esa-sceva/satcom-chunk-collection huggingface dataset:
# Application of Extracellular Polymeric Substances during Cultivation of Microalgae Biomass
###### Abstract  
Extracellular polymeric substances (EPS) produced by microorganisms contain polymers that are used for the biofloculation of microalgae; however, these polymers are also organic compounds that might be used as carbon sources. The study analyzed two strategies for the introduction of EPS for _Tetraselmis subcardiormis_, _Chorella_ sp., and _Arthrospira platensis_ biomass harvesting. In the first variant, EPS in the dose of 100 mg TOC/g were added to the photobioreactor every other day from the beginning of the cultivation, while in the second variant, EPS in the two doses of 100 mg TOC/g and 300 mg TOC/g were only added at the end of cultivation. In the first variant, the results proved that microalgae/cyanobacteria can use the EPS as external carbon sources. The cultures were characterized by a faster increase in biomass concentration, which contained less chlorophyll. However, the EPS content did not change. In the second variant, the addition of EPS did not affect the EPS content and the sedimentation of the _Chorella_ sp. biomass. The biomass of _T. subcardiormis_ was characterized by a much better sedimentation coefficient. The greatest differences were observed in the _A. platensis_ culture: the biomass concentration increased from 1.2 \(\pm\) 0.2 g/L to 1.9 \(\pm\) 0.2 g/L, EPS content increased by 16%, and sedimentation efficiency increased to 72%.  
biomass harvesting; EPS; biofoculation; mixotrophic growth Article
# Spaceborne GNSS-R for Sea Ice Classification Using Machine Learning Classifiers
## 3 Theory and Methods
### Sea Ice Classification Method  
Many previous studies indicate that RF and SVM show great potential in classifications [33; 38; 39; 42], while they have not been used for classifying FYI and MYI using GNSS-R features. Thus, these two classifiers are used in this study to classify sea ice types.
# Investigation on the Mass Flow Rate of a Refrigerator Compressor Based on the p-V Diagram
## 4 Results and Discussion
### Effect of Suction Pressure on the Compressor Performance  
Volume efficiency and flow loss are two important performance indexes of compressors. Based on the experimental p-V diagram and the mass flow rate calculation method proposed in this paper, the effect of suction pressure on the volume efficiency and the suction flow loss are investigated.  
The volumetric efficiency of the refrigerator compressor is calculated as follows:  
\[\eta_{v}=\frac{\dot{m}}{\rho_{Inlet}V_{thno}} \tag{3}\]  
where \(\dot{m}\) is the actual mass flow rate of the compressor, \(V_{thno}\) is cylinder volume of the refrigerator compressor without clearance volume, and \(\rho_{Inlet}\) is the refrigerant density at the suction conditions.
# A Novel Device-Free Counting Method Based on Channel Status Information
## 4 Experiment Results and Analysis
### Impact of Dilatation Coefficient  
The dilatation coefficient is a scaling factor, which used to expand the percentage. We random choose integer 0-20 as scale factor, and this factor is not affected by the environmental change. Figure 10 shows the impact of dilatation coefficient. It can be seen that the percentage increases with the growth of dilatation coefficient, when the matrix resolution \(R\) is constant. Among them, the percentage reveals the relationship between the number of people and CSI variations. Although there is great difference in the percentage when the number of people is different, it would not induce detection errors. Figure 10a,b shows the variation on the percentage of amplitude and phase (under different dilatation coefficient \(D\)), respectively.  
When \(D=0\), the percentage remains constant with the increase in the number of people, since each column has only one non-zero element before dilatation. When \(D=20\), the percentage not only keeps constant, but tends to 100%. As such, the dilatation coefficient \(D=20\) is the maximum scale factor in this paper. Thus, if \(D\) is excessively either high or low, then it will affect the detection results. However, when \(D\) is equal to 5, 10 and 15, although there exists a monotone increase between percentage and number of people, the curve track is different. Therefore, the different dilation coefficients will bring different experimental results. Many experimental results show that \(D=10\) is optimal value selection. Therefore, in our work, \(D=10\) is set as the dilation coefficient.  
