esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Materials and methods
### Adsorption Experiments of Methylene Blue and Congo Red onto BCs  
The stock solutions of dyes (methylene blue (MB, 100 mg L\({}^{-1}\)) and Congo red (CR, 100 mg L\({}^{-1}\)) were used for the adsorption study of dyes (MB and CR) onto BCs. The stock solutions of dyes were adjusted to pH 4, 7, and 10 by 1M HCl and 1M NaOH. A 0.01 g of the BCs produced at 350-750 \({}^{\circ}\)C was added to 20 mL of MB solution (100 mg L\({}^{-1}\)) and CR solution (100 mg L\({}^{-1}\)) in 50 mL glass vials. These experiments were performed in a shaking incubator at various temperatures, such as 20 \({}^{\circ}\)C, 30 \({}^{\circ}\)C, and 40 \({}^{\circ}\)C, with shaking at 200 rpm for 5 days. Then the supernatants were collected to measure the adsorption efficiency after centrifugation of samples at 5000 rpm. The MB and CR value in aqueous phase was measured as an absorbance at 660 nm and 500 nm, respectively. The results were converted to the concentration using the calibration curve (concentration vs. absorbance). The correlations between dye concentration and absorbance were made through regression analysis:  
For MB,  
\[\mathrm{Y}=4.4818\mathrm{X}-1.2352\ (\mathrm{R}^{2}=0.9999) \tag{2}\]  
For CR,  
\[\mathrm{Y}=33.692\mathrm{X}+0.0278\ (\mathrm{R}^{2}=0.9999) \tag{3}\]  
where Y is dye concentration measured, and X is absorbance measured.  
The MB adsorption efficiency was calculated following Equation (4):  
\[\mathrm{Adsorption\ efficiency\ (\%)=(A-B)/A\times 100} \tag{4}\]  
where A is the initial concentration of dye, and B is the final concentration of dye after adsorption experiment.  
The MB adsorption capacity was calculated following Equation (5):  
\[\mathrm{Adsorption\ capacity\ (q)\ =\ \frac{(C0\ -\ Ci)\ X\ V}{W}} \tag{5}\]  
where (q): mg of dye adsorbed onto the biochar; (C\({}_{0}\)): initial dye concentration in mg per L; [C\({}_{i}\)]: final dye concentration in mg per L; V: volume of dye solution in L; W: amount of biochar in g.
# K-Means Clustering Algorithm Based on Chaotic Adaptive Artificial Bee Colony
## 2 Relative Work
### K-MEANS Cluster Algorithm  
Clustering methods are suitable for finding internally homogeneous groups in data. The K-means algorithm is one of the oldest clustering techniques [1], which is constructed based on the iterative hill-climbing process. The main idea is to gather the original data into K clusters according to similar attributes. The main processing procedure is as follows. Firstly, K samples are randomly selected from the original data, and each sample is taken as the center of K clusters. Then the distance between the K center samples and the remained samples is separately calculated. According to the calculation, each sample is classified into the nearest cluster. The iterative process is repeated until the cluster no longer changes. Therefore, the traditional K-means clustering is expressed as follows.  
\(x=\left\{x_{i}\in R^{d},i=1,2,\cdots,n\right\}\) is the original data sample, where \(x_{i}(i=1,2,\cdots,n)\) is \(d\) -dimensional vectors. \(C=\left\{C_{1},C_{2},\cdots,C_{k}\right\}\) is the cluster sets, where \(k\) is the number of clusters.  
K-means criterion function is expressed as follows:  
\[J=\sum_{j=1}^{k}\sum_{x_{i}\in C_{j}}d\left(x_{i},C_{j}\right) \tag{5}\]  
where \(d\left(x_{i},C_{j}\right)\) represents the distance between data \(x_{i}\) and its clustering center \(C_{j}\), and \(J\) represents sum of its internal distances.
