esa-sceva/satcom-chunk-collection huggingface dataset:
# An Assessment of the Impact of Gypsum Deposit Development on Changes in the Radiation Environment
## 3 Results and Discussions
### Bottom Sediments
#### 3.2.1 Activity Concentrations of Radionuclides in River Sediments
The anthropogenic contribution is mainly associated with the disintegration of rocks and soil cover during mining operations (see Figure 1) and the subsequent transfer of dissolved uranium to bottom sediments. The isotopes \({}^{232}\)Th and \({}^{40}\)K weakly correlate with each other (r = 0.52, \(p\) = 0.16). The correlation of \({}^{232}\)Th and potassium is approximately of the same order (r = 0.48, \(p\) = 0.12). In addition, a connection is observed between \({}^{40}\)K and the fraction of the grain size distribution 45-100 \(\mu\) (r = 0.50, \(p\) = 0.14). This may reflect the lithogenic nature of these isotopes. Potassium is one of the main rock-forming elements, second in average (clarke) content in clayey deposits (2.7%) only to silicon, aluminum and iron [61]. In carbonate minerals, its content is ten times lower. However, the isotopic content of \({}^{40}\)K is very low and amounts to 0.0117% [61,62]. That is, the content of \({}^{40}\)K in clays and carbonates is about 3.16 and 0.316 mg kg\({}^{-1}\), respectively. The average concentrations of thorium in clays and carbonates are 12 and 1.7 mg kg\({}^{-1}\), respectively [61], with an isotopic content of \({}^{232}\)Th of 99.98% [62,63]. In dissolved form, the \({}^{232}\)Th concentrations in surface waters in the study area did not exceed 0.02 \(\mu\)g L\({}^{-1}\). The average concentration of potassium was 1.2 mg L\({}^{-1}\) (Table S1); that is, the concentrations of \({}^{40}\)K, taking into account the isotopic content of 0.0117%, were about 0.14 \(\mu\)g L\({}^{-1}\). This may indicate the transport and precipitation of these isotopes mainly as part of mechanical suspensions. For radium-226, only a weak correlation can be noted with Pb (r = 0.54, \(p\) = 0.11), the \(\leq\)45 \(\mu\) fraction (r = 0.47, \(p\) = 0.17), OM (r = 0.45, \(p\) = 0.19) and \({}^{137}\)Cs (r = 0.42, \(p\) = 0.23). This indicates the isolated nature of \({}^{226}\)Ra. It is a consequence of the radioactive decay of uranium isotopes, but its relationship with uranium isotopes and chemical elements correlating with uranium is weak. This is explained by the low migration capacity of radium compared with uranium. Being an analogue of alkaline earth elements, especially calcium and barium [48], it actively precipitates as RaSO\({}_{4}\) in the sulfate-rich environment of gypsum deposits. This is also indicated by the weak correlation with Pb, fraction \(\leq\) 45 \(\mu\), OM and \({}^{137}\)Cs.
# The Current Development of Structural Health Monitoring for Bridges: A Review
## 2 Monitoring Technology  
During the service life of bridges, unfavorable status changes often occur due to internal structural characteristics and external environmental effects, which pose safety hazards. Failure to detect these unfavorable changes in a timely manner may lead to catastrophic consequences and result in a significant loss of life and property. BHM systems use a large number of sensors installed at optimal positions on a bridge through reasonable methods [10,11], to monitor and provide feedback on its structural response, structural defects, and external environment in real-time. For cracks, peeling, deformation, rusting, and other structural issues, image-based methods are used for detection [12, 13, 14]. In this section, current research hotspots in sensor systems and computer vision-based monitoring methods will be reviewed.
# Heat Transfer Enhancement of Falling Film Evaporation on a Horizontal Tube by Thermal Spray Coating
## 2 Experimental Apparatus and Methods
### Tested Tubes  
Details of the test section are shown in Figure 2. The test section was a copper tube with an outer diameter of 19.05 mm and a length of 50 mm; it was heated by a cartridge heater inserted along the center axis. The heating length of the heater was equal to that of the test section, and the input power was measured by a wattmeter. The outer wall temperature of the test tube was measured by T-type thermocouples placed at the bottom, to avoid disturbances to the falling liquid film. A constanta wire with a diameter of 0.1 mm was soldered on the surface of the tube at each measurement point.  
