esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results
### Effects on Photosynthetic Pigments and Biochemical Markers  
#### 3.7.1 Chlorophyll Content  
The chlorophyll pigments of wheat plants showed significantly different values depending on the composition of the soil and the bacterial treatments (Figure S5). The data revealed that the salinity of the soils affected the chlorophyll content and that bacterial inoculation improved this content in the wheat plant by reducing stress at different levels of salinity.  
Plants in soil 1 and 2 showed high levels of chlorophyll content when inoculated by bacteria. Chlorophyll a increased markedly after inoculation with all strains and the different combinations except strain BR5 which had a lower rate (Figure S5A). Chlorophyll levels in soil 3 seemed to be improved, especially for monoculture inoculations. The contents of chlorophyll b and total followed the same rate (Figure S5B,C). It should also be noted that these rates had increased markedly for plants of soil 2 and 3 inoculated with the BR5 strain. The carotenoids content (Figure S5D) also displayed significantly high values in plants treated with bacteria whatever the nature of the soil, however, the BR5 strain had a better rate for the most stressful soil. Carotenoids contents were less expressed in soil 3 except OR15 strain which had a higher level.
# Motion Trajectory Prediction in Warehouse Management Systems: A Systematic Literature Review
## 6 Discussion
### Insights  
Regarding the use of object trajectory prediction methods in a warehouse environments, it is necessary to evaluate their feasibility and effectiveness with regard to human safety. Usually, manual implementation is required to test these methods; however, it is possible to use publicly available source code for some of them. Thus, testing and evaluating these two properties emerges as the first avenue of research.  
In this line of thinking, it should be noted here that one of the more valuable findings was presented in a paper by [PERSON] et al. [88], which explores the implementation of UWB location sensors to enhance warehouse safety and operational efficiency. The study concludes that the metrics outlined in the paper can be used to evaluate employee performance and safety. Additionally, the authors propose a framework system that can be considered for implementation in similar projects.  
During the initial stage of the research, the LSTM model proposed by [PERSON] et al. [66] was identified as a promising approach for next position prediction. However, the NSP-SFM model [69], despite being considered state-of-the-art, was found to be impractical due to its large size and tendency to overfit the training data. This issue was discussed in the paper analysing the robustness of PECNet by [PERSON] and [PERSON] [62]. They emphasized the suboptimal suitability of such complex models for real-world applications.  
Furthermore, the literature review revealed a paucity of accurate worker trajectory prediction methods in real warehouse environments. Many existing models were deemed unrealistic for manufacturing applications, as underscored in the aforementioned PECNet paper. In this context, the authors evaluated the performance of PECNet across different datasets, comparing it to the established benchmark. They noted its limited capacity to learn effectively from subtle noise, which presents a significant challenge considering the localization error of up to 40 cm in UWB sensors.  
Nevertheless, an improved version of PECNet may offer a promising starting point for the real-world application of trajectory prediction in a warehouse environment. To sum up, exploring the performance of this method in the different settings will confirm its validity. Thus, the need of more replication studies emerges as the second avenue of research.
## 1 Introduction  
This work provides extended research to the study [1] related to sharing of the frequency band 6425-7125 MHz, between 5G and fixed satellite services transponders in geostationary orbit. In the previous study, only one satellite transponder was considered that covered the Eastern European region, whereas in this study two additional transponders that cover the Eurasian landmass and Pacific region are considered. Additionally, the authors greatly extended scenarios of calculation. First, apart from urban and suburban deployment of the interfering 5G base stations, rural deployment was taken into account as well, second in the calculation, several new modulation and coding rates of the victim receiver modems were considered which allows for more better understanding how 5G deployment will affect the performance of satellite bent pipe transponder links.  
Govements of many states around the world recognize the importance of the 5G mobile communication services and their evolution as one of the main drivers in the development of their economies. In the past, cellular technologies provided voice and Internet access services. Now with the advent of 5G, the set of provides services has expanded to many other applications such as immersive communications (AR/VR), smart cities, the smart industry with low latency, smart deliveries with drones, robotics, and many others. These new usage scenarios will lead to traffic volumes that will surpass the smartphones' traffic volumes. Recent studies concluded that 5G will increase world GDP by 960 billion dollars by 2030, 610 billion of which will be the result of the 5G rollout in the mid bands. However, it is also concluded that this forecast won't come true without allocating additional mid-band spectrum for mobile services.  
5G networks utilize bands below 6 GHz (FR1) which have good coverage but lower data rates and the bands above 24 GHz (FR2) which quite contrary, have high data rates but poor coverage area. The 6425-7125 MHz frequency band provides a perfect compromise between the data rates of FR2 and the coverage areas of FR1. Extension of the 5G standard to the 6425-7125 MHz will allow increasing the effectiveness of 5G networks.  
