esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results  
### Study Selection  
A total of 1705 publications were identified through an initial search in the database. After excluding duplicate studies and applying eligibility criteria, 12 articles were selected for systematic evaluation. A detailed overview of the selection process is shown in Figure 1.  
The screening process for this study involved several steps. In the initial literature search, a total of 1705 publications were identified. After removing duplicates and applying the eligibility criteria, 1087 papers were retrieved from the Web of Science (WOS) and SCOPUS databases, with 841 from WOS and 246 from SCOPUS. The discrepancy between the numbers reflects the removal of irrelevant or duplicate studies during the screening process. The papers were then merged and imported into Zotero for management, where duplicate and unusable entries were identified. After this review, 139 duplicates and one retracted article were removed, leaving 947 valid papers.  
Following title screening, 831 papers were excluded based on several criteria: papers that were irrelevant to the topic of virtual reality exergames, literature reviews that did not present original data, and studies that did not specifically target healthy older adults. This process left 116 relevant articles. Subsequently, during the abstract screening, an additional 79 papers were excluded for the following reasons: they involved other hardware devices such as augmented reality, Kinect, balance boards, or treadmills, which fell outside the scope of this review; they did not focus on cognitive or physical abilities such as acceptance or tolerance; and they included participants with conditions such as Alzheimer's disease, physical disabilities, or cognitive impairments, which were not relevant to our study of healthy older adults. As a result, 37 relevant papers remained for further analysis.  
A final review of the full texts excluded 25 articles, leaving 12 that met the inclusion criteria: (1) the experimental setup involved only VR hardware (includes hardware related to VR operation such as positioners, joysticks, and streaming boxes), without other devices such as AR, Kinect, balance boards, or treadmills; and (2) participants were healthy older adults without any diseases.
# Development of Chest X-ray Image Evaluation Software Using the Deep Learning Techniques
## 2 Materials and Methods
### Evaluating the Created Models  
In this study, we evaluated the CLM using overall accuracy on the confusion matrix and the SSM using the mean intersection over union (mIoU). When evaluating \"the chest X-ray image evaluation software\" with three CLMs and one SSM, the time taken for the input CXR image to pass through each created model and that for the system to show a response as to whether a retaking is necessary (response) were evaluated using the response time on this software (RT). Because each model was created independently, the RT per image of the software was calculated by summing up the RT per image of each model. The formulas for the evaluation indices were as follows, where TP is true positive, FP is false positive, TN is true negative, FN is false negative, N is the number of images, RT\({}_{\text{CLM1}}\) is the response time of the lung field defect CLM, RT\({}_{\text{CLM2}}\) is the response time of the disorder shade CLM, RT\({}_{\text{CLM3}}\) is the response time of the disordered shadow location CLM, and RT\({}_{\text{SSM}}\) is the response time of the lung field area SSM:  
\[\textit{Overlay Accuracy}\left[\%\right]=\frac{TP+TN}{TP+FP+TN+FN}\times 100 \tag{1}\]  
\[mIoU=\frac{1}{N}\Sigma_{N=1}^{N}\frac{TP_{N}}{TP_{N}+FP_{N}+FN_{N}} \tag{2}\]  
\[\textit{Response Time}\left[s\right]=RT_{CLM1}+RT_{CLM2}+RT_{CLM3}+RT_{SSM} \tag{3}\]  
Because each model was trained and evaluated using a fivefold cross validation, the mean values of the overall accuracy and mIoU of the obtained five models were used to calculate the evaluation of each model.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Environment** & **Content** \\ \hline Software & MATLAB 2021a (developed by MathWorks) \\ OS & Windows 10 \\ CPU & Intel Core i9-10980 XE 3.0 GHz \\ GPU & NDIVIA RTX A6000 48 GB \(\times\) 2 \\ Memory & DDR4 2933 Quad-Channel \\ \hline \hline \end{tabular}
\end{table}
Table 4: Equipment and software used.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Label** & **Content** \\ \hline Network & ResNet-50 \\ Minibatch size & 256 \\ Epoch & 5 \\ Optimizer & Stochastic gradient descent with momentum \\ Momentum & 0.9 \\ Initial learning rate & 0.0001 \\ L2 regularization & 0.0001 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Learning conditions for creating the classification models.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Label** & **Content** \\ \hline Network & DeepLabv3+ \\ Minibatch size & 128 \\ Epoch & 3 \\ Optimizer & Stochastic gradient descent with momentum \\ Momentum & 0.9 \\ Learn rate drop factor & 0.3 \\ Initial learning rate & 0.001 \\ L2 regularization & 0.005 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Training conditions for creating the semantic segmentation model.
