esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract  
Several high-speed wireless systems use Orthogonal Frequency Division Multiplexing (OFDM) due to its advantages. 5G has adopted OFDM and is expected to be considered beyond 5G (B5G). Meanwhile, OFDM has a high Peak-to-Average Power Ratio (PAPR) problem. Hybridization between two PAPR reduction techniques gains the two techniques' advantages. Hybrid precoding-companding techniques are attractive as they require small computational complexity to achieve high PAPR reduction gain. Many precoding-companding techniques were introduced to increasing the PAPR reduction gain. However, reducing Bit Error Rate (BER) and out-of-band (OOB) radiation are more significant than increasing PAPR reduction gain. This paper proposes a new precoding-companding technique to better reduce the BER and OOB radiation than previous precoding-companding techniques. Results showed that the proposed technique outperforms all previous precoding-companding techniques in BER enhancement and OOB radiation reduction. The proposed technique reduces the Error Vector Magnitude (EVM) by 15 dB compared with 10 dB for the best previous technique. Additionally, the proposed technique increases high power amplifier efficiency (HPA) by 11.4%, while the best previous technique increased HPA efficiency by 9.8%. Moreover, our proposal achieves PAPR reduction gain better than the most known powerful PAPR reduction technique with a 99% reduction in required computational complexity.  
5G; beyond 5G (B5G); orthogonal frequency division multiplexing (OFDM); peak-to-average power ratio (PAPR) reduction; out-of-band (OOB) radiation reduction; high power amplifier (HPA); hybrid PAPR reduction techniques; precoding techniques; companding techniques; Partial Transmit Sequence (PTS) +
Footnote †: journal: _Sensors_
# Exploring the Evolution of Drought Characteristics in Balochistan, Pakistan
## 2 Materials and Methods
### Drought Trends and Evolution  
The identification of statistically significant trends in SPEI and drought characteristics has been carried out using the non-parametric Mann-Kendall trend test [42] and Sen's slope. The Mann-Kendall calculation involves the subtraction of a trend estimate [43] from the time series.  
This test has been recommended by the World Meteorological Organization (WMO) to be conducted in climatology studies due to its allowance for missing values, low sensitivity to outliers, and no requirements for the sample to conform to a certain distribution [15]. Sen's slope is another non-parametric test which is usually run to estimate the true slope of trends found to be significant by the Mann-Kendall trend test [44; 45]. The Mann-Kendall trend test is applied at a significance level of 0.05, and Sen's slope is used to estimate the magnitude of the slope.  
To study the evolution of drought characteristics from 1902 to 2015, two types of analyses were carried out. First, the Mann-Kendall trend test was applied to the entire time series of SPEI and drought characteristics. Secondly, the study period was divided into two parts, with one being pre-1960 and the other post-1960. Then, descriptive statistics were calculated for each time period. The division was undertaken to isolate the effects of climate change, which is widely reported to have been accelerated since the 1960s [46; 47].
# Quality Assessment by Region and Land Cover of Sharpening Approaches Applied to GF-2 Imagery
## 3 Results
### Quantitative Quality Assessment by Land Covers
The CN method achieved the best result for the unsown farmland (11.2%), followed by the salt water in the salt pan (21.1%), bare soil (88.7%), aquaculture water (105.7%), impervious surface (177.9%), reservoir water (204.0%), shrub and grassland (204.5%), winter wheat (425.9%), canal areas (621.9%), sea water (839.8%), and forest (990.2%). The GS method achieved the best result for the unsown farmland (11.7%), followed by the salt water in the salt pan (21.9%), aquaculture water (84.3%), bare soil (89.1%), impervious surface (187.6%), shrub and grassland (193.5%), reservoir water (204.0%), winter wheat (504.6%), canal areas (598.7%), sea water (878.9%), and forest (979.1%). Generally, reducing the CC value between bands was helpful for reducing the amount of redundant information between the bands, although it could change the relationship between them, thereby affecting various indices, such as the NDVI and NDWI. Therefore, with regard to preserving the CC values between the four bands, for impervious surface, forest, shrub and grassland, bare soil, winter wheat, canal area, sea water, and salt water in the salt pan, the mIHS method can achieve the best pansharpened result, and for unsown farmland, the CN method can achieve the best pansharpened result, and for reservoir water, the PCA method can achieve the best pansharpened result, for aquaculture water, the GS method can achieve the best pansharpened result (see Figure A8 from Appendix B). Generally, for most land covers, the mIHS method was the best, and the PCA method was the worst.
