esa-sceva/satcom-chunk-collection huggingface dataset:
# Simulation of Achievable Data Rates of Broadband Power Line Communication for Smart Metering
## 7 Simulation--Real Topology
### Simulation Set-Up  
To evaluate the capacity of BB-PLC channels for worst-case noise scenario, these parameters for real topology simulation are considered:  
* The frequency band 1.8-30 MHz for broadband PLC.
* QAM64 modulation.
* According to IEEE 1901 standard and FFT OFDM PHY specifications, 917 active carriers were considered.
* Transmitting power was 13.8 nW according to a previous study [53].
* Background noise was set up according to real measurements [54] at the value of -70 dBm/Hz. This value represents very noisy conditions in the real power line networks.
* The throughput on physical layer of 1 Mbps at the minimum was considered for simulation.
# Potential of Plant Stem Cells as Helpful Agents for Skin Disorders--A Narrative Review
## 6 Large-Scale Production of Plant Cell Cultures  
The research on cultivating plant cells and organs continued to advance to acquire a greater phytochemical output, particularly for industrial-scale manufacturing. [PERSON] and [PERSON] discovered a method of cultivating plants in liquid culture under submerged and aerated conditions, which was followed by the production of secondary metabolites from _Lithospermum erythrorhizon_ [PERSON]. et Zucc. and _Coptis japonica_ (Thumb.) [PERSON] using suspension culture systems of a mass of undifferentiated cells for shikonin and berberine production [107]. A breakthrough in cosmetic application and production from plant stem cells began with the publication of the findings of the research on _Malus domesticus_ stem cells for skin and hair longevity [72]. Since then, knowledge and understanding of the manufacturing process based on plant cell culture improved greatly and found its way into the cosmetic industry.  
Stirred-tank and wave bioreactors are effective systems for producing plant cell cultures. A stirred-tank bioreactor is the most common because it provides simple scalability, high oxygen transfer capability, a proper fluid mixing system, and a wide range of alternative impellers [108]. The process of Paclitaxel production uses stainless steel bioreactors with a capacity of up to 75,000 L, demonstrating the robustness and capability of mass-scale production [37]. This type of bioreactor is widely used in cosmetic industries, e.g., for the cell cultures of cloudberry [109], marigolds [33], Japanese aster [48], Asiatic pennywort [50], Edelweiss [22] and sacred lotus [23], as shown in Table 1.  
Wave bioreactors adopt the mixing mechanism based on the rocking wave-like movement of a disposable inflated bag-like container. The motion also promotes oxygenation and bulk mixing with shear, stress-free characteristics. Moreover, a wave bioreactor is easy to operate and time-effective (no preparation, cleaning, or sterilization is required). Also, it increases biomass productivity, does not change cell morphology, and has low contamination risk [110; 111]. A wave bioreactor is used to produce pharmaceutically important isoflaves from _Glycine max_ (L) Merr. and _Nicotiana tabacum_ L. suspension cells up to 70 and 100 L working volume [112]. Wave bioreactors have also found practical applications in the production of cellular biomass, which is an ingredient of cosmetic formulations containing such valuable taxa as _Malus domestica_ Borkh. [24; 72], _Vitis vinifera L., Argania spinosa_ (L.) Sheels, and _Rhododend Forrugineum_ L. [37; 113].
## 1 Introduction  
Mobile Ad hoc Networks (MANETs) and Peer-to-Peer (P2P) networks share concepts of self-organization and decentralization. Both systems operate without a central, coordinating entity and do not require a preexisting communication infrastructure for operation. Considering these similarities, combining MANETs and P2P networks is reasonable to obtain a fully distributed, decentralized and infrastructure-less communication substrate. Several architectures for such mobile P2P (MP2P) networks already exist. The proposed approaches differ in terms of the layer(s) on which they are implemented and in terms of the deployed mechanisms for the lookup process that is responsible for locating services available in the system as well as in terms of the self-organized network maintenance. Combining both architectures at a single layer or enabling a cross-layer information exchange may increase network efficiency since the overhead for network operation and maintenance can be reduced.  
