esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Discussion
### Implications for the Viability of Chemical Looping Combustion  
In a parallel study, LD-slag from the same source as used here has been examined as an oxygen carrier for chemical looping combustion in small pilot reactors for gaseous fuels and for biomass [28]. The results reported in the study were positive and suggested that LD-slag could be an attractive oxygen carrier for this process. The study presented here verifies that production of LD-slag particles of suitable size can be scaled up and constitutes a practically viable bed material for a CFB boiler of significant size, utilizing high gas velocities. Further, the bed samples extracted during the campaign presented in this paper have been analysed in a separate study [23], in which, among other things, it was shown that LD-slag was not deactivated by biomass ash during operation, but largely retained its reactivity with fuel gases. Together, these three studies suggest that LD-slag could indeed be a good choice for bed material in chemical looping combustion, especially for solid fuels such as biomass. Good availability and potentially very low cost are other attractive properties of LD-slag as an oxygen carrier for chemical looping combustion.
# Explainable Two-Layer Mode Machine Learning Method for Hyperspectral Image Classification
## 1 Introduction
First, a two-layer mode machine learning method for HSI classification is proposed, combining the data re-expression and classification layers. Second, entropy-rate superpixel segmentation is used to reduce the impact of homogeneity and heterogeneity caused by different geographical locations. Third, an explainable mathematical model employs the \(l_{2,1}\) norm, the graph regulation term, which maintains the robustness and inherent geometric local structure of HSI data. Figure 1: Structure diagram of two-layer mode machine learning method. Fourth, numerical comparison on three HSI data sets, i.e., TeaFarm, Salinas, and Indian Pines datasets, with the existing HSI classification methods indicate that the proposed method works well.
## 3 Survey of Techniques for Updating
### Dissemination
#### 3.1.6 Multihop Network Reprogramming (MNP)  
MNP [32] is targeted at MICA2 motes running TinyOS and the XNP boot-loader. The protocol operates in four phases. During Advertisement/Request sources advertise the new version of the code, and interested nodes make requests. Sources overhear all other advertisements and requests--a suppression scheme to avoid network overload. During Forward/Download a source broadcasts a _StartDownload_ message to prepare the receivers, and then sends the program code a packet at a time: there is no ack. During Query/Update the source broadcasts a Query to all its receivers, which respond by unicast asking for the missing packets. Receivers, having received the full image, now become source nodes and start advertising. During Reboot, entered when a source receives no requests in response to an advertisement, the new program image is transferred to program memory, and the node reboots with the new code. Download requests are sent to all sources to reduce the hidden terminal effect, and select only one active sender in a neighborhood. Flow control is rate based, determined by the EEPROM write speed.  
MNP provides dissemination and activation of updates, but no additional significant features supporting autonomous updates.
### Protein and Amino Acid Profile Determination  
The total cellular protein content was assessed following the biuret method, as detailed in a previous study [24]. Protein concentration was quantified in terms of albumin equivalents and expressed as a percentage of dry biomass (P/x%).  
The amino acid composition of the microalgae was determined following acid hydrolysis (6 N, 110 \({}^{\circ}\)C, 24 h) and derivatization using AccQ-Tag\({}^{\text{TM}}\) Ultra, in line with the amino acid analysis application solution (Waters Corporation, Milford, MA, USA) and [PERSON] et al. (2020) [26]. DL-Norvaline (Sigma) 2.5 mM was used as an internal standard. Ultra-Performance Liquid Chromatography (UPLC) was conducted on an Acquity system (Waters Corporation) equipped with a photodiode array (PDA) detector, with the detection wavelength set to \(\lambda\) = 260 nm. A BEH C18, (100 mm \(\times\) 2.1 mm i.d., 1.7 \(\upmu\)m) from Waters was used, with a flow rate of 0.7 mL/min and the column temperature was maintained at 55 \({}^{\circ}\)C. Peak identification and integration were carried out using Empower v.2.0 software (Waters), employing Amino Acid Standard H (Thermo Scientific, Waltham, MA, USA) as an external standard. All analyses were performed in duplicate. If the replicate values did not meet the standardized acceptance criteria based on mean and standard deviation (<5%), new duplicate analyses were carried out in accordance with established protocols. It is noted that tryptophan was not quantified due to its sensitivity to acid hydrolysis, while cysteine reacted with cysteine, forming a disulfide bond to generate cystine.  
