esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results
### Stepping Characteristics  
No significant interactions were observed between direction and amplitude for step size, total step count and step frequency. A significant main effect was seen for group for total step (F\({}_{(2,40)}\) = 140.06, \(p\) < 0.001, \(\eta_{\mathrm{p}}\)\({}^{2}\) = 0.58) and step size (F\({}_{(2,40)}\) = 21.4, \(p\) < 0.001, \(\eta_{\mathrm{p}}\)\({}^{2}\) = 0.17). The older group showed a significantly greater number of total steps (\(p\) < 0.001), with differences at 90\({}^{\circ}\), 135\({}^{\circ}\) and 180 degrees of 2.78, 3.48 and 4.33 steps, respectively. The older group showed a smaller step size (\({}^{\circ}\)) (\(p\) < 0.001), with differences at 90\({}^{\circ}\), 135\({}^{\circ}\) and 180 degrees of 60.81\({}^{\circ}\), 71.21\({}^{\circ}\), and 80.28\({}^{\circ}\), respectively. In addition, significant main effects were seen for turn amplitude for total step (F\({}_{(2,40)}\) = 148.35, \(p\) < 0.001, \(\eta_{\mathrm{p}}\)\({}^{2}\) = 0.77) and step size (F\({}_{(2,40)}\) = 16.32, \(p\) < 0.001, \(\eta_{\mathrm{p}}\)\({}^{2}\) = 0.27) (Table 1, Table 2 and Figure 4). Post hoc pairwise comparisons showed significant differences in total step and step size for turn amplitude between 90\({}^{\circ}\) and 180\({}^{\circ}\), 135\({}^{\circ}\) and 180\({}^{\circ}\) and 90\({}^{\circ}\) and 135\({}^{\circ}\) (\(p\) < 0.001) with both increasing with increasing turn amplitudes (Figure 4). No significant main effects were seen for group or turn amplitude for step frequency.  
The analysis of step duration with MM ANOVA demonstrated a significant interaction between groups and turn amplitudes (\(p\) < 0.001) (Table 1). In addition, RM ANOVA found a main effect of turning amplitude on step duration within the older adults group (F\({}_{(2,40)}\) = 23.46, \(p\) < 0.001, \(\eta_{\mathrm{p}}\)\({}^{2}\) = 0.41) and in the younger group (F\({}_{(2,40)}\) = 55.67, \(p\) < 0.001, \(\eta_{\mathrm{p}}\)\({}^{2}\) = 0.26) (Table 2). Post hoc pairwise comparisons showed that the step duration increased  
Figure 4: Bar graph showing the effect of group and turn amplitude on stepping characteristics; total number step, step size, step frequency, and step duration. Values are mean \(\pm\) SEM. ✓Denotes a significant interaction (\(p\) < 0.05) from Mixed Model Analysis of Variance. \({}^{\star}\) Denotes post hoc pairwise comparisons of turning amplitudes within group from Repeated Measure Analysis of Variance. \({}^{\star\star}\) Denotes main effects of group and amplitude from Mixed Model Analysis of Variance.  
significantly (\(p<0.001\)) with all increases in turning amplitudes in both groups (Table 1 and Figure 4).
