esa-sceva/satcom-chunk-collection huggingface dataset:
# Trends in Compliance Monitoring Devices (CMDs) in Ships' Ballast Water Treatment Systems
## 2 A Holistic Approach to Monitoring Threats to the Environment in Ballast Water
### The Ballast Water Testing Skid (Ship Tank-to-Tank)  
A case study was conducted by [PERSON] et al. comparing a ballast water testing skid against some traditional ballast water testing devices. They ran an experiment testing the skid against the manhole, sounding pipe and plankton net. After testing for various organisms, they found that though sampling with a skid slowed down the flow of the water being tested and thus provided a more stable and reliable result, the skid results did not have a significantly different result compared to other testing methods. In their case study, the authors provide valuable insight on selecting the most accurate method of testing ballast water, as ship conditions and laboratory conditions may significantly affect the result and thus give a wrong reading. The case study has many invaluable insights, one of which is ensuring that the testing methods selected are up to the International Organization for Standardization (ISO) Ships and Marine Technology standards, in particular, Ships and Marine Technology (Aquatic Nuisance Species) Part 1: Ballast Water Discharge Port, ISO 11711-1 (2019) [27]. The ISO standard is held in high regard by the authors as they also submit that best way to test treated ballast water is the tank-to-tank method, thus minimizing all chances of discharging non-compliant water into the sea [28].
## 2 Performance Degradation Analysis of Space TWTA
### Analysis of Anode Voltage Degradation Characteristic  
From above, the vacuum degree in the tube and the degradation degree of the cathode are the main factors affecting the life of the space TWTA. When the vacuum degree in the tube is good, the degradation degree of the cathode directly determines the life of the space  
Figure 1: Constructional structure of the TWT.  
TWTA. From the output power \(P_{0}=I_{k}\times V_{H}\times\eta_{e}\), where \(I_{k}\) represents the cathode emission current, \(V_{H}\) is the helix voltage, and \(\eta_{e}\) means the electron efficiency, we can find that the decrease of the cathode emission current is the main reason for the decline of the output power of the TWTA with the increase in the working time. To protect the cathode emission current from falling too fast to affect the drop of the output power of the TWTA, it is usually used to improve the modulated anode voltage to increase the cathode emission current. Within the modulation range, the anode voltage increases monotonically with its rising rate and amplitude, mainly characterizing the degradation of the cathode performance of the TWTA.
## 2 Data Collection and Preprocessing
### Climate Factor Data  
The climate factor data, which is used extensively in the modeling and prediction of the glacier variations, is time series data collected by several different sensors. The specific factors selected for the analysis were temperature in degrees Celsius, Carbon Dioxide (CO\({}_{2}\)) concentration in parts per million (ppm) and Precipitation in millimeters (mm). Each of these factors were collected by the appropriate national agencies with daily sampling frequency in the regions containing the glaciers in this study.  
Daily climate data was collected from the weather station closest to Franz Josef and Gorner glaciers from the National Oceanic and Atmospheric Administration Climate Data Online platform available at [[https://www.ncdc.noaa.gov/cdo-web/datasets/GHCND/stations/GHCND:NZ000936150/detail](https://www.ncdc.noaa.gov/cdo-web/datasets/GHCND/stations/GHCND:NZ000936150/detail)]([https://www.ncdc.noaa.gov/cdo-web/datasets/GHCND/stations/GHCND:NZ000936150/detail](https://www.ncdc.noaa.gov/cdo-web/datasets/GHCND/stations/GHCND:NZ000936150/detail)) (accessed on 7 July 2022). The data for Franz Josef was taken from the Hokitika Aerodrome weather station in New Zealand and spans the two decades from 1989 to 2009. For the Gorner glacier, the dataset was from the Sion weather station in Switzerland spanning from 1985 to 2009. The dataset contains daily information on minimum, maximum, and average temperate, and precipitation. To attain comparable resolution for the response, i.e., glacier variations estimated using spatiotemporal satellite imagery, and the predictors, i.e., climate factors, monthly data was calculated by averaging observed daily climate factors in the data preprocessing phase.  
