esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Study on Mining Layout Pattern Based on Numerical Simulation
### Establishment of Numerical Model and Design of Simulation Scheme  
Based on the geological conditions and mining layout of the second and third panels of the mine, a numerical simulation computational model is established for the layout pattern of a small panel and a large coal pillar beneath the extra-thick water-bearing key strata. The size of the numerical simulation model is 4300 m \(\times\) 3300 m \(\times\) 1280 m, and the model is divided into 2,898,252 zones. The model employs the Mohr-Coulomb constitutive model, fixes the bottom boundary of the model, applies a displacement constraint to the surrounding boundaries, and has a free boundary at the top, with the top representing the ground surface. Combining with field measurement and the rock mechanics test, the rock's physical and mechanical parameters used in the model are listed in Table 1. The schematic diagram of the model is shown in Figure 8.  
The orthogonal experimental method is employed to investigate the influence of the width of the panel-isolated coal pillar and the mining scale of the small panel on the stability of the panel-isolated coal pillar. The width of the panel-isolated coal pillar is varied from 150 m to 300 m. When the width of the panel-isolated coal pillar is 200 m, the mining scale of the third panel is set between 400 m and 580 m. Similarly, when the width of the panel-isolated coal pillar is 250 m, the mining scale of the third panel ranges from 580 m to 760 m. The interval between values is set at 30 m.
## 1 Introduction
The results showed that the horizontal positioning errors were about 1.38-4.42 cm, and the vertical positioning errors were about \(-\)1.31-4.34 cm in the mid-latitude area after convergence. [PERSON] et al. [35] used BDS B1I, B3I, B1C, and B2a to evaluate the performance of the BeiDou PPP model of a single frequency, dual frequency, triple frequency, and quad frequency, with theoretical comparison of the models, positioning performances, precise time transfer, zenith tropospheric delay (ZTD), inter-frequency bias (IFB), and differential code bias (DCB), but the station was only analyzed on one day. Although the above-mentioned literature carried out some research into the PPP positioning performance of BDS-3, there are few comprehensive positioning performance evaluations of the B1c and B2a frequencies on a global scale. Evaluation of the new signals (B1C/B2a) can expand our understanding of the performance of BDS-3 (B1C/B2a) PPP in the global range, providing a basis for the subsequent combination of three-frequency or four-frequency positioning, thereby increasing the effect of global positioning. In this paper, the B1C and B2a dual-frequency signals of BDS-3 are used to analyze the global PPP performance of BDS. Twenty days of observation data from 17 stations distributed around the world are used to analyze the positioning accuracy and convergence performance of kinematic and static PPP. The PPP performances of GPS, BDS-2 + 3 (B1 IB3I), GPS + BDS-3 (B1 cB2a), and GPS+BDS-2 + 3 (B1 IB3I) are also compared.
## 6 Conclusions  
One of the main difficulties to compare and validate the performance of different UWSN proposals is the lack of a common standard to model the acoustic propagation in the underwater environment. In this paper we analyzed several underwater acoustic propagation models from a simple approach to more detailed and accurate models, in order to study whether differences between then may seriously impact in the performance evaluation of higher layer protocols. As a first conclusion we found that accurate and low-complexity propagation models are required for network simulation in order to obtain reliable results attained to the specific scenario and environmental parameters.  
Also we perform several simulation experiments to determine the sensibility of higher layer protocols (MAC and routing protocols) to propagation models and scenario environmental parameters. From the obtained results, we conclude that: (a) n-way handshake protocols, like CSMA/CA or DACAP suffer from high packet delays, but they show better behavior in terms of goodput and energy consumption; and (b) crosslayer approaches between routing and MAC layers are required to improve network performance, so it is highly recommended to allow routing protocols to get appropriate feedback from MAC layer about network and environmental conditions found at physical layer, since in UWSNs we showed the impact of physical layer modeling on network performance.  
The importance of not only choosing a realistic propagation model but also defining with precision the environment, starting with the geographic position and the parameters that we can obtain from it to the physical environment conditions like the season of the year or the ocean wave motion has been settled, so when designing network architectures for UWSNs, the role of physical layer should be seriously taken into account to be in a position to assert that simulation results will be close to the ones obtained in real network scenarios.
