esa-sceva/satcom-chunk-collection huggingface dataset:
# Estimating the Local Radius of Convergence for Picard Iteration
## 4 The Algorithm  
In finite dimensional spaces the condition of quasi-expansivity is superfluous, since the first two conditions of Theorem 1 are sufficient for the convergence of the Picard iteration. Therefore, in finite dimensional spaces, supposing that the condition (i) of Theorem 1 is fulfilled, we can develop the following algorithm to estimate the local radius of convergence:  
Find the largest value for \(r_{0}\) such that  
\[m=\min_{x\in B_{r_{0}}}\frac{\langle x-T(x),x-p\rangle}{\|x-T(x)\|^{2}}, \tag{6}\]  
and \(m>0.5\).  
This procedure involves the following main processing:  
1. Apply a line search algorithm (for example of the type half-step algorithm) on the positive real axis to find the largest value for \(r_{0}\);
2. At every step of 1 solve the constraint optimization problem (6) and verify the condition \(m>0.5\).  
The main processing of this algorithm is the solution of the constraint optimization problem (6). Therefore we need to use a global constrained optimization method which, generally, has a considerable computational effort. In our experiences we used a population-based metaheuristic method in combination with a local search method.  
The algorithm involves an outer iteration (for line search procedure) and an inner iteration (for solving the constrained optimization problem). In \(N\)-dimensional spaces, every step of the inner iteration involves \(2N\) evaluations of some functions of \(N\) variables each (the components of \(T\)), for the computation of \(\langle x-T(x),x-p\rangle\) and \(\|x-T(x)\|^{2}\).  
**Remark 2**.: _Most of the algorithms for estimation the radius of convergence involve the computation of the optimal Holder/Lipschitz constant of the derivative of \(T\). This implies \(N^{2}\) evaluations of some functions in \(N\) variable each (the components of the derivative of \(T\)). Therefore a step of inner iteration involves a polynomial complexity of order 2 combined with the complexity of computing the components of \(T\). The proposed algorithm involves \(2N\) evaluations of components of \(T\), and, presumptively has a lower complexity. However this estimation has only a relative worth, because the main influence on the computational effort is exerted by the global constrained optimization method, which, as it is well known, is a very expensive computation. A good implementation of these algorithms have some positive impact on the computational process._
## 2 The Smart Angel Project
### Overall Description of the Smart Angel System  
In Figure 1, the main components of the Smart Angel platform are outlined: a set of Serious Games to support the development of basic skills, a monitoring system for the tutors and a set of apps developed for Smart Phones. A central cloud based platform collects all the users' data and connects the other elements of the system.  
The games, based on an immersive virtual reality approach, aim at supporting and stimulating the development of some basic skills needed for independent mobility in town, and are used in the first steps towards independence. All the games exchange data with the central cloud system to guarantee  
Figure 1: Smart Angel main components.  
uniqueness of the user profile and store all the performance data for later use. Nevertheless, they can be used on a standalone computer and automatically synchronize as soon as the connection becomes available.  
When the users start being more independent, the monitoring system becomes a sort of guardian angel, standing by its user and offering help and support when needed without being intrusive. The mobile devices constantly exchange data with the cloud system: storing usage information, retrieving all the needed data and keeping both the tutor and the final user updated. The monitoring system, used by the tutors, allows having real time information on all the end users, configuring the users' systems and analysing the usage data collected in the cloud system.  
The intellectually disabled people involved in Smart Angel have played a central role in all the different phases of the project. They have been actively involved right from the beginning in the user needs collection and analysis. In particular, a collaborative and participatory process has been carried out [17], involving a continuous and intensive dialogue among all the stakeholders (tutors, end users, developers, researchers).  
Based on the user requirements, first prototypes of the Serious Games and the monitoring system have been developed and an initial experimental phase has started with a continuous feedback loop in order to reflect the real needs of the target users on all the stages of the project.