## 3 Key Techniques
### Geometric Model and Material Mapping Method  
Fiber beam-column and multi-layered shell elements have been widely used to simulate beams, columns and shear walls during the nonlinear dynamic analyses of structures [34; 35; 10]. Compared with models that use solid elements, models that use fiber beam-column and multi-layered shell elements reduce the number of elements and the computational workload required, which makes the simulations of large-scale structures easier to conduct. In this study, soil-structure interaction (SSI) effects are neglected, assuming that that the soil underneath the foundations is infinitely rigid. It is worthwhile noting that previous studies have illustrated that SSI effects can significantly affect the lateral displacement demand and collapse capacity of building structures [36; 37; 38]. The classical Rayleigh damping with a damping ratio of 5% based on the initial stiffness of the building is used to model the inherent damping of the structure. Future studies should consider incorporating more accurate approaches to modeling inherent damping, as a few research works have identified drawbacks associated with the use of Rayleigh damping based on initial stiffness [39; 40; 41; 42]. In the FE model, the geometric model of a fiber beam-column element is a line [a one-dimensional (1D) element], and the geometric model of a multi-layered shell element is a plane (a 2D element). However, the geometric model in the physics engine is a solid (a 3D object). Because the geometric models of the physics engine and FE model are different, a method is proposed to convert the FE models of the fiber beam-column and multi-layered shell elements into solid objects for the physics engine.
# The 3D Product Model Research Evolution and Future Trends: A Systematic Literature Review
## 1 Introduction  
Three-dimensional (3D) product models generate value to manufacturing companies in multiple stages of the engineering, assembly, and production processes [1]. Initially used primarily as a design tool, the 3D product model focused on helping engineers create visual models of the product they intended to create. The 3D product model later moved into the production and assembly processes, helping create value in a variety of ways, from allowing operators to see how a product is configured to ensuring the right parts, tools, work instructions, and other critical components are assigned to the right stations [1; 2]. With the development of new software and technologies, the stage is now set for the 3D product model to be utilized in emerging applications and frontiers of industrial and systems engineering [3; 4]. The authors note that the 3D product model can have a large array of meanings from the virtual computer-aided design (CAD) model, to a digital mock-up, to a digital twin, or even a physical 3D model. The 3D product model application focused on in this paper is the value of bringing the virtual CAD model and digital 3D assembly mock-up to the assembly process beyond the engineering design. The authors have recognized that the 3D product models usability has increased as computer graphics have improved, mathematical models have emerged to simplify the 3D product model representations, and technology such as virtual reality glasses provide new 3D product model applications. As concepts such as artificial intelligence, robotics, and the digital twin emerge in both academia and industry, the authors aimed to understand the 3D product models role in these evolving applications. Doing so led the authors down a path ofreviewing how the 3D product model research has developed to date, which was followed by interviewing industry experts on anticipated future trends.  
The authors recognized a significant amount of research in the body of knowledge on 3D product models with similar focus topics but did not come across any research that established themes around these topics and categorized the research accordingly. This generated the question \"How has the 3D product model research evolved over time?\" and, once these themes were determined, \"Where is the research and industry applications of the 3D product model projected to head in the future?\" The authors' intent is to answer those questions and close the current gap in the research, providing the foundation for future comprehensive 3D product model research ontology. This work collects a comprehensive list of approximately 300 articles and conference proceedings that discuss the 3D product model and its applications to assembly and production processes, develops themes across the research, categorizes the research by those themes, and projects future applications and research trends.
