esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Synchronous Measurement Structure of Crankshaft Journal  
### Probe Arrangement  
The synchronous measurement scheme for the crankshaft journal is to measure the spindle journal and connecting rod journal synchronously under one-time clamping. Multiple probes are arranged in both axial and radial directions of the journal to shorten the measurement time and improve the measurement accuracy. When the probe is in contact with the circumferential surface of the main journal and the connecting rod journal, one revolution of the crankshaft can not only measure the surface profile data of the main journal but also collect the whole surface profile data of the connecting rod journal. The mechanical structure of multi-probe is relatively simple, the adaptability to the environment is high, and the anti-interference ability is strong. It can eliminate machining errors, as well as installation and clamping errors, and can be used for error separation.  
The profile for the measured crankshaft and the distribution of measured points is shown in Figure 1. Among them, J1-J5 are the main journals, and P1-P4 are the connecting rod journals. In the measurement process, the spindle journals J1-J5 perform autorotation motion around the rotation axis, and the connecting rod journals P1-P4 perform circular motion around the rotation axis. The diameter, roundness, cylindricity, and concentricity of each journal of the crankshaft can be calculated by one rotary motion. This method realizes the synchronous measurement of crankshaft multi-journal and multi-parameters.
## 5 Applications
### Optometry and Opthalmology  
The human eye and optical elements are generally analysed with geometrical optics. The design of corrective refractive elements is also generally handled with geometrical optics. Then, when it comes to wavefront aberrations, especially high-order aberrations, waves and wavefronts are used. However, when designing corrective refractive elements, it is more convenient to use, from the beginning, an approach that is more rigorous than geometrical optics, since wavefront aberrations come into play. Our approach is embedded in this spirit and presents a solution.  
Moreover, when using photoablation-based (PRK, LASIK,... ) corrections, especially for correcting astigmatism, including high-order astigmatism, our approach is more appropriate than the conventional method for treating this situation. Conventionally, we use a combination of geometrical optics with wavefront aberrations.  
Finally, when analysing the retinal image quality and conceiving/applying metrics for image quality, our approach is appropriate [32], since it starts from diffraction theory from the beginning. For example, our approach can easily be used for measuring the influence of anteropia on the retinal image quality of the human eye [36].  
Our approach also enables handling polarization; wavefront aberrations is a straightforward way, since our approach is wave-based. Very useful metrics, such as PSF, the OTF, and the MTF, are straightforwardly processed by using our formalism. For example, the results of [9; 32; 36] are straightforwardly reachable by using our approach without any complex calculation.
## 3 Hypothesis Development
### Engagement  
In fact, interactive aspects of visualization typically contribute considerably to a high level of user engagement and enjoyment. The relationship between interactivity, user engagement, and attitudes has not received much attention in the field of visualization and data journalism, but studies on this topic have been discussed for a very long time in the HCI field. From the perspective of the user gratification theory, interactivity has been shown to promote emotional and social gratification, which are both important indicators of sustained media engagement [36; 37]. According to several studies, participants randomly assigned to higher interaction conditions demonstrated more engagement with online advertising than those in lower interaction conditions [38]. [PERSON] et al. [39] found a strong positive correlation between all measures of perceived interactivity and engagement. Past research has demonstrated that modality interactivity can increase user engagement by altering users' perceptions and attitudes toward mediated material in various contexts [40; 41; 42]. These results indicate that users may be more motivated to engage and process content if there is more interactivity, engaging them with content they might not otherwise attempt to consume. Hence, the following hypothesis is offered:  