# In Silico Investigation of the RBC Velocity Fluctuations in Ex Vivo Capillaries
## 3 Validation
The computational domain consists of \(100\times 19\times 15.2\) um\({}^{3}\). A Zou-He condition is applied to the inlet and outlet, with the remaining boundary conditions set to periodic. The gap between the upper/lower walls and the slit walls is 0.2 um. The RBC is initialized 10 um away from the slit entrance (\(L_{2}\)), and the average inlet velocity is set to 50 um/s. For this case specifically, the lattice size is reduced to 0.1 um to accurately capture the flow within the slit. Consequently, the Lagrangian resolution (particle-to-particle distance) is matched to the lattice resolution, with \(\Delta s/\Delta x\approx 1.42\), and the material model parameters are adjusted to maintain the same mechanical behavior. Figure 4: **(left)** Shear profile used in the simulations. (**right**) Validation against the experimental result of the Yao [47]. Figure 3: **(left)** A single RBC stretched by applying a force of 173 pN. (**right**) Simulation result comparison with the [46] upper side shows axial diameter (AD) changes, while the lower side shows the transversal diameter (TD). Figure 5(right) shows the deformation of RBCs in three different initial orientations: a, b, and c. Although the resulting RBC shapes show minor differences from the reference studies, this is an expected outcome due to variations in computational methodologies. Even with the same methodology, the resulting RBC shapes can differ [48; 50; 51]. However, general behavior and transport times are not significantly affected by these small local shape differences; therefore, capturing the exact shape is unnecessary. It is evident that the current model can successfully calculate the RBC transit time in extremely confined geometries without any instability.
## 1 Introduction
In several experiments using a low-profile pallet robot, we compare the localization performance with T265 stereo odometry, GPO, and the Extended Kalman Filtering (EKF) of GPO and T265 [4,5]. By applying EKF with GPO and T265, we achieve a 0.058 m mean localization error in meters based on three indoor odometry experiments. The structure of this study is as follows. In Section 2, we briefly describe conventional studies related to this paper. In Section 3, we explain the details of each step of the proposed method. In Section 4, we show several experiments and evaluation results. Finally, in Section 5, we conclude this paper. Figure 1: A fisheye image from a low-profile robot. (**Left**): A fisheye camera is mounted at the front of a pallet robot. (**Right**): A sample image from the fisheye camera.
## 5 Discussion  
### Performance of LGViT for Different Visual Tasks  
For image classification, LGViT achieves a top-1 accuracy of 82.1% on Imagenet1K, which is the best in compared approaches. From Table 3, we can see vision transformers usually outperform CNNs. The typical Resnet-50 [3] only obtains 76.2% top-1 accuracy while most transformer-based models get an accuracy over 81.0%. This is mainly due to the superiority of vision transformers to learn long-range dependencies. CNN is good at extracting high-frequency information, so it works better locally. The transformer is good at extracting low-frequency information, thus working better globally. For these natural images in Imagenet, the scale is mostly limited to a single object and global features are more important. Therefore, transformers can achieve such a good performance than CNNs. Besides, when adopting a hierarchical design [7; 23; 68], the performance of vision transformers can be further improved compared with naive ViT [5]. The hierarchical design enables the model to learn multi-scale features as well as introduce locality to perform better. Similar experimental results can also be seen in object detection on COCO2017 and semantic segmentation on ADE20 kK. LGViT still outperforms other approaches.
## 3 Proposed Methodology
### Federated Classification Method with ResVGG-SwinNet
#### 3.7.3 Federated Learning Classification Output  
After federated learning, the ResVGG-SwinNet model classifies input data as regular traffic or DDoS attacks. The model returns a probability distribution with probabilities for each class depending on its relevance to the input data using the softmax function. No raw data are exchanged across clients. Thus, federated learning offers quick model training while protecting privacy. Model aggregation and updating enhance the global model as it learns from each client's data, improving DDoS attack detection.  
Federated learning and ResVGG-SwinNet provide a fast and scalable multi-label DDoS attack detection system. The model optimises deep-feature representations and learns long-range relationships utilising ResNet, VGGNet, and Swin-Transformer blocks. The federated-learning system trains the model across numerous clients while protecting data as shown in Algorithm 1.
