esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Fermentation Diversity and Dynamics
Both _Pantoea_ and _Enterobacter_ are known for their diverse metabolic capabilities, including the production of cellulases, pectinases, and xylanases [27; 28]. These enzymes are crucial for breaking down complex carbohydrates found in plant materials, facilitating the release of simpler sugars that are more readily fermentable. _Pantoea_, for instance, has been studied for its role in plant growth promotion and biological control, with a focus on its enzymatic activities related to plant interactions [29]. Similarly, _Enterobacter_ species are known for their metabolic versatility, including the ability to degrade plant-derived polysaccharides [30; 31]. The metabolic activities of these bacteria can lead to the production of various metabolites during fermentation. These include organic acids, alcohols, and esters, which are key contributors to the flavor profile of fermented coffee [2]. However, the dominance of _Pantoea_ and _Enterobacter_ presents a notable deviation from the typical microbial profile observed in coffee fermentations in other regions, where LAB are often dominant [5; 12]. The prominence of _Pantoea_ and _Enterobacter_ in this study may reflect a natural adaptation to the specific environmental conditions of subtropical areas, processing methods, or the intrinsic qualities of the coffee beans. Understanding these variations is crucial for tailoring fermentation practices to enhance desired flavor profiles and improve coffee quality. The contrasting microbial dominance observed here could also indicate the potential need for an inoculation process in subtropical coffee fermentation. At the genus level, _Fusarium_, _Cladosporium_, and _Penicillium_ dominated the fermentation process. _Fusarium_ showed a significant increase in abundance from 28.80 (0 h) to 57.54% (24 h), while _Cladosporium_ and _Penicillium_ showed fluctuations during the fermentation. The decline of fungal genera throughout fermentation (e.g.,: _Bonordeniella; Phaeosporia_) may be due to changes in environmental conditions during coffee processing, as previously mentioned. _Fusarium_ and _Cladosporium_, which exhibit stronger dominance as fermentation progresses, possess enzymatic apparatuses that enable them to utilize complex carbohydrates present in coffee pulp [32; 33]. This capability allows them to thrive and outcompete other microorganisms as the fermentation environment becomes more selective. _Fusarium_ species are known for their production of a wide array of enzymes, including cellulases and xylanases [34]. _Cladosporium_ also possesses enzymes capable of degrading complex polysaccharides [33]. These enzymatic activities enable both _Fusarium_ and _Cladosporium_ to access nutrients from the coffee pulp, supporting their growth and dominance during fermentation, as recently suggested by [PERSON], [PERSON], and [PERSON] and [PERSON] et al. [13; 17; 26].
# Precipitation Estimation Using FY-4B/AGRI Satellite Data Based on Random Forest
## 2 Materials and Methods
### Methods
#### 2.3.3 Selection of Feature Variables
There are 18 feature variables in the day model and 16 feature variables in the night model. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Feature Variables** & **Day** & **Night** \\ \hline \multirow{3}{*}{CTH} & \(\Delta T_{6,25-10.8}\) & \(\Delta T_{6,25-10.8}\) \\  & \(\Delta T_{7,42-12}\) & \(\Delta T_{7,42-12}\) \\  & \(IR_{10,8}\) & \(IR_{10,8}\) \\ \multirow{3}{*}{CTT} & \(Var(IR_{10,8})\) & \(Var(IR_{10,8})\) \\  & \(Gm(IR_{10,8})\) & \(Gm(IR_{10,8})\) \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Physical-related features used by the model during the day and at night and their specific expressions.
###### Abstract  
An experiment was done to explore the effects of two virtual display systems on the accuracy of exocentric distance judgment and position. Sixteen participants viewed animated virtual targets using either a head-mounted display (HMD) or a stereoscopic widespread display (SWD). The virtual targets have been shown, one at a time, at three depth levels and with two corresponding exocentric distances and three target sizes at each target distance and, afterward, via pointing by holding a stick to estimate the exocentric distance and position of each target. The position data were collected using an OptiTrack motion capture system. The results showed that the accuracy of exocentric distance judgment was higher with the head-mounted displays than with the stereoscopic widespread displays. In addition, higher position accuracy in the X-direction was obtained from the stereoscopic widespread displays, whereas no significant difference was observed in position accuracy in the Y-direction. However, it is possible that the HMD could give better accuracy in both exocentric distance and position judgments in the frontal plane, if the HMD had been perfectly mounted and flawlessly fit the participant's eyes. The result also revealed that exocentric distance judgment was significantly higher at the farthest target distances than at the nearest distance. Similarly, the position accuracy significantly increased as exocentric distance decreased. Moreover, engineers may allude to the findings as the evidence from the study suggests that the intermediate target distances might be fitting or ideal distances to design and structure 3D applications.  
