esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Materials and Methods
### UPLC-MS/MS Analysis
#### 4.2.2 UPLC-MS/MS Conditions  
The abundances of flavonoid compounds were quantified with ultrahigh-performance liquid chromatography (UPLC)-mass spectrometry (MS/MS). The UPLC conditions were as follows: (1) SB-C18 column (1.8 \(\upmu\)m, 2.1 mm \(\times\) 100 mm, Agilent, Palo Alto, CA, USA); (2) column temperature: 40 \({}^{\circ}\)C; (3) flow rate: 0.35 mL per minute; (4) injection volume: 2.0 \(\upmu\)L; (5) fluid phase: phase A is 0.1% formic acid solution, phase B is 0.1% formic acid acetonitrile solution; (6) elution procedure: 0 min, 95% A, 5% B; 0-9 min, 5% A, 95% B; 9-10 min, 5% A, 95% B; 10-11.1 min, 95% A, 5.0% B; 11.1-14 min, 95% A, 5.0% B. The quadrupole orbital trap mass spectrum conditions were as follows: (1) detection mode: positive ion mode (P+), 5500 V and negative ion mode, \(-\)4500 V; (2) ESI temperature: 550 \({}^{\circ}\)C; (3) GSI, 50 psi; GSII, 60 psi; the curtain gas, 25.0 psi; (4) collision-induced ionization parameter: high; (5) quality scanning range \(m/z\) 100-1200, scanning time 0.2 s; (6) a specific set of MRM transitions were monitored for each period according to the metabolites eluted within this period.  
The metabolites were analyzed qualitatively by comparing the UPLC-MS/MS data with the local metabolite databases built by Met Ware, and the quantitative analysis of each metabolite was completed by MRM analysis of triple quadrupole mass spectrometry. And then, the mass spectrogram of all metabolites in petals with different color were obtained and the peak area of the mass spectrogram of each metabolite was integrated. Analyst 1.6.3 software (AB SCIEX, Concord, ON, Canada) was applied to process the UPLC-MS/MS data. The MultiaQuant(tm) software 3.0.3 (AB SCIEX, Concord, ON, Canada) was used to integrate and correct the chromatographic peaks, and the peak area of each chromatographic peak represented the relative content of the corresponding metabolite.
###### Abstract  
White grape pomace (winery by-product) stabilized by blanching and high hydrostatic pressure has recently been successful at delaying lipid oxidation in burgers. The aim of this study was to investigate whether it can also delay lipid oxidation in dry-cured sausages, and to compare its effect when added at 0.5 and 3% with those of synthetic additives (sodium nitrite and ascorbic acid) and no additives (Control) in lipid and protein oxidation, the instrumental color, the sensory characteristics, and the volatile compounds. The pomace (68.7 \(\pm\) 7.4 mmol \(\mathrm{Trolox}\)\(\mathrm{g}^{-1}\)) was as effective as the additives at preventing lipid oxidation, resulting in values 3.2-3.8 times lower than the Control sausages. However, the pomace was not effective at decreasing the microbial counts, improving the instrumental and sensory color and the volatile compound profile, and decreasing the off-odor and off-flavor developed in the Control sausages. The lack of a detrimental effect of the pomace at 0.5% on the volatile compounds and the sensory characteristics and its benefits to delay lipid oxidation suggest that it might be useful to improve the oxidative stability. Conversely, at 3%, with a detrimental effect on some sensory characteristics and no benefits over the lower dosage, is not advisable.  
g rape pomace; wine by-product; dry-cured sausage; nitrite-free meat; antioxidant; oxidation; high hydrostatic pressure; HHP +
Footnote †: journal: Physics Letters B  
Article  
High-Hydrostatic-Pressure-Stabilized White Grape Pomace to Improve the Oxidative Stability of Dry-Cured Sausages
# A DEM Study on Bearing Behavior of Floating Geosynthetic-Encased Stone Column in Deep Soft Clays
## 3 Results and Discussion
### Stresses of the Soil around the Column and the Underlying Stratum  
The measurement spheres No. 12-37 were used to measure the stresses of the soil around the column and the underlying stratum. Figure 13 shows the vertical stresses of the soil around the column and the underlying stratum at various distances from the column center. The vertical stress of the soil near the column slightly increased with the settlement, as shown in Figure 13a. The increase in the vertical stress in the encased section was more obvious than that in the unreinforced section. However, the increase was still much smaller than that of the column body. The vertical stress of the soil near the side boundary was basically unchanged with the settlement, as shown in Figure 13b. The vertical stress was distributed by gravity and increased linearly along the depth.  
