esa-sceva/satcom-chunk-collection huggingface dataset:
# Effect of Bentonite Content and Hydration Time on Mechanical Properties of Sand-Bentonite Mixture
## 1 Introduction
Hollow cylindrical torsional shear tests under three typical stress conditions were simulated [28]. [PERSON] et al. (2017) adopted the 3D discrete element method to simulate true triaxial compression tests and elucidate the failure mechanism of sandstone and the effect of the intermediate principal stress [29]. [PERSON] et al. (2019) established a series of 3D discrete element models studying the effect of gravel content on the simple shear behavior of SGM from a microscopic point of view [30]. The influence of bentonite on the sand was attributed to the combination of physico-mechanical action and chemical action. In the physico-mechanical perspective, the interface contact between sand particles was reorganized by bentonite, which has an influence on the mechanical behavior of sand. Thereby, the newly developed sensors and numerical approaches were used for experimental tests and field conditions [31; 32; 33]. In this study, a macro and meso study was conducted on the effect of bentonite on mechanical properties of the sand-bentonite mixture by means of experimental tests and numerical methods. Firstly, a series of drainage static triaxial tests on sand specimens with various bentonite contents were conducted to study the effect that bentonite has on the sand-bentonite mixture. Then, a series of 3D DEM models were established to simulate the experimental drainage static triaxial tests. The numerical model parameters were calibrated by experimental results. Finally, the effect of bentonite content and hydration time on the mechanical properties of the sand-bentonite mixture and the meso-mechanism were discussed and revealed. It would be helpful to understand further the mechanism of bentonite on the mechanical properties of the sand-bentonite mixture from the macro and meso aspects, respectively.
# Investigations into Picture Defogging Techniques Based on Dark Channel Prior and Retinex Theory
## 4 Experimental Outcomes and Discussion  
An 11 th Generation Intel(R) Core (TM) i7-11800H CPU operating at 2.30 GHz and running Windows 11 comprises the hardware environment for this experiment. The technique is implemented using the MATLAB 2023a platform. In order to verify the effectiveness and generalizability of this technique, we conducted comparative experiments with the MSR [15], DCP [19], Meng [27], Tarel [29], and Grid_Net [38] algorithms.  
As shown in Figure 5, we selected 10 test images: 6 self-selected images (Img1-6) and 4 public dataset images (Img7-10). Img7 and Img8 are from the dataset NH-HAZE, and Img9 and Img10 are from the dataset RESIDE. Img1, Img3, Img4, Img5, Img7, and Img9 contain sky regions, while Img2, Img6, Img8, and Img10 do not contain sky regions. A comprehensive evaluation of the Retinex and dark channel a priori defogging algorithms was performed using both subjective and objective evaluations, with particular attention paid to halo artifact suppression in the non-sky regions, color fidelity in the sky scene, and consistency across datasets.  
Figure 5: Test images: (**a**–**f**) self-collected foggy images (Img1–6); (**g,h**) NH-HAZE dataset (Img7–8); (i,j) RESIDE dataset (Img9–10).
# Seismic Analysis of Slender Monumental Structures: Current Strategies and Challenges
## 4 Structural Analysis Methods
The non-linear static analysis shows a diffuse cracking in the lowest part of the tower and a base overturning mechanism, but the maximum load factor results are very dependent on the adopted force distribution (Figure 8a): in fact, the load factors proportional to the first mode and to the linear distribution equal, respectively, 35% and 53% of the load factor proportional to the mass. The collapse section varies as well: in the case of forces proportional to the mass, the analysis shows a base collapse mechanism, whereas for the other analyses the collapsesoccur at the level of the first balcony. By contrast, the non-linear dynamic analysis proves that the most vulnerable parts of the minaret are the top two stories (Figure 8b), which is in agreement with the damage observed during past earthquakes. Such a difference in the results is due to the influence that higher modes have on the seismic behavior of the tower, modes whose participation is not considered in the standard pushover. To account for this aspect, the seismic assessment was repeated using a modal pushover analysis and considering seven modes for each direction. While displacements and drifts for the first three levels (Figure 8c) are similar to those estimated with the non-linear dynamic analyses, MPA is not able to reproduce satisfactory the failure mechanism of the last two levels. This inconsistency is explained by the variation of the tower's dynamic properties during the damage process, variation that cannot be caught with a modal pushover because the influence of each mode is considered constant throughout the analysis. An alternative is to adopt adaptive pushover analysis [65,66], in which the load distribution depends on the current main mode of vibration, but poor results have been obtained for these complex and relatively brittle structures. Figure 8: Seismic assessment of the Qutb Minar tower. Comparison of the results from different analysis methods [64]: (**a**) capacity curves for pushover analyses, (**b**) maximum load factor and displacements along the minaret height for dynamic analyses, (**c**) displacements and drifts along the minaret height for modal pushover and non-linear dynamic analyses. Given the time-dependency of the problem, the non-linearity of the material and the influence of higher modes on the seismic behavior of slender monumental structures, non-linear dynamic analyses appear to be the most appropriate numerical procedures to evaluate the performance of these special constructions against earthquakes [67, 68]. It is noted that the definition of collapse and other performance levels is quite difficult, and the pros and cons of adopting such a complex tool must be carefully considered. Depending on the prominence of the monument and on the objectives of the analysis, a balance between accuracy and complexity must be achieved.
