esa-sceva/satcom-chunk-collection huggingface dataset:
# RotJoint-Based Action Analyzer: A Robust Pose Comparison Pipeline
## 3 Benchmark
### Ambiguity Pose Definition  
**Viewpoint ambiguity:** Variations in camera viewpoints can distort action recognition in 2D pose estimation. Movements may appear similar when projected onto a 2D plane, especially from side views, making it difficult to distinguish forward and backward actions, such as forward and backward kicks.  
**Shape ambiguity:** Differences in human body shapes, such as limb lengths and body proportions, can cause variations in skeletal angles for identical movements. This leads to ambiguity in pose comparisons, as actions may be interpreted differently based on an individual's anatomy.  
**Torsional ambiguity:** Rotational changes in joints (e.g., torso or wrist rotations) are difficult to perceive and are often overlooked by skeletal-based methods. This results in ambiguity when comparing poses with torsional movements.  
Thus, we propose three tasks to evaluate pose recognition: Invariance to body shape variations, invariance to viewpoint changes, and sensitivity to twisting variations in limb movements. These tasks are assessed through three sub-benchmarks: the Shape-Variations Set, which compares pose pairs with different body shapes; the Viewpoint-Variations Set, which compares pose pairs from different viewpoints; and the Torsional-Pose Set, which tests the ability to distinguish torsional variations in limb movements rather than just limb movement types.
## 2 Materials and Methods
### Structural Design and Motion Analysis of Cutting Device
#### 2.2.2 Motion Analysis of the Cutting Device
The displacement \(S_{x}\), velocity \(v_{x}\), and acceleration \(a_{x}\) at any point on the blade of the cutter can be converted to variable values according to the equal proportions of the lengths of the upper and lower segments of the pendulum rod, respectively:  
\[S_{x}=-\frac{rL_{2}}{L_{1}}\cos\omega t \tag{2}\]  
Figure 5: Schematic representation of the crank linkage mechanism: (**a**) Schematic diagram of mechanism motion (crank in an arbitrary position); (**b**) Cutting device from extreme left to extreme right operation diagram. \[v_{x}=\frac{rL_{2}\omega}{L_{1}}\text{sin}\,\omega t \tag{3}\]  
\[\alpha_{x}=\frac{rL_{2}\omega^{2}}{L_{1}}\text{cos}\,\omega t \tag{4}\]  
where \(r\) represents the crank length (mm), \(L_{1}\) denotes the length of the upper section of the pendulum rod (\(L_{1}\) = 205 mm), \(L_{2}\) is the length of the lower section of the pendulum rod (\(L_{2}\) = 170 mm), \(\omega\) represents the rotational angular velocity of the crank (rad/s), and \(t\) is the crank from the extreme left point of the time of rotation (s). Since the speed of movement of the cutter is variable, the average speed (\(v_{p}\)) is generally utilized to express the cutting speed of the cutter:  
\[v_{p}=\frac{S}{T}=\frac{nrL_{2}}{L_{1}\times 15} \tag{5}\]  
in which \(v_{p}\) represents the average cutting speed of the cutter (mm/s), \(S\) denotes the cutting stroke (the distance traveled when moving from the extreme left position to the extreme right position, or vice versa in mm), \(T\) stands for the time taken by the cutter to move one cutting stroke (s), and, finally, \(n\) signifies the crank rotation speed (r/min). In addition, since the cutting method belongs to unsupported cutting, it is crucial to reduce the bending deformation of the GLVs root during the cutting process. This will help to prevent issues such as GLVs being pushed, cut diagonally, or cut without breaking such as when the cutting stroke of the cutter is too large. To achieve this, the crank length is initially determined based on the physical parameters of GLVs and the experience of previous studies. Then, the maximum distance of unidirectional movement of point O at the end of the connecting rod \(L\) would be \(S_{r}=2r=40\) mm, and the cutting stroke of the cutter is calculated as \(S=\frac{S_{r}\times L_{2}}{L_{1}}=33.17\) mm. To guarantee that the GLVs are cut off at the instant of the unsupported cutting of the root, the cutting speed should not be too low, so, based on the previous experimental research, the preliminary design of the crank is performed for the rotation speed of 600 r/min.
