esa-sceva/satcom-chunk-collection huggingface dataset:
# Plant-Derived Phytobiotics as Emerging Alternatives to Antibiotics Against Foodborne Pathogens
### Organosulfur Compounds (OSCs)  
Organosulfur compounds are organic molecules containing carbon-sulfur bonds, prevalent in various plants, particularly in _Allium_ (e.g., garlic, onion) and _Brassica_ (e.g., broccoli, cabbage) vegetables [54; 55]. Organosulfur compounds are present in the structure of certain essential amino acids, such as cysteine, cystine, and methionine, which constitute components of proteins, the tripeptide glutathione, as well as vitamins, various enzymes, coenzymes, and hormones [56]. OSCs play a critical role in plant defense mechanisms, exhibiting broad-spectrum antimicrobial activity against bacteria, fungi, and viruses, which enhances plant resistance to pathogens [55]. Organosulfur compounds, such as allicin, exert antibacterial effects by reacting with thiol groups in bacterial enzymes, leading to enzyme inactivation, membrane disruption, and inhibition of bacterial growth, including that of Gram-positive, Gram-negative, and multidrug-resistant strains. Additionally, OSCs interfere with biofilm formation, highlighting their potential application in the development of novel antibiotics and strategies to combat antimicrobial resistance, particularly in food preservation [57]. Moreover, plants such as _Petiveria alliacea_ produce OSCs in response to herbivory, with their production being tightly regulated through feedback inhibition mechanisms, helping plants adapt to biotic stressors [58]. OSC compounds can be classified into several classes based on their chemical structure and biological properties. Alk(en)yl Cysteine Sulfoxides are commonly found in _Allium_ vegetables, such as garlic and onions. Notable examples include S-allyl cysteine and thiosulfinates, including allicin, which inhibit microbial growth. Another group includes sulfur-containing compounds such as diallyl sulfides (mono-, di-, and trisulfides), primarily found in garlic. Vinyldithiins and ajoenes, formed during garlic processing, exhibit significant biological activity, particularly anticancer properties [54]. Next class, glucosinolates, found mainly in Brassica vegetables such as broccoli, kale, and cabbage, are hydrolyzed to form bioactive molecules such as isothi cyanates [59, 60]. This group also includes dimethylsulfoniopropionate produced by some land plants and marine algae, serving as an anti-stress molecule and also as a precursor to dimethyl sulfide, a volatile compound involved in climate regulation [61]. Glutathione (GSH), a tripeptide composed of glutamate, cysteine, and glycine, is another sulfur-containing molecule classified within plant OSCs. It plays a crucial role as an antioxidant, protecting cells against oxidative stress and contributing to detoxification processes [62].
# Analysis of 'Pre-Fit' Datasets of gLAB by Robust Statistical Techniques
## 4 Results, Discussion and Proposal for Further Work
### Further Work  
There have been several attempts at using robust statistics techniques in GNSS positioning, as mentioned in Section 1. Our study relies on the specific gLAB module dealing with the analysis of pre-fit data where the difference between the modeled and computed range, the pre-fit residuals as in Table 1, is meaningful. In this case, we showed that outlier detection via FS gives an advantage both in terms of number of true outliers found and computational efficiency with respect to LMS and LTS. This advantage can be further improved by considering all the information available, like _elevation, geometric dilution of precision_ and _correlation between epochs and satellites_. Moreover, it is quite natural to wonder whether robust methods can be used in other modules of gLAB, namely the PREPROCESSING and the FILTER modules, in order to distribute the effort of the outlier detection and ultimately improve the quality of SPP and possibly, the precise point positioning (PPP) [23]. Another research direction would be to apply the FSDA functions to actual data collected by a moving receiver, as for instance autonomous drones [24]. In this regard, we remark that the current implementation of the Kalman filter in the FILTER module is the classical one, hence it is not robust. This kind of analysis will probably involve the use of _robust_ time  
Figure 11: Monitoring the intercept estimates obtained with the FS on the basis of a moving time window of 10 epochs. Small deviances of the intercept estimates around zero indicate that the estimated pre-fit position remains stable. The time monitoring of the deviances (bottom panel) is complemented by views on the intercept fluctuations distribution (top left histogram) and normality departure (top right normal probability plot). The x axes of the upper panels refer again to the deviance, while the y axes refer, respectively, as it is customary, to the bin frequencies and the cumulative normal distribution function evaluated at the empirical deviance values.  
series, a topic which will be the main subject for the continuation of the present work. By aiming at'real-time' applications, we note that the translation in C language of the FSDA functions is a task currently in progress that should improve the time overhead in the use of robust methods remarked at the end of Section 3. A subsequent analysis of the flow of data in the C code could lead to a parallel implementation of the basic routines and a subsequent translation in an appropriate high-level language for hardware design.