## 1 Introduction
This paper addresses the problem of how to localise query dissemination and maximise data aggregation in an on-demand manner. The goal of the proposed approach is not only to reduce total energy consumption of information retrieval in sensor networks, but also to balance energy consumption among individual sensor nodes. We propose an approach of localised on-demand information retrieval that explores the name resolution for each query before the query message is forwarded to sensor nodes. The name resolution resolves a query name to the addresses of sensors that are corresponding to the query, leading to node-wise information retrieval in sensor networks. According to the location of each sensor that corresponds to the query, the area where the resolved sensors reside can be specified. To localise query dissemination and maximise in-network data aggregation, we propose the use of sink proxies as local query broadcasters and local data collectors. Each sink proxy is selected among sensor nodes according to the name resolution result. The specific features of this paper are as follows: first, an attribute-object naming system and query resolution operation are adopted in the on-demand information retrieval. The query resolution, which could be considered analogous to the function of the Domain Name System (DNS) in the Internet, resolves a query's name to local node IDs, the locations of a collective of corresponding sensors, and sink proxies, before the query message is disseminated to the sensor network. Second, we adopt a localised on-demand information routing scheme that consists of two parts: Localised Data Query Distribution (LDQD) and Localised Sensing Data Collection (LSDC). LDQD and LSDC significantly reduce the energy consumption of information retrieval. Given consideration of the temporal-spatial nature of user queries, LDQD and LSDC adopt dynamic sink proxies based on query content to improve the balance of energy consumption among sensor nodes. Third, to effectively select a sink proxy for each query, an analytical model is provided to describe the criteria of sink proxy selection. Both energy efficiency and energy balance are considered to effectively choose and utilise sink proxies. Fourth, this paper extensively studies the performance of the proposed approach for localised data query and collection through simulation evaluations of the NS-2 simulator integrated with the IEEE 802.15.4 module [12, 13]. In the simulation, we investigate protocol performance in terms of both total energy consumption and the distribution of energy consumption among individual sensor nodes. The remainder of this paper is organised as follows. Section 2 introduces the related work. Section 3 introduces the procedures for a proposed approach to localised information retrieval. Section 4 describes the system analysis of the proposed approach. Section 5 describes the evaluation and numerical results of the proposed approach and Section 6 concludes.
# Fractal Metasurfaces and Antennas: An Overview for Advanced Applications in Wireless Communications
## 5 Conclusions  
The concept of fractals as applied to antennas and metasurfaces has been discussed in this paper. A comprehensive review of fractal antennas and metasurfaces has been undertaken, exploring their design principles and performance. Several examples of fractal-based antennas and metasurfaces have been discussed and compared, highlighting their advantages, limitations, and potential applications. Some multifunctional fractal reflectarrays have been presented, offering polarization and frequency diversity, which are useful for enhancing the capacity, coverage, and throughput performance of new generation telecommunication systems. Additionally, the potential of fractal metasurfaces has been discussed, demonstrating their application in UHF-RFID multipath mitigation and energy harvesting systems.  
In conclusion, the application of fractal concepts to antenna and metasurface design has brought significant advancements and advantages in the field of electromagnetics. Fractal antennas and metamaterials, with their self-similar and intricate geometric patterns, offer several benefits over traditional structures, such as their multiband/wideband operation, compact size, and high degree of design flexibility. Ongoing research and development in these areas aim to explore new designs and fabrication techniques to further advance their capabilities and broaden their range of applications, such as for statistical arrays [96; 97].  
Conceptualization, F.V. and S.C.; methodology, F.V.; validation, F.V., S.C. and A.B.; investigation, F.V. and S.C.; resources, F.V.; writing--original draft preparation, F.V.; writing--review and editing, F.V. and S.C. All authors have read and agreed to the published version of the manuscript.  
This research was funded in part by the European Union under the Italian National Recovery and Resilience Plan (NRRP) of NextGenerationEU, in partnership with \"Telecommunications of the Future\" (PE00000001--program \"RESTART\", project \"SPARKS\"), by the PNRR project \"TechdyCou--Technologies for climate change adaptation and quality of life improvement\"(ECS 00000009, CUP H23C2200037006, Piano Nazionale di Ripresa e Resilienza), and by Ministero dell'Universita e della Ricerca (MUR), Italy, as part of Programma Operativo Nazionale (PON) Ricerca e Innovazione (2014-2020)--Area di Specializzazione AEROSPAZIO.  
The authors declare no conflict of interest.
## 1 Introduction
### Goal and Benefits of This Study  
The present study considered four sources of published data on electron-neutral collision cross sections for scattering by six species, which represent five gaseous species common in combustion, either as combustion reactants (molecular hydrogen and molecular oxygen; H\({}_{2}\) and O\({}_{2}\)) or as combustion products (carbon dioxide, carbon monoxide, and water vapor; CO, CO\({}_{2}\), and H\({}_{2}\)O). The sixth species is potassium vapor, which is considered an important seeded element (added in a small amount) to facilitate ionization and thus to act as the main source of electrons in the plasma [32]. The electron-neutral collision cross sections were investigated for a range of absolute electron temperatures from 2000 K to 3000 K, which is a suitable range for representing conventional air-fuel combustion with unheated air, hotter-air combustion with preheated air, or even-hotter oxygen-fuel (oxy-fuel) combustion [33; 34; 35; 36].  
