esa-sceva/satcom-chunk-collection huggingface dataset:
# Optimization of Vacuum Freeze-Drying Process and Quality Evaluation of _Stropharia rugosanmulata_
## 3 Results and Discussion  
### Effects of Pre-Freezing on the Freeze-Drying Quality of Stropharia rugosaannulata  
A pre-freezing treatment can be used to induce microstructural changes in fruit and vegetable tissues, thereby improving drying efficiency and the final product's drying quality [23]. The purpose of pre-freezing is to immobilize the free water contained in _Stropharia rugosaannulata_[24]. It has two main functions: first, to maintain the quality of _Stropharia rugosaannulata_ and to prevent morphological changes such as a collapse after processing; second, to facilitate the sublimation of water during vacuum freeze-drying. The size of the ice crystals formed during pre-freezing significantly affects the rehydration capacity of the dried product. The more numerous and smaller the ice crystals formed during pre-freezing, the higher the rehydration capacity of the freeze-dried product. The formation of ice crystals is greatly influenced by the cooling rate. The pre-freezing temperature is a crucial parameter in the processing of freeze-dried _Stropharia rugosaannulata_ products as it affects the sample's freezing rate. Studies have shown that the freezing rate significantly affects the formation of ice crystals, which in turn affects the drying rate and quality of freeze-dried products [25]. In our study, we specifically investigate the effects of different pre-freezing temperatures and times on the freeze-drying process and the resulting product quality of _Stropharia rugosaannulata_. The goal is to determine the optimal pre-freezing conditions to achieve the best freeze-dried product quality. This work builds on prior research that indicates how faster cooling rates form numerous small ice crystals, minimizing cell damage, while slower rates form fewer large ice crystals, causing greater damage to cells. Our experiments aim to optimize pre-freezing parameters, including temperature and time, as these are critical factors affecting the freeze-drying process and the best quality of _Stropharia rugosaannulata_.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Code**} & \multicolumn{2}{c}{**Pre-Freezing**} & \multicolumn{2}{c}{**Pre-Freezing Time**} & \multirow{2}{*}{**Freeze-Drying Time**} \\  & **Temperature (A)/\({}^{\circ}\)C** & & **(B)/h** & **(C)/h** \\ \hline
1 & \(-20\) & \(48\) & \(60\) \\
2 & \(-40\) & \(60\) & \(72\) \\
3 & \(-80\) & \(72\) & \(84\) \\ \hline \hline \end{tabular}
\end{table}
Table 3: Orthogonal experimental design with three factors and three levels.
## 2 Sensory Evaluation: TDS and TL Methods
### Results of TDS and TL Tasks  
Figure 4 presents the TDS and TL curves for the four coffee brands. At the normalized time of 0.67 (10 s after the initiation of the task), participants were expected to have consumed the coffee. They then reported the tastes or flavors perceived in the mouth after drinking.  
\begin{table}
\begin{tabular}{c l} \hline \hline
**Attribute** & **Description** \\ \hline Astringent & Dry taste like unripe fruit. \\ Bitter & Bitter (the basic taste). \\ Caramel-like & Flavor of caramel or burnt sugar. \\ Cocoa-like & Flavor of cacao products and chocolates. \\ Nutty & Taste and flavor of dried nuts. \\ Rich & Complex, thick and harmonious flavors. \\ Roasted & Toasty, fully roasted, and not raw or green. \\ Smoky & Flavor of smoked or charcoal-grilled foods. \\ Smooth & Smooth texture, not powdery or grainy. \\ Sour & Sour (the basic taste). \\ Sweet & Sweet (the basic taste). \\ \hline \hline \end{tabular}
\end{table}
Table 1: Description of attributes presented to the panels.  
Figure 4: TDS/TL curves of four brands of coffee. (**a**) TDS curves of Kilimanjaro. (**b**) TL curve of Kilimanjaro. (**c**) TDS curves of Columbia. (**d**) TL curve of Columbia. (**e**) TDS curves of Brazil. (**f**) TL curve of Brazil. (**g**) TDS curves of Mocha. (**h**) TL curve of Mocha.  
Across all brands, a prominent sour taste was observed throughout the tasting period. Additionally, the liking curves for all brands showed a sharp increase during the initial phase (approximately 0.2), followed by fluctuations between 4 and 6 until the end of the task. The characteristic features of each brand are summarized below.  
Kilimanjaro. Sourness diminished in the final phase, with bitterness becoming the most dominant taste. The TL curve nearly peaked at the normalized time of 0.3 and remained stable until the end of the task.  