exocentric distance; head-mounted display; stereoscopic widespread display 2020
## 2 Overview of Electric Vehicles and Electric Taxis in Hong Kong
### Initiation of Electric Taxis in Hong Kong  
To become environmentally friendly, the government and automobile companies tried to manufacture more sustainable vehicles, such as hybrid vehicles and electric vehicles [21; 22]. The government launched Stage Two of the project in the late 2000s to early 2010s, with the mass supply of production of electric vehicles. The government also set up a steering committee in 2009 in order to coordinate EV promotion strategies and study the feasibility of installing charging facilities in the Hong Kong government multistory car parks [17]. In 2011, the government offered a Gross Floor Area (GFA) concession for car parks in new developments, to require and encourage the provision of charging facilities. At the same time, the government also set up the Pilot Green Transport Fund, in order to encourage the public transport sector to try out green innovative transport technologies and also to promote the technological development of electric vehicles, especially for electric commercial vehicles, for instance, taxis [23].  
At the end of 2012, some automobile companies introduced hybrid vehicles, but they failed to access the Hong Kong market because of the high purchasing price. In 2013, BYD Automobile Co. Ltd. introduced 45 electric taxis through the Pilot Green Transport Fund. However, because the charging time of electric taxis is extremely long, there were insufficient charging facilities. In addition, many users thought that electric vehicles were unlikely to replace conventional petrol cars, as the available driving range of petrol cars was much larger. However, the government has waived the First Registration Tax (FRT) on purchasing electric vehicles, which could attract users to change from petrol to electric vehicles. The plan eventually failed, and BYD Automobile retreated from Hong Kong in 2014. Despite this, it tried to re-enter the Hong Kong market in 2021. BYD introduced the second generation of the E6 model for both private cars and Hong Kong taxis, and trials will be started in 2022 [24].  
Because people have not been eager to purchase electric vehicles in the past few years, the government launched Stage Three in 2014, with a longer driving range of electric vehicles. The price of electric vehicles, after being adjusted, is more comparable to conventional petrol cars. Additionally, the FRT policy was extended, and the government even revised the FRT concession with a \"One-for-One Replacement\" scheme to make sure that the policy would not be affected by high-priced electric cars [17]. As a result of these effective policy incentives, the penetration of EVs has been developed in-depth in Hong Kong in the past five years, as shown in Figure 1.
## 4 Results and Discussion
### Results for EIS
#### 4.1.2 EIS of Solutions after Addition of Ethanol  
Based on the results obtained in Section 4.1.1, the frequency range from 50 kHz to 300 kHz was analysed for the ternary solutions. The charts in Figure 6a-f shows the results from the experiment after the addition of ethanol. All the experimental results were acquired in the static solution of 100 mL. The three ethanol to water ratios of 0.33, 0.66, and 0.99 were analysed. The sucrose to ethanol ratio at 0.33 ranged from 1 to 2, at 0.66 it ranged from 0.5 to 1, and the sucrose to ethanol ratio at 0.99 ranged from 0.33 to 0.66. Figure 6a,c,e and Figure 6b,d,f show the changes in impedance and phase angles, respectively. Impedance magnitude, as the representation of the dielectric properties of the solution, increased, whereas the phase angle decreased as the concentration ratio of the sucrose to ethanol in the solution increased. This trend was observed for every set of concentrations with constant ethanol to water ratios (0.33, 0.66, and 0.99). Similar qualitative behaviour was obtained in the sucrose solution without ethanol addition, as seen in Figure 5c,d.  
