esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction
In these experiments [22; 23; 24; 25], the effectiveness of TMD was merely verified with a limited number of TMD parameters, as the adjustment of TMD parameters was inconvenient. The optimal frequency and damping parameters of the TMDs are thus hard to obtain experimentally. For robustness, the vibration control device installed on a lattice tower needs to be capable of controlling the vibration of the structure under different wind directions. In addition, the device needs to mitigate the along-wind response and across-wind response of the tower simultaneously. Hence, it is of great significance to design an omnidirectional device that is able to accommodate different wind directions and vibration directions. Eddy current tuned mass damper (ECTMD) is a newly developed and promising device for vibration mitigation. It has been implemented in tall buildings [14] and transmission towers [27], and has attracted considerable interest [28; 29; 30]. For a traditional TMD in which viscous dampers are used to provide damping, it is found that there exists a concern of fluid  
Figure 1: Collapse of a transmission tower in China caused by wind loading. leakage, and the damping adjustment is difficult. The concerns raised can be attenuated by using ECTMD, in which an eddy current is employed to provide the damping. The relative movement between the magnetic field and the conductor in the device produces a damping force approximately proportional to the relative velocity, which can be considered linear damping [31] in the case of an ECTMD mass swaying in small amplitude. The separation of damping and stiffness in an ECTMD makes it potentially feasible to design an adjustable TMD for performing passive [32; 33] or semi-active vibration control in the further study. In this paper, an omnidirectional cantilever-type ECTMD is designed and fabricated. Its adjustability is examined via a free vibration test. Wind tunnel tests are conducted to attain relatively optimal parameters of the ECTMD installed on an aeroelastic model of a lattice tower, in the case of prescribed design wind loading. After applying the parameters to the ECTMD, the dynamical responses of the damped tower under different wind speeds and wind directions are then measured to verify the effectiveness of the ECTMD. Finally, a frequency domain method is presented for evaluation of the dynamic response of the tower, and the numerical results based on the proposed computing method are compared with the experimental results.
###### Abstract  
We measure the near field distribution of a microwave horn with a resonant atomic probe. The microwave field emitted by a standard microwave horn is investigated utilizing Rydberg electromagnetically inducted transparency (EIT), an all-optical Rydberg detection, in a room temperature caesium vapor cell. The ground 6S\({}_{1/2}\), excited 6P\({}_{3/2}\), and Rydberg 56D\({}_{5/2}\) states constitute a three-level system, used as an atomic probe to detect microwave electric fields by analyzing microwave dressed Autler-Townes (AT) splitting. We present a measurement of the electric field distribution of the microwave horn operating at 3.99 GHz in the near field, coupling the transition 56D\({}_{5/2}\to 57\)P\({}_{3/2}\). The microwave dressed AT spectrum reveals information on both the strength and polarization of the field emitted from the microwave horn simultaneously. The measurements are compared with field measurements obtained using a dipole metal probe, and with simulations of the electromagnetic simulated software (EMSS). The atomic probe measurement is in better agreement with the simulations than the metal probe. The deviation from the simulation of measurements taken with the atomic probe is smaller than the metal probe, improving by 1.6 dB. The symmetry of the amplitude distribution of the measured field is studied by comparing the measurements taken on either side of the field maxima.  
microwave; near field; atomic probe; EIT-AT spectrum; stark effect 1
# Stabilization of Pickering Emulsions by Hairy Nanoparticles Bearing Polyanions
## 3 Results and Discussion
### Water:Oil Ratio  
There are two ways to control over stability and type of Pickering emulsion: tailoring the amphiphilicity of particle emulsifiers or changing the compositions of the emulsion phases [23]. Based on the Ostwald packing theory, it is well known that changing the water:oil ratio of emulsion systems in a wide range could give rise to interconversion between different types of emulsions which is commonly named emulsion phase inversion [39; 40]. During the process, emulsion droplets size and the emulsion volumes also depended on the volume ratios of water and oil. As shown in Figure 8a, hexadecane/H2O Pickering emulsion stabilized by PS@PSS had the maximal emulsion volume when water:oil volume ratio was 1:1. When water:oil ratio was over 1, an O/W emulsion was formed successfully shown as W2O1 which meant the volume ratio of water and oil (hexadecane) was 2:1. We could clearly see that there was an obvious boundary between emulsion and water phase in Figure 8a. The lower layer was PS@PSS as verified by DLS. The size was still around 250 nm. Both the emulsions above could exist stably for three months. When water:oil ratio was less than 1, only a thin O/W emulsion layer was temporarily formed, and the emulsion was broken automatically five hours later.  
