esa-sceva/satcom-chunk-collection huggingface dataset:
# Tension Force Detection of Short Suspender by Using Laser Doppler Vibrometer
## 4 Discussion  
The above results show that the tension force can be accurately calculated according to the quadratic regression relationships between tension force and vibration frequency obtained by using LDV. This represents the fact that the tension force of short suspenders can be detected in real time to provide guidance for timely maintenance and life prediction. As an accurate and rapid detection method, the advantages of LDV can be listed as follows. First, using LDV to accomplish tension force detection of short suspender belongs to remote and non-contact measurement method, the scope of which is 100 m. Within the effective range, the accuracy of signal can be achieved only by adjusting the angle of the host to aim at the object, and many adverse effects can be avoided. By contrast, conventional sensors need be installed in the object, being more susceptible to the changes in their own properties and surroundings. Second, the sampling frequency and resolution of LDV are all higher than conventional sensors due to its remote and non-contact characteristics, effectively avoiding the errors caused by the additional quality of sensors and wire length in the test. Third, using LDV to obtain the vibration characteristics of short suspender is a nondestructive monitoring method, having no influence on the construction and service process of cables. Fourth, the short suspender surface does not require special processing to obtain enough reflection signal. In particular, the reflector can be pasted in the test position to achieve a strong enough signal [24].  
Identifying the vibration frequency of short suspender accurately and then establishing the accurate relationships between tension force and vibration frequency are the key problems for real-time detection of the service condition of cables by using the frequency method. The complex boundary conditions and flexural rigidity of short suspenders produces a large error for the experimental and calculated values of tension force based on tension string vibration frequency. The quadratic relationships between vibration frequency and tension force provide an approach for establishing an accurate method to detect tension force for steel rod-type short suspenders by using vibration frequency.
# Broadening of Light Coupling to Waveguide Modes in Solar Cells by Disordered Grating Textures
## 1 Introduction  
Advanced light-trapping concepts are one way to enhance light absorption in the absorber layer and thereby improve solar cell efficiencies. This holds in particular for thin absorber layers, where the thickness of the device gets similar to or smaller than the absorption length of impinging light in a broad spectral range. In such thin devices, the resonant coupling to waveguide modes is of utmost importance [1]. Since resonant light coupling to waveguide modes is only possible in small spectral regions compared to the broad solar spectrum, an engineered light-trapping design to address the whole spectrum efficiently is necessary.  
Periodic light trapping textures have demonstrated strong enhancement of the external quantum efficiency (EQE) of solar cells in spectrally sharp resonances [2; 3]. In contrast, solar cells with random textures show a spectrally broad improvement of EQE [4; 5; 6; 7]. However, due to the missing optical resonance, this improvement remains below the values for solar cells with periodic textures at their resonances [8].  
Disordered grating textures offer the opportunity to couple incident light to guided modes in the absorber layer within a spectrally broader regime with a slightly reduced maximum, as compared to the well-ordered grating textures. It was shown experimentally that such disordered grating textures can improve the overall efficiency of the solar cells even further compared to the well-ordered grating textures [9].  
In this study, we investigate the impact of disordered grating textures on the EQE of solar cells by applying the Finite-Difference Time-Domain (FDTD) method [10; 11]. We used a hydrogenatedamorphous silicon (a-Si:H) thin-film solar cell in superstrate configuration with a nominal absorber layer thickness of 250 nm as a test device. The disorder is introduced by two different ways, a variation of the particle position within the unit cell while keeping the shape of the particles constant, and a variation of the radius of the particles while keeping the position of the particles within the unit cell constant. The simulations were performed in the relevant spectral range for light trapping with a spectral resolution of 2 nm in order to resolve the resonances accurately.  
By taking into account the Fourier transform of the interface topography as well as the local layer thickness, we show that the improvement in EQE due to the disorder can be explained by both a spectral broadening of the waveguide mode itself and a diffuse wave vector transfer at the disordered grating texture. We show that the disorder in the particle position dominantly leads to a diffuse wave vector transfer, while the disorder in the particle radius dominantly leads to a broadening of the waveguide mode itself.
