esa-sceva/satcom-chunk-collection huggingface dataset:
# Centrifugal Model Study of Seepage and Seismic Behavior in a Homogeneous Reservoir Dam with Parapet
## 2 Materials and Methods
### Modeling and Experimental Conditions  
The reservoir dam prototype was a homogeneous small-scale reservoir with a height of 6 m, dam crest width of 4 m, and slopes of 1:1.2 and 1:1.3 on the downstream and upstream sides, respectively. Figure 3 shows the design conditions applied to the model dam construction. A silicon mat (thickness: approximately 2 cm) was installed at the boundary between the model dam and foundation to ensure seepage only within the embankment. The foundation was 15 cm deep, comprising hard sand with over 95% compaction. Accelerometers and three water pressure gauges were used to measure seepage and seismic behavior. Additionally, three small pumps were used to circulate water and maintain the upstream water level during the experiment. The small pump was designed to pass water only through a wire mesh to prevent failure due to soil mixing. The parapet was made of cement with dimensions of 30 \(\times\) 20 \(\times\) 200 mm (height \(\times\) width \(\times\) depth) and a weight of 2.07 kg. The upstream water level was applied to the viscous fluid. For 100% saturated soils, the physical properties of the soil, such as strength and stiffness, are not affected by viscous fluids [19].  
In the centrifugal model test, instantaneous failure may occur owing to comparatively fast seepage flow caused by massive gravitational acceleration. Consequently, the viscous fluid was designed to have the same viscosity (50 G) as that of the scale factor of the model. For monitoring equipment, an action camera was placed in front of the model to observe cracks caused by the weight of the parapet structure and deformation of the dam. Additionally, DIPP-Motion V image analysis software was used to numerically track the deformation of the model dam after centrifugal loading [20]. For image analysis, a marker was assigned to the model image captured by the camera and used to calculate the deformation displacement before and after the experiment by tracking the RGB value of a specified pixel. Displacement can be measured and described in both longitudinal and transverse directions.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Properties** & **Prototype** & **Scaling Factor** & **Properties** & **Prototype** & **Scaling Factor** \\ \hline Density & 1 & 1 & Mass & 1 & 1/N2 \\ Length & 1 & 1/N & Force & 1 & 1/N2 \\ Displacement & 1 & 1/N & Stress & 1 & 1 \\ Velocity & 1 & 1 & Strain & 1 & 1 \\ Centrifuge acceleration & 1 & N & Time (static) & 1 & 1/N2 \\ Seismic velocity & 1 & N & Time (dynamic) & 1 & 1/N \\ \hline \hline \end{tabular}
\end{table}
Table 2: Similarity law in the centrifugal model test.  
Figure 2: Scenario setting.
# A Reliability Engineering Approach for Managing Risks in CubeSats
## 4 Results
### Step 1: SPEC CubeSat Design and Functional Block Diagram
The spacecraft will transmit the images to an available ground station in Malindi (Kenya), through a patch antenna, while the UHF communications will be managed through a deployable \(\lambda/4\) monopole antenna, with two ground stations in Rome (Italy) and Nairobi (Kenya). As reported before, the achievement of the mission objectives depends on the well-functioning of the ADCS. On this purpose, the ADCS operations will be coordinated by a dedicated computer. While magnetorquers and reaction wheels will be used as attitude actuators, fine Sun sensors, star trackers, magnetometers and gyroscope will monitor the angular position and velocity of the spacecraft. The structure, compliant with the 6U CubeSat standard and the strictest regulations on CubeSat launch and deployment [36; 40], will be manufactured from a single aluminum 6061-T6 alloy shell. The structure will also include dedicated room for the deployable components, such as the telescope, the monopole antenna and the four solar panel wings. These will contain 40 solar cells, assuring a maximum power generation of 31.3 W. The power generation maximization is needed to decrease as much as possible the depth of discharge of the on-board batteries, whose total stored energy will amount to 40 Whr. Moreover, Mylar covers will allow the temperature stabilization of the telescope sensor, by assuring the quality of the acquired images. The satellite End-of-Life operations will be managed by a dedicated _de-commissioning_ mode, in order to ease the satellite disposal and to comply with the current space debris mitigation regulations [41]. The CAD model of the spacecraft is depicted in Figure 4.  