To assess the predictive viability of CO\({}_{2}\) on glacier variations in the modeling process, the monthly Mauna Loa CO\({}_{2}\) average data was sourced from NOAA. The sourced data contains monthly average CO\({}_{2}\) levels from March 1958 to May 2021 recorded at the Mauna Loa station in Hawaii. The data is a proxy for many other human activities that contribute to climate change and the warming temperatures on the globe. Local temperature for each glacier was sourced from the closest regional station. An overall monthly global average temperature was also calculated in order to assess the overall temperature variations. A monthly data set was utilized from NOAA which contains samples of the monthly average temperature from January 1880 to December 2021. The result is a data set which contains a total of six predictors measured at both the global and local levels. Next, glacier variations (estimated either by detected terminus or by quantified area) will be modeled in response to monthly measurements of the predictors of interest (aforementioned data) for identification of potential relationship between temporal glacier variations and climate factors.
# Mechanically Reconfigurable, Beam-Scanning Reflectarray and Transmitarray Antennas: A Review
###### Abstract
Finally, mechanically reconfigurable unit cells tend to have a wider range of re-radiated phase change, significantly reducing the phase quantization error. In this paper, we review the state-of-the-art of mechanically reconfigurable beam-scanning RAs and TAs. We categorize the mechanically reconfigurable architectures into four categories: (i) element movement, (ii) array movement, (iii) feed movement and (iv) a hybrid category that represents combinations of the first three categories. We discuss  
Figure 1: The geometry of a reflectarray antenna consisting of a feed antenna and a single planar aperture consisting of numerous spatial phase shifters. the advantages and disadvantages and typical performance metrics of each approach, including illustrative examples. We note that some of the approaches, especially element movement approaches, rely on the performance of actuators. Such actuators can be designed for various applications ranging from precision micron control of fragile optical components to the displacement of large masses [1]. This presents opportunities for the further development of mechanically-reconfigurable agile beam scanning RAs and TAs.
## 5 Simulation Results and Discussion
### Results under Varying outdoor Temperature  
In this case, if solar irradiance is maintain fixed i.e., 1000 W/m\({}^{2}\), and outdoor temperature is continuously changed, the obtained observations are depicted in Figure 14. It is clearly seen in the Figure that generated voltage from FFNN with changing outdoor temperature profile is successfully tracked using the developed AOSMC. However, an overshoot of 7 V was observed (See Figure 15). Similarly, for varying temperature levels, the PV system output power is presented in Figure 16, which portrays that the maximum power was obtained in 0.01 s without oscillations.  
Figure 12: Tracking the PV voltage under varying irradiance.  
Figure 13: PV output power under varying irradiance.  
Figure 16: The PV output power under varying temperature.  
Figure 14: Varying levels of temperature.  
Figure 15: Voltage tracking in PV system under varying temperature conditions.  
From both of the above cases, it is evident that the proposed AOSMC can extract the maximum power, which is transmitted with 98 % efficiency to load under changing temperature and irradiance levels. To evaluate performance of the developed controller, the backstepping controller [26] is considered as a benchmark under similar changing conditions.
## 4 Case II: Active Eavesdropper
### Mean Square Error (MSE) Performance  
#### 4.3.1 MSE at the Legitimate Receiver User A  
First of all, Figures 15 and 16 illustrate the MSEs of the SI channel and the main channel at user A for the blind feedback scheme and the semi-blind feedback scheme, respectively, versus \(SNR_{A}\) for different power values of the jamming-to-noise ratio \(\rho_{EA}\) broadcast from user E, while the self-interference-to-noise ratio at user A, \(\rho_{AA}\), is fixed at 30 dB. It can be seen that the presence of the jamming signal from user E significantly impacts the SI channel estimation at user A, where it increases the noise level at the receiver side at user A, compared with the passive case. Indeed, the gain between each MSE's curve is bigger than in the passive case, whatever the algorithm used, which means that the system requires higher \(SNR_{A}\) to estimate the channel. Furthermore, the semi-blind feedback scheme outperforms the blind feedback scheme, i.e, it converges faster to the error floor and achieves better results than the blind feedback scheme because the traces of four pilot symbols is used. Therefore, using the semi-blind algorithm can improve the channel estimation processes and reduce the impact of the jamming signal from the eavesdropper.
