esa-sceva/satcom-chunk-collection huggingface dataset:
# Three-Dimensional Processing of Reflections for Passive-Source Seismology Based on Geometric Design
## 4 Conclusions  
Seismic exploration based on reflections from a passive source uses the imaging of background noise, is cheap, and can be used as an effective supplement to methods of  
Figure 19: (**a**) Migration profile of 3D virtual shot records obtained by using a geometry with a wide azimuth. (**b**) Direct migration profile of reflection from a 3D passive source using a geometry with a wide azimuth.  
exploring deep active seismic sources. However, its computational cost and storage-related requirements constitute constraints on its further development.  
Using a geometry based on the given geological structure can solve the above problem in practice. A set of geometric parameters that are suitable for the given area can reduce the cost of acquisition and the difficulty of data processing while improving their resolution. In this paper, we used experience in processing data on seismic exploration based on reflections from a 3D active source to design a reasonable and efficient geometry to obtain data for a 3D passive source. On the premise of ensuring a high signal-to-noise ratio, uniform folds, and reasonable azimuth, we used SPS files to guide the relevant correlations and obtain the virtual shot records; this improved the computational efficiency. At the same time, we obtained data on reflections of waves from the 3D passive source through forward modeling, and generated a clear seismic profile by calculating according to the above process.  
In addition, we tested the feasibility of imaging based on direct migration using random reflection-induced noise. The method of generating virtual shot records is similar to the migration imaging algorithm based on correlation-based imaging conditions, that is, this method of migration can omit the correlations in the virtual shot records, thus reducing the requisite computational resources and storage space and improving efficiency. After intercepting multiple, random time windows of noise for multiple folds, the results also yielded images of high quality. The proposed method is thus efficient in terms of the seismic exploration of a passive source based on reflections.  
The proposed method can accelerate the calculation of reflections from a passive source, and its many virtues can help promote the use of such technology on a large scale.  
Conceptualization, Y.L.; Software, Y.L.; Validation, Y.L.; Writing-original draft, Y.L.; Project administration, G.L.; Funding acquisition, G.L. All authors have read and agreed to the published version of the manuscript.  
This study was supported by the NSFC (Grant No. 42074131), and the National Key R&D Program of China (Grant Nos. 2021 YFC2801404 and 2022 YFC280016803).  
Not applicable.  
The authors declare no conflict of interest.
## Appendix B  
The accuracy of different models is measured in terms of three common statistical indicators very often used in solar radiation modeling, i.e., coefficient of determination (\(R^{2}\)), normalized root mean square error (\(nRMSE\)), and normalized mean bias error (\(nMBE\)):  
\[R^{2}=1-\frac{\sum\limits_{i=1}^{M}{(m_{i}-c_{i})^{2}}}{\sum\limits_{i=1}^{M}{(m _{i}-\overline{m})^{2}}} \tag{10}\]  
\[nRMSE=\frac{\left[{M\sum\limits_{i=1}^{M}{(c_{i}-m_{i})^{2}}}\right]^{1/2}}{ \sum\limits_{i=1}^{M}{m_{i}}} \tag{11}\]  
\[nMBE=\frac{\sum\limits_{i=1}^{M}{(c_{i}-m_{i})}}{\sum\limits_{i=1}^{M}{m_{i}}} \tag{12}\]  
where \(c\) and \(m\) refer to the estimated and measured values, respectively, \(\overline{m}\) is the mean of measured values, while \(M\) denotes the number of measurements.
# Crystal Structure of Human Lysozyme Complexed with \(N\)-Acetyl-\(\alpha\)-D-glucosamine
###### Abstract  
Human lysozyme is a natural non-specific immune protein that participates in the immune response of infants against bacterial and viral infections. Lysozyme is a well-known hydrolase that cleaves peptidoglycan in bacterial cell walls. Several crystal structures of human lysozyme have been reported, but little is known regarding how it recognizes sugar molecules. In this study, the crystal structures of human lysozyme in its native and two \(N\)-acetyl-\(\alpha\)-D-glucosamine (\(\alpha\)-D-NAG)-bound forms were determined at 1.3 A and 1.55/1.60 A resolution, respectively. Human lysozyme formed a typical c-type lysozyme fold and the \(\alpha\)-D-NAG molecule was bound to the middle of subsites C and D. The \(N\)-acetyl and glucosamine groups of \(\alpha\)-D-NAG were stabilized by hydrophobic interactions (Vall17, Ala126, and Trp127), hydrogen bonds (Asn64, Asn78, Ala126, and Val128), and water bridges. Conformational changes of Arg80, Tyr81, Val128, and Arg131 of human lysozyme were observed due to the interactions of \(\alpha\)-D-NAG with the active-site cleft. The binding configuration of \(\alpha\)-D-NAG in human lysozyme was distinct compared with that of other sugar-bound lysozymes. Findings from this structural analysis provide a better understanding of the sugar recognition of human lysozyme during the immune response to microbial pathogens.  