In terms of risk management, all the components have been selected in order to relay on space-qualified items. In particular, EPS, and OBDH (On-Board Data Handling) units have already been used together in spaceflight of CubeSats. ADCS uses a single block of integrated sensors, actuators with a dedicated computer (even guaranteed to work properly as OBDH), TT&C (Telemetry, Tracking and Command) has flight proven radio modules and the active thermal protection of the InGaAs sensor is autonomous and included in the payload sensor. These design choices reduce risks in terms of integration of subsystems and components within a specific subsystem.
## 7 Conclusions  
In this paper, we investigate inter-satellite cooperative task offloading and resource allocation in an MEC-enabled STN. The task completion delay optimization problem for all IoT devices when the tasks are indivisible is formulated and decomposed. Then, we propose a joint offloading decision and resource allocation optimization scheme, which consists of a task offloading decision algorithm based on the GWO algorithm and a computing resource allocation algorithm based on the Lagrange multiplier method, thus obtaining the optimal task offloading decision and allocating optimal computing resources of the local satellite's MEC server and neighboring satellites' MEC servers. Simulation results validate that the proposed scheme performs better than the other baseline schemes in the following cases: the number of IoT devices is large, the number of satellites is large, each satellite has numerous computing resources, the computation intensity is high, or the data size is big. Much work remains to be done in the future. For example, we will investigate inter-satellite cooperation, where multiple satellites with MEC servers can simultaneously receive tasks offloaded by IoT devices and assist IoT devices in computing tasks in areas not covered by terrestrial networks.  
Conceptualization, M.T.; methodology, M.T. and S.L.; software, M.T.; validation, M.T.; formal analysis, M.T.; investigation, M.T.; resources, X.W.; data curation, M.T.; writing--original draft preparation, M.T.; writing--review and editing, M.T., S.L., X.W. and P.W.; visualization, M.T.; supervision, S.L.; project administration, S.L. and X.W.; funding acquisition, X.W. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Key Research and Development Program of China grant number 2018 YFC1504502.  
Figure 8: Delay vs. number of IoT devices.  
Figure 7: Delay vs. data size of each task.
# Probabilistic Analysis of Low-Emission Hydrogen Production from a Photovoltaic Carport
## 4 Results
### Probability of Monthly Energy Production Levels in Poland
Using Metalog, determining the probability for a given monthly or daily amount of energy production requires a simulation process that uses the determination of the inverse function of the Cumulative Distribution Function. GeNIe 4.1 Academic software has built-in families of Metalog distributions and allows for the quick determination of the Cumulative Distribution Function and Probability Density Function and provides a simple way to obtain information from the knowledge base. From the shape of the Probability Density Function, it can be concluded that there are several different contexts for the operation of the photovoltaic system, which will be proven in this article. \begin{table}
\begin{tabular}{c c} \hline \hline  & **Energy Production [kWh]** \\ \hline Count & 12 \\ Minimum & 57.044 \\ Maximum & 945.084 \\ Mean & 529.221 \\ StdDev & 350.765 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Basic statistical analysis of the energy generated monthly by a 6.3 kWp photovoltaic system in Poland. \begin{table}
\begin{tabular}{c c} \hline \hline
**Probability** & **Energy Production [kWh]** \\ \hline
0.05 & 57.04399871826 \\
0.25 & 212.4069976807 \\
0.5 & 634.7689819336 \\
0.75 & 871.0469970703 \\
0.95 & 945.083984375 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Extended statistical analysis of the energy generated monthly by a 6.3 kWp photovoltaic system in Poland. Based on the data on monthly energy production (presented in Figure 7), the software creates models that constitute the knowledge base. Importantly, this information from the knowledge base can be easily obtained. For example, one can ask the following question: What is the probability of generating monthly energy equal to or less than 200 kWh by the tested photovoltaic system? Based on the models in the form of the CDF and PDF, the database provides an answer: 0.25. Therefore, the probability of generating monthly energy greater than 200 kWh by the tested photovoltaic system is \(1-0.25=0.75\). The results of acquiring knowledge from the knowledge base are presented in Table 3.  
