esa-sceva/satcom-chunk-collection huggingface dataset:
# Efficient LDPC Encoder Design for IoT-Type Devices
## 7 Discussion  
The ECC-encoding procedure presented in this paper is devoted to error protection in IoT node devices constructed with microcontroller-type equipment and without strict throughput requirements, but with the energy efficiency being an important factor. We showed that QC-LDPC codes, which are usually considered for high-throughput communication systems and advanced protocols can also be considered for these types of computationally constrained devices. We provided Richardson-Urbanke LDPC encoding expressed for QC-LDPC codes, and we showed how the encoding can be decomposed into elementary operations that are suitable for implementation in a simple microcontroller device.  
The whole encoding algorithm was implemented and verified for a few QC-LDPC parity-check matrices. Comparisons with other known block codes (RS and BCH) are also provided, showing that the memory requirements are not greater than for standard block codes, while the achievable throughput is increased and the encoding time is reduced, which enables the energy consumption reduction. At the same time, the error-correction performance of LDPC codes is significantly better than for standard block codes. This provides the potential for the reduction in the energy consumption of the communication links used to connect IoT nodes with IoT gateways.  
Conceptualization, [PERSON] and W.S.; methodology, [PERSON] and W.S.; software, [PERSON]; validation, [PERSON], W.S., W.I., L.D. and W.F.; experimental investigation, [PERSON], W.S., W.I., L.D. and W.F.; data acquisition, [PERSON], [PERSON], [PERSON], L.D. and W.F.; writing, [PERSON], [PERSON], [PERSON], L.D. and W.F.; supervision, [PERSON] All authors have read and agreed to the published version of the manuscript.  
This research was co-financed by the Ministry of Education and Science of Poland under grant No. DWD/3/7/2019 as well as SUBB.  
Not applicable.  
The authors declare no conflict of interest.
# Low-Cost Goethite Nanorods for As (III) and Se (VI) Removal from Water
## 4 Conclusions  
Uniform \(\alpha\)-FeOOH NRs resembling cigar-like nanostructures (\(\sim\)40 nm diameters) were synthesized by a simple hydrolysis method that does not use any toxic chemicals. The proposed synthesis method is easy, rapid, and scalable. The phase structure of \(\alpha\)-FeOOH was verified by XRD, SAED, and Raman spectroscopy. Also, surface properties of \(\alpha\)-FeOOH were studied by FTIR and zeta potential  
Figure 7: X-ray diffractograms of \(\alpha\)-FeOOH nanorods after regeneration experiments.  
measurements as a function of pH and found that the zero charges point was observed at pH\({}_{\text{p2c}}\) = 5.2. The obtained \(\alpha\)-_FeOOH_ NRs was used as an efficient adsorbent for As(III) and Se(VI) from water. The analysis of the dose study shows that 0.4 g/L of \(\alpha\)-_FeOOH_ NRs are an optimum dose for the removal of \(\sim\)500 \(\mu\)g/L of As(III) and Se(VI). Additionally, \(\alpha\)-_FeOOH_ NRs exhibited rapid adsorption kinetics in less than 1 h even at higher dilution (8300 \(\mu\)g/L). The maximum adsorption capacities of \(\alpha\)-_FeOOH_ adsorbent (which is calculated using Langmuir isotherm) for As(III) and Se(VI) were estimated at 8.23 and 4.75 mg/g, respectively. The adsorption capacity of \(\alpha\)-_FeOOH_ (Dose 1 g/L) was experimentally verified by performing kinetic experiments at As(III) and Se(VI) concentrations of \(\sim\)8300 \(\mu\)g/L and the results showed 99.3% and 84% removal in 1 h contact time, respectively. The adsorption measurements elucidated that the adsorption of As(III) and Se(VI) to the \(\alpha\)-_FeOOH_ NRs is rapid and monolayer in nature. Finally, \(\alpha\)-_FeOOH_ polymorph is a potential excellent adsorbent owing to its scalable and easy synthesis, insolubility in water, low-toxicity, and cost-effective material.  
Conceptualization, M.A.A., M.Z.R.; data curation, M.A.A., T.M.K.; formal analysis, M.A.A. and A.M.G., A.E.R.; investigation, M.A.A., A.E.R.; methodology, M.A.A., A.E.R.; resources, M.A.A., M.Z.R.; software, M.A.A., A.M.G., M.Z.R.; supervision, M.A.A.; validation, M.A.A., T.M.K.; visualization, M.A.A., A.M.G., M.Z.R., T.M.K.; writing--original draft, M.A.A. and A.M.G.; writing--review and editing, A.E.R., M.Z.R., T.M.K. All authors have read and agreed to the published version of the manuscript. The authors extend their appreciation to the Deanship of Scientific Research at King Saud University for funding this work through research group No (RG-1439-008).  
