.-A. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Data Availability StatementData sets are not published. Please contact the author if necessary.  
The authors declare no conflict of interest.