esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Numerical Results
### Results of Parametric Analysis
#### 4.3.3 Influence of Strain-Hardening Properties  
The strain-hardening properties relate to the YPL of the stress-strain curve for YPT pipes, and the PLUS ratio for RHT pipes. The influence of variations in \(D/t\) ratio on the relationship between the CLS and the strain-hardening properties is considered to be significant, and is therefore included in the CLS-trend illustrations in Figures 12-15. The plots in Figures 12 and 13 are both obtained for YPT pipes, with \(D/t\) ratio = 41.15 and 82.16, respectively, while the plots in Figures 14 and 15 are both obtained for RHT pipes, with \(D/t\) ratio = 41.15 and 82.16, respectively. The plots for combined axial compression + bending in Figures 12c, 13c, 14c and 15c are all obtained for pipes subjected to compression factor, \(f_{c}\) = 0.2.  
Figure 11: Plots of CLS vs. \(f_{p}\) of RHT pipes with PL/US = 0.691 for (**a**) uniform axial compression, (**b**) uniform bending, and (**c**) combined loading (\(f_{c}\) = 0.6).  
Figure 12: Plots of CLS vs. YPL of YPT DT1 pipes for (**a**) uniform axial compression, (**b**) uniform bending, and (**c**) combined loading (\(f_{c}\) = 0.2).  
Figure 10: Plots of CLS vs. \(f_{p}\) of YPT pipes with YPL = 1.25% for (**a**) uniform axial compression, (**b**) uniform bending, and (**c**) combined loading (\(f_{c}\) = 0.6).  
The plots above indicate that the influence of the strain hardening properties of the pipe material is more prevalent in pipes with low \(D/t\) ratios (DT1) for YPT pipes; as the \(D/t\) ratio of the pipe increases, the influence of the YPL on the CLS diminishes. For YPT pipes of low \(D/t\) ratio (DT1), a positive relationship is observed between the YPL and the CLS at a high internal pressure (\(f_{p}\) = 0.8). The YPL indicates a progressively negative correlation with the CLS as the internal pressure drops below 60% YS. On the other hand, a negative correlation between the PLUS ratio and the CLS is more apparent at higher \(D/t\) ratios and the influence tends to diminish as the \(D/t\) ratio decreases. As is the case for YPT pipes with low \(D/t\) ratio (DT1), a positive (but relatively less significant) relationship between the PLUS ratio and the CLS of RHT pipes with low \(D/t\) ratio (DT1) is also observed at high internal pressure (\(f_{p}\) = 0.8).
## 2 Materials and Methods
### Substrates and Inoculum Characterisation  
The main substrate used in the experiments was the AS derived from fish oil extraction. A co-substrate mimicking fruit and vegetable market waste (MW), and composed of 49.0% \(w/w\) of potatoes, 44.4% \(w/w\) of apples, and 6.6% \(w/w\) of carrots, was also used. Both substrates were characterized by measuring the total and volatile solids, pH, and carbon to nitrogen ratio (C/N), while \(d\)-limonene content was determined only in the AS. Total and volatile solids and pH were evaluated according to standard methods [22], the C/N was measured using an elemental analyser TOC-LCSH (Shimadzu; Kyoto, Japan) while the analysis of the residual \(d\)-limonene, present in the substrate, was carried out according to the analytical procedure previously reported [15], by mixing 0.3 g of AS with 3 mL of a toluene solution (as an internal standard) in cyclohexane (0.1 M) for 6 h. The liquid suspension was then filtered and injected into an offline GC-FID (Agilent 6890 N) equipped with a CP-WAX 52 CB column (60 m, id. 0.53 mm).  
The inoculum used in batch and semi-continuous experiments was a digestate coming from previous experiments. It was characterized by measuring total and volatile solids and pH evaluated according to standard methods [22]. Table 1 reports the main characteristics of substrates and inocula.
