esa-sceva/satcom-chunk-collection huggingface dataset:
# Adaptive Navigation in Collaborative Robots: A Reinforcement Learning and Sensor Fusion Approach
## 3 Methodology
### The Haversine Formula  
The Haversine formula is used to get the distance between two positions on a sphere using their coordinates. It is especially valuable in navigation and mapping applications for determining the shortest path between two locations on Earth [31; 32]. Using this formula, a vehicle can determine whether it has reached its destination. Mathematical equations are shown below:  
\[x=sin^{2}\bigg{(}\frac{\Delta\phi}{2}\bigg{)}+cos(\phi_{1})cos(\phi_{2})sin^{2} \bigg{(}\frac{\Delta\lambda}{2}\bigg{)} \tag{1}\]  
\[y=2\cdot a\cdot tan2\bigg{(}\sqrt{x},\sqrt{1-x}\bigg{)} \tag{2}\]  
\[d=R\cdot c \tag{3}\]  
where \(\phi_{1}\), \(\phi_{2}\) are the latitudes of current location and destination in radians. \(\lambda_{1}\), \(\lambda_{2}\) are the longitudes of current location and destination in radians. \(\Delta\phi=\phi_{1}-\phi_{2}\) is the latitude difference. \(\Delta\lambda=\lambda_{1}-\lambda_{2}\) is the longitude difference. \(R\) is the radius of Earth. \(c\) is the angular distance between the points. \(d\) is the distance between the two points.
# YOLO-SE: Improved YOLOv8 for Remote Sensing Object Detection and Recognition
## 2 Related Work
### Attention Mechanism  
The attention mechanism empowers neural networks to concentrate on crucial features while disregarding less pertinent ones [24]. Convolution operations combine channel information and spatial information to extract features, making attention-mechanism designs consider both channel and spatial aspects. Currently, there are three main types of attention mechanisms:  
(1) Channel Attention: This type of attention mechanism prioritizes important features or channels within the data. For example, SENet [25] focuses on crucial channels for better feature representation.  
(2) Spatial Attention: Spatial attention directs the model's focus to essential spatial positions within the data. Self-attention mechanisms, such as those used in deformable convolutional networks (DCNs) [26], excel at capturing spatial relationships.  
(3) Mixed Attention Mechanisms: Some attention mechanisms, like the Convolutional Block Attention Module (CBAM) [27], combine both channel and spatial attention characteristics. CBAM can simultaneously attend to channels and spatial positions, contributing to improved model accuracy and noise suppression by considering both aspects of the data.  
Additionally, we acknowledge the significance of other works. Many works also use neural attention to improve feature learning, such as Motion-attentive Transition for Zero-shot Video Object Segmentation [28] and Regional Semantic Contrast and Aggregation for Weakly Supervised Semantic Segmentation [29]. These works further demonstrate the diverse applications of attention mechanisms for feature learning.  
These attention mechanisms play a crucial role in enhancing model performance by selectively emphasizing relevant information, which is particularly beneficial in tasks like object detection and image analysis.
# Satellite Image Compression Guided by Regions of Interest
## 5 Conclusions
We expect that the energy savings in data transmission will be greater than the energy required to make use of the proposed method, resulting in benefits that go beyond bandwidth reductions and lower transmission costs. Analyses involving energy consumption are not within the scope of this paper, but can be carried out in future work. Conceptualization, C.S., I.S., F.B., M.P., J.E. and C.F. ; methodology, C.S. and I.S. ; software, C.S. ; validation, C.S. ; formal analysis, C.S., I.S., F.B., M.P., J.E. and C.F. ; investigation, C.S. ; writing--original draft preparation, C.S. ; writing--review and editing, C.S. ; supervision, C.F. and I.S. ; project administration, C.F. ; funding acquisition, C.F. All authors have read and agreed to the published version of the manuscript. This study was financed by Conselho Nacional de Desenvolvimento Cientifico e Tecnologico--CNPq, Centro de Pesquisa e Inovacao Sueco-Brasileiro--CISB, and Saab AB. Grant 201549/2020-4. The authors also would like to thank the Saab AB for the dataset, and the Unibap AB for the support regarding the satellite. Not applicable. This study made use of 25 images (cropped) from PlanetScope for the simulations, as described in Section 2. More information about the PlanetScope images can be found in [25]. The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.
