esa-sceva/satcom-chunk-collection huggingface dataset:
# Nonlinear Tank-Level Control Using Dahlin Algorithm Design and PID Control
The performance characteristics of integer order and fractional order PID controller on the current integer order plant, which obtains a minimum objective function by Nelder-Mead optimization technique is studied in [25]. Comparison of the conventional PI controller with the fractional PI (FOPI) controller is described in [11]. Linear model predictive control can be efficiently used for coupled tank system liquid-level control [5]. Experimental evaluation of the adaptive three tank-level control is described in [26]. None of the mentioned approaches for controlling the liquid level in the tank utilize the Dahlin controller [27; 28; 29; 30; 31; 32]. The Dahlin controller provides the aperiodic response of the assigned time constant. A stable, with no error, response of the desired dynamics can be achieved. Considering that the vast majority of processes, as in the case with a tank-level control system, require the achievement of aperiodic response (i.e., response without overshoot with parameters of the transient response, such as rise time, settling time, and dominant time constant, which should be as short as possible), we believe that it would be suitable for controlling the liquid level in a ship's tank. The problem with designing a Dahlin controller lies in the control signal, which can have sudden changes. This can be successfully overcome by eliminating poles with a negative real part inside the unit circle, as well as complex conjugated poles. Therefore, it was necessary to modify the Dahlin controller in order to achieve the same response but without sudden changes in the control signal. This paper aims to show that with particular simple modifications, the Dahlin controller can be very successfully applied for controlling the liquid level in a ST and CT system. The quality of the obtained performance will be shown by comparison with other classical PID controller design methods (such as Ziegler-Nichols (ZN), Takahashi (T), and Auto-tuning (AT)), and by comparison with the results reported in the literature. The remainder of the paper is organized as follows: Nonlinear mathematical models for the ST and CT systems are derived, and then methodologies are utilized to linearize the systems and controller design approaches. This is followed by the presentation of the results. Finally, the findings, prospective future work, and implications of this research are presented.
## 1 Introduction  
In order to provide a basic theory for the research of a bionic wear-resistant surface and structure, it is important to investigate the wear behavior of typical biological wear-resistant surfaces [1; 2; 3]. The Malayan pangolin (_Manis pentadactyla_) is a typical soil animal which often digs and locomotes in sand and soil to feed on prey. Pangolin has a uniquely evolved body surface, which can efficiently resist the abrasion of abrasive sand/soil due to its long period of evolution. The morphology of the pangolin surface is composed of a series of arranged scales [4; 5], which are about 3 cm long and 2 cm wide, as shown in Figure 1.  
Figure 1: The scales of pangolin (_Manis pentadactyla_).  
In general, some important wear behaviors that occur at a meso-microscopic scale are difficult to analyze using laboratory experiments [6], such as the breakaway of partial structure and the desquamation of abrasive debris. Meanwhile, the traditional method of numerical simulation, such as the Finite Element Method (FEM), cannot analyze the uneven evolvement of structure or the dynamic fracture and breakaway at the meso-scale [7]. For the nonuniform evaluation of the dynamic wear behaviors of non-smooth biological surfaces, the Discrete Element Method (DEM) can be applied to simulate and analyze injury and failure in the nonuniform area of the continuum at a meso-microscopic scale.  
DEM is a numerical simulation method which has been widely used in the non-continuous materials. However, research proves that DEM can also be used to analyze the continuous materials and structures [8]. Furthermore, DEM can reveal the mechanism of the mechanical, physical and even the chemical evaluative process of materials and structures [8]. Therefore, DEM provides a new way to study the wear evolution process of the complex biological non-smooth surface.  
