esa-sceva/satcom-chunk-collection huggingface dataset:
# Symmetry of the Non-Analytic Solution of the Dirac Equation Inside the Proton of Hydrogen Atoms
###### Abstract  
In one of our previous papers, we obtained a general class of potentials inside the nucleus, such that the singular solution of the Dirac equation for the S-states of hydrogen atoms outside the nucleus can be matched with the corresponding regular solution inside the nucleus (the proton) at the boundary. The experimental charge density distribution inside the proton generates a particular case of such potentials inside the proton. In this way, the existence of the second kind of hydrogen atom was predicted: atoms having only S-states. This theoretical prediction was then evidenced by several different types of atomic experiments and by astrophysical observations. In the present paper we provide the following new results. First, we show that the solution of the Dirac equation inside the proton can be (and is) found within the class of functions that are _non-analytic_ at r = 0--in distinction to the traditional practice of limiting the search for the solution by the class of analytic functions. We demonstrate that this non-analytic solution inside the proton can be matched at the proton boundary R with the corresponding singular solution outside the proton regardless of the particular value of R. Second, we show that the interior and exterior solutions are _scale-invariant_ with respect to the change of the boundary R between these two regions. Such invariance is the manifestation of a _new symmetry_--in addition to the previously discussed symmetries of the Dirac equation in the literature. Third, based on the new, more accurate results for the wave function inside and outside the proton, we revisit the resolution of the neutron lifetime puzzle initially outlined in our previous papers. On the basis of the more accurate calculations, we reconfirm that (A) the 2-body decay of neutrons produces overwhelmingly the SFHA (rather than the usual hydrogen atoms) and (B) the strengthened-in-this-way branching ratio for the 2-body decay of neutrons (compared to the 3-body decay) is in excellent agreement with the branching ratio required for reconciling the neutron lifetime values measured in the trap and beam experiments, so that the neutron lifetime puzzle seems to be indeed resolved in this way.  
Dirac equation; non-analytic solution; new symmetry; second flavor of hydrogen atoms; two-body decay of neutrons; dark matter +
Footnote †: journal: Physics Letters B  
**[PERSON]**  
Physics Department, Auburn University, 380 Duncan Drive, Auburn, AL 36849, USA; [EMAIL_ADDRESS]
## 2 Materials and Methods
### Discrete Wavelet Transform (DWT)  
Wavelet transform decomposition (WTD) can be generally classified as continuous wavelet transform (CWT) and discrete wavelet transform (DWT) [68; 69]. DWT requires less time of the arithmetic processes, and is easier to implement than CWT [68; 70]. A fast DWT algorithm requires four filters for perfect implementation (e.g., decomposition low-pass, decomposition high-pass, reconstruction low-pass, and reconstruction high-pass) [68; 71; 72; 73]. The low-pass filter for decomposition and reconstruction categories permits the interpretation of low frequency components, while the high-pass filter approves the investigation of high frequency components [72; 74]. The multi-resolution approach using [PERSON]'s DWT algorithm can be explained as a process to depict 'approximation' and 'details' for an underlying signal. An approximation produces a conventional trend of the original signal, while the details provide its high-frequency components [72; 73; 75]. The feature reports for [PERSON]'s DWT algorithm can be found in [PERSON] [76] and Percival and Walden [77]. Figure 2 shows [PERSON]'s DWT algorithm for three-level decomposition [73].
## 2 Materials and Methods
### Post-Questionnaires  
The post-questionnaire consisted of two parts. A comprehensive questionnaire for patients and therapists assessed the system's usability. It contained the following categories: usefulness, ease of use and learnability, interface quality, interaction quality, reliability, satisfaction, future use, and intention to use, based on the TUQ [17]. The intention to use questions originated from the Technology Usage Inventory (TUI) [18]. The format was a 7-point Likert scale, where one indicated \"completely disagree\" and seven signified \"completely agree.\"  
The second part consisted of open questions, different for patients, therapists, and relatives. For patients, twelve questions addressed the experience with the combined therapy concept (therapy with the platform, potential obstacles, motivation, advantages, willingness to pay, and therapy progress).  
