esa-sceva/satcom-chunk-collection huggingface dataset:
# Gradient-Guided and Multi-Scale Feature Network for Image Super-Resolution
## 3 Proposed Network
### Gradient Branch  
To effectively exploit the gradient features of LR images, we design a gradient branch structure. On the gradient branch, the gradient feature map of the LR image is used to estimate the one of the HR image, which is used as structural prior information to guide the super-resolution process.  
The gradient map is generally acquired through exploring the difference between adjacent pixels in the horizontal and vertical directions,  
\[\begin{array}{l}I_{x}(\mathbf{x})=I(x+1,y)-I(x-1,y)\\ I_{y}(\mathbf{x})=I(x,y+1)-I(x,y-1)\\ \
abla I(\mathbf{x})=\left(I_{x}(\mathbf{x}),I_{y}(\mathbf{x})\right)\\ G(I)=\left\|\
abla I(\mathbf{x})\right\|_{2}\end{array}, \tag{10}\]  
where \(\mathbf{x}=(x,y)\), denotes the coordinate of the pixels, \(G(\cdot)\) represents the gradient function, and \(\left\|*\right\|_{2}\) represents the second norm. Considering that the gradient map is close to zero in most regions of an image, it facilitates CNN to pay more attention to explore the spatial relationship of the image structure, thereby estimating an approximate gradient map for the SR image.  
As shown in Figure 1, several intermediate-level features on the trunk branch are sequentially propagated to the gradient branch, so the output of the gradient branch not only contains the image structure features, but also contains abundant detail and texture features. Such a design method is not only effectively supervised to recover the gradient map, but also significantly reduces the number of parameters of the gradient branch. At the same time, since the gradient map is able to directly reveal whether a particular region of the image is sharp or smooth, we fuse the gradient features obtained from the gradient branch to the features on the trunk branch to guide the super-resolution process. Specifically, in our network, the features from the 5 th, 10 th, 15 th, and 20 th modules in the trunk branch are propagated to the gradient branch, and then the gradient features obtained by the gradient branch are integrated into the trunk branch.
## Abstract  
Exposure assessment is a crucial part in studying potential effects of RF-EMF. Using data from the HERMES study on adolescents, we developed an integrative exposure surrogate combining near-field and far-field RF-EMF exposure in a single brain and whole-body exposure measure. Contributions from far-field sources were modelled by propagation modelling and multivariable regression modelling using personal measurements. Contributions from near-field sources were assessed from both, questionnaires and mobile phone operator records. Mean cumulative brain and whole-body doses were 1559.7 mJ/kg and 339.9 mJ/kg per day, respectively. 98.4% of the brain dose originated from near-field sources, mainly from GSM mobile phone calls (93.1%) and from DECT phone calls (4.8%). Main contributors to the whole-body dose were GSM mobile phone calls (69.0%), use of computer, laptop and tablet connected to WLAN (12.2%) and data traffic on the mobile phone via WLAN (6.5%). The exposure from mobile phone base stations contributed 1.8% to the whole-body dose, while uplink exposure from other people's mobile phones contributed 3.6%. In conclusion, the proposed approach is considered useful to combine near-field and far-field exposure to an integrative exposure surrogate for exposure assessment in epidemiologic studies. However, substantial uncertainties remain about exposure contributionsfrom various near-field and far-field sources.  
Keywords:exposure assessment; RF-EMF; mobile phone; adolescents; dose calculation +
Footnote †: journal: Journal of Environmental Research
# Challenges of PBFT-Inspired Consensus for Blockchain and Enhancements over Neo dBFT
## 2 Background
### Message Delivery  
Most works consider an _asynchronous scenario_, where messages are delayed, but will eventually arrive. This way, previous works argue that _guaranteed delivery of messages_ can be achieved by replaying messages, as a way to circumvent (P.1), a strategy that we will call \(\overline{(P.1)}\).  
In practice, there is no central authority or absolute control over the P2P network (including its software), so it is very hard to guarantee that certain properties hold, including \(\overline{(P.1)}\). Software bugs and upgrades on different clients (at different times) may generate unexpected behavior, leading to eventual message loss and temporary disruption of the P2P channel. These disruptive events may also be caused by external decisions related to off-chain governance and the incentive model for the network.  