In this paper, based on a geometric model of a single pangolin scale, a DEM model of the arranged scales and their wear systems were established using PFC2D\({}^{\bigotimes}\). The abrasive wear behaviors of the pangolin scale model were analyzed through a qualitative analysis of the morphology, contact bond fields, contact force chains, velocity fields, displacement fields under different velocities. Furthermore, the dynamic force and the wear rate of the wear-resistant structure were studied through quantitative analysis. In the simulation, we observed meso-microscopic scale changes due to micro-injury, fractures and debris locomotion, and further revealed the wear behavior of the biological wear-resistant body surfaces. Moreover, our analysis provides a theoretical basis for the research of bionic wear parts, so as to improve the wear performance of traditional parts and develop parts with high wear resistance, which is of great significance for saving energy, manpower and improving machine production efficiency.
## 1 Introduction
### Cathode Mechanism  
In S-ZABs, two types of electrode arrangements are available, a three-electrode system with a separate electrode for OER and ORR, or a two-electrode system that uses the same electrode for OER and ORR. The second system is more commonly used, in which the electrochemical reactions occur at the bifunctional air cathode [39; 40]. The benefits are that using a single electrocatalyst for the two reactions reduces the cost and eliminates the side effects that come with using two catalysts. The redox reaction at the cathode corresponds to the charging and discharging of the battery. In the cathode, oxygen reduction and evolution take place, which involves a series of complex electrochemical reactions, either the Langmuir-Hinshelwood (LH) or the Eley-Rideal (ER) pathway; in the first one, intermediates react on the surface, and in the second, the electrolyte reacts with the surface intermediate. Due to the lower reaction energy barrier, many researchers have theoretically studied OER and ORR based on the ER mechanism, which takes one of two reaction paths, with either two or four electrons depending on the electron transferred during the reduction of O\({}_{2}\) on the catalyst [41; 42; 43]. The four-electron transfer is the direct dissociation of an O-O bond without any byproduct, which requires more energy to dissociate O\({}_{2}\).  
Two-electron transfer dissociates O\({}_{2}\) by generating intermediate species of HO\({}_{2}\)\({}^{-}\) or H\({}_{2}\)O\({}_{2}\). Among these two, four-electron transfer is more capable because it does not spend its energy in byproduct formation.  
In an alkaline electrolyte,  
\[\mathrm{O_{2}+2H_{2}O+4e^{-}\to 4 OH^{-}\;(Four\_electron\;transfer)} \tag{7}\]  
\[\mathrm{O_{2}+H_{2}O+2e^{-}\to HO_{2}\;^{-}+OH^{-}\;(Two\_electron\;transfer)} \tag{8}\]  
\[\mathrm{H_{2}O+HO_{2}\;^{-}+2e^{-}\to 3 OH^{-}} \tag{9}\]During charging, OER occurs in which the formed hydroxyl ions give away electrons and O\({}_{2}\) forms. As in ORR, intermediates also form, such as hydroxide, oxide, and oxy-hydride. The four elementary steps of the OER mechanism are described as follows:  
\[\text{OH}^{-}+\text{M}\rightarrow\text{MOH}_{\text{ads}}+\text{e}^{-} \tag{10}\]  
\[\text{MOH}_{\text{ads}}+\text{OH}^{-}\rightarrow\text{MO}_{\text{ads}}+\text{ H}_{2}\text{O}_{\text{(I)}}+\text{e}^{-} \tag{11}\]  
\[\text{MO}_{\text{ads}}+\text{OH}^{-}\rightarrow\text{MOOH}_{\text{ads}}+\text{ e}^{-} \tag{12}\]  
\[\text{MOOH}_{\text{ads}}+\text{OH}^{-}\rightarrow\text{M}+\text{O}_{\text{2(g) }}+\text{H}_{2}\text{O}_{\text{(I)}}+\text{e}^{-} \tag{13}\]  
Figure 4a,b depicts a schematic illustration of the gas diffusion layer, the part of the air cathode at which the oxygen electrocatalysis takes place, and the OER and ORR reaction pathways of NiCo/Pyri-NG in multiple steps. The round-trip efficiency of rechargeable ZAB decreases because of the overpotential at the cathode, and the cell potential decreases as well. These complex intermediate reactions must be accelerated to achieve ZABs with commercial value.
