esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Improvement Measures
The height of the external cross-beams could reach only 0.15 m, the stiffness was weak, and the deformation of the cross-beam led to an increase in the track beam displacement. When the track beam height was maintained at 1.5 m and two external end cross-beams and three external middle cross-beams were set between the track beams, the vertical deflection, vertical acceleration, and beam end bending angle of the bridge were improved, while the transverse deformation, transverse acceleration, and midspan torsion angle were increased. The external middle beams strengthened the connection between the two track beams, but the increase in track beam transverse responses caused by the deformation of the middle cross-beams exceeded the decrease in the response caused by the integrity of the bridge. In terms of the improvement degree of the bridge responses, measures of widening the inner cross-beams, increasing the track beam height, or a combination of the two methods were the most effective approaches. Figure 14d-f indicate that in the case where the inner cross-beams were widened, the vehicle acceleration, transverse Sperling index, and the rate of wheel load reduction rate all decreased, whereas  
Figure 14: Responses of the bridge and the train under different improvement cases—(**a**) bridge deflection, (**b**) bridge acceleration, (**c**) bridge angle, (**d**) train acceleration, (**e**) Sperling index, and (**f**) rate of wheel load reduction. the vertical Sperling index did not change significantly. When only the beam height was increased, all vehicle responses were obviously reduced, and the comfort improvement effect was much better. When the inner cross-beams were widened on the basis that the track beam height was 1.7 m, the monorail vehicle responses were almost the same as those when only the beam height increased. When the beam height was unchanged and two external end cross-beams were placed between the track beams, the vehicle acceleration and the rate of wheel load reduction decreased, whereas the Sperling index hardly improved. When the beam height was unchanged and two external end cross-beams and three external middle cross-beams were placed between the track beams, the vehicle acceleration was significantly reduced, the Sperling index and the rate of wheel load reduction decreased, and the monorail vehicle comfort was improved to a certain extent. Considering the improvement degree of the monorail vehicle responses, it was most effective to widen the internal cross-beams, increase the track beam height, or set the external end cross-beams and middle cross-beams between the track beams. The combination of the above analysis results revealed that the most effective measures to improve the riding comfort of straddle-type monorails were to widen the inner cross-beams and increase the track beam height appropriately, which essentially increased the stiffness of the bridge.
# Prediction of Cell-Penetrating Peptides Using a Novel HSIC-Based Multiview TSK Fuzzy System
## 3 Results
### Performance Analysis after Feature Selection  
In this study, the correlation-based feature selection algorithm was utilized because of its excellent performance. We splice the 121-D SSA features with the 50-D Pse-AAC features. The obtained 171-D hybrid features are employed as the input to the feature selection algorithm. Then a 37-dimensional feature subset was obtained, which included 15 SSA features and 22 Pse-AAC features. Among the 121-D SSA features, only 15 features were selected into the optimal feature subset, while 22 of 50-D Pse-AAC were selected. Combined with the performance analysis of the single view, we believe that the Pse-AAC descriptor provides more valuable information for predicting CPPs.  
Table 2 shows the five-fold cross validation results after feature selection. It can be observed that the average ACC is 92.2%, the average SN is 90.8%, the average SP is 93.5%, and the average MCC is 0.844. These metrics indicate that there is improvement relative to the prior feature selection, along with a reduction in feature dimensions. CFS improves the computational efficiency as well as the prediction performance of the model.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Feature** & **ACC (\%)** & **SN (\%)** & **SP (\%)** & **MCC** \\ \hline Pse-AAC & 91.1 & 90.5 & 91.6 & 0.822 \\ SSA & 88.4 & 86.2 & 90.8 & 0.768 \\ Pse-AAC+SSA & 90.1 & 89.2 & 90.8 & 0.802 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Performance of different features on the training set in five-fold cross validation.