Mostly, an MP2P network benefits from its inherent self-x features as, e.g., a single node failure will (most probably) not affect the whole network. Yet, on the other hand, securing decentralized networks in common and MP2P networks in particular is a challenging task. The routing algorithms for both P2P networks and MANETs have to rely on the benign behavior of the nodes forming the network to forward messages to the destination correctly. In both architectures, nodes join and leave the network in a flexible way. Due to this, both are susceptible to routing or Sybil attacks. On the other hand, various MANET and P2P related security measures were proposed to increase the robustness of the routing algorithms and to detect Sybil attacks. However, the question on which layer the countermeasures has to be implemented to optimize the network security and efficiency in MP2P networks is still open.  
In this paper, we survey different approaches proposed for establishing Mobile P2P (MP2P) networks and briefly summarize the basics of the underlying MANET and P2P architectures. Further, we survey selected attacks on both basic architectures independently from each other and derive the effects of those attacks on MP2P networks. As the attacks we selected are well known, several countermeasures exist. We compare these countermeasures and discuss their efficiency concerning the requirements of MP2P networks. Further, we propose a first outline of a cross-layer countermeasure for MP2P networks that may increases the robustness to multiple routing attacks.  
In Section 2 we introduce P2P networks; we describe basic architectures including lookup algorithms and point out major challenges. In the next section, we focus on MANET architectures and challenges. In Section 4, we present the three different categories of MP2P architectures that have been proposed by now and, in Section 5, we survey attacks and countermeasures for the three presented architectures. In the last section, we summarize the discussed attacks on mobile P2P networks and provide an outlook on our future work in this area.
# The New Paradigm of Deepfake Detection at the Text Level
## 1 Introduction  
In the academic environment, researchers face problems with plagiarism and artificial intelligence (AI) text generation. The problem of original content is also found in other areas in which the result might have more dangerous effects. At the level of social media platforms, these deepfake texts can deceive users into believing that the content is generated by a certain person, usually one of notoriety. Implementing an algorithm that identifies whether the text is associated with the attributed author at the time of posting would reduce cases of misinformation. The identification of AI-generated texts can be countered by using AI identification tools. However, such a text could be written by someone else or generated by AI and then modified by another person in order to seem convincing, although still not written by the person to whom it is attributed.  
Current textual analysis tools can identify whether a text is plagiized, grammatically correct, or generated by AI. Instances requiring material authenticity certainty should also address more advanced aspects, such as the text's original author. To achieve this goal, the authors of the present paper propose, as a starting point for research in this direction, an analysis of writing style characteristics. This idea is based on the fact that experienced authors have a certain pattern in writing materials. These innovative methods can be applied to detect AI intervention and validate the author's authenticity. Thus, the present article proposes a new direction in research based on linguistic style analysis, highlighting the elements that differentiate an AI approach from a custom-made writing style.  
The main contributions of the paper are as mentioned below:  
* Proposing a hybrid solution for identifying deepfake texts;
* Integrating stylistic analysis methods in detecting unique characteristics in the writing of texts;
* Designing a custom classification machine learning deepfake detection model, named the custom deepfake text model (CDFTM), for classifying between human content and AI-generated content;
* Developing an anomaly deepfake text model (ADFTM) for identifying anomalies in unique characteristics at the text level to determine the authorship of a specific author;
* Opening new research directions for applying these methods in various fields.  
The paper follows the formal structure of a research study, consisting of six sections. Related works concerning the concepts of deepfakes and AI models used in the area of deepfake text are described in Section 2. Section 3 presents the materials and methods, introducing innovative elements by describing the issues related to building the dataset for the classification models, and providing detailed descriptions of the two models. Section 4 details the experimental outcomes of the architecture used in the classification model and the results obtained from the anomaly-detection model for textual characteristics. The discussion of the results, including their implications, is explored in Section 5, and the conclusions and future work are shown in Section 6.