For therapists, twelve questions focused on the user experience (e.g., system evaluation, obstacles, most used features, advantages, and disadvantages) and organizational aspects of the therapy, such as the number of therapy sessions per week and integrability into daily work life with the time needed to learn to use the system, evaluation of the quality of teletherapy sessions compared to standard therapy, or preparation of exercises. Furthermore, four patient-related questions were asked (patient exercised more or less, patient's motivation, the therapist's rating of the system, and overall satisfaction).  
Relatives who supported the patient in using the technology platform were asked four questions on demographic data and ten questions on their support in using the technology platform. The post-questionnaires can be found in Supplementary Materials S.2, S.4, and S.5.
###### Abstract  
The climate anomaly in the Amazon River basin (ARB) has a very important influence on global climate change and has always been the focus of scientists from all over the world. To fill the 11-month data gap between Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) missions, we fused the TWSC results from six GRACE solutions by using the generalized three-cornered hat and the least square method to improve the reliability of TWSC results, and then combined Swarm data to construct an uninterrupted long time series of a TWSC-based drought index (GRACE/Swarm-DSI). The drought index was used to detect and characterize the drought events in the ARB between 2003 and 2020. The results show that GRACE/Swarm-DSI has a strong correlation with Self-Calibrating Palmer Drought Severity Index (SCPDSI) (0.6345), Standardized Precipitation Evapotranspiration Index-3 (SPEI-3) (0.5411), SPIE-6 (0.6377) and SPIE-12 (0.6820), and the Nash-Sutcliffe efficiency between GRACE/Swarm-DSI and the above four drought indices are 0.3348, 0.2786, 0.4044 and 0.4627, respectively. Eleven drought events were identified in the ARB during the study period, and the 2005, 2010 and 2016 droughs are the most severe and the longest. The correlation between GRACE/Swarm-DSI and precipitation (PPT) (the correlation coefficient is 0.55 with a 2-month delay) is higher than that of evapotranspiration (ET) (the correlation coefficient is \(-0.18\) with a 12-month delay). It explains that less PPT is the main cause of drought events in the ARB. The influence of PPT is greater in the plains than the one in the mountains and the response time of GRACE/Swarm-DSI to PPT is 1-2 months in most regions. Our results provide a certain reference for the hydrological application of the Swarm model in filling the gap between GRACE and GRACE-FO missions.  
ombined drought index; long time series; Amazon River basin; time variable gravity field model 2022142887. [[https://doi.org/10.3390/rs14122887](https://doi.org/10.3390/rs14122887)]([https://doi.org/10.3390/rs14122887](https://doi.org/10.3390/rs14122887))
# Robust Backstepping Control Applied to UAVs for Pest Recognition in Maize Crops
## 6 Detection of Pest in Corn Leaves
### Vision System  
The modules of the vision system include the camera and the image processing (a PC and MATLAB software). The natural light illuminates the plants to be inspected. The GoPro HERO8 Black camera [36] is mounted under the UAV frame (see Figure 13).  
While the quadrotor flies over the crops, the camera lens captures and sends images to the camera sensor in the form of light. This sensor converts this light to a digital image that is then stored in the camera's memory for later analysis. For the image processing, the \"Color Thresholding\" toolbox is used (included in MATLAB Software), in which the interesting areas in the analyzed images are selected based on the color spaces: [PERSON], Green, Blue (RGB); Hue, Saturation, Value (HSV); Luma, Blue and Red chromaticity (YCbCr) and  
Figure 13: UAV with the GoPro HERO8 Black camera.  
\begin{table}
\begin{tabular}{l c c} \hline \hline  & **Trajectory Tracking** & \\ \hline
**Performance Index** & **BS** & **PD** \\ \hline \(J_{\tau_{\varphi}}\) & 6051.2 & 6662 \\ \(J_{\tau_{\varphi}}\) & 7337 & 8661 \\ \(J_{u_{\star}}\) & 519.647 & 662.5175 \\ \(J_{\tau_{\varphi}}\) & 802.8 & 848.2 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Comparison of absolute control values during the trajectory tracking phase.  