## 3 Results
### Cytotoxicity and Selectivity Indices of Plant Extracts
\begin{table}
\begin{tabular}{c c c c c c c c c c c c c c c c c} \hline \hline \multicolumn{1}{c}{**Plants**} & \multicolumn{1}{c}{**Extraction**} & \multicolumn{1}{c}{\(\mathbf{LC_{00}}\) (mg/ml)} & \multicolumn{1}{c}{**Mean Si**} & \multicolumn{1}{c}{**STA**} & \multicolumn{1}{c}{**STA**} & \multicolumn{1}{c}{**STA**} & \multicolumn{1}{c}{**STA**} & \multicolumn{1}{c}{**STA**} & \multicolumn{1}{c}{**STA**} & \multicolumn{1}{c}{**STA**} & \multicolumn{1}{c}{**STA**} & \multicolumn{1}{c}{**STA**} & \multicolumn{1}{c}{**STA**} & \multicolumn{1}{c}{**NAS A**} & \multicolumn{1}{c}{**NAS B**} & \multicolumn{1}{c}{**NAS C**} & \multicolumn{1}{c}{**NAS D**} & \multicolumn{1}{c}{**STA ATCC**} \\ \hline Artificial mean consumer & Acc & 0.08 \(\pm\) 0.00 & 0.65 \(\pm\) 0.15 & 0.68 & 0.56 & 0.91 & 0.82 & 0.68 & 0.30 & 0.68 & 0.68 & 0.68 & 0.68 & 0.68 & 0.45 & 0.67 \\ Artificial mean consumer & Eth & 0.48 \(\pm\) 0.16 & 1.24 \(\pm\) 0.51 & 0.92 & 2.76 & 1.37 & 1.37 & 0.92 & 1.37 & 0.92 & 0.92 & 0.92 & 0.92 & 1.37 & 1.39 \\ Semi-like increase & Acc & 0.15 \(\pm\) 0.02 & 4.69 \(\pm\) 0.99 & 2.82 & 4.13 & 1.27 & 4.13 & 8.11 & 1.02 & 2.88 & 2.88 & 2.88 & 2.88 & 4.71 & 2.14 \\ Semi-like increase & Eth & 0.79 \(\pm\) 0.09 & 4.64 \(\pm\) 0.78 & 4.04 & 6.08 & 6.08 & 4.34 & 4.85 & 5.52 & 4.04 & 4.04 & 4.04 & 4.04 & 4.34 & 4.94 \\ Eryth-offine offine offine & Acc & & 2.69 \(\pm\) 1.18 & 2.13 & 3.19 & 3.19 & 1.60 & 2.56 & 2.13 & 2.13 & 2.13 & 2.13 & 2.13 & 2.13 & 3.19 & 6.25 \\ Eryth-offine offine & Eth & \(>\)1 & 8.30 \(\pm\) 2.05 & 8.55 & 8.55 & 8.55 & 12.82 & 8.55 & 8.55 & 8.55 & 8.55 & 8.55 & 8.55 & 8.55 & 6.41 & 3.23 \\ \hline \multicolumn{11}{c}{STA = Steph/success curve, NAS = Non-curves display/concept, Acc = Acetone, Eth = Ethanol, ATCC = American type culture collection, LC = lethal concentration.} \\ \hline \hline \end{tabular}
\end{table} 
Table 9: Cytotoxicity against Vero cells LC\({}_{50}\) (mg/ml) and selectivity indices of the six selected crude extracts. In relation to the MICs of the extracts against each of the organisms tested, the ethanol extract of _E. catffra_ had the best mean selectivity index (SI) (8.30 \(\pm\) 2.05) against all the pathogens (Table 9), while the acetone extract of _A. venosum_ had a poor mean SI (0.65 \(\pm\) 0.15).
## 3 Results and Discussion
### Ferric Reducing Antioxidant Power (FRAP)  
The FRAP assay is based on reducing a ferric-tripyridyl-triazine complex to its ferrous, colored form under acidic conditions (pH 3.6) in the presence of antioxidants [48]. The FRAP analyzed in the espresso and drip is presented in Table 5. The FRAP was not significantly different at the Light-medium, Medium, and Moderately Dark, regardless of the extraction method. However, at the Very Dark roasting, the FRAP was considerably lower than the others in both the expresso and drip. Some studies have reported that the radical reduction power is deceased as the roasting degree increases, suggesting that lightly roasted coffee beans are better antioxidants than intensely roasted beans [30]. For example, in a study by [PERSON] and [PERSON], it has been reported that the FRAP of coffee beans decreased with increasing roasting time and temperature [49]. [PERSON] et al. have also reported that green beans and Medium light roasted coffee beans have lower IC\({}_{50}\) of reducing power than the Medium and Medium-dark roasted coffee beans [39]. On the other hand, thermal processing can enhance the antioxidant properties of naturally occurring compounds or generate new compounds containing antioxidant properties so that the antioxidant capacity increases or remains unaffected [50]. [PERSON] et al. have reported that the free radical scavenging ability of coffee melanoidins is reduced with increasing roasting degrees [51], whereas Maillard reaction products produced through the amino-carbonyl reaction during roasting are increased; thereby, the antioxidant capacity of the non-phenolic fraction can be maintained or increased [47]. Since FRAP is a non-specific, redox-related, colorimetric analysis, the production and decomposition of various antioxidant components during roasting may be related to the fact that there are no significant differences in FRAP coffee extracts at the Light-medium, Medium, and Moderately dark roasting. However, according to the results, it is estimated that the decomposition of antioxidants proceeds overwhelmingly at Dark roasting than production.
