esa-sceva/satcom-chunk-collection huggingface dataset:
# A Review of AlGaN-Based Deep-Ultraviolet Light-Emitting Diodes on Sapphire
## 16 Frontiers of Current AlGaN-Based DUV-LEDs  
In Figure 1, a difficulty of the DUV-LEDs in the wavelength region where \(\lambda\) is less than about 270 nm can be seen. The EQE rapidly decreases as the wavelength decreases from around 270 nm. A possible reason for the low EQE (\(\lambda<\) 270 nm) is the increased number of NRCs due to V\({}_{Al}\) with increasing AlN content. Thus, lower IQE can be one of the reasons. The decrease in the CIE also limits the LED performance due to the insufficient electrical properties of EB layer. When we performed beryllium (Be) doping using MOCVD in an attempt to improve the EB layer and low CIE, Be was not detected in the AlGaN film and no significant result was obtained. In addition to the low CIE and IQE, the polarization of light emitted from AlGaN QWs changes from transverse electric (TE) (C\(\perp\)E) to transverse magnetic (TM) (C\(\parallel\)E) [140,141] at a high AlN content of around 60%. TM polarization is considered to be suitable for LDs [142,143,144] due to the edge emitting device structure, and the control of the polarization for DUV-LEDs has also been studied [145] to solve the lowered LEE. The use of a nanorod structure [146] to extract TM light has also been studied. Moreover, very thin QWs and quantum disks (QDs) for generating TE-polarized emission at wavelengths of \(\lambda<\) 240 nm have been reported [147,148,149].  
LEDs with emitting wavelength range between 300 and 350 nm appear to have lower EQEs as shown in Figure 1. The EQEs of InGaN LEDs tend to decrease with increasing wavelength away from the blue-to-NUV regions [16; 66] with increasing In content in InGaN. Similarly, the EQEs of AlGaN LEDs tend to decrease from 300 nm to 350 nm with increasing Ga in AlGaN. For an AlGaN-based LED with GaN wells, an EQE of 6.7% at 345 nm was obtained; for this LED, ELO technique was used to reduce the TDD of the n-AlGaN cladding layer [35; 36]. Thus, reducing the TDD is considered to be among the key methods for improving 300-350 nm LEDs if the carrier localization effect is limited due to a high GaN content. This wavelength region is expected to be used in the application related to the protein from the industrial viewpoint.  
AlGaN-based DUV-LEDs produced by several manufacturers are already on the market. Novel uneven MQWs are an example of the application of the unexpected features of nitride materials. The mechanism of the higher EQEs by virtue of the relatively high IQEs in uneven MQWs has not yet been clarified, although the enhanced carrier localization due to macrosteps has been suggested [13]. After InGaN-based LEDs were on the market, the mechanism of the carrier localization in InGaN QWs was clarified. The study of the detailed mechanism of AlGaN-based LEDs with uneven MQWs is also expected to accelerate the improvement of LEDs.
# A Fast Sparse Coding Method for Image Classification
###### Abstract  
Image classification is an important problem in computer vision. The sparse coding spatial pyramid matching (ScSPM) framework is widely used in this field. However, the sparse coding cannot effectively handle very large training sets because of its high computational complexity, and ignoring the mutual dependence among local features results in highly variable sparse codes even for similar features. To overcome the shortcomings of previous sparse coding algorithm, we present an image classification method, which replaces the sparse dictionary with a stable dictionary learned via low computational complexity clustering, more specifically, a \(k\)-medoids cluster method optimized by \(k\)-means++. The proposed method can reduce the learning complexity and improve the feature's stability. In the experiments, we compared the effectiveness of our method with the existing ScSPM method and its improved versions. We evaluated our approach on two diverse datasets: Caltech-101 and UIUC-Sports. The results show that our method can increase the accuracy of spatial pyramid matching, which suggests that our method is capable of improving performance of sparse coding features.  
