esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Materials and Methods
### Automated IS-SPME-GC-MS Instrumental Set-Up and Analysis Conditions  
Automated SPME for IS sampling was performed using a MPS-2 multipurpose sampler (Gerstel, Mulheim a/d Ruhr, Germany) online integrated with an Agilent 7890 GC unit coupled to an Agilent 5977C MS spectrometer equipped with a High-Efficiency Source (HES) (Agilent, Little Falls, DE, USA) operating in EI mode at 70 eV. The transfer line was set to 280 \({}^{\circ}\)C. A HES Tune was used and the scan range was set to \(m/z\) 35-350 (full scan acquisition), with a scanning rate of 1000 amu/s, to obtain a suitable number of data points for each chromatographic peak to ensure reliable identification. Analyses were also acquired in Single-Ion Monitoring (SIM) mode for the accurate quantification of selected (key aroma) markers. A SE52 capillary column (95% polydimethylsiloxane, 5% phenyl--30 m \(\times\) 0.25 mm \(d_{c}\)\(\times\) 0.25 \(\upmu\)m \(d_{f}\)) from Mega (Legnano, Milan, Italy) was used.  
For Linear Retention Index (\(l^{T}\)) determination, the \(n\)-alkane liquid sample solution (100 mg/L) was injected using the MPS-2 multipurpose sampler (Gerstel) under the following conditions: injection mode: split, split ratio 1:50, injector temperature 250 \({}^{\circ}\)C, injection volume 1 \(\upmu\)L.  
The analytes sampled by IS-SPME were thermally desorbed from the fiber for 5 min, directly into the GC injector, under the following conditions: injection mode: split, split ratio 1:20, injector temperature 250 \({}^{\circ}\)C. The carrier gas was helium, with a constant flow rate of 1.0 mL/min. The temperature program was 40 \({}^{\circ}\)C (1 min) to 170 \({}^{\circ}\)C at 3 \({}^{\circ}\)C/min and to 260 \({}^{\circ}\)C at 10 \({}^{\circ}\)C/min (5 min).
# Ionic Liquids Hybridization for Carbon Dioxide Capture: A Review
## 4 Application of ILs Hybrid Material in Carbon Dioxide
### ILs/Mof
However, the reduction in the peak intensity at 7.5\({}^{\circ}\) and 16.5\({}^{\circ}\) for all complexes indicates changes in ZIF-8 electron density. Furthermore, functional group analysis showed changes in peak shifting and intensity that are believed to be caused by the interaction between ILs and ZIF-8. This IL-MOF interaction has also been confirmed by TGA analysis in which ZIF-8/ILs TG curves showed two-step decomposition instead of single-stage mass loss as observed in pristine ZIF-8. Additional analysis on \({}^{19}\)F NMR revealed ILs with [Tf\({}_{2}\)N]\({}^{-}\) anion could be found in exterior structure of ZIF-8. Meanwhile, a study on CO\({}_{2}\) and CH\({}_{4}\) separation was conducted in terms of individual isotherm and was later used to calculate the ideal selectivity. The adsorption of hybrid ZIF-8/ILs at high pressures was lower than pristine ZIF-8. This is directly related to the reduction in total pore volume and BET surface area. Nevertheless, ZIF-8/[EMIM][OAc] presented an 8.0% increase in adsorption at low pressure (0.5 bar) mainly caused by the [OAc]\({}^{-}\) chemical interaction with CO\({}_{2}\). For the ZIF-8 coupled with Tf\({}_{2}\)N-based ILs, the CO\({}_{2}\) adsorption had reduced as the cation alkyl chain increased. This result is contrary to several previous studies conducted on CO\({}_{2}\) absorption by ILs alone in which the longer the alkyl chain, the higher the CO\({}_{2}\) sorbent capacity [26; 27]. In terms of MOF/ILs, the flexibility of a long alkyl side-chain has led to additional pore blockage compared to ILs with shorter chain which, in turn, reduces gas accessibility to the available pores. For functional group comparison, the combination of ZIF-8 and hydroxyl ILs produced lower CO\({}_{2}\) adsorption than ZIF-8/[EMIM][Tf\({}_{2}\)N]. As non-polar CO\({}_{2}\) and CH\({}_{4}\) were preferable to be attracted to less polar ILs, the presence of a polar hydroxyl group (OH) in ILs caused the repulsion force with both gases thus lead to poor adsorption capacity. Although the CO\({}_{2}\) uptake of all hybrid material was less than pristine ZIF-8, the calculated ideal selectivity indicates the selectivity increased up to 40% at 0.5 bar mainly for ZIF-8/[EMIM][OAc] and ZIF-8/[HMIM][DCN].
