esa-sceva/satcom-chunk-collection huggingface dataset:
# Principles and Methods of Servomotor Control: Comparative Analysis and Applications
## 3 Basic Principles of Servomotor Control
### Digital Signal Processing in Servomotors  
Digital signal processing has allowed for the optimization of servomotor control, expanding boundaries in control methods and opening up new possibilities. Digital signal processing enables the limitations of analog control systems to be bypassed, thus laying a new foundation for more effective servomotor management. Based on [59; 60; 61; 62], it is possible to identify the key aspects in the construction of this principle and draw conclusions about its advantages and disadvantages.  
Key points in digital signal processing for servomotor control include:  
1. Precision control. Digital signal processing allows the use of advanced control algorithms that enhance control accuracy. This is achieved as digital controllers can receive, process, and respond to changes in input signals in real time, skipping many stages in tuning the control action.
2. Adaptive control. Since servomotors operate in dynamic environments with changes in load and the occurrence of various errors, the principle of digital signal processing helps integrate adaptive control for servomotors. This type of control neutralizes  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Characteristic** & **Value** \\ \hline Torque & 2.4 Nm \\ Input (operating) voltage & 116 V AC \\ Rotational speed & 3000 r/min \\ Output power & 0.75 kW \\ \hline \hline \end{tabular}
\end{table}
Table 1: The main technical characteristics of the Hirata Cartesian robot servomotor [47; 58].  
disturbing influences in real time and adjusts control depending on new conditions, thus improving the performance and efficiency of servomotors.
3. Noise filtering. In real production environments, servomotors are subject to interference and noise from other devices, production line structures, additional loads, etc. The principle of digital signal processing allows the identification and neutralization of noise to maintain the accuracy of the control signal at the required level.
4. Network interaction and communication. The communication of servomotors within a unified system is facilitated by the principle of digital signal processing. Coordinating actions, adjusting control, and other networking capabilities enable synchronized control of servomotors in complex manufacturing processes, such as robotic technological lines.  
However, along with the merits of digital signal processing, there are some drawbacks to this principle:  
1. Computational power. Implementing digital signal processing algorithms requires significant computational resources. To ensure real-time signal processing, it is necessary to accurately calculate the processing time and controller signal responses to fully realize the potential of the entire control system.
2. Integration with existing control systems. Integrating control based on digital signal processing with other systems may pose challenges due to compatibility issues and the need for proper design of the control interface.
# Sustainable Approach of Generating Water and Energy:
## 4 Results and Discussion
Almost all energy required in a residential building in Saudi Arabia comes from nonrenewable sources. In addition, most of desalinated water for residents in the Riyadh region is transported from Jubail and Ras Al-Khair plants [36], which are 500 km away. The environmental and energy cost for such transportation is high. It was reported by  
Figure 10: Monthly power generation of PVT, load demand, and exported and imported grid power to the house, and overall energy saving. Figure 9: Annual auxiliary heating as function of number of panels and mass flow rate. other researchers that the energy required to transport 1 m\({}^{3}\) of desalinated water from the nearest desalination plant is 14 kWh/m\({}^{3}\), which is equivalent to 5 kg CO\({}_{2}\)/m\({}^{3}\)[36]. Thus, decentralized water is imperative. Figure 12 shows the results of the optimized system. The annual CO\({}_{2}\) saving for a single residential building is 4300 kg as a result of decentralized water and energy. Figure 11: The SCW at different number of panels connected in series. Figure 12: Environmental analysis and monthly water production. The capital and investment costs of the proposed system have a significant impact on the SCW. The impact of the PVT system's capital cost and the cost of auxiliary heating on the SCW was investigated using a sensitivity analysis, as shown in Figure 13. As mentioned previously, auxiliary heating is used to ensure the hot feed water to the DCMD unit to not fall below 70 \({}^{\circ}\)C. It is clear from Figure 13 that the SCW is proportional to both PVT capital price and the auxiliary heating cost. It is worth noting that the average price for the PVT is 1800 $/kW. With current market price, the SCW for the proposed system is 23.6 $/m\({}^{3}\). In addition, previous studies show that the cost of desalinated water (SCW) varies from 15 to 18.34 Figure 7:0/m\({}^{3}\).
