esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Methodology
### Emergency Observation Mission Scheduling Model
#### 2.3.2 Optimization Objective Function of Satellite Scheduling  
The satellite mission scheduling is in reality a multi-objective optimization problem with multiple constraints. During emergency response, it not only requires that the completion rate of key emergency missions is high and the mission revenue is large, but also needs to ensure a high scheduling efficiency for each mission to optimally use satellite resources. Based on these consideration, we use a linear weighted sum method to build optimization objective function for solving this model:  
1. Sub-objective function 1: to maximize the sum of priority levels of the missions: \[\begin{array}{c}Maximize\quad f_{1}=\sum_{j=1}^{n}\sum_{i=1}^{m}\sum_{k=1}^{ k_{ij}}x_{ijk}p_{i}\end{array}\] (12) where \(X=\left\{x_{ijk}\right\}_{m\times n\times k_{ij}}\) is the decision matrix of mission scheduling, \(x_{ijk}=1\) represents the \(k\)-th observation opportunity of mission \(t_{i}\) assigned to satellite \(s_{j}\); otherwise, \(x_{ijk}=0\).
2. Sub-objective function 2: to maximize the total mission revenues: \[\begin{array}{c}Maximize\quad f_{2}=\sum_{j=1}^{n}\sum_{i=1}^{m}\sum_{k=1}^ {k_{ij}}x_{ijk}w(t_{i})\end{array}\] (13)
3. Sub-objective function 3: to minimize the waiting time for missions that require urgent execution: \[\begin{array}{c}Minimize\quad f_{3}=\sum_{j=1}^{n}\sum_{i=1}^{m}\sum_{k=1}^ {k_{ij}}\left(bst_{i}-tsb_{i}\right)/(tse_{i}-tsb_{i})\cdot urgent(t_{i})\cdot x _{ijk}\end{array}\] (14)  
Based on each term of the objective functions, the global optimization objective function is obtained by the linear weighted sum method:  
\[\begin{array}{c}Maximize\quad f=\alpha\cdot f_{1}+\beta\cdot f_{2}+\gamma \cdot 1/f_{3}\end{array} \tag{15}\]  
where \(\alpha\), \(\beta\) and \(\gamma\) are the weighting factors, and the sum of these factors is 1. The value of the weighting factor determines the importance of each term in the objective function. Our study takes the mission priority as the key factor in the emergency response. Thus, we set \(\alpha=0.6\), \(\beta=0.2\) and \(\gamma=0.2\).
###### Abstract  
Stripe rust (_Puccinia vitiformis_ f. sp. _tritici_ (_Pst_)) is one of the most devastating fungal diseases of durum wheat (_Triticum turgiatum_ L. var. _durum_ Desf.). Races of _Pst_ with new virulence combinations are emerging more regularly on wheat-growing continents, which challenges wheat breeding for resistance. This study aimed to identify and characterize resistance to _Pst_ races based on a genome-wide association study. GWAS is an approach to analyze the associations between a genome-wide set of single-nucleotide polymorphisms (SNPs) and target phenotypic traits. A total of 139 durum wheat accessions from Iran were evaluated at the seedling stage against isolates _Pst_-37 and _Pst_-40 of _Pst_ and then genotyped using a 15K SNP chip. In total, 230 significant associations were identified across 14 chromosomes, of which 30 were associated with resistance to both isolates. Furthermore, 17 durum wheat landraces showed an immune response against both _Pst_ isolates. The SNP markers and resistant accessions identified in this study may be useful in programs breeding durum wheat for stripe rust resistance.  
durum wheat; stripe rust; _Pst_-37 and _Pst_-40 isolates; GWAS; SNP markers
# Generative Adversarial Networks in Histological Image Segmentation: A Systematic Literature Review
## 3 Fundamentals and Basic Definitions
### Types of GANs
#### 3.3.3 StyleGAN  
StyleGAN [43, 44] is a generative adversarial network architecture specifically designed to improve the control and quality of image synthesis. Unlike traditional GANs, which map a latent vector \(z\) directly to an image, StyleGAN introduces an intermediate latent space \(\mathcal{W}\), allowing for greater disentanglement of image features. The latent vector is first passed through a mapping network to produce \(w\in\mathcal{W}\), which is then used to modulate the layers of the generator via adaptive instance normalization (AdaIN). This mechanism enables fine-grained control over various visual attributes, such as texture, pose, and structure, at different levels of the network.  
