esa-sceva/satcom-chunk-collection huggingface dataset:
## 6 Discussion
### Considerations Regarding the RL DLNN Control Strategies' Applicability  
The proposed RL DLNN control strategies are well suited for handling the complexities of real-world centrifugal chiller systems, due to the abilities of the RL agents to cope with dynamic environments (e.g., varying cooling loads, weather conditions, or equipment performance) and to detect and compensate for system faults or degradation. Moreover, with the rapid advancements in edge computing and hardware acceleration, RL controllers can perform real-time optimization, making them practical for real-world applications. Moreover, RL DLNN controllers can be effectively scaled for centrifugal chiller systems due to a combination of attributes, including their modularity, ease of transfer learning (i.e., pre-trained RL models can be fine-tuned for different chiller systems or operating conditions, reducing the need for extensive retraining), and distributed control capabilities (i.e., RL agents can be deployed in a distributed manner, controlling multiple chillers in a plant or across different locations, and coordinated to achieve global objectives).  
From another point of view, the applicability of the proposed RL DLNN control strategies in real-life scenarios can be affected by three important factors: (a) the customized reward function design based on step response specifications may not cover all operational constraints, such as energy efficiency, or the long-term stability of the MIMO Centrifugal Chiller control system, requiring fine-tuning for each specific HVAC application; (b) safety and stability concerns resulting from possibly damaging actions the RL agents explore during training; and, (c) high computational cost, since the RL DLNN models can be computationally expensive to train and deploy, demanding significant hardware resources. These limitations may be mitigated by employing carefully pre-trained RL agents deployed on real-time and low-cost embedded systems.
## 2 State of the Art
### Research Gap and Future Work
A key challenge for future studies is the interoperability of these systems, which requires the development of standardized protocols for seamless integration across logistics networks. Beyond the port sector, similar technologies could be adapted to improve efficiency in container management, multimodal transport, and urban mobility solutions. Recent studies, such as those by [35; 36], have highlighted innovative approaches that could be leveraged for these advancements.
## 4 Discussion
### Study Limitations  
This study provides the results of a first assessment of the proposed system, with the aim to measure its accuracy and to preliminary determine its utility for ergonomic assessment. Many studies should be carried out to fully understand its practical suitability to be used for ergonomic assessment in real working environments. The experiment was conducted only in the laboratory and not in a real working environment. This limits the study results. Therefore, it did not allow the researchers to evaluate the instrument's sensitivity to any changes in lighting or unexpected illumination conditions (e.g., glares or reflections). Further studies are needed to fully evaluate the implementation constraints of the proposed system in a real working environment.  
In addition, the study is limited to evaluating the RULA risk index related to static postures only. Further studies will be needed to evaluate the possibility of using the proposed system for the acquisition of data necessary for other risk indexes (e.g., REBA, OCRA), also considering dynamic postures.  
Another limitation is that the experiment conducted did not entirely evaluate the proposed system functionalities in conditions of severe occlusion (e.g., as could happen when the workbench partially covers the subject). Despite results evidenced that the proposed system, unlike Vicon, does not suffer from minor occlusion (i.e., due to the presence of a box during a picking operation), further studies are needed to accurately assess the sensitivity of the proposed system with different levels of occlusion.  
Another limitation is the small number of subjects involved in the study. A small group of subjects was involved, with limited anthropometric variation, assuming that the tf-pose-estimation model was already trained on a large dataset. Further studies will need to confirm whether anthropometric variations affect the results (e.g., whether and how the BMI factor may affect the estimated angle accuracy).
# CloudformerV3: Multi-Scale Adapter and Multi-Level Large Window Attention for Cloud Detection
## 3 Materials and Methods
### Multi-Scale Adapter  
The traditional adapter [33] comprises three components: Spatial Prior Module, Injector, and Extractor. Spatial Prior Module is used to extract spatial information from the image, while Injector and Extractor modules facilitate interaction with the backbone. When applied to cloud detection, due to the substantial disparities between natural images and remote sensing images, using the backbone trained on natural images directly for fine-tuning yields unsatisfactory outcomes. In contrast, the adapter can infuse prior information from remote sensing images into the backbone trained on natural images, rendering the model better suited for cloud detection. This adaptation enhances the model's effectiveness in cloud detection tasks.  