# Electrochemical Ion Pumping Device for Blue Energy Recovery: Mixing Entropy Battery
## 5 Intercalation Materials as Cathode Electrode in MEB
### Cobalt Hexacyanoferrate (CoHCF)  
Cobalt Hexacyanoferrate is one of the most interesting inorganic polymers. As shown in Figure 2, the redox process in CoHCF involves two different metal transition ions (Fe and Co). Unlike other materials of the same class, the redox process is driven by a metal to metal charge transfer mechanism. The \(Fe^{3+}\) and \(Co^{3+}\) makes it possible to observe both redox couples, \(Fe^{3+}\)/ \(Fe^{2+}\) and \(Co^{3+}\)/ \(Co^{2+}\) in the same material [41]. The principal intercalation reaction for \(Na^{+}\) ions is shown in the following reactions [23].  
\[Co_{1.5}^{2+}\big{[}Fe^{3+}(CN)_{6}\big{]}+Na^{+}+e^{-}\leftrightarrow NaCo_{1.5}^{2+}\big{[}Fe^{2+}(CN)_{6}\big{]} \tag{40}\]  
\[NaCo^{2+}\big{[}Fe^{3+}(CN)_{6}\big{]}+Na^{+}+e^{-}\leftrightarrow Na_{2}Co^{ 2+}\big{[}Fe^{2+}(CN)_{6}\big{]} \tag{41}\]  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Ref.** & **Natural Source** & **Cl\({}^{-}\) [ppm]** & **Na\({}^{+}\) [ppm]** & **Mg\({}^{2+}\) [ppm]** & **Ca\({}^{2+}\) [ppm]** & **Li\({}^{+}\) [ppm]** \\ \hline [29; 32] & Seawater & 19.345 & 10.752 & 1.195 & 0.416 & 0.179 \\ [33; 34] & Geothermal & 7.899 & 4.459 & 1.700 & 250 & 34,27 \\ [35] & Atacama Brine & 198.000 & 42.700 & 40.500 & 368 & 1.820 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Main ion compositions of natural brines.
# Satellite Monitoring of Italian Vineyards and Spatio-Temporal Variability Assessment
## 2 Materials and Methods
### Biomass Developing Evolution
Chardonnay is an international grape variety widely spread throughout the country. The monitoring period began 20 days before flowering and ended 40 days after that date. Then, the mean and the CV of the whole vineyard's VIs were computed according to Equations (3)-(5). In addition, for each pixel of the satellite images, the Vis' values were interpolated across time, and the slope of the linear regression line was calculated according to Equation (6). Then, the mean and the CV of slopes were computed. \[\text{NDVI}=\frac{\text{NIR}-\text{Red}}{\text{NIR}+\text{Red}} \tag{1}\]  
\[\text{NDRE}=\frac{\text{NIR}-\text{Vegetation red edge}}{\text{NIR}+\text{ Vegetation red edge}} \tag{2}\]  
\[\overline{x}=\frac{\sum x_{i}}{N} \tag{3}\]  
\[\text{SD}=\sqrt{\frac{\sum(x_{i}-\overline{x})^{2}}{N-1}} \tag{4}\]  
\[\text{CV}=\frac{\text{SD}}{\overline{x}} \tag{5}\]  
\[\text{Slope}=\frac{\sum_{i}^{n}{(x_{i}-\overline{x})*(y_{i}-\overline{y})}}{ \sum_{i}^{n}{(x_{i}-\overline{x})^{2}}} \tag{6}\] \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Band Number** & **Wavelength Range (nm)** & **Spatial Resolution (m)** & **Band Name** \\ \hline
4 & 650–680 & 10 & Red \\
5 & 697.5–712.5 & 20 & Red edge 1 \\
8 & 784.5–899.5 & 10 & NIR \\ \hline \hline \end{tabular} [[https://sentinel.esa.int/web/sentinel/user-guides/sentinel-2-msi/resolutions/spectral](https://sentinel.esa.int/web/sentinel/user-guides/sentinel-2-msi/resolutions/spectral)]([https://sentinel.esa.int/web/sentinel/user-guides/sentinel-2-msi/resolutions/spectral](https://sentinel.esa.int/web/sentinel/user-guides/sentinel-2-msi/resolutions/spectral)) January 2024).  
\end{table} 
Table 1: Specifications of the Sentinel-2 bands used in this paper are listed.
