esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract  
Cyanobacterial proliferations display rapid spatiotemporal variations that can interfere in the assessment of water contamination levels by microcystins (MC), and make necessary the use of integrative tools. This study evaluates the pertinence of bivalves _Anodonta anatina_ and _Dreissena'polymorpha_ as bioindicators of the presence of MC-producing cyanobacteria in water. Ingested MC accumulates into two fractions in bivalve tissues--the cellular free and the protein-bound fractions--both forming the total MC fraction. Mussels were exposed to the cyanobacteria _Planktothrix agardhi_ at densities producing an equivalent of 1, 10 and 100 \(\upmu\)g/L of intracellular MC, with the evaluation of: (i) cyanobacterial cells and MC daily intake by mussels, (ii) free and total MC kinetics in whole individuals (using all the tissues) or only in the digestive gland, during and after the exposure, (iii) bioaccumulation factors. For each species, the kinetics of the two accumulation fractions were compared to evaluate which one best reflect levels and dynamics of MC-producing cyanobacteria in water. Results showed that the dynamic of free MC in bivalve tissues better highlight the dynamic of intracellular MC in water. Using whole \(D\)_. polymorpha_ may be appropriate to reveal and discriminate the water contamination levels above densities of cyanobacteria producing 1 \(\upmu\)g MC/L. Digestive glands of _A. anatina_ appeared more sensitive to reveal low environmental concentration, but without direct correlation with levels of water contamination. Further experimentations in situ are necessary to confirm those results in order to propose the use of freshwater bivalves for a biomonitoring of MC-producing cyanobacteria in fresh waters.  
microystins; bioaccumulation; _Anodonta anatina; Dreissena polymorpha_
## 5 State-of-the-Art and Open Challenges
### Hybrid vNF Implementation
The proposed architecture can offload specified components of a network function, and at the same time provide support in situations where NF offloading is not desirable. The management component of the framework comprises: (1) an interface for service providers (the user module), which can be used by users to initiate or stop an offload request; (2) a module for translating offload code that has been compiled for installation on data-plane programmable devices, (3) a module that serves as the offload manager,for handling compiled offload code and communication with the NFV component; and (4) NFV and SDN modules for handling connections to the controller, topological data, and flow rule installation (SDN module), while communication with the offload agents on the network functions is handled by the NFV module. Although the proposal presented by [PERSON] et al. [103] aims to push some components of network functions down to the data plane of the network, it is not entirely a hybrid framework that composes packet processing pipelines from diverse NFV frameworks. Similarly, refs. [100; 101; 102] attempted to solve the problem of data plane and user-space packet processing using network functions built from the same framework(s).
## 3 Results and Discussion
### Total Polypphenols, Carotenoids, and Antioxidant Capacity of TPW, TPW-PEEL, and TPW-SEED
As expected, the amounts of lycopene were significantly  
higher compared to \(\beta\)-carotene, and the pigment was predominantly found in TPW-PEEL, while the amounts in TPW-SEED were significantly lower (214.5 \(\pm\) 0.9 mg/100 g and 51.6 \(\pm\) 0.2 mg/100 g, respectively). Similar differences, even though less pronounced, were obtained for \(\beta\)-carotene content that ranged from 10.3 \(\pm\) 0.1 mg/100 g in TPW-SEED to 18.7 \(\pm\) 0.2 in TPW-PEEL. Our results are consistent with the recent review [52] reporting that tomato peels are rich in lycopene, accounting for 80-90% of total carotenoids, with lycopene content ranging from 50 to 1930 mg/100 g whereas tomato seeds contain much lower lycopene levels, around 22-37 mg/100 g. As seen from the presented data, type of TPW drying (air drying at 70 \({}^{\circ}\)C or lyophilization) did not have significant effect on the amounts of \(\beta\)-carotene (12.8 \(\pm\) 0.3 and 12.8 \(\pm\) 0.1 mg/100 g, respectively) but it significantly affected lycopene content (79.4 \(\pm\) 0.8 and 99.9 \(\pm\) 2.5 mg/100 g, respectively) suggesting more pronounced thermal instability of lycopene. This is consistent with the available literature data showing that during thermal processing of tomato pastes, lycopene content decreases with extended heating times, while \(\beta\)-carotene, though present in lower amounts, remains relatively more stable under the same conditions [75]. Figure 3: Impact of drying method and grinding degree on the content of total antioxidants, polyphenols (**a**), and \(\beta\)-carotene and lycopene (**b**). The data are presented as mean \(\pm\) SD. Statistical analysis was performed using one-way ANOVA followed by [PERSON]’s post hoc test. Different letters above the bars indicate statistically significant differences (\(p\) < 0.05) between samples within each measured component. TPW-70: tomato processing waste air dried at 70 \({}^{\circ}\)C; TPW-LIO: tomato processing waste dried by lyophilization; TPW-PEEL: peel fraction of tomato processing waste air dried at 70 \({}^{\circ}\)C; TPW-SEED: seed fraction of tomato processing waste air dried at 70 \({}^{\circ}\)C.