In addition, during acid hydrolysis, asparagine is converted to aspartate (i.e., the ionic form of aspartic acid) and glutamine to glutamate (i.e., the ionic form of glutamic acid). Therefore, the reported values for these amino acids represent the sum of both amino acids.
# Proxy Signature-Based Management Model of Sharing Energy Storage in Blockchain Environment
## 2 SES and Its Management Model
### Management Model of SES
A flowchart for selecting the appropriate management model of SES is shown in Figure 2. The owners can select the right management model considering the energy storage scale, budget cost, profit expectation, management ability and market rules. As shown in Figure 2, firstly, the energy storage resources held by the owner are checked, and one or more target markets to participate in are chosen according to the scale and type of energy storage resources and the requirements of theowner. In addition, the budget cost and management capacity of human resources and facilities of the owner are evaluated to assist the decision-making of the management model. Moreover, the rules of energy storage facilities for the target markets are analyzed and the market access conditions for the given types of energy storage resources can be obtained. If the energy storage of the owner cannot meet the access conditions, the owner needs to participate in the markets jointly with other owners of small-scale energy storage resources under the aggregation of an SESO. The owner can delegate all the management rights to the SESO provided his budget cost and management capacity is insufficient--i.e., the many-to-one full delegation model is selected. Otherwise, the owner can select the many-to-one partial delegation model where only the transaction rights are delegated to the SESO. On the other hand, if the energy storage of the owner can meet the access conditions, the owner can participate in the markets as an independent market entity. Provided that the owner is a mature operator who has a sufficient budget, management capacity, market experience and information sources, the self-operation model is suitable for him due to the higher profit expectation. Otherwise, the one-to-one full delegation model and the one-to-one partial delegation model can be selected according to the evaluation of the above indexes for the owner. Figure 2: The flowchart for selecting the appropriate management model of SES.
# A Pilot Study of Stacked Autoencoders for Ship Mode Classification
## 4 Approach
### Composition of Models for Comparison Experiments  
We performed experiments on SAE models that had various structures and latent layer sizes to find the best SAE model. The hidden layers of the model were all fully connected, and a rectified linear unit (ReLU) activation function was used. A total of five model structures were employed in the comparison experiments. We used (depth, size) to express the model structures and depict the composition of the models. Here, depth refers to the number of hidden layers in the encoder and decoder, including the latent layer. Size refers to the number of neurons in the first hidden layer of the encoder. The encoder had a structure in which the number of hidden layer neurons decreased by half compared to that in the previous layer. Additionally, the decoder structure was symmetrical with the encoder structure. Table 4 shows the structures of the models used in the comparison experiments.  
\begin{table}
\begin{tabular}{c c} \hline
**Structure (Depth, Size)** & **Neurons in Each Layer** \\ \hline \((5,32)\) & 32–16-size of the latent layer-16–32 \\ \((5,64)\) & 64–32-size of the latent layer-32–64 \\ \((5,128)\) & 128–64-size of the latent layer-64–128 \\ \((7,64)\) & 64–32–16-size of the latent layer-16–32–64 \\ \((7,128)\) & 128–64–32-size of the latent layer-32–64–128 \\ \hline \end{tabular}
\end{table}
Table 4: Structures of the models for comparison.  
Here, to find the exact size of the latent layer, we performed experiments that changed the latent layer values to 3, 6, 9, and 12. In addition, the collected dataset was divided into training, testing, and validation datasets to prevent the overfitting problem when training the classification model. Further, 60% of the entire dataset was used as the training dataset, and 20% was used as the testing dataset. The last 20% of the dataset was utilized as the validation dataset. Furthermore, an Adam optimizer [36] was employed as the optimization function in the training of all models, and a value of \(1\times 10^{-4}\) was used as the learning rate. The evaluation experiments for comparison were performed with the Python, Scikit-Learn, and TensorFlow libraries.
