esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Antioxidant Activity  
The antioxidant and oxidoreductase characteristics of the extracts are presented in Table 3.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Extracts** & \begin{tabular}{c} **TFC** \\ **(mg QE/g dw)** \\ \end{tabular} & \
\begin{tabular}{c} **TPC** \\ **(mg GAE/g dw)** \\ \end{tabular} &
\begin{tabular}{c} **TTC** \\ **(mg linalool/g dw)** \\ \end{tabular} \\ \hline Water & 0.64 \(\pm\) 0.01 \({}^{\text{a}}\) & 2.08 \(\pm\) 0.06 \({}^{\text{a}}\) & 47.3 \(\pm\) 0.3 \({}^{\text{a}}\) \\ Ethanol & 8.85 \(\pm\) 0.03 \({}^{\text{e}}\) & 9.78 \(\pm\) 0.18 \({}^{\text{e}}\) & 427.7 \(\pm\) 2.6 \({}^{\text{c}}\) \\ Methanol & 5.90 \(\pm\) 0.02 \({}^{\text{b}}\) & 9.33 \(\pm\) 0.28 \({}^{\text{d}}\) & 384.0 \(\pm\) 0.4 \({}^{\text{b}}\) \\ Propanol & 6.18 \(\pm\) 0.03 \({}^{\text{c}}\) & 8.27 \(\pm\) 0.18 \({}^{\text{b}}\) & 429.6 \(\pm\) 1.8 \({}^{\text{c}}\) \\ Acetone & 7.87 \(\pm\) 0.05 \({}^{\text{d}}\) & 8.74 \(\pm\) 0.19 \({}^{\text{c}}\) & 587.9 \(\pm\) 0.7 \({}^{\text{d}}\) \\ \hline \hline \end{tabular}
\end{table}
Table 2: Total flavonoid content (TFC), total polyphenols content (TPC), and total terpenoid content (TTC) of extracts. Different lower-case letters mean statistically different values (_p_ = 0.05).  
The acetone fraction had the highest (\(p<0.05\)) FRAP value, and the lowest (\(p<0.05\)) was with the water fraction. The FRAP values of the remaining fractions were nearly identical. These findings are consistent with previous research on the antioxidant activity of plant extracts. [PERSON] and [PERSON] [36] reported that the FRAP values of most of the plants in their study were less than 2 uM after evaluating the antioxidant properties of 20 medicinal plant extracts traditionally used in Aymvice medicine in Sri Lanka. A recent study by [PERSON] et al. [37] provided the antioxidant results of Apocynum hendersonii extracts quite similar to our results, especially for FRAP.  
Extracts obtained from organic solvents were found to have higher (\(p<0.05\)) antioxidant power than water-based extracts. [PERSON] and [PERSON] [38] found that the water-based extract of Hibiscus cannabinus leaf extracts had the lowest reducing power, which was attributed to the low solubility of the antioxidant constituents in water, and this corresponds to the ABTS and DPPH results obtained in this study. Except for the water extract, which had an ABTS value of 0.97 \(\pm\) 0.05 mg TE/g dw (\(p<0.05\)), all of the ABTS values were in the 4 mg TE/g dw range (\(p>0.05\)). This was also the case for DPPH, with the water extract having a DPPH value of 0.95 \(\pm\) 0.01 mg TE/g (\(p<0.05\)).  
The ethanol extract outperformed the methanol and acetone extracts in terms of DPPH scavenging activity. According to [PERSON] and [PERSON] [39], studying 11 medicinal plants, all plant extracts had DPPH values less than 2 mg TE/g, and 9 of the plant extracts had values less than 4 mg TE/g. In fact, our study demonstrates higher antioxidant activity than some previous analyses on medicinal plants.