However, the traditional adapter cannot be applied to the hierarchical backbone structure, which makes the multi-scale feature extraction suffer. To solve this problem, this paper proposes a novel multi-scale adapter that inserts DownSample Layer between each Extractor and Injector, as shown in Figure 3. After the \(i\)th Extractor, it can obtain the output feature \(F^{i}_{sp}\in\mathbb{R}^{(HW/(2i)^{2}+HW/(4i)^{2}+HW/(8i)^{2})\times D_{i}}\). In the DownSample Layer, it is first split and reshaped to obtain three feature maps \(F^{i}_{sp1}\in\mathbb{R}^{H/(2i)\times W/(2i)\times D_{i}}\), with different resolutions. Then the feature map is reduced to one-half of its original length and width by the Patch Merging layer [36] to obtain \(\hat{F}^{i}_{sp1}\in\mathbb{R}^{H/(4i)\times W/(4i)\times D_{i+1}}\), \(\hat{F}^{i}_{sp2}\in\mathbb{R}^{H/(8i)\times W/(8i)\times D_{i+1}}\), and \(\hat{F}^{i}_{sp3}\in\mathbb{R}^{H/(16i)\times W/(16i)\times D_{i+1}}\). Finally, \(\hat{F}^{i}_{sp1}\), \(\hat{F}^{i}_{sp2}\), and \(\hat{F}^{i}_{sp3}\) are flattened and concatenated to obtain \(\hat{F}^{i}_{sp}\in\mathbb{R}^{(HW/(4i)^{2}+HW/(8i)^{2}+HW/(16i)^{2})\times D_ {i+1}}\), which is injected into the next Injector. The process can be formulated as:  
\[F^{i}_{sp1},F^{i}_{sp2},F^{i}_{sp3}=Reshape\Big{(}Split\big{(}F_{sp}{}^{i} \big{)}\Big{)} \tag{1}\]  
\[\hat{F}^{i}_{spj}=PatchMerging(F_{spj}),j\in\{1,2,3\} \tag{2}\]  
\[\hat{F}^{i}_{sp}=Flatten\Big{(}Concat(\hat{F}^{i}_{sp1},\hat{F}^{i}_{sp2},\hat {F}^{i}_{sp3})\Big{)} \tag{3}\]  
Figure 2: The overall structure of CloudformerV3 consists of three main components: Green dashed outline represents the input image and prior information, blue dashed outline represents the encoder and purple dashed outline represents the decoder.  
The utilization of a multi-scale adapter accomplishes more than just enhancing the model's suitability for the cloud detection task and introducing prior information. It also empowers the backbone to acquire precise prior information across all scales, enabling a more comprehensive grasp of the image's structure and features. This facilitates improved differentiation between regions containing clouds and those without, particularly in intricate scenarios.
# A Comparative Analysis of Feature Detectors and Descriptors for Image Stitching
## 3 Materials and Methods
### Method: Comparative Analysis
#### 3.2.3 Execution Time  
The overall time required to identify, match and stitch the input images is referred to as the execution time. The execution time is a significant consideration when choosing an image stitching method for real-time applications. For some detector-descriptor pairs, either correct matches are zero or less than four. Therefore, for those pairs, execution time has no meaning because we consider execution time as total time from detection to final stitched image generation. In order to quantitatively compare those pairs with other pairs, we used a large dummy value for the execution time of those pairs. In this study, set this dummy value equal to 100 s.  
The abovementioned IQA measures are used to assess the stitched image's quality. The quality of the stitched image produced from every feature detector-descriptor pair is assessed by comparing the quality of the overlapping area of the input and the final stitched image. As shown in Figure 3, the overlapping regions of each left image (L) and right image (R) are compared to the overlapping areas of the final stitched image. In Figure 3, the overlapping area in the left image, right image and stitched image is represented by Lo, Ro and So, respectively. Quality metrics were calculated for each image pair and each detector-descriptor pair. In order to acquire quality metrics, the overlapping region So was compared to Lo and Ro individually, and then the mean value was computed. Figure 3 illustrates the entire workflow for evaluating the performance of the feature detector-descriptor combination for image stitching.  
Figure 3: Workflow adopted for comparison of feature detector–descriptor pair for image stitching algorithm.
