esa-sceva/satcom-chunk-collection huggingface dataset:
# Dynamics of Polar Resonances and Their Effects on Kozai-Lidov Mechanism
## 4 Dynamics of Interior Polar Resonance, the \(2/1\) Case  
### Results of Numerical Experiments  
We first investigate the dynamics of the interior polar resonance, taking the case of the most critical \(2/1\) resonance. Figure 1 shows the results of the numerical experiments. The initial elements of the 5000 generated particles are plotted on a \(e-\omega\) plane. The different colors represent the lifetime of the particles in the numerical experiments, and the value is the ratio of the particle's lifetime to the whole integration time span. It should be noted that the initial orbital elements of the 5000 particles are generated randomly with \(a=a_{0}\), \(i=90^{\circ}\). Almost all of the highly eccentric particles die from the integration, while most small eccentric bodies survive. Figure 2 illustrates the dynamical evolution of two representatives particles, plane a and b depict the surviving and dead cases, respectively. We can conclude some rules from the numerical experiments, which can provide essential guidance for the semi-analytical work. Firstly, the oscillations of critical (resonant) angle \(\sigma\) illustrate the regular resonant motions. Most of the 5000 particles are trapped in \(2/1\) resonance with the planet because of the initial elements' selection. Secondly, we can neglect the weak librations of the semi-major axis and inclination over the integrations. Therefore, we can set the semi-major axis \(a=a_{0}\) and inclination \(i=90^{\circ}\) in analyzing the secular dynamics inside polar resonance to make the computations easier [64]. Thirdly, the difference in the lifetime of particles mainly comes from the variation in eccentricities. Generally, the eccentricities of survivors are relatively small and oscillate within a specific range, while the others die because their eccentricities increase to close to 1. As we have explained in Section 2, the selection of ascending node \(\Omega\) can be ignored considering the geometric symmetry of the CRTBP. Numerical experiments can also verify this assumption. We change the initial values of \(\Omega\) while keeping the other parameters unchanged and repeat the numerical experiments to obtain consistent patterns.
# Planning of Optical Connections in 5G Packet-Optical xHaul Access Network
## 4 Optimization Problem  
The packet-optical xHaul access network planning problem addressed in this paper consists of finding a set of transmission paths between a given set of remote sites and a hub site. A transmission path is realized either as a direct fiber connection between the end sites or a fiber connection going through OADM devices installed at some remote sites (as shown in Figures 1 and 2). Each transmission path carries a number of wavelengths. An OADM allows for joining into an existing transmission path the wavelengths originated at the remote node at which this device is installed (see \(\lambda_{3}\) and \(\lambda_{4}\) in remote site 2 in Figure 1). The connections are constrained by: (a) the allowable number of OADMs traversed by a transmission path, which is limited by the optical power budget of the path (as discussed in Section 3.1), and (b) the maximum number of carried wavelengths that must not exceed the capacity of given WDM system. The use of OADMs allows for decreasing the demand for fiber connections in the network. In this work, we aim at optimizing the configurations of transmission paths, namely their routes and placement of OADMs, to minimize the number of fiber connections required in the network.  
We begin by introducing the notions and notation used in problem modeling. Afterwards, we formulate the connection planning problem as an ILP optimization problem.
## 2 Materials and Methods
### Statistical Analysis  
The results obtained were compared by condition (with PD vs. CL) according to age range. We compared the mean global wavelet curves, the brainwave power profiles, and the anteroposterior power gradients from power anomalies profiles. The morphology of the mean global wavelet curves was contrasted with Pearson's correlation coefficients using a significance level of 95%, and the most representative brainwaves of each group were compared for frequency and power. The Pearson's correlation coefficients gave values regarding the similarity of the curves, indicating if the brain activity of the five brainwaves oscillated in a similar or different way between the groups. To assess the brainwave power profiles, ANOVA analyses were performed on the mean power values of each brainwave, using a significance level of 95%. ANOVA revealed if there were statistically significant differences between the values of the compared groups. The anteroposterior gradients were evaluated according to their y-intercept and slope values. The differences in slope gave information about the rate of change of power between anterior and posterior brain regions of each group, where a larger slope means a larger rate of change. The y-intercept values gave information about the power dispersion range in standard deviations (SD) corresponding to the brain activity from all the EEG channels for each group.  
Statistical analyses were also performed between our results and our previous analysis from women with PD and age-matched controls acquired with the same method [23].  
