esa-sceva/satcom-chunk-collection huggingface dataset:
# Prediction of Air Quality Combining Wavelet Transform, DCCA Correlation Analysis and LSTM Model
## 4 Discussion  
Using DCCA correlation coefficients, the correlation analysis of air quality achieves quantification at several scales. It facilitates multidimensional feature meritocracy in time series prediction, which minimizes the amount of input data for the prediction model while ensuring accuracy, and it gives a means to incorporate feature weighting parameters in the model, which helps to increase prediction accuracy. The research can be expanded to incorporate models with more complex characteristics, and the model can be paired with  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Window** & **Model** & **Train Loss** & **Valid Loss** & **MSE** & **Time(s)** \\ \hline \multirow{2}{*}{5000} & LSTM & 0.009910 & 0.006814 & 0.2568583 & 662.7335 \\  & DCCA-LSTM & 0.008748 & 0.005752 & 0.2008781 & 640.0185 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Model performance parameters for medium and long scale with window lengths of 5000.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Window** & **Model** & **Train Loss** & **Valid Loss** & **MSE** & **Time(s)** \\ \hline \multirow{2}{*}{24} & LSTM & 0.052742 & 0.049323 & 0.08974096 & 17.0574 \\  & DCCA-LSTM & 0.049790 & 0.047054 & 0.08095255 & 16.0810 \\ \multirow{2}{*}{48} & LSTM & 0.034793 & 0.032198 & 0.13867431 & 21.3187 \\  & DCCA-LSTM & 0.033351 & 0.030843 & 0.12241591 & 19.4778 \\ \multirow{2}{*}{168} & LSTM & 0.018447 & 0.015060 & 0.15315998 & 41.0941 \\  & DCCA-LSTM & 0.017658 & 0.014200 & 0.13412123 & 37.6885 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Model performance parameters for short scales with window lengths of 24, 48, and 168.  
Figure 7: 5000 h comparison of forecasts. (**a**) Results of prediction without DCCA factor weighting. (**b**) Prediction outcomes following DCCA factor weighting.  
an attention mechanism to give weighting factors to multidimensional features, improving the prediction model's accuracy.
# A Review of Regional and Global Gridded Forest Biomass Datasets
## 3 Current Gridded Forest Biomass Maps
### Forest AGB Maps from Field Inventory Data and Optical and/or Radar Remotely Sensed Data
#### 3.2.15. Colombia AGB Maps  
[PERSON] et al. [76] derived aboveground live biomass with a pixel size of 500 m in Colombia by developing empirical models with field, enhanced vegetation index (EVI) and VCF data. The empirical models were fitted independently for primary forest, secondary forest and savannas. The biomass model performed better in low biomass regions and there was an underestimation tendency when vegetation cover increased in secondary forests.
## 3 Results and Discussion
### Determination of Antioxidant Activity and Quantification of Total Phenolic Content
[32] concluded that an extremely intense irrigation deficit could negatively affect the TPC. The effects caused by water stress on the values of the TPC were similar to those previously reported in the literature. For example, [PERSON] et al. [28] showed that polyphenols increased by 26.8%, 52.2% and 49.3% when minimum \(\Psi_{stem}\) was reduced from \(-\)1.2 MPA to \(-\)3.5 MPA, \(-\)5.0 MPA and \(-\)6.0 MPA, respectively. In the current study, in the 2018 season, the TPC increased by 55.2%, 56.9% and 77.6% compared to the value of the control treatment when the control min \(\Psi_{stem}\) (\(-\)2.21 MPa) was reduced to \(-\)2.74 MPA, \(-\)4.71% and \(-\)3.75%, respectively. A similar trend was also observed in the 2019 season, with TPC increasing by 31.3%, 93.8% and 93.8% compared to the control when min \(\Psi_{stem}\) decreased from the \(-\)1.54 MPa of the control down to \(-\)3.15, \(-\)5.21 and \(-\)3.99 MPa, respectively. other 'Arbequina' orchards when deficit irrigation was applied. Those differences could be generated by the different locations of the orchards [34] and geaphoclimatic conditions [35]. In this sense, the highest concentration of oleic acid was reached in samples obtained from trees subjected to sustained deficit irrigation (T\({}_{3}\), 48.9%). The second most abundant compound was palmitic acid (C16:0), with 14.6% and 18.4% in the 2018 and 2019 season, respectively. This fatty acid did not present significative differences among