# Forklift Tracking: Industry 4.0 Implementation in Large-Scale Warehouses through UWB Sensor Fusion
## 4 Experimental Analysis
### Computational Burden  
Finally, before installing the localization algorithm on the onboard microcontroller, we demonstrated the relatively low computational burden of the proposed method. For such an analysis, the elaboration time of the test cases I-IX has been measured when the processing was done on a laptop with an Intel(R) Core(TM) i7-7700 HQ CPU @ 2.80 GHz and 16 GB RAM through a MATLAB code. The trajectory processing time is reported in Table 4. By considering the number of UKF timesteps, we can observe that the average processing time for each timestep is 0.82 ms. By considering a sampling time of \(\Delta t=10\) ms, we can therefore conclude that the method is suitable for real-time applications, even with less performing CPUs. Indeed, the proposed system might also be considered in the future to be tested for safety applications to prevent forklift-to-forklift and forklift-to-human collisions [70].
## 5 Conclusions  
The transmission of the new navigation signal leads to the need to verify its performance in ranging and positioning. We propose a method for SDR to use L1C signal for ranging and joint positioning. The evaluation methodology is also proposed for the results using in-orbit signals. The comparison of ranging difference between BOC(1,1) and TMBOC(6,1,4/33) transmitted by GPS III and QZSS is given. The results from GPS III and QZSS demonstrate that the ranging performance of TMBOC(6,1,4/33) has better than BOC(1,1) but the choice of correlator spacing needs to be considered. The poor selection of correlator spacing will result in worse ranging performance for TMBOC(6,1,4/33).  
The experiment of Xi'an adopted the L1C signal transmitted by the first GPS III satellite, Vespucci, to verify the positioning performance. The joint positioning results prove that the QZSS L1C signal has the claimed enhancement and supplement effect on GPS. We give a direct comparison of GPS III + QZSS joint positioning vs. QZSS-only using in-orbit signals collected in Sanya. Due to the optimization of the constellation configuration, the positioning error of joint positioning is reduced. Meanwhile, the positioning results using different correlator spacing verify that the ranging difference of TMBOC(6,1,4/33) caused by the poor correlator spacing will affect the positioning result. But properly selecting the correlator spacing allows the positioning performance of TMBOC(6,1,4/33) outperforms that of BOC(1,1).  
[PERSON] conceived and wrote the paper; [PERSON] supervised the paper and suggested modifications; [PERSON] and [PERSON] analyzed the data; [PERSON] and [PERSON] collected the data. 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.
# Robust Image Watermarking in Spatial Domain Utilizing Features Equivalent to SVD Transform
## 1 Introduction
Using well-known evaluation metrics, such as the structural similarity measure (SSIM), peak signal-to-noise ratio (PSNR), bit error ratio (BER), and normalized correlation coefficient (NCC), the proposed watermarking approach is compared to similar approaches described in the literature. The result's analysis demonstrates the robustness of the proposed watermarking scheme against image distortion attacks and its excellent imperceptibility. The following is a summary of the key contributions of this work:  
1. Replication of the redistributed invariant wavelet transform concept to the spatial domain;
2. Application of the matrix 2-norm instead of SVD to obtain singular values;
3. Development of a new image watermarking scheme in the spatial domain;
4. Evaluation of the performance of the proposed scheme for grayscale images using a number of metrics and attacks. The article is structured as follows. An overview of the algorithmic concepts is provided in Section 2. The proposed watermarking scheme is described in Section 3. Section 4 compares and analyzes the results. Section 5 contains the concluding observations and suggestions for future research.
# Unity Power Factor Operation in Microgrid Applications Using Fuzzy Type 2 Nested Controllers
###### Abstract  
The issue of low-power factor operation microgrids was reported for several layouts. Although numerous power factor improvement strategies have been applied and tested, various concerns remain to be addressed such as transient performance, simplicity of implementation, and satisfying the power-quality standards. The presented research aimed to design and implement controllers that can improve the transient response of microgrids due to changes in the load demand and achieve a near-unity power factor at the AC grid side, to which the DC microgrid is connected. Due to the nonlinear nature of microgrids, as they rely on power electronics converters, a Fuzzy type 2 controller was designed, implemented, and tested. The focus was given to improving the power factor of the DC microgrids. The validation of the proposed technique was verified by comparing its performance with Fuzzy type 1 and autotuned conventional PI controllers. To achieve the set aims, two nested control loops were designed with an inner current loop and an outer voltage loop. Besides MATLAB/Simulink simulations, a 10 kHz-sampling dSPACE platform was used to implement the suggested system. Two operational scenarios were tested: (1) a step change in the DC link voltage and (2) a change in the AC load (increase and decrease) at the output of the power inverter, connected to the DC grid. The simulation and experimental results confirmed that the proposed Fuzzy type 2 controller performed better than the other two techniques regarding the dynamic response, steady-state error, and compliance with power quality standards. Conventional approaches develop controllers using a linearized model, which limits the model accuracy and ignores higher-order variability. The method employs the nonlinear model. Fuzzy type 2 can better approximate high-precision problems than Fuzzy type 1.  