It is important to mention that due to the data dispersion, we also obtained median curves for the global wavelet curve profiles (curves not shown) and compared their characteristics with the mean curves. According to ANOVA analysis, there were no statistically significant differences between the mean and median curves: CL \(<\) 60 group (F = 0.01, prob \(>\) F = 0.9396), PD \(<\) 60 group (F = 0.06, prob \(>\) F = 0.8095), CL \(>\) 60 group (F = 0.03, prob \(>\) F = 0.8619) and PD \(>\) 60 group (F = 0, prob \(>\) 0.9476). Pearson's correlation coefficients also were used to compare the curves. For all cases, coefficients were greater than 0.99: CL \(<\) 60 = 0.998; CL \(>\) 60 = 0.998; PD \(<\) 60 = 0.996; PD \(>\) 60 = 0.999, using a significance level of 95%.  
The brainwave power profiles were also additionally assessed with a Kruskal-Wallis test due to data dispersion. The test results showed two cases with differences with respect to the ANOVA analysis based on mean values. In the comparison between men and women CL \(<\) 60 groups, ANOVA showed in the \(\delta\) brainwave significant differences, while the Kruskal-Wallis test showed no differences (Chi-sq = 2.47, prob \(>\) Chi-sq = 0.1159). In the comparison between male and female PD groups, ANOVA showed significant differences in the \(\theta\) brainwave results, while the Kruskal-Wallis test showed no differences (Chi-sq = 2.02, prob \(>\) Chi-sq = 0.1552).  
All the statistical analyses were performed with the MATLAB software (version 9.7.0.1471314, R2019b; RRID:SCR_001622).
## 3 Results and Discussion
### Prediction of Dimethyl-8-Hydroanphtalen and 2-Methylisobornel Using NIRS Technology  
To harness the potential of the NIRS technique in analyzing compounds after clean water purification, a Partial Least Squares (PLS) algorithm was employed to develop quantification models to predict the content of the main off-flavor compounds. PLS models were built between the concentration of dimethyl-8-hydronaphtalen and 2-methylisobornel and analyzed using the reference method and the data obtained using NIRS technology. The outcomes are shown in Figure 5.  
A calibration set was used to select the optimum number of components and build the PLS model. Two different PLS models were built, one for each VOC. Eight components were required to obtain the model for GEO and MIB, explaining 94% and 96% of the total variance, respectively.  
A strong linear correlation can be seen between the concentration of VOCs obtained by the reference method and the data obtained with the near-infrared equipment. The \(R_{CV}^{2}\) values for the two models were 0.94 and 0.96, respectively, with RMSECV values of 1.00 and 3.62 ug/g. Furthermore, the model was validated with tench samples subjected to different water purification methods. The validation results show strong model performance, with an \(R_{p}^{2}\) value of 0.98 for dimethyl-8-hydronaphtalen and 0.97 for 2-methylisobornel. The RMSEP values were 0.54 and 2.24 ug/g, respectively. These values confirm that NIR spectroscopy combined with PLS can accurately predict GEO and MIB in this species of fish.  
Figure 4: Principal component analysis of fish samples after application of different clean water deprivation processes at 0 h, 12 h, 24 h, 48 h, 72 h, and 96 h.  
It can determine the optimal point at which tench present the minimum levels of off-flavor aroma so that they may be marketed with the highest quality. To the best of our knowledge, no such specific studies have verified the off-flavor compounds of fish with NIRS equipment. However, our study aligns with previous studies in which a Partial Least Squares regression with NIRS data and other chemical parameters were used to evaluate food quality and safety. [PERSON] et al. [38], for instance, demonstrated NIRS to be a rapid method to predict the chemical properties of fish muscle. NIRS also successfully predicted the freshness of fish at the initial stage of decomposition [35]. NIRS combined with a PLS algorithm were used to assess fish spoilage during a period of 12 days in low-temperature storage [39]. [PERSON] et al. [40] proposed a multivariate analysis using NIRS for the characterization of sardine, silverside, and anchovy to quantify freshness.  
Given our findings and the results obtained by other researchers, it would be beneficial to incorporate a processing line with NIRS equipment that allows aquaculture industry professionals to predict the content of off-flavor aromatic compounds in fish. This would enable them to assess the need for a purification system prior to slaughter.
## 3 Results and Discussion
### Antioxidant Activity of the Films  
Incorporation of all extracts rich in lipids and bioactives into the films resulted in an increased antioxidant activity, with statistically significant differences observed in both ABTS and DPPH assays (Table 8). Film B exhibited higher ABTS and DPPH values than the control film (film A). These findings align with previous reports on alginate films enriched with protein-rich (P-rich) and bioactive-rich extracts from _Limnospira_ sp. [63], indicating that the enhanced antioxidant activity is largely due to the presence of bioactive-rich extracts.  