## 3 Design and Implementation
### Hardware and Functional Units  
The ID tag consists of a three-axis acceleration sensor (model MMA7260, an Atmega 16 L Microprocessor from Atmel, Microchip Technology, Chandler, AZ, USA) from NXP Semiconductor  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Pattern** & \begin{tabular}{c} **Description of Manipulation of the** \\ **Identification (ID) Tag** \\ \end{tabular} & \begin{tabular}{c} **Latency** \\ **(ms)** \\ \end{tabular} & \begin{tabular}{c} **User** \\ **Preference** \\ \end{tabular} & \begin{tabular}{c} **Data from** \\ **Axes** \\ \end{tabular} \\ \hline TAP & \begin{tabular}{c} TAPping on the frontal \\ side of the tag \\ \end{tabular} & 622 & 17.8\% & x, y, z \\ \hline SHK & \begin{tabular}{c} SHaking the tag \\ \end{tabular} & 1790 & 10.4\% & x, y, z, y-z \\ \hline VF90 & \begin{tabular}{c} Vertical upward Flipping \\ by 90 degree \\ \end{tabular} & 1315 & 13.3\% & x, z, y-z \\ \hline VF180 & \begin{tabular}{c} Vertical upward Flipping \\ by 180 degree \\ \end{tabular} & 1527 & 11.1\% & x, z, y-z \\ \hline HFR & \begin{tabular}{c} Horizontal Flipping by 90 \\ degree to the Right \\ \end{tabular} & 1353 & 24.4\% & x, y, z, y-z \\ \hline HFL & \
\begin{tabular}{c} Horizontal Flipping by 90 \\ degree to the Left \\ \end{tabular} & 1257 & 15.6\% & x, y, z, y-z \\ \hline TO &
\begin{tabular}{c} Turning Over and back to \\ the normal position \\ \end{tabular} & 3137 & 7.4\% & x, z, x-z \\ \hline \hline \end{tabular}
\end{table}
Table 1: Description of the finalized haptic gestures to generate a passcode.  
(Eindhoven, Netherlands) running at 8 MHz maximum clock speed and an RFID tag with 915 MHz frequency. The acceleration sensor output is sampled at a bandwidth of 33 Hz.  
The dimensions of the entire hardware enclosure in the ID tag are \(60\times 75\times 4\) mm, and the weight of the ID tag is 64 g including a battery. Figure 1 shows a user manipulating the prototype ID tag with an acceleration sensor and an RFID tag to generate the haptic passcode once the initial entry authentication process is completed.
## 3 Results  
### Surface Characterization of Ti Samples  
#### 3.1.1 SEM/EDS Analysis  
At the SEM analysis specific and clearly distinguishable surface characteristics for turned samples, T-4 and T-5, and for mildly acid-etched samples, MA-4 and MA-5 (Figure 1) accordingly with the surface treatment applied, could be observed.  
Turned surfaces showed an anisotropic texture with concentric microgrooves due to the producing process. MA samples did not show this pattern, probably because the adjunctive etching treatment reduced the entity of the microgrooves. The MA surface was characterized by repeated concavities, pits and ridges of homogeneous dimensions produced by the organic acids.  
A similar composition for all the tested surfaces was measured by EDS analysis, with a high peak of Ti and adjunctive lower peaks of Al and V proper of the grade 5 Ti alloy for T-5 and MA-5 samples, whereas in none of the surfaces tested were detected organic or inorganic contaminants (Figure 2).
## 3 System Model  
In this section, we firstly establish an SDN-based SIN architecture. On this basis, this article takes the use of LEO communication satellites and GEO data relay satellites for information transmission as an example; the network model, satellite coverage and transmission model, communication link model, caching model, and computing model of the SIN are analyzed.