# Changes in the Cell Division of Chang Liver Cells Induced by Simulated Microgravity
###### Abstract  
Background: Simulated microgravity (SMG) has not been well characterized in terms of its impact on cell division structures. This research aimed to assess the changes in cell division in Chang liver cells (CCL-13 cells) under SMG conditions. Methods: CCL-13 cells were exposed to SMG conditions via a 3D clinostat for 72 h. The cells from the control group were kept under the same conditions, without exposure to SMG. The changes in cell division were assessed via cell cycle progression analysis, the transcript expression of the genes associated with the cell cycle, and the appearance of the contractile ring, microvilli, and spindle in CCL-13 cells. Results: The CCL-13 cells from both the control group and the SMG group exhibited a typical epithelial-like shape. The CCL-13 cells of both groups displayed normal nuclear morphologies and were devoid of fragmentation and condensation, which are signs of apoptosis. There were changes in the cell cycle of CCL-13 cells in the SMG condition, which were shown via an increase in the cell percentage in the G0/G1 phase and a decrease in the S phase and G2/M phase. The cell area of the SMG-exposed CCI-13 cells increased, while their nuclear area decreased, which led to a reduction in the nuclear/cytoplasmic ratio. Moreover, the transcript expression of cyclin b1, cyclin d1, cdk2, and cdk6 was downregulated in CCL-13 cells under SMG conditions compared to the control group. Interestingly, SMG-exposed CCL-13 cells exhibited a decreased appearance of microvilli, changes in the formation of the contractile ring, and polar spindle microtubules during cytokinesis. Conclusions: SMG attenuated the cell division of CCL-13 cells by driving cells into the arrest phase and altering the cell division structures.  
Chang liver cells; cell division; mitosis; simulated microgravity 2023
## 1 Introduction
This method utilized a vertical continuous flow reactor in distilled water at temperatures of 300-350 \({}^{\circ}\)C and pressures of 10-15 MPa. The method was sensitive to the particle size of the aluminum powder [33], with larger particles used in the experimental plant up to 40 \(\upmu\)m [34]. A key drawback was that tiny aluminum particles could clog valves and pipes, posing technical and safety challenges under high-pressure and high-temperature conditions. Coarse aluminum could offer a cost-effective alternative to aluminum powders, given that fine aluminum powders can be considerably more expensive than aluminum ingots, depending on the powder dispersion. A recent study demonstrated the feasibility of completely oxidizing aluminum granules of about 1 cm in size [35]. However, this study suggested that the oxidation process might be affected by the state of the water (liquid or steam). In the present study, we aim to examine this assumption by conducting a series of oxidation experiments on aluminum granules in a 5 L autoclave reactor. We also examine the influence of aluminum's chemical purity on the hydrothermal oxidation process, a topic not previously explored. Additionally, this investigation examines the impact of aluminum's chemical purity on the process of hydrothermal oxidation, a topic that has not previously been extensively explored. This research focus is based on previous findings indicating that the chemical composition of both aluminum and water significantly influences the oxidation process. While this research delves into the study of aluminum oxidation in both liquid water and steam within the same experimental setup, it also investigates a more cost-effectiveapproach using coarse aluminum. The study offers a comprehensive examination of aluminum hydrothermal oxidation, exploring parameters such as aluminum granule size and oxidation rates in different states of water. Furthermore, this research seeks to address challenges related to the use of fine aluminum powder in oxidation processes. The tendency of fine aluminum particles to clog valves and pipes presents significant safety and operational concerns in high-pressure and high-temperature environments. By comparing the conversion degrees from these experiments, this study strives to obtain deeper insights into the role of aluminum purity and water state in aluminum hydrothermal oxidation. The ultimate goal is to enhance our understanding of efficient hydrogen production using sustainable methods, contributing to the larger scientific discourse on low-carbon energy strategies. Our findings have the potential to drive advancements in the hydrogen production sector, facilitating more eco-friendly and efficient processes that align with the goals of sustainable energy development.
