esa-sceva/satcom-chunk-collection huggingface dataset:
# Assessing Crisis Management Tools for Sustainability of Industrial Safety
## 5 ALOHA Software, Strengths, Limitations, and Need for Improvements
### Limitations of ALOHA Software  
While ALOHA's short-term predictions are a major strength, the software is less effective for long-term risk assessments or situations where conditions change rapidly. For instance, the reliance on static input variables limits ALOHA's ability to dynamically adjust to real-time environmental changes. This shortcoming is highlighted in the [PERSON] et al. (2024) study, which simulated toxic gas releases and emphasised the need for real-time data integration to improve the prediction accuracy during evolving emergencies [19; 20]. The lack of such functionality in ALOHA constrains its effectiveness in complex industrial settings where the nature of the hazard can change rapidly.  
In addition, [PERSON] and [PERSON] (2013) compared ALOHA with another simulation tool during a chemical accident in Aliaga, Turkey, and found that while ALOHA was useful for initial predictions, its limited capacity to handle long-term evacuation planning and dynamic updates could hinder its application in larger, ongoing incidents. The authors demonstrated that combining ALOHA with a more comprehensive simulation tool would provide a better overview of risk management for extended crises [21; 22; 23]. Similarly, [PERSON] (2007) emphasized the importance of robust consequence assessments in scenarios involving hazardous substances, highlighting the need for tools capable of addressing long-term risk factors in complex environments [24].  
The study by [PERSON] et al. (2018) further emphasised these limitations by comparing ALOHA with other risk assessment tools used in South Korea for hazardous chemical management. While ALOHA excelled in short-term incident scenarios, its ability to manage longer-term risk assessments was outperformed by alternative software solutions that could incorporate more complex, quantitative analyses [15; 24].
## 2 Background  
Pacaya volcano, located in the Central American Volcanic Arc (CAVA) (Figure 1a) is a several thousand year old basaltic complex that has experienced eruptive episodes typically lasting a few centuries, with repose intervals of similar length [16; 17]. One notable event was a large (0.6-0.8 km\({}^{3}\)) sector collapse that occurred between 600 and 1500 years ago [18; 19], the collapse scrap of which is still visible today (Figure 1b). The current eruptive episode began in 1961, with interspersed Strombolian eruptions, ash plumes, and effusive lava flows depositing material primarily on the west and southwest flank within the collapse scrap [20]. The majority of lava flows and explosive activity originates from the summit of the active cone; however, many of the high-volume lava flows tend to erupt from vents lower on the volcano's flanks [21].  
Using ALOS-1 data from 2007 to early 2010, an InSAR survey of the CAVA found no deformation faster than 27 mm/year that could be attributed to magmatic processes at any of the 20 historically active volcanoes [14]. At Pacaya, this was attributed to a high proportion of basalt ascending directly from the base of the crust without a period of crustal storage [14]. An InSAR investigation into explosive eruptions rated as VEI-3 eruptions on the Volcanic Explosivity Index (VEI) on the 27 and 28 of May 2010 found that the southwest flank of the edifice moved \(\sim\)3 m to the southwest during this two-day eruption [22]. This flank displacement, combined with historic collapse, confirms that slope instability is a serious threat at Pacaya.  
In addition to the slope movement, eruptive activity during the May 2010 eruptions produced several topographic changes to the edifice. On 27 May, about a 600 m long linear collapse initiated at the summit vent oriented NNW (Figure 1b), the origin of which is still debated [(23)]. On 28 May, a large lava flow erupted from 12 clustered vents to the SE of the summit around 1800 m above sea level (asl), being the first historic lava flow to originate outside of the collapse scarp (Figure 1b; [(20)]). According to reports by the National Coordinator for Disaster Reduction [(24)], the flow originally moved at a rate of 100 m/h. The flow rate slowed in the following days to 15 m/h by 6 June and 1 m/h by 8 June, until ceasing on 30 June. This is one of the largest lava flows that has erupted in the last 55 years, which flowed to the south for \(\sim\)3 km before curving west around 1300 m asl, following the local gradient. Ultimately, the flow reached \(\sim\)5.4 km in length, covering an area of 1.6 \(\times\) 10\({}^{6}\) m\({}^{2}\). Thickness estimates of 1-4 m result in a volume range of 1.6-6.4 \(\times\) 10\({}^{6}\) m\({}^{3}\)[(20)]. With continual eruptive activity and evidence of slope instability, it is imperative to monitor deformation events at Pacaya volcano.