The DPPH value for film B was similar to that reported by [PERSON] et al. [34] for a 2% alginate film containing 0.5% P-rich and 0.25% bioactive-rich extracts from _Lobosphaera_ sp., which exhibited 212.81 \(\pm\) 39.12 uM TE/mg film. [PERSON] et al. [64] also demonstrated that the incorporation of _Arthospira platensis_ into a bioccomposite film made with Zedo gum and sodium caseinate significantly improved antioxidant activity.  
[PERSON] et al. [65] reported that zein fibers containing phycocyanin and a 70% hydroethanolic spirulina extract showed DPPH antioxidant activities of 42.86 \(\pm\) 0.13% and 47.98 \(\pm\) 0.64%, respectively. The strong antioxidant properties of spirulina extracts are attributed to their high total phenolic and flavonoid contents, alongside contributions from \(\beta\)-carotene and chlorophyll, known antioxidant agents.  
\begin{table}
\begin{tabular}{c c c c c} \hline
**Film** & **L*** & **_a*_ & **_b*_ & **Hue (*)** & **Chroma** \\ \hline A & 49.98 \(\pm\) 5.55 a & \(-\)0.22 \(\pm\) 0.11 b & 15.60 \(\pm\) 0.96 b & \(-\)89.18 \(\pm\) 0.36 b & 15.61 \(\pm\) 0.96 b \\ B & 30.49 \(\pm\) 2.26 b & 4.70 \(\pm\) 0.32 a & 23.94 \(\pm\) 1.12 a & 78.89 \(\pm\) 0.63 a & 24.40 \(\pm\) 1.14 a \\ \hline \end{tabular} Different letters mean significant differences (_p_ < 0.05). Three replicates.  
\end{table}
Table 7: Color parameters of the films.  
Figure 5: Film (**A**): alginate (3%) + zein (1%); film (**B**): alginate (3%) + zein (1%) + lipid-rich extract from _Namochloropsis_ sp. (0.25%) + bioactive-rich extracts from _Namochloropsis_ sp. (0.125%) and _Limnospira_ sp. (0.125%).  
\begin{table}
\begin{tabular}{c c c} \hline
**Film** & **ABTS** & **DPPH** \\  & & **(uM TE/mg Film)** \\ \hline A & 128.81 \(\pm\) 10.40 b & 104.98 \(\pm\) 14.31 b \\ B & 316.80 \(\pm\) 32.29 a & 240.53 \(\pm\) 14.75 a \\ \hline \end{tabular} Different letters mean significant differences (_p_ < 0.05). Four replicates.  
\end{table}
Table 8: Antioxidant activity of the films.
# Stateflow-Based Energy Management Strategy for Hybrid Energy System to Mitigate Load Shedding
## 3 Modeling of HES Components
### Generator  
A split (two-tier) diesel generator system, as shown in Figure 7, is proposed; this is against the commonly used single generator [36; 37]. The reason is to allow the commitment of generators to match the load demand at a specific instant, thus minimizing the fuel consumption and net CO\({}_{2}\) emission. Furthermore, this structure increases the reliability and the redundancy of the system. The first generator, Gen1, is smaller in size (10 kW) as compared to the second generator, Gen2 (20 kW). Gen1 will be turned on when the required load demand is low. Accordingly, Gen2 will be started when the demand exceeds the capacity of Gen1. In the case of peak demand, both generators will operate simultaneously. For this research, the selection of an appropriate generator is performed by calling the truth table function in the SF. It should be noted that the generators are only turned on when there is a need to cover the energy deficit during load shedding intervals. This condition applies when the PV and ESU are not able to meet the load demand. In general, the power output of a generator can be expressed according to the rated power (\(P_{rated}\)) and its efficiency (\(\eta_{Gm}\)).  
\[P\_Gen=P_{rated}\times\eta_{Gm} \tag{7}\]  
Accordingly, the fuel consumption of the generator can be calculated using the following formula.  