## 5 Conclusion
\begin{table}
\begin{tabular}{c c c c c c c c c c c c c c} \hline \hline \multicolumn{2}{c}{**Parameter**} & \multicolumn{4}{c}{**Capacity Deviation of \(\pm\)1\%**} & \multicolumn{4}{c}{**Capacity Deviation of \(\pm\)2\%**} & \multicolumn{4}{c}{**Capacity Deviation of \(\pm\)3\%**} \\  & **Bat \#1** & **Bat \#2** & **Bat \#3** & **Bat \#4** & **Bat \#1** & **Bat \#2** & **Bat \#3** & **Bat \#4** & **Bat \#1** & **Bat \#2** & **Bat \#3** & **Bat \#4** \\ \hline Voltage & Min & 3.048 & 3.086 & 2.997 & 3.048 & 3.086 & 3.151 & 2.996 & 3.086 & 3.121 & 3.207 & 2.997 & 3.121 \\ (V) & Max & 4.129 & 4.105 & 4.163 & 4.129 & 4.127 & 4.102 & 4.201 & 4.127 & 4.115 & 4.099 & 4.241 & 4.115 \\ SOC & Min & 6.97 & 7.40 & 6.43 & 6.97 & 7.48 & 8.31 & 6.50 & 7.48 & 8.00 & 9.22 & 6.58 & 8.00 \\ (\%) & Max & 98.01 &The simulation results of the cell balance method proposed in Table 11 and the cell balance method of the existing simple voltage comparison method are summarized here. For the existing simple voltage comparison cell balancing method, the maximum voltage of the battery greatly increased from 4.213 V to 4.331 V as the allowable capacity deviation of the series-connected batteries increased. However, in the case of the proposed cell balance method, the highest voltage rose from 4.167 V to 4.211 V, which was relatively very small. In addition, for the existing simple voltage comparison cell balance method, it was confirmed that as the allowable capacity deviation of series-connected batteries increased, the aging of batteries with relatively small capacities more quickly proceeded. However, in the case of the proposed cell balance method, the aging and the aspect of the battery were different. This was because the use area of a battery with a relatively small capacity is limited according to the allowable capacity deviation of the battery.
# Biological and Technical Challenges Related to Cultured Meat Production
## 3 Challenges Related to Cultured Meat Production
### Biotechnological Challenges
#### 3.1.7 FBS Alternatives
However, it is a waste product with a high environmental pollution load as reported by [PERSON] et al. [62]. Indeed, it has been calculated that its polluting potential is equal to a biochemical oxygen demand \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Matrices** & **Cell Type** & **Effects** & **Refs.** \\ \hline
**Plant peptones** & CHO-320 (CHO K1 clone) & Improved cultivation and productivity of & [48] \\  & & Human interferon gamma & \\ \hline
**Yeast hydrolysate** & CHO & Higher productivity of Human beta interferon & [49; 50] \\  & rCHO (recombinant CHO) & Higher cell growth & [49; 50] \\ \hline
**Rice protein hydrolysate** & CHO-320 & Protection against oxidation stress from & \\  & Human HepG cells & hydrogen peroxide & [51; 52] \\ \hline
**Soy peptones** & CHO DG44 & Improved cell production & [53] \\ \hline
**Wheat hydrolyses** & CHO & Improved cell viability & [54] \\ \hline
**Marine cyanobacterium** & Human Lung Carcinoma & Improved cell viability and proliferation & [55] \\
**Spirulina _maxima_** & & & \\ \hline
**Chlorella vulgaris extract** & CHO-K1 and MSC & Promoted cell growth & [56] \\ \hline
**Rapeseed caked** & CHO-C5 & Promoted cell growth & [57] \\ \hline
**Silk sericin hydrolysate** & CHO and Hela cells & Improved cell growth and proliferation & [58] \\ \hline
**Whey protein** & CHO K1 & Improved cell viability and proliferation & [59] \\  & JURKAT E6.1 & & \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Applications and analysis of different matrices in cell cultures. Modified by [PERSON] et al. [47]. approximately 175-fold higher than the sewage system of modern cities. Therefore, it causes serious environmental problems when discarded [62]. For this reason, although it is of animal origin, its use as an alternative to FBS might be considered. Moreover, its production is high; this would make it possible to meet the high market demand typical of FBS. Overall, it is of paramount importance to find suitable alternatives for FBS, considering the combined use of plant-based products (e.g., those reported in Table 2). However, due to the high variability in their chemical composition and mechanism of action of these matrices, it is necessary to investigate the effects of their combination on cell cultures.
