esa-sceva/satcom-chunk-collection huggingface dataset:
# Conformational Transitions of Double-Stranded DNA in Thin Films
###### Abstract  
Conformational transitions of double-stranded DNA in different environments have long been studied as vital parts of both in vitro and in vivo processes. In this study, utilizing Fourier transform infrared spectroscopy (FTIR), we provide detailed analysis of dynamics of A- to B-form transitions in DNA thin films of different hydrated states based on a statistical analysis of a substantial number of spectra and band shape analysis (peak fitting) in both the phosphate (1150-1000 cm\({}^{-1}\)) and sugar-phosphate (900-750 cm\({}^{-1}\)) region. Hydration of DNA thin films is systematically controlled by the time spent in the desicator chamber (from 3 min to 40 min) allowing conformation and hydration signatures, in addition to variations due to ambient conditions, to be resolved in the spectra. Conformation transition from A-form to more ordered B-form is observed if sufficient time in the desiccator chamber is allowed and is confirmed by changes on the bands at \(\approx\)890, 860, 837, and 805 cm\({}^{-1}\). Phosphate vibrations at \(\approx\)1230 cm\({}^{-1}\) and 1089 cm\({}^{-1}\), and backbone vibrations at \(\approx\)1030 cm\({}^{-1}\) and 765 cm\({}^{-1}\) were found to be sensitive to changes in hydration rather than conformation. Additionally, we found that spectral variations caused by ambient conditions can be significantly reduced without inducing conformational changes, which serves as a good basis for quality assurance.  
DNA thin films; FTIR; hydration; conformation; peak fitting; A-form; B-form Article Conformational Transitions of Double-Stranded DNA in Thin Films.
## 4 Analysis of Numerical Results
### Lateral Deformation Characteristics of a Caisson with Reinforcement  
#### 4.2.1 Influence of Reinforcement Thickness  
In order to reduce effectively the influence of the disturbance ring on the lateral bearing performance of the caisson, the outer soil of the caisson at the loading point is reinforced. As shown in Figure 5b, the reinforcement area is fan-shaped with a reinforcement height of \(h\) = 4 m. Figure 11 shows the load-lateral displacement distribution curve at the loading point of the caisson for different reinforcement thicknesses \(t\) when the thickness of the disturbance ring \(\delta\) is 2 m and the angle of the fan-shaped reinforcement \(\theta\) is 90\({}^{\circ}\). It can be seen from the figure that reinforcement of the soil at the loading point can effectively increase the horizontal stiffness of the caisson and reduce the lateral displacement. However, when the reinforcement thickness \(t\) exceeds 4 m (2 times the thickness of the disturbance ring), increasing the thickness of the reinforcement zone will not further improve the lateral bearing capacity of the caisson. Therefore, it is recommended that the thickness of the reinforcement area not exceed 2 times the thickness of the disturbance ring in practical engineering, in order to minimize the cost of the project and the difficulty of construction.  
Figure 10: Distribution of the soil plastic zone under different thicknesses of the disturbance ring: (a) \(\delta\) = 0 m; (b) \(\delta\) = 2 m.  
Figure 9: Variation curve of horizontal displacement along the caisson depth with different thicknesses of the disturbance ring.  
Figure 12 shows the variation curve of the lateral displacement of a caisson along the depth for different reinforcement thicknesses, which is consistent with the deformation characteristics of a caisson without reinforcement. In addition, when the reinforcement thickness exceeds 2 m, the lateral displacement of the caisson cannot be further reduced by continuing to increase the thickness of the reinforcement.
## 5 Discussion
### Policy Implications  
The findings of the RUMC-CART model analysis can help shape policy interventions targeted at improving the safety performance of young drivers.  
One key suggestion driven by this study is to implement driver licensing programs which consider the important factors that emerged from the model results, such as the number of vehicles and casualties. These programs would limit young drivers' access to high-risk vehicles, particularly during their initial licensing stages. Through these programs, young individuals can become more aware about risks associated with distraction and peer influence.  