There are no conflicts of interest to disclose.
###### Abstract
In addition, we conduct plenty of simulation experiments using synthetic DAG, analyze the convergence curves of each strategy, and discuss the time delay and energy consumption when the number of tasks and the communication to calculation ratio are different, which correspond to the characteristics of real applications. The results show that the proposed method outperforms other comparison algorithms in dynamic MEC scenarios.
###### Abstract  
This work details a technique tailored to the analysis of complex radome structures based on the non-overlapping separation of two different domains: antenna and radome. Both domains are analyzed isolated using the method of moments with the multilevel fast multipole algorithm (MoM-MLFMA) for the antenna domain and a modified characteristic basis function method with the multilevel fast multipole algorithm approach for the radome domain. An iterative procedure is then applied to compute the effect of each domain over the complementary domain. This approach usually converges into a few iterations, yielding very good results and significant efficiency improvements with respect to other efficient approaches such as a full-wave MoM-MLFMA analysis of the full problem. A realistic test case is included, considering a radome with an embedded frequency selective structure on one of its interfaces. The results show a very good agreement considering only three iterations between domains, requiring only one-third of the CPU-time needed by the conventional approach.  
radome; macro basis functions; method of moments; electromagnetic analysis +
Footnote †: journal: _electronics_  
0000-0001-8296-339X/0000-00001-8296-3
## 6 Cellular Basis of Laser-driven Radiation Therapy
### Oxygen Effect and Dose Rate  
We briefly consider here the cell and its environment, as opposed to the isolated cell of the preceding sections. The presence of oxygen is known to enhance cell lethality by a factor of about 3 for low LET radiation [106]. This enhancement is probably due to the fact that DNA radicals readily react with oxygen to generate biologically relevant DNA damage [107]. At ultra-high dose rates (\(\sim\)10\({}^{9}\) Gy/second or more) for low LET radiation this oxygen effect is evident in hypoxic tissue, as several Gy dose levels deplete the oxygen level at such dose rates. Although oxygen is easily accessible to single monolayer cells, oxygen recovery to regions of diffusion-related hypoxia, which are often observed in a relatively small proportion of tumor tissues, can require significant time (several seconds for tissues having distances of more than 100 \(\upmu\)m from a tumor blood vessel) [106]. This means that the efficiency of cell inactivation in a tumor needs to be optimized or improved with the mode of irradiation featuring breaks (brief time intervals with no irradiation) of adequate duration (\(\sim\)seconds) such that all cells in a tissue are accessible to oxygen.  
We suggest that this important oxygen effect also needs to be studied with laser-driven moderate LET (proton) irradiation, since the dose required to deplete oxygen is unknown and could be different with low LET irradiation. In contrast we note that high LET irradiation exhibits no such oxygen effect. Lethality enhancement due to the presence of oxygen rapidly diminishes if the LET exceeds \(\sim\)60 KeV/micron [90]. This is possibly attributed to the decomposition of water with high ionization density or an effect of the increased clustering of lesions.
# Experimental Validation of a Gyroscope Wave Energy Converter for Autonomous Underwater Vehicles
## 5 Parametric Analysis
### Wave Period  
The analysis in Sections 3 and 5.1 concludes that the output of the system is maximum when the system frequency is the same as the wave frequency. However, in the hardware design of this paper, GWEC is solidly connected to the experimental platform, which means GWEC obtains the maximum response of the simulation platform under any circumstances. Therefore, the performance of GWEC under different wave cycles can be observed by changing the platform motion cycle.  
Figure 11 shows the influence of the wave period on the system when the GWEC obtains the complete response to the wave amplitude. The increase in the wave period can only increase the maximum precession angular displacement slightly. Although a small wave period can obtain an ideal power output, it will produce a huge peak voltage and torque for the system, which will cause a shock to the system and significantly increase the hardware requirements and experimental costs of the platform. Therefore, too small a wave period is not suitable for wave energy generation, even if the system can fully respond to waves. A larger wave period reduces the system demand but also reduces the output power, so there is a trade-off between wave period and system output to determine a suitable system frequency according to the ocean conditions.