## 4 Numerical Examples  
### Simply Supported Square Plate Subjected to Uniform Load  
A simply supported square plate subjected to a uniform load \(q\) is tested to show the reliability and convergence of the present elements. The side length of the plate is \(L\), and the thickness of the plate is \(h\). A quarter of the plate is modeled as a result of symmetry, as illustrated in Figure 10. For the isotropic plates, the in-plane displacements \((u_{0},v_{0})\) and their DOFs in Equations (1), (2), and (5) are neglected in the following analyses. The displacement boundary conditions of the present theory along the simply supported edges in local coordinates are \(\overline{\theta}_{s}=0\) and \(w=0\). The \(n\times n\) regular mesh and irregular mesh illustrated in Figures 11 and 12 are employed for convergence studies. Figure 8: Minor movement for the implementation of VCCT. Figure 7: Triangular elements for a cracked plate. Figure 9: Calculating SIFs by VCCT. The elements DST-BL (Discrete Mindlin triangular plate element) [7] and RDKTM (Re-constituting discrete Kirchhoff triangular plate element) [14] have been selected for comparison with the present elements based on HSDTs. The reference solutions in the following Tables 1-6 are taken from [PERSON] et al. [67], which are also labeled as analytical solutions in [67]. Table 1 lists the normalized defection \(W_{0}=W_{c}/\frac{q\,\mathrm{\mu}^{4}L}{100\mathrm{\Omega}\mathrm{\Omega}}\) of the simply supported square plate, where \(W_{c}\) is the central deflection of the plate and \(D_{b}=\frac{Eh^{3}}{12(1-v^{2})}\). Table 2 reports the normalized bending moment \(M_{0}=M_{c}/\frac{q\,\mathrm{\mu}^{2}}{10}\) of the simply supported square plate, where \(M_{c}\) is the central bending moment of the plate. The convergence of the deflection for the simply supported square plate using different elements when the aspect ratio \(h/L=0.1\) is shown in Figure 13. It is observed that all the present TrSDTPE, F5 BDTPE, and FiSDTPE shows a good convergence rate and high accuracy, and avoids the shear-locking problem. The results  
Figure 11: Regular 16 \(\times\) 16 mesh for the square plate. Figure 10: A quarter model of the square plate. The width-to-length ratio \(d/l\) of the fictitious thin layer \(e_{l}\) plays an important role in the present formulations. Table 3 reports the effect of the ratio \(d/l\) on the normalized defection \(W_{0}\) for the simply supported square plate, where \(16\times 16\) regular mesh and an aspect ratio of \(h/L=0.1\) are employed. The results in Table 3 indicate that the artificial parameter \(d/l\) has little effect on the solution accuracy when \(d/l\leq 0.001\), and it is easy to select a reasonable \(d\) in the current formulation. In this work, width \(d\) is taken as \(d=0.0001l\). The condition numbers of the global stiffness matrices of the simply supported square plate using the present elements are also computed and reported in Figure 14. As seen, the variation of the condition number in Figure 14 reflects that the present elements show a good conditioning and stability in the case of mesh refinement.
## 6 Conclusions  
In this paper, the implementation of the NPDSCH receiver chain and the NPUSCH transmitter chain is presented starting from the algorithm design and passing through the hardware implementation, MATLAB and RTL simulations, and synthesis for each block in the chain. Then, the chain integration is performed, and then MATLAB and RTL are simulated and tested on FPGA Virtex 7. The chain meets all 3 GPP NB-IoT LTE standard Release 14 (Rel-14) specifications, and it has a maximum rate of 98.666 Kbps. This rate is calculated according to some assumptions, TBS = 296, including pilots, and coding 1/3, then taking three subframes with respect to the upper layer; therefore, Max Rate = 296/3 ms = 98.666 Kbps and a latency of 1.45 ms. Furthermore, the implementation of the NB-IoT system, comprising two UEs and an implemented NB-IoT base station, is successful, as data sent from one UE to another through the base station are correctly received. As the base station is modeled on MATLAB, the NPUSCH base station receiver receives the data from the FPGA (UE 1), and it passes them to be sent again through the NPDSCH base station transmitter to be received on the receiving FPGA (UE 2). The USRP is used in this model to be the RF part of our system. This model tests the Tx and Rx chains to send different TBSs. The future work is to share more memory resources across the chain, implement soft demodulation and soft decoding to enhance performance, and optimize on the block level, in turn, reducing area and power.  
Data curation, A.A. and R.M.T.; Formal analysis, A.A. and R.M.T.; Methodology, R.M.T., M.S.D. and H.M.; Project administration, H.M.; Supervision, M.S.D. and H.M.; Validation, A.A. and R.M.T.; Visualization, A.A. and R.M.T.; Writing--original draft, A.A., R.M.T. and M.S.D.; Writing--review & editing, M.S.D. and H.M. All authors have read and agreed to the published version of the manuscript.  
