esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Materials and Methods
### Fabrication of Porous Transport Layers  
The porous transport layers (PTEs) were fabricated by coating the electrode onto the substrates. The anode, an oxygen evolution reaction electrode, was prepared using commercially available iridium oxide (IrO\({}_{2}\), Ir 84.5% min, Alfa Aesar, Haverhill, MA, USA) nanoparticles, PiperION(r) dispersion (5 wt.%, Versogen, Newark, DE, USA) as anion-exchange ionomer (AEI), and a titanium substrate (2 GDL09N-025, Bekaert, Zwevegem, Belgium). The anode catalyst ink was fabricated by mixing IrO\({}_{2}\), PiperION(r), D.I. water, and 2-propanol (99%, Carlo Erba Reagents, Cornaredo, Italy), with a total solid content of 4 wt.% and an ionomer content of 20 wt.%. The cathode, a hydrogen evolution reaction electrode, was prepared using commercially available Pt/C (Pt 46.4%, TKK TEC10F50E, TANAKA, Tokyo, Japan), PiperION(r) AEI, and carbon paper (JNT20-A3, JNTG, Gyeonggi-do, Republic of Korea). The cathode catalyst ink was fabricated by mixing Pt/C, PiperION(r), D.I. water, 1-propanol (99%, Carlo Erba Reagents, Cornaredo, Italy), and 2-propanol, with a total solid content of 4 wt.% and an ionomer content of 30 wt.%. Both the anode and cathode PTEswere prepared by directly spraying the catalyst ink onto the substrates. The resulting PTEs had a loading of 1.0 mg \(\mathrm{IrO_{2}}\)\(\mathrm{cm^{-2}}\) for the anode and 0.4 mg \(\mathrm{Pt\,cm^{-2}}\) for the cathode.
# Harnessing the Potential of Emerging Technologies to Break Down Barriers in Tactical Communications
## 5 Discussion and Future Trends
### From a Signal Processing Point of View  
Foundational components like radios and waveforms require initial upgrades. The classical waveforms mentioned earlier utilize multiplexing and various access schemes based on conventional resources, like frequency-division multiple access, time-division multiple access, or code-division multiple access. However, these prove limiting, given the high number of active components in today's tactical scenarios. Consequently, the innovative nonorthogonal multiple access technique shows promise, surpassing the performance of traditional MAS but also posing challenges for tactical networks. Furthermore, these radios and waveforms are designed for low-communication bandwidths, which proves incompatible with the advanced technologies driven by 5G.  
Apart from the emerging technologies outlined in Section 3, it is worth highlighting the progress in massive multi-antenna systems, enabling the integration of non-coherent communications [59; 60; 61]. This form of communication relies on the capability to demodulate signals without requiring channel estimation information. While non-coherent communications are not novel technologies, they have re-surged in interest and significance due to technological progress. They hold potential value in the tactical field, as the ability to detect without relying on channel information mitigates interception and signal attack concerns. The Doppler effect in high-speed varying channels is solved with non-coherent processing. Enhanced anti-jamming techniques can be improved using the same proposals, which is a challenge for new tactical radio.
# Performance Characterization of GNSS/IMU/DVL Integration under Real Maritime Jamming Conditions
## 4 Setup and Measurement Campaign  
In order to enable experimental jamming tests under real life maritime conditions, the DLR in cooperation with the German Federal Network Agency has allocated a civilian maritime GNSS jamming testbed in the Baltic Sea. The test area is located approximately 10 km North of the Dar8 Peninsula (see Figure 1). The measurement campaign took place in November 2015. A PPD jammer (WolvesFleet 212G, output power: 2 W) was mounted on the monkey deck of the tugboat AARON (length 26 m, beam 8 m) (see Figure 2). During the campaign, the AARON was anchored in the center of the jamming test area, keeping a fixed position and heading. Due to waves (wave height: 1-2 m), the roll and pitch angle of the vessel varied significantly.  
