esa-sceva/satcom-chunk-collection huggingface dataset:
# Application of Riemannian Seismic Ray Path Tracing in Salt Dome Prospecting
## 5 Discussion  
### Assessment of the Ray Tracing in the Previous Geophysical Setups  
#### 5.1.1 Two Different Homogeneous Strata Separated at \(z=2500\) km  
Although this is a very simple example, it serves to exemplify both the usage of this method as well as its accuracy. Firstly, it is important to note, from Figure 1, that within the sections of constant P-wave speed (red or blue regions), this formalism reproduce the straight lines which are expected within this kind of media.  
According to the velocity model shown in Section 4.1, the diffraction indexes for both regions are \(n_{1}=0.0679755\) and \(n_{2}=0.189078\). On the other side, the refraction angles are \(\alpha_{1}=50.19^{\circ}\) and \(\alpha_{2}=16.02^{\circ}\). With such values, it is straightforward to verify that [PERSON]'s law (law of refraction),  
\[n_{1}\sin(\alpha_{1})=n_{2}\sin(\alpha_{2})\, \tag{27}\]  
is fully satisfied.  
On the other side, for the reflection process, it can be observed that the obtained reflection angle is given by \(\beta=50.19^{\circ}\), which is consistent with the laws of reflection.
## 4 Implementation
### System Architecture
Along with these, the integer value 0 for \"false\" and 1 for \"true\" corresponding to the threshold set for the number of inliers is also passed from _cameraPoseEstimation_ after homography refinement. If the condition is true during a sequence of 2 frames, the minimum number of inliers has been detected by RANSAC and the 3D model is visualized. Otherwise, the pattern object cannot be recognized, the 3D model is hidden from the scene and returns the visibility state to the _onRender_ function to update pose tracking. Tracking the same inliers in a set of frames reduces the flickeringeffect during visualization due to occlusion, motion blur, or oven, camera noise. In this way, the model continues to be displayed for at least a number of 2 frames. When the condition is true, a flag enables instancing the _onDrawFrame_ function and the _ModelViewProjection_ matrices are recalculated. The ModelView matrix of the model is updated with the pose values and visualization takes place. The 3D rendering thread is initialized when the instance of the 3D graphics engine is associated with the application layer. The _mRenderer_ activity constructs a new renderer for the _SurfaceCameraView_. The _onSurfaceCreated_ class enables depth testing and culling to remove non-visible back faces while _onSurfaceChanged_ adjusts the viewport based on  
Figure 2: Activity diagram illustrating the main processes performed by the ModAR prototype. geometry changes and calculates the frustrum. Then, the shader type and the framebuffer of 3D engine along with the methods _mClear_ and _mDraw_ are defined. After performing these internal initializations, the graphics engine invokes the method _initScene_, with the essential for the rendering of the scene objects. All the necessary functionalities for loading the files and configuring the camera are provided by the _ObjParser_, _ObjLoader_, _mTexture-Compression_, _Camera_ and _Math3D_ classes of the 3D engine. Then, the ModelView arrays are instantiated, in addition to the basic lighting for viewing the scene. In the _JavaCameraView_ class, three main operations are executed: (i) getProjectionMat estimates the camera every time the camera is initialized or reconfigured and the _mRenderer_ class is notified through the _onProjectionChanged_ method to update the _CamProjMat_ variable with the new matrix; (ii) _getIntrinsicParam_ sets the intrinsic camera matrix and translates it into a projection matrix; and (iii) _onCameraFrame_ gets and stores every frame in order to be sent to _CameraPoseEstimation_. The _AndroidCameraView_ class captures the frame to be used as pattern image and converts it from bitmap to Mat in order to be passed to _processPatternImage_. Finally, the _MainARActivity_ checks for runtime camera permission and library dependencies, holds the views and sets their order and enables the _PoseTracking_ function execution.
## 3 Therapeutics in HCC
### Anti-Angiogenic Therapies  
The anti-angiogenic class includes the following:  
* Multi-tyrosine kinase inhibitors (mTKIs). Tyrosine kinases are involved in the activation of a wide range of proteins by phosphorylation. TKIs bind to the active site of tyrosine kinases, preventing phosphorylation and inhibiting downstream signal transduction of a range of growth factors, including the vascular endothelial growth factor receptor (VEGFR) [105]. Therefore, this class includes VEGF receptor inhibitors like sorafenib, lenvatinib, cabozantinib, and regorafenib. Atezolimamb plus bevacizumab (atezo + bev) or durvalumab plus tremelimumab (durva + treme) are recommended as first-line treatments. However, when contraindications to atezo + bev or durva + treme are present, sorafenib, lenvatinib, or durvalumab may be considered as alternative first-line options. Following first-line treatment with sorafenib or lenvatinib, second-line therapy options include cabozantinib or regorafenib [106].