# Energy-Balanced Routing Algorithm Based on Ant Colony Optimization for Mobile Ad Hoc Networks
###### Abstract  
The mobile ad hoc network (MANET) is a multi-hop, non-central network composed of mobile terminals with self-organizing features. Aiming at the problem of extra energy consumption caused by node motion in MANETs, this paper proposes an improved energy and mobility ant colony optimization (IEMACO) routing algorithm. Firstly, the algorithm accelerates the convergence speed of the routing algorithm and reduces the number of route discovery packets by introducing an _offset coefficient_ of the transition probability. Then, based on the energy consumption rate, the remaining lifetime of nodes (RLT\(n\)) is considered. The position and velocity information predicts the remaining lifetime of the link (RLT\(l\)). The algorithm combines RLT\(n\) and RLT\(l\) to design the pheromone generation method, which selects the better quality path according to the transition probability to ensure continuous data transmission. As a result, the energy consumption in the network is balanced. The simulation results show that compared to the Ad Hoc on-demand multipath distance vector (AOMDV) algorithm with multipath routing and the Ant Hoc Max-Min-Path (AntHocMMP) algorithm in consideration of node energy consumption and mobility, the IEMACO algorithm can reduce the frequency of route discovery and has lower end-to-end delay as well as packet loss rate especially when nodes move, and can extend the network lifetime.  
energy constraint; ant colony optimization algorithm; convergence; remaining lifetime +
Footnote †: journal: Sensors
## 3 Results and Discussion
### Effect of Adaptation to Cd Stress on Biomass of the Middle European Ecotype of S. nigrum
#### 3.3.3 Reactive Oxygen Species (ROS)  
Reactive oxygen species (ROS), the superoxide anion (O\({}_{2}\)\({}^{\bullet-}\)) and hydrogen peroxide (H\({}_{2}\)O\({}_{2}\)) generated in excess, are involved in physiological stress and pathological processes in the apoplast of plant cells. They displayed a distinct increase in the leaves of both non-adapted N0 and adapted A50 varieties in parallel to the increase in Cd content in the soil, indicating growing oxidative stress (Figure 3). However, no signs of crisis and deep cell damage with respect to superoxide anion content was observed. The increase for N0 and A50 was regular, by 105% and 69%, respectively, at Cd treatments over the entire range between T0 and T50. The O\({}_{2}\)\({}^{\bullet}\) level was nonetheless considerably (by 31%) bigger in leaves of N0 than of A50 (Figure 3a) indicating lesser oxidative stress of the adapted variety.  
Figure 3: Effects of different Cd treatments on ROS contents: (**a**) superoxide anion and (**b**) hydrogen peroxide in in non-adapted N0 and adapted A50 varieties of _S. nigrum_ L. (1) 0 to 50 means control and soil treatments with Cd (mg kg\({}^{-1}\)); (2) Data for the same treatments marked by the same capital letters over bars are not significantly different at \(p<0.05\). Data for different treatments marked by the same lowercase letters over bars are not significantly different at \(p<0.05\).  
Figure 2: Effects of different Cd treatments on (**a**) RbcL and (**b**) RbcS content in the non-adapted N0 and adapted A50 varieties of _S. nigrum_ L. (1) 0 to 50 means control and soil treatments with Cd (mg kg\({}^{-1}\)); (2) Data for the same treatments marked by the same capital letters over bars are not significantly different at \(p<0.05\). Data for different treatments marked by the same lowercase letters over bars are not significantly different at \(p<0.05\).  
Oxidative stress caused by hydrogen peroxide (H\({}_{2}\)O\({}_{2}\)) also appeared to be more pronounced for the N0 variety. A substantially higher level of this ROS was detected in its leaves at T50 compared to T30 treatment (by 74%), while increase of H\({}_{2}\)O\({}_{2}\) in the treatment range T0-T30 was weaker (by 58%). In contrast, the adapted A50 variety did not show much growth of H\({}_{2}\)O\({}_{2}\) level over the entire Cd concentration range (scarcely by 29% compared to T0). This indicated its high resistance to Cd stress practically up to the highest T50 treatment, at a distinctly lower ROS level in the leaves of the adapted A50 variety. Inversely, sharp up-regulation of H\({}_{2}\)O\({}_{2}\) at T30-T50 range in N0 showed symptoms of greater stress at T50.