Figure 5: Impedance magnitude and phase response for sucrose solution before ethanol addition from 1 kHz to 1 MHz (**a**,**b**) from 50 kHz to 300 kHz (**c**,**d**).
# Unified Performance Analysis of Direct Air-to-Underwater RF/UWOC Systems
## 2 System and Channel Models
The simulation results are in good agreement with the numerical simulation curve, indicating that the derived results are correct. To investigate the impact of EGG parameters \(a\) and \(b\) on the system BER, Figure 7 shows the impact of EGG parameters \(a_{0}\) and \(\beta\) on the BER. We assume that all average signal-to-noise ratios are equal and that parameter \(c\) is a positive integer. It can be observed from the graph that as a increases, the error rate decreases, while as \(b\) increases, the error rate increases. At this point, for convenience, we assume \(c=1\). From the figure, it can be seen that when the distribution function of the atmospheric turbulence channel is \(\mathcal{F}\) distribution, \(\alpha_{0}=0.457\) and \(\beta=0.175\), and the signal-to-noise ratio is \(20\) dB, the BER of the system is close to \(10^{-8}\). When the signal-to-noise ratio of EGK and \(\alpha-\mu\) is \(20\) dB, the BER is \(10^{-6}\) and \(10^{-4}\), respectively. The BER obtained by using EGK distribution and \(\alpha-\mu\) distribution in the RF link is higher than that of the \(\mathcal{F}\) distribution. The lower the BER, the better the system performance. The simulation results are in good agreement with the numerical simulation curve, indicating that the derived results are correct. Figure 5: Performance of BER under different fog conditions. capacity is 5 and 15 lower than when the RF link adopts \(\mathcal{F}\) distribution, respectively. As the fog concentration increases, the signal is absorbed and scattered. This leads to a decrease in signal reliability and thus affects transmission rate. The simulation results show good agreement with the numerical simulation curve, indicating that the derivation results are correct. In the UWOC link, the parameters of the EGG distribution also have a significant impact on the system performance. Figure 9 shows the impact of parameters on the system channel capacity. We assume that all average signal-to-noise ratios are equal and that parameter \(c\) is a positive integer. It can be observed from the graph that as the parameter \(u_{1}\) increases, the stability and transmission rate of the channel \(c\) increase, while as the parameter increases, the transmission rate of the channel decreases. Similarly, taking the \(\mathcal{F}\) distribution as an example, when \(u_{1}=0.51\), \(c=1\), and the signal-to-noise ratio is 16 dB, the channel capacity of the system reaches 15. When the signal-to-noise ratio is 20 dB, the channel capacity can reach 26. The simulation results match well with the numerical simulation curve. Figure 8: Effects of fog conditions on channel capacity under different atmospheric turbulence.
# A Quadrilateral Geometry Classification Method and Device for Femtocell Positioning Networks
## 6 Conclusions  
This paper proposes a novel NMLP geometry classifier and IGT algorithm for autonomously reducing the positioning error of four-FeNB TDOA measurements. Three optimum geometry disposition decision criteria are analyzed for the square, lozenge, and other IQ shape of the four FeNBs, for positioning the moving MUE. The derived analytical expressions are generally applicable to geometries where the MUE is surrounded by the selected FeNBs. The simulation results have confirmed that the proposed NMLP geometry classifier and optimum geometry disposition decision criteria can provide accurate outdoor geo-location information on the MUE for indoor femtocells to support its quality of services in HetNet. A comparison of the analytical results with simulations using the typical geometries of outdoor positioning systems shows good agreement.  
The computational burden is mainly caused by the offline IGT algorithm simulations pertaining to the construction of the training data. Once the initial learning of the NMLP is finished using the collected training data to optimize network weights based on the NMLP network outputs of five neurons for five different shapes, the additional computation overhead in NMLP is light. Since the operations of the NMLP geometry classification are executed in the server, it is assumed that the computation ability of the server is powerful enough to determine the optimal geometry disposition for femtocell positioning networks. The information regarding the training data that governs the NMLP geometry classification operation of femtocell positioning networks is stored in a database. As soon as a new operation condition occurs, the new training data is generated from the simulation and included in the database to rerun the IGT training procedure of Figure 3. The simulation results show that the proposed method is particularly suitable for the application of MUE positioning with a huge number of FeNBs.  
