esa-sceva/satcom-chunk-collection huggingface dataset:
# 2D Semantic Segmentation: Recent Developments and Future Directions
## 3 Classical Networks Based on Deep Learning
### SegNet  
SegNet [44] adopts an encoder-decoder structure to combine shallow and deep information to optimize segmentation results, as shown in Figure 4. Skip connections are used to directly connect the feature maps of the encoder network with those of the corresponding decoder network, thus improving the memory utilization and computational efficiency of SegNet. The innovation of SegNet is that it records the position of max pooling during each downsampling because max pooling and downsampling operations reduce the spatial resolution of feature maps. However, recording the position of max pooling increases memory consumption. Therefore, only the index of max pooling is recorded. In addition to effectively combining transpose convolution and non-cooling, SegNet adopts batch normalization [45] to solve the problem of vanishing gradients.  
However, SegNet also has some limitations. First, SegNet employs an encoder-decoder structure to combine shallow and deep information for optimizing segmentation results. However, segmentation accuracy may decrease due to the lack of multiscale information guidance. Second, although SegNet records the maximum pool position for each downsampling operation to preserve spatial resolution, it increases memory consumption. Therefore, SegNet may be unsuitable for use in computationally and memory-constrained scenarios. Lastly, SegNet employs batch normalization to address vanishing gradients, but in some cases, batch normalization may lead to overfitting. The following directions can be considered to solve these problems:  
1. Introducing multiscale information such as pyramid pooling and multiscale fusion can improve segmentation accuracy. SegNet's model structure can be simplified using a lightweight network structure to reduce memory and computational resource consumption.
2. Other methods such as residual connections and attention mechanisms can be explored to address the problem of vanishing gradients. Although the SegNet algorithm has certain limitations, it is still a classic semantic segmentation algorithm that can perform well in specific scenarios.
## 7 Conclusions  
This paper investigates the motion control problem of Maritime Autonomous Surface Ships (MASS) for not only collision avoidance, but also for speed optimization and sailing smoothness. By utilizing the rich information of the locations and velocities of surrounding ships and remote ships, the VO model is exploited for collision avoidance. A multiple objective optimization problem model is set up, and three algorithms are proposed to address the motion planning optimization problem: (1) a greedy motion-planning algorithm, (2) a greedy algorithm with consideration of future collision risk, and (3) a dynamic programing-based multiple interval motion-optimization algorithm. The dynamic programming method utilizes the remote information provided by AIS, which was shown to provide better sailing safety and efficiency than the two greedy algorithms. However, the DP algorithm needs accurate motion information of surrounding ships. If there are vessels whose motions are not captured by AIS, the MASS still needs the interval-based greedy method to avoid local collisions. We will study the joint work of DP and the locally-greedy algorithm in future work.  
Data, modelling and algorithm, X.G.; writing and simulation, Y.W.; project leader, P.W.; resources, B.Z.  
This work was supported in part by the National Natural Science Foundation of China Grant Nos. 11671400, 61672524, The Fundamental Research Funds for the Central University, the Research Funds of Renmin University of China, 2015030273, the National Key Technology Support Program, 2014 BAK12B06, and the National Key Technology Support Program, 2015 BAG20B02.  
Our deepest gratitude goes to the anonymous reviewers and guest editor for their careful work and thoughtful suggestions that have helped improve this paper substantially.  
The authors declare no conflict of interest.
