esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Sentinel-1: Opportunities
### Monitoring of Water Volumes Retained at Reservoirs  
In order to evaluate the potentiality of Sentinel-1 in measuring water volumes in semi-arid regions, we compared a series of simulated COSMO-SkyMed images superimposed to a 9 m spatial resolution DEM and a series of simulated Sentinel-1 images superimposed to a 15 m spatial resolution DEM for different levels of the water contour height. The results of the comparison are shown in Figure 8 for the Laaba reservoir. Such a comparison provides an estimation of the effect of the loss in spatial resolution introduced by Sentinel-1 with respect to the COSMO-SkyMed products used in the WARM-SAR project.  
As expected, the discrepancy between Sentinel-1 (blue curve) and COSMO-SkyMed (orange curve) arises especially when the basin tends to fill up. In fact, when the water level increases, its contour is better  
Figure 8: Laaba basin: Surface water as function of the contour height.  
Figure 9: Laaba basin: retained water volume as function of the contour height.  
delineated by the higher COSMO-SkyMed resolution. The error introduced by the loss in spatial resolution is in the order of 15%-20% and it is almost constant for water contour height \(\in\)[339.5, 341].  
The estimated surface is then used for computing the water volume retained into the basin considering each pixel belonging to the water mask extracted from the simulated Level-1\(\alpha\) products as a water column, as explained in Section 5.1.  
Results of this analysis are shown in Figure 9. The errors in the estimation of the surface areas do not affect significantly the retained volume calculation since they are mainly located at the boundary of the basin, where the contributions to the summation of (4) are small.
# Energy-Efficient Wireless Hopping Sensor Relocation Based on Prediction of Terrain Conditions
## 1 Introduction
In fact, no matter how small the observation field to obtain interested data is, the exchange of information and establishment of paths among the cluster header sensors are difficult in real world, and involve a storm of numerous control messages. Recently, our research team has solved these problems drastically [19]. First of all, every cluster header does not need to know all information of other cluster headers or all networks. It is a distributed networking-based relocation protocol that recovers a sensing hole by simply requesting necessary sensor nodes from neighbor cluster headers. A cluster header node selects appropriate hopping sensors based on information communicated among all sensor nodes in its cluster, and they are moved to the requesting neighbor cluster. Up to now, however, most relocation protocols have assumed that the observation fields, in which mobile sensors are scattered, are ideal environments. In other words, the areas where sensors move are likely to be irregular, under the existence of obstacles like stones or mud. Reference [18] is the first study of hopping sensor relocation based on probabilities of existence of obstacles, however there is a limitation that the assumption that every cluster header sensor grasps all information of rugged terrains in all regions is not very realistic. In this paper, a novel relocation protocol that considers the probabilities of the level of obstacles using the information of success rate for migration is proposed. Here, it is not necessary for each cluster header sensor node to know all information of entire network; the cluster header only knows the information such as the probabilities between neighbor clusters. In addition, as far as we know, it can be very meaningful to have the first realistic simulation with OMNeT++ [20], similar to the actual environment. The rest of this paper is organized as follows. Section 2 summarizes the mobility model of hopping sensor and the related relocation protocol. In Section 3, the proposed relocation protocol is explained along with the scenario in detail. The simulation results are analyzed in Section 4, and Section 5 concludes this paper.
# Prediction of Belt Drive Faults in Case of Predictive Maintenance in Industry 4.0 Platform
## 3 Research Area
### Autoencoder  
Autencoder as one of the types of neural networks has a very high ability in remembering and comparing patterns. This feature is effective in time-varying signal problems for which there are problems of deviation from reference signals. Using the comparison with the pattern, encoder networks are a very good tool in problems related to the monitoring of anomalies in sequential signals, so in the research work conducted within the framework of the presented paper, it was decided to analyze the effectiveness of the network in the belt drive example.  