## 2 System Design
### Multilateration Principle  
Multilateration is a positioning method used to determine the position of an object in a space by measuring the distance from three or more than three transmitters to a receiver as a terminal device. If three transmitters are used to determine the position of the receiver, then the system is known as a trilateration system. However, to increase the accuracy of the positioning system, the number of transmitters should be increased; additionally, the position should be stationary and known. The fundamental principle of the multilateration positioning system is to measure the distance between the receivers and simultaneously communicate with the transmitters to determine the position of the receiver. Figure 6 shows the system design for the basics of the multilateration principle, where \(T_{1}\), \(T_{2}\), \(T_{3}\), and \(T_{4}\) represent the transmitter LEDs, \(R\) represents the receiver, and \(L_{1}\), \(L_{2}\), \(L_{3}\), and \(L_{4}\) indicate the distance between transmitter and receiver. However, by utilizing this localization technique with VLC technology for large coverage areas in an indoor environment, an LED light can be used as a transmitter, and a smartphone camera image sensor can be used as a receiver device.
## 1 Introduction
In response to this phenomenon, researchers have proposed various simplification schemes, among which [35; 36] reduce the number of triplets required for fitting by quantifying perturbation parameters, while other studies [23; 37] convert the multiplication operation of signals into signals rotation, reducing the number of multiplication required in the algorithm. Recent studies have shown that the RP model can flexibly allocate the proportion of pre-equalization and post-equalization at the transmitter and the receiver [38] or be applied to super-channel systems [39]. Additionally, analyzing the capacity of wavelength division multiplexing (WDM) using the RP model is also an interesting topic [40]. This paper proposes a modified RP algorithm that provides higher accuracy, more accurate signal-to-noise ratio, and a larger launch power range without increasing the complexity of traditional RP models. The low-complexity MRP model proposed in this paper sets trainable parameters for the step size and nonlinear coefficients of each branch of the RP model. Waveform-wise data generated by standard SSFM is used as labels, and supervised learning is used to optimize each trainable parameter. The trained MRP model can achieve high-precision simulation of fiber dispersion and nonlinear interactions, reducing the fitting errors by more than 75% compared to the standard RP model after transmitting through a 120 km standard single-mode fiber. In addition, this paper analyzed the complexity of the MRP model and walked through different complexity, fiber length, and launch power conditions to verify the robustness of the model. The results show that the model has high accuracy and a wide range of applicability. In this paper, we only considered the scenario of the single-span fiber optic transmission, but we emphasize that the basic structure of this model will not change under multi-span systems. We will discuss and demonstrate the detail of the performance of this model under multi-span systems in our future research.
# A Review of Properties of Nanocellulose, Its Synthesis, and Potential in Biomedical Applications
## 4 Nanocellulose-Based Composites
### Chitosan/Nanocellulose  
Bacterial cellulose (BC) is a versatile material that holds promise for use in various biomedical and cosmetic applications because of its mechanical strength, shape, non-toxicity, biocompatibility, and chemical controllability. The BNC-based composites with other constituents such as synthetic and natural polymers allow the production of several biomedical goods [89]. In situ and ex situ approaches are widely employed for BNC composite synthesis [90]. The in situ method incorporates reinforcing materials into the culture media to aid BC synthesis; these materials eventually become a part of the generated hydrogel. For the ex vivo approach, composites are formed by impregnating or incorporating reinforcing components into synthetic polymer [91]. Both in situ and ex situ techniques have been used to prepare a composite of chitosan (Ch) and BC; the presence of O-H and N-H groups and structural similarities induce strong bonding between Ch and BC, and the composite subsequently exhibits notable enhancement in biological and physicochemical properties [92; 93; 94]. The remarkable biological qualities of gelatin have been studied for its use with scaffold material such as BC. BC-gelatin composites are produced via in situ and ex situ approaches. The composites showed improved cell proliferation and adhesion properties and have been employed for biomedical applications. Several polymers, including collagen, alginate, and Novo aloe vera, can be used with BC to broaden its therapeutic potential [95; 96; 91]. These composites with polymeric materials are widely used to confer antifungal, antimicrobial, and tissue regeneration properties. By impregnating BC sheets into an AgNO\({}_{3}\) solution, [PERSON] et al. developed a BC-Ag composite. Nanoparticles adhered to the BC surface were examined with XRD spectral peaks and UV absorption. The BC-Ag composite exhibited extremely potent antibacterial activities against Gram-positive and Gram-negative bacteria [97]. Hence, the study indicated that incorporating metals and metal oxides into the BC composites imparts electrical conductivity and antimicrobial properties [97; 98; 99; 100].