## 1 Introduction
To verify the effectiveness of the proposed control method, a two-bus system was configured, and a generator dropout accident was simulated based on power systems computer-aided design/electromagnetic transients for DC (PSCAD/EMTDC), which is a time-domain transient simulation tool for power systems. The main contributions of this study are summarized as follows. * The conventional FFR control does not use energy efficiently from the viewpoint of the frequency nadir because various energy sources are activated simultaneously. In addition, a second frequency nadir may occur, which may reduce the frequency stability. Thus, a novel coordinated control strategy was proposed to improve the nadir frequency by using energy more efficiently than the conventional FFR control. * FFR has a very fast response; even a small delay will affect the results. Therefore, IBR activation delay, frequency detection delay, and communication delay were applied to the simulation to reflect the actual characteristics of the IBRs. The remainder of this article is organized as follows. PMSG modeling is demonstrated for the simulation, which is introduced in Section 2. In Section 3, a novel coordinated control strategy for PMSGs and battery energy storage systems (BESSs) with fast frequency response is proposed. Finally, the simulation results and discussions are presented in Sections 4 and 5.
## 4 Discussion
### Lessons Learned from the Design and Evaluation of Each Application Case Study
Expert reviews and standardized questionnaires like SUS and NPS provide quantitative data to benchmark usability and measure user engagement. This holistic approach is essential for coordinating efforts across multiple teams, ensuring that every aspect of the user experience is meticulously evaluated and optimized. By leveraging both qualitative and quantitative data, PLUGGY's framework facilitates robust, evidence-based decision-making, ultimately leading to a more reliable, user-friendly application that meets the diverse needs of its stakeholders and end-users. The design of the PLUGGY evaluation framework also exemplifies a type of triangulated approach by integrating multiple parallel methods to comprehensively assess the complex user experience in a mutually informative way. Triangulation involves using diverse data sources and evaluation techniques, and collecting multiple perspectives, to thoroughly validate and cross-check the diverse findings and ensure a well-rounded understanding of usability and user engagement. This particular design of the experiments was triangulated in the following way:  
1. Diverse Methods: Combining qualitative methods (interviews and pilot studies) with quantitative measures (SUS and NPS) allows for capturing both subjective user insights and objective usability metrics. 2. Formative and Summative Evaluations: Formative methods like usability testing and pilot studies refine the prototype iteratively, while summative evaluations such as expert reviews and standardized questionnaires validate the final design's effectiveness. 3. Multiple Perspectives: Personas ensure the design aligns with varied user needs, expert reviews provide professional usability assessments, and representative end-user feedback from diverse tasks highlights real-world application strengths and weaknesses. This triangulated design is crucial for large, multi-party development teams with many stakeholders with different professional backgrounds and professional expertise, as it ensures that all aspects of the user experience are meticulously evaluated from different angles. By leveraging both qualitative and quantitative data, teams can make informed, evidence-based decisions that enhance the interface's accuracy, user-friendliness, effectiveness, and efficiency. This comprehensive approach minimizes the risk of overlooking critical usability issues, fosters collaboration across diverse teams, and ultimately leads to a robust, user-centered application that meets both technical and cultural heritage objectives.
# Research on VVC Intra-Frame Bit Allocation Scheme Based on Significance Detection
## 2 Related Work
### Conventional Rate Control Algorithms
The findings of this research served as inspiration for a redesign of frame-level bit allocation, which further reduces the prediction error of the R-\(\lambda\) model at the frame-level and CTU-level by utilizing the statistical information of skip block ratios and disregarding the parameter updating information of the skip blocks.
# Development of a Vibroacoustic Stochastic Finite Element Prediction Tool for a CLT Floor
## 6 Results and Discussion  
### Quantification of Uncertainties  
One of the objectives of this article is to investigate the effects of uncertainties induced by material properties on the model output and to ultimately obtain a reliable model to predict the vibro-acoustic behavior of different designs. To achieve that, 100 steady-state simulations with different combinations of material properties were carried out in Abaqus.  
In Figure 13, each subfigure has 100 FRF simulations and the measurement results are shown in blue. Figure 13 shows that there is an obvious envelope overlapped around the first four peaks lower than 100 Hz. The large variation envelope range is due to varying five mechanical constants in one time since five elastic constants variations have a larger impact on the dynamic response of CLT than only changing one elastic constant in one time.  