The generator in StyleGAN progressively synthesizes high-resolution images through a coarse-to-fine architecture, while the discriminator learns to distinguish real images from those generated. The result is the production of highly realistic images, especially in human face synthesis, with improved variability and control over style compared to earlier GAN models.
# Improving Polar-Coded SCMA System by Information Coupling and Parity Check
## 5 Optimization of Partially Information-Coupled Polar Code Based on EXIT Idea  
In this section, the partially information-coupled polar code is optimized based on EXIT idea. The effects of weight factor \(\alpha\), impact of couple rate \(\delta\), and performance comparison of different code are analyzed based on transfer characteristics (TC) chart. Additionally, searching for the optimal value of \(\alpha\) and optimization of couple rate \(\delta\) for the PIC PCCA-polar code are performed in this section. We use the EXIT idea to guide our search for the optimal design \(\delta\)-value, which is the key parameter of the PIC PCCA-polar code.
## 5 Simulations and Experiments  
The BER comparison of the proposed method and the conventional one was executed by the simulation and practical lake and ocean experiments. For the fair BER comparisons, the DoMs of the two methods needed to be the same, and all whistles in Figure 8 needed to be utilized. The TFSK modulation parameters of \(M\) and \(N\) were four each and \(B_{c}\) was chosen as 300 Hz as in Section 4. Since the shortest whistle time in Figure 8 was measured by 0.13 s, the minimum sequence length was set as 39 by Equation (9) and the Kasami sequence with the length of 39 was used for the proposed method. When the sequence length was 39, \(\Delta t\) was chosen as 5 ms and \(\Delta f\) was set to 600 Hz by Equation (10). The modulation parameters of \(M\), \(N\), \(\Delta t\), and \(\Delta f\) were the same for the proposed method and the conventional one.
## 3 Results
### Refametinib Mitigates 5-FU-Induced PD-L1 Expression in SCC4 Cells  
Previous studies have suggested that cancer cells may use immune checkpoints as a survival mechanism to overcome chemotherapy-induced stress [30; 31]. Furthermore, the MAPK/MEK/ERK pathway has been shown to regulate the expression of PD-L1 in various cancer types [20]. Given the observed activation of ERK1/2 by 5-FU in SCC4 cells, our study aimed to investigate the effect of 5-FU treatment on PD-L1 expression in SCC4 cells. As demonstrated in Figure 3A,B, PD-L1 protein levels were significantly increased in SCC4 cells treated with various concentrations of 5-FU (50, 100, 200, and 400 uM) for 24 h (\(p<\) 0.05). Additionally, our flow cytometry data indicated a significantly higher surface expression of PD-L1 in the treated cells compared to control cells (\(p<\) 0.05) (Figure 3C,D). To further explore the effect of combined treatment with 5-FU and MEK inhibition on PD-L1 expression in SCC4 cells, cells were pretreated with Refametinib (50 nM) prior to treatment with increasing concentrations of 5-FU (100, 200, and 400 uM). As shown in Figure 3E-G, PD-L1 expression in SCC4 cells treated with 5-FU was significantly reduced through the combined treatment with Refametinib, while the surface expression of PD-L1 remained nearly unchanged. To verify the pharmacologic specificity of these findings, a second MEK inhibitor, U0126, was used and produced similar results (Figure 3H-J), further supporting the conclusion that the MEK/ERK pathway modulates 5-FU-induced PD-L1 expression in SCC4 cells. Together, our results suggest that combined treatment with 5-FU and MEK inhibition could mitigate whole-cell PD-L1 expression in SCC4 cells.  