Prioritizing improvements to road design and enforcement aligns with the model's findings regarding several factors, such as the speed limit or vehicle maneuvers during the crash. Advocating for and enforcing lower speed limits, especially in areas with significant pedestrian or cyclist activity [46], are essential to mitigate the severity of crashes involving young drivers. Additionally, investing in infrastructure enhancements and vehicle-aided navigation (e.g., through advanced driving assisting systems--ADAS) to improve visibility at critical road elements (e.g., intersections) and simplify complex maneuvers corresponds with the insights provided by the RUMC-CART analysis.  
Enhancing driver education and training is of the utmost importance, considering the model's findings relating to such factors as vehicle maneuvers and lighting conditions. Mandatory advanced driving courses focusing on essential skills, like emergency braking, hazard perception, and navigating complex maneuvers, as highlighted by the RUMC-CART results, would better prepare young drivers for challenging driving scenarios.  
The findings of the study highlight the impact of road conditions, vehicle characteristics, and speed limits on the crash injury severity of young drivers, thus paving the way for targeted mitigation policies. Investments in rural road infrastructure, enhanced urban traffic management, in-vehicle assistance systems, and tailored educational programs for young drivers can potentially address--to some extent--the sources of driving risk for young individuals. However, such policy implications are applicable to young drivers from England and may not be generalized to similar demographics from different populations or spatial settings. In addition, issues relating to the under-reporting of crashes involving young drivers or the accuracy of classification of injury outcomes may induce bias to data analyses from crash databases. The joint consideration of crash and hospital data by future studies could potentially enhance the predictability and the explanatory power of injury severity analyses focusing on vulnerable road user groups, such as young individuals.
###### Abstract  
Color independency is an important factor in visible light communication (VLC) systems. This paper aims to review and summarize recent achievements in color-independent visible light communication based on color space, with the main focus being on color-space-based modulation (CSBM), termed as generalized color modulation (GCM), which allows VLC to adapt to any target color. The main advantages of GCM are its color independency, reasonable bit error rate (BER) performance during color variation, and dimming control. We also address our past research works that aimed to achieve a color-independent visual MIMO system by incorporating the advantages of GCM, which can lead to higher data rates over longer distances and improved performance, using image processing in addition to color independency. Finally, two case studies are introduced to demonstrate the potential applicability of a color-independent visual-MIMO system using color-space-based modulation techniques.  
visible light communication; generalized color modulation; color-space-based modulation; color independence; visual MIMO; wearable device; V2X +
Footnote †: journal:
## 5 Discussion
### Uncertainties of the Model and the Interference of Mixed Pixels  
In the study, based on MODIS NDVI data, land parameters and meteorological data derived from 34 meteorological stations and from Chongqing for years 2001-2011, we improved the GLOPEM-CEVSA model and investigated the seasonal variation and spatial distribution of NPP as well as analyzed the relationship between NPP and the climate factors. However, our estimate still retain some uncertainties for the following reasons.  
First, there exists the scale effect between remotely sensed data and meteorological data. The spatial resolution of MODIS NDVI data is 1 KM, affecting the inversion accuracy of FPAR. In the process of interpolating meteorological data, we have taken the average value to reduce the estimation error caused by the spatially or temporally scale effect. Second, the validated data used in the study came from the MOD17 NPP, which is a global land vegetation net productivity product calculated by model and has been validated widely, across most of the world [40]. In the process of the calculations, some of the maintenance respiration could consume the output of the total NPP, which is termed PSNnet (net photosynthesis). Thus, it is necessary to distinguish the true NPP and forest inventory data. NPP, as a result of the verification is modeled by the measured biomass data, and the biomass data collected in the field inevitably has some error, resulting in some errors for the verification results.  
Understanding and identifying the sources of uncertainties and then devoting efforts to improving them are critical in improving the accuracy of model estimation; therefore, more research is needed in the future for reducing the uncertainties from different sources in the process of NPP simulation, especially for the localization of model parameters, spatial scale matching between each module data of the model.  
The mixed pixel is often one of the most important error sources for the simulation of NPP. Because the land cover mixtures are more complex and spatially heterogeneous, most pixels of MODIS data consist of several land cover due to the low spatial resolution, which will complicate the quantitative evaluation of mixed pixel effect on NPP, which affects the estimation accuracy of net primary productivity to a certain extent. Therefore, NPP assessment with complex land cover mixtures still needs further investigation.