boast converter; Fuzzy type 2; microgrids; unity power factor +
Footnote †: journal: Applied Sciences
## 2 Related Work
There are multiple other object tracking algorithms including the Siamese network for object tracking presented by [PERSON] et al. [19] and multi-domain convolutional neural networks (MDNet) for visual tracking by [PERSON] et al. [20]. Both presented deep learning-based object tracking algorithms with good accuracy and processing speed on GPU. However, their speed on a CPU did not meet the criteria of being in real time. The goal of our system was to be in real time on a CPU, which could be used by a wide range of users in resource constraint hardware systems. Therefore, we used a simple correlation filter-based tracker with additional modules to achieve efficient object tracking in 360\({}^{\circ}\) at high frame speed on a CPU. Moreover, in [21], the results proved that in achieving good accuracy at high frameates, simple correlation filter-based trackers are able to compete with complicated deep architecture-based trackers. Moreover, another problem in using deep learning-based trackers for tracking arbitrary objects is a lack of extensive 360\({}^{\circ}\) video data. Deformation of the object occurs in distorted stitched areas of panoramic frames, which makes it difficult to train a network for various appearances of an object. Focus assistance plays a very important part in storytelling and guiding experiences in VR. There are various focus assistance techniques proposed to follow the ROI including [2; 5]. In 2018, [PERSON] et al. discussed the important immersion factors that influence effective storytelling in 360\({}^{\circ}\) videos [22]. However, there are various existing issues in these techniques. There is a high probability that the viewer may not properly follow the visual guidance and lag behind the actual 360\({}^{\circ}\) experience. Consequently, they lose interesting information or the understanding of the overall story. Existing focus assistance techniques did not provide any mechanism to overcome this problem. However, we make our proposed focus assistance technique more adaptive to the user by providing the adjustment of frame rate and transparency of visual indicators based on the angular distance between viewer's head pose and angle required to view the ROI. In this way, a viewer can easily synchronize with the actual 360\({}^{\circ}\) experience with minimum loss of visual information.
###### Abstract
On the one hand, most of the physical models do not realize the radiation transmission from the atmosphere to the vegetation canopy [16], and atmospheric correction is a separate process that needs to be performed. On the other hand, previous studies on crop parameter inversion have focused on the establishment of spectral index and LUTs [11; 27], and there is limited information on inversion methods to extract crop multiparameters synchronously. Therefore, this study considers the atmospheric composition during the establishment of the forward model and evaluates the contribution of crop parameters to the forward model. In addition, we propose an optimal inversion framework for the synchronous retrieval of crop phenotypic parameters to solve the multiparameter inversion problem. The main objectives include the following: (1) to construct a forward model by coupling the PROSAIL model and UNL-VRTM model; (2) to analyze the sensitivity and information content of the model to crop parameters and to determine retrieved parameters; (3) to use optimal estimation theory and other techniques to find the minimum of the cost function; and (4) to establish and validate the optimal inversion framework for the synchronous retrieval of crop phenotypic parameters. In Section 1, we introduced two main approaches currently for the inversion of crop parameters and the research purpose of this paper. The components of our forward coupling model are described in Section 2, and we present the method for the synchronous retrieval of multiparameters in Section 3. In Section 4, we performed the parameter sensitivity analysis and information content analysis to determine the contribution of parameters to the model. In Section 5, we verified the accuracy of the forward model and tested the consistency of the inversion framework used to retrieve LAI and Cab. The discussion and conclusion are in Sections 6 and 7, respectively.