###### Abstract
This paper proposes a UAV data-link health status prediction method based on a BN. This approach combines information about the health status of hardware devices that have different lifetime characteristics with data about links health status as affected by the environment. The degraded health status of the UAV data-link system due to hardware device performance degradation and link failure can be described by this model and provides a unified framework for the health status prediction of the UAV data-link system. The remainder of this paper is organized as follows: Section 2 provides an overview of BNs, including a summary of the concept, construction and inference algorithms used in Bayesian network models. Section 3 proposes a Bayesian network modeling method for UAV data-links that considers the networking mode and the bit error rate. In Section 4, we present a case study in which we apply our research to a type of solar-powered UAV. Finally, Section 5 provides our conclusions and future work.
## 4 Results and Discussion
### Building Technique and Population Vulnerability  
Figure 5 presents a comparative analysis of the identified characterized zones in terms of fire risk evaluation and the population potentially exposed to the risk. The analysis reveals that most buildings were constructed before 1945 and have a high or very high Fire Risk Index (Figure 5a). This high risk can be attributed to the traditional construction techniques employed in the city center. The dominant construction techniques, known as \"taipa de rodizio\" and \"taipa de fasquio\", involve using plaster as the final coating within a timber matrix, followed by the application of handmade paints. These techniques, rooted in medieval practices, have persisted over time due to their ease of implementation. The \"taipa de rodizio\" technique is primarily used for exterior and interior walls above the ground floor, while the ground floor is always constructed using granite masonry. On the other hand, the \"taipa de fasquio\" technique is also employed for exterior and interior walls above the ground floor. These walls consist of wooden planks placed vertically and nailed to a second panel of diagonally arranged planks secured with a lath known as \"fasquio\", giving the technique its name.  
The analysis also considers the potential population exposed to fire risk. (Figure 5b). It is worth noting that most of the buildings do not have regular occupants. However, among those with regular inhabitants, there is a moderate to high risk, including families  
Figure 5: Mapping of the sociodemographic vulnerability. Legend (**a**) The age of the buildings and fire risk assessment and (**b**) the number of people living in each building, number of people with a disability, and fire risk assessment.  
with three members, as well as residential buildings accommodating individuals with disabilities. This analysis underscores the vulnerability of the city center of Guimaraes in terms of fire risk and emphasizes the importance of considering sociodemographic data in understanding the potential impact of fires in the area of study.
## 3 Results  
### Biomechanical Performance  
The insertion torques of screws in the S-Cy, S-Co, S-PCo, D-Cy, D-Co, and D-PCo groups were 1.07 \(\pm\) 0.25, 1.15 \(\pm\) 0.27, 1.0 \(\pm\) 0.17, 1.4 \(\pm\) 0.35, 1.68 \(\pm\) 0.22, and 1.44 \(\pm\) 0.44 N\(\cdot\) m, respectively (Figure 4). For screws with the same shape (cylindrical, conical, or proximal-conical), insertion torque was significantly higher in the dual-thread groups than in the single-thread groups. For screws with the same thread profile (single- or dual-thread), there was no significant difference between the different screw shapes.  
A typical force-displacement curve and the mean maximum pullout strength for various screws are shown in Figures 5 and 6, respectively. The pullout forces of screws in the S-Cy, S-Co, S-PCo, D-Cy, D-Co, and D-PCo groups were 689.45 \(\pm\) 128.25, 760.08 \(\pm\) 145.03, 739.05 \(\pm\) 128.72, 911.37 \(\pm\) 132.77, 1007.99 \(\pm\) 196.1, and 939.72 \(\pm\) 160.4 N, respectively (Figure 6). For screws with the same screw shape, the ultimate pullout force was significantly higher in the dual-thread  
Figure 4: Mean maximal insertion torque for screws of various geometries. The insertion torques of screws in the S-Cy, S-Co, S-PCo, D-Cy, D-Co, and D-PCo groups were 1.07 \(\pm\) 0.25, 1.15 \(\pm\) 0.27, 1.0 \(\pm\) 0.17, 1.4 \(\pm\) 0.35, 1.68 \(\pm\) 0.22, and 1.44 \(\pm\) 0.44 Nm, respectively. For screws with the same shape, the insertion torque was significantly higher in the dual-thread groups than in the single-thread groups. For screws with the same thread profile, there was no significant difference between the different screw shapes. Groups with significant differences are indicated with the \"\(\star\)\" symbol.  