###### Abstract
[28] proposed a short-term traffic flow prediction method based on the 1 DCNN-LSTM model, which aims to effectively solve traffic travel and management problems. Evidently, the CNN-LSTM architecture can fully combine the advantages of these two independent models, which is demonstrated to fulfill more complicated tasks. From the above literature review, the following conclusions can be drawn: (1) Shallow features used for damage identification are usually not suitable for nonlinear situations and harbor poor sensitivity. (2) CNN can extract the high-dimensional features, which is beneficial to characterize the current damage state of the structure. (3) LSTM can meticulously model the structural time history response, which is promising to depict the historical damage state. (4) CNN-LSTM model holds outstanding performance in numerous application scenes. Inspired by this, this study integrates the advantages of CNN and LSTM in feature extraction and time-series modeling. A CNN-LSTM-based damage identification method for long-span bridges is proposed. This method directly acts on the structural accelerations. It uses CNN to extract high-dimensional features of accelerations and LSTM to extract time-series features. Eventually, the extracted features are fused and input into the fully connected layer to complete the damage identification. The remainder of this article is expanded in the following sections. Section 2 introduces the basic structure and optimization methods of CNN and LSTM and presents the procedure of the proposed method. Section 3 uses numerical simulation to obtain data samples and build a database to verify the feasibility and effectiveness of the proposed method. Section 4 discusses the influence of environmental noise on the proposed method and compares the performance of the proposed method with that of the CNN. Section 5 concludes this paper.
# Resource Management in Converged Optical and Millimeter Wave Radio Networks: A Review
## 8 Conclusions  
### Contributions of This Study  
In this article, a literature survey is presented to understand the key concepts and the key network state parameters used to evaluate the performance of AI-based network optimization algorithms, to identify the future demands and to analyze the options for novel contributions and the limitations of resource management in converged optical and mmWave radio networks. We aimed to identify the main features, objectives, and the resource allocation solution methods in mmWave networks by also considering the relationship between the use of optimization algorithms for virtualized resource allocation and the use of the ANM technological enablers in the 5G and beyond-5G network architecture. Furthermore, a dedicated discussion is provided for each resource management objective to identify the gaps in the existing literature and to provide potential directions for future research.
## 3 Implementation
### Algorithm and Model Training
The mean relative error (MRE) was calculated using Formula (3) as follows:  
Figure 11:2 \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Object** & **Date** & **11–23** & **11–30** & **12–07** & **12–14** & **12–21** & **12–28** & **01–04** \\ \hline Area of Optics & Predicted Value & 189.50 & 201.75 & 215.41 & 228.32 & 240.57 & 254.97 & 263.62 \\ A (mm\({}^{2}\)) & Actual Value & 180.74 & 192.81 & 211.21 & 232.04 & 247.89 & 260.38 & 271.29 \\ \hline Area of Optics & Predicted Value & 80.07 & 94.54 & 109.41 & 124.41 & 139.81 & 154.2 & 169.17 \\ B (mm\({}^{2}\)) & Actual Value & 74.63 & 89.92 & 103.45 & 117.23 & 130.53 & 148.36 & 160.72 \\ \hline Area of Optics & Predicted Value & 404.07 & 407.31 & 410.57 & 413.85 & 417.17 & 420.51 & 423.87 \\ C (mm\({}^{2}\)) & Actual Value & 403.54 & 404.46 & 408.22 & 411.38 & 412.98 & 418.44 & 425.34 \\ \hline Area of Optics & Predicted Value & 179.00 & 191.56 & 204.99 & 219.37 & 234.76 & 251.23 & 268.85 \\ D (mm\({}^{2}\)) & Actual Value & 175.76 & 187.23 & 207.79 & 217.67 & 228.61 & 259.52 & 270.87 \\ \hline Area of Optics & Predicted Value & 52.64 & 61.43 & 71.69 & 83.67 & 97.64 & 113.95 & 132.98 \\ E (mm\({}^{2}\)) & Actual Value & 