A possible Pickering emulsion droplets scheme is given in Figure 8b. Moreover, microscope images in Figure 8c also showed that emulsion droplets with diameters of \(\sim\)12.0 \(\upmu\)m were the most homogeneous when the water:oil ratio was 1:1. When this ratio was over 1, Pickering emulsion phase formed at the upper layer and spherical droplets with diameters of \(\sim\)8.0 \(\upmu\)m were clearly observed in the corresponding optical microscopy images (Figure 8d).  
On the one hand, no stable emulsion under low water:oil ratio was formed, which was attributed to the hydrophilic nature of PS@PSS nanoparticles. On the other hand, for stable emulsions when water:oil ratio was over 1, decreasing water:oil ratio resulted in larger emulsion droplets and more emulsion volume fractions. [PERSON] et al. reported that for stable emulsions with lower water contents, fewer nanoparticles were able to stabilize the droplets [41]. Therefore, there were few PS@PSS nanoparticles adsorbed at the interface of hexadecane and water to form a complete interfacial film. Then the small emulsion droplets tended to coalesce into larger ones, resulting in an increase in the uniformity of the droplet shapes.
## 2 Materials and Methods
### Data Source
#### 2.2.2 Soil Moisture Data  
The monthly root-zone soil moisture (SM\({}_{\text{root}}\)) and surface soil moisture (SM\({}_{\text{surf}}\)) datasets at a 0.25\({}^{\circ}\) spatial resolution from the latest version (v3.5) of the Global Land Evaporation Amsterdam Model (GLEAM) ([[https://www.gleam.eu/](https://www.gleam.eu/)]([https://www.gleam.eu/](https://www.gleam.eu/)), accessed on 21 March 2021) were adopted in this study. The above global datasets are based on satellite and reanalysis data and span a 41-year period from 1 January 1980 to 31 December 2020. Furthermore, the datasets were validated in the field across a wide range of ecosystems [29; 30].  
Figure 1: Land-use types and meteorological station distribution (**a**); location (**b**); elevation information (**c**); annual mean Tem (**d**) and PPT (**e**) during 2000–2020 of the study area. Note: HB, HN, JX, JS, AH, ZJ, and FJ are the abbreviations for Hubei, Hunan, Jiangxi, Jiangsu, Anhui, Zhejiang, and Fujian provinces, respectively.
# Development of a Digital System for Monitoring Emergency Conditions in 20 kV Distribution Networks
## 2 Materials and Methods
For signal indication and comparison at different stages of their transformation, we use the virtual observer-oscilloscope Scope, applied in the created model to visualize the ongoing processes and enable the viewing of oscillograms of transmitted and received signals. To ensure the mathematical compatibility of signals and oscilloscope inputs, special mathematical modules are required. We use the Complex to Magnitude-Angle block to convert complex numbers into amplitude and phase display format. The amplitude signal from the block's output in real form will be fed to the control input of the Scope oscilloscope block, which displays only real numbers. The model includes the following auxiliary technological modules and blocks [6]:  
The Sum block, which generates the error signal at the receiver by subtracting the input and output signals, necessary for determining the difference in the form of the error signal error as the mathematical difference between the transmitted and received messages. The Complex to Real-Imag blocks, which convert complex numbers into a format separating the real and imaginary parts, used in the mode of generating a time-domain diagram of the modulated signal. Using an additional adder, the outputs of this block are summed. The Integer Delay block, which creates a time delay of the transmitted message by one clock cycle, necessary for time synchronization and comparison of the transmitted and received messages, and in case of mismatch, generating the error signal by subtraction 8 [6]. As illustrated in Figure 8, the structural model of the transmission system incorporates features to minimize transmission errors and improve data reliability, which aligns with the study's objectives. Figure 7: Block diagram of the transmission channel model. In this scheme, it is necessary to ensure the comparison of the original signal at the input of the transmission path and the signal at the output of the reception path in such a way that, in the event of errors, the error is detected, and a graphical representation of the error appears in one of the oscilloscope channels.