This way, a well designed and healthy decentralized network can guarantee _at least_ that messages are _almost always_ delivered, with the exception of extremely rare events (where it can eventually halt), which we call \(\overline{(P.1)}\). In our perspective, this modeling is a better approximation of a public decentralized blockchain ecosystem. This path is also in line with decisions of public blockchain projects, such as Neo, that do not expose the public IPs of consensus nodes, nor connect them directly (thus they depend on a healthy network to be able to communicate).  
Therefore, in this work, we will explore alternative models to deal with (P.1), namely \(\widetilde{(P.1)}\) and \(\overline{(P.1)}\). This may not be a good approach to devise correctness proofs, yet it is useful to argue for pros and cons of existing consensus models.
## 2 Materials and Methods
### Data Analysis  
Statistical analysis was performed using the STATISTICA 10 (StatSoft) computer program. To verify the normality of the data the Shapiro-Wilk test was used. Because normality tests failed to confirm that all the parameters variables studied had normal distribution (most probable reason for not normal distribution in footballers group was the small number of participants), all variables were analyzed with non-parametric statistics--the Mann-Whitney U-test--for differences between groups. Statistically significant changes were those with a statistical significance level of \(p<0.05\).
###### Abstract  
One of the food industry's greatest challenges is to find natural ingredients capable of conferring antioxidant and color properties. In addition, the agri-food industry generates by-products that are often treated as waste, despite their abundance of phytochemicals that can be recovered and used as food ingredients. This study explores the potential of elderberry pomace, an industrial by-product of juice processing rich in anthocyanins and polyphenols, as a natural food additive in blueberry sorbet. Elderberry pomace was incorporated into the sorbet formulation in powder form or as aqueous extracts at two different concentrations. The analysis of the pomace extract by UHPLC-DAD-MS showed the presence of four anthocyanins: cyanidin-3,5-O-dialglucoside, cyanidin-3-O-sandubioside-5-O-glucoside, cyanidin-3-O-sandubioside, and cyanidin-3-O-glycoside. The physicochemical properties of the sorbet s such as pH, \({}^{\circ}\)Brix, overrun, melting rate, and color were evaluated, as well as their levels of total phenolic compounds, total monomeric anthocyanins, and in vitro antioxidant activity. The potential of sorbet s to stimulate the growth of probiotic bacteria was evaluated and a sensory analysis was conducted to assess consumer acceptance. Results indicated that the sorbet containing the more concentrated extract presented higher overrun, faster melting rate, higher contents of phenolic compounds and anthocyanins, and higher antioxidant activity compared to the control. Additionally, this formulation showed a darker hue (lower \(L^{\star}\) value) and a tendency to stimulate probiotic bacteria. Moreover, the sorbet s with pomace in their composition had good consumer acceptability. These findings highlight the potential of elderberry pomace to be used as a natural, sustainable ingredient in the ice cream industry, aligning with growing consumer trends towards healthier and eco-friendly products.  
elderberry; by-product; polyphenols; anthocyanins; recovery; sorbet; antioxidant; color; sensory properties +
Footnote †: journal: applied sciences
# Assessing the Performance of the Multi-Beam Echo-Sounder Bathymetric Uncertainty Prediction Model
## 5 Conclusions
Accounting for these considerations, however, requires knowledge of the pulse shape, speed of the array at reception, and transmission of the signal and sediment characteristics, which might not be always available. * Based on the insights obtained by accounting for the contribution of the baseline decorrelation and Doppler effect, one can conclude that the good model-data agreement obtained without accounting for these contributions might have been a coincidence. This occurred as a consequence of accounting for the baseline decorrelation in an approximate manner and discarding the contribution of the Doppler effect; for the situations considered here, it was found that the contributions of the baseline decorrelation when accounting for the pulse shape and Doppler effect counteracted each other. However, for a different environmental condition, survey configuration, or pulse shape, this might not occur. Consequently, not accounting for these contributions in the uncertainty prediction model can lead to incorrect predictions. * Overall, this paper showed that the current capabilities of modeling the MBES bathymmetric uncertainties in a computationally efficient way (error propagation) provided estimates that were in good agreement with those obtained experimentally. Conceptualization, T.H.M. ; data curation, T.H.M. ; methodology, T.H.M. and M.S. ; software, T.H.M. ; investigation, T.H.M. ; writing, original draft preparation, T.H.M. ; writing, review and editing, T.H.M., M.S., and D.G.S. ; visualization, T.H.M. ; supervision, M.S. and D.G.S. ; funding acquisition M.S. and D.G.S. All authors read and agreed to the published version of the manuscript  
This investigation is part of research funded by the Ministry of Infrastructure and Water management of The Netherlands, Rijkswatersstaat, The Netherlands. The authors would like to thank the Ministry of Infrastructure and Water Management of the Netherlands (Rijkswatersstaat) for data acquisition and for providing measurements equipment. The authors would like to specifically thank [PERSON] for supporting the data acquisition. The authors declare no conflict of interest.