Luminosity, Red/Green and Yellow/Blue chromaticity coordinates (CIE-Lab). This is done by applying segmentation methods on the images; in this regard, image segmentation is a processing technique that refers to the extraction of useful information from a frame to facilitate observation and analysis since the rest of the image content is not useful for the purpose, i.e., if within an image the red color is selected, everything that is not red is discriminated by the segmentation method. This toolbox is selected because it allows comparing the intensity level, pixel by pixel, with a certain threshold previously defined by the user. To establish this threshold, it is necessary to analyze the interest region to be isolated, finding a characteristic and exclusive color level.
# Rapid Classification of Wheat Grain Varieties Using Hyperspectral Imaging and Chemometrics
## Materials and Methods
### Hyperspectral Image Acquisition and Correction  
Some relevant parameters need to be adjusted to obtain explicit and distortionless images before hyperspectral image collection in order to assure each sample's availability. In this study, the height between lens of CCD camera and samples was set to 15 cm, the exposure time was set to 3 ms, and the mobile platform was set at a constant speed of 13 mm/s along the X-axis. Without adhesion, the wheat seeds were randomly put on a black plank and then placed on the mobile platform to acquire hyperspectral images. One hyperspectral image was obtained through every scanning. The number of wheat seeds might be inconsistent for different images. The eventual number of wheat seeds was calculated by related functions that are included in our written spectral extraction algorithm in Matlab.  
Before extracting spectra and conducting spectral analysis, the raw hyperspectral images needed to be corrected by using the white and the dark reference images. Among them, the white reference image was obtained by using a white Teflon tile with 100% high-reflectance and the dark reference image was obtained by covering the lens with its opaque cap completely while turning off all of the lights. By calculating the Equation (1), below, the corrected images can be acquired.  
\[I_{C}=\frac{I_{\text{raw}}-I_{\text{dark}}}{I_{\text{white}}-I_{\text{dark}}} \tag{1}\]  
where \(I_{C}\) is the corrected hyperspectral image, \(I_{\text{{raw}}}\) is the raw hyperspectral image, and \(I_{\text{{white}}}\) and \(I_{\text{{dark}}}\) are the white and the dark reference images, respectively.
# AUV-Aided Optical--Acoustic Hybrid Data Collection Based on Deep Reinforcement Learning
## 4 Multi-Modal Data Collection Analysis
### Energy Consumption Associated With Data Collection  
To satisfy the energy constraint (9d) in the optimization problem (9), we analyze the AUV energy consumption and node energy consumption. In the data collection process, there are extra costs associated with the AUV if it runs out of energy before returning to the sink node. Therefore, the trajectory of the AUV should be scheduled to minimize energy consumption. The power of the AUV at each time slot mainly consists of the sum of propulsion power \(\Phi_{prop}\) and hotel load power \(\Phi_{H}\)[42]. The hotel load \(\Phi_{H}\) is the power consumed by all subsystems other than propulsion mechanism and is typically negligible in comparison with \(\Phi_{prop}\)[43]. Therefore, the power of the AUV trajectory can be expressed as  
\[\Phi_{prop}=\frac{\rho}{2\eta_{p}}C_{D}A_{s}\|V_{AUV}\|^{3}, \tag{16}\]  
where \(\|\cdot\|\) denotes the Euclidean vector norm and \(\rho\) is the density of water. \(\eta_{p}\), \(C_{D}\) and \(A_{s}\) indicate the efficiency of the AUV's propulsion system, the drag coefficient and the wetted surface area, respectively [7]. Consequently, with the relations in (4), (6), (11)-(13) and (16), the total energy consumption can be expressed as  
\[\begin{split} E_{tot}&=\sum_{i=1}^{N}e_{i}+\varpi \Phi_{prop}\mathcal{T}_{travel}\\ &=\sum_{i=1}^{N}x_{i}^{ac}\mathcal{T}_{i}^{ac}P_{trans}^{ac}+x_{ i}^{op}\mathcal{T}_{i}^{op}P_{trans}^{op}+\varpi\Phi_{prop}\mathcal{T}_{travel}, \end{split} \tag{17}\]  
where \(\varpi\) is a weighted parameter that measures the balance between the energy consumption of the sensor node and that of the AUV.