Keywords:image classification; sparse coding; spatial pyramid matching; \(k\)-medoids; image feature +
Footnote †: journal: Applied Sciences
# Evaluation of the Possibilities of Using Out Malt in Wheat Beadmaking
## 3 Results and Discussion  
### Chemical and Color Characteristics of Quality of Baking Flours  
The chemical characteristics and the color measurement of three types of flour, including wheat flour (WF), and wholeemal non-bread flour samples, i.e., oat flour (OF) and oat malt flour (MF), were evaluated and are summarized in Table 2.  
The moisture content plays an important role during food packaging and transportation [5]. The lowest moisture content was in MF flour (average 6.91%) in comparison with WF and OF, the main reason for which could be found with the malting process. The assessed flour samples were characterized by moisture in the optimal range (below 15%), safe for them during storage. The tested three flour samples differed statistically (\(p\leq 0.05\)) in all assessed chemical composition parameters (Table 2). The results showed that WF flour was characterized by statistically lower protein, fat, ash, and TDF contents (average 12.60, 1.06, 0.50, and 3.15% d.m., respectively) compared to the OF and MF flour samples (Table 2). However, the carbohydrate content was at the highest level in WF flour (average 82.74% d.m.). Compared to non-bread oat flour (OF), the MF sample had a higher content of protein, fat, ash, and carbohydrates (average 14.30, 8.69, 2.42, and 64.35% d.m., respectively). However, the statistically significant differences were found only for fat and carbohydrate content. In turn, a higher TDF content was found in OF than in MF (average 13.05 and 10.24% d.m., respectively), and in both samples, the insoluble fiber (IN-DF) fraction predominated (Table 2). Similarly, in the study by [PERSON] et al. [1], commercial wheat malt flour, in comparison with wheat flour, contained more protein, lipid, fiber, and ash contents, and lower carbohydrate content. [PERSON] et al. [51] reported that compared to other cereals, wholemeal oat flour contains the most protein and fat, but the least carbohydrates. Differences between the quantitative composition of wholemeal flour samples obtained with naked oats and corresponding oat malt may result from the vital and biochemical changes that occur in the grain during the malting process. During germination, as the new plant develops, grain respiration is activated and metabolism occurs. At the same time, a pool of enzymes is activated and created, which are responsible for loosening the grain
# Technology and Data Fusion Methods to Enhance Site-Specific Crop Monitoring
## 2 Sensor Types
### Radar Sensors
#### 2.6.2 SAR Polarimetry Technique  
The SAR return signal from the source depends on various properties, such as crop density, moisture availability, canopy structure, and soil moisture. Advantages of using SAR polarimetry include the delivery of high amounts of quantitative data in single and dual polarization among all four linear polarization combinations. Several decomposition methods for estimating scattering have been proposed. Coherent decomposition is beneficial for analyzing the crop sources and cannot be applied for natural sources. While incoherent decomposition is considered as more beneficial for crop monitoring purposes, its dispersion provides canopy orientation, structure, and crop moisture data [46]. To address these issues, [PERSON] et al. [119], [PERSON] et al. [120], [PERSON] et al. [121] and [PERSON] et al. [122] mapped crop types, using time-series of the SAR imagery, phenological data, and time-analysis for Euclidean and angular distance estimation.
# LoRaWAN Behaviour Analysis through Dataset Traffic Investigation
## 4 LoRaWAN Analysis
### Device-Gateway Interaction  
The goal of this analysis is to investigate the number of devices handled by each gateway. Since we do not know the unique identifier of a device (DevEUI), we can count the number of \"temporary\" devices, which are differentiated by DevAddress field encoded as clear-text in the header.  
We have parsed the dataset and group the packets by gateway. Then we have counted the number of distinct device-address seen for each gateway. We plot the obtained results in Figure 11.  
Figure 10: Plot of CDF of devices in function of percentage of packet loss.  
Figure 9: PDF distribution of lost packets. To compute it, we isolated the packets of each device in the network. Then, we computed the ratio of lost packets for each device. The PDF in figure is the distribution of those ratios.  