lysozyme; muramidase; \(N\)-acetylmuramide glycanhydrolase; human; \(N\)-acetyl-\(\beta\)-D-glucosaminidase; NAG; crystal structure  
1
# Improved Control Strategy of MMC-HVDC to Improve Frequency Support of AC System
## 4 Improved Inertia Control of MMC-HVDC
### Improved Inertia Response Control  
Figure 3 is an improved virtual inertia control loop diagram. The dq transformer gets values of the voltage and current from the AC system. Besides, as we need to calculate the ESCR of the AC system, we also get the rated power from the AC system. We use equation 8 to calculate ESCR and pass the result to (23). It can calculate the reference value of the DC voltage. Then, compare it with the actual DC voltage value to get the new result, and finally pass the signal generated by the PI controller to the inner loop controller. The value of \(\theta\) required for dq transformer is calculated by phase lock loop (PLL). In addition, we use Q controller to control the reactive power of the system.  
We assume that the loss of both the transformers and cables in the entire system is 0. If the entire power system is in a fully idealized state, then \(\Delta P_{1}\) is equal to \(\Delta P_{2}\), and both are 0. A new formula can be obtained by combining (15) and (18) as follows:  
\[\frac{2H}{f_{iAC}}\frac{d\Delta f_{AC}}{dt}=\frac{6N_{SM}C_{arm}\ V_{DC}}{P_{ DC_{total}}}\frac{dV_{DC}}{dt} \tag{19}\]  
Figure 3: Improved inertia control diagram.  
By simultaneously integrating both sides of (19) and recombining it with (8), we obtain (20):  
\[\int\frac{2H_{MMC}}{f_{i_{AC}}}\;df=\int\frac{6N_{SM}\text{C}_{arm}\;V_{DC}}{P_{ DC_{ntd}}}\;dV_{DC} \tag{20}\]  
\[2H_{MMC}\cdot\left(\frac{f_{AC}}{f_{i_{AC}}}\right)=\frac{6N_{SM}\text{C}_{arm} ESCR}{2S_{ac}}\left(V_{DC}^{2}-V_{DC_{i}}^{2}\right)+2H_{MMC} \tag{21}\]  
Based on (8) in subsection A, the formula for the inertia time constant of the MMC is calculated based on the ESCR of the AC system as follows:  
\[H_{MMC}=\frac{3N_{SM}\text{C}_{arm}\;V_{DC_{i}}^{2}\left[\left(\frac{\Delta V_ {DC}}{V_{DC}}+1\right)^{2}-1\right]ESCR}{2\frac{\Delta f_{AC}}{f_{i_{AC}}} \cdot\left(S_{AC}-Q_{CAC}\right)} \tag{22}\]  
where \(V_{dc_{i}}\) is the initial voltage of the MMC-HVDC, and \(V_{dc}\) is the actual voltage of the MMC-HVDC. As the capacitor of the submodules can store energy, the MMC-HVDC can supply reactive power to the system without additional reactive power compensators, and therefore \(Q_{C_{AC}}\) is 0. Thus, we can calculate \(V_{DC_{ref}}\) using (22) as follows [21; 23; 24; 25]:  
\[V_{DC_{ref}}=\sqrt{\frac{2H_{MMC}S_{AC}}{3N_{SM}\text{C}_{arm}\cdot\text{ESCR} }\left(\frac{f_{AC}}{f_{i_{AC}}}-1\right)+V_{DC_{i}}^{2}} \tag{23}\]  
The DC voltage reference is not calculated solely based on the frequency variation of the AC system in (23). Furthermore, changes in the rated capacity of the AC system and the robustness of the AC system can also affect the reference calculation of the DC voltage, as shown in Figure 4. Using (23), we can easily control the frequency stability of AC systems at various intensities.
