esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Materials and Methods
### Air Pollutant Levels and Meteorological Conditions  
The concentrations of PM\({}_{2.5}\), PM\({}_{10}\), and NO\({}_{2}\) were obtained from Air Korea (www.airkorea.or.kr/web) [36], and all data were applied to the Korea Registry of Environment (KMOE)'s Quality Assurance/Quality Control (QA/QC) procedure. There are 25 and 15 The Air Quality Monitoring Stations (AQMS) in Seoul and Daegu, respectively (Figure 2). We obtained the air pollutant levels on an hourly basis and calculated the daily and weekly averages to compare them to the previous three years (2017-2019). In this study, air pollution levels were analyzed for a total of 18 weeks. Observations were made from January 1, 2020, until May 5, when social distancing (SD) was implemented.  
In addition, we evaluated the AQI to efficiently access air quality related to health concerns. The AQI is widely used as a tool to easily communicate how polluted the air currently is and the level of health effects on the public. The AQI was classified into six categories and expressed in colors representing different levels of health concern. The AQI of the air pollutants was calculated as interpolation Equation (1) [37]:  
\[I=\ \frac{I_{high}-I_{low}}{C_{high}-C_{low}}*(C-\ C_{low})+I_{low} \tag{1}\]  
where  
I: Air Quality Index  
C: pollutant concentration  
C: the concentration breakpoint \(\leq C\)  
C: the concentration breakpoint \(\geq C\)  
I:\(I_{low}\): the index breakpoint corresponding to \(C_{low}\)  
I:\(I_{high}\): the index breakpoint corresponding to C_{high  
Figure 2: Location of Seoul (left) and Daegu (right) in Korea. Red dots indicate the location of the air quality monitoring stations (AQMS).  
Meteorological conditions including precipitation, wind speed, temperature, and humidity were analyzed through open data available on the Korea Meteorological Administration website [38]. As shown in Table S1, no significant differences were observed between the previous three years and 2020 in meteorological conditions.  
To analyze the wind speed and direction of Northeast Asia including Korea, 'ERA5 monthly averaged data on single levels' provided by the European Centre for Medium-Range Weather Forecasts (ECMWF) [39] was used to investigate speed and wind direction in the East Asian region from January to March 2020. Using this data, we made a wind map in meters per second by using ArcGIS 10.6 at a height of 100 m above the surface of the Earth.
# When Intelligent Transportation Systems Sensing Meets Edge Computing: Vision and Challenges
## 2 Intelligent Transportation Systems (ITS)
### Information Communication and Control  
There are two purposes of information communication: (1) gathering information to support decision making and (2) disseminating the decisions and control strategies to devices and road users. Traditional communication relies a lot on wired communication. Actuated traffic signal control collects vehicle arrival data from loop detectors underneath the roadway surface and pedestrian signal data via push button at intersections [68]. This information is gathered through wires into the signal controller cabinet, which is usually located at the roadside near an intersection. A similar communication method is for ramp metering control at freeway entrances [69]. Loop detectors are located underneath the freeway mainstream lanes and sometimes also underneath ramp lanes and they communicate with the cabinet through wire [70]. Using an Ethernet cable is another common method for wired communication for ITS. It can either connect devices to the Internet or serves as media for local communication, such as video streaming [71]. Controller Area Network (CAN bus) is a standard vehicle bus designed for microcontrollercommunications without a host computer [72], which enables the parts within vehicles to communicate with each other. Wired communication through CAN is an important way to test vehicle onboard innovations and solutions in ITS studies.  
Wireless communication has been widely used in different applications, thanks to the rapid development of general communication technologies. Probe vehicle data can be available in real-time through vehicle-cloud communications. Companies, such as INRIX [73], and Wejo [74], have such connected vehicle data, such as trajectories and driver events, given their good connections to the vehicle OEMs. Similar vehicle and traffic data are available via devices other than the vehicle itself, such as smartphones, to provide real-time information for drivers via phone apps, such as Google Maps and Waze [75]. A connected vehicle, in many other scenarios, refers to not only vehicle-cloud communication but also vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), and even vehicle-to-everything (V2X) [76]. Dedicated Short Range Communication (DSRC) was a standard communication protocol for V2X application [77]; however, recently, C-V2X has been proposed as a new communication protocol with the emergence of 5G for high bandwidth, low latency, and highly reliable communication among a broad range of devices in ITS [78]. Information, such as variable speed limit via control strategy, work zone information, and real-time travel time, can be disseminated via variable message signs on the roadways in Advanced Traffic Management System (ATMS) and Advanced Traveler Information System (ATIS), from traffic management centers to road users [79; 80].