* Monoclonal anti-angiogenic antibodies: Bevacizumab targets vascular endothelial growth factor (VEGF), a family of soluble proteins that regulate angiogenesis in blood and lymphatic vessels. VEGF-A is considered the main pro-angiogenic factor in human malignancies, including HCC [83].  
For unresectable advanced HCC, mTKIs such as sorafenib, regorafenib, and lenvatinib have been used. However, the therapeutic efficacy of mTKIs was insufficient, leading to numerous randomized trials exploring the use of immunotherapy with ICIs, including anti-programmed death-1 (PD-1) and anti-programmed death-ligand 1 (PD-L1) antibodies [107].  
In 2017, the FDA approved the anti-PD-1 monoclonal antibody nivolumab for treating HCC after previous sorafenib treatment, based on the findings of the CheckMate-040 study [108]. In 2018, pembrolizumab, another anti-PD-1 monoclonal antibody, was approved for HCC patients previously treated with sorafenib, based on the KEYNOTE-224 study. However, ICI monotherapy for patients with metastatic or unresectable HCC did not demonstrate a significant survival benefit. This led to the exploration of combination therapies, as a better understanding of the tumor microenvironment (TME) emerged.
## 3 Design and Verification of Proposed Hybrid IPT Charger for CC/CV Modes
### Verification of the Proposed IPT Charger for CC/CV Modes  
It is necessary to verify the design's compensation parameters. Therefore, to validate the proposed hybrid IPT charger, we used MATLAB to verify the simulation results as shown in Figure 12a,b. Figure 12 presents the input phase angle, transconductance gain, and voltage gain changes under dynamic loads. As shown, \(G_{Ull}\) can be kept constant on the premise of ZPA. Similarly, graphs of the voltage gain \(G_{Ull}\) and input impedance \(Z_{IN}\) with respect to the load are presented in Figure 12b. There were smooth voltage and current gains at approximately \(f=85\) kHz, indicating that the proposed hybrid-compensated IPT system is highly stable.  
Figure 11: The design of the proposed hybrid IPT system’s compensation parameters process.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Symbols** & **Value** & **Symbols** & **Value** \\ \hline \(U_{IN}\) & 220 V & \(L_{1}\) & 15.25 uH \\ \(f\) & 85 kHz & \(L_{2}\) & 15.15 uH \\ \(C_{p1}\) & 229.83 nF & \(C_{fcc}\) & 76.025 nF \\ \(C_{p2}\) & 229.79 nF & \(C_{fcc}\) & 63.045 nF \\ \(C_{f1}\) & 145.67 nF & \\ \hline \hline \end{tabular}
\end{table}
Table 1: Designed compensated parameters of the proposed IPT chargers.  
In this study, ACSs (\(S_{1}\), \(S_{2}\)) connected back-to-back by two MOSFETs were adopted to realize the switch from the CC to CV mode. As shown in Figure 13a, the battery charger's ACSs used the same drive signal. Figure 13b shows the logic circuit diagram for the ACSs control drive. \(U_{b}\) represents the charging voltage, and \(k_{v}=U_{REF}/U_{b}\). As the batteries are charged, because the output voltage of the IPT charger is relatively low, the switches \(S_{1}\) and \(S_{2}\) go into the \"on\" state and the IPT charger works in the CC output mode. In contrast, as the output voltage reaches the reference voltage \(U_{REF}\), \(S_{1}\) and \(S_{2}\) go into the \"off\" state and the IPT charger operates in the CV output stage.
