esa-sceva/satcom-chunk-collection huggingface dataset:
# Assessing the Performance of Different Grains in Gluten-Free Bread Applications
## 3 Results and Discussion
### Physical Properties of Flows  
The granularity of the flour samples is an important physical parameter because of the high influence on the quality of the bakery products. The granularity of the flours was estimated by determining the tailing and sieve fractions on a set of sieves with mesh aperture ranging from 500 to 125 \(\upmu\)m, and the fineness modulus.  
The sorghum and millet flours had highest percentage of particles with size between 125 and 315 \(\upmu\)m, of 80.7 and 74.9%, respectively (Table 2). In case of rice flour highest percentage of particles had larger size, ranging between 315 and 500 \(\upmu\)m, while in case of quinoa flour the particles size was most homogenous, even if the percentage of particles with size between 125 and 315 \(\upmu\)m was about two times higher than of those between 315 and 500 \(\upmu\)m, and three times higher than of those with size less than 125 \(\upmu\)m. The higher percentage of larger particles in case of rice flour resulted in higher fineness module (of 2.85) compared to the rest of flours. Sorghum flour had the lowest percentage of particles higher than 315 \(\upmu\)m and the lowest fineness module of 1.63.  
The fineness module is a measure of the distribution of fine and coarse particles in the analyzed sample, and can be influenced on one hand by grains related factors such as compactness of the endosperm, composition and texture of the pericarp and embryo, and by the milling method on the other hand. Taking into account that sorghum, millet and rice flours are commercial flours, it was not possible to factor the effect of grinding on the particle size distribution. Anyway, the difference between the values of the fineness modulus of the investigated flour might be due to the differences in terms of compactness of the rice endosperm.  
The starch damaged of sorghum flour (8.17%) was higher than other flows (3.85-4.44%) (Table 2). A positive correlation of 0.87 was registered between the fineness module and damaged starch (\(p<0.05\)).  
The color parameters of the investigated flours are presented in Table 2. The lowest lightness values (L*) were obtained in case of quinoa and sorghum flours. Sorghum flour presented the highest value of redness (a*) and lowest values of yellowness (b*), chroma (C*) and hue angle (h\({}^{\circ}\)), and most probably these values might be explained by the presence of colored polyphenics such as tannins and anthocyanins [17]. On the other hand, the higher values of yellowness (b*) registered in case of quinoa, millet and rice flour might be explained by the presence of carotenoids in these samples [39].
# Mechanical Behavior of Bi-Layer and Dispersion Coatings
## 2 Materials and Methods
### Nanoindentation Studies  
Nanoindentation tests were performed with the NanoTest(tm) Vantage (Micro Materials, Wrexham, Great Britain) equipment, except for the MWCNTs reference coating which was measured with the nanoindentation tester NHT\({}^{3}\)([PERSON], Buchs, Switzerland), equipped with an optical microscope. All samples were tested using a Berkovich three-sided pyramidal diamond probe. The combined samples: the MWCNTs/TiO2 and the MWCNTs_Cu coatings were measured in twenty-five (5 \(\times\) 5) points, while the MWCNTs reference coating was tested in the best place, based on optical microscopy observation. The measurements were carried out according to a test method following the ISO 14577 standard (the maximum applied force: 10 mN, the loading and unloading rate: 20 s, the dwell period at maximum load: 10 s). The distances between the subsequent indents were 20 \(\upmu\)m. The load-displacement curve was determined by the Oliver and Pharr method, and surface hardness (H), reduced Young's modulus (Er), elastic and plastic deformation energies were calculated using the integrated software. Young's modulus (E) parameter was estimated based on the reduced Young's modulus (Er) parameter and the Poisson's ratio (v). Assuming the MWCNTs/TiO2 and MWCNTs_Cu coatings as unidirectional composite materials, the values of v, E, and H parameters were calculated from the Halpin-Tsai (H-P) model, explained in our previous publication [47]. The volume fraction was calculated according to [48] and assuming densities of 2.10 g/cm\({}^{3}\)[49], 4.23 g/cm\({}^{3}\)[50], and 8.94 g/cm\({}^{3}\)[51] for MWCNTs, TiO2, and nanoCu, respectively.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Coating** & **Substrate** & **Deposited Materials** & \begin{tabular}{c} **Content of Component** \\ **in a Bath (wt. pct.)** \\ \end{tabular} & \begin{tabular}{c} **EPD Time** \\ **(min)** \\ \end{tabular} & \
\begin{tabular}{c} **EPD Voltage** \\ **(V)** \\ \end{tabular} \\ \hline MWCNTs & Ti Grade II & MWCNTs & 0.25 & 1 & 20 \\ MWCNTs_TiO2 & Ti Grade II &
\begin{tabular}{c} (I) MWCNTs \\ (II) TiO2 \\ \end{tabular} & 0.30 & 4 & 50 \\ MWCNTs/Cu & Ti Grade II & MWCNTs + nanoCu & 0.25 & 4 & 50 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Parameters of synthesis of coatings.  
