esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Experimental Methods
### Surface Roughness  
The surface roughness of the BJ3 DP test pieces was evaluated using a Keyence VK-X3000 laser microscope (Keyence, Osaka, Japan) equipped with a white-light interferometer. This non-contact measurement system provides high spatial resolution with a precision of 0.1 nm, enabling an accurate detection of micro-scale surface variations that contact-based profilometers may not fully capture. Surface roughness measurements were conducted on a representative sample fabricated using the BJ3 DP process. Figure 5 shows the measurement area. From this figure, ten distinct lines, labeled 1 through 0, were selected for detailed evaluation. The corresponding roughness values for these lines are summarized in Table 1.  
The average arithmetic mean roughness (\(S_{\text{a}}\)) across the evaluated area was 9.14 \(\upmu\)m, while the maximum height roughness (\(S_{\text{z}}\)) reached 108.5 \(\upmu\)m. These results indicate a significantly rough surface characteristic of the components produced by metal additive manufacturing processes like BJ3 DP.  
According to [PERSON] et al. [44], test surfaces with higher roughness values within a reported range of Sa = 0.045 to 1.22 \(\upmu\)m demonstrated improved heat transfer performance in pool-boiling applications. While the average Sa measured in the present study (9.14 \(\upmu\)m) exceeds this specific range cited by [44], the enhanced complex surface topography produced via additive manufacturing is expected to promote bubble nucleation and vapor-liquid interactions significantly. The literature also suggests that the relationship between roughness and heat transfer enhancement depends on the specific surface preparation method. Consequently, despite exceeding the range from this particular study, the high and complex roughness achieved through BJ3 DP is anticipated to positively impact boiling heat transfer efficiency by providing a high density of active nucleation sites.
###### Abstract  
The effects of black seed (_Nigella sativa_), allspice, bay leaf, caraway, cardamom, clove, and nutmeg extracts on the quality of raw ground chicken legs stored at 4 \({}^{\circ}\)C were investigated. During 12 days of storage, conjugated diene (CD) content, thiobarbituric acid reactive substances (TBARS), oxidation induction time (IP) by DSC (differential scanning calorimetry), hexanal content by GC-SPME-MS, thiol group (SH) content were determined. Moreover, microbial growth, pH and color of the samples were investigated. Sensory analysis was also realized. All extracts increased oxidative stability and safety of meat, significantly changed the color of the samples, stabilized the pH and increased their sensory scores (except color of samples with bay leaf and black seed) when comparing to control. Black seed, allspice and clove extracts showed high antioxidant capacity in lipid (CD = 0.23%, 0.28%, and 0.37%, respectively; TBARS = 0.55, 0.50, and 0.48 mg/kg, respectively) and protein fraction (SH content = 47.9, 52.1 and 52.7 nmol/g, respectively), although the ABTS\({}^{\star+}\) radical scavenging activity of black seed (33.1 \(\upmu\)M/g) was significantly lower than the cloves (2496 \(\upmu\)M/g) and allspice (815 \(\upmu\)M/g). In the sensory analysis the highest scores were ascribed to the sample with cardamom followed by cloves. Principal component analysis (PCA) indicated complex and inseparable interrelationship among lipid and protein oxidation processes and the relationship of the protein oxidation on the lightness of meat. The results enabled to discriminate the meat samples, showing a great impact of the extracts on the final quality of raw chicken meat with black seed being potent antioxidant active additive.  
black seed; cloves; allspice; spice extracts; lipid oxidation; protein oxidation; raw chicken meat; microbiological analysis; chemometric analysis +
Footnote †: journal: materials  
_Antioxidants_**2020**, \(9\), 903; doi:10.3390/antiox9090903
## 4 Results and Discussion
Briefly, we can state that dynamic provisioning of containers and respective microservices were tested and evaluated using a computing cloud where the user-defined number of data centers was established for a real evaluation of the part of the framework schema. The simulation findings showed that the predistribution of microservices depending on their levels of engagement activities greatly decreases carbon dioxide emissions while increasing green energy use [58]. The usage of cutting-edge container microservice architecture required the use of several containers scattered across various data centers in the cloud environment. The suggested microservice ranking technique [58] allowed services to be separated from one another, resulting in groups of microservices that may be hosted in geographically scattered data centers. It infers that a rank-based distribution lowers the communication latency considerably. It however, requiring performing intensive modeling and simulation of containerized computing environments using a software package named ContainerCloudSim [59], which is an extension of CloudSim. Moreover, to test in the real-world environment, it needs to use DeathStarBench [60] which is an open-source benchmark suite for cloud microservices. DeathStarBench provides end-to-end services including social network, hotel reservation service, and media service. The proposed conceptual framework will be tested on well-known input parameters and variables and deployment scenarios (hybrid cloud/multicloud/federated cloud). The key evaluation parameters will include power  
Figure 12: Response time over a period of 12.5 h when microservices are deployed using the arbitrary distribution model. Figure 13: Response time over a period of 12.5 h when microservices are deployed using the design-pattern distribution. usage efficiency (PUE), server utilization rate, server refresh rate, virtualization ratio, and carbon footprint.