Figure 11: Coordination number changes of the FGESC with the settlement.  
Figure 14 shows the radial stresses of the soil around the column and the underlying stratum at various distances from the column center. The radial stress of the soil near the column slightly increased with the settlement, as shown in Figure 14a. When the settlement reached 27 mm and 36 mm, there was a certain increase in the radial stress in the soil near the unreinforced section. The radial stress of the soil near the side boundary was basically unchanged with the settlement, as shown in Figure 14b. The radial stresses in the underlying stratum were largely unaffected by the settlement.  
Figure 14: Radial stresses of the soil around the column and the underlying stratum at various distances from the column center: (**a**) 65 mm and (**b**) 105 mm.  
Figure 12: Sliding fraction changes of the FGESC with the settlement.  
Figure 13: Vertical stresses of the soil around the column and the underlying stratum at various distances from the column center: (**a**) 65 mm and (**b**) 105 mm.  
The above analysis shows that the stresses of the soil near the column were affected by settlement, and the stresses of the soil near the side boundary were largely unaffected by settlement. Due to the presence of the geogrid, the movement of the aggregates was restricted. It prevented the transfer of significant stress from the column to the soil around the column.
## 2 Data Collection and Processing
### Data Collection  
PostgreSQL is designed for local use by applications running on the same machine. However, by configuring a global IP address on the host system, it can be accessed remotely from any location worldwide. This configuration enables clients to establish an internet connection to the database from multiple computers. PostgreSQL must be configured to allow remote connections so that data can be gathered from the database via the Internet. This is accomplished by setting an individual port for the connections, adding the IP addresses of the clients to PostgreSQL's configuration file, and limiting access to those with permission only by demanding a specific username and password. With the help of these safeguards, regulated and safe database access is made possible, facilitating effective online data collection from distant users.
## 3 Results and Discussion
### Meteorology and Air Quality

Table 2: Characteristics of the meteorology during the monitoring period (standard deviations are given in parentheses). ground wind speeds could affect the local air quality by hindering the ventilation/dilution of emissions from the roadways. As expected, the concentrations of traffic-related primary pollutants (CO and NO2) decreased sharply as wind speeds increased in both summer and winter. The decreasing rates as a function of wind speed were larger and more prominent for the ground wind speed than the prevailing wind speeds (Figure 3a,b,e,f). When the ground wind speed exceeded 2 m\(\cdot\)s\({}^{-1}\), the primary pollutant concentration reached the urban background level in this area (Figure 3e,f). Ozone concentrations increased with wind speed because, under calm conditions, high NO\({}_{\text{X}}\) levels would be expected, as shown by the NO2 measurements (Figure 3b,f), so the abundant NO could effectively remove ozone under the urban canopy. The PM2.5 concentrations displayed a similar trend to that of the primary gaseous pollutants because the accumulation of precursor gases under calm conditions favors secondary PM2.5 production, and PM2.5 is not affected by chemical loss processes unlike ozone [27; 28]. Figure 2: Comparison of the hourly meteorology between the KMA AWS site (prevailing wind) and ground level (Site-1 in summer and Site-2 in winter). (**a**,**d**) show wind direction, (**b**,**e**) wind speed, and (**e**,**f**) the temperature in summer and winter, respectively. Black circles denote westerly prevailing winds, blue squares easterlies, and yellow triangles other directions. The gray x indicates that ground wind speeds were less than 0.3 m\(\cdot\)s\({}^{-1}\) (wind direction could not be determined). The black solid and gray dotted lines in (**b**,**e**) represent the linear fits for the black circles and blue squares, respectively.