## 6 Conclusions  
A new hybrid opportunistic scheduling method was presented in multi-antenna full-duplex systems with partial CSIT where the effective channel gain information is only available at the transmitter. Unlike the prior work in [26], both the downlink and uplink MSs were opportunistically selected in the proposed method, which leads to an improved user scaling law (i.e., the reduced number of MSs). It was analyzed that the proposed method asymptotically achieves the DoF of \(2M\) provided that the number of MSs, \(N\), scales faster than \(\text{SNR}^{M}\). That is, it was shown that the full DoF is guaranteed under the improved user scaling law without any extra CSIT compared to the state-of-the-art scheduling method in [26] that requires the user scaling condition of \(N=\omega(\text{SNR}^{2M-1})\). Numerical evaluation was also shown to verify that our method outperforms the conventional one under realistic network conditions (e.g., finite \(N\) and SNR) with respect to achievable sum-rates.  
Further investigation of the numerical evaluation in a more general setup, which includes different large-scale path-loss components for each link by considering the spatial location of MSs, remains for future work. Suggestions for further research in this area also include examining the effects of MS mobility on the performance via extensive computer simulations.  
Figure 4: The achievable sum-rates versus SNR when \(M=2\) and \(\beta\in\{0.2,0.5,0.8,1.2,1.5\}\).  
**Acknowledgments:** This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2017R1D1A1A09000835) and by the Institute for Information & communications Technology Promotion (IITP) grant funded by the Korea government (MSIT) (2014-0-00532, Development of PS-LTE System and Terminal for National Public Safety Service).  
**Author Contributions:** [PERSON] wrote the simulation code and performed experiments; [PERSON] in part designed the system model; [PERSON] in part designed the protocol; and [PERSON] conceived and designed the overall protocol, and derived the main theorem.  
**Conflicts of Interest:** The authors declare no conflict of interest.
_applied sciences_  
_Article_  
**Challenge Test in Catalan \"Mato\" Fresh Cheese to Assess the Antimicrobial Activity of _Ericaria__selagnoides_ Extracts against _Bacillus cereus_**  
[PERSON] \({}^{1}\)\({}^{\copyright}\), [PERSON] \({}^{1,*}\), [PERSON] \({}^{2}\)\({}^{\copyright}\), [PERSON] \({}^{1}\)\({}^{\copyright}\) and [PERSON] \({}^{1}\)  
\({}^{1}\) IRTA, Food Safety and Functionality Program, Finca Camps i Armet s/n, Monells, 17121 Girona, Spain  
\({}^{2}\) Spanish Institute of Oceanography of the Spanish National Research Council (IEO, CSIC), Oceanographic Centre of Santander, Marine Culture Units \"El Bocal\", Seaweeds Centre, Barrio Corbanera s/n, Monte, 39012 Santander, Spain  
\({}^{*}\) Correspondence: [EMAIL_ADDRESS]  
**Abstract:** Growing consumer demand for high-quality products coupled with minimally processed products and a minor use of synthetic food additives have increased the need to search for new sources of natural antimicrobials to ensure product safety. This study aimed to evaluate the antimicrobial activity of extracts from the brown algae _Ericaria__selagnoides_ against _Bacillus cereus_ in typical Catalan fresh cheese (\"mato\") by means of challenge testing. Three concentrations of a crude extract and its corresponding two subfractions (non-polar and mid-polar) obtained after purification showed an antimicrobial dose-dependent effect on _B. cereus_, from inhibition to inactivation. The best results were obtained with higher concentrations of the non-polar subfraction that caused a total inactivation of the inoculated pathogen after 2 or 4 days, followed by the mid-polar that inactivated _B. cereus_ after 2 or 6 days. The results showed an improvement in the antimicrobial effect after purification compared with the effect observed when the crude extract was tested. Moreover, compounds of different chemical natures may be involved in this antimicrobial activity since it remained in both subfractions after purification. The results obtained in this work show the great potential of macroalgae extracts as natural food preservatives against _B. cereus_ in fresh cheese.  
