esa-sceva/satcom-chunk-collection huggingface dataset:
# Personalization of the 3D-Printed Upper Limb Exoskeleton Design--Mechanical and IT Aspects
## 5 Discussion
### Limitations of Current Approach  
Personalization of medical devices, especially individually tailored and made by 3D printing (including within the Industry 4.0 and Industry 5.0 paradigm), is a major challenge and a research gap. In accordance with the above-mentioned paradigm, technical control takes place at all stages of planning, design and production, and even the life cycle of a medical device and the range of possible changes in the dimensions of the tested object is significant (possible differences in hand sizes, finger construction or even deformations and/or fingers/digits amputations).  
This is a significant research gap in technical sciences (medical informatics, mechanical engineering and biomedical engineering) as well as in clinical practice, which has not found a satisfactory solution so far. This gap must be filled as soon as possible because the market of 3D-printed medical devices is growing dynamically, and it is necessary to automate the process of testing, wearing and selecting 3D-printed rehabilitation supplies.  
Despite the personalization of the arm exoskeleton, the procedure for its selection (e.g., for type and level of deficit and type of activity) and testing should be comparable and reproducible. Therefore, there is a need to standardize and structure tests to ensure replication and thus provide a simple, fast, accurate and generally recognized test environment. Ultimately, this will benefit everyone: designers, manufacturers, clinicians and, most importantly, users of arm exoskeletons and their families/carers.  
The guidelines for testing require it to be: reproducible, accurate, fast and, in most cases, also versatile (general applicability), i.e., it should not be limited to a selected group of cases, and it should allow testing of both the healthy hand and the hand with a deficit as well as in an exoskeleton, left and right.  
So far, robotic devices for the rehabilitation of motor deficits have been studied, especially in stroke patients. It should be noted, however, that most of the tested devices only allow the practice of stereotypical elements of simulated functional tasks in the clinic. In addition, few exoskeletons have been studied so far that can support movements during real functional activities, including at home. Hand exoskeletons, singled out as a subgroup in upper limb exoskeletons and despite significant advances, face several design challenges:  
* Achieving the intended size and functional capabilities at the lightest possible weight;
* Ensuring sufficient grip strength;
* Conforming to natural patterns of grasping movements;
* Ensuring the safety of the user's hands;
* Maintaining short donning (arming) and doffing times in emergency situations;
* Little comprehensive research describing with sufficient accuracy all phases of design, manufacture, fit, use and recycling of the hand exoskeleton [94; 95].
## 2 Experimental Program
### Materials  
High calcium fly ash class C (FA-C), low calcium fly ash class F (FA-F), ground granulated blast furnace slag (GGBPS), silica sand (maximum particle size, 600 \(\upmu\)) as well as two types of powder-based reagents were used to develop AAM mixes using the dry mixing technique [24]. Reagent 1 was composed of a combination of calcium hydroxide (Ca(OH)\({}_{2}\)) and sodium meta-silicate (Na\({}_{2}\)SiO\({}_{3}\)\({}_{5}\)\({}_{2}\)O), having a modular ratio (SiO\({}_{2}\)/Na\({}_{2}\)O) of 1.0. The constituents of the reagent 2 were calcium hydroxide (Ca(OH)\({}_{2}\)) and sodium sulfate (Na\({}_{2}\)SO\({}_{4}\)). The specific gravities of calcium hydroxide (CH), sodium metasilicate (SM) and sodium sulfate (SS) were 2.24, 1.81 and 2.70 g/cm\({}^{3}\), respectively. The alkalinity in terms of pH values of CH, SM and SS were 12.4-12.6, 14 and 7, respectively. All the reagents were of lab-grade quality, having a purity of 95-100%. Additionally, Type GU-general use cement was used for producing control mortar mixes. A polycarboxylate ether-based superplasticizer having a pH of 6, a specific gravity of 1.06 g/cm\({}^{3}\) and an approximate solid content of 40% was used as a high range water reducer admixture (HRWRA) to produce flowable mortar mixes. The chemical compositions obtained through X-ray fluorescence spectrometer analysis and the physical properties of SCMs and cement are presented in Table 1. The grain size distribution of the SCMs, cement and silica sand are presented in Figure 1.  