This research is supported by Science, Technology, and Innovation Funding Authority (STIFA), Egypt, under grant No. 34876, [PERSON] received the grant.  
This study did not report any data.  
The authors would like to thank the Opto-Nano-Electronics laboratory (ONE Lab.), Cairo University, and Science, Technology, and Innovation Funding Authority (STIFA), Egypt. The authors declare no conflict of interest.  
Figure 24: Receiving data on the second UE (UE2).
## 5 Innovative Approaches for Enzyme Immobilization
### Self-Healing Hydrogels for Enzyme Immobilization  
Hydrogels are 3D porous networks with high water absorption capacity due to their hydrophilic groups [189], making them ideal for enzymes in non-aqueous media [190]. For instance, enzyme can be encapsulated or covalently bound to polymers (e.g., cellulose, agarose, and dextran) via functional groups (e.g., amino, aldehyde, carboxyl, and epoxy), preventing leaching [191].  
Hydrogels can be natural (hyaluronic acid, chitosan, heparin, alginate, gelatin) or synthetic; the natural hydrogels are biocompatible and biodegradable, and enhance tissue regeneration, but they lack the stability and strength of synthetic (PVA, polyethylene glycol, and sodium polyacrylate) types. Natural hydrogels are biocompatible and biodegradable but mechanically weaker, while synthetic variants offer greater rigidity and stability [192].  
Hydrophilic polymers often expand in aqueous environments, leading to poor rigidity and enzyme leaching [114]. Cross-linkers like polyethylene glycol diacrylate (PEGDA) can mitigate these issues by forming highly cross-linked hydrogel networks under mild conditions, without requiring heat or solvents. High water content is beneficial for enzyme activity, but often leads to enzyme leakage, which can be reduced through co-polymerization with hydrophobic or covalent monomers [190].  
Biobased hydrogels enhance enzyme immobilization, improving stability, reusability and catalytic activity. For example, sodium alginate grafted with acrylamide and glycolyl methacrylate immobilizes PersiXyn9 [193], while agarose-chitosan hydrogel cross-linked with N-hydroxy-succinimide (NHS) stabilizes horseradish peroxidase (HRP), doubling its activity [194]. Similarly, lactose [195] and alcohol dehydrogenase [196] show enhanced pollutant bioconversion and stability when immobilized on cross-linked hydrogels. Notably, SOD-coupled ferrocene in a PEGDA hydrogel enables precise tumor cell detection, with high stability and selectivity, in the monitoring of inflammatory byproducts [197]. Table 2 summarize the hydrogel-immobilized enzyme's improved activities and applications.
## 2 Materials and Methods  
### Study Design and Eligibility Criteria  
The Ethics Committee at the Faculty of Dentistry, Tokyo Medical and Dental University, reviewed and approved the study protocol (Number 693) for a long-term, randomized, unblinded clinical trial. Comprehensive information about the study, both written and verbal, was provided to each participant, who then signed informed consent forms. The study's specifics and the preliminary outcomes (12-month patient satisfaction) have already been published [21]. This study adheres to the guidelines outlined in the 2010 Consolidated Standards of Reporting Trials (CONSORT) statement [22].  
In brief, participants had to adhere to the following criteria to be involved: (1) complete edentulism in the mandible and any maxillary condition, (2) sufficient bone volume in the anterior mandible for the placement of two implants with a minimum dimension of 4.0 \(\times\) 10.0 mm, (3) no requirement to bone augmentation, (4) willingness to wait at least four months for healing post-extraction, (5) good oral hygiene, and (6) possession of a sufficient command of written and spoken Japanese to respond to the questionnaires. Patients were not eligible if they had (1) uncontrolled systemic diseases that might compromise implant surgery; (2) experienced head and neck radiotherapy or chemotherapy; (3) a history of heavy smoking; (4) previously taken bisphosphonates.  
A sample size of 10 participants per group was chosen for the preliminary investigation [21] and this 5-year follow-up report, as no previous studies had compared the patient-reported results of immediate and conventional loading protocols utilizing magnetic attachments. Initially, a total of 23 patients were recruited; however, 4 were omitted as they either refused to participate (\(n=2\)) or did not meet inclusion criteria (\(n=2\)). Hence, nineteen subjects were randomly allocated to one of the two treatment groups: the immediate loading group and the conventional loading group. The allocation was performed using the minimization method to assure pretreatment comparability of the groups about age, gender, and American College of Prosthodontists (ACP) classification [23]. During the first year of observation, one patient in the conventional loading group was lost before the follow-up due to implant failure.