## 4 Discussion
### Identification of Main Fluorophores in Arbutus, Inula and Alfafla Honey, and Forest Honeydew  
Inula and alfalfa honeys are rare in Italy, however, a few local productions are known in Tuscany. Arbutus (or strawberry tree) honey is more common in Sardinia (Italy) and the chemical composition of arbutus honey from this region was reported in the literature [45]. Forest honeydew is produced in several area of Italy, but Tuscan forest honeydew was never studied before. All these samples are characterized by low intensity of fluorescence when excited at \(\lambda_{\text{ex}}\) < 300 nm (see Figure 2) and this aspect is evident from the low intensity of band (**I**) in the synchronous spectra, too (Figure 3). Interestingly, at higher exciting wavelengths, these four samples present similar spectral emission features.  
In Figure 13, the experimental emission spectra of these samples (AA1, FH1, AR1, and IN1) obtained by exciting at 340 nm are reported showing in all cases an emission band (or shoulder) at \(\sim\)375 nm. This feature is distinctive of these honey samples, as seen in Figures 2b and 13. Emission spectra of inula and arbutus honey, at \(\lambda_{\text{ex}}\) = 340 nm, are very similar and a good reproduction is obtained by considering vitamin B6, vitamin B9, and quercetin as the main fluorophores (Figure 13a,c). In the case of alfalfa honey, the emission spectrum has a large band with a smooth maximum centered at 400 nm and a shoulder at 375 nm (Figure 13b), which can be reproduced with the same fluorophores than inula and arbutus honeys, but with a different relative contribution. Alfafla honey is indeed obtained more in vitamin B6 and p-coumaric acid than others. Forest honeydew has the lowest fluorescence (Figure 13d), indicating a low content of bioactive compounds. Moreover, as shown in Figure 3, forest honeydew has a very low content of pigments and absence of chlorophyll derivatives. As a general feature, these samples seem to have very low content in phenolic acids and this aspect will be further investigated.
# Analysis of Inductive Displacement Sensors with Large Range and Nanoscale Resolution
## 4 Q Value and Excitation Frequency Analysis
### Analysis for Increasing \(Q\) Value and Excitation Frequency
For example, amorphous alloys and nanocrystalline alloys exhibit more than 1-fold lower conductivity than that of Fe-Ni alloys and can better suppress the eddy current loss at the same sheet thickness. Ferrite cores with ultra-low conductivity may be ideal, do not require lamination and have little eddy current loss. Without changing the core material, the \(Q\) value of inductive sensors can also be improved by optimizing the coil turns \(N\) and the core size. According to the FEM results shown in Figure 17a, increasing \(N\) can slightly increase the \(Q\) value. This is because the inductance increases with \(N\). However, changing \(N\) cannot increase the allowable maximum excitation frequency of the inductive sensor, which proves that the allowable maximum excitation frequency is only determined by the core. Figure 17b shows that reducing the cross-section size of the core can also help improve the \(Q\) value and increase the allowable excitation frequency slightly, because the core loss power is directly proportional to the volume. The methods of increasing \(Q\) value and excitation frequency \(f\) are briefly summarized, and the limitations to be considered in using these methods are indicated as follows:  
1. The magnetically permeable material with lower conductivity can be selected as core. However, the precondition of low coercivity and high permeability is required. Moreover, if the ferrite with low permeability is selected, the temperature stability and fragility of the core need to be considered;
2. Reduce the thickness of sheets of the laminated core. We need to consider whether the corresponding manufacturing process can be achieved, and whether too thin sheets will reduce the permeability of the core;
3. Reduce the cross-sectional dimension of the core. It should be considered that the sensitivity of the sensor will be reduced and the winding of the coil may be more difficult. Figure 16: The variation of \(Q\) wih excitation frequency of different core conductivity (\(\delta\) = 0.2 mm). Figure 17: The variation of \(Q\) wih \(f\) of the inductive sensor of different coil turns and core sizes analyzed by FEM: (**a**) \(Q\) vs. \(f\) of different coil turns \(N\) (\(\delta\) = 0.2 mm, **a** = 1.5 mm); (**b**) \(Q\) vs. \(f\) of different cross section side length (_a_) of the core (\(N\) = 1000, \(\delta\) = 0.2 mm). 4. Increase the number of coil turns. It is necessary to consider that the size of sensor probe will increase. In addition, the increase of coil turns is limited by the area of the core window; In addition, the increase of coil turns will also make it difficult to guarantee the precision of coil winding. It is noteworthy that increasing the coil turns can only increase the \(Q\) value, but the allowable excitation frequency can not be effectively improved.