## 2 Dynamic Modeling of HDFRMS
### Mechanical Subsystem Model
Considering the coordinate system and the kinematics of three link rigid-flexible manipulators, the kinetic energy of the mechanical subsystem can be obtained as  
\[\begin{array}{ll}T&=(\frac{1}{6}\rho_{2}L_{2}^{3}+\frac{1}{2}m_{3}L_{2}^{2}+ \frac{1}{2}\rho_{3}L_{3}L_{2}^{2}+\frac{1}{2}ML_{2}^{2})(\hat{\theta}_{2}^{2}+ \hat{\phi}_{2}^{2}\hat{\theta}_{1}^{2})+[\frac{1}{6}\rho_{1}(r_{2}^{3}-r_{1}^{ 3})+\frac{1}{2}m_{2}r_{1}^{2}]\hat{\theta}_{1}^{2}\\ &+\rho_{3}L_{2}\int_{0}^{L_{3}}\dot{\omega}dr\hat{\rho}_{2}c_{3}+\frac{1}{2}ML_ {3}^{2}[(\hat{\theta}_{2}+\hat{\phi}_{3})^{2}+\hat{\theta}_{1}^{2}\hat{\kappa} _{2}^{2}]+\hat{\theta}_{2}\rho_{3}\int_{0}^{L_{3}}\dot{\omega}dr+(\frac{1}{2} \rho_{3}L_{2}L_{3}^{2}\\ &+ML_{2}L_{3})[c_{3}\hat{\theta}_{2}(\hat{\theta}_{2}+\hat{\theta}_{3})+s_{2} s_{2}\hat{\theta}_{1}^{2}]+(\frac{1}{2}\rho_{3}l_{3}^{L_{3}}\omega^{where \(c_{1}=\cos\theta_{1}\), \(c_{2}=\cos\theta_{2}\), \(c_{3}=\cos\theta_{3}\), \(s_{1}=\sin\theta_{1}\), \(c_{23}=\cos(\theta_{2}+\theta_{3})\), \(s_{3}=\sin\theta_{3}\), \(s_{2}=\sin\theta_{2}\), \(s_{23}=\sin(\theta_{2}+\theta_{3})\), \(\omega=\omega(r,t)\), \(\dot{\omega}=\[PERSON]_{1}(r)\dot{q}_{1}(t)+\[PERSON]_{2}(r)\dot{q}_{2}(t)\), \(\dot{\omega}_{L_{3}}=\[PERSON]_{1}(L_{3})\dot{q}_{1}(t)+\[PERSON]_{2}(L_{3})\dot{q}_{2}(t)\) and \(\frac{\partial^{2}\omega}{\partial\omega^{2}}=\dot{\Phi}_{1}(r)q_{1}(t)+\dot{ \Phi}_{2}(r)q_{2}(t)\).  
Defining a Lagrange function \(L\), which consists of total potential energy \(V\) and total kinetic energy \(T\), we get \(L=T-V\).  