## 3 Results Analysis and Optimization
### Analysis of the Response Surface  
In order to intuitively analyze the relationship between test factors and indexes, the response surface diagram was obtained using Design-Expert software together with the multifactor test data. The response surface is shown in Figure 7.  
Figure 7a shows the interaction between disc cutter thickness and disc cutter rotation speed on the maximum cutting force when the feeding speed and edge angle are at an intermediate level. It can be concluded from Figure 7a that when the disc cutter rotation speed is lower, the maximum cutting force increases notably with the increase in the disc cutter thickness. However, when the disc cutter rotation speed is higher, this trend is relatively gentle. As the thickness of the disc cutter increases, the fiber undergoes elastic-plastic recovery and squeezes the disc cutter, which leads to greater cutting surface resistance and an increase in the maximum cutting force of the disc cutter. When the disc cutter rotation speed is low, the castor stalk only partially produces sufficient elastic-plastic deformation. Therefore, the friction force of the disc cutter caused by the elastic-plastic deformation is larger, and the maximum cutting force significantly increased. When the disc cutter rotation speed is high, the stalk is cut at one time and there is less local elastic-plastic deformation. The failure process tends to be a one-time fracture, and the maximum cutting force increases slowly.  
According to the correlation regression equation and the density of contour distribution in the response surface, the maximum cutting force is influenced by the interaction between the edge angle and the feeding speed, as shown in Figure 7b. When the edge angle is small, the maximum cutting force decreases significantly with increased feeding speed. When the edge angle is large, the maximum cutting force increases slowly and then flattens out as the feeding speed increases. The main reason for this is that the smaller cutting angle usually results in higher local stress, which makes it easier to break the stalk fiber, and the maximum cutting force is, therefore, smaller. The sliding-cutting angle is negatively correlated with the cutting resistance. With a small edge angle, a faster feeding speed causes a notable increase in the sliding-cutting angle and the maximum cutting force decreases. When the edge angle is larger, the physical structure resistance of the cutting  
Figure 7: Response surface of the maximum cutting force. (**a**) Interaction factors of disc cutter rotation speed and thickness; And (**b**) interaction factors of edge angle and feeding speed.  
edge is larger, and the increase in the sliding-cutting angle is insignificant, resulting in a nonsignificant increase in the maximum cutting force.
## 3 Results and Discussion
### In Vitro Antiproliferative Activity Assay
values obtained by maceration were 16.55 \(\pm\) 0.58 and 17.95 \(\pm\) 0.58 \(\upmu\)g/mL, respectively, which were slightly lower than those obtained with the Soxhlet extract MDA-MB-231; 19.93 \(\pm\) 0.74 \(\upmu\)g/mL and MCF-7; 20.22 \(\pm\) 0.89 \(\upmu\)g/mL. Regarding prostate cancer cells 22 RV1 and LnCap, the IC\({}_{50}\) values obtained by the maceration extract (22 RV1: 11.75 \(\pm\) 0.35 \(\upmu\)g/mL; LnCap: 11.91 \(\pm\) 0.54 \(\upmu\)g/mL) were also lower than those obtained with Soxhlet (22 RV1: 13.47 \(\pm\) 0.52 \(\upmu\)g/mL; LnCap: 19.64 \(\pm\) 1.05 \(\upmu\)g/mL). Therefore, we can confirm that our extract of _B. hispanica_ possesses an important anti-proliferative activity against different cancerous cell lines. These results agree with those reported in the literature, which showed that genus _Berberis_ contained tamarixetin, rutin, and caffe acid, all known for their cytotoxic effects against cancer cell lines including HeLa cells with IC\({}_{50}\) > 100 \(\upmu\)g/mL. Moreover, the alkaloid extract from indigenous species to Algeria induced cell death and morphological changes [13; 19].