Figure 10: Cumulative Distribution Function (CDF) and Probability Density Function (PDF) for the power generated monthly by a 6.3 kWp photovoltaic system placed in Poland. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Energy Production** & **Probability** & **Probability** \\
**[kWh]** & \(\leq\) & **>** \\ \hline
200 & 0.25 & 0.75 \\
400 & 0.4167 & 0.5833 \\
600 & 0.5 & 0.5 \\
800 & 0.6667 & 0.3333 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Results of the probability of energy production monthly by a 6.3 kWp photovoltaic system in Poland.
# A Multimodal Recurrent Model for Driver Distraction Detection
## 2 Materials and Methods
### Data Collection
#### 2.1.1 Recording Setup  
The recording setup was centrally managed from a notebook, which acted as a control center during the drives. A Python application was developed to handle communication with the data sources and to perform initial preprocessing tasks, such as decoding OBD2 data. Data from each recording session was organized in a timestamped folder on the notebook.  
The setup included three key data sources:  
* Camera: A _Logitech C920 PRO HD_ webcam was mounted on the passenger side, facing the driver. It captured 30 frames per second at 1920 \(\times\) 1080 resolution, which was later downscaled to 224 \(\times\) 224 pixels for model training. Each image was timestamped and stored in the recording folder.  
* IMU (steering wheel): A microcontroller (_NodeMCUI Lua Amica Module V2 ESP8266_) equipped with a 9-axis IMU (_BlueDot BNO055_) was attached to the steering wheel to record vehicle dynamics and steering movements. IMU data, including acceleration, angular velocity, and magnetic field strength, was transmitted to the notebook via MQTT protocol at 40 samples per second. The data were stored in JSON files with regular checkpoints to prevent loss.
* OBD2 Interface: A Bluetooth-enabled OBD2 adapter (_Veepeak OBDCheck VP11_) was used to capture additional vehicle sensor data. The laptop established a Bluetooth connection to continuously request and record parameters such as vehicle speed, engine speed, and throttle position at a frequency of 5 Hz. These data were also stored in JSON files alongside the IMU data.
###### Abstract  
Low-voltage (LV) and high-voltage (HV) DC distribution systems are being investigated as alternatives due to the growth of DC distribution energy resources (DER), DC loads such as solar and wind power systems, and energy storage sources (ESSs). Furthermore, an HV/LV DC distribution system offers various advantages, including lower conversion losses, an easier connecting strategy for DC DERs, and less complex power management techniques. As renewable energy sources are increasingly incorporated into the electrical grid, it is important to create novel, effective approaches for connecting such sources and loads. It would hence be effective to merge DC distribution with AC distribution to fulfill the energy demands of both DC and AC consumers. To this end, this study proposes a multizone design with four buses: low-voltage direct current (LVDC), high-voltage direct current (HVDC), low-voltage alternating current (LVAC), and an electrical grid. A model of this system that covers crucial elements, including power systems, DER systems, and power electronic devices, to serve as a foundation for the analysis and design of this architecture is proposed. MATLAB/Simulink is used to conduct a simulation study to verify the performance of the proposed design. In this study, a hybrid electrical grid with an LVDC, HVDC, and LVAC distribution network test is used and implemented. Additionally, a transient and steady-state characteristic analysis of the test system is performed.  