###### Abstract  
The effects on liver and intestinal histomorphology and on intestinal microbiota in gilthead seabream (_Sparus aurata_) fed diets that contained poultry by-product meal (PBM) and hydrolyzed feather meal (HFM) as fishhead replacements were studied. Fish fed on a series of isointrogenous and isoenergetic diets, where fishhead protein of the control diet (FM diet) was replaced by either PBM or by HFM at 25%, 50% and 100% without amino acid supplementation (PBM25, PBM50, PBM100, HFM25, HFM50 and HFM100 diets) or supplemented with lysine and methionine (PBM25+, PBM50+, HFM25+ and HFM50+ diets). The use of PBM and HFM at 25% fishhead replacement generated a similar height histopathology to FM-fed fish, indicating that both land animal proteins are highly digestible at low FM replacement levels. However, 50% and 100% FM replacement levels by either PBM or HFM resulted in pronounced hepatic alterations in fish with the latter causing more severe degradation of the liver. Dietary amino acid supplementation delivered an improved tissue histology signifying their importance at high FM replacement levels. Intestinal microbiota was dominated by _Proteobacteria_ (58.8%) and _Actinobacteria_ (32.4%) in all dietary groups, but no specific pattern was observed among them at any taxonomic level. This finding was probably driven by the high inter-individual variability observed.  
nutrition; aquaculture; fishhead replacement; land animal proteins; histology; intestinal microbiota; _Sparus aurata_
## 1 Introduction
They found that LF-EHAD can promote the dissociation of hydrates and the heat distribution is more uniform than wellbore electric heating, avoiding wellbore instability caused by continuous high temperatures [23]. Previous research work has effectively improved the technical feasibility of the non-fluid-assisted thermal method in NGH mining. The group well mining scheme is an inevitable choice for the future industrial development of hydrates, and the vertical well is an important basic well type of the group well mining scheme. It is necessary to further study the application strategy of assisted heating methods in vertical well depressurization. On-site testing is difficult and costly, and numerical simulation methods are the best choice for studying the large-scale development of NGHs. Some well-known simulators include TOUGH+HYDRATE, CMG-STARS, MH21-HYDRES, STOMP-HYD, etc. [24; 25; 26; 27]. Except for TOUGH+HYDRATE and CMG-STARS, which are widely used, other simulators are limited to use by development departments because of technical confidentiality and intellectual property reasons. TOUGH+HYDRATE is specifically developed for hydrate exploitation simulation and has the best applicability, although its disadvantage is weak pre- and post-processing. CMG is not specifically developed for simulating hydrate extraction, and its description of hydrate characteristics may be insufficient, but it has more advantages in pre- and post-processing. This work adopted TOUGH+HYDRATE and numerically analyzed the effects of different heating parameters such as heating power, heating location, heating time, and heating mode on gas production in a Class 1-type hydrate reservoir with a single vertical well depressurization and proposed an efficient application strategy for assisted in situ electric heating. The research results provide a reference for hydrate extraction in the Shenhu Sea area.
# Spectral Domain-Based Data-Embedding Mechanisms for Display-to-Camera Communication
## 3 Performance Evaluation and Results
### BER vs PSNR  
Figure 7a presents the simulated BER performance of all three data-embedding mechanisms with respect to the PSNR values. For this simulation, we considered the scenario in which the data-embedded images were not affected by channel noise. To observe the effect of geometric image rotation on BER performance, we rotated the data-embedded images by \(10^{\circ}\). In all three mechanisms, we can observe the degradation of BER performance with increasing PSNR. However, at similar BER values, M1 outperformed M2 and M3 in terms of PSNR. When data were directly added to the selected frequency coefficients, the intensity of image pixel was less affected, and thus the PSNR of M1 was better than others. Furthermore, we can observe a significant increment of BER for all mechanisms when the PSNR increased along the x-axis. Although a higher PSNR indicates better image quality, it is achieved in the cost of degraded communication performance. From Equations (3)-(5), we can note that the PSNR has an inverse relationship with \(\alpha\). With a small value of \(\alpha\), the visual quality of the data-embedded image is well preserved, and the PSNR value is high. On the other hand, a larger \(\alpha\) tends to degrade image quality and the PSNR value becomes low. In Figure 7b, when the size of \(\mathbf{b}\) was increased from 250 to 500, we can see that BER performance is slightly degraded. However, since this result is caused by sending data twice as much, the user can control this trade-off relationship according to the communication requirements of the target system.  