## 4 Discussion  
The long-term mooring measurements of ambient noise demonstrated a proportional relationship between the snap rate and the surface water temperature at 71 times/minute for every 1 \({}^{\circ}\)C. The fluctuation of the snap rate was highest in the summer at night, sunrise, and sunset and lowest during the day in the coastal sea of western Jeju Island for 90 days from mid-September. The snap rate had a weak coherence with the tidal level for about 15 and 30 days (Lunar cycles), but the 45-day consecutive measurements were not enough to make a concrete conclusion. These results show the indirect measurements of snapping shrimp activity, which is highly related to water temperature and tidal level with a semidiurnal and diurnal variation.  
Even though we measured the ambient noise twice for 45 days, there was a gap of 6 days (for hydrophone-battery and SD-card replacement) between the two measurements, making it challenging to have a consecutive long-term analysis of the tidal period. The high-frequency component disappeared while processing the unmeasured data for 6 days using a moving average, but there was no significant effect on circadian and lunar cycle changes. To compensate for this, a plausible way is employed to give an artificial signal-based mean and standard deviation correlated with different temperatures and tidal levels. It is expected that a more accurate long-term analysis will be possible if the analysis method that can fill this measurement gap is further supplemented by future research.  
The quantitative analysis of snapping sound has rarely been done in situ. There is a recent paper regarding the sound of the snapping shrimp measured in relatively deep waters of the southern part of Korea [29]. Unlike this study, the snap rate was quantitatively  
Figure 6: Wavelet transform analysis of snap and tide level. (\(\Circle\): Full moon, \(\bullet\): New moon, \(\blacksquare\): fill in the missing snap rate data); The wavelet analysis results in (**a**) coherence between snap rate and tidal level, (**b**) tidal level, and (**c**) snap rate.  
expressed by analyzing the data measured for a short period at depths where visible light rarely enters. Although there is a seasonal difference in the measurement period in May, a snap rate of 200 to 1200 times occurred, and the snap rate changed according to the sea level [31].  
The circadian change of the snap rate of snapping shrimp was observed in a few studies as shown in Table 1. For example, in St. John, located in the Caribbean Sea, USA, the snap rate of snapping shrimp increased rapidly at sunrise and sunset, but it was higher during the day than at night [29]. In contrast, in North Carolina (USA), day and night snap rates changed with measurement time [16]. Meanwhile, at the Ieodo Science Station in the south of Jeju, the snap rate of snapping shrimp showed a change with wind speed but did not exhibit a circadian pattern [15].
## 3 Results
### Description of Response to Perturbation for Kinematic and Kinetic Parameters-Perturbed Limb
#### 3.2.2 Kinematic Parameters  
In this section, the approach was identical to the previous one. The maximal and minimal values of lower limb joint angles were compared between young and old subjects within each strategy and treadmill gait (Figure 6A-D).  
Figure 5: The means and standard deviations for the ground reaction force curves of the perturbed limb (left) compared to those noted during treadmill gait in a group of young (Y) and elderly (O), where: **(A)** Strategy I, **(B)** Strategy II, **(C)** Strategy III, **(D)** Tradmill gait (reference), PD–vertical component, AP–anterior-posterior component, ML–medial-lateral component. The tables show the minimum and maximum values for the three components of ground reaction forces for the three strategies and treadmill gait, as well as statistically significant differences between the groups and effect size (r). Bold font indicates that values in group O were higher than in group Y. When comparing negative values, their absolute values were considered.  