## 3 Impedance-Based Assist-as-Needed Controller
### Rehabilitation Training Mode of the Controller  
According to the analysis in Section 3 (A), the parameters of the proposed AAN controller contain the radius of the virtual channel of the FTR \(R_{W}\), the upper and lower limits of the stiffness field \(K_{0}\) and \(K_{1}\), the assistance factor \(K_{t}\), and the stiffness inside the FTR \(K_{2}\), which can make the controller show different performances by adjusting these parameters. Different controller parameters could satisfy the training requirement of patients at different rehabilitation stages. There are four rehabilitation training modes that could be realized through configuration and combination of those parameters above, namely passive rehabilitation training, assistant rehabilitation training, active rehabilitation training, and resistant rehabilitation training. The specific controller parameters of those training modes are shown in Table 1.  
As can be seen from Table 1, the robot moves with a high stiffness value with no fault tolerance without considering the participation of the patient in the passive training mode. The robot moves the patient's arm to finish the training tasks on a fixed trajectory, which is suitable for patients in the early recovery stage. The controller provides a virtual FTR in the assistant training mode. The patient has complete freedom within the FTR and the robot does not provide any assistance force, while the controller will generate a series of columnar stiffness walls to provide the time-varied assistance force according to the patient's functional ability when deviating from the FTR. It is suitable for patients with partial control ability of the upper limb in the middle and late rehabilitation stages. The radius of the FTR is infinite and the stiffness of the virtual stiffness wall is zero in the active training mode. The robot is in a completely compliant and backward-driven state and the patient has complete freedom. It is suitable for patients who have a certain upper limb motor ability and need to conduct movement stability training at the later rehabilitation stage. The controller has the characteristic of obstructing the patient's movement in the resistant training mode, and it requires a certain amount of strength for the patients to overcome the obstacles to finish the rehabilitation task. It is suitable for patients in the later rehabilitation stage and patients who need to further strengthen their muscle force.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Mode** & \(R_{W}\) **(mm)** & \(K_{0}\) **(N/m)** & \(K_{1}\) **(N/m)** & \(K_{t}\) **(N/m)** & \(K_{2}\) **(N/m)** \\ \hline Passive & 0 & Max & Max & Max & Max \\ Assistant & Const & Const & Const & Const & 0 \\ Active & \(\infty\) & 0 & 0 & Const & 0 \\ Resistant & Const & Const & Const & Const & Const \\ \hline \hline \end{tabular}
\end{table}
Table 1: The controller parameters of different rehabilitation training modes.  
Figure 8: The diagram control scheme of the proposed assist-as-needed controller.
## 3 Results and Discussion
### Oxidative Stability (OS) of the Edible Fixed Oils  
The oxidation induction times (OIT) of oil samples were determined by Rancimat measurements and used as an index for the OS of edible fixed oils. The oxidation induction times of the edible fixed oils are provided in Table 2. The oxidation induction times of oil samples ranged from 0.12 to 69.3 h. Virgin coconut oil and sea buckthorn oil had the highest OIT values (69.3 h and 31.9 h, respectively) among the other oils, mainly due to the considerable percentage of saturated fatty acids (94.10% and 36.91%, respectively). Linseed, chia seed, pine cone, and walnut oils were the least stable oils against oxidation, probably attributed to their higher polyunsaturated fatty acid content (>60%) (Table 2). Interestingly, despite their high polyunsaturated fatty acid percentage, evening primrose and grape seed oils had similar OIT values (1.15 h and 1.03 h, respectively) and were higher than the above-mentioned oils, possibly due to the presence of natural antioxidants such astocopherol and b-carotene [18; 31; 32].  
The existing differences in the fatty acid composition of the edible fixed oils may affect their oxidative stability since edible oils with a high amount of polyunsaturated fatty acids are more susceptible to oxidation than oils with monounsaturated or saturated fatty acids. Monounsaturated fatty acids have fewer bonds available to react with oxygen and, therefore, oxidize [33]. More specifically, the rate of oxidation increases in relation to the degree of PUFAs, with linolenic acid oxidizing twice as fast as linoleic acid and 25 times faster than oleic acid [34]. In the case of the present study, almond, hazelnut, avocado,and macadamia oils containing more than 70% monounsaturated fatty acids presented relatively high OIT values (3.44 h, 2.60 h, 10.2 h, and 7.75 h, respectively).