# Toxin \(\zeta\) Reduces the ATP and Modulates the Uridine Diphosphate-N-acetylglucosamine Pool
## 1 Introduction
Thus, the blockage of the first committed step in the biosynthesis of peptidoglycan should lead to loss of cell shape and integrity [18; 26]. This led to the proposal that toxin \(\zeta\) might act by irreversibly depleting the pool of UNAG followed by bacterial cell lysis and death [23]. However, toxin \(\zeta\) action, at or near physiological concentration, showed that it is reversible by nature, even in distantly related bacteria, such as _Escherichia coli_ and _Bacillus subtilis_[13; 27]. At or near physiological concentrations, toxin \(\zeta\) reversibly halts _B. subtilis_ proliferation rather than triggering cell lysis [13; 14; 25]. Furthermore, upon \(\zeta\) expression, a large fraction of cells are still sensitive to fosfomycin, an antibiotic which selectively inhibits MurA activity [26], suggesting that only a fraction of the UNAG pool is irreversibly phosphorylated in vivo by toxin \(\zeta\)[24]. A deeper understanding of the mechanism of \(\zeta\) action, which inhibits cell proliferation by interfering with vital processes and sensitizes bacterial cells to different antibiotics [13; 14; 15], will greatly facilitate targeted engineering of its activity as a potent antimicrobial. In this study, the interactions of toxin \(\zeta\) or its variants with ATP and UNAG have been subjected to detailed computational and biochemical analyses to investigate how \(\zeta\) controls UNAG phosphorylation and how this process may contribute to stress control. A quantitative analysis of the reaction reveals that \(\zeta\) can hydrolyze \(>95\%\) of ATP in the reaction, but under these conditions, only a small fraction of UNAG (up to \(7\%\)) is phosphorylated. Computer modeling was built up to explain why the transfer of the phosphate is so inefficient. These findings led us to propose that toxin \(\zeta\), by hydrolyzing ATP, induces a metabolic ATP/GTP imbalance. This leads to altered gene expression with increased (p)ppGpp synthesis, which reduces the pool of purine nucleotides and halts cell proliferation to cope with the stress [13; 14; 25]. Complementarily, toxin \(\zeta\) phosphorylates a fraction of UNAG, leading to unreactive UNAG-P, rather than depleting the UNAG pool.
## 3 Results and Discussion
### Surface Settlement Analysis  
Surface settlement is one of the most important indicators used to judge the degree of impact on the surrounding environment. Excessive settlement might cause pavement collapse, endanger the surrounding facilities' safety, and even cause serious engineering accidents.  
The surface deformation curves of the sections of Rings 101 and 130 are shown in Figure 8, where the positive value represents the surface uplift, and the negative value represents the surface subsidence. The results show that the surface deformation of the two sections has experienced the trend of uplift first and then subsidence. This is because of the influence of tunnel face thrust, grouting pressure, shield tail gap, and other factors. During the shield cutter head passing through the measuring point section, due to the shield tail grouting, the Ring 101 section reached the maximum uplift value of 2.9 mm, which increased by 3.19 mm compared with the deformation before the measuring point. The Ring 130 section reaches the maximum uplift value of 1.29 mm, 1.36 mm higher than before reaching the measuring point. After the shield tail passes through, there is a gap between the soil and the segment, and the overlying soil moves downward. Both sections show large settlements. After the cutter head passes far away from the measuring point, the settlement increases further with the dissipation of excess pore water pressure and the consolidation and compression of the soil. The final uplift of the 101-ring section is 2.9 mm, and the final uplift of the 130-ring section is 0.3 mm. In addition, due to the partial load caused by an extensive range of slopes and high retaining walls on the left side of the excavation direction, the soil settlement near the tunnel axis is inconsistent, and the settlement on the left side is significantly larger than that on the right side. This may be because the formation stress on the eccentric loads side is larger.