# Swing Analysis and Control Research of the Space Tethered Combination in the Maneuver Process
## 1 Introduction
Firstly, a dynamical model of the space tethered combination, based on the maneuver of the mission platform, was established. Additionally, three formations of the swing of the tethered combination were analyzed according to the dynamical model. Secondly, in order to solve the swing problem, the anti-swing control strategies, such as linear feedback control, approximate linearization control and variable structure control, were proposed. Lastly, the ground experiment setup was built to test the control strategies.
## 5 Discussions
### Fall Detection Sensors and Devices  
The great majority of the proposals surveyed in this review research rely solely on accelerometer readings for detection. Only in ten of the studies does the system employ the information produced from the gyroscope measurements (as additional inputs) [37]. Given that inertial measurement units (IMUs) have a combination of accelerometers and gyroscopes as standard, the computational times based on hardware resources should be minimal, especially the signals from the gyroscopes in the detection decision. The systematic examination of the benefits brought by integrating the gyroscope and accelerometer readings is still an open question in the research field. Recent research with CNNs has shown that using gyroscope signals can improve discrimination reliability when compared to solely using accelerometer measures [69].  
One of the current problems with portable fall detection sensors is the long delay time for getting the appropriate assistance to arrive at the site where the fall happens [85]. The injured person's life may be lost as a result of this delay before getting the necessary assistance or medical treatment. Therefore, there is a trend to develop a reliable video-based fall detection sensor that will eventually exceed existing portable fall detection sensors as follows. The video-based sensor will be cost-effective and more accurate in detecting falls to provide fast response detection of a fall; consequently, the delay time to provide the necessary assistance to the injured person will be reduced. Moreover, it will protect people's privacy by using only the binary image of the person. Furthermore, older people will be more comfortable without wearing portable fall detection devices all the time during their daily activities [85]. However, it is not always the ideal case, especially for elderly people with cardiac and breathing disorders, because there is always a need to monitor all their vital signs via wearable sensors.
## 3 Results
### Quality Parameters of Fried Potato Fries
#### 3.3.3 Acrylamide Content in Fries  
The contamination of fries with acrylamide (AA) increased with the frying time. Only in the case of fries fried at BW 0.5 was an inverse relationship observed. For all products, the AA level was high and exceeded the value of 500 \(\mu\)g/kg set in the Commission Regulation (EU) 2017/2158 of 20 November 2017. However, the color did not indicate excessive frying or burning. It was found that fries fried in media with waxes contained more AA than fries fried in rapeseed oil without additives. In the first frying cycle, the lowest contamination of this carcinogenic substance was found in fries fried in RO and RW 0.25, while the highest was in RW 0.5. The formation of AA is one of the products of the Millard reaction, mainly influenced by the presence of reducing sugars and asparagine; these are ingredients present in potatoes. One of the theories says that acrolein (a substance formed as a result of the breakdown of triacylglycerlycerols) may influence the formation of AA [18]. In the case of fries fried in the third cycle, the lowest values were reported for products prepared in RO and BW 0.5 media, which was confirmed by statistical analysis (Figure 4). Studies on acrylamide formation in fried foods showed that an increased acidity (above 0.5 mg KOH/g) in oils can mitigate it [27]. This study is in opposition to these findings. Until now, the effect of waxes on acrylamide formation had not been studied before. It was found that RW may have a stronger effect than BW on AA formation, especially in the case of longer frying times on the same medium. However, other substances present in the waxes, as well as the oil oxidation products of the oil and waxes, may have influenced AA formation [37].  
In the studies of [PERSON] et al. [38], it was found that the type of frying medium may influence the amount of AA contamination. Those authors found that red palm olein, followed by soybean oil and sunflower oil, had the highest content of this cancerogenic compound, and palm olein had the lowest. However, most of the oil degradation parameters were not significantly different. Another study by [PERSON] et al. [39] showed that with an increase in frying times and degradation processes of palm oil-based frying media, the AA concentration increased. Moreover, researchers found that the addition of TBHQ antioxidants was the most effective in the mitigation of acrylamide formation in fries and potato snacks, but a combination of TBHQ and E330 significantly increased the concentration of this substance, including palm oil-rapeseed oil mixtures without additives.  