AutoEncoder is a generative unsupervised deep learning algorithm used for reconstructing high-dimensional input data using a neural network with a narrow bottleneck layer in the middle which contains the latent representation of the input data [20; 21] (Figure 6). Autoencoder neural network is an unsupervised machine learning algorithm that applies back propagation by setting target values equal to inputs. An autoencoder consists of three components: an encoder, a coder, and a decoder. The encoder's job is to compress the input data, then the encoder's job is to generate the code so that the final decoder reconstructs the input data as accurately as possible using only that code. Given a data point \(x\in\mathcal{R}^{d}\), the loss function is viewed as minimizing the reconstruction error between the training data (\(x\)) and the autoencoder outputs \(\hat{x}\)[22]:  
\[L(x,\hat{x})=\|x-\hat{x}\|^{2}, \tag{2}\]  
After the training process, the autoencoder uses the reconstruction error as the anomaly score. Data with high reconstruction error score are considered as anomalies because only normal data are used to train the autoencoder. The autoencoder, by correctly fitting undamaged data, will reconstruct normal data very well, while it will not do so when there is damage that the autoencoder has not encountered.  
Figure 6: Examplary structure of autoencoder.  
For the conducted research, it was assumed that the network in its structure consisted of 6 layers (16-8-4-4-8-16). The input size was equal to 36, rectified linear unit activation function for each neuron was used Equation (3).  
\[f(x)=\max(0,x), \tag{3}\]  
During the study, 1000 examples were generated, which were divided into a training set consisting of 70% and a verification set consisting of 30%. The number of epochs in the training process was equal to 200. The learning process was carried out using the ADAM optimizer.
# Impacts of Compound Hot-Dry Events on Vegetation Productivity over Northern East Asia
## 2 Materials and Methods
### Observational Data  
Observations of GPP, SM, and ET are utilized to analyze the ecological and hydrological characteristics of the CHD events.  
The daily GPP data at a spatial resolution of 0.05\({}^{\circ}\) were acquired from the Global MODIS and FLUXNET-derived Daily Gross Primary Production (FluxSat) v2.2 dataset [37]. This dataset integrated ground-based station observations to calibrate and validate the MODIS remote sensing data, ensuring precise estimations of GPP with remarkable spatial and temporal resolution.  
\begin{table}
\begin{tabular}{p{56.9 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Experiment No.** & **Experiment Name** & **Forcings of the Experiment** \\ \hline \hline  & _Control_ & Observed forcings in hourly frequency and 0.5\({}^{\circ}\) spatial resolution from 2003 to 2019. \\ \hline \hline
1 & \(SE\_Clim\) & Climatological means in 2 m temperature, precipitation, radiation, and 2 m specific humidity during the compound hot-dry (CHD) events. \\
2 & \(SE\_PRQ\) & Similar to \(SE\_Clim\), but with observed precipitation, radiation, and 2 m specific humidity. \\
3 & \(SE\_RQ\) & Similar to \(SE\_Clim\), but with observed radiation and 2 m specific humidity. \\
4 & \(SE\_TR\) & Similar to \(SE\_Clim\), but with observed 2 m temperature and radiation. \\
5 & \(SE\_R\) & Similar to \(SE\_Clim\), but with observed radiation. \\
6 & \(SE\_P\) &  
The daily SM in the depth between the surface and 10 cm depth of soil and ET data were extracted from the Global Land Evaporation Amsterdam Model (GLEAM) v3.7b dataset [38; 39]. This dataset utilizes satellite observations to estimate terrestrial evaporation and SM, providing global-scale data with a resolution of 0.25\({}^{\circ}\). These data are of great significance for studying global terrestrial water cycle dynamics, evaluating ET patterns in different ecosystems, and understanding the impacts of climate change [40; 41; 42].  
The GLEAM and FluxSat datasets are aligned to and averaged at a spatial resolution of 0.5\({}^{\circ}\) compared to CLM5.