In this study, a thermal spray coating was applied to the heat transfer surface for heat transfer enhancement. First, the surface of the test tube was sandblasted, and then melted copper was sprayed. Microphotographs of the thermal spray coating are shown in Figure 3. The coating was formed using an arc wire spraying method in the open air. The top view showed the rough surface formed by the sprayed molten drops. The average surface roughness measured by a laser microscope was 20.6 \(\upmu\)m. In the cross-sectional view, the bright orange area was the base material, and the brown area on the base material was the coating layer. Microscale cavities were observed on the inner and outer surfaces of the coating.  
Figure 1: Schematic of the experimental apparatus.  
Figure 2: Details of the test section.  
The heat transfer coefficient was measured using HFC-134a as the working fluid at a saturation temperature of 20 \({}^{\circ}\)C with a set pressure of 0.57 MPa. The film Reynolds number was varied from 214 to 673, and the heat flux was varied from 15 to 85 kW\(\cdot\)m\({}^{-2}\). The subcooling degree was maintained within 0.5 K for the falling film evaporation experiments. The evaporation and boiling behavior on the test section was observed from the horizontal direction during the experiments.
## 3 Results and Discussion
### Juice
#### 3.2.5 Content of Betalain Pigments in Juice  
Table 2 presents the content of betalain pigments (betanin and vulgaxanthin) in the raw beetroots and juices. The beetroots that were not pretreated with a PEF (B0) were characterized by a pigment content of 778 mg betanin/100 g solids and 261 mg vulgaxanthin/100 g solids, and the obtained results showed that the use of PEF treatment significantly increased the betalain content. This concurs well with previous findings of [PERSON] et al. [16], who conducted research on the PEF's influence on beetroots' bioactive compounds. In the case of betanins, no effect of the number of applied pulses on the extractability was observed, while in the case of vulgaxanthins, increasing the number of electric pulses resulted in a better extraction of these pigments. These findings confirm that the PEF increased the cell membrane permeability as a result of electroporation.  
Generally, the highest content of betalain pigments among all the tested samples was noted in juices (betanins: 2615-2867 mg/100 g solids, vulgaxanthin: 743-878 mg/100 g solids). Variants J1 and J2 were characterized by a higher content of pigments than the untreated variant J0. As stated before, PEF treatment increased the extractability of pigments from the vegetable tissue.
# Efficient Wheel-Rail Stick-Slip Numerical Modeling for Railway Traction Vehicles
## 2 Materials and Methods
### Mode Selection  
The static friction force acts as a function of the applied forces on the object (denoted by \(\Sigma F\)). It essentially counteracts these forces, resulting in a net force of zero. When the magnitude of the applied forces surpasses a certain threshold value, motion initiates. At this exact moment, the static friction force reaches its maximum value, \(F_{sMax}\), and acts in a direction that directly opposes \(\Sigma F\). To prevent the friction force from exceeding a certain threshold (\(F_{sMax}\)), an additional condition needs to be introduced. This supplementary  
Figure 2: A non-smooth friction law for rolling contacts.  
condition also facilitates the numerical determination of the transition point from stick to slip during the computation process.  
\[F_{f}\in\left\{\begin{array}{c}F_{s}(t,v)\text{sign}(v),\text{ if }|v|>\eta\\ \sum F,\text{ if }|v|\leq\eta\text{ and }|\sum F|\leq F_{sMax}\\ F_{sMax}\text{sign}(\sum F),\text{ if }|v|\leq\eta\text{ and }|\sum F|>F_{sMax} \end{array}\right. \tag{3}\]  
The friction law illustrated in Figure 2 can be mathematically represented by the set-valued function in Equation (3). The static friction force can assume any value within a specific set while the absolute relative velocity remains less than \(\eta\). However, for most practical applications, these multi-valued laws are used alongside equations of motion governing dynamical systems, typically leading to a unique solution for the static friction value (when \(\Sigma F\) is determined).  
While the transition from stick to slip only occurs when the maximum static friction force (\(F_{sMax}\)) is reached, the transition from slip to stick exhibits a different behavior. During this transition, when the relative velocity reaches values below \(\eta\), the force value can abruptly drop from \(F_{sMax}\) to any value within the set \([-F_{sMax},F_{sMax}]\). This discontinuity occurs at the point \((\,|\,v\,|=\eta)\) and the hysteretic characteristic in the interval \([-\eta,\eta]\)[40]. As explained above, the numerical approach in this paper equivalates the point \(v=0\) with the interval \([-\eta,\eta]\).