According to the following Lagrange equation [25]  
\[\frac{d}{dT}(\frac{\partial L}{\partial p_{i}})-\frac{\partial L}{\partial p_ {i}}=\tau_{i} \tag{6}\]  
the dynamic model of the rigid-flexible manipulator without the viscous damping and the external interference can be expressed as  
\[M(\theta,q) \begin{bmatrix}\ddot{\theta}\\ \ddot{q}\end{bmatrix} +K \begin{bmatrix}\theta\\ q\end{bmatrix} +G(\theta,\dot{\theta},q,\dot{q})= \begin{bmatrix}\tau\\ 0\end{bmatrix}  \tag{7}\]  
where \(M(\theta,q)\) is the \(5\times 5\) positive definite, symmetric, time-varying generalized inertia matrix, \(K=diag(k_{1},k_{2})\) is the stiffness matrix of the flexible link 3, \(G(\theta,\dot{\theta},q,\dot{q})=[g_{1}g_{2}g_{3}g_{4}g_{5}]^{\rm T}\) consists of Coriolis force, centrifugal force and gravity, \(\theta~{}=~{}[\theta_{1}\theta_{2}\theta_{3}]^{\rm T}\) is the joint angles, \(q~{}=~{}[q_{1}q_{2}]^{\rm T}\) is the mode coordinates and \(\tau~{}=~{}[\tau_{1}\tau_{2}\tau_{3}]^{\rm T}\) is the control torque. **Remark 1**. : _Utilizing the Lagrange equation, \(p\) contains joint angles \(\theta\) and elastic displacement \(\omega\). The joint angles \(\theta\) and control torque \(\tau\) are considered when \(i=1,2,3\). Otherwise, we have_  
\[\frac{d}{dT}(\frac{\partial L}{\partial\dot{\omega}})-\frac{\partial L}{ \partial\omega}~{}=~{}0\]
## 4 Flight Test Results and Discussion
### Flight Test Records
Furthermore, we found a large interval time at the beginning of the flight that resulted in a large trajectory gap, as indicated in Figure 8. The data indicate that the latency and interval data times varied over time due to the signal quality of the 4G communication used. The complete flight data as mentioned in the record of Table 2 is shown in Appendix A. Each flight test record consisted of two sets of charts from module 1 and module 2 of the Remote ID. In general, the UTM monitoring system functioned as intended. However, its performance varied due to some influencing factors, the analysis of which is discussed in the later part of this section.
# Experimental Study on Interface Frictional Characteristics between Sand and Steel Pipe Jacking
## 3 Analysis of Test Results  
### Effect of Particle Size on Shear Stress  
It can be seen from Figure 3 that the variation of the shear stress-displacement curve of sandy soil, with and without slurry lubrication, is basically the same at a normal stress of 40 kPa. In the initial stage of shear, with the increase of shear displacement, the shear stress increases, and there is an obvious peak value of the curve. After reaching the peak, the shear stress will decrease with the increase of the shear displacement and then gradually stabilize, showing an obvious strain-softening type. Figure 3a shows that without slurry lubrication, the peak and stable values of the shear stress are related to the grade of the soil sample, which shows that powder sand > fine sand > medium sand > coarse sand > gravel sand, that is, the peak and stable values of the shear stress decrease with the increase of the sand soil particles. Figure 3b shows that the order of peak shear stress and the stable value in the slurry-lubricated test group is the same as that without slurry lubrication, but the value is smaller than that without slurry lubrication. The following test results can be obtained by comparing the test groups with reference to different normal stress conditions: the larger the sand particles are, the smaller the shear stress between the steel plate and the sand, when other conditions are the same. [PERSON] et al. [17] in 2000 showed that the internal friction angle of sandy soil is positively related to its average grain size, and as the grain size of sandy soil increases, the internal friction angle of sandy soil increases, and the shear stress between sandy soil and a steel plate increases. The above experimental phenomenon is just the opposite of Sitharam, which is analyzed as follows. There are differences in the mechanical parameters between the contact surface of sandy soil and a steel plate with different grain sizes, which are related to the sandy soil grain size and grain gradation. The sandy soil configured in the test is divided into five types according to the average particle size. The sandy soil particles are all irregularly shaped with sharp angles, and the sandy soil with a large average particle size has a high content of large particles. The contact mode between large particles is mostly point contact, the pores between particles are large and the effective contact area is relatively small, so the effective contact area between the same steel plate is small. The sand with a small average particle size has a high content of small particles, a good filling effect between particles and a denser structure, so the effective contact area with the steel plate is also larger. Therefore, the peak shear stress between the sand with a small average particle size and the steel plate is larger under the same condition of normal stress.