\begin{table}
\begin{tabular}{c c c c c} \hline
**Chemical Composition (\%)** & **FA-C** & **FA-F** & **GGBFS** & **Cement** \\ \hline SiO\({}_{2}\) & 36.53 & 55.66 & 35.97 & 19.35 \\ Al\({}_{2}\)O\({}_{3}\) & 18.26 & 22.09 & 9.18 & 5.31 \\ Fe\({}_{2}\)O\({}_{3}\) & 5.66 & 4.26 & 0.50 & 3.10 \\ CaO & 20.97 & 7.97 & 38.61 & 62 \\ MgO & 5.08 & 1.16 & 10.99 & 3 \\ K\({}_{2}\)O & 0.68 & 1.49 & 0.36 & - \\ Na\({}_{2}\)O & 4.04 & 4.10 & 0.28 & 0.23 \\ MnO & 0.03 & 0.03 & 0.25 & - \\ TiO\({}_{2}\) & 1.26 & 0.61 & 0.39 & - \\ P\({}_{2}\)O\({}_{5}\) & 0.96 & 0.43 & 0.01 & - \\ LOI. & 2.18 & 1.05 & 0.74 & 2.40 \\ \hline Physical properties & FA-C & FA-F & \multicolumn{1}{c}{GGBFS} & \multicolumn{1}{c}{Cement} \\ \hline Density (g/cm\({}^{3}\)) & 2.61 & 2.02 & 2.87 & 3.15 \\ \hline Retained on 45 \(\upmu\) (\%) & \textless{}5 & \textless{}10 & \textless{}5 & \textless{}10 \\ Blaine fineness (m\({}^{2}\)/kg) & 315 & 306 & 489.30 & 410 \\ \hline \end{tabular}
\end{table}
Table 1: Chemical composition and physical characteristics of fly ash-class C, fly ash-class F, GGBFS and cement.
## 1 Introduction
Compared to Binary Huff curves [16] and Hessian curves [17], Binary Edwards curves are not only faster and more secure, but also have a smaller key size and require less computational resources, making them ideal for constrained environments [6]. The potential use of these curves can be found in applications such as cloud computing [18], secure messaging [19], digital signatures [20], and internet of things [21; 22; 23], where high security, high throughput, and efficient resource utilization are critical. Overall, the adoption of Binary Edwards curves can significantly enhance the security of these applications while maintaining optimal performance.
# The DLR FireBIRD Small Satellite Mission: Evaluation of Infrared Data for Wildfire Assessment
## 2 Materials and Methods
### FireBIRD Active Fire Detection and Analysis at Subpixel Level  
#### 2.2.1 Active Fire Detection  
The fire detection method is similar to the method originally developed for the HSRS onboard the BIRD satellite, the precursor of the FireBIRD mission [28]. BIRD featured the same MWIR and LWIR band ranges as FireBIRD. In the updated version used for FireBIRD, the red band is used to exclude cloud and sun glint pixels for daytime scenes, instead of the NIR band. First, a threshold is applied to the MWIR/LWIR band surface temperature in order to derive potential fire pixels. Secondly, the final fire pixels are derived using a contextual approach.
# Evaluation of Malolactic Starters in White and Rose Winemaking of Moschofilero Wines
## 4 Discussion
Improvement of buttery and vanilla notes, among others, were reported by [PERSON] et al. [35] as the descriptors that distinguished wines that had undergone MLF from the ones that had not. In the case of Chardonnay wines, this was also reported to occur after the MLF of Chardonnay wine [36]. Citric acid metabolism has been implicated in buttery notes enhancement through the production of diacetyl via the activation of the citrate pathway [37]. The level of production plays a crucial role as the detection threshold is low and highly dependent upon the bacterial strain and the composition of the fermentation niche. According to our results, citric acid consumption led to wines with significantly increased buttery notes compared to the control condition. Even though the citric acid degradation capacity was significantly different among the tested conditions, the relative effect on buttery wine notes was only slightly different between the bacterial strains used. It should be taken into consideration that some bacterial strains are also able to reduce diacetyl to the corresponding alcohol, 2,3-butanol, which is a compound with no aromatic impact [38]. The ester groups have a great impact on the fruity sensory profile of wine, and they are formed during alcoholic and malolactic fermentation [39]. MLF fermentation can lead to either an increased or a decreased content of esters, influencing the aromatic composition of the wine [18; 40]. LAB have been reported to both synthesize and hydrolyze esters through their esterase activities [41]. In our present study, we showed that the impact of MLF fermentation on ethyl esters was highly strain-dependent and less influenced by the wine type, which was in accordance with the literature [41; 42]. However, [43] reported that only the branched hydroxylated esters, especially the R form, were strongly influenced by the bacterial strain.
