esa-sceva/satcom-chunk-collection huggingface dataset:
# Enhancing Channelized Feature Interpretability Using Deep Learning Predictive Modeling
## 1 Introduction
### SEG Advanced Modeling (SEAM) Dataset  
To ensure the algorithms are robust and effective, we use the Society of Exploration Geophysicists (SEG) Advanced Modeling (SEAM) Phase 1 dataset [8] as the training data.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Category** & **Class** & **Type** & \\ \hline Instantaneous & I & Reflection Strength, Instantaneous Phase, Instantaneous & Lithology Contrasts, Bedding \\ Attributes & I & Frequency, Quadrature, Instantaneous Q & Continuity, Porosity, DHIs, \\  & & & Strattigraphy, Thickness \\ \hline Geometric & II & \begin{tabular}{c} Semblance and Eigen-Based Coherency/Similarity, \\ Curvature (Maximum, Minimum, Most Positive, Most \\ Negative, Strike, Dip) \\ \end{tabular} & \begin{tabular}{c} Faults, Fractures, Folds \\ Anisotropy, Regional Stress Fields \\ \end{tabular} \\ \hline \begin{tabular}{c} Amplitude- \\ Acetuating \\ Attributes \\ \end{tabular} & III & RMS Amplitude, Relative Acoustic Impedance, Sweetness, & Porosity, Stratigraphic \\  & & Average Energy & and Lithologic \\  & & Variations, DHIs \\ \hline AVO Attributes & IV & \begin{tabular}{c} Intercept, Gradient, Intercept/Gradient Derivatives \\ Fluid Factor, Lambda–Mu-Rho, Far–Near, (Far–Near) Far \\ \end{tabular} & Pore Fluid, Lithology, DHIs \\ \hline Seismic Inversion & V & \begin{tabular}{c} Colored Inversion, Sparse Spike, Elastic Impedance \\ Extended Elastic Impedance, Prestack Simultaneous \\ Inversion, Stochastic Inversion \\ \end{tabular} & Lithology, Porosity, Fluid \\ \hline Spectral & VI & \
\begin{tabular}{c} Continuous Wavelet Transform, Matching Pursuit \\ Exponential Pursuit \\ \end{tabular} &
\begin{tabular}{c} Layer Thicknesses, \\ Stratigraphic Variations \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table}
Table 1: Seismic attribute classification used as guided by [7].  
Figure 1a shows a general overview of geological structures in the SEAM Reservoir Model, which consists of highly channelized complexes, sheet turbidites, and localized turbidite fans, with the red region marked as the training dataset. Three reservoir types representing local turbidite fans, widespread and superposed turbidite sheets with highly channelized complexes were developed, consist of various types of fluids (oil, gas, and brine). Seven localized turbidites were present in Pleistocene formation, while extensive sheet turbidites covered several stratigraphic horizons of Middle and Lower Miocene macro-layers. Full turbidite complexes with a pair of estimated 80 m-thick sub-sheets were parted by shale background layers with estimated channel width of 2 km in the same interval, with clear indication of en echelon structures, as depicted in Figure 1b. A section of volume of shale illustrates stratigraphic features from the Pleistocene to Cretaceous, highlighting the stacked channels in Upper Miocene. Superposed sixteen pairs of stacked channels with horizontal distance of 8 km are depicted in Figure 1c.
###### Abstract  
This paper proposes a new optical design that will cooperate with 3D image technology, infrared spectrum technology, future medical diagnostics, the cloud, and big data analysis. We first conducted image recognition experiments to compare the pros and cons of 2D and 3D frameworks in order to make sure that the optical and mechanical framework of a glasses-type 3D ophthalmoscope would be a better choice. The experimental results showed that a 3D image recognition rate (90%) was higher than a 2D image recognition rate (84%), and hence the 3D mechanism design was selected. The glasses-type 3D ophthalmoscope design is primarily based on the specification of indirect ophthalmoscope requirements and two working spectrums: a near infrared and a visible spectrum. The design is a 2.5x magnification fixed focal telecentric relay system with a right-angle prism, which uses a large aperture to increase the amount of incident light (F/# = 2.0). As the infrared spectrums that have better transmittance towards human eye tissue are 965 nm and 985 nm, so that we took account of the visible spectrum and the near-infrared spectrum simultaneously to increase the basis of the physician's diagnosis. In this research, we conclude that a wearable ophthalmoscope can be designed optically and mechanically with 3D technology, an infrared and a visible working spectrum and further, possibly in cooperation with the cloud and big data analysis.  
