esa-sceva/satcom-chunk-collection huggingface dataset:
# Task Migration with Partitioning for Load Balancing in Collaborative Edge Computing
###### Abstract  
Multi-access edge computing (MEC) has emerged as a promising technology to facilitate efficient vehicular applications, such as autonomous driving, path planning and navigation. By offloading tasks from vehicles to MEC servers (MECSs), the MEC system can facilitate computation-intensive applications with hard latency constraints in vehicles with limited computing resources. However, owing to the mobility of vehicles, the vehicles are not evenly distributed across the MEC system. Therefore, some MECSs are heavily congested, whereas others are lightly loaded. If a task is offloaded to a congested MECS, it can be blocked or have high latency. Moreover, service interruption would occur because of the high mobility and limited coverage of the MECS. In this paper, we assume that the task can be divided into a set of subtasks and computed by multiple MECSs in parallel. Therefore, we propose a method of task migration with partitioning. To balance loads, the MEC system migrates the set of subtasks of tasks in an overloaded MECS to one or more underloaded MECSs according to the load difference. Simulations have indicated that, compared with conventional methods, the proposed method can increase the satisfaction of quality-of-service requirements, such as low latency, service reliability, and MEC system throughput by optimizing load balancing and task partitioning.  
multi-access edge computing; task migration; task partitioning; load balancing Article
# On Construction of a Campus Outdoor Air and Water Quality Monitoring System Using LoRaWAN
## 3 System Design and Implementation
### Sensor Deployment
#### 3.5.2 Water Monitoring Sensor and LoRa Deployment  
The terminal sensors are integrated and log data by a lab-made PCB board with RENESAS RX64M MCU, using LoRa to transmit the data. The MCU of Renesas RX64M [39] with 170 Pins and 128 I/O Ports is capable of operating at up to 120 MHz and allows for high-speed and low power consumption. The RX64M Group is suitable for network devices, industrial equipment, and other applications that require large-capacity memory, real-time performance, and harsh environments.  
According to the development process, we used Renesas chips and constructed and simulated the necessary circuits with ADS (Advanced Design System) software based on the circuit principle. After several integrated tests of interface matching, we achieved success, and then used Altium Designer (PCB Design Software) to draw the PCB Layout diagram shown in Figure 8a. We then constructed it as a real system as shown in Figures 8b and 9a.  
Modbus [40] is widely used in industrial settings because it is simple to implement and maintain compared to other standards and has minimal constraints. Modbus allows several devices to be connected to the same cable to communicate with each other. A gadget that measures temperature and another that monitors humidity, for example, might be linked to the same cable and transmit measurements to the same computer, just like the water sensor we employed in this paper, as shown in Figure 9b.  
This system collects four parameters: pH, DO Conductivity, and Temperature. The data are broadcast to the network using MQTT. The message is then captured by the MQTT client and saved to the database. We used a mini ship to collect the water parameters from the lake. Figure 10 illustrates the mini ship used in our experiments.  
The data were transmitted with LoRa and broadcasted using an MQTT gateway, as shown in Figure 11. In comparison to the Wi-Fi transmission system, the cost is much lower [41]. Furthermore, the stable remote transmission prevents data loss and allows for more reliable recording and analysis of the data collected. As a result, LoRa is the transmission technology of choice for the majority of people.  
Figure 8: PCB model: (**a**) The PCB Layout Figure of repaid rapid monitoring station; (**b**) Complete diagram of all-component welding.
# Enhanced Phosphorus Removal from Wastewater Using RSPRC and a Novel Reactor
## 3 Results and Discussion  
### Effect of Proportion of Activated Clay in RSPRC on Decolorization and Phosphorus Removal  
The experimental results reveal that the decolorization rate was only 46.7% without the addition of activated clay in RSPRC; following the addition of activated clay, a significant increase in the decolorization rate of the wastewater was recorded. When the proportion of activated clay was 15%, the decolorization rate was as high as 70.8%. This indicates that the adsorbent RSPRC is equipped with a better decolorization performance because of the addition of activated clay. The experimental results of exploring the phosphorus removal performance of activated clay are given in Figure 4. The phosphorus removal rate was 75.20% when the proportion of activated clay in group 3 was 15%. On the other hand, the phosphorus removal rate of the adsorbent containing no activated clay in group 4 was merely 68.74% at 180 min. The results show that there is a clear trend of an increasing phosphorus removal rate with the addition of activated clay. For instance, the phosphorus removal rate of the adsorbent with 15% increased by 6.46%. It is apparent that the addition of activated clay can effectively improve the phosphorus removal performance of the adsorbent. This result may be explained by the fact that the activated clay was obtained by rinsing and drying bentonite after it was activated by inorganic acid, and that its main composition is montmorillonite, which has a high specific surface area [21]. During the acid activation treatment, [PERSON] et al. found that Na\({}^{+}\), Mg\({}^{2+}\), K\({}^{+}\), Ca\({}^{2+}\) and other cations between the bentonite layers can be converted into soluble salts and dissolved  
Figure 3: Adsorbent distribution of four experimental conditions (**a–d**).  