The histogram reported in Figure 11 represents the number of distinct device-address seen by each gateway. We observe that the two gateways that have seen the highest number of distinct DevAddress, GW6, and GW5, are the ones which were up and running by the longest time period, of 552 and 573 days, respectively. However, the same gateways are placed in an indoor environment, which is not optimal for receiving LoRa packets. Indeed, they have managed only 186,592 and 76,706 packets, respectively.  
On the other hand, GW3 manages packets generated by only 2705 distinct DevAddress, but it is the one that handles the highest number of 5,757,575 packets in a relatively short period of activity of 56 days.
# ISAC towards 6G Satellite-Terrestrial Communications: Principles, Status, and Prospects
## 5 Potential Research for ISAC towards 6G ISTNs
### Artificial Intelligence  
With the rapid development of artificial intelligence (AI) technology, its influence has expanded to various fields. AI-based communication technology has been widely studied, such as edge learning [133], and data-driven algorithms have created new opportunities for ISTNs. In the future, in the context of ISTN environments, the highly complex and data-intensive environment poses challenges for system optimization, and AI algorithms will be used to address these complex optimization problems. At the same time, advancements in hardware enable the deployment of AI algorithms in communication devices. There have been studies focusing on ISTNs, but for future scenarios, AI methods will be needed to allocate resources efficiently and optimize communication performance.  
In [134], the authors used multiple UAVs as mobile aerial platforms for ISTNs. The method utilized centralized and distributed deep reinforcement learning solutions to optimize ISAC performance, UAV trajectory planning, power allocation, and spectrum efficiency. Furthermore, AI can enhance ISAC performance in interference management. In [135], an unsupervised learning-based communication-sensing-intelligence converged network architecture is proposed to coordinate interference. Each base station is equipped with a deep neural network for power allocation and beamforming. An unsupervised learning algorithm is proposed to allocate power for interference management, and a transfer learning approach is used to handle interference management in terms of beamforming. Therefore, the research on AI-assisted ISAC within the integrated satellite and terrestrial architecture is meaningful.
# Connectivity Analysis in VANETs with Dynamic Ranges
## 4 Discussion
### Distribution of Ranges  
We verify the impact of big vehicle shadowing (BVS) and path-loss exponent, \(\alpha\) on the communication range distribution. The communication range distribution functions for different fading environments are plotted against a varying headway distance or inter-vehicle distance, \(D(m)\).
## 2 Background of Research and Construction of New Dataset  
### Summary of Existing Research on A2G Channel Models by Terrain  
Various research results have been derived recently for studying A2G channel models in the air domain [11; 12; 13; 14; 15; 16; 17]. Among them, representative results measured channel characteristics by mounting channel-sounding equipment on an aircraft and derived channel models based on the measured data. Figure 1 shows the classification of channel measurement environments according to the terrain. It can be broadly divided into flat land, hill, mountain, and water. Flat land and hill area can be subdivided into downtown, suburban, and rural area, and water areas can be divided into the sea and freshwater. Table 1 summarizes the contents of A2G channel model studies conducted through aerial measurements in various literature. The criteria for categorizing the topographic environment are not absolute because the average altitude, mountain height, buildings, etc., vary depending on the country. Therefore, the number of classification classes can differ for different countries.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Setting** & **Location** & **Specific Environment** \\ \hline Over Sea [14] & Oxnard, CA & Open salt water with few stationary structures \& watercraft \\ \hline Urban [16] & Cleveland, OH & Cityscape view with many tall buildings on flat terrain, adjoining open freshwater \\ \hline Hilly Suburban [16] & Latrobe, PA & A mix of rural terrain \& urban structures in the valley, viewed from the airport \\ \hline \hline \end{tabular}
\begin{tabular}{c c} \hline \hline  & Ground station (GS) antenna beam to a mountain ridge \\ Hilly [15] & Latrobe, PA & w/natural cover. Ridge extends into line-of-sight between UAV \& GS \\ \hline \hline \end{tabular}
\end{table}
Table 1: Examples of A2G channel measurement environments [14; 15; 16].  
Figure 1: Classification of A2G propagation topography [11].
