esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Materials and Methods
### Electric Stimulation  
The carbon rod electrodes used in this study were spectroscopic graphite electrodes with a diameter of 6 mm and a length of 20 mm. The power supplies (Maisheng Electronics, Shenzhen, China) utilized were direct current regulated power supplies equipped with a digital display and adjustable voltage settings. The electrical stimulation applied was direct current (DC) stimulation.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Component** & **Concentration (g/L)** \\ \hline Potassium Nitrate (KNO\({}_{3}\)) & 90 \\ Monopotassium Phosphate (KH\({}_{2}\)PO\({}_{4}\)) & 20 \\ Ferric Citrate (Fe\({}_{2}\)SO\({}_{4}\)) & 2.5 \\ Manganese Sulfate (MnSO\({}_{4}\)) & 0.25 \\ EDTA (C\({}_{10}\)H\({}_{16}\)N\({}_{2}\)O\({}_{8}\)) & 20 \\ Sodium Silicate (Na\({}_{2}\)SiO\({}_{3}\)) & 10 \\ Vitamin B1 & 0.1 \\ Vitamin B2 & 0.0005 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Formulation of the 1000\(\times\) microalgae culture medium stock solution.  
Figure 1: Photo and diagram of the photobioreactor system.  
The electric stimulation experiments were performed in a sterile hood, with the work surface UV-disinfected for 30 min. The hood provided 5000 lux illumination. Carbon rod electrodes were sterilized with 75% alcohol and fixed 2 cm apart. For short-term stimulation, voltage gradients were set at 0 V (control), 1 V, 3 V, 5 V, and 10 V, with microalgae inoculated in a 1 L beaker to an initial OD\({}_{750}\) of 0.150. Electrodes were placed in conical flasks for 5 s, and samples were transferred to three 250 mL flasks. For continuous stimulation, voltage gradients were 0 V, 0.05 V, 0.5 V, and 1 V. Samples were pre-divided before electrodes were inserted. Conditions matched the short-term experiment. The lab temperature was maintained at 20 \({}^{\circ}\)C, with continuous lighting for 24 h. The algal suspension was agitated 2-3 times daily, for 7 days.  
For the continuous electric stimulation, the voltage gradients for each experimental group were set at 0 V, 0.05 V, 0.5 V, and 1 V. Three 150 mL samples of microalgae suspension were transferred into three 250 mL conical flasks, and then the carbon rod electrodes were placed into the conical flasks for continuous electrical treatment. All other conditions were identical to those of the short-term electric stimulation experimental groups. The laboratory temperature was maintained at a constant 20 \({}^{\circ}\)C, with continuous light for 24 h. The algal suspension was agitated 2 to 3 times daily, and the experiments lasted for 7 days.  
The photobioreactor system was modified to apply different intensities of direct current stimulation via external power supplies (Figure 2). A pair of carbon rods were secured with three PLA connectors, fixing the distance between the electrodes at 2 cm. One end of each rod was connected to the positive and negative leads, insulated with two layers of heat-shrink tubing. After the system was inoculated and circulated via the electric pump, electrical stimulation of 0-3 V was applied for the duration of one circulation cycle.
# Implementation of Portable Automatic Tourniquet with High-Elasticity Biocompatible Strap
## 1 Introduction  
Recently, medical technologies have attracted much attention due to rapid technological development. Among medical technologies, basic screening techniques to diagnose a patient's illness are crucial. The most common screening method is through blood collection using an intravenous procedure. In general, conventional blood collection support tools such as latex tubing and buckle type-tourniquets are used to compress the patient's blood vessels [1; 2; 3; 4; 5; 6; 7; 8]. These conventional blood collection methods are operated using passive methods in which medical staff directly apply the tourniquet to the patient's limb. Long-term use of tourniquets can lead to physical damage such as hemolysis due to blood vessel compression. Furthermore, according to some research results, the reuse of the latex tubing tourniquets may threaten patients' safety (e.g., leading to site contamination and potential bloodstream infection); therefore, such material should be supplemented accordingly [9; 10; 11]. In addition, some latex allergy sufferers may experience allergic shock [12; 13; 14; 15; 16]. To solve these problems, in some countries single-use tourniquets (e.g., the Tournistrip device (Iskus Health Ltd., Ireland)) have been used for many years. Similar tourniquets are easy to tighten and adjust, and their position on the same patient can be changed; moreover, unlike some rubber-band designs, they do not pinch the patient's skin. Nevertheless, medical staff have also expressed the need for fully automatic devices with single-use tourniquets.  