## 2 Proposed Approach
### Model Architecture
#### 2.3.3 Overall Procedure  
The overall DCMA-SELD architecture is illustrated in Figure 2, and the feature dimensions and hyper-parameters are summarized in Table 2.  
Figure 2: The overall DCMA-SELD architecture. Q. K, and V indicate the query, key, and value in the attention, respectively. For the SED stream, the input feature tensor has four channels. Each of the four channels has spectral features obtained from each of the four signals formatted in the FOA format, which consists of a 256-dimensional log-mel spectrum, a 12-dimensional chroma vector, and an 11-dimensional spectral feature per frame. For the DOAE stream, the input feature tensor has three more channels in addition to the four channels for the SED stream.
## 4 ABER for SIMO TOW Systems with Receivers' Diversity
### SIMO TOW System with IM/DD OOK
Therefore, the obtained multiple integral can be estimated through the following multiplication of single integrals [66]  
\[P_{e,\alpha\
u,M}^{OOK}\approx\frac{1}{12}\prod\limits_{m=1}^{M}\int\limits_{0 }^{\infty}\exp\Bigg{(}-\frac{\eta_{m}^{2}h_{m}^{2}}{4 MN_{0}}\Bigg{)}f_{h_{m}} (h_{m})dh_{m}+\frac{1}{4}\prod\limits_{m=1}^{M}\int\limits_{0}^{\infty}\exp \Bigg{(}-\frac{\eta_{m}^{2}h_{m}^{2}}{3 MN_{0}}\Bigg{)}f_{h_{m}}(h_{m})dh_{m}. \tag{24}\]  
Next, by substituting (10) into (24) we get  
\[P_{e,\alpha\
u,M}^{OOK} \approx\frac{1}{12}\frac{h_{l,m}^{\psi_{m}^{2}-1}\psi_{m}^{2}}{ \left(A_{0,m}\pi\right)^{\psi_{m}^{2}}}\prod\limits_{m=1}^{M}\int\limits_{0}^{ \infty}\exp\Bigg{(}-\frac{\eta_{m}^{2}h_{m}^{2}}{4 MN_{0}}\Bigg{)}h_{m}^{-\psi_ {m}^{2}}dh_{m} \tag{25}\] \[+\frac{1}{4}\frac{h_{l,m}^{\psi_{m}^{2}-1}\psi_{m}^{2}}{\left(A_{ 0,m}\pi\right)^{\psi_{m}^{2}}}\prod\limits_{m=1}^{M}\int\limits_{0}^{\infty} \exp\Bigg{(}-\frac{\eta_{m}^{2}h_{m}^{2}}{3 MN_{0}}\Bigg{)}h_{m}^{-\psi_{m}^{2} }(h_{m})dh_{m}\]  
Thus, by using \(\int\limits_{0}^{\infty}x^{n}e^{-x^{2}}dx=\frac{\Gamma((n+1)/2)}{2z^{\frac{n+1 }{2}}},n>-1,z>0\)[59], and by substituting (3) in (25), the ABER of a IM/DD OOK SIMO TOW system with OC under both skin-induced attenuation and NZB pointing errors conditions, is estimated as  
\[P_{e,\alpha\
u,M}^{OOK} \approx\frac{1}{12}\prod\limits_{m=1}^{M}\frac{\psi_{m}^{2}\exp (-\alpha(\lambda_{m})\beta_{m}/2)^{\psi_{m}^{2}-1}\Gamma\left[(1-\psi_{m}^{2})/ 2\right]}{2\left(\frac{\eta_{m}^{2}}{4 MN_{0}}\right)^{\frac{1-\psi_{m}^{2}}{2}} \left(A_{0,m}\pi\right)^{\psi_{m}^{2}}} \tag{26}\] \[+\frac{1}{4}\prod\limits_{m=1}^{M}\frac{\psi_{m}^{2}\exp(-\alpha( \lambda_{m})\delta_{m}/2)^{\psi_{m}^{2}-1}\Gamma\left[(1-\psi_{m}^{2})/2 \right]}{2\left(\frac{\eta_{m}^{2}}{4 MN_{0}}\right)^{\frac{1-\psi_{m}^{2}}{2}} \left(A_{0,m}\pi\right)^{\psi_{m}^{2}}}\]  
Alternatively, by substituting (12) into (26) we get the latter as a function of the average electrical SNR, \(\mu_{m}\)  
\[P_{e,\alpha\
u,M}^{OOK} \approx\frac{1}{12}\prod\limits_{m=1}^{M}\frac{\psi_{m}^{3-\psi_{m }^{2}}\left(A_{0,m}\pi\right)^{1-2\psi_{m}^{2}}\left(4\widetilde{\