irrigation treatments. The third predominant compound was linoleic acid (C18:2 _cis6_), which had a season mean content of 11.6% in 2018 and 17.4 in 2019. Regarding fatty acid families, monounsaturated fatty acids (MUFAs), with oleic acid as the main compound, were the predominant family (62% in 2018 and 55.6% in 2019), and their content depended on the irrigation treatment, especially higher after T\({}_{3}\) (61.1%). This family is extensively associated with beneficial effects on human health [36]. Saturated fatty acids (SFAs) were the second most concentrated family, with 17% in 2018 and 24.5% in 2019. Finally, polyunsaturated fatty acids (PUFAs) were lower in the 2018 season than in the 2019 season (12.5% and 19.2%, respectively), and control irrigation treatment reached the highest content (16.9%) and lower PUFA content was reached after T\({}_{2}\), 14.9%. Regarding the health indicators, thrombogenic index (TI) and atherogenic index (AI) values were higher in the 2019 season (0.541 and 0.249, respectively). On the other hand, irrigation treatments only had an effect on the atherogenic index, with lower values reached when sustained deficit irrigation was applied (T\({}_{3}\), 0.221). Both parameters are associated with correct blood circulation [37]. Similar values were obtained by [PERSON] et al. [24] with the same variety and other irrigation treatments.
## 3 Controller Design  
### Overall Framework  
In order to address the trajectory tracking control problem of a hydraulic-driven skid-steer mobile robot, a hierarchical control strategy is proposed in this study. This strategy aims to achieve accurate tracking control by considering both the robot's motion control and the hydraulic drive system control. The overall control structure is depicted in Figure 3 and consists of two main layers: the motion control layer (upper-level controller) and the hydraulic control layer (lower-level controller).  
The upper-level controller adopts the NMPC method, which controls the robot to track the desired trajectory, \(X_{r}=[x_{r},y_{r},\theta_{r}]^{T}\). The output \([v_{d},\omega_{d}]^{T}\) is the desired linear velocity and angular velocity of the mobile robot. Then, the velocity decoupling module converts \([v_{d},\omega_{d}]^{T}\) into the angular velocity of hydraulic motors \([w_{m,l}^{d},w_{m,r}^{d}]^{T}\), which is the reference input of the lower-level controller. Based on nonlinear current-velocity mapping, a look-up method is adopted in the lower-level controller, which outputs the control current \([u_{l},u_{r}]^{T}\) for hydraulic actuators. In addition, sensors, including RTK-GPS and encoders, are installed to measure the robot posture \([x,y,\theta]^{T}\) and the angular velocity \([w_{m,l}^{s},w_{m,r}^{s}]^{T}\), and feedback for the upper-level controller and the lower-level controller, respectively.  
The hierarchical control strategy allows for the decoupling of the motion control and hydraulic control tasks, which simplifies the overall controller design and improves the system's robustness and performance. By separating the control objectives and utilizing different control algorithms at each layer, the system can effectively handle the complex dynamics and nonlinearities of the hydraulic-driven mobile robot.  
Figure 3: The overall control framework of this research.  
Figure 2: Nonlinear velocity mappings: (**a**) left-side motors; (**b**) right-side motors.
# A Full-Duplex 60 GHz Transceiver with Digital Self-Interference Cancellation
## 3 Design and Implementation  
Some of the detailed sub-block circuit designs for the proposed transceiver are presented in previously published works [15; 16; 24; 25; 26]. In this work, the proposed transceiver needs to additionally support FDD and FD operations. The optimized DVGA with a bandwidth extension is presented in [16]. An updated PLL synthesizer with a power distribution network to provide LO signals to the transmitter and receiver chains at the same time is introduced and presented in [26]. The optimized matching network, including high-isolation switches for efficient power delivery, and both the HD and FD modes are described in it. Compared to the HD mode, the maximum LO power to the transmitter chains in the FDD and FD modes drops by 3 dB, and it degrades the transmitter's maximum output power by 6 dB.  
