esa-sceva/satcom-chunk-collection huggingface dataset:
# Agricultural Residue Management for Sustainable Power Generation: The Poland Case Study
## 1 Introduction
### Power Generation in Poland  
In 2018 total energy consumption of Poland was 4490.7 PJ. The country produces its own energy resources which cover 60% of the national energy requirements. The share of renewable energy reached 8.2% of the total energy consumption [31].  
National electricity generation is growing, and in 2018 it was 170.04 TWh. Coal-based power plants generate over 80% of electricity. Around 21.58 TWh of electricity were generated by renewable energy sources (Figure 1). Their share exceeded 12% [31; 32]. Meanwhile, since 2015 electricity generated by biomass and biogas has decreased (Figure 1). In 2018 their share fell from 59.8% in 2012 to 30.2%.  
The main problem of the energy sector is its transition to meet national environment and climate policies. This process is regulated by the Energy Law Act [33]. The Polish power industry is regulated by two primary documents: The National Renewable Energy Action Plan [34; 35] and the Energy Policy of Poland until 2030 [36]. They stipulate gradual diversification of fuels and an increase in the share of renewable energy resources in power generation. The development of renewable energy utilization is supported by the Energy Law [33]. The National Renewable Energy Action Plan comprises four sources of biomass: forestry, agriculture (energy crops and residues), municipal and industrial waste. It must be emphasized that biomass production in agriculture should not compete for arable land with f  
Figure 1: Renewable electricity generation.  
Agriculture generates a significant volume of organic residues. They are valuable feedstock for energy production. Thus, agriculture can become a significant producer of renewable energy. It is important to reveal still underestimated sides of agricultural residues-based power generation. All in all, there are still knowledge gaps concerning agricultural residue resources, their spatial-temporal distribution, and energy potential for energy cluster formation in Poland. The aim of this study is to determine agricultural residue energy potential on a regional level; select suitable regions for biomass-based power generation; determine the potential carbon dioxide emission savings.  
This paper is organized as follows. The Literature Review is elaborated in Section 2. The methods of this study are described in Section 3 (Materials and Methods). Section 4 (Results) comprises four subsections. Crop residue availability is analyzed in Section 4.1. Biogas production potential is estimated in Section 4.2. The impact of sugar beet leaf on total energy potential is studied in Section 4.3. Followed by a carbon dioxide emission saving is presented in Section 4.4. Conclusion remarks are given in Section 5. This study is based on previous authors' publications concerning cluster analysis of renewable energy resources [38; 39].
# Optimal Design and Control of MMC STATCOM for Improving Power Quality Indicators
## 8 Conclusions  
The compensation of harmonics is a major task in the modular multilevel converter (MMC). The Full-Bridge MMC block with 22 modules per phase is presented in this paper. The optimal design of the MMC capacitor and the optimized parameters of the PI controller were determined using HHO and ASO techniques. Moreover, two realistic representative cases of studies were designed and tested:  
Figure 23: The voltage and current at the grid side with an imbalanced load with MMC STATCOM.  
Figure 24: The voltage DC link of the MMC with an imbalanced load.  
nonlinear and imbalanced loads. The THD of the current before applying the proposed algorithm was 10.97%, where with the optimal values of the capacitor converters, the THD decreased to 0.60% by using the HHO algorithm, whereas THD decreased to 1.21% using the ASO. The results show that with the application of the MMC STATCOM, the voltage and current load are rapidly adjusted in the case of the imbalanced load. Moreover, the voltage DC-link of the converter has a stability value, and this will reduce the value of the current circulation within the converter. In the two cases of nonlinear and imbalanced loads, the voltage in the DC-link has a stabilized value, and this, in turn, improves the performance of the control system and the power quality indicators in the studied network. In addition, the application of the MMC in grid-connected photovoltaic and wind energy systems and micro grids is also an important issue for our future works. In spite of this, the study of this topic is outside of the framework of this paper, and it can be covered in future works. Finally, the authors would like to remark that, due to the lack of laboratory equipment and apparatus with the high voltage rating, the real time implementation of the proposed algorithm was not performed. However, in future work, one of the aspects of our work will be to experimentally implement the presented control system. Additionally, future work will present the application of other control algorithms to achieve an improvement of the overall system performance.  