u}_{S}M \right)^{\frac{1-\psi_{m}^{2}}{2}}\Gamma\left[(1-\psi_{m}^{2})/2\right]}{2\left[ \mu_{m}(\psi_{m}^{2}+2)\right]^{\frac{1-\psi_{m}^{2}}{2}}} \tag{27}\] \[+\frac{1}{4}\prod\limits_{m=1}^{M}\frac{\psi_{m}^{3-\psi_{m}^{2}} \left(A_{0,m}\pi\right)^{1-2\psi_{m}^{2}}\left(3\widetilde{\
u}_{S}M\right)^{ \frac{1-\psi_{m}^{2}}{2}}\Gamma\left[(1-\psi_{m}^{2})/2\right]}{2\left[\mu_{m}( \psi_{m}^{2}+2)\right]^{\frac{1-\psi_{m}^{2}}{2}}}\]
## 1 Introduction
[PERSON] and [PERSON] [25] and [PERSON] and [PERSON] [26] developed a tracking system based on the direct tracking method and indirect tracking method, respectively. Through this, the performance of electricity generation due to the application of the tracking system was evaluated. Third, in terms of the monitoring system, some of the previous studies have analyzed the technical performance of the PV system. [PERSON] et al. [27] analyzed the relationship between the two variables by monitoring the electricity generation and temperature on the blind's integrated PV panels. [PERSON] et al. [28] developed a monitoring system for electricity generation and the temperature of PV surface by using Labview software developed by National Instruments (Austin, TX, USA). [PERSON] et al. [29] and [PERSON] et al. [30] performed the monitoring of the electricity generation and illuminance to analyze the electricity generation and incoming daylight from the PV blind. As with the literature review, there are several limitations in the previous studies. First, the electricity generation of the c-Si PV panel and the a-Si PV panel were analyzed for the PV blind and rooftop PV system, whereas that of the copper-indium-gallium-selenide (CIGS) PV panel was not taken into account for the analysis. Second, as for the rooftop PV system, various tracker types (i.e., fixed, single-axis, and dual-axis tracker types) and tracking methods (i.e., direct and indirect tracking methods) were analyzed. On the other hand, as for the PV blind, only the fixed type and single-axis tracker type was analyzed and, accordingly, there is a lack of research that comprehensively considers the dual-axis tracker type and tracking method. Third, few studies are conducted to evaluate the feasibility of the PV blind that takes into consideration the three properties (i.e., PV panel, tracking system, and monitoring system) and performs the experimental research. To address these challenges, this study aimed to design and develop the prototype models of the smart photovoltaic system blind (SPSB) with consideration of the three properties (i.e., PV panel, tracking system, and monitoring system). The three properties (i.e., PV panel, tracking system, and monitoring system) of the SPSB were defined in Section 2. Additionally, detailed techniques applicable to the SPSB by property (i.e., PV panel: PV techniques and PV panel's design variables; tracking system: tracker type and tracking method; and monitoring system: monitoring factor) were explained. In Section 3, the developed three prototype models of the SPSB were described in terms of three properties (i.e., PV panel, tracking system, and monitoring system). Finally, the conclusion of this study was presented in Section 4.