## 4 Control System Design  
### Control System Hardware Design  
The control motherboard is the core hardware of the underwater control system, and its main control chip adopts STM32F103 VET6. As shown in Figure 8, the control motherboard consists of three layers of circuit boards. The first layer of the circuit board mainly includes a main control chip, two motor drive modules, a communication module, a power interface, and two underwater lighting interfaces. The second layer of the circuit board mainly includes two waterproof motor interfaces, a depth sensor module, and an attitude sensor module. The third layer of the circuit board is mainly composed of six thruster interfaces and electronic speed modules.  
Figure 7: Physical diagram of the control box. (**a**) Diagram of the control box’s internal parts. (**b**) Overall structure diagram of the control box.  
In order to ensure that the digital and analog signals on the control panel can be directly read by the embedded computer, a digital analog acquisition module is designed using an STM32F407 VET6 chip. As shown in Figure 9, the acquisition interface for digital and analog signals is designed on the module, which can collect various signals of the rocker, the button, the knob, and other components on the control panel and connect to the embedded computer through USB to a 485 serial port converter. The output end of the 24 V switching power supply is connected to the acquisition module and directly used to supply power to the module. The ROV's interface on the module outputs a 24 V voltage, which is connected to the DC contactor to supply power to the ROV. The DC voltmeter on the control panel and the battery in the control box are connected to the power interface on the module, and the battery power can be displayed on the voltmeter. The acquisition module is installed on the back of the control panel, which is conducive to the connection between the components on the control panel and the module.  
The application of the power carrier module in ROV communication has the advantages of simplifying wiring, improving reliability, real-time data transmission, remote control, and monitoring. Its characteristics of adapting to complex environments, data security, compatibility, and scalability give it broad application prospects in underwater operations. In this paper, power carrier communication is used to communicate between the upper computer and the lower computer, as shown in Figure 10, which is the power carrier module designed in this paper.  
Figure 8: Control motherboard.  
Figure 9: Digital analog acquisition module.
## 5 Gaofen-3 Time Series Results Analysis and Comparison  
### The Subsidence Results Acquired from Gaofen-3 Images  
Since the incidence angles of the Gaofen-3 and Sentinel-1 SAR images are different, all the los (Line of Sight) velocities derived from the two datasets were converted into vertical direction by dividing the corresponding factor \(cos\theta_{inc}\) (\(\theta_{inc}\) is the incidence angle) to avoid incidence angle interference [25]. A map of mean velocity derived from the Gaofen-3 SAR images over the study area from September 2020 to April 2021 is shown in Figure 9. The negative velocities represent the subsidence (red color) that moves away from the sensor, and the positive velocities represent the uplift (blue color) that moves towards the sensor. According to the InSAR-derived results from the Gaofen-3 SAR images, the average subsidence rate ranged from \(-80\) mm/a to \(30\) mm/a in the vertical direction in the study area. For most metropolitan areas over Beijing, the land subsidence velocity ranged from \(-15\) mm/a to \(15\) mm/a. It can be seen from Figure 9 that the observed subsidence mainly occurred inside the Chaoyang District and Haidian District (red dashed lines in Figure 9). The primary large-scale subsidence bowl is observed at the northeastern part of Chaoyang District with \(--80\) mm/a, where cumulative subsidence was as high as about \(40\) mm from September 2020 to April 2021, as shown in the time-series results map of the feature points (black star in Figure 9) in Figure 10. There was another subsidence bowl with a relatively lower subsidence velocity at \(--73\) mm/a at the northwestern part of Haidian District. The most severe subsidence bowls in Beijing have subsided up to \(-40\) mm from September 2020 to April 2021. As shown in Figure 9, the uplift areas are distributed randomly and caused by some phase noise, and they could not be removed completely from the interferograms due to the limited interferograms for time-series processing.  
Figure 8: The refined wrapped interferograms of the Gaofen-3 SAR images by removing the orbit-related artifacts.
## 1 Introduction
Therefore, it is necessary to further optimize the structure of protective boxes and explore methods of uniform thickness protection in all directions, resulting in better weight, volume, and protection. The main objective of this work is to provide complete protection for both the detectors and electronics in the system. The protective box design was investigated based on geometry relations, in addition to shielding implementation for the detectors. The Geant 4 Monte Carlo Simulation Toolkit [23; 24] was used to simulate particle-material interactions and evaluate the shielding characteristics of materials. The optimal combination of multilayer shielding materials was calculated using the particle environment at the FY-3 satellite's orbit altitude. All materials thicknesses mentioned in this paper were converted to equivalent Al thicknesses for better weight comparison. Finally, future improvements and potential solutions were outlined.