LVDC; HVDC; LVAC; DER; ESS; electrical grid; MATLAB/Simulink
# Drilling Fluid and Cement Slurry Design for Naturally Fractured Reservoirs
## 5 Lost Circulation While Cementing through Naturally Fractured Reservoirs
### Cement Slurries for Primary Cementing through Fractured Formations
#### 5.3.3. Cross-Linked Cement Slurry  
Cross-linked cement slurries have been used to temporarily or indefinitely seal critical intervals where drilling and cementing operations are very difficult to be successfully accomplished due to severe lost circulation. A cross-linked cement slurry is a combination of cement and track products mixed as regular cement slurry in a gelled fluid. The combination results in a homogeneous mix, which is pumped as a linear fluid. In down-hole conditions, a cross-linked cement slurry sets rapidly when placed into the lost circulation zone where it develop significant compressive strength. The cement slurry density and thickening time can be adjusted to satisfy the specific application by the addition of common oil well cement additives. It can be designed to be used in pay zones (i.e., Magnesia cross-linked cement, up to 98% soluble in HCI) or to cure severe lost circulation problems in situations where there are, natural or induced fractures, primarily in non-productive zones and low-cost environments (i.e., regular cross-linked cement, 73% soluble in HCI) ([PERSON] et al., 2014). Magnesia cross-linked cement is mixed with carboxy-methyl hydroxy-ethyl-cellulose as a gellant and fluid loss control agent, a borax-based retarder, a zirconium cross-linker and in some critical cases, calcium carbonate and can be used at temperatures up to 121 \({}^{\circ}\)C ([PERSON] et al., 2014).  
The setting of a magnesia cross-linked cement slurry is a chemical reaction activated by temperature as opposed to conventional cements that are set by hydration. A magnesia cross-linked cement slurry, as well as a regular cross-linked cement slurry, develop enough compressive strength to resist dynamic forces that will be generated while drilling or completion operations continue. They are also used as cement plugs. Positive results have been observed in field applications of both cement slurries.
# Microbes as Medicines: Harnessing the Power of Bacteria in Advancing Cancer Treatment
## 2 Mechanism of Tumor Suppression
### Bacterial Directed Enzyme Prodrug Therapy (BDEPT)
studied the bystander effect of various nitroaromatic prodrugs (metronidazolezole, CB1954, nitro-CBI-DEI, PR-104A, and SN27686) in combination with nitroroductase expressing _E. coli_ N/_sA_. It was observed that reduced metabolites of metronidazoleze, PR-104A, and SN27686 exhibited little cell to cell transfer while nitro-CBI-DEI and reduced metabolites of CB1954 passed it effectively. It was also demonstrated that 2-nitro reduction products showed substantially higher bystander effect as compared to 4-nitro reduction products [83]. [PERSON] et al. exploited the natural enzymolome of the wild-type probiotic bacteria such as _Escherichia coli_ Nissle, _Bifidobacterium breve_, _Lactococcus lactis_, and _Lactobacillus_ species to activate multiple prodrugs owing to their safety. _E. coli_ activated multiple drugs such as CB1954, 5-FC, AQ4N, and fludarabine phosphate simultaneously, and exhibited significant reduction in tumor growth in mice bearing subcutaneous CT26 murine colon carcinoma tumors. These findings demonstrated that wild strains of probiotic bacteria in conjunction with prodrug combinations were efficacious without the need for genetically engineering the bacteria [84].
## 5 Experiment Evaluation
### Positioning Satisfaction  
The VoD system enables the users to perform VCR operations and quickly search for interesting content. The users hope that the player resumes playing the video exactly from their designated point after the VCR operation. Positioning satisfaction is the indicator to evaluate the proximity of the designated point and the actual playback point.  
As shown in Figure 7, with the increase in number of VCR operations, the positioning satisfaction of the three strategies basically remains stable. The API strategy prefetches the original anchor points and popular segments. To a certain degree, the API strategy improves the positioning satisfaction. However, compared with the API strategy, the proposed DSA strategy in this paper improves the positioning satisfaction by approximately 60%.  
Figure 6: Average playback delay of different strategies.  
Figure 7: Average positioning satisfaction of different strategies.
## 3 Materials and Methods
### Data  
Level 2A images from the Sentinel-2 mission with relative orbits 79 and 122 were used for classification. Weather conditions in the study area only allowed the collection of 14 cloud-free images at unequal time intervals, which are presented in Figure 2. In addition, it was necessary to capture field information about crop types in a specific region. For this purpose, 14 field visits were conducted between the dates of 18 May 2020 and 11 April 2020 to properly identify crop types.  