Conceptualization, A.A.Z.D. and R.A.; Data curation, H.M.S. and Z.M.A.; Formal analysis, A.A.Z.D. and H.M.S.; Methodology, T.E., A.A.Z.D. and R.A.; Resources, A.A.Z.D., R.A. and Z.M.A.; Software, H.M.S.; Supervision, A.A.Z.D.; Validation, T.E. and A.A.Z.D.; Visualization, A.A.Z.D., H.M.S. and Z.M.A.; Writing--original draft, T.E., A.A.Z.D., R.A. and H.M.S.; Writing--review & editing, A.A.Z.D., R.A. and Z.M.A. All authors together organized and refined the manuscript in the present form. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The authors declare no conflict of interest.  
References
## 2 Materials and Methods
### Data Collection and Tool  
The data were collected by trained research assistants between August 2019 and December 2019, using a modified WHO STEPwise questionnaire, which included demographic information (personal and household), lifestyle factors (tobacco and alcohol use) and physical measurements (anthropometry and blood pressure) [41] (see supplementary file). For quality assurance, the questionnaire was validated through content and face validity, independent translators, a pilot study and the training of research assistants [42]. Three readings were conducted for both systolic (SBP) and diastolic (DBP) blood pressure using an Elite 1219 Blood Pressure Monitor (Shanghai International Holding Corp. GmbH (Hamburg, Germany), adhering to standard procedure [43]. The average of the last two readings was used as a participant's blood pressure [44], hypertension was defined at SBP \(\geq\) 140 mmHg and/or DBP \(\geq\) 90 mmHg for hypertension [18], high SBP was \(\geq\)140 mmHg and high SBP was \(\geq\)90 mmHg. Weight, height, and waist and hip circumferences were measured according to the WHO recommendations [45] using a smart D-quip electronic scale, stadiometer and non-stretchable tape measure, respectively, and to the nearest 0.1 kg, 0.1 cm and 0.1 cm, respectively. BMI was calculated by dividing an individual's weight in kilograms (kg) by height in meters squared, and overweight was defined as BMI \(\geq\) 25-29.9 kg/m\({}^{2}\) and obesity as BMI \(\geq\) 30 kg/m\({}^{2}\), while abdominal obesity was indicated by WHtR of \(\geq\)0.5 [46], WC \(\geq\) 90 cm and WHt \(>\) 0.90.
## 4 Results and Discussions
### Crash Analysis of Oromia Region  
#### 4.3.1 Number of Deaths Due to RTCs in the Oromia Region  
According to the Oromia traffic police bureau's eight-year (2010-2017) crash database record, fatalities that occurred due to RTCs had shown an increasing trend. Despite population growth, the number of crash fatalities increased by more than double from 906 in 2010 to 1882 in 2017 (see Figure 5a). The Ethiopian Federal Transport Authority has stated that there has been significant motor vehicle growth in the Oromia region, which has a strong correlation with the increased fatalities [60]. According to the Oromia Traffic Police Bureau crash data, denying priority for pedestrians pass, unsafe vehicle passing, driver's alcohol and drug consumptions, over-speeding, driver workload, insufficient vehicle following time and vehicle problems are the recognized significant factors for the increasing number of deaths in Oromia [67]. This increase in fatalities in the region demonstrates the impact of road traffic crashes on the socio-economic well-being of the country as a whole and the Oromia region in particular. To minimize road traffic crashes and their consequences, the Oromia transport bureau, traffic management, traffic police, road authority and concerned governmental and non-governmental organizations should all work together to address this serious problem. Figure 5a depicts the number of RTC fatalities in the Oromia region over eight consecutive years.  
Male fatalities were 2.7 times higher than females (Figure 5). According to the population census commission's 2007 survey, the percentage of males and females in Oromia was roughly equal; moreover, males accounted for 73% of the region's road traffic crash victims. This can be explained by the fact that, in comparison to females, males have greater exposure to road transportation as drivers and passengers for a variety of reasons. For example, males are over-represented in professional driving careers (i.e., jobs in remote areas, operators, taxi, nighttime driving and so on) and females are under-represented in self/paid employment or outdoor activities in Ethiopia [68], which could reduce female vulnerability to RTCs. Furthermore, males are more likely than females to engage in risky driving behaviors such as careless overtaking, the use of alcohol, impatience, exceeding posted speed limits and having a lower risk perception [69; 70]. As compared to females,
## 4 Discussion  
The pre-processing of our method is relatively complicated, as the round-trip TM of a scattering medium should be measured prior to image the object, which will usually take a few minutes. However, this is just a one-time procedure, once calibrated, the TM is effective continuously as long as the medium has not been disturbed.  