## 4 Discussion  
### Summary of Key Findings  
This study showed that nearly 55% of pediatric patients aged 9-18 years at UTSD clinics did not receive the complete HPV vaccination series. Among the unvaccinated,  
\begin{table}
\begin{tabular}{l c c c c c c c} \hline \hline
**Age Group** & **Yes N** & **\% (95\% CI)** & **No N** & **\% (95\% CI)** & **Total N** & **\% (95\% CI)** & \(p\)**-Value 1** \\ \hline
9–11 & 19 & 10.4 (6.4–15.8) & 60 & 27.5 (21.7–34.0) & 79 & 19.8 (16.0–24.0) & \(p<0.001\) \\
11–14 & 93 & 51.1 (43.6–58.6) & 112 & 51.4 (44.5–58.2) & 205 & 51.3 (46.2–56.3) & \\
15 = 18 & 70 & 38.4 (31.4–46.0) & 46 & 21.1 (15.9–27.1) & 116 & 29.0 (24.6–33.7) & \\
**Gender** & & & & & & \\ Male & 74 & 40.7 (33.5–48.2) & 112 & 51.4 (44.5–58.2) & 186 & 46.5 (41.5–51.5) & \(p=0.031\) \\ Female & 108 & 59.3 (51.8–66.6) & 106 & 48.6 (41.8–55.5) & 214 & 53.5 (48.5–58.5) & \\
**Race/Ethnicity** & & & & & & \\ White & 18 & 9.9 (6.0–15.2) & 20 & 9.2 (5.7–13.8) & 38 & 9.5 (6.8–12.8) & \(p=0.952\) \\ Black & 28 & 15.4 (10.5–21.5) & 34 & 15.6 (11.1–21.1) & 62 & 15.5 (12.1–19.4) & \\ Latino/Hispanic & 108 & 59.3 (51.8–66.6) & 130 & 59.6 (52.8–66.2) & 238 & 59.5 (54.5–64.4) & \\ Asian & 15 & 8.2 (4.7–13.2) & 15 & 6.9 (3.9–11.1) & 30 & 7.5 (5.1–10.5) & \\ N/A & 13 & 7.1 (3.9–11.9) & 19 & 8.7 (5.3–13.3) & 32 & 8.0 (5.5–11.1) & \\
**Language Spoken** & & & & & & \\ English (235) & 111 & 61.0 (53.5–68.1) & 124 & 56.9 (50.0–63.6) & 235 & 58.8 (53.8–63.6) & \(p=0.651\) \\ Spanish (111) & 49 & 26.9 (20.6–34.0) & 62 & 28.4 (22.6–34.9) & 111 & 27.8 (23.4–32.4) & \\ N/A (55) & 22 & 12.1 (7.7–17.7) & 32 & 14.7 (10.3–20.0) & 54 & 13.5 (10.3–17.2) & \\
**Insurance type** & & & & & & \\ Medicaid (259) & 119 & 65.4 (58.0–72.3) & 131 & 60.0 (53.3–66.6) & 261 & 65.3 (60.4–69.9) & \(p=0.142\) \\ Commercial (80) & 30 & 16.5 (11.4–22.7) & 50 & 22.9 (17.5–29.1) & 80 & 20.0 (16.2–24.3) & \\ None (61) & 33 & 18.1 (12.8–24.5) & 37 & 17.0 (12.2–22.6) & 59 & 14.8 (11.4–18.6) & \\ \hline \hline \end{tabular} \({}^{1}\) Pearson Chi-square test.  
\end{table}
Table 1: Demographic characteristics of pediatric patients according to HPV vaccination status. Have you received the complete HPV vaccine series?  
Figure 2: Parent-reported reasons for no HPV vaccine at the dentist, overall.  
21% indicated a willingness to receive the vaccine at a dental academic institution. We evaluated the reasons among those who were unwilling to accept the HPV vaccine at the dental school. To the best of our knowledge, this is the first study to apply this assessment among dental patients in a dental academic institution.  