**H2a:**_A higher level of user-perceived interactivity will lead to a higher level of engagement in data journalism._  
We also wanted to test the relationship between user engagement and user attitudes in the context of data journalism. [PERSON] and [PERSON] [43] suggested that active participation in the advertising process may be an important element of advertising effectiveness. A variety of studies have used [PERSON]'s Personal Involvement Inventory (PII) [44] to measure the extent to which individuals participate in online activities [39; 45; 46; 47]. Generally, these studies found that user engagement is positively related to attitude toward websites [39]. We, therefore, argue that:  
**H2b:**_Higher user engagement will predict a more positive attitude toward the news._
# Multi-Modal X-ray Imaging and Analysis for Characterization of Urinary Stones
## 2 Materials and Methods
### X-ray Grating-Based Interferometry (GI)  
An in-house X-ray Talbot-Lau grating interferometry setup was also employed to acquire multi-contrast images from three urinary stone samples. The interferometer con sisted of a Varian HPX 160-11 conventional source, a Teledyne Dalsa Shad'o'Box flat-panel detector with Gadox scintillator, and three line gratings made by KIT Microworks. The source grating G0 was made of multiple 70 \(\upmu\)m-high gold lines etched into a Si wafer with a 30 \(\upmu\)m pitch and 0.3 duty cycle. The G0 creates partially coherent beams from the incoherent X-ray tube, working at 45 kVp and 20 mA. The phase grating G1 had multiple 2.92 \(\upmu\)m-pitch line patterns with a 6.1 \(\upmu\)m nickel depth. This grating creates a periodic wave pattern, generating interference fringes at the 4 th Talbot distance on the absorption grating G2. The grating G2 was made of multiple 70 \(\upmu\)m-high gold lines etched into a Si wafer with a period of 3.24 \(\upmu\)m. The G0 to G1 and G1 to G2 distances were 1238 mm and 134 mm, respectively. The detector pixel size was 49.5 \(\upmu\)m [35].  
The three samples were scanned through an 11-step scanning process over one G2 period, and the same process was performed without the sample to obtain the reference images. Each frame was acquired in 2.2 s, which, in total, took 50 s for the whole image acquisition for each sample. The fringe intensity modulation was recorded and analyzed through a common Fourier analysis in a built-in MATLAB program at Empa to retrieve three attenuation, differential phase-contrast, and dark-field images from the interferometer.
# Finite Element Analysis of the Epiretinal Membrane Contraction
## 2 Materials and Methods
### Anisotropic Hyperelastic Constitutive Model for the ERM  
In order to simulate the ERM contraction, a fibrocellular tissue, the transversely isotropic constitutive model proposed by [PERSON] et al. [29] for the simulation of skeletal muscles contraction, was considered. The original model was implemented and modified so that it takes into account two families of fibres embedded into the isotropic matrix. The soft ERM will act as an orthotropic material if the fibres form an angle of \(90^{\circ}\) between them. In any other case, if the angle is different, the ERM membrane will present an anisotropic behaviour [27; 28].  
For the modified version of the Martins, [PERSON] et al. [29], the stored strain energy function is defined by:  
\[\Psi_{\mathrm{JACf}}=\Psi_{\mathrm{JACmat}}+\sum_{i=1}^{2}\Psi_{\mathrm{fib_{ i}}}+\Psi_{\mathrm{vol}} \tag{8}\]  
where \(\Psi_{\mathrm{JACmat}}\) is the isotropic contribution of the matrix:  
\[\Psi_{\mathrm{JACmat}}=c\big{\{}exp\big{[}b\big{(}\overline{I}_{1}-3\big{)} \big{]}\big{\}}. \tag{9}\]  
The contribution of each family of fibres \(\Psi_{\mathrm{fib_{i}}}\) can be divided into a passive elastic part, \(\Psi_{\mathrm{fib_{i}}}^{PE}\) and an active part, \(\Psi_{\mathrm{fib_{i}}}^{SE}\), responsible for the muscles contraction:  
\[\Psi_{\mathrm{fib_{i}}}=\Psi_{\mathrm{fib_{i}}}^{PE}+\Psi_{\mathrm{fib_{i}}}^ {SE} \tag{10}\]  
where  
\[\Psi_{\mathrm{fib_{i}}}^{PE}=A\bigg{\{}exp\bigg{[}a\Big{(}\overline{\lambda}_ {f}-1\Big{)}^{2}\bigg{]}-1\bigg{\}} \tag{11}\]  
is the passive elastic part and  
\[\Psi_{\mathrm{fib_{i}}}^{SE}=T_{0}^{m}\int_{1}^{\overline{\lambda}_{f}}f_{SE }d\overline{\lambda}_{f} \tag{12}\]  
is the active part.  
