esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Results
### Invention Classification
#### 4.2.2 Fuel Delivery  
Patents in this category tackle the challenges of safely and efficiently transferring and conditioning hydrogen and oxidizers for use in aviation fuel cells and combustion systems. These inventions propose modular, automated, and thermally integrated solutions to enable precise and responsive hydrogen handling across diverse aircraft platforms. Innovations include solid and cryogenic hydrogen storage systems that generate gas on demand through chemical or thermal activation. These systems often have integrated pressure and flow control tailored for fuel cells. Both ground-based and airborne refueling systems use robotic, vertically engaging, or modular interfaces to streamline cryogenic fuel transfer and minimize downtime. Several technologies optimize hydrogen vaporization and preheating using engine-derived or recuperated heat. Some of the patents claim novel injectors and swirlers to ensure safe combustion or flashback prevention. Oxygen and inert gas delivery systems further enhance reactant control, enabling robust, high-efficiency operation under varied altitudes and thermal loads. Together, these patents aimed to develop a resilient and scalable hydrogen fueling infrastructure in aviation.  
The following are two examples of patents in this category that tackle both the physical and chemical aspects of delivering hydrogen to propulsion systems. [PERSON] and [PERSON] (2024) introduced a heat-activated detergent additive for hydrogen fuels that activates at combustion temperatures [45]. This significantly reduces residue buildup in injectors and valves while preserving fuel properties. This innovation enhances system reliability and reduces maintenance intervals. Complementing this, [PERSON] and [PERSON] (2024) developed a hydrogen heat exchanger comprising an inner tube bank with a surrounding thermal buffer of tunable thickness and conductivity [46]. This system optimizes pre-combustion fuel temperature using waste heat, ensuring stable ignition and minimizing thermal gradients. Collectively, these patents demonstrate the interplay of fuel conditioning and system cleanliness in enabling robust hydrogen delivery.
# Privacy-Preserving Handover Optimization Using Federated Learning and LSTM Networks
## 5 Discussion  
Our study demonstrates the effectiveness of the dynamic handover algorithm in reducing unnecessary handovers while maintaining network performance. The Dynamic algorithm significantly outperforms traditional methods, such as the A3_Event and Greedy algorithms, by adapting to real-time network conditions. This adaptability leads to a substantial decrease in the probability of HOPP events, which are a common issue in mobile networks.  
Our approach leverages the predictive power of LSTM models to forecast RSRP and NRxRSRP values accurately, enabling more informed handover decisions. By dynamically adjusting the Time-to-Trigger and handover thresholds based on the predicted values, our algorithm achieves a balance between minimizing HOPP events and ensuring reliable handovers.  
The dynamic algorithm is superior to the traditional method because we dynamically adjust the threshold through the error of model prediction to adapt to the changing wireless environment, thereby improving handover efficiency and overall system performance. In real scenarios, if the HOPP probability is low, it means that the ping-pong effect occurs less often, thereby improving user experience.  
Next, is the issue of limitations. Our study assumes that the RSRP and Near RSRP data collected across different clients are representative of typical network conditions, but potential biases in the dataset, such as uneven data distribution among clients or underrepresented scenarios, could affect the generalizability of our results. Additionally, while Federated Learning offers significant privacy benefits, it introduces computational overhead due to the need for local training on clients and the aggregation of models, which could limit scalability in resource-constrained environments.  
Overall, our dynamic handover algorithm provides a robust solution to the challenges of handover management in mobile networks. Future work can build on these findings by exploring advanced machine-learning techniques and expanding the algorithm's applicability to diverse network environments.
# Carbon Nanotube-Based Composite Filaments for 3D Printing of Structural and Conductive Elements
## 1 Introduction
Due to the development of new kinds of specialized composite materials used in FDM technology, 3D conductive structures can also be obtained, which opens an original path for the development of consumer electronics. One of the functional phase materials that improves both the mechanical properties of the composite and introduces electrical conductivity to the polymer composites is carbon nanotubes. In this study, we present the manufacturing process of acrylonitrile butadiene styrene (ABS) matrix composite filament filled with different amounts of carbon nanotubes (CNT). The mechanical and electrical behavior of printed structures is analyzed and described. The developed group of materials is expected to be used in the manufacture of structural and printed electronics using the additive FDM technology. The main goals of developing a composite filament with improved mechanical properties, as well as good electrical conductivity combined with appropriate rheological and processing parameters that also allow its use also with simple, non-industrial FDM printers, have been achieved.