Figure 1: An overview of the civilian maritime jamming test area 10 km north of Peninsula Dar8 (54,5474 N, 12,8154 E).  
Figure 2: AARON with the jammer mounted on the monkey deck.  
The applied PPD jammer was sweeping a continuous wave signal with an update rate of \(\sim\)10 us around the GPS L1 frequency covering a bandwidth of 17 MHz (see Figure 3) affecting both GPS L1 and Galileo E1 signal tracking, while GLONASS L1 mainly remained unaffected. This allowed us to use GLONASS for the calculation of a Precise Point Positioning (PPP) reference trajectory using RTKLib software [42] even in the direct vicinity of the jammer.  
The measurement equipment was installed on BALTIC TAUCHER II, the multipurpose research and diving vessel (length 29 m, beam 7 m, see Figure 4), which was navigated around the tugboat AARON with a maximum speed of 8 knots and a distance to the jammer varying from \(\sim\)50 m to 4000 m. The vessel was equipped with three separate dual frequency GNSS receivers (type: Javad Delta, antenna type: navXperience 3G+C maritime), a FOG IMU (type Imar IMU FCAI, list of specifications at [43]), a gyrocompass, and a DVL (type: Furuno DS 60, list of specifications at [44]). All relevant sensor measurements were provided either directly via Ethernet or via serial to Ethernet adapter to a Box PC where the measurements were processed in real-time and in parallel stored in a SQlite3 database along with the corresponding time stamps. The described setup enables record and replay functionality for further processing of the original sensor data. The system consists of a highly modular hardware platform and a Real-Time software Framework implemented in ANSI - C++ as described in [45].
# Cable-Driven Exoskeleton for Ankle Rehabilitation in Children with Cerebral Palsy
## 2 Exoskeleton Development and Control Methodology
### Discover2 Walk Overview  
The D2W (see Figure 1) features a flexible structure that adapts easily to the child's morphology, allowing guided movement along three-dimensional trajectories tailored to the patient's characteristics, but with a high degree of freedom. In other words, unlike rigid exoskeletons, the D2W does not restrict the child's freedom of movement, enabling them to explore their motor skills and interact with the surrounding environment. Additionally, the inertia introduced by the robot is significantly lower than that of rigid exoskeletons. The D2W is specifically designed to treat children between the ages of 2 and 5 years [40].  
The Discover2 Walk is composed of three modules (see Figure 2) that act independently, but are coordinated and communicated with each other to perform a joint action [41]. The three modules are pelvic module, ankle module, and traction module. Communication and coordination between the elements of the system are achieved through a bio-inspired architecture that mimics the action of the CNS [41].  
Figure 2: Discover2 Walk modules: pelvis (based on four cables), ankle (based on eight cables), and traction control module.
## 5 Nanocarriers as a Strategy to Fight Biofilms
### Affinity to Bacterial Cells  
Nanocarriers can improve the internalization of antimicrobial substances by bacterial cells by fusion with the bacterial membranes. The ability to merge with phospholipid membranes is the most distinctive characteristic of liposomes [87]. Transmission electron microscopy reveals that liposomes closely interact with the Gram-negative bacterial outer membrane, inducing changes in the membrane structure. Liposome fusion with the bacterial membrane has also been verified using flow cytometry and lipid-mixing assays [88]. Lipid nanocarriers' fusion with bacterial cells improves antimicrobial internalization. Additionally, electrostatic attraction or ligand-receptor binding extends the interaction betweennanocarriers and bacteria. This enhances the antibacterial effect and results in a more potent anti-biofilm effect [89].
# Convergence Gain in Compressive Deconvolution: Application to Medical Ultrasound Imaging
## 2 Method  
### Preliminaries  
#### 2.1.1 Variational Reformulation of Equation (4)  
In this section, inspired by [PERSON] and [PERSON]'s approach [17], we equivalently convert the convex minimization model expressed by Equation (4) to a variational form. It makes sense to perform such reformulation, because convergence analysis becomes more concise under the variational model.  