To realize 5G in the 6425-7125 MHz band it is required to do sharing and co-existence studies with incumbent services in this band. In the Radiocommunication sector of the International Telecommunications Union (ITU-R) under agenda item 1.2 of World Radiocommunication Conference 2023 (WRC-23) the question of identification of the 6245-7125 MHz band to International Mobile Services (IMT) is studied. The 6425-7125 MHz frequency band is allocated to the Fixed Satellite Service (Earth-to-space) and is utilized by the satellite transponders in geostationary orbit to provide communication services. Thus, before rolling out 5G networks, it is important to do interference analysis studies and figure out whether satellite links may experience disruptive interference levels from 5G.
# Bioelectrical Signals for the Diagnosis and Therapy of Functional Gastrointestinal Disorders
## 1 Introduction
The techniques to measure bioelectrical activity and/or apply bioelectrical therapy differ for each organ (see Figure 1), but they can broadly be categorized in two groups: (i) invasive and (ii) non-invasive methods. Invasive methods utilize electrodes in contact with the surface of organs, which limit their widespread use. However, these methods provide the most accurate results in measurement or treatment. Non-invasive methods utilize electrodes on the body surface or away from the body, meaning techniques can be more widely applied. However, as the electrodes are located away from the target organs, the acquired or applied signals are less well-defined. This review primarily focuses on the slow wave activity in the GI tract and covers existing techniques for measuring bioelectrical activities from organs in the GI tract (see Table 1) and the bioelectrical signatures of certain disorders that can potentially guide diagnosis. In addition, the review also covers bioelectrical therapies for FGIDs (see Table 2).
## 3 Results  
Table 2a presents the occurrence of SSBs and DSBs at different ratios of gold to iron when exposed to a 50 keV photon beam. In Figure 2, the nanoparticle configuration reveals iron as the core with gold wrapped around it. The findings indicate that when the proportion of iron exceeds that of gold within the nanoparticle, there is a decrease in the number of SSBs and DSB. In addition, it is observed that the number of DSBs is consistently smaller than that of SSBs across all photon beam energies. Similar trends can be observed in Table 2b,c for the 100 keV and 150 keV photon beams, respectively. These findings suggest that the iron serves as a core surrounded by the gold in the nanoparticle heterojunction. The volume of gold increases proportionally with the percentage ratio of gold to iron. Forinstance, when the percentage ratio is 100% gold and 0% iron, the nanoparticle is entirely composed of gold. Conversely, a pure iron nanoparticle is observed when the percentage ratio is 0% gold and 100% iron. Each simulation in Table 2 was conducted with 10 million histories. The relationship between the number of strand breaks and the percentage of volume of gold in the nanoparticle heterojunction is depicted in Figure 3 for various photon beam energies. The uncertainties of the results are based on the information from the Monte Carlo simulations. The results demonstrate that an increase in the percentage of volume of gold in the nanoparticle heterojunction correlates with a higher number of DNA strand breaks.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Percentage of Gold to Iron** & **SSBs** & **DSBs** \\ \hline  & **(a)** & \\ \hline  
\hline \end{tabular}
\end{table}
Table 2: SSBs and DSBs present at different ratios of gold to iron when irradiated by (a) 50 keV, (b) 100 keV, and (c) 150 keV photon beam, respectively.  
Figure 3: Relationship between number of strand breaks and percentage of gold in iron-gold nanoparticle heterojunction at different photon beam energies.
## 3 Model Parameters and Boundary Conditions  
### Project Overview  
There is a canal excavated with a depth of 36-47 m in the SNWDP Xichuan Section. The canal is located on the edge of the northern subtropical zone and also in the humid area. Affected by the monsoon climate all year round, it has four distinct seasons and abundant rainfall, with an average annual rainfall of more than 730 mm. In addition, this canal has a high groundwater level. Given that canals with high fills are more likely to undergo slope instability, this paper selects a typical section of the said deep canal in Xichuan Section for research. Its slope is reinforced by the combination of large-section excavation and water collection well. The canal consists of concrete lining plates, a geomembrane, sand-gravel  
Figure 2: Flowchart of seepage/stress-damage coupling analysis.  
cushions, and foundations. There are three-level bridleways on both banks, which can withstand vehicle loads, canal water pressure, groundwater pressure, and gravity.  
As illustrated in Figure 3, a three-dimensional finite element numerical simulation model of a representative portion of a deep dug channel was created. It was accomplished by considering the central point of the canal bottom as the origin, the \(X\)-axis as the horizontal direction of the vertical water flow, the \(Y\)-axis as the direction parallel to the flow direction, and the \(Z\)-axis as the vertical direction the vertical water flow. The canal structure in the numerical model was discrete based on the C3D8 RP (hexahedral reduced-integration) element. It had 185,000 elements and 208,098 nodes in total. The bottom of the finite element model was constrained fully, and the surrounding was constrained normally. The boundary conditions of the total head and the free seepage section were set. The monitored seepage flow of the canal was converted into the seepage velocity and set as the seepage velocity boundary condition.
