esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Sensitivity Analysis and Optimization Implementation
### Optimization Implementation  
The design domain is discretized by four-node bilinear elements. Numerical instabilities involved in the optimization process, such as the checkerboard pattern and the mesh dependence, are addressed by the sensitivity-based filter method [15]. The sensitivity filter radius is set to 1.5 times the element size. The present multi-constraint optimization problem is solved by using the well-known method of moving asymptotes (MMA) [66]. The convergence criterion is that the maximum iteration number attains 2000 or the maximum variation of design variables is less than 0.01.  
Here, we summarize the optimization procedure for the topology optimization of MIMO compliant mechanisms in this paper as follows:  
Step 1. Make an initialization by setting initial values for parameters.  
Step 2. Carry out the finite element analysis (FEA) to obtain \(u_{Oi}\), \(\widetilde{u}_{Oj,i}\), \(\widetilde{u}_{Ij,i}\), \(C_{li}\) and \(C_{Oi}\).  
Step 3. Calculate \(\omega_{l}\), \(w_{li}\) and \(w_{Oi}\) by Equations (5), (9) and (10), respectively.  
Step 4. Compute and then filter the sensitivities related to the design problem (13).  
Step 5. Update design variables by the method of moving asymptotes (MMA).  
Step 6. Check for convergence. If not converge, go to Step 2.
# B-Line Detection and Localization in Lung Ultrasound Videos Using Spatiotemporal Attention
## 4 Materials and Experimental Setup  
### Data Collection and Annotation  
The LUS scans were performed using a Sonosite M-Turbo machine (Fujifilm Sonosite, Inc., Bothell, WA, USA) with a low-medium frequency (3.5-5 MHz) convex probe by qualified sonographers. A standardised operating procedure based on the Kigali ARDS protocol [28] (assessment for B-lines [29; 30], consolidation and pleural effusion) was performed at six points on each side of the chest (two anterior, two lateral and two posterolateral).  
Data were collected from 60 Dengue patients at the Hospital of Tropical Diseases (HTD) in Ho Chi Minh City, Vietnam. All patients were recruited following approved institutional ethics and after informed consent, and in agreement with the Declaration of Helsinki. This LUS video dataset contains approximately five hours B-line and non-B-line video data with video resolution of 640 \(\times\) 480 pixels and a frame rate of 30 fps. Then, each four-second clip was saved in Audio Video Interleave (AVI) format, fully anonymised through masking, and cropped to a square-shaped region around the ultrasound frustum, as shown in Figure 5.  
These anonymised LUS video clips were annotated by a qualified clinician using the VGG annotation tool [31]. During the annotation procedure, a label that is either B-line or non-B-line was assigned to each video clip. Then, the B-line frames in the B-line videos were annotated for the temporal localization task using the proposed temporal attention mechanism. Furthermore, the B-line regions were annotated using a straight line as shown in Figure 5 for the spatial localization task with our spatial attention mechanism. The  
Figure 5: Examples of B-line regions annotation used for spatial attention task. A straight yellow line was drawn on the B-line region extending from the surface of the lung distally following the direction of propagation of the sound waves.  
annotation outputs were saved in Java Script Object Notation (JSON): [[https://www.json.org/](https://www.json.org/)]([https://www.json.org/](https://www.json.org/)) (accessed on 1 December 2021) format to be used as ground truth.  
For training the model, we converted each four-second video clip into shorter clips of one second with 20% overlap between consecutive frames in the video. The overview of our LUS video dataset is presented in Table 2.
###### Abstract  
Quasi-zero stiffness (QZS) has become a promising way of realizing low-frequency vibration isolation, where magnetic springs have been widely adopted for constructing negative stiffness. However, existing single-layer magnetic springs often have a small-amplitude negative stiffness, so the loading capacity is low. In order to address this issue, this paper presents novel Halbach-cylinder magnetic springs (HCMSs) by using the Halbach array. Firstly, stiffness formulas of basic single-layer magnetic springs are analytically built based on the Amperian current model. The stiffness of the HCMS is derived from combining multiple single-layer magnetic springs. Then, nonlinear stiffness characteristics of both single-layer magnetic springs and HCMSs are investigated in terms of the amplitude, the uniformity, and the displacement range of negative stiffness. Analytical results show that HCMSs can generate negative stiffness with different equilibrium positions, and the amplitude of negative stiffness of HCMSs is much larger than that of single-layer magnetic springs. The amplitude of negative stiffness is in conflict with the uniformity, so a trade-off design is needed. In addition, increasing the number of layers of Halbach cylinders can be adopted to realize larger-amplitude and wider-range negative stiffness. This study will provide new insights into designing QZS with heavy-load capacity.  
