esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Biological Activities of Hop Compounds
### Antioxidant Activity  
Several of the compounds identified in hops and hop products have been investigated for their antioxidant properties. The antioxidant potential of hop extracts depends on various factors including the type of assay used to determine the antioxidant activity, the extraction solvent, as well as the cultivar of hop [43; 49; 56]. For example, [PERSON] et al. [56] evaluated the antioxidant potential of hop cone extracts from three different cultivars (Magnum, Lubelski, and Marynka) measured by DPPH and ABTS methods. The aqueous extracts of the three cultivars presented the highest DPPH values; however, the ethanolic extracts exhibited a higher value of antioxidant activity by the ABTS assay.  
[PERSON] et al. [2] tested the antioxidant capacity of methanolic extract from hop seeds through different in vitro assays, namely the DPPH, reducing power, \(\beta\)-carotene bleaching inhibition, and thiobarbituric acid reactive substances (TBARS) formation inhibition. This extract had a greater inhibitory effect on the generation of TBARS from the ex vivo decomposition of certain lipid peroxidation products (with an EC\({}_{50}\) value of 128 \(\upmu\)g/mL), but it exhibited the worst behavior for the \(\beta\)-carotene bleaching inhibition capacity (with an EC\({}_{50}\) value of 1330 \(\upmu\)g/mL). The latter indicates that the hop extract is less active to neutralize the linoleic hydroperoxyl radicals formed in vitro from the oxidation of linoleic acid. The authors attributed the antioxidant potential mainly to the presence of (+)-catechin and (-)-epicatechin in hop seed extract.  
In a previous study, [PERSON] et al. [57] found that ethanolic extracts of hop cones presented up to ca.5-fold more DPPH activity compared to that obtained in the leaf extracts. On the contrary, the best activity measured by the ferric reducing antioxidant power (FRAP) trial was found in the leaf extracts. In another study, [PERSON] et al. reported that the xanthohumol present in the hops showed an antioxidant activity that was 8.9 and 2.9 times higher than the reference compound 6-hydroxy-2,5,7,8-tetramethylchroman-2-carboxylic acid (TROLOX) in scavenging hydroxyl and peroxyl radicals, respectively [58].  
In a study carried out by [PERSON] et al. [59], the hydroxyl radical scavenging activity of different hops fractions (hop bitter acids, isomerized hop bitter acids, and others) was evaluated. The results indicated that all the compounds showed antioxidant potential at different levels, of which the \(\alpha\)-acids were those that exhibited a lower EC\({}_{50}\). Humulone, lupulone, and some terpen (linalool, \(\beta\)-pinene and \(\gamma\)-terpinene, \(\beta\)-farnesene) from hop essential oils have also been reported for their antioxidant potential [12].
# Data-Driven Prediction Method for Power Grid State Subjected to Heavy-Rain Hazards
## 5 Method and Materials  
The grid state can be represented by the normal state or outage state. In this study, we considered the problem of binary classification for predicting the state of the grid, as follows.  
Define a binary event, O as follows:  
\[O=\left\{\begin{array}{ll}-1;&\text{Outage state}\\ +1;&\text{Normal state}\end{array}\right.. \tag{1}\]  
A data-driven method can be used to solve the above binary classification problem. SVM models have been widely used in that field, but their model performance is dependent on a dataset. SVM always guarantees the global optimum and is less prone to overfitting than neural network models, which are also widely used [34]. Moreover, SVM could be suited to small and medium datasets. Severe weather events and power outage events occur with low probability and therefore, the used dataset in this study is a relatively smaller dataset than other application field datasets, such as image recognition and natural language. For those reasons, this study utilizes the SVM approach despite SVM not always guaranteeing the most suitable model.