In this study, to overcome the disadvantages of conventional blood collection support tools, an automatic tourniquet was successfully implemented. It automatically compresses the limb in preparation for blood collection and is easily operated. Therefore, the damage caused by improper tourniquet use by medical staff, such as latex allergy, site contamination, and potential bloodstream infection, will be reduced significantly. Additionally, a high-elasticity biocompatible strap has been used for the automatic tourniquet. Therefore, it can be used for some patients with a latex allergy. Specifically, among the various materials available, a thermoplastic elastomer (TPE) strap was selected on the basis of the experimental results. The proposed automatic tourniquet was designed to automatically adjust the strap length through the activation of a direct current (DC) motor. This mechanism was developed based on the current control of the system main controller. To evaluate the performance of the automatic tourniquet, blood flow characteristics were verified using ultrasound equipment and compared with the conventional blood collection support tools of latex tube and buckle-type tourniquet.
# A Comprehensive Review of Indoor Localization Techniques and Applications in Various Sectors
## 5 Future Research Directions
### Enhanced Localization for Special Populations  
Developing localization systems tailored for special populations, such as Alzheimer's patients or mobility-impaired individuals, is a critical area of future research. High-accuracysystems integrated with wearable devices and AI algorithms can enhance patient safety by providing continuous monitoring and timely alerts for wandering or emergency situations [60].
## 3 Experimental Results and Analysis
### Experimental Results and Analysis
#### 3.3.3 Effect of the Leading Automated Vehicle on Mobility and Energy Efficiency  
Figure 9 shows the MOE evaluation in terms of average speed, delay time, fuel consumption, and emissions based on the AV penetration rates. The results of the MOE evaluation indicate that the simulation became more effective as the AV penetration rate increased. Regarding mobility, the average speed gradually increased and the delay time gradually decreased as the AV penetration rate increased. As can be seen in Figure 9a,b, full-autonomy traffic achieved an improvement in average speed of 1.19 times and an improvement in delay time of 1.76 times compared with the 10% AV penetration rate. The energy efficiency, fuel consumption, and emissions slightly decreased as the AV penetration rate increased. As shown in Figure 9c,d, full-autonomy traffic achieved an improvement in fuel consumption of 1.05 times and an improvement in emissions of 1.22 times compared with the 10% AV penetration rate. Thus, leading autonomous vehicles are more effective in terms of mobility and energy efficiency when the AV penetration rate increases.
## 6 Architecture Measurements
### Network Measurements  
In order to check the performance of the developed architecture, the behavior of the nodes in the initialization phase has been measured for 10 minutes. It allows us to see how the network performs when the nodes join in. It gives us the amount of control traffic introduced by our architecture. The following graphs are the most representative measurements obtained over multiple experiments. We have performed several times the same topology obtaining very close results (we think that their difference is given because of the operative system response or due to electronic issues).  
It can be observed that when all these nodes started sequentially, only 4 groups were created and the CHs were nodes 1, 3, 7 and 9. The number of broadcasts sent by the nodes when the network is setting up is shown in Figure 17. There are broadcast peaks due to new joining nodes in the first 160 seconds, but the highest peaks had eight broadcasts. There are no more than two broadcasts per second when the network is stabilized. So it demonstrates that there is low bandwidth consumption and little energy is wasted because there are few broadcasts.  
Figure 18 shows the number of bytes/s in the network. At the beginning there are many peaks because of keepalive messages and joining nodes in the initial process. When the network has converged, there are peaks approximately every 60 seconds because of keepalive messages, but the number of bytes/s is very similar. It demonstrates that little additional traffic will be introduced when the topology changes. On the other hand, there is a mean value of 1,482.5 Bytes per second, with a maximum value of 9,823 bytes per second and a minimum value of zero.  
Figure 16: Nodes distribution and the connections established.  
Taking into account that the test bench was performed in an IEEE 802.11g Wireless LAN with 54 Mbps (16 nodes in 200 \(\times\) 200 meters), we can state that, when our protocol is running, the limitation of number of devices in the network will be given by the overheads and timing constraints from all other network layers, not by our protocol.  