In the present study, (1) four different methods of electron-neutral collision cross sections for combustion plasma are presented. This can help plasma modeling researchers in comparing these methods and utilizing the appropriate one for their CFD models. The results are discussed, and connections with the electric conductivity and combustion type (air-fuel versus oxy-fuel) are established. (2) Quantitative measures of the disparity between the four methods of computing electron-neutral collision cross sections are reported, which indicate the reasonableness of applying a speed-independent approximation given the implied high levels of uncertainties. (3) Linear regression models for the electron neutral collision cross sections are developed based on discrete values reported in one of the sources, for the six species covered herein. (4) The idea of implementing the mean kinetic energy in the monoenergetic collision cross section functions for the six species is tested, and it is found to give acceptable results in most of the covered species. (5) Examples of the monoenergetic profiles of electron-neutral collision cross sections are visualized for the six considered species, which demonstrate how these profiles can vary largely from one species to another and also show that this speed-dependence can be far from monotonic. (6) A mathematical description is given for how the speed-independent electron-neutral collision cross sections can be obtained from the speed-dependent profiles.
## 3 Results and Discussion
### Effect of the Enzyme Treatments on TFs and TRs in Tea Extracts  
Tyrosinase and lactose have enzymatic oxidation functions and can catalyze catechins to form theaflavins, thearubigins, theabrownines (TBs), and other compounds [6], which positively impact the aroma and functional quality of tea. As shown in Figure 10, the theaflavin content of TYR, TYR-LAC, and TAN-TYR-LAC increased by 55.56%, 66.67%, and 51.11%, respectively, compared to the control group, while the samples with the highest theaflavin content were those treated with LAC and TYR-LAC, having a theaflavin content that was 3.29 and 3.57 times higher than that of the control group. EGCG, ECG, EGC, and C can be oxidized to theaflavins by tyrosinase and lactose. Tyrosine produced theaflavins at higher levels than lactose (Figure 10). Pyrogallol- and catechol-type catechins are conjugated by ECG and EGC to produce theaflavin 3\({}^{\prime}\)-O-gallate (TF2B), and by EGCG and ECG to produce theaflavin 3,3\({}^{\prime}\)-di-O-gallate (TF3) [21]. While theaflavins, a good substrate for lactose, continue to be oxidized into thearubigins and other catechin polymers, tyrosinase itself cannot oxidize theaflavins. Laccase continues to participate in the subsequent reactions, presumably because theaflavins no longer have an O-dihydroxyl B-ring [17] (Figure 8b). Thearubigins are considered ill-defined polyphenol components that contain heterogeneous polymers; therefore, their structure remains largely unclear [6]. The theaflavin content resulting from the TAN-TYR and TAN-TYR-LAC treatments was lower than that resulting from the TYR treatment, and the thearubigin content resulting from the TAN-LAC and TAN-TYR-LAC treatments was lower than that resulting from the LAC treatment (Figure 10). Therefore, it is speculated that tannase may have an inhibitory effect on lactose. This inhibition may be reflected in the inhibition of the activity of lactose  
Figure 9: Contents of gallic acid (**a**), gallated catechins (**b**), and non-gallated catechins (**c**) in tea extract. GA: gallic acid; EGCG: (\(-\))-epigallocatechin gallate; ECG: (\(-\))-epicatechin gallate; EGC: (\(-\))-epigallocatechin; and C: (\(+\))-catechin. The error bar represents the standard error of the mean, and by the LSD test, the average of different lowercase letters indicates a significant difference (\(p<0.05\)).  
by tannase, as well as in the competitive inhibition of the substrate, because tannase has an excellent ability to convert gallated catechins. At the same time, phenolic substances such as EGC and EGCG may also inhibit the activity of tyrosinase, while EC, C, and their oxidation products may also affect the activity of laccase [17]. Therefore, the single addition of tyrosinase or laccase, or a combination of both enzymes, seem to have a better ability to increase the theaflavin and thearubigin contents than adding a combination of tannase and another enzyme.