## 3 Methodology
### Setup of the Simulation  
For this work, the process illustrated in Figure 8 was used to simulate detection experiments under adverse weather situations. The foundation of this process is the virtual environment Carla [39], which simulates road traffic scenes. In this environment, any of the common ADAS sensors and their outputs can be simulated by adding them to a primary vehicle, hence the technical expression ego vehicle. Additionally, other road users such as cars, bicycles, and pedestrians and the environmental conditions can be controlled and dynamically simulated. The ego vehicle can either move within the simulation automatically or can be static. For this work, a Valeo lidar system was simulated, based on publicly available information. The system scans the environment via raycasting, which yields a semantic point cloud, where additional information is also generated for each point. Besides the XYZ coordinate, also the incidence angle on the surface, type of object, and, if available, the object ID is annotated. This semantic point cloud gets periodically published as a ROS2 topic [40]. Within ROS2, the reflected intensity of each point will be calculated in real time based on the weather-related extinction coefficient \(\alpha\), the incidence angle, and the reflection characteristic of the object. In the next step, noise is added based on the backscattering coefficient \(\beta\). To generate a realistic point cloud, the actual extinction and backscattering coefficient of the current weather must be known. The calculation of these coefficients by empirical models will be discussed in the following section. This newly constructed point cloud also contains the semantic information and is published as a ROS2 topic. Finally, the sensor efficiency will be evaluated. Every point in the cloud with a calculated intensity below a sensor-specific threshold will be discarded from the point cloud. This filtered point cloud can then be used to perform detection experiments. For the detection experiment, a target car will be placed in front of the ego car at a defined distance. In Carla, different weather scenarios will be generated, and the points that are related to the target car will be counted in the semantic-filtered point cloud. By increasing the extinction coefficient, the amount of points should start to decrease significantly above a certain extinction coefficient threshold.
## 4 Computational Experiments
### Computational Results  
The computational results are presented in Tables 5 and 6. For each of the two testsets, we report:  
* the name of the test instance,
* the objective value \(z_{0}\) in minutes of the NNP solution,
* the objective value \(z_{1}\) in minutes of the ML-NNP solution,
* the percentage of improvement \(DEV\) of \(z_{1}\) with respect to \(z_{0}\).  
In our implementations, the maximum running time of both algorithms is only a few seconds or even a fraction of a second. Therefore we prefer not to report these figures. As shown in Tables 5 and 6,  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Zone** & **Mean Error** & **Mean Absolute Error** & **Standard Error** \\ \hline
1 & \(-\)1.02 & 18.55 & 23.74 \\
2 & 2.40 & 15.29 & 20.14 \\
3 & 0.74 & 19.69 & 24.30 \\
4 & \(-\)2.78 & 28.85 & 36.53 \\
5 & 5.53 & 44.65 & 52.49 \\
6 & 1.33 & 24.00 & 29.55 \\ \hline
**Average** & 1.03 & 25.17 & 31.13 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Mean errors in the Paris instances.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Instance** & \(\mathbf{z_{0}}\) & \(\mathbf{z_{1}}\) & \(DEV\%\) & **Instance** & \(\mathbf{z_{0}}\) & \(\mathbf{z_{1}}\) & \(DEV\%\) \\ \hline
10\_L1 & 406.13 & 406.13 & 0.00 & 10\_L10 & 484.56 & 447.78 & 7.59 \\ \hline
10\_L11 & 449.64 & 449.64 &
## 7 Conclusions  
Cooperative communication is one of the best solutions to overcome the multipath fading and provides diversity gain. In this research work, an experimental testbed comprised of USRP and LabVIEW is used to build a cooperative network SDR platform. Extensive experiments are carried out for capacity gain of CC over DC in lab environment. Experimental performance analysis shows that CC significantly improves the performance of the system than DC. Experimental analysis shows an increase in the transmit antenna gain results in improving the SNR at receiver. High SNR provides more channel capacity by using higher order PSK modulation. The performance of CC significantly increases the system reliability and the channel capacity of the system with and without obstacle environment. It is also analyzed that channel capacity increases by placing the relay at center between source and destination.
# Modeling Transient Flows in Heterogeneous Layered Porous Media Using the Space-Time Trefftz Method
## 2 The Methodology
### The Continuity Conditions of the Interface  
To model transient flows in heterogeneous layered porous media, the domain decomposition method (DDM) was utilized [35]. The continuity of the head and the flux conservation at the interface between two layered porous media were considered.  