How to optimally determine four FeNBs to position the UE in indoor scenarios is another hot research topic in current telecommunication industries and academics. The proposed NMLP geometry classifier and IGT algorithm will be applied to the study of indoor femtocell positioning networks.  
**Acknowledgments:** The research work was supported by Ministry of Science and Technology, Taiwan, R. O. C. (MOST 105-2218-E-155-001).  
**Author Contributions:** [PERSON] conceived, designed and wrote the paper; [PERSON] and [PERSON] performed the experiments; [PERSON], [PERSON] and [PERSON] analyzed the data.  
**Conflicts of Interest:** The authors declare no conflict of interest.
In addition, vegetation drought changes with climatic region. Generally, arid regions exhibit sparse vegetation due to poor soil conditions; however, their contributions to these areas cannot be disregarded [37]. Similar to climatic regions, different vegetation types exhibit different sensitivities when subjected to drought [38]. grasslands are the most responsive and vulnerable vegetation type [39], but there is still spatial heterogeneity in vegetation sensitivity to drought [40]. These phenomena are scientific issues of global concern to ecologists, necessitating further exploration and validation. We focused on Central Asia, one of the largest arid regions in the Northern Hemisphere [41]. Due to sparse vegetation and poor soil, deserts and grasslands are the major land use types [42], and the ecosystem is extremely fragile and susceptible to environmental impacts [43; 44]. Nevertheless, Central Asia's economy is still primarily based on agriculture, making the region more vulnerable to drought events [45]. Furthermore, as the core region linking the Eurasian continent, the terrestrial ecosystem in this area is perennally plagued by drought stress, which may impact the achievement of Sustainable Development Goal (SDG) 15 (protect, restore, and promote sustainable use of terrestrial ecosystems; combat desertification) [46; 47]. Therefore, in the context of escalating drought events driven by global climate change, it is imperative that we gain a thorough understanding of the lossesand recovery of terrestrial ecosystems following drought as well as the primary causes contributing to these losses. This is also a prerequisite for guiding regional ecological and environmental management. This study primarily attempts to construct a comprehensive vegetation assessment index in regard to drought conditions. By utilizing this index, the focus is on assessing post-drought vegetation loss and recovery under different climatic conditions and vegetation types and comparing it with single vegetation assessment indices. Therefore, the objectives of this study are (1) to utilize MODIS data to construct the temperature vegetation dryness index (TVDI) for the Central Asia region from 2000 to 2020 to monitor vegetation drought conditions; (2) to construct the remote sensing vegetation index (RSVI) based on four vegetation indices--EVI, FVC, GPP, and LAI--and evaluate its effectiveness in monitoring vegetation during drought periods; (3) to investigate the differences in post-drought vegetation loss and recovery times in different climatic regions and vegetation types in Central Asia using the RSVI and compare it with four other vegetation indices; and (4) to further analyze the relative sensitivity of vegetation change to climate factors. The research findings will provide new methodological support for quantitatively assessing post-drought vegetation loss and recovery in the arid regions of Central Asia, offering crucial theoretical groundwork for maintaining terrestrial ecosystem stability and promoting sustainable development of terrestrial ecosystems.
# Pocs-Augmented CycleGAN for MR Image Reconstruction
## 2 Materials and Methods
### The Structure of the Entire POCS-Augmented CycleGAN (POCS-CycleGAN)
The function of this training process is to assist the first training process to train the generator \(G_{u2f}\) as accurately as possible. After training the entire CycleGAN for several epochs (P), the output of \(G_{u2f}\), \(\hat{y}\) was inversely transformed back to the k-space and updated by POCS. The POCS-processed output images of the first-pass CycleGAN of all training samples were added to the original training dataset to be used as the new and augmented training data for the second-pass CycleGAN. The whole training process is illustrated in Algorithm 1. Figure 2: The discriminator \(D_{y}\) was trained first by fully sampled image \(y\). Then, generator \(G_{u2f}\) and \(G_{f2u}\) were trained in order. The input of \(G_{u2f}\) is the undersampled image, and the output of \(G_{u2f}\) is reconstructed image \(\hat{y}\). Then, \(\hat{y}\) was fed into discriminator \(D_{y}\) and generator \(G_{f2u}\) simultaneously. The discriminator was expected to distinguish \(y\) and \(\hat{y}\). For \(G_{f2u}\), its output should be the reconstructed zero-filled images \(\hat{y}_{u}\). We forced \(\hat{y}_{u}\) to be similar to \(y_{u}\) by minimizing the value of \(\left\|\hat{y}_{u}-y_{u}\right\|_{l1}^{1}\).