# A New COVID-19 Detection Method Based on CSK/QAM Visible Light Communication and Machine Learning
## 2 State-of-the-Art Techniques
### Work Related to the VLC Channel
#### 2.1.2 Work on Scattering Distribution Patterns  
When the dust particle size is very small, the proposed dispersion distribution models can be implemented in any type of multipath wireless communication system. However, as the dust particle size increases and the dust concentration causes small holes in the sensors, the waves revert to particle behaviour and scatter more. Previous studies modelled different arrival schemes over time and various communication scenarios [39; 40; 41]. A dust disc around the optical receiver was modelled as a uniform distribution within a 2D disc region [42; 43]. In [40], a statistical analysis was conducted in a hemispheric area around a base station. Using a geometric model of a mobile transmitter channel, the signal's arrival time and direction were analysed. A Gaussian scatter distribution model was presented. Due to the model's spatial-temporal properties, in terms of the arrival angle and arrival time [41], it will eventually be possible to apply it to multipath wireless communication systems. [PERSON] [44] proposed a three-dimensional (3D) stochastic geometry model with a Gaussian distribution centred on an arbitrary point within a sphere.
# Improving Forensic Triage Efficiency through Cyber Threat Intelligence
## 2 Related Work
### Digital Forensic Readiness Operations  
Concentrating on operational approaches for implementing DFR, [PERSON] et al. [14] proposed a network forensic readiness and security awareness framework that aims to preserve, analyse and extract relevant knowledge. However, they did not provide any implications concerning its efficiency. The consideration that many organisations increasingly tend to use flexible Bring Your Own Device (BYOD) policies, which in turn can significantly affect their overall information security and DFR posture, guided [PERSON] et al. [15] to work towards proposing a DFR framework that incorporates honeypot technology to collect, preserve and store Potential Digital Evidence (PDE). Despite its innovativeness, that paper spent little effort proactively analysing PDE and so requires improvement. Similar approaches that employ benign botnets with the aim of achieving DFR on cloud services were proposed by [PERSON] et al. [16; 17; 18]. The idea behind that concept included the installation of obfuscated software on clients' cloud virtual appliances that managed to collect and transmit PDE to pre-configured databases that operated under the Infrastructure as a Service (IaaS) architecture. The prototype they built indicated the applicability of their research, which was primarily focused on proactively gathering PDE, which, in turn, is considered a required step towards ensuring DFR.  
Many researchers agree that fostering proactive forensics requires proper elaboration of the obtained PDE [19; 20; 21; 22; 23]. However, to the knowledge of the authors, there is no technical framework proposed that describes how PDE can be proactively analysed. In addition, the authors have not found any previous work that incorporates threat intelligence as part of the DFR procedures for accurately limiting the volume of digital evidence an investigator needs to examine should an incident occur. To this extent, the next section presents the authors' previous work on efficiently introducing threat intelligence into DFR procedures.
# Sulfonation Treatment of Polyether-Ether-Ketone for Dental Implant Uses
###### Abstract  
There has been a recent uptake in the use of polyether-ether-ketone (PEEK), which is an organic thermoplastic polymer, in the manufacturing of various medical devices, implants, and equipment. Finding the best time and procedure for PEEK after sulfonation is the goal of this research. A total of 30 PEEK discs were sulfonated in this study by immersing them in concentrated (H\({}_{2}\)SO\({}_{4}\)) sulfuric acid for various durations and subsequently treated using various post-treatment techniques. Five experiments were carried out, aimed studying the effect of immersion time (5 s-2 min). The methods used as post-treatment were hydrothermal treatment, immersion in NaOH, and washing with acetone. The sulfonation time was measured, and the post-treatment techniques, surface characterizations, were conducted using scanning electron microscopy (SEM) (Electron Optics Instruments, LLC., West Orange, NJ, USA), atomic force microscopy (AFM) (AFM, Via Burton, CA, USA), and hydrophilic properties. The results were confirmed by attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR). The findings of this study demonstrate that sulfonating PEEK caused a structure with a porous network to form in every sample. As the sulfonation time increased, the porous structure became more noticeable and the concentration increased. As a consequence, the roughness of the surface increased notably, and the modified PEEK surface's wettability improved noticeably. Hydrothermal treatment was determined to be the most successful way for eliminating the leftover sulfuric acid, and sulfonation for 2 min was determined to be ideal. By understanding the best post-treatment procedures and ideal sulfonation duration, a theoretical foundation for the production of sulfonated PEEK for orthopedic uses may be laid.  