**Keywords:** brown macroalgae; _Ericaria__selagnoides_; antimicrobial activity; foodborne pathogens; _Bacillus cereus_; challenge test; fresh cheese
## 3 Results
### Noise Impact  
Our equipment utilizes cooled detectors, which to some extent mitigate the influence of noise. Nevertheless, it remains imperative to evaluate the robustness of our algorithm against noise. As illustrated in Figure 12, even after the introduction of varying degrees of Gaussian white noise, the algorithm proposed in this paper is still capable of detecting all small targets, demonstrating its robustness in noisy environments.
## 3 System Identification for Position Model  
Using input-output data from an open-loop configuration, the MATLAB system identification toolbox was employed to generate the mathematical formula of the FBBA system. The experimental setup established communication between MATLAB and the actual plant by utilising an Arduino Uno as a data acquisition device. Setting up an experiment, collecting data, selecting a model set, constructing model estimation, validating the model, and selecting the mathematical model with the highest best-fit percentage are all steps in the SI procedure. The models were evaluated in a simulated plant and then in a real plant to demonstrate the validity of the mathematical formula generated through the SI approach. The input data were the voltage supplied to the electro-pneumatic valve, and the resulting data were the bending angle of the FBBA system that indicates position.
# A Design of a Lightweight In-Vehicle Edge Gateway for the Self-Diagnosis of an Autonomous Vehicle
## 5 Conclusions  
This paper proposes the LI-VEG for smooth communication between in-vehicle protocols and presents results from three experiments. The results are as follows. The LI-VEG reduces the transmission delay time by an average of 10.83% and the error rate by 0.8% for message translation and transmission, compared to the existing in-vehicle gateways. When network traffic becomes lower, the LI-VEG reduces the transmission delay by about 16.3%. Therefore, the LI-VEG has a lower error rate and a lower transmission delay than the existing method when a message is translated and transferred.  
According to the experiment, the LI-VEG has the following characteristics. First, the header is much lighter because only the necessary information for transformation is extracted from the header information of a message. Second, because the Input Queue and Output Queue managing messages are classified into a Priority Multi-Queue and an Event Queue, the LI-VEG translates emergent messages more rapidly than the existing FIFO. Third, the LI-VEG supports communication among all primary protocols used inside a current vehicle.  
The LI-VEG must be tested on real vehicles. If the real experiment on the vehicle is almost the same as the simulation result, the LI-VEG could be applied to the gateway of future autonomous vehicles.  
[PERSON] proposed the idea. [PERSON], [PERSON] and [PERSON] made the paper based on the idea and carried out the experiments in Korean Language. [PERSON] guided and supervised the research and translated the paper into English. All authors read and approved the final manuscript.  
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. NRF-2018R1A2B6007710).  
The authors declare no conflict of interest.
## 3 Results
### Treatments Altered Dentin Surface and hDPSCs Response  
Dentin surfaces appeared different between treatment groups (Figure 3). Intertubular dentin appeared sleek and dentinal tubule orifices were intact on NTAPP-treated dentin (Group I and II). Smear layers were absent on EDTA-treated dentin (Groups I and III). Irregular scaly surfaces and eroded tubule orifices appeared on dentin treated with NaOCI alone (Group IV).  
Figure 3: hDPSCs attachment and spreading on dentin slices observed through scanning electron microscopy (left, \(\times\)500; right, \(\times\)2000). (**A**) Group I (NaOCI + EDTA + NTAPP): Numerous hDPSCs had attached and spread out onto dentin surfaces in multiple layers, entangled by long cytoplasmic processes. (**B**) Group II (NaOCI + NTAPP): hDPSCs had formed multilayer structures on dentin. (**C**) Group III (NaOCI + EDTA): Few hDPSCs had spread out onto dentin without multilayers. (**D**) Group IV (control, NaOCI only): Few isolated hDPSCs had attached to dentin.  
hDPSCs attached and spread out on all dentin surfaces (Figure 3), with differences in densities between treatments that reflected differences in viability (Figure 2). There was more attachment, spreading, longer cytoplasmic processes and higher densities from multiple layers that had merged to form clusters on NTAPP-treated dentin. Instead, markedly fewer isolated cells, much less spreading and shorter processes were seen on dentin controls (NaOCl-only).