Figure 10: The impact on dilatation coefficient. (**a**) amplitude; (**b**) phase.  
Figure 9: Comparison of amplitude and phase. (**a**) Comparison of mean in eigenvalue; (**b**) the relationship between percentage and the number of people.
## 6 Discussion
### Interpreting Answers to RQs and PQs
#### 6.1.2 Interpreting Answers to PQs  
Interpreting Answers for PQ1  
According to the gathered evidence to answer PQ1, we can note that from 2010 to 2018, there was a continuous growth in the number of published papers. Then, between the years 2019 to 2020, the number of articles did not exceed five per year, obtaining a notorious decrease in the year 2020, recovered in the year 2021 with seven papers. A possible interpretation could be that management of DSPLs is still booming, and the pause in the publication for 2019 and 2020 may be due to external causes, such as the pandemic generated by COVID-19. Another cause could be that the research led to more specific subtopics that we have not captured in this paper due to the limitation of the application area towards self-adaptive systems. Whether these ideas are confirmed or not, much more extensive bibliometric research is required.  
\begin{table}
\begin{tabular}{l l l} \hline \hline
**Criteria** & **FM-Based Approaches** & **MAPE-K Control Loop** \\ \hline Allows describing possible system states & ✓ & \\ Allows to change the variability of a system & ✓ & ✓ \\ at runtime & & ✓ \\ Allows to store the record of changes in & & ✓ \\ variability & & \\ \hline \hline \end{tabular}
\end{table}
Table 13: Comparison between feature model-based approaches and the MAPE-K control loop.  
Interpreting Answers for PQ2  
Based on the evidence collected to answer PQ2, we can remark that more than 65% of the papers were published at conferences. The SPLC (twelve papers), SEAMS (five papers), VaMoS (four papers), and SBES (four papers) seem to be the most relevant conferences for variability management in DSPL. The rest of the conferences only registered two or one paper each. On the other hand, approximately 30% of the papers were published in a journal. The most important journals seem to be _Journal of Systems and Software_ (five papers), _ACM SIGPLAN Notices_ and _Science of Computer Programming_ (three papers each), _IEEE Software_ and _Journal of Software: Evolution and Process_ (two papers each). The remains of the journals register only one paper each. Finally, the most relevant publishers were ACM, IEEE, and Science Direct. In the classification of the conferences according to the Conference ranks web site [[http://www.conferenceranks.com/](http://www.conferenceranks.com/)]([http://www.conferenceranks.com/](http://www.conferenceranks.com/)), under the Qualis ranking (accessed May 2022). Sixteen conferences or workshops are not classified because several workshops are inactive and therefore are not indexed under the CORE or Qualis ranking. For details, see Figure 16.
# A Systematic Survey on 5G and 6G Security Considerations, Challenges, Trends, and Research Areas
## 2 Related Works
### Zero Trust Importance  
ZTA focuses on a shift in security perspective from perimeter defense to defending each transaction within a network [13]. It is built around the assumption that the attacker may already have penetrated into the network and established a foothold. In ZTA environments, therefore, each transaction is individually scrutinized to ensure the integrity of every communication attempt and enforce strict policy compliance. This shift in network security is vitally important to 5G networks that inherently operate in an untrusted environment [14]. The added security of a ZTA can be used for a variety of applications, including military applications shown in [14; 15]. Table 1 lists and describes the tenets of ZTA provided by the National Institute of Science and Technology (NIST), including backbone considerations for the deployment of a ZTA system.  
Zero Trust and the development of similar security principles have circulated within the research community ever since the term was coined in 1994 by [PERSON] [16]. Since then, the idea of limiting the trust shown to users of a network or networked resource to zero has gained popularity, especially over the past few years. Figure 3 shows the rapid increase in publications that mention the term 'Zero Trust' per year, giving weight to ZTA and the exploration of its feasibility in real-world deployments across different network and application implementations. This search was conducted using Google Scholar with the search phrase of \"network, security, \"zero trust\" -game -health -mechanical\". The negated words are used to exclude publications that are not within this domain of literature. Topics akin to the excluded keywords initially showed up in the study but were excluded after their relevance was seen to be outside of this search domain. We then looked at the incorporation of both ZTA and 5G/6G in publications and see a similar growth in interest in the past few years. Figure 4 illustrates the increasing amount of publications including ZTA and 5G/6G, providing more weight to the importance of ZTA and the discovery of applications in a 5G or 6G network environment with each category growing in popularity at a rate that is nearly doubling year-over-year. This search was similarly conducted usingFigure 4: Mentions of the term ‘Zero Trust’ in conjunction with either 5G or 6G in network security-oriented research publications, starting from the year 2016.  