## 2 Proposed Model  
### Research Methodology  
In this paper, we address the microgrid sizing problem, which involves determining the components to be installed in a microgrid to optimize its cost while prioritizing the reliability and efficiency of energy supply. We focus on three main objectives. First, to develop a comprehensive model that captures the microgrid sizing problem, accounting for specific characteristics such as its multi-period nature and the stochastic behavior of certain components. Second, to design a solution strategy capable of efficiently solving realistically sized instances of the problem. Third, to validate the proposed model using data derived from a real-world case study.  
Sizing decisions take into account the characteristics of the power-generating devices and the relevant weather conditions; the goal is to develop a framework that can predict optimal microgrid sizes under various scenarios, incorporating economic, environmental, and reliability aspects primarily using renewable energy sources.  
In this study, we consider the four research stages outlined in Figure 1. The process begins with defining the optimization problem. Next, a model formulation is developed to mathematically describe the problem. Due to the complexity of the formulated problem, the design of a solution strategy emerges by pivoting from a pure exact solution approach based on a commercial solver to an approximated solution approach based on the combination of metaheuristics and simulation methods; thus, we applied an iterated local search (ILS) algorithm. We simulated each model under various scenarios to assess the impact of different levels of uncertainty in renewable energy production and demand forecasts.  
The proposed model relies on several assumptions. For instance, it assumes that demand grows at a constant linear annual rate and follows two distinct patterns: weekdays and weekends. In the multi-year model, variations in electricity demand, fuel costs, and equipment degradation over time are considered. The latter is modeled using a decreasing geometric progression, which reduces generation capacity over time. Finally, to calculate the LCOE, the total cost is divided by the demanded energy rather than the generated energy, ensuring a linear expression.
# An Overview of the Applications of Earth Observation Satellite Data: Impacts and Future Trends
## 4 Discussion
### Other Significant Satellite Missions
mechanisms for estimating top-of-canopy height (TCH) from Dove images and provided a root mean square error (RMSE) of 4.36 m in Peru, which provided a significant advance in monitoring tropical forests. The technology of miniature satellites will be also an important trend in the future development of EO.
# Remote Sensing for International Peace and Security: Its Role and Implications
## 4 Discussion
Various United Nations, governmental, and non-governmental organizations have shown a substantial interest in remote sensing technologies for international peace and security. The main purpose of these organizations is to provide scientific information toward international peace and security. The cooperation between various space agencies can provide useful information to decision-makers, helping to establish global peace and security. For an example, the \"International Charter Space and Major Disasters\" platform provides satellite-based information for relief during humanitarian disasters. Satellite data are made available for rapid response to reduce disaster losses and damages. Advanced near real-time geospatial data can provide useful information to control the conflicts if combined with mobile data [115]. Big data initiatives can be helpful in conflict prevention and uncovering the relationship between conflict dynamics and development goals [116]. This review indicated that there has been significant progress in several technologies (like electronics, sensors, data analysis, and machine learning) being subsumed together with remote sensing applications for better understanding and realization of the project objective. However, the role of disciplines from social sciences and humanities along with remote sensing is still an underexplored territory. The absence of humanities somewhere also limits in understanding the key issues behind major conflicts and violence within a society. The future applications of remote sensing can be made more comprehensive by enriching the foundations with qualitative information from the ground level like issues with race, ethnicity, social structures, economic conditions, historical and anthropological foundations, and so on.