## 5 Applications
### Cosmetics
Moreover, research has revealed avocado extract's other beneficial qualities, in addition to its beauty benefits. Its remarkable antibacterial and anti-inflammatory properties have been helpful in the treatment of infections and skin wounds [135; 139]. Furthermore, the extract's potential to help speed up wound healing is demonstrated by its capacity to reduce bleeding, mature scar tissue, and stimulate collagen synthesis. In summary, avocado extract's complex qualities make it an intriguing component with a range of advantages for skincare formulas, providing a comprehensive strategy for promoting and preserving skin health and vitality (2% addition of avocado oil) [135; 136; 140]. The fatty acid content of avocado contributes to its positive effect on the skin. They have well-known roles in energy production and storage, as well as in the synthesis of membrane lipid bilayers, but they also play important roles in other aspects of epidermal function. First, the permeability barrier depends on fatty acids and ceramides, one of the complex lipids made from fatty acids. Second, the complex lipids in sebum--which is secreted by sebaceous glands--are constructed by fatty acids. Thirdly, fatty acids are crucial for keratinocyte signaling that control epidermal homeostasis. Fatty acids, for instance, have the ability to bind to peroxisome proliferator-activated receptors, which enhances the permeability barrier and encourages keratinocyte development. Furthermore, they can alter skin signaling molecules. For example, they can control hair follicle development and epidermal homeostasis by palmitoylation proteins [141]. Beyond just directly benefitting the skin, avocado's bioactive components extend their effects through antibacterial, anti-inflammatory, and antioxidant properties, making them a versatile ingredient for overall skin health, protection against external aggressors, and preservative agents. The preservation qualities of avocados help skincare products last longer, maintaining their stability and effectiveness over time (0.5% addition of avocado oil) [139; 142]. All activities of avocado's bio-functional ingredients and their applications in cosmetic uses are summarized in Table 5. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Bio-Functional Ingredients** & **Activity** & **Application** & **References** \\ \hline Avocado Oil & Increase in collagen synthesis, reduction in the number of inflammatory cells, accelerating coagulation and regeneration of epithelium Reduction in wound area compared to control group & Wound healing & [135] \\ \hline Avocado oil & One-grade improvement in GLS (Global) aesthetic Improvement Scale) in 30\% and 45\% of participants after 6 and 12 weeks, respectively Significant increase in net elasticity (R5) and gross elasticity (R2) after 12 weeks & Anti-wrinkle cream & [136] \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Activities of avocado’s bio-functional ingredients and their applications in cosmetic uses.
# Automatic 2D Floorplan CAD Generation from 3D Point Clouds
## 2 Backgrounds and Related Works  
The main process when generating a 2D floorplan from unstructured 3D point clouds is to create BIM objects from 3D point clouds. This process can be divided into two steps, i.e., 3D reconstruction and conversion into a BIM format such as the industry foundation classes (IFC) format.  
3D reconstruction commonly consists of three parts after the acquisition of the point cloud: data preprocessing, plane segmentation, and plane classification. First, the 3D point cloud data are preprocessed to create structured data in order to save time during the process and achieve more efficient results. In 2D methods, the point cloud is represented as a set of images consisting of a slice of points or other information [8; 9]. In 3D methods, the point cloud is restructured as a voxel octree which allows efficient neighborhood searches [10]. Subsequently, the point cloud is segmented. Typically, lines are used for point cloud segmentation in 2D methods such as RANSAC based [8; 11; 12] and Hough transform based [13; 14; 15] methods, while planes are used for point cloud segmentation in 3D methods [10; 16; 17]. Finally, the segments are classified into categories such as floors and walls by using heuristics or machine learning techniques [18; 19; 20; 21].  
After 3D reconstruction, wall geometry modeling is the most important part of the next step. There have been several studies of the reconstruction of wall geometries. [PERSON] et al. and [PERSON] reconstructed planar wall boundaries and openings based on machine learning [18; 22]. [PERSON] and [PERSON] reconstructed severely occluded wall surfaces using Bayesian graph-cut optimization based on cell complex decomposition [23].  
The relationship between elements in a building leads at the end to the BIM establishment. Additionally, element topology can serve to describe building elements. Topological data assign spatial relationship information, whereas the dimensions and locations of elements are represented by geometrical data. Types of elements and relationships with other elements are associated with these processes. Several proposed models determine topological relationships among objects automatically. [PERSON] et al. presented an approach that automatically analyzes the topological relationships of building elements [24]. [PERSON] et al. implemented a prototype system for the semantic improvement of prior factual model files [25]. In their system, shared and slab collection concepts were acknowledged and topological, geometric, and other generic operators were used in collections of rule sets. [PERSON] et al. presented a semi-automatic algorithm which calculated the boundaries and adjacency of objects in 3D point clouds [26]. It generated depictions of objects in the IFC format.