out, increasing the layer spacing, and forming a porous active substance with a microporous mesh structure and a large specific surface area. Additionally, the impurities distributed in the bentonite structure channels can also be removed. The pore volume was increased, which is beneficial to the diffusion of adsorbate molecules [17].  
Although the phosphorus removal performance of the adsorbent was improved with the increase in the proportion of activated clay in the substrate, the improvement was not obvious enough. Taking into account economic factors, the basic ratio of adsorbent materials was fly ash:steel slag:activated clay:cement = 14:2:3:1 in the subsequent experiments.
# Improving a Process-Based Model to Simulate Forest Carbon Allocation under Varied Stand Density
###### Abstract  
Carbon allocation is an important mechanism through which plants respond to environmental changes. To enhance our understanding of maximizing carbon uptake by controlling planting densities, the carbon allocation module of a process-based model, TRIPLEX-Management, was modified and improved by introducing light, soil water, and soil nitrogen availability factors to quantify the allocation coefficients for different plant organs. The modified TRIPLEX-Management model simulation results were verified against observations from northern Jiangsu Province, China, and then the model was used to simulate dynamic changes in forest carbon under six density scenarios (200, 400, 600, 800, 1000, and 1200 stems ha\({}^{-1}\)). The mean absolute errors between the predicted and observed variables of the mean diameter at breast height, mean height, and estimated above-ground biomass ranged from 15.0% to 26.6%, and were lower compared with the original model simulated results, which ranged from 24.4% to 60.5%. The normalized root mean square errors ranged from 0.2 to 0.3, and were lower compared with the original model simulated results, which ranged from 0.3 to 0.6. The Willmott index between the predicted and observed variables also varied from 0.5 to 0.8, indicating that the modified TRIPLEX-Management model could accurately simulate the dynamic changes in poplar (_Populas_ spp.) plantations with different densities in northern Jiangsu Province. The density scenario results showed that the leaf and fine root allocation coefficients decreased with the increase in stand density, while the stem allocation increased. Overall, our study showed that the optimum stand density (approximately 400 stems ha\({}^{-1}\)) could reach the highest aboveground biomass for poplar stands and soil organic carbon storage, leading to higher ecological functions related to carbon sequestration without sacrificing wood production in an economical way in northern Jiangsu Province. Therefore, reasonable density control with different soil and climate conditions should be recommended to maximize carbon sequestration.  
plating density; simulation model; carbon dynamics; above-ground biomass +
Footnote †: journal: Physics Letters
# Brief Review of Recent Developments in Fiber Lasers
## 4 Raman Fiber Lasers
### Brightness Enhancement in Raman Fiber Lasers  
In cladding-pumped RE-doped fiber lasers, the low-brightness pump light is coupled into the fiber cladding while the laser signal undergoes amplification in a fiber core, which supports only low-order modes with superior brightness relative to the pump. Brightness enhancement in the system can be estimated as follows:  
\[BE=B_{L}/B_{P} \tag{16}\]  
where \(B_{L}\) and \(B_{P}\) are the laser output brightness and the pump input brightness, respectively. Like RE-doped fiber lasers, Raman fiber lasers can provide brightness enhancement too. For example, one can use the same cladding-pumped approach (usually based on double cladding) to achieve brightness enhancement in Raman lasers.  
Another way to achieve brightness enhancement in Raman fiber lasers consists of utilizing multimode graded-index (MM-GRIN) fibers. As in the case of the cladding-pumped approach, in the MM-GRIN approach, the Stokes laser signal is generated in the high-brightness core, while the pump propagates through a larger diameter of the fiber cladding. The first Raman fiber laser based on MM-GRIN fibers was demonstrated in 2018 [84]. A total of 135 W of the output power was obtained with 68% efficiency relative to launched pump power. Its brightness enhancement was \(BE\approx 5.6\).  