### Benefits of Incorporating Notch Structure  
The performance of an antenna and its ability to suppress interference in the 4.4-5.7 GHz band can be greatly improved by incorporating a notch structure. This is especially true in terms of bandwidth augmentation. Enhanced Bandwidth: a notch structure can reduce undesired frequencies in an antenna's operational spectrum. This suppression allows the antenna to operate over a wider bandwidth, making it more versatile and adaptable to different communication needs. Adding a notch structure improves antenna gain, radiation pattern, and impedance matching [21]. The notch reduces resonances and standing waves, making the antenna more stable and efficient. Interference mitigation: multiple wireless communication systems coexist in the 4.4-5.7 GHz region, making interference difficult. The notch structure can target specific interfering frequencies to reduce interference and improve the antenna's capacity to receive and transmit signals in noisy environments. Notch structures can dynamically target different interfering frequencies, allowing frequency reconfigurability. This versatility is crucial when the interference landscape changes or numerous frequency bands are needed.
# Internet of Things Geosensor Network for Cost-Effective Landslide Early Warning Systems
## 1 Project Overview Inform@Risk
### Geology and Landslide Processes  
The geology of Medellin is dominated by magmatic and metamorphic rocks, as well as landslide debris and alluvial deposits. In the east of the city, amphibites and dunites are the predominant rocks. The Medellin Dunite is primarily serpentinized and highly fractured due to tectonic processes. This leads to complex weathering profiles, which makes the dunite particularly prone to landslides [19]. Geophysical investigations have shown that the weathering depth can reach up to 50 m in some areas [20]. On top of the bedrock, residual soil (saprolite) alternates with slope deposits (colluvium) of varying depth. While the saprolite is usually clay dominated and free of stones and blocks near the surface, the composition of the slope deposits can vary greatly. It can best be described as \"block in matrix\" material, where many stones and blocks are embedded in a clay dominated matrix. Overall, the soil profile on top of the weathered dunite is very complex and heterogeneous.  
As geological and morphological mapping of the project area has shown, the prevalent landslide process is rotational sliding, followed by a comparably small number of translational slides, debris flows in the creeks and minor rockfall at the few rock outcrops within the project area [18]. The slides usually are of small to medium size and depth (up to about 50 m in length and width, and up to 10 m deep). Due to the geological heterogeneity of the subsurface, it is impossible to predict exactly where future slides within the soil cover might occur. However, mainly based on the depth of soil cover (colluvium and saprolite) and the slope inclination it is possible to spatially differentiate the level of landslide hazard throughout the project area. Regarding the velocities of the landslides, we expect initial slow to moderate movements, which can accelerate to rapid and very rapid movements, depending on the water saturation [21].
## 5 Experimental Results
### Learning Motivation  
Table 4 gives the results of the Mann-Whitney U test for learning motivation of the two groups. As can be seen from the results, there is no significant difference in intrinsic motivation (\(p=0.164\)) and extrinsic motivation (\(p=0.992\)) between the two groups before the experiment. However, after the experiment, significant differences were observed between the experimental and control groups in both intrinsic and extrinsic motivation. This suggests that the game-based AI chatbot is more conducive to improving learners' intrinsic and extrinsic motivation than the traditional AI chatbot.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline  & **Group** & **N** & **Mean** & **Mean Rank** & **U** & **Z** & \(p\) \\ \hline intrinsic motivation & CG & 39 & 3.48 & 35.54 & 606 & \(-1.391\) & 0.164 \\ (pre-test) & EG & 38 & 3.72 & 42.55 & & & \\ \hline intrinsic motivation & CG & 39 & 3.8 & 31.12 & 433.5 & \(-3.174\) & 0.002 ** \\ (post-test) & EG & 38 & 4.27 & 47.09 & & & \\ \hline extrinsic motivation & CG & 39 & 3.7 & 39.03 & 740 & \(-0.01\) & 0.992 \\ (pre-test) & EG & 38 & 3.75 & 38.97 & & & \\ \hline extrinsic motivation & CG & 39 & 3.85 & 33.73 & 535.5 & \(-2.13\) & 0.033 * \\ (post-test) & EG & 38 & 4.21 & 44.41 & & & \\ \hline \hline \end{tabular}  
* \(p<0.05\), **_p_\(<0.01\).  