## 3 Results and Discussion
### The Results of the Biocompatibility Assessment  
In the cytotoxicity test of CCK-8 (Figure 12), the proliferation rate of MSCs cells in culture for 5 days in PCL, CNC-3/PCL, and control is shown in Figure 13. As shown in Figure 12, the relationship between absorbance and culture time. The absorbance value of scaffolds printed by PCL increases from 1.022 \(\pm\) 0.22 to 1.759 \(\pm\) 0.17 in 5 days while the absorbance value of scaffolds printed by CNC-3/PCL changes 1.005 \(\pm\) 0.17 from to 1.67 \(\pm\) 0.04. The absorbance value and cell growth trend of scaffolds do not differ significantly from those in the control. The result can prove that the scaffold can support the growth and proliferation of MSCs cells. The absorbance values of each well increased with increasing culture time, indicating that the number of cells on the scaffolds increased with increasing culture time. The daily absorbance values of the cells cultured on the scaffolds of the three groups were analyzed by one-way ANOVA using Graphpad prism 5. 0 software, and the absorbance of the same number of cells cultured in normal culture medium was used as the control group, and the results showed that the absorbance values of each well were not statistically different (\(p>0.05\)) [40]. It indicates that the cell proliferation rate is comparable in the three solvent groups, with increasing culture time. And there was no change in cytotoxicity of CNC/PCL composites when compared with PCL.  
It was observed in Figure 13 that the differentiation of MSCs cells with PCL, CNC-3/PCL, and control group for 1 day (a,b,c) and 5 days (d,e,f). After 1d, there were few MSCs, small in size, growing in clusters, with different morphologies, mostly shuttle-shaped. 5d later, the number of MSCs increased, and the cell morphologies were varied, including round, shuttle-shaped, irregularly shaped, etc., and were arranged in an orderly manner. This phenomenon indicated that MSCs cells grew well in the scaffold.  
Figure 12: Results of CCK-8 cytotoxicity test.
# A Two-Stage Anomaly Detection Method Based on User Preference Features and the Deep Fusion Model
## 4 Results
### Evaluation Method  
We utilize the classical evaluation metrics, which consist of accuracy, precision, recall, and F1-score.  
\[\text{Acc}=\frac{\text{TP}+\text{TN}}{\text{TP}+\text{FP}+\text{TN}+\text{FN} ^{\prime}}\]  
\[\text{Rec}=\frac{\text{TP}}{\text{TP}+\text{FN}^{\prime}}\]  
\[\text{Pre}=\frac{\text{TP}}{\text{TP}+\text{FP}^{\prime}}\]  
\[\text{F1-score}=2\times\frac{\text{Pre}\times\text{Rec}}{\text{Pre}+\text{ Rec}^{\prime}}\]  
where TP represents the correctly classified samples, FP represents the misclassified attack samples, TN represents the correctly classified normal samples, and FN represents the misclassified normal samples.  
The accuracy rate is the proportion of correctly classified traffic to the total traffic data, reflecting the overall detection performance of the model. The precision rate is determined as the proportion of real attack traffic in the number of attack traffic, reflecting the precision of the model in judging the attack. The recall rate is the proportion of the identified attack traffic to the total attack traffic, which reflects the coverage of attack data achieved by the model. The F1-score is an evaluation index that uses the harmonic mean combined with the recall rate and the precision rate to effectively reflect the overall performance of the detection model.
## 3 Results and Discussion
### Description of Energy Dissipation  
In accordance with the principles of thermodynamics, energy transformation is a fundamental aspect of physical processes involving matter, and the destruction of matter is a consequence of energy-driven destabilization of its state [32]. Assume that in an adiabatic system, the energy input into the system by external forces is \(U\), and according to the first law of thermodynamics, all of this energy is transformed into the internal energy \(U_{I}\) of the system. This energy can be divided into two parts, the recoverable elastic strain energy \(U_{E}\) and the dissipation energy of the element \(U_{D}\). The energy can be divided into two parts, the recoverable elastic strain energy and the dissipation energy of the element. The variation pattern of \(U_{D}\) conforms to the second law of thermodynamics, which states that the entropy of the system tends to increase and is irreversible. The damage to concrete structures is accompanied by energy dissipation. Therefore, it can be assumed that \(U_{D}\) is strongly correlated with element damage, making \(U_{D}\) a suitable indicator for evaluating tunnel lining damage.  