Among our adolescent patients aged 14-18 years, 51.6% self-reported receiving the HPV vaccine, comparable to the 2021 HPV vaccination coverage among Texas teens aged 13-17 years of 51.5% [19]. The percentage of children aged 11-17 years who had ever had an HPV vaccine was 40.8%, which was lower than the 54.3% reported by the Health of Houston Survey 2018 [17]. The reasons for the difference might be that, as of 2021, HPV vaccination rates among teens dropped by 3.4% compared to 2020 [20], and there are differences in the source population.
# Dynamic Prediction Model for Progressive Surface Subsidence Based on MMF Time Function
## 3 Case Study
### MMF Time Function Validation with Measured Data  
Data observation of mining-induced surface subsidence included a traverse survey and a trigonometric elevation survey. Fifteen days after the first observation with a total station, the workings began to advance. The final coordinate survey was carried out 325 days after the first observation. Fifteen observations were conducted at 26 points on the strike observation line, as shown in Figure 12. Five observations were made on the tendency observation line, however, there are a lack of data, so the dynamic prediction model proposed in this paper is validated and analyzed mainly based on the data on the strike observation line. As demonstrated in Figure 12, from 309 days after the first observation, the surface movement stabilized and the maximum subsidence reached 1898 mm, which is located at No. 18.  
To illustrate the feasibility and applicability of the MMF time function for predicting the progressive surface subsidence, the MMF time function was fitted to the measured settlement data. The measured data of six observation points on the strike line of the working panel 22101 were selected, including No. 10, No. 13, No. 16, No. 19, No. 22 and No. 25.  
In order to eliminate differences of subsidence values at different points and to highlight the common feature of subsidence over time, we transformed the subsidence of each point to a subsidence ratio, which is equal to \(W_{\rm i}/W_{0}\), and took the values in the range 0-1. The parameters \(a\) and \(b\) of MMF time function are solved by nonlinear least squares algorithm through loop iteration. Considering the large discrepancy in order of magnitude between parameter \(a\) and parameter \(b\), we replaced parameter \(a\) with logarithm \(a\).  
The fitting results for the six points are shown In Figure 13.  
Figure 11: The Layout of working panel 22101.  
Figure 12: Measured subsidence curves of the strike observation line.  
Figure 13: The fitting results for six chosen points.  
Each MMF fitting result is consistent with the corresponding time-subsidence ratio data, with R\({}^{2}\) greater than 0.97 and even greater than 0.99 for the majority of R\({}^{2}\). This suggests that the MMF time function is well suited for predicting dynamic subsidence at surface points caused by coal mining.  
Furthermore, the surface subsidence when the maximum subsidence velocity occurs is not always about half of the final subsidence, like the points near the boundary of the working panel (No. 10, No. 13, No. 16). In addition, regardless of the time function and coordinate system used, the parameters at different locations are different.
# Comparative Analysis of Machine Learning Methods for Predicting Energy Recovery from Waste
###### Abstract  
In the context of escalating energy demands and the quest for sustainable waste management solutions, this paper evaluates the efficacy of three machine learning methods--ElasticNet, Decision Trees, and Neural Networks--in predicting energy recovery from municipal waste across the European Union. As renewable energy sources increasingly dominate the energy production landscape, the integration of Waste-to-Energy (WTE) processes presents a dual advantage: enhancing waste management and contributing to the renewable energy mix. This study leverages a dataset incorporating economic and environmental indicators from 25 European countries, spanning 2013-2020, to compare the predictive capabilities of the three machine learning models. The analysis reveals that Neural Networks, with their intricate pattern recognition capabilities, outperform ElasticNet and Decision Trees in predicting energy recovery metrics, as evidenced by superior performance in key statistical indicators such as R-value, Mean Squared Error (MSE), and Mean Absolute Error (MAE). The comparative analysis not only demonstrates the effectiveness of each method but also suggests Neural Networks as a pivotal tool for informed decision-making in waste management and energy policy formulation. Through this investigation, the paper contributes to the sustainable energy and waste management discourse, emphasizing the critical intersection of advanced technologies, policy considerations, and environmental stewardship in addressing contemporary energy challenges.  