Figure 3: Mentions of the term ‘Zero Trust’ in network security oriented research publications starting from the year 1994.
# Specific Resonant Properties of Non-Symmetrical Microwave Antennas
## 1 Introduction  
In the process of modernizing new aircraft avionics systems, it is often necessary to install another antenna on the aircraft's fuselage. Determining an optimal position for the new aircraft antenna is a key problem. At present, the solution to this problem usually starts with a computer simulation. After the introductory suggestion of an optimal position, experimental measurements on an aircraft scale model, with the use of a miniaturized antenna model, are performed. To perform such measurements, the aircraft model as well as the antenna model must be miniaturized. In this way, it is necessary to transform the theory and practice of antennas from a full-size aeronautical frequency band in MHz to a frequency range in the microwave band [1, 2]. The miniaturized antenna model working in a resonance frequency in the GHz range must possess certain parameters (characteristics, VSWR, etc.) identical with the real aircraft antenna working in the MHz range [3].  
This paper deals with interesting resonance characteristics of such antennas, which were discovered serendipitously during measurements on models of small microwave antennas in the GHz range performed as part of the process described above. Analysis of the resonance characteristics of non-symmetrical microwave antennas was performed in frequency ranges from 1 GHz to 4 GHz. The common parameter of the antenna set measured was their transverse dimension, shape, and material [4; 5; 6]. The length of the antennas, which was the variable parameter, ranged from 2 cm to 7 cm. During the analysis, the focus was on the first series quarter-wave resonance of each antenna. When doing summary analysis in the common graph of measured parameters, the microwave antennas revealed resonance characteristics that are not shown by classical cylindrical antennas. As simulation programs for antenna characteristics are based on the theory of mainly classical antennas, the new knowledge presented in this paper provides an important basis for updating such simulation programs. Ultimately this information, derived from small-scale MHz range observations, applies to full-size flat microwave antennas for automobile systems or UAVs in higher frequencies in the GHz range.  
The paper is structured as follows. The first three short sections present the purpose of the experimental measurements during which the specific resonance characteristics of flat microwave antennas were observed. In the introductory subsection of the fifth section of this paper a brief theory of microwave antennas focused on the problem solved in the paper is presented. Next, the second sub-section confirms this well-known theory with the results measured on classical cylindrical antennas. The final, third sub-section reveals the new, unknown resonance characteristics we discovered from the results of the measurement of flat microwave antennas. The presented findings open certain new possibilities to design small microwave antennas for automotive and aviation technology in the higher GHz frequencies [7; 8; 9].