## 3 Results
### Risk Reduction Outcomes
#### 3.2.1 Life Safety and Evacuation Improvement  
Early detection and effective smoke management are critical determinants of life safety during fire events, particularly in enclosed or high-occupancy environments. The proposed system demonstrates substantial improvements in occupant survivability by significantly reducing the time to detection and actively controlling smoke spread during the critical early stages of combustion.  
As reported in Section 3.1.1, the mean fire detection time was 5.8 s, far earlier than the 20-30 s typical of conventional smoke or heat detectors. This early alert enables immediate actuation of ventilation mechanisms, which, as shown in Section 3.1.2, cleared 90% of visible smoke within 88-95 s. In contrast, traditional systems relying on delayed sprinkler activation do not facilitate preemptive smoke removal, often resulting in hazardous conditions before mechanical or manual response occurs.  
Improved visibility and air quality directly enhance occupant evacuation speed and reduce the risk of disorientation or smoke inhalation injury. Thermal imaging and gas sensor data collected during evacuation simulations indicated that the proposed system maintained breathable conditions (O\({}_{2}>\) 19.5%, CO \(<\) 50 ppm) for at least 90 s longer than the baseline system, a critical margin in multi-floor or subterranean environments [61; 62].  
These findings support the conclusion that the proposed platform substantially enhances life safety outcomes by reducing critical response time, improving egress conditions, and maintaining air quality during the highest-risk phases of a fire event.
## 2 Materials and Methods
### Candidate Sex-Related Genes Analysis  
The assembled transcriptome was selected as a reference because of the lack of genome information of _S. elongata_. All clean reads were aligned to the references with Bowtie 2 [31]. Then, RSEM version v1.2.12 was used to normalize the expression levels of the unigenes [32]. R package DEG-seq was used to identify differentially expressed genes (DEGs) [33]. The thresholds of DEGs were defined as \(1\log_{2}\) fold change \(\mid\geq 2\) and a \(p\) value \(\leq\) 0.001. Enrichment analyses (GO and KEGG) of the DEGs were performed based on the hypergeometric distribution test. A significance test was applied, and a Q-value value \(\leq\) 0.05 indicated significantly enriched terms.
# Detecting Symptoms and Dispersal of Pine Tortoise Scale Pest in an Urban Forest by Remote Sensing
## 2 Material and Methods
### Phenological Dataset  
A dataset of long-term near-infrared (NIR) and visible red reflectance data on a randomly chosen subset of locations in the Estate was used to drive the choice of the month and year with which to estimate the PTS symptom detection map and the threshold reflectance value to separate the binary classes of the presence/absence of symptoms.  
Forty locations were randomly selected in stone pine stands and labeled as presence/absence of symptoms according to visual ground checks and historical reconstruction of the PTS infestation by the Estate's personnel. A visual ground inspection included the sight of sooty mold, needle yellowing, and branch desiccation. Such symptoms are strictly associated with PTS infestations, whereas the other stone pine pests that are known to be present in that area, mainly coleopterans belonging to the families Curculionidae and Cerambicidae, as well as lepidopterans belonging to the families Tortricidae and Notodontidae, are responsible for unequivocally different damage to the canopy and trunk. On the other hand, the other Mediterranean scale species producing similar symptoms on stone pines (i.e., _Crisicoccus pini_ (Kuwana) and _Marchalina hellenica_ (Gennadius)) are known to be absent in the surveyed area.  
The Copernicus Sentinel-2 mission satellites aim to provide multispectral data products with a 5-day revisit frequency and a 10 \(\times\) 10 m spatial resolution [51]. Cloud and cirrus formations were detected and removed through the product quality assurance metadata. Near-infrared (NIR) and visible red reflectance data were collected on the sampling points from all images in the timeframe 2017-2022 and aggregated as median value composites using Google Earth Engine [52] (Figure 2).  
Figure 1: (**A**) Geographical location of the Castelporziano Presidential Estate in the Rome municipality area (In red the Lazio region, Italy). (**B**) Map of Castelporziano Estate with the scale pest infestation hotspot, the concentric circles representing a uniform dispersion model (cyan color), and the linear spread along the line of the prevailing wind passing through the infestation hotspot (yellow color). Coordinate Reference System: WGS84/UTM zone 33N.