## 4 Experiments Analysis and Discussion
### Impact of Different Parameter \(S\)  
TSNN-ESTD fuses the results of long-term prediction (\(\gamma 1_{Long}\in\mathbb{R}^{\mathrm{N\times L}},\gamma 2_{Long}\in\mathbb{R}^{ \mathrm{N\times L}}\)) and short-term \(\big{(}\gamma 2_{short}\in\mathbb{R}^{\mathrm{N\times S}},\ L=n\times S\big{)}\) prediction by the strategy of weighted average. This section addresses the problem of choosing the time step \(S\) for short-term prediction. Specifically, we fixed the input time step as 96 and the long-term prediction time step as 288, and, on this basis, integrated the results of the short-term forecast with different time steps from 1 to 288, as shown in Figure 4. The TSNN-ESTD model makes multiple copies of the results of the short-term predictions to align the long-term predictions. Therefore, if the short-term time step \(S\) is too short, it will not capture the periodicity of the prediction rule, which may interfere with the long-term performance. Conversely, a too long short-term time step \(S\) does not play a role in correcting long-term bias. With a sampling frequency of 1 h for the ECL dataset, the prediction error shows a significant optimization when the parameter \(S\) is set to 24, which happens to show a strong correlation with the daily cycle variation. Exchange and Weather datasets are recorded with a frequency of 1 day and 10 min, and the curves do not fluctuate greatly. However, the curves all show a trend of decreasing at first, reaching the lowest point when the time step is around 24, and then gradually increasing. Therefore, it is recommended to set \(S\) to 24 for most application scenarios.
## 4 The Compressive Acquisition Model for Gas Data Flow
### Two Different Networks for the Transmission of Gas Data Flow
#### 4.1.1 The Single-Hop Mode  
As illustrated in Figure 3, the current study assumed that all mobile gas detection instruments were within the communication range of wireless access points, periodically measured the environmental gas data and directly sent the data to wireless access points (fusion centers).  
Assume that \(N\) denotes the number of mobile gas detection instruments and \(x_{j}\) denotes the gas data measured by the \(j\)-th sensor. According to the requirements of compressed sensing theory, the measured gas data by each mobile gas detection instrument at \(M\) time intervals were multiplied by \(M\) random coefficients \(\left\{\Phi_{i,j}\right\}_{i=1}^{M}\), and the products were then transmitted to wireless access points. The random coefficients were generated by setting the ID of the mobile gas detection instrument as the seed of the pseudo-random sequence generator. At the \(i\)-th time interval, \(N\) mobile gas detection instruments simultaneously transmitted \(\Phi_{i,j}x_{j}\) to wireless access points; therefore, the signal received by the wireless access point at the i-th time interval can be written as [23; 24]:  
\[y_{i}=\sum_{j=1}^{N}\Phi_{i,j}x_{j} \tag{4}\]  
At each time interval, the signal received by the wireless access point is the sum of all the \(N\) measurements of mobile gas instruments multiply the \(N\) random coefficients \(\left\{\Phi_{i,j}\right\}_{j=1}^{N}\), so the wireless access point is also called fusion center.  
At the end of \(M\) time intervals, the signal vector received by wireless access points can be written as: \(\mathbf{y}=[y_{1},\cdots,y_{M}]^{T}\). In a matrix form, \(y\) can also be rewritten as follows:  
\[\mathbf{y}=\mathbf{\Phi}\mathbf{x} \tag{5}\]  
where \(\mathbf{\Phi}\) denotes an \(M\times N\) matrix.  
Although the transmitted gas vector \(\mathbf{x}\) is not sparse, gas vectors can be regarded to be sparse in some transform domains due to the spatial correlation of physical phenomena. By assuming the gas vector \(\mathbf{x}\) has a decomposition coefficient \(s\) under certain orthogonal bases, and \(s\) is sparse, the following expression can be acquired:  
\[\mathbf{y}=\mathbf{\Phi}\mathbf{x}=\mathbf{\Phi}\mathbf{\Psi}\mathbf{s} \tag{6}\]  
It can thus be transformed into a standard compressed sensing problem.  
Figure 3: Single-hop wireless networks.
## 1 Introduction
used a ferroelectric liquid crystal-based spatial light modulator to develop a simple but fast DOPC system that focuses light not only through, but also inside, scattering media. They employed a ferroelectric liquid crystal-based SLM to achieve binary-phase modulation for high speed and high focusing quality [26]. At present, some scholars in China are interested in researching the relevant performance of DOPC from theoretical and practical aspects [27; 28; 29; 30; 31; 32]. However, most of the above-mentioned DOPC systems use four-step phase-shifting holography to extract the speckle phase. This method requires four interferograms to be acquired continuously in the experiment. The phase shift of the corresponding reference light is 0, \(\pi\)/2, \(\pi\), and \(3\pi\)/2, and the acquisition time of the images greatly limits the time reversal efficiency of the digital optical phase conjugate system. In this paper, an optical phase conjugate system based on off-axis digital holography is designed. The phase distribution of the speckle is calculated by collecting only one interference image at a time. Compared with the four-step phase shift method, the phase acquisition time is greatly shortened, and the optics phase conjugate efficiency is also improved. At the same time, we tested the reduction performance of the phase conjugate system, and optical focusing through the diffuser is achievable.