# Robust Symbol and Frequency Synchronization Method for Burst OFDM Systems in UAV Communication
## 3 Improved Burst OFDM Synchronization Method
### Symbol Timing Synchronization Method Based on 2-Bit Non-Uniform Quantization  
This study proposes an improved synchronization algorithm based on 2-bit non-quantization to achieve accurate symbol timing synchronization with low computational complexity. The computation complexity is significantly reduced by replacing the complex multiplications in correlation processing with XOR and addition operations. This approach preserves crucial signal information while minimizing any loss in synchronization accuracy by carefully designing the quantization levels. We need to clarify that the proposed non-uniform quantization method is only applied during the symbol synchronization process. In the subsequent signal processing steps, such as channel estimation, equalization, and channel decoding, the traditional uniform quantization method is employed.
# A Method of Defect Depth Recognition in Active Infrared Thermography Based on GRU Networks
###### Abstract  
Active infrared thermography (AIRT) is a significant defect detection and evaluation method in the field of non-destructive testing, on account of the fact that it promptly provides visual information and that the results could be used for quantitative research of defects. At present, the quantitative evaluation of defects is an urgent problem to be solved in this field. In this work, a defect depth recognition method based on gated recurrent unit (GRU) networks is proposed to solve the problem of insufficient accuracy in defect depth recognition. AIRT is applied to obtain the raw thermal sequences of the surface temperature field distribution of the defect specimen. Before training the GRU model, principal component analysis (PCA) is used to reduce the dimension and to eliminate the correlation of the raw datasets. Then, the GRU model is employed to automatically recognize the depth of the defect. The defect depth recognition performance of the proposed method is evaluated through an experiment on polymethyl methacrylate (PMMA) with flat bottom holes. The results indicate that the PCA-processed datasets outperform the raw temperature datasets in model learning when assessing defect depth characteristics. A comparison with the BP network shows that the proposed method has better performance in defect depth recognition.  
active infrared thermography; defect depth recognition; gated recurrent unit; principal component analysis +
Footnote †: 2021: 11, 6387. [[https://doi.org/10.3390/app11146387](https://doi.org/10.3390/app11146387)]([https://doi.org/10.3390/app11146387](https://doi.org/10.3390/app11146387))
# Study on the Effect of Anchor Cable Prestress Loss on Foundation Stability
## 2 Overview of the Project
### Foundation Pit Support Program  
The metro station of this project is an underground 2-story single-arch large-span structure constructed by prefabricated assembly technology. The assembly section in the middle of the station pit is supported by drilled piles + first concrete support + anchor cable, as shown in Figure 1. The 850 mm thick TRD retaining wall stopping curtain is set on the outside of the bored piles. The support structure hardly occupies the internal space of the pit, which maximizes the construction space.  
The diameter of the bored piles is 1000 mm, the spacing is 1500 mm, and the inner support is an 800 \(\times\) 800 mm concrete support. Crown beams are installed on the top; the size of the crown beams is 1200 \(\times\) 1200 mm, and the slope surface is made of sprayed concrete with reinforcing mesh.  
According to the design documents, a total of four anchor cables is installed in the foundation pit of this project, and the specific anchor cable parameters are shown in Table 1 below.
## 4 Attempts to Quantify GSI with an Explicit Focus on the Vertical Axis of the V-GSI Chart
### Maintaining a Geological Perspective  
While [PERSON] and [PERSON] [13] are clear that the purpose of the graphical GSI system is to maintain a geological perspective that is easy to use, they do not seem to subscribe to the philosophy that no attempts should be made to improve the GSI chart or that a quantified chart can never exist, as per the authors of [1]. To quote [PERSON], [PERSON], and [PERSON], 2007 [25], \"The GSI system has considerable potential for use in rock engineering because it permits many characteristics of a rock mass to be quantified, thereby enhancing geological logic and reducing engineering uncertainty. Its use allows the influence of variables, which make up a rock mass, to be assessed and thus the behaviour of rock masses to be explained more clearly.\" While this quote is somewhat ambiguous, it certainly does not advocate that no improvements or research that involves the quantification of the GSI chart should be attempted.  