Figure 2: Refametinib sensitizes SCC4 cells to 5-FU treatment for suppressing cell proliferation and promoting apoptosis. **(A,B)** The cells were treated with 5-FU (50 uM) for the indicated time intervals. The **(A)** Western blot analysis and **(B)** relative densitometric graph showing the phosphorylation of ERK1/2. **(C–H)** The cells were pre-incubated with Refametinib (Re; 50 nM) for 1 h and then treated with increasing concentrations of 5-FU (50, 100, 200, and 400 uM) for 24 h. **(C)** The cell viability was measured using MTS/PMS assay. The **(D)** Western blot analysis showing the protein expression of PARP, cleaved PARP, pro-caspase-3, and caspase-3. The relative densitometric graphs showing PARP and caspase-3 cleavage. **(E)** The cell density was observed under a light microscope (10\(\times\)). **(F)** Representative images of colony formation assay and their quantitative analysis. **(G,H)** Mitochondrial membrane potential was measured through flow cytometry using TMRE. * \(p\) < 0.05, as compared to the control. # \(p\) < 0.05, 5-FU alone vs. 5-FU + Refametinib. All experiments were independently performed at least three times.
# Identification of Critical Road Links Based on Static and Dynamic Features [PERSON]
## 4 Experimental Setup  
### Dataset Description  
In this paper, the central area of Huangpu District in Shanghai was selected as the study area, and the basic data included two data sources. The first one was the GIS map of the urban area of Huangpu District in Shanghai, which included road direction, road level, design speed, number of lanes, and other relevant information. The second one was the automatic vehicle identification (AVI) data in Shanghai during January, which contained the AVI device number, the desensitized license plate of the vehicle, vehicle type, passing time, driving direction, lane number, and other relevant information. We reconstructed the travel trajectories of all vehicles based on the travel time estimation method and mapped individual travel behavior to the road network for calculation. This process enabled us to obtain the traffic flow and average speed of each road link during a specific time interval.  
We constructed a directed dual traffic network in the central area of Huangpu District using the data sources described above, as illustrated in Figure 3. This network comprised 277 road link nodes and 769 edges. By integrating the AVI data, we were able to obtain the traffic flow and average speed of each road link during a specific time interval.
# Zero-Shot Recognition Enhancement by Distance-Weighted Contextual Inference
## 4 Experiments
### Detector Comparison
The \(\text{HM}_{path}\) method on \(\text{ConSE}\) is applied to the contextual inference, and its optimized values of balancing parameters, \(\alpha\) and \(\beta\) on \(\text{GT}_{\text{S}}\), are used for the evaluation. Figure 3 depicts several qualitative experimental results. The upper three and lower two results show the positive and negative effects of our method, respectively. In the first example, the ground-truth class label of the target object (orange box) is _chair_. The visual inference predicts _chair_-like _bathtub_ and _toilet_ in the first and second rank, respectively, with _chair_ in the third. By referring to the nearby objects, _table_ and _sofa_, which are related to a living room, the contextual inference calibrates the prediction results to rank _chair_ first. Another surrounding object, _fan_, far from the target, does not adversely affect the positive calibration because the degree of reference is reduced by distance-weighting. This verifies our assumption that related objects are likely to be located nearby. In fact, the CSs of _sofa_ and _table_ with _chair_ in GloVe are both above 0.4, whereas that of fan is approximately 0.11. Similar positive phenomena are confirmed from the second and third examples, as well. Our methods infers the correct class label, _flower_, which is not even in the top-5 of the visual-only prediction, into the top-3 by using the contexts close to the target, _leaf_ and _vase_, in the second example. In the third example, which has little useful surrounding information, the rank of _collar_ is slightly increased by the closest object, _dog_, with our distance formula. Although the overall performance is enhanced by the positive calibration of contextual inference, it still has some negative effects, particularly in the cases of general categories irrelevant to specific objects. For example, the visually fourth-ranked ground-truths, _writing_ and _sky_ are excluded from the top-5 and re-ranked to ninth and sixth, respectively. The tableware objects surrounding _writing_ negatively affect the prediction and produces high rankings for tableware-related categories such as _coffee_ and _chair_. _Sky_, which appears in most outdoor images regardless of the particular environment, generally does not have a semantic relation with a specific object. In the last example, the ground-truth category is undervalued by the contextual inference and rather structure-related _window_ and _building_ are overvalued due to the low similarities between _sky_ and its surrounding _roof_ and _train_. However,