Our method is effective for imaging through the thick scattering medium, and it does not involve any scanning operations during the imaging process. Therefore, it probably has potential applications in some new fields. On one hand, one can monitor the target through an apparently opaque screen (used as a barrier), while it is incapable of being observed by it. On the other hand, instead of as a barrier which undermines the imaging ability, a scattering medium can also be used actively as an imaging sensor. For example, the single multimode optical fiber, as a scattering medium due to the mode dispersion, could potentially open up new, less invasive forms of endoscopy to perform high-resolution imaging of tissues out of reach of current conventional endoscopes [19; 25; 26].  
Figure 6: (a) Intensity (amplitude) distribution of the illumination wave. (b) Amplitude of the object. (c) Amplitude of the reflected wave. Scale bar: 550 \(\upmu\)m.  
At present, the preliminary result shows that our method has the ability to recover the complex amplitude information of the object. However, as an early study, no real 3D object has been tested yet. In fact, many problems should be further resolved when imaging a real 3D object. For example, the \(2\pi\) ambiguity problem when there is an abrupt change in surface height of the object. This problem could can be solved if the size of the DMD segment that used to measure the TM is further reduced.
## 4 Simulation and Analysis of Magnetic Field Distribution
### Magnetic Field Distribution for Offset Coils
#### 4.2.3 Magnetic Field Distribution of Offset Coils  
Similar to the simulation results of alignment, the magnetic field distribution under different offset conditions are obtained, the result of maximum magnetic field distribution is shown in Figure 15. The axial plane of coils and the central axis of driver's seat are selected as an observation plane. It can be seen that as offset increases, the magnetic field of axial plane of coils moves to the left. The distribution  
Figure 14: Phase of the primary current: (**a**) phase of the primary current at test point A3; (**b**) relationship between the offset and the phase of the maximum magnetic field.  
Figure 13: Currents of primary and secondary coils.  
of magnetic field becomes irregular, and the area of a red region with a larger magnetic field also decreases, which may reduce the transmission efficiency. Correspondingly, the energy transmission area will move towards the axial plane of the seat. Areas with high magnetic field strength are mainly distributed under the chassis of the vehicle, and the magnetic field strength inside the vehicle body is much smaller. Figure 16 is obtained based on the magnetic field strength of six test points in five offsets except A1.  
Apart from A1 located in the transmission region, the magnetic field strength at A3 is larger than 30.4 A/m required by SAE J2954 at 40% offset and 50% offset. The magnetic field strength under other offsets are not exceeded. The effective magnetic field between the coupling coils decreases with the increase of the offset. When the offset ratio exceeds 10%, the magnetic field of A2 drops greatly, which is close to a negative correlation. When the offset is less than 20%, the field at A3 is nearly invariable. However, after this ratio is exceeded, the amount of magnetic field leakage continues to increase, and after more than 40%, the exceeding strength appears. As the offset increases, the primary coil on the ground gradually approaches A3, making A3 close to the energy transmission region. However, while A4 is far away the coils, the offset has little effect on it. Since the vehicle body is an enclosed conductor, the magnetic field strength of B1, B2, B3 has little fluctuation with the offset, and maintains less than 1 A/m.  
Figure 16: Magnetic field strength: (**a**) test points of A2, A3, A4; (**b**) test points of B1, B2, B3.  
Figure 15: Magnetic field distribution: (**a**) 10% offset—60 mm; (**b**) 30% offset—180 mm; (**c**) 50% offset—300 mm.