The v values of 0.254 and 0.251 were assessed for the MWCNTs/TiO\({}_{2}\) and MWCNTs_Cu coating, respectively.
# The Impact of Contact Force on Signal Quality Indices in Photoplethysmography Measurements
## 4 Results
### Zero-Crossing Rate (\(Z_{SQI}\)) Analysis  
Table 4 shows the descriptive statistics of the \(Z_{SQI}\). The mean and median values across the CF range from 0 to 0.8 are consistent, oscillating primarily around 0.02. This  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**CF Range** & **Mean** & **Std** & **Min** & **Max** & **Median** \\ \hline
0–0.2 & 5.80 & 23.11 & \(-\)1.17 & 105.39 & \(-\)0.60 \\
0.2–0.4 & \(-\)0.03 & 0.99 & \(-\)0.99 & 3.21 & \(-\)0.36 \\
**0.4–0.6** & **0.29** & **3.07** & \(-\)**1.16** & **13.16** & \(-\)**0.64** \\
0.6–0.8 & 5.46 & 19.25 & \(-\)0.87 & 87.18 & 0.19 \\
0.8–1.0 & 16.81 & 27.10 & 1.30 & 110.18 & 3.93 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Descriptive statistics of \(K_{SQI}\) by CF range, highlighting in bold the identified optimal range.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**CF Range** & **Mean** & **Std** & **Min** & **Max** & **Median** \\ \hline
0–0.2 & 0.52 & 0.25 & 0.09 & 0.82 & 0.64 \\
0.2–0.4 & 0.55 & 0.26 & 0.07 & 0.88 & 0.67 \\
**0.4–0.6** & **0.56** & **0.26** & **0.09** & **0.90** & **0.69** \\
0.6–0.8 & 0.54 & 0.24 & 0.12 & 0.90 & 0.62 \\
0.8–1.0 & 0.51 & 0.22 & 0.18 & 0.91 & 0.57 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Descriptive statistics of \(R_{SQI}\) by CF range, highlighting in bold the identified optimal range.  
suggests that, regardless of the applied pressure, the number of zero crossings in PPG signals tends to be stable. This indicates that the signals maintain a basic level of periodicity and stability across varied contact conditions. The low SD (0.01) across these ranges reflects minimal variability in the zero-crossing rate between different signals within the same CF range. In the higher range of CF (0.8-1.0), the signal shows more significant variability due to the decrease in signal quality, evidenced by a lower mean and higher maximum value of the \(Z_{SQI}\). This suggests that excessive CF introduces unwanted noise and jitter. The CF range of 0.4-0.6 appears to be optimal due to its stability and low variability, with a slightly higher maximum that may indicate a clean signal with useful details.
## 8 Conclusions  
Optical backscatter reflectometry is an easy to use method to obtain information about the strain inside large cast structures during the hardening process of the casting material, like, e.g., cement or a polymer. However, the optical fiber used for these strain measurements may be subject to physical conditions that will not allow obtaining meaningful data with the regular post-processing methods used nowadays.  
In this work, an experimental setup is presented to attain such conditions on the optical fiber in epoxy. It is shown that the strain data deteriorate significantly, before the physical limits of the OBR instrument used are reached.  
Without the need for new equipment or software, we propose a new way to approach the data analysis to retrieve the strain values. This proposed method determines the strain differences from one measurement to the next instead of the absolute strain compared to before the measurement started. Adding up these strain differences yields the absolute strain for a given measurement.  
