esa-sceva/satcom-chunk-collection huggingface dataset:
# Flexible DEM Model Development and Parameter Calibration for Rape Stem
## 2 Materials and Methods
### Calibration of Flexible Discrete Element Parameter for Rape Stem  
#### 2.4.1 Flexible Discrete Element Model  
The position of each spherical unit in the rigid stem model is fixed, so it cannot simulate the deformation behaviors of the stem such as bending and twisting. To address the problem wherein the rape stem is a flexible body and the rigid model cannot accurately express its mechanical characteristics, the rape stem flexible discrete element model (Figure 7) was built based on EDEM API and Hertz-Mindlin with Bonding contact model.  
Firstly, a rigid unit for the rape stem flexible model was built through spherical particle filling as shown in Figure 7a. The rape stem was approximated as a hollow structure since the internal spongy structure of the rape stem is loose and of low strength. According to the result of the rape stems' structure test, the overall diameter of the rigid discrete unit and the internal hollow core diameter were determined to be 7.0 mm and 3.0 mm, respectively. Spherical particles with a diameter of 2.0 mm were used for filling, and each rigid unit contained 24 particles. Secondly, several rigid units were arranged sequentially along their axes through the EDEM software particle factory API. Finally, the rigid units were bonded together (Figure 7c) by the Hertz-Mindlin with bonding contact model to replace the initial rape stem rigid discrete element model (Figure 7b). The rigid units are bonded to each other and able to withstand a certain amount of normal and tangential displacement. The bond will fracture when reaching the critical normal and tangen  
Figure 7: Rape stem flexible discrete element model. (**a**) Rigid discrete unit; (**b**) Rigid discrete element model; (**c**) Flexible discrete element model.  
developed rape stem flexible model can simulate a variety of mechanical behaviors such as tensile, bending, torsion, and fracture behaviors.
# Toward Improving the Reliability of Discrete Movement Recognition of sEMG Signals
## 3 Methods
### Evaluation  
Accuracy is usually used to evaluate the performance of a classifier. For classifiers with rejection options, their performance depends not only on accuracy but also on rejection rate. To differentiate the accuracy defined in conventional classifiers and the one with a rejection option, total classification accuracy (tAcc), active classification accuracy (aAcc) [27], and rejection rate [16] are used to evaluate the performance of proposed algorithms, and they are defined as follows.  
\[\text{tAcc}=\frac{\text{number of correct classifications}}{\text{total number of classifications}}\times 100\% \tag{3}\]  
\[\text{aAcc}=\frac{\text{number of correct active classification}}{\text{total number of active classification}}\times 100\% \tag{4}\]  
\[\text{rejection rate}=\frac{\text{number of rejected classifications}}{\text{total number of classifications}}\times 100\% \tag{5}\]  
where active decisions are the decisions that would lead to prostheses moves when the algorithm is applied for prostheses control. If the classifier does not reject any observations, tAcc and aAcc will be the conventional classification accuracy, and the rejection rate will be zero. When a classifier tends to reject all of the observations, tAcc will be approaching 0%, aAcc will tend to 100%, and the rejection rate will be 100%. So tAcc, aAcc, and rejection rate should be used together [39] to evaluate the performance of a classifier with a reject option. A method for comparing classifiers with reject options by sketching an accuracy rejection curve (ARC) was proposed in [40]. The ARC plots the accuracy of a classifier against its rejection rate. Given the acceptable rejection rate, the best available classifier can be selected from the ARC curve with the highest classification accuracy. Therefore, the ARC curve is also sketched when the performance of the classifier is compared.  
The method mentioned above is used to evaluate the performance of the classifier to discriminate between trained classes. To assess the ability of the classifier to reject untrained movements, leave-one-out error analysis (LEA) [37] is applied in this study. The error rate of the untrained movements is defined as follows.  
\[\text{error rate}=\frac{\text{number of active decisions}}{\text{number of total decisions}}\times 100\% \tag{6}\]  
For each untrained movement, if the classifier assigns a known class label to it, the decision is an active decision, which means it is an error. So, this index can be used to evaluate the capability of the classifier to reject unknown movement patterns. Each of the 12 movements is sequentially omitted during classifier training but sent to the classifier for prediction.