On the contrary of the frequency range lower than 100 Hz, the simulated FRFs begin to scatter above 100 Hz. No clear envelope peaks can be found around the measured resonances higher than 100 Hz. One possible reason of these scattering curves in a relative higher frequency range is the complexity of the mode shapes. It is known that the lower the eigen-frequency is, the simpler the mode shape is and the longer the wave length is. Long wavelength are not sensitive to the small details in the CLT panel, such as the non-uniform air gaps throughout the laminas and the edge bonding (c.f. Figure 14). It implies that the dynamic behavior of CLT in a low frequency range can be mimicked by a simplified homogeneous orthotropic laminated FE model. However, when the mode shapes become more complex in a higher frequency range, the wavelength becomes smaller. As a consequence, small details of the CLT panel begin to affect the vibration of the CLT panel. In this case, the homogeneous orthotropic laminated FE model could not properly describe the dynamic response of the CLT panel in the higher frequency range. In order to increase the accuracy of the FE in a high frequency range, non-homogeneous laminate layer, such as an account for the irregular air gap in laminas, should be modeled. Nevertheless, it should be aware that the calculation time will become longer, when more details are taken into account in the model. The stochastic method needs a large number of calculations to quantify the uncertainties induced by the material properties so that a compromise should be carefully made between the accuracy of the model and the calculation time.
# Free Vibration Analysis of Arches with Interval-Uncertain Parameters
## 4 Numerical Simulation and Discussion
### The Natural Frequencies Based on the Traditional Deterministic Method  
According to the calculation example provided in reference [19], the arch cross-section is assumed to be rectangular; its physical parameters are presented in Table 1. In this paper, the total number of discretized sample points of arch \(H\) is 21. Waterfall plots of the first fourth-order natural frequencies with the central angle varying in the interval [\(\pi/6\), \(\pi\)] and the radius varying in the interval [1,3] are shown in Figure 3. Firstly, it is shown that, under the conditions of equal radius and central angle, the natural frequency demonstrates a discernible upward trend with increasing orders, which aligns convincingly with empirical evidence. Then, it is also shown that the frequency of each order increases as the radius and central angle decrease, with a more pronounced increase observed in higher-order frequencies compared to lower-order frequencies. Furthermore, the frequency remains numerically continuous within the range of the central angle, thus confirming the appropriateness of the surrogate model utilized in this paper. Specifically, it is essential for the objective function of the model to maintain continuity.
## 3 Methodology
### 3D Rendering
Normals are also converted into normalized integers stored in vertex arrays. Filling vertex buffers with half float coordinates improves the overall rendering performance. Moreover, indexed draw calls of a small index type are used while the vertices of the meshes are drawn. This decreases the amount of index data that the GPU needs to access for each draw call, at the expense of slightly more complicated application logic. To reduce the scene range and the amount of data transmission between CPU and GPU, chunks of the models that are not temporarily displayed are excluded using frustrum culling. Only the vertices that are visible, even partially, are sent to the GPU. This is achieved by setting the positive values of near and far distances into the orthographic projection matrix. During instancing, the same mesh is being drawn multiple times. This process involves storing \(n\) matrices in a uniform buffer and calling them once to draw \(n\) copies. The matrix needed for each instance is fetched from the uniform buffer using an indexed unique value that has to be declared in the shader. The geometry-instancing technique renders all vertices and triangles of a scene through the shader using one call [53]. Unique attributes, such as transformation matrices, can be provided for every single occurrence of the mesh but repetition is a priori. In our case, the AR session comprises one 3D model that is loaded once the camera module detects the pattern and image matching occurs. Whentracking is lost between 2 consecutive frames, the 3D model is drawn again at the specific pose. Destroying and re-rendering or creating a copy of the 3D model's data to a new object are expensive procedures for low-end GPUs. Therefore, a batch system that renders all the active models based on geometry-instancing has been developed. The vertices of the meshes are already stored into a vertex buffer and the transformation matrices to a uniform buffer. Then, an instancing stream that contains the index of the matrix within the uniform buffer is created. The index should be used by the vertex data when rendering and this approach leads to an identical instancing setup and uniform buffer data. Besides instancing copies of a single mesh, this technique achieves fast drawing of multiple non-identical meshes. The aforementioned methods and proposed strategies are implemented in the context of an independent 3D graphics engine that configures a complete rendering pipeline for OBJ 3D models. They reside as activities or functions and constitute building blocks for the rendering and visualization of the AR scene of ModAR. In addition, they can be built and used standalone for any other graphics application based on OpenGL ES 2.0.
## 2 Materials and Methods
### Evaluation of Reliability  
All measurements were traced by one expert operator that was blinded to the treatment. Measurements were repeated on 20 randomly selected dental casts by the same operator and a different one--even he was blinded to the group allocation--to assess intra- and interoperator variability. Intraclass correlation coefficients (ICC) were calculated to compare within-subject variability to between-subject variability.