Keywords:quasi-zero stiffness; heavy load; large-amplitude negative stiffness; magnetic spring; Halbach arrays; Halbach-cylinder magnetic spring Article
# A Method for Efficient Quality Control and Enhancement of Mobile Laser Scanning Data
## 2 Approaches to Modeling, Determining, and Mitigating Errors in MLS Point Clouds  
### Error Modelling  
In the early days of mobile laser scanning, much of the scientific work focused on the theory of the emerging technology. [PERSON]. [12] elaborated on the functional relationships and formulas of lasers, laser ranging, and airborne laser scanning. While the paper made assumptions and simplifications, it provided a thorough examination of the influencing factors. Ref. [13] modified the lidar equation (see Equation (8)) to introduce typical error values. The difference between an ideal and an error-contaminated system gives insight into the effects of the global positioning system (GPS), inertial measurement units (IMU), ranges, scan angle, mounting, and time biases. [PERSON]. [13] pointed out that the choice of flight pattern can help recover some errors directly. While [8] followed a similar strategy for introducing random errors, they differentiated the lidar equation with respect to eight potentially biased parameters: lever arm (three), boresight angles (three), laser range, and scan angle. Although the expressions derived were based on several assumptions, these expressions allowed them to study the optimal flight configuration. [PERSON]. [9] pursued a similar strategy with a different goal. His first-order error analysis incorporated six additional parameters, three each for position and attitude. By introducing typical error values from data sheets and experience values in the error formula, he estimated the 3D accuracy of the laser footprint of airborne and land-based MLS. This methodology can give a sense of the achievable accuracy and whether a hardware update will deliver the expected results. In addition to the investigations regarding positioning and calibration insufficiencies, [PERSON]. [14] also addressed the systematic effects of the scanning geometry. They derived a quality measure that depends on the normal of the terrain model and the laser beam direction.
_Article_  
**Comparative Life Cycle Assessment of Glucose**  
**Production from Maize Starch and Woody Biomass**  
**Residues as a Feedbackstock**  
**[PERSON]\({}^{\circledR}\), [PERSON]\({}^{\circledR}\), [PERSON]\({}^{\circledR}\), [PERSON] and [PERSON] *\({}^{\circledR}\)**  
Chemical & Environmental Engineering Group, Universidad Rey Juan Carlos, Tulipan s/n, 28933 Madrid, Spain; [PERSON]SS] (J.B.); [PERSON]S] (J.I.); [PERSON] ([PERSON]); [PERSON]ESS] (J.A.M.)  
* Correspondence: [EMAIL_ADDRESS]  
Received: 15 February 2020; Accepted: 21 April 2020; Published: 24 April 2020  
**Featured Application: Glucose is a key intermediate in many routes of biomass transformation to obtain valuable bio-products. The sustainability of glucose production is essential to improve the environmental profile of 'greener' bio-products. In this work, LCA methodology was used to determine the strengths and weaknesses of processes devoted to glucose production, starting from different types of biomass. Alternatives to reduce the environmental impacts of glucose generation are highlighted from our LCA results.**  
**Abstract:** The sustainability of glucose production from two different feedstocks, maize starch (MS) and woody biomass residues (WBR), was evaluated by means of life cycle assessment (LCA) methodology. The aim of this work was to compare the environmental performance of conventional technology (glucose from MS by enzymatic hydrolysis) with a novel alternative (glucose from WBR by a three-step process: pretreatment -crushing, deacetylation, and diluted-acid treatment-; conditioning -acid-alkali-acid treatment-; and enzymatic hydrolysis), which is specifically oriented towards the circular economy context. Life cycle inventory was completed by simulation of the different processes, followed by integration of the mass and energy inputs and outputs in an LCA software (GaBi 7.3). LCA results evidenced benefits in all the evaluated environmental impacts when using WBR as a glucose source alternative. Environmental damages associated with the starch production process, which involves more than 60% of the impacts calculated for glucose production from maize starch, has been detected as the key step in which focusing the improvement efforts for this process. On the other hand, pretreating of the biomass residues was the most contributing stage in the WBR process, principally due to the large heat and electricity requirements associated with this stage. Finally, we concluded that the WBR process proposed here might be considered as a valuable alternative in sustainability terms for the production of glucose within the biorefinery concept. Likewise, we have identified the critical points that should be considered to further improve this technology.  