Figure 10 depicts the energy dissipation time history of the tunnel lining in Case 2 and Case 3. The total energy dissipation of the lining in Case 2 is approximately 11,500 kJ, with around 6000 kJ dissipated during the fault dislocation stage and about 5500 kJ during the seismic action stage. In Case 3, the tunnel lining dissipated approximately 3000 kJ of energy. Comparing it with Case 2, despite both experiencing the same ground motion input, the tunnel lining in Case 2 releases an additional 2500 kJ of energy, representing nearly an 85% increase in energy dissipation. This shows that the damage to the tunnel caused by the combined effects of fault dislocation and seismicity is not a simple superposition, and the initial damage caused by fault dislocation will aggravate the damage of the tunnel during the seismic stage.
## 3 Results  
### Characterization and Identification of CH-AgNPs  
After mixing _Prunus cerasus_ leaf extract with AgNO\({}_{3}\) solution, we observed a color change from colorless to brown and yellowish brown, which indicates the formation of AgNPs and CH-AgNPs, respectively. The synthesis of AgNPs and CH-AgNPs were confirmed via UV-Vis spectroscopy analysis. UV-Vis spectra of nanoparticles were recorded in the range of 200-800 nm. UV-Vis spectra of AgNPs and CH-AgNPs exhibited a peak at 429 and 445 nm, respectively, which is mainly due to the surface plasmon resonance of nano forms of silver (Figure 1).  
The second step in physicochemical characterization is the average particle size distribution by dynamic light scattering (DLS). The data highlighted that the average sizes of AgNPs and CH-AgNPs were 32.16 and 50 nm, respectively, with a polydispersity index of 0.2 (Figure 2a,b). The increase in CH-AgNP size is due to the chitosan coating AgNPs. We further investigated our biologically synthesized AgNPs and CH-AgNPs with surface charge definition via zeta potential analysis. The results indicate that AgNPs had a charge of \(-7.20\) mV, while CH-AgNPs scored a value of 9 mV, with both measurements indicating the nanoparticles were stable (Figure 3a,b).  
Figure 1: UV–Vis absorption spectra of synthesized AgNPs (429 nm) and CH-AgNPs (445 nm).  
Figure 2: Particle size distribution of synthesized (**A**) silver nanoparticles (32.16 nm) and PDI (0.2), and (**B**) silver chitosan nanoparticles (50 nm) and PDI (0.2).
## 4 Implementation
### Collaborative Framework
#### 4.2.2 Anchor Synchronization  
In order to share the same AR experience, AR devices make use of anchors, which are entities used to align virtual objects in the same physical location and rotation (thus, multiple users see the virtual elements in the same physical position). In the implemented protocol, once a node receives the role of slave, it asks for the shared anchor directly from the master node over TCP (this process is illustrated in Figure 3). Since an anchor is usually sent in a large packet (often between 60 MB and up to hundreds of MBs), the use of TCP instead of UDP ensures that certain communications errors that may occur during the data transmission are automatically handled. During the synchronization process, the change of state of the anchor is indicated by different colors: red (system ready), blue (requesting anchor), yellow (importing anchor), and finally, green (anchor synchronized).
# Spatial Distribution and Monitoring of Land Subsidence Using Sentinel-1 SAR Data in Java, Indonesia
## 3 Results
### Spatial Distribution and Land Subsidence Rate
#### 3.1.4 Bandung Basin  
LS in the Bandung area (6.9175\({}^{\circ}\) S, 107.6191\({}^{\circ}\) E) is also referred as LS in the Bandung Basin, which administratively consists of four areas, which are Bandung City, Bandung Regency, West Bandung Regency, and Cimahi Regency. These areas are geologically dominated by an alluvial plain. The study of LS in Bandung has been performed intensively since almost three decades ago. The LS in Bandung is triggered by a combination of both natural and anthropogenic factors. However, it is dominantly caused by groundwater exploitation and natural compaction [4]. The impact of LS in Bandung has also been mapped [3]. Recently, the impact of LS on infrastructure has drawn the government's attention due to the construction of critical infrastructure in Bandung, such as Kereta Cepat Indonesia-China (KCIC; Indonesia-China High-Speed Train).  
The result shows that the LS rate in Bandung has not been slowed, which in some cases may reach up to 200 mm/year (see Figure 6a). The LS area is spread, particularly in the southern part of Bandung City and in several industrial areas. All of the LS areas are located within a thick layer of alluvial sediment [18]. Figure 6b emphasizes the locations with the highest rate of LS, Figure 6(b.1) indicates the LS time series, and Figure 6(b.2) indicates the field condition of LS in the region highlighted by the black box (b).  