Colombia. Sourness, bitterness, and astringency alternated throughout the task. As-tringency reached its highest value during the middle phase of the tasting. The TL curve increased monotonically, nearly reaching its peak at the end of the task.  
Brazil. Sourness was the dominant taste throughout the task, except in the final phase. Smoothness and bitterness were most pronounced during the last period after drinking the coffee. The TL curve resembled that of Kilimanjaro, peaking early and remaining stable until the end.  
Mocha. Sourness was the most dominant attribute across all four brands and persisted throughout the entire task. Despite this, the TL curve for Mocha showed a similar profile to Brazil, peaking early and remaining relatively stable.  
These results highlight the distinct sensory and liking profiles of the four coffee brands, suggesting that cross-brand prediction among these brands poses a significant challenge.
# Evaluation of the Machinability of Ti-6 Al-4V Titanium Alloy by AWJM Using a Multipass Strategy
## 3 Results and Discussion
### The Effect of the Multipass Method on the Top Width of the Slots  
In all five experimental cases, one can see that the output values varied in different ranges. The most significant parameter influencing the top kerf width was the stand-off distance [7], which in this case was constant; however, other parameters such as the traverse feed rate caused some variations between slots. In most tests, increasing the number of passes led to an increase in the kerf width, at least for the average value. In Figure 5, there is a visible trend in some cases, in which after the third pass, the results approached a  
Figure 4: Ratio of depth obtained with 2, 3, or 4 passes, with respect to the depth of the first pass under various experimental conditions.  
relatively high level. This might have been due to the curvature of the stream during each pass and the influence of the other machining parameters to varying degrees during the different passes. On the other hand, the results from different input parameters did not differ significantly, something that can be attributed on the fact that the traverse feed rate and especially the jet pressure were less significant in regulating the kerf width than the stand-off distance. Based on the presented graph, it can be concluded that, although in most cases a greater number of passes widened the top kerf, direct control of the width of the grooves using the tested parameters was not possible.  
Figure 6 shows the ratio of widths, which was created by dividing the value of the top kerf width after four passes by the value obtained after one pass. This operation was repeated for each case. This ratio informs us about how often the slot would be wider after four passes, as compared to with one pass. In this case, the results show that the ratio value oscillated around 1.1-1.2, which means that the multipass strategy did not have a significant influence on the top kerf width of the slots, as was also observed in another study of multipass AWJM [10]. On the other hand, in every case, the ratio value exceeded one, therefore increasing the number of passes four times tended to generate wider slots.  
It can be concluded that in the case of the top kerf width, a direct trend between the top kerf width and number of passes could not be established in every case. In some cases, the widening of the kerf occurred after two passes and remained practically constant after the third pass, whereas in some cases, such as 1 and 2, a considerable increase of the kerf width occurred only after the third pass. Finally, after four passes, the increase of top kerf width, with respect to its value after the first pass, was clear. Thus, the only clear trend that could be established was that after four passes, the top kerf width increased independently from the other conditions.  
Figure 5: Variation of the top kerf width with an increasing number of passes and different process conditions.
## 2 Novel Technologies of 6G for Smart Grid Applications
### Device-to-Device (D2D) Communication  
D2D communication defines a communication architecture that facilitates direct communication among adjacent devices, except in traditional BSs or infrastructure intermediaries. In D2D communication, devices, such as smartphones, tablets, or IoT devices, can communicate directly with each other, forming ad hoc networks or forming a direct link when they are in close proximity.  
D2D communication reduces the gap between the sender and receiver. Moreover, it can enhance the battery life of the device as well [1]. The spectral efficiency can be improved by introducing mMIMO for D2D communication. Moreover, D2D also provides low-latency communication by maintaining machine-to-machine communication [101].
## 1 Introduction
Inspired by the recent paper [19], where the initial multi-layered composite plate in FEM simulations was replaced with a single anisotropic layer and advancing the results from papers [34; 35], the current work aims at the further investigation of the applicability of equivalent single layer models for the EGW phenomena simulation related to NDT/SHM applications. For this purpose, a typical problem for ultrasonic-based NDT/SHM is considered, namely in-plane EGW excitation and sensing with surface-mounted piezoelectric wafer transducers (PWT) as well as their scattering by a T-shaped stringer in symmetric cross-ply laminates with different lamination schemes, which are examined by employing the recently developed semi-analytical hybrid approach (SAHA) [36; 37; 38]. To simulate the waveguide structure, along with the wave dynamics of a complete multi-layered structure, two homogenized models are considered. While the first one relies on a well-developed static long-wave homogenization approach [31], for the latter, dynamic homogenization is adopted based on the concept proposed in Ref. [33], which serves as a starting point. The obtained results illustrate that while homogenized models rather adequately follow the dispersion properties of the considered multi-layered structures, the output voltage of a sensing PWT either in the presence of the T-shaped stringer or in its absence could be only qualitatively represented.