# Link-State Aware Hybrid Routing in the Terrestrial-Satellite Integrated Network +
## 5 Simulation and Analysis  
In order to evaluate the routing performance of the proposed algorithm, a Hongyun constellation is created in the Satellite Tool Kit (STK) [41], which can provide realistic 2D and 3D visual dynamic scenes of the constellation orbit. The performance of the space-time Topology-based Satellite Routing (TSR) algorithm and Terrestrial-Satellite integrated network Hybrid Routing (TSHR) algorithm are respectively carried out in the QualNet simulator by using real-world satellite parameters supplied from STK. Meanwhile, packet delay, throughput and packet drop rate are adopted as the performance metrics. In the experiments, the proposed TSR algorithm is compared with the Dijkstra Shortest-Path (DSP) [23], Traffic-Light-based Routing (TLR) [25], Netgrid-based Shortest path Routing (NSR) [21] and Selective Split Load Balancing routing Strategy (SSLB) [26]. Specifically, DSP adopts the gathered global propagation delay to find the optimal routing path, TLR is a load balancing routing scheme, which considers local route adjustment, NSR utilizes static cubes to find the shortest distance path, and SSLB is a distributed strategy, which diverts the traffic flow of congestion nodes to neighboring nodes. The proposed TSHR method is compared with the improved Open Shortest Path First+ (OSPF+) algorithm [17], Traffic-Aware Contact plan (TACR) algorithm [36], and Hyperbolic Geometry-based Routing (HGR) algorithm [34]. Specifically, OSPF+ takes advantage of the regularity of the constellation and conducts periodic route calculations to find the shortest distance path, TACR integrates traffic information into a mixed integer linear programming to find the optimal link connection planning, and HGR utilizes greedy forwarding strategy and hyperbolic geometry coordinate mapping to achieve optimal path selection. We repeat the same simulation 10 times with different generated packets for each point in routing performance comparisons, and we plot the average value with 95% confidence interval in all figures.
# Reverse Coarsening and the Control of Particle Size Distribution through Surfactant
## 2 Results and Discussion
### Isolated Particle in a Binary Solution
More interestingly, if \(\Gamma<0\) the molecular chemical potential is lower for smaller particles, and energy minimization requires the A-molecules to be transferred from bigger to smaller particles. This process of reverse coarsening (\"size focusing\") results in a  
Figure 1: Effective surface energy \(\Gamma\) (red) and concentration \(n_{S}\) of surfactant molecules (B) on particle surface (blue) as functions of A–B bonding \(\varepsilon_{AB}\) for two values of the bulk concentration of surfactant \(n_{S}\ =\ 0.002\) (solid) and \(n_{S}\ =\ 0.01\) (dotted) plotted according to Equation (2) for \(\gamma\ =\ 0.01\) eV and \(T\ =\ 0.032\) eV. mono-disperse (for thermodynamic limit, see [51]) particle ensemble with the equilibrium particle radius \(R_{eq}\) determined by the initial PSD function f(R), and the particles' total volume as  
\[R_{eq}=\left[\int\limits_{0}^{\infty}R^{3}f(R)dR/\int\limits_{0}^{\infty}f(R)dR \right]^{1/3} \tag{3}\]  
For instance, if the initial PSD is a Gaussian \(f(R)=\frac{1}{\sqrt{2\pi\cdot\sigma}}\exp\Bigl{(}-\frac{1}{2\sigma}(R-\langle R \rangle)^{2}\Bigr{)}\) with a mean radius \(\langle R\rangle\) significantly higher than the variance \(\sigma\), then the value of \(R_{eq}\) is very close (within a few percents) to \(\langle R\rangle\) and does not depend on \(\varepsilon_{AB}\).