## 4 Results  
In this section, the performance of the proposed system in terms of path loss, received power, channel capacity, and outage probability will be demonstrated. To validate the accuracy of the derived theoretical expression in the previous sections, a numerical simulation is conducted using MATLAB(r) software, version R2023a. Since weather conditions have a significant impact on outdoor V2I-VLC systems, they are considered in the discussion. In the simulation, corresponding to each value of \(I_{V_{1}-PD}\), \(3\times 10^{6}\) channels are considered. In addition, all the simulation parameters related to the proposed V2I-VLC system are referred to in Table 2.
## 4 Results
### Economic Feasibility  
In Table 5, the results of Question 6 (Appendix A, Table A1) are displayed, listing the economic barriers of the DSP concept. According to Shapiro-Wilk and Chi-Square testing, the null hypothesis  
Figure 4: Percentages of printable components according to their size (printed as one component). m-PBF (metal-based PBF), p-PBF (plastic-based PBF), p-BJ (plastic-based Binder Jetting), MJ (Material Jetting), m-BJ (metal-based Binder Jetting), VP (Vat Photopolymerization), FE (Filament-based Extrusion).  
is in most cases not fulfilled. Costs for DSP compared to traditional manufacturing were considered as the main barrier, followed by costs needed to be spent to establish an environment for additively manufactured DSP, and insufficient employees' skills.  
The Mann-Whitney test (Appendix A, Figure A1) leads to the claim that investment costs are seen as a more crucial aspect comparing medium (mean 4.14) to very large companies (mean 2.83; \(p=0.026\)). Furthermore, insufficient skills of employees are perceived as a larger challenge for large (mean 3.44) than for very large (mean 2; \(p=0.048\)) and for micro (mean 3.19) compared to very large companies (mean 2; \(p=0.05\)). Also, the employees' skills are considered as significantly not sufficient if 3D printing is part of the organization's supply chain (means 2.7 and 3.56; \(p=0.033\)).  
It seems that very large companies can easily accumulate the required investment costs required by DSP implementations. Medium-sized companies see greater challenges to fund a DSP IT-system, which could arise from a more powerful monetary situation of large corporations. Additionally, large corporations have better access to hiring employees with advanced skills. The reason behind the observation that employees' skills are described as insufficient, especially when the organization uses 3D printed components in their supply network, could lie in the fact that previously unknown employee skills are needed when applying 3D printing for end-use components. High AM production costs must be considered a main obstacle, especially for the mass production of standard components. In most cases, AM only provides advantages for small batch numbers of highly complex products. This is a limitation which is not likely to change drastically in the following years.
## 5 Application of Self-Sensing Materials for
### Cathodic Protection System  
Inherently, reinforced cementitious composites benefit from protection against corrosion due to the formation of protective oxide films around steel rebars, a result of the high alkalinity nature of cementitious composites. However, the ingress of chloride ions and carbonation formation, originating from harsh environmental conditions, can deteriorate the protective layer and lead to rebar corrosion within the cementitious composites [274]. Corrosion stands as a significant challenge in civil engineering projects, posing risks to infrastructure safety due to corrosion-induced cracks and degradation [275]. For instance, reinforced cementitious composites utilized in civil engineering structures such as bridges, tunnels, railways, and reinforced road pavements are susceptible to corrosion induced by the infiltration of sodium chloride ions [276]. It is noteworthy that reinforced cementitious composite elements used in transportation infrastructure are particularly vulnerable to corrosion due to the salt deicing technique employed in cold regions. Additionally, coastal transportation infrastructures are highly prone to premature degradation and damage.  