# Two-Step Classification with SVD Preprocessing of Distributed Massive Datasets in Apache Spark
## 3 Proposed Method
### Classification Algorithms  
#### 3.2.1 Decision Trees  
Decision trees constitute a classification algorithm which can be represented as a tree structure [42]. The nodes of the tree represent features of the dataset and, depending on each feature's value, we navigate through the tree structure. This procedure continues until a leaf is reached, as a leaf represents an output class. The root of the tree is chosen as the feature which best partitions the training dataset by minimizing a loss function. This procedure is recursively executed to each subtree, each representing a dataset partition, until the training data are divided into subsets of the same class.
# Adversarial Sample Generation Method Based on Frequency Domain Transformation and Channel Awareness
## 4 Channel Estimation Method Based on Deep Learning
### The Super-Resolution Denoising Network Model Based on OMP Algorithm
#### 4.2.2 Online Estimation  
In the online estimation stage of channel estimation, the optimal parameter model obtained after offline training of the neural network will be deployed to the wireless communication system. In the process of online estimation, the system will first capture the real-time received signal and convert it into a real-valued matrix suitable for neural network processing according to the formula. These real-valued matrices are then fed into a trained neural network, SDNet, and the predicted channel information is obtained through forward propagation.  
However, with the increase in network depth in the OMP-SDNet, the problem of over-fitting or gradient disappearance may be encountered, resulting in a poor estimation effect. Therefore, in order to further improve the accuracy of channel estimation, we will propose a neural network architecture based on ResNet in the next section.
# A Review of the Use of Native and Engineered Probiotics for Colorectal Cancer Therapy
## 3 Genetically Modified-Bacteria for Colorectal Cancer (CRC) Treatment
### Engineered Bacteria Treat CRC via Therapeutic Protein Delivery
#### 3.1.3 Angiogenesis Regulation Proteins  
Tumor angiogenesis is an important feature in CRC development [73]. Based on targeting tumor blood vessels to treat CRC using engineered bacteria, both antiangiogenesis and vascular destruction are widely researched vessel-targeting therapies (Figure 4). For example, an early study engineered _L. lactis_ NZ9000 to express recombinant endostatin, a powerful inhibitor of endogenous angiogenesis. The administration of this engineered strain led to an increased mean survival time in a DMH-induced CRC rat model [74]. In addition, endostatin was also delivered by the attenuated _S. typhimurium_ mutant strain S636. When feeding constructed _S. typhimurium_ to CT26 colon carcinoma-bearing mice, the colonization of strains and the expression of endostatin were observed. These resulted in an increased apoptosis level and the suppression of tumor angiogenesis and ultimately caused the inhibition of tumor growth [75]. Another antiangiogenic protein, tumstatin, also a type of inhibitor of angiogenesis, is similar to endostatin. Both are from the noncollagenous domain fragments of collagen molecules [76]. [PERSON] et al. developed a Tumstatin delivery system using _Bifidobacterium longum_, which is nonpathogenic and anaerobic, as a vector. The pBADs promoter was employed to control the expression of Tumstatin on this vector. This Tumstatin delivery system significantly reduced the microvessel density of the tumor, induced the apoptosis of vascular endothelial cells, and inhibited tumor growth in CT26 tumor-bearing mice [77]. Recently, it was reported that bacteria that colonize tumors triggered local inflammation and induced tumor thrombosis [78; 79]. Based on this, [PERSON] et al. constructed an engineered strain therapeutic platform, AIB@ClyA, using _E. coli_ K-12 strains. After the engineered strains were administered to mice bearing CT26 tumors, they first accumulated and proliferated within the tumors; this led to intratumoral thrombosis and nutrient deprivation. Next, the ClyA protein expression caused membrane perforation and further exacerbated tumor thrombosis. Based on the above, the AIB@ClyA strategy resulted in a 79% tumor proliferation reduction and decreased tumor metastasis [61]. However, it did not seem to achieve the desired therapeutic effect via anti-angiogenesis and the destruction of tumor blood vessels due to the resistance mechanisms driving tumor regeneration [80]. An emerging concept is to promote the \"normalization\" of abnormal  
Figure 3: Engineered bacteria harboring myrosinase can convert dietary glucosinolates into anti-cancer molecule sulforaphene for CRC treatment.  
tumor vasculature, which more effectively delivers drugs and oxygen to cancer cells and thus improves the efficacy of radiotherapy and chemotherapy [80; 81]. Therefore, these studies illustrate the complexity and flexibility of tumor treatment based on targeting the vasculature.