## 4 FWA Design Considerations, Challenges, and Solutions
### Envisaged 5G Deployment Spectrum
#### 4.1.3 Non-Ideal LoS Conditions  
The related physical and environmental requirements for different transmission schemes vary significantly regarding individual tolerance to other-than-ideal conditions [283]. FWA deployment with non-ideal LoS conditions, as illustrated in Figure 14b, predominantly results in significantly reduced signal quality. Subsequently, this lowers the anticipated throughputs and, thus, brings about a poor quality of experience (QoE) [252]. This hitch can be effectively addressed with the implementation of techniques such as diversity and wireless multihop network cooperative transmission schemes. The scheme's implementation helps in creating a distributed virtual antenna arrays that are capable of enhancing the signal robustness to the propagation environments [284]. Furthermore, the schemes can also help significantly in reducing energy consumption, enhancing communication reliability, and decreasing the associated transmission latency [285; 286; 287; 288]. Besides, both parametric and nonparametric methods can be employed to mitigate error in the non-LoS scenarios [95; 289].
###### Abstract  
The functional capacity of the cervical spine plays a central role in healthy living. The aim of this study was to examine the sex-related effect on cervical strength, range of motion (ROM), and the musculoskeletal pain profile in young physically active individuals. A total of 30 males and 30 females (21.53 \(\pm\) 1.15 years old), without injury or chronic pain at the cervical joint, participated in the study. ROM (forward flexion, extension, lateral flexion-rotation), maximal isometric strength (forward flexion, extension, lateral flexion), and musculoskeletal pain were assessed using an electronic goniometer, a handheld dynamometer, and the Nordic questionnaire, respectively. The results revealed that: (a) females had higher ROM during extension and lateral flexion than males (\(p<0.05\)); (b) males had higher absolute strength than females in all movement directions, and higher relative strength/body mass (at forward flexion) and flexion/extension ratio (\(p<0.05\)); (c) ROM and strength were not significantly different between right and left sides (\(p>0.05\)); (d) a large proportion (43.3%) of the participants had cervical pain; and (e) cervical strength showed a significant small negative correlation with pains (\(p<0.05\); \(r=-0.225\) to \(-0.345\)). In conclusion, the derived reference values may be used by health and fitness professionals to extensively evaluate the cervical spine and to design specific exercise programs for injury prevention and rehabilitation.  
neck; isometric contraction; muscle strength; range of motion; musculoskeletal pain; fitness testing; injuries; rehabilitation Article
## 3 Experimental Data and Estimation Algorithms
### Kalman Filter  
The Kalman filter is one of the most popular solutions to the linear discrete-data filtering problem. It was presented by [PERSON] in 1960 [23]. The reasoning behind it is that it provides an optimal solution for a known linear system in the presence of white Gaussian noise by minimizing the state estimation error [23]. The linear system can be represented by the following two equations [24]:  
\[x_{k+1}=Ax_{k}+Bu_{k}+w_{k} \tag{8}\]  
\[z_{k+1}=Cx_{k+1}+v_{k+1} \tag{9}\]  
where \(A\) is the dynamics matrix, \(B\) is the input matrix, \(C\) is the output matrix, \(x\) is the system state, \(z\) is the measurement output, \(u\) is the input, \(w\) is the system noise, and \(v\) is the measurement noise.  
Moreover, the KF algorithm can be represented as a two-stage process: prediction and update [24].  
\((i)\)_Prediction Stage_ :  
\[\hat{x}_{k+1|k}=A\hat{x}_{k|k}+Bu_{k} \tag{10}\]  
\[P_{k+1|k}=AP_{k|k}A^{\top}+Q \tag{11}\]  
\[w\sim N(0,Q) \tag{12}\]  
Figure 3: B034 Measured Battery Capacity at the end of each discharge cycle [22].  
\[v\sim N(0,R) \tag{13}\]  
\((ii)\)_Update Stage_ :  
\[K_{k+1}=P_{k+1|k}C^{T}\Big{[}CP_{k+1|k}C^{T}+R\Big{]}^{-1} \tag{14}\]  
\[\hat{x}_{k+1|k+1}=\hat{x}_{k+1|k}+K_{k+1}\Big{(}\hat{x}_{k+1}-C\hat{x}_{k+1|k} \Big{)} \tag{15}\]  
\[P_{k+1|k+1}=[I-K_{k+1}C]P_{k+1|k}(I-K_{k+1}C)^{T}+K_{k+1}RK_{k+1}^{T} \tag{16}\]  
where \(Q\) and \(R\) are the system and measurement noise covariance matrices, respectively.