In light of this, anticorrosion measures play a crucial role in enhancing the safety and service life of structural elements. Various corrosion protection systems based on electrochemical methods such as desalination, realkalization, cathodic protection, and surface treatment are widely employed [277]. CP systems are categorized into sacrificial anode cathodic protection (SACP) and impressed current cathodic protection (ICCP) [118]. However, materials utilized as anodes in CP systems, including activated titanium mesh, metalized zinc, coke breeze asphalt, and conductive organic paints, often suffer from high cost, low durability, and compatibility issues with concrete. To address these deficiencies, electrically conductive cementitious composites have been proposed [278]. Multifunctional cementitious composites incorporating conductive fillers can serve as auxiliary anodes in cathodic protection systems, safeguarding reinforced cementitious composites against corrosion phenomena [279]. For example, electrically conductive cementitious composites incorporating activated carbon were employed for SACP in a coastal bridge to protect piers against corrosion [280]. Results from this real-world project demonstrated promising outcomes, highlighting the potential application of electrically conductive cementitious composites for CP. Similarly, the use of electrically conductive cementitious composites for ICCP systems has been evaluated in previous studies [279].
# Defining Blood Plasma and Serum Metabolome by GC-MS
## 5 Workflow of GC-MS Analysis of Blood Metabolome
### Gas Chromatography
#### 5.2.4 Retention Times and Indices  
Depending on the column's stationary phase, various intermolecular interactions (Van der Waals and dipole-dipole forces, hydrogen bonding, etc.) and polarity of individual compounds of the mixture will determine the strength of its retaining in the column. The stronger interaction between column and compound, the longer its retention time (RT). Compounds with lower boiling points and polarity tend to rapidly transfer through the column and have shorter RTs [126]. However, RT depends not only on the physical-chemical properties of the certain compound but also on various technological aspects of the CG method applied (e.g., column characteristics, thermal conditions, etc.). One of the concepts allowing identification and increasing the convergence of interlaboratory results consists in fixing all possible parameters of the system (the column used, the nature and flow of the carrier gas, temperature conditions) so that the absolute RTs carry information at a qualitative level. Nevertheless, it is difficult to imagine standardization of this level in the entire metabolomics community.  
An alternative well-established practice suggests using retention indices (RI) for standardized comparison between different analytical parameters and different GC systems used in different laboratories.  
The Kovats index is a pioneer among retention indexes built on a series of n-alkanes (C7-C40, C8-C20, C21-C40) [127]. In addition to n-alkanes, the series of fatty acid methyl esters (FAME) or the so-called M-series, which consists of alkyl-bis-(trifluoromethyl)-phosphine sulfides (CF\({}_{3}\))\({}_{2}\)P(S)\({}_{\text{C}}\)H\({}_{2\text{n+1}}\) are used [128]. A homologous batch is added to each sample. Each homolog has a specific point on the retention index scale, and all other compounds are assigned a specific index based on the \"coordinates\" of the standards. Thus, unlike absolute RT, the compound index between the two reference compounds will remain constant even if the RTs of these analytes change.  
Using RI as the only parameter for identifying a compound is risky because RI is not a unique characteristic inherent in only one and no other chemical substance. However, RI is excellent for orthogonal confirmation of identification, supported by mass spectrometry results [129].
# Suitability of Aerial Photogrammetry for Dump Documentation and Volume Determination in Large Areas
## 1 Introduction
The advantages of this method consist of the very short time for measurement, fast and automated data processing procedures, sufficient precision, the non-contact method of measuring, and the minimized working time in the factory [3; 18; 23]. However, it was necessary to confirm the suitability of the digital aerial photogrammetry method as a primary method for future measurements regarding comparability and reliability of results with previous measurements. For this purpose, a one-time validation project of heap documentation and volume determination was realised with data collected by aerial photogrammetry compared to the reference method TLS and GNSS as previously used methods. This case study presents verifying the appropriateness of the photogrammetric techniques for the documentation and volume determining of material deposited in dumps of larger scale. The requirements for the measurement and processing methods are determined in particular by continuous operation in the plant (and therefore also in a landfill), the minimal forced shutdown of loaders, and the adequate accuracy of the determined volumes.
## 6 Conclusions  
Our novel neural network approach with fleet learning offers encouraging findings. The voltage prediction is in good accordance with the measured values. There is no significant difference between training and validation sections, indicating that the model has correctly learned the underlying battery behavior. Within a first proof-of-concept, we have also shown that the fleet model structure enables the information transfer between devices, lowering the RMSE compared to model learning with a single device. The model and training design can also assess capacity and resistance trends and differentiate between devices.