It is also the perspective of the authors of this paper that introducing scale on the vertical axis of the V-GSI chart does not negate or detract from the geological logic implicit in the original graphic chart. An understanding of geology and the development of a geological model should always be the first priority for any project on or in rock when using the empirical GSI system and the empirical H-B failure criteria, i.e., the use of GSI and the H-B equation derivatives \"are not intended to replace and indeed, depend for their successful application on, careful thought, detailed appraisals of site geology, carefully conducted site characterization and laboratory test programmes, and detailed evaluation of the mechanics of engineering problems being addressed\" ([PERSON], 2008 [26]). It is argued that even Dr. [PERSON] (one of the main proponents of modern rock mechanics) and one of the primary authors of the GSI system recognized that a sense of scale on the vertical axis is a useful addition to the original graphical GSI chart. For example, ref. [21] used rock quality designation (RQD) to provide scale on the vertical axis of the GSI chart because they recognized that it provided easily quantifiable estimates of block size. While the choice of RQD as a parameter to measure the scale or degree of blockiness is debatable (for many reasons, such as orientation bias and scale limitations), it nevertheless shows that there was recognition globally that an understanding of scale and scale effects is a necessity and that this can and should be incorporated in the GSI system.
# Defect Tailoring in HfO2/Si Films upon Post-Deposition Annealing and Ultraviolet Irradiation
## 4 Discussion
The blue dotted circles in Figure 11b indicate the presence of extended absorption tails, which explain the variations  
Figure 11: Electronic band diagram of the S1–S4 films considering (**a**) fluorescence data and (**b**) (F(R)hv\({}^{2}\) = 0 transitions from the UV–visible spectra. in the transition values, as observed in Figure 10. With respect to the indirect transitions, many of them showed a sharp onset, which is consistent with the Davies-Mott model for amorphous semiconductors [19]. The electrical behavior of samples can now be discussed in light of the proposed electronic diagrams. In the case of S1 sample, conduction occurred predominantly through the oxygen vacancies [27]. After thermal annealing at 350 \({}^{\circ}\)C, resistivity was lowered by the increase in oxygen vacancies, as depicted in Figure 11a. In the case of samples S3 and S4, which were UV-irradiated, novel unoccupied states at 3.5 eV and 3.8 eV were formed, which decreased the difference h described in Section 3.3, acting as traps for electrons injected into the conduction band [27]. On the other hand, the oxygen vacancy states increased in S4 with respect to S3, while the trap states at 3.5 eV and 3.8 eV were reduced, and the state close to the valence band around 2 eV increased, which, on the whole, may explain the metallic-like behavior of the S4 sample and the large resistivity and rupture for the reverse bias of sample S3. Thus, the electrical properties of HfO\({}_{2}\) could be controlled by the balance between the intrinsic oxygen vacancies and the states tailored by post-deposition treatments. As a final consideration, the results suggest that in addition to doping [8] or preparing heterostructures [9; 10], it is possible to tailor the electronic structure of HfO\({}_{2}\) using an adequate selection of thermal and UV treatment for photocatalytic/electrocatalytic applications. Also, the present study sheds more light on the defects that control the performance of HfO\({}_{2}\) for its potential applications in microelectronics, electro and photocatalysis, and optical devices.
## 8 Conclusions and Future Prospects
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Species** & **Bands** & **Wavelength/nm** & **Laser Type** & **Techniques** & **LOD/ppb** & **Refs** & **Applications** \\ \hline \multirow{4}{*}{NO/NO\({}_{2}\)/NH\({}_{3}\)} & \multirow{4}{*}{\(v_{1}\)/\(v_{1}\)/\(v_{3}\)} & 5263 & & & 0.20\(\,\)100 s; & \\  & & & 0.96\(\,\)61 s & & 0.12\(\,\)100 s; & \\ \cline{1-1} \cline{5-7}  & & 6250 & & 0.94\(\,\)61 s & & Industrial & emission \\ \cline{1-1} \cline{5-7}  & & 9063 & & & 0.10\(\,\)100 s; & \\ \cline{1-1} \cline{5-7}  & & & 0.86\(\,\)601 s & & & \\ \hline NH\({}_{3}\)/C\({}_{4}\)H\({}_{10}\) & \(v_{2}\)/\(v_{24}\) & 8500 & QCL & MHS [2] & / & [48] & Technique \\ \hline NO\({}_{2}\)/ & \multirow{2}{*}{\(v_{1}\)/} & 6234 & \multirow{2}{*}{QCL} & \multirow{2}{*}{TILDAS [3]} & 0.03 & \multirow{2}{*}{[264]} & Atmospheric \\ HONO & & 6024 & & & 0.3 & & pollution \\ \hline SO\({}_{2}\)/SO\({}_{3}\) & \multirow{2}{*}{\(v_{3}\)} & 7500 & \multirow{2}{*}{QCL} & \multirow{2}{*}{DAS} & \multirow{2}{*}{(1-2)\(\times 10^{3}\)} & \multirow{2}{*}{[265]} & Industrial \\ \cline{1-1} \cline{5-7}  & & 7160 & & & & & \\ \hline C\({}_{2}\)H\({}_{5}\)Cl/CH\({}_{2}\)Cl\({}_{2}\)/ & \multirow{2}{*}{//\(v_{4}\)} & \multirow{2}{*}{7949} & \multirow{2}{*}{EC-QCL} & \multirow{2}{*}{DAS} & 4 & \multirow{2}{*}{[266]} & Atmospheric \\ CHCl\({}_{3}\) & & & & & & & VOCs \\ \cline{1-1} \cline{5-7}  & & & & & & & \\ \hline \hline \end{tabular}  
* \({}^{1}\) WMDM-2f: Wavelength modulation-division multiplexing-2f; [2] MHS: Multiheterodyne spectroscopy; [3] TILDAS: Tunable infrared laser differential absorption spectroscopy.  