## 3 Results
### Technical and Diagnostic Success Rates  
Technical and diagnostic success results are shown in Table 2. Diagnostic success results for \"easy\" and \"difficult\" lesion subgroups are shown in Tables 3 and 4. Technical success and diagnostic success were, respectively, achieved in 57 (95.0%) and 56 (93.3%) patients in the NAV-group and in 56 (93.3%) and 55 (91.6%) in the CT-group, with no significant difference between the two groups (\(p\) = 1.00 and \(p\) = 1.00, respectively). For \"easy\" and \"difficult\" lesions, the diagnostic success rates were higher in the NAV-group (100.0% and 85.2%, respectively) than in the CT-group (95.9% and 72.7%, respectively), with no significant difference (\(p\) = 0.513 and \(p\) = 0.390, respectively).  
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & **NAV Group** & **CT Group** & \(p\) \\ \hline No. of patients & 60 & 60 & \\ Sex ratio M/F & 28/32 & 33/27 & 0.465 \\ Mean age (range) (years) & 66 (58; 72) & 68 (60; 73) & 0.576 \\ BMI (range) (kg.m\({}^{-2}\)) & 26 (23; 28) & 24 (21; 29) & 0.187 \\ Position (P/SU/SI) & 25/33/2 & 33/26/1 & 0.187 \\ Operator & & & \\ Senior (\%) & 57 (95.0) & 54 (90.0) & 0.328 \\ Resident (\%) & 3 (5.0) & 6 (10.0) & \\ Lesion size (mm) & 20.0 [12.8; 37.0] & 29.5 [20.0; 49.5] & 0.007 \\ No. of lesions \(<\) 2 cm (\%) & 29 (48.3) & 14 (23.3) & 0.007 \\ Distance to the skin \(\pm\) SD (mm) & 70.2 \(\pm\) 22.1 & 62.2 \(\pm\) 16.8 & 0.028 \\ Distance to pleura (mm) & 18 [10.0; 33.3] & 21.5 [7.0; 28.0] & 0.340 \\ Localization (\%) & & & 0.754 \\ Right lower lobe & 12 (20.0) & 13 (21.7) & \\ Right upper lobe & 23 (38.3) & 19 (31.7) & \\ Middle lobe & 3 (5.0) & 4 (6.7) & \\ Left lower lobe & 10 (16.7) & 7 (11.7) & \\ Left upper lobe & 12 (20.0) & 17 (28.3) & \\ No. of easy lesions (\%) & 33 (55.0) & 49 (81.7) & \\ No. of difficult lesions (\%) & 27 (45.0) & 11 (18.3) & 0.002 \\ Trajectory angle 1 (\({}^{\circ}\)) & 15.5 [3.0; 31.5] & 6.0 [2.0; 13.0] & 0.008 \\ Trajectory angle 2 (\({}^{\circ}\)) & 10.0 [3.0; 16.3] & 1.0 [1.0; 5.0] & \(<\)0.0001 \\ \hline \hline \end{tabular}  
* No., number; M, male; F, female; BMI, body mass index; P, prone position; SU, supine position; SI, by the side position; mm, millimeters; %, percentage. Continuous and discrete variables are presented using median, first and third quartile (M [QJ; Q3]) unless otherwise specified. \(p<0.05\) was considered as significant.  
\end{table}
Table 1: Characteristics of the patients and the lesions.
# Cancer Treatment: An Overview of Pulsed Electric Field Utilization and Generation
## 5 Nano/Pico-Second Pulsed Electric Field Effect on Mammalian Cells  
Cancer cells do not respond to normal cell death signals; however, it has been proven that nanoscale pulses can stimulate cell apoptosis, thereby suppressing cancer development and growth [41]. This discovery demonstrated that nanosecond pulse technology can lead to an entirely physical apoptosis-based cancer therapy [42]. Nanosecond PEF (nsPEF) not only prevents tumour growth, it stimulates the immune system to fight cancers and enables a vaccine-like effect that protects against future cancer relapse/recurrence [43].  
Figure 4: Equivalent electrical model of cell [33; 39].  
Another application of nsPEF has arisen as a result of the finding that the release of calcium from membrane nanopores and intracellular stores leads to platelet aggregations in which rapid wound healing occurs [44]. Additionally, nsPEF can be used as a treatment for cardiac arrhythmia (abnormal heart rhythm); nsPEF is utilized in many ways for various treatments, among which several are listed below:  
* Electrochemotherapy [45].
* Electrically triggered intra-cellular calcium release [46; 47].
* Shrinkage and complete elimination of tumours [42].
* Activation of platelets for accelerated wound healing [48; 49].  
Electrodes of different shapes in direct contact with tissues are needed to deliver pulses for treatment, although utilizing ultrashort picosecond-scale pulses make it possible to use a wideband antenna for contactless pulse delivery [50].