For the volumetric strain energy, associated with the volume change \(\Psi_{\mathrm{vol}}\), the same equation given by Equation (3) is used.  
In these equations \(c\), \(b\), \(A\) and \(a\) are material constants, \(\overline{\lambda}_{f}\) is the stretch ratio of the ERM fibres, \(T_{0}^{m}\) is the maximum tension produced by the fibres at resting length and \(f_{SE}\) is given by Equation (13) [29]:  
\[f_{SE}=\delta\begin{cases}1-4(\overline{\lambda}_{f}-1)^{2}&\text{for }0.5< \overline{\lambda}_{f}<1.5\\ 0&\text{otherwise}\end{cases} \tag{13}\]  
where \(\delta\in[0,1]\) is the activation variable [27].
## 3 Results and Discussion
It is confirmed that the polarization decreases as the tolerance factor increases due to the gradual increase in the Sn\({}^{4+}\) substitution amount, thus the antiferroelectric properties become unstable, as presented in Figure 6. Therefore, the polarization and the loss were increased, as shown in Figure 7a,b. In the results in Figure 6, the dielectric constant decreased rapidly when the Sn\({}^{4+}\) substitution amount was 0.6. In addition to the slightly decreased sintering density, the dielectric constant decreased rapidly due to the effect of low polarization. However, as the amount of substitution of Sn\({}^{4+}\) increased, the breakdown electric field increased from 4 to 9 kV\(\cdot\)mm\({}^{-1}\). In the results in Figure 4, the grain size decreased as the amount of Sn\({}^{4+}\) substitution increased. As the grain size decreases, the number of grain boundaries increases in the same volume. [PERSON] and [PERSON] [23,24] et al. reported that ferroelectrics with small grain and ceramics with antiferroelectric properties had a higher breakdown electric field; therefore, the results are in good agreement. Figure 7c is a graph in which energy density and efficiency are calculated in the hysteresis curve. The energy storage density (\(J\)) and efficiency (\(\blacksquare\)) are calculated using the formulas below:  
\[J=\int~{}EdP \tag{2}\]  
\[\blacksquare=\frac{J}{J+J_{loss}} \tag{3}\]  
\(E\) = applied electric filed and \(P\) = polarization, where \(J_{loss}\) is the energy-loss density. The energy-loss density was calculated by the numerical integration of closed area of the hysteresis loop [25]. The energy density increased as the amount of substitution gradually increased, but the amount of substitution of Sn\({}^{4+}\) decreased from 0.6. This is considered to be a result of an increase in loss caused by an increase in the tolerance factor value and a decrease in the sintering density. As a result, when the substitution amount of Sn\({}^{4+}\) was 0.4, an energy density of about 3.5 J\(\cdot\)cm\({}^{-3}\) and high energy efficiency of 80% was obtained.