Keywords: ophthalmoscope; lens design; medical optics and biotechnology +
Footnote †: journal: Applied Soft 2019, 9, 717; doi:10.3390/app9040717
# Exploring Metalloprotease from _Dunaliella_ sp.: Production, Regulation, and Structural Insight
## 3 Results and Discussion
### Molecular Investigation
#### 3.5.3.  
Analyzation of the Cis-Acting Element of the _DsFtsH2_ Gene  
For a deep investigation of the cis-elements of the _DsFtsH2_ gene, the 2000 bp 5\({}^{\prime}\) upstream region was studied using the PlantCARE database. The different cis-acting elements could be categorized into three groups: (i) environmental stress-related elements (i.e., drought inducibility: DI, light-responsive: LRE, and defense and stress responsiveness: DRE/SRE), (ii) hormone-responsive elements (e.g., Gibberellin (GRE), Me-Jasmonic acid MeJARE, auxin (AUXRE), and abscisic acid-responsive (ABARE)), and (iii) development-related elements (i.e., meristem expression: ME). It is noteworthy that the major cis-acting elements of the _DsFtsH2_ gene are light, Me-Jasmonic acid, and auxin responses (Figure 4c). These findings indicate that this gene may be involved in development processes as well as abiotic and biotic stress responses.  
Figure 4: (**a**) Phylogenetic tree (a1), protein conserved motifs (a2), protein conserved domains (a3), and gene structure (a4) analysis of _DsFtsH_ gene family. (**b**) Phylogenetic analysis of FtsH proteins identified in different species: _Dunaliella salina_ ([PERSON]), _Arabidopsis thaliana_ (At), _Glycine max_ (Gm), _Oryza sativa_ (Os), and _Chlamydomonas reinhardtii_ (Cre). (**c**) Representation of the cis-elements in the promoter of _FtsH2_ using TBtools software. Each cis-element is identified by a unique color. GRE: gibberellin-responsive element, ME: meristem expression, LRE: light-responsive element, ABARE: abscisic acid-responsive element, DRE/SRE: defense and stress responsiveness, AUXRE: auxin-responsive element, MeJARE: Methyl Jasmonic Acid responsive element. (**d**) Relative expression levels of the _FtsH2_ gene in _Dunaliella_ sp. under various induced stress conditions.
## 4 Results
### Scenario 1
#### 4.1.2 Second Example Test  
The results of a different test from Scenario 1 (with parameters \(K=9\), \(N=4\), \(L=4\), \(QBER=7\)) are presented in Table 2 and Figure 3. In the case of this test, compared to the previous one, the number of updates between victims-presented in the second column of Table 2 and in Figure 3a-is comparable across all combinations of update rules (\(\approx\)111 on average). However, many of the previously described observations related to the synchronization percentage remain valid. Based on the data presented in the third column of Table 2 and in Figure 3b, we can conclude several statements.  
* In hebbian-oriented tests, the attacker was able to obtain less information when the victims were using dynamic_rows or dynamic_matrix (\(\approx\)59% in both cases), compared to the scenario in which all parties used the hebbian algorithm.
* The attacker's synchronization percentage is lower when they choose the update rule randomly, while the victims choose dynamic_rows or dynamic_matrix (\(\approx\)63.5% in both cases), compared to any combination in which the attacker uses the random walk algorithm (\(\approx\)69% on average). The values are also comparable with the attacker's synchronization when all parties use the hebbian algorithm (\(\approx\)63.5%), although the confidence intervals are not narrow enough to definitely conclude which of these combinations is more beneficial for the victims.
* Additionally, compared to previously presented tests, in this case, the mean value of the attacker's synchronization was lower when the attacker used the random walk rule, and the victims used either dynamic_rows or dynamic_matrix (\(\approx\)68% and \(\approx\)69%, respectively), compared to all parties using random walk (\(\approx\)69%). However, in the case of dynamic_matrix, this observation is not conclusive, due to the width of the confidence intervals.  