**Keywords:** bio-refinery; sustainability; glucose production; LCA; woody biomass residues
# CQFormer: Cyclic Quasi-Dynamic Transformers for Hourly Origin-Destination Estimation
## 5 Experiments
### Results and Discussion
#### 5.4.4 Result Analysis
As can be seen in Figure 8, CQDFormer and MLP basically capture complete traffic demand structures in the real data set. This is one of the main reasons why they can outperform other baselines and achieve minimal dispersion in Figure 7. However, MLP has relatively poor performance in capturing low-density traffic structures due to the distribution shift. In contrast, as observed in Figure 8e, cyclic consistency improves the coverage of the estimation with respect to the low-density clusters, but since the GAN focuses more on capturing the distribution of the data rather than the exact OD values, making the OD matrices generated by CycleGAN discrete and not precise enough. CQDFormer introduces cyclic consistency along with the use of a prior matrices to anchor the demand structures, and realizes the accurate mapping from a specific spatio-temporal evolutionary pattern to the corresponding demand structure through the self-attention mechanism. The above results and discussion demonstrate the competence of the proposed model in the OD estimation problem in complex urban environment. Figure 7: Comparison of real and estimated OD flows.
# Quantum Perspective on Digital Money: Towards a Quantum-Powered Financial System
## 2 Defining Quantum Money and Quantum Wallets
### Creation of Quantum Money  
To create quantum money, various physical systems can be used for encoding specific quantum states [13; 14; 15]. For instance, atoms or ions could serve as the \"carriers\" of quantum money, with their energy levels encoding unique patterns that represent different values. Imagine a single atom of rubidium or calcium, where its specific quantum properties, such as spin or energy states, can be carefully adjusted in a lab to create an identifiable and secure \"signature\" that represents a set amount of money. This atomic state could then be stored and verified using sophisticated quantum devices.  
Another possibility involves using photons, the fundamental particles of light, which can be encoded with specific polarization or time-bin states [16]. These photons could represent quantum money in a secure way because their quantum state is highly sensitive to any attempt at measurement, immediately flagging any interference. For instance, the horizontal or vertical polarization of a photon might encode different monetary values, and these photons could be stored in special quantum memories or transmitted over secure quantum communication channels.  
Larger structures like molecules could also encode quantum money, with each molecule's specific quantum configuration acting as a unique and unforgeable marker. Certain molecules could be designed to have stable quantum states within their electron configurations, creating a \"molecular signature\" that is resistant to tampering. These molecules would be stored in quantum-stable environments to protect the encoded value over time.  
In essence, quantum money could be implemented by highly sensitive and complex quantum states--whether in atoms, photons, or molecules--as secure carriers of value, making it possible to create a currency that is nearly impossible to replicate without detection.
# PSDFH: A Phase-Space-Based Depth from Hologram Extraction Method
## 2 Related Works
### Phase-Space-Based Methods  
One of the pioneer works on the extraction of depth information directly from a hologram without any numerical reconstruction was published in [3]. The proposed method is based on [PERSON]'s analysis of a 1D cross section of 2D in-line holograms. Each particle that was used to record the hologram is represented by a cross-shaped pair of line impulses in [PERSON]'s analysis of the hologram. The authors showed analytically that if one of the two straight lines slopes is known, the distance between the particle and the hologram plane can be obtained. The experiments were conducted using several holograms with a varying number from one to three particles that are spaced far enough. The obtained results confirmed the analytical formula and showed that the proposed approach can be used to obtain an accurate estimate of the particle depth.  
