esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussions
### Optimization of Dispersive Solid-Phase Extraction Procedure
#### 3.2.2 Selection of Emission Lines  
With the herein used ICP-AES instrument, multiple spectral lines can be used for the quantification of the target analytes. The selection of the emission line was based on the absence of spectral interferences in combination with the higher sensitivity, i.e., higher slope of calibration curve for the standard solutions. Finally, the following emission lines were chosen: Ba 233.527 II; Cd 226.502 II; Cu 324.752 I; Ni 232.003 I; Pb 217.000 I; Zn 213.857 I.
# Improvement of Hexacopter UAVs Attitude Parameters Employing Control and Decision Support Systems
## 2 Related Work
### Sensors Equipment
In order to compensate for the three-axis movement of the drone based on user's input, the flight controller needs PID (proportional-integral-derivative) controllers or combinations of these (PI, PD and so on). The study performed by [PERSON] et al. [59] concentrates on the efficacy of PID controllers in maintaining the stability of a multicopter drone. The results showed that by altering the gain values based on the different conditions of the disturbances, one can achieve a stabile drone. During further testing, it was observed that by adjusting PID gain values, the stability of the drone can be achieved within a specific fixed measure of time for a changing number of disturbances, even in tough conditions, which include wind speed and change in direction. [PERSON] et al. [60] illustrate in a comprehensive study a drone with advanced mobility on which four prototype brackets were developed. These prototypes include optimized sensors, devices and a camera, which work together as an integrated system platform. The sensors and communication system were employed as a new platform for atmospheric measurements at in situ locations, including the development of a wireless communication system for long distances and also a system for monitoring and visualizing in real-time the in situ local area measurements. The study was focused on gathering data regarding atmospheric phenomena and related environmental information, especially particulate matter (PM), as a major cause of air pollution. The obtained results were satisfactory, though, as a forthcoming design, based on regular flight measurements, and it is necessary to validate the resilience of the suggested system and its stability for long-term operation. The novelty of the present study, from the sensors point of view, is the relatively economical and largely accessible equipment of the hexacopter, in two versions, in terms of avionics equipment, respectively photo/video acquisition components and telemetry data transmission and reception.
# Performance Analysis of Physical Layer-Based Multiple-Input Multiple-Output on WiMAX (MIMO-WiMAX) +
## 2 WiMAX Physical Layer Model
### Forward Error Correction  
After randomization, the output bits from the randomizer are input into the FEC encoder, which encrypts data bursts on both the uplink and the downlink using a concatenated outer RS code and an inner convolutional code [7]. RS codes are utilized for the purposes of error detection, as well as error repair.  
REED SOLOMEN CODE (RS): RS codes are used to change block size, and are responsible for correcting block faults. In order to include superfluous bits in the initial bit stream, the encryption technique for the RS encoder depends on Galois field calculation to do its job. The Galois field F (28), on which WiMAX is built, correlates to RS (N = 255, K = 239, T = 8).  
CONVOLUTIONAL CODES (CC): outer RS codes are concatenated with a punctured inner convolutional code. These convolutional codes are used to repair random faults, and they are easier to build than RS codes [8].  
These programs use linear shift memory registers to add unnecessary bits to the data stream (k). Changing the encoded bit'm' into an n-bit symbol is how the convolutional code, also known as CC, is defined. The pace of the code may be expressed as m/n [9]. At the receiving end, the Viterbi algorithm is used to decipher the encoded sequence.  
Figure 1: Block diagram of WiMAX.  
Figure 2: PRB generator for randomization.