## 3 Results  
### Meteorological Conditions  
Figure 1 shows microclimate behavior for Rainfied and Irrigated. PAR was observed on both sites mainly as diffuse radiation, which was evident because of variations over time. This is typical for the study area, characterized by high cloud cover. The average of daily mean PAR was significantly higher (\(p\) < 0.05) in Irrigated (724.5 \(\pm\) 216.7 umol photons m\({}^{-2}\) s\({}^{-1}\)) compared to Rainfied (567.9 \(\pm\) 230.7 umol photons m\({}^{-2}\) s\({}^{-1}\)). Nevertheless, the average daily mean (Tmean) and the maximum air temperature (Tmax) were higher in Rainfied (Tmean: 16.80 \({}^{\circ}\)C \(\pm\) 0.92, Tmax: 20.32 \({}^{\circ}\)C \(\pm\) 1.29) than in Irrigated (Tmean: 16.51 \({}^{\circ}\)C \(\pm\) 1.02, Tmax: 19.73 \({}^{\circ}\)C \(\pm\) 1.23). The average daily maximum vapor pressure deficit (DPV) was higher in Rainfied (0.80 KPa \(\pm\) 0.24) compared to Irrigated (0.73 KPa \(\pm\) 0.25), while the average daily mean DPV did not show a significant difference in Rainfied (0.40 KPa \(\pm\) 0.12) and Irrigated (0.38 KPa \(\pm\) 0.16).  
Low water availability in Rainfied (SWC < WP) was the determinant for solar radiation to be directed more for air heating than evapotranspiration [34]. The accumulated precipitation for Rainfied was 229 mm, with a non-uniform time distribution, including events of consecutive dry days and high precipitations, observed by the end of the crop cycle, reaching 98 mm in one week (101 to 107 DPP). The accumulated precipitation for Irrigated (306 mm) was higher and more uniformly distributed, however, a drier lapse occurred, from 13 March to 22 April 2021 (50-90 DPP). The decision to irrigate the crop was made after identifying soil water deficit using a water balance calculated according to FAO-56 [36] and monitoring the soil tensiometers installed inside each plot.
# Separable Data-Hiding Scheme for Encrypted Image to Protect Privacy of User in Cloud
## 4 Experiments
### Performance Analysis of the Proposed Scheme
There was no difference in our scheme before or after the hidden data were extracted. So, the quality of the recovered image after extracting the hidden data in [PERSON] et al. 's scheme [24] and [PERSON] et al. 's scheme [25] was better than that of our proposed scheme. In addition, in our scheme, the hidden data can be extracted completely as long as the stego-images are not distorted, but the other schemes cannot do this without small distortions. In terms of the complexity of the extraction, our proposed scheme only requires a simple modular operator, and this is very easy to provide.
_Applied_  
_sciences_  
_Article_  
**A Simplified Method for Real-Time Prediction of Temperature in Mass Concrete at Early Age**  
[PERSON] **1**\({}^{\copyright}\), [PERSON] **2**, [PERSON] **1**, [PERSON] **1,* and [PERSON] **1**  
Received: 9 June 2020; Accepted: 24 June 2020; Published: 28 June 2020  
**Featured Application: An early warning system for maximum concrete temperature control was established based on the temperature forecasting method in this paper and the real-time monitoring system for the Baihetan arch dam and Wudongde arch dam.**  
**Abstract: According to the practice of temperature control in dam concrete, within a few days after a concrete block is poured, the temperature at the core of the concrete rises rapidly. The maximum temperature may still exceed the standard even under a relatively perfect post-cooling system, which is mostly caused by failure to quickly and correctly judge the development of the early-age temperature. This study investigates concrete temperature at an early age via in situ monitoring data collected from Baihetan arch dam and Wudongde arch dam. A simplified algorithm of temperature prediction is formed, which only considers the heat released by cement hydration and the cooling effect of cooling pipes. The influence of a cooling pipe on the measuring point of the thermometer is investigated, and a simple empirical formula to calculate the cooling effect is obtained. An equation for the rate of hydration temperature rise is achieved by combining measured data and the formula used to calculate the cooling effect. Furthermore, through the explorations of the related data, it is determined that the cement hydration ratio of the two dams is quite low during concreting. On the basis of the data collected from the field, the method to predict temperature proposed in this study is tested and proven.