# Secure On-Off Transmission in UAV Relay-Assisted mmWave Networks
## 1 Introduction
### Related Work and Motivation
In addition, taking into account the practical limitation in terms of imperfect beam alignment at legitimate nodes, the effects of beam alignment errors on the secrecy performance of UAV relay-assisted mmWave networks still needs to be investigated.
## 3 Results and Discussion
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Effect** & **F-Ratio** & **\(p\)-Level** \\ \hline Year & 0.01 & 0.91 \\ Soil & 0.35 & 0.56 \\ PGR & 4.26 & \textless{}0.001 \\ Year \(\times\) Soil & 0.74 & 0.39 \\ Year \(\times\) PGR & 2.25 & 0.03 \\ Soil \(\times\) PGR & 1.58 & 0.15 \\ Year \(\times\) Soil \(\times\) PGR & 1.34 & 0.24 \\ Length of stems & 18.44 & \textless{}0.001 \\ Length of roots & 0.08 & 0.77 \\ Number of shoots & 0.16 & 0.69 \\ Number of stems & 0.00 & 0.97 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Evaluation of the effect of the research factors, PGRs, soil type, and year of vegetation, on dry biomass yield following M-GLM procedures (\(R_{\text{adj}}^{2}=0.74\), \(F=8.9\), \(p<0.001\)). treatment of rhizomes and resulted in longer stem length under this treatment. For the first year of vegetation in Soil II, the impact of PGRs had the following order: Ch2, Ch1 > R1, S2; for other treatments, the effect was neglected and close to the control treatment. In the case of Soil II, the effect of treatment by Charkor, which influences root system development [9], was the main factor for the first year of growing, similar to Soil I. For the second year, the influence of PGRs had the following order: Ch2 \(\geq\) Ch1 > S2, S1; for other treatments, the influence of PGRs was the same as for the control. These results highlighted that for the second year the influence of PGRs in the better quality Soil II was altered compared to the influence in the poorer quality soil of Soil I. For both years, the prevailing impact of Charkor in the better quality Soil II revealed that this particular PGR could be recommended for increasing stem length (and biomass value) when the crop is produced in good quality soil. When the soil quality is worse (Soil I), combined treatment with the other PGRs studied, Stimpo and Regoplant, gives almost the same effect as Charkor for increasing stem length (biomass value). PGR treatment impacts on dry biomass yield showed (Figure 2) that the most potent influence was observed for Ch2; the order of impact was the following: Ch2 followed by S2, R2, R2, Ch1; for another treatment, the effect was neglected and almost the same as for control. This observation is correlated with the impact of PGR treatment on length and is in line with the results of [9], which showed that Charkor is an effective substance for enhancing \(M\). \(\times\)_giganteus_ development due to stimulation of the root system, which is among the main factors in plant development [64]. The stimulating effects of two factors (Year and PGR) were essential for the second year of vegetation and noted for almost all PGR treatments besides Ch1, S1, and S3. Comparison of Ch1 and Ch2 showed that Ch2 had a greater stimulating influence on the effects of the two factors.
# Cloud-Based Analytics Module for Predictive Maintenance of the Textile Manufacturing Process
## 7 Conclusions  
IoT is transforming multiple fields, including the textile manufacturing industry. IIoT is concerned with industrial frameworks in which several devices or pieces of equipment are connected and synchronized using gateway software in human-to-machine and machine-to-machine communications. Recently, IIoT applications in PdM have attracted considerable attention from enterprises [46]. In this study, we surveyed PdM-related literature, examining results from 3697 publications associated with PdM and related studies. We used descriptive statistics, PoP, to analyze studies from 2010 to 2019 in Google Scholar. The PdM-related concept has rapidly developed across diverse manufacturing applications, including quality management, scheduling, facility management, and capacity optimization. PdM-related studies are highly cited. Most studies focused on building ML models to address PdM challenges, whereas only a few studies have examined the deployment and validation. The primary IoT consulting company has reported manufacturing operation and production asset management in IoT applications to be cloud deployment of IoT software and vertical IIoT platforms [11]. For practical and research applications,sustainable use of a trained model is important for data analytics in a range of industries. We demonstrated a complete data analytics process based on the standard KDD procedure for a practical textile manufacturing use case. We built an ML model and deployed the trained model as a PdM API on a cloud platform. The PdM API can be integrated with third-party platforms and used for ML analysis workflows. Quality management is important in the textile industry. Substandard textile products are discarded, requiring the entire manufacturing process to be repeated to achieve certified quality management. In this study, data analytics was employed to achieve PdM associated with quality management. The production line could produce high-quality products by optimizing equipment settings in warping, beaming, and sizing processes. The equipment data were preprocessed, and the features of the preprocessed data were selected by professionals using strong domain knowledge. ML algorithms were applied to the equipment data to predict equipment settings required to optimize product quality. The results demonstrate that linear regression had significantly less error than other regression approaches. The trained model could enable optimized equipment management to improve quality management. Many consulting institutions emphasized the importance of PdM. Herein, we conducted a case study for textile manufacturing to demonstrate data analytics and developed a PdM API that provides users cloud-based alternatives to on-premise infrastructure such that enterprises can avoid poor quality and high return and defect rates.