To achieve a similar SINR requirement that fulfills the specifications, we can either increase the received signal power or reduce the unwanted noise power, including the SI. However, in the FD mode, the transmitter power is in direct proportion to the received power for a given communication distance, and the SI isolation factor is fixed for a given system. The receiver chains will amplify both the received signal and the SI signal simultaneously. In other words, the transmission power determines the SI noise power, regardless of the communication distance. A shorter communication distance can relax the transmission power required while maintaining the received signal power, and the reduced transmission power will simultaneously scale down the SI noise. For the shortest distance, e.g., the line-of-sight (LoS) channel in this work, it provides a 6 dB power gain when reducing the communication distance by half.
## 2 Materials and Methods
### Eddy Covariance and Ancillary Measurements  
At each station, the EC system consisted of an infrared gas analyser (LI-COR, Lincoln, NE, U.S.A.) and an ultrasonic anemometer (Gill, Hampshire, U.K.) measuring at a 20 Hz frequency (models are specified in Table 2). Each system was mounted on a tower several meters above the forest canopy. The EC measurements were complemented by an extensive set of sensors to collect the required auxiliary meteorological data. Measurements included the air temperature (Tair) and humidity profile with EMS33 temperature and humidity sensors (EMS, Brno, Czech Republic) and precipitation using Precipitation Gauge 386C (Met One Instruments, Grants Pass, OR, U.S.A.). Measurements for the incoming photosynthetic active radiation was made using LI-190R Quantum Sensor (LI-COR, Lincoln, NE, U.S.A.) at Bally Kriz and EMS12 sensor (EMS, Brno, Czech Republic) at Rajec. Additionally, profiles of soil moisture were measured by using the CS616 (Campbell Scientific, Inc., Logan, UT, U.S.A.) sensors. An overall description of the instrumentation at the study sites is given in Table 2.  
\begin{table}
\begin{tabular}{l l l} \hline \hline
**Site Name** & **CZ-BK1** & **CZ-RAJ** \\ \hline Location & Moravian-Silesian Beskids & \\  & Mountains & Drahany Highland \\ Coordinates & 49\({}^{\circ}\)30\({}^{\prime}\)08\({}^{\prime\prime}\) N, 18\({}^{\circ}\)32\({}^{\prime}\)13\({}^{\prime\prime}\) E & 49\({}^{\circ}\)26\({}^{\prime}\)37\({}^{\prime\prime}\) N, 16\({}^{\circ}\)41\({}^{\prime}\)48\({}^{\prime\prime}\) E \\ Elevation (in m a.s.l) & 875 & 625 \\  & Mountains (13\({}^{\circ}\) slope with & \\ Topography & SSW exposure, located close & \\  & to a mountain ridge) & \\ Ecosystem Type & Coniferous evergreen forest & \\  & Norway Spruce & \\ Prevailing species & (_Pica abies_ (L.) H.Karst.) & (_Pica abies_ (L.) H.Karst.) \\ Canopy height (m) & 16 (mean, as of 2015) & 33 (mean, as of 2015) \\ Stand age (years) & 35 (as of 2016) & 113 (as of 2016) \\ Mean annual air temperature & 7.2 (2014–2016) & 8.3 (2014–2016) \\ (May–September; \({}^{\circ}\)C) & & \\ Mean annual precipitation & 1143 (2014–2016) & 610 (2014–2016) \\ (May-September; mm) & & \\ evapotranspiration & 569 (2014–2016) & 649 (2014–2016) \\ (May–September; mm) & & \\ Soil type & Haplic and Entic Podzol & \\ Max and min fetch (m) & 717 (WNW) and 115 (ENE) & 697 (SSW) and 96 (NNW) \\ References & [31; 37; 38] & [31] \\ \hline \hline \end{tabular}
\end{table}
Table 1: Characteristics of the study sites.  
ecosystem respiration (R\({}_{\text{eco}}\)). The flux partitioning approach by [49] using daytime data was applied to estimate half-hourly GPP (umol m\({}^{-2}\) s\({}^{-1}\)) values. The half-hourly GPP values were aggregated to obtain daily and monthly GPP sums.
# Icing Detection over East Asia from Geostationary Satellite Data Using Machine Learning Approaches
## 1 Introduction
The objectives of this research were to (1) develop icing detection algorithms for a portion of East Asia based on machine learning approaches with COMS MI and Himawari-8 AHI products; (2) compare the proposed algorithms with the existing FIT and KMA algorithms; and (3) interpret the properties of the potential icing clouds identified by the algorithms. Two machine learning approaches--random forest (RF) and multinomial log-linear model (MLL)--were used in this study.