## 3 Results and Discussion
### Optimization of UAE of the Antioxidant Bioactive Compounds
\begin{table}
\begin{tabular}{l c c c c c c c c c c c c c c c c c c c c} \hline \hline  & \multicolumn{4}{c}{**RP**} & \multicolumn{4}{c}{**WP**} & \multicolumn{4}{c}{**WP**} \\ \cline{2-13}  & \multicolumn{4}{c}{**TPC**} & \multicolumn{4}{c}{**FRAP**} & \multicolumn{4}{c}{**TPC**} & \multicolumn{4}{c}{**FRAP**} \\ \hline  & **Degrees of** & **Sum** & **Mean** & **F-Ratio** & **Degrees of** & **Sum** & **Mean** & **Mean** & **Degrees of** & **Sum** & **Mean** & **F-Ratio** & **Degrees of** & **Sum** & **Mean** & **F-Ratio** \\  & **Freedom** & **Squares** & **Square** & **F-Ratio** & **Degrees of** & **Square** & **Mean** & **F-Ratio** & **Degrees of** & **Mean** & **F-Ratio** & **Degrees of** & **Sum** & **Mean** & **F-Ratio** \\ \hline Lack of fit & 15 & 908.701 & 60.5801 & 2.84 \({}^{*}\) & 15 & 292.04 & 194.736 & 1.96 \({}^{*}\) & 15 & 207.78 & 13.852 & 0.68 \({}^{*}\) & 15 & 1834.02 & 122.268 & 1.11 \({}^{*}\) \\ Pure error & 4 & 85.2637 & 21.359 & & 4 & 397.862 & 99.4605 & & 4 & 81.6453 & 20.411 & 4 & 441.37 & 110.342 & \\ Total (empty) & 2 & 37.436 & & 29 & 14.2793 & & 29 & 1973.638 & & & & & 29 & 1357.23 & \\ R\({}^{*}\) & 0.73 & & & 0.77 & & & 0.84 & & & & & & 0.84 & \\ Ad-R\({}^{2}\) & 0.59 & & & & 0.65 & & & 0.75 & & & & & & 0.75 & \\ \hline \multicolumn{13}{c}{\({}^{*}p\)\(>\) 0.05} \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Analysis of variance for the response surface quadratic models of TPC and FRAP. The analysis of variance showed that the extraction time did not significantly influence (\(p>0.05\)) the TPC or FRAP. However, the ratio-time interaction had a significant effect (\(p<0.05\)) on both variables for the RP and on FRAP only for the WP. The TPC and FRAP improved when the extraction time and solvent ratio were increased [60].
## 2 Tissue-Engineered Scaffolds with GBM and Neural Tissues
### Hydrogels
A study depicted that the introduction of positive surface charges (OPF and OPF-MTAC hydrogels) to conductive carbon components (GO and carbon nanotube, CNT) can remarkably stimulate nerve cell responses [72]. Using anti-inflammatory drug is an alternative approach to enable nerve regeneration that can be combined with loading GBMs. A hydrogel was engineered using GO sheets with four-armed polyethylene glycol and functionalized with diacrein as an M2 drug (4 arm-PEG-diacrein or PD). The designed hydrogel was injectable and self-recovery due  
Figure 6: (**A**) Mechanism of the engineered system of GO-based gene delivery that induces differentiation of recruited BMSCs for cutaneous nerve regeneration. Reused with permission from [69]. (**B**) Immunofluorescence images indicate the structure of the injured spinal cords and the distribution of three important marker proteins: glial fibrillary acidic protein (GFAP), microtubule-associated protein 2 (MAP-2), and neuron-specific class III \(\beta\)-tubulin (TUJ-1). Scale bar: 500 \(\upmu\)m. Reused with permission from [70]. to the strong physical interactions between GO and diacerein. The range of conductivity of the PD/GO hydrogel was consistent with suitable conductivity for NTE materials [78; 79]. It has been reported that a suitable range of electric conductivities is 1-10 S m\({}^{-1}\), which results in neuron growth, longer neurite length, faster neurite growth rate, and better axon remyelination [78; 79]. Further, PD/GO hydrogel provided an anti-inflammatory microenvironment; synapses appeared around the cells. Therefore, this hydrogel can promote neuronal network formation at the cellular level and inhibit subsequent hyperactivation of astrocytes caused by reactive oxygen species (ROS). In addition, PD/GO hydrogels remarkably reduced the lesion area and the site of inflammation compared to the others (Figure 6B) [70]. Other approaches similar to hydrogel, such as aerogel and foam, are also considered common methods in fabricating high porous materials for biomedical applications. For instance, a G foam/hydrogel scaffold has been utilized for peripheral nerve regeneration. The in vitro results indicated that ADSCs can regulate Nrf/HO-1, NF-kB, and PI3K/AKT/mTOR signaling pathways, showing multiple functions in reducing oxidative stress and inflammation and regulating cell metabolism, growth, survival, proliferation, angiogenesis, differentiation of Schwann cell, and myelin formation. Furthermore, the in vivo results demonstrated ADSCs-loaded composite scaffold significantly promoted nerve recovery and inhibited the atrophy of targeted muscles [80]. Likewise, some recent cases with GBMs and these techniques (aerogel and foam) for NTE have been listed in Table 1, although they are limited at present when compared with other techniques.