# Robustness Analysis on Graph Neural Networks Model for Event Detection
## 5 Experiments
### Model Performance on the Adversarial Data
#### 5.3.4 Model Robustness to Data Subpopulations  
The experimental results show that the performance of models upgrade where the length \(\leq 50\), while degrade where length \(>50\). The reason is obvious:  
* In the program, the model masks the filled placeholder (padding) at the end of the input sequence. When reading, humans also ignore meaningless symbols at the end of sentences. Therefore, a short sentence filled with placeholders still retains the original meaning.
* On the contrary, truncation affects the structural and semantic integrity of a long sentence (i.e., making the sentence incomplete and difficult to understand for both humans and machines); thus the important information may be lost.  
Most of the text in the original data are short sentences so that the performance of each model on length \(\leq 50\) is comparable to that of the original data. However, many associations between long-distance words exist in a long sentence, A-MDL-EEGCN and MOGANED significantly (\(p=0.05\)) outperform EE-GCN on length \(>50\), illustrating that it is essential to capture these associations in long sentences for ED. Moreover, the time consumption in the training of MOGANED (about 1000 s per epoch) is much longer than that of A-MDL-EEGCN and EE-GCN (about 6 s per epoch) in our experimental environment, illustrating that A-MDL-EEGCN is efficient and effective.  
The model's performance on Perplexity-0-20% is worse than that on Perplexity-0-50%, and the model's performance on Perplexity-0-50% is worse than that on the original data, indicating that the Perplexity of GPT-2 could measure the quality of the input text and the quality of the input text affects ED model performance. Perplexity-0-20% is the top 20% input texts in terms of Perplexity, and the models' F1 on it decreases by not more than 10, demonstrating that the GNN-based ED models are robust in regards to texts with high Perplexity. Moreover, more metrics than just Perplexity are needed to measure the quality of the input text to evaluate the ability of the ED model to detect events represented by low-quality text.
## 3 Results and Discussion
### Growth of CNPs on ITO  
The growth process of CNPs on ITO was investigated by chronopotentiometry (V-t characteristic curve) experiment with electrodeposition parameters of 5 A/dm\({}^{2}\) and 40 \({}^{\circ}\)C. The obtained potential-time curve (Figure 6a) can be divided into three stages during the growth process. At the beginning, a thin copper layer with a thickness of \(\sim\)200 nm was generated in the tiny gap between the AAO film and the ITO glass, as shown in Figure 6b. The gap distance between AAO film and ITO glass slightly changed in each experiment. Thus, the time for the first stage will have a tiny change. However, the varying distance does not affect subsequent stages. The first section of growth is to fill the gap and obtain a uniform copper layer, which will be the seed layer for the subsequent growth of the copper pillars. As long as the gap is filled, and a uniform seed layer is formed, copper nano-pillars could grow uniformly on this basis. The potential was extremely negative, indicating the difficulties for electrodeposition on ITO glass [20; 21]. It was believed that the surface of ITO glass (with the surface roughness of 0.312 nm) is relatively smooth and it is difficult to find nucleation sites. Hence, great negative potential was necessary to provide the drive force for copper atoms diffusion onto ITO glass. With the continuous deposition of copper atoms, a thin copper layer covered the ITO glass surface. The deposition on the copper layer was easier and the potential increased. After filling of gap between AAO film and ITO glass, Cu\({}^{2+}\) accumulated in the nano-pores and CNPs was formed (Figure 6c). It was difficult for Cu\({}^{2+}\) to pass through the nano-pores of the template, so the potential was still relatively negative to provide the drive force. As the heights of CNPs increased, the diffusion distance required for Cu\({}^{2+}\) to the deposition surface was shorter and the potential increased. At the last period, the potential is almost constant, indicating that the growth of CNPs finished and copper atoms deposited on the surface of the AAO film (Figure 6d).  
The electrodeposition process can be divided into four steps [22]. Firstly, the hydrated copper cations diffused from the electrolyte onto the cathode surface. Secondly, the hydrated copper cations transformed into copper atoms by dehydration and reduction. Thirdly, the copper atoms deposited onto the cathode surface. Finally, the deposited copper atoms incorporated into the ionic metal lattices and started to crystallize.
# Computational Complexity of Modified Blowfish Cryptographic Algorithm on Video Data
## 5 Conclusions  
Although Blowfish is one of the best cryptographic algorithms, it performs poorly when encrypting huge files. Therefore, there is a need to modify the algorithm. The structure of the F function of the algorithm was altered in this research by using two S-boxes rather than four as in the classic Blowfish algorithm. Regarding the outcome of estimating the time required to encrypt and decode a video file, as well as the execution time and throughput, the modified Blowfish algorithm outperforms Blowfish.  