Figure 4: Acrylamide content in fries. A, B, C indicate homogeneous groups determined by [PERSON]’s test (_p_-value < 0.05) for 1 frying cycle; a, b, c, d indicate homogeneous groups for the 3 rd frying cycle.
# The Role of Data Analytics in the Assessment of Pathological Speech--A Critical Appraisal
## 2 ML Methods in Laryngeal Pathology Assessment
### Methodological Considerations  
The first issue to be examined is to which extent voice disorder diagnosis itself can be granted by current AI methods. What most research publications report is binary classification on voice recordings, labeling them as pathological or not based on acoustical correlates, a result that can be barely considered a true diagnosis under clinical standards. The diagnosis of voice disorders is a rather complex process conducted by highly specialized professionals (medical doctors) applying many different analytic and exploratory methods, which include visual and instrumental inspection, such as video laryngoscopy, imagery from x-ray, fMRI, echography, electroglottography, etc., and supported by sophisticated syndrome definitions and differential diagnosis methods. Clinically speaking, what might be expected from voice disorder diagnosis should be the main label (with an associated posterior probability) selecting the potential pathology from a list of voice disorders [10], and the etiology of the pathology, conditioned to a set of features estimated not only from one but from as many acoustical recordings as possible, is assumed to be the ones better suited to describe the problem. What may be expected from laryngeal pathology assessment ML systems is a qualified and objective help estimating specific meaningful features which may be indicators of anomalous phonation, respiration, articulation, and fluency of sufficient value to address the patient to specialized services, which will be in charge of completing medical diagnosis. This has to be substantially made clear by any publication, therefore, any claim on providing automatic diagnosis from the acoustic speech signal to their ultimate implications might be taken with care, under the risk of being untrustworthy and misleading.
# An Automatic Participant Detection Framework for Event Tracking on Twitter
## 3 Materials & Methods
### Framework
#### 3.1.6 Post-Processing  
The post-processing step concludes the framework by cleaning the participant names. This step depends on the designated application for participants, but since we map participants to Wikipedia, it would generally be desirable to remove text in parentheses because it serves as a disambiguation detail. For example, the article title of Barcelona's goalkeeper, [PERSON], is [PERSON] (footballer, born, 1989) due to his relatively common surname. Post-processing reduces this title to just [PERSON].  
We also note that sports domains, which we focus on in this article, are filled with informal orthography. In particular, it is common practice to refer to participants by their surnames, and on Twitter they are seldom written with accents. Therefore we remove accents and reduce the names of persons to their surnames, unless the surname is an English lexeme. To decide whether a participant is a person, we look for a date of birth in their Wikipedia page.  
The final ranking concatenates the lists of resolved and extrapolated participants. We place the resolved participants first since the algorithm captured them directly from the pre-event stream, and thus we can be more certain that they are discriminative and temporally-relevant. Before analyzing this final ranking, we introduce our evaluation methodology for APD.