**  
**Keywords: temperature prediction; field data; early-age concrete; cement hydration; cooling effect**
# Computational Fluid Dynamics Applied to
## 5 Results
### Categorization of Relevant Papers Exploiting the Rigid Mesh Motion and Sliding Meshes Approaches
In Figure 4, it is possible to see that most of the works simulated a level of complexity of 4 (more specifically, 15 works out of 29) achieving an average accuracy of 80%-90%. It is interesting to \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Paper** & **Year** & **Software** & **System** & **Target** & **Validation** & **Accuracy** & **Complexity** \\ \hline
[86] & 2008 & Comm. & Gears & Fluxes & Yes & Qualitat. & 3 \\
[108] & 2012 & Open & Pump & Both & Yes & 80\%–90\% & 3 \\
[35] & 2013 & Comm. & Gears & Both & Yes & \textgreater{}95\% & 4 \\
[107] & 2013 & Open & Pump & Fluxes & Yes & Qualitat. & 3 \\
[33] & 2013 & Open & Pump & Fluxes & Yes & Qualitat. & 3 \\
[88] & 2014 & Open & Gears & Both & Yes & \textgreater{}95\% & 3 \\
[95] & 2014 & Comm. & Bearing & Both & No & N.A. & 4 \\
[100] & 2014 & Comm. & Bearing & Both & Yes & 90\%–95\% & 5 \\
[101] & 2014 & Comm. & Pump & Both & Yes & \textgreater{}95\% & 4 \\
[32] & 2015 & Open & Gears & Both & Yes & \textgreater{}95\% & 3 \\
[94] & 2015 & Comm. & Gears & Both & No & N.A. & 3 \\
[98] & 2015 & Comm. & Bearing & Both & Yes & 80\%–90\% & 5 \\
[96] & 2015 & Comm. & Bearing & Both & No & N.A. & 4 \\
[93] & 2016 & Open & Gears & Both & Yes & 90\%–95\% & 4 \\
[89] & 2016 & Comm. & Gears & Both & Yes & 90\%–95\% & 4 \\
[99] & 2016 & Comm. & Bearing & Both & Yes & 80\%–90\% & 4 \\
[97] & 2016 & Comm. & Bearing & Fluxes & Yes & 90\%–95\% & 4 \\
[103] & 2016 & Open & Pump & N.A. & No & N.A. & 4 \\
[87] & 2017 & Open & Gears & Fluxes & No & N.A. & 3 \\
[102] & 2017 & Open & Pump & Fluxes & No & N.A. & 4 \\
[90] & 2019 & Comm. & Gears & Both & Yes & 90\%–95\% & 4 \\
[91] & 2019 & Comm. & Gears & Both & Yes & 90\%–95\% & 4 \\
[92] & 2019 & Comm. & Gears & Fluxes & No & N.A. & 3 \\
[109] & 2019 & Comm. & Pump & Both & Yes & 80\%–90\% & 4 \\
[104] & 2019 & Open & Pump & Both & Yes & 90\%–95\% & 3 \\
[34] & 2019 & Open & Pump & Forces & No & N.A. & 4 \\
[106] & 2019 & Comm. & Pump & Fluxes & No & N.A. & 3 \\
[105] & 2019 & Comm. & Pump & Both & Yes & \textgreater{}95\% & 4 \\
[31] & 2020 & Open & Bearing & Both & Yes & \textgreater{}95\% & 5 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Classification of the pertinent papers exploiting the rigid mesh motion and sliding meshes approaches. notice that the RMM/MSL approaches can simulate a level of complexity of 5. However, this level of complexity has been studied only in the bearings. Indeed, these approaches are not able to reproduce the gear meshing and, when it has been applied to planetary gearboxes, the teeth have not been modelled engaged. It is possible to notice that the only study that simulates bearings by applying the RMM/MSL approaches through OpenFOAM(r) [31] has achieved the highest possible level of accuracy.
# Silica Mesoporous Structures: Effective Nanocarriers in Drug Delivery and Nanocatalysts
## 4 Catalytic Applications of Mesoporous Silica Materials  
In recent years, catalytic applications of mesoporous materials have been explored due to their adjustable pore sizes, biodegradability, and ease of modification with various functional groups. They are very much considered for organic syntheses and the removal of organic dye pollutants. In the following sections, an update from literature is given regarding the recent advances of mesoporous silica-based materials for catalytic applications.