Figure 3: Scenario 1–\(K=9,N=4,L=4,QBER=7\).  
\begin{tabular}{c c c} \hline \hline
**Update Rules** & **Victims’ Updates** & **Attacker’s Synchronization** \\ \hline all parties: hebbian & 115.62 \(\pm\) 5.27 & 63.62 \(\pm\) 0.1 \\ \hline victims: dynamic_rows, attacker: hebbian & 110.32 \(\pm\) 2.56 & 59.13 \(\pm\) 0.25 \\ \hline victims: dynamic_matrix, attacker: hebbian & 110.78 \(\pm\) 2.60 & 58.97 \(\pm\) 0.24 \\ \hline all parties: random walk & 112.5 \(\pm\) 2.56 & 69.31 \(\pm\) 0.29 \\ \hline victims: dynamic_rows, attacker: random walk & 108.8 \(\pm\) 2.52 & 68.35 \(\pm\) 0.29 \\ \hline victims: dynamic_matrix, attacker: random walk & 113.28 \(\pm\) 2.76 & 68.92 \(\pm\) 0.27 \\ \hline victims: dynamic_rows, attacker: random rule & 107.93 \(\pm\) 2.6 & 63.55 \(\pm\) 0.29 \\ \hline victims: dynamic_matrix, attacker: random rule & 110.35 \(\pm\) 2.56 & 63.48 \(\pm\) 0.31 \\ \hline \hline \end{tabular}
## 2 Experimental Setup
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Additives**} & **Chemical** & **Molecular** & **Density** & **Heat of** \\  & **Formula** & **Weight (g/mol)** & **(kg/m\({}^{3}\))** & **Combustion (kJ/g)** \\ \hline \multirow{2}{*}{Humectant} & Isopropanol & C\({}_{3}\)H\({}_{8}\)O & 60.06 & 786 & 33.08 \\  & Ethanol & C\({}_{2}\)H\({}_{6}\)O & 46.07 & 789 & 29.68 \\ \hline \multirow{2}{*}{Plasticizer} & Dibutyl phthalate & C\({}_{16}\)H\({}_{22}\)O & 278.34 & 1047 & 30.99 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Physical parameters of the additives [30]. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Samples**} & \multirow{2}{*}{\(L\) **(cm)**} & **Bulk Density** & **Atmospheric** & **Ambient** & **Relative** \\  & & **(kg/m\({}^{3}\))** & **Pressure (kPa)** & **Temperature (\({}^{5}\)C)** & **Humidity (\%)** & **Measurements** \\ \hline NC-I & \(8,10\) & 156.3 & & & & \(\bullet\) Mass loss \\ NC-E & \(8,10\) & 156.3 & \(100.3\pm 0.3\) & \(28\pm 2\) & \(40\pm 3\) & \(\bullet\) Video \\ NC-D & \(8,10\) & — & & & \(\bullet\) HRR \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Detailed information of experimental configurations. Figure 2: Photos of arrangements of the three samples for the burner dimension with \(L\) = 8 cm. In order to achieve the research goal, the experiments in Table 2 are firstly performed in an open space. An electronic scale (Mettler Toledo XP10002S, Mettler-Toledo, Zurich, Switzerland) with a readability of 0.01 g is used to measure the history of mass loss, which will be further processed to give the MLR. A square insulation board with 20 cm side is placed beneath the burner to shield the electronic scale from elevated temperature. A 25-fps high-resolution camera (Sony, HDR-XR160E) is employed to record the whole burning process for acquiring the flame height data. Then, the experiments above will be retested by means of the ISO 5660 to acquire the HRR data with the absence of incident radiation, as illustrated in Figure 3. The ventilation conditions are determined by the airflow speed of the pump. A volumetric flow rate of 0.035 m\({}^{3}\)/s is set to remove gases by the pump which meets the ventilation efficiency stipulated in ISO 5660 standard [31; 32]. The gases are continuously sampled via a Servomex 4100 gas analyzer (Servomex Group Limited, Surrey, UK) to monitor the concentrations of O\({}_{2}\), CO\({}_{2}\), and CO, which will be transferred to the PC to calculate the HRR based on the oxygen consumption principle. For all the tests, the samples are ignited in the middle of the burner with a butane lighter.
# FTIR Characterization of Asphalt SARA Fractions in Response to Rubber Modification
## 2 Materials and Methods
### Methods  
The experimental program consisted of four stages, as illustrated in Figure 1. The first stage involved asphalt-rubber interactions. After this stage, the A-RBs were obtained at various interaction conditions. The A-RB matrix consisted of undissolved rubber and the liquid phase of asphalt (Figure 2). Partial dissolution of the rubber occurred during the interaction, and the remaining particles were still present as undissolved particles. The second stage was to extract the liquid phases, asphalt without undissolved rubber particles, from the A-RBs. Following that, the neat binder and the A-RBs were fractionated into asphalt SARA fractions. The neat binder and A-RB SARA fractions were evaluated chemically, and their FTIR spectra were compared. The third stage aimed to confirm the FTIR spectra comparison using a thermogravimetric analyzer (TGA). Undissolved rubber particles were extracted from the A-RBs and evaluated thermally using a TGA to understand the dissolved rubber percentage and its components released in the binder. Finally, the FTIR and TGA analyses will be aligned with the rheological analysis of the neat binder and A-RBs, revealing the effects of the interaction between rubber and asphalt on altering the performance of the overall modified binder. The following subsections elucidate the experimental program's stages.