# Model-Based Methods to Produce Greener Metakaolin Composite Concrete
## 2 The Strength Evaluation Model
### Verification of the Strength Evaluation Model  
The strength evaluation model was verified using experimental results from references [25; 26]. [PERSON] et al. [25] measured the reaction extent of metakaolin in a cement-metakaolin composite at 3, 7, 28, and 90 days of age. The water/binder ratio of composite paste specimens was 0.30. The degree of reaction of metakaolin was measured using selective dissolution methods. Figure 1 shows the analysis results versus experimental results of metakaolin's degree of reaction. First, we can see that as the replacement percentage of metakaolin increased from 10% to 20%, the degree of reaction of metakaolin decreased. This is because of the reduction in the alkali activation impact of calcium hydroxide [27]. Second, at 90 days old, the degree of reaction of metakaolin was about 40-50%, which was much lower than hydration degree of Portland cement. In other words, the pozzolanic reaction of metakaolin is much slower than that of cement. [PERSON] et al. [26] performed extensive experimental studies on the strength of metakaolin composite concrete. The mixtures of specimens are shown in the Table 1. In total, 24 mix  
Figure 1: Experimental versus predicted values for the degree of reaction of metakaolin. tures were used. The water/binder ratio of concrete specimens ranged from 0.45 to 0.65. The metakaolin/binder ratios of concrete specimens ranged from 0 to 25%, the curing temperature was 20 \({}^{\circ}\)C, and the ages during compressive strength measurements ranged from 1 day to 365 days. The input parameters of the hydration model are concrete mixtures and curing temperatures. Based on the mixtures shown in Table 1, the degrees of reaction of cement and metakaolin in cement-metakaolin binary composite concretes were determined. As shown in Figure 2a, for the water/binder ratio 0.65 group, after the addition of metakaolin, the improvement in the hydration extent of Portland cement was marginal. Compared with the water/binder ratio 0.65 group, the hydration degree of Portland cement in the water/binder ratio 0.45 group was slightly higher (shown in Figure 2b). This was because, compared with the water/binder ratio 0.65 group, the dilution effect from the addition of metakaolin for water/binder ratio 0.45 group was more obvious. Moreover, as the water/binder ratio decreased from 0.65 to 0.45, the hydration extent of Portland cement decreased. This was because of the shortage of capillary water for concrete specimens with lower water/binder ratios. Figure 3a,b show that, as the replacement ratio of metakaolin increases, the degree of reaction of metakaolin greatly reduces. When the water/binder ratio changes from 0.65 to 0.45, the degree of reaction of metakaolin slightly reduces. Hence, compared with the water/binder ratio, the impact of the replacement percentage on the degree of reaction of metakaolin is more significant. Moreover, based on the comparison of Figures 2 and 3, we can see the reactivity of Portland cement is much stronger than that of metakaolin.
## 3 Optical Simulation Method
Moreover, the plasmonic waveguide loss (Figure 3 shows) affects the quality factor (Q) and insertion loss (IL) of the micro-ring. The Q factor increases from 119.9 to 387 and IL decreases from \(-\)3.3 dB to \(-\)0.3 dB as the thickness of SiO\({}_{2}\) varies from 5 nm to 40 nm. The high Q factor is a key aim in many fields, such as micro-ring sensors and microring modulators, because it is sensitive to the refractive index change [20,21]. It has benefits for modulating, insofar as a slight change in refractive index would shift the resonance peak away from the aiming wavelength. Therefore, it does not consume much energy when low peak-to-peak voltage is applied. However, the side effects of the high Q factor are also obvious for two reasons. First, the high Q factor induces the micro-ring sensitivity to the temperature effects that limit its application. Second, the high Q factor impedes the minority carrier, which causes low bandwidth [2]. In this work, the plasmonic micro-ring modulator with a low Q factor is discussed to utilize its insensitivity.
## 4 Simulation Results and Analysis  
### When \(H\) and \(D_{1}\) Remain Unchanged, the Influence of \(D\) Changes the Flow Force  
When the fixed values \(H\) = 4 mm, \(D_{1}\) = 16 mm, spool opening \(x_{v}\) = 1 mm are unchanged, \(D\) changes within the range of 4-12 mm, where every 2 mm is a measuring point. As shown in Figure 4, when \(D\) changes within the range of 4-12 mm, the variation range of the force on surface 1 is very small, and the maximum difference is only 0.45 N compared with the  
Figure 3: Structural parameters of the improved spool.  
Figure 2: Improved spool compensation principle.  
unimproved spool. The direction of the force on surface 1 is vertical surface 1 to the left. This is because the liquid flow state at the left end of the spool and the spatial distribution of surface 1 are basically not affected by the change of the diameter at the right end, and the pressure on the left side remains basically unchanged. As shown in Figure 5, as the diameter of the right end decreases, the force on surface 2 gradually increases, and the force direction is negative, that is, in the spool's closing direction. This is because the diameters of the left and right ends of the spool are different, forming a certain stress area on the side surface of the spool stem, resulting in the leftward force. With decreasing diameter, the force on the surface 2 increases.  