## 2 System Model and Transmission Process
### Transmit Power Constraints in Secondary Networks  
In underlay mode, primary and secondary users in CRNs can work within the same spectrum simultaneously. However, if the secondary network has no transmit power constraint, it will cause serious signal interference to the primary network. Therefore, in order to ensure the performance of the primary network, in this paper, BS and the selected relay adaptively adjust their transmit powers.  
Next, \(I_{th}\) is defined as a threshold and represents the maximum tolerable interference level of primary network, at which reliable communication can be guaranteed. Assuming that the maximum permissible transmit powers of BS and relays are \(P_{1}\) and \(P_{2}\), respectively, the transmit powers of BS and relays are constrained as [33].  
\[P_{S}=min\left\{\frac{I_{th}}{\big{|}h_{SR}\big{|}^{2}},P_{1}\right\}\text{ and }P_{R}=min\left\{\frac{I_{th}}{\big{|}h_{R_{n}R}\big{|}^{2}},P_{2}\right\}. \tag{9}\]  
Especially, when U\({}_{1}\) is used as an optimal relay, \(h_{R_{n}R}\) in (9) will be replaced by \(h_{U_{1}R}\).
## 3 Results and Discussion
### Extraction and Fractionation of the Pigments  
We proposed to use a mixture of hexane and ethanol alcohol in a ratio of 2:1 as an extracting agent, which resulted in the high yield of the pigment complex.  
The saponification step to separate chlorophylline acids is the key to obtain the carotenoid fraction. Saponification at low KOH concentrations (0.01 and 0.2 M) gives the best results for astaxanthin extraction.  
Long-term saponification with relatively high KOH concentrations (0.2 and 0.5 M) gives the best results for xanthophyll extraction.  
The research of the KOH concentration's effect on the spectral profile of _C. vulgaris_ extracted pigments is shown in Figure 7. It was found that an alkali concentration of 0.2 M is most appropriate, and that it allows us to obtain the highest concentrations of the determined substances.  
The alkali-free extract of carotenoids in hexane had a pH level of 5.5. [PERSON] and [PERSON] [30] reported that the major stability of carotenoids is revealed in the pH range from 6 to 7. Thus, it is required that we remove excess alkali after the carotenoids' saponification in order to obtain neutral pH values. The required pH values are reached after the third stage of washing with oxygen-free distilled water in an inert atmosphere.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Homogenization Speed, rpm** & **C\({}_{\text{Car}}\)**\(\upmu\)**/mL** \\ \hline
0 (control) & 11.46 \\
6000 & 23.16 \\
8000 & 14.85 \\
10,000 & 17.52 \\
12,000 & 14.85 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Influence of the rate of homogenization on the yield of carotenoids in the extracts.  
Figure 6: Influence of the rate of homogenization on the quantity of cell disintegration.  
It was found that the amount of impurities (carotenoid ethers and chlorophyll derivatives) in the extract was reduced. The carotenoid loss amounted to an average of 6%. The spectral profile of the carotenoids showed a distinctive \"corona\", with three peaks at 420, 445 and 472 nm. A complex of peaks similar to those obtained was described by the author for neurosporene (414, 439, 467 nm), and by the authors for \(\alpha\)-carotene (423, 444, 473 nm) and \(\beta\)-carotene (425, 450, 478 nm) [31].  
The carotenoid pigments' composition is analyzed in Table 3.  
The obtained sample of carotenoids had a bright orange color, and the content of the main substance was 52 \(\pm\) 3 mg/mL. The carotenoids of _C. vulgaris_ microalgae are represented by lutein (about 45%), fucoxanthin (about 12%) and \(\beta\)-carotene (4.3%). The total carotenoids were resuspended in soybean (castor) oil in order to obtain the oil concentrate that we propose to use as a dietary supplement in the future.
## 4 Materials and Methods
### Subcellular Localization of OpWRKY3  
To investigate the subcellular localization of _OpWRKY3_, its full length of _OpWRKY3_ was amplified and inserted into vector pMON530-GFP located at the restriction site of _Bgl_ II and _Kpn_ I to generate _pMON530-OpWRKY3-GFP_. The constructed expression vector was transferred into _Agrobacteriumium_ strain ASE and injected into 60-day old tobacco leaves. GFP fluorescence was observed using the confocal microscope after 48 h of cultivation [47]. In total, 1 \(\mu\)g mL\({}^{-1}\) 4, 6-diamidino-2-phenylindole (DAPI) was injected into tobacco leaves for 3 h before observation. A corresponding empty vector was considered as the control.