It can be seen that there are more packets per second in the architecture when there are more clusters in the network (between 140 and 160 seconds can be seen in Figure 19). It is because new CMs request neighbor CMs of other clusters. Once the network has converged, there are not so much variations. The mean value has been 17.41 packets per second. We obtained a maximum value of 101 packets per second.  
Figure 17: Number of broadcasts per second.  
Figure 18: Number of bytes per second.
## 3 Results  
### DisA Is a Diadenylate Cyclase in C. glutamic  
We first sought to identify genes putatively involved in c-di-AMP metabolism in _C. glutamicum_. Whereas homologs to known diadenylate cyclase (DAC) genes, such as _cdaA_ or _cdaS_, were not detected, genome analysis revealed a single gene containing the DAC domain, _cg2951_, encoded in an operon together with the DNA-damage-related gene _radA_[63; 64; 65]. It encodes a 366 amino acid DisA homolog with 41% identity to the well characterized DisA diadenylate cyclase from _B. subtilis_. The gene was thus designated _disA_ and was cloned into the _E. coli_ expression vector pBAD33, also introducing a C-terminal Strep-tag to the protein. The c-di-AMP-negative [7] host _E. coli_ DH5\(\alpha\) was transformed with the plasmid pBAD33_disA-strep_, as well as with the empty vector, and the resulting strains were cultivated in 2 xTY medium in presence of the inducer arabinose. The cells were harvested after 8 h; cell-free extracts were prepared and analyzed for adenosine nucleotide derivatives via HPLC. As shown in Figure 1a, a peak corresponding to pure c-di-AMP was observed in the cell-free extract of the strain-expressing _disA-strep_, which was absent in the cell-free extract of the strain carrying the empty vector. In a second approach, DisA-Strep was first produced in _E. coli_, enriched via Strep affinity chromatography from cell-free extract and the protein was then incubated with ATP at 30 \({}^{\circ}\)C, and the reaction product was analyzed via HPLC. Figure 1b shows the production of c-di-AMP by the Strep-affinity column enriched DisA-Strep from ATP, where after 15 min the substrate was nearly completely converted to c-di-AMP. We thus concluded that _cg2951/disA_ indeed encodes a functional DAC of the DisA-family in _C. glutamicum_. We applied two different established deletion protocols based on homologous recombination and CRISPR [52; 66] with selection on complex and minimal medium but were unable to obtain a viable _disA_ knockout strain. Although we were not able to detect the c-di-AMP in cell-free extracts of _C. glutamicum_ via HPLC (see below, Figure 2d), this suggests that c-di-AMP might be present at rather low concentrations but still be an essential second messenger in _C. glutamicum_, at least under standard conditions. As no other DAC was predicted from the genome sequence, we thus speculate that _disA_ encodes the sole and essential DAC in _C. glutamicum_.
## 3 WADGPS Architecture  
The WADGPS is a network composed of several Reference Stations (RSs) and a Master Station (MS). The RSs are distributed geographically at the precisely known locations that receive GPS L1-L2 dual-frequency signals and archive the raw observations from the monitored GPS satellites. The GPS L1-L2 dual-frequency measurements collected at each RS are sent to the MS. The MS data collector receives GPS raw measurements from each RS and updates the previous measurements in real time. Moreover, the statuses of GPS signals for all monitored satellites are checked including the rationalities of the code and carrier phase measurement at L1 and L2 frequencies, Signal-to-Noise Ratios (SNR), and Doppler frequency. The raw GPS observations are subsequently processed to reduce local errors by the carrier smoothing method [11]. The WADGPS MS then uses these smoothed measurements to generate vector corrections for the ionospheric delay, and the satellites ephemeris and clock errors [3]. In addition to these vector corrections, the messages generated by the MS also include the confidence bounds of these corrections. These messages are packed into the SBAS message format [8] and then transmitted to users _via_ Internet according to the appropriate scheduling time. The WADGPS MS implemented in this paper includes a monitor and control graphic user interface (GUI) to show the real time statuses of all RSs and MS processes. Figure 3 shows a diagram that summarizes the overall WADGPS system architecture and data processes.  