## 1 Introduction
For instance, using a petrol-hydrogen mixture containing 10% hydrogen by mass and increasing the air excess ratio from 1.4 to 1.6 results in only a minor increase in combustion duration, approximately 1-2 degrees of crank angle (CA) [41]. Hydrogen also changes the fraction of carbon-based fuel used, leading to lower emissions of CO, CO\({}_{2}\), and hydrocarbons. Studies have shown that even a small fraction of hydrogen can reduce unburned HC emissions by up to 9% across all load points, including tests conducted at full load, with an additional hydrogen flow of 0.25 kg/h. This reduction is due to the increased combustion speed and improved fuel oxidation by hydrogen, and a rise in combustion temperature [42]. However, while the addition of hydrogen enhances the oxidation of carbon-based fuels, it also influences thermal NO\({}_{\rm x}\) formation. The increased combustion temperature caused by hydrogen leads to higher NO\({}_{\rm x}\) emissions. Studies have shown that reducing the hydrogen fraction in the fuel mixture from 15% to 10% decreases NO emissions by 14%, with a further 17% reduction observed when the hydrogen fraction is lowered to 5% [43]. To achieve a more comprehensive evaluation of hydrogen's impact--considering the additional mass of H\({}_{2}\) tanks and driving at different speeds--the WLTP driving simulation will be performed [44; 45]. This study is designed to assess the effect of hydrogen as an additive in ICE under energy and performance indicators through experimental investigation and numerical modelling. The rest of this paper is organized as follows: Section 2 describes the materials and methods used for experimental research and numerical simulation. Section 3 discusses the results and comparative analysis based on energy and environmental performance indicators. In Section 4, the conclusions and further research are summarized.
## 2 Methodology  
A single Holoscopic image records the scene's spatial and angular details. Hence, it is possible to compute the scene's depth map from a single shot. In or proposed method, as seen in Figure 3, pre-processing is carried out on the EIs, which is crucial before computing the disparity to improve their quality, as they inherently have a low resolution and lack texture. This procedure consists of two primary stages: noise reduction by bilateral filtering and contrast enhancement via histogram equalisation.  
The disparity among EI pixels is computed via the Semi-Global Block Matching (SGBM) algorithm [12], which is favoured due to its flexibility to adapt to the unique features of EIs and its optimal balance between precision and computing efficiency. The SGBM algorithm is enhanced through a multi-resolution approach to address the limitations of EIs in terms of resolution. This involves creating an upscaled pyramid of EIs to capture details at different scales and performing a content-aware analysis to adaptively adjust the SGBM window size parameters. This ensures optimal estimation of disparities across various texture and complexity levels within the EIs. Ultimately, a weighted least squares (WLS) filter is employed to further enhance the optimisation process.  
EIs are known to be low in resolution, lack texture, and only capture a portion of the scene. Several deep learning models have been designed to estimate disparity maps, including many specifically designed for VPIs. Deep learning necessitates a substantial and comprehensive dataset specifically designed for Holoscopic imagery. Pre-existing, pre-trained deep learning stereo-matching solutions would not be compatible with EIs due to differences in training data properties. These solutions are mostly learned using high-quality images, while EIs have a low resolution and lack texture. Deep learning  
Figure 2: (**a**) Perspective projection. (**b**) Orthographic projection.  
algorithms have the potential to be highly effective in stereo vision tasks, but their effectiveness is contingent upon the quality and range of the training data. If the training data lack sufficient representation of scenarios, including low resolutions, limited textures, and narrow disparity ranges, the model may exhibit poor generalisation in these settings. Deep learning algorithms may encounter difficulties in generating intricate details in such situations, resulting in unclear outcomes.