## 6 Discussion  
### Pipeline Damage and Wear  
Damage and wear caused by transported rock particles were found in each component of the pipeline system. To address pipeline wear, wear-monitoring work was performed, and the results are presented in Figure 15. The largest wear amounts measured were more than 80 mm at the two points of the 90\({}^{\circ}\) elbow pipe, indicating that the 90\({}^{\circ}\) elbow was the most severely worn part. The straight pipe inclined at 60\({}^{\circ}\) with the horizontal was second, with an attained wear amount of approximately 40 mm. The total wear amounts were approximately 27 mm at the monitoring points of the pipeline installed at the tunnel along a small radius curve. For monitoring points along straight pipe sections, the wear amounts were the lowest, at approximately 12 mm. It was found that before segment ring 705, the measured wear rates were slow, at approximately 4 mm per 100 rings of the 90\({}^{\circ}\) elbow pipe, approximately 2.14 mm per 100 rings of the 60\({}^{\circ}\) inclined pipe, approximately 1 mm per 100 rings of the pipe along the curved tunnel with a small radius, and approximately 0.71 mm per 100 rings of the straight tunnel segment. After segment ring 705, the machine drove into rock ground, and the wear rates increased by one to two times.  
The results are analyzed as follows: The damage and wear of slurry discharge pipelines are influenced by many factors, such as the mechanical properties of the carrier slurry, the flow rate of the slurry, the pipeline type (pipe or elbow/bend), and, most importantly, the physical and mechanical properties of the transported rock particles. Referring to Figure 6, the flow rate of the slurry in the pebble layer is generally higher than that in the rock ground, but the observed pipeline wear results exhibit a higher wear rate when tunneling into rock ground. Thus, there must exist another dominating factor that governs pipeline damage and wear. From the rock particles shown in Figures 5 and 6, the reasons could be attributed to the angularities of the rock fragments from rock cutting with disc cutters. Angular rock particles with sharp edges produce more wear and tear on pipelines compared with rounded and subrounded rock particles from the pebble layer.  
Figure 21: Preparing additional pipes beforehand.
# Numerical Study of the Filtration Performance for Electrospun Nanofiber Membranes
## 2 Numerical Simulation Method
### Theoretical Basis of Numerical Simulation  
#### 2.2.1 Gas Control Equation  
When using the FlowDict module of GeoDict to simulate the flow field of the electrospun nanofiber membrane, only the fluid passes through the fibrous membrane without carrying particles. It is assumed that the fluid is in a stationary state, that is, the state of the fluid will not change with time. At this time, the partial differential equations to be solved will not involve the time derivative. In the GeoDict software, the geometric structure of an object is obtained through the analytical calculation of the grid, namely the voxel. In the content of this study, the geometric morphology of the pores inside the fiber filter medium is represented by analyzing the calculation grid. This means that the pore space and the solid material are decomposed into numerous voxels together.  
When conducting the flow simulation of the electrospun nanofiber membrane, it is assumed that the fluid passing through the nanofiber filter material is a viscous, incompressible, and steady-state fluid. Then, the mass conservation equation describing the fluid flow is shown in Equation (1) as follows:  
\[\
abla\cdot\overset{\rightarrow}{u}=0 \tag{1}\]  
In the equation, \(\overset{\rightarrow}{u}\) is the velocity vector, m/s.  