As long as the traditional method returns meaningful data, it is shown that the new method yields the same strain values. The newly-developed running reference approach, however, works even when the traditional method fails to deliver results.  
Four challenging issues of the new approach are discussed and how these can easily be overcome by automatizing the involved steps.  
The software used by the authors is provided to the community. It is extensively documented and commented, free of charge and published under the GPL Version 3 [54]. Among other things, this license gives the user the right to change the software according to his/her requirements without the need to ask the authors for allowance. By providing these simple tools under this license, we hope to encourage interested scientists and engineers to apply the running reference analysis method when handling challenging OBR data.
# The Free-Energy Landscape of a Mechanically Bistable DNA Origami
## 1 Introduction  
The DNA origami technique [1, 2] has emerged as a powerful approach to create self-assembled nanostructures and nanodevices. The potential applications of origami structures include nanofabrication, nanophotonics and nanoelectronics, multi-functional materials, catalysis, molecular machines, biosensing, drug delivery and biophysics [3, 4, 5, 6]. One area of increasing interest is their use as nanoscale mechanical devices [7]. In this field of DNA \"mechanotechnology\" [8] DNA constructs are used to generate [9, 10, 11], transmit [12] and sense [13] nanoscale forces. One approach is through the use of flexible DNA origami that can undergo large-scale structural changes [14, 15, 16]; for example, an externally-actuated shape change could be used to apply a force [17], or a force could be sensed through the change in structure it induces [18, 19, 20].  
For such applications, it is important to fully understand the shape changes that origamis can undergo and how the thermodynamics and mechanics of these shape changes can be controlled through the origami design. In this regard, computational approaches have the potential to play an important role as they can provide direct insight into how the microscopic features of the design impact the overall properties of the origami [21, 22, 23].  
Here, we explore these issues further by providing a detailed simulation analysis of the jointed DNA origami introduced by [PERSON] et al. [24] that is designed to be bistable with the free-energy barrier between the two stable states being a result of the internal mechanical stresses associated with intermediate states. Although this is a proof-of-principle example, the potential utility of nanodevices that can switch between conformations in response to some (environmental) perturbation is clear, for example, as biosensors. Observations of ensembles of origami structures by electron microscopy seem to have confirmed the essential bistability of the design. In particular, we will compute the free-energy landscape of this system and explore the role of the properties of the individual joints in determiningthe overall behaviour. The study will raise interesting questions about the potential role of defects on the properties of these origami systems.
# A Digital Twin-Based Approach for Detecting Cyber-Physical Attacks in ICS Using Knowledge Discovery
## 2 Background
### Process Logs and Models
#### 2.5.1 Petri Nets  
A Petri net is a mathematical modeling language used for describing distributed systems and their processes. Petri nets are composed of two types of nodes, namely, places and transitions. Places represent conditions or states, while transitions represent events that may change the state. Directed arcs connect places to transitions (and vice versa), dictating the flow of control in the system.  
**Definition 4**.: _Formally, a Petri net is a tuple \(PN=(P,T,F)\), where:_  
* \(P\) _is a finite set of places,_
* \(T\) _is a finite set of transitions (disjoint from_ \(P\)_),_
* \(F\subseteq(P\times T)\cup(T\times P)\) _is the set of directed arcs, indicating how places and transitions are connected._  
Petri nets are particularly well suited for modeling concurrent, parallel, and synchronized activities within a workflow process. They allow for the discovery of causal relationships and control flows that can be derived from event logs.
## 2 Materials and Methods
### Analysis Method  
Notably, the turbidity and suspended-sediment concentration are closely related; however, standard conventions for calibrating methods are yet to be proposed [26]. The turbidity is an optical property of water, and water transparency is known to decrease in the presence of undissolved particles. This can be commonly observed using repellometry [27]. Overall, to estimate the concentrations of suspended sediments more accurately, establishing a precise relationship between the two is essential. However, a single accurate formal method for obtaining this turbidity-concentration relationship is not available; therefore, three commonly employed forms were adopted here: (1) the power law, (2) second-order polynomial, and (3) first-order polynomial. In a recent study, turbidity was predicted based on water color changes (RGB value), following which the suspended-sediment concentration was estimated based on the predicted turbidity [23]. In this study, a multilinear regression model that could directly predict the change in concentration based on color change was developed. In particular, after analyzing the relationship between concentration and turbidity, a model was developed using the form presenting the best correlation. Finally, the suspended-sediment concentration predicted by the model was compared with other predictions based on the turbidity-concentration relationship. The developed multiple regression models were evaluated based on the root-mean-square error (_RMSE_) (Equation (1)), and the variance inflation factor (_VIF_) in multicollinearity problems was calculated using Equation (2).  