## 5 Application Instances of Proposed SDP  
In this section, we provide two instances to illustrate how to apply the proposed SDP baseline estimation model to existing latent factor-based recommendation algorithms that use classical baseline estimation. The main method adds factor \(\left(\frac{\sigma_{u}}{\sigma}\right)\) to \(b_{i}\) and makes some improvement during model learning. We selected two famous and efficient existing latent factor-based CF recommendations for improved instances. The first instance improves SVD++ [5] by SDP, named SDPSVD++; the second improves TrustSVD [11; 12] by SDP, named SDPTrustSVD.
## 2 Current CORNERSTONE Platforms
### Carrier Based Modulators
A bespoke TDFA was also used to boost the optical power at the input. Figure 6: Measured DC performance of a 1.8 mm long Si depletion modulator. (**a**) Phase shift and (**b**) modulator efficiency. Figure 7: Measured 40 Gb/s optical eye-diagram of a Si photonic carrier depletion modulator. The modulation efficiency at a reverse bias of 4 V was measured to be 2.89 V-cm at \(\lambda\) = 1950 nm. Under a DC bias of \(-\)4.5 V, with a peak-to-peak alternating current (AC) amplitude of 2 V applied to each arm (operating in push-pull configuration) the device modulates at 10 Gbit/s with an extinction ratio of 12.7 dB, as in Figure 8a. At 20 Gbit/s the extinction ratio is 10.3 dB, as in Figure 8b, and at 25 Gbit/s the extinction ratio is 6.25 dB, as in Figure 8c. The insertion loss of the Mach-Zehnder modulator (MZM) with a 2 mm phase shifter is 4.96 dB, and a similar MZI without doping and metal is also tested to have an insertion loss of 1.25 dB. Due to the bandwidth limit of the detector we were unable to obtain an eye diagram for data rates greater than 25 Gbit/s at 2 \(\upmu\)m wavelength.
# Chemical Substance Exposure of Some Cleaning Workers in Korea: Focusing on Inhalation Exposure
## 3 Results
### Analysis of 5-Year Work Environment Measurement Data for Korean Cleaning Workers (2016-2020)
#### 3.1.2 Restaurant Industry  
The analysis of the measurement data for harmful agents in the restaurant industry is summarized in Table 3. Two organic compounds were measured (i.e., 2-butoxyethanol and isopropyl alcohol), both of which were undetectable. The measured concentration of sodium hydroxide was 0.045 \(\pm\) 0.049 mg/m\({}^{3}\), that of potassium hydroxide was 0.008 \(\pm\) 0.010 mg/m\({}^{3}\), that of hydrogen peroxide was 0.001 \(\pm\) 0.002 ppm, and that of hydrochloric acid was 0.012 \(\pm\) 0.020 ppm. Phosphoric acid was not detected.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \multirow{2}{*}{**Classification**} & \multirow{2}{*}{**Substance**} & \multirow{2}{*}{**No. of**} & \multirow{2}{*}{**Unit**} & \multirow{2}{*}{**\(\mathbf{\ast}\)OEL**} & \multicolumn{4}{c}{**Representative Value**} \\ \cline{6-9}  & & & & & * **AM** & & **\(\mathbf{\dagger}\)SD** & \(\mathbf{\ddagger}\)**GM** & \(\mathbf{\lx@sectionsign}\)**GSD** \\ \hline \multirow{4}{*}{Organic Compound} & 2-Butoxyethanol & 46 & ppm & 20 & 0.042 & 0.083 & 0.112 & 3.565 \\  & Isopropyl alcohol & 35 & ppm & 200 & 8.405 & 16.79 & 1.128 & 3.553 \\  & Ethanolamine & 45 & ppm & 3 & 0.001 & 0.003 & 0.010 & 5.318 \\  & Mixed organic chemicals & 50 & - & 1 & 0.002 & 0.004 & 0.031 & 3.511 \\ \hline \multirow{3}{*}{Metal} & Zinc oxide & 20 & mg/m\({}^{3}\) & 0.05 & 0.001 & 0.001 & 0.031 & 2.126 \\  & Iron oxide & 2 & mg/m\({}^{3}\) & 5 & 0.003 & 0.003 & 0.057 & 2.390 \\ \hline \multirow{4}{*}{Acid and Alkali} & Sodium hydroxide & 52 & mg/m\({}^{3}\) & C2 & 0.045 & 0.049 & 0.176 & 2.426 \\  & Potassium hydroxide & 18 & mg/m\({}^{3}\) & C2 & 0.008 & 0.010 & 0.081 & 2.524 \\  & Hydrogen peroxide & 9 & ppm & 1 & 0.001 & 0.002 & 0.034 & 2.728 \\  & Hydrochloric acid & 24 & ppm & 1 & 0.012 & 0.020 & 0.076 & 3.160 \\  & Nitric acid & 17 & ppm & 2 & 0.003 & 0.007 & 0.029 & 4.054 \\  & Sulfuric acid & 9 & ppm & 0.2 & 0.017 & 0.029 & 0.088 & 3.176 \\ \hline \multirow{4}{*}{Dust} & Other mineral dust & 37 & mg/m\({}^{3}\) & 10 & 1.376 & 1.706 & 0.721 & 2.624 \\  & Other dust & 9 & mg/m\({}^{3}\) & 10 & 0.168 & 0.014 & 0.459 & 1.088 \\ \cline{1-1}  & Welding fume & 2 & mg/m\({}^{3}\) & 5 & 0.239 & 0.012 & 0.537 & 1.052 \\ \cline{1-1}  & Metal working fluids & 6 & mg/m\({}^{3}\) & 2 & 0.098 & 0.034 & 0.344 & 1.404 \\ \hline \end{tabular}  
* AM: Arithmetic mean. ** OEL: Occupational exposure limit. \(\mathbf{\ddagger}\) SD: Standard deviation. \(\mathbf{\ddagger}\) GM: Geometric mean. \(\mathbf{\lx@sectionsign}\) GSD: Geometric standard deviation.  
\end{table}
Table 2: Number of measurements and measurement values for each harmful factor to be measured in the building cleaning business.
## 3 Data, Methods and Results
### SAR Data Processing
The mean velocity of the Agia Eleoussa landslide was found to be 1.8 mm/yr (\(\sim\)0.2 cm/year) downward and 7.7 mm/yr (\(\sim\)0.8 cm/year) eastward. We also computed the histograms of the velocities from both ascending and descending tracks and the Up and E-W components of the movement for Krini and Agia Eleoussa, respectively (Table 1, Figures 7 and 8). The area affected by the Krini landslide is 4,080,000 square meters (m\({}^{2}\)). The area of the active landslide around the village of Pittisa is 800,000 square meters (m\({}^{2}\)), and the area of the landslide near the monastery of Agia Eleoussa is 1,600,000 square m\({}^{2}\). It is probable that the two landslides are in fact part of one feature (mass movement). However, the uncertainty in our InSAR motion rates (\(\sim\)3 mm/yr LOS, see Figure 5c,d) is within the values we mapped in the area between the two landslides. \begin{table}
\begin{tabular}{c c c} \hline \hline  & **Mean Velocity (mm/yr)** & **Median Velocity (mm/yr)** \\ \hline Krini Up Component & \(-\)6.0 & \(-\)4.6 \\ \hline Krini E-W Component & 28.7 & 24.5 \\ \hline Krini LOS (ascending) & \(-\)22.0 & \(-\)18.7 \\ \hline Krini LOS (descending) & 12.5 & 11.0 \\ \hline Agia Eleoussa Up Component & \(-\)1.8 & \(-\)1.2 \\ \hline Agia Eleoussa E-W Component & 7.7 & 7.0 \\ \hline Agia Eleoussa LOS (ascending) & \(-\)7.1 & \(-\)6.3 \\ \hline Agia Eleoussa LOS (descending) & 5.5 & 5.2 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Table of mean and median velocities of active landslides in the village of Krini and at the monastery of Agia Eleoussa. The landslide outlines are shown in Figure 6e,f. The period of observation was 2016–2020. Figure 7: Histograms of LOS/E-W/U-D velocities of active landslides in the village of Krini (Affected area: 4,080,000 m\({}^{2}\)).