## 2 The Hume-Rothery Electron Concentration Rule
Thus, the formation of a pseudogap at the Fermi level with a width of 0.5 to 1 eV and a height 0.2 to 0.6 times as high as the typical free electron DOS can lower the electronic energy by 30 to 50 kJ/mol [27; 28]. On the other hand, in QCs bearing TM atoms, along with the Fermi-surface-Brillouin-zone interaction mechanism due to diffraction of delocalized electrons by ordered atomic lattice planes, the structure stabilization can be influenced by the wave functions overlapping among contiguous atoms, giving rise to the formation of bonding and antibonding levels due to orbitals hybridization between neighboring Al-3p and TM-3d atomic orbitals [27]. A detailed systematic investigation of Al-based i-QCs bearing TM elements, using soft X-ray emission spectroscopy, allowed for a quantitative analysis of the partial densities of 3p and 3s,d states at the aluminum edge of the electronic structure, as well as of 3d states at the TM edge, respectively [29]. From the obtained data hybridization between 3p and d states is clearly seen in all the considered samples (see Figure 9b), naturally arising the question regarding the relative importance of covalent bonding in the final stabilization of this class of QCs [30]. Additional evidence on the important role of orbital hybridization in QCs stability come from band structure calculations of i-Cd(Yb,Ca) QCs approximant crystals, indicating that low-lying d unoccupied states play an essential role in the formation of a pseudogap due to hybridization with Cd 5p states producing orbitals just below E\({}_{\rm F}\). In this case, the Fermi energy is not located close to the bottom of the resulting pseudogap (as it is usual for QCs stabilized via the Fermi-surface-Jones-zone mechanism), but is pinned at a shoulder of the DOS [31]. Similar numerical studies for approximant crystals related to i-Ag-In-Yb QCs, which are obtained from i-Cd-Yb by replacing Cd by Ag and In (the adjacent elements to Cd in periodic table, thereby preserving the original overall e/a ratio), also yield the presence of a hybridization-induced pseudogap in the DOS close to the Fermi level. These theoretical results were, subsequently, experimentally confirmed from ultraviolet photoemission spectroscopy studies [32; 33]. Therefore, one reasonably expects the nature of chemical bonding among certain constituent atoms should play a significant role in the onset of non-metallic physical properties of QCs bearing TM elements. Accordingly, any prospect on the origin of the pseudogap at the Fermi level in the Al-Cu-(Fe,Ru,Os), Al-Pd-(Mn,Re), and Al-Cu-(Ni,Co) alloy systems should consider both metallic and covalent bonding styles in order to determine the relative number of itinerant versus localized electrons in the resulting QCs. This issue will be further discussed in Section 6.
# Ionospheric Error Models for Satellite-Based Navigation--Paving the Road towards LEO-PNT Solutions
## 3 Methodology
### Data Sources  
There are several ionospheric models in the literature to choose from in order to simulate the impact of ionospheric delay in our software, as described in Section 2. However, unlike GNSS satellites, LEO satellites do not have designated ionospheric correction models. Therefore, we aimed to derive a model that is not based on transmitted atmospheric  
Figure 3: Illustration of VTEC and STEC corresponding to a satellite signal.  
data from the satellites. Also, we wanted a model that could function offline without needing a constant connection to a server because this can add significant waiting time to the receiver processing, especially when dealing with thousands of measurements.  
The NeQuick and Klobuchar models, while good as a benchmark, do not satisfy our target constraint of having an extensible, file-independent solution that could be used for any satellite constellation or scenario since they rely on broadcasted parameters in ephemeris messages. In our opinion, neural network models are also not highly suitable due to their complexity and regional limitations. The IRI model, which was selected as a second benchmark, has an open-access Matlab implementation. Still, it also requires an online connection to retrieve information about the electron density and TEC content from its server. However, the IONEX files provided by the IGS could fulfil our needs. The IGS was proven to be better than the Klobuchar and NeQuick models in resolving the ionospheric delay for single-frequency receivers [6], and many researchers have tested its accuracy and relied on it as a benchmark to test their model [45; 55; 56]. For these reasons, we chose to build our model upon the data extracted from the IGS IONEX files.