\[Fuel_{Gen}(t)=C_{1}\times P_{rated}+C_{2}\times\ P_{Gen}(t) \tag{8}\]  
Here, \(C_{1}\) and \(C_{2}\) refer to the coefficients of the fuel consumption curve. Their values are 0.246 and 0.08145, respectively [38]. While \(P_{rated}\) and \(P\_Gen\) represent the rated power and the generated power of the generator (in kW), respectively. Since this research considers two generators, the total power supplied by the generator system at time (\(t\)) is the sum of the individual generator contribution. It can be expressed as  
\[P\_Gen\ (t)=\alpha_{Gm1}\times P_{-}Gen1\ (t)+\alpha_{Gm2}\times P_{-}Gen2\ (t) \tag{9}\]  
\(P\_Gen1\) and \(P\_Gen2\) represent the power supplied by the Gen1 and Gen2, respectively. The values for power (\(P\_Gen1\), \(P\_Gen2\)) and fuel consumption (\(Fuel_{Gm1}\), \(Fuel_{Gm2}\)) of corresponding generators can be found through Equations (7) and (8), while \(\alpha\) is a binary variable that describes the state of the considered generator at a specific hour. In case the Gen1 is working and Gen2 is not working at any hour, the corresponding values will be \(\alpha_{Gen1}\ =1\) and \(\alpha_{Gen2}=0\), respectively. This research considers suitable diesel generators from [39] to supply standby power in the proposed HES. Some technical parameters of the main components of HES are presented in Table 2.
## 3 Materials and Methods
### Crystallization, Data Collection and Processing  
To analyze the effect of uridyylated and fluororudylylated VPgs (UMP-VPg1 and FUMP-VPg1, respectively) on the polymerase activity, 3 DPpol was incubated overnight in presence of equimolar proportions of a UMP-VPg1 and FUMP-VPg1. Crystals were obtained by the hanging-drop vapor-diffusion method at 20 \({}^{\circ}\)C in a 24 well Greiner plate, crystallization drops contained 1 \(\mu\)L of protein solution and 1 \(\mu\)L of crystallization buffer (0.2 M ammonium acetate, 30% PEG 4 K, 0.1 M MES pH 6.0 and 4% \(\gamma\)-butyrolactone) and were equilibrated against 1 mL of crystallization buffer. Crystals appeared in 2 or 3 days. Prior to data collection, crystals were transferred to a cryo-protecting solution in a reservoir solution and 20% (_v_/_v_) glycerol, and flash-frozen in liquid nitrogen.  
Crystals that contain FUMP-VPg1 were collected at 100 K at the ESRF beamline ID29 (Grenoble, France). Diffraction images were processed with XDS [40] and internally scaled with SCALA [41]. Best crystals, belonging to the tetragonal space group P4\({}_{1}\)2\({}_{1}\)2\({}_{1}\) diffracted to 2.3 A resolution (Table 1). The structure of this complex was determined by following a rigid body refinement procedure with Refmac5 [42], using the structure of the unbound FMDV 3 DPpol (PDB id.1U09) as an initial model. This model was manually rebuilt, using Coot [43] and positionally refined with Refmac5 [42] and Phenix [44]. The statistics of the refinement are summarized in Table 1. The refined coordinates and structure factors are available at the PDB under accession code 6S2L.
# Smooth 3D Dubins Curves Based Mobile Data Gathering in Sparse Underwater Sensor Networks
## 1 Introduction
It is noted that the efficiency and smoothness of the planned paths for mobile data collection can be improved [14]. Previous research on MDG using AUVs has focused primarily on a reduction in the length of the AUVs' traveling paths. However, as a result of well-known kinematic constraints, the data collecting trajectory of AUVs should be of geometric continuity and smoothness [16]. The Dubins based traveling salesman problem (DTSP) [17] is designed to generate the minimum total length while visiting a set of sensor nodes with Dubins curves, but it can only be used in 2D planes. [PERSON] et al. [18] propose a linear interpolation method to convert 2D Dubins curves to 3D Dubins curves for underwater glider path planning. However, linear interpolation in the \(Z\)-axis fails to satisfy the 3D smoothness constraint. [PERSON] et al. propose a smooth path generation method for automated vehicles on the basis of the Bezier curve [19], but it is only applicable to 2D planes. Although these algorithms can provide optimal or near-optimal paths that pass through all predefined waypoints, they cannot guarantee smoothness in 3D regions. To deal with these problems, given a mobile AUV and a set of underwater sensors, this paper proposes continuous and smooth 3D Dubins curves with Bezier interpolation in the \(Z\)-axis for MDG of USNs. _Statement of Contributions_: (1) This paper extends the traditional 2D Dubins curve to a 3D Dubins curve with continuous Bezier interpolation instead of the linear interpolation method; (2) this paper also designs the interpolation of smooth 3D Bezier curves in the \(Z\)-axis and proves its smoothness. Although the curvature-continuous-path planning algorithm has been used in unmanned aerial vehicles (UAVs) [20], it has not yet been well studied for USNs. Moreover, the Catmull-Rom curve construction method to satisfy the curvature continuity condition in [20] is overladen for USNs. To the best of our knowledge, this is the first report to design smooth 3D curves for MDG of USNs. Extensive results verify that the proposed method can achieve trajectory smoothness with little extra cost. The rest of this paper is organized as follows. Section 2 presents the problem statement and network model. In Section 3, smooth 3D Dubins curves with the Bezier interpolation based MDGalgorithm are presented. Simulation results are shown in Section 4, followed by the conclusions in Section 5.