## 2 Materials and Methods
### The Design of a Method for Finger Vein Image Deblurring Restoration Tasks  
The blurred finger vein image can be expressed as follows [19]:  
\[Img_{fv-blur}=K\otimes Img_{fv-sharp} \tag{1}\]  
where \(Img_{fv-blur}\) refers to a blurred finger vein image, \(Img_{fv-sharp}\) refers to a clear finger vein image, \(K\) denotes the blur kernel, and \(\otimes\) denotes the convolution operation. For the blurring problems encountered with finger vein images, we have divided them into two categories: Gaussian blurring and motion blurring. Gaussian blur is an imaging blur caused by the focal length of the image sensor of the finger vein capture device; motion blur is caused by the relative motion between the image sensor of the finger vein capture device and the finger of the person being captured. The blurring of finger vein images is variable due to different external factors and physical environments, so different blurring kernels need to be selected to deal with different finger vein image blurring problems. However, in practical applications, the method is not robust and generalization because of the unknown blurring kernels of the image and significant computing resources to identify the appropriate convolution kernel.  
In this study, assuming that the blurring kernels are unknown, we propose a method for blurring restoration of finger vein images that is appropriate for various environments. Accordingly, we have designed a finger vein deblurring generative adversarial network based on the DeblurGAN-v2 network with the Inception-Resnet-v2 backbone and evaluated the framework on diverse dataset. While the original DeblurGAN showed good performance in the deblurring task, the improved DeblurGAN-v2 has shown exceptional performance in both the deblurring effects and the extraction of image features. In the following discussion, the design ideas of the deblurring method in this paper will be described in detail in terms of three aspects, namely the generator, discriminator, and loss function of the network.
# Regolith-Rich PEEK Composite Bricks: Steps Towards Space-Ready Lunar Construction Materials
## 1 Introduction
### Insights from Previous PLA-Based Samples  
The manufacturing process developed in this study relies on a thermoplastic phase. This choice allows the raw powders to transform into the final product simply by heating above the polymer's melting point, without any chemical reaction. Additionally, dry processing simplifies the initial blending and reduces overall complexity. Thermoplastics also offer recyclability [15]: components can be crushed, remelted, and reshaped, making them a sustainable and efficient choice for space applications. Selecting an appropriate grade is critical due to the extreme conditions in space, such as large temperature fluctuations (from +124 \({}^{\circ}\)C at the equator to \(-\)178 \({}^{\circ}\)C before sunrise [16]), high vacuum (10\({}^{-11}\) mbar overnight to 10\({}^{-9}\) mbar during the day [17]), radiation, and potential meteorite impacts. Additionally, the mechanical properties of the thermoplastic are essential, as they establish the performance limits of the composite material in this context [10].  
In the companion paper [5], PLA (polylactic acid) was used as a non-space-grade option to simplify the initial phase of process understanding. This choice allowed for a rapid assessment of key parameters before transitioning to specialized polymers that are more challenging to process. The study focused on compression and bending strengths, finding that both properties improved with increased binder content (investigated between 5 wt% and 20 wt%), higher compaction pressures (0.50 MPa to 5.00 MPa), and a heterogeneous grain size distribution within the regolith phase. At just 10 wt% binder, the compression strength met the Earth construction requirements per the ASTM standards for industrial floor [18], building [19], and hollow bricks [20], while the equivalent requirements on the  
Figure 1: Proof-of-concept designs for interlocking elements made from regolith-rich composite material, demonstrating the feasibility of constructing modular, mortar-free structures using minimal thermoplastic binders.  
Moon, scaled down by the same factor as lunar gravity [21; 22; 23; 24], were already met at 5 wt%. Compression strengths equivalent to concrete (grades 20 to 85 MPa) [25; 26] for foundational and structural uses on the Moon were achieved with 5 wt% binder, though the bending strength results were less conclusive due to the setup limitations. This study seeks to further advance the technology by integrating advanced thermoplastics as the binder, optimizing process parameter selection, and evaluating the influence of critical environmental factors on both the manufacturing process and the quality of the final products.