## 3 UAV Power Supply and Charging Mechanisms
### Battery Powered UAVs
#### 3.1.3 Wireless Power Transfer/Wireless Charging  
Wireless power transfer (WPT) is another technique for countering and overcoming the limitations of conventional battery power supply mechanisms to UAVs. The concept of wireless charging was introduced by Nikola Tesla [49]. To perform the wireless charging of electronic devices, a transmission pad is used to charge the device using the resonant inductive coupling [49]. A typical WPT consists of two main components: namely, a transmitting device and a receiving device. A transmission device is used for the conversion of the source energy into \"time-varying electromagnetic fields\" which is then transmitted using a transfer media, which converts the time-varying electromagnetic arrays into electrical power that is, in turn, used to power the UAV.  
Currently, the WPT technique is in its early stages and there are still several issues and limitations that need to be addressed. For instance, due to the significant propagation loss of RF signals over long distances, the performance of WPT systems with a wide coverage range is essentially hampered by their low end-to-end power transmission efficiency. As a result, fixed-location energy transmitters (ETs) must be distributed in an ultra-dense way in order to provide pervasive wireless energy access for enormous low power energy receivers (ERs) deployed over a wide area.  
Using WPT, some UAVs can serve as recharging UAVs to ensure that batteries of other UAVs--that are serving user requests--are not depleted by flying to their respective locations to recharge their batteries while they are in operation. This will prevent service interruptions that might occur if each UAV has to fly to a charging station located at a distance from the UAV operating region to replenish its depleted battery. In such an arrangement, there is normally a transmitting UAV (tUAV) whose responsibility is to transmit RF signals to the serving UAVs (sUAVs), which have been equipped with sensors to convert the received RF signals to electrical energy needed to power the UAVs [50].
## 2 NDT Methods for Evaluation of Steel Fiber-Reinforcement Concrete (SFRC)
### Ultrasonic Method  
The ultrasonic method is one of the most widely used electrodynamic non-destructive diagnostic methods. When an ultrasonic wave passes through the environment, its energy decreases, and thus its acoustic pressure, depending on the properties of the environment. The cause of this attenuation is wave absorption, reflection, refraction, bending and scattering. Ultrasound absorption in solids arises as a result of internal friction, hysteresis losses, plastic creep and relaxation and thermal phenomena. The attenuation of longitudinal waves is greater than of transverse ones.  
In ultrasonic flaw detection, the oscillations are excited by a transducer called an ultrasonic pulse. The time of one oscillation corresponds to one wavelength \(\lambda\).  
Two basic ultrasonic methods are most often used in construction. The oldest and simplest is the pass-through method, the main feature of which is the measurement of the transmitted acoustic pressure or the determination of the time of passage of ultrasonic waves through the examined environment. The second is the impulse ultrasonic method. The principle of the pulse method consists in the transmission of pulses, which are captured and displayed using the so-called A-scan. The reflected pulses return either to the same electroacoustic transducer or to the receiving transducer. It is suitable for structural diagnostics, where access is allowed only from one side of the structure.  
At present, two technical standards CSN 73 1371 [15] and CSN EN 1250-4 [16] describing measurement methods using ultrasound are in force.  
The ultrasonic method has been used in construction for many decades. It is commonly used to determine the modulus of elasticity of concrete, estimation of compressive strength, uniformity of concrete, the presence of cracks or cavities, changes in properties over time. Ultrasonic devices measure the time of passage of the ultrasonic pulse through the tested material and from the knowledge of the length of the measuring base the speed of propagation of the ultrasonic pulse according to CSN 73 1371 [15] is evaluated. The Czech Technical Standard [16] discusses in some detail the factors that may affect the measurement of the pulse propagation rate. These are the moisture content of the concrete, the length of the measuring base and the presence of reinforcement in the concrete element.  
It has been shown that the steel fiber reinforced concrete can be expected to have a higher rate of propagation of the ultrasonic pulse compared to the unreinforced concrete of the same quality [17]. This method is suitable for evaluating the disturbance of the internal structure of steel fiber-reinforced concrete or its uniformity as well as for plain concrete. Thanks to the relatively easy handling of ultrasonic devices for testing building structures in situ, very suitable.