## 2 Materials and Methods
### B-Camera with Larger Sensor Array  
In order to test the scalability as well as to facilitate large-area observation, we constructed a system with a larger array consisting of 320 sensors in 5 \(\times\) 4 subarrays. Figure 2 shows the block diagram of the system. The subarray consisted of 16 sensors connected via a 1-to-16 multiplexer to one slave microcontroller. Slave microcontrollers were connected to the master microcontroller via an SPI (Serial Peripheral Interface) bus. This allowed faster communication between those microcontrollers without the need for multiplexing. One operation cycle started with the master microcontroller giving orders to all slave microcontrollers to measure the field. Each slave microcontroller instructed the 16 sensors to start the measurement, wait before all the data were ready, collect the measured field data and send them to a master microcontroller. Lastly, the master microcontrollers sent the data via a communication unit to the computer-based PDU.  
This cascade configuration allowed all slave microcontrollers to operate simultaneously in parallel. For the 20 subarrays, the time difference between the first and the last measurements (in one subarray) was measured at \(4.6\pm 1.2\) ms. This was due to the time required for the multiplexer to select and pass the data from the 16 sensors. The maximum time difference among the 320 sensors was 4.98 ms, which occurred between the measurements at the first sensor (of the first subarray) and the last sensor (from the last subarray). Since these maximum time differences were still less than the sensor's conversion time in single measurement mode, this showed the potential to incorporate more sensors in a scalable manner without losing too much speed.
# An Analysis of Commercial Noni Juice: LC-MS/MS Phenolic Profiles and Cytotoxic Activity
## 4 Conclusions  
This study conducted a detailed investigation of the phenolic composition of commercial noni juice from the Pacific region using targeted LC-MS/MS, as well as an investigation of their biological activity using in vitro cytotoxicity screening. A total of 21 phenolic compounds were identified across the five noni juice brands, with the most abundant compounds generally being rutin, 4-hydroxybenzoic acid and gentisic acid. However, the phenolic profiles varied drastically between brands. This indicates that the phytochemical composition of Pacific Island noni juice is not standardised and is highly dependent upon the chemistry of the source materials and/or manufacturing processes used. For example, the rutin content ranged from 0.1-41 mg L\({}^{-1}\). A similar level of variation was also observed in the total phenolic contents and antioxidant capacities, while moderate variation was seen in the cytotoxic activities. Furthermore, non-concentrated noni juice does not appear to show significant anti-cancer activity. Future work is necessary to directly link the content of individual phenolics to specific bioactive properties.  
The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/app122413034/s1](https://www.mdpi.com/article/10.3390/app122413034/s1)]([https://www.mdpi.com/article/10.3390/app122413034/s1](https://www.mdpi.com/article/10.3390/app122413034/s1)).  
Conceptualization, J.B.J.; methodology, J.B.J. and J.S.M.; software, J.B.J.; validation, J.B.J.; formal analysis, J.B.J. and J.S.M.; investigation, J.B.J. and J.S.M.; resources, J.B.J. and M.N.; data curation, J.B.J.; writing--original draft preparation, J.B.J.; writing--review and editing, J.B.J., J.S.M. and M.N.; visualization, J.B.J.; supervision, M.N.; project administration, J.B.J.; funding acquisition, M.N. All authors have read and agreed to the published version of the manuscript.  
Figure 4: The percentage cell viability of HT29 cells treated with different sources Noni juice extracts at 500 \(\upmu\)g/mL. Different letters on the bar indicate significant difference between the different sources of Noni crude extracts (\(p<0.05\)). Negative control: cells without treatment; positive control: cells treated with 10 \(\upmu\)g/mL cisplatin (chemotherapy drug). Abbreviations: FN = Fijian Noni; LHN = Life Health Noni; DHN = Dynamic Health Noni; TON = Tahitian Organic Noni; CIN = Cook Island Noni.  
**Funding:** This work was supported by a New Staff Grant (RSH/5343) awarded by CQUniversity to one of the authors ([PERSON]). One of the authors ([PERSON]) acknowledges support from the Australian Government in the form of a Research Training Program Scholarship.  