Most of the values recorded in the older group were higher than those achieved in the young group. Non-significant exceptions included the ankle dorsiflexion and the hip flexion angles in Strategy I. Moreover, significantly higher plantarflexion was observed in the young group. In Strategy II, the significant differences from the rule were for ankle plantarflexion and knee flexion. In Strategy III, the exception was only for ankle  
+++ ==WARNING: Truncated because of repetitions==
plantarflexion, which was significantly greater for young people. During treadmill gait, hip flexion angle, and ankle and knee joints' extreme values were higher in the young group.  
The strategy with the highest number of extreme values deviating the least from those recorded for treadmill gait seems to be the one that should be adopted most often by the subjects. For this purpose, the differences between the extreme values adopted for each strategy and those for treadmill gait were counted separately in the two groups (Table 2). In the youth group, out of six differences, four were minimal, one was medium, and one was maximum for Strategy I. For Strategy II: 1-minimum, 4-medium, and 1-maximum. For Strategy III: 1-minimum, 1-medium, and 4-maximum.  
Among older people, out of the six differences, three were minimum, one was medium, and two were maximum for Strategy I. For Strategy II: 1-minimum, 4-medium, and 1-maximum. For Strategy III: 2-minimum, 1-medium, and 3-maximum.
## 3 Searches for Physics Beyond the Standard Model
### Dedicated Search for Axion-Like Particles  
Compared to the mass region probed by VMB measurements, a heavier region can be studied by using X-rays [41; 42]. Especially, the ALP mass around 10-100 meV attracts recent cosmological interests in the inflation, the cosmic microwave background radiation, and dark matter [43]. The photon conversion into a real-state ALP (or vice versa) in a magnetic field is referred to as the \"Primakoff effect\". Up to now, a large number of laboratory searches for ALPs have been carried out with a \"light shining through a wall (LSW)\" technique [16]. The first X-ray LSW search was carried out at the European Synchrotron Radiation Facility (ESRF) with superconducting magnets, extending the limit on the ALP-two-photon coupling constant (\(g_{\alpha\gamma\gamma}\)) up to around 1 eV [44]. While searches for ALP flux from the Sun have also probed this mass region [45], the flux estimation inevitably relies on a solar model and its complex magnetic activity [46], showing the importance of complementary searches using terrestrial and extra-terrestrial X-ray sources [44].  
Figure 10 shows a schematic of our LSW setup using four magnets described in Section 2.3. The ALPs generated in the first pair of magnets pass through a beam dump that blocks the unconverted photons. Some of the ALPs then reconvert into detectable photons by an inverse process in the second magnet pair. We carried out the first measurement at SPring-8 BL19 LXU [47] in 2015 using a continuous X-ray beam with high intensity. The data obtained with a total of 27,676 pulses produced in a net run time of two days show no events in the signal region (Figure 11, left). This provides a limit on \(g_{\alpha\gamma\gamma}\) that is more stringent by a factor of 5.2 compared to the previous X-ray LSW limit for the ALP mass \(\lesssim\)0.1 eV (Figure 11, right). The pulsed nature of the magnet provides better sensitivity when used with pulsed X-rays (the repetition is 30 Hz at SACLA; see Figure 7(left) for the corresponding time interval between the magnetic pulses). The expected sensitivity at SACLA with the same magnets and configurations are also shown in the figure.  
Figure 9: Photon–photon scattering by axion-like particles. (**Left**) \(s\)-channel. (**Right**) \(t\)-channel.