# Landslide Susceptibility Modeling Using a Deep Random Neural Network
## 4 Results and Discussion
### Influence of Critical Parameter Settings  
In this subsection, the impact of the important parameters of the DRNN on landslide modeling accuracy is studied. These parameters mainly include \(L\) (the number of hidden layers in the random hidden block), \(R_{node}\) (the node dropping ratio), and \(R_{layer}\) (the layer dropping ratio).  
In terms of hidden layers, all performance metrics increase first and then decrease as \(L\) increases from 8 to 20, reaching the maximum value when \(L=16\) (Figure 10a). Increasing hidden layers means increasing the model's complexity, which is conducive to the fitting power [81]. However, overemphasizing the fitting power may damage the generalization of landslide modeling. Thus, the number of hidden layers should be set to a moderate value. The random strategy of DRNN makes expanding the model's depth to 20 layers feasible while avoiding overfitting. This development may be helpful for future landslide modeling studies exploring deeper network models.  
The results with respect to \(R_{node}\) and \(R_{layer}\) are shown in Figure 10b,c, which present some similarities. The model variants of DRNN achieve the highest landslide modeling accuracies at moderate levels of \(R_{node}\) and \(R_{layer}\). The results are reasonable because  
Figure 10: Influence of critical parameters: (**a**) Hidden layers, (**b**) Node dropping ratio, (**c**) Layer dropping ratio.  
Figure 9: Robustness test on the training data size: (**a**) Changes in K values, (**b**) Changes in OA values.  
dropping too many nodes or layers may damage the model's structure, whereas too slight of a perturbation is insufficient for realizing effective regularization.
# Wideband Millimeter-Wave Perforated Hemispherical Dielectric Resonator Antenna
## 3 Measurements and Discussions
### An HDRA Prototype with a Polyimide Coating  
The hemispherical DRA element has been manufactured by the T-CERAM company (Hradec Kralove, Czech Republic) using alumina with a fabrication tolerance of 0.06 mm as well as a dielectric constant of \(\varepsilon_{\mathrm{r1}}=10\) and loss tangent of tan \(\delta<0.002\). The antenna's coat layer has been fabricated with the aid of 3D-printing technology at the Protolabs Company (Maple Plain, MN, USA) using polyimide material with a dialectic constant of 3.5 and a loss tangent of 0.0027. The antenna and its feed network are illustrated in Figure 14. The simulated and measured reflection coefficients are depicted in Figure 15 with close agreement between simulated and measured impedance bandwidths of 57% and 51%, respectively, with a marginal discrepancy that can be attributed to the measurements and fabrication error. These results demonstrate that a layered DRA supports a multimode operation, where the resonance modes of TE\({}_{311}\), TE\({}_{112}\), TE\({}_{511}\), and TE\({}_{312}\) have been excited at 19 GHz, 24.6 GHz, 28.6 GHz, and 33.4 GHz, respectively. In addition, Figure 16 demonstrates that adding the outer dielectric layer enhances the AR bandwidth to \(\sim\)18.2% over simulated and measured frequency ranges of 25.16 to 30.17 GHz and 25 to 30.6 GHz, respectively. Furthermore, the bandwidth improvement in the presence of the dielectric coat layer can be attributed to minimizing wave reflections at the coat-air interface, which lowers the quality factor of the antenna.  
Figure 17 presents the layered DRA's gain as a function of frequency, from which it can be noted that the maximum gain has been achieved at 29 GHz with simulated and measured peaks of 7.57 dBic and 6.9 dBic, respectively. It should be noted that the maximum gain has been achieved when the higher-order resonance mode, TE\({}_{511}\), is excited. It is worth pointing out that the drop in the measured gain could be attributed to experimental errors such as losses in the cables, SMA soldering as well as the alignment in the anechoic chambers. Figure 18 illustrates good agreement between the simulated and measured H-plane and E-plane radiation patterns at 22 GHz and 29 GHz, respectively.  
Figure 14: (**a**) Prototype of the multi-layer hemispherical DRA, and (**b**) measurements setup.