# Reversible Data Hiding Scheme in Homomorphic Encrypted Image Based on EC-EG
## 3 Proposed Scheme
### Data Hiding  
The data hider first scrambles the extra information with the hidden key \(k_{2}\). Then, it groups the scrambled additional data \(w\), and each group has n bits, which is recorded as \(w_{0},w_{1},\cdots,w_{n-1}\). From this, the decimal value of each dataset can be calculated as:  
\[S_{w}=\sum_{i=0}^{n-1}w_{i}\times 2^{i},(S_{w}=0,1,\cdots,2^{n}-1) \tag{19}\]  
Figure 4: Image partition and self-reversible embedding.  
To enhance confidentiality, the data hider can choose a random integer \(r_{S_{w}}(r_{S_{w}}<n)\) for each \(S_{w}\) and encrypt it with EC-EG to get the ciphertext \(C_{S_{w}}\).  
\[M(c_{S_{w}})=(r_{S_{w}}G,M(S_{w})+r_{S_{w}}pk) \tag{20}\]  
According to the method of room reserving, the encrypted image is divided into non-overlapping \(A_{E},B_{E},C_{E}\). The data hider embeds additional data into the encrypted domain as following:  
\[\begin{split} M(c_{t}^{{}^{\prime\prime}})&=M(c_{ t}^{\prime})+M(c_{S_{w}})\\ &=(r_{t}G,M(t^{\prime})+r_{t}pk)+(r_{S_{w}}G,M(S_{w})+r_{S_{w}}pk) \\ &=M(t^{\prime})+r_{t}pk+M(S_{w})+r_{S_{w}}pk-skr_{t}G-skr_{S_{w}}G \\ &=M(t^{\prime})+M(S_{w})\end{split} \tag{21}\]  
Among them, \(c_{t}^{{}^{\prime\prime}}\) is the encrypted target pixel with hidden data. Suppose that a group contains 3 bits of data, which are \(n=3,(w_{0}w_{1}w_{2})=(100)\). Then, we can calculate \(S_{w}=1,c_{S_{w}}=E(1,r_{S_{w}})\). As shown in Figure 4(e), the data hider performs homomorphic addition in ciphertexts to embed 3 bits  
Figure 5: \(n=3\) is used as an example to illustrate the program flow.  
of additional data into the corresponding \(MCC[c_{t}^{\prime}=E(160,r_{r}),c_{r}=E(160,r_{r})]\), and then obtains the corresponding \(c_{t}^{{}^{\prime\prime}}=E(161,r_{S_{w}}+r_{r})\).
## 1 Introduction
### Contribution  
This work aims to address the challenge of energy management and decision-making under the high penetration of distributed RES and the application of large scale IoT devices in next-generation DN. Firstly, a fog-cloud hierarchical architecture is proposed for energy management and decision-making. With the generated large-scale data in DN, AI technologies deployed separately in fog and cloud layers can capture the usage of customers and the RES output. Moreover, various stakeholders in the distribution system, including common customers, prosumers, and distribution system operator (DSO) are modeled, and the user's electricity consumption behavior is captured with the concept of microeconomics. Finally, the validity of the proposed method is demonstrated through retail electricity price optimization and real-time revenue management of various stakeholders in the DN. The rest of the paper is organized as follows. Section 2 proposes the cloud-fog hierarchical architecture for the energy management of a DN, where the underlying structure, and the function of fog/cloud layers are introduced. The model for normal customers, prosumers and distribution system operators (DSOs) is established in Section 3. The verification conducted is implemented in Section 4, where AI technologies are embedded into the fog and cloud layers to implement the energy management and decision-making processes. At the fog layer, the aims mainly include the prediction of the user's electricity usage behavior and RES output; at the cloud layer, optimization of the calculation for a given target takes place. In addition, a utility and revenue model for normal users, prosumers, and DSO in a regional DN is established to achieve maximum goal optimization with full social welfare simulation.