Adaptive Least-Squares Collocation Algorithm Considering Distance Scale Factor for GPS Crustal Velocity Field Fitting and Estimation  
[PERSON]  
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[PERSON] [PERSON] [PERSON] [PERSON] [PERSON]  
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Footnote 1: email: 29 October 20  
observation points and can accurately describe the regional crustal movement trend [6]. The LSC algorithm has been used to estimate crustal movement signals from GPS velocity fields [9; 10; 11; 12; 13; 14; 15]. It has also been used in various earth science fields to control systematic and anomaly errors in GIS spatial data [16], detect outliers in multibeam bathymetric data [17], solve common point coordinate errors in 3D coordinate transformation [18], improve the accuracy of mobile light detection and ranging (LiDAR) systems in hostile environments [19], improve the results of downward continuation values of airborne gravity data [20], and refine the local covariance model of gravity anomalies [21].  
The reliability and accuracy of the LSC algorithm is based on the exact covariance function; however, at present, it is difficult to establish an ideal empirical covariance function. Unreliable covariance function can cause inconsistencies in observation noise and signal variance. Furthermore, in view of the complexity of the measured data, during the process of using Gaussian functions (the most commonly used empirical covariance function) as an empirical covariance function to establish the mapping of distance and covariance, the covariance will appear negative, which violates the positive definiteness of the Gaussian function. In this case, the commonly used approach is to avoid the negative value, which affects the data utilization and leads to the reduction in the reliability of the fitting model.  
In this study we propose an adaptive least-squares collocation algorithm considering the distance scale factor and show that the new algorithm has great advantages in actual GPS observation studies. The improvements of the new algorithm over previous ones are as follows: the distance scale factor is first introduced to establish a comparative relationship between the covariance of observations and the cross-covariance of two observations with the farthest distance. This step ensures the positive definiteness of the data and allows a reasonable Gaussian model parameter to be obtained. It also weakens the systematic error of the model. Then, on the basis of the first step, the variance component estimation method (VEM) is created to construct an adaptive factor. This step is further adjusted to ensure a coordinated weight ratio between the signals and the observation so as to improve the accuracy of the estimated points.
## 3 Results
### Efficiency and Photomixing Results  
In a recent publication we have emphasized not only the high THz output power of the pulsed QD-array device, but also the photonic-to-THz power conversion efficiency [8]. From Figure 3a, we calculate a conversion efficiency of 117 uW/65 mW = 0.2%. The conversion efficiency has already been emphasized and improved in 1550-nm THz photoconductive devices [9], and the present results are amongst the highest 1550 nm-driven THz efficiencies ever reported. We attribute this performance in large part to the superradiance phenomenon, as supported by Figure 4b,d.  
Further support for the superradiance is provided by pulsed vs. cw (photomixing) results. As described above, photomixing measurements were carried out on the same devices (Figure 2) as the pulsed measurements. Although the total 1550 nm power (295 mW) was much higher than  
Figure 4: (**a**) The waveform in time domain when the pulsed device was pumped with 780 nm pulsed laser. (**b**) The waveform in time domain when the pulsed device was pumped with 1550 nm pulsed laser. (**c**) The power spectrum of the 780 nm driven radiation. (**d**) The power spectrum of the 1550 nm driven radiation.  
Figure 5: Waveform of a commercial InGaAs-based switch device under 1550 nm pump.  
in the pulsed experiments, the heavily infrared (IR) filtered maximum average THz power from the photomixing was only \(\sim\)3.4 nW at 337 GHz as measured with the cross-calibrated Golay cell detector (Figure 6). This corresponds to a conversion efficiency of \(1.2\times 10^{-8}\). The power dropped continuously as the difference frequency increased but was still detectable up to 1.2 THz, consistent with the THz signal coming from photomixing and not just heating. Thus the broadband pulsed-mode is \(\sim\)\(1.5\times 10^{5}\) more efficient than the narrowband photomixing mode, which is significantly greater than in cross-bandgap-driven (e.g., 780 nm) THz photoconductive devices. Since superradiance is only expected to be significant in 1550 nm pulsed mode (see below), it is the logical discriminator.