The forces on the improved spool surface 3 and surface 4 are shown in Figure 6. The force on the surface 3 of the improved spool increases with the decrease of diameter, \(D\). This is because when \(H\) and \(D_{1}\) remain unchanged, the smaller the \(D\), the greater the included angle between surface 3 and the horizontal plane, and the greater the impact of liquid flow on plane 3, that is, the greater the force. At the same time, changing the diameter will not affect the spatial distribution of surface 4, and the impact of fluid on surface 4 will not change greatly, that is, the force on surface 4 is basically unchanged. As can be seen in Figure 6, the sum of the forces on surface 3 and surface 4 of the improved spool is greater than that on surface 3 of the unimproved spool, and it is in the positive direction. Although this improvement will increase the force on surface 2, the forces in the positive direction on surface 3 and surface 4 increases more. The resultant forces on surfaces 2, 3 and 4 of the improved spool are greater than those of the unimproved spool, and the direction of the resultant forces is positive. This resultant force is opposed to the flow force and can counteract part of the flow force. So, the resultant force compensates for the flow force and is conducive to the stability of the spool. The sums of forces on surfaces 1, 2, 3 and 4 of two sp  
Figure 4: Force on surface 1 of two spools.  
Figure 5: Force on surface 2 of two spools.
# An Improved Method Based on EEMD-LSTM to Predict Missing Measured Data of Structural Sensors
## 1 Introduction
Given the ability of EEMD to decompose the measured signal data and the powerful performance of deep learning methods in time series prediction tasks, this study not only provides a method to predict the missing data of measured signals by EEMD-based models incorporating deep learning but also provides suggestions for EEMD-LSTM models to be used for different conditions. In Section 2, the principles of the used method are described more concretely, and the relevant details of the experiments are provided in Section 3. In Section 4, the experiments and prediction results are provided for analysis. Finally, in Section 5, the conclusions regarding the different models are given.
# The CIPCA-BPNN Failure Prediction Method Based on Interval Data Compression and Dimension Reduction
## 4 Experiments Description
### Experiments
#### 4.2.2 Dimension Reduction  
We used CIPCA to carry out variable dimension reduction on the obtained flight interval data. The method is explained in Section 2.2. In addition, we compared the dimensionality reduction results of traditional PCA as a comparison. The data used by PCA were extracted from the original flight data of each sortie every 0.1 s, ensuring the consistency of the data volume with CIPCA.
# Negative Poisson's Ratio Lattice Structure with Chiral and Re-Entrant Properties
## 2 Structural Design and Methods
### Design of Re-Entrant and Chiral Structures  
To investigate the influence of geometric parameters on NPR, this study incorporated the length ratio (\(a\)/\(b\)) and the deflection angle (\(\theta\)) as variables that represented the structural geometric parameters.  
Figure 2: The schematic diagram of geometric parameters: the length of the chiral cross \(a\) (**a**), the diameter of the re-entrant circle \(b\) (**b**), the arc radius connecting the cross structure and the concave structure \(r\) (**c**) and the deflection angle \(\theta\) (**d**).  
To examine the influence of geometric parameters on the NPR phenomenon in a structure, a comprehensive set of 90 unique models, consisting of re-entrant and chiral lattice structures, were generated specifically for finite element numerical simulation. The NPR of typical representative units (as shown in Figure 3) was observed and subsequently subjected to comparison. The transverse representation is employed to illustrate structural components at different deflection angles (\(\theta\)) ranging from 0\({}^{\circ}\) to 45\({}^{\circ}\), including increments of 5\({}^{\circ}\) (i.e., 0\({}^{\circ}\), 5\({}^{\circ}\), 10\({}^{\circ}\), 15\({}^{\circ}\), 20\({}^{\circ}\), 25\({}^{\circ}\), 30\({}^{\circ}\), 35\({}^{\circ}\), 40\({}^{\circ}\), and 45\({}^{\circ}\)). On the other hand, the utilization of the vertical representation is employed to visually depict the various structural units at distinct length ratios, such as 0.237, 0.343, 0.621, 0.810, 1.046, 1.771, 2.367, 3.290, and 7.202.
# Low-Latency Bit-Accurate Architecture for Configurable Precision Floating-Point Division
## 4 General Architecture and Main Parts  
The proposed Predict-Correct algorithm can apply to both fixed-point division and floating-point division. Based on the bit-accurate Predict-Correct algorithm, this paper designs a multi-precision FP division architecture with low latency.  