Much progress has been made in the last few years in both of these techniques. In 2018, the highest brightness enhancement \(BE\approx 7\) for the cladding-pumped configuration was demonstrated at a record Raman fiber laser power of 1.2 kW with 85% efficiency relative to launched pump power [85]. At such high (over kW) output power levels, the beam quality \(M^{2}\approx 2.75\) was obtained.  
In 2019, a Raman fiber laser power of 1002.3 W at 1060 nm with 84% efficiency was demonstrated using the MM-GRIN configuration [86]. The brightness enhancement was about 2.57 at the maximum output power. The beam quality was \(M^{2}\approx 5\).
# Enhancing Reactive Ad Hoc Routing Protocols with Trust
## 2 Background  
### Related Work  
Methods to enhance ad hoc routing protocols with trust can be divided into two groups. The first represents approaches that apply trust during the route discovery phase. Either the control messages are rejected based on the trust, or they contain a special field in the header that collects the trust value of the path during the dissemination of the discovery message. Examples of such approaches are [PERSON] et al. [15], [PERSON] and [PERSON] [5], [PERSON] et al. [6], [PERSON] et al. [7], and [PERSON] et al. [10]. The second group represents approaches that select routes according to their trust values stored in routing tables. Examples are [PERSON] et al. [4], [PERSON] et al. [17], and [PERSON] et al. [3]. Our approach falls into the first group.
## 2 Experimental Methods and Simulations
### Simulation Methods
#### 2.2.3 Misorientation Angle  
The misorientation angle between two objects is defined as the smallest rotation angles among equivalent rotations relating two given orientations of the objects, which is generally used to characterize the rotation of the grains. For duplex titanium alloys, because the \(\alpha\) phase has a hexagonal lattice structure, it is necessary to convert the three-axis coordinate system (_hkil_)[_uvtw_] to the four-axis coordinate system (_HKL_) [_UVW_]:  
\[\begin{array}{l}crystal\ face\ index:(HKL)\rightarrow(hkil),and\left\{ \begin{array}{l}h=H\\ k=K\\ i=-(h+k)\\ l=L\end{array}\right.\\ \\ \text{crystal orientation index}:[UVW]\rightarrow[uvtw],and\left\{ \begin{array}{l}u=\frac{2U-V}{3}\\ v=\frac{2V-1}{3}\\ t=-(u+v)\\ w=W\end{array}\right.\\ \end{array} \tag{9}\]  
The misorientation matrix \(M\) is defined as:  
\[M=g_{1}g_{2}^{-1} \tag{10}\]  
where \(g_{1}\) is the orientation matrix before deformation and \(g_{2}\) is the orientation matrix after deformation. Furthermore, the real misorientation matrix \(M\)' is calculated by \(M\) and the symmetry operator \(T\):  
\[M^{\prime}=TM \tag{11}\]  
\begin{table}
\begin{tabular}{c c c c c} \hline
**Slip System** & **CRSS (GPA)** & \(\tau_{1}\) **(GPA)** & \(\theta_{0}\) **(GPA)** & \(\theta_{1}\) **(GPA)** \\ \hline \(\left\{0001\right\}<11\overline{2}0>\) & 0.36 & & & & \\ \hline \(\left\{10\overline{1}0\right\}<11\overline{2}0>\) & 0.38 & 0.13 & 0.115 & 0.0021 \\ \hline \(\left\{10\overline{1}1\right\}<11\overline{2}0>\) & 0.5 & & & & \\ \hline \(\left\{10\overline{1}1\right\}<11\overline{2}3>\) & 0.52 & & & & \\ \hline \(\left\{110\right\}<111>\) & 0.45 & & & & \\ \hline \(\left\{112\right\}<111>\) & 0.46 & 0.13 & 0.105 & 0.0016 \\ \hline \(\left\{123\right\}<111>\) & 0.47 & & & & \\ \hline \end{tabular}
\end{table}
Table 2: The critical resolved shear stress (CRSS) and hardening coefficient of slip systems [30].  