## 3 Results and Discussion
### Analytical Study
#### 3.4.3 Selectivity  
The developed biosensor is intended to work in complex environments like the blood, body fluid, food samples, etc. Hence, the analytical performance of the developed biosensor should be studied to check the selectivity towards its analyte in the presence of potential and common interfering agents found in biological environments. The potential interfering agents for H\({}_{2}\)O\({}_{2}\) detection was selected from previous study which are KCl, NaCl, glucose, and ascorbic acid [29]. The same concentration of the analyte and the interfering agents was used to study the selectivity and effect of the potential interfering agents. The measuring solution was subjected to successive double injections of 100 \(\upmu\)mol L\({}^{-1}\) of H\({}_{2}\)O\({}_{2}\) standard, followed by injection with the same concentration of NaCl, KCl, glucose, ascorbic acid and, again, double injections of H\({}_{2}\)O\({}_{2}\) at 100 \(\upmu\)mol L\({}^{-1}\). As shown in Figure 6A, with each injection of H\({}_{2}\)O\({}_{2}\), an apparent current drop was achieved, while no significant current response was observed with the addition of the potential interfering agents. With the last injections of H\({}_{2}\)O\({}_{2}\), again, the current drop was realized by confirming the high selectivity of the developed sensor. The change in the current response with the addition of the interfering agent is also represented in Figure 6B.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Linear ranges** & 99.90–792.86 \(\upmu\)mol L\({}^{-1}\) \\
**Slope** & 0.068 \(\upmu\)A \(\upmu\)M\({}^{-1}\) \\
**Intercept** & 2.055\(\upmu\)A \\
**Sensitivity** & 0.068 \(\upmu\)A \(\upmu\)M\({}^{-1}\) \\
**Limit of detection LOD** & 27.020 \(\upmu\)mol L\({}^{-1}\) \\
**Limit of Quantification LOQ** & 89.26 \(\upmu\)mol L\({}^{-1}\) \\
**Relative standard deviation RSD%** & 6.14 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Analytical parameters of the developed sensor GCE/MWCNT/UN-MNPs at an applied potential of \(-\)0.3 V for H\({}_{2}\)O\({}_{2}\) detection.  
Figure 5: Three successive concentration dependencies of peak current obtained by chronoamperometry with the same GCE/MWCNT/UN-MNPs. Successive injection of 100 \(\upmu\)mol L\({}^{-1}\) H\({}_{2}\)O\({}_{2}\) with an applied potential of \(-\)0.3 V in 10 mL 0.01 M PBS buffer.
### Target Model and the Integrated Energy Market in the EU
Contractual Balancing Service Providers (BSPs) are paid a payment of availability in Balancing Capacity Markets [20]. The TSO is in charge of resolving imbalances by charging contacted parties for imbalances in their portfolios [6; 21; 22]. The amount of activated energy is determined by real-time imbalances [14]. The net quarter-hourly difference between the BRP's total injections and offtakes is the BRP's imbalance [14]. The net sum of all BRP imbalances in the control area equals the total imbalance in the control area [14; 23]. By activating reserves, the TSO will keep the system balanced. The Net Regulation Volume (NRV) is the number of reserves that have been activated. A positive NRV indicates upward regulation, while a negative NRV indicates downward regulation [14; 15]. The Imbalance Settlement Period (ISP) is a key feature in calculating an imbalance price [9; 19; 20; 21]. By 1 January 2021, the ISP must be synchronized to 15 min [4; 22]. The implementation of platforms for the exchange of balancing energy is a critical component [23; 24; 25; 26; 27; 28; 29; 30; 31; 32]. These platforms are: (a) for the RR platform, the Trans-European Replacement Reserves Exchange (TERRE), (b) for the mFRR platform, the Manually Activated Reserves Initiative (MARI), (c) for the aFRR platform, the Platform for International Coordination of Automated Frequency Restoration and Stable System Operation (PICASSO), and (d) for the  
Figure 2: The Balancing Reserve Market [20]. IN platform, the International Grid Control Cooperation (IGCC). Redispatch is required when the results of the market's outcome in generation and consumption schedules that would potentially violate the limits of operation of a specific network element. Redispatch is typically accomplished by increasing or decreasing the output of a generator. Electricity will have a crucial role in the economy of the EU [29]. To achieve this, the energy system must be more flexible, and the existing interconnections have to use their full capacity, while maintaining the system's security. The current bidding zone configuration is under strain at high voltage levels. Grid expansion could not keep up with the impressive capacities of installed renewables, and as a result, among other issues, redispatch costs are high and continuing to rise. Furthermore, at low-voltage levels, distribution networks would need to be expanded to accommodate increasing consumer PV installation, electrification of heating and transportation [16].