It is worth noting that the highest rate of LS occurs in residential areas rather than in industrial areas. A field survey revealed that residents in this location extract groundwater for daily use. According to the local residents, the average depth of wells in this area is about 60-80 m deep. With a population density exceeding 15,000 people per km\({}^{2}\) in this area, a significant amount of water is required to meet the daily need [40].
###### Abstract  
The aim of this study was to analyze the effects of different exercise interventions involving chronic exercise (endurance and strength groups) carried out in physical education on physical fitness and cognitive functions. A group of 72 adolescent students from the city of Melilla (Spain) aged between 13 and 17 years old (M = 15.38, SD = 0.78) participated in the current study. A D2 attention test was used in order to analyze selective attention and concentration. Physical fitness was measured through the ALPHA-Fitness battery. The analysis taken indicated a significant relationship between physical fitness level, attention and concentration. Moreover, the intervention resulted in significant reductions in body weight and waist circumference in the resistance and strength groups compared to the control group, indicating positive effects on body composition. All the groups demonstrated enhanced aerobic capacity, as evidenced by improvements in VO2 max after the intervention period. Furthermore, significant enhancements in most attentional measures (TR, TA, O, C, TOT, CON and TR\(-\)) were observed across all the groups, with an additional temporary improvement in TR\(+\) for the strength group. Our findings suggest that an 8-week school-based exercise intervention, regardless of specific exercise type (resistance or strength), can positively impact body composition, aerobic capacity and attention in adolescents. These results emphasize the importance of integrating physical activity programs into school environments to promote holistic health and well-being in this population. Future research should focus on elucidating the underlying mechanisms of these effects and exploring the long-term benefits of such interventions.  
endurance; strength; cognitive; adolescent; attention +
Footnote †: journal: Applied Sciences
# Regularized Within-Class Precision Matrix Based PLDA in Text-Dependent Speaker Verification
## 5 Experiments
### Results
In RSR 2015 part 1 trials, the proposed method revealed relative EER reductions of approximately 7% (for the x-vector) to 19% (for the d-vector) on the validation trials, reductions of approximately 7% (for the i-vector) to 13% (for the d-vector) on the male evaluation trials, and reductions of approximately 5% (for the x-vector) to 23% (for the d-vector) on the female evaluation trials. In RSR 2015 part 2, the proposed method similarly revealed relative EER reductions of approximately 7% (for the x-vector) to 16% (for the r-vector) on the validation trials, reductions of approximately 3% (for the i-vector) to 13% (for the r-vector) on the male evaluation trials, and reductions of approximately 6% (for the x-vector) to 15% (for the d-vector) on the female evaluation trials. Finally, we performed a score-level fusion of all proposed systems for each dataset. The weights for each score were estimated using logistic regression with the scores from the validation trials. With score-level fusion, we achieved significant performance improvements. Figure 10: The EERs (%) of the PLDA (dashed red line), GLASSO-PLDA (solid blue line), PCA-PLDA (dotted red line), and PCA-GLASSO-PLDA (solid green line) according to \(\rho\) on the evaluation trials of RSR 2015 part 2: (**a**) male trials for d-vector, (**b**) male trials for r-vector, (**c**) male trials for x-vector, (**d**) female trials for d-vector, (**e**) female trials for r-vector, and (**f**) female trials for x-vector. EERs of the PCA-PLDA are not shown if the PLDA and PCA-PLDA have the same EER. Figure 9: The EERs (%) of the PLDA (dashed red line), GLASSO-PLDA (solid blue line), PCA-PLDA (dotted red line), and PCA-GLASSO-PLDA (solid green line) according to \(\rho\) on the validation trials of RSR 2015 part 2 for the (**a**) d-vector, (**b**) r-vector, and (**c**) x-vector; EERs of the PCA-PLDA are not shown if the PLDA and PCA-PLDA have the same EER.
# Provably Secure ECC-Based Anonymous Authentication and Key Agreement for IoT
## 5 Security Analysis
### Descriptive Security Analysis  
#### 5.2.1 No Key Escrow Issues  
During registration, \(S\) obtains the long-term private key, \(k_{s}=(r_{s}+r_{ta}^{s})\) mod \(q\). TA only generates the partial private key \(r_{ta}^{s}\), which avoids the key escrow problems. The long-term private key of SP is similar.