There are 12 symmetry operator matrices for the \(\alpha\) phase and 24 symmetry operator matrices for the \(\beta\) phase. Therefore, the \(M^{\prime}\) has a number of equivalent solutions and the smallest one was chosen in this study. Finally, the misorientation angle \(\theta\) was calculated:  
\[\cos\theta=(M^{\prime}_{11}+M^{\prime}_{22}+M^{\prime}_{33}-1)/2 \tag{13}\]  
For the misorientation angles between the \(\alpha\) and \(\beta\) phases, the (0001) plane of hexagonal crystal structure is parallel to the (011) plane of the cubic crystal structure and the \(\left[\overline{121}0\right]\) crystal direction of the hexagonal crystal structure is parallel to the \(\left[\overline{111}\right]\) crystal direction of the cubic crystal structure. As a result, the (0001) plane of the \(\alpha\) phase and the (011) plane of the \(\beta\) phase were determined in this study to calculate the misorientation angles.
## 1 Introduction  
The development towards increasingly larger and leaner buildings and the focus on resource-saving construction are placing new requirements on building materials. Long-span bridges or wind turbines not only require higher material strengths to carry the static loads but must also be able to resist the increasing demands of system-related vibrations. High performance (HPC) and ultra-high performance (UHPC) concretes have been developed for reinforced concrete construction to increase material efficiency. The stresses of the material require a comprehensive state of knowledge of the fatigue behavior of the material. This has already been investigated by various researchers [1; 2; 3; 4; 5; 6; 7; 8; 9]. When determining fatigue strengths and creating Wohler curves, for example, tests according to [10] are recommended in Germany. A large number of required load changes can be achieved with high frequencies so that the attempts do not take too long. In previous investigations of UHPC and HPC samples, the warming up of the specimens was measured [11; 12; 13; 14; 15; 16]. For normal concrete, however,no heating has been measured so far, which is the reason why the effect has not yet been studied in such detail. Normal concrete is generally less well packed and has significantly more pores inside due to the higher water-cement ratio. As a result, the internal friction potential under a pressure-swelling load is significantly lower. This internal friction between binder and aggregate is assumed to be the reason for the heating. A summary of the state of knowledge for the heating phenomenon is given in [17] as a basis for the investigations. This article deals with this effect related to UHPC. The hypothesis is that the additional specimen heating has a significant influence on the fatigue strength of high performance concretes. An influence on the fatigue strength during the tests would lead to a frequency-dependent reduction in the possible number of load cycles of the concretes if standard values were to be created. Furthermore, it will be interesting in the future which frequencies become relevant in praxis and whether the effect is then not only a test-related influence, but can even become decisive for the application.  
The aim was to conduct a parameter study to find out what causes the temperature increase. In further steps the influence on the fatigue strength was to be determined. For this purpose, tests were carried out in which the load-related parameters frequency and related maximum stress level were varied. In addition, two concretes with different mixtures and similar compressive strength were used to determine the influence of aggregates of different sizes.
###### Abstract  
Southern Thailand suffers from floods due to heavy rainfalls every year. Post-flood increases in indoor fungi are a public health concern. Here, we investigated fungal assemblages on indoor surfaces with visible mold growth in homes after the 2016 flood disaster in Trang Province in Southern Thailand, using swab sampling followed by high-throughput DNA sequencing of the fungal internal transcribed spacer 1 region. The most abundant phyla detected were Ascomycota and Basidiomycota, with respective mean relative abundances of 87% and 13%. The dominant genera and their mean relative abundances were _Leptospora_ (12.0%), _Cystobasidium_ (7.7%), and _Pyrenochaetopsis_ (6.5%). P-tests showed that indoor visible fungal assemblages in flooded homes in Thailand were significantly different from those in the non-flooded mold-laden homes observed in our previous study in South Korea. We detected 20 genera that contain species that can induce type I allergies, including _Alternaria_ (3.8%) and _Trichoderma_ (4.0%). Genera related to infectious, melanized, and toxigenic fungi were also detected. Indoor fungal measurements gathered using a DNA-based approach revealed fungal communities in homes in Thailand and provide important information about the potential health risks. Future research should examine the fungal infections and allergies that might be caused by flood disasters in less well studied tropical countries.  