50.97 & 57.27 & 64.53 & 76.49 & 90.26 & 109.75 & 121.46 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Comparison between predicted values and actual values of damage areas. Figure 16: (**a**) Numerical simulation of the relationship between a single damage area and the energy; (**b**) the development and prediction of total damage areas. where \(\varepsilon_{MR}\) is the MRE, and \(n\) is the total number of samples. Based on Formula (3), we calculated that \(\varepsilon_{MRA}\approx 2.99\%\), \(\varepsilon_{MRB}\approx 5.80\%\), \(\varepsilon_{MRC}\approx 0.55\%\), \(\varepsilon_{MRD}\approx 1.84\%\), \(\varepsilon_{MRE}\approx 7.50\%\). We set the tolerance to 10%; thus, any data whose error within this range can be regarded as a valid prediction. Based on the above calculation results, it can be concluded that the accuracy of the area prediction exceeds 90%. In Figure 16, the gray dotted lines represent the historical daily output energy, while the blue lines depict the planned daily output energy. The fold lines depict the changes in the overall damage area of the optic over time. These lines connect the damage areas at each time point, clearly showing the trend of damage area variation. By observing these trends, we can understand the accumulation of damage and whether the rate of damage development is within acceptable limits. By defining a critical point for the damage area, we can determine the latest maintenance date by identifying the intersection point between the fold line and the corresponding energy output point. This approach enables us to establish a proactive maintenance schedule based on critical damage thresholds and energy output levels, ensuring optimal operational efficiency and component longevity.
# Adsorption of Arsenic and Heavy Metals from Solutions by Unmodified Iron-Ore Sludge
## 1 Introduction  
The pollution of wastewater with arsenic (As) and heavy metals is one of the most serious environmental problems worldwide. Considerable amounts of wastewater, generated from anthropogenic activities such as mining and smelting, fertilizer production, agriculture, and battery manufacturing, pose a high risk to the environment, ecosystems, and human health [1, 2]. A variety of treatment methods have been applied to eliminate heavy metals from water, including coagulation [3], adsorption [4], ion exchange [5], electrocoagulation [6], and biological processes [7, 8]. Of these, adsorption is considered the most cost-effective [9] when using sorbents that require little processing, are abundant in nature, or are by-products or waste materials from industry [10, 11, 12].  
Solid wastes from mining activities have been assessed as low-cost adsorbents for wastewater purification [12, 13, 14, 15, 16, 17]. A variety of solid wastes have been used for water treatment, including clay-bearing mining waste [18], red mud [19, 20, 13, 21], coal mine-drainage sludge [22], iron-ore slime [17], and waste mud from copper mines [16]. The use of mining waste is considered to be an environmentally-friendly technique because both solid waste and contaminated water are treated and could result in waste-free production [12, 14, 16, 23, 24].  
Vietnam's mining sector is the third largest contributor to the national gross domestic product (GDP) [25]. An increasing demand for iron in the steel and construction industries, and the abundance of iron deposits in Vietnam [26] have generated a large volume of solid waste. Failure of the sludge reservoir at the Ban Cuon iron-ore processing area, Bac Kan Province on July 20, 2014 damaged agricultural land and drainage infrastructure of the Ngoc Phai commune [27]. This event highlights anurgent need for the management and treatment of such solid wastes. The use of iron-ore sludge for water treatment is potentially one solution; however, there are few studies on the capacity of iron-ore sludge to adsorb As and heavy metals or their potential use for water purification.  
The aim of this research was to determine the adsorption behavior of As, Mn, Zn, Cd, and Pb in batch experiments using iron-ore drainage sludge collected from an iron processing area in northern Vietnam.