Figure 3: The WADGPS architecture.
# Satellite Remote Sensing of Surface Urban Heat Islands: Progress, Challenges, and Perspectives
## 6 Research Challenges
### Methodological Problems and Recommendation  
Uncertainties associated with the previously mentioned challenges have been further exacerbated by the methods widely used in the currently available SUHI publications [43]. The major issue is the analysis of limited data. For example, approximately 64% of the publications used a single-time-point data to represent the SUHI effect in a season or year. These publications focused on local-scale variability of SUHI based on Landsat and/or ASTER data. The fact is that the LST/SUHI values vary constantly and substantially by time due to changing climate/weather conditions, vegetation activities, and human activities [53; 119]. Using a single or a limited number of LST images may be misleading especially for those studies concentrating on the temporal changes of SUHI. In addition, some studies retrieved the LST from the top-of-atmosphere radiances by employing only the emissivity correction [91; 93; 133; 243; 244]. As stressed in Section 6.1, both atmospheric and emissivity corrections are key for an accurate estimation of LST. Given the free availability of long-term archived data, the use of a large number of images or a time-series-analysis is greatly recommended in future studies [215; 245]. In addition, reviewers of scientific manuscripts should ensure that these studies use sufficient data and perform the necessary atmospheric corrections for the interpretations made.
# Vehicle-in-the-Loop in Global Coordinates for Advanced Driver Assistance System
## 1 Introduction
At the same time, the risk of collision with external objects that may occur during testing can be eliminated. [PERSON] proposed a hardware configuration that links augmented reality to existing vehicle simulators [15; 16]. [PERSON] has shown that it can be applied in the development of active safety lights to conduct tests in the daytime [17]. VIL is used for driver reaction of critical situations [18; 19; 20; 21]. Figure 1: MIL vs. SIL vs. HIL vs. VIL vs. Test Drive. Additionally, [PERSON] and [PERSON] suggested VIL with a head-mounted display (HMD) device for the parking assistance system. [22; 23]. [PERSON] validated a speed advisory system via VIL [6; 24]. [PERSON] developed a VIL program for simulation of intersection controller [25; 26]. [PERSON] and [PERSON] showed a VIL simulation environment that validates ADAS controllers with virtually preceding vehicles [27; 28]. [PERSON] used VIL as a traffic controller simulator and [PERSON] suggested a VIL with the control center and connectivity [29; 30]. Previous studies have suggested the composition and application of VIL. However, the working algorithm of VIL for ADAS simulation was not published and only showed the environment in which the study was conducted. The studies in [17; 18; 19; 20; 21; 21; 31] use VIRES's Virtual Test Drive (VTD) without revealing the algorithm. [22; 23] and [28] also constructed their VIL system with commercial simulation tools, CarMaker and CarSim. [6; 24; 27; 29] verified their target system based on SUMO as an opensource tool, but this tool does not cover ADAS with buildings, pedestrians and road lines as targets. VIL in the research [25; 26] seems to have its own tools, however, the VIL is programmed for intersection controller simulation and provides only limited information, not available to the ADAS controller. There is no research suggesting an effective development algorithm for VIL. In this paper, we propose a VIL topology that can be developed and modified independently by separating each module. Although the ADAS controller is considered a vehicle-based local coordinates system, the VIL has been developed as a global coordinates system for connectivity with virtual environments. In Section 2, we present the basic structure of VIL and the essential parameters of each module. In Section 3, we compare the method of integrating each module and the similarity test between the actual ADAS vehicle and VIL to confirm whether the proposed system meets the VIL purpose. Finally, Section 4 describes the module variability of the proposed VIL system.