## 2 Materials and Methods
### Sample Characterization  
The cross-section specimens for TEM were studied in a Titan 80-300 TEM/STEM (FEI, USA) at an accelerating voltage of 300 kV. The energy filtered TEM (EFTEM) measurements were performed in the low loss region of the electron energy loss spectrum with a 2 eV energy slit around the bulk Si plasmon loss peak (16.7 eV), which is commonly used to visualize a sample superlattice structure. High-resolution TEM (HRTEM) images showing individual Si nanocrystals were obtained at Scherzer defocus value. Phase separation of SiN\({}_{\mathrm{x}}\) was studied by X-ray photoelectron spectroscopy (XPS) performed on the ESCA branch of the NanoPES station at the Kurchatov synchrotron radiation source (National Research Center Kurchatov Institute) with Al \(K_{\alpha}\) excitation (1486.61 eV). Sample surface sputtering was carried out by the 1.5-keV Ar\({}^{+}\) ions bombardment in order to remove organic contaminations and native oxide. To study superlattice structure stability against thermal annealing, angular dependences of the intensity of X-ray reflectivity (XRR) were measured in step mode 2\(\theta\)/\(\omega\) on X-ray diffractometer with a rotating anode (Rigaku SmartLab, Japan) using the characteristic Cu \(K_{\alpha}\)1 line (radiation energy 8.048 keV). In-plane grazing incidence X-ray diffraction (XRD) studies were conducted on BM25B beamline at the European Synchrotron Radiation Facility (ESRF) using 22.025 keV radiation energy (incidence angle 0.1\({}^{\circ}\)). Photoluminescence (PL) was excited by a He-Cd laser (\(h\
u_{\rm exc}\) = 3.81 eV, 20 mW power) focused into a spot with 1 mm diameter. The PL signal was measured using a 500 mm focal length spectrometer (SOLAR MS 350, Belarus) equipped with a CCD camera with a sensitivity range of 200-1100 nm. The spectra were taken at room temperature and corrected for the system response, as well as for spectrometer dispersion by multiplying by \(\lambda^{2}\). For time-resolved PL measurements pulsed Nd:YAG laser excitation (\(h\
u_{\rm exc}\) = 2.33 eV, pulse duration 34 ps, laser pulse fluence \(\sim\)3 mJ/cm\({}^{2}\), repetition rate 10 Hz) was used. The PL signal was collected by means of intensified CCD (PI-MAX Gen III, Princeton Instruments) coupled to a 500 mm focal length imaging spectrograph (Princeton Instruments SpectraPro 2500i, USA). All PL spectra were detected within 1 \(\upmu\)s gate width taking various delays after excitation pulse onset in the range from 0 to 40 \(\upmu\)s. The PL decays for different emission energy (1.5 and 2 eV) are plotted using the PL intensity at a chosen photon energy values as a function of delay time.
## 2 Results
### Phytosterol Analysis  
GC-MS analysis identified nine phytosterols, and the respective concentrations influenced by the different drying methods and drying intensities are shown in Table 3. The major phytosterols in fresh _S. crispus_ were \(\beta\)-sitosterol, stigmasterol, and campesterol, with concentrations of 1476.67, 1207.96, and 791.57 mg 100 g\({}^{-1}\) db, respectively. Considerable losses of phytosterol were noted in dried samples. [PERSON] et al. (2009) reported that the stability of phytosterols is affected by chemical structure, processing temperature, and time [33]. In our study, VMD at 9 W/g retained the highest phytosterol content (542.48 mg 100 g\({}^{-1}\) db) because of the favorable drying condition of the reduced oxygen and the accelerated drying process. The freeze-dried samples had the lowest phytosterol content (462.07 mg 100 g\({}^{-1}\) db). Overall, moderate hot air temperature (CD at 50 \({}^{\circ}\)C) and microwave power (9 W/g) retained higher phytosterol contents. [PERSON] et al. (2004) reported that several factors, such as temperature and heating duration, phytosterol structure, and lipid matrix composition, affect the oxidative stability of phytosterols [34]. [PERSON] et al. (2015) demonstrated that high phytosterol degradation in rapeseed is related to high drying temperature [35]. With respect to the results of our study, the applied moderate drying intensity effectively reduced the drying duration to prevent the high extent of degradation and oxidation due to long drying time. However, such intensity induced a heat degradative effect on phytosterols. In addition, phytosterols are most likely lost through an oxidation process, especially during CD. Similar findings were reported by [PERSON] et al. (2009) [33]. With the application of appropriate hot air temperature and microwave power, attaining relatively higher retentions of phytosterols was possible.  
[PERSON] et al. (2012) indicated that the degradation level of phytosterols depends on their chemical structure [36] and investigated the degradation behavior of \(\beta\)-sitosterol, stigmasterol, and campesterol at 180 \({}^{\circ}\)C. They found that campesterol is highly susceptible to degradation, similar to \(\beta\)-sitosterol, and with stigmasterol less susceptible. However, in our study, the highest percentage reduction of phytosterols among the fresh samples and the samples subjected to VMD at 9 W/g was observed in campesterol (91.6%), followed by stigmasterol (87.8%) and \(\beta\)-sitosterol (84.5%).