# An Efficient Digital Channelized Receiver for Low SNR and Wideband Chirp Signals Detection
###### Abstract  
Synthetic aperture radar (SAR) is essential for obtaining intelligence in modern information warfare. Wideband chirp signals with a low signal-to-noise ratio (SNR) are widely used in SAR. Intercepting low-SNR wideband chirp signals is of great significance for anti-SAR reconnaissance. Digital channelization technology is an effective means to intercept wideband signals. The existing digital channelization methods have the following problems: the contradiction of reception blind zone and signal spectrum aliasing, high computational complexity, and low estimating accuracy for chirp signals with a low SNR. This paper proposes a non-critical sampling digital channelized receiver architecture to intercept chirp signals. The receiver architecture has no blind zone in channel division and no aliasing of signal spectrum in the channel, which can provide reliable instantaneous frequency measurements. An adaptive threshold generation algorithm is proposed to detect signals without prior information. In addition, an improved instantaneous frequency measurement (IFM) algorithm is proposed, improving low SNR chirp signals' frequency estimation accuracy. Moreover, a simple channel arbitration logic is proposed to complete the cross-channel combination of wideband signals. Simulations show that the proposed receiver architecture is reliable and robust for low SNR and wideband chirp signal detection. When the input SNR is 0 dB, the absolute frequency root-mean-square error (RMSE) of bandwidth and the center frequency is 0.57 MHz and 1.05 MHz, respectively. This frequency accuracy is great for radio frequency (RF) wideband systems.  
c 2023 by the authors. Liconse MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ([[https://creativecommons.org/licenses/by/4.0/](https://creativecommons.org/licenses/by/4.0/)]([https://creativecommons.org/licenses/by/4.0/](https://creativecommons.org/licenses/by/4.0/))).  
c 2023133080. [[https://doi.org/10.3390/app13053080](https://doi.org/10.3390/app13053080)]([https://doi.org/10.3390/app13053080](https://doi.org/10.3390/app13053080))
# Modeling of Geophysical Flows through GPUFOW
## 6 Conclusions  
Mathematical modeling represents a powerful tool for forecasting the area affected by geophysical flows and assessing the associated hazard and risk. The improvements to GPUFLOW presented in this paper expand the scope of application of the model to a wider range of geophysical flows and can improve the accuracy of the simulation in many circumstances by taking into account additional factors that can affect the flow emplacement. The validation carried out on two real events, debris flow in the Dolomites and lava flow from the Etna volcano, confirmed the overall reliability of the model for these two kinds of geophysical flows and assessed the numerical robustness of its implementation.  
The model is currently able to simulate debris and lava flows under specific assumptions and conditions. For example, the simulation of debris flows neglects the temperature of the material and the variation in the material composition during the event. Moreover, lava flows are subject to strong thermal effects, including phase transition, which can cause the formation of leves, crusts, and tunnels. These phenomena, which are currently not considered, are fundamental for hazard purposes, possibly impacting flow emplacement and redirecting the flow.  
GPUFLOW is actively maintained and updated to introduce new features and optimizations. Future topics of research will include an automatic calibration of the geometric bias coefficient based on the local slope of the terrain. The simulation of debris flow will be validated by using other real test cases, with measured detached niches and deposits and different transported materials. Different rheological models will also be considered in order to allow GPUFLOW to cover a wider range of geophysical flows, including different types of landslides.  
Conceptualization, A.C. and G.B.; Data curation, A.C. and G.G.; Formal analysis, A.C. and G.B.; Funding acquisition, A.C.; Investigation, G.G.; Methodology, A.C., G.B. and G.G.; Software, G.B.; Writing--original draft, A.C., G.B. and G.G. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the INGV project Pianeta Dinamico (CUP D53J19000170001) funded by MIUR (\"Fondo finalizzato al rilancio degli investimenti delle amministrazioni centrali dello Stato e allo sviluppo del Paese,\" legge 145/2018), Tema 8-PANACEA.  
The authors declare no conflict of interest.