## 4 Discussion
The amino acid profile of the HFM-based diets used in the present study showed high levels of crucial amino acids, such asarginine, leucine, lysine, and valine. These amino acids are essential for prawns' physiological functions, growth, and immune responses [20]. Although methionine levels in HFM-based diets were slightly lower than in standard fishmeal [26], this limitation was compensated through the addition of DL-methionine in the formulations, ensuring nutritional adequacy. Moreover, the final carcass proximate composition and stable amino acid profile observed in prawn carcass (see Supplementary Materials) further suggest that the amino acid composition of HFM-based diets effectively supported tissue building and protein metabolism during the nursery phase and that dietary HFM did not impact prawn flesh nutritional quality. Additionally, the antenna length serves as a physical indicator of welfare in decapods. Assessing this feature offers a non-invasive approach to evaluating the welfare of famed prawns. Long and intact antennae reflect good health and appropriate husbandry conditions [54]. Prawns fed diets with the highest levels of HFM inclusion exhibited longer antennae, reflecting an improved welfare. The maintenance of digestive enzyme activities and antioxidant status in the hepatopancreas of _M. rosenbergii_ post-larvae when incorporating HFM as a partial replacement for fishmeal is particularly significant in the context of the growing demand for sustainable and cost-effective alternative protein sources in aquaculture feeds. Poultry by-products, such as feather meal, represent a promising alternative due to their high protein content, balanced amino acid profile, and widespread availability [55; 56]. The absence of differences in the digestive enzymes, including maltase, sucrase, chymotrypsin, and trypsin, among dietary treatments suggests that HFM did not impair digestive function and, thus, nutrient assimilation. Nevertheless, further research is needed to corroborate this hypothesis through digestibility trials. While the present study demonstrates that dietary inclusion of HFM up to 6.0% enhances growth performance and maintains physiological and nutritional balance in _M. rosenbergii_ PL, the feasibility of higher inclusion levels needs to be confirmed. Limitations may include the relatively low digestibility of residual keratin, the methionine deficiency, and the risk of bioaccumulation of undesirable compounds if processing quality is sub-optimal. Higher HFM inclusion levels may also affect diet palatability, which could lead to reduced feed intake, particularly in early life stages. Therefore, while our results are promising, further studies are suggested to investigate the effect of higher HFM inclusion levels, the long-term effect of HFM, including in more advanced stages of the culture cycle (e.g., juveniles and adult prawns), and its economic value in commercial aquaculture farms.
# A New Ground-Motion Prediction Model for Shallow Crustal Earthquakes in Turkiye
## 2 Database and Selection Criteria
The rate of decrease at larger distances (\(R_{\rm{JB}}>80\) km) is higher for shorter periods than for longer periods. The curvature in the distance-dependent decay function is addressed by adding an anelastic term to the path function. Similarly, the magnitude scaling of the observed GMIMs (PGA, PGV, and PSA at \(T\) = 0.2 s and \(T\) = 3.0 s) for different distance group ranges is shown in Figure 1.2 In the magnitude scaling, a linear trend is observed with relatively wide scatter in PGA and short-period (\(T\) = 0.2 s) PSA. In the long-period (\(T\) = 3.0 s) PSA ordinates, there is less scatter, and a notable slope break occurs, particularly for moderate magnitudes in the range of 5.5 to 6.0. For PGV values, a more pronounced increase in slope at larger magnitudes is observed with lower scatter  
Figure 1.3 Histogram of the number of records by site classes (following NEHRP-2009 and TBEC-2018). across nearly all ranges. That is, after a certain magnitude, it is observed that GMIMs do not increase with magnitude (the slope decreases). Figure 1.4 Ground-motion intensity measures plotted versus distance (\(R_{JB}\)) and color-coded by magnitude ranges. A summary of the criteria for the variables used in our GMPMs is as follows:  
Figure 1.5 Magnitude scaling of observed GMMs (PGA, PGV, and PSA with \(T=0.2\) s and \(T=3.0\) s periods) for different distance group ranges. * Moment magnitude (\(M_{W}\)) ranging from 4.0 to 7.8 for shallow crustal earthquakes,
* Mainshock and aftershock events with focal depths \(\leq\) 35 km,
* A source-to-site distance (\(R_{JB}\)) ranging from 0 to 350 km,
* The used records are characterized by \(SS\) (9410), \(NS\) (9713), and \(RS\) (1050) fault types,
* The ground-motion data, obtained from the databases, consist of horizontal-component recordings that have been processed and converted to RotD50 [31]. The dataset includes PGA, PGV, and 5% damping PSA values for 36 different periods ranging from 0.01 to 10.0 s.