## 2 Data and Methods  
### Study Area and Data  
The study area was located in a part of the Kuroshio current (20-40\({}^{\circ}\) N, 125-145\({}^{\circ}\) E), which is shown in Figure 1 (image adapted from Shaded Relief, [[http://www.shadedrelief.com/](http://www.shadedrelief.com/)]([http://www.shadedrelief.com/](http://www.shadedrelief.com/)) (accessed on 15 March 2021)). The Kuroshio current is the western boundary in the wind-driven, subtropical, and subarctic circulations of the North Pacific Ocean. The Kuroshio brings the high temperature and high salinity seawater of the equatorial Pacific Ocean to the vast offshore sea areas, which has a huge impact on the ocean, meteorology, and hydrology of these areas. Moreover, the Kuroshio also transports a large amount of heat from the low latitudes of the North Pacific to the middle and high latitudes, so its seasonal and interannual changes have an important impact on the climate and environment of neighboring countries and even the world [5; 18]. There is important scientific significance in studying the MDT and geostrophic current in this area.
# AIS for Malware Detection in a Realistic IoT System: Challenges and Opportunities
## 3 NPS Simulations and Evaluation
### Nsl-Kdd Dataset  
The NSL-KDD dataset is an extension of the KDD'99 dataset [18], aiming to eliminate redundant records present in the original KDD'99 dataset. This refinement led to a reduction in the number of borderline records, setting it apart from other datasets. It has gained widespread popularity for evaluating AIS methods, including NPS and NSSNN methods. The dataset's traffic data were captured using 420 machines and 30 servers across 5 distinct departments. While not IoT-specific, the NSL-KDD dataset encompasses diverse malware attack types and provides a range of file features, making it well suited for experimentation in this context. See the details of the dataset in Table 1.  
Figure 1: Stages for detector generation and detection in artificial immune systems. The new file represents incoming files which may be benign or malicious.
# Lightning Protection Methods for Wind Turbine Blades: An Alternative Approach
## 3 Wind Turbine Blades and Its Protection Methods
### Lightning Damage to Wind Turbines and Blades  
According to many field observations and studies [15; 16; 17; 18], wind turbines receive significant amounts of lightning attachments during their designed lifetime, mostly on rotor blades. The damages caused mostly from unsuccessful attachments on air terminations or from induced voltages from electric and electromagnetic fields. The highest percentage of damages occurred on the control system, although, on some cases, the damage were simple interruptions. Meanwhile the damage caused on blades are 11%, it often corresponds with severe damage. The damages associated with lightning are generally blade rupturing and burnout, wire melting, surface cracking and delamination, lightning receptor vaporization, and loss [19; 20; 21; 22; 23; 24; 25].  
The most popular lightning protection model used nowadays for large turbines consist of an internal down conductor and metal receptors or air terminators penetrating the surface of the blade to serve as desired attachment points. These two systems are then connected together inside of the blade to carry the lightning current to earth. The receptors are installed at nearby the tip of the blade or placed at equal distance from each other alongside the blade from the root to the tip.  
One of the main issues with this type of protection is that since the receptors are small compared to the blade planform area, it decreases the efficiency of the attachment of the lightning, causing damage on the surface of the blade [21; 22; 23; 24; 25].  
Considering the distribution of the lightning attachment and damage along the blade, it can be seen that majority of the attachment occurs at the tip, and the percentage decreases as the distance increasing from the end of the blade. As it can be seen, around 60% of the total damage was located in the last meter of the turbine blade, and 90% of the total damage occurred in the first 4 m [26].  
Even though there are many different designs for the lightning protection of blades, there is still potential room for improvement. On the interception of the lightning to the air terminations to increase the effectiveness of the captured lightning flashes and on the down conduction part with the connections of different parts to conduct the current safely to earth.