## 4 Experimental Results
### Significance Test  
To compare the forecasting performance of the different models, non-parametric statistical tests were employed. Specifically, the Friedman test--a post hoc method--was used to identify statistically significant differences among the algorithms. The corresponding Friedman statistics are provided in Table 12. In cases where the \(p\)-value was less than 0.05, the null hypothesis--stating that the models' average performances were equal--was rejected. This result indicates that at least one of the models performed significantly better than the others, confirming the presence of statistically meaningful differences among them.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Model** & **MAPE** & **RMSE** & **TIC** & **STD\_AE** & **RAE** & **STD\_APE** \\ \hline LSTM & 0.0474 & 542 & 0.024 & 364 & 0.1032 & 5.517 \\ GRU & 0.0488 & 544 & 0.024 & 359 & 0.105 & 5.447 \\ RNN & 0.0568 & 634 & 0.0282 & 431 & 0.119 & 7.244 \\ NARX & **0.042** & **449** & **0.022** & **311** & **0.0947** & **5.267** \\ \hline \hline \end{tabular}
\end{table}
Table 10: Model predictions for bus public transit: Kadikov–Pendik route.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Model** & **LSTM** & **GRU** & **RNN** & **NARX** \\ \hline LSTM & 1 & 0.00819 & 0.00021 & 0.03792 \\ GRU & 0.00819 & 1 & 0.00437 & 0.00062 \\ RNN & 0.00021 & 0.00437 & 1 & 0.00005 \\ NARX & 0.03792 & 0.00062 & 0.00005 & 1 \\ \hline \hline \end{tabular}
\end{table}
Table 12: Post hoc results of the Friedman test.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Model** & **LSTM** & **GRU** & **RNN** & **NARX** \\ \hline LSTM & 1 & 0.00819 & 0.00021 & 0.03792 \\ GRU & 0.00819 & 1 & 0.00437 & 0.00062 \\ RNN & 0.00021 & 0.00437 & 1 & 0.00005 \\ NARX & 0.03792 & 0.00062 & 0.00005 & 1 \\ \hline \hline \end{tabular}
\end{table}
Table 11: Model predictions for rail public transit: Kadikov–Pendik route.
###### Abstract  
This paper presents a comprehensive analysis of the phytochemical profile of a proprietary rosmary (_Rosmarinus officinalis_ L.) extract rich in carnosic acid. A characterization of the (poly)phenolic and volatile fractions of the extract was carried out using mass spectrometric techniques. The (poly)phenolic composition was assessed by ultra-high performance liquid chromatography-electrospray ionization-mass spectrometry (UHPLC-ESI-MS\({}^{\text{n}}\)) and a total of 57 compounds were tentatively identified and quantified, 14 of these being detected in rosmary extract for the first time. The rosmary extract contained 24 flavonoids (mainly flavones, although flavonols and flavanones were also detected), 5 phenolic acids, 24 triterpenoids (carnosic acid, carnosol, and rosmanol derivatives), 1 triterpen (betulinic acid), and 3 lignans (medioresinol derivatives). Carnosic acid was the predominant phenolic compound. The volatile profile of the rosmary extract was evaluated by head space solid-phase microextraction (HS-SPME) linked to gas chromatography-mass spectrometry (GC-MS). Sixty-three volatile molecules (mainly terpenes, alcohols, esters, aldehydes, and ketones) were identified. This characterization extends the current knowledge on the phytochemistry of _Rosmarinus officinalis_ and is, to our knowledge, the broadest profiling of its secondary metabolites to date. It can assist in the authentication of rosmary extracts or rosmary-containing products or in testing its bioactivity. Moreover, this methodological approach could be applied to the study of other plant-based food ingredients.  
rosemary; polyphenol; volatile compound; phytochemical characterization; UHPLC-ESI-MS\({}^{\text{n}}\); HS-SPME/GC-MS +
Footnote †: journal: molecules
# Blockchain Technology and Its Potential to Benefit Public Services Provision: A Short Survey
## 5 Applications
### Public Records Management  
The all-embracing term \"public record\" refers to any piece of personal information that has been processed and stored by a public office. Within this context, blockchain technology could be used to provide access to information stored in a single location, moving beyond a scenario in which different pieces of personal information are usually stored in different databases that do not communicate with each other. The so-called \"integration of resources\", namely the enhanced information exchange and cooperation between different public organizations, is one of the key benefits that the technology could bring. Refs. [68; 74] mention civil registration, the storage of birth/marriage/death certificates, as one of the main areas of blockchain application. By storing information in a decentralized way, the technology could prevent unauthorized access, thereby preventing the records from being tampered with. Ref. [19] identifies public record management as the main sector that could potentially be affected by blockchain technology, with the latter being used to make records more accessible, reducing the cost of registering information and ensuring that records are kept up to date. Blockchain-based technologies could also be leveraged for asset registration. Ref. [24] highlights the use of smart contracts for property registration to verify the identity of the buyer and seller and automatically register the property on behalf of the new owner [71]. Land registry is cited by both [63; 64] as a field where blockchain technology could be exploited as well, with the latter reporting Sweden's experimentation of a blockchain-based solution for the transfer of land titles, reducing the amount of time required for property registration from 4 months to a few days, leading to time and cost savings [37].