# YOLOv5-Sewer: Lightweight Sewer Defect Detection Model
## 2 YOLOv5-Sewer Network Design
### YOLOv5-Sewer Network Architecture
#### 2.2.1 Lightweight Network  
In the traditional YOLOv5 series [30], the backbone utilizes the complex CSPDarknet53 network structure, which significantly increases the computational load of the model, resulting in slower detection speeds. This limitation poses challenges to the practical applicability of the model, particularly in on-site computing devices, where deploying large and intricate models for sewer defect detection can be problematic.  
To address this issue, the proposed YOLOv5-Sewer model opts for a more lightweight backbone structure, utilizing MobileNetV3 block stacking. This choice aims to reduce the computing and memory requirements during training, albeit with a slight decrease in mean Average Precision (mAP). The MobileNet block, constituting the backbone, consists of three main components. Firstly, the input undergoes a \(1\times 1\) ordinary convolution to increase the dimensionality. Subsequently, depth-wise separable convolutions with different kernel sizes (\(3\times 3\) or \(5\times 5\)) are applied. Finally, a \(1\times 1\) ordinary convolution reduces the dimensionality for the output. This inverted residual structure helps to maintain the correlation between the input and output, and the low-dimensional features are extended to high-dimensional ones by depth-wise separable convolutions. The incorporation of a non-linear activation function enhances the interaction capabilities among channels, contributing to an efficient and lightweight backbone structure for sewer defect detection.  
As illustrated in Figure 2, MobileNetV3 incorporates the Squeeze and Excitation Network (SENet) [31] after depth-wise separable convolutions. This integration allows for the adjustment of the weights in different channels, facilitating a focused emphasis on relevant channels. Additionally, to enhance the model's computation speed, some swish activation functions are replaced with hard swish activation functions.  
The introduction of the Squeeze and Excitation Network enhances the adaptability of the MobileNetV3 backbone by enabling the model to dynamically adjust its focus on relevant channels, thereby improving its ability to capture important features. Moreover, the substitution of the swish activation functions with hard swish contributes to faster  
Figure 1: The framework of the YOLOv5-Sewer model.  
model computation. The combined effect of these enhancements results in a significantly advantageous and lightweight MobileNetV3 backbone for sewer defect detection. This lightweight design proves beneficial, particularly in environments with limited computational resources, making the proposed model well suited for deployment in scenarios where the computing capabilities are constrained.
## 3 Results and Discussion
### Determination of the Antimicrobial Activity
Because they present a wide diversity of components, the possibility of synergistic action among chemical species found in red propolisis, such as vestitol, neovestitol, isoliquiritigenin and galagin (not tested in this study), cannot be ruled out as a potential explanation for its antimicrobial activity [108, 109, 110, 111, 112, 113]. However, [PERSON] et al. [33] identified the correlation between antimicrobial activity against _S. aureus_ and _P. aeruginosa_ and the flavonoid for  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Sample**} & \multicolumn{2}{c}{_Staphylococcus aureus_\({}^{1}\)} & \multicolumn{2}{c}{_Escherichia coli_\({}^{2}\)} \\ \cline{2-5}  & **MIC** & **MBC** & **MIC** & **MBC** \\ \hline E:UT & 11 & 750 & 46 & 187 \\ E:25\(-\)10 & 6 & \(>\)1000 & 46 & 93 \\ E:25\(-\)20 & 11 & \(>\)1000 & 93 & 187 \\ E:25\(-\)30 & 11 & \(>\)1000 & 23 & 93 \\ E:50\(-\)10 & 23 & 23 & 93 & 750 \\ E:50\(-\)20 & 11 & 11 & 46 & \(>\)1000 \\ E:50\(-\)30 & 23 & 23 & 93 & \(>\)mononetin present in the ethanolic extracts of Brazilian red propolis originated in the state of Pernambuco. The MIC values for red propolis extracts are reported in different studies, with variations between 3.8 and 100 \(\upmu\)g\(\cdot\)mL\({}^{-1}\) for _S. aureus_[14, 21, 113] and between 6.3 and \(>\)1000 \(\upmu\)g\(\cdot\)mL\({}^{-1}\) for _E. coli_[48, 114]; propolis is thus considered to be a strong antibacterial agent based on the classification by [PERSON] et al. [78]. The influence of the extraction method on the antimicrobial activity and the potential of the red propolis extracts from Alagoas was also demonstrated by other studies in our research group [41, 48]. It is also noteworthy that different authors have reported the influence of seasonality on the antimicrobial activity of propolis, which makes studies using samples from the same region even more relevant [115, 116, 117]. Therefore, the antimicrobial data for the samples of red propolis extracts analyzed here propose that these extracts present a relevant potential action against foodborne microorganisms, and they may thus constitute an important preservative to add to food formulations [118, 119, 120, 121]. [PERSON] et al. [122] demonstrated the potential effect of propolis when it is applied in the food and pharmaceutical industries, owing to the antimicrobial effect presented by this matrix against some bacteria and fungi of interest in drugs and foods. For example, [PERSON] et al. [123] demonstrated the positive effect of red propolis as a food additive through oral administration in sheep, which resulted in improved biochemical parameters. It is noteworthy that among the biological properties of red propolis, its antimicrobial activity has the highest relevance, which means this work can provide support to clarify this potential application.