# Deep Learning for Medical Image Cryptography: A Comprehensive Review
## 3 Vulnerability of Deep Learning-Based Medical Image Analysis
### Adversarial Attacks against Medical Images  
In this section, we list some of the most popular adversarial strategies that have been suggested for use against medical images. Deep learning model architectures are used to execute various tasks on medical pictures while analyzing a variety of adversarial threats. Systems for medical imaging that rely on deep learning are seriously at risk from these types of attacks. A \"White Box Attack\" is one in which the attacker has knowledge of the architecture and parameters of the underlying model. On the other hand, the attack is referred to as a \"Black Box Attack\" if the attacker does not have access to the deployed model architecture. Additionally, \"Untargeted Adversarial Attacks\" are those that just want the implemented model to be confused and forecast the incorrect class. \"Targeted Adversarial Attacks\", on the other hand, are those that force the model to forecast a (false) desired output. In this review, the following adversarial attacks from recently released research publications are analyzed:
## 2 Related Work
### Deep Learning
#### 2.2.2 U-Net  
Our approach for extracting edge features uses an improved FCN model, U-net [20] model. U-net model consists of symmetric contracting path and expansive path, so it is characterized by the U-shaped architecture.  
U-net model consists of a series of kernels acting as filters to map out particular features of the input image. It has two main components [33]: A \"down\" component and an \"up\" component. The former one is applied to detect desired features of the images in progressively smaller layers, during which pooling layers are used for each convolutional layer to down-sample the output. The latter one is used for up-sampling the output of the previous layer. To reconstruct output images, the last convolutional layer concatenated the previous layer with the same size as the input images [34]. During the \"up\" component, the detailed global features of the convolutional layer and the contextual information of the previous layer are combined together, which are then fed to the next convolutional layers. U-net has attained promising results in biomedical image segmentation [32; 35], building extraction [36; 37] and road network extraction from aerial imagery [33; 38].  
U-net combines low-resolution information (providing object-based identification) and high-resolution information (providing segmentation-based identification), so it is ideal for extracting perceptual features of HRRS images for generating perceptual hash sequences. In this study, we use an improved U-net model with a novel training sample generation method to extract the robust edge feature of HRRS images.
# CFD-Simulink Modeling of the Inflatable Solar Dryer for Drying Paddy Rice
## 3 Results  
### CFD Simulations  
#### 3.1.1 Simulation of the Airflow Distribution  
The simulation of the airflow pattern in the inflatable solar dryer (ISD) is shown in Figure 7, where the airflow direction travels from left to right. Figure 7a shows the vortex caused by the fans located at the inlet. The vortex covers the first meters of the ISD, where the air velocity is the highest (Figure 7b). Furthermore, the airflow in the drying area forms a transition zone, where the airflow presents an even distribution over the paddy rice. However, backflow was observed one meter before exiting the dryer. The turbulence model \(k\)-\(e\) predicted the presence of the air turbulence in the area located at 3 to 4 m from the fans well, creating a recirculation pattern.
## 1 Introduction  
Different connection methods are used for modular structures depending on the main materials that the modules are composed of, their shape, and the method of load transfer. In the research conducted by [PERSON] et al. [1], steel was the main module material, and box type frames with columns and beams were the conventional module shapes. [PERSON] et al. [2] described stacking modules to fabricate low-rise buildings, with stabilization systems such as braces added for medium-rise buildings, and lateral force-resisting systems (such as concrete cores or reinforcement frames) used for high-rise buildings. For steel-framed buildings, the lateral force has to be resisted as well as the gravitational load, and the number of stacked modules is limited if there is no separate lateral force-resisting system.  