# Leveraging Digital Twin Technology for Sustainable and Efficient Public Transportation
## 2 Review of Different Aspects of Digital Twins
### Public Transportation and Digital Technologies
The integration of ITSs with digital twins is yet another significant area of research. One research study proposed a system that would combine the use of sensing devices on the vehicle, real-time simulation models, and predictive maintenance technologies to track the conditions of different vehicle components in terms of their remaining useful life [64]. Digital twin technology stands as a landmark opportunity for cities and vehicles to interact, which will improve urban mobility and vehicle performance, thereby enhancing transport management [67]. As the system evolves, it is a step towards an integrated system that can move from a Digital Shadow and become a fully functional digital twin. Blockchain technology, when combined with digital twins, opens up possibilities for the next generation of transport, and thus better service [22]. Guaranteeing secure data-sharing among transportation stakeholders, such as operators, regulators, and users, is among the benefits of blockchain's decentralized structure. The interaction between blockchain and digital twins can enhance safety, support sustainable transportation solutions, and optimize the available set of solutions.
# Perceived Brightness and Resolution of Holographic Augmented Reality Retinal Scan Glasses
## 1 Introduction  
Retinal scan (\"RS\") glasses are near-eye displays that use laser beam scanning for retinal image projection. A collimated light beam is projected via an optical combiner and through the human pupil onto the retina [1]. Recent advances in holographic manufacturing [2] have enabled the use of holographic optical elements (\"HOEs\") as transparent, diffractive optical combiners [3]. This allows for lightweight augmented reality displays to be integrated into all-day wearable smart glasses with a small formfactor.  
Research and development in the field is progressing quickly [4]. First efforts have been made to define new parameters like the ambient contrast ratio (\"ACR\") [5] that are necessary to characterize the performance of holographic augmented reality displays [6] in real visual environments. We elaborate on these efforts and show that for the special case of RS displays, interactions with the human eye must be considered.  
Most conventional display technologies such as LCD, LED, or waveguides emit light from each pixel into a large solid angle. Their emission profiles roughly obey Lambert's cosine law to keep luminance constant across different viewing angles. We use the term\"Lambertian\" to describe such displays. From Lambertian displays, only a small portion of the emitted light enters the human eye at any given time. In contrast, all light emitted by RS displays is confined to a narrow scanning beam which passes through the pupil. This makes RS displays not only energy efficient but also leads to important consequences for fundamental display parameters like the brightness and resolution.  
One challenge is that some conventional measurement devices such as luminance cameras cannot be used directly with RS glasses due to the interaction of the projection system with the human pupil. Instead, the luminance of an RS display must be computed in a certain way to achieve accurate results. We introduce a theoretically derived formula to calculate the retinal scan luminance and ambient contrast ratio. This formula incorporates various parameters including optical powers, wavelengths, field of view, and human pupil diameter. Building on this formula, we designed and conducted a psychophysical study to measure the perceived resolution of RS glasses in augmented reality settings.  
While contrast and resolution perception have been investigated in many previous studies as fundamental parameters of human visual perception [7], augmented reality glasses provide new opportunities to take the measurements of these parameters outside of controlled laboratory environments. This work presents novel theory and methods for such out-of-laboratory measurements.
## 5 Conclusions  
In this paper, we present Hybrid-DeepSCS, a novel semantic-aware digital speech communication system that bridges the gap between traditional digital transmission and emerging deep learning-based semantic communication. Our approach integrates a semantic encoder and decoder within a conventional digital transmission chain, enabling the extraction, discretization, and reconstruction of structured semantic features from speech. This hybrid design allows compatibility with existing communication infrastructures while leveraging deep learning for enhanced feature representation and speech reconstruction.  
Experimental results demonstrate that Hybrid-DeepSCS significantly improves performance in challenging channel conditions, such as Rayleigh and Rician fading. While conventional systems maintain an advantage in high-SNR AWGN channels, our method offers superior robustness and perceptual quality--measured through PESQ and SDR--under noisy and multipath fading conditions, making it particularly suited for real-world wireless environments. Although STOI performance varies, our findings highlight the trade-off between bit-level accuracy and semantic preservation. Prioritizing semantic content enhances speech intelligibility and resilience, particularly in low-SNR and fading scenarios.  