## 4 Discussion
### Contribution to the LIBs Industry  
Our findings demonstrated that development trends from the patents with high forward citation were similar in the main lithium salts and organic solvents. The most noteworthy part is the development of additives. Patent assignees used various additive compounds to improve multiple characteristics of LIBs. Therefore, developing new additives to fulfill different purposes is vital. In addition, the use of electrolyte additives is seen as one of the most economic and effective methods to enhance LIBs performance [22]. [PERSON] et al. [10] also showed that additives had the largest counts of patent documents during 2006-2010. Our findings also demonstrated that additives, such as the carbonate compound, e.g., vinylene carbonate, vinylethylene carbonate can be used to mix with the (1) aromatic compound, e.g., substituted-benzene, (2) fluorine-containing compound, e.g., fluoroalkyl (C2-C20) carboxylic acids, (3) sulfur compound, e.g., ethylene sulfite, (4) anisole compound, e.g., 3-fluoroanisole, (5) sulfone compound, e.g., methyl sulfone, and (6) chelating agent, e.g., ethylene diamine tetraacetic acid (EDTA), to enhance/improve LIBs performance. Therefore, we believed that additives covered a broader range than lithium salts and organic solvents in terms of chemical compounds and possible functionalities. Furthermore, this might be an easier way to make batteries different from other existing electrolyte formulations from the viewpoint of applications.  
In addition, the additive compound should satisfy the diverse functional requirements for better battery performance. These major functional requirements include characteristics of the charge and discharge, capacity, cycle life, and safety that are mainly considered by the top patent assignees.
# Performance Evaluation for China's Planned CO\({}_{2}\)-Ipda
## 3 Results
### Critical Hardware Parameters  
The energy of a single pulse and the laser repetition frequency determine the output photon number per unit time, which eventually determines the SNR of received signals. The repetition frequency was fixed after the laser was developed; consequently, only the pulse energy is considered here. In reality, many other hardware parameters, such as line width, wavelength stability, and the quantum efficiency of detectors, also affect the performance of the CO\({}_{2}\)-IPDA. However, these parameters do not affect the allocation of satellite resources and are therefore not included in this analysis. The diameter of the telescope is the major determining factor for the volume of the CO\({}_{2}\)-IPDA load, while the pulse energy determines its power consumption. Three contour lines for the relative error are drawn in Figure 6, representing our ideal target (0.3%), medium target (0.5%), and threshold (1%). Figure 6 shows that pulse energy plays an almost identical role to telescope diameter in determining the relative error. This phenomenon is to be expected because the laser energy determines the total number of photons emitted, while the diameter of the telescope determines the proportion of photons that can arrive at the detector. According to Equations (1)-(3), the relative random error is inversely proportional to \(E\) and to the square of diameter. Hence, increasing the diameter has a larger effect than increasing \(E\). However, from an engineering perspective, it is easier to double \(E\) than to double the diameter.  
Considering the standard diameter of commercially available telescopes, a diameter of 1 m is considered a suitable design. Based on this premise, the corresponding single-pulse energy can be  
Figure 5: **(a,b)** Coverage of the CO\({}_{2}\)-IDPA for two months using different orbit altitudes. The symbols are as defined for Figure 4.  
halved compared with the original design, which leaves a margin to reduce energy consumption. The combination of a pulse energy of 75 mJ and a diameter of 1 m would leave sufficient buffer space for the extreme conditions that might be encountered during actual measurements. In conclusion, there is some room for compromise in the design parameters for the pulse energy or telescope diameter.
# Dynamic Modeling and Optimization of Tension Distribution for a Cable-Driven Parallel Robot
## 4 Optimization Algorithm of Tension Distribution
### Factors Affecting Minimum Cable Tension
#### 4.5.3 Cable Length Changes  
The variation in cable length is determined by the trajectory of the end effector. It is an important parameter affecting the tension distribution. During the movement of the end effector, the length of each cable will change, which will affect the tension distribution of the cable. The length variation in each cable is calculated according to the displacement of the end effector and the cable geometry.