# Performance Analysis of Maximal Risk Evaluation Formulas for Spectrum-Based Fault Localization
## 2 Background
### Risk Evaluation Formulas
or simply \"maximal formulas\", if it is clear from the context. Following the definition in [14], a formula \(R_{1}\) is said to be a maximal formula in a set \(S\) of formulas, if for any formula \(R_{2}\in S\), \(R_{2}\) is better than \(R_{1}\) implies \(R_{2}\) is equivalent to \(R_{1}\) because no other formulas can outperform a maximal formula. The theoretical analysis in [11; 14; 15] shows that among 30 risk evaluation formulas, there are five maximal formulas with the assumption that only one fault is in the program. Moreover, these five formulas can be grouped into two groups in which all formulas in the same group have the same performance. These two maximal groups are \(ER1\) and \(ER_{5}\). Formulas in \(ER1\) are Naish1 (abbreviated as N1) and Naish2, both are from [13], whereas formulas in \(ER_{5}\) are Wong1 (abbreviated as W1) from [9], Russel & Rao from [28], and Binary from [13]. In the follow-up work [16; 17], the researchers proposed to use genetic programming (GP) techniques to come up with 30 GP-evolved risk evaluation formulas. Among these 30 GP-evolved formulas, they further identified four more maximal formulas; namely, GP02, GP03, GP13, and GP19 [27]. Moreover, GP13 was proven to be equivalent to those maximal formulas in the \(ER1\) group [16]. As a result, the \(ER1\) group is now denoted as \(ER_{1}^{{}^{\prime}}\), which also includes GP13. The other three GP-evolved formulas form three new groups of maximal formulas. In summary, among 60 risk evaluation formulas, there are nine maximal formulas which can be grouped into five maximal formula groups. All five maximal formula groups are listed in Table 1.  
Since no other formulas can outperform the formulas in these five maximal risk evaluation formula groups, it is intuitively appealing to do more research work on comparing the performance across these five maximal formula groups. Furthermore, [PERSON] et al. [18] showed that there never exists a greatest formula outperforming all other formulas.
## 2 Methods
### Data Collection  
The physical performance data were collected using the Titan 2 GNSS device (Integrated Bionics Inc., Houston, TX, USA), operating at a sampling frequency of 10 Hz. The validity and between-unit reliability of comparable GNSS systems have been established in the literature [28], supporting their appropriateness for monitoring distance, peak speed, and high-intensity actions in team sports.  
To enhance the reliability of data acquisition, each player consistently wore the same GNSS unit across all matches to minimize inter-unit variability. All devices were activated simultaneously by the research team exactly 15 min prior to kick-off, ensuring consistent satellite acquisition and stable signal reception. Devices were placed between the scapulae in specially designed vests, in accordance with best practice recommendations.  
Raw data were manually checked after each match for signal dropout, artifacts, or missing values. Only complete and valid recordings were included in the analysis. No imputation or correction of missing data was applied.  
The external load of the football players during the team's official matches over the course of one year was recorded using the above GNSS system. Only the matches in which the team played the entire 90 min in a 1-4-2-3-1 formation were included in the analysis.  
The external load variables used were total distance, distance per speed zone, and the frequency of accelerations and decelerations. The distance covered by the football players was divided according to their movement speed into Zone 1 (3.6-10.8 km/h), Zone 2 (10.9-18.0 km/h), Zone 3 (18.1-25.19 km/h), and Zone 4 (\(\geq\)25.2 km/h). For accelerations (ACC) and decelerations (DEC), only those exceeding 2 m/s\({}^{2}\) were taken into account.
# Spectrum Slicing for Multiple Access Channels with Heterogeneous Services
###### Abstract
In contrast, when the intermittent users aim to optimize the packet latency, the slicing mechanism must be carefully selected based on the access load and the number of users, as there is no single slicing method that provides the best trade-offs. In summary, the main contributions of this paper are the following:  
* We analyze the trade-offs and regions of operation of OMA and NOMA schemes with a broadband and multiple intermittent users in a collision channel with erasures. * We investigate the impact of the metrics of interest on the overall system design and on the achievable gains with OMA and NOMA. * We investigate the impact of the activation probability of intermittent users on the performance of the slicing mechanism. * We derive Pareto frontiers, which define the best possible trade-offs between throughput of the broadband user and latency/AoI of the intermittent users with the considered schemes. Figure 1: Toy example for for a case where the broadband user implements a 4-out-of-6 erasure code. No channel erasures are considered in this example. Collisions among intermittent users cannot be recovered, but SIC can be used to recover collisions between the broadband and intermittent users after decoding the broadband user. The rest of the paper is organized as follows. Section 2 presents the literature review. The system model is described in Section 3. The analyses for OMA and NOMA schemes are presented in Sections 4 and 5, respectively. The results are presented in Section 6. Section 7 concludes the paper.