# Uni-Planar MIMO Antenna for Sub-6 GHz 5G Mobile Phone Applications
## 1 Introduction
The MIMO antenna offers 13 dB of isolation between array elements, with a gain of 4 dBi and an antenna efficiency of more than 40%. In [15], an integrated MIMO antenna system for LTE and millimeter-wave frequency bands was designed. The designed antenna structure comprised two elements for LTE communications and four elements for 5G millimeter-wave communication. A modified rectangular radiator was utilized for both frequency bands. In addition, defects in the ground plane were introduced using rectangular and circular shapes. The designed antenna element provides resonance for the 5.5 GHz frequency band. A uni-planar sub-6 GHz MIMO loop antenna array was developed in [16]. The antenna antennas were organized in such a way so that they could offer both polarization and pattern diversity. Furthermore, the improvement in isolation was achieved by designing an arrow-shaped strip between the antenna elements. In [17; 18], the authors designed a co-planar waveguide (CPW)-fed MIMO antenna array for sub-6 GHz applications. For the design, an L-shaped and T-shaped radiation elements were selected. By utilizing CPW technique, an isolation of \(>\)15 dB was achieved in the band of interest. The abovementioned MIMO antennas have some limitations in terms of non-planar configurations, large size, and complex structures. In addition, these antennas suffer due to low radiation efficiency, which ultimately leads to poor antenna gain. To accommodate the drawbacks of previously published designs, this research presents a four-element uni-planar MIMO antenna system for 5G smartphone applications. For a single antenna, a loop-shaped element is chosen. The radiation elements are arranged at each corner of the PCB, which follows the principle of pattern diversity and makes room for other smartphonecomponents. The results show that the designed MIMO antenna offers wideband response in the 3.5 GHz frequency band. The intended MIMO topology has low mutual coupling between antennas, resulting in a low envelope correlation coefficient (ECC) and high diversity gain (DG). Moreover, the proposed MIMO antenna offers an efficiency of \(>\)90%.
## 2 Literature Review and Theoretical Foundation
### Antecedents to Information Disclosure
#### 2.2.3 Information Disclosure  
Customer information disclosure originates from the idea of _self-disclosure_ in the psychology literature, which is defined as \"any information about [oneself] which Person A communicates verbally to a Person B\" [63] (p. 73). Information disclosure online can happen implicitly or explicitly [64]. On the one hand, data can be collected indirectly through the use of cookies, location data, and many other means. On the other hand, data can also be gathered directly by asking users for their information [65].  
People's disclosures are known to be multidimensional [66] meaning disclosures can be broken down into distinct elements and analyzed in different ways. Some of these factors include the number of words used to answer or the use of emotional vocabulary in the response [17; 67]. One of the simplest ways to assess disclosure is through the use of two simple axes: the _breadth_ and the _depth_ of the disclosure [68]. Breadth refers to the number of disclosure instances, while depth refers to the sensitivity of each disclosure. [PERSON] et al.'s [68] research found two proxy measures to evaluate these axes. Allowing users to leave a question unanswered permits measuring the breadth of disclosure and the \"inclusion of items of varying sensitivity\" measures the depth of disclosure [68] (p. 2168).  
Disclosure in the context of chatbots has mostly been studied for social bots and mental health conversational agents [60; 69; 70]. On the contrary, user disclosure to chatbots used as recommendation agents in an e-commerce context has been under-investigated. To better understand how information disclosure happens in online communication exchanges, two phenomena are presented below.