## 1 Introduction
They analyzed influences of different placement of sound-absorbing materials on the sound absorptive performance for the composite absorber, and proposed a wideband sound-absorbing configuration in which the sound-absorbing material was placed in front of the micro-perforated plate. However, the composite absorber still requires a large installation space. More recent work has laid foundations of improving the low frequency sound absorption performance by using extended tube resonators [15, 16, 17, 18, 19]. [PERSON] et al. [16, 17, 18] presented a kind of multiple extended tube resonators to enhance the low frequency range from 100 to 1600 Hz in a constrained space of 100 mm. In order to further improve the low frequency sound absorption of a thin layer melamine foam below 500 Hz, a new type of resonant absorber comprised of hollow perforated spherical structure with extended tubes is introduced in the present work. Hence we theoretically and experimentally investigated the low sound absorption performance of the combined absorber, and found that the coupling between the Helmholtz resonance and the quarter wavelength resonance shows a great potential to ameliorate sound absorptive performance of a traditional porous foam at low- and mid- frequencies. Meanwhile, the sound absorption in low frequency range could be greatly enhanced by tuning the tube parameters. Our proposed sound absorber reaches the same sound absorption performance of PPETs-PSAM [17,18], while it is more practical in noise control application since this device is simply made of a thin and lightweight hollow perforated spherical structure, and could be easily combined with porous foams. In what follows, we firstly conduct a theoretical analysis of the performance of combined absorber in Section 2, and then focus on parametric studies in Section 3. Section 4 is aimed at experimental verifications by impedance tube. Finally, Section 5 draws some conclusions.
# A Survey of OCR in Arabic Language: Applications, Techniques, and Challenges
## 4 Discussion and Conclusions
\begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Method** & **Pros** & **Cons** \\ \hline Template matching & Simple and easy to implement & Limited accuracy, sensitive to noise and variations in text \\ Deep learning & High accuracy, can handle variations in text & Requires large amounts of training data, computationally expensive \\ \(k\)NN & For small datasets, takes less training time and make predictions quickly & Sensitive to noisy or irrelevant features \\ RNN & For processing large sequential data and can learn term dependencies & Computationally expensive and sensitive to overfitting \\ Hough Transformation & Robust to noise and can detect lines and circles at any orientation & Computationally expensive when dealing with large images \\ Histogram Oriented Gradient & Extracts features such as edge orientation and texture, and is computed quickly & Ineffective at detecting finer details and is sensitive to variations in lighting and contrast \\ Hidden Markov Model & Models complex patterns and can be trained on large/sequential datasets & Computationally expensive to train and sensitive to model parameters \\ Profile Projection & Extracts features from images, such as character width and spacing & Sensitive to variations in lighting and contrast. \\ Random Forest & Relatively easy to train and can handle noisy or missing data & Does not perform well on highly imbalanced or sparse datasets \\ SVM & Used for classification tasks and can handle high-dimensional data & Computationally expensive non-linear kernels require hyperparameter tuning \\ Hybrid approaches & Combines the strengths of multiple methods & More complex and difficult to implement \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Pros and cons of various recognition methods for Arabic OCR.
# Pedestrian Fall Detection Methods for Public Traffic Areas: A Literature Review
## 2 Methodology  
This section provides an overview of the methodology and rationale employed in the criteria for selecting review references. To better understand the state-of-the-art (SOTA) methods for fall detection [5], we identified numerous keywords related to fall detection research and categorized them into two groups based on their relevance: those related to detection methods and those related to research objectives.  
As Figure 1 shows, the detection methods group includes keywords such as \"fall detection\", \"fall detection system\", \"fall detection method\", \"fall detection dataset\", \"fall detection algorithm\", and \"fall\". The objectives group includes keywords like \"the elderly\", \"public area\", \"crowd\", \"accident\", and \"stampede\". By combining the keywords from both groups with logical \"OR\" operators, a literature search was conducted in various databases. After retrieving data from the databases, Google Scholar and Web of Science were selected as the primary sources of reference for this study.  
From 2013 to 2023, over 13,000 articles were found for \"fall detection\". The research methods reported in these articles were classified into different categories: computer vision (CV), machine learning (ML), Internet of Things (IoT), smartphone (SP), kinematic (K), sound analysis (SA), cloud-based (C), sensor (S), biomedical signal (BS), and wearable device-based (WD) methods. Among these, we selected five research methodologies with the most promising applicability in PTAs for thorough analysis: CV, IoT, SP, K, and WD.  
As Figure 2 shows, the number of research papers on fall detection in the Web of Science shows an annual increase from 2006 to the present. We performed a secondary selection based on the citation frequency of the articles while also ensuring a temporal distribution that reflects the comprehensive evolution of the research field. A total of 31 references were selected for bibliometric and content analysis and to determine the prospects for research on fall detection.  
In the early stages, fall detection research was focused on providing more efficient medical assistance to the elderly. However, such methods do not appropriately meet the application requirements of fall detection. Therefore, we considered the practical application needs of fall detection. For instance, in the context of elderly health management, it is necessary to assess the severity of a detected fall behavior, whether it poses a threat to the safety of the elderly individual, and whether it requires immediate contact with healthcare professionals for assistance.