The flow of the fluid in the pores is described by the Navier-Stokes (momentum conservation equation) equation, as shown in Equation (2) below:  
\[-\mu\Delta\overset{\rightarrow}{u}+\rho(\overset{\rightarrow}{u}\cdot \
abla)\overset{\rightarrow}{u}+\
abla p=\overset{\rightarrow}{f} \tag{2}\]  
In the equation, \(\mu\) is the dynamic viscosity, Pa-s; \(\rho\) is the fluid density, kg/m\({}^{3}\); \(p\) is the pressure, Pa; and \(\overset{\rightarrow}{f}\) is the external force acting on the fluid, Pa.  
In the fibrous filter medium, the flow usually exhibits a slow and laminar state, and there is no external force acting, i.e., \(\overset{\rightarrow}{f}=0\). Therefore, the Navier-Stokes equation can be simplified to the Stokes equation to describe this situation, as shown in Equation (3) below:  
\[\
abla p=\mu\Delta\overset{\rightarrow}{u} \tag{3}\]  
For the flow simulation of electrospun nanofiber membranes, the no-slip boundary condition was applied at the fiber surfaces. This means that the velocity of the fluid at the fiber surface is equal to the velocity of the fiber itself (zero velocity since the fibers are stationary), which is consistent with the continuum flow assumption for air at the given operating conditions (face velocity = 6.89 cm/s, ambient pressure). The Knudsen number (Kn) for the airflow in this study was calculated to be approximately 0.001, which is much smaller than 0.01. This confirms the validity of the no-slip condition according to the continuum flow theory (Kn < 0.01 indicates a continuum flow regime where the no-slip condition is applicable).
## 5 Numerical Examples
_For the demand parameters_ \(a\) _and_ \(b\)_, an increase in the value of_ \(a\) _causes increases in_ \(\omega^{*}\)_,_ \(p^{*}\)_,_ \(q^{*}\)_,_ \(Q^{*}\)_,_ \(TP^{*}_{\text{CT}\
u}\)__\(TP^{*}_{\text{CT}\
u}\)__\(TP^{*}_{\text{CT}\
u}\)__\(E^{*}_{\
u}\)__\(E^{*}_{\
u}\)__,_ \(T^{*}_{\text{CT}\
u}\)__\(E^{*}_{\
u}\)__, and_ \(E^{*}_{b}\)_. The results show that autonomous consumption has positive effects whereas induced consumption has negative effects on the manufacturer's and retailer's optimal equilibrium policies. In addition, all manufacturer's and retailer's total profits and carbon emissions increase as autonomous consumption increases or induced consumption decreases._
2. _An increase in the retailer's order cost or fixed shipping cost corresponds to an increase in the manufacturer's optimal equilibrium shipping quantity and the retailer's optimal equilibrium order quantity but a decrease in the manufacturer's optimal equilibrium technology investment for carbon emission reduction. Furthermore, the retailer's order cost or fixed shipping cost has positive effects on the manufacturer's total profit but negative effects on the retailer's total profit. With regard to the amount of carbon emissions from both the manufacturer and retailer, it decreases with higher retailer's order cost or fixed shipping cost._
3. _Higher retailer's holding cost or deterioration rate of finished goods implies a corresponding decrease in the manufacturer's optimal equilibrium shipping quantity and the retailer's optimal equilibrium order quantity, which results in a drop in the total profits of both players. This is very intuitive because the retailer does not want to keep too much inventory when the holding cost or deterioration rate is high._
4. _Moreover, any increases in the retailer's variable shipping cost lessens the manufacturer's optimal equilibrium technology investment for carbon emission reduction, shipping quantity, the retailer's optimal order quantity, the total profits of the manufacturer and the retailer, and the carbon emissions from themanufacturer and the retailer. Furthermore, the retailer's selling price increases with higher retailer's variable shipping cost. 5. Overall, changes in autonomous or induced consumption is relatively sensitive to the optimal equilibrium solutions, profits or carbon emissions for the manufacturer and the retailer. Conversely, changes in retailer's other parameters are less sensitive to the optimal equilibrium solutions (especially the technology investment for carbon emission reduction and selling price).