## 2 Materials and Methods
Three independent authors ([PERSON], COP, and [PERSON]) employed the bias assessment tool, Risk of Bias in Non-randomized Studies--of Exposures (ROBINS-E) from Cochrane Collaborations, to evaluate the bias of included papers [16]. The three reviewers further discussed and resolved any disputes they had about the bias assessment. Bias was classified as \"low risk\", \"high risk\", or \"some concerns\" based on the authors' assessments. The Newcastle-Ottawa Scale (NOS) from the Ottawa Hospital Research Institute (OHRI) is a quality assessment tool for cohort and cross-sectional studies, focusing on three areas: participant selection, group comparability, and outcome measurement. We used the NOS to analyze the quality of included studies. The maximum possible score for cross-sectional research is between 0 and 10, then for cohort studies, it is between 0 and 9. The score is seven or above indicates that an article was of \"good\" quality. The NOS guidelinesprovide the specific NOS criteria. Studies with a high risk of bias will be excluded from the systematic review to maintain the integrity of the data in this research [17]. The findings for each miRNA's sensitivity and specificity were shown as ratios with a 95% confidence interval (CI) in the typical table. We transformed the data to be expressed as a Log Odds Ratio to perform pooled analysis. In order to assess the heterogeneity between the studies, the I-squared (I\({}^{2}\)) statistic was used in this review; I\({}^{2}\) values larger than 50% are indicative of significant heterogeneity. A fixed-effect model (FEM) was used to do meta-analysis when the included studies were judged homogenous (little variability in study findings or variation due to random error), as shown by a \(p\geq 0.10\) or an I\({}^{2}\leq 50\%\). If \(p<0.10\) or I\({}^{2}>50\%\), we employed a random-effect model (REM). Otherwise, we did not. In a forest plot, the pooled Log Odds Ratio was displayed. To further evaluate the diagnostic performance of miRNA in the early detection of colorectal cancer, we conducted a Summary Receiver Operating Characteristic (SROC) analysis. The trade-off between true positive and false positive rates across the research can be evaluated using this method. A quantitative indicator of diagnostic accuracy was determined by calculating the area under the SROC curve (AUC), where values nearer 1 denote improved diagnostic performance. [PERSON]'s test and funnel plots were used to check for publication bias. If asymmetry was detected, we planned to explore the study characteristics to identify potential biases or other factors like methodological differences. Significant heterogeneity will be assessed with meta-regression analysis, focusing on variables such as sample size, age, and sex, selected based on their relevance to the study's goals. Potential variables for meta-regression include ethnicity, gender, and sample type. All the analyses were carried out using R Studio [18].
## 2 Methodology: Computation of the Altimetry Performance
### Non-Instrumental Error Sources in GNSS-R Altimetry
#### 2.2.2 Impact of the Ionosphere
In order to mitigate ionospheric effects, a Sun-synchronous orbit has to be selected, preferably a 6 a.m.-6 p.m. one, because it avoids passing through the ionosphere after sun set and midnight local time. If this is not possible, e.g., GEROS experiment on-board the ISS, a potential solution may consist of the calculation of a running average and a running standard deviation of consecutive observables (e.g., 10) and check if the expected standard deviation is consistent with the expected one, either from theory or from previous observations. If it is anomalously larger, this would be a clear indication of ionospheric scintillation (or of the presence of radio frequency interference) and therefore measurements could be flagged in real time.
# Clustering Method of Large-Scale Battlefield Airspace Based on Multi A * in Airspace Grid System
## 4 Airspace Clustering Steps Based on Multi-A \({}^{*}\) Algorithm
### Clustering Data Processing
#### 4.4.1 Airspace Clustering Line Marking  
According to the idea of airspace clustering method, the whole battlefield airspace is divided into multiple airspace clusters through the intersection of multiple airspace clustering lines. It can be considered to find the key nodes where multiple airspace clusters intersect, and then it marks the boundaries of each airspace cluster through the grid coding combination of the edges and intersections of the clustering lines. Computing the intersection of edge lines of airspace clusters mainly involves the method of grid overlap detection. First, the airspace clustering map generated in the previous section is enlarged, at the intersection node of airspace clustering lines (as shown in the Figure 11).  
In the process of grid overlap conflict detection, the grid code data structure in the following Table 4 is used, where \(Code\_ID\) is grid code, \(L_{1}\_Set\) is the object grid coding set in clustering line, and \(L_{1}\_L_{2}\_Set\) is the set of object grid codes in clustering line \(L_{2}\).  
Figure 11: Detection diagram of intersecting nodes of airspace clustering lines.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Airspace Cluster Number** & **Airspace Number** \\ \hline \⃝1 & none \\ ⃝2 & none \\ ⃝3 & 1, 8, 9, 10, 15 \\ ⃝4 & 4, 5, 12, 13 \\ ⃝5 & 2, 3, 11 \\ ⃝6 & 6, 7, 14 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Statistics of airspace clustering.  