By solving Equation (12), we can obtain two sets of unknown coefficients, \(\epsilon_{\Omega_{1}}\) and \(\epsilon_{\Omega_{2}}\), for subdomains \(\Omega_{1}\) and \(\Omega_{2}\), respectively. The computed head at the inner points can then be computed by Equation (5), utilizing \(\mathbf{A}_{\Omega_{1}}\) and \(\mathbf{B}_{\Omega_{1}}\) for \(\Omega_{1}\), and \(\mathbf{A}_{\Omega_{2}}\) and \(\mathbf{B}_{\Omega_{2}}\) for \(\Omega_{2}\). In this study, the commercial program MATLAB backslash operator was utilized to solve Equation (12). The schematic diagram for modeling the transient flows in the heterogeneous layered porous media is displayed in Figure 2.  
The continuity conditions at the interface of the subdomains are satisfied in terms of the DDM, such that the proposed method is capable of dealing with transient flows in heterogeneous layered porous media. Numerical solutions are approximated based on the superposition theorem using the space-time basis functions of the governing equation. Using the space-time collocation scheme, the numerical solutions of the problem are solved with boundary and initial data assigned on the space-time boundaries, as shown in Figure 1b. The spatial and temporal discretizations are then combined in the space-time  
Figure 1: Collocation points on the (**a**) space domain and (**b**) space–time domain.  
domain. Accordingly, the transient flows through the heterogeneous layered porous media in the space-time domain can be solved without using the time-marching scheme.
# Folding Every Point on a Polygon Boundary to a Point
## 2 Preliminaries
### Many Parabolas  
In this section, we analyze the structure of the intersection of \(k\) semi-confocal parabolas, extending the result from the previous section.  
Let \(p_{1},p_{2},\ldots,p_{k}\) be \(k\) semi-confocal parabolas with different directional angles. We shall consider the safe region of these parabolas and prove the following lemma.  
**Lemma 3**: _Each parabola touches at most one arc of the safe region._  
Figure 5: Arc decomposition of a parabola.  
Proof.: We prove by induction on \(k\) for the case where \(k=2\) follows from Lemma 2. Consider \(k\) parabolas. Let \(R^{\prime}=\bigcap_{i=1}^{k-1}H(p_{i})\). Inductively, each parabola \(p_{1},p_{2},\ldots,p_{k-1}\) touches at most one arc of \(R^{\prime}\). We consider \(R=R^{\prime}\cap H(p_{k})\), we shall show that \(p_{k}\) only touches at most one arc of \(R\). If \(R^{\prime}\subseteq H(p_{k})\), then \(R=R^{\prime}\) and \(p_{k}\) does not touch \(R\); hence, the lemma is true. We then assume that \(R^{\prime}\
ot\subseteq H(p_{k})\).  
Clearly, \(p_{k}\) touches one arc of \(R=R^{\prime}\cap H(p_{k})\). We call that arc \(a_{k}\). Each endpoint of \(a_{k}\) belongs to some arc of \(R^{\prime}\).  
There are two cases.  
_Case 1_: Both endpoints of \(a_{k}\) belongs to a single arc of \(p_{i}\). In this case, \(p_{k}\) intersects exactly one arc of \(R^{\prime}\) exactly twice. Then, the safe region \(R\) is the intersection of exactly two parabolas, i.e., \(R=H(p_{i})\cap H(p_{k})\). Thus, the lemma follows from Lemma 2.  
_Case 2_: One endpoint of \(a_{k}\) belongs to \(p_{i}\) while the other belongs to \(p_{j}\). We show that in this case, \(p_{k}\) intersects exactly two arcs, implying the lemma. We consider \(p_{i}\) first, i.e., we look at the intersection \(R_{i}=H(p_{k})\cap H(p_{i})\). Let \(q_{i}\) be the intersecting point of \(p_{i}\) and \(p_{k}\). We can partition \(p_{k}\) into three arcs; let \(b_{k}\) be the unbounded arc starting at \(q_{i}\). From Lemma 2, we know that \(b_{k}\) only intersects \(R_{i}\) once. Since \(R\subseteq R_{i}\), we have that \(b_{k}\) also intersects \(R\) at most once at \(q_{i}\). We follow the same argument for \(p_{j}\). Thus, \(p_{k}\) only intersects \(R^{\prime}\) exactly twice, as claimed.