## 5 Evaluation
### Impacts of Experimental Parameters
#### 5.6.1 Impact of Number of Codewords  
The resolution of the RIS in previous experiments was set to \(15^{\circ}\), inducing \(C=144\), which is already far more than what current RIS prototypes can provide. Here, we further enlarged \(C\) for more harsh scenarios by assuming smaller resolutions, i.e., \(10^{\circ}\) and \(5^{\circ}\), obtaining \(C=324\) and \(C=1296\), respectively. Note that for the oracle case, \(C\) always equals one for the purpose of benchmarking. Other parameters remained unchanged in this section--i.e., \(A=51.84\) and \(\sigma=0\). Figure 17 illustrates the location-estimation errors of the oracle/baseline cases and our solution. As \(C\) increases, both the MSE and the standard deviations become larger, as the feature extractor has to adapt to more codewords at the same time. Nonetheless, the performance of our solution is still nearer to that of the oracle case than the baseline case. When \(C=1296\), our solution even performs better than the baseline case when \(C=144\). These performances demonstrate that our solution maintains its capability of being codeword-independent when \(C\) becomes much larger than current prototypes. This proves the robustness to the number of available codewords. Table 3 presents the corresponding numerical results.  
\begin{table}
\begin{tabular}{c|c c c c} \hline  & \multicolumn{2}{c}{**LoS**} & \multicolumn{2}{c}{**NLoS**} \\ \cline{2-5}  & **MSE** & **Var** & **MSE** & **Var** \\ \hline Oracle case & 0.045 & 0.002 & 0.047 & 0.003 \\ \hline Our solution (CV ver.) & 0.050 & 0.007 & 0.090 & 0.018 \\ \hline Our solution (RV ver.) & 0.125 & 0.010 & 0.199 & 0.013 \\ \hline Baseline case & 2.053 & 0.958 & 2.956 & 1.033 \\ \hline \end{tabular}
\end{table}
Table 2: The localization errors (\(m\)) of LoS (orange) and NLoS (blue) areas for the oracle/baseline cases, and the CV/RV versions of our solution when \(\{C=144,A=51.84,\sigma=0\}\).  
Figure 17: The location-estimation errors of both LoS and NLoS areas for the oracle/baseline cases and our solution when \(\{C=144/324/1296,A=51.84,\sigma=0\}\). Given the squared error set \(e\), for each bar, the middle line is \(mean(e)\), i.e., MSE, and its height ranges from \(\text{MSE}-std(e)\) to MSE + \(std(e)\). Note that for the oracle case, \(C\) always equals 1 for reference.
## 3 Results and Discussion
### Bioactivity of the Kiwi Peel Extract Obtained under Optimized UAE Conditions
#### 3.6.2 Cytotoxic and Anti-Inflammatory Activity  
The cytotoxic activity of the kiwi peel extract against tumor (MCF-7, NCI-H460, AGS and CaCo-2) and non-tumor (Vero) cell lines was evaluated, as well as its anti-inflammatory activity via NO production inhibition. The extract showed activity against NCI-H460 (non-small cell lung cancer) cells, with an GI\({}_{50}\) of 309 \(\pm\) 16 \(\upmu\)g/mL. However, no activity was observed against other cell lines (MCF-7, AGS and CaCo-2) at the tested concentrations (GI\({}_{50}>\) 400 \(\upmu\)g/mL). Despite these results, [PERSON] [29] attributed cytotoxic effects to kiwi peel and pulp extracts against HepG2 (hepatocellular carcinoma) and CaCo-2 cells. [PERSON] et al. [25] also demonstrated that kiwi peel hydroethanolic extracts have cytotoxicity to MCF-7, NCI-H460, HepG2 and HeLa (cervical carcinoma) cells. In turn, [PERSON] et al. [30] investigated the anti-proliferative effects of kiwi extracts against HepG2, HT29 (colon carcinoma) and LoVo (colon carcinoma) tumor cells and observed that the extracts did not effectively inhibit cell proliferation. The absence of toxicity to non-tumor cells was herein demonstrated with the Vero cells (GI\({}_{50}>\) 400 \(\upmu\)g/mL). The kiwi peel extract also did not show anti-inflammatory activity, contrary to what has been described in the studies by [PERSON] et al. [31] and [PERSON] et al. [25].  
The difference observed between the activities presented by our sample and the literature data may be explained by the fact that the data were obtained from different plant parts, by differences in the adopted analytical and extraction methodologies and in the used proportions of solvents, but also because they are from different varieties or species of the same genus. Therefore, further studies using different human tumor cell lines and purified compounds will be needed to confirm the bioactivity of the kiwi peel compounds.