# An Experimental Study on the Reflection Characteristics of Laser Echo Light Waves
## 4 Analysis and Discussion
### Distribution Characteristics of Light Spot Centroid Drift  
In the process of in-depth research on the light spot drift phenomenon, we usually use the method of monitoring the changes in the center of mass position of the light spot to quantitatively describe the drift behavior of the light spot. In the experimental setting, there is a linear correspondence between the grayscale value of the spot image and the intensity of the incident light, which indicates that statistical analysis of the light intensity of the spot image is essentially an analysis of the grayscale value of each pixel in the image. We use the grayscale centroid algorithm to extract the centroid of the light spot. Usually, by observing the changes in the position of the centroid of the light spot, we can effectively describe the phenomenon of light spot drift. Table 7 shows the weather conditions when Link 1 and Link 2 measured the spot samples. T23-T27 are samples of Link 1, and T28-T32 are samples of Link 2.  
A 256 \(\times\) 256 pixel window was selected to observe the areas of 0.8 km and 4 km transmission distances. Taking the lower left corner of the image as the origin, the centroid data were converted to the actual scale, and the data within the same transmission distance were restricted to the same coordinate scale. To ensure the consistency of the data, samples at around 9 pm in each weather condition were selected as observation objects. Figure 6 is a distribution diagram of the centroid of the light spot on a sunny day at a transmission distance of 0.8 km, and Figure 7 is a distribution diagram of the centroid of the light spot on a cloudy day at a transmission distance of 4 km. It can be seen from the two figures that whether at a distance of 0.8 km or 4 km, the range of the centroid distribution decreases  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Measuring** & **Sunny** & **Lightly Rainy** & **Moderately Rainy** & **Heavily Rainy** & **Cloudy** \\ \hline R\({}_{2}\)\({}^{2}\) & 0.9343 & 0.9444 & 0.9306 & 0.9712 & 0.9824 \\ R\({}_{2}\)\({}^{2}\) & 0.9916 & 0.9825 & 0.9813 & 0.9665 & 0.9624 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Link 2 probability density distribution fitting parameters.
## 5 Experimental Evaluation
### Application-Level Latency Results
#### 5.3.2 Hazard Reported by the Traffic Management System  
In this scenario, the application-level latency is measured by computing the elapsed time since the transmission of a DENM message by the TMS until the subsequent reception of that DENM message on OBU 1 and OBU 2. We have carried out one measurement campaign with OBU 1 and OBU 2 connected to the same edge cloud. OBU 1 communicates with the Edge Geoserver using the UDP/HTTP protocol, whilst OBU 2 uses the MQTT protocol to communicate via the Edge MQTT broker. Both of the OBUs were assigned the role of roadside hazardous events receivers reported from the TMS, which periodically transmitted a DENM message for a road incident at a fixed time interval of 10 s.  
Figure 9 presented the results of application-level latency from the TMS to the OBUs. Each boxplot in the figure represents the distribution of measured application-level latencies over the total number of collected samples for each receiving OBU, indicating mean and median values, respectively, by the triangle and the horizontal line.  
The average application-level latency from the TMS to the UDP/HTTP-based OBU is 93.3 ms with a standard deviation of 48.7 ms, and the average latency from the TMS to the MQTT-based OBU is 88.6 ms with a standard deviation of 47.6 ms, as can be observed in Figure 9. We devise the similar observations as was before such that effectively the delay (i.e., RTT/2) over the 4G radio access network is accounting for around 40% and 42% of the average application-level latency of UDP/HTTP- and MQTT-based communications, respectively. Moreover, it can be noticed that UDP/HTTP-based communication introduces an extra delay of close to 5 ms higher than MQTT-based communication. Similarly, we can make the same proposition as before, such that the Edge Geoserver introduces extra processing delays and, consequently, impacts on the application-level latency.
## 2 Experimental Setup  
In this study, vehicle dynamometer (EC Type, Jastec Co., Seongnam, Korea) and the hybrid electric vehicle (2011 YF Sonata HEV, Hyundai Motor Co., Seoul, Korea) were used for vehicle experiment, and data were acquired by the chassis dynamometer, current measurement device (PicoScope, Pico Technology, Cambridgeshire, UK), and OBD-II monitoring system (Cantalker, DeK Information Communication Technology, Anyang, Korea).  