## 5 Plant Growth-Promoting Metabolites for Soil Remediation and Crop Improvement
### Bacterial Phytohydromes
It significantly enhanced plant height, filler and panicle number, paddy yield and (NPK) content, hence suggesting that the precursor of kinetin was converted to cytokinin by rhizospheric microorganisms before absorption or transformed into cytokins inside plant tissues. Otherwise, [PERSON] et al. [200] studied the separate effect of the synthetic cytokinin trans-zeatin, _Bacillus subtilis_ IB-22 (able to produce zeatin-type cytokinin) or _Bacillus subtilis_ IB-21 (unable to produce cytokins) on amino acid release from wheat roots in a split-root system. This system allowed the spatial separation of the zeatin or rhizobacterial application to one compartment and analyses of amino acid rhizodeposition into the other compartment. The application of _B. subtilis_ IB-22 or trans-zeatin greatly enhanced amino acid liberation in the soil solution compared to _B. subtilis_ IB-21 or the untreated plants, suggesting that the ability of cytokinin-producing _B. subtilis_ IB-22 to enhance rhizodeposition may constitute an important process in improving the rhizobacterial colonization of the wheat rhizosphere. Abb Ascisic acid  
Abscisic acid (ABA) is the most important hormone produced by plants in response to abiotic stresses. However, ABA is also synthesized by bacteria, fungi, algae and animals. The prokaryotic pathway for synthesizing this fifteen-carbon sesquiterpene originates from isoprene, known as isopentenyl pyrophosphate, which is synthesized from the mevalonate pathway [201; 202]. [PERSON] et al. [203] investigated the influence of abscisic acid on wheat physiology and yield under field conditions with limited amounts of water during antihesis and postanthesis. Abscisic acid application significantly enhanced leaf area, chlorophyll and carotenoid content in flag leaf and soluble carbohydrates in shoots at anthesis. [PERSON] et al. [204] found that the application of exogenous abscisic acid significantly promoted proline accumulation (as a response to water stress and/or dark-induced senescence) in the detached rice leaf when investigated in both dark and light conditions. Moreover, [PERSON] et al. [205] studied the promotive effect of abscisic acid on floating rice growing at a low relative humidity and its interactive role together with ethylene and gibberellin in internodal elongation. Their results revealed that the separate application of the abscisic acid had no promoting effect on the internodal elongation of the stem sections. However, the simultaneous application of abscisic acid, gibberellin and ethylene efficiently enhanced the internodal elongation of the stem sections, suggesting that abscisic acid could be a good enhancer of the ethylene- and gibberellin-induced internodal elongation at low humidity, hence preventing the reduction of water potential via apoplast transpiration.
## 4 A Case Study of Urban Tourism in Chiang Mai and Phuket in Thailand
### Data and Methodology  
This article relied on mixed methods--quantitative methods and qualitative methods [88]--within the case study, focusing on the description of the foundations of urban tourism development plan-making practices towards sustainability and the public participation that appeared to affect it. First, for the quantitative methods, the author developed a questionnaire to investigate two questions; what is the capacity of urban tourism development towards sustainability, and what is the five year urgent need for urban tourism development towards sustainability? For the purpose of data collection, 600 copies of the questionnaire were send out to the citizens of Chiang Mai/Phuket city between March and May, 2019. The perceptual measures are based on \"Likert\" scales: the questionnaire had five levels, with the respondents responding to a statement on a scale from 1--lowest (Very dissatisfied) to 5--highest (Very satisfied). The information data were analyzed by Statistical Package for the Social Sciences: SPSS25 version and Microsoft excel 2013. Most informants were female (57.3% of the informants were female, and 42.7% of the informants were male), and the majority were aged between 20 and 30 years (40.8% of the informants), followed by between 31 and 40 years (25.5% of the informants). Most of them held a bachelor's degree (45.7% of the informants), and were business owners/entrepreneurs (46.2% of the informants), followed by government officials (26.2% of the informants). The majority of the informants were citizens (65.8% of the informants). Second, for the qualitative methods, an in-depth interview was conducted, using semi-structured interview and open-ended interview [89] structures. All fifteen samples were divided into the individual levels of the main elements of stakeholders in urban tourism policy/planning-making (Table 1), which shall be used to discuss the research questions: determine how urban tourism development plan-making practices impact sustainable development policy performance in Thailand and what the overall participation of urban tourism development plan-making practices is. Then, the interview was informally performed with five people from other groups, who had similar characteristics to the sample, in order to test the accuracy, relevance of the interview, appropriateness of language, and coverage of the key topics and data. Data analysis verified the reliability of the data from each group of the key informants, together with content analysis, by using the conceptual framework of key informants through the interpretation and comparability of important data with consistent words, which was summarized as a diagram and displayed with maps of the research results received.