# An Observation Scheduling System for Radio Telescope Array
## 4 Main Function Testing
### uv Coverage Test and Analysis
The resulting \(uv\) coverage ratios for the six datasets are 0.3%, 0.5%, 0.8%, 1.0%, 1.3%, and 1.5%, respectively. These findings suggest that as the observation time increases, both the \(uv\) coverage area and the coverage ratio also increase. Figure 11 displays the \(uv\) coverage maps for these six datasets, showing that the density of the \(uv\) coverage increases as the observation duration increases. This is consistent with their \(uv\) coverage ratios. Figure 10: Upgraded telescope array layout configuration. To determine the telescope array layout that offers the best \(uv\) coverage, we also tested circular and Y-shaped configurations. Figure 12 illustrates the layout configuration of the circular array. The \(uv\) coverage maps corresponding to observation durations of 1, 2, 4, 8, 12, and 24 h are presented in Figure 13. The coverage ratios for these durations are calculated as 0.5%, 1.0%, 1.9%, 3.9%, 5.8%, and 6.5%, respectively. Figure 14 shows the layout configuration of the Y-shaped array. The \(uv\) coverage maps for the Y-shaped array, for observation durations of 1, 2, 4, 8, 12, and 24 h, are presented in Figure 15. The corresponding coverage ratios are 0.2%, 0.4%, 0.6%, 1.0%, 1.6%, and 1.7%, respectively. The integration time for each observation duration of these two arrays was set at 5 min. Figure 11: \(uv\) coverage maps of the upgraded array for observation durations of 1, 2, 4, 8, 12, and 24 h.  
Figure 12: Circular array configuration. Finally, a comparison of the coverage ratios for the three telescope array configurations is depicted in Figure 16. The analysis reveals that the circular array exhibits the greatest variation and the highest peak in coverage ratio compared to the other configurations, making it the optimal layout for this station in terms of coverage. The coverage ratios for both the upgraded and Y-shaped configurations are nearly identical across the six observation durations. The Y-shaped layout, a common configuration in radio astronomy such as the NRAO Very Large Array [27], is noted for its widespread use. Given the primary scientific objective of the radio telescope array under construction--to detect transient sources like fast radio bursts (FRBs)--the observation duration at any single position is significantly less than one hour, typically on the order of minutes. Under these circumstances, the coverage rates of the three layout configurations are essentially equivalent based on the current computational results. Therefore, after a comprehensive evaluation, we have decided to adopt the upgraded layout configuration. Figure 14: Y-shaped array configuration. Figure 9:0 \(uv\) coverage maps of the circular array for observation durations of 1, 2, 4, 8, 12, and 24 h.
# Synthesis of Hydrogel-Based Microgels and Nanogels Toward Therapeutic and Biomedical Applications
## 4 Paradigm Shift: Bulk Hydrogels to Hydrogel Micro/Nanoparticles
### Designing Stimuli-Responsive Properties
#### 4.1.1 pH Sensitivity  
The basis of the pH-sensitive behavior of hydrogels is the ionizable functional groups present in their molecular structure, where the dissociation or protonation of these chemical moieties modulates the swelling behavior, mechanical strength, and permeability of a hydrogel. Anionic hydrogels contain acidic functionalities such as a carboxyl group, which could deprotonate at higher pH levels [76]. Deprotonation of an acidic group renders its surface potential negative, increasing electrostatic repulsion and swelling. This behavior is suitable for the controlled drug release in basic environments such as the intestines, where the pH value begins at 6 and reaches approximately 7.4. PAA hydrogels are widely adapted in the DDS specialized in oral administration, since the micro/nanogels could encapsulate drug molecules at their interior to physically separate them from the surrounding environment [53; 150; 193]. This allows us to avoid undesirable interactions between normal cells and the drugs in the acidic gastric environment and to release them in the basic intestinal tract.  
Cationic hydrogels contain basic functionalities, like amine groups of chitosan, and these groups can protonate in acidic conditions, at below their dissociation constant (pKa), inducing extensive swelling of the gels [68; 194]. This behavior is advantageous in tumor-targeted therapy, since the tumor microenvironment exhibits a slightly acidic pH ranging from 5.6 to 6.8 due to the high level of glycolysis and hypoxia [13; 110; 195].
# Intelligent Transaction Scheduling to Enhance Concurrency in High-Contention Workloads
## 4 Design of DCoS
### Conflict-Free Partitioning Phase  
Given a transaction batch \(\mathcal{B}\), DCoS applies a partitioning function \(\Phi\) to minimize concurrency control to divide it into:  
* \(p\) conflict-free clusters \(\{\mathcal{Q}_{1},\mathcal{Q}_{2},\ldots,\mathcal{Q}_{p}\}\);
* A residual set \(\mathcal{T}\), where \(|\mathcal{T}|\leq\alpha|\mathcal{B}|\), and \(\alpha\in[0,1]\) serves as the residual threshold parameter.  