This work marks an important step toward the practical deployment of semantic communication systems, providing a pathway for gradual integration with current technologies. Future research will focus on optimizing semantic encoding and decoding, exploring adaptive modulation strategies, and assessing the impact of different network topologies on overall system performance. Another promising area for future research can be to investigate federated or transfer learning methods to improve the model's ability to adapt to various speakers and languages. In addition, a further direction is to analyze the system's performance under extreme bandwidth limitations by testing its effectiveness at ultra-low bit rates. We hope that our work will provide valuable insight for the gradual transition to practical digital semantic communication technologies for future networks.  
Conceptualization, B.K.C.; methodology, B.K.C., M.Z. and E.Z.E.; software, M.Z.; validation, E.Z.E.; formal analysis, M.Z. and B.K.C.; investigation, M.Z. and B.K.C.; data curation, M.Z.; writing--original draft preparation, M.Z.; writing--review and editing, B.K.C. and E.Z.E.; visualization, M.Z.; supervision, B.K.C. and E.Z.E. All authors have read and agreed to the published version of the manuscript. This research received no external funding.  
Data are contained within the article.  
The authors declare no conflicts of interest.
# Measuring the Effect of Circular Public Procurement on Government's Environmental Impact
## 3 Results
### Exploration of Measures  
Finally, the potential effects of promising CPP criteria were explored for four product groups.  
Regarding furniture, when all tenders in 2017-2018 would have applied a longer life time of 20 instead of 10 years and refurbished 10% of their furniture instead of buying new furniture, this was estimated to result in savings of 53,000 tons of CO2 eq and 9300 tons of materials (Supplementary Materials S2) [28].  
For buildings, an example of potential measures that could be stimulated by CPP is increasing the circularity of concrete applied in new buildings. Due to the production process of concrete and the amount of concrete generally used in new buildings, it contributed largely to the material and carbon footprint of the buildings. One measure could be to replace 20% of the sand and gravel with concrete granulate. This saves material use (sand and gravel) but requires more energy than regular concrete because of the required breaking of old concrete into granulate. Another measure could be to replace CEM I cement (>95% Portland cement) with CEM III cement (up to 90% slags from blast furnaces). When these two measures are applied to the estimated yearly amount of newly built governmental buildings in the Netherlands (EIB 2019), an estimated 292 tons of CO2 eq. and 4.2 ktons of material (sand and gravel) could be saved (Supplementary Materials S2).  
In road construction, based on the estimated yearly amount of asphalt used in the Netherlands, extrapolation of the effects found in the sample indicated 24 kilotons of CO2 eq. and 300 kilotons of materials could be realized (Supplementary Materials S2). When the two identified measures of longer life and higher recycled content were applied in all road construction and maintenance work in the Netherlands, this could result in estimated GHG savings of 0.6 Mtons of CO2 eq. and 11.5 Mtons of material (Supplementary Materials S2) [28]. It must be emphasized that this is a potential estimation if 50% recycled content can be reached. This potential was based on the road area to be replaced and not the available supply of secondary material.  
For workwear, cotton is the most commonly used fiber in the Netherlands. Post-consumer recycling of cotton is challenging, however, mainly because wearing of the fabric and the mechanical recycling process itself result in shorter fibers, which are harder to spin (fine) yarn from. Other challenges are sorting collected used fabric based on fiber type, the efficient removal of zippers and buttons and recycling fiber blends. Finding technical solutions to these challenges could be stimulated by governmental organizations by actively deploying CPP criteria on recycled content. The interviewees estimated the maximum post-consumer recycled content of cotton in workwear which can presently be provided by the market to be 10%. When all governmental tenders on workwear in 2017-2018 would have used this criterium, the estimated saved GHG emissions would have been 600 tons of CO2 eq. and 190 tons of materials (Supplementary Materials S2).