\end{table} 
Table 3: _Cont._  
**Author Contributions:** This review article was jointly written and proof-read by all authors. [PERSON] proposed the idea, drafted the outline and structure, and contributed to the principle, detection methods as well as conclusion. [PERSON] collected references, composed the whole manuscript, and contributed to the summary. [PERSON] contributed to the system configuration and detection methods. [PERSON] contributed to the system configuration. [PERSON] contributed to the detection methods. **Funding:** This research was funded by the National Natural Science Foundation of China (61505142), the Tianjin Natural Science Foundation (16)CQNJC02100), the Science & Technology Development Fund of the Tianjin Education Commission for Higher Education (2017 KJ085), and the Natural Science Foundation of Hebei Province (F2014202065). **Acknowledgments:** This work was supported by the open project of Key Laboratory of Micro Opto-electro Mechanical System Technology, Tianjin University, Ministry of Education. **Conflicts of Interest:** The authors declare no conflict of interest.
# Effectiveness of High-Intensity Therapy in Rehabilitation of Parkinson's Disease Patients
## 2 Methods
### Cardiovascular, Physiological Monitoring, and Follow-Up Assessments  
Heart rate, blood pressure, and Borg RPE were recorded at every training session. Posturography and quality of life outcomes were assessed within one week before and after the 14-week training period. Physiological responses to training were monitored through heart rate (HR), measured before and after each session, recording both average and maximal values. Blood pressure (BP), including systolic and diastolic values, was assessed pre- and post-training to evaluate cardiovascular responses. Posturography metrics analyzed center of pressure (COP) sway, comparing eyes open vs. closed and firm vs. unstable surfaces to assess balance control and postural stability. Sway velocity, displacement, and sway area (cm\({}^{2}\)) provided objective measures of stability and fall risk. Participants were closely observed for dizziness, fatigue, or cardiovascular distress, with safety protocols ensuring hydration breaks and supervised rest periods to minimize exercise-induced discomfort. Post-intervention assessments were conducted within one week of the 14-week training period, using the same baseline evaluation tests. The EQ-5D Health Questionnaire assessed mobility, self-care, daily activities, pain/discomfort, and anxiety/depression, while the EQ-5D Visual Analog Scale (VAS) measured self-reported health status. These follow-ups provided quantitative data on motor function improvements, agility, and fall risk reduction, enabling statistical analysis of treatment efficacy across intervention groups.
# Helium Atmospheric Pressure Plasma Jet Source Treatment of White Grapes Juice for Winemaking
## 3 Results and Discussion
### Characterization of White Grapes juice and Wine
#### 3.2.2 ATR-FTIR Spectroscopy of White Grapes Juice and Wine  
As it can be depicted from Figure 5, the transmittance spectra of the wine samples, in the 500-4500 cm\({}^{-1}\) wavenumber range, could be divided into four regions important for wine characterization, both from the chemical content as well as from the chemometric point of view.  
Figure 4: The absorbance spectra of untreated and treated must in the 200–1100 nm range.  