# On Simulating the Propagation and Countermeasures of Hate Speech in Social Networks
## 6 Simulation Results
### Countermeasures Simulation Results
#### 6.2.3 Counter Activism  
In the case of counter activists (see Section 5.3), we used five different simulation setups with the aim of increasing the strength of the counter movement. Table 2 details how these setups where parameterised. Specifically, the strength of the counter movement strictly increases from setups #1, #2, #4, and #5 due to subsequent increases of the convincing probability \(p_{convince}\), the number of activists' connections \(c_{a}\), the inclusion of stubbornness,  
Figure 9: Effects of deferring hateful content as countermeasure for different network sizes (0, 500, 1000, 2000, 5000) and depending on \(p_{defer}\), the probability of deferring hateful posts: (**Top**) fraction of hateful users; (**Middle**) fraction of hateful posts; (**Bottom**) fraction of swaps to a hateful society.  
and the selection of activists by their influence, respectively. Setup #3 is in fact a variation of setup #2, as it has higher convincing probability but less connections.  
Surprisingly, none of those simulations lead to a clear decrease of hateful users as depicted on the top of Figure 10, where values fluctuate within the [0.025, 0.08] interval for the different network sizes. Exceptionally, a decrease could be only recorded for settings with bigger networks over 5000 users in setups 2-4. The same happens to the fraction of swaps to a hateful society, whose values fluctuate in the [0.03, 0.41] interval for different setups and network sizes.  
Even so, a drop of the mean hate score was recorded--especially for the settings with stubborn activists--as seen on the middle of Figure 10, the mean hate score drops from ca. 0.4 to values within the interval [0.21, 0.32]. Thus, activists seem to create higher polarisation within the society by dragging some persons into the positive direction without affecting hateful persons. This depletes representatives of the median opinion, so that people with higher hate scores are rather attracted by very hateful users.  
Additionally, the bottom of Figure 10 plots an increase in the mean path length of activists' posts from values below 0.9 up to values of ca. 3.4. This can be attributed to the strengthening of the counter movement and replicates the tendency of activists to mimic the behaviour of hateful users. Overall, our simulations seem to suggest that activism needs to be carried out in a very sensible way. Otherwise, it may not lead to the desired results.  
Figure 10: Effects of counter activists as countermeasure for different network sizes (0, 500, 1000, 2000, 5000) and for the five different setups from Table 2: (**Top**) fraction of hateful users; (**Middle**) mean hate score; (**Bottom**) mean path length of activists’ posts.
## 2 Results and Discussion  
### Identification and Quantitation of Compounds and OAV Analysis  
The compounds were identified by comparison of retention index (RI), odor descriptors with authentic standards, as shown in Table 1(a). In this study, 37 odorant compounds were detected after the GC-O analysis of RRT samples. The different AIs of the volatile compounds in each of the samples were mainly induced by concentration differences of these compounds. The AIs of the compounds ranged from 0.2 to 5. Ethyl butanoate exhibited the highest AI in RRT samples. Esters were shown to be the largest class of aroma compounds in the RRT fruit samples. Thirteen esters were identified, which are summarized in Table 1(a). These included ethyl acetate, ethyl 2-methylpropanoate, ethyl butanoate, ethyl 2-methylbutanoate, 3-methyl butylacetate, ethyl hexanoate, ethyl 2-methylcroonat, ethyl 3-hexenoate, ethyl heptanoate, ethyl E-2-hexenoate, ethyl octanoate, ethyl benzoate, and ethyl cinnamate. Esters were generally associated with fruity notes in the sensory descriptions from panelists. These esters were widespread in many fruits [16; 17; 18]. Higher AI values, presented in four compounds, ethyl 2-methylpropanoate, ethyl butanoate, ethyl 2-methylbutanoate, and ethyl hexanoate, which were the most powerful odor-active compounds contributing to the aroma profile of RRT fruit, were identified to be primarily responsible for aroma in several cultivators.
## 4 New Electronic Control System of the Receiver for the Installation on SRT  
The original control system of the ex-PdBI receiver consists of three control boards developed by IRAM, two of which are used to control the SIS mixer (and the Gunn-based local oscillator) and the other being dedicated to the management of the calibration system. All boards are connected to a VME-based microprocessor using an Ethernet link. These control boards are devoid of on-board intelligence and they are unable to operate in a telescope such as the SRT, where the remote control of the receiver is essential. Therefore, a new ad hoc electronic control system has been designed and developed to make the receiver suitable for the SRT.  