## 2 Methods
### Case 1: High-Latitude Region
#### 3.1.4 Validation of Ionospheric Correction  
Figure 8 presents the interferometric phase at the profile A-A' in Figure 7a,c-e. It is found that the integration-corrected interferometric phase becomes more stable, implying that the proposed method can effectively mitigate ionospheric errors. For the whole images, the statistics show that the mean standard deviations have reduced nearly a factor of eight times for corrected phase (2.5 rad) versus original phase (21.6 rad), demonstrating the validation of our correction once more.
## 4 Conclusions  
Two natural and two conventional chemical coagulants were tested for the treatment of aquaculture wastewater. Among the natural coagulants, one was produced by extracting tannins from chestnut shells due to its availability in Portugal. The extracted tannins were chemically modified via the Mannich reaction using NH\({}_{4}\)Cl and formaldehyde. Addressing the research gap regarding the use of natural coagulants in continuous flow systems, this study evaluated their performance under optimal conditions (coagulant dosage and pH) and at different dosages under natural pH. The results demonstrated that all coagulants could remove color, organic matter, phosphorus, and nitrogen from raw aquaculture water. Although nitrogen removal rates were relatively low, the ability of natural coagulants to reduce nitrogen concentrations in continuous flow is a promising finding. Color reduction was particularly important for improving visibility in fish tanks, and the chestnut shell-derived coagulant outperformed the conventional ones in this aspect, showing high efficiency even at lower dosages. Another significant advantage of using the chestnut shell-based coagulant is the absence of residual aluminum in the treated water. Future studies should explore the combined use of different coagulants, as potential synergistic effects could enhance treatment efficiency and help optimize operational conditions for aquaculture wastewater treatment. Overall, this study confirms that chestnut shells are a valuable source for producing tannin-based coagulants, with proven efficiency in both batch and continuous flow treatments--bringing this natural solution a step closer to application at larger treatment scales.  
Investigation, I.T.T.; conceptualization, I.T.T.; methodology, I.T.T. and C.M.S.B.; visualization, I.T.T.; formal analysis, I.T.T.; data curation, I.T.T.; writing--original draft preparation, I.T.T.; validation, C.M.S.B. and R.A.R.B.; writing--review and editing, C.M.S.B. and R.A.R.B.; supervision, C.M.S.B. and R.A.R.B.; project administration, C.M.S.B.; funding acquisition, C.M.S.B. and R.A.R.B. All authors have read and agreed to the published version of the manuscript.  
This work was financially supported by UID/50020 of LSRE-LCM--Laboratory of Separation and Reaction Processes--Laboratory of Catalysis and Materials--funded by Fundacao para a Ciencia e a Tecnologia, I.P./MCTES through national funds, and by ALiCE, LA/P/0045/2020 (DOI: 10.54499/LA/P/0045/2020). I.T.T. acknowledges the doctoral scholarship BD/11977/2022(DOI: [[https://doi.org/10.54499/2022.11977.BD](https://doi.org/10.54499/2022.11977.BD)]([https://doi.org/10.54499/2022.11977.BD](https://doi.org/10.54499/2022.11977.BD))) awarded by the Portuguese Science and Technology Foundation (FCT).  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** The data presented in this study are available on request from the corresponding author due to privacy restrictions.  
**Conflicts of Interest:** The authors declare no conflicts of interest.