# Investigation of Nanocutting Characteristics of Off-Axis 4H-SiC Substrate by Molecular Dynamics
## 3 Results and Discussion
### Influence of Lattice Orientation
#### 3.1.2 Cutting Force and Workpiece Temperature  
Figure 6 shows the tangential and normal forces of the cutting with different lattice orientations. Tangential force is the component of a cutting force parallel to the xy-plane, and normal force is the z-component of the cutting force. Tangential force increases rapidly at the beginning of cutting, and then it grows with fluctuations as chip forms. The sudden decrease in the tangential force of on-axis model is marked with a circle. It is induced by the structure transformation on the surface of the on-axis model. Normal force decreases at the beginning and then increases with the cutting tool moving forward. The peak in the normal force of the off-axis model corresponding to Figure 4c is marked with a circle. As the defect propagates to the surface, normal force increases gradually. It decreased when the defect vanished on the surface. Figure 7 shows the temperature of SiC workpieces with different lattice orientations during cutting. The temperature of the on-axis model was slightly higher than the rest. Due to the absence of surface steps, more atoms were involved in the cutting of the on-axis model.  
Lattice orientation has an impact on the 4H-SiC structure after cutting. Defects in the three models were all found in the basal plane. This is identical to the observation in the experiment conducted by [PERSON] et al. [15]. The defects were identified as stacking faults, and bond reconstruction was found in the vicinity of the slip plane. Since defects propagate along the basal plane, the behavior of the defects depends on the angle between cutting direction and the c-axis. When the angle is smaller than 90\({}^{\circ}\), defects propagate deep into the workpiece. When the angle is larger than 90\({}^{\circ}\), defects propagate to the surface. To control the quality of the SiC substrate, the angle greater or equal to 90\({}^{\circ}\) is preferred. However, it is impossible to control this angle during substrate thinning in practice because the  
Figure 6: Tangential force and normal force of the cutting with different lattice orientations.  
Figure 7: Workpiece temperature of the cutting with different lattice orientations.  
grinding pad and the substrate are both rotating. Cutting force and temperature are also affected by the lattice orientation, while the effects are limited. The cutting force is sensitive to the structure trasformation. Tangential force and normal force are decreased when the atoms beneath the cutting tool are changed to amorphous phase. The cutting tool accumulates and releases energy through elastic deformation, which accounts for the fluctuation of the cutting force.
## 3 Topology Adaptive Differential Protection
### Topology Adaptive Technology  
Figures 4 and 5 show the flow charts of the process of obtaining the change of the topology of the distribution network and the process making the change of differential protection setting.  
The operation procedure for the user is as follows:  
1. When the site is ready for construction to carry out feeder modification, the control engineer in the control room first switches off the feeder, then issues a command to block the protection function associated with the feeder.
2. After the feeder is isolated and earthed, construction work then starts.
3. The feeder is then ready for switching on after the construction is completed.
4. The control engineer then issues command to send new topology information to the affected DTUs through DMS system.
5. After DTU receives the new topology information, the differential protection then changes its configuration settings to suit the new topology of the feeder. The control engineer then issues command to enable the differential protection, the feeder is then ready to be switched on.  
Figure 3: (**a**) Communication of current differential protection for a two-terminal circuit; (**b**) Communication of current differential protection for a three-terminal circuit.  
Figure 4: Flow chart for obtaining distribution network topology information.
###### Abstract  
This work aimed to determine the effect of the addition of different types of reinforcing fibers on the strength properties of geopolymers such as flexural and compressive strength. Geopolymers are an attractive alternative to conventional binders and building materials; however, one of the main problems of their widespread use is their low resistance to brittle fracture. To improve the mechanical properties, reinforcement in the form of glass, carbon, and basalt fibers (as grids) was applied to geopolymers in the following work. Additionally, composites with these fibers were produced not only in the matrix of pure geopolymer but also as a hybrid variant with the addition of cement. Furthermore, basalt grids were used as reinforcement for geopolymers not only based on ash but also metakaloin. An additional variable used in the study was the molar concentration of the alkali solution (5 M and 10 M) for the different types of geopolymer samples. The mechanical properties of geopolymer materials and geopolymer-cement hybrids are the highest when reinforcement in the form of carbon fiber is used. Strength values for geopolymers reinforced with basalt mats depend on the number of reinforcement layers and the concentration of the alkaline solution used. All produced composites were tested for compressive strength and bending strength. When using basalt mesh, it was possible to achieve a bending strength of 12 MPa. The highest compressive strength that was achieved was the value of 66 MPa, while for samples not reinforced with fibers, only about 40 MPa was achieved.  