For succedent analysis of the proposed algorithm, let us denote \(z_{1}=v=\Psi a\) and \(z_{2}=p=\left(\begin{array}{c}w\\ x\end{array}\right)\). Then the ultrasound imaging model can be reformulated as  
\[\min_{z_{1},z_{2}\in\mathbb{R}^{N}}\theta_{1}(z_{1})+\theta_{2}( z_{2}) \tag{7}\] \[s.b.\quad Az_{1}+Bz_{2}=0,\]  
where \(\theta_{1}(z_{1})=\frac{1}{2\mu}\|y-\Phi z_{1}\|_{2}^{2}\), \(\theta_{2}(z_{2})=\|w\|_{1}+\alpha\|x\|_{p}^{p}\). The Lagrangian function and augmented Lagrangian function of Equation (7) can be, respectively, expressed as  
\[\mathcal{L}(z_{1},z_{2},\lambda)=\theta_{1}(z_{1})+\theta_{2}(z_{2})-\lambda^ {\mathsf{T}}(Az_{1}+Bz_{2}) \tag{8}\]\[\mathcal{L}_{\beta}(z_{1},z_{2},\lambda)=\theta_{1}(z_{1})+\theta_{2}(z_{2})- \lambda^{\mathsf{T}}(Az_{1}+Bz_{2})+\frac{\beta}{2}\|Az_{1}+Bz_{2}\|^{2}, \tag{9}\]  
where \(\lambda\in\mathbb{R}^{N}\) represents the Lagrangian multiplier. Then hunting for a saddle point of \(L(z_{1},z_{2},\lambda)\) is to seek \((z_{1}^{*},z_{2}^{*},\lambda^{*})\) such that  
\[\mathcal{L}_{\lambda\in\mathbb{R}^{N}}(z_{1}^{*},z_{2}^{*},\lambda)\leq \mathcal{L}(z_{1}^{*},z_{2}^{*},\lambda^{*})\leq\mathcal{L}_{z_{1}\in\mathbb{ R}^{N},z_{2}\in\mathbb{R}^{N}}(z_{1},z_{2},\lambda^{*}). \tag{10}\]  
That is, for any \((z_{1},z_{2},\lambda)\), we have  
\[\theta_{1}(z_{1})+\theta_{2}(z_{2})-(\theta_{1}(z_{1}^{*})+\theta_{2}(z_{2}^{ *}))-(z_{1}-z_{1}^{*})^{\mathsf{T}}A^{\mathsf{T}}\lambda^{*}-(z_{2}-z_{2}^{*} )^{\mathsf{T}}B^{\mathsf{T}}\lambda^{*}\geq 0, \tag{11a}\] \[(\lambda-\lambda^{*})^{\mathsf{T}}(Az_{1}+Bz_{2})\geq 0. \tag{11b}\]  
Then, resolving Equation (4) is equivalent to seeking \(w=(z_{1}^{*},z_{2}^{*},\lambda^{*})\) such that  
\[\text{VI}(\Omega,F,\theta):\theta(u)-\theta(u^{*})+(w-w^{*})^{\mathsf{T}}F(w^{ *})\geq 0,\forall w\in\Omega \tag{12}\]  
where  
\[u=\left(\begin{array}{c}z_{1}\\ z_{2}\end{array}\right),\ w=\left(\begin{array}{c}z_{1}\\ z_{2}\\ \lambda\end{array}\right),\ \theta(u)=\theta_{1}(z_{1})+\theta_{2}(z_{2})\quad\text{and} \quad F(w)=\left(\begin{array}{c}-A^{\mathsf{T}}\lambda\\ -B^{\mathsf{T}}\lambda\\ Az_{1}+Bz_{2}\end{array}\right). \tag{13}\]  
Especially, the mapping \(F(w)\) defined in Equation (13) is affine with a skew-symmetric matrix, it is monotone. We express by \(\Omega^{*}\) the solution set of \(\text{VI}(\Omega,F,\theta)\).