[PERSON] et al. [9] extended the previous work by replacing the Wigner-Ville distribution by the Cohen bilinear class with fixed kernels given by analytical expressions in order to improve the precision in the case of multiple particles. The proposed method was compared to a scaling of the chirp transformation [10] and showed better results in terms of automation of the algorithm and a better visual interpretation of the obtained results.  
In the same spirit, [PERSON] et al. [11] used the Gabor transform to extract the depth information of small particles from in-line holograms by using the analytical relation between the Gabor angle and the object distance from the CCD camera. The experiments were performed on a 1D cross section of a 2D in-line hologram of three particles located at the same depth. The 1D cross section was analyzed using the Gabor transform, and the Gabor angle was calculated manually in order to obtain a depth estimate. The estimated depth is very close to the ground truth with an approximation error of 3 \(\upmu\)m. The authors pointed out that the estimation error may be due to the high signal-to-noise ratio caused by the acquisition conditions.  
Other applications based on the phase space transform are discussed in [12].
## 3 Results
\begin{table}
\begin{tabular}{c c c c c c} \hline
**Time Point** & **Group** & **Na\({}_{\textbf{v}}\) (mM)** & **K\({}_{\textbf{v}}\) (mM)** & **HCT (\%)** & **Hb (g/dL)** \\ \hline \multirow{2}{*}{Rest} & N & \(140.5\pm 1.6\) & 3.96 \(\pm\) 0.24 & 44.2 \(\pm\) 2.2 & 15.9 \(\pm\) 1.2 \\  & P & \(140.3\pm 1.2\) & 4.14 \(\pm\) 0.21 & 44.0 \(\pm\) 3.4 & 15.2 \(\pm\) 0.9 \\ \hline \multirow{2}{*}{Warm-up} & N & \(142.2\pm 1.5\) & 4.45 \(\pm\) 0.28 & 45.1 \(\pm\) 2.5 & 16.4 \(\pm\) 1.2 \\  & P & \(141.8\pm 1.2\) & 4.54 \(\pm\) 0.25 & 44.7 \(\pm\) 3.1 & 15.5 \(\pm\) 1.0 \\ \hline \multirow{2}{*}{5 th interval} & N & \(142.7\pm 1.5\) & 4.41 \(\pm\) 0.16 & 45.4 \(\pm\) 2.5 & 16.5 \(\pm\) 1.1 \\  & P & \(142.0\pm 1.1\) & 4.56 \(\pm\) 0.23 & 45.0 \(\pm\) 3.1 & 15.6 \(\pm\) 1.0 \\ \hline \multirow{2}{*}{20 th interval} & N & \(142.9\pm 1.3\) & 4.49 \(\pm\) 0.21 & 45.7 \(\pm\) 2.5 & 16.6 \(\pm\) 1.0 \\  & P & \(142.2\pm 0.8\) & 4.62 \(\pm\) 0.23 & 45.6 \(\pm\) 3.2 & 15.6 \(\pm\) 1.0 \\ \hline \multirow{2}{*}{35 th interval} & N & \(143.3\pm 1.3\) & 4.56 \(\pm\) 0.16 & 45.8 \(\pm\) 2.4 & 16.7 \(\pm\) 1.1 \\  & P & \(142.4\pm 0.8\) & 4.71 \(\pm\) 0.28 & 45.4 \(\pm\) 3.5 & 15.7 \(\pm\) 1.0 \\ \hline \multirow{2}{*}{45 th interval} & N & \(143.4\pm 1.6\) & 4.63 \(\pm\) 0.25 & 45.8 \(\pm\) 2.4 & 16.7 \(\pm\) 1.1 \\  & P & \(142.8\pm 0.7\) & 4.80 \(\pm\) 0.32 & 45.2 \(\pm\) 3.6 & 15.7 \(\pm\) 1.1 \\ \hline \multirow{2}{*}{Cool-down} & N & \(142.9\pm 1.9\) & 4.88 \(\pm\) 0.22 & 45.1 \(\pm\) 2.4 & 16.6 \(\pm\) 1.1 \\  & P & \(142.4\pm 0.8\) & 5.06 \(\pm\) 0.36 & 44.8 \(\pm\) 3.7 & 15.7 \(\pm\) 1.1 \\ \hline \end{tabular} Na\({}_{v}\) = venous sodium concentration; K\({}_{\textbf{v}}\) = venous potassium concentration; HCT = hematocrit; Hb = venous hemoglobin concentration; no significant differences between the groups.  