\[RMSE=\sqrt{\frac{1}{n}{\sum_{i=1}^{n}(x_{i}-y_{i})^{2}}} \tag{1}\]  
\[VIF=\sqrt{\frac{1}{1-R^{2}}} \tag{2}\]
# 2D-Unitary ESPRIT Based Multi-Target Joint Range and Velocity Estimation Algorithm for FMCW Radar
## 1 Introduction
The 2D-ESPRIT algorithm [22; 23] derives the 2D frequency parameters by utilizing the rotation invariance and translation invariance of the 2D signal matrix. The Modified Matrix Enhancement and Matrix Pencil (MMEMP) algorithm [24; 25] is an improvement of the Matrix Enhancement and Matrix Pencil (MEMP) algorithm [26], which allows joint estimation of 2D frequencies. However, the above methods [18; 19; 20; 21; 22; 23; 24; 25; 26] suffer from high computational complexity, limited accuracy of pairing, and low resolution in range-velocity estimation. In order to deal with the problems described above, this paper proposes a 2D-Unitary ESPRIT-based joint range and velocity estimation algorithm for multiple targets. First, the IF signal is constructed into a 2D virtual array signal matrix and preprocessed by the 2D-spatial smoothing technique [27; 28]. Then, the preprocessed matrix signal is converted into a real signal matrix, and two real-valued matrixes associated with the range and velocity are extracted using the rotation invariance of this real signal subspace. Next, a new complex matrix is constructed by using the above two real-valued matrixes as its real and imaginary parts. Finally, the 2D-Unitary ESPRIT algorithm [29] is utilized on this complex matrix to obtain automatic pairing of the range-velocity estimates of multiple targets. The main contributions of this article are as follows. The 2D-Unitary ESPRIT algorithm [29; 30] is commonly utilized for 2D direction of arrival (DOA) estimation in array signals. In this paper, we employ this algorithm for range and velocity estimation in FMCW radar. The 1D IF frequency signal is constructed into a 2D virtual array signal, this virtual array signal is reconstructed as a new complex matrix using a 2D-spatial smoothing technique to apply the 2D-Unitary ESPRIT algorithm for 2D frequency estimation. It is worth noting that this part of the method is also applicable to the 2D-Root MUSIC algorithm. The rest of this paper is organized as follows. In Section 2, the signal model of the FMCW radar is described and the range and velocity estimation principle is derived. In Section 3, the 2D-Unitary ESPRIT-based joint range and velocity estimation algorithm of multiple targets is proposed. In Section 4, simulation results are conducted to evaluate the performance of the proposed algorithm. Finally, conclusions are presented in Section 5.
# Smart Bandwidth Assignation in an Underlay Cellular Network for Internet of Vehicles
## 3 Problem Definition
### Problem Formulation  
This paper addresses an efficient radio resource assignment in an underlay cellular network where V-UEs communications coexist with cellular C-UEs communications. We denote this assignment efficient because we aim for improving the spectral efficiency of the underlay network by maximizing the number of users served with the minimum number of radio resources.  
In the same way as in [16], we study two different resource sharing situations: (1) SPC when V-UE asks for an infotainment transmission and (2) MPC for safety, management and efficiency ITS applications transmissions. However, in this paper we will focus only on transmission on CAM transmissions, which follow the second situation. We decided to center this research in CAMs because information distributed by CAM Management is commonly used by related use cases, e.g., Approaching Emergency Vehicle or Slow Vehicle Warning, and therefore the CAM Management is a mandatory facility [28].  
Therefore, we will have a multi-objective optimization problem with two different terms: one related with C-UE optimization conditions and the other one associated to CAM transmissions QoS requirements. The first term is defined by the maximization of C-UE's sum-rate Equation (1), which is a common performance requirement.  
\[Th^{C-UE}=\sum_{n=1}^{N}\log_{2}(1+\varepsilon_{n}^{c}) \tag{1}\]  
being \(\varepsilon_{n}^{c}\) the SINR (Signal-to-Interference-plus-Noise Ratio) of the C-UE-eNodeB link.  