# Optimal Maintenance Schedule for a Wind Power Turbine with Aging Components
## 7 Case Studies
### Case Study 1  
This section deals with the full model of four components. The results for different initial ages of four components are shown in Table 2.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Initial Ages** & \(j=1\) & \(j=2\) & \(j=3\) & \(j=4\) & **PM** & **CM** \\ \hline \((0,0,0,0)\) & 62 & x & 62 & x & 9.937 & 13.756 \\ \((30,30,30,30)\) & 32 & x & 32 & x & 10.815 & 15.064 \\ \((30,30,0,30)\) & 46 & x & 46 & 46 & 10.469 & 14.868 \\ \((20,60,0,30)\) & 47 & 47 & 47 & 47 & 10.458 & 14.668 \\ \((0,0,40,0)\) & x & x & 12 & x & 10.364 & 14.229 \\ \hline \hline \end{tabular}
\end{table}
Table 2: The next PM plan for 4 components with different initial ages.  
Figure 4: **Left panel**: the optimal time to perform the next PM as a function of the parameter \(m\). **Right panel**: different average cost based on different PM plans and different monthly value loss \(m\).  
Figure 5: Plots of \(t_{(s,0)}\) for different \(s\).  
Comparing the first two cases, we find that \(62=30+32\), in accordance with Proposition 2. The two rightmost columns compare monthly maintenance costs for PM planning and the pure CM strategy (no PM planning). Note that the maintenance cost becomes larger if the components are older at the start. On the other hand, according to Table 2, the PM planning may save around USD 4000 per month, which is around 30%, compared to the pure CM strategy. In all five scenarios presented in Table 2, the optimal maintenance plan includes a PM activity for the gearbox. In four of the cases, a PM for the rotor is suggested. This is due to the higher replacement costs and failure frequency of the gearbox and the rotor. Notably, in one of the scenarios, the optimal maintenance plan suggests performing PM on all four components simultaneously. (The pure CM monthly costs are obtained by choosing a parameter \(m\) value so high that it is never beneficial to plan a PM activity.)
## 3 Network Slicing in 5G Networks
### Energy Demand of Network Slicing Service Types
In the realm of **Vehicle-to-Everything (V2X)** communication, vehicles are engaged in a bidirectional exchange with various Internet of Things (IoT) systems enabling autonomous driving, driver and pedestrian safety management, traffic management, road infrastructure management, etc. This shift is attributed to the progress in ICT and the swift evolution of IoT within the transportation sector. Within V2X communications, the data gleaned from IoT smart devices and other origins traverse through robust links characterized by low latency (within the sub-millisecond range [19]), high bandwidth, and reliability [28]. Additionally, in 3 GPP Release 18, the introduction of the **high-data-rate and low-latency communications (HDLLC)** NS aims to provide a suitable response to the increased QoS demands of extended reality and multi-modality (XRM) streams. XRM services include concurrent video, audio, ambient-sensor and haptic data encryption, and data exchange in 5G networks. Network resources that need to ensure the functionality of the **V2X** and XRM slices will have high energy requirements, as shown in Figure 4. The 3 GPP lifecycle management of a network slice's is more demanding due to the need for high reliability and exploitability among the NS resources that are expected to be used in these slices [16]. Figure 4: 3 GPP lifecycle management of a network slice [16].
# Analysis of Total-Forms of Cyanotoxins Microcystins in Biological Matrices: A Methodological Review
## 2 Quantification of Total MC by the MMPB Method
### Lemieux Oxidation Step  
The oxidation step, the key step in the extraction of the total forms of MCs, is the one that has been optimized the most. Although the reagents used in the different studies are the same (KMnO4 and NaIO3 or NaIO4), the yield of the oxidation differs according to several criteria, among which are the concentration, pH, the volume of reagents, and the time of oxidation. Several studies have compared these different criteria in order to identify what could improve the yields obtained following oxidation, taking into account that this yield varies according to the matrix (water, cyanobacteria blooms, sediments, or animal matrices such as tissues or biological fluids).
## 2 Experiment Description
### Three Regulatory Driving Cycles  
The three regulatory driving cycles, FTP-75, HWFET, and US06, which were established by the EPA (Environment Protection Agency), were selected for measuring vehicle emissions. These three driving cycle modes show various situations that can occur on real roads.  