## 1 Introduction
Therefore, it is especially important to slow down the capacity decay of the battery while driving. Charge-discharge behavior, usable capacity, and resistance are the most common parameters used to describe the capacity decay of lithium-ion batteries [18]. Studies have shown that battery degradation is related to factors such as temperature [19], charge-discharge rate [20], depth of discharge [21], and charge-off voltage [22; 23]. Based on these parameters affecting battery degradation, [PERSON] et al. [24] studied the capacity decay process of LiFePO4 batteries and proposed a semi-empirical model based on experimental data on battery capacity loss. [PERSON] et al. [25] introduced Ah throughput, a quantitative indicator related to battery life, to measure fuel economy and battery aging in hybrid electric vehicles and extend battery life without affecting vehicle driving performance. [PERSON] et al. [26] established a cost function combining energy loss and capacity drop, and used dynamic programming to obtain the optimal torque curve for vehicles traveling on ramping roads. From a careful analysis of the above studies, it can be found that some researchers optimize vehicle acceleration [27] or motor torque [28] by considering energy consumption when developing electric vehicle driving strategies, but ignore the effect of battery capacity reduction during driving. Some researchers have studied battery capacity degradation, taking into account battery degradation caused by driving on slopes [29], or optimizing to reduce costs incurred during driving [30]. Although research into saving battery energy and extending battery life is receiving increasing attention, according to the results of the study cited in reference [31] this topic has not yet been fully researched. [PERSON] et al. optimized energy consumption and battery life by planning vehicle speed in a car-following mode [32]. [PERSON] et al. improved driving economy and reduced battery aging rates by restricting battery current and torque [33], but they lacked a direct description and quantitative model of the battery capacity decay rate. This paper explores the performance of light-duty electric vehicles in practical use by studying battery consumption during the driving process in the car-following mode, and establishes a semi-empirical model for battery aging which considers the effect of battery capacity degradation characteristics. Inaddition, this paper also designs an AMPC controller that considers the safety, comfort, following, and economic aspects of vehicle driving to determine the driving strategy of the vehicle. Therefore, the research in this paper has important practical application value for extending battery life, improving the energy utilization efficiency of light-duty electric vehicles, and optimizing their driving range.
## 2 Materials and Methods
### In Vitro Trials-Effect of photosensitization on A. flavus Spores
#### 2.5.2 Evaluation of Photosensitization Effect on _A. flavus_ Spores  
For photosensitization trials, 1 mL of _A. flavus_ spore suspension (equivalent to 10\({}^{4}\) CFU\(\cdot\)mL\({}^{-1}\)) was mixed with 1 mL of curcumin solution in a small Petri dish (35 mm \(\times\) 10 mm), followed by incubation for 10 min at room temperature in dark before illumination. Peptone water (0.1%; \(w/\
u\)) was used instead of photosensitizer in the negative control (P\({}^{0}\)L\({}^{0}\)) and light treatment (P\({}^{0}\)L\({}^{+}\)). Then, the Petri dish (without lid) was placed under the light source with 10 cm distance and illuminated at 430 \(\pm\) 3 nm. After treatment, 100 \(\upmu\)L aliquots of the photosensitized mixtures were plated onto MEA and incubated at 25 \({}^{\circ}\)C for 72 h to determine the Colony-Forming Unit (CFU) using a colony counter (Stuart Scientific, Stone, UK). The fungal survival was calculated by log reduction (LR) of CFU following Equation (2):  
\[\text{LR}=\text{Log}_{10}\ \text{(A)}-\text{Log}_{10}\ \text{(B)} \tag{2}\]  
where: A: CFU\(\cdot\)mL\({}^{-1}\) of the negative control; B: CFU\(\cdot\)mL\({}^{-1}\) of photosensitized spores.