# Thermal Performance of Cryogenic Micro-Pin Fin Coolers with Two-Phase Liquid Nitrogen Flows
###### Abstract  
This study experimentally explores the thermofluidic performance of a cryogenic micro-pin fin cooler with two-phase liquid nitrogen flows. The liquid nitrogen cooling system is introduced to investigate the performance of the micro-pin cooler in a cryogenic condition. The result reveals that the nominal value of the base heat transfer coefficients of the micro-pin fin cooler with liquid nitrogen flows, 240 kW/m\({}^{2}\)-K at a mass flow rate of 2.23 g/s, is an order of magnitude greater than that with FC-72 flows. The result also demonstrates that the base heat transfer coefficient of the micro-pin fin cooler is nearly three times greater than that of the micro-gap cooler, not containing any fins. This study shows the feasibility of the cryogenic micro-pin fin cooler for thermally controlling very high heat density devices such as high-power laser diode bars, of which the heat density can reach 2000 kW/m\({}^{2}\).  
cryogenic; micro-pin fin; two-phase; liquid nitrogen; heat transfer +
Footnote †: journal: Applied Sciences
## 4 Discussion
By contrast, the small cross-sectional area contributed to the lower UTS of 2 Shape. Hence, it is recommended to use 2 Shape in straight or slightly curved root canals. The mechanical tests in this study were conducted at 22 \({}^{\circ}\)C. In the heating curves of the DSC profiles, the peak temperatures attributed to the austenitic transformations of ProTaper Gold, ProfaTaper Gold, HyFlex CM, and V Taper 2H were 40.89, 43.27, 36.29, and 28.74 \({}^{\circ}\)C, respectively (Figure 6B,C,D,E, respectively). Evidently, the phase composition of these NiTi files varies with increasing environmental temperature from 22 to 37 \({}^{\circ}\)C. Previous studies have reported that cyclic fatigue resistance decreases at elevated testing temperatures [12; 31; 42]. Therefore, further studies on the bending, buckling, cyclic fatigue, and torsional resistances of NiTi files at body temperature are needed. One of the limitations of our study is that the phase transitions of NiTi files were not studied in real time through in situ crystallography based on X-ray diffraction. Instead, we performed DSC, which provides limited information, to elucidate the possible metallurgical features of the samples. The DSC results combined with the data from the literature were sufficient to verify our main findings and hypotheses. Another drawback is that this study establishes weak correlations between the tested mechanical properties, which makes it difficult to draw decisive conclusions about possible clinical implications. 2 Shape was operated utilizing two file systems: TS1 (#25/04) followed by TS2 (#25/06), up to the working length. ProFile, HyFlex CM, and K3 XF were intended for use with a crown-down technique. ProTaper Gold and ProfaTaper Gold instructions mandated the sequential use of four to five files along the working length. V Taper 2H instructions stated that it should be used in conjunction with a glide path-preparing file, followed by #20/04 and #25/06 for the working length. The amount of dentin removed during canal shaping varies depending on the NiTi file brand, as does the amount of stress generated by the NiTi files. The cutting, centering, and debris removal efficiencies of each file during canal shaping should be investigated further. Interaction between a titanium implant and metal prosthesis may induce galvanic corrosion, ion release, and peri-implantitis [48]. Nickel release from orthodontic brackets has been widely reported, which is an issue that requires attention due to the possibility of allergic reactions in patients [49]. Therefore, the mechanisms underlying ion release from NiTi files manufactured through different heat treatments must be investigated. This study revealed that CM-wire NiTi files have superior flexibility and exhibit high cyclic fatigue resistance. Although the cross-sectional shapes of all tested files are triangular or the files have modified triangular cross-sections, their mechanical properties vary depending on the heat treatment type. More research, however, is required to further our understanding of the differences in the characteristics of CM-wire, gold-wire, T-wire, and R-phase wire.