machine learning: waste-to-energy; energy recovery; neural networks +
Footnote †: journal: _Applied_
## 4 Results and Discussion
### Development of Univariate Hybrid Model
The two machine learning models, SVR and LSTM, perform similarly; however, SVR performance is better by a small margin, making it difficult to choose one over the other for a given time step of a forecast horizon. This analysis suggests that the persistence model is best for wind speed prediction one hour or two hours ahead, the Weibull-based model is best for six hours ahead or longer forecast horizons, and ARIMA or machine learning models are best for in between these two forecast horizons. However, in this research, we have proposed to use all these models by providing weight functions for each model in each time step. The results after providing the weight function for the hybrid model are shown below in Tables 10-13. Results from our four case study sites indicate performance improvement for each time step of the forecast horizon as well as overall accuracy. The hybrid model can produce a better result with a MAPE as low as 7.8%, MAE as low as 1.1, and RMSE as low as 1.2.
# Modeling and Application of Dynamic Soaring by Unmanned Aerial Vehicle
## 1 Introduction
The trajectory optimization still takes a lot of time and is unsuitable for the real-time dynamic soaring decision. Meanwhile, the flight test mainly focused on dynamic soaring feasibility, and the limited dynamic soaring type was verified (closed-loop trajectory). Moreover, the accuracy of the energy harvesting mechanism model lacked verification, although the derivation of the energy harvesting mechanism has been applied many times. Hence, this paper aims to achieve the UAV dynamic soaring by giving a new soaring trajectory decision method and verifying it using flight simulation. The decision method will give the altitude and yaw angle instructions rather than a whole detailed trajectory. The instructions are summarized through the typical dynamic soaring cycle combined with the UAVs' performance. This simulation will carry out the test flight with the affirmative UAV model to record the flight data, including real-time airspeed, position, etc. Furthermore, the energy variation will be recorded during the test flight and compared with the energy harvesting mechanism model. Finally, this paper points out the possible further studies on the dynamic soaring application based on the result.
# Leveraging IPv6 and ICMPv6 for Delay-Tolerant Networking in Deep Space
## 3 Architecture Proposal  
An architecture has been designed to implement a DTN node capable of handling both DTN and non-DTN traffic while maintaining IPv6 compliance. This approach circumvents the limitations of previous solutions (e.g., the Bundle Protocol), which required existing nodes, some not directly affected by disruptions, to modify their protocol stacks.  
To avoid the challenges of modifying the Linux kernel, the solution can be implemented with LightWeight IP (LwIP) [24], which also allows better control of the stack. LwIP is an open-source, lightweight implementation of the Linux networking stack, optimized for constrained devices, an advantage particularly relevant for DTNs. In addition to the protocol stack, LwIP provides a library of APIs that developers can use to integrate and interact with the functionalities of the stack. Figure 1 provides a schematic representation of the design of a node.  
To implement the proposed design, a network TUNnel (TUN) interface is established between the kernel and the userspace, instructing the kernel to forward all inbound IP packets to this interface without further processing of the headers. Once in the userspace, the IP packets are processed by an LwIP instance enhanced with an additional DTN Module. This implements the DTN functionalities needed in a modular way through custom and specialized functions. DTN packet forwarding completely bypasses the IP stack implemented in the operating system kernel, using raw sockets to deliver the IP packets directly to the correct L2 interface. This is necessary because, otherwise, once the packet is handed back to LwIP, the routing decisions made by the DTN Module would be disregarded, and the packet would not be forwarded in a DTN-aware manner. This approach ensures fine-grained control over DTN traffic flow.  
The modular design and placement of the proposed solution in the userspace presents significant advantages, particularly in terms of testing and maintenance. For example, it allows for straightforward substitution of the routing algorithm or the definition of new signaling messages without requiring extensive modifications. However, to support the continued development and widespread adoption of the architecture, a native implementation within the operating system kernel should be considered. Such integration has the potential to enhance performance, simplify operation, and increase the robustness and efficiency of the solution in production environments.