## 5 Conclusions  
Adaptive power management techniques like Dynamic Power Switching, Dynamic Voltage and Frequency Scaling and Adaptive Voltage Scaling have become common place in many chips. We expect further enhancements and widespread adoption of adaptive techniques in the future due to three fundamental driving forces: Rising chip design costs, increasing process variability, increasing numbers of battery operated appliances. Rising chip costs imply that a single design will attempt to cover a wide range of applications. Hence one can expect a large dynamic range in the computational demands on such chips. Increased process variations in deep sub-micron nodes will imply a large spread in the voltage-frequency relationship for the chips. Finally the rise of battery powered applications forces the designer to extract power efficiencies from all possible design strategies. This naturally leads to adaptive techniques to help chips be power efficient across a large range of computation loads in advanced process nodes with large process variations.
###### Abstract  
Mapping of lava flows in unvegetated areas of active volcanoes using optical satellite data is challenging due to spectral similarities of volcanic deposits and the surrounding background. Using very high-resolution PlanetScope data, this study introduces a novel object-oriented classification approach for mapping lava flows in both vegetated and unvegetated areas during several eruptive phases of three Indonesian volcanoes (Karangetang 2018/2019, Agung 2017, Krakatau 2018/2019). For this, change detection analysis based on PlanetScope imagery for mapping loss of vegetation due to volcanic activity (e.g., lava flows) is combined with the analysis of changes in texture and brightness, with hydrological runoff modelling and with analysis of thermal anomalies derived from Sentinel-2 or Landsat-8. Qualitative comparison of the mapped lava flows showed good agreement with multispectral false color time series (Sentinel-2 and Landsat-8). Reports of the Global Volcanism Program support the findings, indicating the developed lava mapping approach produces valuable results for monitoring volcanic hazards. Despite the lack of bands in infrared wavelengths, PlanetScope proves beneficial for the assessment of risk and near-real-time monitoring of active volcanoes due to its high spatial (3 m) and temporal resolution (mapping of all subaerial volcanoes on a daily basis).  
lava; volcanoes; PlanetScope; change detection; object-based image analysis 2022
## 3 Results and Discussion
### Comparison of Bioactive Components
#### 3.3.2. Tocopberols, Squalene, and Polyphenols
In this study, various distributions of total polyphenols in different types of camellia oils were observed, as illustrated in Figure 4a. Total polyphenols were detected in C.O, C.G, and C.S, with the highest amount found in C.S, followed by C.G and C.O. Notably, no polyphenols were observed in C-C.O, suggested that the refining process, particularly the temperatures used, may play a significant role in the presence or absence of polyphenols in camellia oil. As polyphenols are highly unstable and can be easily degraded during post-harvesting and processing, it is crucial to consider the impact of refining methods on their preservation. Correspondingly, [PERSON] et al. [16] reported that the total polyphenol content in refined camellia oil (not detected) was significantly reduced compared with cold-pressed camellia oil (19.15 mg/kg). Additionally, it was expected that no polyphenols would be detected in C-C.O-DAG due to the absence of polyphenols in C-C.O (Figure 4a). As demonstrated above, various camellia oils are rich in bioactive components, such as tocopherols, squalene, and polyphenols. Therefore, for those looking to increase their antioxidant intake, using these camellia oils is recommended. On the other hand, although DAG-enriched oils contain reduced levels of bioactive components, like tocopherols, squalene, and polyphenols, DAG-enriched oils have been proven beneficial for fat metabolism and blood lipid control [34]. Additionally, this study shows that DAG-enriched oils contain higher levels of unsaturated fatty acids (Table 2), making them a good choice for individuals with chronic conditions, such as cardiovascular diseases [34]. Cluster analysis, utilizingtocopherol, squalene, and total polyphenol contents as variables, revealed distinct distributions among different camellia oils (Figure 4b). Specifically, C.S was characterized by its high total polyphenol content, C.G by its squalene content, and C.O by its topcherol content. In contrast, low contents oftocopherol, squalene, and total polyphenols were characteristic of C-C.O and DAG-enriched counterparts, in the order of C-C.O-DAG 80% \(<\) C-C.O-DAG 40% \(<\) C-C.O. These findings suggested that tocopherol, squalene, and total polyphenols are useful indicators for distinguishing different types of camellia oils.