# Cooperative Opportunistic Pressure Based Routing for Underwater Wireless Sensor Networks
###### Abstract  
In this paper, three opportunistic pressure based routing techniques for underwater wireless sensor networks (UWSNs) are proposed. The first one is the cooperative opportunistic pressure based routing protocol (Co-Hydrocast), second technique is the improved Hydrocast (improved-Hydrocast), and third one is the cooperative improved Hydrocast (Co-improved Hydrocast). In order to minimize lengthy routing paths between the source and the destination and to avoid void holes at the sparse networks, sensor nodes are deployed at different strategic locations. The deployment of sensor nodes at strategic locations assure the maximum monitoring of the network field. To conserve the energy consumption and minimize the number of hops, greedy algorithm is used to transmit data packets from the source to the destination. Moreover, the opportunistic routing is also exploited to avoid void regions by making backward transmissions to find reliable path towards the destination in the network. The relay cooperation mechanism is used for reliable data packet delivery, when signal to noise ratio (SNR) of the received signal is not within the predefined threshold then the maximal ratio combining (MRC) is used as a diversity technique to improve the SNR of the received signals at the destination. Extensive simulations validate that our schemes perform better in terms of packet delivery ratio and energy consumption than the existing technique; Hydrocast.  
underwater wireless sensor network; energy balancing; cooperation; opportunistic routing +
Footnote †: journal: Sensors
# Proteomics in Forensic Analysis: Applications for Human Samples
###### Abstract
presented a standard bottom-up proteomic workflow [23]. In addition, [PERSON] et al. described details of sample preparation in bottom-up proteomics [24], and [PERSON] et al. focused on proteomics sample treatment procedures applied for tissues [25]. Another review summarized some applications of proteomics in forensics, including human identification from hair samples and identification of body fluids [11]. A recent review presented some forensic proteomic applications, such as human samples (hair, bone, and body fluids), species identification, toxins, and microbial forensics [4]. Our current review aims to focus on a wide range of human samples used in forensic proteomics with updated findings from the literature. They include hair, bone, body fluids (blood, urine, semen, vaginal fluid, saliva), muscle, fingernail, muscle, brain, and fingermarks. These samples are different from each other in terms of sample amount, sample availability, and protein amount. The amount of sample collected may vary depending on the forensic contexts. Some samples may have relatively low amounts, such as hair, body fluids, tissues, and their traces in fingermail and fingermark. Protein amounts are different among samples. In sport doping, urine and blood can be used. Urine usually has low protein content as compared with that of blood; however, it is easily available. Some samples, such as bone, muscle, brain, and decomposition fluid might be only available from corpse. Human samples can be used for various forensic proteomic applications. Hair is a valuable sample for identifications of ethnic groups, gender, and individual [18; 26; 27]. Urine and blood are are used to identify and quantify illegal peptides and small protein hormones for sport doping [28]. Some samples, such as bone, muscle, brain, cerebrospinal fluid, and decomposition fluid are used to estimate post-mortem interval (PMI) [29; 30; 31; 32; 33]. Fingernail and fingermark may contain traces of body fluids and tissues and thus, be used for their identification [34; 35]. Table 1 summarizes some applications of proteomics in forensics using different types of human samples. In this review, we present an overview of proteomics in forensic analysis, with a particular focus on applications in human samples. We introduce general proteomics methods that are applied in forensic studies, including sample preparation techniques, data acquisition using LC-MS/MS, and data analysis using database search, spectral library search, and de novo sequencing. Notably, we summarize recent applications in the past decade of forensic proteomics that use human samples for analysis, such as hair, bone, body fluids, muscle, fingernail, brain, blood, and fingermarks.
# A New Approach to Quantify Soccer Players' Readiness through Machine Learning Techniques
## 2 Materials and Methods
### External Load Data Collection  
Players' external load was recorded during 511 training sessions (first team, n = 199, duration: 67.7 \(\pm\) 14.1 min; U19: 166, duration: 85.6 \(\pm\) 18.2 min; U18: 146, duration: 85.6 \(\pm\) 13.5 min) and 116 official matches (first team, n = 38; U19, n = 40; U18, n = 38). An average of 169 \(\pm\) 31 observations per player were recorded. Subjects who registered less than 85 observations were excluded from further analysis in order to remove players who only partially played during the season due to injuries or any other reason (e.g., transfer to another club). Thus, a total of 10,857 individual observations were collected. External training/match load was obtained using the WIMU Pro system (RealTrack Systems, Almeria, Spain), which consists of various inertial sensors (three 3D gyroscopes with 8000\({}^{\circ}\)/s full-scale output range, a 3D magnetometer, a 10-Hz global positioning system, a 20-Hz ultra-wide band) whose validity and reliability have been previously tested [11; 12; 13]. The GPS devices were placed between the players' scapulae through a tight vest. Eighteen different external load metrics were extracted (Table 1).