## 3 Method
### Neighborhood Microimage Selection Under Multiple Constraints
#### 3.1.1 Photometric Consistency Constraints  
Photometric consistency is a key means for increasing the accuracy of feature point matching. It assumes that corresponding feature points of the same object should exhibit similar illumination intensities from different viewpoints [30]. Through photometric consistency constraints, the matched feature points can maintain similar photometric values across different viewpoints, effectively filtering out unreliable matches and thereby improving the accuracy and robustness of the matching process.  
During the neighborhood selection process employed for light field microimages, two key factors are considered: photometric consistency and the number of matching feature points. High photometric consistency means minimal illumination differences between adjacent images, ensuring stable textures. More matching feature points suggest more distinct features and complex textures, aiding accurate matching.  
Figure 1: Workflow of Our method.  
During the feature point matching process, a small window centered on each potential matching point is selected, and its photometric consistency is measured by calculating the luminance differences in all the pixels within the window. To increase the attained matching accuracy, the normalized cross-correlation coefficient (NCC) is employed to evaluate the similarity of the pixels within the window. If an NCC value exceeds a preset threshold, the photometric consistency is considered good, and the corresponding matching point is deemed reliable; conversely, if the NCC value is low, it indicates a significant photometric difference, and the matching pair is regarded as a mismatch and thus excluded.  
Consequently, eliminating feature points with substantial photometric differences during feature point matching aids in providing more effective visual features for the subsequent depth estimation task, thereby enhancing the precision and robustness of the developed algorithm.
# Optimizing DNA Sequence Classification via a Deep Learning Hybrid of LSTM and CNN Architecture
## 4 Proposed Model  
### Pre-Processing  
Raw DNA sequences were preprocessed so that they are deep learning model compatible. The following steps were utilized:  
**One-Hot Encoding:**  
Each nucleotide (A, T, C, G) was encoded as a 4-dimensional binary vector (e.g., A = [1, 0, 0, 0]).  
The encoding preserves the categorical representation of DNA sequences without introducing ordinal bias.  
**Sequence Padding/Truncation:**  
Sequences were padded/truncated to a fixed length of 100 nucleotides (nt) for LSTM input requirements.  
Shorter sequences were end-zero-padded, while longer sequences were truncated. This length was employed to sacrifice computational efficiency in favor of the retention of biologically relevant motifs.  
**Z-Score Normalization:**  
Figure 1: Data distribution.  
This was applied to numerical features (e.g., k-mer counts) to scale the input.
## 1 Introduction
Our attention has been channeled to cost-effectively increase the overall antenna efficiency with a widened bandwidth, with lower weight, and with a reduction in fabrication costs [4; 27; 28]. The main objective of the paper is to propose microstrip LWAs with a low profile and to analyze the bending effects. The bending effects in a microstrip transmission line need to be analyzed rigorously along with the dispersion analysis. The authors have made an effort to propose designs that are low profile, compact, easy to fabricate, low cost, and have achieved good antenna characteristics with frequency scanning in the operating frequency band.
# Scan to BIM Mapping Process Description for Building Representation in 3D GIS
###### Abstract  
This paper introduces a novel approach for mapping process description with Scan data to Building Information Modeling (BIM) in a 3D Geographic Information System (GIS). The methodology focuses on automatically generating building mass and facade information on the GIS platform using Point Cloud Data (PCD) of Airborne Laser Scanning (ALS). Advanced scanning techniques capture detailed geometry from the physical site and generate high-resolution point clouds, which are processed to create 3D models for GIS integration. The critical contribution of this research lies in a scalable Scan to BIM mapping process, which can be used for generating building footprints and masses, including attributes, on 3D GIS. The resulting integrated BIM-GIS dataset provides an accurate building mass, facade information, facility asset management, and architectural design and facilitates improved decision-making in urban planning based on enhanced visualization, analysis, and simulation. This study suggests a flexible Scan to BIM mapping process description based on use cases, including algorisms. Through prototype development, a case study demonstrates the effectiveness of the process approach, the automatic generation of BIM on a 3D GIS platform, and reducing the manual efforts. The proposed method automatically creates DEM, SHP, GeoJSON, IFC, and coordinate system information from scan data and can effectively map building objects in 3D GIS.  
scan; ALS; BIM; GIS; mapping; description; digitalization Article
# LSANet: Lightweight Super Resolution via Large Separable Kernel Attention for Edge Remote Sensing
## 4 Implementation Details
### Ablation Study
#### 4.4.1 Effectiveness of Feature Extraction Module  
To validate the effectiveness of RLSKAB and determine the optimal large separable kernel attention configuration, this ablation study systematically experiments with the LSKA settings listed in the table. Table 3 presents the model performance when using different feature extraction modules. The two values in the \"LSKA Size\" column denote the kernel sizes of the depthwise convolution and depthwise dilated convolution (DW-Conv and DW-D-Conv) in the large kernel attention mechanism.  