## 3 Results
### Effect of Rock-Bolt Length
#### 3.1.2 Effect of Grout Properties and Thickness  
Based on the grout-material types, fully grouted bolts are divided into two sets, i.e., resin-grouted and cement-grouted bolts. The mechanical properties of resin are comparatively high [42]. The resin-grouted bolts are more rigid than the cement-grouted ones [43]; however, poor resin mixing and cartridge accumulation in bolted holes decrease their efficiency. The best resin mixing and bolt encapsulation occur in the bolt's middle region, whereas, at the bore-hole end, the cartridge accumulation causes anchorage problems [44]. This anchorage problem, which arises due to poor mixing, increases the reinforcement cost from 10%-30% [45]. Cementitious grout types, on the other hand, are made of a mixture of cement, water, and other substances that may reduce shrinkage, increase pump-ability, or improve the mechanical properties of the mixture. Mechanical properties of the grout govern the bolt capacity, which can be changed by altering the water-to-cement ratio, additives, proper mixing of grout components, and curing time [36]. The pull-out capacity of the cement-grouted bolts increases with the decrease in the water-cement ratio, and its optimum value is 0.34-0.4 in terms of pump-ability and resistance [35; 36]. The effect of the water-cement ratio was investigated in moderate rock masses for a 4 m length rock bolt, and the average test result is shown in Figure 6. For the purpose, pull-out tests were carried out on 25 mm diameter rock bolts for the water-cement ratio of 24% and 40%.  
Figure 5: Effect of rock-bolt diameter on pull-out load [36].  
Cement-grouted rock bolts have several limitations for immediate support applications, owing to settling time requirements. The load-carrying capacity of cement-grouted rock bolt for different curing times (12, 24, and 36 h) was tested, and results are shown in Figure 7. For the same diameter and water-cement ratio, the results of 18 pull-out tests for the two rock-mass classes and three curing times are shown.
# A Review of Pedestrian Indoor Positioning Systems for Mass Market Applications
## 2 Network Based Systems
### Range Based  
There are different ways for extracting geometric information from the wireless signals, the most common ones are the methods based on the propagation time of the signal, between the transmitter and the receiver, the Angle of Arrival (AoA) or the Received Signal Strength (RSS). In the following, we briefly detail the fundamentals of each class of methods analyzing its advantages and disadvantages.
# Operation State Evaluation of Miter Gate Based on On-Line Monitoring and Finite Element Analysis
## 4 Signal Analysis and Discussion
### Crack Signal Analysis
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Sensor**} & \multicolumn{4}{c}{**Crack Propagation Displacement Variation (mm)**} \\ \cline{2-6}  & & **First Time** & **Second Time** & **Third Time** & **Fourth Time** \\ \hline \multirow{3}{*}{Group1} & LY60 & **0.0750** & **0.1160** & **0.1240** & **0.0870** \\  & LY61 & 0.0560 & 0.0730 & 0.0420 & 0.0530 \\  & LY62 & 0.0240 & 0.0350 & 0.0250 & 0.0390 \\ \hline \multirow{3}{*}{Group2} & LY64 & **0.1050** & **0.1470** & **0.1640** & **0.1550** \\  & LY65 & 0.1030 & 0.1070 & 0.1060 & 0.1040 \\  & LY66 & 0.0210 & 0.0520 & 0.0340 & 0.0480 \\ \hline \multirow{3}{*}{Group3} & LY68 & **0.0400** & **0.0530** & **0.0370** & **0.0370** \\  & LY69 & 0.0340 & 0.0560 & 0.0390 & 0.0480 \\  & LY70 & 0.0650 & 0.0710 & 0.0490 & 0.0510 \\ \hline \multirow{3}{*}{Group4} & LY71 & **0.0830** & **0.0840** & **0.0750** & **0.0870** \\  & LY78 & 0.0420 & 0.0710 & 0.0450 & 0.0600 \\  & LY97 & 0.0600 & 0.0600 & 0.0270 & 0.0450 \\ \hline \multirow{3}{*}{Group5} & LY83 & **0.0410** & **0.0470** & **0.0410** & **0.0510** \\  & LY98 & 0.1370 & 0.2520 & 0.2270 & 0.2560 \\  & LY99 & 0.0820 & 0.1260 & 0.1040 & 0.1190 \\ \hline \multirow{3}{*}{Group6} & LY72 & **0.0960** & **0.2120** & **0.1710** & **0.1720** \\  & LY105 & 0.0710 & 0.0890 & 0.0750 & 0.0730 \\ \hline \multirow{3}{*}{Group7} & LY88 & **0.0860** & **0.1600** & **0.1340** & **0.1520** \\  & LY89 & 0.2060 & 0.3370 & 0.2970 & 0.3110 \\ \hline \hline \end{tabular} Note: The first sampling time is 5 July 2021, the second sampling time is 14 April 2022, the third sampling time is 5 May 2022, and the fourth sampling time is 4 July 2022.  
\end{table} 
Table 3: Crack propagation displacement variation of the miter gate at the different positions by four times of sampling (mm).