# CeRA-eSP: Code-Expanded Random Access to Enhance Success Probability of Massive MTC
## 5 Performance Evaluation
### Simulation Results
#### 5.2.3 Trade-Off Analysis between Preamble Transmission Rate and Random Access Rate  
Figure 9 shows the RA step performance for the various RA schemes. The baseline and ACB and BO schemes utilized fewer preamble sequences than allocable PUSCH resources; therefore, the preamble transmission success rate and RA success rate had the same value as mentioned previously. As shown in Figure 9a, the legacy CeRA method achieved the highest preamble transmission success rate. This is because legacy CeRA utilized the largest preamble codeword set. The ACB and BO method showed a higher preamble transmission success rate than the proposed CeRA-eSP method when the number of devices was less than \(N=70,000\). This is because the ACB and BO method maintained the number of access devices in one RAO by utilizing the barring rate. As the access intensity increased, the ACB and BO scheme converged to a preamble transmission success rate similar to the baseline because of the limited number of preamble sequences. The proposed CeRA-eSP method utilized the preamble codeword, which is an expanded form of the preamble sequence; thus, it showed a higher preamble transmission success rate than the ACB and BO method in high-access-intensity situations.  
In Figure 9b, it can be seen that the proposed CeRA-eSP method achieved the highest RA success rate in all cases. The baseline and ACB and BO methods degraded RA performance owing to the high collision problem. The legacy CeRA method degraded RA performance owing to the codeword ambiguity problem, which was caused by a large preamble codeword set of 2916. The proposed CeRA-eSP method achieved the highest RA success rate by considering the preamble collision, codeword utilization, and PUSCH timeout rates. Therefore, the legacy CeRA scheme consumed PUSCH resources in a phantom codeword and achieved less than a 60% RA success rate, whereas the proposed CeRA-eSP method achieved the highest RA success rate. Even in the high-access-intensity situation of \(N=150,000\), the proposed CeRA-eSP method achieved an RA success rate of 25%.  
Figure 8: (**a**) Number of Successful preamble transmissions and (**b**) Number of successful random accesses.
## 4 Conclusions  
The new method of \"dry\" aerosol jet printing, including the synthesis of nanoparticles by spark discharge, has prospects in the production of printed electronics products due to the absence of the need to prepare nano-ink, the simplicity, and versatility of the spectrum of the obtained nanomaterials (metals and their oxides, semiconductors and carbon). In this work, we have demonstrated the compatibility of this method with substrates made of various inorganic materials, such as alumina, borosilicate glass, and silicon. It was found that the broadening effect of the formed lines on various substrates practically does not appear in comparison with traditional approaches of \"wet\" printing. Depending on the conditions of post-printed heat treatment, both metallic and semiconducting (gas-sensitive) microstructures based on copper nanoparticles can be easily obtained. Sintering of copper oxide nanoparticles begins at the temperature of 450 \({}^{\circ}\)C in hydrogen atmosphere with the shrinkage of 45-60%. Copper lines based on spherical nanoparticles show a low electrical resistivity of 5 \(\upmu\Omega\)-cm after reduction sintering at 550 \({}^{\circ}\)C for 60 min. In turn, semiconductor micro-structures based on unsintered agglomerates of oxidized copper have a fairly high sensitivity to NH\({}_{3}\) and CO. Response of the sensor fabricated based on non-sintered oxidized copper nanoparticles to ammonia and carbon monoxide concentration of 40 ppm is about 20% and 80%, respectively.  
Conceptualization, A.A.E.; methodology, D.V.K. and A.I.B.; investigation, E.I.K., N.B.P., A.V.N., and A.E.V.; data curation, A.I.B., D.V.K., and P.V.A.; writing--original draft preparation, D.V.K.; writing--review and editing, A.A.E.; visualization, A.A.L.; project administration, A.A.E. and V.V.I. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the Russian Science Foundation (project no. 19-79-00375).  
Not applicable.  
The data presented in this study are available upon request from the corresponding author.  
The authors declare no conflict of interest.
###### Abstract  
The principle of image super-resolution reconstruction (SR) is to pass one or more low-resolution (LR) images through information processing technology to obtain the final high-resolution (HR) image. Convolutional neural networks (CNN) have achieved better results than traditional methods in the process of an image super-resolution reconstruction. However, if the number of neural network layers is increased blindly, it will cause a significant increase in the amount of calculation, increase the difficulty of training the network, and cause the loss of image details. Therefore, in this paper, we use a novel and effective image super-resolution reconstruction technique via fast global and local residual learning model (FGRLR). The principle is to directly train a low-resolution small image on a neural network without enlarging it. This will effectively reduce the amount of calculation. In addition, the stacked local residual block (LRB) structure is used for non-linear mapping, which can effectively overcome the problem of image degradation. After extracting features, use \(1\times 1\) convolution to perform dimensional compression, and expand the dimensions after non-linear mapping, which can reduce the calculation amount of the model. In the reconstruction layer, deconvolution is used to enlarge the image to the required size. This also reduces the number of parameters. We use skip connections to use low-resolution information for reconstructing high-resolution images. Experimental results show that the algorithm can effectively shorten the running time without affecting the quality of image restoration.  