# Cold-Adapted Fungi: Goldmine of Biomolecules Applicable in Industry
## 2 Diversity and Ecological Role of Cold-Adapted Fungi
The most widespread genera reported from different Antarctic habitats are _Antarctomyces, Pseudogymoascus_ (formerly _Geomyces_), _Mortierella_, and _Cryptococcus_[15]. _Antarctomyces_, originally reported from different Antarctic soils, is represented by only two endemic Antarctic species: _A. psychrotrophicus_[22] and _A. pellizariae_[23]. _Pseudogymoascus_ displays a broad geographic distribution in cold environments around the world and includes various species. It is prevalent in soils [24; 25; 26], and associated with plants [27], marine macroalgae [28; 29], lichens [30], sponges [31], and in freshwater lakes [32; 33]. The genus _Mortierella_ includes approximately 85 species, which have been isolated using traditional culture methods and detected using metabarcoding from rocks [19], marine sediments [34], mosses [35], snow [36], and lake sediments [37; 38]. _Cryptococcus_, representing the phylum Filobasidiella (Basidiomycota), displays a wide distribution in Antarctica [39; 40; 41], including soils [40], sediment, freshwater, the rhizosphere of _Deschampsia antarctica_, penguin guano [42], thalli of lichens [30], and macroalgae [28]. For decades, the biodiversity of Antarctica and other cold environments was studied using traditional microbiological techniques [2; 43]. It is estimated that only a small percentage (\(\sim\)0.1%) of microorganisms can be cultured under laboratory conditions, particularly those from extreme environments. Therefore, the development of next-generation sequencing (NGS) technologies has enabled precise, rapid, and cost-effective sequencing of psychrophile genomes and transcriptomes, as well as the metagenomes of their habitats [44; 45]. Metagenomic approaches allow for the identification of microorganisms without the need for cultivation. This has led to a better understanding of the microflora of deep ocean trenches [14], ice-volcanic caves [46], cryptoendolithic niches [47], and microbial mats from the Arctic and Antarctica [48]. This finding is confirmed by the results of the studies conducted by [PERSON] et al. (2023). The researchers employed the metabarcoding approach, which enabled the detection of a diverse and intricate mycboimge comprising a range of fungal taxa with varying ecological roles [15]. These included saptrophic, human- and animal-associated, phytopathogenic, mutualistic, and cosmopolitan fungi. This confirms the necessity of developing improved culture-independent methods for the enhanced detection of cold-adapted fungi, particularly through the development of more effective molecular markers for investigating true fungal diversity. It is imperative to conduct comprehensive research into the origin and evolution of species that cause ecological crises or have economic significance. An understanding of the ecological functions and adaptation mechanisms of specific species will provide a comprehensive insight into the diversity of cold-adapted fungi.
## 5 Results and Discussion
### Satellite Spectral Analysis  
The use of spectral-enhancement indices (IPVI and WV-II) coupled with edge-detection spatial filtering resulted in the identification of numerous potential archaeological features that had yet to be recorded by any expedition in the eastern sector.
## 3 The Critical Importance of Product Identity in Agricultural Supply Chains
### Systemic Deficiencies in Current Traceability Systems
#### 3.1.2 Digital-Physical Interface Challenges  
As for challenges regarding digital-physical interfaces, the main ones should be the implementation of digital twins, the physical-digital connection, and the complexities inherent to verification:  
* Implementation of digital twins: The sources indicate that creating a \"digital twin\" of a product is essential for effective traceability. This means that a digital representation must be accurately linked to the physical product. Without this, efforts to maintain and verify a product's identity are severely hampered [25].
* Linking physical and digital: A key challenge is to create a secure link between the physical product and its digital representation. This linkage is critical to establish a clear and verifiable identity for the product in the digital space [26].  
* Verification issues: The difficulty in verifying that digital data truly reflect the physical product and its journey through the supply chain creates uncertainty and devalues the usefulness of product identity [27].