# Cancelable Multimodal Biometrics Based on Chaotic Maps
## 4 Experimentation Results
### Security Analysis  
The constant parameters used in the Torus Automorphism transformation matrix and the user-specific kernel play a critical role in obtaining an appropriate level of security. Three primary concerns should be taken into consideration when developing a Torus Automorphism transformation matrix to protect the fingerprint minutia points: (1) the sensitivity to the transformation parameter values; (2) the effect on the performance recognition rate; and (3) the ability to produce multiple templates.  
The keyspace provided by the proposed Torus Automorphism transformation is restricted to a value of \((R-1)N^{2}\). In case the parameter values utilized are \(a=9\), \(b=9\), and \(N=128\), the recurrence time \(R\) can be determined by simulation, and it is almost equal to \(N-1\)[21]. Thus, the keyspace is equal to \(127\times 128^{2}\), which means that it is sufficiently difficult for an adversary to formulate an estimation.  
The user-specific kernel can be changed and generated using a different key (i.e., different chaotic map). Since each user has a unique kernel, it is necessary to study the effect of assigning the same kernel to all users. Figure 6 shows that in the case of using the same kernel for all users, the proposed approach achieves the same GAR as the baseline system (without protection). Hence, we conclude that the simple proposed convolution process does not deteriorate the performance accuracy under the baseline system when the kernel is stolen.  
Figure 5: The ROC curve of the proposed cancelable approach.
# The Role of Trees in Sand Dune Rehabilitation: Insights from Global Experiences
## 4 Discussion
### The Effects of Afforestation on Sand Dunes
#### 4.5.4 Invasive Species and the Health of the Ecosystems  
Most of the articles regarding the invasive species from sand dunes belong to the Acacia genus and are mainly described by authors from Israel. As such, our review shows that invasive species (including _Acacia longifolia_, _Acacia saligna_, and _Pinus_) can lead to significant disruptions in the ecosystems of dunes. This includes a reduction of native plants, an altering of the soil microbial communities, and an overall reshaping of entire ecological processes [41; 43; 44; 99]. If we return to the concrete example from Israel, _A. saligna_ was first introduced to stabilize dunes [122], but has reached a point nowadays where it invades sandy habitats and alters native biodiversity and soil properties [123; 124]. These invasion mechanisms are also documented at a global level for _Acacia saligna_ and other Australian acacias [125; 126; 127].  
We also found some cases where these invasive species, like _A. cynonphylla_, have temporarily enhanced soil fertility [41]. However, this comes at significant costs on the resilience of ecosystems and native biodiversity. An example in this case comes again from Israel, where the invasion of _A. saligna_ in the Nizzanim Nature Reserve led to a significant loss in endemic species and declines in the overall ecologic ecosystem [43]. This pattern was also observed in other areas of the globe, like Portugal [41] and Brazil [74]. These countries saw the introduction of _Acacia_ to stabilize sand dunes [128]. Other examples come from Italy, where the same _Acacia saligna_ is considered a major invader and is present in stands from coastal environments [129].  
Our synthesis shows both benefits and disadvantages in the afforestation of sand dunes. Most outcomes are strongly linked with the geographic context, the selection of certain species, and the management of objectives. These dual perspectives are presented below for certain categories impacted by afforestation.  
Implications for Groundwater and Vegetation  
Sand dunes in arid areas play a crucial role in groundwater recharge, especially due to high infiltration rates [89]. The paradox is that afforestation may reduce wateravailability as tree transpiration and canopy interception diminish groundwater recharge. In this context, we recommend implementing strategies that take into account this trade-off between groundwater recharge and the stabilization of dunes, especially in environments where water is scarce.
###### Abstract  
In this paper, a procedure is proposed to design a power line communication (PLC) system to perform the digital transmission in a distributed energy storage system consisting of fleets of electric cars. PLC uses existing power cables or wires as data communication multicarrier channels. For each vehicle, the information to be transmitted can be, for example: the models of the batteries, the level of the charge state, and the schedule of charging/discharging. Orthogonal frequency division multiplexing modulation (OFDM) is used for the bit loading, whose parameters are optimized to find the best compromise between the communication conflicting objectives of minimizing the signal power, maximizing the bit rate, and minimizing the bit error rate. The off-line design is modeled as a multi-objective optimization problem, whose solution supplies a set of Pareto optimal solutions. At the same time, as many charging stations share part of the transmission line, the optimization problem includes also the assignment of the sub-carriers to the single charging stations. Each connection between the control node and a charging station has its own frequency response and is affected by a noise spectrum. In this paper, a procedure is presented, called Chimera, which allows one to solve the multi-objective optimization problem with respect to a unique frequency response, representing the whole set of lines connecting each charging station with the central node. Among the provided Pareto solutions, the designer will make the final decision based on the control system requirements and/or the hardware constraints.  