polyether-ether-ketone; surface modification; sulfonation; dental implant +
Footnote †: journal: Applied Sciences
## 3 Results and Discussions
### Plenolic Compounds and Antioxidant Activity  
Phenolic compounds are secondary metabolites of plants, and their antioxidant properties have been widely studied [68; 69] due to the benefits they can bring to human health. Derived from the fruits and vegetables that constitute the probiotic beverages, it would be expected that they contain a large amount and variety of phenolic compounds, which makes them high-value-added products. The presence of non-flavonoid phenolic compounds, such as hydroxybenzoic and hydroxycinnamic acids, and flavonoid compounds, such as anthocyanins, flavonols, flavan-3-ol derivatives, and flavones, among others, can be highlighted in fruits and vegetables [60; 62; 63; 64; 66; 68; 70; 71].  
Figure 3 shows the values of total phenolic compounds and the antioxidant activity of the probiotic beverages produced. PFVB1 exhibited the highest total phenolic content, followed by PFVB4, PFVB2, and PFVB3. Statistically significant differences (\(p\leq 0.05\)) were found among the total phenolic content of all PFVB formulations. Regarding antioxidant activity, significant differences were also observed between all of the beverages produced, with PFVB1 reaching the highest value, which is probably related to a higher concentration of phenolic compounds (0.853 \(\pm\) 0.007 g gallic acid/L). However, PFVB3 presented a higher antioxidant activity value (48.1% \(\pm\) 0.628 of DPPH inhibition) than PFVB2 and PFVB4 (33.5% \(\pm\) 1.05 and 46.0% \(\pm\) 1.07 of DPPH inhibition, respectively). Some studies have shown that antioxidant activity is closely related to the content of total phenolic compounds [66; 72; 73], although it must be considered that this parameter is influenced by other non-phenolic compounds such as vitamins, betalains, carotenes, chlorophylls, etc., present in the probiotic beverages. This consideration could justify the values shown by PFVB3. In this sense, the beetroot used in this beverage provides betalains such as betacyanins (red-violet color) and betaxanthins (yellow-orange color), which are potent antioxidants [74].  
Figure 2: Representation of the a\({}^{*}\), b\({}^{*}\), and L coordinates of CIELab space of the different PFVBs.
# Use of SMAP Soil Moisture and Fitting Methods in Improving GPM Estimation in Near Real Time
## 5 Discussion
[69] result, here we also estimated a performance metric based on the national averaged mean error, and found a 64% (from 1.47 mm/day to 0.53 mm/day) reduction with the linear fitting method, which is similar to the reduction in [PERSON] et al. [69]. In addition, we also conducted a sensitivity experiment using the Bayesian method--the same method as used in [PERSON] et al. [69]. In this sensitivity experiment, we calibrate the GPM-CMPA relationship during the 2015-2016 period, and apply the relationship to the bias correction on GPM in 2017. The results show that the Bayesian method makes a smaller improvement (20% reduction in national averaged mean error) than the linear or nonlinear fitting method. The low effectiveness may be associated with thedrawbacks of the Bayesian method--it requires a large number of samples in order to calculate the conditional probability, which limits its applicability when the observational period is short. The daily time step is used in the API model when the SAMP soil moisture is assimilated into the model in this study. As the time scale of surface soil moisture response to precipitation can be shorter, the use of sub-daily time step in the API model would better characterize the fast interaction between soil water and precipitation, which may improve the effect of the bias correction. This should be explored in future research. Figure 6: Box plot of relative difference in RMSE (%) between SMP and GPM (defined as 100% \(\times\) (SMP \(-\) GPM)/GPM) with different ranges of LAI values. Figure 7: Frequency of SMAP overpass in China in 2017.
## 2 Problem Definition and Application of Haptic Feedback Technologies
### Haptic Feedback's Physiological Mechanisms  
Kineshtetic feedback and tactile feedback are the two main categories of haptic feedback. Both have to do with how human muscles, joints, and tendons feel, which may provide us with information regarding weight, strain, gestures, etc. Skin sensation, created through tactile feedback, enables perceiving fine tactile perceptions such as vibration, pressure, texture, etc. As a result, when we engage with the actual world, they help us discern between the form, texture, and other surface features. Joint motions with several degrees of flexibility enable various actions in our daily and professional life. Actuators that can deliver both force and torque are necessary for kinesthetic feedback. The majority of kinesthetic feedback systems rely on heavy external mechanical equipment. Including actuators within the body is a huge problem in creating a torque with a high force required.