## 2 Materials and Methods
### HPLC-DAD-MS Analyses of Carotenoids  
HPLC-DAD-MS analyses were carried out with an Agilent model 1100 equipped with quaternary pump solvent delivery, a thermostated column compartment, diode array detector, and XCT-trap mass detector (Agilent Technologies, Palo Alto, CA, USA). A positive electrospray mode was used for the ionization of molecules with acquisition of mass spectra between _m/z_ 100 and 1200, capillary voltage at -4000 V, and skimmer voltage at 30 V. The reversed stationary phase employed was a YMC pack C\({}_{30}\) (YMC Inc., Wilmington, NC, USA) 5 \(\upmu\)m (250 \(\times\) 3 mm i.d.) with a precolumn C\({}_{30}\) 5 \(\upmu\)m (20 \(\times\) 3 mm i.d.). The following gradient system was used with H\({}_{2}\)O (solvent A), methanol (solvent B), and tert-butyl methyl ether (solvent C): 0 min, %A-%B-%C, 40-60-0; 5 min, %A-%B-%C, 20-80-0; 10 min, %A-%B-%C, 4-81-15; 60 min, %A-%B-%C, 4-11-85; 65 min, %A-%B-%C, 4-11-85; 65 min, %A-%B-%C, 4-11-85; 70 min, %A-%B-%C, 40-60-0. Stop time at 70 min with a re-equilibration time of 20 min corresponding to ca 3.0 column volumes (Vc = 1.3 mL). The column was kept at 20 \({}^{\circ}\)C, the flow was maintained at 0.2 mL/min, and the sample injection volume was 3 \(\upmu\)L. Diode array detection was between 250 and 700 nm and absorbance was recorded at 447 nm. Positive electrospray mode was used for the ionization of molecules with a capillary voltage at -4000 V and skimmer voltage at 40 V. The nebulizer pressure was 15 psi and the nitrogen flow rate was 5 L/min. The temperature of drying gas was 350 \({}^{\circ}\)C. In the full scan mode, the monitored mass range was from _m/z_ 100 to 1200. MS\({}^{2}\) was performed byusing helium as the collision gas at a pressure of \(4.6\times 10^{-6}\) mbar. Collision induced dissociation (CID) spectra were obtained with an isolation width of 4.0 \(m\)/z for precursor ions and a fragmentation amplitude of 0.6 V for epoxyxanthophylls, and 1.0 V for the other carotenoids. Compound identification was achieved by combining different information: the positions of absorption maxima (\(\lambda_{\text{max}}\)), the degree of vibration fine structure (% III/II), the ratio of the absorbance of the _cis_ peak to the absorbance of the second absorption band in the visible region, known as the Q ratio or D\({}_{\text{B}}\)/D\({}_{\text{II}}\)[8; 24], and the capacity factor values k\({}^{\prime}\) and mass spectra were compared with those from pure standards and interpreted with the help of structural models already hypothesized in the literature (such as (9Z) or (9\({}^{\prime}\)Z)-lutein and the other lutein-like structures reported in Table 1, which were only tentatively identified) [4].
## 4 Results and Discussion  
### Benchmark Response Curves  
Before starting the experimental campaign, according to Table 2, some pilot tests were carried out in order to optimize the layout and check the effectiveness of the procedure.  
Two pilot tests were performed in parallel on specimens produced from Portland (CEM II/A) and pozzolanic (CEM IV/B) cement pastes, respectively; the tests aimed at experimentally reproducing well-established theoretical results. Specifically, it is known from the literature that the high content of clinker in CEM II/A cement produces very quick hardening with high stiffness reached in a reduced amount of time, with nearly the final value approached after 28 days of curing. Conversely, the low content of clinker characterizing CEM IV/B cement yields slower hardening with respect to the previous case in the same initial period. Such theoretical trends were confirmed by the experimental outcomes, as shown in Figure 4. Figure 4a shows the evolution of the elastic modulus E as a function of time for the two specimens. A time window of 120 h since casting was considered, and the value of E was normalized with respect to the maximum value E\({}_{\text{max}}\) recorded in that period for the considered specimen in order to improve comparability of the curves: in fact, these refer to cement types characterized by different final strength and stiffness properties. Furthermore, a 23-term moving average was applied to smoothen the curves and further reduce the noise influence.  
The incremental ratio R of E/E\({}_{\text{max}}\) computed over the time interval of 15 min is reported in Figure 4b, together with a detailed view of the trends, while the curves of the elastic modulus approach the maximum value. Figure 4b points out that the CEM II/A curve grows faster and higher than the CEM IV/B one. Indeed, at the point of inflection, R is equal to 0.32 1/h for the CEM II/A curve and 0.22 1/h for the CEM IV/B curve. From 72 to 120 h (see top of Figure 4b), the CEM II/A curve is almost approaching zero, i.e., the maximum stiffness, whereas the CEM IV/B curve is still far from the horizontal axis. In fact, the fitting lines (dotted lines) yield R values at 120 h equal to 3 \(\times\) 10\({}^{-4}\) 1/h and 3.2 \(\times\) 10\({}^{-3}\) 1/h, respectively.