## 1 Introduction
In view of this, this paper takes the underground karst area of Tianmeixin village in the northern extension of Guanghua Interior Railway Line 18 as the research object, combines the results of preliminary engineering investigations, comprehensively considers the detection requirements and the complex hydrological, geological, geomorphological, and built environment faced by the detection area, optimizes a combination of the electrical resistivity tomography method and the cross-well seismic computed tomography method and borehole verification and other technical methods to detect the development range of underground karst areas, possible water channels, and the accurate locations of hidden karst caves, and solves the technical problems of hidden karst detection under the constraints of complex engineering geological conditions in the city. At the same time, the application research of this detection technology method can also provide a theoretical basis and technical guidance for the detection and evaluation of hidden karst under similar engineering geological conditions.
## 4 Analysis of Test Results
### Earth Pressure Analysis  
Figure 9 shows the measured soil pressure variation curves under different working conditions. For the measured active earth pressure, the active earth pressure above the bottom of the pit gradually increases under each excavation condition, showing a small distribution at the top and large at the bottom. This is because the supporting pile moves into the pit under the action of the excavated soil in front of the pile and the additional load at the top after the pile, which drives the soil behind the pile to move forward as well, and the soil stress in the active zone increases gradually. For the passive zone soil pressure, as the excavation depth increases, the measured soil pressure below the excavation surface is displaced onto the excavation side due to the supporting pile, and the stress of the soil in front of the pile increases due to the extrusion. In the early stage of excavation, the soil stress in the passive zone in front of the pile increases with depth and shows a small distribution in the upper part and large in the lower part of the figure. At the later stage of excavation, the passive soil pressure in front of the pile is distributed in the shape of large at the top and small at the bottom.  
In order to verify the reasonableness of the measured soil pressure, we calculated the Rankine soil pressure of the support structure and compared it with the measured soil pressure. We found that the measured soil pressure is smaller than the Rankine soil pressure and has a non-linear distribution. This is because the Rankine earth pressure theory is based on the rigid retaining wall, which assumes that the soil reaches the ultimate state [36], while the foundation pit does not allow the soil to reach the ultimate state. Therefore, when designing and analyzing the pile-anchored support structure based on the Rankine earth pressure theory of traditional rigid retaining walls, the calculation results may be large.  
Figure 8: Final strain of different support piles.  
In the presence of complex excavation conditions or where the deformation range of the support structure is strictly limited, the results calculated by the classical Rankine earth pressure theory may not meet the requirements of the project. Therefore, further research on non-limit states of earth pressure applicable to the foundation pit enclosure structure is needed at a later stage.
## 3 Results
### Differential Pulse Voltammetry  
#### 3.4.1 Analysis with the aGCE  
The DPV analyses with aGCE, as previously written, were performed measuring the reduction peak of the by-product. The measurements were carried out in two steps:(i) the DCF was first electrochemically oxidized and transformed into its by-product by the application of an anodic potential; the DCF by-product generated was adsorbed onto the electrode surface; (ii) a cathodic potential scan was then performed with the aGCE immersed in a blank solution, after washing with ultrapure water. The parameters used for the anodic preconditioning: medium 5 \(\times\) 10\({}^{-2}\) mol L\({}^{-1}\) H\({}_{3}\)PO\({}_{4}\)/KH\({}_{2}\)PO\({}_{4}\) (pH 2.0) with different DCF concentrations (3-30 \(\mu\)g L\({}^{-1}\)); potential applied: 0.8 V, conditioning time: 30 s. The parameter used for the potential cathodic scan were those optimized by the DoE procedure (Table 2).  