\end{table}
Table 4: The Mann–Whitney U test results for the two groups’ learning motivation.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline  & **Group** & **N** & **Mean** & **Mean Rank** & **U** & **Z** & \(p\) \\ \hline problem-solving tendency (pre-test) & CG & 39 & 3.46 & 37.27 & 673.5 & \(-0.693\) & 0.489 \\ \hline problem-solving tendency (pre-test) & EG & 38 & 3.67 & 40.78 & & & \\ \hline problem-solving tendency (post-test) & CG & 39 & 3.65 & 30.96 & 427.5 & \(-3.216\) & 0.001 ** \\ (post-test) & EG & 38 & 4.16 & 47.25 & & & \\ \hline computational thinking (pre-test) & CG & 39 & 3.12 & 35.35 & 598.5 & \(-1.462\) & 0.144 \\ (pre-test) & EG & 38 & 3.39 & 42.75 & & & \\ \hline computational thinking (post-test) & CG & 39 & 3.57 & 32.12 & 472.5 & \(-2.757\) & 0.006 ** \\ \hline creative tendency (pre-test) & EG & 38 & 3.97 & 46.02 & & & \\ \hline creative tendency (pre-test) & CG & 39 & 3.49 & 38.77 & 732.0 & \(-0.093\) & 0.926 \\ (post-test) & EG & 38 & 3.61 & 39.24 & & & \\ \hline creative tendency (post-test) & CG & 39 & 3.81 & 39.97 & 703.0 & \(-0.391\) & 0.696 \\ (post-test) & EG & 38 & 3.78 & 38.00 & & & \\ \hline \hline \end{tabular}  
* \(p<0.01\), **_p_\(<0.001\).  
\end{table}
Table 3: The Mann–Whitney U test results for the two groups’ higher-order thinking skills.
## 3 Results
### Morning and Afternoon Transitions of the Urban Boundary Layer
#### 3.3.2 WS and Vertical Variance Profiles  
Composite vertical profiles of WS and \(\sigma_{w}^{2}\) averaged in the three wind classes during the MT and AT periods are illustrated in Figure 9. For the median WS profiles, WS was mostly below 5 m s\({}^{-1}\) and 7 m s\({}^{-1}\) for weak and moderate wind classes, respectively, while it could reach 17 m s\({}^{-1}\) at about 1400 m for the strong wind class. Obviously, during MT, low-level jet (LLJ) was detected in all three wind classes, which was mainly attributed to large- and local-scale forcings, e.g., synoptic pattern, local topographic flows, buoyancy, friction, and entrainment processes [69; 70; 71]. For the weak wind class, an LLJ occurred at about 400-600 m. Previous studies have revealed that the LLJ can affect the transition of aerosol pollutants via advection flow and vertical mixing [72; 73]. A southwesterly LLJ was found in [29], with the jet core at 300-500 m, which might have transferred polluted air from the south via advection to Beijing on 2 December; plus, this LLJ also generated significant wind shear, which could have mixed transported and local pollutants via vertical mixing. In our study, the vertical changes in the wind profile were smaller for weak and moderate wind classes in both the MT and AT periods.  
For \(\sigma_{w}^{2}\), its value was smaller in the MT period than in the AT period (Figure 9), suggesting that the vertical mixing intensity for MT was obviously weaker than for AT for all wind classes. Specifically, the median values of \(\sigma_{w}^{2}\) were \(<\) 0.1 m\({}^{2}\) s\({}^{-2}\) for MT, while at AT they could reach 0.35 m\({}^{2}\) s\({}^{-2}\). During the AT period, there was an increasing \(\sigma_{w}^{2}\) between 150 m and 300 m, which can be explained by the strong wind shear as mentioned above. Combined with Figure 7e, it can be clearly seen that weak vertical mixing accompanied high PM\({}_{2.5}\) concentrations.  
Figure 8: Schematic illustration of the diurnal cycle of the atmospheric boundary layer (ABL) over Beijing on 19 December 2016.