geopolymers; fiber composites; reinforced by glass/carbon/basalt +
Footnote †: journal: Applied Sciences
# Potential of Plant Stem Cells as Helpful Agents for Skin Disorders--A Narrative Review
## 4 Mechanistic Insights into the Skin Aging of Plant-Derived Stem Cells
### Improving Cell Proliferation  
During the process of wound healing, the tissue undergoes four overlapping phases: hemostasis, inflammation, proliferation, and remodeling. The hemostasis and the inflammation phases occur immediately after injury and are associated with the removal of dead cells [90]. The occurrence of tissue injury initiates the activation of immune cells, resulting in the generation of pro-inflammatory cytokines. These include potent initiators of fibrogenesis such as IL-1B, TNF-\(\alpha\), and transforming growth factor beta (TGF-\(\beta\)) [94]. Cells treated with _Daphne odora_ and _Coffea canephora_ stem cell extracts suppressed pro-inflammatory cytokines TNF-\(\alpha\) and IL-6 as well as IL-1B and IL-8, respectively [21; 55]. Moreover, the _Coffea canephora_ extract inhibited the NF-\(\kappa\)B transcription factor. The results suggest that the flavonoids, phenolic acids, and lignan components from the stem cells of these species are valuable anti-inflammatory and anti-fibrotic agents in skin wound healing. Anti-fibrotic activity was also reported for the dipeptide Gly-Pro (GP) isolated from the _Hibiscus sabdariffa_ cell culture. It is postulated that the activity was achieved by regulating the TGF-\(\beta\)1-ATF4-serine/glycine biosynthesis pathway [59].  
Mechanical stress and TGF-\(\beta\) signaling at the proliferation stage cause the cells to migrate into the wound site. Under the regulation of TGF-\(\beta\), fibroblasts could multiply and secrete collagens I and III and fibronectin [95; 96]. It was further shown that senescent cells accelerate wound closure by inducing myofiblost differentiation through platelet-derived growth factor AA (PDGF-AA) secretion [95] and restricting fibrosis formation due to matricellular protein CCN1 expression in the wound site [83]. Plant stem cell extracts can accelerate healing of the skin cells during the proliferation phase. The mechanism of wound healing through fibroblast or keratinocyte proliferation was shown to be stimulated by _Fitzroug cupressoides_[57], _Citrus junos_[52], _Coffea canephora_[54; 55], _Pueraria candilei_[66], and _Pyrus pyrifolia_[19] from their scratch test assay. Moreover, these extracts also induce cell migration [19; 55; 64; 69], resulting in accelerated wound closure. The deposition of the extracellular matrix proteins and cellular adhesion through fibronectin synthesis was also observed after treatment with _Daphne odora_[21] and _Hibiscus syriacus_[60]. However, a detailed understanding of how plant stem cell extracts improve wound healing at the molecular level remains to be fully elucidated.
# Design of Direct Current Microgrid Converter with Cost-Effective Low-Voltage Battery Storage System
## 4 MPPT Algorithm Overview  
Solar cells or wind turbines have variable output power due to weather conditions. This can be modeled from an energy source point of view, like different internal resistance. For example, see Figure 5. There are AV and PV characteristics of solar cells; for an example, we present one case of light intensity.  
Figure 4: Principal block scheme of proposed buck (leg T2 + T1)–boost (leg T3 + T4) converter with one common energy storage (L1) and output filter capacitor (C1).  
Figure 5: (**a**) AV characteristic of solar cell; (**b**) PV characteristic of solar cell.  
The system is supposed to find the maximum power point (MPP) in almost real time. For small power systems, many algorithms can track MPP. The basic algorithm from a family of \"hill climbing\" algorithms is called perturb and observe.  