# Metachrylate-Based Polymeric Sorbents for Recovery of Metals from Aqueous Solutions
## 8 Adsorption on Magnetic Polymeric Sorbents
In addition, the selectivity of mPGME-data for Re(VII) sorption was studied at a different contact time and Re/Mo ratio. High uptake of oxyanions was noted, i.e., 92% of Re(VII) and 98% of Mo(VI) were sorbed at pH 2. [PERSON] et al. investigated the adsorption of vanadium (V) oxyanions from aqueous solutions onto diethylene triamine functionalized magnetic macroporous GMA-based copolymer prepared in the presence of magnetite nanoparticles coated with 3-aminopropyltrimethoxysilane, (m-Si-poly(GME)-data) [104]. Vanadium (V) sorption was tested as a function of metal ions concentration, contact time, and pH. Sorption was rapid, with the sorption half time of 1 min and maximum sorption capacity of 28.7 \(\mu\)mol/g. The sorption process was best described by the pseudo-second-order model and Freundlich isotherm. The quantum chemical calculations were performed using the Gaussian09 software package (Gaussian, Inc., Wallingford, CT, USA). The sorption process is favorable in the pH range of 3-6 due to the strong electrostatic interactions between the absorption centers of copolymer and vanadium (V) oxyanions. In the investigated pH range, data absorption centers with two and three protonated N atoms were in equilibrium as studied by quantum chemical modeling. [PERSON] et al. tested magnetite (MG) modified cellulose membrane (Cell-MG), and diethylenetriaminepentaacetic acid dianhydride functionalized waste cell fibers (Cell-NH\({}_{2}\) and Cell-DTPA), and amino-modified diatomic in heavy metal ions [143]. The effects of sorption parameters on adsorption capacity and kinetics were studied. The capacities for nickel, lead, chromium, and arsenic (Ni(II), Pb(II), Cr(VI), and As(V)) ions were 88.2, 100.7, 95.8, and 78.2 mg/g, respectively. [PERSON] et al. observed that chitosan/organic rectorite-Fe\({}_{3}\)O\({}_{4}\) composite magnetic adsorbent (CS/\(\chi\)OREC-Fe\({}_{3}\)O\({}_{4}\)), exhibited better adsorption capacity for removing Cd(II) and Cu(II) ions than magnetic organic-rectorite (OREC-Fe\({}_{3}\)O\({}_{4}\)) and chitosan [144]. The best fit for Cu(II) and Cd(II) uptake provided the Langmuir isotherm model and pseudo-second-order kinetic model. The XPS analysis indicated the adsorption of metal ions by -NH\({}_{2}\) on the adsorbent surface via physical and chemical adsorption. Recycling experiments showed that after four sorption/desorption circles with Na\({}_{2}\)EDTA solutions, the adsorption capacity of CS/OREC-Fe\({}_{3}\)O\({}_{4}\) was above 55%. [PERSON] et al. used porous polymeric adsorbents obtained by suspension polymerization of styrene, divinylbenzene, and GMA and modified with diglycolamic acid ligands for the recovery of rare earth elements [63]. The adsorption isotherm was a Langmuir-type, with an adsorption capacity of 0.113 mmol/g.
# Technology-Economy-Policy: Biochar in the Low-Carbon Energy Transition--A Review
## 4 Technologies: Biochar Production
### Gasification  
Gasification is the process of decomposing biomass into gaseous fuel (H\({}_{2}\), CO, and CH\({}_{4}\), etc.) at higher temperatures (500-1400 \({}^{\circ}\)C) under oxygen-deficient conditions. The production of the gas product can be increased by passing various gasification agents, such as steam, CO\({}_{2}\), and some mixtures of gases. While gasification, like pyrolysis, can produce biochar by heating biomass at high temperatures in a controlled environment with a limited supply of oxygen, it targets the production of syngas for energy purposes, with less emphasis on biochar production [80]. During this process, more than 50% of the biomass is converted into gaseous fuel, and the biochar produced via this process is smaller in size and resistant to chemical oxidation [81]. Temperature is an important factor in the gasification process and results in the increased production of carbon monoxide and hydrogen, with a decrease in carbon dioxide, methane, and hydrocarbons at higher temperatures [82]. The surface area of the biochar produced via gasification is usually smaller and has fewer functional groups, such as hydroxyl, carbonyl, and carboxyl groups, than biochar produced via pyrolysis [83]. The quality and performance of biochar is also affected by the equivalency ratio (ER). A higher ER means that more oxygen is supplied to the gasifier, which can have a positive or negative effect on the properties of the biochar. Ina study by [PERSON] et al. in 2018, the biochar yield and carbon content decreased from 0.22 to 0.14 kg g\({}^{-1}\) of biomass and 88.17% to 71.6%, respectively, along with an increase in ER from 0.1 to 0.6 [84]. The high presence of oxygen molecules results in increased ash content with reduced mechanical strength and performance of biochar. [PERSON] et al. conducted research on the effect of air flow on the properties of biochar made from pine chips. They noted that an air flow of 8 to 20 L min\({}^{-1}\) produces alkaline biochar (pH \(>\) 7.0), and that no acidic functional groups are present at a high air flow [85]. Biochar produced via gasification has a high content of alkali and alkaline earth metals, which depends mainly on the type of biomass [86].