## 4 Conclusions
Additionally, a pseudo-distance is estimated sequentially for a long time, which is then input to the orbit determination (OBD), enabling an estimation of the position through precise orbit estimation of geostationary orbit satellites [27], though this study only focused on point positioning using GNSS. Other studies, including [27], suggest the need for using orbit determination techniques for further research [28]. Conceptualization, G.-H.J., K.-H.K. and J.-H.W. ; methodology, G.-H.J., K.-H.K. and J.-H.W. ; software, G.-H.J. ; validation, G.-H.J. and J.-H.W. ; formal analysis, G.-H.J. ; investigation, G.-H.J. ; writing--original draft preparation, G.-H.J. ; writing--review and editing, J.-H.W. ; visualization, G.-H.J. ; supervision, J.-H.W. ; project administration, J.-H.W. All authors have read and agreed to the published version of the manuscript. This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (Grant no. 2020R1A2C2013091), and Inha University Research Center Grant (INHA-54466). The authors declare no conflict of interest.
# Alginate Silver Nanoparticles and Their Effect on Sperm Parameters of the Domestic Rabbit
## 2 Materials and Methods
### Scanning Electron Microscopy (SEM)  
Samples for electron microscope analysis were prepared by drop-coating 10 \(\mu\)L of the sample onto carbon-coated 200 mesh copper (100) grids (TAAB Laboratories, Aldermaston, Berkshire, UK). Prior to analysis, the samples underwent a coating process which involved the application of a 20 nm layer of Cr using a K575X Turbo Sputter Coater (Emitech, Ashford, UK). The morphology and size distribution of the silver nanoparticles were characterized using a high-resolution scanning electron microscope (SEM) JEOL 7550  
temperature inside the hall varies, depending on the season, from 15 \({}^{\circ}\)C to 21 \({}^{\circ}\)C. Gravity ventilation ensures regular air exchange in the room. The animals were kept in a 16L:8D lighting system, with a light intensity of 60 lux and a relative humidity of about 60-75%. In order to improve the conditions of the breeding animals, cages were used, equipped with boxes to ensure the expression of their natural behavior and environmental enrichment elements, such as teachers and high-quality meadow hay. Semen was collected on an artificial vagina after the males were prepared for semen donation. Decision No. 335/2019 of the 1 st LKE for Animal Experiments in Cracow, dated 30 October 2019.  
The collected ejaculates suspended in Ringer's liquid were separated into Eppendfors, into 4 groups: negative control (fresh semen 0 h--control 0 h and control 24 h--semen storage for 24 h without additional components), positive control, which was sodium alginate only, experimental group I and II. In groups I and II, rabbit semen was exposed to silver nanoparticles suspended in sodium alginate, but obtained with different reductants, respectively. For group I, it was xylose (AgNP AlgX), and for group II, it was sodium borohydride (AgNP AlgB). Before the exposure, dilutions of silver nanoparticles and control sodium alginate were prepared using phosphate-buffered saline (PBS, Sigma Aldrich, Poznan, Poland) to a concentration of 10 ppm. Ejaculates were mixed with the test compounds at a volume ratio of 1:1 (50 uL each), 50 uL of PBS (Sigma Aldrich, Poznan, Poland) was added to the semen in the negative control, and the semen was exposed for 24 h at room temperature.  
After exposure, analysis of sperm DNA or chromatin integrity abnormalities was carried out using an alkaline comet assay, and changes in morphological structure were assessed by eosin and nigrosin staining.
## 4 Mathematical Modeling and Analysis
### Channel and Link Distance Models  
The channel and link distance models are defined by signal power. The received signal power of CUE, \(P_{j,c}^{CUE}\), from CUE \(j\) to eNB \(c\), can be derived as follows:  
\[P_{j,c}^{CUE}=G_{j,c}^{CUE}p^{CUE}, \tag{1}\]  
where \(G_{c,j}^{CUE}=|H_{c,j}^{CUE}|^{2}\). Similarly, the received signal power of DUE-Rx from DUE-Tx \(i\) to DUE-Rx \(j\), \(P_{i,j}^{D2D}\), can be defined as follows:  
\[P_{i,j}^{D2D}=G_{i,j}^{D2D}p^{D2D}, \tag{2}\]  
where \(G_{i,j}^{D2D}=|H_{i,j}^{D2D}|^{2}\).