###### Abstract  
This paper presents a low-power CMOS receiver with a complex continuous-time delta-sigma ADC designed for IoT applications in the 2.4 GHz band. The architecture employs a quadrature bandpass continuous-time delta-sigma ADC optimized for Bluetooth Low Energy (BLE) standards, achieving an ENOB of 10.9 bits while consuming only 0.81 mW from a 1.0 V supply. The receiver demonstrates impressive performance metrics, including a sensitivity of \(-95\) dBm at a \(10^{3}\)-bit error rate, an image rejection ratio of 54.2 dBc, and a spurious-free dynamic range of 79.8 dBc. Operating at a 1.5 MHz intermediate frequency with a 2 MHz bandwidth, the ADC achieves superior energy efficiency with a figure of merit (FOMW) of 103.2 fJ/conv. Implemented in 28 nm CMOS technology, the complete receiver occupies 0.375 mm\({}^{2}\) for the RF front-end and 0.145 mm\({}^{2}\) for the ADC while consuming 4.08 mW total power, making it well suited for battery-powered IoT sensor nodes requiring both power efficiency and reliable wireless connectivity.  
Bluetooth Low Energy (BLE); continuous-time delta-sigma ADC; complex bandpass ADC; CMOS; Internet of Things (IoT); low-power receiver; wireless sensor networks (WSN); low-IF architecture; image rejection; energy efficiency +
Footnote †: journal: Sensors  
Academic Editors: [PERSON] and [PERSON]  
Received: 3 February 2025  
Revised: 5 March 2025  
Accepted: 7 March 2025  
Published: 12 March 2025  
**Citation**: [PERSON]-S. A Low-Power Complementary Metal-Oxide-Semiconductor Receiver with Quadrature Bandpass Continuous-Time Delta-Sigma Analog-to-Digital Converter for IoT Applications. _Sensors_**2025**, 25, 1748.  
[[https://doi.org/10.3390/s25061748](https://doi.org/10.3390/s25061748)]([https://doi.org/10.3390/s25061748](https://doi.org/10.3390/s25061748))  
Copyright: 02 2025 by the author.  
Ulonsec 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/)).
# Distributed Passive Actuation Schemes for Seismic Protection of Multibuilding Systems
###### Abstract  
In this paper, we investigate the design of distributed damping systems (DDSs) for the overall seismic protection of multiple adjacent buildings. The considered DDSs contain interstory dampers implemented inside the buildings and also interbuilding damping links. The design objectives include mitigating the buildings seismic response by reducing the interstory-drift and story-acceleration peak-values and producing small interbuilding approaches to decrease the risk of interbuilding collisions. Designing high-performance DDS configurations requires determining convenient damper positions and computing proper values for the damper parameters. That allocation-tuning optimization problem can pose serious computational difficulties for large-scale multibuilding systems. The design methodology proposed in this work--(i) is based on an effective matrix formulation of the damped multibuilding system; (ii) follows an \(H_{\infty}\) approach to define an objective function with fast-evaluation characteristics; (iii) exploits the computational advantages of the current state-of-the-art genetic algorithm solvers, including the usage of hybrid discrete-continuous optimization and parallel computing; and (iv) allows setting actuation schemes of particular interest such as full-linked configurations or nonactuated buildings. To illustrate the main features of the presented methodology, we consider a system of five adjacent multistory buildings and design three full-linked DDS configurations with a different number of actuated buildings. The obtained results confirm the flexibility and effectiveness of the proposed design approach and demonstrate the high-performance characteristics of the devised DDS configurations.  
energy-dissipation systems; distributed damping systems; optimal placement; multibuilding systems; seismic protection; hybrid genetic algorithm; parallel computing; bounding protection Article