DNA metabarcoding; high-throughput sequencing; mycobiome; dampness; mold 2020; 10, 5322; doi:10.3390/app10155322
## 4 Simulation and Analysis of the DLLFP
### Dispersion Curves at Different Frequency-Thickness Products  
Figure 6 shows the dispersion curves of phase velocity versus frequency-thickness product for different guided wave modes in the acoustic-structural coupling domain. With parametric scanning, the excitation frequency \(f_{0}\) is scanned from 10 Hz to \(f_{\mathrm{max}}\) = 25 kHz with a scan step set to 249.9 Hz, and the wall thickness of Layer 1 is scanned from 2 mm to 3.5 mm, with a scan step set to 0.15 mm and the scan type set to the specified combination. The mode analysis frequency is given as \(f_{0}\) = 10,000 Hz for the interior of the pipe, the mode search method is set to the manual search method, the APPACK solver is selected as the mode solver, and the mode search base \(k_{0}\) = 2\(\pi\)\(f_{0}\)/c\({}_{0}\). Numerical simulation is solved with the MUMPS direct solver, the free triangular meshing technique is chosen to divide the mesh in the pressure acoustic domain, and the mapped distribution is chosen to divide the mesh in the solid mechanics domain, with 6638 cells in the whole geometric mesh. The \(x\)-axis is the frequency-thickness product _fd_ (Hz-m), and the \(y\)-axis is the phase velocity value \(c_{\mathrm{p}}\) (m/s). The black asterisk line indicates the dispersion curve obtained with the analytic calculation, and the red dot line indicates the dispersion curve obtained with the numerical simulation. The dispersion curve of the pipe in this case is calculated, where the wall thickness of Layer 2 is 3 mm and the pipe is filled with water.  
As Figure 6 shows, the number of propagating guided wave modes in the DLLFP grows with the frequency-thickness product, which implies an increase in interference during ultrasonic guided wave nondestructive fault detection. When the frequency-thickness product _fd_ = 0-18 Hz-m, the propagating guided wave in the DLLFP is dominated by the straight-through mode, and the phase velocity hardly varies with changes in the frequency-thickness product. When the frequency-thickness product _fd_ = 18-67 Hz-m, modes with a higher phase velocity of propagating guided waves start to appear. The different propagating guided wave modes start to intersect. In ultrasonic guided wave nondestructive testing, these intersections corresponding to the frequency-thickness product are to be avoided because the guided wave modes excited by the thickness product at this frequency have equal phase velocity, and the time domain display on the oscilloscope is the simultaneous arrival of echoes, which will cause serious interference to the nondestructive fault echo analysis. When the frequency-thickness product fd = 67-85 Hz-m, the phase velocity of the excited propagating guided waves tends to be the same and the number of propagating guided wave modes excited by the same frequency-thickness product is high, which is not conducive to ultrasonic guided wave nondestructive testing; thus, this frequency-thickness product excitation range should be avoided.
# Telecommunication Systems for Small Satellites Operating at High Frequencies: A Review
## 3 MarCO
### Operations  
MarCO was launched on May 2018 [5] from the Vandenberg Air Force Base near Lompoc, California. MarCO was deployed after InSight and DSN received the first telemetry from MarCO A at approximately 5.55 am, while data from MarCO-B were received shortly after at 6:05 am [5]. During the first pass, commands were issued to deploy both the X-Band high gain antenna and the UHF loop antenna.  
During cruise, uplink functionalities were used to load new command sequences from the ground when desired. In downlink, both spacecraft transmitted mostly health and status data and occasionally pictured taken with the cameras. Navigation was performed using both ranging and Delta-DOR modes. Still during cruise, three main additional activities were performed:  
1. The gain of the HGA reflectarray antennas were characterized on both spacecraft by pointing the antenna to different attitudes and measuring the received power on the ground
2. The bent-pipe EDL mode was tested using the UHF Stanford ground station that simulated the InSight spacecraft and sent signals to both MarCo spacecraft. Both MarCO spacecraft successfully retransmitted the signal to the Deep Space Network
3. Both MarCo spacecraft were also received by the Morehead State University ground station, the same as ASTERIA that for the occasion was upgraded with X-Band receiving capabilities.  
Once arrived at Mars, both spacecraft successfully supported the EDL of the InSight mission by recording and retransmitting over 600 KB of data (MarCO-A transmitted 694 KB and MarCO-B transmitted 712 KB). This data volume is significant and it is higher than what is conventionally done using Mars relay orbiter assets such as MRO for the same EDL phase [5].  
After the EDL phase, both spacecraft completed the flyby of Mars and continued their journey in the solar system transmitting pictures back to Earth until contact was lost (with MarCO-B on 29 December 2018 and with MarCO-A on 4 January 2019) [5].  
Figure 8: UHF loop antenna [8].