The FTP-75 cycle is shown in Figure 3a. The cycles are introduced to simulate the urban way. Characteristics of cycles are described with distance traveled, 17.77 km, duration 1874 s, and average speed 34.1 km/h. As seen in Figure 3a, the FTP mode can be separated into three regions with different operating conditions. The first phase in the range from 0\(\sim\)505 s is called the cold start phase. Since the engine does not start until the FTP cycle begins, it is relatively colder than in other phases. The cold start phase is followed by a second phase, called the transient phase, that plays the role of warming up the engine. In the third phase, called the hot start phase, the vehicle is driven along the same trace as the first phase region.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Item** & **Specification** \\ \hline Roll type \& diameter & Roll type \& diameter Single Roll (48 inch MIM type) \\ Simulated vehicle weight & 454\(\sim\)5400 kg \\ Electric motor absorber type & AC IGBT \\ Max. speed & 200 km/h \\ Registration of actual speed value & \(\pm\)0.01\% km/h \\ Registration of actual tractive force value & \(\pm\)0.1\% F.S. (5870 N) \\ Measurement of driving distance & Encoder type \\ Max. flow rate of cooling fan & 63,000 CFM \\ \hline \hline \end{tabular}
\end{table}
Table 2: Specifications of the chassis dynamometer.  
Figure 2: Schematics of the gasoline vehicle emission measurement system.  
The HWFET cycle is shown in Figure 3b. The driving cycle is developed for simulating a mixture of interstate highway and rural driving. The cycle is tested using a warmed-up engine, and distinguished from other driving cycles with regard to making no-stop during the test. Details of the model are given in Table 1.  
Figure 3: Three regulatory driving cycles established by the Environment Protection Association (EPA). (**a**) FTP-75 driving cycle, (**b**) highway mode (HWFET) driving cycle, and (**c**) US06 driving cycle.  
the cycle's characteristics are described with duration of 765 s, total distance of 16.45 km, and average speed of 77.7 km/h.  
The US06 profile is shown in the Figure 3c. The driving cycle can be distinguished from other cycles in terms of the presence of frequent acceleration and deceleration regions. Characteristics of the cycle are a total distance of 12.8 km, average speed of 77.9 km/h, maximum speed of 129.2 km/h, and duration of 596 s. In addition, the US06 drive cycle can be divided into two regions, city, and highway mode.
## Materials and Methods
### Synthesis and Characterization of SPIONs  
The synthesis of SPIONs has been described previously [19]. Briefly, iron (III) acetylacetonate (1.06 g), oleylamine (2.98 mL), oleic acid (2.85 mL), and 1,2-hexadecanediol (3.88 g) were added and stirred under nitrogen flow for approximately 10 min in 30 mL phenyl ether at room temperature. After removing the stir bar, the mixture was heated for 30 min to 200 \({}^{\circ}\)C under nitrogen gas flow, and then the temperature was increased to 265 \({}^{\circ}\)C for another 30 min. A black precipitate was formed,which was cooled and dissolved in hexanes in the presence of oleylamine and oleic acid and centrifuged at 6000 rpm for 10 min to remove any undispersed residue. Finally, 100-nm Fe\({}_{3}\)O\({}_{4}\) nanoparticles was obtained by precipitation in ethanol. The SPION is prepared in a similar method and can be seen by XRD and SEM image. (Figures 1-3).  
Figure 1: Morphological changes of D1 Mesenchymal stem cells (MSCs) following neurogenic, osteogenic, and chondrogenic differentiation. (**A**) The zero phase of D1 cells before differentiation exhibiting MSC morphology. (**B**) After neurogenic induction, neuronal morphology was observed at 6 h after replacement the neurogenic media. (**C**) At 24 h later, most D1 cells had differentiated into neuroocytes. However, some cells recovered. (**D**) Osteogenic differentiation and (**E**) chondrogenic differentiation induction for 21 days.  
Figure 2: (**A,B**) Superparamagnetic iron oxide nanoparticles (SPIONs) fluorescence was measured with a fluorescence microscope from day 1 to 7. (**C**) Cell viability was determined by a modified 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolzolium bromide, a tetrazole (MTT) assay. After 24 h during which up to 100 \(\upmu\)g/mL SPIONs were used to label D1 MSCs, the cells were incubated with 0.5 mg/mL MTT solution for 2 h. Absorbance values were measured at 540 nm.