groups than in the single-thread groups. For screws with the same thread profile, there is no significant difference among different screw shapes. Dual-thread screws were proven to have better biomechanical performance than single-thread screws, and the increased percentage of insertion torque was 31% in cylindrical screws, 46% in conical screws, and 62% in proximal-conical shape screws (Figure 4). The increased percentage of pullout force from the single- to dual-thread groups was 32% in cylindrical screws, 33% in conical screws, and 27% in proximal-conical screws (Figure 6).  
Figure 5: Typical force–displacement curve for screws of various geometries. Dual-thread screws had a higher pullout force than single-thread screws.  
Figure 6: Mean maximal pullout force for screws of various geometries. For screws with the same shape, the ultimate pullout force was significantly higher in the dual-thread groups than in the single-thread groups. For the same thread profile, there was no significant difference between the different screw shapes. The increased percentage of pullout force from the single- to dual-thread groups was 32% in cylindrical screws, 33% in conical screws, and 27% in proximal-conical screws. Groups with significant differences are indicated with the \"\" symbol.
# Identification of _Bradyrhizobium elkanii_ Genes Involved in Incompatibility with _Vigna radiata_
###### Abstract  
The establishment of a root nodule symbiosis between a leguminous plant and a rhizobium requires complex molecular interactions between the two partners. Compatible interactions lead to the formation of nitrogen-fixing nodules, however, some legumes exhibit incompatibility with specific rhizobial strains and restrict nodulation by the strains. _Bradyrhizobium elkanii_ USDA61 is incompatible with mung bean (_Vigna radiata_ cv. KPS1) and soybean cultivars carrying the _RJ4_ allele. Here, we explored genetic loci in USDA61 that determine incompatibility with _V. radiata_ KPS1. We identified five novel _B. elkanii_ genes that contribute to this incompatibility. Four of these genes also control incompatibility with soybean cultivars carrying the _Rj4_ allele, suggesting that a common mechanism underlies nodulation restriction in both legumes. The fifth gene encodes a hypothetical protein that contains a _its_ box in its promoter region. The _its_ box is conserved in genes encoding the type III secretion system (T3 SS), which is known for its delivery of virulence effectors by pathogenic bacteria. These findings revealed both common and unique genes that are involved in the incompatibility of _B. elkanii_ with mung bean and soybean. Of particular interest is the novel T3 SS-related gene, which causes incompatibility specifically with mung bean cv. KPS1.  
symbiosis; nodulation; _Bradyrhizobium elkanii_; _Vigna radiata_; _Rj4_ soybean
# Analysis of Security Issues and Countermeasures for the Industrial Internet of Things
## 3 Security Issues in IIoT Systems
### Security Issue 3--Floading Attack  
In this type of attack, attackers send an extremely high volume of traffic that causes service unavailability to its users. The most common form of this type of attack is _DoS_ and _DDoS_ attacks [84]. In these attacks, attackers take control over the network and make the network traffic unavailable to the users connected to the network. These types of attacks are more vulnerable for IIoT systems because of the resource-limited nature of the IIoT devices (e.g., memory size, processing capability, or battery power). That is, these resource-constrained devices are running out of memory with unwanted information rather than holding a piece of actual information. In such cases, a compromised device can make an impact on the services of other interconnected devices for delivering dedicated performances [85].  
In a similar way to the DoS and DDoS attacks, attackers can also flood the network by the _SYN flooding_ attacks [86]. In this attack, attackers exploit the transmission and stuff the network by sending a succession of SYN requests over a long period to saturate a system's computational resource, making the system unresponsive to legitimate traffic. The SYN requests are the half-opened TCP connections that are generated by the victim's node. The fundamental of this attack is that when two nodes communicate with one anotherover the Internet's TCP, they must establish three-way handshaking before a successful communication occurs. However, in such attacks, the attackers flood the network with the SYN requests, which does not allow the other nodes to complete handshaking to make a full open connection between them. One of such significant attacks in the smart healthcare sector is the \"WannaCry\" ransomware attack [32].  