# Three-Dimensional Multi-Agent Foraging Strategy Based on Local Interaction
## 5 3D Multi-Agent Foraging Strategy
### Control of an Agent Based on Local Interactions  
In Algorithms 2, 4 and 5, an agent, say \(n_{i}\), travels along a path until meeting the last agent on the path. Let \(P=\{m_{1}\to m_{2}\rightarrow\cdots\to m_{end}\}\) define the agents on the path. After \(n_{i}\) encounters \(m_{j}\) (\(j\leq end-1\)), \(n_{i}\) heads towards \(m_{j+1}\). We address 3D local controls for \(n_{i}\) such that \(n_{i}\) travels along \(P\) until reaching \(m_{end}\).  
Using the definition of edge in \(T\), this path \(P\) is collision-free and a sense-communication link is established between \(m_{j}\) and \(m_{j+1}\) in \(P\). Along \(P\), each end point of a straight line is set as the way point for \(n_{i}\).  
Local controls for \(n_{i}\) are developed in discrete-time systems. Let \(\mathbf{n}_{i}(k)\) define the global coordinates \(\mathbf{n}_{i}\) at sample step \(k\). Let \(W\) define the next waypoint that \(n_{i}\) will encounter as \(n_{i}\) travels along \(P\). Let \(\mathbf{W}\) define the global coordinates of \(W\).  
For convenience, let \(\mathbf{g}=\mathbf{W}-\mathbf{n}_{i}(k)\). According to Assumption (A1), \(n_{i}\) can measure \(\mathbf{g}\) utilizing its local sensors. For example, \(n_{i}\) emits signal pings for measuring its neighbor agent. Suppose that the pings emitted from \(n_{i}\) are reflected from its neighbor agent, say, \(m\in\mathcal{N}(n_{i})\). In this case, \(n_{i}\) can estimate the elevation angle, azimuth angle, and range to \(m\) through the 3D MUSIC algorithm [40].  
Recall that \(dt\) denotes the sampling interval of our controls. If \(\|\mathbf{g}\|>MaxS\times dt\), then \(\mathbf{v}_{i}(k)\) in (1) is set as  
\[\mathbf{v}_{i}(k)=MaxS\times\frac{\mathbf{g}}{\|\mathbf{g}\|}. \tag{8}\]  
This implies that \(n_{i}\) moves towards \(\mathbf{W}\) with its maximum speed. If \(\|\mathbf{g}\|\leq MaxS\times dt\), then \(n_{i}\) heads towards the next waypoint after \(\mathbf{W}\).  
Suppose that we consider an agent, such as an AUV, with non-holonomic constraints. Along the AUV's path \(P\), each end point of a straight line is set as a waypoint for the AUV. With the waypoints set, we can utilize the path following controllers in [38; 39] while considering the dynamics of the AUV to make the AUV visit the waypoints. How to ensure that an agent with motion constraints moves along waypoints is beyond the scope of the present paper.
# Consolidating ICESat-2 Ocean Wave Characteristics with CryoSat-2 during the CRYO2 ICE Campaign
## 4 Results  
Comparisons between the SWHs determined from CryoSat-2 and the ICESat-2 derived models are presented in this section. The full dataset from 2020 to 2021 is used. The wave fitting of each ground track is presented with examples in Section 4.1, and the behavior of the full dataset is shown in Section 4.2. In Section 4.3, the dependency of the models on the sea state is analyzed.