Figure 8 depicts the BER performance under real-world conditions with optical wireless channel, using a commercial display and off-the-shelf smartphone camera. It can be seen from the figure that the trend of the overall curves is similar to that of Figure 7. For M1, M2, and M3, the BER is observed to be poorer for a higher PSNR level, resulting in a degradation of communication performance. As a wireless optical channel was introduced between the display and camera during the real-world experiment, the system was more resilient to errors, leading to a much greater deterioration of the BER than in the previous experimental results of Figure 7.  
Figure 7: Bit error rate (BER) performance with respect to PSNR [dB], in simulations in which images were rotated at the receiver. (**a**) \(m=250\) and (**b**) \(m=500\).
## 4 The Proposed Adaptive Channel Coding Technique
### The Outer Loop Link Adaptation Approach  
The outer loop link adaptation approach consists of the MCS level selection which is performed as described below:  
* If a certain number of ACKs are successively successfully decoded at the NB-IoT receiver, then the MCS level is increased. * On the other hand, when a certain number of NACKs are successively decoded at the NB-IoT receiver, then the MCS level is decreased. In general, the number of ACKs is greater than that of NACKs to ensure a slow increase of the MCS level with ACK feedback and a quick decrease of the MCS level with NACK feedback. Due to the narrowband and low data rate for NB-IoT systems, the settings for LTE systems may not be applicable. Therefore, two aperiodic and event-based actions are defined for the EEACC approach namely the fast upgrade (FUG) and the emergency downgrade (EDG). In the event of FUG, the MCS is increased by one while in the event of an EDG it is decreased by one.
# Design and Performance Analysis of Navigation Signal Based on OFDM
## 4 Analysis of ACF and PSD
### Modulation Parameter Analysis
#### 4.1.4 Effect of Cyclic Prefix Length on Navigation Characteristics  
We assume that the bandwidth of the receiver is much larger than that of the navigation signal, ignoring the effect of the filter on the signal. Similar to the analysis in Section 4.1.3, when the other experimental conditions are unchanged, the length of the cyclic prefix mode is changed and successively set as \(T_{g}=(10,20,32,64)\Delta t\). Figure 8a shows that for different cyclic prefix lengths, the main peak of the ACF and the secondary peak near the main peak basically do not change. Near the horizontal coordinate 1 us, the secondary peak caused by the cyclic prefix mode increases with the increase in cyclic prefix, but the position and width of this secondary peak basically do not change. The length of the cyclic prefix is generally determined according to the maximum multipath delay in the actual application environment. As can be seen from the figure, the smaller the length of the cyclic prefix, the lower the peak value of the secondary peak in the ACF of the OFDM navigation signal. Therefore, choosing a smaller length of cyclic prefix can reduce the peak value of the ACF secondary peak and avoid the false lock of the code tracking loop. As can be seen in Figure 8b, when the cyclic prefix increases, the main lobe bandwidth occupied by the PSD of the OFDM navigation signal remains unchanged, and the PSD will slightly increase.
## 2 Convert Information Mapping Aided GSDM  
As shown in Figure 1, a directional modulation system which transmits in free space is considered in this paper. The transmitter Alice is equipped with \(N_{t}\) antennas and the legitimate Bob is equipped with \(N_{r}\) cooperative single-antenna receivers, which are located in different spatial directions and are linked through optical fibers. In addition, there are \(N_{u}\) receivers at Bob activated in communication where \(N_{u}<N_{r}\). That is to say, only part of receivers at Bob are participated in transmission. Meanwhile, it is assumed that Eve is equipped with \(N_{e}\) cooperative single-antenna receivers linked through optical fibers as well, which sends nothing to hide itself and try its best to eavesdrop. In this section, the GSDM system will be introduced at first and followed by the proposed CIM-GSDM system in details.
# Amodal Segmentation Just Like Doing a Jigsaw
## 3 Methods  
### The Architecture of ARCNN  
On the basis of Faster-RCNN [12], Mask-RCNN [4] adds the mask head to generate the mask of the object, and modifies RoI pooling to RoI Align to deal with the problem that the mask is not aligned with the object in the original image. ORCNN [6] can directly predict the amodal mask and visible mask of the object by adding a mask head on the basis of Mask R-CNN [4].  