These regions of interest, as can be seen in the Figure 5, expressed the content of polyols, glycerin/glycerol and hydroxil radicals in the 2800-3500 cm\({}^{-1}\); the presence of organic acids (known also as 'total acidity') and amino acids, or carboxylates in the 1250-2000 cm\({}^{-1}\); the extant of carbohydrates, including polysaccharides (namely glucose, fructose, oligosaccharides) and polyols, in the 1000-1200 cm\({}^{-1}\), and also the presence of phenolic compounds (like phenols, esters, acetals or ketols) in the 500-960 cm\({}^{-1}\) region [68; 72; 73; 76; 77; 112; 113]. Moreover, two clear absorption bands between 3600-3200 cm\({}^{-1}\) and 1700-1560 cm\({}^{-1}\) were correlated with O-H stretching vibrations. The small, yet evident, peak between 3040-2800 cm\({}^{-1}\) is usually associated with the stretching vibration of C-H bond. Small differences were noticed in the FTIR spectra of all wine samples, plasma treated or untreated. These were related to the shift of the wavenumber of some observed peaks and further on listed in Table 4.  
FTIR spectroscopy was involved in monitoring of wine process and prediction of its parameters (e.g., monitoring wine aging), as well as wine authenticity and traceability, or prediction of a white wine aromatic potential, as well as studies of phenolic profile and antioxidant activity during the winemaking process. All of these (and other aspects previously mentioned) make this technique very important in the vine and winemaking industry, underlining the usage of it in this study.  
\begin{table}
\begin{tabular}{c c c c c} \hline
**Wine Samples** & **Region 1** & **Region 2** & **Region 3** & **Region 4** \\
**Samples** & **500–960** & **1000–1200** & **1250–2000** & **2800–3500** \\  & **(cm\({}^{-1}\))** & **(cm\({}^{-1}\))** & **(cm\({}^{-1}\))** & **(cm\({}^{-1}\))** \\ \hline MB & 865, 903 & 1044, 1084 & 1318, 1385, 1636 & 2983, 3290 \\ PB & 876 & 1044, 1088 & 1317, 1397, 1456, 1636 & 2984, 3303 \\ MH & 876 & 1044, 1085 & 1274, 1392, 1455, 1636 & 2983, 3290 \\ PH & 875 & 1044, 1084 & 1320, 1388, 1456, 1636 & 2980, 3313 \\ \hline \end{tabular}
\end{table}
Table 4: Wavenumber regions measured in the studied wine samples, similar to those reported by [68; 72; 73; 76; 77; 112].  
Figure 5: The IR transmittance spectra of untreated and plasma treated wine samples (1y old).
## 2 The Rotational Speed Control Problem of the Propeller of the Prototype Electric MAV  
The prototype electric MAV, 0.8 m in height and 0.55 m in diameter, is shown in Figure 1. A duct is formed through the fuselage, and a propeller is mounted to the middle portion of the fuselage. Four deflecting vanes are mounted along the longitudinal and lateral axes of symmetry below the propeller to provide pitch, roll and yaw movements. Most of the anti-torque generated by the propeller is compensated by the stators configured inside the duct while the remaining anti-torque is balanced by the deflecting vanes. A center-symmetric landing gear consisting of four legs, _i.e._, left, right, front, back, made from glass fiber-reinforced plastics is installed on the MAV [2]. The propulsion system mainly consists of an advanced lithium battery, a brushless DC electric motor with an electronic speed controller (ESC), a subminiature encoder, and a propeller. The propeller driven by the electric motor can provide sufficient thrust force to lift the MAV.  
The rotational speed control of the electric propeller is desired for a high-performance MAV, because the characteristics of the rotational speed are nonlinear, and strongly affect the flight dynamics, stability and reliability of the MAV. It is, however, noted that, until recent times, the rotational speed of the electric propeller is only regulated according to the signal from a command signal generator without a closed-loop rotational speed control structure under fairly stable conditions, thus degrading the flight performance of the MAV. Therefore, the goal of this study is to design a reliable rotational speed controller for the electric propeller.
# Applying Topological Information for Routing Commercial Vehicles Around Traffic Congestion
## 5 Results
### Model Scalability  
The methodology described in this study can be applied to roadway networks in other locations in order to facilitate diversion decisions. The presented framework can also be used as a basis for making more efficient rerouting decisions while maintaining operational safety.  
While this study was conducted on Interstate 75 in Florida, the developed framework can be generalized to all of the Florida interstate corridors.  
By following the same procedure developed in this study, decision makers would be able to achieve the following:  
* Predicting incident clearance duration at the study area of interest.
* Building a dynamic routable network.
* Implementing alternative route selection criteria into the network to select the optimal route that is suitable to divert truck traffic.
* Quantifying the benefits resulting from diverting truck traffic to the selected alternative route.  
The effects of incident data for other highways would be different depending on different road characteristics and different traffic conditions; therefore, a different incident timeline could be predicted. However, the developed framework could be applied to other regions in the U.S. interstates.