# Voice Maps as a Tool for Understanding and Dealing with Variability in the Voice
## 3 Voice Maps in Practice
### Mapping of Other Statistics  
So far we have considered mostly the _mean_ of a metric, per voice map cell. However, any other per-cell statistic, such as standard deviations, metric gradients, or inter-metric correlations can in themselves be taken as scalar fields that can also be represented on maps. For instance, the standard deviation of the EGG contact quotient often has a local maximum in the transition region, where VF contacting sets in, due both to oscillatory instability and to hysteresis. Maps can be made also of the _correlation_ between metrics of phonation and other physiological signals acquired in parallel, such as vertical larynx height, lung volume, subglottal pressure, etc. Examples can be found in [19].
## 4 Application
### Pumping Test Results And Analyses
#### 4.3.2 Pumping Test Results and Analyses  
(1) Groundwater drawdown  
Figure 11a,b display the variation of groundwater drawdown in observation wells that were installed inside and outside the excavation during pumping test. As can be seen from Figure 11a, the stabilized drawdown of well W9 inside the West zone was about 8.4 m after the 24 h pumping test. The maximum drawdown of observation wells installed inside the Central zone is up to 14.9 m, being located at well W15 after the 48 h pumping test. The stabilized drawdown of well W23 inside the East zone was about 6.8 m after he 80 h pumping test. Due to the lower water level at both the West and East zone from the results of the initial observation, the water table inside the excavation could be lowered to the excavation bottom. As shown in Figure 11b, the maximum groundwater drawdown outside the West zone, Central zone, and East zone was 0.16 m, 0.18 m, and 0.1 m when the water level inside stabilized.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Test**} & \multirow{2}{*}{**Subsection**} & \multirow{2}{*}{**Pumping Wells**} & \multicolumn{2}{c}{**Observation Wells**} & \multirow{2}{*}{**Pumping Time**} \\ \cline{3-3} \cline{5-5}  & & & **Inside** & **Outside** & \\ \hline \multirow{2}{*}{1} & \multirow{2}{*}{West Zone} & W1, W3, W4, W5, W6, & \multirow{2}{*}{W9} & Q2, Q4, Q6, & \multirow{2}{*}{5} \\  & & \(W7\), W8 & & P2, P4 & \\ \hline \multirow{2}{*}{2} & Central & W10, W12, W13, W14, & \multirow{2}{*}{W15} & Q6, Q8, Q10, & \multirow{2}{*}{4.5} \\  & Zone & W16, W17 & & Q12, P4, P5, P6 & \\ \hline \multirow{2}{*}{3} & \multirow{2}{*}{East Zone} & W18, W19, W20, W21, & \multirow{2}{*}{W23} & Q12, Q14, & \multirow{2}{*}{4} \\  & & W22 & & P6, P7 & \\ \hline \hline \end{tabular}
\end{table}
Table 4: Procedure of pumping tests.  
Figure 10: The location of the pumping and observation wells.  
(2) Pumping rate of wells  
Figure 12 displays the evolution of the pumping rate of operative wells installed inside the excavation during the pumping test. It can be seen that the total pumping rate of operative wells gradually decreased as the pumping test went. After the stabilization of water level, the total pumping rate of all operative wells in the West zone, Central zone, and East zone was 270.24, 169.92, and 109.68 m\({}^{3}\)/d, respectively. When compared with the data measured at the initial period of pumping test, the total pumping rate of wells obviously decreased, especially the total pumping rate of wells in the central zone declined by more than 75%.
# Seismic Multi-Parameter Full-Waveform Inversion Based on Rock Physical Constraints
###### Abstract  
Seismic multi-parameter full-waveform inversion (FWI) integrating velocity and density parameters can fully use the kinematic and dynamic information of observed data to reconstruct underground models. However, seismic multi-parameter FWI is a highly ill-posed problem due to the strong dependence on the initial model. An inaccurate initial model often leads to cycle skipping and convergence to local minima, resulting in poor inversion results. The introduction of prior information can regularize the inversion problem, not only improving the crosstalk phenomenon between parameters, but also effectively constraining the inversion parameters, enhancing the inversion efficiency. Multi-parameter FWI based on rock physical constraints can introduce prior information of underground media into the objective function of FWI. Taking a simple layered model as an example, the results show that the inversion strategy based on rock physical constraints can enhance the stability of inversion and obtain high-precision inversion results. Application to the international standard 1994 BP model further confirms that the proposed inversion strategy has good applicability to complex geological models.  
full-waveform inversion; multi-parameter inversion; rock physical constraints Article