Figure 7a shows the DPV voltammograms obtained for DCF concentrations included between 3 and 30 \(\mu\)g L\({}^{-1}\). To evaluate the stability of the signals, for each concentration level, the measurement was repeated three times. Figure 7b shows the current values obtained by increasing the DCF concentration. In this case, four independent replicates, with one measurement for each concentration level, have been performed. It can be seen that the trend is linear up to a DCF concentration of 16 \(\mu\)g L\({}^{-1}\), after which the saturation of the electrode surface occurs, as expected when an adsorption process is involved. Figure 7c shows the linear fit obtained in the linearity range, and the inset Table shows the fit parameters.  
From the plots shown in Figure 7c, the mean values of LoD (limit of detection) and LoQ (limit of quantification) were estimated by the standard deviation of the intercepts defined by the ordinary linear regressions. The LoD and LoQ values correspond to the analyte amount for which the current signal is equal to 3.3 times or 10 times the standard deviation of the intercepts, respectively. The estimated values of the LoD and LoQ were, respectively, 1.6 \(\mu\)g L\({}^{-1}\) and 4.8 \(\mu\)g L\({}^{-1}\).
###### Abstract  
Binary Edwards Curves (BEC) play a pivotal role in modern cryptographic processes and applications, offering a combination of robust security as well as computational efficiency. For robust security, this article harnesses the inherent strengths of BEC for the cryptographic point multiplication process by utilizing the Non-Adjacent Form (NAF) algorithm. For computational efficiency, a hardware architecture for the NAF algorithm is proposed. Central to this architecture is an Arithmetic Logic Unit (ALU) designed for streamlined execution of essential operations, including addition, squaring, and multiplication. One notable innovation in our ALU design is the integration of multiplexers, which maximize ALU efficiency with minimal additional hardware requirements. Complementing the optimized ALU, the proposed architecture incorporates a radix-4 multiplier, renowned for its efficiency in both multiplication and reduction. It eliminates resource-intensive divisions, resulting in a substantial boost to overall computational speed. The architecture is implemented on Xilinx Virtex series Field-Programmable Gate Arrays (FPGAs). It achieves throughput-to-area ratios of 14.819 (Virtex-4), 25.5 (Virtex-5), 34.58 (Virtex-6), and 37.07 (Virtex-7). These outcomes underscore the efficacy of our optimizations, emphasizing an equilibrium between computational performance and area utilization.  
c 2023 by the authors. Licensee 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/))).
###### Abstract  
Ascorbic acid (AsA) has high antioxidant activities, and its biosynthesis has been well studied by engineering of a single structural gene (SG) in staple crops, such as tomato (_Solanum lycopersicum_). However, engineering the AsA metabolic pathway by multi-SG for biofortification remains unclear. In this study, pyramiding transgenic lines including GDP-Mannose \({}^{3}\),\({}^{5}\)-epimerase (_GME_) \(\times\) GDP-d-mannose pyrophosphrolase (_GMP_), GDP-l-Gal phosphorylase (_GGP_) \(\times\) l-Gal-l-P phosphatase (_GPP_) and _GME_\(\times\)_GMP_\(\times\)_GGP_\(\times\)_GPP_, were obtained by hybridization of four key genes to get over-expression transgenic plants (_GME_, _GMP_, _GGP_, and _GPP_) in tomato. Pyramiding lines exhibited a significant increase in total ascorbate in leaves and red fruits except for _GGP_\(\times\)_GPP_. Expression analysis indicated that increased accumulation of AsA in pyramiding transgenic lines is due to multigene regulation in AsA biosynthesis. Substrate feeding in leaf and fruit suggested that AsA biosynthesis was mainly contributed by the d-Man/l-Gal pathway in leaves, while alternative pathways may contribute to AsA accumulation in tomato fruit. Pyramiding lines showed an enhanced light response, stress tolerance, and AsA transport capacity. Also, fruit shape, fruit size, and soluble solids were slightly affected by pyramiding. This study provides the first comprehensive analysis of gene pyramiding for ascorbate biosynthesis in tomato. SGs pyramiding promotes AsA biosynthesis, which in turn enhances light response and oxidative stress tolerance. Also, the data revealed an alternative ascorbate biosynthesis pathway between leaves and fruit of tomato.  
T omato (_Solanum lycopersicum_); AsA; gene pyramiding; biosynthesis pathway; oxidative stress