In our design, take \(m=11\), \(t=3\) and \(n=3\). According to the Predict-Correct algorithm, 32 bits of new quotient can be generated per cycle. Denote a desired accuracy of quotient as _precision_, which is determined by the 2-bit input signal _type_. According to IEEE-754 standard, _precision_ and _type_ cover three FP formats: _type_ = 2'b00 and _precision_ = 23 for single precision (SP, 32 bits, 23 bits of mantissa), _type_ = 2'b01 and _precision_ = 52 for double precision (DP, 64 bits, 52 bits of mantissa), and _type_ = 2'b10 and _precision_ = 113 for quadruple precision (QP, 128 bits, 113 bits of mantissa).  
The overall architecture of our proposed FP divider is illustrated in Figure 2. The proposed design is divided into three parts. The inputs are two multi-precision FP numbers: _dividend_In_ and _divisor_In_. Part1 PRECONFIG involves pre-configuration and exception judgement of the two inputs, Part 2 MANFISSA_DIVIDE mainly fulfills 29-bit-accurate quotient approximation and subsequent 3-bit quotient selection, and Part 3 NORMALize achieves normalization.
# 108 m Underwater Wireless Optical Communication Using a 490 nm Blue VECSEL and an AOM
## 3 Experimental Details  
Figure 4a presents the schematic of the experimental setup for VECSEL-based underwater optical wireless communications using AOM and PPM modulation. Due to the laser's structure, external modulation was used in this experiment. The UWOC system was first evaluated at different received optical powers, and then tested over the 108 m long distance. The major components of the experimental setup are indicated in Figure 4b-e. All studies were conducted in a dark setting to reduce the effect of optical noise. At the transmitter side, a pseudo-random binary sequence (PRBS) generated by a Personal Computer (PC) was loaded into an arbitrary waveform generator (Tektronix AWG70002A) for digital-to-analog conversion, and the analog signals were transmitted to the driver of the AOM (250 MHz bandwidth) to perform analog modulation of the incident laser beams. A lens with a short focal length (\(f_{1}=100\) mm) was used to focus the 490 nm blue laser before it entered the AOM. The angle of incident light was adjusted to achieve the optimum diffraction intensity of the AOM, and then an aperture was used to filter out the diffracted light emitted from the AOM. Another lens with a long focal length (\(f_{2}=300\) mm) was used on the other side to collimate the laser beam to reduce its divergence. The modulated laser beam passed through a 6 m long water tank. The water channel was filled with tap water. To obtain a maximum communication distance of 108 m, reflectors were put on both sides of the water tank. On the receiver side, the output laser beam was focused by a lens onto an avalanche photodetector (Thorlabs APD210), and the APD module was used to convert the received optical signals into electrical signals. A mixed-signal oscilloscope (Tektronix MSO68B) was used for data acquisition, and then the signals were processed offline.  
Figure 3: The measured M\({}^{2}\) factor of the VECSEL.
# DARAL: A Dynamic and Adaptive Routing Algorithm for Wireless Sensor Networks
## 3 Dynamic and Adaptive Routing Algorithm (DARAL)
### Node States  
As Figure 2 shows, each node of the net can be in one of the three node states defined in \(DARAL\): _SEARCHING_, _AWATING_ and _CONNECTED_. In either _AWATING_ and _CONNECTED_ states, a node can send and receive data messages, but a VC cannot route packets as long as it is not in the _CONNECTED_ state.  
An EN only changes between two states, _SEARCHING_ and _CONNECTED_, although a VC transits the three states, but only with connection purposes. Both VCs and ENs start in the _SEARCHING_ state, and as long as they finish the execution of \(DRSP\), the EN changes to _CONNECTED_ and the VC changes to _AWATING_. In the _AWATING_ state, a VC requests a new vID for its sub-network, and once it is  
Figure 1: \(DARAL\) basic concepts.  
received, it updates its information and changes to _CONNECTED_, allowing other nodes to connect with it.  