# PVPBC: Privacy and Verifiability Preserving E-Voting Based on Permissioned Blockchain
## 7 Security Analysis
### Security Attributes
#### 7.1.3 Integrity  
The PVPBC-voting-system design ensures that even an insider at the EA or an attacker gaining access to the vote cannot invisibly change votes, as any change can be detected by a voter performing a verification. Consequently, the PVPBC voting system no longer requires the election provider to be trusted to ensure election integrity. This is because it can be verified independently. Use of DLT trustees means that the authority alone cannot change the commitments and verifiability parameters, because collusion between a majority threshold of trustees would be required.
# Automated Anomaly Detection and Causal Analysis for Civil Aviation Using QAR Data
## 6 Experimental Evaluations
### Case Study  
To verify whether the proposed model can be truly applied in reality, we conducted practical experiments on other flight data.  
Figure 10 shows an example of anomaly detection and causal analysis. According to Figure 10a, it can be seen that there has been an _ILS glide slope deviation_ on this flight route and the red markers in the figure indicate the outliers. Further analysis of the abnormal situation was performed and the results are shown in Figure 10b.  
Specifically, it shows the feature contribution ranking of the abnormal event of _ILS glide slope deviation_ during this flight. The parameters with the highest contribution ranking (excluding the radio altitude of the monitoring point and the monitoring parameters of each abnormal event) include ILS Heading (_LOC_DEVICE_), difference between air speed and approach speed target (_IAS - VAPP_), rudder position (_RUDD_), and so on. These parameters are all flight state parameters and monitoring parameters of FOQA in Table 2, formed by pilot operations. Therefore, we preliminarily conclude that the abnormal event of this flight was caused by human factors.  
Figure 11 shows the detection results of multi-type anomalies. According to the figure, the red markers indicate outliers. The method in this paper detected multi-type abnormal events during the approach phase of this flight--namely, _ILS Heading Deviation_, _Large Decline Rate (500 ft\(\sim\)50 ft)_, and _ILS Glide Slope Deviation_.  
Figure 10: Example of anomaly detection and causal analysis. (**a**) high speed during approach phase; (**b**) causal analysis of high speed during approach.  
Figure 9: SHAP Interpretation Chart. (**a**) SHAP interpretation chart of MAD-XFP; (**b**) SHAP interpretation chart of anomaly label 1 (removed IVV, RALTC, and their combinations).  
Figure 12a-c are feature contribution ranking diagrams of the abnormal events that occurred during the flight of the aircraft shown in Figure 11. Similar to the above analysis method, parameters more related to the _ILS Heading Deviation_ include ILS glide slope (_GILDE_DEV_), gross weight of aircraft (_GW_), geographic location information (_LONPC/LATPC_), and speed of low-pressure turbine (_N11_). In addition to the parameters mentioned above, the parameters more related to _Large Decline Rate (500 ft\(\sim\)50 ft)_ include flight path angle (_FPA_), interaction information between flight parameters and flight status (_N11/VB11_), ground speed (_GSC_), and so on. The parameters more related to the _ILS Gilde Slope Deviation_ include wind speed (_WIN_SPD_). Based on the analysis of the above characteristics, the abnormality that occurred during this flight was the result of the combined effects of human factors and environmental factors.
# A Completion Method for Missing Concrete Dam Deformation Monitoring Data Pieces
## 1 Introduction
### Monitoring Data Characteristics
#### 1.2.3 Uncertainty  
In the concrete dam deformation monitoring system, uncertainty arises since the interaction among the dam body, the dam foundation, and the monitoring system require different monitoring methods. The instrument precision variance, instrument performance degradation, and other factors also increase the uncertainty of the measured monitoring values [26; 27]. In addition, the process of both manual and automatic monitoring can introduce errors and noises, which contributes to another source of uncertainty in monitoring data. Therefore, the monitoring information of the concrete dam deformation is uncertain.