## 11 Conclusions and Future Work  
With the implementation of unitary decomposition, OpenQL can now be used for any quantum algorithm that uses arbitrary unitary gates. One such algorithm is QiBAM [8], which cannot be implemented without unitary decomposition.  
The decomposition generates more gates than the theoretical minimum, but the structure of the decomposition means that further optimizations can be easily integrated with the current implementation. The decomposition is performed using Quantum Shannon Decomposition, which is up to 10 times more efficient in the number of generated gates than Qubiter and only 50% less efficient than the implementation of UQC. Two optimizations were implemented to take advantage of the internal structure of the input or intermediate unitary matrices, which can drastically reduce the length of the resulting circuit. With these optimizations, the final resulting gate count can be much lower than the illustrated worst case numbers.  
The decomposition results in \(O(\frac{3}{4}4^{n})\) CNOT gates and \(O(\frac{9}{4}4^{n})\) total gates. Although the execution time of the decomposition is \(O(8^{n})\) for matrices of size \(2^{n}\times 2^{n}\), for the decomposition of up to 10-qubit gates, our implementation is 10-100 times faster than Qubiter and about 500 times faster than the implementation in UQC.  
There are several avenues that can further bring down the number of gates the decomposition generates, which are as follows:  
* The implementation of a minimum two-qubit circuit, such as the one described in [22] using the method from [29], if applicable;
* Additionally, the implementation of a universal three-qubit gate, such as the one in [30];
* Implementing the multiplexed \(R_{z}\) gate with a CZ gate, as expressed in [22];
* Reworking the QSD so that the intermediate matrices cancel out, as the input matrix has fewer degrees of freedom than the matrices resulting from the QSD. Therefore, it might be possible to choose some of these intermediate matrices in such a way that they can be decomposed using fewer elementary gates;
* The implementation of other specific efficient decompositions, such as controlled unitary gates (as opposed to uniformly controlled gates), quantum multiplexers or specialized multi-controlled rotation gates.  
Methodology, A.M.K. and A.S.; software, A.M.K. and I.A.; supervision, Z.A.-A. and K.B.; writing--original draft, A.M.K.; writing--review and editing, Z.A.-A. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
Data Availability Statement: The OpenQL source code, including the implementation of unitary decomposition presented in this paper, is available at [[https://github.com/QE-Lab/OpenQL](https://github.com/QE-Lab/OpenQL)]([https://github.com/QE-Lab/OpenQL](https://github.com/QE-Lab/OpenQL)) (accessed on 6 January 2022).  
The authors declare no conflict of interest.
# Automatic Fabric Defect Detection Method Using PRAN-Net
## 2 PRAN-Net Fabric Defect Detection Method Based on Faster R-CNN
### Defect Classification Network  
The structure of the classification network is shown in Figure 4. Defect proposals and their corresponding feature maps are resized by a RoI Align layer [14] to the fixed size. Then, the features are fed into a sequence of full-connection layers and are finally branched to classification and bounding box regression. The classification branch outputs the prediction of defect category, and the regression branch outputs the prediction of defect position after the secondary location.  
We introduce the softmax loss as the classification loss \(L_{cls}\) and the smooth L1 loss as the bounding box regression loss \(L_{reg}\) to supervise the classification network loss of fabric defects.  