* Time-averaged 30 m shear-wave velocities of \(V_{S30}\) = 131 to 1862 m/s,
* The strong-motion records controlling our equations are derived principally only from Turkiye and were mostly obtained from high-resolution digital recorders in free-field stations, while a limited number of records before 2000 were provided from single-story buildings and analog instruments,
* Records with low resolution, noise, anormal peaks, or with S-triggers, and those containing consecutive earthquakes in the same series, have been excluded.
# Fibre Wireless Distributed Antenna Systems for 5G and 6G Services
## 5 Challenges and Future Prospects  
The proposed fibre wireless distributed antenna system would have some higher complexity for RAU because it contains more photonic components than the MHU, including a laser source, DPX, amplifiers, filters and photodiode. The limitations of the experimental setting forced the 6G THz link's wireless transmission distance to be 3 m with a clear deficit of 7 dB. THz amplifiers could be used to make up for the additional losses brought on by the longer wireless range [11]. For instance, a 20 dB amplifier gain will provide a 10\(\times\) increase in distance (i.e., 30 m).  
Additionally, the linearization mechanism will be required at some point to further improve the performance of this system. This means that receiving feedback signals from the BS to the RAU is crucial. This is because the feedback link may be nonlinear; in fact, it may be just as nonlinear as the Fi-Wi-DAS link. The present solutions available only take into account the non-idealities of the RoF link, which is first compensated for by utilising a post distorter and known training signal from the RAU. Following that, the downlink RoF link that has already been compensated may be used as a feedback connection for the compensation. However, a plausible solution can be achieved by moving the complex signal processing at the Central Office/Base Transmit Station as a potential feedback situation (CO-BTS).  
Similarly, in the coming years, the 6G era will face a massive surge of applications requiring extremely low latency, ultra-high reliability, high capacity, hyper-connectivity, scalable, ubiquitous, and distributed communication paradigms. A good number of research articles are readily available in the literature detailing the envisioned 6G architecture and the possible disruptive technologies. To meet the stringent requirements of the 6G mobile technology and for provisioning the 6G transport over the access network, the passive optical network (PON) has been considered as a cost-effective solution. In such cases, PON-based DAS systems should be evaluated.  
For high-speed computing, we also need to fulfil the low latency requirement. Although multilevel pulse amplitude modulation (PAM) can be used to expand the capacity of components with limited bandwidth, it has strict criteria for driving electronics and photonics in terms of linearity and noise tolerance. For this kind of short-reach application, on-off keying (OOK) merits further investigation. In this study, 222 Gbaud OOK transmission over a 120-m single-mode fibre (SMF) was accomplished using a plasmonic modulator with a high-speed 2:1 selection; however, the configuration also included two erbium-doped fibre amplifiers (EDFA) [45]. Additionally, the power split ratio of the analog optical link to realize the shared infrastructure, leading to further cost/energy reduction, should be addressed.
# A Method to Optimize Routing Paths for City-Pair Airlines on Three-Layer Air Transport Networks
## 2 Multi-Layer Air Transport Networks
### Mapping of Air Transport Networks
#### 2.2.3 Coupling Relationship between \(G_{ARN}\) and \(G_{fn}\)  
As discussed earlier, from the coupling relationships between \(G_{AN}\) and \(G_{ARN}\), we can obtain all city-pair airlines, whose routing path contains a given air route segment. Furthermore, for each city-pair airline \(l_{i,j}=(a_{i},a_{j})\in L(G_{AN})\), we can also obtain the flights along this city-pair airline at different times. Thus, for a given air route segment, we can obtain the flights through it.  
Conversely, for each flight \(f^{i}\) in \(G_{FN}\), the routing paths on \(G_{ARN}\) that it will fly in reality can be obtained by the coupling relations of three-layer networks.  
According to the mapping relations between the three-layer air transport networks, we can find that the flight operation network will affect the traffic flow distribution ofthe air route network if the routing paths for city-pair airlines are determined.