# A Communication-Efficient Secure Routing Protocol for IoT Networks +
## 4 Proposed Method
### Route Reply Phase-1  
In the proposed method, the RREP procedure of the route is divided into two situations: (i) when \(\mathsf{D}\) generates the RREP, and (ii) when the intermediate nodes on the route generate the RREP instead of \(\mathsf{D}\). First, we describe the former case.  
1. \(\mathsf{D}\) generates an RREP signed with its own signature and broadcasts it. If \(\mathsf{N}_{n}\) receives this packet, this phase can be denoted by \[\mathsf{D}\rightarrow\mathsf{N}_{n}:(\mathrm{RREP})_{\mathsf{SigD}}\] (4) This RREP now employs the destination's location information (\(\mathrm{LI}_{\mathsf{D}}\)) compared with the RREP of the original AODV (\(\mathrm{RREP}_{\mathrm{AODV}}\)), while information about the hop count is excluded. The contents of the RREP in this method are expressed as follows: \[\mathrm{RREP}=(\mathrm{RREP}_{\mathrm{AODV}},\,\mathrm{LT},\,\mathrm{LI}_{ \mathsf{D}})\] (5)2. \(\mathsf{N}_{n}\) verifies the signature from \(\mathsf{D}\) in the received packet and stores the routing information and sent RREP in its own table. Subsequently, \(\mathsf{N}_{n}\) adds its own signature and address (ID\({}_{\mathsf{N}_{n}}\)) to the RREP and forwards it. This is denoted by \[\mathsf{N}_{n}\rightarrow\mathsf{N}_{n-1}:((\mathrm{RREP})_{\mathrm{ Sig}_{\mathsf{D}}},\,\mathrm{ID}_{\mathsf{N}_{n}})_{\mathrm{ Sig}_{\mathsf{N}_{n}}}\] (6)
3. \(\mathsf{N}_{n-1}\) receives the RREP from \(\mathsf{N}_{n}\), verifies the signatures of \(\mathsf{D}\) and \(\mathsf{N}_{n}\), establishes a path in the direction of \(\mathsf{D}\), and stores the RREP from \(\mathsf{N}_{n}\). Subsequently, \(\mathsf{N}_{n-1}\) replaces the signatures and addresses of \(\mathsf{N}_{n}\) with its own signature.
4. This RREP storage and forwarding procedure is repeated until the RREP reaches \(\mathsf{S}\).  
As in the RREQ phase, this relaying is stopped when the distance between a node and \(\mathrm{LI}_{\mathsf{D}}\) exceeds a threshold.
## 4 Discussion
### Nature of the Reaction Product
We found OSCN\({}^{-}\) after LPO oxidation of SCN\({}^{-}\) and I\({}_{2}\) after LPO oxidation of I\({}^{-}\). OSCN\({}^{-}\) is not able to oxidize amine(NH\({}_{2}\))-group [8; 22], because of its relatively weak oxidative strength that makes OSCN\({}^{-}\) specific regarding its molecular target, i.e., a thiol moiety. This implies a lower antimicrobial activity, particularly against fungus, as shown in our study and the reviewed literature [22; 30; 31]. The iodine/hypoiodite ions have a stronger oxidative strength that allows them both to oxidize thiol and amine groups [32; 33; 34; 35]. However, its antimicrobial effect can be hampered by the catalytic reaction between iodine and H\({}_{2}\)O\({}_{2}\), and could explain the low level of oxidant produced and the absence of antifungal activity in our study [36]. In iodide and thiocyanate mixtures, there is a strong competition between SCN\({}^{-}\) and I\({}^{-}\) to fix LPO; I\({}^{-}\) hampers the interaction of SCN\({}^{-}\) with LPO, inducing a 10-fold increase of the dissociation constant (K\({}_{\rm D}\)) of SCN\({}^{-}\) from LPO [37]. In other words, the affinity of LPO for SCN\({}^{-}\) decreases, so that in our experimental conditions the quantity of generated oxidants decreased, too [37]. Based on various distinct techniques, our results show that OSCN\({}^{-}\), OCN\({}^{-}\), and I\({}_{2}\) were not present as stable oxidants, whereas SO\({}_{4}\)\({}^{2-}\) was a stable byproduct. SO\({}_{4}\)\({}^{2-}\) was measured in high concentrations, demonstrating that SCN\({}^{-}\) was oxidized. \({}^{13}\)C NMR showed that no interhalogen such as ICN, I(SCN)\({}_{2}\)\({}^{-}\), or I\({}_{2}\)SCN\({}^{-}\) was observable [25; 38]. Anionic chromatography did not detect OI\({}^{-}\). OI\({}^{-}\) stability is relative because aqueous I\({}_{2}\) has a very complex behavior; consequently, OI\({}^{-}\) stability strongly depends on matrix interactions and on the pH of the medium [8]. The chromatography technique separated each reaction product during the analytical process; this may have reduced OI\({}^{-}\) stability [8; 39; 40; 41]. On the other hand, the stability of the oxidant, when stored at 4 \({}^{\circ}\)C over a long period of time, its NH\({}_{2}\)-oxidizing capacity, and its capacity to inhibit fungi, argue in favor of an I\({}^{-}\)-derived active ion [8; 12; 35].