On-board diagnostics (OBD) is an automotive term referring to a vehicle's self-diagnostic and reporting capability. OBD systems provide the vehicle owner or service technician access to the status of various vehicle subsystems. The amount of diagnostic information available via OBD has varied widely since its introduction in the early 1980s versions of on-board vehicle computers.  
Modern OBD implementations use a standardized digital communications port to provide real-time data in addition to a standardized series of diagnostic trouble codes, or DTCs, that allow one to rapidly identify and remedy malfunctions within the vehicle.
## 3 Results and Discussion  
### Characterization  
The XRD pattern of as-synthesized ZIF-8 is shown in Figure 1a. This pattern is similar to the XRD pattern simulated by [PERSON] and et al. [31]. Characteristic peaks at 29 of 7.35\({}^{\circ}\), 10.40\({}^{\circ}\), 12.75\({}^{\circ}\), 14.73, 16.48\({}^{\circ}\), 22.18\({}^{\circ}\) and 24.55\({}^{\circ}\) ascertain the formation of a high-purity crystalline phase ZIF-8.  
Figure 1b shows the FT-IR spectra of as-synthesized ZIF-8 which is in very good agreement with previously-reported FT-IR bands of ZIF-8 [32; 38; 39; 46]. The adsorption bands for ZIF-8 at 3135 and 2929 cm\({}^{-1}\) can be assigned to the aromatic and aliphatic C-H stretch of imidazole, respectively. The band at 1584 cm\({}^{-1}\) belongs to the C=N stretch and the peak at 1606 cm\({}^{-1}\) can be assigned to the C=C stretch. The 421 cm\({}^{-1}\) band is for Zn-N stretching mode. In addition, the peaks in the region of 1350-1500 cm\({}^{-1}\) belong to the entire ring stretching. The in-plane bending of the ring are found in the 900-1350 cm\({}^{-1}\) while those below 800 cm\({}^{-1}\) are associated with the out-of-plane bending of the ring.  
The morphologies and particle size distributions of as-synthesized ZIF-8 were studied using SEM imagery, which are depicted in Figure 1c,d, respectively. The cubic shape of the ZIF-8 crystals can be seen from SEM image clearly. The mean and standard deviation of the particle sizes of ZIF-8 is ca. 0.64 \(\upmu\)m and 0.08, respectively.
# Machine Learning Reconstruction of Wyrtki Jet Seasonal Variability in the Equatorial Indian Ocean
## Appendix A  
### Validation of OSCAR Reanalysis Data Against RAMA Mooring Observations  
To validate the accuracy of OSCAR reanalysis data in the equatorial Indian Ocean, this study systematically evaluated the dataset using in situ velocity measurements. Daily velocity observations from the Research Moored Array for African-Asian-Australian Monsoon Analysis and Prediction (RAMA) were employed to assess OSCAR velocity products in the same region. Raw RAMA data underwent 5-day averaging to match the temporal resolution of the reanalysis dataset. As shown in Figure 11, six representative stations were selected for validation: 67\({}^{\circ}\) E, 0\({}^{\circ}\) N (Figure 12a), 80.5\({}^{\circ}\) E, 0\({}^{\circ}\) N (Figure 12b), 90\({}^{\circ}\) E, 0\({}^{\circ}\) N (Figure 12c), 67\({}^{\circ}\) E, 1.5\({}^{\circ}\) N (Figure 12d), 67\({}^{\circ}\) E, 1.5\({}^{\circ}\) S (Figure 12e) and 67\({}^{\circ}\) E, 4\({}^{\circ}\) N (Figure 12f). Comparison of the zonal velocity time series at 10 m depth demonstrated that OSCAR reanalysis data accurately captured temporal variation characteristics of measured velocities across three representative stations. This confirms its ability to reliably characterize near-surface current dynamics in the equatorial Indian Ocean. Based on this validation, OSCAR data were subsequently used for seasonal-scale reconstruction of the Wyrtki Jet (WJ) in this study.