Our Amodal R-CNN (ARCNN) is shown in Figure 2. Inspired by Occlusion R-CNN (ORCNN) [6], we extend Mask R-CNN (MRCNN) [4] with two additional heads to predict amodal masks (amodal mask head) and the occlusion masks (occlusion mask head). As for the original mask head of MRCNN, it's used to predict visible masks(visible mask head). Different from ORCNN, our ARCNN predicts the amodal mask by flattening the visible mask and occlusion mask  
Figure 2: The architecture of ARCNN.  
Firstly, image features are extracted by the ResNet50 [18]. In order to take into account the effect of object segmentation of different sizes, we perform multi-scale fusion of features. After these features are sent to FPN [19] for multi-scale fusion, they are input into the RPN to generate proposals. RPN is a network used to generate an area and determine whether there is a possible object in it. For areas where there may be a object, RPN will output it as a proposal. The proposals then are sent to RoIAlign to get RoIs as the input of visible mask head and occlusion mask head. The outputs of these two mask heads correspond to the visible and occlusion masks, respectively. Finally, the output of visible mask head and occlusion mask head are concated, then sent to the amodal mask head to obtain the amodal mask. Among them, in order to make the generated proposals can include the visible mask and occlusion mask of the instance, the RPN is trained with the bounding box of the amodal instance as the ground truth.  
The visible mask head and occlusion mask head have the same structure, that is, four cascaded 3 \(\times\) 3 convolutional layers, a 2 \(\times\) 2 deconvolutional layer with stride 2, a 1 \(\times\) 1 convolutional layer. These convolutional layers are used to predict the visible mask and the occlusion mask by using features from RoIs. The amodal mask head is a 1 \(\times\) 1 convolutional layer, which is used to flatten the visible mask and the occlusion mask.  
We propose the method to concat the visible mask and occlusion mask of the instance in a jigsaw-like operation so that we can decompose the prediction of the amodal mask into the prediction of the visible mask and the occlusion mask and make each branch focus on the modeling of the object. So as to better cope with the challenges brought by the complex task of amodal segmentation.
# Exploring the Spectral Variability of Estonian Lakes Using Spaceborne Imaging Spectroscopy
## 2 Materials and Methods
### Data Processing
Environmental data (i.e., lake surface water temperature) were downloaded from ERA5 to support the discussion. Application n.8 concerns the detection of submerged, floating, and emergent macrophytes in Lake Vortsjarv. Spectral signatures were extracted from selected 3 \(\times\) 3 pixel ROIs and compared with the literature. Application n.9, related to the estimation of the surface reflectance of an image acquired over Lake Vortsjarv covered by ice and snow, was performed through the integration of surface reflectance across the visible and near-infrared spectrum [85].
# Secure and Transparent Space Exploration Data Management Using a Hybrid Blockchain Model
## 3 Proposed Model  
### Hybrid Blockchain Data Storage Strategy  
In the hybrid model, all mission data are classified as either public data or private data based on their sensitivity level. Public data includes information such as mission logs and general scientific findings, which can be accessed by all users and are directly stored on the public blockchain, allowing anyone to verify them. Due to the high storage cost of directly writing data to the blockchain, only the cryptographic hash of the original data is stored on-chain. A smart contract is used to encapsulate the hash value and relevant metadata, and users can call the smart contract to retrieve the metadata and verify the integrity of the data via hash comparison. Private data, on the other hand, includes confidential records such as astronaut medical histories or proprietary mission strategies, which are stored on a permissioned blockchain to restrict access and maintain confidentiality.  
To achieve this, the proposed system adopts a layered architecture that separates the public and private domains while maintaining secure interoperability. Public blockchain components, such as the Ethereum Linea Testnet, are leveraged for their transparency and auditability features, ensuring that all public information remains tamper-evident and verifiable. Private blockchain components, specifically Hyperledger Fabric, are used due to their modular architecture and fine-grained access control capabilities. Hyperledger Fabric's support for permissioned membership and its use of the Practical Byzantine Fault Tolerance consensus algorithm enables low-latency transactions and enhanced control over user roles and permissions.  