The transaction-partitioning problem is generally NP-hard, and extensive research has been conducted in this domain [3; 15; 24]. We adopt the dynamic partitioning algorithm following [15], and DCoS is also compatible with other partitioning functions.  
DCoS follows a proactive framework that leverages the knowledge of the complete database scheme and the complete set of stored procedures in OLTP applications. DCoS analyzes the contention among transactions based on their read-write sets by creating the data access graph from the read-write set of transactions. Specifically, the partitioning phase consists of three key processes:  
Figure 1: DCoS workflow in transaction processing for OLTP system.
# Quantum Eigenstates of Curved and Varying Cross-Sectional Waveguides
###### Abstract  
A simple one-dimensional differential equation in the centerline coordinate of an arbitrarily curved quantum waveguide with a varying cross section is derived using a combination of differential geometry and perturbation theory. The model can tackle curved quantum waveguides with a cross-sectional shape and dimensions that vary along the axis. The present analysis generalizes previous models that are restricted to either straight waveguides with a varying cross-section or curved waveguides, where the shape and dimensions of the cross section are fixed. We carry out full 2D wave simulations on a number of complex waveguide geometries and demonstrate excellent agreement with the eigenstates and energies obtained using our present 1D model. It is shown that the computational benefit in using the present 1D model to calculate both 2D and 3D wave solutions is significant and allows for the fast optimization of complex quantum waveguide design. The derived 1D model renders direct access as to how quantum waveguide eigenstates depend on varying cross-sectional dimensions, the waveguide curvature, and rotation of the cross-sectional frame. In particular, a gauge transformation reveals that the individual effects of curvature, thickness variation, and frame rotation correspond to separate terms in a geometric potential only. Generalization of the present formalism to electromagnetics and acoustics, accounting appropriately for the relevant boundary conditions, is anticipated.  
Keywords:quantum eigenstates; varying cross section; effective analytical and numerical methods +
Footnote †: journal: Applied
## 2 Materials and Methods  
### Materials  
Leca particles (Leca(r) S) used in the experiments were kindly provided by Leca Portugal S.A (Avelar, Portugal). Leca(r) S is a commercial product of spherical particles (1 to 5 mm in diameter) of non-combustible expanded clay, obtained by processing natural clay and is normally used in concrete, prefabrication, and mortar in buildings, roads, and civil engineering works. The density is about 430 kg/m\({}^{3}\), compressive strength \(>\) 1.8 N/mm\({}^{2}\), chloride concentration \(<\) 0.1 wt%, sulphate \(<\) 0.4 wt% and sulphur \(<\) 0.2 wt%. Leca(r) S is composed of a mixture of oxides of silicon, aluminum, iron, and other minor elements, formed during the firing of natural clay.  
The synthetic effluent with a concentration of 1 mg/L of SMX (98%, Sigma-Aldrich, St. Louis, MO, USA) was prepared in ultrapure water for further use in the photocatalytic oxidation experiments.  
The Aeroxide P25 (70% anatase and 30% rutile), ethanol (99%), nitric acid, and hydrochloric acid were acquired from Sigma-Aldrich. Ethanol and nitric acid were used in the dispersion process of TiO\({}_{2}\) nanoparticles before impregnation.
# Enhanced Radiation Therapy of Gold Nanoparticles in Liver Cancer
## 3 Results and Discussion
### Enhanced Radiotherapy  
A clonogenic cell survival assay was used to determine the radio-sensitization effect between the two nanoparticles in H22 and HepG2 cells, and the results are shown in Figure 8a,b, respectively. After treated with or without PEG-coated SNPs for 24 h, both cell lines were radiated under 0, 1, 2, and 4 Gy by \({}^{137}\)Cs. Under 1 Gy of the radiation, the survival fraction of control group, the 14.4 nm group, and the 30.5 nm group was 95.00%, 49.46% and 76.61% in H22 cells respectively; while in HepG2 cells was 90%, 49.92% and 50.25% respectively. When exposed to 2 Gy, the survival fraction of control group, 14.4 nm group, and 30.5 nm group were 47.98%, 31.42% and 33.58% in H22 cells respectively; and 56.96%, 28.04% and 33.75% in HepG2 cells respectively. In previous work, the sensitizer enhancement ratios were 1.16-1.66, which depended on the particles size, cellar line, surface coating and radiation energy (Table 1). In our work, sensitizer enhancement ratios were about 1.2-1.3 according to previous calculation methods [18]. These data illustrated that no matter whether they were radiated alone or radiated and treated with nanoparticles, the cell colony formation rates were low, indicating that the nanoparticles and radiation can inhibit tumor cell proliferation.  