It is also possible that the attackers flood the victim's routing table to make the routing path unavailable to an authorized node within the system [87]. In such a case, the attacker node creates excessive numbers of route advertisements and channels them to the network to flood the routing table. Recall that, due to the high mobility of the IIoT systems, it is impractical to enforce a predefined routing path for them. In addition, this type of attack makes the device more vulnerable resulting in legitimate devices becoming unable to communicate with one another [88].
# The Firmware Design and Implementation Scheme for C Form-Factor Pluggable Optical Transceiver +
## 4 Evaluation and Result
### Results  
#### 4.2.1 Functional Test Result  
The results for the CFP register memory map, transmitted/received optical power during CFP operation, alarm operation according to the received optical power, data throughput for transmission/reception, and DDM accuracy are presented in this section.  
Figure 11 shows the values read from the FPGA-based CFP memory map. The addresses range from 0 \(\times\) 8000 to 0 \(\times\) 80 FF. This result shows that the MDIO interface within the FPGA block worked normally in slave mode. Moreover, the MDIO writing function of ONT equipment confirmed that the desired value could be successfully written to the CFP standard memory.  
Figure 12a,b show the transmitted and received optical power values, respectively, which are within an acceptable error range (+/\(-\)2 dB). This is the result output by the DDM function proposed in Section 3. In addition, we confirmed that the temperature, CFP transceiver voltage, and DDM values of the optical components characteristics were monitored normally. Figure 12c shows the results of blocking the optical input of the receiver to check whether the alarm was displayed according to the requirements of the standard. The received optical power was found to be \(-\)40 dBm, and the loss of signal was displayed accordingly. We also confirmed that GLB_ALRM was operating normally following the implementation of the FAWS mechanism in Section 2.  
Figure 10: Temperature Testbed Block Diagram.
# A Study on Data Profiling: Focusing on Attribute Value Quality Index
## Materials and Methods
### Research Model  
#### 2.5.1 Research Model for Data Quality Index Calculation  
This study used the numerical, date, and categorical data attributes for structured data, and text data for unstructured data in order to calculate the data quality index. In order to calculate the value quality index of the structured data, this study analyzed descriptive statistics, missing values, and outliers, and used the term frequency inverse document frequency (TF-IDF) and neural network technique Word2 vec to calculate the quality index of the unstructured data. The data profiling model using a neural network and statistical analysis (DPNS), which can calculate the data quality index, is presented in Figure 1.  
\begin{table}
\begin{tabular}{p{85.4 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Division** & **Data Quality Error Calculation** & **Attribute Extraction Using Geometric Means** \\ \hline Quality diagnosis method & In principle, data profiling is performed for all attributes, and, in some cases, target attributes are selected according to the subjective judgment of the person who performs data profiling. & Data profiling is performed targeting the attributes derived from the attribute extraction model. \\ \hline Advantages & By performing data profiling targeting all attributes, you can explore the data value characteristics of each attribute. & This can be done for attributes that possibly have errors, and only those attributes that possibly have errors can be selected depending on attribute weights. \\ \hline Disadvantages & It is inefficient because it takes a long time when there is a lot of data as it is performed for all attributes. Depending on the subjective judgment of the pattern, the data quality diagnosis result may be different. & Using the attribute extraction model, it is possible to select an attribute with a high probability of error according to the attribute weight, but it cannot determine the degree of data value quality for each attribute. \\ \hline \hline \end{tabular}
\end{table}
Table 5: Comparison of data quality diagnostic methods.  
In this study, a structured data attribute value quality index was calculated, and a data profiling target attribute was derived using the calculated attribute value quality index. In addition, the value quality index of structured data using the data attribute value quality index was calculated.