The new electronic control system is composed of a Raspberry Pi 2 (Model B) [42], which serves as the brain of the system and controls three different Arduino UNO REV3 microcontrollers, based on Atmel ATmega 328P [43]. Each Arduino UNO REV3 microcontroller manages one or more electronic boards dedicated to a specific function for the receiver operation: biasing the SIS mixer, controlling the receiver calibration system, and biasing and tuning the ALMA local oscillator. The Raspberry Pi 2 board permits linking of the receiver to the SRT software control and managing and it consequently makes remote control of the receiver available. The architecture of the electronic control system is illustrated in Figure 5. Table 1 summarises the technical features and functioning of each subsystem.  
Figure 5: Architecture of the new electronic control system.  
All components of the new control system are integrated into a unique rack, which can be installed close to the cryostat. With the aim of reducing the self-generation of radio frequency signals, which represents a noise for the radio astronomy observations performed with others SRT receivers (i.e., P, L, C, and K frequency bands [18; 19; 20]), all electronic boards are enclosed in aluminium boxes.
# Painting Path Planning for a Painting Robot with a RealSense Depth Sensor
## 4 Wall Extraction Algorithm
### Statistical Filter  
The first operation for the given point cloud before the wall extraction step was to apply a statistical filter to remove unnecessary, noisy gross outlier data. Namely, stereo cameras generated point clouds of varying point densities and the resulting point clouds had sparse outliers that corrupted the results. This complicated the estimation of local point cloud characteristics, such as surface normal or curvature changes, leading to incorrect values, which in turn could cause point cloud processing failures.  
The applied filter used point neighborhood statistics to filter outlier data [30]. The sparse outlier removal step corrected these irregularities by computing the mean and standard deviation of nearest \(k\) neighbor distances and pruning the points that fell outside the calculated threshold \(t\):  
\[t=\mu\pm\alpha\sigma \tag{1}\]  
Figure 2: A block diagram of the wall extraction algorithm.  
where \(\mu\) is the mean, \(\sigma\) is the standard deviation, and \(\alpha\) is the multiplier. The value of \(\alpha\) depends on the size of the analyzed neighborhood [30]. The values of \(k\) and \(\alpha\) are set experimentaly. For instance, if 1% of point cloud points are considered as noise outliers, one example would be \(\alpha=1\) and \(k=30\), because experiments with multiple datasets have confirmed the applicability of the \(\mu\pm\sigma\) threshold as a good practice [30].  
Basically, the filtering algorithm iterates through the entire input point cloud twice. During the first iteration, it computes the average distance that each point has to its nearest \(k\) neighbors [29]. Further, the mean and standard deviation of all these distances are computed in order to determine a distance threshold. During the second iteration, the points can be classified as either inliers or outliers if their average neighbor distances are below or above the threshold, respectively [30].
## 3 Results and Discussion
### Basic Electrical and E-Field Characterization of Plasma Source
While the discharge peak is still proven to result from the discharge between the two ring electrodes around the capillary, the guided streamers leaving the system follow shortly after [67]. This correlates with the observed peaks in the electrical field strength measurements that are delayed by few microseconds from the main discharge peak. Figure 4: Electrical field strength as function of applied voltage for Ar-CAP and He-CAP (**left**) and for He-CAP as function of distance from the G1 electrode to 10 mm in front of the exit nozzle (**right**). The EO-probe was moved axially to the CAP tube and measurements were made at the nozzle exit (‘b’ = 0 mm), at 5 mm away from nozzle (‘c’), at 10 mm away from nozzle (‘d’) and near the ground electrode, on the tube at \(-5\) mm from the nozzle exit (positioned instead of the letter ‘a’), exactly as in the right figure (orange circles = EO-probe). Figure 3: The applied voltage, discharge current and electrical field data for the Ar (**left**) or He (**right**) CAP facing a dielectric surface at a distance d = 10 mm (probe head). The probe is actively placed into the discharge channel and the dielectric surface acts as a third electrode, including charging and discharging through the plasma channel as measured previously [66]. While the maximal value correlates with measured and simulated values from other groups in helium or argon discharges [64; 68; 69; 70], the high plateau is interpreted to result more from charge accumulation than from ongoing discharge dynamics.