On the other hand, CAM's QoS requirements can be defined as a MPC problem, so the other term of the optimization problem is defined by Equation (2)  
\[Th^{D2D}=min_{ke\{1,\ldots,M\}}\log_{2}(1+\varepsilon_{m}^{d}) \tag{2}\]
## 3 Deformation and Failure Characteristics of Surrounding Rock of Roadway
### Analysis of Roadway Damaged Characteristics  
The maximum load capacities of the cable and rod bolt supports are 454 kN and 240 kN, respectively. They were installed in sections. Failure of a supporting structure can be classified into six main categories: bending of I-beams, ripping of steel strips, fracture of bolts and anchor cables, and loosening of bolts and anchor cables. Most broken bolts fail due to tension, as shown in Figure 6a,b. In the anchor cable, only one or two steel strands break instead of the entire strand, as shown in Figure 6c. Loose anchor bolts or cables often detach the tray from the roof or coal wall surface (Figure 6d,f), and some loose anchor cables are secured to the tray (Figure 6e). The most common cause of roof steel strip tearing is shear failure (Figure 6g). Bending failure of the I-beam support structure is often caused by significant ceiling sinking during roadway excavation (Figure 6h).  
Figure 6: Characterization of damage to roadway support structures. (**a**,**b**) broken bolt; (**c**) broken cable; (**d**) loose bolt; (**e**,**f**) loose cables in coal sides and the roof; (**g**) tearing steel belt; (**h**) curve steel beam.  
Despite implementing the expanding support strength plan to prevent deformation of the surrounding rock in the 1409 airway, the combined effect of the anchor, mesh, and cable-I-steel support is still not optimal. Based on the results of above-ground pressure monitoring, the roadway continues to experience significant deformation, roof separation, and a high load on the top anchor cable throughout the construction process. After closely examining the challenging geological conditions, support configuration, and damage to adjacent rocks in the 1409 airway, the following main problems were identified:  
1. The support from the upper wall has limited effectiveness. The bottom plate lacks support, and the support strength on the sides is significantly lower than the overall support strength on the roof. As a result, the roof, floor, and sides of the roadway gradually deform under the high mining stress.
2. There are significant differences between roof bolts and anchor cables. As the support strength increases during roadway excavation, the difference in support strength between anchor cables and anchor bolts becomes more pronounced. This leads to excessive stress on the anchor cables and very low stress on the anchor bolts during the initial stages of roadway construction. Additionally, the small anchoring area of a single anchor cable and the practice of combining roof anchor cables greatly reduce the effectiveness of the anchor cables.
# Hybrid Encoding Scheme for AMBTC Compressed Images Using Ternary Representation Technique
## 5 Conclusions  
In this paper, we propose a hybrid encoding scheme for AMBTC compressed images using a ternary representation technique. Considering that the number of quantized values greatly affects the quality of the reconstructed image, the proposed method classifies image blocks into flat, smooth, and complex. These three types of blocks are encoded by using one, two, or three quantized values. Flat blocks require no bitmap, whereas smooth and complex blocks require binary and ternary maps, respectively, to record the quantized  
Figure 8: Visual quality comparisons of the proposed method and that of [PERSON] et al.  
values to be used to reconstruct the corresponding pixels. A sophisticated design indicator is prepended before the code stream of a block to signify the block type. The proposed method achieves a better image quality than that of prior works with a smaller bitrate. The effectiveness of the proposed method is observed from the experimental results. Note that although the \(k\)-means algorithm used in the proposed method may require slightly higher computational cost than that of the discrete cosine transform (DCT) based methods, it is only applied to smooth blocks in the encoding stage to obtain the representative bitmaps rather than the whole image. Furthermore, the \(k\)-means algorithm does not need to be applied again during decoding. Therefore, the overall computational cost of the proposed method is smaller than that of DCT-based compression methods.  
[PERSON], [PERSON], and [PERSON] contributed to the conceptualization, methodology, and writing of this paper. [PERSON] and [PERSON] conceived the simulation setup, formal analysis and conducted the in-vestigation. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
Data Availability StatementData is contained within the article.  
The authors declare no conflict of interest.