The experimental results of our proposed modification of the time complexity and throughput are superior to the classic Blowfish algorithm, as the average execution time is 110.4 ms for the classic Blowfish while it is 108.9 ms for the modified Blowfish algorithm. Our approach achieves an improvement in terms of time complexity. Our approach achieves a throughput of 7.3% over the 5.4% of the classic Blowfish, which signifies that our proposed modified algorithm takes less time during the encryption of any video file. Based on the experimental results of this study, it is suggested to utilize the Blowfish encryption algorithm when encrypting sensitive data and applications, rather than the  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Video Size (kb)** & **Variance in Key (\%)** & \
\begin{tabular}{c} **Blowfish Algorithm** \\ **Avalanche Effect (\%)** \\ \end{tabular} &
\begin{tabular}{c} **Modified Blowfish** \\ **Algorithm Avalanche** \\ **Effect (\%)** \\ \end{tabular} \\ \hline
187 & 30 & 50.7176 & 43.3398 \\
342 & 30 & 50.5176 & 43.1653 \\
575 & 30 & 50.4782 & 42.9867 \\
762 & 30 & 50.4486 & 42.8815 \\
970 & 30 & 50.  
modified Blowfish, for better security. Otherwise, if speed and system resources are priorities, the modified Blowfish encryption technique is recommended. For instance, banking applications require a higher level of security while gaming applications require efficient time and memory to work effectively. Therefore, this study contributes to the literature together with providing a state-of-the-art study demonstrating that Blowfish or the modified Blowfish algorithm can be used to encrypt and decrypt any form of data (text, audio, image, and video).  
For further work, we plan to complete our approach in order to consider other performance metrics such as energy and a large video dataset of different file sizes to demonstrate the benefits of our approach.  
Conceptualization, A.E.A. and E.D.; methodology, E.D.; software, A.E.A.; validation, E.D., A.E.A., S.M. and A.B.J.; investigation, E.D. and A.E.A.; resources, A.E.A. and E.D.; data curation, E.D. and A.E.A.; writing-original draft preparation, E.D. and A.E.A.; writing-review and editing, S.M. and A.B.J.; supervision, S.M.; project administration, S.M. and A.B.J.; funding acquisition, S.M. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The data used in the study was randomly generated by the authors.  
Authors do not have any conflict of interest.
# Signal Detection Based on Separable CNN for OTFS Communication Systems
## 3 Problem Formulation
### Input-Output Relationship  
By vectorizing the DD-domain signals, the overall input-output relationship of the OTFS system can be expressed as:  
\[\mathbf{y}=\mathbf{H}_{\text{DD}}\mathbf{x}+\mathbf{w}, \tag{7}\]  
Figure 1: OTFS system.  
where \(\mathbf{x}=\text{vec}(x[k,l])\) is the transmitted symbol vector, \(\mathbf{y}=\text{vec}(y[k,l])\) is the received symbol vector, \(\mathbf{H}_{\text{DD}}\in\mathbb{C}^{NM\times NM}\) is the DD-domain channel matrix, and \(\mathbf{w}\sim\mathcal{CN}(\mathbf{0},N_{0}\mathbf{I})\) is the vectorized noise.
### Related Work  
The impact of UAV deployment has been intensively investigated in [14; 15; 16; 17; 18]. To optimize the 3D deployment of UAVs, the authors in [14] establish an integer linear programming model, while the authors in [15] approximate the rate expression to identify the concave regions and to apply alternating optimization. Particle swarm optimization [16] and game-theoretic framework [17] are also studied to optimize UAV deployment. Differently, ref. [18] not only determines the 3D coordinates but also minimizes the number of UAVs, in which a K-Means algorithm is proposed.  
The work in [23; 24] focuses on the caching problems in UAV-assisted networks. In [23], the caching strategy is optimized by investigating the user request preference with the aid of latent Dirichlet allocation, while [24] proposes a dual dynamic adaptive caching algorithm. Refs. [9; 10; 11] consider the optimization of UAV location and caching strategy. Refs. [19; 20] focus on beamforming and caching optimization in cellular networks, in which the locations of base stations are fixed, different from UAV scenarios. Ref. [21] optimizes UAV location and beamforming jointly, where a framework based on difference of convex (DC) is proposed. Moreover, UAV trajectory is considered in [25; 26], while resource is considered in [27; 28]. Ref. [12] jointly optimizes resource, deployment and caching; ref. [22] jointly optimizes UAV location, beamforming, and power control; and ref. [13] optimizes UAV location, association, caching and computing resource. Much research has been carried out in the field of cache-enable UAV-assisted communications. However, we find that existing work has not sufficiently considered the impact of the joint design of UAV caching, beamforming and location, and the optimization in this scenario remains an open problem.