## 3 Contemporary 3D TLS and the Methodology of Their Use for Documenting Archaeological Artefacts
### Scanning Methodology  
When carrying out the task of scanning cultural heritage objects with the use of TLS scanners, it is necessary to follow a specific methodology. This methodology should enable the scanning work to be carried out in a way that, after processing the obtained data, would not force repetition of the actions. The 3 DScaMITE methodology of scanning cultural heritage objects with TLS scanners presented by the authors in [9], distinguishes the following stages: planning, implementation, results processing and dissemination of results. The methodology modified for petroglyph scanning tasks is presented in Table 1.  
The suitability of the scanner used in the research (Faro Focus X330) has been assessed based on scanner specifications. Although the scanner has a systematic error of 1 mm at 20 m (repeatable for each scanner unit), this refers to the global position of the petroglyph surface. The error of measuring petroglyph carvings depth is represented by the random measurement error (noise), which is 0.3-0.5 mm, depending on the surface reflection. This error is additionally reduced by the scanner hardwired procedure of repeating the measurement of each point multiple times (increasing the beam exposure time for each point). This, compared with the expected petroglyph carvings depth of 1-8 mm and the scanner-to-surface distance within the 1.5-5 m range, allows for the claim that the scanner used is suitable for distinguishing petroglyph carvings.  
Figure 4: Sensor panel of the FARO Focus TLS.
_Appl. Sci._**2014**, \(4\), 28-41; doi:10.3390/app4010028  
_Applied sciences_  
**ISSN 2076-3417**  
www.mdpi.com/journal/applsci  
_Article_  
**Terahertz Optoelectronic Property of Graphene:**  
**Substrate-Induced Effects on Plasmonic Characteristics**  
**[PERSON] 1, [PERSON] 1, [PERSON] 2 and [PERSON] 1,**  
1 Electrical Engineering Department, University of California, Los Angeles, Los Angeles, CA 90095, USA; E-Mails: [EMAIL_ADDRESS] (I-T.L.); [EMAIL_ADDRESS] (Y.-P.L.)  
2 Department of Electrophysics, National Chiao-Tung University, Hsinchu 300, Taiwan; E-Mail: [EMAIL_ADDRESS]  
* Author to whom correspondence should be addressed; E-Mail: [EMAIL_ADDRESS]; Tel.: +1-310-206-2097; Fax: +1-310-206-4685.  
_Received: 27 December 2013; in revised form: 22 January 2014 / Accepted: 7 February 2014 / Published: 20 February 2014_  
**Abstract:** The terahertz plasmon dispersion of a multilayer system consisting of graphene on dielectric and/or plasma thin layers is systematically investigated. We show that graphene plasmons can couple with other quasiparticles such as phonons and plasmons of the substrate; the characteristics of the plasmon dispersion of graphene are dramatically modified by the presence of the coupling effect. The resultant plasmon dispersion of the multilayer system is a strong function of the physical parameters of the spacer and the substrate, signifying the importance of the substrate selection in constructing graphene-based plasmonic devices.  