super-resolution; convolutional neural network; fast global local residual learning network; local residual block; skip-connection; deconvolution +
Footnote †: journal: Applied Physics Letters B
# True Random Number Generator Based on Fibonacci-Galois Ring Oscillators for FPGA
## 3 True Random Number Generators Design and Evaluation on FPGA Technology
### FiGaRO RNG Design
#### 3.3.1 Health Tests  
In every entropy source, the statistical quality of the output must be continuously tested to check if significant deviations are taking place, due to changed environmental conditions, electric fields or side-channel attacks. To avoid situations where the entropy is too low, it is mandatory to quickly diagnose a possible fault, inhibiting the output until the quality is restored. As recommended by NIST in [29], two on-line health tests are needed for an entropy source: the repetition count test and the adaptive proportion test, which are described in the following.  
The repetition count test triggers an alarm if the same output value is maintained too many times in a row. To perform this test, a rate of false probability \(\alpha\) must be chosen: the higher is this rate, the lower number of repetitions will trigger the alarm. Once chosen \(\alpha\), the number of repetitions which trigger an alarm is given by this formula:  
\[n=1+\left\lceil\frac{-log_{2}(\alpha)}{H}\right\rceil \tag{17}\]  
A hardware that implements this test for binary sources is proposed hereafter: a shift register continuously acquires the outputs of the entropy source and additional logic checks if shift register's parallel output is made up by only ones or only zeros. This implementation is depicted in Figure 14.  
Figure 13: Histograms of the first run and of the second run of acquisitions for the FiGaRO TRNG.  
The adaptive proportion test is built to check if the frequency of occurrence of every possible output value falls within a certain confidence interval. If an output occurs too much frequently, it means that the statistical quality of the randomness source is lowered and an alarm should be triggered. For binary outputs, the test must be performed on a window of 1024 samples. The number of ones must be counted and compared to two different values: if the count of ones exceeds a cut-off value \(C\) or is lower than \((1024-C)\) an alarm should be raised. Cut-off values are indicated by NIST as a function of the bitstream entropy. Again, a hardware implementation, depicted in Figure 15 of this test is proposed. A shift register of 1024 bit maintains the memory of the last output values and whenever a new value comes in, its value is summed into an accumulator register, while the last value is subtracted. By doing so, the accumulator always maintains the count of the number of ones inside the observation window and two comparators can check if the frequency lies inside the upper and lower thresholds.
###### Abstract
Generally, routing protocols are categorized into two main classes: proactive and reactive. The proactive routing is a table-driven routing protocol. All nodes store information of each route in the network and network topology changes as the changes in the status of the network occur. This results in low latency because nodes already know where a packet must be forwarded based on routing information stored, hence the forwarding delay is short. On the other hand, the reactive routing protocols find the route on demand by sending many request packets, which results in huge acoustic delays because of the low speed of sound, and this makes the reactive protocols not appropriate for UWSNs [3]. One of the most important undesired effect in UWSNs, is the node death due to improper consumption of energy which is usually caused by inappropriate or inefficient selection of routing. Thus, to address this, the need of an energy efficient routing protocols is of extreme necessity. The main criteria to choose a routing protocol are based on how to select the forwarding node. This node selection process depends on several factors such as distance, number of hops, residual energy, etc. In this work, the problem of energy efficiency in routing protocols in underwater acoustic communication networks is addressed. A routing algorithm is proposed that improves the energy efficiency of a previous work [4]. The principle of operation of the new algorithm chooses the forwarding node by fuzzy logic interference. As the unknown structure of the network topology, a wide set of rules has been envisaged and implemented inside the core of the fuzzy decision. The results will demonstrate and quantify the pursued objective: decreasing in the average energy consumption of the network. The paper is structured in six different sections. Section 2 contains the state-of-the-art. Section 3 describes the system model considering network 3D model, propagation, and energy consumption model. Section 4 explains detailed operation of proposed protocol, followed by Section 5 in which performance results are presented. Finally, a detailed discussion on the purpose and performance of the proposed protocol is found in Section 6.