## 4 Results and Discussions
### Effect of Pile Inclinations
#### 4.1.3 Earth Pressure  
Figure 12 sketches the non-dimensional earth pressure profiles acting on the piles of different pile inclinations. For the case of \(p=34.375\) kPa, the maximum non-dimensional earth pressure would increase from 0.01 to 0.12, while the pile inclination varies from \(-20^{\circ}\) to \(+20^{\circ}\); as to the case of \(p=84.375\) kPa, the maximum non-dimensional earth pressure would increase from 0.05 to 0.42, while the pile inclination varies from \(-20^{\circ}\) to \(+20^{\circ}\). That is, the earth pressure on vertical piles is the intermedial of three types of piles rather than the limits. This characteristic is different from that of the pile deflection and bending moment, and the difference can be first interpreted by the greater stress transfer onto the pile because of the closer embankment-pile distance and then the additional self-weight of soil overlying the positive battered pile.  
The earth pressures on these piles would all increase first and then decrease, and almost all the maximum earth pressure would appear at \(z_{\rm{a}}=0.5\). Moreover, the earth pressures on the negative battered piles decrease to zero near \(z_{\rm{a}}=1.25\), whereas those of the positive battered piles are close to zero near \(z_{\rm{a}}=1.5\). The common downtrend is attributed to the increased distances between a point of the pile and the surcharge with the depth. The greater depth of zero-earth pressure in the cases of positive battered piles can be interpreted by the greater overlying soil self-weight of the pile and the closer distance from the embankment when the pile tip of the positive battered pile is approaching the embankment. The elevated location of the zero-earth pressure with a shortened affected length of earth pressure on the piles indicates that the effect of embankment on the pile is greatly minimized for the negative battered piles.
## 2 CFD Model Setup and Validation
### Numerical Model  
The Reynolds-Averaged Navier-Stokes (RANS) equations are employed to resolve the flow field around the thrusters. For incompressible Newtonian fluids, the continuity and momentum equations are given as  
\[\frac{\partial u_{i}}{\partial x_{i}}=0\text{ and } \tag{1}\]  
\[\rho\left(\frac{\partial u_{i}}{\partial t}+u_{j}\frac{\partial u_{i}}{ \partial x_{j}}\right)=-\frac{\partial p}{\partial x_{i}}+\frac{\partial}{ \partial x_{j}}\left[\mu\left(\frac{\partial u_{i}}{\partial x_{j}}+\frac{ \partial u_{j}}{\partial x_{i}}\right)\right]+\frac{\partial}{\partial x_{j}} \left(-\rho\overline{u_{i}^{\prime}u_{j}^{\prime}}\right), \tag{2}\]  
where \(\rho\) is the fluid density, \(u_{i}\) (\(i=1,\,2,\,3\), representing the component in the \(x,\,y,\,z\) direction) is the mean velocity component, \(t\) is the flow time, \(p\) is the pressure, \(\mu\) is the dynamic viscosity, and \(-\rho\overline{u_{i}^{\prime}u_{j}^{\prime}}\) is the Reynolds stress term.  
The direct modeling of the Reynolds stress is based on the Boussinesq hypothesis, which assumes the Reynolds stress to be a linear function of the mean velocity gradients [12]. For incompressible Newtonian flows, the Reynolds stress is calculated as  
\[-\rho\overline{u_{i}^{\prime}u_{j}^{\prime}}=\mu_{t}\left(\frac{\partial u_{i }}{\partial x_{j}}+\frac{\partial u_{j}}{\partial x_{i}}\right)-\frac{2}{3}pk \delta_{ij} \tag{3}\]  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Parameter** & **Unit** & **Value** \\ \hline Number of blades & - & 4 \\ Blade diameter & m & 0.25 \\ Blade area ratio & - & 0.7 \\ Blade pitch ratio & - & 1.0 \\ Duct type & - & 19A \\ Propeller type & - & Ka \\ \hline \hline \end{tabular}
\end{table}
Table 1: Geometric details for the ducted propeller and the RDT used in this study.  
Figure 2: Geometrical models of (**a**) the ducted propeller and (**b**) the RDT.  
where \(\mu_{t}\) is the turbulent eddy viscosity and \(\delta_{ij}\) is the Kronecker symbol.  
To complete the set of equations, the SST \(k\)-\(\omega\) turbulence model developed by [PERSON] (1973) is adopted, as the SST \(k\)-\(\omega\) model takes advantage of both the \(k\)-\(\omega\) model in a robust near-wall treatment due to the simple low Reynolds number formulation and the ability to compute flows with moderate adverse pressure gradients, and the \(k\)-\(\epsilon\) model in a better performance near the boundary layer edge and away from the walls because of its insensitivity to the free stream values. In this model, two additional transport equations are solved for the turbulent kinetic energy, \(k\), and the specific turbulent dissipation rate, \(\omega\). These equations are solved together with Equations (1) and (2) using the commercial software ANSYS Fluent.