\end{table} 
Table 4: Summary of sodium, potassium, hematocrit, and hemoglobin in the nitrate group (N) and in the placebo group (P) at the indicated time points. Since no differences in CRN, XA, and UA concentrations were found, correlations were calculated for the whole group (n = 17). Plasma CRN concentrations correlated positively with XA (\(p\) = 0.035; r = 0.195) and UA (\(p\) < 0.001; r = 0.357) at all time points. A correlation was also found between UA and XA (\(p\) = 0.018; r = 0.219). To characterize lipid metabolism, plasma concentrations of FFA, Glyc, and TG were measured, in addition to RER (Table 5). During TR, FFA (\(p\) = 0.497) and Glyc (\(p\) = 0.486) did not differ between the supplementation and placebo groups, but both increased significantly during the interval phase (\(p\) < 0.001). Significant main effects were found for TG concentration (group: \(p\) = 0.010; time: \(p\) = 0.032). Post hoc tests revealed significant differences for TG between N and P at six of the seven time points (5'IT: \(p\) = 0.051; others: \(p\) \(\leq\) 0.029). There was a significant difference between TG at the end of warm-up and at the end of cool-down (\(p\) = 0.002). No group\(\times\)time interactions were found for the lipid metabolites (FFA: \(p\) = 0.881; Glyc: \(p\) = 0.810; TG: \(p\) = 0.416).
## 5 Methods and Algorithms
### Infill Strategy Weighting
This is done under the assumption that two TCP poses adjacent in Cartesian space belong to the same robot configuration exactly when a direct move from one TCP pose to another causes a minimal movement in joint space. This procedure covers the maximum movement of the robot required for a zigzag infill pattern and ensures that the individual poses are as close to each other as possible and result in as minimal movement of the robot as possible. The set of different robot poses is next analyzed to calculate the reachability component \(g_{reachability}\) (see Formula (2)), if all tested characteristic poses have at least one valid solution. For each robot joint \(i\), the maximum motion range \(\Delta\varphi_{i}\) in order to reach all characteristic poses is determined first. A linear function is then used to interpolate proportionally between the minimum (\(\Delta\varphi_{i}=0\)) and maximum (\(\Delta\varphi_{i}=\Delta\varphi_{lim}\)) motion (see Figure 16a). To get the complete reachability weight of a polygon, all joint specific weights \(g_{reach,i}\) are summed up. For the second part of the infill weight the geometric properties \(g_{geometry}\) of the polygon relative to the infill main orientation are analyzed. The maximum length of the polygon along the main direction \(\delta_{length}\), as well as the maximum width perpendicular to the infill main direction \(\delta_{width}\) can be calculated. The ratio \(r_{geometry}=\delta_{width}/\delta_{length}\) determines whether many small zigzag movements are necessary to fill the area (\(r_{geometry}<1\)), or the path consists of fewer long segments (\(r_{geometry}>1\)). A quadratic function depending on a specified critical ratio \(r_{crit}\) is used to determine a scalar ge  
Figure 14: (**a**) Coverage graph with 4 nodes connected by 3 edges and (**b**) weighted infill graph of the example slice with 82 nodes and 544 edges. Figure 15: Inverse kinematics test-poses for a convex sub-polygon. minimum and maximum weight limits (see Figure 16b). In addition, it is also checked at this point whether the analyzed slice allows the planning of a valid path at all. If, for example, the calculated width \(\delta_{width}\) of the polygon perpendicular to the main infill direction is smaller than twice the expected path width of the welding process, no zigzag-shaped path can be generated at all. By adjusting the limit intervals of the reachability or geometry weight and modifying the interpolation functions, it is possible-after extensive software tests and welding process analysis which are still to be done--to adjust the individual magnitude of the components.