The algorithm is based on changing (constant increment or decrement) the value of the duty cycle, and according to changes in voltage and power in the system, the algorithm can find the maximum power point. For this case, a small microprocessor's computing power is required, and the algorithm can be applied by a maximum of five \"if\" statements. The cause of power loss due to a constant increase or decrease around the maximum power point is negligible for the power scale presented.
## 2 Background and Related Work  
### Stream Processing Systems  
An SPS is a distributed system that processes the flow of events in real-time. Streams are built with an unbounded number of continuous events, the basic unit of the data generated by applications. Generally, SPSs are deployed in a cluster of computers. The SPSs applications are represented using a graph-based paradigm, specifically building a directed acyclic graph with processing operators as vertices and the flow of events as edges. Processing operators may be of diverse complexity, for example, a union, filter, or counting of events. These operators are distributed over processing nodes using virtualized processing resources.  
We base our work on Storm [2], which is widely used for its simple programming model by applications of companies such as Spotify, Twitter, Yahoo, and Alibaba. The processing graph in Storm differentiates between two types of processing operators: spouts and bolts. Spouts transform data from an external source into events (tuples), and bolts execute topology processing tasks. Storm architecture has three main components: Zookeeper, Nimbus, and processing nodes (workers). Zookeeper [12] is a service layer that coordinates applications in a distributed and concurrent mode and is used to transmit application information and the cluster's state between Nimbus and the processing nodes. Nimbus is the master node, distributes the application among the processing nodes, and applies corrective policies in case of failure. A process called _supervisor_ manages one or more workers in a physical machine.  
Scheduling events in SPSs have several approaches. In Spark, a delayed event is retransmitted to another operator, improving events' processing delay. [PERSON] et al. [13] state that the hardware resources of the processing nodes and the operators' characteristics should be considered when planning events. To that end, each application evaluates benchmark operators in different machines to find the best configuration performance. In Storm, eight types of event distribution techniques are available. For example, shuffle grouping distributes events randomly between bolts, and field grouping distributes events by their attributes, causing events with the same attribute to be processed by the same bolt. [PERSON] et al. designed and evaluated a QoS-aware scheduler in Storm [14] that allows the system to automatically change operator placement, locating them as near as possible to the data sources and the final consumer. These techniques work in static nodes that deploy the SPS. However, unlike SLedge, they do not fit an edge architecture built with mobile devices integrating the SPS.
## 1 Introduction
Consequently, the reflection coefficient (S11) is maintained below \(-\)12 dB across 1-4 GHz, achieving a gain between 4.9 and 11.6 dBi, and even hitting 11.6 dBi within the 8-28 GHz range. In this study, we introduce a design for an array, using Vivaldi antennas to provide the wide bandwidth and gain for 5G mobile phones [18]. Inherently, Vivaldi antennas have resistance tolerances in circuit manufacturing thanks to their wideband and high-gain traits. Hence, during the production process, its realisation is not more complex than that of Yagi antennas or dipole antennas [11]. In other words, the Vivaldi antenna exhibits a significant tolerance for smartphones. Based on the results from simulations and measurements, the antenna in question is deemed appropriate for use on 5G mobile devices. The compact Vivaldi antenna, utilising W-band chips with standard 0.18 \(\upmu\)m CMOS fabrication technology, has dimensions of 1200 \(\upmu\)m \(\times\) 1200 \(\upmu\)m. The frequency range covered is from 85 to 102 GHz [19]. Utilising the Vivaldi antenna as a power divider, the antenna is then manufactured on a CMOS 0.18 \(\upmu\)m process for the second part, where structural modifications are made to enhance the lower operating frequencies. A parameter analysis is performed to examine the interplay between the cavity and the antenna, with the aim of identifying the optimal performance for the antenna [20, 21, 22, 23]. Additionally, parameter studies are conducted to evaluate the influence of critical parameters on the performance of the Vivaldi [16, 18]. The third part describes the evolution process of the Vivaldi antenna, while the fourth part discusses the final results obtained as well as the measurement results [14]. The results of the simulations show that this symmetric Vivaldi antenna fulfils the standard needs of mobile applications [11].