Field inspection showed that in the study area there were seven crop types: beetroot, potato, canola, sunflower, maize, winter wheat, and rye. In total, 54 fields were identified, including 2 beetroot fields, 13 potato fields, 1 canola field, 4 sunflower fields, 17 maize fields, 15 winter wheat fields, and 2 rye fields. These data were used for training and testing the dataset.
# An Improved Skewness Balancing Filtering Algorithm Based on Thin Plate Spline Interpolation
## 5 Conclusions  
Diverse changing terrain environments and complex parameter settings pose great challenges to airborne LiDAR filtering. To improve the accuracy and automation of the filtering method, this paper proposed an improved skewness balancing filtering algorithm based on thin plate spline  
Figure 11: Comparison of total errors of other four improved filters for the seven samples.  
Figure 10: Comparison of type II errors of other four improved filters for the seven samples.  
Figure 9: Comparison of type I errors of other four improved filters for the seven samples.  
interpolation. Our experiments indicate that the proposed method can achieve good filtering performance without parameter settings. Thus, this method can be easily applied by inexperienced researchers. In comparison with the other eight filtering methods tested by the ISPRS, the proposed method also outperforms most of these methods. Although the average total error of the proposed method is slightly larger than that of the PTD method proposed by [PERSON], the proposed method has a high degree of automation. Furthermore, this paper also compared the results of some other recently proposed improved methods. The comparisons indicate that the proposed method in this paper can achieve the smallest type I error. Thus, a better DTM can be generated using the filtering result since there are fewer non-ground points that are misclassified. Moreover, the total errors for the seven samples are also small. Therefore, the proposed method can achieve promising and comparable performance when faced with diverse landscapes. However, the Type II error of the proposed method is slightly larger. Especially in areas with complex objects, the proposed method may erroneously accept some nonground points as ground points. This problem can be overcome by cooperating with segmentation methods in future research.  
[PERSON] had the original idea for the study. [PERSON] drafted the manuscript. [PERSON] and [PERSON] contributed to improvement of the original idea and revision of the manuscript. [PERSON], [PERSON] and [PERSON] performed the experiments and experimental analysis.  
This research was funded by The National Key Research and Development Program of China (2017 YFB0503704), National Science Foundation (NSF) (41801325, 41861052, 41601416), Education Department of Jiangxi Province (GJJ170449), Key Laboratory for Digital Land and Resources of Jiangxi Province, East China University of Technology (DLIJ201806), East China University of Technology Ph.D. Project (DHBK2017155) and the Spark planning project of Jiangxi Province (20161 BBB9002), Key Laboratory of Watershed Ecology and Geographical Environment Monitoring, NASG (WE2016006).  
The authors express their appreciation to the anonymous reviewers for their valuable suggestions.  
The authors declare no conflict of interest.
## 3 Proposed Receiver
### ICI Mitigation  
As in related works [3; 23; 25], an iterative receiver is proposed, in which the estimated data can be reused to perform interference cancellation in the data, attaining an improved channel estimation in the next iteration. Mathematically, the estimated data in a \(it\)-th iteration can be described recursively as:  
\[\mathbf{u}_{it}^{k}=\mathbf{u}_{it-1}^{k}-[\hat{\mathbf{G}}_{it-1}^{k}]_{\tau}\mathbf{s}_{it-1} ^{k}, \tag{29}\]  
where the sub-index \(it=\{0,1,2,\ldots\}\) denotes the iteration number; \(\mathbf{u}_{it}^{k}\) is the \(k\)-th received signal, \([\hat{\mathbf{G}}^{k}]_{\tau}\) is the estimated channel matrix with null elements in the main diagonal and \(\mathbf{s}_{it-1}^{k}\) the received signal of the previous iteration.  
Figure 3: Plot of an example of \(\|\mathbf{K}\|^{2}\) in dB, where the quasi-band structure of \(\mathbf{K}\) in V2V-DSC allows application of a matrix truncation with \(\lambda+1\) strips.