## 3 Results and Discussion
### The Distillation Experiments of REMES and the Phase Changes of REEs
#### 3.2.1 The Distillation Experiments on the Distillation Time for the Phase Changes of REMES  
The REMES sample was heated at 1573 K and 0.1 Pa with the distillation time varying from 2 h to 8 h. The results are showcased in Figure 4. They suggest that when the distillation time was 2 h, the diffraction peaks of NdF\({}_{3}\) significantly decreased, while those of NdOF still remained. After the distillation time reached 4 h, NdF\({}_{3}\) disappeared and only NdOF could be observed. Additionally, the recovery of LiF could be completed at 2 h, and the rare earth recovery efficiency reached a maximum of 42.04% at 4 h (see Figure 4b). This phenomenon indicated that there were at least two kinds of phase transitions for the rare earth compounds during the distillation process, including the evaporation of rare earth fluorides and LiF as well as the generation of NdOF.  
To completely investigate the transition of rare earth compounds, it was necessary to conduct experiments at different distillation temperatures. The distillation time was chosen as 6 h to ensure the complete transition.
# A Vehicle-Bridge Interaction Element: Implementation in ABAQUS and Verification
## 2 Formulations for Vehicle-Bridge Interaction (VBI) Element Applied in ABAQUS
### VBI Element Formulation
By applying \(\{f_{ci}\}\) into \(\{f_{\rm{bei}}\}\) and expressing \(\{f_{ci}\}\) in terms of \(\{d_{\rm{bi}}\}\)[43], we obtain the updated equation of motion for the \(i\)th VBI element:  
\[ \begin{array}{l}\left[m_{\rm bi}\right]\left\{\dot{d}_{\rm{bi}}\right\}_{t +\Delta t}+\left[c_{\rm bi}\right]\left\{d_{\rm{bi}}\right\}_{t+\Delta t}+ \left[k_{\rm bi}\right]\left\{d_{\rm{bi}}\right\}_{t+\Delta t}\\ =\left\{f_{\rm bi}\right\}_{t+\Delta t}-\sum_{j=1}^{n}\left(\left[m_{\rm cij}^ {*}\right]\left\{\dot{d}_{\rm{bj}}\right\}+\left[c_{\rm ci}^{*}\right]\left\{ d_{\rm{bj}}\right\}+\left[k_{\rm ci}^{*}\right]\left\{d_{\rm{bj}}\right\} \right)-\left\{p_{\rm ci}^{*}\right\}_{t+\Delta t}-\left\{q_{\rm ci}^{*}\right\} \end{array}  \tag{4}\]  
where  
\[\left[m_{\rm cij}^{*}\right]=\{N_{\rm ci}^{\rm v}\}m_{cij}\langle N_{\rm c}^ {\rm v}\rangle \tag{5}\]  
\[\left[c_{\rm cij}^{*}\right]=\{N_{\rm ci}^{\rm v}\}c_{cij}\Big{\langle}N_{cj }^{\rm v}\Big{\rangle} \tag{6}\]  
\[\left[k_{\rm cij}^{*}\right]=\{N_{\rm ci}^{\rm v}\}k_{cij}\Big{\langle}N_{cj }^{\rm v}\Big{\rangle} \tag{7}\]  
and the equivalent force vectors are  
\[\{p_{\rm ci}^{*}\}_{t+\Delta t}=\{N_{\rm ci}^{\rm v}\}p_{{\rm ci},t+\Delta t}, \quad\{q_{\rm ci}^{*}\}_{t}=\{N_{\rm ci}^{\rm v}\}q_{ci,t} \tag{8}\]  
where the contact matrices \([m_{\rm c}]\), \([c_{\rm c}]\) and \([k_{\rm c}]\) and the load vectors \(\{p_{\rm c}\}\) and \(\{q_{\rm c}\}\) are related to the mass, damping, and stiffness matrices and the contact force and external force vectors for the vehicle system. The details of the algebra process are presented in [43]. Based on the above algorithm, the equation of motion for a VBI element can be solved directly by updating its stiffness, damping, and mass matrices without iteration, enabling ABAQUS to realize it through a user-element subroutine (UEL).