Figure 3 shows the first process in _DARAL_, where a node _EN-A_, which is in _SEARCHING_ state, tries to connect to the network. Figures 4 and 5 show the message flow to carry it out. First of all, _EN-A_ broadcasts an _ASSOCIATION_REQ_ message. In Figure 3, the VCs from sub-networks 1 (VC-1), 2 (VC-2) and 3 (VC-3) are within its communication range, so they are receiving the _ASSOCIATION_REQ_ message. After checking the message, they proceed to answer with an _ASSOCIATION_REP_ message. _EN-A_ receives those _ASSOCIATION_REP_ from VC-1, VC-2 and VC-3 and fires the _DRSP_ algorithm (Section 3.2), in order to choose the best sub-network to join, in terms of link quality indicator (LQI). Once a sub-network is chosen and _EN-A_ selects its role, _EN-A_ changes its state to _AWAITING_ or _CONNECTED_ and sends a message to the corresponding VC, VC-2 in Figure 3, and from then on it belongs to that sub-network, i.e., sub-network 2 for this example.  
Figure 3: Example of node collecting LQIs for the link selection and role adoption process.  
Figure 2: _DARAL_ state machine.
## 7 Discussion  
The search for space in the conditions of dense urban development sets the trend for deep excavations near densely arranged objects. Additionally, the presence of underground utilities and the necessity to limit the lateral movements of the soil make it extremely difficult to properly protect such a trench. Therefore, it requires combination of geotechnical, hydrological, structural, civil engineering and waterproofing expertise. The protections are implemented with diaphragm walls, steel sheet pile walls, large-diameter struts, walls made of columns by jet routing, etc. These solutions are designed so that the protections are stable and that they limit the deformation caused by excavations to levels acceptable for neighboring buildings. To achieve this, computer simulations using the finite element method (PLAXIS 2D, MIDAS/GTS) are performed to demonstrate the behavior of these protections in terms of stress distribution and soil deformation characteristics under adjacent buildings in sensitive areas [39; 40; 41]. The model used for soil simulation is the Mohr-Coulomb model for an elastic-perfectly plastic material.  
Another important aspect of this type of construction is the optimal reinforcement and protection of the walls and foundations of existing buildings. This reinforcement can be executed, e.g., using injection, drilled and screwed micro-piles. Traditionally, temporary steel spatial frames or strut-and-beam structures are used to support the walls of existing buildings. These solutions are not optimal due to the high consumption of steel and the large space around the building, which makes construction work very difficult. The recommended solution by the authors of the article is the Push-Pull Props system (PERI, Wroclaw, Poland), which, in combination with its fastening to reinforced concrete piles, is characterized by low steel consumption, quick assembly and disassembly, and no restriction of construction works inside the building. Monitoring is a very important issue  
Figure 22: The numerical model of the supporting structure of the gable wall.  
related to the technical problems of construction near deep excavations and the ensuring of safety. Currently, the most innovative monitoring system is the hydrostatic leveling cell (HLC) system connected with a recording computer and an LTE modem for data transmission, which is used to measure the movement of structural elements. On the basis of real, continuous measurements made on-line, with the help of this system it is possible to create a database and develop accurate theoretical models of the response of existing buildings to construction works carried out nearby. The use of these models in the future will optimize the methods of protecting of existing buildings, and by introducing complete automation of deformation measurement, it will increase the safety of works.
# Evolution towards Smart and Software-Defined Internet of Things
## 2 IoT Classification and Applications
### IoT for Security Solutions  
Every industry requires security. With the advancement in edge technologies and multi-application usage, it is only evident that users demand seamless and secure access to their data and applications [36]. However, through traditional methods of securing edge and access, this user experience expectation cannot be met. It is through IoT that users can access their edge applications with the security they need in the consumer-friendly manner they desire. [PERSON] et al. in [36] propose a multi-factor authentication mechanism to address the security challenges discussed to grant reliable user-friendly access to advanced IoT applications. In a similar attempt to exploit IoT for security applications, [PERSON] et al. in [37] examine the architecture of mobile edge computing in an attempt to enhance security and efficiency in data usage.  
Security and safety are some of the very important characteristics of IoT. IoT devices communicate with each other to provide sufficient security in an environment. IoT sensors sense the surroundings and inform about the current state of the environment. This helps to prevent any unwanted events in an environment [38]. For instance, in an autonomous car, a sensor is measuring the pressure of tires so it can help to prevent the tire bursting if pressure somehow crosses a threshold. In a heavy industrial area, IoT can prevent the damage of machines by measuring their temperature. Similarly, smart wearables can monitor a harmful environment, and wireless body area networks (WBAN) can monitor the physiological parameters providing safety and security [39].