## 5 Overview of 5G-Enabling Technologies
### Spectrum Sharing in 5G  
The 5G NR networks need small cells and should be highly populated to operate. These networks might share a frequency band with other services that operate on distinct bands. The current spectrum-sharing plans will be effectively used as 5G is developed to fulfill the requirements of relevant applications. A summary of a few spectrum-sharing plans that may be adopted for 5G technology is given as follows.  
* TV White Space: Frequencies for TV not used by authorized users are referred to as \"white spaces\". The FCC recommended sharing unused TV frequencies with authorized users and their low-powered equipment. The primary consumers are TV receivers, which are protected from interference and given higher transmission priority. Users who lack a license are secondary users. They have poor transmission priority and are not protected from interference from major users.
* Licensed Shared Access (LSA): TVWS has a drawback in that it cannot deliver the necessary level of service to secondary users. Hence, it cannot completely address the issue of spectrum scarcity. A novel approach to spectrum sharing, known as the LSA, has been made available to mobile operators [129]. While the LSA sharing scheme protects new licensees from interference, allowing them to access the spectrum with predictable quality of service, Authorized Spectrum Access (ASA) allows spectrum owners (current owners of the underutilized spectrum) to grant a small number of mobile operators access to their underutilized spectrum. This benefits both the incumbent, who may be permitted to stay in the band longer and eventually receive financial compensation, and the LSA licensee, who may use an underutilized band at an inexpensive cost while the band cannot be cleared or rebuilt. The 2300-2400 MHz band was the first to be authorized for LSA in Europe [129]. C. Spectrum Access Sharing (SAS): The Spectrum Access System (SAS) was initially suggested in the United States, particularly for the 3550-3700 MHz band, as one of many projects aimed at providing more spectrum for mobile broadband [130]. In contrast to earlier sharing strategies, SAS employs a three-tier sharing structure that permits the use of the available spectrum by three different user categories: Federal users, Priority Access Licensed (PAL) users, and General Authorized Access (GAA) users. The Federal users are shielded from all types of interference and have full access to the spectrum. The PAL users are shielded from interference from all users except the Federal users and can utilize the spectrum only when the Federal users are not. Only opportunistic access to the spectrum is available to the GAA users as a result of their lowest priority, and they have no interference protection.
# A Two-Stage Kalman Filter-Based Carrier Tracking Loop for Weak GNSS Signals
## 4 KF-Based Two-Stage Carrier Tracking Loop
### Basic Equations of KF-Based Tracking
In (12), the measurement noise, \(v_{k}\), is white Gaussian noise with a variance, \(\sigma_{v}^{2}\). The measurement noise covariance, \(\mathbf{R}\), for the output of the two-quadrant arctangent discriminator, can be expressed as [16]:  
\[\mathbf{R}=\sigma_{v}^{2}=E\Big{[}v_{k}v_{k}{}^{T}\Big{]}=\frac{1}{2 Tc/n_{0}} \bigg{(}1+\frac{1}{2 Tc/n_{0}}\bigg{)} \tag{16}\]where \(c/n_{0}\) is the carrier-to-noise ratio, which is typically obtained by:  
\[c/n_{0}=10^{\frac{C/N_{0}}{10}} \tag{17}\]  
The unit of \(C/N_{0}\) is dB-Hz.
# Magnetic Field Penetration Depth in Various Materials and Applications
## 3 Results
### Reporting of Times and Countries of Experiments  
Figure 5 shows a trend of a significant increase in the number of studies over the years, with a remarkable growth in the interval 2004-2021, which has the highest value (17), while the first three intervals (1991-2003) have low values, i.e., in recent years, the trend is disruptive because there is research on magnetic field penetration in various types of materials.  
Figure 4: Relationship between frequency and materials in the reviewed studies.  
The review of experiments carried out in different countries around the world shows in Figure 6 that in Latin America there is less research on magnetic field penetration, while China and the United States are the countries where the most research is done.  
Germany and Poland have three studies each; Australia, Ukraine, Brazil, Sweden, Singapore, South Korea, Spain, Portugal, the United Kingdom, and Romania have one study each; the United States and China have nine studies each; Italy and Switzerland have five studies each; Russia has four studies; and Japan has two studies. The map shows the locations of experiments on magnetic field penetration in various types of materials in terms of continents. However, these experiments are carried out in physics laboratories, universities, and research centers all over the world, and the most relevant sites in this field tend to be located in regions with advanced scientific infrastructure, such as the United States and China.  
Figure 5: Temporal evolution of the studies on the subject under review.  
Figure 6: Number of studies found in the review, organized by country.