# Research on Disease Spreading Behavior Oriented to Three-Layer Complex Networks
## 3 Construction of Three-Layer Complex Networks
### Three-Layer EBE Network Modeling  
The construction algorithm of the three-layer EBE network model is as follows.  
Step 1: The initial conditions are as described above.  
Step 2: The single network layers \(\alpha\) and \(\gamma\) are both randomly connected in the intra-layer. This intermediary layer \(\beta\) uses a BA scale-free network construction algorithm that combines a growth and priority link mechanism with an initial network of \(m_{0}\) nodes. After that, one node at a time is added and connected to \(m\) old nodes, and \(m\leq m_{0}\), while the probability that a new node connects to an old node \(i^{\beta}\) satisfies the relationship \((k_{i}+1)/\sum\limits_{j}(k_{j}+1)\), here \(k_{i}\) it the degree of node \(i^{\beta}\), and the algorithm ends when the total number of nodes in the network increases to \(N_{\beta}\).  
Step 3: The inter-layer is connected using random link method, and there are no directly connected edges between the first and third layer of the network.  
The network model is constructed according to the above three-layer EBE network construction method. Figure 1c shows the three-layer EBE network model with the following parameters: \(N_{\alpha}=25\), \(N_{\beta}=20\), \(N_{\gamma}=17\), \(m_{0}=10\), \(m=3\), \(P_{\alpha}=0.2\), \(P_{\gamma}=0.2\), \(P_{\alpha\beta}=0.2\), and \(P_{\beta\gamma}=0.2\).
## 3 Toxic Effects of BPA on Human Health
Investigations carried out on animals have shown that BPA exposure can impair the health through hampering the hypothalamus pituitary pathway. Animal studies varying the timing, length, and dose of BPA exposure during pregnancy have also been carried out and the results demonstrated that a high exposure to BPA (100 mg/kg bW/day) during pregnancy severely affects preimplantation embryonic development leading to the complete prevention of implantation in mice [48] as well as decreasing the number of live offspring rats [58]. A number of scientific works based on human and animal studies have investigated the long-term impact of BPA exposure on brain organization. Early exposure has been linked to several adverse outcomes such as reduced brain development and function [39] and alteration of brain sexual differentiation [59] in rats. Animal studies have also shown that different levels of BPA exposure can be the cause of behavioural changes such as aggression (2 or 20 ng/g bW/day) [60], anxiety (2 and 200 mg/kg bW/day) [61], cognitive deficits (100 mg/kg bW/day) [62], learning memory impairment (30 ng/g or 2 mg/g diet) [63] and modified socio-sexual behaviour (40 mg/kg bW/day) [64]. Furthermore, BPA can also contribute to the pathogenesis of cancer and several metabolic disorders. For instance, in vitro studies have shown that BPA (2.28 \(\times\) 10\({}^{-9}\)-2.28 \(\times\) 10\({}^{-3}\) g/L) increased the proliferation of a human breast cancer line [65] and may also be a factor in the development of prostate cancer [66]. The latter research reported significantly higher concentrations of BPA (5.74 mg/g) in the urine of men with prostate cancer than the control group (1.43 mg/g). In addition, [PERSON] et al. reported a link between BPA exposure and the modulation of glucose utilization in muscles, interference with adipose tissue endocrine function, neuroendocrine regulation of glucose metabolism and promotion of glucose metabolism dysfunction such as glucose intolerance and insulin resistance [67]. BPA exposure have also been reported to be linked to other metabolic dysfunctions such as obesity and type 2 diabetes [68] as well as cardiovascular toxicity [69] and immune toxicity [70]. Although there are numerous studies about the negative impact of BPA exposure, in 2015 EFSA announced that there are variables that make it impossible to claim that BPA is toxic to human health in respect to toxicokinetic differences between animal and human models, different routes of exposure, and the non-reproducibility of the studies [5]. Therefore, more scientific studies are needed in this area to have concrete evidence of the impact of BPA on human health.