# Signal Detection for Ambient Backscatter Communication with OFDM Carriers
## 5 Conclusions  
In this paper, we have studied the signal detection for the AmBC system with OFDM carriers, while providing some key mathematical insights underlying this theory and proposing an improved energy detector with optimum power orders. Especially, in order to maximize the probability of correct detection, the power order of energy detector was chosen subject to the target probability of false alarm. The proposed detector was shown to improve energy efficiency for spectrum sharing via AmBC.  
Moreover, based on the insightful results we suggest the following directions for future work.  
1. Regarding tag operation, an important direction is to come up with a model that examines the energy harvesting model and enhances the detection performance accordingly.
2. In our problem formulation, we use a simple noise uncertainty model, i.e., the variance of \(v(n)\) is assumed to be bounded by a given number \(B\). This value depends only on a single value \(\rho\), thus, it may not incorporate the RF strength and other changes in the environments. Therefore, we need to investigate other nonlinear models that relate to energy detector's inherent noise uncertainty.
3. We have shown that the proposed energy detector can be effective for the AmBC system with OFDM carriers. However, it needs more theoretical bounds on \(D\) and SNR \(\gamma\) along with numerical results.
4. In the problem formulation, we assumed that the tag has two states: backscattering and non-backscattering, while in practice its antenna load may switch among three states: no reflecting, reflecting in the same phase, and reflecting in the opposite phase, resulting in a ternary signal \(B(n)\). Thus, we need to design a waveform \(x(n)\) to convey the corresponding bits.  
We expect that the above future directions can contribute to the advancement of energy detection and estimation areas.  
Figure 6: ROC curve with SNR \(\gamma\). An ROC curve is obtained by taking the average over 100 independent trials. From the figure, for each false alarm rate \(P_{f}\), there is a SNR value \(\gamma\) for achieving the objective probability of correct detection \(P_{d}\).  
**Author Contributions:** The work was realized with the collaboration of all the authors. T.L.N.N. contributed to the main results and code implementation. Y.S., J.Y.K. and D.I.K. organized the work, provided the funding, supervised the research and reviewed the draft of the paper. All authors discussed the results, approved the final version, and wrote the paper.  
**Funding:** This work was supported by the National Research Foundation of Korea grant funded by the Korean government (MSIT) (2014 RIA5A1011478).  
**Conflicts of Interest:** The authors declare no conflict of interest.
## 2 Initial Phase of NCS Prior to 2000
The above method can adjust the sampling period to be as minimum as possible, allocating all the network bandwidth. The basic properties of real time distributed systems were compared in Reference [25]. In addition, the characteristics of time triggered and event-triggered distributed systems in robotics were discussed in References [26; 27] using the artificial intelligence, particularly focusing on the predictability, resource utilization, extensibility, etc. In Reference [28], the authors achieved the asymptotic stability and improved controller performance by scheduling the use of the network. At the end of 20 th century, a basic controller called an event-based proportional-integral-derivative (PID) controller was described in Reference [29], decreasing the resource consumption, only with the deprivation in the performance of trivial control. The proposed work was validated with simulations on a double-tank process. Next, two types of algorithms were suggested in Reference [30] for approximating the plant operation: one was an open-loop arrangement analyst, and the other was a closed-loop arrangement analyst/predictor. Again, the NCS's stability was analyzed in Reference [31], showing the effects of sampling rate manipulation and network delay on the system stability. The above historical developments are summarized in tabular form in Table 2 on the basis of area/network/parameter. Table 2 shows the distribution of available papers in the different areas prior to year 2000: on decentralized-based networks, there are around 10 papers; on smart network-based systems, there are around 9 papers (during this period, the smart networks are in development stage); stable and robust networks can be found in all types of networks. The table here describes about the evolution of networked systems from decentralization of the available conventional networks. As there are many shortcomings in decentralized systems, the evolution of smart/wireless networks/discreet event-based networks came into existence. The distribution of the papers prior to 2000 is shown in Figure 3. The majority of the works are related to decentralized networks, followed by smart networks, and only a small percentage of works dealt with stable/robust networks. \begin{table}
\begin{tabular}{c c c} \hline \hline
**S.No.** & **Papers** & **Parameter/Area/Network** \\ \hline
1 & [11; 12; 13; 14; 15; 16; 17; 18; 19; 23] & Decentralized, Robust Control Network \\ \hline
2 & [20; 21; 22; 24; 25; 26; 27; 28; 29] & Smart, Wireless and Discreet Control Networks \\ \hline
3 & [30; 31] & Stable and Robust Networks \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Summarized discussion of development of NCS prior to 2000.