# Applications of Multi-Agent Deep Reinforcement Learning: Models and Algorithms
## 6 Application of Multi-Agent Deep Reinforcement Learning: State of the Art
### SADRL Applied to Distributed Agents in a Multi-Agent Environment  
The traditional SADRL approach (see Section 3.1) has been applied in distributed agents to handle large state and action spaces. For instance, the resource allocation scheme (A.1) in [51; 68; 69; 70] address the challenge of high dynamicity (C.2) and enhance the throughput performance (P.3) of distributed agents in 4G networks. Using the SADRL approach, distributed agents: (a) do not exchange local information among themselves, and so the signaling overhead is reduced (O.4); and (b) use a lesser amount of data, including states and actions, for learning, and so it increases scalability (O.5) with a lower computational complexity. Nevertheless, applying SADRL in distributed agents has two main shortcomings, whereby distributed agents: (a) are unstable and unable to converge to the optimal joint action; and (b) are unable to solve complex tasks due to limited information. Hence, various approaches have been proposed. For instance, [PERSON] et al. enable distributed SADRL agents to use historical knowledge to ensure stability (O.1) in [69], and [PERSON] et al. detects missing data for improved reliability of medical image analysis in [71]. The rest of this section presents the SADRL approaches applied to multi-agent environments.
## 4 Conclusions  
For Sr\({}_{2-x}\)Eu\({}_{x}\)ZnMoO\({}_{6}\) powders, the 20 value of the (220) diffraction peak shifted to a higher value and the FWHM value for the (220) diffraction peak decreased as the synthesizing temperature increased. When the \(x\) value (the concentration of Eu\({}^{3+}\) ions) increased from 0 to 0.12 and the synthesizing temperatures rose from 900 \({}^{\circ}\)C to 1200 \({}^{\circ}\)C, the cell parameters of the Sr\({}_{2-x}\)Eu\({}_{x}\)ZnMoO\({}_{6}\) powders were changed from \(a=b=c/\sqrt{2}=0.3968\) nm to \(a=b=c/\sqrt{2}=0.3971\) nm and from \(a=b=c/\sqrt{2}=0.3971\) nm to \(a=b=c/\sqrt{2}=0.3974\) nm (cubic crystal structure). When the synthesizing temperature was 900-1100 \({}^{\circ}\)C, the emission intensities of the Sr\({}_{2-x}\)Eu\({}_{x}\)ZnMoO\({}_{6}\) phosphors peaked at \(x=0.08\) and decreased as the concentration of Eu\({}^{43}\) ions increased. There was an observable concentration-quenching effect of Eu\({}^{3+}\) ions in the Sr\({}_{2-x}\)Eu\({}_{x}\)ZnMoO\({}_{6}\) phosphors. The emission spectrum of Sr\({}_{2}\)ZnMoO\({}_{6}\) powder consisted of one broad band in the 400-575 nm region, and the emission spectra of the Sr\({}_{2-x}\)Eu\({}_{x}\)ZnMoO\({}_{6}\) phosphors (except for the Sr\({}_{2}\)ZnMoO\({}_{6}\) powder) consisted of two parts: one broad band in the 400-575 nm region and two sharp peaks located at 597 nm and 616 nm. The lifetimes of the Sr\({}_{2-x}\)Eu\({}_{x}\)ZnMoO\({}_{6}\) phosphors, which depended on synthesizing temperature and were independent of the concentration of Eu\({}^{3+}\) ions, were 2.04-2.10 ms, 1.93-2.03 ms, 1.78-1.82 ms, and 1.65-1.67 ms when the synthesizing temperature was 900 \({}^{\circ}\)C, 1000 \({}^{\circ}\)C, 1100 \({}^{\circ}\)C, and 1200 \({}^{\circ}\)C, respectively. We found that when the synthesizing temperature was in the range of 900-1200 \({}^{\circ}\)C, the relationship between the lifetime and the synthesizing temperature could be determined by the following equation: \(t=-0.0016\times T+3.543\), where \(t\) and \(T\) represent the emitting lifetime of the luminescent material and the synthesizing temperature (\({}^{\circ}\)C).  