power line communication (PLC); energy storage management; vehicle to grid (V2G); smart grid; multi-objective optimization Article
# Numerical Simulation of Non-Isothermal Mixing Flow Characteristics with ELES Method
## 2 Turbulence Model and CFD Methodology
### Precursor Simulations  
When the ELES simulations are carried out, unsteady fluctuations at the RANS-LES interface are required to be provided to the LES domain [19]. Therefore, precursor RANS simulations are conducted for the profiles of inlet turbulence quantities and the pre-estimation of mesh size in the central mixing zone, and the K-omega SST turbulence model is employed before carrying out the ELES. In the precursor RANS simulations, turbulent flows are conducted in pipes with a diameter of \(1\)\(D_{m}\) and \(1\)\(D_{b}\), respectively. In order to obtain the fully developed inlet profiles, the pipe lengths are set as \(18\)\(D_{m}\) and \(10\)\(D_{b}\), respectively, as the requirement stated in reference [19]. Through the precursor simulations, the profiles of inlet turbulence quantities can be obtained.  
Precursor simulations of three cases with typical flow patterns are simulated in the pipes with the K-omega SST turbulence model. Details of the three cases are listed in Table 1. According to reference [5], the flow pattern can be predicted by the momentum ratio \(M_{R}\): \(M_{R}\) < 0.35: impinging jet, \(0.35<M_{R}\) < 1.35: deflecting jet, \(M_{R}\) > 1.35: wall jet. Furthermore, the momentum ratio \(M_{R}\) is defined as Equation (17):  
\[M_{R}=\frac{M_{m}}{M_{b}}=\frac{D_{m}D_{b}\rho_{m}V_{m}^{2}}{\pi/4D_{b}^{2} \rho_{b}V_{b}^{2}} \tag{17}\]
## 2 Materials and Methods
### Machine Learning Model
#### 2.3.3 Sensitivity Analysis  
A sensitivity analysis assesses how variations in input values influence output variables, providing insights into the robustness and reliability of an ML model. SHapley Additive exPlanations (SHAP) [62] comprise an explainability technique based on the Shapley value concept introduced by [PERSON] [63] in cooperative game theory. Essentially, the Shapley value calculates the average contribution of a feature across all possible subsets \(F\). Unlike variance-based decomposition methods such as Sobol indices, SHAP values offer a more accurate reflection of the input-output relationship in design exploration, as input variables are considered to be nonrandom [64]. The Shapley value of the \(j\)-th feature is defined as  
\[\phi_{j}\big{(}\hat{\mathbf{f}},\mathbf{X}\big{)}=\frac{1}{m}\sum_{S\subseteq F\setminus \{j\}}\binom{m-1}{|S|}^{-1}\big{(}\hat{\mathbf{f}}_{S\cup\{j\}}\big{(}\mathbf{X}_{S \cup\{j\}}\big{)}-\hat{\mathbf{f}}_{S}(\mathbf{X}_{S})\big{)} \tag{10}\]  
where \(S\) is the one subset of \(F\) and the right term is the marginal contribution of feature \(j\) to a subset \(S\). An essential characteristic of the Shapley value is its efficiency, ensuring that the total sum of Shapley values for all features equals the model output. Therefore, the output value of \(\hat{\mathbf{f}}(\mathbf{X})\) can be expressed as  
\[\hat{\mathbf{f}}(\mathbf{X})=\phi_{0}+\sum_{j=1}^{m}\phi_{j}(\mathbf{X}) \tag{11}\]  
where \(\phi_{0}\) is the output of reference input value or \(\hat{\mathbf{f}}_{\emptyset}(\mathbf{X}_{\emptyset})\). For a global sensitivity analysis, averaged SHAP values are utilized to assess feature sensitivity at a global scale [64]. Averaged SHAP values indicate the average impact of input variables on specific outputs. The averaged SHAP of the \(j\)-th feature can be expressed as  
\[\big{|}\hat{\phi_{j}}\big{|}=\frac{1}{n_{s}}\sum_{i=1}^{n_{s}}\big{|}\phi_{j} \big{(}\mathbf{X}^{(i)}\big{)}\big{|} \tag{12}\]