**Keywords:** graphene; plasmon; coupling; phonon; scattering rate; optical conductivity; terahertz; Drude model
# Thermal Conductivity of Nanofluids: A Review on Prediction Models, Controversies and Challenges
## 2 Thermal Conductivity Measurements Overview
### Transient Plane Source Theory  
A fast and sensitive technique with similar principle as the transient hot wire consists of replacing the wire by a hot disk. Similarly, to obtain the temperature and thus calculate the thermal conductivity, the time variation of the electrical resistance is recorded. Like in the case of the Transient Hot Wire Method, convection currents in the fluid might affect the measurements [5; 24].
## 2 Results
### Identification and Determination of DAPs in SRPs by iTRAQ  
Two (R1 and R2) independent 8-plex isobaric tags for relative and absolute quantification (iTRAQ) experiments were performed to determine the DAPs in the SRPs from the D24-, D48-, E24-, and E48-treated rubber latex samples. Altogether, 2596 high-quality unique proteins were determined in the SRPs (Table S3). Venn diagram analysis resulted in 2024 shared unique proteins between R1 (2371 unique proteins) and R2 (2249 unique proteins). There were 347 and 225 specific proteins in R1 and R2, respectively (Figure 4A). Furthermore, we detected 226 DAPs (named as I1 to I226) from the 2024 shared unique proteins in SRPs. These DAPs changed at least 2-fold (\(p<0.01\)) upon ethylene stimulation (E24 and/or E48). Among them, 174 proteins were up-regulated and 126 proteins were down-regulated after ethylene treatment for 24 and/or 48 h. Ten shared DAPs were detected from the iTRAQ and DIGE experiments (Figure 4A).  
Based on the changed patterns, the 226 DAPs from iTRAQ were classified into four areas. The first area contained 60 proteins, which were reduced under E24 but induced in E48. The second area contained 22 proteins which were induced under all ethylene treatments. The third area contained 15 decreased proteins under all ethylene treatments. Finally, the fourth area contained 129 proteins which were induced under E24 but reduced in E48. Our interest was focused on the 22 proteins in the second area that were induced under all ethylene treatments. The 22 proteins in the second area mainly contained REF175 (I66), Nogo-B receptor (I69), rubber cis-poly prenyltransferase HRT2 (I116), elongation factor 1-gamma (I22), albumin-2 like protein, and the vacuolar protein sorting-associated protein 27 (Table S3).
# Examining Pipe-Borehole Wall Contact and Pullback Loads for Horizontal Directional Drilling
## 2 Analysis of Pipe-Borehole Wall Contact
### Classical Contact Models  
The contact between the pipe and borehole wall shown in Figure 2 is a typical internal cylinder contact problem. Researchers have developed different methods for determining the contact pressure distribution and external load-displacement relationship for the internal cylinder contact problem. It should be noted that, unlike classical contact models, the HDD pipe-borehole wall contact model needs to consider the effect of drilling fluid pressure. At this point, the maximum contact pressure between the pipe and the borehole wall changes. Therefore, in this paper, the maximum contact pressure without drilling fluid pressure is denoted as \(q_{0}\), while the maximum contact pressure in HDD (considering the drilling fluid pressure) is denoted as \(p_{0}\). The relationship between \(q_{0}\) and \(p_{0}\) will be discussed in the following sections.
# Compensation of Measurement Uncertainty in a Remote Fetal Monitor
## 3 Uncertainty Estimation Approach
### System Model  
In the block diagram of Figure 1, a system of single input \(u_{k}\) and single output \(y_{k}\) (SISO) is shown in simplified form. Noise \(\xi_{k}\) presence is assumed a priori, and, in this case, white noise properties are attributed, which is presented as additive noise \(r_{k}\) in the system output.  
Figure 1: Single-input and single-output (SISO) system: (**a**) With white noise to the input; (**b**) With additive noise to the output.  
It is considered that an input-output data set of the system is available \((y_{k},\ u_{k};k=1,\ 2,\cdots,n)\) where \(n\) is the measurement number taken from the input and output for modeling.