# Design and Experiment of a Passive Vibration Isolator for Small Unmanned Aerial Vehicles
###### Abstract  
The advancement of sensor, actuator, and flight control technologies has increasingly expanded the possibilities for drone utilization. Among the technologies related to drone applications, the vibration isolator technology for payload has a significant impact on the precision of optical equipment in missions such as detection, reconnaissance, and tracking. However, despite ongoing efforts to develop vibration isolators to mitigate the impact of vibrations transmitted to optical equipment, research on drone-specific natural frequencies and payloads has been lacking. Consequently, there is a need for research on vibration isolators tailored to specific drone types and optical equipment payloads. This study focuses on exploring the correlation between the natural frequencies of drones and the weight of the payload, and proposes methods for developing and testing vibration isolators that consider both factors. To achieve this, the study measured the stiffness of vibration isolator rubbers and conducted cross-validation between random vibration tests and finite element method (FEM) analyses to verify the vibration reduction effects resulting from changes in the dynamic characteristics of vibration isolator rubbers. The rubber with a shore hardness of 70 exhibited relatively high damping and damping performance during random vibration tests. Additionally, it showed relatively high stability with only one resonance point measured within the operational frequency band. Through the findings of this study, a methodology for selecting vibration isolators for drones is proposed, aiming to enhance the stability of optical equipment.  
vibration isolator; rubber characteristics; frequency response characteristics; passive damper; drone ground vibration test +
Footnote †: journal: Applied sciences
# A Novel Cascaded Modular Photovoltaic Energy Storage System for Partial Shading Conditions
## 3 Experimental Verification
Furthermore, this relationship between the compensation current and SOC can also be found and verified in other ES modules, as shown in Figure 9b-d. Therefore, it can be seen that the _SOCs_ of all ES modules are maintained within the range of 20% and 80%, which means that all of the ES modules are prevented from deep charging and discharging. In addition, the _SOCs_ of all of the ES modules obtain convergence trends toward 50%, which is consistent with the control purpose of the energy optimization strategy. Moreover, the proposed PV/ES system achieves efficiency at about 97% under a partial shading condition, which is higher than the conventional string structure PV system with an efficiency of 90% [19], and is similar to the distributed and hybrid structure PV systems with an efficiency of about 97% [20,24], providing an effective and practical solution for power generation system. Figure 10 shows the current of the DC bus and the power of the PV/ES system. The \(i_{\text{opt}}\) is the optimal current of the DC bus searched out by the PSO algorithm, which is the global best position given in (10), while the \(i_{\text{bus}}\) is the actual current of the DC bus. It can be seen that the current of the DC bus follows its optimal values. In Figure 10, the \(P_{\text{pysum}}\) is  
Figure 9: PV power, compensation current, and \(SOC\) in the PV/ES modules: (**a**) PV/ES module 1, (**b**) PV/ES module 2, (**c**) PV/ES module 3, (**d**) PV/ES module 4.  
the sum of the power generated by all of the PV modules in the PV/ES system, while \(P_{\text{grid}}\) is the active power of the grid-connected converter, i.e., the active power from the PV/ES system to the grid. According to Figure 10, although \(P_{\text{p}\text{v}\text{v}\text{m}}\) varies with the light intensity, the active power from the PV/ES system to the grid is constant in the given time period.