## 4 Discussion
[17] showed good correlations between NDVI with extreme climate indices (P \(<\) 0.01), such as TXn, TNn, TXx, TNx, TMAXmean, TMINmean, RX1 day, and RX5 day, a similar conclusion is obtained in this paper. In addition, more extreme climate factors, and time-lag effects are discussed. Among the 9 indices of extreme climate factors, DTR has a lag effect on vegetation growth from 0 to 3 months, and the other 8 extreme climate indexes have an impact on NDVI in the same month. Analysis of the delay effect of meteorological factors and NDVI, it is found that SSD had 0-3 months of lag response to vegetation while the lag effect of PWV and RHU on vegetation is mainly 1 month in the Loess Plateau. The main reasons for this phenomenon may be the characteristics of topography and rapid growth of vegetation in this area; in addition, the level of urbanization may also be another important reason for the change of climate and meteorological factors. Changes in the growing season can affect the exchange and transfer of energy through the biosphere and atmosphere, as well as the global carbon and energy cycles [45]. Therefore, variations in GSL were investigated, and GSL was found to be extended over the past 34 years, which agrees with the conclusions of [PERSON] et al. [4] and [PERSON] et al. [45] that the GSL in Northern China is prolonged. The extreme climatic and meteorological factors change, and their responses to vegetation growth in the recent 33 years may be associated with the vegetation growth rapidly and topography in the Loess Plateau. The surface vegetation cover change and urbanization recent 33 years may be one of the important reasons for climate change in the Loess Plateau during the S2 period [46; 47; 48]. Additionally, only 53 and 68 meteorological stations in the Loess Plateau were used by [PERSON] et al. [17] and [PERSON] et al. [19], whereas 83 meteorological stations were selected in this paper. More evenly distributed meteorological stations can better reflect the actual situation of the entire Loess Plateau. Hence, the results obtained in this paper may slightly differ from those of previous studies.
# Directional Paging for 5G Communications Based on Partitioned User ID
## 4 Performance Analysis and Results
Moreover, to understand the impact of paging rate on the number of beams, for all the cases, the value of \(N2\) is fixed at 32 in Figure 5d. As the paging rate increases, both \(C_{PIDP}\) and \(C_{DP}\) increase. For a higher paging rate, the network configures more POs in the case of direction paging with the full UE ID (Equation (12)). At the same time, in the PIDP mechanism, the UE per PO increases with the increase in paging rate (Equation (7)). As a result, a higher percentage of system capacity is required for both \(C_{PIDP}\) and \(C_{DP}\) with the increase in the paging rate. At a paging rate of 4000 UE/s and for 128 beams, the percentage of system capacity required for paging with the full UE ID is 92.25 in comparison to only 81.56 in the PIDP mechanism. Figure 6a demonstrates the base station's power saving gain (\(\Psi_{gain}\)) as a percentage for PIDP with respect to variations in the paging rate for 64 beams. The gain is obtained in comparison to directional paging with the full user ID. Cropped UE ID sizes with values of \(32,34,36\) and \(38\) are considered since they are less than the threshold obtained in Figure 5c. As the paging rate increases, the percentage of gain of PIDP increases. It can be observed from Equation (17) that the power saving gain scales exponentially with the factor \(N1=N-N2\). Therefore, while the increase is steeply exponential for lower values of \(N2\) (32), it shows less variations for higher values of \(N2\) (38) when the paging rate increases. For higher \(N2\) (38), the factor \(2^{N1}\) becomes less prominent compared to other terms and does not show a drastic effect on the gain percentage. For \(N2=32\) bits, the number of POs configured in PIDP is high (\(2^{8}\)). When the paging rate is low (1600), the number of POs configured by the network is less in directional paging with the full UE ID. Thus the gain for 32 bits at a lower paging rate is not remarkable. However, as the paging rate increases, the number of POs in directional paging also increases, resulting in substantial gains. The number of POs for 34 bits in PIDP is noticeably less (\(2^{6}\)) than it was for 32 bits. Thus, for increasing paging rate, the power saving gain for 34 bits shows less variation compared to 32 bits. In Figure 6b, we show the effect of the increase in the number of beams on the power saving gain (in %) of PIDP for paging rates of 6400 UE/s and UE ID size values of \(32,34,36\) and \(38\). As is clear from the analysis, the number of TX beams does not affect either the number of POs or the UE per PO. Therefore, as the number of beams increases, the gain percentage remains constant. Thus, the PIDP mechanism substantiates uniform percentage gains for both a lower, as well as a higher number of  
Figure 6: (**a**) Power saving gain vs. paging rate; (**b**) power saving gain vs. the number of beams. beams. Moreover, as expected for a lower value of \(N2\) (32), more gain is manifested compared to the higher value of \(N2\) (38).