## 2 Materials and Methods
### THP-1 Phagocytosis Assay  
A protocol modified form [33] was used to study _S. aureus_ intracellular survival in macrophage-like cells. THP-1 (ATCCIB2020) monocyte cultures were maintained throughout the assay at 37 \({}^{\circ}\)C in the presence of 5% CO\({}_{2}\) in a base medium containing RPMI 1640 (Dutch edition) (Gibco, Invitrogen, Thermo Fisher Scientific, Paisley, UK) supplemented with 10% fetal bovine serum (FBS) (BioWhittaker, Lonza, Basel, Switzerland) and 2 nM l-glutamine (BioWhittaker). The cells were seeded into 24-well tissue culture plates (Costar, Corning Inc., Corning, NY, USA) at a density of \(4\times 10^{5}\) cells/well in a base medium supplemented with 0.05 mM 2-mercaptoethanol(Gibco) and 20 \(\mathrm{\SIUnitSymbolMicro m}\)L gentamicin (Fluka, Buchs, Switzerland) and differentiated with 160 nM phorbol 12-myristate 13-acetate (PMA, Sigma-Aldrich, St. Louis, MO, USA) for 48 h into macrophage-like adherent cells. Biofilms corresponding to the samples EDBF_24 h and SDBF_24 h were grown and harvested as described above in four individually inoculated replicate cultures. The suspended biofilms were vortexed briefly to disperse the possible remaining aggregates and adjusted to OD\({}_{600}=0.07\) with 100 mM Tris-HCl, pH 6.8. The differentiated THP-1 cells were conditioned in the base medium (in the absence of gentamicin and mercaptoethanol) for 30 min and infected at a MOI (multiplicity of infection) of 1 in a final volume of 500 \(\mathrm{\SIUnitSymbolMicro m}\). The plates were centrifuged for 10 min at 500\(\times\)\(g\) and further incubated for 50 min. Next, the infected medium was replaced with the base medium supplemented with 100 \(\mathrm{\SIUnitSymbolMicro g}\)/mL gentamicin and 20 \(\mathrm{\SIUnitSymbolMicro g}\)/mL lysostaphin and incubated for 1 h to kill the extracellular bacteria. The wells were then washed twice with PBS and the cells were detached with 0.25% trypsin, suspended in the base medium in a final volume of 1 mL, and pelleted by centrifugation at 500\(\times\)\(g\) (5 min, 4 \({}^{\circ}\)C). The pellets were resuspended in 1 mL of sterile water and incubated for 10 min at 37 \({}^{\circ}\)C to lyse the THP-1 cells. Serial dilutions of the lysates were prepared in PBS, plated on TSA in duplicate, and incubated overnight at 37 \({}^{\circ}\)C under aerobic conditions to enumerate intracellular bacteria. Additional plates for the further time points were replenished with 1 mL of the base medium containing 20 \(\mathrm{\SIUnitSymbolMicro g}\)/mL gentamicin and incubated until sampling for 3 and 24 h. An unpaired \(t\)-test was used to compare differences in bacterial viability.
# Simulation Tool for Winter Navigation Decision Support in the Baltic Sea
## 8 Verification and Validation of the Simulation Model
### Verification: Adherence to Conceptual Description  
The field experts participated in demonstrations where the model was run at a perceptible speed. The movements of the vessels and icebreakers were carefully inspected, along with the formation of dirways, changing ice conditions, and the formation of convoys.  
Further, the vessel speeds were monitored over a small geographical area with high ice variability to ensure that the speeds were reevaluated with changing ice conditions. The dirway changes were also inspected, a change being expected every week of the runtime. When a dirway changes, there may be some vessels in transition, that have not yet reached their destinations. These vessels continue their journeys along the old dirways. All new journeys are scheduled on the new dirways. Until all previously scheduled assistance missions are complete, icebreakers navigate along both old and new dirways. Figure 7a shows two snapshots of the visualization. To indicate varying ice thickness, different shades of blue are used in the visualization. A darker shade of blue indicates thicker ice. In Figure 7b, the vessels and icebreakers can be visualized more clearly. For ease of inspection, the names of all vessels and icebreakers are displayed. A dynamic field for vessel speed is also displayed, indicating the current speed. This helps to verify that the vessels and icebreakers indeed calculate different speeds for different ice thicknesses and use these for their navigation. The ship names are anonymized to protect data confidentiality.  
The validation of the model is described below.