# Design of Adaptive Kalman Consensus Filters (a-KCF)
## 3 Kalman Consensus Filtering Algorithm  
In this section, we provide a retrospective view of the previous work of [PERSON] [17], in which the author presented the continuous-time distributed Kalman filtering strategy without adopting the consensus filtering algorithm, instead forcing consensus through state estimates. We treat this work as the fundamental background for designing our adaptive Kalman consensus filters.  
In [17], the author considered \(n\) distributed agents working cooperatively to complete a common task for estimating the state of a linear system, defined in Equation (1), with the sensing capability defined as in Equation (2). Each agent shares its instant state estimates with its immediate neighbors \(\mathcal{N}_{i}\) through the communication topology \(\mathcal{G}\). [PERSON] [17] proposed individual agents applying the following distributed estimation algorithm:  
\[\begin{array}{l}\hat{x}_{i}=A\hat{x}_{i}+K_{i}(y_{i}-C_{i}\hat{x}_{i})+\gamma P _{i}\sum_{j\in N_{i}}(\hat{x}_{j}-\hat{x}_{i})\\ K_{i}=P_{i}C_{i}^{T}R_{i}^{-1},\quad\gamma>0\\ \hat{P}_{i}=AP_{i}+P_{i}A^{T}-K_{i}R_{i}K_{i}^{T}+BQB^{T}\end{array} \tag{3}\]  
with initial conditions \(P_{i}(0)=P_{0}\) and \(\hat{x}_{i}(0)=x(0)\).  
Through this distributed algorithm, it was claimed that the collective dynamics of the estimation errors are \(e_{i}=x_{i}-x\) (in the absence of noise, this assumption is made to ease the computation complexity of the proof; later work showed that even if process and measurement noise are present, the stability and convergence properties of the adaptive Kalman consensus filtering algorithm remain valid). The errors converge to zero through analysis of the Lyapunov function \(V(e)=\sum_{i=1}^{n}e_{i}^{T}P_{i}^{-1}e_{i}\). Furthermore, all agents with the estimator structure in Equation (3) asymptotically agree with each other on their state estimates, which match the value of the true states of the linear system in Equation (1), such as \(\hat{x}_{1}=...=\hat{x}_{n}=x\). See the proof in [17] for more detail.
## 4 Simulations
### Throughput Balancing in Multiple Stream Scenarios  
In this simulation, the throughput balancing between two streams was studied. One important parameter to investigate is the amount of time it takes to balance multiple streams if one or multiple streams start to transmit data with some delay. Two topologies from Figure 17 were implemented with two UDP data streams. They consist of three and four nodes, two nodes as end points and one or two routers in the middle serving as repeaters. Simulations ran on both of these topologies. Maximum channel throughput between every node was set to 1 Mb/s, except for the channel between first end node and first repeater where the artificial bottleneck was inserted to observe its effect on the simulations. In these simulations, only two data streams were used for simplicity of the scenarios, and three values of bottleneck (100, 200 and 300 kb/s) and five delay times were applied (1, 5, 10, 100, 200 s) to determine the pattern for the balancing time.  
The resulting values shown in Figure 18 are absolute values of balancing time, i.e., from the time the second stream started transmitting to the time the transmitting speeds were balanced. The lower value the bottleneck has, the longer time interval it takes to balance the streams. The number of repeaters does affect the balancing speed; however, in our simulations only bottleneck with 300 kb/s was significantly affected. It caused the balancing to take less time with delays 100 and 200 s. The reason why significant differences occurred only with the bottleneck value of 300 kb/s was most likely that bottlenecks 100 and 200 kb/s are extremely low values in comparison to the generation of data from both streams, which was 1000 kb/s (bottleneck 100-300 kb/s was considered from real-case scenarios  
Figure 16: Scenario 2B.  
Figure 17: Simulation topology for balancing of two streams with one and two repeaters.  
obtained from our measurements [22; 63; 64; 67]). Simulations discovered that when considering the implementation of PLC into the network in different locations, it is not necessary to take into consideration the influence of repeaters if there is a bottleneck link with lower throughput than around 30% of the stream data generation speed or of the link throughput between other nodes. If the second stream starts transmitting with delay higher than 10 s, the balancing time no longer rises, and in case of bottleneck value of 300 kb/s it even slightly decreases.