# Blockchain for Doping Control Applications in Sports: A Conceptual Approach
## 3 Blockchain-Based Approach for the AD Domain
### Design of a Decentralized Anti-Doping Ecosystem  
Considering the analysis towards the adoption of a permissioned blockchain, platform-specific articles, design guides, and books were checked [14; 74; 78; 82]. Hyperledger Fabric (HLF) was the chosen platform for this work. HLF is an open-source project governed by the Linux Foundation, possessing a modular architecture that enables confidentiality, flexibility, and scalability and allows components such as the consensus and membership services to function as plug-and-play accessories [74]. HLF modularity can be described horizontally by identity management, ledger management, transaction management, and smart contracts components, and vertically by membership management, consensus services, chaincode services (chaincode is the proprietary name given to SC implementation in HLF), and security and cryptographic services components [83]. All nodes in the network are identifiable, enabling a controlled environment. The concept of consensus follows an execute-order-validate process, which eliminates uncertainties in the formation of blocks. Another important characteristic of HLF is its ledger technology, which is decomposed in two parts, a blockchain log and a state database. The blockchain log stores the history of transactions; in other words, the state transitions of an asset, which is a write-only process, and each block recorded is a collection of transactions. The state database is a representation of the current state of an asset, which allows some performance improvement for the system; its absence would require computer programs to traverse the whole transaction log to calculate the asset state. In HLF, the assets stored in the state database are defined as key-value pairs, which can be created, erased, or updated; therefore, the state database can change frequently [9; 14; 74]. The privacy protection, anonymity, and security of the ledger can be handled by the platform's cryptographic services and digital certificate management system [14; 74]. In any blockchain system, different aspects of privacy shall be considered: Transactional Data Privacy; State Data Privacy; SC Privacy; and User Privacy (which refers to the anonymity and unlinkability of users). These aspects are not properly addressed by permissionless blockchains, but in HLF three first aspects are implemented by default, while the aspect of user privacy requires additional attention [74; 83]. The main aspects of this conceptual approach are discussed in what follows.
# A Reversed-Phase HPLC Method for Determination of Osteopontin in Infant Formula
## Materials and Methods  
### Preparation of OPN Standard  
Bovine OPN standard was purchased from Sigma-Aldrich (Saint Louis, MO, USA) to prepare a standard stock solution of 5 mg/L in 40% acetonitrile (ACN) in 0.1% trifluoroacetic acid (TFA) to confirm the miscibility of the standard. Further, a serial dilution was followed to prepare 0.6125, 1.25, 2.5 and 5 mg/L OPN solution. Moreover, an OPN solution of 1 mg/mL was also prepared to study the precision, accuracy and robustness of the method. HPLC-grade ACN (\(\geq\)99.9%), purchased from Sigma-Aldrich (CAS 75-05-8, Castle Hill, Australia), and Milli-Q water were used to prepare the solutions.
## 3 Results
### Direct Authenticity Test and Evaluation of FY-4A LST Using In Situ Measurement
The ability of the FY-4A LST product to capture changes in LST decreased as elevation increased (R gradually decreased), but the deviation from in situ observation gradually decreased (Bias and RMSE both improve greatly). This may also be related to the decrease in LST as elevation increased.