## 4 Enterprise Network Functionality
### Embedded Security Architecture: Zero Trust and SASE
#### 4.3.2 Secure Access Service Edge  
The SASE is an emerging paradigm of cybersecurity, a cloud-based design that moves typical on-premise security and network connectivity to the cloud for proximity to data [5; 68]. It ensures secure access for branch offices and remote users alike. Additional security is guaranteed by integrating software-defined WAN (SD-WAN) capabilities with network security features such as ZTNA [69], firewall-as-a-service (FWaaS) [70], secure web gateways (SWG), and cloud access security broker (CASB) [69]. In addition, SASE creates the convergence and integration of security functions and cloud-based connectivity [71]. As illustrated in Figure 6, it is important to note that SASE can be viewed beyond a single solution paradigm. Rather, as a platform for dynamically deploying network, data, application, cloud, and security structures for adaptability. Due to adaptability of SASE architecture, there is no restriction on what can be implemented.  
Figure 5: Zero trust network architecture framework [8].  
Figure 6: SASE model for security and network integration.
## 1 Introduction
Thus, building detection in two dimensions remains the preferred method in many urban application scenarios. In building height estimation by shadows, many high-level remote sensing products are already calibrated; the parameters, such as digital orthophoto products and images from Google Earth indicating the solar altitude and sun height, are lost. This means that shadow direction cannot be calculated with parameters taken directly from the image. Most recently, [PERSON] et al. [31] proposed building height estimation using shadows from Google Earth images, with some provided building heights as a references. [PERSON] and [PERSON] [32] also applied shadow length, combined with predefined shadow length, or estimated solar elevation angle to estimate building height. As shadows can still roughly differentiate the height of the buildings without related angle data or some building heights, we propose a building detection and height-classification algorithm that mines shadow information from images with large-area shadows, requiring only RGB information. The mined shadow information includes the shadow size, shadow edge, shadow direction, and shadow length. We use the shadow size and edge to determine the shadow direction and then generate seed-blocks based on the shadow direction. Aided by shadow length and its distribution, our method semi-automatically groups buildings into three layers: low-rise buildings, middle rise-buildings, and high-rise buildings, labeling them in different colors; this information can be applied to flood disaster risk assessment, population estimation, and building change detection. The main differences between the proposed algorithm and the previous 2D building detection methods are as follows:  
1. As a method for urban images with large-area shadows, it fully utilizes the shadow information to detect and classify buildings. There are lower requirements for image quality, as only RGB band information is used to extract buildings and classify them by height levels. The information of reference height or related angle information is not required. 3. The proposed approach could use seed-blocks to detect buildings with high precision and a low missed detection rate. This study consists of six main sections. The first includes a literature review of the subject of the study, the second details the study areas, the third introduces the methodology, the forth shows the results and an analysis, the fifth comprises the discussion regarding errors and applications, and the last presents the conclusion.
## 4 Results and Discussion
### Data Analysis
#### 4.2.1 Air Temperature  
As can be seen in Figure 12, the average air temperature values were 27.3 \({}^{\circ}\)C, 27.8 \({}^{\circ}\)C, 27.1 \({}^{\circ}\)C, and 24.7 \({}^{\circ}\)C, respectively through June to September. The average air temperature remained relatively stable from June to August but decreased in September. The minimum air temperature levels were observed to be 22.3 \({}^{\circ}\)C, 21.4 \({}^{\circ}\)C, 17.8 \({}^{\circ}\)C, and 17.1 \({}^{\circ}\)C, respectively, with September recording the lowest minimum air temperature. The maximum air temperature levels were observed to be 37.3 \({}^{\circ}\)C, 40.0 \({}^{\circ}\)C, 40.1 \({}^{\circ}\)C, and 35.7 \({}^{\circ}\)C, respectively, with August recording the highest maximum air temperature.