First, the encoding data in \(L_{1\_Set}\) and \(L_{2\_Set}\) are imported into \(Code\_ID\), then the grid object in \(Code\_ID\) is listed as the detection object, and if it is occupied by \(L_{1}\) or \(L_{2}\), it is assigned a value of 1. If none of them are occupied, the value is 0. If it is occupied twice, it is assigned a value of 2. Taking the above scenario as an example, as shown in the Figure 12, two cluster lines intersect, and an airspace-overlapping grid is detected.  
Through airspace grid overlap detection, the grid code of intersection nodes of airspace clustering lines is obtained. In the above example, the grid code of intersection nodes of clustering lines \(L_{1}\) and \(L_{2}\) is \"\(D01126\)\". According to this method, the intersection nodes of the airspace clustering lines can be represented by grid coding, and the combination of the intersection nodes of the points on the clustering lines can complete the grid representation of the airspace clustering lines.
## 4 Effect of Viscoelastic Damping on Underwater Acoustic Radiation
### Damping Thickness  
Figures 9 and 10 show the acoustic radiation fields corresponding to damping of 5 mm thick, 10 mm thick and 20 mm thick. The results show that the thickness of the damping layer has little influence on the distribution of sound pressure. However, with the increasing damping layer thickness, the amplitude of the sound pressure level has a marked decline, and the damping effect at a high frequency is better than that at a low frequency. Furthermore, greater thickness is not always better, as a too thick damping layer may increase the mass of the whole structure, which leads to the worse damping effect. Thus, the characteristics of structure vibration and loads should be comprehensively considered in the actual situation.
## 4 Simulation Results
### Solution Results and Comparison
Compared to both the conventional OPF and the VSCOPF, the proposed approach provides higher values for time to live (TTL), TML, and ALC. The use of enhanced LMPs also results in an improved total ISO payment, although the accrued system losses are higher according to the TTL. Meanwhile, the conventional OPF provides the lowest VSM of 364.37 MW after CM has been applied. Despite the fact that the OPF relives congestion, it does not ensure secure operations of the power network. The stability margin could be low, leading to a vulnerable network. When compared to the OPF, the VSCOPF alleviates congestion, ensuring the power system's security in terms of voltage stability. Nevertheless, the stability margin of VSCOPF remains low after congestion relief has taken place. This means that the total ISO payment should increase because of the additional set of system constraints. In addition, neither the conventional OPF nor the VSCOPF considers the probabilistic effects between the congestion and the wind farm's variability, taking only the mean value of the wind farm's output into account. On the other hand, the proposed approach not only provides the system with a larger VSM of 685.43 MW but can also relieve congestion by considering the margin of the system's stability with respect to the uncertainty in the wind farm. The ISO makes selective payments to both participants that can mitigate congestion as well as those that affect the system stability margin significantly. Figure 9: Comparison of optimal pricing for CM. (**a**) LMPs; (**b**) NCPs. To evaluate the ongoing security after CM has been executed, the voltage profiles of the buses for the three methods are shown in Figure 10. The horizontal and vertical axes represent the bus numbers and the voltage magnitudes, respectively. A good voltage profile is one of the indications of a more secure power system. The voltages of P-VSCOPF are the highest among all methods for all of the buses. Thus, P-VSCOPF not only provides a greater stability margin but also leads to a better voltage profile than the other OPF methods do. This means that the system is more robust and can maintain stability even under the most severe circumstances.
# Hybrid Deep Learning Approach for Automated Sleep Cycle Analysis
## 3 Methodology
### Model Training
#### 3.4.4 Parameter Optimization  
Optimization methods such as stochastic gradient descent, root mean square propagation, and adaptive moment estimation improve the efficiency of the model learning process beyond standard GD.  
* Stochastic Gradient Descent (SGD): Updates weights using a random sample per iteration [47], reducing the complexity; efficient in large datasets.
* Root Mean Square Propagation (RMSProp): Modifies the learning rate dynamically by tracking the moving mean value of squared gradients [48], accelerating convergence.
* Adaptive Moment Estimation (ADAM): Integrates momentum and learning rate adaptation [48], using decaying averages of past gradients for faster and stable convergence.  
The optimization choice depends principally on the task, the data, and the hyperparameters.