## 2 Case Presentation
### VR for Surgical Planning  
CT images and facial scan data were obtained for the computer-assisted surgery. Facial markers were attached to the patient's skin before CT and facial scanning. CT and facial scans (Artec(r) Space Spider; Artec(r) Group; Luxembourg) were sequentially performed. Using Mimics software (17.0, Materialise, Leuven, Belgium), lesions and normal bone tissue were segmented separately from the CT images. 3D images of normal bone tissue and lesions extracted from CT, and 3D images of skin through the facial scan, were converted into STL files. 3D models were registered according to the facial markers. We developed a VR simulation software using Unity 3D, which could simulate preoperative planning using a head mounted display (VIVE pro, HTC, Taoyuan, Taiwan) with intuition and immersiveness. Using this VR simulation, an osteotomy line was designed considering the anatomical structures, safety margins, and accessibility of the instruments used in the actual surgery. The osteotomy line was displayed in the form of a plane that indicated the cutting lines and directions in consideration of the visibility in the AR viewer developed by us (Figure 3). Preplanned 3D models were exported as STL files. The exported models were imported by the AR viewer. The AR viewer could track the markers automatically and overlay the 3D models with adjustable transparency on the actual patient. In addition, a customized polycaprolactone mesh (T&Biofab Co., Ltd., Si-heung, Korea) was prepared for the reconstruction of the orbital floor. The polycaprolactone (PCL) orbital mesh is a patient specific implant, which was produced with biocompatible PCL in T&R Biofab's 3D printing system. For the design of the customized mesh, standard data were established based on the data obtained from the computed tomography (CT) images. Through computer-aided designing, the 3D model of PCL mesh was extracted from the curvature to the orbital wall and floor. PCL orbital mesh size was 36 mm width, 39 mm length, 14 mm height, and 1.15 mm thickness. PCL mesh was fixated in the orbital floor by being sutured to the remained bone.
# A Real-Time Automated System for Dual-Aperture Common-Path Interferometer Phase-Shifting
## 4 Results and Discussion
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Simulated Value** & **Calculated Value** & **Error (Absolute Value)** \\ \hline \(\alpha_{0}=0\) & \(\alpha_{0}=0\) & - \\ \(\alpha_{1}=1.57079\) & \(\alpha_{1}=1.586469\) & 0.015 \\ \(\alpha_{2}=3.14159\) & \(\alpha_{2}=3.142185\) & 0.0005 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Comparison between the simulated and the calculated values for the phase shifts. Figure 5: Front panel of LabView for the implemented algorithm with simulated interferograms: (**a**) simulated pattern without phase shift, (**b**) simulated pattern with phase shift of \(\pi/2\) rad, (**c**) simulated pattern with phase shift of \(\pi\) rad, (**d**) calculated wrapped phase function, (**e**) original 2D phase function, (**f**) recovered (unwrapped) 2D phase function, (**g**) difference between the original and the recovered phase, and (**h**) recovered 3D phase plot. Figure 6: Experimental pattern captures. The results of the characterization of the phase shift introduced by each stepper motor rotation step are shown in Figure 8. The measurement was obtained from 47 consecutive experimental pattern captures. The calculated values of \(\alpha\) from the consecutive images recorded were obtained by using the aforementioned algorithm. The first set of results was computed with the obtained interferograms from 1 to 3, the second set of results was computed with the obtained interferograms from 2 to 4, and so on to complete all 46 calculations of the phase step. The theoretical phase step value calculated with Equation (2) is \(\alpha_{T}=2.493\) rad (blue line), whereas the average value of the experimental phase step of \(\overline{\alpha}=2.483\) rad (green line) was obtained from the calculated values of \(\alpha\) from the consecutive recorded interferograms. The bias between the theoretical and experimental values is \(|\alpha_{T}-\alpha|=0.01\) rad. The average standard deviation of the total result is of \(\sigma=0.197\). Finally, it is possible to calculate the average value with the uncertainty percentage as \(\overline{\alpha}=2.483\) rad \(\pm\) 8%, which is comparable to the result obtained by manual transversal displacement of the ruling in a DACPI system but with measurements obtained over half a step of the reported values [29]. It is important to mention that because the algorithm is capable of evaluating phase changes with non-uniform shifts, the system was able to obtain the phase function with complex implementation, high-precision devices, and special calibration. Figure 8: Experimental estimation of error in the phase step. Figure 7: Experimental results: (**a-c**) phase-shifted consecutive experimental interferograms, (**d**) wrapped phase, (**e**) 2D plot unwrapped phase, and (**f**) 3D plot unwrapped phase.