The authors would like to acknowledge the financial supports of MOST 104-2221-E-390-013-MY2, MOST 105-2622-E-390-003-CC3, and MOST 105-2221-E-344-002.  
[PERSON] and [PERSON] helped proceeding the experimental processes, measurements, and data analysis; [PERSON] and [PERSON] organized the paper and encouraged in paper writing; Also, [PERSON] and [PERSON] helped proceeding the experimental processes and measurements.  
The authors declare no conflict of interest.
# 6G Use Cases and Scenarios: A Comparison Analysis Between ITU and Other Initiatives
## 13 Results and Discussion
### Analysis 3: Comparison Among All Proposed 6G Use Cases
This distance reaches a value of 0.08 in the following comparisons: (i) integrated sensing and communication (ITU) and distributed sensing and communications (NGA), (ii) ubiquitous connectivity (ITU) and living and working everywhere (6G IA), (iii) ubiquitous connectivity (ITU) and network evolution (NGMN). The rest of the very good matches (with Hamming distance equal to 0.12) are obtained when the AI and communication ITU 6G usage scenario is compared with ubiquitous connectivity (ITU) or fully connected world (HEXA) use cases. In addition, the same situation in terms of the Hamming distance value happens when the integrated sensing and communication ITU 6G usage scenario is compared with massive communication (ITU) or trusted environments (HEXA). Finally, the comparison within the ITU 6G usage scenarios gives the same value of Hamming distance (0.12), as in the case of (i) massive communication with integrated sensing and communication, and (ii) ubiquitous connectivity with AI and communication. The Hyper-Reliable and Low-Latency Communication 6G usage scenario proposed by ITU does not provide a very good match with the other 6G use cases. From the results summarized in Table 13, some ITU 6G usage scenarios are very similar in terms of the required technologies.
# Bacteria-Mediated Modulatory Strategies for Colorectal Cancer Treatment
## 2 Bacterotherapy in CRC Treatment
### Mechanisms Used in Bacterotherapy in CRC
#### 2.1.3 Bacteria as Carriers for Therapeutic Agents  
Besides using bacteria and their metabolites as directly targeting cytotoxic anti-cancer agents, they have also been demonstrated to be used as therapeutic carriers in the treatment of CRC. Several studies have shown that bacterial carriers are not only able to selectively target cancer cells but also metastases [31; 107]. Using imaging techniques such as bioluminescence has been exhibited as a non-invasive method making it possible to detect and monitor tumors, including CRC, and even metastases by generating bioluminescent cancer-colonizing bacteria offering novel opportunities in cancer diagnosis and treatment [29; 31]. Moreover, using _Lysteria monocytogenes_ as a vector for an anti-cancer vaccine has been shown to promote a remarkable amplification of its anti-cancer effects, whereby the intracellular microorganism is able to pass intestinal membranes to then trigger immune responses by activating CD8\({}^{+}\) and CD4\({}^{+}\) T-cells. In addition, the use of bacterial vectors can be considered as a safe treatment method due to clinical trials [27; 28]. Another bacterial microorganism used as a carrier in the treatment of CRC is represented by the species of _Clostridium novyi_-NT, a non-toxic variant of the superior cancer-colonizing strain _Clostridium novyi_. The application of _C. novyi_-NT spores to tumor mouse models has even been shown to sprout within avascular regions and thus eradicate CRC cells. In combination with conventional chemotherapy, _C. novyi_-NT administration even exhibited hemorrhagic necrosis within 24 h after application, demonstrating a synergistic interaction against CRC cells and revealing _C. novyi_-NT as a promising bacterial carrier [30; 108]. Therefore, using bacteria as therapeutic carriers in order to detect, target and fight viable cancer cells and metastases represents a powerful tool in the treatment of CRC.