According to the data in the table, compared with Experiment (a) using only SRB as the feature extraction module, Experiment (b) incorporating RLSKAB achieves significant improvements: PSNR increases by 0.20 dB and SSIM by 0.0023, accompanied by a 39.3% reduction in parameters and 41.4% decrease in computational complexity. This demonstrates that RLSKAB enables more efficient feature extraction. Further analysis of Experiments (b)-(f) reveals that as the LSKA scale increases, the model's computational cost slightly rises while performance continues to improve. For instance, Experiment (d) outperforms Experiment (b) with a 0.06 dB PSNR gain and 0.0018 SSIM improvement, while the computational overhead only increases by 11.0%.  
Considering that the improvement of experiments (e) and (f) is limited compared with (d) (PSNR decreases by 0.04 dB and increases by 0.02 dB, respectively, and SSIM decreases by 0.0013 and increases by 0.0006, respectively), experiment (d) is finally selected as the optimal solution as the basis for subsequent experiments, and the corresponding LSKA size is (5, 7).
## 3 Void Avoidance Algorithm (VAA)
### Distance Cost (DC)  
DC from each sensor node to the BS is defined as (TD\({}_{\text{k}}\), \(\ldots\), \(\ldots\), TD\({}_{\text{2}}\), TD\({}_{\text{1}}\), VD). VD is virtual distance, initially set to Euclidian distance (ED) from the node to the BS. TD\({}_{\text{1}}\)\(\ldots\) TD\({}_{\text{k}}\) are tag distances and initially set to NULL. These tag distances help void nodes turn into non-void nodes, if the nodes remain void after upgrading VD.  
A study that characterized the impact of routing holes on geographic routing shows that the majority of voids can be circumvented in four hops or less [24]. Considering this fact from [24], we design DC as a three-tuple (TD\({}_{\text{2}}\), TD\({}_{\text{1}}\), VD) that can construct void-free topology. In most cases, two TD fields are sufficient to create void-free topology. Our simulation results in random topology with various average node degree, as in Figure 23, shows the number of upgrades required to circumvent voids. However, it can be increased based on network size. Figure 6 illustrates the DC. Figure 6 (a)  
Figure 6: Distance cost.  
shows the TDs and VD's positions. In Figure 6 (b) node n\({}_{0}\), n\({}_{1}\) and n\({}_{2}\) have NULL value for TD\({}_{1}\) and TD\({}_{2}\) and ED value for VD. Figure 6 (c) shows the DC with values.  
The precedence of DC is in lexicographic order. Our algorithm upgrades stuck nodes' ED temporally that is called VD. It restores the ED if any node finds itself as a non-stuck node.
## 5 On-Site-Application Effect  
The strike length of the 824-machine roadway in the XT Coal Mine is about 1547 m and the dip length is approximately 246 m (Figure 8). The stratigraphic column is shown in Figure 9. The HAAS for deep, fully mechanized roadways was officially installed in January 2018. During the trial excavation process from February to March, the stability tests for single-machine operations and multimachine linkage operations were implemented. The normal production began in April and the production capacity met the design  
Figure 7: (**a**) Stress and (**b**) displacement distributions of the advance support under different roof-dip angles.  
2. Wide coverage of the roof support: The hydraulic support delivers effective support to the roof within 6 m of the roadway head, leaving abundant safe space for operators in the roadway head.
3. Success in remote control: The operators stand under the permanent support at the back of the advance support so that they can operate the hydraulic system away from the roadway head. In this way, they have no need to approach the roadway head or receive safety threats from the roof, thereby achieving intrinsic safety.
4. High adaptability of the support: Since the support is well-adapted to changes in the roof-dip angles and roadway slopes, it can be widely used in various roadways with complex conditions.
5. Improvement of the working cycle: Compared with traditional temporary supports, the hydraulic support with a long step distance extends the working cycle from 1.6 m to 3.2 m, which greatly boosts the single heading level of roadway excavation.
6. Improvement of support efficiency: The support with low labor intensity is run by only one person. It performs continuous operations of excavation and support. By using support for an extensive cover, the parallel operations with two anchor-drilling machines are now implemented by four machines, greatly improving the efficiency of roadway support.