Figure 8 showed how PEG-coated SNPs affected cell survival fraction under different radiation doses. Enhanced effect of nanoparticles modified with PEG-SH was observed on inhibition of the cell viability by radiation. Under identical concentration of PEG-coated SNPs, cells showed decreased survival percentages when radiation doses increased.  
Figure 8: Cloning formations in H22 (**a**) and HepG2 cells (**b**) after treated with 0.05 mM 14.4 or 30.5 nm PEG-coated SNPs.  
Figure 7: Concentration dependent toxicity in vitro H22 (**a**) and HepG2 cells (**b**) treated with 14.4 or 30.5 nm PEG-coated SNPs after 24 h.
## 3 Experimental Apparatus and Approach  
The original design of the FAOT with a throttling plate is here described as the LFT design and the present focused case with the absence of a throttling plate is described as the ZFT design. An LFT tool with a 120 mm diameter was manufactured, and subsequently, a ZFT could be modified from the LFT. As displayed in Figure 3, in order to experimentally evaluate the working performance of an FAOT, three pressure transducers (Sensata Technologies, Inc., Attleboro, MA, USA) with the same specifications were used to sense the pressure fluctuation at three different positions of the oscillation tool, i.e., (i) the inlet of the fluidic oscillator; (ii) one of the side passages; and (iii) the front chamber of the cylinder. Besides, a displacement transducer (Sensata Technologies, Inc., Attleboro, MA, USA) was mounted on the sleeve to measure the amplitude of axial oscillation. All of the experimental tests were carried out on level ground and the drilling mud in the experiments was the conventional drilling fluid successfully used in directional well drilling. The tested FAOT was driven by a high pressure truck-mounted pump (Yantai Jereh Oilfield Services Group Co., Ltd., Yantai, China), which supplied it with drilling mud. Various quantities (volume flow rate, \(Q_{V}\)) of drilling fluid were supplied to the fluidic oscillator, to drive the oscillation tool to work. As depicted in Figure 3, both the pressure and displacement at the measuring positions of the oscillation tool were acquired and recorded by a data acquisition system. The statistic of the measured pressure and displacement spectrum was 0.5%, at a 95% confidence level. In the end, the received data were analyzed and displayed by a computer.  
\begin{table}
\begin{tabular}{c c c c} \hline
**Specification** & **Number of Cells** & **Mean Pressure Drop (MPa)** & **Oscillation Frequency (Hz)** \\ \hline Coarse grid & 50,000 & 2.21 & 7.64 \\ Medium grid & 80,000 & 2.13 & 7.52 \\ Fine grid & 120,000 & 2.10 & 7.47 \\ \%Difference a & - & 5.24 & 2.28 \\ \hline \end{tabular}  
* The percentage difference between the coarse and fine grids.  
\end{table}
Table 1: The details of the grid independence analysis of a fluidic axial oscillation tool.  
Figure 3: Schematic of the experimental system.  
In order to study the performance of the fluidic axial oscillation tool with the absence of a throttling plate and try to figure out the differences between the ZFT and LFT designs, a comparison analysis in terms of the pressure drop, oscillation amplitude, and pressure fluctuations in the measured positions between the two designs was performed by the experimental system. In addition, the oscillation frequency and the dependence between the supplied volume flow rate and the oscillation frequency are also some of our main concerns.
## 3 Calibration of ATMD with Viscous Damping-Stiffness Control Force
### Active Control Force  
The active control force to be applied by the active actuator of the ATMD is assumed to be calculated using the relative displacement \(x_{d}\) and velocity \(\dot{x}_{d}\) signals. In practice, the relative displacement can be directly measured using a single displacement sensor. The relative velocity can be then obtained from the measured relative displacement signal.  
The active control force is thus expressed as:  
\[f_{a}=c_{a}\dot{x}_{d}+k_{a}x_{d}, \tag{12}\]  
where the viscous damping coefficient \(c_{a}\) and the positive or negative stiffness \(k_{a}\) represent the feedback gains. These gains require calibration to satisfy a specific control objective.  
Figure 1: Primary structure with mass dampers under consideration: (**a**) Optimal ATMD with a viscous damping–stiffness force; (**b**) Sub-optimal STMD with a clipped viscous–stiffness control force; (**c**) optimized STMD with an adjusted clipped viscous–stiffness control force to compensate, as much as possible, for clipping.