# Computing the Matrix Logarithm with the Romberg Integration Method
## 2 Romberg Method for the Matrix Logarithm  
In this section, a theoretical study of the error committed by the inverse scaling and squaring Romberg method is carried out. This will allow us to determine the number of iterations \(m\) required by the Romberg method, so that the error incurred in the calculation of the logarithm of a matrix, previously scaled \(s\) times, is less than or equal to the unit roundoff. We provide algorithms for the calculation of the suitable values of the scaling parameter \(s\) and the number of iterations \(m\), as well as for computation of the matrix logarithm using the Romberg technique.
# A Novel Real-Time Virtual 3D Object Composition Method for 360\({}^{\circ}\) Video
## 1 Introduction  
Three-hundred-and-s Sixty-degree video is receiving attention as highly immersive virtual reality (VR) content, where users can observe all viewpoints in their desired direction from the fixed position where the video is recorded, through the intentions of the videographer (who dictates environment position and height). Such video has been used to create highly realistic virtual environments not only in the media industry, including the capture of live performances, movies, and broadcasting, but also in education and games. It can provide a higher sense of immersion to users through the insertion of a computer-graphics-based virtual object, and subsequent user interaction with this inserted virtual object. These techniques have become essential elements for VR content. Typical examples include synthesizing virtual characters or objects in VR movies or displaying information markers in a 3D virtual space. This technique of inserting virtual objects into 360\({}^{\circ}\) video is called 3D composition.  
In general, 360\({}^{\circ}\) video is viewed by wearing a head-mounted display (HMD). Many people experience physical discomfort and symptoms such as headaches, disorientation, and nausea when they wear an HMD [1]. This is VR motion sickness. One of the reasons this occurs is due to the user receiving insufficient updates regarding sensory information from the vestibular system [2].  
When 360\({}^{\circ}\) video content includes fast camera movement, visual information keeps changing but the user's actual body position is fixed, which causes motion sickness. For this reason, most 360\({}^{\circ}\) video clips are taken from a fixed position. Synthesizing a virtual object into a fixed 360\({}^{\circ}\) video clip does not require a long processing time. The clip can be inserted at the desired position from the center of the camera. There have recently been various types of VR content used in film, education, and tourism which include stable movements filmed using special drones or cars. In the case of a 360\({}^{\circ}\) video clip including camera motion, a process of synchronizing the motion of the Red-Green-Blue (RGB) camera (actual camera) and a virtual camera is applied for the 3D composition. This process works by extracting internal (focal length) and external (position and rotation) parameters from the RGB camera used to capture a real scene [3, 4]. From these parameters, we can retrieve the motion of the RGB camera, and this is called camera tracking [5]. The traditional 3D composition method estimates the trajectory of the camera by analyzing the feature points of each frame from the captured images. This method has a disadvantage in that the video resolution and camera-tracking processing times are proportional, and the composition results can only be confirmed after several processes (e.g., recording and camera tracking).  
In this paper, we propose a novel method using stereo vision that can extract a depth map in real-time for 3D composition, rather than the traditional method using captured images.
###### Abstract  
Water shortage threatens agricultural sustainability in Horqin Sandy Land, northeast China. To explore the effects of various surface mulching patterns with micro-spray irrigation on the yield, water consumption (ET\({}_{\text{c}}\)), and water-saving potential of maize (_Zea mays_ L.), we used three treatments: straw mulching (JG), organic fertilizer mulching (NF), and no mulching (WG; control). In each treatment, plants were supplied with 500 mm of total water (irrigation plus precipitation) during the entire growing season and were irrigated with the amount of total water supply minus precipitation. Yield and water use efficiency (WUE) showed a significant negative correlation with water saving potential per unit yield (P\({}_{\text{y}}\)) and water saving potential per unit area (S\({}_{\text{p}}\)), which were also consistent with their relationships in the function model. Meanwhile, a remarkably positive correlation occurred between yield, WUE, and net economic profit, respectively. The JG treatment, which was mainly affected by light and temperature production potential (Y\({}_{\text{c}}\)), grain yield, and ET\({}_{\text{c}}\), showed the lowest P\({}_{\text{y}}\) (0.16 m\({}^{3}\) kg\({}^{-1}\)) and S\({}_{\text{p}}\) (2572.31 m\({}^{3}\) km\({}^{-2}\)), and the maximum increase in yield, WUE, and net economic profit, extending to 16,178.40 kg hm\({}^{-2}\), 3.25 kg m\({}^{-3}\), 17,610.09 yuan hm\({}^{-2}\), respectively, which were significantly higher than those in NF and WG, (_p_ <0.05). Thus, straw mulching with micro-spray irrigation was the best treatment for maximizing yield and WUE. Organic manure mulching and no mulching need further investigation, as these showed high P\({}_{\text{y}}\) and S\({}_{\text{p}}\), which were together responsible for lower WUE.  
water resources; surface mulching; water saving potential; micro-spray irrigation; economic profit +
Footnote †: journal: Applied Sciences