## 3 Results and Discussion  
### Multi-Axis Motion Platform Mechanism  
The platform design with multi-axis motion mainly consisted of three sets of crank and linkage mechanisms. The servo motor was connected with a reducer to magnify the torque output. In order to increase the stroke of the crank, the output setting position was raised to 21 cm above the ground to avoid the cranks hitting the ground when the platform moved to the lowest point. Then, the output shaft was linked with the crank. After that, the crank and the linkage were connected by a rotating pair, and the upper platform was assembled with a fish-eye joint to connect with the linkage to facilitate motion. The platform limitation of roll and pitch was \(\pm\)20\({}^{\circ}\), have stroke was \(\pm\)20 cm, yaw was \(\pm\)180\({}^{\circ}\) and the supporting weight could not exceed \(\sim\)400 kg. According to the safety rule, the highest position of the single-person sports platform could not exceed 1.5 m. The prototype of the multi-axis motion platform was shown in Figure 11. The multi-axis motion platform specifications are shown in Table 2.
Most common procedures to install bird flight diverters on power lines require human intervention, using lifts, helicopters, suspended carts, or climbing the pylons. These operations are quite risky, particularly when the forces are high, or the required working time is long. Moreover, diverters are typically installed at 5 to 10 m intervals along the power line cable to be effective, so any time reduction of this operation would significantly contribute to decreasing the costs and risks. Figure 1: (**a**) Clip-type bird flight diverter developed by Wigeva currently installed on a power line cable; (**b**) detailed view of the diverter’s clip part (red) with the cable inserted. The main goal of this work is the automation of the installation process of clip-type diverters. For this purpose, a prototype based on an unmanned aerial platform with a custom-made tool has been developed; it allows a user to install the diverters on the cable without human intervention. The tool has to generate enough force to push the diverter on the cable without endangering the aerial platform stability. The system is designed to isolate the high force needed to install the diverter (440 N) from the aerial robot, and so the UAV flying conditions are minimally perturbed. The required force is generated inside the tool, and a net-zero external force is exerted on the UAV. The main contributions of this work are:  
* Design and manufacturing of a novel prototype for the installation of a kind of clip-type bird flight diverter;
* Development of a semi-autonomous method for bird diverter installation on overhead power line cables using an unmanned aerial robot;
* Experimental validation of the prototype in an indoor testbed, closing the control loop with a vision-based Opti-Track system;
* Experimental validation and performance evaluation of the complete installation task. The paper is organized as follows. Section 2 presents the prototype designed and developed. Section 2.1 describes the aerial platform and Section 2.2 the installation tool for clip-type bird diverters. Test results are reported in Section 3. Finally, the discussion and conclusions are presented in Section 4.
## 8 Conclusions  
The next generation mobile communication networks, such as 6G, have stringent requirements of supporting a massive number of devices with their computing and communication needs with ultra-low latency and high bandwidth. UAVs are being considered as an integral part of these networks to bring additional capacity of communication and computing where the devices are located. To this end, mobile edge computing services provided by UAVs can significantly contribute to fulfilling the data processing needs of IoT devices, addressing computation-intensive offloading and latency issues. Motivated by applications of UAV computing in 6G and Industry 4.0/5.0, in this survey, we provided a comprehensive review of UAV edge computing technology for 6G smart environments. We illustrated the utility of UAV edge computing, which can be a crucial infrastructure in various application domains. We drew special attention to the need of providing privacy-preserving computing solutions, especially when ML is used, in UAV computing. In particular, we explained the role of FL in privacy-preserving UAV edge computing, drawing from the recent literature. We thoroughly investigated a novel area of research where federated learning methods are applied to improve the performance of UAV computing networks. Specifically, we elaborated the role of FL in UAV computing achieving privacy, which includes the decentralization of data for FL model development and the reduction in information sharing among the FL agents to achieve data privacy. We explained the collaboration of multi-UAV computing for achieving common goals in the real world. We further discussed UAV edge computing challenges and opportunities that will guide future research in this area. The UAV and IoT energy limitations, wireless communication security,data privacy, as well as the scalability of ML solutions will dictate future research in the domain of UAV-assisted mobile edge computing in smart IoT environments.  
Conceptualization, S.H.A.; Data curation, S.K.; Formal analysis, S.H.A., J.H., R.S. and A.H.; Funding acquisition, A.H.; Investigation, S.H.A., J.H. and R.S.; Methodology, S.H.A., A.V.S., J.H. and S.V.S.; Project administration, M.A.A. and A.H.; Resources, A.V.S. and M.A.A.; Software, S.V.S. and R.S.; Supervision, S.K. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The authors declare no conflict of interest.