The two blockchain environments are synchronized via a dedicated interoperability layer powered by Chainlink's cross-chain interoperability protocol. CCIP enables real-time, event-driven data synchronization by allowing signed and authenticated messages to be transferred between the chains. This ensures that when a change occurs on the private blockchain, the corresponding integrity proof is securely and automatically relayed to the public chain without disclosing the raw data itself. By replacing traditional centralized oracles with CCIP, the system avoids single points of failure and ensures decentralized validation of cross-chain interactions. The overall architecture and performance summary are presented in Table 1. And Figure 1 shows a hybrid blockchain model where each country stores sensitive data on a private blockchain and shares verified public data through a public blockchain. Zero-knowledge proofs are used to ensure data integrity without exposing the actual content.
## 6 Conclusions and Future Directions
### Future Directions
#### 6.2.2 Accuracy Enhancement Strategies  
Study error propagation mechanisms. From trajectories to paths, from paths to parameters, each step may introduce errors. Error propagation models need to be established to quantitatively assess final parameter uncertainty.  
Explore active learning strategies. Identify high-uncertainty situations during parameter extraction, gradually improving overall accuracy through manual annotation or supplementary data.
## 3 Problem Statement  
The prevailing approach in pedestrian re-identification involves feeding the entire image into a neural network and then extracting image features through multiple layers of neural networks. By comparing the similarity of different image features, it is determined whether the target pedestrian is present. However, this recognition process faces the following challenges:  
Existing methods based on the entire pedestrian image unavoidably introduce background information. Extracting only the pedestrian foreground as input is a natural way to mitigate background interference. Ideally, using a clean pedestrian foreground devoid of any background would significantly enhance pedestrian recognition accuracy. Unfortunately, there is currently no mature pedestrian extraction network specifically designed for pedestrian re-identification. The mainstream pedestrian instance segmentation networks cannot accurately extract the pedestrian foreground. Extracted pedestrian foregrounds suffer from issues such as background information and missing features, leading to discrepancies between segmented and true pedestrian foregrounds. Relying solely on imprecise segmentation results as input for pedestrian re-identification not only fails to improve recognition accuracy but may even degrade performance to some extent. To address these challenges, one potential approach is to incorporate pedestrian masks as an additional input dimension. These masks not only include the pedestrian's contour information but also provide approximate location details within the image. By utilizing masks as input, we can enrich the feature information used for pedestrian recognition.  
Pedestrian image edges typically represent abrupt changes in brightness or color within an image. These edges can reveal object contours, textures, shapes, and structures, containing rich detail features. While edge features have been widely applied in fields such as object detection, image segmentation, and image enhancement, they are currently underexplored in the domain of pedestrian re-identification. Introducing edge features into pedestrian re-identification tasks and studying their impact on re-identification performance is meaningful.  
Different parts of pedestrians exhibit unique semantic features, and there exists a natural intrinsic connection between these parts. Exploring the inherent relationships among different body parts of the same pedestrian contributes to enriching their features. Some scholars have proposed using hard segmentation to divide pedestrian images into distinct parts, thereby investigating the relationships among these segments. However, hard segmentation compromises the semantic integrity of different pedestrian body parts. Besides, each segmented part contains substantial background information, which adversely affects the extraction of component features.
# IAACaaS: IoT Application-Scoped Access Control as a Service +
## 3 System Requirements for Access Control in IoT
### Flexible  
In order for the AC architecture to be used in all security contexts, the framework for describing authorization policies should fit the level of granularity that the service administrator desires. For this purpose, (a global nonprofit consortium that works on the standards definition for security, IoT and other areas) standardized the eXtensible Access Control Markup Language (XACML) [22], which allows the definition of fine-grained policies. XACML serves as a standard not only for the format of authorization policies and evaluation logic, but also for that of the request/response interactions that take place during an authorization decision. In any case, either this one or any other policy description language should be used, so that a multi-tenant authorization scheme can be created in the exact way that the administrator wishes.