The total loss \(L\) is the sum of the priori anchor location loss \(L_{lac}\), the priori anchor shape loss \(L_{shape}\), the classification loss \(L_{cls}\) and the bounding box regression loss \(L_{reg}\), as follows:  
\[L=L_{loc}+L_{shape}+L_{cls}+L_{reg} \tag{6}\]
# Analysis of Small-Loop Electromagnetic Signals to Detect Subsurface Anomaly Zones
## 4 Detection of Anomaly Zones by Visual Observation
### Underground Facilities  
Figure 9a shows the 2D ER contour map of the ER distribution in Section 5. This section is where the bottle filled with water, empty bottle, concrete block, and asphalt block (\(0.5\times 0.5\times 0.1\) m in size) were each installed at a depth of 0.35 m. They were laid at 1, 2, 3, and 4 m, respectively. Figure 10a shows the 2D ER contour map of Section 7 in Figure 2, where an empty bottle, asphalt block, and concrete block (\(1\times 1\times 0.1\) m in size) were each installed at a depth of 0.55 m. They were installed at 1, 2.5, and 4 m, respectively. The empty bottle represented a cavity in the ground, while the asphalt and concrete blocks represented rocks or other artificial structures that might exist in the ground. Each item had nonconductive characteristics, while the bottle filled with water had conductive characteristics.  
As shown in Figures 9a and 10a, the empty bottle, asphalt block, and concrete block, which had nonconductive characteristics, exhibited higher ER than the surrounding ground, whereas the bottle filled with water exhibited lower ER. The ER was nearly constant at each measurement position for all depths except 0.26 m, which was where the underground facilities were installed, as shown in Figure 9b. At a depth of 0.26 m, the ER significantly varied at the measurement positions where the facilities were installed. The ER significantly decreased at the measurement position where the bottle filled with water was located, owing to its conductive characteristics, whereas the ER increased at the measurement position of the empty bottle, concrete block, and asphalt block because they were nonconductive. Similarly, the ER was nearly constant for all depths at measurement positions where no facilities were installed, whereas the ER significantly varied according to the measurement position at a depth of 0.52 m, where the underground facilities were installed, as shown in Figure 10b.  
Figure 9: _Cont._Figure 10: _Cont._  
Figure 9: Test result for the underground facilities (Section No. 5); (**a**) Distribution of the ER. (**b**) ER according to the position at each depth.  
Figure 11: Test result for the steel plate (Section No. 7). (**a**) Distribution of the ER. (**b**) ER according to the position at each depth.
# Design of a Novel Electric Diagnostic Technique for Fault Analysis of Centrifugal Pumps
## 1 Introduction
The main limitation of this method is that amplitude detection in the motor current signature analysis (MCSA) is affected by the amplitude of random environmental noise. Furthermore, MCSA requires a harmonic frequency model to identify fault-related harmonics. These harmonic frequency models are available only for bearing defects, and models for impeller faults and pipe blockages do not exist. Thus, the MCSA technique cannot diagnose such faults [19; 20; 21]. The instant power technique has been suggested as an alternative non-invasive approach to MCSA for diagnosing bearing faults in an induction motor [22]. The mathematical model of the instant power technique provides an extra harmonic frequency related to the faults, and provides more information related to the health of the machine. However, the instant power technique requires information from the current sensor and the voltage sensor, and has thus been proven to be expensive when compared with MCSA [23; 24]. Furthermore, the capability of the instant power technique to diagnose pump impeller and cavity faults has yet to be investigated. [PERSON]'s vector analysis of the motor current has been used by some researchers to analyze the bearing, eccentricity, and rotor faults [25; 26; 27; 28]. In their work, the three-phase current has been converted to a two-phase current, and the frequency analysis of the two-phase current spectrum gives information about the machine health. Although the frequency spectrum of the two-phase current gives better information about the machine faults, the intensive mathematical computation is a major limitation [28]. Furthermore, the capability of the two-phase analysis technique to diagnose centrifugal pump faults has never been investigated in previously published research. The main contribution of this paper is to develop a non-intrusive EDT to diagnose impeller faults and pipe blockages. The developed EDT collects the three-phase currents from the sensors, and transforms them into two-phase d-q currents. These d-q currents are plotted to get d-q patterns. The visual and statistical analyses of these d-q patterns give the health status of the centrifugal pump. The rest of the paper is structured as follows: Section 2 gives the components of the fault analysis test rig. Section 3 provides an analysis of the results. Finally, Section 4 provides conclusions.