## 3 Model of Tooth Contact Analysis with Shaft Misalignments
### Theories of Meshing Point and Transmission Error  
The calculation of the meshing points of the theoretical tooth surface without load is discussed below. As shown in Figure 11, we assume that the gear and pinion are at a certain rotational angle \(\kappa_{1}\), \(\kappa_{2}\) and the theoretical tooth flanks are \(\sum_{1}\), \(\sum_{2}\), on which the location vectors and normal vectors of any points are \(r_{\Sigma 1}^{(p)}(\kappa_{1},u_{1},v_{1})\), \(r_{\Sigma 2}^{(g)}(\kappa_{2},u_{2},v_{2})\) and \(n_{\Sigma 1}^{(p)}(\kappa_{1},u_{1},v_{1})\), \(n_{\Sigma 1}^{(p)}(\kappa_{1},u_{1},v_{1})\), respectively. These vectors are given by  
\[n_{\Sigma 1}^{(p)}(\kappa_{1},u_{1},v_{1})=M_{01}^{(p)}(M_{\kappa 1}^{(p)}.n _{1}^{(p)}) \tag{30}\]  
\[n_{\Sigma 2}^{(g)}(\kappa_{2},u_{2},v_{2})=M_{\kappa 2}^{(g)}.n_{2}^{(g)} \tag{31}\]  
If there are contact points on the tooth surface, the following requirements should be determined: the position vector and unit normal vector need to be equal to that of the other tooth surface at the tooth contact point of the gear pair in the absolute coordinate system at any time.  
\[M_{01}^{(p)}.(M_{\kappa 1}^{(p)}.r_{1}^{(p)})=M_{\kappa 2}^{(g)}.r_{2}^{(g)} \tag{32}\]  
Figure 11: Tooth surface vectors.  
\[M_{01}^{(\rm p)}(\cdot M_{\kappa 1}^{(\rm p)}\cdot n_{1}^{(\rm p)})=-M_{\kappa 2}^{( \rm g)}\cdot n_{2}^{(\rm g)} \tag{33}\]  
From the above Equations (30) and (31), we can obtain five independent equations, including three independent equations of the corresponding coordinate vectors on the contact points of the gear and pinion and two independent equations of the unit normal vectors of the contact points which are opposite to each other. Therefore, when \(\kappa_{1}\) is determined, the meshing point can be calculated correspondingly. Further, the contact trajectory of meshing points can be calculated by rotating the pinion. Generally, the contact trajectory of meshing points is called the tooth contact path.  
We assume that the rotation angle of the pinion is a function of time \(t\); that is, \(\kappa_{1}=\kappa_{1}(t)\). The rotation angle of the meshing point of the gear can be a function of time \(t\) by Equations (20) and (21); that is, \(\kappa_{1}=\kappa_{1}(t)\). Thus, the rotation error of the gear is given by  
\[\psi(t)=\kappa_{2}(t)-\kappa_{1}(t).\frac{z_{1}}{z_{2}} \tag{34}\]  
The heterogeneity of gear transmission can be obtained through analyzing \(\psi(t)\) with its variation to time, which can be used as an evaluation index to evaluate the dynamic characteristics, transmission stability, and separation of center distance about the new tooth profile gears.
# TSKT-ORAM: A Two-Server \(k\)-ary Tree Oblivious RAM without Homomorphic Encryption +
## 7 Comparisons
### Practical Comparisons
#### 7.2.2 Computational Cost  
Because the bit-wise XOR operations on data blocks are the major contributors of computational cost for both TSKT-ORAM and CNE-ORAM, we here only compare the amount of such operations with both schemes.  
In TSKT-ORAM, the server needs to conduct \(18(\lceil\frac{\log N+1}{\log k}\rceil-1)(k-1)\) such operations. Due to \(2^{16}\leq N\leq 2^{34}\) and \(k=128\), \(3\leq\lceil\frac{\log N+1}{\log k}\rceil\leq 5\). Therefore, the total number of XOR operations ranges from 4572-9144.  
In CNE-ORAM, the XOR operations are determined by the binary tree height \(\log N\) and the node size denoted as \(\theta\). \(\theta\) is related to the security parameter. From the regression evaluation in the CNE-ORAM work, \(\theta=20(\lambda-10)\). Furthermore, the XOR operations need to be performed on half of these blocks. Hence, the total number of such operations is 10\((\lambda-10)\cdot\log N\). For fairness, we set security parameter \(\lambda\) in CNE-ORAM to 80. Then, the total number of operations ranges from 11,200-23,800.  
Therefore, we can see that TSKT-ORAM incurs a computational cost less than half of that incurred by CNE-ORAM.