# A Supervised Speech Enhancement Approach with Residual Noise Control for Voice Communication
## 5 Results and Analysis
### The Impact of \(\alpha\)  
To analyze the impact of \(\alpha\), we select one type of parameter configuration, with\(\gamma=2,\ \beta_{0}=-20\ \mathrm{dB}\), and \(\mu=1\), which has shown the best performance among various configurations. The value of \(\alpha\) ranges from \(1\) to \(2\) with the interval \(0.1\). The reason for choosing \(\alpha\geq 1\) is to avoid the gradient value infinite problem during the back-propagation process for \(\alpha<1\). The metric results w.r.t. \(\alpha\) are given in Figure 3. One can observe the following phenomena. First, the increase of \(\alpha\) will decrease both NA and SA values. This is because the estimated gain in each T-F bin ranges from \(0\) to \(1\), and the increase of \(\alpha\) will lead to a larger value, cf. (17). As a consequence, the network tends to attenuate less background interference and preserve more speech components. Second, both PESQ and SDR tend to decline with  
Figure 2: Test results in terms of NA, SA, PESQ and SDR. The averaged PESQ score of the noisy signals is \(1.80\) and its averaged SDR is \(2.51\ \mathrm{dB}\). Here \(\alpha_{0}\) is fixed at \(1\) for all conditions.  
the increase of \(\alpha\), which can be explained as more residual noise components are preserved, and they will heavily degrade the speech quality although the speech distortion is reduced.
## 3 Applications of NMR in polysaccharide Research  
The applications of NMR in polysaccharide research span many areas, indicating flexibility and strong functions as an analytical tool. NMR has played an important part in elucidating the structure-function relationships of polysaccharides, contributing to the development of biomedical, food, and environmental sciences.  
For instance, it has provided insights into the immunomodulatory and anticoagulant activities of polysaccharides, which promotes therapeutic innovation [15, 53]. In the food industry, NMR is vital for studying how polysaccharides interact in complex arrays. This interaction can improve the texture, stability, and sensory properties of food [19, 54].  
The NMR analysis of marine microorganisms and polysaccharides is beneficial for environmental applications, providing solutions for biofilm management and sustainable technologies [10]. These various applications show that NMR plays a crucial role in turning structural insights into practical benefits in many fields.  
To summarize these diverse applications, we have compiled key studies into Table 3. This table outlines the major contributions of NMR in biomedical applications, food science, and environmental research. It highlights key findings, methodologies, and potential impacts in each field.  
Figure 4: Overview of \({}^{13}\)C, \({}^{15}\)N, and \({}^{1}\)H-detection solid-state NMR, supplemented by DNP, to compare the structural organization of cell wall polymers and their assembly in the cell walls of _A. fumigatus_ and _A. nidulans_. Copyright (2025) Elsevier.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Field** & **Key Findings** & **Methodology** & **Potential Impact** \\ \hline Biomedical & Elucidation of immunomodulatory and anticoagulant polysaccharides & Solution-state NMR, HSQC, NOESY & Development of therapeutics for immune modulation and clotting \\ Structural characterization of bacterial capsular polysaccharides & Multidimensional NMR, isotopic labeling & Improved vaccine design and efficacy \\ for vaccines & Antioxidant activity of polysaccharides & \({}^{1}\)H NMR, MD & Reduced oxidative stress; therapeutic innovation \\ \hline \hline \end{tabular}
\end{table}
Table 3: Applications of NMR in polysaccharide research.
## 2 Related Work
### Semantic Preservation Techniques  
Recent work by [PERSON] et al. [12] introduced syntax-space hiding techniques, achieving higher embedding capacity while preserving semantic coherence. Their HISS-Stega framework demonstrated significant improvements in maintaining text naturalness. [PERSON] et al. [13] addressed the critical issue of segmentation ambiguity in generative steganography, proposing a secure token-selection principle that enhanced both security and semantic preservation.