Sensors_**2014**, _14_, 23650-23672; doi:10.3390/s141223650  
_Sensors_  
ISSN **1424-8220**  
www.mdpi.com/journal/sensors  
_Article_  
**Analysis of Radio Wave Propagation for ISM 2.4 GHz Wireless Sensor Networks in Inhomogeneous Vegetation Environments**  
**[PERSON] 1,*, [PERSON] 1, [PERSON] 1, [PERSON] 1, [PERSON] 2, [PERSON] 2 and [PERSON] 1**  
1 Electrical and Electronic Engineering Department, Universidad Publica de Navarra, Pamplona 31006, Spain; E-Mails: [EMAIL_ADDRESS] (P.L.-I.); [EMAIL_ADDRESS] (E.A.); [EMAIL_ADDRESS] (I.M.); [EMAIL_ADDRESS] (F.F.)  
2 Mathematics and Computer Engineering Department, Universidad Publica de Navarra, Pamplona 31006, Spain; E-Mails: [EMAIL_ADDRESS] (J.J.A.);[EMAIL_ADDRESS] (J.V.)  
* Author to whom correspondence should be addressed; E-Mail: [EMAIL_ADDRESS]; Tel.: +34-948-169-095; Fax: +34-948-169-720.  
External Editor: [PERSON]  
_Received: 15 October 2014; in revised form: 14 November 2014 / Accepted: 25 November 2014 / Published: 10 December 2014_  
**Abstract:** The use of wireless networks has experienced exponential growth due to the improvements in terms of battery life and low consumption of the devices. However, it is compulsory to conduct previous radio propagation analysis when deploying a wireless sensor network. These studies are necessary to perform an estimation of the range coverage, in order to optimize the distance between devices in an actual network deployment. In this work, the radio channel characterization for ISM 2.4 GHz Wireless Sensor Networks (WSNs) in an inhomogeneous vegetation environment has been analyzed. This analysis allows designing environment monitoring tools based on ZigBee and WiFi where WSN and smartphones cooperate, providing rich and customized monitoring information to users in a friendly manner. The impact of topology as well as morphology of the environment is assessed by means of an in-house developed 3D Ray Launching code, to emulate the realistic operation in the framework of the scenario. Experimental results gathered from a measurement campaign conducted by deploying a ZigBee Wireless Sensor Network, are analyzed and compared with simulations in this paper. The scenario where this network is intended to operate is a combination of buildings and diverse vegetation species. To gain insight in the effects of radio propagation, a simplified vegetation model has been developed, considering the material parameters and simplified geometry embedded in the simulation scenario. An initial location-based application has been implemented in a real scenario, to test the functionality within a context aware scenario. The use of deterministic tools can aid to know the impact of the topological influence in the deployment of the optimal Wireless Sensor Network in terms of capacity, coverage and energy consumption, making the use of these systems attractive for multiple applications in inhomogeneous vegetation environments.  
**Keywords:** Wireless Sensor Network; vegetation environment; 3D Ray Launching
# Response of Global Terrestrial Carbon Fluxes to Drought from 1981 to 2016
## 3 Results
### Spatial Patterns of Sensitivity of the Terrestrial Carbon Fluxes to Drought  
Based on the identified lagged time scales of SPEI, the sensitivity of carbon fluxes to drought was calculated for each grid cell for the month in which the carbon fluxes and the SPEI were found to have the highest correlation coefficients (Figure 5). The sensitivity of terrestrial carbon fluxes to drought was high in the eastern United States, most of Europe, East Asia, and eastern South America, and was low in the high latitudes of the Northern Hemisphere, the western United States, northern and southern Africa, Central Asia, and western Australia. This could be attributed to differences in the size of terrestrial carbon fluxes themselves and differences in the responses of carbon fluxes to drought in different regions.  
In order to remove the influence of the state of terrestrial carbon fluxes in different regions, the sensitivity was further calculated based on the detrended and normalized terrestrial carbon fluxes (\(\mathrm{F_{normalized}=(F-F_{mean})/F_{std}}\); \(\mathrm{F_{normalized}}\) and F are the normalized and detrended monthly carbon fluxes; \(\mathrm{F_{mean}}\) and \(\mathrm{F_{std}}\) are the mean and standard deviation of F over the study period) (Figure 6). As a result, the sensitivity of terrestrial carbon fluxes to drought showed an alternative spatial pattern. In general, the sensitivity was higher at low and middle latitudes in the Northern Hemisphere and in the Southern Hemisphere, while the sensitivity values were relatively lower at high latitudes in the Northern Hemisphere.  
Figure 4: Changes of lagged time (month) for response of terrestrial GPP (**a**), NPP (**b**), ER (**c**), and NEP (**d**) to drought with annual water balance averaged over the period from 1981 to 2016.