# Towards a Hybrid Approach to Context Reasoning for Underwater Robots
## 1 Introduction
A lot of context reasoning methods have been off-the-shelf and reviewed in [13; 14]; however, none of them is versatile and could individually solve all the reasoning requirements in underwater robots. There is a necessity for a shift towards a combination of different context reasoning methods [7]. Ontological reasoning [15] is the widely used context reasoning method as it could can ontology consistency and concept subsumption. SWRL (Semantic Web Rule Language) [16] rules are proposed to be incorporated into ontologies and could mitigate the lack of ontologies in determining useful information based on rules [17]. However, both of them lack the ability to reason under uncertainties as they assume a deterministic world. Probability is considered the most well-known formalism for computational scientific reasoning under uncertainties [18]. The emerging probabilistic reasoning method, namely the Multi-Entity Bayesian Network (MEBN) [18], as an extension of the standard Bayesian Network (BN), could represent and reason about problems that involve a varying number of uncertain entities. Such complex reasoning problems are common in the underwater robot field. For example, the investigated robot may have more than one robot around. The collision risk is  
Figure 1: The lifecycle of context awareness. affected by all possible nearby robots, thus resulting in a problem that involves a varying number of entities. The MEBN shows a lot of potential in reasoning about such complex problems in underwater robots. Therefore, in this paper, the first proposal of using a hybrid context reasoning mechanism, including ontological, rule-based, and MEBN reasoning, in underwater robots is presented. The incorporation of ontological, rule-based, and MEBN reasoning methods can provide better performance by compensating for individual weaknesses using others' strengths. The proposed reasoning mechanism is more flexible and effective to provide different reasoning capabilities to satisfy different reasoning needs. It could provide a logic reasoning strategy to deal with certain context information while enabling a probabilistic inference on uncertain contexts. A scenario of oil spill detection is simulated and it is used to theoretically verify the proposed hybrid reasoning mechanism in terms of applicability and usefulness. The remainder of this paper is structured as follows. Section 2 reviews existing context-aware frameworks for underwater robots and different context reasoning methods used in the realization of context awareness. An overview of the context-aware framework and the SWARMs ontology proposed in the SWARMs project is provided in Section 3. In Section 4, the proposed hybrid context reasoning is presented and the specific workflow of the hybrid context reasoning engine is shown. A case study of an oil spill monitoring problem is provided in Section 5 to show the usefulness of the proposed reasoning mechanism. Finally, conclusions are given in Section 6 and future work is pointed out as well.
###### Abstract  
This article compares two methods of algorithmically processing bandlimited time-continuous signals in light of the general problem of finding \"suitable\" representations of analog information on digital hardware. Albeit abstract, we argue that this problem is fundamental in digital twinning, a signal-processing paradigm the upcoming 6G communication-technology standard relies on heavily. Using computable analysis, we formalize a general framework of machine-readable descriptions for representing analytic objects on Turing machines. Subsequently, we apply this framework to sampling and interpolation theory, providing a thoroughly formalized method for digitally processing the information carried by bandlimited analog signals. We investigate discrete-time descriptions, which form the implicit quasi-standard in digital signal processing, and establish continuous-time descriptions that take the signal's continuous-time behavior into account. Motivated by an exemplary application of digital twinning, we analyze a textbook model of digital communication systems accordingly. We show that technologically fundamental properties, such as a signal's (Banach-space) norm, can be computed from continuous-time, but _not_ from discrete-time descriptions of the signal. Given the high trustworthiness requirements within 6G, e.g., employed software must satisfy assessment criteria in a provable manner, we conclude that the problem of \"trustworthy\" digital representations of analog information is indeed essential to near-future information technology.  
digital twinning; sampling; interpolation; Shannon series; bandlimited signals; Turing machines; computability; computable analysis; trustworthiness +
Footnote †: This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ([[https://creativecommons.org/licenses/py/4.0/](https://creativecommons.org/licenses/py/4.0/)]([https://creativecommons.org/licenses/py/4.0/](https://creativecommons.org/licenses/py/4.0/))).