## 2 EO Satellite and In Situ Observations for Earth Surface
### Ground-Based Networks
Despite the effort of data collection of long term precipitation observations e.g., [58], a precipitation dataset that can support climate change studies and can be readily considered in reanalysis, remains largely unavailable. Earth system models also rely increasingly on non-atmospheric ground-based observation networks including information on river discharge from river gauging stations such as the databases held by the WMO Global Runoff Data Centre (GRDC) and groundwater levels from wells. Such networks are notably at risk from decline in network coverage and restricted national-scale data access [59]. More comprehensive coverage of the in situ networks availability is included in the status report of the global observing system for climate by GCOS in 2015 [60].
###### Abstract  
The crop yield in commercial fields is a very important parameter for farmers. The use of Precision Agriculture tools has been shown to improve rice crop yields. One of these tools is remote sensing on satellite platforms. Sentinel-2 provides free data on reflectance at different wavelengths. Focusing on commercial farms, correlations between the yield and satellite reflectance were studied over several years and locations for 'Sendra' rice crops. Four years of yield maps for 706 ha composed the database. Mid tillering-MT, panicle initiation-PI and grain filling-GF reflectance values and Vegetation Indices (VIs) were used. At MT, correlations with the yield were variable (0.23-0.70). At PI, correlations with the yield increased in NIR (0.39-0.85), but the other regions and VIs experienced a decrease. Visible bands and B05 Red Edge were significantly correlated with each other; similarly, B08 NIR was highly correlated with B06, B07, and B8A; SWIR bands were correlated with each other but not with the yield. At GF, the previous pattern was similar. Substantial limitations in estimating yield variability directly from reflectance or VIs were discussed. Two periods were established. The first is designing strategies to increase NIR and decrease red reflectance from MT to PI. The second is avoiding the relationship between crop greenness and NIR from PI to harvest. NIR was a better variable than VIs, but the single use of this band is challenging. Future recommendations focus on the visible-NIR collinearities to interpret differences between years or locations.  
rice; yield; Precision Agriculture; Sentinel-2; Vegetation Indices +
Footnote †: journal: Applied sciences
# Dynamic Frequency Support from a DFIG-Based Wind Turbine Generator via Virtual Inertia Control
###### Abstract  
As the penetrated level of wind in power grids increases, the online system inertia becomes weak. Doubly-fed induction generator (DFIG)-based wind turbine generators (WTGs) are required to provide virtual inertia response to support system frequency. The present inertia control strategy with fixed control gain is not suitable and may cause stall of the DFIG-based WTG, as the virtual inertia response potential from the DFIG-based WTG is different with various wind speed conditions. This paper addresses a virtual inertia control method for the DFIG-based WTGs to improve the system frequency stability without causing stalling of the wind turbine for various wind speed conditions. The effectiveness of the proposed virtual inertia control method is investigated in a small system embedded with the DFIG-based WTG. Results demonstrate that the proposed virtual inertia strategy improves the frequency stability without causing the rotor speed security issue. Thus, the proposed control strategy can secure the dynamic system frequency security of power systems under the scenarios of full and partial loads, and, consequently, the proposed method provides a promising solution of ancillary services to power systems.  
wind energy; wind generation; virtual inertia control; DFIG-based WTG +
Footnote †: journal: Applied Sciences