**Data Availability Statement:** Data are available upon request from the corresponding author.  
**Acknowledgments:** Thanks to [PERSON] from Shimadzu for assistance in setting up the LC-MS method.  
**Conflicts of Interest:** The authors declare no conflict of interest.
## 6 Conclusions  
Metaheuristic optimization methods are developing rapidly and have been widely applied to numerous optimization design problems, such as the optimum dimensional synthesis of the path-generating four-bar linkages in this study. However, the selection of an accurate, effective, and fast converge optimization method is still worth exploring. This research comparatively studies the exploration and efficiency of five selected metaheuristic optimization methods, including two swarm intelligence-based algorithms (PSO and HPSO) and three evolutionary-based algorithms (DE-gr, EPSDE, and L-EPSDE), which are widely used and are easily implemented metaheuristic optimization methods, by performing five representative synthesis problems of path-generating four-bar linkages. The five representative problems (three examples with prescribed timing and two examples without prescribed timing) were investigated using 100 experimental trails, in which each has a maximum iteration of 1000 (except Case 4, which has 2000). The accuracy and efficiency of the five metaheuristic methods were compared through the statistical analyses of the extensive optimal results and were also compared to those of previously reported algorithms in the literature. The results revealed that the five metaheuristic methods employed in this study can only require the execution of several optimization iterations and effectively converge to a global optimal solution of the dimensional synthesis problems of path-generating four-bar linkages. In summary, both the adaptive EPSDE and L-EPSDE methods outperformed the PSO, HPSO, and DE-gr methods and some previous algorithms presented in literature with higher accuracy (lower mean values) and efficiency (lower SDs). In addition, L-EPSDE outperformed EPSDE in the high dimensional problem owing to its ability to linearly reduce the population size in the next generation. However, DE-gr (the golden ratio numbers were selected as the parameters of the cross rate and mutation factor) exhibited similar outperforming characteristics such as EPSDE and L-EPSDE in the middle dimensional problem, and HPSO exhibited improved accuracy and efficiency than that of PSO method. Moreover, the HPSO, EPSDE, and L-EPSDE methods are potential applications in complicated middle or high dimensional optimization problems, such as the optimum dimensional synthesis of path-generating six-bar or eight-bar linkages.  
Y.-H.K.: Conceptualization, methodology, validation, investigation, resources, writing--original draft preparation, writing--review and editing, supervision. J.-W.L.: Investigation, writing--review and editing, supervision. W.-C.Y.: Software, data curation, validation, formal analysis. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Figure 23: The statistical values of the five metaheuristic optimization methods.
###### Abstract  
Today, the use of safety solutions in Intelligent Transportation Systems (ITS) is a serious challenge because of novel progress in wireless technologies and the high number of road accidents. Vehicular ad hoc network (VANET) is a momentous element in this system because they can improve safety and efficiency in ITS. In this network, vehicles act as moving nodes and work with other nodes within their communication range. Due to high-dynamic vehicles and their different speeds in this network, links between vehicles are valid for a short time interval. Therefore, routing is a challenging work in these networks. Recently, reinforcement learning (RL) plays a significant role in developing routing algorithms for VANET. In this paper, we review reinforcement learning and its characteristics and study how to use this technique for creating routing protocols in VANETs. We propose a categorization of RL-based routing schemes in these networks. This paper helps researchers to understand how to design RL-based routing algorithms in VANET and improve the existing methods by understanding the challenges and opportunities in this area. Vehicular ad hoc network (VANET); reinforcement learning (RL); artificial intelligence (AI); machine learning (ML); wireless networks +
Footnote †: journal: _Mathematics_  
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Designing an efficient routing approach is a serious issue in VANET [5; 6]. Routing protocols are responsible for determining paths between source-destination pairs [7]. Also, when breaking the discovered paths, routing protocols are responsible for forming an alternative route. In such a case, if the routing path is not properly selected, it diminishes network performance. Path efficiency is measured based on the participation of nodes in the data transmission process. Due to very dynamic topology and high-speed vehicles, efficient routing solutions are a serious challenge in these networks. Therefore, many researchers have attempted to modify the existing routing schemes in VANETs. Despite many efforts in this regard, routing protocols are still vulnerable and are not complete. Recently, machine-learning (ML) is a new field originated from artificial intelligence (AI) that includes efficient and strong techniques [8; 9]. They can be applied to integrate autonomous decision-making systems in vehicular ad hoc networks to solve their various challenges and issues such as routing. ML can produce more intelligent machines trained on past experiences without human interference. This means that they do not need explicit programming. Machine learning involves three branches: supervised, unsupervised, and reinforcement learning. The first class (i.e., supervised learning) consists of an input dataset and corresponding outputs (i.e., labels). Techniques related to this class seek to form a learning model to explore the relationship between data samples and labels
## 4 Simulation Experiment and Result Analysis
### The Impact of a Planned Path Length on Search Effectiveness
Nevertheless, the increase in \(D_{wp,1}\) also enables UAVs to consider situation information over a larger range during path planning, resulting in more globally optimal planning outcomes. Consequently, the overall search effectiveness remains almost unaffected by \(D_{wp,1}\).