Because the behavior of connections in steel frame structures can affect the distribution of member forces and deformation shapes, connection behavior is considered significant in analysis and design. Generally, connection behavior can be evaluated in terms of strength, stiffness, and deformation capability. Connections can be the weakest components, and thus may determine the bearing strength capacity of the structural system. Hence, connections are considered important components [3].  
In modular structures, the overall structural system is composed of units that are interconnected or connected to separate lateral force-resisting systems. Therefore, the beam-column connection used to construct a unit has to be able to transfer the gravitational load onto the slab. In the case of low-rise structures where the lateral load is resisted only by the modular units, sufficient lateral stiffness is necessary so that the internal forces of an individual member can be exerted. Connections between modular units that make up the entire framing system should have sufficient strength capacity and stiffness to transfer the lateral force to the surrounding modules and guarantee the stability of the entire structure.  
In conventional modular systems, rectangular tubes or channels are generally used for the columns, and channels are used for beam members [4; 5]. However, in current systems, although the specifications of connections between units can vary depending on the scope of the module interior and exterior, as well as the construction error [5], modular units are generally connected using bolts [6; 7; 8; 9], interlocking devices [10; 11; 12], and steel plate welding [13]. However, these methods are not technically or practically suitable for all types of modular buildings, such as high-rise modular buildings.  
Here, we describe a novel technology for connecting modular units that can ensure the safety of modular structures. In this study, connections using straight and cross-shaped metal connectors between modules that use rectangular tubular columns and channel beams are proposed. Their structural performance, in terms of strength, stiffness, and deformation capability, is evaluated through cyclic loading tests by controlling the story drift angle of the modular units in both the width and longitudinal directions.
## 3 Related Work
### Sink Nodes  
The sink node broadcasts, at every \(s\) seconds, to the network _PHE_ messages, which will be forwarded and used by U-sensors to determine the next hop to the sink. When the sink node receives beacon signals from an AUV, it initiates negotiation with the AUV to determine the channel for data transmission, the transmission rate, and the modulation scheme. Then, the sink node receives the aggregated data from the AUV using the negotiated short-range/high-rate channel. The sink node also receives data from U-sensors that have generated the data or are relaying data generated by other U-sensors. A sink node discards PHE messages from GWs. It is worth noting that AURP can be readily extended for an architecture with multiple sink nodes.
# High Efficiency Continuous-Variable Quantum Key Distribution Based on ATSC 3.0 LDPC Codes
## 5 Conclusions  
In conclusion, we combined a multidimensional reconciliation protocol with our proposed LDPC codes based on ATSC LDPC codes. Generally, for a CVQKD system, we needed to improve the reconciliation efficiency in order to achieve higher performances of secret key rate and transmission distance. In this paper, our aim was to maximize reconciliation efficiency \(\beta\) for a given FER. The simulation results showed that ATSC LDPC codes can achieve high reconciliation efficiency, which resulted in good performance of secret key rate and transmission distance. Furthermore, the SC-LDPC codes and QC-LDPC codes that we constructed can further improve the performance of reconciliation efficiency, which resulted  
Figure 10: Final secret key rate as a function of transmission distance.  
Figure 9: FER values corresponding to ATSC LDPC codes and proposed spatially coupled (SC)-LDPC codes, QC-LDPC codes for different SNRs under the (**Left**) code rates \(R=2/15\) and (**Right**) \(R=5/15\), respectively.  
in better performance of final secret key rate and longer transmission distance. The efficiency of our proposed codes can reach up to 0.96.  
[PERSON]-[PERSON] proposed the new construction method; [PERSON] calculated the transmission distance; [PERSON] analyzed channel capacity; [PERSON] performed the simulations; [PERSON] designed the simulations and wrote the paper. All authors have read and agreed to the published version of the manuscript.  
This work was supported by Shanghai Municipal Science and Technology Major Project (grant number 2019 SHZDZX01), the National Natural Science Foundation of Shanghai (20 ZR1400700), the State Key Laboratory of Advanced Optical Communication Systems and Networks China and also supported by the Fundamental Research Funds for the Central Universities and Graduate Student Innovation Fund of Donghua University (CUSF-DH-D-2020084).  
The authors declare no conflict of interest.